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High packaging density in the present VLSI era builds an acute power crisis, which limits the use of MOSFET device as a constituent block in CMOS technology. This leads researchers in looking for alternative devices, which can replace the MOSFET in CMOS VLSI logic design. In a quest for alternative devices, tunnel field effect transistor emerged as a potential alternative in recent times. The purpose of this study is to enhance the performances of the proposed device structure and make it compatible with circuit implementation. Finally, the performances of that circuit are compared with CMOS circuit and a comparative study is made to find the superiority of the proposed circuit with respect to conventional CMOS circuit.

Silicon–germanium heterostructure is currently one of the most promising architectures for semiconductor devices such as tunnel field effect transistor. Analytical modeling is computed and programmed with MATLAB software. Two-dimensional device simulation is performed by using Silvaco TCAD (ATLAS). The modeled results are validated through the ATLAS simulation data. Therefore, an inverter circuit is implemented with the proposed device. The circuit is simulated with the Tanner EDA tool to evaluate its performances.

The proposed optimized device geometry delivers exceptionally low OFF current (order of 10^−18 A/um), fairly high ON current (5x10^−5 A/um) and a steep subthreshold slope (20 mV/decade) followed by excellent ON–OFF current ratio (order of 10^13) compared to the similar kind of heterostructures. With a very low threshold voltage, even lesser than 0.1 V, the proposed device emerged as a good replacement of MOSFET in CMOS-like digital circuits. Hence, the device is implemented to construct a resistive inverter to study the circuit performances. The resistive inverter circuit is compared with a resistive CMOS inverter circuit. Both the circuit performances are analyzed and compared in terms of power dissipation, propagation delay and power-delay product. The outcomes of the experiments prove that the performance matrices of heterojunction Tunnel FET (HTFET)-based inverter are way ahead of that of CMOS-based inverter.

Germanium–silicon HTFET with stack gate oxide is analytically modeled and optimized in terms of performance matrices. The device performances are appreciable in comparison with the device structures published in contemporary literature. CMOS-like resistive inverter circuit, implemented with this proposed device, performs well and outruns the circuit performances of the conventional CMOS circuit at 45-nm technological node.

This study aims to focus on building a conceptual closed-loop vaccine supply chain (CLVSC) to decrease vaccine wastage and counterfeit/fake vaccines.

Through a focused literature review, the framework for the CLVSC is described, and the system dynamics (SD) research methodology is used to build a causal loop diagram (CLD) of the proposed model.

In the battle against COVID-19, waste management systems have become overwhelmed, which has created negative environmental and extremely hazardous societal impacts. A key contributing factor is unused vaccine doses, shown as a source for counterfeit/fake vaccines. The findings identify a CLVSC design and transshipment operations to decrease vaccine wastage and the potential for vaccine theft.

This study contributes to establishing a pandemic-specific VSC structure. The proposed model informs the current COVID-19 pandemic as well as potential future pandemics.

A large part of the negative impact of counterfeit/fake vaccines is on human well-being, and this can be avoided with proper CLVSC.

This study develops a novel overarching SD CLD by integrating the epidemic model of disease transmission, VSC and closed-loop structure. This study enhances the policymakers’ understanding of the importance of vaccine waste collection, proper handling and threats to the public, which are born through illicit activities that rely on stolen vaccine doses.

This study aims to estimate the electric power production of the 20 MWp solar photovoltaic (PV) plant installed in the Adrar region, South of Algeria using minimal knowledge about weather conditions.

In this study, simulation models based on linear and nonlinear approaches were used to estimate accurate energy production from minimum radiometric and meteorological data. Simulations have been carried out by using multiple linear regression (MLR) and artificial neural network (ANN) models with three basic types of neuron connection architectures, namely, feed-forward neural network, cascade-forward neural network (CNN) and Elman neural network. The performance is measured based on evaluation indexes, namely, mean absolute percentage error, normalized mean absolute error and normalized root mean square error.

A comparison of the proposed ANN models has been made with MLR models. The performance analysis indicates that all the ANN-based models are superior in prediction accuracy and stability, and among these models, the most accurate results are obtained with the use of CNN-based models.

The considered model will be adopted in solar PV forecasting areas as part of the operational forecasting chain based on numerical weather prediction. It can be an effective and powerful forecasting approach for solar power generation for large-scale PV plants.

The operational forecasting system can be used to generate an effective schedule for national grid electricity system operators to ensure the sustainability as well as favourable trading performance in the electricity, such as adjusting the scheduling plan, ensuring power quality, reducing depletion of fossil fuel resources and consequently decreasing the environmental pollution.

The proposed method uses the instantaneous radiometric and meteorological data in 15-min time interval recorded over the two years of operation, which made the result exploits a fact that the energy production estimation of PV power generation station is comparatively more accurate.

Despite studies claiming gender inclusion is beneficial for organizations, the under-representation of females in the workforce is a reality. As recruitment practices impact employees' entry into organizations, examining the salient predictors of job pursuit intention might foster gender inclusivity.

Based on a mixed-method study conducted in two phases (Phase 1: a sample of 2,084 professionals; Phase 2: interviews of 20 senior human resource (HR) professionals and interviews with 26 women professionals), we examine the key predictors of job pursuit intention of women. We employed a qualitative study as Phase 2 employed a qualitative study to understand why some of the proposed hypotheses were not supported.

We found that work–life balance, perceived job security and perceived ethical behavior of organizations were more important for female than the male applicants in influencing their job pursuit intention. Also, the type of work and person–organization (P–O) fit were found to be equally important for both the gender groups. The implications of the study to theory and practice were discussed.

Our study extends the existing literature by identifying salient factors (such as work–life balance, perceived job security and ethical citizenship) that are found to be more important for female applicants compared to their male counterparts while pursuing a job. Also, females were found to worry more about losing or not finding a job than males. Our results further indicate that type of work and P–O fit have a significant effect on job pursuit intention for both male and female applicants. The study addresses the need for research on targeted recruitment to increase gender inclusion.

The contribution of this paper lies in identifying critical factors relevant to the female applicants in India who potentially constitute a large talent pool waiting to be leveraged. It adds to the body of knowledge on enabling inclusivity and affirmative action for increasing gender diversity through recruitment. By highlighting the factors that should be given prominence in job promotions to attract more female candidates and emphasizing the gender-focused HR policies and practices and through internal and external communication, it helps practitioners attract and retain female applicants in an emerging economy like India.

Our study contributes in three ways. First, it attempts to plug the gap by investigating gendered preferences in job pursuit intentions between male and female applicants, especially in different cultural environments and in emerging markets such as India. Second, existing studies on job pursuit intentions were based mostly on inputs from student respondents. Our study has collected data from professionals working in organizations who have worked and experienced gender-related HR practices in organizations. Third, our study used a mixed-method approach to get a nuanced understanding of female talent expectations and preferences during the job-seeking behavior.

The involvement of wear, friction and lubrication in engineering systems and industrial applications makes it imperative to study the various aspects of tribology in relation with advanced technologies and concepts. The concept of Industry 4.0 and its implementation further faces a lot of barriers, particularly in developing economies. Real-time and reliable data is an important enabler for the implementation of the concept of Industry 4.0. For availability of reliable and real-time data about various tribological systems is crucial in applying the various concepts of Industry 4.0. This paper aims to attempt to highlight the role of sensors related to friction, wear and lubrication in implementing Industry 4.0 in various tribology-related industries and equipment.

A through literature review has been done to study the interrelationships between the availability of tribology-related data and implementation of Industry 4.0 are also discussed. Relevant and recent research papers from prominent databases have been included. A detailed overview about the various types of sensors used in generating tribological data is also presented. Some studies related to the application of machine learning and artificial intelligence (AI) are also included in the paper. A discussion on fault diagnosis and cyber physical systems in connection with tribology has also been included.

Industry 4.0 and tribology are interconnected through various means and the various pillars of Industry 4.0 such as big data, AI can effectively be implemented in various tribological systems. Data is an important parameter in the effective application of concepts of Industry 4.0 in the tribological environment. Sensors have a vital role to play in the implementation of Industry 4.0 in tribological systems. Determining the machine health, carrying out maintenance in off-shore and remote mechanical systems is possible by applying online-real-time data acquisition.

The paper tries to relate the pillars of Industry 4.0 with various aspects of tribology. The paper is a first of its kind wherein the interdisciplinary field of tribology has been linked with Industry 4.0. The paper also highlights the role of sensors in generating tribological data related to the critical parameters, such as wear rate, coefficient of friction, surface roughness which is critical in implementing the various pillars of Industry 4.0.

The purpose of this study is to develop a cylindrical capacitive sensor that has the advantages of high resolution, small size and designability and can be easily installed on lubricant pipeline to monitor lubricant oil debris.

A theoretical model of the cylindrical capacitive sensor is presented to analyze several parameters’ effectiveness on the performance of sensor. Numerical simulations are then conducted to determine the optimal parameters for preliminary experiments. Experiments are finally carried out to demonstrate the detectability of developed capacitive sensors.

It is clear from experimental results that the developed capacitive sensor can monitor the debris in lubricant oil well, and the capacitance values increase almost linearly when the number and size of debris increase.

There is lot of further work to do to apply the presented method into the application. Especially, it is necessary to consider several factors’ influence on monitoring results. These factors include the flow rate of the lubricant oil, the temperature, the debris distribution and the vibration. Moreover, future work should consider the influence of the oil degradation to the capacitance change and other contaminations (e.g. water and dust).

This work conducts a feasibility study on application of capacitive sensing principle for detecting debris in aero engine lubricant oil.

The novelty of the presented capacitance sensor can be summarized into two aspects. One is that the sensor structure is simple and characterized by two coaxial cylinders as electrodes, while conventional capacitive sensors are composed of two parallel plates as electrodes. The other is that sensing mechanism and physical model of the presented sensor is verified and validated by the simulation and experiment.

Introduction: Cost competitiveness, customer focus, and sustainability compliance are essential for new-age firms to survive and succeed in the VUCA market environment. This study examines how automobile corporations have improved cost competitiveness, productivity, and product quality.

Purpose: This study examines the importance of cost competitiveness, customer focus, and sustainability compliance for the long-term survival of organisations in VUCA markets, looking at the practical efforts made by automobile corporations to enhance cost competitiveness, productivity, and quality.

Methodology: The study utilises a comprehensive analysis of the strategies and initiatives implemented by the selected automobile companies. It involves a review of relevant literature, case studies, financial data analysis, and interviews with key industry experts, providing a holistic understanding of the actions taken by these organisations to achieve their goals.

Findings: The study reveals that cost competitiveness, customer focus, and sustainability compliance are critical factors for the long-term survival and success of organisations in the automotive industry. The analysed automobile companies have undertaken practical efforts to improve cost competitiveness, enhance productivity, and ensure high-quality products, enabling them to navigate the challenges and maintain a competitive edge.

Significance: The findings of this study contribute to a deeper understanding of the importance of cost competitiveness, customer focus, and sustainability compliance in the automotive industry. It highlights the need for organisations to constantly monitor both qualitative and quantitative profit to avoid complacency and ensure long-term efficiency. The study’s insights are relevant to businesses operating in other sectors, as they face similar challenges in the VUCA market environment.

The authors aimed to identify the opinions of young adult consumers regarding food processing companies’ (FPCs) credibility in terms of food safety (FS).

The authors surveyed Generation Z (GenZ) consumers. The authors assessed the reliability of the research questionnaire using Cronbach’s alpha statistics. The authors used descriptive statistics and one-way ANOVA analysis of variance in the data analysis to determine intergroup variability. The authors performed statistical analyses using IBM SPSS Statistics. 27.

The most valued determinants for consumers were competence and skills, and the most valued family members’ opinions on FS, followed by experts’ opinions. FS concerns are more associated with FPCs than with farmers. The ethics of conduct and moral responsibility play an important role in assessing the FPCs’ credibility.

The questionnaire did not focus on specific food industries, such as fruit and vegetables, fish, meat, dairy, etc. In the future, a similar survey on producers’ credibility should consider the issue of FS risks associated with the specifics of a particular industry.

The authors proposed a set of factors that may determine young adult consumers’ perception of the FPCs’ credibility, which they may use for research within other consumer groups.

The purpose of this paper is to explore the brand relationships between a mega-sports event, the Olympic Games, and its branded main sponsors, using the lens of brand personality.

The study uses the internet-based website communications of the sponsor and event brands to assess congruence in brand personality identity exhibited in the communications of sponsors and how these relate to the event brand itself. A lexical analysis of the website text identifies and graphically represents the dominant brand personality traits of the brands relative to each other.

The results show the Olympic Games is communicating excitement as a leading brand personality dimension. Sponsors of the Olympics largely take on its dominant brand dimension, but do not adapt their whole brand personality to that of the Olympics and benefit by adding excitement without losing their individual character. The transference is more pronounced for long-running sponsors.

Sponsorship of the Olympic Games does give brands the opportunity to capture or borrow the excitement dimension alongside building or reinforcing their own dominant brand personality trait or to begin to subtly alter their brand positioning.

This study is the first to examine how the sponsor’s brand aligns with the event being sponsored as a basis for developing a strong shared image and associative dimensions complimentary to the positioning of the brand itself.

The Indian banking industry has undergone many changes with the advent of changing economic environment in the country. Many changes have taken place in terms of customer services, work culture, infrastructure, approach to sales and customer relationship management amongst others. This paper aims to attempt to evaluate the adherence of BCSBI code by the banks. Customer perception has been evaluated to analyse the adherence of the code. Also, the authors have tried to evaluate the impact of customer type (mass and class customers) and bank type (based on bank ownership- private and public banks) on the compliance of the code by the bankers or minimum regulatory requirements with respect to customer services. Questionnaire has been developed as per the Banking Code and Standard Board of India (a customer services cell of Reserve Bank of India), and BCSBI has been used as a regulatory standard to compare the level of compliance by the banks.

Primary data have been collected from private and public sector banks. In the first step, instrument validity and reliability has been checked by using structural equation modelling; in the second step, descriptive statistics has been used to know the extent of fulfillment of standard by banks; and in the third step, a two-way multivariate analysis of variances has been used to do the comparative analyses of the respondents data.

The overall finding of the research shows that overall adherence of the dimension of code are not in sync with the objective of the code. Study also has shown the mindset of the Indian bankers that how they predominantly serve the class customers and push those products to the customers which are target based or earn profitability for the banks and incentives for the banker. Private banks are ahead in compliance with respect to the customer services, but they are also ahead in sales malpractices.

This study is an eye opener for the regulators, as per BCSBI regulations, surprise supervision take place every year, but this study shows the ineffectiveness of that supervision. Following the BCSBI norms by the banks is just eyewash of regulators, but all the norms are fulfilled only in papers but not in actual practice.

The research paper is original piece of work; the researcher did not find any study related to BCSBI code in Indian as well as in international literature.