Resultados totales (Incluyendo duplicados): 33854
Encontrada(s) 3386 página(s)
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200232
Dataset. 2023

CHARACTERIZATION OF WO3 NANOSTRUCTURES USED IN THE DEGRADATION OF METHYLPARABEN

  • García Antón, José|||0000-0002-0289-1324
  • Cifre Herrando, Mireia|||0000-0002-8800-3585
  • Roselló Márquez, Gemma
  • García García, Dionisio Miguel|||0000-0001-8951-4558
The data were use to study the degradation of Methylparaben using WO3 Nanostructures. WO3 nanostructures were synthesized with different complexing agents (0.05 M H2O2 and 0.1 M citric acid) and annealing conditions (400 _C, 500 _C and 600 _C) to obtain optimal WO3 nanostructures to use them as a photoanode in the photoelectrochemical (PEC) degradation of an endocrine disruptor chemical. X-ray photoelectron spectroscopy was performed to provide information of the electronic states of the nanostructures. The crystallinity of the samples was observed by a confocal Raman laser microscope and X-ray diffraction. Furthermore, photoelectrochemical measurements (photostability, photoelectrochemical impedance spectroscopy, Mott–Schottky and water-splitting test) were also performed using a solar simulator with AM 1.5 conditions at 100 mW_cm-2. Once the optimal nanostructure was obtained, the PEC degradation of methylparaben was carried out. It was followed by ultra-high-performance liquid chromatography and mass spectrometry, which allowed to obtain the concentration of the contaminant during degradation and the identification of degradation intermediates.

DOI: Dataset/10251/200232" target="_blank">http://hdl.handle.net/10251/200232, https://dx.doi.org/10.4995/Dataset/10251/200232
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200232
HANDLE: Dataset/10251/200232" target="_blank">http://hdl.handle.net/10251/200232, https://dx.doi.org/10.4995/Dataset/10251/200232
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200232
PMID: Dataset/10251/200232" target="_blank">http://hdl.handle.net/10251/200232, https://dx.doi.org/10.4995/Dataset/10251/200232
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200232
Ver en: Dataset/10251/200232" target="_blank">http://hdl.handle.net/10251/200232, https://dx.doi.org/10.4995/Dataset/10251/200232
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200232

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200255
Dataset. 2023

PREPARATION OF ELECTRODES BASED ON WO3 NANOSTRUCTURES FOR LI-ION BATTERIES

  • García Antón, José|||0000-0002-0289-1324
  • Roselló Márquez, Gemma
  • García García, Dionisio Miguel|||0000-0001-8951-4558
  • Cifre Herrando, Mireia|||0000-0002-8800-3585
  • Blasco Tamarit, María Encarnación|||0000-0001-7314-082X
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.

DOI: Dataset/10251/200255" target="_blank">http://hdl.handle.net/10251/200255, https://dx.doi.org/10.4995/Dataset/10251/200255
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200255
HANDLE: Dataset/10251/200255" target="_blank">http://hdl.handle.net/10251/200255, https://dx.doi.org/10.4995/Dataset/10251/200255
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200255
PMID: Dataset/10251/200255" target="_blank">http://hdl.handle.net/10251/200255, https://dx.doi.org/10.4995/Dataset/10251/200255
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200255
Ver en: Dataset/10251/200255" target="_blank">http://hdl.handle.net/10251/200255, https://dx.doi.org/10.4995/Dataset/10251/200255
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200255

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200260
Dataset. 2023

REAL-WORLD DATASETS FOR SUSTAINABLE PORTFOLIO SELECTION

  • García Bernabeu, Ana María|||0000-0003-3181-7745
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.

Proyecto: //
DOI: Dataset/10251/200260" target="_blank">http://hdl.handle.net/10251/200260, https://dx.doi.org/10.4995/Dataset/10251/200260
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200260
HANDLE: Dataset/10251/200260" target="_blank">http://hdl.handle.net/10251/200260, https://dx.doi.org/10.4995/Dataset/10251/200260
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200260
PMID: Dataset/10251/200260" target="_blank">http://hdl.handle.net/10251/200260, https://dx.doi.org/10.4995/Dataset/10251/200260
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200260
Ver en: Dataset/10251/200260" target="_blank">http://hdl.handle.net/10251/200260, https://dx.doi.org/10.4995/Dataset/10251/200260
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/200260

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/201071
Dataset. 2023

GEOREFERENCED DATASET OF ABANDONED CITRUS CROPS (COMUNITAT VALENCIANA, SPAIN)

  • Morell Monzó, Sergio|||0000-0001-8883-2618
  • Sebastiá Frasquet, María Teresa|||0000-0002-8042-5628
  • Estornell Cremades, Javier|||0000-0003-0854-5358
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

DOI: Dataset/10251/201071" target="_blank">http://hdl.handle.net/10251/201071, https://dx.doi.org/10.4995/Dataset/10251/201071
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/201071
HANDLE: Dataset/10251/201071" target="_blank">http://hdl.handle.net/10251/201071, https://dx.doi.org/10.4995/Dataset/10251/201071
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/201071
PMID: Dataset/10251/201071" target="_blank">http://hdl.handle.net/10251/201071, https://dx.doi.org/10.4995/Dataset/10251/201071
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/201071
Ver en: Dataset/10251/201071" target="_blank">http://hdl.handle.net/10251/201071, https://dx.doi.org/10.4995/Dataset/10251/201071
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/201071

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/201304
Dataset. 2024

THE NASA VIDEOS COLLECTION ON TWITCH

  • Orduña Malea, Enrique|||0000-0002-1989-8477
  • Lopezosa García, Carlos
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.

DOI: Dataset/10251/201304" target="_blank">http://hdl.handle.net/10251/201304, https://dx.doi.org/10.4995/Dataset/10251/201304
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/201304
HANDLE: Dataset/10251/201304" target="_blank">http://hdl.handle.net/10251/201304, https://dx.doi.org/10.4995/Dataset/10251/201304
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/201304
PMID: Dataset/10251/201304" target="_blank">http://hdl.handle.net/10251/201304, https://dx.doi.org/10.4995/Dataset/10251/201304
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/201304
Ver en: Dataset/10251/201304" target="_blank">http://hdl.handle.net/10251/201304, https://dx.doi.org/10.4995/Dataset/10251/201304
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/201304

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/201647
Dataset. 2024

KNOWLEDGE MANAGEMENT APPLIED TO ENTERPRISE AND SUPPLY CHAIN RESILIENCE. A TEACHING CASE

DATASET RELATED TO A TEACHING CASE ON KNOWLEDGE MANAGEMENT APPLIED TO ENTERPRISE AND SUPPLY CHAIN RESILIENCE

  • Arias-Vargas, Marco|||0000-0002-7586-4140
  • Sanchis, Raquel|||0000-0002-5495-3339
  • Poler, Raúl|||0000-0003-4475-6371
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).

DOI: Dataset/10251/201647" target="_blank">http://hdl.handle.net/10251/201647, https://dx.doi.org/10.4995/Dataset/10251/201647
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/201647
HANDLE: Dataset/10251/201647" target="_blank">http://hdl.handle.net/10251/201647, https://dx.doi.org/10.4995/Dataset/10251/201647
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/201647
PMID: Dataset/10251/201647" target="_blank">http://hdl.handle.net/10251/201647, https://dx.doi.org/10.4995/Dataset/10251/201647
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/201647
Ver en: Dataset/10251/201647" target="_blank">http://hdl.handle.net/10251/201647, https://dx.doi.org/10.4995/Dataset/10251/201647
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/201647

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202148
Dataset. 2023

BER-EVM-POWER-OVS-SCM (RAW DATA)

  • Pérez Pascual, Mª Asunción|||0000-0002-6925-6878
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.

DOI: Dataset/10251/202148" target="_blank">http://hdl.handle.net/10251/202148, https://dx.doi.org/10.4995/Dataset/10251/202148
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202148
HANDLE: Dataset/10251/202148" target="_blank">http://hdl.handle.net/10251/202148, https://dx.doi.org/10.4995/Dataset/10251/202148
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202148
PMID: Dataset/10251/202148" target="_blank">http://hdl.handle.net/10251/202148, https://dx.doi.org/10.4995/Dataset/10251/202148
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202148
Ver en: Dataset/10251/202148" target="_blank">http://hdl.handle.net/10251/202148, https://dx.doi.org/10.4995/Dataset/10251/202148
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202148

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202149
Dataset. 2020

OVS-SCM MODULATION (RAW DATA)

  • Pérez Pascual, Mª Asunción|||0000-0002-6925-6878
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.

DOI: Dataset/10251/202149" target="_blank">http://hdl.handle.net/10251/202149, https://dx.doi.org/10.4995/Dataset/10251/202149
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202149
HANDLE: Dataset/10251/202149" target="_blank">http://hdl.handle.net/10251/202149, https://dx.doi.org/10.4995/Dataset/10251/202149
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202149
PMID: Dataset/10251/202149" target="_blank">http://hdl.handle.net/10251/202149, https://dx.doi.org/10.4995/Dataset/10251/202149
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202149
Ver en: Dataset/10251/202149" target="_blank">http://hdl.handle.net/10251/202149, https://dx.doi.org/10.4995/Dataset/10251/202149
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202149

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202500
Dataset. 2024

IMAGE DATABASE FOR THE SCIENTIFIC PAPER: DEEP LEARNING ALGORITHM, BASED ON CONVOLUTIONAL NEURAL NETWORKS, FOR EQUIVALENT ELECTRICAL CIRCUIT RECOMMENDATION FOR ELECTROCHEMICAL IMPEDANCE SPECTROSCOPY

  • Pérez Herranz, Valentín|||0000-0002-4010-0888
  • Giner Sanz, Juan José|||0000-0003-0441-6102
  • Sáez Pardo, Fermín
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

DOI: Dataset/10251/202500" target="_blank">http://hdl.handle.net/10251/202500, https://dx.doi.org/10.4995/Dataset/10251/202500
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202500
HANDLE: Dataset/10251/202500" target="_blank">http://hdl.handle.net/10251/202500, https://dx.doi.org/10.4995/Dataset/10251/202500
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202500
PMID: Dataset/10251/202500" target="_blank">http://hdl.handle.net/10251/202500, https://dx.doi.org/10.4995/Dataset/10251/202500
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202500
Ver en: Dataset/10251/202500" target="_blank">http://hdl.handle.net/10251/202500, https://dx.doi.org/10.4995/Dataset/10251/202500
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202500

RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202369
Dataset. 2024

AL GUEFOAMS PROTECTED AGAINST CORROSION BY RGO

  • Rodrigo, Rubén
  • Molina, Javier|||0000-0003-3378-8271
  • Bonastre, José|||0000-0002-5068-6608
  • Maiorano, Lucila P
  • Molina, José M
  • Cases, Francisco|||0000-0001-8105-4489
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.

DOI: Dataset/10251/202369" target="_blank">http://hdl.handle.net/10251/202369, https://dx.doi.org/10.4995/Dataset/10251/202369
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202369
HANDLE: Dataset/10251/202369" target="_blank">http://hdl.handle.net/10251/202369, https://dx.doi.org/10.4995/Dataset/10251/202369
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202369
PMID: Dataset/10251/202369" target="_blank">http://hdl.handle.net/10251/202369, https://dx.doi.org/10.4995/Dataset/10251/202369
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202369
Ver en: Dataset/10251/202369" target="_blank">http://hdl.handle.net/10251/202369, https://dx.doi.org/10.4995/Dataset/10251/202369
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
oai:riunet.upv.es:10251/202369

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