“Caracterización de los sistemas de producción de ovinos de pelo en el suroeste del departamento de Matagalpa 2010”

Con el objetivo de caracterizar los sistemas de producción de ovinos de pelo en el territorio suroeste del departamento de Matagalpa 2010. (Sébaco, Ciudad Darío, San Isidro y Matagalpa). Se aplicó una encuesta a 103 productores que poseen ovinos de pelo, la muestra se definió aleatoriamente utilizando la ecuación planteada por Scheaffer (1987), se utilizó la técnica de muestreo de bola de nieve, planteada por Frey et al (2000). Esta investigación permitió conocer las debilidades y oportunidades en los sistemas de explotación de esta especie promisoria para la zona seca del país. Con los resultados obtenidos de las encuestas se procedió ha elaborar una base de datos en el programa SPSS versión 11.5 en español. Encontrando un predominio del sexo femenino como titulares de las explotaciones ovinas, 58.3% cursó educación primaria, el 98% de las explotaciones cuentan con raza pelibuey, el 100% de las explotaciones realizan destete y monta de forma natural, una media de mortalidad de corderos de 1, alimentan a las ovejas con potrero sin división (81.6%), se suministra pasto de corte, pastoreo, leguminosas y se suplementa sal común 49.5%, aplican vacunas contra ántrax y pierna negra (63.1%), desparasitaciones internas y externas (66%), ambos con una frecuencia de 2 veces al año, en el manejo productivo no se lleva control en la actividad ovina (100%), los equipo e instalaciones son rústicas, los corrales ovinos el son elaborados con alambre y/o madera, techado con plástico y/o zinc (49.51%), en cuanto a asistencia técnica el 58.3% ha recibid

The overall architecture of the Inception-ResNet network.

<p>The overall architecture of the Inception-ResNet network.</p

Preservation of the primordial follicle pool in Oo<i>Pten</i>^−/− ovaries by rapamycin treatment.

<p>(<b>A</b>) Prevention of the primordial follicle over-activation in Oo<i>Pten</i>^−/− mice by treatment with rapamycin. Rapamycin (5 mg/kg body weight) was injected daily into Oo<i>Pten</i>^−/− mice from postnatal day (PD) 4 to PD 22, and the ovaries were collected at PD 23 for morphological analysis. Ovaries from rapamycin-treated Oo<i>Pten</i>^−/− mice appeared smaller (c) than the ovaries from vehicle-treated Oo<i>Pten</i>^−/− mice (a). Scale bar = 50 µm. Clusters of primordial follicles were seen in rapamycin-treated Oo<i>Pten</i>^−/− mice at PD 23 (d, arrows) whereas all primordial follicles were activated in vehicle-treated Oo<i>Pten</i>^−/− mice at PD 23 (b, arrows). Scale bar = 50 µm. (<b>B</b>) Average numbers of total and primordial follicles in Oo<i>Pten</i>^+/+, Oo<i>Pten</i>^−/− (vehicle-treated), and Oo<i>Pten</i>^−/− (rapamycin-treated) ovaries at PD 23. Proportions of primordial follicles ± SEM (relative to the total number of follicles) are also shown. The proportion of primordial follicles in rapamycin-treated Oo<i>Pten</i>^−/− ovaries was 20±4.1%, which was smaller than the proportion in the Oo<i>Pten</i>^+/+ ovaries (70±3.1%). Three mice were used for each experimental group. Rapa, rapamycin. (<b>C</b>) Comparison of the rpS6 and Akt phosphorylation levels in the ovaries of vehicle- and rapamycin-treated Oo<i>Pten</i>^−/− mice. Rapamycin (5 mg/kg body weight) was injected daily into Oo<i>Pten</i>^−/− mice from PD 4 to PD 22, the ovaries were collected at PD 23 and homogenized, and immunoblotting was performed as described in <i>Materials and Methods</i>. Rapamycin injection effectively suppressed the level of phosphorylated rpS6 (p-rpS6) without affecting the level of phosphorylated Akt (p-Akt) in the ovaries of Oo<i>Pten</i>^−/− mice. Levels of total rpS6, Akt, and β-actin were used as internal controls.</p

The result of the ternary classification for the networks with chain architecture.

<p>The result of the ternary classification for the networks with chain architecture.</p

The number of patients and lesions.

<p>The number of patients and lesions.</p

The validation error rate of the classification for the 3D multi-view networks with DAG architecture.

<p>The validation error rate of the classification for the 3D multi-view networks with DAG architecture.</p

The error rate of the 3D SV-CNN (top) and 3D MV-CNN (bottom) with chain architecture for the ternary classification.

<p>From left to right, there are the error rates of Softmax, CNN1, CNN2 and CNN3, respectively.</p

The architectures of the 3D single view CNN (SV-CNN) (top) and 3D MV-CNN (bottom).

<p>The architectures of the 3D single view CNN (SV-CNN) (top) and 3D MV-CNN (bottom).</p

Some classification results on LIDC-IDRI dataset.

<p>Some classification results on LIDC-IDRI dataset.</p

Compare the multi-view-one-network strategy with the one-view-one-network strategy.

<p>Compare the multi-view-one-network strategy with the one-view-one-network strategy.</p