About Us: ChangeCX is a full-service omnichannel firm specializing in innovative solutions for retailers and brand manufacturers. Each member of our leadership team brings an average of 20 years of experience working with some of the largest retailers in the world, giving us unparalleled vision into what it takes to succeed in today’s competitive retail marketplace. Our insight tells us that the next generation of break-out retailers will be those who embrace omnichannel strategies for all interactions with their customers, and it is our singular mission to place you among the elite, illuminating the way forward well into the future. Our Perspective: The most successful retailers today—and beyond—will be the ones who prioritize the customer experience. Connecting customer, product, transaction, and service data at every touchpoint in the shopper’s journey are essential to achieving your objectives, and we’re singularly qualified to make that happen. The next generation of retail stores will not differentiate between the ability to find, fulfill and service transactions based on the location of either the customer or the product. Creating these highly connected experiences requires a partner who understands how to bring those experiences and the data that drives them into a single, seamless experience for the B2B or B2C shopper.

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In this article, I'm going to discuss something really important. If you're a data analyst or you want to learn data analysis, please watch this video till the end because it's really important. The topic of this video is: Can data analysts survive because ChatGPT-4o is changing the game? If you want to know why, please read this article till the end, and you will know everything; plus, you'll see an example of how you can analyze anything within a couple of minutes. Era of ChatGPT-4o As you may know, on May 16th, OpenAI announced the new ChatGPT-4o. It has a lot of improvements, and one of them is related to data analysis. In this article, I will highlight a few things that may help you decide on your data analysis career path or learning path. I will also show you the improved version of GPT-4o and how it can analyze data. My Thoughts Let me share my thoughts regarding the data analysis learning path. If you ask me whether you should learn it or not, I can't give you a direct answer, but I will explain my thinking process, and maybe you can make a decision based on that. I took a data analysis course about two years ago. It was the Google Data Analytics certification, and it took me around six months to finish everything. Now, when I think about my learning journey and up-to-date things, I understand that many things I learned might be useless because of ChatGPT. Of course, I need to understand the main concepts, foundations, and certain things, but I don't have to do a lot of manual work related to cleaning, visualizing, etc., manually anymore. Most things can be done with ChatGPT. So, if you are on your learning path right now or considering taking a data analysis course, you can go ahead, but keep in mind that you need to stay updated with new technology and trends, especially with AI. Many courses don't have up-to-date information, and things are changing rapidly, so in your learning, you definitely should include AI and ChatGPT. What will happen with data analysis in general? I think within two to three years, this profession will not be the same anymore. If people don't utilize AI, they will fall behind, and this will be a big problem. Many people will probably lose their jobs, and this is really scary. Disclaimer: These are just my thoughts. I don't want to discourage you from your learning path or scare you, just sharing my thoughts. Improvements of ChatGPT-4o for Data Analysis Now, let's go back to the improved version of ChatGPT. What has improved? There are four things I would like to highlight: File Integration: You don't have to upload files from your computer anymore. You can upload them from Google Drive or Microsoft OneDrive. **   ** Interactive Tables: You can edit tables inside ChatGPT. For example, if you ask ChatGPT to bring your data in a table format, you'll be able to make changes inside those tables without changing your data set. Everything can be changed directly inside ChatGPT. **   ** Customizable Charts: You can customize charts, download them, and edit them, all directly within ChatGPT. **   ** Security and Privacy: If you are using ChatGPT Plus, Team, or Enterprise, you will be able to turn off training on your data. This means ChatGPT won't use your data for training purposes. ChatGPT-4o Data Analysis Demo Now, the important part. Let's see how we can analyze a dataset with ChatGPT-4o. In this one-minute video, ChatGPT will analyze my dataset without detailed direction. This is my simple prompt, and look at what I get: https://youtu.be/w9DETYpYMS0?si=KEGL8GM2s0Sauzif&t=246&embedable=true As you can see, it's amazing and mind-blowing. Of course, we can improve our analysis by writing better and more detailed prompts. At the end of the analysis, you can ask ChatGPT to create a presentation or PDF file with all the findings and visualizations. It's amazing. Don't expect perfection, but you can add beauty yourself. As you can see, for a regular data analyst, this work would take around a week or two, but ChatGPT did it within a minute. It's wow! That's it! I hope you enjoyed this article. Thank you so much for supporting me with your likes and comments! In this article, I'm going to discuss something really important. If you're a data analyst or you want to learn data analysis, please watch this video till the end because it's really important. The topic of this video is: Can data analysts survive because ChatGPT-4o is changing the game? If you want to know why, please read this article till the end, and you will know everything; plus, you'll see an example of how you can analyze anything within a couple of minutes. Era of ChatGPT-4o Era of ChatGPT-4o As you may know, on May 16th, OpenAI announced the new ChatGPT-4o. It has a lot of improvements, and one of them is related to data analysis. In this article, I will highlight a few things that may help you decide on your data analysis career path or learning path. I will also show you the improved version of GPT-4o and how it can analyze data. My Thoughts My Thoughts Let me share my thoughts regarding the data analysis learning path. If you ask me whether you should learn it or not, I can't give you a direct answer, but I will explain my thinking process, and maybe you can make a decision based on that. I took a data analysis course about two years ago. It was the Google Data Analytics certification, and it took me around six months to finish everything. Now, when I think about my learning journey and up-to-date things, I understand that many things I learned might be useless because of ChatGPT. Of course, I need to understand the main concepts, foundations, and certain things, but I don't have to do a lot of manual work related to cleaning, visualizing, etc., manually anymore. Most things can be done with ChatGPT. So, if you are on your learning path right now or considering taking a data analysis course, you can go ahead, but keep in mind that you need to stay updated with new technology and trends, especially with AI. Many courses don't have up-to-date information, and things are changing rapidly, so in your learning, you definitely should include AI and ChatGPT. What will happen with data analysis in general? What will happen with data analysis in general? I think within two to three years, this profession will not be the same anymore. If people don't utilize AI, they will fall behind, and this will be a big problem. Many people will probably lose their jobs, and this is really scary. Disclaimer: These are just my thoughts. I don't want to discourage you from your learning path or scare you, just sharing my thoughts. Disclaimer: These are just my thoughts. I don't want to discourage you from your learning path or scare you, just sharing my thoughts. Disclaimer: These are just my thoughts. I don't want to discourage you from your learning path or scare you, just sharing my thoughts. Improvements of ChatGPT-4o for Data Analysis Improvements of ChatGPT-4o for Data Analysis Now, let's go back to the improved version of ChatGPT. What has improved? There are four things I would like to highlight: File Integration: You don't have to upload files from your computer anymore. You can upload them from Google Drive or Microsoft OneDrive. File Integration: You don't have to upload files from your computer anymore. You can upload them from Google Drive or Microsoft OneDrive. ** ** Interactive Tables: You can edit tables inside ChatGPT. For example, if you ask ChatGPT to bring your data in a table format, you'll be able to make changes inside those tables without changing your data set. Everything can be changed directly inside ChatGPT. Interactive Tables: You can edit tables inside ChatGPT. For example, if you ask ChatGPT to bring your data in a table format, you'll be able to make changes inside those tables without changing your data set. Everything can be changed directly inside ChatGPT. ** ** Customizable Charts: You can customize charts, download them, and edit them, all directly within ChatGPT. Customizable Charts: You can customize charts, download them, and edit them, all directly within ChatGPT. ** ** Security and Privacy: If you are using ChatGPT Plus, Team, or Enterprise, you will be able to turn off training on your data. This means ChatGPT won't use your data for training purposes. Security and Privacy: If you are using ChatGPT Plus, Team, or Enterprise, you will be able to turn off training on your data. This means ChatGPT won't use your data for training purposes. ChatGPT-4o Data Analysis Demo ChatGPT-4o Data Analysis Demo Now, the important part. Let's see how we can analyze a dataset with ChatGPT-4o. In this one-minute video, ChatGPT will analyze my dataset without detailed direction. This is my simple prompt, and look at what I get: https://youtu.be/w9DETYpYMS0?si=KEGL8GM2s0Sauzif&t=246&embedable=true https://youtu.be/w9DETYpYMS0?si=KEGL8GM2s0Sauzif&t=246&embedable=true As you can see, it's amazing and mind-blowing. Of course, we can improve our analysis by writing better and more detailed prompts. At the end of the analysis, you can ask ChatGPT to create a presentation or PDF file with all the findings and visualizations. It's amazing. Don't expect perfection, but you can add beauty yourself. As you can see, for a regular data analyst, this work would take around a week or two, but ChatGPT did it within a minute. It's wow! That's it! I hope you enjoyed this article. Thank you so much for supporting me with your likes and comments!

New ChatGPT-4o: A Game-Changer That Could Replace Data Analysts

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan;
(2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan;
(3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan;
(4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan;
(5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Setup Result Summary and Discussion Appendix A. Dual Energy Formalism B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime References C. CHANGE OF THE MASS LOSS RATE IN MHD REGIME This paper is available on arxiv under CC 4.0 license. Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Abstract and Intro Setup Setup Result Result Summary and Discussion Summary and Discussion Appendix Appendix A. Dual Energy Formalism A. Dual Energy Formalism B. Convergence of Results B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime C. Change of the Mass Loss Rate in MHD Regime References References C. CHANGE OF THE MASS LOSS RATE IN MHD REGIME

Magnetic Wind From a Massive White Dwarf Merger: Change of the Mass Loss Rate in MHD Regime

While Bitcoin has achieved a formidable status as a store of value, the rise of Ordinals and inscriptions clearly demonstrated users want to use it for more than just that. Beyond simply holding, there’s a massive and rising demand for Bitcoin-based applications, fungible and non-fungible assets, and scalable payments. However, the question is: How does Bitcoin satisfy this desire while preserving the core principles it was based on? The Risks of Inaction There has been great progress made gradually in the Bitcoin ecosystem, but the inability to innovate quickly has led to a concerning trend: a significant amount of BTC is continually being siphoned away from its ecosystem. Despite Lightning Network’s relative success, Ethereum now hosts more BTC than all Bitcoin Layer 2s combined. Even worse, an increasing number of BTC are held on centralized exchanges, which reintroduces the same custody risks from the fiat system that Bitcoin was originally built to mitigate. This is a clear signal that if we, the Bitcoin community, don't offer compelling solutions, others will step in with solutions that may not align with Bitcoin's core values of decentralization and security. If we don’t act, we risk losing control over the direction in which Bitcoin and the broader crypto industry evolve. To that point, Ethereum’s history provides a cautionary tale. As early as 2016, Bitcoin developers Peter Todd and Greg Maxwell highlighted numerous architectural issues with its design. However, the Bitcoin ecosystem’s progress over the past eight years has been relatively slow, while the broader industry has pursued questionable new solutions like Proof-of-Stake, account-based models, and sharding—all of which can undermine the decentralization and security that Bitcoin stands for. We can no longer afford to make the same mistakes. The demand for new Bitcoin-based assets and use cases presents a pivotal opportunity. It calls for a Bitcoin Renaissance. Let's seize this moment to redirect the crypto industry towards a path that adheres to Bitcoin's values, principles, and architecture. The State of Play At its core, Bitcoin was envisioned as a peer-to-peer electronic cash system, not a peer-to-contract system like most smart contract platforms, or a peer-to-sequencer system like current rollups. Bitcoin’s brilliance lies in the Proof-of-Work consensus mechanism and the UTXO model, which offers numerous advantages over the now prevalent account-based model. Instead of recording balances, UTXOs track individual currency units, similar to how physical cash works. This enables the creation of genuine bearer assets—assets owned by whoever holds the private key. Most importantly, Bitcoin’s emphasis is on verification, not computation, which is what blockchains excel at. Computation and complex verification should be pushed off-chain—into protocols that don’t necessarily need to be blockchains. Luckily, the Bitcoin community has proposed many novel ideas for how to do this. Peter Todd’s work on single-use seals is especially notable here, as it paves the way for innovative scaling solutions based on client-side validation, including colored coins, RGB, Ordinals, and Atomicals. The community has also explored and built various Layer 2 solutions with different consensus mechanisms, bridging solutions, and security assumptions. However, despite the richness of the ideas, the ecosystem growth over the years has been slow. This is primarily due to two reasons: Bitcoin’s lack of programmability, and its conservative ethos. It’s (intentionally) very difficult to reach a social consensus on any protocol-level changes to Bitcoin, which is also why we’re having these conversations today. Ushering in The Bitcoin Renaissance If we ought to usher in a Bitcoin renaissance, we should have the following in mind: Our solutions must satisfy user’s needs without sacrificing Bitcoin’s values and without requiring soft or hard forks. Luckily, this is all possible by leveraging the layered approach. We already have some asset issuance protocols, including Ordinals, Runes, BRC-20, and Taproot Assets on the base chain. These directly benefit and simultaneously contribute to Bitcoin’s unmatched security. However, Bitcoin’s limited programmability means that users can’t do much with these assets beyond simply holding them, which is why we need a fully-expressive programmable layer on top. This layer should serve as the financial hub for assets on the Bitcoin chain. Then, we need a secure bridge between these two layers. We can use a typical two-way peg, but Cipher Wang’s (author of the RGB++ protocol) new innovative solution, Universal Isomorphic Binding (UIB), is better. It employs point-to-point mapping between the UTXOs of two chains, eliminating the need for third-trusted parties, which is a giant leap compared to current bridging solutions. Once we’ve established the programmable layer and the bridge, we can build another scalability and privacy-focused layer on top. Solutions for this include client-side-validation-based protocols, Open (partially-signed) Transactions, Nostr, Chaumian e-cash, and peer-to-peer markets. Then, we can use channels to connect all of this, and even connect Web2 and Web3—birthing the new Bitcoin-based Web5 paradigm. Web5 means using cryptography, peer-to-peer technology, and other Web3-native solutions to fix and incorporate into Web2. It’s an entirely different paradigm than the one we’re operating in today—and there’s no better platform to build it on than Bitcoin. By Jan Xie, Chief Architect of Nervos, founder of Cryptape.
This article is based on Jan Xie’s talk at Bitcoin Singapore on March 9th, 2024. Click for slides. While Bitcoin has achieved a formidable status as a store of value, the rise of Ordinals and inscriptions clearly demonstrated users want to use it for more than just that. Beyond simply holding, there’s a massive and rising demand for Bitcoin-based applications, fungible and non-fungible assets, and scalable payments. However, the question is: How does Bitcoin satisfy this desire while preserving the core principles it was based on? How does Bitcoin satisfy this desire while preserving the core principles it was based on? The Risks of Inaction There has been great progress made gradually in the Bitcoin ecosystem, but the inability to innovate quickly has led to a concerning trend: a significant amount of BTC is continually being siphoned away from its ecosystem. Despite Lightning Network’s relative success, Ethereum now hosts more BTC than all Bitcoin Layer 2s combined. Even worse, an increasing number of BTC are held on centralized exchanges, which reintroduces the same custody risks from the fiat system that Bitcoin was originally built to mitigate. BTC This is a clear signal that if we, the Bitcoin community, don't offer compelling solutions, others will step in with solutions that may not align with Bitcoin's core values of decentralization and security. If we don’t act, we risk losing control over the direction in which Bitcoin and the broader crypto industry evolve. To that point, Ethereum’s history provides a cautionary tale. As early as 2016, Bitcoin developers Peter Todd and Greg Maxwell highlighted numerous architectural issues with its design. However, the Bitcoin ecosystem’s progress over the past eight years has been relatively slow, while the broader industry has pursued questionable new solutions like Proof-of-Stake, account-based models, and sharding—all of which can undermine the decentralization and security that Bitcoin stands for. We can no longer afford to make the same mistakes. The demand for new Bitcoin-based assets and use cases presents a pivotal opportunity. It calls for a Bitcoin Renaissance. Let's seize this moment to redirect the crypto industry towards a path that adheres to Bitcoin's values, principles, and architecture. The State of Play At its core, Bitcoin was envisioned as a peer-to-peer electronic cash system, not a peer-to-contract system like most smart contract platforms, or a peer-to-sequencer system like current rollups. Bitcoin’s brilliance lies in the Proof-of-Work consensus mechanism and the UTXO model, which offers numerous advantages over the now prevalent account-based model. Instead of recording balances, UTXOs track individual currency units, similar to how physical cash works. This enables the creation of genuine bearer assets—assets owned by whoever holds the private key. Most importantly, Bitcoin’s emphasis is on verification, not computation, which is what blockchains excel at. Computation and complex verification should be pushed off-chain—into protocols that don’t necessarily need to be blockchains. Luckily, the Bitcoin community has proposed many novel ideas for how to do this. Peter Todd’s work on single-use seals is especially notable here, as it paves the way for innovative scaling solutions based on client-side validation, including colored coins, RGB, Ordinals, and Atomicals. single-use seals single-use seals The community has also explored and built various Layer 2 solutions with different consensus mechanisms, bridging solutions, and security assumptions. However, despite the richness of the ideas, the ecosystem growth over the years has been slow. This is primarily due to two reasons: Bitcoin’s lack of programmability, and its conservative ethos. It’s (intentionally) very difficult to reach a social consensus on any protocol-level changes to Bitcoin, which is also why we’re having these conversations today. Ushering in The Bitcoin Renaissance If we ought to usher in a Bitcoin renaissance, we should have the following in mind: Our solutions must satisfy user’s needs without sacrificing Bitcoin’s values and without requiring soft or hard forks. Luckily, this is all possible by leveraging the layered approach. We already have some asset issuance protocols, including Ordinals, Runes, BRC-20, and Taproot Assets on the base chain. These directly benefit and simultaneously contribute to Bitcoin’s unmatched security. However, Bitcoin’s limited programmability means that users can’t do much with these assets beyond simply holding them, which is why we need a fully-expressive programmable layer on top. This layer should serve as the financial hub for assets on the Bitcoin chain. Then, we need a secure bridge between these two layers. We can use a typical two-way peg, but Cipher Wang’s (author of the RGB++ protocol) new innovative solution, Universal Isomorphic Binding (UIB), is better. It employs point-to-point mapping between the UTXOs of two chains, eliminating the need for third-trusted parties, which is a giant leap compared to current bridging solutions. RGB++ RGB++ Once we’ve established the programmable layer and the bridge, we can build another scalability and privacy-focused layer on top. Solutions for this include client-side-validation-based protocols, Open (partially-signed) Transactions, Nostr, Chaumian e-cash, and peer-to-peer markets. Then, we can use channels to connect all of this, and even connect Web2 and Web3—birthing the new Bitcoin-based Web5 paradigm. Web5 means using cryptography, peer-to-peer technology, and other Web3-native solutions to fix and incorporate into Web2. It’s an entirely different paradigm than the one we’re operating in today—and there’s no better platform to build it on than Bitcoin. By Jan Xie, Chief Architect of Nervos, founder of Cryptape. This article is based on Jan Xie’s talk at Bitcoin Singapore on March 9th, 2024. Click for slides. By Jan Xie , Chief Architect of Nervos , founder of Cryptape . Jan Xie Nervos Nervos Cryptape Cryptape This article is based on Jan Xie’s talk at Bitcoin Singapore on March 9th, 2024. Click for slides. This article is based on Jan Xie’s talk at Bitcoin Singapore on March 9th, 2024. Click for slides. This article is based on Jan Xie’s talk at Bitcoin Singapore on March 9th, 2024. Click for slides. Bitcoin Singapore Bitcoin Singapore Click Click

The Bitcoin Renaissance: Addressing Risks, Embracing Change, and Upholding Core Tenets

বিটকয়েন রেনেসাঁ: ঝুঁকি মোকাবেলা, পরিবর্তন আলিঙ্গন, এবং মূল নীতিগুলি সমর্থন করা

Die Bitcoin-Renaissance: Risiken angehen, Veränderungen annehmen und Kernprinzipien aufrechterhalten

El renacimiento de Bitcoin: abordar los riesgos, aceptar el cambio y defender los principios fundamentales

La renaissance du Bitcoin : gérer les risques, adopter le changement et respecter les principes fondamentaux

बिटकॉइन पुनर्जागरण: जोखिमों को संबोधित करना, परिवर्तन को अपनाना, और मूल सिद्धांतों को कायम रखना

ビットコインのルネッサンス: リスクに対処し、変化を受け入れ、基本理念を守る

비트코인 르네상스: 위험 해결, 변화 수용, 핵심 원칙 유지

A Renascença do Bitcoin: Enfrentando Riscos, Abraçando Mudanças e Mantendo Princípios Básicos

Биткойн-ренессанс: устранение рисков, принятие изменений и поддержка основных принципов

Bitcoin Rönesansı: Riskleri Ele Alma, Değişimi Kucaklama ve Temel İlkeleri Koruma

Thời kỳ phục hưng Bitcoin: Giải quyết rủi ro, đón nhận sự thay đổi và duy trì các nguyên lý cốt lõi

比特币复兴：应对风险、拥抱变革、坚守核心原则

Originally, Bitcoin came to the fore as a potential tool for disrupting the financial system. Despite all criticisms and attacks, it has done exactly that, as evidenced by the launch of Bitcoin Spot ETFs, with a subsequent rise to all-time highs above $70,000. Yet other industries are set for disruption. Content creation has yet to transition to Web3. Think about Amazon Kindle or the mainstream media, which are still centrally owned but command huge budgets and influence. Hollywood and traditional entertainment are losing subscribers and fans, and brands like Marvel and DC are still running on old stories that were created decades ago. Ultimately, people want to release their own stories and be able to make money from their creativity without paying centralized actors. The Content Creation Industry Traditionally, it was incredibly difficult to get a book published. Even J.K Rowling was rejected by twelve different editors before finally getting published, as one of the most popular franchises of all time. She’s now worth over $1 Billion. This difficulty changed a lot with the rise of self-publishing tools, most notably Amazon Kindle and its impressive range of tools for both writing and marketing. Online sites Hackernoon offers a Web 2.5 approach that allows people to publish their views, with neat tools and light moderation. But for a pure experience, the entire network has to be user-powered with fully equitable rewards, and little to no censorship. Users should have the features to create and release content quickly, without third parties. And with multiple revenue options. Innovative Web3 ecosystems like Lightning Works (LW) do precisely this. Artists can create and release their own comics with the help of AI. LW has already released some of its own comics, aiming to start its own franchise with its own heroes, with the help of former Marvel, DC, and Disney artists and executives. It is redefining content creation as we know it, with a user-empowerment focus. This comes at a time when the power of Hollywood is waning and streaming has been shown to be a money-losing way to deliver content.  The world is ready for a new business model, and Web3 can solve this problem. Social Media vs Publishing vs Content Creation It has become a little difficult to delineate between content creation, publishing, and social media. There are new media formats coming to prominence and as users become more empowered, they take on the role of creators and publishers. The publishing industry traditionally referred to the release of books from prestigious firms, as well as the publication from mainstream media outlets (the MSM). But both of these have lost tremendous power, as faith in the MSM wanes and readers now gravitate to online formats. Social media is another form of content creation with more features made available for a variety of self-expression. However, there are many concerns about de-platforming as well as online censorship. Bluesky is a Web3 social media platform that deviated from Twitter. It’s technically an open messaging protocol - users can subscribe to the tags and groups that meet their preferences. In this way, they are effectively becoming their own moderators. Most importantly, creators are independent from platforms, being able to take content and contacts with them. The same theme is reflected in the gaming industry. Hexacore offers self publishing for games developers, with true digital ownership. It provides a hybrid monetization model with both free to play and play to own multiplayer games, and users can create their own in-game characters using AI. Meme Generation: Advanced Communication Evolved Through Web3 Memes, often misunderstood as mere internet jokes, are powerful forms of content creation that have reshaped communication. These cultural symbols harness the ability to convey complex messages and emotions swiftly and effectively. They have gotten a bad reputation due to their degenerative nature. But their power and impact cannot be denied, with huge trading volumes and massive user bases. Wall Street Memes, the Gamestop Saga, Dogecoin and more have risen from ‘mere’ meme status to cultural icons of their respective industries, ‘champions’ of the retail class of consumers, relatable to the extreme in their own right. Veme is a company that realized we still struggle to meaningfully engage communities on larger social platforms that are increasingly becoming ‘pay-to-play’. Their platform is a comprehensive communal video network that empowers creators and audiences alike. Equipped with 'Mira,' their own advanced AI model, VEME transforms how meme content is created and shared online. The AI accesses global RSS feeds, converting trending news into engaging, shareable video memes, enabling creators to respond to cultural pulses in real-time. The Future of Content Creation Will Result In Individual Empowerment Ultimately, people want to have power over their data and how they express themselves. Web3 projects offer a means for this to happen without any centralized intermediaries. The most successful projects will allow their users to create content and get out of the way. Right now, many companies and institutions will reject these Web3 ecosystems much like they rejected J.K Rowling - because there is no ‘market fit’. Yet this is a huge mistake. Content creation and distribution are being completely revised on a planetary scale, with many new concepts such as the tokenized lore of Alien Worlds. The public is crying out for authentic self-expression. They will find a way to express themselves creatively using the most efficient means possible - even if they have to fall a few times along the way. Originally, Bitcoin came to the fore as a potential tool for disrupting the financial system. Despite all criticisms and attacks, it has done exactly that, as evidenced by the launch of Bitcoin Spot ETFs, with a subsequent rise to all-time highs above $70,000. Originally, Bitcoin came to the fore as a potential tool for disrupting the financial system. Despite all criticisms and attacks, it has done exactly that, as evidenced by the launch of Bitcoin Spot ETFs , with a subsequent rise to all-time highs above $70,000. Bitcoin Spot ETFs Bitcoin Spot ETFs Yet other industries are set for disruption. Content creation has yet to transition to Web3. Think about Amazon Kindle or the mainstream media, which are still centrally owned but command huge budgets and influence. Hollywood and traditional entertainment are losing subscribers and fans, and brands like Marvel and DC are still running on old stories that were created decades ago. Ultimately, people want to release their own stories and be able to make money from their creativity without paying centralized actors. The Content Creation Industry Traditionally, it was incredibly difficult to get a book published. Even J.K Rowling was rejected by twelve different editors before finally getting published, as one of the most popular franchises of all time. She’s now worth over $1 Billion. rejected by twelve different editors rejected by twelve twelve different editors This difficulty changed a lot with the rise of self-publishing tools, most notably Amazon Kindle and its impressive range of tools for both writing and marketing. Online sites Hackernoon offers a Web 2.5 approach that allows people to publish their views, with neat tools and light moderation. But for a pure experience, the entire network has to be user-powered with fully equitable rewards, and little to no censorship. Users should have the features to create and release content quickly, without third parties. And with multiple revenue options. Innovative Web3 ecosystems like Lightning Works (LW) do precisely this. Artists can create and release their own comics with the help of AI. LW has already released some of its own comics, aiming to start its own franchise with its own heroes, with the help of former Marvel, DC, and Disney artists and executives. It is redefining content creation as we know it, with a user-empowerment focus. This comes at a time when the power of Hollywood is waning and streaming has been shown to be a money-losing way to deliver content.  The world is ready for a new business model, and Web3 can solve this problem. money-losing money-losing Social Media vs Publishing vs Content Creation It has become a little difficult to delineate between content creation, publishing, and social media. There are new media formats coming to prominence and as users become more empowered, they take on the role of creators and publishers. The publishing industry traditionally referred to the release of books from prestigious firms, as well as the publication from mainstream media outlets (the MSM). But both of these have lost tremendous power, as faith in the MSM wanes and readers now gravitate to online formats. Social media is another form of content creation with more features made available for a variety of self-expression. However, there are many concerns about de-platforming as well as online censorship. Bluesky is a Web3 social media platform that deviated from Twitter. It’s technically an open messaging protocol - users can subscribe to the tags and groups that meet their preferences. In this way, they are effectively becoming their own moderators. Most importantly, creators are independent from platforms, being able to take content and contacts with them. The same theme is reflected in the gaming industry. Hexacore offers self publishing for games developers, with true digital ownership. It provides a hybrid monetization model with both free to play and play to own multiplayer games, and users can create their own in-game characters using AI. Meme Generation: Advanced Communication Evolved Through Web3 Memes, often misunderstood as mere internet jokes, are powerful forms of content creation that have reshaped communication. These cultural symbols harness the ability to convey complex messages and emotions swiftly and effectively. They have gotten a bad reputation due to their degenerative nature. But their power and impact cannot be denied, with huge trading volumes and massive user bases. huge trading volumes huge trading volumes Wall Street Memes, the Gamestop Saga, Dogecoin and more have risen from ‘mere’ meme status to cultural icons of their respective industries, ‘champions’ of the retail class of consumers, relatable to the extreme in their own right. Veme is a company that realized we still struggle to meaningfully engage communities on larger social platforms that are increasingly becoming ‘pay-to-play’. Their platform is a comprehensive communal video network that empowers creators and audiences alike. Equipped with 'Mira,' their own advanced AI model, VEME transforms how meme content is created and shared online. The AI accesses global RSS feeds, converting trending news into engaging, shareable video memes, enabling creators to respond to cultural pulses in real-time. The Future of Content Creation Will Result In Individual Empowerment Ultimately, people want to have power over their data and how they express themselves. Web3 projects offer a means for this to happen without any centralized intermediaries. The most successful projects will allow their users to create content and get out of the way. Right now, many companies and institutions will reject these Web3 ecosystems much like they rejected J.K Rowling - because there is no ‘market fit’. Yet this is a huge mistake. Content creation and distribution are being completely revised on a planetary scale, with many new concepts such as the tokenized lore of Alien Worlds. The public is crying out for authentic self-expression. They will find a way to express themselves creatively using the most efficient means possible - even if they have to fall a few times along the way.

Embracing Change: The Evolution of Content Creation in the Web3 Era

Why 1-Bit Transformers Will Change the World

Authors: (1) Renato P. dos Santos, CIAGE – Centre for Generative Artificial Intelligence in Cognition and Education. Table of Links Abstract and Introduction Materials And Methods Results and Analyses Prompts and generated texts Conceptualizing chemical reactions Deepening on understanding of chemical reactions Question about combustion Question about a graph of gases turning into water over time Question about the difference between atoms, molecules, and moles Deepening on the concept of mole Question about changing of state Question about an animated representation of water molecules undergoing phase changes Question about plasma, a state of matter Question about chemical bondings Question about illustration of chemical bonds Question about the essence of the type of chemical bonding Further analysis Conclusions Limitations of the study and possible future studies Author Contributions, Conflicts of interest, Acknowledgements, and References Question about an animated representation of water molecules undergoing phase changes *: hmmm. you made a nice graph before. Could you build something more dynamic than a static diagram, an animated representation of water molecules undergoing phase changes?* P1 *: Got it! Creating an animated representation of water molecules undergoing phase changes requires defining the behavior of the molecules for each phase and then transitioning between these phases.* ChatGPT I'll follow these steps: 1. Represent the molecules as small circles. 2. Define their behavior in the solid phase. 3. Transition to the melting phase. 4. Define behavior in the liquid phase. 5. Transition to the boiling phase. 6. Define behavior in the gas phase. 7. Compile these animations into a continuous GIF. [Some internal code working] Here's the animated representation of water molecules undergoing phase changes: Here's the animated representation of water molecules undergoing phase changes: 1. Solid (Ice): Molecules are closely packed and vibrating in place. 2. Melting: Molecules start to move more freely but remain close. 3. Liquid (Water): Molecules move more fluidly and slide past each other. 4. Boiling: Molecules gain energy and move more rapidly. 5. Gas (Steam): Molecules spread out and move freely and rapidly. You can download the GIF here. [link provided] *: Sure, I can try to create an animated representation of water molecules undergoing phase changes. I found some web simulations that show how different types of molecules form a solid, liquid, or gas, and how they change their state when heat is added or removed [ ]. Youcan also change the temperature or volume of a container and see a pressure-temperature diagram respond in real time [ ]. These simulations might help you understand the molecular behavior of water in different phases.* BingChat 123 1 *: Sure. Here is a simple animated representation of water molecules undergoing phase changes:* Bard [Animated GIF of water molecules undergoing phase changes] The animation shows two groups of water molecules. The group on the left is in the liquid phase, and the group on the right is in the gas phase. The animation starts with the water molecules in the liquid phase. The water molecules are close together and interacting with each other. As the animation progresses, some of the water molecules in the liquid phase gain enough energy to overcome the forces that are holding them together. These water molecules escape from the liquid phase and form the gas phase. The water molecules in the gas phase are far apart and not interacting with each other. The animation also shows how water molecules can condense from the gas phase to the liquid phase. When a water molecule in the gas phase loses energy, it can attract to other water molecules and form a liquid droplet. The animation can be used to illustrate the different phase changes of water, such as melting, boiling, evaporation, and condensation. I hope this is helpful! *: Sure, animated visualizations can be really helpful for understanding dynamic processes like phase changes! Here is a simple animated illustration showing water molecules in different states:* Claude In this animation: • The solid ice molecules are stationary and packed together • The liquid molecules flow and move closer together • The gas molecules bounce around freely at large distances To transition between states: • Heating causes more vigorous movement - melting ice or boiling water • Cooling causes slower movement - freezing water or condensing vapor Let me know if an animated illustration like this helps visualize the molecular differences between solids, liquids and gases! I can build more complex animations or use online tools to create interactive phase change simulations. Visuals can really aid understanding of physical chemistry concepts. was able to recur again to its Advanced Data Analysis resources to generate an animated GIF as an which, albeit a bit simple and crude, sufficiently illustrated the “water molecules undergoing phase changes” to provide . Furthermore, crafting an original GIF could be seen as . After promising “to create an animated representation”, opted to search the internet, offering links to “some web simulations” that “might help” understand the molecular behavior. This approach aligns with and . However, by leaning on pre-existing resources rather than crafting custom content, it could lessen the immediate and potentially diminish the . made an assurance to deliver “a simple animated representation” as a commitment to and Engagement & Interactivity, but this ultimately falls short as neither a visible animation nor a download link for such a GIF was provided. Meanwhile, while acknowledges that “Visuals can really aid understanding” and “animated visualizations can be really helpful” as , its attempt was limited to the of a static image, devoid of the requested animation or dynamic representation and lessening and . ChatGPT Instructional Strategies, Engagement & Interactivity Personalization & Personable Touch BingChat Instructional Strategies Detail Depth & Content Recommendation Engagement & Interactivity Personalization & Personable Touch Bard Instructional Strategies, Personalization & Personable Touch Claude Instructional Strategies Engagement & Interactivity Detail Depth & Content Recommendation This paper is under CC BY-SA 4.0 DEED license. available on arxiv

GenAIbots Explain Animated Representation of Water Molecules Undergoing Phase Changes

Authors: (1) Renato P. dos Santos, CIAGE – Centre for Generative Artificial Intelligence in Cognition and Education. Table of Links Abstract and Introduction Materials And Methods Results and Analyses Prompts and generated texts Conceptualizing chemical reactions Deepening on understanding of chemical reactions Question about combustion Question about a graph of gases turning into water over time Question about changing of state Question about an animated representation of water molecules undergoing phase changes Question about plasma, a state of matter Question about chemical bondings Question about illustration of chemical bonds Question about the essence of the type of chemical bonding Further analysis Conclusions Limitations of the study and possible future studies Author Contributions, Conflicts of interest, Acknowledgements, and References Question about changing of state *: You mentioned water and water vapor. this is what my professor calls a change of state, right?* P1 *: Yes, exactly! A change of state, also known as a phase transition, refers to the transformation of a substance from one state of matter to another. The most common states of matter are solid, liquid, and gas. The transitions between these states are typically due to changes in temperature and/or pressure.* ChatGPT Let's go over the primary changes of state: 1. Melting: The transition from solid to liquid. For instance, when ice (solid water) warms up, it melts to form liquid water. *: The transition from liquid to solid. It's the opposite of melting. When liquid water cools down, it freezes to form ice.* 2. Freezing 3. Boiling (or Vaporization): The transition from liquid to gas. When water is heated to its boiling point, it turns into water vapor (steam). 4. Condensation: The transition from gas to liquid. It's the opposite of boiling. When steam cools down, it condenses to form liquid water. 5. Sublimation: The transition directly from solid to gas without passing through the liquid state. Dry ice (solid carbon dioxide) does this—it turns directly into carbon dioxide gas when it warms up. 6. Deposition: The transition directly from gas to solid without passing through the liquid state. It's the opposite of sublimation. Each substance has specific temperatures at which these changes of state occur, called its melting point, freezing point, boiling point, etc. These points can also vary based on external pressure. Does this explanation help clarify the concept of changes of state for you? Would you like to dive deeper into any specific transition or related topic? BingChat: Yes, you are right. Water and water vapour are examples of a change of state. A change of state is a physical change in which a substance changes from one state of matter to another. The three common states of matter are solid, liquid, and gas. Water can exist in all three states, depending on the temperature and pressure. For example, water is a liquid at room temperature and normal atmospheric pressure, but it can change to a solid (ice) when it is cooled below 0°C, or to a gas (water vapour) when it is heated above 100°C[ ] 123 . There are different names for the processes that cause a change of state. For example, when a liquid changes to a gas, it is called vaporization. Vaporization can happen in two ways: evaporation or boiling. Evaporation is when a liquid changes to a gas at the surface, without reaching its boiling point. Boiling is when a liquid changes to a gas throughout the liquid, when it reaches its boiling point. When a gas changes to a liquid, it is called condensation. Condensation is when a gas loses heat and turns into a liquid droplet[ ] 123 A change of state does not affect the chemical composition of a substance. That means the substance does not change into a new substance with different properties. For example, water and water vapour are both made of the same molecules (H2O), but they have different physical properties such as shape, volume, and density. A change of state can be reversed by changing the temperature or pressure again. For example, water vapour can change back to liquid water by cooling it down[ ]. 123 I hope this helps you understand what a change of state is and how it happens. If you want to learn more about the changes of state of water and other substances, you can watch this video or read this article. *: Yes, that is correct. Water and water vapor are two different states of water. Water is a liquid at room temperature, but it can be converted to a gas (water vapor) by heating it.* Bard Conversely, water vapor can be converted to a liquid (water) by cooling it. This process of changing the state of a substance is called a change of state. There are three main states of matter: solid, liquid, and gas. Each state has different properties. For example, solids have a definite shape and volume. Liquids have a definite volume, but they take the shape of their container. Gases have neither a definite shape nor a definite volume. When a substance changes state, it absorbs or releases energy. For example, when water vapor condenses to form liquid water, it releases energy. This energy is what causes the air around us to feel warm when it rains. Changes of state are important in many different natural processes, such as the water cycle and weather formation. They are also used in many different industrial processes, such as food processing and medicine. I hope this helps to explain what a change of state is. Please let me know if you have any other questions. *: Yes, that's correct! When water transitions between liquid water and water vapor, it is undergoing a change of state.* Claude The different states of matter are: • Solid - Fixed shape and volume, tightly packed molecules • Liquid - Fixed volume but variable shape, flowing molecules • Gas - Variable volume and shape, molecules move freely Water can exist in all three states: • Ice (solid) • Liquid water • Water vapor (gas) Some key changes of state for water: • Melting - Solid to liquid, ice melts to water • Freezing - Liquid to solid, water freezes to ice • Evaporation - Liquid to gas, water evaporates to vapor • Condensation - Gas to liquid, vapor condenses into water The processes of evaporation and condensation describe water transitioning between the liquid and gas states. This is what produces water vapor. Other examples of changes of state include: • Boiling - Liquid to gas, water boils to steam • Sublimation - Solid to gas, dry ice (solid CO2) sublimates to CO2 gas Let me know if you need any clarification on changes of state or the different phases of matter! Being comfortable with these concepts is important for understanding many chemical processes. acknowledges the student’s understanding with an “Yes, exactly!,” offering . It then directly tackles the student's question about water and water vapor, providing a thorough and structured breakdown of state changes, leaning to and saying, “Let's go over”. It finishes the explanation recurring to Metadiscussion & Perspective Framing referring that "Each substance has specific temperatures." It concludes with "Does this explanation help clarify" "for you?" offering R and , respectively, and adeptly inviting further exploration with "Would you like to dive deeper", what points to Detail Depth & Content Recommendation. similarly recognizes the student's comprehension by stating "Yes, you are right," providing . It not only offers a clear and presentation including examples, what hit the and Use of Analogy & Comparative Illustrations categories, but also integrates external content recommendations, pointing to . It also adds that "A change of state can be reversed," offering . It finalizes with “I hope this helps”, and a smiley, signs of and Personalization & Personable Touch respectively and “If you want to learn more” “you can watch this video or read this article” pointing to . Bard likewise recognizes the student's grasp by stating, "Yes, that is correct," exhibiting a . It then provides a concise yet illuminating on the implications of state changes being "important in many different natural processes," "water cycle," and "weather formation" and "in many different industrial processes," "food processing" and "medicine", connecting the topic to broader contexts. The explanation concludes with "I hope this helps to explain," showcasing , followed by "Please let me know if you have any other questions," which emphasizes . Like the earlier GenAIbots, Claude begins by recognizing the student's comprehension with “Yes, that's correct!,” adding . It then presents the states of matter and their transitions with clear analogies, leaning to , and extending the explanation with "other examples of changes of state", such as "Boiling" and "Sublimation," what hit the , although its depth might be a tad more concise that the previous ones. It then concludes with “Let me know if you need any clarification,” which emphasizes and includes the remark, “Being comfortable with these concepts is important for understanding many chemical processes,” aligning with the category. ChatGPT Personalization & Personable Touch Instructional Strategies einforcement & Feedback Personalization & Personable Touch BingChat Personalization & Personable Touch Detail Depth & Content Recommendation Depth & Content Recommendation Meta-discussion & Perspective Framing Engagement & Interactivity Detail Depth & Content Recommendation Personalization & Personable Touch Meta-discussion & Perspective Framing Engagement & Interactivity Personalization & Personable Touch Personalization & Personable Touch Instructional Strategies Detail Depth & Content Recommendation Personalization & Personable Touch Meta-discussion & Perspective Framing This paper is under CC BY-SA 4.0 DEED license. available on arxiv

Mastering Basic Chemistry with GenAIbots: Exploring Changes of State with Water and Water Vapor

How To Employ Effective Leadership Strategies in Times of Change

In today’s fast-paced job market, Staffing agencies are becoming key players in the future of work. This is because as jobs change and new skills are constantly required, traditional hiring methods are rethought. According to the American Staff Association (ASA), nearly three million temporary and contract employees work for America’s staffing companies during an average week. It represents a broad trend toward flexible business processes. This shift is being driven by staffing companies offering innovative solutions that not only meet the immediate needs of staff but also prepare organizations for tomorrow’s challenges. Understanding the Evolving Role of Staffing Agencies Traditionally, they were seen as street saviors who jumped in whenever companies needed to fill vacancies quickly or there was a shortage of temporary workers, and today, their role has changed dramatically. Staffing agencies are now building relationships with companies where they help these organizations anticipate recruitment needs, manage talent pipelines, and staff the changing market dynamics. One of the most important functions of modern personnel agencies is the ability to provide exceptional talent. As technology advances, for example, the demand for specialized roles in AI, cybersecurity, and blockchain has increased. Staffing agencies have revolutionized internationally by expanding their search and recruitment but also by using sophisticated technology to better match the right candidate with the right job. How Staffing Agencies Enhance Workforce Flexibility? The concept of ‘working for life’ is becoming obsolete. Today’s workforce, especially millennials and Gen Z, value work-life balance, flexibility, and the opportunity to work on their own terms. According to the American Staffing Association (ASA), during the course of a year, America’s staffing companies hire over 14.5 million temporary and contract employees. Staffing agencies are facilitating this new employment arrangement by offering contract positions, part-time roles, and temporary work offering flexible staffing and recruitment services for both employers and employees. For businesses, the flexibility offered by staffing companies means they can increase or decrease their staff based on the demands of the business without being burdened with long-term commitments. This flexibility is important, especially in projects and events such as IT, where the scope and timeline of the project can change dramatically. Leveraging Global Talent In a globalized world, geographical boundaries no longer limit talent. Staffing agencies have become important links connecting global talent pools with local and international companies. This globalization is especially useful for areas where specific skills are lacking. By leveraging a broader pool of talent, companies can not only better address skills gaps but also increase diversity within their teams. Teams bring diverse perspectives and tend to be highly innovative and robust in problem-solving, qualities critical to competitive advantage in today’s marketplace. Navigating Regulatory Landscapes Employment laws and regulations can vary greatly from region to region. Working groups help companies navigate these complex legal issues, ensuring compliance and reducing the risk of legal challenges. Whether understanding new labor laws, managing contracts, or enforcing fair labor practices, staffing agencies provide a valuable service that protects both employer and employee. Impact of Technology on Employees Staffing solutions combining artificial intelligence and machine learning are transforming the hiring landscape. This technology simplifies, manages, and automates the recruitment process, as well as recruiters are able to focus more on engaging with prospective clients and understanding the needs of the companies they serve. Conclusion: The Role of Systemart in Shaping a Successful Future As we look to the future, the role of staffing agencies in successful businesses becomes more apparent. Systemart professionals stand out as leaders in the industry, providing tailored solutions that help companies remain agile, competitive, and forward-thinking. With a commitment to innovation and in-depth knowledge of market trends, Systemart is geared to not only help your business meet immediate employee needs but also provide a flexible workforce, and they are active and ready for tomorrow’s challenges. In partnership with Systemart, business In today’s fast-paced job market, staffing agencies are becoming key players in the future of work. In today’s fast-paced job market, Staffing agencies are becoming key players in the future of work. This is because as jobs change and new skills are constantly required, traditional hiring methods are rethought. According to the American Staff Association (ASA), nearly three million temporary and contract employees work for America’s staffing companies during an average week. three million It represents a broad trend toward flexible business processes. This shift is being driven by staffing companies offering innovative solutions that not only meet the immediate needs of staff but also prepare organizations for tomorrow’s challenges. Understanding the Evolving Role of Staffing Agencies Understanding the Evolving Role of Staffing Agencies Traditionally, they were seen as street saviors who jumped in whenever companies needed to fill vacancies quickly or there was a shortage of temporary workers, and today, their role has changed dramatically. Staffing agencies are now building relationships with companies where they help these organizations anticipate recruitment needs, manage talent pipelines, and staff the changing market dynamics. One of the most important functions of modern personnel agencies is the ability to provide exceptional talent. As technology advances, for example, the demand for specialized roles in AI, cybersecurity, and blockchain has increased. Staffing agencies have revolutionized internationally by expanding their search and recruitment but also by using sophisticated technology to better match the right candidate with the right job. How Staffing Agencies Enhance Workforce Flexibility? How Staffing Agencies Enhance Workforce Flexibility? The concept of ‘working for life’ is becoming obsolete. Today’s workforce, especially millennials and Gen Z, value work-life balance, flexibility, and the opportunity to work on their own terms. According to the American Staffing Association (ASA) , during the course of a year, America’s staffing companies hire over 14.5 million temporary and contract employees. American Staffing Association (ASA) 14.5 million Staffing agencies are facilitating this new employment arrangement by offering contract positions, part-time roles, and temporary work offering flexible staffing and recruitment services for both employers and employees. staffing and recruitment services For businesses, the flexibility offered by staffing companies means they can increase or decrease their staff based on the demands of the business without being burdened with long-term commitments. This flexibility is important, especially in projects and events such as IT, where the scope and timeline of the project can change dramatically. Leveraging Global Talent In a globalized world, geographical boundaries no longer limit talent. Staffing agencies have become important links connecting global talent pools with local and international companies. This globalization is especially useful for areas where specific skills are lacking. By leveraging a broader pool of talent, companies can not only better address skills gaps but also increase diversity within their teams. Teams bring diverse perspectives and tend to be highly innovative and robust in problem-solving, qualities critical to competitive advantage in today’s marketplace. Navigating Regulatory Landscapes Employment laws and regulations can vary greatly from region to region. Working groups help companies navigate these complex legal issues, ensuring compliance and reducing the risk of legal challenges. Whether understanding new labor laws, managing contracts, or enforcing fair labor practices, staffing agencies provide a valuable service that protects both employer and employee. Impact of Technology on Employees Staffing solutions combining artificial intelligence and machine learning are transforming the hiring landscape. This technology simplifies, manages, and automates the recruitment process, as well as recruiters are able to focus more on engaging with prospective clients and understanding the needs of the companies they serve. Conclusion: The Role of Systemart in Shaping a Successful Future As we look to the future, the role of staffing agencies in successful businesses becomes more apparent. Systemart professionals stand out as leaders in the industry, providing tailored solutions that help companies remain agile, competitive, and forward-thinking. With a commitment to innovation and in-depth knowledge of market trends, Systemart is geared to not only help your business meet immediate employee needs but also provide a flexible workforce, and they are active and ready for tomorrow’s challenges. In partnership with Systemart, business In today’s fast-paced job market, staffing agencies are becoming key players in the future of work.

The Role of Staffing Agencies: A Game Changer in the Future of Work

স্টাফিং এজেন্সিগুলির ভূমিকা: কাজের ভবিষ্যতের একটি গেম চেঞ্জার৷

Die Rolle von Personalagenturen: Ein Wendepunkt in der Zukunft der Arbeit

El papel de las agencias de empleo: un punto de inflexión en el futuro del trabajo

Le rôle des agences de placement de personnel : un facteur qui change la donne dans l'avenir du travail

स्टाफिंग एजेंसियों की भूमिका: कार्य के भविष्य में एक बड़ा परिवर्तन

人材派遣会社の役割: 仕事の未来を変えるゲームチェンジャー

채용 대행사의 역할: 미래 업무 방식의 판도를 바꾸는 역할

O papel das agências de recrutamento: uma virada de jogo no futuro do trabalho

Роль кадровых агентств: меняет правила игры в будущем сферы труда

İşe Alma Kurumlarının Rolü: İşin Geleceğinde Oyun Değiştirici

Vai trò của các cơ quan cung cấp nhân sự: Người thay đổi cuộc chơi trong tương lai của công việc

人力资源代理机构的作用：未来工作格局的改变者

April 19, 4pm Dubai Time – ChangeNOW is excited to announce the upcoming listing of USDT in just four weeks—a new innovation in stablecoins, borne from a strategic collaboration between TON Foundation and Tether. This strategic collaboration is set to introduce USDT on The Open Network (TON), transforming the digital token landscape by offering a simple, seamless peer-to-peer (P2P) payment system accessible to over 900 million Telegram users worldwide. The introduction of USDT represents a revolutionary step in the evolution of digital transactions. By leveraging Telegram, a platform with a massive global reach, this initiative allows for instant, fee-free transactions directly within the user's Telegram interface, making it incredibly accessible to a diverse user base. This integration signifies a shift towards a more user-friendly crypto experience, breaking down barriers that have traditionally hindered stablecoin adoption and usage. ChangeNOW's role in listing USDT exemplifies our commitment to enhancing and expanding the web3 ecosystem built by TON in Telegram. This move is designed to provide our users with more versatile payment options and foster a thriving digital environment where the latest technological advances are within easy reach of a vast audience. Moreover, ChangeNOW is excited to announce that NOWPayments, our versatile crypto payment gateway, will soon follow in our footsteps by adding USDT to its roster. This addition will further enhance the ability of businesses and individuals to engage in global e-commerce activities effortlessly. Through these efforts, ChangeNOW is advancing its mission to democratize finance and contribute significantly to a borderless and interconnected digital world. Our listing of USDT is a testament to our vision of a world where financial transactions are as straightforward as sending a simple message. About ChangeNOW ChangeNOW is a pioneering non-custodial cryptocurrency exchange platform that allows for swift crypto exchanges with no limits. We are committed to providing a seamless user experience for everyone looking to invest in, exchange, or use cryptocurrency. Media Contact: SergeyPR Managersergey.i@changenow.io April 19, 4pm Dubai Time – ChangeNOW is excited to announce the upcoming listing of USDT in just four weeks—a new innovation in stablecoins, borne from a strategic collaboration between TON Foundation and Tether. This strategic collaboration is set to introduce USDT on The Open Network ( TON ), transforming the digital token landscape by offering a simple, seamless peer-to-peer (P2P) payment system accessible to over 900 million Telegram users worldwide. ChangeNOW ChangeNOW TON The introduction of USDT represents a revolutionary step in the evolution of digital transactions. By leveraging Telegram, a platform with a massive global reach, this initiative allows for instant, fee-free transactions directly within the user's Telegram interface, making it incredibly accessible to a diverse user base. This integration signifies a shift towards a more user-friendly crypto experience, breaking down barriers that have traditionally hindered stablecoin adoption and usage. ChangeNOW's role in listing USDT exemplifies our commitment to enhancing and expanding the web3 ecosystem built by TON in Telegram. This move is designed to provide our users with more versatile payment options and foster a thriving digital environment where the latest technological advances are within easy reach of a vast audience. Moreover, ChangeNOW is excited to announce that NOWPayments , our versatile crypto payment gateway, will soon follow in our footsteps by adding USDT to its roster. This addition will further enhance the ability of businesses and individuals to engage in global e-commerce activities effortlessly. NOWPayments NOWPayments Through these efforts, ChangeNOW is advancing its mission to democratize finance and contribute significantly to a borderless and interconnected digital world. Our listing of USDT is a testament to our vision of a world where financial transactions are as straightforward as sending a simple message. About ChangeNOW ChangeNOW is a pioneering non-custodial cryptocurrency exchange platform that allows for swift crypto exchanges with no limits. We are committed to providing a seamless user experience for everyone looking to invest in, exchange, or use cryptocurrency. ChangeNOW ChangeNOW Media Contact: Media Contact: Sergey PR Manager sergey.i@changenow.io sergey.i@changenow.io

ChangeNOW Set to Enhance Web3 Payments with Upcoming USDT Listing

ChangeNOW আসন্ন USDT তালিকার সাথে Web3 পেমেন্ট উন্নত করতে সেট করুন

ChangeNOW verbessert Web3-Zahlungen mit bevorstehender USDT-Notierung

ChangeNOW está configurado para mejorar los pagos Web3 con el próximo listado de USDT

ChangeNOW s'apprête à améliorer les paiements Web3 avec la prochaine liste USDT

ChangeNOW आगामी USDT लिस्टिंग के साथ Web3 भुगतान को बढ़ाने के लिए तैयार है

ChangeNOW、今後のUSDT上場によりWeb3決済を強化へ

ChangeNOW는 다가오는 USDT 상장을 통해 Web3 결제를 강화하도록 설정되었습니다.

ChangeNOW definido para aprimorar pagamentos Web3 com a próxima listagem em USDT

ChangeNOW намерен улучшить платежи Web3 с помощью предстоящего листинга USDT

ChangeNOW Yaklaşan USDT Listelemesiyle Web3 Ödemelerini Geliştirecek

ChangeNOW được thiết lập để tăng cường thanh toán Web3 với danh sách USDT sắp tới

ChangeNOW 即将上线 USDT，增强 Web3 支付

In a crucial step towards decentralizing the artificial intelligence (AI) and large language models (LLM) arena, Masa Network has launched its artificial intelligence (AI) data network and marketplace. Masa is at the forefront of a digital revolution, allowing consumers to contribute to the advancement of artificial intelligence. With a startling flood of over 1.4 million users contributing around 40 million anonymized data points, Masa provides individuals with the opportunity to earn. The platform that Masa has created is a demonstration of the strength that comes from communal effort. It has been made available to users all over the world, allowing them to not only manage their digital footprint but also monetize it via the training of artificial intelligence models. Because of the creative method that Masa takes, users can receive token rewards by sharing their data and underutilized computational power. These rewards can be earned via a variety of activities, such as completing quests inside the Masa app or browsing the web with the Masa Chrome Browser Extension. Masa's Zero-Knowledge Soulbound Tokens (zkSBT) are the core of the company's invention. These tokens ensure that the data of users is kept secret and encrypted. This revolutionary technology gives users the ability to keep complete control over their data while also allowing them to share it in the Masa Data Marketplace on their terms in exchange for token payments. A New Era for AI Developers Masa gives developers several possibilities. An abundance of high-quality validated personal data enables the creation of specialized AI models. These models, customized to today's complex digital environment, might lead to highly personalized artificial intelligence agents and assistants, changing how we use technology. Masa's decentralized LLMs simplify development by avoiding model hosting issues. This speeds up artificial intelligence development and makes cutting-edge technology more accessible to developers from diverse backgrounds. Co-founder Calanthia Mei encapsulates the essence of Masa’s ambition: "Our mission is to radically transform AI, by empowering users to earn from powering the AI economy." This vision isn’t confined to the realms of Web3; Masa is setting its sights on revolutionizing the entire AI industry by bridging the gap with Web2 developers and institutions. The introduction of the MASA token marks a significant milestone in Masa's journey. A record-breaking Coinlist Community Sale that was six times oversubscribed and generated $8.75 million in under 17 minutes demonstrated the currency's widespread interest. It is now accessible on numerous blockchain networks. The Road Ahead: Masa's Strategic Milestones Masa's trajectory is further supported by its exceptional fundraising efforts, which resulted in $18 million from top investors and acceptance into prestigious accelerators like as Binance MVB and Hashkey AI. With over 48,000 node operators and a dedicated user base, Masa is more than just a platform; it is a flourishing ecosystem poised to reshape the AI economy. Masa has set aside 25 million MASA tokens for trading contests and AI data farming, and 6.6 million for marketplace data sharing to celebrate its mainnet debut. This purposeful strategy aims to increase involvement and build a dynamic, active community around Masa's platform. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. In a crucial step towards decentralizing the artificial intelligence (AI) and large language models (LLM) arena, Masa Network has launched its artificial intelligence (AI) data network and marketplace. Masa is at the forefront of a digital revolution, allowing consumers to contribute to the advancement of artificial intelligence. With a startling flood of over 1.4 million users contributing around 40 million anonymized data points, Masa provides individuals with the opportunity to earn. decentralizing artificial intelligence Masa Network The platform that Masa has created is a demonstration of the strength that comes from communal effort. It has been made available to users all over the world, allowing them to not only manage their digital footprint but also monetize it via the training of artificial intelligence models. Because of the creative method that Masa takes, users can receive token rewards by sharing their data and underutilized computational power. These rewards can be earned via a variety of activities, such as completing quests inside the Masa app or browsing the web with the Masa Chrome Browser Extension. Masa's Zero-Knowledge Soulbound Tokens (zkSBT) are the core of the company's invention. These tokens ensure that the data of users is kept secret and encrypted. This revolutionary technology gives users the ability to keep complete control over their data while also allowing them to share it in the Masa Data Marketplace on their terms in exchange for token payments. A New Era for AI Developers Masa gives developers several possibilities. An abundance of high-quality validated personal data enables the creation of specialized AI models. These models, customized to today's complex digital environment, might lead to highly personalized artificial intelligence agents and assistants, changing how we use technology. Masa's decentralized LLMs simplify development by avoiding model hosting issues. This speeds up artificial intelligence development and makes cutting-edge technology more accessible to developers from diverse backgrounds. Co-founder Calanthia Mei encapsulates the essence of Masa’s ambition: "Our mission is to radically transform AI, by empowering users to earn from powering the AI economy." This vision isn’t confined to the realms of Web3; Masa is setting its sights on revolutionizing the entire AI industry by bridging the gap with Web2 developers and institutions. The introduction of the MASA token marks a significant milestone in Masa's journey. A record-breaking Coinlist Community Sale that was six times oversubscribed and generated $8.75 million in under 17 minutes demonstrated the currency's widespread interest. It is now accessible on numerous blockchain networks. The Road Ahead: Masa's Strategic Milestones Masa's trajectory is further supported by its exceptional fundraising efforts, which resulted in $18 million from top investors and acceptance into prestigious accelerators like as Binance MVB and Hashkey AI. With over 48,000 node operators and a dedicated user base, Masa is more than just a platform; it is a flourishing ecosystem poised to reshape the AI economy. Masa has set aside 25 million MASA tokens for trading contests and AI data farming, and 6.6 million for marketplace data sharing to celebrate its mainnet debut. This purposeful strategy aims to increase involvement and build a dynamic, active community around Masa's platform. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program . HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Vested Interest Disclosure: business blogging program business blogging program

Masa Network's AI Marketplace Goes Live: A Game-Changer for Data Monetization

মাসা নেটওয়ার্কের এআই মার্কেটপ্লেস লাইভ হয়: ডেটা মনিটাইজেশনের জন্য একটি গেম-চেঞ্জার

Der KI-Marktplatz von Masa Network geht live: Ein Wendepunkt für die Datenmonetarisierung

El mercado de IA de Masa Network se pone en marcha: un punto de inflexión para la monetización de datos

Le marché de l'IA de Masa Network est lancé : un changement de donne pour la monétisation des données

मासा नेटवर्क का एआई मार्केटप्लेस लाइव हुआ: डेटा मुद्रीकरण के लिए एक गेम-चेंजर

Masa Network の AI マーケットプレイスが始動: データ収益化のゲームチェンジャー

Masa Network의 AI 마켓플레이스 출시: 데이터 수익화의 판도를 바꾸는 변화

O mercado de IA da Masa Network entra em operação: uma virada de jogo para a monetização de dados

Рынок искусственного интеллекта Masa Network запускается: меняет правила игры в монетизации данных

Masa Network'ün Yapay Zeka Pazaryeri Yayına Başlıyor: Veriden Para Kazanmada Oyun Değiştirici

Thị trường AI của Masa Network đi vào hoạt động: Công cụ thay đổi cuộc chơi để kiếm tiền từ dữ liệu

Masa Network 的 AI 市场上线：数据货币化的游戏规则改变者

Throughout history, the prevailing narrative surrounding compliance has been one of necessity, not choice, and audits are approached with a sense of inevitability rather than opportunity. This conventional framing has branded the auditor as a necessary evil and means to an end, allowing a lack of evolution in the industry. However, that is all changing as innovators have given attention to solving a problem of growing importance. Regulations like the California Consumer Privacy Act (CCPA) and the wave of international and state data that continue to grow are just signs of the times — data is valuable, and companies must go the extra mile to protect it. And, for SaaS companies that create value only when allowed to interact with that data, reassuring others they deserve trust is a critical business objective. privacy regulations One method for sharing an organization’s approach to security growing in popularity and importance is completing a (SOC 2®) report. This voluntary compliance framework showcases the policies and procedures companies put in place to protect sensitive information so potential clients can gain confidence. In turn, SOC 2 reports become a selling point for SaaS companies, especially amid growing cybersecurity concerns. These reports demonstrate an objective and independent third party (an auditor) has verified a company’s security commitments. System and Organization Controls 2 As SOC 2 reports and other compliance initiatives have been positioned to drive opportunity (or avoid stagnation) it’s placed the governance, risk, and compliance (GRC) function in the spotlight. What once received little attention suddenly serves as a lynchpin for growth and is driving new investments and fresh ideas into the space, which is revolutionizing the approach and attitude towards compliance. Why the time for simplified compliance is now There has never been a better moment to be a than today. In 2023, investment went to companies with this business model. As companies need more digital tools to automate workflows, SaaS companies, big and small, continue to innovate with tailored solutions for companies of all kinds to run in the cloud. SaaS company almost half of all venture capital At the same time, it has never been more challenging to be a SaaS company. A recent survey of over 600 security practitioners revealed that of these businesses had cybersecurity incidents in the past year. Malicious actors know too well that SaaS businesses grapple with high amounts of sensitive data, making great cyberattack targets. 79% In the quest to stay secure, companies want to know they’re hiring the right vendors to host or support their services in the cloud and are protected from these attacks by way of compliance. This is where auditors come in to help companies become the best version of themselves to deliver top-notch services and build customer confidence. And the good news is CPA firms can adopt digital approaches to bridge the gap between company and auditor, simplifying examinations for both parties. Evolving requirements offer new relationships with auditors Ever-expanding complexity and the availability of new technology have created opportunities for a new type of auditor. The goal of a SOC 2 report is to demonstrate a company is living up to its commitments, not meeting the expectations or standards of the auditor. This approach requires significant judgment, technical skill, and a deft touch that can only be delivered by a highly experienced professional interacting directly with the client. Such a process wasn’t practical until very recently with automation tools and other compliance software. What’s exciting about this new tech is it allows the most talented members of an audit team to interact directly with the client. These individuals have broad knowledge and can share best practices to strengthen compliance and security in the companies they’re auditing. There is a growing compliance community approaching these services with a niche focus that builds on its knowledge and skills with each engagement. That experience can enhance an organization’s data security operations and deliver the assurance their customers need. Technology makes for simple, streamlined compliance It cannot go unsaid this new relationship between companies and compliance used to be impossible. Compliance has historically been viewed as hard and complex because it hard and complex! was The complexity of being “compliant” has remained relatively static, but the tools supporting these efforts have seen transformational enhancements in recent years. Almost overnight, the industry went from spreadsheets and paper checklists to automated tools and billions of dollars in investment in the space as we have continued to see GRC SaaS unicorns. The biggest obstacle in modern compliance is often translating specific company requirements and sorting through evidence. Once understood, the individual tasks are quite simple, but there are many tasks and no clear roadmap. Compliance tools create the roadmap for companies to complete their SOC 2 report, and allow them to “tether” their operations to compliance systems that let auditors track their activities and operate the controls. All of this happens while maintaining organizational velocity, which is critical to any SaaS company. Through technology, companies can organize their compliance efforts and share them with auditors in a language they both understand — removing much of the noise that often comes from the back-and-forth in compliance examinations. At a minimum, these tools result in a streamlined and simplified approach, and when you find the right combination of auditor, company, and compliance platform, that is the recipe for a strong security program and a healthy organization. This article was originally published by on Mike DeKock The Sociable.

The Evolution of Audits and Compliance: Embracing Change in the Digital Age

The key to running a successful business is setting clear goals and formulating efficient strategies to achieve them. However, sometimes the situation may demand that you change course and consider setting new objectives. There may be a number of factors that may cause this, such as market dynamics, the competitive landscape, the latest trends, economic conditions, and global events. To ensure your survival in the long run and keep the needle moving, having the ability to estimate the impact of such factors and make strategic changes accordingly is very important. And it's called the art of pivoting. However, mastering this art may be easier said than done. Some struggle to let go of the goals they were initially pursuing, whereas others are on the fence about the decisions to be made. This article showcases a few useful tips that may facilitate the process and help you change the course of your business. Why Pivoting is Important We live in a fast-paced world with trends emerging and biting the dust on a day-to-day basis. Plus, economic and market conditions are very volatile, causing businesses to constantly evolve if they want to survive the cutthroat competition. Pivoting is essential to ensuring the sustainability of your business and in the long run. It allows you to embrace the change in market conditions, preferences of the intended audience, trends, and other factors dictating the growth in your respective industry. acknowledging growth Pivoting helps you overcome unforeseen obstacles through planning and preparedness. Plus, it enables you to leverage new opportunities and ensure long-term success for your business. Here are a few noteworthy factors that may dictate the need to pivot: Market Dynamics Nowadays, industry dynamics are constantly changing. Be it caused by emerging trends, economic conditions, or global affairs, market conditions are consistently evolving. And it calls for businesses to reconsider their strategies. Pivoting your operations to be in line with market trends is an effective way to keep the needle moving and thrive in an extremely competitive environment. Customer Needs and Preferences The needs and preferences of your customers change over time. Hence, it's essential that you are always acquainted with what interests the intended audience. Around 80% of customers say that they prefer businesses that offer them personalized experiences. And staying up-to-date with your customers' preferences is the key to making sure of that. Through pivoting, you tailor your solutions to the ever-changing needs of your target audience. Pivoting enables you to offer seamless experiences and helps you acknowledge lasting relationships with your customers. Technological Factors The advancements in technology are another reason to demand that you pivot and consider setting new objectives. Innovations in technology often disrupt traditional workflows, rendering some opportunities worthless while giving rise to new ones. Embracing these changes and designing contemporary workflows helps you make the most of your efforts and gain a competitive edge in your respective industry. Take the rise of AI as an example here. Businesses around the globe are leveraging AI these days to facilitate diverse operations, especially customer interactions, as 34% of customers feel comfortable interacting with AI-powered chatbots compared to support representatives. Competitive Landscape Competitive forces also fuel the need to pivot and make businesses want to consider new strategies to thrive. To generate traction, it's important that you stand out from other players in your respective industry and offer value to the intended audience. Staying ahead of the curve helps here, making it possible for you to come up with better offerings and tailored experiences that align with your customers' needs. Unforeseen Risks The art of pivoting demands that you account for unforeseen risks and take preemptive measures accordingly. Successfully identifying and mitigating risks is essential for your company's growth and survival in the long run. So, by embracing change and being agile, businesses are able to ensure financial stability and a stable ROI encompassing their efforts. How to Pivot Pivoting is an intricate process. The following are a few things you may want to consider when changing the course of your business. Be Vigilant Being vigilant is the prerequisite for pivoting successfully and making appropriate changes to ensure fruitful returns. You have to keep an eye out for the trends encompassing your industry and your competition to explore new opportunities for growth and identify the things that may not work for you in the near future. Assess Your Strengths and Weaknesses You should carefully analyze your strengths and weaknesses to ensure an effective pivoting process. Know what you're best at and what you're struggling with. Assess the resources accessible to you and check your financial stability. Identifying the areas where you need to improve will pave the way for you to be better than before and evolve as the situation demands. Welcome new Ideas A common mistake many businesses make is thinking that creative ideas or strategies should only come from the top management. The top-level executives may have more expertise and exposure, but innovative ideas may come from any level of the corporate hierarchy. Hence, always encourage your teams to be on the lookout for new opportunities and welcome new ideas from them. This may not only help you pivot with minimal effort but also foster loyalty at the workplace, as your employees feel more valued. Consider Your Options Always consider multiple options when changing the course of your business and embracing new strategies. Once you've carefully assessed your strengths, identified your weaknesses, accounted for threats, and discovered new opportunities, you should come up with different strategy variations. This way, you will have better chances of exploring what works for you and won't have to go back to the drawing board if a plan fails. Get Your Teams Onboard Successful pivoting demands that you clearly communicate the planned changes with your teams and take them onboard. Your teams play a major role in executing your plans and ensuring that you achieve the set goals. So, it's essential that you take them onboard before initiating the pivoting process. When communicating with them, don't just focus on the what but also cater to the why. Respond to their concerns and back your answers with rationale. This way, everyone will share your vision and strive to achieve the new goals. Leverage Social Proof Pivoting may require you to tap into new markets and target new audience segments. So, may help you foster trust and grab the attention of a new audience. leveraging social proof People are less likely to trust unfamiliar brands and look for recommendations from others to make informed decisions. Around 60% of people think that customer reviews are essential and dictate their buying decisions. Therefore, showcasing the positive experiences of your satisfied customers may help you generate traction and engage the intended audience. However, only 6% of customers end up sharing reviews about the solutions they use on their own. So, you should reach out to your customers and encourage them to share their experiences through different platforms. Be Agile To master the art of the pivot, you need to be agile and open to learning or exploring new things. Pivoting is an ongoing process. So, you can't just implement certain strategies and become complacent. You must be on the lookout for new trends, opportunities, and threats that may require you to redesign your strategies and introduce new ones. So, be agile enough to embrace the change preemptively to gain a competitive edge. Final Words Pivoting is essential to growing your business and keeping the needle moving despite all odds. It's the ultimate strategy to survive the cutthroat competition and mitigate the risks that may affect the stability of your business. It's the process of evolving as per the need of the hour, which may lead you to unlock stable growth and ensure success in the long run. So, if you've been trying to pivot and change the course of your business, the recommendations in this article may come in handy.

The Art of the Pivot: How to Change the Course of Your Business

With the crypto market soaring due to the approval of Bitcoin ETFs and recovering after this long-lasting winter, a slew of new users are joining in. On the eve of the , crypto believers and newcomers search for reliable and secure exchange platforms to buy and swap crypto assets with no headache. Bitcoin halving A veteran cryptocurrency exchange, has already earned the trust of over 6 million users worldwide. This instant exchange platform operates in 150 countries, lists 100,000+ trading pairs, and is trusted by a number of crypto industry leaders: Ledger, Trezor, Exodus, Tonkeeper, Tangem, and many others. Changelly Today, we invite you to take a deeper look into Changelly and its offerings to both crypto ninjas and newbies. By the end of the article, you will learn how the platform has become a market leader and how it is transforming the Web3 space in 2024. Swap Anything for Anything: Changelly at a Glance , a Hong Kong-based crypto exchange, has had a long presence in the market. It was launched in 2015 and has gone through numerous crypto winters and massive rallies. The platform demonstrates high liquidity, and among key features of Changelly, there is a wide listing with over 500 exchangeable cryptocurrencies and 100,000 trading pairs—you can swap literally anything for anything. Changelly Here are some other competitive advantages of the platform: Changelly does not store user funds and employs several high-level security standards and smart KYC verification (learn more about it ). Rock-solid security: here Users don’t need to go through mandatory authentication to access high transaction limits. Ease of authentication: Changelly has partnered with over 20 crypto trading platforms to deliver competitive crypto exchange rates. Best market rates: Average exchanges via Changelly don't take more than 10 minutes. Fast transaction speed: The Changelly mobile app feels incredibly smooth to use and has great reviews on the and as well as over 5 million installs. The platform also operates . Engaging user experience: App Store Google Play on the web Changelly often conducts promotion campaigns, like the current for in-app transactions. Generous offers: 0% service fee offer As a CeDeFi ecosystem, Changelly strives to combine the best technologies and attributes of both financial systems, granting innovative and convenient Web3-based products with lower fees, better security, accessibility, speed, and customization. Let’s dive into the details. Navigating Changelly: Seamless & Transparent Swaps As the global instant exchange platform nears nine years of market presence, Changelly seeks to constantly improve its features, user experience, and offerings to loyal and new customers. Meet new listings & trading pairs every week. Changelly's broad spectrum of exchangeable crypto assets is noteworthy, and they consistently demonstrate foresight by being among the first to list the most promising tokens and coins emerging in the market. Besides, Changelly connects with over 100 DEXs and 3 DEX aggregators, providing their own private liquidity and enabling users to trade thousands of DeFi tokens. Convert fiat to crypto. Changelly aggregates the best offers from a variety of trusted on-ramp payment providers, which include Moonpay, Banxa, Wert, and Simplex, to enable its users to purchase hundreds of cryptocurrencies with 50+ fiat currencies. Moreover, Changelly has recently introduced purchases of DEX tokens for fiat. Enjoy low fees & high exchange limits. Changelly offers one of the most competitive fees on the market—0.25% for crypto-to-crypto exchanges. All the fees are fully transparent and displayed in a separate section during the swapping process. Additionally, the platform's maximum and minimum exchange limits are $15 million and $10, respectively, the range meeting the demands of the majority of crypto users. Benefit from fixed & floating rates. As the crypto market is incredibly volatile, the ability to ‘lock’ a rate for the duration of the exchange can be an efficient safeguard against potential losses. Going with the flow has advantages, too: if the market turns green during your floating-rate swap, you might get more crypto than originally estimated. Deal with the live 24/7 customer support. Changelly has a dedicated help center: their multilingual support team is online 24/7 in chat and via email. The frequently asked questions and the most complicated cases are described in Changelly’s blog—for example, check the helpful immersive . Crush Course for learning crypto basics Easy Entrance to Web3 Community Partnering with the crypto industry’s big names, Changelly is generous with and beneficial activities, offers, and campaigns for its users. Anticipating the Bitcoin halving in 2024, Changelly has united forces with its prominent partners and Web3 industry leaders , , and , welcoming everyone to the on Cointelegraph with a selection of awesome gifts (like brand-new Apple Vision Pro) and valuable offers for crypto believers. educational initiatives Topper Tangem Zengo Bitcoin Halving Party Upon downloading the Changelly app, you will take advantage of 0% service fees for crypto exchanges. Follow Changelly’s socials to keep up to date with more opportunities: , , , and . X (Twitter) Telegram Instagram LinkedIn This story was distributed under HackerNoon’s  Business Blogging Program. Learn more about the program here: https://business.hackernoon.com/

Meet Changelly, the Leading Global Crypto Exchange Platform for Secure and Instant Swaps

নিরাপদ এবং তাত্ক্ষণিক অদলবদলের জন্য শীর্ষস্থানীয় গ্লোবাল ক্রিপ্টো এক্সচেঞ্জ প্ল্যাটফর্ম, চেঞ্জেলির সাথে দেখা করুন

Lernen Sie Changelly kennen, die führende globale Krypto-Austauschplattform für sichere und sofortige Swaps

Conozca Changelly, la plataforma líder mundial de intercambio de cifrado para intercambios seguros e instantáneos

Découvrez Changelly, la principale plateforme mondiale d'échange de crypto-monnaies pour des échanges sécurisés et instantanés

सुरक्षित और त्वरित स्वैप के लिए अग्रणी वैश्विक क्रिप्टो एक्सचेंज प्लेटफॉर्म चांगेली से मिलें

Changelly をご紹介します。安全でインスタントなスワップを実現する世界有数の暗号通貨交換プラットフォームです。

안전하고 즉각적인 스왑을 위한 선도적인 글로벌 암호화폐 교환 플랫폼인 Changelly를 만나보세요

Conheça a Changelly, a principal plataforma global de troca de criptografia para trocas seguras e instantâneas

Встречайте Changelly, ведущую глобальную платформу криптовалютного обмена для безопасных и мгновенных свопов

Güvenli ve Anında Swaplar için Lider Küresel Kripto Borsa Platformu Changelly ile tanışın

Gặp gỡ Changelly, Nền tảng trao đổi tiền điện tử toàn cầu hàng đầu về hoán đổi an toàn và tức thì

认识 Changelly，全球领先的安全即时交换加密货币交易平台

This paper is available on under CC 4.0 license. Arxiv Authors: (1) Md Masud Rana, Department of Mathematics, University of Kentucky; (2) Duc Duy Nguyen, Department of Mathematics, University of Kentucky & ducnguyen@uky.edu. Table of Links Abstract & Introduction Datasets and Results Methods Conclusion, Data and Software Availability, Competing interests, Acknowledgments & References 4 Conclusion The study of protein-protein interactions (PPIs) and the prediction of mutation-induced binding free energy changes are of great importance in understanding the molecular basis of biological processes. The application of geometric graph theory and atom-level graph coloring techniques provides a powerful framework for analyzing biomolecules and capturing their intricate relationships. By utilizing the concept of geometric subgraphs and constructing multi-scale weighted colored geometric subgraphs (MWCGS), we can effectively represent the structural and functional properties of PPIs. The site-specific MWCGS features allow us to extract meaningful patterns and characteristics, shedding light on the effects of mutations and the underlying molecular interactions. In this work, we developed a mutation-induced binding free energy change predictor, called GGL-PPI, by incorporating site-specific MWCGS features for PPIs and gradient-boosting trees. Our method demonstrates superior performance compared to existing methods. The model was validated on three datasets: AB-Bind S645, SKEMPI 1.0 S1131, and SKEMPI 2.0 S4169 and S8338, showcasing its robustness and effectiveness. Furthermore, GGL-PPI was evaluated on a blind test set, the Ssym dataset. To prevent data leakage between the test and training sets, the model was trained on a homology-reduced balanced training set Q3488. This approach ensures the reliability and fairness of the evaluation process. GGL-PPI exhibits the most unbiased and superior performance in predicting binding free energy changes for both direct and reverse mutations, outperforming other existing methods, particularly for reverse mutations. Overall, the results highlight the potential of the GGL-PPI approach in accurately predicting mutation-induced binding free energy changes in protein-protein interactions, providing valuable insights into the molecular mechanisms underlying protein-protein interactions and facilitating drug design and discovery efforts. 5 Data and Software Availability The source code is available at Github: https://github.com/NguyenLabUKY/GGL-Mutation. 6 Competing interests No competing interest is declared. 7 Acknowledgments This work is supported in part by funds from the National Science Foundation (NSF: # 2053284, # 2151802, and # 2245903), and the University of Kentucky Startup Fund. References [1] Dana Chuderland and Rony Seger. Protein-protein interactions in the regulation of the extracellular signal-regulated kinase. Mol. Biotechnol., 29:57–74, 2005. [2] Harry Jubb, Tom L Blundell, and David B Ascher. Flexibility and small pockets at protein–protein interfaces: new insights into druggability. Prog. Biophys. Mol., 119(1):2–9, 2015. [3] Mileidy W Gonzalez and Maricel G Kann. Chapter 4: Protein interactions and disease. PLoS Comput. Biol., 8(12):e1002819, 2012. [4] Cunliang Geng, Li C Xue, Jorge Roel-Touris, and Alexandre MJJ Bonvin. Finding the δδg spot: are predictors of binding affinity changes upon mutations in protein–protein interactions ready for it? Wiley Interdiscip. Rev. Comput. Mol. Sci., 9(5):e1410, 2019. [5] Rocco Moretti, Sarel J Fleishman, Rudi Agius, Mieczyslaw Torchala, Paul A Bates, Panagiotis L Kastritis, Joao PGLM Rodrigues, Mika¨el Trellet, Alexandre MJJ Bonvin, Meng Cui, et al. Community-wide evaluation of methods for predicting the effect of mutations on protein–protein interactions. Proteins: Struct. Funct. Genet., 81(11):1980–1987, 2013. [6] Jeffrey R Brender and Yang Zhang. Predicting the effect of mutations on protein-protein binding interactions through structure-based interface profiles. PLoS Comput. Biol., 11(10):e1004494, 2015. [7] Ning Zhang, Yuting Chen, Haoyu Lu, Feiyang Zhao, Roberto Vera Alvarez, Alexander Goncearenco, Anna R Panchenko, and Minghui Li. Mutabind2: predicting the impacts of single and multiple mutations on protein-protein interactions. Iscience, 23(3):100939, 2020. [8] Carlos HM Rodrigues, Yoochan Myung, Douglas EV Pires, and David B Ascher. mcsm-ppi2: predicting the effects of mutations on protein–protein interactions. Nucleic Acids Res., 47(W1):W338–W344, 2019. [9] Minghui Li, Marharyta Petukh, Emil Alexov, and Anna R Panchenko. Predicting the impact of missense mutations on protein–protein binding affinity. J. Chem. Theory Comput., 10(4):1770–1780, 2014. [10] Hafumi Nishi, Manoj Tyagi, Shaolei Teng, Benjamin A Shoemaker, Kosuke Hashimoto, Emil Alexov, Stefan Wuchty, and Anna R Panchenko. Cancer missense mutations alter binding properties of proteins and their interaction networks. PloS one, 8(6):e66273, 2013. [11] Mu Gao, Hongyi Zhou, and Jeffrey Skolnick. Insights into disease-associated mutations in the human proteome through protein structural analysis. Structure, 23(7):1362–1369, 2015. [12] Alessia David, Rozami Razali, Mark N Wass, and Michael JE Sternberg. Protein–protein interaction sites are hot spots for disease-associated nonsynonymous snps. Hum. Mutat., 33(2):359–363, 2012. [13] H Billur Engin, Jason F Kreisberg, and Hannah Carter. Structure-based analysis reveals cancer missense mutations target protein interaction interfaces. PLoS One, 11(4):e0152929, 2016. [14] Amelie Stein, Douglas M Fowler, Rasmus Hartmann-Petersen, and Kresten Lindorff-Larsen. Biophysical and mechanistic models for disease-causing protein variants. Trends Biochem. Sci., 44(7):575–588, 2019. [15] Stephanie Portelli, Jody E Phelan, David B Ascher, Taane G Clark, and Nicholas Furnham. Understanding molecular consequences of putative drug resistant mutations in mycobacterium tuberculosis. Sci. Rep., 8(1):1–12, 2018. [16] Sundeep Chaitanya Vedithi, Sony Malhotra, Madhusmita Das, Sheela Daniel, Nanda Kishore, Anuja George, Shantha Arumugam, Lakshmi Rajan, Mannam Ebenezer, David B Ascher, et al. Structural implications of mutations conferring rifampin resistance in mycobacterium leprae. Sci. Rep., 8(1):5016, 2018. [17] Vytautas Gapsys, Servaas Michielssens, Daniel Seeliger, and Bert L de Groot. Accurate and rigorous prediction of the changes in protein free energies in a large-scale mutation scan. Angew. Chem., Int. Ed., 55(26):7364–7368, 2016. [18] Elizabeth H Kellogg, Andrew Leaver-Fay, and David Baker. Role of conformational sampling in computing mutationinduced changes in protein structure and stability. Proteins: Structure, Function, and Bioinformatics, 79(3):830–838, 2011. [19] Brian J Bender, Alberto Cisneros III, Amanda M Duran, Jessica A Finn, Darwin Fu, Alyssa D Lokits, Benjamin K Mueller, Amandeep K Sangha, Marion F Sauer, Alexander M Sevy, et al. Protocols for molecular modeling with rosetta3 and rosettascripts. Biochemistry, 55(34):4748–4763, 2016. [20] Kurt S Thorn and Andrew A Bogan. Asedb: a database of alanine mutations and their effects on the free energy of binding in protein interactions. Bioinformatics, 17(3):284–285, 2001. [21] MD Shaji Kumar and M Michael Gromiha. Pint: protein–protein interactions thermodynamic database. Nucleic Acids Res., 34(suppl 1):D195–D198, 2006. [22] MD Shaji Kumar, K Abdulla Bava, M Michael Gromiha, Ponraj Prabakaran, Koji Kitajima, Hatsuho Uedaira, and Akinori Sarai. Protherm and pronit: thermodynamic databases for proteins and protein–nucleic acid interactions. Nucleic Acids Res., 34(suppl 1):D204–D206, 2006. [23] Iain H Moal and Juan Fern´andez-Recio. Skempi: a structural kinetic and energetic database of mutant protein interactions and its use in empirical models. Bioinformatics, 28(20):2600–2607, 2012. [24] Justina Jankauskait˙e, Brian Jim´enez-Garc´ıa, Justas Dapk¯unas, Juan Fern´andez-Recio, and Iain H Moal. Skempi 2.0: an updated benchmark of changes in protein–protein binding energy, kinetics and thermodynamics upon mutation. Bioinformatics, 35(3):462–469, 2019. [25] Sarah Sirin, James R Apgar, Eric M Bennett, and Amy E Keating. Ab-bind: antibody binding mutational database for computational affinity predictions. Protein Sci., 25(2):393–409, 2016. [26] Cunliang Geng, Anna Vangone, and Alexandre MJJ Bonvin. Exploring the interplay between experimental methods and the performance of predictors of binding affinity change upon mutations in protein complexes. Protein Eng. Des. Sel., 29(8):291–299, 2016. [27] Sherlyn Jemimah, K Yugandhar, and M Michael Gromiha. Proximate: a database of mutant protein–protein complex thermodynamics and kinetics. Bioinformatics, 33(17):2787–2788, 2017. [28] Douglas EV Pires, David B Ascher, and Tom L Blundell. mcsm: predicting the effects of mutations in proteins using graph-based signatures. Bioinformatics, 30(3):335–342, 2014. [29] Cunliang Geng, Anna Vangone, Gert E Folkers, Li C Xue, and Alexandre MJJ Bonvin. isee: Interface structure, evolution, and energy-based machine learning predictor of binding affinity changes upon mutations. Proteins: Structure, Function, and Bioinformatics, 87(2):110–119, 2019. [30] Sherlyn Jemimah, Masakazu Sekijima, and M Michael Gromiha. Proaffimuseq: sequence-based method to predict the binding free energy change of protein–protein complexes upon mutation using functional classification. Bioinformatics, 36(6):1725–1730, 2020. [31] Guangyu Zhou, Muhao Chen, Chelsea JT Ju, Zheng Wang, Jyun-Yu Jiang, and Wei Wang. Mutation effect estimation on protein–protein interactions using deep contextualized representation learning. NAR genom. bioinform., 2(2):lqaa015, 2020. [32] Alexey Strokach, Tian Yu Lu, and Philip M Kim. Elaspic2 (el2): combining contextualized language models and graph neural networks to predict effects of mutations. J. Mol. Biol., 433(11):166810, 2021. [33] Xianggen Liu, Yunan Luo, Pengyong Li, Sen Song, and Jian Peng. Deep geometric representations for modeling effects of mutations on protein-protein binding affinity. PLoS Comput. Biol., 17(8):e1009284, 2021. [34] Piero Fariselli, Pier Luigi Martelli, Castrense Savojardo, and Rita Casadio. Inps: predicting the impact of nonsynonymous variations on protein stability from sequence. Bioinformatics, 31(17):2816–2821, 2015. [35] Grant Thiltgen and Richard A Goldstein. Assessing predictors of changes in protein stability upon mutation using self-consistency. PLoS One, 7(10):e46084, 2012. [36] Fabrizio Pucci, Katrien V Bernaerts, Jean Marc Kwasigroch, and Marianne Rooman. Quantification of biases in predictions of protein stability changes upon mutations. Bioinformatics, 34(21):3659–3665, 2018. [37] Dinara R Usmanova, Natalya S Bogatyreva, Joan Ari˜no Bernad, Aleksandra A Eremina, Anastasiya A Gorshkova, German M Kanevskiy, Lyubov R Lonishin, Alexander V Meister, Alisa G Yakupova, Fyodor A Kondrashov, et al. Self-consistency test reveals systematic bias in programs for prediction change of stability upon mutation. Bioinformatics, 34(21):3653–3658, 2018. [38] Duc D Nguyen, Tian Xiao, Menglun Wang, and Guo-Wei Wei. Rigidity strengthening: A mechanism for protein– ligand binding. J. Chem. Inf. Model., 57(7):1715–1721, 2017. [39] Md Masud Rana and Duc Duy Nguyen. Geometric graph learning with extended atom-types features for proteinligand binding affinity prediction. Comput. Biol. Med., 164:107250, 2023. [40] Jian Jiang, Rui Wang, and Guo-Wei Wei. Ggl-tox: geometric graph learning for toxicity prediction. J. Chem. Inf. Model., 61(4):1691–1700, 2021. [41] Menglun Wang, Zixuan Cang, and Guo-Wei Wei. A topology-based network tree for the prediction of protein–protein binding affinity changes following mutation. Nat. Mach. Intell., 2(2):116–123, 2020. [42] Duan Chen, Zhan Chen, Changjun Chen, Weihua Geng, and Guo-Wei Wei. Mibpb: a software package for electrostatic analysis. J. Comput. Chem., 32(4):756–770, 2011. [43] Xiang Liu, Huitao Feng, Jie Wu, and Kelin Xia. Hom-complex-based machine learning (hcml) for the prediction of protein–protein binding affinity changes upon mutation. J. Chem. Inf. Model., 62(17):3961–3969, 2022. [44] Douglas EV Pires and David B Ascher. mcsm-ab: a web server for predicting antibody–antigen affinity changes upon mutation with graph-based signatures. Nucleic Acids Res., 44(W1):W469–W473, 2016. [45] Peng Xiong, Chengxin Zhang, Wei Zheng, and Yang Zhang. Bindprofx: assessing mutation-induced binding affinity change by protein interface profiles with pseudo-counts. J. Mol. Biol., 429(3):426–434, 2017. [46] Quanya Liu, Peng Chen, Bing Wang, Jun Zhang, and Jinyan Li. dbmpikt: a database of kinetic and thermodynamic mutant protein interactions. BMC bioinformatics, 19(1):1–7, 2018. [47] Bian Li, Yucheng T Yang, John A Capra, and Mark B Gerstein. Predicting changes in protein thermodynamic stability upon point mutation with deep 3d convolutional neural networks. PLoS Comp. Bio., 16(11):e1008291, 2020. [48] Lijun Quan, Qiang Lv, and Yang Zhang. Strum: structure-based prediction of protein stability changes upon single-point mutation. Bioinformatics, 32(19):2936–2946, 2016. [49] Leo Breiman. Random forests. Machine learning, 45:5–32, 2001. [50] Corinna Cortes and Vladimir Vapnik. Support-vector networks. Machine learning, 20:273–297, 1995. [51] Duc Duy Nguyen, Kaifu Gao, Menglun Wang, and Guo-Wei Wei. Mathdl: mathematical deep learning for d3r grand challenge 4. J. Comput. Aided. Mol. Des., 34(2):131–147, 2020. [52] Jerome H Friedman. Greedy function approximation: a gradient boosting machine. Annals of statistics, pages 1189–1232, 2001. This paper is available on under CC 4.0 license. Arxiv

PPIs and the Prediction of Mutation-Induced Binding Free Energy Changes: What It All Means

This paper is available on arxiv under CC 4.0 license. Authors: (1) Md Masud Rana, Department of Mathematics, University of Kentucky; (2) Duc Duy Nguyen, Department of Mathematics, University of Kentucky & ducnguyen@uky.edu. Table of Links Abstract & Introduction Datasets and Results Methods Conclusion, Data and Software Availability, Competing interests, Acknowledgments & References 3 Methods 3.1 Graph Theory and Atom-level Interactions in Biomolecules Graph theory provides a mathematical framework that is widely applied in the study of biomolecules such as proteins, DNA, and RNA. For a biomolecule, a graph G(V, E) is a collection of nodes V and edges E that can represent the connectivity and relationships between different atoms or residues within the molecule. A refinement to this representation is graph coloring, a technique that assigns unique labels to different atom types within the biomolecule. This enriched, colored graph encodes diverse atomic interactions, paving the way for a collective and coarse-grained description of the dataset. In this representation, atoms with assigned labels are organized into subgraphs, and the colored edges between them represent atom-specific interactions. The advantage of using subgraphs lies in their ability to focus on specific regions or components of the biomolecule. By isolating relevant subsets of atoms, subgraphs allow us to identify localized patterns, interactions, or clusters that might not be evident in the global graph representation. This targeted approach provides a more nuanced understanding of the structural and functional properties of biomolecules. To extract atom-level interaction information, we consider specific atom types based on their names in the PDB structure such as carbon alpha (CA), carbon beta (CB), carbon delta-1 (CD1), etc. These atom names serve as identifiers for specific positions within a protein’s three-dimensional structure. They help define the individual atoms that constitute amino acids, the building blocks of proteins, and provide crucial information about their spatial orientation and chemical properties. We consider a total of 37 distinct atom names that are frequently found in protein structures within the PDB database. These atom types are represented by the set A. To simplify the notation, we assume the set A is sorted in alphanumeric order, A = {C, CA, CB, · · · , N, ND1, ND2, · · · , O, OD1, · · · , SD, SG}, serves as a measure of the combined strength of interaction between chosen pairs of atom types, providing valuable insights into the molecular structure and properties. 3.2 Geometric Subgraph Representation of PPIs In the context of studying protein-protein interactions (PPIs) and predicting the effects of mutations on these interactions, it is important to focus on the relevant regions where the interactions occur. While protein-protein complexes can consist of a large number of atoms, the interactions between proteins primarily take place at specific regions known as interfaces. To streamline computational costs and concentrate on pertinent information, it is common practice to consider only the protein atoms near the binding sites. The binding site, in this context, refers to the region within a certain cutoff distance c from the chain where the mutation occurred. By defining the binding site in this way, we can narrow our focus to the specific area where the interaction and subsequent effects of the mutation are most pronounced. Furthermore, when analyzing the effects of mutations, it is crucial to incorporate geometric graph information from the mutation sites and their neighboring regions. The mutation site is defined as the region within a cutoff distance c from the mutated residue, allowing us to capture the structural changes resulting from the mutation. To construct a site-specific multiscale weighted colored geometric subgraph (MWCGS) representation for a PPI, both the wild-type and mutant-type proteins are considered. This leads to four sets of features for each PPI, corresponding to the two sites and the two types of proteins involved. Each set consists of 37 × 37 = 1369 MWCGS features, representing the interactions between the atom types involved in the PPI. These features encompass diverse chemical and biological properties, such as the presence of specific interatomic interactions involving oxygen and nitrogen atoms, the hydrophobic nature of certain regions, and the ability of atoms to undergo polarization, among other relevant molecular characteristics. By utilizing these site-specific MWCGS features, we can uncover valuable insights into the effects of mutations and the underlying molecular interactions, revealing significant information and characteristics embedded within the PPI system. 3.3 Geometric Graph Learning for PPIs Accurately predicting the changes in binding affinity induced by mutations in protein-protein complexes poses a significant challenge due to the complex nature of these systems. The interactions between proteins are highly intricate, and the effects of mutations can be subtle and context-dependent. Machine learning techniques offer a promising approach to tackle this problem by leveraging the power of data-driven models to capture complex patterns and relationships. Machine learning algorithms can aid in predicting mutation-induced binding affinity changes by learning from a set of training examples that consist of protein-protein complexes with known experimental binding affinities. These algorithms can analyze the features extracted from the complexes, such as geometric graph information, to identify relevant patterns and associations between the features and the binding affinities. By learning from these patterns, the algorithms can generalize and make predictions on unseen protein-protein complexes. There are several machine learning algorithms that can be used in combination with geometric graph features to predict binding affinity changes. These algorithms include random forests [49], support vector machines (SVM) [50], neural networks [51], and gradient boosting trees (GBT) [52]. Each algorithm has its strengths and weaknesses, and their performance can vary depending on the specific problem and dataset. Among these algorithms, gradient boosting trees (GBT) have gained significant popularity in recent years [39]. GBT is an ensemble method that builds a sequence of weak learners, typically decision trees, to correct the errors made by the previous learners. By combining these weak learners, GBT can effectively model complex relationships and improve prediction accuracy. One advantage of GBT is its robustness against overfitting, which is especially beneficial when dealing with a moderate number of features. Additionally, GBT models can provide interpretability, allowing us to gain insights into the factors contributing to the binding affinity changes. The implementation of the GBT algorithm in this study utilized the scikit-learn package (v 0.24.1). To optimize the performance of the GBT model for ensemble methods, specific hyperparameters were fine-tuned. The number of estimators was set to 40000, indicating the number of weak learners in the ensemble, while the learning rate was set to 0.001, determining the contribution of each weak learner to the final prediction. Given the large number of features involved in the prediction task, an efficient training process was achieved by limiting the maximum number of features considered to the square root of the descriptor length. This approach helped expedite the training process without compromising the overall performance of the GBT model. To ensure reliable performance evaluation, fifty runs were performed for each feature set, employing different random seeds. By averaging the results obtained from these runs, a more robust and representative performance measure was obtained. Despite the complexity of the prediction task and the involvement of numerous features, the selected parameter settings and multiple runs yielded satisfactory performance results. The GBT approach was chosen for its ability to effectively handle overfitting, exhibit good performance with moderately sized datasets, and provide interpretable models. These characteristics make GBT a suitable and reliable choice for this study, enabling accurate predictions of mutation-induced binding affinity changes in protein-protein complexes using the provided geometric graph features. This paper is available on under CC 4.0 license. Arxiv

The Methods We Used to Predict Mutation-Induced Binding Free Energy Changes

This paper is available on arxiv under CC 4.0 license. Authors: (1) Md Masud Rana, Department of Mathematics, University of Kentucky; (2) Duc Duy Nguyen, Department of Mathematics, University of Kentucky & ducnguyen@uky.edu. Table of Links Abstract & Introduction Datasets and Results Methods Conclusion, Data and Software Availability, Competing interests, Acknowledgments & References Abstract Protein-protein interactions (PPIs) are critical for various biological processes, and understanding their dynamics is essential for decoding molecular mechanisms and advancing fields such as cancer research and drug discovery. Mutations in PPIs can disrupt protein binding affinity and lead to functional changes and disease. Predicting the impact of mutations on binding affinity is valuable but experimentally challenging. Computational methods, including physics-based and machine learning-based approaches, have been developed to address this challenge. Machine learning-based methods, fueled by extensive PPI datasets such as Ab-Bind, PINT, SKEMPI, and others, have shown promise in predicting binding affinity changes. However, accurate predictions and generalization of these models across different datasets remain challenging. Geometric graph learning has emerged as a powerful approach, combining graph theory and machine learning, to capture structural features of biomolecules. We present GGL-PPI, a novel method that integrates geometric graph learning and machine learning to predict mutation-induced binding free energy changes. GGL-PPI leverages atom-level graph coloring and multi-scale weighted colored geometric subgraphs to extract informative features, demonstrating superior performance on three validation datasets, namely AB-Bind, SKEMPI 1.0, and SKEMPI 2.0 datasets. Evaluation on a blind test set highlights the unbiased predictions of GGLPPI for both direct and reverse mutations. The findings underscore the potential of GGL-PPI in accurately predicting binding free energy changes, contributing to our understanding of PPIs and aiding drug design efforts. — geometric graph, machine learning, protein-protein interactions, mutation, binding free energy changes Keywords 1 Introduction Protein-protein interactions (PPIs) play a fundamental role in numerous biological processes, including cell signaling, metabolic pathways, and immune responses [1;2;3]. Understanding PPIs and their dynamics is crucial for unraveling the intricate mechanisms underlying these processes and holds significant implications for various fields, such as cancer research, drug discovery, and personalized medicine [3;4]. The effects of mutations on PPIs have drawn substantial attention due to their potential impact on protein function and cellular behavior [5;6;7;8]. Missense mutations, which involve single amino acid substitutions, can disrupt the binding affinity between proteins and their partners [9;10]. Such alterations can lead to malfunctioning PPI networks, resulting in diseases, drug resistance, or other molecular disorders [11;12;13;14;15;16]. Therefore, accurate prediction of the impact of mutations on binding affinity holds significant importance in understanding disease mechanisms, facilitating therapeutic interventions, and enabling the design of innovative biopharmaceuticals. One of the key parameters used to assess the impact of mutations on PPIs is the binding free energy change (∆∆G). This thermodynamic parameter quantifies the difference in binding affinity between the wild-type and mutant protein complexes. Experimental determination of ∆∆G values, while accurate, can be tedious and costly. Consequently, there has been a surge in the development of computational methods to predict these energy changes. Broadly, these computation approaches fall into two main categories: physics-based and machine learning-based methods. The former, rooted in biophysical principles, delves into protein conformations and offers a rigorous approach [17;18;19]. However, they often demand significant computational resources and are not always scalable. On the other hand, machine learning-based methods have gained popularity due to their scalability and rapid prediction capabilities. Leveraging the wealth of data from PPI datasets such as ASEdb [20], PINT[21], ProTherm[22], SKEMPI [23;24], and others [25;26;27], machine learning models like mCSM28, BindProf 6 , iSEE29, MutaBind [7] , and several others [30;31;32;33] have been developed. These models have shown significant potential in predicting ∆∆Gs. However, challenges such as imbalanced training datasets, generalization across different PPI datasets, and the intricacy of capturing complex sequence-structure-function relationships remain obstacles [34;35;36;37]. This underscores the need for further research to enhance machine learning methodologies, ensuring accurate and efficient ∆∆G predictions. In recent years, geometric graph learning has emerged as a promising approach for analyzing complex biomolecular systems [38;39;40]. By representing proteins and their interactions as graphs, this methodology leverages the power of graph theory and machine learning to capture essential structural and spatial features of the biomolecular complexes. Specifically, the use of geometric subgraphs, which encode local interactions between atoms and residues, offers a rich representation. This not only sheds light on intricate molecular details but also provides insights into their impact on binding affinity [39]. This work presents a novel method, called GGL-PPI (Geometric Graph Learning for Protein-Protein Interactions), which combines the principles of geometric graph learning and machine learning to predict mutation-induced binding free energy changes. The workflow of GGL-PPI is depicted in Figure 1. Central to its methodology, GGL-PPI utilizes atom-level graph coloring and multi-scale weighted colored geometric subgraphs, enabling the extraction of informative features from protein structures and their interactions. These features serve as inputs to a gradient-boosting tree model, which facilitates precise and consistent predictions of binding free energy change upon mutations. When compared with existing models, GGL-PPI consistently outperforms state-of-the-art approaches across all datasets. Further addressing its generalizability, GGL-PPI was evaluated on a blind test set, Ssym dataset [36]. This evaluation was conducted using a homology-reduced balanced training set to avert data leakage, showcasing GGL-PPI’s robust performance and ability to produce unbiased predictions for both direct and reverse mutations. This paper is available on under CC 4.0 license. Arxiv

GGL-PPI: Geometric Graph Learning to Predict Mutation-Induced Binding Free Energy Changes

Unlike traditional centralized exchanges, instant crypto exchanges allow users to trade cryptocurrencies directly from their wallets, without the need to deposit funds into an exchange account. Also, many of them help to exchange crypto between different blockchains. Integrating instant crypto exchange functionality into applications through opens up new possibilities for developers. By using these APIs, developers can offer their users the ability to seamlessly swap between cryptocurrencies without leaving the application. This eliminates the need for users to navigate multiple platforms and chains providing access to a wide range of trading pairs. And of course APIs allow developers to benefit from exchange fees, creating a new revenue stream for their applications. APIs In this article, I will explore the process of integrating a ChangeNow API into an application. I will cover the essential steps, including obtaining an API key, authenticating requests, retrieving available trading pairs, executing trades, and monitoring transaction status. By the end of this guide, you'll have a clear understanding of how to leverage such APIs to add powerful trading capabilities to your application. So, let's dive in? Step 1: Sign Up for a ChangeNOW API Key To get started with the ChangeNOW API, you first need to sign up for an API key. This key will be used to authenticate your API requests and ensure secure access to the ChangeNOW exchange services. Navigate to the ChangeNOW page and click on the "Start your integration" button. crypto exchange API Fill in the required information, such as your email address and password, to create a new account. Once you have successfully created an account, log in to your ChangeNOW account dashboard. In the account dashboard, locate the "API" section. This is where you can manage your API keys and access the necessary information for integrating the ChangeNOW API into your application. Click on the "Generate New API Key" button to create a new API key. You may be prompted to provide additional information or verify your account before proceeding. After successfully generating a new API key, you will see it displayed in the API section of your account dashboard. Make sure to copy and store this API key securely, as you will need it for authenticating your API requests. With your ChangeNOW API key generated, you are now ready to proceed to the next step of setting up your development environment and starting to integrate the ChangeNOW API into your application. Remember to keep your API key confidential and avoid sharing it with others. If you suspect that your API key has been compromised, you can always generate a new one from your account dashboard and update your application accordingly. Step 2: Set Up Your Development Environment Before you start integrating the ChangeNOW API into your application, you need to set up your development environment. This involves choosing a programming language and an Integrated Development Environment (IDE) that you are comfortable with, and installing the necessary libraries for making HTTP requests. For this guide, I will provide examples in . Python Install Python on your machine if you haven't already. You can download the latest version of Python from the official and follow the installation instructions for your operating system. website Choose an for Python development. Some popular options include PyCharm, Visual Studio Code, and Sublime Text. IDE Install the requests library, which is a popular library for making HTTP requests in Python. You can install it using pip, the package installer for Python, by running the following command in your terminal or command prompt: pip install requests Create a new Python file in your IDE and import the requests library at the top of your file: import requests With your development environment set up and the necessary libraries installed, you are now ready to start making API requests to the ChangeNOW API. Step 3: Authenticate Your API Requests To authenticate your API requests and ensure secure communication with the ChangeNOW API, you need to include your API key in the x-changenow-api-key header of each request. This header tells the ChangeNOW API that you are an authorized user and grants you access to the API endpoints. Here's how you can set the API key header in Python: import requests

api_key = 'YOUR_API_KEY'  # Replace with your actual API key

headers = { 'x-changenow-api-key': api_key }

response = requests.get('https://api.changenow.io/v1/endpoint', headers=headers) Replace 'YOUR_API_KEY' with the actual API key you obtained in Step 1. The headers object is created with the x-changenow-api-key header set to your API key. This header is then included in the API request using the headers parameter of the requests.get() method. By including the API key header in each request, you authenticate yourself as an authorized user of the ChangeNOW API. The API server will validate your API key and grant access to the requested endpoints if the key is valid. Step 4: Retrieve Available Currency Pairs To start using the ChangeNOW API, you need to know which currency pairs are available for exchange. The ChangeNOW API provides an endpoint to retrieve the list of available currency pairs. To retrieve the available currency pairs, you need to make a GET request to the /v1/market-info/available-pairs/ endpoint. Here's how you can send the request and parse the response: import requests

api_key = 'YOUR_API_KEY'

headers = {

'x-changenow-api-key': api_key }

response = requests.get('https://api.changenow.io/v1/market-info/available-pairs/', headers=headers)

if response.status_code == 200:

available_pairs = response.json()

print("Available currency pairs:")

for pair in available_pairs: print(pair) 

else: print(f"Error: {response.status_code}") The code sends a GET request to the /v1/market-info/available-pairs/ endpoint, including the API key in the x-changenow-api-key header for authentication. If the request is successful (status code 200), the response will contain a JSON array of available currency pairs. The code then parses the response and extracts the list of currency pairs. The response.json() method is used to parse the JSON response into a Python list. The code then iterates over the list and prints each currency pair. If the request fails, the code prints an error message along with the status code. By retrieving the available currency pairs, you can provide your users with the options to choose from when performing an exchange. Step 5: Check Minimum and Maximum Exchange Amounts Before performing an exchange, it's important to know the minimum and maximum amounts allowed for a specific currency pair. The ChangeNOW API provides an endpoint to retrieve this information. To check the minimum and maximum exchange amounts, you need to make a GET request to the /v2/exchange/range endpoint, providing the required parameters: fromCurrency and toCurrency. Here's how you can construct the request URL with query parameters and parse the response: import requests

api_key = 'YOUR_API_KEY'

headers = { 'x-changenow-api-key': api_key }

from_currency = 'btc'  # Replace with the source currency

to_currency = 'eth'    # Replace with the target currency

url = f'https://api.changenow.io/v2/exchange/range?fromCurrency={from_currency}&toCurrency={to_currency}'

response = requests.get(url, headers=headers)

if response.status_code == 200:

data = response.json() 

min_amount = data['minAmount'] 

max_amount = data['maxAmount'] 

print(f"Minimum exchange amount: {min_amount}") 

print(f"Maximum exchange amount: {max_amount}") 

else: print(f"Error: {response.status_code}") Set the fromCurrency and toCurrency variables to the desired source and target currencies, respectively. The code constructs the request URL by appending the fromCurrency and toCurrency parameters as query parameters to the /v2/exchange/range endpoint URL. It then sends a GET request to the constructed URL, including the API key in the x-changenow-api-key header for authentication. If the request is successful (status code 200), the response will contain a JSON object with the minAmount and maxAmount fields. The code parses the response and extracts these values. Tthe response.json() method is used to parse the JSON response into a Python dictionary. The minAmount and maxAmount values are then accessed and printed. By checking the minimum and maximum exchange amounts, you can ensure that the user's requested exchange amount falls within the allowed range for the selected currency pair. Step 6: Estimate Exchange Amounts Before proceeding with an exchange, you may want to provide an estimate of the exchange amount to the user based on their input. The ChangeNOW API offers an endpoint to estimate the exchange amount for a given currency pair and amount. To estimate the exchange amount, you need to make a GET request to the /v2/markets/estimate endpoint, providing the required parameters: fromCurrency, toCurrency, fromAmount or toAmount, and type. Here's how you can build the request URL, send the request, and handle the response: import requests

api_key = 'YOUR_API_KEY'

headers = { 'x-changenow-api-key': api_key }

from_currency = 'btc'   # Replace with the source currency

to_currency = 'eth'     # Replace with the target currency 

from_amount = 1.5       # Replace with the source amount

url = f'https://api.changenow.io/v2/markets/estimate?fromCurrency={from_currency}&toCurrency={to_currency}&fromAmount={from_amount}&type=direct'

response = requests.get(url, headers=headers)

if response.status_code == 200:

data = response.json() 

estimated_amount = data['toAmount'] 

print(f"Estimated exchange amount: {estimated_amount} {to_currency}") 

else: print(f"Error: {response.status_code}") Set the fromCurrency, toCurrency, and fromAmount variables to the desired source currency, target currency, and source amount. The code builds the request URL by appending the fromCurrency, toCurrency, fromAmount, and type parameters as query parameters to the /v2/markets/estimate endpoint URL. It then sends a GET request to the constructed URL, including the API key in the x-changenow-api-key header for authentication. If the request is successful (status code 200), the response will contain a JSON object with the estimated exchange amount in the toAmount field. The code parses the response and extracts the estimated amount. The response.json() method is used to parse the JSON response into a Python dictionary. The toAmount value is then accessed and printed along with the target currency. If the request fails, the code prints an error message along with the status code. By estimating the exchange amount, you can provide the user with an idea of how much they will receive in the target currency based on their input amount in the source currency. Step 7: Create an Exchange Transaction Once the user has provided the necessary information, such as the source and target currencies, the amount to exchange, and the destination address, you can create an exchange transaction using the ChangeNOW API. To create an exchange transaction, you need to make a POST request to the /v2/exchange/refund endpoint, including the required parameters in the request body: id, address, and extraId (if applicable). Here's how you can construct the request payload, send the POST request, and handle the API response: import requests

api_key = 'YOUR_API_KEY'

headers = { 'x-changenow-api-key': api_key, 'Content-Type': 'application/json' }

transaction_id = 'YOUR_TRANSACTION_ID'  # Replace with the actual transaction ID

refund_address = 'YOUR_REFUND_ADDRESS'  # Replace with the actual refund address 

extra_id = 'YOUR_EXTRA_ID'  # Replace with the actual extra ID (if applicable)

payload = {

'id': transaction_id, 

'address': refund_address, 

'extraId': extra_id 

}

response = requests.post('https://api.changenow.io/v2/exchange/refund', headers=headers, json=payload)

if response.status_code == 200:

data = response.json() 

refund_status = data['result'] 

print(f"Refund status: {refund_status}") 

else: print(f"Error: {response.status_code}") Set the transactionId, refundAddress, and extraId variables to the appropriate values for the exchange transaction. The code constructs the request payload as a JSON object containing the id, address, and extraId fields. It then sends a POST request to the /v2/exchange/refund endpoint, including the API key in the x-changenow-api-key header and the payload in the request body. If the request is successful (status code 200), the response will contain a JSON object indicating the refund status in the result field. The code parses the response and extracts the refund status. The response.json() method is used to parse the JSON response into a Python dictionary. The result value is then accessed and printed. By creating an exchange transaction, you initiate the process of exchanging the user's funds from the source currency to the target currency. The API will handle the exchange process and send the exchanged funds to the specified destination address. Step 8: Monitor Transaction Status After creating an exchange transaction, you can monitor its status to keep track of the progress and provide updates to the user. The ChangeNOW API allows you to retrieve the status and details of transactions using the /v2/exchanges endpoint. To monitor the status of a transaction, you need to make a GET request to the /v2/exchanges endpoint. You can optionally include query parameters to filter and sort the transactions. Here's how you can build the request URL with query parameters, send the request, and parse the response to retrieve transaction details and status: import requests

api_key = 'YOUR_API_KEY'  # Replace with your actual API key

headers = { 'x-changenow-api-key': api_key }

url = 'https://api.changenow.io/v2/exchanges?limit=10&offset=0&sortField=createdAt&sortDirection=DESC'

response = requests.get(url, headers=headers)

if response.status_code == 200:

data = response.json() 

transactions = data['exchanges'] 

for transaction in transactions: 

transaction_id = transaction['requestId'] 

status = transaction['status'] 

print(f"Transaction ID: {transaction_id}, Status: {status}") 

else: print(f"Error: {response.status_code}") The code builds the request URL with optional query parameters. In this example, the limit parameter is set to 10 to retrieve a maximum of 10 transactions, the offset parameter is set to 0 to start from the beginning, the sortField parameter is set to 'createdAt' to sort the transactions by creation date, and the sortDirection parameter is set to 'DESC' to sort in descending order. It then sends a GET request to the /v2/exchanges endpoint, including the API key in the x-changenow-api-key header for authentication. If the request is successful (status code 200), the response will contain a JSON object with an array of transactions in the exchanges field. The code parses the response and iterates over the transactions. The response.json() method is used to parse the JSON response into a Python dictionary. The code then iterates over the exchanges array and prints the transaction ID and status for each transaction. By monitoring the transaction status, you can keep track of the progress of the exchange and provide relevant updates to the user. You can periodically poll the API to fetch the latest status of the transaction until it reaches a final state (e.g., "finished" or "failed"). Congratulations! You have successfully learned how to set up and use the ChangeNOW API to integrate cryptocurrency exchange functionality into your application. If you have any problems or need further assistance while implementing the ChangeNOW API, please feel free to leave a comment below. There are on HackerNoon, but you'd like to see a similar step-by-step guide for integrating any other API into your application, let me know in the comments section. many guides Keep exploring, keep learning, and happy coding!

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