科大讯飞翻译机在医疗领域的应用及其特点分析（西汉）

En consonancia con el Instituto Nacional de Estadística (INE) de España, desde 1988, el número de inmigrantes chinos en España ha aumentado significativamente, pasando de 12.306 a 223.591 hasta el 1 de enero de 2022.1 Además, la cantidad de turistas chinos que visitan a España ha incrementado, con 699.108 llegadas en 2019, siendo los principales destinos Cataluña, Madrid y Andalucía. 2 Aunque la pandemia de coronavirus había disminuido de cierta manera el número de inmigrantes y turistas, con la apertura de las políticas y el alivio de las restricciones de viaje, la cantidad sigue creciendo rápidamente. Es por esto que ha generado una gran mayor necesidad de traducción en el ámbito sanitario. No obstante, la traducción humana tradicional no puede satisfacer la demanda de los usuarios. Como líder de empresas de tecnología de traducción, iFLYTEK ha desarrollado una serie de traductores que cuenta con funciones de traducción e interpretación en tiempo real, reconocimiento de dialectos y acentos, traducción e interpretación sin conexión de internet, terminologías en campos específicos, conocimientos profesionales, etc. El objetivo de esta tesis consiste en analizar la aplicación del traductor iFLYTEK en el ámbito sanitario y explorar sus ventajas y limitaciones. Para realizarlo, se ha creado un corpus bilingüe concentrándose en la tuberculosis como ejemplo y se traduce el texto español al chino utilizando iFLYTEK. Además, se aplican dos métricas: BLUE (Bilingual Evaluation underestudy) y TAUS (Translation Automation User Association) para realizar la evaluación automática y le evaluación humana de este texto traducido. Esta metodología requiere una base teórica: 1) La definición de traducción especializada 2) Características del lenguaje médico español y chino 3) Rasgos y dificultades de traducción sanitaria en España y China 4) La tipología de traducción automática 5) Evaluación automática y evaluación humana En resumen, el análisis de la calidad de traducción muestra que el iFLYTEK tiene varios problemas en la traducción en el ámbito sanitario. Dada la capacidad limitada de la evaluación humana, este estudio toma como ejemplo el tema de la tuberculosis. Por lo tanto, aún queda mucho camino por recorrer para la investigación de la aplicación del traductor iFLYTEK en el ámbito sanitario根据西班牙国家统计局（NIE）数据显示，自 1998 年以来，截至 2022 年 1 月 1 日，居 住在西班牙的中国移民数量从 12036 人增加到 223591 人。2019 年，中国游客入境西班 牙次数高达 699108 次，其中主要目的地是加泰罗尼亚，马德里和安达卢西亚。尽管受 疫情影响，这两年游客人数有所下降，但随着各国政策的放宽和疫情的缓解，移民西班 牙的中国人以及前往西班牙旅游的人数仍在迅速增长。因此，在医疗领域存在着很大的 翻译需求。 然而，传统的人工翻译无法完全满足这种需求。作为翻译的龙头企业，科大讯飞开发的 翻译机具有实时翻译、方言翻译、口音识别、离线翻译，配有专业领域术语库及专业知 识等多种功能。本论文旨在探讨科大讯飞翻译机在西班牙语和中文之间医疗领域的应用， 以及其特点优劣。 为此，本文以结核病为例，创建了双语语料库， 然后应用科大讯飞对文本进行西班牙 语到中文的翻译。并使用 BLEU(双语评价研究)和 TAUS（翻译自动化用户协会）分别 对译文进行自动评价和人工评价，对比两种评价方式的特点，分析翻译文本的质量。应 用此研究方法需要足够的理论支撑： 1) 定义特定领域的翻译 2) 分析西班牙语和中文医学语言的特点 3) 总结两个医疗领域翻译的特点以及遇到的难点 4) 分析机器翻译系统的分类 5) 研究两种评价译文的方式 6) 介绍科大讯飞翻译机的特点 最后，通过文本翻译质量的分析，科大讯飞在医疗领域的翻译仍然存在许多问题。鉴于 人工评价的能力有限，本文对于医疗文本翻译的研究以结核病为例，研究范围不够广泛， 多样。因此，对于科大讯飞的翻译功能仍有待进一步研究。Máster Universitario en Comunicación Intercultural, Interpretación y Traducción en los Servicios Públicos. Especialidad en CHI-ESP (M196

The Application of OCTA in Assessment of Anti-VEGF Therapy for Idiopathic Choroidal Neovascularization

Purpose. To assess the morphology of idiopathic choroidal neovascularization (ICNV) by optical coherence tomography angiography (OCTA) and determine the therapeutic effects of intravitreal antivascular endothelial growth factor (anti-VEGF). Method. Patients with naive ICNV were assessed by spectral domain optical coherence tomography (SD-OCT) and OCTA in this observational study. The timing of observation was before treatment, 1 day after treatment with intravitreal anti-VEGF injection, and 1 month after the treatment. The central retina thickness (CRT) on SD-OCT, selected CNV area, and flow area on OCTA were measured. Results. A total of 17 eyes from 17 patients with ICNV were included in this study. OCTA showed visible irregular choroidal neovascularization with “tree-in-bud” form on outer retinal layer. After treatment, as well as in the 1-day follow-up, CNV decreased in size from the periphery, and the vessel density was reduced. As shown on OCTA, the selected CNV area and flow area were significantly reduced compared to pretreatment. The rate of CNV vessel area changes was higher on OCTA than the changes in CRT on SD-OCT at 1-day and 1-month follow-up. Conclusion. Intravitreal injection of anti-VEGF is effective for idiopathic choroidal neovascularization, and the treatment outcomes are observable after 1 day. OCTA provides a useful approach for monitoring and evaluating the treatment of intravitreal anti-VEGF for CNV

Stock Market Simulation

Simulation tools and information available on the internet were used to conduct a 5-week stock market simulation with four different trading strategies: swing, technical, position and day trading. Trading results were analyzed and compared to find out the differences of the trading methods and determine the most profitable one. This project was helpful for the team members to have a better knowledge of the stock market and gain valuable trading experiences to become more competent and more confident investors in the future

Agent Based Simulation of Group Emotions Evolution and Strategy Intervention in Extreme Events

Agent based simulation method has become a prominent approach in computational modeling and analysis of public emergency management in social science research. The group emotions evolution, information diffusion, and collective behavior selection make extreme incidents studies a complex system problem, which requires new methods for incidents management and strategy evaluation. This paper studies the group emotion evolution and intervention strategy effectiveness using agent based simulation method. By employing a computational experimentation methodology, we construct the group emotion evolution as a complex system and test the effects of three strategies. In addition, the events-chain model is proposed to model the accumulation influence of the temporal successive events. Each strategy is examined through three simulation experiments, including two make-up scenarios and a real case study. We show how various strategies could impact the group emotion evolution in terms of the complex emergence and emotion accumulation influence in extreme events. This paper also provides an effective method of how to use agent-based simulation for the study of complex collective behavior evolution problem in extreme incidents, emergency, and security study domains

Stand for Something or Fall for Everything: Predict Misinformation Spread with Stance-Aware Graph Neural Networks

Although pervasive spread of misinformation on social media platforms has become a pressing challenge, existing platform interventions have shown limited success in curbing its dissemination. In this study, we propose a stance-aware graph neural network (stance-aware GNN) that leverages users’ stances to proactively predict misinformation spread. As different user stances can form unique echo chambers, we customize four information passing paths in stance-aware GNN, while the trainable attention weights provide explainability by highlighting each structure\u27s importance. Evaluated on a real-world dataset, stance-aware GNN outperforms benchmarks by 32.65% and exceeds advanced GNNs without user stance by over 4.69%. Furthermore, the attention weights indicate that users’ opposition stances have a higher impact on their neighbors’ behaviors than supportive ones, which function as social correction to halt misinformation propagation. Overall, our study provides an effective predictive model for platforms to combat misinformation, and highlights the impact of user stances in the misinformation propagation

GLOBER: Coherent Non-autoregressive Video Generation via GLOBal Guided Video DecodER

Video generation necessitates both global coherence and local realism. This work presents a novel non-autoregressive method GLOBER, which first generates global features to obtain comprehensive global guidance and then synthesizes video frames based on the global features to generate coherent videos. Specifically, we propose a video auto-encoder, where a video encoder encodes videos into global features, and a video decoder, built on a diffusion model, decodes the global features and synthesizes video frames in a non-autoregressive manner. To achieve maximum flexibility, our video decoder perceives temporal information through normalized frame indexes, which enables it to synthesize arbitrary sub video clips with predetermined starting and ending frame indexes. Moreover, a novel adversarial loss is introduced to improve the global coherence and local realism between the synthesized video frames. Finally, we employ a diffusion-based video generator to fit the global features outputted by the video encoder for video generation. Extensive experimental results demonstrate the effectiveness and efficiency of our proposed method, and new state-of-the-art results have been achieved on multiple benchmarks

Only 5\% Attention Is All You Need: Efficient Long-range Document-level Neural Machine Translation

Document-level Neural Machine Translation (DocNMT) has been proven crucial for handling discourse phenomena by introducing document-level context information. One of the most important directions is to input the whole document directly to the standard Transformer model. In this case, efficiency becomes a critical concern due to the quadratic complexity of the attention module. Existing studies either focus on the encoder part, which cannot be deployed on sequence-to-sequence generation tasks, e.g., Machine Translation (MT), or suffer from a significant performance drop. In this work, we keep the translation performance while gaining 20\% speed up by introducing extra selection layer based on lightweight attention that selects a small portion of tokens to be attended. It takes advantage of the original attention to ensure performance and dimension reduction to accelerate inference. Experimental results show that our method could achieve up to 95\% sparsity (only 5\% tokens attended) approximately, and save 93\% computation cost on the attention module compared with the original Transformer, while maintaining the performance.Comment: Accepted by AACL 202

A Cross-Cultural Perspective on the Preference for Potential Effect: An Individual Participant Data (IPD) Meta-Analysis Approach

A recent paper [Tormala ZL, Jia JS, Norton MI (2012). The preference for potential. Journal of personality and social psychology, 103:567-583] demonstrated that persons often prefer potential rather than achievement when evaluating others, because information regarding potential evokes greater interest and processing, resulting in more favorable evaluations. This research aimed to expand on this finding by asking two questions: (a) Is the preference for potential effect replicable in other cultures? (b) Is there any other mechanism that accounts for this preference for potential? To answer these two questions, we replicated Tormala et al.'s study in multiple cities (17 studies with 1,128 participants) in China using an individual participant data (IPD) meta-analysis approach to test our hypothesis. Our results showed that the preference for potential effect found in the US is also robust in China. Moreover, we also found a pro-youth bias behind the preference for potential effect. To be specific, persons prefer a potential-oriented applicant rather than an achievement-oriented applicant, partially because they believe that the former is younger than the latter