Methanol oxidation on Au/TiO2 catalysts

We have investigated the adsorption and reaction of methanol with Au/TiO₂ catalysts using a pulsed flow reactor, DRIFTS and TPD. The TiO₂ (P25) surface adsorbed a full monolayer of methanol, much of it in a dissociative manner, forming methoxy groups associated with the cationic sites, and hydroxyl groups at the anions. The methoxy is relatively stable until 250 °C, at which point decomposition occurs, producing mainly dimethyl ether by a bimolecular surface reaction. As the concentration of methoxy on the surface diminishes, so the mechanism reverts to a de-oxygenation pathway, producing mainly methane and water (at ~330 °C in TPD), but also with some coincident CO and hydrogen. Au catalysts were prepared by the deposition-precipitation method to give Au loadings between 0.5–3 wt %. The effect of low levels of Au on the reactivity is marked. The pathway which gives methane, which is characteristic of titania, remains, but a new feature of the reaction is the evolution of CO₂ and H₂ at lower temperature (a peak is seen in TPD at 220 °C), and the elimination of the DME-producing state. Clearly this is associated with the presence of Au and appears to be due to the production of a formate species on the surface of the Au component. This formate species is mainly involved in the reaction of methanol with the Au/TiO₂ catalysts which results in a combustion pathway being followed, with complete conversion occurring by ~130 °C.     

Content of antinutritional factors and HCl-extractability of minerals from white bean (Phaseolus vulgaris) cultivars: Influence of soaking and/or cooking

White bean seeds were subjected to soaking in distilled water for 1, 2 and 3 days. In order to perform complete processing, the seeds were cooked until soft. Effects of soaking and/or cooking of white bean seeds on antinutritional factors, mineral contents and HCl-extractability were studied. Phytic acid and polyphenol contents of all cultivars were reduced. Soaking alone and soaking, followed by cooking, reduced mineral contents of the cultivars, but HCl-extractability was significantly (P ? 0.01) improved to varying extents, depending on cultivar type. Soaking and/or cooking treatment was thus found to be an effective technique and caused further improvement in the availability of both major and trace minerals in white bean.     

Process Development and Product Quality of Micro-Metal Powder Injection Molding

Injection molding has been found to be an efficient and cost-effective manufacturing technique for the production of a wide variety of parts and components at both macro- and microscale. This is attributed to the application of robust design and process development. However, every manufacturing technique is challenged by quality issues and part defects, but tackled by continuous improvement framework(s). This systematic monitoring and control approach of dimensional accuracy, mechanical properties, and surface quality of the finished part strongly depend on process conditions at different production stage. Therefore, the aim of this study is to review process development of micro-metal injection molding; focusing on critical factors influencing part quality and optimization of process parameters. The critical factors that influenced the finished part quality are part design, mold design, material selection, machine, and process conditions. Optimizing mold temperature, melt temperature, injection speed, injection pressure, cooling time, packing, and holding parameters improve the quality of the molded part. This trend of process development of injection molding gave rise to a broad scope of applications with brighter future potentials for the next decades, particularly for medical and electronics applications.     

A systematic review and meta-analysis of artificial neural network application in geotechnical engineering: theory and applications

Artificial neural network (ANN) aimed to simulate the behavior of the nervous system as well as the human brain. Neural network models are mathematical computing systems inspired by the biological neural network in which try to constitute animal brains. ANNs recently extended, presented, and applied by many research scholars in the area of geotechnical engineering. After a comprehensive review of the published studies, there is a shortage of classification of study and research regarding systematic literature review about these approaches. A review of the literature reveals that artificial neural networks is well established in modeling retaining walls deflection, excavation, soil behavior, earth retaining structures, site characterization, pile bearing capacity (both skin friction and end-bearing) prediction, settlement of structures, liquefaction assessment, slope stability, landslide susceptibility mapping, and classification of soils. Therefore, the present study aimed to provide a systematic review of methodologies and applications with recent ANN developments in the subject of geotechnical engineering. Regarding this, a major database of the web of science has been selected. Furthermore, meta-analysis and systematic method which called PRISMA has been used. In this regard, the selected papers were classified according to the technique and method used, the year of publication, the authors, journals and conference names, research objectives, results and findings, and lastly solution and modeling. The outcome of the presented review will contribute to the knowledge of civil and/or geotechnical designers/practitioners in managing information in order to solve most types of geotechnical engineering problems. The methods discussed here help the geotechnical practitioner to be familiar with the limitations and strengths of ANN compared with alternative conventional mathematical modeling methods.

     

Grey and black optical solitary waves,and modulation instability analysis to the perturbed nonlinear Schrödinger equation with Kerr law nonlinearity

This paper addresses the nonlinear Schrödinger equation (NLSE) with Kerr law nonlinearity and perturbation terms in optical fibre. A class of grey and black optical solitary wave solutions of this equation are retrieved by adopting an appropriate solitary wave ansatz solution. These types of solitary waves play a vital role in understanding various physical phenomena in nonlinear systems. This lead to a constraint condition on the solitary wave parameters which must hold for the solitary waves to exist. Moreover, the modulation instability (MI) analysis of the model is studied by employing the concept of linear-stability analysis (LSA) and the MI gain spectrum is got. Physical interpretations of the acquired results are demonstrated. It is hoped that the results reported in this paper can enrich the nonlinear dynamical behaviours of the equation.     

A survey of symbiotic organisms search algorithms and applications

Nature-inspired algorithms take inspiration from living things and imitate their behaviours to accomplish robust systems in engineering and computer science discipline. Symbiotic organisms search (SOS) algorithm is a recent metaheuristic algorithm inspired by symbiotic interaction between organisms in an ecosystem. Organisms develop symbiotic relationships such as mutualism, commensalism, and parasitism for their survival in ecosystem. SOS was introduced to solve continuous benchmark and engineering problems. The SOS has been shown to be robust and has faster convergence speed when compared with genetic algorithm, particle swarm optimization, differential evolution, and artificial bee colony which are the traditional metaheuristic algorithms. The interests of researchers in using SOS for handling optimization problems are increasing day by day, due to its successful application in solving optimization problems in science and engineering fields. Therefore, this paper presents a comprehensive survey of SOS advances and its applications, and this will be of benefit to the researchers engaged in the study of SOS algorithm.

     

Fault tolerance aware scheduling technique for cloud computing environment using dynamic clustering algorithm

In cloud computing, resources are dynamically provisioned and delivered to users in a transparent manner automatically on-demand. Task execution failure is no longer accidental but a common characteristic of cloud computing environment. In recent times, a number of intelligent scheduling techniques have been used to address task scheduling issues in cloud without much attention to fault tolerance. In this research article, we proposed a dynamic clustering league championship algorithm (DCLCA) scheduling technique for fault tolerance awareness to address cloud task execution which would reflect on the current available resources and reduce the untimely failure of autonomous tasks. Experimental results show that our proposed technique produces remarkable fault reduction in task failure as measured in terms of failure rate. It also shows that the DCLCA outperformed the MTCT, MAXMIN, ant colony optimization and genetic algorithm-based NSGA-II by producing lower makespan with improvement of 57.8, 53.6, 24.3 and 13.4 % in the first scenario and 60.0, 38.9, 31.5 and 31.2 % in the second scenario, respectively. Considering the experimental results, DCLCA provides better quality fault tolerance aware scheduling that will help to improve the overall performance of the cloud environment.

     

Optimization of furfural production from millet husk using response surface methodology

Biomass has been recognized as a viable source for energy and bio-based chemicals. This study reported furfural production from millet husk via simultaneous hydrolysis and dehydration processes. Effect of reaction variables such as temperature (120–200°C), resident time (15–45 min), and acid concentration (5–10%) was studied using central composite design. Furfural yield (71.55%) was achieved at 184°C, 39 min, and 9% acid concentration. FT-IR spectrum of the produced furfural showed absorption at 1,697 and 2,880 cm^?1 indicating a conjugated carbonyl functional group and aldehydic hydrogen. The results revealed that millet husk could be a potential substrate for furfural production.     

Efficient Resource Allocation with Improved Interference Mitigation in FFR-Aided OFDMA Heterogeneous Networks

Fractional frequency reuse (FFR) has recently emerged as an efficient inter-cell interference coordination technique for orthogonal frequency division multiple access (OFDMA) based multi-tier cellular networks due to its low complexity, minimal signaling over-head, and coverage improvement. In this work, an intermediary region (IR) at the border of the center region (CR) and edge region (ER) is defined, which prevents severe cross-tier interference and is usually ignored by other schemes. Furthermore, a strategic resource allocation scheme is proposed, which allows macro users in this new region to be served more resources due to their good channel conditions close to the serving base station (BS), while femto users are assigned resource blocks from sub-bands that receive the least net interference from a set of usable sub-bands in any region. We find by analysis and simulation the optimal threshold for IR, which minimizes the cross-tier interference, and show that the femto throughput is also maximized for this threshold. Numerical results show the proposed scheme outperforms other notable schemes in terms of throughput and outage performances.