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The number of people with special needs, including citizens and military personnel, has increased as a result of terrorist attacks and challenging conditions in Iraq and other countries. With almost 80% of the world’s amputees having below-the-knee amputations, Iraq has become a global leader in the population of amputees. Important components found in lower limb prostheses include the socket, pylon (shank), prosthetic foot and connections.

There are two types of prosthetic feet: articulated and nonarticulated. The solid ankle cushion heel foot is the nonarticulated foot that is most frequently used. The goal of this study is to use a composite filament to create a revolutionary prosthetic foot that will last longer, have better dorsiflexion and be more stable and comfortable for the user. The current study, in addition to pure polylactic acid (PLA) filament, 3D prints test items using a variety of composite filaments, such as PLA/wood, PLA/carbon fiber and PLA/marble, to accomplish this goal. The experimental step entails mechanical testing of the samples, which includes tensile testing and hardness evaluation, and material characterization by scanning electron microscopy-energy dispersive spectrometer analysis. The study also presents a novel design for the nonarticulated foot that was produced with SOLIDWORKS and put through ANSYS analysis. Three types of feet are produced using PLA, PLA/marble and carbon-covered PLA/marble materials. Furthermore, the manufactured prosthetic foot undergoes testing for dorsiflexion and fatigue.

The findings reveal that the newly designed prosthetic foot using carbon fiber-covered PLA/marble material surpasses the PLA and PLA/marble foot in terms of performance, cost-effectiveness and weight.

To the best of the author’s knowledge, this is the first study to use composite filaments not previously used, such as PLA/wood, PLA/carbon fiber and PLA/marble, to design and produce a new prosthetic foot with a longer lifespan, improved dorsiflexion, greater stability and enhanced comfort for the patient. Beside the experimental work, a numerical technique specifically the finite element method, is used to assess the mechanical behavior of the newly designed foot structure.

This study aims to add to the growing literature on the trade–finance nexus by exploring the interplay between a country's level of financial development, the external finance dependence of firms and their exporting decisions.

The study first develops a theoretical model to motivate the idea that a firm's liquidity (financial) position and its home country's level of financial development act as substitute factors in its export market entry decisions. It then empirically tests whether an improvement in a country's financial development level enhances the number of entrants in the foreign markets and boosts the exports of incumbent exporters using firm-level data of manufacturing firms in India for the period 1993–2020.

Empirical results suggest that a higher level of financial development helps increase the exporting probability of firms that rely more on external finance for their operations. Further, the study finds that the sunk costs-induced hysteresis effect plays a major role in firms' exporting decisions and financial factors don't play a significant role in the exporting activities of incumbent exporters.

The findings suggest that a well-developed financial market is necessary to help more and more firms initiate their foreign market operations. The results underscore that trade-liberalisation measures alone may not increase India's exports and the government must complement them with financial sector reforms.

Studies highlighting the role of financial sector development in helping financially-constrained Indian firms overcome the entry barriers associated with exporting are extremely limited. This study contributes to this nascent literature by conducting an empirical investigation on an extensive database of Indian manufacturing firms. Moreover, in contrast to the previous firm-level studies in this area, this empirical analysis uses the actual values of external finance raised by the firms as a critical factor in determining their extensive and intensive margin of exports instead of the usual balance sheet variables such as liquidity and leverage.

The purpose of this paper is to examine the impact of compulsory presence of female members due to gender quota on corporate boards on firms’ credit ratings.

We investigate the impact of female directorial appointment on a firm’s credit rating using firm-level panel data in a regression framework with industry- and year-fixed effects to account for unobserved heterogeneity. Further, to address endogeneity, we employ the difference-in-differences (DiD) technique by exploiting the changes in the corporate board composition induced by the exogeneous gender quota regulation. We also employ the Oster (2019) approach to test for omitted variable bias.

In this paper, we find that the firms that appoint female members on corporate boards post-gender quota mandate (treatment firms) enjoy improved credit ratings as compared to firms that had female members on corporate boards before the gender quota mandate (control group firms) became effective. The findings are robust to alternate definitions of credit rating, treatment and post variables.

We employ an alternative econometric technique, such as Oster’s (2019) specification, to show that the involvement of female directors on corporate boards helps firms in improving firm’s credit ratings. We also identify corporate risk measured using stock return volatility and cash flow volatility as the potential channels through which female directors’ involvement on corporate boards leads to the improvement in firms’ credit ratings.

This paper aims to find the effective 3D printing process parameters based on mechanical characteristics such as tensile strength and hardness of poly lactic acid (PLA)/carbon fibre composites (CF-PLA) by implementing intelligent frameworks.

The experiment trials are conducted based on design of experiments (DoE) using Taguchi L9 orthogonal array with three factors (speed, infill % and pattern type) and three levels. The factors have been optimized by solving the regression equation which is obtained from analysis of variance (ANOVA). The contour plots are generated by response surface methodology (RSM). The influencing parameters are found by using Box–Behnken design. The second order response surface model demonstrated the optimal combination of input parameters for higher tensile strength and hardness.

The influencing parameters are found by using Box–Behnken design. The second order response surface model demonstrated the optimal combination of input parameters for higher tensile strength and hardness. The results obtained from RSM are also confirmed by implementing the machine learning classifiers, such as logistic regression, ridge classifier, random forest, K nearest neighbour and support vector classifier (SVC). The results show that the SVC can predict the optimized process parameters with an accuracy of 95.65%.

3D printing parameters which are considered in this work such as pattern types for PLA/CF-PLA composites based on intelligent frameworks has not been attempted previously.

This study aims to evaluate the information behavior of the Banarasi Sarees weaving community and propose an information-focused policy tailored to their needs.

This study was conducted in seven weaver-centered areas in Varanasi and was designed around semi-structured interviews to explore various information-related aspects among the weavers. It aims to focus on their knowledge of weaving, their information needs, seeking behavior, preferred communication channels, prioritization of information and methods for enhancing information-related situations.

It was found that a lack of information among weavers significantly impacts their livelihoods and businesses. They struggle to make product, pricing and marketing decisions without access to accurate, timely and relevant information. They cannot expand their businesses and invest in new equipment and materials. The weavers need a library with a specialized collection and a qualified librarian to guide them in using the information sources. They also need a dedicated information system and community information centers to provide better information services.

This study is a work whose expected results and findings would help policymakers adopt measures to encourage providing information services through public libraries and community information centers. The results of this study may be further used to frame information policy for weavers and other occupational communities.

The construction industry has an intricate and constantly evolving supply chain (SC) that includes multiple stakeholders and processes. Enhancing SC resilience (SCR) is essential for promoting industry expansion and competitiveness. The SCR has attracted considerable interest because of the increasing worldwide challenges and threats facing SCs. This study introduces a conceptual framework for recognizing and classifying resilient supply chains’ critical success factors (CSFs) in sustainable construction.

This research employs a sequential mixed-methods approach, combining qualitative and quantitative analyses. Initially, an extensive literature review and expert consultations were conducted to identify potential CSFs. The fuzzy decision-making trial and evaluation laboratory (DEMATEL) method was then applied to classify these CSFs into cause-and-effect groups. To further analyse the interrelationships among the CSFs, interpretive structural modelling (ISM) was utilised, establishing a hierarchical framework. This integrated methodology provides a comprehensive understanding of the CSFs’ relative importance and their driving and dependence power, facilitating targeted interventions for enhancing supply chain resilience in the construction sector.

This integrated methodology establishes a hierarchical ranking of CSFs across five levels by revealing their causal interrelationships. The study addresses crucial SCR issues and provides actionable insights. The 17 finalized CSFs have 12 causal and five effect factors. The “safety measures and guidelines” have the highest driving potential, whereas the “availability of standardized materials/equipment” and “skilled human resources” depend highly on causal CSFs. The findings will offer a detailed perspective to narrow the gap between unsustainability and sustainability by enhancing the resilience of CSC.

It offers a pragmatic framework for allocating resources and efforts to enhance the resilience of construction supply chains (CSCs). Policymakers can also use this study to create a more resilient SC for sustainable construction.

This study uniquely identifies and evaluates CSFs for SCR in the construction industry, providing a novel analysis of their driving power, dependence power and ranking. No previous studies have demonstrated such a comprehensive evaluation.

Due to dynamic work contexts, mid-level managers struggle to advance their careers in contemporary organisations. Literature has consistently showcased that leadership style and gender significantly impact subordinates’ career and work-related outcomes. This study investigates the relationship between authentic leadership, gender, perceived career barriers and occupational well-being.

Using self-report questionnaires, we collected data from 198 mid-level managers employed in the information technology (IT) sector in Delhi-NCR. We tested two mediation models simultaneously, investigating the mediation of perceived career barriers on occupational well-being. Authentic leadership and gender were the predictors of the first and second models, respectively.

Authentic leadership was positively associated with occupational well-being but negatively with perceived career barriers. Perceived career barriers partially mediated the link between authentic leadership and occupational well-being. Gender had a significant impact on perceived career barriers. Finally, perceived career barriers fully mediated the association between gender and occupational well-being.

The study showed that perceived career barriers were predicted by authentic leadership perception. In the face of career-related obstacles, managers with authentic leaders tend to have better well-being at the workplace. Further, perceived career barriers are essential in the relationship between gender and occupational well-being. However, the context of India’s IT sector is unique; therefore, caution must be practised when generalising.

Organisations must promote authentic leadership at the upper echelons. Such a leadership style helps reduce the hurdles for managers and improves their well-being. Furthermore, addressing gender-specific career barriers, such as lack of cultural fit, is the key to enhancing female managers’ well-being.

We turned towards positive psychology and utilised the construct of authentic leadership to address the issues of career barriers and diversity in IT organisations.

Motivated by the evidence highlighting the role of sentiments and cognitive biases in investors' decision-making, this study examines a novel behavioral finance-based asset pricing model incorporating the prospect theory framework in the Indian equity market. Specifically, the study’s primary objective is to investigate the importance of Prospect Theory Value (PTV) in the cross-sectional pricing of stocks.

The empirical findings rely on data taken from NIFTY 500 and BSE S&P 500 stocks, encompassing daily, weekly and monthly observations. The analysis employs diverse statistical techniques, including Ordinary Least Squares (OLS), Fama–Macbeth Cross-section Regressions, Panel Fixed Effect and Quantile Regression.

The study demonstrates an asymmetric association between PTV and subsequent stock returns. The findings maintain their robustness even when factoring in stock-specific attributes such as market capitalization and book-to-market ratio, market beta and indicators related to lottery-like behavior such as skewness and MAX. This observed pattern persists when analyzing data at various frequencies, including daily, weekly and monthly intervals. Loss aversion behavior dominates among Indian equity investors, contrary to lottery preferences in the US equity market.

As far as the authors are aware, the study is the first to introduce a new behavioral finance-motivated stock return predictor (PTV) in the Indian stock market. The study also marks the pioneering use of a novel method that evaluates the predictability of PTV across various sections of the conditional return distribution using quantile regression.

The aim of this paper is to review the literature on the prediction of cutting tool life. Tool life is typically estimated by predicting the time to reach the threshold flank wear width. The cutting tool is a crucial component in any machining process, and its failure affects the manufacturing process adversely. The prediction of cutting tool life by considering several factors that affect tool life is crucial to managing quality, cost, availability and waste in machining processes.

This study has undertaken the critical analysis and summarisation of various techniques used in the literature for predicting the life or remaining useful life (RUL) of the cutting tool through monitoring the tool wear, primarily flank wear. The experimental setups that comprise diversified machining processes, including turning, milling, drilling, boring and slotting, are covered in this review.

Cutting tool life is a stochastic variable. Tool failure depends on various factors, including the type and material of the cutting tool, work material, cutting conditions and machine tool. Thus, the life of the cutting tool for a particular experimental setup must be modelled by considering the cutting parameters.

This submission discusses tool life prediction comprehensively, from monitoring tool wear, primarily flank wear, to modelling tool life, and this type of comprehensive review on cutting tool life prediction has not been reported in the literature till now. The future suggestions provided in this review are expected to provide avenues to solve the unexplored challenges in this field.

The empirical studies of the options market efficiency have reported contradictory results, which sometimes confuse practitioners and academicians. The aim of this study was to clarify several aspects of options market efficiency by exploring the answers to two main questions: Under what conditions is the options market more efficient? Are the discrepancies in the estimated efficiency due to the reality of efficiency or mismeasurement?

Using a meta-analysis approach, 54 studies have been analyzed, which included 1,315 tests. The sum of the observations for all of the tests is 3.7 m observation sets. The effect size (type r) has been used to compare the different statistics in different studies. The cumulative effect size and its diversification have been calculated by the random effects model and Q statistic, respectively.

The most interesting finding of the study was that the options market, in all circumstances, is significantly inefficient. Another important finding was that the heterogeneity of options market efficiency is due to the complexity of pricing relations, test time, violation index and price type. To overcome this heterogeneity and accuracy, future studies should test the no-arbitrage options pricing relations at different times and by different price types, using complex and simple pricing relations and either mean violation or violation ratio efficiency measures.

Public disagreement about the options market efficiency in past studies means that this variable is heterogeneous in different conditions. As a significant contribution, this study develops the literature by proposing the causes of options market efficiency heterogeneity.