cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/fb8b57xz6w
title: Supplementary materials for "Genomic prediction and validation strategies for reproductive traits in Holstein cattle across different Chinese regions and climatic conditions"

description: Figure S1. Daily average temperature humidity index (THI) across the whole year for the Beijing (BJ) and Ningxia (NX) regions.

Figure S2. The number of records in each temperature humidity index (THI) level for interval from first to last insemination (IFL), conception rate at first insemination (CR_f), and number of inseminations (NS).

Figure S3. Genetic correlations estimated by reaction norm models (RNMs) with ssGBLUP for interval from first to last insemination (IFL), conception rate at first insemination (CR_f), and number of inseminations (NS). The color indicates the magnitude of the genetic correlation. The x-axis and y-axis are the average THI, ranging from 35 to 80.

Figure S4. Trends of phenotypes change along different temperature humidity index (THI) level for interval from first to last insemination (IFL), conception rate at first insemination (CR_f), and number of inseminations (NS).
DOI: 10.17632/jhdv4drxbx
title: Development and performance of a HemeLB GPU code for human-scale blood flow simulation

description: In recent years, it has become increasingly common for high performance computers (HPC) to possess some level of heterogeneous architecture - typically in the form of GPU accelerators. In some machines these are isolated within a dedicated partition, whilst in others they are integral to all compute nodes - often with multiple GPUs per node - and provide the majority of a machine's compute performance. In light of this trend, it is becoming essential that codes deployed on HPC are updated to execute on accelerator hardware. In this paper we introduce a GPU implementation of the 3D blood flow simulation code HemeLB that has been developed using CUDA C++. We demonstrate how taking advantage of NVIDIA GPU hardware can achieve significant performance improvements compared to the equivalent CPU only code on which it has been built whilst retaining the excellent strong scaling characteristics that have been repeatedly demonstrated by the CPU version. With HPC positioned on the brink of the exascale era, we use HemeLB as a motivation to provide a discussion on some of the challenges that many users will face when deploying their own applications on upcoming exascale machines.
DOI: 10.17632/jvgdrmjvs3
title: RT Spoofing Attacks on MIL-STD-1553 Communication Traffic

description: Please refer to the associated Data In Brief article: "Datasets of RT Spoofing Attacks on MIL-STD-1553 Communication Traffic", R. Yahalom et al. (2019) for the full details of the data synthesis process, the motivation for our preprocessing into sequences, and the format of the CSV files.
DOI: 10.6084/m9.figshare.25274011.v1
title: Research Data.xlsx

description: There are three sets of data in the dataset, which are the data of niche online community, mainstream online community and pre-test.In the demographic data, the "frequency" represents "how often do you use that niche online community?",uses seven-level likert scale, from completely disagree to completely agree, and other items like gender, age and other serial numbers can be seen in Table I.In the data,"UI" represents user interaction,"SA" represents customer satisfaction, "PO" represents psychological ownership,"WOM" represents word of mouth, and "KS" represents knowledge sharing, and the specific items can be seen in Table II.
DOI: 10.6084/m9.figshare.7304075.v4
title: Transgenerational effects of ungulates and pre-dispersal seed predators on offspring success and resistance to herbivory

description: Plant and within-plant effects of ungulates and pre-dispersal seed predators on Moricandia moricandioides seed quality and seedling emergence, perfomance and resistance.<br>Dataset corresponding to the following article:<br>"Transgenerational effects of ungulates and<br>pre-dispersal seed predators on offspring<br>success and resistance to herbivory"<br>PLoS ONE 13(12):e0207553.<br><br>https://doi.org/10.1371/journal.pone.0207553<br>
DOI: 10.17632/cjjcd8743c
title: Data for: High-quality, high-throughput cryo-electron microscopy data collection via beam tilt and astigmatism-free beam-image shift

description: Script 1. Automatic coma determination program. Data was collected using the apo-ferritin sample with a continuous carbon-film grid at -2um defocus value. It is necessary to eliminate the original astigmatism and coma in manual before measurement to get original beam tilt angles (ori_X and ori_Y). Script 2. Coma search of beam-image shift. Run script 2 and record changes of astigmatism and coma in different α and d. The changes of astigmatism obtain from the Stigmator window of serialEM and coma obtain via automatic coma determination program. Fit all the parameters to get the fitting curves and formulas which are applied to the beam-image shift data collection. Script 3. 6×6 data collection via beam-image shift. In theory, only to know α0 and r (Figure 3), we can calculate all the parameters needed for data collection. But there is a slight difference between the actual and theoretical values due to the error in grid production or other objective factors.
DOI: 10.17632/pg9z22d9pz
title: Combining transmission speckle photography and convolutional neural network for determination of fat content in cow milk: an exercise in classification of parameters of a complex suspension

description: This is a sample of the whole data used in the study "Combining transmission speckle photography and convolutional neural network for determination of fat content in cow milk - an exercise in classification of parameters of a complex suspension". Commercial milk samples of different fat content classes were purchased from supermarkets (where fresh milk was re-frigerated but ultra-pasteurized (UHT) milk was left on the open shelf). The samples were mainly from 3 dairy plants. We label the samples as Dairy 1 to Dairy 5 and a Collection of Dairies (CoD, see Table 1 in the paper). Dairies 4 and 5 were added to supplement the lack of 1.5% class in Dairies 1 and 2. The undiluted milk sample (10 μL) was loaded into a flat thin cuvette and covered with a 0.19 mm-thick coverslip. The cuvette was prepared by sticking a 50 μm-thick adhesive tape on a microscope slide and cutting out a 10 mm circular segment from the center of the tape. The sample in the cuvette was illuminated perpendicularly with a 5 mW, 1.7 mm collimated beam from a green frequency-doubled Nd:YAG laser at 532 nm. A 14-bit colour camera (Pike F-032C, AVT) was used to record laser speckle videos at 26.9o angle and 85 mm distance from the sample and at a constant temperature of 21±1oC. Two experimental runs were performed for each 1L-container of milk opened. In the first experimental run, the milk was loaded into the cuvette and 10 movies were recorded at 10 different locations on the sample (different background/static speckle) and labelled as “Version 1”. After recording 10 movies for Version 1 the cuvette was cleaned. It involved gently dipping it in a diluted cleaning solution, sonication for a minute and rinsing off with distilled water. Finally it was dried clean by blowing dry nitrogen gas (99.8%) over it. It was then loaded again with milk to record the movies for Version 2. At a single illumination point, ~1000 frames (13 s @ 75 fps) movie was recorded, the 10-locations on the same sample was exhaustive. Using milk form Dairy 1 only we experimented on 3 exposure time Protocols and confirmed our finding with milk from Dairies 2 and 3. The speckle images were extracted and normalized to grayscale level (0 - 1). Convolutional Neural Network (CNN) was trained on the version 1 of the data and tested on test set from version 1 and independent set (version 2). The study revealed that when "fully-developed laser speckles" are recorded from changing concentration and different particle sizes of suspensions CNN can be used to classify them unambiguously. In the folders there are sample images, videos, trained convolutional neural networks and classification algorithm
DOI: 10.6084/m9.figshare.28529024.v1
title: Breaking the linear-scaling limit in multi-electron-transfer electrocatalysis through intermediate spillover

description: Raw Data
DOI: 10.6084/m9.figshare.4224210.v1
title: Multiple Locus Genome-wide Association Studies for Important Economic Traits of Oil Palm

description: These are the raw data analyzed in the paper entitled “Multiple Locus Genome-wide Association Studies for Important Economic Traits of Oil Palm”. The file has two sheets. The first sheet stores the genotype data consisted of 1081 SNPs from the 422 oil palms. The second sheet named “phenotype” is the field data of 13 traits.
DOI: 10.17632/2vhvsh7wxj
title: Effect of home based exercise program in women with pregnancy induced hypertension

description: To assess the efficiency of a home fitness programme for pregnant women who have hypertension.On the basis of selection criteria, 29 pregnant women over the age of 18 who also had pregnancy-related hypertension were recruited. Following the evaluation of the baseline outcome measurements (SBP & DBP), the home-based exercise programme, which consists of buteyko breathing, Ujjayi Pranayama, aerobic activities, and upper- and lower-extremity stretching, was described to and shown to all participants. Up to the birth, a follow-up was conducted once a month, at which time blood pressure was tested and documented. Two research participants withdrew midway through, thus the data from 27 individuals were taken into account for data analysis. Systolic blood pressure (SBP) decreases by a median of 10 millimetres per hour (mmHg) and diastolic blood pressure (DBP) decreases by a median of 8 millimetres per hour (mmHg), which is a highly significant reduction (p=0.000) in both systolic and diastolic blood pressure. 
To control pregnancy-induced hypertension, a home exercise programme that combines buteyko breathing, Ujjayi Pranayama, cardiovascular activities, and stretching of the upper and lower extremities is helpful.
DOI: 10.17632/67f2sxfwxn
title: Systems biology approaches identify metabolic signatures of dietary lifespan and healthspan across species

description: Raw data and code for the paper "Systems biology approaches identify metabolic signatures of dietary lifespan and healthspan across species" from the Buck Institute published in Nature Communications (https://www.nature.com/articles/s41467-024-52909-y).
DOI: 10.17632/j5rffs3hy8
title: BioAuxdataset: a dataset of ground-dwelling nocturnal fauna for object detection and classification

description: The study of nocturnal fauna living in the soil is a challenging research task due to its multiple implications in different fields such as pesticide use control, crop yield prediction or plant disease identification. 
BioAuxdataset is the synthesis of hundreds of gigabytes of images taken in the field of insects and plant auxiliaries over several years. 
7 common species of ground-dwelling nocturnal fauna are represented: ground beetles, mice, opilion, slugs, shrews, small slugs and worms.
BioAuxdataset consists of a directory of 7470 jpg images and their corresponding 7470 xml annotation files. 
BioAuxdatset is available in the rar compressed format and its images are separated into two different directories: non-augmented images and augmented images.
The objectives of the dataset range from monitoring the number of organisms and their characteristics (size, development stage) to early detection of plant diseases for more environmentally-friendly precision agriculture.
DOI: 10.17632/zjfbbztc6b
title: Villach Dobratsch February 2019

description: PV output power distribution; comparison between Villach (low altitude) and Dobratsch (high altitude); February 2019; Columns: hour, minute, second, azimuth, elevation, power The setup and experiment description for this dataset is documented in the paper Jelenko Karpic, Ekanki Sharma, Tamer Khatib, and Wilfried Elmenreich. Comparison of solar power measurements in alpine areas using a mobile dual-axis tracking system. Proceedings of the 8th DACH+ Conference on Energy Informatics, Salzburg, Austria, September 2019. The paper will be published in September 2019. Please contact us per email for a pre-print of the paper, we are happy to discuss and share our results. Link to publication: https://resource-cms.springernature.com/springer-cms/rest/v1/content/17197556/data/v1
DOI: 10.6084/m9.figshare.21550545.v3
title: Dataset of wild bees and their forage resources along livestock grazing gradient of northern Tanzania

description: A dataset describing the occurrence of wild bees along livestock grazing gradient is critical for the conservation and management of wild bees and their associated forage resources in the changing world. Despite this need, the dataset to understand the occurrence of different species of wild bees across varying levels of livestock grazing is scarce in East Africa, and northern Tanzania is no exception. Therefore, here we present a dataset of wild bees across sites with different levels of livestock grazing intensity (low, medium & high livestock grazing intensity). The dataset will therefore serve as the baseline data necessary for understanding the diversity and distribution of wild bees and their associated forage resources in the northern parts of the country, which is a critical step in devising robust conservation and monitoring strategies for their populations.
DOI: 10.6084/m9.figshare.3983856.v2
title: A spiking neuron model of adaptive arm control - Supplementary material - data package 4

description: Analysis data required for generating correlations-CB/neural_activity 66-100 using the scripts provided at https://github.com/studywolf/REACH-paper/tree/master/analysis
DOI: 10.6084/m9.figshare.8123567.v1
title: House 13 in ENERTALK dataset

description: Zip files enertalk-dataset-{house_number} contain a directory for each houses. Each directory holds a set of subdirectories that contain Parquet files for the daily aggregate and appliance-level data. The naming convention for these subdirectories is “” (e.g. “20161124” for November 24, 2016). The Parquet files are named “\_.parquet.gzip” (e.g. “01\_fridge.parquet.gzip”). In these names, the two-digit integer is uniquely associated with a distinct measuring device in a house. Each Parquet file consists of three columns: “timestamp,” “active\_power,” and “reactive\_power.” The “timestamp” column contains Unix timestamps in milliseconds, such that 1000 corresponds to one second. The “active\_power” column represents active power in watts and the “reactive\_power” column represents reactive power in VAR (volt-ampere reactive) units.
DOI: 10.6084/m9.figshare.20090183.v1
title: Determinants of using the WHO Surgical Safety Checklist..xlsx

description: Data was collected from a descriptive cross sectional study at a tertiary facility in Ghana which sort to assess utilization and determinants of utilization of the WHO Surgical Safety Checklist among surgical personnel.
DOI: 10.6084/m9.figshare.28806113.v1
title: Almeidaetal.revised.xlsx

description: This study examines whether rock cavies (Kerodon rupestris), which are social rodents, modulate their alarm calls in response to various threat contexts. Conducted across four sample areas within two study sites in the Brazilian Caatinga region, alarm calls were collected using the ad libitum method. The acoustic responses of free-ranging rock cavies were then analyzed using discriminant function analysis, principal component analysis, and generalized mixed linear models to classify vocal types and assess differences in vocalization rates and acoustic parameters. The findings reveal that rock cavies produce both slow and fast alarm whistles in response to threats. Fast alarm whistles, emitted exclusively in response to nearby ocelots (Leopardus pardalis), exhibited a lower pitch (F1, 26.81=22.15, P&lt;0.001), shorter duration (F1, 28.66=30.08, P&lt;0.001), and shorter pulse intervals (F1, 29.30=9.95, P=0.004) compared to the slow alarm whistles. Slow alarm whistles were produced when rock cavies were threatened by distant ocelots, as well as by both distant and closer humans, dogs (Canis familiaris), marmosets (Callithrix spp.), tayras (Eira barbara), and birds of prey (Caracara plancus). The type of threat influenced the number of pulses (F6, 20.76=3.60, P=0.013) and pulse intervals (F6, 12.20=11.57, P&lt;0.001) of slow alarm whistles. Rock cavies produced more pulses when threatened by dogs and birds of prey compared to humans (P&lt;0.05) and shorter pulse intervals when threatened by ocelots compared to humans and dogs (P&lt;0.05). Additionally, lower-pitched slow alarm whistles (F1, 19.84=7.46, P=0.013) with shorter pulse intervals (F1, 21.02=17.04, P&lt;0.001) were emitted when threats were nearby compared to more distant threats. This study highlights the influence of various threats and their proximity on the modulation of rock cavy alarm calls, showcasing their behavioral adaptability. This crucial survival strategy not only enhances our understanding of rock cavies’ behavior but also has the potential to inspire research in other species and ecological contexts.
DOI: 10.6084/m9.figshare.28943819.v1
title: IEEE PHM 2012 data.zip

description: IEEE PHM 2012 dataset
DOI: 10.17632/tj7mgd6m3m
title: Neuropsychology of language: Normative data for Verbal Repetition, Comprehension, Verbal Fluency & BNT indexes

description: This dataset is a collaborative work for the subject "Neuropsychology of Language" taught at the Universidad Autónoma de Madrid, Spain (2024/2025 academic year). The aim is to determine the influence of age, years of education, and gender on four classic language assessment tasks: verbal repetition (subtest from the Test Barcelona Revisado; TBR), comprehension (subtest from the TBR), verbal fluency (COWAT and Isaacs Set-Test) and Boston Naming Test. Also, from the sample data, normative data in young and middle-aged adults can be obtained. For the application of the tests, the conventional instructions were followed, which can be consulted, for example, in Strauss et al. (2006).
In addition to the sociodemographic variables above-mentioned, the following cognitive parameters are also included in the dataset:
-Score for each item from the verbal repetition task
-Total score for the verbal repetition task (range 0-60; a higher score means better performance)
-Score for each item from the comprehension task
-Total score for the comprehension task (range 0-16; a higher score means better performance)
-Number of items correctly evoked in period 1-15" for each phonetic and semantic category
-Number of items correctly evoked in the period 16-30" for each phonetic and semantic category
-Number of items correctly evoked in the period 31-45" for each phonetic and semantic category
-Number of items correctly evoked in the period 45-60" for each phonetic and semantic category
-Number of items correctly evoked in the period 45-60" for each phonetic and semantic category
-Total number of items correctly evoked 1-60" (sum of the above) for each phonetic and semantic category.
-Total number of errors for each phonetic and semantic category 
-Total number of perseverations for each phonetic and semantic category
-Total number of spontaneous hits in the BNT
-Total number of hits after semantic clue in the BNT
-Total number of hits after phonological clue in the BNT
-Total number of hits after semantic clue in the BNT (sum of spontaneous hits + hits after semantic clue)

*All authors contributed equally in this work
DOI: 10.17632/ymgs23x3j8
title: Compressive Strength Prediction of Nano-Modified Concrete.

description: Original database presents the datasets compiled from multiple literature sources, comprising a total of 94 data points.Figure 5 presents the correlation coefficients among the nine variables, clearly indicating the specific instances of positive or negative correlation between each pair of variables as well as the varying intensities of their relationships. Figure 6 displays the model performance evaluation metrics for each fold in the 10-fold cross-validation of the four models. Figure 7 provides numerical values for five evaluation indicators based on the prediction results of the four machine learning models on the test set. Figure 8 demonstrates the determination coefficients of each model by comparing the outcomes of the respective algorithms' computer code runs with the actual values. Figure 9 presents the specific predicted values, allowing for an assessment of whether the models tend to underestimate or overestimate the actual values through a comparison of the differences between them.
DOI: 10.6084/m9.figshare.22117559.v3
title: EUSEDcollab.v1

description: The EUropean SEDiments collaboration (EUSEDcollab) database contains a compilation of data contributions from monitored catchments from across multiple European institutions. The focus of the database is small to medium catchments containing water discharge and sediment delivery time series measurements for soil erosion, sediment delivery and runoff studies. These measurements from various institutions provide insights into the processes governing soil erosion and sediment delivery across a spectrum of spatial and temporal scales. The data is aimed at multiple end-user applications, such as providing baseline information for further analytical studies and model application/development, allowing comparison with real measurements of process rates. As a user-orientated EUSO initiative, the contributed data is harmonised with a common metadata and time series structure to allow efficient reuse. This database aims to provide the research community with a starting point for new research opportunities in a range of sediment-related research avenues. Description: EUSEDcollab is available as a single repository containing multiple sub-folders with catchment data: 1) METADATA: A series of files (.csv format) containing the completed metadata inputs for each catchment. 2) Q_SSL: A time series (.csv format) containing time series of water discharge, suspended sediment concentration and total suspended sediment load. 3) Q_SSL_QUALITY_CONTROL: (.json format) containing evaluations of the time series completeness with specific evaluations for the different dataset temporal structures. A description of each data quality check is given in (Data_quality_check_fields.xlsx). 4) PRECIPITATION: Precipitation time series data from catchments with available measurements. 5) SED_RATING_CURVES: Original sediment rating curve data from catchments with available data. 6) ADDITIONAL_FILES: Other auxiliary information for each catchment e.g. readme files with additional information, catchment boundary polygons, land-use information, additional reports. 7) EUSEDcollab_submission_templates: The template files to make a submission to the EUSEDcollab database. See the ESDAC page for details (https://esdac.jrc.ec.europa.eu/content/EUSEDcollab). <br> 2 additional files containing database compilations can also be found in the parent directory: 1) 'ALL_METADATA.csv' - a compilation of all metadata inputs. 2) 'all_timeseries.pickle' - a pickle file containing a dictionary of dataframes for all catchments. This allows the database to be read as one single file and accessed based on the catchment ID number. <br> The accompanying code can be found at: https://github.com/matfran/EUSEDcollab.git <br>
DOI: 10.6084/m9.figshare.29163251.v1
title: Appendix: Statements and factor arrays

description: This appendix includes factor array data used in the study titled "Teachers’ Enactment of ICT Affordances in Secondary Level Rural English Classrooms: A Q Methodological Study"