cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/wpxb2mkx2m
title: 3D Digital Outcrop Models Late Jurassic (Oxfordian) Hanifa Fm - Wadi Birk, Central Saudi Arabia: Shallow marine carbonate platform sediments equivalent to Arabian subsurface reservoirs

description: In February 2019 drones were utilized to collect aerial imagery of the Tuwaiq mountain outcrops in central Saudi Arabia exposing the Hanifa Formation at Wadi Birk. A 4x4 km2 was selected for the drone survey, where the study area was scanned by a fixed-wing (Wingtra) UAV for top-down view and a hexacopter (DJI M-600) for cliffs (oblique view). Both the drones were equipped with a 42-megapixel camera. During the data collection, a total of >10,000 photographs with 70% overlap were collected. Ground control points (GCPs) were laid before the survey in the study area. The imagery for the nadir survey was collected from 130 m above the ground elevation in auto mode, whereas the oblique cliff imagery was collected manually at 50-100 m distance away from the cliff face. The aerial imagery was then stitched using the Structure from Motion (SfM) technique (Pix4D and Agisoft) to develop the 3D Digital Outcrop Models. A total of eight models have been created. Seven models are for the oblique cuts of the cliff and vary in resolution from 2x2 cm2 per pixel to 5x5 cm2 per pixel, whereas one is a top-down view/nadir model that is approx. 5x5 cm2 per pixel in resolution. This dataset provides the location of the Digital Outcrop Models and the .obj files for the models.
These outcrop datasets display the Late Jurassic – Oxfordian Hanifa Formation, which is in this location composed of shallow marine lagoonal carbonate platform strata. These are equivalent in facies to many Oxfordian and Kimmeridgian subsurface reservoirs of the Arabian platform and elsewhere in the Middle East.
DOI: 10.6084/m9.figshare.23928468.v5
title: minus_assembly_dataset

description: Contains seven items:<i>V. vitis-idaea</i> ssp. <i>minus</i> <i>de novo</i> assembly in fasta format.<i>V. vitis-idaea</i> ssp. <i>minus</i> scaffolded assembly by mapping to the bilberry genome in agp format based on contig names in the <i>de novo</i> assembled genome (<i>V. myrtillus</i>; Wu et al. 2021).<i>V. vitis-idaea</i> ssp. <i>minus</i> scaffolded assembly by mapping to the bilberry genome in fasta format (<i>V. myrtillus</i>; Wu et al. 2021).Annotation of genes/mRNAs associated with the scaffolded genome in .gff3 format.Protein sequences from gene annotation in amino acid fasta or faa format.Coding sequences in nucleotide fasta format.Annotation of transposable elements associated with the scaffolded genome in gff3 format.Raw sequences generated in this study are found in NCBI under PRJNA998787: Oxford Nanopore (SRR25468432-SRR25468441), Illumina NovaSeq (SRR25477289)The contig-level assembly fasta can also be found in NCBI: JAUYVF000000000Reference: Wu,C., Deng,C., Hilario,E., Albert,N., Lafferty,D., Plunkett,B., Elborough,C., Saei,A., Jaakola,L., Karppinen,K., Grande,A., Kylli,R., Allan,A., Espley,R. and Chagne,D. 2021. A chromosome-scale assembly of the bilberry genome identifies a complex locus controlling berry anthocyanin composition. Molecular Ecology Resources, DOI 10.1111/1755-0998.13467
DOI: 10.17632/8z9532ps65
title: Academic procrastination data of students in Makassar, Indonesia

description: This data was obtained from an assessment that used an academic procrastination scale on 586 students in the XIII semester at Makassar, Indonesia. Students responded to statements by using a Likert-scale of 5,4,3,2,1, which represents strongly agree, agree, doubt, disagree, and strongly disagree, respectively.
DOI: 10.17632/th5tgy7bzk
title: Work Design Questionnaire

description: The WDQ is a scale derived from: Morgeson, F. P., & Humphrey, S. E. (2006). The Work Design Questionnaire (WDQ): Developing and validating a comprehensive measure for assessing job design and the nature of  work. Journal of Applied Psychology, 91, 1321-1339. The objective of the research was to verify the work design in the midst of the COVID-19 pandemic. Quantitative research with survey-type data collection and data analysis with psychometric validation and multivariate statistics with confirmatory factor analysis.
DOI: 10.6084/m9.figshare.6205595.v2
title: Chronic sleep curtailment, even without extended (&gt;16-h) wakefulness, degrades human vigilance performance

description: This is a data set derived from controlled in-laboratory conditions of individuals exposed to either control (equivalent to a sleep opportunity ~8h) or chronic sleep restricted conditions (equivalent to a sleep opportunity ~5.6h). This study was accomplished using a circadian forced desynchrony design on a 20-h day length. All subjects provided written informed consent prior to participation and all procedures were approved by the Partners Healthcare Institutional Review Board.
DOI: 10.6084/m9.figshare.7414817.v1
title: Additional file 3: of Genome-wide identification and localization of chalcone synthase family in soybean (Glycine max [L]Merr)

description: List of 40,972 duplicated gene pairs in Glycine max genome (XLSX 2404 kb)
DOI: 10.17632/ksypsm2zh3
title: Housing submarket segmentation house price dataset. A typology-based case study in Madrid

description: This dataset contains a series of house sales prices metrics at neighborhood level for the city of Madrid, from the Spanish real estate listings portal www.idealista.com. The objective of the related research is to demonstrate that a segmentation of administrative divisions improve the significance of price parameters, such as average price.

We defined 8 typomorphologic using the K-Means algorithm:

 Compact fabric (historic center)
 Consolidated fabric (old neighborhoods)
 Compact block (expansion)
 Open block (new extensions) 
 Open building 1 (compact)
Open Building 2 (Fine Grain)
Single-family home 1 (medium intensity)
Single-family home 2 (low intensity)

Data is delivered at neighborhood level, with the following variable set:

    DISTRICTNAME: District name
    NEIGHBORHOODNAME: Neighborhood name
    CLUSTER: Interquartile name
    N: Number of ads in the stratum 
    AVG_UNITPRICE: Average unit price euros/square meters (geometric mean)
    Q1_UNITPRICE: 1st quartile price eur/sqm
    Q3_UNITPRICE: 3rd quartile price eur/sqm 
    IQR: Interquartile range
    CV: Coefficient of variation of the stratum

We include data split in typomorphological groups or at neighborhood level (when CLUSTER contains the literal 'Complete neighborhood').

Polygons are also included in EPSG: 4326.

Data corresponds to ad published during the year 2018.
DOI: 10.17632/s4rfcckr39
title: Ghana Annual Conversion to Gold Mining 2007-2017 and Total Conversion up to 2019

description: These data are associated with an article published in Science of the Total Environment in 2021 (currently in revision). In this study, the Landsat image archive available through Google Earth Engine was used to quantify the total footprint of vegetation loss due to artisanal gold mines in Ghana from 2002-2019 and understand how conversion of forested regions to mining has changed over a decadal period from 2007-2017. Areas that experienced anomalous vegetation loss from 2005 to 2019 were identified through assembling a Landsat imagery timestack from 2002 to 2005. A separate imagery timestack was assembled from 2010 to 2019 to establish an observation period. A combination of machine learning and change detection algorithms were then used to calculate land cover conversion to gold mining and the timing of conversion annually. Details regarding methods and Earth Engine code can be found in the supplemental information with the manuscript. File Description: FullConversiontoMiningExtent2019: Total area of gold mining conversion detected from 2002-2019. Attributes: MineType, AreaM2, AreaKM2. MineType 1 = Artisanal Mines MineType 2 = Industrial Mines Resolution: 30m MiningConversion_2007_2017Vec Annual gold mining conversion for 2007-2017. Attributes: count, classifica classifica = Year of Conversion (7 = 2007, 8= 2008, etc.) Resolution: 30m Barenblitt, Abigail; Payton, Amanda; Lagomasino, David; Fatoyinbo, Lola; Asare, Kofi; Aidoo, Kenneth; Pigott, Hugo; Som, Chalres Kofi; Seidu, Omar; Smeets, Laurents; Wood, Danielle (in review). The large footprint of small-scale artisanal gold mining in Ghana. Science of the Total Environment.
DOI: 10.6084/m9.figshare.26135734.v2
title: Numerical models of magmatism in the convective mantle of the Moon 2: Role for Localized Radioactive Enrichment

description: The data for manuscript entitled "Long-lasting Volcanism of the Moon Aided by the Switch in Dominant Mechanisms of Magma Ascent: Role of Localized Radioactive Enrichment in a Numerical Model of Magmatism and Mantle Convection".
DOI: 10.17632/rgsgbbyrws
title: Studies on the mechanism of general anesthesia
DOI: 10.6084/m9.figshare.24761286.v1
title: Data on Profit Attribution of Hybrid Bond Issuers and Their Parent Companies as at March 2023

description: This dataset comprises a global list of publicly-listed issuers of hybrid bonds classified as equity (hybrids) and parent companies in non-financial sectors, and their treatment of profit attributable to hybrids (hybrids’ profit) when computing profit attributable to owners (owners’ profit) presented in income statements and profit attributable to ordinary shareholders used as the numerator of earnings per share (EPS). Hybrids issuers and parent companies are identified based on Bloomberg’s list of outstanding corporate non-convertible perpetual bonds as at 1st February 2023, and the audited financial statements of each company, available as at March 2023, are referenced to determine whether they have excluded profit attributable to hybrids held by non-controlling interests from owners’ profit and hybrids’ profit from EPS, in accordance with the requirements of the International Financial Reporting Standards.
DOI: 10.17632/7s47pjfhch
title: Data on Governance-Growth Nexus

description: The dataset contains annual observations from 2002 to 2019 used in the article "governance-growth nexus". The variables are governance predictors, GDP growth, net saving rate, human capital, and gross fixed capital formation.
DOI: 10.17632/br4r55dkc3
title: Data for: Network-based estimation of systematic and idiosyncratic contagion: The case of Chinese financial institutions
DOI: 10.17632/gxw26z33xf
title: Understanding the Space-Time Continuum A Comprehensive study on the Theory of Relativity As revealed in Vedic literature

description: The concept of the space-time continuum is one of the most profound and revolutionary ideas in the field of theoretical physics. It lies at the heart of Albert Einstein’s theory of relativity, which has reshaped our understanding of the fundamental structure of the universe. The space-time continuum is a fundamental and groundbreaking idea that has transformed our understanding of the universe. It unifies two seemingly distinct dimensions, space, and time, into a single, interconnected fabric that underlies the very nature of reality. This concept was famously introduced by Albert Einstein in his theory of general relativity, and it has since become a cornerstone of modern physics. This study provided critical analysis of the theory of Relativity and its exposure in Vedic literature. The relationship between space and time is a fundamental concept in modern physics, particularly in Einstein’s theory of relativity. This concept, known as the space-time continuum, has revolutionized our understanding of the physical universe. Surprisingly, there are intriguing parallels between the ancient Vedic literature, specifically the Srimad Bhagavata MahaPurana, and the modern scientific understanding of the space-time continuum. In this exploration, we will delve into these connections and elucidate the profound insights offered by Vedic texts regarding the interplay between matter and time. While these ideas are deeply philosophical and rooted in ancient cosmology, they offer a unique perspective on the nature of the material world and its relationship with time.
DOI: 10.17632/svnv7z65sn
title: Precision Oncology, Signaling Pathways Reprogramming and Targeted Therapy: A Holistic Approach to Molecular Cancer Therapeutics

description: The TCGA Research Network started in 2005 has profiled and analyzed a large number of human tumors to discover molecular aberrations at the DNA, RNA, protein, and epigenetic levels and thereby provided reliable diagnostic and prognostic biomarkers for different cancer types since then.The presence of mutated genes is strongly correlated with cancer incidence, very specific causative genes or a small set of genes for most cancers have not been confirmed after decades of genomic studies. Nobel laureate James D. Watson opined at Cancer World 2013: "We can go ahead and sequence every piece of DNA that has ever existed, but I don't think we'll find the Achilles heel of cancer. Importantly,, it is not only necessary to associate genetic mutations with different cancers but also to work on the mechanism of action of mutagens by focusing on enzymes which could invariably mediate oncogenic transformations. For example, overexpression of the ribonucleotide reductase (RnR) enzyme which catalyzes the formation of deoxyribonucleotides from ribonucleotides necessary for cell division, is implicated in many forms of cancer and the genes for the components of the enzyme are often mutated, leading to hyperactivity of the enzyme. But there are instances indicating that cytoplasmic material rather than the karyoplast would be responsible for cellular transformation that might be better explained as a consequence of certain epigenetic modulation than purely genetic changes. .RnR active site inhibitors have been developed accordingly to biophysically deactivate the enzyme when necessary, with positive results A comprehensive analysis of tumors based on their genomic studies must reveal the alterations in signaling pathways indicating patterns of vulnerabilities and the means to identify prospective targets for the development of personalized treatments and new combination therapies. In this regard, the Cancer Cell Map Initiative (CCMI), launched in 2015 by researchers at the University of California, San Francisco and the University of California, San Diego, allowed researchers to determine how hundreds of genetic mutations involved in a few types of cancer affect the activity of certain crucial proteins which ultimately lead to the manifestation of cancer. As there is a large amount of sequence data from many different cancer types, efforts are being made to extract mechanistic insights from the available information, requiring an integrated computational and experimental strategy that will help place these alterations in the higher order contexts of signaling mechanisms in cancer cells. This is the defined goal of the CCMI and has the potential to create a resource that can be used for cancer genome interpretation, enabling the identification of key complexes and pathways to better understand the biology underlying different cancer types and conditions for precise treatment of the disease.
DOI: 10.6084/m9.figshare.22654951.v3
title: source code, data, surface plot

description: Static analysis tools (SATs) are widely applied to detect defects in software projects. However, SATs are overshadowed by a large number of unactionable warnings, which severely reduces the usability of SATs. To address this problem, the existing approaches commonly use machine learning (ML) techniques for actionable warning identification (AWI). For these ML-based AWI approaches, the warning feature determination is one of the most critical parts to effectively identify actionable warnings. To eliminate redundant and irrelevant warning features, ML-based AWI approaches usually incorporate feature selection to determine the feature subset by calculating the importance or correlation of features with warning labels. Nevertheless, warning labels are not always available directly in practice. Thus, it is vital and challenging to select warning features for ML-based AWI approaches when warning labels are absent. To address the above problem, we propose an UNsupervised fEAture SElection approach called UNEASE for ML-based AWI. (1) UNEASE first performs the feature clustering to gather warning features into clusters, where the number of clusters is automatically determined and features in the same cluster are considered redundant. (2) Subsequently, UNEASE performs the feature ranking to sort warning features in each cluster with three newly proposed ranking strategies and selects the top-ranked warning feature from each cluster. Based on the selected features, we train a ML classifier to identify actionable warnings. We conduct experiments on nine large-scale and real-world warning datasets. Compare UNEASE with seven typical feature selection techniques, the experimental results show that while taking a low cost to perform the feature selection and maintaining a low redundancy rate in the selected warning features, UNEASE still obtains the top-ranked AUC.
DOI: 10.17632/wm83krbf32
title: HoloSelecta Dataset

description: This dataset contains 295 labelled images for computer vision based detection and identification of packaged products in a vending machine. In addition, the dataset contains data from a user study with 61 participants on the impact of mixed reality headset mediated interventions on food choices. The results indicate that the display of Nutri-Score during the product selection process can alter decisions towards healthier choices. References: * Fuchs, K., Grundmann, T., Fleisch, E., Towards Identification of Packaged Products via Computer Vision, in The 9th International Conference on the Internet of Things (IoT 2019), Bilbao, Spain. * Fuchs, K., Grundmann, T., Haldimann, M., Fleisch, E., Impact of Mixed Reality Food Labels on Product Selection: Insights from a User Study using Headset-mediated Food Labels at a Vending Machine, in 5th International Workshop on Multimedia Assisted Dietary Management In conjunction with the 27th ACM International Conference on Multimedia (ACMMM2019).
DOI: 10.6084/m9.figshare.6299477.v1
title: Brown Planthopper

description: This is the raw data contains sticky pad images.
DOI: 10.17632/838bhncx76
title: INTRODUCCIÓN A LOS CIRCUITOS ELÉCTRICOS: Dispositivos Pasivos

description: Se presentan algunos apuntes sobre el curso de Dispositivos Pasivos impartidos en la Universidad del Cauca (Colombia) para la carrera de Ingeniería Física
DOI: 10.17632/fm996rrfyz
title: Long-term discharges, water levels, salinity concentrations, and precipitation in the Mekong River basin

description: Hydropower dams have been increasingly and planned in the Mekong River basin, and questions about the impacts of the largest hdyropower dams in the Lancang cascade remain largely unknown. To quantify the impacts of existing hydropower dams in the Mekong River basin on flow regimes on the lower Mekong River and associated impacts on salinity intrusion in the Vietnamese Mekong Delta, we collected and analyzed long-term observed discharges, water levels, salinity concentrations, and precipitation along the entire lower Mekong River, from Chiang Saen, Thailand to the Vietnamese Mekong Delta. Then, we applied various hydrological indicator and trend test methods to interpret the time series data. Discharges and water levels are available over 36 years (1980-2015) at Chiang Saen (Thailand), Kratie (Cambodia), Tan Chau, Chau Doc, and My Thuan (Vietnam), and salinity concentrations are available during the period 1990-2016 at Tra Vinh and Cau Quan in the Vietnamese Mekong Delta. These data were provided by the Vietnamese National Hydro-meteorological Data Center and Mekong River Commission. Annual precipitation at seven rain gauges in the Mekong River basin (Lincang, Simao, Lancang, Jinhong, Chiang Saen, Pakse, and Nong Khai) were collected over the period 1954-2015 for the analysis.
DOI: 10.17632/8hxtgyyxrw
title: Railway Track Surface Faults Dataset

description: This dataset is related to railway track faults which includes different types of railway track surface faults. The data was acquired as a video through two EKEN-H9R cameras mounted on both sides of the railway inspection vehicle. The cameras were capable of recording videos at 120 FPS and with a FOV (field of view) of approximately 14 inches. Unnecessary parts of the collected videos were removed in the second step. Then, the necessary frames were extracted from the video. After extracting required frames out of videos manual labeling of the images was done. The established datasets includes classes: Grooves, Joints, Cracks, Flakings, Shellings, Spallings, and Squats.
DOI: 10.17632/b4kcw9r32n
title: Dataset for Hierarchical Object Detection of Nordic Fish Species

description: The dataset contains data used in the thesis "Hierarchical Fish Species Detection in Real-Time Video Using YOLO". It consists of the weights of the models that was used for the different experiments, some framework configurations, and the object detection dataset. The detector runs on the Darknet framework. The object detection dataset is a collection of 1879 images of underwater fish taken from a stationary camera in Lindesnes, Norway. Each image has a corresponding annotation file that defines a bounding box and class for each fish. The images are annotated with hierarchical classification and biological taxonomy in mind. The hierarchy is defined in fish_taxonomy.xml. This means that if the species cannot be discerned, a higher class in the hierarchy will be used. There is 7721 annotated fish in the dataset.
DOI: 10.17632/52vc6v4czj
title: QazUNTv2: Dataset of high school math problems on english and russian languages

description: This dataset is intended for the subsequent verification of the correctness of LLM (GPT-3.5 Turbo) generated responses to mathematics problems similar to those found in exams for graduate schools. The dataset includes problems and their types in both Russian and English, along with five options, manually solved answers, and detailed solutions in both languages. The primary goal is to analyze and compare LLM (GPT-3.5 Turbo)-generated answers with provided correct solutions. 
The data has been collected and structured across the following sections of mathematics: Algebra, Probability and Logic. We ensured a comprehensive evaluation of GPT's capabilities in understanding and solving these problems. The dataset is divided into the following sections with the corresponding number of problems: 
1. Algebra: 436 problems; 
2. Logic: 312 problems; 
3. Probability: 163 problems.
This dataset will facilitate a detailed assessment of GPT's performance in mathematical problem-solving across various domains.
For the future analysis, we also calculated quantity of tokens that may help to generate responses from ChatGPT-3.5 Turbo: 
The English math problems comprise 37563 tokens. 
The Russian math problems comprise 66406 tokens. 
The average number of tokens per English task is approximately 39.96 and for the problems in Russian this number is approximately 70.64.
DOI: 10.17632/prwxp69snf
title: Data and Code for “Kuwait Stock Exchange: A Re-examination of Seasonal Anomalies”

description: This repository contains the complete replication package for the study titled “Kuwait Stock Exchange: A Re-examination of Seasonal Anomalies”, which investigates the evolution of seasonal return patterns in the Kuwaiti stock market from 2012 to 2023. All data and R scripts necessary to replicate the empirical results reported in the manuscript are included. The dataset spans multiple market segments (Kuwait 15, Premier Market, Main Market) and is constructed using official daily data from Boursa Kuwait. Code files are clearly organized and labeled to match the main tables and figures presented in the paper. Please refer to the included Replication Guide for a detailed description of each file and its purpose.