The PATH Study was launched in 2011 to inform the Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study sampled over 150,000 mailing addresses across the United States to create a national sample of people who use or do not use tobacco. 45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent. At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled Primary Sampling Unit (PSU)s and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the civilian, noninstitutionalized population at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort. At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This "second replenishment sample" was combined for estimation and analysis purposes with the Wave 7 adult and youth respondents from the Wave 4 Cohorts who were at least age 15 and in the civilian, noninstitutionalized population at the time of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort. Please refer to the Restricted-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts. Dataset 0002 (DS0002) contains the data from the State Design Data. This file contains 7 variables and 82,139 cases. The state identifier in the State Design file reflects the participant's state of residence at the time of selection and recruitment for the PATH Study. Dataset 1011 (DS1011) contains the data from the Wave 1 Adult Questionnaire. This data file contains 2,021 variables and 32,320 cases. Each of the cases represents a single, completed interview. Dataset 1012 (DS1012) contains the data from the Wave 1 Youth and Parent Questionnaire. This file contains 1,431 variables and 13,651 cases. Dataset 1411 (DS1411) contains the Wave 1 State Identifier data for Adults and has 5 variables and 32,320 cases. Dataset 1412 (DS1412) contains the Wave 1 State Identifier data for Youth (and Parents) and has 5 variables and 13,651 cases. The same 5 variables are in each State Identifier dataset, including PERSONID for linking the State Identifier to the questionnaire and biomarker data and 3 variables designating the state (state Federal Information Processing System (FIPS), state abbreviation, and full name of the state). The State Identifier values in these datasets represent participants' state of residence at the time of Wave 1, which is also their state of residence at the time of recruitment. Dataset 1611 (DS1611) contains the Tobacco Universal Product Code (UPC) data from Wave 1. This data file contains 32 variables and 8,601 cases. This file contains UPC values on the packages of tobacco products used or in the possession of adult respondents at the time of Wave 1. The UPC values can be used to identify and validate the specific products used by respon

The Population Assessment of Tobacco and Health (PATH) Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study was launched in 2011 to inform the FDA's tobacco regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). For Wave 1 (baseline), the PATH Study sampled over 150,000 mailing addresses across the United States to create a national sample of people who use or do not use tobacco, yielding interviews with 45,971 adult and youth respondents. 45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent.At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled PSUs and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the civilian, noninstitutionalized population at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort.At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This second replenishment sample was combined for estimation and analysis purposes with Wave 7 adult and youth respondents from the Wave 4 Cohort who were at least age 15 and in the civilian, noninstitutionalized population at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort Please refer to the Restricted-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts.Biospecimen Collection Each adult respondent, who completed the interview at Wave 1, was asked to provide at least two biospecimens. Providing biospecimens was voluntary and was not a condition of participation. Respondents were asked to report their use of all nicotine-containing products during the 3-day period prior to the time of any biospecimen collection (Nicotine Exposure Questions (NEQs)) to facilitate interpretation of biomarker results. Of the 32,320 respondents who completed the adult interview at Wave 1, 21,801 (67.4 percent) provided a urine specimen and 14,520 (44.9 percent) provided a blood specimen. For the purposes of subsampling adults into the Wave 1 Biomarker Core, adult participants were grouped by tobacco product use at Wave 1 into nine mutually exclusive groups.A sample of 11,522 adults who provided sufficient urine for the planned analyses were selected from the first six tobacco product use groups see section 3.1 of the Biomarker Restricted-Use Files User Guide representing people who never used tobacco, currently use tobacco, and formerly used tobacco (within the last 12 months). This group constitutes the original Wave 1 Biomarker Core. Of the 11,522 adults, 7,159 also provided a blood specimen. All urine and blood specimens provided by the Wave 1 Biomarker Core were sent for laboratory analysis.Subsequent to this selection, an additional stratified probability sample of adults who completed the Wave 1 adult interview and provided a sufficient amount of urine for the planned analyses at Wave 1 (independent of whether th

The NIST Electron Inelastic-Mean-Free-Path Database provides values of electron inelastic mean free paths (IMFPs) principally for use in surface analysis by Auger-electron spectroscopy and X-ray photoelectron spectroscopy. The database includes IMFPs calculated from experimental optical data and IMFPs measured by elastic-peak electron spectroscopy. If no calculated or measured IMFPs are available for a material of interest, values can be estimated from the predictive IMFP formulae of Tanuma et al. and of Gries. IMFPs are available for electron energies between 50 eV and 10,000 eV although most of the available data are for energies less than 2,000 eV. A critical review of calculated and measured IMFPs has been published [C. J. Powell and A. Jablonski, J. Phys. Chem. Ref. Data 28, 19 (1999)].

This data has been collected as part of a larger project by the City of Austin's Watershed Protection and Development Review Department to inventory its drainage infrastructure and create a GIS to store this information. The project includes an internal team developing a GIS based on record documents and an external team locating ground level appurtenances using GPS field collection units. The data in this data set represents the former.

The pathway representation consists of segments and intersection elements. A segment is a linear graphic element that represents a continuous physical travel path terminated by path end (dead end) or physical intersection with other travel paths. Segments have one street name, one address range and one set of segment characteristics. A segment may have none or multiple alias street names. Segment types included are Freeways, Highways, Streets, Alleys (named only), Railroads, Walkways, and Bike lanes. SNDSEG_PV is a linear feature class representing the SND Segment Feature, with attributes for Street name, Address Range, Alias Street name and segment Characteristics objects. Part of the Address Range and all of Street name objects are logically shared with the Discrete Address Point-Master Address File layer. Appropriate uses include: Cartography - Used to depict the City's transportation network _location and connections, typically on smaller scaled maps or images where a single line representation is appropriate. Used to depict specific classifications of roadway use, also typically at smaller scales. Used to label transportation network feature names typically on larger scaled maps. Used to label address ranges with associated transportation network features typically on larger scaled maps. Geocode reference - Used as a source for derived reference data for address validation and theoretical address _location Address Range data repository - This data store is the City's address range repository defining address ranges in association with transportation network features. Polygon boundary reference - Used to define various area boundaries is other feature classes where coincident with the transportation network. Does not contain polygon features. Address based extracts - Used to create flat-file extracts typically indexed by address with reference to business data typically associated with transportation network features. Thematic linear _location reference - By providing unique, stable identifiers for each linear feature, thematic data is associated to specific transportation network features via these identifiers. Thematic intersection _location reference - By providing unique, stable identifiers for each intersection feature, thematic data is associated to specific transportation network features via these identifiers. Network route tracing - Used as source for derived reference data used to determine point to point travel paths or determine optimal stop allocation along a travel path. Topological connections with segments - Used to provide a specific definition of _location for each transportation network feature. Also provides a specific definition of connection between each transportation network feature. (defines where the streets are and the relationship between them ie. 4th Ave is west of 5th Ave and 4th Ave does intersect with Cherry St) Event _location reference - Used as source for derived reference data used to locate event and linear referencing.Data source is TRANSPO.SNDSEG_PV. Updated weekly.

Contains id of participant (CTRL + num, ASD + num), time, behavior and patch where it happened.

The Population Assessment of Tobacco and Health (PATH) Study began originally surveying 45,971 adult and youth respondents. The PATH Study was launched in 2011 to inform Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study sampled over 150,000 mailing addresses across the United States to create a national sample of people who use or do not use tobacco. 45,971 adults and youth constitute the first (baseline) wave of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent. At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled Primary Sampling Unit (PSU)s and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the civilian, noninstitutionalized population at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort.Dataset 0001 (DS0001) contains the data from the Master Linkage file. This file contains 14 variables and 67,276 cases. The file provides a master list of every person's unique identification number and what type of respondent they were for each wave. At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This second replenishment sample was combined for estimation and analysis purposes with Wave 7 adult and youth respondents from the Wave 4 Cohort who were at least age 15 and in the civilian, noninstitutionalized population at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort. Please refer to the Public-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts.Dataset 1001 (DS1001) contains the data from the Wave 1 Adult Questionnaire. This data file contains 1,732 variables and 32,320 cases. Each of the cases represents a single, completed interview. Dataset 1002 (DS1002) contains the data from the Youth and Parent Questionnaire. This file contains 1,228 variables and 13,651 cases.Dataset 2001 (DS2001) contains the data from the Wave 2 Adult Questionnaire. This data file contains 2,197 variables and 28,362 cases. Of these cases, 26,447 also completed a Wave 1 Adult Questionnaire. The other 1,915 cases are "aged-up adults" having previously completed a Wave 1 Youth Questionnaire. Dataset 2002 (DS2002) contains the data from the Wave 2 Youth and Parent Questionnaire. This data file contains 1,389 variables and 12,172 cases. Of these cases, 10,081 also completed a Wave 1 Youth Questionnaire. The other 2,091 cases are "aged-up youth" having previously been sampled as "shadow youth." Dataset 3001 (DS3001) contains the data from the Wave 3 Adult Questionnaire. This data file contains 2,139 variables and 28,148 cases. Of these cases, 26,241 are continuing adults having completed a prior Adult Questionnaire. The other 1,907 cases are "aged-up adults" having previously completed a Youth Questionnaire. Dataset 3002 (DS3002) contains the data from t

The entity relatedness problem refers to the question of computing the relationship paths that better describe the connectivity between a given entity pair. This dataset supports the evaluation of approaches that address the entity relatedness problem. It covers two familiar domains, music and movies, and uses data available in IMDb and last.fm, which are popular reference datasets in these domains. The dataset contains 20 entity pairs from each of these domains and, for each entity pair, a ranked list with 50 relationship paths. It also contains entity ratings and property relevance scores for the entities and properties used in the paths.The data is compressed in .zip format and can be uncompressed by standard compression utilities. The data are split into three archives:EntityRelatednessTestData to RDF.zip: contains raw (.txt) and rdf test data along with test scripts (.java) and java class (.class) files. ontology.zip: contains the .rdf ontology for the entity relatedness test datasetdataset.zip: contains the entity relatedness test dataset in .rdf, .ttl and .nt formatsThe underlying data and code can be accessed through standard text edit software.

This dataset provides information about the number of properties, residents, and average property values for Pleasant Path cross streets in Ellicott City, MD.

The PATH Study was launched in 2011 to inform the Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study sampled over 150,000 mailing addresses across the United States to create a national sample of tobacco users and non-users. 45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent. At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled primary sampling units (PSU)s and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the civilian, noninstitutionalized population at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort. Please refer to the Restricted-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1 and Wave 4 Cohorts. Wave 4.5 was a special data collection for youth only who were aged 12 to 17 at the time of the Wave 4.5 interview. Wave 4.5 was the fourth annual follow-up wave for those who were members of the Wave 1 Cohort. For those who were sampled at Wave 4, Wave 4.5 was the first annual follow-up wave. Wave 5.5, conducted in 2020, was a special data collection for Wave 4 Cohort youth and young adults ages 13 to 19 at the time of the Wave 5.5 interview. Also in 2020, a subsample of Wave 4 Cohort adults ages 20 and older were interviewed via the PATH Study Adult Telephone Survey (PATH-ATS). Dataset 1002 (DS1002) contains the data from the Wave 4.5 Youth and Parent Questionnaire. This file contains 1,617 variables and 13,131 cases. Of these cases, 11,378 are continuing youth having completed a prior Youth Interview. The other 1,753 cases are "aged-up youth" having previously been sampled as "shadow youth" Datasets 1112, 1212, and 1222, (DS1112, DS1212, and DS1222) are data files comprising the weight variables for Wave 4.5. The "all-waves" weight file contains weights for participants in the Wave 1 Cohort who completed a Wave 4.5 Youth Interview and completed interviews (if old enough to do so) or verified their information with the study (if not old enough to be interviewed) in Waves 1, 2, 3, and 4. There are two separate files with "single wave" weights: one for the Wave 1 Cohort and one for the Wave 4 Cohort. The "single-wave" weight file for the Wave 1 Cohort contains weights for youth who completed an interview in Wave 1 and in Wave 4.5, regardless of their participation in the intervening waves. The "single-wave" weight file for the Wave 4 Cohort contains weights for all Wave 4.5 Youth Interview respondents in the Wave 4 Cohort. Dataset 1402 (DS1402) contains the Wave 4.5 State Identifier data for Youth and Parents and has 5 variables and 13,131 cases. The State Identifier dataset includes PERSONID for linking the State Identifier to the questionnaire data and 3 variables designating the state (state Federal Information Processing System (FIPS), state abbreviation, and full name of the state). The State Identifier values in this dataset represent participants' state of residence at the time of Wave 4.5. Dataset 1503 (DS1503) contains data derived from responses to questionnaires in Wave 1, Wave 2, Wave 3, Wave 4, and Wave 4.5 indicating if participants had ever/never used various tobacc

Path Station Locations

The Critical Path for Alzheimer's Disease (CPAD: http://c-path.org/programs/cpad/) CODR data base contains patient-level control arm data (6,500 patients; 24 clinical trials; MCI and AD), fully anonymized and remapped using CDISC SDTM v3.1.2 Standard. The database includes, but is not limited to, demographic information, APOE4 genotype, concomitant medications and cognitive scales (MMSE, ADAS-Cog, CDR-SB). Currently no AD fluid biomarker or imaging data are included.

According to INSPIRE transformed “Cross Path” development plan of the city of Calw based on an XPlanung dataset in version 5.0.

This dataset provides information about the number of properties, residents, and average property values for Fox Path cross streets in Pembroke, MA.

A repository of de-identified control arm data of patients from clinical studies of Alzheimer's disease and Mild Cognitive Impairment. It provides the ability to analyze the data online with the R statistical analysis program, create and download standard reports, run complex queries, or download data to a desktop for further analysis. Additional data will be added to the database over time. Critical Path Institute consortia members and qualified researchers may upload and work on scientific data relevant to biomarkers of drug toxicity, neurodegenerative diseases, and patient-reported outcomes.

This dataset provides information about the number of properties, residents, and average property values for Abigails Path cross streets in East Hampton, NY.

Made available for NPDC GeoHUB (GIS Hub Site and Open Data Portal) : A full description is available in the Metadata. See Terms of Use. Notes:The "Updated" date, noted here in the item, does not accurately reflect the currency of the data within the Feature Layer. The data available for download on NPDC GeoHUB is updated daily, this results in differences between what is available online and NPDC's databases.

Purpose: The dataset is the one used the manuscript "An open source GIS-based decision support system for forest accessibility mapping" (Journal of Maps, T&F) refers to. Specific content: Vector and raster input dataset include administrative boundaries, land uses, forest types, road network, forest management plan and morphological data computed using a digital elevation model, necessary to run the GIS-based DSS model SOFIA described in the manuscript. The dataset including filename, description and data source is detailed in the Readme.txt file.

This repository contains the source code, simulation data, and analysis from the study by Lazzeri, Jung, Bolhuis, and Covino (paper submitted in 2023). The code, adaptable for any two-state molecular dynamics system, is paired with annotations to promote understanding. The dataset allows full replication of the paper's results and figures.

We designed a 12.2 km walking transect so that an observer would pass within 50m of all habitat in the estuary and also minimize fording large channels. This transect was drawn using the path tool in Google Earth on a satellite image of the survey area. The path was printed on top of paper maps and used by observers as a map in the field. Most often, the entire transect was walked by two observers, one starting in the far West, the other in the middle of the estuary. Observers were permitted to deviate from the map to get clear views of certain features like incised channels or to identify a particular bird. The transect spacing worked for most birds, but was too sparse to accurately count Belding’s Savannah Sparrows. In general, the transect was walked from west to east, though there was no fixed direction and observers could choose a direction based on convenience and the angle of the sun.