China Europe International Business School

China Europe International Business School

China Europe International Business School
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    40292 research outputs found

    Long Term Effects and Maintenance of Exercise Oncology Interventions

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    The benefits of exercise for individuals diagnosed with cancer are well-documented, particularly in areas such as physical function, fatigue reduction, and quality of life. However, most studies primarily evaluate outcomes during or immediately following these interventions, with limited research focusing on their long-term effects. This gap in the literature makes it unclear whether the benefits achieved through structured exercise programs are sustained beyond the intervention period or if these improvements decline over time. The current systematic review aims to synthesize evidence on the long-term effects of exercise oncology interventions, particularly examining the extent to which improvements in lean mass, strength, physical function, fatigue, and quality of life are maintained post-intervention. By investigating this question, we hope to identify any potential declines in outcomes, and provide recommendations for structuring exercise oncology programs that support the maintenance of benefits over time. This project is registered and will be published on the Open Science Framework, ensuring transparency in our methodology and enabling future research to build on these findings. The current systematic review aims to synthesize evidence on the long-term effects of exercise oncology interventions, particularly examining the extent to which improvements in physical function, fatigue, quality of life, and overall health are maintained post-intervention. By investigating this question, we hope to identify factors associated with long-term adherence to physical activity, highlight any potential declines in health outcomes, and provide recommendations for structuring exercise oncology programs that support the maintenance of benefits over time. This project is registered and will be published on the Open Science Framework, ensuring transparency in our methodology and enabling future research to build on these findings

    Interactions Between Faces and Visual Context in Emotion Perception: A Meta-Analysis

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    Long-standing theories argue that we primarily perceive others’ emotions through facial expressions. However, compelling evidence shows other visual context, such as body posture or scenes, influences emotions perceived from faces and vice versa. We used meta-analysis to synthesise and quantify these effects for the first time, testing if faces have primacy over context. Both context and faces were found to have large effects on each other in emotion perception. Effects were larger for emotionally incongruent than congruent pairings and were moderated by how clearly stimuli signalled the target emotion. Once these factors were accounted for, faces were no more influential in emotion perception than other types of visual context. Future research should account for emotional congruency and signal clarity

    Scale2fit: Disentangling the determinants of vowels' spectral properties using mixed effects models

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    This paper introduces scale2fit, a framework for evaluating multiple factors affecting vowels’ acoustic properties jointly, which proves useful for vowel normalization and avoiding over-normalization. The acoustic properties of vowels stem from a combination of multiple factors including the intended vowel quality, vocal tract length, coarticulation, and speech rate. However, most current vowel normalization approaches do not distinguish among the different determinants. Scale2fit uses mixed effects models to jointly evaluate multiple factors, avoiding their conflation in vowel normalization. Study 1 shows that the new method excels in a series of comparisons with other normalization methods. Study 2 shows that the proposed framework excels at preserving vowel space reduction that follows from short duration, and is therefore more appropriate for studying vowel space reduction. Finally, Study 3 shows that it is possible to establish variety norms and add speakers incrementall

    Arbiter Framework

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    The Arbiter Framework is a modular environment for studying emergent intelligence within multi-agent systems. Designed with ethical governance, reinforcement learning, and real-time consensus mechanisms, this framework enables dynamic interaction, persistent learning, and decision-making among specialized agents. Integrated with OpenAI’s API for natural language oversight, it allows for real-time monitoring and scenario adjustment, making it ideal for exploring complex, socially interactive AI behavior within a controlled simulation

    Prevalence of Adverse Childhood Experiences and Mental Health Difficulties among Adolescents

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    The present study aimed to study the prevalence of adverse childhood experiences, and mental health difficulties in adolescents. Purposively selected 269 participants (MA= 14.90, SD=1.67), out of which 129 47.96%) were from Rolpa, a rural area and 140 (52.04%) were from Kathmandu, an urban area responded to Adverse Childhood Experiences International Questionnaire (ACEs-IQ) and Strengths and Difficulties Questionnaire (SDQ). Data were analyzed using Statistical Package for the Social Sciences (SPSS version-21). A high prevalence of ACEs and behavioral difficulties were found among the participants. Among the ACEs category, the prevalence of physical abuse (91.5%) and community violence (96.7%) were at a higher level. Similarly, conduct problems (18.9%) and peer problems (9.29%) were higher among SDQ components. Participants from Kathmandu reported significantly higher ACEs than participants from Rolpa. Participants from Rolpa had significantly higher total difficulties than participants from Kathmandu. Participants from Kathmandu reported significantly fewer mental health difficulties than participants from Rolpa even though they had significantly higher ACES. Keywords: ACEs, strengths, difficulties, behavioral problems, adolescent

    Dynamic updating of spatial working memory across eye movements: a computational investigation of transsaccadic integration

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    The brain continuously integrates rapidly changing visual input across eye movements to maintain stable perception, yet the precise mechanisms underpinning dynamic working memory and how these break down in brain diseases remain unclear. We developed a novel eye-tracking paradigm and computational models to investigate how spatial and colour information are updated across saccades. Our findings reveal that saccades selectively impair spatial but not colour memory. Computational modelling identified that spatial representations are maintained in a dual eye-centred frame of reference which is actively updated by a noisy memory of saccades but is vulnerable to interference. Using this model we found that specific mechanistic failures in initial encoding and memory decay, rather than the saccadic updating process itself, account for spatial working memory deficits in Alzheimer's and Parkinson’s disease. These results provide a mechanistic understanding of how dynamic spatial memory operates in health and its disruption in neurodegenerative disorders

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