从文化差异的角度分析国际留学生对跨文化教育的适应

本研究的基本信息是对比分析影响留学生适应跨文化教育的因素有哪些， 通过一系列具体的分析和论证的到结果。本文选取去西班牙留学的中国学生和来到中国留学的西班牙学生为主体研究对象，附带部分其他国籍的留学生，通过对比分析跨文化交流的背景，日常基本语言的比较，社会语言行为和文化模式，社会价值观，两国教育系统的比较，文化因素的兼容性和渗透性，以及自然环境因素，日常生活习惯和接受信息的方式来研究影响留学生适应跨文化教育的因素。并且以语言为主体分析存在的问题，对这些影响因素提出解决方案以供参考。所使用的研究方法主要是访谈法，得到的主要重要结论是不同文化的渗透性和兼容性对国际学生适应跨文化教育有着决定性的影响。 关键词：跨文化教育 文化适应 心理适应 社会文化 对策El mensaje básico de esta investigación es comparar y analizar qué factores afectan a la adaptación de los estudiantes internacionales a la educación intercultural, mediante una serie de análisis y argumentaciones específicas a los resultados. Los sujetos elegidos para este trabajo son principalmente estudiantes internacionales de ambos países y algunos estudiantes de otras nacionalidades. Así como compara y analiza el contexto de la comunicación intercultural, la comparación del lenguaje básico cotidiano, el comportamiento sociolingüístico y los patrones culturales, los valores sociales, la comparación de los sistemas educativos de los dos países, la compatibilidad y permeabilidad de los factores culturales, así como los factores naturales del entorno, los hábitos de la vida cotidiana y la forma de recibir información. Así como formas de recibir información para examinar los factores que influyen en la adaptación de los estudiantes internacionales a la educación intercultural. También analizamos los problemas con la lengua como tema principal y proponemos soluciones a estos factores de influencia de referencia. El método de investigación utilizado es principalmente el método de la entrevista y la principal conclusión importante obtenida es que la permeabilidad y la compatibilidad de las diferentes culturas influyen de manera decisiva en la adaptación de los estudiantes internacionales a la educación intercultural.Máster Universitario en Comunicación Intercultural, Interpretación y Traducción en los Servicios Públicos. Especialidad e

Reversible Transition Between Thermodynamically Stable Phases with Low Density of Oxygen Vacancies on SrTiO3_3(110) Surface

The surface reconstruction of SrTiO$_3$(110) is studied with scanning tunneling microscopy and density functional theory (DFT) calculations. The reversible phase transition between (4$\times$1) and (5$\times$1) is controlled by adjusting the surface metal concentration [Sr] or [Ti]. Resolving the atomic structures of the surface, DFT calculations verify that the phase stability changes upon the chemical potential of Sr or Ti. Particularly, the density of oxygen vacancies is low on the thermodynamically stabilized SrTiO$_3$(110) surface.Comment: Accepted by Physical Review Letter

Category-selective Attention Modulates Unconscious Processing: Evidence from ERP

Aims: Recently, using the fMRI method in a paradigm in which visible word cues were followed by masked faces at a completely unconscious level or masked tools at a partially conscious level, Tu, Qiu, Martens, & Zhang [31] showed that the top-down modulation effects were in opposite directions for the two conditions. Because five different pictures of masked faces/tools were displayed in a trial, the authors proposed that the modulation effects could further interact with the conscious component of the partial awareness processing (i.e., awareness of the global contour change). In the present event-related potential study, we employed a paradigm similar to that of Tu et al.’s [31] except that the masked stimulus was displayed only once to test the effect of category selective attention on unconscious processing of picture identity and to try to investigate the above hypothesis. Study Design: Two semantic category cues (“face” or “tool”) and two types of subliminal stimuli (face or tool images) were crossed to generate four conditions: a face cue followed by a masked face picture, a face cue followed by a masked tool picture, a tool cue followed by a masked face picture, and a tool cue followed by a masked tool picture. Place and Duration of Study: Department of psychology, Institute of education, China West Normal University, between September 2013 and April 2014. Methodology: The technique of event-related potentials (ERP) was used. Results: Processing of masked face and tool images both elicited the ERP components of C1, P1, N1, and P2. In addition, C1 component between 25 ms and 55 ms was smaller in the valid category cue-word condition (face cue-word followed by masked face image & tool cue-word followed by masked tool image) than in the invalid cue-words (face cue-word followed by masked tool image & tool cue-word followed by masked face image). The other three waves, P1, N1, and P2, were found to be unaffected by the top–down modulation Conclusion: Category-selective attention can modulate unconscious processes at an early stage of visual processing supporting the interaction hypothesis

Evolution of the Surface Structures on SrTiO3_3(110) Tuned by Ti or Sr Concentration

The surface structure of the SrTiO$_3$(110) polar surface is studied by scanning tunneling microscopy and X-ray photoelectron spectroscopy. Monophased reconstructions in (5$\times$1), (4$\times$1), (2$\times$8), and (6$\times$8) are obtained, respectively, and the evolution between these phases can be tuned reversibly by adjusting the Ar$^{+}$ sputtering dose or the amount of Sr/Ti evaporation. Upon annealing, the surface reaches the thermodynamic equilibrium that is determined by the surface metal concentration. The different electronic structures and absorption behaviors of the surface with different reconstructions are investigated.Comment: 10 pages, 14 figure

JointCL : a joint contrastive learning framework for zero-shot stance detection

Zero-shot stance detection (ZSSD) aims to detect the stance for an unseen target during the inference stage. In this paper, we propose a joint contrastive learning (JointCL) framework, which consists of stance contrastive learning and target-aware prototypical graph contrastive learning. Specifically, a stance contrastive learning strategy is employed to better generalize stance features for unseen targets. Further, we build a prototypical graph for each instance to learn the target-based representation, in which the prototypes are deployed as a bridge to share the graph structures between the known targets and the unseen ones. Then a novel target-aware prototypical graph contrastive learning strategy is devised to generalize the reasoning ability of target-based stance representations to the unseen targets. Extensive experiments on three benchmark datasets show that the proposed approach achieves state-ofthe- art performance in the ZSSD task

Critical roles of edge turbulent transport in the formation of high-field-side high-density front and density limit disruption in J-TEXT tokamak

This article presents an in-depth study of the sequence of events leading to density limit disruption in J-TEXT tokamak plasmas, with an emphasis on boudary turbulent transport and the high-field-side high-density (HFSHD) front. These phenomena were extensively investigated by using Langmuir probe and Polarimeter-interferometer diagnostics

Health Consequences Among COVID-19 Convalescent Patients 30 Months Post-Infection in China

The health consequences among COVID-19 convalescent patients 30 months post-infection were described and the potential risk factors were determined. In August 2022 we recruited 217 COVID-19 convalescent patients who had been diagnosed with COVID-19 in February 2020. These convalescent patients were residents of multiple districts in Wuhan, China. All convalescent patients completed a detailed questionnaire, laboratory testing, a 6-min walk test, a Borg dyspnea scale assessment, lung function testing, and had a chest CT. The potential risk factors for health consequences among COVID-19 convalescent patients 30 months post-infection were identified using a multivariate logistic regression model. The majority of convalescent patients were in good overall health and returned to work 30 months post-infection; however, 62.2% of the convalescent patients had long COVID symptoms. The most common symptoms were chest pain, fatigue, and dizziness or headaches. The convalescent patients with severe symptoms had a significantly higher proportion of depression disorder ( P = 0.044) and lower health-related quality of life ( P = 0.034) compared to the convalescent patients with mild symptoms. Compared to convalescent patients who were not vaccinated, convalescent patients who received three vaccines had significantly less fatigue, lower anxiety and depression scores, and had a better health-related quality of life (all P < 0.05). Older age was associated with a higher risk of long COVID (OR = 1.52, 95% CI = 1.16–2.02) and chest CT abnormalities (OR = 1.75, 95% CI = 1.33–2.36). Female gender was associated with a higher risk of anxiety (OR = 3.20, 95% CI = 1.24–9.16) and depression disorders (OR = 2.49, 95% CI = 1.11–5.92). Exercise was associated with a lower risk of anxiety (OR = 0.41, 95% CI = 0.18–0.93). Notably, vaccination protected convalescent patients from developing long COVID symptoms (OR = 0.18, 95% CI = 0.06–0.50), anxiety disorders (OR = 0.22, 95% CI = 0.07–0.71), and depression disorders (OR = 0.33, 95% CI = 0.12–0.92). The majority of COVID-19 convalescent patients were in good overall health 30 months post-infection and returned to work. More attention should be paid to convalescent patients who are older, female, physically inactive, and not vaccinated

Global implications of capital account liberalisation in China

This paper studies the determinants of foreign direct and portfolio investment flows and projects China’s balance of payments and international investment positions from 2016 to 2025. By conducting dynamic panel regressions on 24 sample countries for two periods 1997-2009 and 2003-2015, we provide empirical evidence for structural shift in global capital markets. Our projections for China’s international investment positions are based on the assumption that China’s capital account liberalisation would be largely achieved by the end of 2025. Based on the regression model, the projections show that China’s foreign direct investment assets will gradually catch up with foreign direct investment liabilities and exceed the latter by 2025. Meanwhile, China’s foreign portfolio investment assets and liabilities will accumulate at a similar pace with negative net foreign portfolio investment position over the next decade. Moreover, official foreign reserves of China will grow in value but decline as a share of GDP. Overall, China will continue to be a net creditor, but the current account as a share of GDP will decrease over time.Bachelor of Art

Simulation Analysis for Opening Performance of Medium Voltage Vacuum Circuit Breaker Based on ADAMS and Maxwell

The circuit breakers play a important role in control and protect the power systemand the vacuum circuit breaker has beenwidely used in the field of medium voltage with its excellent opening performance.Virtual prototyping technology is alsobecamemore and more popularin design and optimization of the vacuum circuit breaker. In this paper, the electromagnetic simulation software Ansoft Maxwell is used to analyze the electric repulsion of the circuit breaker in the case of open the rated short circuit breaking current. The 3D model that wasbuilt by CREOis imported into ADAMS. Thenconstraints, contact force, and the electric repulsion forcethat was analysezed in Ansoft Maxwell is added into the 3D model.Therefore, we can carry on the multi-body dynamics simulation to the 3D model. Then We can get the openingperformance of the vacuum circuit breakerin the condition of open circuit rated short circuit breaking current. The simulation results show that the circuit breaker can still meet the performance requirements in the condition of open circuit rated short circuit breaking current

Semisupervised Learning Based Disease-Symptom and Symptom-Therapeutic Substance Relation Extraction from Biomedical Literature

With the rapid growth of biomedical literature, a large amount of knowledge about diseases, symptoms, and therapeutic substances hidden in the literature can be used for drug discovery and disease therapy. In this paper, we present a method of constructing two models for extracting the relations between the disease and symptom and symptom and therapeutic substance from biomedical texts, respectively. The former judges whether a disease causes a certain physiological phenomenon while the latter determines whether a substance relieves or eliminates a certain physiological phenomenon. These two kinds of relations can be further utilized to extract the relations between disease and therapeutic substance. In our method, first two training sets for extracting the relations between the disease-symptom and symptom-therapeutic substance are manually annotated and then two semisupervised learning algorithms, that is, Co-Training and Tri-Training, are applied to utilize the unlabeled data to boost the relation extraction performance. Experimental results show that exploiting the unlabeled data with both Co-Training and Tri-Training algorithms can enhance the performance effectively