Search Results (2,172)

Public green spaces play a critical role in fostering social cohesion in rapidly industrializing cities. However, empirical research on how urban residents in non-Western contexts perceive, evaluate and use these spaces remains limited, particularly in Islamic industrial cities with distinct cultural practices and urban development patterns. This study examines determinants of visitor satisfaction in Coastal Park, Asaluyeh, a rapidly industrializing Persian Gulf city. The city’s industrial character, marked by acute green space scarcity and demographic imbalances due to workforce migration, provides a distinctive context for examining urban park dynamics in Iran’s petrochemical industrial zones. Using structured questionnaires and systematic field observations, we assess factors influencing park satisfaction and the role of the park in facilitating community bonds. Results reveal that vegetation quality shows the strongest association with visitor satisfaction (r = 0.45, p < 0.001), surpassing demographic characteristics in explanatory power. The park predominantly serves group-based activities, with family gatherings representing the dominant form of social interaction, reflecting cultural preferences for communal recreation. Significant disparities emerge across men and women in satisfaction levels and usage patterns. Temporal concentration during weekend evenings is driven by extreme daytime heat, while transportation barriers limit equitable access. Statistical analyses indicate weak correlations between demographic variables and satisfaction, underscoring the primacy of experiential factors in shaping visitor perceptions. The findings provide evidence-based recommendations for culturally sensitive park design in industrial Islamic cities, emphasizing the need for infrastructure, amenities, and improved public transport connectivity to ensure equitable access across diverse demographic groups. Full article

The purpose of this research is to explore the relationships among food healthiness, price fairness, and loyalty in the context of Subway sandwich restaurants. Another objective of this study is to examine the moderating effects of temperature, personalization, and eco-friendly packaging on the relationship between food healthiness and loyalty. To achieve these objectives, an online survey was conducted. Data were analyzed based on 283 valid responses collected from consumers in the U.S. market. The findings indicate that food healthiness positively influences both price fairness and loyalty. In addition, price fairness exerts a positive effect on loyalty. Furthermore, the results empirically confirmed the significant moderating roles of temperature, personalization, and eco-friendly packaging. This research holds significance in that it empirically clarifies the relationships among the six variables through the case of Subway, providing meaningful marketing insights into consumer perceptions and loyalty in the food service industry. Full article

Autonomous driving technology is a core enabler for new energy vehicle industrial upgrading and a critical pillar for achieving sustainable development goals (SDGs), especially sustainable urban mobility, low-carbon transportation, and efficient intelligent transportation systems (ITS). However, unstable nighttime low-light perception severely restricts autonomous driving deployment, hindering sustainable transportation development—rooted in visual feature degradation and cross-modal imbalance that impair 3D object detection (autonomous driving’s core perception technology). To address this and advance sustainable autonomous driving, this paper proposes a Bird’s-Eye View (BEV)-based multi-modal 3D object detection approach tailored for nighttime scenarios, integrating low-light adaptive components while preserving the original BEV pipeline. Without modifying core inference, it enhances low-light robustness and cross-modal fusion stability, ensuring reliable perception for sustainable autonomous driving operation. Extensive experiments on the nuScenes nighttime subset quantify performance via rigorous metrics (NDS, mAP, mATE). Results show the method outperforms BEVFusion with negligible parameter/inference overhead, achieving 1.13% NDS improvement. This validates its effectiveness and provides a sustainable technical tool for autonomous driving perception, promoting new energy vehicle popularization, optimizing urban ITS efficiency, reducing perception-related accidents and carbon emissions, and directly contributing to transportation and socio-economic sustainability. Full article

Seafood products are highly perishable and particularly susceptible to contamination by pathogenic and spoilage microorganisms, including Listeria monocytogenes, Vibrio spp., Salmonella spp., and Escherichia coli. Conventional control strategies in seafood processing and storage largely rely on chemical preservatives and thermal treatments, which may negatively affect sensory quality and increasingly conflict with consumer demand for minimally processed, “clean-label” foods. In this context, bacteriophages, viruses that specifically infect and lyse bacterial hosts, have emerged as natural, targeted, and environmentally sustainable biocontrol agents for food safety applications. This review provides a comprehensive assessment of bacteriophage applications in seafood processing and storage, with particular emphasis on their mechanisms of action, host specificity, and ability to selectively reduce pathogenic bacteria without compromising nutritional or sensory attributes. Recent advances in phage-based technologies, including phage cocktails, immobilized phage systems, and genetically engineered phages, are discussed in relation to their efficacy against major seafood-associated pathogens under both laboratory and industrial conditions. Key challenges limiting large-scale implementation such as phage resistance development, regulatory considerations, stability during processing and storage, and consumer perception are critically evaluated. In addition, the review highlights emerging evidence on the synergistic use of bacteriophages with complementary preservation strategies, including natural antimicrobials and innovative packaging systems. Overall, this review underscores the potential of bacteriophage-based interventions as practical and sustainable tools to enhance seafood safety, extend shelf life, and support modern seafood processing practices aligned with evolving regulatory and consumer expectations. Full article

Simulator-based digital twins are widely used in robotics education and industrial development to accelerate prototyping and enable safe experimentation. However, they often hide implementation details that are essential for understanding, diagnosing, and correcting system failures. This paper introduces a technology-independent model-based design framework that provides students with full visibility of the computational mechanisms underlying robotic controllers while remaining feasible within a 150-h undergraduate course. The approach relies on representing controller behavior using networks of Extended Finite State Machines (EFSMs) and their stacked extension (EFS2M), which unify all abstraction levels of the control architecture—from low-level reactive behaviors to high-level deliberation—under a single formal model. A structured programming template ensures traceable, optimization-free software synthesis, facilitating debugging and enabling self-diagnosis of design flaws. The framework includes real-time synchronized simulation, transparent switching between virtual and physical robots, and a smart data logger that captures meaningful events for model updating and error detection. Integrated into the Intelligent Robots course, the system supports topics such as kinematics, control, perception, and simultaneous localization and mapping (SLAM) while avoiding dependency on specific middleware such as Robot Operating System (ROS) 2. Over three academic years, students reported positive hands-on experiences, strong adaptability to diverse modeling approaches, and consistently high survey ratings reflecting the course’s overall quality. The proposed environment thus offers an effective methodology for teaching end-to-end robot controller design through transparent, simulation-driven digital twins. Full article

This paper presents a comprehensive review of quadruped robots in the construction industry, focusing on their applications, technological capabilities, and integration with digital construction workflows. Quadruped robots have emerged as promising mobile platforms due to their ability to traverse uneven terrain, operate autonomously, and support multimodal sensing, enabling tasks such as site inspection, 3D reality capture, safety monitoring, logistics support, and integration with Building Information Modeling (BIM) and digital-twin systems. Despite these advantages, real-world deployment remains constrained by limitations in battery endurance, payload capacity, communication reliability, perception robustness, and system interoperability. This review synthesizes findings from 20 studies published between 2015 and 2025 and incorporates a quantitative bibliometric analysis using both SciVal and Scopus. While SciVal provides performance-based indicators and global research trends, Scopus offers complementary publication coverage, improving analytical reliability. Unlike general robotics surveys, this review adopts a construction-centric perspective by explicitly linking quadruped robot capabilities to construction engineering objectives under practical site conditions. The findings highlight current application domains, technological gaps, and adoption barriers, and outline future research directions to support the effective integration of quadruped robots into construction practice. This review provides actionable insights for researchers, engineers, and practitioners assessing the readiness and limitations of quadruped robots in construction environments. Full article

The global water crisis and the urgent need to transition toward regenerative economic models position the circular water economy as a strategic pathway for achieving Sustainable Development Goal 6. While technical feasibility and engineering performance of water reuse technologies have been extensively documented, the socio-organisational and institutional factors conditioning their adoption by industrial and urban entities remain poorly understood. This study addresses this knowledge gap by examining how organisational resources, institutional frameworks, and psychosocial factors are associated with implementation outcomes of circular water economy practices. Using partial least squares structural equation modelling (PLS-SEMs) on survey data from 150 organisational decision-makers across three Peruvian regions (Lima, Trujillo, and Cajamarca), we tested a multidimensional theoretical model integrating resource-based view, theory of planned behaviour, and institutional theory. Results reveal that external regulatory pressure (β = 0.345, p < 0.001), institutional framework quality (β = 0.287, p < 0.001), organisational resource availability (β = 0.273, p = 0.001), and pro-environmental organisational culture (β = 0.255, p = 0.013) show significant positive associations with technology implementation. Counterintuitively, individual attitudes exhibited a negative association (β = −0.350, p < 0.001), suggesting that favourable perceptions disconnected from organisational capacity may generate resistance rather than facilitate adoption. Implementation fully mediates all relationships with performance outcomes (R² = 82.3%), confirming its role as a critical bottleneck in the adoption process. These findings provide empirical evidence for prioritising institutional reforms and organisational capacity-building over awareness campaigns in water reuse promotion strategies, particularly in emerging economy contexts characterised by regulatory fragmentation and limited technical capabilities. Full article

Lake Chapala is the main freshwater reservoir in Mexico and faces notable environmental pressure associated with urban, industrial, and agricultural activities, with documented evidence of heavy metal contamination. Thus, the artisanal fishers from Lake Chapala occupy a strategic position for understanding the socio-environmental dynamics of this lacustrine system. The objective of this study was to analyze their perceptions of pollution in Lake Chapala and the health risks associated with heavy metal contamination, with particular emphasis on the consumption of charal (Chirostoma spp.). Based on the results, 70% of fishers agreed that Lake Chapala is polluted, and 50% identified solid waste as the main source of contamination. Regarding water quality, 41% considered that it had not changed in recent years, while 37% perceived that it had deteriorated. With respect to heavy metals, 50% reported being aware of their presence in the lake; however, slightly more than 50% expressed concern about the possibility that charal could be contaminated. Fishers acknowledged the environmental pressure faced by Lake Chapala but prioritized risks based on visibility and their everyday experiences. Incorporating the perceptions of key stakeholders is essential for addressing socio-environmental problems, strengthening environmental communication and public health strategies, and effectively managing this lacustrine system. Full article

Nowadays, sensorless control of permanent magnet synchronous linear motors (PMLSM) is widely utilized in industrial applications due to its inherent cost and spatial advantages. However, existing sensorless control methods for PMLMs face insufficient observation accuracy of states and disturbances and poor variable-speed trajectory tracking. To address these issues, this paper proposes a sensorless control method combining multi-observer coordinated perception and robust adaptive control. Firstly, a sliding mode observer based on an improved saturation switching function is designed, which suppresses current noise with a low-pass filter to achieve unbiased estimation of back electromotive force (EMF). Secondly, an extended state observer with back-EMF as input is constructed to synchronously observe disturbances such as the mover speed, position, and thrust ripple of linear machine. Then, a robust adaptive controller is designed to compensate for system uncertainty via an adaptive law, forming closed-loop control with SVPWM. Compared with the traditional methods, the proposed multi-observer coordinated perception scheme can significantly enhance the observation accuracy of the mover speed, position, and lumped disturbances, and the robust adaptive controller can effectively improve the variable-speed trajectory, tracking performance under system uncertainties. Finally, the simulation results have confirmed the effectiveness of the proposed method in accurately observing and tracking speed and position, providing a feasible solution for high-precision sensorless control of PMLSM. Full article

Municipal solid waste incineration (MSWI) is a typical complex industrial process for achieving sustainable development of the global environment. It implements the “perception-prediction–control” mode based on domain experts by using multimodal information. To harness the complementary value of different modal data, prevent information conflicts or fusion failures caused by misalignment, and ensure the availability of multimodal datasets and the reliability of analytical conclusions, constructing a benchmark operational condition multimodal dataset is essential. The objective of this work was to create a multimodal reference database for the operational status of IMSW processes. Based on the description of the MSWI process and the analysis of the characteristics of the multimodal data, the process data is first preprocessed under different missing scenarios, missing value processing and outlier processing. Then, single-frame images of the flame video are captured on a minute scale, and the missing combustion lines are quantized by using machine vision technology. Finally, the alignment of combustion line quantization (CLQ) values with the minute time scale of process data is achieved through the multimodal time synchronization module. Taking an MSWI power plant in Beijing as the research object, the combustion flame video and process data under the benchmark operating conditions were collected. The hybrid missing value management strategy combining linear interpolation with the LRDT model improved data integrity, and a spatiotemporal aligned multimodal dataset was constructed. The standardized benchmark operating condition multimodal data was obtained to support combustion state analysis during the incineration process, pollutant generation prediction, and process optimization. Therefore, the objectives of ‘reduction, harmlessness, and resource utilization’ of municipal solid waste, addressing land resource shortages, protecting the ecological environment, and promoting the dual carbon goal can be supported. Additionally, data and technical support for environmental and urban sustainable development are provided. Full article

Sorting defective cocoons is a critical procedure in the silk reeling industry to ensure the quality of raw silk products. Currently, this process relies heavily on manual inspection, which is labor-intensive, subjective, and inefficient. While automated sorting based on machine vision offers a promising alternative, existing object detection algorithms struggle to balance accuracy and computational complexity, particularly when detecting tiny surface defects or distinguishing morphologically similar cocoons in dense scenarios. To address these challenges, this paper proposes an efficient silkworm cocoon defect detection model named LMD-YOLO, based on the YOLOv10 architecture. In this model, we introduce three key improvements to enhance feature extraction and multi-scale perception. First, we integrate a Large Separable Kernel Attention (LSKA) module into the C2f structure (C2f-LSKA) of the backbone. This design decomposes large kernels to capture global shape features with minimal computational cost, effectively distinguishing double cocoons from normal ones. Second, we replace standard upsampling with a DySample module in the neck, which utilizes dynamic point sampling to recover fine-grained texture details of tiny defects like surface stains. Third, a Multi-Scale Dilated Attention (MSDA) mechanism is embedded before the detection heads to aggregate semantic information across different scales, improving robustness against background interference. YOLOv10 was selected as the baseline due to its NMS-free characteristic, which mitigates the latency caused by post-processing in high-speed sorting tasks. Evaluations on a self-constructed multi-category dataset indicate that LMD-YOLO surpasses established detectors, including YOLOv8n and Faster R-CNN. Relative to the YOLOv10n baseline, our method improves mAP@0.5 by 3.11%, achieving 94.46%. Notably, Precision and Recall are increased by 3.50% and 2.97%, reaching 89.98% and 93.61%, respectively. With a compact size of 2.68 M parameters and an inference speed of 115 FPS, the proposed model offers a practical trade-off between accuracy and latency for real-time cocoon defect detection. Full article

Objective: This metasynthesis analyzes the current evidence on the perceptions of sexism among video game players (men and women) and the video game industry. Methods: The databases Scopus and ProQuest were used to select 15 qualitative studies in a final analysis. The analysis used the reciprocal translation technique to analyze and interpret the data. Results: Three primary themes emerged: normalized violence in gamer environments (n = 13), strategies to confront sexism/gender harassment (n = 10), and internal ambivalence and tension (n = 10). The results show that female videogame players experience daily hostility due to the fact of being women in an environment of male dominance. This leads to recurring confrontations, which can result in female video game players being questioned in terms of identity and behavior by both themselves and the community. Conclusions: This metasynthesis suggests that sexism in online video game environments is not an isolated phenomenon and directly affects the experience of female video game players. Furthermore, it highlights the importance of further exploring the perceptions and experiences of different groups within gamer communities, in order to make progress towards a more egalitarian and diverse culture. Full article

With the transition from Industry 4.0 to Industry 5.0, human–robot collaborative assembly (HRCA) has progressed from physical copresence to cognitive integration and knowledge sharing. Digital twins (DTs) serve as enabling technologies that connect physical and virtual spaces. Support is provided for dynamic, safe, and human-centered collaboration. This study presents a systematic review of the research progress and practical applications of DT-enabled HRCA. First, conceptual boundaries between HRCA and general human–robot collaboration (HRC) in manufacturing are defined. Core elements of DT-driven state perception, task planning, and constraint modeling are described. Second, four task-allocation paradigms are classified and summarized, including optimization-based, constraint satisfaction-based, data-driven intelligent, and large language model (LLM)-assisted approaches. Applicable scenarios are identified. Third, the effects of collaboration modes and interaction modalities on planning logic are analyzed. Collaboration modes are categorized as parallel, sequential, and tightly coupled. Interaction modalities are grouped into AR-based explicit interaction, implicit intention perception, and multimodal fusion. Fourth, cross-domain application characteristics and engineering bottlenecks are summarized. Target domains include precision assembly, disassembly and remanufacturing, and construction on-site operations. Finally, four core challenges are distilled, including dynamic uncertainty, multi-objective conflicts, human factor adaptation, and system integration. Four future directions are outlined: LLM-enabled adaptive planning, safety–efficiency co-optimization, personalized collaboration, and standardized integration. The proposed technology–application–challenge–outlook framework is intended to provide a theoretical reference and practical guidance for transitioning HRCA from laboratory prototypes to large-scale industrial deployment. Full article

This study provides a comprehensive empirical examination of the factors influencing the adoption of smart technologies in the Serbian hotel industry by integrating structural equation modeling (SEM), mediation and multigroup analyses, and machine-learning-based robustness testing. Grounded in the UTAUT framework, the research investigates how perceptual, organizational, and social determinants shape employees’ Behavioural Intention (BI) and actual Use Behaviour (USE). A key theoretical contribution is the introduction of the construct Perceived Spatial Impact of Technology (PST), which captures employees’ perceptions of how smart technologies transform the architectural concept, spatial organization, aesthetics, and functional logic of hotels. Although UTAUT traditionally focuses on users, neither prior studies nor the present one examine these dynamics from the perspective of architects or designers who create hotel spaces. Thus, the findings serve as an initial step from the user viewpoint, while future research should incorporate expert architectural reasoning to better understand how spatial knowledge and design logic intersect with user perceptions. All core UTAUT constructs significantly predict BI and USE, with Performance Expectancy and BI emerging as the strongest predictors across SEM and Random Forest models. PST exerts a fully mediated effect on USE through BI, and multigroup analysis reveals notable differences across job roles, hotel categories, and age groups. Overall, the results highlight that digital transformation in hospitality is not only technological and organizational, but also fundamentally architectural. Full article

Integrated Project Delivery (IPD) is a collaborative approach proposed to address fragmentation and performance issues in the AEC industry, yet its adoption remains limited. This study examines Brazilian professionals’ perceptions of IPD and identifies the barriers, challenges, and enablers associated with it. Drawing on a survey and a systematic review, the findings indicate that although benefits such as improved collaboration are recognized, concerns about contractual feasibility, shared risks, and organizational readiness persist. Technological aspects are seen as more familiar than contractual or managerial changes, diverging from international empirical evidence, which typically identifies contractual and governance-related challenges as the primary barriers to IPD adoption. The study reveals both shared global challenges and unique Brazilian issues, particularly regarding implementation complexity. Adoption depends more on organizational and contractual preparedness than on technology, informing strategies for introducing collaborative models in emerging markets. Full article