Search Results (901)

Under the dual challenges of global energy crisis and climate change, the building sector, as a major carbon emitter consuming 33% of global primary energy, has seen its energy efficiency optimization become a critical pathway towards achieving carbon neutrality goals. The Window-to-Wall Ratio (WWR), serving as a core parameter in building envelope design, directly influences building energy consumption, with its optimized design playing a decisive role in balancing natural daylighting, ventilation efficiency, and thermal comfort. This study focuses on the traditional One-Seal dwellings (Yikeyin) in Kunming, China, establishing a dynamic wind field-thermal environment coupled analysis framework to investigate the impact mechanism of window dimensions (WWR and aspect ratio) on indoor thermal comfort under natural wind conditions in transitional climate zones. Utilizing the Grasshopper platform integrated with Ladybug, Honeybee, and Butterfly plugins, we developed parametric models incorporating Kunming’s Energy Plus Weather meteorological data. EnergyPlus and OpenFOAM were employed, respectively, for building heat-moisture balance calculations and Computational Fluid Dynamic (CFD) simulations, with particular emphasis on analyzing the effects of varying WWR (0.05–0.20) on temperature-humidity, air velocity, and ventilation efficiency during typical winter and summer weeks. Key findings include, (1) in summer, the baseline scenario with WWR = 0.1 achieves a dynamic thermal-humidity balance (20.89–24.27 °C, 65.35–74.22%) through a “air-permeable but non-ventilative” strategy, though wing rooms show humidity-heat accumulation risks; increasing WWR to 0.15–0.2 enhances ventilation efficiency (2–3 times higher air changes) but causes a 4.5% humidity surge; (2) winter conditions with WWR ≥ 0.15 reduce wing room temperatures to 17.32 °C, approaching cold thresholds, while WWR = 0.05 mitigates heat loss but exacerbates humidity accumulation; (3) a symmetrical layout structurally constrains central ventilation, maintaining main halls air changes below one Air Change per Hour (ACH). The study proposes an optimized WWR range of 0.1–0.15 combined with asymmetric window opening strategies, providing quantitative guidance for validating the scientific value of vernacular architectural wisdom in low-energy design. Full article

Periodontitis, a chronic inflammatory disease, causes alveolar bone loss. Current treatments show limitations in achieving dual antimicrobial and anti-inflammatory effects. We evaluated an emodin-loaded thermoresponsive hydrogel as a local drug delivery system for periodontitis treatment. Emodin itself demonstrated antibacterial activity against Porphyromonas gingivalis, with minimal inhibitory and minimal bactericidal concentrations of 50 μM. It also suppressed mRNA expression of proinflammatory cytokines [tumor necrosis factor alpha, interleukin (IL)-1β, and IL-6] in lipopolysaccharide-stimulated RAW 264.7 cells. The hydrogel, formulated with poloxamers and carboxymethylcellulose, remained in a liquid state at room temperature and formed a gel at 34 °C, providing sustained drug release for 96 h and demonstrating biocompatibility with human periodontal ligament stem cells while exhibiting antibacterial activity against P. gingivalis. In a rat model of periodontitis, the hydrogel significantly reduced alveolar bone loss and inflammatory responses, as confirmed by micro-computed tomography and reverse transcription quantitative polymerase chain reaction of gingival tissue. The dual antimicrobial and anti-inflammatory properties of emodin, combined with its thermoresponsive delivery system, provide advantages over conventional treatments by maintaining therapeutic concentrations in the periodontal pocket while minimizing systemic exposure. This shows the potential of emodin-loaded thermoresponsive hydrogels as effective local delivery systems for periodontitis treatment. Full article

Foraging behavior in hens is an important indicator of animal welfare. It involves both the search for food and exploration of the environment, which provides necessary enrichment. In addition, it has been inversely linked to damaging behaviors such as severe feather pecking. Conventional studies rely on manual observation to investigate foraging location, duration, timing, and frequency. However, this approach is labor-intensive, time-consuming, and subject to human bias. Our study developed computer vision-based methods to automatically detect foraging hens in a cage-free research environment and compared their performance. A cage-free room was divided into four pens, two larger pens measuring 2.9 m × 2.3 m with 30 hens each and two smaller pens measuring 2.3 m × 1.8 m with 18 hens each. Cameras were positioned vertically, 2.75 m above the floor, recording the videos at 15 frames per second. Out of 4886 images, 70% were used for model training, 20% for validation, and 10% for testing. We trained multiple You Only Look Once (YOLO) object detection models from YOLOv9, YOLOv10, and YOLO11 series for 100 epochs each. All the models achieved precision, recall, and mean average precision at 0.5 intersection over union (mAP@0.5) above 75%. YOLOv9c achieved the highest precision (83.9%), YOLO11x achieved the highest recall (86.7%), and YOLO11m achieved the highest mAP@0.5 (89.5%). These results demonstrate the use of computer vision to automatically detect complex poultry behavior, such as foraging, making it more efficient. Full article

In this paper, preliminary gate reliability of p-GaN HEMTs under high positive gate bias is studied. Gate robustness is of great interest both from an academic and industrial point of view; in fact, different tests and models can be explored to estimate the device lifetime, which must meet some minimum product requirements, as specified by international standards (AEC Q101, JESD47, etc.). However, reliability characterizations are usually time-consuming and are performed in parallel on multiple packaged devices. Therefore, it would be useful to have a faster method to screen out weaker gate trials, already on-wafer, before reaching the packaging step. For this purpose, a room-temperature stress procedure is presented and described in detail. Then, this screening test is applied to devices with a reference gate process, and, as a result, high gate leakage degradation is observed. Afterwards, a different process implementing a dielectric layer between p-GaN and gate metal is evaluated, highlighting the improved behavior during the stress test. However, it is also observed that devices with this process suffer from very high drain leakage, and this effect is then studied and understood through TCAD (technology computer-aided design) simulations. Finally, the effect of a surface treatment performed on the p-GaN is analyzed, showing improved gate pre-reliability while maintaining low drain leakage. Full article

With the continuous expansion of data center scales worldwide, the problem of energy consumption has become increasingly prominent. To address the multi-parameter control challenge in environmental temperature regulation for large data center computer rooms, achieve precise control of hot-aisle temperatures in data centers, and reduce energy waste, this paper designs a multi-parameter model-free adaptive control (MMFAC) algorithm suitable for computer room environmental temperatures. The algorithm integrates the model-free adaptive control (MFAC) algorithm with a weight matrix to perform scaling transformations. Considering the large parameter space of the MFAC controller and the dynamic complexity of data center temperature control systems, compact-form dynamic linearization (CFDL) technology and optimization mathematical methods are used to simplify the parameter identification of the pseudo-Jacobian matrices and the calculation of control quantities for the regulation devices. Simulation experiments based on measured data from a data center show that the proposed algorithm can calculate control quantities for equipment such as air conditioners according to real-time environmental parameter measurements and drive each device based on these control quantities. Meanwhile, the algorithm can reduce errors in key parameters by adjusting the weight matrix. Comparative tests with other control algorithms show that the algorithm has faster response in temperature control and smaller control errors, verifying the effectiveness and application prospects of the algorithm in data center temperature control. Full article

Street view imagery has become a vital tool for assessing urban street greenery, with the Green View Index (GVI) serving as the predominant metric. However, while GVI effectively quantifies overall greenery, it fails to capture the nuanced, human-scale experience of urban greenery. This study introduces the Front-Facing Green View Index (FFGVI), a metric designed to reflect the perspective of pedestrians traversing urban streets. The FFGVI computation involves three key steps: (1) calculating azimuths for road points, (2) retrieving front-facing street view images, and (3) applying semantic segmentation to identify green pixels in street view imagery. Building on this, this study proposes the Street Canyon Green View Index (SCGVI), a novel approach for identifying boulevards that evoke perceptions of comfort, spaciousness, and aesthetic quality akin to room-like streetscapes. Applying these indices to a case study in Nanjing, China, this study shows that (1) FFGVI exhibited a strong correlation with GVI (R = 0.88), whereas the association between SCGVI and GVI was marginally weaker (R = 0.78). GVI tends to overestimate perceived greenery due to the influence of lateral views dominated by side-facing vegetation; (2) FFGVI provides a more human-centered perspective, mitigating biases introduced by sampling point locations and obstructions such as large vehicles; and (3) SCGVI effectively identifies prominent boulevards that contribute to a positive urban experience. These findings suggest that FFGVI and SCGVI are valuable metrics for informing urban planning, enhancing urban tourism, and supporting greening strategies at the street level. Full article

The dynamic scheduling optimization of sports facilities faces challenges posed by real-time demand fluctuations and complex interdependencies between facilities. To address the adaptability limitations of traditional centralized approaches, this study proposes a decentralized multi-agent reinforcement learning framework based on graph neural networks (GNNs). Experimental results demonstrate that in a simulated environment comprising 12 heterogeneous sports facilities, the proposed method achieves an operational efficiency of 0.89 ± 0.02, representing a 13% improvement over Centralized PPO, while user satisfaction reaches 0.85 ± 0.03, a 9% enhancement. When confronted with a sudden 30% surge in demand, the system recovers in just 90 steps, 33% faster than centralized methods. The GNN attention mechanism successfully captures critical dependencies between facilities, such as the connection weight of 0.32 ± 0.04 between swimming pools and locker rooms. Computational efficiency tests show that the system maintains real-time decision-making capability within 800 ms even when scaled to 50 facilities. These results verify that the method effectively balances decentralized decision-making with global coordination while maintaining low communication overhead (0.09 ± 0.01), offering a scalable and practical solution for resource management in complex built environments. Full article

1,3-Diphenylisobenzofuran (DPBF) is a widely used fluorescent probe for singlet oxygen (¹O₂) detection in photodynamic applications. In this work, we present an integrated experimental and computational analysis to describe its spectroscopic, photophysical, and reactive properties in ethanol, DMSO, and DMF. UV-Vis and fluorescence measurements across a wide concentration range show well-resolved S₀ → S₁ electronic transition of a π → π* nature with small red shifts in polar aprotic solvents. Fluorescence lifetimes increase slightly with solvent polarity, showing stabilization of the excited state. The 2D PES and Boltzmann populations analysis indicate two co-existing conformers (C_s and C₂), with C_s being slightly more stable at room temperature. TD-DFT calculations have been performed using several density functionals and the 6-311+G(2d,p) basis set to calculate absorption/emission wavelengths, oscillator strengths, transition dipole moments, and radiative lifetimes. Overall, cam-B3LYP and ωB97X-D provided the best agreement with experiments for the photophysical data across all solvents. The photophysical behavior of DPBF upon interaction with ¹O₂ can be explained by a small-barrier, two-step reaction pathway that goes through a zwitterionic intermediate, resulting in the formation of 2,5-endoperoxide. This work explains the photophysical properties and reactivity of DPBF, therefore providing a solid basis for future studies involving singlet oxygen. Full article

Due to the unique physicochemical properties of ammonia fuel, any leakages in the engine room will inevitably endanger ship safety. This study focuses on investigating the diffusion behavior of ammonia fuel within the engine room during ship navigation after leakage, aiming to identify hazardous points and implement measures, such as installing air-blowing and extraction devices, to mitigate the risks. To address potential leakage risks in ammonia-fueled ships, a simplified three-dimensional computational model was developed based on ship design drawings and field investigations. ANSYS Fluent software (2024 R2) was employed to simulate ammonia fuel leakage from pipelines and equipment, analyzing the diffusion patterns of leakage at different locations and evaluating the impact of adding air-blowing and extraction devices on leaked fuel in the engine room. The simulation results demonstrate that leakage at point 3 poses the greatest operational hazard, and ammonia fuel leakage during navigation generates combustible gas mixtures within the explosion limit range around the main engine, severely threatening both vessel safety and crew lives. Installing air-blowing and extraction devices in high-risk areas effectively reduces the explosion limit range of ammonia fuel, with air outlet 3 showing optimal mitigation effectiveness against ammonia fuel leakage during ship transportation. Full article

Introduction: Bioinformatics is a relatively recent multidisciplinary research field continuously offering novel opportunities. Although many researchers are actively working in/with bioinformatics, some research centers still face difficulties in hiring bioinformaticians and establishing the appropriate (first) bioinformatics infrastructures and computational resources. In our research center, we started from scratch and established initial bioinformatics infrastructures for common use and also for the specific case of precision/personalized medicine. Case description: Here, we report a case study reflecting our specific needs and circumstances during the implementation of a novel bioinformatics laboratory. This involved the preparation of rooms, computer networks, computational resources novel designs, and upgrades to existing designs. Moreover, this work involved people from diverse areas and institutions, such as companies, institutional projects, informatics, and technical infrastructures services. Discussion and evaluation: The work resulted in the implementation of four novel designs dedicated to genomic medicine and in the adaptation of two existing designs dedicated to common use located in the dry-lab room. This is not an accurate and objective work, as it often depends on the available computer hardware and the target bioinformatics field(s). The four novel designs offered substantial improvements when compared to the upgraded designs, additionally corroborated by performance evaluations, which resulted in an overall highest performance of the novel designs. Conclusions: We present work that was developed over two years until completion with functioning infrastructure. This project enabled us to learn many novel aspects not only related to redundant disk technologies, but also related to computer networks, hardware, storage-management operating systems, file systems, performance evaluation, and also in the management of services. Moreover, additional equipment will be important to maintain and expand the potential and reliability of the bioinformatics laboratory. We hope that this work can be helpful for other researchers seeking to design their bioinformatics equipment or laboratories. Full article

The growing demands for sanitary regulations in medical facilities, particularly operating rooms, highlight the importance of ensuring high air quality and minimizing airborne hospital-acquired infections. Improperly designed ventilation systems may lead to contamination of up to 90–95% of patients, especially in light of evolving threats, such as COVID-19. This study focuses on enhancing the energy efficiency and performance of air conditioning and ventilation systems for cleanrooms, where air recirculation is not permissible. A novel energy-efficient direct-flow air treatment scheme is proposed, integrating a heat pump system with adjustable thermal output. A computational fluid dynamics CFD model of a clean operating room was developed to assess the impact of inlet air velocity on aerosol particle removal and airflow stabilization time. The model also considers the effect of personnel movement. The results supported optimized air distribution, reducing microbial contamination risks, with less than 10 CFU/m³, and improved thermal performance. The proposed system was evaluated for energy and cost efficiency compared to conventional setups. Findings can inform the design and operation of cleanroom ventilation in surgical environments and other high-tech applications. This research contributes to improving indoor air quality and reducing infection risks while enhancing sustainability in healthcare infrastructure. Full article

The control of ventilation systems is often performed by automatic algorithms which often do not consider the future evolution of the system in its control politics. Digital twins allow system forecasting for a more sophisticated control. This paper explores a novel methodology to create a Machine Learning (ML) model for the predictive control of a ventilation system combining Computational Fluid Dynamics (CFD) with Artificial Intelligence (AI). This predictive model was created to forecast the temperature and humidity evolution of a ventilated room to be implemented in a digital twin for better unsupervised control strategies. To replicate the full range of annual conditions, a series of CFD simulations were configured and executed based on seasonal data collected by sensors positioned inside and outside the room. These simulations generated a dataset used to develop the predictive model, which was based on a Deep Neural Network (DNN) with fully connected layers. The model’s performance was evaluated, yielding final average absolute errors of 0.34 degrees Kelvin for temperature and 2.2 percentage points for relative humidity. The presented results highlight the potential of this methodology to create AI-driven digital twins for the control of room ventilation. Full article

Ammonia is emerging as a promising zero-carbon marine fuel due to its high hydrogen density, low storage pressure, and long-term stability, making it well-suited for supporting sustainable maritime energy systems. However, its adoption introduces serious safety challenges, as its toxic, flammable, and corrosive properties pose greater risks than many other alternative fuels, necessitating rigorous risk assessment and safety management. This study presents a comprehensive investigation of potential ammonia leakage scenarios that may arise during the fuel gas supply process within confined compartments of marine vessels, such as the fuel preparation room and engine room. The simulations were conducted using FLACS-CFD V22.2, a validated computational fluid dynamics tool specialized for flammable gas dispersion and explosion risk analysis in complex geometries. The model enables detailed assessment of gas concentration evolution, toxic exposure zones, and overpressure development under various leakage conditions, providing valuable insights for emergency planning, ventilation design, and structural safety reinforcement in ammonia-fueled ship systems. Prolonged ammonia exposure is driven by three key factors: leakage occurring opposite the main ventilation flow, equipment layout obstructing airflow and causing gas accumulation, and delayed sensor response due to recirculating flow patterns. Simulation results revealed that within 1.675 s of ammonia leakage and ignition, critical impact zones capable of causing fatal injuries or severe structural damage were largely contained within a 10 m radius of the explosion source. However, lower overpressure zones extended much further, with slight damage reaching up to 14.51 m and minor injury risks encompassing the entire fuel preparation room, highlighting a wider threat to crew safety beyond the immediate blast zone. Overall, the study highlights the importance of targeted emergency planning and structural reinforcement to mitigate explosion risks in ammonia-fueled environments. Full article

This article presents a novel off-cloud anchor sharing framework designed to enable seamless device interoperability for Mixed Reality (MR) multi-user and multi-platform applications. The proposed framework enables local storage and synchronization of spatial anchors, offering a robust and autonomous alternative for real-time collaborative experiences. Such anchors are digital reference points tied to specific positions in the physical world that allow virtual content in MR applications to remain accurately aligned to the real environment, thus being an essential tool for building collaborative MR experiences. This anchor synchronization system takes advantage of the use of local anchor storage to optimize the sharing process and to exchange the anchors only when necessary. The framework integrates Unity, Mirror and Mixed Reality Toolkit (MRTK) to support seamless interoperability between Microsoft HoloLens 2 devices and desktop computers, with the addition of external IoT interaction. As a proof of concept, a collaborative multiplayer game was developed to illustrate the multi-platform and anchor sharing capabilities of the proposed system. The experiments were performed in Local Area Network (LAN) and Wide Area Network (WAN) environments, and they highlight the importance of efficient anchor management in large-scale MR environments and demonstrate the effectiveness of the system in handling anchor transmission across varying levels of spatial complexity. Specifically, the obtained results show that the developed framework is able to obtain anchor transmission times that start around 12.7 s for the tested LAN/WAN networks and for small anchor setups, and to roughly 86.02–87.18 s for complex physical scenarios where room-sized anchors are required. Full article

Natural fibre-reinforced composites are becoming increasingly popular due to their affordability, sustainability, and biodegradability. These composites, made from recyclable materials, are suitable for various sustainable energy applications due to their remarkable mechanical properties and life cycle advantages. The biodegradable composite materials are a sustainable alternative for energy applications. This composite construction uses Soric XF (Lantor Composites, Veenendaal, The Netherlands) as the fibre reinforcement core material and jute fibre, an eco-friendly and sustainable substitute for glass fibre reinforcement composite materials, as the outer face sheet obtained from jute bags. The dry fibres are piled as dry loads at various fibre orientation angles, including 0°, 45°, and 90°, and this orientation will be reflected in the composite strength. Vacuum-assisted resin transfer moulding (VARTM) is a technique used to fabricate this material at room temperature. Further, this research focuses on a comparative analysis of experimental and computational results involving composite materials with jute fibre as the outer face sheet and Soric XF as the fibre reinforcement core material. The experimental investigation included tensile ASTM D638-03 and flexural ASTM D790 to evaluate the composite’s mechanical properties and structural integrity under various load conditions. Simultaneously the computational simulations were performed using the ANSYS-Mechanical 2023 R2 to replicate these conditions and predict the composite’s performance. The experimental and simulated data were analysed and compared. This study demonstrates the efficacy of using computational tools to predict the behaviour of natural fibre composites. It underscores the importance of experimental validation for enhancing the reliability of simulation models. The results from the computational study are compared with the experimental results to study the predictive nature of the NFRC material. Full article