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This paper aims to highlight the very recent cases of internet shutdown during the creation of Union territory of Jammu and Kashmir and enactment of Citizenship Amendment Act and the detention under Section 66 (A) of Information Technology Act 2000.

This study takes up a broad explorative discussion of the challenges posed to the consolidation of democracy in India due to frequent internet shutdowns for online communication and social media usages.

As findings, it is narrated that due to politically motivated reasons, India compromises its commitment to the pluralism and diversity in views, in particular, individual rights to freedom of expression and opinion, enshrined in the constitution.

Right to freedom of speech and expression has now taken a new shape due to the emergence and availability of the internet that enriches the quality of democracy.

The purpose of this paper is to explore the use of chiral single‐walled carbon nanotubes (SWCNTs) as mass sensors. Analysis of SWCNT with chiralities is performed using an atomistic finite element model based on a molecular structural mechanics approach.

The cantilever carbon nanotube (CNT) is modeled by considering it as a space frame structure similar to three‐dimensional beams and point masses. The elastic properties of the beam element are calculated by considering mechanical characteristics of covalent bonds between the carbon atoms in the hexagonal lattice. The mass of each beam element is assumed as point mass at nodes coinciding with carbon atoms. An atomistic simulation approach is used to find the natural frequencies and to study the effects of defect like atomic vacancies in CNTs on the resonant frequency. The migration of the atomic vacancies along the length is observed for different chiralities.

A reduction in the simulated natural frequency is observed with the maximum value occurring, when the vacancy is found nearer to the fixed end. It is quite evident from the simulation results that the effect of vacancies is significant, and the effect diminishes at 10⁻² femtograms mass. Using the higher modes of vibration of SWCNT‐based mass sensors, the amount and the position of the mass on the nanotube can be identified.

CNT have been used as mass sensors extensively. The present approach is focused to explore the use of chiral SWCNT as sensing device with vacancy defect in it. The variation of the atomic vacancies in CNT along the length has been taken and is analyzed for different chiralities. The effects of defect like atomic vacancies in CNTs on the resonant frequency have been analyzed and observed that the maximum reduction in natural frequency occurs when the vacancy is found nearer to the fixed end due to large stiffness variation.

The advancement in modern manufacturing technology generated the need to develop new materials for better wear resistance. The purpose of this paper is to use the Taguchi optimization approach to examine which wear parameter significantly affects weight loss and coefficient of friction for RZ5-TiC composite. It is a simple and efficient method to find performance of wear parameter using minimum experimental runs.

RZ5-TiC composites were prepared using RZ5 as matrix, reinforced with TiC through self-propagating high-temperature synthesis technique. In the present work, an attempt has been made to study the influence of wear parameters like applied load (AL), sliding distance (SD) and Wt.% of TiC (WTC) on responses like weight loss and coefficient of friction of RZ5/TiCp composites. The pin-on-disc apparatus used to conduct abrasive wear test. The wear process parameters are optimized for minimum wear based on L27 Taguchi orthogonal design. The Taguchi technique using design of experiments (DOE) is used to obtain the data. The ANOVA and an orthogonal array are used to examine the influence of wear parameters on responses. The purpose is to examine parametric significances which affect responses.

It observed that wear parameters have the significant influence on responses of RZ5/TiCp composites. The interaction of sliding distance/Wt.% of TiC is observed and found significant influence on both responses. The optimum level of the significant wear parameters is achieved based on the maximum S/N ratio for RZ5/TiCp composites. The optimal interaction for weight loss and coefficient of friction is AL1-SD1-WTC3 and AL3-SD1-WTC3, respectively. Finally, the confirmation test is conducted and the results are obtained within the confidence interval.

The current manuscript provides an optimization of wear parameters using Taguchi approach. The extensive experimental data are used for this purpose and effects of wear parameters on responses are analyzed from the presented results. The results obtained are useful in improving the wear resistance of the RZ5-TiC composite.

In rotary machines, the bearing failure is one of the major causes of the breakdown of machinery. The bearing degradation monitoring is a great anxiety for the prevention of bearing failures. This paper aims to present a combination of the stationary wavelet decomposition and extra-trees regression (ETR) for the evaluation of bearing degradation.

The higher order cumulants features are extracted from the bearing vibration signals by using the stationary wavelet decomposition (stationary wavelet transform [SWT]). The extracted features are then subjected to the ETR for obtaining normal and failure state. A dominance level curve build using the dissimilarity data of test object and retained as health degradation indicator for the evaluation of bearing health.

Experiment conducts to verify and assess the effectiveness of ETR for the evaluation of performance of bearing degradation. To justify the preeminence of recommended approach, it is compared with the performance of random forest regression and multi-layer perceptron regression.

The experimental results indicated that the presently adopted method shows better performance for detecting the degradation more accurately at early stage. Furthermore, the diagnostics and prognostics have been getting much attention in the field of vibration, and it plays a significant role to avoid accidents.

The aim of this paper is to study the effect of deterministic roughness and small elastic deformation of surface on flow rates, load capacity and coefficient of friction in Rayleigh step bearing under thin film lubrication.

Reynolds equation, pressure-density relationship, pressure-viscosity relationship and film thickness equation are discretized using finite difference method. Progressive mesh densification (PMD) method is applied to solve the related equations iteratively.

The nature and shape of roughness play a significant role in pressure generation. It has been observed that square roughness dominates the pressure generation for all values of minimum film thickness. Deformation more than 100 nm in bounding surfaces influences the film formation and pressure distribution greatly. Divergent shapes of film thickness in step zone causes a delay of pressure growth and reduces the load capacity with decreasing film thickness. The optimum value of film thickness ratio and step ratios have been found out for the maximum load capacity and minimum coefficient of friction, which are notably influenced by elastic deformation of the surface.

It is expected that these findings will help in analysing the performance parameters of a Rayleigh step bearing under thin film lubrication more accurately. It will also help the designers, researchers and manufacturers of bearings.

Most of the previous studies have been limited to sinusoidal roughness and thick film lubrication in Rayleigh step bearing. Effect of small surface deformation due to generated pressure in thin film lubrication is significant, as it influences the performance parameters of the bearing. Different wave forms such as triangular, sawtooth, sinusoidal and square formed during finishing operations behaves differently in pressure generation. The analysis of combined effect of roughness and small surface deformation has been performed under thin film lubrication for Rayleigh step bearing using PMD as improved methods for direct iterative approach.

The aim of this paper is to study the dynamic vibrations of embedded double‐walled carbon nanotubes (DWCNTs) subjected to a moving harmonic load with simply supported boundary conditions.

The model of DWCNTs is considered as an Euler‐Bernoulli beam with waviness along the length, which is more accurate than the straight beam in previous works. Based on the nonlocal beam theory, the governing equations of motion are derived by using the Hamilton's principle, and then the separation of variables is carried out by the Galerkin approach, leading to two second‐order ordinary differential equations (ODEs).

The influences of the nonlocal parameter, the amplitude of the waviness, the surrounding elastic medium, the material length scale, load velocity and van der Waals force on the nonlinear vibration of DWCNTs are important.

The dynamic responses of DWCNTs are obtained by using the precise integrator method to ordinary differential equations.

The purpose of this paper is to examine the potential of single-walled carbon nanotubes as mass sensors by developing analytical expressions and then comparing the outcome with structural mechanics corresponding predictions.

The carbon nanotube (CNT) resonators are assumed to be either single or double clamped. Analytical formulas capable of describing the vibrational behavior of such CNT-based nanoresonators with an attached mass at nanotube tip or various intermediate positions are developed by combining the Euler–Bernoulli theory and Krylov–Duncan functions.

The validity and the accuracy of these formulas are examined for a wide range of cases via comparisons with corresponding results arisen by spring- or beam-based structural mechanics predictions. Both structural mechanics approaches utilize three-dimensional nanoscale elements formulated according to the molecular theory. The results indicate that the new sensor equations may be utilized for the estimation of vibration response of CNT-based mass sensors with reasonable accuracy.

Simple analytical formulas are proved to approximate the mass sensing ability of CNTs adequately, the fact that may significantly contribute in the effort of developing new sensor devices.

This paper aims to explore how the context in a dynamically developing country affects employee silence in India.

Qualitative design involving semi-structured interviews with employees and managers from different sectors in the Mumbai and Delhi areas. An abductive approach was used to analyze the data.

Two types of social mobility concerns – advancement aspiration and fear of social decline – emerged as salient drivers of silence and can be attributed to a volatile job market, social status markers, transferability of qualification, someone’s socio-economic situation and the overall economic situation. Pathways were specified from social mobility concerns to silence tendencies that are motivated by both low approach and high avoidance.

Social mobility as a specific factor in the Indian distal context and as a characteristic of emerging markets can motivate silence while organization-related concepts like job satisfaction or commitment may have less predictive value. Propositions that were derived from the interview study need to be validated by deductive research. Generalizability of Indian findings across other emergent markets needs to be shown.

To the organizational behavior (OB) scholarship on silence, this research contributes by identifying antecedents of silence that are situated beyond the organizational boundaries challenging the dominant role of established factors at the team- and organizational level. To the human resource management/employment relations (HRM/ER) scholarship, this research contributes by theorizing psychological processes that link environmental factors to silence behaviors.

The RZ5 mg alloy is used in automotive and aerospace applications including helicopter gearboxes and aircraft components. These components are prone to the wear as per the demands. The present work is the study of the significance of hard particle/ceramic, i.e. titanium carbide (TiC) in RZ5 mg alloy to protect the machine components from wear.

The abrasive wear analysis of in-situ RZ5-TiC magnesium matrix composite is considered for the study. The primary focus of the present work is to analyze the effects of varying control parameters, i.e. Wt.% of TiC, sliding distance and applied load on the responses, i.e. weight loss and coefficient of friction. Full factorial design of the experiment based on statistical analysis is used.

It is observed that the individually Wt.% of TiC and sliding distance show the comparatively significant effect on both responses. Similarly, the interaction between sliding distance and Wt.% of TiC indicated the considerable impact on weight loss. The regression equations are developed and validated for estimating responses. It is observed that the percentage errors are not appearing more than 10 per cent of responses. Therefore, the close agreement between measured and predicted values shows the adequacy of the model. The control factor is optimized using multi-response optimization. The variations of the order of 2.47 and 2.35 per cent in target value of the coefficient of friction and weight loss are achieved.

The current manuscript provides a detailed abrasive wear statistical analysis of RZ5-TiC composite. The influence of control parameters on the responses using the full factorial design, the main effect plots and interaction effects are presented.

The purpose of this paper is to develop a maintenance decision support system (DSS) framework using in-service lubricant data for fault diagnosis. The DSS reveals embedded patterns in the data (knowledge discovery) and automatically quantifies the influence of lubricant parameters on the unhealthy state of the machine using alternative classifiers. The classifiers are compared for robustness from which decision-makers select an appropriate classifier given a specific lubricant data set.

The DSS embeds a framework integrating cluster and principal component analysis, for feature extraction, and eight classifiers among them extreme gradient boosting (XGB), random forest (RF), decision trees (DT) and logistic regression (LR). A qualitative and quantitative criterion is developed in conjunction with practitioners for comparing the classifier models.

The results show the importance of embedded knowledge, explored via a knowledge discovery approach. Moreover, the efficacy of the embedded knowledge on maintenance DSS is emphasized. Importantly, the proposed framework is demonstrated as plausible for decision support due to its high accuracy and consideration of practitioners needs.

The proposed framework will potentially assist maintenance managers in accurately exploiting lubricant data for maintenance DSS, while offering insights with reduced time and errors.

Advances in lubricant-based intelligent approach for fault diagnosis is seldom utilized in practice, however, may be incorporated in the information management systems offering high predictive accuracy. The classification models' comparison approach, will inevitably assist the industry in selecting amongst divergent models' for DSS.