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LIVE!sTREAMs!* FIS Nordic Combined Continental Cup Ruka 2022 Live Free Tv BROADCAST CLICK TO WATCH FREE LIVE It can be hard to know where to watch rugby on TV — especially in the US. Read on to learn how to watch wherever you live!Rugby is a sport that is already immensely popular in certain parts of the world and is starting to gain traction in countries such as the United States and Canada. As a result, interest in streaming rugby matches is significant/increasing. Streaming your favorite sport is not always easy, especially when you’re trying to watch from another country. Interest in rugby, a contact sport similar in many ways to football, has been steadily growing in the United States for some years now. While it’s easier than ever to find a local team to play with, it’s not so easy to watch a professional rugby game in the United States. If you’re a dedicated rugby fan looking to watch professional games, there is some good news for you. While there are quite a few ways to stream live rugby games in the US, you’ll have to stay up late to catch the game (or in some cases wake up early). We’re taking a look at some of the most efficient ways to stream rugby, no matter what country the game is taking place in. Here’s a quick preview of some upcoming games that you can stream live. All times are in Eastern and Pacific Time. 2021-09-09: Version 6.0.0 was created. Now includes data for the North Sea Link (NSL) interconnector from Great Britain to Norway (https://www.northsealink.com). The previous version (5.0.4) should not be used - as there was an error with interconnector data having a static value over the summer 2021.dd Version 144 of the dataset. MAJOR CHANGE NOTE: The dataset files: full_dataset.tsv.gz and full_dataset_clean.tsv.gz have been split in 1 GB parts using the Linux utility called Split. So make sure to join the parts before unzipping. We had to make this change as we had huge issues uploading files larger than 2GB's (hence the delay in the dataset releases). The peer-reviewed publication for this dataset has now been published in Epidemiologia an MDPI journal, and can be accessed here: https://doi.org/10.3390/epidemiologia2030024. Please cite this when using the dataset.gd This dataset contains impact metrics and indicators for a set of publications that are related to the COVID-19 infectious disease and the coronavirus that causes it. It is based on:gs Τhe CORD-19 dataset released by the team of Semantic Scholar1 and Τhe curated data provided by the LitCovid hub2.sa These data have been cleaned and integrated with data from COVID-19-TweetIDs and from other sources (e.g., PMC). The result was dataset of 621,235 unique articles along with relevant metadata (e.g., the underlying citation network). We utilized this dataset to produce, for each article, the values of the following impact measures:gww Influence: Citation-based measure reflecting the total impact of an article. This is based on the PageRank3 network analysis method. In the context of citation networks, it estimates the importance of each article based on its centrality in the whole network. This measure was calculated using the PaperRanking (https://github.com/diwis/PaperRanking) library4.sff Influence_alt: Citation-based measure reflecting the total impact of an article. This is the Citation Count of each article, calculated based on the citation network between the articles contained in the BIP4COVID19 dataset. Popularity: Citation-based measure reflecting the current impact of an article. This is based on the AttRank5 citation network analysis method. Methods like PageRank are biased against recently published articles (new articles need time to receive their first citations). AttRank alleviates this problem incorporating an attention-based mechanism, akin to a time-restricted version of preferential attachment, to explicitly capture a researcher's preference to read papers which received a lot of attention recently. This is why it is more suitable to capture the current "hype" of an article.ggwsw Due to the relevance of the COVID-19 global pandemic, we are releasing our dataset of tweets acquired from the Twitter Stream related to COVID-19 chatter. Since our first release we have received additional data from our new collaborators, allowing this resource to grow to its current size. Dedicated data gathering started from March 11th yielding over 4 million tweets a day. We have added additional data provided by our new collaborators from January 27th to March 27th, to provide extra longitudinal coverage. Version 10 added ~1.5 million tweets in the Russian language collected between January 1st and May 8th, gracefully provided to us by: Katya Artemova (NRU HSE) and Elena Tutubalina (KFU). From version 12 we have included daily hashtags, mentions and emoijis and their frequencies the respective zip files. From version 14 we have included the tweet identifiers and their respective language for the clean version of the dataset. Since version 20 we have included language and place location for all tweets.dfgg 2021-05-05: Version 5.0.0 was created. Datetimes now in ISO 8601 format (with capital letter 'T' between the date and time) rather than previously with a space (to RFC 3339 format) and with an offset to identify both UTC and localtime. MW values now all saved as integers rather than floats. Elexon data as always from www.elexonportal.co.uk/fuelhh, National Grid data from https://data.nationalgrideso.com/demand/historic-demand-data Raw data now added again for comparison of pre and post cleaning - to allow for training of additional cleaning methods. If using Microsoft Excel, the T between the date and time can be removed using the =SUBSTITUTE() command - and substitute "T" for a space " "gww 2021-03-02: Version 4.0.0 was created. Due to a new interconnecter (IFA2 - https://en.wikipedia.org/wiki/IFA-2) being commissioned in Q1 2021, there is an additional column with data from National Grid - this is called 'POWER_NGEM_IFA2_FLOW_MW' in the espeni dataset. In addition, National Grid has dropped the column name 'FRENCH_FLOW' that used to provide the value for the column 'POWER_NGEM_FRENCH_FLOW_MW' in previous espeni versions. However, this has been changed to 'IFA_FLOW' in National Grid's original data, which is now called 'POWER_NGEM_IFA_FLOW_MW' in the espeni dataset. Lastly, the IO14 columns have all been dropped by National Grid - and potentially unlikely to appear again in future.fgwf 2020-12-02: Version 3.0.0 was created. There was a problem with earlier versions local time format - where the +01:00 value was not carried through into the data properly. Now addressed - therefore - local time now has the format e.g. 2020-03-31 20:00:00+01:00 when in British Summer Time.stuu 2020-10-03: Version 2.0.0 was created as it looks like National Grid has had a significant change to the methodology underpinning the embedded wind calculations. The wind profile seems similar to previous values, but with an increasing value in comparison to the value published in earlier the greater the embedded value is. The 'new' values are from https://data.nationalgrideso.com/demand/daily-demand-update from 2013.fgew Previously: raw and cleaned datasets for Great Britain's publicly available electrical data from Elexon (www.elexonportal.co.uk) and National Grid (https://demandforecast.nationalgrid.com/efs_demand_forecast/faces/DataExplorer). Updated versions with more recent data will be uploaded with a differing version number and doidf All data is released in accordance with Elexon's disclaimer and reservation of rights.derrr This disclaimer is also felt to cover the data from National Grid, and the parsed data from the Energy Informatics Group at the University of Birmingham.

The European Medicines Agency (EMA) started operating under its new legal mandate on 1 April 2022. The mandate brings new responsibilities to the Agency in three different areas: • Reinforcement of the role and activities of the EMA pandemic Task Force(which is now known as the Emergency Task Force (ETF)). • A stronger role of EMA in the monitoring of shortages of critical medicines, medical devices and in-vitro diagnostics, both in anticipation of and during a crisis. • A more coordinated mechanism of European Union (EU) experts advice on medical devices classified as high-risk (class IIa and III or class D (1)) and in-vitro diagnostic medical devices. Here we consider the impact of the COVID-19 pandemic on the operations of EMA and the European medicines regulatory network, and how EMA’s new mandate will strengthen the Agency’s and the Network’s ability to face crises. EMA’s extended mandate brings clear benefits in terms of response to public health emergencies at EU level, which ranges from improvements in crisis management to avoiding medicine shortages and improving access to diagnostics and medical devices that are safe and conform to their expected function.

DIS2022 conference presentation

PRUF Working Paper No. 1

This paper is on a brief interpretation of class P and NP as bounds over the number of jumps between strings in an infinite Hamming cube consisting all the instances of a language on a Turing machine’s tape. It is shown that P and NP are more comparable when defined in Hamming space respecting its cubic structure; while, this results P = NP.