An Integral Abutment Bridge with Precast Concrete Piles, May 2007

The use of precast, prestressed concrete piles in the foundation of bridge piers has long been recognized as a valuable option for bridge owners and designers. However, the use of these precast, prestressed concrete piles in integral abutment bridges has not been widespread because of concerns over pile flexibility and the potential for concrete cracking and deterioration of the prestressing strands due to long-term exposure to moisture. This report presents the details of the first integral abutment bridge in the state of Iowa that utilized precast, prestressed concrete piles in the abutment. The bridge, which was constructed in Tama County in 2000, consists of a 110 ft. long, 30 ft. wide, single-span PC girder superstructure with a left-side-ahead 20º skew angle. The bridge was instrumented with a variety of strain gages, displacement sensors, and thermocouples to monitor and help in the assessment of structural behavior. The results of this monitoring are presented, and recommendations are made for future application of precast, prestressed concrete piles in integral abutment bridges. In addition to the structural monitoring data, this report presents the results of a survey questionnaire that had been mailed to each of the 50 state DOT chief bridge engineers to ascertain their current practices for precast, prestressed concrete piles and especially the application of these piles in integral abutment bridges.

SIS: Sistema Integral Sanitario

Desarrollo de una aplicación para responder a la necesidad del ministerio de Sanidad de informatizar todo el sistema sanitario, desde hospitales hasta farmacias.

Compact matrix expressions for generalized Wald tests of equality of moment vectors

Asymptotic chi-squared test statistics for testing the equality ofmoment vectors are developed. The test statistics proposed aregeneralizedWald test statistics that specialize for different settings by inserting andappropriate asymptotic variance matrix of sample moments. Scaled teststatisticsare also considered for dealing with situations of non-iid sampling. Thespecializationwill be carried out for testing the equality of multinomial populations, andtheequality of variance and correlation matrices for both normal andnon-normaldata. When testing the equality of correlation matrices, a scaled versionofthe normal theory chi-squared statistic is proven to be an asymptoticallyexactchi-squared statistic in the case of elliptical data.

Glut-1 deficiency syndrome masquerading as idiopathic generalized epilepsy.

To report the case of a child with short absences and occasional myoclonias since infancy who was first diagnosed with an idiopathic generalized epilepsy, but was documented at follow-up to have a mild phenotype of glucose transporter type 1 deficiency syndrome. Unlike other reported cases of Glut-1 DS and epilepsy, this child had a normal development as well as a normal head growth and neurological examination. Early onset of seizures and later recognized episodes of mild confusion before meals together with persistent atypical EEG features and unexpected learning difficulties led to the diagnosis. Seizure control and neuropsychological improvements were obtained with a ketogenic diet.

The Hippo Transducer YAP1 Transforms Activated Satellite Cells and Is a Potent Effector of Embryonal Rhabdomyosarcoma Formation.

The role of the Hippo pathway effector YAP1 in soft tissue sarcomas is poorly defined. Here we report that YAP1 activity is elevated in human embryonal rhabdomyosarcoma (ERMS). In mice, sustained YAP1 hyperactivity in activated, but not quiescent, satellite cells induces ERMS with high penetrance and short latency. Via its transcriptional program with TEAD1, YAP1 directly regulates several major hallmarks of ERMS. YAP1-TEAD1 upregulate pro-proliferative and oncogenic genes and maintain the ERMS differentiation block by interfering with MYOD1 and MEF2 pro-differentiation activities. Normalization of YAP1 expression reduces tumor burden in human ERMS xenografts and allows YAP1-driven ERMS to differentiate in situ. Collectively, our results identify YAP1 as a potent ERMS oncogenic driver and a promising target for differentiation therapy.

Improving generalized regression analysis for the spatial prediction of forest communities

Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.

Sistema de Talleres Dirigido a la Superación Profesional de los Docentes de la Enseñanza Básica Integral en la Atención a la Diversidad de Niños con Necesidades Educativas Especiales en la República de Cabo Verde

La presente tesis abordó un tema de gran actualidad y pertinencia social: la superación profesional de los docentes de la Enseñanza Básica Integral en atención a la diversidad de niños con necesidades educativas especiales en la República de Cabo Verde, da una respuesta encaminada a la atención a la diversidad en la escuela regular, esta como la diferencia entre culturas, lenguas, valores, sexualidad, género, religión, desarrollo y necesidades educativas especiales asociadas a una discapacidad. Esta necesidad ha sido reconocida en documentos nacionales e internacionales como la Ley General de Educación la Declaración Universal de la UNESCO. Se asume como el proceso de atención psicopedagógica encaminada a los alumnos con necesidades educativas especiales y se considera como uno de los principales retos que la sociedad actual, creciente en su pluralidad, plantea al sistema educativo, y en concreto a las instituciones escolares. Es objetivo del trabajo proponer un sistema de talleres dirigido a la superación profesional de los docentes en la atención a la diversidad de niños con necesidades educativas especiales. Desde el enfoque general dialéctico materialista y los métodos teóricos y empíricos de investigación se modela la solución del problema. Los datos obtenidos revelan las posibilidades de cambios y transformación en el objeto de estudio: la superación de los docentes en la atención a la diversidad necesidades educativas especiales regular.

Adaptive approach heuristics for the generalized assignment problem

The Generalized Assignment Problem consists in assigning a setof tasks to a set of agents with minimum cost. Each agent hasa limited amount of a single resource and each task must beassigned to one and only one agent, requiring a certain amountof the resource of the agent. We present new metaheuristics forthe generalized assignment problem based on hybrid approaches.One metaheuristic is a MAX-MIN Ant System (MMAS), an improvedversion of the Ant System, which was recently proposed byStutzle and Hoos to combinatorial optimization problems, and itcan be seen has an adaptive sampling algorithm that takes inconsideration the experience gathered in earlier iterations ofthe algorithm. Moreover, the latter heuristic is combined withlocal search and tabu search heuristics to improve the search.A greedy randomized adaptive search heuristic (GRASP) is alsoproposed. Several neighborhoods are studied, including one basedon ejection chains that produces good moves withoutincreasing the computational effort. We present computationalresults of the comparative performance, followed by concludingremarks and ideas on future research in generalized assignmentrelated problems.

Generalized canonical correlation analysis of matrices with different row and column orders

A Method is offered that makes it possible to apply generalized canonicalcorrelations analysis (CANCOR) to two or more matrices of different row and column order. The new method optimizes the generalized canonical correlationanalysis objective by considering only the observed values. This is achieved byemploying selection matrices. We present and discuss fit measures to assessthe quality of the solutions. In a simulation study we assess the performance of our new method and compare it to an existing procedure called GENCOM,proposed by Green and Carroll. We find that our new method outperforms the GENCOM algorithm both with respect to model fit and recovery of the truestructure. Moreover, as our new method does not require any type of iteration itis easier to implement and requires less computation. We illustrate the methodby means of an example concerning the relative positions of the political parties inthe Netherlands based on provincial data.

Aprovechamiento de la materia prima en la elaboración de harina de pescado tipo integral

Estudio técnico y económico de dos métodos del aprovechamiento de la materia prima en la elaboración de harina de pescado tipo integral. Contiene el balance de materia y la composición de la materia prima y sus rendimientos.

Nonlinear models and small sample performance of the generalized method of moments

In this paper I explore the issue of nonlinearity (both in the datageneration process and in the functional form that establishes therelationship between the parameters and the data) regarding the poorperformance of the Generalized Method of Moments (GMM) in small samples.To this purpose I build a sequence of models starting with a simple linearmodel and enlarging it progressively until I approximate a standard (nonlinear)neoclassical growth model. I then use simulation techniques to find the smallsample distribution of the GMM estimators in each of the models.