Search Results (1,206)

The impact of the built environment on physical and mental health and wellbeing has been evidenced worldwide. Quality and design affect residents’ wellbeing and physical and mental health outcomes. A local authority planning team in London introduced new guidance to improve the quality of amenity space within residential developments. This paper aims to evaluate the early implementation of this guidance using Normalisation Process Theory. A qualitative design was employed using semi-structured interviews (n = 34), with a purposive sample of planning staff, applicants, review panel members and organisers and elected officials. Framework analysis was undertaken. All stakeholders perceived the introduction of the new amenity space guidance positively, but views of the planning officer training that accompanied it were more nuanced. Key factors influencing implementation included attitude towards and understanding of the new guidance, use of common language, workload, number of policy and guidance documents and a lack of a guidance template from the beginning. Further contextual barriers included the need for economic viability for developers and affordable housing in the area. To further embed and sustain implementation, it is recommended that the guidance continues to be used in a flexible manner with ongoing training and focused support for both planning officers and planning applicants. Full article

This study examines how emotional and reflexive processes jointly relate to transfer of learning in workplace training contexts. Drawing on organizational learning theory, it introduces Reflexivity on Emotions (RoE) as a metacognitive capability through which individuals become aware of, critically examine, and respond to their emotional experiences. Integrating RoE, reflexivity on practice, positive affect, and negative affect within a person-centered framework, the study applies Latent Profile Analysis (LPA) to data collected from 609 correctional officer cadets enrolled in a six-month training program. The analysis identified four emotional–reflexive profiles (Generative–Reflexive, Balanced–Reflexive, Detached–Unreflexive, and Inhibited–Unreflexive), which showed different levels of transfer of learning. Notably, the Generative–Reflexive profile, characterized by elevated negative affect alongside strong reflexive resources, was associated with the highest levels of transfer, suggesting that negative emotions are not uniformly associated with poorer learning outcomes. More broadly, the findings indicate that transfer of learning is better understood through emotional–reflexive configurations rather than through isolated factors. The study contributes to organizational learning research by extending reflexivity into the emotional domain and by demonstrating the value of person-centered approaches for understanding individual differences in workplace learning. Practical implications for training design and the development of emotionally reflective learning environments are discussed. Full article

Smart buildings require intelligent and scalable solutions to monitor environmental conditions and manage increasingly complex data streams generated by distributed sensing infrastructures. In this context, the paper presents an edge-enabled Digital Twin framework for smart office environments, integrating real-time data acquisition, distributed intelligence, and machine learning-based analytics. The framework adopts a multi-layer architecture composed of a sensor layer, a cloud-edge intelligence layer, and an interaction layer, aligned with Digital Twin reference models. By enabling low-latency processing at the edge and supporting continuous model lifecycle management through Machine Learning Operations (MLOps) practices, the proposed approach overcomes key limitations of traditional cloud-centric solutions. Autoencoder-based models are deployed across the cloud-edge continuum to perform real-time anomaly detection on time-series sensor data. A prototype has been implemented in a real smart office environment, where heterogeneous environmental data are continuously collected and processed. Experimental results demonstrate effective end-to-end data flow, stable long-term operation, and reliable anomaly detection with low-latency response. The system enables real-time monitoring and data-driven analysis of environmental conditions, improving situational awareness and supporting operational decision-making. These findings confirm the effectiveness of integrating Digital Twin technologies with edge AI and MLOps principles for scalable and efficient smart building monitoring systems. Full article

Conventional full-space heating systems waste massive fossil-derived energy on unoccupied indoor areas and cause uncomfortable “warm head, cold feet” issues against sustainable building targets. To fill this gap and advance low-carbon indoor heating solutions for sustainable office development, this study proposes an innovative localized heating terminal combining radiant panels and downward laminar air supply. An experimental platform was established, with twelve testing cases covering varied supply air velocity, supply air temperature and radiant panel temperature to explore its thermal comfort and energy-saving sustainability performance. Experimental results demonstrate that, under the optimal operating condition (0.55 m/s airflow, 23.5 °C supply air, 36 °C radiant panel), the vertical head–foot temperature difference reduces to merely 1.2 °C, far below the 3–5 °C threshold of conventional heating equipment; the draught rate approaches zero to eliminate cold draft discomfort. Critically, 65–75% of total supplied heat concentrates within human-occupied zones, drastically cutting redundant heat loss and advancing building heating sustainability. The terminal features dual working modes: convection contributes 78.7–94.4% of total heat for rapid warm-up while radiant heat maintains stable long-term comfortable surroundings. Such flexible dual-mode design supports sustainable part-load operation matching intermittent office occupancy, making this terminal a feasible low-carbon option for modern sustainable office buildings prioritizing energy efficiency and a healthy indoor environment. Full article

Students and workers spend much of their day in school and office environments, where poor indoor air quality (IAQ) can negatively affect health and comfort. Indoor vegetation is increasingly proposed as a low-cost nature-based solution (NBS) to improve IAQ. This study evaluated the effects of phytoremediation on IAQ and indoor microclimate in schools across different regions and educational levels, as well as in office environments, under real-world conditions. Several C₃ plants (e.g., Chamaedorea, Schefflera, Ficus, Epipremnum, Yucca, and Spathiphyllum) were used, with crassulacean acid metabolism (CAM) plants (Sansevieria) included in selected settings. Temperature, relative humidity, CO₂, PM_2.5, and PM₁₀ were continuously monitored using intercalibrated low-cost sensors in absence and presence of vegetation. A comparable plant configuration was implemented in offices to assess its effects on volatile organic compounds (VOC). Indoor greenery reduced particulate matter, especially PM10 (18–20%), and improved microclimatic conditions by lowering air temperature (1–2 °C) and increasing relative humidity (6–15%). However, CO₂ reductions were limited and context-dependent. In the tested office environments, plant introduction was associated with reduced total VOC concentrations (25–50%). Overall, our results further support that indoor vegetation constitutes a robust, cost-effective nature-based solution (NBS) capable of complementing conventional ventilation systems in both school and office environments. Full article

Naturally ventilated office spaces present a dual challenge: open windows are sources of thermal comfort and acoustic disturbances. Despite growing interest in adaptive comfort frameworks, the acoustic adaptation effects specific to naturally ventilated indoor environments and the role of biophilic design elements in mediating them remain insufficiently investigated. This study was conducted to examine the influence of audio–biophilic elements in a naturally ventilated space with a green view, with 53 participants recruited from a real, operational open-office space. Under typical open window field noise conditions, four levels of birdsong (45, 49, 52, and 55 dBA) were introduced at the receiver position. The participants’ perceptual responses were measured using the ISO/TS 12913:2019 and ISO/TS 12913:2025, as well as indoor-soundscape scales. Satisfaction, the perceived appropriateness of the conditions for work, and preferences were evaluated. Environmental descriptors, including psychoacoustic and thermal parameters and perceived auditory and visual content, were also recorded. Statistical analyses were conducted using RM-ANOVA, the Friedman test, and post hoc comparisons. The results revealed that audio–biophilic interventions can enhance adaptive acoustic comfort in naturally ventilated spaces. Although the existing ISO and indoor soundscape scales are highly correlated, they are not interchangeable. These findings offer actionable guidance for acoustic designers and facility managers: introducing contextually appropriate birdsong at moderate levels (not exceeding a background noise level of more than 3 dBA) can serve as an effective masking strategy in naturally ventilated open-plan offices without increasing perceived disturbance, supporting the integration of audio–biophilic systems in green building design. This study contributes field-based evidence to the literature on audio–biophilic interventions and their role in adaptive acoustic comfort in naturally ventilated spaces. Full article

Accelerated by the COVID-19 pandemic, organizations have shifted to remote work to transform traditional office conditions and take advantage of the new arrangements. Studies confirm working remotely sustains and boosts performance and satisfaction compared to conventional office states. However, work stress remains a constant concern negatively impacting well-being, engagement, and productivity across both settings. Less explored is how workplace authenticity, shaped by authentic living, accepting external influence, and self-alienation, impacts work stress and performance. We address this research gap by studying how these authenticity dimensions predict work stress across both working-from-home and office work environments and its effect on performance. We used extensive survey data to test the hypothesis implied by these relationships. The findings indicate that work stress is negatively associated with work in both settings. Additionally, accepting external influence and self-alienation may seem to increase work stress, while authentic living reduces it across both contexts. The results of this study provide a cross-context validation rather than strong differentiation between working from home and in office. Organizations should promote authentic living and target self-alienation to attenuate work stress. This is the first study to provide empirical evidence that these dynamics hold in both remote and office work contexts. Full article

The study examines whether corporate green innovation enhances the information content of stock prices among U.S. publicly listed firms from 1997 to 2023. Using green patent data from the United States Patent and Trademark Office, we find that firms engaging in green innovation exhibit significantly lower stock price synchronicity, indicating greater firm-specific information reflected in their prices. This finding is robust to alternative innovation measures, the lead dependent variable, the exclusion of the COVID-19 period, and the propensity score matching with Rosenbaum bounds sensitivity analysis. Exploiting the 2018 America’s Water Infrastructure Act as an exogenous regulatory shock, we find that the informativeness effect is substantially expanded following the shock. Citation-based analyses confirm that higher-quality green patents generate a stronger impact after adjusting for truncation bias. We identify analyst coverage and institutional ownership as two economic mechanisms through which green innovation improves the corporate information environment. Our findings suggest that green innovation represents a valuable source of firm-specific information content with meaningful implications for capital market efficiency. Full article

Private 5G mobile networks are emerging as a platform for wireless connectivity in professional applications across smart industrial sectors such as automated warehousing, logistics, autonomous vehicle deployments in campus environments, mining, and material processing, among others. It is expected that most Machine-to-Machine (M2M) and Industrial Internet of Things (IIoT) communication links will increasingly rely on wireless solutions, as the flexibility they offer provides clear advantages over hard-wired network installations. To gain insight into workers’ exposure to radiofrequency electromagnetic fields (RF EMF) emitted by 5G private mobile networks, an analysis was conducted based on measured and calculated RF EMF levels from various 5G private networks in real-world scenarios across different smart industrial sectors and R&D platforms in three countries. Several exposure scenarios were evaluated, including production facilities, logistics operations, office environments, and research sites. The installations included different configurations: private standalone and non-standalone 5G networks operating at 3.5 GHz and 26 GHz, as well as public networks with private slicing. The results clearly demonstrated that exposure levels in all investigated scenarios were well below existing exposure limits. In a typical indoor industrial environment where pico 5G base stations are deployed, the measured exposure was found to be no greater than 0.006% of the Directive 2013/35/EU action value and 0.03% of the ICNIRP guideline limits for the general public. Full article

Oil Detection Canines (ODCs) have been proven to detect spilled oil in various environments, including targets and residual oil sequestered along shorelines. A limitation within the capability is that an ODC detects and responds to all types of stranded hydrocarbons, including any from historical spills or naturally occurring chronic oils, such as tarballs washed up from offshore seeps. In locations historically known for chronic tar deposits, the value of a K9-supported Shoreline Cleanup Assessment Technique (SCAT) survey is limited when large numbers of tar deposits are present, because the canine detects and responds to all of them. This thoroughness can slow down SCAT surveys, reduce efficiency by requiring investigation of each response, and fatigue the canines from the number of alerts. A project supported by the Texas General Land Office (TGLO) was designed to investigate the ability of a trained ODC to discriminate hydrocarbons on a beach that represent a newly spilled oil while ignoring other potential “background” oils. In 2021, Texas Tech University’s Canine Olfaction Lab conducted a laboratory-based study to investigate canines’ ability to respond to weathered oil samples. This research demonstrated that trained canines could effectively discriminate between weathered oils in a laboratory environment. This knowledge was used to design a field program to conduct monthly surveys with two teams: one involved deploying two canines trained on a sample representative of relatively unweathered spilled oils, handled by citizen-scientist volunteers, and the other involved an ODC trained on a range of oil types. The field survey results show that a Specific Oil Detection Canine (SODC) can discriminate between unweathered oil deposits and other background deposits typical of chronic oiling at the same location. Field surveys indicated that SODCs consistently responded exclusively to target oil samples and disregarded naturally occurring background hydrocarbons, while a generalist ODC responded to all hydrocarbon sources present. Full article

One of the most intensively developed areas of wireless telecommunications in recent years is the practical application of reconfigurable intelligent surfaces (RISs). This paper presents the results of experimental research conducted at 5.5 GHz using a 16 × 16 element RIS to verify the accuracy of the Tang, Zheng, and Jeong theoretical models, which describe signal behavior upon reflection from an RIS. In contrast to purely simulation-based papers, this study utilizes different antenna types in a laboratory environment representative of a typical office space. The performance of the models is evaluated across distances of 1 m, 1.5 m, and 2 m through a comprehensive quantitative analysis. The study reports core error metrics, including mean and median root mean square error (RMSE), mean absolute error (MAE), and sum of squared differences (SSD), as well as the Interquartile Range (IQR) to assess modeling stability. Furthermore, a Wilcoxon signed-rank test is employed to statistically compare the modeling accuracy. Full article

Office openness comprises two physically distinct dimensions—spatial openness and visual openness—yet studies quantifying their independent contributions to cognitive efficiency at the individual level remain scarce. Prior research has predominantly reported group-mean effects, leaving bidirectional individual responses insufficiently examined. This study independently manipulated both dimensions and measured individual-level EEG responses in 24 adults using a 3 × 3 within-subject factorial design. The beta/alpha ratio change rate was computed as an index of cognitive efficiency. Substantial neurophysiological variation across conditions was confirmed in every participant. The absence of significant group-level effects was interpreted not as a lack of environmental influence but as the result of bidirectional individual responses canceling each other out in group averages. Spatial and visual openness induced response ranges of equivalent magnitude at the individual level, and individually optimal conditions were widely distributed across the nine experimental conditions. The correspondence rate between subjective preferences and EEG-identified optimal conditions did not exceed chance, and this bidirectional cancellation mechanism is proposed as an explanation for the contradictory findings that have long characterized open-office research. These results support design strategies that offer diverse combinations of spatial and visual openness within activity-based working environments, paired with feedback systems grounded in objective cognitive performance data. Full article

The post-pandemic evolution of education involving mechatronics and machine learning has shifted the demand for robotic hardware from centralized laboratories to accessible laboratories in home environments. This paper presents a portable three-wheeled holonomic robotic platform designed for remote research and home office experimentation. The proposed system utilizes a modular design and low-cost philosophy comprising a custom embedded control system driven by an ESP32-WROOM microcontroller, which manages a closed-loop PID velocity controller using Hall effect feedback from three DC micromotors. In contrast, external nodes allow the reception, conditioning, and classification of 8-channel surface electromyography (sEMG) data sampled at 500 Hz. To address the non-stationarity and stochastic noise in raw sEMG signals, this study implements a hybrid Deep Learning (DL) architecture that complements 2D Convolutional Neural Networks (CNN) for spatial feature extraction with Long Short-Term Memory (LSTM) networks for temporal context awareness. This model decodes the neuromuscular intent of the user into real-time holonomic velocity vectors, achieving validation accuracies of 80.51% for horizontal movement, 84.86% for vertical translation, and 99.56% for the Fist/no-Fist state. By synthesizing advanced AI-based teleoperation with a portable design, this study establishes a scalable framework for the next generation of “laboratory-at-home” educational tools and research regardless of physical location. Full article

Background/Objectives: Wrist cock-up orthoses are standard for work-related musculoskeletal disorders, yet consensus is lacking on whether commercial orthoses (COs) or custom-made thermoplastic orthoses (THs) better preserve function. While COs offer availability, THs provide a superior anatomical fit. This study evaluated dexterity and satisfaction in healthy female employees to establish a functional baseline for preventive strategies. Methods: Healthy female office workers with no prior musculoskeletal or neurological conditions participated in this randomized cross-over study. Manual dexterity was assessed at baseline and after each of two consecutive workdays, during which participants wore, in a randomized order, either a CO or a TH made by an expert physiotherapist. Outcome measures included the Functional Dexterity Test (FDT), recording time and errors, and the Client Satisfaction with Device (CSD-It) scale. Results: Twenty right-handed women (mean age 45.6 ± 11 years) participated. A significant difference in FDT completion times across conditions (χ² = 12.6, p = 0.002) was found. While both orthoses slowed performance compared to baseline (p < 0.01), the CO allowed for faster dexterity than the TH (p < 0.01). No differences were found in error rates. Regarding satisfaction, the CO achieved significantly better CSD-It scores than the TH (p = 0.0047), despite 60% of users reporting increased skin temperature with the CO. Final preferences were nearly evenly split (55% CO vs. 45% TH). Conclusions: Both orthoses impact manual dexterity without compromising precision. While the CO offered better execution speed and overall satisfaction, the TH version was preferred for prolonged skin tolerability. Selection should be individualized, balancing mechanical efficiency with the superior fit of custom-fabricated solutions in office environments. Full article

Heritage buildings constitute a significant element of the United Kingdom’s (UK) built environment, with 460,000 listed buildings across England, Scotland, Wales and Northern Ireland. These assets present substantial challenges for national decarbonisation due to statutory constraints on fabric alteration and the need to consider whole-life carbon impacts. This study evaluates the impact of conservation-compatible retrofit strategies on the operational energy and carbon performance of Fitzroy House, a Grade II listed late-modern office building in Nottingham. Dynamic building simulation (IES Virtual Environment) was used to assess baseline performance and to develop two retrofit scenarios incorporating improvements to glazing, airtightness, roof insulation, and the introduction of mechanical ventilation with heat recovery (MVHR). Climate resilience was evaluated using future weather files for the 2080s. Results are derived from comparative scenario-based modelling rather than calibrated predictions of absolute performance. Within this framework, the proposed measures can reduce annual heating demand by up to 68%, cooling demand by 60%, and operational carbon emissions by approximately 41% (district heating) to 64% (natural gas), relative to the as-built baseline under the most advanced retrofit scenario. Performance remains broadly robust under future climate scenarios, although cooling loads increase modestly. The findings demonstrate that, while meaningful reductions in operational carbon are achievable, retrofit outcomes are fundamentally shaped by conservation constraints, which act as an interpretive framework defining the limits and possibilities of intervention. However, results should be interpreted as indicative of relative performance improvements rather than fully generalizable or predictive outcomes, and embodied carbon impacts are not included within the scope of this study. The research provides an evidence-based pathway for improving similar late-modern listed office buildings while highlighting the limits imposed by conservation requirements and existing building fabric. Full article