Search Results (23)

Caregivers of children with Autism Spectrum Disorder (ASD) frequently experience chronic psychological stress, thereby necessitating accessible support. Although artificial intelligence (AI)-based assisted technologies have the potential to reduce caregiver workload, most existing solutions lack robust privacy control and clinical interoperability, which significantly limits their adoption in regulated healthcare environments. To address these challenges, this paper proposes a Privacy-by-Design (PbD) multi-agent architecture that enables consent-aware, auditable, and privacy-preserving AI-assisted support for caregivers of children with ASD. The effectiveness of the proposed architecture was evaluated using two datasets: one focusing on clinically grounded autism-related knowledge and another reflecting naturalistic caregiver observation language. System performance was assessed using a Retrieval-Augmented Generation Assessment (RAGAs)-based framework with a Large Language Model (LLM)-as-a-Judge approach implemented via a locally deployed Llama 3 8B model. The system achieved answer relevancy scores of 0.767 for the clinical dataset and 0.750 for the observational dataset, with corresponding Recall@K values of 0.400 and 0.742, respectively. Context precision ranged from 0.599 to 0.631, and no harmful content was detected. Overall, the proposed architecture demonstrates secure caregiver–specialist collaboration through consent-aware routing, anonymised data storage, and controlled data reconstruction, providing a regulation-aligned design option for privacy-preserving AI integration in assisted care platforms. Full article

With accelerating urbanization and climate change, outdoor thermal comfort (OTC) in high-intensity urban blocks presents a critical challenge. While existing studies have established the general correlation between morphology and microclimate, most remain descriptive and lack a systematic framework to quantitatively integrate the non-linear coupled effects between multi-dimensional morphological variables and green infrastructure. To address this, this study proposes an automated performance-based design (PBD) framework for urban morphology optimization in Shenzhen. Unlike traditional simulation-based analysis, this framework serves as a generative tool for urban renewal planning. It integrates a multi-dimensional design element system with a genetic algorithm (GA) workflow. Analysis across four urban typologies demonstrated that the Full Enclosure layout is the most effective strategy for mitigating thermal stress, achieving a final optimized UTCI of 37.15 °C. Crucially, this study reveals a non-linear synergistic mechanism: the high street aspect ratios (H/W) of enclosed forms act as a “radiation shelter”, which amplifies the cooling efficiency of green infrastructure (contributing an additional 1.79 °C reduction). This research establishes a significant, strong negative correlation between UTCI and the combined factors of building density and green shading coverage. The results provide quantifiable guidelines for retrofitting existing high-density districts, suggesting that maximizing structural shading is prioritized over ventilation in ultra-high-density, low-wind climates. Full article

Construction on soft, highly compressible soils increasingly requires reliable ground improvement solutions. Among these, Rigid Inclusions (RIs) have emerged as one of the most efficient soil-reinforcement techniques. This paper synthesizes evidence from over 180 studies to provide a comprehensive state-of-the-art review of RI technology encompassing its governing mechanisms, design methodologies, and field performance. While the static behavior of RI systems has now been extensively studied and is supported by international design guidelines, the response under cyclic and seismic loading, particularly in liquefiable soils, remains less documented and subject to significant uncertainty. This review critically analyzes the degradation of key load-transfer mechanisms including soil arching, membrane tension, and interface shear transfer under repeated loading conditions. It further emphasizes the distinct role of RIs in liquefiable soils, where mitigation relies primarily on reinforcement and confinement rather than on drainage-driven mechanisms typical of granular columns. The evolution of design practice is traced from analytical formulations validated under static conditions toward advanced numerical and physical modeling frameworks suitable for dynamic loading. The lack of validated seismic design guidelines is high-lighted, and critical knowledge gaps are identified, underscoring the need for advanced numerical simulations and large-scale physical testing to support the future development of performance-based seismic design (PBSD) approaches for RI-improved ground. Full article

Pipe leakage and bursts are the primary contributors to water losses in water distribution networks (WDNs). However, the use of object detection techniques for identifying such failures is underexplored. This study proposes a novel deep-learning-based framework for pipe burst detection and localization (PBD&L) within WDNs. The framework employs spatial encoding of pressure fields obtained from hydraulic simulations of normal and burst scenarios. These encoded images serve as inputs to a faster region-based convolutional neural network (Faster R-CNN) object detection model, specifically designed for infrastructure monitoring. The framework was tested on three WDNs—Fossolo, PB23, and CM53—under varying sensor coverages (100%, 75%, and 50%). The results indicate that the model consistently achieves high detection accuracy across different network configurations, even with limited sensor availability. For Fossolo and PB23, the model demonstrated stable performance; however, for the CM53 network, accuracy decreased at full sensor coverage, possibly owing to overfitting or signal redundancy. Overall, the proposed method presents a robust solution for PBD&L in WDNs, showcasing significant practical applicability. Its ability to maintain high performance under partial observability and diverse network conditions demonstrates its potential for integration into real-time smart water management systems, enabling automated monitoring, rapid response, and improved operational efficiency. Full article

This study proposes a GPU-accelerated Position-Based Dynamics (PBD) system for realistic and interactive cloth simulation in Extended Reality (XR) environments, and comprehensively evaluates its performance and functional capabilities on standalone XR devices, such as the Meta Quest 3. To overcome the limitations of traditional CPU-based physics simulations, we designed and optimized highly parallelized algorithms utilizing Unity’s Compute Shader framework. The proposed system achieves real-time performance by implementing efficient collision detection and response handling with complex environmental meshes (RoomMesh) and dynamic hand meshes (HandMesh), as well as capsule colliders based on hand skeleton tracking (OVRSkeleton). Performance evaluations were conducted for both single-sided and double-sided cloth configurations across multiple resolutions. At a 32 × 32 resolution, both configurations maintained stable frame rates of approximately 72 FPS. At a 64 × 64 resolution, the single-sided cloth achieved around 65 FPS, while the double-sided configuration recorded approximately 40 FPS, demonstrating scalable quality adaptation depending on application requirements. Functionally, the GPU-PBD system significantly surpasses Unity’s built-in Cloth component by supporting double-sided cloth rendering, fine-grained constraint control, complex mesh-based collision handling, and real-time interaction with both hand meshes and capsule colliders. These capabilities enable immersive and physically plausible XR experiences, including natural cloth draping, grasping, and deformation behaviors during user interactions. The technical advantages of the proposed system suggest strong applicability in various XR fields, such as virtual clothing fitting, medical training simulations, educational content, and interactive art installations. Future work will focus on extending the framework to general deformable body simulation, incorporating advanced material modeling, self-collision response, and dynamic cutting simulation, thereby enhancing both realism and scalability in XR environments. Full article

Conventional seismic design regulations, even when rigorously adapted to local conditions, often fail to ensure the resilience of reinforced concrete buildings. Code-based prescriptive methods rely on simplified assumptions that do not fully capture the complex nonlinear behavior of structures during strong earthquakes, potentially underestimating seismic demands and structural vulnerabilities. This study evaluates the seismic performance of a 44-story reinforced concrete building designed per the EN-2015 code, currently adopted in Ethiopia. The building was analyzed using Response Spectrum Analysis (RSA), Linear Dynamic Time History Analysis (LDTHA), and Classical Modal Analysis in ETABS v19, with 11 ground motions from the PEER database. Ground motion scaling was performed using SeismoMatch and ETABS. Results indicate that LDTHA predicts 25.68% higher maximum story displacement, 26.49% greater inter-story drift ratios, 15.35% higher story shear, and 27.5% greater overturning moments compared to RSA. The fundamental time period for the first mode was found to be 3.956 s in Classical Modal Analysis, 3.806 s in RSA, and 3.883 s in LDTHA. These discrepancies highlight the limitations of code-based design and underscore the necessity of performance-based seismic design for achieving safer, more resilient structures in high-seismic regions. Full article

Performance-based seismic design (PBD) has emerged as a key approach for rationalizing prescriptive code provisions and improving the explicit assessment of structural performance. In Chile, where reinforced concrete shear wall buildings are the predominant structural typology, evaluating their seismic response beyond traditional linear methodologies is crucial. This study assesses the seismic performance of a representative Chilean shear wall residential building using the ACHISINA manual’s performance-based seismic design framework. A nonlinear static (pushover) analysis is performed to verify compliance with prescribed design criteria, incorporating capacity design principles and a moment envelope approach to prevent premature yielding in upper stories. The results confirm that the building meets the performance objectives for both Immediate Occupancy and Additional Deformation Capacity limit states. The application of capacity design effectively controls shear demand, preventing brittle failure, while the flexural design ensures the formation of the yielding mechanism (plastic hinge) at the intended critical section. Additionally, the study highlights the limitations of pushover analysis in capturing higher-mode effects and recommends complementary nonlinear time-history analysis (NLTHA) for a more comprehensive assessment. The computed response reduction factors exceed those used in the prescriptive design, suggesting a conservatively safe approach in current Chilean practice. This research reinforces the need to integrate performance-based methodologies into Chilean seismic design regulations, particularly for shear wall structures. It provides valuable insights into the advantages and limitations of current design practices and proposes improvements for future applications. Full article

In the context of seismic hazard assessment and engineering design, a comprehensive understanding of local geological and geophysical factors is essential. However, previous studies have lacked crucial components such as local soil condition, ground response analysis, topographic influences, active fault characteristics, slip rates, groundwater behaviour, and slope considerations. To ensure the accuracy of the seismic hazard map of a country for the safe and cost-effective design of engineering structures in urban areas, a detailed analysis of these factors is imperative. Moreover, multidisciplinary investigations, such as logic-tree considerations, are needed to enhance seismic hazard maps. As a result, adopting a performance-based approach in structural design has become an essential priority. A performance-based approach allows engineers to design buildings to specified performance levels (IO, LS, CP) even without a reliable seismic hazard map. This approach is akin to a miracle for countries that do not have a reliable seismic hazard map. This study presents a systematic and comprehensive bibliometric analysis of the academic literature pertaining to performance-based design (PBD). By fostering collaborative efforts and expanding research networks, we aim to facilitate the development of coordinated initiatives within the field. Preferred journals, leading countries, leading organisations, and international institutions were identified utilizing the Scopus database. This study examined 3456 PBD-related publications spanning from 1969 to 2023 using VOSviewer version 1.6.19, a bibliometric mapping and visualization software tool. The analysis of co-citations revealed that performance-based design serves as the primary theoretical foundation for structural design and analysis. Furthermore, through a co-word analysis, we tracked the evolution of research topics within the PBD domain over time. This investigation uncovered noteworthy trends, including the steady growth of research output, the increasing prominence of the term “PBD”, and a focus on various types of performance-based analyses. Full article

Chile, recognized as one of the world’s most earthquake-prone nations, has gained valuable insights from significant earthquakes, such as those in 1985 and 2010, which have influenced updates to the nation’s design codes. Although Chile’s seismic design approach has been largely effective in recent earthquakes and demonstrated an “operational” performance level in most structures, performance-based design (PBD) methods have not yet been officially incorporated as valid approaches in the Chilean seismic design codes for buildings. However, in 2017, the Chilean Association on Seismology and Earthquake Engineering (ACHISINA) introduced a PBD approach, primarily for verification purposes, based on the Los Angeles Tall Buildings Structural Design Council (LATBSDC) framework. In this work, firstly, we provide an overview of Chile’s PBD methodology, focusing on the thresholds for various performance levels. These levels are established through experimental and numerical analysis, correlating performance with permissible damage levels. The second part of the paper examines the seismic performance of a residential building, designed before the 2010 Maule earthquake and subsequently damaged, using Chile’s PBD guidelines. This case study highlights the implementation and effectiveness of PBD for assessing seismic resilience in Chilean structures. Full article

In South Korea, the need to link fire and evacuation simulations to compare the available safety egress time (ASET) and required safety egress time (RSET) in real time when implementing performance-based design in buildings is increasing. Accordingly, the Consolidated Model of Fire Growth and Smoke Transport (CFAST) has been discussed as an alternative to the fire dynamics simulator, which requires high computational costs, sufficient experience in fire dynamics numerical calculations, and various input parameters and faces limitations in integration with evacuation simulations. A method for establishing a reasonable computational domain to predict the activation times of smoke and heat detectors has been proposed. This study examined the validity of using CFAST to predict factors relevant to the ASET evaluation. The results showed that CFAST, which solved empirical correlations based on heat release rates, predicted high gas temperatures similarly. Moreover, the applicability of the visibility distance calculation method using smoke concentration outputs from CFAST was examined. The results suggest that despite the limitations of the zone model, CFAST can produce reasonable ASET results. These results are expected to enhance the usability of CFAST in terms of understanding general fire engineering technology and simple fire dynamics trends. Full article

Masonry is among the most widely used construction materials around the world. Contemporary masonry buildings are primarily designed to comply with prescriptive building code regulations. In recent decades, performance-based design (PBD) has gained increasing attention and achieved significant success in critical structures or infrastructure systems. Instead of being the first mover, the masonry research and practice community can be a faster follower in response to the design paradigm shift towards PBD for masonry buildings. A reliable performance assessment of masonry buildings is of paramount importance in the PBD framework. To facilitate this, this paper presents an up-to-date comprehensive literature review of experimental and analytical studies with emphasis on their contributions to advancement towards performance assessment of masonry buildings. This review categorized available works into two sub-topics: (1) traditional unreinforced masonry and (2) modern reinforced masonry. In each sub-topic, studies focusing on the structural behaviors of masonry at the component-level (i.e., masonry wall) are discussed first, followed by the building system-level-related studies. Through this literature review, the current state of the art and remaining research gaps are identified to provide guidance for future research needs and to pave the way for implementing PBD in the masonry industry. Full article

Favipiravir (FAV) has become a promising antiviral agent for the treatment of COVID-19. Herein, a green, fast, high-sample-throughput, non-instrumental, and affordable analytical method is proposed based on surfactant-assisted dispersive liquid–liquid microextraction (SA-DLLME) combined with thin-layer chromatography–digital image colourimetry (TLC-DIC) for determining favipiravir in biological and pharmaceutical samples. Triton X-100 and dichloromethane (DCM) were used as the disperser and extraction solvents, respectively. The extract obtained after DLLME procedure was spotted on a TLC plate and allowed to develop with a mobile phase of chloroform:methanol (8:2, v/v). The developed plate was photographed using a smartphone under UV irradiation at 254 nm. The quantification of FAV was performed by analysing the digital images’ spots with open-source ImageJ software. Multivariate optimisation using Plackett–Burman design (PBD) and central composite design (CCD) was performed for the screening and optimisation of significant factors. Under the optimised conditions, the method was found to be linear, ranging from 5 to 100 µg/spot, with a correlation coefficient (R²) ranging from 0.991 to 0.994. The limit of detection (LOD) and limit of quantification (LOQ) were in the ranges of 1.2–1.5 µg/spot and 3.96–4.29 µg/spot, respectively. The developed approach was successfully applied for the determination of FAV in biological (i.e., human urine and plasma) and pharmaceutical samples. The results obtained using the proposed methodology were compared to those obtained using HPLC-UV analysis and found to be in close agreement with one another. Additionally, the green character of the developed method with previously reported protocols was evaluated using the ComplexGAPI, AGREE, and Eco-Scale greenness assessment tools. The proposed method is green in nature and does not require any sophisticated high-end analytical instruments, and it can therefore be routinely applied for the analysis of FAV in various resource-limited laboratories during the COVID-19 pandemic. Full article

Fabric phase sorptive extraction (FPSE) has become a popular sorptive-based microextraction technique for the rapid analysis of a wide variety of analytes in complex matrices. The present study describes a simple and green analytical protocol based on in-matrix methyl chloroformate (MCF) derivatization of non-steroidal anti-inflammatory (NSAID) drugs in urine samples followed by FPSE and gas chromatography-mass spectrometry (GC-MS) analysis. Use of MCF as derivatizing reagent saves substantial amounts of time, reagent and energy, and can be directly performed in aqueous samples without any sample pre-treatment. The derivatized analytes were extracted using sol–gel Carbowax 20M coated FPSE membrane and eluted in 0.5 mL of MeOH for GC-MS analysis. A chemometric design of experiment-based approach was utilized comprising a Placket–Burman design (PBD) and central composite design (CCD) for screening and optimization of significant variables of derivatization and FPSE protocol, respectively. Under optimized conditions, the proposed FPSE-GC-MS method exhibited good linearity in the range of 0.1–10 µg mL⁻¹ with coefficients of determination (R²) in the range of 0.998–0.999. The intra-day and inter-day precisions for the proposed method were lower than <7% and <10%, respectively. The developed method has been successfully applied to the determination of NSAIDs in urine samples of patients under their medication. Finally, the green character of the proposed method was evaluated using ComplexGAPI tool. The proposed method will pave the way for simper analysis of polar drugs by FPSE-GC-MS. Full article

Malachite green (MG) dye is a common environmental pollutant that threatens human health and the integrity of the Earth’s ecosystem. The aim of this study was to investigate the potential biodegradation of MG dye by actinomycetes species isolated from planted soil near an industrial water effluent in Cairo, Egypt. The Streptomyces isolate St 45 was selected according to its high efficiency for laccase production. It was identified as S. exfoliatus based on phenotype and 16S rRNA molecular analysis and was deposited in the NCBI GenBank with the gene accession number OL720220. Its growth kinetics were studied during an incubation time of 144 h, during which the growth rate was 0.4232 (µ/h), the duplication time (td) was 1.64 d, and multiplication rate (MR) was 0.61 h, with an MG decolorization value of 96% after 120 h of incubation at 25 °C. Eleven physical and nutritional factors (mannitol, frying oil waste, MgSO₄, NH₄NO₃, NH₄Cl, dye concentration, pH, agitation, temperature, inoculum size, and incubation time) were screened for significance in the biodegradation of MG by S. exfoliatus using PBD. Out of the eleven factors screened in PBD, five (dye concentration, frying oil waste, MgSO₄, inoculum size, and pH) were shown to be significant in the decolorization process. Central composite design (CCD) was applied to optimize the biodegradation of MG. Maximum decolorization was attained using the following optimal conditions: food oil waste, 7.5 mL/L; MgSO₄, 0.35 g/L; dye concentration, 0.04 g/L; pH, 4.0; and inoculum size, 12.5%. The products from the degradation of MG by S. exfoliatus were characterized using high-performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS). The results revealed the presence of several compounds, including leuco-malachite green, di(tert-butyl)(2-phenylethoxy) silane, 1,3-benzenedicarboxylic acid, bis(2-ethylhexyl) ester, 1,4-benzenedicarboxylic acid, bis(2-ethylhexyl) ester, 1,2-benzenedicarboxylic acid, di-n-octyl phthalate, and 1,2-benzenedicarboxylic acid, dioctyl ester. Moreover, the phytotoxicity, microbial toxicity, and cytotoxicity tests confirmed that the byproducts of MG degradation were not toxic to plants, microbes, or human cells. The results of this work implicate S. exfoliatus as a novel strain for MG biodegradation in different environments. Full article

Streptomyces alfalfae XN-04 has been reported for the production of antifungal metabolites effectively to control Fusarium wilt of cotton, caused by Fusarium oxysporum f. sp. vasinfectum (Fov). In this study, we used integrated statistical experimental design methods to investigate the optimized liquid fermentation medium components of XN-04, which can significantly increase the antifungal activity and biomass of XN-04. Seven variables, including soluble starch, KNO₃, soybean cake powder, K₂HPO₄, MgSO₄·7H₂O, CaCO₃ and FeSO₄·7H₂O, were identified as the best ingredients based on one-factor-at-a-time (OFAT) method. The results of Plackett–Burman Design (PBD) showed that soluble starch, soybean cake powder and K₂HPO₄ were the most significant variables among the seven variables. The steepest climbing experiment and response surface methodology (RSM) were performed to determine the interactions among these three variables and fine-tune the concentrations. The optimal compositions of medium were as follows: soluble starch (26.26 g/L), KNO₃ (1.00 g/L), soybean cake powder (23.54 g/L), K₂HPO₄ (0.27 g/L), MgSO₄·7H₂O (0.50 g/L), CaCO₃ (1.00 g/L) and FeSO₄·7H₂O (0.10 g/L). A verification experiment was then carried out under the optimized conditions, and the results revealed the mycelial dry weight of S. alfalfae XN-04 reaching 6.61 g/L. Compared with the initial medium, a 7.47-fold increase in the biomass was achieved using the optimized medium. Moreover, the active ingredient was purified from the methanol extract of S. alfalfae XN-04 mycelium and then identified as roflamycoin (a polyene macrolide antibiotic). The results may provide new insights into the development of S. alfalfae XN-04 fermentation process and the control of the Fusarium wilt of cotton and other plant diseases. Full article