cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5683/sp3/wxcn3k
title: Replication data for: Growth and vegetable yield of Amaranthus hybridus L. as impacted by harvest methods in southern Ontario, Canada

description: The primary objective of this study was to evaluate which harvest techniques are the most effective at optimizing both yield and quality of A. hybridus in southern Ontario. These results may increase the potential to grow more vegetable amaranth in southern Ontario and may be used in further studies on this crop.
description: SAS, 9.4
DOI: 10.34808/psmz-wg86
title: Micro- and Nano- structure of biomass-based polyurethane-wood composites (PU-WC)

description: The following collection of research data contains data characterising the structure of PU-WC micro- and nano-composites. The tests were performed using scanning electron microscopy (SEM), atomic force microscopy (AFM) combined with QNM.
DOI: 10.5683/sp3/8hiu4q
title: Biogeographic barriers are differentially permeable based on traits: movement of hypoxia tolerant mormyrid fish in the Lake Victoria basin (Data and code for publication)

description: This dataset comprises the data and code for analysis for a publication submitted to the Journal of Great Lakes Research by McGill researchers in fall 2024. Below is the abstract of the publication at submission.

In the Lake Victoria Basin, Lake Nabugabo is a small satellite lake of Lake Victoria proper that is separated by deeply hypoxic swamps. These swamps form a biogeographic barrier to fish assemblages; Nabugabo hosts species not shared with Lake Victoria, and other species show high differentiation across the barrier. However, there are air-breathing fishes which show near zero genetic differentiation across this barrier. We used pooled RAD-seq to examine the degree of genetic differentiation in two species of non-air-breathing but hypoxia-tolerant mormyrid fishes, &lt;i&gt;Marcusenius victoriae&lt;/i&gt; and &lt;i&gt;Petrocephalus degeni&lt;/i&gt;. Since they are hypoxia-tolerant, we hypothesized that they would have low genetic differentiation across the barrier more in line with air-breathing fish rather than other species which are not air-breathing. We discovered that the genetic differentiation in our focal species was very low, with F&lt;sub&gt;ST&lt;/sub&gt; values of 0.02 to 0.04, as opposed to other non-air-breathing fishes in previous work that ranged from 0.05 to 0.20, mostly above 0.10. The values we found in our focal species were in fact much more comparable to obligately or facultatively air-breathing fishes that had F&lt;sub&gt;ST&lt;/sub&gt; values of near zero. We conclude that this barrier and other analogous ones should be understood as differentially permeable depending on the traits of the organisms crossing them, namely hypoxia tolerance in this case.
DOI: 10.5683/sp3/bfymhm
title: Replication Data for: Not all animal surrender is the same: Comparisons of sought support and ultimate outcomes in surrendering owners

description: Animal shelters aim to divert intake by encouraging pet retention in homes (e.g., support services) or through alternative methods of surrender (e.g., self-rehoming); however, it remains unclear what factors contribute to decisions to seek pet support services, as well as select different methods to surrender a pet. Using a sample of 452 U.S. and Canadian public members who rehomed a dog or cat within the past five years, the present study identified groups of pet owners who share similar patterns of responses to surrender circumstances using latent class analysis. The model revealed three heterogeneous classes of surrendering pet owners distinguished largely by the reason for surrender and the length of ownership. Comparisons revealed differences across classes regarding the proportion of respondents, the pathways used to surrender, and the concerns reported by respondents during surrender. Qualitative analysis revealed that respondents wanted or sought a variety of different support services, including behavioural support, part-time care, and veterinary care. Future research should consider the heterogeneity in surrender decision-making when addressing issues of intake diversion from animal shelters.
DOI: 10.5683/sp3/hikrsh
title: Tuition and Living Accommodation Costs for Full-time Students at Canadian Degree-granting Institutions, 2024-2025
title: TLAC 1993-2021; Frais de scolarité et de subsistance des étudiants à pleins temps dans les universités et collèges du Canada qui confèrent des grades, 2024-2025 [Excel]

description: The objective of this survey is to gather information on tuition fees, living accommodation costs at residences/housing and additional compulsory fees paid by full-time university students at Canadian universities. Data are collected annually by questionnaire through the Registrar or the Business Office of universities. Survey results are available at the end of August. Data for undergraduate programs are available by institution, by province, by program and by type of students (Canadian or Foreign). Data for graduate programs are available by institution, by province and by type of students (Canadian or Foreign). Additional compulsory fees are available by institution, by province and by type (athletics, health services, student association, and other). Living accommodation costs at residence/housing are available by institution, by type of students (single or married) and by type of costs (room, meal plan,or both). For current TLAC data refer to Statistics Canada
description: Migration from Nesstar
description: Notes: 2017-2018 (latest release);
DOI: 10.5683/sp3/nrepzm
title: The Arc Loss Dataset

description: The Arc Loss Dataset is a benchmark dataset designed for time series classification in industrial applications, particularly for fault detection and diagnosis (FDD). It was collected from a large-scale pyrometallurgical plant and captures the real-world complexities of industrial processes, including high dimensionality, sensor noise, and variable system dynamics. The dataset consists of 3,226 multivariate time series samples, each containing 1,101 time steps (equivalent to 55 minutes) with 96 process variables. The dataset is split into three subsets: I) train.pt (70% of the samples, 2,258 samples), II) val.pt (10%, 323 samples), and III) test.pt (20%, 645 samples). More information can be found in the README.txt
DOI: 10.5683/sp3/8fxngm
title: The CSTH Dataset

description: The CSTH Simulated Benchmark Dataset is designed for time series classification and fault detection and diagnosis (FDD). It is generated using the continuous stirred tank heater (CSTH) simulation model (https://zenodo.org/records/10093059). The model represents a heating system in which hot and cold water are mixed, heated by steam, and regulated through a closed-loop control system.

The dataset consists of 9,000 multivariate time series samples, each with 200 time steps and three process variables (cold water flow, tank level, and temperature). It includes both normal operating conditions (Y=0) and faulty scenarios (Y=1), where faults are introduced through instrumentation errors. The dataset is split into: i) train.pt (70%, 6,300 samples), ii) val.pt (10%, 900 samples), and iii) test.pt (20%, 1,800 samples). This dataset is processed and ready for machine learning applications.
DOI: 10.5683/sp3/med7ln
title: Replication Data for: "White matter microstructure among straight and gay cisgender men, sao praphet song, and straight cisgender women in Thailand"

description: Questionnaire data and mat files with DTI data
DOI: 10.6084/m9.figshare.30664231
title: Cross-population analyses between cashmere, angora and non-fibre-producing goats identified signatures of divergent selection

description: Angora and Cashmere goats differ in hair follicle biology and fibre traits. To explore the genetic basis of these differences, Whole Genome Sequencing (WGS) of Cashmere, Angora, and non-fibre goats were used to identify divergent selection signatures and allele frequency differences. Cross-population analyses found 5,252 variants differentially selected between Cashmere and non-fibre goats, 2,414 between Angora and non-fibre, and 326 between Cashmere and Angora. Three fibre-related genes, <i>COL14A1</i>, <i>FGF5</i>, and <i>CUX1</i>, showed divergence across all comparisons. Fisher’s exact test on coding variants with high or moderate predicted phenotypic impact identified 735 significant variants in skin-expressed genes showing differing allele frequencies between Cashmere and non-fibre goats, with fewer such variants found between the other groups. These variants likely influence fibre differences among populations. Though their exact effects are unclear, this study advances understanding of fibre goat genetics. Divergent selection analysis of Cashmere, Angora, and non-fibre-producing goats identified variants potentially linked to fibre production.The genes <i>COL14A1</i>, <i>FGF5</i>, and <i>CUX1</i> exhibited divergent selection across all three goat groups, highlighting their roles in fibre biology.Findings enhance understanding of genetic selection for fibre traits, influencing goat breeding strategies and the fibre industry. Divergent selection analysis of Cashmere, Angora, and non-fibre-producing goats identified variants potentially linked to fibre production. The genes <i>COL14A1</i>, <i>FGF5</i>, and <i>CUX1</i> exhibited divergent selection across all three goat groups, highlighting their roles in fibre biology. Findings enhance understanding of genetic selection for fibre traits, influencing goat breeding strategies and the fibre industry.
DOI: 10.5683/sp3/hinx0d
title: Advocate Beach field data

description: The files in this dataset relate to the paper "Submarine groundwater discharge at a mega-tidal beach" published in Hydrological Processes. See "Read me" file for more details.
DOI: 10.6084/m9.figshare.30664231.v1
title: Cross-population analyses between cashmere, angora and non-fibre-producing goats identified signatures of divergent selection

description: Angora and Cashmere goats differ in hair follicle biology and fibre traits. To explore the genetic basis of these differences, Whole Genome Sequencing (WGS) of Cashmere, Angora, and non-fibre goats were used to identify divergent selection signatures and allele frequency differences. Cross-population analyses found 5,252 variants differentially selected between Cashmere and non-fibre goats, 2,414 between Angora and non-fibre, and 326 between Cashmere and Angora. Three fibre-related genes, <i>COL14A1</i>, <i>FGF5</i>, and <i>CUX1</i>, showed divergence across all comparisons. Fisher’s exact test on coding variants with high or moderate predicted phenotypic impact identified 735 significant variants in skin-expressed genes showing differing allele frequencies between Cashmere and non-fibre goats, with fewer such variants found between the other groups. These variants likely influence fibre differences among populations. Though their exact effects are unclear, this study advances understanding of fibre goat genetics. Divergent selection analysis of Cashmere, Angora, and non-fibre-producing goats identified variants potentially linked to fibre production.The genes <i>COL14A1</i>, <i>FGF5</i>, and <i>CUX1</i> exhibited divergent selection across all three goat groups, highlighting their roles in fibre biology.Findings enhance understanding of genetic selection for fibre traits, influencing goat breeding strategies and the fibre industry. Divergent selection analysis of Cashmere, Angora, and non-fibre-producing goats identified variants potentially linked to fibre production. The genes <i>COL14A1</i>, <i>FGF5</i>, and <i>CUX1</i> exhibited divergent selection across all three goat groups, highlighting their roles in fibre biology. Findings enhance understanding of genetic selection for fibre traits, influencing goat breeding strategies and the fibre industry.
DOI: 10.5683/sp3/audttu
title: Postal Code Conversion File [Canada], August 2019, Census of Canada 2016
title: Postal Code Conversion File, August 2019
title: PCCF [Canada], August 2019
title: Fichier de conversion des codes postaux [Canada], août 2019

description: &lt;p&gt;The Postal Code Conversion File (PCCF) is a digital file which provides a correspondence between the Canada Post Corporation (CPC) six-character postal code and Statistics Canada's standard geographic areas for which census data and other statistics are produced. Through the link between postal codes and standard geographic areas, the PCCF permits the integration of data from various sources. The Single Link Indicator provides one best link for every postal code, as there are multiple records for many postal codes.&lt;/p&gt; 

&lt;p&gt;To obtain the postal code conversion file or for questions, consult the &lt;a href="https://www.statcan.gc.ca/eng/dli/contact" target="_blank"&gt; DLI contact&lt;/a&gt; at your educational institution.&lt;/p&gt; 

&lt;p&gt;The geographic coordinates attached to each postal code on the PCCF are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for planning, or research purposes.&lt;/p&gt; 

 &lt;p&gt;The geographic coordinates, which represent the standard geostatistical areas linked to each postal code&lt;sup&gt;OM&lt;/sup&gt; on the PCCF, are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for marketing, planning, or research purposes. In April 1983, the Statistical Registers and Geography Division released the first version of the PCCF, which linked postal codes&lt;sup&gt;OM&lt;/sup&gt; to 1981 Census geographic areas and included geographic coordinates. Since then, the file has been updated on a regular basis to reflect changes. For this release of the PCCF, the vast majority of the postal codes&lt;sup&gt;OM&lt;/sup&gt; are directly geocoded to 2016 Census geography while others are linked via various conversion processes. A quality indicator for the confidence of this linkage is available in the PCCF.&lt;p&gt;
description: Postal Code Conversion File
DOI: 10.5683/sp3/x2cmwf
title: Fichier de conversion des codes postaux [Canada], août 2019, Recensement de la population 2016
title: Fichier de conversion des codes postaux [Canada], août 2019
title: FCCP [Canada], août 2019
title: Postal Code Conversion File [Canada], August 2019

description: &lt;p&gt;Le Fichier de conversion des codes postaux (FCCP) est un fichier numérique qui permet d’établir un lien entre les codes postaux à six caractères fournit par la Société canadienne des postes (SCP) et les unités géographiques normalisées de Statistique Canada pour lesquelles les données du recensement et d’autres statistiques sont produites. Les liens entre les codes postaux et les unités géographiques normalisées font du FCCP un outil permettant d’intégrer des données de diverses sources. &lt;/p&gt; 

&lt;p&gt;Pour obtenir le fichier de conversion des codes postaux ou pour des questions, consultez &lt;a href="https://www.statcan.gc.ca/fra/idd/contact" target="_blank"&gt;la personne-ressource IDD&lt;/a&gt; de votre établissement d'enseignement. &lt;/p&gt; 

&lt;p&gt;Les coordonnées géographiques attribuées à chaque code postal dans le FCCP sont généralement utilisées pour cartographier la distribution des données aux fins d’analyse spatiale (p. ex., les clients, les activités). Les renseignements sur la localisation s’avèrent un outil puissant aux fins de planification ou de recherche.&lt;/p&gt; 

&lt;p&gt;C’est en avril 1983 que la Division de la géographie a diffusé une première version du FCCP qui établissait un lien entre les codes postaux et les unités géographiques du recensement et comprenait des coordonnées géographiques. Depuis, le fichier a été actualisé de façon périodique afin de refléter les changements.Pour la présente édition du FCCP, la majorité des codes postaux ont été directement géocodés aux régions géographiques du Recensement de 2016. Cette technique a permis d’améliorer la précision du fichier obtenu par comparaison avec le procedé de conversion, précedemment utilisé les codes postaux ont, pour la plupart, été géocodés à la géographie du Recensement de 2016. Par comparaison avec le procédé de conversion précédemment utilisé (pour aligner les appariements entre les codes postaux et les nouvelles régions géographiques à l'issue de chaque recensement) cette technique permet d'améliorer la précision du fichier obtenu. &lt;/p&gt;
description: Fichier de conversion des codes postaux
description: Notes: Codes postaux les plus récents correspondant à la géographie du Recensement de 2016, août 2019.;Notes: La date de référence géographique est la date fixée par Statistique Canada aux fins du parachèvement du cadre géographique dans lequel les données du recensement seront recueillies, totalisées et diffusées. Pour le Recensement de 2016, la date de référence géographique est le 1er janvier 2016.;Notes: Contient des enregistrements pour les codes postaux nationaux;
DOI: 10.5683/sp3/2tsjoq
title: Postal Code Conversion File [Canada], November 2019, Census of Canada 2016
title: Postal Code Conversion File, November 2019
title: PCCF [Canada], November 2019
title: Fichier de conversion des codes postaux [Canada], novembre 2019

description: &lt;p&gt;The Postal Code Conversion File (PCCF) is a digital file which provides a correspondence between the Canada Post Corporation (CPC) six-character postal code and Statistics Canada's standard geographic areas for which census data and other statistics are produced. Through the link between postal codes and standard geographic areas, the PCCF permits the integration of data from various sources. The Single Link Indicator provides one best link for every postal code, as there are multiple records for many postal codes.&lt;/p&gt; &lt;p&gt;To obtain the postal code conversion file or for questions, consult the &lt;a href="https://www.statcan.gc.ca/eng/dli/contact" target="_blank"&gt; DLI contact&lt;/a&gt; at your educational institution.&lt;/p&gt; &lt;p&gt;The geographic coordinates attached to each postal code on the PCCF are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for planning, or research purposes.&lt;/p&gt; &lt;p&gt;The geographic coordinates, which represent the standard geostatistical areas linked to each postal code&lt;sup&gt;OM&lt;/sup&gt; on the PCCF, are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for marketing, planning, or research purposes. In April 1983, the Statistical Registers and Geography Division released the first version of the PCCF, which linked postal codes&lt;sup&gt;OM&lt;/sup&gt; to 1981 Census geographic areas and included geographic coordinates. Since then, the file has been updated on a regular basis to reflect changes. For this release of the PCCF, the vast majority of the postal codes&lt;sup&gt;OM&lt;/sup&gt; are directly geocoded to 2016 Census geography while others are linked via various conversion processes. A quality indicator for the confidence of this linkage is available in the PCCF.&lt;p&gt;
description: Postal Code Conversion File
description: Notes: Most up-to-date postal codes corresponding to 2016 Census Geography, November 2019.;Notes: Contains records for National postal codes;
DOI: 10.5683/sp3/8vigza
title: Fichier de conversion des codes postaux [Canada], novembre 2019, Recensement de la population 2016
title: Fichier de conversion des codes postaux [Canada], novembre 2019
title: FCCP [Canada], novembre 2019
title: Postal Code Conversion File [Canada], November 2019

description: &lt;p&gt;Le Fichier de conversion des codes postaux (FCCP) est un fichier numérique qui permet d’établir un lien entre les codes postaux à six caractères fournit par la Société canadienne des postes (SCP) et les unités géographiques normalisées de Statistique Canada pour lesquelles les données du recensement et d’autres statistiques sont produites. Les liens entre les codes postaux et les unités géographiques normalisées font du FCCP un outil permettant d’intégrer des données de diverses sources. &lt;/p&gt; 

&lt;p&gt;Pour obtenir le fichier de conversion des codes postaux ou pour des questions, consultez &lt;a href="https://www.statcan.gc.ca/fra/idd/contact" target="_blank"&gt;la personne-ressource IDD&lt;/a&gt; de votre établissement d'enseignement. &lt;/p&gt; 

&lt;p&gt;Les coordonnées géographiques attribuées à chaque code postal dans le FCCP sont généralement utilisées pour cartographier la distribution des données aux fins d’analyse spatiale (p. ex., les clients, les activités). Les renseignements sur la localisation s’avèrent un outil puissant aux fins de planification ou de recherche.&lt;/p&gt; 

&lt;p&gt;C’est en avril 1983 que la Division de la géographie a diffusé une première version du FCCP qui établissait un lien entre les codes postaux et les unités géographiques du recensement et comprenait des coordonnées géographiques. Depuis, le fichier a été actualisé de façon périodique afin de refléter les changements.&lt;/p&gt;

&lt;p&gt;Pour la présente édition du FCCP, la majorité des codes postaux ont été directement géocodés aux régions géographiques du Recensement de 2016. Cette technique a permis d’améliorer la précision du fichier obtenu par comparaison avec le procedé de conversion, précedemment utilisé les codes postaux ont, pour la plupart, été géocodés à la géographie du Recensement de 2016. Par comparaison avec le procédé de conversion précédemment utilisé (pour aligner les appariements entre les codes postaux et les nouvelles régions géographiques à l'issue de chaque recensement) cette technique permet d'améliorer la précision du fichier obtenu. Un indice de qualité reflétant la fiabilité de l’appariement est disponible dans le FCCP. &lt;/p&gt;
description: Fichier de conversion des codes postaux
description: Notes: Codes postaux les plus récents correspondant à la géographie du Recensement de 2016, novembre 2019.;Notes: La date de référence géographique est la date fixée par Statistique Canada aux fins du parachèvement du cadre géographique dans lequel les données du recensement seront recueillies, totalisées et diffusées. Pour le Recensement de 2016, la date de référence géographique est le 1er janvier 2016.;Notes: Contient des enregistrements pour les codes postaux nationaux;