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Introduction Plastic deformation of steel causes crystalline imperfections such as increased dislocation density, vacancies, cracks and microvoids which, in turn, influence dissolution and transport of hydrogen in traps. The increased dislocation density and dislocation pile‐ups against cementile lamella or non‐metallic inclusions lead to microcrack formation. The dislocation pile‐ups are mobile under stress. Transport of hydrogen by dislocation under stress can be expected but the temperature should be neither so high as to force the hydrogen to leave the dislocation sites nor so low that the hydrogen cannot diffuse into the dislocation sites.

This study examines a link between firms' product market power, industry concentration, the degree of earnings management and the role of governance in curbing earnings management.

The author uses different panel techniques of feasible generalized least squares (FGLS) and system generalized method of moments (GMM) to show robust study findings.

The study results reveal that firms lacking product market pricing power engage in earnings management, adding a new dimension to the existing literature. These findings mirror even at the industry level, where the authors document immense competitiveness led to earnings manipulation and stringent corporate governance mechanism has the potency to curb earnings management.

The paper has valuable insights and practical implications for policymakers and market participants. The results indicate robust institutional oversight mechanisms can deter earnings management in a concentrated market.

To the best of the authors’ knowledge, this is among the first paper from India, a growing emerging economy, to look at the various aspects of market characteristics, earnings management and the role of corporate governance.

The development of high‐temperature, oxidation‐resistant coatings needs to be thoroughly studied owing to the metal loss incurred from short‐ or long‐term exposure to high temperatures before final processing. Particularly, short‐term exposure (intermittent heating or soaking or other heat treatment schedules) always produces often unwanted scales, which cause problems in subsequent metal working, loss of metal or further necessary pickling, etc. Studies the performance of some slurry‐based coatings with regard to the protection of metals during short‐term exposure to high temperatures.

Like aqueous corrosion of metals, atmospheric corrosion of metallic articles has also been a matter of great anxiety due to the individual and joint action of oxygen, humidity and various types of pollution gases and ions in the atmospheres. As there is no limit of oxygen availability in the open atmosphere, this type of corrosion of metals is mainly controlled by humidity. In industrial mines and marine environments, however, metal attack is controlled by aggressive gases, ions and chloride ions respectively.

The purpose of this paper is to design and develop precipitation hardened Al-Mg alloy imparting enhanced strength with acceptable ductility through minor addition of Sc and Cr by using multi-objective genetic algorithm-based searching. In earlier attempts of strengthening aluminum alloys, owing to the formation of Al₃Sc and Al₇Cr phase, addition of Sc and Cr have yielded attractive precipitation hardening, respectively. Both the Al-Sc and Al-Cr system are quench sensitive due to presence of a sloping solvus in their phase diagrams. It is also known that both the Al₃Sc and Al₇Cr phases nucleate directly from the supersaturated solid solution without formation of GP-zones or transient phases prior to the formation of the Al₃Sc and Al₇Cr. Sc also found to have beneficial effect on the corrosion property of such alloys. In view of the above, it is of interest to explore the possibility of enhancing the age hardening effect in Al-Mg alloy by addition of Sc and Cr.

The paper uses an approach where experimental information of two different alloy systems (namely, Al-Mg-Sc and Al-Cr) has been combined to generate a single database involving the potential features of both the systems with the aim to formulate the suitable artificial neural network (ANN) models for strength and ductility. The models are used as the objective functions for the optimization process. The patterns of the optimized Pareto front are analyzed to recognize the optimal property of the alloy system. The hitherto unexplored Al-Mg-Sc-Cr alloy, designed from the Pareto solutions and suitably modified on the basis of prior knowledge of the system, is then synthesized and characterized.

The paper has demonstrated the ANN- and genetic algorithm (GA)-based design of a hitherto unexplored alloy by utilizing the existing information concerning the component alloy systems. The paper also established that analyses of the Pareto solutions generated through multi-objective optimization using GA provide an insight of the variation of the parameters at different combination of strength and ductility. It also revealed that the Al-Mg-Sc-Cr alloy has exhibited a two-stage age hardening effect. The first and second stages are due to the precipitation of Al₃Sc and Al₇Cr phases, respectively.

In the present study the two alloy systems are used in tandem to develop models to describe the properties involving the distinct mechanistic features of phase evolution inherent in both the systems. Though the ANN models having the capability to capture huge non-linearity of a system have been employed to predict the convoluted effects of those characteristics when an alloy containing Mg, Sc and Cr are added simultaneously, but the ANN models predictions can be checked experimentally by the future researchers.

The paper demonstrates the role of scandium and chromium addition on the ageing characteristics of the alloy by analyzing the age hardening behavior of the designed alloy in cast and cold rolled condition clearly.

The approach stated in this paper is a novel one, in the sense that experimental data of two different alloy systems have been clubbed to generate a single database with the aim to formulate the suitable ANN models for strength and ductility.

Iron and silicon are the two inherent impurities present in commercial aluminium which impair its corrosion resistance. Influence of silicon/iron ratio present in aluminium alloys containing different amounts of silicon has been studied through electrochemical polarization in some inorganic and organic acids (0.1 N). It has been observed that Si/Fe ratio has potential role on corrosion rates in different acids studied.

This paper aims to obtain the optimal wire sizing of buffered global interconnects and to investigate the impact of weight factor on the optimized system performance for various technology nodes.

The width and spacing of interconnects are optimized under two scenarios, and corresponding optimum line width is determined by minimizing the value of power‐delay product which is defined as a figure of merit (FOM). Based on the results, the impact of weight factor on the optimized system performance, such as delay and power dissipation per unit length, is analyzed for various technology nodes.

The analytical expressions of the optimum width are derived under two scenarios. Better FOMs can be achieved for the S=W scenario, but the wireability of the chip degrades considerably. The optimized delay increases with the increasing of weight factor, while the optimized power dissipation decreases with it. For a given weight factor, smaller latency and less power dissipation can be achieved for the S=W case.

The analytical expressions of the optimum width of interconnects are given, and a comprehensive study of the impact of weight factor on the optimized results under two scenarios is presented.

The purpose of the paper is to model the relationship between the yield strength of austenitic stainless steel and its chemical composition through the employment of artificial neural network (ANN). The effect of annealing temperature is also taken into consideration.

The influence of network parameters, total number of neurons, number of neurons in a hidden layer, number of hidden layers and the interlayer distribution of neurons with a constant total neuron number, on the achievable training error is studied. Different learning rules available in MATLAB are used to assess the learning efficiencies of various networks.

It is found that increasing neuron number leads to a lowering of achievable training error up to a certain value beyond which training error remains constant. Increasing number of layers at constant total number of neurons causes a rise in the achievable training error. It is noted that if there is a sudden restriction of data flow in an ANN architecture, the achievable training error becomes higher. Interlayer distribution of neurons in ANNs used with different algorithms is found to have significant influence on the predictive performance of the networks.

From the study on metallurgical validation of the output of various ANNs, it appears that mere attainment of a lower training error is not sufficient to achieve better generalization. A convergent network topology is found to be better than a divergent one in respect of effectively describing the input‐output relationship in austenitic stainless steel.

The purpose of this paper is to design an out-of-plane micro electro-thermal-compliant actuator based logic gates which work analogously to complementary metal oxide semiconductor (CMOS) based logic gates. The proposed logic gates used a single-bit mechanical micro ETC actuator per logic instead of using 6-14 individual transistors as in CMOS.

A complete analytical modelling is performed on a single ETC vertical actuator, and a relation between the applied voltage and the out-of-plane deflection is derived. Its coupled electro-thermo-mechanical analysis is carried out using micro electro mechanical system (MEMS) CAD tool CoventorWare to illustrate its performance.

This paper reports analytical and numerical simulation of basic MEMS ETC actuator-based logic gates. The proposed logic gate operates on 5 V, which suits well with conventional CMOS logic, which in turn reduces the power consumption of the device.

The proposed logic gates uses a single-bit MEMS ETC actuator per logic instead of using more transistors as in CMOS. The unique feature of this proposed logic gates is that the basic mechanical ETC actuator is customized in its structure to function as specific logic gates depending upon the given inputs.

Delay and power dissipation are the two major design constraints in very large scale integration (VLSI) circuits. These arise due to millions of active devices and interconnections connecting this gigantic number of devices on the chip. Important technique of repeater insertion in long interconnections to reduce delay in VLSI circuits has been reported during the last two decades. This paper deals with delay, power dissipation and the role of voltage‐scaling in repeaters loaded long interconnects in VLSI circuits for low power environment.

Trade off between delay and power dissipation in repeaters inserted long interconnects has been reviewed here with a bibliographic survey. SPICE simulations have been used to validate the findings.

Optimum number of uniform sized CMOS repeaters inserted in long interconnects, lead to delay minimization. Voltage‐scaling is highly effective in reduction of power dissipation in repeaters loaded long interconnects. The new finding given here is that optimum number of repeaters required for delay minimization decreases with voltage‐scaling. This leads to area and further power saving.

The bibliographic survey needs to be revised in future, taking the various other aspects of VLSI interconnects viz. noise, cross talk extra into account.

The paper is of high significance in VLSI design and low‐power high‐speed applications. It is also valuable for new researchers in this emerging field.