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Fuelled by her passion to help the next generation of girls, Nigerian activist Priscilla Efe Johnson is destigmatising menstruation and women’s health. Her

Meet the Generation17 Young Leaders: The Story of Priscilla Efe Johnson – Samsung Newsroom South Africa

Samsung to meet with media and industry professionals to share company’s AI-enhanced lineup of Neo QLED 8K, OLED and lifestyle products and discuss latest industry trends

Samsung Showcases Innovative AI TV Technologies at 2024 Southeast Asia Tech Seminar – Samsung Global Newsroom

Samsung Electronics Co., Ltd., the world leader in advanced memory technology, today announced that it has begun mass production for its one-terabit (Tb) triple-level cell (TLC) 9th-generation Vertical NAND (V-NAND), solidifying its leadership in the NAND flash market.

Samsung Electronics Begins Industry's First Mass Production of 9th-Gen V-NAND | Samsung Semiconductor Global

August 29th, 1997. That’s the day Skynet became self-aware, and the day it decided to attack humanity. Of course, that was in Terminator 2. A movie. Nothing close to real life. While it’s a classic, it’s guilty of emphasizing the negative consequences of technology that most humans couldn’t understand at the time. Things are different now. Artificial Intelligence (AI) has made unprecedented advancements in recent years: think self-driving cars, voice assistants, and smart home systems. And none of these things are “bad” or “evil.” Examples like from Marvel's series and Samantha from the film come to mind. Jarvis Iron Man Her While these AI systems have been glamorized and personified in Hollywood, it begs the question: are we on the cusp of seeing such advanced AI in our lifetime? Let’s get into the possibility and implications of such a reality. The Evolution of AI: A Historical Perspective AI has been touted as the next big thing for decades. The term 'Artificial Intelligence' was first used in the 50s by at a conference in Hanover, New Hampshire. computer scientist John McCarthy Since then, researchers have made impressive strides in developing AI systems capable of complex tasks and even learning from experience. From Turing's Test to Deep Learning In 1950, computer scientist Alan Turing proposed a test to determine if a machine could exhibit intelligent behavior equivalent to a human's. This became known as the “ ” and remains a benchmark for measuring AI. Turing Test Deep learning - a subset of - took center stage in 2012 with an AI system that could recognize cats in YouTube videos. machine learning The breakthrough sparked the current deep learning revolution, leading to natural language processing, image recognition, and autonomous decision-making advancements. Current State of AI: How Close Are We? Today's AI systems can perform a wide range of tasks. They can play complex games like chess and automate routine tasks in industries such as finance and healthcare. While these systems are impressive, they still fall short in terms of general intelligence - the ability to adapt and learn new things. Narrow vs. General AI The current AI landscape is dominated by narrow AI. These are systems efficiently. designed to perform specific tasks It can be used for professional and entertainment purposes. Many marketers use automation tools to help them do more in less time. General AI, on the other hand, can reason and think like a human. It can learn and adapt. That’s what would be required to come up with a Jarvis or a Samantha. But achieving general AI is no easy feat. We’ll need to push through significant scientific ceilings in areas such as natural language processing, emotional intelligence, and creativity, among others. The Path to Advanced AI: Challenges and Considerations While we may be closer than ever to witnessing advanced AI systems like Jarvis and Samantha, significant challenges still need to be addressed. These include: AI systems rely on vast amounts of data to learn and make decisions. Any bias in the data can lead to unideal outcomes. Data bias: Advanced AI systems with general intelligence raise important questions about safety and ethical considerations. Who is responsible if an AI system makes a harmful decision? How can these systems be used ethically? Safety and ethics: If advanced AI systems become a reality, how will they interact with humans? Will they be able to empathize and understand human emotions? Human interaction: Jarvis and Samantha: Breaking Down the Fictional Reality The idea of AI systems like Jarvis and Samantha is not entirely out of the realm of possibility. We’ve already seen significant advancements in natural language processing and emotional intelligence in AI systems. Companies like are laying the groundwork today for what AI will be tomorrow. It’s essentially AI as a Service, allowing users to chat with AI based on fictional characters. Users can also create their own chat buddy. Moemate But what can we see from brands like this five or 10 years from now? There’s no way to know, but the results so far are stellar. It’s also important to note that Jarvis and Samantha are highly romanticized versions of AI. They have personalities and emotions modeled after humans. While it is possible that we may see AI systems, such as what Moemate has developed, with similar capabilities in our lifetime, they won’t be exactly the same as the characters depicted in movies. The Future of AI: What Can We Expect? The journey towards advanced AI, like Jarvis and Samantha, is still evolving. While we have made significant strides in AI technology, we have yet to completely bridge the gap between today's AI and tomorrow's possibilities. The challenges, primarily concerning data bias, ethical considerations, and human interaction, need attention. However, with the rapid pace of technological advancements, we remain optimistic. The focus should lie on nurturing an AI future that is beneficial and safe for humanity. While the prospect of seeing AI like Jarvis and Samantha remains an enticing possibility, these AI systems will blend our technological accomplishments and our shared human values when they do come to life. These values may be much different from what we saw in movies over a decade ago.

Will We See AI Like Jarvis and Samantha in Our Lifetime?

If you’re not familiar with , it’s an Ethereum-based smart contract security CTF game, presented by . For a long time, it’s been the same 26 puzzles, each one of which presents a smart contract with a security vulnerability. The game is to find and exploit the vulnerability, then submit proof of having done so to pass the level. The first person to win all levels gets awarded a free lambo! Or, the only awards are the entertainment/educational value gleaned from the exercise, I forget which. Ethernaut OpenZeppelin Spoiler alert: you can see some of my solutions explained . here if you plan to solve the problems on your own. Avoid that link Well, for a while it’s been the same 26 puzzles, but recently I visited the site again and noticed that a was added: new one The new one is called “Good Samaritan”, and (again ) I will walk you through the problem and the solution. spoiler alert The Problem The problem is explained succinctly . here, on the Ethernaut website There is a network of three smart contracts, comprising a Coin (a very simplified version of an ERC20 token), a Wallet (holds the coin/token), and a front-end contract for donating 10 of the token upon request. This front-end contract owns the wallet which owns a large quantity of the token. The condition for winning is to rob the entire contents of the GoodSamaritan’s wallet. The Solution So, there is actually nothing stopping you from just requesting 10 tokens over and over, except that it will require 100,000 separate requests, will take forever and will cost a ton in gas fees. If you did it this way, I imagine that you would be declared a winner. But that wouldn’t be fun and would miss the point of the challenge. There’s a second way, just using a plain old reentrancy attack. But I won’t get into the details of this, as it’s still too time-consuming and costly. It’s basically the same thing as repeatedly requesting, but with slightly fewer steps. Finally, the real solution (as the Ethernaut description indicates) has to do with the newer way of throwing errors. So, we have a call stack that goes from GS.requestDonation() → Wallet.donate10() → Coin.transfer() Examining this, it’s pretty unremarkable; on examination, there’s no obvious hook to be seen, whereby one could disrupt the process or inject some malicious functionality. However, then the chain is like this: if the caller happens to be another contract, GS.requestDonation() → Wallet.donate10() → Coin.transfer() → INotifyable.notify That last step is clearly the opportunity to disrupt the expected flow. The INotifyable.notify() is an optional hook back to the caller (the calling contract). This is essentially allowing you, the caller, to inject code into the process, right at that point. You code and deploy your own contract to act on your behalf, and execute custom code at that exact spot. So, what code to execute? Well, the first thing that comes to mind is reentrancy, the core of so many attacks in this game (and in real life). Looking at the Coin.transfer function, we can see that it follows the checks-effects-interactions pattern to defend against reentrancy attacks. It has its checks: if(amount_ <= currentBalance) Followed by its effects: balances[msg.sender] -= amount_;
balances[dest_] += amount_; and finally, interactions: INotifyable(dest_).notify(amount_); Now, the trick is that we know one thing: in the GoodSamaritan contract, the result of a error being caught, is that the GoodSamaritan will dump its entire wallet contents onto the caller! NotEnoughBalance } catch (bytes memory err) {
      if (keccak256(abi.encodeWithSignature("NotEnoughBalance()")) == keccak256(err)) {
           // send the coins left
           wallet.transferRemainder(msg.sender);
           return false;
      }
} Hmmm… it seems that the way to get that code to execute, would be to simply cause a NotEnoughBalance error to be thrown. And since the process is allowing us to execute our own custom code…. well there it is. You can see and download my complete solution . The solution itself is visible in the and the . The used in the solution is here. here execute script unit tests custom contract Conclusion There are other smart contract CTFs. What I don’t like about Ethernaut’s is that I feel that they do a bit too much to ‘feed’ you the solution. It would be nice to see a more realistic scenario that contains more complexity and ‘noise’ - a bunch of details that are not related to the solution, that might serve to distract one from the real solution. Which is what you’d see in the real world. What I do like about Ethernaut is that IMO they do a good job in covering many of the most crucial aspects of EVM smart contract security. I’d definitely recommend Ethernaut for someone who is already fairly well-versed in smart contract development, but who is maybe wanting to expand their knowledge of security issues. Also, these exercises are a fun challenge that you can do within a few spare hours, in most cases.

Good Samaritan - The New Ethernaut CTF Challenge

In this AMA, the team at Hackernoon talks to Samantha Robertell, a marketing manager at Gamers Outreach. Gamers Outreach is a non-profit charity that empowers sick children in hospitals through video game software and equipment provision. Slogging Please check out Gamers Outreach . here This Slogging thread by Jack Boreham, Samantha Robertell, Limarc Ambalina and Mónica Freitas occurred in slogging's official #amas channel, and has been edited for readability. Jack Boreham Nov 9, 2021, 2:01 PM Hey @channel, please join me in welcoming our next AMA guest, Samantha Robertell, a marketing manager at Gamers Outreach. Gamers Outreach is a charity that empowers children in hospitals through video game equipment and software. Please feel free to ask Samantha anything about: What her role is within Gamers Outreach About Gamers Outreach and their projects Marketing and social media promotion Anything about video games Jack Boreham Nov 9, 2021, 2:03 PM Hi Samantha Robertell; thank you for joining us today. Can you tell us a little bit about yourself and what you do? To start things off. Samantha Robertell Nov 9, 2021, 2:18 PM Hi Jack! Thank you so much for having me! A little bit about myself well, I currently work in the non-profit space between gaming and health care. Our mission is to bring video games to hospitalized children and families everywhere. I've been around the gaming space for the past ten years and have enjoyed seeing everything grow! Fun facts: I enjoy rock climbing I have a cute cat named Momo - she's the best I'm super hard-stuck Silver in League of Legends but still, enjoy playing 😄 Limarc Ambalina Nov 9, 2021, 3:33 PM Hi Samantha! Thanks for joining us! So how did you get involved with gamers outreach, and where did your journey into the gaming industry begin? Samantha Robertell Nov 9, 2021, 4:07 PM Hi Limarc Ambalina! My journey has been very sporadic, to say the least. I started ten years ago reffing and adminning online Call of Duty tournaments. That was my big intro to the gaming industry. From there, I did odd jobs, customer service, etc. At the same time, moving around the country - impulsively, haha. My big break didn't come until about three years ago when I was introduced to someone at DreamHack and was hired on as a Social Media Event Coverage person. My ties with DreamHack sort of streamlined my intro into Gamers Outreach due to overlapping partnerships within the space! I ended up meeting Zach Wigal, our founder, at a DreamHack Anaheim event I was working. Coincidentally, they needed some coverage and a Marketing Manager. 🙂 The rest is history! Jack Boreham Nov 9, 2021, 4:29 PM A pleasure to have you here, Samantha Robertell. That's superb! Can you go into more detail about what Gamers Outreach does, such as some of the projects it has carried out to help children in need? Jack Boreham Nov 9, 2021, 4:31 PM Also, what a great name for a cat 😂. I've never managed to get into League; what made you get into it? 😄 Jack Boreham Nov 9, 2021, 4:31 PM Unfortunately, rock climbing is not for me as I'm terrified of heights haha. Samantha Robertell Nov 9, 2021, 4:36 PM Yes, happy to share more! Gamers Outreach provides video games to children via mobile kiosks we like to call GO Karts or "Gamers Outreach Karts." These Karts are easy to wipe down so hospital staff can move them from patient to patient. They also come equipped with a monitor, controllers, and a console that's loaded up with 10-15 games such as Rocket League, Minecraft, and Madden. We also have a volunteer program, Player 2. Due to COVID, Player 2 has been on pause, but this is a program in which gamers can act as a helping hand to hospital staff. They can service GO Karts, answer questions, and play video games with patients! Samantha Robertell Nov 9, 2021, 4:38 PM League - a friend of mine got me into it, and I just got sucked in! I love the lore and the champions a ton. Top champions that I play currently are Lulu, Nami, and Leona - all support champions 😄 Samantha Robertell Nov 9, 2021, 4:39 PM Rock climbing doesn't have to be based around heights, either! You can venture into what is called "bouldering." This is just climbing on a wall that's about 12-15 feet tall! Mónica Freitas Nov 9, 2021, 8:44 PM Hey Samantha Robertell! Thank you for being here! What are the main challenges in developing marketing strategies for a charity organization? Also, what's your favorite part about what you do? Samantha Robertell Nov 9, 2021, 10:13 PM Hi Mónica Freitas! For myself, the biggest challenge is always the unexpected bump in the road. For instance, we recently wrapped up a month-long fundraiser in which we were expected to have around 100-150 broadcasters join us. The unexpected bump was that we ended up having over 500 broadcasters participate, which challenged us to shift gears completely in our marketing efforts and pinpoint priority engagement and social direction. It's always great to have a plan in place, but, in my opinion, something can ALWAYS change those plans. Samantha Robertell Nov 9, 2021, 10:15 PM As far as my favorite part - I love our cause. I joined the team because I  believe in making a difference for patients. I've been in the hospital a couple of times as an adult, and it's lonely, especially during these times with COVID still lingering. Video games give kids the chance to be themselves, engage socially with family members or even hospital staff, and just give them a second to dive into any world they want. Limarc Ambalina Nov 10, 2021, 6:42 AM That's awesome, Samantha! At the moment, is the gaming hardware donated mostly by the manufacturers themselves? Sony, Microsoft or from like retailers? Limarc Ambalina Nov 10, 2021, 6:43 AM Also, how do you think the rise of video game streamers has changed the industry and your marketing tactics? Jack Boreham Nov 10, 2021, 10:42 AM Samantha Robertell, wow, what an amazing organisation and such great projects. So I know when we last talked on my podcast, the Rock had involvement with the Gamers Outreach Karts and Xbox. Can you explain a bit more about his involvement 😄 Jack Boreham Nov 10, 2021, 10:44 AM Also, when do you think player two will get up and running again? I might try bouldering!! My sister loves it, haha. Any tips if I did want to start playing League? For a newbie 😂. Samantha Robertell Nov 10, 2021, 1:45 PM Great question, Limarc Ambalina! Gaming hardware can be donated by manufacturers, but it's not as frequent as you may think. In the cost of a GO Kart, the cost of the console is included as well. There have been instances where Xbox has donated 10-20 consoles for larger activations, though! Samantha Robertell Nov 10, 2021, 1:49 PM The rise of streamers has changed the entire game, and this past fundraising effort is a real testament to that. While the streaming market and feel oversaturated from a creator standpoint, it allows us to reach out to more people about our cause. Our Development team works hard to invite a multitude of people to support our cause and that, in turn, exposes new audiences to our mission. So it's all been very positive for us! Samantha Robertell Nov 10, 2021, 1:52 PM Ah yes, Jack Boreham! It's been one full year since our activation with The Rock and Xbox. In that time 20, GO Karts were delivered to hospitals with these  cool Xbox Series X and S's that had The Rock's signature on them. So this activation was around helping others while also sharing the latest console from Xbox 😄 Samantha Robertell Nov 10, 2021, 1:53 PM We're unsure of when Player 2 will return. It will all be on the hospital's terms of when they're allowing visitors again. ❤ 1 Samantha Robertell Nov 10, 2021, 1:56 PM Tips... I recommend playing with a friend who can teach you the macro side of the game! I also recommend playing a support role first, as their role is a bit different when it comes to the economy. You're able to focus more on the champs you're playing against and less on having to last hit minions while also learning new aspects of a game. Mónica Freitas Nov 10, 2021, 3:17 PM Samantha Robertell Thank you for your answers. That was a big turnout. It must be exhilarating seeing an event or fundraiser reach bigger crowds than you've anticipated. I imagine that planning your marketing efforts for a charity is a bit different than doing it for a corporation - maybe you have fewer funds for big marketing efforts, for instance. What would your advice be for someone starting their professional journey in marketing? What were those key lessons you've learned throughout your career and that you wish you'd know sooner? Mónica Freitas Nov 10, 2021, 3:17 PM Samantha Robertell Do you usually adapt the games for different ages? Kids most love having that bit of fun while they have to stay at a hospital. Jack Boreham Nov 10, 2021, 3:53 PM Samantha Robertell, wow, it must have been incredible to get him on board. Have you had any more celebrities or influencers team up with Gamers Outreach?  Also, I heart that gamers outreach just had a fundraiser. Can you tell us a bit more about that? 😄 Jack Boreham Nov 10, 2021, 3:56 PM Okay, I might jump in! You convinced me, haha. So are Moba games like league your go to? Would you jump into other MOBAS like Dota? Are you a big fan of any other genres? Samantha Robertell Nov 10, 2021, 4:02 PM Mónica Freitas So my first job in marketing was for a digital agency. I was brand new and worked my way up to managing our top clients - we were smaller, but it still was a big deal! My boss always told me to imagine you're working with unlimited funds. If you could do anything for your client, anything at all, what can you come up with creatively for them? Then, scale it down. With our Halloween event, there was a lot of "what if we could BE in a retro video game." With lower funds, it's more along the lines of, "how do we make this feel like a spooky retro/arcade feeling?" TLDR; Pretend you have unlimited funds and even if you think your idea is bad, share it with someone. 💚 1 Samantha Robertell Nov 10, 2021, 4:03 PM The games we have on our GO Karts are great for all ages! We don't carry any M rated games due to age restrictions. You'll often time find most kids playing NHL, Rocket League, Minecraft, even Pacman! 💚 1 Samantha Robertell Nov 10, 2021, 4:06 PM Yes, Jack Boreham! We recently wrapped up our month-long fundraiser, the Spooktacular Streamathon. 👻  This was an event in which we had creators fundraiser in support of our cause each day in October. Some creators and organizations chose to fundraise for more than a day, but our ask was just a minimum of one day. We raised $771K, which is incredible for us. These funds will help us to expand globally, bring GO Karts to new hospitals, and more! You can see highlights here: . https://gamersoutreach.org/spooktacular-2021/ Samantha Robertell Nov 10, 2021, 4:08 PM League is my first and only MOBA! I had a deep love for Call of Duty years ago but eventually transitioned out of MP FPS. These days, I play many calming single-player games like Cozy Grove, Stardew Valley, etc. I  recently picked up Eastward and am looking forward to diving more into it when I have some free time! 🔥 1 Limarc Ambalina Nov 10, 2021, 4:23 PM Samantha Robertell Stardew Valley is addicting. It’s the first time I was ever sucked into a farming simulator. The wife and I play it together split-screen all the time! Samantha Robertell Nov 10, 2021, 4:29 PM I love that! My husband recently picked it up on his phone, and he was sucked in too! Jack Boreham Nov 11, 2021, 12:26 AM Samantha Robertell, wow, what an amazing amount raised! Can people still donate to the fundraiser? Also, how do you go about getting creators to join the fundraiser and stream? Same! There is great comfort in playing warmer, more calming games, especially with winter coming up. Samantha Robertell Nov 11, 2021, 2:26 PM The fundraiser is over, but people can always donate to our cause by visiting our website! 😄 http://www.gamersoutreach.org Samantha Robertell Nov 11, 2021, 2:26 PM And yesssss COZY GAMES ALL THE WAY. ❤ 1 Jack Boreham Nov 11, 2021, 2:37 PM Samantha Robertell, that's amazing. Thank you! That's a wrap on this AMA. Thank you, Samantha, for joining us; it has been a pleasure to have you. As you mentioned, we can donate through the website above, any other places our readers can check out! Or any closing thoughts? 😄 Samantha Robertell Nov 11, 2021, 2:53 PM Thank you for having me! As always, people can follow us on socials, @gamersoutreach, to see what we're up to. We're excited for the future of gaming in healthcare and can't wait to share the awesome things we're working on! ❤ 1

Providing Kids in Need With Access to Games: An Interview w/Samantha Robertell from Gamers Outreach

Are you interested in the future of blockchain, cryptocurrency and token offerings? Panelists: Tim Draper Tim Draper is the founding partner of and and widely recognized as one of the most prominent venture capital and entrepreneurial leaders in the world. He was listed as #46 of the most outstanding alumni, #7 on the Midas List among other awards. Tim has been an outspoken proponent of Bitcoin and and is regarded as one of the first VCs in the space. Draper Associates DFJ Harvard University Forbes blockchain Jimmy Song Jimmy started in Bitcoin Development in 2013 and has worked on numerous Bitcoin projects such as Bitcoin Core, btcd, Armory, pycoin and colored coins. He is now a venture partner (a leading crypto fund) and has served as a developer and programmer at more than a dozen start-ups. Most recently, he served as principal architect at and vice president of engineering at Amory Technologies, where he managed the development of enterprise-level Bitcoin wallet software. Jimmy is also the editor and author of popular blog, and with Jimmy Song runs a seminar teaching developers to build on blockchain. Blockchain Capital Paxos Bitcoin Tech Talk YouTube Off Chain Programming Blockchain Kyle Samani Kyle Samani is cofounder and Managing Partner of , a venture capital-esque crypto hedge fund with at least $250M in assets under management (AUM). Prior to starting Multicoin Capital, Kyle ran (a Google Glass company for surgeons) as CEO, raising $5M and ultimately being acquired. Kyle’s writing and thought leadership has built him up as someone to follow in the ever evolving industry. Multicoin Capital Pristine.io Topics: Network effects in a world cryptocurrency How token incentives drive value and adoption Ways to cryptoassets Why network is a key factor in determining crypto value The importance of first mover effects in blockchain What to expect on the future of Bitcoin And much much more … Do not miss out! Watch it live now! Super excited about the event and would love to see you all there. Want more great round tables and investor interviews. Subscribe today to never miss a thing! Brought to you by Corl is the world’s first revenue sharing token on the blockchain. We’re disrupting traditional startup financing by allowing startups and SMBs to access non-dilutive, on-demand growth capital Corl And if you are interested in learning more, and get in touch. read our whitepaper

[Video] Tim Draper, Jimmy Song and Kyle Samani Roundtable on The Value of Cryptocurrency and…

Some Thoughts on the Future of Work In November 2015, I met Vanessa Kanyi at the Samasource Ungala in San Francisco. You see, I had to meet her — Vanessa had just spoken about her journey. Before Samasource, she was making less than $1 a day in the slums of Nairobi, Kenya. This wasn’t enough to help her with her dream of getting a university degree. Her trajectory in life was halted, simply because of where she was born. But then she told the audience that Samasource picked her up as one of its first employees. She started in data entry, then virtual assistant work, and eventually become a supervisor and manager for Sama. Eventually, she was able to move to California and get a scholarship from Santa Monica Community College. The Ungala audience was moved by her story. I was moved by her story. I simply told her, “thank you for sharing your story.” Because of , Vanessa was able to gain meaningful work, pursue her dreams, and move upwards. Vanessa is one of the 50,000+ people who has been positively impacted by Samasource’s mission to lift people out of poverty by giving them good-paying work, along with the training needed to complete that work (Check out ). Samasource sources its employees and contractors in third world regions such as Kenya and Uganda and gives them meaningful pay that allows them to pursue a better life. Samasource Samaschool “The ticket you draw in life’s birth lottery shouldn’t determine your fate.” ~ Leila Janah Samasource accomplishes all this by Businesses need annotation, classification, and data verification for everything from machine learning to image recognition. Samasource helps businesses accomplish this by employing and contracting thousands of people across the world to accomplish these tasks. helping businesses around the world organize their unstructured data through software and scalable work. If you’re interested in structuring your unstructured data, contact me or the Samasource team . Getting Closer to Sama I first learned of Samasource in September 2009, when founder Leila Janah presented at Facebook’s FbFund Rev demo day. I was an editor for at the time — I even that day. I admired the company and the mission, and my admiration has only grown as I’ve gotten to know Samasource and its dedicated team through meetings, fundraisers, and conversations with supporters. Mashable wrote about Samasource In 2015, I got more involved. After seeing the impact of my book , Leila Janah invited me to attend a board meeting to get an idea of what Samasource really did and whether I could help in a more impactful way. I got a chance to see the books and understand Samasource’s uniqueness as a non-profit making a profit. The mission and the direction truly started to make sense. I officially joined the board three months ago. Captivology As a member of the Samasource board, I will be involved in oversight and governance, providing advice to Janah and her team, and helping steer not just Samasource’s future, but the future of work itself. This leads to me to the reasons why I decided to join the board. Work Provides Identity and Hope Prudence grew up in Kibera — Africa’s largest urban slum. She used her income from Samasource to move her mother and sister into a new house in a safer neighborhood, where she loves hosting friends and baking in her new kitchen. I have always found pride and identity in work. I was thrilled to be a lifeguard and swim instructor as a teen, and I built my relationships and brand as Mashable’s 24-year-old Co-Editor wunderkind. I’ve always been happiest when I was working on something I was genuinely proud of. When I look back to my darkest moments, they were almost always when I hated my job, had no job, or when I didn’t know if I could pay the rent. I suspect many of you have had similar experiences. Having work meant you were a productive member of society; not having a means to pay your bills created a giant weight that paralyzed your thoughts and stoked your fears. There’s a reason why the first question most people ask strangers is, “what do you do for a living?” . Work is how we provide for ourselves and our families. It is the activity we spend the most time doing, outside of sleeping or raising our families. We as a society idolize innovators, entrepreneurs, geniuses, and celebrities because of their work. You know LeBron James for his skills on the basketball court; you know Mark Zuckerberg for the company he created. Work is the core of modern identify You don’t even have to ask a person who is out of work or cannot find it how they feel. . In my eyes, Samasource does not provide jobs — it provides identity. It provides empowerment. It provides hope. Ashamed. Afraid. Depressed. Useless Since 2008, Samasource has given identity, empowerment, and hope to over 50,000 people and lifted thousands out of poverty in the process. That is worthy of celebration, but Samasource is on track to give work to thousands or even millions more over the next decade. I joined the board of Samasource to help Leila Janah and her team accomplish this mission, but I also joined because I believe Samasource is at the forefront of the future of work. Work Is Changing, Thanks to AI The concept of work itself is changing at a rapid pace globally. Technology has enabled millions of jobs that were not possible even a decade ago — data entry, machine learning, and transportation, to name a few. But technology will also make many jobs obsolete in the next few decades. Self-driving cars and trucks, for example, will replace millions of jobs as more people begin to trust a technology that avoids the deadly weaknesses of human drivers. AI , and it will not be long until AI helps automates every industry. Yet it could be these AI advances that create new jobs and improve the lives of millions. Where this technology goes depends upon the people at the forefront of these innovations and the priorities they hold. advances are increasing The only way for me to help shape this future is to be at the forefront of this seismic shift. I envision a world where every member of humanity can pursue his or her passions and dreams through the work they to do. In order to achieve this goal, we must give work to those in greatest need and study and support policies that . choose now democratize access to work and wealth The Future of Work Lakshmi is from a small town near Bangalore. Her parents are rural farm laborers, but her father is injured and currently out of work. Lakshmi is supporting her entire family with her Samasource income, as well as funding her brother’s education. Giving more people meaningful work and shaping the future of AI are personal missions for me, especially since . I cannot predict exactly how work will evolve over the next 20 years. However, I do know that Samasource is providing thousands of people with identities and meaningful incomes, and that the technology they have built and enabled could potentially help millions or even billions more. I’m the founder of an AI company I want to be a part of Samasource’s work to bring work to others. Samasource is unique in that it is run like a true business with a product. Many people know of Samasource’s work to help lift people out of poverty through work and training. But Samasource’s product — the structuring of unstructured data — will also shape the future of work in a tremendous way. The mission to give work is only going to become more important as the new automation revolution advances. How we treat our fellow man during this crucial stage of society will be how future generations judge our actions. Let’s get to work. ~ Ben

Why I Joined the Samasource Board of Directors

Authors:
(1) Eilidh Jack, School of Mathematics and Statistics, University of Glasgow, Glasgow, G12 8QQ (eilidh.jack@glasgow.ac.uk);
(2) Craig Alexander, School of Mathematics and Statistics, University of Glasgow, Glasgow, G12 8QQ (craig.alexander.2@glasgow.ac.uk);
(3) Elinor Jones, Department of Statistical Science, University College London, London, WC1E 7HB (elinor.jones@ucl.ac.uk). Table of Links Abstract and Introduction
Course information
Motivation and intervention
Findings
Discussion
Conclusion and References 6 Conclusion The results we present here are in line with previous research (for example [Lo and Hew, 2017], [Buckley and Doyle, 2016], [Dahlstrøm, 2012]) and show a stark increase in student engagement with pre-lecture activities on a course taught in flipped mode. As the pre-lecture activities of interest were quiz-based - with points awarded for attempting the quizzes on time rather than quiz score - we were able to investigate whether the increased engagement was meaningful or the result of students ‘gaming’ the leaderboard. In our study, there was no evidence of the latter. It is thought that the two statistics courses considered here are the only time the students came across the Level Up! plugin or other form of gamification. It is therefore not known whether the increased engagement is due to the novelty of a leaderboard and whether gamification would be as successful if implemented widely across multiple courses. The significant increase in student engagement after the adoption of a gamification strategy is certainly worthy of further research. Though the results from the gamification intervention were very positive, student engagement is still far from perfect. Diversity in teaching and learning approaches is surely the key to engaging students across their courses, with gamification a valuable strategy in a teacher’s toolbox. 7 References [Alomari et al., 2019] Alomari, I., Al-Samarraie, H., and Yousef, R. (2019). The role of gamification techniques in promoting student learning: A review and synthesis: A review and synthesis. Journal of Information Technology Education:Research, 18:395–417. [Blair, 2017] Blair, A. (2017). Understanding first-year students’ transition to university: A pilot study with implications for student engagement, assessment, and feedback. Politics, 37.2:215–228. [Bredow et al., 2021] Bredow, C. A., Roehling, P. V., Knorp, A. J., and Sweet, A. M. (2021). To flip or not to flip? a meta-analysis of the efficacy of flipped learning in higher education. Review of educational research, 91(6):878–918. [Buckley and Doyle, 2016] Buckley, P. and Doyle, E. (2016). Gamification and student motivation. Interactive Learning Environments, 24(6):1162–1175. [Cronhjort et al., 2017] Cronhjort, M., Filipsson, L., and Weurlander, M. (2017). Improved engagement and learning in flipped-classroom calculus. Teaching Mathematics and its Applications: An International Journal of the IMA, 37(3):113–121. [Dahlstrøm, 2012] Dahlstrøm, C. (2012). Impacts of gamification on intrinsic motivation. Education and Humanities Research, pages 1–11. [Deterding et al., 2011] Deterding, S., Khaled, R., Nacke, L. E., Dixon, D., et al. (2011). Gamification: Toward a definition. In CHI 2011 gamification workshop proceedings, volume 12, pages 1–79. Vancouver, Canadá. [Ding et al., 2018] Ding, L., Er, E., and Orey, M. (2018). An exploratory study of student engagement in gamified online discussions. Computers & Education, 120:213–226. [Domínguez et al., 2013] Domínguez, A., de Navarrete, J. S., de Marcos, L., Fernández-Sanz, L., Pagés, C., and Martínez-Herráiz, J.-J. (2013). Gamifying learning experiences: Practical implications and outcomes. Computers & Education, 63:380–392. [Dong et al., 2012] Dong, T., Dontcheva, M., Joseph, D., Karahalios, K., Newman, M., and Ackerman, M. (2012). Discovery-based games for learning software. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’12, page 2083–2086, New York, NY, USA. Association for Computing Machinery. [Ekici, 2021] Ekici, M. (2021). A systematic review of the use of gamification in flipped learning. Education and Information Technologies, 26(3):3327–3346. [Hakulinen et al., 2013] Hakulinen, L., Auvinen, T., and Korhonen, A. (2013). Empirical study on the effect of achievement badges in trakla2 online learning environment. In 2013 Learning and Teaching in Computing and Engineering, pages 47–54. [Hartikainen et al., 2019] Hartikainen, S., Rintala, H., Pylväs, L., and Nokelainen, P. (2019). The concept of active learning and the measurement of learning outcomes: A review of research in engineering higher education. Education Sciences, 9(4):276. [Heilbrunn et al., 2017] Heilbrunn, B., Herzig, P., and Schill, A. (2017). Gamification Analytics—Methods and Tools for Monitoring and Adapting Gamification Designs, pages 31–47. Springer International Publishing, Cham. [Huang and Hew, 2018] Huang, B. and Hew, K. F. (2018). Implementing a theory-driven gamification model in higher education flipped courses: Effects on out-of-class activity completion and quality of artifacts. Computers & Education, 125:254–272. [Ireland and Mouthaan, 2020] Ireland, J. and Mouthaan, M. (2020). Perspectives on curriculum design: comparing the spiral and the network models. Research Matters. [Kim and Castelli, 2021] Kim, J. and Castelli, D. M. (2021). Effects of gamification on behavioral change in education: A meta-analysis. International Journal of Environmental Research and Public Health, 18(7). [Leitner et al., 2017] Leitner, P., Khalil, M., and Ebner, M. (2017). Learning Analytics in Higher Education—A Literature Review, volume 94, pages 1–23. Springer International Publishing. [Lo and Hew, 2017] Lo, C. K. and Hew, K. F. (2017). A critical review of flipped classroom challenges in k-12 education: possible solutions and recommendations for future research. Research and Practice in Technology Enhanced Learning, 12(1):4. [Lo et al., 2017] Lo, C. K., Hew, K. F., and Chen, G. (2017). Toward a set of design principles for mathematics flipped classrooms: A synthesis of research in mathematics education. Educational Research Review, 22:50–73. [Marcey, 2014] Marcey, D. J. (2014). The lecture hall as an arena of inquiry: Using cinematic lectures and inverted classes (clic) to flip an introductory biology lecture course. Archive of the Academic Commons. [Owens et al., 2020] Owens, D. C., Sadler, T. D., Barlow, A. T., and Smith-Walters, C. (2020). Student motivation from and resistance to active learning rooted in essential science practices. Research in Science Education, 50(1):253–277. [Stone, 2012] Stone, B. B. (2012). Flip your classroom to increase active learning and student engagement. In Proceedings from 28th Annual Conference on Distance Teaching and Learning, Madison, Wisconsin, USA. [Touchton, 2015] Touchton, M. (2015). Flipping the classroom and student performance in advanced statistics: Evidence from a quasi-experiment. Journal of Political Science Education, 11(1):28–44. [Wester et al., 2021] Wester, E. R., Walsh, L. L., Arango-Caro, S., and Callis-Duehl, K. L. (2021). Student engagement declines in stem undergraduates during covid-19–driven remote learning. Journal of Microbiology & Biology Education, 22(1):10.1128/jmbe.v22i1.2385. [Wilson, 2013] Wilson, S. G. (2013). The flipped class: A method to address the challenges of an undergraduate statistics course. Teaching of Psychology, 40(3):193–199. [Wood, 2023] Wood, A. (2023). Effective Teaching in Large STEM Classes. IOP Series in Physics Education. IOP Publishing. Publisher Copyright: © IOP Publishing Ltd 2023. All rights reserved. [Zaric et al., 2017] Zaric, N., Scepanovic, S., Markovic, T., Ljucovic, J., and Davcev, D. (2017). The model for gamification of e-learning in higher education based on learning styles. In International Conference on ICT Innovations, pages 265–273. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Eilidh Jack, School of Mathematics and Statistics, University of Glasgow, Glasgow, G12 8QQ (eilidh.jack@glasgow.ac.uk); (2) Craig Alexander, School of Mathematics and Statistics, University of Glasgow, Glasgow, G12 8QQ (craig.alexander.2@glasgow.ac.uk); (3) Elinor Jones, Department of Statistical Science, University College London, London, WC1E 7HB (elinor.jones@ucl.ac.uk). Authors: Authors: (1) Eilidh Jack, School of Mathematics and Statistics, University of Glasgow, Glasgow, G12 8QQ (eilidh.jack@glasgow.ac.uk); (2) Craig Alexander, School of Mathematics and Statistics, University of Glasgow, Glasgow, G12 8QQ (craig.alexander.2@glasgow.ac.uk); (3) Elinor Jones, Department of Statistical Science, University College London, London, WC1E 7HB (elinor.jones@ucl.ac.uk). Table of Links Abstract and Introduction Course information Motivation and intervention Findings Discussion Conclusion and References Abstract and Introduction Abstract and Introduction Course information Course information Motivation and intervention Motivation and intervention Findings Findings Discussion Discussion Conclusion and References Conclusion and References 6 Conclusion The results we present here are in line with previous research (for example [Lo and Hew, 2017], [Buckley and Doyle, 2016], [Dahlstrøm, 2012]) and show a stark increase in student engagement with pre-lecture activities on a course taught in flipped mode. As the pre-lecture activities of interest were quiz-based - with points awarded for attempting the quizzes on time rather than quiz score - we were able to investigate whether the increased engagement was meaningful or the result of students ‘gaming’ the leaderboard. In our study, there was no evidence of the latter. It is thought that the two statistics courses considered here are the only time the students came across the Level Up! plugin or other form of gamification. It is therefore not known whether the increased engagement is due to the novelty of a leaderboard and whether gamification would be as successful if implemented widely across multiple courses. The significant increase in student engagement after the adoption of a gamification strategy is certainly worthy of further research. Though the results from the gamification intervention were very positive, student engagement is still far from perfect. Diversity in teaching and learning approaches is surely the key to engaging students across their courses, with gamification a valuable strategy in a teacher’s toolbox. 7 References [Alomari et al., 2019] Alomari, I., Al-Samarraie, H., and Yousef, R. (2019). The role of gamification techniques in promoting student learning: A review and synthesis: A review and synthesis. Journal of Information Technology Education:Research, 18:395–417. [Blair, 2017] Blair, A. (2017). Understanding first-year students’ transition to university: A pilot study with implications for student engagement, assessment, and feedback. Politics, 37.2:215–228. [Bredow et al., 2021] Bredow, C. A., Roehling, P. V., Knorp, A. J., and Sweet, A. M. (2021). To flip or not to flip? a meta-analysis of the efficacy of flipped learning in higher education. Review of educational research, 91(6):878–918. [Buckley and Doyle, 2016] Buckley, P. and Doyle, E. (2016). Gamification and student motivation. Interactive Learning Environments, 24(6):1162–1175. [Cronhjort et al., 2017] Cronhjort, M., Filipsson, L., and Weurlander, M. (2017). Improved engagement and learning in flipped-classroom calculus. Teaching Mathematics and its Applications: An International Journal of the IMA, 37(3):113–121. [Dahlstrøm, 2012] Dahlstrøm, C. (2012). Impacts of gamification on intrinsic motivation. Education and Humanities Research, pages 1–11. [Deterding et al., 2011] Deterding, S., Khaled, R., Nacke, L. E., Dixon, D., et al. (2011). Gamification: Toward a definition. In CHI 2011 gamification workshop proceedings, volume 12, pages 1–79. Vancouver, Canadá. [Ding et al., 2018] Ding, L., Er, E., and Orey, M. (2018). An exploratory study of student engagement in gamified online discussions. Computers & Education, 120:213–226. [Domínguez et al., 2013] Domínguez, A., de Navarrete, J. S., de Marcos, L., Fernández-Sanz, L., Pagés, C., and Martínez-Herráiz, J.-J. (2013). Gamifying learning experiences: Practical implications and outcomes. Computers & Education, 63:380–392. [Dong et al., 2012] Dong, T., Dontcheva, M., Joseph, D., Karahalios, K., Newman, M., and Ackerman, M. (2012). Discovery-based games for learning software. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’12, page 2083–2086, New York, NY, USA. Association for Computing Machinery. [Ekici, 2021] Ekici, M. (2021). A systematic review of the use of gamification in flipped learning. Education and Information Technologies, 26(3):3327–3346. [Hakulinen et al., 2013] Hakulinen, L., Auvinen, T., and Korhonen, A. (2013). Empirical study on the effect of achievement badges in trakla2 online learning environment. In 2013 Learning and Teaching in Computing and Engineering, pages 47–54. [Hartikainen et al., 2019] Hartikainen, S., Rintala, H., Pylväs, L., and Nokelainen, P. (2019). The concept of active learning and the measurement of learning outcomes: A review of research in engineering higher education. Education Sciences, 9(4):276. [Heilbrunn et al., 2017] Heilbrunn, B., Herzig, P., and Schill, A. (2017). Gamification Analytics—Methods and Tools for Monitoring and Adapting Gamification Designs, pages 31–47. Springer International Publishing, Cham. [Huang and Hew, 2018] Huang, B. and Hew, K. F. (2018). Implementing a theory-driven gamification model in higher education flipped courses: Effects on out-of-class activity completion and quality of artifacts. Computers & Education, 125:254–272. [Ireland and Mouthaan, 2020] Ireland, J. and Mouthaan, M. (2020). Perspectives on curriculum design: comparing the spiral and the network models. Research Matters. [Kim and Castelli, 2021] Kim, J. and Castelli, D. M. (2021). Effects of gamification on behavioral change in education: A meta-analysis. International Journal of Environmental Research and Public Health, 18(7). [Leitner et al., 2017] Leitner, P., Khalil, M., and Ebner, M. (2017). Learning Analytics in Higher Education—A Literature Review, volume 94, pages 1–23. Springer International Publishing. [Lo and Hew, 2017] Lo, C. K. and Hew, K. F. (2017). A critical review of flipped classroom challenges in k-12 education: possible solutions and recommendations for future research. Research and Practice in Technology Enhanced Learning, 12(1):4. [Lo et al., 2017] Lo, C. K., Hew, K. F., and Chen, G. (2017). Toward a set of design principles for mathematics flipped classrooms: A synthesis of research in mathematics education. Educational Research Review, 22:50–73. [Marcey, 2014] Marcey, D. J. (2014). The lecture hall as an arena of inquiry: Using cinematic lectures and inverted classes (clic) to flip an introductory biology lecture course. Archive of the Academic Commons. [Owens et al., 2020] Owens, D. C., Sadler, T. D., Barlow, A. T., and Smith-Walters, C. (2020). Student motivation from and resistance to active learning rooted in essential science practices. Research in Science Education, 50(1):253–277. [Stone, 2012] Stone, B. B. (2012). Flip your classroom to increase active learning and student engagement. In Proceedings from 28th Annual Conference on Distance Teaching and Learning, Madison, Wisconsin, USA. [Touchton, 2015] Touchton, M. (2015). Flipping the classroom and student performance in advanced statistics: Evidence from a quasi-experiment. Journal of Political Science Education, 11(1):28–44. [Wester et al., 2021] Wester, E. R., Walsh, L. L., Arango-Caro, S., and Callis-Duehl, K. L. (2021). Student engagement declines in stem undergraduates during covid-19–driven remote learning. Journal of Microbiology & Biology Education, 22(1):10.1128/jmbe.v22i1.2385. [Wilson, 2013] Wilson, S. G. (2013). The flipped class: A method to address the challenges of an undergraduate statistics course. Teaching of Psychology, 40(3):193–199. [Wood, 2023] Wood, A. (2023). Effective Teaching in Large STEM Classes. IOP Series in Physics Education. IOP Publishing. Publisher Copyright: © IOP Publishing Ltd 2023. All rights reserved. [Zaric et al., 2017] Zaric, N., Scepanovic, S., Markovic, T., Ljucovic, J., and Davcev, D. (2017). The model for gamification of e-learning in higher education based on learning styles. In International Conference on ICT Innovations, pages 265–273. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

Exploring the Impact of Gamification in Flipped Classrooms: Conclusion and References

Loss of Amazon Rainforest Resilience: Author Contributions

Loss of Amazon Rainforest Resilience: Abstract and Introduction

Hateful Meme Detection: Leveraging PVLMs for Zero-shot VQA Probing

This paper is under CC BY-SA 4.0 DEED license. available on arxiv Authors: (1) Juan Mera Men´endez; (2) Martin Bartlett. Table of Links Abstract and Introduction Initial Application Performance Tests Best Practices and Techniques Combinations Discussion Related Work Conclusion and References VIII. CONCLUSION Performance is an aspect that should always be taken into account when creating Lambda functions, especially if you plan to combine them with Java. Once the performance improvements offered by these approaches for using Java with AWS Lambda have been quantified. It is evident that Java can be used competitively with AWS Lambda without the need to resort to runtimes like Node.js or Python (which usually report better performance). Having tested various combinations of proposed strategies and demonstrated that the performance is similar to what can be achieved with the use of GraalVM, we recommend avoiding its usage. We consider it essential to profile the Java functions to select the optimal memory configuration and using AWS SDK v2. From there, optionally, the next step is to the rest of the techniques to achieve one of the proposed combinations. Additionally, following the general best practices such as initializing connections outside the handler or reduce the bundle size, among others, also contribute to optimizing Java functions. The optimization strategies we propose are not the only ones available, there are many other techniques that can similarly yield excellent results. It is important to highlight that the process of optimizing a function is linear in terms of difficulty. In other words, it’s relatively easy to obtain a significant improvement, but if you want to squeeze out the maximum performance, the process requires trial and error and greater effort. It’s also important to highlight that the percentage of improvement offered by each approach depends on the specific use case in which they are applied. This percentage can vary, either increasing or decreasing. REFERENCES [1] H. Puripunpinyo and M. Samadzadeh, “Effect of optimizing java deployment artifacts on aws lambda,” in 2017 IEEE Conference on Computer Communications Workshops (INFOCOMWKSHPS), 2017, pp. 438–443. DOI: 10.1109/INFCOMW.2017.8116416. [2] D. Bardsley, L. Ryan, and J. Howard, “Serverless performance and optimization strategies,” in 2018 IEEE International Conference on Smart Cloud (SmartCloud), 2018, pp. 19–26. DOI: 10.1109/SmartCloud.2018.00012. [3] D. Jackson and G. Clynch, “An investigation of the impact of language runtime on the performance and cost of serverless functions,” in 2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion), 2018, pp. 154–160. DOI: 10.1109/UCC-Companion.2018.00050. [4] O. Hosseini Mehrshad Sahragard, “Aws lambda language performance,” 2019. [Online]. Available: https://gupea.ub.gu.se/handle/2077/62454. [5] A. L. Dowd, “Performance of java in function-as-a-service computing,” University of Texas Libraries, 2020. [Online]. Available: https://repositories.lib.utexas.edu/handle/2152/84357. [6] S. O’Toole, “Aws lambda java tutorial: Reducing cold starts,” 2020. [Online]. Available: https://www.capitalone.com/tech/cloud/aws-lambda-java-tutorial-reduce-cold-starts/v=1694091771423. [7] D. Quaresma, D. Fireman, and T. E. Pereira, “Controlling garbage collection and request admission to improve performance of faas applications,” in 2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), 2020, pp. 175–182. DOI: 10.1109/SBAC-PAD49847.2020.00033. [8] M. Sipek, D. Muharemagi´c, B. Mihaljevi´c, and ˇ A. Radovan, “Enhancing performance of cloudbased software applications with graalvm and quarkus,” in 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO), 2020, pp. 1746–1751. DOI: 10.23919/MIPRO48935.2020.9245290. [9] Q. I. S. Hassan B. Hassan Saman A. Barakat, “Survey on serverless computing,” Journal of Cloud Computing, 2021. [10] C. D. Ron Mosquera Bryan Alexander y Villegas Armijos, “Mejora del rendimiento de aplicaciones serverless basadas en la nube con graalvm y quarkus,” 2022. [11] StackOverflow, “Developer survey 2022,” 2022. [Online]. Available: https://survey.stackoverflow.co/2022/. [12] Q. Wu and L. K. John, “Performance of java in function-as-a-service computing,” in 2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC), 2022, pp. 261– 266. DOI: 10.1109/UCC56403.2022.00047. [13] Datdog, “The state of serverless,” datadog, 2023. [Online]. Available: https://www.datadoghq.com/state-of-serverless/. [14] AWS, “Best practices to work with aws lambda functions,” [Online]. Available: https://docs.aws.amazon.com/es es/lambda/latest/dg/best-practices.html. [15] AWS, “Developer guide - aws sdk for java 2.x,” [Online]. Available: https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/home.html. [16] AWS, “Improving startup performance with lambda snapstart,” [Online]. Available: https://docs.aws.amazon.com/lambda/latest/dg/snapstart.html. [17] AWS, “Java lambda functions customization settings,” [Online]. Available: https://docs.aws.amazon.com/lambda/latest/dg/java-customization.html. [18] AWS, “Lambda instruction set architectures (arm/x86),” [Online]. Available: https://docs.aws.amazon.com/es es/lambda/latest/dg/foundation-arch.html. [19] AWS, “Profiling functions with aws lambda power tuning,” [Online]. Available: https://docs.aws.amazon.com/lambda/latest/operatorguide/p [20] G. org, “Graalvm overview,” [Online]. Available: https://www.graalvm.org/latest/docs/introduction/. [21] A. Stefano Buliani, “Best practices for aws lambda and java,” [Online]. Available: https://d1.awsstatic.com/events/reinvent/2019/REPEAT 1 B

Performance Best Practices Using Java and AWS Lambda: Conclusion and References

Systems Interoperability Types: The Conclusion to Our Tertiary Study

Older and Younger Adults Are Influenced Differently by Dark Pattern Designs: Conclusion & 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 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. Acknowledgments: Keck:I (HIRES), Kepler, MAST (HLSP, K2), SNO, SSO Facilities: astropy (Astropy Collaboration et al. 2013, 2018), batman (Kreidberg 2015), emcee (Foreman-Mackey et al. 2013), isochrones (Morton 2015), prose (Garcia et al. in prep.), SPOCK (Sebastian et al. in prep.), transitleastsquares (Hippke & Heller 2019), w¯otan (Hippke et al. 2019) Software: REFERENCES Allard, F., Homeier, D., & Freytag, B. 2012, Philosophical Transactions of the Royal Society of London Series A, 370, 2765, doi: 10.1098/rsta.2011.0269 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Sip˝ocz, B. M., et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f Bensby, T., Feltzing, S., & Oey, M. S. 2014, A&A, 562, A71, doi: 10.1051/0004-6361/201322631 Borucki, W. 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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

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