This item contains supplemental material referenced by the paper by Tang et al., “Misuse, Misreporting, Misinterpretation of Statistical Methods in Usable Privacy and Security Papers” at the Symposium on Usable Security and Privacy (SOUPS), 2025.It contains two files:List of Papers: The list of all SOUPS papers, along with the year of publication, considered in this study.Tests and Statistics Considered: The table contains the statistical tests considered in this study along with the associated statistics.

Listing of all (active and inactive) businesses registered with the Office of Finance. An "active" business is defined as a registered business whose owner has not notified the Office of Finance of a cease of business operations. Update Interval: Monthly. NAICS Codes are from 2007 NAICS: https://www.census.gov/cgi-bin/sssd/naics/naicsrch?chart=2007

View yearly data collected by the Civil Service Commission (CSC) on the number of appeals filed by calendar year.

This dataset relates to research on the connections between archives professionals and research data management. It consists of a single Excel spreadsheet with four sheets, containing an analysis of emails sent to two email discussions lists: Archives-NRA (Archivists, conservators and records managers) and Research-Dataman. The coded dataset and a list of codes used for each mailing list is provided.The two datasets were downloaded from the JiscMail Email Discussion list archives on 27 July 2018. The Archives-NRA dataset was compiled by conducting a free text search for "research data" on the mailing list's archives, and the metadata for every search result was downloaded and coded (144 metadata records in total). The resulting coded dataset demonstrates how frequently archivists and records professionals discuss research data on the Archives-NRA list, the topics which are discussed, and an increase in these discussions over time. The Research-Dataman dataset was compiled by conducting a free text search for "archivist" on the mailing list's archives, and the metadata for every search result was downloaded and coded (197 emails total). The resulting coded dataset demonstrates how frequently data management professionals seek the advice of archivists or advertise vacancies for archivists, and how often archivists email this mailing list. The names and email addresses of the mailing list participants have been redacted for privacy reasons but the original full-text emails can be accessed by members of the respective mailing lists using the URLs provided in the dataset.

Taiwan Higher Education Institutions Communication Information

Municipal Fiscal Indicators is an annual compendium of information compiled by the Office of Policy and Management, Office of Finance, Municipal Finance Services Unit (MFS). The data contained in Indicators provides key financial and demographic information on municipalities in Connecticut.

Municipal Fiscal Indicators contains the most current financial data available for each of Connecticut's 169 municipalities. The majority of this data was compiled from the audited financial statements that are filed annually with the State of Connecticut, Office of Policy and Management, Office of Finance. This database of information includes selected demographic and economic data relating to, or having an impact upon, a municipality’s financial condition. The most recent edition is for the Fiscal Years Ended 2015-2019 published in April 2021.

The Grand List is the aggregate valuation of taxable property within a given municipality. The Grand Lists component data provides a breakdown by certain assessment categories and their valuation.

Data on the Municipal Fiscal Indicators is included in the following datasets:

Municipal Fiscal Indicators, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-2019/sb4i-6vik

Municipal Fiscal Indicators: Grand List Components, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Grand-List-Components-/ifrb-kp2b

Municipal Fiscal Indicators: Pension Funding Information For Defined Benefit Pension Plans, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Pension-Funding-Inform/civu-w22d

Municipal Fiscal Indicators: Type and Number of Pension Plans, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Type-and-Number-of-Pen/9f65-c4yr

Municipal Fiscal Indicators: Other Post-Employment Benefits (OPEB), 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Other-Post-Employment-/sa26-46h8

Municipal Fiscal Indicators: Economic and Grand List Data, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Economic-and-Grand-Lis/wpbp-b657

Municipal Fiscal Indicators: Benchmark Labor Data, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Benchmark-Labor-Data-2/db37-h23r

Municipal Fiscal Indicators: Unemployment, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Unemployment-2019/cugp-2za3

According to a survey conducted in *************, **** percent of computer users in Japan neither knew the term nor the meaning of password list attacks. Password list attacks represent a form of account hacking in which attackers gain access to an account via a list of correct IDs and passwords.

Financial overview and grant giving statistics of Ruth's List Florida Action

Financial overview and grant giving statistics of Fill Your Bucket List Foundation

Financial overview and grant giving statistics of Annie's List Training and Engagement Fund

BEA's Public Data Listing

This dataset contains the ICD-10 code lists used to test the sensitivity and specificity of the Clinical Practice Research Datalink (CPRD) medical code lists for dementia subtypes. The provided code lists are used to define dementia subtypes in linked data from the Hospital Episode Statistic (HES) inpatient dataset and the Office of National Statistics (ONS) death registry, which are then used as the 'gold standard' for comparison against dementia subtypes defined using the CPRD medical code lists. The CPRD medical code lists used in this comparison are available here: Venexia Walker, Neil Davies, Patrick Kehoe, Richard Martin (2017): CPRD codes: neurodegenerative diseases and commonly prescribed drugs. https://doi.org/10.5523/bris.1plm8il42rmlo2a2fqwslwckm2 Complete download (zip, 3.9 KiB)

In 2024, around 2.6 thousand children in Japan were on the waiting lists to be accepted to nursery centers. The shortage of daycare centers in the country continued, although the number of children on the waiting lists significantly decreased in recent years.

College Affordability and Transparency List Explanation Form 2016-17 (CATEF 2016-17) is a cross-sectional data collection that collects information on the major areas of institutions' budgets with the greatest cost increases, the explanations for these increases, and the steps institutions have been or will be taking towards reducing these costs. The data collection is conducted on the subset of institutions that appear on the tuition and fees and/or net price increase lists for being in the five percent of institutions in their institutional sector that have the highest increases, expressed as a percentage change, over the three-year time period. This data collection is mandatory and expects a 100 percent response rate. Key statistics produced from CATEF 2016Ã-17 are a description of the major areas in the institution's budget with the greatest cost increases; an explanation of the cost increases; a description of the steps the institution will take toward the goal of reducing costs in the areas described; an explanation of the extent to which the institution participates in determining such cost increase; the identification of the agency or instrumentality of state government responsible for determining such cost increase; and any other information the institution considers relevant to the report.

United States Avg Sale to List: sa: Single-Family: Heber, UT data was reported at 97.044 % in Jul 2020. This records a decrease from the previous number of 97.463 % for Jun 2020. United States Avg Sale to List: sa: Single-Family: Heber, UT data is updated monthly, averaging 96.934 % from Feb 2012 (Median) to Jul 2020, with 102 observations. The data reached an all-time high of 99.625 % in Jan 2016 and a record low of 94.047 % in Mar 2012. United States Avg Sale to List: sa: Single-Family: Heber, UT data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB051: Average Sales to List: by Metropolitan Areas: Seasonally Adjusted.

United States Avg Sale to List: Townhouse: San Luis Obispo, CA data was reported at 101.264 % in Jul 2020. This records an increase from the previous number of 98.462 % for Jun 2020. United States Avg Sale to List: Townhouse: San Luis Obispo, CA data is updated monthly, averaging 98.753 % from Mar 2014 (Median) to Jul 2020, with 41 observations. The data reached an all-time high of 101.581 % in Aug 2019 and a record low of 94.466 % in Sep 2017. United States Avg Sale to List: Townhouse: San Luis Obispo, CA data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB050: Average Sales to List: by Metropolitan Areas.

Explore a comprehensive dataset detailing the list of products exported by GCC countries . Find information on commodities such as cocoa, apparel, pearls, vehicles, plastics, and more. Discover valuable insights into the export activities of Bahrain, China, India, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates.

Cocoa and cocoa preparations, Articles of apparel and clothing accessories, knitted or crocheted, Natural or cultured pearls, precious or semi-precious stones, precious metals, metals clad ..., Vehicles other than railway or tramway rolling stock, and parts and accessories thereof, Plastics and articles thereof, Raw hides and skins (other than furskins) and leather, Prepared feathers and down and articles made of feathers or of down; artificial flowers; articles ..., All products, Railway or tramway locomotives, rolling stock and parts thereof; railway or tramway track fixtures ..., Special woven fabrics; tufted textile fabrics; lace; tapestries; trimmings; embroidery, Animal or vegetable fats and oils and their cleavage products; prepared edible fats; animal ..., Paper and paperboard; articles of paper pulp, of paper or of paperboard, Wadding, felt and nonwovens; special yarns; twine, cordage, ropes and cables and articles thereof, Furniture; bedding, mattresses, mattress supports, cushions and similar stuffed furnishings; ..., Other base metals; cermets; articles thereof, Lead and articles thereof, Toys, games and sports requisites; parts and accessories thereof, Wool, fine or coarse animal hair; horsehair yarn and woven fabric, Cork and articles of cork, Essential oils and resinoids; perfumery, cosmetic or toilet preparations, Tobacco and manufactured tobacco substitutes, Preparations of vegetables, fruit, nuts or other parts of plants, Live animals, Works of art, collectors' pieces and antiques, Beverages, spirits and vinegar, Ores, slag and ash, Miscellaneous edible preparations, Clocks and watches and parts thereof, Glass and glassware, Zinc and articles thereof, Headgear and parts thereof, Live trees and other plants; bulbs, roots and the like; cut flowers and ornamental foliage, Man-made staple fibres, 'TOTAL, Silk, Nickel and articles thereof, Inorganic chemicals; organic or inorganic compounds of precious metals, of rare-earth metals, ..., Edible vegetables and certain roots and tubers, Tools, implements, cutlery, spoons and forks, of base metal; parts thereof of base metal, Lac; gums, resins and other vegetable saps and extracts, Products of the milling industry; malt; starches; inulin; wheat gluten, Fish and crustaceans, molluscs and other aquatic invertebrates, Albuminoidal substances; modified starches; glues; enzymes, Aircraft, spacecraft, and parts thereof, Optical, photographic, cinematographic, measuring, checking, precision, medical or surgical ..., Umbrellas, sun umbrellas, walking sticks, seat-sticks, whips, riding-crops and parts thereof, Articles of iron or steel, Wood and articles of wood; wood charcoal, Rubber and articles thereof, Cotton, Explosives; pyrotechnic products; matches; pyrophoric alloys; certain combustible preparations, Iron and steel, Mineral fuels, mineral oils and products of their distillation; bituminous substances; mineral ..., Copper and articles thereof, Soap, organic surface-active agents, washing preparations, lubricating preparations, artificial ..., Commodities not elsewhere specified, Ships, boats and floating structures, Other made-up textile articles; sets; worn clothing and worn textile articles; rags, Tin and articles thereof, Organic chemicals, Articles of leather; saddlery and harness; travel goods, handbags and similar containers; articles ..., Carpets and other textile floor coverings, Fertilisers, Sugars and sugar confectionery, Edible fruit and nuts; peel of citrus fruit or melons, Miscellaneous chemical products, Manufactures of straw, of esparto or of other plaiting materials; basketware and wickerwork, Furskins and artificial fur; manufactures thereof, Printed books, newspapers, pictures and other products of the printing industry; manuscripts, ..., Meat and edible meat offal, Aluminium and articles thereof, Products of animal origin, not elsewhere specified or included, Pharmaceutical products, Electrical machinery and equipment and parts thereof; sound recorders and reproducers, television, Preparations of meat, of fish or of crustaceans, molluscs or other aquatic invertebrates, Preparations of cereals, flour, starch or milk; pastrycooks' products, Photographic or cinematographic goods, Coffee, tea, spices, Impregnated, coated, covered or laminated textile fabrics; textile articles of a kind suitable, Knitted or crocheted fabrics, Miscellaneous manufactured articles, Dairy produce; birds' eggs; natural honey; edible products of animal origin, not elsewhere, Footwear, gaiters and the like; parts of such articles, Arms and ammunition; parts and accessories thereof, Articles of stone, plaster, cement, asbestos, mica or similar materials, Cereals, Man-made filaments; strip and the like of man-made textile materials, Musical instruments; parts and accessories of such articles, China, Salt; sulphur; earths and stone; plastering materials, lime and cement, Pulp of wood or of other fibrous cellulosic material; recovered (waste and scrap) paper, Other vegetable textile fibres; paper yarn and woven fabrics of paper yarn, Residues and waste from the food industries; prepared animal fodder, Ceramic products, Tanning or dyeing extracts; tannins and their derivatives; dyes, pigments and other colouring, Machinery, mechanical appliances, nuclear reactors, boilers; parts thereof, Oil seeds and oleaginous fruits; miscellaneous grains, seeds and fruit; industrial or medicinal, Vegetable plaiting materials; vegetable products not elsewhere specified or included, Miscellaneous articles of base metal, Articles of apparel and clothing accessories, not knitted or crocheted, Exports, Exporters, Commodity

Bahrain, China, India, Kuwait, Oman, Qatar, Saudi Arabia, United Arab EmiratesFollow data.kapsarc.org for timely data to advance energy economics research..

Bahrain Sources: ITC calculations based on UN COMTRADE statistics since January, 2020.

       ITC

calculations based on Central Informatics Organisation (CIO) statistics since January, 2015 and until January, 2020.

       ITC

calculations based on UN COMTRADE statistics until January, 2015.

China Sources: ITC calculations based on General Customs Administration of China statistics since January, 2015.

       ITC

calculations based on UN COMTRADE statistics until January, 2015.

India Sources: ITC calculations based on UN COMTRADE statistics since January, 2019.

       ITC

calculations based on Directorate General of Commercial Intelligence & Statistics statistics since January, 2015 and until January, 2019.

       ITC

calculations based on UN COMTRADE statistics until January, 2015.

Qatar Sources: ITC calculations based on UN COMTRADE statistics since January, 2016.

       ITC

calculations based on Ministry of Development Planning and Statistics statistics since January, 2009 and until January, 2016.

       ITC

calculations based on UN COMTRADE statistics until January, 2009.

Saudi Arabia Sources: ITC calculations based on Central Department Of Statistics & Information statistics since January, 2019.

       ITC

calculations based on UN COMTRADE statistics since January, 2018 and until January, 2019.

       ITC

calculations based on Central Department Of Statistics & Information statistics since January, 2015 and until January, 2018.

       ITC

calculations based on UN COMTRADE statistics until January, 2015.

Kuwait Sources: ITC calculations based on UN COMTRADE statistics since January, 2018.

       ITC

calculations based on Central Statistical Bureau statistics since January, 2012 and until January, 2018.

       ITC

calculations based on UN COMTRADE statistics since January, 2010 and until January, 2012.

       ITC

calculations based on Central Statistical Bureau statistics since January, 2009 and until January, 2010.

       ITC

calculations based on UN COMTRADE statistics until January, 2009.

United Arab Emirates Sources: ITC calculations based on Federal Competitiveness and Statistics Authority statistics since January, 2017.

       ITC

calculations based on UN COMTRADE statistics until January, 2017.

Oman Sources: ITC calculations based on UN COMTRADE statistics since January, 2016.

       ITC

calculations based on Public Authority for Investment Promotion and Export Development (Ithraa) statistics since January, 2015 and until January, 2016.

       ITC

calculations based on UN COMTRADE statistics until January, 2015.

List of 8 letter words for countdown game. See attached code