cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/95fb84nzcd
title: Nairobi Securities Exchange Prices 2008-2012 for 6 selected stocks

description: Stock market prediction remains active research in a quest to inform investors on how to trade (buy/sell) at the most opportune time. The prevalent methods used by stock market players in trying to predict the likely future trade prices are either technical, fundamental or time series analysis. This research wanted to try out machine learning methods, in contrast to the existing prevalent methods. Artificial neural networks (ANNs) tend to be the preferred machine learning method for this type of application. However, ANNs require some historical data to learn from, in order to do predictions. The research used an ANN model to test the hypothesis that the next day price (prediction) can be determined from the stock prices of the immediate last five days. The final ANN model used for the tests was a feedforward multi-layer perceptron (MLP) with error backpropagation, using sigmoid activation function, with network configuration 5:21:21:1. The data period used was a 5-year dataset (2008 to 2012), with 80% of the data (4-year data) used for training and the balance 20% used for testing (last 1-year data). The original raw data for Nairobi Securities Exchange (NSE) was scrapped from a publicly available and accessible website of a stock market analysis company in Kenya (Synergy, 2020). This daily prices data was first exported to a spreadsheet, then cleaned off headers and other redundant information, leaving only the data with stock name, date of trade and the related data such as volumes, low prices, high prices and adjusted prices. The data was further sorted by the stock names and then the trading dates. The data dimension was finally reduced to only what was needed for the research, which was the stock name, the date of trade and the adjusted price (average trade price). This final dataset was in CSV format, as hereby presented. The research tested three NSE stocks with the mean absolute percentage error (MAPE) ranging between 0.77% to 1.91%, over the 3-month testing period, while the root mean squared error (RMSE) ranged between 1.83 and 3.07. This raw data can be used to train and test any machine learning model that requires training and testing data. The data can also be used to validate and reproduce the results already presented in this research. There could be slight variance between what is obtained when reproducing the results, due to the differences in the final exact weights that the trained ANN model eventually achieves. However, these differences should not be significant. List of data files on this dataset: stock01_NSE_01jan2008_to_31dec2012_Kakuzi.csv stock02_NSE_01jan2008_to_31dec2012_StandardBank.csv stock03_NSE_01jan2008_to_31dec2012_KenyaAirways.csv stock04_NSE_01jan2008_to_31dec2012_BamburiCement.csv stock05_NSE_01jan2008_to_31dec2012_Kengen.csv stock06_NSE_01jan2008_to_31dec2012_BAT.csv References: Synergy Systems Ltd. (2020). MyStocks. Retrieved March 9, 2020, from http://live.mystocks.co.ke/
DOI: 10.17632/9h2y3z8x5r
title: WoW - Wearable Respiration Monitoring Dataset

description: This dataset was acquired by the Institute of Systems and Robotics, University of Coimbra, as a part of the CMU-Portugal WoW project, Wireless biOmonitoring stickers and smart bed architecture: toWards Untethered Patients (https://inovglintt.com/financiamento/wow/). The main objective of the project is to develop wearable devices for remote and continuous patient monitoring. As a part of this project, we focused on respiration data, to evaluate methods for estimation of human respiration rate through simple and low-cost wearable patches. We are as well interested to understand how body motion, and position (sitting/standing/moving) affects the accuracy of the estimation. Hence, we have recorded data from different sensor inputs. This includes printed, thin-film, and stretchable skin-mounted strain gauges installed on different body locations, bioimpedance measurements via skin-interfacing electrodes, and a chest/belly-mounted accelerometer. This dataset contains respiration data from 4 subjects. In all measurement sessions, we also acquired ground truth data via a nose-mounted thermistor. The dataset can be used along with sensor fusion and machine learning techniques, in order to develop algorithms that can precisely estimate the respiration rate, during different body positions and activities.
DOI: 10.17632/pg2t8jmvhk
title: Experimental data of quality parameters in bottled – drink samples of Tiruchirappalli City, South India

description: The present data contribute the analyzed parametric quality of 61 bottled-drink samples collected in the local shops of Tiruchirappalli City located in Tamil Nadu, South India. The quality parameters such as pH, electrical conductivity (EC), total dissolved solids (TDS), salinity, calcium hardness (CH), magnesium hardness (MH), total hardness (TH), total alkalinity (TA), chloride and fluoride were analyzed as per the standard procedure recommended by APHA (2005).
DOI: 10.6084/m9.figshare.25894927.v1
title: Celloc_data

description: The preprocessed data for Celloc.
DOI: 10.6084/m9.figshare.27643182.v8
title: Multivariate Time Series Anomaly Detection Using Directed Hypergraph Neural Networks

description: Multivariate time series anomaly detection is a challenging problem because there can be a number of complex relationships between variables in multivariate time series. Although graph neural networks have been shown to be effective in capturing variable-variable relationships (i.e., relationships between two variables), they are hard to capture variable-group relationships (i.e., relationships between variables and groups of variables). To overcome this limitation, we propose a novel method called DHG-AD for multivariate time series anomaly detection. DHG-AD employs directed hypergraphs to model variable-group relationships within multivariate time series. For each time window, DHG-AD constructs two different directed hypergraphs to represent relationships between variables and groups of positively and negatively correlated variables, enabling the model to capture both types of relationships effectively. The directed hypergraph neural networks learn node representations from these hypergraphs, allowing comprehensive multivariate interaction modeling for anomaly detection. We show through experiments using various evaluation metrics that our proposed method achieves the best scores among the compared methods on two real-world datasets.
DOI: 10.6084/m9.figshare.28874375.v1
title: Quantum Simulation of Singularity Stabilization via Stronger Anti-Time Modulation

description: This OpenQASM 2.0 simulation models the stabilization of a quantum singularity through enhanced anti-time modulation effects. The circuit initializes a virtual-time qubit into superposition to represent fluctuating quantum conditions. A strong phase shift (π/2) is applied to an anti-time qubit, simulating an intensified anti-time stabilization mechanism. The virtual-time qubit is then entangled with an emergent real-time qubit, enabling energy transfer and coherence formation. Final Hadamard operations enhance the structure of the emergent real-time qubit. This model explores how stronger anti-time influences could stabilize virtual singularities and facilitate the emergence of classical spacetime behavior from quantum fluctuations.
DOI: 10.6084/m9.figshare.4154244.v1
title: R code from Mood and personality interact to determine cognitive biases in pigs

description: Complete R code for the analysis
DOI: 10.17632/5zjdtp5w28
title: A Quantitative Analysis of Bank Lending Relationships (Dempsey and Faria-e-Castro)

description: Replication materials for "A Quantitative Analysis of Bank Lending Relationships", by Kyle Dempsey and Miguel Faria-e-Castro, accepted at the Journal of Financial Economics.
Please refer to the readme file for a more detailed explanation of how to reproduce the results.
DOI: 10.17632/vcp7w8t2kg
title: OTT Market Segmentation and Consumer Profiling: A Cluster Approach to the Emerging OTT Consumerism

description: Abstract:
Purpose: As OTT platforms expand, stakeholders need to grasp OTT consumers' distinctively dynamic behaviors. The study addresses the following question: What key determinants affect consumer perception of OTT platforms, and how can the Indian audience be segmented? This study aims to analyze OTT customer segments, preferences, and viewing patterns.
Design: An online survey questionnaire was designed to obtain responses (343) from a convenience sample of OTT consumers in India. The research employed psychographic and demographic characteristics from OTT consumers. These characteristics were used for audience profiling.
Findings: The study reveals how value delivery, content quality, convenience, affordability, peer group influence, and personalization affect Indian consumer perception. It illustrates that the five OTT media consumer segments possess distinct perceptions and preferences. Clusters vary demographically and psychographically. 
Originality: Previous research analyzed the OTT market and consumer behaviors. This study adds to the existing literature by defining Indian customer clusters more precisely to better understand the heterogeneity of the growing OTT audience and provide focused insights that can fuel Indian business strategies. The novelty lies in knowing the emerging market’s audience and updating business strategies accordingly.
Implications: Understanding clusters by industry strategists, media academicians, and professionals helps develop targeted advertising campaigns and personalized content recommendations, enhancing user engagement. The study offers to update marketing, content curation, and client retention strategies by helping stakeholders comprehend the dynamic OTT consumer landscape and tailor products to cater to distinct consumer clusters.
Keywords: OTT platforms, consumer perception, customer segments, audience profiling, demographic and psychographic characteristics, Indian business strategies.
DOI: 10.6084/m9.figshare.11778213.v2
title: VSAD - Dataset

description: This dataset contains the data from : <b> </b> <b>Lacroix, E., Cornet, S., Deggouj, N., Edwards, M. “Visuo-Spatial Abilities Diagnosis - Test (VSAD): Evaluate the potential cognitive difficulties of children with vestibular impairment through a new tablet-based computerised test battery”. </b> <b> </b> <b>(Currently in submission)</b> Data have been generated with the VSAD-Test using the Metrisquare DiagnosIS software (www.metrisquare.net). Access to the test is free of charge but requires author approval. Contact us for a request to use the VSAD: emile.lacroix@uclouvain.be; martin.edwards@uclouvain.be<br>
DOI: 10.6084/m9.figshare.12923189.v1
title: R0195_20171016a_videos

description: Rat 0195, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.1321794.v3
title: Kazakiewicz et al., 2015

description: Supplementary files for Kazakiewicz D, Karr JR, Langner KM & Plewczynski D. Combined systems and structural modeling repositions antibiotics for Mycoplasma genitalium. (In submission).
DOI: 10.6084/m9.figshare.15027561.v1
title: Dataset and R code from "Aridity-driven shift in biodiversity–soil multifunctionality relationships"

description: Dataset and R code used to perform the main analyses described in "Aridity-driven shift in biodiversity–soil multifunctionality relationships"<br>
DOI: 10.6084/m9.figshare.19638630.v1
title: Raw counts, BCR sequences, and TCR sequences for 2021 neurosarcoid scRNA-Seq project

description: The linked paper describes single-cell RNA-Seq analysis of neurosarcoidosis that was either active or inactive compared to individuals without sarcoidosis. These are the raw counts (barcodes, genes, matrix files) for the single-cell RNA-Seq data, along with the TCR and BCR sequences derived from these individuals. The analysis details can be found in the GitHub repository referenced in the linked paper.
DOI: 10.6084/m9.figshare.22411453.v1
title: Statistics.csv

description: Statistics used in the bibliometric review
DOI: 10.6084/m9.figshare.25366645.v1
title: FloodDetectionResults

description: Flood detection results with different threshold.
DOI: 10.6084/m9.figshare.28644929.v1
title: Differential impacts of grazing on grassland plant diversity, biomass, soil C and N across an elevation gradient

description: Understanding how vegetation traits and soil characteristics respond to grazing in grasslands is fundamental to their restoration and management. Here, we investigated changes in species diversity, plant productivity, soil total nitrogen (STN) and soil organic carbon (SOC) storage following grazer exclusion at three grassland sites along an elevation gradient in the Kashmir Himalaya. Plant cover, above- and below-ground biomass (AGB and BGB, respectively), SOC and STN increased following six years of grazing exclusion, though species diversity indices declined over this period. Grazer exclusion increased the biomass of all functional groups (sedges, grasses, legumes, and forbs), with sedges, particularly Carex muricata, showing the highest increase. Grazer effects on above- and below-ground biomass, SOC and STN varied with elevation, with the most pronounced effect of grazing detected at the highest elevation site. Grazer effect on the vertical distribution of root biomass, SOC and STN were restricted to topsoil (10 cm) at low-elevation sites, but extended to deeper layers of soil at high-elevation sites.
DOI: 10.25403/upresearchdata.25187834.v1
title: Investigating the seroprevalence of <i>Toxoplasma gondii</i> and determining the knowledge and practices in an interface area in Mpumalanga, South Africa

description: <i>Toxoplasma gondii</i> (<i>T. gondii</i>) is an obligate protozoan parasite from the phylum, Apicomplexa, that causes a disease known as Toxoplasmosis, in warm-blooded animals. Although toxoplasmosis is mostly asymptomatic, in immune compromised humans and animals it can lead to a severe disease. <i>Toxoplasma gondii</i> is of global importance and affects approximately 30-50% of the population worldwide. Although it is of worldwide importance, in most African countries including South Africa (SA), information on the national prevalence of <i>T. gondii</i> is limited in people and animals and has not yet been fully investigated and documented. The data was collected using Therefore the data presents the seroprevalence of <i>T. gondi</i><i>i</i> in humans, domestic and wild animals as well as assessing the knowledge of the parasite and associated practices among the human population in an interface area in South Africa. Serum samples were collected by the National Institute for Communicable Diseases (NICD). Blood samples from chickens, goats and cats were collected from four villages in the area, namely, Athol, Gottenburg, Tlhavekisa and Utah. Initially, systematic sampling was envisaged by sampling households in every second street of these villages. However, due to the lack of availability of informal farmers (household owners), pet owners (household owners) and the targeted livestock and pets in the villages, opportunistic sampling was performed from eligible households per street. All household owners who had informal farms or were pet owners with the targeted animal species were invited to participate in the study. In participating households, a blood sample was collected from targeted animal species. Furthermore, questionnaires (n =384) were conducted in households in the four villages. The questionnaire focused on obtaining information regarding the socio-environmental and husbandry conditions per household as well as knowledge about Toxoplasma. To detect anti-<i>T. gondii</i> antibodies, the MAST® Toxoreagent™ ID rapid latex agglutination commercial kit (Mast Group Ltd., United Kingdom) was used following the manufacturer’s instructions. <br>
DOI: 10.6084/m9.figshare.28602413.v1
title: Data from /battery topic in ROS(Robot Operation System)

description: This data set contains the voltage and current values in each second of the robot in ROS (Robot operation system).
DOI: 10.6084/m9.figshare.28853300.v1
title: Supplementary Material for: Differentiating Cardiac Sarcoidosis from Arrhythmogenic Right Ventricular Cardiomyopathy: A Systematic Review

description: Objective: Cardiac sarcoidosis (CS) and arrhythmogenic right ventricular cardiomyopathy (ARVC) are distinct disorders with different pathophysiologic pathways, but they share similar clinical presentations that could lead to misdiagnosis and inappropriate therapeutic decisions. Methods: We searched PubMed and Google Scholar databases and other relevant literature to retrieve comparative studies including CS and ARVC that were published before 2024. The National Heart, Lung and Blood Institute checklist was used for quality assessment and the review was conducted according to the PRISMA guidelines. Three reviewers determined study eligibility and made quality assessments. Results: A total of seven studies were included in the review. Patients with CS were older (five of seven studies) and had more comorbidities (two of two studies). PR interval (four of five studies) and QRS duration (four of four studies) were longer in CS. Most studies reported lower left ventricular ejection fraction in CS (five of six studies), and septal involvement on cardiac MRI was more common in CS (two of three studies). 18-Fluorodeoxyglucose uptake on positron emission tomography (PET) scan was seen in up to 90% of CS patients. 62.5% to 100% of patients with CS fulfilled 1994 or 2010 International Task Force criteria for ARVC. Conclusions: Available evidence suggest that atrioventricular and intraventricular conduction defects in an older (&gt;40 years) patient with low left ventricular ejection fraction should raise suspicion for CS, especially when other supportive findings such as 18-fluorodeoxyglucose avidity on PET were present. Neither 1994 nor 2010 ARVC Task Force criteria should be used to discriminate CS from ARVC.
DOI: 10.6084/m9.figshare.12502274.v1
title: JVASP-14089 to JVASP-14839

description: JARVIS-DFT input/output files
DOI: 10.6084/m9.figshare.14226710.v2
title: Topic guide and template for focus group, interview and triangular group

description: Topic guide and template for focus group, interview and triangular group
DOI: 10.6084/m9.figshare.24999290.v1
title: Vegetation type of China; Python code for calculating ecosystem resilience and early warning signals

description: Vegetation type dataset is derived from the 1:1,000,000 Atlas of the Vegetation of China. This atlas is another summarizing achievement of the vegetation ecology workers in China over the past 40 years, following the publication of monographs such as Vegetation of China, which is a basic map of the country's natural resources and natural conditions. Prepared by more than 250 experts from 53 units, including relevant institutes of the Chinese Academy of Sciences, relevant ministries and departments of provinces and districts, and institutions of higher learning, and officially published by the Science Press for domestic and international public distribution.The Bayesian dynamic linear model proposed by Liu et al. (2019, https://doi.org/10.1038/s41558-019-0583-9) was used to calculate the time-varying measure of resilience. We have modified the parameters of the code to be more suitable for the Loess Plateau and Qinba Mountains in China. According to the results of resilience, we could obtain the early warning signals of forest.
DOI: 10.6084/m9.figshare.25539172.v1
title: Effectiveness of Multimodal Integrated Rehabilitation Using Tactile Stimulation, Airway Clearance Technique, Kinesthethic Technique, Oro-motor Stimulation (TAKO) Protocol on Oro-Motor and Respiratory Complications in Infants with Pneumonia: A Protocol for Randomized Controlled Trial completed_SPIRIT_checklist.docx

description: The TAKO protocol proposed for the randomized controlled trial (RCT) targeting infants with pneumonia seems to offer a comprehensive approach to addressing both oromotor and respiratory complications.
DOI: 10.6084/m9.figshare.4975835.v1
title: TPLakes_Temperature

description: The first comprehensive data set of 15-year (2001–2015) nighttime and daytime lake surface water temperature (LSWT) of 374 lakes (≥10 km2 each) over the Tibetan Plateau, using MODIS (Moderate Resolution Imaging Spectroradiometer) Land Surface Temperature (LST) products as well as four lake boundary shapefiles (i.e. 2002, 2005, 2009, and 2014) derived from Landsat/CBERS/GaoFen-1 satellite images.
DOI: 10.17632/gp8hvxgdpn
title: Base de datos condiciones de confort en las viviendas barrio Cavivir-Villavicencio

description: Base datos sobre las condiciones de confort para las viviendas del barrio Cavivir-Villavicencio. Es importante describir que el confort en una vivienda es fundamental para nuestra calidad de vida. Por tanto, aspectos como temperatura, iluminación, ruido, espacialidad, entre otros, es una combinación de factores físicos, emocionales y psicológicos que influyen en nuestra sensación de bienestar en un espacio determinado. Además, este Dataset no solo se observa el bienestar, sino también la productividad y creatividad del barrio Cavivir.
DOI: 10.17632/kjxb2bk3mr
title: Melting phase change heat transfer in a quasi-petal tube thermal energy storage unit - Dataset

description: The row data for plotting the graphs
DOI: 10.17632/tgxc7b9364
title: Whitefly Nymphal Feeding System: Dataset

description: Dataset for standardization of Whitefly Nymphal Feeding System technique with respect to leaf survival, nymphal mortality and water absorption. Further, this technique used to deliver dsRNA in whitefly nymphs.
DOI: 10.25417/uic.25653189.v1
title: Dataset for "Knowing What We Don't Know: A Survey of School Nurse Information Needs"

description: This is the dataset for the manuscript, "Knowing what we don't know: A survey of school nurse information needs."
<br>
Nickum, Annie “Nicky, Rosie Hanneke, and Robin Shannon. "Knowing What We Don’t Know: A Survey of School Nurse Information Needs." <em>The Journal of School Nursing</em> (2023): 10598405231193361.
DOI: 10.6084/m9.figshare.19229229.v2
title: Mitochondrial oxidation of TCA cycle intermediates, fatty acids, amino acids and other substrates in lymphoblasts from ALS patients with mutant SOD1 (mutSOD1) or unknown mutation (undSOD1) and respective controls.

description: Cells were plated at density 160,000 cells/well, and the rate of oxidation of a panel of TCA cycle intermediates, fatty acids, amino acids and other substrates was assessed using Biolog Mitoplate S1 assay. Data were obtained for all cohorts (pool), C1-Female 46 years old, C2- Male 46 years old and C3-Male 26/27 years old. Substrates include pyruvic acid, pyruvic acid + malic acid, citric acid, cis-aconitic acid, isocitric acid, α-ketoglutaric acid, succinic acid, fumaric acid, L-malic acid, L-glutamic acid, L-glutamine and alanine-glutamine, octanoyl L-carnitine (+L-malic acid), palmitoyl L-carnitine (+L-malic acid), D-glucose, D-glucose-1-PO4, D-glucose-6-PO4, D-gluconate-6-PO4, L-lactic acid, D-L-α-glycerol-PO4, glycogen, D-L-β-hydroxybutyric acid, α-ketobutyric acid, γ-aminobutyric acid (+L-Malic acid), tryptamine, serine, L-ornithine, and L-leucine (+L-malic acid).
DOI: 10.6084/m9.figshare.25859311.v1
title: <b>Microbial communities follow organic matter formation in paddy soils: the molecular perspective</b>

description: <b>Microbial communities follow organic matter formation in paddy soils: the molecular perspective</b>
DOI: 10.6084/m9.figshare.7712468.v1
title: Supplementary Material for: A Rare Case of Localized Argyria on the Face

description: Due to its antibacterial actions, silver sulfadiazine is widely used as a topical agent in the treatment of wounds, including burns. Widespread or prolonged topical application of silver sulfadiazine dressings can lead to argyria including systemic symptoms due to the resorption of silver. Here, we report a patient experiencing localized argyria due to sunlight exposure after topical use of silver sulfadiazine cream on his face.