cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25387/g3.26530861.v1
title: Supplemental Material for Grabowski et al., 2024

description: Files to accompany the analysis of the <em>Arachis hypogaea</em> Line8 v1 genome assembly.
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File S1.txt: The percentages of sequence for each annotation within 5Mb windows across the Line8 genome assembly. 
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File S2.txt: Positions of syntentic regions and and inversions between Line8 homeologs.
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File S3.txt: Percent sequence identity, in 100kb windows, for alignments of <em>A.duranensis</em> and <em>A.ipaensis</em> to the full Line8 assembly without Arahy.09_alt.
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File S4.txt:  Percent sequence identity, in 100kb windows, for alignments of <em>A.duranensis</em> and <em>A.ipaensis</em> to Line8 subgenomes A and B separately.
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File S5.vcf.gz:  VCF containing the SNPs for Line8 when mapped to the Tifrunner assembly, including predicted effects of SNPs
DOI: 10.6084/m9.figshare.25037543.v1
title: Genome and annotation of <i>Gleditsia sinensis</i>

description: We use PacBio HiFi and Hi-C data to assemble a chromosome-level genome for <i>Gleditsia sinensis</i>
DOI: 10.6084/m9.figshare.19653123.v2
title: Supplementary Fig. S1-S8, Tables S1-S7 and GTF files_Goldfarb et al_Endocrinology (2022)_Interplay between sex-biased GH-regulated mouse liver transcriptome and hepatic zonation revealed by single nucleus RNAseq

description: Supplementary Figs. S1-S8, Tables S1-S7, and GTF files from a study entitled: Interplay between sex-biased GH-regulated mouse liver transcriptome and hepatic zonation revealed by single nucleus RNAseq [Goldfarb et al, Endocrinology (2022)] <br> Abstract: The zonation of liver metabolic processes is well-characterized; however, little is known about the cell type-specificity and zonation of sexually dimorphic gene expression or its GH-dependent transcriptional regulators. We address these issues using single nucleus RNA-sequencing of 32,000 nuclei representing nine major liver cell types. Nuclei were extracted from livers from adult male and female mice, from males infused with GH continuously, mimicking the female plasma GH pattern, and from mice exposed to TCPOBOP, a xenobiotic agonist ligand of the nuclear receptor CAR that perturbs sex-biased gene expression. Analysis of these rich transcriptomic datasets revealed: 1) expression of sex-biased genes and their GH-dependent transcriptional regulators is primarily restricted to hepatocytes and is not a feature of liver non-parenchymal cells; 2) many sex-biased transcripts show sex-dependent zonation within the liver lobule; 3) gene expression is substantially feminized in both periportal and pericentral hepatocytes when male mice are infused with GH continuously; 4) sequencing nuclei increases the sensitivity for detecting thousands of nuclear-enriched lncRNAs and enables determination of their liver cell type-specificity, sex-bias and hepatocyte zonation profiles; 5) the periportal to pericentral hepatocyte cell ratio is significantly higher in male than female liver; and 6) TCPOBOP exposure disrupts both sex-specific gene expression and hepatocyte zonation within the liver lobule. These findings highlight the complex interconnections between hepatic sexual dimorphism and zonation at the single cell level and reveal how endogenous hormones and foreign chemical exposure can alter these interactions across the liver lobule with large effects on both protein-coding genes and lncRNAs.
DOI: 10.17632/54x3p4c32k
title: Association between biologic and nonbiologic systemic therapy for psoriasis and psoriatic arthritis and the risk of new-onset and recurrent major adverse cardiovascular events: A retrospective cohort study

description: Supplemental materials of the article, "Association between biologic and nonbiologic systemic therapy for psoriasis and psoriatic arthritis and the risk of new-onset and recurrent major adverse cardiovascular events: A retrospective cohort study".

1. Supplementary figure 1. A) Time to MACE for TNF-α inhibitors, nonbiologic systemic, and phototherapy in population without a history of MACE.
2. Supplementary figure 1. B) Time to MACE for Non-TNF-α biologics, nonbiologic systemic, and phototherapy in population without a history of MACE.
3. Supplementary figure 2. A) Time to MACE for TNF-α inhibitors, nonbiologic systemic, and phototherapy in population with a history of MACE.
4. Supplementary figure 2. B) Time to MACE for Non-TNF-α biologics, nonbiologic systemic, and phototherapy in population with a history of MACE. 
5. Supplementary figure 3. Risk of MACE with biologic versus nonbiologic systemic therapy according to history of MACE.
6. Supplementary Table I. Demographic and clinical characteristics of patients based on history of MACE.
7. Supplementary Table II. Risk of MACE with biologics (TNF-α inhibitor, non-TNF-α biologics), nonbiologic systemic therapy, and phototherapy according to MACE history in psoriasis and psoriatic arthritis.
DOI: 10.17632/h392z42k87
title: Identification and characterization of an endogenous biomarker of the renal vectorial transport (OCT2‐MATE1)

description: Original data-E1: metabolomics; E2: differentially Metabolites; E3: uptake of metabolites in control/OCT2-overexpressing cells; E4: uptake of metabolites in control/MATE1-overexpressing cells; E5: validation of potential biomarkers in vitro; E6: validation of potential biomarkers in vivo; E7: Specificity evaluation; E8: Affinity evaluation; E9: Application of biomarker
Original data-2 protein expression and transport function of OCT2 and MATE1
DOI: 10.17632/x6y6f9mmht
title: Brick Masonry Crack Dataset Collected from Battledore of Darbhanga Fort (A Cultural Heritage) for Automatic Crack Detection

description: It contains a dataset of superficial cracks present in the battledore of the Darbhanga Fort, Darbhanga, Bihar, which is a cultural heritage structure made up of red brick masonry. It has a total of 4259 images, including 203 background images (images that don't have cracks), which are present in the train image folder. It has three folders: train (having 3407 images, including 203 background images), val (having 639 images), and test (having 213 images). Both the training and validation datasets also have their corresponding labels. This dataset can be used for training deep learning (DL) models.
DOI: 10.6084/m9.figshare.5280988.v1
title: TREDPARSE supporting data: Simulated BAMs for series of Short Tandem Repeats

description: The simulation was performed using EAGLE. We simulated with 2x150bp reads with paired-end distance of 500bp (with standard deviation of 50bp), at varying level of sequencing depth (5x, 20x and 80x). The reads were then mapped to hg38 using BWA. The STR locus of interest is Huntington's Disease (HD), at location chr4:3074877-3074933.<br>Also included is the benchmark results of TREDPARSE and lobSTR on simulated haploid and diploid with one single allele with <i>h</i> number of CAGs, where <i>h</i> varies between 1 to 300 CAGs.<br>
DOI: 10.6084/m9.figshare.9980630.v1
title: RuBisCO tree (including Form I')

description: Fasta file and maximum likelihood tree of trimmed, aligned RuBisCo sequences (including Form I'). Sequences are taken from metagenomic assemblies and are representative across all Forms of RuBisCO.
DOI: 10.17632/9kjr9kj84d
title: Content  Analysis of Twitter Data related to Trust and Covid-19

description: This is a public repository of the ongoing research work on ‘Content  Analysis of Twitter Data related to Trust and Covid-19’ . For accessing the live streams of tweets , for downloading the existing tweets (hydration) based on the filters and for dehydrating the tweeter data twac tool, twitter api , tweepy libraries were utilized. The python code consists of two notebooks for the said purposes. it includes Master Data (Tweeter Data ) notebook having data cleaning function.The cleaning of the tweeter data include removal of emojis, unwanted characters and symbols , image links and other unwanted objects.
DOI: 10.17632/pxg7d955yk
title: COMPARATIVE EFFECT OF DRY NEEDLING AND NEURAL MOBILISATION ON PAIN, STRENGTH AND QUALITY OF LIFE IN PATIENTS WITH LATERAL EPICONDYLITIS: TWO GROUP PRETEST POSTEST DESIGN

description: Background: - Lateral Epicondylitis is the most prevalent condition of the elbow which causes pain over the lateral aspect of the elbow and weakness in grip strength. This study is planned to investigate between Dry Needling and Neural Mobilization technique and its effectiveness in the management of lateral epicondylitis. Purpose: - The purpose of this study was aimed to evaluate the effectiveness of the comparative effect of Dry Needling and Neural Mobilization in order to treat lateral epicondylitis. Material and methods: - Participants with lateral epicondylitis within age group between 35-54 years having Cozen test and ULTT2b positive will be included in the study .Participants were recruited by purposive sampling method and were allotted into Group 1 and Group2 randomly. Group1 received Dry Needling with Conventional therapy and Group2 received Neural Mobilization with Conventional therapy . The intervention was given on alternate days for a period of 2 weeks. Pre and post treatment outcome were assessed with PRTEE Questionnaire, Algometer, Hand held Dynamometer and Goniometer. Results: - Data analysis was done by Wilcoxon signed rank test /paired t-test for within group and Mann Whitney U-test/independent t-test for between groups. The significance level will be set at 0.05. All outcome measures showed highly significant results post 2-week intervention. Conclusion: Both the groups received the treatment hence both interventions provided positive effects to the participants with lateral epicondylitis. However, adding Dry Needling treatment technique to the previous conventional therapy further provided an improvement to the pain, grip strength, range of motion, and quality of life of the participants.
DOI: 10.17632/xkcm46vxjz
title: Housing consumption data

description: # This is the procedure to follow to reproduce all tables and graphs pertaining to the article: 
# Housing rare disaster events and asset prices by Messaoud CHIBANE and Patrice PONCET
# The scripts are Matlab script and can be run independently as follows or for more efficiency it can be run through a single 
# script called "script_and_graph_script_matlab.m"
# All produced Tables and Figures are put in the sub directory "Findings"

Here we assume that non housing and housing consumption are driven by rare disaster events overlaying Gaussian dynamics and that the representative agent aggregates the two goods in a CES utility. Combined with recursive utility we use the model to estimate the relative risk aversion and intratemporal and intertemporal elasticity of substitution, calibrated to the equity premium, the risk-free rate and the term structure of equity premia and interest rates. Consumption data are extracted from the Bureau of Economic Analysis and financial data are coming from Kenneth French Wed site
DOI: 10.17632/9766x3dcsf
title: Systematic Review of Intralesional Therapies for Cutaneous Warts

description: This dataset includes the data table created by this systematic review and the search strategy to find the appropriate articles to review.
DOI: 10.6084/m9.figshare.25472341.v1
title: Model Checkpoints

description: The checkpoints of generation model and similarity model.
DOI: 10.17632/47ydz8v6nd
title: Dataset of a composite drought index based on remote sensing data for Niger

description: The present dataset was created for agricultural drought characterization in the Sahelian climate zone of Niger. The dataset comprises the seasonal time series of a composite drought index (CDI) and the corresponding drought classes at a spatial resolution of 1 km2 for the period 2000-2020. The CDI was computed from remotely sensed data, namely precipitation of the CHIRPS (Climate Hazards Group InfraRed Precipitation with Stations), normalized difference vegetation index (NDVI) and land surface temperature (LST) data from MODIS (Moderate Resolution Imaging Spectroradiometer).

The files in the present dataset are:
- A netcdf file containing drought intensities and drought classes
- A netcdf of the accumulated seasonal CHIRPS rainfall data
- A netcdf file of the mean seasonal NDVI data
- A netcdf file of the mean day time LST data
- A shapefile of the map of Niger
- A jpeg file describing the study area
- Three png file of the figure used in the data in brief article
DOI: 10.17632/ts2t5t4tp3
title: Excessive Polyamine Generation in Keratinocytes Promotes Self-RNA Sensing by Dendritic Cells in Psoriasis

description: Uncropped versions of western blots; All peptides ≤ 3 kD identified in immunoprecipitates pulled from human plasmas by a Spermidine/Spermine antibody ; All peptides ≤ 3 kD identified in mouse sera.
DOI: 10.6084/m9.figshare.25277314.v1
title: SymPrompt Focal Method Benchmark for Unit Test Generation

description: Benchmark focal methods for our paper <i>Code-Aware Prompting: A Study of Coverage-Guided Test Generation in Regression Setting using LLM</i>, to appear in FSE 2024. In this paper, we present SymPrompt, a code-aware prompting strategy for LLMs in test generation. SymPrompts's approach is based on recent work that demonstrates LLMs can solve more complex logical problems when prompted to reason about the problem in a multi-step fashion. We apply this methodology to test generation by deconstructing the testsuite generation process into a multi-stage sequence, each of which is driven by a specific prompt aligned with the execution paths of the method under test, and exposing relevant type and dependency focal context to the model. Our approach enables pretrained LLMs to generate more complete test cases without any additional training. We implement \approach using the TreeSitter parsing framework and evaluate on a benchmark challenging methods from open source Python projects. SymPrompt enhances correct test generations by a factor of 5 and bolsters relative coverage by 26% for CodeGen2. Notably, when applied to GPT-4, SymPrompt improves coverage by over 2x compared to baseline prompting strategies.
DOI: 10.6084/m9.figshare.29063147.v2
title: Dataset on the Comparative Effects of Concept Mapping and Student-Team Achievement Division on Secondary School Students' Achievement in Photosynthesis.xlsx

description: This study examined the effects of Concept Mapping (CM) and the Student-Team Achievement Division (STAD) on students<b>'</b> achievement in Photosynthesis among secondary school students in Nyamagabe and Gicumbi districts, Rwanda. A quasi-experimental pre-and post-test non-equivalent control group research design was used in the study. Data were obtained from 70 students who were taught using CM, 66 who were taught using STAD, and 65 who taught using the Conventional Teaching methods (CTM ). The Photosynthesis Achievement Test (PAT), which served as pre-and post-test, was the instrument used to gather the data before and after interventions in the study groups
DOI: 10.17632/dh4hh4p3vx
title: Upadacitinib for Refractory Alopecia Areata Unresponsive to Prior Systemic Therapies: A Retrospective Study

description: Supplementary Materials of Upadacitinib for Refractory Alopecia Areata Unresponsive to Prior Systemic Therapies: A Retrospective Study
DOI: 10.17632/f236r4xpp7
title: Data for: Environmental magnetic evidence for enhanced aridification in the Tarim Basin since ~5.3 Ma, NW China

description: The data used in this study
DOI: 10.17632/p36gs28ys5
title: Research data and model codes for healthcare resilience improvement using collaborative care in response to disasters

description: These files are research data and model codes used in the article titled healthcare resilience improvement using collaborative care in response to disasters.
DOI: 10.6084/m9.figshare.25046987.v1
title: Code and data

description: Decision-making requires processing of sensory information, comparing the gathered evidence to make a judgement, and performing the action to communicate it. How neuronal representations transform during this cascade of representations remains a matter of debate. Here, we studied the succession of neuronal representations in the primate prefrontal cortex. We trained monkeys to judge whether a pair of sequentially presented displays had the same number of items. We used a combination of single neuron and population-level analyses and discovered a sequential transformation of represented information with trial progression. While numerical values were initially represented with high precision and in conjunction with detailed information such as order, the decision was encoded in a low-dimensional subspace of neural activity. This decision encoding was invariant to both retrospective numerical values and prospective motor plans, representing only the binary judgment of 'same number' versus 'different number,' thus facilitating the generalization of decisions to novel number pairs. We conclude that this transformation of neuronal codes within the prefrontal cortex supports cognitive flexibility and generalizability of decisions to new conditions.
DOI: 10.17632/8czn4rxz68
title: Dataset of Congruent Inhibitors and Decoys (D-COID)

description: This dataset contains Rosetta energy-minimized crystal structure of protein-ligand complex and their congruent, property-matched decoys. It was created to serves as a realistic benchmark dataset for tasks in computational drug discovery.
DOI: 10.17632/88t7cx9mh8
title: Data for: How Does Environmental Knowledge Translate into Pro-Environmental Behaviors?: The Mediating Role of Environmental Attitudes and Behavioral Intentions

description: The data are taken from the 2010 Chinese General Social Survey (CGSS2010) , which was associated collected by the Renmin University of China and Hong Kong University of Science and Technology in 2010.
DOI: 10.6084/m9.figshare.25656951.v1
title: CHM_Drought

description: CHM_Drought，an innovative and comprehensive long-term meteorological drought dataset with a spatial resolution of 0.1° and data collected from 1961 to 2022 in mainland China. It features six pivotal meteorological drought indices: the standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), evaporative demand drought index (EDDI), Palmer drought severity index (PDSI), self-calibrating Palmer drought severity index (SC-PDSI), and vapor pressure deficit (VPD), of which SPI, SPEI, and EDDI contain multi-scale features for periods of 2 weeks and 1–12 months.The dataset features a comprehensive application of high-density meteorological station data and a complete framework starting from basic meteorological elements (the China Hydro-Meteorology dataset, CHM).
DOI: 10.6084/m9.figshare.8848517.v3
title: 9-node natural gas network.xlsx

description: a 9-node natural gas network
DOI: 10.17632/b58rncnfg5
title: Data for: Molecular Fingerprint-Derived Similarity Measures for Toxicological Read-Across: Recommendations for Correct Use

description: Tanimoto coefficients for the data set analysed
DOI: 10.17632/v5hp75hrtj
title: A Printing-Inspired Digital Twin for the Self-Driving, High-Throughput, Closed-Loop Optimization of Roll-to-Roll Printed Photovoltaics

description: Datasets related to the manuscript 'A Printing-Inspired Digital Twin for the Self-Driving, High-Throughput, Closed-Loop Optimization of Roll-to-Roll Printed Photovoltaics' by Ng et al. The hypothesis of this research is that integrating high-throughput roll-to-roll (R2R) fabrication with machine learning (ML) models can significantly enhance the scalability and performance of printed organic photovoltaic (PV) devices. By employing a digital twin approach, fabrication parameters can be optimized in real-time, improving power conversion efficiency (PCE) and overall device performance through closed-loop feedback. The dataset includes raw data from the initial fabrication and characterization of 11,800 devices, along with refined data for ML modeling. The PV devices were fabricated using an R2R process, with layers deposited onto polyethylene terephthalate (PET) strips, and characterized under 1 sun conditions (AM 1.5G). The raw data contains 649,055 data points, including fabrication parameters, characterization results, and environmental conditions. 

The dataset comprises two main parts:

Dataset 1: The raw data collected from the initial high-throughput fabrication and characterization of 11,800 organic photovoltaic devices.
Dataset 2: The refined and cleaned dataset used for machine learning modeling, which includes training, validation, and testing subsets.

Data Collection Methodology
Fabrication: The photovoltaic devices were fabricated using a roll-to-roll process, with functional layers deposited onto a strip of polyethylene terephthalate (PET) with a patterned transparent conducting electrode (TCE). Multiple sensors embedded in the MicroFactory collected data from 36 manufacturing features, including deposition parameters, temperatures, and environmental conditions.
Characterization: Each device was characterized in-line under standard 1 sun conditions (AM 1.5G), measuring key performance metrics such as short-circuit current density (Jsc), open-circuit voltage (Voc), fill factor (FF), and power conversion efficiency (PCE).
Raw Data (Dataset 1): Contains 649,055 data points, including fabrication parameters, characterization results, and environmental conditions for each of the 11,800 devices.
Cleaned Data (Dataset 2): Includes selected variables from Dataset 1 that were used for machine learning modeling, divided into training, validation, and testing sets.
DOI: 10.17632/xydncc3cy7
title: Compositional moving interface example files- CuNi

description: Example Lammps input files to use the compositional moving interface method to calculate the liquidus and solidus of CuNi.
DOI: 10.6084/m9.figshare.28846619.v1
title: BMSD 2025 Data Contract Gray Literature Review

description: This is the replication package of the BMSD 2025 paper. It includes a complete list of sources and a qualitative analysis of these sources, performed using Atlas.ti tool.
DOI: 10.17632/2dytmtksnc
title: Raw Data of Magnetic Test for Variation of Microcarbonyl iron of Loading Natural Rubber Nanocomposites

description: The performance of magnetic rubber device is dependent on mechanical and magnetic properties of composite rubber materials. A vibrating sample magnetometer (VSM) is an instrument to detect the magnetic properties. 
The magnetic field versus magnetization was carried out to study the magnetic characteristics of the nanocomposite samples. VSM Lakeshore 7404 Series was used to analysis the magnetic properties of nanocomposite material. In the present study, the samples were tested under two (2) variations; i) containing the same amount of magnetic fillers, which is about 30 pphr in the composites but vary in nanocarbon loading i.e. 0%, 1%, 3% and 5% and ii) samples containing the same amount of 1 pphr nanocarbon fillers, in the composites with different loading of microcarbonyl iron (MCI). the increasing of magnetic properties of the samples is not consistent with the increasing of nanocarbon loading as A1 has a higher magnetization value than A5, which is really contrast with the previous work (Zaborski et al., 2009). This phenomenon occurred because of the fillers are well dispersed in the compound A1. Zaborski et al. (2009) found that the magnetization retentively increase with higher filler content of iron oxides. It has been found that in general, the addition of iron nanoparticles enhances the MRE mechanical and magnetic properties. In fact, the addition of iron nanoparticles as a filler in the hard matrix along with 24% of dispersant agent has proved to create the composite material that exhibits the best properties.