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Safety climate plays an important role in the high-risk construction industry. Advances have been made in the understanding of construction safety climate in terms of four interrelated themes, specifically, its definition, measurement, antecedents and consequences. However, knowledge remains fragmented as the studies are scattered, and a systematic review covering these four themes is lacking. To address this research gap, this study aims to perform a systematic literature review of construction safety climate literature regarding the four themes.

Following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) protocol guidelines, 178 eligible articles were obtained. This study provided thematic analysis of the 178 papers to identify what is known and what is not yet fully known regarding the four themes of construction safety climate. This study also conducted a descriptive analysis to identify the influential scholars, keywords, theories and research methods used by the literature, and finally presented an integrative framework directing future research.

The literature has not reached a consensus on the definition and measurement of construction safety climate. While it has identified the impact of safety climate on both behavioral and accident consequences, it has paid less attention to the antecedents and their underlying mechanisms regarding safety climate. Fang D. and Lingard H. are identified as the most influential authors in this field. “Questionnaire” and “safety behavior” are the keywords most closely related to safety climate. Unfortunately, the existing evidence for the causal relationships between safety climate and its antecedents and consequences is weak, as many studies lack clear theoretical substance, use a concurrent research design and focus only on individual-level climate perceptions. Finally, to support the development of construction safety climate around the four themes, potential research directions and research methods supporting them are illustrated.

This review makes contributions by integrating existing construction studies covering its definition, measurement, antecedents and consequences. This review also makes contributions to specific themes: no review exists on the antecedents of construction safety climate, and this review fills that gap; with regard to consequences, the existing reviews focus either on safety outcomes or safety behavior, but this review included both of them and further elaborated the different theories underpinning the relationships between safety climate and them. It is hoped that this systematic review will be helpful to the research community toward developing a nomologic network and promoting knowledge integration with respect to construction safety climate.

Purpose: This chapter identifies performance factors that have the strongest impact on companies’ sustainable outcomes and compares the obtained results across different sectors.

Methodology: About 3,384 observations were gathered from 2015 to 2022 from companies in communication services, energy, financials, real estate, and utilities sectors that comprise the ‘STOXX Global ESG Leaders Select 50’ index. The multiple regression model is constructed with companies’ ESG scores as dependent variables and independent variables representing operational, financial, and market performance.

Findings: Companies that tend to have higher operational and financial performance in the financial sector are more likely to have higher ESG performance. The financial performance results of companies showed the strongest statistically significant relationship with environmental and the weakest with governance scores.

Implications: Results benefit private and institutional investors aiming to create more sustainable portfolios. The obtained results indicate that these investors should focus on companies operating in the financial and energy sectors with higher performance results. Better ROE, ROA, and Tobin’s Q may have a negative impact on sustainable outcomes for companies operating in the real estate and utility sectors.

Limitations: Firstly, not all ESG index providers disclose information about their index constituents. Secondly, within the chosen ‘STOXX Global ESG Leaders Select 50’ index, not all constituents had complete ESG data available on the Bloomberg platform. When selecting the analysis period, it was observed that the accessible ESG data on Bloomberg covers a relatively short time span, only from 2015 onwards.

Future research: A larger number of companies by choosing a more comprehensive available ESG index.

The 6D pose estimation is a crucial branch of robot vision. However, the authors find that due to the failure to make full use of the complementarity of the appearance and geometry information of the object, the failure to deeply explore the contributions of the features from different regions to the pose estimation, and the failure to take advantage of the invariance of the geometric structure of keypoints, the performances of the most existing methods are not satisfactory. This paper aims to design a high-precision 6D pose estimation method based on above insights.

First, a multi-scale cross-attention-based feature fusion module (MCFF) is designed to aggregate the appearance and geometry information by exploring the correlations between appearance features and geometry features in the various regions. Second, the authors build a multi-query regional-attention-based feature differentiation module (MRFD) to learn the contribution of each region to each keypoint. Finally, a geometric enhancement mechanism (GEM) is designed to use structure information to predict keypoints and optimize both pose and keypoints in the inference phase.

Experiments on several benchmarks and real robot show that the proposed method performs better than existing methods. Ablation studies illustrate the effectiveness of each module of the authors’ method.

A high-precision 6D pose estimation method is proposed by studying the relationship between the appearance and geometry from different object parts and the geometric invariance of the keypoints, which is of great significance for various robot applications.

This paper aims to investigate the suppression of end-point vibrations in industrial robot systems that exhibit joint flexibility and are subject to external disturbances.

The real-time position tracking error is effectively decomposed by using feedforward control based on a dynamic model. Various proportional-derivative controllers and adapted versions are used to compute real-time compensation torque for different position tracking errors. This approach aims to simultaneously achieve rapid response and stability in the control system, resulting in reduced end vibration in the industrial robot.

Experiments were conducted in torque compensation on a 6R industrial robot platform. Compared to the dynamic model calculate torque feedforward compensation method, the maximum reduction of the root mean square of the position error of each joint reached 77% and the minimum reduction was 36.2%. This enhancement improves the trajectory tracking accuracy and effectively suppresses the end-effector vibration.

An improved torque feedforward compensation method is proposed and verified. According to the experimental results, the method can effectively suppress vibration and further improve the trajectory tracking accuracy.

The purpose of this study is to value the thermal and hydraulic transport augmentation of turbulent fluid flow within the round-pipe axis fixed by a twisted-staggered concave/convex dimples tape.

This study meets the report’s novel design by axis-inserting a twisted plastic tape with staggered concave/convex dimples of varying diameters (4 and 6 mm) and depths (1, 1.4 and 1.8 mm). Introducing a realizable model integrated with an improved wall function and SIMPLE solving procedure evaluates the thermo-hydraulic transport as Reynolds number is feasible as 5,000, 10,000, 15,000 and 20,000. In addition, using the findings from the present experimental work validates the numerical methodology.

This paper reveals that the staggered concave/convex dimples on the axis-fixed plastic tape can significantly improve thermo-hydraulic transport within this outer-heated tube. Furthermore, the processed dimples can cause flow disturbance, which increases turbulent kinetic energy and accelerates fluid mixing around a twisted plastic tape, resulting in enhanced thermal convection. The six kinds of twisted tapes (C1−C6) result in the thermo-hydraulic performance index (η) of 1.18–1.32 at Re = 5000. Among all the cases, the dimples using 4 mm combined with 6 mm diameter and 1.4 mm height (C4) earn the highest, around 1.40 at Re = 5,000.

The conditions of constant hydraulic-thermal characteristics of working fluid (air), steady Newtonian fluid considered, and the ignored radiative heat transfer and gravity are the research limitations of the numerical simulation.

The given results can benefit from a round tube design of a thermal apparatus axis fixed by a twisted-staggered concave/convex dimples tape to augment the thermo-hydraulic transport.

Staggered concave/convex dimples on the surface of a twisted tape allow for impinging and swirling flow along the tape. These processed dimples can induce flow disturbance, which increases the turbulent kinetic energy and facilitates fluid mixing in a twisted tape. Furthermore, the hybrid-diameter dimples have enough flow channels for fluid separation-reattachment, and the thermo-hydraulic performance index has improved. This paper then presents a helpful passive approach for cooling a thermal device.

This study introduces a new type of platform recommendation about mutual funds and draws on the signaling theory to conduct a quasi-experimental design to investigate how the platform recommendation influences investors’ investment decisions. Moreover, the authors examine the combined effect of star ratings and the platform recommendation on fund flow and test the investment value of recommended funds.

This study implements a quasi-experimental design based on 1,295 mutual funds traded on Alipay’s online platform to test the hypotheses.

The empirical results show that the recommended funds received higher fund flows from investors when the platform recommendation was established. Moreover, a substitution effect between tag recommendation and star ratings on fund flow was identified. We also uncovered that investing in platform-recommended funds can yield significant and higher fund returns for investors than those without platform recommendations.

Our findings shed new insights into the role of platform recommendations in helping fund investors make investment decisions and contribute to the business of online mutual fund transactions by investigating the effect of platform recommendations on fund flow and performance.

Green innovation in human-centric smart manufacturing (HSM-GI) has emerged as a new paradigm in innovation management for Industry 5.0. The evaluation analysis method is crucial for measuring the development progress and guiding continual improvements of HSM-GI. Since this process of HSM-GI can be regarded as complex and interactive, a holistic picture is often required to describe the interrelations of its antecedents and consequences. In this respect, this study aims to construct a causality network indicator system and proposes a synergy evaluation method for HSM-GI.

Firstly, based on the Driver force-State-Response (DSR) causal-effect framework, this study constructs a holistic indicator system to analyze the interactions between environmental and human concerns of HSM-GI. Secondly, owing to the imprecision of human cognition and synergy interaction in the evaluation process, a flexible hesitant fuzzy (HF) superiority-inferiority synergetic evaluation method is presented. This method quantifies the strengths of causal relationships and expresses the incentives and constraints attitudes of humans. Finally, the proposed framework is applied to six HSMs in the electronic technology industry.

The driving force and state of the HSM-GI system exhibit an upward trend, while the response continues to decline due to changing market demands. The order and synergy degree have shown an increasing trend during 2021–2023, particularly significant for BOE and Haier Smart Home. HSM-GI systems with higher scores mostly have functional coordination and a coherent synergy structure.

This study demonstrates the proposed approach’s applicability and assists policymakers in formulating targeted strategies for green innovation systems.

This study aims to investigate the cause of high-order wheel polygonization in a plateau high-speed electric multiple unit (EMU) train.

A series of field tests were conducted to measure the vibration accelerations of the axle box and bogie when the wheels of the EMU train passed through tracks with normal rail roughness after re-profiling. Additionally, the dynamic characteristics of the track, wheelset and bogie were also measured. These measurements provided insights into the mechanisms that lead to wheel polygonization.

The results of the field tests indicate that wheel polygonal wear in the EMU train primarily exhibits 14–16 and 25–27 harmonic orders. The passing frequencies of wheel polygonization were approximately 283–323 Hz and 505–545 Hz, which closely match the dominated frequencies of axle box and bogie vibrations. These findings suggest that the fixed-frequency vibrations originate from the natural modes of the wheelset and bogie, which can be excited by wheel/rail irregularities.

The study provides novel insights into the mechanisms of high-order wheel polygonization in plateau high-speed EMU trains. Futher, the results indicate that operating the EMU train on mixed lines at variable speeds could potentially mitigate high-order polygonal wear, providing practical value for improving the safety, performance and maintenance efficiency of high-speed EMU trains.

This paper proposes a framework for director evaluation in the context of Chinese state-owned enterprises (SOEs), taking into account the influences of traditional and modern Chinese ideologies.

Following the Delphi method, a series of semi-structured interviews were conducted with Chinese SOE directors.

The framework used has been validated by examining seven dimensions of virtue and four dimensions of competence functions in Chinese SOEs. Effective and representative characteristics of each dimension are identified through interviews.

First, through this research, indicators of virtue have been materialized and those of competence have been specified in a broader range. Second, this research provides advice for training of candidate directors whose experience were in private firms before they step in as SOE directors.

In smart cities striving for innovation, development, and prosperity, hydrogen offers a promising path for decarbonization. However, its effective integration into the evolving energy landscape requires understanding regional intricacies and identifying areas for improvement. This chapter examines hydrogen transport from production to utilization, evaluating technologies’ pros, cons, and process equations and using Analytic Hierarchy Process (AHP) as a Multi-Criteria Decision-Making (MCDM) tool to assess these technologies based on multiple criteria. It also explores barriers and opportunities in hydrogen transport within the 21st-century energy transition, providing insights for overcoming challenges. Evaluation criteria for hydrogen transport technologies were ranked by relative importance, with energy efficiency topping the list, followed by energy density, infrastructure requirements, cost, range, and flexibility. Safety, technological maturity, scalability, and compatibility with existing infrastructure received lower weights. Hydrogen transport technologies were categorized into three performance levels: low, medium, and high. Hydrogen tube trailers ranked lowest, while chemical hydrides, hydrail, liquid organic hydrogen carriers, hydrogen pipelines, and hydrogen blending exhibited moderate performance. Compressed hydrogen gas, liquid hydrogen, ammonia carriers, and hydrogen fueling stations demonstrated the highest performance. The proposed framework is crucial for next-gen smart cities, cutting emissions, boosting growth, and speeding up development with a strong hydrogen infrastructure. This makes the region a sustainable tech leader, improving air quality and well-being. Aligned with Gulf Region goals, it is key for smart cities. Policymakers, industries, and researchers can use these insights to overcome barriers and seize hydrogen transport tech opportunities.