cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.25505182.v1
title: Strain relaxation and multidentate anchoring in n-type perovskite transistors and logic circuits

description: NMR data spectra for Figure 2.
DOI: 10.6084/m9.figshare.27606492.v2
title: xdm_metadata.txt

description: This metadata file provides units and explanation of all variables contain in the three datasets of the <i>XyloDensMap </i>collection.
DOI: 10.6084/m9.figshare.7013003.v2
title: hcp_tractogram

description: Testing tractogram of one of the HCP dataset subjects to be used in DIPY's tutorials.<br><br><br>
DOI: 10.17632/my3fx9wzyb
title: Reciprocating wear testing raw data on piston aluminum alloys

description: Experimental data from reciprocating wear testing on piston aluminum-silicon alloys under various forces and speeds
DOI: 10.6084/m9.figshare.12673985.v1
title: JVASP-64402 to JVASP-65229

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.25593708.v1
title: Supplementary Material for: PROVIT-CLOCK - A potential influence of probiotics and Vitamin B7 add-on treatment and metabolites on clock gene expression in major depression

description: Introduction
An increasing body of evidence suggests a strong relationship between gut health and mental state. Lately, a connection between butyrate-producing bacteria and sleep quality has been discussed. The PROVIT study, as a randomized, double-blind, four-week, multispecies probiotic intervention study, aims at elucidating the potential interconnection between the gut’s metabolome and the molecular clock in individuals with major depressive disorder (MDD). 
Methods
The aim of the PROVIT-CLOCK study was to analyze changes in core clock gene expression during treatment with probiotic intervention versus placebo in fasting blood and the connection with the serum- and stool-metabolome in patients with MDD (n= 53). In addition to clinical assessments in the PROVIT study, metabolomics analyses with 1H Nuclear Magnetic Resonance (NMR) Spectroscopy (stool and serum) and gene expression (RT-qPCR) analysis of the core clock genes ARNTL, PER3, CLOCK, TIMELESS, NR1D1 in peripheral blood mononuclear cells (PBMCs) of fasting blood, were performed.
Results
The gene expression levels of the clock gene CLOCK were significantly altered only in individuals receiving probiotic add-on treatment. TIMELESS and ARNTL gene expression changed significantly over the four-week intervention period in both groups. Various positive and negative correlations between metabolites in serum/stool and core clock gene expression levels were observed. 
Conclusion
Changing the gut microbiome by probiotic treatment, potentially influences CLOCK gene expression. The preliminary results of the PROVIT-CLOCK study indicate a possible interconnection between the gut microbiome and circadian rhythm potentially orchestrated by metabolites.
DOI: 10.6084/m9.figshare.28462835.v1
title: Mexico's High Resolution Climate Database (MexHiResClimDB): daily average temperature for Mexico.

description: Daily average temperature for Mexico for the 1951-2020 period. This gridded dataset is georeferenced and provided in geographic coordinates (resolution 20 arc sec); the daily average temperature provided was obtained by averaging the interpolated Tmin and Tmax rasters for each day.
DOI: 10.6084/m9.figshare.92128.v2
title: Zoloft changes the shape of red blood cells in accordance with the bilayer couple model

description: The bilayer couple model was proposed in 1974 by Singer and Sheetz in their landmark paper: "Biological Membranes as Bilayer Couples. A Molecular Mechanism of Drug-Erythrocyte Interactions." The bilayer couple model states that charged molecules accumulate asymmetrically in lipid bilayer. This drug-membrane interaction can be easily visualized in red blood cells, which conveniently have a single outer lipid bilayer. The Perlstein lab generated these unpublished images of red blood cells treated with different concentrations of the the SSRI antidepressant sertraline/Zoloft®, which is a cationic amphipath. Sertraline accumulated in the inner monolayer of the red blood cell plasma membrane, causing the plasma membrane to curve inward, culminating in cup formation. The degree of cup formation is proportional to sertraline concentration, beginning at single-digit micromolar concentrations up to a critical concentration at which membrane lysis occurs. Don't worry. The extremely low serum concentration of Zoloft in people taking the drug means that your red blood cells are just fine.
DOI: 10.17632/kxcb3tnr3t
title: Synthetic and Real Key-Value Data Sets

description: We present key-value data sets where each data set is composed of various data types. We present eight datasets including synthetic and real data sets for storing them in the key-value stores such as LevelDB of Google, RocksDB of Facebook, and Berkeley DB of Oracle. The key-value stores have a strength that can deal with various data types by assigning data of an arbitrary type as the value and the unique ID as the key. When we construct key-value data sets, we focus on various data types (i.e., variety) in real data sets and various sizes (i.e., volume) in synthetic data sets. We generate four synthetic data sets according to the various size of data set: (1) KVData1, (2) KVData2, (3) KVData3, and (4) KVData4. The total number of objects are varied from 10K to 10M. For each key-value pair, we generate a random string with a variable length and a unique ID for a key. For real datasets, we crawled user tweets and relevant information from Twitter using Tweepy library (https://www.tweepy.org/) and each data set consists of various data types: 1) Geo-location, 2) hashtag, 3) Tweets, and 4) the number of followers. That is, all the data sets are designed to have different data types such as geo-locations, texts, and integers. Table 2 shows the characteristics of the real data sets. We crawled four kinds of real data sets: (1) ID-Geo, consisting of the tweet ID and the location information of the tweet, (2) ID-Hashtag, consisting of the tweet ID and the hashtags in the tweet, (3) ID-Tweet data set, consisting of the tweet ID and the tweet text, and (4) User-Followers, consisting of the user ID and the number of followers of the user.
DOI: 10.6084/m9.figshare.23695398.v1
title: <strong>Genetic associations with ratios between protein levels detect new pQTLs and reveal protein-protein interactions</strong>

description: File content: processed_gwas_region_files.1.tgz : Full summary statistics for +/- 500kb regional refinements around 8,462 rQTL lead SNPs using imputed genotype data in the discovery cohort (tab-separated, text). <br> processed_gwas_region_files.2.tgz : Full summary statistics for +/- 500kb regional refinements around 8,462 rQTL lead SNPs using imputed genotype data in the replication cohort (tab-separated, text). <br> OLINK_analyze_gwas_regions.pdf : Regional association plots for local refinements (multi-page PDF) <br> MANHATTAN_PLOTS.tgz : Manhattan plots for 2,821 GWAS with ratios (multiple PDF files)
DOI: 10.6084/m9.figshare.27152670.v1
title: <b>A virtual tracer experiment to assess the temporal origin of root water uptake, evaporation, and </b><b>drainage</b>

description: The temporal origin of drainage, evaporation, and root water uptake (RWU) are indicators of ecosystem functioning that shed light on how natural and anthropogenic disturbances affect plant resilience and aquifer vulnerability. A virtual tracer experiment was carried out in HYDRUS-1D using data from a soil lysimeter planted with winter rye in Austria. The RWU (<i>t</i><sub><em>R</em></sub>), evaporation (<i>t</i><sub><em>E</em></sub>), and drainage (<i>t</i><sub><em>D</em></sub>) transit times (<i>t</i>) were determined by using the actual dispersivity optimized in a prior study. First, <i>t</i><sub><em>R</em></sub> and <i>t</i><sub><em>D</em></sub> were compared to RWU (<i>t</i><sub><em>PT,R</em></sub>) and drainage (<i>t</i><sub><em>PT,D</em></sub>) advective transit times estimated using the particle tracking algorithm. The <i>t</i><sub><em>R</em></sub> values were in agreement with <i>t</i><sub><em>PT,R</em></sub> while large discrepancies were detected when estimating drainage transit times using the two approaches. A sensitivity analysis revealed that dispersivity had a mild, poor, and strong influence on <i>t</i><sub><em>R</em></sub>, <i>t</i><sub><em>E</em></sub>, and <i>t</i><sub><em>D</em></sub>. The longitudinal dispersivity describes how a tracer spreads along the flow paths. The longer the flow paths, the more dispersion affects the tracer transport. On average, water parcels originating from rainfall in the growing season took 18 and 201 days to reach the roots (with RWU being 21% of rainwater) and the soil profile bottom (with drainage being 36% of rainwater), respectively. In contrast, 10% of rainwater that fell in the dormant season became RWU after 264 days, while 79% became drainage after 294 days. The temporal origin of water can be explored in other plots by using the guidelines proposed in this study.Two open-source Matlab scripts are available in the zip-files. The PT.m Matlab code determines the drainage transit time based on the particle tracking algorithm, while the VTE.m Matlab code determines the drainage and RWU transit times and relative rainfall contributions to actual evaporation, actual transpiration, and drainage using isotope transport simulations in HYDRUS-1D. The file LEVEL_01.DIR will be generated by the MATLAB script
DOI: 10.6084/m9.figshare.29047283.v1
title: Simulation data from "Eliciting priors and relaxing the single causal variant assumption in colocalisation analyses"

description: Simulation data fromEliciting priors and relaxing the single causal variant assumption in colocalisation analysesChris WallacePMID: <b>32310995</b> PMCID: PMC7192519 DOI: 10.1371/journal.pgen.1008720
DOI: 10.6084/m9.figshare.7223621.v1
title: STL_REDLINING_Analysis.csv

description: A tract-level data set of segregation, redlining, and demographic data combined with health outcomes measures from the Centers for Disease Control. This data set is specific to the City of St. Louis.
DOI: 10.6084/m9.figshare.7853306.v1
title: All data

description: IV relationships from NMDA receptor and AMPA/kainate currents from hippocampal Schaffer-CA1 synapses from sham and sound stimulated animals.-Data from AMPA/kainate EPSCs recorded at -80 mV from Schaffer-CA1 synapses in hippocampal pyramidal neurons from rats sham and sound stimulated animals.-Data from NMDA EPSCs recorded at 70 mV from Schaffer-CA1 synapses in hippocampal pyramidal neurons from rats sham and sound stimulated animals. All glutamatergic currents were recorded in the presence of picrotixi.-Data from GABAergic spontaneous IPSCs (in the presence of DNQX) and miniature IPSCs recorded at --80 mV. mIPSCs were recorded in the presence of TTX.<br>The sound stimulation protocol was described in Cunha <i>et al., </i><i>Neuroscience</i>. 310:114-27. 2015.
DOI: 10.17632/stt8557n86
title: Main Ethiopian Rift - ground fissures

description: Supporting datasets for the research of ground fissures in the Main Ethiopian Rift. The data includes precipitation data (month averages) from available meteorological stations, WGS84 coordinates of individual research sites and dimesnions of researched fissures, laboratory determined data of soil samples and the field seismic records (SEG-2 format) used for the anisotropy calculations. Please, contact owner on e-mail valentah@natur.cuni.cz before use to prevent misunderstandings.
DOI: 10.6084/m9.figshare.13604192.v1
title: Imaging Mass Cytometry Breast Cancer

description: Please cite original article: https://doi.org/10.1038/s41586-019-1876-x
DOI: 10.6084/m9.figshare.1546747.v2
title: Data and stimuli for "Dot comparison stimuli are not all alike: The effect of different visual controls on ANS measurement"

description: This is the full data set and stimuli for Clayton, S., Gilmore, C., & Inglis, M. (in press). Dot comparison stimuli are not all alike: The effect of different visual controls on ANS measurement. Acta Psychologica. The excel columns in the data file refer to the following: Participant: Participant identifier number Trialorder: The order the trials were presented for each participant (random order) Accuracy: 1= correct, 0 = incorrect Response time: Response time in milliseconds ImageFile: The file name of the dot array image GebuisImageType: This is the category of the trial in terms of convex hull congruency and cumulative surface area congruency, as generated by the Gebuis & Reynvoet (2011) script. 1 & 8= Convex hull congruent, cumulative surface area congruent; 2 & 7= Convex hull incongruent, cumulative surface area incongruent; 3 & 6= Convex hull congruent, cumulative surface area incongruent; 4 & 5= Convex hull incongruent, cumulative surface area congruent. TrialNumber: The number of the trial (not in order of presentation) Procotol: The method used to generate the dots. Gebuis= Gebuis, T., & Reynvoet, B. (2011). Generating nonsymbolic number stimuli. Behavior Research Methods, 43, 981–986, Panamath= Panamath software, Halberda, J., Mazzocco, M., & Feigenson, L. (2008). Individual differences in nonverbal number acuity predict maths achievement. Nature, 455, 665-668. Time: Participants completed each trial twice. Time1= first presentation of trials, Time2= second presentation of trials. Numerosity1_Left: The number of dots in the left array. Numerosuty2_Right: The number of dots in the right array. Left:RightNumerosity: The ratio between the number of dots in each of the arrays in each trial (number of dots on the left / number of dots on the right) ConvexHull1_Left: The size of the convex hull of the left array. ConvexHull2_Right: The size of the convex hull of the right array, Left:RightConvexHull: The ratio between the convex hull of arrays in each trial (size of left convex hull / size of right convex hull) pixels1_Left: The number of pixels in the left array. pixels2_Right: The number of pixels in the right array. Left:RightPixels: The ratio between the number of pixels in each of the arrays in each trial (number of pixels in left array / number of pixels in right array). Dot size1_Left: Average size of dots in the left array (pixels / numerosity) Dotsize2_Right: Average size of dots in the right array (pixels / numerosity) Left:RightDotSize: The ratio between the average size of the dots in each array in each trial (avergae dot size of left array / average dot size of right array).
DOI: 10.6084/m9.figshare.22336786.v2
title: antibacterial effect of Barium Titanate

description: these data belong to the article entitled:<strong>"Assessment the antibacterial effect of Barium titanate nanoparticles against </strong><em><strong>staphylococcus epidermidis</strong></em><strong> adhesion after addition to maxillofacial silicone"</strong>. and the data include the followings:
1-Raw data representing optical densty absorption for bacterial test.
2- VITEK 2 Microbiology Chart Report
<br>
3-pictures of steps of bacterial test
4-FTIR data for barium titanate and silicone befor and after addition of barium titanate 
5- FE-SEM for barium titanate and silicone befor and after addtion of barium titanate
6- particle size analyzer report
DOI: 10.6084/m9.figshare.23731056.v1
title: Graphene Review.enl

description: File contains manuscripts to be uploaded to EndNote for complete reference.. Abstract: The growing demand for more efficient materials for medical applications brought together two previously distinct fields: medicine and engineering. Regenerative medicine has evolved with the engineering contributions to improve materials and devices for medical use. In this regard, graphene is one of the most promising materials for bone tissue engineering and its potential for bone repair has been studied by several research groups. The aim of this study is to conduct a scoping review including articles published in the last 12 years (from 2010 to 2022) that have used graphene and its derivatives (graphene oxide and reduced graphene) in preclinical studies for bone tissue regeneration, searching in PubMed/MEDLINE, Embase, Web of Science, Cochrane Central, and clinicaltrials.gov (to confirm no study has started with clinical trial). Boolean searches were performed using the defined key words “bone” and “graphene”, and manuscript abstracts were uploaded to Rayyan, a web-tool for systematic and scoping reviews. This scoping review was conducted based on Joanna Briggs Institute Manual for Scoping Reviews and the report follows the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses – Extension for Scoping Reviews (PRISMA-ScR) statement. After the search protocol and application of the inclusion criteria, 77 studies were selected and evaluated by five blinded researchers. Most of the selected studies used composite materials associated with graphene and its derivatives to natural and synthetic polymers, bioglass, and others. Although a variety of graphene materials were analyzed in these studies, they all concluded that graphene, its derivatives, and its composites improve bone repair processes by increasing osteoconductivity, osteoinductivity, new bone formation, and angiogenesis. Thus, this systematic review opens up new opportunities for the development of novel strategies for bone tissue engineering with graphene.
DOI: 10.6084/m9.figshare.28726733.v1
title: Supplementary Table 3 8h DEG.xlsx

description: Supplemental data for: CCAAT/Enhancer-Binding Proteins α and β Regulate Ovulation and Gene Expression via Dose- and Stage-Dependent Mechanisms
DOI: 10.6084/m9.figshare.21304992.v1
title: COPD .sav

description: SPSS file for COPD exacerbation related admission analysis
DOI: 10.6084/m9.figshare.24353028.v1
title: Factor Augmented Sparse Throughput Deep ReLU Neural Networks for High Dimensional Regression

description: This article introduces a Factor Augmented Sparse Throughput (FAST) model that uses both latent factors and sparse idiosyncratic components for nonparametric regression. It contains many popular statistical models. The FAST model bridges factor models on one end and sparse nonparametric models on the other end. It encompasses structured nonparametric models such as factor augmented additive models and sparse low-dimensional nonparametric interaction models and covers the cases where the covariates do not admit factor structures. This model allows us to conduct high-dimensional nonparametric model selection for both strong dependent and weak dependent covariates and hence contributes to interpretable machine learning, particularly to the feature selections for neural networks. Via diversified projections as estimation of latent factor space, we employ truncated deep ReLU networks to nonparametric factor regression without regularization and to a more general FAST model using nonconvex regularization, resulting in factor augmented regression using neural network (FAR-NN) and FAST-NN estimators, respectively. We show that FAR-NN and FAST-NN estimators adapt to the unknown low-dimensional structure using hierarchical composition models in nonasymptotic minimax rates. We also study statistical learning for the factor augmented sparse additive model using a more specific neural network architecture. Our results are applicable to the weak dependent cases without factor structures. In proving the main technical result for FAST-NN, we establish a new deep ReLU network approximation result that contributes to the foundation of neural network theory. Numerical studies further support our theory and methods. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.25241827.v1
title: <b>GLOBAL CONSERVATION GENOMICS OF BLUE WHALES CALLS INTO QUESTION SUBSPECIES TAXONOMY AND REFINES KNOWLEDGE OF POPULATION STRUCTURE</b>.

description: Bmus_16661SNP_276.vcfVCF with 276 blue whale samples genotyped for 16,661 high-quality SNPs.
DOI: 10.6084/m9.figshare.26186534.v1
title: eyetracking data for aging and anticipation

description: This study investigated how ageing impacts anticipation during comprehension, considering that both language experience and cognitive factors modulate prediction during comprehension. We investigated whether older adults can utilize gender-marked adjectives to predict the target noun during Hindi sentence comprehension. Two visual world paradigm studies (Experiment 1 & 2) were conducted, where young and older adults listened to sentences containing a target word while looking at a visual display containing the target object and three distractors. The sentences consisted of adjectives which were highly associated with the target object. We measured anticipatory gaze towards the target object before it was mentioned in the sentence indexing prediction using adjectives. The results from both experiments showed that older adults exhibited anticipatory gaze towards the target noun soon after hearing the adjective, which did not differ from that of young adults
DOI: 10.15468/dl.ywshwb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Holtbyrnia innesi (Fowler, 1934)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((11.7957 -6.2886,12.3365 -7.1504,17.9648 -7.1504,17.9648 1.8496,9.1702 1.8496,8.9648 1.4824,8.9648 -2.2147,9.212 -2.6876,11.2887 -4.7775,11.6694 -5.4096,11.7957 -6.2886))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013418-250525065834625/datasets/export for details.
DOI: 10.6084/m9.figshare.11687064.v5
title: Example Dataset for BIDS Manager

description: This folder contains data from a fictional participant that you can use to test BIDS Manager (https://github.com/Dynamap/BIDS_Manager).
DOI: 10.6084/m9.figshare.21746141.v2
title: Silva et al - SI.pdf

description: Supplementary Information
DOI: 10.6084/m9.figshare.21931875.v2
title: ProjecTILs human reference atlas of CD8+ tumor-infiltrating T cells, version 1

description: ProjecTILs human reference atlas of CD8+ tumor-infiltrating T cells, generated by semi-supervised STACAS integration of scRNA-seq datasets spanning 7 cancer types. <br> The dataset is available as a Seurat object, with functional cluster, sample of origin and several other measurement for each cell stored in the object metadata. The object can be loaded into an R session using the readRDS() function, and directly used as a reference atlas for ProjecTILs (Andreatta et al. 2021). <br> Code to reproduce the atlas can be found here: https://github.com/carmonalab/human_TIL_atlas
DOI: 10.6084/m9.figshare.7053701.v4
title: Data-files of ecology and evolution.xlsx

description: The data of manuscripts number ECE-2018-09-01065 of the journal "ecology and evolution"