Resultados de investigación

Dataset for the review article "Gender-based violence in the context of the Future of Work: A qualitative review of the literature," published in the journal Trauma, Violence, & Abuse. The article examines 39 academic articles, book chapters, reports, and conference papers published between 2016 and 2023 using qualitative content analysis to provide a preliminary understanding of empirical data on gender-based violence in platform work.

Replication data for the publication: "rSIREM: an R package for MALDI spectral deconvolution" by Del Castillo Pérez et al. The deposited data are SALDI-MSI data of three consectutive thin tissue sections from mouse cerebellum measured at the different mass resolutions at the same instrument (MALDI-MSI: Spectroglyph Injector - Orbitrap Exploris). The paper describes a new R package (rSIREM) to computationally improve the mass resolution of an MSI post-measurement. The developed R package (https://github.com/EdelCastillo/rSirem ) applies a statistical treatment on the concentration of spatial images obtained by separately considering each of the m/z over all the pixels. A representative scalar is associated with each image, obtained by applying a new measure (SIREM) to it, derived from Shannon's entropy. The perturbations of this measure, when considering a sequence of consecutive images, reveal the existence of overlap, if it exists. This information serves as a seed to initialize the EM algorithm in the Gaussian Mixture Model context. The efficiency of the method has been verified using three independent procedures.

This dataset features illustrations in raster format that represent different Nature Based Solutions (NBS) for urban water management, organized into two main categories depending on the type of water: wastewater treatment and stormwater management. The illustrations explain each solution in a simple manner, using cross-sectional views. This approach allows for an observation of both the internal functioning of the system and its external appearance. The images are designed to provide a clear understanding of the water treatment or management process, as well as the design and external structure of each solution.

Data of available stable isotope measurements of archaeological interest (?13C, ?15N, ?34S, ?18O, and 87Sr/86Sr) reported for humans, and animals from several archaeological sites of the Central Coast of Peru. The dataset includes the results of a pilot study of compound-single isotope amino acids analysis (CSIA) in a subset of 19 individuals (15 humans and 4 animals) from the same region. These data were produced by the PACHAMAMA Project (MSCA – Horizon 2020) and are part of several publications and submitted reports.

Dataset of the transcriptional analyses performed with OpenArray technology to study the effects of different cultivating conditions to the expression of key genes involved in Komagataella phaffii metabolism in a recombinant protein producing strain. In particular, 27 genes were studied from glycolysis/gluconeogenesis, pentose phosphate pathway, glyoxylate cycle, oxidative stress response, lipids biosynthetic metabolism, the recombinant gene of interest and four more relevant genes related to heterologous protein production. The dataset contains information of the genes studied, the sequences used for amplification and the results of both the no template control (NTC) and the samples. The samples results are expressed in terms of relative expression and log2fold.

We applied mass-spectrometry-based techniques to quantify 569 lipid species and related indexs in plasma samples from 171 subjects (39 centenarians, 63 centenarians’ offspring, and 69 non-centenarians’ offspring without familial connections).

Dataset related to the characterization of formate and glycerol dehydrogenases, reaction medium engineering, and optimization of the multi-enzymatic production of formate and DHA from industrial waste such as CO2 and glycerol. Additionally, the evaluation of the reaction under industrially relevant conditions using real industrial waste was included., Data of the simultaneous production of formate and DHA by a multi-enzymatic system for the valorization of industrial waste: CO2 and glycerol.

Experimental raw data for all figures presented in the paper "Hydrogen Evolution Reaction of Electrodeposited Ni-W Films in Acidic Medium and Performance Optimization Using Machine Learning" are provided. The data were utilized to investigate and optimize the electrodeposition conditions of Ni-W films for hydrogen evolution reaction (HER) using machine learning. The study began with an analysis of bath and electrodeposition conditions (Figure 1), followed by SEM imaging of the film morphologies at several current densities and temperatures (Figure 2). The crystal structure of the films was characterized by GIXRD (Figure 3), and the electrocatalytic properties were tested (Figures 4, 5). Additionally, the durability of the films in acidic media was assessed (Figures 6, 7). Subsequently, machine learning was employed to optimize the deposition conditions (ML data). The best-performing samples were further analysed using SEM, TEM, electrochemical measurements (Figures 8, 9), XPS (Figure 11), and XRD (Figure 12) to evaluate the optimized film properties both before and after HER testing.

The dataset includes the results on the description task of the Catalan Comprehensive Aphasia test (CAT-CAT, Salmons et al. 2021) of 109 control subjects, 20 individuals with aphasia and 4 individuals with cognitive impairment. The scoring method consists in a closed-rating system that evaluates productivity, discourse efficiency, fluency, grammatical complexity and grammaticality. The goal was to analyze and investigate the production abilities of Catalan-speaking individuals and to evaluate whether the scoring system used is helpful to diagnose language pathologies and to discriminate different patterns of language impairment. Some of the transcriptions of the participantsÕ responses are available at https://ddd.uab.cat/record/257486

Databases containing raw analytical data obtained in the SEROCOV-1 and SEROCOVAC studies and personal covariates used in the publication Moncunill G, Aguilar R, et al EBioMedicine. 2022 Jan 11;75:103805. doi: 10.1016/j.ebiom.2021.103805. Data correspond to antibody levels to SARS-CoV-2 and four seasonal coronaviruses, and the neutralization capacity of samples from 578 participants recruited from 28 March- 9 April 2020, and the follow-up visits after one, three, six, nine and twelve months. In months 9 and 12, data on vaccination status was collected and some participants had already received the 1st (N=64) or the 2nd doses (N=4). Month 12 follow-up mostly included participants who had a blood sample taken two weeks post 2nd dose. The analytical data is completed with participants' information on occupation, comorbidities, previous COVID19 diagnoses and other sociodemographic characteristics. The code was developed using R version 4.0.3.