cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/h8mmnthn5w
title: GreEn-ER - Electricity Consumption Data of a Tertiary Building

description: This dataset provides electricity consumption data collected from the building management system of GreEn-ER. This building, located in Grenoble, hosts Grenoble-INP Ense³ Engineering School and the G2ELab (Grenoble Electrical Engineering Laboratory). It brings together in one place the teaching and research actors around new energy technologies. The electricity consumption of the building is highly monitored with plus than 300 meters. The data from each meter is available in one csv file, which contains two columns. One contains the Timestamp and the other contains de electricity consumption in kWh. The sampling rate for all data is 10 min. There are data available for 2017 and 2018. The dataset also contains data of the external temperature for 2017 and 2018. The files are structured as follows: - The main folder called "Data" contains 2 sub-folders, each one corresponding to one year (2017 and 2018). - Each sub-folder contains 3 other sub-folders, each one corresponding to a sector of the building. - The main folder "Data" also contains the csv files with the electricity consumption data of the whole building and a file called "Temp.csv" with the temperature data. - The separator used in the csv files is ";". - The sampling rate is 10 min and the unity of the consumption is kWh. It means that each sample corresponds to the energy consumption in these 10 minutes. So if the user wants to retrieve the mean power in this period (that corresponds to each sample), the value must be multiplied by 6. - Four Jupyter Notebook files, a format that allows combining text, graphics and code in python are also available. These files allow exploring all the data within the dataset. - These jupyter notebook files contains all the metadata necessary for understanding the system, like drawings of the system design, of the building etc. - Each file is named by the number of its meter. These numbers can be retrieved in tables and drawings available in the Jupyter Notebooks. - A couple of csv files with the system design are also available. They are called "TGBT1_n.csv", "TGBT2_n.csv" and "PREDIS-MHI_n.csv".
DOI: 10.6084/m9.figshare.19519684.v1
title: XRD (raw data)

description: XRD mineralogy data for Enspel and Messel shales controls.<br>
DOI: 10.6084/m9.figshare.28629152.v1
title: Analysis of Cognitive Biases in Construction Health and Safety in New Zealand

description: The construction industry's intricate and high-risk characteristics create considerable challenges in decision-making, often leading to mistakes that threaten health and safety performance. Cognitive biases can further skew risk evaluations and shape decision-making, ultimately impacting safety behaviors and outcomes. While numerous studies have looked into cognitive biases in construction, a comprehensive understanding of how these biases interact with crucial decision factors related to health and safety is still lacking. This study aimed to enhance sustainable health and safety practices within the construction sector by investigating the repercussions and interactions of cognitive biases with fundamental decision factors through a systematic literature review. A total of two hundred and eighty-three articles published between 2018 and 2024 were examined, with forty-five selected for inclusion. The findings from the network analysis highlight key decision factors, reinforcing loops, and essential paths that influence health and safety performance, demonstrating how cognitive biases shape risk perception, decision intricacy, and workplace safety behaviors. The insights derived from this research underscore the challenges and the possibilities for improvement, providing a basis for researchers, construction safety professionals, and policymakers to create targeted strategies that reduce cognitive biases, improve risk perception, and reinforce decision-making frameworks, ultimately enhancing health and safety performance in the construction industry.<br>
DOI: 10.6084/m9.figshare.28768301.v1
title: DFT_dataset (M06-2X/def2-TZVP)

description: DFT dataset containing 1582 reactions.In the csv file of this dataset:<br>- The ID code of the reaction that enables to group together the reactions with the same reactants<br>- The R number of the reaction<br>- The fully mapped smiles code of the reaction<br>- The activation free energy of the reaction (G(TS) = G(TS) - G(monomer 1) - G(monomer 2))<br>- The reaction free energy (DrG = G(product) - G(monomer 1) - G(monomer 2))- All the energies are given in kcal/mol and were calculated at the M06-2X/def2-TZVP level.In each reaction subdirectory:<br>- Geometry of the monomers<br>- Geometry of the transition state- Geometry of the product
DOI: 10.17632/crvy9jgb6g
title: IMU Data for Pitch and Roll Compensation and Vertical Acceleration Estimation: A Machine Learning Approach for Strapdown Gravimeters

description: Strapdown gravimeters are multi-sensor systems capable of providing all necessary data to reconstruct gravity measurements collected onboard a moving platform (e.g., an airplane, a boat, or a submarine). The primary challenge lies in removing from the gravimeter readings the effects of disturbances, such as unaccounted rotations of the moving platform.
This dataset was generated using an experimental setup comprising a three-axial gyroscope and a three-axial accelerometer (i.e., an Inertial Measurement Unit, IMU) installed on a “training platform”. The training platform, equipped with three linear actuators acting as feet, aimed to replicate the operational environment of a moving platform, such as a boat. In this version of the training platform, the IMU was subjected to tilt oscillations (pitch and roll) as well as vertical oscillations, with the latter being monitored by three linear encoders attached to the linear actuators. By analyzing the linear encoders data, one can infer the vertical acceleration and, according to the Equivalence Principle of Einstein, utilize it as a proxy for gravity variations to be measured.
The key challenge is to reconstruct from the IMU data the vertical acceleration derived from the linear encoders data. The methodologies developed to address this challenge will play a pivotal role in the advancement of a novel type of strapdown gravimeter known as “Gravimetro Aereo INtelligente” (GAIN), which relies on Machine Learning techniques for data processing.
DOI: 10.6084/m9.figshare.12249965.v1
title: Data For Paper 2

description: This is the Data that was used in the Paper
DOI: 10.6084/m9.figshare.25055033.v1
title: Plant community data and site environmental variables for "The large-scale restoration of fire and water regimes in Everglades National Park reveal little change in plant diversity along an elevational gradient."

description: Quantifying the response of plant diversity to large-scale restoration is essential for measuring management success. One of the world’s largest restoration efforts began in 2000 in the Everglades ecosystem in Florida, USA through the Comprehensive Everglades Restoration Plan (CERP). In coordination with ongoing fire management, this restoration effort aims to restore natural hydrologic and fire regimes in this dynamic ecosystem. Restored water and fire regimes in the Everglades interact along an elevational gradient between seasonally inundated marl prairie and frequently burned pine rockland on Long Pine Key (LPK) in Everglades National Park (ENP). To determine the effects of management on plant community richness and composition, we resampled transects spanning the elevational gradient between marl prairie and pine rockland initially sampled prior to the implementation of current restoration efforts (c. 1997-1999). We measured percent plant cover and developed generalized linear mixed models to determine the effects of fire frequency, average water depth, and elevation on plant species richness and composition across the two time periods.
DOI: 10.6084/m9.figshare.28131662.v1
title: Supplementary Material for: Incidence and clinical features of inguinal metastases of testicular germ cell tumors

description: Introduction
Half of all patients with testicular germ cell tumours (GCTs) present with metastases to retroperitoneal lymph nodes or visceral organs. Inguinal metastases (I/M) are very rare. We aimed to evaluate the relative frequency and clinical features of I/M and to look for predisposing factors.
Methods
A cohort of 740 GCT patients treated between 2010-2022 was analyzed. The frequency of I/M and their clinical features were statistically compared among the subgroups. 
Results
Eight patients had I/M, with a median age of 55 years, all of whom had primary seminoma, six had previous groin surgery. The relative frequency of I/M is 1.1% and 8.3% in the GCT patient cohort and the metastasized seminoma subgroup, respectively. All patients were cured, six underwent surgery and additional chemotherapy, and two received cisplatin-based chemotherapy alone. 
Discussion
Inguinal metastases occur in approximately 1% of GCT patients. Prior groin surgery, bulky retroperitoneal metastases and possibly histology of seminoma represent risk factors for I/M. The presence of I/M does not adversely affect prognosis, and all cases can be cured with standard therapeutic measures. Lymph node excision may be required to establish the diagnosis. In patients with risk factors, follow-up examinations should include the groins.
DOI: 10.6084/m9.figshare.28225544.v2
title: <b>S4 Table </b><b>SNP</b><b> </b><b>calling</b><b> </b><b>score</b><b> </b><b>from individual sequencing data.</b><b> </b><b>score</b><b> </b><b>from individual sequencing data</b>

description: <i>Bromus auleticus</i>, a valuable forage grass native to the Pampa biome, is currently suffering genetic erosion. Therefore, it is central to assess the appropriate methodologies for developing population genomic studies and contributing to the conservation of this plant genetic resource. This study evaluated five accessions using two genotyping strategies: individual sequencing (ind-seq) and pooled sequencing (pool-seq). To compare their efficacy, was investigated the correlation between allele frequencies calculated using each approach. Geneticdiversity and population structure were also analyzed using both methods. These comparisons explicitly accounted for the potential effects of one or more of the following parameters: sample size, missing data, sequencing depth, and minor allele frequencies. Notably, the highest concordance and percentage of common SNPs between ind-seq and pool-seq was achieved using 30 to 60 plants per accession, with a maximum missing data threshold of 10% and a more tolerant minimum allele frequency threshold for pool-seq (0.01) compared to ind-seq (0.05). Reaching maximum similarity in allele frequencies also required a higher sequencing depth for pool-seq (4.8 million reads-Mr) than for ind-seq (0.9 Mr). Pools of 50 individuals yielded the highest number of polymorphic sites, averaging over 9,000 across all accessions at a sequencing depth of 4.8 Mr. Under these conditions, pool-seq consistently yielded a means across all accessions of 0.09 higher expected heterozygosity and 0.24 lower allelic richness compared to ind-seq across all accessions. The population structure detected with both methodologies showed agreement, aligning with the outcrossing nature of <i>B. auleticus</i> and the geographical origin of each accession. The average inbreeding coefficient of 0.2 indicates signs of inbreeding, highlighting the importance of conservation efforts of this valuable plant genetic resource. Based on these findings, two workflows were proposed to carry out population genomics studies of <i>Bromus auleticus</i>.
DOI: 10.17605/osf.io/tuvmb
title: Orientation Tuned Surround-Suppression Is Strongest Within Perceived 3D Surfaces.

description: Raw data files are saved in .mat format and can be opened in MATLAB. Loading the file will create one variable, a MATLAB table called 'results' with one row for each trial in the experiment (n = 31680 for Experiment 1, 31415 for Experiment 2, 19404 for Experiment 3)

Experiment 1:

results has the following fields:
subjID: numerical ID of subject
sessID: numerical ID for experimental session
testFirst: 1 = reference presented first, 2 = reference presented second
depth: 1 = Flat, 2 = Depth
contrastDelta: Difference in contrast between the test and reference gratings.
orientation: 1 = Iso, 2 = Cross
response: 1 = chose the 2nd grating as being higher in contrast, 2 = chose the 1st grating as being higher
RT: RT from the onset of the question.

Experiment 2 is structured in the same way.

Experiment 3 has the following additional fields:

condition: 1 = Bump, 2 = Average, 3 = Near
phase: phase offset of central grating
DOI: 10.6084/m9.figshare.23849340.v1
title: Soil stress analysis at different depths after agricultural vehicle operation

description: The stepwise compression experiment of soil samples was carried out by WG single lever consolidation instrument (medium and low pressure) and NSIF geotechnical test control data acquisition and processing system, and the compression curve of the pore ratio and external load of the sample soil under the side limit condition and the change of soil stress measured at different depths of the soil were obtained: with the increase of external load, the pore ratio of soil gradually decreased, and the compressive modulus gradually increased. The larger the soil pore ratio, the smaller the allowable bearing capacity of the soil, and when the soil pore ratio is reduced to a certain extent, the stress strain change of the test soil tends to be stable.
DOI: 10.6084/m9.figshare.28806191.v1
title: Factors influencing fine root decomposition rate in response to nitrogen addition vary across root characteristics

description: The increase in nitrogen (N) deposition has significant effects on litter decomposition, nutrient release, and soil organic matter cycling, which has altered carbon allocation patterns in terrestrial ecosystems. Although most studies on the effects of N addition have focused on aboveground litter decomposition, the responses of fine root decomposition rate to N addition and their drivers, particularly across different root characteristics, remain unclear.<br>We synthesized 144 observations from 30 peer-reviewed publications and used meta-analysis to elucidate the responses of fine root decomposition rate to N addition and to identify the primary factors influencing these responses under different root characteristics.<br>N addition reduced fine root decomposition rate and mass loss by 8.52% and 6.24%, respectively. Specifically, fine roots with diameters ≤ 2 mm and first- and second-order roots exhibited negative responses to N addition. Overall, soil microbial biomass N and soil clay content were the main factors affecting the fine root decomposition rate in response to N addition. Within different root characteristics, soil microbial biomass N and soil N content were the primary factors regulating the response of fine roots ≤ 1 mm decomposition to N addition, while the N addition amount was the key factor of third to fifth-order root decomposition in response to N addition.<br>Our results suggested that the primary factors regulating the response of fine root decomposition rate to N addition varied across fine root characteristics. These differences in controlling factors highlighted the importance of incorporating fine roots characteristics into ecosystem models to predict the responses of belowground carbon and nutrient release to future climate changes.
DOI: 10.6084/m9.figshare.5128822.v1
title: Supplementary Material for: Neural Correlates of Schizophrenia Negative Symptoms: Distinct Subtypes Impact Dissociable Brain Circuits

description: <b><i>Background:</i></b> The negative symptoms of schizophrenia include deficits in emotional expression and motivation. These deficits are stable over the course of illness and respond poorly to current medications. Previous studies have focused on negative symptoms as a single category; however, individual symptoms might be related to separate neurological disturbances. We analyzed data from the Functional Biomedical Informatics Research Network dataset to explore the relationship between individual negative symptoms and functional brain activity during an auditory oddball task. <b><i>Methods:</i></b> Functional magnetic resonance imaging was conducted on 89 schizophrenia patients and 106 healthy controls during a two-tone auditory oddball task. Blood oxygenation level-dependent (BOLD) signal during the target tone was correlated with severity of five negative symptom domains from the Scale for the Assessment of Negative Symptoms. <b><i>Results:</i></b> The severity of alogia, avolition/apathy and anhedonia/asociality was negatively correlated with BOLD activity in distinct sets of brain regions associated with processing of the target tone, including basal ganglia, thalamus, insular cortex, prefrontal cortex, posterior cingulate and parietal cortex. <b><i>Conclusions:</i></b> Individual symptoms were related to different patterns of functional activation during the oddball task, suggesting that individual symptoms might arise from distinct neural mechanisms. This work has potential to inform interventions that target these symptom-related neural disruptions.
DOI: 10.6084/m9.figshare.6025340.v1
title: Electricity-gas unit commitment

description: This dataset included two integrated electrical and gas systems. Please refer to my paper "Unit Commitment of Integrated Electrical and Gas System with an Enhanced SOC Gas Flow Model" is published online.
DOI: 10.17632/7kbgfn5tfh
title: Impact of traffic on heavy metal pollution of urban soils (Lublin, Poland)

description: Information on the heavy metals content in urban soils is important for a comprehensive assessment of environmental pollution. An important source of soil pollution can be traffic-related emissions. The objective of the study was to assess the sources and level of soil pollution in medium-sized city (Lublin, E Poland). Concentrations of As, Cd, Cr, Cu, Ni, Pb and Zn were determined in 62 samples of road dust and 90 soil samples. We applied following geochemical indices to determine the degree of pollution. PCA and CA were also used to assess sources of pollution. Geochemical indices showed the existence of medium to high pollution of dust and soils near roads by Cu and Zn and high for Cd, Cu and Zn in post-industrial soils. The results of the statistical analyses showed the same pollution sources for road dust and roadside soils. It is represented by transport-related emissions.
DOI: 10.17632/89c7xbxj6x
title: Tumour Infiltrating Lymphocytes in Follicular Lymphoma - additional data 8

description: Part 8/10 Description provided in dataset linked below.
DOI: 10.17632/bk7zrx4gfw
title: English version of the Computer Vision Symptom Scale (CVSS17)

description: Research hypothesis: The English and the Spanish version of the Computer Vision Symptom Scale (CVSS17) are equivalente and show similar psychometric properties.

The dataset is composed by two text files used as control file for WINSTEPS analysis:

1. Datos para DIF CVSS17 vs CVSS17ENG.txt: The first group of lines, from &INST to &END configures the analysis performed in WINSTEPS to perform a Differential Item Analysis (DIF), based on the Rasch analysis results, between CVSS17 English Version and the original version, developed in European Spanish. The line starting with "PDELETE" shows the respondents excluded from the analysis. The next 17 lines indicates the ID for each questionnaire item. The following lines, until the end of the archive, contains the responses obtained from the participant. Each line displays the responses of each person. The first letter indicates whether the respondent answered the English version (i) or the Spanish version (E) , followed by four numbers (assigned by random), followed by one digit showing whether the respondent was a male (2) or a female (1), followed by a group of two letters describing if the respondent was presbyope (&gt;39 years old) or non presbyope. The next 17 numbers displays the option chosen by the respondent for each item (in the order defined by the labels displayed at the begining of this file), N was used to label missing responses. 
2. Datos para análisis de Rasch de la CVSS17ENG.txt: The first group of lines, from &INST to &END configures the analysis performed in WINSTEPS to assess the structural validity of the CVSS17 English Version. The line starting with "PDELETE" shows the respondents excluded from the analysis. The next 17 lines indicates the ID for each questionnaire item. The following lines, until the end of the archive, contains the responses obtained from the participant. Each line displays the responses of each person. The first letter indicates thar the respondent answered the English Vesion (i), followed by four numbers (assigned by random), followed by one digit showing whether the respondent was a male (2) or a female (1), followed by a group of two letters describing if the respondent was presbyope (&gt;39 years old) or non presbyope. The next 17 numbers displays the option chosen by the respondent for each item (in the order defined by the labels displayed at the begining of this file), N was used to label missing responses. 

Those interested in using this data just need to use any of these two files as a control file for WINSTEPS analysis. The interpretation of the results will be shown in a scientific paper.
DOI: 10.6084/m9.figshare.1217519.v1
title: 8.8 nm in 50 % Glycerol (3)

description: PhRICS imaging of 8.8 nm gold nanoparticles in 50 % (v/v) Glycerol/Water (Exp3).
DOI: 10.6084/m9.figshare.1368643.v1
title: Texture analysis in gel electrophoresis images using an integrative kernel-based approach

description: How to cite this article: Fernandez-Lozano, C. et al. Texture analysis in gel electrophoresis images using an integrative kernel-based approach. Sci. Rep. 5, 19256; doi: 10.1038/srep19256 (2015). <br>In order to generate the dataset, ten 2-DE images of different types of tissues and different experimental conditions were used. These images are from the dataset owned by G.-Z Yang (Imperial College of Science, Technology and Medicine, London) and have been used in several publications. For each image, two different clinicians agreed on 100 regions of interest manually segmented that were selected to build a training set with 1000 samples and 274 textural variables. We considered six groups of textural features: Histogram-based (first-order statistical texture features), Absolute Gradient, Run-length Matrix (high-order statistical texture features), Co-occurrence Matrix (second-order statistical texture features), Autoregressive Model and Wavelet. These features are based on image histogram, co-occurrence matrix (information about the grey level value distribution of pairs of pixels), image gradients (spatial distribution of grey level values), auto-regressive models (description of texture based on statistical correlation between pairs of pixels) and wavelet analysis (information about image frequency at different scales). We calculated those features with a specialized software called Mazda. Various approaches have demonstrated the effectiveness of this software, extracting textural features in different types of medical images
DOI: 10.6084/m9.figshare.25266307.v1
title: Source data for Fig. 2-4 of of <b>NM23082803A</b>

description: Drift-free iontronic sensing is achieved by using a rationally designed leakage-free and creep-free polyelectrolyte elastomer.