cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/hjppd5d9gt.1
title: Data for source apportionment of suspended sediment using grain-size end-member analysis

description: This data was uploaded for supporting findings in the manuscript entitled “Source apportionment of suspended sediment using grain-size end-member analysis”. The data includes: a) the in-situ suspended sediment grain-size distribution data collected by a LISST-100X particle analyzer (Sequoia Scientific, Inc., USA; Type C) in Haizhou Bay coastal waters; b) the corresponding current measured by a three-dimensional high-frequency point Doppler current velocimeter (ADV, 6 MHz, Nortek AS., NOR); c) the grain-size distribution of the surface sediment taken near the observation point (measured using LISST-100X particle analyzer); and d) the suspended sediment grain-size distribution of Linhong river (measured using LISST-100X particle analyzer).
DOI: 10.17632/yf79hm5584.1
title: Subduction thermal regime, petrological metamorphism and seismicity under the Mariana arc

description: The data includes the three-dimensional temperature field (degrees Celsius), water content (wt%), dehydration rate (wt%/km), rock phase change distribution, and subduction velocity field (cm/yr) of the subducting plate, as well as the coastline and volcano distribution. The data coordinates are an orthogonal coordinate system, where the origin of the coordinates is (147.8E, 17.5N), the x+ azimuth is 85 degrees clockwise from the north, the y+ azimuth is 355 degrees clockwise from the north, and the z+ direction is vertical downwards, in kilometers. The data source method is a three-dimensional finite difference numerical simulation. The geophysical calculation is ensured after the subduction thermal regime reaches a steady state. The temperature field error range is ±50 degrees Celsius, and the velocity field error range is ±0.1cm/ yr. This data can be further used to analyze the geophysical field of the subduction zone.
DOI: 10.17632/d4vzbcxxcy.1
title: Spectral Water Quality Data

description: This dataset was used in a study entitled Open statistical learning algorithms of characteristic wavelength selection and surrogate monitoring for UV‒Vis absorption spectroscopy-based in situ water quality sensing, by Jiping Jiang*, Meiyu Luo, Wenyu Wang, Hongliang Xu, Sijie Tang,  and Yi Zheng.
DOI: 10.17632/m88cj3z45b.1
title: supplyment file (Proteomic characterization and comparison of milk fat globule membrane proteins of Saanen goat milk from three habitats in China using SWATH-MS technique)

description: The detailed information for differentially expressed proteins (DEPs) of milk fat globule membrane (MFGM) protein in goat milk for GD vs IM, GD vs SX and IM vs SX. GD=Guangdong; IM=Inner Mongolia; SX=Shaanxi.
DOI: 10.17632/pdp2tdmvrt.1
title: Effect of inactivated and mRNA COVID-19 vaccination on thyroid function among patients treated for hyperthyroidism - Supplementary Tables

description: Supplementary Tables
DOI: 10.17632/3ytht93wcs.1
title: Soil lab results_Agroforestry species impact on soil chemical property

description: This data is collected from Kindo didaye woreda in Wolaita zone, Ethiopia. The data was collected to study the impact of agroforestry species selection decision on the soil chemical properties.
DOI: 10.17632/66rg4fhfzf.1
title: Effect of gas type on liquid injectivity in a surfactant-alternating-gas foam process

description: Foam is injected into geological formations in a number of applications, including enhanced oil recovery, CO2 sequestration, and soil remediation. Surfactant-Alternating-Gas (SAG) is one of the most common methods of foam injection. Injectivity is a key factor in a SAG foam process for both economics and diversion. Depending on process goals and local availability, varies types of gas can be injected. Previous studies suggest that gas properties play an important role in the evolution of gas and liquid injectivity in a SAG process. However, the mechanisms of the effect of gas type on injectivity remain poorly understood. In this study, various types of gas, N2, CO2 and Kr, are employed to investigate the effect of gas type on fluid behavior and injectivity in a SAG process. In one experiment, we partially pre-saturate injected liquid with CO2 to explore the effect of gas-dissolution capacity on liquid injectivity. We observe that the process of dissolution of trapped gas into liquid fingers is strongly affected by gas solubility. The lower the gas solubility in water, the slower the gas dissolution process, and the slower the rise in liquid injectivity. The gas-dissolution process takes much longer with injection of partially pre-saturated liquid than with unsaturated liquid. The propagation of the collapsed-foam front during gas injection is also affected by the gas type: the greater the solubility of water in gas, the faster the foam-collapse process. One practical implication is that CO2 SAG foam injectivity is substantially better than foam made with other gases.

The data sets include: cross-sectional water saturation profile during liquid injection following Nitrogen foam obtained from CT scan. Foam scan data for various types of gas at the same superficial velocity. The sectional pressure gradient data during gas injection following foam, liquid injection following foam and a period of gas injection. Researchers can directly draw the curve of pressure gradient change against pore volumes liquid/gas injection in various scenarios.
DOI: 10.17632/9vnztvcrcp.2
title: Climate induced change in spatial distribution of bee forage species in Southwest Western Australia

description: Species distribution models (SDM) for thirty key bee forage species targetted by beekeepers in Western Australia were obtained for current and a moderate emission climate scenario using the presence-only Maxent algorithm. Species occurrences are included as a Comma Separated Value (CSV) files with species name, latitude and longitude coordinates. Maxent outputs are formatted as GeoTiff files and included in folders named as respective scenario (i.e. Baseline and Future). Maxent outputs were converted to presence absence grids using maximum training sensitivity plus specificity threshold. Change in geographic distribution distribution between baseline and future was calculated for each bee forage species using QGIS. Species ranges shift maps and tablular data containing names of the study species, sample size, Maxent results, magnitude and the direction of species range shift is included as pdf file.
DOI: 10.17632/jy92ch3c9t.1
title: Data from: Bitomský et al. Plant functional groups and phylogenetic regularity control plant community bioelement composition through calcium and magnesium

description: Data from: Bitomský et al. (2022). Plant functional groups and phylogenetic regularity control plant community bioelement composition through calcium and magnesium. Oikos. doi: 10.1111/oik.09546

The dataset includes four files:
1. Community_matrix.txt = site x species community matrix (tab separated).

2. Phylogenetic_tree.txt = phylogenetic tree in a newick format. For detailed information on phylogeny inference please see Bitomský et al. (2021, Mycorrhiza, doi: 10.1007/s00572-021-01047-0). The tree used in this study was pruned from the tree in Bitomský et al. (2021).

3. Plot_data.txt = data on all community aspects, phylogenetic diversity, plant community bioelement composition (PCBC) and soil nutrient availability (tab separated).

4. Species_data.txt = species occurrences in plots with linked tissue bioelement concentrations and soil nutrient concentrations (tab separated). This format is suitable for fitting phylogenetic generalised linear mixed models (PGLMM).

See the Supplementary section of the paper (Tables S1-S2) for detailed information on soil and climate in the experimental sites.
DOI: 10.17632/4bpxncxnhh.1
title: The Second Order Shannon Total Generalized Variation 

description: The Supplementary Matlab files of the paper
                     "Alireza Hosseini and Sohrab Bazam, The Second Order Shannon Total Generalized Variation" 
for Image deblurring are available here. The Instruction is accessible in the Text file "read me first"
DOI: 10.17632/4bpxncxnhh.2
title: The Second Order Shannon Total Generalized Variation for Image Restoration

description: The Supplementary Matlab files of the paper
"Alireza Hosseini and Sohrab Bazm, The Second Order Shannon Total Generalized Variation for Image Restoration"

Alireza's Email: hosseini.alireza@ut.ac.ir.

The matlab codes of deblurring and Denoising images by means of seven variational models are implemented:
1- Total Variation ROF model  (TV)
2- Shannon Total Variation 
3- Second Order Total Generalized Variation 
4- The Infimal Convolution
5- Total Laplace
6- Anisotropic TV
7- The Second order Shannon Total Generalized Variation: Proposed Model
DOI: 10.17632/4bpxncxnhh.3
title: The Second Order Shannon Total Generalized Variation for Image Restoration

description: The Supplementary Matlab files of the paper
"Alireza Hosseini and Sohrab Bazm, The Second Order Shannon Total Generalized Variation for Image Restoration, Signal Processing"

Alireza's Email: hosseini.alireza@ut.ac.ir.

The matlab codes of deblurring and Denoising images by means of seven variational models are implemented:
1- Total Variation ROF model  (TV)
2- Shannon Total Variation 
3- Second Order Total Generalized Variation 
4- The Infimal Convolution
5- Total Laplace
6- Anisotropic TV
7- The Second order Shannon Total Generalized Variation: Proposed Model
DOI: 10.17632/83wvdfxt27.1
title: Direct Effects of Air Humidity on Dust Aerosol Production: Evidences for the Surprising Role of Electrostatic Forces

description: Dust aerosols are produced by wind erosion, and it is widely accepted that dust aerosols can be produced only if the wind speed exceeds a certain threshold velocity, which is largely controlled by soil moisture content. The relative humidity (RH) in the air could affect soil moisture content, thereby impacting dust production indirectly. However, it is not clear if the RH can directly change dust aerosol production. Here we simulated dust production and show that the RH does play a direct role in affecting the production of dust aerosol in a quite complicated way, which can be explained by a proposal that the RH affects both the electrostatic forces and wet-bonding forces between soil particles in opposite directions. The current formula for dust aerosol production flux does not include the direct RH effect, and this study strongly suggests that it could lead to significant errors in estimating dust production.
DOI: 10.17632/b98t6jftdr.1
title: Altered and allele-specific open chromatin landscape reveals epigenetic and genetic regulators of innate immunity in COVID-19

description: While SARS-CoV-2 infection causes mild respiratory disease in the majority of individuals, a small group of patients develops severe COVID-19. Dysfunctional innate immune responses have been identified to contribute to differences in COVID-19 severity, but the key regulators are still unknown. Here, we present an integrative single-cell epigenetics, transcriptomic, and genetics analysis of peripheral blood mononuclear cells from hospitalized and convalescent COVID-19 patients. In classical monocytes, we identified 41.3% of significantly up-regulated genes in hospitalized COVID-19 patients potentially induced by differential chromatin accessibility. Sub-clustering and motif-enrichment analyses of monocytes reveal disease condition-specific regulation by transcription factors, such as C/EBPs and SPI1, and their targets, including a long-noncoding RNA LUCAT1, which further regulates interferon responses and is associated with the need for oxygen supply of COVID-19 patients. The interaction between C/EBPs and LUCAT1 was validated through loss-of-function experiments. Finally, we investigated genetic risk variants that exhibit allele-specific open chromatin (ASoC) in promoters/enhancers of COVID-19 patients. Integrating our data with publicly available expression quantitative trait loci and chromosomal interactions indicates that ASoC SNP rs6800484-C is associated with lower expression of CCR2, which may contribute to higher viral loads in the lungs and a higher risk of COVID-19 hospitalization. Altogether, our study highlights the diverse genetic and epigenetic regulators that contribute to the innate immune responses of different COVID-19 patients.

This dataset includes figures, tables, and supplementaries used in the publication of our paper titled "Altered and allele-specific open chromatin landscape reveals epigenetic and genetic regulators of innate immunity in COVID-19".
DOI: 10.17632/d3dykhm22c.1
title: Dataset on The Mediating Role of Integrated Agro-tourism Cluster Development  on Regional Development in Indonesia

description: The dataset is a statistical research data in analyzing the mediating role of integrated agro-tourism cluster development 
on regional development in Indonesia. Three variables were examined namely government role, integrated agro-tourism cluster development and regional development.
DOI: 10.17632/gyr6c4nbsc.1
title: CSIDA

description: The dataset is for Wi-Fi-based human activity recognition. The dataset is comprised of six experiments performed by 5 different subjects in five different locations in two different indoor environments. Each subject performed 20 trials for each of the experiments which makes the overall number of recorded trials in the dataset equals to 3000 trials (6 experiments × 5 subjects × 5 locations × 20 times). To record the data, we used the channel state information (CSI) tool to capture the exchanged Wi-Fi packets between a Wi-Fi transmitter and receiver. The utilized transmitter and receiver are retrofitted with the Intel 5300 network interface card which enabled us to capture the CSI values that are contained in the recorded transmissions. The related articles is  "WiFi-based Cross-Domain Gesture Recognition via Modified Prototypical Networks" , whose url is  https://github.com/Zhang-xie/WiGr. For storage space reasons, the data is uploaded in two parts. The first part includes the final data and its label, and the second part includes the raw data.

The dataset folder contained seven sub-directories, which were the original data, the data with random phase offset removed, the data with noise removed, the action gesture label, the environment label, the location label, and the person label. This data was stored in zarr data format and needed to be read using python's zarr library. Zarr saved data in blocks. Frankly speaking, it was to divide a block of data into sub-blocks of the same size. Each sub-block was saved into a file named *.. The advantage of such processing was that it was very friendly to large scale data.
DOI: 10.6084/m9.figshare.21499929
title: x x x

description: x x x x
DOI: 10.6084/m9.figshare.21499929.v2
title: x x x

description: x x x x
DOI: 10.6084/m9.figshare.21499929.v1
title: method.R

description: <br> ### function for calculating growth synchrony ### fun_syn = function(chron, interval){ syn = data.frame() for(i in 1900:(2014 - interval + 1)){ res = filter(chron, year %in% c(i : (i + interval - 1))) res = res[, colSums(is.na(res)) == 0] %&gt;% select(-year) %&gt;% cor() n = ncol(res) res = res[lower.tri(res)] res = data.frame(year = i + interval - 1, mean = mean(abs(res)), sd = std.error(abs(res)), n = n) syn = rbind(syn, res)} return(syn)} <br> ###### within-population growth syn calculation ###### wps = list() res1 = data.frame() res2 = data.frame()
DOI: 10.17632/559n9zbb7c.1
title: FN-MNIST

description: The Fixational Neuromorphic MNIST dataset is an event-based version of the full MNIST benchmark, where bio-inspired fixational drift movements have been used to drive the camera. Training and test data are provided as separate ZIP archives and each data sample (binary file) contained therein can be loaded using the utility function from the given Python file.
DOI: 10.17632/559n9zbb7c.2
title: FN-MNIST

description: The Fixational Neuromorphic MNIST dataset is an event-based version of the full MNIST benchmark, where bio-inspired fixational drift movements have been used to drive the camera. Training and test data are provided as separate ZIP archives and each data sample (binary file) contained therein can be loaded using the utility function from the given Python file.
DOI: 10.17632/w999vnkdzn.1
title: HRD predictions

description: Predictions of HRD for the in-house and TCGA datasets.
DOI: 10.17632/6jzb3tnzy3.1
title: LINF_330031900

description: protein kinase
Leishmania infantum (strain JPCM5)
DOI: 10.17632/ptftdjfjyv.1
title: Vitamin B5 rewires Th17 cell metabolism via impeding PKM2 nuclear translocation

description:  We validated the interaction between PKM2 and CoA by IP/WB, the immunoblotting showed that CoA strongly interacted with endogenous PKM2. We measured the phosphorylation and nuclear tanslocation of PKM2 with VB5 or CoA treatment.
DOI: 10.17632/9n2t994kh7.1
title: CSIDA part 2

description: This is the part 2 of CSIDA data, including the raw data.
DOI: 10.17632/hnjvy2p4ph.1
title: LINF_330031800

description: MYND finger containing protein
Leishmania infantum (strain JPCM5)
DOI: 10.17632/v47jv6wvr3.1
title: LINF_330032500

description: Rab-GTPase-TBC domain containing protein
Leishmania infantum (strain JPCM5)
DOI: 10.17632/p5wz9tg2mb.1
title: SSU rRNA metabarcode of bacteria in trout cultured in Angara river

description: Composition of bacterial communities associated with cultured trout sampled from a fish farm on Angara river. A chronic bacterial disease of unknown etiology was observed on this fish farm; to identify the pathogen for further studies, visibly diseased and apparently healthy fishes were taken into analysis. The primary goal of this analysis was to identify the pathogen, which turned out to be Flavobacterium psychrophilum. Although the community in diseased fishes is heavily dominated by this bacterium, other bacteria inhabiting trout were also detected.
DOI: 10.17632/r3mcjwb9mb.1
title: LINF_330032400

description: Acetate:succinate CoA transferase
Leishmania infantum (strain JPCM5)
DOI: 10.17632/pwj34nk6bz.1
title: LINF_330032000

description: UDP-glucose 4-epimerase
Leishmania infantum (strain JPCM5)
DOI: 10.17632/z2wj33w435.1
title: A spatially varying model for small area estimates of biomass density across the contiguous United States

description: Data and code to reproduce the results in the like-named paper. Code is an R script that implements a Fay-Herriot model with spatial error and spatially varying regression coefficients to make estimates of above ground biomass density (AGBD) for 64,000 ha hexagons across the contiguous United States. Uses FIA direct estimates along with area predictors from the Global Ecosystem Dynamics Investigation (GEDI) and the NLCD Tree Canopy Cover (TCC) map.

'UShex_SFH_RSE.R' contains the code, and is well-commented, but those unfamiliar with INLA
might want to refer to the free, online book https://becarioprecario.bitbucket.io/spde-gitbook/
in order to fully understand the code. The code, as is, fits the GEDI+TCC Spatial Fay-Herriot model, 
but predictors and spatial effects can be omitted/introduced according to the users desires. 
The later part of the script executes the 10-fold cross-validation study.

'GEDI_HEX.RData' contains the data necessary to fit the GEDI model.
'TCC_HEX.RData' contains the data necessary to fit the TCC model.
Both are needed to fit the GEDI+TCC model. The variables inside are described in the comments
of the R script.

CONUSbiohex2020 is a folder with the shapebundle from Menlove & Healey, 
and is also available at https://daac.ornl.gov/CMS/guides/FIA_Forest_Biomass_Estimates.html#datadescraccess.
It's not necessary for the analysis in the R script, but is useful for spatial plots,
and for comparing to (or using) the post-stratification estimates.
DOI: 10.17632/s9vrhj8tsk.1
title: Supplementary data for manuscript on metabolites extracted from African walnut (Tetracarpidium conophorum) using two different solvents

description: Raw & processed dataset, and mass spectra of the metabolites extracted from walnut using acetonitrile/methanol/water (40:40:20 v/v/v) and methanol/water (80:20 v/v) solvents.
DOI: 10.17632/hh88yrjg4p.1
title: Initial Graphene Structures

description: Initial graphene platelet structures with embedded dislocation prior to thermalization and shear loading. The data can be processed by using the MD software of your choice to thermalize and then shear the respective structures.
DOI: 10.17632/fh6t5n2zf4.1
title: Spanish Language Course Certificate

description: This is my Spanish Language Course Certificate B2.
DOI: 10.17632/v8mbnvx8pv.1
title: RoadRuttingDatasetSekilab

description: Road rutting is a severe road distress that can cause premature failure of road incurring early and costly maintenance costs. Research on road damage detection using image processing techniques and deep learning is being actively conducted in the past few years. However, these researches are mostly focused on detection of cracks, potholes, and their variants. Very few research has been done on the detection of road rutting. This dataset presents a novel road rutting dataset comprising of 949 images and provides both object level and pixel level annotations. For more information on experiments conducted on this dataset, please refer to the article at https://www.researchgate.net/publication/363920770_Road_Rutting_Detection_using_Deep_Learning_on_Images .
DOI: 10.17632/n8hp45bdrj.1
title: Code for analysing intracellular pH on a single cell level

description: Cells were plated in triplicate at 50,000-100,000 cells per well in black wall, flat coverslip bottom µ-plate 96-well plates with a growth area of 0.56 cm2 per well (Ibidi) and were left to attach overnight. They were then incubated in media supplemented with cSNARF1-AM (5 µg/mL, Invitrogen) and the nuclear stain Hoechst-33342 (10 µg/mL, Molecular Probes), for 15 min, and then replaced with medium of varying sodium bicarbonate concentration (twice). Images of fluorescence excited at 377 nm and collected at 447 nm (Hoechst-33342), and of fluorescence excited at 531 nm and collected at 590 nm and 640 nm (cSNARF1), were acquired using Cytation 5 imaging plate reader (Biotek) and its bespoke software. Images were either acquired using a 4x objective, or a 10x objective, as indicated in figure legends. Measurements were performed in an atmosphere of 37 °C and 5% CO2, established in the plate reader. Further analysis of the population distribution of pH data was performed using a MATLAB script. Images saved as stack.tif act as input for the script (supplementary_code_1). cSNARF1 fluorescence ratios were converted into pHi using a calibration curve obtained through the nigericin method. pHi distributions from replicate wells were pooled, and low intensity measurements were removed using a second MATLAB script (Supplementary_Code_2).
DOI: 10.17632/mnkmyffmjh.1
title: Graphene Shear/Tensile Test Results

description: Resulting stress-strain data from the tensile and shear tests performed on graphene platelet structures. The data is given in plain text files with the first colum being the respective simulation time step and the other columns the stress components. Shear test results are given in the sch* folders, tensile tests in the zug* folders. The file mkplots.sh can be used to visualize the data exactly as found in the paper.