How does food price increase affect Ugandan households?: An augmented multimarket approach

"Almost unaffected by the 2008 wave of soaring world food prices, Ugandan local market prices exhibit signs of high price volatility in the first quarter of 2009. At the household level, while net producers may reap some benefits from this increase in food prices, net consumers are more likely to suffer from it. However, the net consumption impact of food price increase is not as straightforward as reported in previous studies. In this paper, we extend Singh et al. (1986) multimarket model by adding demand elasticities from the Almost Ideal Demand System (AIDS). We use the integrated Ugandan National Household Survey (UNHS) 2005/2006 to estimate a measure of net consumption impact that includes both price and profit effects. Overall, we found that household welfare is expected to decrease with loss in consumption and increase with income gain as a result of higher food prices for the cereals producers. Simulating change in cereals consumption induced by a 50 percent increase in cereals price and taking into account the profit effect, our results predict a 23 percent decrease in food consumption for net sellers, compared with 44 percent when using the consumption approach alone. Accounting for such substitution effects, our results suggest that the impact of rising food prices may be mitigated because some households will attempt to substitute more expensive food items with cheaper ones; however, this apparent coping strategy often leads to a much poorer diet. The results suggest that the majority of households with expected positive income impact, the gainers, live in rural areas. These households also tend to have better access to agricultural services than the nongainers." from authors' abstractConsumption, Elasticity, Food prices, households, Multimarket, Science and technology, Institutional change, Innovation systems, Supply and demand, Household resource allocation, Gender,

Restoration of Blurred and Noisy Images Using Inverse Filtering and Adaptive Threshold Method

A restoration scheme for images that are corrupted with both blur and impulsive noise is proposed in this paper to reconstruct an image with minimum degradation. The restoration scheme consists of two stages in sequence where the first stage is applied to the blurred image and the second stage is applied to de-blurred image that has been subject to noise through electronic transmission. The first stage uses frequency domain filtering while the second utilizes spatial filtering to reduce the indicated blur and noise, respectively. In particular, truncated inverse filtering is used for reducing the blur and an adaptive algorithm with an estimated threshold is used for minimizing the noise. Simulation of the introduced method uses several performance measuring indices such as mean absolute error (MAE) and peak signal-to-noise ratio (PSNR). Results of these simulations show great performance of the proposed method in terms of reducing the blur and noise significantly while keeping details and sharpness of the image edges

El orujo de Physalis peruviana suprime la hipercolesterolemia inducida por una dieta rica en colesterol en ratas

Physalis peruviana (goldenberry) is a promising fruits that can be an ingredient in several functional foods. No reports are available on the effect of the administration of goldenberry pomace on different aspects of the plasma lipid profile in experimental animals. According to the chemical composition of the fruit pomace which includes high levels of bioactive compounds, the hypothesis was that feeding Physalis peruviana pomace may have health-promoting and hypercholesterolemic impacts on rats fed a high cholesterol diet (HCD). Therefore, the objective of this study was to investigate the effect of feeding goldenberry pomace on hypercholesterolemia by analyzing the changes in lipid profiles in HCD fed rats. The chemical composition, lipid profiles (fatty acids, tocopherols and sterols) and phenolic contents of the fruit pomace were determined. Generally, rats fed the fruit pomace showed lower levels of total cholesterol (TC), total triacylglycerol (TAG) and total low density lipoprotein (LDL) cholesterol as well as higher levels of high density lipoprotein (HDL) cholesterol in comparison with animals fed HCD and cholesterol free diets (CFD). Histological examinations of the liver and kidney were also studied. The results demonstrated that goldenberry pomace consumption provides overall beneficial effects on reversing HCD associated detrimental changes.Physalis peruviana (aguaymanto) es un fruto prometedor que puede ser parte de diferentes alimentos funcionales. No hay datos disponibles sobre el efecto de la administración del orujo de aguaymanto sobre diferentes aspectos del perfil de lipídos plasmáticos en animales de experimentación. De acuerdo con la composición química del orujo de la fruta que incluye altos niveles de compuestos bioactivos, se demostró la hipótesis de que la alimentación con orujo de Physalis peruviana puede tener efectos saludables y sobre la hipercolesterolemia en ratas alimentadas con una dieta alta en colesterol (HCD). Por tanto, el objetivo de este estudio fue investigar el efecto de una alimentación con orujo de Physalis peruviana o sobre la hipercolesterolemia analizando los cambios del perfil lipídico en ratas alimentadas con una dieta alta en colesterol (HCD). Se determinó la composición química, el perfil lipídico (ácidos grasos, tocoferoles y esteroles) y contenido fenólico del orujo de aguaymanto. En términos generales, las ratas alimentadas con orujo de aguaymanto mostraron niveles más bajos de colesterol total (TC), triglicéridos totales (TAG) y lipoproteínas de baja densidad totales, así como superiores niveles de lipoproteínas de alta densidad (HDL) en comparación con los animales alimentados con HCD y con una dieta libre de colesterol (CFD). El examen histológico del hígado y de los riñones fue también realizado. Los resultados demostraron que el consumo de orujo de aguaymanto proporciona efectos beneficiosos generales invirtiendo los cambios perjudiciales asociados a una dieta HCD

Optimum Image Filters for Various Types of Noise

In this paper, the quality performance of several filters in restoration of images corrupted with various types of noise has been examined extensively. In particular, Wiener filter, Gaussian filter, median filter and averaging (mean) filter have been used to reduce Gaussian noise, speckle noise, salt and pepper noise and Poisson noise. Many images have been tested, two of which are shown in this paper. Several percentages of noise corrupting the images have been examined in the simulations. The size of the sliding window is the same in the four filters used, namely 5x5 for all the indicated noise percentages. For image quality measurement, two performance measuring indices are used: peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The simulation results show that the performance of some specific filters in reducing some types of noise are much better than others. It has been illustrated that median filter is more appropriate for eliminating salt and pepper noise. Averaging filter still works well for such type of noise, but of less performance quality than the median filter. Gaussian and Wiener filters outperform other filters in restoring mages corrupted with Poisson and speckle noise

Effect of kernel size on Wiener and Gaussian image filtering

In this paper, the effect of the kernel size of Wiener and Gaussian filters on their image restoration qualities has been studied and analyzed. Four sizes of such kernels, namely 3x3, 5x5, 7x7 and 9x9 were simulated. Two different types of noise with zero mean and several variances have been used: Gaussian noise and speckle noise. Several image quality measuring indices have been applied in the computer simulations. In particular, mean absolute error (MAE), mean square error (MSE) and structural similarity (SSIM) index were used. Many images were tested in the simulations; however the results of three of them are shown in this paper. The results show that the Gaussian filter has a superior performance over the Wiener filter for all values of Gaussian and speckle noise variances mainly as it uses the smallest kernel size. To obtain a similar performance in Wiener filtering, a larger kernel size is required which produces much more blur in the output mage. The Wiener filter shows poor performance using the smallest kernel size (3x3) while the Gaussian filter shows the best results in such case. With the Gaussian filter being used, similar results of those obtained with low noise could be obtained in the case of high noise variance but with a higher kernel size

Cross-cultural impact on the budgeting cycle: a preliminary analysis of Anglo-American and Libyan companies operating in Libyan oil sector

[Abstract]: Globalization is causing the rapid integration of markets, nations, and technology, which facilitates faster contact between people, corporations, and nations. However, there is a failure to notice cultural differences that exist between workforces across nations. Thus all staff needs to have cultural sensitivity, which could be helped by studying cross-cultural differences. Current understanding of how and why specific budget aspects and budgeting processes are different could be attributed to cultural differences. This study utilizes societal cultural dimensions identified by Hofstede to identify differences in budgets and budgeting process between Libyan and Anglo-American companies operating in Libyan oil sector. Some preliminary analysis is discussed

Studies on properties and estimation problems for modified extension of exponential distribution

The present paper considers modified extension of the exponential distribution with three parameters. We study the main properties of this new distribution, with special emphasis on its median, mode and moments function and some characteristics related to reliability studies. For Modified- extension exponential distribution (MEXED) we have obtained the Bayes Estimators of scale and shape parameters using Lindley's approximation (L-approximation) under squared error loss function. But, through this approximation technique it is not possible to compute the interval estimates of the parameters. Therefore, we also propose Gibbs sampling method to generate sample from the posterior distribution. On the basis of generated posterior sample we computed the Bayes estimates of the unknown parameters and constructed 95 % highest posterior density credible intervals. A Monte Carlo simulation study is carried out to compare the performance of Bayes estimators with the corresponding classical estimators in terms of their simulated risk. A real data set has been considered for illustrative purpose of the study.Comment: 22,

An Overview on Evaluation of E-Learning/Training Response Time Considering Artificial Neural Networks Modeling

The objective of this piece of research is to interpret and investigate systematically an observed brain functional phenomenon which associated with proceeding of e-learning processes. More specifically, this work addresses an interesting and challenging educational issue concerned with dynamical evaluation of e-learning performance considering convergence (response) time. That's based on an interdisciplinary recent approach named as Artificial Neural Networks (ANNs) modeling. Which incorporate Nero-physiology, educational psychology, cognitive, and learning sciences. Herein, adopted application of neural modeling results in realistic dynamical measurements of e-learners' response time performance parameter. Initially, it considers time evolution of learners' experienced acquired intelligence level during proceeding of learning / training process. In the context of neurobiological details, the state of synaptic connectivity pattern (weight vector) inside e-learner's brain-at any time instant-supposed to be presented as timely varying dependent parameter. The varying modified synaptic state expected to lead to obtain stored experience spontaneously as learner's output (answer). Obviously, obtained responsive learner's output is a resulting action to any arbitrary external input stimulus (question). So, as the initial brain state of synaptic connectivity pattern (vector) considered as pre-intelligence level measured parameter. Actually, obtained e-learner’s answer is compatibly consistent with modified state of internal / stored experienced level of intelligence. In other words, dynamical changes of brain synaptic pattern (weight vector) modify adaptively convergence time of learning processes, so as to reach desired answer. Additionally, introduced research work is motivated by some obtained results for performance evaluation of some neural system models concerned with convergence time of learning process. Moreover, this paper considers interpretation of interrelations among some other interesting results obtained by a set of previously published educational models. The interpretational evaluation and analysis for introduced models results in some applicable studies at educational field as well as medically promising treatment of learning disabilities. Finally, an interesting comparative analogy between performances of ANNs modeling versus Ant Colony System (ACS) optimization presented at the end of this paper