Hydro-institutional mapping in the Steelpoort River Basin, South Africa

River basins / Institutions / Organizations / Private sector / Public sector / Local government / Mapping / Water resource management / Water policy / Legislation / Rural women / Constraints / Groundwater / Surface water / Water quality / Water use / Water users / Dams / Reservoirs / Large-scale systems / Irrigation management / Industrialization / Case studies / Operations / Maintenance / Canals / Conflict / Farmer-agency interactions / Policy / Water supply / Rural development

Limits on the Electromagnetic and Weak Dipole Moments of the Tau-Lepton in E_6 Superstring Models

We obtain limits on the electromagnetic and weak dipole moments of the tau-lepton in the framework of a Left-Right symmetric model (LRSM) and a class of $E_6$ inspired models with an additional neutral vector boson $Z_\theta$. Using as an input the data obtained by the L3 and OPAL Collaborations for the reaction $e^+e^-\to \tau^+\tau^-\gamma$, we get a stringent limit on the LRSM mixing angle $\phi$, $-1.66\times 10^{-3}< \phi<1.22\times 10^{-3}$, which in turn induces bounds on the tau weak dipole moments which are consistent with the bounds obtained recently by the DELPHI and ALEPH Collaborations from the reaction $e^+e^-\to \tau^+\tau^-$. We also get similar bounds for the weak dipole moments of the tau lepton in the framework of $E_6$ superstring models.Comment: 18 pages, 5 figure

Fifteen years experience: Egyptian metabolic lab

Background: Inborn errors of metabolism (IEM) are single gene disorders responsible for abnormalities in the synthesis or catabolism of proteins, carbohydrates and fats by means of defective enzymes or transport proteins which results in a block of the metabolic pathway and accumulation of metabolites in different tissues. This study shows the most common diagnosed inherited inborn errors of metabolism among the Egyptian population. Prior to 1995, the diagnosis of inherited metabolic disorders in Egypt was very limited and diagnosed mainly on clinical suspicion. In 1995, The Biochemical Genetics Unit at The National Research Centre has been established as a part of The Human Genetics Department and later on in 2003 it was developed into The Biochemical Genetics Department by applying advanced techniques and equipments and providing early diagnosis for the metabolic disorders which led to better outcome in our patients. Material and methods: We have retrospectively reviewed a total of 12,148 cases suspected to have inborn errors of metabolism (IEM) with different age groups. They had been referred from several diagnostic centers and hospitals in Egypt to The Department of Biochemical Genetics at The National Research Centre. The diagnosis of these disorders was confirmed by qualitative determination of amino acid profile, quantitative determination of phenylalanine and galactose levels using dried blood spots (DBSs), quantitative determination of urinary glycosaminoglycans (GAGs), twodimensional electrophoretic separation of GAGs in urine and the assay for lysosomal enzymes activities in plasma and leukocytes. Results: Out of the total number of cases; 1041 (8.6%) patients were proved to have metabolic disorders. Those patients were classified as: 722 patients (69.4%) with lysosomal storage disorders, 302 patients (29%) with amino acid disorders and 17 patients (1.6%) with galactosemia. Conclusion: This study illustrates the experience of the reference metabolic lab in Egypt over 15 years. The lab began metabolic disorder screening by using simple diagnostic techniques like thin layer chromatography and colored tests in urine which by time updated and upgraded the methods to diagnose a wide range of disorders. This study shows the most common diagnosed inherited inborn errors of metabolism among the Egyptian population.Keywords: IEM; Consanguineous marriages; Aminoacidopathies; Lysosomal storage disorder

Automated BWO design using iterative learning control

Summary form only given, as follows. In our earlier works we reported on experimental results showing how finite length variations in a high power backward wave oscillator (BWO) will result in sinusoidal variations in both frequency and power outputs. By manually shifting the slow wave structure with respect to the cutoff neck by one-quarter of a wavelength we were able to achieve maximum frequency agility (large bandwidth). Automated control of the shifting, beam current, and cathode voltage will allow the device to perform specific tasks and will ultimately lead to a “Smart Tube.” Such tasks may include the ability to maximize power of efficiency for a given frequency, or to achieve maximum frequency agility at a given constant power. Accomplishing these goals requires the development of a learning control system in conjunction with directed hardware. In this paper, we report on various completed subsystems of such a smart tube. In particular, we report on the implementation and testing of a vacuum-compatible step motor assembly and the corresponding motor control, for shifting the slow wave structure. We also report on the design and implementation of a pressure control device for the nitrogen in the spark gap, in order to adjust the cathode voltage. We finally report on the design and simulation of an iterative learning controller which automatically adjusts the pressure and shifting in order to achieve frequency agility

Deep Learning Model Based on ResNet-50 for Beef Quality Classification

Food quality measurement is one of the most essential topics in agriculture and industrial fields. To classify healthy food using computer visual inspection, a new architecture was proposed to classify beef images to specify the rancid and healthy ones. In traditional measurements, the specialists are not able to classify such images, due to the huge number of beef images required to build a deep learning model. In the present study, different images of beef including healthy and rancid cases were collected according to the analysis done by the Laboratory of Food Technology, Faculty of Agriculture, Kafrelsheikh University in January of 2020. The texture analysis of the beef surface of the enrolled images makes it difficult to distinguish between the rancid and healthy images. Moreover, a deep learning approach based on ResNet-50 was presented as a promising classifier to grade and classify the beef images. In this work, a limited number of images were used to present the research problem of image resource limitation; eight healthy images and ten rancid beef images. This number of images is not sufficient to be retrained using deep learning approaches. Thus, Generative Adversarial Network (GAN) was proposed to augment the enrolled images to produce one hundred eighty images. The results obtained based on ResNet-50 classification achieve accuracy of 96.03%, 91.67%, and 88.89% in the training, testing, and validation phases, respectively. Furthermore, a comparison of the current model (ResNet-50) with the classical and deep learning architecture is made to demonstrate the efficiency of ResNet-50, in image classification

Information dynamics: patterns of expectation and surprise in the perception of music

This is a postprint of an article submitted for consideration in Connection Science © 2009 [copyright Taylor & Francis]; Connection Science is available online at:http://www.tandfonline.com/openurl?genre=article&issn=0954-0091&volume=21&issue=2-3&spage=8

A control theory approach on the design of a Marx generator network

A Marx generator is a well-known type of electrical circuit first described by Erwin Otto Marx in 1924. It has been utilized in numerous applications in pulsed power with resistive or capacitive loads. To-date the vast majority of research on Marx generators designed to drive capacitive loads relied on experimentation and circuit-level modeling to guide their designs. In this paper we describe how the problem of designing a Marx generator to drive a capacitive load is reduced to that of choosing a diagonal gain matrix F that places the eigenvalues of the closed-loop matrix A+BF at specific locations. Here A is the identity matrix and B characterizes the elements of the Marx generator and depends on the number of stages N. Due to the special structure of matrix F, this formulation is a well-known problem in the area of feedback control and is referred to as the structured static state feedback problem. While the problem is difficult to solve in general, due to the specific structures of matrices A and B, various efficient numerical algorithms exist to find solutions in specific cases. In a companion paper by Buchenauer it is shown that if certain conditions hold, then setting the natural frequencies of the circuit to be harmonically related guarantees that all the energy is delivered to the load capacitor after a suitable delay. A theorem formalizing this result is presented. Earlier aspects of this research have been published in two theses