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The purpose of this paper is to investigate the influence of forced, in-line oscillation of a circular cylinder on an incoming incompressible flow field at different Reynolds numbers.

A space-time finite element approach is employed to model the flow around an oscillating cylinder.

The results show that two (2S), four (2P, two pair) and three vortices (P+S, one pair and one single) are shed in each cycle. In addition, a 2P _o mode is also observed, which is similar to the 2P mode but the vortices of the 2P _o mode differ in strength. The 2P mode of vortex shedding is observed along the entire wake of the flow field and 2P _o mode in the far wake. In some cases, the vortex street is transformed as it travels towards the exit to produce new patterns. One such pattern is observed for the first time in the present work, which is referred to as 2P _o* mode. The drag and lift coefficients observed are perfectly periodic at a Reynolds number of 200 and they reach a chaotic pattern as the Reynolds number is increased to a value of 350.

Originality of the paper lies in the observation of 2P vortex shedding mode or its variants in the downstream of the cylinder.

Automated skin lesion analysis plays a vital role in early detection. Having relatively small-sized imbalanced skin lesion datasets impedes learning and dominates research in automated skin lesion analysis. The unavailability of adequate data poses difficulty in developing classification methods due to the skewed class distribution.

Boosting-based transfer learning (TL) paradigms like Transfer AdaBoost algorithm can compensate for such a lack of samples by taking advantage of auxiliary data. However, in such methods, beneficial source instances representing the target have a fast and stochastic weight convergence, which results in “weight-drift” that negates transfer. In this paper, a framework is designed utilizing the “Rare-Transfer” (RT), a boosting-based TL algorithm, that prevents “weight-drift” and simultaneously addresses absolute-rarity in skin lesion datasets. RT prevents the weights of source samples from quick convergence. It addresses absolute-rarity using an instance transfer approach incorporating the best-fit set of auxiliary examples, which improves balanced error minimization. It compensates for class unbalance and scarcity of training samples in absolute-rarity simultaneously for inducing balanced error optimization.

Promising results are obtained utilizing the RT compared with state-of-the-art techniques on absolute-rare skin lesion datasets with an accuracy of 92.5%. Wilcoxon signed-rank test examines significant differences amid the proposed RT algorithm and conventional algorithms used in the experiment.

Experimentation is performed on absolute-rare four skin lesion datasets, and the effectiveness of RT is assessed based on accuracy, sensitivity, specificity and area under curve. The performance is compared with an existing ensemble and boosting-based TL methods.

The study aims to cope with the problems confronted in the skin lesion datasets with less training data toward the classification of melanoma. The vital, challenging issue is the insufficiency of training data that occurred while classifying the lesions as melanoma and non-melanoma.

In this work, a transfer learning (TL) framework Transfer Constituent Support Vector Machine (TrCSVM) is designed for melanoma classification based on feature-based domain adaptation (FBDA) leveraging the support vector machine (SVM) and Transfer AdaBoost (TrAdaBoost). The working of the framework is twofold: at first, SVM is utilized for domain adaptation for learning much transferrable representation between source and target domain. In the first phase, for homogeneous domain adaptation, it augments features by transforming the data from source and target (different but related) domains in a shared-subspace. In the second phase, for heterogeneous domain adaptation, it leverages knowledge by augmenting features from source to target (different and not related) domains to a shared-subspace. Second, TrAdaBoost is utilized to adjust the weights of wrongly classified data in the newly generated source and target datasets.

The experimental results empirically prove the superiority of TrCSVM than the state-of-the-art TL methods on less-sized datasets with an accuracy of 98.82%.

Experiments are conducted on six skin lesion datasets and performance is compared based on accuracy, precision, sensitivity, and specificity. The effectiveness of TrCSVM is evaluated on ten other datasets towards testing its generalizing behavior. Its performance is also compared with two existing TL frameworks (TrResampling, TrAdaBoost) for the classification of melanoma.

The purpose of this study is to investigate the application of Ni₃Al coating for boilers and other power plant equipment, which suffer severe erosion-corrosion problems resulting in substantial losses. Currently, superalloys are being used to increase the service life of the boilers. Although the superalloys have adequate mechanical strength at elevated temperature, they often lack resistance to erosion-corrosion environments.

In this paper, the erosion-corrosion performance of plasma-sprayed nickel aluminide (Ni₃Al) coating on nickel- and iron-based superalloys have been evaluated by exposing them to the low temperature primary superheater zone of the coal-fired thermal power plant at the temperature zone of 540^°C for ten cycles of 100 h duration. The exposed products were analysed along the surface and cross-section using scanning electron microscopy (SEM), X-ray diffraction (XRD) and electron micro probe analysis (EPMA).

The XRD, SEM and EPMA analyses have shown the formation of mainly NiO, NiAl₂O₄ and indicated the presence of Ni₃Al, Ni and Al₂O₃. In the boiler environment, Ni₃Al coating partially oxidizes and acts as a perfect barrier against erosion-corrosion of superalloys. The partially oxidised Ni₃Al coating remains intact even after 1,000 h cycle exposure.

The probable mechanism of attack for the plasma-sprayed Ni₃Al coating in the given boiler environment is presented.

This study aims to examine the literature from the Web of Science database published on board committees between 2002 and 2023 and outline the quantitative summary, journey of board committees’ research and suggest future research directions.

This study examines bibliometric-content analysis combined with a systematic literature review of articles on board committees to document the summary of the field. The authors used co-citation, co-occurrence and cluster analysis under bibliometric-content analysis to present the field summary.

Board committee composition, such as their gender, independence and expertise, as well as factors affecting corporate governance, such as reporting quality, earnings management and board monitoring, all have a significant impact on board committee literature. The field is getting growing attention from authors, journals and countries. Nevertheless, there is a need for further exploration in areas like expertise, member age and tenure, the economic crisis and the nomination and remuneration committee, which have not yet received sufficient attention.

This paper has both theoretical and practical contributions. From a theoretical perspective, this study substantiates the prevalence of agency theory within board committee literature, reinforcing the foundational role of agency theory in shaping discussions about board committees. On practical ground, the comprehensive overview of board committee literature offers scholars a road map for navigating this field and directing their future research journey. The identification of research gaps in certain areas serves as a catalyst for scholars to explore untapped dimensions, enabling them to strengthen the essence of the committees’ performance.

This paper seeks to summarise the results of available research on the use of high velocity oxy‐fuel (HVOF) thermal‐spray technique to provide protection against high temperature corrosion and erosion‐corrosion of materials.

This paper describes one of the recent thermal‐spray processes, namely HVOF thermal‐spray technology and presents a survey of the studies on the use of this technique to provide protection against corrosion and erosion‐corrosion of high temperature alloys, with a special emphasis on boiler steels.

High temperature corrosion and erosion‐corrosion are serious problems observed in steam‐powered electricity generation plants, gas turbines, internal combustion engines, fluidized bed combustors, industrial waste incinerators and recovery boilers in paper and pulp industries. These problems can be prevented by changing the material or altering the environment, or by separating the component surface from the environment. Corrosion prevention by the use of coatings for separating materials from the environment is gaining importance in surface engineering. Amongst various surface modifying techniques, thermal spraying has developed relatively rapidly due to the use of advanced coating formulations and improvements in coating application technology. One of the variants of thermal spraying, namely HVOF has gained popularity in recent times due to its flexibility for in‐situ applications and superior coating properties.

This review covers mainly information that has been reported previously in the open literature, international journals and some well‐known textbooks.

The paper presents a concise summary of information for scientists and academics, planning to start their research work in the area of surface engineering.

This paper fulfils an identified information/resources need and offers practical help to an individual starting out on a career in the area of surface engineering for erosion‐corrosion and wear.

The purpose of this study is to propose a financial distress prediction (FDP) model and method suitable for listed Indian small and medium enterprises (SMEs).

A three-part screening criteria similar to Platt and Platt (2006) was tested independently and jointly on Indian SMEs using statistically significant financial variables. Five stepwise multiple discriminant analysis (MDA) models were developed and the best-performing model was further compared against seminal models to check for robustness.

Model C2 developed under Criterion C which stated “if net income before special items is negative in any given year the firm is considered as ‘unwell’” proved robust and effective.

The proposed model identifies the importance of profitability and efficiency ratios over leverage ratios in determining financial distress and therefore, has implications for SME owners/managers and shareholders.

During the COVID-19 pandemic, the three-dimensional (3D) printing community is actively participating to address the supply chain gap of essential medical supplies such as face masks, face shields, door adapters, test swabs and ventilator valves. This paper aims to present a comprehensive study on the role of 3D printing during the coronavirus (COVID-19) pandemic, its safety and its challenges.

This review paper focuses on the applications of 3D printing in the fight against COVID-19 along with the safety and challenges associated with 3D printing to fight COVID-19. The literature presented in this paper is collected from the journal indexing engines including Scopus, Google Scholar, ResearchGate, PubMed, Web of Science, etc. The main keywords used for searches were 3D printing COVID-19, Safety of 3D printed parts, Sustainability of 3D printing, etc. Further possible iterations of the keywords were used to collect the literature.

The applications of 3D printing in the fight against COVID-19 are 3D printed face masks, shields, ventilator valves, test swabs, drug deliveries and hands-free door adapters. As most of these measures are implemented hastily, the safety and reliability of these parts often lacked approval. The safety concerns include the safety of the printed parts, operators and secondary personnel such as the workers in material preparation and transportation. The future challenges include sustainability of the process, long term supply chain, intellectual property and royalty-free models, etc.

This paper presents a comprehensive study on the applications of 3D printing in the fight against COVID-19 with emphasis on the safety and challenges in it.

Purpose: This chapter aims to evaluate the significant impact of Gandhian values on sustainable consumption behaviour (SCB) by applying the value-attitude-behaviour (VAB) framework. This chapter contributes by incorporating Gandhian values as one influencing factor for SCB.

Need for the Study: Values are considered as guiding principles in people’s lives. Studies suggest that values and other social and psychological factors can be vital in determining consumers’ behaviour towards sustainable consumption. There needs to be more empirical research on consumer behaviour facets of sustainable consumption for markets in India.

Methodology: The study uses partial least square structural equation modelling to empirically test proposed hypotheses and the research model of the relationship. The study results are based on data collected by administering a survey through a questionnaire confined to India.

Findings: The results indicated that Gandhian values, attitude, and sustainable consumption intention significantly influence SCB. Intention acts as a mediator between both outward and inward environmental attitudes and behaviour. The study provides directions for further research.

Practical Implications: This research study is helpful for researchers, marketers, and policymakers.

The research examines how the principle of Dharma can be included in the Indian National Education Policy (NEP) 2020. The study seeks to know how Dharma as an educational framework can be infused with contemporary education to promote moral and ethical development as well as intellectual growth among students in India.

This research uses qualitative analysis of NEP 2020 documents and literature related to Indian Knowledge Systems (IKS) and the concept of Dharma. It analyses the philosophical bases behind NEP including traditional texts like Vedas, Upanishads, among others. Moreover, this study also evaluates how current Dharma teachings are implemented into curriculum by assessing its present status of incorporation as a part of Indian Knowledge System.

This research has found that national educational reforms have considered many traditional Indian beliefs and values, but they have not done enough when it comes to incorporating Indian Knowledge System and the concept of Dharma into practice through the curriculum. The paper advocates for a system that is grounded on morals, thus blending the current learning standards with cultural heritage. These findings call for continuous endeavouring in order to embed ethical and moral dimensions of Dharma across all levels within India’s education systems.

The integration of Dharma and IKS in education can enhance the development of well-rounded individuals who are not only intellectually competent but also ethically and morally grounded. This strong foundation of Dharma will also act as a personal and professional guide. Educators and policymakers can use these insights to design curricula that promote holistic growth, aligning with both global educational standards and cultural values.

This paper examines the philosophical and ethical foundation of NEP 2020 instead of only considering its pedagogical and skill-enhancement characteristics, thereby giving a fresh viewpoint. It contributes to the discussion on educational reforms in India by highlighting how present educational needs should be linked with traditional values. The research shows that the concept of dharma can help learners develop holistically so that they can meet present-day problems without losing touch with timeless morals.