cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/7vn837fkhw
title: Online Micro Intervention for mood improvement dataset

description: The aim of the current study is to improve the understanding of the effects of behavioral activation (BA) online micro intervention targeting enjoyment levels and mood. The hypotheses were to: 1. explore the association between confidence, motivation, activities, and mood; 2. analyze the effect of number and type of activities (Pleasant, Mastery, and Meaningful) on mood and enjoyment levels; 3. evaluate the immediate impact of the brief internet intervention on confidence and motivation to improve one’s mood; and 4. determine if levels of engagement with the intervention have an effect on participants’ outcomes.

Participants were recruited from the United States and aged 18 and older from Amazon Mechanical Turk. Eligible participants filled out a demographic questionnaire, mood questions, confidence questions, motivation questions, and activity level questions.  All participants were then randomly assigned into one of two conditions: intervention condition or the waitlist control (WLC) condition. 

The participants in the WLC were directed to a screen thanking them for their participation. Participants in the intervention condition proceeded to a webpage with psychoeducation on using behavioral activation to improve mood. These participants then completed an activity scheduling exercise wherein the participants selected the activities that they would like to engage in throughout the week. Participants in the intervention conditions were then asked follow-up questions regarding their current mood, confidence, and motivation. 

A regression analysis showed that confidence and motivation were significantly associated with mood. Additionally, the total number of activities reported in the last two days was associated with participants' current mood and current enjoyment. When splitting up the types of activities, mastery and meaningful activities improved mood but not pleasant activities. Pleasant and meaningful activities impacted enjoyment but not mastery activities.
For individuals in the active condition, there was a significant increase in confidence but not motivation from pre to immediate post intervention. Those who scheduled at least one activity in the calendar showed a significant increase in motivation and confidence, but there was no significant increases for those that did not schedule activities. In addition, a mediation analysis found that confidence mediated the relationship between total activities and current mood. Additionally, motivation mediated the affect between total activities and current mood.
DOI: 10.17632/p4zt8vfdjv
title: Characterization of metabolic features derived from the non-polar metabolite UHPLC-QTOF dataset of Jaspis sp. collected from the waters off Pulau Banggi, Sabah, Malaysia: UHPLC-QTOF Dataset

description: This dataset contains a list of metabolic features detected from the metabolite survey of Jaspis sp. isolated from the waters Pulau Banggi, Sabah, Malaysia. The frozen Jaspis sp. was freeze dried and homogenized, after which the non-polar metabolites were extracted using Folch's extraction buffer with modifications. The extracted non-polar metabolites, blank, and non-polar phase of the extraction buffer were subjected to UHPLC-QTOF profiling in both positive and negative modes. After removing the metabolic features detected in the Jaspis sp. sample that were also detected in the blank and non-polar phase of the extraction buffer, the remaining detected metabolic features were clustered and the representative metabolic features (with the highest detected intensity) were tentatively identified using a combination of MS2 spectral database search (with various MS2 spectral databases) as well in silico compound identification.
DOI: 10.6084/m9.figshare.24994206.v1
title: WB_Figure1

description: western blot
DOI: 10.6084/m9.figshare.26649703.v1
title: Number of NIH Funded papers with a link to a dataset - based on Data Citation Corpus

description: We at Digital Science have been looking at the Data Citation Corpus, to dig deeper into data citation counts.The first release is based on a seed file that includes data citations from the following sources:Data citations from DataCite and Crossref DOI metadata, via Event Data.Data citations from the CZI Science Knowledge Graph, identified via a Named Entity Recognition model algorithm that searches for mentions to datasets in the full text of journal articles and preprints in Europe PMC.So we are basically looking at papers that have a link to a DataCite DOI or accession number.By combining this dataset with Dimensions.ai data in Google Big Query, we we're able to add more dimensions to the dataset (pardon the pun), such as funder or institution. The Data Citation Corpus only gave us about 70% of the paper links that were resolvable DOIs. This should improve over time.This allows us to track how well things like the NIH open data policy is encouraging linking to datasets from papers.
DOI: 10.6084/m9.figshare.27139062.v1
title: PPG signals in .TXT files

description: This information is related to the project "PPG-Based Cholesterol Assessment," which showcases different PPG signals along with the cholesterol levels of the subjects. The purpose is to validate techniques or tools for estimating total cholesterol levels in the blood using the PPG signal.
DOI: 10.6084/m9.figshare.3523649.v1
title: Appendix A. A table listing studies used in the analysis of C:N:P ratios.

description: A table listing studies used in the analysis of C:N:P ratios.
DOI: 10.17632/svgj43n3ct
title: LINF_190018800

description: MBOAT family member; Leishmania infantum (strain JPCM5)
DOI: 10.6084/m9.figshare.26028622.v1
title: GeoGPT-Data-Release

description: None
DOI: 10.6084/m9.figshare.28555010.v1
title: <b>Evidence for a push-pull interaction between superior colliculi in monocular dynamic vision mode</b>

description: A superior colliculus (SC) push-pull interaction during the dynamic vision mode upon monocular stimulation was revealed with functional MRI and brain lesions in key regions with strong feedback connections to the SC.
DOI: 10.6084/m9.figshare.28824389.v1
title: Exploring Mitochondrial Genome Sequence of Swamp deer subspecies (Rucervus duvaucelii): Comparative and Phylogenetic insights

description: The <i> </i>close linkages between the three subspecies of the genus Rucervus was establisied by complete mitogenome analysis. The G+C content of the transfer RNA (tRNA) genes ranged from 20.3% (<i>trn</i><i>Arg</i>) to 45.2% (<i>trn</i><i>Asn</i>). Two repeated hepta nucleotide motifs (‘ttttccc’ and ‘gtacata’) were observed in the control region. The <i>atp8</i> gene presented the highest evolutionary rate, with a dN/dS ratio of (0.348) whereas <i>cox1</i> presented the lowest ratio (0.0106).
DOI: 10.6084/m9.figshare.7636193.v6
title: A gridded dataset of belowground autotrophic respiration from 1980 to 2012 in global terrestrial ecosystems upscaling of observations

description: This data repository contains (1) yearly global autotrophic respiration (RA) dataset from 1980 to 2012 with a spatial resolution of 0.5°; (2) original field observations to develop Random Forest (RF) model; (3) main R codes to produce RA database.Model description:The globally gridded RA database was developed by Random Forest (RF) with 449 field observations (see “dataset.csv” in this repository, updated from Bond-Lamberty and Thomson, 2018) using 11 global variables, including gridded temperature, precipitation, diurnal temperature range, potential evapotranspiration, Palmer Drought Severity Index, nitrogen deposition, downward shortwave radiation, soil carbon content, soil nitrogen density, soil water content, land cover. <br>Dataset information:Dataset name: “Respiration_autotrophic_belowgroud_glob_1980_2012_yr_half_dgree.nc”Which means globally belowground autotrophic respiration from 1980 to 2012 with a spatial resolution of 0.5° at a yearly step.Units: g C m<sup>-2</sup> yr<sup>-1</sup>Format: network Common Data Form (netCDF)Spatial coverage: 90S-90N, 180W-180EThe “dataset.csv” file is the field observation from peer review publications combining Global Soil Respiration Database (SRDB v4, Bond-Lamberty and Thomson, 2018), which is publicly available at https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1578. Besides, The database was further updated using observations collected from the China Knowledge Resource Integrated Database (www.cnki.net) up to November 2018 according to the criteria of SRDB. This dataset is provided in format of “.csv”.<br>R codes:10fold_CV_RA.txt: 10-fold CV for RAAnnual_variability_RA.txt: annual variability for global RACMP_RA.txt: comparing RF-RA and Hashimoto2015-RA using CMP approachRa_DD_CC_plot.txt: plotting the comparing results from CMPRA_MAT_MAP_anomaly.txt: plotting and modelling the relationship between temperature/precipitation anomalies and RA RGB_plot.txt: deriving RGB plot to detecting the relative importance of temperature, precipitation and shortwave radiation. <br>
DOI: 10.17632/5j5vs5ch89
title: Deciphering Tumour Microenvironment of Liver Cancer through Deconvolution of Bulk RNA-seq Data with Single-cell Atlas

description: For the reproducibility of the paper "Deciphering Tumour Microenvironment of Liver Cancer through Deconvolution of Bulk RNA-seq Data with Single-cell Atlas"
DOI: 10.17632/tpcdgw7h6m
title: Activating alternative transport modes in a multidrug resistance efflux pump to confer chemical susceptibility

description: Small multidrug resistance (SMR) transporters perform coupled antiport of protons and toxic substrates, contributing to antibiotic resistance through efflux of these compounds from the bacterial cytoplasm. Extensive biophysical studies of the molecular transport mechanism of the E. coli SMR transporter EmrE indicate that it should also be capable of performing proton/drug symport or uniport, either of which will lead to drug susceptibility rather than drug resistance in vivo. Here we show that EmrE does indeed confer susceptibility to some small molecule substrates in the native E. coli in addition to conferring resistance to known polyaromatic cation substrates. In vitro experiments show that substrate binding at a secondary site triggers uncoupled proton uniport that leads to susceptibility. These results suggest that the SMR transporters provide one avenue for bacterial-selective dissipation of the proton-motive force. This has potential for antibiotic development and disruption of antibiotic resistance due to drug efflux more broadly.
DOI: 10.6084/m9.figshare.12794075.v1
title: G-RUN ENSEMBLE

description: G-RUN ENSEMBLE (pronounced GeRUN) consists in a multi-forcing global reanalysis of monthly runoff rates created by means of machine learning and a global collection of river discharge observations. G-RUN ENSEMBLE allows for an unprecedented view on global terrestrial water dynamics on time scales ranging from months to a full century. Quantification of the uncertainty stemming from the atmospheric forcing data makes G-RUN ENSEMBLE the ideal candidate for reliable and robust water resources assessments.<br>------------------------------------------------------------------------------<b>File description </b><b><br></b>- <i>G-RUN_ENSEMBLE_MMM.nc </i>covers<i> </i>the time period from 1902 to 2019 and provide the<i> </i>median of the G-RUN ENSEMBLE members. If you want to rely on one single estimate this is likely the file you are interested in.<br>- <i>G-RUN_ENSEMBLE_MEMBERS.zip </i>contains ensemble mean reconstructions for 21 different atmospheric forcing datasets. The time range depends on the considered forcing.<br>- Each remaining file called <i>G-RUN_ENSEMBLE_*.zip (</i><i></i>where * denotes the acronym of the atmospheric forcing dataset used to force the model)<i>, </i>contains 25 runoff reconstructions obtained by training models on different subsets of the available runoff observations.<br><b> </b>------------------------------------------------------------------------------<br><b>References</b><br>- Ghiggi, G., Humphrey, V., Seneviratne, S. I., & Gudmundsson, L. (2021). G-RUN ENSEMBLE: A multi-forcing observation-based global runoff reanalysis. Water Resources Research, 57(5), e2020WR028787. https://doi.org/10.1029/2020WR028787<br><br>- Ghiggi, G., Humphrey, V., Seneviratne, S. I., & Gudmundsson, L. (2019). GRUN: an observation-based global gridded runoff dataset from 1902 to 2014. <i>Earth System Science Data</i>, <i>11</i>(4), 1655–1674. https://doi.org/10.5194/essd-11-1655-2019 <br>
DOI: 10.6084/m9.figshare.12894386.v1
title: Gene database of Thermotoga maritima MSB8

description: <i>Thermotoga maritima </i>is a thermophile able to survive at temperatures of 80 <sup>o</sup>C in water. This resource sought to provide foundational information about the genetic makeup of this organism through parsing its annotated genome sequence downloaded from Genbank. Comprising gene name, gene function, and gene sequence, the resource should find use in functional genomics workflow seeking to postulate hypothesis concerning the evolutionary processes that led to ability to survive under thermophilic conditions by this thermophile.
DOI: 10.6084/m9.figshare.19419506.v1
title: carbon-monitor-cities-data-v1.zip

description: Timely monitoring of CO2 emissions from fossil fuel combustion and cement production are fundamental prerequisites to understanding the global carbon cycle and designing evidenced-based policies for reducing carbon emissions. Here we provided daily CO2 emission data record started from Jan. 1st 2019. The dataset uncovered the daily CO2 dynamics through daily, weekly and seasonal variations as well as the change of daily CO2 due to the holiday events and the impact of COVID-19 pandemic. Such near-real-time CO2 dataset would be of great advantage to further monitoring the human activities and to capture the impacts of COVID-19 for long term.<br><br>Dataset for:Carbon Monitor Cities, near-real-time daily estimates of CO2 emissions from 1500 cities worldwide<br>
DOI: 10.6084/m9.figshare.3422788.v1
title: hSSB1-ssDNA structural model (lowest energy)

description: PDB coordinates of a molecular model of a complex between the protein hSSB1 and single-stranded DNA (ssDNA)<br><br>if used please cite:<br>------------------------<br>Christine Touma, Ruvini Kariawasam, Adrian X. Gimenez, Ray E. Bernardo, Nicholas W. Ashton, Mark N. Adams, Nicolas Paquet, Tristan I. Croll, Kenneth J. O’Byrne, Derek J. Richard, Liza Cubeddu and Roland Gamsjaeger (2016); A structural analysis of DNA binding by hSSB1 (NABP2/OBFC2B) in solution; Nucleic Acids Research; doi:10.1093/nar/gkw617<br>
DOI: 10.17632/cwcbfjvwzz
title: Alas Strait Vessel Mounted ADCP Dataset

description: Dataset of Ocean Current Profile from field measurement in Alas Strait, Indonesia in September 2022. The data are acquired using ADCP along cross-sectional survey lines, deployed downward from the moving vessel, and recorded using WinRiver II software.
DOI: 10.17632/tfn8ycrds3
title: Current knowledge on dietary studies of amphibians in Colombia: research gaps and trends

description: Trophic interactions are essential components of population and community structuring. Amphibians are primarily a generalist predator group and are essential in the energy transformation chain in different ecosystems globally. Many amphibian species lack any basic information about diet or prey consumption, which is essential for understanding ecological requirements, changes in the natural history of species and populations, the impact of habitat modification, and to develop conservation strategies. We present current knowledge on amphibian diets in Colombia—the second most diverse and endemic rich, and the most threatened nation for amphibians—to determine: (a) the number of species studied and their spread across families and genera; (b) the temporal and regional patterns in scientific productivity on trophic ecology, and (c) the trends of topics studied associated with trophic ecology in Colombian amphibians. We found 70 published studies on amphibian trophic ecology between years 1914 and 2022, spanning 100 amphibian species. The Andean region is the best represented, and the Amazon and Orinoco the least. The topics most frequently studied are the prey items consumed and ontogeny, followed by a predominance of systematic and taxonomy, and land-use change impacts. Forty-one prey items were consumed, with invertebrates being the best represented group. While the development of information on dietary ecology has recently increased, knowledge remains limited, with a significant information gap for many Colombian species in different regions. This synthesis is a starting point to identify research gaps for amphibian diet in Colombia, and ultimately for implementing conservation strategies in Colombian amphibians.
DOI: 10.17632/vg2vhrhwhc
title: Data for: The effect of stepwise increasing of water injection rates on enhanced oil recovery after preformed particle gel flooding

description: Used for argumentative arguments and experimental explanations of the article.
DOI: 10.6084/m9.figshare.21656399.v1
title: Legislative Oversight of EU Agencies through Hearings: Police Patrol vs Fire Alarm?

description: Dataset of hearings of of EU agencies taking place in EU agencies' parent committees during the 8th parliamentary term + accompanying dataset of control variables on agency characteristics.
DOI: 10.6084/m9.figshare.23542632.v1
title: Crime risk prediction incorporating geographical spatiotemporal dependency into machine learning models

description: Crime risk prediction incorporating geographical spatiotemporal dependency into machine learning models
DOI: 10.17632/z36fppc77v
title: Bangladesh Drug Use and Social Influence Dataset (BDSID) - 2025

description: This dataset contains survey responses related to drug addiction analysis among individuals from the Sylhet and Dhaka divisions of Bangladesh. The data was collected through a structured questionnaire using Google Forms. A total of 1,624 responses were recorded, capturing demographic information, perceptions about drug use, social influences, and personal experiences regarding substance use. The dataset is intended to support research on drug addiction patterns, influencing factors, and potential preventive measures.

Data Collection Method:
• Survey Type: Online survey (Google Forms)
• Respondents: Individuals from Sylhet and Dhaka divisions, Bangladesh
• Total Responses: 1,624

Data Attributes: 
The dataset consists of multiple variables divided into three main sections:
1. Demographics: Age, gender, education level, living arrangement
2. Perception & Social Environment: Views on drug use, social circle, family relationships, financial condition, suicidal thoughts, and exposure to drug users
3. Drug Use & Influencing Factors: Drug use history, reasons for initiation, types of substances used, frequency of usage, occasions for drug use, willingness to try drugs, and perceived control over substance use

Potential Use Cases:
• Understanding drug addiction trends in Bangladesh
• Identifying risk factors associated with substance abuse
• Developing targeted intervention strategies
• Analyzing the relationship between mental health and drug use

Ethical Considerations: 
The dataset is anonymized to protect respondents' identities. It is intended for research purposes only, and any use should adhere to ethical guidelines for data handling and analysis.
DOI: 10.6084/m9.figshare.19921358.v1
title: Science teaching in early childhood education: a ludic proposal in the approach to science, technology and society (STS)

description: Abstract This study aimed to analyze the contributions of the relationship between ludicity and STS Approach to science teaching in Early Childhood Education. Following a qualitative approach to pedagogical intervention, ludic activities were developed concerning the topic of school environment with a kindergarten II class in the city of Belém, Pará state, Brazil. It was found that STS principles emerged, fostering a problematization of social issues by children, their participation in decisions on matters related to their daily lives, as well as the construction of attitudes and values related to the care for the environment, thus enabling interdisciplinary, contextualized, and dialogical teaching of sciences, in which ludicity is seen as a foundation element for the implementation of STS interactions. We can conclude that an STS approach contributes to children’s scientific education by stimulating criticism and their development for the exercise of citizenship, considering the specificities of this stage of human development.
DOI: 10.6084/m9.figshare.3176152.v1
title: dataset328.sav

description: Dataset for neuropathy and balance article
DOI: 10.6084/m9.figshare.5897551.v1
title: Two Phase Flow Matlab Code

description: The MATLAB code was programmed for simulating two-phase flow (CO2 - brine) in rough fractures.
DOI: 10.17632/3sb447pkr8
title: Good And Bad Classification Of Laddu

description: The project "Good and Bad Classification of Laddu" involves a dataset containing 1,000 samples of Laddus, evenly split between two classes: 500 labeled as "Good" and 500 labeled as "Bad." The primary objective of the dataset is to build and evaluate machine learning models that can accurately classify a given Laddu as either good or bad based on various features.

Dataset Overview:
Total Samples: 1,000
Class Distribution:
Good Laddus: 500 samples
Bad Laddus: 500 samples
Features: The dataset contains multiple features that represent the physical, chemical, and sensory properties of each Laddu sample. These features may include but are not limited to:
Physical Characteristics: Size, weight, color, and texture of the Laddu. These features are often determined through sensory evaluations and could include measures such as smoothness, roundness, firmness, and visual appeal.
Chemical Composition: Nutrient values such as moisture content, fat percentage, sugar levels, and the presence of any additives or preservatives.
Sensory Features: Attributes such as taste, aroma, and overall palatability, which can be subjectively scored by experts or consumers on a rating scale.
Defect Indicators: Features that explicitly signal the presence of undesirable characteristics like improper cooking, spoilage, contamination, or ingredient imbalance.
Data Structure:
Each row in the dataset represents one Laddu sample, and the columns correspond to the extracted features that describe the sample. The final column will contain the label (either "Good" or "Bad") corresponding to the quality classification of the Laddu.

Feature Columns: F1, F2, ..., Fn (representing various features)
Label Column: Class (0 for Bad, 1 for Good)
Project Goals:
The primary goal of this project is to train a classification model that can differentiate between good and bad Laddus based on the given features. The project will involve the following key tasks:

Data Preprocessing: Handling missing values, normalizing features, and possibly performing feature engineering to derive new, informative variables.
Exploratory Data Analysis (EDA): Understanding the distribution of features for good and bad samples, identifying key differences, and visualizing trends or patterns.
Model Building: Using machine learning algorithms like Decision Trees, Support Vector Machines, or Neural Networks to build a classification model.
Model Evaluation: Assessing the model's performance using metrics such as accuracy, precision, recall, F1-score, and the area under the ROC curve (AUC). Cross-validation may also be used to validate the model's robustness.
Optimization: Hyperparameter tuning to improve the model's performance, possibly using grid search or random search techniques.
Challenges:
Class Balance: Since the dataset is balanced, model performance will not be skewed by imbalanced data. However, ensuring that both classes are well represented in the training and testing sets will be important.
Feature Selectio
DOI: 10.21954/ou.rd.14932131.v1
title: iNaturalist Young People verifiable data

description: iNaturalist young volunteers' observations: data quality and contributions to biodiversity. <br>