Influence of Concrete Compressive Strength on Transfer and Development Lengths of Prestressed Concrete

This research examines the relationship between concrete compressive strength and strand bond. The goal of this research was to develop an equation that relates strand bond to concrete compressive strength at strand release (approximately 1 day of age) and at 28 days of age, and those equations are presented in this investigation. Strand bond is assessed by measuring the transfer length and development length for prestressed beams cast in the laboratory. In the U.S., strand bond is predicted using transfer length and development length equations provided by the American Concrete Institute (ACI-318) Building Code and American Association of State and Highway Transportation Official (AASHTO) LRFD Bridge Design Specifications which were developed based on the 1950´s investigations. The equations provided by both ACI and AASHTO do not address concrete strength while equations, developed in this investigation, do account for the compressive strength of concrete at release and testing time. Although there has been much research conducted in this matter, this research provides a reliability data analysis relating to transfer and development lengths of prestressed concrete beams. Unlike many of the previous programs, this research includes strands of a known quality, the largest database of test specimens, and a variety of concrete mixtures and concrete strengths. This research concludes with the development of an analytical model to predict transfer length which includes concrete strength at release with fracture propagation around the strand

Bullying y clima escolar en estudiantes del sexto grado de primaria del distrito de Pilcomayo

En el estudio se analiza la relación existente entre el bullying en el status de víctima y el clima escolar percibido en un grupo de 127 estudiantes que cursan estudios regulares en el periodo 2018 en el sexto grado de primaria de instituciones educativas de gestión pública de Pilcomayo. El estudio se caracteriza por alcanzar acotaciones descriptivas y comparativas en torno a los dos factores de análisis. La muestra de estudio fue no probabilística y consideró a 49 mujeres (39%) y 78 varones (61%). Para el análisis contextual de las variables se tomó como fundamento a los planteamientos teóricos derivados del Enfoque Ecológico de Desarrollo Humano Uriel Bronfenbrenner (1979). Los resultados estadísticos tomados como base para el análisis descriptivo dan cuenta de un marcado predominio de estudiantes (tanto varones como mujeres) que han padecido bullying con mediano riesgo. Los factores más críticos observados en este colectivo estudiantil son la agresión verbal y la agresión física directa e indirecta y, con menor incidencia, la exclusión social. En cuanto al clima escolar, la mayoría de estos estudiantes perciben un clima escolar medianamente negativo dentro del centro escolar en el cual cursan sus estudios actualmente. Finalmente, se constató que existe relación inversa y significativa entre el bullying (status de víctima) y el clima escolar percibido por parte de los estudiantes investigados

Probabilistic interval predictor based on dissimilarity functions

This work presents a new methodology to obtain probabilistic interval predictions of a dynamical system. The proposed strategy uses stored past system measurements to estimate the future evolution of the system. The method relies on the use of dissimilarity functions to estimate the conditional probability density function of the outputs. A family of empirical probability density functions, parameterized by means of two scalars, is introduced. It is shown that the proposed family encompasses the multivariable normal probability density function as a particular case. We show that the presented approach constitutes a generalization of classical estimation methods. A validation scheme is used to tune the two parameters on which the methodology relies. In order to prove the effectiveness of the presented methodology, some numerical examples and comparisons are provided.Comment: 10 pages, 3 figure

Una metafísica de la existencia para el siglo XXI

En este ensayo partimos de la pregunta por un pensamiento filosófico a la altura del nuevo siglo que vivimos, es decir, alejado ya de las formulaciones típicas del siglo XX y, en cierta medida, de toda la historia de la filosofía. Se propone así, desde la problemática del sentido y el sinsentido, una filosofía centrada en la noción de “existencia” (en todo su alcance) en cuanto verdad absoluta del pensamiento. Desde esta propuesta se cuestionan las posturas que han hablado de un “retorno a lo religioso” (y del “giro teológico”) abogando por un ateísmo crítico y positivo. Se hace una valoración del contenido ateo de la figura de Cristo como vía para la superación interna de la conciencia religiosa. Todo lo anterior se expone a través del comentario de la obra del filósofo francés Jean-Luc Nancy, así como de algunos otros autores. A manera de conclusión, definimos en cinco puntos tanto las condiciones como las tareas y compromisos básicos de una filosofía renovada acorde con nuestra época

Ontología de la resistencia

A partir del uso político-social del término “resistencia”, este ensayo propone un análisis filosófico del concepto de resistencia a través de ciertos pensadores importantes del pensamiento del siglo XX y lo que va de este siglo. Se analiza así el concepto fenomenológico y ontológico de resistencia en cuanto cualidad ontológica (el Ser es lo que resiste a las determinaciones epistémicas y antropológicas) en Merleau-Ponty y autores recientes vinculados al llamado nuevo realismo o realismo especulativo (Meillassoux, Harman, Ferraris). A través de una recuperación de ideas de Deleuze y Foucault se ofrece un concepto político de resistencia como proceso “primario” respecto al poder, a partir de lo cual se propone una redefinición de la democracia como el poder de resistencia del pueblo

Search-Based Evolution of XML Schemas

The use of schemas makes an XML-based application more reliable, since they contribute to avoid failures by defining the specific format for the data that the application manipulates. In practice, when an application evolves, new requirements for the data may be established, raising the need of schema evolution. In some cases the generation of a schema is necessary, if such schema does not exist. To reduce maintenance and reengineering costs, automatic evolution of schemas is very desirable. However, there are no algorithms to satisfactorily solve the problem. To help in this task, this paper introduces a search-based approach that explores the correspondence between schemas and context-free grammars. The approach is supported by a tool, named EXS. Our tool implements algorithms of grammatical inference based on LL(1) Parsing. If a grammar (that corresponds to a schema) is given and a new word (XML document) is provided, the EXS system infers the new grammar that: i) continues to generate the same words as before and ii) generates the new word, by modifying the original grammar. If no initial grammar is available, EXS is also capable of generating a grammar from scratch from a set of samples

Parámetros productivos de cuyes mejorados en tres densidades de crianza, distrito de Tocache

The objective of the research was to evaluate the adequate space to improve the productive and reproductive parameters of guinea pig breeding; the specific objectives were to evaluate the climatic adaptability, productive parameters and adequate density for the improved lines of Peru, Inti and Creole guinea pigs. 216 guinea pigs were evaluated, using the bioclimatic methodology of temperature, mixed feeding system and different densities of improved and creole guinea pigs in an area of ​​1 m2; the study carried out was of an application type and explanatory level, using the DBCA experimental design (completely randomized block design); The data resulting from the collection of the weight variable and its relationship were processed in the Excel program, through the analysis of variance (ANOVA). Concluding, that the guinea pig of the Peru line relatively responds better to the 3 population densities (5, 6 and 7 guinea pigs) under the conditions of a living space of 1 m2 in the climatic conditions variable; while the guinea pigs of the Inti and Criollo lines at the same densities show better development and growth in relation to weight. Regarding guinea pigs from the Peru and Inti lines, they have shown an average increase in weight of 20 grams and guinea pigs from the Criolla line expressed a weight of 15 grams per week.El objetivo de la investigación fue evaluar el espacio adecuado para mejorar los parámetros productivos y reproductivos de la crianza de cuyes; los objetivos específicos fueron: evaluar la adaptabilidad climática, parámetros productivos y densidad adecuada para las líneas mejoradas de cuyes Perú, Inti y criollo. Se evaluaron 216 cuyes, utilizando la metodología bioclimática de temperatura, sistema de alimentación mixta y diferentes densidades de cuyes mejorados y criollos en un área de 1 m2; el estudio realizado fue de tipo aplicativo y de nivel explicativo, utilizando el diseño experimental DBCA (Diseño bloque completamente al azar); los datos producto de la recopilación de la variable peso y su relación, fueron procesados en el programa Excel, mediante el análisis de varianza (ANOVA). Concluyendo, que el cuy de la línea Perú relativamente responde mejor las 3 densidades poblacionales (5, 6 y 7 cuyes) bajo las condiciones de espacio vital de 1 m2 en la variable condiciones climatológicas; mientras los cuyes de las líneas Inti y Criollo en las mismas densidades muestran mejor desarrollo y crecimiento en relación al peso. En cuanto a cuyes de la línea Perú e Inti han demostrado incremento promedio de peso en 20 gramos y los cuyes de la línea Criolla expresaron peso de 15 gramos por semana

Seasonal changes in the distribution and abundance of marine cladocerans of the Northwest Alboran Sea (Western Mediterranean), Spain

The annual cycle of marine cladocerans was studied over six years from 1994 to 1999 within the frame of the monitoring Project ECOMALAGA at a nine stations in the NW of the Alboran Sea, with the aim of assessing seasonal patterns and interannual trends in distribution and abundance of marine cladocerans. Seven species (Penilia avirostris, Evadne nordmanni, Evadne spinifera, Pseudoevadne tergestina, Pleopis polyphemoides, Podon leuckarti and Podon intermedius) were detected in the northwest Alboran Sea. Total cladoceran relative abundance varied from 0 to 89 % of the total cladocerans. The abundance of cladocerans was higher in summer-autumn than in winter-spring (7012 - 4711.100 and 743 - 217.100m-3 , respectively). The species composition was very different in terms of seasonality. P. polyphemoides, P. leuckarti and P. intermedius appeared mostly during the spring. P. tergestina, E. spinifera and E. nordmanni predominantly occurred during the winter. P. avirostris occurred mostly during the summer and autumn

Machine learning in Alzheimer’s disease genetics

: Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest European consortium on Alzheimer's disease (AD) to investigate the effectiveness of various ML algorithms in replicating known findings, discovering novel loci, and predicting individuals at risk. We utilised Gradient Boosting Machines (GBMs), biological pathway-informed Neural Networks (NNs), and Model-based Multifactor Dimensionality Reduction (MB-MDR) models. ML approaches successfully captured all genome-wide significant genetic variants identified in the training set and 22% of associations from larger meta-analyses. They highlight 6 novel loci which replicate in an external dataset, including variants which map to ARHGAP25, LY6H, COG7, SOD1 and ZNF597. They further identify novel association in AP4E1, refining the genetic landscape of the known SPPL2A locus. Our results demonstrate that machine learning methods can achieve predictive performance comparable to classical approaches in genetic epidemiology and have the potential to uncover novel loci that remain undetected by traditional GWAS. These insights provide a complementary avenue for advancing the understanding of AD genetics