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A identificação de talentos esportivos no basquetebol brasileiro carece de sistematização. O objetivo foi criar um modelo matemático de avaliação do potencial esportivo de jovens basquetebolistas e testar suas propriedades psicométricas. 178 jovens atletas do sexo masculino (12 a 17 anos; nível competitivo regional/estadual) foram submetidos a uma bateria de testes multidimensional e avaliados pelos seus treinadores (aspectos intangíveis do potencial esportivo e expectativa de sucesso futuro). Foram calculados escores Z e percentis. Através de procedimentos analíticos e heurísticos, criou-se o Gold Score Basketball, um índice híbrido (testes + olhar do treinador) e ponderado para estimativa do potencial esportivo com 26 indicadores objetivos e 2 indicadores subjetivos. O modelo classificou 5,1% dos atletas como potencial de excelência (Gold Score >90). A consistência interna foi moderada (r = 0,59) e a estabilidade do diagnóstico foi elevada (r = 0,82). Atletas com maior nível competitivo (62,9 ± 14,4 vs. 50,7±15,6, p<0,001; validade de construto) e que venceram campeonatos estaduais/nacionais (64,3 ± 15,4 vs. 52,1 ± 15,6, p<0,001; validade de critério) apresentaram maior Gold Score. Conclui-se que o Gold Score Basketball é um modelo científico válido e fidedigno de avaliação do potencial esportivo de jovens basquetebolistas, sendo útil na identificação de talentos esportivos. Palavras-chave: identificação de talentos; seleção de talentos; modelagem estatística; basquetebol.

Background: The Gyr breed is widely used in Colombian low tropic dairy production systems. During the last 10 years, the Asociación Colombiana de Criadores de Ganado Cebú† - ASOCEBU, has been leading a dairy milk control program which led to the creation of a dataset that permits to carry out the first analysis of milk yield in Gyr cattle in the country using records from several herds. Objectives: To study milk production dynamics of Gyr cattle in the Colombian low tropic through the estimation of lactation curves and four derived production parameters: total milk yield between 5 and 305 days (TMY305), peak milk yield (PMY), days at peak (DP) and persistency (P). Methods: 13,798 daily milk yield records from 1,510 cows performing in 103 herds were used; the total number of lactations was 2,480. Four models were considered: Wood, Wiltmink, Papajcsik & Bordero, and a second-degree polynomial. Mean square error, mean absolute error, mean square error of prediction, Akaike and Bayesian information criteria were used to select the model better describing each lactation using the majority rule, that is, the model selected by most criteria was the chosen one. The shape of each fitted lactation curve was checked using basic results from calculus which permitted the classification of the estimated curves into two groups: typical and atypical; only typical functions were used to compute the four aforementioned production parameters. Results: The second-order polynomial was the model most frequently selected, while the Papajcsik & Bordero model had the lowest frequency. Average TMY305, PMY, DP and P were 3,489.86 kg, 17.28 kg, 57.17 days, and 0.83, respectively, with coefficients of variation: 0.27, 0.21, 0.41, and 0.16. Conclusions: This study permitted to identify individuals with outstanding phenotypic performance. To the best of our knowledge, this is the first study of this kind involving thousands of lactations from Gyr cows performing in several regions of Colombian low tropic.

Monitoring the relationship between water supply and demand in vulnerable and strategic areas, such as the Bauru Aquifer System (BAS), is necessary for balance economic and ecological interests of activities developed in these areas. The aim of this study is to explain, from HARTT (Hydrograph Analysis: Rainfalland Time Trend) autoregression model, the behaviour of water table oscilations of Bauru Aquifer System at native vegetation (Cerrado) areas in order to understand how groundwater levels respond to different stresses from precipitation events and vegetation management. Time series of precipitation and water table depths monitored at five piezometers are used as data inputs at HARTT model. The model results presented similarities with the original data ranging calibrations with R2 superior to 80%. The delay from a precipitation event to a groundwater response was one month for all wells. In other words, it means that after a precipitation event, the groundwater levels rise after this temporal delay. These results are need in order to generate the technical knowledge necessary for the management of this resource. The use of time series models allowed to detect changes in the hydrological cycle and patterns associated mostly with precipitation.

En este trabajo, se presentan los resultados originados de una investigación sobre el usode la simulación de procesos de manufactura para ayudar a una empresa a tomar decisiones frentea cambios en sus modelos de producción. El objetivo de este artículo es presentar una metodologíaque otras empresas puedan seguir para simular sus procesos productivos en busca de mejorarlos.La metodología empleada consistió en realizar el reconocimiento del proceso de producción de laempresa, después hacer la toma de datos del proceso por estudiar y, fnalmente, realizar el modelamiento y la simulación tanto del sistema actual tipo push como de propuestas sugeridas tipo pull.Se encontró que con un modelo tipo pull, empleando subcontratación de algunas partes, es posiblemejorar ostensiblemente el proceso productivo de la empresa. Una de las limitaciones en este tipode trabajos es que se debe tenerse información sufciente del proceso. Además, el uso de resultadosen la toma de decisiones implica indagar sufcientemente las distintas posibilidades de los modelos.En este trabajo, se logró mostrar a la empresa diferentes posibilidades para realizar su proceso demanufactura y sus bondades en términos económicos y de efciencia.