Organise gives people the tools, network and confidence to make change happen in their workplace

Organise

As a developer, you need to organise your tasks to manage your time and successfully complete a sprint. These 6 VS Code extensions help devs get organised and work effectively. 1. TODO Highlight If you like to mark sections of code with TODO and FIXME tags but keep forgetting about them then this plugin will solve your problem. It highlights TODO or FIXME phrases in the code so that you don’t forget what you wanted to fix or improve. 2. Todo Tree The Todo Tree extension collects all your tasks scattered throughout the application at your command into one tree on the left side of the editor workspace. You can quickly search your workspace for comment tags like TODO and FIXME, and see them in a tree view. 3. Stepsize Stepsize goes beyond just highlighting TODOs. It allows you to: Create and organise your bookmarks and TODOs into issues Prioritise them in VSCode editor or webapp See technical debt and code to refactor And finally share your findings with your teammates to discuss at your next sprint plannin 4. GitKraken Boards If you want to track progress of your cards, assign tasks, link cards to GitHub pull requests GitKraken Boards will help you do that and more! 5. Project Dashboard VSCode Project Dashboard is a Visual Studio Code extension that lets you organize your projects in a speed-dial like manner. Pin your frequently visited folders, files, and SSH remotes onto a dashboard to access them quickly. Also published on: https://dev.to/alexomeyer/top-6-vs-code-extensions-to-organise-your-code-3mbi

5 Best VS Code Extensions to Help Organise Your Code in 2021

As human beings, we all have likes, dislikes, moments, memories, fears, hopes, wishes, dreams and aspirations. They are all infinitely, formed and reformed every day, every second. We are also a slave to our subconscious patterns, habits and reflexes. It could be something as simple as — we don’t do it , do we? Our brain, in effect, becomes the ultimate recorder for all of these versions and iterations of thoughts. And we continue to wire our brain wetting our feet before starting a bath or wearing a pair of socks in the right foot first intentionally subconsciously. Let’s quantify the amount of information our brain can store — it has a storage and memory power of a super-duper-computer — it can store about i.e. 2.5 million gigabytes of data. It won’t be an overstatement to call the brain a complex machine. A machine that keeps everything in check and never stops working, not for our lifetime at the least. 2.5 petabytes Mirror mirror on the wall This is one of the most famous line, referenced every now and then, since our childhood’s Disney days. This ‘Snow White’ quote is also immortalised on various kinds of merchandise — t-shirts, mugs and what not! In fact, there is even a movie on Snow White, released in 2012, called ‘Mirror Mirror’. Spinoff Mirror mirror on the wall ~ Snow White It’s not what the movie said! What if I told you the quote is wrong? In the movie, they actually say ‘ ’. Magic mirror on the wall How did this happen? How did our brain, not just yours or mine, for most of us, made us believe that it’s and not ? There are an amazing amount of explanations floating on the internet for this. mirror mirror magic mirror From a higher level, it’s known as the — a phenomenon where thousands of people, with no relation to each other, have the same collective misremembering of the one event. It is one of the popular conspiracy theories on the internet that has been messing with the brains worldwide. Mandela Effect The term was coined by Fiona Bloome in 2013, after the death of human rights activist Nelson Mandela. People from all over the world were confused because most had the same vivid memory of him dying in prison during the 1980s. People have even found old textbooks and biographies that state that Nelson Mandela actually did die in the 80s. The theories for Mandela Effect are in abundance. Some believe that it may be due to the shifting of parallel universes. Or like I believe, it could just be our brain machine erring. The messed up brain How’d you find your Deadpool t-shirt in this mess? There are boards on Pinterest for Messy Closets ~ Messy Brains More often than not, this is the condition of our brains — unorganised and in a state of complete mess. It can grow confused and reach a state of overload. What will happen if the search engine of the brain erred?What if the machine (brain) took too long to process the query? There are dozens, if not more, instances where we would have forgotten an important task in last one month. And more, where we feel frustrated or burnt out. Perhaps, these are the signs that our brain needs some work — some organisation — the thinking machine needs a rethinking! Doesn’t it, already? It is extremely critical to make use of our brain in the most efficient and optimum manner possible. In short, grease it well and organise information better. How do we do rewire our brain? Compartmentalise Start by doing one job at a time. Divide your work according to urgency or importance. This will help you prioritise tasks. Do not overburden yourself by thinking of too many things at the same time. Your focus and energy should be dedicated to one specific task. As mentioned before, your brain is a machinery. If you overload it, it will get exhausted and won’t function properly. This doesn’t mean that you ignore the rest of your problems. In fact, compartmentalisation would actually allow you to give your full attention to a specific task without getting distracted by other tasks at hand. You need to micromanage considerably in the beginning since you are training your brain. Once you do it a few times, it will seem natural to you and in effect, will save a lot of productive time. Set deadlines Try to finish your work within the deadline’s time frame. Do not offer yourself easy deadlines or even the tight ones, or else you would be fooling yourself and this exercise will not be able to help you. An easy deadline will make you lazy and carefree, whereas a tight deadline will just invite stress. “The biggest enemy you will ever face or deal in life is yourself.” — Robert Tew Meeting your deadlines on time makes you feel more efficient and proud. Self-gratification is a great motivator of human behaviour and encourages us to be better in ways more than one. Don’t be a slave — say no Yes, we are all slaves. We are slaves to our own vices — to 5 more minutes of sleep, to not starting work immediately but after 5 minutes, and to smoke or coffee breaks as we near the completion of a task. To overcome these, we should learn to say NO, to ourselves. Take a hard stand. Fight your greed. Fight every moment that pulls you back. Fight against your sweet 5 minutes of sleep, or 5 more minutes of break. Finish the work and then have your coffee/smoke break. You will discover that this makes you happier and more satisfied. The very fact that you have completed a task and won’t have to go back to work on it again, is a great satisfier in adult life. Closure These little improvements will save you a lot of time. Remember, if you are your biggest enemy, you are your biggest challenger as well. Observe and study yourself. Start with the smallest of the things. It can be anything — your diction or a habit. Mine used to be starting each sentence with a — ‘ok so?’. It is quite critical to correct yourself every now and then. Take a pause; start small. These little tweaks will help you , making you more efficient, organised and smart. rewire your brain

Rewire your brain — be efficient, organised and smart

Well, is a simple web which will help you to keep all your tags organized and provide you with quick access to your most used ones, but more importantly, it will help you save tons of time. AG Tags Generator tool All social platforms have different tag requirements in terms of quantity, separators & prefixes as well as other requirements. With this tool you can generate perfectly customized tags for your posts for all the different social networks in mere seconds. The tool builds customizable boards to organize categories and tags. For instance, if I’m a photographer who’s uploading tons of new photos each week to photodune, I will use my own “Photography” board with my own categories like”Beach” which will include all the tags that fit to describe beaches, by pressing the edit button, I could just add my own new tags and so on, the same goes for say a musician, video maker, and code developer. Here’s how you can use the tool: Go over to and log in with either your social accounts, or create an account by using your email address. After doing that you’ll be greated with the main screen, where you’ll immediately see some of the : tagsgenerator.com main features include Easy Copy/Paste and organizing of your tags. Custom separator and prefix. Chrome Extension Tags Presets Custom Boards Boards 1 .Boards: Here you add/edit/delete & favorite your boards2.Be sure to sign in to your account to keep your changes for the next time.3.The Setting gear.4.Your tags presets (Which will be also applied for your chrome extension)5.After choosing all to your tags you can now add your own presets by clicking on the’+’ sign.6.If all your tags are set, now you just have to press the green button which will execute the keyboard shortcut of CMD+C or Ctrl+c on a pc. Editing and Adding Tags. Hit the edit button for the edit mode.Enter your tag name and hit enter to add the tag to the list(it will order alphabetic )Press The red ‘X’ to erase the tags you don’t need for this board Settings Here you can choose any character to separate you tags.With the tag prefix you can choose the characters that will appear before the chosen tags.You also can choose the capitalization for your tagsIf you are viewing to many tags you can choose the see all the tags on a small font for your convenience.This line will show you the setting results . Chrome Extension With the help of the chrome extension you can access the tool easily to get to all your previously created presets. To add more presets simply go back to the main webpage. Hope you’ll enjoy using the Tags Generator! Here is how its looks like Here is the chrome extension More info about : Are you offering this helpful tool for free? This all started 3 years ago, when I’ve first learned about , and after getting my music track sold. I knew back then that my life was about to change completely and it really did! Envato Market From a musician working hard, 7 days a week, to make a living, here I am, finally having some free time for my family, myself and for creating and composing, which was my real passion in music. Since then, I’ve always looked at this amazing community and tried hard to figure out a way in which I can give something back, for all good things that it did for me in the past 3 years since I’ve been selling my music on . I thought to myself: “ ” AJ how can I really make something that would benefit all of us and help us with saving a little time, leaving us a little bit more time to create and focus on our music? I quickly found out that there isn’t really an easy way to fill in the submission tags field, so I figured I could make a small java code that will help me to copying and pasting my favorite tags. The only problem was: How can I do that if I don’t know a single line of code? :) This is why I love the internet! You can always learn everything by yourself! I took a fast course on JavaScript and started with this nice and simple code which back then I’ve posted on my composer website as a blog post. I got really great feedback and people were telling me how much they loved it! This is when I knew I just got what I’ve always wanted and that I was bringing back some love to all the amazing people on Envato. If I had everyone’s home address, I’d definitely send them flowers :) 2 years after gathering all the great feedback, from all around the community, I thought: “why not to take this tool one step further and make it a really standalone tool which not only could be helpful for my musician friends, but also for all other Envato authors?” This became one of my main goals when creating the website. In conclusion — yes its free and it will stay like that because this is my way to say “Thank you all for helping me to change my world.” :) www.TagsGenerator.com Hope you will like it, please let me know your thoughts.

How To Keep All your #Hashtags Organise in one place ? Introducing Tags Generator Web Tool.

Mastering the Craft of Transforming Data into Engaging Visual Narratives in User Interfaces

Authors:
(1) Prabath Jayatissa, University of Colombo
(2) Roshan Hewapathirane, University of Colombo Table of Links Abstract & Introduction Methodology Results Conclusion & References 2. METHODOLOGY The review article focuses on the issue of interoperability among health information systems in low and middle-income countries (LMICs). The methodology employed involves a rigorous process that includes several key steps. First, a comprehensive literature review encompasses relevant research articles, reports, and publications from reputable sources. The findings from the literature review are then synthesised to identify common challenges faced by LMICs in achieving interoperability in their health information systems. The challenges identified include a lack of standardisation, fragmented systems, limited resources, and data privacy concerns. These challenges hinder the seamless exchange of health information among different health information systems, leading to inefficiencies and suboptimal health outcomes.Next, the review article proposes strategies to enhance interoperability in LMICs. These strategies are derived from the analysis and interpretation of the literature findings. Proposed strategies include standardisation of data formats and protocols, consolidation of health information systems, investment in health IT infrastructure, and capacity building of health IT professionals in LMICs.Once the strategies are identified, the review article is organised and written, providing a concise and coherent overview of the current state of interoperability among health information systems in LMICs and potential strategies for improvement. The article is then revised and finalised for submission, taking into account feedback from peers and experts in the field. In summary, the methodology for the review article involves conducting a comprehensive literature review, synthesising findings, identifying challenges and strategies, analysing and interpreting results, and writing and finalising the article. The article provides insights into the current state and potential strategies for enhancing interoperability among health information systems in LMICs, to improve healthcare delivery and outcomes in these regions. 2.1. Literature Review Interoperability has been recognised as a critical factor for effective health information exchange and care coordination at the national and international levels1 . In LMICs, achieving interoperability among health information systems is particularly challenging due to various factors. Several studies have identified challenges to interoperability in LMICs, including: Lack of standardisation: LMICs often need morestandardised data formats, coding systems, and terminologies, which hinder the accurate and seamless exchange of health information (AdlerMilstein et al., 2013; Kamadjeu, 2019). This lack of standardisation makes integrating data from different sources challenging, resulting in fragmented and incomplete health information2 Fragmented health information systems: Many LMICs have fragmented health information systems, where different systems are used for different healthcare functions, such as patient registration, electronic health records (EHRs), and laboratory systems, leading to data silos3 . This fragmentation hampers the exchange of data across different systems, hindering interoperability. Limited resources: LMICs often need more resources, including limited funding, technical expertise, and infrastructure, which can pose challenges in implementing and maintaining interoperable health information systems4 .The high cost of health IT infrastructure, such as servers, software, and networking, can hinder achieving interoperability in LMICs. Data privacy and security concerns: Data privacy, security, and consent are critical concerns in health information exchange, and LMICs often lack robust policies, regulations, and safeguards to address these issues effectively5 . This can hinder the sharing of health information among different systems due to concerns about data breaches and misuse. Despite these challenges, several strategies have been proposed to enhance interoperability among health information systems in LMICs. Standardisation: Adoption of internationally recognised health IT standards, such as HL7 and SNOMED CT, can facilitate data standardisation and ensure consistency and accuracy of data exchange6 . Standardisation of data formats, coding systems, and terminologies can enable seamless data exchange and promote interoperability. Consolidation and integration: The integration of fragmented health information systems into a unified health information exchange (HIE) platform can facilitate data exchange and coordination of care7 . Developing national HIE policies and governance frameworks can support the establishment and sustainability of HIEs in LMICs. Investment in health IT infrastructure: Investment in health IT infrastructure, including hardware, software, and networking, is crucial for supporting interoperable health information systems8 .Partnerships and collaborations with governments, non-profit organisations, and the private sector can help overcome resource constraints and facilitate the development of robust health IT infrastructure. Capacity building and training: Capacity building and training programs for the health IT workforce can enhance technical expertise and knowledge in LMICs9 . Training programs can focus on building skills in health IT standards, data management, and interoperability concepts, Interoperability, the ability of different health information systems to exchange and use data seamlessly, is a critical factor for effective health information exchange and coordination of care at the national and international levels10. In LMICs, achieving interoperability among health information systems is particularly challenging due to various factors. Several studies have identified challenges to interoperability in LMICs, including lack of standardisation, fragmented health information systems, limited resources, and data privacy and security concerns11 . Lack of standardisation is a major challenge in LMICs, as they often needstandardised data formats, coding systems, and terminologies, which hinder the accurate and seamless exchange of health information12. Fragmented health information systems, which are used for different healthcare functions, such as patient registration, electronic health records (EHRs), and laboratory systems, must also be improved for interoperability12,21. This fragmentation leads to data silos, hindering data exchange across different systems. Limited resources, including funding, technical expertise, and infrastructure, are often faced by LMICs, which can pose challenges in implementing and maintaining interoperable health information systems13. The high cost of health IT infrastructure, such as servers, software, and networking, can hinder achieving interoperability in LMICs. Data privacy and security concerns are also critical challenges, as LMICs often lack robust policies, regulations, and safeguards to address these issues effectively9,10,11. This can hinder the sharing of health information among different systems due to concerns about data breaches and misuse. Despite these challenges, several strategies have been proposed to enhance interoperability among health information systems in LMICs. Standardisation, such as adopting internationally recognised health IT standards like HL7 and SNOMED CT, can facilitate data standardisation and ensure data exchange consistency and accuracy of data exchange9,21 . Consolidating and integrating fragmented health information systems into a unified health information exchange (HIE) platform can facilitate data exchange and coordination of care10,12,15. Investment in health IT infrastructure, including hardware, software, and networking, is crucial for supporting interoperable health information systems in LMICs7,9,11. Capacity building and training programs for the health IT workforce can enhance technical expertise and knowledge in LMICs, focusing on health IT standards, data management, and interoperability concepts13,14,16,20 Further research is needed to evaluate the impact of these strategies on improving interoperability, identifying novel approaches specific to LMICs, and addressing the unique challenges faced by different regions and contexts within LMICs. Additionally, research on the cost-effectiveness and sustainability of interoperable health information systems17,18,19. This paper is available on arxiv under CC 4.0 license. Authors: (1) Prabath Jayatissa, University of Colombo (2) Roshan Hewapathirane, University of Colombo Authors: Authors: (1) Prabath Jayatissa, University of Colombo (2) Roshan Hewapathirane, University of Colombo Table of Links Abstract & Introduction Abstract & Introduction Methodology Methodology Results Results Conclusion & References Conclusion & References 2. METHODOLOGY The review article focuses on the issue of interoperability among health information systems in low and middle-income countries (LMICs). The methodology employed involves a rigorous process that includes several key steps. First, a comprehensive literature review encompasses relevant research articles, reports, and publications from reputable sources. The findings from the literature review are then synthesised to identify common challenges faced by LMICs in achieving interoperability in their health information systems. The challenges identified include a lack of standardisation, fragmented systems, limited resources, and data privacy concerns. These challenges hinder the seamless exchange of health information among different health information systems, leading to inefficiencies and suboptimal health outcomes.Next, the review article proposes strategies to enhance interoperability in LMICs. These strategies are derived from the analysis and interpretation of the literature findings. Proposed strategies include standardisation of data formats and protocols, consolidation of health information systems, investment in health IT infrastructure, and capacity building of health IT professionals in LMICs.Once the strategies are identified, the review article is organised and written, providing a concise and coherent overview of the current state of interoperability among health information systems in LMICs and potential strategies for improvement. The article is then revised and finalised for submission, taking into account feedback from peers and experts in the field. In summary, the methodology for the review article involves conducting a comprehensive literature review, synthesising findings, identifying challenges and strategies, analysing and interpreting results, and writing and finalising the article. The article provides insights into the current state and potential strategies for enhancing interoperability among health information systems in LMICs, to improve healthcare delivery and outcomes in these regions. 2.1. Literature Review Interoperability has been recognised as a critical factor for effective health information exchange and care coordination at the national and international levels1 . In LMICs, achieving interoperability among health information systems is particularly challenging due to various factors. Several studies have identified challenges to interoperability in LMICs, including: Lack of standardisation: LMICs often need morestandardised data formats, coding systems, and terminologies, which hinder the accurate and seamless exchange of health information (AdlerMilstein et al., 2013; Kamadjeu, 2019). This lack of standardisation makes integrating data from different sources challenging, resulting in fragmented and incomplete health information2 Fragmented health information systems: Many LMICs have fragmented health information systems, where different systems are used for different healthcare functions, such as patient registration, electronic health records (EHRs), and laboratory systems, leading to data silos3 . This fragmentation hampers the exchange of data across different systems, hindering interoperability. Limited resources: LMICs often need more resources, including limited funding, technical expertise, and infrastructure, which can pose challenges in implementing and maintaining interoperable health information systems4 .The high cost of health IT infrastructure, such as servers, software, and networking, can hinder achieving interoperability in LMICs. Data privacy and security concerns: Data privacy, security, and consent are critical concerns in health information exchange, and LMICs often lack robust policies, regulations, and safeguards to address these issues effectively5 . This can hinder the sharing of health information among different systems due to concerns about data breaches and misuse. Despite these challenges, several strategies have been proposed to enhance interoperability among health information systems in LMICs. Standardisation: Adoption of internationally recognised health IT standards, such as HL7 and SNOMED CT, can facilitate data standardisation and ensure consistency and accuracy of data exchange6 . Standardisation of data formats, coding systems, and terminologies can enable seamless data exchange and promote interoperability. Consolidation and integration: The integration of fragmented health information systems into a unified health information exchange (HIE) platform can facilitate data exchange and coordination of care7 . Developing national HIE policies and governance frameworks can support the establishment and sustainability of HIEs in LMICs. Investment in health IT infrastructure: Investment in health IT infrastructure, including hardware, software, and networking, is crucial for supporting interoperable health information systems8 .Partnerships and collaborations with governments, non-profit organisations, and the private sector can help overcome resource constraints and facilitate the development of robust health IT infrastructure. Capacity building and training: Capacity building and training programs for the health IT workforce can enhance technical expertise and knowledge in LMICs9 . Training programs can focus on building skills in health IT standards, data management, and interoperability concepts, Interoperability, the ability of different health information systems to exchange and use data seamlessly, is a critical factor for effective health information exchange and coordination of care at the national and international levels10. In LMICs, achieving interoperability among health information systems is particularly challenging due to various factors. Several studies have identified challenges to interoperability in LMICs, including lack of standardisation, fragmented health information systems, limited resources, and data privacy and security concerns11 . Lack of standardisation is a major challenge in LMICs, as they often needstandardised data formats, coding systems, and terminologies, which hinder the accurate and seamless exchange of health information12. Fragmented health information systems, which are used for different healthcare functions, such as patient registration, electronic health records (EHRs), and laboratory systems, must also be improved for interoperability12,21. This fragmentation leads to data silos, hindering data exchange across different systems. Limited resources, including funding, technical expertise, and infrastructure, are often faced by LMICs, which can pose challenges in implementing and maintaining interoperable health information systems13. The high cost of health IT infrastructure, such as servers, software, and networking, can hinder achieving interoperability in LMICs. Data privacy and security concerns are also critical challenges, as LMICs often lack robust policies, regulations, and safeguards to address these issues effectively9,10,11. This can hinder the sharing of health information among different systems due to concerns about data breaches and misuse. Despite these challenges, several strategies have been proposed to enhance interoperability among health information systems in LMICs. Standardisation, such as adopting internationally recognised health IT standards like HL7 and SNOMED CT, can facilitate data standardisation and ensure data exchange consistency and accuracy of data exchange9,21 . Consolidating and integrating fragmented health information systems into a unified health information exchange (HIE) platform can facilitate data exchange and coordination of care10,12,15. Investment in health IT infrastructure, including hardware, software, and networking, is crucial for supporting interoperable health information systems in LMICs7,9,11. Capacity building and training programs for the health IT workforce can enhance technical expertise and knowledge in LMICs, focusing on health IT standards, data management, and interoperability concepts13,14,16,20 Further research is needed to evaluate the impact of these strategies on improving interoperability, identifying novel approaches specific to LMICs, and addressing the unique challenges faced by different regions and contexts within LMICs. Additionally, research on the cost-effectiveness and sustainability of interoperable health information systems17,18,19. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Unraveling Interoperability Challenges in LMIC Health Information Systems

Navigating the Web3 Security Frontier: Insights from GoPlus Labs' Latest Report It's hard to stress enough how important it is to impose strict security measures in the Web3 world, which changes so quickly. If you want to know how to use user security data for risk management in Web3, GoPlus Labs is the leader in its field and gives you the information you need. On top of that, the internet world is spreading out more at this point. New report from them, "Uncharted Consensus: The Widespread Use and Potential of User Security Data in Web3," is a big step towards understanding the problems and chances in the Web3 security system. A Deep Dive into Web3 Security Trends A pioneer in the field of Web3 security, GoPlus Labs, has disclosed data that shed light on the growing need for sophisticated security technologies that are capable of securing digital assets, validating the validity of non-fungible tokens (NFTs), and monitoring decentralised applications (dApps) for potential risks. This rise in demand has been brought about as a consequence of the growing usage of GoPlus's application programming interface (API) suite. This suite offers stakeholders a comprehensive look into the vulnerabilities and health of cryptocurrencies, non-fungible tokens (NFTs), and decentralised apps (dApps). Adding application programming interfaces (APIs) to the Web3 environment, like the Token Risk API, the NFT Risk API, and the dApp Security API, shows that the company is taking a proactive approach to finding and managing risks. It's especially interesting that the study shows that these application programming interfaces (APIs) are being used a lot more. Starting in November 2023, the Token Risk API will see over 20 million calls per day. This is a very important discovery that needs extra attention. As dangers have grown in the security business, there has been a movement towards strategic risk management. This change is shown by the rise in uses. A Call to Action for Comprehensive Security Measures If there is one thing that people should take away from GoPlus's study, it is that Web3 security data is very important for dealing with the complicated risk situation. As the digital world continues to grow quickly, it's becoming more and more important to have extensive protection knowledge. This encourages not only the development of new security measures, but also an organised effort to teach users about possible threats and raise knowledge of those threats. A lot of progress has been made by GoPlus Labs in making the Web3 environment safer with projects like the Secscan security engine and the launch of the GoPlus Token. Getting people involved in these projects makes the Web3 world safer and more user-friendly. GoPlus Labs wants to make users safer by using open, AI-powered danger detection and distributed data solutions. This paper's results show how dedicated they are to that goal. The Evolving Threat Landscape and User Security Insights The GoPlus analysis provides an analytical view on the "high-risk" tokens and NFTs, revealing a danger environment that is just as dynamic as the cryptocurrency market itself. It is important to note that the majority of these tokens have been banned or recognised as honeypots, which highlights the dynamic nature of the security vulnerabilities that are present in Web3. A further demonstration of the ever-evolving strategies used by malicious actors is provided by the growing occurrence of problems with non-fungible tokens (NFTs), such as unauthorised transfers and systems that self-destruct. Due to the fact that the research also emphasises the various degrees of user involvement and security issues that are present across various blockchain ecosystems, this complex web of security difficulties is not uniform across the board. BNB Chain, for example, emerged as a prominent participant throughout the study period, using GoPlus APIs more than 92.7 million times. This demonstrates a strong community commitment to reducing the risks associated with security. Don’t forget to like and share the story! This author is an independent contributor publishing via our brand-as-author program. Be it through direct compensation, media partnerships, or networking, the author has a vested interest in the company/ies mentioned in this story. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure:

Redefining Digital Safety: How GoPlus Labs is Leading Web3 Security Innovations

ডিজিটাল নিরাপত্তার পুনঃসংজ্ঞায়িত করা: GoPlus ল্যাবস কিভাবে Web3 নিরাপত্তা উদ্ভাবনের নেতৃত্ব দিচ্ছে

Digitale Sicherheit neu definiert: Wie GoPlus Labs Web3-Sicherheitsinnovationen anführt

Redefiniendo la seguridad digital: cómo GoPlus Labs lidera las innovaciones de seguridad Web3

Redéfinir la sécurité numérique : comment GoPlus Labs mène les innovations en matière de sécurité Web3

डिजिटल सुरक्षा को पुनर्परिभाषित करना: कैसे गोप्लस लैब्स वेब3 सुरक्षा नवाचारों का नेतृत्व कर रही है

デジタル セーフティの再定義: GoPlus Labs が Web3 セキュリティ イノベーションをどのようにリードしているか

디지털 안전의 재정의: GoPlus Labs가 Web3 보안 혁신을 주도하는 방법

Redefinindo a segurança digital: como o GoPlus Labs está liderando as inovações em segurança da Web3

Переосмысление цифровой безопасности: как GoPlus Labs лидирует в инновациях в области безопасности Web3

Dijital Güvenliği Yeniden Tanımlamak: GoPlus Labs Web3 Güvenliği Yeniliklerine Nasıl Liderlik Ediyor?

Định nghĩa lại An toàn kỹ thuật số: Cách GoPlus Labs dẫn đầu các cải tiến về bảo mật Web3

重新定义数字安全：GoPlus Labs 如何引领 Web3 安全创新

This paper is available on arxiv under CC 4.0 license. Authors: (1) Ayei E. Ibor, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (2) Mark Hooper, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (3) Carsten Maple, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (4) Gregory Epiphaniou, WMG, University of Warwick, United Kingdom. Table of Links Abstract & Introduction Background Review of Literature Methodology Discussion of Findings Conclusion and Future Work & References Abstract Foundational identity systems (FIDS) have been used to optimise service delivery and inclusive economic growth in developing countries. As developing nations increasingly seek to use FIDS for the identification and authentication of identity (ID) holders, trustworthy interoperability will help to develop a cross-border dimension of e-Government. Despite this potential, there has not been any significant research on the interoperability of FIDS in the African identity ecosystem. There are several challenges to this; on one hand, complex internal political dynamics have resulted in weak institutions, implying that FIDS could be exploited for political gains. On the other hand, the trust in the government by the citizens or identity holders is habitually low, in which case, data security and privacy protection concerns become paramount. In the same sense, some FIDS are technology-locked, thus interoperability is primarily ambiguous. There are also issues of cross-system compatibility, legislation, vendor-locked system design principles and unclear regulatory provisions for data sharing. Fundamentally, interoperability is an essential prerequisite for e-Government services and underpins optimal service delivery in education, social security, and financial services including gender and equality as already demonstrated by the European Union. Furthermore, cohesive data exchange through an interoperable identity system will create an ecosystem of efficient data governance and the integration of cross-border FIDS. Consequently, this research will seek to identify the challenges, opportunities, and requirements for cross-border interoperability in an African context. Our findings show that interoperability in the African identity ecosystem is vital to strengthen the seamless authentication and verification of identity holders for inclusive economic growth and widen the dimensions of e-Government across the continent. Keywords: cross-border interoperability, digital identity, trustworthiness, e-Government 1. Introduction One of the Sustainable Development Goals (SDGs) of the United Nations is to provide legal identity for all citizens, which also includes birth registration by 2030 (World Bank Group, 2018). Primarily, identification allows individuals to exercise their rights to be identified and legally recognised while the government and private sector depend on it for effective service delivery. In this sense, a national identity system is crucial to the identification and authentication of natural or legal persons and provides a means for citizens to access critical services including participation in formal political, social, and economic life (Gelb and Metz, 2018). Achieving sustainable development is a key consideration of most national governments and forms the basis for inclusive and responsible identification schemes at the foundational level. Fundamentally, national identification schemes are the pivot for social security, immigration, financial and economic inclusion, healthcare, voting, gender equality, transportation, and education (Colbern and Ramakrishnan, 2018). Consequently, identity management plays a key role in promoting e-government by bringing services closer to the people. Modern identification systems are robust tools for the delivery of transparent administration, reduction in fraud and leakages for social benefits, providing adequate security for the citizens, extracting accurate biographic data for effective economic planning, and responding to natural disasters (Atick, 2016). These seeming benefits are yet to solve the identification crisis in most developing nations as about 850 million people across the globe are yet to have access to a valid identity credential, mostly in sub-Saharan Africa and South Asia (The World Bank, 2023a). According to the World Bank Identification for Development (ID4D) dataset (The World Bank, 2023a), most people without official identification are residents of low-income countries. These sets of persons also include marginalised and vulnerable groups consisting of children, whose births were not documented in the civil registry of the affected country, women in rural areas with no access to digital services, and adults below the age of 25 years. Particularly, digital identification systems can improve how the public and commercial sectors provide services and lay the groundwork for new markets, services, and systems, such as egovernment, cashless transactions, and the digital economy. Identification systems must, however, have high levels of coverage and inclusion within the population, be resilient to fraud and error, operate within a governance framework that protects personal data, fosters trust and accountability, and facilitates end-user control to fulfil their potential for facilitating sustainable development and increasing public sector efficiency (African Union, 2020; Bandura and Ramanujam, 2021). There is a growing demand for digital identity to be mutually recognised and portable between countries in the modern digital age through an interoperability framework and in the context of regional and global integration and migration, which can be facilitated through trust and standards. Interoperability, in this context, refers to the ability of disparate foundational identity systems to exchange data through seamless communication of identification and authentication information. These exchanges must be trustworthy or inherently secure, available, and reliable. Although there are complex internal political dynamics in most developing countries that result in weak institutions, and the lack of trust in government by the citizens including the notion of security and privacy protection concerns, legislation, cross-system compatibility, vendor-locked system design principles and unclear regulatory provisions for data sharing, our findings show that interoperability is vital to widen the dimensions of e-Government. In this paper, the challenges, opportunities, and requirements for trustworthy cross-border interoperability are discussed. The rest of the paper is organised as follows; in Section 2, the background to the study is given while in Section 3, a review of literature is discussed. Section 4 presents the methodology of the research. In Section 5, the discussion of findings is presented, and the conclusion and future work is given in Section 6. This paper is available on under CC 4.0 license. Arxiv

A Trustworthy Cross-Border Interoperable Identity System for Developing Countries: The Beginning

This paper is available on arxiv under CC 4.0 license. Authors: (1) Vianney Brouard, ENS de Lyon, UMPA, CNRS UMR 5669, 46 All´ee d’Italie, 69364 Lyon Cedex 07, France; E-mail: vianney.brouard@ens-lyon.f. Table of Links Abstract & Introduction and presentation of the model Main results and biological interpretation First-order asymptotics of the mutant sub-populations for an infinite mono-directional grap First-order asymptotics of the mutant sub-populations for a general finite trait space (Theorem 2.1) Convergence for the stochastic exponents (Theorem 2.2) Acknowledgements & References Abstract We aim at understanding the evolution of the genetic composition of cancer cell populations. To this aim, we consider a branching individual based model representing a cell population where cells divide, die and mutate along the edges of a finite directed graph (V, E). The process starts with only one cell of trait 0. Following typical parameter values in cancer cell populations we study the model under large population and power law mutation rates limit, in the sense that the mutation probabilities are parameterized by negative powers of n and the typical sizes of the population of our interest are positive powers of n. Under non-increasing growth rate condition (namely the growth rate of any sub-population is smaller than the growth rate of trait 0), we describe the time evolution of the first-order asymptotics of the size of each sub-population on the log(n) time scale, as well as in the random time scale at which the initial population, resp. the total population, reaches the size n t . In particular, such results allow to characterize whose mutational paths along the edges of the graph are actually contributing to the size order of the sub-populations. Without any condition on the growth rate, we describe the time evolution of the orders of magnitude of each sub-population. Adapting techniques from [13], we show that these converges to positive deterministic non-decreasing piecewise linear continuous functions, whose slopes are given by an algorithm. Keywords: cancer evolution, multitype branching processes, finite graph, long time behavior, power law mutation rates, population genetics. 1 Introduction and presentation of the model In the present work the population of cells will be studied in different time-scales: the random timescale and the following deterministic approximation where For any finite oriented labeled graph (V, E, L) under the following non-increasing growth rate condition Without any assumption on the growth rate function λ, the study is made on the deterministic timescale of Equation (4). As in [13, 3, 5, 8, 14, 2, 30] the asymptotic behaviors are obtained on the following stochastic exponent processes The results are presented in Theorem 2.2. It is the exponent as a power of n that is tracked for any sub-populations, whereas Theorem 2.1 gives directly the size order on n, this is a refined result. Up to our knowledge, it is the first model considering the power law mutation rates regime (1) capturing this level of refinement on the asymptotic behaviors. Two new significant results emerge. First it shows the remarkable result that under Assumption (5) the randomness on the first-order asymptotics of any mutant sub-populations is fully given by the stochasticity of only one random variable W -encoding the randomness on the long time for the lineage of wild-type cells issued from the initial cell. It means that the stochasticity for any mutant sub-population is fully driven, at least at the first-order asymptotics, by the randomness on the growth of the wild-type population and not from the dynamics of any lineage of a mutant cell, as well as the stochastic processes generating mutations. Second it characterizes exactly whether a mutational path on the graph structure of the trait space asymptotically contributes to the growth of the mutant sub-populations. Whereas having asymptotic results on the stochastic exponents only allows to discriminate some paths and not to determine exactly whose paths are actually contributing to the asymptotic growth of the mutant sub-populations. More precisely, if the weight of a path is defined as the sum of the label of its edges, asymptotic results on the stochastic exponent gives that for every trait v, among the paths from 0 to v only those with the less weight might contribute to the asymptotic growth of trait v. On the contrary, having results directly on the first-order asymptotics of the mutant sub-populations allows to discriminate among those paths with the less weight those which actually contributes to the dynamics of trait v. In particular among those paths with the less weight only those with the maximal number of neutral mutations on their edges have an asymptotic impact on the growth of trait v. Indeed an additional multiplicative factor of order log(n) for each neutral mutation of a path is captured when looking at the first-order asymptotics and is obviously not captured with asymptotic results only on the stochastic exponents. Moreover it is the first time that this power-law mutation rates regime is studied in the random timescale of Equation (3) up to our knowledge. From the biological point of view it is more interesting to get result on such random time-scale instead of the deterministic one. We obtain that the randomness on the first-order asymptotics of any mutant sub-populations is fully given by the stochasticity on the survival of the lineage of wild-type cells issued from the initial cell. As in [7, 6], compared to the different models in [13, 3, 5, 8, 14, 2, 16], the initial population Z (n) (0) is not assumed to have a macroscopic size. It introduces a supplementary randomness on how the wild-type population is stochastically growing to get a macroscopic size. But contrary to [7, 6], we do not condition on the survival of the wild-type population or on the stopping times of Equation (3) to be finite. In [28] Nicholson and Antal study a similar model under a slightly less general non-increasing growth rate condition. More precisely, in their case all the growth rates of the mutant populations are strictly smaller than the growth rate of the wild-type population: ∀v ∈ V \{0}, λ(v) < λ(0). But the main difference remains the mutation regime. In their case, only the last mutation is in the power law mutation rates regime, all other mutations have a fixed probability independent of n. In Theorem 2.1 the case where all mutations are in the power law mutation rates regime is treated. Also Nicholson and Antal are interested in obtaining the distribution of the first time that a mutant sub-population gets a mutant cell. Whereas in the present work the first-order asymptotics of the sizes of the mutant sub-populations over time are studied. In [29] Nicholson, Cheek and Antal study the case of a mono-directional graph where the time tends first to infinity with fixed mutation probabilities. In particular they obtain the almost sure first-order asymptotics of the size of the different mutant sub-populations. Under the non-increasing growth rate condition, they are able to characterized the distribution of the limit random variables they obtained. Without any condition on the growth rates, they study the distribution of the random limit they obtained under the small mutation probabilities limit, using the hypothesis of an approximating model with less stochasticity. Notice that the mutation regime they study is not the large population power law mutation rates regime of Eq. (1) as considered in the present work. Under the latter regime both the size of the population goes to infinity and the mutation probabilities to 0, through the parameter n, see Equation (1). In [18] Gunnarson, Leder and Zhang study a similar model as the one in the present work and are also interested in capturing the evolution over time of the genetic diversity of a population of cells, using in their case the well-known summary statistic called the site frequency spectrum (SFS). The main difference is the mutation regime because they are not considering the power law mutation rates limit. In their case the mutation probabilities are fixed. Also, they restrict the study to the neutral cancer evolution case. In particular, as in the present work, they capture the first-order asymptotics of the SFS at a fixed time and at the random time at which the population first reaches a certain size. Two noticeable similarities in the results are that the first-order asymptotics of the SFS converges to a random limit when evaluated at a fixed time and to a deterministic limit when evaluated at the stochastic previous time. One could argue that in the present work the correct convergence for the latter case is actually a stochastic limit. But the stochasticity is fully given by the survival of the initial lineage of cells of trait 0, so conditioned on such an event at the end the limit is a deterministic one. In particular the results of Gunnarson, Leder and Zhang are all conditioned on nonextinction of the population. In [16] Gamblin and Lambert study a model of an exponentially growing asexual population that undergoes cyclic bottlenecks under the large population power law mutation rates regime. Their trait space is composed of 4 sub-populations 00, 10, 01 and 11, where two paths of mutations are possible 00 7→ 10 7→ 11 and 00 7→ 01 7→ 11. They study the special case where one mutation (10) has a high-rate but is a weakly beneficial mutation whereas the other mutation (01) has a low-rate but is a strongly beneficial mutation. In particular they show the noticeable result that due to cyclic bottlenecks only a unique evolutionary path unfolds but modifying their intensity and period implies that all paths can be explored. Their work relies on a deterministic approximation of the wild-type sub-population 00 and some parts of the analysis of the behavior of the model is only obtained due to heuristics. The present work, and more specifically Theorem 2.2 because they are considering selective mutations, can be used and adapted to consider the case of cyclic bottlenecks in order to prove rigorously their results, in the specific trait space that they consider as well as on a general finite trait space. The rest of the paper is organised as follows. In Section 2 the results and their biological interpretations are given. Sections 3 and 4 are dedicated to prove Theorem 2.1, which assumes Equation (5). In Section 3 the mathematical definition of the model is given for an infinite mono-directional graph as well as the proof in this particular case. The generalisation of the proof from an infinite mono-directional graph to a general finite graph is given in Section 4. In Section 5, Theorem 2.2 is proved adapting results from [13].

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