Search Results (476)

Interim periods between peak and off-peak operations in urban rail transit networks often suffer from mismatched headways across lines, which increases passenger transfer waiting and operating costs. This paper proposes a passenger-oriented timetable synchronization method for network-wide interim period train service. In this study, based on the AFC data, passengers are assigned to the shortest travel time paths, and passenger transfer flows are linked to connecting train pairs by consideration of the maximum acceptable waiting time. As a result, the transfer waiting time is accurately calculated by matching passengers’ platform arrival times with the departures of feasible connecting trains. A mixed integer nonlinear programming model then jointly optimizes departure headways at each line’s first station, arrival and departure times at transfer stations, subject to safety headways and time bounds. The objective minimizes total cost, combining transfer waiting time cost and train operating cost (depreciation and distance-related cost). A simulated-annealing-based genetic algorithm (SA-GA) is designed to solve the NP-hard problem. A case study on the Nanjing rail transit network from 6:30 to 7:30 reduces total cost by 6.88%, including 3.77% lower transfer waiting time cost and 14.49% lower operating cost, and shows stable results under typical transfer demand fluctuations. Full article

Optimizing the furniture layout of middle school laboratories is crucial for improving the emergency safety, operational efficiency, and resilience of teaching buildings. This study used AnyLogic software to model and simulate pedestrian evacuation behavior in a typical middle school laboratory layout. In a standardized laboratory (90.75 m²), we constructed a behavior-oriented multi-agent evacuation model. The model incorporated key student parameters, including shoulder width (312–416 mm), walking speed (1.5–2.5 m/s), and reaction time (10–15 s). To ensure comparability between different layouts, the number of evacuees was fixed at 48. Evacuation performance was evaluated based on total evacuation time, spatial density, and detour distance. The results showed that the hybrid layout achieved the shortest evacuation time (28.0 s), which was 10.3% shorter than the island layout (31.2 s) and 34.7% shorter than the parallel layout (42.9 s). The hybrid layout also had a shorter average detour distance (9.78 m) and the lowest path variability (coefficient of variation CV = 0.33), indicating a more balanced evacuation load and a smaller bottleneck effect. Overall, these findings provide evidence-based recommendations for improving laboratory safety, space utilization, and behavioral adaptability, and provide a quantitative reference for updating educational building codes, school laboratory construction standards, and guidelines for laboratory furniture and safety facility configuration. Full article

Total anomalous pulmonary venous connection (TAPVC) is one of the most severe congenital heart defects; however, prenatal diagnosis remains suboptimal. A normal fetal heart has a junction between the pulmonary venous (PV) and left atrium (LA). In contrast, no junctions are observed in patients with TAPVC. In the present study, we attempted to visualize and detect fetal PV-LA connections using artificial intelligence (AI) trained on the fetal cardiac ultrasound videos of 100 normal cases and six TAPVC cases. The PV-LA aggregate area was segmented using the following three-dimensional (3D) segmentation models: SegResNet, Swin UNETR, MedNeXt, and SegFormer3D. The Dice coefficient and 95% Hausdorff distance were used to evaluate segmentation performance. The mean values of the shortest PV-LA distance (PLD) and major axis angle (PLA) in each video were calculated. These methods demonstrated sufficient performance in visualizing and detecting the PV-LA connection. In terms of TAPVC screening performance, MedNeXt-PLD and SegResNet-PLA achieved mean area under the receiver operating characteristic curve values of 0.844 and 0.840, respectively. Overall, this study shows that our approach can support unskilled examiners in capturing the PV-LA connection and has the potential to improve the prenatal detection rate of TAPVC. Full article

The computational tractability of Integrated Information Theory (IIT) is fundamentally constrained by the exponential cost of identifying the Minimum Information Partition (MIP), which is required to quantify integrated information (Φ). Existing approaches become impractical beyond ~15–20 variables, limiting IIT analyses on realistic neural and complex systems. We introduce GeoMIP, a geometric–topological framework that recasts the MIP search as a graph-based optimization problem on the n-dimensional hypercube graph: discrete system states are modeled as graph vertices, and Hamming distance adjacency defines edges and shortest-path structures. Building on a tensor-decomposed representation of the transition probabilities, GeoMIP constructs a transition-cost (ground cost) structure by dynamic programming over graph neighborhoods and BFS-like exploration by Hamming levels, exploiting hypercube symmetries to reduce redundant evaluations. We validate GeoMIP against PyPhi, ensuring reliability of MIP identification and Φ computation. Across multiple implementations, GeoMIP achieves 165–326× speedups over PyPhi while maintaining 98–100% agreement in partition identification. Heuristic extensions further enable analyses up to ~25 variables, substantially expanding the practical IIT regime. Overall, by leveraging the hypercube’s explicit graph structure (vertices, edges, shortest paths, and automorphisms), GeoMIP turns an intractable combinatorial search into a scalable graph-based procedure for IIT partitioning. Full article

The spatial relationship between the incisive canal (IC) and maxillary central incisors (U1) is a critical anatomical consideration during orthodontic tooth movement, particularly in patients with maxillary dental midline deviation. This study aimed to evaluate the proximity between the IC and U1 roots in relation to maxillary dental midline deviation using cone-beam computed tomography (CBCT) images. Sixty-four patients with skeletal Class I malocclusion were divided into two groups according to the degree of the maxillary dental midline deviation. Group 1 (n = 32; mean age, 23.95 ± 5.40 years) exhibited < 2 mm deviation (0.28 ± 0.39 mm), whereas Group 2 (n = 32; mean age, 27.75 ± 6.21 years) showed > 2 mm deviation (2.45 ± 0.57 mm). CBCT images were analyzed to measure U1 root length and inclination, IC width, inter-root distance, and U1-IC proximity. In Group 2, the anteroposterior U1-IC distance on the deviated side was significantly shorter than on the contralateral side (p < 0.05), while the shortest U1–IC distances did not differ significantly between sides (p > 0.05). Moreover, a significant negative correlation was observed between differences in U1 inclination and root proximity at most vertical levels, indicating that a more proclined U1 on the deviated side tended to be closer to the IC. These findings suggest that maxillary dental midline deviation may be associated with asymmetric positioning of the U1 relative to the IC and underscore the importance of careful three-dimensional evaluation and individualized biomechanical control when planning orthodontic treatment in patients with midline asymmetry. Full article

For long horizontal-section drilling in reservoirs and complex formations, efficient and robust trajectory planning with real-time closed-loop control must be achieved under curvature and mechanical constraints. This study systematically investigates the application of the Dubins curve, a shortest-path model satisfying a minimum curvature constraint, in closed-loop wellbore trajectory control. Six canonical configurations (LSL, RSR, LSR, RSL, LRL, and RLR) are analyzed, and a standardized procedure for path solution and coordinate reconstruction is established. Parametric analyses reveal the effects of curvature limit, target direction, and target distance on trajectory feasibility and path length. Case studies show that unoptimized Dubins trajectories can achieve a high reservoir-contact ratio (99.69%) but exhibit curvature discontinuities at segment junctions, which induce torque and friction peaks. By introducing a multi-objective optimization strategy combining minimum turning-radius expansion and adaptive target adjustment, these curvature discontinuities are effectively mitigated: the maximum curvature was reduced to 11.15°/30 m, the average curvature to 2.57°/30 m, the average friction to 1118.7 N, and the cumulative torque to 31,468 Nm, while maintaining nearly unchanged reservoir contact. The proposed method effectively improves trajectory smoothness and mechanical drillability while preserving real-time computational efficiency, offering a practical approach for closed-loop trajectory optimization in complex geological settings. Full article

A newly discovered myxosporean parasite was described from the gallbladder of Nemipterus virgatus Houttuyn, 1782 collected from the East China Sea. Mature myxospores are crescent-shaped with shell valves that taper gradually toward rounded ends. Each myxospore contained two sub-spherical polar capsules located near the anterior end, closely aligned along the suture line. The mature myxospores measured 6.2 ± 0.6 (5.4–6.9) μm in length and 44.8 ± 4.6 (38.5–53.1) μm in thickness. Polar capsules measured 2.8 ± 0.2 (2.4–3.1) μm in length and 2.3 ± 0.2 (1.9–2.6) μm in width, with polar filaments coiled in 2–3 turns. The small subunit ribosomal DNA (SSU rDNA) sequence of Ceratomyxa nemiptera sp. nov. was distinct from all known myxosporeans, showing the highest similarity (93.56%) and the shortest genetic distance (0.0637) with Ceratomyxa arcuata Thélohan, 1892. The phylogenetic analysis revealed that C. nemiptera sp. nov. was positioned within a later-diverging lineage, forming a sister-group relationship with a clade containing C. arcuata and Ceratomyxa cretensis Kalatzis, Kokkari & Katharios, 2013. This is the first report of a Ceratomyxa species infecting N. virgatus. Full article

Background: Tibial shaft fractures are frequently treated with intramedullary nailing; however, malalignment remains a concern, particularly in proximal metaphyseal fractures. The surgical approach influenced the nail entry point; however, the three-dimensional (3D) geometric characteristics of the entry point among different approaches remain unclear. Methods: This single-center retrospective study included 68 patients with acute tibial shaft fractures (AO/OTA type 42) treated with reamed and locked intramedullary nails from January 2014 to June 2024. The surgical techniques employed included lateral parapatellar (LPA, n = 31), infrapatellar (IPA, n = 27), and suprapatellar (SPA, n = 10) approaches. Postoperative computed tomography (CT) data were reconstructed into standardized 3D images. The mediolateral insertion ratio was calculated as the percentage distance from the lateral tibial plateau edge to the nail entry point relative to the plateau’s width in the coronal plane. The shortest distance from the tibial articular surface to the nail (r) was measured in the sagittal plane. The Kruskal–Wallis test and Dunn’s post hoc comparisons were used to analyze group differences. Results: Baseline patient and fracture characteristics did not significantly differ among the groups. The mediolateral insertion ratio significantly differed (p < 0.0001), with a more lateral entry for the LPA (44.0% [43.0–47.0]) than for the IPA (51.0% [49.0–53.0], post hoc p < 0.0001) and SPA (49.0% [47.0–51.3], post hoc p = 0.0034). Further, the sagittal distance r significantly differed (p < 0.0001), with a more distal entry for the LPA (14.8 [12.8–20.1] mm) than for the IPA (9.7 [7.0–11.8] mm, post hoc p < 0.0001) and SPA (10.5 [5.5–12.9] mm, post hoc p = 0.0008). No statistically significant difference was observed between the IPA and SPA. Conclusions: The LPA generates a significantly more lateral and distal tibial nail entry point than the IPA and SPA. No statistically significant differences were detected between the IPA and SPA in either plane. These 3D-CT findings may warrant attention during approach selection and guidewire placement, particularly for fractures extending into the proximal metaphysis. Full article

Urban tunnel portals constitute critical safety zones for autonomous vehicles, where abrupt luminance transitions, shortened sight distances, and densely distributed structural and traffic elements pose considerable challenges to perception reliability. Existing driving scenario datasets are rarely tailored to tunnel environments and have not quantitatively evaluated how specific infrastructure components influence perception latency in autonomous systems. This study develops a requirement-driven framework for the identification and sensitivity ranking of information perception elements within urban tunnel portals. Based on expert evaluations and a combined function–safety scoring system, nine key elements—including road surfaces, tunnel portals, lane markings, and vehicles—were identified as perception-critical. A “mandatory–optional” combination rule was then applied to generate 48 logical scene types, and 376 images after brightness (30–220 px), blur (Laplacian variance ≥ 100), and occlusion filtering (≤0.5% pixel error) were obtained after luminance and occlusion screening. A ResNet50–PSPNet convolutional neural network was trained to perform pixel-level segmentation, with inference rate adopted as a quantitative proxy for perceptual sensitivity. Field experiments across ten urban tunnels in China indicate that the model consistently recognized road surfaces, lane markings, cars, and motorcycles with the shortest inference times (<6.5 ms), whereas portal structures and vegetation required longer recognition times (>7.5 ms). This sensitivity ranking is statistically stable under clear, daytime conditions (p < 0.01). The findings provide engineering insights for optimizing tunnel lighting design, signage placement, and V2X configuration, and offers a pilot dataset to support perception-oriented design and evaluation of urban tunnel portals in semi-enclosed environments. Unlike generic segmentation datasets, this study quantifies element-specific CNN latency at tunnel portals for the first time. Full article

Street trees are vital components of urban ecosystems, contributing to air purification, microclimate regulation, and visual landscape enhancement. Thus, accurate segmentation of individual trees from point clouds is an essential task for effective urban green space management. However, existing methods often struggle with noise, crown overlap, and the complexity of street environments. To address these challenges, this paper introduces a multi-constraint and shortest path optimization method for individual urban street tree segmentation from point clouds. In this paper, object primitives are first generated using multi-constraints based on graph segmentation. Subsequently, trunk points are identified and associated with their corresponding crowns through structural cues. To further improve the robustness of the proposed method under dense and cluttered conditions, the shortest-path optimization and stem-axis distance analysis techniques are proposed to further refine the individual tree extraction results. To evaluate the performance of the proposed method, the WHU-STree benchmark dataset is utilized for testing. Experimental results demonstrate that the proposed method achieves an average F1-score of 0.768 and coverage of 0.803, outperforming superpoint graph structure single-tree classification (SSSC) and nyström spectral clustering (NSC) methods by 17.4% and 43.0%, respectively. The comparison of visual individual tree segmentation results also indicates that the proposed framework offers a reliable solution for street tree detection in complex urban scenes and holds practical value for advancing smart city ecological management. Full article

Underwater Wireless Sensor Networks (UWSNs) are widely used technologies in aquatic environments. However, these types of networks face several constraints caused by the mobility of nodes, energy consumption, and constraints due to acoustic communication. In light of this, the location of nodes appears as a promising axis for improving the services expected from these networks. To address these, we suggest the LUCOTED approach—a Linear Constraint Optimization Technique for estimating unknown node positions by selecting anchor nodes with the highest energy and shortest distance, based on randomly initialized conditions. It achieves 98% accuracy, exceeding Gradient Descent and Trilateration methods. Moreover, our method LUCOTED outperforms the DEEC algorithm in terms of error when the number of anchor nodes is below 80 and achieves higher accuracy than the EPRP technique when the number exceeds 100. Full article

The growing adoption of Unmanned Surface Vessels (USVs) in commercial and defense domains raises challenges for safe navigation and strict adherence to the International Regulations for Preventing Collisions at Sea (COLREGs). This paper presents the implementation and field validation of three collision-avoidance approaches on a real USV: (i) behavior-based, (ii) a modified Velocity Obstacles (VO) algorithm, and (iii) a modified A* path-planning algorithm. Field trials in Guanabara Bay (Brazil) show that the behavior-based algorithm achieved the best balance between safety and efficiency, maintaining a safe mean Closest Point of Approach (30.0 m) while minimizing operational penalties: shortest total distance (179.4 m average), lowest mission completion time (174.7 s average), and smallest trajectory deviation (27.2% average increase). The VO algorithm operated with reduced safety margins (13.0 m average CPA) at the expense of larger detours (37.6% average distance increase), while the modified A* maintained equivalent safety (30.0 m average CPA) but produced the largest deviations (46.5% average increase). The trade-off analysis reveals that algorithm selection depends on operational priorities between safety margins and route efficiency. Full article

Bike-sharing services contribute to reducing emissions and conserving natural resources within urban transportation systems. They also promote public health by encouraging physical activity and generate economic benefits through shorter travel times, lower transportation costs, and decreased demand for parking infrastructure. This paper examines the use of shared micro-mobility services in the Italian cities of Florence and Bologna, based on an analysis of GPS origin–destination data and associated temporal coordinates provided by the RideMovi company. Given the still-limited number of studies on free-floating and electric-scooter-sharing systems, the objective of this work is to quantify the performance of electric bikes and e-scooters in bike-sharing schemes and compare it to traditional, muscular bikes. Trips were reconstructed starting from GPS data of origin and destination of the trip with a shortest path criteria that considers the availability of bike lanes. Results show that e-bikes are from 22 to 26% faster on average with respect to muscular bikes, extending trip range in Bologna but not in Florence. Electric modes attract more users than traditional bikes, e-bikes have from 40 to 128% higher daily turnover in Bologna and Florence and e-scooters from 33 to 62% higher in Florence with respect to traditional bikes. Overall, turnover is fairly low, with less than two trips per vehicle per day. The performance is measured in terms of trip duration, speed, and distance. Further characteristics such as daily turnover by transport mode are investigated and compared. Finally, spatial analysis was conducted to observe demand asymmetries in the two case studies. The results aim to support planners and operators in designing and managing more efficient and user-oriented services. Full article

Robots are widely used to carry goods in automated warehouses. Planning collision-free paths for multiple robots which are continuously given new goals is called Lifelong Multi-Agent Pathfinding. In a lifelong environment, conflicts may emerge among the robots, and continuous replanning is needed. We propose, develop, implement, and evaluate the novel approach called the Clustered Reverse Resumable A* (CRRA*) algorithm to enhance the continuous computation of the shortest path from the changing position of a robot to its goal. The Priority Inheritance with Backtracking (PIBT) algorithm is the currently known most efficient algorithm to handle the pathfinding of thousands of robots in a warehouse. The PIBT algorithm requires that in each step each robot evaluates the distances from its surrounding positions to its goal; therefore, we integrate the CRRA* algorithm with the PIBT algorithm to evaluate CRRA*. The evaluation results show that the CRRA* leads to a significant reduction in computation time, especially in larger warehouses where the obstacles form well-separated spaces. At the same time, the degradation in solution quality is minimal. The CRRA* algorithm is more efficient in larger warehouses than the plain Reverse Resumable A* (RRA*) algorithm. The faster computation of slightly suboptimal paths can be useful in many practical applications, especially in situations where real-time planning is more important than finding the optimal paths. CRRA* can also be used as a heuristic in any multi-agent pathfinding solution to obtain a faster, nearly accurate heuristic. Full article

Extensive research on path planning and automated navigation has been carried out for weeding robots in fields such as corn, soybean, wheat, and sugar beet, but until now, no literature reports relative studies in turfs that are not cultivated using row-crop methods. This paper proposes a practical solution that comprises path planning and path tracking to minimize the weeding robot’s travel distance in turfs for the first time. An inter-sub-region scheduling algorithm is developed using the Traveling Salesman Problem (TSP) model, followed by a boundary-shifting-based coverage path planning algorithm to achieve full coverage within each weed subregion. For path tracking, a Real-Time Kinematic Global Positioning System (RTK-GPS) fusion positioning method is developed and combined with a dynamic pure pursuit algorithm featuring a variable preview distance to enable precise path following. After path planning based on real-world site data, the weeding robot traverses all weed subregions via the shortest possible path. Field experiments showed that the robot traveled along the shortest path at speeds of 0.6, 0.8, and 1.0 m/s; the root mean square errors of autonomous navigation deviation were 0.35, 0.81, and 1.41 cm, respectively. The proposed autonomous navigation solution significantly reduces the robot’s travel distance while maintaining acceptable tracking accuracy. Full article