Nucleation and Growth Characteristics of Cavities during the Early Stages of Tensile Creep Deformation in a Superplastic Zirconia–20 wt% Alumina Composite

Constant-stress tensile creep experiments on a superplastic 3-mol%-yttria-stabilized tetragonal zirconia composite with 20 wt% alumina revealed that cavities nucleate relatively early during tensile deformation. The number of cavities nucleated increases with increasing imposed stress. The cavities nucleate at triple points associated largely with an alumina grain, and then grow rapidly in a cracklike manner to attain dimensions on the order of the grain facet size. It is suggested that coarser-grained superplastic ceramics exhibit lower ductility due to the ease in formation of such grain boundary facet-cracks and their interlinkage to form a macroscopic crack of critical dimensions.     

On the induction plasma deposition of tungsten metal

The central particle injection and long residence time characteristics of induction plasma have given rise to the complete melting of tungsten particles injected into an Ar- H₂ plasma under soft vacuum conditions. The influences of process variables such as power level, chamber pressure, and spray distance on splat morphology, apparent density, and deposition efficiency have been studied. Dense tungsten deposits with no oxidation have been obtained. Scanning electron microscopy (SEM) micrographs reveal a well-flattened lamellar structure in deposits. Radiative cooling is observed to play a significant role in the plasma spraying of this refractory metal.     

Upper bound on singlet fraction of two-qubit mixed entangled states

We demonstrate a new method to achieve the maximum singlet fraction using an entangled mixed two-qubit state as a resource. For this, we establish a tight upper bound on singlet fraction and show that the maximal singlet fraction obtained in Verstraete and Verschelde (Phys Rev Lett 90:097901(1)–097901(4), 2003) does not attain the upper bound on the singlet fraction derived here. Interestingly, we found that the required upper bound can, in fact, be achieved using local filtering operations.     

Communication controller and control unit design for Qi wireless power transfer

Qi, the wireless power standard, has been proposed to allow low power systems to receive power through wireless inductive power transfer. The standard outlines the essential, desired and optional requirements for developing the wireless power transfer platform. In this paper, we present the design and implementation results of communication controller for guided positioning single transmitter–single receiver wireless power transfer platform. Apart from the basic design, additional processing and data storage capability is introduced to make the design adaptive in terms of response time and the size of control data transfer. The method of estimating the amount of power transfer is modified to reduce design complexity and internal power consumption of power transmitter and receiver. The implementation results help to access the ratio of power transferred to resource utilization and the ratio of power transferred to power consumed in simplistic wireless power transfer platform.     

Designing parity check matrix to achieve linear encoding time in LDPC codes

Low-density parity-check (LDPC) codes have become the part of various communication standards due to their excellent error correcting performance. Existing methods require matrix inverse computation for obtaining a systematic generator matrix from parity check matrix. With the change in code rate or code length the process is repeated and hence, a large number of pre-processing computations time and resources are required. In the existing methods, the complexity of encoding is essentially quadratic with respect to the block length. In this paper, it is shown that the parity check matrix can be constructed using patterned sub-matrix structure such that the matrix inverse operation is replaced by matrix multiplication of sparse matrices. The sparseness of matrices is then utilized to obtain efficient encoders which can achieve encoding in real time with reduced pre-computation complexity. Hardware implementation of encoder and simulation results show that the proposed encoder achieves throughput in excess of 1 Gbps with the same error correcting performance as the conventional designs.     

Optimal job sequence determination and operation machine allocation in flexible manufacturing systems: an approach using adaptive hierarchical ant colony algorithm

In this paper, an Adaptive Hierarchical Ant Colony Optimization (AHACO) has been proposed to resolve the traditional machine loading problem in Flexible Manufacturing Systems (FMS). Machine loading is one of the most important issues that is interlinked with the efficiency and utilization of FMS. The machine loading problem is formulated in order to minimize the system unbalance and maximize the throughput, considering the job sequencing, optional machines and technological constraints. The performance of proposed AHACO has been tested over a number of benchmark problems taken from the literature. Computational results indicate that the proposed algorithm is more effective and produces promising results as compared to the existing solution methodologies in the literature. The evaluation and comparison of system efficiency and system utilization justifies the supremacy of the algorithm. Further, results obtained from the proposed algorithm have been compared with well known random search algorithm viz. genetic algorithm, simulated annealing, artificial Immune system, simple ant colony optimization, tabu search etc. In addition, the algorithm has been tested over a randomly generated problem set of varying complexities; the results validate the robustness and scalability of the algorithm utilizing the concepts of ‘heuristic gap’ and ANOVA analysis.     

Magnetic field-assisted photochemical machining (MFAPCM) of SS316L

In this paper, a new technique of photochemical machining (PCM) process has been described. The objective of this study is to investigate the effect of applying a magnetic field on the PCM of AISI 316?L stainless steel. The experiments were planned and conducted using a Full Factorial Design (FFD) approach. The control parameters selected were magnetic field, temperature, concentration and time. The analysis of the results shows significant improvement in the etch rate due to the application of a magnetic field. The highest etch rate was achieved at a concentration of 700?g/l, at the temperature of 60°C in a static magnetic field. The improvement of the etch rate is 2.5 times with the application of magnetic field as compared to the conventional PCM process.     

Biosynthesis of zinc oxide nanoparticles by petals extract of Rosa indica L., its formulation as nail paint and evaluation of antifungal activity against fungi causing onychomycosis

Aim: The authors report the biological synthesis of zinc oxide nanoparticles (ZnO‐NPs) from the petals extract of Rosa indica L. (rose). Its efficacy was evaluated against two dermatophytes: namely: Trichophyton mentagrophytes and Microsporum canis which cause onychomycosis. The activity of antibiotics against the tested dermatophytes was enhanced, when evaluated in combination with ZnO‐NPs. Methods and results: The synthesised ZnO‐NPs were preliminary detected by using ultraviolet UV visible spectroscopy, which showed specific absorbance. The ZnO‐NPs were further characterised by nanoparticle tracking analysis (NTA), Fourier transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), X‐ray diffraction and Zetasizer. Moreover, nanoparticles containing nail paint (nanopaint) was formulated and its antifungal activity was also assessed against T. mentagrophytes and M. canis. ZnO‐NPs and formulated nanopaint containing ZnO‐NPs, both showed significant antifungal activity. The maximum activity was noted against M. canis and lesser against T. mentagrophytes. Minimum inhibitory concentration of ZnO‐NPs was also determined against the dermatophytes causing onychomycosis infection. Conclusion: ZnO‐NPs can be utilised as a potential antifungal agent for the treatment of onychomycosis after more experimental trials.Inspec keywords: diseases, zinc compounds, nanoparticles, nanofabrication, antibacterial activity, microorganisms, nanomedicine, ultraviolet spectra, visible spectra, Fourier transform infrared spectra, transmission electron microscopy, X‐ray diffraction, biomedical materials, patient treatmentOther keywords: zinc oxide nanoparticle biosynthesis, Rosa indica L petals extract, nail paint, antifungal activity evaluation, dermatophyte, Trichophyton mentagrophytes, Microsporum canis, antibiotics activity, ultraviolet‐visible spectroscopy, nanoparticle tracking analysis, Fourier transform infrared spectroscopy, transmission electron microscopy, X‐ray diffraction, zetasizer, antifungal agent, onychomycosis treatment     

VMI versus information sharing: an analysis under static uncertainty strategy with fill rate constraints

A vendor-managed inventory (VMI) relationship between a downstream retailer and an upstream vendor consists of two distinct components: (i) information sharing (IS) and (ii) a shift in decision-making responsibility. This study compares these two components of VMI in a two-stage serial supply chain based on the ‘static uncertainty’ strategy under dynamic and random demand with fill rate constraints. Numerical experiments are conducted using analytical models to identify the conditions where the incremental value of VMI over IS is significant. The results provide guidelines relevant to academia and supply chain practitioners in taking VMI adoption decision above and beyond IS according to their specific business environment.     

Fusion of probabilistic A* algorithm and fuzzy inference system for robotic path planning

Robotic Path planning is one of the most studied problems in the field of robotics. The problem has been solved using numerous statistical, soft computing and other approaches. In this paper we solve the problem of robotic path planning using a combination of A* algorithm and Fuzzy Inference. The A* algorithm does the higher level planning by working on a lower detail map. The algorithm finds the shortest path at the same time generating the result in a finite time. The A* algorithm is used on a probability based map. The lower level planning is done by the Fuzzy Inference System (FIS). The FIS works on the detailed graph where the occurrence of obstacles is precisely known. The FIS generates smoother paths catering to the non-holonomic constraints. The results of A* algorithm serve as a guide for FIS planner. The FIS system was initially generated using heuristic rules. Once this model was ready, the fuzzy parameters were optimized using a Genetic Algorithm. Three sample problems were created and the quality of solutions generated by FIS was used as the fitness function of the GA. The GA tried to optimize the distance from the closest obstacle, total path length and the sharpest turn at any time in the journey of the robot. The resulting FIS was easily able to plan the path of the robot. We tested the algorithm on various complex and simple paths. All paths generated were optimal in terms of path length and smoothness. The robot was easily able to escape a variety of obstacles and reach the goal in an optimal manner.