cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/g3pr923wf2
title: Data for: Regulation of the caudal neurosecretory system by environmental salinity in salmonid fishes

description: Supporting data for "Regulation of the caudal neurosecretory system by environmental salinity in salmonid fishes".

Tab 1: Effects of freshwater to seawater transfer on plasma cortisol and osmolality, and transcript abundance of corticotropin-releasing factor peptides in the caudal neurosecretory system (CNSS) of rainbow trout
Tab 2: CRF System Component Distribution in the caudal neurosecretory system (CNSS) of rainbow trout
Tab 3: Seasonal changes in transcript abundance of corticotropin-releasing factor peptides in the caudal neurosecretory system (CNSS) of smolt and parr Atlantic salmon
Tab 4: Changes in transcript abundance of corticotropin-releasing factor peptides in the caudal neurosecretory system (CNSS) of smolt and parr Atlantic salmon following transfer from freshwater to seawater
Tab 5: Effects of seawater to freshwater transfer on transcript abundance of corticotropin-releasing factor peptides in the caudal neurosecretory system (CNSS) of Atlantic salmon
DOI: 10.17632/ycv96d9pf3
title: Dataset on mental health, suicidal behaviors, literacy and stigma in Bangladeshi dental students

description: This paper presents data on mental health, suicidal behaviors, and suicide literacy and suicide stigma. A cross-sectional, face to face interview project was carried out between August and October 2019 within a total 5- Bangladeshi undergraduate dental institutes. Using a convenient sampling technique, a total of 487 students participated in the survey and 468 were kept for final analysis. The questionnaire included questions on (i) socio-demographics, (ii) family and personal psychiatric history, (iii) depression, (iv) anxiety, (v) suicidal behaviors, (vi) suicide literacy, and (vii) suicide stigma. Data was analyzed by using Statistical Package for Social Science (SPSS) version 22 and represented as frequencies, percentages herein. Further study from this data may help providing necessary information to develop effective healthcare policy and reduce adverse psychological effects and unexpected suicidal behaviors among dental students.
DOI: 10.17632/35hg67z8cj
title: AN ANALYSIS OF SPEECH ACTS IN NEWSPAPER NARRATIVES ON IMMIGRATION IN THE USA

description: The analysis of data involved exploring various types of speech acts within articles, concentrating on their distribution and the pragmatic functions they serve in immigration narratives featured in US newspapers. Each article examined serves as a case study on the distinct use of speech acts including constatives, directives, commissives, and acknowledgments.
DOI: 10.17632/bt98v4nxkd
title: Dataset: Air Quality Index (AQI) of Major Indian Cities and Stations 2/5/2024

description: The dataset contains air quality information for various cities across India. It includes parameters such as Air Quality Index (AQI), concentrations of particulate matter (PM2.5 and PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), as well as geographical coordinates and time stamps. This dataset enables analysis and comparison of air quality levels among different cities, aiding in understanding environmental health impacts and informing policy decisions.
DOI: 10.17632/v46jkbbzv3
title: A Benchmark Dataset for Detecting Disease in Plant Leaves: An Essential Resource for Deep Learning Models.

description: This dataset has been developed for research on plant leaf disease detection, specifically targeting Gourd, Zucchini, Bitter melon, Bean, Aubergine and Yardlong bean leaves. It contains high-resolution images capturing various disease symptoms to support the development and evaluation of deep learning models in agriculture. The dataset is ideal for use in image classification, segmentation, and disease diagnosis applications.

Dataset Overview:
Contains images of plant leaves affected by various diseases (Bacterial, YMV, Fungal, Viral infections) commonly found in agricultural crops.
Captured under controlled conditions, ensuring realistic and diverse real-world scenarios.
Includes images from multiple plant species and varying disease stages.

Types of Plant Leafs:
1. Gourd (537)
2. Zucchini (186)
3. Bitter melon (300)
4. Bean (517)
5. Aubergine (242)
6. Yardlong bean (500)
 
Key Features:
Number of Images: 2820
Number of Augmented Images: 2561(to increase dataset variability and model robustness)
File Formats: JPEG

Disease Types: Bacterial, YMV, Fungal, and Viral infections.

Applications:
Deep Learning: This dataset is specifically designed for the development and evaluation of deep learning models for plant disease detection. It can be used to train convolutional neural networks (CNNs) and other advanced deep learning architectures for tasks such as image classification, object detection, and segmentation, providing insights into plant health status and disease severity.

Machine Learning: In addition to deep learning, this dataset can also be utilised in traditional machine learning methods for disease recognition, but its primary value lies in enabling the use of cutting-edge neural networks for automated, scalable disease detection.

Agricultural Technology: The dataset supports the development of mobile applications and automated systems for real-time plant health monitoring. Deep learning models trained on this data can be integrated into mobile platforms or drone-based systems to provide instant, accurate disease diagnosis in agricultural settings, aiding farmers in timely interventions.

Agricultural Research: Researchers can use this dataset to better understand the impact of diseases on various plant species and their visual symptoms. The rich diversity of images will also help in studying disease progression, improving the design of predictive models, and contributing to better crop protection practices.

Dataset Collection:
1. Compiled from publicly available plant images and field-controlled environments.
2. Includes varying lighting conditions, leaf positions, and disease stages for robust model training.

By providing detailed, high-quality images of diseased plant leaves from multiple species, this dataset plays a critical role in advancing deep learning applications in agriculture. It enables more accurate disease detection, which can lead to faster responses and more sustainable farming practices.
DOI: 10.17632/3f6fn8343d
title: Replication files for "Macroprudential capital requirements, monetary policy, and financial crises"

description: Files allow to reproduce all tables, figures and further data in the article "Macroprudential capital requirements, monetary policy, and financial crises".
DOI: 10.17632/7f9d6k8m85
title: Growth in the e-commerce sector

description: Thid dataset contains the information about e-commerce companies globally.

The indicators include: region of operations (developed / developing), business-model (1st party trade / 3d party trade), key financial indicators
DOI: 10.17632/92r8jgbb9x
title: Municipal solid waste generation forecasting

description: Supplementary materials for reproducibility of the study on the use of socio-economic, climatic, and land use land cover patterns for municipal solid waste generation forecasting.
DOI: 10.17632/9t9s5sjztk
title: Data from "Initiation of bivalve larval calcification under ocean acidification: integrating insights from shell to cell"

description: Dataset encompassting responeses of shell length, deformity, elemental and isotopic compositions, and transcriptomic profiles of Ruditapes philippinarum grown at pH 8.1, 7.7, and 7.4, respectively.
DOI: 10.17632/bpf7jm4b8d
title: A dataset of clinical parameters of infertile women undergoing IVF, including FSHR rs6166 and LHCGR rs2293275 genotypes

description: A dataset of clinical parameters of infertile women undergoing through ovarian stimulation for assisted reproductive technologies in Rostov-on-Don, Russia. A short gonadotropin-releasing hormone antagonist protocol was used for ovarian stimulation. Early-follicular-phase follicle-stimulating hormone, luteinizing hormone, anti-mullerian hormone and progesterone levels were assayed in serum on 3-5-th menstrual cycle day 5-6 cycles before ovarian stimulation, with “Access hFSH”, “Access hLH”, “Access AMH” and “Access Progesterone” kits using Automatic Immunochemical Analyzer “Access 2” (Beckman Coulter, USA). Genotyping of the FSHR rs6166 variant was also carried out applying RFLP analysis using restrictase BsrI and primers: 5´-TTTGTGGTCATCTGTGGCTGC-3´, 5´-CAAAGGCAAGGACTGAATTATCATT-3´ [11]. Genotyping of the LHCGR rs2293275 variant was carried out applying primers: forward 5´-GCAACAGCTCCGTAACCAAG-3´, reverse 5´-GTGAAAGCACAGTAAGGAAAGTGTA-3´, and reverse mut 5´-TGAAAGCACAGTAAGGAAAGTGCG-3´. PCR products were detected by horizontal electrophoresis in 2% agarose gel. Results were validated by double genotyping.
DOI: 10.17632/djcgvgtcfm
title: Pomegranate Thermal Images

description: This dataset includes thermal images of pomegranate. The dataset consists of thermal images of pomegranate taken post harvesting. The pomegranates are at first stored and ensured that they are brought to temperature below the ambience. The temperature difference is necessary to allow the thermal radiation between pomegranate and the atmosphere. The digital image and thermal image of the same fruit is taken by placing both cameras at same angle. The fruits with digital and thermal images are categorized in three parts viz. no defect, minor defect and major defect. This categorization is done manually.
DOI: 10.17632/wdz96cz3nr
title: Forensic Genetic Genealogy Project v. DEC2024

description: This research seeks to collect all publicly available information concerning cases that were successfully cleared through forensic investigative genetic genealogy (FIGG), going back as far as possible in time and ending on December 31, 2024.

Cases were selected for inclusion in the dataset through internet searches, discussion boards, as well as press releases and blog posts from private companies and non-profit organizations known to perform FIGG, publications devoted to advances in forensic science, and published court records. 

Cases were chosen for inclusion in the sample only if a public authority had confirmed that FIGG was used to clear the investigation, and the investigation met the following definition of FIGG:

1. Investigative Body: The investigation was led by a public, and not a private, authority, such as a law enforcement agency or a coroner/medical examiner’s office. 

2. Investigative Techniques: The investigation must use the techniques of genomics, computer database technologies, and traditional genealogy. Cases were included when family lineages were drawn out to at least three or more generations. The sample includes investigations that use Y-chromosome STR profiles and/or mitochondrial DNA profiles to trace the paternal and maternal lineages of persons of interest. Cases solved through familial searching of law enforcement databases were excluded from the sample, as this technique raises separate legal and ethical issues. 

3. Investigative Purpose: The investigation must be for a forensic purpose, meaning that the evidence thus produced is relevant to an ongoing legal dispute. Most cases considered here are for the identification of perpetrators of criminal offences or the identification of decedents but can also include the identification of living does. Not included in this data are cases that are of purely historical interest, or the identification of unknown soldiers by military authorities. The term ‘forensic genetic genealogy’ has been chosen for this project in preference to the broader, and more generic term ‘investigative genetic genealogy’, which has also been used, to highlight the fact that these investigations are directed towards an ongoing legal dispute before the public legal system. 

4. Causation: This database only includes cases that have been successfully cleared using FIGG. The resolution of any investigation – particularly very large and lengthy investigations as were many of the cases described in this data – has many causes. To be included here, the FIGG investigation must have played a significant causal role in the resolution of the case. 

More complete information about how the data was coded, as well as an annotated bibliography and a short digest of each case, can be found in the Code Book, included in previous versions of this project. You may read a short digest of each case cleared, including references for all data collected, in the Case Digests below.
DOI: 10.17632/278fy5m2yj
title: CITE-seq - MS Twin Study

description: We performed single-cell transcriptome, surface proteome and TCR analyses using 10X Chromium Single Cell Immune Profiling Solution (5’ approach) with feature barcoding. We successfully sequenced 8 selected twin pairs discordant for MS (16 individuals in total) + 2 additional healthy MS Twins. This allowed us to pair the high-throughput CyTOF data from 116 Twin samples with a high-resolution map of highly multiplexed surface protein expression and an unbiased in-depth analysis of the transcriptome (single-cell indexing of transcriptomes and epitopes: CITE-seq).

Sequencing raw data and processed gene expression data have been deposited into the GEO repository under the accession numbers GSE193181.
DOI: 10.17632/9mxm455dfm
title: Social Media Addiction SMA10 Dataset

description: Coding category: 

Q1_Gender 
1. Male 
2. Female

Q2_Living_Area 
1. Urban 
2. Rural 

Q3_Maritial_Status 
1. No
2. Yes

SMAQ1 – SMAQ10 
1. Never
2. Rarely 
3. Sometimes 
4. Often 
5. Always 

SMA_Scale_value
 
less than 20 to more than 40.

SMA_Scale (Class_Lebel) 
1. Low addiction: Total score equal & less than 20
2. Moderate addiction: Total score in between 20 and 40
3. High addiction: Total score equal & greater than 40
 

This Dataset analyzed Social Media Addiction data from Daffodil International University (DIU) to classify their levels of Addiction into five categories: 1 (Never), 2 (Rarely), 3 (Sometimes), 4 (Often), and 5 (Always). The dataset used was included information on 1,030 participants from various Departments of DIU. The dataset contained 10 main attributes, comprising ten questions each for Social Media Addiction. The target SMA_Scale (Class_Lebel) was categorized as 1 (Low Addiction), 2 (Moderate Addiction), 3 (High Addiction). The distribution of instances for Class_Lebel was 728 (Low Addicted), 259 ((Moderate Addicted), 42 (High Addicted).
DOI: 10.17632/fnpwzj37gw
title: Dense sampling of bird diversity increases power of comparative genomics

description: Data accompanying the manuscript "Dense sampling of bird diversity increases power of comparative genomics" In Nature releasing of 267 bird genomes as part of the Bird 10,000 Genome Project (B10K), in addition to orthology assignments and analyses on a total of 363 genomes. The dataset includes - Extended Data Figures. Zoomable PDFs for some Extended Data Figures 2e, 3, 6, 7c, 8a with tip labels; gene tree file for GH orthologs shown in Extended Data Figure 6. - Supplementary Tables 1 to 15. Captions are given in supplementary_table_captions.txt. Tables can be downloaded individually or as a package (supplementary_tables.zip). Sample information for each genome and genome statistics (Supplementary Table 1) can also be viewed online at https://b10k.scifeon.cloud/. - B10K_name_map.xls. Allows translation of B10K sample codes, short 6 letter codes used in ortholog annotations and species latin name. - Supplementary File 2. The tree file in newick format for all 10,135 species of birds. The tree was pruned from the synthesis tree by excluding all subspecies, operational taxonomic units and unaccepted species as described in Supplementary File 1.
DOI: 10.17632/hff49h4zpn
title: Psoriasis and COVID-19: A bidirectional Mendelian randomization study

description: Supplementary tables
DOI: 10.17632/prwss59472
title: To evaluate the effectiveness of quadratus lumborum muscle stretching exercises in reducing mechanical low back pain among the young and middle-aged population of Haryana.

description: This study explored the effectiveness of passive stretching of the quadratus lumborum (QL) muscle in individuals with mechanical low back pain (MLBP). Through six treatment sessions over 21 days, significant improvements were observed in back pain distribution. This study contributes valuable insights into addressing MLBP and advocates for the inclusion of QL stretching in clinical practice.Healthcare professionals commonly encounter low back pain, a widespread condition affecting individuals across all age groups and believed to be a leading cause of disability worldwide, in both developed and developing countries. While males are generally less affected than females, approximately 80% of patients report experiencing moderate to severe pain that significantly disrupts their daily routines. Quadratus lumborum muscle is already being used separately in different conditions, So there is a need to investigate the effectiveness of QL muscle for improving ADLS and reducing pain in patients with mechanical low back pain. The results suggest that QL stretching can reduce MLBP and enhance daily functioning. The findings underscore the importance of integrating QL stretching into physiotherapy protocols for MLBP management, offering a cost-effective and accessible treatment option.
DOI: 10.17632/sybd454yjd
title: Pakistan journal of advance in medicine and medical research 

description: Pakistan journal of Advances in Medicine and Medical Research
DOI: 10.17632/zrrmtp5bgp
title: I2P Data

description: This data set comprises all data and supplementary files for the study:
"Significance Testing Of Differences In Baseline Variables Versus The I2 Test For Detecting Selection Bias In Randomised Controlled Trials - A Simulation Study"
DOI: 10.17632/2y7vx9xkfh
title: Disruption of the Integrator complex triggers the Integrated Stress Response through formation of double-stranded RNA

description: Uncropped Images for the research work titled "Disruption of the Integrator complex triggers the Integrated Stress Response through formation of double-stranded RNA"
DOI: 10.17632/4f5rjsxsh8
title: Tables_Machine Learning Models Comparison for Bankruptcy Predication for Indian Companies

description: The table provides a Scenario-wise list of predictive variables. We log-transformed the absolute values and used the ratios as is. The dataset contains no missing value. We tested the variables for correlation. We kept correlated variables as output under different scenarios are being compared. The data is complied using EMIS
DOI: 10.17632/8hry654mxr
title: Supplementary Information for: "Simulation of convective moistening of extratropical lower stratosphere using a numerical weather prediction model"

description: Video SI.1: the animation of 1 km simulation on a chosen cross-section during the convection event from 18:40 to 20:40 UTC, 25 Aug 2013. 1st panel: temperature (colour) and isentropic lines (thin white lines); 2nd panel: ice water content in logarithm scale; 3rd panel: water vapor content in ppmv (colour saturated at 20 ppmv); 4th panel: vertical wind speed (m s-1). Video SI.2: water vapor content in ppmv at the altitude of 16.5 km from 18:00 to 23:00 UTC (5 hours) within the evaluation Domain A. Figure SI.1: the transported water vapor in the simulation domain of 0.25 km (green box in Fig. 1) from 1800 to 19:00 UTC 25 Aug. The vertical advection of 10 km simulation is decomposed into two parts: grid scale advection (light blue bar) and sub-grid scale advection from KFC parameterization (darker blue bar). For the results presented in Fig. SI.1, the evaluation is performed for the simulated domain of 0.25 km grid-spacing (green box in Fig. 1) for the first hour of the evaluation time window (from 18:00 to 19:00 UTC 25 Aug for the three high resolution models, from 21:30 to 22:30 UTC 25 Aug for 10 km simulation). The tropopause levels are defined using the mean laps rate &lt;2˚C km-1. The use of limited time window is due to the fact that the storm moves quickly to the outside of the simulation domain. Figure SI.1 shows the mass transport budget for the 4 simulations with different horizontal resolutions, we found that the direct transport of water vapor of 0.25 km simulation is higher than all the other simulations. Although the contributions from ice sublimation and turbulent mixing of 0.25 km simulation are the lowest. The contribution from ice sublimation is negative which suggests that vapor deposition rate is very high in the convection updrafts and exceeds that of ice sublimation. Although the results presented here should be viewed with caution due to the short evaluation period (1 hour), it corroborates the finding that higher resolution model tends to have a stronger direct vertical transport of water vapor and a weaker contribution from the ice sublimation. Figure SI.2: background: ice water content at the altitude of ~14 km, 1940 UTC 27 Aug; gray line: ER-2 aircraft path in 27 Aug highlighted by red dots for the areas with ice; circles: starting points of back tracking at 19:40 UTC 27 Aug; triangles: ending point of back tracking at 04:00 UTC 27 Aug. Figure SI.3: the changes of the properties of the highlighted air parcel in Fig. R2 along its back trajectory from 19:40 UTC to 03:00 UTC 27 Aug.
DOI: 10.17632/hjnfzm949y
title: Human Skin Microbiome Data (16S rRNA sequencing) dataset #2

description: 16S rRNA sequencing data on human skin microbiome samples collected before and after swimming in the ocean. This dataset contains raw sequencing data contained in fasta and qual files produced from an Ion Torrent PGM sequencer. There were 2 sampling occurrences (041218 and 092718) and each occurrence has an associated fasta and qual file. This dataset contains the 092718 sampling data only due to storage restrictions. The other dataset is published separately. Our research has shown that the human skin microbiome is altered after swimming in the ocean. Normal commensals were washed off and simultaneously, exogenous bacteria were deposited on the skin. QIIME was used for initial analysis and indicated that the abundance and diversity of microbial communities on the skin increased after swimming and these changes persisted for more than 24 hours. Downstream analysis using PICRUSt to predict functional metagenomics indicated that there was an increase in antibiotic resistance genes, antibiotic biosynthesis genes, and virulence factor genes on the skin after ocean water exposure.
DOI: 10.17632/n8zb2wpjp6
title: Real-fluid thermophysicalModels: An OpenFOAM-based library for reacting flow simulations at high pressure

description: Although OpenFOAM is a widely-used open source computational fluid dynamics (CFD) tool, it is limited to numerical simulations of multi-dimensional reacting/nonreacting flows at relatively-low pressures. This is not only because real-fluid models that can evaluate thermophysical properties at high pressures are not available in the thermophysicalModels library of OpenFOAM, but also because the existing mixing model cannot handle various mixing rules of real-fluid models. In the present study, we develop a novel algorithm applicable for a mixture model incorporating various mixing rules in OpenFOAM. Based on the new algorithm, we update the thermophysicalModels library of OpenFOAM 6.0 by implementing a set of real-fluid models such as the Soave-Redlich-Kwong/Peng-Robinson equation of state, Chung's model for dynamic viscosity and thermal conductivity, mixture averaged model for mass diffusivity using Takahashi's correction for binary diffusion coefficients at high pressure. The new library is validated against experimental data and is further assessed for compressible reacting flows by performing two-dimensional numerical simulations of axisymmetric laminar non-premixed counterflow flames and one-dimensional numerical simulations of premixed CH_4/air flames at high pressures. The developed library can be used for any reacting flow solvers in OpenFOAM 6.0 that adopt a set of implemented real-fluid models.