cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/wb6r97mb5s.1
title: pyMCD: Python package for searching transition states via the multicoordinate driven method

description: Elucidation of activation barriers is essential to understand the energetics of chemical reactions. Transition states (TSs) are the key information necessary to evaluate activation barriers. Among various methods, the multicoordinate driven (MCD) method is particularly useful for searching TSs because it requires simple inputs but shows high reliability with reasonable computation costs. This method starts from reactants and generates a reaction path by scanning multiple active coordinates until it arrives at the products, eventually leading to a TS and the corresponding activation barrier. Despite its high reliability, however, the source code is not publicly available. Herein, we present a Python package, hereafter referred to as pyMCD that searches for TSs using the MCD method. We slightly revised the original MCD method proposed by Berente and coworkers [1] to improve its computational efficiency while minimizing loss of accuracy. The package is extremely user-friendly, requiring minimal effort from users for input preparation. Moreover, it is well organized, so users can readily customize it for their purposes. The current version has been interfaced with Gaussian and ORCA, but can be interfaced with any quantum chemistry package by slightly modifying the source code. We demonstrated the high reliability of the revised method by testing it with various chemical reactions.
DOI: 10.17632/3jgrhtt4pd.1
title: Proprioception triggers dispersal and immune response under crowdedness

description: data of "Proprioception triggers dispersal and immune response under crowdedness"
DOI: 10.17632/429rszyc65.1
title: Very accurate time propagation of coupled Schrödinger equations for femto- and attosecond physics and chemistry, with C++ source code

description: In this article, I present a very fast and high-precision (up to 33 decimal places) C++ implementation of the semi-global time propagation algorithm for a system of coupled Schrödinger equations with a time-dependent Hamiltonian. It can be used to describe time-dependent processes in molecular systems after excitation by femto- and attosecond laser pulses. It also works with an arbitrary user supplied Hamiltonian and can be used for nonlinear problems. The semi-global algorithm is briefly presented, the C++ implementation is described and five sample simulations are shown. The accompanying C++ source code package is included. The high precision benchmark (long double and float128) shows the estimated calculation costs. The presented method turns out to be faster and more accurate than the global Chebyshev propagator.
DOI: 10.17632/34nfrk36dt.1
title: Vehicle Insurance data

description: The vehicle insurance dataset was obtained from the Ethiopian Insurance Corporation. It is a large dataset that can be used for machine-learning purposes.
DOI: 10.17632/v4gkfx7t8r.1
title: Code for Cleansing by Tight Credit: Rational Cycles and Endogenous Lending Standards, Farboodi-Kondor JFE

description: This is the mathematica code to produce the figures in the paper "Cleansing by Tight Credit:
Rational Cycles and Endogenous Lending Standards" by Maryam Farboodi and Peter Kondor.

No data is inclded.
DOI: 10.17632/gcg645gwhk.1
title: Faecal nutrient deposition of domestic and wild herbivores in an alpine grassland

description: Our main objectives were 1) explore if herbivore faecal nutrient content (C, N, P, and K) and stoichiometry (C/N) differed between herbivore species (chamois, sheep, horse, and cattle) and body size groups in an alpine grassland (Spanish Pyrenees), 2) analyse seasonal differences in faecal nutrient content and stoichiometry of each species, and 3) quantify the amount of nutrients released annually by each herbivore. 
The data folder contains: 1) 1_nutrient_content: data to analyse the differences in faecal nutrient content and stoichiometry of the four herbivore species in an alpine grassland in the Spanish Pyrenees. Other information is also included: body size (small or large), feeding strategy (browser or grazer), digestive system (ruminant or non-ruminant), month and year of collection of the dung, and study area where the dung was collected. 2) 2_nutrient_input: data to quantify the annual nutrient input of each herbivore per each nutrient. This dataset includes information per species about dry dung weight, defecation events per day, days on the field, and extension of the study area. 
The scripts folder contains: 1) 1_models: R script of the statistical analysis to check the differences in faecal nutrient content and stoichiometry among herbivore species and between body sizes. Also, the seasonal nutrient content differences. 2) 2_graphs: R script to create figure2, figure3 and figure4.
DOI: 10.17632/4vj3zyy5d6.1
title: Recent Changes in the Climatological Characteristics of Daily Contiguous Rain Areas over India Mansi Bhowmick, Sandeep Sahany, Ananda Kumar Das

description: Codes for data analysis and plotting.
Processed data is available from first author upon reasonable request.
DOI: 10.6073/pasta/6dc6f16b6f573d017cf21fd1661de051
title: Jornada Basin LTER Cross-scale Interactions Study (CSIS) Block 13 meteorological station: Daily average soil volumetric water content data: 2013 - ongoing

description: Daily Average of 30-minute Soil Volumetric Water Content data at 10 cm at CSIS Block-13. Collection of soil water content data at Jornada LTER Cross-scale Interactions Study (CSIS) blocks, New Mexico, supports the environmental monitoring objectives of the Jornada LTER monitoring program that look at plant-soil water dynamics. Soil volumetric water content is measured every 30 minutes at 10 cm depth at 3 locations at each of the 4 plots per block and averaged for the daily value. The locations in each plot are under bare soil, under perennial grass, and under shrub. Volumetric water content, bulk electrical conductivity, soil temperature, and bulk dielectric permittivity are recorded at an automated meteorological station installed at Jornada LTER CSIS Block-13 site. This is an ONGOING dataset.
DOI: 10.5066/p91h5qoy
title: Data for Regression Models to Estimate Water Use in Providence, Rhode Island, 2014-2021

description: This data release contains input data and programs (scripts) used to estimate monthly water demand for retail customers of Providence Water, located in Providence, Rhode Island. Explanatory data and model outputs are from July 2014 through June 2021. Models of per capita (for single-family residential customers) or per connection (for multi-family residential, commercial, and industrial customers) water use were developed using multiple linear regression. The dependent variables, provided by Providence Water, are the monthly number of connections and gallons of water delivered to single- and multi-family residential, commercial, and industrial connections. Potential independent variables (from online sources) are climate variables (temperature and precipitation), economic statistics, and a drought statistic. Not all independent variables were used in all of the models. The data are provided in data tables and model files. The data table RIWaterUseVariableExplanation.csv describes the explanatory variables and their data sources. The data table ProvModelInputData.csv provides the monthly water-use data that are the independent variables and the monthly climatic and economic data that are the dependent variables. The data table DroughtInputData.csv provides the weekly U.S. drought monitor index values that were processed to formulate a potential independent variable. The R script model_water_use.R runs the models that predict water use. The other two R scripts (load_preprocess_input_data.R and model_water_use_functions.R) are not run explicitly but are called from the primary script model_water_use.R. Regression equations produced by the models can be used to predict water demand throughout Rhode Island.
DOI: 10.6073/pasta/934db83b139e377b17b285b55c1e891b
title: Jornada Basin LTER Cross-scale Interactions Study (CSIS) Block 13 meteorological station: Daily summary data: 2013 - ongoing

description: This data package contains hourly air temperature, relative humidity, wind speed, wind direction, and precipitation summary data from Jornada Basin LTER Cross Scale Interactions Study (CSIS) Block-13 met station. Air temperature, relative humidity, wind speed, wind direction, and precipitation are measured and calculated at an automated meteorological station connected to a 900 MHz spread spectrum wireless network. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. Measurements are aggregated at intervals of 5, 30, 60 minutes and daily, with precipitation additionally provided with 1 second aggregation during precipitation events. The met station variables measured include air temperature, precipitation, relative humidity, wind direction, wind speed. Precipitation is not measured at Block 1 and Block 12 because of proximity to Block 2 and Block 13, respectively . This is an ONGOING dataset.
DOI: 10.6084/m9.figshare.23706018
title: Myeloid dickkopf-1 fuels neurovascular and neuroimmune alterations in ischemic stroke. (Supplementary information)

description: Myeloid dickkopf-1 fuels neurovascular and neuroimmune alterations in ischemic stroke, Supplementary information <br> Supplementary information 1 : Original western blot for PSD95 and SHANK3. <br> Supplementary information 2 : Different gene expression among groups used to generate volcano plot. <br> Supplementary information 3 : RNA_seq raw data. <br> Supplementary information 4 : Used to generate GO analyses.
DOI: 10.6084/m9.figshare.23706018.v1
title: Myeloid dickkopf-1 fuels neurovascular and neuroimmune alterations in ischemic stroke. (Supplementary information)

description: Myeloid dickkopf-1 fuels neurovascular and neuroimmune alterations in ischemic stroke, Supplementary information <br> Supplementary information 1 : Original western blot for PSD95 and SHANK3. <br> Supplementary information 2 : Different gene expression among groups used to generate volcano plot. <br> Supplementary information 3 : RNA_seq raw data. <br> Supplementary information 4 : Used to generate GO analyses.
DOI: 10.6084/m9.figshare.23713047
title: Groundwater Residence Time Compilation for Precambrian Rocks

description: Residence times estimates from noble gases are provided for various locations in Canada, Finland, Sweden and South Africa along with porosities. Depth of samples are documented.
DOI: 10.21223/lijfeh
title: Variety Labeler for Image Recognition

description: A prototype was developed for accurately labeling different varieties of Peruvian potatoes from digital images. Users can easily add labels for four native potato types (Peruanita, Amarilla del Centro, Huayro Rojo, and Huamantanga), with each label distinguished by a unique color. The labeler automatically generates bounding boxes around the potatoes, which can be adjusted for precise fitting. Once labeling is completed, the information is saved within the image, and the total number of bounding boxes is displayed for each potato photo in the system. The labeler's architecture comprises a frontend implemented in Vite React, deployed on Vercel, and connected to the backend through Axios. The backend is built with Node, deployed on Heroku, and incorporates New Relic and Sequelize ORM for efficient operations. It is connected to a PostgreSQL database for data persistence. Additionally, the information is stored in AWS.
DOI: 10.17632/jvpbh5bygv.2
title:  Geochronological data of Paleozoic rocks from the Olkhon Terrane (southern Siberia)

description: This supporting material contains two supplemental tables (Table S1 to S2) and a supplemental figure (Figure S1). Table S1 shows the LA-ICP-MS monazite and zircon U-Pb data for the key samples of the Olkhon Terrane. Table S2 displays the biotite 40Ar/39Ar stepwise heating data of the Olkhon Terrane. Figure S1 shows the BSE images of monazite grains and CL images of zircon grains of LA-ICP-MS analyzed.
DOI: 10.17632/7nh3f55w2s.1
title: QOL in NMSC Supplemental File 1

description: This supplemental file outlines detailed methods for the manuscript titled "Health Utilities Associated with Nonmelanoma Skin Cancer".
DOI: 10.17632/9rdv3r3xvc.1
title: Nagasaka et al., 2023 MolCell

description: unprocessed Western blot and gel images
DOI: 10.6073/pasta/7db12d87ce02f5fce94f2b7c206490c6
title: Jornada Basin LTER Cross-scale Interactions Study (CSIS) Block 14 meteorological station: 30-minute summary data: 2017 - ongoing

description: This data package contains 30-minute air temperature, relative humidity, and wind summary data from Jornada Basin LTER Cross Scale Interactions Study (CSIS) Block-1 met station. Average air temperature, relative humidity, wind speed, wind direction, and precipitation are measured and calculated at an automated meteorological station connected to a 900 MHz spread spectrum wireless network. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. Measurements are aggregated at intervals of 5, 30, 60 minutes and daily, with precipitation additionally provided with 1 second aggregation during precipitation events. The met station variables measured include air temperature, precipitation, relative humidity, wind direction, wind speed. Precipitation is not measured at Block 1 and Block 12 because of proximity to Block 2 and Block 13, respectively. This is an ONGOING dataset.
DOI: 10.6073/pasta/1e0b6ebbe1bd8398766decab95de4bc3
title: Jornada Basin LTER Cross-scale Interactions Study (CSIS) Block 14 meteorological station: 5-minute summary wind and air temperature data: 2013 - ongoing

description: This data package contains 5-minute air temperature and wind summary data from Jornada Basin LTER Cross Scale Interactions Study (CSIS) Block-14 met station. Average air temperature, wind speed, and wind direction are measured and calculated at an automated meteorological station connected to a 900 MHz spread spectrum wireless network. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This is a subset of baseline weather data collected at the 15 Jornada Basin LTER CSIS study blocks, New Mexico. Measurements are aggregated at intervals of 5, 30, 60 minutes and daily, with precipitation additionally provided with 1 second aggregation during precipitation events. The met station variables measured include air temperature, precipitation, relative humidity, wind direction, wind speed. Precipitation is not measured at Block 1 and Block 12 because of proximity to Block 2 and Block 13, respectively . This is an ONGOING dataset.
DOI: 10.5281/zenodo.8165307
title: Data for the paper of "Does Government Environmental Audit Promote Green Transformation? Evidence from China's High-carbon Enterprises"

description: This study selected listed companies in high-carbon industries in the A-share market of China from 2013 to 2019 as the initial sample. The specific screening process is as follows: Firstly, based on the "China Listed Company Carbon Emission Ranking (2021)" jointly released by the "Caijing" magazine and China Carbon Investment Group, which includes thirteen high-energy consumption and heavily polluting industries such as petrochemicals, chemicals, building materials, steel, non-ferrous metals, papermaking, electricity, aviation, mining, fermentation, textiles, brewing, and pharmaceuticals (Yang et al., 2020), the top 100 A-share companies in terms of carbon emissions on the ranking were identified. Then, according to the industry classification standards of the China Securities Regulatory Commission in 2012, the industries in which these companies are classified were determined. Specifically, 11 industries including electricity, non-metallic mineral products, air transportation, ferrous metal smelting and rolling processing, coal mining and washing, petroleum processing, coking and nuclear fuel processing, and non-ferrous metal smelting and rolling processing were selected as high-carbon industries. To ensure the robustness of the results, ST, *ST companies, and samples with missing variable values were further excluded, resulting in a final sample of 2344 data observations. The data on GEA were manually compiled from the "China Audit Yearbook," while the data on green patent applications by listed companies were sourced from the CNRDS database. Other data were obtained from the CSMAR database. To eliminate the potential impact of outliers on the research results, this study winsorized continuous variables at the 1st and 99th percentiles. Data processing and analysis were conducted using Stata 16 and Excel 2021 software.
DOI: 10.5281/zenodo.8165306
title: Data for the paper of "Does Government Environmental Audit Promote Green Transformation? Evidence from China's High-carbon Enterprises"

description: This study selected listed companies in high-carbon industries in the A-share market of China from 2013 to 2019 as the initial sample. The specific screening process is as follows: Firstly, based on the "China Listed Company Carbon Emission Ranking (2021)" jointly released by the "Caijing" magazine and China Carbon Investment Group, which includes thirteen high-energy consumption and heavily polluting industries such as petrochemicals, chemicals, building materials, steel, non-ferrous metals, papermaking, electricity, aviation, mining, fermentation, textiles, brewing, and pharmaceuticals (Yang et al., 2020), the top 100 A-share companies in terms of carbon emissions on the ranking were identified. Then, according to the industry classification standards of the China Securities Regulatory Commission in 2012, the industries in which these companies are classified were determined. Specifically, 11 industries including electricity, non-metallic mineral products, air transportation, ferrous metal smelting and rolling processing, coal mining and washing, petroleum processing, coking and nuclear fuel processing, and non-ferrous metal smelting and rolling processing were selected as high-carbon industries. To ensure the robustness of the results, ST, *ST companies, and samples with missing variable values were further excluded, resulting in a final sample of 2344 data observations. The data on GEA were manually compiled from the "China Audit Yearbook," while the data on green patent applications by listed companies were sourced from the CNRDS database. Other data were obtained from the CSMAR database. To eliminate the potential impact of outliers on the research results, this study winsorized continuous variables at the 1st and 99th percentiles. Data processing and analysis were conducted using Stata 16 and Excel 2021 software.
DOI: 10.3886/e192847
title: Replication Package: Incidental Adaptation: The Role of Non-climate Regulations

description: Replication package for all analysis completed for the research article: Incidental Adaptation: The Role of Non-climate Regulations
DOI: 10.3886/e192847v1
title: Replication Package: Incidental Adaptation: The Role of Non-climate Regulations

description: Replication package for all analysis completed for the research article: Incidental Adaptation: The Role of Non-climate Regulations
DOI: 10.6073/pasta/a49460f08bfe741678d056d82f3027ee
title: Jornada Basin LTER Cross-scale Interactions Study (CSIS) Block 14 meteorological station: 1-hour summary data: 2017 - ongoing

description: This data package contains hourly air temperature, relative humidity, wind speed, wind direction, and precipitation summary data from Jornada Basin LTER Cross Scale Interactions Study (CSIS) Block-14 met station. Air temperature, relative humidity, wind speed, wind direction, and precipitation are measured and calculated at an automated meteorological station connected to a 900 MHz spread spectrum wireless network. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. Measurements are aggregated at intervals of 5, 30, 60 minutes and daily, with precipitation additionally provided with 1 second aggregation during precipitation events. Precipitation is not measured at Block 1 and Block 12 because of proximity to Block 2 and Block 13, respectively . This is an ONGOING dataset.
DOI: 10.18112/openneuro.ds003568.v1.0.4
title: Mood induction in MDD and healthy adolescents
DOI: 10.5066/p97ywd2d
title: Geospatial files and tabular exposure estimates of sinkhole susceptibility for counties in the conterminous United States for current conditions and projections for the years 2070-2079 - Overview

description: These datasets support the conclusions in the journal article entitled "Current and future sinkhole susceptibility in karst and pseudokarst areas of the conterminous United States" as described in the abstract below: Sinkholes in karst and pseudokarst regions threaten infrastructure, property, and lives. We mapped closed depressions in karst and pseudokarst regions of the conterminous United States (U.S.) from 10-meter-resolution elevation data using high-performance computing, and then created a heuristic additive model of sinkhole susceptibility that also included nationally consistent data for factors related to geology, soils, precipitation extremes, and development. Maps identify potential sinkhole hotspots based on current conditions and projections for 50 years into the future (the years 2070-2079) based on climate change and urban development scenarios. Areas characterized as having either high or very high sinkhole susceptibility contain 94-99% of known or probable sinkhole locations from three U.S. state databases. States and counties with the highest amounts and percentages of land in zones of highest sinkhole susceptibility are identified. Projected changes in extreme precipitation and development did not substantially change current hotspots of highest sinkhole susceptibility. Results provide a uniform index of sinkhole potential that can support national planning, instead of existing assessments produced through various methods within individual states or smaller areas.
DOI: 10.5066/p93u3b3e
title: Long-term soil carbon data and accretion from four marsh types in Mississippi River Delta in 2015

description: The Mississippi River Deltaic Plain has extensive marsh habitats (fresh, intermediate, brackish, and saline) where soil cores were collected to a depth of 100 cm at 24 sites to assess long-term carbon accumulation rates and coast-wide burial rates. Each core was sectioned into 2-cm depth intervals, and select intervals were analyzed for percent moisture, bulk density, total carbon, and radionuclide (137Cs and 210Pb).
DOI: 10.25345/c51r6nb01
title: MassIVE MSV000092485 - The Proteogenomics of Prostate Cancer Radioresistance
title: In Prostate cancer, aggressive radioresistant relapses can arise, and the molecular underpinnings of radioresistance are unknown. Modern clinical practice is evolving to deliver the same dose of radiation in fewer fractions (hypofractionation). We therefore analyzed genomic, transcriptomic and proteomic data to characterize the determinants of prostate cancer radioresistance in cells treated with both conventionally fractionated and hypofractionated radiotherapy. Independent of fractionation schedule, resistant to radiotherapy involved massive genomic instability and abrogation of DNA mismatch repair. Specific prostate cancer driver genes were modulated at the RNA and protein levels, with distinct subcellular responses to radiotherapy. Conventional fractionation led to a far more aggressive biomolecular response than hypofractionation.
DOI: 10.6084/m9.figshare.23712933
title: data.nc

description: Sample oceanic dataset from Dr. Lei Liu
DOI: 10.6084/m9.figshare.23712933.v2
title: data.nc

description: Sample oceanic dataset from Dr. Lei Liu
DOI: 10.6084/m9.figshare.23712933.v1
title: data.nc

description: Sample oceanic dataset from Dr. Lei Liu