Supporting Adolescent Mental Health Within School Culture and Curricula: Inviting Adolescents to Utah\u27s Mental Health Conversation

Utah is facing a mental health crisis. Between 2011 and 2017, teen suicides nearly tripled in Utah and had become the leading cause of death for children ages 10-17. Educators and policymakers are scrambling to provide students with mental health supports in schools, but an incomplete understanding of the challenges that students face can make it difficult to meet their needs. Each year state agencies ratchet up awareness, funding, and the determination to support mental health initiatives, but each year adolescent mental health in Utah becomes more precarious. The purpose of this study is to change the conversation by inviting adolescents to join Utah’s mental health conversation. The stories and insights these students share suggest the need for the development of a more comprehensive model of mental health support in schools—one that includes consideration of their needs for safety, respect, inclusion, connection, empowerment and transforming purpose

Mediators of the relationship between self-control and pathological technology use: Negative affect and cognitive failures, but not self-efficacy

The widespread adoption of technologies such as smartphones, the Internet, and social media has been associated with the emergence of pathological technology use (e.g., Internet addiction). Prevalence rates of pathological technology use vary widely across age groups, cultures, and medium, although it is not uncommon for rates of mild to moderate pathological use to exceed 20%-30%. These relatively high prevalence rates have motivated researchers to identify the predictors of pathological use. The current study focuses on the relationship be- tween self-control and pathological technology use, and demonstrates that negative affect and cognitive failures, but not self-efficacy, partially mediate the association between self-control and pathological technology use. These findings re- veal some of the pathways by which poor self-control could lead to elevated levels of pathological technology use

Identidade, Cultura e Museus. Moradas Colectivas: um estudo de caso sobre o Centro de Arte Moderna, Fundação Calouste Gulbenkian

Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Antropologia – Culturas em cena e TurismoEsta breve dissertação debruça-se sobre a construção dos discursos do Museu através de um projecto de intervenção artística e social. Durante o período de 2009-2010, o Serviço educativo do CAM e o Projecto Percursos Acompanhados do CESIS, empreenderam um projecto que permitiu contribuir para a reflexão sobre o papel dos museus na sociedade actual e a sua pertinência na transformação de percursos de vida dos que nesse espaço se descobrem e definem, através de práticas artísticas. O contexto desconfigurado, híbrido e múltiplo do campo cultural necessita hoje de uma sensibilidade antropológica para entender as reformulações identitárias e culturais que se vêm evidenciando. Através da descoberta do contexto periférico como espaço de criatividade e inovação, novos terrenos de produção cultural emergem e neste sentido, o projecto Moradas Colectivas revela como no espaço do museu de misturam e reconfiguram noções de identidade, cultura, exclusão e interculturalidad

Formulating polyurethanes using case based reasoning

A large amount of historical knowledge exists in the form of ‘formulation experiences’ across polyurethane manufacturing companies. This knowledge is difficult to formalise, share and use in new formulations. As a part of an effort to support the polyurethane formulating problem, the use of case based reasoning (CBR) has been assessed. Two basic problems in the development of the proposed hybrid tool that uses past formulations to solve new problems are studied. The problems investigated are related to the retrieval of former formulations that are similar to a new problem description by the CBR module, and the adaptation of the retrieved case to meet the problem constraints using an artificial neural network (ANN). Results indicated that the CBR-ANN system is useful for reusing historical data. Although the obtained ANN is unable to generalise well when presented with more data independent from the original data set, results proved that real formulation data can be used as a ‘knowledge repository’ that can guide CBR adaptation without human expert intervention

Longitudinal Analysis of Antibody Responses to Trachoma Antigens Before and After Mass Drug Administration.

Blinding trachoma, caused by the bacteria Chlamydia trachomatis, is a neglected tropical disease targeted for elimination by 2020. A major component of the elimination strategy is mass drug administration (MDA) with azithromycin. Currently, program decisions are made based on clinical signs of ocular infection, but we have been investigating the use of antibody responses for post-MDA surveillance. In a previous study, IgG responses were detected in children lacking clinical evidence of trachoma, suggesting that IgG responses represented historical infection. To explore the utility of serology for program evaluation, we compared IgG and IgA responses to trachoma antigens and examined changes in IgG and IgA post-drug treatment. Dried blood spots and ocular swabs were collected with parental consent from 264 1-6 year olds in a single village of Kongwa District, central Tanzania. Each child also received an ocular exam for detection of clinical signs of trachoma. MDA was given, and six months later an additional blood spot was taken from these same children. Ocular swabs were analyzed for C. trachomatis DNA and antibody responses for IgA and total IgG were measured in dried bloods spots. Baseline antibody responses showed an increase in antibody levels with age. By age 6, the percentage positive for IgG (96.0%) was much higher than for IgA (74.2%). Antibody responses to trachoma antigens declined significantly six months after drug treatment for most age groups. The percentage decrease in IgA response was much greater than for IgG. However, no instances of seroreversion were observed. Data presented here suggest that focusing on concordant antibody responses in children will provide the best serological surveillance strategy for evaluation of trachoma control programs

Combining business process and failure modelling to increase yield in electronics manufacturing

The prediction and capturing of defects in low-volume assembly of electronics is a technical challenge that is a prerequisite for design for manufacturing (DfM) and business process improvement (BPI) to increase first-time yields and reduce production costs. Failures at the component-level (component defects) and system-level (such as defects in design and manufacturing) have not been incorporated in combined prediction models. BPI efforts should have predictive capability while supporting flexible production and changes in business models. This research was aimed at the integration of enterprise modelling (EM) and failure models (FM) to support business decision making by predicting system-level defects. An enhanced business modelling approach which provides a set of accessible failure models at a given business process level is presented in this article. This model-driven approach allows the evaluation of product and process performance and hence feedback to design and manufacturing activities hence improving first-time yield and product quality. A case in low-volume, high-complexity electronics assembly industry shows how the approach leverages standard modelling techniques and facilitates the understanding of the causes of poor manufacturing performance using a set of surface mount technology (SMT) process failure models. A prototype application tool was developed and tested in a collaborator site to evaluate the integration of business process models with the execution entities, such as software tools, business database, and simulation engines. The proposed concept was tested for the defect data collection and prediction in the described case study

A case-based reasoning approach for low volume, high added value electronics

This paper will report on the application of the Case-Based Reasoning (CBR) approach [1] to develop a defect prediction system to support the development of new printed circuit assembly (PCA) products. Using a CBR system, past PCA design specifications and manufacturing experiences including defect and yield results can be effectively stored and reapplied for future problem solving. For example, the CBR can then be used at design stage to amend designs or define process options to optimise the product yield and service reliability. A case study using a case-base provided by a PCA manufacturer is presented

Component detection with on-board UHF RFID reader for Industrie 4.0 capable Returnable Transit Items

Industrie 4.0, Cyber-Physical Systems and Smart Manufacturing are all terms used to describe a vision of how intelligent products, processes and services can provide connectivity and real time information based technologies to improve manufacturing. This can be realised by embedding intelligence at the product and operational level to provide predictive, risk preventative and high performing manufacturing systems. The work outlined in this paper details how a Returnable Transit Item (RTI) can become an integral part of the Industrie 4.0 vision as an intelligent container that can interact with components, machines and other manufacturing services