This statistic shows the usage of paper towels in the United States in 2020. The data has been calculated by Statista based on the U.S. Census data and Simmons National Consumer Survey (NHCS). According to this statistic, 321.87 million Americans used paper towels in 2020.

This statistic shows the usage of plastic / paper / kitchen and food wrap in the United States in 2020. The data has been calculated by Statista based on the U.S. Census data and Simmons National Consumer Survey (NHCS). According to this statistic, ****** million Americans used plastic / paper / kitchen and food wrap in 2020.

Question Paper Solutions of chapter Introduction to Statistics of Mathematics for Computing, 3rd Semester , Bachelor of Computer Application 2020-2021

Question Paper Solutions of year 2020 of Statistics, Question Paper , Graduate Aptitude Test in Engineering

This statistic shows the number of packages of paper napkins used within one month in the United States in 2020. The data has been calculated by Statista based on the U.S. Census data and Simmons National Consumer Survey (NHCS). According to this statistic, ***** million Americans used * or more packages of paper napkins in 2020.

This publication is an introductory/summary paper to a virtual special issue of the journal Science of the Total Environment titled: Advances in Mercury Research--Reviews of Recent Advances in Mercury Research and Understanding the Biogeochemical Cycle. The special issue contained 11 Research Articles that focused on different aspects of mercury cycling. All these papers were “review papers” and relied on synthesizing conclusions from existing published research and did not involve any direct data collection. The Gustin et al, 2020 paper (which is associated with this Metadata Statement) provides an introduction to the journal’s special issue and briefly summarizes the primary conclusions from the other 11 papers. Therefore, there are not any datasets associated with this publication. This dataset is not publicly accessible because: This publication is an introductory/summary paper to a virtual special issue of the journal Science of the Total Environment titled: Advances in Mercury Research--Reviews of Recent Advances in Mercury Research and Understanding the Biogeochemical Cycle. The special issue contained 11 Research Articles that focused on different aspects of mercury cycling. All these papers were “review papers” and relied on synthesizing conclusions from existing published research and did not involve any direct data collection. The Gustin et al, 2020 paper (which is associated with this Metadata Statement) provides an introduction to the journal’s special issue and briefly summarizes the primary conclusions from the other 11 papers. Therefore, there are not any datasets associated with this publication. It can be accessed through the following means: This paper does not include any data. Format: This paper does not include any data. Citation information for this dataset can be found in the EDG's Metadata Reference Information section and Data.gov's References section.

Version: 5

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2023/09/05

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers. File list:

• data_articles_journal_list_v5.xlsx: full list of 140 academic journals in which data papers or/and software papers could be published
• data_articles_journal_list_v5.csv: full list of 140 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 5th version - Information updated: number of journals, URL, document types associated to a specific journal.

Version: 4

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2022/12/15

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers. File list:

• data_articles_journal_list_v4.xlsx: full list of 140 academic journals in which data papers or/and software papers could be published
• data_articles_journal_list_v4.csv: full list of 140 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 4th version - Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types - Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Journal Citation Reports (JCR) and/or Scimago Journal and Country Rank (SJR), Scopus and Web of Science (WOS), Journal Master List.

Version: 3

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2022/10/28

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers. File list:

• data_articles_journal_list_v3.xlsx: full list of 124 academic journals in which data papers or/and software papers could be published
• data_articles_journal_list_3.csv: full list of 124 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 3rd version - Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types - Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Journal Citation Reports (JCR) and/or Scimago Journal and Country Rank (SJR).

Erratum - Data articles in journals Version 3:

Botanical Studies -- ISSN 1999-3110 -- JCR (JIF) Q2 Data -- ISSN 2306-5729 -- JCR (JIF) n/a Data in Brief -- ISSN 2352-3409 -- JCR (JIF) n/a

Version: 2

Author: Francisco Rubio, Universitat Politècnia de València.

Date of data collection: 2020/06/23

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers. File list:

• data_articles_journal_list_v2.xlsx: full list of 56 academic journals in which data papers or/and software papers could be published
• data_articles_journal_list_v2.csv: full list of 56 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 2nd version - Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types - Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Scimago Journal and Country Rank (SJR)

Total size: 32 KB

Version 1: Description

This dataset contains a list of journals that publish data articles, code, software articles and database articles.

The search strategy in DOAJ and Ulrichsweb was the search for the word data in the title of the journals. Acknowledgements: Xaquín Lores Torres for his invaluable help in preparing this dataset.

Abstract

Globally, more than 130 million people are estimated to be in food crisis. These humanitarian disasters are associated with severe impacts on livelihoods that can reverse years of development gains. The existing outlooks of crisis-affected populations rely on expert assessment of evidence and are limited in their temporal frequency and ability to look beyond several months. This paper presents a statistical foresting approach to predict the outbreak of food crises with sufficient lead time for preventive action. Different use cases are explored related to possible alternative targeting policies and the levels at which finance is typically unlocked. The results indicate that, particularly at longer forecasting horizons, the statistical predictions compare favorably to expert-based outlooks. The paper concludes that statistical models demonstrate good ability to detect future outbreaks of food crises and that using statistical forecasting approaches may help increase lead time for action.

Geographic coverage

Afghanistan, Burkina Faso, Chad, Democratic Republic of Congo, Ethiopia, Guatemala, Haiti, Kenya, Malawi, Mali, Mauritania, Mozambique, Niger, Nigeria, Somalia, South Sudan, Sudan, Uganda, Yemen, Zambia, Zimbabwe

This dataset was used to generate plots for a paper conditionally accepted in the Journal of Advances in Modeling Earth Systems (JAMES), an AGU journal. It comprises four different data sources: WRF simulations, radar observations, an idealized steady-state column model called the Bayesian Observationally-Constrained Statistical Scheme (BOSS), and idealized column rainshaft model using bin microphysics. The WRF simulations consist of output from a set of 11 runs using either bulk or bin microphysics schemes. The version of WRF is V3.9.1. To limit storage requirements, we have only saved a single time-slice of output at hour 6 of the simulations, along with the namelist.input file to generate these runs. The observational data are gridded and rotated composite NEXRAD reflectivity measurements from central Oklahoma. BOSS model output consists of microphysical parameter probability density functions and profiles of (as described in the meta-file for these data). The idealized bin microphysics rainshaft model output consists of profiles of drop mean size, reflectivity factor, precipitation rate, and drop concentration at two different time slices (described in the meta-data file for these data). We are requesting these data be added to the managed NCAR repository so they may be accessible to the community per AGU publication policy and in accordance with a U.S. DOE grant that partially supported this work.

This dataset contains data from the National Center for Education Statistics' Academic Library Survey, which was gathered every two years from 1996 - 2014, and annually in IPEDS starting in 2014 (this dataset has continued to only merge data every two years, following the original schedule). This data was merged, transformed, and used for research by Starr Hoffman and Samantha Godbey.This data was merged using R; R scripts for this merge can be made available upon request. Some variables changed names or definitions during this time; a view of these variables over time is provided in the related Figshare Project. Carnegie Classification changed several times during this period; all Carnegie classifications were crosswalked to the 2000 classification version; that information is also provided in the related Figshare Project. This data was used for research published in several articles, conference papers, and posters starting in 2018 (some of this research used an older version of the dataset which was deposited in the University of Nevada, Las Vegas's repository).SourcesAll data sources were downloaded from the National Center for Education Statistics website https://nces.ed.gov/. Individual datasets and years accessed are listed below.[dataset] U.S. Department of Education, National Center for Education Statistics, Academic Libraries component, Integrated Postsecondary Education Data System (IPEDS), (2020, 2018, 2016, 2014), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7[dataset] U.S. Department of Education, National Center for Education Statistics, Academic Libraries Survey (ALS) Public Use Data File, Library Statistics Program, (2012, 2010, 2008, 2006, 2004, 2002, 2000, 1998, 1996), https://nces.ed.gov/surveys/libraries/aca_data.asp[dataset] U.S. Department of Education, National Center for Education Statistics, Institutional Characteristics component, Integrated Postsecondary Education Data System (IPEDS), (2020, 2018, 2016, 2014), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7[dataset] U.S. Department of Education, National Center for Education Statistics, Fall Enrollment component, Integrated Postsecondary Education Data System (IPEDS), (2020, 2018, 2016, 2014, 2012, 2010, 2008, 2006, 2004, 2002, 2000, 1998, 1996), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7[dataset] U.S. Department of Education, National Center for Education Statistics, Human Resources component, Integrated Postsecondary Education Data System (IPEDS), (2020, 2018, 2016, 2014, 2012, 2010, 2008, 2006), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7[dataset] U.S. Department of Education, National Center for Education Statistics, Employees Assigned by Position component, Integrated Postsecondary Education Data System (IPEDS), (2004, 2002), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7[dataset] U.S. Department of Education, National Center for Education Statistics, Fall Staff component, Integrated Postsecondary Education Data System (IPEDS), (1999, 1997, 1995), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7

This statistic illustrates consumption, production, prices, and trade of sulphite wrapping paper in South Korea from 2007 to 2018

Question Paper Solutions of year 2020 of Microeconomics I and Statistics, Semester I , Bachelors of Commerce (General)

Question Paper Solutions of year 2020 of Business Mathematics and Statistics, Semester III , Bachelors of Commerce (Honours)

This statistic illustrates consumption, production, prices, and trade of paper hand towels in Eastern Asia from 2007 to 2018

The German Library Statistics (DBS) is the national statistics of the German library system and contains statistical key figures. It includes public libraries, scientific libraries, as well as specialized scientific libraries. More information can be found at DBS. This dataset contains the following information on academic libraries in Bavaria 2020: Number (titles) of e-journals and newspapers licensed and digitised in the reporting year, number (titles) of e-journals and newspapers licensed in the reporting year, including [referring to (131)]: Number of e-journals and e-newspapers licensed in the reporting year, number of e-journals and e-newspapers licensed in the reporting year, including [referring to (131)]: Number (titles) of electronic purchase journals and newspapers held on an ongoing basis in the reporting year, expenditure on electronic periodicals and newspapers held on an ongoing basis in the reporting year, other expenditure on electronic periodicals and newspapers, number (titles) of electronic periodicals and newspapers held on an ongoing basis in the reporting year, including [relative to (133)]: newly licensed electronic purchasing magazines and newspapers Note: Due to the pandemic, the data for the reporting years 2020/2021/2022 are only comparable to a limited extent with those of previous years!

The data set contains 2500 manually-stance-labeled tweets, 1250 for each candidate (Joe Biden and Donald Trump). These tweets were sampled from the unlabeled set that our research team collected English tweets related to the 2020 US Presidential election. Through the Twitter Streaming API, the authors collected data using election-related hashtags and keywords. Between January 2020 and September 2020, over 5 million tweets were collected, not including quotes and retweets.

Paper: Knowledge Enhanced Masked Language Model for Stance Detection

Question Paper Solutions of chapter Sample Space of Numerical and statistical Methods, 5th Semester , Bachelor of Computer Application 2020-2021

Question Paper Solutions of Numerical and statistical Methods (BCAD501D),5th Semester,Bachelor of Computer Application 2020-2021,Maulana Abul Kalam Azad University of Technology

Question Paper Solutions of chapter Numerical Differentiation of Numerical and statistical Methods, 5th Semester , Bachelor of Computer Application 2020-2021

Question Paper Solutions of chapter Statistical Quality Control of Data Analytics Skills for Managers, 5th Semester , Bachelor in Business Administration 2020 - 2021