cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/xnbc337tmw
title: LINF_180012500

description: Dynein light chain; Leishmania infantum (strain JPCM5)
DOI: 10.6084/m9.figshare.13262615.v1
title: Experimental Data for Near Critical Turbulent Heat Transfer of Supercritical Carbon Dioxide in Rectangular Microchannels subject to Uniform Single Wall Heating

description: The attached data were obtained at Oregon State University in the Thermal Energy Systems and Transport (TEST) Laboratory. The experiments were conducted using the supercritical facility with 99.5% (food grade) carbon dioxide (CO2). Experiments were conducted in a horizontally oriented test section with a channel hydraulic diameter of 923 micron and an aspect ratio of 3.33. Experimental variables included the mass flux (430 &lt; G &lt; 800kg m<sup>-2</sup> s<sup>-1</sup>, heat flux (5.7&lt; q" &lt;14.12 W cm<sup>-2</sup>, inlet temperatures (31&lt; T<sub>inlet </sub>&lt;32.9<sup>o</sup>C), and a reduced pressure (P<sub>R</sub>) of 1.04. The test section was fabricated using Inconel-718, Torlon 4203, and stainless steel. Infrared thermography was used to obtain local heat transfer data. Heating was applied and limited to the bottom wall of the flow channels.The data reported in the attached sheets contains the experimentally measured:<br> 1. Surface temperatures of the heated metal (T_surf) 2. Heat transfer coefficients (HTC) 3. Experimentally measured inlet, exit, and channel absolute pressure. (T_inlet, T_exit, Abs_P) 4. Bulk fluid temperature along the flow channel. (T_bulk) 5. Applied heat flux (q) 6. Channel mass flux (G)<br> Please note that the surface temperatures (T_surf), bulk fluid temperatures (T_bulk), and the heat transfer coefficients (HTC) correspond to the region of the test section represented by the ''Interrogation Window'' in the figure contained in the attached sheet. <br> This means that the heat duty of the inlet header region needs to be added to the experimentally measured inlet temperature to obtain the bulk fluid temperature at the inlet of the flow channel. In a similar fashion, the heat duty of the exit header region needs to be added to the bulk fluid temperature at the end to interrogation window to obtain the experimentally measured bulk fluid temperature. <br> The heat transfer coefficients and the surface temperature measurements reported here are an average of seven data points (pixels) across the width of the interrogation window. <br><br>
DOI: 10.6084/m9.figshare.19985453.v1
title: Example Student Data.xlsx

description: In the attached Excel file, "Example Student Data", there are 6 sheets. There are three sheets with sample datasets, one for each of the three different exercise protocols described. Additionally, there are three sheets with sample graphs created using one of the three datasets. · Sheets 1 and 2: This is an example of a dataset and graph created from an exercise protocol designed to stress the creatine phosphate system. Here, the subject was a track and field athlete who threw the shot put for the DeSales University track team. The NIRS monitor was placed on the right triceps muscle, and the student threw the shot put six times with a minute rest in between throws. Data was collected telemetrically by the NIRS device and then downloaded after the student had completed the protocol. · Sheets 3 and 4: This is an example of a dataset and graph created from an exercise protocol designed to stress the glycolytic energy system. In this example, the subject performed continuous squat jumps for 30 seconds, followed by a 90 second rest period, for a total of three exercise bouts. The NIRS monitor was place on the left gastrocnemius muscle. Here again, data was collected telemetrically by the NIRS device and then downloaded after he had completed the protocol. · Sheets 5 and 6: In this example, the dataset and graph are from an exercise protocol designed to stress the oxidative system. Here, the student held a light-intensity, isometric biceps contraction (pushing against a table). The NIRS monitor was attached to the left biceps muscle belly. Here, data was collected by a student observing the SmO2 values displayed on a secondary device; specifically, a smartphone with the IPSensorMan APP displaying data. The recorder student observed and recorded the data on an Excel Spreadsheet, and marked the times that exercise began and ended on the Spreadsheet.
DOI: 10.6084/m9.figshare.25075727.v1
title: Supplementary materials: "Mapping publications by Sustainable Development Goal at the faculty level to highlight inter-faculty collaborations"

description: Achieving the United Nations’ Sustainable Development Goals requires partnerships across nations, sectors, and stakeholders. In academia, interdisciplinary research can help to address complex challenges related to the Goals. This paper offers a structured approach to identifying current and potential research collaborations across faculties at a Canadian university.Publications from the Dimensions database that had been assigned to an SDG category were matched against publications indexed by the university’s Research Information Management System. The resulting matches were then sorted and tabulated by ANZSRC research category and by the faculty affiliation of the authors. Potential interdisciplinary research collaborations are then identified by matching authors from different faculties who both have publications within the same research category. Leveraging this methodology and an institution’s RIMS system provides university leaders with insight to track progress and plan research activities across the institution. A simple methodology is presented that combines the power of data processing with the user's contextual insights to uncover novel pairings of faculty members whose research is aligned. Institutions can apply this methodology to track SDG-related publications, to analyze current interdisciplinary publications, and to identify potential interdisciplinary collaborations.<br>
DOI: 10.6084/m9.figshare.29107727.v1
title: OrthoKnow-SP

description: This dataset supports the public release of <b>OrthoKnow-SP</b>, a large-scale megastudy on Spanish orthographic knowledge. Over 27,000 native speakers of Spanish completed an 80-trial forced-choice task in which they selected the correctly spelled word from a pair containing one real word and one pseudohomophone. The study captured over 2.17 million data points, alongside rich metadata on participant demographics and response dynamics.To facilitate reuse and reproducibility, the following three files have been included in the repository:<br><b>ORTHOKNOW-SP PARTICIPANT DATA.csv: </b>This file contains participant-level information, including a unique identifier, age, gender, highest education level, the date and time of task completion, and the type of device used. It enables researchers to analyze performance by sociodemographic and technological variables.<b>ORTHOKNOW-SP RESPONSE DATA.csv: </b>This file includes trial-level response data for each participant. For each of the 80 trials, it reports the correct word, the incorrect pseudohomophone, the position of the trial, the participant’s reaction time in milliseconds, and whether the response was accurate. It is the main file for behavioral analyses.<b>OrthoKnow-SP.R: </b>This R script contains all data processing routines used to generate the final dataset. It performs key steps such as data import, participant filtering, reaction time trimming, and computation of composite difficulty scores. The script ensures transparency and full reproducibility of the analyses reported in the manuscript.All files are encoded in UTF-8 and can be directly opened in standard environments such as R, Python, or spreadsheet software.
DOI: 10.6084/m9.figshare.5125096.v1
title: LGK and TEM-1.1 Enzyme Solubility Datasets

description: Solubility datasets for LGK and TEM-1 from:<br>Klesmith, J. R., Bacik, J.-P., Wrenbeck, E. E., Michalczyk, R., and Whitehead, T. A. (2017) Trade-offs between enzyme fitness and solubility illuminated by deep mutational scanning, Proceedings of the National Academy of Sciences 114, 2265-2270.
DOI: 10.17632/h43s4d4zfn
title: GNSS Dataset (with Interference and Spoofing) Part II

description: GNSS Dataset (with Interference and Spoofing) consists of three parts: 
Part I (Raw data of 2023 12 to 20, Sept, 2023, clean data), 
Part II (Raw data of 2023 21 to 30, Sept, 2023, clean data) and 
Part III (Processed data 12 to 30, Sept, 2023; data collected with spoofing and jamming on 21 Dec, 2023; Scripts and Material) .

The data were recorded by a GNSS receiver installed on the 5th floor of the Science Hall of Yunnan University. HackRF One emits spoofing signals and the commercial jammer emits suppression jamming to attack the receiver on 21 Dec, 2023. The provided datasets are interesting for the GNSS monitoring, GNSS security, anti-jamming and anti-spoofing mechanisms based scientific communities.

These data provide the most comprehensive information available on the spatial and temporal patterns of GNSS satellites, observation and receiver parameters, referring to five constellations (GPS, Campass, Galileo, GLONASS and QZSS) and eight signal bands (L1C/A, L2C, E1, E5b, B1, B2, L1, L2). The dataset provides observations of the receiver three scenarios: normal state, affected by commercial jammers, and spoofed by SDR HackRF One. These observations include more details such as carrier-to-noise density ratio (C/N0), signal spectrum, Doppler shift, pseudorange, carrier phase, satellite health indicator, real-time position data and dilution of precision (DOP), etc. These data can be used to analyze navigation satellite operation rules, satellite covering time above the receiver, satellite overhead time prediction and GNSS monitoring system construction, provides a large amount of fine-grained data that can be used as an example to study safeguards at civil aviation airports, monitoring for harmful radio interference.
DOI: 10.17632/kffy2227cz
title: Análise Qualitativa dos Trabalhos (IA + ACV)

description: PT: Tabela referente a análise qualitativa dos trabalhos que utilizam a integração entre Inteligência artificial (IA) e Avaliação do Ciclo de Vida (ACV) com caráter preditivo.
Criada no trabalho: ANÁLISE CRÍTICA DA PRODUÇÃO CIENTÍFICA SOBRE A INTELIGÊNCIA ARTIFICIAL E A AVALIAÇÃO DO CICLO DE VIDA DE PRODUTOS - SIMPEP 2023.

EN: Table referring to the qualitative analysis of studies that employ the integration between Artificial Intelligence (AI) and Life Cycle Assessment (LCA) with a predictive nature.
Created in the study: CRITICAL ANALYSIS OF SCIENTIFIC PRODUCTION ON ARTIFICIAL INTELLIGENCE AND LIFE CYCLE ASSESSMENT OF PRODUCTS - SIMPEP 2023.
DOI: 10.17632/mwfw6brj5n
title: Data for: Which States Most Effectively Discipline Attorneys? New Measures of State Corruption Within the United States

description: The American Bar Association’s annual Survey on Lawyer Discipline (SOLD) reports complaints and charges regarding lawyer misconduct, the caseload per disciplinary attorney, and each state’s budget for attorney discipline. From these reports, we develop five measures of attorney discipline: 1. COMPLAINTS – the percent of attorneys in the state who receive complaints from the public. 2. CHARGED – the percent of attorneys that are charged with some form of misconduct during the year; 3. CHARGED/ COMPLAINTS – the percent of the attorneys receiving COMPLAINTS that are eventually CHARGED with malpractice; 4. BUDGET (in dollars) – the state’s annual budget for implementing attorney discipline relative to the number of attorneys; and 5. CASELOAD – the number of AD cases per state disciplinary attorney per year. In our study "Attorney Discipline, the Quality of Legal Systems and Economic Growth within the United States" we use these measures to examine the quality of legal systems within the United States and the relation between this quality and state economic growth. The panel data set, included here, contains the values of the 5 attorney discipline measures for each state from 2000-2017. We use these data in our study.
DOI: 10.17632/r5ftnf4j9f
title: Protein and Ligand Dataset for Drug Repositioning in Childhood Acute Lymphoblastic Leukemia (ALL)

description: This dataset includes two main components (proteins and ligands), which can be used in computational research focused on drug repositioning in Childhood Acute Lymphoblastic Leukemia (ALL):

1- Protein Sequences (proteins.txt): This dataset file contains amino acid sequences of selected proteins used in a study aiming to identify novel therapeutic candidates by drug repositioning for Childhood Acute Lymphoblastic Leukemia (ALL). The sequences were extracted from the UniProt database and are proteins which are known or predicted to be associated with ALL pathogenesis, treatment procedures, or immunological relevance. The file is structured in a JSON-like format with UniProt IDs as keys and amino acid sequences as values. Each entry corresponds to one protein. 
Additional Metadata:
- Data Type: Amino acid sequence data (FASTA-like JSON format)
- Unique Proteins: 8479
- Average Sequence Length: 529.81
- Maximum Sequence Length: 14507

2. Ligand Data (ligands.txt): A collection of drug-like small molecules represented in SMILES or similar formats. The ligands in this file were selected by considering their therapeutic potential and relevance to ALL-related targets. The data was sourced from databases such as ChEMBL and DrugBank. Also, some data related to FDA approved drugs were added manually. 
Additional Metadata:
- Data Type: SMILES strings in JSON-like format (key-value pairs).
- Number of ligands: ~220.000

The combined dataset supports research in bioinformatics, drug discovery, and leukemia-specific therapeutic targeting.

The dataset is designed to aid computational biology, bioinformatics and artificial intelligence research, especially for researchers in the field of leukemia biology, drug-target interaction modeling, and systems pharmacology.
DOI: 10.6084/m9.figshare.25593804.v2
title: Single-cell genomics on supraspinal projection neurons

description: single-cell sequencing approaches to assess the response of adult supraspinal projection neurons to spinal injury.
DOI: 10.17608/k6.auckland.4248656.v3
title: figures6and7EJP.ipynb

description: jupyter notebook to create the figures of our EJP article on earthquake location with school seismograms.
DOI: 10.17632/mbt6845jjb
title: Complementary material: Code and data from an ADALINE network trained with the RTRL and LMS algorithms for an MPPT controller in a photovoltaic system

description: In this dataset you will find the training algorithms (LMS and RTRL) developed for an ADALINE neural network, used as an MPPT control mechanism in a photovoltaic system completely isolated from the electrical network. Additionally, the results obtained in computational tests (simulation data) and experimental tests carried out in the field are available.
DOI: 10.17632/v7frv3k2d3
title: Various geotechnical surveys in several arrays of Taipei Basin

description: The datasets include the results of standard penetration tests (SPT), seismic piezocone penetration tests (SCPT), and a series of in-situ shear wave velocity (Vs) measurements conducted at 13 selected Holocene alluvium sites in the Taipei Basin. The geographical coordinates of each site are enumerated in one spreadsheet, and marked on the map as well.
DOI: 10.17632/274xbhc5rx
title: Tumour Infiltrating Lymphocytes in Follicular Lymphoma - additional data

description: The composition of the tumour microenvironment in follicular lymphoma (FL) is a relevant factor in determining disease progression and treatment response. This dataset is a collection of 349 FL diagnostic tissue micro-array (TMA) cores from 130 patients, stained using multi-plex immunofluorescence for: • CD4+ cells • Cytotoxic T cells (CD8+) • T regulatory cells (Tregs [CD4+FOXP3+]) • Macrophages (CD68+) • PD1+ lymphocytes • B cells/follicular dendritic cells (CD21+) • DAPI (4′,6-diamidino-2-phenylindole) nuclear counterstain Changes from previous version 2 ---------- - Raw .im3 image files provided - Spectral library images provided - Labels of nuclear annotations in 16bit format Cohort -------- FL patients according to the WHO 2008 classification were identified from the archives of The Christie NHS Foundation Trust, Manchester, UK. The study was conducted with approval by the North-West Multi-centre Ethics Committee (03/08/016) and according to the Declaration of Helsinki. Examination of the records of 350 FL patients in a random order identified 262 patients meeting the inclusion criteria: adult patients with previously untreated FL; diagnosed from incisional or excisional biopsy; and treated at first presentation with radiotherapy, watchful waiting or a combination of chemotherapy and rituximab immunotherapy. Pre-treatment biopsies were requested for 262 patients, of which 130 had sufficient tissue for analysis. A histological diagnosis of FL was confirmed by an expert haemato-pathologist (R.B). Note: Three patients (FL_59, FL_106 and FL_129) have grade 3b, which is considered equivalent to Diffuse Large B-cell lymphoma. Image format and software compatibility --------------------------------------------- Each image represents a single TMA core as a .im3 raw multispectral image format, containing the following spectra: • DAPI (nuclear) • 650 fluorophore signal for CD68 marker (membrane) • 570 fluorophore signal for CD21 marker (membrane) • 540 fluorophore signal for CD8 marker (membrane) • 690 fluorophore signal for PD1 marker (membrane) • 620 fluorophore signal for CD4 marker (membrane) • 520 fluorophore signal for FOXP3 (nuclear) • Auto-fluorescence The commercial software inForm 2.4 (Akoya Biosciences) is compatible with this format. The images can be unmixed with inForm software by using the spectral library provided. Annotations ------------- Annotations are provided for nuclear segmentation. In a set of 41 small patches the outlines have been drawn manually for 69780 nuclei. A patch from the DAPI channel and corresponding label are given as .tif images. Data structure ---------------- The data is split across multiple different datasets, all referenced below. They include: • FL_0-129 zip files: Raw images for 130 patients, each zip file a single patient. • nuclear_segmentation_annotations.zip: The nuclear segmentation annotations. • spectral library.zip: The raw images used to build the spectral library with inForm software.
DOI: 10.17632/mdty358x8m
title: Good and Bad Eggs Identification Image Dataset

description: The Good and Bad Eggs Identification Image Dataset provides high-resolution images and detailed measurements to facilitate the classification of eggs based on quality. This dataset captures key attributes such as shell texture, color, shape, and visible defects, making it a valuable resource for food quality assessment, and deep learning applications in automated egg sorting.
Dataset Overview
• Total Images: 1,000 original images captured in real-world conditions
• Augmented Images: 6,000 (generated using data augmentation techniques)
Augmentation Pipeline
To enhance dataset diversity and improve model generalization, the following augmentation techniques were applied:
1. Horizontal flipping (50% probability)
2. Vertical flipping (30% probability)
3. Random brightness and contrast adjustments
4. Rotation within a range of -30° to +30°
5. Shear transformation along both X and Y axes
6. Addition of random noise
This dataset serves as a robust foundation for developing AI-driven quality inspection systems, enabling automated identification of defective eggs and improving food safety standards.
DOI: 10.6084/m9.figshare.11881146.v1
title: Supplementary Material for: Increased Lipid Accumulation under Hypoxia in SZ95 Human Sebocytes

description: <b><i>Background:</i></b> Excessive sebum is produced by specialized cells called sebocytes and is considered a cause or consequence of acne, sebaceous cysts, hyperplasia, and sebaceous adenoma. <b><i>Objective:</i></b> To report changes in lipid accumulation in human sebocytes under hypoxia, which occurs under conditions of seborrhea. <b><i>Methods:</i></b> Sebocytes from the immortalized human gland cell line SZ95 were cultured under conditions of hypoxia for 48 h; lipid formation was confirmed by Nile red and Oil Red O staining. To investigate whether HIF-1α plays a role in lipid accumulation, SZ95 cells transfected or treated with dimethyloxalylglycine (DMOG) were assessed by Nile red. For protein expression of the sterol regulatory element-binding protein-1 (SREBP-1) and perilipin 2 (PLIN2), Western blot analysis was performed. Differentially expressed genes (DEGs) in SZ95 sebocytes under hypoxia were revealed by RNA-Seq analyses, and the statistical significance of the correlation between hypoxic and acne/non-acne skin was evaluated using gene set enrichment analysis. <b><i>Results:</i></b> Hypoxia induces lipid accumulation in SZ95 sebocytes. In addition, the levels of SREBP-1 and PLIN2 were regulated by HIF-1α in SZ95 sebocytes under hypoxia. RNA-Seq analyses of DEGs in SZ95 sebocytes under hypoxia revealed 256 DEGs, including several lipid droplet-associated genes. DEGs between acne and non-acne skin are significantly enriched in hypoxia gene sets. We also detected 93 differentially expressed inflammatory mediators. <b><i>Conclusions:</i></b> To the best of our knowledge, this study is the first to show that a hypoxic microenvironment can increase lipogenesis and provides a link between seborrhea and inflammation.
DOI: 10.6084/m9.figshare.14259992.v1
title: Supplementary Material for: Variants in <b><i>ACE2</i></b> and <b><i>TMPRSS2</i></b> Genes Are Not Major Determinants of COVID-19 Severity in UK Biobank Subjects

description: It is plausible that variants in the <i>ACE2</i> and <i>TMPRSS2</i> genes might contribute to variation in COVID-19 severity and that these could explain why some people become very unwell whereas most do not. Exome sequence data was obtained for 49,953 UK Biobank subjects, of whom 82 had tested positive for SARS-CoV-2 and could be presumed to have severe disease. A weighted burden analysis was carried out using SCOREASSOC to determine whether there were differences between these cases and the other sequenced subjects in the overall burden of rare, damaging variants in <i>ACE2</i> or <i>TMPRSS2</i>. There were no statistically significant differences in weighted burden scores between cases and controls for either gene. There were no individual DNA sequence variants with a markedly different frequency between cases and controls. Whether there are small effects on severity, or whether there might be rare variants with major effect sizes, would require studies in much larger samples. Genetic variants affecting the structure and function of the ACE2 and TMPRSS2 proteins are not the main explanation for why some people develop severe symptoms in response to infection with SARS-CoV-2. This research was conducted using the UK Biobank Resource.
DOI: 10.6084/m9.figshare.19652700.v6
title: Questionnaire to employees in the automotive industry

description: Through questionnaire to employees in the automotive industry The measuring instrument includes 23 items and is structured in five sections. The first one, consisting of four items, deals with items on the employee’s general information. The second section includes a) freedom of association or right to bargain, b) access to social or job security, and c) development of intra- and inter-industry trade. Section 3 covers: a) employees’ personality and attitude, b) skilled manpower, c) unskilled manpower, and d) innovation in productive processes/technology introduction. Section 4 considers a) export support programs, b) subsidies and financial support, c) political and trade reforms (FDI law), and d) economic model (privatizations, industry deregulation, and FDI).Section 5 is composed by: a) annual average of sales growth in the last two years, b) sales percentage related to new products in the past two years, and c) market growth percentage regarding competition in the past two years.