Valariis in the Alternative Lending Industry

Valari

valari

Howdy Hackers! I’m Valerie and I’m in Business Operations @ Squad, a payment company in Nigeria. First off, I’d like to express my gratitude to the staff, and all other beautiful humans of HackerNoon, for nominating me for a 2022 Noonies award! I’ve been nominated for the following categories and if you think my writing offers good value, please take some time to check out these award pages and vote for me: HACKERNOON CONTRIBUTOR OF THE YEAR- HUMOR ALL ABOUT TEAMWORK As a writer in the tech industry, I believe that Fintech is the most exciting technology of the present because the world revolves around technology, payments, and finance. The interview below explains my views on embedded finance and my journey in the tech industry. 1. What do you currently do and what’s your favorite part about it? I work in a payment company - Squad in Nigeria. We launched in June 2022 and it’s been an exciting experience so far. The best part of what I do is having to interact with customers, getting to know how Squad has helped them with their payment needs. Getting to discover how much more we can enhance the product to suit their needs even better. The truth is every great product starts and ends with our customers and we never want to lose sight of that. 2. How did you get started with your Tech Career? I started my career in the bank even though I majored in CS. In my country at the time, it was the next best field for new graduates if they could not get into oil and gas. I started in customer service and gradually moved to different departments in the company. Teller services, loans, products, promotions, e-commerce, and experiential marketing with a lot of focus on SMEs. This was the discovering phase of my corporate life and I’m thankful for the exposure. With the proliferation of fintech and my experience, my move into the fintech space was only natural and I’m excited about the future. 3. If Utopia were a color what color do you think it’d be and why? I would choose blue. Why blue? Well for one, it’s my favorite colour. 🙂 Many illustrations - blue skies, blue seas, blue eyes, etc. - most times evoke peace, tranquility, and security and these are the elements that foster inspiration and innovation, especially in a world of chaos and instability. 4. If everything about HackerNoon changed drastically, what is one detail you’d like to keep exactly the same?  OR What’s your favorite thing to do with HackerNoon and why? The liberty to write as one chooses - as freely but as humanely as possible. 5. Tell us more about the things you write/make/manage/build! My love for writing started some twenty-something years ago. I never knew I was capable of writing till I tried it one day. I like writing about my experiences and the experiences of others. I particularly love humorous content. I have always believed that if written content, without the help of facial expressions, body movements, videos, pictures, or sound, was hilarious, then, the humor was as original and existential as can be. Humor in tech takes it to a whole new level because let’s face it, technology is generally perceived to be a field that’s for nerds and geeks who need to be serious to be taken seriously which is one of the reasons why I love stories on HackerNoon. It’s home to several talented, charismatic and amusing tech writers. 6. What’s your favorite thing about the internet? I live for the memes on the internet. On any platform, I find them but more like on a place like HackerNoon that already encourages this. Humor just like Love is all around us and in us. Like with all skills, it takes a bit of soul searching to discover, harness, and nurture them but it’s there. It never left. And while adulthood has a way of damping that inner child that loves to laugh, we have to protect that child within cause without it, we start to lose our essence, our humanity, our soul. 7. It’s an apocalypse of ‘walking dead’ proportions and you can only own a singular piece of technology, what would it be? It has to be a mobile phone for me. Beyond the primary reason for mobile phones which is the ease of communication, the mobile phone has become a necessary piece of technology able to provide multiple functions. As with several devices or tech tools, without access to the internet, there’s a limit to how much a phone can do these days but I have now come to accept my mobile phone does so much for me without me realizing it. 8. What is your least favorite thing about the internet? The intrusion and lack of privacy get to me now and then. I recall times when I needed to search the internet for a word or item but I’ll have to open a web browser in incognito mode to avoid getting flustered with unending product recommendations from google. And I’m sure this still does not puts me in the clear from robots eavesdropping on my conversations. 9. If you were given $10 million to invest in something today what would you invest in and why? In my country, where commerce is limited by so many crucial factors, I would want to do something different in the commerce space. Using creative and practical ways to solve problems on funding, logistics, sourcing, distribution, and everything along the supply chain. 10. What’s something you’re currently learning or excited to learn? I recently came across the learning platform . I have been learning about UX/UI on and off but am excited to take an actual course and start applying myself in this somewhat new territory. interaction design foundation 11. Would you rather travel 10 years into the past or 10 years into the future? Give reasons for your answer. Why do I feel like this is a trick question? lol 10 years in the past will have me looking younger so I’ll definitely be rooting for that if it’s up for voting 😄 I have been fortunate in the past 10 years and TBH, I’ll love to do it all again but maybe a little differently, not because I have regret but rather to have more impact with what I now know.

Teamwork, Humor and Fintech: Interview with 2022 Noonies Nominee Valerie Ejegi 

HackerNoon Reporter: Please tell us briefly about your  background. Hi, I’m Valerio, software engineer, bass player, and CTO at Inspector. I spent the last 10 years working as a software developer in Europe. Since the beginning of my career my dream was to build a sustainable SaaS company able to make other developers’ lives easier. After two years as a software engineer at Ericsson I left my job to start my own company with two friends and follow my dream. I have published many MVPs and the first times were obviously failures but I learned many lessons and now I’m running . Inspector What's your company called? And in a sentence or two, what does it do? Inspector is a Code Execution Monitoring tool that helps software developers identify bugs and bottlenecks in their application before users stumble onto the problem. What is the origin story? The idea behind Inspector was to create a monitoring environment specifically designed for software developers avoiding any server or infrastructure configuration that many developers hate to deal with. In fact, thanks to Inspector, you will never have the need to install things on the server or make complex configuration at the infrastructure level. It works with a lightweight software library that you can install in your application like any other dependency based on the framework you used to build your backend (Laravel, Symfony, Nodejs, etc.). I myself am one of those developers who hates installing and configuring software at the server level, because these installations are out of the software development lifecycle, or are even managed by external teams. Forcing teams with different goals (Developers, IT infrastructure, Cyber Security, etc.) to work on the same tools can cause confusion or compromise the ability of developers to quickly identify and resolve problems within applications. Inspector allows developers to have a code-driven monitoring environment completely under their control. What do you love about your team? Two things probably closely related to each other: Their ability to listen; Their minds are open to change; Working together for eight years we have created a safe space to post any doubts, questions or experiments trying to build a better future for the company. If you weren’t working at your company, what would you be doing? I would certainly work in the technology space. I’ve experienced working in a big enterprise but it isn’t the right environment for me. Without my company I would be on the team of a startup somewhere in Europe. At the moment, how do you measure success? What are your core metrics? Our business has two main branches where success is measured in different ways. The SaaS platform, with a plug&play experience perfect for startups, small/medium developer teams, and the on-premise installation for big enterprises with dedicated technical support. The enterprise segment moves slower than the SaaS, so in terms of speed of growth SaaS is the most important unit of our business. The SaaS segment is built around the typical metrics of any subscription based business (LTV, CAC, etc). But the most important component of our success is “Content Marketing”. Transfering our experience in valuable contents that other developers can read and replicate is the real driver of our growth. It’s our way to help our community to overcome their bottlenecks and use our product with the highest return possible. Measuring the trend of the organic traffic is like measuring the trend of the trust that developers have in our work. What’s most exciting about your company traction to date? The most exciting thing about our journey is the opportunity to collaborate with other professionals all around the world. It’s the SaaS model DNA I think. Our customers come from Singapore, USA, Chile, Kenya, France, Germany, Indonesia, Hong Kong, and many other countries. Thanks to the web you can be global from day one. Awesome! What technologies are you currently most excited about, and most worried about? And why? We are a team of PHP enthusiasts. Inspector is a PHP application itself. Since the release of PHP 7 we have seen a professional growth of this ecosystem and it was the first technology supported by Inspector. It is a full-featured object oriented programming language with excellent performance and the largest offering of open source libraries and tools. Recently we have implemented a little micro-service in NodeJs to optimize the performance of a particular task inside our system so we used this experience to implement Inspector’s NodeJs integration library. It’s an ongoing project because the asynchronous nature of NodeJs makes it a really tricky technology for backend development. What drew you to get published on HackerNoon? What do you like most about our platform? I personally dedicate up to five hours per week to reading the experiences of other founders. I’m always looking for new ideas, ways to avoid mistakes, and evaluating new strategies that could help me to obtain concrete results. I believe that learning from other’s experiences is an extremely valuable process. HackerNoon is one of the most relevant containers of this great content and has helped me to satisfy this need. So I love the opportunity to be an active part of this community and help others as well. What advice would you give to the 21-year-old version of yourself? Start to learn things outside of the institutional environment (family, school, university, etc.). Read books, join in more communities, don’t judge, and keep your mind open. What is something surprising you've learned this year that your contemporaries would benefit from knowing? If I had to be honest it’s not in the professional field. I learned of my father’s illness so in 2021 I began to understand how much value there is in small daily gestures. This experience helped me to face difficult moments with a different approach, listen more, and turn off unnecessary hysteria when faced with a problem. In a way, I have reconsidered the meaning of the word “problem”. I have certainly become more sensitive to the requests of my collaborators and feel a duty to help anyone who has the strength to ask for help. You can also vote for Inspector to become the Startup of the Year in Naples, Italy

"Make Other Developers’ Lives Easier" Valerio Barbera, CTO at Inspector

As our world approaches the time where artificial intelligence becomes as widespread as electricity, we sat down with Valeria Sadovykh, a leading expert in the decision making and decision intelligence aspects of AI. Valeria holds a Ph.D. from the University of Auckland Business School and has over 10 years of experience focusing her efforts on emerging technologies with PwC in New Zealand, Singapore, and the US. The future will be focused on collaboration between humans and machines. In your recent piece on VentureBeat , you stated that AI needs human input to predict crises and crucial decisions. On the other hand, you say that it’s nearly impossible to predict an important event because they are all unique. Do you think it’s ever going to be possible to predict the next pandemic like the current coronavirus? How exactly can we train AI for that? Factually speaking, historical data is the key variable for predicting any events, whether it’s a pandemic, financial crisis, or natural disaster. The success rate of a prediction depends on the quantity and quality of the data available so that a data scientist can run successful algorithms. However, if we want to predict a black swan, we need to have a lot more pandemics and crises around us to get better at prediction. Thankfully, such events are sparse. Moreover, to learn from the historical data, we need to generalize rules for the future. AI systems should be proficiently analyzing millions of what-if scenarios to answer and react on in the future. We also need to empower AI through continued model optimization and self-learning. There are more than 2.5 created daily, and that pace is only accelerating. Solutions like (AutoML) platforms can automate the ingestion of a variety of data formats, running several algorithms on the same data set, and selecting the best algorithms for decision-making models. ML will never stop learning with continuous optimization of hyperparameters, random and grid search. quintillion bytes of data automation in machine learning We all know about AI’s ability to remember, but fail to consider its ability to forget the data. During COVID, the AI was partly successful in building models on tactical issues, such as prediction and recognition of symptoms, as well as contact tracing and tracking how the disease spread by reading various data points and other preventive measures. However, it failed at predicting cognitive human behavior, reactions, and its impact on daily decision-making. The irrational behavior of stocking up on toilet paper and Clorox had not been foreseen by either AI or traditional forecasting techniques. This historical experience has been collected in various data points, however, this doesn’t mean that every time we face a new viral disease, AI should push us to the pandemic shopping list. As we are empowering AI, we should make sure it serves for the good. What are the main principles people should follow while working on AI? Do you think there should be an obligatory course on ethics for software engineers as well as scientists, similar to those that doctors and journalists have at universities? What should be included? The AI systems are designed by qualified and intelligent individuals, but it still becomes a victim of biases, because it’s led by humans. An algorithm that was built by someone without proper ethical training and then used by likewise users without established controls and governance could produce serious errors and threats to human privacy, dignity, safety, and even create additional discrimination. We need to educate our society on responsible AI and ethics concerns. Not many people understand the impact of the recent push of face tracking and video surveillance tools. This is the job of our scientists, governments, and policymakers. There are initiatives by government agencies, for example, , as well as by the that proposed an AI Governance Framework and Assessment guide. The tech giants, such as , , and IBM are also proposing their own Responsible AI principles on the development and usage of AI. However, currently, these policies serve as recommendations rather than regulations. AI.gov World Economic Forum Google Microsoft We should also think about the consequences of excessive emerging tech usage in daily life and the impact of it on the cognitive thinking processes. While using predictable mechanisms and recommender systems created by AI, brain cell activation is actually reduced. I would also like to bring attention to the recent hype of the “working from home” trend. I’m not sure organizations, individuals, and the government have realized the impact of it and how it invades people’s privacy. We need to ensure that AI mechanisms are protective and take into account privacy, security, consent, access, transparency, explainability, etc. This requires a serious AI culture makeover, and we need to make sure AI is not only protecting shareholders but also us - average citizens. Where is the fine line between empowering AI and making it lead our decisions? Can you imagine a situation where the machine gets power over humanity? In the late 2000s, when the tech became affordable to the developing ,  people started to handover their decision giving power to machines without even realizing it. As part of my academic research, I’ve been studying how emerging tech impacts human decision-making through the longitudinal convergent observation of online communities for over 10 years. One of the main findings was the evidence that people outsource their decision-making process to the online wisdom of crowds, which is a heavily machine-manipulated environment. Specifically, people bypass their design thinking phase and go straight to the “choice” phase by selecting already available choices that are presented in an online environment for them. Automation of recruitment, credit card applications, loan approvals, robo-advisers, and health checking processes are some examples of machines with applied biases making decisions for us. world For those who doubt the age of spiritual machines, , a prediction model created by Intel co-founder, Gordon Moore, has been already proved accurate for several decades and used by many conglomerates to guide long term strategy planning. One thing that AI is not fully capable of yet is capturing our emotions, brain and mind. Our thinking contradicts ourselves, so it’s hard to build a statistical model. On the other hand, cases such as humanity can already be defeated by AI, at least in strategic games. Moore's law AlphaGo beating humans at the game Go shows that We already see how authoritarian governments use technology -  facial recognition, for instance - to keep track of people no matter whether they give permission or not. How can we make sure people in power don’t take advantage of it to the detriment of others? All the technology, including facial recognition, social tracking and activities tracing, are fantastic innovations and have been designed with good intentions. However, they put pressure on privacy and human freedom. This goes back to the educational and policy initiatives which we touched on before. How informed is our society on the usage of those technologies? Have we been transparent on what data we are collecting from each individual? The answer is no. First and foremost, it is self and institutional education that is currently not in place. Tesla CEO Elon Musk admitted that “excessive automation” at his company was a mistake, saying that technology can’t really remove humans. Companies tend to eliminate humans because robots are more consistent and cost less, which eventually can lead to overbalance and lack of critical thinking. How should a leader decide where they replace a human with or robot and where not? Many organizations face cost pressure and require innovation to bring more efficiency into their operation. Intelligent Automation is not a radical loss of a job that brings with it less critical thinking. It is actually the opposite -- a loss of mundane tasks and the creation of more critical thinking. Industries are creating higher-value jobs where more intellect will be required and new skills will be necessary. The collaborative workplace between humans and machines will be beneficial in the long term. It’s widely discussed, and many educational institutions and companies are proposing workforce transformation roadmaps. In addition to creating new tech jobs, indicators highlight the need of “soft skills” and “creativity” — skills for problem-solving and working in a team. The danger is within the speed of change and the ability of the workforce to transform fast enough to meet the requirements of automation. The question is whether we can reskill our accountants, auditors and lawyers to become creative data scientists with soft skills within the next few years. Universities already report that by the time students graduate, their job might be replaced by robots or be obsolete. For instance, has predicted that 85 percent of the jobs that today’s students will do in 2030 don’t exist yet. There is a need to create an educational and workforce ecosystem where people are constantly being educated and retooled to stay relevant. The Institute for the Future What fascinates you most about this technology? Where would you like to apply your knowledge most? I am mostly fascinated by the human aspect of AI - how it changes our way of living and impacts our decision-making processes. I am a big advocate of technology being used for humanity and social good. I believe we now have an abundance of tech advances that should be utilized to serve our humanity. Journalists point out many “negative” aspects of AI, however, it's humans who make it work that way. The recent pandemic has exposed fundamental weaknesses in the tech system. It has shown how AI has not been utilized for the prevalence of poverty, weak health systems, lack of education, unstable government support and other global problems. Crises force us to embrace tech advances in renewable energy, education, healthcare, green technology and sustainable new sectors that put humanity on a fast-track path to achieving sustainable goals. The question of whether people will ultimately begin to accept this intrusion into their lives, in return for the increased security and convenience is widely discussed in both the private and public sector. Do you think there will be an increasing trend of people getting out of their devices, canceling social networks profiles, etc, in order to keep their lives private? Will we appreciate our anti-digital world more? We can talk about the concept of neo-luddism — there are people who resist usage of any modern technologies, but we can't really slow down technology's acceleration. One of their arguments is that technologies should be proven safe before adoption, due to the unknown effects that new technologies might inspire. Here again, we come back to the question of policies, education, responsible AI and safety regulations of the AI usage. This pandemic has also shown how powerful they are - during the lockdown, it was the only way to connect with our friends, coworkers and family. Quitting online social media would be impossible now. However, we can change the way we rely on the platforms in our real life. In your research, you’ve focused on the healthcare system. How can AI improve it here in the US? What are the main spheres you foresee being the most disrupted/influenced by AI in the near future? The US Healthcare system acutely lacks a unification of diverse data sources. Patient Data is not matched with Physicians Data which doctors hold at hand, and it is not matched with Pharmacy Data or Provider Data, which hospitals look at. Insurance data is also barely matched with any of those. There are severe limitations to implementing holistic AI solutions that impact a patient's health.  If all of the above systems were connected, a patient who has suffered an incident could be treated better. It’s a complex problem. Moreover, a patient who is trying to recover from a life threatening ailment needs to be guided to live their life well, with the right medication, delivered at the right time, after performing the right exercise before going to bed at the right time. So the healthcare system needs to manage the patient’s lifestyle, too. I agree with Vas Bhandarkar, ’s CEO, who says that a good healthcare system should be able to access this centrally accessible normalized data to deliver all manner of  therapeutic, preventive, and curative treatments. Companies like ScoreData are solving the predictive patient behavior problem by computing propensities for readmission and delivering a sequence of nudges that help the patient take medicines on time, exercise at the right time of day, eat well, and rest well. ScoreData AI has penetrated our daily lives. Banks, health insurance, and consumer companies are all using the technology to improve their services and increase revenues. To me, the most fascinating aspect of AI is coming from its integration with neuroscience and psychology. AI will be most impactful in introducing new ways of interacting with machines, by using robots or building human-level general AI (AGI). This is when a computerized system exhibits abilities similar to those of the human mind. However, currently most of the disruptions are happening around deep learning — the use of computing power, which is trying to detect patterns in mountains of seemingly unrelated data.

"We Know About AI's Ability To Remember, But Forget About Its Ability To Forget." - Valeria Sadovykh

How Understanding CPU Caches Can Supercharge Your Code: 461% Faster MatMul Case Study

This paper is under CC 4.0 license. available on arxiv : Authors (1) Linda Pigureddu, University of Turin, Italy, 332079@edu.unito.it; (2) Cristina Gena, Dept. of Computer Science, University of Turin, Italy, cristina.gena@unito.it. Table of Links Introduction The Project Memes Conclusion and References CONCLUSION The analysis of the interactions and dialogues that took place during the therapeutic laboratory for autonomies endorsed with the inclusion of the Pepper robot provided an interesting perspective on the communication dynamics of children in the lab. The results obtained showed the effectiveness of the robot in promoting autonomy and functional acquisition, demonstrating that the therapeutic method based on assistive robotics is a valuable resource to support the rehabilitation needs of communication and social skills of autistic children. The analysis highlights new possibilities for their engagement and active participation as a co-designer, as we already experienced in the past with neuro-typical children [19], representing an innovative opportunity to promote the development and wellness of autistic people and opening to new perspectives for therapeutic intervention more aware of the needs of autistic minds. In conclusion, this paper highlights the need to provide the robot with the ability of adapt to the children’s peculiarity and features and sharing her/his vocabulary, especially by recognizing and using memes during interactions, to inspire greater trust in children and allowing the use of common slang, already in use with classmates, allowing them to consider Pepper a peer and effectively insert it in the role of mediator. In addition, it would allow children to use a simplified type of communication during meetings to compensate for the typical communication deficits associated with autism spectrum disorders. In the future we will work in this directions (co-design, user’s adaptations, using and recognizing memes during children-robot communication) having the robot able to communicate and express adapting to user tastes and preferences and and try again to field a real-world evaluation that takes into account the effectiveness of different levels of user adaptation [23]. REFERENCE [1] M. Biondi e M. Maj, DSM-5: diagnostic and statistical manual of mental disorders: text revision, 5. ed. Milano: Raffaello Cortina. [2] E. Hollander, R. Hagerman, e C. Ferretti, Textbook of Autism Spectrum Disorders, Second Edition. American Psychiatric Association Publishing, 2022. [3] ISS - Istituto superiore di sanità, «Osservatorio Nazionale Autismo», OssNA. https://osservatorionazionaleautismo.iss.it [4] P. Pennisi et al., «Autism and social robotics: A systematic review», Autism Research, vol. 9, fasc. 2, pp. 165–183, 2016, doi: 10.1002/aur.1527. [5] S. Shamsuddin, H. Yussof, S. Mohamed, e F. A. Hanapiah, «Design and Ethical Concerns in Robotic Adjunct Therapy Protocols for Children with Autism», Procedia Computer Science, vol. 42, pp. 9–16, gen. 2014, doi: 10.1016/j.procs.2014.11.027. [6] K. Dautenhahn e I. Werry, «Towards Interactive Robots in Autism Therapy: Background, Motivation and Challenges», Pragmatics & Cognition, vol. 12, pp. 1–35, giu. 2004, doi: 10.1075/pc.12.1.03dau. [7] C. Li, Q. Jia, e Y. Feng, «Human-Robot Interactoin Design for Robot-Assisted Intervention for Children with Autism Based on E-S Theory», in 2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), Hangzhou, China: IEEE, ago. 2016, pp. 320–324. doi: 10.1109/IHMSC.2016.103. [8] A. Peca et al., «Robot Enhanced Therapy for Children with Autism Disorders: Measuring Ethical Acceptability», IEEE Technol. Soc. Mag., vol. 35, fasc. 2, pp. 54–66, giu. 2016, doi: 10.1109/MTS.2016.2554701. [9] B. Robins, K. Dautenhahn, e J. Dubowski, «Does appearance matter in the interaction of children with autism with a humanoid robot?», IS, vol. 7, fasc. 3, pp. 479–512, nov. 2006, doi:10.1075/is.7.3.16rob. [10] E. S. Kim, «Robots for social skills therapy in autism: evidence and designs toward clinical utility», 2013, doi: 10.13140/2.1.3038.2083. [11] «Autismo», Neuraxpharm Italia. https://www.neuraxpharm.com/it/disordini/autismo [12] L. Hull, K. V. Petrides, e W. Mandy, «The Female Autism Phenotype and Camouflaging: a Narrative Review», Rev J Autism Dev Disord, vol. 7, fasc. 4, pp. 306–317, dic. 2020, doi: 10.1007/s40489-020-00197-9. [13] D. Cohen et al., «NAO, a humanoid robot as a therapeutic mediator for young people with autism». [14] Cristina Gena, Claudio Mattutino, Andrea Maieli, Elisabetta Miraglio, Giulia Ricciardiello, Rossana Damiano, Alessandro Mazzei: Autistic Children's Mental Model of an Humanoid Robot. UMAP (Adjunct Publication) 2021: 128-129 [15] Rossana Damiano, Cristina Gena, Andrea Maieli, Claudio Mattutino, Alessandro Mazzei, Elisabetta Miraglio, Giulia Ricciardiello: UX Personas for Defining Robot's Character and Personality 213-216. IUI Workshops 2022: 213-216. [16] Cristina Gena, Claudio Mattutino, Stefania Brighenti, Andrea Meirone, Francesco Petriglia, Loredana Mazzotta, Federica Liscio, Matteo Nazzario, Valeria Ricci, Camilla Quarato, Cesare Pecone, Giuseppe Piccinni: et al., Sugar, Salt & Pepper - Humanoid robotics for autism, in Joint Proceedings of the ACM IUI 2021 Workshops co-located with 26th ACM Conference on Intelligent User Interfaces (ACM IUI 2021), College Station, United States, April 13-17, 2021, D. Glowacka e V. R. Krishnamurthy, A c. di, in CEUR Workshop Proceedings, vol. 2903. CEUR-WS.org, 2021. [17] Cristina Gena, Rossana Damiano, Claudio Mattutino, Alessandro Mazzei, Andrea Meirone, Loredana Mazzotta, Matteo Nazzario, Valeria Ricci, Stefania Brighenti, Federica Liscio, Francesco Petriglia: Preliminary results of a therapeutic lab for promoting autonomies in autistic children. arXiv, doi: 10.48550/arXiv.2305.02982. [18] B. C. Carbo, «The Use of Social Stories with Individuals with Autism Spectrum Disorders», University of Delaware ProQuest Dissertations Publishing, Newark, DE, 2005. [Online]. Disponibile su: https://udspace.udel.edu/server/api/core/bitstreams/cd5e8850-e57c-41d2-a7b4ac5e25a4b659/content [19] V. Cietto, C. Gena, I. Lombardi, C. Mattutino and C. Vaudano, "Co-designing with kids an educational robot," 2018 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), Genova, Italy, 2018, pp. 139-140, doi: 10.1109/ARSO.2018.8625810. [20] A. Mousa, «Sherry Turkle, Reclaiming Conversation. The Power of Talk in a Digital Age», Questions de communication, fasc. 34, Art. fasc. 34, dic. 2018, doi:10.4000/questionsdecommunication.16891. [21] H.-M. Chiang e M. Carter, «Spontaneity of Communication in Individuals with Autism», J Autism Dev Disord, vol. 38, fasc. 4, pp. 693–705, apr. 2008, doi: 10.1007/s10803-007-0436-7. [22] Gena, C., Cena, F., Vernero, F., Grillo, P. The evaluation of a social adaptive website for cultural events. User Model User-Adap Inter 23, 89–137 (2013) https://doi.org/10.1007/s11257-012-9129-9 [23] Gena, Cristina, and Ilaria Torre. "The importance of adaptivity to provide onboard services: A preliminary evaluation of an adaptive tourist information service onboard vehicles." Applied Artificial Intelligence 18.6 (2004): 549-580.

The Power of Memes: The Pepper Robot as a Communicative Aid for Autistic Children - Conclusion

Let's learn about via these 74 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Writing Tips /Learn Repo 1. "Even in the digital age, finding the best and most original source can be difficult" Jeffrey is an entertainment reporter with interests in film & TV criticism, comics, anime & manga, MMA, and pro wrestling. 2. “Perfection is the enemy of good.” - Voltaire x GPT-J GPT-J  takes on Voltaire and proceeds to 3. Meet the Writer: HackerNoon's Contributor Pragati Verma, Software Developer Meet the Writer: Pragati Verma is a software developer and a Junior Editor at HackerNoon. 4. How to Get Started with Writing Online Here’s what you need to know about the writing process to get you started with writing online. 5. Aleksandr Pindyk on Creating, Playing and Writing About Games This story is a part of Hacker Noon's Meet the Writer series of interviews. 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This paper is under CC 4.0 license. available on arxiv Authors: (1) Prajwal Niraula, Department of Earth, Atmospheric and Planetary Sciences; (2) Julien de Wit, Department of Earth, Atmospheric and Planetary Sciences; (3) Benjamin V. Rackham, Department of Earth, Atmospheric and Planetary Sciences; (4) Elsa Ducrot, Astrobiology Research Unit, University of Li`ege; (5) Artem Burdanov, Department of Earth, Atmospheric and Planetary Sciences; (6) Ian J. M. Crossfield, Kansas University Department of Physics and Astronomy; (7) Valerie Van Grootel´, Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege; (8) Catriona Murray, 5Cavendish Laboratory; (9) Lionel J. Garcia, Astrobiology Research Unit, University of Li`ege; (10) Roi Alonso, Instituto de Astrof´ısica de Canarias & Dpto. de Astrof´ısica, Universidad de La Laguna; (11) Corey Beard, Department of Physics & Astronomy, The University of California; (12) Yilen Gomez Maqueo Chew, Instituto de Astronom´ıa, Universidad Nacional Aut´onoma de M´exico, Ciudad Universitaria; (13) Laetitia Delrez, Astrobiology Research Unit, University of Li`ege, Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege & 0Observatoire de lUniversit´e de Gen`eve; (14) Brice-Olivier Demory, University of Bern, Center for Space and Habitability; (15) Benjamin J. Fulton, NASA Exoplanet Science Institute/Caltech-IPAC; (16) Michael Gillon, Astrobiology Research Unit, University of Li`ege; (17) Maximilian N. Gunther, Department of Physics, and Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology; (18) Andrew W. Howard, California Institute of Technology; (19) Howard Issacson, Department of Astronomy, University of California Berkeley; (20) Emmanuel Jehin, Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege; (21) Peter P. Pedersen, Cavendish Laboratory; (22) Francisco J. Pozuelos, Astrobiology Research Unit, University of Li`ege & Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege; (23) Didier Queloz, Cavendish Laboratory; (24) Rafael Rebolo-Lopez, Instituto de Astrof´ısica de Canarias & Dpto. de Astrof´ısica, Universidad de La Laguna'; (25) Sairam Lalitha, School of Physics & Astronomy, University of Birmingham; (26) Daniel Sebastian, Astrobiology Research Unit, University of Li`ege (27) Samantha Thompson, Cavendish Laboratory; (28) Amaury H.M.J. Triaud, School of Physics & Astronomy, University of Birmingham. Table of Links Abstract & Introduction Observation Analysis and Validation Future Prospects & References 4. FUTURE PROSPECTS The search for transiting planets around small stars has been motivated in large part by their potential for atmospheric characterization. Owing to the size and proximity of its host, K2-315b is thus one of the few known terrestrial exoplanets possibly amenable for atmospheric characterization in the next two decades. In order to quantify and contextualize its prospects for atmospheric study, we followed the same approach as for TRAPPIST-1 in Gillon et al. (2016) (see de Wit & Seager 2013), focusing here on all known terrestrial planets. We selected terrestrial planets as planets with a reported radius below 1.6 R⊕ in the NASA Exoplanet Archive[4] (Rogers 2015; Fulton et al. 2017). We thus derive the amplitude of the planets’ signals in transmission as: where Rp is the planetary radius, R∗ is the stellar radius, and heff is the effective atmospheric height, µ is the atmospheric mean molecular mass, T is the atmospheric temperature and g is the local gravity. We assume heff to cover seven atmospheric scale heights, µ the atmospheric mean molecular mass to be 20 amu, and the atmospheric temperature to be the equilibrium temperature for a Bond albedo of 0. For the planets with missing masses, we estimated g using the model of Chen & Kipping (2017). The signal amplitudes are reported in Figure 7 together with the SNR relative to TRAPPIST-1 b’s, calculated by scaling the signal amplitude with the hosts’ brightness in J band. We find that K2-315b fares closely to the outer planets of TRAPPIST-1 in terms of potential for atmospheric exploration with JWST— its warmer and thus larger atmosphere compensating for its larger star. In fact, its relative SNR for transmission spectroscopy is half those of TRAPPIST-1 f–h, meaning that assessing the presence of a µ ∼ 20 atmosphere around the planet would require of the order of 40 transits—four times the ∼10 transits required for a similar assessment for TRAPPIST-1 f–h (Lustig-Yaeger et al. 2019). K2-315b is thus at the very edge of JWST’s capability for atmospheric characterization, mostly due to its “large” host star. The derivation above allows us to rank planets in terms of relative potential for atmospheric characterization, assuming a similar atmospheric scenario. In practice, a significant difference in atmospheric mean molecular mass, surface pressure, and/or cloud/haze altitude will strongly affect the actual potential of a planet for characterization (Lustig-Yaeger et al. 2019). For example, in some cases clouds could render the characterization of the favorable TRAPPIST-1 e difficult even with the generation of instruments following the JWST (i.e., LUVOIR, Pidhorodetska et al. 2020). With an estimated radial velocity semi-amplitude of 1.3 m s−1 (assuming a mass comparable to that of Earth), the planet could be accessible for mass measurements using modern ultra-precise radial velocity instruments. Such possibilities and a ranking amongst the 10 best-suited Earth-sized planets for atmospheric study, EPIC 249631677 b will therefore play an important role in the upcoming era of comparative exoplanetology for terrestrial worlds. It will surely be a prime target for the generation of observatories to follow JWST and bring the field fully into this new era. This project makes use of publicly available K2 data. P.N. would like to acknowledge funding for Kerr Fellowship and Elliot Fellowship at MIT. J.d.W. and MIT gratefully acknowledge financial support from the Heising-Simons Foundation, Dr. and Mrs. Colin Masson and Dr. Peter A. Gilman for Artemis, the first telescope of the SPECULOOS network situated in Tenerife, Spain. B.V.R. thanks the Heising-Simons Foundation for support. V.V.G. is a F.R.S.-FNRS Research Associate. M.G. and E.J. are F.R.S.-FNRS Senior Research Associates. This work was also partially supported by a grant from the Simons Foundation (PI Queloz, grant number 327127), and funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013) ERC Grant Agreement Number 336480, from the ARC grant for Concerted Research Actions financed by the Wallonia-Brussels Federation, from the Balzan Prize Foundation, from F.R.S-FNRS (Research Project ID T010920F), from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (grant agreement n◦ 803193/BEBOP), and from a Leverhulme Trust Research Project Grant n◦ RPG-2018-418. 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π Earth: a 3.14-day Earth-sized Planet from K2's Kitchen Served Warm: Future Prospects & References

This paper is under CC 4.0 license. available on arxiv Authors: (1) Prajwal Niraula, Department of Earth, Atmospheric and Planetary Sciences; (2) Julien de Wit, Department of Earth, Atmospheric and Planetary Sciences; (3) Benjamin V. Rackham, Department of Earth, Atmospheric and Planetary Sciences; (4) Elsa Ducrot, Astrobiology Research Unit, University of Li`ege; (5) Artem Burdanov, Department of Earth, Atmospheric and Planetary Sciences; (6) Ian J. M. Crossfield, Kansas University Department of Physics and Astronomy; (7) Valerie Van Grootel´, Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege; (8) Catriona Murray, 5Cavendish Laboratory; (9) Lionel J. Garcia, Astrobiology Research Unit, University of Li`ege; (10) Roi Alonso, Instituto de Astrof´ısica de Canarias & Dpto. de Astrof´ısica, Universidad de La Laguna; (11) Corey Beard, Department of Physics & Astronomy, The University of California; (12) Yilen Gomez Maqueo Chew, Instituto de Astronom´ıa, Universidad Nacional Aut´onoma de M´exico, Ciudad Universitaria; (13) Laetitia Delrez, Astrobiology Research Unit, University of Li`ege, Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege & 0Observatoire de lUniversit´e de Gen`eve; (14) Brice-Olivier Demory, University of Bern, Center for Space and Habitability; (15) Benjamin J. Fulton, NASA Exoplanet Science Institute/Caltech-IPAC; (16) Michael Gillon, Astrobiology Research Unit, University of Li`ege; (17) Maximilian N. Gunther, Department of Physics, and Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology; (18) Andrew W. Howard, California Institute of Technology; (19) Howard Issacson, Department of Astronomy, University of California Berkeley; (20) Emmanuel Jehin, Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege; (21) Peter P. Pedersen, Cavendish Laboratory; (22) Francisco J. Pozuelos, Astrobiology Research Unit, University of Li`ege & Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege; (23) Didier Queloz, Cavendish Laboratory; (24) Rafael Rebolo-Lopez, Instituto de Astrof´ısica de Canarias & Dpto. de Astrof´ısica, Universidad de La Laguna'; (25) Sairam Lalitha, School of Physics & Astronomy, University of Birmingham; (26) Daniel Sebastian, Astrobiology Research Unit, University of Li`ege (27) Samantha Thompson, Cavendish Laboratory; (28) Amaury H.M.J. Triaud, School of Physics & Astronomy, University of Birmingham. Table of Links Abstract & Introduction Observation Analysis and Validation Future Prospects & References 3. ANALYSIS AND VALIDATION 3.1. Stellar Host Characterization 3.1.1. Semi-empirical Stellar Parameters We constructed the spectral energy distribution (SED) of EPIC 249631677 using photometric magnitudes from Gaia (GBP and GRP ; Gaia Collaboration et al. 2018) and the AllWISE source catalog (J, H, Ks, W1, W2, and W3; Cutri et al. 2013). The corresponding fluxes for these magnitudes are tabulated on VizieR (Ochsenbein et al. 2000) and shown in Figure 5 and Table 1. The parallax of EPIC 249631677 is π = 17.61 ± 0.09 mas, which yields a distance of 56.8 ± 0.3 pc (Gaia Collaboration et al. 2018; Stassun & Torres 2018). We then derived the stellar luminosity L∗ by integrating over the SED, which yielded L∗ = 0.0041 ± 0.0001L . Two independent methods were applied to obtain stellar mass. First, we used the empirical M∗−MKs relation (applying the metallicity obtained in Section 3.1.2) from Mann et al. (2019) to obtain M∗ = 0.1721 ± 0.0044M . We also applied stellar evolution modeling, using the models presented in Fernandes et al. (2019), using as a constraint the luminosity inferred above and the metallicity derived in Sect. 3.1.2). We considered the stellar age to be >1 Gyr in the absence of signs of youth, such as presence of prominent flares (Ilin et al. 2019, see Section 3.1.3). We obtained with this method M∗ = 0.176 ± 0.004 M . This uncertainty reflects the error propagation on the stellar luminosity and metallicity, but also the uncertainty associated with the input physics of the stellar models. We combined these two mass estimates as in Van Grootel et al. (2018) to obtain M∗ = 0.174±0.004M as our best estimate for the stellar mass of EPIC 249631677. Given its proximity, we expect minimal extinction (Av) for the target; the SED fitting analysis described in Section 3.2.1 similarly constrains it to be 0.02 at 3σ confidence and we adopt that upper limit here. Finally, we note that given its luminosity, mass, and Gaia colors this star is likely to be fully convective (Jao et al. 2018; Rabus et al. 2019). Due to the absence of a strong constraint on the stellar density from the transits, we further obtained stellar radius, surface gravity, effective temperature and density from our evolutionary models. Table 1 summarizes the results from this analysis, along with other properties of the star. Our values are consistent with those listed in the TESS Input Catalog (Stassun et al. 2019), and we adopt them for the remainder of this analysis. 3.1.2. Reconaissance Spectroscopy To confirm EPIC 249631677’s stellar properties and better characterize the system, we acquired an optical spectrum using Keck/HIRES (Vogt et al. 1994) on UT 30 May 2020. The observation took place in 0.6 00 effective seeing and using the C2 decker without the HIRES iodine gas cell, giving an effective resolution of λ/∆λ ≈ 55, 000 from 3600 ˚A to 7990 ˚A. We exposed for 1800 s and obtained SNR of roughly 23 per pixel. Data reduction followed the standard approach of the California Planet Search consortium (Howard et al. 2010). We used our Keck/HIRES radial velocity and Gaia DR2 data to estimate the 3D galactic (UV W) space velocity using the online kinematics calculator[2] of Rodriguez (2016). Following Chubak et al. (2012), our Keck/HIRES spectrum gives a barycentric radial velocity of 6.25±0.17 km s−1 . With the Gaia-derived coordinates, proper motion, and distance listed in Table 1, we find (U, V, W) values of (−17.02, −9.06, +33.66) km s−1 , indicating a likely membership in the Milky Way’s thin disk (Bensby et al. 2014). Using the SpecMatch-Empirical algorithm (Yee et al. 2017), we derive from our HIRES spectrum stellar parameters of Teff = 3195 ± 70 K, R∗ = 0.23 ± 0.10R , and [Fe/H]= −0.24 ± 0.09, consistent with the values tabulated in Table 1. The three best-matching stars in the SpecMatch-Empirical template library are GJ 15B, GJ 447, and GJ 725B, which have spectral types of M3.5V, M4V, and M3.5V, respectively. Given the close match between the spectra of these stars and our target (see Fig. 4), we therefore classify EPIC 249631677 as an M dwarf with subclass 3.5±0.5. We see no evidence of emission line cores at Hα, consistent with our determination that our target is not a young star. We see no evidence of spectral broadening compared to these three stars (which all have v sin i < 2.5 km s−1 ; Reiners et al. 2012), so we set an upper limit on EPIC 249631677’s projected rotational velocity of < 5 km s−1 , comparable to the spectral resolution of HIRES. 3.1.3. Stellar Variability The long-term variations apparent in the everest light curve (Figure 1) are not evident in light curves from other reduction pipelines (e.g., K2SFF). These variations likely arise from systematics and are not reliable for estimating the stellar rotation period (Esselstein et al. 2018). Similarly, no flares are apparent either in the K2 or SPECULOOS data. Flare rates peak for ∼M3.5 stars in TESS data (G¨unther et al. 2020). However, given the long integration time of 29.4 minutes as well as a need for data processing which corrects for the saw-tooth pattern, flare signals, unless very prominent, are expected to be difficult to detect in K2 long cadence data. 3.2. Vetting In order to produce a transit depth on the level of 0.2% in the light curve of the primary target, a background eclipsing binary producing eclipses with depths of 25% to 50% would have to be 5.25 to 6.0 mag fainter than the target, respectively. Qualitatively, the odds of EPIC 249631677 hosting a planet are higher than the odds of such magnitude contrast eclipsing binary being present within the SPECULOOS aperture, given occurrence rates of M-dwarf planets (Dressing & Charbonneau 2013; Mulders et al. 2015; Hardegree-Ullman et al. 2019). A stringent quantitative constraint can be placed using the ingress/egress duration (T12/T34) compared to the total transit duration (T14) (Seager & Mall´enOrnelas 2003, Equation 21). Such a test yields an upper limit on the relative radius of the transiting body. By assuming equal effective surface temperatures, the lower magnitude limit ∆m (corresponding to a flux difference ∆F) for a blended binary mimicking a signal of depth δ is given by: Using the posterior for the transit fit (See Section 3.3), we find for EPIC 249631677 that such a background object can be fainter at most by 1.73 mag at the 3σ level. Fortunately, EPIC 249631677 has a significant proper motion, ∼140 mas yr−1 , which allows us to investigate the presence of background sources at its current sky position. We looked at archival imaging of EPIC 246331677 going back to 1953[3] . A POSS I plate from 1953 is the publicly available oldest image of EPIC 249631677, and it does not show any background source at the current position of the target as shown in Figure 6. The plate is sensitive to objects at least 3.5 magnitudes fainter than the target. Similarly, the Hubble Guide Star Catalogue (GSC), with a limiting magnitude of 20 (Lasker et al. 1990), does not show any background source. While POSS II would go the deepest in terms of limiting magnitude (20.8, Reid et al. 1991), the star has moved appreciably closer to its current location, precluding a definitive measurement from this image. Overall, using archival images we can rule out the possibility of the transit signal originating from background star at a high level of confidence. 3.2.1. Binarity of the Host Star Despite the lack of background sources, the host star could produce a false-positive transit signal if it were a grazing eclipsing binary or a hierarchical eclipsing binary. We investigated the evidence for host star binarity using the isochrones software package (Morton 2015), which performs isochrone fitting in the context of the MESA (Paxton et al. 2011, 2013, 2015) Isochrones and Stellar Tracks database (Dotter 2016; Choi et al. 2016). Single-star and binary evolutionary models are available within isochrones, and the inference is performed via the nested sampling algorithm MULTINEST (Feroz et al. 2009) (as implemented in the PyMultiNest software package (Buchner et al. 2014)), which allows for direct comparisons of the Bayesian evidence ln Z. We tested both single-star and binary models using the priors on photometric magnitudes and stellar distance described in Section 3.1.1. The inferred properties from the single-star model fit are consistent with those given in Table 1 at the 2σ level. The ln Z for the single-star model is −213.86±0.04, whereas the ln Z for the binary model is −229.6 ± 0.2. According to Kass & Raftery (1995), the corresponding Bayes factor of 16 indicates “decisive” evidence in favor of the single-star model. We also examined our Keck/HIRES spectrum for secondary lines that would indicate the presence of another star following the approach of Kolbl et al. (2015). We found no evidence of additional lines down to the method’s standard sensitivity limit of ∆V = 5 mag for ∆v > 10 km s−1 , consistent with EPIC 249631677 being a single, isolated star. We therefore conclude that the available data strongly support EPIC 246331677 being a single star. 3.2.2. Photometric Tests We performed a series of tests on the photometric data to rule out false-positive scenarios. First, we performed an even-odd test on the target using K2 photometry. The even and odd transits are consistent with one another in transit depth to within 1σ. We also looked for secondary eclipses in the phase-folded light curve and found none to be present. Note that since we observe consistent signals in both the K2 and SPECULOOS data sets, we can rule out the signal originating from systematics. The transit depth in SPECULOOS observations with I+z filter, which is redder than Kepler bandpass, are consistent to K2 transit depths within 1σ level, keeping up with the expectation of the achromatic nature of planetary transit. Furthermore, a massive companion, such as a faint white dwarf, can be ruled out using the ellipsoidal variation, which puts a 3σ upper limit on the mass of any companions at the given orbital period of the transit signal as ∼100 MJup (Morris 1985; Niraula et al. 2018). From the transit fit, we can rule out a grazing eclipse originating from a larger transiting object (i.e. ≥ 2R⊕) at >3σ confidence. Together, these tests rule out the object at 3.14 days being a massive companion. 3.3. Transit Fitting We used the refined estimates of the host properties together with a joint analysis of the K2 and SPECULOOS light curves to derive the planetary properties. In order to calculate the transit model, we used batman (Kreidberg 2015). We simultaneously model both the K2 observation as well as the ground-based observations with 21 parameters in a Monte Carlo Markov Chain (MCMC) framework using the emcee package (ForemanMackey et al. 2013). We use a Gaussian prior on the scaled semi-major axis of the orbit a/R∗ of N (25.72, 0.27), derived using Eq. 30 from Winn (2010) along with the stellar density of 32.6 ± 1.0 g cm−3 (see Section 3.1.1) and orbital period of 3.1443 days from the TLS search. As for the limb darkening, we use the non-informative q1, q2 parameterization of the quadratic limb-darkening law as suggested by Kipping (2013). We fixed the eccentricity to 0, given that the expected time of circularization is 50 Myr (assuming a quality factor Qp ∼ 500, Goldreich & Soter 1966; Patra et al. 2017), which is at least an order of magnitude smaller than the estimated age of the system. For K2 data, we supersample the transits by a factor of 15 in batman to take into account the effect of non-negligible integration time. As for the ground-based data, we use second-order polynomials to detrend against the observables airmass and FWHM. We ran the MCMC for 50,000 steps with 150 walkers performing a combined fit of K2 and SPECULOOS — (1) This work. (2) Huber et al. (2016). (3) Stassun et al. (2019). (4) Cutri et al. (2003). (5) Gaia Collaboration et al. (2018). (6) Cutri et al. (2013). (7) This work, evolutionary model analysis. (8) This work, Keck/HIRES analysis. (9) This work, SED analysis. References data, and use the last half of the run to build the parameter posteriors. We assessed the convergence of walkers using the suggested autocorrelation test for emcee. The resulting median values from the fit with 1σ deviation are reported in Table 2, while the best-fit transit models are shown in Figure 2 and Figure 3. [2] http://kinematics.bdnyc.org/query [3] http://stdatu.stsci.edu/cgi-bin/dss form

π Earth: a 3.14-day Earth-sized Planet from K2's Kitchen Served Warm: Analysis and Validation

This paper is under CC 4.0 license. available on arxiv Authors: (1) Prajwal Niraula, Department of Earth, Atmospheric and Planetary Sciences; (2) Julien de Wit, Department of Earth, Atmospheric and Planetary Sciences; (3) Benjamin V. Rackham, Department of Earth, Atmospheric and Planetary Sciences; (4) Elsa Ducrot, Astrobiology Research Unit, University of Li`ege; (5) Artem Burdanov, Department of Earth, Atmospheric and Planetary Sciences; (6) Ian J. M. Crossfield, Kansas University Department of Physics and Astronomy; (7) Valerie Van Grootel´, Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege; (8) Catriona Murray, 5Cavendish Laboratory; (9) Lionel J. Garcia, Astrobiology Research Unit, University of Li`ege; (10) Roi Alonso, Instituto de Astrof´ısica de Canarias & Dpto. de Astrof´ısica, Universidad de La Laguna; (11) Corey Beard, Department of Physics & Astronomy, The University of California; (12) Yilen Gomez Maqueo Chew, Instituto de Astronom´ıa, Universidad Nacional Aut´onoma de M´exico, Ciudad Universitaria; (13) Laetitia Delrez, Astrobiology Research Unit, University of Li`ege, Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege & 0Observatoire de lUniversit´e de Gen`eve; (14) Brice-Olivier Demory, University of Bern, Center for Space and Habitability; (15) Benjamin J. Fulton, NASA Exoplanet Science Institute/Caltech-IPAC; (16) Michael Gillon, Astrobiology Research Unit, University of Li`ege; (17) Maximilian N. Gunther, Department of Physics, and Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology; (18) Andrew W. Howard, California Institute of Technology; (19) Howard Issacson, Department of Astronomy, University of California Berkeley; (20) Emmanuel Jehin, Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege; (21) Peter P. Pedersen, Cavendish Laboratory; (22) Francisco J. Pozuelos, Astrobiology Research Unit, University of Li`ege & Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege; (23) Didier Queloz, Cavendish Laboratory; (24) Rafael Rebolo-Lopez, Instituto de Astrof´ısica de Canarias & Dpto. de Astrof´ısica, Universidad de La Laguna'; (25) Sairam Lalitha, School of Physics & Astronomy, University of Birmingham; (26) Daniel Sebastian, Astrobiology Research Unit, University of Li`ege (27) Samantha Thompson, Cavendish Laboratory; (28) Amaury H.M.J. Triaud, School of Physics & Astronomy, University of Birmingham. Table of Links Abstract & Introduction Observation Analysis and Validation Future Prospects & References 2. OBSERVATIONS 2.1. A Candidate in Archival K2 Data EPIC 249631677 was observed by K2 in Campaign 15 from 2017-08-23 22:18:11 UTC to 2017-11-19 22:58:27 UTC continuously for about 90 days as part of program GO 15005 (PI: I. Crossfield). The pointing was maintained by using two functioning reaction wheels, while the telescope drifted slowly in the third axis due to radiation pressure from the Sun, which was corrected periodically by thruster firing (Howell et al. 2014). As a consequence of such a modus operandi, uncorrected K2 light curves can show saw-tooth structures. Many pipelines have been built to correct for such systematics. Two popular detrending algorithms for K2 light curves are K2SFF (Vanderburg & Johnson 2014) and everest (Luger et al. 2016). These pipelines have helped to achieve precision comparable to that of Kepler by correcting for systematics caused by intrapixel and inter-pixel variations. In the case of EPIC 249631677b, the standard deviation of the flattened light curve for K2SFF was observed to be 1230 ppm, compared to 685 ppm for everest. Considering this, we use the light curve from the everest pipeline, available from the Mikulski Archive for Space Telescopes, throughout this analysis. We use a biweight filter with a window of 0.75 days, as implemented in w¯otan (Hippke et al. 2019), to generate the flattened light curve for further analysis, and use only data with quality factor of 0. This light curve can be seen in Figure 1. The simple aperture photometric light curve has a scatter of 2527 ppm, which improves to 685 ppm after everest processing. We searched the flattened data for periodic transit signals using the transit least squares algorithm (TLS) (Hippke & Heller 2019), and found a prominent peak around 3.14 days as can be seen in Figure 2. We assessed the presence of additional candidate signals after modeling out the 3.14-d signal by re-running TLS, but did not find any with a significant signal detection efficiency (i.e., SDE>10). 2.2. Candidate Vetting with SPECULOOS Telescopes We followed up on the planetary candidate by observing with SPECULOOS Southern Observatory (SSO) two transit windows on UT 25 February 2020 by Ganymede and on UT 18 March 2020 by Io, and one transit window with SPECULOOS Northern Observa-. tory on UT 18 May 2020 by Artemis. SSO is composed of four telescopes: Io, Europa, Ganymede and Callisto, which are installed at ESO Paranal Observatory (Chile) and have been operational since January 2018. SNO is currently composed of one telescope (Artemis), which is located at the Teide Observatory (Canary Islands, Spain) and operational since June 2019. All SPECULOOS telescopes are identical robotic Ritchey-Chretien (F/8) telescopes with an aperture of 1-m. They are equipped with Andor iKon-L cameras with e2v 2K × 2K deep-depletion CCDs, which provide a Field of View (FoV) of 12 0 × 12 0 and the corresponding pixel scale is 0.35 00 pixel−1 (Delrez et al. 2018; Jehin et al. 2018). To schedule those windows we used the SPeculoos Observatory sChedule maKer (SPOCK), described in Sebastian et al. (in prep.). Observations were made with an exposure time of 40 s in an I+z filter, a custom filter (transmittance >90% from 750 nm to beyond 1000 nm) designed for the observation of faint red targets usually observed by the SPECULOOS survey (Delrez et al. 2018; Murray et al. 2020). SSO data were then processed using the SSO Pipeline, which accounts for the water vapor effects known to be significant for differential photometry of redder hosts with bluer comparison stars (Murray et al. 2020). SNO data were processed using prose, a Python-based data reduction package, which generates light curves from raw images (Garcia et al. in prep.). It creates a stacked image to extract the positions of the stars in the field, and uses the positions to perform aperture annulus photometry. A differential light curve is produced using a weighted light curve derived from the field stars, while the instrumental systematics, such as pointing shift and full width half maximum, are recorded to assist later in detrending. We show detrended light curves from SPECULOOS in Figure 3, where we recovered the transit events within 1σ of the calculated ephemeris from K2 data. Since these observations were obtained two years after K2 Campaign 15, they improve the precision of the transit ephemeris by an order of magnitude.

π Earth: a 3.14-day Earth-sized Planet from K2's Kitchen Served Warm: Observation

This paper is under CC 4.0 license. available on arxiv Authors: (1) Prajwal Niraula, Department of Earth, Atmospheric and Planetary Sciences; (2) Julien de Wit, Department of Earth, Atmospheric and Planetary Sciences; (3) Benjamin V. Rackham, Department of Earth, Atmospheric and Planetary Sciences; (4) Elsa Ducrot, Astrobiology Research Unit, University of Li`ege; (5) Artem Burdanov, Department of Earth, Atmospheric and Planetary Sciences; (6) Ian J. M. Crossfield, Kansas University Department of Physics and Astronomy; (7) Valerie Van Grootel´, Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege; (8) Catriona Murray, 5Cavendish Laboratory; (9) Lionel J. Garcia, Astrobiology Research Unit, University of Li`ege; (10) Roi Alonso, Instituto de Astrof´ısica de Canarias & Dpto. de Astrof´ısica, Universidad de La Laguna; (11) Corey Beard, Department of Physics & Astronomy, The University of California; (12) Yilen Gomez Maqueo Chew, Instituto de Astronom´ıa, Universidad Nacional Aut´onoma de M´exico, Ciudad Universitaria; (13) Laetitia Delrez, Astrobiology Research Unit, University of Li`ege, Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege & 0Observatoire de lUniversit´e de Gen`eve; (14) Brice-Olivier Demory, University of Bern, Center for Space and Habitability; (15) Benjamin J. Fulton, NASA Exoplanet Science Institute/Caltech-IPAC; (16) Michael Gillon, Astrobiology Research Unit, University of Li`ege; (17) Maximilian N. Gunther, Department of Physics, and Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology; (18) Andrew W. Howard, California Institute of Technology; (19) Howard Issacson, Department of Astronomy, University of California Berkeley; (20) Emmanuel Jehin, Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege; (21) Peter P. Pedersen, Cavendish Laboratory; (22) Francisco J. Pozuelos, Astrobiology Research Unit, University of Li`ege & Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege; (23) Didier Queloz, Cavendish Laboratory; (24) Rafael Rebolo-Lopez, Instituto de Astrof´ısica de Canarias & Dpto. de Astrof´ısica, Universidad de La Laguna'; (25) Sairam Lalitha, School of Physics & Astronomy, University of Birmingham; (26) Daniel Sebastian, Astrobiology Research Unit, University of Li`ege (27) Samantha Thompson, Cavendish Laboratory; (28) Amaury H.M.J. Triaud, School of Physics & Astronomy, University of Birmingham. Table of Links Abstract & Introduction Observation Analysis and Validation Future Prospects & References ABSTRACT We report on the discovery of a transiting Earth-sized (0.95R⊕) planet around an M3.5 dwarf star at 57 pc, K2-315b. The planet has a period of ∼3.14 days, i.e. ∼π, with an instellation of 7.45 S⊕. The detection was made using publicly available data from K2’s Campaign 15. We observed three additional transits with SPECULOOS Southern and Northern Observatories, and a stellar spectrum from Keck/HIRES, which allowed us to validate the planetary nature of the signal. The confirmed planet is well suited for comparative terrestrial exoplanetology. While exoplanets transiting ultracool dwarfs present the best opportunity for atmospheric studies of terrestrial exoplanets with the James Webb Space Telescope, those orbiting mid-M dwarfs within 100 pc such as K2-315b will become increasingly accessible with the next generation of observatories. stars: individual (2MASS J15120519-2006307, EPIC 249631677, TIC 70298662, K2-315b) – planets and satellites: detection Keywords: 1. INTRODUCTION The redesigned Kepler mission, K2 (Howell et al. 2014), has been a success by adding almost 400 confirmed planets to the 2,348 discovered by the original mission[1]. Building upon Kepler (Borucki et al. 2010), K2 expanded the search of planets around brighter stars, covered a wider region of sky along the ecliptic, and studied a variety of astronomical objects . Together, these endeavors have revolutionized the field of exoplanetary science by quadrupling the number of exoplanets known at the time, while K2 in particular has led to exciting discoveries, such as disintegrating planetesimals around the white dwarf WD-1145 (Vanderburg et al. 2015), multi-planet systems around bright stars like GJ 9827 (K2-135) (Niraula et al. 2017; Rodriguez et al. 2018), and resonant chains of planets like the K2-138 system with five planets (Christiansen et al. 2018). Space-based platforms such as Kepler can provide high-quality continuous monitoring of targets above the Earth’s atmosphere. The simultaneous photometric monitoring of tens of thousands of stars enables finding rare configurations (e.g., WD-1145) and answering science questions regarding planetary populations that are more statistical in nature such as how unique our own Solar System is, or what are the most common type of planets (e.g. Fressin et al. 2013; Fulton et al. 2017). Ground-based facilities, on the other hand, often detect fewer planets while operating at a lower cost. These planets frequently exhibit larger signal-to-noise ratios (SNRs) in various metrics (e.g., transmission), thereby allowing for these planets to be characterized further. One such example is the TRAPPIST-1 planetary system (Gillon et al. 2016, 2017), discovered by the TRAPPISTUltra Cool Dwarf Transiting Survey, a prototype survey for the SPECULOOS Survey (Gillon et al. 2013). The goal of the SPECULOOS Survey is to explore the nearest ultracool dwarfs (Teff <3000 K) for transits of rocky planets (Burdanov et al. 2018; Delrez et al. 2018; Jehin et al. 2018; Sebastian et al. in prep.). Although few systems are expected (Delrez et al. 2018; Sebastian et al. in prep.), their impact on the field will be significant as they should provide most of the temperate Earthsized exoplanets amenable for atmospheric studies with the next generation of observatories such as JWST (e.g. Gillon et al. 2020). Beyond the SPECULOOS Survey, which monitors nearby late-M dwarfs for terrestrial planets, the SPECULOOS telescopes have been used to study the planetary population around mid- and late-M dwarfs. In that context, SPECULOOS facilities have been involved in following up and validating planetary candidates, notably from TESS (G¨unther et al. 2019; Kostov et al. 2019; Quinn et al. 2019). Next to confirming planetary candidates that cross detection thresholds, we have started to investigate weaker signals. For this work, we revisited K2 data, a mission which ended only in 2019. We reanalyzed the light curves of stars with Teff < 3500 K, a Kepler magnitude < 15, and a log g > 4.5. While these criteria were motivated particularly to look for planets around ultra-cool dwarfs, they were relaxed in order to allow room for errors in the stellar properties and improve completeness of the analysis. Among the 1,213 stars fitting these criteria, EPIC 249631677 presented the strongest periodic transit-like signal. In this paper, we report the discovery of an Earthsized K2 planet in a close-in orbit around EPIC 249631677. The paper is structured as follow; observations (Section 2), analysis and validation (Section 3), and the discussion in regards to future prospects for characterization (Section 4). In this paper, we report the discovery of an Earthsized K2 planet in a close-in orbit around EPIC 249631677. The paper is structured as follow; observations (Section 2), analysis and validation (Section 3), and the discussion in regards to future prospects for characterization (Section 4). [1] https://exoplanetarchive.ipac.caltech.edu

π Earth: a 3.14-day Earth-sized Planet from K2's Kitchen Served Warm: Abstract & Intro

This paper is available on arxiv under CC BY-SA 4.0 DEED license. Authors: (1) Mathias-Felipe de-Lima-Santos, Faculty of Humanities, University of Amsterdam, Institute of Science and Technology, Federal University of São Paulo; (2) Wilson Ceron, Institute of Science and Technology, Federal University of São Paulo. Table of Links Abstract & Introduction Data and Methods Results Discussion and Conclusions Funding and References Funding This project was partially funded by the University of Amsterdam’s RPA Human(e) AI and by the European Union’s Horizon 2020 research and innovation programs No 951911 (AI4Media). References (1) Sunstein, C. R. #Republic: Divided Democracy in the Age of Social Media; Princeton University Press: Princeton, New Jersey, 2017. (2) Garimella, K.; De Francisci Morales, G.; Gionis, A.; Mathioudakis, M. Political Discourse on Social Media. 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Disinformation Echo-Chambers on Facebook: Funding and References

Software Engineering for OpenHarmony—A Research Roadmap: Conclusion & References

Let's learn about via these 77 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Content Writing /Learn Repo 1. Write Attention-Grabbing Headlines With This Classic Copywriting Formula Since the headline is the first thing your readers see, it should grab attention.  Write headlines with urgency, uniqueness, ultra-specificity, and usefulness. 2. 99.9% of Content Will Be AI-Generated by 2025: Does Anyone Care? Soon AI bots will create 99.9% of all content on the internet. This creates serious problems for free thinking and creativity. Can we solve these problems? 3. 12-step Process I Use to Make $5,000 Monthly From Writing Here's my simple 12-step process I use to make $5,000 every month (you can have it for free). 4. 5 Top Free Tools I Use to Create Great Content for HackerNoon Content creation has become an important part of any business on the Web. I share and discuss 5 top free tools I use to create superb content for HackerNoon 5. Why I Started A Free Blogging Course My 6-year old daughter once told me “Mama, I do not understand your work. Why you don’t go to an office? Why do you always just type on your laptop? It’s too wordy. Too many envelopes (email)!” 6. A Human Writers Thoughts on AI Writing Bots My thoughts on artificial intelligence writing bots. 7. Kadeem Clarke On Love of Cars & Keeping Up With the Blockchain World Meet HackerNoon contributor Kadeem Clarke, Head of Labs at Momentum 6 and Founder of Clarke Global. 8. How to Get Started with Writing Online Here’s what you need to know about the writing process to get you started with writing online. 9. Content Is King: 5 Content Creation Tips for Marketing Professionals Follow these five steps to create content for digital marketing of product and services. Spearhead your digital marketing campaigns with high quality content 10. 5 Ways AI Helps You Write Better Content Discover how artificial intelligence is assisting writers in improving the content they produce and removing much of the busywork associated with writing. 11. Learning the Art of Storytelling from Pixar Pixar has successfully presented stories using a structure that works every time; it is a must-explore for any storyteller. 12. StoryLab.ai Uses GPT-3 to Make Content Marketing Easier for Everyone We believe we’re building something special. And we believe humans need more than AI to create more and better stories. We need each other to grow. 13. Reimagining Customer Behavior Through Machine Learning Here what you need to know about Machine Learning in business market strategy 14. 10 Free Ways to Promote Your Content   on the Web How to promote content on the Web? Why content is important in marketing? How to promote content on the blog? 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Has AI Changed Copywriting FOREVER? The W3S group has developed an in-house AI (Artificial Intelligence) copywriting bot named Trevor. Trevor generates community content for web2 & web3 companies. 25. Meet the Writer: HackerNoon Contributor Michael Faith Loves Playing Chess A writer is someone who communicates ideas through written words in various writing styles and techniques. 26. Meet the Writer: HackerNoon's Contributor Karen Shidlo, CMO at Fiat24 Meet the Writer: HackerNoon's Contributor Karen Shidlo, CMO at Fiat24, a web3 banking concept based in Switzerland. 27. How Image to Text Technology Can Ease Your Writing Process To collect the information from the images, you do not have to write it down manually.  Instead of that, you can use image-to-text technology. 28. Aleksandr Pindyk on Creating, Playing and Writing About Games This story is a part of Hacker Noon's Meet the Writer series of interviews. Aleksandr Pindyk is an AI game developer and HackerNoon contributor. 29. How I Use Mind Mapping to Create Content (This One, Too) Find out how to leverage mind mapping to supercharge your content creation process. 30. Top PR Tricks and Free Tools for Startups in the Era of Decreasing Valuations Startups and well-established companies are looking for low-budget tools for getting media coverage amidst the economic downturn. 31. Growth Hacks to Attract More Visitors to Your Website In this digital world, having a business website is no longer an option but a necessity. However, there is a huge difference between creating a website and driving traffic towards it, and this difference turns out to play a vital role in the success of different businesses. 32. 9 Research Sources to Generate B2B Content That Stands Out on the SERPs and Converts Quality contents have one thing in common and that is quality research. Here are 9 places to research to generate B2B content that drives traffic and converts 33. AI Is Coming for Content Writing. Here Is Why It's a Good Thing Already, AI writing tools can write better than many humans who do content writing for a living. So is it just a matter of time before the machines come for my 34. Becoming a Rich Writer: The Tale of Two Writers This vision is hard — nearly impossible — to achieve for many writers. 35. 17 Best Freelance Writing Job Sites In 2022 Have a look at the 20 best places to find freelancing writing jobs. Keep reading to get the complete information. 36. Content Marketer Deb on Writing, Impostor Syndrome, and #Noonies Nomination Content marketer Debashri M Dutta speaks to HackerNoon about her nomination to #Noonies 2022. 37. A Pessimistic Take on the Future of Content Marketing Fast food content marketing is cheap, easy to process, and it comes in unlimited quantities. 38. Overcoming Challenges to Market Research in a Bad Economy Research provides valuable insights into customer behavior, competitors, and market trends and should in no way be left behind. 39. Top 5 Reasons Why "Top [X] Posts" Aren't That Bad Finding myself annoyed by all the "Top X Things to Know About Y" posts, I'm taking some time to list the top 5 things that I find positive about them. 40. 4 Easy Ways to Cultivate a Writing Habit Developing the habit of writing can offer life-changing value to you and your business. Here are 4 tips that will help. 41. Google May Not Be Able to Crack Down on AI  Generated Words Google will fail to crack down on AI Generated content, but not for the reasons you think. In this blog post, I explored why and how I arrived at my conclusion. 42. Should We Have the Right to Write What We Want Even When It's Technically Incorrect? Do we have the 'right' to 'write' what we want, even if it is technically incorrect? Read about an experience I had and decide for yourself. 43. Meet Hacker Noon’s Contributor and Serial Hobbyist Abbey Perini Meet Hacker Noon’s writer and serial hobbyist Abbey Perini! 44. How to Write SEO Friendly Blog Posts: A Complete Guide + Infographic In this extensive guide, you'll learn how SEO writing is done with all the advanced tips and a free on-page SEO infographic for you to start ranking 45. Gathering Material is the Most Laborious Part of the Writing Process My full name is Valerii Udodov; I often write about application architecture and different practices in software development. 46. AI and the Future of Digital Marketing Artificial intelligence will undoubtedly have an influence on the future of digital marketing. 47. What to Do and What Not to Do in Content Creation Many tips and tricks on how to make amazing content. 48. 8 Tactics for Crafting Unique Content That Grabs Attention and Builds Authority Learn to craft content pieces that give you an edge in the SERP and become the standard everyone wants to match. 49. 7 Ways to Improve the Internet with Well Written Content In this article, I will be writing about those things that should be remembered when writing content. This article is basically about what I do when writing content. However, this is my third article on my website. But, I have been working as a content writer in Truemark Technology. You can check out my articles on Truemark Blog. 50. 5 Platforms Rewarding Content Writers with Tokens If you are a content creator or technical writer, these are five websites that let you make passive income in cryptocurrency tokens by writing for platforms. 51. 8 Warning Signs Your Website Is Not SEO-friendly SEO optimization of the website is essential for any online business's success. Here are 8 aspects that don't allow your website to rank in the top 5 of SERP. 52. How to Become a Successful Freelance Copywriter Making the shift from full-time employment to freelance can be frustrating. Our handy guide will help you ace the transition and earn 6-figure income in no time 53. How to Use Different Headline Structures to Boost Your Google SEO Rankings You've heard that keywords are important to your SEO rankings. This is true to a large degree but probably not in the way you expect. 54. Your New HackerNoon Profile Shines Bright Like a Diamond 55. How to Write for Money: From Clickbait Listicles to Full-Time Gigs The VP of Growth at Hacker Noon answers questions about the writer's life, writing for the web, and finding content writing gigs. 56. Meet the Writer: HackerNoon's Contributor, King Abimbola, A B2B/B2C Content Writer I am Mosobalaje M. Abimbola, a creative writer with a background in physical sciences who switched careers to become a B2B cum B2C writer. 57. Is it worth believing in mankind or has competition taken over? Is it worth believing in mankind? Here I have raised up the questions that have been inside me due to growing competition in the recent generation. 58. What Inspired us to Write About Games? Here at Hacker Noon, we love both games and writing. In this slogging post, we discuss what inspired us to write about games and our fondest gaming memories. 59. Will Content Continue to Rule? In the movie Little Women, Jo March’s (Saoirse Ronan) inky fingers give her away as the writer rather than just the bearer of someone else’s manuscript; as she claims initially in the newspaper editor’s office, she’s nervously visiting. The editor decisively strikes through many pages before accepting a story and making an offer of payment. Thrilled to the core, Jo March runs through the streets for she had sold her first piece of content! 60. How Top Tech Marketers Receive Quality Traffic: 7 Tips Proven to Reap Recurring Revenue for Years How Top Tech Marketers Receive Quality Traffic: Proven To Reap Recurring Revenue For Years. 7 lessons in 5 years 61. Want To Get Better at Public Relations? Start Writing Articles When I started doing Public Relations, more than 20 years ago, I was kind of a mess… 62. 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Do you want to learn how to write about a product? Learn the power of copywriting and how to do it. Read Joseph Sugarman 73. How to Write Meta Descriptions to Optimize Your Search Engine Results In this article, we will discuss the various aspects of meta description writing, as well as tips for making it stand out from the crowd! 74. How to Create Better Content with an SEO Content Outline (Tips from 30+ Experts) Advice from 30+ experts on creating SEO content outlines. 75. Why is Writing Important? (Slogging Insights) Writing, in a sense, is a way to help you understand the world, understand concepts and help others to understand those concepts too. 76. How to Become a Web3 Technical Writer: How These 10 Pros Did It. I asked 10 Web3 technical writers how they started in Web3, their core skills, the challenges they face and how they can help newbies navigate this path. 77. How to Make Money Writing: 50+ Websites that Pay Premium for Writers. All freelance writers want to earn premium for their work. In this article, I listed over 50 websites that help you earn over $100 for writing articles. Thank you for checking out the 77 most read stories about Content Writing on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

77 Stories To Learn About Content Writing

This paper is available on arxiv under CC 4.0 license. Authors: (1)Eason Chen, Carnegie Mellon University; (2) Justa Liang, Bucket Protocol; (3) Ray Huang, Bucket Protocol; (4) Pierce Hung, Bucket Protocol; (5) Damien Chen, Bucket Protocol; (6) Ashley Hsu, Bucket Protocol; (7) Konstantinos Chalkias, Mysten Labs; (8) Stefanos Pleros Mysten Labs. TABLE OF LINKS Abstract and Introduction Background Randomness Practice in Blockchain System Development Transaction Fee Comparison Discussion Conclusion and References 7. CONCLUSION This paper explained how to build a fair, verifiable, efficient random raffle on the Sui Network. We investigate a range of smart contract design methodologies for constructing chance-based games through smart contracts, identify their inherent constraints, and propose remedies. Furthermore, we furnish insights drawing from the advantages and limitations of different design choices. Through these insights, we provide valuable guidance to researchers and developers engaged in randomness games using smart contracts. REFERENCES [1] Sam Blackshear, Evan Cheng, David L Dill, Victor Gao, Ben Maurer, Todd Nowacki, Alistair Pott, Shaz Qadeer, Dario Russi Rain, Stephane Sezer, et al. 2019. Move: A language with programmable resources. Libra Assoc (2019), 1. [2] Joseph Bonneau, Jeremy Clark, and Steven Goldfeder. 2015. On bitcoin as a public randomness source. Cryptology ePrint Archive (2015). [3] Joseph Bonneau and Valeria Nikolaenko. 2022. Public Randomness and Randomness Beacons. https://a16zcrypto.com/posts/article/public-randomness-andrandomness-beacons/. (Accessed on 10/10/2023). [4] Chainlink. 2023. Chainlink VRF | Chainlink Documentation. https://docs.chain. link/vrf. (Accessed on 10/07/2023). [5] Kostas Kryptos Chalkias. 2022. Fair Randomness in Decentralized Games. https://docs.google.com/presentation/d/ 1a9wddWhqKM4GXMV1UrhrpaH1sBMUxZWI. (Accessed on 10/10/2023). [6] Ting Chen, Xiaoqi Li, Xiapu Luo, and Xiaosong Zhang. 2017. Under-optimized smart contracts devour your money. In 2017 IEEE 24th international conference on software analysis, evolution and reengineering (SANER). IEEE, 442–446. [7] Alonso de Gortari. 2023. MystenLabs.sui on X: "Seeing is believing on @SuiNetwork: Increasing Transactions + Stable Gas Fees = Affordable Scalability" / X. https://twitter.com/Mysten_Labs/status/1683566765253468162. (Accessed on 10/05/2023). [8] Ben Edgington. 2023. BLS12-381 For The Rest Of Us - HackMD. https://hackmd. io/@benjaminion/bls12-381. (Accessed on 10/07/2023). [9] Paul Feldman. 1987. A practical scheme for non-interactive verifiable secret sharing. In 28th Annual Symposium on Foundations of Computer Science (sfcs 1987). IEEE, 427–438. [10] Ethereum Foundation. 2023. Proof-of-stake (PoS) | ethereum.org. https: //ethereum.org/en/developers/docs/consensus-mechanisms/pos. (Accessed on 10/07/2023). [11] Ethereum Foundation. 2023. Zero-Knowledge rollups | ethereum.org. https:// ethereum.org/en/developers/docs/scaling/zk-rollups/. (Accessed on 10/09/2023). [12] Sara Gherghelas. 2023. State of the Dapp Industry in Q2 2023. https://dappradar. com/blog/state-of-the-dapp-industry-in-q2-2023. [13] Shafi Goldwasser, Silvio Micali, and Chales Rackoff. 2019. The knowledge complexity of interactive proof-systems. In Providing sound foundations for cryptography: On the work of shafi goldwasser and silvio micali. 203–225. [14] The News Lense. 2023. Dinter’s "Lineage M" Purple Cloth Incident: The fair will fine Gamania 2 million TWD, legislators and the public call for the promotion of the "Gashapon Law" - The News Lens Key Comment Network. https://www. thenewslens.com/article/168188. (Accessed on 10/07/2023). [15] Ralph C Merkle. 1987. A digital signature based on a conventional encryption function. In Conference on the theory and application of cryptographic techniques. Springer, 369–378. [16] Satoshi Nakamoto. 2008. Bitcoin: A peer-to-peer electronic cash system. Decentralized business review (2008). [17] Newzoo. 2023. Newzoo Global Games Market Report 2023 | Free Version. https://newzoo.com/resources/trend-reports/newzoo-global-gamesmarket-report-2023-free-version. (Accessed on 10/07/2023). [18] Rune Kristian Lundedal Nielsen and Pawel Grabarczyk. 2019. Are Loot Boxes Gambling?: Random reward mechanisms in video games. Transactions of the Digital Games Research Association 4 (2019), 171–207. [19] League of Entropy. 2023. Drand - Distributed Randomness Beacon. https: //drand.love. (Accessed on 10/07/2023). [20] League of Entropy. 2023. Specification | Drand - Distributed Randomness Beacon. https://drand.love/docs/specification/. (Accessed on 10/07/2023). [21] Stefanos Pleros and Konstantinos Chalkias. 2023. Time-locked Satoshi Coin Flip. https://github.com/MystenLabs/satoshi-coin-flip. (Accessed on 10/10/2023). [22] Yolan Romailler. 2022. Multi Frequency Support and Timelock Encryption Capabilities are coming in drand! https://drand.love/blog/2022/02/21/multi-frequencysupport-and-timelock-encryption-capabilities/. (Accessed on 10/10/2023). [23] The MystenLabs Team. 2022. The Sui Smart Contracts Platform. https://docs.sui. io/paper/sui.pdf. (Accessed on 10/04/2023). [24] Zhipeng Wang, Stefanos Chaliasos, Kaihua Qin, Liyi Zhou, Lifeng Gao, Pascal Berrang, Benjamin Livshits, and Arthur Gervais. 2023. On how zero-knowledge proof blockchain mixers improve, and worsen user privacy. In Proceedings of the ACM Web Conference 2023. 2022–2032. [25] Zibin Zheng, Shaoan Xie, Hongning Dai, Xiangping Chen, and Huaimin Wang. 2017. An overview of blockchain technology: Architecture, consensus, and future trends. In 2017 IEEE international congress on big data (BigData congress). Ieee, 557–564. This paper is under CC 1.0 license. available on arxiv

Designing Fair and Efficient Blockchain Games: Conclusion and References

242 Stories To Learn About Ml

Hi, I’m Aaron Sankin, and I’m a reporter here at The Markup. Over the past year, I’ve focused on investigating and what you (other than shoot dirty looks at your modem, which doesn’t really care about your opinion). why the internet connection at your house is slow can do about it Tucked deep in the , signed by President Joe Biden in 2021, is a short provision giving the Federal Communications Commission (FCC) broad leeway to fundamentally reshape how America connects to the internet. Infrastructure Investment and Jobs Act Under a section titled “Digital Discrimination,” the legislation tasks the FCC with adopting “rules to facilitate equal access to broadband internet access service, taking into account the issues of technical and economic feasibility presented by that objective, including … preventing digital discrimination of access based on income level, race, ethnicity, color, religion, or national origin.” The section itself is short—under 400 words—and relatively light on detail, leaving it largely up to the FCC to decide how much power it wants to grab for itself to close the digital divide. Various actors have rushed into that void of legislative ambiguity, forcefully advocating for their own agendas. On one side are advocacy groups and some local governments who hope the FCC will take the opportunity to aggressively hold internet service providers (ISPs) to account for what they see as generations of inequitable broadband infrastructure deployment across the country. Some propose levying fines on ISPs guilty of discrimination or, as the agency did when it approved a merger between Charter Communications and Time Warner Cable in 2016, companies build out high-speed infrastructure in new areas. mandating On the other side are ISPs, the industry groups representing them, and ideologically aligned pro-business think tanks. They want nothing more than for the FCC to merely supplement its historic light-touch regulation of the broadband industry with generous subsidies—that make investing in high-speed internet infrastructure in marginalized communities more beneficial to the companies’ bottom lines. The crux of this fight is over a concept called “disparate impact” and whether the FCC should use it to identify whether an ISP has engaged in discrimination. The idea behind disparate impact is that discrimination isn’t always explicit. So, if an institution’s policies have created a situation where certain protected groups experience markedly worse outcomes than others, this impact matters just as much as any intentionally biased practices. For example: A company’s CEO decides that people should always physically look up to their managers, so only people over 6 feet, 3 inches get promoted to managerial roles. As a result, the management staff is entirely male, since men tend to be taller on average. Did the company engage in gender discrimination? Under a disparate impact standard, yes. But, under a standard where intent prevails, this discrimination is a lot harder to prove, because the rules that resulted in a management team where everyone can dunk said nary a peep about gender. “From my point of view, disparate impact is really just discrimination through the back door,” said John Yinger, a professor of economics and public administration at Syracuse University, who has disparate impact and wrote a about discrimination in mortgage lending. studied book “If you have a system that doesn’t recognize and address disparate impact, you allow people to, either on purpose [or] by accident, engage in a lot of discrimination.” The problem, Yinger noted, is that to assess disparate impact, the first step is determining which allocation of a certain scarce set of resources—be it broadband access or corporate promotions—is fair, and then determine if different groups’ receipt of that resource violates that standard of fairness. Intentions Matter, or Do They? Consider an we published last year showing how a quartet of ISPs consistently gave the worst deals for internet service to households in low-income, less-White, and historically redlined neighborhoods in major cities across the country. investigation When we were reporting that story, we certainly were curious these disparities existed, but that was less important than the fact that we could prove they existed in the first place. why why Last year, when we reached out to CenturyLink, one of the companies we found consistently charging high prices for sluggish service in marginalized areas, spokesperson Mark Molzen insisted at the time that the company was committed to anti-racism. “While we can’t comment on behalf of other providers, we can say we do not enable services based on any consideration of race or ethnicity, and the methodology used for the report on our network is deeply flawed.” Molzen never pointed to any specific inaccuracies in our data collection or analysis. The “flaw” he identified was in an inference the company read into the story about its motives. Our October 2022 investigation showed absolutely zero evidence that CenturyLink had partitioned cities into geographic areas based on race and used that to determine where to deploy high-speed internet infrastructure. And, honestly, it would be pretty wild if it actually had. Nevertheless, we found that CenturyLink offered addresses in the least-White parts of Des Moines, Iowa, slow-speed internet service 19 percentage points more frequently than the Whitest parts of the city—and all for the same price. In Las Vegas, Nev., that gap was 31 percentage points. In Omaha, Neb., 33 percentage points. A comment within a June 2022 FCC with Lumen, CenturyLink’s parent company, mentioned the company’s expectations “to deploy fiber to approximately one million new locations in 2022 and around 1.5 to 2 million new locations in 2023.” digital discrimination proceeding However, there wasn’t any specificity regarding how many of these new fiber deployments would go to low-income or predominantly non-White areas. When it comes to the FCC’s responsibility, the question is whether the FCC will look at the levels of access that different racial, ethnic, and socioeconomic groups have to affordable, blazing-fast internet, find substantial inequality, and then do something about it. Or, as the telecom industry would prefer, will the agency only intervene after finding direct evidence of an ISP making inequitable decisions about where to deploy infrastructure explicitly based on characteristics like race or ethnicity? “ ” In Some Circumstances, It Can Be Profitable The legal theory behind disparate impact goes back to , a 1971 Supreme Court case about how a company required all employees to pass a pair of intelligence tests if they wanted to move into higher-paying roles. Black people were far less likely to pass those tests, which were unrelated to the jobs’ responsibilities. Griggs v. Duke Power Co. The court ruled that these tests—which the company just so happened to implement on the very day the 1964 Civil Rights Act—prohibited race-based employment discrimination, and were illegal due to the effect they had on Black employees’ career advancement. The use of disparate impact to identify discrimination grew in the ensuing decades and was finally into law in 1991. “Because individual motives may be difficult to prove directly, Congress has frequently permitted proof of only discriminatory impact as a means of overcoming discriminatory practices,” reads a U.S. Department of Justice on the subject. codified manual “The Supreme Court has, therefore, recognized that disparate impact liability under various civil rights laws ‘permits plaintiffs to counteract unconscious prejudices and disguised animus that escape easy classification as disparate treatment.’ ” During the administration of President Donald Trump, who famously settled a in the 1970s over his family’s real estate company’s practice of not renting properties to Black tenants, the Department of Housing and Urban Development dramatically the government’s ability to use disparate impact, but the rules were shortly after President Biden took office. lawsuit weakened reinstated While disparate impact has been used by the government to regulate employment and housing, it hasn’t yet been used to assess the role ISPs are playing in the digital divide. As a result, when the FCC went about implementing the digital discrimination rules mandated by Congress, the agency specifically that the public weigh in on whether the standard should be used and, if so, how. requested The responses the agency received on the issue largely fell into two categories. The telecom industry argued in favor of using as a metric, which holds that discrimination occurs when people are explicitly divided up by a protected category (like race) and then treated worse as a result. Digital inclusion advocacy groups argued that is the only feasible metric. disparate treatment disparate impact “Rational, profit-seeking actors will discriminate because, in some circumstances, it can be profitable to do so. Whether this is intentional or not is beside the point,” argued the National Digital Inclusion Alliance and Common Sense Media, two nonprofit advocacy groups, in one . comment “The point … is that discrimination occurs and will continue to occur unless providers’ incentives are changed.” The groups’ comment urges the FCC to look for disparate impact in a plethora of ISP practices ranging from the prices customers are charged for a service, and under what contract terms, to the actual speeds different areas receive and how companies prioritize network maintenance. “For decades, the disability community has noted that discrimination occurs unintentionally and often results from seemingly neutral policies,” the American Association of People with Disabilities in another comment. concurred “Too often, disabled people experience discrimination not because of malicious intent or explicit exclusion within programs or policies but because the disabled people were simply not considered in the first place.” The Greenlining Institute, a California-based nonprofit that for digital inclusion efforts, insisted in its that applying disparate impact to broadband would be consistent with how it has been used across the government for decades. advocates comment “Adoption of the disparate impact standard in the wake of the Civil Rights Act of 1964 allowed for a whole-of-government approach that targeted discrimination in public goods such as education and housing,” Greenlining asserted. “It would be consistent to apply this similar treatment to digital public infrastructure and services such as broadband internet.” The tenor of comments from folks who might theoretically be held accountable if their actions were found to have treated some communities worse than others was, unsurprisingly, markedly different. A primary industry worry is that requiring ISPs to constantly weigh equity concerns may dissuade them from deploying new infrastructure widely in the first place. “Adopting a disparate impact test would cause carriers to choose between prioritizing deployment based on closing the digital divide, as required by Congress, and paralyzing deployment for fear that a regular, common business decision may disproportionately affect a minority community,” asserted the Lincoln Network, a free market think tank, in its . comment Another industry argument is that Congress didn’t really mean for the FCC to use disparate impact to identify “discrimination of access based on income level, race, ethnicity, color, religion, or national origin.” Verizon, for example, that the phrase “based on” in the legislation specifically means that discrimination has to be a direct result of company decisions made because of protected demographic characteristics of a particular area. asserted For its part, AT&T asserted in its that, even if a disparate impact standard were applied, the broadband industry wouldn’t be found to have delivered less connectivity to historically marginalized areas. comment While there have been localized studies showing inequitable deployment in places like , , , and , the company said that the only way to accurately assess deployment would be to look at a comprehensive, national picture of everywhere every single ISP offers service. Cleveland Dallas Oakland Los Angeles AT&T to an analysis from former FCC chief economist Glenn Woroch that showed that “broadband availability rates for census-based ‘non-white’ households are higher than for white households and that availability rates for households above and below the poverty line are nearly identical.” pointed Woroch’s research relies on data from a broadband availability map produced by the FCC that is supposed to show what service ISPs offer across the country. While a footnote in Woroch’s comment insists his data source doesn’t skew the results, that map has been for inaccuracies, and a 2020 Princeton found that “the FCC’s data disproportionately overstates coverage in rural and minority communities.” widely criticized study The FCC released a last year designed to rectify those issues, but that map has its own set of and is still effectively in its beta testing phase. As a result, obtaining data accurate enough to meet the standards pushed for by AT&T remains a tall order. new map profound accuracy problems The battle over the FCC’s potential use of disparate impact hasn’t been limited to the public comment process. In a recent , The Wall Street Journal’s historically laissez-faire editorial board used the specter of disparate impact to lobby against Public Knowledge’s co-founder Gigi Sohn, whom Biden unsuccessfully nominated to lead the agency, but withdrew following telecom industry opposition. op-ed “Public Knowledge, the outfit that Ms. Sohn co-founded and led from 2001 to 2013, has urged the FCC to interpret its regulatory mandate broadly to micromanage broadband competition and development,” the editorial charged. Now would be the time to mention that The Markup does, in fact, have a pack of dogs in this fight. Our newsroom is based on the idea that if you evaluate the inputs and outputs of a big, complex technical system, you can identify serious problems in how it treats different groups without having to know the precise intentions of the people who developed it. The technology does not yet exist to do a regression controlling for the vagaries of the human heart. In March, Markup reporter and freelance data journalist used data analysis to determine that an algorithm for deciding which patients got life-saving liver transplants people in a handful of states, almost all of which were in the South and Midwest. The day after that story was published, the Department of Health and Human Services major reforms to that very system. Malena Carollo Ben Tanen systematically disadvantaged announced One thing I’m working on—along with my colleague, investigative data reporter —is a step-by-step guide showing everyday people how they can evaluate whether ISPs have left a digital divide in their towns. It should be dropping sometime in the next few weeks. Leon Yin We’re hoping that if people use the guide and find something interesting, they can tell the FCC about it. And, who knows, depending on how this disparate impact proceeding goes, maybe the agency will even do something about it. Sincerely, Aaron Sankin Investigative Reporter The Markup By Aaron Sankin Also published here Photo by on Annie Spratt Unsplash

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