School Excellence: Principals’ Perceptions

It was generally believed that the education system of Pakistan, in general, and Khyber Pakhtunkhwa, in particular, was in shambles. Barring a few exceptions, the schools in Khyber Pakhtunkhwa direly needed improvement. Turning schools into Centres of Excellence required identification of factors that promoted effectiveness and excellence. The study was carried out to identify factors promoting excellence in schools in Khyber Pakhtunkhwa, Pakistan. The population of the study included all the boys’ high Schools of Peshawar city. The sample comprised 30 principals/headmasters of boys’ high schools (26 from private sector and 4 from public sector). The tool of the study was an opinionnaire, which was fielded to principals/headmasters of both sectors. The opinionnaire contained items and statements of multi-dimensional nature. The data analysis was given both quantitative and qualitative treatment. In order to be logical and scientific in approach the analysis was further made meaningful with the application of statistical measures. The outcome of the study revealed a number of factors that could help convert a school into a centre of excellence. Keywords: Excellence, Effective, Public and private schools, Opinionnaire, Factor

Role of Oxidative Stress in various stages of Psoriasis

Background: Psoriasis is a chronic inflammatory, immune mediated, provocative and challenging skin condition. It is a non-contagious but debilitating disease and a leading cause of socioeconomic burden on the health system. Objective: To evaluate the role of antioxidant levels, lipid peroxidation status and lipid profile in the etiology and degree of severity of psoriatic illness among psoriasis patients presenting in Dermatology department. Study Design: This study was carried out as a retrospective case control study. Place and duration of Study: It was carried out by the Department of Biochemistry, Basic Medical Sciences Institute (BMSI) in collaboration with Departmnt of Biochemistry, Khyber Medical College, Peshawar and Department of Skin and Venereal disease, Jinnah Post Graduate Medical Centre (JPMC) Karachi. Material and Methods: One hundred and twenty cases (n=130) of already diagnosed psoriasis patients were randommely and fifty healthy matched controls (n=50) of the same age and gender were included from the general population for comparison. Lipid profile including serum total cholesterol, TG, HDL-c and LDL-c levels were measured by enzyme colorimetric analysis on Micro Lab 300 (Merck & Germany). Antioxidant status SOD and lipid peroxidation status MDA were measured by ELISA technique. Statistical analysis was performed using SPSS software Version 16. In this analysis, a “p” value of less than 0.05 was considered to be significant. Results: The study showed significantly elevated levels of MDA, serum TG, total cholesterol and LDL-c levels in psoriatic patients in comparison with controls, whereas SOD levels and HDL-c levels were found to be significantly lower in psoriatic patients as compared to normal healthy matched controls. Conclusion: The findings of this study support the hypothesis that an imbalance in oxidant-antioxidant system may play a role in the etiology of psoriasis and the degree of severity of its presentation. The study also concluded that dyslipidemia was an observed risk factor for the development of cardiovascular diseases in psoriatic patients.

WaveBound: Dynamic Error Bounds for Stable Time Series Forecasting

Time series forecasting has become a critical task due to its high practicality in real-world applications such as traffic, energy consumption, economics and finance, and disease analysis. Recent deep-learning-based approaches have shown remarkable success in time series forecasting. Nonetheless, due to the dynamics of time series data, deep networks still suffer from unstable training and overfitting. Inconsistent patterns appearing in real-world data lead the model to be biased to a particular pattern, thus limiting the generalization. In this work, we introduce the dynamic error bounds on training loss to address the overfitting issue in time series forecasting. Consequently, we propose a regularization method called WaveBound which estimates the adequate error bounds of training loss for each time step and feature at each iteration. By allowing the model to focus less on unpredictable data, WaveBound stabilizes the training process, thus significantly improving generalization. With the extensive experiments, we show that WaveBound consistently improves upon the existing models in large margins, including the state-of-the-art model.Comment: NeurIPS 202

GREEN SYNTHESIS OF SILVER NANOPARTICLES USING THE LEAF EXTRACT OF PUTRANJIVA ROXBURGHII WALL. AND THEIR ANTIMICROBIAL ACTIVITY.

 Objective: This study deals with the synthesis of silver nanoparticles (AgNP's) from the extract of the leaves of the plant Putranjiva roxburghii wall.Using biological method, i.e., green synthesis.Methods: The extract from the leaves acts as a reducing and stabilizing agent for the AgNP's. Further characterization was done using varioustechniques like ultraviolet (UV)-visible spectrophotometry, which shows surface plasmon resonance, Fourier transform infra-red spectroscopyanalysis shows formation of various bonds, scanning electron microscope (SEM) and transmission electron microscope (TEM) analysis depictsthe distribution and average size of nanoparticles. The antimicrobial activity was also checked against various bacteria and fungi using minimuminhibitory concentration and well diffusion assay.Result: UV analysis shows strong plasmon resonance between 420 and 480 nm SEM analysis shows the distribution of synthesized nanoparticles,whereas TEM analysis shows the average particle size to be near about 5 nm and well diffusion assay proved that these nanoparticles are effectiveagainst different microorganisms.Conclusion: P. roxburghii wall. shows strong potential for the reduction of silver from Ag+ to Ag0 and nanoparticles so formed are strongly activeagainst various microorganism.Keywords: Putranjiva roxburghii, Fourier transform infra-red, Scanning electron microscope, Transmission electron microscope

Sensorless Control of Induction Motor Drive During Low Speed Region Using IFLC based MRAS Speed Observer

ABSTRACT: Sensorless controls of induction motor drives are widely used in industry due to their high performance. Of the various Sensorless control technique Model Reference adaptive system (MRAS) is the most widely used, in which PI controllers are conventionally used in the adaptation mechanism. The performance of many of the previously developed sensorless schemes for control of induction motor in low speed region is not found to be satisfactory. To improve the performance in the low speed region a novel method is proposed in this paper in which the conventionally used PI controller is replaced by an integrated fuzzy logic controller (IFLC) which is nothing but the combination of PI and fuzzy logic controller. Simulations are performed in Matlab/Simulink to verify the effectiveness of the proposed method. Simulation results are presented, analysed and compared for both PI and IFLC based MRAS speed observer and it is observed that the performance of motor during low speed region is improved with IFLC when compared to PI controller. Keywords: Sensorless control, MRAS, PI controller, IFLC I. INTRODUCTION Induction motors are widely used in high performance ac drives due to their low cost, ruggedness and reliable operation when compared to DC motors. Although induction motors have many advantages, they posses time-varying dynamic interactions and hence it is very difficult to design a high performance induction motor drive system using PI controller. Also when we are using speed sensors for speed measurement the reliability of the system decreases and hence the need for sensorless control of induction motor arises. With the use of sensorless control the cost and size of the drive are reduced there by increasing the reliability and robustness of the system with considerable reduction in maintenance requirement. Of the various sensorless techniques discussed in literature, it is observed that these techniques have been applied successfully for high and medium speed operation [1, 2] but very low speed and zero speed operation still pose a problem. Amongst the different sensorless technique in literature MRAS is one of the most attractive techniques used due to their simplicity of design Majority of adaptation schemes used PI controller in the adaptation mechanism to generate the estimated motor speed. Conventionally used PI controller in the adaptation mechanism was replaced by a fuzzy logic controller i

Monetary union for the development process in the East African community: business cycle synchronization approach

This paper empirically examines the suitability of monetary union in East African community members namely, Burundi, Kenya, Rwanda, Tanzania and Uganda, on the basis of business cycle synchronization. This research considers annual GDP (gross domestic product) data from IMF (international monetary fund) for the period of 1980 to 2010. In order to extract the business cycles and trends, the study uses HP (Hodrick-Prescott) and the BP (band pass) filters. After identifying the cycles and trends of the business cycle, the study considers cross country correlation analysis and analysis of variance technique to examine whether EAC (East African community) countries are characterized by synchronized business cycles or not. The results show that four EAC countries (Burundi, Kenya, Tanzania and Uganda) among five countries are having similar pattern of business cycle and trend from the last ten years of the formation of the EAC. The research concludes that these countries, except Rwanda, do not differ significantly in transitory or cycle components but do differ in permanent components especially in growth trend