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Stereolithography (SLA) additive manufacturing (AM) technique has enabled the production of inconspicuous and aesthetically pleasing orthodontics that are also hygienic. However, the staircase effect poses a challenge to the application of invisible orthodontics in the dental industry. The purpose of this study is to implement chemical postprocessing technique by using isopropyl alcohol as a solvent to overcome this challenge.

Fifteen experiments were conducted using a D-optimal design to investigate the effect of different concentrations and postprocessing times on the surface roughness, material removal rate (MRR), hardness and cost of SLA dental parts required for creating a clear customized aligner, and a container was constructed for chemical treatment of these parts made from photocurable resin.

The study revealed that the chemical postprocessing technique can significantly improve the surface roughness of dental SLA parts, but improper selection of concentration and time can lead to poor surface roughness. The optimal surface roughness was achieved with a concentration of 90 and a time of 37.5. Moreover, the dental part with the lowest concentration and time (60% and 15 min, respectively) had the lowest MRR and the highest hardness. The part with the highest concentration and time required the greatest budget allocation. Finally, the results of the multiobjective optimization analysis aligned with the experimental data.

This paper sheds light on a previously underestimated aspect, which is the pivotal role of chemical postprocessing in mitigating the adverse impact of stair case effect. This nuanced perspective contributes to the broader discourse on AM methodologies, establishing a novel pathway for advancing the capabilities of SLA in dental application.

Cushioning is a useful material property applicable for a range of applications from medical devices to personal protective equipment. The current ability to apply cushioning in a product context is limited by the appropriateness of available materials, with polyurethane foams being the current gold standard material. The purpose of this study is to investigate additively manufactured flexible printing of scaffold structures as an alternative.

In this study, this study investigates triply periodic minimal surface (TPMS) structures, including Gyroid, Diamond and Schwarz P formed in thermoplastic polyurethane (TPU), as a possible alternative. Each TPMS structure was fabricated using material extrusion additive manufacturing and evaluated to ASTM mechanical testing standard for polymers. This study focuses attention to TPMS structures fabricated for a fixed unit cell size of 10 mm and examine the compressive properties for changes in the scaffold porosity for samples fabricated in TPU with a shore hardness of 63A and 90A.

It was discovered that for increased porosity there was a measured reduction in the load required to deform the scaffold. Additionally, a complex relationship between the shore hardness and the stiffness of a structure. It was highlighted that through the adjustment of porosity, the compressive strength required to deform the scaffolds to a point of densification could be controlled and predicted with high repeatability.

The results indicate the ability to tailor the scaffold design parameters using both 63A and 90A TPU material, to mimic the loading properties of common polyurethane foams. The use of these structures indicates a next generation of tailored cushioning using additive manufacturing techniques by tailoring both geometry and porosity to loading and compressive strengths.

Soft robots are known for their excellent safe interaction ability and promising in surgical applications for their lower risks of damaging the surrounding organs when operating than their rigid counterparts. To explore the potential of soft robots in cardiac surgery, this paper aims to propose an adaptive iterative learning controller for tracking the irregular motion of the beating heart.

In continuous beating heart surgery, providing a relatively stable operating environment for the operator is crucial. It is highly necessary to use position-tracking technology to keep the target and the surgical manipulator as static as possible. To address the position tracking and control challenges associated with dynamic targets, with a focus on tracking the motion of the heart, control design work has been carried out. Considering the lag error introduced by the material properties of the soft surgical robotic arm and system delays, a controller design incorporating iterative learning control with parameter estimation was used for position control. The stability of the controller was analyzed and proven through the construction of a Lyapunov function, taking into account the unique characteristics of the soft robotic system.

The tracking performance of both the proportional-derivative (PD) position controller and the adaptive iterative learning controller are conducted on the simulated heart platform. The results of these two methods are compared and analyzed. The designed adaptive iterative learning control algorithm for position control at the end effector of the soft robotic system has demonstrated improved control precision and stability compared with traditional PD controllers. It exhibits effective compensation for periodic lag caused by system delays and material characteristics.

Tracking the beating heart, which undergoes quasi-periodic and complex motion with varying accelerations, poses a significant challenge even for rigid mechanical arms that can be precisely controlled and makes tracking targets located at the surface of the heart with the soft robot fraught with considerable difficulties. This paper originally proposes an adaptive interactive learning control algorithm to cope with the dynamic object tracking problem. The algorithm has theoretically proved its convergence and experimentally validated its performance at the cable-driven soft robot test bed.

The purpose of this systematic review is to critically analyze pharmaceutical industry case studies on the implementation of Lean 4.0 methodologies to synthesize key lessons, benefits and best practices. The goal is to inform decisions and guide investments in related technologies for enhancing quality, compliance, efficiency and responsiveness across production and supply chain processes.

The article utilized a systematic literature review (SLR) methodology following five phases: formulating research questions, locating relevant articles, selecting and evaluating articles, analyzing and synthesizing findings and reporting results. The SLR aimed to critically analyze pharmaceutical industry case studies on Lean 4.0 implementation to synthesize key lessons, benefits and best practices.

Key findings reveal recurrent efficiency gains, obstacles around legacy system integration and data governance as well as necessary operator training investments alongside technological upgrades. On average, quality assurance reliability improved by over 50%, while inventory waste declined by 57% based on quantified metrics across documented initiatives synthesizing robotics, sensors and analytics.

As a comprehensive literature review, findings depend on available documented implementations within the search period rather than direct case evaluations. Reporting bias may also skew toward more successful accounts.

Synthesized implementation patterns, performance outcomes and concealed pitfalls provide pharmaceutical leaders with an evidence-based reference guide aiding adoption strategy development, resource planning and workforce transitioning crucial for Lean 4.0 assimilation.

This systematic assessment of pharmaceutical Lean 4.0 adoption offers an unprecedented perspective into the real-world issues, dependencies and modifications necessary for successful integration, absent from conceptual projections or isolated case studies alone until now.

The purpose of this study is to shed light on the influence of climate governance on carbon emission disclosure.

This study is based on S&P BSE 500 Indian firms over six years, i.e. from 2016–2017 to 2021–2022. The panel regression has been used to determine the association between climate governance and carbon emission disclosure.

The results of this study suggest that climate governance exerts a significant influence on corporate carbon emission disclosure. Moreover, results corroborate that climate governance elements such as the environment committee, carbon strategy and environment management system are critical contributors to carbon emission disclosure.

This study adds to the emerging literature on climate change, carbon emission disclosure, corporate governance and climate governance.

This work provides valuable insights to corporate managers and policymakers as the study concludes that climate governance enhances firms’ carbon emission disclosure.

Earlier literature has examined the influence of corporate governance on carbon emission disclosure. However, this study extends to the corporate governance literature by providing novel insights into how integrating climate governance elements into corporate governance can influence carbon emission disclosure. Moreover, to the best of the authors’ knowledge, this study is the first to explore the association between climate governance and carbon emission disclosure in the Indian context.

The study aims to examine whether board gender diversity and corporate social responsibility (CSR) affect real earnings management (REM) practices of public companies in Nigeria.

The study analyzes data of public companies for the period of 2011 through 2020. Data on board gender diversity, CSR and REM were collected from audited financial statements.

The empirical findings show that companies with greater diverse board are effective in restraining REM, thus supporting the theoretical framework of the study. Also, the result provides strong evidence of association between CSR performance and REM for policy management decision.

The study is constrained by not considering all public companies in the country. Furthermore, it considered only gender among numerous important board attributes and environmental, social and governance (ESG) among numerous CSR attributes. Hence, future studies should consider other important attributes on REM and important attributes of board diversity and CSR on real earnings management.

To the best of the authors’ knowledge, this study is the first to investigate the relationship between heterogeneous board gender diversity, CSR via ESG and REM in emerging markets such as Nigeria. Therefore, it provides appropriate treatment of CSR with science and technology via EGS viewpoint of organizational operations and behavior of managing earnings. Therefore, developing better policy management for sustainable development

This study seeks to examine the relationship between macroeconomic shock indicators, namely geopolitical risk (GPR), global economic policy uncertainty (GEPU) and financial stress (FS), and returns as well as volatilities on seven carefully selected stock markets in Africa. Specifically, the study intends to unravel the co-movement and interdependence between the respective macroeconomic shock indicators and each of the stock markets under consideration across time and frequency.

This study employed wavelet coherence approach to examine the strength and stability of the relationships across different time scales and frequency components, thereby providing valuable insights into specific periods and frequency ranges where the relationships are particularly pronounced.

The study found that GEPU, Financial Stress (FS) and GPR failed to induce significant influence on African stock market returns in the short term (0–4 months band), but tend to intensify in the long-term band (after 6th month). On the contrary, stock market volatilities exhibited strong coherence and interdependence with GEPU, FSI and GPR in the short-term band.

This study happens to be the first of its kind to comprehensively consider how the aforementioned macro-economic shock indicators impact stock markets returns and volatilities over time and frequency. Further, none of the earlier studies has attempted to examine the relationship between macro-economic shocks, stock returns and volatilities in different crisis periods. This study is the first of its kind in to employ data spanning from May 2007 to April 2023, thereby covering notable crisis periods such as global financial crisis (GFC) and the COVID-19 pandemic episodes.

Climate change has led to a rise in the frequency, intensity and scope of droughts, posing significant implications for businesses. This study examines the impact of local community drought levels on audit pricing. Additionally, it explores the moderating effects of high-tech industries, auditor busyness and the level of local community concern regarding the drought crisis.

This study employs a mixed-methods approach to rigorously test the research hypotheses. The quantitative phase of the study utilizes a sample of 1,278 firm-year observations from Iran’s capital market. For the analysis of the quantitative data, ordinary least squares regression with clustered robust standard errors is used. Additionally, this research supplements its quantitative findings with qualitative evidence obtained through semi-structured interviews with 19 Iranian audit partners.

The results suggest that firms operating in provinces facing severe droughts experience notably higher audit fees. Furthermore, the positive relationship between drought and audit fees is weakened when auditors are busy, local community concern regarding the drought crisis is high or the firm operates within high-tech industries. These findings are supported by a range of robustness checks and qualitative evidence gathered from the field.

This research contributes to the growing literature on climate change by examining the influence of local community drought levels on audit pricing within an Iranian context. Additionally, our study sheds light on how high-tech industries, auditor workload and the level of local community concern regarding the drought crisis moderate the relationship between drought and audit fees. Importantly, our study pioneers in providing mixed-methods evidence of the association between drought severity and audit fees.