Pd/Cu-Free Cobalt-Catalyzed Suzuki and Heck Using Green Bio-Magnetic Hybrid and DFT-Based Theoretical Study

Catalysis Letters - Several highly efficient and magnetically recyclable cobalt catalytic systems were prepared using magnetic chitosan and some safe and available organic compounds...     

Complexity and design of QoS routing algorithms in wireless mesh networks

Quality of service (QoS) provisioning in wireless mesh networks (WMNs) is an open issue to support emerging multimedia services. In this paper, we study the problem of QoS provisioning in terms of end-to-end bandwidth allocation in WMNs. It is challenging due to interferences in the networks. We consider widely used interference models and show that except a few special cases, the problem of finding a feasible path is NP-complete under the models. We propose a k-shortest path based algorithmic framework to solve this problem. We also consider the problem of optimizing network performance by on-line dynamic routing, and adapt commonly used conventional QoS routing metrics to be used in WMNs. We find the optimal solutions for these problems through formulating them as optimization models. A model is developed to check the existence of a feasible path and another to find the optimal path for a demand; moreover, an on-line optimal QoS routing algorithm is developed. Comparing the algorithms implemented by the proposed framework with the optimization models shows that our solution can find existing feasible paths with high probability, efficiently optimizes path lengths, and has a comparable performance to the optimal QoS routing algorithm. Furthermore, our results show that contrary to wireline networks, minimizing resource consumption should be preferred over load distribution even in lightly loaded WMNs.     

Heterogenous Server Placement for Delay Sensitive Applications in Green Mobile Edge Computing

Wireless Personal Communications - The importance of environmental pollution has motivated the researchers to investigate the electrical power consumption of any emerging technology. Edge Computing...     

Optimizing linear alkyl benzene sulfonate removal using Fenton oxidation process in Taguchi Method

Linear alkyl benzene sulfonate (LAS), which is the most common used anionic surfactant in detergents manufacturing, can discharge onto water resources through wastewater and causes change in taste and odor, disruption in water treatment processes, aquatics death, and oxygen transfer limitation. Accordingly, this article investigates to optimize LAS removal using Fenton oxidation process in Taguchi Method for the first time. LAS removal using Fenton oxidation was perused experimentally in a lab-scale reactor. In order to save relevant costs, 25 runs were qualified to specify the optimum conditions of Fenton oxidation using Taguchi method by Minitab 16 software. Sampling and testing procedures were executed based on the standard methods for the examination of water and wastewater. The optimum conditions included 900 mg/L hydrogen peroxide, 170 mg/L ferrous ion, pH of 4 and the reaction time of 20 min. Fenton oxidation, as a second order reaction with the rate coefficient of 0.0152 L/mg?min, provided 86.5% efficiency for LAS removal in the optimum conditions. Despite Fenton oxidation appeared as a high efficiency process in LAS removal, low removal efficiency of chemical oxygen demand corresponding with LAS affirmed its partial degradation.     

Application of adaptive neuro-fuzzy inference system in prediction of fluid density for a gamma ray densitometer in petroleum products monitoring

This paper presents the application of adaptive neuro-fuzzy inference system (ANFIS) for prediction of fluid density in a previously designed and constructed gamma ray densitometer for pipes of various diameters and different fluids densities. The input parameters of the proposed ANFIS model are the pipe diameter and the number of the counted photons and the output is the density of the considered material. The required data for training and testing the ANFIS model has been obtained based on simulations using MCNP4C Monte Carlo code. A hybrid learning algorithm consists of back-propagation and least-squares estimation is used for training the proposed ANFIS model. Simulations for 4-in. polyethylene pipe had been validated with the experimental data previously. The proposed ANFIS model has achieved good agreement with the experimental results and has a small error between the estimated and experimental values. The obtained results show that the mean relative error percentage (MRE%) for training and testing data are less than 2.14% and 2.64%, respectively.     

Antimicrobial Ionic Liquid-Based Materials for Biomedical Applications

Excessive and unwarranted administration of antibiotics has invigorated the evolution of multidrug-resistant microbes. There is, therefore, an urgent need for advanced active compounds. Ionic liquids with short-lived ion-pair structures are highly tunable and have diverse applications. Apart from their unique physicochemical features, the newly discovered biological activities of ionic liquids have fascinated biochemists, microbiologists, and medical scientists. In particular, their antimicrobial properties have opened new vistas in overcoming the current challenges associated with combating antibiotic-resistant pathogens. Discussions regarding ionic liquid derivatives in monomeric and polymeric forms with antimicrobial activities are presented here. The antimicrobial mechanism of ionic liquids and parameters that affect their antimicrobial activities, such as chain length, cation/anion type, cation density, and polymerization, are considered. The potential applications of ionic liquids in the biomedical arena, including regenerative medicine, biosensing, and drug/biomolecule delivery, are presented to stimulate the scientific community to further improve the antimicrobial efficacy of ionic liquids.     

Performance analysis of the internet‐protocol multimedia‐subsystem's control layer using a detailed queueing Petri‐net model

In the current trend in telecommunications industry towards all‐internet‐protocol (IP) infrastructures, IP multimedia subsystem (IMS) plays a critical role by providing a coherent data and control‐plane solution for large‐scale live multimedia applications in a flexible and cost‐effective manner. On the other hand, such a large‐scale service platform would inevitably fail without effective support for the quality‐of‐service (QoS) requirements perceived by its users. Among the most important factors that influence user QoS are system performance and scalability. In this paper, a performance model for IMS systems is developed using the queueing Petri nets (QPNs) as the modeling formalism. The model's parameters are tuned based on the measurements carried out using a well‐known IMS implementation. The model is validated against the real system. During the model calibration, the Java garbage‐collector process used in the home subscriber‐server (HSS) implementation was found to be a main factor in the discrepancy between the model and the reality. In addition, the effects of other factors such as the network stack in the operating system are investigated. The validated model is employed to give insights into the scalability of every single instance of IMS implementation. The model is extended to study load balancing among multiple instances of HSS to remove the main bottleneck in the system. It provides a valuable platform for resource management of various components of the IMS ecosystem to support the intended level of QoS for the users.     

Multi-Objective Firefly Integration with the K-Nearest Neighbor to Reduce Simulation Model Calls to Accelerate the Optimal Operation of Multi-Objective Reservoirs

Reservoirs are used as one of the surface water sources for different and often conflicting water supply purposes. Given the complex management policies governing a basin, it is essential to simultaneously consider different goals and cope with the associated trade-off in water resources management. This purpose requires coupling a multi-objective optimization algorithm with a reservoir simulation model, which this approach increases required computational efforts. Various simulation–optimization approaches have been developed and used for solving the related problems. However, they often have complicated methods and certain limitations in real-world applications. In this study, a new multi-objective firefly algorithm—K nearest neighbor (MOFA-KNN) hybrid algorithm is developed which is time-efficient and is not as complicated as previous approaches. The proposed algorithm was evaluated for both benchmark and real problems. The results of the benchmark problem showed that the execution time of the MOFA-KNN hybrid algorithm was up to 99.98% less than that of the multi-objective firefly algorithm (MOFA). In the real problem, the MOFA-KNN algorithm was linked to the 2D hydrodynamic and water quality model, CE-QUAL-W2, to test the developed framework for reservoir operation. The Aidoghmoush reservoir as a case study investigated to minimize the total released dissolved solids (TDS) and the water temperature difference between the inflow and the outflow. The results demonstrated that the MOFA-KNN algorithm significantly reduced the simulation–optimization execution time (>?660 times compared with MOFA). The minimum released TDS from the reservoir was 13.6 mg /l and the minimum temperature difference was 0.005 °C.

     

The implicit personality theory of Islam.

Almost every traditional personality theorist had something to say about religion, but the topic of how religious beliefs might affect individuals’ views of human nature remains largely unstudied. All religions, however, contain certain implicit ideas regarding personality that are likely to impact individual behavior. This article draws on Islamic sources to consider what a practicing Muslim might believe about motivation, personality development, the self, the unconscious, psychological adjustment, and the individual and society. In general terms, understanding these beliefs can be useful in the broader study of how cultural issues affect personality. More specifically, understanding Islamic beliefs related to personality can assist in planning for the provision of psychological services to Muslims, as well as understanding the psychological perspectives of Muslims who are not extremists. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Robust Flash Calculation Algorithm for Microemulsion Phase Behavior

The HLD-NAC model was recently modified to match and predict microemulsion phase behavior experimental data for Winsor type III regions. Until now, the HLD-NAC model could not generate realistic phase behavior for type II? and type II+ two-phase regions, leading to significant saturation and composition discontinuities when catastrophe theory is applied. These discontinuities lead to significant failures in modeling surfactant applications. We modify the HLD-NAC equations to ensure consistency over the entire composition space including type II? and II+ regions. A robust and efficient algorithm is developed that always converges and provides continuous estimates with any formation variable of tie lines and triangles for all Winsor types. Discontinuities are eliminated and limiting tie lines near critical points are determined analytically. The tuning procedure is demonstrated using several sets of experimental data. Excellent predictability of tie lines and tie triangles, and solubilization ratios are shown.