La imagen de la ciudad. Deriva en la sociedad capitalista

Este Trabajo de Fin de Máster trata sobre la ciudad a partir de la experiencia personal. Habiendo nacido y sido educada en Taiwan, a los 20 años empecé a viajar: primero Exeter, después Londres en 2012, Salamanca en 2016, Sevilla 2017 y Madrid donde resido actualmente. La confrontación de la experiencia urbana desde el punto de vista oriental y occidental son el origen de este trabajo. Mi visión parte de cómo me he ido involucrando en las distintas ciudades que me ha tocado vivir. Soy una recolectora de residuos de las ciudades, recorriéndolas y conociendo sus detalles he analizado lo que me han transmitido. Este trabajo es un modo de reflexión a través del arte sobre todo este proceso, impresiones, experiencias y comunicación entre mi persona y las ciudades y también sobre cómo los demás se comportan en el mismo espacio en el que vivo.This thesis which regards the city is based on my personal experience. Being born and raised in Taiwan, I have been travelling since I was 20 years old: first to Exeter, then to London in 2012, following by different cities in Spain, Salamanca in 2016, Sevilla in 2017 and and Madrid where I am currently living. The comparation of the urban experience rooted from the oriental and occidental perspectives is the source of this thesis. My vision comes from how I was implicating myself in those cities that I was once living in. I am a collector of the municipal wastes by wandering around and learning their details that they convey. This thesis is a way of thinking by means of art regarding all these process, impressions, experiences and the communication between me and the cities, as well as how all those residents who share the same space with me.Universidad de Sevilla. Máster en Arte: Idea y Producció

Polysaccharides isolated from Morinda officinalis How roots inhibits cyclophosphamide-induced leukopenia in mice

Purpose: To investigate the optimum parameters for extracting polysaccharides from Morinda officinalis How (MOP), and explore their inhibitory effects on leukopenia in mice.Methods: Orthogonal design was performed to investigate the optimum parameters for extracting MOP. A leukopenia mouse model was established by injection of cyclophosphamide (CTX) for three days. Thereafter, MOP (100, 200 and 400 mg/kg) was administered orally for 10 days. Furthermore, blood cells (leukocytes, neutrophil, lymphocyte and mononuclear cell) were analyzed, while serum IL-3 and IL- 6 were determined by ELISA. The thymus and spleen of the mice were separated and weighed to determine viscera indices.Results: Orthogonal design showed that the influence order of the four factors was extraction times (C) > ratio of water to raw material (RWM, D) > extraction time (B) > extraction temperature (A). The optimum extraction parameters for MOP were: extraction temperature (80 °C), extraction duration (2 h), no. of extractions (3), and ratio of water to raw material (30 mL/g). Furthermore, the results indicate that MOP (100, 200 and 400 mg/kg) elevated the levels of leukocyte (p < 0.01), neutrophil (p < 0.01), lymphocyte (p < 0.01) and mononuclear cell (p < 0.01) in leukopenia mice. Besides, MOP (100, 200 and 400 mg/kg) also increased thymus (p < 0.01) and spleen (p < 0.05) indices and serum levels of IL-3 (p < 0.05) and IL-6 (p < 0.01).Conclusion: Orthogonal design is a good strategy for optimizing extraction parameters of MOP. Furthermore, MOP stimulated synthesis of leukocytes in CTX-induced leukopenia in mice. Thus, MOP is a potential adjunct for the treatment of tumors/cancers.Keywords: Morinda officinalis, Polyscacharide, Orthogonal design, Leukopenia, Thymus index, Spleen inde

Enhancing Near-Field Sensing and Communications with Sparse Arrays: Potentials, Challenges, and Emerging Trends

As a promising technique, extremely large-scale (XL)-arrays offer potential solutions for overcoming the severe path loss in millimeter-wave (mmWave) and TeraHertz (THz) channels, crucial for enabling 6G. Nevertheless, XL-arrays introduce deviations in electromagnetic propagation compared to traditional arrays, fundamentally challenging the assumption with the planar-wave model. Instead, it ushers in the spherical-wave (SW) model to accurately represent the near-field propagation characteristics, significantly increasing signal processing complexity. Fortunately, the SW model shows remarkable benefits on sensing and communications (S\&C), e.g., improving communication multiplexing capability, spatial resolution, and degrees of freedom. In this context, this article first overviews hardware/algorithm challenges, fundamental potentials, promising applications of near-field S\&C enabled by XL-arrays. To overcome the limitations of existing XL-arrays with dense uniform array layouts and improve S\&C applications, we introduce sparse arrays (SAs). Exploring their potential, we propose XL-SAs for mmWave/THz systems using multi-subarray designs. Finally, several applications, challenges and resarch directions are identified

Task-driven Semantic-aware Green Cooperative Transmission Strategy for Vehicular Networks

Considering the infrastructure deployment cost and energy consumption, it is unrealistic to provide seamless coverage of the vehicular network. The presence of uncovered areas tends to hinder the prevalence of the in-vehicle services with large data volume. To this end, we propose a predictive cooperative multi-relay transmission strategy (PreCMTS) for the intermittently connected vehicular networks, fulfilling the 6G vision of semantic and green communications. Specifically, we introduce a task-driven knowledge graph (KG)-assisted semantic communication system, and model the KG into a weighted directed graph from the viewpoint of transmission. Meanwhile, we identify three predictable parameters about the individual vehicles to perform the following anticipatory analysis. Firstly, to facilitate semantic extraction, we derive the closed-form expression of the achievable throughput within the delay requirement. Then, for the extracted semantic representation, we formulate the mutually coupled problems of semantic unit assignment and predictive relay selection as a combinatorial optimization problem, to jointly optimize the energy efficiency and semantic transmission reliability. To find a favorable solution within limited time, we proposed a low-complexity algorithm based on Markov approximation. The promising performance gains of the PreCMTS are demonstrated by the simulations with realistic vehicle traces generated by the SUMO traffic simulator.Comment: Accepted by IEEE Transactions on Communication

Flexible Precoding for Multi-User Movable Antenna Communications

This letter rethinks traditional precoding in multi-user wireless communications with movable antennas (MAs). Utilizing MAs for optimal antenna positioning, we introduce a sparse optimization (SO)-based approach focusing on regularized zero-forcing (RZF). This framework targets the optimization of antenna positions and the precoding matrix to minimize inter-user interference and transmit power. We propose an off-grid regularized least squares-based orthogonal matching pursuit (RLS-OMP) method for this purpose. Moreover, we provide deeper insights into antenna position optimization using RLS-OMP, viewed from a subspace projection angle. Overall, our proposed flexible precoding scheme demonstrates a sum rate that exceeds more than twice that of fixed antenna positions

A Cross-project Defect Prediction Model Using Feature Transfer and Ensemble Learning

Cross-project defect prediction (CPDP) trains the prediction models with existing data from other projects (the source projects) and uses the trained model to predict the target projects. To solve two major problems in CPDP, namely, variability in data distribution and class imbalance, in this paper we raise a CPDP model combining feature transfer and ensemble learning, with two stages of feature transfer and the classification. The feature transfer method is based on Pearson correlation coefficient, which reduces the dimension of feature space and the difference of feature distribution between items. The class imbalance is solved by SMOTE and Voting on both algorithm and data levels. The experimental results on 20 source-target projects show that our method can yield significant improvement on CPDP

STAR-RIS-Assisted Privacy Protection in Semantic Communication System

Semantic communication (SemCom) has emerged as a promising architecture in the realm of intelligent communication paradigms. SemCom involves extracting and compressing the core information at the transmitter while enabling the receiver to interpret it based on established knowledge bases (KBs). This approach enhances communication efficiency greatly. However, the open nature of wireless transmission and the presence of homogeneous KBs among subscribers of identical data type pose a risk of privacy leakage in SemCom. To address this challenge, we propose to leverage the simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) to achieve privacy protection in a SemCom system. In this system, the STAR-RIS is utilized to enhance the signal transmission of the SemCom between a base station and a destination user, as well as to covert the signal to interference specifically for the eavesdropper (Eve). Simulation results demonstrate that our generated task-level disturbance outperforms other benchmarks in protecting SemCom privacy, as evidenced by the significantly lower task success rate achieved by Eve

Semantic Change Driven Generative Semantic Communication Framework

The burgeoning generative artificial intelligence technology offers novel insights into the development of semantic communication (SemCom) frameworks. These frameworks hold the potential to address the challenges associated with the black-box nature inherent in existing end-to-end training manner for the existing SemCom framework, as well as deterioration of the user experience caused by the inevitable error floor in deep learning-based semantic communication. In this paper, we focus on the widespread remote monitoring scenario, and propose a semantic change driven generative SemCom framework. Therein, the semantic encoder and semantic decoder can be optimized independently. Specifically, we develop a modular semantic encoder with value of information based semantic sampling function. In addition, we propose a conditional denoising diffusion probabilistic mode-assisted semantic decoder that relies on received semantic information from the source, namely, the semantic map, and the local static scene information to remotely regenerate scenes. Moreover, we demonstrate the effectiveness of the proposed semantic encoder and decoder as well as the considerable potential in reducing energy consumption through simulation. The code is available at https://github.com/wty2011jl/SCDGSC.gi

Energy-Efficient Cell-Free Network Assisted by Hybrid RISs

In this letter, we investigate a cell-free network aided by hybrid reconfigurable intelligent surfaces (RISs), which consists of a mixture of passive and active elements that are capable of amplifying and reflecting the incident signal. To maximize the energy efficiency (EE) of the system, we formulate a joint transmit beamforming and RIS coefficients optimization problem. To deal with the fractional objective function, Dinkelbach transform, Lagrangian dual reformulation, and quadratic transform are utilized, with a block coordinate descent (BCD) based algorithm proposed to decouple the variables. In addition, successive convex approximation (SCA) method is applied to iteratively to tackle the non-convexity of the sub-problems. Simulation results illustrate the effectiveness and convergence of the proposed algorithm through analyzing the EE and sum rate performance with varying parameter settings. The proposed hybrid RISs schemes can achieve 92% of the sum rate but 188% of EE of active RISs schemes. As compared with passive RISs, 11% gain in sum rate can be achieved with comparable EE

Assessing Nozzle Geometry, Spacing and Height Effect on Pesticide Spray Characteristics and Swath from Ground and Aerial Sprayers

Nozzle is the basic aperture that controls pesticide spray jet onto targeted substrates. It is moulded from stainless steel, brass, ceramic and plastics at different wear rates. The efficiency of pesticide application is dependent on chemical efficacy and nozzle type. Both flat fan and hollow cone nozzles are commonly used to enhance pesticide spray characteristics and deposition. The surface coverage and spray distribution are influenced by nozzle spacing and spraying height. Therefore, using a nozzle type, spacing and spraying height that give pesticide spray-overlap is of interest to researchers. This review therefore analyses the effect of nozzle geometry, nozzle spacing and spraying height regimes on pesticide spray droplets characteristics from mechanical boom sprayers. To improve on uniformity of pesticides spray coverage on plant surfaces, a unitary relative span is reported suitable for application, but there had not been clearly defined nozzle type, spacing and height regime for effective spraying. The review further proposes an optimum parameters combination with specific nozzle type, spacing and spraying height for efficient application of pesticides