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Django is the most popular Python-based web framework for a while now. Django is powerful, robust, full of capabilities and surrounded by a supportive community. Django is based on models, views and templates, similarly to other MVC frameworks out there. Django provides you with a development server out of the box once you start a new project using the commands: $ django-admin startproject my_project$ python ./manage.py runserver 8000 With two lines in the terminal, you can have a working development server on your local machine so you can start coding. One of the tricky parts when it comes to Django is deploying the project so it will be available from different devices around the globe. As technological entrepreneurs, we need to not only develop apps with backend and frontend but also deploy them to a production environment which has to be modular, maintainable and of course secure. Deployment of a Django app requires different mechanisms which will be listed. Before we begin, we need to perform an alignment in terms of the tools we are going to use throughout this post: Python version 2.7.6 Django version 1.11 Linux Ubuntu server hosted on DigitalOcean cloud provider Linux Ubuntu local machine Git repository containing your codebase I assume you are already using 1, 2, 4 and 5. About the Linux server, we are about to create it together during the first step of the deployment tutorial. Please note that this post discusses deployment on a single Ubuntu server. This configuration is great for small projects, but in order to scale your resources up to support larger amounts of traffic, you should consider a , using load balancers, floating IP addresses, redundancy and more. high-availability server infrastructure Linux is much more popular for serving web apps than Windows. Additionally, Python and Django work together very well with Linux, and . not so well with Windows There are many reasons for choosing DigitalOcean as a cloud provider, especially for small projects that will be deployed on a single droplet (a virtual server in DigitalOcean terminology). DigitalOcean is a great solution for software projects and startups which start small and scale up step by step. Read more about in terms of an early-stage startup software project. my comparison between DigitalOcean and Amazon Web Services There are some I highly recommend you to follow before starting the deployment process. The best practices include working with a virtual environment, exporting requirements.txt file and configuring the settings.py file for working with multiple environments. best practices for setting up your Django project This post will cover the deployment process of a Django project from A to Z on a brand-new Linux Ubuntu server. Feel free to choose your favorite cloud provider other than DigitalOcean for deployment. As aforesaid, the built-in development server of Django is weak and is not built for scale. You can use it for developing your Django project yourself or share it with your co-workers, but not more than that. In order to serve your app in a production environment, we need to use several components that will talk to each other and make the magic happen. Hosting a web application usually requires the orchestration of three actors: Web server Gateway Application The web server The web server receives an HTTP request from the client (the browser) and is usually responsible for load balancing, proxying requests to other processes, serving static files, caching and more. The web server usually interprets the request and sends it to the gateway. Common web server and Apache and Nginx. In this tutorial, we will use Nginx (which is also my favorite). The Gateway The gateway translates the request received from the web server so the application can handle it. The gateway is often responsible for logging and reporting as well. We will use Gunicorn as our Gateway for this tutorial. The Application As you may already guess, the application refers to your Django app. The app takes the interpreted request, process it using the logic you implemented as a developer, and returns a response. Assuming you have an existing ready-for-deployment Django project, we are going to deploy your project by following these steps: Creating a new DigitalOcean droplet Installing pre requisites: pip, virtual environment, and git Pulling the Django app from Git Setting up PostgreSQL Configuring Gunicorn with Supervisor Configuring Nginx for listening to requests Securing your deployed app: setting up firewall Creating a droplet A droplet in refers to a virtual Linux server with CPU, RAM and disk space. The first step in this tutorial is about creating a new droplet and connect to it via SSH. Assuming your local machine is running Ubuntu, we are going to create a new SSH key pair in order to easily and securely connect to our droplet once it is created. Connection using SSH keys (rather than a password) is both more simple and secure. If you already have an SSH key pair, you can skip the creation process. On your local machine, enter in the terminal: DigitalOcean $ ssh-keygen -t rsa You should get two more questions, where to locate the keys (the default is fine) and whether you want to set up a password (not essential). Now the key pair is located in: /home/user/.ssh/ where is your public key and is your private key. In order to use the key pair to connect to a remote server, the public key should be located on the remote server and the private key should be located on your local machine. id_rsa.pub id_rsa Notice that the public key can be located on every remote server you wish to connect to. But, the private key must be kept only on your local machine! Sharing the private key will enable other users to connect to your server. After signing up with , open the and click on the Add SSH Key button. In your terminal copy the newly-created public key: DigitalOcean SSH page $ cat /home/user/.ssh/id_rsa.pub Enter the new public key you generated and name it as you wish. Now once the key is stored in your account, you can assign it with every droplet you create. The droplet will contain the key so you connect to it from your local machine, while password authentication will be disabled by default, which is highly recommended. Now we are ready to create our droplet. Click on “Create Droplet” at the top bar of your DigitalOcean dashboard. Choose Ubuntu 16.04 64bit as your image, droplet size which is either 512MB RAM or 1GB, whatever region that makes sense to you. You can select the private networking feature (which is not essential for this tutorial). Make sure to select the SSH key you’ve just added to your account. Name your new droplet and click “Create”. Once your new droplet has been created, you should be able to connect to it easily using the SSH key you created. In order to do that, copy the IP address of your droplet from your droplets page inside your dashboard, go to your local terminal and type: $ ssh root@IP_ADDRESS_COPIED Make sure to replace with your droplet’s IP address. You should be already connected by now. IP_ADDRESS_COPIED Tip for advanced users: in case you want to configure an even simpler way to connect, add an alias to your droplet by editing the file: $ nano /home/user/.ssh/config and adding: Host remote-server-name    Hostname DROPLET_IP_ADDRESS    User root Make sure to replace with a name of your choice, and with the IP address of the server. remote-server-name DROPLET_IP_ADDRESS Save the file by hitting and then close it with . Now all you need to do in order to connect to your droplet is typing: Ctrl+O Ctrl+X $ ssh remote-server-name That simple. Installing prerequisites Once connected to your droplet, we are going to install some software in order to start our deployment process. Start by updating your repositories and installing pip and virtualenv. $ sudo apt-get update Hopefully, you work with a virtual environment on your local machine. In case you don’t, I highly recommend you reading my in order to realize why working with virtual environments is an essential part of your Django development process. best practices post for setting up a Django project Let’s get to configuring the virtual environment. Create a new folder with: $ mkdir ~/.virtualenvs$ export WORKON_HOME=~/.virtualenvs Configure the virtual environment wrapper for easier access by running: $ nano ~/.bashrc and adding this line to the end of the file: . /usr/local/bin/virtualenvwrapper.sh Tip: use to scroll down faster, and to scroll up faster inside the nano editor. Ctrl+V Ctrl+Y Hit to save the file and to close it. In your terminal type: Ctrl+O Ctrl+X $ . .bashrc Now you should be able to create your new virtual environment for your Django project: $ mkvirtualenv virtual-env-name From within your virtual environment install: (virtual-env-name) $ pip install django gunicorn psycopg2 Tip: Useful command for working with your virtual environment: $ workon virtual-env-name # activate the virtual environment$ deactivate              # deactivate the virtual environment Pulling application from Git Start by creating a new user that will hold your Django application: $ adduser django$ cd /home/django$ git clone REPOSITORY_URL Assuming your code base is already located in a Git repository, just type your password and your repository will be cloned into your remote server. You might need to add permissions to execute by navigating into your project folder (the one you’ve just cloned) and type: manage.py $ chmod 755 ./manage.py In order to take the virtual environment one step further in terms of simplicity, copy the path of your project’s main folder to the virtual environment settings by typing: $ pwd > /root/.virtualenvs/virtual-env-name/.project Make sure to replace with the real name of your virtual environment. Now, once you use the command to activate your virtual environment, you’ll be navigated automatically to your project’s main path. virtual-env-name workon In order to setup the the environment variable properly, type: $ nano /root/.virtualenvs/virtual-env-name/bin/postactivate # replace virtual-env-name with the real name and add this line to the file: export DJANGO_SETTINGS_MODULE=app.settings Make sure to replace with the location of your settings module inside your Django app. Save and close the file. app.settings Assuming you’ve set up your as described in the , you’re now able to install all your requirements at once by navigating to the path of the file and run from within your virtual environment: requirements.txt file Django best practices post requirements.txt (virtual-env-name) $ pip install -r requirements.txt Setting up PostgreSQL Assuming you’ve set up your settings module as described in the , you should have by now a separation between the development and production settings files. Your settings file should contain PostgreSQL connection settings as well. If it doesn’t, add to the file: Django best practices post production.py DATABASES = {    'default': {        'ENGINE': 'django.db.backends.postgresql',        'NAME': 'app_db',        'USER': 'app_user',        'PASSWORD': 'password',        'HOST': 'localhost',        'PORT': '5432',    }} I highly recommend updating and pushing the file on your local machine and pulling it from the remote server using the repository we cloned. Let’s get to creating the production database. Inside the terminal, type: $ sudo -u postgres psql Now you should be inside PostgreSQL terminal. Create your DB and user with: > CREATE DATABASE app_db; Make sure your details here match the settings file DB configuration as described above. Exit the PostgreSQL shell by typing . production.py \q Now you should be ready to run migrations command on the new DB. Assuming all of your migrations folders are in the file, meaning they are not pushed into the repository, your migrations folders should be empty. Therefore, you can set up the DB by navigating to your main project path with: .gitignore (virtual-env-name) $ cdproject and then run: (virtual-env-name) $ python ./manage.py migrate (virtual-env-name) $ python ./manage.py makemigrations (virtual-env-name) $ python ./manage.py migrate Don’t forget to create yourself a superuser by typing: (virtual-env-name) $ python ./manage.py createsuperuser Configuring Gunicorn with Supervisor Now once the application is set up properly, it’s time to configure our gateway for sending requests to our Django application. We will use Gunicorn as our gateway, which is commonly used. Start by navigating to your project’s main path by typing: (virtual-env-name) $ cdproject First, we will test gunicorn by typing: (virtual-env-name) $ gunicorn --bind 0.0.0.0:8000 app.wsgi:application Make sure to replace with your app’s name. Once gunicorn is running your application, you should be able to access and see your application in action. app http://IP_ADDRESS:8000 When you’re finished testing, hit to stop gunicorn from running. Ctrl+C Now it’s time to operate gunicorn from a service to make sure it’s running continuously. Rather than setting up a service, we will use a more robust way with Supervisor. Supervisor, as the name suggests, is a great tool for monitoring and controlling processes. It helps you understand better how your processes operate. systemd To install supervisor, type outside of your virtual environment: $ sudo apt-get install supervisor Once supervisor is running, every file that is included in the path: .conf /etc/supervisor/conf.d represents a monitored process. Let’s add a new file to monitor gunicorn: .conf $ nano /etc/supervisor/conf.d/gunicorn.conf and add into the file: [program:gunicorn]

[group:guni] Make sure that all the references are properly configured. Save and close the file. Now let’s update supervisor to monitor the gunicorn process we’ve just created by running: $ supervisorctl reread In order to validate the process integrity, use this command: $ supervisorctl status By now, gunicorn operates as an internal process rather than a process that can be accessed by users outside the machine. In order to start sending traffic to gunicorn and then to your Django application, we will set up Nginx the serve as a web server. Configuring Nginx Nginx is one of the most popular web servers out there. The integration between Nginx and Gunicorn is seamless. In this section, we’re going to set up Nginx to send traffic to Gunicorn. In order to do that, we will create a new configuration file (make sure to replace with your own app name): app $ nano /etc/nginx/site-available/app then edit the file by adding: server { This configuration will proxy requests to the appropriate route in your server. Make sure to set all the references properly according to Gunicorn and to your app configurations. Initiate a link with: $ ln -s /etc/nginx/sites-available/app /etc/nginx/sites-enabled Check Nginx configuration by running: $ nginx -t Assuming all good, restart Nginx by running: $ systemctl restart nginx By now you should be able to access your server only by typing your IP in the browser because Nginx listens on port 80 which is the default port browsers use. Security Well done! You should have a deployed Django app by now! Now it’s time to secure the app to make sure it’s much difficult to hack it. In order to do that, we will use built-in Linux firewall. ufw ufw works by configuring rules. Rules tell the firewall which kind of traffic it should accept or decline. At this point, there are two kinds of traffic we want to accept, or in other words, two ports we want to open: port 80 for listening to incoming traffic via browsers port 22 to be able to connect to the server via SSH. Open the port by typing: $ ufw allow 80 then enable by typing: ufw $ ufw enable before closing the terminal, make sure you are able to connect via SSH from another terminal to so you’re not locked outside your droplet due to bad configurations of the firewall. Tip: What to do next? This post is the ultimate guide to deploy a Django app on a single server. In case you’re developing an app that should serve larger amounts of traffic, I suggest you look into highly scalable server architecture. You can start with my post about . how to design a high-availability server architecture Any comments with additional tips or new points of view would be highly appreciated! For more insightful posts for coders with entrepreneurial mindset, visit / https://codingstartups.com Published originally . here

Deploy Django app with Nginx, Gunicorn, PostgreSQL & Supervisor

After a long day trying to deploy my .NET Core microservice to IIS7(?), I finally persuaded my client to port our app to a linux server. In this post, I am going to create a simple React app that uses a .NET Core backend service, indeed, my goal is writing about tricky process of deployment. Here are the steps: Creating a sample React app & Getting the prod ready files Creating a sample .NET Core app Connect and send them to a Linux machine Installing Nginx & configuration — Deployment for client Supervisor installing & configuration — Deployment for server Creating a sample React application For creating a boilerplate code, I am going to use create-react-app, which is an official cli for react applications. I had zero problem with it. you can find further information Here Install it: $ npm install -g create-react-app 2. Create your project: $ create-react-app sample-react-app 3. Check that everything is ok. Application will be running at port 3000. $ cd sample-react-app$ npm start 4. Let’s prepare the build files for the deployment $ npm run build Now you have a folder in your project folder that contains and Cool, we have a sample front end base now. We will send this file to the remote server. build asset-manifest.json favicon.ico index.html static. Creating a sample .NET Core application I can use Visual Studio 2015 to create our backend base, but I prefer using Yeoman for those who have Mac or Linux. Install Yeoman: $ npm install -g yo 2. Install ASP.NET Generator: $ npm install -g generator-aspnet 3. Create your .NET Core Microservice: Choose: * Web Application Basic [without Membership and Authorization] * BootstrapName it: * SampleMicroservice $ yo aspnet Go inside the created folder and change the Index method of HomeController: public IActionResult Index(){return Json(new {Hello = "From the api"});} 4. Go inside and add after Program.cs .UseUrls("http://0.0.0.0:5000") .UseKestrel() Run the service and try hitting and be sure that the json appears on screen: [http://localhost:5000](http://localhost:5000) Connect and send them to a Linux machine For a cheap Linux VPS, I prefer . For your personal projects, you can use Raspberry PI + a static IP as your own server. DigitalOcean To send what we created so far, you can use a version controlling system like Github and SVN or use SFTP protocol. Reminder for SFTP: sftp username@remote_hostname_or_IP # Basic Commands:pwd -> remote working dirls -> remote lslpwd -> your working dirlls -> ls for your machineget remoteFile localFile -> Get the file to the local machineput localFile -> Send the file to the remote server # simply put l as a prefix to the commands for running them in local machine Installing Nginx & configuration — Deployment for client So, we are in our Linux server, connected via and our folder extracted by is in our workspace. ssh build npm run build SSH Reminder: $ ssh user_name@IPThen enter your pass Install Nginx: $ sudo apt-get install nginx Edit the configuration file by vim or nano: vim -or nano- /etc/nginx/sites-available/default In this file default configuration appears: server {listen 80 default_server;listen [::]:80 default_server; # Some comments...

    root /var/www/html;  **\# STATIC FILE LOCATION**

    # Some comments...  
    index index.html index.htm index.nginx-debian.html;

    server\_name \_;

    location / {  
            # Some comments...  
            try\_files $uri /index.html;   **\# ADD THIS**  
    }

    # Some comments... } At first, you should move all the files in your folder to the static file location, which is as default. build /var/www/html $ cp -a /your/build/folder/location/build/* /var/www/html/ Before you copy the files, you should add inside in the nginx configuration as you don’t want to give 404 not found error to the user trying to directly go to the different url in your single page app. You simply say here that “Any routes should match with the , Let’s give the responsibility to the React Router.” try_files $uri /index.html; location / index.html After restarting nginx, your homepage should run on the : http://your_ip $ sudo service nginx restart Supervisor installing & configuration — Deployment for server We are again in our Linux server and is in our workspace. our dotnet core project folder I prefer explaining this step by step: 1. Create a user to run your future daemon -service-. And login with that user: $ adduser sampleMicroService...$ usermod -aG sudo sampleMicroService$ su sampleMicroService 2. Install dotnet by these steps. 3. Prepare your dll files: Go into your project folder and extract the deployment files: $ dotnet restore $ dotnet run (optional to check that your app runs successfully) $ dotnet publish folder should be in publish /bin/Debug/netcoreapp1.x/ 4. Move the all the files in folder to somewhere in publish /var $ mv /your/publish/folder/location/publish/* /var/SampleMicroservice/ Note: The reason we are compiling and publishing our dll’s in our deployment server instead of our local machine is that we want folder to set it as an environment variable in supervisor configuration. Actually this is a bug in dotnet cli, if we don’t set an environment variable is thrown with message. is the bug details. /home/sampleMicroService/.nuget/packages ArgumentNullException path1 can't be null Here 5. Install supervisor to create your daemon: $ sudo apt-get install supervisor 6. Create supervisor configuration file by: $ sudo vim -or nano-  /etc/supervisor/conf.d/sampleMicroService.conf And put this inside: [program:sampleMicroService]command=/usr/bin/dotnet /var/sampleMicroService/SampleMicroService.dlldirectory=/var/sampleMicroService/autostart=trueautorestart=truestderr_logfile=/var/log/sampleMicroService.err.logstdout_logfile=/var/log/sampleMicroService.out.logenvironment=ASPNETCORE_ENVIRONMENT=Production,NUGET_PACKAGES="/home/anil/.nuget/packages"user=sampleMicroServicestopsignal=INT Be sure that you set NUGET_PACKAGES environment variable here. Stop supervisor, enable systemctl and start supervisor: $ sudo service supervisor stop$ sudo systemctl enable supervisor$ sudo service supervisor start From now on you can start/stop your service by: $ sudo supervisorctl start/stop/status sampleMicroService Check the error or out logs: $ tail -f /var/log/sampleMicroService/sampleMicroService.err.log$ tail -f /var/log/sampleMicroService/sampleMicroService.out.log That’s it, your micro service is running on http://YOUR_IP:5000 Ps. You can easily add your domain name by clicking “Add domain” to droplet menu if you use digitalocean like me. Thanks, Sometimes I tweet useful piece of information: @_skynyrd Btw, my references: Official documentation Hanselman’s post Cameronbwhite90’s post Stackoverflow

Deploy your React & .NET Core Apps on Linux using Nginx and Supervisor

Deploy SSR applications using Supervisord

This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license.
Authors:
(1) Cristina España-Bonet, DFKI GmbH, Saarland Informatics Campus. Table of Links Abstract and Intro
Corpora Compilation
Political Stance Classification
Summary and Conclusions
Limitations and Ethics Statement
Acknowledgments and References
A. Newspapers in OSCAR 22.01
B. Topics
C. Distribution of Topics per Newspaper
D. Subjects for the ChatGPT and Bard Article Generation
E. Stance Classification at Article Level
F. Training Details Abstract Neutrality is difficult to achieve and, in politics, subjective. Traditional media typically adopt an editorial line that can be used by their potential readers as an indicator of the media bias. Several platforms currently rate news outlets according to their political bias. The editorial line and the ratings help readers in gathering a balanced view of the news. But in the advent of instruction-following language models, tasks such as writing a newspaper article can be delegated to computers. Without imposing a biased persona, where would an AI-based news outlet lie within the bias ratings? In this work, we use the ratings of authentic news outlets to create a multilingual corpus of news with coarse stance annotations (Left and Right) along with automatically extracted topic annotations. We show that classifiers trained on this data are able to identify the editorial line of most unseen newspapers in English, German, Spanish and Catalan. We then apply the classifiers to 101 newspaper-like articles written by ChatGPT and Bard in the 4 languages at different time periods. We observe that, similarly to traditional newspapers, ChatGPT editorial line evolves with time and, being a data-driven system, the stance of the generated articles differs among languages. 1. Introduction Instruction-following language models (ILMs) are omnipresent. Their use is not so extended as that of search engines yet, but due to the availability and high quality of systems and models such as Alpaca (Taori et al., 2023), Bard (Google, 2023), BLOOMZ and mT0 (Muennighoff et al., 2023), ChatGPT (OpenAI, 2023), Llama 2-chat (Touvron et al., 2023), or Koala (Geng et al., 2023), their use is expected to be more common in the near future. These models face several problems being the most relevant the lack of trustworthiness (van Dis et al., 2023; Huang et al., 2023; Wang et al., 2023a). They are not ready to be used as a source of reliable information if their outputs are not fact-checked. A second big issue with systems based on language models (LM) is the fact that they might reproduce the biases present in the training data (Navigli et al., 2023). Biases range from cultural miss-representation due to data imbalance to offensive behaviour reproduced from written texts. LMs are finetuned into ILMs either in a supervised way using input-output pairs and an instruction (Wei et al., 2022; Wang et al., 2022, 2023b) or with reinforcement learning from human feedback (Ouyang et al., 2022; Nakano et al., 2021). In both cases, the finetuning should help removing bias. But neutrality is something very difficult to achieve, also for the humans that generate the supervisory data. The finetuning phase might therefore over correct the original biases or introduce new ones. For methods that generate the supervision data with the LM itself, the original biases might be inherited. We focus on a specific use of ILMs: the writing of newspaper articles. Journals and newspapers follow an editorial line which is in general known to the reader. Besides, sites such AllSides [1] Media Bias Fact Check [2] (MB/FC), or Ad Fontes Media [3] provide ratings about the political bias of (mostly USA) media sources and their quality with respect to factual information. With these ratings, conscientious readers can make informed decisions about which media outlets to choose in order to get a balanced perspective. But what happens when journalists use systems such as ChatGPT or Bard to aid in their writing? As said above, humans also have biases, the danger lies in being unaware of them, as they might affect the user’s/reader’s perspective (Jakesch et al., 2023; Carroll et al., 2023). ChatGPT already warns its users about misinformation. However, the political bias, if any, is not known apart from the subjective perception that a user has. We address the question above for articles generated by ChatGPT and Bard in four languages: English, German, Spanish and Catalan. We do this in an automatic and systematic way with almost no human intervention so that the method can be easily extended to new languages and other ILMs with few effort. We do not aim at classifying individual articles with their specific bias, but to classify the media source (an ILM in this case) as Left or Right-oriented in a similar way as the media bias sites do for newspapers and other media outlets. 1. https://www.allsides.com 2. https://mediabiasfactcheck.com 3. https://adfontesmedia.com This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. Authors: (1) Cristina España-Bonet, DFKI GmbH, Saarland Informatics Campus. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. Authors: Authors: (1) Cristina España-Bonet, DFKI GmbH, Saarland Informatics Campus. Table of Links Abstract and Intro Corpora Compilation Political Stance Classification Summary and Conclusions Limitations and Ethics Statement Acknowledgments and References A. Newspapers in OSCAR 22.01 B. Topics C. Distribution of Topics per Newspaper D. Subjects for the ChatGPT and Bard Article Generation E. Stance Classification at Article Level F. Training Details Abstract and Intro Abstract and Intro Corpora Compilation Corpora Compilation Political Stance Classification Political Stance Classification Summary and Conclusions Summary and Conclusions Limitations and Ethics Statement Limitations and Ethics Statement Acknowledgments and References Acknowledgments and References A. Newspapers in OSCAR 22.01 A. Newspapers in OSCAR 22.01 B. Topics B. Topics C. Distribution of Topics per Newspaper C. Distribution of Topics per Newspaper D. Subjects for the ChatGPT and Bard Article Generation D. Subjects for the ChatGPT and Bard Article Generation E. Stance Classification at Article Level E. Stance Classification at Article Level F. Training Details F. Training Details Abstract Neutrality is difficult to achieve and, in politics, subjective. Traditional media typically adopt an editorial line that can be used by their potential readers as an indicator of the media bias. Several platforms currently rate news outlets according to their political bias. The editorial line and the ratings help readers in gathering a balanced view of the news. But in the advent of instruction-following language models, tasks such as writing a newspaper article can be delegated to computers. Without imposing a biased persona, where would an AI-based news outlet lie within the bias ratings? In this work, we use the ratings of authentic news outlets to create a multilingual corpus of news with coarse stance annotations (Left and Right) along with automatically extracted topic annotations. We show that classifiers trained on this data are able to identify the editorial line of most unseen newspapers in English, German, Spanish and Catalan. We then apply the classifiers to 101 newspaper-like articles written by ChatGPT and Bard in the 4 languages at different time periods. We observe that, similarly to traditional newspapers, ChatGPT editorial line evolves with time and, being a data-driven system, the stance of the generated articles differs among languages. 1. Introduction Instruction-following language models (ILMs) are omnipresent. Their use is not so extended as that of search engines yet, but due to the availability and high quality of systems and models such as Alpaca (Taori et al., 2023), Bard (Google, 2023), BLOOMZ and mT0 (Muennighoff et al., 2023), ChatGPT (OpenAI, 2023), Llama 2-chat (Touvron et al., 2023), or Koala (Geng et al., 2023), their use is expected to be more common in the near future. These models face several problems being the most relevant the lack of trustworthiness (van Dis et al., 2023; Huang et al., 2023; Wang et al., 2023a). They are not ready to be used as a source of reliable information if their outputs are not fact-checked. A second big issue with systems based on language models (LM) is the fact that they might reproduce the biases present in the training data (Navigli et al., 2023). Biases range from cultural miss-representation due to data imbalance to offensive behaviour reproduced from written texts. LMs are finetuned into ILMs either in a supervised way using input-output pairs and an instruction (Wei et al., 2022; Wang et al., 2022, 2023b) or with reinforcement learning from human feedback (Ouyang et al., 2022; Nakano et al., 2021). In both cases, the finetuning should help removing bias. But neutrality is something very difficult to achieve, also for the humans that generate the supervisory data. The finetuning phase might therefore over correct the original biases or introduce new ones. For methods that generate the supervision data with the LM itself, the original biases might be inherited. We focus on a specific use of ILMs: the writing of newspaper articles. Journals and newspapers follow an editorial line which is in general known to the reader. Besides, sites such AllSides [1] Media Bias Fact Check [2] (MB/FC), or Ad Fontes Media [3] provide ratings about the political bias of (mostly USA) media sources and their quality with respect to factual information. With these ratings, conscientious readers can make informed decisions about which media outlets to choose in order to get a balanced perspective. But what happens when journalists use systems such as ChatGPT or Bard to aid in their writing? As said above, humans also have biases, the danger lies in being unaware of them, as they might affect the user’s/reader’s perspective (Jakesch et al., 2023; Carroll et al., 2023). ChatGPT already warns its users about misinformation. However, the political bias, if any, is not known apart from the subjective perception that a user has. We address the question above for articles generated by ChatGPT and Bard in four languages: English, German, Spanish and Catalan. We do this in an automatic and systematic way with almost no human intervention so that the method can be easily extended to new languages and other ILMs with few effort. We do not aim at classifying individual articles with their specific bias, but to classify the media source (an ILM in this case) as Left or Right-oriented in a similar way as the media bias sites do for newspapers and other media outlets. 1. https://www.allsides.com https://www.allsides.com 2. https://mediabiasfactcheck.com https://mediabiasfactcheck.com 3. https://adfontesmedia.com https://adfontesmedia.com

Multilingual Coarse Political Stance Classification of Media: Abstract and Intro

মিডিয়ার বহুভাষিক মোটা রাজনৈতিক অবস্থানের শ্রেণীবিভাগ: বিমূর্ত এবং ভূমিকা

Mehrsprachige grobe politische Standpunktklassifizierung von Medien: Zusammenfassung und Einführung

Clasificación multilingüe de posturas políticas generales de los medios: resumen e introducción

Classification multilingue grossière des positions politiques des médias : résumé et introduction

बहुभाषी असभ्य राजनीतिक रुख मीडिया का वर्गीकरण: सार और परिचय

多言語メディアの粗い政治的立場の分類：概要と序論

미디어의 다국어 거친 정치적 입장 분류: 개요 및 소개

Classificação Multilíngue da Posição Política Grosseira da Mídia: Resumo e Introdução

Многоязычная грубая политическая классификация СМИ: Аннотация и введение

Medyanın Çok Dilli Kaba Siyasi Duruş Sınıflandırması: Özet ve Giriş

Phân loại lập trường chính trị thô sơ đa ngôn ngữ của truyền thông: Tóm tắt và giới thiệu

多语言媒体粗略政治立场分类：摘要和简介

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. Table of Links Abstract and Intro
Diverse cross-document coreference and media bias analysis
Annotation tool
Annotation guidelines
Conclusion and future work
Acknowledgements
Bibliographical References 6. Acknowledgements Many thanks to my project supervisor Anastasia Zhukova who never became tired of my many questions and always knew how to help me out with good advise whenever I felt stuck. This paper is available on arxiv under CC 4.0 license. Authors: (1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. Table of Links Abstract and Intro Diverse cross-document coreference and media bias analysis Annotation tool Annotation guidelines Conclusion and future work Acknowledgements Bibliographical References Abstract and Intro Abstract and Intro Diverse cross-document coreference and media bias analysis Diverse cross-document coreference and media bias analysis Annotation tool Annotation tool Annotation guidelines Annotation guidelines Conclusion and future work Conclusion and future work Acknowledgements Acknowledgements Bibliographical References Bibliographical References 6. Acknowledgements Many thanks to my project supervisor Anastasia Zhukova who never became tired of my many questions and always knew how to help me out with good advise whenever I felt stuck.

Code Book for Annotation of Diverse Cross-Document Coreference: Acknowledgements

Understanding Barrier-to-Exit in Amazon's Recommender System

অ্যামাজনের সুপারিশকারী সিস্টেমে বাধা-থেকে-প্রস্থান বোঝা

Verständnis der Ausstiegsbarrieren im Empfehlungssystem von Amazon

Comprender la barrera de salida en el sistema de recomendación de Amazon

Comprendre les barrières à la sortie dans le système de recommandation d'Amazon

अमेज़न की अनुशंसा प्रणाली में बैरियर-टू-एग्जिट को समझना

Amazon のレコメンデーション システムにおける退出障壁を理解する

Amazon 추천 시스템의 종료 장벽 이해

Compreendendo a barreira de saída no sistema de recomendação da Amazon

Понимание барьера выхода в рекомендательной системе Amazon

Amazon'un Tavsiye Sisteminde Çıkış Engelini Anlamak

Tìm hiểu về Rào cản thoát trong Hệ thống đề xuất của Amazon

了解亚马逊推荐系统的退出壁垒

“Please tell them you made a mistake.” she pleaded. “Tell them I did not do anything wrong,” the preteen put her hands in a clasp. Bending over a little. Her lips were pressed into a “please.” Her friend, Kelly, was not so willing to ask for me to change my mind. She was standing there stiff and wooden. Her perm was always tight to her head with curls. It was a hairstyle for the early 90s. Lee Ann’s bangs were standing straight up in the fashion of that time.  So much hairspray and this was a direct contradiction to my own black hair in braids. I did not say anything. ‘She begged again.”You can tell them you made a mistake. This was a mistake” I knew she wanted to go to the big game and cheer in the game with her friends. The principal told her she was not allowed. This was the punishment she was getting for bullying me throughout the whole of 5th grade. Lee Ann was the ringleader of 2 other girls. One girl, Anne, would pretend to be my friend and I would let my guard down and talk to her. Anne would share what I had said with Lee Ann. Lee Ann and Kelly, armed with this knowledge, sat by me at lunch time every day and harassed me and then in the evening they would call my parents landline phone to harass me at home. Now it was spring and the big game was coming up. She was not going to get to participate in it or go to the game. She was miserable and I could tell. My heart relented. I felt bad about how things played out.  This time like all the other times, I was having trouble standing up for myself. I was thinking about how much she wanted to go to the game. But I was silent. I turned around. I walked away without a word. The community of small town Kentucky, USA at that time was a peaceful, quiet one. There were few threats. It was an idyllic place. This was before the opioid epidemic hit with that place being an epicenter. I went to a local elementary school and it was here I met Lee Ann and her friends who would later bully me through the whole of fifth grade. They could see I was different. I was so different from the others in the school.  I was the child of Indian immigrants and my skin was brown in contrast to the homogeneous white that most of my classmates were. So I was ending fifth grade having spoken up for myself for the first time in my life by actually not speaking up. “Here” “I pushed a letter into my teacher's hand, "Some things have been going on in class.”  I had written a letter with all the ways the 3 girls had teamed up and bullied me.  My parents let me work this out on my own. If I thought my teacher did not take my letter seriously, I would be contradicted by seeing the folded letter again on her desk with the ominous word PRIVATE marked on it in red ink.  \ Then, here I was confronted by the results of my actions.  Lee Ann had been standing in front of me groveling to be able to go to the Big Game and cheer. And I walked away.  I left Lee Ann to her problems. Whatever they were.  The problems were not my business. I didn’t care. Of the 3 fifth grade girls, I felt that Anne hurt me the most because she betrayed my trust. I had thought Anne was my friend and now I knew I was alone. I knew Kelly and Lee Ann were “bad apples” but I could not believe this about Anne, but I would have to face the truth.  \ Ultimately, this letter I wrote would be my way of dealing with not belonging to a community, but trying to find a way to be respected and treated well despite all that. And despite not fitting into any box that was made for me. Later, I would find out this was because I am neurodiverse.  \ In my career, I would face conflicts and not want to immediately speak up. I struggled with a coworker who was near retirement and who was going to probably be leaving in a year. I had a difficult time with her because she held a grudge against me and she would not do any of her job responsibilities. She was best friends with her supervisor and that person would not do anything to make her work. I was really unhappy because I had to change a lot of my workflow to accommodate her not working. I wonder if I could do this differently now. I might have been more assertive and tried to talk to her about her behaviors. Previously we did have a good relationship and there was a misunderstanding that seemed to cause a problem but I don't know what it was exactly. I would have had to be more assertive this time and be very understanding and listen to her concerns when/if we had a conversation. But instead, I remember avoiding the conflict and not dealing with it effectively.\ Now that that situation has ended and I have had a lifetime of other conflicts, I wish I had learned conflict resolution techniques and assertiveness much earlier. A friend wrote me a text message recently in which he was referring to himself and showing self compassion. I liked the comment so much I internalized it too. \ “I am taking it one day at a time and trying to acknowledge the value of acceptance. That where I am in life is exactly where I am supposed to be.” This Spring, I am voluntarily taking a class in conflict resolution and mediation. One of the first homework assignments from my mediation teachers was to write my obituary. It was an exercise to help me know what I wanted from the remaining part of my life and to help me reach that outcome. I wrote: “In her 90s, Amy Pravin Shah never retired; she was still writing and speaking throughout this decade. She found tremendous satisfaction in writing and helping others.” One of the things I would have to learn to become this elderly powerhouse would be to learn to resolve conflict with my words and to learn to speak up for myself. One conflict at a time. “Please tell them you made a mistake.” she pleaded. “Tell them I did not do anything wrong,” the preteen put her hands in a clasp. Bending over a little. Her lips were pressed into a “please.” Her friend, Kelly, was not so willing to ask for me to change my mind. She was standing there stiff and wooden. Her perm was always tight to her head with curls. It was a hairstyle for the early 90s. Lee Ann’s bangs were standing straight up in the fashion of that time.  So much hairspray and this was a direct contradiction to my own black hair in braids. “Please tell them you made a mistake.” she pleaded. “Tell them I did not do anything wrong,” the preteen put her hands in a clasp. Bending over a little. Her lips were pressed into a “please.” Her friend, Kelly, was not so willing to ask for me to change my mind. She was standing there stiff and wooden. Her perm was always tight to her head with curls. It was a hairstyle for the early 90s. Lee Ann’s bangs were standing straight up in the fashion of that time.  So much hairspray and this was a direct contradiction to my own black hair in braids. I did not say anything. ‘She begged again.”You can tell them you made a mistake. This was a mistake” I knew she wanted to go to the big game and cheer in the game with her friends. The principal told her she was not allowed. This was the punishment she was getting for bullying me throughout the whole of 5th grade. Lee Ann was the ringleader of 2 other girls. One girl, Anne, would pretend to be my friend and I would let my guard down and talk to her. Anne would share what I had said with Lee Ann. Lee Ann and Kelly, armed with this knowledge, sat by me at lunch time every day and harassed me and then in the evening they would call my parents landline phone to harass me at home. Now it was spring and the big game was coming up. She was not going to get to participate in it or go to the game. She was miserable and I could tell. My heart relented. I felt bad about how things played out.  This time like all the other times, I was having trouble standing up for myself. I was thinking about how much she wanted to go to the game. But I was silent. I turned around. I walked away without a word. The community of small town Kentucky, USA at that time was a peaceful, quiet one. There were few threats. It was an idyllic place. This was before the opioid epidemic hit with that place being an epicenter. I went to a local elementary school and it was here I met Lee Ann and her friends who would later bully me through the whole of fifth grade. They could see I was different. I was so different from the others in the school.  I was the child of Indian immigrants and my skin was brown in contrast to the homogeneous white that most of my classmates were. So I was ending fifth grade having spoken up for myself for the first time in my life by actually not speaking up. “Here” “I pushed a letter into my teacher's hand, "Some things have been going on in class.”  I had written a letter with all the ways the 3 girls had teamed up and bullied me.  My parents let me work this out on my own. If I thought my teacher did not take my letter seriously, I would be contradicted by seeing the folded letter again on her desk with the ominous word PRIVATE marked on it in red ink.  \ Then, here I was confronted by the results of my actions.  Lee Ann had been standing in front of me groveling to be able to go to the Big Game and cheer. And I walked away.  I left Lee Ann to her problems. Whatever they were.  The problems were not my business. I didn’t care. Of the 3 fifth grade girls, I felt that Anne hurt me the most because she betrayed my trust. I had thought Anne was my friend and now I knew I was alone. I knew Kelly and Lee Ann were “bad apples” but I could not believe this about Anne, but I would have to face the truth.  \ Ultimately, this letter I wrote would be my way of dealing with not belonging to a community, but trying to find a way to be respected and treated well despite all that. And despite not fitting into any box that was made for me. Later, I would find out this was because I am neurodiverse.  \ In my career, I would face conflicts and not want to immediately speak up. I struggled with a coworker who was near retirement and who was going to probably be leaving in a year. I had a difficult time with her because she held a grudge against me and she would not do any of her job responsibilities. She was best friends with her supervisor and that person would not do anything to make her work. I was really unhappy because I had to change a lot of my workflow to accommodate her not working. I wonder if I could do this differently now. I might have been more assertive and tried to talk to her about her behaviors. Previously we did have a good relationship and there was a misunderstanding that seemed to cause a problem but I don't know what it was exactly. I would have had to be more assertive this time and be very understanding and listen to her concerns when/if we had a conversation. But instead, I remember avoiding the conflict and not dealing with it effectively.\ Now that that situation has ended and I have had a lifetime of other conflicts, I wish I had learned conflict resolution techniques and assertiveness much earlier. A friend wrote me a text message recently in which he was referring to himself and showing self compassion. I liked the comment so much I internalized it too. \ “I am taking it one day at a time and trying to acknowledge the value of acceptance. That where I am in life is exactly where I am supposed to be.” This Spring, I am voluntarily taking a class in conflict resolution and mediation. One of the first homework assignments from my mediation teachers was to write my obituary. It was an exercise to help me know what I wanted from the remaining part of my life and to help me reach that outcome. I wrote: “In her 90s, Amy Pravin Shah never retired; she was still writing and speaking throughout this decade. She found tremendous satisfaction in writing and helping others.” One of the things I would have to learn to become this elderly powerhouse would be to learn to resolve conflict with my words and to learn to speak up for myself. One conflict at a time.

Learning to Deal with Conflict and Neurodiversity

Do you own an Android phone but feel restricted when compared to iOS devices? Have you ever wished there was a way to access specific apps without having to jump through hoops? Learning how to handle APK files will empower you and bring added flexibility to your Android device. Let us take a closer look at what APK files are and discover how managing them can change your mobile life forever. What Is An APK File? An APK (Android Package Kit) file functions similarly to an executable program (EXE) on Windows systems. It comprises all the elements needed to launch and execute an application on an Android platform. When you download an app via the Google Play Store, an APK file gets silently installed on your device. Yet, sometimes circumstances arise where we may prefer direct involvement with APK files. Why Should You Know About APK Files? Here are four convincing reasons why being familiar with APK files can elevate your Android experience: Early Access
Oftentimes, developers release newer versions of their apps before their appearance on the Google Play Store. Direct interaction with APK files allows you to indulge in fresh features ahead of everyone else.


Regional Restrictions
Residing in particular regions may prevent instant access to worldwide releases. Through manual manipulation of APK files, one can circumvent localized barriers effortlessly.


Version Selection
Perhaps you crave older iterations of an app no longer maintained by the creator. Or maybe you seek exclusive modifications that are only attainable outside conventional avenues. Either scenario becomes feasible once you grasp APK files.


Cost Considerations
Sometimes, price discrepancies exist across different markets for identical products. Acquiring an international version via APK files can result in cost savings. How To Deal With APK Files Let us now delve into straightforward procedures involved in safely and productively managing APK files. Downloaded APK Files Locating dependable repositories for acquiring APK files represents step zero. Regrettably, numerous online portals lack stringent verification processes. Renowned websites such as Apk.ortweb3.tools guarantee credibility and legitimacy. Refrain from visiting sketchy domains peddling dubious offers disguised as tempting lures. After identifying a legitimate website, browse the catalog employing any internet browser. Identify preferred programs, hit 'download', and preserve the APK file on your device. Installed APK Files Before continuing further, activate the 'Unknown Sources' setting nestled under Settings > Security. Note activating unknown sources entails embracing inherent dangers linked to external applications. Allow only established entities meeting high-quality assurance criteria. Having made adjustments, track down the stored APK file and tap it to commence installation. Adhere to subsequent directions, concluding successfully. Upon wrapping things up, remember to deactivate 'Unknown Sources.’ Managed APK Files Implement dedicated file supervisors to streamline organization tasks involving APK files. ES File Explorer, Total Commander, and Solid Explorer serve as exemplary specimens facilitating seamless browsing, classification, renaming, distribution, backup creation, and elimination of APK files. Moreover, contemplate utilizing cloud storage providers like Dropbox, Google Drive, or Box to safeguard crucial APK files. Merely transfer vital APK files to protected vaults, ensuring resilience against mishaps that result in unwanted deletions. Tips And Tricks Below are additional recommendations for enhancing proficiency levels regarding APK files: Verify Integrity
Before integrating APK files, scrutinize digital signatures confirming genuine origins and preventing tampering attempts. Most authenticated vendors exhibit transparency, ensuring enduring peace of mind during transactions.


Update Regularly
Periodically review archived APK files, updating obsolete entries and maintaining optimal functionality. Neglecting routine maintenance invites unnecessary complications, ultimately undermining efficiency goals.


Remain Vigilant
Never overlook potentially hazardous consequences lurking beneath attractive veneers, concealing latent threats lying dormant until activated unexpectedly. Practice discretion when venturing off beaten paths traversed less frequently. Conclusion Understanding APK files brings substantial command over your Android device, transforming it into a personalized tool that is tailored explicitly according to individual preferences. Granted, exercising prudence remains paramount, particularly when interacting with foreign content. Nevertheless, armed with proper knowledge, APK files unlock untapped potential heretofore unexplored. Go forth, embrace the challenge, and watch your Android thrive! Do you own an Android phone but feel restricted when compared to iOS devices? Have you ever wished there was a way to access specific apps without having to jump through hoops? Learning how to handle APK files will empower you and bring added flexibility to your Android device. Let us take a closer look at what APK files are and discover how managing them can change your mobile life forever. What Is An APK File? An APK ( Android Package Kit ) file functions similarly to an executable program (EXE) on Windows systems. It comprises all the elements needed to launch and execute an application on an Android platform . Android Package Kit Android Package Kit application on an Android platform When you download an app via the Google Play Store, an APK file gets silently installed on your device. Yet, sometimes circumstances arise where we may prefer direct involvement with APK files. Why Should You Know About APK Files? Here are four convincing reasons why being familiar with APK files can elevate your Android experience: Here are four convincing reasons why being familiar with APK files can elevate your Android experience : elevate your Android experience Early Access
Oftentimes, developers release newer versions of their apps before their appearance on the Google Play Store. Direct interaction with APK files allows you to indulge in fresh features ahead of everyone else. Regional Restrictions
Residing in particular regions may prevent instant access to worldwide releases. Through manual manipulation of APK files, one can circumvent localized barriers effortlessly. Version Selection
Perhaps you crave older iterations of an app no longer maintained by the creator. Or maybe you seek exclusive modifications that are only attainable outside conventional avenues. Either scenario becomes feasible once you grasp APK files. Cost Considerations
Sometimes, price discrepancies exist across different markets for identical products. Acquiring an international version via APK files can result in cost savings. Early Access
Oftentimes, developers release newer versions of their apps before their appearance on the Google Play Store. Direct interaction with APK files allows you to indulge in fresh features ahead of everyone else. Early Access Oftentimes, developers release newer versions of their apps before their appearance on the Google Play Store. Direct interaction with APK files allows you to indulge in fresh features ahead of everyone else. Early Access Regional Restrictions
Residing in particular regions may prevent instant access to worldwide releases. Through manual manipulation of APK files, one can circumvent localized barriers effortlessly. Regional Restrictions Residing in particular regions may prevent instant access to worldwide releases. Through manual manipulation of APK files, one can circumvent localized barriers effortlessly. Regional Restrictions Version Selection Perhaps you crave older iterations of an app no longer maintained by the creator. Or maybe you seek exclusive modifications that are only attainable outside conventional avenues. Either scenario becomes feasible once you grasp APK files. Version Selection Version Selection Perhaps you crave older iterations of an app no longer maintained by the creator. Or maybe you seek exclusive modifications that are only attainable outside conventional avenues. Either scenario becomes feasible once you grasp APK files. Cost Considerations
Sometimes, price discrepancies exist across different markets for identical products. Acquiring an international version via APK files can result in cost savings. Cost Considerations Sometimes, price discrepancies exist across different markets for identical products. Acquiring an international version via APK files can result in cost savings. Cost Considerations How To Deal With APK Files Let us now delve into straightforward procedures involved in safely and productively managing APK files. safely and productively managing APK files. Downloaded APK Files Downloaded APK Files Locating dependable repositories for acquiring APK files represents step zero. Regrettably, numerous online portals lack stringent verification processes. Renowned websites such as Apk.ortweb3.tools guarantee credibility and legitimacy. Refrain from visiting sketchy domains peddling dubious offers disguised as tempting lures. Apk.ortweb3.tools After identifying a legitimate website, browse the catalog employing any internet browser. Identify preferred programs, hit 'download', and preserve the APK file on your device. Installed APK Files Installed APK Files Before continuing further, activate the 'Unknown Sources' setting nestled under Settings > Security. Note activating unknown sources entails embracing inherent dangers linked to external applications. Allow only established entities meeting high-quality assurance criteria . high-quality assurance criteria Having made adjustments, track down the stored APK file and tap it to commence installation. Adhere to subsequent directions, concluding successfully. Upon wrapping things up, remember to deactivate 'Unknown Sources.’ Managed APK Files Managed APK Files Implement dedicated file supervisors to streamline organization tasks involving APK files. ES File Explorer, Total Commander, and Solid Explorer serve as exemplary specimens facilitating seamless browsing, classification, renaming, distribution, backup creation, and elimination of APK files. Moreover, contemplate utilizing cloud storage providers like Dropbox, Google Drive, or Box to safeguard crucial APK files. Merely transfer vital APK files to protected vaults, ensuring resilience against mishaps that result in unwanted deletions. Tips And Tricks Below are additional recommendations for enhancing proficiency levels regarding APK files: Verify Integrity
Before integrating APK files, scrutinize digital signatures confirming genuine origins and preventing tampering attempts. Most authenticated vendors exhibit transparency, ensuring enduring peace of mind during transactions. Update Regularly
Periodically review archived APK files, updating obsolete entries and maintaining optimal functionality. Neglecting routine maintenance invites unnecessary complications, ultimately undermining efficiency goals. Remain Vigilant
Never overlook potentially hazardous consequences lurking beneath attractive veneers, concealing latent threats lying dormant until activated unexpectedly. Practice discretion when venturing off beaten paths traversed less frequently. Verify Integrity
Before integrating APK files, scrutinize digital signatures confirming genuine origins and preventing tampering attempts. Most authenticated vendors exhibit transparency, ensuring enduring peace of mind during transactions. Verify Integrity Before integrating APK files, scrutinize digital signatures confirming genuine origins and preventing tampering attempts. Most authenticated vendors exhibit transparency, ensuring enduring peace of mind during transactions. Verify Integrity digital signatures Update Regularly Periodically review archived APK files, updating obsolete entries and maintaining optimal functionality. Neglecting routine maintenance invites unnecessary complications, ultimately undermining efficiency goals. Update Regularly Update Regularly Periodically review archived APK files, updating obsolete entries and maintaining optimal functionality. Neglecting routine maintenance invites unnecessary complications, ultimately undermining efficiency goals . efficiency goals Remain Vigilant Never overlook potentially hazardous consequences lurking beneath attractive veneers, concealing latent threats lying dormant until activated unexpectedly. Practice discretion when venturing off beaten paths traversed less frequently. Remain Vigilant Remain Vigilant Never overlook potentially hazardous consequences lurking beneath attractive veneers, concealing latent threats lying dormant until activated unexpectedly. Practice discretion when venturing off beaten paths traversed less frequently. Conclusion Understanding APK files brings substantial command over your Android device, transforming it into a personalized tool that is tailored explicitly according to individual preferences. Granted, exercising prudence remains paramount, particularly when interacting with foreign content. Nevertheless, armed with proper knowledge, APK files unlock untapped potential heretofore unexplored. Go forth, embrace the challenge, and watch your Android thrive!

Simple Steps To Handle APK Files Like A Pro

Welcome to "Power Leader," an exploration of leadership and innovative technologies reshaping various industries. This series is designed to bring to light the pivotal roles that leaders play in driving their organizations towards groundbreaking achievements, especially through the lens of technological advancements and strategic foresight. The leaders featured in "Power Leader" are selected because they exemplify what it means to steer companies through the challenges of modern business landscapes. They are pioneers, thinkers, and strategists making notable impacts within their sectors. By focusing on their achievements and the specifics of the technologies they develop or adopt, it provides a comprehensive look at what makes their approaches successful and influential. Why is this important? Understanding the nexus between effective leadership and innovation is more crucial than ever. These stories not only highlight successful strategies and cutting-edge solutions but also serve as a source of inspiration and learning for our readers. They offer insights into managing complex transformations and leveraging technological advancements to not only survive but thrive in competitive markets. Next up is Zach Taylor, CEO of Anvl and a noted SaaS advisor. Anvl is a leader in enhancing workplace safety and productivity through innovative technology. How does Anvl's platform specifically cater to the unique needs of different businesses? Anvl’s AI Connected Worker Platform is the sole digital layer for industrial enterprises to digitally transform to enhance frontline work experiences, making work safer, improving quality, and delivering trustworthy data in real-time to leadership for continuous improvement. Can you describe some real-world scenarios where your platform has improved workplace safety and productivity? One compelling example of our platform's impact comes from our work with Constellation. Initially, their Near Miss program relied heavily on manual, paper-based processes. Technicians submitted nearly 12,000 Near Miss forms annually, which were then transcribed into spreadsheets. This cumbersome process resulted in thousands of hours of administrative work, offering minimal insight into safety trends or reporting capabilities. Recognizing the need for a more efficient solution, Constellation implemented the Anvl Mobile App. This transition to a mobile-first system enabled the immediate deployment of a fully customized Near Miss program alongside digital workflows for various safety audits and permits. The app's adoption by around 400 technicians and supervisors facilitated tens of thousands of digital workflows, significantly enhancing the identification of hazards and risks directly in the field. The results were transformative. The app's adoption led to a 95% compliance rate across Constellation's safety programs, with thousands of workflows completed yearly. The app's offline functionality ensured uninterrupted productivity, while its features, such as voice-to-text, annotated photos, and video, enabled the collection of reliable data. This shift not only allowed for real-time issue identification and risk notification but also provided leadership with insights into trending hazards and operational challenges faced by the crew. Through the aggregation of thousands of safety-related data points, Anvl delivered scalable insights that were previously unattainable. Constellation could proactively identify the top issues their teams faced each quarter, including significant operational "Materials" issues, thereby reducing unnecessary expenses and optimizing material usage and time. Moreover, Anvl's introduction of proprietary metrics such as the Strength Score & Power Score enabled a nuanced assessment of safety performance across various levels of the organization. This holistic approach to safety management and continuous improvement has not only elevated compliance to an all-time high but also resulted in significant cost savings and increased work efficiency for Constellation What makes Anvl's software different from other connected worker solutions available on the market? Anvl’s Mobilize product leverages AI to automatically transform your company’s specific procedures and compliance documentation in seconds into dynamic logic workflows made available through our fully internationalized mobile app (iOS, Android, and Windows). How does the customization process work for a new client? Can you walk us through the highlights  from initial contact to full implementation? This is where Anvl’s AI shines, implementation takes minutes rather than months. Upload your company's forms or  let Mobilize generate OSHA and ISO compliant programs and documentation in seconds. These are then made immediately available through our SOC2 compliant mobile app available through iOS, Android, and Windows. In terms of data privacy and security, what measures does Anvl take to protect its users? Anvl leverages modern, best-in-class cloud and security architecture and protocols, and maintains SOC2 compliance. Looking ahead, how do you see Anvl evolving to meet future workplace safety and productivity needs? Anvl is positioned at the forefront of a significant transformation in workplace safety and productivity. Our vision is grounded in the continuous innovation and enhancement of our platform to not only meet but anticipate the evolving needs of the modern workforce. One key area of focus is the further integration of artificial intelligence and machine learning capabilities into our software. This will enable us to provide even more predictive analytics, offering businesses foresight into potential safety risks before they occur. By analyzing patterns and trends from the extensive data collected through our platform, we can identify probable hazards and advise on preventive measures, thereby shifting from reactive to proactive safety management. As the tenured labor force with vast institutional knowledge starts retiring en masse and a new generation, accustomed to smartphones and digital apps take their place , Anvl intends to enhance connectivity and real-time communication features. This will ensure that regardless of location, employees can access critical safety information, report incidents immediately, and receive timely support. Our goal is to create a seamless, integrated experience that prioritizes employee well-being and promotes a culture of safety, regardless of geographical boundaries. We are committed to making our platform even more user-friendly and accessible. By simplifying the user interface and enhancing the mobile experience, we aim to encourage higher engagement levels among frontline workers. Their direct input and feedback are invaluable for building a comprehensive safety culture. Collaboration with industry partners and regulatory bodies will also be a priority to ensure our solutions not only comply with but also influence future safety standards and practices. By staying ahead of regulatory changes and industry trends, Anvl can provide businesses with the tools they need to remain compliant and competitive. Lastly, sustainability and environmental health will play a larger role in our platform's evolution. Recognizing the intersection between environmental practices and worker safety, Anvl will expand its capabilities to support organizations in their pursuit of sustainability goals, ensuring a safe, healthy, and sustainable workplace for all. Our commitment to innovation, coupled with a deep understanding of our clients' needs, positions us to lead the way in creating safer, more efficient, and more resilient workplaces worldwide. How does Anvl stay ahead of changes in workplace regulations and ensure its platform remains compliant? Anvl’s AI ensures we are constantly evolving with the changing requirements and allows for real-time edits and customizations by clients. What advice would you give to businesses considering implementing a connected worker platform? Ensure you implement a platform over a point solution; obsess over frontline worker usability and adoption (does it work offline?) and information integrity (how does the platform ensure data parity and data integrity while simultaneously solving for bespoke experiences for different areas and/or sites. Looking at the current landscape of workplace technology, where do you see the biggest gaps or opportunities for innovation? Innovation is happening at a rapid clip, what the broader Industrial SaaS world needs is more integration and interoperability. Larger, established players should be willing and wanting to optimize end-user experiences and data enablement via simple integrations. Welcome to "Power Leader," an exploration of leadership and innovative technologies reshaping various industries. This series is designed to bring to light the pivotal roles that leaders play in driving their organizations towards groundbreaking achievements, especially through the lens of technological advancements and strategic foresight. The leaders featured in "Power Leader" are selected because they exemplify what it means to steer companies through the challenges of modern business landscapes. They are pioneers, thinkers, and strategists making notable impacts within their sectors. By focusing on their achievements and the specifics of the technologies they develop or adopt, it provides a comprehensive look at what makes their approaches successful and influential. Why is this important? Understanding the nexus between effective leadership and innovation is more crucial than ever. These stories not only highlight successful strategies and cutting-edge solutions but also serve as a source of inspiration and learning for our readers. They offer insights into managing complex transformations and leveraging technological advancements to not only survive but thrive in competitive markets. Next up is Zach Taylor, CEO of Anvl and a noted SaaS advisor. Anvl is a leader in enhancing workplace safety and productivity through innovative technology. Zach Taylor, Anvl How does Anvl's platform specifically cater to the unique needs of different businesses? How does Anvl's platform specifically cater to the unique needs of different businesses? Anvl’s AI Connected Worker Platform is the sole digital layer for industrial enterprises to digitally transform to enhance frontline work experiences, making work safer, improving quality, and delivering trustworthy data in real-time to leadership for continuous improvement. Can you describe some real-world scenarios where your platform has improved workplace safety and productivity? Can you describe some real-world scenarios where your platform has improved workplace safety and productivity? One compelling example of our platform's impact comes from our work with Constellation. Initially, their Near Miss program relied heavily on manual, paper-based processes. Technicians submitted nearly 12,000 Near Miss forms annually, which were then transcribed into spreadsheets. This cumbersome process resulted in thousands of hours of administrative work, offering minimal insight into safety trends or reporting capabilities. Recognizing the need for a more efficient solution, Constellation implemented the Anvl Mobile App. This transition to a mobile-first system enabled the immediate deployment of a fully customized Near Miss program alongside digital workflows for various safety audits and permits. The app's adoption by around 400 technicians and supervisors facilitated tens of thousands of digital workflows, significantly enhancing the identification of hazards and risks directly in the field. The results were transformative. The app's adoption led to a 95% compliance rate across Constellation's safety programs, with thousands of workflows completed yearly. The app's offline functionality ensured uninterrupted productivity, while its features, such as voice-to-text, annotated photos, and video, enabled the collection of reliable data. This shift not only allowed for real-time issue identification and risk notification but also provided leadership with insights into trending hazards and operational challenges faced by the crew. Through the aggregation of thousands of safety-related data points, Anvl delivered scalable insights that were previously unattainable. Constellation could proactively identify the top issues their teams faced each quarter, including significant operational "Materials" issues, thereby reducing unnecessary expenses and optimizing material usage and time. Through the aggregation of thousands of safety-related data points, Anvl delivered scalable insights that were previously unattainable. Constellation could proactively identify the top issues their teams faced each quarter, including significant operational "Materials" issues, thereby reducing unnecessary expenses and optimizing material usage and time. Moreover, Anvl's introduction of proprietary metrics such as the Strength Score & Power Score enabled a nuanced assessment of safety performance across various levels of the organization. This holistic approach to safety management and continuous improvement has not only elevated compliance to an all-time high but also resulted in significant cost savings and increased work efficiency for Constellation What makes Anvl's software different from other connected worker solutions available on the market? What makes Anvl's software different from other connected worker solutions available on the market? Anvl’s Mobilize product leverages AI to automatically transform your company’s specific procedures and compliance documentation in seconds into dynamic logic workflows made available through our fully internationalized mobile app (iOS, Android, and Windows). How does the customization process work for a new client? Can you walk us through the highlights  from initial contact to full implementation? How does the customization process work for a new client? Can you walk us through the highlights  from initial contact to full implementation? This is where Anvl’s AI shines, implementation takes minutes rather than months. Upload your company's forms or  let Mobilize generate OSHA and ISO compliant programs and documentation in seconds. These are then made immediately available through our SOC2 compliant mobile app available through iOS, Android, and Windows. This is where Anvl’s AI shines, implementation takes minutes rather than months. Upload your company's forms or  let Mobilize generate OSHA and ISO compliant programs and documentation in seconds. These are then made immediately available through our SOC2 compliant mobile app available through iOS, Android, and Windows. In terms of data privacy and security, what measures does Anvl take to protect its users? In terms of data privacy and security, what measures does Anvl take to protect its users? Anvl leverages modern, best-in-class cloud and security architecture and protocols, and maintains SOC2 compliance. Looking ahead, how do you see Anvl evolving to meet future workplace safety and productivity needs? Looking ahead, how do you see Anvl evolving to meet future workplace safety and productivity needs? Anvl is positioned at the forefront of a significant transformation in workplace safety and productivity. Our vision is grounded in the continuous innovation and enhancement of our platform to not only meet but anticipate the evolving needs of the modern workforce. One key area of focus is the further integration of artificial intelligence and machine learning capabilities into our software. This will enable us to provide even more predictive analytics, offering businesses foresight into potential safety risks before they occur. By analyzing patterns and trends from the extensive data collected through our platform, we can identify probable hazards and advise on preventive measures, thereby shifting from reactive to proactive safety management. As the tenured labor force with vast institutional knowledge starts retiring en masse and a new generation, accustomed to smartphones and digital apps take their place , Anvl intends to enhance connectivity and real-time communication features. This will ensure that regardless of location, employees can access critical safety information, report incidents immediately, and receive timely support. Our goal is to create a seamless, integrated experience that prioritizes employee well-being and promotes a culture of safety, regardless of geographical boundaries. We are committed to making our platform even more user-friendly and accessible. By simplifying the user interface and enhancing the mobile experience, we aim to encourage higher engagement levels among frontline workers. Their direct input and feedback are invaluable for building a comprehensive safety culture. Collaboration with industry partners and regulatory bodies will also be a priority to ensure our solutions not only comply with but also influence future safety standards and practices. By staying ahead of regulatory changes and industry trends, Anvl can provide businesses with the tools they need to remain compliant and competitive. Collaboration with industry partners and regulatory bodies will also be a priority to ensure our solutions not only comply with but also influence future safety standards and practices. By staying ahead of regulatory changes and industry trends, Anvl can provide businesses with the tools they need to remain compliant and competitive. Lastly, sustainability and environmental health will play a larger role in our platform's evolution. Recognizing the intersection between environmental practices and worker safety, Anvl will expand its capabilities to support organizations in their pursuit of sustainability goals, ensuring a safe, healthy, and sustainable workplace for all. Our commitment to innovation, coupled with a deep understanding of our clients' needs, positions us to lead the way in creating safer, more efficient, and more resilient workplaces worldwide. How does Anvl stay ahead of changes in workplace regulations and ensure its platform remains compliant? How does Anvl stay ahead of changes in workplace regulations and ensure its platform remains compliant? Anvl’s AI ensures we are constantly evolving with the changing requirements and allows for real-time edits and customizations by clients. What advice would you give to businesses considering implementing a connected worker platform? What advice would you give to businesses considering implementing a connected worker platform? Ensure you implement a platform over a point solution; obsess over frontline worker usability and adoption (does it work offline?) and information integrity (how does the platform ensure data parity and data integrity while simultaneously solving for bespoke experiences for different areas and/or sites. Looking at the current landscape of workplace technology, where do you see the biggest gaps or opportunities for innovation? Looking at the current landscape of workplace technology, where do you see the biggest gaps or opportunities for innovation? Innovation is happening at a rapid clip, what the broader Industrial SaaS world needs is more integration and interoperability. Larger, established players should be willing and wanting to optimize end-user experiences and data enablement via simple integrations.

POWER LEADER: Anvl's Zach Taylor on the Connected Worker Platform for Safety and Productivity

What Is Design Mentoring? (In a Nutshell) It’s a given that after years of working as a designer, you accumulate immense knowledge on the subject. What’s also a given is that, sooner or later, you will likely want to (or have to) share this knowledge with some newbie. Whether it’s your tips on how to use designer tools or on how to build proper communication inside your team, or your ideas on how to make one’s first steps in the industry - trust me, any wisdom will be appreciated. If you are not actively seeking an apprentice, you still might end up with one in the form of onboard mentoring. Say, you are working in a rapidly growing design team. Newcomers will likely need help in learning the trade’s tricks, design tool hacks, and other things in order to assimilate and become productive. But newbies won’t be the only ones who would benefit from having you as a mentor. Mentoring is a wonderful opportunity to structure your own skills and knowledge and even make them a lot more profound. Types of Design Menoting (Personal Experience) After I’ve had a few mentees of my own, I have distinguished three types of mentoring: Designer newcomer mentoring Mentoring fellow designers during a design course or program Personal mentoring upon a mentee’s request All these types have their peculiarities, but despite these differences, becoming a proper mentor takes you through a string of phases. And as I found out firsthand, these phases are pretty much universal. Before I walk you through them, I have to mention that these phases do not necessarily go in that order. Besides, depending on your own personality, you might easily skip one or two. In the end, your journey to mentorship will greatly depend on the time you can devote to mentoring, your mentee’s level of training, and their willingness to openly communicate. By the way, a spoiler: more often than not, proper communication is the thing that kick-starts a mentee’s development. Now, ready? Off we go then! Mentorship Phases (Problems and Solutions) Genuine anticipation During this phase, you eagerly (or not so much) await your interaction with your mentee. You might have way too high expectations when it comes to your mentee’s communication skills, work ethic, and efficiency. This is all especially true if you are new to this whole mentoring thing. You might even start to question your own ability to be a mentor for a fellow designer. The most important thing to do is to get to know your mentee better before mentoring actually begins. Learn about their education, background, and their go-to tools. Then, also beforehand, you need to know the exact goal of your mentoring, both for yourself and the mentee. This knowledge will help you shape your mentoring style for this specific case. And it certainly won’t hurt to frequently check on these goals in order to evaluate your mutual progress. Tips: Frustration You might enter this stage during your first encounter with your mentee. These are the tale-tell signs that they are not willing to engage with you: They keep silent They don’t ask questions They are not willing to turn on their camera if you are meeting online one-on-one, especially when they are among other mentees on the call (I’ve had a few of those). : Make sure to use your first encounters to set basic communication rules that will be used throughout your whole mentoring. Don’t be shy to remind your mentee of these rules should your apprentice neglect them. If breaking of the rules persists, ask why. This might be for a good reason. Tips Plateau This is the phase when you receive the results of your mentee’s work, whether these are complete tasks, or design fixes after your reviews. This stage encourages you to go on, even though problems from the previous phase might still manifest themselves. : Try your hand at role-playing. Put on a mask of a person ignorant of design, or become a customer. This will prompt your mentee to assume the position of power and explain their views of design. Tips Breakthrough Every proper mentor anticipates the phase. This is the moment when your mentee exceeds your expectations or when they make a leap in development as a designer. I’m not talking about perfect designs or flawless mockups (these are fine, too, don’t get me wrong). But proper communication, the ability to effectively defend one’s point of view, or mastery in holding a presentation showing a design’s journey from a concept to application are just as important in my opinion. : Don’t pressure your apprentice too hard. Instead, support them, and engage them to ask questions. And don’t be nitpicky. This especially applies to mockups and components done in Figma or Sketch. Tips Total mess There might be instances when your mentees skip your meetings without any warning. Or they fail to deliver their assignments on time. Or worse, they ignore the rules that you have set prior. This will inevitably cause you frustration. : Here’s my simple rule to deal with it - you need to have a talk (no aggression, no accusations) after the first instance of such nature. Do not wait till this behavior becomes a habit. During the talk, you need to find out the reason for breaking your rules (the situation could be understandable). Apart from that, you need to decide on the solutions to the miscommunication problem and receive your mentee’s confirmation that they will further restrain from such behavior. Tips This could happen that apart from you two, a manager and a supervisor might be involved in a talk like that. After all, such cases are slightly beyond your primary job (and above your pay grade as well). Enjoyment and progress This is obviously the best stage in mentoring. You have proper communication established, you know that the mentee is motivated, and you see their progress. One of the best things about this phase is your ability as a mentor to articulate your point of view, explain the subject, and be open to the mentee’s questions : At a certain point, your mentee might be asked to give feedback on you as a mentor. Many companies overlook this opportunity, believing that mentors’ opinion matters more because of their advanced knowledge. However, feedback is valuable even for seasoned pros, as they provide reviews of their strengths and weaknesses. Tips Why Even Bother? (My Opinion) Being a mentor is almost as hard as being a mentee. Each of these roles comes with its own strengths, weaknesses, and flaws. Still, there is a reason for a designer to try their hand at mentoring. It will give you a chance to look at your own expertise in a new light. What if you are still lacking some experience and knowledge? Then there’s a solid reason to become a mentee yourself, thus closing the designer mentor-designer mentee cycle.

How to Be Good Mentor for a Fellow Designer

How Useful are Computational Models to Traders in Their Decision Making?

In the era of widespread adoption of AI models, the data science community exhibits a rich diversity of backgrounds, fostering an environment conducive to innovation. Collaborative efforts stemming from this diversity continue to propel us toward the envisioned future of a decade or two ago. However, innovation often follows incremental patterns and may require decades before yielding tangible commercial benefits. Among industries adept at translating ideas into tangible products, automotive manufacturers stand out, boasting a deep familiarity with research and development processes and advanced algorithms. This proficiency is evident in the innovation pipeline for super and hypercars, drawing inspiration from advancements in rocket science. Leveraging extensive simulations and field tests, these manufacturers consistently push the boundaries of performance and safety in vehicle design. Major manufacturers have achieved breakthroughs with torque vectoring systems by capitalizing on established development pipelines and harnessing the capabilities of reinforcement learning. The late 2010s witnessed a surge in commercial vehicles featuring these systems, attributed partly to their association with electric and hybrid vehicles and partly to the appeal of enhanced safety. While the full extent of their influence on driver experience remains to be realized, these systems have already demonstrated remarkable efficacy, particularly in high-performance vehicles. So, what exactly is a torque vectoring system, and how is this innovation shaping the landscape of automotive manufacturing? What is Torque Vectoring In Torque Vectoring Systems (TVS), torque denotes a rotational force applied to a vehicle’s differentials or generated by independent electric motors on its wheels. These systems aim to regulate this rotational force to enhance speed, stability, handling, balance, and other performance aspects. A compelling illustration of the protracted nature of innovation is evident in the evolution of torque vectoring systems, with the first cars equipped with Torque Vectoring Systems (TVS) debuting in the 1990s, pioneered by Mitsubishi. Initially known as Active Yaw Control, Mitsubishi integrated this technology into vehicles like the 1996 Mitsubishi Lancer Evolution IV GSR models. The initial implementation relied on steering, throttle inputs, and g-force sensors to mitigate torque steer, a phenomenon where engine torque influences steering behavior. Initially geared towards racing applications, these systems have since evolved to cater to broader audiences, with companies like Rimac continuing to employ them for racing. In contrast, others emphasize safety and enhanced handling features for everyday drivers. Furthermore, advancements driven by the pursuit of eco-friendly transportation have led to the utilization of independent electric motors in torque vectoring systems, further expanding their applicability. Commercial Applications Ricardo (Honorable Mention) In 2006, Ricardo, a renowned engineering consultancy with over a century of experience, introduced the concept of torque vectoring. Ricardo rolled out its initial torque vectoring project centered around the Audi A6 4.2L, intending to license its technology to interested automakers. Unlike Mitsubishi’s Active Yaw Control system and similar counterparts, Ricardo’s torque vectoring approach prioritized safety and stability, showcasing a different aspect of the technology. Limited information is currently available on Ricardo’s involvement in assisting manufacturers in developing these systems for commercially available vehicles. However, they have publicly provided engineering support to Chinese students building cars for the global multi-event Formula SAE race in 2019. Rimac When discussing electric vehicles, Tesla typically takes the spotlight regarding market dominance. However, Rimac stands out as a company dedicated to crafting high-performance electric hypercars, where they excel. Just ask Elon… ( t) X pos Rimac burst onto the scene in January 2016 with their inaugural concept car, the Concept_One prototype. This marked the debut of their torque vectoring system (TVS) in an all-wheel-drive fully electric vehicle. Spearheaded by Tomislav Šimunić, Rimac’s TVS development pushed the boundaries by employing individual motors on each wheel. Moreover, they implemented reinforcement algorithms utilizing data from various sensors, including accelerometers, gyroscopes, steering angle, and wheel speed sensors. This data is then used to predict torque distribution to optimize vehicle stability. https://www.youtube.com/shorts/i4jVW29gbDc?embedable=true Currently, Rimac boasts one of the fastest and safest hypercars on the market. Their innovation has led to unprecedented control, resulting in their car achieving the title of the fastest production car ever in 21 acceleration and deceleration categories. Furthermore, their TVS is so reliable that their drivers can cruise hands-free at speeds exceeding 230 mph while enjoying gelato! Toyota In 2018, Toyota introduced their Dynamic Torque Vectoring AWD and Electric 4WD systems, expanding the scope of this technology beyond on-road safety and control to encompass off-road safety features and enhanced fuel efficiency. https://www.youtube.com/watch?v=LCqCa7PP1gE&embedable=true The video above showcases Toyota’s emphasis on “proactive torque transfer,” allowing for seamless adjustment of torque distribution when one or more wheels lose traction, enabling drivers to navigate various terrains more effectively. https://youtu.be/d1UG1a38diw?embedable=true Furthermore, Toyota optimizes torque distribution to enhance fuel-efficiency, shifting from AWD to 2WD when conditions permit, directing torque predominantly to the front wheels and thus cutting fuel consumption. Their limited content suggests the employment of a Dynamic Control System designed for stability, taking into account challenging driving scenarios. Moreover, the system can evaluate tire traction levels. These functionalities resonate with the research findings discussed below, showcasing the seamless transition from research concepts to practical implementation in the automotive industry. Research Review Conceptual Models — Bicycle, Vehicle, Tire Model Following Occam’s razor principle, simplicity reigns supreme when initiating modeling endeavors, with complexity introduced only when its benefits are worthwhile. This philosophy holds for TVS as well. Early TVS adopted a bicycle model, allowing researchers to streamline vehicle dynamics assumptions by confining movements to two wheels. This simplified framework facilitated the study of lateral vehicle dynamics during various events like braking, acceleration, and cornering under typical conditions. Key inputs into the bicycle model include yaw rate, lateral acceleration, steering angle, and velocity. Yaw rate denotes the vehicle’s rotation speed around its vertical axis, aiding in determining its orientation during maneuvers like cornering. Lateral acceleration captures sideways movements perpendicular to the vehicle’s direction of travel. Steering angle refers to the front wheel angle, typically in relation to the rear wheel positioning, while velocity represents the vehicle’s speed. For more details, check out this article explaining a simple bicycle model. https://dingyan89.medium.com/simple-understanding-of-kinematic-bicycle-model-81cac6420357?embedable=true Simplicity in modeling often comes with assumptions that may not hold, especially in challenging driving scenarios. Extreme conditions like rain, snow, or rough off-road terrain expose the limitations of the traditional bicycle model. The assumption of symmetry between the left and right wheels hinders the accurate analysis of lateral dynamics across all four wheels. To address this, researchers upgraded to a more comprehensive 4-wheel vehicle model. One such model, proposed in the 2023 journal article by Hui Deng, Youqun Zhao, Fen Lin, and Qiuwei Wang, boasts seven degrees of freedom. This expanded model captures all four wheels’ lateral, longitudinal, rotational, tilting, leaning, and spinning movements. However, it still falls short in capturing driving dynamics such as suspension behavior and tire-road interactions. Although suspension dynamics may be indirectly represented within the model, a separate tire model is necessary to capture tire-road interactions accurately. Deep Reinforcement Learning-Based Torque Vectoring Control Considering Economy & Safety² Tire models typically include parameters like tire force and slip angles. In the journal article by Michele Vignati, Edoardo Sabbioni, and Federico Cheli, researchers describe a simple tire model that incorporates lateral and longitudinal dynamics, slip angles, and slippage. Like the seven degrees of freedom model indirectly addresses suspension dynamics, the tire model considers slippage influenced by latent variables such as surface texture, conditions, and angles. This comprehensive approach allows researchers to analyze vehicle dynamics across various conditions and terrains, enhancing the torque vectoring system’s adaptability and performance. A Torque Vectoring Control for Enhancing Vehicle Performance in Drifting³ Control Schemes/Implementations In Torque Vectoring Systems (TVS) development, a significant portion of research revolves around employing Reinforcement Learning techniques, leveraging real-time data collected from various measurement devices. These solutions are predominantly implemented in all-wheel drive, four-wheel drive hybrid, and electric vehicles. Typically, the training of these systems takes place within simulated environments. However, in certain instances, researchers conduct road tests and utilize live test outcomes to validate simulation results. Torque Vectoring System Testing While specific details about testing TVS are often limited, researchers generally have three options: entirely computer-based simulations, hardware-in-the-loop testing combining simulation with real parts, and full-scale vehicle road tests. Computer-based simulations offer cost-effective evaluation of TVS with precise control over various driving conditions. Hardware-in-the-loop testing balances simulation and road tests, providing insights aligned with real-world performance. Although the most expensive, road tests offer the most reliable results by implementing TVS fully, enabling the most accurate evaluation of model performance. In the study by Shayan Taherian, Sampo Kuutti, Marco Visca, and Saber Fallah, computer-based simulations were utilized to test their RL algorithm across diverse environments. The researchers employed an adaptive algorithm based on Deep Deterministic Policy Gradient to update TVS control parameters as it learns from the environment. Testing across various velocity and friction environments allowed validation of their adaptive algorithm, particularly in high-speed/low-velocity scenarios. Self-adaptive Torque Vectoring Controller Using Reinforcement Learning⁴ Similarly, in the research by Wei Xu, Hong Chen, Haiyan Zhao, and Bingtao Ren, real-time Simulink simulations were leveraged to validate their model predictive controller. This controller predicts future system states and optimizes for multiple energy efficiency and safety objectives. Tests were conducted using an electric vehicle model with a 120 km/h velocity and an “adhesion coefficient” of .85, measuring tire friction between tire and ground. Torque Optimization Control for Electric Vehicles with Four In-Wheel Motors Equipped with Regenerative Braking System⁵ Powertrain & Fuel Types The specific problem addressed by torque vectoring systems heavily influences the powertrain choice and fuel types utilized in their implementations. Traditional gasoline and diesel vehicles necessitate mechanical implementations due to a single torque source, leading to complex mechanical differentials, challenges in power distribution, and overall less efficiency compared to hybrid and electric vehicle setups, which enable independent motor implementations. Similarly, All-Wheel Drive (AWD) and Four-Wheel Drive (4WD) powertrains offer superior advantages over other options. These configurations enhance stability, versatility, and energy efficiency. The work of Jeongmin Cho and Kunsoo Huh, in their study , underscores the stability and versatility benefits of AWD vehicles. By distributing power to all four wheels, AWD enhances the effectiveness of torque vectoring systems, granting increased control over each wheel. This translates to improved vehicle dynamics during cornering, acceleration, and deceleration. Torque Vectoring System Design for Hybrid Electric–All-Wheel Drive Vehicle⁶ Meta Control Algorithms In Reinforcement Learning (RL), an agent decides actions based on the current situation to maximize a reward function. It learns which actions yield the highest rewards by assessing the outcomes of its actions. In torque vectoring algorithms, auto manufacturers define different reward functions based on the specific goals of their TVS, which vary depending on the type of vehicles used, such as sports cars versus mini-vans. These goals include increased stability, controllability, fuel economy, cornering performance, and optimizing various vehicle dynamics behaviors. One example of a multi-objective implementation is outlined in the paper by Jae-Young Park, Seung-Jin Heo, and Daeoh Kang. Their algorithm features a supervisory controller that selects between an “agile” mode and a “safe” mode based on vehicle and driving conditions. Agile mode prioritizes driver controllability, while safe mode focuses on stability. Controllability refers to the synchronization between driver steering input and vehicle direction, while stability relates to the vehicle’s resistance to deviations or disturbances. Inputs such as vehicle speed, steering angle, yaw rate, lateral acceleration, and wheel slip guide the supervisory controller’s decision-making process. Development of Torque Vectoring Control Algorithm for Front Wheel Driven Dual Motor System and Evaluation of Vehicle Dynamics Performance⁷ Another example is presented in the paper by Hui Deng, Youqun Zhao, Fen Lin, and Qiuwei Wang. Here, the researchers optimize for safety, economy, and driver load. Economy involves assessing motor efficiency and energy savings compared to vehicles without torque vectoring systems. Safety focuses on vehicle stability, while driver load considers the physical and cognitive load based on the correlation between the driver’s steering wheel angle and the vehicle’s longitudinal acceleration. Deep Reinforcement Learning-Based Torque Vectoring Control Considering Economy and Safety⁸ The algorithm includes an active safety controller and a torque allocation layer. The active safety controller calculates total longitudinal acceleration and additional “yaw moment” values based on driving conditions, applying safety and driver load penalties. These values are then fed to the torque allocation layer, which distributes torque to all four wheels. Additionally, the researchers implement a tire model using a Fibonacci tree optimization algorithm and a vehicle model with 7 degrees of freedom to enhance system performance. The , research done by Park et al., aims to enhance the driver’s experience through improved smoothness and convergence. Their TVS, designed for commercial application, underwent rigorous validation through real vehicle experiments conducted under various conditions. Torque Vectoring Algorithm of Electronic-Four-Wheel Drive Vehicles for Enhancement of Cornering Performance⁹ The researchers implemented a smooth sliding controller, GPS, and sensor inputs to generate desired yaw moment values. These values are then utilized by the torque allocation algorithm, which employs a daisy-chaining allocation method to distribute torque efficiently. The goal is to optimize the convergence from current yaw moment values to target values, thereby reducing the instability during this transition. Conclusion The evolution of torque vectoring systems underscores the transformative power of innovation within the automotive industry. From pioneering beginnings to cutting-edge applications, these systems have revolutionized vehicle dynamics, speed, stability, and handling. As automotive manufacturers continue to push the boundaries of technology and leverage advancements in advanced algorithms, the future holds promise for further improvements in safety, performance, and driver experience. However, hurdles remain in integrating this technology into internal combustion engine vehicles, and ongoing research and development efforts are required to overcome them. With continued dedication to innovation, torque vectoring systems are poised to shape the future landscape of automotive manufacturing, driving us toward a new era of mobility. Research Reference Martin Dendaluce Jahnke et al., “Efficient Neural Network Implementations on Parallel Embedded Platforms Applied to Real-Time Torque-Vectoring Optimization Using Predictions for Multi-Motor Electric Vehicles,” 8, no. 2 (February 22, 2019): 250 Electronics Huifan Deng et al., “Deep Reinforcement Learning-Based Torque Vectoring Control Considering Economy and Safety,” 11, no. 4 (April 6, 2023): 459 Machines Michele Vignati, Edoardo Sabbioni, and Federico Cheli, “A Torque Vectoring Control for Enhancing Vehicle Performance in Drifting,” 7, no. 12 (December 5, 2018): 394 Electronics Shayan Taherian et al., “Self-Adaptive Torque Vectoring Controller Using Reinforcement Learning,” , September 19, 2021 2021 IEEE International Intelligent Transportation Systems Conference (ITSC) Wei Xu et al., “Torque Optimization Control for Electric Vehicles with Four In-Wheel Motors Equipped with Regenerative Braking System,” 57 (February 2019): 95–108 Mechatronics Jeongmin Cho and Kunsoo Huh, “Torque Vectoring System Design for Hybrid Electric–All Wheel Drive Vehicle,” 234, no. 10–11 (April 7, 2020): 2680–92 Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering Jae-Young Park, Seung-Jin Heo, and Dae-Oh Kang, “Development of Torque Vectoring Control Algorithm for Front Wheel Driven Dual Motor System and Evaluation of Vehicle Dynamics Performance,” 21, no. 5 (October 2020): 1283–91 International Journal of Automotive Technology Huifan Deng et al., “Deep Reinforcement Learning-Based Torque Vectoring Control Considering Economy and Safety,” 11, no. 4 (April 6, 2023): 459 Machines Giseo Park et al., “Torque Vectoring Algorithm of Electronic-Four-Wheel Drive Vehicles for Enhancement of Cornering Performance,” 69, no. 4 (April 2020): 3668–79 IEEE Transactions on Vehicular Technology

Driving Innovation: The Science of Torque Vectoring Systems

The landscape of chatbot technology has seen significant evolution. Chat-bots 5-10 years ago were simple, they used State Machines. Today, Chat-bots are Large Language Models which use AI Agents instead of traditional States. I want to propose the concept of AI routing, which promises to enhance the efficiency and effectiveness of multiple LLM agents. From Deterministic to Probabilistic Automation Pre-GPT Chatbots: State Machines Originally, chatbots were Finite Determined Automation, behaving predictably with each user interaction. These chatbots functioned as "State Machines," moving from one state to another based on predefined rules. If you ever interacted with pre-GPT chatbots, most of them were straightforward. They ask for step 1, step 2, step 3. Every state was predictable. However, this is not how we dialogue, because any dialogue quickly goes out of the scope of any state. Current Stage: Transition to Undetermined Automation New generation chat-bots are Undetermined: Each state has a probability to move to the next state. This probability is determined by the random seed of the LLM model which is used. That is why this model is a Finite Undetermined Automation. Or Even Infinite Undetermined Automation The Current Landscape of AI Interaction Deterministic Supervision and Chain-of-Interaction Chain of thought (CoT) prompting is a recent advancement in prompting methods that encourage Large Language Models (LLMs) to explain their reasoning. It leverages multiple LLM calls within an expert framework to better predict the course of the dialogue, as demonstrated in research on psychiatric behavior understanding. 1 Speaking easy, it gives more logic to the input, sharing more examples with the LLM. LLMs like examples; the same as humans. Without a doubt, it boosts the quality of the outcome. How efficient is that? Well, for some models it may triple the quality: CoT is widely used in research for Math Word Problems and other topics where logical reasoning is important. Chain-of-Interaction: LLMs for Psychiatric Behavior Understanding But CoT is not used only in Math problems. In the article, researchers have put Deterministic supervisory: based on user interaction predict the next state. , Chain-of-Interaction: Enhancing Large Language Models for Psychiatric Behavior Understanding by Dyadic Contexts Example: Psychiatric LLM realizes a person doesn`t want to talk about drinking, the model must recognize a new state “Change talk” and push a new talk to the dialogue. This approach was proposed in the article “ prompting” where the model predicts a chain: Chain-of-Interaction Interaction Definition Involvement Assessment Valence Analysis Long story short, instead of predicting the next state of an LLM-therapist, they do multiple calls of LLM, and they use an expert framework. This expert framework and a sequence of LLM calls give better predictions of the next state of interaction. What if LLMs Start Debating? The third example of the Chain of Thought approach is ChainLM. If there is a complex question, then you can run the game like in a GAN - one agrees, the other disagrees, and they make iterations of the reasoning. Repeat until you get a response. ChainLM: Empowering Large Language Models with Improved Chain-of-Thought Prompting This thing is being further trained using common sense data sets. It highlights the importance of real-world observations. Because if you do the same but for regular LLMs, it may fail in reasoning, and debates will end with a meaningless point. Optimizing With AI Routing Routing is an important step to assist existing apps in creating the optimal selection of LLMs. GPT-4 can give accurate results in various topics, but is expensive, slow, and not as efficient overall, due to high price. While some other models may be cheaper, faster, and better for specific tasks. Studies such as Routerbench have highlighted the potential for cost optimization through intelligent model selection, while Tryage introduces a real-time, intelligent routing system inspired by the human brain's architecture. ROUTERBENCH: A Benchmark for Multi-LLM Routing System Advanced Routing and Coordination Mechanisms Choosing the right model for a task presents a unique challenge since different models perform differently on various datasets. Caltech researchers have proposed the Tyage architecture, inspired by the human brain's structure. In the brain, the thalamus directs sensory inputs to specific parts of the cortex. Similarly, the Tyage system is designed to direct user prompts to the most suitable Large Language Models. This approach allows for efficient processing of information, akin to how the brain handles tasks like identifying objects, detecting motion, localizing objects, and recognizing faces by routing these tasks to specialized areas for processing. Further Ideas If you manage the coordination of AI Agents, you want to get more value for the company. You don’t want to use unsafe agents in medical care startups, and you don't want to use clickbait advertisement agents in the sales scripts because they will start promoting NSFW content. Managing AI Agents is a trade-off between short-term value and long-term value. Short-term values can be money, click-through-rate, session length Long-term values are company reputation, safety Throughout the lifetime, each chat with AI Assistant within various contexts is labeled as . Context_j In mathematical terms, the goal is to evaluate and rank each Large Language Model ( ) based on a value metric within every given context ( ). LLM_i Context_j Therefore, for each specific context ( ), the appropriate LLM_i must be chosen to ensure that the value in the subsequent context ( ) is maximized, as well as maximizing the value in the ultimate context ( ). Context_j Context_(j+1) Context_inf You had an argument, and you asked, “AI what should I do?” Let`s imagine your AI is a family coach. And it must give you a piece of advice. Visiting a strip club requires money and provides immediate stress relief, but may lead to questions from your spouse shortly afterward. Meditation costs nothing, offers immediate stress relief, and does not result in questions from your spouse. Talking with your spouse may not provide immediate stress relief, but it offers benefits far beyond those of a strip club. Returning to work generates extra income, but does not directly address the issue at hand. Even in this example, our Value is a combination of personal benefits and group benefits. And this example is radical. In real life, we have to work with epsilon function and continuous A/B tests of AI agents. These challenges are typically addressed using a multi-armed bandit approach that strikes a balance between the exploration of new strategies and the exploitation of known effective ones. Following this, existing LLMs ( ) can be enhanced through a Chain of Thoughts and recurrent LLM debates. LLM_i If you found this discussion intriguing and are curious about exploring the possibilities of AI Router further, I'd be thrilled to dive deeper into this topic with you. The engineering challenges we face in advancing AI technologies are complex, but it's precisely these challenges that fuel our progress and innovation. If you're interested in a pilot project or simply wish to exchange ideas, please don't hesitate to get in touch. Together, we have the potential to shape a brighter, more innovative future

From Chatbots to AI Routing: An Essay

Tools like ChatGPT have been a big help for programmers, offering code suggestions in chat and even directly within their coding environment. But these helpers have limitations. They can’t do everything a programmer can, like checking for errors or running the code to see if it works. This is where AutoDev steps in to make a difference. It’s like a super-powered coding assistant that can take action directly within your code files. AutoDev can edit files, search for information within the code, build and run the code, test it for errors, and even use command-line tools. This means it can help you complete complex coding tasks without you having to do everything manually. In essence, AutoDev takes existing coding helper tools to the next level by giving them the ability to directly work on your code and automate more steps in the coding process. Key Features: Conversation Manager Customizable Tools Agent Scheduler Evaluation Environment A novel framework that empowers AI agents to manage complex software development workflows. We demonstrate its effectiveness through evaluations using established datasets and showcase its ability to handle diverse software engineering objectives. The results highlight AutoDev’s potential to significantly automate software development tasks while maintaining a secure and user-controlled development environment. How It Works Behind the Scenes Imagine a team of AI helpers for your coding projects. That’s what AutoDev is! It lets these AI agents work together to tackle complex software development tasks without needing you to look over their shoulders constantly. Here’s a breakdown of how it works: First, you tell AutoDev what the AI helpers can and can’t do. You can choose from a list of pre-built commands, like editing files, running tests, or checking for bugs. You can even fine-tune these permissions to fit your specific needs. Think of it as giving your AI helpers a rulebook to follow. Setting the Rules: Once the rules are set, you tell AutoDev what you want to achieve. For example, you might ask it to create test cases for your code, making sure they work properly and catch any errors. This is like giving your AI helpers a specific task to complete. Giving Instructions: This part acts as the project manager for your AI helpers. It keeps track of everything that’s said and done, making sure everyone is on the same page. It also decides when to pause things and check in with you, just in case. The Conversation Manager: The AI helpers might suggest actions, but the Conversation Manager needs to make sure they’re following the rules and using the right commands. It also translates their responses into clear messages for you to understand. Understanding the Helpers: After the AI helpers take action (like running a test), the Conversation Manager gathers the results and puts them in a clear report for you. This way, you can see what the AI helpers did and what the outcome was. Keeping You Informed: Imagine AutoDev as a team manager for AI helpers in coding. This is like the team leader who assigns tasks to different AI helpers based on their strengths. Some helpers are better at understanding code (like OpenAI GPT-4), while others are better at creating code (like smaller language models). The leader decides who does what and in what order, using different methods like taking turns (round robin), letting someone work until finished (token-based), or prioritizing tasks based on importance. The Scheduler: These are like the coding assistants. They can’t directly write code, but they can follow instructions and use tools to help with various coding tasks. They communicate with each other and the team leader using plain English. The AI Helpers: This is like a toolbox with different functions for the helpers. There are tools for editing files (like code, instructions, or notes), searching for specific information within the code, building and running the code to see if it works, checking for errors, and even communicating with the team leader or you (the user) if they need help. The Tool Library: This is a secure environment where the helpers use the tools to work on the code. It keeps everything safe and makes sure no mistakes are accidentally made to the original code. The Safe Zone: How it works: You tell AutoDev what you want the code to do (the objective). It assigns different parts of the task to different AI helpers based on their skills. The helpers use the tools and communicate with each other to achieve the objective. Everything happens in the safe zone to avoid messing up the original code. This process keeps going back and forth until the code is finished, you ask AutoDev to stop, or there have been too many attempts without success. Overall, It helps automate complex coding tasks by using a team of AI helpers with different skills and a safe environment for them to work in. Testing AutoDev’s Skills Imagine you want to see how good AutoDev is at different coding tasks. That’s what the researchers did here. They set up some experiments to answer three main questions: Can AutoDev write code? Can AutoDev create tests for existing code? How efficient is AutoDev at doing these tasks? Write Code The researchers gave some unfinished code snippets and asked them to complete them. They compared AutoDev’s performance to other approaches, including directly using a powerful AI model like GPT-4. It did a very good job (almost as good as the best) at writing code, even without any extra training! They measured success by checking if the code AutoDev generated passed all the existing tests for that code snippet. Creating Test This test flipped things around. The researchers gave AutoDev complete code and asked it to create new tests for that code. They compared AutoDev’s tests to tests written by humans. Here’s the key finding: While AutoDev wasn’t perfect, it created tests that were almost as good as human-written tests in terms of how well they covered the code. The Efficiency Test This test looked at how many steps and resources AutoDev used to complete the tasks. They looked at things like how many times it had to call on the helper AI model and how many words it used in its conversations. This is important because you wouldn’t want AutoDev to take too long or use too much power to do its job. Overall, these tests show that AutoDev is a promising tool that can both write code and create tests for existing code. It’s still under development, but it has the potential to be a valuable helper for programmers. The Results: How Well Does AutoDev Do? The researchers looked at how well AutoDev performed on different tasks: They found that it did a great job (almost the best) at writing missing parts of code, even without any extra training! This is better than directly using a powerful AI model like GPT-4 on its own. Writing Code: AutoDev was also good at creating tests for existing code. Its tests were almost as good as human-written tests in terms of how well they covered the code. Creating Tests: AutoDev takes a few more steps than some other approaches, but that’s because it does more than just write code. It also checks the code it writes to make sure it works properly, which is an important step programmers normally do themselves. How Many Steps Does It Take? AutoDev is a promising tool that can both write code and create tests for existing code. It achieves good results without needing extra training data. It takes a bit more effort (steps) than some other approaches, but that’s because it does more thorough work. Technical Details (can be skipped by most readers): The researchers compared AutoDev to other methods and found it performed well. They measured success by looking at how many times it completed the task correctly on the first try (Pass@1). It uses more “tokens” (words) than some other approaches, but that’s because it takes extra steps, like testing the code it writes. It uses a secure environment to run the code it creates. AutoDev in Action We tell AutoDev to generate a Pytest test with specific assertions for a function in . Here's the Python code for the function: human_answer.py def is_bored(S):
  """
  You'll be given a string of words, and your task is to count the number of boredoms. 
  A boredom is a sentence that starts with the word "I". Sentences are delimited by '.', '?' or '!'.
  For example:
  >>> is_bored("Hello world") 0
  >>> is_bored("The sky is blue. The sun is shining. I love this weather") 1
  """
  import re
  sentences = re.split(r'[.?!]\s*', S)
  return sum(sentence[0:2] == 'I ' for sentence in sentences) We tell AutoDev to write the test to a new file named with a specific format. test_HumanEval_91.py It creates a new test file ( ) with the following code: test_HumanEval_91.py from .human_answer import *
import pytest
def test_is_bored():
  assert is_bored('Hello world') == 0
  assert is_bored('I am bored. This is boring!') == 2
  assert is_bored('The sky is blue. The sun is shining. I love this weather.') == 1
  assert is_bored('I think, therefore I am. I am bored?') == 2
  assert is_bored('') == 0 It discovers an error. One of the assertions fails. AutoDev Detects and Fixes the Error It identifies that the test for fails because it expects the function to return 2, but according to the function's logic, it should only return 1. 'I am bored. This is boring!' It corrects the failing test by updating the assertion statement in (line 5) to: test_HumanEval_91.py assert is_bored('I am bored. This is boring!') == 1 AutoDev runs the tests again, and this time, all tests pass. It successfully creates a test suite that covers all the functionalities of the function. This example highlights two key features : is_bored It can identify errors in its generated code and fix them. Self-evaluation: It keeps the user informed about its actions throughout the process. User Transparency: Conclusion Imagine them as little code-writing helpers. Instead of developers doing all the work, they become supervisors. And don’t worry, this won’t happen overnight. It’s a gradual shift, and developers will still play a crucial part in shaping the software world. So, while AutoDev is exciting, it won’t replace human developers in the long term. They’ll continue to be essential making sure the robots stay in line! 🤖👩‍💻👨‍💻 C# Programming🚀 Thank you for being a part of the C# community! Before you leave: If you’ve made it this far, please show your appreciation with a clap and follow the author! 👏️️ Follow us: | ** | | | | X LinkedIn Dev.to Hashnode Newsletter Tumblr Visit our other platforms: | | | | ** GitHub Instagram Tiktok Quora Daily.dev More content at C# Programming Also published . here

From Davin to Microsoft Autodev: Elevating AI Coding Assistants to Super-Powered Code Editors

A successful cyberattack targeting solar infrastructure could adversely impact convenience, safety, and national security. While the price of inaction is high, many modern panel arrays lack basic security controls and are vulnerable. can be the solution. Cybersecurity Why Is Cybersecurity for Solar Equipment Crucial? Without more resilient cybersecurity for solar, cities across the country are at risk. Critical energy infrastructure relies on solar panels, meaning a single well-placed cyberattack could cause widespread blackouts. Smart cities and homeowners with solar panels aren’t the only ones affected, either. Solar adoption rates have accelerated rapidly in recent years, meaning everyone getting their electricity from a utility-scale power plant has the potential to be impacted. Another commonly overlooked reason solar cybersecurity is crucial is the country’s reliance on satellites. Most of them to convert sunlight into electrical energy, powering their payloads and processes. Low-orbit satellites are used in everyday life for communication and military surveillance. use solar array systems While many people only consider power plants and panel arrays when they think about cybersecurity for solar, the truth is many more critical technologies and infrastructure can be affected by cyberattacks. The federal government has grown concerned with solar cybersecurity and wants to find a solution. The United States Department of Energy has made it a priority, describing it as and the country’s economy. critical for national security The Major Challenges of Solar Cybersecurity For decades, solar’s cyber-risk was insignificant because it was relatively rare and unadvanced. Now that adoption is widespread and digital transformation has accelerated, more components have become interconnected — meaning they’ve become much easier to hack. Realistically, solar operations regardless of how strong their defenses are. Infiltrations and hacks are inevitable when human error and security gaps exist. Still, the chances of attacks being successful is higher than it should be. are always at risk of a breach More solar photovoltaic inverters — components that convert the direct current produced by solar panels into a usable alternating current — are becoming Internet of Things (IoT) devices. This interconnectedness and always-online state make them vulnerable to cyberthreats. A single inverter can spread malware throughout an entire solar array, even if it isn’t an IoT device. Whether an employee plugs in an infected USB or someone falls for a phishing attempt, the initial infection can progress as long as the components are interconnected. Inverters aren’t the only component lacking adequate security. Most supervisory control and data acquisition (SCADA) systems — computer networks for equipment supervision — have numerous physical and cyber vulnerabilities. The U.S. Cybersecurity and Infrastructure Security Agency warns SCADA systems that allows hackers to create, overwrite, or delete files without authentication or authorization. Unfortunately, the operating technology (OT) solar infrastructure relies on has numerous well-documented — and largely unaddressed — weaknesses. are vulnerable to a critical vulnerability On top of everything else, solar infrastructure is likely to experience ransomware and distributed denial-of-service attacks because it provides essential services and is often run by government or city entities. Hackers target it at a higher rate because of the possibility of a big payout. How Hackers Target and Attack Solar Equipment Previously unknown cyberthreats emerge as more solar panel arrays and utility-scale power plants come online. The as adoption increases, and OT becomes more reliant on the IoT for monitoring, information exchange, and control. risk of cyberattacks increases Even something as minor as infrequent patches and missed updates enables hackers to intercept and manipulate inverter data. They’re often quick to exploit these vulnerabilities to gain an edge for launching future cyberattacks. Since low-orbit satellites lack basic security controls, they’re no harder to hack than inverters or SCADA systems. Hackers for 10 minutes per hour when they pass overhead. Although the wait might discourage some people, it won’t stop them. can try to hack commercial satellites Without photovoltaic technology, satellites can’t recharge their batteries and essentially become useless. When cyberattacks interrupt their power supply, they go dark — potentially causing an information blackout. What Happens When Solar Cyberattacks Are Successful? If hackers successfully attack solar equipment, they can take control of inverters — even without authorization — to reduce power output by altering the AC current or voltage. At best, their meddling will cause the lights to flicker or chargers to be slow. At worst, they cause blackouts. Although solar infrastructure is dispersed — meaning one cyberattack won’t down multiple systems — well-placed attacks can cause widespread service interruptions. While one lone hacker might not be cause for concern, organized threat actors or terror groups could easily work together to interrupt the power supply to large areas. Hackers can also overload batteries, making solar arrays fail and causing permanent physical damage. If hackers adjust the AC voltage or current too drastically, they could even cause electrical fires and damage the grid. Utility-scale power plants often have storage systems to hold surplus solar-generated electricity, so they’re likely targets. Tips to Increase Solar Cybersecurity Resiliency Robust solar cybersecurity relies on threat identification, real-time detection, timely incident response, and rapid recovery. 1. The Principle of Least Privilege The principle of least privilege restricts every person’s access to data and systems, limiting them to the bare essentials they need to complete their responsibilities. With this approach, power plant operators can prevent unauthorized access attempts more consistently. 2. Network Segmentation Network segmentation is critical for solar equipment relying on the IoT since it confines devices into segments based on their risk level. Even if an attacker’s infiltration attempt is successful, they’ll be confined to one place, and their lateral movement will be restricted. 3. Intelligent Automation Technology Intelligent automation technology can enhance incident response. Since it , it enables plant operators to proactively adjust accordingly before issues arise. For example, they can send in technicians or reroute power flow. can forecast likely sources of failure 4. Security Information and Event Management A security information and event management (SIEM) system protects networks from malware. It monitors activity by aggregating data from multiple sources, enabling real-time log analysis and a timely incident response. Solar Cybersecurity Becomes More Critical Every Day All kinds of people, from homeowners to military personnel, would be affected by a successful solar cyberattack. As this technology becomes more widespread, the potential adverse impact becomes more pronounced. Early intervention and timely action are crucial.

Why Cybersecurity for Solar Is Crucial — And Difficult

কেন সৌর জন্য সাইবার নিরাপত্তা অত্যন্ত গুরুত্বপূর্ণ - এবং কঠিন

Warum Cybersicherheit für Solarenergie entscheidend – und schwierig – ist

Por qué la ciberseguridad para la energía solar es crucial y difícil

Pourquoi la cybersécurité pour l’énergie solaire est cruciale – et difficile

सौर ऊर्जा के लिए साइबर सुरक्षा क्यों महत्वपूर्ण है - और कठिन भी

太陽光発電のサイバーセキュリティが重要であると同時に難しい理由

태양광 발전을 위한 사이버 보안이 중요하면서도 어려운 이유

Por que a segurança cibernética para energia solar é crucial – e difícil

Почему кибербезопасность для солнечной энергетики имеет решающее значение и трудна

Güneş Enerjisi İçin Siber Güvenlik Neden Önemli ve Zor?

Tại sao an ninh mạng cho năng lượng mặt trời lại quan trọng - và khó khăn

为什么太阳能网络安全至关重要且困难重重

Imagine you're in the taxi business, cruising through the competitive landscape where companies have to make a big choice – whether to focus on regular folks (B2C) or on businesses (B2B). It's a tough call because most of the industry, like 60 to 70%, goes after regular customers. You might be wondering why more companies aren't jumping into the business customer pool. Let's take a peek at the taxi world, ruled by big players like , , , and Yandex Taxi. We'll see how they deal with regular customers who just want a quick, affordable, and reliable ride. On the flip side, there are corporate customers with a whole different wishlist – they're into service integration, detailed billing, and top-notch safety measures. It's like they have a whole set of demands because of their more complicated needs. Uber Lyft Bolt Now, if your company is thinking about leaning towards or away from the business side, this comparison is gold. Knowing what each group wants is key to customizing your services, sorting out how things run, and planning your marketing game. It's like having a map to navigate the different roads of customer demands. B2C segment Alright, picture this – you're in the hustle and bustle of B2C commerce, where businesses are all about selling stuff directly to regular folks like you and me. It's like a big party with all kinds of shops – from the local stores around the corner to those fancy online shops and even your favorite diners. They all want to be buddies with us, the customers, trying to make a direct connection. Now, for these businesses, the main goal is to make us happy by solving our problems or meeting our needs. They want their stuff to be not just cool but also competitive in the market. And here's the trick – they don't have to be the best at everything. What they need is their special thing, like a "secret ingredient" that makes people pick them. Take the ride-hailing gang, for example. Us regular folks care about the cost, how fast and reliable the ride is, the quality of the service, how easy the app is to use, and any cool extras that make the service even better. It's like a global rule – no matter where you are, everyone wants the most bang for their buck. That's the name of the game, everywhere. Imagine you're picking a ride, and there are two types of folks on your mind. First, some dig the VIP treatment – willing to shell out a bit more for a swanky experience. They crave a ride that screams quality. Then, there's the crew who's all about personalization. They want their ride to vibe with them, maybe choosing the tunes or deciding if they're down for a chat. Now, some companies get it. Like Wheely – they're all about rolling out the red carpet, focusing on those high-end customers. On the flip side, there's Gett, letting folks in Russia tailor their ride, choosing everything from the music to their preferred chat level. But here's the cool part – Yandex Go wants to be the superhero for everyone. They offer different service levels, from Economy to Premium, trying to catch the eye of all kinds of customers. No matter who they're targeting, these companies are on a mission to make us regular folks happy. It's like a dance, always switching things up to keep us, the customers, at the center. It's pretty awesome how each of them has their own way of making us feel special. B2B segment In the B2B (Business-to-Business) sector, companies primarily cater to other businesses, including manufacturers, wholesalers, and providers of business services. This model involves a transactional relationship where the end consumer is typically another business, acting as an intermediary. In the B2B realm, the focus shifts to creating value for business partners, rather than directly for individual consumers. For instance, in the taxi service industry, engaging B2B clients often entails offering transportation services to corporate employees rather than enabling other businesses to resell services. The emphasis here is on understanding and fulfilling the unique needs of business clients. A critical first step in addressing the B2B segment is to categorize it into sub-segments, each with distinct needs: (Small and Medium Enterprises): Representing the majority of businesses globally, SMEs usually have a smaller number of employees (less than 250). SMB/SME These are bigger companies with more employees and established internal processes and policies to manage operations effectively. Large enterprises: Addressing the needs of each segment requires a nuanced approach. For SMEs, the strategy might resemble B2C tactics due to their size and structure. Conversely, when dealing with large enterprises, it's crucial to tailor value propositions to internal decision-makers within the company, often valuing their needs as equal or sometimes more critical than the end users (passengers) themselves. SMB segment When it comes to small and medium-sized businesses (SMBs), they use taxi apps a bit differently. The person who decides in these businesses is often someone who either uses the app themselves or hears feedback from employees using it. Unlike apps made for regular folks, the ones for businesses need to think about what the company needs and what the actual users want. Getting this balance right is super important for making products that work well and get good results for the business. These business decision-makers might use the app for both work and personal stuff, trying to mix it into their business when they need to. Why focus on SMBs: If you're already doing well with regular customers (B2C), you don't need extra stuff to get into the SMB market. Companies might use different ways to get business clients, like making it easy for them to join or doing marketing to bring them in. And the cool part? You don't need to grow your team much to handle this new business. So, if your app doesn't match what regular customers love, these business clients might leave. But making things better for regular customers will also make the SMB folks happy. Challenges of the SMB segment Each joining business likely contributes a small incremental revenue due to the small size of the businesses, requiring a significant volume of companies to make a substantial impact. Instead of creating solutions with direct consideration of the end-user, developers must navigate through a complex network of business needs, stakeholder expectations, and profitability goals. The ultimate aim? To build a product that not only satisfies the immediate needs of the business but also supports its long-term strategic objectives. However, this business-centric focus does not diminish the importance of the end-user. On the contrary, understanding and addressing the end-user's issues are critical to the product's success and, by extension, the business outcomes it seeks to achieve. Moreover, feedback mechanisms inherent in B2B and B2B2C models add another layer of complexity. In direct-to-consumer (DTC) sales models, feedback can be direct and immediate, with users directly conveying their impressions, issues, or suggestions to the product team. In contrast, in B2B and B2B2C models, end-user feedback often goes through several layers—be it through their organizations, direct supervisors, or indirect channels—before reaching developers. This indirect feedback path can dilute the clarity of the user's voice, making it more challenging to identify and meet their true needs and preferences. Integrating direct user interaction tools into the product, such as interactive surveys, in-app feedback modules, or user forums, facilitates direct communication. This direct dialogue enables the collection of first-hand user feedback, providing valuable insights into their experience and needs. Enterprise segment Unlike small and medium-sized businesses (SMBs), getting into the enterprise market means dealing with big companies. It's not just about having a good taxi app; you need to connect with the people inside these companies, convince them, and make sure your app meets their needs. But here's the catch: the folks who decide on buying or developing the product might have different ideas than the ones actually using it. They might like features that seem cool but don't really matter to the people who use the app every day. To win over big clients, you've got to think about what the decision-makers want. It's not as simple as offering a cheap and reliable taxi app. You need to solve their specific problems, like giving them negotiated rates, a system to manage expenses, and tools to handle employees. Dealing with big companies also means spending a lot of money and having a special team to meet their unique needs, which might include customizing the product. How big companies work Most big companies have someone or a whole team making decisions. For example, a transportation department would: Figure out what transportation the company needs. Find transportation partners. Make sure costs are predictable and the terms are good. Run daily operations and make sure everyone who needs access has it. Manage and cut down on costs. But going after big companies has some good things: These companies often have branches in other countries or employees traveling for work. A taxi service that works internationally can make things way easier for their global business. Big companies need a taxi service that can do it all – local rides, long-distance trips – to fit all their needs. Working with big companies usually brings in a lot of money. Just one contract can mean getting hundreds or even thousands of clients. Lots of clients still want the same kinds of things. There's a good chance that not many others in your industry are focusing on big companies. Big companies aren't expecting fancy designs like you see in regular customer apps. If your product already looks modern, that could make you stand out in this market. For example, here's what some corporate platforms for booking taxis and flights look like…) Challenges include: Entering this segment requires your company to invest in several directions: Market research to assess its real size Hiring a team of experts Creating products and operational processes ready for B2B Meeting specific customer needs here and there Moreover, your company needs to understand the specific problems of these individuals in your industry. For the taxi market, typically relevant aspects include: Contractual, predictable rates: Unlike the B2C market, where service prices can fluctuate based on current demand and supply, most large companies expect fixed rates for the duration of the contract. Centralized expense management: Your product should provide centralized reporting and billing on agreed terms, ideally ready for integration with internal expense accounting systems. Centralized employee management: Provide the decision-maker with tools for centralized employee management within the service, ideally through integration with the internal HR system. Centralized expense management: A tool that allows limiting employees' use of trips according to internal policies. As an example, consider the key advantages global mobility platform  uses to attract the corporate segment in the UK: And here we come to the main challenges: First, get ready because stepping into this industry means you'll need a team of pros in sales and customer service. They'll be the experts in talking and keeping good relationships with big companies. Second, focus on making a product that suits the folks who make decisions in the company. Create something that helps manage the company's profile within your product. Third, remember, quick and small approaches usually don't work with big companies. They want your product to be perfect from the get-go, not getting better bit by bit. So, you'll need to put in a bunch of money upfront, way before you get the first big company to use your product Here's the lowdown: sometimes, a partner might ask for things that seem totally new and unexpected. You didn't plan on making these for regular customers or the businesses already using your app. But guess what? 80% of the time, those requests might not be that unique. It's worth digging into the market more to check if other folks need the same thing. For the other 20%, you've got a choice to make. Stick to your regular product and maybe lose this client, or make your product fit whatever they want. But here's the real deal: going all customizable can cost you more in the long run. The upside? If the top management in the company is happy with the tools in your product, little hiccups in your main product (like not finding a driver twice for employee X) won't make them ditch the deal. And in the taxi world, where a perfect ride isn't guaranteed, that's a win. But here's a heads-up: don't let the top management down. Another mess-up in getting a ride might make the travel manager think twice about keeping you around. So, get to know these VIPs and go the extra mile to make sure their trips (or any other deals) go smooth. Conclusion Instead of a lengthy conclusion, I propose three main takeaways from this article: Big companies want a full-fledged product from the get-go. They expect solutions not just for the basics but for different jobs in the company. And that often means tweaking the product, which can jack up the costs. Top management at companies want top-notch security in your product. That means spending more on checks, following rules, and maybe sticking to providers that meet their strict standards. Solving problems for big companies can spill over into regular people's lives, opening up new chances in the regular customer market.

Why Product-Marketers Ignore the Goldmine of B2B Segments: Lessons From the Taxi Industry

Automation systems have radically changed the face of industries, revolutionizing their potential and enabling them to attain higher levels of efficiency, productivity, and profitability. With progress in technology and the emergence of smart manufacturing, automation systems have become a crucial driver of success for businesses across a variety of sectors. The manufacturing sector is undergoing a major transformation, and the growth of robotics is at the center of this change. Industrial robots are a crucial part of contemporary manufacturing processes as technology advances because they provide efficiency, accuracy, and versatility. In this article, we examine the beneficial effects of robotics on manufacturing and examine the challenges and impacts. According to a recent McKinsey Global Institute analysis the quick evolution of Artificial intelligence and robots by 2030. According to the research notes those losses could be offset by a boost in productivity, economic growth, and other factors. However, sustaining full employment will probably be extremely difficult because it would necessitate significant changes to the labor market and economy. could eliminate 73 million American jobs Benefits of Automation in Industries Robotic manufacturing systems may be a relatively new idea for some segments of the manufacturing industry, although the technology has been around for decades. By combining traditional production methods with higher forms of technology, factory managers and business owners can greatly raise their output rates and improve their bottom line. Robots have impacted manufacturing in a variety of positive ways. The manufacturing has a wide-ranging effect, boosting productivity and success for the entire organization. When human workers are relieved from activities that robots can complete with ease, they can devote more of their attention to contributing much-needed knowledge and ideas within higher organizational goals. When implemented correctly, robotics creates an undisputable improvement shift within an organization's operations. impact of automated Production improvement: Automating tasks allows not only greater efficiency in the process by being able to perform various tasks more quickly but also production can be maintained 24 hours a day. Higher quality: Automating tasks allows not only greater efficiency in the process by being able to perform various tasks more quickly but also production can be maintained 24 hours a day. Cost savings: Although automation can involve an initial investment, it also allows great savings. This is caused by several factors, such as fewer errors, which makes the product more cost-effective, and reduces the amount of waste that mistakes create. Information: An automated system allows the collection and storage of a large amount of information regarding the process. This makes it easy to perform analyses that can help further improve the process and make it more efficient. Safety: By automating the most difficult tasks, people are prevented from being put into dangerous situations. Furthermore, automated systems have excellent security measures that help to avoid accidents from occurring. Flexibility: By having greater control of the systems, they can more easily adapt to different situations. As an increased amount of work, or the introduction of fresh elements in the production. Less supervision: Once the system is validated, the appearance of problems in it is very rare, and in case of situations, the systems are prepared to notify them. They therefore require less supervision of their operation. Challenges and Concerns of Automation in Industries The high costs of implementation are one of the main obstacles when deploying industrial robotics. The initial integration procedure will be time-consuming, arduous, and costly. The specifications of new demands may require redesigning the workspace and repurposing robot workers. A specialized integrator may be required for even small changes to a production line. Costs: Trying to integrate new robotic systems with existing infrastructures and technologies is challenging. Smaller-scale SMEs frequently find the expenses too high or prohibitive. To recover the initial investment, production quantities and sales levels must also be sustained for the duration of the anticipated ROI period. This lack of cooperation is another challenge in industrial robotics. A single manufacturer will not only provide its hardware but also software solutions. Then, to coordinate across various devices, a variety of application programming interfaces are required, which may even call for specialized software. The possible roles of robots are limited by the inflexibility of current robotics technologies. Even skilled and experienced line workers are frequently unable to enhance manufacturing processes by this means. Inflexibility: New technologies call for new protocols, and these immediately introduce new safety hazards into the workplace. Industrial robots are no exception and strict regulations surrounding robotic safety, as well as severe penalties. Safety Concerns: Before integrating any industrial robot system, manufacturers need to be ready and have a safe workplace for workers that ensures full compliance. Investment in industrial robots would be encouraged if businesses could achieve an optimal balance between safety, versatility, and speed. Operators must also pick up new knowledge and skills. Employees usually lack the knowledge to operate new types of machinery and, in the case of mobile robots, they don’t know how to behave correctly around them. They often obstruct the way of a robot’s path or are confused about the allocation of tasks between humans and automated workers. Workforce Skills: There isn't the same embedded academic training as with older skills because the technology is still relatively new. Many workers will therefore require training, and in the meantime, it will be necessary to hire additional staff who already possess the necessary education, certifications, and experience. Industrial robots are intended to improve a facility’s entire performance. This implies that they must interact with people in a mutual dependency. Until staff obtains the essential skills, the facility will be much less efficient and therefore less cost-effective. Basic robotics training will increase worker's awareness of how robotic systems behave and how humans should react. Emphasizing the mutual reliance between industrial robotics and humans can lead to an increase in overall efficiency. Workforce Training: This can be assisted by using advanced analytics and data collection to identify key issues as much data as possible should be gathered by operators, such as the number and kind of journey undertaken by robotic systems, downtime resulting from errors and malfunctions, battery charging durations, and idle times. Utilizing this information, operators can modify the necessary procedures to target certain problems and boost robot efficiency. Product workflows need to be assessed to see what benefits could be made by utilizing robots. This involves calculating the speed and orientation of part presentation to robots to ensure production is maximized, without overloading existing systems. Anecdotal and experiential evidence from workers can be analyzed by using data to enhance workflow and assess how their contributions impact design and integration processes. This could also assist in assessing the total impact on performance and production cycles, to get rid of inefficiency. Managing Workflows: Even though they have a wide range of uses, industrial robotics problems are often similar. With all the technological advancements in Industry that enable modern robotic systems, many of these problems are being resolved. Latest Advances: Frequent training will boost people's comprehension of robotic platform operation. In the long run, more people will acquire the requisite skills and could learn how to develop their robotic platforms. Both no-code and open-source programming environments are being used in new programming solutions. The Future of Work in a Robotic Society Automated systems can identify inefficiencies that a human mind could unintentionally overlook, while AI-driven systems help ensure no errors. Consequently, there may be a decrease in the demand for supervisory positions whose primary objectives are quality assurance and productivity management. These digitally-driven systems also enable workers to have short breaks and more freedom from jobs that have become more intense and stressful in current times. This is the most common characteristic of robotics and automation adoption: the augmentation of human labor, rather than its replacement. This technique paves the way for the most ideal situation – humans and robots collaborating, empowering, and transforming the workforce as a whole. The fear that robots will take over human employements, and become the boss, stands invalid. The digital workforce facilitates efficient management of resources – different industries leverage AI-driven solutions to solve the shortage of human resources and promote improved customer service. One example we see frequently: is a new service model that integrates robotics and automation with e-commerce to provide more personalized services. Conclusion Production operations are now controlled by industrial automation. In some ways, the implementation of this system tends to be a substitute for the work done by humans. In short, replacing human beings in an industry. The time consumed on manufacturing has been deducted since robots never get distressed and are capable of engaging in risky jobs. Therefore, labor opportunities may be decreased by up to 50% as it turned automation technologies are budget-friendly. Nevertheless, technology was proven to create jobs rather than destroy the opportunity through robotics, blockchain technology, artificial intelligence, telecommunication, and more. Any size business could find enormous success by implementing automation.

Robots at Work: How Automation is Transforming Industries

Authors: (1) Gopal Yadav, Department of Physics, Indian Institute of Technology & Chennai Mathematical Institute. Table of Links Abstract Acknowledgment PART I Chapter 1: Introduction Chapter 2: SU(3) LECs from Type IIA String Theory Chapter 3: Deconfinement Phase Transition in Thermal QCD-Like Theories at Intermediate Coupling in the Absence and Presence of Rotation Chapter 4: Conclusion and Future Outlook PART II Chapter 5: Introduction Chapter 6: Page Curves of Reissner-Nordström Black Hole in HD Gravity Chapter 7: Entanglement Entropy and Page Curve from the M-Theory Dual of Thermal QCD Above Tc at Intermediate Coupling Chapter 8: Black Hole Islands in Multi-Event Horizon Space-Times Chapter 9: Multiverse in Karch-Randall Braneworld Chapter 10: Conclusion and Future outlook APPENDIX A APPENDIX B APPENDIX C Bibliography ACKNOWLEDGMENTS I am very grateful to my supervisor, Prof. Aalok Misra, for guiding me during my Ph.D. and making me what I am today. I enjoyed all the discussions that we have together. He trained me so that I can now do independent research. Apart from the research part, I learned many things from him, which helped me in the development of my personality in real life and as a researcher. I am very fortunate to have him as my supervisor. I am very thankful to my supervisor and his family, who always treated me like a family member, and for their encouragement, appreciation, and blessings. Without all these, my Ph.D. journey would not have been so smooth and pleasant. I would like to thank the very humble members of my research committee known as “Student Research Committee (SRC)”: Prof. Tashi Nautiyal (chairperson SRC), Prof. Dibakar Roychowdhury (internal member), Prof. Sugata Gangopadhyay (external member - Department of Computer Science and Engineering, I.I.T. Roorkee) and Prof. Arnab Kundu (Saha Institute of Nuclear Physics (SINP), Kolkata, India, an external member of me as a research fellow of CSIR), for their appreciation, encouragement, valuable comments, questions and evaluating me time to time. I am very grateful to Prof. Dibakar Roychowdhury for the discussions related to the research and post-doctoral position. He always encouraged me not to get tired and never give up. I would like to thank my collaborators, my supervisor, Dr. Vikas Yadav and Mr. Nitin Joshi (Indian Institute of Technology Ropar, Punjab, India) for working on the projects and publishing the papers with me. I would like to thank my colleagues from the string theory and high energy physics group Shivam, Hemant, Jitendra, Salman, Debarshi, Pushpa, Sumit and Abhishek for the valuable discussions, comments and questions. I am very grateful to the two former students from our research group Prof. Pramod Shukla (Bose Institute, Kolkata, India) and Dr. Karunva Sil (University of Cyprus) for their very helpful suggestions and guidance to me which helped me in getting a post-doctoral position. I am very grateful to Prof. Keshav Dasgupta for the help related to academia. I would like to thank Prof. Juan Maldacena (IAS, Princeton, USA), Prof. Andreas Karch (The University of Texas, Austin, USA), Prof. Tadashi Takayanagi (YITP, Kyoto University, Kyoto, Japan), Prof. Kostas Skenderis (University of Southampton, UK), Prof. Thomas Hartman (Cornell University), Prof. Suvrat Raju (ICTS, Bangalore), Prof. David Berenstein (University of California, Santa Barbara, USA), Prof. Xi Dong (University of California, Santa Barbara, USA), Prof. Arpan Bhattacharyya (IIT Gandhinagar, India), Prof. Christoph Uhlemann (University of Oxford), Prof. Rong-Xin Miao (Sun Yat-Sen University, China), Prof. Xuanhua Wang (UCAS, Wenzhou, China), Prof. Xian-Hui Ge (Shanghai University, China), Prof. Mohsen Alishahiha (IPM, Tehran, Iran), Prof. Sanjay Siwach (BHU, India), Prof. Chethan Krishnan (IISc Bangalore) for the useful discussions and comments during my PhD. I would also like to thank Prof. Suresh Tiwari, Prof. Rudra Prakash Malik, and Prof. Bhabani Prasad Mandal from the Banaras Hindu University (BHU), India, who helped me to start my journey into the Theoretical High Energy Physics during my master’s. I would also like to thank the editors, associate editors, and referees of the Journal of High Energy Physics (JHEP), Physical Review D (PRD), Physics Letters B (PLB), and European Physical Journal C (EPJC) for their comments, criticism, etc. Those comments helped me in learning something new which was missing in my papers. I am very grateful to the organizers (including speakers and participants) of the various conferences/workshops/schools for organizing very interesting events. I enjoyed those events and learned about the many new research topics. I would like to thank the members of Indian Physics Association (IPA) Roorkee chapter. I enjoyed working with them. The members include, Prof. Akhilesh Kumar Mishra, Prof. Anjani Kumar Tiwari, Ishani, Aalok, Jaikhomba, Nifeeya, Prem Sagar, Priyanshu, Ritika, Shikha, Tsewang, Vanshaj, Vidisha. I would like to extend my gratitude to all the faculty members, staff, and to students, and postdocs in the Department of Physics at I.I.T. Roorkee for making this a memorable journey. I would like to thank my colleagues from the : Shakti, Soumya, Monika, Amarjyoti, Sonu, Pooja, Pooja, Manish, Veer and Mukesh for bearing me and making the workplace vibrant. I also thank my colleagues from the all the research scholar rooms. I thank my friends Shailesh, Rahul, Anurag, Nandeshwar, Sarvesh, Amit, Ramnivas, Shubhajit for their time to time motivation and encouragement. research scholar room 2 I am very thankful to have wonderful seniors who treated me like younger brother: Shubham, Naveen, Aalok, Dibyendu. I specially thank Prem Sagar who took care of me always during my stay at IIT Roorkee and Deepak for the wonderful company. I would like to thank Priyanka, Pooja and Jaikhomba who helped in various way during pre-synopsis and thesis submission. I am very thankful to Anil, Ramashish, Amarjyoti, Shakti and Soumya for their real life knowledge, I feel everyone should have friends like them but please don’t follow them otherwise you may get bitten at some places. I am also thankful to Shivam and Shubranshu for their valuable time and discussion on the real life issues. It was a great pleasure to have Manish, Brij Mohan, Ashutosh, Arun, Harsh, Ishitwa, Shakti at IIT Roorkee who are the alumni from BHU. I thank my friends Divya, Pavneet, Ankur, Anshu, Hemant, Anju, Rahul, Ashish, Tejaswini, Gagan, Uwais for their valuable time and discussions (on various topics) during my stay at IITR. I am very grateful to my family for their continuous support and everything. I am very grateful to my parents (Shri Shyam Narayan Yadav and Shrimati Chinta Devi) who always left me free to do what I wanted to do. I was very fortunate to learn many things about life from my grandfather (Late Shri Ghurfekan Yadav). Seeing me as “Dr. Gopal Yadav” was his dream, I think he will be very happy for me wherever he will be now. I thank my maternal uncle and aunty, “Phupha” and “Bua”, and brother in laws who always encouraged me to believe in myself and for their support. I am very fortunate to have bhaiya and bhabhi, Rinki di, Priyanka di, Shaloo, Prity, Sandip, Arvind bhaiya, Santosh bhaiya, Ravi bhaiya, Bunty, Aman, Aditya, Mahesh, Vipul, Pooja, Ranjita di, Anjali, Akriti, Ankita, Shrija, Devansh, Shreya, Shivansh, Tejas in my life. I am very grateful to my school teachers, college/university professors, and all of my gurus in various fields for educating me in various aspects of life. Education can bring changes and what I am today is the perfect example of it. This paper is under CC 4.0 license. available on arxiv

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