BUSCADOR RECOLECTA

The numerical information in these datasets consists of two files. The first file (Dataset_SRI.xlsx) contains the asset data of monthly returns and ESG risk scores for three fund managers from January 2011 to December 2019. The second file (Pareto_Fronts.xlsx) contains the mean-variance-ESG Pareto fronts and the Pareto sets of non-dominated solutions for each manager obtained using the ev-MOGA algorithm. To get these Pareto fronts, we have considered an in-sample period of 72 monthly returns over six years from January 2011 to December 2016. To implement the ev-MOGA algorithm, we use an initial population of 50000 individuals and an auxiliary population of 500. The number of boxes defining the space of each function is 100.

This dataset contains georeferenced agricultural citrus parcels with information on crop status (non-productive, productive or abandoned) for the years 2019, 2020 and 2021 in GeoJSON format. The dataset is divided into 7 subsets (OLV_19, LSF_20, LSF_21, PV_21, TV_21, BP_21, and NL_21) in different locations of the Comunitat Valenciana (Spain). However, most of the data are located in the region of La Safor. Each of these subsets has its own characteristics in terms of sampling/classification method, date of acquisition and number of parcels. In total there are 1676 agricultural parcels labeled. The boundaries of the parcels are defined by the Geographic Information System of Agricultural Parcels (SIGPAC) database, which corresponds to the cadastral limits (“parcela” in SIGPAC nomenclature). Each parcel may contain one or more subplots ("recinto" in SIGPAC nomenclature) but with only one crop status. Data are derived from: Morell Monzó, S. (2023). “Desarrollo de procedimientos para la detección del abandono de cultivos de cítricos utilizando técnicas de teledetección” [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/193058

This dataset includes the raw data used to conduct a Twitch case study. The dataset includes the metrics collected from Twitch API to characterize a specific channel (NASA), the bibliographic data collected from bibliographic databases to systematically review the literature about Twitch, supplementary material, and the scripts used to collect data from Twitch API.

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).

This dataset contains the raw data of the measurements presented in the paper "Hardware Architecture of a QAM Receiver for Short-Range Optical Communications" (https://doi.org/10.1109/JLT.2022.3217357). Data presents the BER and EVM measurements made by changing the optical power transmitted for the proposed modulator.

This dataset contains the raw data of the measurements presented in the paper: "A Computational Efficient Nyquist Shaping Approach for Short-Reach Optical Communications" (https://doi.org/10.1109/JLT.2019.2961506). - Medidas_BER_EVM.xls: contains BER and EVM measurements made for different types of modulations for both the HC-SCM modulator and the OVS-SCM, varying the following parameters: oversampling factor, transmitter filter span, rolloff factor, receiver filter span, receiver equalizer order, pre-emphasis filter (in transmission) - Medidas_Potencia.xls: contains BER and EVM values varying the received power for HC-SCM and OVS-SCM modulations; for all QAM modulations under study.

The present dataset is the database and image database used to train and test the Convolutional Neural Network models of the scientific paper: Deep Learning algorithm, based on convolutional neural networks, for electrical equivalent electrical circuit recommendation for Electrochemical Impedance Spectroscopy

To enhance their corrosion protection, Guefoams were coated with RGO using both potentiostatic and potentiodynamic methods. The potentiodynamic method produced the thickest RGO coating and the lowest Cl, O, and Al content, as observed using FESEM and EDX. The Guefoams were exposed to a 3.5% NaCl solution and steam. The polarization resistance was examined, electro-chemical impedance spectroscopy was performed, and polarization curves were constructed to monitor the corrosion process. After 28 days, the Al concentrations in the solutions were meas-ured, and were found to be 145 mg/L (bare Guefoam), 70 mg/L (RGO-coated, potentiostatic), and 35 mg/L (RGO-coated, potentiodynamic). The potentiodynamic RGO coating also showed the best corrosion protection values., Thanks to the projects PDC2021-121617-C21 and PDC2021-121617-C22, funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR. and Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital (Generalitat Valenciana) (GVA-COVID19/2021/097).The Electron Microscopy Service of the UPV (Universitat Politècnica de València) is gratefully acknowledged for their help with the FESEM and EDX characterization.

[EN] This study examines the degradation of atrazine (ATZ) with Pt-modified textile electrodes using an electrochemical method that is comparatively studied in two electrochemical cell configurations: cells with separated anodic and cathodic compartments (divided configuration); and without any separation (undivided configuration). The influence of the presence of chloride ions was studied. The best results were obtained when an undivided cell was used. The morphology and composition of the dispersed Pt coatings were analyzed using field emission scanning electron microscopy (FESEM) and Energy Dispersive X-Ray Analysis. The FESEM analyses confirmed that the textile surface was effectively modified by the electrocatalytic material. High performance liquid chromatography, gas chromatography mass spectrometry, and spectroscopic methods were used to follow the evolution of major oxidation products. Total organic carbon, chemical oxygen demand, and total nitrogen were used to evaluate the degradation efficiency of treated aqueous solutions. The experimental results obtained indicate that the efficiency of the electrochemical treatment was high with a low energy consumption when using electrodes based on textile materials, such as anodes or as cathodes (in particular, in electrolysis without compartment separation). All these can be produced at very competitive prices., Chemviron Carbon who kindly donated the FlexzorbTM FM10 activated carbon fabrics and Funding for open access charge, CRUE-Universitat Politècnica de València, are acknowledged.

[EN] In this study, flexible textile supercapacitors were obtained on jute fabrics. Insulating jute fibers were converted into electrically conducting using an optimized reduced graphene oxide (rGO) deposition method. Supercapacitors were made of jute fabric and polypyrrole (PPy) as conducting polymer. rGO improved the electrical behavior of PPy-jute supercapacitors obtained by chemical polymerization. These chemical PPy-jute supercapacitors presented a low surface resistivity (6 Ω/sq) suitable for subsequent electrochemical polymerization. The best results were obtained for rGO-PPy-jute supercapacitors synthesized by electrochemical polymerization, with capacitance values of 5127 mF cm-2 (117 F g-1) in a 3-electrode system; and 1770 mF cm-2, 39.9 F g-1, 250 μW h cm-2 and 1100 μW cm-2 in a 2-electrode system. It is essential to highlight that the jute supercapacitors obtained are eco-friendly, low cost, flexible and with very competitive energy-storage values compared to recent investigations., This research is part of the Spanish R + D + i contract PDC2021-121617-C22 funded by MCIN/AEI/10.13039/501100011033 and by the “European Union NextGenerationEU/PRTR” as well as the Red E3Tech Plus: Proyecto Redes de Investigación de la AEI Network E3Tech PLUS (RED2022-134552-T) project. Funding for open access charge: CRUE-Universitat Politècnica de València. Electron Microscopy Service of Universitat Politècnica de València is gratefully acknowledged for help with FESEM microscope.