953 resultados para non-content method
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One of the outstanding problems of the modelling of temperate ice dynamics is the limited knowledge on the rheology of temperate ice and, in particular, on how the rate factor depends on the liquid water content. Though it is well known that the rate factor depends strongly on the water content, in practice the only available experimentally-based relationship is that by Duval (1977), which is only valid for water contents up to 1%. However, actual water contents found in temperate and polythermal glaciers are sometimes substantially larger.
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This paper proposes a novel combination of artificial intelligence planning and other techniques for improving decision-making in the context of multi-step multimedia content adaptation. In particular, it describes a method that allows decision-making (selecting the adaptation to perform) in situations where third-party pluggable multimedia conversion modules are involved and the multimedia adaptation planner does not know their exact adaptation capabilities. In this approach, the multimedia adaptation planner module is only responsible for a part of the required decisions; the pluggable modules make additional decisions based on different criteria. We demonstrate that partial decision-making is not only attainable, but also introduces advantages with respect to a system in which these conversion modules are not capable of providing additional decisions. This means that transferring decisions from the multi-step multimedia adaptation planner to the pluggable conversion modules increases the flexibility of the adaptation. Moreover, by allowing conversion modules to be only partially described, the range of problems that these modules can address increases, while significantly decreasing both the description length of the adaptation capabilities and the planning decision time. Finally, we specify the conditions under which knowing the partial adaptation capabilities of a set of conversion modules will be enough to compute a proper adaptation plan.
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Many image processing methods, such as techniques for people re-identification, assume photometric constancy between different images. This study addresses the correction of photometric variations based upon changes in background areas to correct foreground areas. The authors assume a multiple light source model where all light sources can have different colours and will change over time. In training mode, the authors learn per-location relations between foreground and background colour intensities. In correction mode, the authors apply a double linear correction model based on learned relations. This double linear correction includes a dynamic local illumination correction mapping as well as an inter-camera mapping. The authors evaluate their illumination correction by computing the similarity between two images based on the earth mover's distance. The authors compare the results to a representative auto-exposure algorithm found in the recent literature plus a colour correction one based on the inverse-intensity chromaticity. Especially in complex scenarios the authors’ method outperforms these state-of-the-art algorithms.
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The Actively Heated Fiber Optic (AHFO) method is shown to be capable of measuring soil water content several times per hour at 0.25 m spacing along cables of multiple kilometers in length. AHFO is based on distributed temperature sensing (DTS) observation of the heating and cooling of a buried fiber-optic cable resulting from an electrical impulse of energy delivered from the steel cable jacket. The results presented were collected from 750 m of cable buried in three 240 m colocated transects at 30, 60, and 90 cm depths in an agricultural field under center pivot irrigation. The calibration curve relating soil water content to the thermal response of the soil to a heat pulse of 10 W m−1 for 1 min duration was developed in the lab. This calibration was found applicable to the 30 and 60 cm depth cables, while the 90 cm depth cable illustrated the challenges presented by soil heterogeneity for this technique. This method was used to map with high resolution the variability of soil water content and fluxes induced by the nonuniformity of water application at the surface.
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We present here an information reconciliation method and demonstrate for the first time that it can achieve efficiencies close to 0.98. This method is based on the belief propagation decoding of non-binary LDPC codes over finite (Galois) fields. In particular, for convenience and faster decoding we only consider power-of-two Galois fields.
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A new method has recently been proposed by us for accurate measurement of the solar cell temperature in any operational regime, in particular, at a maximum power point (MPP) of the I-V curve (T-p-n(MPP)). For this, fast switching of a cell from MPP to open circuit (OC) regime is carried out and open circuit voltage V-oc is measured immediately (within about 1 millisecond), so that this value becomes to be an indicator of T-p-n(MPP). In the present work, we have considered a practical case, when a solar cell is heated not only by absorption of light incident upon its surface (called "photoactive" absorption of power), but also by heat transferred from structural elements surrounding the cell and heated by absorption of direct or diffused sunlight ("non-photoactive" absorption of power with respect to a solar cell). This process takes place in any concentrator module with non-ideal concentrators. Low overheating temperature of the p-n junction (or p-n junctions in a multijunction cell) is a cumulative parameter characterizing the quality of a solar module by the factor of heat removal effectiveness and, at the same time, by the factor of low "non-photoactive" losses.
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Los objetivos de esta tesis fueron 1) obtener y validar ecuaciones de predicción para determinar in vivo la composición corporal y de la canal de conejos en crecimiento de 25 a 77 días de vida utilizando la técnica de la Impedancia Bioeléctrica (BIA), y 2) evaluar su aplicación para determinar diferencias en la composición corporal y de la canal, así como la retención de nutrientes de animales alimentados con diferentes fuentes y niveles de grasa. El primer estudio se realizó para determinar y después validar, usando datos independientes, las ecuaciones de predicción obtenidas para determinar in vivo la composición corporal de los conejos en crecimiento. Se utilizaron 150 conejos a 5 edades distintas (25, 35, 49, 63 y 77 días de vida), con un rango de pesos entre 231 y 3138 g. Para determinar los valores de resistencia (Rs,) and reactancia (Xc,) se usó un terminal (Model BIA-101, RJL Systems, Detroit, MI USA) con cuatro electrodos. Igualmente se registró la distancia entre electrodos internos (D), la longitud corporal (L) y el peso vivo (PV) de cada animal. En cada edad, los animales fueron molidos y congelados (-20 ºC) para su posterior análisis químico (MS, grasa, proteína, cenizas y EB). El contenido en grasa y energía de los animales se incrementó, mientras que los contenidos en proteína, cenizas y agua de los animales disminuyeron con la edad. Los valores medios de Rs, Xc, impedancia (Z), L y D fueron 83.5 ± 23.1 , 18.2 ± 3.8 , 85.6 ± 22.9 , 30.6 ± 6.9 cm y 10.8 ± 3.1 cm. Se realizó un análisis de regresión lineal múltiple para determinar las ecuaciones de predicción, utilizando los valores de PV, L and Z como variables independientes. Las ecuaciones obtenidas para estimar los contenidos en agua (g), PB (g), grasa (g), cenizas (g) and EB (MJ) tuvieron un coeficiente de determinación de (R2) de 0.99, 0.99, 0.97, 0.98 y 0.99, y los errores medios de predicción relativos (EMPR) fueron: 2.79, 6.15, 24.3, 15.2 y 10.6%, respectivamente. Cuando el contenido en agua se expresó como porcentaje, los valores de R2 y EMPR fueron 0.85 and 2.30%, respectivamente. Al predecir los contenidos en proteína (%MS), grasa (%MS), cenizas (%MS) y energía (kJ/100 g MS), se obtuvieron valores de 0.79, 0.83, 0.71 y 0.86 para R2, y 5.04, 18.9, 12.0 y 3.19% para EMPR. La reactancia estuvo negativamente correlacionada con el contenido en agua, cenizas y PB (r = -0.32, P < 0.0001; r = -0.20, P < 0.05; r = -0.26, P < 0.01) y positivamente correlacionada con la grasa y la energía (r = 0.23 y r = 0.24; P < 0.01). Sin embargo, Rs estuvo positivamente correlacionada con el agua, las cenizas y la PB (r = 0.31, P < 0.001; r = 0.28, P < 0.001; r = 0.37, P < 0.0001) y negativamente con la grasa y la energía (r = -0.36 y r = -0.35; P < 0.0001). Igualmente la edad estuvo negativamente correlacionada con el contenido en agua, cenizas y proteína (r = -0.79; r = -0.68 y r = -0.80; P < 0.0001) y positivamente con la grasa y la energía (r = 0.78 y r = 0.81; P < 0.0001). Se puede concluir que el método BIA es una técnica buena y no invasiva para estimar in vivo la composición corporal de conejos en crecimiento de 25 a 77 días de vida. El objetivo del segundo estudio fue determinar y validar con datos independientes las ecuaciones de predicción obtenidas para estimar in vivo la composición de la canal eviscerada mediante el uso de BIA en un grupo de conejos de 25 a 77 días, así como testar su aplicación para predecir la retención de nutrientes y calcular las eficacias de retención de la energía y del nitrógeno. Se utilizaron 75 conejos agrupados en 5 edades (25, 35, 49, 63 y 77 días de vida) con unos pesos que variaron entre 196 y 3260 g. Para determinar los valores de resistencia (Rs, ) y reactancia (Xc, ) se usó un terminal (Model BIA-101, RJL Systems, Detroit, MI USA) con cuatro electrodos. Igualmente se registró la distancia entre electrodos internos (D), la longitud corporal (L) y el peso vivo (PV) del cada animal. En cada edad, los animales fueron aturdidos y desangrados. Su piel, vísceras y contenido digestivo fueron retirados, y la canal oreada fue pesada y molida para posteriores análisis (MS, grasa, PB, cenizas y EB). Los contenidos en energía y grasa aumentaron mientras que los de agua, cenizas y proteína disminuyeron con la edad. Los valores medios de Rs, Xc, impedancia (Z), L y D fueron 95.9±23.9 , 19.5±4.7 , 98.0±23.8 , 20.6±6.3 cm y 13.7±3.1 cm. Se realizó un análisis de regresión linear múltiple para determinar las ecuaciones de predicción, utilizando los valores de PV, L and Z como variables independientes. Los coeficientes de determinación (R2) de las ecuaciones obtenidas para estimar los contenidos en agua (g), PB (g), grasa (g), cenizas (g) and EB (MJ) fueron: 0.99, 0.99, 0.95, 0.96 y 0.98, mientras que los errores medios de predicción relativos (EMPR) fueron: 4.20, 5.48, 21.9, 9.10 y 6.77%, respectivamente. Cuando el contenido en agua se expresó como porcentaje, los valores de R2 y EMPR fueron 0.79 y 1.62%, respectivamente. Cuando se realizó la predicción de los contenidos en proteína (%MS), grasa (%MS), cenizas (%MS) y energía (kJ/100 g MS), los valores de R2 fueron 0.68, 0.76, 0.66 and 0.82, y los de RMPE: 3.22, 10.5, 5.82 and 2.54%, respectivamente. La reactancia estuvo directamente correlacionada con el contenido en grasa (r = 0.24, P < 0.05), mientras que la resistencia guardó una correlación positiva con los contenidos en agua, cenizas y proteína (r = 0.55, P < 0.001; r = 0.54, P < 0.001; r = 0.40, P < 0.005) y negativa con la grasa y la energía (r = -0.44 y r = -0.55; P < 0.001). Igualmente la edad estuvo negativamente correlacionada con los contenidos en agua, cenizas y PB (r = -0.94; r = -0.85 y r = -0.75; P < 0.0001) y positivamente con la grasa y la energía (r = 0.89 y r = 0.90; P < 0.0001). Se estudió la eficacia global de retención de la energía (ERE) y del nitrógeno (ERN) durante todo el periodo de cebo (35-63 d), Los valores de ERE fueron 20.4±7.29%, 21.0±4.18% and 20.8±2.79% en los periodos 35 a 49, 49 a 63 y 35 a 63 d, respectivamente. ERN fue 46.9±11.7%, 34.5±7.32% y 39.1±3.23% para los mismos periodos. La energía fue retenida en los tejidos para crecimiento con una eficiencia del 52.5% y la eficiencia de retención de la energía como proteína y grasa fue de 33.3 y 69.9% respectivamente. La eficiencia de utilización del nitrógeno para crecimiento fue cercana al 77%. Este trabajo muestra como el método BIA es técnica buena y no invasiva para determinar in vivo la composición de la canal y la retención de nutrientes en conejos en crecimiento de 25 a 77 días de vida. En el tercer estudio, se llevaron a cabo dos experimentos con el fin de investigar los efectos del nivel de inclusión y de la fuente de grasa, sobre los rendimientos productivos, la mortalidad, la retención de nutrientes y la composición corporal total y de la canal eviscerada de conejos en crecimiento de 34 a 63 d de vida. En el Exp. 1 se formularon 3 dietas con un diseño experimental factorial 3 x 2 con el tipo de grasa utilizada: Aceite de Soja (SBO), Lecitinas de Soja (SLO) y Manteca (L) y el nivel de inclusión (1.5 y 4%) como factores principales. El Exp. 2 también fue diseñado con una estructura factorial 3 x 2, pero usando SBO, Aceite de Pescado (FO) y Aceite de Palmiste como fuentes de grasa, incluidas a los mismos niveles que en el Exp. 1. En ambos experimentos 180 animales fueron alojados en jaulas individuales (n=30) y 600 en jaulas colectivas en grupos de 5 animales (n=20). Los animales alimentados con un 4% de grasa añadida tuvieron unos consumos diarios y unos índices de conversión más bajos que aquellos alimentados con las dietas con un 1.5% de grasa. En los animales alojados en colectivo del Exp. 1, el consumo fue un 4.8% más alto en los que consumieron las dietas que contenían manteca que en los animales alimentados con las dietas SBO (P = 0.036). La inclusión de manteca tendió a reducir la mortalidad (P = 0.067) en torno al 60% y al 25% con respecto a las dietas con SBO y SLO, respectivamente. La mortalidad aumentó con el nivel máximo de inclusión de SLO (14% vs. 1%, P < 0.01), sin observarse un efecto negativo sobre la mortalidad con el nivel más alto de inclusión de las demás fuentes de grasa utilizadas. En los animales alojados colectivo del Exp. 2 se encontró una disminución del consumo (11%), peso vivo a 63 d (4.8%) y de la ganancia diaria de peso (7.8%) con la inclusión de aceite de pescado con respecto a otras dietas (P < 0.01). Los dos últimos parámetros se vieron especialmente más reducidos cuando en las dietas se incluyó el nivel más alto de FO (5.6 y 9.5%, respectivamente, (P < 0.01)). Los animales alojados individualmente mostraron unos resultados productivos muy similares. La inclusión de aceite pescado tendió (P = 0.078) a aumentar la mortalidad (13.2%) con respecto al aceite de palmiste (6.45%), siendo intermedia para las dietas que contenían SBO (8.10%). La fuente o el nivel de grasa no afectaron la composición corporal total o de la canal eviscerada de los animales. Un incremento en el nivel de grasa dio lugar a una disminución de la ingesta de nitrógeno digestible (DNi) (1.83 vs. 1.92 g/d; P = 0.068 en Exp. 1 y 1.79 vs. 1.95 g/d; P = 0.014 en Exp. 2). Debido a que el nitrógeno retenido (NR) en la canal fue similar para ambos niveles (0.68 g/d (Exp. 1) y 0.71 g/d (Exp. 2)), la eficacia total de retención del nitrógeno (ERN) aumentó con el nivel máximo de inclusión de grasa, pero de forma significativa únicamente en el Exp. 1 (34.9 vs. 37.8%; P < 0.0001), mientras que en el Exp. 2 se encontró una tendencia (36.2 vs. 38.0% en Exp. 2; P < 0.064). Como consecuencia, la excreción de nitrógeno en heces fue menor en los animales alimentados con el nivel más alto de grasa (0.782 vs. 0.868 g/d; P = 0.0001 en Exp. 1, y 0.745 vs. 0.865 g/d; P < 0.0001 en Exp.2) al igual que el nitrógeno excretado en orina (0.702 vs. 0.822 g/d; P < 0.0001 en Exp. 1 y 0.694 vs. 0.7999 g/d; P = 0.014 en Exp.2). Aunque no hubo diferencias en la eficacia total de retención de la energía (ERE), la energía excretada en heces disminuyó al aumentar el nivel de inclusión de grasa (142 vs. 156 Kcal/d; P = 0.0004 en Exp. 1 y 144 vs. 154 g/d; P = 0.050 en Exp. 2). Sin embargo, la energía excretada como orina y en forma de calor fue mayor en el los animales del Exp. 1 alimentados con el nivel más alto de grasa (216 vs. 204 Kcal/d; P < 0.017). Se puede concluir que la manteca y el aceite de palmiste pueden ser considerados como fuentes alternativas al aceite de soja debido a la reducción de la mortalidad, sin efectos negativos sobre los rendimientos productivos o la retención de nutrientes. La inclusión de aceite de pescado empeoró los rendimientos productivos y la mortalidad durante el periodo de crecimiento. Un aumento en el nivel de grasa mejoró el índice de conversión y la eficacia total de retención de nitrógeno. ABSTRACT The aim of this Thesis is: 1) to obtain and validate prediction equations to determine in vivo whole body and carcass composition using the Bioelectrical Impedance (BIA) method in growing rabbits from 25 to 77 days of age, and 2) to study its application to determine differences on whole body and carcass chemical composition, and nutrient retention of animals fed different fat levels and sources. The first study was conducted to determine and later validate, by using independent data, the prediction equations obtained to assess in vivo the whole body composition of growing rabbits. One hundred and fifty rabbits grouped at 5 different ages (25, 35, 49, 63 and 77 days) and weighing from 231 to 3138 g were used. A four terminal body composition analyser was used to obtain resistance (Rs, ) and reactance (Xc, ) values (Model BIA-101, RJL Systems, Detroit, MI USA). The distance between internal electrodes (D, cm), body length (L, cm) and live BW of each animal were also registered. At each selected age, animals were slaughtered, ground and frozen (-20 ºC) for later chemical analyses (DM, fat, CP, ash and GE). Fat and energy body content increased with the age, while protein, ash, and water decreased. Mean values of Rs, Xc, impedance (Z), L and D were 83.5 ± 23.1 , 18.2 ± 3.8 , 85.6 ± 22.9 , 30.6 ± 6.9 cm and 10.8 ± 3.1 cm. A multiple linear regression analysis was used to determine the prediction equations, using BW, L and Z data as independent variables. Equations obtained to estimate water (g), CP (g), fat (g), ash (g) and GE (MJ) content had, respectively, coefficient of determination (R2) values of 0.99, 0.99, 0.97, 0.98 and 0.99, and the relative mean prediction error (RMPE) was: 2.79, 6.15, 24.3, 15.2 and 10.6%, respectively. When water was expressed as percentage, the R2 and RMPE were 0.85 and 2.30%, respectively. When prediction of the content of protein (%DM), fat (%DM), ash (%DM) and energy (kJ/100 g DM) was done, values of 0.79, 0.83, 0.71 and 0.86 for R2, and 5.04, 18.9, 12.0 and 3.19% for RMPE, respectively, were obtained. Reactance was negatively correlated with water, ash and CP content (r = -0.32, P < 0.0001; r = -0.20, P < 0.05; r = -0.26, P < 0.01) and positively correlated with fat and GE (r = 0.23 and r = 0.24; P < 0.01). Otherwise, resistance was positively correlated with water, ash and CP (r = 0.31, P < 0.001; r = 0.28, P < 0.001; r = 0.37, P < 0.0001) and negatively correlated with fat and energy (r = -0.36 and r = -0.35; P < 0.0001). Moreover, age was negatively correlated with water, ash and CP content (r = -0.79; r = -0.68 and r = -0.80; P < 0.0001) and positively correlated with fat and energy (r = 0.78 and r = 0.81; P < 0.0001). It could be concluded that BIA is a non-invasive good method to estimate in vivo whole body composition of growing rabbits from 25 to 77 days of age. The aim of the second study was to determine and validate with independent data, the prediction equations obtained to estimate in vivo carcass composition of growing rabbits by using the results of carcass chemical composition and BIA values in a group of rabbits from 25 to 77 days. Also its potential application to predict nutrient retention and overall energy and nitrogen retention efficiencies was analysed. Seventy five rabbits grouped at 5 different ages (25, 35, 49, 63 and 77 days) with weights ranging from 196 to 3260 g were used. A four terminal body composition analyser (Model BIA-101, RJL Systems, Detroit, MI USA) was used to obtain resistance (Rs, ) and reactance (Xc, ) values. The distance between internal electrodes (D, cm), body length (L, cm) and live weight (BW, g) were also registered. At each selected age, all the animals were stunned and bled. The skin, organs and digestive content were removed, and the chilled carcass were weighed and processed for chemical analyses (DM, fat, CP, ash and GE). Energy and fat increased with the age, while CP, ash, and water decreased. Mean values of Rs, Xc, impedance (Z), L and D were 95.9±23.9 , 19.5±4.7 , 98.0±23.8 , 20.6±6.3 cm y 13.7±3.1 cm. A multiple linear regression analysis was done to determine the equations, using BW, L and Z data as parameters. Coefficient of determination (R2) of the equations obtained to estimate water (g), CP (g), fat (g), ash (g) and GE (MJ) content were: 0.99, 0.99, 0.95, 0.96 and 0.98, and relative mean prediction error (RMPE) were: 4.20, 5.48, 21.9, 9.10 and 6.77%, respectively. When water content was expressed as percentage, the R2 and RMPE were 0.79 and 1.62%, respectively. When prediction of protein (%DM), fat (%DM), ash (%DM) and energy (kJ/100 g DM) content was done, R2 values were 0.68, 0.76, 0.66 and 0.82, and RMPE: 3.22, 10.5, 5.82 and 2.54%, respectively. Reactance was positively correlated with fat content (r = 0.24, P < 0.05) while resistance was positively correlated with water, ash and protein carcass content (r = 0.55, P < 0.001; r = 0.54, P < 0.001; r = 0.40, P < 0.005) and negatively correlated with fat and energy (r = -0.44 and r = -0.55; P < 0.001). Moreover, age was negatively correlated with water, ash and CP content (r = -0.97, r = -0.95 and r = -0.89, P < 0.0001) and positively correlated with fat and GE (r = 0.95 and r = 0.97; P < 0.0001). In the whole growing period (35-63 d), overall energy retention efficiency (ERE) and nitrogen retention efficiency (NRE) were studied. The ERE values were 20.4±7.29%, 21.0±4.18% and 20.8±2.79%, from 35 to 49, 49 to 63 and from 35 to 63 d, respectively. NRE was 46.9±11.7%, 34.5±7.32% and 39.1±3.23% for the same periods. Energy was retained in body tissues for growth with an efficiency of approximately 52.5% and efficiency of the energy for protein and fat retention was 33.3 and 69.9%, respectively. Efficiency of utilization of nitrogen for growth was near to 77%. This work shows that BIA it’s a non-invasive and good method to estimate in vivo carcass composition and nutrient retention of growing rabbits from 25 to 77 days of age. In the third study, two experiments were conducted to investigate the effect of the fat addition and source, on performance, mortality, nutrient retention, and the whole body and carcass chemical composition of growing rabbits from 34 to 63 d. In Exp. 1 three diets were arranged in a 3 x 2 factorial structure with the source of fat: Soybean oil (SBO), Soya Lecithin Oil (SLO) and Lard (L) and the dietary fat inclusion level (1.5 and 4%) as the main factors. Exp. 2 had also arranged as a 3 x 2 factorial design, but using SBO, Fish Oil (FO) and Palmkernel Oil (PKO) as fat sources, and included at the same levels than in Exp. 1. In both experiments 180 animals were allocated in individual cages (n=30) and 600 in collectives cages, in groups of 5 animals (n=20). Animals fed with 4% dietary fat level showed lower DFI and FCR than those fed diets with 1.5%. In collective housing of Exp. 1, DFI was a 4.8% higher in animals fed with diets containing lard than SBO (P = 0.036), being intermediate for diet with SLO. Inclusion of lard also tended to reduce mortality (P = 0.067) around 60% and 25% with respect SBO and SLO diets, respectively. Mortality increased with the greatest level of soya lecithin (14% vs. 1%, P < 0.01). In Exp. 2 a decrease of DFI (11%), BW at 63 d (4.8%) and DWG (7.8%) were observed with the inclusion of fish oil with respect the other two diets (P < 0.01). These last two traits impaired with the highest level of fish oil (5.6 and 9.5%, respectively, (P < 0.01)). Animals housed individually showed similar performance results. The inclusion of fish oil also tended to increase (P = 0.078) mortality (13.2%) with respect palmkernel oil (6.45%), being mortality of SBO intermediate (8.10%). Fat source and level did not affect the whole body or carcass chemical composition. An increase of the fat sources addition led to a decrease of the digestible nitrogen intake (DNi) (1.83 vs. 1.92 g/d; P = 0.068 in Exp. 1 and 1.79 vs. 1.95 g/d; P = 0.014 in Exp. 2). As the nitrogen retained (NR) in the carcass was similar for both fat levels (0.68 g/d (Exp. 1) and 0.71 g/d (Exp. 2)), the overall efficiency of N retention (NRE) increased with the highest level of fat, but only reached significant level in Exp. 1 (34.9 vs. 37.8%; P < 0.0001), while in Exp. 2 a tendency was found (36.2 vs. 38.0% in Exp. 2; P < 0.064). Consequently, nitrogen excretion in faeces was lower in animals fed with the highest level of fat (0.782 vs. 0.868 g/d; P = 0.0001 in Exp. 1, and 0.745 vs. 0.865 g/d; P < 0.0001 in Exp.2). The same effect was observed with the nitrogen excreted as urine (0.702 vs. 0.822 g/d; P < 0.0001 in Exp. 1 and 0.694 vs. 0.7999 g/d; P = 0.014 in Exp.2). Although there were not differences in ERE, the energy excreted in faeces decreased as fat level increased (142 vs. 156 Kcal/d; P = 0.0004 in Exp. 1 and 144 vs. 154 g/d; P = 0.050 in Exp. 2). In Exp. 1 the energy excreted as urine and heat production was significantly higher when animals were fed with the highest level of dietary fat (216 vs. 204 Kcal/d; P < 0.017). It can be concluded that lard and palmkernel oil can be considered as alternative sources to soybean oil due to the reduction of the mortality, without negative effects on performances or nutrient retention. Inclusion of fish impaired animals´ productivity and mortality. An increase of the dietary fat level improved FCR and overall protein efficiency retention.
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This paper presents a new selective and non-directional protection method to detect ground faults in neutral isolated power systems. The new proposed method is based on the comparison of the rms value of the residual current of all the lines connected to a bus, and it is able to determine the line with ground defect. Additionally, this method can be used for the protection of secondary substation. This protection method avoids the unwanted trips produced by wrong settings or wiring errors, which sometimes occur in the existing directional ground fault protections. This new method has been validated through computer simulations and experimental laboratory tests.
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Since the beginning of 3D computer vision problems, the use of techniques to reduce the data to make it treatable preserving the important aspects of the scene has been necessary. Currently, with the new low-cost RGB-D sensors, which provide a stream of color and 3D data of approximately 30 frames per second, this is getting more relevance. Many applications make use of these sensors and need a preprocessing to downsample the data in order to either reduce the processing time or improve the data (e.g., reducing noise or enhancing the important features). In this paper, we present a comparison of different downsampling techniques which are based on different principles. Concretely, five different downsampling methods are included: a bilinear-based method, a normal-based, a color-based, a combination of the normal and color-based samplings, and a growing neural gas (GNG)-based approach. For the comparison, two different models have been used acquired with the Blensor software. Moreover, to evaluate the effect of the downsampling in a real application, a 3D non-rigid registration is performed with the data sampled. From the experimentation we can conclude that depending on the purpose of the application some kernels of the sampling methods can improve drastically the results. Bilinear- and GNG-based methods provide homogeneous point clouds, but color-based and normal-based provide datasets with higher density of points in areas with specific features. In the non-rigid application, if a color-based sampled point cloud is used, it is possible to properly register two datasets for cases where intensity data are relevant in the model and outperform the results if only a homogeneous sampling is used.
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Mode of access: Internet.
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Thesis (Ph.D.)--University of Washington, 2016-06