Category Archives: Data Mining

Orange Data Mining – Data Mining

Ferenc Borondics, Ph.D.

"The scientific community is in need of tools that allow easy construction of workflows and visualizations and are capable of analyzing large amounts of data. Orange is a powerful platform to perform data analysis and visualization, see data flow and become more productive. It provides a clean, open source platform and the possibility to add further functionality for all fields of science."

"I teach Orange workshops monthly to a diverse audience, from undergrad students to expert researchers. Orange is very intuitive, and, by the end of the workshop, the participants are able to perform complex data visualization and basic machine learning analyses. Most of our attendees have been able to incorporate this tool in their research practice."

"My laboratory produces large amounts of data from RNA-seq, ChIP-seq and genome resequencing experiments. Orange allows me to analyze my data even though I dont know how to program. It also allows me to communicate with my collaborators, who are experts in data mining, and with my colleagues and trainees."

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Orange Data Mining - Data Mining

Russia proposes ban on use and mining of cryptocurrencies – CNBC

Russia's central bank on Thursday proposed banning the use and mining of cryptocurrencies on Russian territory, citing threats to financial stability, citizens' wellbeing and its monetary policy sovereignty.

The move is the latest in a global cryptocurrency crackdown as governments from Asia to the United States worry that privately operated and highly volatile digital currencies could undermine their control of financial and monetary systems.

Russia has argued for years against cryptocurrencies, saying they could be used in money laundering or to finance terrorism. It eventually gave them legal status in 2020 but banned their use as a means of payment.

In a report published on Thursday, the central bank said speculative demand primarily determined cryptocurrencies' rapid growth and that they carried characteristics of a financial pyramid, warning of potential bubbles in the market, threatening financial stability and citizens.

The bank proposed preventing financial institutions from carrying out any operations with cryptocurrencies and said mechanisms should be developed to block transactions aimed at buying or selling cryptocurrencies for fiat currencies.

The proposed ban includes crypto exchanges. Cryptocurrency exchange Binance told Reuters it was committed to working with regulators and hoped the report's release would spawn dialogue with the central bank on protecting the interests of Russian crypto users.

Restrictions on owning cryptocurrency are not envisaged, said Elizaveta Danilova, head of the central bank's financial stability department.

Active cryptocurrency users, Russians have an annual transaction volume of about $5 billion, the bank said.

The central bank said it would work with regulators in countries where crypto exchanges are registered to collect information about the operations of Russian clients. It pointed to steps taken in other countries, such as China, to curb cryptocurrency activity.

In September, China intensified its crackdown on cryptocurrencies with a blanket ban on all crypto transactions and mining, hitting bitcoin and other major coins and pressuring crypto and blockchain-related stocks.

"For now there are no plans to ban cryptocurrencies similar to the experience of China," Danilova said. "The approach we have proposed will suffice."

Joseph Edwards, head of financial strategy at crypto firm Solrise Group, played down the report's significance, saying no one outside Russia would be losing sleep over it.

"Moscow, like Beijing, is always rattling its sabre over 'crypto bans', but Russia has never been a pillar of any facet of the industry in the same way as China has been at times," he said.

Russia is the world's third-largest player in bitcoin mining, behind the United States and Kazakhstan, though the latter may see a miner exodus over fears of tightening regulation following unrest earlier this month. read more

The Bank of Russia said crypto mining created problems for energy consumption. Bitcoin and other cryptocurrencies are "mined" by powerful computers that compete against others hooked up to a global network to solve complex mathematical puzzles. The process guzzles electricity and is often powered by fossil fuels.

"The best solution is to introduce a ban on cryptocurrency mining in Russia," the bank said.

In August, Russia accounted for 11.2% of the global "hashrate" - crypto jargon for the amount of computing power being used by computers connected to the bitcoin network.

Moscow-based BitRiver, which operates data centers in Siberia hosting bitcoin miners, said it did not consider a complete crypto ban likely, expecting a balanced position to develop once different ministries have discussed the proposals.

The central bank, which is planning to issue its own digital rouble, said crypto assets becoming widespread would limit the sovereignty of monetary policy, with higher interest rates needed to contain inflation.

Excerpt from:

Russia proposes ban on use and mining of cryptocurrencies - CNBC

RDS and Trust Aware Process Mining: Keys to Trustworthy AI? – Techopedia

By 2024, companies are predicted to spend $500 billion annually on artificial intelligence (AI), according to the International Data Corporation (IDC).

This forecast has broad socio-economic implications because, for businesses, AI is transformativeaccording to a recent McKinsey study, organizations implementing AI-based applications are expected to increase cash flow 120% by 2030.

But implementing AI comes with unique challenges. For consumers, for example, AI can amplify and perpetuate pre-existing biasesand do so at scale. Cathy ONeil, a leading advocate for AI algorithmic fairness, highlighted three adverse impacts of AI on consumers:

In fact, a PEW survey found that 58% of Americans believe AI programs amplify some level of bias, revealing an undercurrent of skepticism about AIs trustworthiness. Concerns relating to AI fairness cut across facial recognition, criminal justice, hiring practices and loan approvalswhere AI algorithms have proven to produce adverse outcomes, disproportionately impacting marginalized groups.

But what can be deemed as fairas fairness is the foundation of trustworthy AI? For businesses, that is the million-dollar question.

AI's ever-increasing growth highlights the vital importance of balancing its utility with the fairness of its outcomes, thereby creating a culture of trustworthy AI.

Intuitively, fairness seems like a simple concept: Fairness is closely related to fair play, where everybody is treated in a similar way. However, fairness embodies several dimensions, such as trade-offs between algorithmic accuracy versus human values, demographic parity versus policy outcomes and fundamental, power-focused questions such as who gets to decide what is fair.

There are five challenges associated with contextualizing and applying fairness in AI systems:

In other words, what may be considered fair in one culture may be perceived as unfair in another.

For instance, in the legal context, fairness means due process and the rule of law by which disputes are resolved with a degree of certainty. Fairness, in this context, is not necessarily about decision outcomesbut about the process by which decision-makers reach those outcomes (and how closely that process adheres to accepted legal standards).

There are, however, other instances where application of corrective fairness is necessary. For example, to remedy discriminatory practices in lending, housing, education, and employment, fairness is less about treating everyone equally and more about affirmative action. Thus, recruiting a team to deploy an AI rollout can prove a challenge in terms of fairness and diversity. (Also read: 5 Crucial Skills That Are Needed For Successful AI Deployments.)

Equality is considered to be a fundamental human rightno one should be discriminated against on the basis of race, gender, nationality, disability or sexual orientation. While the law protects against disparate treatmentwhen individuals in a protected class are treated differently on purposeAI algorithms may still produce outcomes of disparate impactwhen variables, which are on-their-face bias-neutral, cause unintentional discrimination.

To illustrate how disparate impact occurs, consider Amazons same-day delivery service. It's based on an AI algorithm which uses attributessuch as distance to the nearest fulfillment center, local demand in designated ZIP code areas and frequency distribution of prime membersto determine profitable locations for free same-day delivery. Amazon's same-day delivery service was also found to be biased against people of coloureven though race was not a factor in the AI algorithm. How? The algorithm was less likely to deem ZIP codes predominantly occupied by people of colour as advantageous locations to offer the service. (Also read: Can AI Have Biases?)

Group fairness' ambition is to ensure AI algorithmic outcomes do not discriminate against members of protected groups based on demographics, gender or race. For example, in the context of credit applications, everyone ought to have equal probability of being assigned a good credit score, resulting in predictive parity, regardless of demographic variables.

On the other hand, AI algorithms focused on individual fairness strive to create outcomes which are consistent for individuals with similar attributes. Put differently, the model ought to treat similar cases in a similar way.

In this context, fairness encompasses policy and legal considerations and leads us to ask, What exactly is fair?

For example, in the context of hiring practices, what ought to be a fair percentage of women in management positions? In other words, what percentage should AI algorithms incorporate as thresholds to promote gender parity? (Also read: How Technology Is Helping Companies Achieve Their DEI Goals in 2022.)

Before we can decide what is fair, we need to decide who gets to decide that. And, as it stands, the definition of fairness is simply what those already in power need it to be to maintain that power.

As there are many interpretations of fairness, data scientists need to consider incorporating fairness constraints in the context of specific use cases and for desired outcomes. Responsible Data Science (RDS) is a discipline influential in shaping best practices for trustworthy AI and which facilitates AI fairness.

RDS delivers a robust framework for the ethical design of AI systems that addresses the following key areas:

While RDS provides the foundation for instituting ethical AI design, organizations are challenged to look into how such complex fairness considerations are implemented and, when necessary, remedied. Doing so will help them mitigate potential compliance and reputational risks, particularly as the momentum for AI regulation is accelerating.

Conformance obligations to AI regulatory frameworks are inherently fragmentedspanning across data governance, conformance testing, quality assurance of AI model behaviors, transparency, accountability, and confidentiality process activities. These processes involve multiple steps across disparate systems, hand-offs, re-works, and human-in-the-loop oversight between multiple stakeholders: IT, legal, compliance, security and customer service teams.

Process mining is a rapidly growing field which provides a data-driven approach for discovering how existing AI compliance processes work across diverse process participants and disparate systems of record. It is a data science discipline that supports in-depth analysis of how current processes work and identifies process variances, bottlenecks and surface areas for process optimization.

R&D teams, who are responsible for the development, integration, deployment, and support of AI systems, including data governance and implementation of appropriate algorithmic fairness constraints.

Legal and compliance teams, who are responsible for instituting best practices and processes to ensure adherence to AI accountability and transparency provisions; and

Customer-facing functions, who provide clarity for customers and consumers regarding the expected AI system inputs and outputs.

By visualizing compliance process execution tasks relating to AI training datasuch as gathering, labeling, applying fairness constraints and data governance processes.

By discovering record-keeping and documentation process execution steps associated with data governance processes and identifying potential root causes for improper AI system execution.

By analyzing AI transparency processes, ensuring they accurately interpret AI system outputs and provide clear information for users to trust the results.

By examining human-in-the-loop interactions and actions taken in the event of actual anomalies in AI systems' performance.

By monitoring, in real time, to identify processes deviating from requirements and trigger alerts in the event of non-compliant process tasks or condition changes.

Trust aware process mining can be an important tool to support the development of rigorous AI compliance best practices that mitigate against unfair AI outcomes.

That's importantbecause AI adoption will largely depend on developing a culture of trustworthy AI. A Capgemini Research Institute study reinforces the importance of establishing consumer confidence in AI: Nearly 50% of survey respondents have experienced what they perceive as unfair outcomes relating to the use of AI systems, 73% expect improved transparency and 76% believe in the importance of AI regulation.

At the same time, effective AI governance results in increased brand loyalty and in repeat business. Instituting trustworthy AI best practices and governance is good business. It engenders confidence and sustainable competitive advantages.

Author and trust expert Rachel Botsman said it best when she described trust as, the remarkable force that pulls you over that gap between certainty and uncertainty; the bridge between the known and the unknown.

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RDS and Trust Aware Process Mining: Keys to Trustworthy AI? - Techopedia

DeepTarget Expands Leadership Team with the Addition of Mark Schwartz as Director of Sales – Business Wire

HUNTSVILLE, Ala.--(BUSINESS WIRE)--DeepTarget Inc., a solution provider that utilizes data mining and business intelligence in order to deliver targeted communications across digital channels for banks and credit unions, today announced the addition of Mark Schwartz as Director of Sales.

Poised for accelerated growth, DeepTarget enters 2022 coming out of an extremely successful year of new customers, technology innovations including an awarded patent, and new partnerships and alliances. Schwartz brings strong leadership credentials for accelerating enterprise solution sales, assembling sales talent, and building scalable sales processes.

I am delighted to lead DeepTarget through its next phase of accelerated growth building on the strong success record of more than 200 banks and credit unions, said Mark Schwartz. With the accomplishment of so many successful and happy customers as a foundation, I am doubly excited about guiding new bank and credit union prospects to digital success using this patented and results-driven Digital Experience Platform. 2022 is going to be a remarkable year.

Many banks and credit unions are facing the stress of fierce competition and digital disruption. They find themselves spending marketing budgets on communications that dont reach or resonate with the modern consumers high expectations. DeepTarget simplifies digital marketing with a sophisticated and comprehensive digital experience platform that leverages AI and BI to effortlessly reach each individual consumers through automated, targeted campaigns of highly relevant financial products and services. DeepTargets FI customers often reduce marketing spend while quadrupling ROI and exceed industry standards for digital engagement.

Mark is a valuable addition to our sales team, said Preetha Pulusani, CEO of DeepTarget. He brings tremendous industry knowledge and experience to our company and he will be an instrumental asset to our continued growth. There is undoubtedly an increase in demand for digital consumer engagements but many financial institutions are unaware about how to get started on this digital journey. Marks expertise will help many more banks and credit unions appreciate the availability and benefits of innovative, automated solutions enabling them to meet the demands of their consumers in an efficient manner, further increasing revenue and consumer satisfaction for these organizations.

Prior to joining DeepTarget, Schwartz led business development and sales initiatives for financial services organizations, where he proved to be a trusted, results-driven, entrepreneurial leader. He has established a strong ability to train, mentor, develop and motivate teams to achieve determined goals. He most recently served as Director of Business Development for Ncontracts, where he created and implemented a Business Development Representative program, resulting in the team performing at 136% of quota. He has held key positions at LSQ Funding Group, Coupon Mint and Bancsource.

About DeepTarget

DeepTarget helps financial institutions integrate data sources for the purpose of driving meaningful digital engagements that yield more loans and deposits. Their solutions help financial institutions connect with their customers with messages that resonate. DeepTargets intelligent digital marketing and sales solutions are used by hundreds of financial institutions to provide a seamless communications experience wherever, whenever and however their customers bank. For additional information visit http://www.deeptarget.com. To boost your digital presence and cross-sell results, connect with Mark Schwartz directly at sales@deeptarget.com.

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DeepTarget Expands Leadership Team with the Addition of Mark Schwartz as Director of Sales - Business Wire

Russia proposes ban on use and mining of cryptocurrencies – Reuters

MOSCOW, Jan 20 (Reuters) - Russia's central bank on Thursday proposed banning the use and mining of cryptocurrencies on Russian territory, citing threats to financial stability, citizens' wellbeing and its monetary policy sovereignty.

The move is the latest in a global cryptocurrency crackdown as governments from Asia to the United States worry that privately operated and highly volatile digital currencies could undermine their control of financial and monetary systems.

Russia has argued for years against cryptocurrencies, saying they could be used in money laundering or to finance terrorism. It eventually gave them legal status in 2020 but banned their use as a means of payment.

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In a report published on Thursday, the central bank said speculative demand primarily determined cryptocurrencies' rapid growth and that they carried characteristics of a financial pyramid, warning of potential bubbles in the market, threatening financial stability and citizens.

The bank proposed preventing financial institutions from carrying out any operations with cryptocurrencies and said mechanisms should be developed to block transactions aimed at buying or selling cryptocurrencies for fiat currencies.

Dont Miss: Robinhood to start rolling out crypto wallets

The proposed ban includes crypto exchanges. Cryptocurrency exchange Binance told Reuters it was committed to working with regulators and hoped the report's release would spawn dialogue with the central bank on protecting the interests of Russian crypto users.

Restrictions on owning cryptocurrency are not envisaged, said Elizaveta Danilova, head of the central bank's financial stability department.

Active cryptocurrency users, Russians have an annual transaction volume of about $5 billion, the bank said.

Dont Miss: New York Mayor Adams to receive first paycheck in cryptocurrency

SHADOWING CHINA?

The central bank said it would work with regulators in countries where crypto exchanges are registered to collect information about the operations of Russian clients. It pointed to steps taken in other countries, such as China, to curb cryptocurrency activity.

In September, China intensified its crackdown on cryptocurrencies with a blanket ban on all crypto transactions and mining, hitting bitcoin and other major coins and pressuring crypto and blockchain-related stocks.

"For now there are no plans to ban cryptocurrencies similar to the experience of China," Danilova said. "The approach we have proposed will suffice."

Joseph Edwards, head of financial strategy at crypto firm Solrise Group, played down the report's significance, saying no one outside Russia would be losing sleep over it.

"Moscow, like Beijing, is always rattling its sabre over 'crypto bans', but Russia has never been a pillar of any facet of the industry in the same way as China has been at times," he said.

CRYPTO MINING

Russia is the world's third-largest player in bitcoin mining, behind the United States and Kazakhstan, though the latter may see a miner exodus over fears of tightening regulation following unrest earlier this month. read more

The Bank of Russia said crypto mining created problems for energy consumption. Bitcoin and other cryptocurrencies are "mined" by powerful computers that compete against others hooked up to a global network to solve complex mathematical puzzles. The process guzzles electricity and is often powered by fossil fuels.

"The best solution is to introduce a ban on cryptocurrency mining in Russia," the bank said.

In August, Russia accounted for 11.2% of the global "hashrate" - crypto jargon for the amount of computing power being used by computers connected to the bitcoin network.

Moscow-based BitRiver, which operates data centres in Siberia hosting bitcoin miners, said it did not consider a complete crypto ban likely, expecting a balanced position to develop once different ministries have discussed the proposals.

The central bank, which is planning to issue its own digital rouble, said crypto assets becoming widespread would limit the sovereignty of monetary policy, with higher interest rates needed to contain inflation.

Register

Reporting by Elena Fabrichnaya and Alexander Marrow; additional reporting by Tom Wilson in London; Editing by Emelia Sithole-Matarise

Our Standards: The Thomson Reuters Trust Principles.

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Russia proposes ban on use and mining of cryptocurrencies - Reuters

Digging Into The Data Of Bitcoin Mining Decentralization | Bitcoinist.com – Bitcoinist

The Bitcoin mining landscape has undergone shifts over the past year due to Chinas crackdowns. Heres some data that shows how decentralized the BTC network currently is.

One way to study about decentralization in the BTC mining network is to go through hashrate dominance data of the major mining pools and companies.

The hashrate is an indicator that measures the total amount of computing power currently connected to the Bitcoin network.

Higher the value of this metric, more is the mining power on the chain, and hence better is the overall performance.

On the Bitcoin network, there are several big publicly-traded mining companies present. The percentage of the hashrate each of them make up for may shed some light on the degree of the decentralization on the BTC blockchain.

Here is some data from Arcane Research that shows the hashrate dominance of the major mining companies:

As you can see in the above graph, Marathon, the largest of the Bitcoin mining companies, makes up for just a little less than 2% of the hashrate.

The five biggest mining companies in the market combined control around 7% of the total hashrate on the BTC blockchain.

Related Reading |Bitcoin Spot Volume Nose Dives To Lowest Since Summer Selloff

This isnt that big a percentage so this picture of the network may suggest that the network is relatively decentralized.

However, many major mining companies actually combine their hashrate and mine under the various mining pools.

The below chart shows how the hashrate is distributed among the major Bitcoin mining pools.

Now this data, on the other hand, makes the Bitcoin network look more centralized. The largest mining pool, AntPool, accounts for 16% of the hashrate alone.

The five largest pools make up for 70% of the total hashrate on the BTC blockchain. This is a pretty significant number.

Related Reading |Update: Intels Bitcoin-Mining Chip Bonanza Bags Mining Startup As First Client

The report concludes that the bottleneck for Bitcoin decentralization lies not among mining companies, but mining pools. As such, decentralized mining pools may be the way to go for decentralization in the future.

At the time of writing, Bitcoins price floats around $42k, down 4% in the last seven days. Below is a chart that shows the trend in the value of BTC over the last five days.

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Digging Into The Data Of Bitcoin Mining Decentralization | Bitcoinist.com - Bitcoinist

Senior/Research Data Analyst, Manager job with SINGAPORE UNIVERSITY OF SOCIAL SCIENCES | 278258 – Times Higher Education (THE)

Short Description

An exciting opportunity has arisen for a Senior/Research Data Analyst to join the Teaching & Learning Centre (TLC).

TLC promotes excellence in teaching and learning through the design and implementation of innovative pedagogies; facilitation of Faculty development and training; scholarship of teaching & learning; and provides academic support for students whilst developing lifelong learning attributes in our graduates.

Job Description

As Senior/Research Data Analystyou will be proactive and crucial to the successful development and implementation of adaptive learning systems and web applications to augment the quality of teaching and learning within the university. You will be responsible for developing and implementing data analytics solutions, and research tasks related to educational data mining. These include data extraction, wrangling, examination, interpretation, and evaluating relevant models (e.g., machine learning) for the system. With guidance and assistance from colleagues, you will also contribute to reports and publications to communicate success/progress of development works.

Job Requirements

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Senior/Research Data Analyst, Manager job with SINGAPORE UNIVERSITY OF SOCIAL SCIENCES | 278258 - Times Higher Education (THE)

Special Scientist, Research Associate, Research Fellowship Position job with UNIVERSITY OF CYPRUS | 278736 – Times Higher Education (THE)

UNIVERSITY OF CYPRUSMarie-Curie Initial Training Network RAIS: Real-Time Analytics for the Internet of Sportshttp://rais-itn.euANNOUNCEMENT OF Research Fellowship in Edge computing, Complex systems and Data analytics

Title:Special Scientist (Research Associate) Research fellowship positionNo. of Position(s):1Category:ESR1 (13 months full time)Location:University of Cyprus, Nicosia

The University of Cyprus (UCY) announces the availability of one Special Scientist (Research Associate) (1) Research fellowship position, under the Marie Sklodowska-Curie Initial Training Network (ITN) RAIS: Real Time Analytics for the Internet of Sports. The position is in the area of edge computing, complex systems and data analytics.

Position Code:

RAIS-UCY-ESR1 Adaptive monitoring Framework for Wearable devices: hosted by the Laboratory of Internet Computing, Dept. of Computer Science

The period of employment is as follows:

ESR1: starting date 1st June 2022 (13 months - within the approved limits of its budget).

The position is funded by the European Commission under the Marie Sklodowska--Curie Initial Training Network (ITN) program RAIS, which focuses on the design of decentralized, scalable and secure collective awareness platforms for real-time data analytics and machine learning, which preserve end-user privacy and information ownership. The RAIS consortium aspires to establish a fertile multidisciplinary research and innovation community with a strong entrepreneurial culture that will advance wearable sport-sensing and quantified-self devices and accompanying middleware. The consortium comprises scientists and research groups from the Royal Institute of Technology, Sweden; the Univ. of Cyprus; the Univ. of Insubria, Italy; the Foundation of Research and Technology-Hellas (FORTH), Greece; the Aristotle University of Thessaloniki, Greece; RaceFox, Sweden and a number of associated research and industrial partners (Cambridge University, UK; MIT Sloan School of Management, USA; Open Data Institute, UK; EIT Digital, Belgium; Recorded Future, Sweden; Kinetic Analysis, The Netherlands; Berklee College of Music, USA).

The main objective of the RAIS Initial Training Network is to provide world class training for the next generation of researchers, data scientists, and Web engineers, emphasizing on a strong combination of advanced understanding in both theoretical and experimental approaches, methodologies and tools that are required to develop Decentralized Platforms for Real-Time Data Analytics.

Requirements, Eligibility Criteria and Funding

We seek candidates with experience and/or research interests in the following areas and topics:

Preference will be given to highly motivated candidates with strong programming and analytical skills, excellent knowledge of English (for non-native speakers required to take TOEFL or equivalent test), and a proven commitment to their studies. Eligible applicants are required to have completed a higher education degree (M.Sc.) of computer science, statistics or other related areas from an internationally recognized university. The applicant must have less than 4 years of full-time research experience after obtaining their degree. At the time of recruitment by the UCY, the early-stage researcher must not have resided or carried out their main activity (work, studies, etc.) in Cyprus for more than 12 months in the 3 years immediately prior to the reference date.

Students in their final year of Master education may also apply and if qualified, receive a conditional offer. If the applicant has not completed his/her studies, he/she should include a written statement from the degree administration office (or equivalent department), confirming that he/she is enrolled on the final year of his/her education and stating the expected completion date. If the applicant receives a conditional offer, the candidate should present the degree certificate before enrolment.

Marie Curie fellows enjoy good salaries and working conditions, career development opportunities and work-life balance. We especially encourage women researchers to apply for the aforementioned positions.. For Marie Curie fellows with family (Family means persons linked to the researcher by marriage (or a relationship with equivalent status to a marriage recognised by the legislation of the country where this relationship was formalized) or dependent children who are actually being maintained by the Marie Curie fellow), a monthly family allowance will be given. Marie Curie fellows will also get coverage of expenses related to the participation in research and training activities (contribution to research-related costs, meetings, conference attendance, training actions, etc.).

Career Stage : Early stage researcher or 0-4 years of experience (Post graduate) According to the H2020 (Marie S. Curie Actions) Regulations. Eligibility rules for the Marie S. Curie fellows can be found at the H2020 MSCA 2018-2020 Work programme: http://ec.europa.eu/research/participants/data/ref/h2020/wp/2018-2020/main/h2020-wp1820-msca_en.pdf

Benefits:

Applications:

Interested parties are requested to submit the following files:

Required

Applications should be submitted electronically to Mrs. Demetra Katziani at dkatzi01@cs.ucy.ac.cy with subject line RAIS/vacancies2022/ NAME SURNAME.

While expressions of interest are accepted on a continuous basis, applications received by March 31, 2022 will be considered in the first evaluation cycle. The decisions are expected to be reached in April 2022.

The offer of the position is subject to the final approval of the European Commission and any other regulatory approval.

About the University of Cyprus:

The University of Cyprus (UCY) is the largest University and the main research organization in Cyprus. The University was established in 1989. The University is featured in the Shanghai list of world-class Universities. It is ranked in the top 351-400 Universities worldwide and is in the 52nd position amongst Universities that are less than 50 years old, according to the Times Higher Education World Rankings. The University is located in Nicosia, the capital city of the Republic of Cyprus, a European Union member state, a major financial, business, tourist, and educational hub in the Eastern Mediterranean, and one of the safest countries in the world. Nicosia combines a modern European culture with ancient enchantment and world-class tourist and archaeological attractions. RAIS ITN at UCY is coordinated by a multidisciplinary group of faculty members from the Laboratory for Internet Computing, Department of Computer Science (School of Pure and Applied Sciences) and the Social Analytics & Networks Lab, Department of Business Administration (School of Economics and Business):

For more information please contact Associate Professor George Pallis (gpallis@cs.ucy.ac.cy).

At least the best three candidates that satisfy the required qualifications, will be interviewed by a 3-member Committee.

Candidates shall be informed of the result of their application by the relevant entity.

The University of Cyprus shall collect and process your personal data according to the provisions of the General Regulation on Personal Data 2016/679 (EU).

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Special Scientist, Research Associate, Research Fellowship Position job with UNIVERSITY OF CYPRUS | 278736 - Times Higher Education (THE)

Bitcoin network difficulty jumps more than 9% to new all-time high – The Block Crypto

Quick Take

Bitcoin's network mining difficulty has risen by more than 9%, marking the biggest difficulty adjustment since last summer.

According to BTC.com, which tracks mining difficulty data, the difficulty rose by 9.32%. Today's jump was the second thus far in 2022, following January 8's 0.41% adjustment.

The Bitcoin network's mining difficulty level adjusts every 2,016 blocks, on a roughly two-week schedule. Difficulty changes are designed to maintain an average block time of 10 minutes as the hash rate rises and falls, though actual per-block times often vary.

With the exception of a 1.49% decrease on November 28, the difficulty has seen steady growth since last summer's mining crackdown in China, which plunged the difficulty by its largest share on record as miners in that country shut down their equipment and decamped to countries like the United States and Kazakhstan.

As noted on The Block's Data Dashboard, the mining hash rate has fully recovered since late August, with the US emerging as the world's current mining powerhouse.

According to an analysis from The Block Research, the total bitcoin hash rate has increased by about 18 EH/s since December 11. Notably, Foundry USA -- owned by the Digital Currency Group subsidiary -- has increased by approximately 5 EH/s in that time.

This represents the fastest rate of growth among the world's top mining pools. The second-fastest growth during that period came from F2Pool, which expanded its collective mining power by 3.3 EH/s.

2021 The Block Crypto, Inc. All Rights Reserved. This article is provided for informational purposes only. It is not offered or intended to be used as legal, tax, investment, financial, or other advice.

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Bitcoin network difficulty jumps more than 9% to new all-time high - The Block Crypto

Vibrent Health Powers NIH Precision Nutrition Research Project to Accelerate Discoveries in Food and Dietary Patterns – PRNewswire

FAIRFAX, Va., Jan. 20, 2022 /PRNewswire/ -- Vibrent Health, a health technology startup powering the future of precision health research, today announced that the company's Digital Health Solutions Platform (DHS Platform) will support the National Institutes of Health (NIH) Common Fund's Nutrition for Precision Health, powered by the All of Us Research Program (NPH).The NPH willexplore the dietary health of All of Us participants to inform the development of evidence-based, personalized nutrition recommendations. The NIH is awarding $170 million over five years, pending the availability of funds, to clinics and centers across the country to conduct the study.

The NPH program will build on recent advances in biomedical science including artificial intelligence (AI), genetics and microbiome research and will be the first ancillary study to leverage thelarge and diverse All of Us cohort and its existing data and infrastructure. The NPH program will add valuable data about the dietary habits of participants to the All of Us Research Program and use modern data mining techniques to develop and validate algorithms for clinical application.

"Our technology and expertise enable the NPH and the All of Us Research Program's nationwide network of health research partners to recruit, electronically consent, engage and support the diverse participants of the precision nutrition cohort," said Vibrent Health CEO Praduman "PJ" Jain. "We came together around a common mission to help people to utilize their personal data to improve health."

Vibrent Health's technology provides the data collection and engagement platform that will enable the data to be used to:

Using Vibrent's DHS Platform, researchers will collect broad datasets on multiple potential predictive factors and combine it with existing data in the All of Us database to develop a more complete picture of how individuals respond to different foods or dietary routines.

"With the introduction of the Nutrition for Precision Health initiative, the All of Us Research Program is reaching an exciting new stage for a large cohort program. As the Participant Technology System Center (PTSC) for NIH All of us, Vibrent Health is in the critical position of delivering advanced technologies enabling researchers to remotely engage with diverse cohorts at a national scale. Together we'll collect unique valuable datasets and support participants in ways that would not be possible without our advanced digital tools," said Vibrent Health Vice President Mark Begale.

"Data-driven and tailored health is the future," says Jain. "Precision health research is key to helping individuals achieve optimal health through solutions designed to take into account data about many aspects of health, including fitness, mental well-being, sleep, diet and metabolic health based on their biology and individual needs."

All of Us andNutrition for Precision Health, powered by the All of Us Research Program,are service marks of the U.S. Department of Health and Human Services. The Vibrent Health award is supported by NIH Common Fund supplement 1 OT2 OD030043-01S8.

About Vibrent HealthVibrent Health develops digital health technology and research tools for health organizations, researchers and research participants.Powering the next generation of precision medicine, Vibrent's scalable technologyplatform for individual and population health provides actionable insights to help accelerate medical discoveries. Vibrent Health is proud to serve, since 2017, as the Participant Technology Systems Center for the National Institutes of Health'sAll of UsResearch Program, which aims to collect health data from one million or more people to support a wide variety of research studies. To learn more, visitvibrenthealth.com.

Contact:Pearson Brown(310) 994-7057[emailprotected]com

SOURCE Vibrent Health

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Vibrent Health Powers NIH Precision Nutrition Research Project to Accelerate Discoveries in Food and Dietary Patterns - PRNewswire