Estudio del valor nutritivo de la melaza para cerdos.

Se presentan los resultados de 3 experimentos de alimentación de cerdos con melaza, realizados con un total de 462 animales en las Granjas Experimentales de Tibaitatá y Palmira. En el experimento 1, realizado en Tibaitatá con su replicación en Palmira, se estudia el efecto de 13, 16 y 19 por ciento de proteína de niveles de 0, 25.5 y 30 por ciento de melaza, sobre el comportamiento de cerdos en crecimiento y acabado. Los resultados indican que cuando la dieta incluye melaza, puede usarse torta de soya como suplemento proteíco para dar un nivel de 13 a 16 por ciento de proteína. La melaza se puede incluír a niveles de 22.5 a 30 por ciento sin afectar los aumentos de peso, reduciendose el costo de producción aunque se aumente la cantidad de alimento. En el experimento 2 se suministra K en la forma de acetato y carbonato en la cantidad que lo contiene un nivel de 30 por ciento de melaza. Ninguna de las formas de suministro del K produjo transtornos gastrointestinales ni afectó los aumentos de peso o la eficiencia alimenticia. En el experimento 3 se estudia cuál de 4 niveles de melaza: 0, 15, 22.5 y 30 por ciento es el más adecuado para incorporar en la dieta para cerdos en crecimiento y acabado. Los niveles de 22.5 y 30 por ciento produjeron los aumentos de peso más económicos. Además al estudiar la doble suplementación de vitaminas del Complejo B se concluye que no mejora la tasa de aumento ni de utilización del alimentoPorcicultur

Nonparametric nonlinear model predictive control

Model Predictive Control (MPC) has recently found wide acceptance in industrial applications, but its potential has been much impeded by linear models due to the lack of a similarly accepted nonlinear modeling or databased technique. Aimed at solving this problem, the paper addresses three issues: (i) extending second-order Volterra nonlinear MPC (NMPC) to higher-order for improved prediction and control; (ii) formulating NMPC directly with plant data without needing for parametric modeling, which has hindered the progress of NMPC; and (iii) incorporating an error estimator directly in the formulation and hence eliminating the need for a nonlinear state observer. Following analysis of NMPC objectives and existing solutions, nonparametric NMPC is derived in discrete-time using multidimensional convolution between plant data and Volterra kernel measurements. This approach is validated against the benchmark van de Vusse nonlinear process control problem and is applied to an industrial polymerization process by using Volterra kernels of up to the third order. Results show that the nonparametric approach is very efficient and effective and considerably outperforms existing methods, while retaining the original data-based spirit and characteristics of linear MPC

Towards understanding the myometrial physiome: approaches for the construction of a virtual physiological uterus

Premature labour (PTL) is the single most significant factor contributing to neonatal morbidity in Europe with enormous attendant healthcare and social costs. Consequently, it remains a major challenge to alleviate the cause and impact of this condition. Our ability to improve the diagnosis and treatment of women most at risk of PTL is, however, actually hampered by an incomplete understanding of the ways in which the functions of the uterine myocyte are integrated to effect an appropriate biological response at the multicellular whole organ system. The level of organization required to co-ordinate labouring uterine contractile effort in time and space can be considered immense. There is a multitude of what might be considered mini-systems involved, each with their own regulatory feedback cycles, yet they each, in turn, will influence the behaviour of a related system. These include, but are not exclusive to, gestational-dependent regulation of transcription, translation, post-translational modifications, intracellular signaling dynamics, cell morphology, intercellular communication and tissue level morphology. We propose that in order to comprehend how these mini-systems integrate to facilitate uterine contraction during labour (preterm or term) we must, in concert with biological experimentation, construct detailed mathematical descriptions of our findings. This serves three purposes: firstly, providing a quantitative description of series of complex observations; secondly, proferring a database platform that informs further testable experimentation; thirdly, advancing towards the establishment of a virtual physiological uterus and in silico clinical diagnosis and treatment of PTL

Utilización de torta (harina) de algodón en alimentación de cerdos.

Información básica y aplicada sobre este efecto. En la primera parte se discuten aspectos generales sobre el valor nutritivo y análisis químico de los diferentes tipos de torta de algodón disponibles en latinoamérica. En la segunda parte se analizan en forma resumida los resultados de evaluaciones nutritivas durante las distintas fases de producción en cerdos, presentando alternativas con raciones a base de torta de algodón como fuente proteínica para cerdos en crecimiento, acabado, gestación y lactancia. Se concluye que: la torta de algodón es una fuente abundante de proteína vegetal en la mayoría de los países latinoamericanos, siendo gran parte de este subproducto de baja calidad debido a deficiente procesamiento industrial. Para cerdos con menos de 50 kg de peso no debe utilizarse un nivel superior al 10 por ciento de la torta en la ración, cuando se presente más del 0.2 por ciento de gosipol libre y más del 10 por ciento de fibra cruda. Raciones con más del 10 por ciento de torta generalmente producen resultados satisfactorios en cerdos adultos. Para cerdos en cabado se recomienda la adición de sulfato ferroso cuando la concentración de gosipol libre en la ración total sea superior al 0.03 por ciento. La deficiencia de lisina en raciones para cerdos jóvenes se puede subsanar utilizando el aminoácido sintético o productos ricos en lisina. Por medio de un procesamiento adecuado se puede obtener torta de algodón de buena calidad con precios menores entre 20 y 50 por ciento con respecto a otras fuentes proteínicas convencionalesAlgodón-Gossypium herbaceu

Subproductos de la caña de azúcar en la nutrición porcina.

Se presenta una análisis sobre las investigaciones más recientes en latinoamérica relacionadas con el uso de subproductos de la caña de azúcar en nutrición de cerdos. Tanto el azúcar como los diversos tipos de melaza son fuentes ricas en carbohidratos, que con suplementación adecuada, pueden reemplazar ventajosamente gran parte de los granos de cereales empleados. Los niveles de melaza superiores al 15 por ciento en crecimiento y al 20 por ciento en acabado ocasionan un ligero efecto laxante, que se acentúa a medida que aumenta el porcentaje en la ración. Con niveles bajos de melaza, 15 y 20 por ciento, no se observa disminución en el rendimiento en peso de los cerdos, afectándose ligeramente la conversión alimenticia, pero con niveles altos, de 40 a 50 por ciento, se afectan en forma negativa el rendimiento en peso y la conversión alimenticia. La toleancia a la melaza aumenta a la medida que los cerdos tienen más peso. Se recomiendan niveles de 5 a 10 por ciento en cerdos de 15 a 20 kg de peso, terminando con niveles de 30 a 40 por ciento en cerdos de 90 a 100 kg de peso. Las hembras gestantes y lactantes toleran porcentajes altos de melaza en la ración sin presentarse efectos adversos en el rendimiento reproductivo. El azúcar también utilizado exitosamente como fuente de carbohidratos en la dieta. El azúcar es un producto de alta concentración energética que no ocasiona el efecto laxante de la melaza, pudiéndose utilizar en porcentajes elevados con cerdos de todas las edades, con efectos excelentes en el rendimiento. La principal limitación para utilizar el azúcar radica en el alto costo del product

1964: Abilene Christian College Bible Lectures - Full Text

LEADERSHIP IN THE CHURCH” Being the Abilene Christian College Annual Bible Lectures 1964 Price: $3.95 Published by ABILENE CHRISTIAN COLLEGE STUDENTS EXCHANGE ACC Station Abilene, Texa

Prediction of Preterm Deliveries from EHG Signals Using Machine Learning

There has been some improvement in the treatment of preterm infants, which has helped to increase their chance of survival. However, the rate of premature births is still globally increasing. As a result, this group of infants are most at risk of developing severe medical conditions that can affect the respiratory, gastrointestinal, immune, central nervous, auditory and visual systems. In extreme cases, this can also lead to long-term conditions, such as cerebral palsy, mental retardation, learning difficulties, including poor health and growth. In the US alone, the societal and economic cost of preterm births, in 2005, was estimated to be $26.2 billion, per annum. In the UK, this value was close to £2.95 billion, in 2009. Many believe that a better understanding of why preterm births occur, and a strategic focus on prevention, will help to improve the health of children and reduce healthcare costs. At present, most methods of preterm birth prediction are subjective. However, a strong body of evidence suggests the analysis of uterine electrical signals (Electrohysterography), could provide a viable way of diagnosing true labour and predict preterm deliveries. Most Electrohysterography studies focus on true labour detection during the final seven days, before labour. The challenge is to utilise Electrohysterography techniques to predict preterm delivery earlier in the pregnancy. This paper explores this idea further and presents a supervised machine learning approach that classifies term and preterm records, using an open source dataset containing 300 records (38 preterm and 262 term). The synthetic minority oversampling technique is used to oversample the minority preterm class, and cross validation techniques, are used to evaluate the dataset against other similar studies. Our approach shows an improvement on existing studies with 96% sensitivity, 90% specificity, and a 95% area under the curve value with 8% global error using the polynomial classifier

Position resolution and particle identification with the ATLAS EM calorimeter

In the years between 2000 and 2002 several pre-series and series modules of the ATLAS EM barrel and end-cap calorimeter were exposed to electron, photon and pion beams. The performance of the calorimeter with respect to its finely segmented first sampling has been studied. The polar angle resolution has been found to be in the range 50-60 mrad/sqrt(E (GeV)). The neutral pion rejection has been measured to be about 3.5 for 90% photon selection efficiency at pT=50 GeV/c. Electron-pion separation studies have indicated that a pion fake rate of (0.07-0.5)% can be achieved while maintaining 90% electron identification efficiency for energies up to 40 GeV.Comment: 32 pages, 22 figures, to be published in NIM

Energy Linearity and Resolution of the ATLAS Electromagnetic Barrel Calorimeter in an Electron Test-Beam

A module of the ATLAS electromagnetic barrel liquid argon calorimeter was exposed to the CERN electron test-beam at the H8 beam line upgraded for precision momentum measurement. The available energies of the electron beam ranged from 10 to 245 GeV. The electron beam impinged at one point corresponding to a pseudo-rapidity of eta=0.687 and an azimuthal angle of phi=0.28 in the ATLAS coordinate system. A detailed study of several effects biasing the electron energy measurement allowed an energy reconstruction procedure to be developed that ensures a good linearity and a good resolution. Use is made of detailed Monte Carlo simulations based on Geant which describe the longitudinal and transverse shower profiles as well as the energy distributions. For electron energies between 15 GeV and 180 GeV the deviation of the measured incident electron energy over the beam energy is within 0.1%. The systematic uncertainty of the measurement is about 0.1% at low energies and negligible at high energies. The energy resolution is found to be about 10% sqrt(E) for the sampling term and about 0.2% for the local constant term

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal