Smallholders’ Soil Fertility Management in the Central Highlands of Ethiopia: Implications for Nutrient Stocks, Balances and Sustainability of Agroecosystems

Low agricultural productivity caused by soil degradation is a serious problem in the Ethiopian Highlands. Here, we report how differences in soil fertility management between farming systems, based either on enset (Ensete ventricosum) or on teff (Eragrostis tef) as the major crops, affect the extent of nutrient stocks, balances and ecosystem sustainability. We collected information on farmers’ resources and nutrient management practices from stratified randomly selected households in two watersheds in the Central Highlands of Ethiopia. In addition, we collected soil samples from each land use and calculated nutrient stocks, partial and full nutrient balances (N, P and K) for one cropping season. Our results show that farmers in the two farming systems manage their soils differently and that nutrient inputs were positively related to farmers’ wealth status. The watershed with the enset-based system had higher soil N and K stocks than the watershed with the teff-based system, while P stocks were not different. Management related N?and K fluxes were more negative in the teff-based system (?28 kg N ha^?1 yr^?1 and ?34 kg K ha^?1 yr^?1) than in the enset-based system (?6 kg N ha^?1 yr^?1 and ?14 kg K ha^?1 yr^?1) while P fluxes were almost neutral or slightly positive. Within the enset-based system, a strong redistribution of N, P and K took place from the meadows and cereals (negative balance) to enset (positive balances). Although in the teff-based system, N, P and K were redistributed from meadows, small cereals and pulses to maize, the latter still showed a negative nutrient balance. In contrast to nutrient balances at land use level, nutrient balances at the watershed scale masked contrasting areas within the system where nutrient oversupply and deficiencies occurred.     

A coupling algorithm for partitioned solvers applied to bubble and droplet dynamics

Bubbles and droplets both consist of a liquid in contact with a gas. In this paper, we consider the interface between the incompressible liquid and the gas as a zero thickness structure. The position of the interface is determined by the equilibrium between surface tension effects and the fluid pressure difference across the interface. So, the structure interacts with the fluids on either side. The behaviour of a limited number of bubbles and droplets can therefore be simulated as a Fluid-Structure Interaction (FSI) problem.Most existing techniques frequently used for studying bubble and droplet dynamics, such as Level Set or Volume Of Fluid, use monolithic schemes. The flow on both sides of the interface and the position of the interface are calculated in a single code. In this contribution, a partitioned approach is presented. The position of the interface is calculated with a structural solver. Given a displacement of the interface, a separate flow solver calculates the flow on the liquid side of the interface with the Arbitrary Lagrangian-Eulerian (ALE) technique. The structural solver uses a reduced order model of the flow solver to obtain implicit coupling between both solvers. This reduced order model is built up during the coupling iterations of a time step. Grid and time converged solutions of two axisymmetric problems are calculated: an oscillating water droplet in air and the growth and detachment of an air bubble from the outlet of a vertical needle, submerged in quiescent water.     

Selection process for security packages

The primary goal of this paper is to provide a simplified process which can be used for the selection of a security package. The material has been made specifically non-technical so that it can be used by persons with little technical background. The process is based on a formula, which, after application, results in a single measure by weighing the security features in a package against the requirements as set by management.     

Microscale fluctuation assay coupled with Sep-PakR concentration as a rapid and sensitive method for screening mutagens in drinking water

A sensitive short-term mutagenicity test, the microscale fluctuation test has been coupled with a concentration method based on adsorption on Sep-Pak^R C₁₈ cartridges as a method for screening drinking water mutagens. Comparison with XAD-2 concentration method showed that Sep-Pak adsorbed 5 times higher quantity of organics but was slightly less efficient for adsorbing TOX.Microscale fluctuation test was found to be more sensitive than Ames test by testing known direct-acting mutagens and concentrates of drinking water. Samples derived from conventional treatment including chlorination from eight surface water supplies in Norway were concentrated at pH 2 by adsorption on the disposable columns. The adsorbates were tested at different doses by the microscale fluctuation assay. The mutagenic properties of drinking water samples were also related to total organic carbon (TOC), total organic halogen (TOX) and trihalomethanes (THM) concentrations. Dose-related mutagenic responses were found for all the samples with S. typhimurium TA 100 and TA98 strains without metabolic activation. Good relationship was found between mutagenicity data and TOX and THM results. The method showed to be simple, rapid and suitable for routine screening of mutagens in drinking water.     

Application of reinforcement learning to the game of Othello

Operations research and management science are often confronted with sequential decision making problems with large state spaces. Standard methods that are used for solving such complex problems are associated with some difficulties. As we discuss in this article, these methods are plagued by the so-called curse of dimensionality and the curse of modelling. In this article, we discuss reinforcement learning, a machine learning technique for solving sequential decision making problems with large state spaces. We describe how reinforcement learning can be combined with a function approximation method to avoid both the curse of dimensionality and the curse of modelling. To illustrate the usefulness of this approach, we apply it to a problem with a huge state space—learning to play the game of Othello. We describe experiments in which reinforcement learning agents learn to play the game of Othello without the use of any knowledge provided by human experts. It turns out that the reinforcement learning agents learn to play the game of Othello better than players that use basic strategies.     

Phase Transitions in Liquid Crystal Doped with Magnetic Particles of Different Shapes in Combined Electric and Magnetic Fields

We have studied the influence of electric and magnetic fields on the orientational structure of ferronematics based on a thermotropic nematic 4-trans-4 \(^{\prime }\) -n-hexylcyclohexyl-isothiocyanato-benzene (6CHBT). The 6CHBT liquid crystal has been dissolved in phenyl isothiocyanate and doped with rod-like or chain-like magnetic particles. In such a mixture, the phase transition from an isotropic to a nematic phase is via a droplet state, i.e., coexistence of nematic and isotropic phases. The obtained results showed that a combination of the electric and magnetic fields can change the character of a phase transition from the isotropic to the nematic phase via the droplet state in such systems. Moreover, magneto-dielectric measurements of structural transitions showed the magnetic field induced a shift of the phase transition temperature from the isotropic to the droplet state.     

Positive expectations predict health after heart transplantation.

We explored the relations between positive expectations and adjustment, adherence, and health in cardiac transplant patients. Thirty-one patients and their nurse completed questionnaires before transplantation and at 3 times after surgery. As predicted, patients' self-reported positive expectations were generally associated with good mood, adjustment to the illness, and quality of life, even in patients who experienced health setbacks. High preoperative expectations predicted later adherence to a complex medical regimen. Positive expectations measured before the transplant predicted a substantial amount of the variance in the nurse's ratings of physical health 6 months after surgery, covarying for adherence behavior and preoperative health. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Image analysis applied to engineering geology, a literature review

Image analysis is a technique used in a number of subjects, but to date not extensively used in the geological sciences. The paper describes the way image analysis is used in the various disciplines and presents an overview of the methods and its potential uses in geology and particularly engineering geology. Emphasis is placed on the way image analysis can be applied to rock structures and textures. It is hoped that this overview will provide an introduction to the literature, which is published in a variety of related fields. Electronic Publication