cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/4wd9scvdvk.4
title: Assessing recovery-related behaviors, emotions, and cognitions among members of Alcoholics Anonymous over 7 days: A quantitative daily diary study

description: The main purpose of this research study was to investigate the relationship between selfishness, helping behavior, and gratitude among members of the 12-step program Alcoholics Anonymous. The research hypotheses centered around ideas discussed at length in 12-step literature- When people in AA spend more time helping others and feeling grateful, they think less about their own cares and concerns. The data provides preliminary evidence of this relationship: significant daily associations were uncovered between helping behavior, gratitude and selfishness. Participants reported less self-absorption on days when they helped more people and were more grateful. A number of additional control variables were collected at baseline and throughout the study that may be of interest to other researchers. This was a quantitative daily dairy study that consisted of an initial baseline assessment followed by 7 nightly reports that were collected each evening at 8pm. Participants (N = 113) were recruited through social media networks (e.g., large recovery-related facebook groups, twitter, Instagram, etc.) as well as an email list from people in recovery who had previously participated in research and had provided consent to be contacted in the future. After the baseline survey, participants were sent a reminder to fill out the survey each evening at 8 pm in their respective time zones via text and email. This data is well-suited for multilevel modeling analyses for all daily variables. A complete list of the measures is below. Baseline: Addiction Severity - Short Inventory of Problems-Revised (SIP-R) Adult Attachment - Experiences in Close Relationships Scale - Short (ECR-S) Trait Narcissism - Narcissistic Personality Inventory (NPI-13) Altruism - Altruistic Personality Scale (APS) Trait Gratitude - Gratitude, Resentment, and Appreciation Test (GRAT) Personality - Ten-Item Personality Inventory (TIPI) Psychological Distress - Kessler Psychological Distress Scale (K-6) Social Desirability - Marlow Crowne Social Desirability Scale (SDS) Locus of Control - Alcohol-Related God Locus of Control Scale (AGLOC) Self-Esteem - Rosenberg Self-Esteem Scale (RSE) Recovery Capital - Brief Assessment of Recovery Capital (BARC) Daily: Self-Absorption - Self-Absorption Scale (SAS) Narcissism - Hypersensitive Narcissism Scale (HSNS) Mood - Positive/Negative Affect (PANAS) Helping Behavior - Service to Others in Sobriety (SOS) State Gratitude - Gratitude Checklist (3-item Daily Gratitude) Self-Efficacy - Self-Efficacy Scale (SES)
DOI: 10.17632/s9t7sr52wg.1
title: Indian Bay Leaves or Cinnamomum Tamala Leaves Dataset

description: This dataset contains high-resolution images of Indian bay leaves (Cinnamomum tamala) categorized into three folders for classification tasks:

Healthy Leaf: This folder contains images of fresh, green Indian bay leaves without any visible damage or disease.
Dried Leaf: This folder contains images of dried Indian bay leaves, commonly used in cooking. The leaves may appear brown or slightly lighter depending on the drying process.
Diseased Leaf: This folder contains images of Indian bay leaves exhibiting signs of disease. These may include discoloration, spots, wilting, or other abnormalities.
This dataset is valuable for researchers and developers working on:

Machine learning for food quality inspection: Classifying healthy bay leaves for commercial use.
Disease detection in plants: Training algorithms to identify potential diseases in Indian bay trees.
Image recognition for medicinal plants: Developing applications for recognizing Indian bay leaves used in traditional medicine.
DOI: 10.17632/36fjrg9s69.3
title: Dataset for COVID-19 segmentation and severity scoring

description: In this dataset, we present a set of chest X-ray images of COVID-19 positive and negative patients, with the aim of performing segmentation and scoring of disease-affected areas in the lungs. The total number of images is 1,364. Of them, 580 are COVID-19 positive images (43%) and 784 images show no findings (57%). Each COVID-19 image contains the segmentation mask of the COVID-19-affected area and the associated severity score.

We collected and pre-processed four publicly available datasets used for the classification of COVID-19 and pneumonia, namely:
•	Actualmed COVID-19 Chest X-ray Dataset containing 49 images of COVID-19 patients [1];
•	COVID-19 Radiography Database containing 104 images of COVID-19 patients [2];
•	COVID Chest X-Ray Dataset  containing 399 images of COVID-19 patients [3];
•	Figure1 COVID Chest X-ray Dataset containing 28 images of COVID-19 patients [4].

Then, two senior radiologists in our team, from the United States and Russia, annotated anteroposterior and posteroanterior radiographs. Each annotator has more than 10 years of experience and has been working extensively during the COVID-19 pandemic. The annotators labeled the datasets independently. Despite being time-consuming, this allowed us to get a consensus severity score of COVID-19-positive patients. Each patient has been labeled on a scale from 0 to 6, where 0 means no findings, while 6 is a severe form of COVID-19 which affects more than 85% of the lungs.

In addition to COVID-19 data, we also used two datasets with normal lungs without any pneumonia or any other abnormalities. Those healthy lung images have also been validated by the same two radiologists. Those images are represented by two datasets, namely:
•	Chest X-ray Normal Dataset containing 431 images of patients with no findings [5];
•	RSNA Normal Dataset containing 353 images of patients with no findings [6].

References:
1. 	Wang L, Wong A, Qiu ZL, McInnis P, Chung A, Gunraj H, et al. Actualmed COVID-19 Chest X-ray Dataset Initiative. 2020. Available: https://github.com/agchung/Actualmed-COVID-chestxray-dataset
2. 	COVID-19 Radiography Database. Available: https://www.kaggle.com/tawsifurrahman/covid19-radiography-database
3. 	COVID-19 Image Data Collection. 2020. Available: https://github.com/ieee8023/covid-chestxray-dataset
4. 	Wang L, Wong A, Qiu ZL, McInnis P, Chung A, Gunraj H, et al. Figure 1 COVID-19 Chest X-ray Dataset Initiative. 2020. Available: https://github.com/agchung/Figure1-COVID-chestxray-dataset
5. 	Chest X-Ray Images (Pneumonia). Available: https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia
6. 	RSNA Pneumonia Detection Challenge. Available: https://www.kaggle.com/c/rsna-pneumonia-detection-challenge
DOI: 10.17632/m5p5xmrr7k.1
title: GR5J hydrological model code

description: In a river basin, the mass balance equation links total water storage (TWS), precipitation (P), actual evapotranspiration (E) and river discharge (Q). Though, a focused portion of the catchment, located between two river discharge stations, can be studied. Indeed, TWS in a downstream sub-catchment can be estimated based on the mass balance equation dTWS/dt = P + Qin - E - Qout - Qgw; where Qin, Qout, Qgw are respectively incoming river inflow, outcoming river discharge, and potential groundwater import/export in a surrounding basin. Among the different water fluxes, P, Qin and Qout can be measured, whereas actual evapotranspiration and Qgw should be estimated with a model. E and Qgw can be estimated with the lumped parameter rainfall-runoff hydrological model GR5J (Pushpalatha et al., 2011), which allow to quantify daily TWS at the scale of single hydrological basins. Here we provide a MATLAB code of the GR5J model. This model is forced with precipitation, temperature and potential evapotranspiration and computes actual river discharge. The model is based on two storage compartments - production and routing stores - which mimic the typical response of soils and groundwater to antecedent precipitation and evapotranspiration. Snow is considered and it is estimated following the method described in the HBV (Hydrologiska Byrns Vattenbalansavdelning) model (Lindstrom et al., 1997): mean catchment temperature defines both rainfall/snowfall partitioning and snow melt events. It is worth noting that GR5J does not need the specific knowledge of any intrinsic structure/property of the basin. The model is parsimonious and designed to model river discharge. Although the GR5J model is a simplified conceptual model, where only five mathematical parameters define the dynamics of the two stores and their relations, it has proven skillful in predicting river discharge better than more complex models (de Lavenne et al., 2016) and has been successfully applied to represent groundwater storage changes in Nepal rivers (Andermann et al., 2012). GR5J parameters are calibrated using a Marquard-Levenberg least squares regression analysis using root mean square error on the logarithm of observed river discharge to limit the impact of floods and promote the description of the whole water cycle.
DOI: 10.17632/85sbvw7vpw
title: Journal of Iran's Economic Essays; "Jostarhaye Eghtesadiye Iran; No. 28

description: Journal of Economic Essays; an Islamic approach (JEE) is an open-access double-blind peer-reviewed academic quarterly journal that publishes original research, written with an Islamic approach in various Economic areas including Islamic economics and finance, Iran's economy, Fiqh (Islamic jurisprudence) and economics, philosophy of economics, economic theory, ethics and business, Islamic banking, economic development, and social security institution in Islam. JEE especially welcomes comparative articles that study the western and Muslim scholars' viewpoints about important economic issues to find the best answer to theoretical and applied questions and also to explore their differences and similarities with the aim of bringing them closer to each other. This journal accepts analytical articles that reread Muslim scholars' ideas according to new approaches in economics, moral philosophy, Islamic banking and finance, social security, econometrics, and Islamic economic institutions. Therefore, it aims to serve the interests of a wide range of thoughtful and academic readers, economists, philosophers, theologians, banking and finance experts and others interested in the multidisciplinary study of economics and Islam (including Fiqh "Islamic jurisprudence"). We hope that this publication creates an atmosphere of constructive dialogue on different economic topics between national and international scholars by which it could have a role in the growth of Islamic economic thought in Iran. In addition, Islamic solutions to the economic problems of Iran and the world will be examined and analyzed, and they will be presented to the policy makers to help improve the Islamic economic system.

Major Topics

 The Journal publishes papers, including the following fields:

- Islamic economics and finance;

 - Iran's economy;

 - Fiqh (Islamic jurisprudence) and economics;

 - Philosophy of economics;

 - Economic theory;

 - Ethics;

- Islamic economic institutions

 - Islamic banking;

 - Economic development;

- Social security.
DOI: 10.17632/pprkvz3vbd.1
title: Full Scale Wastewater Treatment Plant Data

description: Energy consumption, climate, and wastewater characteristics of Melbourne eastern wastewater treatment plant for preiod of six years (2014-2019). https://www.researchgate.net/profile/Faramarz-Bagherzadeh-2
DOI: 10.17632/v4kcfkh9ky.1
title: Data and Code for: How to Reduce the Default Contagion Risk of Intercorporate Credit Guarantee Networks? Evidence from China

description: This dataset includes capital buffer and relative capital buffer loss data for 615 companies in Wenzhou City, Zhejiang Province, China, between June 2011 and December 2018. This code is called the GuaranteeRank code, which corresponds with the newly proposed GuaranteeRank model in this paper.
DOI: 10.17632/z25p7f4zvt.1
title: Quantitative activity profile and context dependence of all human 5′ splice sites. Wong et al.

description: Pre-mRNA splicing is an essential step in the expression of most human genes. Mutations at the 5′ splice site (5′ss) frequently cause defective splicing and disease due to interference with the initial recognition of the exon-intron boundary by U1 small nuclear ribonucleoprotein (snRNP), a component of the spliceosome. Here, we use a massively parallel splicing assay (MPSA) in human cells to quantify the activity of all 32,768 unique 5′ss sequences (NNN/GYNNNN) in three different gene contexts. Our results reveal that although splicing efficiency is mostly governed by the 5′ss sequence, there are substantial differences in this efficiency across gene contexts. Among other uses, these MPSA measurements facilitate the prediction of 5′ss sequence variants that are likely to cause aberrant splicing. This approach provides a framework to assess potential pathogenic variants in the human genome and streamline the development of splicing-corrective therapies.
DOI: 10.17632/vfj9sf7s8t.1
title: Threonine-rich carboxyl-terminal extension drives aggregation of stalled polypeptides. Chang, Yoon et al.

description: Original data for western blots and microscopy images published in the paper "Threonine-rich carboxyl-terminal extension drives aggregation of stalled polypeptides"
DOI: 10.17632/my2vkfyffd.1
title: TRACT: Tweets Reporting Abuse Classification Task Corpus

description: Out of many social media sites, Twitter has some unique characteristics which attract diverse categories of people. Twitter has been utilized as an important source of user-generated data that can provide unique insights into population. Many of these studies involve retrieving tweets for sentiment analysis, named entity recognition and disambiguation tasks. In recent decades we have noticed a considerable increase in reports or confession posts of abuse victims on twitter. Most of the time victims do not report it to their guardians or the concerned authorities. Part of these victims tweets about their incident to let go of pain and suffering or as a cry for help. Identifying such reports is challenging, to address such an important task we develop and release a first small-scaled corpus on Tweet Reportings (TRACT). To retrieve the small number of tweets that mention reporting of abuse we mined from millions of tweets in our database, The approach relies on a lexicon and lexical variants from a set of lexicon entries manually collected after extensive research. Tweets containing these lexicons and tweets containing lexicons similar to these lexicons are extracted.
DOI: 10.17632/fgvscdjsmt.1
title: FlameVision : A noble dataset for wildfire classification and detection using aerial imagery 

description:  N/A
DOI: 10.17632/b39x2kfbj4.1
title: Data for: The mineral diversity of Jezero crater: Evidence for possible lacustrine carbonates on Mars

description: All CRISM spectra from plots are stored in an Excel worksheet. Includes ratio spectra as shown in figures as well as original reflectance spectra and alternative ratio spectra. Mosaics of Jezero CRISM RGB combinations over CTX basemaps are included at various zooms and resolutions, as used in figures.
DOI: 10.17632/fdw347mttz.1
title: Gender Diversity, Corporate Governance and Firm Specific Data of All Public Listed US Firms

description: This dataset covers all publically listed companies in the United States from 2000 to 2018, which are listed in the S&P index. The starting point of 2000 is due to the minimal data available in the BoardEX database before this time in relation to board directors' information. Compustat is the source of financial data. As previous research indicates, financial and utilities firms are excluded from the sample due to their distinct regulations, which expose their directors to liability risks that non-financial firms are not subject to (Adams and Mehran, 2012; Sila et al., 2016). The sample size of non-financial firms amounts to 17,220. Financial variable outliers are adjusted to the 98% level in accordance with Bharath and Shumway's (2008) study.
DOI: 10.17632/6h6c3b57mj.1
title: Can growth mindset interventions improve academic achievement?

description: Encouraging the idea of a growth mindset in which students believe that they can improve their ability, as opposed to a fixed mindset, has been suggested as an effective and relatively cheap approach to improving student attainment at school. This paper offers a comprehensive review of the evidence from growth mindset interventions. After a rigorous search, screening, and evaluation, the inclusion criteria led to 24 studies. All were randomised control trials (RCTs) focused on growth mindset of intelligence interventions for school-age children, and included output measures for academic performance assessment. Their findings reveal that the strongest studies, characterised by larger sample sizes, minimal missing data, and high data quality, exhibit null or very small effect sizes, ranging from Cohen's d = -0.008 to +0.054. Additionally, certain findings raise concerns about a potential conflict-of-interest bias, suggesting that some negative or null results may remain unpublished. The review identifies three evaluations with a high degree of trustworthiness and with no conflict of interest. Among these, two studies indicate no discernible impact, while one shows a small impact. Given these findings, it is not advisable for schools, school districts, or governments to allocate significant time or resources to the implementation of growth mindset interventions, as the anticipated outcomes are likely to be either null or very modest. However, if there is an opportunity to implement such interventions at a minimal or negligible cost, or as part of another objective, it might be reasonable to proceed with them, considering the potential for a small positive impact.
DOI: 10.17632/n36vrd8zrp.1
title: Datasets on the GRP of Russian regions, GRP sectoral composition and growth rates in 2013 - 2018

description: This work presents a comprehensive large-scale assessment of the gross regional products of 85 Russian regions. The computations characterize the level of economic development of different parts of the country: GRP measures the value of goods and services produced in a region; GRP per capita reflects the economic output of a region and the standard of living; the ratio of different economic sectors defines the sectoral composition of regional economies. Special attention was paid to the analysis of datasets for the production of goods, market and non-market services.
DOI: 10.17632/64xkbj2ry5.1
title: The American Customer Satisfaction Index (ACSI): A Sample Dataset and Description

description: This dataset provides a sample of survey data collected by the American Customer Satisfaction Index (ACSI). Using online sampling and stratified interviewing techniques of actual customers of predominantly large market-share (“large cap”) companies, the ACSI annually collects data from some 400,000 consumers residing across the United States for more than 400 companies within about 50 consumer industries. For this data depository, consumers’ perceptions of their experiences with individual companies included within four consumer industries as defined and measured by ACSI – processed food, commercial airlines, Internet service providers, and commercial banks – are included in the dataset. The overall sample size is n=8239 consumer responses for this sample ACSI dataset.
DOI: 10.15468/dl.ncbmvn
title: Occurrence Download

description: A dataset containing 179887 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2024-11-05",
 "EventDate is less than or equal to 2024-12-05",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 }
 ]
}

 The dataset includes 179887 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009340-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/sc8whx4pvm.1
title: Old_ADA_Bridge-damage_vibration_data

description: This data presents the vibration data of a steel truss bridge situated in Japan: Old ADA bridge. Five different damage scenarios were designed to represent different real-world cases by introducing artificial damage in the truss.
DOI: 10.17632/k7h24dmmr9.1
title: Femur Bone X- Ray Images

description: Here are the Femur Bine Images, used for Diagnosis purpose of problems or diseases in human beings largest bone by clinicians.
DOI: 10.17632/hgkcshcbrw.1
title: A Comparative study on hydrochemical profile of Alang- World’s largest shipbreaking yard and Gopnath

description: The preset study was undertaken at Alang which is known as a world’s largest ship breaking yard and Gopnath (Gulf of khambhat), Gujarat, India.  The tidal, geographical, and climatic features make Alang an ideal ship breaking location with thousandths of ships getting scrapped each year. The aim of this research was to monitor temporal and spatial variation of hydrochemical characteristics. The water samples were collected bimonthly basis from two different locations at both the site. The surface water quality of marine water was assessed using 14 hydrochemical parameter e.g. physical variables (Temperature, EC), chemical variables (pH, DO, PA, TA, Chloride, Total Hardness, Ca Hardness, Mg Hardness, and nutrients variables (Sulphate, Phosphate, Nitrate). In present study the pH of seawater at Alang ranged from 8.7 to 9.2 whereas pH of seawater at Gopnath ranged from 8.7 to 9.1. Salinity of Alang fluctuated from 26.5 to 35 % and salinity of Gopnath ranged from 29.7% to 35%. Temperature was reached maximum in pre monsoon period by 33°C and minimum was noticed in post monsoon with 24°C. The electrical conductivity of Alang and Gopnath ranged from 34 ms/cm to 50 ms/cm and 41 ms/cm to 74 ms/cm respectively. The DO refers to the amount of oxygen dissolved in the sea water and it is particularly important in limnology (aquatic ecology). The study shows that the DO at Alang and Gopnath varied from 6.3 mg/L to 7.6 mg/L and 6.7 mg/L to 7.2 mg/L respectively. Seawater is more alkaline due to hardness of water. Calcium and magnesium both play an important role in provoking the toxic effects of various ions and neutralizing the excess acid produced. The calcium and magnesium hardness of Alang’s seawater  ranged from 2187 mg/L to 4776 mg/L and 787 mg/L to 1312 mg/L respectively, Whereas calcium and magnesium hardness of Gopnath’s seawater ranged from 2798 mg/L to 6595 mg/L and 790 mg/L to 1102 mg/L respectively. Maximum phosphate concentration recorded at Alang and Gopnath was 0.6 mg/L to 0.9 mg/L respectively. Whereas maximum sulphate concentration recorded at Alang and Gopnath was 2.4 mg/L to 2.0 mg/L respectively and the maximum concentration of nitrate at Alang was 1.2 mg/L and at Gopnath it was 1.7 mg/L respectively. The physicochemical parameter of water including pH, DO, Sulphate and nitrate were higher in Alang whereas Salinity, Hardness and phosphate concentration were higher in Gopnath. Shipbreaking activity carried out at Alang releases number of organic, inorganic chemicals as well as heavy metal which affect the marine water quality and the marine water quality of Gopnath is affected by the religious activity. This baseline study on marine environment monitoring, aquatic pollution and environmental sustainability will be helpful to ecologists, environmentalists and biologists to conserving, protecting, and managing Gujarat's existing marine ecosystems.