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.     

Automatic navigation of mobile robots in unknown environments

Online navigation with known target and unknown obstacles is an interesting problem in mobile robotics. This article presents a technique based on utilization of neural networks and reinforcement learning to enable a mobile robot to learn constructed environments on its own. The robot learns to generate efficient navigation rules automatically without initial settings of rules by experts. This is regarded as the main contribution of this work compared to traditional fuzzy models based on notion of artificial potential fields. The ability for generalization of rules has also been examined. The initial results qualitatively confirmed the efficiency of the model. More experiments showed at least 32 % of improvement in path planning from the first till the third path planning trial in a sample environment. Analysis of the results, limitations, and recommendations is included for future work.     

CHARACTERIZATION OF EFFECTIVE TIRE CONTACT AREA FOR VARIOUS TREAD PATTERNS

The effective tire-pavement contact area affects the relative damage of asphalt pavement and should be incorporated in both mechanistic and empirical response analyses of pavements. A new machine called ROTOCOM Wheel Tracker (RCWT) was designed and fabricated to capture the effective tire contact area apart from slab compacting, and conducting simulative laboratory wheel tracking tests. The main focus of this paper is laboratory measurement of effective tire contact areas for various tread patterns. Seven tire treads were selected for the footprint image analyses at five tire loads and four tire inflation pressures. An image processing MATLAB-based program was coded to calculate the contact areas of the 280 imprints obtained from both sides of the RCWT. Factorial analysis indicated significant effects of tire tread, tire load, and inflation pressure on the resulting contact area. Comparison between effective and traditional contact areas indicated that the current pavement design procedure with traditional circular contact area extremely overestimates the actual tire-pavement contact area up to 92%.     

Enhancement of biohydrogen production from sustainable orange peel wastes using Enterobacter species isolated from domestic wastewater

Five facultative anaerobic bacterial isolates were recovered from domestic wastewater. These isolates were identified based on the 16S rRNA as Enterobacter aerogenes (one isolate), Enterobacter cloacae (two isolates), and Cronobacter sakazakii (three isolates). These isolates were examined for their potential to evolve hydrogen on a glucose medium. The most potent hydrogen‐producing isolates, E aerogenes (KY549389) and E cloacae (KY524293), were examined for their capacity to generate hydrogen, acetone, butanol, and ethanol using orange peel (OP) hydrolysate. OP powder was pretreated with n‐hexane to remove the toxicity of d ‐limonene. Different concentrations (4%, 6%, and 8% w/v) of limonene‐free OP were subjected to the boiling water (temperature of 100°C) or acid (HCl) treatments. The maximum fermentative H₂ production of 1700 and 1620 mL/L was obtained from 6% OP hydrolysate extracted with boiling water using facultative anaerobic E aerogenes (KY549389) and E cloacae (KY524293), respectively. Hydrogen production efficiency was 0.99 and 1.19 mol H₂/mol glucose for E aerogenes and E cloacae, respectively. The total fermentative acetone, butanol, and ethanol (ABE) generated by E aerogenes and E cloacae were 0.78 and 0.38 g/L including acetone (0.05 and 0.04 g/L), butanol (0.011 and 0.013 g/L), and ethanol (0.71 and 0.32 g/L), respectively. The maximum ABE productivity was 0.01 and 0.005 g/L/h generated at 60 g/L OP hydrolysate by E aerogenes and E cloacae, respectively. These strains were positive for nitrogen fixation (nitrogenase) capability estimated by the acetylene reduction assay. Application of OP hydrolysate without the addition of any nutritional components or reducing agent is considered an eco‐friendly, economical, and commercial substrate for desired biofuel production.     

Design and implementation of a new tuned hybrid intelligent model to predict the uniaxial compressive strength of the rock using SFS-ANFIS

This study proposes a novel design to systematically optimize the parameters for the adaptive neuro-fuzzy inference system (ANFIS) model using stochastic fractal search (SFS) algorithm. To affirm the efficiency of the proposed SFS-ANFIS model, the predicting results were compared with ANFIS and three hybrid methodologies based on ANFIS combined with genetic algorithm (GA), differential evolution (DE), and particle swarm optimization (PSO). Accurate prediction of uniaxial compressive strength (UCS) is of great significance for all geotechnical projects such as tunnels and dams. Hence, this study proposes the use of SFS-ANFIS, GA-ANFIS, DE-ANFIS, PSO-ANFIS, and ANFIS models to predict UCS. In this regard, the fresh water tunnel of Pahang–Selangor located in Malaysia was considered and the requirement data samples were collected. Different statistical metrics such as coefficient of determination (R²) and mean absolute error were used to evaluate the models. Referring to the efficiency results of SFS-ANFIS, it can be found that the SFS-ANFIS (with the R² of 0.981) has higher ability than PSO-ANFIS, DE-ANFIS, GA-ANFIS, and ANFIS models in predicting the UCS.

     

The effects of a “distinct window” screen design on computer-mediated group decision making

An experiment was performed to test a distinct-window conferencing screen design as an electronic cue of social status differences in computer-mediated group decision-making. The screen design included one distinct window to symbolize high-status, and two nondistinct windows to symbolize low-status. The results indicated that the distinct-window screen design did produce status affects in groups of peers making decisions on judgmental problems. Randomly assigned occupants of the distinct window had greater influence on group decisions and member's attitudes than occupants of nondistinct windows.The authors would like to thank Shyam Kamadolli and Phaderm Nangsue, the programmers who developed the software used in this experiment. We would also like to thank the editor and our three anonymous reviewers for exceedingly helpful comments on an earlier draft of this article.     

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.