This is a release of management information about patients previously identified as clinically extremely vulnerable (CEV) and at high risk of death from coronavirus (COVID-19) who were on the Shielded Patient List (SPL). The purpose behind the public release of SPL data has been to make available anonymous and summarised regional and local data to allow for its use in public health analysis. As the UK government has ended the shielding programme in England, the SPL dashboard will not be updated after 07 October 2021. The final dashboard and release of management information is based on version 75 of the SPL clinical methodology, with the data extracted on 30 September 2021.

Analysis of people previously considered to be clinically extremely vulnerable (CEV) in England during the coronavirus (COVID-19) pandemic, including their behaviours and mental and physical well-being.

• The spreadsheet shows MDS recoveries made after post payment verification (PPV) covering April 2020 – March 2021 – this covers the whole time period when the service was available for clinically extremely vulnerable (CEV) patients. • Each pharmacy branch ("contractor") only appears in the list once. However, the recovery value may relate to one or more sample periods covering April 2020 to March 2021. Some contractors receive combined recoveries for more than one sample period. Other contractors may have had a recovery for one sample period, but their case is on-going for another, which could result in further deductions being made.Column B shows the total monetary value of MDS claims paid to the contractor between April 2020 - March 2021. • Column C shows the monetary value recovered from each contractor as of the May 2023 schedule of payments as this was the latest available data as of 31 July 2023 – some contractors are on payment plans so this will only show the instalments deducted to date. • Column E shows a ‘Yes’ for those contractors who have appealed a recovery decision. Where the appeal outcome is ‘Awaiting Outcome’, the monetary value of the appealed recovery is not included in column E. A contractor may have agreed to a recovery for one period, but appealed a recovery decision for another. Where the appeal outcome begins ‘Appeal Dismissed’, the monetary value of the appealed recovery is included in column E and the date the appeal was dismissed is also contained in this column. Additional expenses incurred due to the Covid-19 pandemic

The Current Population Survey Civic Engagement and Volunteering (CEV) Supplement is the most robust longitudinal survey about volunteerism and other forms of civic engagement in the United States. Produced by AmeriCorps in partnership with the U.S. Census Bureau, the CEV takes the pulse of our nation’s civic health every two years. The CEV can support evidence-based decision making and efforts to understand how people make a difference in communities across the country.

The findings on this page are based on data collected in September of 2017, 2019, 2021, and 2023. All figures are weighted to account for the random selection of eligible respondents and missing data due to nonresponse. They reflect national rates of 17 measures of civic engagement. Please see column descriptions for details.

A spreadsheet with all of these figures is provided as an attachment along with additional resources about the CEV data. Click on "Show More" to view and download.

To explore CEV findings in an interactive dashboard, please see https://data.americorps.gov/stories/s/AmeriCorps-Civic-Engagement-and-Volunteering-CEV-D/62w6-z7xa

For the full CEV datasets, please see https://data.americorps.gov/browse?q=cev&sortBy=last_modified&utf8=%E2%9C%93

Headline indicators from the Opinions and Lifestyle Survey covering the period 1 December 2021 to 3 January 2022 by disability and clinically extremely vulnerable status.

Cat & Dog Lub Cev Segmentation Cov Ntaub Ntawv Ntxiv yog tsim rau kev lag luam kev lom zem pom, suav nrog ntau yam duab sau hauv internet nrog cov kev daws teeb meem siab tshaj 440 x 440 pixels. Cov ntaub ntawv no tsom mus rau contour segmentation, tshwj xeeb tshaj tawm cov ntsiab lus ntawm miv thiab dev ntawm ntau hom tsiaj, muab cov ntaub ntawv ntxaws ntxaws rau cov ntawv thov uas xav tau cov neeg sawv cev zoo.

The Current Population Survey Civic Engagement and Volunteering (CEV) Supplement is the most robust longitudinal survey about volunteerism and other forms of civic engagement in the United States. Produced by AmeriCorps in partnership with the U.S. Census Bureau, the CEV takes the pulse of our nation’s civic health every two years. The data on this page was collected in September 2017. The CEV can generate reliable estimates at the national level, within states and the District of Columbia, and in the largest twelve Metropolitan Statistical Areas to support evidence-based decision making and efforts to understand how people make a difference in communities across the country. This page was updated on January 16, 2025 to ensure consistency across all waves of CEV data. Click on "Export" to download and review an excerpt from the 2017 CEV Analytic Codebook that shows the variables available in the analytic CEV datasets produced by AmeriCorps. Click on "Show More" to download and review the following 2017 CEV data and resources provided as attachments: 1) CEV FAQs – answers to frequently asked technical questions about the CEV 2) Constructs and measures in the CEV 3) 2017 CEV Analytic Data and Setup Files – analytic dataset in Stata (.dta), R (.rdata), SPSS (.sav), and Excel (.csv) formats, codebook for analytic dataset, and Stata code (.do) to convert raw dataset to analytic formatting produced by AmeriCorps. 4) 2017 CEV Technical Documentation – codebook for raw dataset and full supplement documentation produced by U.S. Census Bureau 5) 2017 CEV Raw Data and Read In Files – raw dataset in Stata (.dta) format, Stata code (.do) and dictionary file (.dct) to read ASCII dataset (.dat) into Stata using layout files (.lis)

Tib neeg lub cev High Precision Segmentation Dataset yog ib qho kev sau dav dav tsom rau cov khaub ncaws, e-lag luam, thiab kev lom zem ua haujlwm pom, sib txuas cov duab thaij duab thiab hauv internet sau nrog cov kev daws teeb meem los ntawm 316 × 600 mus rau 6601 × 9900. Nws tsom rau qhov siab-precision segmentation ntawm tib neeg lub cev, cov ntsiab lus ntawm daim tawv nqaij, lub ntsej muag, lub ntsej muag thiab lub ntsej muag. accessories.

Data on clinically extremely vulnerable people in England during the coronavirus (COVID-19) pandemic from the Shielding Behavioural Survey. Includes information on their behaviours and well-being since receiving shielding guidance.

Extensible Event Stream (XES) software event log obtained through instrumenting the NASA CEV class using the tool available at {https://svn.win.tue.nl/repos/prom/XPort/}. This event log contains method-call level events describing a single run of an exhaustive unit test suite for the Crew Exploration Vehicle (CEV) example available and documented at {http://babelfish.arc.nasa.gov/trac/jpf/wiki/projects/jpf-statechart} (trac) {http://babelfish.arc.nasa.gov/hg/jpf/jpf-statechart} (mercurial repository). Note that the life-cycle information in this log corresponds to method call (start) and return (complete), and captures a method-call hierarchy. We attached a slightly preprocessed variant of this event log, where the execution of each unit test method is represented as a separate trace.

BackgroundsThe Enterovirus genus of the family of Picornaviridae consists of 9 species of Enteroviruses and 3 species of Rhinoviruses based on the latest virus taxonomy. Those viruses contribute significantly to respiratory and digestive disorders in human and animals. Out of 9 Enterovirus species, Enterovirus E-G are closely related to diseases affecting on livestock industry. While enterovirus infection has been increasingly reported in cattle and swine, the enterovirus infections in small ruminants remain largely unknown.MethodsVirology, molecular and bioinformatics methods were employed to characterize a novel enterovirus CEV-JL14 from goats manifesting severe diarrhea with morbidity and mortality respectively up to 84% and 54% in China.ResultsCEV-JL14 was defined and proposed as a new Enterovirus species L within the genus of Enterovirus of the family Picornaviridae. CEV-JL14 had a complete genome sequence of 7461 nucleotides with an ORF encoding 2172 amino acids, and shared 77.1% of genomic sequence identity with TB4-OEV, an ovine enterovirus. Comparison of 5’-UTR and structural genes of CEV-JL14 with known Enterovirus species revealed highly genetic variations among CEV-JL14 with known Enterovirus species. VP1 nucleotide sequence identities of CEV-14 were 51.8%-53.5% with those of Enterovirus E and F, 30.9%-65.3% with Enterovirus G, and 43.8–51. 5% with Enterovirus A-D, respectively. CEV-JL14 was proposed as a novel species within the genus of Enterovirus according to the current ICTV demarcation criteria of enteroviruses.ConclusionsCEV-JL14 clustered phylogenetically to neither Enterovirus E and F, nor to Enterovirus G. It was defined and proposed as novel species L within the genus of Enterovirus. This is the first report of caprine enterovirus in China, the first complete genomic sequence of a caprine enterovirus revealed, and the unveiling of significant genetic variations between ovine enterovirus and caprine enterovirus, thus broadening the current understanding of enteroviruses.

Lub Segmentation thiab Cov Ntsiab Lus Tseem Ceeb ntawm Tib Neeg Lub Cev Dataset yog tsim los rau cov khaub ncaws thiab kev lom zem saib, uas muaj cov duab sau hauv internet nrog cov kev daws teeb meem xws li 1280 x 960 txog 5184 x 3456 pixels. Cov ntaub ntawv no nthuav dav, suav nrog piv txwv thiab ntu ntu ntawm 27 pawg ntawm lub cev nrog rau 24 lub ntsiab lus tseem ceeb, muab cov ntaub ntawv ntxaws ntxaws rau tib neeg lub cev kev tshuaj xyuas thiab kev siv.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

CEV Eaton Vance California Municipal Income Trust Shares of Beneficial Interest

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

California Dreaming: Is Eaton (CEV) a Golden Investment?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

The CEV Dashboard, produced and published by the AmeriCorps Office of Research and Evaluation, is an interactive, user-friendly tool for exploring findings from the Current Population Survey Civic Engagement and Volunteering (CEV) Supplement. The CEV dashboard displays findings from survey waves conducted in September of 2017, 2019, 2021, and 2023. Users can explore trends for all types of civic engagement measured in the CEV at the national level, state level, and across different demographic groups. The dashboard also provides detailed insights into the intensity of formal volunteering activities at the national level.

Sequence identities of CEV-JL14 with known representative enterovirus species (A, B, C, D, E, F, G, H, J).

Philippines Consumer Price Index (CPI): CEV: Health data was reported at 109.300 2012=100 in Jun 2018. This records an increase from the previous number of 108.500 2012=100 for May 2018. Philippines Consumer Price Index (CPI): CEV: Health data is updated monthly, averaging 102.600 2012=100 from Jan 2012 (Median) to Jun 2018, with 78 observations. The data reached an all-time high of 109.300 2012=100 in Jun 2018 and a record low of 99.000 2012=100 in Jan 2012. Philippines Consumer Price Index (CPI): CEV: Health data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.I010: Consumer Price Index: 2012=100: Other Regions.

Autonomous Fuel Supply Module (AFSM), Lunar Surface Access Module (LSAM), Crew Exploration Vehicle (CEV) concepts

During the Phase I NASA SBIR, MATECH GSM (MG) has developed and evaluated the world's first ultra-high temperature (UHT) Zr-(O)-C ceramic fiber pre-form / organic ablative matrix composite TPS system. This Phase II NASA SBIR Proposal from MG seeks to expand this technology to the following areas: 1)Microstructural level refinements and optimization of the char- and ablator phases for more reproducible material systems 2)Scaling-up for the fabrication of a larger and more complex-shape geometry 3)TPS design data generation with extensive arc-jet testing for a full TPS Component demonstration in Phase III. In this TPS material concept, the "char" phase is UHT zirconium carbide (Zr(O)C) ceramic fiber pre-forms, which have dual functions of high compressive strength of ligaments and non-recession of fiber components after matrix ablation. MG's ablative TPS are designed to retain their shape, thereby reducing the thickness requirement and lowering the TPS total mass, crucial at high re-entry velocity. MG's new ablator slowly absorbs high levels of energy during high temperature ablation. At the completion of the Phase II-Base and Phase II-Option program, MG will have fabricated a high specific strength C-Zr(O)C / C-ablator (CZOCA) and have demonstrated one TPS component, operational at > 5000oF.

Philippines Consumer Price Index (CPI): CEV: Restaurants & Misc Goods & Services data was reported at 107.400 2012=100 in Jun 2018. This stayed constant from the previous number of 107.400 2012=100 for May 2018. Philippines Consumer Price Index (CPI): CEV: Restaurants & Misc Goods & Services data is updated monthly, averaging 103.300 2012=100 from Jan 2012 (Median) to Jun 2018, with 78 observations. The data reached an all-time high of 107.400 2012=100 in Jun 2018 and a record low of 98.300 2012=100 in Mar 2012. Philippines Consumer Price Index (CPI): CEV: Restaurants & Misc Goods & Services data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.I010: Consumer Price Index: 2012=100: Other Regions.