Search Results (4,986)

Background: In recent years, prepectoral implant-based breast reconstruction supported by acellular dermal matrices (ADMs) has become an increasingly adopted alternative to submuscular techniques. Although this approach can improve patient comfort and aesthetic outcomes, fluid accumulation around the implant remains one of the most frequent and clinically relevant complications. Our unit progressively modified the handling and wrapping of the Braxon^® ADM with the aim of optimizing pocket configuration and reducing seroma formation. Methods: We performed a retrospective analysis of consecutive patients who underwent immediate prepectoral, direct-to-implant breast reconstruction with Braxon^® ADM at our institution between October 2019 and January 2025. Two techniques were compared: a standard full-wrap configuration and a modified approach in which the posterior ADM sheet is trimmed and only anterior coverage is maintained, with fenestrations created in the anterior wall. Clinical data and postoperative complications, including seroma rates, were recorded and compared between groups. Categorical variables were summarized as counts and percentages, and continuous variables as means and standard deviations. The primary comparison between techniques was performed on the presence of at least one postoperative complication using Fisher’s exact test, and odds ratios (OR) with 95% confidence intervals (CI) were calculated where appropriate. A p-value <0.05 was considered statistically significant. Results: A total of 138 direct-to-implant prepectoral reconstructions were included, 90 performed with the standard full-wrap technique and 48 with the modified wrapping approach. The overall complication rate was 27.8% (25/90) in the standard group and 10.4% (5/48) in the new-technique group. Seroma occurred in 8 patients (8.9%) in the standard group and in 1 patient (2.1%) in the modified-technique group. Fisher’s exact test demonstrated a significantly lower overall complication rate in the modified-technique cohort (10.4% vs. 27.8%; p = 0.02; OR 3.31; 95% CI 1.18–9.31), indicating that patients treated with the standard technique had approximately 3.3-fold higher odds of developing at least one complication than those treated with the modified technique. Conclusions: Anterior-only ADM coverage with selective trimming of the posterior sheet and fenestration of the anterior wall appears to reduce complications, particularly seroma, in ADM-assisted prepectoral breast reconstruction. Small technical refinements in ADM handling and pocket configuration, combined with a structured drainage protocol, may substantially improve postoperative outcomes in this setting. Full article

This study investigates the thermal transport behavior of a time-dependent viscoelastic nanofluid moving over a widening cylindrical surface. A steady magnetic influence is introduced along the transverse direction due to photonic heating, thermal sources, or absorbers, and modified Fourier conduction. A mixture of $CoF{e}_2{O}_4$ and $F{e}_3{O}_4$ nanoparticles are uniformly distributed in ethylene glycol to form a hybrid nanofluid. Using a suitable similarity transformation, the governing equations were reformulated into a set of nonlinear ordinary differential equations. The collocation method (CM) is employed as a discretization approach, combined with feedforward neural networks (FNNs) to enhance computational accuracy. Unsteady patterns in both fluid motion and heat distribution were identified, with the localized Nusselt coefficient influenced by relevant scaling parameters. Results are illustrated through plots and structured data formats for various nanoparticle geometries, including spherical, brick, and platelet forms. The analysis revealed that spherical nanoparticles enhance heat transfer by up to 18–22% compared with brick and platelet forms under strong unsteadiness and relaxation effects. As temporal fluctuation indicators intensify, the thermal distribution increases; however, increasing the relaxation coefficient in the heat response leads to diminished energy levels. Full article

Among various statistical process -control (SPC) methods, control charts are widely employed as essential instruments for monitoring and improving process quality. This study focuses on a new modified exponentially weighted moving-average (New Modified EWMA) control chart that enhances detection capability under integrated and fractionally integrated time-series processes. Special attention is given to the effect of symmetry on the chart structure and performance. The proposed chart preserves a symmetric monitoring configuration, in which the two-sided design ($\mathrm{LCL}>0$) establishes control limits that are equally spaced around the center line, enabling balanced detection of both upward and downward shifts. Conversely, the one-sided version ($\mathrm{LCL}=0$) introduces a deliberate asymmetry to increase sensitivity to upward mean shifts, which is particularly useful when downward deviations are physically implausible or less critical. The efficacy of the control chart utilizing both models is assessed through Average Run Length (ARL). Herein, the explicit formula of ARL is derived and compared to the ARL obtained from the Numerical Integral Equation (NIE) in terms of both accuracy and computational time. The accuracy of the analytical ARL expression is validated by its negligible percentage difference ($\%diff$) in comparison to the results derived using the NIE approach, and the display processing time not exceeding 3 s. To confirm the highest capability, the suggested method is compared to both the classic EWMA and the modified EWMA charts using evaluation metrics such as ARL and SDRL (standard deviation run length), as well as RMI (relative mean index) and PCI (performance comparison index). Since asset values are volatile due to positive and negative market influences, symmetry is crucial in financial monitoring. Thus, symmetric control-chart structures reduce directional bias and better portray financial market activity by balancing upward and downward movements. Finally, examination of US stock prices illustrates performance, employing a symmetrical two-sided control chart for the rapid detection of changes through the new modified EWMA, in contrast to standard EWMA and modified EWMA charts. Full article

Drug-induced cardiotoxicity (DICT) severely hampers drug development and threatens patient safety. Together with the growing global burden of cardiovascular disease, there is an urgent need to establish more predictive preclinical models. Recently, human pluripotent stem cell-derived cardiac organoids (hCOs) have emerged as a promising three-dimensional in vitro model, achieving significant progress in simulating the complex structure and function of the human heart. However, existing reviews predominantly focus on technical construction or specific applications, lacking an integrated discussion of pathological model construction and their use under evolving regulatory frameworks. This review distinguishes itself by proposing a novel, holistic framework that bridges “construction technology,” “pathological modeling,” and “application evaluation.” We systematically categorize and summarize three major strategies for building hCO-based pathological models: patient-specific, gene-edited, and microenvironment-modulated approaches. Furthermore, we highlight the unique advantages of hCOs in preclinical drug assessment and detail their cutting-edge applications in early DICT warning, metabolism-related safety evaluation, and personalized drug evaluation. Finally, we address current challenges, including maturation and standardization, and outline future directions involving integration with organ-on-a-chip technology and artificial intelligence. This review aims to provide a theoretical foundation and roadmap toward more reliable and human-relevant drug development paradigms. Full article

To address the limitations of traditional energy dissipation technologies, such as difficulty in arranging energy dissipators due to narrow river valleys and complex geological conditions and the low energy dissipation efficiency of existing air jet collision methods, this study proposes a novel structural form of a horizontal opposing jet energy dissipator. Water is diverted to the open area downstream of the reservoir hub via diversion pipelines, and energy dissipation is achieved through horizontal opposing collision of jets in the air. Focusing on this new energy dissipator, numerical simulations combined with physical experiments were conducted to investigate its energy dissipation characteristics, with the dimensionless parameters l/d (collision distance/pipeline diameter) and Reynolds number (Re) as the main variables. The results indicate that two opposing jets formed a crown-shaped water jet after horizontal collision in the air. The rising height in the Z-direction and expanding width in the Y-direction of the crown-shaped water jet exhibit a negative correlation with l/d and a positive correlation with Re. Energy dissipation was achieved through jet collision, mixing, friction, diffusion, aeration, and fragmentation in the air. This energy dissipation method improved the energy dissipation rate by extending the collision time and mixing length of jets in the air. The primary factors influencing the energy dissipation rate were l/d and Re. Under the study conditions, the energy dissipation rate of jet collision in the air ranged from 16.25% to 39.54%. The energy dissipation efficiency exhibits a negative correlation with l/d and a positive correlation with Re. This study provides a new approach for energy dissipation in hydraulic engineering. Full article

The electric vehicle (EV) battery supply chain plays a critical role in promoting sustainable transportation and tackling scarce resources, environmental costs, and supply chain vulnerabilities. The current study aims to conduct an extensive literature review of the EV battery supply chain given its importance for developing sustainable and efficient EVs. Using keyword co-occurrence and article co-citation analyses, this study analyses more than 681 publications from 2005 to 2024 and sourced from the Scopus database. Findings show that the number of articles increased considerably after 2020, which can be attributed to the global focus on decarbonization, electromobility, and circular economy practices. The review identifies important themes such as sustainability challenges, critical materials management, reverse logistics, and policy-driven frameworks for closed-loop supply chains. The findings from this study highlight a multidimensional approach where the integration of technologies, innovative policies, and collaborative actions can contribute to the resilience and sustainability of EV battery supply chains. It offers practical insights for stakeholders, strategic directions to maximize EV battery lifecycle management, and outlines the pathways to reach carbon neutrality in the transportation sector. By identifying the intellectual structure of this emerging field, the study contributes to academic discourse and informs the formulation of practical strategies to advance sustainable mobility. Full article

Background: Intracranial atherosclerotic disease (ICAD) remains a major global cause of ischemic stroke—particularly in Asian, Black, and Hispanic populations—and is characterized by high recurrence rates despite advances in intensive medical management. Objectives: This review synthesizes current evidence on surgical and endovascular approaches for ICAD, including extracranial–intracranial bypass, encephaloduroarteriosynangiosis, angioplasty, and hybrid revascularization strategies. Methods: We performed a structured narrative literature search of PubMed and Scopus. Searches were conducted up to 1 October 2025 using combinations of subject headings and keywords, including “intracranial atherosclerotic disease”, “ICAD”, “intracranial stenosis”, “bypass”, “encephaloduroarteriosynangiosis”, “angioplasty”, “stenting”, “revascularization”, and “stroke”. We also scanned reference lists of key articles and relevant reviews. Non-English language articles were excluded. Results: While randomized trials such as SAMMPRIS, VISSIT, and CASSISS reaffirm intensive medical management as first-line therapy, emerging data suggest that surgical revascularization may benefit select patients with hemodynamic compromise refractory to medical therapy. Recent studies incorporating physiologic imaging—such as PET, SPECT, and perfusion MRI—have refined patient selection, reducing perioperative risk and improving long-term outcomes. Innovations in indirect revascularization, hybrid procedures, and intraoperative imaging continue to expand therapeutic possibilities. However, evidence remains heterogeneous, underscoring the need for well-powered randomized trials integrating modern surgical techniques, objective hemodynamic endpoints, and AI-enhanced imaging analytics. Conclusions: While intensive medical management remains the first-line standard of care, select patients with refractory, hemodynamically significant ICAD may benefit from direct, indirect, or hybrid surgical revascularization. Future directions emphasize personalized, physiology-based management frameworks that combine medical, surgical, and technological advances to optimize stroke prevention and long-term vascular outcomes in ICAD. Full article

Grey systems theory has provided a change in paradigm related to how numbers and their mathematics are perceived. By including various levels of knowledge associated with the variables, the theory has succeeded in modelling systems characterised by incomplete or partially known information. Among the methods offered by the grey systems theory, the grey clustering approach offers a distinct perspective on clustering methodology by allowing researchers to define degrees of importance for the variables included in the analysis. Despite its expanding use across disciplines, a comprehensive synthesis of grey clustering research is lacking. In this context, this study aims to provide a comprehensive and structured overview of the research field associated with grey clustering and its applications, rather than the more rhetorical formulation previously included. By using a PRISMA approach, a dataset containing papers related to grey clustering is extracted from the Clarivate Web of Science database and analysed through bibliometric tools and further enhanced by providing thematic maps and topics discovery through the use of Latent Dirichlet Allocation (LDA) and BERTopic analyses. The final dataset includes 318 articles, and their examination allows for a detailed assessment of publication trends, thematic structures, and methodological directions. The annual scientific production showcased an increase of 10.78%, while the thematic analysis revealed key themes related to performance management, risk assessment, evaluation models for enhancing organisational performance, urban and regional planning, civil engineering, industrial engineering and automation, and risk evaluation for health-related issues. Additionally, a detailed review of the most-cited papers has been performed to highlight the role of grey clustering in various research fields. Full article

This paper considers the problem of unconstrained minimization of smooth functions. Despite the high efficiency of quasi-Newton methods such as BFGS, their performance degrades in ill-conditioned problems with unstable or rapidly varying Hessians—for example, in functions with curved ravine structures. This necessitates alternative approaches that rely not on second-derivative approximations but on the topological properties of level surfaces. As a new methodological framework, we propose using a procedure of incomplete orthogonalization in the directions of gradient differences, implemented through the iterative least-squares method (ILSM). Two new methods are constructed based on this approach: a gradient method with the ILSM metric (HY_g) and a modification of the Hestenes–Stiefel conjugate gradient method with the same metric (HY_XS). Both methods are shown to have linear convergence on strongly convex functions and finite convergence on quadratic functions. A numerical experiment was conducted on a set of test functions. The results show that the proposed methods significantly outperform BFGS (2 times for HY_g and 3.5 times for HY_XS in terms of iterations number) when solving ill-posed problems with varying Hessians or complex level topologies, while providing comparable or better performance even in high-dimensional problems. This confirms the potential of using topology-based metrics alongside classical quasi-Newton strategies. Full article

Natural disasters pose significant risks to engineering projects, necessitating a systematic analysis of their risk factors. This study focuses on identifying and mapping these factors using a mixed-methods approach that integrates a qualitative literature review with scientometric analysis via Social Network Analysis (SNA). Through a meta-analysis of 81 peer-reviewed articles from Web of Science, Scopus, and ScienceDirect, the qualitative review establishes a comprehensive list and classification of 48 natural disaster risk factors, categorized into geological, climatic, hydrological, topographic, and biological groups, while providing a theoretical foundation. SNA complements this by quantifying co-occurrence frequencies, centrality metrics (degree, betweenness, and eigenvector), and network structures, revealing dynamic interactions, key influential factors, and research gaps—particularly in under-explored areas like hydrological hazards, extreme temperatures, lightning storms, and temperature variations—that qualitative methods alone might miss. This multi-perspective integration highlights discrepancies between theoretical discussions and practical applications, underscoring overlooked cascading effects. Findings emphasize the absence of an integrated model for all 48 factors, urging the development of a holistic predictive framework to bolster disaster resilience. Theoretically, the study offers a novel SNA-based quantification of factor importance and interrelations, addressing literature fragmentation. Practically, it guides project managers in prioritizing risks for optimized design, resource allocation, and prevention strategies. Future research should incorporate real-time data sources to refine this framework for enhanced risk management in engineering projects. Full article

In the context of the digital transition, office environments are increasingly shaped by flexibility, technological integration, and occupant-centered design. These transformations influence not only building operations but also the social dynamics and well-being of workers, thereby intersecting with the broader goals of socially sustainable design. To address this complexity, Building Management Systems (BMS) and Digital Twins must evolve from static automation to adaptive frameworks that recognize and respond to diverse workplace activities and social interactions. This study proposes a standardized taxonomy of office activities as a foundation for activity recognition and environment adaptation. A systematic literature review identified key activity categories and defining attributes, which were refined and validated through direct observations, diary logs, and semi-structured interviews in small, shared offices with open-plan workspaces. The resulting taxonomy comprises four main classes—Focused Work, Meetings, Shallow Work, and Resting—each defined by contextual attributes such as plannability, social interaction, number of participants, posture, modality, location, and duration. The framework supports the development of human-centric, situationally aware BMS capable of dynamically adjusting environmental conditions to promote comfort, well-being, and energy efficiency. By integrating user agendas and feedback, this approach contributes to more inclusive and socially sustainable work environments, aligning with the emerging paradigm of adaptive, human-oriented architecture. Full article

This study presents an artificial intelligence-based predictive framework as an efficient alternative to conventional analytical procedures for evaluating elastic–plastic thermal stresses in long functionally graded solid cylinders (FGSCs) subjected to uniform internal heat generation. A hybrid artificial neural network-based fuzzy logic (ANNBFL) model is developed to estimate dimensionless thermal load parameters at both the cylinder center and outer surface by learning from validated analytical reference solutions. The material properties, including yield strength, elastic modulus, thermal conductivity, and thermal expansion coefficient, are assumed to vary radially following a parabolic gradation law. Eight influential material parameters are incorporated as input variables to describe the coupled thermo-mechanical behavior of the FGSC. Multiple ANNBFL subnetworks are trained using analytically generated datasets and subsequently integrated into a unified prediction framework, enabling rapid and accurate stress field estimation without repeated analytical calculations. Model performance is systematically assessed by direct comparison with analytical solutions, demonstrating an overall prediction consistency of approximately 98.2%. The results confirm that the proposed ANNBFL approach provides a reliable, computationally efficient surrogate modeling tool for parametric evaluation and optimum material design of functionally graded cylindrical structures under thermal loading. Full article

The growing proportion of older adults has created significant societal pressure for sustainable, inclusive solutions that enhance health, autonomy, and well-being in old age. Smart elderly care has therefore emerged as a multidisciplinary research frontier at the intersection of technology, health, and social sustainability. This study provides a comprehensive systematic review to map and conceptualize its evolving landscape in the digital era. Following the PRISMA guidelines, 55 peer-reviewed articles published in the Web of Science database were analyzed using document co-citation analysis and natural language processing-based content analysis, utilizing CiteSpace and Leximancer for implementation. The findings reveal that existing studies have predominantly focused on technology acceptance and adoption among older adults, with quantitative approaches such as Structural Equation Modeling within the Technology Acceptance Model framework being most frequently used. Building on these insights, the review identifies five key directions for advancing sustainable wellbeing: (1) conceptual clarification and operationalization of smart elderly care, (2) theoretical integration across disciplines, (3) examination of influencing factors shaping user engagement, (4) evaluation of social and well-being outcomes, and (5) methodological and disciplinary diversification. By synthesizing fragmented knowledge into a coherent framework, this study contributes to the understanding of smart elderly care as a critical component of sustainable aging societies and lays the groundwork for future academic inquiry and policy innovation. Full article

Antimicrobial resistance threatens a new “dark age” in medical practice. Chronic antibiotic overuse has driven the rise in antimicrobial resistance and promoted the emergence of multidrug-resistant organisms. To address this problem, researchers have developed new approaches. Antimicrobials derived from bacteriophage, which are viruses that target bacteria, are promising candidates. Amongst these candidates, bacteriophage enzymes used in the viral replication cycle are of significant interest. Specifically, endolysins are used by bacteriophage to lyse the bacterial cell wall, leading to structural collapse and cell lysis. Researchers are increasingly applying these proteins externally to multidrug-resistant organisms as a novel antimicrobial treatment. Following this increased interest, many studies have presented protein engineering methods to further enhance the effectiveness of endolysins as antimicrobials. These methods include attachment of membrane-permeabilizing peptides, domain-swapping, and catalytic-site modification. Recent advances in all three fields have seen the implementation of tools like novel in silico design pipelines and library-based screening methods. This review summarizes these recent advances in the rapidly developing field of endolysin engineering and discusses potential future directions in this field. Full article

Crosstalk between elements in ultrasonic transducer arrays significantly degrades image quality in medical ultrasound systems by introducing noise and reducing spatial resolution. This review provides a comprehensive overview of the origins of crosstalk—acoustic, mechanical, and electrical—and the main characterization methods used to analyze it, including direct measurements, impedance analysis, finite element modeling, and equivalent circuit approaches. Emphasis is placed on recent advances in passive and active mitigation strategies, such as material coatings, structural decoupling, phononic crystals, adaptive filtering, and impedance matching. A key finding is that the optimal crosstalk reduction method depends strongly on the transducer technology employed—whether CMUT, PMUT, or bulk PZT. The review highlights the importance of tailoring mitigation techniques to the physical properties and operating conditions of each technology. By synthesizing current knowledge and identifying remaining challenges—particularly the role of filler material losses—this work offers a solid foundation for the development of next-generation ultrasound arrays with enhanced imaging performance. Full article