Search Results (47)

In deep-sea environments characterized by global climate change and frequent typhoons, the long-term structural stability of offshore buildings depends on the adaptability of their morphology to complex, multi-directional wind loads. Current offshore engineering predominantly emphasizes passive structural resistance, with a notable lack of research on proactive wind-diversion strategies from a morphological design perspective. Utilizing the PHOENICS-FLAIR platform and the Chen–Kim k-ε turbulence model, this study conducted numerical simulations across eight typical wind direction scenarios. The independence of the medium-mesh scheme was verified through Grid Convergence Index (GCI) analysis, and the high reliability of the numerical model was validated against the AIJ Case A wind tunnel experiments. Quantitative results demonstrate that, compared to the benchmark rectangular prism, the optimized composite polyhedral form featuring “curved sloped facades” performs superiorly under multi-directional conditions: the maximum positive wind pressure is reduced by up to 50%, and the total surface wind pressure differential decreases by 62–65%. This research proves that a polyhedral continuous envelope configuration can achieve balanced aerodynamic performance across all wind directions, providing a feasible direction for the design strategy of offshore buildings to shift from “passive resistance” to “proactive diversion”. Full article

As heritage museums shift toward more experience-oriented development, fragmented layouts and discontinuous visitor flows can reduce both spatial efficiency and the coherence of on-site experience. This study proposes an immersive experience-centred evaluation framework for exhibition layout in heritage museums, intended to translate experience goals into practical and diagnosable criteria for spatial optimization. An indicator system was refined through two rounds of Delphi consultation with an interdisciplinary expert panel, resulting in a hierarchical framework comprising five dimensions and multiple indicators. To support intervention prioritization in design and operations, weights were derived using the Group Analytic Hierarchy Process (GAHP), with Aggregation of Individual Judgments (AIJs) and consistency checks applied to control group judgement quality. A CV–entropy procedure was further used to support prioritization at the third-indicator level. Importance–Performance Analysis (IPA) was then employed to convert “importance–fit” assessments into an actionable sequence of optimization priorities. The results indicate that narrative and scene design carries the greatest weight (0.2877), followed by circulation and spatial organization (0.2281), sensory experience and atmosphere (0.1981), authenticity and sense of place (0.1644), and interactivity and participation (0.1217), suggesting that a “narrative–circulation–atmosphere” chain forms the core support for immersive layout design. A feasibility application using the Yinxu Museum demonstrates the framework’s value for benchmarking and diagnosis, helping decision-makers enhance visitor experience while respecting conservation constraints and more precisely target spatial investment priorities. Full article

In response to the urgent need for developing super-low-energy buildings (SLEBs) under extreme climatic conditions, a critical research gap lies in scientifically quantifying the passive climate adaptation mechanisms of vernacular architecture and translating them into modern design strategies. To this end, this study proposes a multidimensional “Monitoring–Visualization–Quantification” analytical method. Using the Aijing Zhuang building in central Fujian, China, as a case study, this method systematically analyzed its passive regulatory performance through high-frequency monitoring and spatial-interpolation techniques. This research revealed a distinct “Gradient-Buffering-and-Dynamic-Adjustment” mechanism: a maximum indoor–outdoor temperature difference of 5.7 °C was achieved, with indoor temperature variability reduced by 62%. The courtyard, functioning as a “Thermal Buffer” and “Ventilation Hub”, orchestrated the internal climatic gradients. This study provides systematic quantitative evidence for the modern translation of traditional wisdom, and the revealed mechanism can be directly transformed into design strategies for SLEBs adapted to extreme climates. Full article

This paper explores the static and cyclic behaviours exhibited by X-joints fabricated from circular hollow sections (CHS) incorporating curved chords under bending loading. First, a finite element (FE) model of CHS X-joints was established, and the accuracy was validated by the test results. Then, the influence of the geometric parameters on the ultimate capacity of these joints was deeply conducted through variable parameter expansion analysis, including the chord curvature (R)-to-diameter (D) ratio α, brace diameter (d)-to-chord diameter (D) ratio β, and chord diameter (D)-to-double thickness (2T) ratio γ. In addition, the formulae for the in-plane bending bearing capacity of CHS X-joints with curved chords were examined based on the FE results and typical design guides. Finally, the hysteresis performance of the joints was investigated to modify such formulae. The results show that (1) the bending bearing capacity decreases with increasing α when 3 ≤ α ≤ 12 and changes slightly when α > 12. The bending bearing capacity increases with increasing β and decreases with increasing γ. (2) The bending bearing capacity design formula is modified by FEM results on the basis of the formula derived from Eurocode 3. The API-WSD and LRFD design codes do not consider the effect of γ, and the AIJ seems to be overly conservative. (3) In light of the hysteresis analysis, the smaller the magnitude of γ and the larger that of β, the more favourable the bending load-bearing capacity, ductility coefficient and plastic deformation capability of the joints are found to be. The bending bearing capacity under cyclic loading was close to the value under static loading when α ≥ 9, whereas a reduction coefficient of 0.9 was considered when α < 9. Comparison analyses indicated that the adjusted design formula was suitable for engineering design. Full article

This study presents a machine learning framework for predicting the axial compressive strength of circular concrete-filled steel tube (CFST) columns subjected to concentric and eccentrically applied axial loads. A harmonized database of 1287 test specimens was compiled, encompassing diverse material strengths, geometric configurations, and eccentricity levels. Among the trained models, the CatBoost (CatB) algorithm exhibited the highest predictive performance. A 300-run Monte Carlo simulation yielded a mean R² of 0.966 (Min: 0.804; Max: 0.996), with a mean RMSE of 588.8 kN and MAPE of 8.36%, demonstrating accuracy and robustness across repeated randomized splits. Comparative benchmarking against current design equations revealed that CatBoost substantially reduced prediction scatter, improving the mean ratio and reducing the COV from 70–75% (ACI/AIJ/Wang) to 5.43%, while maintaining a nearly unbiased mean prediction ratio of 1.00. In addition, inverse prediction models based on CatBoost achieved test-set R² values of 0.908 for compressive strength and 0.945, 0.900, and 0.816 for key design parameters (D, t, L), indicating promising capability for supporting preliminary sizing and parameter selection. The outcomes of this study highlight the potential of data-driven modelling to complement existing design provisions and assist engineers in early-stage decision-making for axially loaded circular CFST columns. Full article

This paper examines decision-making challenges that arise when information is incomplete, specifically when judgments are missing or unavailable in the context of individual and group applications of the Analytic Hierarchy Process (AHP). Two illustrative examples are provided. The first, adapted from a recently published study in the field of artificial intelligence, demonstrates how different methods for generating missing judgments can affect the outcomes of an individual decision-maker. The second example addresses a real-world problem of allocating farmland among three crops, wheat, corn, and soybeans, using four evaluation criteria: expenses, labor, reliability, and market considerations. In this example, two decision-makers form a group, and their incomplete judgments leave gaps in pairwise comparison matrices at different levels of the hierarchy. The solution incorporates both transition-based approaches (general transition rule and First-Level Transition Rule) and established methods such as Harker’s and van Uden’s. In addition, aggregation of individual judgments (AIJ) is applied where at least one judgment exists, while geometric aggregation is used when multiple judgments are available. This enables prioritization of decision elements in both examples, with particular attention to cases requiring a priori and a posteriori aggregation of individual judgments across hierarchical levels. A critical analysis of the results highlights key differences between methods, revealing ongoing controversies regarding their reliability in practice. Although it is shown that the First-Level Transition Rule method in the presented examples and other authors’ tests outperforms other methods used, the findings suggest that further research is needed to refine and establish more trustworthy procedures for handling incomplete information in AHP applications. Full article

Accurate prediction of urban wind flow is essential for urban planning and environmental assessment. Classical computational fluid dynamics (CFD) methods are computationally expensive, while machine learning approaches often lack explainability and generalizability. To address the limitations of both approaches, we propose Diff-KNN, a hybrid method that combines Coarse-Scale CFD simulations with a K-Nearest Neighbors (KNN) model trained on the residuals between coarse- and fine-scale CFD results. Diff-KNN reduces velocity prediction errors by up to 83.5% compared to Pure-KNN and 56.6% compared to coarse CFD alone. Tested on the AIJE urban dataset, Diff-KNN effectively corrects flow inaccuracies near buildings and within narrow street canyons, where traditional methods struggle. This study demonstrates how residual learning can bridge physics-based and data-driven modeling for accurate and interpretable fine-scale urban wind prediction. Full article

Lactic acid bacteria (LAB) preserve many foods and play a vital role in fermented food products. This study designed a controlled biotechnological process of catfish (Clarias gariepinus) fermentation with a LAB starter culture isolated from corn hydrolysate. The BY (Barbu-Yelouassi) LAB strain was characterized regarding fermentative and antimicrobial potential, and its adaptability in the simulated gastrointestinal system (SGIS). After 10–12 h of cultivation on MRS broth (De Man Rogosa and Sharpe), the strain achieved the maximum exponential growth, produced maximum lactic acid (33.04%), and decreased the acidity up to pH 4. Also, the isolated strain showed increased tolerance to an acidic pH (3.5–2.0), high concentrations of salt (2–10%), and high concentrations of bile salts (≤2%). The behavior in SGIS demonstrated good viability after 2 h in artificial gastric juice (AGJ) (1 × 10⁷ CFU/mL) and up to 2 × 10³ CFU/mL after another 6 h in artificial intestinal juice (AIJ). The characterized BY strain was identified with the API 50CHL microtest (BioMerieux) as Lactiplantibacillus pentosus (Lbp. pentosus) (90.9% probability), taxon confirmed by genomic DNA sequencing. It was also demonstrated that Lbp. pentosus BY inhibited the growth of pathogenic bacteria, including Escherichia coli, Staphylococcus aureus, Listeria monocytogenes, and sporulated bacteria, such as Bacillus cereus. Additionally, it suppressed the sporulation of fungi like Aspergillus niger, Fusarium sp., and Penicillium sp. Furthermore, the Lbp. pentosus BY strain was used to ferment catfish, resulting in three variants of lanhouin (unsalted, with 10% salt, and with 15% salt), which exhibited good microbiological safety. Full article

This study investigates the flexural performance of desert sand concrete-filled steel tube (DS-CFST) members through experimental validation and finite element modeling (FEM). An extensive database of square and circular CFST specimens subjected to pure bending was analyzed to validate an ABAQUS-based FEM. Parametric studies evaluated the influence of steel yield strength, steel ratio, stirrup confinement, and desert sand replacement ratio (r) on ultimate bending moment, stiffness, and failure modes. The results indicated that steel yield strength and section geometry significantly affected bending capacity, while desert sand substitution (r ≤ 1) had a negligible impact on capacity, reducing it by less than 3%. The FEM accurately predicted buckling patterns, moment-curvature relationships, and failure modes. New design formulas for predicting ultimate bending moment and flexural stiffness were proposed, demonstrating superior accuracy (mean error < 1%) compared to existing design codes (AIJ, AISC, GB). This study highlights that DS-CFST members, particularly circular sections, offer robust flexural performance, with enhanced ductility and uniform stress distribution. The findings underscore the potential of using desert sand as a sustainable material in concrete-filled steel tube structures without compromising structural integrity. Full article

The global growth of solar power has led to a significant increase in solar photovoltaics (PV) waste, which is expected to rise significantly in the coming years. The recommended end-of-life (EOL) management techniques for wasted PV panels include landfill disposal, recycling, or panel reuse. However, a comprehensive decision-making strategy is necessary to assess the appropriate EOL plans from various perspectives, including economic, environmental, sociological, technological, regulatory, and business. This study aims to establish a comprehensive approach for examining disposition alternatives and suggest guidelines for PV EOL management. The Analytic Hierarchy Process (AHP) is used to prioritize disposition alternatives for solar PV waste, considering five key criteria: environmental impact, economic viability, social implications, policy and legislative compliance, and technical feasibility. The AHP Aggregating Individual Priorities (AIP) aggregation approach is used to analyze data using a pairwise comparisons matrix. The research indicates that recycling is the most preferred option based on the primary criteria, achieving the highest overall score compared to other alternatives. However, discrepancies were observed in the decisions among individual stakeholder groups and subfactor evaluations. To address these variations, this study provides policy recommendations to guide the sector in adopting optimal decision-making strategies for PV EOL management. Full article

Background and Objectives: Pediatric traumatic brain injury (pTBI) remains a major pediatric public health problem, despite well-developed injury prevention programs. The purpose of this study is to analyze the emergency surgical outcomes of pTBI in a single institute ten-year retrospective study to offer a real-world clinical result. Materials and Methods: Our institute presented a clinical retrospective, single-institute research study of 150 pediatric TBI cases that were diagnosed and underwent emergency surgical treatment from 2010 to 2019. Results: The incidence of radiological findings is detailed as follows: brain edema (30%, 45/150), followed by acute subdural hematoma (27.3%, 41/150), epidural hematoma (21.3%, 32/150), chronic subdural hemorrhage (10%, 15/150), skull fracture (6.7%, 10/150), and traumatic subarachnoid hemorrhage (4.7%, 7/150). Surgical intervention data revealed that decompressive craniectomy was still the main effective surgical method. The results showed longer hospital stays and higher morbidity rates in the brain edema, acute subdural hematoma, and chronic subdural hemorrhage groups, which were viewed as poor surgical outcome groups. Epidural hematoma, skull fracture and traumatic subarachnoid hemorrhage were categorized into good surgical outcome groups. Notably, the data revealed gross improvement in Glasgow Coma Scale/Score (GCS) evolution after surgical interventions, and the time to cranioplasty was a significant factor in the development of post-traumatic hydrocephalus (PTH). Conclusions: Our study provided real-world data for the distribution of etiology in pTBI and also categorized it into six groups, indicating disease-orientated treatment. In addition, our data supported that decompressive craniectomy (DC) remains a mainstay surgical treatment in pTBI and early cranioplasty could decrease the incidence of PTH. Full article

Glioblastoma multiforme (GBM) is a highly aggressive brain cancer with a poor prognosis despite current treatments. This is partially attributed to the immunosuppressive environment facilitated by tumor-associated macrophages, which predominantly underlie the tumor-promoting M2 phenotype. This study investigated the potential of hyperbaric oxygen (HBO) therapy, traditionally used to treat conditions such as decompression sickness, in modulating the macrophage phenotype toward the tumoricidal M1 state and disrupting the supportive tumor microenvironment. HBO has direct antiproliferative effects on tumor cells and reduces hypoxia, which may impair angiogenesis and tumor growth. This offers a novel approach to GBM treatment by targeting the role of the immune system within the tumor microenvironment. The effects of HBO on macrophage polarization and GBM cell viability and apoptosis were evaluated in this study. We detected that HBO promoted M1 macrophage cytokine expression while decreasing GBM cell viability and increasing apoptosis using GBM cell lines and THP-1-derived macrophage-conditioned media. These findings suggest that HBO therapy can shift macrophage polarization toward a tumoricidal M1 state. This can improve GBM cell survival and offers a potential therapeutic strategy. In conclusion, HBO can shift macrophages from a tumor-promoting M2 phenotype to a tumoricidal M1 phenotype in GBM. This can facilitate apoptosis and, in turn, improve treatment outcomes. Full article

Gliomas are the most common primary brain tumors in adults. Despite multidisciplinary treatment approaches, the survival rates for patients with malignant glioma have only improved marginally, and few prognostic biomarkers have been identified. Peroxisome proliferator-activated receptor γ (PPARγ) coactivator-1α (PGC-1α) is a crucial regulator of cancer metabolism, playing a vital role in cancer cell adaptation to fluctuating energy demands. In this study, the clinicopathological roles of PGC-1α in gliomas were evaluated. Employing immunohistochemistry, cell culture, siRNA transfection, cell viability assays, western blot analyses, and in vitro and in vivo invasion and migration assays, we explored the functions of PGC-1α in glioma progression. High PGC-1α expression was significantly associated with an advanced pathological stage in patients with glioma and with poorer overall survival. The downregulation of PGC-1α inhibited glioma cell proliferation, invasion, and migration and altered the expression of oncogenic markers. These results conclusively demonstrated that PGC-1α plays a critical role in maintaining the malignant phenotype of glioma cells and indicated that targeting PGC-1α could be an effective strategy to curb glioma progression and improve patient survival outcomes. Full article

The geometric shape of the roof and the opening position are important parameters influencing the internal cross-ventilation of buildings. Although there has been extensive research on natural ventilation, most of it has focused on flat or sloping roofs with the same opening positions. There is still limited research on the impact of different opening positions and sloping roofs on natural ventilation. In this study, computational fluid dynamics (CFD) was used to investigate the air exchange efficiency (AEE) in general isolated buildings. These buildings encompassed three distinct opening configurations (top–top, top–bottom, and bottom–top) and six varying slope angles for gable roofs (0°, 9°, 18°, 27°, 36°, and 45°). Computational simulations were carried out using the SST k-omega turbulence model, and validation was performed against experimental data supplied by the Japanese AIJ Wind Tunnel Laboratory. Grid independence validation was also conducted to ensure the reliability of the CFD simulation results. The study revealed that the highest AEE was 48.1%, achieved with the top–bottom opening configuration and a gable roof slope angle of 45°. Conversely, the lowest AEE was 31.4%, attained with the bottom–top opening configuration and a gable roof slope angle of 27°. Furthermore, it was observed that when the opening configuration was set to top–top and bottom–top, the slope angle of the gable roof had minimal influence on AEE, with an average AEE of only around 33%. When the opening configuration was top–bottom, it was found that there was a positive correlation between the gable roof slope angle and AEE. Full article