In vivo Antidiabetic and Antioxidant Potential of Pseudovaria macrophylla Extract

This study has investigated the antidiabetic and antioxidant potential of Pseudovaria macrophylla bark extract on streptozotocin–nicotinamide induced type 2 diabetic rats. LCMSQTOF and NMR experiments were done to determine the chemical composition in the methanolic bark extract. For in vivo experiments, the STZ (60 mg/kg/b.w, 15 min after 120 mg/kg/1 nicotinamide, i.p.) induced diabetic rats were treated with methanolic extract of Pseuduvaria macrophylla (200 and 400 mg/kg·bw) and glibenclamide (2.5 mg/kg) as positive control respectively. Biochemical parameters were assayed in the blood samples of all groups of rats. The pro-inflammatory cytokines, antioxidant status and plasma transforming growth factor βeta-1 (TGF-β1) were evaluated. The histological study of the pancreas was examined and its expression level of insulin was observed by immunohistochemistry. In addition, the expression of glucose transporters (GLUT 1, 2 and 4) were assessed in pancreas tissue by western blot analysis. The outcomes of the study displayed that the bark methanol extract of Pseuduvaria macrophylla has potentially normalized the elevated blood glucose levels and improved serum insulin and C-peptide levels with significant increase in the antioxidant enzyme, reduced glutathione (GSH) and decrease in the level of lipid peroxidation (LPO). Additionally, the extract has markedly decreased the levels of serum pro-inflammatory cytokines and transforming growth factor beta-1 (TGF-β1). Histopathology analysis demonstrated that Pseuduvaria macrophylla has the potential to protect the pancreas of diabetic rats against peroxidation damage by downregulating oxidative stress and elevated hyperglycaemia. Furthermore, the expression of insulin protein, GLUT-1, GLUT-2 and GLUT-4 in pancreatic cells was enhanced. The findings of this study support the anti-diabetic claims of Pseudovaria macrophylla bark.

e-Collaborative Learning Circles

In this paper, we introduce an e-collaborative learning circles methodology which utilizes the information and communication technologies (ICTs) in e-educational processes. In e-collaborative learning circles methodology, the teachers and students announce their research projects on various mailing lists and discussion boards using available ICTs. The teachers & moderators and students who are already members of the e-forums, discuss the project proposals in their classrooms sent out by the potential global partner schools and return the requested feed back to the proposing school(s) about their level of the participation and contribution in the research. In general, an e-collaborative learning circle project is implemented with a small and diverse group (usually 8-10 participants) from around the world. The students meet regularly over a period of weeks/months through the ICTs during the ecollaborative learning process. When the project is completed, a project product (e-book / DVD) is prepared and sent to the circle members. In this research, when taking into account the interests and motivation of the participating students with the facilitating role of the teacher(s), the students in each circle do research to obtain new data and information, thus enabling them to have the opportunity to meet both different cultures and international understandings across the globe. However, while the participants communicate along with the members in the circle they also practice and develop their communication language skills. Finally, teachers and students find the possibility to develop their skills in using the ICTs as well.

2-Dimensional Finger Gesture Based Mobile Robot Control Using Touch Screen

The purpose of this study was to present a reliable mean for human-computer interfacing based on finger gestures made in two dimensions, which could be interpreted and adequately used in controlling a remote robot's movement. The gestures were captured and interpreted using an algorithm based on trigonometric functions, in calculating the angular displacement from one point of touch to another as the user-s finger moved within a time interval; thereby allowing for pattern spotting of the captured gesture. In this paper the design and implementation of such a gesture based user interface was presented, utilizing the aforementioned algorithm. These techniques were then used to control a remote mobile robot's movement. A resistive touch screen was selected as the gesture sensor, then utilizing a programmed microcontroller to interpret them respectively.

Experimental Investigation of the Maximum Axial Force in the Folding Process of Aluminum Square Columns

In this paper, a semi empirical formula is presented based on the experimental results to predict the first pick (maximum force) value in the instantaneous folding force- axial distance diagram of a square column. To achieve this purpose, the maximum value of the folding force was assumed to be a function of the average folding force. Using the experimental results, the maximum value of the force necessary to initiate the first fold in a square column was obtained with respect to the geometrical quantities and material properties. Finally, the results obtained from the semi empirical relation in this paper, were compared to the experimental results which showed a good correlation.

Easy Shopping by Electronic Credit

In this paper we suggest a method for setting electronic credits for the customers. In this method banks and market-sites help each other to make doing large shopping through internet so easy. By developing this system, the people who have less money to buy most of the things they want, become able to buy all of them just through a credit. This credit is given by market-sites through a banking control on it. The method suggested can stop being imprisoned because of banking debts.

Dynamic Performances of Tubular Linear Induction Motor for Pneumatic Capsule Pipeline System

Tubular linear induction motor (TLIM) can be used as a capsule pump in a large pneumatic capsule pipeline (PCP) system. Parametric performance evaluation of the designed 1-meter diameter PCP-TLIM system yields encouraging results for practical implementation. The capsule thrust and speed inside the TLIM pump can be calculated from the combination of the PCP fluid mechanics and the TLIM equations. The TLIM equivalent circuits derived from those of the conventional three-phase induction motor are used as a model to predict the static test results of a small-scale PCP-TLIM system. In this paper, additional dynamic tests are performed on the same small-scale PCP-TLIM system with two capsules of different diameters. The behaviors of the capsule inside the pump are observed and analyzed. The dynamic performances from the dynamic tests are compared with the theoretical predictions based on the TLIM equivalent circuit model.

Analysis of Plasmids and Restriction Fragment Length Polymorphisms of Acinetobacter baumannii Isolated from Hospitals- AL Jouf Region- KSA

Abstract–The objectives of the current study are to determine the prevalence, etiological agents, drug susceptibility pattern and plasmid profile of Acinetobacter baumannii isolates from Hospital-Acquired Infections (HAI) at Community Hospital, Al Jouf Province, Saudi Arabia. A total of 1890 patients had developed infection during hospital admission and were included in the study. Among those who developed nosocomial infections, 15(9.4), 10(2.7) and 118 (12.7) had respiratory tract infection (RTI), blood stream infections (BSI) and urinary tract (UTI) respectively. A total of 268 bacterial isolates were isolated from nosocomial infection. S. aureus was reported in 23.5% for of the total isolates followed by Klebsiella pneumoniae (17.5%), E. coli (17.2%), P. aeruginosa (11.9%), coagulase negative staphylococcus (9%), A. baumannii (7.1%), Enterobacter spp. (3.4%), Citrobacter freundii (3%), Proteus mirabilis (2.6%), and Proteus vulgaris and Enterococcous faecalis (0.7%). Isolated organisms are multi-drug resistant, predominantly Gram-positive pathogens with a high incidence of methicillin-resistant S. aureus, extended spectrum beta lactamase and vancomycin resistant enterococci organisms. The RFLP (Fragment Length Polymorphisms) patterns of plasmid preparations from isolated A. baumannii isolates had altered RFLP patterns, possibly due to the presence of plasmid(s). Five A. baumannii isolates harbored plasmids all of which were not less than 2.71kbp in molecular weight. Hence, it showed that the gene coding for the isolates were located on the plasmid DNA while the remaining isolates which have no plasmid might showed gene coding for antibiotic resistance being located on chromosomal DNA. Nosocomial infections represent a current problem in Community Hospital, Al Jouf Province, Saudi Arabia. Problems associated with SSI include infection with multidrug resistant pathogens which are difficult to treat and are associated with increased mortality.

On a New Numerical Analysis for the Symmetric Shortest Queue Problem

We consider a network of two M/M/1 parallel queues having the same poisonnian arrival stream with rate λ. Upon his arrival to the system a customer heads to the shortest queue and stays until being served. If the two queues have the same length, an arriving customer chooses one of the two queues with the same probability. Each duration of service in the two queues is an exponential random variable with rate μ and no jockeying is permitted between the two queues. A new numerical method, based on linear programming and convex optimization, is performed for the computation of the steady state solution of the system.

Multivariate School Travel Demand Regression Based on Trip Attraction

Since primary school trips usually start from home, attention by many scholars have been focused on the home end for data gathering. Thereafter category analysis has often been relied upon when predicting school travel demands. In this paper, school end was relied on for data gathering and multivariate regression for future travel demand prediction. 9859 pupils were surveyed by way of questionnaires at 21 primary schools. The town was divided into 5 zones. The study was carried out in Skudai Town, Malaysia. Based on the hypothesis that the number of primary school trip ends are expected to be the same because school trips are fixed, the choice of trip end would have inconsequential effect on the outcome. The study compared empirical data for home and school trip end productions and attractions. Variance from both data results was insignificant, although some claims from home based family survey were found to be grossly exaggerated. Data from the school trip ends was relied on for travel demand prediction because of its completeness. Accessibility, trip attraction and trip production were then related to school trip rates under daylight and dry weather conditions. The paper concluded that, accessibility is an important parameter when predicting demand for future school trip rates.

Feature Reduction of Nearest Neighbor Classifiers using Genetic Algorithm

The design of a pattern classifier includes an attempt to select, among a set of possible features, a minimum subset of weakly correlated features that better discriminate the pattern classes. This is usually a difficult task in practice, normally requiring the application of heuristic knowledge about the specific problem domain. The selection and quality of the features representing each pattern have a considerable bearing on the success of subsequent pattern classification. Feature extraction is the process of deriving new features from the original features in order to reduce the cost of feature measurement, increase classifier efficiency, and allow higher classification accuracy. Many current feature extraction techniques involve linear transformations of the original pattern vectors to new vectors of lower dimensionality. While this is useful for data visualization and increasing classification efficiency, it does not necessarily reduce the number of features that must be measured since each new feature may be a linear combination of all of the features in the original pattern vector. In this paper a new approach is presented to feature extraction in which feature selection, feature extraction, and classifier training are performed simultaneously using a genetic algorithm. In this approach each feature value is first normalized by a linear equation, then scaled by the associated weight prior to training, testing, and classification. A knn classifier is used to evaluate each set of feature weights. The genetic algorithm optimizes a vector of feature weights, which are used to scale the individual features in the original pattern vectors in either a linear or a nonlinear fashion. By this approach, the number of features used in classifying can be finely reduced.

Effects of Wastewater Strength and Salt Stress on Microalgal Biomass Production and Lipid Accumulation

This work aims to investigate a potential of microalgae for utilizing industrial wastewater as a cheap nutrient for their growth and oil accumulation. Wastewater was collected from the effluent ponds of agro-industrial factories (cassava and ethanol production plants). Only 2 microalgal strains were isolated and identified as Scenedesmus quadricauda and Chlorella sp.. However, only S. quadricauda was selected to cultivate in various wastewater concentrations (10%, 20%, 40%, 60%, 80% and 100%). The highest biomass obtained at 6.6×106 and 6.27×106 cells/ml when 60% wastewater was used in flask and photo-bioreactor. The cultures gave the highest lipid content at 18.58 % and 42.86% in cases of S. quadricauda and S. obliquus. In addition, under salt stress (1.0 M NaCl), S. obliquus demonstrated the highest lipid content at 50% which was much more than the case of no NaCl adding. However, the concentration of NaCl does not affect on lipid accumulation in case of S. quadricauda.

Statistics over Lyapunov Exponents for Feature Extraction: Electroencephalographic Changes Detection Case

A new approach based on the consideration that electroencephalogram (EEG) signals are chaotic signals was presented for automated diagnosis of electroencephalographic changes. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. This paper presented the usage of statistics over the set of the Lyapunov exponents in order to reduce the dimensionality of the extracted feature vectors. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Multilayer perceptron neural network (MLPNN) architectures were formulated and used as basis for detection of electroencephalographic changes. Three types of EEG signals (EEG signals recorded from healthy volunteers with eyes open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. The selected Lyapunov exponents of the EEG signals were used as inputs of the MLPNN trained with Levenberg- Marquardt algorithm. The classification results confirmed that the proposed MLPNN has potential in detecting the electroencephalographic changes.

The Weight of Corporate Social Responsibility Indicators in Measurement Procedure

The Corporate Social Responsibility (CSR) performance has garnered significant interest during the last two decades as numerous methodologies are proposed by Social Responsible Investment (SRI) indexes. The weight of each indicator is a crucial component of the CSR measurement procedures. Based on a previous study, the appropriate weight of each proposed indicator for the Greek telecommunication sector is specified using the rank reciprocal weighting. The Kendall-s Coefficient of Concordance and Spearman Correlation Coefficient non-parametric tests are adopted to determine the level of consensus among the experts concerning the importance rank of indicators. The results show that there is no consensus regarding the rank of indicators in most of stakeholders- domains. The equal weight for all indicators could be proposed as a solution for the lack of consensus among the experts. The study recommends three different equations concerning the adopted weight approach.

Thermal Analysis of the Current Path from Circuit Breakers Using Finite Element Method

This paper describes a three-dimensional thermal model of the current path included in the low voltage power circuit breakers. The model can be used to analyse the thermal behaviour of the current path during both steady-state and transient conditions. The current path lengthwise temperature distribution and timecurrent characteristic of the terminal connections of the power circuit breaker have been obtained. The influence of the electric current and voltage drop on main electric contact of the circuit breaker has been investigated. To validate the three-dimensional thermal model, some experimental tests have been done. There is a good correlation between experimental and simulation results.

Exponential Stability Analysis for Switched Cellular Neural Networks with Time-varying Delays and Impulsive Effects

In this Letter, a class of impulsive switched cellular neural networks with time-varying delays is investigated. At the same time, parametric uncertainties assumed to be norm bounded are considered. By dividing the network state variables into subgroups according to the characters of the neural networks, some sufficient conditions guaranteeing exponential stability for all admissible parametric uncertainties are derived via constructing appropriate Lyapunov functional. One numerical example is provided to illustrate the validity of the main results obtained in this paper.

Cardiac Function and Morphological Adaptations in Endurance and Resistance Athletes: Evaluation using a new Method

Background: Tissue Doppler Echocardiography (TDE) assesses diastolic function more accurately than routine pulse Doppler echo. Assessment of the effects of dynamic and static exercises on the heart by using TDE can provides new information about the athlete-s heart syndrome. Methods: This study was conducted on 20 elite wrestlers, 14 endurance runners at national level and 21 non-athletes as the control group. Participants underwent two-dimensional echocardiography, standard Doppler and TDE. Results: Wrestlers had the highest left ventricular mass index, enddiastolic inter-ventricular septum thickness and left ventricular Posterior wall thickness. Runners had the highest Left ventricular end-diastolic volume, LV ejection fraction, stroke volume and cardiac output. In TDE, the early diastolic velocity of mitral annulus to the late diastolic velocity ratio in athletic groups was greater than the controls with no significant difference. Conclusion: In spite of cardiac morphological changes in athletes, TDE shows that cardiac diastolic function won-t be adversely affected.

Self-tuned LMS Algorithm for Sinusoidal Time Delay Tracking

In this paper the problem of estimating the time delay between two spatially separated noisy sinusoidal signals by system identification modeling is addressed. The system is assumed to be perturbed by both input and output additive white Gaussian noise. The presence of input noise introduces bias in the time delay estimates. Normally the solution requires a priori knowledge of the input-output noise variance ratio. We utilize the cascade of a self-tuned filter with the time delay estimator, thus making the delay estimates robust to input noise. Simulation results are presented to confirm the superiority of the proposed approach at low input signal-to-noise ratios.

Second Order Admissibilities in Multi-parameter Logistic Regression Model

In multi-parameter family of distributions, conditions for a modified maximum likelihood estimator to be second order admissible are given. Applying these results to the multi-parameter logistic regression model, it is shown that the maximum likelihood estimator is always second order inadmissible. Also, conditions for the Berkson estimator to be second order admissible are given.

The Smoke Suppression Effect of Copper Oxideon the Epoxy Resin/Intumescent Flame Retardant/Titanate Couple Agent System

Fire disaster is the major factor to endanger the public and environmental safety. People lost their life during fire disaster mainly be attributed to the dense smoke and toxic gas under combustion, which hinder the escape of people and the rescue of firefighters under fire disaster. The smoke suppression effect of several transitional metals oxide on the epoxy resin treated with intumescent flame retardant and titanate couple agent (EP/IFR/Titanate) system have been investigated. The results showed manganese dioxide has great effect on reducing the smoke density rate (SDR) of EP/IFR/Titanate system; however it has little effect to reduce the maximum smoke density (MSD) of EP/IFR/Titanate system. Copper oxide can decrease the maximum smoke density (MSD) and smoke density rate of EP/IFR/Titanate system substantially. The MSD and SDR of EP/IFR/Titanate system can reduce 20.3% and 39.1% respectively when 2% of copper oxide is introduced.