New evidence on nanotechnology has shown interest in the creation and assessment of nanoparticles for cancer treatment. Worldwide, a wide range of tumor-targeted approaches are being developed to reduce side effects and boost the efficacy of cancer therapy. One strategy that shows promise is the use of metallic nanoparticles to increase the radio sensitization of the cancer cells while reducing or maintaining the normal tissue complication probability during radiation therapy. In this study, atmospheric plasma was created using argon gas to create Au NPs using the plasma jet scheme, and their ability to induce apoptosis as an anticancer mechanism was tested. Aqueous gold tetrachloride salts (HAuCl4·3H2O) ere used to produce gold nanopartic

In this work, a joint quadrature for numerical solution of the double integral is presented. This method is based on combining two rules of the same precision level to form a higher level of precision. Numerical results of the present method with a lower level of precision are presented and compared with those performed by the existing high-precision Gauss-Legendre five-point rule in two variables, which has the same functional evaluation. The efficiency of the proposed method is justified with numerical examples. From an application point of view, the determination of the center of gravity is a special consideration for the present scheme. Convergence analysis is demonstrated to validate the current method.

In this paper we describe several different training algorithms for feed forward neural networks(FFNN). In all of these algorithms we use the gradient of the performance function, energy function, to determine how to adjust the weights such that the performance function is minimized, where the back propagation algorithm has been used to increase the speed of training. The above algorithms have a variety of different computation and thus different type of form of search direction and storage requirements, however non of the above algorithms has a global properties which suited to all problems.

In this paper, we use concepts and results from percolation theory to investigate and characterize the effects of multi-channels on the connectivity of Dynamic Spectrum Access networks. In particular, we focus on the scenario where the secondary nodes have plenty of vacant channels to choose from-a phenomenon which we define as channel abundance. To cope with the existence of multi-channels, we use two types of rendezvous protocols: naive ones which do not guarantee a common channel and advanced ones which do. We show that, with more channel abundance, even with the use of either type of rendezvous protocol, it becomes difficult for two nodes to agree on a common channel, thereby potentially remaining invisible to each other. We model this

Cognitive radio technology is used to improve spectrum efficiency by having the cognitive radios act as secondary users to access primary frequency bands when they are not currently being used. In general conditions, cognitive secondary users are mobile nodes powered by battery and consuming power is one of the most important problem that facing cognitive networks; therefore, the power consumption is considered as a main constraint. In this paper, we study the performance of cognitive radio networks considering the sensing parameters as well as power constraint. The power constraint is integrated into the objective function named power efficiency which is a combination of the main system parameters of the cognitive network. We prove the exi

In the last two decades, networks had been changed according to the rapid changing in its requirements. The current Data Center Networks have large number of hosts (tens or thousands) with special needs of bandwidth as the cloud network and the multimedia content computing is increased. The conventional Data Center Networks (DCNs) are highlighted by the increased number of users and bandwidth requirements which in turn have many implementation limitations. The current networking devices with its control and forwarding planes coupling result in network architectures are not suitable for dynamic computing and storage needs. Software Defined networking (SDN) is introduced to change this notion of traditional networks by decoupling control and

Planning of electrical distribution networks is considered of highest priority at the present time in Iraq, due to the huge increase in electrical demand and expansions imposed on distribution networks as a result of the great and rapid urban development.

Distribution system planning simulates and studies the behavior of electrical distribution networks under different operating conditions. The study provide understanding of the existing system and to prepare a short term development plan or a long term plan used to guide system expansion and future investments needed for improved network performance.

The objective of this research is the planning of Al_Bayaa 11 kV distribution network in Baghdad city bas

A substantial percentage of the world’s energy consumption (almost 40%) and carbon dioxide (CO2) emissions (around 37%) come from the construction industry, especially schools. This work presents a new hybrid artificial intelligence (AI) engineering model that aims to maximize energy performance on campuses in a holistic way. Modules for data-driven forecasting, metaheuristic optimization, and real-time adaptive control are all part of the concept. A thorough energy simulation of a university campus building is used in conjunction with the AI model to assess its performance through a co-simulation framework. Findings show that yearly peak electricity demand may be reduced by 18.7% and total site energy consumption by 22.4% when co

In this study, a mathematical model is presented to study the chemisorption of two interacting atoms on solid surface in the presence of laser field. Our mathematical model is based on the occupation numbers formula that depends on the laser field which we derived according to Anderson model for single atom adsorbed on solid surface. Occupation numbers formula and chemisorption energy formula are derived for two interacting atoms (as a diatomic molecule) as they approach to the surface taking into account the correlation effects on each atom and between atoms. This model is characterized by obvious dependence of all relations on the system variables and the laser field characteristics which gives precise description for the molecule –

The effect of high energy radiation on the energy gap of compound semiconductor Silicon Carbide (SiC) are viewed. Emphasis is placed on those effects which can be interpreted in terms of energy levels. The goal is to develop semiconductors operating at high temperature with low energy gaps by induced permanent damage in SiC irradiated by gamma source. TEACO2 laser used for producing SiC thin films. Spectrophotometer lambda - UV, Visible instrument is used to determine energy gap (Eg). Co-60, Cs-137, and Sr-90 are used to irradiate SiC samples for different time of irradiation. Possible interpretation of the changing in Eg values as the time of irradiation change is discussed