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Bitfinex Bitcoin whale hints recent BTC rally to $9,850 is manipulated and unsustainable – CryptoSlate

Joe007, a well-known whale who trades with massive size, hinted that the recent Bitcoin rally to $9,800 is manipulated. According to the Bitfinex Leaderboard, Joe007 has traded $68 million in volume in the past week alone. Why is the Bitcoin upsurge manipulated? Ever since the Bitcoin price was at around $8,300, major platforms like BitMEX []

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Lightning Labs Raises $10M Series A to Be the ‘Visa’ of Bitcoin – CoinDesk

Lightning Labs has raised $10 million in Series A financing as it gears up to launch its first paid service for merchants looking to accept bitcoin payments.

Craft Ventures led the round, with Managing Director Brian Murray joining Lightning Labs board of directors. Other investors include Slow Ventures, former Goldman Sachs co-head of securities David Heller, Avichal Garg of Electric Capital and Ribbit Capital.

The funding round suggests some investors see the San Francisco-based startup as one of the few protocol-oriented firms with a prospective business model.

If bitcoin is going to reach its potential as a viable global currency, its going to need to scale beyond the base layer, Murray said. Similar to how Visa relieves banks from handling all fiat currency traffic, Lightning relieves the base bitcoin chain from handing all transactions, thus bring more speed and fee efficiency to the network.

Stepping back, Lightning Labs released a beta version of the scaling solution LND in 2018 and previously raised $2.5 million in a seed round from investors including Twitter CEO Jack Dorsey, Square executive Jacqueline Reses, litecoin creator Charlie Lee and former PayPal COO David Sacks. Lightning Labs also launched a mobile wallet app in June 2019, and as of today the company is offering a paid service called Lightning Loop.

Loop aims to help merchants manage their payment channels more effectively. Lightning payment channels need to have bitcoin in them in order to stay open, which is a problem for those who actually use these channels without a perfectly balanced in-and-out flow.

Loop in helps people put funds into their existing channel kind of like a prepaid debit card for a lightning account, Lightning Labs CEO Elizabeth Stark said. Loop out is currently the most popular product because it allows people to continue receiving funds on lightning.

This service, which will charge a small percentage of each full loop, helps merchants and exchanges maintain liquidity in the channels.

With nearly a dozen lightning startups sprouting up over the past two years, Stark said her startup will distinguish itself by becoming an infrastructure provider to other startups.

The first Lightning Conference in Berlin attracted 500 participants in 2019, so there may initially be a small pool of developers and service providers willing to pay for back-end support. The way I see it, there will be an aggregate of financial services, of which Loop is one, and you can batch all of those, Stark said. The blockchain becomes an anchor layer for other Layer 2 services on lightning.

One example might include the shopping app Fold, which processed roughly 1,600 lightning payments during the 2019 holiday shopping season.

"Were growing fast and Lightning Labs loop service makes it simple to manage our lightning nodes liquidity, letting our team focus on building out great user experiences that bring lightning to the world," Fold's Will Reeves told CoinDesk.

Infrastructure spending

Beyond Loop, Stark said her startup will focus on options for larger payment channels in 2020, both opt-in channels that can individually hold more than $1,500 and Atomic Multi-Path Payments, which break payments into smaller parts and are able to return the whole amount if all the small parts dont promptly arrive at the same recipient.

River Financial CEO Alexander Leishman said his exchange startup, which uses LND to offer users lightning liquidity and trading functions, said Lightning Labs and ACINQ are the only two startups in the space focused on the nitty gritty of protocol development.

If it allows us to support larger amounts [of bitcoin] off-chain, it improves the experience for our users. Weve already had users that are frustrated with the [Lightning Networks] limits, Leishman said. Services that would make [lightning transactions] easy for us are definitely of interest.

Stark, who is an adviser to Leishmans exchange, said her goal for Lightning Labs is to enable automated services so the network will just work without clients needing to tamper with channel allocation and flows. The peer-to-peer messaging app Sphinx also uses LND, which Murray said is only possible because of what Lightning Labs is building.

Lightning Labs is building the channels for bitcoin to fulfill its promise as a medium of exchange, a means of micropayment, as remittance infrastructure, and much more," investor Jill Carlson of Slow Ventures said in a press release.

Murray agreed, adding he strongly believes the infrastructure behind popular mobile apps will take a different shape over the next decade because it will enable direct payments between peers instead of reliance on a third-party provider that monetizes user data.

In the meantime, Stark is optimistically curious about the ability to send small amounts of data and have payments attached to them.

Speaking more broadly of the batched services Lightning Labs will offer by this time in 2021, she concluded: These are lightning-native financial services that help improve the network.

The leader in blockchain news, CoinDesk is a media outlet that strives for the highest journalistic standards and abides by a strict set of editorial policies. CoinDesk is an independent operating subsidiary of Digital Currency Group, which invests in cryptocurrencies and blockchain startups.

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Dutch university pays $220K in Bitcoin to alleged Russian hackers – The Next Web

A Dutch university resorted to paying hackers $220,000 in Bitcoin BTC to release computer systems held for ransom since Christmas Eve, reports Reuters.

University of Maastricht vice president Nick Bos announced at a press conference on Wednesday it had bowed to the cyberattackers demands, as it otherwise wouldve had to rebuild its entire IT network to get back online.

The damage of that to the work of the students, scientists, staff, as well as the continuity of the institution, can scarcely be conceived, said university vice president Nick Bos, as quoted by Reuters.

Bos confirmed the attackers gained entry to the network after compromising an employees email account in November 2019 via phishing.

By December 24 last year, the hackers had encrypted the universitys computer systems, including workstations and email servers, and demanded 30 BTC for a tool to unlock them (worth $216,000 then, $294,000 today).

Cybersecurity firm Fox-IT, hired by the University of Maastricht to recover its systems, found Russian-speaking cybercriminal group TA505, also known as Evil Corp, responsible for the attack.

The US Department of Justice believes TA505 has caused over $100 million worth of losses since its inception, having hit financial institutions and retailers in several countries with its information-stealingDridex malware.

A recent investigation found more than 1,000 potential TA505 victims across the world.

Ransomware incidents like these persist across the world. In the past two years, hackers have taken over the computer networks of governments, businesses, hospitals, and schools,often demanding millions of dollars in cryptocurrency (mostBitcoin) for a decryption tool.

Theyre indeed so prevalent that the FBI issued a warning in October urging ransomware victims not to pay their hackers, lest they be encouraged to carry out more attacks.

As for the University of Maastricht, its computer systems are reportedly back online and now fully operational.

Published February 7, 2020 11:27 UTC

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Warren Buffett Changes His Take on Bitcoin (BTC) Is This Real? – U.Today

During the overhyped meal with the Tron chief executive Justin Sun, which finally took place earlier this year, investment guru Warren Buffett did not say a singlebad word about Bitcoin to the Tron CEO and his guests: eToro CEO Charlie Leeand other top reps from the blockchain sphere.

While talking to Justin Sun and the other top reps of the blockchain and crypto industries, Warren Buffett spoke his mind on several major issues.

The old school investment guru said that Bitcoin still has a long ways to go to fulfillthe value of the blockchain. Therefore, he is certainthat his grandson will inherit his fortune not in Bitcoin but in good-old US dollars.

The DLT technology has great potential, reckons Buffett. A lot of the companies he has invested in, including JP Morgan, the banking giant, are studying blockchain and the opportunities it may offer. As per Justin Sun, the investment guru is curious to see how DLT will change the sphere of payments in the next decade.

Must Read

Being of a positive opinion of Elon Musk as an entrepreneur, Buffett thinks that Tesla shares are not the best asset to invest in at the moment Tesla has too many competitors in the market who havea lot of cash and who will not go away, the investor believes.

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US Marshals Will Auction $40M in Bitcoin This Month – Coindesk

The U.S. Marshals Service is auctioning nearly $40 million in bitcoin, the first such auction since the end of 2018.

The Marshals will auction "approximately" 4,040 bitcoin, worth $37.7 million at press time, according to CoinDesk's Bitcoin Price Index, to registered bidders on Feb. 18, the press release said. Potential bidders must register by Feb. 12.

"The auction will take place during a six-hour period Feb. 18. Bids will be accepted by email from pre-registered bidders only," the release said.

Bidders will also be required to make a $200,000 deposit before being able to bid. Participants who do not win their bids will receive these back.

The bitcoin will be sold in four lots, with 2,500, 1,000, 500 and 40.54069820 bitcoin each. The first three lots are further split into blocks, each with their own set number of bitcoin.

The bitcoin for this month's auction come from more than 50 administrative forfeitures and legal cases, according to the Marshals' website.

The leader in blockchain news, CoinDesk is a media outlet that strives for the highest journalistic standards and abides by a strict set of editorial policies. CoinDesk is an independent operating subsidiary of Digital Currency Group, which invests in cryptocurrencies and blockchain startups.

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Bitcoin Starts Convincing Rally To $10K After Short Term Correction: Here Are Key Hurdles – newsBTC

Bitcoin price remained well bid above $9,000 and rallied to a new 2020 high against the US Dollar. BTC is now trading nicely above $9,500 and signaling a strong increase to $10,000.

Recently, there was a downside correction in bitcoin from the $9,600 area against the US Dollar. BTC traded below the $9,400 and $9,300 levels, before the bulls took a stand above $9,000.

A swing low was formed near $9,079 and the price started a fresh increase above the $9,200 resistance area. The bulls gained pace and pushed the price above the 100 hourly simple moving average and the $9,500 resistance area.

Finally, there was a break above the $9,600 resistance area and the price traded to a new 2020 high at $9,764. Bitcoin is currently correcting lower below the $9,700 level.

It traded below the 23.6% Fib retracement level of the recent rally from the $9,076 low to $9,764 high. However, the previous resistance near the $9,500 and $9,520 levels is acting as a strong support area.

More importantly, there is a major bullish trend line forming with support near $9,460 on the hourly chart of the BTC/USD pair. On the upside, there are short term hurdles near the $9,700 and $9,750 levels.

Bitcoin Price

A successful break above the $9,750 level is likely to set the pace for a larger upward move. The main target could be $10,000, followed by $10,200.

On the downside, there are many key supports for bitcoin bulls near the $9,500 area. The next key support is seen near the $9,420 level. It coincides with the 50% Fib retracement level of the recent rally from the $9,076 low to $9,764 high.

Any further losses may perhaps lead the price towards the $9,340 level and the 100 hourly SMA, where the bulls are likely to take a stand.

Technical indicators:

Hourly MACD The MACD is about to move back into the bullish zone.

Hourly RSI (Relative Strength Index) The RSI for BTC/USD is currently rising and it is well above the 55 level.

Major Support Levels $9,500 followed by $9,420.

Major Resistance Levels $9,700, $9,750 and $10,000.

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Bitcoin Starts Convincing Rally To $10K After Short Term Correction: Here Are Key Hurdles - newsBTC

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Stats Perform’s Chief Scientist of Artificial Intelligence to Deliver Keynote at AI in Team Sports Conference – Business Wire

CHICAGO--(BUSINESS WIRE)--Stats Perform, the revolutionary leader in sports AI and data, announced that Chief Scientist Dr. Patrick Lucey will deliver keynote remarks at the Association for the Advancement of Artificial Intelligence (AAAI-20) Workshop in Team Sport in New York on Saturday, February 8.

Dr. Luceys presentation Interactive Sports Analytics will examine new ways to break down player or team performance using big data and AI software. The presentation will include examples of how coaches can draw up and search for specific plays and, using AI and Stats Performs decades of tracking and multi-agent trajectory data, simulate likely outcomes specific to a particular opponent and the players involved. In addition, Dr. Lucey will demonstrate the capabilities of new body-pose data made possible through Stats Performs state of the art AutoSTATS technology.

We have reached an exciting moment in sports where coaches and analysts can now leverage big data and AI to generate advanced insights on play development and likely outcomes, Dr. Lucey said. Imagine a coach drawing up an Xs and Os play, the same way he would on chalkboard, on an iPad and simulating likely outcomes based on different sets of offensive and defensive opponents in-play. Imagine then being able to search that play and find video of every time a near similar play was run. With AI and big data, we are already making that happen at Stats Perform and I cant wait to meet and discuss this with the illustrious group of researchers at the AAAI Workshop.

The AAAI Workshop in Team Sport is one of the leading conferences for AI in team sports with participation from some of the leading global research institutions. The 34th AAAI Conference will include a research paper and poster track.

About Stats Perform

Stats Perform collects the richest sports data in the world and transforms it through revolutionary artificial intelligence (AI) to unlock the most in-depth insights for media and technology, betting and team performance. With company roots dating back almost 40 years, Stats Perform embraces and solves the dynamic nature of sport be that for digital and broadcast media with differentiated storytelling, tech companies with reliable and fast data to power their innovations, sportsbooks with in-play betting and integrity services, or teams with first-of-its-kind AI analysis software. As the leading sports data and AI company, Stats Perform works with the top global sports media, tech companies, sportsbooks, teams and leagues. For more information, visitStatsPerform.com

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Global Forecast on Artificial Intelligence (AI) in the Freight Transportation Industry (2020 to 2025) – Disruptive Impact of AI on Freight…

The "Artificial Intelligence (AI) in the Global Freight Transportation Industry, Forecast to 2025" report has been added to ResearchAndMarkets.com's offering.

This study analyses the key trends and applications of artificial intelligence in the freight transportation industry by mode of transport i.e. road, rail, air, and ocean freight transportation. This research also analyses the disruptive impact of artificial intelligence on freight transportation business operations and discusses its adoption prospects until 2025.

Market Insights

With increased trade flow, the fleet population in freight transportation has become denser, and expectations of customers have evolved beyond recognition, resulting in complex transport operations, requiring operational flexibility from freight operators. Human errors in operations, underutilized assets, low workforce productivity, inefficient operational planning, inability to match supply with demand, and trimmed profit margins are key prevailing concerns with freight operators.

The emergence of digital technologies and the rapid technological advancements in digitization have transformed the business and operational landscape of the global freight transportation industry. It is essential for freight operators to embrace such operational complexity and evolve by adopting technologies to turn complexity into an advantage.

Today, the world is connected more than ever, and the growth of data generation has been exponential with smart devices and process automation. Data-driven insights help freight operators move forward and gain a competitive advantage over their peers. Artificial intelligence enables freight operators to harness data more effectively for actionable insights.

Artificial intelligence-powered systems in conjunction with other digital technologies such as internet of things and big data analytics utilize data to its full potential to anticipate events for freight operators, aiding them to avoid risks and create innovative solutions. Machine learning algorithms based on neural networks powered by artificial intelligence would unlock multiple benefits for companies operating in the freight transportation industry.

AI brings changes to the supply chain with autonomous vehicles, helping fleet operators reduce operating cost with and fuel consumption and plan optimized routes for service. The freight operators that are enhancing their capabilities with artificial intelligence are reaping its benefits by increasing efficiency with predictive intelligence. Artificial intelligence also enriches the relationship between the shipper and carrier with personalized service offerings.

Advanced sensor fusion with artificial intelligence supports the integration of smart infrastructure and operating assets and the freight operators in the development of connected freight ecosystem, aiding autonomous fleet management. The transformation of the logistics industry due to artificial intelligence is imperative in the near future; however, the readiness and openness of freight operators for an AI-based data-driven environment will determine how well this industry copes with challenges.

Key Topics Covered:

1. Executive Summary

2. Research Scope and Methodology

3. AI in Logistics Industry

4. AI in Freight Forwarding

5. AI in Freight Transportation

6. Stature of AI Adoption in Freight Transportation

7. Growth Opportunities and Companies to Action

8. The Last Word

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/nusb51

View source version on businesswire.com: https://www.businesswire.com/news/home/20200207005450/en/

Contacts

ResearchAndMarkets.comLaura Wood, Senior Press Managerpress@researchandmarkets.com For E.S.T Office Hours Call 1-917-300-0470For U.S./CAN Toll Free Call 1-800-526-8630For GMT Office Hours Call +353-1-416-8900

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2020-2025 Worldwide 5G, Artificial Intelligence, Data Analytics, and IoT Convergence: Embedded AI Software and Systems in Support of IoT Will Surpass…

The "5G, Artificial Intelligence, Data Analytics, and IoT Convergence: The 5G and AIoT Market for Solutions, Applications and Services 2020 - 2025" report has been added to ResearchAndMarkets.com's offering.

This research evaluates applications and services associated with the convergence of AI and IoT (AIoT) with data analytics and emerging 5G networks. The AIoT market constitutes solutions, applications, and services involving AI in IoT systems and IoT support of various AI facilitated use cases.

This research assesses the major players, strategies, solutions, and services. It also provides forecasts for 5G and AIoT solutions, applications and services from 2020 through 2025.

Report Findings:

The combination of Artificial Intelligence (AI) and the Internet of Things (IoT) has the potential to dramatically accelerate the benefits of digital transformation for consumer, enterprise, industrial, and government market segments. The author sees the Artificial Intelligence of Things (AIoT) as transformational for both technologies as AI adds value to IoT through machine learning and decision making and IoT adds value to AI through connectivity and data exchange.

With AIoT, AI is embedded into infrastructure components, such as programs, chipsets, and edge computing, all interconnected with IoT networks. APIs are then used to extend interoperability between components at the device level, software level, and platform level. These units will focus primarily on optimizing system and network operations as well as extracting value from data.

It is important to recognize that intelligence within IoT technology market is not inherent but rather must be carefully planned. AIoT market elements will be found embedded within software programs, chipsets, and platforms as well as human-facing devices such as appliances, which may rely upon a combination of local and cloud-based intelligence.

Just like the human nervous system, IoT networks will have both autonomic and cognitive functional components that provide intelligent control as well as nerve end-points that act like nerve endings for neural transport (detection and triggering of communications) and nerve channels that connect the overall system. The big difference is that the IoT technology market will benefit from engineering design in terms of AI and cognitive computing placement in both centralized and edge computing locations.

Taking the convergence of AI and IoT one step further, the publisher coined the term AIoT5G to refer to the convergence of AI, IoT, 5G. The convergence of these technologies will attract innovation that will create further advancements in various industry verticals and other technologies such as robotics and virtual reality.

As IoT networks proliferate throughout every major industry vertical, there will be an increasingly large amount of unstructured machine data. The growing amount of human-oriented and machine-generated data will drive substantial opportunities for AI support of unstructured data analytics solutions. Data generated from IoT supported systems will become extremely valuable, both for internal corporate needs as well as for many customer-facing functions such as product life cycle management.

There will be a positive feedback loop created and sustained by leveraging the interdependent capabilities of AIoT5G. AI will work in conjunction with IoT to substantially improve smart city supply chains. Metropolitan area supply chains represent complex systems of organizations, people, activities, information, and resources involved in moving a product or service from supplier to customer.

Research Benefits

Key Topics Covered

1. Executive Summary

2. Introduction

3. AIoT Technology and Market

4. AIoT Applications Analysis

5. Analysis of Important AIoT Companies

6. AIoT Market Analysis and Forecasts 2020-2025

7. Conclusions and Recommendations

Artificial Intelligence in Big Data Analytics and IoT: Market for Data Capture, Information and Decision Support Services 2020-2025

1. Executive Summary

2. Introduction

3. Overview

4. AI Technology in Big Data and IoT

5. AI Technology Application and Use Case

6. AI Technology Impact on Vertical Market

7. AI Predictive Analytics in Vertical Industry

8. Company Analysis

9. AI in Big Data and IoT Market Analysis and Forecasts 2020-2025

Story continues

10. Conclusions and Recommendations

11. Appendix

5G Applications and Services Market by Service Provider Type, Connection Type, Deployment Type, Use Cases, 5G Service Category, Computing as a Service, and Industry Verticals 2020-2025

1. Executive Summary

2. Introduction

3. LTE and 5G Technology and Capabilities Overview

4. LTE and 5G Technology and Business Dynamics

5. Company Analysis

6. LTE and 5G Application Market Analysis and Forecasts

7. Conclusions and Recommendations

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/rigm8o

View source version on businesswire.com: https://www.businesswire.com/news/home/20200207005390/en/

Contacts

ResearchAndMarkets.comLaura Wood, Senior Press Managerpress@researchandmarkets.com For E.S.T Office Hours Call 1-917-300-0470For U.S./CAN Toll Free Call 1-800-526-8630For GMT Office Hours Call +353-1-416-8900

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Artificial Intelligence Is Not Ready For The Intricacies Of Radiology – Forbes

Radiology is one of the most essential fields in clinical medicine. Experts in this field are specialists in deciphering and diagnosing disease based on various imaging modalities, ranging from ultrasound, magnetic resonance imaging (MRI), computerized tomography (CT), and x-rays. Studies have shown that the use of radiology in clinical practice has exponentially grown over the years: at the Mayo Clinic, between the years 1999 to 2010, use of CT scans increased by 68%, MRI use increased by 85%, and overall use of imaging modalities for diagnostic purposes increased by 75%, all numbers that have likely continued to rise, and indicate the sheer demand and growth of this robust field.

A unique proposal that has become prominent over the last few years to help alleviate this increased demand is the introduction of artificial intelligence (AI) technology into this field. Simply put, the premise of AI as an addition to the practice of radiology is straightforward, and has been envisioned in two main ways: 1) a system that can be programmed with pre-defined criteria and algorithms by expert radiologists, which can then be applied to new, straightforward clinical situations, or 2) deep learning methods, where the AI system relies on complex machine learning and uses neural-type networks to learn patterns via large volumes of data and previous encounters; this can then be used to interpret even the most complicated and abstract images.

Variety of body scans.

However, while much of the theoretical basis for AI in the practice of radiology is extremely exciting, the reality is that the field has not yet fully embraced it. The most significant issue is that the technology simply isnt ready, as many of the existing systems have not yet been matured to compute and manage larger data sets or work in more general practice and patient settings, and thus, are not able to perform as promised.Other issues exist on the ethical aspects of AI. Given the sheer volume of data required to both train and perfect these systems, as well as the immense data collection that these systems will engage in once fully mainstream, key stakeholders are raising fair concerns and the call for strict ethical standards to be put into place, simultaneous to the technological development of these systems.

Furthermore, the legal and regulatory implications of AI in radiology are numerous and complex. There are significant concerns in the data privacy space, as the hosting of large volumes of patient data for deep learning networks will require increased standards for data protection, cybersecurity, and privacy infrastructure. Additionally, given that AI systems will act as an additional diagnostic tool that must be accounted for in the patient encounter, legal frameworks will be required to fully flush out and navigate where liability falls in the case of misdiagnosis or medical negligence. Will this become an issue for the product manufacturer, or will there be a dynamic sharing of the responsibility by multiple parties? This will depend significantly on the amount of autonomy afforded to these systems.

However, radiologists must remain central to the diagnostic process. While AI systems may be able to detect routine medical problems based on pre-defined criteria, there is significant value provided by a trained radiologist that software simply cannot replace. This includes the clinical correlation of images with the physical state of the patient, qualitative assessments of past images with current images to determine progression of disease, and ultimately the most human aspect of medicine, working with other healthcare teams to make collaborative care decisions.

Using a human brain model to interpret MRI scans.

Indeed, there are significant potential benefits to the mass integration of certain AI systems into the practice of radiology, mainly as a means to augment a physicians workflow, especially given increasing radiology demands in clinical medicine. With some reports citing an expected rise in the use of AI in radiology by nearly 16.5% within the next decade, significant complexities remain unaddressed. However, these issues will ultimately need to be resolved in order to achieve a comprehensively capable and ethically mindful AI infrastructure that can become an integral part of clinical radiology.

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Artificial Intelligence Is Not Ready For The Intricacies Of Radiology - Forbes

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