cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17868305
title: Conjunto de notas de leitura de processos relativos à ação de "Construção da Casa do Povo de S. Miguel de Rio Torto, Abrantes [1938-1956]"

description: Conjunto de notas de leitura de processos relativos à ação de "Construção da Casa do Povo de S. Miguel de Rio Torto, Abrantes [1938-1956]" existente nos Arquivo Municipal Eduardo Campos, em Abrantes, e na Biblioteca do Gabinete de Estratégia e Planeamento do Ministério do Trabalho, Solidariedade e Segurança Social, em Lisboa.

Registos efetuados em abril de 2024 no âmbito do projeto de investigação ReARQ.IB – Built Environment Knowledge for Resilient, Sustainable Communities: Understanding Everyday Modern Architecture and Urban Design in the Iberian Peninsula (1939-1985) (ERC GA949686) e publicado online em https://arquitecturaaqui.eu/pt/atividades/acoes/35360/construcao-da-casa-do-povo-de-s-miguel-de-rio-torto-abrantes-1938-1956. 

Dados exportados da plataforma Arquitectura Aqui (https://arquitecturaaqui.eu), repositório do referido projeto, em dezembro de 2025.
DOI: 10.15468/dl.d2gqna
title: Occurrence Download

description: A dataset containing 4157 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Letharia vulpina",
 "Country is one of (Norway)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1986",
 "Year is less than or equal to 2025",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is Machine Observation"
 ]
 }
 }
 ]
}

 The dataset includes 4157 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015497-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18112/openneuro.ds007067.v2.2.0
title: spine_fMRI_7T
DOI: 10.5281/zenodo.18632705
title: ФИЗИОЛОГИЧЕСКИЕ МАРКЕРЫ РАННЕЙ ДИАГНОСТИКИ ЗАБОЛЕВАНИЙ

description: Ранняя диагностика заболеваний остаётся ключевой задачей современной медицины. Традиционные клинико-лабораторные методы часто выявляют патологию уже на стадии выраженных морфологических изменений. В то же время физиологические параметры организма изменяются значительно раньше и могут служить ранними маркерами неблагополучия. Целью данного исследования явилась оценка диагностической значимости ряда физиологических показателей (вариабельность сердечного ритма, показатели микроциркуляции, сатурация кислорода, параметры дыхания и вегетативной регуляции) для раннего выявления сердечно-сосудистых, респираторных и метаболических нарушений. В исследовании приняли участие 180 пациентов группы риска и 60 практически здоровых лиц. Выявлено, что изменения вариабельности сердечного ритма, индекса микроциркуляции и дыхательных параметров статистически достоверно предшествуют клиническим проявлениям заболеваний в среднем на 4–8 месяцев.
DOI: 10.5281/zenodo.18632706
title: ФИЗИОЛОГИЧЕСКИЕ МАРКЕРЫ РАННЕЙ ДИАГНОСТИКИ ЗАБОЛЕВАНИЙ

description: Ранняя диагностика заболеваний остаётся ключевой задачей современной медицины. Традиционные клинико-лабораторные методы часто выявляют патологию уже на стадии выраженных морфологических изменений. В то же время физиологические параметры организма изменяются значительно раньше и могут служить ранними маркерами неблагополучия. Целью данного исследования явилась оценка диагностической значимости ряда физиологических показателей (вариабельность сердечного ритма, показатели микроциркуляции, сатурация кислорода, параметры дыхания и вегетативной регуляции) для раннего выявления сердечно-сосудистых, респираторных и метаболических нарушений. В исследовании приняли участие 180 пациентов группы риска и 60 практически здоровых лиц. Выявлено, что изменения вариабельности сердечного ритма, индекса микроциркуляции и дыхательных параметров статистически достоверно предшествуют клиническим проявлениям заболеваний в среднем на 4–8 месяцев.
DOI: 10.5281/zenodo.18632702
title: THE ROLE OF MATHEMATICAL MODELING IN REAL LIFE

description: Mathematical modeling plays an important role in understanding, analyzing, and solving real-world problems in various fields. This paper aims to explore the importance of mathematical modeling as an effective tool for representing real-world phenomena using mathematical concepts and structures. In the Methods section, the study uses a qualitative analytical approach based on a review of the scientific literature and practical examples from economics, engineering, medicine, and environmental research. The results show that mathematical models can help simplify complex systems, predict outcomes, optimize processes, and support decision-making. They are particularly effective in predicting economic trends, simulating physical processes, controlling engineering systems, and analyzing disease outbreaks. The discussion highlights the advantages and limitations of mathematical modeling, emphasizing that the accuracy of the model depends on the assumptions, data quality, and appropriate model selection. In conclusion, the article shows that mathematical modeling is an indispensable tool in modern society, making a significant contribution to scientific development, technological innovation, and solving problems in everyday life.
DOI: 10.5281/zenodo.18632701
title: THE ROLE OF MATHEMATICAL MODELING IN REAL LIFE

description: Mathematical modeling plays an important role in understanding, analyzing, and solving real-world problems in various fields. This paper aims to explore the importance of mathematical modeling as an effective tool for representing real-world phenomena using mathematical concepts and structures. In the Methods section, the study uses a qualitative analytical approach based on a review of the scientific literature and practical examples from economics, engineering, medicine, and environmental research. The results show that mathematical models can help simplify complex systems, predict outcomes, optimize processes, and support decision-making. They are particularly effective in predicting economic trends, simulating physical processes, controlling engineering systems, and analyzing disease outbreaks. The discussion highlights the advantages and limitations of mathematical modeling, emphasizing that the accuracy of the model depends on the assumptions, data quality, and appropriate model selection. In conclusion, the article shows that mathematical modeling is an indispensable tool in modern society, making a significant contribution to scientific development, technological innovation, and solving problems in everyday life.
DOI: 10.15468/dl.kebhqq
title: Occurrence Download

description: A dataset containing 9904 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "TaxonKey is Procambarus clarkii",
 "Country is United States of America",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 9904 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015498-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cruyny
title: Occurrence Download

description: A dataset containing 350 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Kadua affinis",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 350 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015499-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ssq9r5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Poecilia waiapi",
 "DecimalLatitude is not null",
 "DecimalLongitude is not null"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015500-260208012135463/datasets/export for details.
DOI: 10.15468/dl.wjqxbz
title: Occurrence Download

description: A dataset containing 2598 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plathymenia reticulata",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 2598 records from 140 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015501-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14829824
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5281/zenodo.18630536
title: Interprofessional Collaboration in Suicide Prevention: Repeated Cross-Sectional Survey Data (EIS and PIS, Switzerland)

description: Anonymized raw data of our repeated cross-sectional survey
DOI: 10.5281/zenodo.18630537
title: Interprofessional Collaboration in Suicide Prevention: Repeated Cross-Sectional Survey Data (EIS and PIS, Switzerland)

description: Anonymized raw data of our repeated cross-sectional survey
DOI: 10.15468/dl.xxnucs
title: Occurrence Download

description: A dataset containing 388 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bothrops taeniatus"
 ]
}

 The dataset includes 388 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015502-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18632713
title: ФИЗИОЛОГИЯ СТРЕССА И АДАПТАЦИЯ В УСЛОВИЯХ СОВРЕМЕННОЙ ЖИЗНИ

description: Современный ритм жизни характеризуется высокой нагрузкой, постоянным информационным потоком и социальным стрессом. Длительное влияние стрессоров вызывает функциональные изменения в организме, которые могут приводить к развитию сердечно-сосудистых, метаболических и психоэмоциональных нарушений. Цель исследования — изучить физиологические реакции на стресс у взрослых в условиях городской жизни и определить маркеры ранней дисфункции. В исследовании приняли участие 200 человек, из которых 150 — активные работники с высокой социальной и профессиональной нагрузкой, и 50 контрольных лиц с низким уровнем стрессов. Установлено, что у 68% участников группы высокого стресса наблюдались значимые изменения вариабельности сердечного ритма, артериального давления и уровня кортизола, что подтверждает связь хронического стресса с развитием функциональных нарушений.
DOI: 10.5281/zenodo.18632714
title: ФИЗИОЛОГИЯ СТРЕССА И АДАПТАЦИЯ В УСЛОВИЯХ СОВРЕМЕННОЙ ЖИЗНИ

description: Современный ритм жизни характеризуется высокой нагрузкой, постоянным информационным потоком и социальным стрессом. Длительное влияние стрессоров вызывает функциональные изменения в организме, которые могут приводить к развитию сердечно-сосудистых, метаболических и психоэмоциональных нарушений. Цель исследования — изучить физиологические реакции на стресс у взрослых в условиях городской жизни и определить маркеры ранней дисфункции. В исследовании приняли участие 200 человек, из которых 150 — активные работники с высокой социальной и профессиональной нагрузкой, и 50 контрольных лиц с низким уровнем стрессов. Установлено, что у 68% участников группы высокого стресса наблюдались значимые изменения вариабельности сердечного ритма, артериального давления и уровня кортизола, что подтверждает связь хронического стресса с развитием функциональных нарушений.
DOI: 10.4211/hs.78b18403e2034647bd55c03f10366b8b
title: Landslide catalog for upper Skagit in the North Cascades

description: Mapped landslides used to evaluate modeled landslide hazard location in Keck et al. 2025, submitted to WRR on 20250125.

Polygons represent the source areas of all active, shallow-pore-water-driven landslides in the model domain. Shallow landslides were mapped from repeat satellite imagery (1998, 2006, 2013 and 2016) draped over a 30-meter DEM in Google Earth (Google Earth, 2023). The image years that were reliably clear enough to make out details like boulders, scarp edges and changes in vegetation and bare areas included 2013 and 2016 images. Image years 1998 and 2006 were not as clear but were good enough to make out changes in vegetation and bare areas. 
A landslide was considered active if: (1) it formed or enlarged between photos or; (2) it appeared recent (denuded, and void of any vegetation) and could be traced to a colluvial fan or alluvial fan that exhibited evidence of new deposition. New deposition was identified by changes in color and composition of the colluvial/alluvial deposit between photos. A landslide was considered shallow-pore-water-driven if it formed in convergent topography or slopes where a slight increase in pore water pressure might trigger failure (e.g., slopes exceeding the friction angle of the regolith). Deep seated landslides, which were interpreted as all landslides whose geometry appeared to form independent of the surface topography, and rock fall, which were interpretated as topple like failures and formed deposits of a few boulders, were not mapped.
DOI: 10.4211/hs.d3efc527a6b64b9890cfe5154954ce09
title: Compiled data for modeling episodic salinization of Midwestern and Northeastern US rivers by road salt

description: This resource contains data used to understand characteristics of rivers that experience episodic salinization from winter road salting events. These data products represent snapshots of public data compiled to support the AGU Water Resources Research publication, "Episodic Salinization of Midwestern and Northeastern US Rivers by Road Salt" (Platt and Dugan 2025), available at https://doi.org/10.1029/2024WR039496. The code used to generate the data in this resource is available via a reproducible R pipeline published at https://doi.org/10.5281/zenodo.17095176.
DOI: 10.4211/hs.064e5da7690048849e31bf36c524ba7f
title: Virginia Forest - Soil water content, Soil temperature, Electrical conductivity - Jun 2021-Jul 2024

description: This dataset includes volumetric water content (soil moisture, in cubic meter per cubic meter), soil temperature (degrees C) and soil electrical conductivity (mS/cm) measurements from four monitoring locations at the Virginia Forest site (Virginia Coast) for the CZNet Coastal Cluster. Soil moisture, temperature and conductivity were measured continuously in the field at 15-minute intervals with METER Group TEROS 12 sensors and ZL6 dataloggers. Data was measured in 60-minute intervals from Jun2021-Feb 2022. All four locations have sensors measuring from both a shallow (0.1-0.2 m) and deep (0.2-0.3 m) depth interval. No correction was done to the reported values. Gaps in the record are indicated by blank values.
DOI: 10.4211/hs.e99ee3f096964b31add85947894d812c
title: Virginia Forest - DTW, Water Temperature, Specific conductance - Jun 2021-Jul 2024

description: This dataset includes depth to water (m, from ground surface), water temperature (degrees C) and specific conductance (uS/cm) measurements from four monitoring wells at the Virginia Forest site (Brownsville) for the CZNet Coastal Cluster. Pressure, temperature and electrical conductivity were measured continuously in the field at 15-minute intervals with Solinst Levelogger 5 Model 3001s installed in each monitoring well. The Leveloggers were attached to a nylon cord and installed at the approximate depth of the well screen mid-point. Depth to water measurements were converted from Levelogger-measured pressure values. Pressure values were corrected for barometric pressure fluctuations and converted to depth to water values using reference manual depth to water measurements collected at the start and stop of each Levelogger deployment. No correction was done to the temperature values. Specific conductance values were calculated from Levelogger-measured electrical conductivity using the equation given by Standard Method 2510B. Between deployments, each Levelogger was submerged in a calibration solution with a known SC and the real-time reading was recorded. If the real-time reading was +/-5% of the calibration solution concentration, the sensor was calibrated according to manufacturer specifications. SC values were adjusted for sensor drift by adding a correction factor to the sensor-measured value. Leveloggers were occasionally swapped between wells to allow for sensor maintenance and calibration. Because the Leveloggers were periodically stopped to download data before being redeployed, there may be gaps in the record between deployments.
DOI: 10.4211/hs.de8341f1e4544c61b0f0128099cfc08a
title: Metompkin Farm - DTW, Water Temperature, Specific conductance - Jul 2022-Jul 2024

description: This dataset includes depth to water (m, from ground surface), water temperature (degrees C) and specific conductance (uS/cm) measurements from four monitoring wells at the Virginia Agricultural site (Metompkin Farm) for the CZNet Coastal Cluster. Pressure, temperature and electrical conductivity were measured continuously in the field at 15-minute intervals with Solinst Levelogger 5 Model 3001s installed in each monitoring well. The Leveloggers were attached to a nylon cord and installed at the approximate depth of the well screen mid-point. Depth to water measurements were converted from Levelogger-measured pressure values. Pressure values were corrected for barometric pressure fluctuations and converted to depth to water values using reference manual depth to water measurements collected at the start and stop of each Levelogger deployment. No correction was done to the temperature values. Specific conductance values were calculated from Levelogger-measured electrical conductivity using the equation given by Standard Method 2510B. Between deployments, each Levelogger was submerged in a calibration solution with a known SC and the real-time reading was recorded. If the real-time reading was +/-5% of the calibration solution concentration, the sensor was calibrated according to manufacturer specifications. SC values were adjusted for sensor drift by adding a correction factor to the sensor-measured value. Leveloggers were occasionally swapped between wells to allow for sensor maintenance and calibration. Because the Leveloggers were periodically stopped to download data before being redeployed, there may be gaps in the record between deployments. This work was conducted on private property with the cooperation and trust of landowners and farm operators who have requested to remain anonymous.  We have removed select coordinates and information that could be used to identify their operations.
DOI: 10.4211/hs.4c8af0c89d2b4686808bcf9c6f7c0da3
title: Spatially Explicit Agricultural Tile Drainage Maps - US Midwest (SEETileDrain, Wan et al., 2024)

description: The source is a repository of Spatially Explicit Estimate of Tile Drainage (SEETileDrain) products across the US Midwest in 2017 at a 30-m resolution. It includes the binary classification map (tile and non-tile), tile probability (how likely a grid cell is tile-drained). The Python scripts to generate the PAW layers and the R scripts (see also: https://github.com/LuwenWan/SEETileDrain_MidWest) to select variables, implement the random forest model and visualize the figures, are also available. 

In this work, we developed a machine learning model using 31 satellite-derived and environmental variables and trained with 60,938 tile and non-tile ground truth points within the Google Earth Engine cloud computing platform. The results show that our model achieved good accuracy, with 96 % of the points correctly classified and an F1 score of 0.90. When the tile drainage areas are aggregated to the county scale, it agrees well (R-squared = 0.68) with the reported area from the 2017 Ag Census. The product, SEETileDrain (Spatially Explicit Estimate of Tile Drainage), is described in full detail in the manuscript and the supporting information of Wan et al. (2024).  If needed, copies of the tile drainage product can be requested from the corresponding author at luven.wan@gmail.com.

Preferred citation:
L. Wan, A.D. Kendall, J. Rapp, D.W. Hyndman. 2024. Mapping agricultural tile drainage in the US Midwest using explainable random forest machine learning and satellite imagery, Science of the Total Environment. https://doi.org/10.1016/j.scitotenv.2024.175283
DOI: 10.4211/hs.f1957758d24a439ca47e4940bcc0a9f7
title: Illilouette Creek Basin Distributed Air Temperature and Relative Humidity 2015-2021

description: These files contain air temperature and relative humidity in Illilouette Creek Basin, within different post-fire vegetation patches including a wetland, shrub field, and forest. Onset's HOBO U23 Pro V2 temperature and relatively humidity sensors were attached to trees and protected using white plastic radiation shields. Temperatures measured may be impacted by temperature of the tree trunks. These time series can be used to compare air temperature and humidity at different heights above the ground, different canopy covers, and different sides of trees. These data can also be compared to temperature and relative humidity at nearby meteorological stations. Most of these sensors were temporarily removed in order to protect them from the 2017 Empire Fire, but sensor #315 remained in place and shows elevated temperatures on October 16, 2017 due to the fire. See Metadata file for details of sensor locations.
DOI: 10.4211/hs.841f5e85085c423f889ac809c1bed4ac
title: Camels-Chem (collection of stream water chemistry data 1980-2018)

description: The CAMELS-Chem dataset is a comprehensive collection of stream water chemistry data, atmospheric deposition data, and catchment attribute data for 516 minimally impacted headwater catchments across the continental United States. The dataset spans a period of 39 years, from 1980 through 2018, and includes 18 common stream water chemistry constituents, such as Al, Ca, Cl, Dissolved Organic Carbon, Total Organic Carbon, HCO3, K, Mg, Na, Total Dissolved Nitrogen, NO3, Dissolved Oxygen, pH, Si, SO4, and water temperature. Additionally, the dataset provides annual wet deposition loads for several key components. The dataset is based on the existing CAMELS dataset, which provides catchment attribute data such as topography, climate, land cover, soil, and geology. In CAMELS-Chem, this catchment attribute data is paired with atmospheric deposition data from the National Atmospheric Deposition Program and water chemistry data and instantaneous discharge from the US Geological Survey. The dataset also includes paired instantaneous and discharge measurements for all chemistry samples. 
The catchment attribute data files used in the CAMELS-Chem dataset were downloaded from the CAMELS website (https://ral.ucar.edu/solutions/products/camels