Microstructure,wear and corrosion characteristics of multiple-reinforced (SiC–B4C–Al2O3) Al matrix composites produced by liquid metal infiltration

In this study, AA7075 aluminum matrix composites reinforced with the combination of SiC, Al₂O₃, and B₄C particles were fabricated by the liquid metal infiltration method. The effects of the relative ratio of B₄C and Al₂O₃ particles on the microstructural, wear, and corrosion features of the composite samples were analyzed using XRD, light metal microscopy, SEM, EDS, Brinell hardness, ball-on-disc type tribometer, and potentiodynamic polarization devices. It was determined that infiltration occurred more successfully, and homogenously distributed particles with reduced porosity were obtained as the amount of Al₂O₃ increased. Worn surface studies revealed that the specimens were predominantly worn by abrasion and adhesion. The increase in B₄C/Al₂O₃ ratio caused a decrease in the hardness and wear strength, whereas it increased the corrosion resistance.     

Masking the Peroxidase-Like Activity of the Molybdenum Disulfide Nanozyme Enables Label-Free Lipase Detection

Two-dimensional MoS₂ nanoparticles (2D-nps) exhibit artificial enzyme properties that can be regulated at bio-nanointerfaces. We discovered that protein lipase is able to tune the peroxidase-like activity of MoS₂ 2D-nps, offering low-nanomolar, label-free detection and identification in samples with unknown identity. The inhibition of the peroxidase-like activity of the MoS₂ 2D-nps was demonstrated to be concentration dependent, and as low as 5 nm lipase was detected with this approach. The results were compared with those obtained with several other proteins that did not display any significant interference with the nanozyme behavior of the MoS₂ 2D-nps. This unique response of lipase was characterized and exploited for the successful identification of lipase in six unknown samples by using qualitative visual inspection and a quantitative statistical analysis method. The developed methodology in this approach is noteworthy for many aspects; MoS₂ 2D-nps are neither labeled with a signaling moiety nor modified with any ligands for signal readout. Only the intrinsic nanozyme activity of the MoS₂ 2D-nps is exploited for this detection approach. No analytical equipment is necessary for the visual detection of lipase. The synthesis of the water-soluble MoS₂ 2D-nps is low costing and can be performed in bulk scale. Exploring the properties of 2D-nps and their interactions with biological materials reveals highly interesting yet instrumental features that offer the development of novel bioanalytical approaches.     

Novel T-rail electrodes for substrate removed low-voltage high-speed GaAs/AlGaAs electrooptic modulators

A novel traveling-wave electrode utilizing capacitively loaded T-rail elements was developed for low-voltage high-speed substrate-removed GaAs/AlGaAs electrooptic modulators. Electrodes with varying dimensions were fabricated and characterized. Electrode phase velocity, characteristic impedance, loss coefficient, and capacitive loading were extracted from the measured s-parameters up to 40 GHz. Electrode was also simulated using a finite-element solver. The measured and calculated electrode capacitance values were found to be in excellent agreement, showing that the electrode can be precisely designed. Approaches were outlined to provide a group velocity-matched very high-speed modulator electrode suitable for a low drive-voltage substrate-removed GaAs/AlGaAs electro-optic modulator     

Viscoelastic State for the Solutions of Spherically Symmetric Viscoelasticity Problems

The solutions of the spherically symmetric, linear, isothermal, and transient viscoelasticity problems via reciprocity theorem have been investigated for a specific material. The integral form of stress–strain relations has been used. The Laplace transform of a viscoelastic state, which is necessary for the integral equation arising as a result of reciprocity theorem, has been derived. This integral equation has been solved by Laplace transform. A sample problem has been solved to test the presented formulation. A numerical application of the analytic solution of this problem has been given.     

Plastic Limit, Liquid Limit and Undrained Shear Strength of Soil—Reappraisal

The concept that plasticity index of soils can be defined as a range of water contents producing a 100-fold variation in undrained shear strength has been experimentally verified with the help of a large number of tests on soils of diverse nature. This has led to the redefinition of the plastic limit as the water content at which undrained shear strength is around 170 kN/m2. Undrained shear strength of a soil at the liquid limit can be considered to be around 1.7 kN/m2. Accordingly, both the liquid limit and the plastic limit have been determined in the present work by a single consistent method, i.e., the Swedish fall cone method. The undrained shear strength-water content relationship has been found to be log-linear for a wide range of water contents beginning from lower than the plastic limit to higher than the liquid limit. This resulted in the formulation of an expression for predicting undrained shear strength of a remolded soil at any water content based solely on its liquid limit and plastic limit.     

A comprehensive survey: artificial bee colony (ABC) algorithm and applications

Swarm intelligence (SI) is briefly defined as the collective behaviour of decentralized and self-organized swarms. The well known examples for these swarms are bird flocks, fish schools and the colony of social insects such as termites, ants and bees. In 1990s, especially two approaches based on ant colony and on fish schooling/bird flocking introduced have highly attracted the interest of researchers. Although the self-organization features are required by SI are strongly and clearly seen in honey bee colonies, unfortunately the researchers have recently started to be interested in the behaviour of these swarm systems to describe new intelligent approaches, especially from the beginning of 2000s. During a decade, several algorithms have been developed depending on different intelligent behaviours of honey bee swarms. Among those, artificial bee colony (ABC) is the one which has been most widely studied on and applied to solve the real world problems, so far. Day by day the number of researchers being interested in ABC algorithm increases rapidly. This work presents a comprehensive survey of the advances with ABC and its applications. It is hoped that this survey would be very beneficial for the researchers studying on SI, particularly ABC algorithm.     

Approximate variational inference based on a finite sample of Gaussian latent variables

Variational methods are employed in situations where exact Bayesian inference becomes intractable due to the difficulty in performing certain integrals. Typically, variational methods postulate a tractable posterior and formulate a lower bound on the desired integral to be approximated, e.g. marginal likelihood. The lower bound is then optimised with respect to its free parameters, the so-called variational parameters. However, this is not always possible as for certain integrals it is very challenging (or tedious) to come up with a suitable lower bound. Here, we propose a simple scheme that overcomes some of the awkward cases where the usual variational treatment becomes difficult. The scheme relies on a rewriting of the lower bound on the model log-likelihood. We demonstrate the proposed scheme on a number of synthetic and real examples, as well as on a real geophysical model for which the standard variational approaches are inapplicable.