First-principles study of static nanoscale friction between MoO3 and MoS2

The motion of a nanoscale MoO3 crystal on an MoS2 substrate is an ideal case for the study of the effects of microstructure on macroscopic phenomena like friction, because both components of this system can be prepared with atomically flat surfaces. We apply a recently developed real-space density functional theory method to investigate the energetics of sliding an MoO3 crystal on an MoS2 substrate. We then link the results to simple models based on continuum elastic theory, in order to study the mechanical behavior of the oxide crystals under loads that correspond to realistic situations. Based on these results, we extract estimates of the force which must be applied with an atomic force microscope in order to move the oxide crystal on the substrate, for different orientations of the two components.     

Machining parameters optimization for satisfying the multiple objectives in machining of MMCs

The metal matrix composites (MMCs) have gained acceptance in an extensive range of applications owing to their high strength to mass ratio. Machining of such complex MMCs is often challenging. It is essential to optimize the controllable machining parameters to simultaneously attain manifold objectives. In the current work, response surface design is created for experiments, and Genetic algorithm (GA) combined with Principal Components Analysis (PCA) coupled Grey Relational Analysis (GRA) is employed to improve the straight turning process of MMCs. The procedure is demonstrated by machining aluminum-based MMC with 25% SiC particulates. The procedure aims at identifying optimal combination of machining parameters to obtain high surface quality at lower cutting force without increasing the specific power consumption. PCA is helpful in providing the individual uncorrelated quality characteristics called as quality indices that do not have any influence on other responses. Individual quality indices have been utilized to obtain the grey relational grade through GRA. GRA has been used to alter manifold quality indices into singular column of grey relational grade as a means to change the manifold objective problem into a sole objective problem. Then, GA has been used to get the optimal parameters combination. The novelty present in this work is the avoidance of correlation existing among the quality characteristics and combining of the GRA and GA. This is an endeavor to augment the performance and accuracy of GA to solve the optimization problem associated with the turning operation.     

$$C^3$$-index: a PageRank based multi-faceted metric for authors’ performance measurement

Ranking scientific authors is an important but challenging task, mostly due to the dynamic nature of the evolving scientific publications. The basic indicators of an author’s productivity and impact are still the number of publications and the citation count (leading to the popular metrics such as h-index, g-index etc.). H-index and its popular variants are mostly effective in ranking highly-cited authors, thus fail to resolve ties while ranking medium-cited and low-cited authors who are majority in number. Therefore, these metrics are inefficient to predict the ability of promising young researchers at the beginning of their career. In this paper, we propose \(C^3\)-index that combines the effect of citations and collaborations of an author in a systematic way using a weighted multi-layered network to rank authors. We conduct our experiments on a massive publication dataset of Computer Science and show that—(1) \(C^3\)-index is consistent over time, which is one of the fundamental characteristics of a ranking metric, (2) \(C^3\)-index is as efficient as h-index and its variants to rank highly-cited authors, (3) \(C^3\)-index can act as a conflict resolution metric to break ties in the ranking of medium-cited and low-cited authors, (4) \(C^3\)-index can also be used to predict future achievers at the early stage of their career.     

Optimizing MapReduce for energy efficiency

The efficient use of energy is essential to address concerns of cost and sustainability. Many data centers contain MapReduce clusters to process Big Data applications. A large number of machines and fault tolerance capabilities make MapReduce clusters energy inefficient. In this paper, we present a Configurator based on performance and energy models to improve the energy efficiency of MapReduce systems. Our solution is novel as it takes into account the dependence of the performance and energy consumption of a cluster on MapReduce parameters. While this dependence is known, we are the first to model it and design a Configurator to optimize these parameter settings for maximizing the energy efficiency of MapReduce systems. Our empirical evaluations show that the Configurator can result in up to 50% improvement in the energy efficiency of typical MapReduce applications in two architecturally different clusters.     

Pyroelectric and Electrostrictive Properties of (1 –x–y) PZN ·xBT ·yPT Ceramic Solid Solutions

The pyroelectric and electrostrictive properties of lead zinc niobate–lead titanate–barium titanate (PZN–BT–PT) ceramic solid solution were investigated. These properties of the (1 – x )PZN · x BT series were qualitatively explained with a composition fluctuation model. The pyroelectric depolarization temperatures of (1 – x – y )PZN · x BT · y PT ceramics were utilized to select compositions for room-temperature electrostrictive applications. Among them, 0.85PZN · 0.10BT · 0.05PT ceramic with Q ₁₁= 0.018 m⁴/ C², Q ₁₂=−0.0085 m⁴/C², s ₂ at 25 kV/cm =−6.1 × 10⁻⁴, T _max= 75°C at 1kHz, and T _t= 27°C shows optimum properties for micropositioner applications.     

Efficacy of bioactive compounds isolated from Albizia amara and Albizia saman as source of antifungal and antiaflatoxigenic agents

The antifungal and antiaflatoxigenic activities of budmunchiamine A (BUA) isolated from Albizia amara and pithecolobine (PI) isolated from Albizia saman were assessed. The present study reports the broad-spectrum and concentration-dependent antifungal activities of BUA and PI with zone of inhibitions and minimum inhibitory concentrations ranging from 6.8 to 19.6 mm and 0.015–0.5 mg/mL, respectively. Aspergillus flavus growth and its aflatoxin B₁ production were completely inhibited in vitro by BUA and PI at concentration of 1 mg/mL. BUA severely inhibited the growth of wide range of seed-borne fungi of maize including aflatoxigenic A. flavus with an increased seedling vigour index in vivo at a lower concentration (1.0 g/kg) than PI (2.0 g/kg). Enhanced seedling vigour was observed in BUA and PI treatments with no adverse effect on seed germination. The present findings indicate the possible use of BUA and PI as antifungal agents against post harvest fungal infestation of food commodities and mycotoxin contamination.     

Ionic-liquid-assisted mixed alkali system for reactive dye fixation in a batch process – optimisation through response surface methodology

An ionic liquid, choline hydroxide, was synthesised and used in a mixed alkali system for fixation of homobifunctional reactive dyes. Its molecular structure was confirmed using FTIR, ¹H NMR, and ¹³C NMR spectroscopy. Response surface methodology was employed to optimise the dyeing conditions for reactive dyes using a sodium carbonate–choline hydroxide mixed alkali system. A Box–Behnken design with three variables, namely sodium carbonate concentration, choline hydroxide concentration, and fixation time, was used to design the experimental runs. Analysis of variance was used to estimate the statistical parameters and to evaluate the quality of the statistical model fit. The quality and model terms were evaluated using Fisher's F-test, the coefficient of determination, and probability values. The interactive effect of operating variables on the response (K/S) was studied using three-dimensional response surface plots. The results obtained from the solutions of highest desirability were found to be comparable with conventionally used alkali systems, namely sodium carbonate alone and sodium carbonate–sodium hydroxide mixed alkali. The ionic liquid choline hydroxide could be effectively used along with sodium carbonate for fixation of reactive dyes, with the advantage of reductions in pollution load, total dissolved solids, and chemical oxygen demand.     

Evaluation of Dynamic Channel and Power Assignment for Cognitive Networks

In this paper, we develop a unifying optimization formulation to describe the Dynamic Channel and Power Assignment (DCPA) problem and an evaluation method for comparing DCPA algorithms. DCPA refers to the allocation of transmit power and frequency channels to links in a cognitive network so as to maximize the total number of feasible links while minimizing the aggregate transmit power. We apply our evaluation method to five representative DPCA algorithms proposed in the literature. This comparison illustrates the tradeoffs between control modes (centralized versus distributed) and channel/power assignment techniques. We estimate the complexity of each algorithm. Through simulations, we evaluate the effectiveness of the algorithms in achieving feasible link allocations in the network, and their power efficiency. Our results indicate that, when few channels are available, the effectiveness of all algorithms is comparable and thus the one with smallest complexity should be selected. The Least Interfering Channel and Iterative Power Assignment algorithm does not require cross-link gain information, has the overall lowest run time, and achieves the highest feasibility ratio of all the distributed algorithms; however, this comes at a cost of higher average power per link.