Effectiveness of agricultural extension with respect to farm size: The case of Uganda

Raising the incomes of agricultural households is central to reducing poverty in Uganda. In many areas of the country agriculture has encroached into marginal or fragile lands, leaving little room for the expansion of agricultural lands (Kraybill, Bashaasha, and Betz 2009). Additionally, soil degradation has become a barrier to agricultural productivity (Pender et al. 2004), especially in the Eastern region of the country. Farmers now look for alternatives that will increase output without further depleting soil fertility or expanding into fragile lands. Agricultural extension is the primary government mechanism through which developing country governments attempt to improve the knowledge and methods that farmers use to increase output; However, many extension programs throughout Sub-Saharan Africa have the reputation of being largely ineffective (Dejene 1989; Gautam 2000). This study estimates an agricultural production function for 3 farm sizes to determine whether agricultural extension has differential effects on farms of different size. Extension is found to have a positive and significant relationship with the value of output produced for small and large farms, but has not significant relationship with the value of output for medium size farms. This result has distinct policy implications for the design and implementation of agricultural extension programs in Uganda and other parts of Sub-Saharan Africa.Uganda, Africa, agriculture, extension, productivity, NAADS, Agricultural and Food Policy, Farm Management, International Development, Production Economics,

Breaking the chain

We consider the motion of a Brownian particle in $\mathbb{R}$, moving between a particle fixed at the origin and another moving deterministically away at slow speed $\epsilon>0$. The middle particle interacts with its neighbours via a potential of finite range $b>0$, with a unique minimum at $a>0$, where $b<2a$. We say that the chain of particles breaks on the left- or right-hand side when the middle particle is greater than a distance $b$ from its left or right neighbour, respectively. We study the asymptotic location of the first break of the chain in the limit of small noise, in the case where $\epsilon = \epsilon(\sigma)$ and $\sigma>0$ is the noise intensity.Comment: 13 pages, 2 figures. v2: Corrected a mistake in proof of second part of main theore

The CERN Resonant WISP Search (CROWS)

The subject of this work is the design, implementation and first results of the ""CERN Resonant WISP Search"" (CROWS), which probes the existence of Axion Like Particles and Hidden Sector Photons (HSPs) using microwave techniques. By exploiting low loss cavity resonators, multiple layers of electromagnetic shielding and a micro-Hz bandwidth detection scheme, new exclusion limits could be set. For HSPs, sensitivity was improved by a factor of ~7 compared to previous laboratory experiments

Federal Invome Tax Discrimination Between Married and Single Taxpayers

This article explores the present tax rate structure and its implications, considers the historical events and policies which created four separate tax rates, analyzes the tax policies embodied by the different rate treatment of married and single taxpayers, and examines the constitutional problems involved in maintaining the present disparate tax treatment. An alternative tax rate treatment, which will avoid the discrimination inherent in the present system, is suggested

Is Epistemic Trust of Veritistic Value?

Epistemic trust figures prominently in our socio-cognitive practices. By assigning different (relative) degrees of competence to agents, we distinguish between experts and novices and determine the trustworthiness of testimony. This paper probes the claim that epistemic trust furthers our epistemic enterprise. More specifically, it assesses the veritistic value of competence attribution in an epistemic community, i.e., in a group of agents that collaboratively seek to track down the truth. The results, obtained by simulating opinion dynamics, tend to subvert the very idea that competence ascription is essential for the functioning of epistemic collaboration and hence veritistically valuable. On the contrary, we find that, in specific circumstances at least, epistemic trust may prevent a community from finding the truth effectively

Effects of flow baffles on flow profile, pressure drop and classification performance in classifiers

This paper presents a study of the use of flow baffles inside a centrifugal air classifier. An air classifier belongs to the most widely used classification devices in mills in the mineral industry, which is why there is a great interest in optimizing the process flow and pressure loss. Using Computational Fluid Dynamics (CFD), the flow profile in a classifier without and with flow baffles is systematically compared. In the simulations, turbulence effects are modeled with the realizable k–ε model, and the Multiple Reference Frame approach (MRF) is used to represent the rotation of the classifier wheel. The discrete phase model is used to predict the collection efficiency. The effects on the pressure loss and the classification efficiency of the classifier are considered for two operating conditions. In addition, a comparison with experimental data is performed. Firstly, the simulations and experiments show good agreement. Furthermore, the investigations show that the use of flow baffles is suitable for optimizing the flow behavior in the classifier, especially in reducing the pressure loss and therefore energy costs. Moreover, the flow baffles have an impact on the classification performance. The impact depends on the operation conditions, especially the classifier speed. At low classifier speeds, the classifier without flow baffles separates more efficiently; as the speed increases, the classification performance of the classifier with flow baffles improves

Development of Prediction Models for Pressure Loss and Classification Efficiency in Classifiers

This paper presents the development of prediction models for pressure loss and classification efficiency in classifiers. Classifiers belong to one of the most important classification devices in gas particle processing and a fast and accurate determination of pressure loss and cut size is of great interest. The first model developed in this work allows the calculation of pressure loss as a function of geometric and operational parameters. It is based on a number of measured values that are obtained from previous numerical simulations (CFD). The maximum deviation of the model is less than 20% and the model operates in real time. However, the model requires calibration for each type of classifier. The second model for classification efficiency is based on a simplified two-dimensional approach in which the flow profile and particle trajectories are determined exclusively for the area between two classifier blades. The model is applicable for all geometrical and operational parameters and calculates the desired parameters within a few minutes, with a maximum error rate of 25%. In combination, the two models allow for the process optimization of classifiers in complete systems

Development of a New Solver to Model the Fish-Hook Effect in a Centrifugal Classifier

entrifugal air classifiers are often used for classification of particle gas flows in the mineral industry and various other sectors. In this paper, a new solver based on the multiphase particle-in-cell (MP-PIC) method, which takes into account an interaction between particles, is presented. This makes it possible to investigate the flow process in the classifier in more detail, especially the influence of solid load on the flow profile and the fish-hook effect that sometimes occurs. Depending on the operating conditions, the fish-hook sometimes occurs in such apparatus and lead to a reduction in classification efficiency. Therefore, a better understanding and a representation of the fish-hook in numerical simulations is of great interest. The results of the simulation method are compared with results of previous simulation method, where particle–particle interactions are neglected. Moreover, a validation of the numerical simulations is carried out by comparing experimental data from a laboratory plant based on characteristic values such as pressure loss and classification efficiency. The comparison with experimental data shows that both methods provide similar good values for the classification efficiency d$_{50}$; however, the fish-hook effect is only reproduced when particle-particle interaction is taken into account. The particle movement prove that the fish-hook effect is due to a strong concentration accumulation in the outer area of the classifier. These particle accumulations block the radial transport of fine particles into the classifier, which are then entrained by coarser particles into the coarse material

Modellierung und Optimierung der strömungstechnischen Vorgänge in Abweiseradsichtern

Centrifugal classifiers are processing machines used in the gas-particle classification. The aim of this work is to reduce energy costs by improving the classification properties and reducing the pressure drop. In addition to design measures, the focus is also on model development. For the development of the models, a deeper understanding of the flow processes is required