Bi-objective optimization of the reliability-redundancy allocation problem for series-parallel system

The main objective of this paper is to solve the bi-objective reliability redundancy allocation problem for series-parallel system where reliability of the system and the corresponding designing cost are considered as two different objectives. In their formulation, reliability of each component is considered as a triangular fuzzy number. In order to solve the problem, developed fuzzy model is converted to a crisp model by using expected values of fuzzy numbers and taking into account the preference of decision maker regarding cost and reliability goals. Finally the obtained crisp optimization problem has been solved with particle swarm optimization (PSO) and compared their results with genetic algorithm (GA). Examples are shown to illustrate the method. Finally statistical simulation has been performed for supremacy the approach.     

Light-Dependent Nitrate Removal Capacity of Green Microalgae

In the present study, Chlamydomonas sp. MACC-216 was used to investigate total nitrate removal in TAP medium with sodium nitrate as the sole nitrogen source under several light conditions made up of permuted combinations of three light colors (referred to as blue, red, and white light) and three light intensities (50 µmol m⁻² s⁻¹, 100 µmol m⁻² s⁻¹, and 250 µmol m⁻² s⁻¹). It was observed that nitrate removal efficiency is influenced by light color as well as light intensity. Additionally, Chlamydomonas sp. MACC-216 was cultivated in synthetic wastewater under four light conditions, namely, Blue 250, Blue 125 + Red 125, Red 250, and White 250, where it showed the highest nitrate removal efficiency and nitrate reductase activity under the Blue 125 + Red 125 light condition. To observe the impact of light color on the nitrate removal capacity of Chlamydomonas sp. MACC-216, the expression of five genes participating in nitrate transport and reduction (NRT1, NRT2.1, NRT2.2, NIA, and MCP) was also analyzed; these genes showed the highest expression under the Blue 125 + Red 125 light condition. Based on the above-mentioned findings, the blue + red light combination emerged as a promising light combination for nitrate removal. Hence, our study suggests the importance of the blue + red light combination together with high light intensity, as the optimal light condition for nitrate removal from synthetic wastewater in comparison to other monochromatic lights with high light intensity.     

Rapid Detection of Wheat Blast Pathogen Magnaporthe oryzae Triticum Pathotype Using Genome-Specific Primers and Cas12a-mediated Technology

Wheat blast, caused by the fungus Magnaporthe oryzae Triticum (MoT) pathotype, is a devastating disease persistent in South America and Bangladesh. Since MoT generally fails to cause visual symptoms in wheat until the heading stage when the infection would have advanced, disease control by fungicide application solely based on the detection of visual symptoms is ineffective. To develop an accurate and sensitive method to detect MoT at the seedling and vegetative stages for disease control, we sequenced the genomes of two MoT isolates from Brazil and identified two DNA fragments, MoT-6098 and MoT-6099, that are present in the MoT genome but not in the genome of the rice-infecting Magnaporthe oryzae Oryzae (MoO) pathotype. Using polymerase chain reaction (PCR), we confirmed the specificity of the two markers in 53 MoT and MoO isolates from South America and Bangladesh. To test the efficiency of the two markers, we first established a loop-mediated isothermal amplification (LAMP) method to detect MoT at isothermal conditions, without the use of a PCR machine. Following this, we used the Cas12a protein and guide RNAs (gRNAs) to target the MoT-6098 and MoT-6099 sequences. The activated Cas12a showed indiscriminate single-stranded deoxyribonuclease (ssDNase) activity. We then combined target-dependent Cas12a ssDNase activation with recombinase polymerase amplification (RPA) and nucleic acid lateral flow immunoassay (NALFIA) to develop a method that accurately, sensitively, and cost-effectively detects MoT-specific DNA sequences in infected wheat plants. This novel technique can be easily adapted for the rapid detection of wheat blast and other important plant diseases in the field.     

Densities and excess molar volumes of mixtures containing diesel,biodiesel and alkanols at temperatures from 288.15 to 313.15 K

The present work is focusing on the synthesization and physico-chemical properties of Jatropha curcas biodiesel with diesel and alcohols.The densities of binary diesel (2)+1-alkanols (C_3 or C_4)(3) and ternary Jatropha curcas biodiesel (1)+diesel (2)+1-alkanols (C_3or C_4)(3) blends have been reported over full range of composition at temperatures within range 288.15 to 313.15 K.Also densities of Jatropha curcas biodiesel (1)+diesel or 1-alkanols (C_3 or C_4)(2) blends have been measured at 313.15 K.Excess molar volumes,V~E,V~E_(123)of binary and ternary blends were calculated from the measured data and the derived properties were correlated to composition using Redlich–Kister equation.A reasonable agreement was found between the measured and estimated values.Further,densities and excess molar volumes data were reasoned to discuss molecular interactions taking into consideration effect of composition and temperature.     

Implementing two methods in GIS software for indoor routing: an empirical study

Multimedia Tools and Applications - With increasing demands for indoor GIS, indoor routing and analysis attracts attention from both GIS and architecture worlds. This paper aimes to provide...     

DFuzzy: a deep learning-based fuzzy clustering model for large graphs

Graph clustering is successfully applied in various applications for finding similar patterns. Recently, deep learning- based autoencoder has been used efficiently for detecting disjoint clusters. However, in real-world graphs, vertices may belong to multiple clusters. Thus, it is obligatory to analyze the membership of vertices toward clusters. Furthermore, existing approaches are centralized and are inefficient in handling large graphs. In this paper, a deep learning-based model ‘DFuzzy’ is proposed for finding fuzzy clusters from large graphs in distributed environment. It performs clustering in three phases. In first phase, pre-training is performed by initializing the candidate cluster centers. Then, fine tuning is performed to learn the latent representations by mining the local information and capturing the structure using PageRank. Further, modularity is used to redefine clusters. In last phase, reconstruction error is minimized and final cluster centers are updated. Experiments are performed over real-life graph data, and the performance of DFuzzy is compared with four state-of-the-art clustering algorithms. Results show that DFuzzy scales up linearly to handle large graphs and produces better quality of clusters when compared to state-of-the-art clustering algorithms. It is also observed that deep structures can help in getting better graph representations and provide improved clustering performance.     

Flat Absorber Phosphorous Black Nickel Coatings for Space Applications

A new process of flat absorber black nickel alloy coating was developed on stainless steel by electrodeposition from a bath containing nickel,zinc and ammonium sulphates;thiocyanate and sodium hypophosphite for space applications.Coating process was optimized by investigating the effects of plating parameters,viz concentration of bath constituents,current density,temperature,pH and plating time on the optical properties of the black deposits.Energy dispersive X-ray spectroscopy showed the inclusion of about 6% phosphorous in the coating.The scanning electron microscopy studies revealed the amorphous nature of the coating.The corrosion resistance of the coatings was evaluated by the electrochemical impedance spectroscopy (EIS) and linear polarization (LP) techniques.The results revealed that,phosphorous addition confers better corrosion resistance in comparison to conventional black nickel coatings.The black nickel coating obtained from hypophosphite bath provides high solar absorptance (α s) and infrared emittance (ε IR) of the order of 0.93.Environmental stability to space applications was established by the humidity and thermal cycling tests.     

Optimization of the Security-Performance Tradeoff in RC4 Encryption Algorithm

Wireless Personal Communications - In this paper, we have investigated different vulnerabilities in RC4 and its enhanced variants to overcome the security attacks. It is established that in spite...     

In vitro ageing and wear behaviour of ceria stabilized zirconia toughened alumina (CSZ-TA) bio-ceramic

15–25 wt% zirconia (stabilized with 14 mol% ceria) toughened alumina was synthesized by co-precipitation technique. The synthesized powders were calcined at different temperatures, compacted and conventionally sintered following two steps sintering process. Uniformly distributed submicron sized grains with Vickers' hardness value up to 1730±6HV20 were achieved after conventional sintering. In order to assess the ageing behaviour, samples were hydrothermally treated (in vitro) at 134 °C under 0.2 MPa in presence of simulated body fluid. Rietveld refinement of the X-ray diffraction patterns was carried out to estimate the phase content after calcination, sintering and after different stages of hydrothermal treatment. No significant phase change (only ∼3%) was observed even after 100 h of hydrothermal treatment. Very few bulged grains (resulted from the tetragonal to monoclinic phase transformation) on the surface and slight decrease in hardness value were observed after hydrothermal treatment. Fretting wear in dry condition was carried out taking ball on flat geometry for 10⁵ cycles at different loads before and after hydrothermal treatment. Wear volumes were directly estimated from the surface scanning of the wear scar using profilometer. Transition of wear and its related mechanisms at different loads along with the effect of ageing on wear were discussed.     

Epoxidized linolenic acid salts as multifunctional additives for the thermal stability of plasticized PVC

Calcium and zinc salts of epoxidized linolenic acid were synthesized and used as multifunctional additives, to minimize or prevent the reaction of epoxidized soybean oil (ESO) with liberated hydrochloric acid (HCl) during the thermal degradation of poly(vinyl chloride) (PVC) in particular. These metal epoxy salts were incorporated as thermal stabilizers for both diisodecyl phthalate and ESO–plasticized PVC blends that underwent thermal degradation studies at 170°C. The overall performance of these metal epoxy salts was examined by thermal gravimetric analysis and visual color retention of the PVC blends. The weight loss profiles of the metal salt stabilized PVC were comparable to those of blends containing metal stearates. There were, however, vast improvements in color retention of the plasticized PVC using these novel additives. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41736.