Search Results (17)

Background: Embodied artificial intelligence (EAI), integrating advanced AI algorithms with robotic platforms capable of sensing, planning, and acting, has emerged as a transformative approach in healthcare delivery. This systematic review synthesizes evidence on robotic perception, decision-making, and clinical impact of EAI systems in healthcare settings. Methods: Following PRISMA 2020 guidelines, we searched PubMed/MEDLINE, Scopus, Web of Science, IEEE Xplore, and ACM Digital Library for studies published between January 2020 and August 2025. Seventeen studies met eligibility criteria, spanning four domains: surgical assistance, rehabilitation, hospital logistics, and telepresence. The protocol was prospectively registered in PROSPERO under ID: CRD420261285936. Results: Perception architectures predominantly employed multimodal sensor fusion, combining vision with force/torque, depth, and physiological signals. Decision-making approaches included imitation learning, reinforcement learning, and hybrid symbolic-neural control. Key findings indicate that surgical robots demonstrated consistency advantages in specific experimental tasks, rehabilitation robotics produced statistically significant improvements (SMD = 0.29) across 396 randomized controlled trials, and both logistics and telepresence systems achieved very high operational success levels. Nonetheless, important barriers remain, including limited external validation, small sample sizes, and insufficient cost-effectiveness data. Conclusions: Future research should prioritize standardized benchmarks, prospective multicenter trials, and patient-centered outcome measures to facilitate clinical translation of EAI technologies. Full article

Submarine structures are typically classified into pressure hulls and non-pressure hulls. The pressure hull is a critical component designed to withstand external pressure at operational depths while ensuring internal structural integrity. It is generally composed of ring frames and bulkheads. However, in modern large-scale submarines, bulkheads are often replaced with deep frames to improve equipment layout flexibility. Deep frames serve as essential structural reinforcements, compensating for the loss of stiffness due to the absence of bulkheads. Despite their importance, research on the design of deep frames remains scarce, and in the absence of established design standards, engineers rely on conservative approaches based on practical experience. Therefore, the objective of this study is to propose initial scantling formulas for deep frames in submarine pressure hulls based on finite element analysis (FEA) and parametric studies. To this end, six design cases reflecting actual ship design ranges were selected, and the structural integrity of the pressure hull ring frames was verified through material and geometric nonlinear analysis using ANSYS Mechanical APDL. Subsequently, a total of 82,440 parametric studies were conducted with the reinforced shell thickness, effective length, height and thickness of the deep frame web, and the width and thickness of the deep frame flange as variables. As a result, the proposed formulas satisfied all Validation cases in terms of structural integrity and were found to be applicable within the section length range of 1.5 to 2.0 times the pressure hull diameter. The results of this study are expected to be effectively utilized in the initial design of deep frames for submarine pressure hulls. Full article

Externally bonded carbon-fiber-reinforced polymer (CFRP) can increase the flexural capacity of steel beams, but the benefit is often limited by the performance of the adhesive interface. This study develops and validates a three-dimensional finite-element model (FEM) with an explicit cohesive-zone representation of the adhesive layer. It reproduced benchmark four-point bending tests in terms of peak load, corresponding mid-span deflection, and the transition from end/intermediate debonding to laminate rupture. A one-factor-at-a-time parametric analysis is carried out to examine the influence of (i) member geometry (beam depth; flange and web thickness), (ii) CFRP configuration (bonded length; laminate thickness), and (iii) bond quality (cohesive normal strength). Within the ranges studied, cohesive strength and bonded length are the primary variables controlling both capacity and failure mode: strengths below about 25 MPa and short plates lead to debonding-governed response. Increasing strength to around 27 MPa and bonded length to 650–700 mm delays debonding, promotes CFRP rupture, and produces the largest incremental gains in peak load, while further increases in length give smaller additional gains. Increasing laminate thickness and steel depth or flange/web thickness always raises peak load, but under baseline bond conditions failure remains debonding and the added material is only partially mobilized. When cohesive strength is increased above the threshold, additional CFRP thickness becomes more effective. A linear regression model is fitted to the FEM dataset to express peak load as a function of bonded length, cohesive strength, laminate thickness, and steel dimensions, and is complemented by a failure-mode map and a cost–capacity chart based on material quantities. Together, these results provide quantitative trends and simple relations that can support preliminary design of CFRP-strengthened steel beams for similar configurations. Full article

The editorial policies of science journals have an impact on access to scientific knowledge. One of the most effective ways to share knowledge with the entire society is to offer it free of charge. Considering the international recognition of Scopus and Web of Science, this study analyses 28 scientific journals in the field of communication that are indexed under the “Communication” category in both databases in order to review their editorial decisions regarding the dissemination of articles they publish. By taking a descriptive approach, the authors have examined the inner workings and design, as well as aspects related to ethics and transparency, as key components of this policy. The findings indicate that most journals are influenced by digital publishing platforms and that various features examined in this study are offered by these platforms by default. This is especially true in terms of design, which simultaneously enables yet influences each journal’s editorial policy. Together with the need for financial support and adequate human resources, this situation makes it difficult to implement an editorial policy free of external encroachment. This article concludes by emphasising the importance of establishing editorial policies that promote open access as a standard practice, thereby reinforcing the democratisation of access to scientific knowledge. It is recommended to strengthen institutional support for journals operating under the diamond model, promote their visibility and thematic specialisation, enhance technical and visual aspects, and clearly articulate ethical commitments within their editorial policies. In short, this analysis provides a comprehensive overview of both strengths and areas of improvement, offering recommendations to help these journals optimise their contribution to the global academic ecosystem. Full article

Critical-sized bone defects (CSBDs) are injuries that exceed the body’s natural capacity for repair and require external intervention. These defects are particularly challenging in the mandible, often resulting from trauma, tumor resection, or implant-related complications. Effective treatment involves scaffold designs that support vascularization, bone formation, and sufficient mechanical strength. This systematic review aims to assess whether ceramic-based scaffold properties, including porosity, pore size, and macroscopic characteristics, improve vascularization, bone formation, and the mechanical properties in the treatment of CSBDs in large animal models. A search of databases (PubMed, Embase, and Web of Science) identified 11 in vivo studies involving CSBDs (>2 cm), ceramic scaffolds, and histological analysis. Findings indicate that scaffolds with porosity exceeding 50% yield optimal outcomes by striking a balance between cell infiltration and mechanical stability. Pore sizes ranging from 300 μm to 700 μm are ideal for vascularization and bone ingrowth. Three-dimensional (3D) printing shows promise in creating scaffolds with precise and reproducible features. However, the studies varied significantly in their methodologies and outcomes, with no consensus on the optimal scaffold properties for mandibular CSBDs. Scaffold porosity and pore size play key roles in promoting vascularization and bone regeneration. Various animal models reinforce this finding, suggesting that scaffold architecture is crucial for biological integration and functional outcomes. This review highlights the importance of standardized research protocols and clear design criteria in enhancing the success of bone regeneration. Future research should investigate emerging biomaterials and new scaffold technologies to overcome current limitations in clinical applications. Full article

As public institutions increasingly adopt AI-driven virtual assistants to support transparency and citizen engagement, the need for explainable, accurate, and context-aware language systems becomes vital. While traditional retrieval-augmented generation (RAG) frameworks effectively integrate external knowledge into Large Language Models (LLMs), their reliance on flat, unstructured document retrieval limits multi-hop reasoning and interpretability, especially with complex, structured e-government datasets. This study introduces a modular, extensible, multi-agent graph retrieval-augmented generation (GraphRAG) framework designed to enhance policy-focused question answering. This research aims to provide an overview of hybrid multi-agent GraphRAG architecture designed for operational deployment in e-government settings to support explainable AI systems. The study focuses on how the hybrid integration of standard RAG, embedding-based retrieval, real-time web search, and LLM-generated structured Graphs can optimize knowledge discovery from public e-government data, thereby reinforcing factual grounding, reducing hallucinations, and enhancing the quality of complex responses. To validate the proposed approach, we implement and evaluate the framework using the European Commission’s Press Corner as a data source, constructing graph-based knowledge representations and embeddings, and incorporating web search. This work establishes a reproducible blueprint for deploying AI systems in e-government that require structured reasoning in comprehensive and factually accurate question answering. Full article

The composite primary structures of railway vehicles endure not only mechanical loads including tension, compression, bending, and torsion, but also external impacts, such as by the crushed stone in ballast. In the present study, the low-velocity impact response of preloaded hybrid composite laminates with different thicknesses is examined using a finite element method based on a progressive damage model. The hybrid plate consists of carbon fiber-reinforced unidirectional and woven prepregs. The progressive damage model, based on the 3D Hashin model, is validated by experiments on hybrid laminate, and further compared with the post-impact appearance obtained from CT scans. Preloading, considered to be tensile, compressive, or shear, corresponds to different positions in a bending beam with flanges and a web. Finally, the effects of impact energy, preloading, thickness, and impact angle on the dynamic response are analyzed, with an emphasis on new results and failure mechanism analysis comparing the influence of preloads under a given impact energy and different thicknesses. Full article

Introduction: A limited March 2024 Google Scholar search regarding COVID-19 redeployment to emergency care in fourteen medical specialties found no oncologist returns. Identifying oncologist redeployment through a scoping review of peer-reviewed research from several databases investigates this anomaly. Method: Searched are Web of Science, Scopus, PubMed, OVID, Google Scholar, and the Cochrane COVID-19 Study Register with the keywords “burnout AND COVID-19 AND emergencies AND oncologists” concerning the emergency experienced, their burnout response, and patient outcome. Results: Following the PRISMA scoping review process, the assessment is of eight reports from 17,848 results. The finding is that there was a redeployment of oncologists to emergency care. It was defined in various ways and caused oncologist burnout for several internally and externally directed reasons. These reasons negatively affected patient outcomes, contributing to the adoption of different coping techniques by oncologists. Oncologists, uniquely among medical specialists, experienced burnout regarding empathy for the increased mortality risk of their patients and the diminished doctor/patient bond. They also lacked symptom-directed coping. Conclusion: The results of this study may reinforce to oncologists the importance of their doctor/patient dyad and of initiating coping strategies that include symptom-directed health improvement techniques when the redeployment of oncologists is again to emergency care. Full article

The increasing demand for energy efficiency and the integration of renewable energy sources have become crucial for sustainability in modern campuses. This work presents a smart green energy management system (SGEMS) that integrates a machine learning model and reinforcement learning (RL) to optimize energy consumption and solar generation across a green campus. Using historical data from three campus buildings, we developed a predictive model to forecast short-term energy consumption and solar generation. The XGBoost algorithm, combined with RL, demonstrated superior performance in predicting energy consumption and generation, outperforming other models with a root mean square error (RMSE) of $14.72$, a mean absolute error (MAE) of $12.00$, and a mean absolute percentage error (MAPE) of $2.18\%$. This work proposes a web-based interface for real-time energy monitoring and decision-making, helping users forecast power shortages and manage energy usage effectively. The proposed approach provides a scalable solution for campuses aiming to reduce reliance on external grids and increase energy efficiency, setting a benchmark for future green campus initiatives. Full article

Cardiovascular diseases (CVDs) remain a major global health challenge and a leading cause of mortality, highlighting the need for improved predictive models. We introduce an innovative agent-based dynamic simulation technique that enhances our AI models’ capacity to predict CVD progression. This method simulates individual patient responses to various cardiovascular risk factors, improving prediction accuracy and detail. Also, by incorporating an ensemble learning model and interface of web application in the context of CVD prediction, we developed an AI dashboard-based model to enhance the accuracy of disease prediction and provide a user-friendly app. The performance of traditional algorithms was notable, with Ensemble learning and XGBoost achieving accuracies of 91% and 95%, respectively. A significant aspect of our research was the integration of these models into a streamlit-based interface, enhancing user accessibility and experience. The streamlit application achieved a predictive accuracy of 97%, demonstrating the efficacy of combining advanced AI techniques with user-centered web applications in medical prediction scenarios. This 97% confidence level was evaluated by Brier score and calibration curve. The design of the streamlit application facilitates seamless interaction between complex ML models and end-users, including clinicians and patients, supporting its use in real-time clinical settings. While the study offers new insights into AI-driven CVD prediction, we acknowledge limitations such as the dataset size. In our research, we have successfully validated our predictive proposed methodology against an external clinical setting, demonstrating its robustness and accuracy in a real-world fixture. The validation process confirmed the model’s efficacy in the early detection of CVDs, reinforcing its potential for integration into clinical workflows to aid in proactive patient care and management. Future research directions include expanding the dataset, exploring additional algorithms, and conducting clinical trials to validate our findings. This research provides a valuable foundation for future studies, aiming to make significant strides against CVDs. Full article

To study the mechanical performance of bolted connections with different structural forms of reinforced rings, based on the results of monotonic loading tests on two bolted connections between a concrete-filled steel tubular column and a steel beam with an outer reinforcing ring, this article uses ABAQUS v.2020 software to establish a three-dimensional refined finite element analysis model of such connections using appropriate constitutive models for concrete and steel. Subsequently, the effect of the dimensions of the steel beam, reinforcing ring, and cover plate on the load-bearing properties and the failure mechanism of the connections is investigated, and the numerical model is consistent with the verification test results. Then, the numerical simulations comparing bolted exterior reinforced rings under seven different construction measures (i.e., number of bolts, stiffeners) based on a conventional welded exterior reinforced rings with rigid connections (i.e., CGJ) are standardized. The research results indicate that when four rows of bolts are introduced on exterior reinforced rings, the web of steel beam is welded with stiffeners, and the top and bottom reinforced rings are also added with stiffeners; this bolted connection with an external reinforcing ring (i.e., GZ-7) can achieve the rigidity and load-bearing capacity of a fully welded external reinforcing ring rigid connection. At the same time, the reinforcing ring plate is bolted to the flange of the steel beam, and the force transmission path at the connection is changed to avoid the brittle fracture easily caused by the welded flange joints. It is also in line with the development trend of sustainable construction of “assembly” and “disassembly”. Full article

Structurally deficient bridges are commonly retrofitted using conventional methodologies, including reinforced concrete, steel jackets, and fiber-reinforced polymers. Although these retrofit methods aim to improve structural performance, exposure to aggressive environments may undermine the durability performance of the retrofit material. More recently, ultra-high-performance concrete (UHPC) has provided an alternative to conventional construction methods, with its superior material characteristics favoring its use in retrofit applications. In this study, a large-scale reinforced concrete (RC) T-beam is constructed and artificially damaged. The T-beam is then retrofitted with an external envelope of UHPC on all faces. Sandblasting is introduced to the surface, providing partially exposed reinforcement in the T-beam to simulate material deterioration. Additional reinforcement is placed in the web and flange, followed by casting the enveloping layer of UHPC around the specimen. The feasibility of this method is discussed, and the structural performance of the beam is assessed by subjecting the beam to cyclic and ultimate flexural loading. This paper presents the results of cyclic and ultimate testing on the RC-UHPC composite T-beam regarding load–displacement, failure mode, and strain responses. The retrofitted T-beam specimen is subjected to a cyclic loading range of 131 kN for 1.576 million cycles. Despite no visible cracks in the cyclic testing, the specimen experiences a 12.22% degradation in stiffness. During the ultimate flexural testing, the specimen shows no relative slip between the two concretes, and the typical flexural failure mode is observed. By increasing the longitudinal reinforcement ratio in the web, the failure mode can shift from localized cracking, predominantly observed in the UHPC shell, toward a more distributed cracking pattern along the length of the beam, which is similar to conventional reinforced concrete beams. Full article

Renovation, restoration, remodeling, refurbishment, and the retrofitting of buildings often imply applying forces (i.e., concentrated loads) to beams that before were subjected to distributed loads only. In the case of reinforced concrete structures, the new condition causes a beam to bear a concentrated load with the crack pattern that resulted from the distributed loads which had acted before. If the concentrated load is applied at or near the beam’s midspan, the new shear demand reaches the maximum where cracks are vertical or quasi-vertical, and where inclined bars are not common according to any standards. So, the actual shear capacity can be substantially lower than new shear demand due to the concentrated load. This paper focuses on reinforced concrete beams whose load distribution has to be changed from distributed to concentrated and presents a design method to bring the beam’s shear capacity up to the new demand. The method consists of applying fiber composites (fiber-reinforced polymers or fiber-reinforced cementitious material) with fibers at an angle of 45° bonded to the beam’s web. This kind of external reinforcement arrangement has to comply with some practical measures, which are presented as well. The paper also provides the analytical model that predicts the concentrated load-carrying capacity of a beam in the strengthened state. The model accounts for the crack’s verticality, which nullifies the contributions of steel stirrups, aggregate interlock, and dowel action, and for the effective bond length of each fiber, which depends on the distance between the ends of the fiber and the crack it crosses. Full article

To accommodate utilities in buildings, different sizes of openings are provided in the web of reinforced concrete deep beams, which cause reductions in the beam strength and stiffness. This paper aims to investigate experimentally and numerically the effectiveness of using carbon fiber reinforced polymer (CFRP) strips, as a strengthening technique, to externally strengthen reinforced concrete continuous deep beams (RCCDBs) with large openings. The experimental work included testing three RCCDBs under five-point bending. A reference specimen was prepared without openings to explore the reductions in strength and stiffness after providing large openings. Openings were created symmetrically at the center of spans of the other specimens to represent 40% of the overall beam depth. Moreover, finite elements (FE) analysis was validated using the experimental results to conduct a parametric study on RCCDBs strengthened with CFRP strips. The results confirmed reductions in the ultimate load by 21% and 7% for the un-strengthened and strengthened specimens, respectively, due to the large openings. Although the large openings caused reductions in capacities, the CFRP strips limited the deterioration by enhancing the specimen capacity by 17% relative to the un-strengthened one. Full article

In this study, the cyclic behavior of reinforced concrete (RC) beam with openings strengthened using carbon fiber-reinforced polymers (FRPs) was experimentally investigated. Seven rectangular RC beams were cast and strengthened through external bonding of carbon fiber-reinforced polymer (CFRP) sheets around the beam web opening with different orientations to evaluate the maximum resistance, secant stiffness, strength degradation, ductility, energy dissipation capacity and behavior of the specimens’ failure mode under cyclic load. One solid beam without an opening (i.e., control specimen) and six beams constructed with circular web openings typically located in the middle of the beam and adjacent to the supports were used in the experiments. Among the six specimens with opening configuration, two beams were unstrengthened, and the remaining four specimens were strengthened with two layers of FRP sheets with vertical and inclined scheme orientation. Numerical studies were performed on ABAQUS software, and finite element modelling analysis results were verified through experiments. Results demonstrated that the use of FRP sheets has a significant effect on the cyclic behavior of RC beams, thereby improving the maximum strength and ultimate displacement to approximately 66.67% and 77.14%, respectively. The validated finite element models serve as a numerical platform to apply beneficial parametric studies, where the effects of opening size and bond length are investigated. Full article