11237 research outputs found
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Tensor-based Adaptive Consensus Graph Learning for Multi-view Clustering
No full textMulti-view clustering has garnered considerable attention in recent years owing to its impressive performance in processing high-dimensional data. Most multi-view clustering models still encounter the following limitations. They emphasize common representations or pairwise correlations between multiple views, while neglecting high-order correlations. The weights of multiple views or prior information of singular values are ignored in the clustering process. Therefore, a Tensor-based Adaptive Consensus Graph Learning (TACGL) model is proposed for addressing above problems. Specifically, all representation matrices of multiple views are stacked into a representation tensor to reveal high-order connections among multiple views. A weighted tensor nuclear norm is imposed on representation tensor to maintain property of low-rank and discovers the prior information of singular values. The weights of graph learning can be automatically assigned to each similarity graph via consensus graph learning, resulting in a unified graph matrix. Laplacian rank constraint is imposed on the unified matrix to help partition the samples into the desired number of clusters. An algorithm based on Alternating Direction Method of Multipliers (ADMM) is designed for solving TACGL. Based on comprehensive experiments conducted on ten datasets, it is clear that the proposed model showcases substantial advantages over fourteen state-of-the-art models.</p
Buzzes are used as signals of aggressive intent in Darwin's finches
No full textSignals of aggression may potentially reduce the fitness costs of conflict during agonistic interactions if they are honest. Here we examined whether the ‘buzz’ vocalization in two species of Darwin’s finches, the small tree finch, Camarhynchus parvulus, and the critically endangered medium tree finch, C. pauper, found in Floreana Island, Galápagos Archipelago, is a signal of aggression. Specifically, we assessed three criteria for aggressive signalling (context, predictive, and response criteria) in an observational study and a playback experiment. In the observational study, buzzes by the resident male were more common when an intruder was present on the territory in medium tree finches but not small tree finches (context criterion). In the playback experiment, buzzes increased during and after a simulated intrusion for both species (context criterion). Buzzes before the playback period predicted aggressive responses by males (predictive criterion) but buzzes during playback did not. Finally, both species responded more strongly to playbacks of conspecific buzzes compared to conspecific songs and heterospecific buzzes (response criterion). Together the results support the aggressive signal hypothesis for buzz vocalizations, although future studies are needed to understand the evolution and development of this interesting signal.</p
Associations Between Nature Exposure and Body Image: A Critical, Narrative Review of the Evidence
No full textResearchers, practitioners, and policy-makers are having to deal with the negative impact of body image concerns in populations globally. One cost-effective way of promoting healthier body image outcomes is through exposure to natural environments. A growing body of research has shown that spending time in, interacting with, and even just looking at natural environments can promote healthier body image outcomes. In this narrative review, I consider the different forms of evidence documenting an association between nature exposure and body image (i.e., cross-sectional and mediational, experimental and quasi-experimental, comparative, prospective, experience sampling, and qualitative research). Beyond this, I shine a critical light on the available evidence, highlighting concerns with methodological (i.e., who research has focused on and what types of natural environments have been considered), psychometric (i.e., how body image and nature exposure are measured), and conceptual issues (how the association is explained). I conclude that, although there are issues affecting the way the existing body of research is to be understood, there are reasons to be hopeful that nature exposure can be leveraged to promote healthier body image outcomes in diverse populations.</p
Prevalence of obesity and associated sociodemographic and lifestyle factors in Ecuadorian children and adolescents
No full textBackground
Given the increasing prevalence of obesity in young people in Ecuador, there is a need to understand the factors associated with this condition. The aim of this study was to assess the prevalence of obesity in Ecuadorian children and adolescents aged 5–17 years and identify its associated sociodemographic and lifestyle factors.
Methods
This cross-sectional study was conducted using data from the Encuesta Nacional de Salud y Nutrición (ENSANUT-2018). The final sample consisted of 11,980 participants who provided full information on the variables of interest.
Results
The prevalence of obesity was 12.7%. A lower odd of having obesity was observed for adolescents; for those with a breadwinner with an educational level in middle/high school or higher; for each additional day with 60 or more minutes of daily moderate-to-vigorous physical activity; and for those with greater daily vegetable consumption (one, two, or three or more servings). Conversely, there were greater odds of obesity in participants from families with medium, poor, and very poor wealth and those from the coast and insular region.
Conclusions
The high prevalence of obesity in Ecuadorian children and adolescents is a public health concern. Sociodemographic and lifestyle behavior differences in young people with obesity should be considered when developing specific interventions.
Impact
As the prevalence of obesity among children and adolescents increases in Latin America, with a particular focus on Ecuador, it becomes crucial to delve into the factors linked to this condition and identify the most successful strategies for its mitigation.
The elevated prevalence of obesity among young individuals in Ecuador raises significant public health concerns.
To develop targeted interventions, it is crucial to account for sociodemographic variables and lifestyle behaviors that contribute to obesity in this population.</p
Effects of Enclosure Complexity and Design on Behaviour and Physiology in Captive Animals
No full textIndividual animals in managed populations are subject to controlled social and physical environmental conditions that impact their behaviour patterns, choice of social associates, ability to experience positive welfare states, and ultimately their overall health status and quality of life. Previous research has shown the importance of ensuring that managed animals experience control and choice (i.e., have a sense of autonomy over what they can do and when) within the sphere of their housing, husbandry, and management regimes...</p
National trends in the prevalence of unmet healthcare and dental care needs amid pandemic, 2009-2022: a Korean representative long-term serial study
No full textNo description supplied</p
Measuring customer experience quality in the public sector: the role of service design perceptions in the UAE
No full textCustomer experience has recently become a key focus in marketing and service research and practice, increasing rapidly among researchers and practitioners. This increased focus is due to its impact on customers and business performance in general for private and public sector organizations. The role of the customer has evolved dramatically for the long-term success of an organization’s product or service, leading toward customer-centric approaches that will enhance the customer experience. Governments worldwide are increasingly focusing on creating a better customer experience by touching all aspects of the service ecosystem.Therefore, managing and monitoring the quality of the customer experience is part of an organization's success. Researchers have called for a better understanding of how to measure customer experience quality, as there is no single well-accepted measurement scale from the researchers to measure the customer experience, such as other concepts, due to the complexity and multidisciplinary of the concept. Moreover, most efforts to build a measurement scale for customer experience were in the private sector, whereas efforts in the public sector are scarce. This study attempts to bridge the gap in the existing literature by examining the customer experience quality scale in the public sector. Furthermore, it tries to link customer experience quality with the service design, examine the effect of the customer perceptions of service design on the customer experience, and tries to analyse the effects of the customer experience on the outcomes of it, which are customer emotions, word of mouth, customer satisfaction and customer well-being.The study adopted the positivist philosophy using a quantitative methodology with a survey questionnaire and used existing measurement scale models adapted to fit the public sector. The survey conducted covered six main dimensions related to customer experience quality. Before launching the survey, a pilot study was conducted, which included academics, practitioners, and customers. The survey had 51 statements distributed online to public sector customers to check their impressions and feelings toward the model dimensions.Reliability and validity were tested and confirmed, including the measurement and structural models. The proposed relationships in the hypotheses were accepted. The perceptions of service design of the customers in the public sector significantly impacted customer experience quality. Likewise, customer experience quality significantly and positively affected customer experience. In summary, all the proposed hypotheses were accepted. Finally, the study's theoretical and managerial implications and contributions were highlighted, providing a pathway for future research, especially in the public sector.</p
Preparing for Assistance Dog Retirement - a PPIE case study
No full textPresentation outlining a best practice case study hat was part of the Preparing for Assistance Dog Retirement project undertakeb by the ARU OneWelfare Research Group, presented at the 2024 Let's Shape Research Together Conference at ARU Cambridge</p
County Line Gangs Research with 6th form students
No full textThis report presents the findings of a qualitative study conducted with sixth-form students to explore their perceptions and understanding of County Lines gangs and grooming tactics. The research, co-authored by Aimee Neaverson, Dr. Niamh O’Brien, and Faye Acton, investigates how young people are targeted and exploited by drug-dealing gangs operating through the County Lines model. The study highlights the vulnerabilities of youth, focusing on grooming techniques, the normalization of drug-dealing lifestyles, and the emotional and social pressures experienced by those at risk. By engaging students in focus groups and discussions, the research provides crucial insights into the preventative measures that could be implemented to safeguard young people from gang involvement. The findings are significant for schools, law enforcement, and policymakers aiming to address child criminal exploitation and to develop more effective interventions.</p
A deep transfer learning approach for lung tumour detection with resilience testing under suboptimal conditions
No full textFatality from lung tumours makes up the most significant proportion of all cancer deaths in the UK, and the 10-year survival rate is less than 10%. This research explores the use of pretrained deep neural networks for lung tumour detection and aims to determine which network is best suited for the task. The report highlights the significance of lung tumours as fatal cancer and the potential of artificial intelligence to improve detection and diagnosis. The methodology involves transfer learning of multiple pretrained neural networks onto a lung tumour dataset and testing robustness against varying levels and types of noise. Implementation and testing have been conducted in Matlab R2022b. Firstly, transfer learning of a number of deep neural networks onto a lung tumour dataset has been performed and a comparison of the performance of all chosen deep neural networks has been obtained. </p
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