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Whilst many lessons were learned from the COVID-19 pandemic, ongoing reflection is needed to develop and maintain preparedness for future outbreaks. Within the field of infectious disease and public health there remain silos and hierarchies in interdisciplinary work, with the risk that humanities and social sciences remain on the epistemological peripheries. However, these disciplines offer insights, expertise and tools that contribute to understanding responses to disease and uptake of interventions for prevention and treatment. In this Perspective, using examples from our own cross-disciplinary research and engagement programme on vaccine hesitancy in South Africa and the United Kingdom (UK), we propose closer integration of expertise, research and methods from humanities and social sciences into pandemic preparedness.

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Data science consulting and collaboration units (DSUs) are core infrastructure for research at universities. Activities span data management, study design, data analysis, data visualization, predictive modelling, preparing reports, manuscript writing and advising on statistical methods and may include an experiential or teaching component. Partnerships are needed for a thriving DSU as an active part of the larger university network. Guidance for identifying, developing and managing successful partnerships for DSUs can be summarized in six rules: (1) align with institutional strategic plans, (2) cultivate partnerships that fit your mission, (3) ensure sustainability and prepare for growth, (4) define clear expectations in a partnership agreement, (5) communicate and (6) expect the unexpected. While these rules are not exhaustive, they are derived from experiences in a diverse set of DSUs, which vary by administrative home, mission, staffing and funding model. As examples in this paper illustrate, these rules can be adapted to different organizational models for DSUs. Clear expectations in partnership agreements are essential for high quality and consistent collaborations and address core activities, duration, staffing, cost and evaluation. A DSU is an organizational asset that should involve thoughtful investment if the institution is to gain real value.

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In this study, we investigated serial effects on the perception of auditory vowel stimuli across three experimental setups with different degrees of context variability. Aligning with recent findings in visual perception, our results confirm the existence of two distinct processes in serial dependence: a repulsive sensory effect coupled with an attractive decisional effect. Importantly, our study extends these observations to the auditory domain, demonstrating parallel serial effects in audition. Furthermore, we uncover context variability effects, revealing a linear pattern for the repulsive perceptual effect and a quadratic pattern for the attractive decisional effect. These findings support the presence of adaptive sensory mechanisms underlying the repulsive effects, while higher-level mechanisms appear to govern the attractive decisional effect. The study provides valuable insights into the interplay of attractive and repulsive serial effects in auditory perception and contributes to our understanding of the underlying mechanisms.

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Orofacial clefts are the most common congenital anomaly of the face, and they significantly affect appearance. The combined effects of demographics, psychology, neurophysiology, and cleft characteristics to explain satisfaction with appearance in young people with a cleft have not yet been comprehensively studied in an interdisciplinary manner. We found that interpersonal difficulties, age, and conscientiousness were significant explanatory factors for satisfaction with appearance (tinterpersonal difficulties = -3.022, p = 0.006; tage = -3.563, p = 0.016; tconscientiousness = 4.161, p = 0.003); the model explained 50% of variance in satisfaction with appearance (R2 Adjusted = 0.504, Fvs. constant = 4.05, p = 0.00117). Furthermore, frontal alpha asymmetry was complexly intertwined with other variables, affecting the overall accuracy of the model, but explaining only 10.5% of variance in satisfaction with appearance when used as a factor alone. The results show that an interdisciplinary approach can substantially expand our understanding of the factors influencing self-perception in young people with orofacial clefts.

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The study examines the interaction between social capital, education, and subjective well-being in Ecuador, highlighting its impact on economic development. The study aims to understand the situation of social capital and subjective well-being and how the identified factors explain the impact on subjective well-being in the Ecuadorian population, using a descriptive and analytical approach with information from the World Value Survey database of waves 6 and 7. The main results show a significant relationship between social capital and subjective well-being, with positive influences such as justice and union membership, and negative effects of public administration and media. In conclusion, the importance of strengthening social capital and improving public services and communication to promote the well-being of the Ecuadorian population is emphasized.

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Population-normalized indicators (e.g., GDP per capita), under the assumption of the indicators scaling linearly with population, are ubiquitously used in national development performance comparison. This assumption, however, is not valid because it may ignore agglomeration effect resulting from nonlinear interactions in socioeconomic systems. Here, we present extensive empirical evidence showing the sub-linear scaling rather than the presumed linear scaling between population and multiple indicators of national development performance. We then develop a theoretical framework based on the scaling rule observed in cities to explore the origin of scaling in countries. Finally, we demonstrate that urbanization plays a pivotal role in transforming national development from limited sub-linear growth to unlimited super-linear growth. This underscores the significance of urbanization in achieving sustained growth and elevating human living standards at the national level. Our findings have the potential to inform policies aimed at promoting equitable inter-country comparison and achieving sustainable development in countries.

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This study proposes a directed acyclic graph (DAG)-based framework for generalized variance decomposition for investigating the heterogeneous return spillovers in financial system and measuring the systemic importance of financial institutions among 34 listed Chinese financial institutions from 2011 to 2023. Findings indicate pronounced information spillovers among institutions within the same sector due to contemporaneous causal relationships. Both static and dynamic financial network analyses highlight the significance of the securities sector. Dynamic structural characteristics align with macroeconomic development and are sensitive to internal and external shocks. Systemic importance assessment reveals that market size alone doesn't determine importance, with notable disparities between banking and non-banking sectors. State-owned and joint-stock commercial banks play a vital role in banking, while local government and private capital-controlled institutions are crucial in the securities sector. This research aids regulatory efforts in maintaining a balanced regulatory environment, ensuring market efficiency, and reducing operational costs.

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In cooperative societies, group members typically exchange different commodities among each other, which involves an incessant negotiation process. How is the conflict of fitness interests resolved in this continual bargaining process between unequal partners, so that maintaining the cooperative interaction is the best option for all parties involved? Theory predicts that relatedness between group members may alleviate the conflict of fitness interests, thereby promoting the evolution of cooperation. To evaluate the relative importance of relatedness and direct fitness effects in the negotiation process, we experimentally manipulated both the relatedness and mutual behavioral responses of dominant breeders and subordinate helpers in the cooperatively breeding cichlid fish Neolamprologus pulcher. Results show that coercion by breeders is crucial for the performance of alloparental egg care by helpers, but that kinship significantly decreases the need for coercion as predicted by theory. This illustrates the relative importance of kinship and enforcement in the bargaining process.

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Gender equality has been a crosscutting issue in Horizon 2020 with three objectives: gender balance in decision-making, gender balance and equal opportunities in project teams at all levels, and inclusion of the gender dimension in research and innovation content. Between 2017 and 2022, the EU funded, in collaboration with national agencies, 13 transnational projects under "GENDER-NET Plus" that explored how to best integrate both sex and gender into studies ranging from social sciences, humanities, and health research. As the projects neared completion, forty researchers from these interdisciplinary teams met in November 2022 to share experiences, discuss challenges, and consider the best ways forward to incorporate sex and gender in research. Here, we summarize the reflections from this workshop and provide some recommendations for i) how to plan the studies (e.g., how to define sex and/or gender and their dimensions, rationale for the hypotheses, identification of data that can best answer the research question), ii) how to conduct them (e.g., adjust definitions and dimensions, perform pilot studies to ensure proper use of terminology and revise until consensus is achieved), and iii) how to analyze and report the findings being mindful of any real-world impact.

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Humans, aware of the social costs associated with false accusations, are generally hesitant to accuse others of lying. Our study shows how lie detection algorithms disrupt this social dynamic. We develop a supervised machine-learning classifier that surpasses human accuracy and conduct a large-scale incentivized experiment manipulating the availability of this lie-detection algorithm. In the absence of algorithmic support, people are reluctant to accuse others of lying, but when the algorithm becomes available, a minority actively seeks its prediction and consistently relies on it for accusations. Although those who request machine predictions are not inherently more prone to accuse, they more willingly follow predictions that suggest accusation than those who receive such predictions without actively seeking them.

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Habituation, the reduction of responding to repetitive stimuli, is often conceptualized as a kind of attentional filter, amplifying salient signals at the expense of non-salient signals. No prior account has explicitly formalized filtering principles that can explain the major characteristics of habituation. In this paper, a simple probabilistic model is developed which permits analysis of the optimal filtering problem. This model exhibits the major characteristics of habituation, while also shedding light on other, relatively neglected, characteristics. These results demonstrate that habituation can be understood as a form of optimal filtering.

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BACKGROUND: Early vascular ageing (EVA) contributes to elevated risk of cardiovascular disease (CVD), which disproportionately affects African American women. Incarceration, an event disproportionately impacting African Americans, may be a stressor contributing to EVA in African American women. Further, the subjective perspective, commonly referred to as appraisal, of incarceration may also be important for health. We hypothesised that having family and/or friends incarcerated and appraising the incarceration as upsetting would be associated with indices of EVA. METHODS: In a community-based cohort of African American women aged 30-46 living in Atlanta, Georgia (n=391), participants were asked, at baseline, about family and/or friend incarceration and to appraise how upsetting the incarceration was. Multivariable linear regression examined associations between: (1) family and/or friend incarceration and indices of EVA (pulse wave velocity, augmentation index, central systolic blood pressure (SBP) and pulse pressure amplification) and (2) appraisal of incarceration and EVA indices. RESULTS: 45% of participants (n=174) reported having a loved one incarcerated, and 59% (n=102) reported the incarceration as upsetting. Having a loved one incarcerated was associated with a higher central SBP (b=4.30; 95% CI 1.61, 6.99) and augmentation index (b=2.29; 95% CI 0.26, 4.33). Appraisal of incarceration was only associated with central SBP. CONCLUSIONS: Family or friend incarceration was highly prevalent in this cohort of African American women and associated with indices of EVA. Mass incarceration of others may affect the physical health of African American women which may contribute to CVD disparities.

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Using publicly available data from 299 preregistered replications from the social sciences, we found that the language used to describe a study can predict its replicability above and beyond a large set of controls related to the article characteristics, study design and results, author information, and replication effort. To understand why, we analyzed the textual differences between replicable and nonreplicable studies. Our findings suggest that the language in replicable studies is transparent and confident, written in a detailed and complex manner, and generally exhibits markers of truthful communication, possibly demonstrating the researchers' confidence in the study. Nonreplicable studies, however, are vaguely written and have markers of persuasion techniques, such as the use of positivity and clout. Thus, our findings allude to the possibility that authors of nonreplicable studies are more likely to make an effort, through their writing, to persuade readers of their (possibly weaker) results.

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A thorough literature search is a key feature of scoping reviews. We investigated the search practices used by social science researchers as reported in their scoping reviews. We collected scoping reviews published between 2015 and 2021 from Social Science Citation Index. In the 2484 included studies, we observed a 58% average annual increase in published reviews, primarily from clinical and applied social science disciplines. Bibliographic databases comprised most of the information sources in the primary search strategy (n = 9565, 75%), although reporting practices varied. Most scoping reviews (n = 1805, 73%) included at least one supplementary search strategy. A minority of studies (n = 713, 29%) acknowledged an LIS professional and few listed one as a co-author (n = 194, 8%). We conclude that to improve reporting and strengthen the impact of the scoping review method in the social sciences, researchers should consider (1) adhering to PRISMA-S reporting guidelines, (2) employing more supplementary search strategies, and (3) collaborating with LIS professionals.

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There has been an increasing acknowledgment of the intricacies inherent in health and healthcare processes, leading to a shift in medical education. This change underscores multidimensional, thorough, reflective, and contextual approaches characterized by mutual interaction and change. The perception of health/well-being and illness is transitioning toward acknowledging them as outcomes arising from the complex interplay of individual, social, and environmental/ecosystemic factors. This includes biological, genetic, behavioral, sociocultural, and environmental influences. In line with this changing perspective, the purpose of this article is to provide a general framework for the integration of behavioral, social, and human sciences into Medical Education Programs in Healthcare and Training Processes. The framework presented is based on the following three conceptual and theoretical basis: (1) Complex systems thinking and reflective, contextual healthcare and education practices, (2) Health systems and socio-economic-political framework, (3) Ecosystem framework in health and disease. Our aim in this article is to provide a guide for the integration of Behavioral, Social, and Humanity Sciences into medical education programs and to present examples from around the world.

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Sensory and emotional experiences are essential for mental and physical well-being, especially within the realm of psychiatry. This article highlights recent advances in cognitive neuroscience, emphasizing the significance of pain recognition and empathic artificial intelligence (AI) in healthcare. We provide an overview of the recent development process in computational pain recognition and cognitive neuroscience regarding the mechanisms of pain and empathy. Through a comprehensive discussion, the article delves into critical questions such as the methodologies for AI in recognizing pain from diverse sources of information, the necessity for AI to exhibit empathic responses, and the associated advantages and obstacles linked with the development of empathic AI. Moreover, insights into the prospects and challenges are emphasized in relation to fostering artificial empathy. By delineating potential pathways for future research, the article aims to contribute to developing effective assistants equipped with empathic capabilities, thereby introducing safe and meaningful interactions between humans and AI, particularly in the context of mental health and psychiatry.

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Algorithmic bias has emerged as a critical challenge in the age of responsible production of artificial intelligence (AI). This paper reviews recent research on algorithmic bias and proposes increased engagement of psychological and social science research to understand antecedents and consequences of algorithmic bias. Through the lens of the 3-D Dependable AI Framework, this article explores how social science disciplines, such as psychology, can contribute to identifying and mitigating bias at the Design, Develop, and Deploy stages of the AI life cycle. Finally, we propose future research directions to further address the complexities of algorithmic bias and its societal implications.

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BACKGROUND: The rapid advancement of technology-focused strategies in neurorehabilitation has brought optimism to individuals with neurological disorders, caregivers, and physicians while reshaping medical practice and training. OBJECTIVES: We critically examine the implications of technology in neurorehabilitation, drawing on discussions from the 2021 and 2024 World Congress for NeuroRehabilitation. While acknowledging the value of technology, it highlights inherent limitations and ethical concerns, particularly regarding the potential overshadowing of humanistic approaches. The integration of technologies such as robotics, artificial intelligence, neuromodulation, and brain-computer interfaces enriches neurorehabilitation by offering interdisciplinary solutions. However, ethical considerations arise regarding the balance between compensation for deficits, accessibility of technologies, and their alignment with fundamental principles of care. Additionally, the pitfalls of relying solely on neuroimaging data are discussed, stressing the necessity for a more comprehensive understanding of individual variability and clinical skills in rehabilitation. RESULTS: From a clinical perspective, the article advocates for realistic solutions that prioritize individual needs, quality of life, and social inclusion over technological allure. It underscores the importance of modesty and honesty in responding to expectations while emphasizing the uniqueness of each individual's experience. Moreover, it argues for the preservation of human-centric approaches alongside technological advancements, recognizing the invaluable role of clinical observation and human interaction in rehabilitation. CONCLUSION: Ultimately, the article calls for a balanced attitude that integrates both scientific and humanistic perspectives in neurorehabilitation. It highlights the symbiotic relationship between the sciences and humanities, advocating for philosophical questioning to guide the ethical implementation of new technologies and foster interdisciplinary dialogue.

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Object recognition is an important ability that relies on distinguishing between similar objects (e.g., deciding which utensil(s) to use at different stages of meal preparation). Recent work describes the fine-grained organization of knowledge about manipulable objects via the study of the constituent dimensions that are most relevant to human behavior, for example, vision, manipulation, and function-based properties. A logical extension of this work concerns whether or not these dimensions are uniquely human, or can be approximated by deep learning. Here, we show that behavioral dimensions are generally well-predicted by CLIP-ViT - a multimodal network trained on a large and diverse set of image-text pairs. Moreover, this model outperforms comparison networks pre-trained on smaller, image-only datasets. These results demonstrate the impressive capacity of CLIP-ViT to approximate fine-grained object knowledge. We discuss the possible sources of this benefit relative to other models (e.g., multimodal vs. image-only pre-training, dataset size, architecture).