Characterization of Smallholder Beef Cattle Production System in Central Vietnam –Revealing Performance, Trends, Constraints, and Future Development

The objective of this study is to evaluate the characteristics of smallholder beef cattle production in Central Vietnam. A total of 360 households were interviewed by using semi-structured questionnaire; a total of 606 beef cows were investigated for evaluating calving interval (CI). Thirty-two fattening cattle were monitored for the estimation of diet structure. Results showed that the cattle herd size was 4.32-4.45 cattle/household. In North Central (NC), 55% of surveyed farmers kept local cattle, 45% kept crossbreeds, and none of surveyed farmers keeping exotic breeds. In South Central (SC), 63% of surveyed farmers kept cross cattle, 32% kept local cattle, and 5% kept exotic breeds. In the breeding method, 70% of surveyed farmers used artificial insemination (AI), 20% used natural mating (NM), and only 10% used both AI and NM in SC, whereas in NC 40% of farmers used AI, 40% used NM, and 20% used both AI and NM. The variety of feedstuffs fed to cattle including roughages and concentrate. The concentrate in the diet for fattening cattle was 25%-35% and protein level was 11%-13%, and the average daily gain of cattle was 0.51-0.63 kg/day. The CI of cows was 12-13 months in SC, whereas in NC it was 13-14 months. There were numerous constraints to cattle production in surveyed households including diseases, lack of good quality feed sources, breeds, knowledge, and lack of capital. In conclusion, cattle production in Central Vietnam is small scale and still largely extensive. There are constraints that must be solved to improve livestock systems in the near future, especially when shifting towards semi-intensive and/or intensive cattle production systems.

Restructuring of colloidal aggregates in shear flow: Coupling interparticle contact models with Stokesian dynamics

A method to couple interparticle contact models with Stokesian dynamics (SD) is introduced to simulate colloidal aggregates under flow conditions. The contact model mimics both the elastic and plastic behavior of the cohesive connections between particles within clusters. Owing to this, clusters can maintain their structures under low stress while restructuring or even breakage may occur under sufficiently high stress conditions. SD is an efficient method to deal with the long-ranged and many-body nature of hydrodynamic interactions for low Reynolds number flows. By using such a coupled model, the restructuring of colloidal aggregates under stepwise increasing shear flows was studied. Irreversible compaction occurs due to the increase of hydrodynamic stress on clusters. Results show that the greater part of the fractal clusters are compacted to rod-shaped packed structures, while the others show isotropic compaction.Comment: A simulation movie be found at http://www-levich.engr.ccny.cuny.edu/~seto/sites/colloidal_aggregates_shearflow.htm

Application of mixed formulations of quasi-reversibility to solve ill-posed problems for heat and wave equations: the 1d case

International audienceIn this paper we address some ill-posed problems involving the heat or the wave equation in one dimension, in particular the backward heat equation and the heat/wave equation with lateral Cauchy data. The main objective is to introduce some variational mixed formulations of quasi-reversibility which enable us to solve these ill-posed problems by using some classical La-grange finite elements. The inverse obstacle problems with initial condition and lateral Cauchy data for heat/wave equation are also considered, by using an elementary level set method combined with the quasi-reversibility method. Some numerical experiments are presented to illustrate the feasibility for our strategy in all those situations. 1. Introduction. The method of quasi-reversibility has now a quite long history since the pioneering book of Latt es and Lions in 1967 [1]. The original idea of these authors was, starting from an ill-posed problem which satisfies the uniqueness property, to introduce a perturbation of such problem involving a small positive parameter ε. This perturbation has essentially two effects. Firstly the perturbation transforms the initial ill-posed problem into a well-posed one for any ε, secondly the solution to such problem converges to the solution (if it exists) to the initial ill-posed problem when ε tends to 0. Generally, the ill-posedness in the initial problem is due to unsuitable boundary conditions. As typical examples of linear ill-posed problems one may think of the backward heat equation, that is the initial condition is replaced by a final condition, or the heat or wave equations with lateral Cauchy data, that is the usual Dirichlet or Neumann boundary condition on the boundary of the domain is replaced by a pair of Dirichlet and Neumann boundary conditions on the same subpart of the boundary, no data being prescribed on the complementary part of the boundary

Load Shedding in Microgrids with Dual Neural Networks and AHP Algorithm

This paper proposes a new load shedding method based on the application of a Dual Neural Network (NN). The combination of a Back-Propagation Neural Network (BPNN) and of Particle Swarm Optimization (PSO) aims to quickly predict and propose a load shedding strategy when a fault occurs in the microgrid (MG) system. The PSO algorithm has the ability to search and compare multiple points, so the proposed NN training method helps determine the link weights faster and stronger. As a result, the proposed method saves training time and achieves higher accuracy. The Analytic Hierarchy Process (AHP) algorithm is applied to rank the loads based on their importance factor. The results of the ratings of the loads serve as a basis for constructing the load shedding strategies of a NN combined with the PSO algorithm (ANN-PSO). The proposed load shedding method is tested on an IEEE 25-bus 8-generator MG power system. The simulation results show that the frequency recovery of the power system is positive. The proposed neural network adapts well to the simulated data of the system and achieves high performance in fault prediction

First Observation of Self-Amplified Spontaneous Emission in a Free-Electron Laser at 109 nm Wavelength

We present the first observation of Self-Amplified Spontaneous Emission (SASE) in a free-electron laser (FEL) in the Vacuum Ultraviolet regime at 109 nm wavelength (11 eV). The observed free-electron laser gain (approx. 3000) and the radiation characteristics, such as dependency on bunch charge, angular distribution, spectral width and intensity fluctuations all corroborate the existing models for SASE FELs.Comment: 6 pages including 6 figures; e-mail: [email protected]

Nonlinear rheology of colloidal dispersions

Colloidal dispersions are commonly encountered in everyday life and represent an important class of complex fluid. Of particular significance for many commercial products and industrial processes is the ability to control and manipulate the macroscopic flow response of a dispersion by tuning the microscopic interactions between the constituents. An important step towards attaining this goal is the development of robust theoretical methods for predicting from first-principles the rheology and nonequilibrium microstructure of well defined model systems subject to external flow. In this review we give an overview of some promising theoretical approaches and the phenomena they seek to describe, focusing, for simplicity, on systems for which the colloidal particles interact via strongly repulsive, spherically symmetric interactions. In presenting the various theories, we will consider first low volume fraction systems, for which a number of exact results may be derived, before moving on to consider the intermediate and high volume fraction states which present both the most interesting physics and the most demanding technical challenges. In the high volume fraction regime particular emphasis will be given to the rheology of dynamically arrested states.Comment: Review articl

Heterozygous Mutation of Drosophila Opa1 Causes the Development of Multiple Organ Abnormalities in an Age-Dependent and Organ-Specific Manner

Optic Atrophy 1 (OPA1) is a ubiquitously expressed dynamin-like GTPase in the inner mitochondrial membrane. It plays important roles in mitochondrial fusion, apoptosis, reactive oxygen species (ROS) and ATP production. Mutations of OPA1 result in autosomal dominant optic atrophy (DOA). The molecular mechanisms by which link OPA1 mutations and DOA are not fully understood. Recently, we created a Drosophila model to study the pathogenesis of optic atrophy. Heterozygous mutation of Drosophila OPA1 (dOpa1) by P-element insertion results in no obvious morphological abnormalities, whereas homozygous mutation is embryonic lethal. In eye-specific somatic clones, homozygous mutation of dOpa1 causes rough (mispatterning) and glossy (decreased lens deposition) eye phenotypes in adult Drosophila. In humans, heterozygous mutations in OPA1 have been associated with mitochondrial dysfunction, which is predicted to affect multiple organs. In this study, we demonstrated that heterozygous dOpa1 mutation perturbs the visual function and an ERG profile of the Drosophila compound eye. We independently showed that antioxidants delayed the onset of mutant phenotypes in ERG and improved larval vision function in phototaxis assay. Furthermore, heterozygous dOpa1 mutation also caused decreased heart rate, increased heart arrhythmia, and poor tolerance to stress induced by electrical pacing. However, antioxidants had no effects on the dysfunctional heart of heterozygous dOpa1 mutants. Under stress, heterozygous dOpa1 mutations caused reduced escape response, suggesting abnormal function of the skeletal muscles. Our results suggest that heterozygous mutation of dOpa1 shows organ-specific pathogenesis and is associated with multiple organ abnormalities in an age-dependent and organ-specific manner

Vertical stratification of the air microbiome in the lower troposphere

The troposphere constitutes the final frontier of global ecosystem research due to technical challenges arising from its size, low biomass, and gaseous state. Using a vertical testing array comprising a meteorological tower and a research aircraft, we conducted synchronized measurements of meteorological parameters and airborne biomass (n = 480) in the vertical air column up to 3,500 m. The taxonomic analysis of metagenomic data revealed differing patterns of airborne microbial community composition with respect to time of day and height above ground. The temporal and spatial resolution of our study demonstrated that the diel cycle of airborne microorganisms is a ground-based phenomenon that is entirely absent at heights >1,000 m. In an integrated analysis combining meteorological and biological data, we demonstrate that atmospheric turbulence, identified by potential temperature and high-frequency three-component wind measurements, is the key driver of bioaerosol dynamics in the lower troposphere. Multivariate regression analysis shows that at least 50% of identified airborne microbial taxa (n = ∼10,000) are associated with either ground or height, allowing for an understanding of dispersal patterns of microbial taxa in the vertical air column. Due to the interconnectedness of atmospheric turbulence and temperature, the dynamics of microbial dispersal are likely to be impacted by rising global temperatures, thereby also affecting ecosystems on the planetary surface

A Hybrid Color Space for Skin Detection Using Genetic Algorithm Heuristic Search and Principal Component Analysis Technique

Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space in terms of skin and face classification performance which can address issues like illumination variations, various camera characteristics and diversity in skin color tones has remained an open issue. This research proposes a new three-dimensional hybrid color space termed SKN by employing the Genetic Algorithm heuristic and Principal Component Analysis to find the optimal representation of human skin color in over seventeen existing color spaces. Genetic Algorithm heuristic is used to find the optimal color component combination setup in terms of skin detection accuracy while the Principal Component Analysis projects the optimal Genetic Algorithm solution to a less complex dimension. Pixel wise skin detection was used to evaluate the performance of the proposed color space. We have employed four classifiers including Random Forest, Naïve Bayes, Support Vector Machine and Multilayer Perceptron in order to generate the human skin color predictive model. The proposed color space was compared to some existing color spaces and shows superior results in terms of pixel-wise skin detection accuracy. Experimental results show that by using Random Forest classifier, the proposed SKN color space obtained an average F-score and True Positive Rate of 0.953 and False Positive Rate of 0.0482 which outperformed the existing color spaces in terms of pixel wise skin detection accuracy. The results also indicate that among the classifiers used in this study, Random Forest is the most suitable classifier for pixel wise skin detection applications

Insulin-Stimulated Degradation of Apolipoprotein B100: Roles of Class II Phosphatidylinositol-3-Kinase and Autophagy

Both in humans and animal models, an acute increase in plasma insulin levels, typically following meals, leads to transient depression of hepatic secretion of very low density lipoproteins (VLDL). One contributing mechanism for the decrease in VLDL secretion is enhanced degradation of apolipoprotein B100 (apoB100), which is required for VLDL formation. Unlike the degradation of nascent apoB100, which occurs in the endoplasmic reticulum (ER), insulin-stimulated apoB100 degradation occurs post-ER and is inhibited by pan-phosphatidylinositol (PI)3-kinase inhibitors. It is unclear, however, which of the three classes of PI3-kinases is required for insulin-stimulated apoB100 degradation, as well as the proteolytic machinery underlying this response. Class III PI3-kinase is not activated by insulin, but the other two classes are. By using a class I-specific inhibitor and siRNA to the major class II isoform in liver, we now show that it is class II PI3-kinase that is required for insulin-stimulated apoB100 degradation in primary mouse hepatocytes. Because the insulin-stimulated process resembles other examples of apoB100 post-ER proteolysis mediated by autophagy, we hypothesized that the effects of insulin in autophagy-deficient mouse primary hepatocytes would be attenuated. Indeed, apoB100 degradation in response to insulin was significantly impaired in two types of autophagy-deficient hepatocytes. Together, our data demonstrate that insulin-stimulated apoB100 degradation in the liver requires both class II PI3-kinase activity and autophagy. © 2013 Andreo et al