cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/d4yhn5b9n6.2
title: Swahili Corpus

description: The repository contains several text files each corresponding to categories of Swahili Corpus. The categories are Health (AFYA), Business and Industries (BIASHARA), Parliament (BUNGE), Religion (DINI), Education (ELIMU), News (HABARI), Agriculture (KILIMO), Social Media (MITANDAO), Non-Governmental Organizations (MASHIRIKA YA KIRAIA), Government (SERIKALI), Laws (SHERIA) and Politics (SIASA).
Also, there is a combines text file for Swahili Corpus generated using all mentioned categories.
DOI: 10.17632/p6zc7krs37.1
title: Bangla ( Bengali ) sentiment analysis dataset

description: Bangla ( Bengali ) sentiment analysis dataset
DOI: 10.17632/yx9ffwdgjg.1
title: Data for: FOOD-RELATED ROUTINES, PRODUCT CHARACTERISTICS, AND HOUSEHOLD FOOD WASTE IN THE UNITED STATES: A REFRIGERATOR-BASED PILOT STUDY

description: Code and data used in: Davenport, M.L., Qi, D. & Roe, B.E. (2019). "Food-related routines, product characteristics, and household food waste in the United States: A refrigerator-based assessment ". Submitted to Resources, Conservation and Recycling. 1. Analysis Stata (.do) file 2. State of the American Refrigerator Survey: Refrigerator Inventory Data
DOI: 10.17632/2w3wy6ctvr.1
title: Solid Wood Board Dataset

description: We established a data set about solid wood board, which was used for image inpainting in order to reconstruct texture. These images are regular small-size images segmented from the complete large image, so as to be used as the input of the model.
DOI: 10.17632/mwfb74s6rk.1
title: Supplemental materials JAAD-D-24-02405

description: Supplemental materials JAAD-D-24-02405: COVID-19 infection is associated with an elevated risk for autoimmune blistering diseases while COVID-19 vaccination decreases the risk: A large-scale population-based cohort study of 112 million individuals
DOI: 10.17632/835yrp4rww.1
title: H2SOLV: Fortran solver for diatomic molecules in explicitly correlated exponential basis

description: Abstract We present the Fortran package H2SOLV for an efficient computation of the nonrelativistic energy levels and the wave functions of diatomic two-electron molecules within the Born–Oppenheimer approximation. The wave function is obtained as a linear combination of the explicitly correlated exponential (Kołos–Wolniewicz) functions. The computations of H2SOLV are performed within the arbitrary-precision arithmetics, where the number of working digits can be adjusted by the user. The key part of H2... Title of program: H2SOLV Catalogue Id: AFBA_v1_0 Nature of problem Numerical solution of the two-center two-electron Schrödinger equation within the Born-Oppenheimer approximation using the explicitly correlated basis set of Kolos-Wolniewicz functions. Versions of this program held in the CPC repository in Mendeley Data AFBA_v1_0; H2SOLV; 10.1016/j.cpc.2016.07.024 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)
DOI: 10.17632/b5s8ywwgwr.1
title: Mechanical Properties Dataset of BFRC for strength prediction with machine learning

description: Data were obtained from a large number of dissertations.As most of the concrete requirements focus on the compressive strength at 28 days, only data referring to specimens that were tested at this age were selected. 
Numerous parameters relating to the mechanical properties and mix design of BFRC were included in this dataset. The parameters of the mix design included in the database were cement (C), silica fume (SF), fly ash (FA), coarse aggregate (CA), fine aggregate (FA), water (W), and superplasticizer (S), and the parameters related to the fiber properties were diameter (FD), length (FL), and fiber volume fraction (FF). Finally, the mechanical properties recorded in the dataset were compressive strength (CS), flexural strength (FS), and splitting tensile strength (STS). The dataset contained 13 parameters divided into ten features and three targets.
DOI: 10.17632/gs97g3mgwv.2
title: Xia et al NEPO wtCaCO3%

description: The data file provides coordinates, depth, wtCaCO3% of the surface/coretop marine sediments in the Northeast Pacific Ocean and sources for the data.
DOI: 10.17632/v7xzbtkww2.1
title: Supplementary dataset of Tingxuan Jiang's PhD dissertation

description: This file contains all the supplementary dataset and figures for my PhD dissertation. For the details, please refer to the dissertation: https://doi.org/10.3990/1.9789036563611
DOI: 10.17632/bs2j56pn7y.1
title: Graphite//LFP synthetic training diagnosis dataset

description: This training dataset was calculated using the mechanistic modeling approach. See the “Benchmark Synthetic Training Data for Artificial Intelligence-based Li-ion Diagnosis and Prognosis“ publication for mode details. More details will be added when published. The diagnosis training dataset was compiled with a resolution of 0.01 for the triplets and C/25 charges. This accounts for more than 5,000 different paths. Each path was simulated with 0.85% increases for each degradation up to 85%. This accounts for 100 simulations per path. The training dataset, therefore, contains more than 500,000 voltage vs. capacity curves. 4 Variables are included: Cell info: Contains information on the setup of the mechanistic model 1 Positive electrode 2 Negative electrode 3 Loading ration 4 Offset 5 Resistance adjustment Qnorm: normalize capacity scale for all voltage curves pathinfo: index for simulated conditions for all voltage curves 1 LLI 2 LAMPE 3 LAMNE 4 Corresponding capacity loss volt: voltage data. Each column corresponds to the voltage simulated under the conditions of the corresponding line in pathinfo.
DOI: 10.15468/dl.wjbsdv
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is India",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Artocarpus heterophyllus Lam.",
 "Year 1970-2000"
 ]
}

 The dataset includes 18 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009313-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/hnvkvj589y.1
title: Afaan Oromoo Text-to-Speech Dataset

description: Afaan Oromo is one of the languages that have huge speakers in the horn of Africa. It is also one of the under-resourced languages like other Ethiopian languages. In this Dataset preparation, the soul purpose of the project was to include Afaan Oromo text-to-speech synthesis in our Final year Humanoid robot that can speak the Oromo language in addition to its vision capability to detect emotion, gender, and detect faces of humans. 
Currently, the natural language processing applications that use this language are in high demand. Furthermore, the linguists and researchers that work on these languages are contributing a lot of data to the growth of this language to make it an international and machine language. 

This dataset has been started by two Electrical Engineering students at Madda Walabu University, during their 4 months industry internship program at iCog-Labs, while working on machine learning tasks related to Natural language processing. The first phase of the audio was recorded at Addis Ababa University by the two students and the preprocessing was also done by them. The second phase of the audio recording was done at Madda Walabu university after their internship was completed. They have selected female students from the Electrical engineering and Afaan Oromo department to record the audio to get more corpus to train the machine learning model. The model used was Tacotron 1 and 2 with waveGlow and TensorFlow framework that was developed by NVIDIA company. 

The Corpus statistics
Total clips:              1,224
Total Words:           17,559
Total characters:     116,439
Total Duration:       03:11:13
Min clip length:     1 sec
max clip length:     59 sec
Unique words:       5,040

Credits
The volunteers that participated in the audio recording need to be appreciated and they were concerned about their language. They are Obsinet Asmare Motuma, Milko Wariyo Gobana, Roza Hailu Isho, Demitu Baye Boyosa.
DOI: 10.17632/mvd57skzd9.1
title: BREMS: A program for calculating spectra and angular distributions of bremsstrahlung at electron energies less than 3 MeV

description: This work describes a program that implements the method developed by Tseng and Pratt in the 1970s for exact screened calculations of atomic-field bremsstrahlung. The calculation method is based on the relativistic partial-wave formulation describing interaction of the incident electron with an arbitrary central potential of the neutral target atom. The set of Fortran-90 codes BREMS has been written with the aim of creating a comprehensive library of spectra and shape functions of unpolarized atomic-field bremsstrahlung for all chemical elements and for the approximate range of the incident electron energy from 10 eV to 3 MeV on a dense energy grid, using the best theory available. Several examples of using this software and its verification against the published data calculated using the same theory are provided. BREMS can be run on modern personal computers, with processing times from several minutes to several hours, depending on the user-specified values of the atomic number, incident electron energy, and photon energy, as well as on the accuracy requested.
DOI: 10.17632/nwxv38dxsr.1
title: Data repository: Annual industrial and commercial heat load profiles: modeling based on k-Means clustering and regression analysis

description: This data repository includes results of the original research article “Annual industrial and commercial heat load profiles: modeling based on k-Means clustering and regression analysis”. In this article, a method to predict annual heat load profiles with a daily resolution for large consumers from industry and commerce is developed. This method is based on a cluster and regression analysis of natural gas load profiles from 797 German consumers, most with a consumption of more than 1.5 GWh/a. The data repository contains plots of all 797 original normalized load profiles and predicted normalized load profiles in the form of time series. The correlation between daily mean ambient temperature and daily normalized natural gas consumption is visualized in additional figures for each load profile. The files in this data repository are sorted by a two-digit numerical code indicating the economy division according to NACE Rev. 2 [1] (see README) and a one-digit numerical code indicating the detected clusters. The dependency of natural gas consumption on working days on mean daily ambient temperature increases from cluster 0 to cluster 3. The cluster CHP includes consumers that were excluded from the analysis, since they operate a combined heat and power plant (CHP). In a plausibility check, additional consumers were excluded from the analysis. These consumers are assigned to the cluster -1. References [1] Eurostat. NACE Rev.2: Statistical classification of economic activities in the European Community. Luxembourg: Office for Official Publications of the European Communities; 2008.
DOI: 10.17632/5z68cvxssn.1
title: CareerMap- Mapping Tech Roles With Personality & Skills

description: The current research done in the field of Career Guidance system has been very nascent and limited in its approaches. In terms of ML Based approaches required to build an AI Career Guidance System, we require a good amount of labeled data. The requirements for which were not being able to be fulfilled in a single dataset. Hence, we took the ensemble approach of combining datasets to solve the problem of building a Career Guidance system. Based on Literature Review conducted, it has been observed that apart form proficiency skills in various domains and concepts of Computer Science, a candidate’s psychological traits also played an important role in predicting their career. Thus, with sufficient literature reviewed and individual datasets obtained, we form our problem definition as:

“To combine datasets of psychological traits and proficiency in technological skills and apply Machine Learning models to predict the career of an individual in the field of Computer Science delivered through an interactive frontend.”

The dataset consists of 9180 rows and 28 features.
The features include: 
1.	Database Fundamentals
2.	Computer Architecture
3.	Distributed Computing Systems
4.	Cyber Security
5.	Networking
6.	Development
7.	Programming Skills
8.	Project Management
9.	Computer Forensics Fundamental
10.	Technical Communication
11.	AI ML
12.	Software Engineering
13.	Business Analysis
14.	Communication skills
15.	Data Science
16.	Troubleshooting skills
17.	Graphics Designing
18.	Openness
19.	Conscientiousness
20.	Extraversion
21.	Agreeableness
22.	Emotional Range
23.	Conversation
24.	Openness to Change
25.	Hedonism
26.	Self-enhancement
27.	Self-transcendence
28.	Role
DOI: 10.17632/pwzndx3yjk.1
title: ‘BHARAT VARSHA’ Authored by Syed Mustafa Siraj(1930-2012) and Translated by Dr. Md Siddique Hossain

description: SUMMARISATION: Syed Mustafa Siraj, a renowned Bengali author, was known for his captivating works, including 'Neel Ghorer Nati' and 'Aleek Manush'. He was a prominent figure in music and later pursued a career in music. Siraj's short story, "Bharat Varsha," was included in a Bangla textbook for students of the West Bengal Council for Higher Secondary Education during a time of deep-seated division in India. The story depicts a marketplace in a rural settlement, surrounded by bamboo and surrounded by a brick kiln. The market is a symbol of resistance against communism and the impact of untimely rainfall on agricultural yields. In a hamlet, people engage in unrestricted behavior, often leading to intense discussions and physical altercations. During winter, they gather near an oven to raise their body temperatures and discuss various topics. The tea vendor, who earns revenue from selling tea, maintains a sense of assurance over remuneration from the locals. One day, an elderly woman, known for her wrinkles and aging appearance, is found motionless and discarded in the riverbed. The villagers, concerned about her fate, decide to transport her to the nearby police station, knowing her decomposition will determine her fate. The decomposing cadaver remains immobile in the sunlight, and the villagers contemplate the arrival of a ravenous vulture swarm. A group of Hindus and Mohammedans recite rituals in Arabic while transporting a corpse from a nearby region. The Hindus, who abandoned the corpse, were enraged and decided to interment her in a cemetery. Rival factions vying for control of the gurney began, with spectators tossing profanities and brandishing swords and pikes. The government watchman tried to avert the conflict, but his words went unnoticed. Unbeknownst to everyone, the deceased corpse trembled and a trembling woman appeared. The bewildered guardian proclaimed, "Burima, you were not dead!" The woman, enraged, questioned her beliefs and demanded to leave before time ran out. The enraged woman gathered her possessions and disappeared, never to be re-observed.
DOI: 10.17632/xh22fsmvmc.2
title: Corruption Dataset

description: The sampling frame used for data collection comprised students and employees from the University of Basra, Iraq, and Basra citizens who were digitally savvy. The sampling technique and procedure used to select the participants for the study was purposive sampling, which is also known as judgmental sampling (Saunders et al., 2016). The rationale for using purposive sampling stemmed from the characteristics of the population and the objective of the study (Saunders et al., 2016). We decided that, based on the objectives of the research, a sampling frame comprising the students and employees of University of Basra, Iraq, as well as interested digitally savvy citizens in Basra was the most suitable and appropriate. The measured items under consideration were translated into Arabic and inserted into Google Forms as an electronic survey. We invited 20 friends and relatives, using the purposive sampling procedure (Saunders et al., 2016) to fill in the form. The items themselves and the results were discussed with five academics from the College of Administration and Economics, University of Basra, for pre-testing purposes (Saunders et al., 2016). Accordingly, we made slight changes to the first version to ensure reliability and validity (Sekaran and Bougie, 2013). The questionnaire (see Table 3. 1) thus became much more understandable for all educational levels.
DOI: 10.17632/zy9w2pd64j.2
title: Business Intelligence Research Dataset (1975-2020)

description: The business intelligence research and publication dataset, which was indexed by Scopus from 1975 to 2020. The dataset contains data authors, authors ID Scopus, title, year, source title, volume, issue, article number in Scopus, DOI, link, affiliation, abstract, index keywords, references, Correspondence Address, editors, publisher, conference name, conference date, conference code, ISSN, language, document type, access type, and EID.
DOI: 10.17632/rc349j45m5.1
title: ISLAN

description: In order to help the deaf-mute community, in this research work we have collected and created a dataset for Indian Sign Language (ISL) Recognition called the ISLAN dataset. ISLAN consists of the ISL representation of English Alphanumeric signs. ISLAN has a total collection of 700 sign images and 24 sign videos. ISLAN dataset is intended to be publicly made available for free for the research community so as to help the impaired community to enable the communication by developing the ISL recognition system.
DOI: 10.17632/9kk26h4w6s.2
title: Developing ML Models for Early Stage Building Energy Prediction (using CNN)

description: The ML model for early stage building energy predictions is developed using convolutional neural network (CNN) approach, proposed by [1] M.M. Singh, P. Geyer, CNN-based Quick Energy Prediction Model using Image Analysis for Shape Information, in: 17th Int. IBPSA Build. Simul. Conf., Brugges, Belgium, 2021. https://www.researchgate.net/publication/354420055
DOI: 10.17632/vgr5r76257.1
title: Genomic insight into the Hyalomma anatolicum biology by comparative genome analysis

description: Supplementary Table 1. Repeat sequence annotation.
Supplementary Table 2. Homology comparision of gene, exon and intron.
Supplementary Table 3. non-Coding RNA.
Supplementary Table 4. Expanded gene families in Hyalomma anatolicum.
Supplementary Table 5. Heme related and hemoglobin digesting genes.
Supplementary Table 6. Oxidative stress associated genes.
Supplementary Table 7. Cytochrome P450 family genes.
Supplementary Table 8. Environment sensing related genes.
Supplementary Table 9. G protein coupled receptors.
Supplementary Table 10. Immune pathway related genes.
Supplementary Table 11.  Genes related to epigenetic molecular mechanism.
Supplementary Table 12. Predicted neruopeptide encoding genes in Hyalomma anatolicum genome.
Supplementary Table 13. Ka/Ks values from pairwise comparisons.
Supplementary Table 14. Funcational annotation of positively selected genes.
DOI: 10.17632/ccd7y6wr7t.1
title: Data for: The First Complete Mitochondrial Genome Data of Hippocampus kuda Originating from Malaysia

description: Malaysian Hippocampus kuda FASTA files for this manuscript
DOI: 10.17632/zfwr38f2bf.1
title: Replication code for Du, Hebert and Li (2023) "Intermediary Balance Sheet and Treasury Yield Curve", forthcoming in Journal of Financial Economics

description: We provide replication code and pseudo data for Du, Hebert and Li (2023) "Intermediary Balance Sheet and Treasury Yield Curve", forthcoming in Journal of Financial Economics”,
DOI: 10.17632/tpf5527bkx.1
title: Data for: Survey dataset on the prevalence of childhood maltreatment history among drug addicts in Malaysia

description: Survey dataset on the prevalence of childhood maltreatment history among drug addicts in Malaysia
DOI: 10.17632/yf786kcn3b.3
title: Precision Agriculture in the United States: A Comprehensive Meta-Review Inspiring Further Research, Innovation, and Adoption

description: Precision agriculture has emerged as a dominant force in the United States, with widespread adoption of advanced technologies and decision support systems (DSS) since the 1980s. Key tools such as variable rate application (VRA), autopilot systems, and remote sensing have become integral for U.S. farmers, offering invaluable insights from crop, soil, and weather information to optimize agricultural production while minimizing environmental impact. To synthesize and categorize the extensive research available on precision agriculture, a systematic review protocol has been designed. Our objective is to offer clear and authoritative insights into the nature, scope, and volume of this field. Implementing a rigorous search strategy, we utilized renowned databases such as ScienceDirect® and Web of ScienceTM to gather relevant and significant materiality. The retrieval process involved the use of indexing terms and Boolean operators, with a focus on 'precision agriculture' and 'precision farming', striking a balance between specificity and comprehensiveness. To ensure the credibility of our findings, only peer-reviewed papers authored by individuals affiliated with U.S. institutions have been included. Expert reviewers with deep knowledge in the field independently assessed the selected papers, thoroughly evaluating titles, abstracts, keywords, methods, conclusions, and declarations. Consistency and eligibility were paramount in determining which papers met the criteria for inclusion. Any discrepancies or disagreements were resolved through rigorous consensus-building discussions among the reviewers. Through this comprehensive meta-review, we provide a scientific contribution that enhances our understanding of precision agriculture, highlighting focus areas for further research and development (R&D). By synthesizing and categorizing the existing literature, we offer authoritative insights into the research landscape, informing future investigations and fostering innovation. Focusing specifically on the U.S., we shed light on the unique aspects and pioneering advancements in precision agriculture within the country. Ultimately, our findings have the potential to drive progress, contributing to sustainable development, increased productivity, enhanced environmental sustainability, and responsible agricultural practices.
DOI: 10.17632/rh82j6shtm.1
title: Disclosure of specific information in social responsibility reports and the cost of debt financing

description: Using machine learning for text analysis on a sample of social responsibility reports from Chinese A-share listed companies between 2009 and 2021, we have constructed an indicator to measure the level of specificity in the disclosure of these reports. We then analyze the effect of this specificity in CSR reports on the cost of corporate debt financing. Our study finds that the specificity of disclosure in CSR reports can significantly reduce the cost of corporate debt financing. This finding remains robust across various robustness tests. Additionally, the impact of specific disclosure in CSR reports on reducing the cost of debt financing is even more pronounced under conditions of higher corporate risk, such as excessive leverage and intense product market competition. Furthermore, further analysis suggests that the disclosure of specific characteristics in CSR reports has a more significant impact on reducing the cost of debt financing when industry disclosure is homogeneous, the information disclosure environment of firms is more perfect, and the intensity of information dissemination is higher.
DOI: 10.17632/ky875dw7df
title: Fetal sex and preeclampsia

description: Database of the research protocol