Search Results (394)

In the context of green building development, the lighting design of campus living rooms in hot summer and cold winter areas faces the dual challenges of glare control in summer and insufficient daylight in winter. Based on BIM technology, this study uses Revit 2016 modeling and the HYBPA 2024 performance analysis platform to simulate and optimize the daylighting performance of the campus activity center of Hunan City College in multiple rounds of iterations. It is found that the traditional single large-area external window design leads to uneven lighting in 70% of the area, and the average value of the lighting coefficient is only 2.1%, which is lower than the national standard requirement of 3.3%. Through the introduction of the hybrid system of “side lighting + top light guide”, combined with adjustable inner louver shading, the optimized average value of the lighting coefficient is increased to 4.8%, the uniformity of indoor illuminance is increased from 0.35 to 0.68, the proportion of annual standard sunshine hours (≥300 lx) reaches 68.7%, and the energy consumption of the artificial lighting is reduced by 27.3%. Dynamic simulation shows that the uncomfortable glare index at noon on the summer solstice is reduced from 30.2 to 22.7, which meets the visual comfort requirements. The study confirms that the BIM-driven “static-dynamic” simulation coupling method can effectively address climate adaptability issues. However, it has limitations such as insufficient integration with international healthy building standards, insufficient accuracy of meteorological data, and simplification of indoor dynamic shading factors. Future research can focus on improving meteorological data accuracy, incorporating indoor dynamic factors, and exploring intelligent daylighting systems to deepen and expand the method, promote the integration of cross-standard evaluation systems, and provide a technical pathway for healthy lighting environment design in summer-hot and winter-cold regions. Full article

Federated Clustering (FL clustering) aims to discover latent knowledge in multi-source distributed data through clustering algorithms while preserving data privacy. Federated learning is categorized into horizontal and vertical federated learning based on data partitioning scenarios. Horizontal federated learning is applicable to scenarios with overlapping feature spaces but different sample IDs across parties. Vertical federated learning facilitates cross-institutional feature complementarity, which is particularly suited for scenarios with highly overlapping sample IDs yet significantly divergent features. As a classic clustering algorithm, k-means has seen extensive improvements and applications in horizontal federated learning. However, its application in vertical federated learning remains insufficiently explored, with room for enhancement in privacy protection and communication efficiency. Simultaneously, client feature imbalance may lead to biased clustering results. To improve communication efficiency, this paper introduces Product Quantization (PQ) to compress high-dimensional data into low-dimensional codes by generating local codebooks. Leveraging the inherent k-means algorithm within PQ, local training preserves data structures while overcoming privacy risks associated with traditional PQ methods that require server-side data reconstruction (which may leak data distributions). To enhance privacy without compromising performance, Multidimensional Scaling (MDS) maps codebook cluster centers into distance-preserving indices. Only these indices are uploaded to the server, eliminating the need for data reconstruction. The server executes k-means on the indices to minimize intra-group similarity and maximize inter-group divergence. This scheme retains original codebooks locally for strict privacy protection.The nested application of PQ and MDS significantly reduces communication volume and frequency while effectively alleviating clustering bias caused by client feature dimension imbalance. Validation on the MNIST dataset confirms that the approach maintains k-means clustering performance while meeting federated learning requirements for privacy and efficiency. Full article

The switching characteristics of GaN HEMT devices exhibit a very complex dynamic nonlinear behavior and multi-physics coupling characteristics, and traditional switching current models based on physical mechanisms have significant limitations. This article adopts a hybrid architecture of convolutional neural network and long short-term memory network (CNN-LSTM). In the 1D-CNN layer, the one-dimensional convolutional neural network can automatically learn and extract local transient features of time series data by sliding convolution operations on time series data through its convolution kernel, making these local transient features present a specific form in the local time window. In the double-layer LSTM layer, the neural network model captures the transient characteristics of switch current through the gating mechanism and state transfer. The hybrid architecture of the constructed model has significant advantages in accuracy, with metrics such as root mean square error (RMSE) and mean absolute error (MAE) significantly reduced, compared to traditional switch current models, solving the problem of insufficient accuracy in traditional models. The neural network model has good fitting performance at both room and high temperatures, with an average coefficient close to 1. The new neural network hybrid architecture has short running time and low computational resource consumption, meeting the needs of practical applications. Full article

A novel stainless steel with high Mn and Mo content (much higher than traditional stainless steel), designated CH241SS, was developed as a potential replacement for Cr-Mo-V alloy steel in the cold forging applications of precision industry. Through carbon reduction in an environmentally friendly manner and a two-stage heat treatment process, the hardness of as-cast CH241 was tailored from HRC 37 to HRC 29, thereby meeting the industrial specifications of cold-forged steel (≤HRC 30). X-ray diffraction analysis of the as-cast microstructure revealed the presence of a small amount of ferrite, martensite, austenite, and alloy carbides. After heat treatment, CH241 exhibited a dual-phase microstructure consisting of ferrite and martensite with dispersed Cr(Ni-Mo) alloy carbides. The CH241 alloy demonstrated excellent high-temperature stability. No noticeable softening occurred after 72 h for the second-stage heat treatment. Based on the mechanical and room-temperature tensile fatigue properties of CH241-F (forging material) and CH241-ST (soft-tough heat treatment), it was demonstrated that the CH241 stainless steel was superior to the traditional stainless steel 4xx in terms of strength and fatigue life. Therefore, CH241 stainless steel can be introduced into cold forging and can be used in precision fatigue application. The relevant data include composition design and heat treatment properties. This study is an important milestone in assisting the upgrading of the vehicle and aerospace industries. 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

Under the context of the dual-carbon policy, reducing energy consumption and emissions in automobiles has garnered significant attention, with automotive lightweighting being particularly important. This paper focuses on the lightweight design of automotive subframes, aiming to minimize weight while meeting performance requirements. Research has revealed that the original subframe allows further room for lightweighting and performance optimization. A topology optimization model was established using the Solid Isotropic Material with Penalization (SIMP) method and solved using the Method of Moving Asymptotes (MMA) algorithm. Integration of the SIMP method was achieved on the Abaqus-Matlab (2022x) platform via Python (3.11.0) and Matlab (R2022a) coding, forming an effective optimization framework. The optimization results provided clear load transfer paths, offering a theoretical basis for geometric model conversion. The subframe model was subsequently reconstructed in CATIA. Material redundancy was identified in the reconstructed subframe model, prompting secondary optimization. Multi-objective size optimization was conducted in OptiStruct, reducing the subframe’s mass from 33.73 kg to 17.84 kg, achieving a 47.1% weight reduction. Static stiffness and modal analyses performed in HyperMesh confirmed that results met all relevant standards. Modal testing revealed a minimal deviation of only −2.7% from the simulation results, validating the feasibility and reliability of the optimized design. This research demonstrates that combining topology optimization with size optimization can significantly reduce weight and enhance subframe performance, providing valuable support for future automotive component design. Full article

Agriculture and animal feeding operations are responsible for 87% of ammonia emissions in the UK. Controlling NH₃ concentrations below 20 ppm is crucial to preserve workers’ and livestock’s well-being. Therefore, ammonia control systems are required for maintaining adequate air quality in livestock facilities. This study assessed the ammonia reduction efficiency of a novel air pollution abatement (APA) system used in a pig farm building. The monitoring duration was 11 weeks. The results were compared with the baseline from a previous pig cycle during the same time of year in 2023. A ventilation-controlled room was monitored during a two-phase campaign, and the actual ammonia concentrations were measured at different locations within the site and at the inlet/outlet of the APA system. A 98% ammonia reduction was achieved at the APA outlet through NH₃ absorption in tap water. Ion chromatography analyses of farm water samples revealed NH₃ concentrations of up to 530 ppm within 83 days of APA operation. Further scanning electron microscopy and energy-dispersive X-ray inspections revealed the presence of salts and organic/inorganic matter in the solid residues. This research can contribute to meeting current ammonia regulations (NECRs), also by reusing the process water as a potential nitrogen fertiliser in agriculture. Full article

Animal production generates gas emissions. It is imperative to reduce them as projections suggest that emissions will continue to increase with rising temperatures, alongside the intensification of agriculture to meet global food demand. Slurry acidification in-house can reduce these emissions. In this study, an acidification technology was installed in a pig-fattening barn to evaluate the influence of the addition of a mixture of organic acids, mainly lactic acid and glycolic acid, on NH₃ and GHG emissions. A total of 384 pigs were allocated to four experimental rooms, two with additive applied to the slurry pits by a spraying system and two as a control. In high-temperature conditions, the spraying system discharged additive over the slurry which, in contrast with other systems, was stored inside the rooms during the whole trial. The concentration of NH₃ and GHG, the temperature, and the air extraction rate were measured continuously. A significant reduction in the emissions of the gases evaluated was achieved. NH₃ emissions were reduced by 26.8%, CH₄ by 23.6%, N₂O by 25.0%, and CO₂ by 28.7%. The role of the dynamic spraying system is considered essential to prevent the acidification effect being reversed by the buffering effect of the slurry itself. Full article

This study analyzed the frequency control challenges within the West Africa Power Pool Interconnected Transmission System (WAPPITS) as it plans to incorporate variable renewable energy (VRE) resources, such as wind and solar energy. Concerns center on the ability of WAPPITS primary frequency control reserves to adapt to high VRE penetration given the synchronization and frequency control problems experienced by the three separate synchronous blocks of WAPPITS. Optimizing solutions requires a better understanding of WAPPITS’ current frequency control approach. This study used questionnaires to understand operators’ practical experience with frequency control and compared these observations to field tests at power plants and frequency response metrics during system events. Eight (8) of ten (10) Transmission System Operators (TSOs) indicated that primary frequency control service was implemented in the TSO, but nine (9) of ten TSOs indicated that the reserves provided were inadequate to meet system needs. Five (5) of ten (10) respondents answered “yes” to the provision of secondary frequency control service, while only one (1) indicated that secondary reserves were adequate. Three (3) TSOs indicated they have AGC (Automatic Generation Control) installed in the control room, but none have implemented it for secondary frequency control. The results indicate a significant deficiency in primary control reserves, resulting in a reliance on under-frequency load shedding for primary frequency control. Additionally, the absence of an AGC system for secondary frequency regulation required manual intervention to restore frequency after events. To ensure the effectiveness of battery energy storage systems (BESSs) and the reliable operation of the WAPPITS with a higher penetration of inverter-based VRE, this paper recommends (a) implementing and enforcing basic primary frequency control structures through regional regulation and (b) establishing an ancillary services market to mobilize secondary frequency control resources. Full article

Against the background of the global concern for environmental protection and the prevalence of the green building concept, the requirements for building design are increasing, as are the technological content and functional requirements. Meanwhile, the urgency to address challenges related to the ecological environment and performance requirements has become increasingly pronounced. Taking a dormitory building in China as an example. Autodesk Revit 2018 software is employed in this study to establish a building information modeling (BIM). Green building software (GBSWARE) simulates and analyzes outdoor wind environment, indoor thermal comfort, calculates building energy conservation, does daylighting analysis, and calculates building daylighting. Although the building’s energy-saving design aligns with the requirements, the lighting and indoor thermal comfort of the rooms do not meet the standards. Additionally, the outdoor wind environment has problems with the wind zone and a wind speed amplification coefficient that surpasses the limit. The thermal environment within the residential building fails to satisfy the requirements. This study leverages a BIM-based model for multifaceted applications, integrating tailored retrofit strategies that align with the building’s inherent characteristics and detailed analyses of its components. By harnessing the building’s energy-saving potential, it enhances energy use efficiency, offering a valuable reference for the conceptual design of green buildings and energy-efficient retrofits. Full article

Infectious bursal disease virus (IBDV) is one of the most important immunosuppressive viruses in poultry, causing the global spread of infectious bursal disease (IBD). It poses a significant threat to the healthy development of the poultry industry. Vaccination is an effective approach for controlling IBDV infection. Therefore, reliable immune monitoring for IBDV is critical for maintaining poultry health. The enzyme-linked immunosorbent assay (ELISA) is a common technique used to detect specific antibodies in clinical serum testing and for the serological evaluation of IBDV vaccines. Among the currently available and under development IBDV vaccines, IBD VP2 subunit-based vaccines account for a considerable proportion. These vaccines stimulate the production of antibodies that are specific only to VP2. However, most IBDV antibody ELISA kits approved for use have applied the whole virus as the coating antigen, which does not adequately meet the diverse requirements for IBDV detection across different conditions. This study utilized a prokaryotic expression system to express the VP2 protein of the IBDV epidemic strain, assembling it into virus-like particles to be used as coating antigens. This approach enabled the establishment of an indirect ELISA method for detecting IBDV VP2 antibody (VP2-ELISA). The optimal coated antigen concentration was determined to be 2.5 μg/mL, with overnight coating at 4 °C; sealing with 5% skim milk at 37 °C for 4 h; serum dilution at 1:500 with incubation at 37 °C for 30 min; secondary antibody dilution at 1:4000 with incubation at 37 °C for 40 min; and then incubation with the substrate solution 3,3′,5,5′-tetramethylbenzidine at room temperature for 20 min. The criterion for interpreting the detection results was OD_450nm ≥ 0.111 indicates IBDV antibody positivity, while OD_450nm < 0.111 indicates negativity. The established VP2-ELISA can specifically detect IBDV-positive sera at the lowest serum dilution of 1:6400, with intra- and inter-batch coefficients of variation of <2%. This indicates that the VP2-ELISA exhibits good specificity, sensitivity, and stability. Detection experiments using 20 laboratory-immunized chicken serum samples and 273 clinical serum samples demonstrated that the results of VP2-ELISA were consistent with those of commercial ELISA kits coated with whole virus. In summary, the VP2-ELISA developed in this study offers advantages in immune response detection for IBD VP2 subunit-based vaccines and is appropriate for evaluating the efficacy of IBD vaccines and detecting clinical serum samples. Full article

With the rapid development of the tourism industry, scientific evaluation of tourism resources is crucial to realize sustainable development. Especially how to quantify resource advantages in international tourism cities has become an important basis for tourism planning and policy making. However, the limitations of traditional evaluation methods in the allocation of indicator weights and nonlinear data processing make it difficult to meet the development needs of international tourism cities. Therefore, this study takes Guilin, an international tourist city, as the research object and proposes a hybrid framework integrating fuzzy neural network (FNN) and analytic hierarchy process-fuzzy comprehensive evaluation (AHP-FCE). Based on 800 questionnaire data covering tourists, practitioners, and local residents, the study constructed a multilevel evaluation system (containing 12 specific indexes in the three dimensions of nature, service, and culture) using the Delphi method of expert interviews. It is found that AHP-FCE can effectively analyze the hierarchical relationship of evaluation indexes, but it is easily affected by the subjective judgment of experts. In contrast, FNN can effectively improve evaluation accuracy through the adaptive learning mechanism, and it especially shows significant advantages in dealing with tourists’ perception data. The empirical analysis shows that Guilin has obvious room for improvement in “environmental friendliness” and “cultural communication effectiveness”. The integration framework proposed in this study aims to enhance the scientific validity and accuracy of the assessment results, and provides reference and inspiration for the sustainable development of Guilin international tourism destination. Full article

Background/Objectives: with the aim of describing how students and their teachers perceive and define their hearing and auditory experience in the classroom, we present the results of a questionnaire that examined the listening challenges faced by students and teachers at the University of Perugia and in four secondary schools in Friuli-Venezia Giulia, Italy. Methods: A survey was developed as part of the A.Ba.Co. project (Overcoming Communication Barriers). Closed or open-ended questions were used to analyze the responses of students and teachers regarding diagnosed or only perceived hearing difficulties in daily life and the quality of listening in school classes. Results: Hearing difficulties, either clinically diagnosed or only perceived, were reported by 8–9% of students. Between teachers, the reported hearing difficulties were 27.1% in high school and 12% at university (p < 0.001). The most frequent reason for less-than-optimal ease of listening in class differed between the two educational levels; 45.8% of high school students blamed it on the noise in the room compared to 18.2% of university students (p < 0.001). Inversely, 40.9% of university students connected listening difficulty with their place in class compared to 9.5% (101/1065) of high school students (p < 0.001). Conclusions: Although the minimum acoustic requirements for educational facilities have been established by the UNI 11532-2 standard, it is speculated that the majority of high school and university classrooms in Italy do not meet optimal listening conditions. Furthermore, the reasons for students’ poor listening quality appear to not be fully understood, neither by students nor by teachers. In addition to the need for greater attention to physical learning spaces (advocating the universal design principles), effective change will also need to involve a greater awareness of what the barriers to listening are and how much they influence both teaching and learning quality and effectiveness. Full article

Based on the resource conservation requirements of GB/T 50378-2019 “Green Building Evaluation Standard”, this study constructed a BIM–Ecotect collaborative analysis model and proposed a “four-dimensional integration” green performance optimization method. Taking a high-rise office building in Wuhan as an example, a LOD 300-level Revit building information model was established, and a multidisciplinary collaborative analysis was achieved through gbXML data interaction. The lighting simulation results show that the average natural lighting coefficient of the office area facing south is 2.4 (the standard 85%), while in the meeting room area, due to the optimized design of the curtain wall, the average natural lighting coefficient has increased to 2.6 (the standard 92%). In terms of energy-saving renovation, a three-dimensional collaborative design strategy was adopted. Through the optimization of the envelope structure, the cooling load of the air conditioning system was reduced by 25.3%, and the heat load was reduced by 23.6% (the u value of the exterior wall was reduced by 56.3%, the SHGC of the exterior windows was reduced by 42.9%, and the thermal resistance of the roof was increased by 150%). The ventilation optimization adopts the CFD flow field reverse design, adjusting the window opening rate of the exterior windows from 15% to 20% to form a turbulent diffusion effect. Therefore, the air change rate in the office area reached 2.5 times per hour, and the CO₂ concentration decreased by up to 27.1% at most. The innovative adoption of the “composite sound insulation curtain wall” technology in acoustic environment control has increased the indoor noise compliance rate by 27 percentage points (from 65% to 92%). The above research data indicate that digital collaborative design can achieve an overall energy-saving rate of over 20% for buildings, providing a replicable technical path for enhancing the performance of green buildings. Full article

Recent advances in Artificial Intelligence (AI)-driven wireless communication are driving the adoption of Sixth Generation (6G) technologies in crucial environments such as hospitals. Visible Light Communication (VLC) leverages existing lighting infrastructure to deliver high data rates while mitigating electromagnetic interference (EMI); however, patient movement induces fluctuating signal strength and dynamic channel conditions. In this paper, we present a novel integration of site-specific ray tracing and machine learning (ML) for VLC-enabled Medical Body Sensor Networks (MBSNs) channel modeling in distinct hospital settings. First, we introduce a Q-learning-based adaptive modulation scheme that meets target symbol error rates (SERs) in real time without prior environmental information. Second, we develop a Long Short-Term Memory (LSTM)-based estimator for path loss and Root Mean Square (RMS) delay spread under dynamic hospital conditions. To our knowledge, this is the first study combining ray-traced channel impulse response modeling (CIR) with ML techniques in hospital scenarios. The simulation results demonstrate that the Q-learning method consistently achieves SERs with a spectral efficiency (SE) lower than optimal near the threshold. Furthermore, LSTM estimation shows that D1 has the highest Root Mean Square Error (RMSE) for path loss (1.6797 dB) and RMS delay spread (1.0567 ns) in the Intensive Care Unit (ICU) ward, whereas D3 exhibits the highest RMSE for path loss (1.0652 dB) and RMS delay spread (0.7657 ns) in the Family-Type Patient Rooms (FTPRs) scenario, demonstrating high estimation accuracy under realistic conditions. Full article