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This study aims to investigate the prevalence of shock boundary layer interaction (SBLI) in air-breathing intake system is highly undesirable since this leads to high pressure gradients, typical stream mutilation and pressure drop. A novel flow control mechanism is incorporated in this research holding an array configuration of passive flow control device (micro ramps [MR]) that is adapted to improve the boundary layer stability.

Two geometric variants of the MR, namely, MR40 and MR80 is considered which reduce the pressure drop during SBLI. The incidence oblique shock wave angle of 34° is considered for the modelling. Large eddy simulation (LES) turbulence model was used with subgrid models of Wall modelled LES, Smagorinsky–Lilly to compute the unsteady effects of SBLI control using micro vortex generators. The unsteady results are compared with steady Reynold’s average Naviers–Stoke’s equation for calibrating the turbulence models.

The array configuration of MR80 reduces the pressure drop by 22% as compared with no ramp configuration and also reduces the flow distortion in hypersonic inlet. The most affected region of the MR is in the vicinity of center-line. Quantitative results prove that the upstream influence of the shock waves has been largely reduces by MR80 array configuration as compared to single MR80 pattern configuration. Different vortex structures found in the experiments was exclusively predicted using LES.

This paper substantiates the requirement of MR array configuration for transferring the momentum from free stream to the boundary layer and thereby energizing the boundary layer. This process of energization delays the flow separation in hypersonic flow.

This study aims to investigate factors that influence the attitudes and intentions of investors towards environmental, social and governance (ESG) stocks in the presence of perceived risk as a moderator.

Data was collected through an online survey method from 341 investors with more than three years of investing experience. Smart PLS was used to analyse the data using two-stage structural equation modelling. First, a measurement model was performed for construct reliability and validity, followed by path analysis (structural model) for hypothesis testing and overall model predictability.

The findings show that both environmental concern (altruistic value) and economic concern (egoistic value) are crucial for the attitude and intention of investors to invest in ESG-backed stocks; however, environmental concern was found to be a more significant predictor of their behaviour, showing evidence of pro-environmental values in the decision-making of utility-seeking individuals. No significant impact of perceived risk was evident as a moderator of the relationship between attitude and intention towards ESG stocks.

The study's findings have implications for fund managers, policymakers, and the government. Values as antecedents were found to be influential in shaping investors’ attitudes and intentions towards the environmental cause. Fund managers could include more ESG-compliant companies in their portfolios, and the government can play an important role in encouraging investors by providing financial incentives. Corporates should also take strategic steps to adopt green production processes to secure long-term, sustainable capital funding.

To the best of the authors’ knowledge, there has been no research done in the field of ESG investing that takes into account the values (both altruistic and egoistic) of investors as potential antecedents of their attitudes and intentions.

The purpose of this paper is to supplement and update previously published articles about artificial intelligence (AI) instruments and operations in banking sectors with the following objectives in mind: to understand the role of AI in banking sectors; to explore the themes and context in this area based on keywords, co-citations and co-words; and to identify future research direction by evaluating the trend and direction of previous research.

This study adopts a semi-inductive approach with the convolution of bibliometrics and literature review. This study used bibliometrics for the identification of literature across multiple databases and systematic literature review on identified articles to explore heterogeneous sectors within AI in banking and finance.

This study contributes a literature-based model that accounts for both the broadly in AI application in banking and finance: predictive modeling in risk assessment and detection; financial decision-making; client service delivery; and emerging FinTech applications of AI and machine learning.

This study is among the few to address the literature of tools and application of AI in banking through mixed-methods approach and produce a synthesized model for the same.

In this research work, the general form of reliability measures, which include availability, mean time to failure (MTTF), and sensitivity analysis, are investigated with their graphical representation, which would help designers and engineers improve the reliability of the system. Along with reliability assessment, a mathematical model is developed and solved to achieve the minimum cost of the system as well as maximum reliability.

In the proposed work, a general model of a solar seed sowing machine is considered for reliability evaluation using the Markov model process. The proposed system is a series-parallel arrangement of components where three components, namely the solar panel, batteries and direct current (DC) motor, are connected in series while all the operators are connected in parallel. The implemented Markov model approach assesses several parameters of reliability, which opens the scope for improvement in reliability and other measures like mean time to failure (MTTF) and sensitivity of the proposed system. So that the machine can deliver the desired output on the field. Also, the particle swarm optimization (PSO) algorithm is applied to optimize the cost of the system with the desired level of reliability.

Implementation of PSO provides the optimal cost for the proposed system with a predetermined level of reliability, which shows the relationship between reliability and cost of the system. Also, the Markov process approach provides the availability function, reliability function, reliability at different time values, MTTF and sensitivity of the proposed system.

This work evaluates the crucial characteristics of reliability for the proposed solar seed sowing machine using the Markov model which is a stochastic model. The assessment of reliability measures such as MTTF, availability and sensitivity plays a vital role in measuring and improving the performance of the machine in the actual environment. Examining the data obtained in this research is of great importance for the manufactures and system designers. Also, the powerful optimization technique PSO is implemented to solve a non-linear mixed-integer programming problem that provides the optimal cost for the system with desired reliability.

There are several methods developed in the recent past to predict the spread of COVID-19 in different countries. However, due to changing scenarios in terms of interaction among people, none could predict the case close to the actual figures. An attempt to simulate people's interaction due to economic reopening concerning the confirmed cases at various places as per changing situation has been made. The scenario development method's base lies in the hypothesis that if there were no inter-state transportation during India's lockdown after May 24th, the number of infection cases would have started lowering down in a normalized progression.

This study has developed three scenarios from the worst to the business-as-usual to the best in order to project the COVID-19 infections in India concerning infections observed from January 30th till May 24th, 2020, since the domestic flights became operational from May 25th, 2020, in India.

Based on the observed cases till May 24th, the rise of cases is projected further in a random progression and superimposed to the normal progression. The results obtained in the three scenarios present that worst case needs complete lockdown, business-as-usual case needs regulatory lockdown and best case assures complete lockdown release by the second week of September 2020. This study suggests the preparedness and mitigation strategy for a threefold lockdown management scheme in all-inclusive.

The work has been done on a hypothesis which is solely original.

The purpose of this paper is to design a ring network topology system and alter it into a series–parallel type framework. Then, reliability of the framework is analysed and authors also discussed the signature to analyse the most sensitive component.

This study presents a ring-shaped network system where this type of topology forms a single continuous pathway for signals through every node. In this study, a system consists of ring network topology is generalized in the series–parallel mixed configuration and reliability characteristics are evaluated with the assistance of universal generating function (UGF) technique. The system consists of wires, repeaters, components or computers and power supply. The wires and repeaters are in series, so, if they fail the whole system will fail and the signals will not go further. The components or computers are connected to each other in parallel configuration. So, the whole system will not fail until the last computer is working. There is also a two-unit power supply system which has one unit in a standby mode. On the failure of first power supply, the second one will start functioning and the whole system fails on the failure of both power supply.

By the assistance of UGF technique, reliability function of the framework is evaluated. Also, Barlow–Proschan index and expected lifetime for the designed system is estimated by considering a numerical example for the general ring-shaped network system.

UGF technique is very effective for estimating the reliability of a system with complex structure and having two performance rates, i.e. completely failed and perfectly working, or more than two, i.e. multi-state performance. This technique enables to estimate every components contribution in the working and failure of the whole system. A general model of ring-shaped network system is taken and generalized algorithm is drawn for the system. Then a particular numerical example is solved for illustrating the use of this technique.

This research mirrors a 360° probe into bibliometric review of various studies aimed to examine the relationship between financial inclusion and sustainable development (FI and SD). It also offers a conspectus of apex contributors, influential articles, key journals and potential avenues for further research in this crucial area of global progress.

The study is the abstract of a total 233 papers on the subject representing a period between 2012 and 2023 in the Scopus database in the domain. This investigation probes into publication trends, the most inexhaustible contributors by national journals, publications and authors. The study conducts keyword co-occurrence analysis and examines thematic evolution using Vosviewer and Biblioshiny.

The findings reveal four prominent clusters: (a) Financial growth with FI, (b) Economic Empowerment with Sustainable Goals, (c) Environmental Sustainability and (d) Microfinance and Digital Era. Furthermore, the study paves way for the future research agenda with the help of these research themes.

To the best of the authors’ knowledge, this paper is the first of its kind in deeply probing the literature on FI and SD from a bibliometric perspective. Hence the findings of this study is a powerful weapon for researchers and practitioners coupled with future research inquiries, offering valuable insights and establishing robust quantitative foundations for advancing knowledge in the realms of FI and SD.

The purpose of this paper is to deal with a linear multi-state sliding window coherent system which generalizes the consecutive k-out-of-r-from-n:F system in the multi-state case. The system has n linearly ordered multi-state elements consisting of m parallel independent and identically distributed elements. Every element of the system can have two states: completely working or totally failed. The system fails if the sum of performance rate is lower than the given weight.

The authors proposed to compute the signature, MTTF and Barlow–Proschan index with the help of UGF technique of multi-state SWS which consists of m parallel i.i.d. components in each multi-state window.

In the present study, the authors have evaluated the signature reliability, expected lifetime, cost analysis and Barlow–Proschan index.

In this study, the authors have studied a linear multi-state sliding window system which consists of n ordered multi-state element, and each multi-state element also consists of m parallel windows. The focus of the present paper is to evaluate reliability metrices of the considered system with the help of signature from using the universal generating function.

The purpose of this paper is to evaluate the reliability and signature reliability of solar panel k-out-of-n-multiplex system with the help of universal generating function.

Energy scarcity and global warming issues have become important concerns for humanity in recent decades. To solve these problems, various nations work for renewable energy sources (RESs), including sun, breeze, geothermal, wave, radioactive and biofuels. Solar energy is absorbed by solar panels, referred to as photovoltaic panels, which then transform it into electricity that can be used to power buildings or residences. Remote places can be supplied with electricity using these panels. Solar energy is often generated using a solar panel that is connected to an inverter for power supply. As a result, a converter reliability evaluation is frequently required. This paper presents a study on the reliability analysis of k-out-of-n systems with heterogeneous components. In this research, the universal generating function methodology is used to identify the reliability function and signature reliability of the solar array components. This method is commonly used to assess the tail signature and Barlow-Proschan index with independent and identically distributed components.

The Barlow-Proschan index, tail signature, signature, expected lifetime, expected cost and minimal signature of independent identically distributed are all computed.

This is the first study of solar panel k-out-of-n-multiplex systems to examine the signature reliability with the help of universal generating function techniques with various measures.

The purpose of this paper is to evaluate the reliability and structure function of refrigeration complex system consisted of four components in complex manner.

Although, a variety of methodologies have been used to assess the refrigeration system's reliability function that has proven to be effective, the universal generating function approach is the basis of this research study, which is used in the calculation of a domestic refrigeration system with four separate components that are related in series and parallel with a corresponding sample to form a complex machine.

In this paper, signature reliability of the refrigeration system has been evaluated with the universal generating function technique. There are four components present in the proposed system in complex (series and parallel) manner. The tail signature, signature, Barlow–Proschan index, expected lifetime and expected cost of independent identically distributed are all computed.

This is the first study of domestic refrigeration system to examine the signature reliability with the help of universal generating function techniques with various measures. Refrigeration systems are an essential process in industries and home applications as they perform cooling or the maintain temperature at the desired value. A cycle of refrigeration consists of four main components such as, heat exchange, compression and expansion with a refrigerant flowing through the units within the cycle.