Search Results (2,007)

Endotracheal prosthesis placement is employed as a therapeutic intervention for tracheal lesions in cases where conventional surgical approaches are not feasible. The learning curve for endotracheal stent placement can vary depending on the type of stent, the training environment, and the clinician’s prior experience; however, it is generally considered moderately complex. Inadequate practice can have serious consequences, as the procedure involves a critical area such as the airway. The main risks and complications associated with inadequate technique or improper execution can include stent migration, formation of granulation tissue or hyperplasia, tracheal or pulmonary infection, obstruction or fracture of the stent, hemorrhage and tracheal perforation, among others. The purpose of the present study is to summarize important information and evaluate the role of different material features in the 3D printing manufacturing of an appropriate tracheobronchial medical device, which should be as appropriate as possible to facilitate placement during surgical practice. A complex stent design was fabricated using three different biodegradable materials, polycaprolactone (PCL), polydioxanone (PDO), and polymer blend of polylactic acid/polycaprolactone (PLA/PCL), through additive manufacturing, specifically fused filament fabrication (FFF)3D printing. Parameter optimization of the 3D printing process was required for each material to achieve an adequate geometric quality of the stent. Experimental analyses were conducted to characterize the mechanical properties of the printed stents. Flexural strength and radial compression resistance were evaluated, with particular emphasis on radial force due to its clinical relevance in preventing collapse after implantation in the trachea. The results provide valuable insights into how material selection could influence device behavior during placement to support surgical requirements. Full article

Rice membrane-covered cultivation offers notable agronomic advantages, including effective weed suppression and improved moisture retention. However, current mechanized approaches remain constrained by high labor requirements, low operational efficiency, and the inherent fragility of biodegradable membranes. To address these limitations, this study integrates a high-speed synchronous membrane-covering device, governed by a PSO-Fuzzy PID control algorithm, into a conventional rice transplanter. This integration enables precise coordination between membrane-laying and transplanting operations. The mechanical properties of the membranes were analyzed, and a tension evaluation model was developed considering structural parameters and roll diameter variation. Experimental tests on three biodegradable membranes revealed an average thickness of 0.012 mm, a longitudinal tensile force of 0.57 N, and a tensile strength of 2.85 N/mm. The PSO algorithm was employed to optimize fuzzy PID parameters (K = 5.3095, K_p = 10.6981, K_i = 0.0100, K_d = 8.2892), achieving adaptive synchronization between membrane output speed and transplanter travel speed. Simulation results demonstrated that the PSO-Fuzzy PID reduced rise time by 53.13%, stabilization time by 90.58%, and overshoot by 3.3% compared with the conventional PID. In addition, a dedicated test bench for the membrane-covering device was designed and fabricated. Orthogonal experiments determined the optimal parameters for the speed-measurement system: a membrane pressure of 5.000 N, a roller width of 28.506 mm, and a placement angle of 0.690°. Under these conditions, the minimum membrane-stretching tension was 0.55 N, and the rotational speed error was 0.359%. Field tests indicated a synchronization error below 1.00%, a membrane-width variation rate below 1.50%, and strong anti-interference capability. The proposed device provides an effective solution for intelligent and fully mechanized rice transplanting. Full article

Background: Rehabilitation of atrophic posterior mandibles using dental implants is often complicated by anatomical limitations, particularly the proximity of the inferior alveolar nerve (IAN). Techniques such as IAN lateralization and transposition enable implant placement but are associated with neurosensory disturbances (NSDs). This systematic review and meta-analysis aimed to assess the incidence, duration, and predictors of NSDs following IAN repositioning for implant placement and to evaluate the effectiveness of adjunctive methods like piezo-surgery and platelet-rich fibrin (PRF) in minimizing complications. Methods: Following PRISMA 2020 guidelines, a comprehensive search of electronic databases and gray literature identified 20 studies, including randomized controlled trials, prospective cohorts, and retrospective analyses published between 2009 and 2024. Outcomes analyzed included incidence of NSDs, recovery rates, implant stability quotient (ISQ), marginal bone loss, and implant success rates. Meta-analysis was performed using RevMan 5.3 software, with heterogeneity and publication bias assessed using standard Cochrane tools. Results: Transient NSDs occurred in 15–40% of cases, with higher rates observed in transposition techniques. Most patients experienced recovery within 6 months. Piezoelectric surgery significantly reduced the incidence and duration of NSDs compared to rotary instruments. Meta-analysis revealed no statistically significant differences between lateralization and transposition techniques in ISQ, marginal bone loss, success rate, or NSDs at 3 months (p > 0.05). PRF was associated with accelerated nerve recovery. IAN repositioning is effective for implant placement in atrophic mandibles with a risk of transient NSDs. Conclusions: Lateralization combined with piezo-surgery and PRF shows favorable outcomes in minimizing nerve injury and optimizing implant success. The PROSPERO registration code is as follows: CRD420251086835. Full article

As the IMO and the EU strengthen carbon emission regulations, eco-friendly voyage planning is increasingly recognized by ship owners as one of the most important performance factors of the vessel fleet. The eco-friendly voyage planning aims to reduce carbon emissions and fuel consumption while satisfying voyage constraints. In this study, a novel route waypoint optimization method is proposed, which combines a fuel consumption forecasting model based on the Transformer and a Proximal Policy Optimization (PPO) algorithm for adaptive waypoint planning. The developed framework suggests a multi-objective methodology unlike the traditional approaches where a single objective is sought after, which characterizes fuel efficiency against navigational safety and operational simplicity. The methodology consists of three sequential phases. First, the transformer model is employed to predict ship fuel consumption using navigational and environmental data. Next, the predicted consumption values are utilized as a reward function in a PPO-based reinforcement learning framework to generate fuel-efficient routes. Finally, the number and placement of waypoints are further optimized with respect to terrain and bathymetric constraints, improving the practicality and safety of the navigational plan. The results show that the proposed method could decrease average fuel consumption by up to 11.33% across three real-world case studies: Busan–Rotterdam, Busan–Los Angeles, and Mokpo–Houston, compared to AIS-based routes. The transformer model outperformed Long Short-Term Memory (LSTM) and Random Forest baselines with the highest prediction accuracy, achieving an R² score of 86.75%. This study is the first to incorporate transformer-based forecasting into reinforcement learning for maritime route planning and demonstrates how the method adaptively controls waypoint density in response to environmental and geographical conditions. These results support the practical application of the approach in smart ship navigation systems aligned with IMO’s decarbonization goals. Full article

The majority (70–85%) of biliary strictures—a narrowing of the bile ducts—are associated with malignancy, particularly pancreatic adenocarcinoma and cholangiocarcinoma, and are unresectable at presentation. Management options for distal biliary obstruction depend on several clinical factors, including the underlying cause and the location and complexity of the stricture. Endoscopic stent placement has lower morbidity and mortality rates compared with more invasive surgical options and is usually the first-line treatment to clear the blockage or allow the bile duct to drain internally. There are several stenting techniques to treat stenosis, but the current quality of evidence regarding the approach for different etiologies mostly ranges from moderate to low, and there is a lack of patient-specific guidelines regarding treatment decisions and for optimizing clinical outcomes. This review describes recent developments in stent technology and distal biliary stricture management, particularly endoscopic ultrasonography-guided drainage, and synthesizes findings from clinical trials and emerging research to highlight the role of patient-specific factors, such as anatomy and comorbidities, in tailoring treatment strategies. The integration of trial evidence into clinical practice paves the way for more effective and personalized care while addressing current knowledge gaps. Future research directions are identified to advance the development of innovative stent designs, enhance the quality of life, and improve long-term outcomes for patients with biliary strictures. Full article

Background: Immediate implant therapy is a highly effective solution for replacing non-restorable teeth, particularly in the esthetic zone, where achieving optimal results can be challenging. In this area, even small imperfections can significantly affect a patient’s satisfaction due to the high visibility of the teeth involved. This narrative review provides an overview of findings from case reports and systematic reviews that highlight the success of immediate implant therapy in the esthetic zone. Additionally, it includes a case illustration to emphasize how meticulous planning, combined with advanced techniques, can achieve successful outcomes. Methods: A comprehensive literature review was conducted to evaluate the effectiveness of immediate implant placement and loading for non-restorable teeth in the esthetic zone. Key factors identified for success include atraumatic tooth extraction, precise implant placement, and effective soft tissue management to achieve natural esthetics and long-term stability. To illustrate these principles, the review features a clinical case involving the replacement of a maxillary right central incisor rendered non-restorable due to trauma. Treatment incorporated advanced digital planning, atraumatic extraction, immediate implant placement, and provisionalization. The final restoration involved soft tissue contouring and ceramic veneers on adjacent teeth, enhancing the patient’s overall smile and confidence. Results: Evidence from the literature indicates that well-planned immediate implant therapy achieves high success rates and long-term stability. In the clinical case presented, the workflow met the patient’s esthetic and functional needs, resulting in a natural, harmonious smile, and improved patient satisfaction. Conclusions: Immediate implant therapy in the esthetic zone is highly effective when critical considerations—such as bone preservation, guided implant placement, soft tissue shaping, and appropriate restoration—are meticulously addressed. Advanced techniques and careful planning are essential for fulfilling both esthetic and functional patient needs, ultimately delivering predictable and successful outcomes. Full article

This paper investigates the inverse reconstruction of temperature fields under both steady-state and transient heat conduction scenarios. The central contribution lies in the structured development and validation of the Gappy Clustering-based Proper Orthogonal Decomposition (Gappy C-POD) method—an approach that, despite its conceptual origin alongside the clustering-based dimensionality reduction method guided by POD structures (C-POD), had previously lacked an explicit algorithmic framework or experimental validation. To this end, the study constructs a comprehensive solution framework that integrates sparse sensor layout optimization with data-driven field reconstruction techniques. Numerical models incorporating multiple internal heat sources and heterogeneous boundary conditions are solved using the finite difference method. Multiple sensor layout strategies—including random selection, S-OPT, the Correlation Coefficient Filtering Method (CCFM), and uniform sampling—are evaluated in conjunction with database generation techniques such as Latin Hypercube sampling, Sobol sequences, and maximum–minimum distance sampling. The experimental results demonstrate that both Gappy POD and Gappy C-POD exhibit strong robustness in low-modal scenarios (1–5 modes), with Gappy C-POD—when combined with the CCFM and maximum distance sampling—achieving the best reconstruction stability. In contrast, while POD-MLP and POD-RBF perform well at higher modal numbers (>10), they show increased sensitivity to sensor configuration and sample size. This research not only introduces the first complete implementation of the Gappy C-POD methodology but also provides a systematic evaluation of reconstruction performance across diverse sensor placement strategies and reconstruction algorithms. The results offer novel methodological insights into the integration of data-driven modeling and sensor network design for solving inverse temperature field problems in complex thermal environments. Full article

Background/Objectives: An evidence-based list of key variables regarding jejunoileal atresia (JIA) care needs to be established to enable quality evaluation and optimization of its care. The aim of this study is to provide an overview of reported patient, treatment, and outcome variables for JIA as documented in recent literature. This list has not been developed previously and will be the foundation for a JIA quality indicator set of the European Pediatric Surgery Audit (EPSA). Methods: A systematic review of the literature on the primary care path of JIA, published between 2013 and 2023, was conducted following the PRISMA guidelines. All relevant patient characteristics, parameters regarding JIA treatment, and outcomes were extracted from the included publications. Results: A total of 844 variables were extracted from 94 included articles. One hundred fifty-seven parameters were mentioned in more than 5% of publications. The most mentioned patient characteristics were sex (86%), gestational age (71%), and associated anomalies (66%). The most mentioned treatment parameters were stoma placement (34%), primary anastomosis (41%), and time to full enteral nutrition (24%). Most mentioned outcomes were mortality (70%), length of hospital stay (55%), and complications (60%). Conclusions: This study created an overview of reported patient characteristics, treatment, and outcome variables regarding the treatment of JIA. A focus on the short-term management and outcomes of JIA was observed; frequently discussed topics were perioperative management, surgical techniques, and feeding management. Our results will serve as the foundation for a Delphi study to develop a core indicator set for JIA, enabling benchmarking and measurement of quality of care. Full article

Background/Objectives: Out-of-hospital cardiac arrest (OHCA) remains a major public health challenge, with survival rates significantly dependent on early defibrillation. In Bialystok, Poland, the bystander usage rate of automated external defibrillators (AEDs) is extremely low, and the current distribution of public-access AEDs may not support optimal response times. The aim of this study was to identify an effective AED placement strategy using spatial analysis. Methods: We retrospectively analyzed 49,649 emergency dispatch records from 2018 to 2019, identifying 787 patients with OHCA within Bialystok’s city limits. After excluding ineligible records, 766 cases were geolocated and subjected to cluster analysis using the K-means algorithm. The goal was to determine optimal AED locations based on the geographic distribution of OHCA cases in both public and residential settings. Results: AEDs were used in only 0.51% of all cases of OHCA. Most cardiac arrests occurred in private homes (80.05% of cases). Cluster analysis identified 18 to 36 optimal AED locations, revealing significant mismatches with the current AED network. Notably, grocery store chain “PSS Spolem” emerged as an ideal AED deployment partner due to alignment with identified high-incidence clusters. Conclusions: The current AED distribution in Bialystok is inadequate for an effective response to OHCA. Geographic cluster analysis can significantly improve placement strategies. Priority should be given to residential areas and commonly accessed sites. Enhanced public education, a national AED registry, and improved accessibility are essential for increasing AED use and survival rates. Full article

In this work we present the shape optimization of a 2000 L water tank placed behind the rear axle of a forestry skidder. The main criterion is the static stability of the vehicle. The purpose of the research is to decrease the impact of the tank on stability of the vehicle. The stability is determined in the form of distances of vectors of a stability triangle and a gravity vector. The tank is divided into small elements and their impact on stability is evaluated independently. Then, the gravity vector, placed in the center of gravity of the vehicle with the tank, combines the gravities of the vehicle and the tank composed of as many elements as required for the desired volume. The Python 3.13 programming language is used to implement the solution. The results for various shapes of the tank are displayed in the form of heatmaps. A slope angle of 20 degrees is used for the analysis. The results show that the longitudinal or lateral stability can be improved by shape modifications of the tank. The most interesting output is the final shape of the tank that improves terrain accessibility of the vehicle. The optimization method is universal and can also be used for different vehicles, tank placements and also auxiliary devices added in general positions. Full article

The large-scale integration of renewable energy and the high penetration of power electronic devices have led to a significant reduction in system inertia and short-circuit capacity. This is particularly manifested in the form of insufficient multiple renewable energy stations short-circuit ratio (MRSCR) and transient overvoltage issues following severe disturbances such as AC and DC faults, which greatly limit the power transfer capability of large renewable energy bases. To effectively mitigate these challenges, this paper proposes an optimal synchronous condenser deployment method tailored for large-scale renewable energy bases. The proposed mathematical model supports a hybrid centralized and distributed configuration of synchronous condensers with various capacities and manufacturers while considering practical engineering constraints such as short-circuit ratio, transient overvoltage, and available bays in renewable energy stations. A practical decomposition and iterative computation strategy is introduced to reduce the computational burden of transient stability simulations. Case studies based on a real-world system verify the effectiveness of the proposed method in determining the optimal configuration of synchronous condensers. The results demonstrate significant improvements in grid strength (MRSCR) and suppression of transient overvoltages, thereby enhancing the stability and transfer capability of renewable energy bases in weak-grid environments. Full article

Maintaining air quality in operating rooms is critical for infection control and patient safety. Particulate matter, originating from surgical instruments, personnel, and external sources, is influenced by airflow patterns and ventilation efficiency. This study employs Computational Fluid Dynamics (CFD) simulations using Simcenter STAR-CCM+ 2410 to analyze airflow and particulate behavior in a surgical-grade operating room. A steady-state solver with the k–ε turbulence model was used to replicate airflow, while the Lagrangian multiphase method simulated particle trajectories (0.5 µm, 1 µm, and 5 µm). The simulation results demonstrated close agreement with the experimental data, with average errors of 17.3%, 17.7%, and 39.7% for 0.5 µm, 1 µm, and 5 µm particles, respectively. These error margins are considered acceptable given the device’s 10% measurement sensitivity and the observed experimental asymmetry—attributable to equipment placement—which resulted in variations of 17.2%, 18.0%, and 26.5% at corresponding symmetric points. Collectively, these findings support the validity of the simulation model in accurately predicting particulate transport and deposition within the operating room environment. Findings confirm that optimizing airflow can achieve ISO Class 7 cleanroom standards and highlight the potential for future studies incorporating dynamic elements, such as personnel movement and equipment placement, to further improve contamination control in critical environments. Full article

This study presents a data-driven approach to predict the three-dimensional distribution of sand-rich channels in hydrocarbon reservoirs using well log data, aiming to optimize site selection for Underground Thermal Energy Storage (UTES) and manage hot and cold well pairs effectively. Leveraging detailed petrophysical datasets from 128 hydrocarbon exploration wells within the Szolnok Formation in southern Hungary, the developed machine-learning workflow—combining XGBoost regression and spatial residual correction—accurately delineated permeable channel systems suitable for thermal energy injection and extraction. The model achieved robust predictive performance (R² = 0.92; RMSE = 0.24), and correlation analyses confirmed significant relationships between predicted channels and sand content and shale content. Clearly identified high-permeability channel zones facilitated strategic well placement, significantly reducing the risk of premature thermal breakthrough and enhancing the reliability and efficiency of UTES operations. Full article

As cities densify, deep underground infrastructure construction such as mass rapid transit (MRT) systems increasingly demand smarter, digitalized, and more sustainable approaches. RC diaphragm walls, essential to these systems, present challenges due to complex rebar configurations, spatial constraints, and high material usage and waste, factors that contribute significantly to carbon emissions. This study presents an AI-assisted rebar optimization framework to improve constructability and reduce waste in MRT-related diaphragm wall construction. The framework integrates the BIM concept with a custom greedy hybrid Python-based metaheuristic algorithm based on the WOA, enabling optimization through special-length rebar allocation and strategic coupler placement. Unlike conventional approaches reliant on stock-length rebars and lap splicing, this approach incorporates constructability constraints and reinforcement continuity into the optimization process. Applied to a high-density MRT project in Singapore, it demonstrated reductions of 19.76% in rebar usage, 84.57% in cutting waste, 17.4% in carbon emissions, and 14.57% in construction cost. By aligning digital intelligence with practical construction requirements, the proposed framework supports smart city goals through resource-efficient practices, construction innovation, and urban infrastructure decarbonization. Full article

This study presents a comparative analysis of two double-toggle drive systems for jaw crushers that are tension based and compression based (this refers to the way in which the connecting rod is mechanically stressed within the drive mechanism), with the objective of identifying the optimal configuration from both kinematic and functional perspectives. Jaw crushers play a critical role in the extractive industry, and their performance is strongly influenced by the geometry and positioning of the drive mechanism. A theoretical approach based on mathematical modeling and numerical simulation was applied to a real constructive model (SMD-117), assessing variations in the linear velocity of the moving links as a function of mechanism placement. The study employed Mathcad 15, Roberts Animator, and GIM (Graphical Interactive Mechanisms) 2025.4 software to perform calculations and simulate motion. Results revealed a sinusoidal velocity pattern with significant differences between the two systems: the tension-based drive achieves peak velocities at the beginning of the angular variation interval, while the compression-based system reaches its maximum toward the end. Link C consistently exhibits higher velocities than link E, indicating increased mechanical stress. Polar graphic analysis identified critical velocity angles, and simulations confirmed the model’s validity with a maximum error of just 1.79%. The findings emphasize the importance of selecting an appropriate drive system to enhance performance, durability, and energy efficiency, offering concrete recommendations for equipment design and operation. Full article