La goma del calzado deportivo suele amarillear en poco tiempo, dando la impresión de estar vieja y descuidada. Esta es la forma más sencilla para que vuelva a estar como el primer día

Sal en las zapatillas: la solución para blanquear sin tener que mojarlas o estén húmedas

Aunque tenga fama de saludable, consumir zumo de fruta presenta problemas para la salud que no se encuentran en la pieza de fruta entera.

Soy médico y esta es la razón por la que jamás tomo zumo de naranja natural en España

1935-2023 Jasper John Zumo, 88, of Cheyenne died October 27. Services will be Thursday November 2, 2023 at 2PM at Schrader Funeral Home located at 2222 Russell Avenue in Cheyenne, Wyoming. There will be a reception to follow at the funeral home. Inurnment ...

Zumo, Jasper John

Karlos Arguiñano ha preparado una cazuela fabulosa de costillas de cerdo con salsa de naranja, cuidada al detalle y con su toque personal.

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Cómo hacer un cóctel de calabaza especial para Halloween. Sorprende a tus invitados con un cóctel otoñal delicioso.

Cóctel de calabaza especial Halloween

Aquí tienes la receta de dos dulces tradicionales, unidos en un plato: los pestiños y la compota de manzana. Esta se prepara con zumo de naranja y luego se sirven juntos.

Pestiños de la abuela con compota casera de manzana

Muchas veces, abandonamos nuestro proyecto de adelgazar porque pasamos hambre o no resistimos las ganas de comer. Unos ataques

Estos son los alimentos 'sanos' que dan hambre y abren el apetito (evítalos si quieres adelgazar)

Minicalabazas de queso brie en 'air fryer'. Dentaduras postizas de Drácula. Perritos calientes momia para Halloween. Con Halloween pisándonos los talones, la fiebre por las recetas terroríficas no hac

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Uno de mejores embajadores de la gastronomía de España por todo el mundo, sorprende a sus seguidores reconociendo que es muy fan de añadir siempre a sus sandwiches, sean como sean, este aderezo impres

El ingrediente que no falta en los bocadillos del chef José Andrés: "Nunca hay suficiente"

Hablar y sonreír a menudo hacen que la piel alrededor de la boca se curve, y ciertas expresiones faciales también pueden contribuir a la formación de arrugas

Adiós a las arrugas de alrededor de la boca: la cucharada de yogur que rejuvenece el rostro

Zumo

zumo

Not all crypto products are born equal. Chainalysis’ 2020 Global Adoption Index recently illustrated just how much the adoption of cryptocurrencies is continuing to grow worldwide year on year. Before Zumo arrived in the app store, choosing a place to buy, sell or store your cryptocurrency was a bit like playing that old favourite Minesweeper; the landscape was littered with an array of well-orchestrated scams and schemes ready to rid you of your hard-earned cash. Cryptocurrency scams netted over $4 billion in 2019. Amongst the targets were popular trading exchanges, world-leading social media platforms, and thousands of private email accounts. Blockchain analytics provider Whale Alert earlier this year indicating that $24 million of cryptocurrency was stolen in the first 6 months of 2020 alone. released figures From fake Bitcoin giveaways hosted by Elon Musk (not the real one) to multi-tier Ponzi schemes, scamming  big business in crypto. Here are 5 ways that you could have lost your crypto in 2020: 1. Falling for the biggest Twitter scam of the year Spend 10 minutes scrolling results of a tag search on Twitter. #cryptocurrency You will find an online community full of tech investors, thought-leaders, top tier computer programmers, revolutionaries, and professional meme artists (yes that is a real job now) that live and breathe everything crypto. But what also becomes all too clear whilst clambering through the depths of what is often referred to as “ ” (or CT for short) is that there are plenty of ways to get fleeced of your cash. Crypto Twitter A popular type of scam on Twitter and one that made world news headlines earlier this year is the “fake giveaway”. On July 15th, . The hackers used their profiles to promote a fake cryptocurrency giveaway that promised users $2,000 in Bitcoin in return for $1000. verified Twitter accounts of high profile figures and companies were hacked Accounts hacked included Apple, President Barack Obama, former Vice President Joe Biden, Elon Musk, Kanye West, Bill Gates, and Uber. Hackers collected over $100k of stolen funds from the attack, and accessed Twitter’s “God Mode” through a phishing attack that tricked a Twitter employee into handing over login credentials (we cover the joys of phishing in #5). If you want a safe giveaway, stick with Zumo’s refer and share programme: guaranteed 0.02 Eth for you and for every person you refer, every time. 2. Leaving funds on a centralised exchange (that gets hacked) Centralised exchanges act as a middleman for anyone looking to buy and sell cryptocurrencies. Offering a variety of currencies to trade in a somewhat regulated environment, centralised exchanges are a popular choice for many newcomers to crypto. But there’s an issue. Once deposited on a centralised exchange, the fate of your funds lie entirely in the hands of the exchange owners. Sounds risky? It can be. On September 25th 2020, from KuCoin, a popular cryptocurrency exchange platform. hackers stole more than $275 million worth of cryptocurrency This incident was one of the largest ever exchange hacks and, as the hackers used various methods including mixers, diversifying into a handful of currencies on decentralised exchanges in an attempt to wash their ill-gotten gains, it has been difficult to trace. It is imperative that you take custody of your own funds when not actively trading them. Holding them in a that only you have access to is the only way that you can ensure safety from large scale hacks. secure personal wallet So write it down, make it your morning mantra, heck get it tattooed in your forehead if you must, but always remember: "Not your keys, not your crypto". Zumo hands you the keys and is by far the safest way to interact with your crypto on the blockchain. 3. Getting SIM swapped SIM swapping is on the rise in 2020. SIM swappers trick your mobile service provider into porting your phone number over to a new SIM card embedded in a device that they control. Scammers can gain access to everything on your phone including email accounts, bank accounts and trading exchange accounts. by professors and Ph.D. students at Harvard University highlighted the increased vulnerability to SIM swap attacks in 2020, especially as more people are working remotely than ever before. Research published earlier this year What is scarier is that whilst conducting the study, one of the authors of the research paper himself was SIM swapped. Go figure. To give you an idea of just how much damage can be done through SIM swapping, hold your breath and of how one man lost $24 million of cryptocurrency in a coordinated attack. read this unfortunate tale But don’t worry, if you’re a Zumo app user, even if your SIM were to be swapped, they still wouldn’t be able to access your crypto without your keys. Always keep your key codes separate to your phone! 4. Being tricked by phishing websites 2020 may go down in the history books as the . “year of the phish” Socially engineered cyber attacks might well be this year’s flavour when it comes to scams, and have been prevalent in the cryptocurrency space. These intricately designed attacks often direct people via email to fake websites, ultimately tricking them into unknowingly handing over their private details. Just earlier this month over by scammers that managed to trick users into visiting replicated versions of the popular hardware wallet website Ledger. $280k of the cryptocurrency Ripple (XRP) was stolen This year also saw accused of stealing nearly $17 million worth of cryptocurrencies, in a spate of phishing attacks during 2017 and 2018 that tricked people into visiting replica websites of popular cryptocurrency exchanges. US authorities jail two Russian men Our advice? Stay well aware from anything phishy by only using the Zumo app to exchange cryptocurrencies. 5. Investing in Ponzi schemes Ponzi schemes have been around for a long time and they don’t seem to be going anywhere anytime soon, especially when it comes to cryptocurrency. Ponzis work by convincing you to invest in something with the promise of sizable returns on your investment and little or no risk. Your returns are made with new money when fresh investors are lured into the scheme, creating a pyramid of promised returns and deceit. Most of the time there is, in reality, little or even no business development going on in the background and ultimately these schemes collapse when the founders disappear with all of your funds. Promising a 30% return to investors, the has collected over to date. most recent high profile Ponzi scheme $4 million Conclusion When it comes to cryptocurrency, it’s still a jungle out there. With the total amount of money stolen in crypto scams to date well into the billions of dollars, the utmost care needs to be taken when dipping your toes into the world of cryptocurrency. It isn’t all doom and gloom though; pioneering tech companies around the world are working hard to address these issues head on, and with great effect. Leading the charge is , a company that offers people a way to get involved in cryptocurrencies without the risks, with a secure and easy to use non-custodial cryptocurrency wallet. Zumo and all encryption performed locally, the Zumo app offers users an airtight and easy to use solution for buying, selling, storing, sending and spending both cryptocurrencies and traditional money. With brute force attack protection Discover how Zumo are leading the way into the future of smart, safe and secure money at https://zumo.money.

Top 5 Ways You Lost Your Crypto in 2020

Last week’s landslide victory for Britain’s Labour Party places Keir Starmer in a unique opportunity to reshape the UK’s financial landscape. The Labour Party has already made, as part of its mandate for financial services published in January, a commitment to expand the use of AI in financial services, to move Open Banking forward for “increased competition in retail payments,” to embrace “Open Finance” and to work on creating a UK-central digital currency, a state-backed digital pound. While the details on various proposals were missing in the party’s manifesto which touched upon a central bank digital currency, Labour’s plans for financial services showed “more of a commitment than any other political party” to a creating a digital pound, according to Jannah Patchay, executive board director at the Digital Pound Foundation. In February 2023, the UK Treasury and the Bank of England already QQi announced that state-backed digital pound would likely be introduced later this decade. While the previous Conservative government did not move towards digital currencies due to the fact that cryptocurrencies are not backed by a central bank and the value can shoot up and down rapidly, the digital pound, issued by the Bank of England, would be far less volatile. Ten digital pounds will always be worth the same as £10 in cash, the Treasury maintains. The next hurdle, for the cryptocurrency trade, however, is to convince the UK Treasury and the Bank of England that the technology proposed to develop the digital pound is similar to that of cryptocurrencies such as Bitcoin and Ethereum. And many experts in the field see the new Labour government as having the potential to move towards digital assets, a move that would position the UK as a global cryptocurrency hub, according to Nigel Green, CEO of deVere Group, a leading financial advisory and fintech. Speaking to the Financial Mirror, Green stated, “To date, Starmer’s stance on crypto remains somewhat nebulous,” adding, “That said, Labour’s Rachel Reeves, the new Chancellor of the Exchequer, has shown openness to the tech sector, while MP Tulip Siddiq (formerly Shadow Economic Secretary to the Treasury) has boldly stated that Labour would transform the UK into a global centre for tokenised assets if victorious.” The previous Conservative government led by Rishi Sunak had many intentions—even some unfulfilled plans—to elevate the status of crypto and Web3 in the UK. However, these plans were not developed in any meaningful way. Now, with yet another change of Prime Minister conterminous to a shift in political ideologies, it is possible that the crypto industry may remain in limbo. That said, the new Labour government has given domestic advocacy groups the perfect opportunity to launch their public manifestos in hopes of guiding government policy on cryptocurrency or even crypto lottery. While this surge of interest has certainly not come to the forefront of discussion around the new government without vast lobbying efforts undertaken by the crypto industry, the fact is that many in the crypto sector have been working for years to get the British government on board with crypto and it seems that Labour might be the party to move this agenda forward. According to a survey commissioned by the digital asset platform, Zumo between June 7 and 11, roughly one-third of 3,124 adults between the ages of 18 and 34 in the UK stated they were concerned about the future of crypto in the country while more than a third of young adults believe “the growth of the crypto sector should be a key consideration for politicians, with four in ten considering it vital for the UK’s economic growth prospects.” The support for the digital pound and cryptocurrency is no longer a fledgling dream for England or the rest of Britain. Now, under the Labour government there is  renewed public support that may transform the way montary systems work in favour of the public and not just the financial industry. Last week’s landslide victory for Britain’s Labour Party places Keir Starmer in a unique opportunity to reshape the UK’s financial landscape. The Labour Party has already made, as part of its mandate for financial services published in January, a commitment to expand the use of AI in financial services, to move Open Banking forward for “increased competition in retail payments,” to embrace “Open Finance” and to work on creating a UK-central digital currency, a state-backed digital pound. mandate mandate While the details on various proposals were missing in the party’s manifesto which touched upon a central bank digital currency, Labour’s plans for financial services showed “more of a commitment than any other political party” to a creating a digital pound, according to Jannah Patchay, executive board director at the Digital Pound Foundation . In February 2023, the UK Treasury and the Bank of England already QQi announced that state-backed digital pound would likely be introduced later this decade. Digital Pound Foundation Digital Pound Foundation While the previous Conservative government did not move towards digital currencies due to the fact that cryptocurrencies are not backed by a central bank and the value can shoot up and down rapidly, the digital pound, issued by the Bank of England, would be far less volatile. Ten digital pounds will always be worth the same as £10 in cash, the Treasury maintains. The next hurdle, for the cryptocurrency trade, however, is to convince the UK Treasury and the Bank of England that the technology proposed to develop the digital pound is similar to that of cryptocurrencies such as Bitcoin and Ethereum. And many experts in the field see the new Labour government as having the potential to move towards digital assets, a move that would position the UK as a global cryptocurrency hub, according to Nigel Green , CEO of deVere Group, a leading financial advisory and fintech. Nigel Green Nigel Green Speaking to the Financial Mirror , Green stated, “To date, Starmer’s stance on crypto remains somewhat nebulous,” adding, “That said, Labour’s Rachel Reeves, the new Chancellor of the Exchequer, has shown openness to the tech sector, while MP Tulip Siddiq (formerly Shadow Economic Secretary to the Treasury) has boldly stated that Labour would transform the UK into a global centre for tokenised assets if victorious.” Financial Mirror The previous Conservative government led by Rishi Sunak had many intentions—even some unfulfilled plans—to elevate the status of crypto and Web3 in the UK. However, these plans were not developed in any meaningful way. Now, with yet another change of Prime Minister conterminous to a shift in political ideologies, it is possible that the crypto industry may remain in limbo. That said, the new Labour government has given domestic advocacy groups the perfect opportunity to launch their public manifestos in hopes of guiding government policy on cryptocurrency or even crypto lottery . While this surge of interest has certainly not come to the forefront of discussion around the new government without vast lobbying efforts undertaken by the crypto industry, the fact is that many in the crypto sector have been working for years to get the British government on board with crypto and it seems that Labour might be the party to move this agenda forward. cryptocurrency crypto lottery crypto lottery lobbying lobbying According to a survey commissioned by the digital asset platform, Zumo between June 7 and 11, roughly one-third of 3,124 adults between the ages of 18 and 34 in the UK stated they were concerned about the future of crypto in the country while more than a third of young adults believe “the growth of the crypto sector should be a key consideration for politicians, with four in ten considering it vital for the UK’s economic growth prospects.” survey survey The support for the digital pound and cryptocurrency is no longer a fledgling dream for England or the rest of Britain. Now, under the Labour government there is  renewed public support that may transform the way montary systems work in favour of the public and not just the financial industry. digital pound fledgling dream

UK Labour Party Commits to Digital Pound While Considering Crypto

44,000 startups. 4,553 cities. “4 billion votes” It was such a blessing to get to know so many of your ideas and innovations from every corner of the world in 2021. The startup community amazed all of us with your hard work and persistence despite all of the challenges that we faced globally throughout last year. Not gonna lie, the competition got our hearts racing like Eurovision. We won’t let you wait for much longer, below are long-awaited results! ✨✨✨ To see who is a winner in each respective city, visit and pick a city. The name at the top of the list is the winner. (Compromised awards are under review.) startups.hackernoon.com The will announce the winners per region in their respective cities. Startups Winners Announcement Series 🔥 Central Europe Central Europe has always caught our attention with the talented pool of people in tech community. But were they able to get through 2021 despite the pandemic? Let’s cheers to the most outstanding amongst 4,500+ startups who have been working hard this year: Basel, Switzerland An overwhelming vote for ~ in their mission of helping machinery companies drive more service revenues from their installed base MachiQ Software Berlin, Germany We have with a whooping 538 votes! Let’s support Plan A with its mission to help companies to measure, monitor and reduce their environmental footprint. Plan A Düsseldorf, Germany It doesn’t get any easier with Kicking off in helping people organize online schedules more easily. EasyWeek! Geneva, Switzerland Manage code quality? We have to give props to for their startup! SonarSource Hamburg, Germany Taking over Hamburg is , an acoustic device to reduce noises in vehicle cabins. No more annoying sounds on the road 🚗 ReCalm Köln, Germany Small business? Hoping to manage your marketing campaign? is winning the vote! rankingCoach Lausanne, Switzerland is a Swiss-based company focused on cryptocurrency management solutions built for financial institutions. Metaco Leipzig, Germany empowers companies to operate and utilize drones for the most effective industrial data applications. FlyNex Mainz, Germany is growing sustainable digital mobility startups! Next Mobility Labs Munich, Germany wins for top-line, high-security international Identity Management! ORY Stuttgart, Germany Remote desktop application? Ask anywhere. AnyDesk Vienna, Austria , an IT company enabling privacy-preserving big data applications in the digital age. Mostly AI Zug, Switzerland Way to go 1762 votes for the first provably live pure Proof-of-Stake (PoS) CBC-Casper blockchain designed for real-world applications. CasperLabs! Nyon Calling for robust data solutions for impact-driven organizations! Havuta LLC Zürich is revolutionizing small business lending to give easy access to capital to those who need it most: SMEs ✨ Teylor Heidelberg, Germany is an innovative HR startup providing a solution for fast and efficient recruiting of employees with simple job profiles. Talk'n'Job Stuttgart, Germany Congratulations for winning this title! AnyDesk Moving on to our buddies in... 🔥 Eastern Europe Eastern Europe is home to many familiar big names in our start-up world. Trace history for Miro, Telegram, and Grammarly and you know where they are from. Who is the next generation for Eastern European startups? Budapest, Hungary is a platform for mobile app development, enabling tens of thousands of developers to automate integration, testing, and deployment. Bitrise I__ __ stanbul, Turkey Leading here is - a brand new software intelligence platform- helps organizations deliver faster, high-quality products by connecting their DevOps tools. Oobeya Kraków, Poland is a human cloud platform that connects global enterprises with European software houses, offering tech talent as a service. Talent Alpha Kyiv, Ukraine 281 votes for , an AI powered app where people can swap faces in the videos, GIFs and images in just a few seconds. Reface Sofia, Bulgaria 387 votes for __ __378, leading Blockchain and DLT solutions company that specializes in helping enterprises and blockchain startups design, build and scale innovative solutions using Blockchain & DLT! LimeChain Warsaw, Poland is a next-generation blockchain document management software (DMS). DoxyChain Yerevan, Armenia Whoever clicked to vote for was sure a vote, because it ended up winning as a full-service software provider delivering Artificial Intelligence & Machine Learning solutions for businesses. SmartClick smart Almaty Just like the name suggested, provides one pass to dozens of gyms and studios. 1FIT Debrecen got all the coders ranked figured out! CodersRank Kharkiv is complete solution digital assets management! Pics.io Minsk, Belarus with 243 votes is the first blockchain-powered sports media platform. Scorum Moscow, Russian Federation 1 e-grocery company in Russia with 26 votes and #1 on our HackerNoon board for Minsk. SberMarket Saint Petersburg, Russian Federation leads this area as a personal finance application that rewards responsible spending and savings. CoinKeeper Kazan, Russian Federation Smelling a sweet victory? 3d App designers for flower bouquets is in the house! Flowito Western Europe 🔥 Brexit? Pandemic? It seems like startups in Western Europe still keep their spirits regardless. Startups in Western Europe that stood out in votes this year go to: Antwerp is on a streak! As a bug bounty platform, it ensures online security through a crowd-sourced platform for computer experts. intigriti Belfast A record-breaking 10,003 votes? is an independent coffee shop. Come grab a coffee! Bobs & Berts Birmingham What’s happening in Birmingham? We have , an innovative UK-based advanced lithium battery developer aiming to accelerate the global shift to cleaner. Aceleron Bordeaux 30 is an open-source web framework for building modern apps and websites with Vue.js. NuxtJS Boulogne-billancourt is a software company that provides an in-store analytics platform to optimize operations. DiGEiZ Brighton In for some jam? offers musical education services. BIMM Bristol Another tasty victory for Western Europe is enabling the strongest digital encryption on the internet. KETS Quantum Security Brussels A fashionable win for , a social fashion network. You scan barcodes in fashion shops and see every influencer wearing those outfits! Share your wishlist with your friends and earn cashback. SCANDALOOK Cardiff is a technology company developing end-to-end digital connectivity for the point-of-care diagnostics market. Bond Digital Health London A whooping number of 1085 vote__ __ offers hardware based cyber-security solution for authentication and encryption in a wired local network. Crypto Quantique Edinburgh Hopping up on the crypto movement, just launched last year but they are already rocking it at making crypto accessible to everyone. Zumo Ghent 5379 votes for ! A Belgian InsurTech startup that helps insurance providers all over the world to better connect with their digital customers. WeGroup Glasgow specializes in single-cell analysis transforming the life sciences. Biomage Paris Show some love in the city of love for , a sports platform that is connected to a mobile sports coaching application. AirFit Aberystwyth enables artificial intelligence, data science & digital innovation solutions for the agriculture, biotech & life sciences industries. Agxio Norwich Congratulations for the amazing win of 1124 votes! WATR Charleroi Congratulations for your amazing win! Hirering Gibraltar Give a round of applause to Fortknoxter! Waltham Abbey is ruling the area with its amazing 72 votes! RPAIR Antwerpen Rocking up Antwerpen area is the rising startup ! Willow Egham What’s happening in Egham? Proudly announcing winning the Noonies this year! ATA.ONE Leicester Leicester is calling the name of as the winner for the region! DeadHappy Macclesfield Who else but ? Congratulations on dominating the award! AeroCloud Northern Europe 🔥 Want to listen to some music? Spotify. Need some games to kill time? Candy Crush. What about a quick call to someone you haven’t seen in a long time? Skype. These are all startups that originated from Northern Europe! Noonies, let’s take a look at the upcoming generation of startups from Northern Europe that hopefully will see an even bigger and brighter future. Gothenburg, Sweden Shipping was never made for small shippers, so took on the mission to built an end-to-end logistics platform to empower small businesses to spend less time and money on shipping and more time on growing their businesses. Sendify The Netherlands provides a virtual platform for many kinds of conferences and events. Let's Get Digital Helsinki, Finland A curated collection of public basketball courts in the Helsinki Metropolitan Area called . Everyone is welcome to submit to their local court. Koripallopaikat Lund, Sweden develops an antibiotic-free, safe and effective treatment of vaginal fungal infections. Gedea Biotech Luxembourg, Luxembourg 🚀 is a job-matching platform that connects developers and tech experts with CTOs and team leads from the best tech companies across Europe. 👾 nexten.io Malmö, Sweden Feeling studious, Noonies? __ __e is a tool for Google Classroom, that enables formative matrix assessment towards course learning objectives directly. StudyBe Oslo, Norway is the platform supports a unified API across all connected device categories, removing significant friction for app developers. Domos Labs Reykjavík, Iceland __ __s is a mobile-first technologically advanced neo-bank. Indo service #S__ __ tockholm, Sweden is the biggest blockchain start-up in Sweden. Double winner of the most prestigious nomination in Nordics 'NyTeknik 33-listan', winner of the Deloitte Fast 50, and now Noonies Award! ChromaWay AB T__ __ allinn, Estonia Passing 1000 votes is a fully digital and decentralized ecosystem for all actors in supply chain. OBORTECH Vilnius, Lithuania is an easy-to-use money app for cards and accounts. Via Genome, users can open a business or a merchant account or a personal one with dedicated IBANs, access transfers, exchange currency, process payments, and manage the funds. Genome Aalborg Digura A legaltech offering tenants fast, digital and reliable legal assistance Aarhus Partisia Market Design provides secure, simple, efficient solutions for auctions and exchanges realizing the potential of the market. Helsingborg is a hi-tech company developing cardiac occlusion devices and other vascular implants. Occlutech Tallinna is an AI-powered system for marketing automation in social networks. POSTOPLAN 🔥 Southern Europe Southern Europe’s economy went through a hard time this year due to a huge reduction in tourism. But our startups are of course always headstrong, from Spain to Italy and all the way through Greece. Who are the heroes rising amidst changes of Southern Europe? Skopje is a versatile software development company that solves the business challenges of SMBs, big brands, and brave hearts with awesome ideas. CodeChem Sliema Sounds like just a relaxing exhale. is a holistic health and wellbeing app built to allow users work on the development of their physical, mental and spiritual health Few Tajonar is a company of experienced business & industry entrepreneurs offering solutions to industries based on cutting-edge technologies. das-Nano Tarragona is a technology-based company focusing on the production of integrated microsystems. IMICROQ Terni is an ICT-based integrated solution that is able to modulate, respond, assist and learn to control most home activities. Mind Tirana is a video content and e-commerce platform for the Balkans built on top of an Albanian language specialized search engine. Gjirafa Torino develops and commercializes algorithms based on Artificial Intelligence to increase the autonomy of small satellite missions. AIKO T__ __ orres Buy online groceries like you would buy offline with personalized picking as fast as in 4 hours with Vedras 360hyper! Trento is a music-based platform built around streaming platforms that allow users to discover new emerging artists and make new friends. Brots 2021, what a YEAR. Congratulations to all of the startups that made it to the top winning list for Europe! Stay tuned for Startup awards in 2022 and let’s cheers to a new year of more innovative ideas, bold innovations, and robust creations from you, Europe 🌷 More Information: If you’re a winner, please answer ! If you’re a reader, participant, just a curious individual, consider answering one of our interviews . this interview here Read the FAQs about or . Startups here here To see all of the winners you may visit , pick any city and view the name that appears at the top. this site If you’re interested in partnering with us, we invite you to look through some of these or reach out to our business department. unique sponsorship options Perhaps creating your very own tickles your fancy or maybe you have a whole new idea for how we can partner! writing contest Thank you to all of our sponsors! We truly appreciate your contribution to the tech world and thus the future! The Startups Awards are sponsored by: , , , , , , , , , , Blockster Brex FreeCodeCamp LaunchDarkly Coil Udacity Udemy Vercel Asia Pacific Transgender Network Bybit Everscale Network This post was written by An Le and edited by Natasha Nel. If you have any questions or concerns or would like to report a discrepancy please email ellen@hackernoon.com.

Meet the Winners of Startups in Europe

Bitcoin is making some serious noise, but true adoption lies in simple, safe, and functional apps for the everyday consumer. Here are some worth looking at The last few months have seen again and cryptocurrencies are finally starting to be accepted as a safe, efficient and decentralised means of payment during a time of increased financial instability in many countries. Bitcoin take the centre stage With the initial steps toward mass adoption having been well and truly taken, the ability to use Bitcoin and others to pay for products and services in real world situations such as supermarkets and department stores is critical for the overall acceptance of cryptocurrencies. As more of the increased speed, security and overall lack of middleman services that comes alongside accepting cryptocurrencies, innovative projects are busy implementing payment rails on existing architectures that will enable your local grocery store to accept Bitcoin, making the dream of fast, frictionless and decentralised payments seem closer than ever before. businesses become aware This is all well and good, but there’s something else that plays a huge part in the global adoption of cryptocurrencies - the end product itself. Although many of the crypto wallet and card products currently on the market are taking strides when it comes to innovation, some are still clunky to use and difficult to understand for those uninitiated to the cryptocurrency world; others offer a dizzying array of complex features that can often scare the user out of fully committing. If the world is to go , we need an everyday solution that is so easy to use that we don’t even notice we’re using it. Below is a list of innovative crypto wallet apps that look to simplify the complex mechanisms of cryptocurrencies and that plan to open the floodgates for global adoption, without sacrificing the decentralisation that underpins Bitcoin's core values. “full-time crypto” Xapo Launched back in 2014 and based in Hong Kong, the team behind wallet look to address accessibility and security in the cryptocurrency space. XAPO Startups and wallet developers must ensure that their apps reflect what their users have come to expect from the traditional banking apps they have become used to in years past, and having stored the funds of more than 1.5 million customers worldwide, Xapo offers its customers an overall experience that attempts to mirror conventional banking apps in several ways. The Xapo app enables users to buy and securely store Bitcoin (currently the only cryptocurrency available on the app), as well as allowing them to convert and store their money in any traditional currency. Referred to by The Wall Street Journal as the “Fort Knox of bitcoin storage” and registered in Gibraltar, and customer funds are stored in offline, secure, encrypted servers that are never connected to the internet. Xapo is the first physical cryptocurrency bank Looking to merge crypto with traditional money, the app offers users an intuitive and friendly experience, with the options to send and receive money quickly and easily. Xapo also gives users access to a free virtual card that they can use to make online purchases with no annual fees. Xapo recently that they are “expanding beyond Bitcoin to become a digital bank”, but it has not been made public just what the plans are yet and whether the app will support further cryptocurrencies moving forward. last year announced Zumo With a mission to “make smart money simple”, the wallet looks to have the complete package, offering everything from a friendly and safe to use multi-currency wallet for consumers, to , a plug and play solution that enables brands to accept payments in cryptocurrency securely and easily. Zumo ZumoPay Without a simple, safe and user-friendly wallet, the everyday consumer will be reluctant to explore the benefits of cryptocurrency at all, nevermind think about parking their hard-earned money in “the cloud”. The team behind has kept this in mind and has delivered a product that makes buying, selling, spending and storing cryptocurrencies so frictionless that it feels the same as using a traditional banking app. Edinburgh-based Zumo The upcoming release of the Zumo convertible debit card will mean that anyone can spend cryptocurrencies at any store or location providing the merchant accepts VISA. Zumo app users can fund their Zumo wallet with Pound Sterling (GBP) after linking to their personal bank account, then can exchange their money to cryptocurrencies easily and with minimal fees. Also built with the everyday investor in mind, the allows users to see exactly how much they are holding in their wallets at all times and can also easily keep track of how much profit or loss they are in at any one time, all with simple functionality and easy-to-follow steps. Zumo “Smartfolio” “Exchange Alerts” in-app make the exchange process easy, notifying the user when a currency reaches a certain price, meaning that they can then choose whether to buy or sell an asset for optimal profits. Having recently announced plans for Series A funding, Zumo have already won over many residents of Edinburgh and Glasgow with a that plastered Bitcoin all over the cities busiest hotspots. funky marketing campaign XPocket enables users to make fast and secure cryptocurrency transactions and combines all of the usual functions of a crypto wallet app with the functionality of an exchange, enabling users to buy cryptocurrency directly on the app. XPocket The XPocket app comes with a fully integrated decentralized exchange named , which brings DEX functionality similar to the likes of Uniswap to the user directly without having to leave the app, but features such as this are largely still out of scope for the everyday user so we will focus on the basics. PocketSwap Usability of wallet apps will make or break the general public’s acceptance and understanding of crypto, and the have worked hard to make the app’s UI “normie friendly”. XPocket team The wallet offers users the ability to buy, store, receive and send cryptocurrencies and users are always in control over their private keys, meaning that they and they alone retain access to their funds at all times. Users can also buy cryptocurrencies through the app with a debit or credit card. Bread Wallet The is a free mobile wallet available for both Android and iOS. Released way back in 2015, the BRD wallet has it’s largest user base in North America, although the company has since expanded to operate in over 150 countries. Bread (BRD) wallet There are already a host of apps that allow users to send decentralised payments all over the world but, in order to stand out, crypto wallets today must either offer functionality that is lacking in the space (such as merchant support or support of various currencies) or be best in class for the basics such as security and ease of use. The BRD wallet just like the Zumo wallet is non-custodial, meaning that the user is the only one who has access to their private key, and this along with a super-simple interface means that is could be favourable amongst those entirely new to the world of cryptocurrencies as it ensures top level security. The BRD wallet is free to download, install and use as is storing your crypto in the wallet. Transacting through the app, however, incurs variable fees depending on various factors such as which blockchain network is used and the amount of currency being exchanged. Using a credit card could incur the user as much as 5% in transaction fees which is arguably not as competitive as other apps, and the user’s bank or debit card provider can also charge a processing fee for USD, EUR, CAD, DKK, and GBP deposits. Nonetheless, BRD wallet has stood the test of time when it comes to crypto wallets and is a favourable option for overall . security and ease of use Conclusion whether the banks like it or not and, as the general public only become more interested in what Bitcoin and blockchain technology can offer them in terms of safety, accessibility and transparency, this is set to continue. Cryptocurrencies are smashing through outdated and centralised barriers With the announcement by VISA that it plans to help banks introduce Bitcoin and cryptocurrency buying and trading services in the future, and PayPal trying (and kind of failing) to break into the world of crypto-commerce, it’s becoming clear that in digital payments and are going to soon enough become the new normal. decentralised currencies are the next logical step As the masses realise that the grass really is greener on the other side and start looking for the best way to buy, sell, spend and save cryptocurrencies, the products offering their users the path of least resistance on the road to adoption will emerge victorious.

Crypto on-the-go? 4 Wallet Apps Compared

The Humans of design unprecedented products, and contribute to the internet in unprecedented ways. One such human is from the US - interviewed here following for contributions to . “In these unprecedented times…” Hacker Noon Agnieszka Zimolag a 2020 Noonie Nomination the subject of Product Design Thank you to our 2020 Noonies partners : Sustany Capital , .TECH Domains , Grant for the Web , Skillsoft , Flipside Crypto , Udacity , and Beyondskills ! The Noonies are Hacker Noon’s way of getting to know — from a community perspective —  what matters in tech today. So, we asked our Noonie Nominees to tell us. Here’s what Agnieszka Zimolag had to share. 1.  Which 2020 Noonie have you been nominated for? Hacker Noon Contributor of the Year - PRODUCT DESIGN . 2. Tell us a bit about yourself. I'm a Product Designer at BCGDV, part of the Boston Consulting Group Inc. with 7 years of industry experience working for startups across the US and India. I am excited to be part of a vastly digitizing world where more and more value is captured online and therefore can be made accessible to people and digital ecosystems around us. Product Design is a tool for me that allows me to build interfaces between people and businesses and allow for the exchange of this value. I am constantly trying to learn and update myself about the changing role of the product designers and bring that fresh perspective to the projects I am working on. As a product designer, I am thinking very holistically about the products/services I am working on and when evaluating the Product Market Fit or the Right To Win - I am taking every aspect of the product such as the UX/ Branding/ User Impact/ Business Impact/ Acquisition/ Retention models. I believe that all puzzles need to work together in order to build sustainable and edge-cutting solutions. 3. Tell us about the things you make / write / manage / build. I write about new ideas for products that can help businesses and users to gain more value out of the digitized world. I like to take the specific aspect of the product design for example; building trust or ethical principles and dissect it into small pieces and advise companies how they can implement these changes into their own offerings. These product ideas can be implemented into the organizational structures/ DevOps too and are not bond purely to product design. I am also very enthusiastic about the new technical solutions for example Explainable AI (XAI) and how that can be brought into the product design so that people can use it in the most intuitive and impactful way. To summarize, I am product designer by heart but I am trying to enrich that discipline by doing research in various fields to see how products are going to evolve in a couple of years and bring that knowledge back to the community. 4. What are you most excited about right now? How technology such as quantum technology, blockchain, AI/ML is becoming accessible on the enterprise level and product designers can get their hands dirty with these amusing offerings and be researchers and main stakeholders at the same time! 5. What are you worried about right now? One of things that bothered me is that discontinuity from the research world and the enterprise level design. I would love to see more connections/ interactions happening so both can influence each other and let designers get up-skilled faster. I would like product design field to be evolving at more accelerated pace just like the tech solutions are. 6.   What's the most useful advice you've ever given somebody? Worry later. Try first. Learn from mistakes. 7. How has the pandemic changed your life and/or career? It made me think that we need to shift from the human-centered thinking to more societal, global, civilizational level as we are one big community that lives off the ecosystems surrounding us. 8. If we gave you $10 million to invest in one thing right now, where would you put it? Program that could allow product designers to work with the companies they always dreamt to work with or projects they really want to be involved. I think eye-opening experiences can accelerate someone's life to unprecedented scale and could let more people be super excited about product design discipline! 9. What's an opinion you have that most people don't agree with? Human Centered Design and Design Thinking. I think these terms are overused. Since we face many global challenges we should shift our thinking from the individual level to be more ecosystem oriented and see impact on a larger scale. Design thinking term became vague to me so i would propose to think beyond it and define what actions we should take to iterate. 10. Which apps can't you live without? Definitely Instagram and Linkedin. I just love the amountoof news cming from the tech and design world everyday. 11. What are you currently learning? I am learning about the smart contracts, quantum computing, product management and just discovered this very exciting website called untools - around systemic thinking. VOTE for Agnieszka Zimolag as Hacker Noon Contributor of the Year - PRODUCT DESIGN before voting closes on 12 October, 2020! 🚀 With gratitude to Hacker Noon's 2020 Noonies Partners: Sustany Capital , .TECH Domains , Grant for the Web , Skillsoft , Flipside Crypto , Udacity , and Beyondskills !

"Worry Later. Try First," says Product Designer Agnieszka Zimolag

Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2. Community Challenges Overview and 2.1 CCKS 2. Community Challenges Overview and 2.1 CCKS 2.2 CHIP and 2.3 CCIR, CSMI, CCL and DCIC 2.2 CHIP and 2.3 CCIR, CSMI, CCL and DCIC 3. Evaluation Tasks Overview and 3.1 Information Extraction 3. Evaluation Tasks Overview and 3.1 Information Extraction 3.2 Text Classification and Text Similarity 3.2 Text Classification and Text Similarity 3.3 Knowledge Graph and Question Answering 3.3 Knowledge Graph and Question Answering 3.4 Text Generation and Knowledge Reasoning and 3.5 Large Language Model Evaluation 3.4 Text Generation and Knowledge Reasoning and 3.5 Large Language Model Evaluation 4. Translational Informatics in Biomedical Text Mining 4. Translational Informatics in Biomedical Text Mining 5. Discussion and Perspective 5.1. Contributions of Community Challenges 5.1. Contributions of Community Challenges 5.2. Limitations of Current Community Challenges 5.2. Limitations of Current Community Challenges 5.3. Future Perspectives in the Era of Large Language Models, and References 5.3. Future Perspectives in the Era of Large Language Models, and References Figure Legends and Tables Figure Legends and Tables Figure Legends and Tables This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. available on arxiv Authors:
(1) Hui Zong, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally;
(2) Rongrong Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally;
(3) Jiaxue Cha, Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Bio-Medicine, Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China;
(4) Erman Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China;
(5) Jiakun Li, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China;
(6) Liang Tao, Faculty of Business Information, Shanghai Business School, Shanghai, 201400, China;
(7) Zuofeng Li, Takeda Co. Ltd., Shanghai, 200040, China;
(8) Buzhou Tang, Department of Computer Science, Harbin Institute of Technology, Shenzhen, 518055, China;
(9) Bairong Shen, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and a Corresponding author. Authors: Authors: (1) Hui Zong, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally; (2) Rongrong Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally; (3) Jiaxue Cha, Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Bio-Medicine, Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China; (4) Erman Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China; (5) Jiakun Li, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China; (6) Liang Tao, Faculty of Business Information, Shanghai Business School, Shanghai, 201400, China; (7) Zuofeng Li, Takeda Co. Ltd., Shanghai, 200040, China; (8) Buzhou Tang, Department of Computer Science, Harbin Institute of Technology, Shenzhen, 518055, China; (9) Bairong Shen, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and a Corresponding author.

Figure Legends and Tables for Our Biomedical Text Mining Research

Future Perspectives in the Era of Large Language Models, and References

Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2. Community Challenges Overview and 2.1 CCKS 2. Community Challenges Overview and 2.1 CCKS 2.2 CHIP and 2.3 CCIR, CSMI, CCL and DCIC 2.2 CHIP and 2.3 CCIR, CSMI, CCL and DCIC 3. Evaluation Tasks Overview and 3.1 Information Extraction 3. Evaluation Tasks Overview and 3.1 Information Extraction 3.2 Text Classification and Text Similarity 3.2 Text Classification and Text Similarity 3.3 Knowledge Graph and Question Answering 3.3 Knowledge Graph and Question Answering 3.4 Text Generation and Knowledge Reasoning and 3.5 Large Language Model Evaluation 3.4 Text Generation and Knowledge Reasoning and 3.5 Large Language Model Evaluation 4. Translational Informatics in Biomedical Text Mining 4. Translational Informatics in Biomedical Text Mining 5. Discussion and Perspective 5.1. Contributions of Community Challenges 5.1. Contributions of Community Challenges 5.2. Limitations of Current Community Challenges 5.2. Limitations of Current Community Challenges 5.3. Future Perspectives in the Era of Large Language Models, and References 5.3. Future Perspectives in the Era of Large Language Models, and References Figure Legends and Tables Figure Legends and Tables 5.2. Limitations of Current Community Challenges There are some limitations in current community challenge evaluation tasks on biomedical text mining. Firstly, there is a lack of representativeness of data in evaluation tasks. Biomedical and healthcare data possess sensitivity and privacy concerns, making it difficult to obtain largescale datasets. This results in many tasks using small or synthetic datasets, which may limit the representativeness and applicability. Data quality and annotation are also challenging, as the annotation of medical data are complex and requires high levels of expertise from annotators. For data types, many tasks only collect a single type of data. In the future, task organizer should consider incorporating data from multiple sources and modalities. Additionally, some datasets are restricted for use only during the evaluations and not made available afterward, limiting the impact of community challenge evaluation tasks. Secondly, the developed solutions may lack sufficient innovation and exhibit poor reproducibility. Some participants tend to apply established methods to achieve quick results, rather than exploring novel and innovative approaches. This can lead to a lack of innovation and diversity in methods, limiting further technical advancements. On the other hand, some algorithms may perform well on specific datasets but fail to generalize to others, reducing their broad applicability and reliability. To encourage innovation, future community challenges should emphasize the exploration of novel techniques and reward participants for their creativity. When integrating with existing systems, algorithm performance must be evaluated across multiple datasets and scenarios to ensure robustness and generalizability. Lastly, there exists a gap between evaluation tasks and applications in clinical practice. These tasks are generally abstracted from complex real-world problems and simplified to facilitate evaluation and comparison. However, such simplification may not reflect the complexity, diversity, and ambiguity of problems in real-world clinical settings. For example, several tasks focus on fundamental NLP tasks, such as medical information extraction and text classification, while more intricate challenges closely aligned with clinical practice are lacking. In real-world clinical practice, models always need to handle more noise and uncertainty, which may not have been fully considered in current evaluation tasks. Therefore, even systems that perform well in evaluation tasks may not be able to achieve similar results in practical applications. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. available on arxiv Authors:
(1) Hui Zong, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally;
(2) Rongrong Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally;
(3) Jiaxue Cha, Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Bio-Medicine, Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China;
(4) Erman Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China;
(5) Jiakun Li, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China;
(6) Liang Tao, Faculty of Business Information, Shanghai Business School, Shanghai, 201400, China;
(7) Zuofeng Li, Takeda Co. Ltd., Shanghai, 200040, China;
(8) Buzhou Tang, Department of Computer Science, Harbin Institute of Technology, Shenzhen, 518055, China;
(9) Bairong Shen, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and a Corresponding author. Authors: Authors: (1) Hui Zong, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally; (2) Rongrong Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally; (3) Jiaxue Cha, Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Bio-Medicine, Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China; (4) Erman Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China; (5) Jiakun Li, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China; (6) Liang Tao, Faculty of Business Information, Shanghai Business School, Shanghai, 201400, China; (7) Zuofeng Li, Takeda Co. Ltd., Shanghai, 200040, China; (8) Buzhou Tang, Department of Computer Science, Harbin Institute of Technology, Shenzhen, 518055, China; (9) Bairong Shen, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and a Corresponding author.

Limitations of Current Biomedical Text Mining Community Challenges

Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2. Community Challenges Overview and 2.1 CCKS 2. Community Challenges Overview and 2.1 CCKS 2.2 CHIP and 2.3 CCIR, CSMI, CCL and DCIC 2.2 CHIP and 2.3 CCIR, CSMI, CCL and DCIC 3. Evaluation Tasks Overview and 3.1 Information Extraction 3. Evaluation Tasks Overview and 3.1 Information Extraction 3.2 Text Classification and Text Similarity 3.2 Text Classification and Text Similarity 3.3 Knowledge Graph and Question Answering 3.3 Knowledge Graph and Question Answering 3.4 Text Generation and Knowledge Reasoning and 3.5 Large Language Model Evaluation 3.4 Text Generation and Knowledge Reasoning and 3.5 Large Language Model Evaluation 4. Translational Informatics in Biomedical Text Mining 4. Translational Informatics in Biomedical Text Mining 5. Discussion and Perspective 5.1. Contributions of Community Challenges 5.1. Contributions of Community Challenges 5.2. Limitations of Current Community Challenges 5.2. Limitations of Current Community Challenges 5.3. Future Perspectives in the Era of Large Language Models, and References 5.3. Future Perspectives in the Era of Large Language Models, and References Figure Legends and Tables Figure Legends and Tables 5.1. Contributions of Community Challenges Community challenges has made significant contributions for biomedical text mining research in many aspects. We summarize five notable contributions ranging from research level to application level, including driving the development of data standards and evaluation benchmarks, promoting technological innovation and development, fostering interdisciplinary collaboration and communication, promoting education and training, facilitating translational informatics application (see Figure 4). Datasets and benchmarks Datasets and benchmarks The community challenges generally release datasets that are related to specific NLP tasks. These datasets are manually annotated by domain experts, and are sourced from a wide range of biomedical materials, such as published literatures, clinical records, and internet forums. These datasets serve as valuable resources for training and evaluating models, as well as benchmarks for comparing the performance of different approaches. For example, researchers have developed the benchmark CBLUE [64], which combines datasets from multiple shared tasks and aims to evaluate the model's ability in Chinese biomedical language understanding. Moreover, Recently, researchers have also transformed numerous tasks into prompt-based language generation tasks and construct an evaluation benchmark PromptCBLUE [59], which aims to evaluate the capabilities of large language models in healthcare domain. Technology innovation and development Technology innovation and development The community challenges encourage participants to propose state-of-the-art algorithms and methodologies to address problems in biomedical text mining. This competitive environment stimulates researchers' innovative thinking and technological advancements, driving the development and breakthroughs in the field. Taking the information extraction tasks as an example. Initially, early solutions relied on rule-based and dictionary-based methods. Then, deep neural network methods, particularly long short-term memory (LSTM) architecture, gradually gained traction and garnered significant attention. Subsequently, BERT renowned for their powerful text representation capabilities, were often used by participants and found applications in various biomedical fields [68]. In recent research, large language models such as ChatGPT have also been leveraged for purposes such as data augmentation or zero-shot information extraction [69], showcasing their potential for advancing the field even further. Interdisciplinary collaboration and communication Interdisciplinary collaboration and communication Numerous experts with different research background participate in these community challenges. These experts, hailing from both academia and industry, come together through academic conferences to showcase their algorithm architectures, performance outcomes, and explore potential collaboration opportunities. Additionally, the community challenges also provide benefits to participants through the publication of papers on specific task topics. This interdisciplinary collaboration and communication play a crucial role in promoting knowledge sharing and cooperation among different domains, thus driving the development of biomedical text mining. Education and training Education and training The evaluation tasks serve as valuable learning and practical resources for students and beginners in the BioNLP domain. They allow participants to focus on specific tasks, engage in competition, discuss with experts, and improve their skills by evaluating their methods and receiving constructive feedback. After the task is completed, the researchers can further utilize the dataset to evaluate the algorithms and publish articles. Moreover, these shared tasks also provide open access to relevant datasets, which are often used by universities for teaching courses and practical exercises to assess student learning performance. It is worth noting that some datasets explicitly state their restriction to be used only during community challenges and are not made available thereafter. Translational informatics application Translational informatics application Biomedical text mining has the potential to contribute significantly to the standardization of knowledge. By extracting valuable information from vast volumes of biomedical literature, it becomes possible to establish high-quality knowledge bases and ontologies. These resources, in turn, can offer timely evidence-based information for researchers, clinicians, and policy makers. For example, mining the gene-disease semantic associations from literatures can help researchers in discovering novel gene candidates related to diseases [70], while extracting PICOS information from the literature can contribute to the construction of clinical evidence knowledge bases [71]. Biomedical text mining plays a crucial role in clinical decision support. Through the extraction and normalization of clinical information, large quantities of unstructured clinical textual data can be converted into structured and computable formats. This transformation enables clinicians to access comprehensive and accurate patient information, facilitating clinical diagnosis and treatment recommendations. Moreover, biomedical text mining techniques can also be employed in epidemic trend prediction and risk assessment. By mining extensive clinical textual data, it becomes possible to identify key features and patterns associated with patients, which enabling the implementation of appropriate intervention measures to improve patient health outcomes. Biomedical text mining holds significant potential for commercial applications. In the community challenges, multiples evaluation tasks are organized by company. These tasks typically employ data from real-world healthcare sources and have clear clinical application scenarios, such as patient health consultation, and automated question answering. The successful development of solutions for these tasks can provide opportunities and competitive advantages for businesses. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. available on arxiv Authors:
(1) Hui Zong, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally;
(2) Rongrong Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally;
(3) Jiaxue Cha, Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Bio-Medicine, Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China;
(4) Erman Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China;
(5) Jiakun Li, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China;
(6) Liang Tao, Faculty of Business Information, Shanghai Business School, Shanghai, 201400, China;
(7) Zuofeng Li, Takeda Co. Ltd., Shanghai, 200040, China;
(8) Buzhou Tang, Department of Computer Science, Harbin Institute of Technology, Shenzhen, 518055, China;
(9) Bairong Shen, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and a Corresponding author. Authors: Authors: (1) Hui Zong, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally; (2) Rongrong Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally; (3) Jiaxue Cha, Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Bio-Medicine, Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China; (4) Erman Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China; (5) Jiakun Li, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China; (6) Liang Tao, Faculty of Business Information, Shanghai Business School, Shanghai, 201400, China; (7) Zuofeng Li, Takeda Co. Ltd., Shanghai, 200040, China; (8) Buzhou Tang, Department of Computer Science, Harbin Institute of Technology, Shenzhen, 518055, China; (9) Bairong Shen, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and a Corresponding author.

The Impact of Community Challenges on Biomedical Text Mining Research

Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2. Community Challenges Overview and 2.1 CCKS 2. Community Challenges Overview and 2.1 CCKS 2.2 CHIP and 2.3 CCIR, CSMI, CCL and DCIC 2.2 CHIP and 2.3 CCIR, CSMI, CCL and DCIC 3. Evaluation Tasks Overview and 3.1 Information Extraction 3. Evaluation Tasks Overview and 3.1 Information Extraction 3.2 Text Classification and Text Similarity 3.2 Text Classification and Text Similarity 3.3 Knowledge Graph and Question Answering 3.3 Knowledge Graph and Question Answering 3.4 Text Generation and Knowledge Reasoning and 3.5 Large Language Model Evaluation 3.4 Text Generation and Knowledge Reasoning and 3.5 Large Language Model Evaluation 4. Translational Informatics in Biomedical Text Mining 4. Translational Informatics in Biomedical Text Mining 5. Discussion and Perspective 5.1. Contributions of Community Challenges 5.1. Contributions of Community Challenges 5.2. Limitations of Current Community Challenges 5.2. Limitations of Current Community Challenges 5.3. Future Perspectives in the Era of Large Language Models, and References 5.3. Future Perspectives in the Era of Large Language Models, and References Figure Legends and Tables Figure Legends and Tables 4. Translational Informatics in Biomedical Text Mining Based on the perspective of translational informatics, Figure 3 demonstrates the community challenges in biomedical text mining, which aims in health information processing that collected from diverse biomedical resources by leveraging various NLP technologies, and has numerous applications in clinical translational research. Translational informatics refers to the application of data science and computational approaches to bridge the gap between biomedical research and clinical practice. In this context, biomedical text mining plays a crucial role in extracting valuable information from large volumes of biomedical texts, such as electronic health records, scientific literatures, clinical trial reports, medical books, clinical practice guidelines, and even the internet. By using a variety of NLP technologies, including named entity recognition, normalization, attribute extraction, relation extraction, event extraction, text classification, text similarity, knowledge graph, question answering, and text generation, biomedical text mining enables the efficient processing and analysis of biomedical texts, leading to various clinical translational applications such as medical text mining and information processing, clinical data management, terminology standardization, health consultation, question-answering, disease prediction, epidemic forecasting, clinical decisionmaking, and knowledge discovery. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. available on arxiv Authors:
(1) Hui Zong, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally;
(2) Rongrong Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally;
(3) Jiaxue Cha, Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Bio-Medicine, Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China;
(4) Erman Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China;
(5) Jiakun Li, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China;
(6) Liang Tao, Faculty of Business Information, Shanghai Business School, Shanghai, 201400, China;
(7) Zuofeng Li, Takeda Co. Ltd., Shanghai, 200040, China;
(8) Buzhou Tang, Department of Computer Science, Harbin Institute of Technology, Shenzhen, 518055, China;
(9) Bairong Shen, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and a Corresponding author. Authors: Authors: (1) Hui Zong, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally; (2) Rongrong Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and the author contributed equally; (3) Jiaxue Cha, Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Bio-Medicine, Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China; (4) Erman Wu, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China; (5) Jiakun Li, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China; (6) Liang Tao, Faculty of Business Information, Shanghai Business School, Shanghai, 201400, China; (7) Zuofeng Li, Takeda Co. Ltd., Shanghai, 200040, China; (8) Buzhou Tang, Department of Computer Science, Harbin Institute of Technology, Shenzhen, 518055, China; (9) Bairong Shen, Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, China and a Corresponding author.

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