cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.mqtvcq
title: Occurrence Download

description: A dataset containing 688 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Towson University - MidAtlantic - Ailanthus altissima - 2011"
 ]
}

 The dataset includes 688 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009243-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/hnwrxg8zm8.1
title: REMP: A Unique Dataset of Rare and Endangered Medicinal Plants in Bangladesh

description: In Bangladesh, there are significant number of medicinal plants, but currently no comprehensive record of these valuable species is publicly available. Alarmingly, some of these plants are in a precarious state of endangerment. Therefore, we are creating a unique dataset of Bangladesh's rare, endangered, and threatened medicinal plants to support conservation efforts. It will help us to track and conserve endangered plant species, ensuring a more organized approach to research and preservation efforts. We conducted on-site visits to the National Botanical Garden and The Government Unani and Ayurvedic Medical College, capturing photographs of these plants in optimal sunlight conditions at various times of the day. This involved fieldwork, detailed image annotations, dataset organization, diversity augmentation, and contribution to the preservation of our natural heritage. We have collected a total of 16 types of rare and endangered medicinal plant leaf photos to create our unique dataset consisting of a total of 3494 images. This dataset will help researchers in biodiversity conservation through building efficient machine learning models and applying advanced machine learning techniques to identify rare and endangered medicinal plants.
DOI: 10.17632/3b28fs62wc.1
title: Solution of the Skyrme-Hartree-Fock-Bogolyubov equations in the Cartesian deformed harmonic-oscillator basis. (VIII) HFODD (v2.73y): A new version of the program.

description: We describe the new version (v2.73y) of the code hfodd which solves the nuclear Skyrme Hartree-Fock or Skyrme Hartree-Fock-Bogolyubov problem by using the Cartesian deformed harmonic-oscillator basis. In the new version, we have implemented the following new features: (i) full proton-neutron mixing in the particle-hole channel for Skyrme functionals, (ii) the Gogny force in both particle-hole and particle-particle channels, (iii) linear multi-constraint method at finite temperature, (iv) fission toolkit including the constraint on the number of particles in the neck between two fragments, calculation of the interaction energy between fragments, and calculation of the nuclear and Coulomb energy of each fragment, (v) the new version 200d of the code HFBTHO, together with an enhanced interface between HFBTHO and HFODD, (vi) parallel capabilities, significantly extended by adding several restart options for large-scale jobs, (vii) the Lipkin translational energy correction method with pairing, (viii) higher-order Lipkin particle-number corrections, (ix) interface to a program plotting single-particle energies or Routhians, (x) strong-force isospin-symmetry-breaking terms, and (xi) the Augmented Lagrangian Method for calculations with 3D constraints on angular momentum and isospin. Finally, an important bug related to the calculation of the entropy at finite temperature and several other little significant errors of the previous published version were corrected.
DOI: 10.17632/kmjs5hcwph.1
title: Stress, anxiety and coping styles during the two waves of the COVID-19 pandemic

description: The data was collected during the first and second waves of the COVID-19 pandemic among students of Opole University of Technology in Poland. The data includes some demographic characteristics of the study sample, as well as standardized psychological questionnaires to assess perceived stress (PSS-10), anxiety (GAD-7) and coping styles (CISS-48). The aim of the study is to examine the Multidimensional Interaction Model of Stress, Anxiety and Coping during the COVID-19 pandemic.
DOI: 10.17632/y5sm4smnfr.5
title: Sheep Facial Expression Primary Data-set

description: The sheep facial expression primary dataset has been cropped of the collection sheep imagesfrom ImageNet, NADIS, Pixabay, Flickr, and Gettyimages with high resolutions. It consists of 1500 plus sheep face images which has two subset normal and abnormal sheep faces. The abnormality of sheep can be identify by ears, eyes and mouth of the sheep. If the ears pinna visible than have no pain else for less visible and not visible have low and high pain respectively. Similarly for eyes and mouth will depends upon V and U shape. Here we uploaded a sample subset and complete dataset. This dataset has been used in our coming research article. We have aim to collect more images which will be helpful to find pain in sheep through deep learning. As deep learning needs big data to complete a desired task from scratch, while currently we used transfer learning to find abnormality of sheep from there faces with deep learning.
DOI: 10.17632/vv6wdpbrsh.1
title: APNEA HRV DATASET

description: The HuGCDN2014 database was provided by the sleep unit of the Dr. Negrín University Hospital (Canary Islands, Spain). It is made up of 77 single-lead ECG recordings, digitized at 200 Hz. The labeling process was performed by an expert based on the simultaneous polysomnography, indicating the presence or absence of apnea in each minute. The database is divided into two groups: 1º) CONTROL: Forty healthy subjects with an AHI lower than 5 (30 men and 10 women). 2º) APNEA: Thirty-seven OSA patients with an AHI higher than 25 (30 men and 7 women). The learning set (L) consists of the first 20 recordings of control subjects and the first 18 OSA patients. The rest belong to the test set (T). The single-lead ECG signal is divided into 5-minute frames, that are shifted in time in increments of 1 minute. The scoring for each segment is assigned to the minute located in the middle position. The RR interval series is constructed as a sequence of time differences between the successive heartbeats.
DOI: 10.17632/k73xwr6zv5.1
title: Anemia in early childhood Arequipa - Perú

description: Objetivo: Comprender las experiencias de las madres en relación al tratamiento con sulfato ferroso en niños de 6 y 36 meses y la prevalencia de la anemia, Preguntas: 1. ¿Cómo es el trato recibido a las madres por los proveedores de la salud? 2. ¿Qué experiencias han tenido las madres en relación al tratamiento con el sulfato ferroso? 3. ¿Cómo son las características socioculturales de las madres con niños con anemia?
DOI: 10.17632/h8td6s77f2.1
title: Tutorial para criação de modelo 3D em Abaqus CAE

description: Esta pasta apresenta tutorial para a construção de um modelo de Elementos Finitos em Software CAE (Abaqus) de uma peça estrutural presente em colheitadeiras (suporte de polia). Isso inclui aspectos sobre a importação de uma geometria, definição de materiais e propriedades mecânicas, criação de “passos” de simulações e análise dos resultados numéricos (tensões e deformações).
DOI: 10.17632/43d75vptz4.3
title: Java Plum Leaf Disease Dataset

description: Description

The Java Plum Leaf Disease Detection Dataset is a comprehensive collection of high-quality images of Java Plum leaves, designed to facilitate the development of robust Java Plum leaf disease detection systems using deep learning models. The dataset was meticulously gathered from two prominent areas in Cumilla, Bangladesh: Titas and Barura. It encompasses a diverse range of Java Plum leaf conditions encountered in real-world Java Plum cultivation, ensuring its practical relevance.

Dataset Characteristics

Origin: Titas and Barura, Cumilla, Bangladesh
Image Type: Color photographs
Image Resolution: Varies
Number of Images: Adequate for training and testing deep learning models
Number of Classes: 6
Bacterial_Spot
Brown Blight
Dry
Healthy
Powdery Mildew
Sooty Mold

Usage

The Java Plum Leaf Disease Detection Dataset is primarily intended for developing and evaluating deep learning models for Java Plum leaf disease detection. It can also be used for various research purposes, such as analyzing the prevalence of different Java Plum leaf diseases and investigating the impact of environmental factors on leaf health.

Significance

The Java Plum Leaf Disease Detection Dataset is a valuable resource for advancing the field of precision agriculture in Bangladesh. By enabling the development of accurate Java Plum leaf disease detection systems, it has the potential to significantly enhance Java Plum cultivation practices, leading to increased productivity and reduced economic losses.
DOI: 10.17632/b3jy2p6k8w.2
title: SAR-CLD-2024: A Comprehensive Dataset for Cotton Leaf Disease Detection

description: The Cotton Leaf Disease Detection Dataset represents a valuable resource for researchers, practitioners, and stakeholders in the agricultural sector, offering insights and tools to address the challenges associated with cotton leaf diseases effectively. Through accurate identification and classification of cotton leaf diseases, the dataset enables early detection, empowering farmers to take timely actions and optimize crop management strategies. Moreover, it supports the advancement of machine learning algorithms and methodologies for disease detection, fostering innovation in agricultural research. This dataset comprises meticulously curated images capturing various stages of cotton leaf diseases, sourced from the National Cotton Research Institute field in Gazipur. These images, captured using a Redmi Note 11s smartphone, represent a diverse range of disease manifestations across different dimensions. Despite challenges like fluctuating lighting conditions, field surveys conducted between October 2023 and January 2024, guided by domain experts, ensured high-quality image acquisition. The dataset contains 2137 images divided into seven classes, covering various cotton leaf conditions like bacterial blight, curl virus, and healthy leaves. These classes represent different issues affecting cotton plants, including diseases, pests, and environmental stress. Additionally, the dataset undergoes thorough preparation and augmentation procedures, including data cleaning, labeling, and augmentation techniques such as flipping and brightening. As a result, it comprises 2137 original images and 7000 augmented images, enhancing the effectiveness of deep learning models for precise classification and diagnosis of cotton leaf diseases.

1. Original (Cotton Leaf Disease Detection) Dataset:
 Number of datasets: 2137
 Data format: .jpg

2. Augmented (Cotton Leaf Disease Detection) Dataset:
 Number of datasets: 7000
 Data format: .jpg
DOI: 10.17632/289jtphg33.2
title: Artificial Intelligence Adoption Prediction Model: Would ChatGPT-3.5 be adopted in English poetry classrooms?

description: This is version 2 of the dataset created and used to explore ChatGPT-3.5's ability to write, justify and analyse English poems. This version was created after the reviewers decision that this paper may be published, if some changes are made.

The purpose of the research was to determine if ChatGPT-3.5 would be adopted in English poetry classrooms. As none of the theoretical models were applicable, the Artificial Intelligence Adoption Prediction Model (AIAPM) was designed. Based on this model, an Artificial Intelligence Adoption Prediction tool (AIAPT) was designed to calculate an Adoption Prediction Score (APS). Then, ChatGPT-3.5's ability to write, justify and analyse poems were explored. 

It was found that ChatGPT-3.5 could write, justify, and analyse poems, but it could also make errors and hallucinate convincingly. Thus, the AIAPT was used to calculate the Adoption Prediction Score. The APS was 9, thus all factors of the AIAPM could drive the adoption decision. Thus, it could be predicted that ChatGPT-3.5 would be adopted in English poetry classrooms, both for ethical and unethical purposes. Based on the results, a few pro-active strategies were suggested.

This dataset contains all data created and used during the research, including the poems which were integrated in the paper: "An Artificial Intelligence Adoption Prediction Model to determine if ChatGPT-3.5 would be adopted in English poetry classrooms" which was submitted toe Heliyon for publication.
DOI: 10.17632/m5wb4pnf6x.1
title: Persistence of Long COVID

description: Dataset relative to the paper "Persistence of Long COVID symptoms  in a heterogeneous prospective cohort
DOI: 10.17632/s48xhds5z9.4
title: A study on archaeological production sites of South Korean bronze bells through slag and soil analysis

description: Fig 1. a) Location of Seocheon and a map of major cities in South Korea; b) Drawing of the casting workshop site in Singeom-ri, Seocheon.
Fig 2. Casting mold found in a workshop at the Singeom-ri, Seocheon archeological site 
Fig 3. A map of bell casting remains and temple bells in Korea
Fig 4. Bell casting remains found in Korea and Japan
Fig 5. Bronze slag and soil samples excavated from the archaeological site in Singeom-ri, Seocheon
Fig 6. X-ray diffraction (XRD) results of slag excavated from the Singeom-ri archaeological site (Cu: cuprite, Ca: cassiterite, Q: quartz, Ma: malachite)
Fig 7. a) Metallurgical microscopic image of SC-1 metal prill and tin oxide on the vitrified matrix; b) metallurgical microscopic image of SC-2 metal prill and tin oxide on the vitrified matrix; c) Scanning electron microscope (SEM) image of SC-1 slag with SnO2 crystal (Cs) and bronze prill (Br); d) SEM image of SC-2 slag with acicular tin(IV) oxide (SnO2) crystal (Cs) and bronze prill (Br); and e) Energy dispersive X-ray spectrometry (EDS) mapping image of SC-2
Fig 8. a) Reduction of a bronze structure observed in SC-3 microscopic metallurgical image; b) α phase and eutectic phase (α+δ) observed in the microscopic metallurgical image of SC-4; c) Scanning electron microscope (SEM) image of SC-3 with observed α and eutectic phases, and chlorine (Cl) detected in the corroded eutectic phase; d) SEM image of SC-4 α and eutectic phases 
Fig 9. a) Map of zones according to the lead isotope ratio of galenas in South Korea; b) comparison of lead isotope ratios of slag samples and galenas in South Korea
Fig 10. a) Location of the archaeological site in Singeom-ri, Seocheon, and excavation sites of Korean bronze bells; and b) a comparison of the distribution of lead isotope ratio of slag samples and galenas of bronze bells in South Korea.

Table 1 Bell casting remains in Korea
Table 2 Composition of Korean bronze bells
Table 3 Wavelength dispersive X-ray fluorescence spectrometer (WD-XRF) analysis of slag samples SC-1 and 2 from the archaeological site in Singeom-ri, Seocheon
Table 4 Wavelength dispersive X-ray fluorescence spectrometer (WD-XRF) analysis of slag samples SC-3 and 4 from the archaeological site in Singeom-ri, Seocheon
Table 5 Energy dispersive X-ray spectrometry (EDS) analysis of SC-3 and SC-4
Table 6 Lead isotope ratio of the slag found at the archaeological site in Singeom-ri, Seocheon
Table 7 Analysis of soil samples from bell foundry remains at the archaeological site in Singeom-ri, Seocheon
DOI: 10.17632/8pkr9jr6v4.1
title: A Meta-Analysis Dataset of the Empirical Agricultural Technology Adoption Literature

description: This meta-analysis dataset is a convenience sample of empirical results from 218 separate studies of agricultural technology adoption in Africa, Asia, and Latin America. Each study uses survey data to estimate a form of multiple regression of adoption of a technology (dependent variable) with a diverse array of predictor variables. 

These data were used in the following publication:
Ruzzante, S., Labarta, R., & Bilton, A. (2021). Adoption of Agricultural Technology in the Developing World: A Meta-Analysis of the Empirical Literature. World Development, 146, 105599. https://doi.org/10.1016/j.worlddev.2021.105599.

The data collection and curation procedures are described in the following publication:
Ruzzante, S., & Bilton, A. (2021). Adoption of Agricultural Technologies in the Developing World: A Meta-Analysis Dataset of the Empirical Literature. Data in Brief, Submitted.

Three data files are included:
1) AgTechAdoption.xlsx: This is the main data file, which contains effect size estimates for certain predictor variables on adoption of agricultural technologies in the developing world, drawn from 384 statistical models published in 218 studies.

2) Data Column Descriptions.pdf: This file provides detailed definitions for each of the column headings in AgTechAdoption V3.xlsx

3) Reference List: This file provides formatted citations for each of the 218 studies included in the meta-analysis dataset.
DOI: 10.17632/8w55xstk83.1
title: libCreme: An optimization library for evaluating convex-roof entanglement measures

description: This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018) Abstract We present the software library libCreme which we have previously used to successfully calculate convex-roof entanglement measures of mixed quantum states appearing in realistic physical systems. Evaluating the amount of entanglement in such states is in general a non-trivial task requiring to solve a highly non-linear complex optimization problem. The algorithms provided here are able to achieve to do this for a large and important class of entanglement measures. The library is mostly writte... Title of program: libCreme Catalogue Id: AEKD_v1_0 Nature of problem Evaluate convex-roof entanglement measures. This involves solving a non-linear (unitary) optimization problem. Versions of this program held in the CPC repository in Mendeley Data AEKD_v1_0; libCreme; 10.1016/j.cpc.2011.08.012
DOI: 10.17632/68yy284sh9.1
title: K-Kotagiri Tea Leaf Dataset

description: In the serene tea fields of Kotagiri (Kaithala), Tamil Nadu, India, a dedicated team embarked on a fascinating journey to delve into the intricacies of tea leaf diseases using captured images. Datasets consist of 4259 images which includes original and augmented images of healthy and disease classes. Out of which, 225 original images of healthy class and 303 original images of disease class. Similarly, 1610 augmented images of healthy class and 2121 augmented images of disease class.
DOI: 10.17632/tz69tvbzt8.1
title: Formyl-methionine-mediated eukaryotic ribosome quality control pathway for cold adaptation. C. -S. Lee et al.

description: Raw image data for the manuscript "Formyl-methionine-mediated eukaryotic ribosome quality control pathway for cold adaptation." by Chang-Seok Lee, Jaehwan Sim, Sang-Yoon Kim, Hyeonji Lee, Tae-Young Roh, and Cheol-Sang Hwang
DOI: 10.17632/h8bdwrtnr5.1
title: RINGS algorithm dataset

description: This repository contains the image dataset and the manual annotations used to develop the RINGS algorithm for automated prostate glands segmentation: - Salvi M., Bosco M., L. Molinaro, Gambella A., Papotti M., Udyavara Rajendra Acharya, and Molinari F., "A hybrid deep learning approach for gland segmentation in prostate histopathological images", Artificial Intelligence in Medicine 2021 (DOI: 10.1016/j.artmed.2021.102076) Background: In digital pathology, the morphology and architecture of prostate glands have been routinely adopted by pathologists to evaluate the presence of cancer tissue. The manual annotations are operator-dependent, error-prone and time-consuming. The automated segmentation of prostate glands can be very challenging too due to large appearance variation and serious degeneration of these histological structures. Method: A new image segmentation method, called RINGS (Rapid IdentificatioN of Glandural Structures), is presented to segment prostate glands in histopathological images. We designed a novel glands segmentation strategy using a multi-channel algorithm that exploits and fuses both traditional and deep learning techniques. Specifically, the proposed approach employs a hybrid segmentation strategy based on stroma detection to accurately detect and delineate the prostate glands contours. Results: Automated results are compared with manual annotations and seven state-of-the-art techniques designed for glands segmentation. Being based on stroma segmentation, no performance degradation is observed when segmenting healthy or pathological structures. Our method is able to delineate the prostate gland of the unknown histopathological image with a dice score of 90.16% and outperforms all the compared state-of-the-art methods. Conclusions: To the best of our knowledge, the RINGS algorithm is the first fully automated method capable of maintaining a high sensitivity even in the presence of severe glandular degeneration. The proposed method will help to detect the prostate glands accurately and assist the pathologists to make accurate diagnosis and treatment. The developed model can be used to support prostate cancer diagnosis in polyclinics and community care centres.
DOI: 10.17632/bz35rgnr8v.1
title: Consumer purchase behavior towards clothing brand Mconte carlo - a study in Ludhiana city

description: In this research we have used a questionnaire to find out the customer’s prospective about Monte Carlo Fashions Ltd. This Research is done to gain familiarity with a phenomenon event / product / service or to determine the frequency, with which something occurs, with which is associated with something else or to test a hypothesis of casual relationship between variables. In short customer perception research is the objective and formal process of systematically obtaining, analyzing and interpreting the data for actionable decision making in customer perception towards an organization (Monte Carlo in my study).The basic objective of this study is to analyze the customer perception towards Monte Carlo
DOI: 10.17632/vvyws6ptvd.2
title: A Pseudomonas Plant Growth Promoting Rhizobacterium and Arbuscular Mycorrhiza differentially modulate the growth, photosynthetic performance, nutrients allocation, and stress response mechanisms triggered by a mild Zinc and Cadmium stress in tomato

description: Supplementary material of manuscript - A Pseudomonas Plant Growth Promoting Rhizobacterium and Arbuscular Mycorrhiza differentially modulate the growth, photosynthetic performance, nutrients allocation, and stress response mechanisms triggered by a mild Zinc and Cadmium stress in tomato