97828 research outputs found
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Comparación de los edificios de principios del siglo XX en Castellón de la Plana y Harbin, y su influencia del Barroco
No full textDespite their geographical distance and cultural differences, Baroque-influenced architecture and early 20th-century European-style buildings are represented in the cities of Castellón de la Plana (Spain) and Harbin (China). Some of these buildings share striking similarities. The study of the factors that have influenced Baroque-style architecture in China and in the province of Castellón, Spain —including historical, geographical, cultural, religious, and social factors— has helped clarify and discern the influence of Baroque style on the 20th-century architecture in Harbin and Castellón de la Plana. Additionally, the architectural styles that emerged in both cities at the beginning of the last century, often referred to as “Neo” (new), have also been studied.A pesar de su distancia geográfica y sus diferencias culturales, la arquitectura de influencia barroca y los edificios de estilo europeo de principios siglo xx están representados en las ciudades de Castellón de la Plana (España) y Harbin (China). Algunos de estos edificios tienen sorprendentes similitudes entre sí. El estudio de los factores que han influido en la arquitectura de estilo Barroco en, China y en la provincia de Castellón, España, incluyendo factores históricos, geográficos, culturales, religiosos y sociales ha ayudado a esclarecer y discernir la influencia del estilo barroco en la arquitectura del siglo xxestudiada en las ciudades de Harbin y Castellón de la Plana. Además, se han estudiado los estilos arquitectónicos de ambas ciudades surgidos a principios del siglo pasado, muchas veces llamados “Neo” (nuevo)
Tin-based halide perovskite nanocrystals: challenges, opportunities, and future directions
No full textTin halide perovskite nanocrystals (THP-NCs) provide a pathway to defy the limitations of lead-based equivalents through their lower toxicity and direct bandgaps suitable for near-infrared (NIR) emissions. Thus far, most studies have been limited to stabilizing the material under environmental conditions. This problem can be attributed to the fast oxidation of Sn2+ to Sn4+, creating high defect density, particularly in tin vacancies, which act as nonradiative recombination centers, implying a lower photoluminescence quantum yield (PLQY) of around 1%. However, to fully uncover the potential of this material system, explorations of more complex synthesis and their properties, both as single materials and in combination with others in optoelectronic systems, will be essential. The THP-NCs were synthesized using different methodologies, such as hot injection, ligand-assisted reprecipitation, and chemical vapor deposition. These have permitted the adjustment of precursor chemistry, ligand engineering, and doping to reduce this limitation partially. Approaches, like appropriate conditions such as Sn-rich reactions and passivation of surface defects, have shown a potential to enhance stability and optical properties. In this Perspective, we summarize state-of-the-art approaches to synthetize the THPNCs and highlight existing knowledge gaps and opportunities in their synthesis and characterization. We also propose a roadmap to accelerate the discovery of more stable materials with environmental robustness and predictable properties via the synergistic combination of experimental and computational efforts to achieve defect-tolerant THP-NCs with improved PLQY. Finally, we identify research opportunities and open questions in developing of next-generation Sn-based materials, optoelectronic devices, innovative systems that can bridge the gap between synthesizing and implementing these materials in real-world engineering applications
Trastorno del Espectro Autista. Conocimientos esenciales para educación, psicología y psicopedagogía
No full textExploring Avatar Utilization in Workplace and Educational Environments: A Study on User Acceptance, Preferences, and Technostress
No full textWith the rise of virtual avatars in professional, educational, and recreational settings, this study investigates how different avatar types—varying in realism, gender, and identity—affect user perceptions of embodiment, acceptability, technostress, privacy, and preferences. Two studies were conducted with 42 participants in Study 1 and 40 in Study 2, including professionals and students with varying VR experiences. In Study 1, participants used pre-assigned avatars they could control during interactions. In Study 2, an interviewer used different avatars to interact with participants and assess their impact. Questionnaires and correlation analyses measured embodiment, technostress, privacy, and preference variations across contexts. Results showed that hyper-realistic avatars resembling the user enhanced perceived embodiment and credibility in professional and educational settings, while non-realistic avatars were preferred in recreational contexts, particularly when interacting with strangers. Technostress was generally low, though younger users were more sensitive to avatar appearance, and privacy concerns increased when avatars were controlled by others. Gender differences emerged, with women expressing more concern about appearance and men preferring same-gender avatars in professional environments. These findings highlight the need for VR platform designers to balance realism with user comfort and address privacy concerns to encourage broader adoption in professional and educational applications
Multimodal Deep Learning Model for Cylindrical Grasp Prediction Using Surface Electromyography and Contextual Data During Reaching
No full textGrasping objects, from simple tasks to complex fine motor skills, is a key component of our daily activities. Our approach to facilitate the development of advanced prosthetics, robotic hands and human–machine interaction systems consists of collecting and combining surface electromyography (EMG) signals and contextual data of individuals performing manipulation tasks. In this context, the identification of patterns and prediction of hand grasp types is crucial, with cylindrical grasp being one of the most common and functional. Traditional approaches to grasp prediction often rely on unimodal data sources, limiting their ability to capture the complexity of real-world scenarios. In this work, grasp prediction models that integrate both EMG signals and contextual (task- and product-related) information have been explored to improve the prediction of cylindrical grasps during reaching movements. Three model architectures are presented: an EMG processing model based on convolutions that analyzes forearm surface EMG data, a fully connected model for processing contextual information, and a hybrid architecture combining both inputs resulting in a multimodal model. The results show that context has great predictive power. Variables such as object size and weight (product-related) were found to have a greater impact on model performance than task height (task-related). Combining EMG and product context yielded better results than using each data mode separately, confirming the importance of product context in improving EMG-based models of grasping.This research was funded by the Valencian Graduate School and Research Network of Artificial Intelligence (ValgrAI) and the Generalitat Valenciana. It was partially developed during collaboration grant from the Ministry of Education grant number 23CO1/006588 and, at present, by a FPU fellowship from the spanish Ministry of Science, Innovation and Universities, grant number FPU23/03540
Learning Interactional Metadiscourse in an EFL Educational Context: Insights from Case Stories
No full textWritten modes of communication have gained prominence in the last few decades, fostered by the development of technology-mediated communication, such as e-mail or chat. Even within diverse communicative scenarios, writers must appropriately employ interactional metadiscourse markers to help readers understand their intentions regarding the message being conveyed, and learning to use metadiscourse markers appropriately becomes crucial. This study explores individual trajectories of four case learners (low and high generators of interactional metadiscourse). Each participant wrote their opinion about school issues in three e-mails addressed to the school principal over one academic year. Considering that metadiscourse has been identified as a resource used by writers to persuade readers (Hyland, 2005, 2017), pragmatic competence was measured as the ability to produce interactional
metadiscourse (e.g., in my opinion). The results illustrate the complexity of the process of learning interactional metadiscourse. The study showed variation and fluctuations at the individual level, which were related to aspects such as learners’ affective domain and attitude toward content learned in the classroom, their overall academic performance at school, and their social integration with their classmates. The paper discusses pedagogical implications related to the need for teachers to consider the dimensions that learners bring with them into the classroom (e.g., emotions, socialization with classmates and overall academic achievement), the importance of raising learners and teachers’ awareness of metadiscourse, and the suitability of using technology-mediated tasks to teach pragmatics in a real context
Translation students’ attitudes towards their native language (L1): an understudied area
No full textThe impact of attitudes on the learning process and on the academic results achieved by students has been the object of numerous studies, e.g. Caroll (1964), Ellis (1994), Sölpük (2017), and Yusup et al. (2023), which have shown a connection between attitudes and learning. Similarly, the impact of students’ attitudes toward learning a foreign language (mainly English) has been explored from a wide range of perspectives (Lennartsson (2008), Getie and Popescu (2020), Chen et al. (2022)). However, there are no empirical studies of students’ attitudes towards their L1 in the context of translation degree programs. Students’ approach towards being taught their ‘own’ language is likely to be considerably different to their attitude towards learning a foreign language. Therefore, this study aims to explore translation and interpreting students’ attitudes towards L1 modules, in order to evaluate whether they are aware of its important role in their training as translators and their future careers, and their predisposition, interest and engagement in these modules. The data and analysis of this investigation shed light on students’ approach to L1 modules, which, in turn, provides a solid basis for a future redesign of these modules, geared towards students' specific academic needs, fostering more efficient learning
Exploring language-related episodes (LREs) in English-medium instruction (EMI) from a translanguaging and multimodal perspective
No full textWith the expansion of English-medium Instruction (EMI) programmes in European universities, studies have begun to point at the linguistic challenges faced by lecturers and students and suggest the need to increase the focus on language in English-taught content lectures. Language-related episodes (LREs), intended as brief transitory shifts of the topic of the discourse from content to language, could be a way of focusing on language within content-based activities. The present study aims to identify the occurrence of LREs in engineering lectures at a Spanish multilingual university and explore their construction from a translanguaging and multimodal perspective. For this purpose, a series of videotaped and verbatim transcribed lectures were analysed following previous frameworks for Multimodal Discourse Analysis (MDA). Results indicate that LREs do occur, with a highly variant frequency rate across lectures. Furthermore, multiple semiotic resources and translanguaging practices are used and play a major contribution to the meaning-making process of the LREs. The outcome of this study calls for a multimodal reconceptualization of LREs and shows instances of good practices that can be potentially included in professional training programmes to develop EMI lecturer awareness
Ethical guidelines for journalistic use of GenAI. The main trends in the international debate and progress in self-regulation in Spain
No full textThe emergence of generative AI (GenAI) has led to a far-reaching transformation of the entire journalistic working process, from the business model to the production, distribution and consumption of content. Beyond the expectations of greater productivity and efficiency it has generated, its use also poses important individual, professional and democratic ethical risks. These include attacks on privacy, a decline in journalistic quality and an increase in misinformation. To deal with this situation, academics and the journalistic sector have been publishing different professional guidelines and codes in an attempt to guide the ethical use of this technology. Based on the systematic review of three sets of academic guidelines and 18 important professional publications, and including data from more than 60 countries, this study establishes a double objective: to identify the main trends determining the international ethical debate; and to examine the degree of correspondence between these trends and the first self-regulation initiatives launched by the Spanish media. The results show the construction of a professional consensus on clear ethical standards: principally transparency, human supervision, verification, and respect for classic journalistic values (truth, loyalty to the public, and checking information). Taking a similar conceptual basis, the Spanish media’s commitment to more operational ethical self-regulation codes –with express recommendations, for example, covering the traceability of sources, the differentiation of synthetic content, and limitations on the use of GenAI– is also clear.La irrupción de la IA generativa (GenAI) ha provocado una profunda transformación de todo el proceso de trabajo periodístico, desde el modelo de negocio hasta la producción, distribución y consumo de contenidos. Más allá de las expectativas generadas de mayor productividad y eficiencia, su utilización también plantea importantes riesgos éticos (individuales, profesionales y democráticos); entre otros, ataques a la privacidad, descenso de la calidad periodística o aumento de la desinformación. Para afrontar esta situación, desde la academia y el sector periodístico se han venido publicando diferentes guías y códigos profesionales tratando de orientar un uso ético de esta tecnología. A partir de la revisión sistemática de 3 guías académicas y 18 publicaciones profesionales de referencia, que incluyen datos de más de 60 países, el presente estudio plantea un doble objetivo: identificar las principales tendencias que determinan el debate ético internacional; y examinar el grado de correspondencia entre estas tendencias y las primeras iniciativas de autorregulación puestas en marcha desde los medios españoles. Los resultados muestran la construcción de un consenso profesional sobre unos estándares éticos claros, principalmente la transparencia, la supervisión humana, la verificación y el respeto a valores periodísticos clásicos (verdad, lealtad ciudadana y verificación). Y, por otra parte, a partir de una base conceptual similar, también se evidencia la apuesta de los medios españoles por códigos de autorregulación ética de carácter más operativo, con recomendaciones expresas, por ejemplo hacia la trazabilidad de fuentes, la diferenciación de contenidos sintéticos y limitaciones al uso de la GenAI
Energy consumption modelling in IoT-surveyed peacekeeping missions
No full textTreball de Final de Màster Universitari Erasmus Mundus en Tecnologia Geoespacial (Pla de 2022). Codi: SJL042. Curs acadèmic 2024-2025The Internet of Things (IoT) framework enables the monitoring of power consumption in electrical devices. Different Machine Learning (ML) techniques can be leveraged in this context to perform energy usage prediction. This work presents three main temporal and spatial methods —Long Short-TermMemory (LSTM), Autoregressive IntegratedMoving Average (ARIMA), and Besag-York-Mollié (BYM)— to build forecast models for electricity consumption in IoT-surveyed peacekeeping mission camps.
The adoption of Deep Learning (DL) to perform forecast tasks has recently dominated the literature in the IoT context. We built the proposed models with a baseline LSTM approach. However, further insights were extracted with other classical methods coming from Statistics. In particular, this work uses the Gaussian adaptation of the BYM model to estimate residuals. With this technique, we aim to enhance accuracy and interpretability. Moreover, we studied the role of neighbourhood features among sensors in increasing the models’ effectiveness and stability.
One of the main challenges in this setting is dealing with noisy readings coming from local network issues or user manipulation. This project presents different data transformations to improve data quality, clean incoming outliers, and tailor it for prediction