Proposal and validation of methodologies for the categorisation of continuous variables in the development of prediction models

158 p.

Relationship between abundance of juvenile rockfishes (Sebastes spp.) and environmental variables documented off northern California and potential mechanisms for the covariation

We estimated annual abundance of juvenile blue (Sebastes mystinus), yellowtail (S. f lavidus), and black (S. melanops) rockfish off northern California over 21 years and evaluated the relationship of abundance to oceanographic variables (sea level anomaly, nearshore temperature, and offshore Ekman transport). Although mean annual abundance was highly variable (0.01−181 fish/minute), trends were similar for the three species. Sea level anomaly and nearshore temperature had the strongest relationship with interannual variation in rockfish abundance, and offshore Ekman transport did not correlate with abundance. Oceanographic events occurring in February and March (i.e., during the larval stage) had the strongest relationship with juvenile abundance, which indicates that year-class strength is determined during the larval stage. Also of note, the annual abundance of juvenile yellowtail rockfish was positively correlated with year-class strength of adult yellowtail rockfish; this finding would indicate the importance of studying juvenile abundance surveys for management purposes.

Effects of an emotional intelligence program in variables related to the prevention of violence

In recent decades, numerous studies have shown a significant increase in violence during childhood and adolescence. These data suggest the importance of implementing programs to prevent and reduce violent behavior. The study aimed to design a program of emotional intelligence (El) for adolescents and to assess its effects on variables related to violence prevention. The possible differential effect of the program on both genders was also examined. The sample comprised 148 adolescents aged from 13 to 16 years. The study used an experimental design with repeated pretest-posttest measures and control groups. To measure the variables, four assessment instruments were administered before and after the program, as well as in the follow-up phase (1 year after the conclusion of the intervention). The program consisted of 20 one-hour sessions. The pretest-posttest ANCOVAs showed that the program significantly increased: (1) El (attention, clarity, emotional repair); (2) assertive cognitive social interaction strategies; (3) internal control of anger; and (4) the cognitive ability to analyze negative feelings. In the follow-up phase, the positive effects of the intervention were generally maintained and, moreover, the use of aggressive strategies as an interpersonal conflict-resolution technique was significantly reduced. Regarding the effect of the program on both genders, the change was very similar, but the boys increased assertive social interaction strategies, attention, and emotional clarity significantly more than the girls. The importance of implementing programs to promote socio-emotional development and prevent violence is discussed.

Filtragem adaptativa aplicada à redução de desvios em séries temporais de previsão numérica climática.

Esta dissertação apresenta resultados da aplicação de filtros adaptativos, utilizando os algoritmos NLMS (Normalized Least Mean Square) e RLS (Recursive Least Square), para a redução de desvios em previsões climáticas. As discrepâncias existentes entre o estado real da atmosfera e o previsto por um modelo numérico tendem a aumentar ao longo do período de integração. O modelo atmosférico Eta é utilizado operacionalmente para previsão numérica no CPTEC/INPE e como outros modelos atmosféricos, apresenta imprecisão nas previsões climáticas. Existem pesquisas que visam introduzir melhorias no modelo atmosférico Eta e outras que avaliam as previsões e identificam os erros do modelo para que seus produtos sejam utilizados de forma adequada. Dessa forma, neste trabalho pretende-se filtrar os dados provenientes do modelo Eta e ajustá-los, de modo a minimizar os erros entre os resultados fornecidos pelo modelo Eta e as reanálises do NCEP. Assim, empregamos técnicas de processamento digital de sinais e imagens com o intuito de reduzir os erros das previsões climáticas do modelo Eta. Os filtros adaptativos nesta dissertação ajustarão as séries ao longo do tempo de previsão. Para treinar os filtros foram utilizadas técnicas de agrupamento de regiões, como por exemplo o algoritmo de clusterização k-means, de modo a selecionar séries climáticas que apresentem comportamentos semelhantes entre si. As variáveis climáticas estudadas são o vento meridional e a altura geopotencial na região coberta pelo modelo de previsão atmosférica Eta com resolução de 40 km, a um nível de pressão de 250 hPa. Por fim, os resultados obtidos mostram que o filtro com 4 coeficientes, adaptado pelo algoritmo RLS em conjunto com o critério de seleção de regiões por meio do algoritmo k-means apresenta o melhor desempenho ao reduzir o erro médio e a dispersão do erro, tanto para a variável vento meridional quanto para a variável altura geopotencial.