cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/xqfhhw
title: Ethnobotanical evaluation and agro-morphological of eleven priority plant species for food security in northwestern Benin, northwest Benin.

description: One of the scourges that Benin suffers from is food insecurity. Thus the role of local food diversity in improving this scourge becomes obvious. This study focused on the ethnobotanical aspect and agronomic characterization of eleven species considered a priority for ensuring food security in northwestern Benin. The overall goal was to assess the ethnobotanical knowledge and agro-morphological parameters of the priority species used to ensure food security for the local populations living in the communes of the Department of Atacora in Benin. Data were collected through a literature review, the application of four prioritization methods Point Scoring Procedure (PSP), Point Scoring Procedure with Weighting (PSPW), Compound Ranking System (BRS), Binomial Ranking System (CRS) for the identification of the eleven priority species, ethnobotanical surveys using semi-structured interviews with 240 informants, and measurements on morphological descriptors of leaves, leaflets, petioles. The results have allowed to identify 70 food species in the study area among which eleven (11) species were considered to be priorities: Adansonia digitata L., Moringa oleifera Lam., Parkia biglobosa R. Br. ex G. Don, Balanites aegytiaca L., Detarium microcarpum Guill. & Perr., Tamarindus indica L., Blighia sapida K.D.Koenig, Hibiscus sabdariffa L., Cleome gynandra L., Ocimum gratissimum L., Vigna radiata (L.) R.Wilczek.. The majority of these species (82 %) are used for at least two categories of use, including food and medicinal use, except for Cleome gynandra L. and Vigna radiata (L.) R.Wilczek., which are used only for food use by the population. The most used organs in order of importance for all species are fruit (Relative frequency of citation (FRC = 57 %), leaf (FRC = 55 %) and seed (FRC = 28 %). The study showed that gender, ethnic group, townships and species significantly influenced the reported food use value (P &lt; 0.05). On the other hand, the commune of Tanguieta, Toucountouna and species significantly influenced the medicinal use value (P &lt; 0.05). Finally, the agro-morphological characteristics varied according to the species and the townships.
description: CGIAR CRP Linkages: Agriculture for Nutrition and Health
DOI: 10.7910/dvn/cuwwyj
title: U.S. Street Network Shapefiles, Node/Edge Lists, and GraphML Files

description: Shapefiles, node/edge lists, and GraphML files of the street networks of every city/town, urbanized area, county, census tract, and Zillow neighborhood in the United States. Street networks include public drivable streets. Created from OpenStreetMap data using the &lt;a href="https://github.com/gboeing/osmnx"&gt;OSMnx&lt;/a&gt; software. Full methodological details in the related publications.
description: OSMnx, 0.8.1
description: Each state-level zip file contains the files (shapefiles, node/edge lists, or GraphML files) of the street networks in that state (at the scale of city/town, urbanized area, county, census tract, or Zillow-defined neighborhood). The files are named like FIPS_code-state_abbreviation-spatial_scale-street_networks-file_type.zip

You can use the search box to filter files for downloading if you only want a certain state or file type or spatial scale.

Urbanized area boundaries come from the 2017 TIGER/Line shapefile of U.S. census bureau urban areas. City and town boundaries come from the 2017 TIGER/Line shapefiles of U.S. census bureau places for all 50 states plus DC. County boundaries come from the 2017 TIGER/Line shapefile of U.S. counties. Census tract boundaries come from the 2017 TIGER/Line shapefiles of U.S. census bureau tracts. Neighborhood boundaries come from the 2017 Zillow neighborhood boundary shapefiles. Each street network was downloaded from OpenStreetMap using OSMnx v0.8.1 and its graph_from_polygon function, passing the parameters network_type="drive" (to download all public, drivable streets) and retain_all=True (to retain all connected components if the graph is disconnected due to discontiguous geography). The networks were then saved as shapefiles, node/edge lists (CSV format), and GraphML files. These GraphML files can be directly reloaded and analyzed with OSMnx.

<b>Citation info:</b>

Boeing, G. 2018. “A Multi-Scale Analysis of 27,000 Urban Street Networks: Every US City, Town, Urbanized Area, and Zillow Neighborhood.” Environment and Planning B: Urban Analytics and City Science. doi:10.1177/2399808318784595

Boeing, G. 2017. “OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks.” Computers, Environment and Urban Systems. 65, 126-139. doi:10.1016/j.compenvurbsys.2017.05.004
description: https://osmnx.readthedocs.io
DOI: 10.18739/a2n00zv77
title: Winter snow depth as a driver of microbial activity, nutrient cycling, tree growth and treeline advance in the Arctic

description: Overview:
 It has long been thought that temperature exerts a direct control on growth of treeline trees and the position of the treeline. However, our recent work in the Arctic with white spruce suggests that indirect effects of temperature on soil nutrient availability may be of equal or greater importance. We hypothesize that cold soils at the treeline, particularly during winter, limit microbial activity and nutrient availability to the point where trees are barely able to survive and grow. Measurements made during winter have revealed that Arctic forests maintain snowpacks that are much deeper than observed at treeline. Trees are thought to trap snow and lead to a deeper snowpack, insulating the soil from cold air and allowing for greater overwinter microbial activity and greater nutrient mineralization. Indeed, we found a strong positive correlation between white spruce growth and winter snow depth. We propose to isolate the mechanisms underlying this correlation by using snowfences to manipulate winter snow depth and fertilizer to increase soil nutrient availability at three treelines that differ in soil moisture. To provide an experimental test of the importance of temperature as a direct control on treeline tree growth, we propose to incorporate experimental shoot warming into our snowfence experiment in a factorial design. We predict that both experimental snow and nutrient additions will lead to large increases in microbial activity, photosynthesis, tree growth, seed quality, seed production, seedling establishment and recruitment of new trees. We expect to observe the greatest positive responses where soils are wet and cold. Meanwhile, we predict that shoot warming will lead to negligible changes in growth. This research will elucidate the relationship between snow depth and soil nutrient availability, and determine the relative importance of nutrient and temperature limitations at treeline to white spruce – a dominant member of the boreal forest and the northernmost tree species in North America.
 Intellectual Merit:
 The position of the Arctic treeline is an important regulator of surface energy budgets, carbon cycling and subsistence resources in high latitude environments. Our recent research provides correlative evidence of the importance of winter snow depth as a driver of tree growth. Here, we propose to experimentally isolate the importance of snow depth and soil nutrient availability and examine the consequences for microbial processes and tree performance. This is a novel proposal, as we aim to link microbial ecology with large-scale landscape patterns of relevance to regional and global climates. If our hypotheses are confirmed, our findings will contradict the prevailing theory of treeline causation, alter our predictions of where and when treelines may advance and necessitate revision of the many paleoclimate reconstructions based upon correlations between temperature and tree growth near the Arctic treeline.
DOI: 10.5281/zenodo.15282659
title: SNR-Efficient Whole-Brain Pseudo-Continuous Arterial Spin Labeling Perfusion Imaging at 7 Tesla

description: # Readme


This repository contains the MATLAB code and simulation data that was used in the paper titled "SNR-Efficient Whole-Brain Pseudo-Continuous Arterial Spin Labeling Perfusion Imaging at 7 Tesla" by Joseph G. Woods, Yang Ji, Hongwei Li, Aaron T. Hess, and Thomas W. Okell and published in Magnetic Resonance in Medicine in 2025.


The code and data can be used to recreate the following simulation figures:

* Figure 3

* Figure 7

* Figure S1

* Figure S2

* Figure S3

* Figure S5

* Figure S8


Privacy policies currently prevent us from freely sharing the in vivo data.


## How to


* First run the setup.m to add the relevant folders to the MATLAB path.


* The code used to optimize the PCASL parameters for max SNR and max labeling efficiency is in __Analyse_PCASL_optimization_data.m__.

* This loads in the pre-generated data from the .mat file PCASLLE_PCASLtypebalanced_RFtypeHann_bVERSE1_RFdutycycle0.5_Gmax_staticLD1800ms_df50Hz.mat which was simulated using the bash script in runOptimisation_group.sh using a high performance cluster.


* The code used to optimize the background suppression pulse waveforms is in __BGS_optimization.m__.


* The code to generate the individual figures from the manuscript can be found in the folder "Code_for_figures"


## Citations


If you use any of this code or data in your own work, please cite the above paper and this repository.


## Notes


Activating MATLAB's parpool will greatly reduce the run time of some of the scripts because parfor loops are used.


This code has only been tested in the Native Apple silicon version of MATLAB 2024a on a Apple MacBook Pro with an M1 chip.
DOI: 10.5281/zenodo.15282660
title: SNR-Efficient Whole-Brain Pseudo-Continuous Arterial Spin Labeling Perfusion Imaging at 7 Tesla

description: # Readme


This repository contains the MATLAB code and simulation data that was used in the paper titled "SNR-Efficient Whole-Brain Pseudo-Continuous Arterial Spin Labeling Perfusion Imaging at 7 Tesla" by Joseph G. Woods, Yang Ji, Hongwei Li, Aaron T. Hess, and Thomas W. Okell and published in Magnetic Resonance in Medicine in 2025.


The code and data can be used to recreate the following simulation figures:

* Figure 3

* Figure 7

* Figure S1

* Figure S2

* Figure S3

* Figure S5

* Figure S8


Privacy policies currently prevent us from freely sharing the in vivo data.


## How to


* First run the setup.m to add the relevant folders to the MATLAB path.


* The code used to optimize the PCASL parameters for max SNR and max labeling efficiency is in __Analyse_PCASL_optimization_data.m__.

* This loads in the pre-generated data from the .mat file PCASLLE_PCASLtypebalanced_RFtypeHann_bVERSE1_RFdutycycle0.5_Gmax_staticLD1800ms_df50Hz.mat which was simulated using the bash script in runOptimisation_group.sh using a high performance cluster.


* The code used to optimize the background suppression pulse waveforms is in __BGS_optimization.m__.


* The code to generate the individual figures from the manuscript can be found in the folder "Code_for_figures"


## Citations


If you use any of this code or data in your own work, please cite the above paper and this repository.


## Notes


Activating MATLAB's parpool will greatly reduce the run time of some of the scripts because parfor loops are used.


This code has only been tested in the Native Apple silicon version of MATLAB 2024a on a Apple MacBook Pro with an M1 chip.
DOI: 10.5281/zenodo.15557945
title: Processed Silent EMG-features
title: Can LLMs Understand Unvoiced Speech? Exploring EMG-to-Text Conversion with LLMs

description: This repository provides the hand-crafted feature representations used in our paper, "Can LLMs Understand Unvoiced Speech? Exploring EMG-to-Text Conversion with LLMs", ACL, 2025. These features are derived from the silent-EMG dataset originally introduced in "Digital Voicing of Silent Speech" (EMNLP 2020, arXiv:2010.02960). The raw dataset can be accessed via Zenodo. For more details on feature extraction and experimental setup, please refer to our paper.
DOI: 10.5281/zenodo.15557946
title: Processed Silent EMG-features
title: Can LLMs Understand Unvoiced Speech? Exploring EMG-to-Text Conversion with LLMs

description: This repository provides the hand-crafted feature representations used in our paper, "Can LLMs Understand Unvoiced Speech? Exploring EMG-to-Text Conversion with LLMs", ACL, 2025. These features are derived from the silent-EMG dataset originally introduced in "Digital Voicing of Silent Speech" (EMNLP 2020, arXiv:2010.02960). The raw dataset can be accessed via Zenodo. For more details on feature extraction and experimental setup, please refer to our paper.
DOI: 10.17028/rd.lboro.11931669.v1
title: Low Temperature Spin Seebeck Effect (T SSE) rig

description: Dataset accompanying development of low T SSE (Temperature Spin Seebeck Effect) measurement.<br>Figures.opju contains analysed data used to create figures.Low T SSE.zip contains raw data obtained during measurement.
DOI: 10.17632/bn2pskgxp3
title: Data for: Evaluation of the Effectiveness of a Multi-Sectional Façade with Venetian Blinds and Roller Shades with Automated Shading Control Strategies

description: Weather data in Taipei and New York City in .epw format and some .xml material files of complex fenestration systems.
DOI: 10.17632/h9vdjh8tk7
title: Data for measuring e-learning systems success during the COVID-19 pandemic: Case of the Higher Education Institutions in Morocco

description: E-learning systems success data.
DOI: 10.17632/snsk3xvjb2
title: Jordanian children with Cerebral Palsy (CP) - Compiled dataset

description: The compiled dataset has 305 records (CP cases) and 316 attributes (features). the dictionary file contains a description for each value and the datatype.

This dataset originated from a CP follow-up registry program for children with CP in Jordan (CPUP-Jordan) developed in 2015.  The CP cases were assessed by trained research assistants (assessors). The data is stored and manipulated on a web server. An excel sheet was exported on February 2020. The original dataset went through different stages of cleansing to provide this compiled dataset.
DOI: 10.17632/wjvn8j82kr
title: DATA SET ON HUMAN DEVELOPMENT INDEX FOR INFORMAL SETTLEMENT IN ENUGU CITY , NIGERIA

description: The methodology of HDI was employed in calculating the human development index of residents of informal settlements in the city of Enugu. Using the geometric mean of the 3 study variables, the inclusive input factor for the determination of the Human Development Index is given by the following equation
HDI = 3√W I * E D I* S D I
Where; WI: Wealth Index
EDI: Quality Housing/ Environment Index
SDI: Social protection Index
DOI: 10.17632/wykjhv8ks6
title: Aksara Bali for RCNN / YOLO

description: The provided is dataset containing aksara bali for the usage of machine learning. Be it classification or just image recognition
DOI: 10.6084/m9.figshare.14935458.v2
title: Th17 cell plasticity towards a T-bet-dependent Th1 phenotype is required for bacterial control in Staphylococcus aureus infection

description: Manuscript:Th17 cell plasticity towards a T-bet-dependent Th1 phenotype is required for bacterial control in <i>Staphylococcus aureus</i> infection<br>Bartsch et al. 2022<b><br></b>Mouse: C57BL/6 IL17A<sup>Cre</sup>xRosa26<sup>eYFP</sup>Organ: Kidney<br>Cells: FACS-sorted CD45<sup>+</sup>CD3<sup>+</sup>CD4<sup>+</sup>eYFP<sup>+</sup>Single Cell Dataset<br>Cellranger Pipeline (version 3.1.0) Output:1. <i>matrix.mtx.gz:</i> Count Matrix in Matrix Market format with columns as cells and rows as genes2. <i>barcodes.tsv.gz:</i> Barcodes File in tab-separated values file format, corresponds to the column-names of 1.3. <i>features.tsv.gz</i>: Feature File in tab-separated values file format, corresponds to the row-names of 1.4. <i>web_summary.html</i>: html-file, statistics and metadata from the cellranger pipeline run<br><br><br>
DOI: 10.6084/m9.figshare.25342699.v1
title: The Impact of Exposure to AI Chatbots on Students' Entrepreneurial Intentions--Based on TPB and TAM（Data 450）.xlsx

description: In November 2023, this study used judgement sampling and convenience sampling by sending the QR code of the questionnaire to 2,766 target respondents with the assistance of engineering student work supervisors at Zhanjiang University of Science and Technology. All respondents who were willing to answer the questionnaire and were eligible were likely to be selected as a sample. After eliminating invalid questionnaires, 450 valid questionnaires were retained.
DOI: 10.6084/m9.figshare.4602016.v2
title: EXCEED - The Extreme Climate Event Database

description: Extreme Climate Event Database is a picture database intended to induce emotionally salient stimuli reactions in the context of natural hazards associated with global climate change and related extreme events.<br>The creation of the database was motivated by the need to better understand the impact that the increase in natural disasters worldwide has on human emotional reactions.<br>This new database consists of 150 pictures divided into three categories: two negative categories that depict images of floods and droughts, and a neutral category composed of inanimate objects.<br>Each image receives an abbreviation identification letter for the category that it belongs to, followed by a crescent number within the group, the respective attribution credit and creative common (CC) license. <br>The letter N represents neutral pictures (range: N01 to N50), FL designates the flood group (range FL01 to FL50), and DR designates drought pictures (range DR01 to DR50). <br>All pictures are in JPEG format; however, the resolution and dimensions could vary between pictures.<br><br>All EXCEED images are under Creative Common (CC) license, and each image is under specific license according to restrictions of modifications and use in commercial settings.<br><br>When using any image from EXCEED, one must be careful to individual license for each picture as well for the credits for the owner and EXCEED.<br>Access &lt; https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0204093 &gt; to read about the development and validation of EXCEED.<br>
DOI: 10.17632/49v62g8whd
title: Cat owner perceptions on having a cat during the COVID-19 pandemic

description: This data includes international responses to an online survey among cat owners. The aim of the study was to investigate how the COVID-19 pandemic affected the health and behaviour of pet cats. The data was collected between May and July 2020. For more information, or to use the data, please contact the authors.
DOI: 10.17632/4k7b395yxx
title: Frying oil data

description: Three csv data files on the chemical parameters of acid value, carbonyl value and total polar compounds which are produced in the potato chips frying process at the temperature of 160,175, 190, 205, and 220°C from the time of 0th hour to 30th hour.
DOI: 10.17632/n56pn9fncw
title: Malabar Spinach dataset for diseases classification using deep learning approach

description: (1) Malabar Spinach disease is a widespread problem affecting the productivity and quality of agricultural production. It has a detrimental impact on the quality of Malabar Spinach crops. Malabar Spinach is a leafy green vegetable frequently grown for its nutritional value and taste. However, under certain non-biological circumstances, diseases can severely harm the yield and quality of Malabar Spinach, resulting in significant economic losses for farmers. Traditional methods of diagnosing these diseases are often time-consuming, labor-intensive, ineffective, and subjective. (2) In recent years, computer vision approaches have shown great promise in addressing the challenges of disease classification and detection in Malabar Spinach crops. (3) To develop machine vision-based algorithms for detecting Malabar Spinach diseases, a comprehensive dataset has been curated. This dataset comprises images representing various Malabar Spinach diseases, including Anthracnose_leaf_spot, Straw_mite, and Healthy Malabar Spinach. The classification of Malabar Spinach diseases was accomplished with the collaboration of experts from agricultural research institutes. (4) A total of 603 images of Malabar Spinach plants were collected from real fields. Additionally, to expand the dataset, 5868 augmented images were generated from the original ones using techniques such as flipping, shearing, zooming, and rotation. This augmentation is crucial for enhancing the accuracy and robustness of the machine vision algorithms for detecting and classifying Malabar Spinach diseases.
DOI: 10.5281/zenodo.15567724
title: Neuroergonomic Evaluation of Risk-Warning eHMI Penetration Rates in Vehicle Platoons: Effects on Pedestrians' Mental Workload, Situation Awareness, and Gap Acceptance
DOI: 10.5281/zenodo.15567725
title: Neuroergonomic Evaluation of Risk-Warning eHMI Penetration Rates in Vehicle Platoons: Effects on Pedestrians' Mental Workload, Situation Awareness, and Gap Acceptance
DOI: 10.6084/m9.figshare.11954511.v1
title: Different responses of tropical cyclone tracks over the western North Pacific and North Atlantic to two distinct SST warming patterns

description: How future tropical cyclone (TC) activity could change under global warming (GW) is enormously important to society, which has been widely assessed using state-of-the-art climate models. However, these models were predominantly based on projection of an El Niño-like warming pattern. Recent studies suggested that a La Niña-like warming pattern is also possible. Here, we compare the responses of TC track density (TCTD) over the western North Pacific (WNP) and North Atlantic (NA) to the two distinct GW patterns. We find that the La Niña-like warming pattern reduces WNP TCTD except in the South China Sea and along China coast and increases NA TCTD, while the El Niño-like warming pattern generally reduces TCTD in both basins. This is due to different responses of large-scale dynamic/thermodynamic conditions to the distinct zonal sea surface temperature gradients associated with the two warming patterns. These results help better understand potential future change in TC tracks.
DOI: 10.6084/m9.figshare.29002502.v1
title: 1.6. Z Pearson's Correlation Pre-test (Underlying Data) - Doomscrolling and Information Overload on Generation Z: Examining the Link Between Excessive Digital Media Consumption and Stress Level

description: Pre-test analysis Z variable (stress level) results using IBM SPSS Statistics 26 for research title "Doomscrolling and Information Overload on Generation Z: Examining the Link Between Excessive Digital Media Consumption and Stress Level".