Resultados de investigación

Typical organisational goals promoted by knowledge management (KM) are being complemented with resilience-related objectives in many organisations worldwide. The need for resilience goes beyond companies, reaching their supply chains in a concept known as enterprise and supply chain resilience (ESCR). In complex times where organisations must learn to deal with disruptive events (DEs), ranging from internal events like inventory stockouts to external events, such as pandemics and wars, knowledge sharing becomes critical. Presenting a teaching case (TC) developed using instructional design principles, which aims to teach ESCR in real-world scenarios, is the main objective of this work. The proposed TC has clear goals, objectives, and learning outcomes, it intends to engage the students in situations that require problem-solving and decision-making. It is an open problem case with multiple perspectives where solutions can vary since DEs are difficult to predict and manage. The case includes detailed context information for the reader to understand and diagnose the situation and, after that, develop and create an action plan and a logic model to solve the problems related to the critical elements of the case. The TC presents a real-life situation, through the present dataset, where an organisation and its supply chain are facing a critical incident, an impactful DE, which is causing severe problems to the flow of products between customers and suppliers. This case has no unique answer, and the solutions require critical thinking., The authors would like to acknowledge the support of the researchers participating in the project “Business Continuity Managers Training Platform” (CONTINUITY) (business-continuity-project.eu).

[EN] The dataset contains the data that have been obtained during the synthesis and the characterization (chemical and photoelectrochemical) of TiO2/ZnO2 hybrid nanosponges used as photoanodes for photoelectrochemical applications. TiO2/ZnO2 hybrid nanosponges were obtained by electrodeposition of ZnO on TiO2 nanosponges with different times (15 min, 30 min, and 60 min), temperatures (25ºC, 65 ºC, and 75 ºC) and Zn(NO3)2 concentrations (0.5-10 mM). A chemical characterization was performed using X-Ray Photoelectron Spectroscopy (XPS) and Grazing Incidence X-Ray Diffraction (GIXRD). Electrochemical characterization of nanosponges was performed by Photoelectrochemical Water Splitting (PWS).

The collated data correspond to the parameters to estimate the resources consumption and the emissions to the environment from the main farming activities (resources consumption and emissions from infrastructure building and management, fertiliser and pesticide production, on-field fertiliser and pesticide emissions, fuel consumption from machinery use, and irrigation), together with the environmental impacts of the unit processes (e.g. electricity mix, production of agricultural inputs) required to assess the environmental impacts from a panel of reference holdings at the main NUTS 2 in Spain., The authors gratefully acknowledge both the Universitat Politècnica de València for providing the funds for N.K. Sinisterra-Solís’s research contract through Subprogram 1 (PAID-01-18).

The data are related with the preparation of electrodes based on WO3 nanostructures used as anode materials for Li-ion batteries. The nanostructured WO3 thin film was effectively synthesized by an electrochemical procedure. Then, an annealing treatment at 600◦C in air environment for 4 h was carried out. In the second electrode synthesized, a carbon layer was uniformly deposited on WO3 nanostructures to obtain a WO3/C electrode. Finally, WO3/WS2 electrodes were prepared by means of in situ sulfurization of WO3 one-step solid-state synthesis using tungsten trioxide (WO3) and thiourea as precursor material. By using X-ray photoelectron spectroscopy, X-ray diffraction analysis and Raman spectra, the three electrodes have been morphologically characterized. Electrochemical properties were analysed by cyclic voltammogram, galvanostatic charge/discharge cycling, and electrochemical impedance spectroscopy.

This dataset includes the raw data collected from two Open Access megapublisher websites (mdpi.com and frontiersin.org) across several SEO tools (Ahrefs, Semrush, SERPstats, Ubersuggest, Sistrix). From each domain name, SEO-level metrics (e.g., organic keywords, global traffic, traffic by country) were collected and structured.

[EN] This dataset includes, as supplementary material, the detailed calculations and expert questionnaires required to carry out the prioritization of Ecosystem Services in three wetlands in Spain, aggregating expert opinions and using the Analytic Network Process (ANP) method.

Twitter dataset for a research on the 2015 Spanish General Election. The tweets were obtained through the Twitter API's Search function since November 2 to December 21, 2015. Three criteria for filtering tweets were established: two general terms linked to the elections ("#20D", "20-D"); the name and usernames of the four main parties (PP, PSOE, Podemos and Ciudadanos), and the name and usernames of the four candidates from those parties. The research assessed the tweet's issue according to Patterson (1980)'s typology for evaluating political mediatisation. The dataset contains three files: the unlabelled collection of the 15.8 million tweet ids obtained through the API, the annotated sample of the 3,117 tweet ids for assessing the issue via machine learning, and the readme.txt file. It is recommended to open the file from a text editor or through a script. The id_str must be handled as a string. If the file is open from Excel, the id_str will be interpreted as a number, and then converted into a float, losing information in this transformation

[EN] These datasets were generated to train ("PopulationDrugsTrainingKrNaLCaL.xlsx") and test ("PopulationDrugsTestKrCaLNaL.xlsx") the uncertainty assessment models developed in the paper "Uncertainty assessment of proarrhythmia predictions derived from multi-level in silico models" by Kopanska, Rodríguez-Belenguer, et al., The authors received funding from the eTRANSAFE project, Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 777365, supported from European Union's Horizon 2020 and the EFPIA. We also received funding from the SimCardioTest supported by European Union’s Horizon 2020 research and innovation programme under grant agreement No 101016496. J.L.L. is being funded by the Ministerio de Ciencia, Innovacion y Universidades for the “Formacion de Profesorado Universitario” (Grant Reference: FPU18/01659). The work was also partially support by the Dirección General de Política Científica de la Generalitat Valenciana (PROMETEO/ 2020/043).

This repository contains the Matlab functions used in [1] and six Excel files named “Tx matrix KrKsCaL.xlsx”, “Tx matix KrNaLCaL.xlsx”, “TqNet matrix KrKsCaL.xlsx”, “TqNet matrix KrNaLCaL.xlsx”, "Ttirang matrix KrKsCaL.xlsx" and “Ttirang matrix KrNaLCaL.xlsx”. These files contain the value of three arrhythmogenic indices proposed in [1] (Tx, TqNet and Ttriang) resulting from simulations of drug effects on the action potential. The simulations were performed in a modified version of the O’Hara-Rudy model (ORd) [2] of human endocardial ventricular cells (492.536 simulations). References: [1]. Llopis J., Gomis-Tena J., Cano J., Romero L., Saiz J., Trenor B. In-Silico Classifiers for Assessment of Drug Proarrhythmicity. 2020 (Currently under revision) [2]. O’Hara, T.; Virág, L.; Varró, A.; Rudy, Y. Simulation of the Undiseased Human Cardiac Ventricular Action Potential: Model Formulation and Experimental Validation. PLoS Comput. Biol. 2011, 7 (5), e1002061., The authors would like to strongly thank Dr. Manuel Pastor from Research Programme on Biomedical Informatics (GRIB), at Universitat Pompeu Fabra (Barcelona, Spain) for its review of the manuscript and expert opinions and suggestions. This work was partially supported by the Dirección general de Política Científica de la Generalitat Valencia (PROMETEU2016/088), Primeros Proyectos de Investigación (PAID-06-18), Vicerrectorado de Investigación, Innovación y Transferencia de la Universitat Politècnica de València (UPV), València, Spain as well as Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016 from the Ministerio de Economía, Industria y Competitividad of Spain (DPI2016-75799-R) and AEI/FEDER, UE. JL is being funded by the Ministerio de Ciencia, Innovación y Universidades for the Formación de Profesorado Universitario (grant reference: FPU18/01659).

This research study investigates the electrooxidation of naproxen (NPX), an anti-inflammatory pharmaceutical, on modified carbon paper (CP) electrodes. Electrochemical modification of CP electrodes was accomplished with Pt or reduced graphene oxide (RGO)-Pt coatings, resulting in the production of electroactive electrodes. RGO coatings synthesized by cyclic voltammetry (CV) for 10 scans provided the optimal coverage for the CP electrode surface. The deposition of Pt nanoparticles (Pt NPs) on the electrodes (CP or CP-RGO) by CV produced a good electrode surface coverage with 20 synthesis scans. The voltammetric analysis of the electrodes in 230 mg/L NPX solution showed oxidation peaks around 1.0 to 1.2 V. Moreover, the inclusion of RGO in the coating led to an increase in the current density of these oxidation peaks and a decrease of the electrode electron transfer resistance as measured by electrochemical impedance spectroscopy. The electrolysis of NPX in different electrolytes (Na2SO4 and Na2SO4/NaCl) was conducted at 1.4 V, and the removal of NPX was analyzed using high-performance liquid chromatography. The CP-RGO-Pt electrode in Na2SO4/NaCl media showed the fastest NPX degradation kinetics, resulting in a 90 % degradation in only 90 min with low charge consumption (0.07 A⋅h⋅L-1). The smaller size of Pt NPs deposited on CP-RGO, as observed by field emission scanning electron microscopy and transmission electron microscopy, contributed to the higher electrochemical response in CV and a faster kinetic degradation of NPX., This research is part of the Spanish R + D + i contract TED2021-130905B-I00 funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR as well as the Red E3Tech Plus: Proyecto Redes de Investigaci´on de la AEI Network E3Tech PLUS (RED2022-134552-T) project. Funding for open access charge: CRUE Universitat Polit`ecnica de Val`encia. The Electron Microscopy Service of the UPV (Universitat Polit`ecnica de Val`encia) is gratefully acknowledged for help with FESEM and EDX characterization.