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This paper aims to facilitate the research and development of resilient navigation approaches, explore the robustness of adversarial training to different interferences and promote their practical applications in real complex environments.

In this paper, the authors first summarize the real accidents of self-driving cars and develop a set of methods to simulate challenging scenarios by introducing simulated disturbances and attacks into the input sensor data. Then a robust and transferable adversarial training approach is proposed to improve the performance and resilience of current navigation models, followed by a multi-modality fusion-based end-to-end navigation network to demonstrate real-world performance of the methods. In addition, an augmented self-driving simulator with designed evaluation metrics is built to evaluate navigation models.

Synthetical experiments in simulator demonstrate the robustness and transferability of the proposed adversarial training strategy. The simulation function flow can also be used for promoting any robust perception or navigation researches. Then a multi-modality fusion-based navigation framework is proposed as a light-weight model to evaluate the adversarial training method in real-world.

The adversarial training approach provides a transferable and robust enhancement for navigation models both in simulation and real-world.

This research endeavors to assess the influence of financial shared service centers (FSSCs) on the quality of accounting information within China’s A-share listed companies. Using a multi-period difference-in-differences (DID) model, the study aims to empirically examine the correlation between the adoption of FSSCs and the quality of accounting information.

The study uses a robust methodology to evaluate the relationship between FSSCs and accounting information quality (AIQ). Leveraging the established FSSCs within China’s A-share listed companies as the treatment group, this research adopts a multi-period DID model. This approach enables a rigorous empirical examination of the influence exerted by FSSCs on the overall quality of accounting information.

The present study delves into the impact of FSSCs on AIQ and conducts empirical analysis using data from Chinese A-share listed companies between 2004 and 2021. The findings substantiate that: FSSCs significantly bolster the quality of accounting information, a conclusion retained even after robustness tests. Specifically, FSSCs exhibit a positive correlation with the comparability, timeliness and disclosure quality of accounting information while demonstrating no significant influence on relevance, robustness and reliability factors.

First, the analysis primarily rests upon data from Chinese A-share listed companies between 2004 and 2021, potentially constraining the generalizability of findings across diverse contexts. Second, despite controlling for various factors, unobserved variables or external factors not encompassed in the model might influence the relationship between FSSCs and AIQ. Additionally, the study’s reliance solely on quantitative data confines exploration into qualitative aspects that might offer a more comprehensive understanding of FSSCs’ impact on AIQ.

This paper establishes a nuanced connection between FSSC operations and AIQ, furnishing direct empirical evidence for their economic implications and propounding a novel avenue for augmenting AIQ. And, it furnishes guidance for forthcoming FSSC development, accentuating the necessity of harnessing information technology to enhance the relevance, reliability and robustness of accounting information.

Majority of prior empirical studies assessing AIQ have focused on singular indicators, lacking a comprehensive depiction of its overall level. To address this gap, this paper pioneers the construction of a comprehensive index for AIQ, providing a holistic representation of its level. Furthermore, this study stands as the inaugural investigation into the relationship between China’s A-share listed firms’ FSSCs and the quality of accounting information.

Weak repeatability is observed in handcrafted keypoints, leading to tracking failures in visual simultaneous localization and mapping (SLAM) systems under challenging scenarios such as illumination change, rapid rotation and large angle of view variation. In contrast, learning-based keypoints exhibit higher repetition but entail considerable computational costs. This paper proposes an innovative algorithm for keypoint extraction, aiming to strike an equilibrium between precision and efficiency. This paper aims to attain accurate, robust and versatile visual localization in scenes of formidable complexity.

SiLK-SLAM initially refines the cutting-edge learning-based extractor, SiLK, and introduces an innovative postprocessing algorithm for keypoint homogenization and operational efficiency. Furthermore, SiLK-SLAM devises a reliable relocalization strategy called PCPnP, leveraging progressive and consistent sampling, thereby bolstering its robustness.

Empirical evaluations conducted on TUM, KITTI and EuRoC data sets substantiate SiLK-SLAM’s superior localization accuracy compared to ORB-SLAM3 and other methods. Compared to ORB-SLAM3, SiLK-SLAM demonstrates an enhancement in localization accuracy even by 70.99%, 87.20% and 85.27% across the three data sets. The relocalization experiments demonstrate SiLK-SLAM’s capability in producing precise and repeatable keypoints, showcasing its robustness in challenging environments.

The SiLK-SLAM achieves exceedingly elevated localization accuracy and resilience in formidable scenarios, holding paramount importance in enhancing the autonomy of robots navigating intricate environments. Code is available at https://github.com/Pepper-FlavoredChewingGum/SiLK-SLAM.

Over the years, the significance of retrofitting has gained much attention with the unveiling of its different applications, such as energy retrofit and deep retrofit, to enhance the climate-resilience of buildings. However, no single study comprehensively assesses the climate-resilience of retrofitting. The purpose of this study is to address this gap via a systematic literature review.

Quality journal studies were selected using the PRISMA method and analysed manually and using scientometrics. Three dimensions of climate-resilience, such as robustness, withstanding and recovery, were used to evaluate the contribution of retrofit measures for achieving climate-resilient houses across four climate zones: tropical, arid, temperate and cold.

Most passive measures can enhance the robustness of residential buildings but cannot verify for withstanding against immediate shocks and timely recovery. However, some passive measures, such as night-time ventilation, show excellent performance over all four climate zones. Active measures such as heating, ventilation and air conditioning and mechanical ventilation with heat recovery, can ensure climate-resilience in all three dimensions in the short-term but contribute to greenhouse gas emissions, further exacerbating the long-term climate. Integrating renewable energy sources can defeat this issue. Thus, all three retrofit strategies should appropriately be adopted together to achieve climate-resilient houses.

Since the research is limited to secondary data, retrofit measures recommended in this research should be further investigated before application.

This review contributes to the knowledge domain of retrofitting by assessing the contribution of different retrofit measures to climate-resilience.

The growing awareness of climate risks associated with food safety issues has drawn the attention of stakeholders urging the food industry to carry out a sustainable food safety management system (FSMS). This study aims to investigate whether the critical success factors (CSFs) of sustainable FSMS can contribute to achieving climate neutrality, and how the adoption of FSMS 4.0 supported by the Industry Revolution 4.0 (IR 4.0) technologies moderates the impact of the CSFs on achieving climate neutrality.

Survey data from 255 food production firms in China and Vietnam were utilised for the empirical analysis. The research hypotheses were examined using structural equations modelling (SEM) with route analysis and bootstrapping techniques.

The results show that top management support, human resource management, infrastructure and integration appear as the significant CSFs that directly impact food production firms in achieving climate neutrality. Moreover, the results demonstrate that the adoption of FSMS 4.0 integrated with the three components (ecosystems, quality standards and robustness) significantly moderates the impact of the CSFs on achieving climate neutrality with lower inputs in human resources, infrastructure investment, integration and external assistance, and higher inputs in strengthening food safety administration.

This study provides empirical findings that fill the research gap in understanding the relationship between climate neutrality and the CSFs of sustainable FSMS while considering the moderating effects of the FSMS 4.0 components. The results provide theoretical and practical insights into how the food production sector can utilise IR 4.0 to attain sustainable FSMS for achieving climate neutrality.

The purpose of this study is to stabilize the rotating speed of the permanent magnet direct current (PMDC) motor driven by a DC-DC boost converter under mismatched disturbances (i.e.) under varying load circumstances like constant, frictional, fan type, propeller and undefined torques.

This manuscript proposes a higher order sliding mode control to elevate the dynamic behavior of the speed controller and the robustness of the PMDC motor. A second order classical sliding surface and proportional-integral-derivative sliding surface (PIDSS) are designed and compared.

For the boost converter with PMDC motor, both simulation and experimentation are exploited. The prototype is built for an 18 W PMDC motor with field programmable gate arrays. The suggested sliding mode with second order improves the robustness of the arrangement under disturbances with a wide range of control. Both the simulation and experimental setup shows satisfactory results.

According to software-generated mathematical design and experimental findings, PIDSS exhibits excellent performance with respect to settling speed, steady-state error and peak overshoot.

This paper aims to develop a robust navigation enhancement framework to handle one of the most urgent needs for real applications of autonomous vehicles nowadays, as these corner cases act as the most commonly occurred risks in potential self-driving accidents.

In this paper, the main idea is to fully exploit the consistent features among spatio-temporal data and thus detect the anomalies and build residual channels to reconstruct the abnormal information. The authors first develop an anomaly detection algorithm, then followed by a corresponding disturbed information reconstruction network which has strong robustness to address both the nature disturbances and external attacks. Finally, the authors introduce a fully end-to-end resilient navigation performance enhancement framework to improve the driving performance of existing self-driving models under attacks and disturbances.

Comparison results on CARLA platform and real experiments demonstrate strong resilience of the authors’ approach which enhances the navigation performance under disturbances and attacks.

Reliable and resilient navigation performance under various nature disturbances and even external attacks is one of the most urgent needs for real applications of autonomous vehicles nowadays, as these corner cases act as the most commonly occurred risks in potential self-driving accidents. The information reconstruction approach provides a resilient navigation performance enhancement method for existing self-driving models.

We conducted this study to examine the relationship between revenue concentration and a firm's financial leverage. We aimed to analyze whether revenue concentration influences a firm's capital structure decisions and whether this relationship is driven by customer-specific investments or the direct effect of revenue concentration itself. Additionally, we investigated the role of asset redeployability in mediating or moderating the relationship between revenue concentration and financial leverage.

The paper investigates the relationship between revenue concentration and a firm's financial leverage. The results indicate a negative association between revenue concentration and financial leverage. This finding holds across various regression models and is statistically significant. Furthermore, the paper explores the potential role of asset redeployability in explaining the relationship between revenue concentration and financial leverage. The results indicate that even after controlling for asset redeployability, the negative relationship between revenue concentration and leverage remains significant, suggesting that revenue concentration affects capital structure decisions independently of the risks associated with relationship-specific investments. Robustness tests are conducted using a three-stage least squares approach to account for the simultaneity between revenue concentration, asset redeployability and capital structure.

Our findings demonstrate that revenue concentration is negatively associated with financial leverage, even after accounting for asset redeployability. This suggests that revenue concentration affects capital structure decisions independently of the risks associated with customer-specific investments. Furthermore, we performed robustness tests to address potential simultaneity issues between revenue concentration, asset redeployability and capital structure.

The study relies on available data sources, which may have inherent limitations in terms of accuracy, completeness or consistency. The quality of the data used in the analysis could impact the robustness of the findings. Time Period: The study focuses on more recent years, which might limit the ability to compare the findings with studies conducted over different time periods. Historical trends or structural changes that could impact the relationship between revenue concentration and financial leverage might not be fully captured.

Firms with higher revenue concentration tend to have lower financial leverage. Recent years show a negative relationship between profitability and market leverage compared to earlier periods. Revenue concentration has a distinct effect on financial leverage, not fully explained by risks from relationship-specific investments or asset redeployability. Insights for firms in managing capital structure decisions, considering revenue concentration and its implications for leverage.

This research is one of the first papers that investigates the impact of revenue concentration on the capital structure choices of firms. By exploring the relationship between revenue concentration and financial leverage, the study contributes to the existing literature by shedding light on an underexplored area. Thus, this study adds originality to the field by addressing a research gap and contributing to the understanding of the relationship between revenue concentration and capital structure choices.

This study aims to investigate the impact of board skill diversity (BSD) on corporate environmental responsibility (CER). In addition, this study explores the moderating effects of formal regulatory pressure and informal media pressure.

This study uses Chinese high polluting companies as the sample and uses regression analysis. Robustness checks, including instrumental variable regression, Heckman two-stage model and propensity score matching method, are performed to test the robustness of the results.

The findings suggest that BSD significantly improves CER performance. Both formal regulatory pressure and informal media pressure strengthen the positive impact of BSD on CER. Further channel analyses reveal that BSD improves CER performance by promoting corporate proenvironmental behaviors rather than by restricting environmental violations; skill diversity of executive directors has a more significant effect on CER than that of independent directors. Finally, the moderating effect of regulatory pressure is only significant after the implementation of the Environmental Protection Law, and the moderating effect of media pressure mainly concentrates on negative media coverage.

The involvement of directors with more diverse skills is essential to improve corporate proenvironmental behaviors. Companies should select qualified directors with different skills to further improve their performance on environmental protection and sustainable development.

Regulators and standard-setters should develop efficient guidelines on corporate board governance to enhance the positive role of companies in environmental and sustainable development.

This study broadens the research on the determinants of CER by examining the influence of BSD on CER and the moderating roles of various stakeholder pressures, thereby providing a deeper understanding of corporate environmental performance and sustainable development.

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.