Data

Recently, there has been a growing research interest in utilizing the electroencephalogram (EEG) as a non-invasive diagnostic tool for neurodegenerative diseases. This article provides a detailed description of a resting-state EEG dataset of individuals with Alzheimer’s disease and frontotemporal dementia, and healthy controls. The dataset was collected using a clinical EEG system with 19 scalp electrodes while participants were in a resting state with their eyes closed. The data collection process included rigorous quality control measures to ensure data accuracy and consistency. The dataset contains recordings of 36 Alzheimer’s patients, 23 frontotemporal dementia patients, and 29 healthy age-matched subjects. For each subject, the Mini-Mental State Examination score is reported. A monopolar montage was used to collect the signals. A raw and preprocessed EEG is included in the standard BIDS format. For the preprocessed signals, established methods such as artifact subspace reconstruction and an independent component analysis have been employed for denoising. The dataset has significant reuse potential since Alzheimer’s EEG Machine Learning studies are increasing in popularity and there is a lack of publicly available EEG datasets. The resting-state EEG data can be used to explore alterations in brain activity and connectivity in these conditions, and to develop new diagnostic and treatment approaches. Additionally, the dataset can be used to compare EEG characteristics between different types of dementia, which could provide insights into the underlying mechanisms of these conditions.

Andreas Miltiadous

Katerina D. Tzimourta

Theodora Afrantou

Panagiotis Ioannidis

Nikolaos Grigoriadis

Dimitrios G. Tsalikakis

Pantelis Angelidis

Markos G. Tsipouras

Euripidis Glavas

Nikolaos Giannakeas

Alexandros T. Tzallas

A Dataset of Scalp EEG Recordings of Alzheimer’s Disease, Frontotemporal Dementia and Healthy Subjects from Routine EEG

阿尔茨海默病、额颞叶痴呆及健康受试者常规脑电图中头皮脑电记录数据集

Coptotermes gestroi (Wasmann) (Blattodea: Rhinotermitidae) is a subterranean termite species from Southeast Asia which has been unintentionally introduced to many parts of the world through commerce and modern transportation. Known for causing extensive damage to timber used in the built environment, the termite also has a habit of nesting in carton nests in wood and wooden structures in buildings. As so little is known of its breeding system, colony, and genetic structure, we initiated work to sequence its genome with an Illumina HiSeq™ 2000 sequencer. In this publication, we announce our paired-end sequencing data and report the isolation of 119,190 microsatellite markers from our DNA assembly. The microsatellite marker reported in this publication can be used to elucidate the mating system and genetic structure of this highly invasive termite species. Additionally, in this announcement the study authors make the Bio Project sequence accession number SRR13105492 accessible from the Sequence Read Archive database.

Li Yang Lim

Shawn Cheng

Abdul Hafiz Ab Majid

Isolation of Microsatellite Markers from De Novo Whole Genome Sequences of Coptotermes gestroi (Wasmann) (Blattodea: Rhinotermitidae)

从新测序的全基因组序列中分离出格斯特乳白蚁（Wasmann）（蜚蠊目：鼻白蚁科）的微卫星标记

The importance of evaluating the stress field of loaded structures lies in the need for identifying the forces which make them fail, redesigning their geometry to increase the mechanical resistance, or characterizing unstressed regions to remove material. In such work line, digital photoelasticity highlights with the possibility of revealing the stress information through isochromatic color fringes, and quantifying it through inverse problem strategies. However, the absence of public data with a high variety of spatial fringe distribution has limited developing new proposals which generalize the stress evaluation in a wider variety of industrial applications. This dataset shares a variated collection of stress maps and their respective representation in color fringe patterns. In this case, the data were generated following a computational strategy that emulates the circular polariscope in dark field, but assuming stress surfaces and patches derived from analytical stress models, 3D reconstructions, saliency maps, and superpositions of Gaussian surfaces. In total, two sets of ‘101430’ raw images were separately generated for stress maps and isochromatic color fringes, respectively. This dataset can be valuable for researchers interested in characterizing the mechanical response in loaded models, engineers in computer science interested in modeling inverse problems, and scientists who work in physical phenomena such as 3D reconstruction in visible light, bubble analysis, oil surfaces, and film thickness.

Juan-Carlos Briñez-De-Leon

Mateo Rico-Garcia

Alejandro Restrepo-Martínez

Isochromatic-Art: A Computational Dataset for Digital Photoelasticity Studies

同色艺术：数字光弹性研究的计算数据集

This paper presents a comprehensive exploration of data quality terminology, revealing a significant lack of standardisation in the field. The goal of this work was to conduct a comparative analysis of data quality terminology across different domains and structure it into a hierarchical data model. We propose a novel approach for aggregating disparate data quality terms used to describe the multiple facets of data quality under common umbrella terms with a focus on the ISO 25012 standard. We introduce four additional data quality dimensions: governance, usefulness, quantity, and semantics. These dimensions enhance specificity, complementing the framework established by the ISO 25012 standard, as well as contribute to a broad understanding of data quality aspects. The ISO 25012 standard, a general standard for managing the data quality in information systems, offers a foundation for the development of our proposed Data Quality Data Model. This is due to the prevalent nature of digital systems across a multitude of domains. In contrast, frameworks such as ALCOA+, which were originally developed for specific regulated industries, can be applied more broadly but may not always be generalisable. Ultimately, the model we propose aggregates and classifies data quality terminology, facilitating seamless communication of the data quality between different domains when collaboration is required to tackle cross-domain projects or challenges. By establishing this hierarchical model, we aim to improve understanding and implementation of data quality practices, thereby addressing critical issues in various domains.

Russell Miller

Harvey Whelan

Michael Chrubasik

David Whittaker

Paul Duncan

João Gregório

A Framework for Current and New Data Quality Dimensions: An Overview

当前与新型数据质量维度的框架：概述

This work focuses on the study of operating heterogeneities on a large MEA’s active surface area in a PEMFC stack. An advanced methodology is developed, aiming at the prediction of local operating conditions such as temperature, relative humidity and species concentration. A physics-based Pseudo-3D model developed under COMSOL Multiphysics allows for the observation of heterogeneities over the entire active surface area. Once predicted, these local operating conditions are experimentally emulated, thanks to a differential cell, to provide the local polarization curves and electrochemical impedance spectra. Coupling simulation and experimental, thirty-seven local operating conditions are emulated to examine the degree of correlation between local operating conditions and PEMFC cell performances. Researchers and engineers can use the polarization curves and Electrochemical Impedance Spectroscopy diagrams to fit the variables of an empirical model or to validate the results of a theoretical model.

Marine Cornet

Arnaud Morin

Jean-Philippe Poirot-Crouvezier

Yann Bultel

Advanced Methodology for Emulating Local Operating Conditions in Proton Exchange Membrane Fuel Cells

质子交换膜燃料电池局部运行条件模拟的先进方法

Prostate cancer (PCa) is a major health burden worldwide, and despite early treatment, many patients present with biochemical recurrence (BCR) post-treatment, reflected by a rise in prostate-specific antigen (PSA) over a clinical threshold. Novel transcriptomic and epigenomic biomarkers can provide a powerful tools for the clinical management of PCa. Here, we provide matched RNA sequencing and array-based genome-wide DNA methylome data of PCa patients (n = 17) with or without evidence of BCR following radical prostatectomy. Formalin-fixed paraffin-embedded (FFPE) tissues were used to generate these data, which included technical replicates to provide further validity of the data. We describe the sample features, experimental design, methods and bioinformatic pipelines for processing these multi-omic data. Importantly, comprehensive clinical, histopathological, and follow-up data for each patient were provided to enable the correlation of transcriptome and methylome features with clinical features. Our data will contribute towards the efforts of developing epigenomic and transcriptomic markers for BCR and also facilitate a deeper understanding of the molecular basis of PCa recurrence.

Jim Smith

Priyadarshana Ajithkumar

Emma J. Wilkinson

Atreyi Dutta

Sai Shyam Vasantharajan

Angela Yee

Gregory Gimenez

Rathan M. Subramaniam

Michael Lau

Amir D. Zarrabi

Euan J. Rodger

Aniruddha Chatterjee

Genome-Scale DNA Methylome and Transcriptome Profiles of Prostate Cancer Recurrence After Prostatectomy

前列腺癌根治术后复发的大规模DNA甲基化和转录组图谱

Italy is divided into 773 Agricultural Regions (ARs) based on shared physical and agronomic characteristics. These regions offer a valuable tool for analyzing various geographical, socio-economic, and environmental aspects of agriculture, including the climate. However, the ARs have lacked geospatial data, limiting their analytical potential. This study introduces the “Italian ARs Dataset”, a georeferenced shapefile defining the boundaries of each AR. This dataset facilitates geographical assessments of Italy’s complex agricultural sector. It also unlocks the potential for integrating AR data with other datasets like the Farm Accounting Data Network (FADN) dataset, in Italy represented by the Rete di Informazione Contabile Agricola (RICA), which samples hundreds of thousands of farms annually. To demonstrate the dataset’s utility, a large sample of RICA data encompassing 179 irrigated crops from 2011 to 2021, covering all of Italy, was retrieved. Validation confirmed successful assignment of all ARs present in the RICA sample to the corresponding shapefile. Additionally, to encourage the use of the ARs Dataset with gridded data, different spatial-scale resolutions are tested to identify a suitable threshold. The minimal spatial scale identified is 0.11 degrees, a commonly adopted scale by several climate datasets within the EURO-CORDEX and COPERNICUS programs.

Sara Quaresima

Pasquale Nino

Concetta Cardillo

Arianna Di Paola

Unlocking New Opportunities for Spatial Analysis of Farms’ Income and Business Activities in Italy: The Agricultural Regions in Shapefile Format

解锁意大利农场收入与经营活动空间分析的新机遇：以Shapefile格式呈现的农业区域

To address the growing electricity demand driven by population growth and economic development while mitigating climate change, West and Central African countries are increasingly prioritizing renewable energy as part of their Nationally Determined Contributions (NDCs). This study evaluates the implications of climate change on renewable energy potential using ten downscaled and bias-adjusted CMIP6 models (CDFt method). Key climate variables—temperature, solar radiation, and wind speed—were analyzed and integrated into the Teal-WCA platform to aid in energy resource planning. Projected temperature increases of 0.5–2.7 °C (2040–2069) and 0.7–5.2 °C (2070–2099) relative to 1985–2014 underscore the need for strategies to manage the rising demand for cooling. Solar radiation reductions (~15 W/m2) may lower photovoltaic (PV) efficiency by 1–8.75%, particularly in high-emission scenarios, requiring a focus on system optimization and diversification. Conversely, wind speeds are expected to increase, especially in coastal regions, enhancing wind power potential by 12–50% across most countries and by 25–100% in coastal nations. These findings highlight the necessity of integrating climate-resilient energy policies that leverage wind energy growth while mitigating challenges posed by reduced solar radiation. By providing a nuanced understanding of the renewable energy potential under changing climatic conditions, this study offers actionable insights for sustainable energy planning in West and Central Africa.

Salomon Obahoundje

Arona Diedhiou

Alberto Troccoli

Penny Boorman

Taofic Abdel Fabrice Alabi

Sandrine Anquetin

Louise Crochemore

Wanignon Ferdinand Fassinou

Benoit Hingray

Daouda Koné

Chérif Mamadou

Fatogoma Sorho

Teal-WCA: A Climate Services Platform for Planning Solar Photovoltaic and Wind Energy Resources in West and Central Africa in the Context of Climate Change

Teal-WCA：一个面向气候变化的西非和中非太阳能光伏和风能资源规划的气候服务平台

Abbreviation	Data. (Basel).
Journal Impact	2.06
Quartiles(Global)	MULTIDISCIPLINARY SCIENCES(Q2)

ISSN	2306-5729
h-index	38

Publication Information	Publisher: Multidisciplinary Digital Publishing Institute (MDPI)，Publishing cycle: ，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2016，Proportion of original research papers: 98.33%，Self Citation Rate:4.50%， Gold OA Rate: 99.19%
Journal Fees	$Details
Average review cycle	网友分享经验：10 Weeks

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A Dataset of Scalp EEG Recordings of Alzheimer’s Disease, Frontotemporal Dementia and Healthy Subjects from Routine EEG

Isolation of Microsatellite Markers from De Novo Whole Genome Sequences of Coptotermes gestroi (Wasmann) (Blattodea: Rhinotermitidae)

Isochromatic-Art: A Computational Dataset for Digital Photoelasticity Studies

A Framework for Current and New Data Quality Dimensions: An Overview

Advanced Methodology for Emulating Local Operating Conditions in Proton Exchange Membrane Fuel Cells

Advanced Methodology for Emulating Local Operating Conditions in Proton Exchange Membrane Fuel Cells

A Framework for Current and New Data Quality Dimensions: An Overview

Genome-Scale DNA Methylome and Transcriptome Profiles of Prostate Cancer Recurrence After Prostatectomy

Unlocking New Opportunities for Spatial Analysis of Farms’ Income and Business Activities in Italy: The Agricultural Regions in Shapefile Format

Teal-WCA: A Climate Services Platform for Planning Solar Photovoltaic and Wind Energy Resources in West and Central Africa in the Context of Climate Change