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The purpose of this study is to examine the effects of sensitization on the metallurgical characteristics of weld joints made up of austenitic stainless steel (AISI 316L) and ferritic stainless steel (AISI 430), using the gas tungsten arc welding (GTAW) process with ER316L filler wires.

A non-consumable tungsten electrode with a diameter of 1.6 mm was used during the GTAW procedure. The filler wire, ER316L, was selected based on the recommendation provided in literature. To explore the interconnections among the structure and properties of these weldments, the techniques including scanning electron microscopy and optical analysis have been used. In addition, the sensitization behaviour of the weldments was investigated using the double loop electrochemical potentio-kinetic reactivation (DLEPR) test.

Microstructural analyses revealed the occurrences of coarsened grains with equiaxed columnar grains and migrating grain boundaries in the weld zone. The results of the DLEPR test demonstrated that heat affected zone (HAZ) of AISI 430 was more susceptible to sensitization than HAZ of AISI 316L. Microstructure analysis also revealed the precipitation of large amounts of chromium carbide at the grain boundaries region of AISI 430 welded steel, causing more sensitization and, as a result, more failure or breaking at the side of AISI 430 weld in the dissimilar weldment of AISI 316L–AISI 430.

The present work has been carried out to determine the appropriate welding conditions for joining AISI 316L and AISI 430, as well as the metallurgical properties of the dissimilar weldment formed between AISI 316L and AISI 430. Owing to the difficulties in measuring the performance of these types of dissimilar joints given their unique mechanical and microstructural characteristics, research on the subject is limited.

Despite a growing body of research focusing on the dark side of sharing economy development, arguments are fragmented and incomplete. This study aims to address the gap by integrating existing viewpoints based on a provider’s perspective.

This study conducted a bibliometric analysis using text mining and clustering algorithm techniques to measure the scope of scientific output on this topic and identify the main research themes.

Through the bibliometric analysis, this study developed an integrative framework based on the platform providers’ internal management issues and external conflicts with consumers, society, government regulations and traditional business. It also identified significant gaps within each research theme and proposed a future research agenda.

Sharing economy development has not yet been fully understood and regulated, leading to unprecedented challenges to existing business systems. The study addresses knowledge gaps and advances the understanding of the dark side of the sharing economy based on the provider’s internal management and interplay with external forces. It offers a roadmap for future research to advance understanding of the “hidden” dark side of the sharing economy.

Social mediametrics is a subfield of measurement in which the emphasis is placed on social media data. This paper analyzes the trends and patterns of paper comprehensively mentions on Twitter, with a particular focus on Twitter's mention behaviors. It uncovers the dissemination patterns and impact of academic literature on social media. The research has significant theoretical and practical implications.

This paper explores the fundamental attributes of Twitter mentions by means of analyzing 9,476 pieces of scholarly literature (5,097 from Nature and 4,379 from Science), 1,474,898 tweets and 451,567 user information collected from Altmetric.com database and Twitter API. The study uncovers assorted Twitter mention characteristics, mention behavior patterns and data accumulation patterns.

The findings illustrate that the top academic journals on Twitter have a wider range of coverage and display similar distribution patterns to other academic communication platforms. A large number of mentioners remain unidentified, and the distribution of follower counts among the mention users exhibits a significant Pareto effect, indicating a small group of highly influential users who generate numerous mentions. Furthermore, the proportion of sharing and exchange mentions positively correlates with the number of user followers, while the incidence of supportive mentions has a negative correlation. In terms of country-specific mention behavior, Thai scholars tend to utilize supportive mentions more frequently, whereas Korean scholars prefer sharing mentions over communicating mentions. The cumulative pattern of Twitter mentions suggests that these occur before official publication, with a half-life of 6.02 days and a considerable reduction in the number of mentions is observed on the seventh day after publication.

Conducting a multi-dimensional and systematic analysis of Twitter mentions of scholarly articles can aid in comprehending and utilizing social media communication patterns. This analysis can uncover literature's distribution patterns, dissemination effects and social significance in social media.

The main purpose of the present work is to study the multi response optimization of dissimilar friction stir welding (FSW) process parameters using Taguchi-based grey relational analysis and desirability function approach (DFA).

The welded sheets were fabricated as per Taguchi orthogonal array design. The effects of tool rotational speed, transverse speed and tool tilt angle process parameters on ultimate tensile strength and hardness were analyzed using grey relational analysis, and DFA and optimum parameters combination was determined.

The tensile strength and hardness values were evaluated from the welded joints. The optimum values of process parameters were estimated through grey relational analysis and DFA methods. Similar kind of optimum levels of process parameters were obtained through two optimization approaches as tool rotational speed of 1150 rpm, transverse speed of 24 mm/min and tool tilt angle of 2° are the best process parameters combination for maximizing both the tensile strength and hardness. Through these studies, it was confirmed that grey relational analysis and DFA methods can be used to find the multi response optimum values of FSW process parameters.

In the present study, the FSW is performed with L9 orthogonal array design with three process parameters such as tool rotational speed, transverse speed and tilt angle and three levels.

Aluminium alloys are widely using in automotive and aerospace industries due to holding a high strength to weight property.

Very limited work had been carried out on multi objective optimization techniques such as grey relational analysis and DFA on friction stir welded joints made with dissimilar aluminium alloys sheets.

The purpose of this study is to apply altmetrics and bibliometric indicators on the top 100 most mentioned articles published related to the sustainable development goal (SDG)-13, Climate Action.

The authors used the Altmetric Explorer’s SDGs filter to extract the most mentioned articles belonging to Climate Action and their other characteristics, such as DOI, titles, tools mentioning them and their demographic descriptions. The same set of papers was searched in the Dimensions database to extract them in the format importable in R-studio to check the distribution of papers across various journals and identify their subject category, countries and institutions publishing these papers. Further, SPSS was used to check the correlation between altmetric attention score (AAS) and citations.

The results of the paper showed the mean of AAS and the citations received by the articles was 3,556.35 and 304.04, respectively. Twitter has been the most used social media platform for mentioning the research related to climate action, covering 88.1% of the total mentions. The Twitter and the News mention demographics show the USA contributing the most tweet mentions (15.2%) as well as news mentions (57.65%) to the papers. Also, the USA has solely published 49 papers from the total papers selected for the study. The papers were published in 31 journals most of them belonging to the quartile first (Q1) category and primarily belonged to the subject category “Earth Sciences.” Pearson’s correlational method showed a significant but low positive correlation between AAS and citation counts (r = 0.365, p = <0.001) and a strong positive correlation between the citations and Mendeley readership counts (r = 0.907).

The research is original in nature and discovered very interesting results about climate action using altmetric and bibliometric techniques.

The Internet of Things (IoT), as one of the new digital technologies, has created wide applications in various industries, and one of the most influential industries of this technology is the transportation industry. By integrating the IoT with the transportation industry, there will be dramatic changes in the industry, and it will provide many entrepreneurial opportunities for entrepreneurs to develop new businesses. Opportunity identification is at the heart of the entrepreneurial process, and entrepreneurs identify innovative goods or services to enter a new market by identifying, evaluating, and exploiting opportunities. Despite the desire of transportation managers to invest in the IoT and the increase in research in this area, limited research has focused on IoT-based entrepreneurial opportunities in the transportation industry. Therefore, the present study aims to identify IoT-based entrepreneurial opportunities in the transportation industry and examine their importance.

To achieve the research objective, the authors applied a mixed approach. First, adapting the lens of the industry value chain theory, a comprehensive literature review, besides a qualitative approach including semi-structured interviews with experts and thematic analysis, was conducted to identify the entrepreneurial opportunities. The identified opportunities were confirmed in the second stage using a quantitative survey method, including the Student t-test and factor analysis. Finally, the identified opportunities were weighted and ranked using the best worst method (BWM).

Entrepreneurial opportunities are classified into five main categories, including “smart vehicles”, “business partners/smart transportation supply side”, “supporting services”, “infrastructures”, and “smart transport management and control”. The infrastructures group of opportunities ranked the highest amongst the identified groups.

This study adds to the digital entrepreneurship opportunity recognition literature by addressing opportunities in a smart industry propelled by digital technologies, including developing new products or new applications of the available technologies. Additionally, inspired by the industry value chain theory, this article develops a framework including various digital entrepreneurial opportunity networks which are necessary to add value to any industry and, thus, could be applied by entrepreneurs to recognize opportunities for new intermediaries to enter other digital-based industries. Finally, the present study identifies the IoT-based entrepreneurial opportunities in the smart transportation industry and prioritizes them, providing practical insights regarding the creation of entrepreneurial ecosystems in the field of smart transportation for entrepreneurs and policymakers.

Personality characteristics have a significant impact on the economic segment of women entrepreneurs. Due to gender biases or other factors, women entrepreneurs are fewer in India than in other countries. The purpose of this study is to identify the personality factors and challenges that affect their growth and success.

Logistic regression was used to show the impact of personality characteristics and firm performance and the moderating effect of challenges between personality characteristics and firm performance.

The findings revealed a significant impact of personality factors on firm performance, the absence of moderating effects of challenges and the presence of a mediation effect of enterprise age and enterprise location.

This research will help policymakers adopt policies and plans to reduce obstacles and challenges so that the economic conditions of women’s entrepreneurship can transform.

Women in the 21st century still live in a male-dominated patriarchal society because they face the problem of financial capital.

The results show the impact of personality traits and challenges on the firm performance of women’s entrepreneurship.

This paper presents a cross-sectional study that assessed the impact of the COVID-19 pandemic on rural migrants in Bihar. The primary objective of this study was to evaluate the overall impact of the pandemic on migrants and examine their livelihoods, with a focus on identifying measures that can mitigate the economic consequences.

This study used a telephonic survey to collect primary data from 419 respondents. Descriptive statistics were used to analyze the data, and three indices were constructed: fear and worries, trust and prevention.

The findings provide insights into the psychological well-being of migrant workers and highlight the challenges they face in sustaining their livelihoods amidst the pandemic. This study concludes by suggesting potential measures to alleviate the economic impact and enhance the resilience of this vulnerable population.

This study may be limited by the representativeness of the sample as well as the potential for social desirability bias. The study may also be limited by the reliability and validity of the measures used to capture the fear and worries, trust and prevention indices.

Numerous studies have examined the impact of the COVID-19 pandemic on rural migrants. However, there are limited studies that estimate the impact of the proposed study based on the challenges faced by rural migrants in Bihar during the pandemic.

The purpose of this paper is to present an applied method to design the low-speed contact between a mass and surface of a beam using an analytical solution based on the first-order shear deformation beam theory. Also, a simulation of impact process is carried out by ABAQUS finite element (FE) code.

In theoretical formulation, first strains and stresses are obtained, then kinetic and potential energies are written, and using a combination of Ritz and Lagrange methods, a set of system of motion equations in the form of mass, stiffness and force matrices is obtained. Finally, the motion equations are solved using Runge–Kutta fourth order method.

The von Mises stress contours at the impact point and contact force from the ABAQUS simulation are illustrated and it is revealed that the theoretical solution is in good agreement with the FE code. The effect of changes in projectile speed, projectile diameter and projectile mass on the results is carefully examined with particular attention to evaluate histories of the impact force and beam recess. One of the important results is that changes in projectile speed have a greater effect on the results than changes in projectile diameter, and also changes in projectile mass have the least effect.

This paper presents a combination of methods of energy, Ritz and Lagrange and also FE code to simulate the problem of sandwich beams under low velocity impact.