Background: The diagnosis of Toxoplasma gondii infection in human can be determined by variable immunological and molecular methods.

Leishmaniasis is a widespread parasitic disease that occurs as a result of infection with a unicellular parasite belonging to the genus Leishmania. Diagnosis by conventional methods is inaccurate and is not sensitive to confirm the genus infection. Here, we have investigated a methods for Leishmania genus diagnosis, which includes the technique of polymerase chain reaction to detect the presence of the parasite at in vitro for promastigote cultures using three genus-specific primer pairs to amplify HSP70, ITS, and ITS2. The results showed single band of ~1422, ~1020, and ~550 respectively. This study has proved the ability of these primer pairs to detect Leishmania infection and recommend them to be used for detection of leishmaniasis in

توطئة

ظهر اهتمام متزايد في إدارة سلسلة التجهيز (Supply Chain Management) خلال الأعوام العشرين الماضية، بوصفها مصدراً ثرياً للتنافسية (Competitiveness) وخلق القيمة (Value Creation). ولقد جاء هذا التطور بفعل موجتين من التطور: الأولى، تمثلت بزيادة التوجه نحو التوريد الخارجي الستراتيجي (Strategic Outsourcing) كرؤية للشركات بأن تصبح سريعة جداً بالتركيز على

Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

Energy efficiency is a significant aspect in designing robust routing protocols for wireless sensor networks (WSNs). A reliable routing protocol has to be energy efficient and adaptive to the network size. To achieve high energy conservation and data aggregation, there are two major techniques, clusters and chains. In clustering technique, sensor networks are often divided into non-overlapping subsets called clusters. In chain technique, sensor nodes will be connected with the closest two neighbors, starting with the farthest node from the base station till the closest node to the base station. Each technique has its own advantages and disadvantages which motivate some researchers to come up with a hybrid routing algorit

       This paper treats the interactions among four population species. The system includes one mutuality prey, one harvested prey and two predators. The four species interaction can be described as a food chain, where the first prey helps the second harvested prey. The first and the second predator attack the first and the second prey, respectively, according to Lotka-Volterra type functional responses. The model is formulated using differential equations. One equilibrium point of the model is found and analysed to reveal a threshold that will allow the coexistence of all species. All other equilibrium points of the system are located, with their local and global stability being assessed. To back up the conclusions of the mathema

In this paper, we study the incorporation of the commensalism interaction and harvesting on the Lotka–Volterra food chain model. The system provides one commensal prey, one harvested prey, and two predators. A set of preliminary results in local bifurcation analysis around each equilibrium point for the proposed model is discussed, such as saddle-node, transcritical and pitchfork. Some numerical analysis to confirm the accruing of local bifurcation is illustrated. To back up the conclusions of the mathematical study, a numerical simulation of the model is carried out with the help of the MATLAB program. It can be concluded that the system's coexistence can be achieved as long as the harvesting rate on the second prey population is

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca