Ensamble sobre violencia simbólica. Producción mediante los Estudios Visuales

Contiene análisis sobre obras artísticas en un contexto específico y registros de la producción personal en video arteTesis de Maestría con análisis de un fenómeno social y la producción artística en videoarteEl Estudiante recibió la beca Conacyt para estudiar la Maestría inscrita en el PNPC-Conacyt-Méxici

Transverse Momentum Moments

We establish robust relations between Transverse Momentum Dependent distributions (TMDs) and collinear distributions. We define weighted integrals of TMDs that we call Transverse Momentum Moments (TMMs) and prove that TMMs are equal to collinear distributions evaluated in some minimal subtraction scheme. The conversion to the $\bar{MS}$-scheme can be done by a calculable factor, which we derive up to three loops for some cases. We discuss in detail the zeroth, the first, and the second TMMs and provide phenomenological results for them based on the current extractions of TMDs. The results of this paper open new avenues for theoretical and phenomenological investigation of the three-dimensional and collinear hadron structures.Comment: 24 pages, 6 figure

Early fever detection on COVID-19 infection using thermoelectric module generators

In 2020 the COVID-19 pandemic has suddenly stopped society and changed human interaction. In this work, a thermoelectric generator wearable device for early fever detection symptoms is presented as a possible solution to avoid higher propagation of this disease. To identify a possible fever symptom, numerical and parametric simulations are developed using a highquality-refined hexahedral mesh. At first, a 2-pair-leg thermoelectric module has undergone simulations to establish temperature conditions, open-circuit voltage, and power output generation; and secondly, these previous results are extrapolated for a larger thermoelectric module containing 28 pair-leg of N-P type material. The numerical study shows that a maximum value of electrical power of 60.70 mW was reached for 28-pair-leg N-P type thermocouples under a constant temperature difference of 20 K

An Energy Potential Estimation Methodology and Novel Prototype Design for Building-Integrated Wind Turbines

ROSEO-BIWT is a new Building-Integrated Wind Turbine (BIWT) intended for installation on the edge of buildings. It consists of a Savonius wind turbine and guiding vanes to accelerate the usual horizontal wind, together with the vertical upward air stream on the wall. This edge effect improves the performance of the wind turbine, and its architectural integration is also beneficial. The hypothetical performance and design configuration were studied for a university building in Eibar city using wind data from the ERA5 reanalysis (European Centre for Medium-Range Weather Forecasts’ reanalysis), an anemometer to calibrate the data, and the actual small-scale behavior in a wind tunnel. The data acquired by the anemometer show high correlations with the ERA5 data in the direction parallel to the valley, and the calibration is therefore valid. According to the results, a wind speed augmentation factor of three due to the edge effect and concentration vanes would lead to a increase in working hours at the rated power, resulting annually in more than 2000 h.The research leading to these results was carried out in the framework of the Programme Campus Bizia Lab EHU (Campus Living Lab) with a financial grant from the Office of Sustainability of the Vice-Chancellorship for Innovation, Social Outreach and Cultural Activities of the University of the Basque Country (UPV/EHU). This programme is supported by the Basque Government. We acknowledge also the availability given by the School of Engineering of Gipuzkoa-Eibar in the University of Basque Country, the EDP-Renewable awards in which we obtained the main award in September 2017, the Youth Enterprise Grant of UPV/EHU, and the project GIU17/02 of EHU/UPV. All computations and representations of this work were developed using the programming language

Model Predictive Control Design and Hardware in the Loop Validation for an Electric Vehicle Powertrain Based on Induction Motors

Electric vehicles (EV) have gained importance in recent years due to environmental pollution and the future scarcity of fossil resources. They have been the subject of study for many years, where much work has focused on batteries and the electric motor (EM). There are several types of motors in the market but the most widely used are induction motors, especially squirrel cage motors. Induction motors have also been extensively studied and, nowadays, there are several control methods used—for example, those based on vector control, such as field-oriented control (FOC) and direct torque control (DTC). Further, at a higher level, such as the speed loop, several types of controllers, such as proportional integral (PI) and model predictive control (MPC), have been tested. This paper shows a comparison between a Continuous Control Set MPC (CCS-MPC) and a conventional PI controller within the FOC method, both in simulation and hardware in the loop (HIL) tests, to control the speed of an induction motor for an EV powered by lithium-ion batteries. The comparison is composed of experiments based on the speed and quality of response and the controllers’ stability. The results are shown graphically and numerically analyzed using performance metrics such as the integral of the absolute error (IAE), where the MPC shows a 50% improvement over the PI in the speed tracking performance. The efficiency of the MPC in battery consumption is also demonstrated, with 5.07 min more driving time

Particle Swarm Optimization-Based Control for Maximum Power Point Tracking Implemented in a Real Time Photovoltaic System

Photovoltaic panels present an economical and environmentally friendly renewable energy solution, with advantages such as emission-free operation, low maintenance, and noiseless performance. However, their nonlinear power-voltage curves necessitate efficient operation at the Maximum Power Point (MPP). Various techniques, including Hill Climb algorithms, are commonly employed in the industry due to their simplicity and ease of implementation. Nonetheless, intelligent approaches like Particle Swarm Optimization (PSO) offer enhanced accuracy in tracking efficiency with reduced oscillations. The PSO algorithm, inspired by collective intelligence and animal swarm behavior, stands out as a promising solution due to its efficiency and ease of integration, relying only on standard current and voltage sensors commonly found in these systems, not like most intelligent techniques, which require additional modeling or sensoring, significantly increasing the cost of the installation. The primary contribution of this study lies in the implementation and validation of an advanced control system based on the PSO algorithm for real-time Maximum Power Point Tracking (MPPT) in a commercial photovoltaic system to assess its viability by testing it against the industry-standard controller, Perturbation and Observation (P&O), to highlight its advantages and limitations. Through rigorous experiments and comparisons with other methods, the proposed PSO-based control system’s performance and feasibility have been thoroughly evaluated. A sensitivity analysis of the algorithm’s search dynamics parameters has been conducted to identify the most effective combination for optimal real-time tracking. Notably, experimental comparisons with the P&O algorithm have revealed the PSO algorithm’s remarkable ability to significantly reduce settling time up to threefold under similar conditions, resulting in a substantial decrease in energy losses during transient states from 31.96% with P&O to 9.72% with PSO

An EM/MCMC Markov-witching GARCH behavioral algorithm for random-length lumber futures trading

This paper tests using two-regime Markov-switching models with asymmetric, time-varying exponential generalized autoregressive conditional heteroskedasticity (MS-EGARCH) variances in random-length lumber futures trading. By assuming a two-regime context (a low s=1 and high s=2 volatility), a trading algorithm was simulated with the following trading rule: invest in lumber futures if the probability of being in the high-volatility regime s=2 is lower or equal to 50%, or invest in the 3-month U.S. Treasury bills (TBills) otherwise. The rationale tested in this paper was that using a two-regime Markov-switching (MS) algorithm leads to an overperformance against a buy-and-hold strategy in lumber futures. To extend the current literature in MS trading algorithms, two location parameter scenarios were simulated. The first uses an unconditional mean or expected value (no factors), and the second incorporates market and behavioral factors. With weekly simulations form 2 January 1994 to 28 July 2023, the results suggest that using MS-EGARCH models in a no-factors scenario is appropriate for active lumber futures trading with an accumulated return of 158.33%. Also, the results suggest that it is not useful to add market and behavioral factors in the MS-GARCH estimation because it leads to a lower performance.Junta de Extremadura | Ref. GR2116

Chemotactic TEG3 Cells' Guiding Platforms Based on PLA Fibers Functionalized With the SDF-1 alpha/CXCL12 Chemokine for Neural Regeneration Therapy

Following spinal cord injury, olfactory ensheathing cell (OEC) transplantation is a promising therapeutic approach in promoting functional improvement. Some studies report that the migratory properties of OECs are compromised by inhibitory molecules and potentiated by chemical concentration differences. Here we compare the attachment, morphology, and directionality of an OEC-derived cell line, TEG3 cells, seeded on functionalized nanoscale meshes of Poly(l/dl-lactic acid; PLA) nanofibers. The size of the nanofibers has a strong effect on TEG3 cell adhesion and migration, with the PLA nanofibers having a 950 nm diameter being the ones that show the best results. TEG3 cells are capable of adopting a bipolar morphology on 950 nm fiber surfaces, as well as a highly dynamic behavior in migratory terms. Finally, we observe that functionalized nanofibers, with a chemical concentration increment of SDF-1α/CXCL12, strongly enhance the migratory characteristics of TEG3 cells over inhibitory substrates

Calibration of Reanalysis Data against Wind Measurements for Energy Production Estimation of Building Integrated Savonius-Type Wind Turbine

In this work, a cost-effective wind resource method specifically developed for the ROSEO-BIWT (Building Integrated Wind Turbine) and other Building Integrated Wind Turbines is presented. It predicts the wind speed and direction at the roof of an previously selected building for the past 10 years using reanalysis data and wind measurements taken over a year. To do so, the reanalysis wind speed data is calibrated against the measurements using different kinds of quantile mapping, and the wind direction is predicted using random forest. A mock-up of a building and a BIWT were used in a wind tunnel to perform a small-scale experiment presented here. It showed that energy production is possible and even enhanced over a wide range of attack angles. The energy production estimations made with the best performing kind of calibration achieved an overall relative error of 6.77% across different scenarios.This research was funded by the University of the Basque Country (UPV/EHU) GIU 17/002, and the Basque Autonomous Government’s BEAZ-SPRI grant for the creation of innovative enterprises (ROSEO EOLICA URBANA)

Using Markov-Switching models in US stocks optimal portfolio selection in a Black–Litterman context (Part 1)

In this study, we tested the benefit of using Markov-Switching (M-S) models to forecast the views of the 26 most traded stocks in the US in a Black–Litterman (B–L) optimal selection context. With weekly historical data of these stocks from 1 January 1980, we estimated and simulated (from 7 January 2000, to 7 February 2022) three portfolios that used M-S views in each stock and blended them with the market equilibrium views in a B–L context. Our position was that the B–L optimal portfolios could generate alpha (extra return) against a buy-and-hold and an actively managed portfolio with sample portfolio parameters (à la Markowitz, SampP). Our results suggest that the outperformance of the B–L managed portfolios holds only in the short term. In the long-term, the performance of the B–L portfolios, the SampP, and the market portfolio are statistically equal in terms of returns or their mean–variance efficiency in an ex-ante or ex-post analysis.Junta de Extremadur