132 research outputs found
Berçário: um lugar para o início da musicalidade.
Trabalho de Conclusão do Curso de Especialização em Educação Infantil - 1ª Edição – Polo Joinville - SC, para a obtenção do Grau de Especialista em Educação InfantilEste artigo trata do trabalho com a musicalização na Educação Infantil. A música enquanto linguagem favorece a aprendizagem nas diversas áreas do conhecimento, a convivência das crianças com o grupo da unidade de ensino e com os demais indivíduos dentro e fora deste contexto. O tema é relevante na medida em que destaca que a música é muito mais do que uma simples ferramenta. É uma linguagem própria que relaciona o indivíduo com o mundo e é tão importante quanto a escrita. Busca dialogar com o Referencial Curricular Nacional para a educação Infantil e analisar a musicalização como um processo de construção do conhecimento, que desperta e desenvolve o gosto musical e que influencia as relações sociais desde os primeiros meses de vida. As principais autoras, entre outros, que embasam o tema em pauta são Alícia Maria Loureiro (2003), Leda Osório Mársico (1982) e Beatriz S. Ilari (2002). Os resultados demonstram que, mesmo com bebês, é possível desenvolver o gosto e a expressão através da música e que ela pode promover a integração do grupo, enquanto várias áreas estão sendo trabalhadas simultaneamente correspondendo à linguagem, à imaginação criadora, à matemática, às percepções, ao movimento, à afetividade. Enfim, a música é importante para o desenvolvimento integral do ser humano
Bioconversion of carbon dioxide in anaerobic digesters for on-site carbon capture and biogas enhancement - A review
Energy consumption of the water sector presents an increasing energy demand, contrary to GHG mitigation aims. As a result, research aimed at capturing emitted CO2 and at developing treatment technologies with a low energy demand and increased renewable energy production has increased, leading to a surge in implementation of anaerobic digestion (AD). Valorization of the biogenic CO2 emitted with biogas AD (estimated at over 1 MtCO2 per annum for the UK water and organic waste sectors), presents an opportunity to further reduce carbon footprint and support energy supply decarburization. This paper reviews bioconversion of CO2 into CH4 in ADs (without addition of H2) as a means to valorize CO2 emissions. The review has concluded this to be a promising solution to reduce carbon footprint and uplift renewable energy production. However, in order to increase readiness for implementation (1) the mechanisms of CO2 utilization need to be elucidated, including the sources of additional H2 needed, (2) studies need to report more thoroughly the conditions of CO2 injection and (3) trials where ADs are integrated with gas to liquid mass transfer technologies need to be performed
Secondary task engagement, risk-taking, and safety-related equipment use in Gerrnan bicycle and e-scooter riders - an observation
lt has been shown that engagement in secondary tasks may contribute to cyclists crash risk [1 ], meditated by cycling errors or risky behaviors. For influences on secondary task: engagement, it is generally found that phone use is negatively correlated with age. In most studies, males are more found engaged in phone tasks than females. lt was also found that users of a bicycle-sharing program more often to wear headphones and engage in more unsafe behavior. The use of safety gear (e.g., wearing a helmet, using reflectors) is often negatively correlated with distracted cycling. Also, cyclists engaged in a secondary task exhibit other risky behaviors more often [2]. The present study's first aim was to get (an updated) estimate of the observable frequency of different secondary tasks, use of additional safety equipment, and rule violations while riding bicycles and e-scooters in Germany. The second aim was to examine possible differences in secondary task: engagement, use of additional safety equipment, and rule violations between different types of users of the cycling infrastructure, i.e., riders of conventional bikes, e-bikes, scooters, and e-scooters. A third aim was to explore whether riders' secondary task engagement is related to active safety precautions (e.g., wearing a helmet), traffic rule violations, and at-fault conflicts and if there are rider profiles regarding safety-related behaviors. As the study is explorative, no hypotheses were formulated. [From: Introduction
Enhancing the anaerobic digestion process through carbon dioxide enrichment: Initial insights into mechanisms of utilisation
Carbon dioxide (CO2) enrichment of anaerobic digesters (ADs) without hydrogen addition has been demonstrated to provide a potential solution to manage CO2 streams generated in the water and organic waste sectors, with concomitant increases in methane (CH4) production. This study investigates the CO2 utilisation mechanisms, by considering chemical and biological pathways in food waste and sewage sludge ADs. Methanosaetaceae was observed to be the dominant methanogen in sewage sludge ADs (Abundance of 83.8 – 98.8%) but scarce in food waste units (3.5 – 5.8%). Methanosarcinaceae was dominant in food waste (14.3 – 32.4%), likely due to a higher tolerance to the free ammonia nitrogen concentration recorded (885 mg·L-1). Ratios of RMethanosaetaceae (ratio of Methanosaetaceae fluorescence signal between test and control) of 1.45 and 1.79 were observed for sludge ADs enriched once and periodically with CO2, respectively (p-value <0.05), suggesting a higher Methanosaetaceae activity associated with CO2 enrichment. Reduction of CO2 by homoacetogenesis followed by acetoclastic methanogenesis was proposed as a CO2 utilisation mechanism, which requires validation by radiolabelling or carbon isotope analysis
Non-Linearity in Ecosystem Services: Temporal and Spatial Variability in Coastal Protection
Natural processes tend to vary over time and space, as well as between species. The ecosystem services these natural processes provide are therefore also highly variable. It is often assumed that ecosystem services are provided linearly (unvaryingly, at a steady rate), but natural processes are characterized by thresholds and limiting functions. In this paper, we describe the variability observed in wave attenuation provided by marshes, mangroves, seagrasses, and coral reefs and therefore also in coastal protection. We calculate the economic consequences of assuming coastal protection to be linear. We suggest that, in order to refine ecosystem-based management practices, it is essential that natural variability and cumulative effects be considered in the valuation of ecosystem services
Polygenic overlap with body-mass index improves prediction of treatment-resistant schizophrenia
Treatment resistant schizophrenia (TRS) is characterized by repeated treatment failure with antipsychotics. A recent genome-wide association study (GWAS) of TRS showed a polygenic architecture, but no significant loci were identified. Clozapine is shown to be the superior drug in terms of clinical effect in TRS; at the same time it has a serious side effect profile, including weight gain. Here, we sought to increase power for genetic discovery and improve polygenic prediction of TRS, by leveraging genetic overlap with Body Mass Index (BMI). We analysed GWAS summary statistics for TRS and BMI applying the conditional false discovery rate (cFDR) framework. We observed cross-trait polygenic enrichment for TRS conditioned on associations with BMI. Leveraging this cross-trait enrichment, we identified 2 novel loci for TRS at cFDR <0.01, suggesting a role of MAP2K1 and ZDBF2. Further, polygenic prediction based on the cFDR analysis explained more variance in TRS when compared to the standard TRS GWAS. These findings highlight putative molecular pathways which may distinguish TRS patients from treatment responsive patients. Moreover, these findings confirm that shared genetic mechanisms influence both TRS and BMI and provide new insights into the biological underpinnings of metabolic dysfunction and antipsychotic treatment.publishedVersio
Supporting stimulation needs in dementia care through wall-sized displays
Beside reminiscing, the increasing cognitive decline in dementia can also be addressed through sensory stimulation allowing the immediate, nonverbal engagement with the world through one’s senses. Much HCI work has prioritized cognitive stimulation for reminiscing or personhood often on small screens, while less research has explored sensory stimulation like the one enabled by large displays. We describe a year-long deployment in a residential care home of a wall-sized display, and explored its domestication through 24 contextual interviews. Findings indicate strong engagement and attachment to the display which has inspired four psychosocial interventions using online generic content. We discuss the value of these findings for personhood through residents’ exercise of choices, the tension between generic/personal content and its public/private use, the importance of participatory research approach to domestication, and the infrastructure-based prototype, illustrated by the DementiaWall and its generative quality
How real-world data can facilitate the development of precision medicine treatment in psychiatry
Precision medicine has the ambition to improve treatment response and clinical outcomes through patient stratification, and holds great potential in mental disorders. However, several important factors are needed to transform current practice into a “precision psychiatry” framework. Most important are (1) the generation of accessible large real-world training and test data including genomic data integrated from multiple sources, (2) the development and validation of advanced analytical tools for stratification and prediction, and (3) the development of clinically useful management platforms for patient monitoring that can be integrated into healthcare systems in real-life settings. This narrative review summarizes strategies for obtaining the key elements – well-powered samples from large biobanks, integrated with electronic health records and health registry data using novel artificial intelligence algorithms – to predict outcomes in severe mental disorders and translate these models into clinical management and treatment approaches. Key elements are massive mental health data and novel artificial intelligence algorithms. For the clinical translation of these strategies, we discuss a precision medicine platform for improved management of mental disorders. We include use cases to illustrate how precision medicine interventions could be brought into psychiatry to improve the clinical outcomes of mental disorders
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