cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.vwj6q5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Sittasomus griseicapillus (Vieillot, 1818))",
 "Country is one of (Bermuda, Canada, Greenland, Saint Pierre and Miquelon, United States of America)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016511-250525065834625/datasets/export for details.
DOI: 10.15468/dl.m7t82s
title: Occurrence Download

description: A dataset containing 16812 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Miniopterus schreibersii",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil)"
 ]
 }
 }
 ]
}

 The dataset includes 16812 records from 171 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003420-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ubph4z
title: Occurrence Download

description: A dataset containing 114823 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Brazil",
 "GadmGid is BRA.3_1"
 ]
}

 The dataset includes 114823 records from 420 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003408-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18442310
title: FARMATSEVTIKA LEKSIKASIDA POLISEMIYA HODISASI

description: Ushbu maqolada  polisemiya va omonimiyaning  farqiga  izoh berilgan shu  bilan   bir   qatorda  tilshunos olimlarning  polisemiya  hodisasiga qaratilgan fikrlari,  uch  tilda: ingliz , rus, o`zbek  tillaridagi termin sifatida qo`llanib  kelayotgan so`zlardagi polisemiya hodisasiga  izoh  berilgan.
DOI: 10.5281/zenodo.18442311
title: FARMATSEVTIKA LEKSIKASIDA POLISEMIYA HODISASI

description: Ushbu maqolada  polisemiya va omonimiyaning  farqiga  izoh berilgan shu  bilan   bir   qatorda  tilshunos olimlarning  polisemiya  hodisasiga qaratilgan fikrlari,  uch  tilda: ingliz , rus, o`zbek  tillaridagi termin sifatida qo`llanib  kelayotgan so`zlardagi polisemiya hodisasiga  izoh  berilgan.
DOI: 10.6084/m9.figshare.30636944
title: An Explainable Percolation-based Clustering Framework for China’s Transport Carbon Emissions Analysis

description: Mitigating carbon emissions requires coordinated actions across jurisdictions, as emissions often exhibit strong spatial spillovers and interdependencies. Understanding how emissions cluster spatially is therefore essential for designing collaborative mitigation strategies. However, existing studies on the spatial clustering of carbon emissions remain limited by subjective parameter settings and insufficient exploration of heterogenous driving factors across clusters. Here, we integrate the percolation theory in physics with a spatial-temporal clustering algorithm to objectively delineate clusters of transport-related carbon emissions (TCE) for 323 Chinese cities in 2019. Building on six identified spatial clusters at the regional level, we employ random forest models and interpretable machine learning techniques to examine the effects of various factors on TCE. The results further uncover regional heterogeneity in emission determinants: nighttime light intensity is predominant in the northwest, population size in the northeast, and industrial added value in central and coastal regions. Higher daily temperatures are generally associated with increased TCE. The green coverage rate of built-up areas is negatively correlated with TCE in the northwest but exhibits the opposite relationship in the central south and southwest. This study contributes to the methodological frontier by introducing a percolation-based spatial clustering framework for emission analysis, which can be generalizable to broader contexts. Furthermore, it provides actionable insights for fostering cross-city coordination in emission mitigation, advancing China's decarbonization targets and sustainable transport goals.
DOI: 10.6084/m9.figshare.30636944.v2
title: An Explainable Percolation-based Clustering Framework for China’s Transport Carbon Emissions Analysis

description: Mitigating carbon emissions requires coordinated actions across jurisdictions, as emissions often exhibit strong spatial spillovers and interdependencies. Understanding how emissions cluster spatially is therefore essential for designing collaborative mitigation strategies. However, existing studies on the spatial clustering of carbon emissions remain limited by subjective parameter settings and insufficient exploration of heterogenous driving factors across clusters. Here, we integrate the percolation theory in physics with a spatial-temporal clustering algorithm to objectively delineate clusters of transport-related carbon emissions (TCE) for 323 Chinese cities in 2019. Building on six identified spatial clusters at the regional level, we employ random forest models and interpretable machine learning techniques to examine the effects of various factors on TCE. The results further uncover regional heterogeneity in emission determinants: nighttime light intensity is predominant in the northwest, population size in the northeast, and industrial added value in central and coastal regions. Higher daily temperatures are generally associated with increased TCE. The green coverage rate of built-up areas is negatively correlated with TCE in the northwest but exhibits the opposite relationship in the central south and southwest. This study contributes to the methodological frontier by introducing a percolation-based spatial clustering framework for emission analysis, which can be generalizable to broader contexts. Furthermore, it provides actionable insights for fostering cross-city coordination in emission mitigation, advancing China's decarbonization targets and sustainable transport goals.
DOI: 10.6084/m9.figshare.30636944.v1
title: An Explainable Percolation-based Clustering Framework for China’s Transport Carbon Emissions Analysis

description: Mitigating carbon emissions requires coordinated actions across jurisdictions, as emissions often exhibit strong spatial spillovers and interdependencies. Understanding how emissions cluster spatially is therefore essential for designing collaborative mitigation strategies. However, existing studies on the spatial clustering of carbon emissions remain limited by subjective parameter settings and insufficient exploration of heterogenous driving factors across clusters. Here, we integrate the percolation theory in physics with a spatial-temporal clustering algorithm to objectively delineate clusters of transport-related carbon emissions (TCE) for 323 Chinese cities in 2019. Building on six identified spatial clusters at the regional level, we employ random forest models and interpretable machine learning techniques to examine the effects of various factors on TCE. The results further uncover regional heterogeneity in emission determinants: nighttime light intensity is predominant in the northwest, population size in the northeast, and industrial added value in central and coastal regions. Higher daily temperatures are generally associated with increased TCE. The green coverage rate of built-up areas is negatively correlated with TCE in the northwest but exhibits the opposite relationship in the central south and southwest. This study contributes to the methodological frontier by introducing a percolation-based spatial clustering framework for emission analysis, which can be generalizable to broader contexts. Furthermore, it provides actionable insights for fostering cross-city coordination in emission mitigation, advancing China's decarbonization targets and sustainable transport goals.
DOI: 10.5281/zenodo.18381757
title: Aligning Disjoint Spectral Manifolds: Cross-Continental Domain Adaptation for Agricultural Monitoring Under Severe Covariate Shift
DOI: 10.5281/zenodo.18381758
title: Aligning Disjoint Spectral Manifolds: Cross-Continental Domain Adaptation for Agricultural Monitoring Under Severe Covariate Shift
DOI: 10.34740/kaggle/dsv/14688706
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.23k35r
title: Occurrence Download

description: A dataset containing 5291374 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Amphibia",
 "Year 2007-2022"
 ]
}

 The dataset includes 5291374 records from 6693 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003391-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/5hkyvbyctj
title: SARS-CoV-2 (COVID-19) spike protein molecular dynamics simulation data

description: Molecular dynamics trajectory data of the SARS-CoV-2 (COVID-19) spike protein. The spike protein is a major target for vaccine development. Datasets include: - 2 x 0.2 µs trajectories of WT prefusion spike protein with site-specific glycans in GROMACS format - 2 x 0.2 µs trajectories of D614G prefusion spike protein with site-specific glycans in GROMACS format - CHARMM-GUI generated GROMACS topologies - GROMACS tpr and checkpoint files for continuing the simulations - Video renderings (protein chains in gray, cyan, and magenta; glycans in yellow) The prefusion spike protein structure used is based on 6VSB (single RBD in the up conformation) with site-specific glycans, see https://www.biorxiv.org/content/10.1101/2020.04.07.030445v1.full. Simulation details: CHARMM36m force field with CHARMM modified TIP3P water model, and 0.15 M NaCl. Equilibration and production (310 K, NPT) were performed with CHARMM-GUI files. *Potential collaborators, please contact eliocino@ufmg.br if you intend to use the data for publication.
DOI: 10.17632/mvxbdd4y59
title: Tool Wear

description: Tool Wear obtained by varying Tool Material, work piece material, speed, Feed, depth of cut, cumulative number of cuts, cumulative time, vibration amplitude
DOI: 10.17632/vwp8wmyw8p
title: Trial CFT for FBSS

description: Statistical Analysis using R of the trial of Cognitive Functional Therapy for Failed Back Surgery Syndrome. 
FBSS_trial (1).R is the R-routine and Banco_Leo_final_V.xlsx is the data bank
Before running the routine, all files must be in the same working directory of the computer
The PDF is a print of the results on R
DOI: 10.17632/622xjc76v3
title: 考虑取送货的多访问无人机-卡车协同路径优化问题研究3-6章测试算例

description: 下面四个文件夹包含了论文第3-6章的所有测试算例。
DOI: 10.17632/vpysb98628
title: "The Impact of Cyberbullying on Undergraduate Students: A Systematic Review of Social, Emotional, and Academic Outcomes

description: The data gathered was based on the studies done by the researchers that are related to the Cyber bullying in school specifically to undergraduate students.It explained the effect on academic ,social and emotional development of students if they experience bullying through social media in posting or direct messages.
DOI: 10.17632/rg8ksbfr8x
title: Wind Forecasting Dataset for STGATN

description: Our experimental area is located in the central part of Xinjiang, in the northwest region of China, between 86°57'51-"88°46'21" east longitude, and between 42°38'22-"44°23'26" north latitude. The experimental area covers large-scale wind farm such as the Sino-clean energy toli wind farm, the Guoneng dabancheng wind farm, the Xinjiang longyuan dabancheng wind farm, and the Huadian toli wind farm. We regard March, April, and May as spring, June, July, and August as summer, September, October, and November as autumn, and December, the following January, and the following February as winter. We collect hourly wind speed and surface pressure data from ERA5 for the years 2022 and 2023, and establish four datasets for spring, summer, autumn, and winter, namely LHZ_Spring, LHZ_Summer, LHZ_Autumn, and LHZ_Winter, for hourly wind speed forecasting. We calculate the daily average of wind speed and surface pressure based on the hourly data of 2022 and 2023, and create the LHZ dataset for daily wind speed forecasting.
DOI: 10.6084/m9.figshare.11918472.v1
title: Processed DNA methylation data from ENCODE

description: Processed data for well-covered CpG triplets WGBS data from 121 experimental replicates representing 77 unique biological samples, publicly available from ENCODE. These replicates include clinical tissue samples, cell lines, and primary cells. We selected replicates using single-end reads which were not flagged by ENCODE as having low coverage or insufficient read length. The list of the sample identifiers is found in ENCODE_IDs.xlsx. Each replicate is associated with a BAM file generated by mapping reads to GRCh38 using Bismark. We used the MethPipe methylation software suite to convert BAM files into MethPipe format and generate epiread files, an efficient format reporting the genomic index and methylation status of each CpG contained in a read. For each replicate, we used the epireads file generated to extract data from ``well-covered'' triplets---i.e. those where all three CpGs are jointly covered by at least 100 reads, discarding reads which report a CpG with ambiguous methylation status. For each autosome in each sample we estimated the exchangeable weight of each well-covered triplet and corrected for estimator bias using a sample mean of N=1000 full bootstrap resamples. Although each estimate of a triplet's exchangeable weight $\hat\lambda$ lies in $[0,1]$, the bias-adjusted estimate $(\hat\lambda-\bar{\hat\lambda^*})$ may be larger than $1$ or smaller than $0$. Therefore we truncate these estimates to $[0,1]$. The Numpy files here contain processed triplets corresponding to each BAM file ID. Each row corresponds to a well-covered triplet, with columns corresponding to 1) chromosome number, 2) index of the triplet on the chromosome, 3) an estimate of the total variation distance to the class of exchangeable distributions, 4) an estimate of the exchangeable weight of the triplet (bias-corrected), 5) a bootstrap estimate of the standard deviation of $\hat\lambda$, 6-13) the counts of each of the 8 possible triplet configurations (ordered lexicographically, i.e. `000', `001', etc.), and 14-21) an estimate of the largest exchangeable component.<br>
DOI: 10.6084/m9.figshare.19095554.v1
title: Supplementary Material for: Superiority of Simplified Acute Physiologic Score II Compared with Acute Physiologic and Chronic Health Evaluation II and Sequential Organ Failure Assessment Scores for Predicting 48-Hour Mortality in Patients Receiving Continuous Kidney Replacement Therapy

description: <b><i>Background:</i></b> Predicting early mortality is important in patients undergoing continuous kidney replacement therapy (CKRT), especially in the first 48 h. This study aimed to determine the predictive performance of the Simplified Acute Physiologic Score (SAPS) II, the Acute Physiologic and Chronic Health Evaluation (APACHE) II, and the Sequential Organ Failure Assessment (SOFA) scores for early mortality in patients receiving CKRT. <b><i>Methods:</i></b> Data from patients with acute kidney injury receiving CKRT were consecutively and retrospectively obtained at a tertiary medical center between August 2017 and March 2021. The outcomes included 48-h and 7-day mortality. The scoring systems were evaluated via discrimination at the time of CKRT initiation (using area under the receiver operating characteristics curve [AUROC]) and calibration (via Hosmer-Lemeshow goodness-of-fit C statistics). <b><i>Results:</i></b> Among eligible 652 patients, 95 (14.6%) and 212 (32.5%) died within 48 h and within 7 days, respectively. The AUROC for SAPS II (0.71, 95% confidence interval [CI]: 0.65–0.77, <i>p</i> = 0.016 vs. APACHE II score, <i>p</i> = 0.044 vs. SOFA score) was significantly higher than that of the APACHE II (0.66, 95% CI: 0.60–0.72) and SOFA scores (0.66, 95% CI: 0.60–0.72) for 48-h mortality. However, no significant differences in the AUROCs for SAPS II, APACHE II, and SOFA scores for 7-day mortality were observed. The calibration of the SAPS II for 48-h and 7-day mortality was adequate (<i>p</i> = 0.507 and <i>p</i> = 0.141, respectively). <b><i>Conclusions:</i></b> The predictive performance of SAPS II for mortality within the first 48 h was superior to that of the APACHE II and SOFA scores in patients with acute kidney injury receiving CKRT.
DOI: 10.17632/pxbhmh64vb
title: Data for: MANY-OBJECTIVE PORTFOLIO OPTIMIZATION APPROACH FOR STORMWATER MANAGEMENT PROJECT SELECTION ENCOURAGING DECISION MAKER BUY-IN

description: Additional Supporting Information (Files uploaded separately) • Data Set S1. An excel spreadsheet containing stormwater harvesting and green score determined by stakeholders, and calculations for costings and water quality performance of individual BMPs. Filename: ds01.xlsx • Data Set S2. A compressed file containing inputs and an executable for the Pareto Ant Colony Optimization Algorithm (PACOA) that can be run on a Windows desktop computer to replicate the optimization results. Filename: ds02.rar • Data Set S3. An excel spreadsheet containing the objective function values, decision options, and alternative data (catchment size, breakdown of benefits by Council) of the Pareto optimal solutions determined by sorting the optimization results for non-dominance in objective space. Filename: ds03.csv • Data Set S4. A .ddv that can be opened in the DiscoveryDV visual analytics program, containing interactive visualization of the Pareto optimal solution data from Data Set S3. Filename: ds04.ddv
DOI: 10.6084/m9.figshare.27299676.v1
title: Genetic diversity of amphibians and reptiles in Qinghai-Tibetan Plateau are greatly impacted by human activities

description: Genetic diversity is the most fundamental dimension of biodiversity, which is important for biodiversity conservation but has been more threatened than other dimensions of biodiversity. Human activities have reshaped ecosystems across the planet and are the greatest threat to biodiversity. However, the impact of human activities on the genetic diversity remains unclear, with significant effects of human activities can’t be detected in a large number of species. This outcome may be due to the influence of extinction filter effects. Species vary in their sensitivity to human activities. In regions greatly impacted by human activities, sensitive species may have already gone locally extinct or migrated. The remaining species are less sensitive to human disturbances. Therefore, it is difficult to detect the effects of human activities in these species. To test this hypothesis, we examined the relationship between anthropogenic factors and geographic patterns of genetic diversity of endemic amphibians and reptiles of the Qinghai-Tibet Plateau. The Qinghai-Tibet Plateau has been minimally affected by human activities. If extinction filter affected the relationships between human activities and genetic diversity, we should detect strong impacts of human activities. Conversely, given the low level of human activity on the plateau, we should not detect any significant impact of human activities. Herein, we constructed the geographic patterns of genetic diversity of seven endemic amphibian and reptile species. We examined the relationships between genetic diversity and natural and anthropogenic factors. Our results showed that human activity was the most important environmental factor affecting species’ genetic diversities, supporting that extinction filter effects may influence the relationship between human activity and genetic diversity. Additionally, we found that the effects of different anthropogenic factors on genetic diversity varied considerably, which suggested factors representing different aspects of human activities should be considered when examining the impacts between human activities.
DOI: 10.6084/m9.figshare.29137187.v1
title: Supplementary Figures_Fainshtein.pdf

description: Excessive hepatic glucose production (HGP) driven by increased gluconeogenesis is a hallmark of type 2 diabetes, making its inhibition a crucial strategy for reducing hyperglycemia. Central to HGP regulation is the transcriptional co-activator PGC-1α, which promotes the expression of key gluconeogenic enzymes. The acetylation state of PGC-1α significantly influences its coactivating potential, with increased acetylation—whether induced genetically or chemically—shown to suppress its gluconeogenic activity and lower hyperglycemia. The delicate balance between specific acetyltransferases and deacetylases determines the acetylation status of PGC-1α and, consequently, its activity. While the role of sirtuin deacetylases in PGC-1α acetylation has been extensively studied, zinc-dependent histone deacetylases (HDACs) have received less attention in this context. In this study, we demonstrate that HDAC1 strongly deacetylates PGC-1α, enhancing its ability to coactivate the transcription factor HNF4α. Furthermore, we show that depleting <i>Hdac1</i> in mouse primary hepatocytes and liver tissue reduces glucose production, consistent with decreased PGC-1α activity. While the HDAC family has been investigated for their contributions to metabolic homeostasis, our findings reveal a specific mechanistic pathway by which HDAC1 modulates glucose homeostasis.
DOI: 10.17632/s5nb3bxyjf
title: Data for: In silico prediction of bioequivalence of Isosorbide Mononitrate tablets with different dissolution proﬁles using PBPK modeling and simulation
DOI: 10.17632/r29psg69z7
title: Descriptive statistics of soil properties, ChE total concentrations and mobile fractions (mg/kg) in Retisols

description: Samples were taken from September 2016 to May 2018 in the southern part of the Central Forest Reserve (Russia) within a catena with c Retisols under coniferous-deciduous forest (Tília cordáta, Pícea ábies, Ácer platanoídes) on loess-like loams underlain by carbonate moraine deposits. Soil properties were analysed at the MSU (Lomonosov Moscow State University) Faculty of Geography: - pH value was measured in suspension (static conditions) using a pH-meter "Expert-рН" (Russia); - total organic carbon (TOC) content was determined in 120 samples using titrimetric method with phenylanthranilic acid (Reeuwijk, 2002); - the particle-size distribution was analyzed using laser diffraction technique and an ‘Analizeter 22’ equipment (Germany). Particle-size classes (Russian system): G1 – clay (&lt;1 μm), G2 – very fine silt (5–1), G3 – medium silt (10–5), G4 – сoarse silt (50–10), G5 –fine sand (250–50), G6 – medium sand (500–250). Total content of chemical elements (ChEs) and mobile fractions was measured at the VIMS (N. M. Fedorovskii All-Russia Institute of Mineral Raw Materials) using an Elan-6100 ICP-MS System and an Optima-4300 DV ICP-AES System. The studied fractions of the ChEs: - F1 (exchangeable) was extracted with NH4Ac (ammonium acetate buffer) - F2 (bound within organo-mineral complexes) was extracted with with 1% EDTA (ethylenediaminetetraacetic acid) - F3 (bound with Fe and Mn hydroxides) was extracted with 1M HNO3 - F4 (residual fraction) - the difference between the total content of elements and the content of mobile forms.
DOI: 10.17632/sscc5m7rrz
title: Data for: Explaining decoupling in highly developed economies: A structural decomposition analysis of the change in energy footprint from 1970 to 2009

description: Dataset contains results for the structural decomposition analysis of the change in energy footprint from 1970 to 2009