The Treatment Episode Data Set -- Admissions (TEDS-A) is a national census data system of annual admissions to substance abuse treatment facilities. TEDS-A provides annual data on the number and characteristics of persons admitted to public and private substance abuse treatment programs that receive public funding. The unit of analysis is a treatment admission. TEDS consists of data reported to state substance abuse agencies by the treatment programs, which in turn report it to SAMHSA. A sister data system, called the Treatment Episode Data Set -- Discharges (TEDS-D), collects data on discharges from substance abuse treatment facilities. The first year of TEDS-A data is 1992, while the first year of TEDS-D is 2006. TEDS variables that are required to be reported are called the "Minimum Data Set (MDS)", while those that are optional are called the "Supplemental Data Set (SuDS)". Variables in the MDS include: information on service setting, number of prior treatments, primary source of referral, sex, race, ethnicity, education, employment status, substance(s) abused, route of administration, frequency of use, age at first use, and whether methadone was prescribed in treatment. Supplemental variables include: diagnosis codes, presence of psychiatric problems, living arrangements, source of income, health insurance, expected source of payment, pregnancy and veteran status, marital status, detailed not in labor force codes, detailed criminal justice referral codes, days waiting to enter treatment, and the number of arrests in the 30 days prior to admissions (starting in 2008). Substances abused include alcohol, cocaine and crack, marijuana and hashish, heroin, nonprescription methadone, other opiates and synthetics, PCP, other hallucinogens, methamphetamine, other amphetamines, other stimulants, benzodiazepines, other non-benzodiazepine tranquilizers, barbiturates, other non-barbiturate sedatives or hypnotics, inhalants, over-the-counter medications, and other substances. Created variables include total number of substances reported, intravenous drug use (IDU), and flags for any mention of specific substances. This study has 1 Data Set.

The Treatment Episode Data Set -- Discharges (TEDS-D) is a national census data system of annual discharges from substance abuse treatment facilities. TEDS-D provides annual data on the number and characteristics of persons discharged from public and private substance abuse treatment programs that receive public funding. Data collected both at admission and at discharge is included. The unit of analysis is a treatment discharge. TEDS-D consists of data reported to state substance abuse agencies by the treatment programs, which in turn report it to SAMHSA. A sister data system, called the Treatment Episode Data Set -- Admissions (TEDS-A), collects data on admissions to substance abuse treatment facilities. The first year of TEDS-A data is 1992, while the first year of TEDS-D is 2006. TEDS-D variables that are required to be reported are called the "Minimum Data Set (MDS)", while those that are optional are called the "Supplemental Data Set (SuDS)". Variables unique to TEDS-D, and not part of TEDS-A, are the length of stay, reason for leaving treatment, and service setting at time of discharge. TEDS-D also provides many of the same variables that exist in TEDS-A. This includes information on service setting, number of prior treatments, primary source of referral, sex, race, ethnicity, education, employment status, substance(s) abused, route of administration, frequency of use, age at first use, and whether methadone was prescribed in treatment. Supplemental variables include: diagnosis codes, presence of psychiatric problems, living arrangements, source of income, health insurance, expected source of payment, pregnancy and veteran status, marital status, detailed not in labor force codes, detailed criminal justice referral codes, days waiting to enter treatment, and the number of arrests in the 30 days prior to admissions (starting in 2008) . Substances abused include alcohol, cocaine and crack, marijuana and hashish, heroin, nonprescription methadone, other opiates and synthetics, PCP, other hallucinogens, methamphetamine, other amphetamines, other stimulants, benzodiazepines, other non-benzodiazepine tranquilizers, barbiturates, other non-barbiturate sedatives or hypnotics, inhalants, over-the-counter medications, and other substances. Created variables include total number of substances reported, intravenous drug use (IDU), and flags for any mention of specific substances.This study has 1 Data Set.

The Treatment Episode Data Set -- Admissions (TEDS-A) is a national census data system of annual admissions to substance abuse treatment facilities. TEDS-A provides annual data on the number and characteristics of persons admitted to public and private substance abuse treatment programs that receive public funding. The unit of analysis is a treatment admission. TEDS consists of data reported to state substance abuse agencies by the treatment programs, which in turn report it to SAMHSA.
A sister data system, called the Treatment Episode Data Set -- Discharges (TEDS-D), collects data on discharges from substance abuse treatment facilities. The first year of TEDS-A data is 1992, while the first year of TEDS-D is 2006.
TEDS variables that are required to be reported are called the "Minimum Data Set (MDS)", while those that are optional are called the "Supplemental Data Set (SuDS)".
Variables in the MDS include: information on service setting, number of prior treatments, primary source of referral, sex, race, ethnicity, education, employment status, substance(s) abused, route of administration, frequency of use, age at first use, and whether methadone was prescribed in treatment. Supplemental variables include: diagnosis codes, presence of psychiatric problems, living arrangements, source of income, health insurance, expected source of payment, pregnancy and veteran status, marital status, detailed not in labor force codes, detailed criminal justice referral codes, days waiting to enter treatment, and the number of arrests in the 30 days prior to admissions (starting in 2008).
Substances abused include alcohol, cocaine and crack, marijuana and hashish, heroin, nonprescription methadone, other opiates and synthetics, PCP, other hallucinogens, methamphetamine, other amphetamines, other stimulants, benzodiazepines, other non-benzodiazepine tranquilizers, barbiturates, other non-barbiturate sedatives or hypnotics, inhalants, over-the-counter medications, and other substances.
Created variables include total number of substances reported, intravenous drug use (IDU), and flags for any mention of specific substances. This study has 1 Data Set.

The Treatment Episode Data Set -- Admissions (TEDS-A) is a national census data system of annual admissions to substance abuse treatment facilities. TEDS-A provides annual data on the number and characteristics of persons admitted to public and private substance abuse treatment programs that receive public funding. The unit of analysis is a treatment admission. TEDS consists of data reported to state substance abuse agencies by the treatment programs, which in turn report it to SAMHSA.
A sister data system, called the Treatment Episode Data Set -- Discharges (TEDS-D), collects data on discharges from substance abuse treatment facilities. The first year of TEDS-A data is 1992, while the first year of TEDS-D is 2006.
TEDS variables that are required to be reported are called the "Minimum Data Set (MDS)", while those that are optional are called the "Supplemental Data Set (SuDS)".
Variables in the MDS include: information on service setting, number of prior treatments, primary source of referral, gender, race, ethnicity, education, employment status, substance(s) abused, route of administration, frequency of use, age at first use, and whether methadone was prescribed in treatment. Supplemental variables include: diagnosis codes, presence of psychiatric problems, living arrangements, source of income, health insurance, expected source of payment, pregnancy and veteran status, marital status, detailed not in labor force codes, detailed criminal justice referral codes, days waiting to enter treatment, and the number of arrests in the 30 days prior to admissions (starting in 2008).
Substances abused include alcohol, cocaine and crack, marijuana and hashish, heroin, nonprescription methadone, other opiates and synthetics, PCP, other hallucinogens, methamphetamine, other amphetamines, other stimulants, benzodiazepines, other non-benzodiazepine tranquilizers, barbiturates, other non-barbiturate sedatives or hypnotics, inhalants, over-the-counter medications, and other substances.
Created variables include total number of substances reported, intravenous drug use (IDU), and flags for any mention of specific substances.This study has 1 Data Set.

The Treatment Episode Data Set -- Admissions (TEDS-A) is a national census data system of annual admissions to substance abuse treatment facilities. TEDS-A provides annual data on the number and characteristics of persons admitted to public and private substance abuse treatment programs that receive public funding. The unit of analysis is a treatment admission. TEDS consists of data reported to state substance abuse agencies by the treatment programs, which in turn report it to SAMHSA. A sister data system, called the Treatment Episode Data Set -- Discharges (TEDS-D), collects data on discharges from substance abuse treatment facilities. The first year of TEDS-A data is 1992, while the first year of TEDS-D is 2006. TEDS variables that are required to be reported are called the "Minimum Data Set (MDS)", while those that are optional are called the "Supplemental Data Set (SuDS)". Variables in the MDS include: information on service setting, number of prior treatments, primary source of referral, sex, race, ethnicity, education, employment status, substance(s) abused, route of administration, frequency of use, age at first use, and whether methadone was prescribed in treatment. Supplemental variables include: diagnosis codes, presence of psychiatric problems, living arrangements, source of income, health insurance, expected source of payment, pregnancy and veteran status, marital status, detailed not in labor force codes, detailed criminal justice referral codes, days waiting to enter treatment, and the number of arrests in the 30 days prior to admissions (starting in 2008) . Substances abused include alcohol, cocaine and crack, marijuana and hashish, heroin, nonprescription methadone, other opiates and synthetics, PCP, other hallucinogens, methamphetamine, other amphetamines, other stimulants, benzodiazepines, other non-benzodiazepine tranquilizers, barbiturates, other non-barbiturate sedatives or hypnotics, inhalants, over-the-counter medications, and other substances. Created variables include total number of substances reported, intravenous drug use (IDU), and flags for any mention of specific substances.This study has 1 Data Set.

The Treatment Episode Data Set -- Discharges (TEDS-D) is a national census data system of annual discharges from substance abuse treatment facilities. TEDS-D provides annual data on the number and characteristics of persons discharged from public and private substance abuse treatment programs that receive public funding. Data collected both at admission and at discharge is included. The unit of analysis is a treatment discharge. TEDS-D consists of data reported to state substance abuse agencies by the treatment programs, which in turn report it to SAMHSA. A sister data system, called the Treatment Episode Data Set -- Admissions (TEDS-A), collects data on admissions to substance abuse treatment facilities. The first year of TEDS-A data is 1992, while the first year of TEDS-D is 2006. TEDS-D variables that are required to be reported are called the "Minimum Data Set (MDS)", while those that are optional are called the "Supplemental Data Set (SuDS)". Variables unique to TEDS-D, and not part of TEDS-A, are the length of stay, reason for leaving treatment, and service setting at time of discharge. TEDS-D also provides many of the same variables that exist in TEDS-A. This includes information on service setting, number of prior treatments, primary source of referral, sex, race, ethnicity, education, employment status, substance(s) abused, route of administration, frequency of use, age at first use, and whether methadone was prescribed in treatment. Supplemental variables include: diagnosis codes, presence of psychiatric problems, living arrangements, source of income, health insurance, expected source of payment, pregnancy and veteran status, marital status, detailed not in labor force codes, detailed criminal justice referral codes, days waiting to enter treatment, and the number of arrests in the 30 days prior to admissions (starting in 2008) . Substances abused include alcohol, cocaine and crack, marijuana and hashish, heroin, nonprescription methadone, other opiates and synthetics, PCP, other hallucinogens, methamphetamine, other amphetamines, other stimulants, benzodiazepines, other non-benzodiazepine tranquilizers, barbiturates, other non-barbiturate sedatives or hypnotics, inhalants, over-the-counter medications, and other substances. Created variables include total number of substances reported, intravenous drug use (IDU), and flags for any mention of specific substances. This study has 1 Data Set.

The Treatment Episode Data Set -- Admissions (TEDS-A) is a national census data system of annual admissions to substance abuse treatment facilities. TEDS-A provides annual data on the number and characteristics of persons admitted to public and private substance abuse treatment programs that receive public funding. The unit of analysis is a treatment admission. TEDS consists of data reported to state substance abuse agencies by the treatment programs, which in turn report it to SAMHSA.
A sister data system, called the Treatment Episode Data Set -- Discharges (TEDS-D), collects data on discharges from substance abuse treatment facilities. The first year of TEDS-A data is 1992, while the first year of TEDS-D is 2006.
TEDS variables that are required to be reported are called the "Minimum Data Set (MDS)", while those that are optional are called the "Supplemental Data Set (SuDS)".
Variables in the MDS include: information on service setting, number of prior treatments, primary source of referral, gender, race, ethnicity, education, employment status, substance(s) abused, route of administration, frequency of use, age at first use, and whether methadone was prescribed in treatment. Supplemental variables include: diagnosis codes, presence of psychiatric problems, living arrangements, source of income, health insurance, expected source of payment, pregnancy and veteran status, marital status, detailed not in labor force codes, detailed criminal justice referral codes, days waiting to enter treatment, and the number of arrests in the 30 days prior to admissions (starting in 2008).
Substances abused include alcohol, cocaine and crack, marijuana and hashish, heroin, nonprescription methadone, other opiates and synthetics, PCP, other hallucinogens, methamphetamine, other amphetamines, other stimulants, benzodiazepines, other non-benzodiazepine tranquilizers, barbiturates, other non-barbiturate sedatives or hypnotics, inhalants, over-the-counter medications, and other substances.
Created variables include total number of substances reported, intravenous drug use (IDU), and flags for any mention of specific substances.This study has 1 Data Set.

This dataset tracks the updates made on the dataset "Treatment Episode Data Set: Admissions (TEDS-A-2005)" as a repository for previous versions of the data and metadata.

This repository contains databases of protein domains for use with Foldclass and Merizo-search. We provide databases for all 365 million domains in TED, as well as all classified domains in CATH 4.3.Foldclass and Merizo-search use two formats for databases. The default format uses a PyTorch tensor and a pickled list of Python tuples to store the data. This format is used for the CATH database, which is small enough to fit in memory. For larger-than-memory datasets, such as TED, we use a binary format that is searched using the Faiss library.The CATH database requires approximately 1.4 GB of disk space, whereas the TED database requires about 885 GB. Please ensure you have enough free storage space before downloading. For best search performance with the TED database, the database should be stored on the fastest storage hardware available to you.IMPORTANT:We recommend going in to each folder and downloading the files; if you attempt to download each folder in one go, it will download a zip file which will need to be decompressed. This is particularly an issue if downloading the TED database, as you will need to have roughly twice the storage space needed as compared to downloading the individual files. Our GitHub repository (see Related Materials below) contains a convenience script to download each database; we recommend using that.

Dataset description:

The Encyclopedia of Domains (TED) is a joint effort by CATH (Orengo group) and the Jones group at University College London to identify and classify protein domains in AlphaFold2 models from AlphaFold Database version 4, covering over 188 million unique sequences and 324 million domain assignments.

In this data release, we will be making available to the community a table of domain boundaries and additional metadata on quality (pLDDT, globularity, number of secondary structures), taxonomy and putative CATH SuperFamily or Fold assignments for all 324 million domains in TED100.

For all chains in the TED-redundant dataset, the attached file contains boundaries predictions, consensus level and information on the TED100 representative.

Additionally, an archive with chain-level consensus domain assignments are available for 21 model organisms and 25 global health proteomes:

For both TED100 and TEDredundant we provide domain boundaries predictions outputted by each of the three methods employed in the project (Chainsaw, Merizo, UniDoc).

We are making available 7,427 novel folds PDB files, identified during the TED classification process with an annotation table sorted by novelty.

Please use the gunzip command to extract files with a '.gz' extension.

CATH annotations have been assigned using the FoldSeek algorithm applied in various modes and the FoldClass algorithm, both of which are used to report significant structural similarity to a known CATH domain.
Note: The TED protocol differs from that of our standard CATH Assignment protocol for superfamily assignment, which also involves HMM-based protocols and manual curation for remote matches.

This dataset contains:

• ted_214m_per_chain_segmentation.tsv
  The file contains all 214M protein chains in TED with consensus domain boundaries and proteome information in the following columns.
  1. AFDB_model_ID: chain identifier from AFDB in the format AF-
• ted_365m_domain_boundaries_consensus_level.tsv.gz
  The file contains all domain assignments in TED100 and TED-redundant (365M) in the format:
  1. TED_ID: TED domain identifier in the format AF-
• ted_100_324m.domain_summary.cath.globularity.taxid.tsv and novel_folds_set.domain_summary.tsv are header-less with the following columns separated by tabs (.tsv).
• ted_324m_seq_clustering.cathlabels.tsv
  The file contains the results of the domain sequences clustering with MMseqs2.
  Columns:
  1. Cluster_representative
  2. Cluster_member
  3. CATH code assignment if available i.e. 3.40.50.300 for a domain with a homologous match or 3.20.20 for a domain matching at the fold level in the CATH classification
  4. CATH assignment type - either Foldseek-T, Foldseek-H or Foldclass
• novel_folds_set.domain_summary.tsv is sorted by novelty.
  1. ted_id - TED domain identifier in the format AF-
• Domain assignments for TED redundant using single-chain and multi-chain consensus in ted_redundant_39m.multichain.consensus_domain_summary.taxid.tsv and ted_redundant_39m.singlechain.consensus_domain_summary.taxid.tsv
  The files contain a header with the following fields. Each column is tab-separated (.tsv).
  1. TED_redundant_id - TED chain identifier in the format AF-
• and ted_redundant_39m.singlechain.consensus_domain_summary.taxid.tsv
  The file contains a header with the following fields. Each column is tab-separated (.tsv).
  1. TED_redundant_id - TED chain identifier in the format AF-
• novel_folds_set_models.tar.gz contains PDB files of all novel folds identified in TED100.
• All per-tool domain boundaries predictions are in the same format with the following columns.
  1. TED_chainID - TED chain identifier in the format AF-
• Domain boundaries predictions share the same format, with each segment separated by '_' and segment boundaries (start,stop) separated by '-'
  
  i.e.domain prediction by Merizo for AF-A0A000-F1-model_v4
  AF-A0A000-F1-model_v4 e8872c7a0261b9e88e6ff47eb34e4162 394 2 10-52_289-394,53-288 0.90077
  
  Merizo predicts one continuous domain and a discontinuous domain,
  Domain1 (discontinuous): 10-52_289-394
  segment1: 10-52
  segment2: 289-394
  Domain 2 (continuous):
  segment 1: 53-288
• ted-tools-main.zip - copy of the https://github.com/psipred/ted-tools repository, containing tools and software used to generate TED.
• cath-alphaflow-main.zip - copy of CATH-AlphaFlow, used to generate globularity scores for TED domains.
• ted-web-master.zip - copy of TED-web, containing code to generate the web interface of TED (https://ted.cathdb.info)
• gofocus_data.tar.bz2 - GOFocus model weights

The p-value is based on the chi-square test for homogeneity.

The Treatment Episode Data Set -- Admissions (TEDS-A) is a national census data system of annual admissions to substance abuse treatment facilities. TEDS-A provides annual data on the number and characteristics of persons admitted to public and private substance abuse treatment programs that receive public funding. The unit of analysis is a treatment admission. TEDS consists of data reported to state substance abuse agencies by the treatment programs, which in turn report it to SAMHSA. A sister data system, called the Treatment Episode Data Set -- Discharges (TEDS-D), collects data on discharges from substance abuse treatment facilities. The first year of TEDS-A data is 1992, while the first year of TEDS-D is 2006. TEDS variables that are required to be reported are called the "Minimum Data Set (MDS)", while those that are optional are called the "Supplemental Data Set (SuDS)". Variables in the MDS include: information on service setting, number of prior treatments, primary source of referral, gender, race, ethnicity, education, employment status, substance(s) abused, route of administration, frequency of use, age at first use, and whether methadone was prescribed in treatment. Supplemental variables include: diagnosis codes, presence of psychiatric problems, living arrangements, source of income, health insurance, expected source of payment, pregnancy and veteran status, marital status, detailed not in labor force codes, detailed criminal justice referral codes, days waiting to enter treatment, and the number of arrests in the 30 days prior to admissions (starting in 2008). Substances abused include alcohol, cocaine and crack, marijuana and hashish, heroin, nonprescription methadone, other opiates and synthetics, PCP, other hallucinogens, methamphetamine, other amphetamines, other stimulants, benzodiazepines, other non-benzodiazepine tranquilizers, barbiturates, other non-barbiturate sedatives or hypnotics, inhalants, over-the-counter medications, and other substances. Created variables include total number of substances reported, intravenous drug use (IDU), and flags for any mention of specific substances.This study has 1 Data Set.

This dataset tracks the updates made on the dataset "Treatment Episode Data Set: Admissions (TEDS-A-2006)" as a repository for previous versions of the data and metadata.

Eine Teilmenge von Tenders Electronic Daily (TED) Daten über die Vergabe öffentlicher Aufträge für den Europäischen Wirtschaftsraum, die Schweiz und die Republik Nordmazedonien vom 01.01.2006 bis 2020-12-31 im Format Komma getrennter Wert (CSV). Diese Daten umfassen die wichtigsten Felder aus der Bekanntmachung und den Standardformularen für die Vergabebekanntmachung, z. B. wer was gekauft hat, von wem, für wie viel, und welches Verfahren und Zuschlagskriterien verwendet wurden.

Im Allgemeinen bestehen die Daten aus Angeboten, die über den Schwellenwerten für die Auftragsvergabe liegen. Die Veröffentlichung unterhalb des Schwellenwerts von Angeboten in TED gilt jedoch als bewährte Verfahren, so dass auch eine nicht unerhebliche Anzahl von Angeboten unterhalb der Schwellenwerte vorhanden ist.

Wichtige Informationen zu den Daten und deren Verwendung finden Sie im folgenden Dokument, einschließlich einer Versionshistorie des Exports.

Die Europäische Kommission ist an den Forschungsergebnissen zur Vergabe öffentlicher Aufträge interessiert, die sich aus der Weiterverwendung dieser Daten ergeben. Daher werden wir dankbar sein, Links zu allen Papieren, Berichten oder Bewerbungen unter GROW-G4@ec.europa.eu zu erhalten.

Ted mit breiterer Abdeckung ist auch im XML-Format unter https://data.europa.eu/euodp/en/data/dataset/ted-1 verfügbar.

This dataset provides information about the number of properties, residents, and average property values for Teds Drive cross streets in Coldwater, MI.

LDC reference: https://catalog.ldc.upenn.edu/LDC2002T03The Translanguage English Database (TED) Transcripts corpus contains transcriptions of thirty-nine of the 188 speeches of the TED Corpus made at Eurospeech'93 in Berlin. The thirty-nine transcripts in this publication are in Universal Transcription Format (UTF) and were prepared by the LDC. All utf files in the transcript publication were validated against an included utf.dtd. Tables containing speaker demographic information and a cross-reference of file names from the TED audio corpus are included.

The TEDS (Transducer Electronic Data Sheet) Microphone market is experiencing robust growth, projected to reach a market size of $563 million in 2025. While the precise CAGR (Compound Annual Growth Rate) is not provided, considering the presence of numerous established players like HBK, RION, and HEAD acoustics alongside emerging Chinese companies like Beijing Shengwang Acoustic-Electric Technology and Zhongke Xinyue (Suzhou) Technology, a conservative estimate of a 7% CAGR from 2025 to 2033 seems plausible. This growth is driven by increasing demand for accurate and reliable acoustic measurements across diverse sectors. The automotive industry, particularly in the development of advanced driver-assistance systems (ADAS) and electric vehicles, is a significant driver. Similarly, the aerospace and defense industries rely heavily on precise acoustic monitoring for testing and quality control. Furthermore, the growing adoption of smart devices and the expansion of the Internet of Things (IoT) create significant opportunities for TEDS microphones in various applications requiring embedded sensor technology. Growth is also influenced by miniaturization trends and the increasing preference for integrated solutions that offer ease of use and data management. The market's segmentation is likely multifaceted, encompassing various microphone types (condenser, electret, etc.), frequency ranges, sensitivity levels, and application domains. The competitive landscape is characterized by a mix of international giants and regional players, suggesting potential for both consolidation and further diversification within the market. Despite this favorable outlook, challenges such as price sensitivity in certain segments and the potential for technological disruption from emerging sensor technologies could influence market growth. Continued innovation in areas such as improved signal-to-noise ratio, wider frequency response, and smaller form factors will be crucial for companies to maintain a competitive edge in this expanding market. We anticipate steady growth through 2033 fueled by ongoing technological advancements and increasing demand across key industries.

TED (diario electrónico de licitaciones) es la versión online del Suplemento del Diario Oficial de la UE (DO S) dedicado a la contratación pública europea.

En el TED encontrará información sobre contratos públicos basados en las normas de la UE sobre contratación pública y publicados en los Estados miembros de la UE, el Espacio Económico Europeo (EEE) y otros países.

Puede examinar, buscar y ordenar los anuncios por países, regiones, sectores de actividad, etc. Los usuarios registrados en la web de TED pueden descargar en masa paquetes XML en la página http://ted.europa.eu/TED/misc/xmlPackagesDownload.do.

Los paquetes XML son de dos tipos:

• ediciones diarias del suplemento del Diario Oficial y

• colecciones mensuales (a partir de enero de 2011).

Desde 1993, los paquetes también están disponibles vía FTP (ftp://ted.europa.eu) con credenciales genéricas (guest/guest). Los archivos y formatos dependen del periodo elegido.

Es posible acceder a un subconjunto de la base TED que incluye los principales epígrafes de los anuncios de licitación y adjudicación en formato CSV: https://data.europa.eu/euodp/en/data/dataset/ted-csv.

Data associated with the following publication: "A fully automated measurement system for the characterization of micro thermoelectric devices near room temperature" (DOI: 10.1016/j.applthermaleng.2023.120111).

Includes questions pertaining to: race & ethnicitygenderagetribal affiliationdisabilityincomelanguagelocationeducation