Search Results (12,554)

Truck drivers experience an elevated risk of being involved in a fatigue-related crash or incident. In Australia, approximately one third of fatal truck crashes are fatigue-related. Various contextual factors are known to increase truck crash risk, including long working hours, irregular schedules, delays while loading and unloading and limited access to suitable rest areas. Studies investigating personal factors affecting Australian truck drivers’ attitudes and compliance with fatigue-management requirements, however, are lacking. Semi-structured interviews were conducted with Australian truck drivers and transport managers (N = 44) to determine how personal and contextual factors influence their intention to comply with fatigue regulation. The findings indicate that personal factors such as familial pressure, financial viability as well as inflexible enforcement and its personal consequences may influence fatigue-related health risks and compliance behaviours. This includes contextual factors such as work scheduling, training and new risk monitoring technologies. It is argued that government, transport industry peak bodies, managers, unions and truck drivers should work together to co-develop fatigue management strategies that account for personal factors likely to influence truck drivers’ intentions regarding fatigue compliance. This will support them to engage in safer and healthier fatigue management practices. Full article

In the era of digital economy, computing power centers, serving as core infrastructure that aggregates computing resources and supports digital transformation, have seen their competitiveness formation mechanism and evaluation methods become important research directions in the field of economics and management. Breaking away from fragmented analyses, this study, based on a complex systems perspective, dissects the formation mechanism of computing power center competitiveness and extracts key influencing factors. Utilizing the entropy weight-TOPSIS-gray correlation method, a fully quantifiable evaluation system for computing power center competitiveness is developed, effectively enhancing the practicality, reusability, and comparability of the evaluation approach. Through an empirical analysis of 35 computing power centers in China, the research found that computing power is the primary influencing factor of competitiveness and pointed out that due to different resource advantages, there are also significant differences in the competitiveness level and development path of computing power centers. Based on these findings, and centered on the dual-wheel drive of technology and cost, four development pathways for computing power centers are proposed: strengthening technological advantages, optimizing cost structures, implementing targeted government policies, and fostering industrial ecosystem synergy. This provides a methodological framework and policy toolkit for enhancing the competitiveness and achieving sustainable development of computing power centers in various countries and regions. Full article

This study examines the adoption and implementation of the Zero Trust (ZT) cybersecurity paradigm using the Technology–Organization–Environment (TOE) framework. While ZT is gaining traction as a security model, many organizations struggle to align strategic intent with effective implementation. We adopted a sequential mixed-methods design combining 27 semi-structured interviews with cybersecurity professionals and a survey of 267 experts across industries. The qualitative phase used an inductive approach to identify organizational challenges, whereas the quantitative phase employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the hypothesized relationships. Results show that information security culture and investment significantly influence both strategic alignment and the technical implementation of ZT. Implementation acted as an intermediary mechanism through which these organizational factors affected governance and compliance outcomes. Strategic commitment alone was insufficient to drive effective implementation without strong cultural support. Qualitative insights underscored the importance of leadership engagement, cross-functional collaboration, and legacy infrastructure readiness in shaping outcomes. The findings emphasize the need for cultural alignment, targeted investments, and process maturity to ensure successful ZT adoption. Organizations can leverage these insights to prioritize resources, strengthen governance, and reduce implementation friction. This research is among the first to empirically investigate ZT implementation through the TOE lens. It contributes to cybersecurity management literature by integrating strategic, cultural, and operational dimensions of ZT adoption and offers practical guidance for decision-makers seeking to institutionalize Zero Trust principles. Full article

The coastline is a constantly evolving boundary between land and sea, shaped by natural forces and human activities. Given its significant ecological and economic value, this zone faces increasing pressures, highlighting the need for continuous monitoring and improved understanding to support sustainable management. This study analyses the spatial and temporal changes along the Al Qunfudhah coastline from 1984 to 2020. Using a combination of multi-temporal Landsat satellite images and geographic information system tools—specifically the digital shoreline analysis system—the research tracks changes over time. Shoreline positions were accurately extracted using automated methods, particularly the Canny edge detection algorithm. Over the 36-year period, analysis using the linear regression rate (LRR) and end point rate (EPR) methods revealed a general pattern of slight shoreline advancement. The highest rates of accretion were recorded at 12.43 m/year (LRR) and 13.36 m/year (EPR), with average rates of 3.63 m/year and 4.17 m/year, especially in the northern region where a corniche road was developed along the coast. Conversely, the most significant erosion occurred near the boat port, with maximum rates reaching −24.4 m/year (LRR) and −20.9 m/year (EPR) and average rates of −1.23 m/year and −1.08 m/year. These results offer valuable insights into the factors driving coastal changes and provide a scientific foundation for making informed, sustainable decisions about the future of the Al Qunfudhah coastline. Full article

Under the global goals of carbon peaking and carbon neutrality, China’s northern agro-pastoral ecotone—an ecologically fragile transition zone with drastic land use/cover change (LUCC)—is characterized by a lack of in-depth understanding of its “land use conflict–carbon sink response” mechanism, which is essential for regional land optimization and carbon neutrality. This study quantified the spatiotemporal dynamics of carbon storage in the zone from 2000 to 2020 using the InVEST model and identified key driving factors by combining the XGBoost model (R² = 0.73–0.88) with the SHAP framework. The results showed that regional total carbon storage increased by 30.11 × 10⁶ tons (a net growth of 0.57%), mainly driven by forest carbon sinks (+65.74 × 10⁶ tons, accounting for 218.3% of the total increase), while cropland and grassland underwent continuous carbon loss (−53.87 × 10⁶ tons and −35.80 × 10⁶ tons, respectively). Spatially, this presents a pattern of “high-value agglomeration in the central–southern region and low-value fragmentation at urban–rural edges”. The Normalized Difference Vegetation Index (NDVI) was the primary driver (average SHAP value: 426.15–718.91), with its interacting temperature factor evolving from air temperature (2000) to nighttime surface temperature (2020). This study reveals the coupling mechanism of “vegetation restoration–microenvironment regulation–carbon sink gain” driven by the Grain for Green Program, providing empirical support for land use optimization and carbon neutrality in agro-pastoral areas. Full article

Ecosystem service value (ESV) is a critical indicator of regional ecological well-being. Assessing and forecasting ESV are essential for achieving the coordinated development of environmental and economic systems. This study employs the SD-PLUS model, integrating Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) to assess the spatiotemporal dynamics of land use and land cover change (LUCC), as well as ESV in Zhengzhou from 2030 to 2040. It analyses the impact of various driving factors on ESV and examines the spatial correlations among ecosystem services across different regions. The results indicate that the total ESV is expected to decrease by 73.53 × 10⁷ yuan, primarily due to significant reductions in cropland and water areas. By 2040, ESV is projected to increase by 14.51 × 10⁷ yuan under the SSP126 scenario, decrease by 73.18 × 10⁷ yuan under the SSP585 scenario, and show a moderate decline under the SSP245 scenario. Climate factors, transportation location, and topographical features have a significantly positive impact on ESV, while environmental and socioeconomic factors exert a negative influence. The analysis of interrelationships among ecosystem services shows that synergies dominate, especially between supporting and cultural services, with only localised trade-offs observed. These findings contribute valuable insights for the development of scientifically sound, well-reasoned, and efficient strategies for ecological conservation and sustainable development. Full article

To address the issues of high labor intensity, high missed harvest rates, and high damage rates associated with traditional subsurface crop harvesters, this paper takes carrots as the research object and designs an automatic row-following device based on collaborative perception and intelligent control. Firstly, the physical characteristic parameters and planting agronomic requirements of carrots in a harvest period were systematically measured and analyzed, and a collaborative control architecture with ‘lateral row-following and longitudinal profiling’ as the core was established. The architecture was composed of a lateral detection mechanism and a ridge surface floating detection mechanism. Building on this, this paper designed a control system with a STC12C5A60S2 single-chip microcomputer as the control core and a fusion fuzzy PID algorithm. By collaboratively driving the lateral and vertical stepper motors, the system achieved a precise control of the digging device’s position and posture, significantly improving the response speed and control stability under complex ridge conditions. Through the simulation of SolidWorks (2019) and RecurDyn (2023), the structural reliability and dynamic profiling effect of key components were validated from both static and dynamic perspectives, respectively. The parameter optimization results based on the response surface method show that the lateral motor speed and the forward speed are the dominant factors affecting the lateral accuracy and the vertical accuracy, respectively. Under the optimal parameter combination, the mean lateral deviation of the device measured in the field test was 1.118 cm, and the standard deviation was 0.257 cm. The mean vertical deviation is 0.986 cm, and the standard deviation is 0.016 cm. This study provides a feasible technical solution for the mechanized agronomic operation of carrots and other subsurface crops. Full article

Land use change is closely related to land surface temperature (LST). Based on remote sensing data from 2001 to 2020, this study analyzed the spatiotemporal variations and driving mechanisms of daytime and nighttime LST in the Urumqi Metropolitan Area (UMA) by combining traditional methods with the eXtreme Gradient Boosting (XGBoost)–SHAP coupled model. Although the average LST trend in the region was one of warming, the pixel-level significance analysis indicated that statistically significant warming (p < 0.05) is concentrated mainly in the urban core (2.65% of the area), while the majority of the region (70%) showed a non-significant warming trend. LST displayed significant spatial clustering, with Moran’s I remaining above 0.990, indicating a positive spatial autocorrelation in spatial distribution. With the advancement of urbanization, the proportion of impervious surfaces increased from 0.87% to 1.14%, while wastelands consistently accounted for approximately 50% of the total area. Different land use types showed distinct effects on the urban heat island (UHI) phenomenon: water bodies, grasslands, and forests played cooling roles, whereas barren land and impervious areas were the main heat contributors. The XGBoost-SHAP analysis further revealed that the importance ranking of driving factors has evolved over time. Among these factors, Elevation dominates, while the influence of population-related factors increased significantly in 2020. This study provides a scientific basis for regulating the thermal environment of cities in arid regions from the perspective of land use. This study provides a scientific basis for regulating the thermal environment of arid-region cities from the perspective of land use. Full article

In the fiercely competitive global contracting market, effective knowledge transfer is paramount for the success of international construction projects (ICPs). However, the unique confluence of high cultural distance, temporary team structures, and knowledge hoarding within ICPs creates profound causal complexity, rendering traditional, net-effect analyses insufficient for developing actionable strategies. Existing research broadly identifies influencing factors but fails to delineate the specific, interconnected configurations of interventions necessary to achieve high knowledge transfer effectiveness (KTE) in this high-stakes context. To address this gap, this study analyzes data from 353 practitioners involved in ICPs using fuzzy-set Qualitative Comparative Analysis (fsQCA 3.0), a methodology uniquely suited to unpack complex causal recipes, to determine the combination strategies that drive superior KTE within ICPs. Drawing on a conceptual model validated through expert interviews and historical case analysis, this research examines a range of transfer subjects, relationship, context, and activity conditions. The configurational analysis yields three distinct, yet equally effective, strategic pathways for maximizing KTE: intercultural-driven, learning-driven, and combined-driven configurations. This research produces two significant contributions. Theoretically, it pioneers the use of configurational theory to structure the antecedent framework of knowledge transfer in ICPs, moving beyond single-factor causality. Practically, it furnishes project managers and business leaders with evidence-based strategic blueprints, enabling targeted resource allocation to achieve optimal KTE amidst the inherent complexity of international projects. Full article

The corporate finance field is inherently engaging, with a strong focus on factors influencing various performance indicators. This study analyzes 66 companies from the Information and Technology sector, all part of the Standard and Poor’s 500 index, over a 22-year period from 2003 to 2024. I applied linear, nonlinear, and interaction-variable models to identify the causal relationship between profitability and key influencing factors. The results reveal that firm size, sales growth rate, current ratio, long-term debt to total capital, free cash flow, asset turnover, receivable turnover, number of board meetings, percentage of women on the board, CEO age, audit committee independence, the presence of compensation and nomination committees, and a pandemic dummy variable all had positive effects on performance. In contrast, firm age, dividend payout ratio, effective tax rate, board size, CEO duality, and the presence of a corporate social responsibility committee negatively impacted firm performance. This research also explores corporate governance by evaluating the role of regulations and internal policies designed to promote financial transparency and protect shareholders’ interests. Additionally, it highlights the importance of board independence, the effectiveness of specialized committees, and the role of ethical leadership in driving long-term corporate success. Full article

China’s rapid economic growth since its reform and opening-up has come at the cost of worsening atmospheric pollution. This study investigates the spatiotemporal evolution and driving mechanisms of PM_2.5 concentrations in Shandong province, a key industrial region, during 2014–2023, using comprehensive air quality monitoring, meteorological observations, and socioeconomic datasets. Through spatial analysis and geodetector methods, we identify that (1) The annual PM_2.5 concentration decreases significantly by 50.9%; spatially, heterogeneity is observed with the western urban agglomeration experiencing more severe pollution, while the eastern coastal urban agglomeration exhibits better air quality. (2) Gravity model analysis shows that the centroids of PM_2.5 pollution undergo distinct migration phases. (3) PM_2.5 levels show a distinct seasonal pattern, peaking in winter at a level 143.7% higher than the summer average. (4) The meteorological driving factors are primarily air temperature (r = 0.511) and wind speed (r = −0.487), while the socioeconomic factors are tertiary industry production (r = −0.971), particulate matter emissions (r = 0.956), and sulfur dioxide emissions (r = 0.938). Concurrently, the combined effect of tertiary industry production and PM emissions account for 99.5% of PM_2.5 variability. Notably, we validate an Environmental Kuznets Curve relationship (R² = 0.805) between economic development and air quality improvement, demonstrating that clean production policy integration can reconcile environmental and economic objectives. These findings provide empirical evidence supporting circular economy strategies for air pollution mitigation in industrializing regions. Full article

Take-over time is a critical factor affecting safety. Accurately predicting the take-over time provides a more reliable basis on issuing take-over requests, assessment of take-over risks, and optimization of human–machine interaction modes. Although there has been substantial research on predicting take-over time, there are still shortcomings in personalized prediction (particularly in accounting for individual differences in driving experience, cognitive abilities, and physiological responses). To gain a comprehensive understanding of the characteristics and applicability of take-over time prediction methods, this review covers four aspects: literature search information, factors influencing take-over time, data acquisition and processing methods, and take-over time prediction methods. Through literature search, research hotspots in recent years have been summarized, revealing the main research directions and trends. Key factors influencing take-over time, including driver factors, autonomous driving systems, and driving environments, are discussed. Data preprocessing stages, including data acquisition and processing, are systematically analyzed. The advantages and disadvantages of classical statistical, machine learning, and cognitive architecture models are summarized, and the shortcomings in current research are highlighted (for instance, the limited generalizability of models trained predominantly on simulator data to real-world driving scenarios). By thoroughly summarizing the strengths and weaknesses of existing research, this review explores under-researched areas and future trends, aiming to provide a solid theoretical foundation and innovative research perspectives for optimizing take-over time prediction, thereby promoting the widespread application and efficient development of autonomous driving technology. Full article

Apple represents one of the most economically significant fruit crops worldwide, and the performance of its scion is largely determined by the physiological and genetic characteristics of the rootstock. Despite their superior ecological adaptability and growth-controlling attributes, many dwarfing apple rootstocks exhibit inherently poor rooting competence, which poses a critical limitation to their large-scale clonal propagation and commercial utilization. Adventitious root (AR) formation is a pivotal yet highly intricate developmental process that governs the success of asexual propagation. It is orchestrated by a complex network of hormonal signaling, transcriptional regulation, metabolic reprogramming, and environmental cues. Over the past decade, remarkable advances have elucidated the physiological, biochemical, and molecular frameworks underpinning AR formation in apple rootstocks. This review provides an integrative synthesis of current progress in vegetative propagation techniques—including cutting, layering, and tissue culture—and systematically dissects the endogenous and exogenous factors influencing AR development. Particular emphasis is placed on the regulatory interplay among phytohormones, carbohydrate and nitrogen metabolism, phenolic compounds, transcription factors (such as WUSCHEL-RELATED HOMEOBOX (WOX), LATERAL ORGAN BOUNDARIES DOMAIN (LBD), and RESPONSE FACTOR (ARF families), and epigenetic modulators that collectively coordinate root induction and emergence. Furthermore, emerging insights into multi-omics integration and genotype-specific molecular regulation are discussed as strategic pathways toward enhancing propagation efficiency. Collectively, this review establishes a comprehensive theoretical framework for optimizing the asexual propagation of apple rootstocks and provides critical molecular guidance for breeding novel, easy-to-root genotypes that can drive the sustainable intensification of global apple production. Full article

Species are disappearing worldwide and the expectation is that this will increase in the future. This review summarizes information on the reasons for the global reduction in biodiversity and what might happen in the future. The literature indicates that the most important factors responsible for this are changes in climate and land use. As changes in land use result in the destruction of natural habitats, they are thought to be the prime driver in the future. Climate change is, however, also often cited as a major driving force. To reduce the effect of climate change on the decline in biodiversity, it is important to know, how climate change affects the abundance and distribution of species. A particular emphasis should be placed not only on conserving specific species but also the environment and communities they live in. In addition, there are many other factors that might play a role, e.g., overexploitation, eutrophication and the introduction and spread of invasive non-native species. Full article

Autonomous driving is anticipated to increase safety, efficiency, and accessibility of passenger transportation. Passengers are given freedom in the use of travel time through the potential to conduct non-driving related tasks (NDRTs). However, factors such as trust and motion sickness pose challenges to the widespread adoption of this technology. Human–machine interfaces (HMIs) have shown potential in mitigating motion sickness and fostering trust calibration in autonomous vehicles (AVs), e.g., by visualizing upcoming or current maneuvers of the vehicle. The majority of research on such HMIs relies on the passengers’ attention, preventing uninterrupted NDRT execution and thus impeding the automation’s usefulness. In this paper, we present a visual HMI, providing AV passengers with information about current driving maneuvers through their peripheral fields of view. This method of information transmission is compared to conventional in-vehicle displays and LED strips regarding perceptibility and distraction. In a controlled laboratory setting, N = 34 participants experienced each HMI condition, indicating their perception of the maneuver visualizations using joystick input while either focusing on a fixation cross to measure perceptibility or solving math tasks to measure distraction. The peripheral HMIs caused better maneuver perception (${{\eta }_{\mathrm{p}}}^2=0.12$) and lower distraction (${{\eta }_{\mathrm{g}}}^2=0.16$) from a visual NDRT than the conventional displays. These results yield implications for the design of HMIs for motion sickness mitigation and trust calibration in AVs. Full article