Search Results (941)

The intensifying global warming and the increasing frequency of extreme weather events have created an urgent need for targeted resilience building in mountainous villages. This study focuses on three typical villages in the Hengduan Mountains region. From the perspective of individual villagers, a disaster resilience evaluation index system was constructed, encompassing four dimensions: disaster prevention capacity, disaster resistance capacity, disaster relief capacity, and recovery capacity. Using the entropy method and a village disaster resilience assessment model, the disaster resilience levels of each village were quantitatively evaluated. The results indicate the following: (1) Disaster resistance capacity is the key factor constraining the disaster resilience level of mountain villages. (2) The overall disaster resilience of mountain villages is at a medium level, with minor differences among villages. (3) Significant disparities exist in capacity dimensions across villages: Qina Village demonstrates the strongest disaster resistance capacity, while Xiamachang Village excels in disaster prevention capacity but shows relative weakness in recovery capacity. (4) Household material endowment has a significant positive impact on disaster prevention, resistance, relief, and recovery capacities, while individual self-rescue capability and individual–government collaboration capacity also significantly enhance disaster prevention, resistance, and relief capacities. We propose the following: Leveraging the rural revitalization strategy as a pivotal point, this approach promotes the diversified development of the village economy. It facilitates the increase in villagers’ income through the implementation of employment skill training programs, thereby strengthening household material foundations to enhance individual disaster resilience. By relying on the mass monitoring and mass prevention mechanism and a disaster information sharing platform, real-time exchange of disaster situation information is achieved, which enhances communication and collaboration between villagers and the government, consequently improving the synergistic efficiency between individuals and governmental bodies. Simultaneously, a villager-centered disaster prevention system is constructed. Through measures such as disaster prevention publicity and practical disaster response drills, villagers’ awareness of disasters and their capabilities for self and mutual rescue are elevated, ultimately strengthening the overall disaster resilience of rural areas in the Hengduan Mountains region. Full article

The three-leg 50-Years Roundabout at King Abdulaziz University (KAU) is known for its vibrance and important location as it is located at the center of several major buildings and hospitals. In recent years, the roundabout is witnessing a huge demand that influences the university road networks’ level of service, “LOS”, which in return, has negative impacts on students and faculties in terms of delay and travel time. Several treatments can be implemented along the roundabout. One of those treatments is applying restrictions during morning peak hours such as blocking and restricting specific lanes. This treatment has the advantage of reducing conflict points that cause sudden and frequent stops at the roundabout; as a result, delay and congestion occur. By reducing conflict points, traffic flow can be improved, in addition to enhancing safety and promoting sustainability. This paper examines the base condition of the 50-Years Roundabout in terms of traffic flow, LOS, delay, capacity, and toxic emissions, and proposes traffic system management (TSM) strategies through applying restricted and designated lanes to improve traffic condition. The study employs PTV Vissim, SIDRA Intersection, and Surrogate Safety Assessment Model “SSAM” to examine the base and proposed conditions. The results show a significant improvement through the reduction in conflict points, so that reflects the positive impacts on sustainability, congestion, delay, travel time, LOS, and overall toxic emissions. Full article

To precisely understand the interaction behaviors of humans, a computer vision system needs to accurately acquire the poses of the hand and its manipulated object. Vision-based hand–object pose estimation has become an important research topic. However, it is still a challenging task due to severe occlusion. In this study, a hand–object pose estimation method based on anchor regression is proposed to address this problem. First, a hand–object 3D center detection method was established to extract hand–object foreground images from the original depth images. Second, a method based on anchor regression is proposed to simultaneously estimate the poses of the hand and object in a single framework. A convolutional neural network with ResNet-50 as the backbone was built to predict the position deviations and weights of the uniformly distributed anchor points in the image to the keypoints of the hand and the manipulated object. According to the experimental results on the FPHA-HO dataset, the mean keypoint errors of the hand and object of the proposed method were 11.85 mm and 18.97 mm, respectively. The proposed hand–object pose estimation method can accurately estimate the poses of the hand and the manipulated object based on a single egocentric depth image. Full article

Operation of vehicle–trailer combinations is currently popular throughout many countries. Connecting a trailer to a passenger car increases the car’s utility value because it is possible to transport more goods over shorter or longer distances. Trailers are also popular as caravans, which provide a home on wheels during holiday periods. As a trailer is connected to a towing vehicle by means of a spherical joint from the mechanics’ point of view, a vehicle–trailer combination has significantly different driving properties in comparison with a sole vehicle. These differences are manifested mainly while driving in a curve as lower stability of the vehicle. In this case, the lower stability is considered an uncontrolled sway motion. This study is focused on researching the driving stability of a vehicle–trailer combination regarding the sway motion problem. The research is fully performed by means of simulation computations in a commercial multibody simulation software. The investigated vehicle–trailer combination consists of an SUV passenger car and a single-axle goods trailer. Two model driving maneuvers are investigated, namely bypassing an obstacle in a lane and changing lanes on a road. Simulation computations are performed for chosen loads of the trailer and for a different position of the center of gravity of the load in the single-axle trailer. The performed research has proven that the applied simulation computations represent a robust tool to investigate real tasks related to vehicle safety without performing expensive and dangerous tests. Very important findings include identifying the proper position of the center of gravity of the load on the trailer to ensure safe driving properties for driving maneuvers that could pose potential danger during real operation. Full article

Background/Objectives: Subunit vaccines composed of purified proteins and adjuvants offer excellent safety, but often generate short-lived immunity due to rapid antigen clearance and limited antigen-presenting cell engagement. Sustained, localized delivery of antigen and adjuvant may improve the magnitude and durability of the immune response without compromising safety. This study evaluated an in-situ polymerizing type I oligomeric collagen (Oligomer) scaffold to localize antigen/adjuvant at the injection site and prolong antigen presentation. Methods: Mice were immunized intramuscularly with ovalbumin (OVA) and CpG oligonucleotide adjuvant delivered alone or co-formulated with Oligomer. Antibody response and inflammation at the injection site were assessed post-booster at early (Day 32) and late (Day 68) time points. Antigen retention and dendritic cell trafficking to draining lymph nodes were evaluated using fluorescently labeled OVA. Results: The Oligomer scaffold retained vaccine antigen at the injection site without eliciting a material-mediated foreign body response. Co-delivery of OVA and CpG within the scaffold enhanced germinal center activity, increased follicular helper T cells and germinal center B cells, and skewed CD4⁺ T cells toward a Th1 phenotype. Humoral responses were greater and more durable, with higher OVA-specific IgG, IgG1, and IgG2a titers and an increased number of bone marrow antibody-secreting cells persisting through Day 68. Antigen-positive dendritic cells, including both resident and migratory subsets, were elevated in draining lymph nodes, indicating enhanced antigen transport. No anti-mouse collagen I antibodies were detected, confirming the maintenance of collagen self-tolerance. Conclusions: The Oligomer delivery platform functioned as a localized, immunotolerant vaccine depot, sustaining antigen availability and immune cell engagement. This spatiotemporal control enhanced germinal center responses and generated a more robust, durable humoral immune response, supporting its potential to improve subunit vaccine efficacy while maintaining an excellent safety profile. Full article

Background/Objectives: Free gracilis (GM) and latissimus dorsi muscle (LDM) flaps are reliable options for complex defect coverage, but long-term sensory outcomes remain underexplored. Sensory impairment, especially the loss of protective cutaneous sensation, increases the risk of injury, thermal damage, and ulceration in reconstructed areas. This study aimed to systematically assess multidimensional sensory recovery after free muscle flap (FMF) reconstruction. Methods: In a prospective single-center study, 94 patients (49 GM, 45 LDM) underwent standardized sensory testing following FMF transfer. Five modalities were evaluated: pressure detection (Semmes-Weinstein monofilaments), vibration perception, two-point discrimination (2PD), sharp–dull differentiation, and temperature differentiation. Measurements were compared to contralateral healthy skin (CHS). Subgroup analyses were performed by anatomical region (head, trunk, extremities). Results: All sensory modalities were significantly impaired in FMF compared to CHS (p < 0.0001). Mean pressure thresholds were markedly higher in FMF (248.8 g) versus CHS (46.8 g). Vibration perception scores were reduced (FMF 3.97 vs. CHS 5.31), and 2PD was significantly poorer (11.6 cm vs. 4.7 cm). Sharp–dull and thermal discrimination were largely absent in FMF (positivity rates < 20%), with 58.5% of patients demonstrating only deep pressure sensation (≥300 g). No significant differences were found between GM and LDM in most modalities, except for worse 2PD in GM. Subgroup analyses confirmed uniform deficits across all anatomical regions. Conclusions: FMFs without neurotization result in profound, persistent sensory deficits, particularly the loss of protective sensation. Clinically, fascio-cutaneous flaps with nerve coaptation should be considered in functionally critical regions. Future strategies should focus on neurotization techniques to enhance sensory recovery. Full article

Accurate spatial sound localization is critical in flight simulators for enhancing situational awareness and pilot training effectiveness, particularly for diagnosing severe faults like engine surge which emit directional sound cues. However, existing spatial audio systems are primarily optimized for a single central listening position, failing to provide consistent localization accuracy for pilots seated in naturally off-center positions within the cockpit. To bridge this gap, this paper proposes a novel compensation method incorporating near-field loudspeakers. A comprehensive mathematical model for multiple off-center listening points is established based on acoustic velocity and energy vector theory. We further formulate a dual-phase optimization framework: a multi-objective model employing the NSGA-II algorithm to Pareto-optimize the trade-off between minimizing localization error and maximizing spatial stability, followed by a maximin model that guarantees robustness during head movements. A formal listening experiment demonstrates that the proposed optimized design significantly improves both localization accuracy and stability over conventional uniform layouts, thereby enhancing the fidelity and safety of flight simulation training. Full article

Solid-state spin centers are at the forefront of developing advanced quantum technologies, engaging in applications of sensing, communication and computing. A semiconductor host matrix compatible with existing silicon technology provides a robust platform for holding spin defects and an opportunity for external manipulation. In this article, negatively charged nitrogen-vacancy (NV) centers in the hexagonal hh position in a 6H polytype silicon carbide crystal was studied using high-frequency (94 GHz) electron paramagnetic (EPR) and electron nuclear double resonances (ENDOR) spectroscopy. Experimentally determined values of hyperfine and quadrupole interactions of ¹⁴N were compared with the values obtained for the centers in NV_k2k1 positions. The distribution of spin density of the defect within a supercell of the SiC crystal lattice was calculated using the density functional theory approach. The theoretical estimation of electron-nuclear interaction constants turned out to be in close agreement with the experimental values, which allows us to refine the microscopic model of a point defect. The temperature dependence of the spin Hamiltonian values (δA/δT ≅ 180 Hz/K) was studied with the possibility of observing the ¹⁴N NMR signal at room temperature. The fundamental knowledge gained about interactions’ parameters’ behavior lays the foundation for the creation of promising quantum platforms. Full article

Background: Internists formulate diagnostic hypotheses and personalized treatment plans by integrating data from a comprehensive clinical interview, reviewing a patient’s medical history, physical examination and findings from complementary tests. The patient treatment life cycle generates a significant volume of data points that can offer valuable insights to improve patient care by guiding clinical decision-making. Artificial Intelligence (AI) and, in particular, Generative AI (GAI), are promising tools in this regard, particularly after the introduction of Large Language Models. The European Federation of Internal Medicine (EFIM) recognizes the transformative impact of AI in leveraging clinical data and advancing the field of internal medicine. This position paper from the EFIM explores how AI can be applied to achieve the goals of P6 Medicine principles in internal medicine. P6 Medicine is an advanced healthcare model that extends the concept of Personalized Medicine toward a holistic, predictive, patient-centered approach that also integrates psycho-cognitive and socially responsible dimensions. An additional concept introduced is that of Digital Therapies (DTx), software applications designed to prevent and manage diseases and disorders through AI, which are used in the clinical setting if validated by rigorous research studies. Methods: The literature examining the relationship between AI and Internal Medicine was investigated through a bibliometric analysis. The themes identified in the literature review were further examined through the Delphi method. Thirty international AI and Internal Medicine experts constituted the Delphi panel. Results: Delphi results were summarized in a SWOT Analysis. The evidence is that through extensive data analysis, diagnostic capacity, drug development and patient tracking are increased. Conclusions: The panel unanimously considered AI in Internal Medicine as an opportunity, achieving a complete consensus on the matter. AI-driven solutions, including clinical applications of GAI and DTx, hold the potential to strongly change internal medicine by streamlining workflows, enhancing patient care and generating valuable data. Full article

Mining articulated vehicles (MAVs) are widely used as primary transportation equipment in both underground and open-pit mines. These include various machines such as Load–Haul–Dump machines and mining trucks. Path tracking control for MAVs has been an important research topic. Most current research focuses on path tracking control during forward driving. However, there are relatively limited studies on reverse path tracking control. Reversing plays a crucial role in the operation of MAVs. Nevertheless, existing methods typically use the center of the front axle as the control point; therefore, the positioning system is usually installed at the front axle. In practice, however, this means the positioning system is actually located at the rear axle during reverse operations. While it is theoretically possible to infer the position and orientation of the front axle from the rear axle, a strong nonlinear relationship exists between the motion states of the front and rear axles, which introduces significant errors in the system. As a result, these existing methods are not suitable for reverse driving conditions. To address this issue, this paper proposes a nonlinear model predictive control (NMPC) method for path tracking during mining-articulated vehicle (MAV) reverse operations. This method innovatively reconstructs the reverse-motion model by selecting the center of the rear axle as the control point, effectively addressing the instability issues encountered in traditional control methods during reverse maneuvers without requiring additional positioning devices. A comparative analysis with other control strategies, such as NMPC for forward driving, reverse NMPC using the front axle model, and reverse linear model predictive control (LMPC), reveals that the proposed NMPC method achieves excellent control accuracy. Displacement and heading error amplitudes do not exceed 0.101 m and 0.0372 rad, respectively. The maximum solution time per control period is 0.007 s. In addition, as the complexity of the reverse path increases, it continues to perform excellently. Simulation results show that as the curvature of the U-shaped curve increases, the proposed NMPC method consistently maintains high accuracy under various operational conditions. Full article

Against the backdrop of the dual carbon goals, the construction industry—as the primary source of carbon emissions accounting for 50.9%—is increasingly relying on green technological innovation to drive its sustainable development transformation. However, construction enterprises currently face three core challenges: the significant incremental costs associated with adopting green technologies, insufficient green credit supply from financial institutions, especially banks, and inadequate policy coordination among government departments. Furthermore, misaligned interests among multiple stakeholders exacerbate the implementation challenges of green technological innovation, hindering the industry′s low-carbon transition. Therefore, systematically exploring the interaction patterns and functional mechanisms among construction enterprises, government agencies, and banks in green technology innovation decision-making is crucial. This study will provide theoretical and empirical support for the green transformation of the construction industry within the dual-carbon framework. This study establishes a tripartite game model involving construction companies, governments, and banks, centered around the decision-making phase of green technology innovation. By integrating evolutionary game theory with system dynamics (SD) approaches, it uncovers the evolutionary trajectories and underlying mechanisms of strategies adopted by each stakeholder. Research indicates that construction companies, governments, and banks ultimately maintain equilibrium at the (1,1,1) point. The study underscores the pivotal role of government guidance during the decision-making stage, highlighting that sustained implementation of proactive policies can foster positive interactions and a balance between construction companies’ pursuit of green technology innovation and banks’ provision of green credit. It can shorten the time required for enterprises and banks to evolve their strategies. Suppressing the probability of innovation failure moderates both parties′ strategies, and adjusting parameters such as green credit interest rates and government subsidies can optimize choices. This research not only enhances the theoretical understanding of green technology innovation in the construction sector but also offers practical insights for promoting industry-wide green innovation, improving the quality of green buildings, and regulating market order. Full article

Three-dimensional fragment assembly technology has significant application value in fields such as cultural relic restoration, medical image analysis, and industrial quality inspection. To address the common challenges of limited feature representation ability and insufficient assembling accuracy in existing methods, this paper proposes a geometry-aware hierarchical fragment assembly framework (GeoAssemble). The core contributions of our work are threefold: first, the framework utilizes DGCNN to extract local geometric features while integrating centroid relative positions to construct a multi-dimensional feature representation, thereby enhancing the identification quality of fracture points; secondly, it designs a two-stage matching strategy that combines global shape similarity coarse matching with local geometric affinity fine matching to effectively reduce matching ambiguity; finally, we propose an auxiliary transformation estimation mechanism based on the geometric center of fracture point clouds to robustly initialize pose parameters, thereby improving both alignment accuracy and convergence stability. Experiments conducted on both synthetic and real-world fragment datasets demonstrate that this method significantly outperforms baseline methods in matching accuracy and exhibits higher robustness in multi-fragment scenarios. Full article

Background: Despite advances in temporary mechanical circulatory support (tMCS), patients with cardiogenic shock (CS) who are treated with a microaxial flow pump (mAFP; Impella^®, Abiomed) still have a high mortality rate. A dysregulated systemic inflammatory response significantly contributes to multiorgan failure in this population. CytoSorb^® hemadsorption has emerged as a potential adjunctive therapy for modulating inflammation, but data on its use in CS are limited. Methods: This retrospective, single-center study used propensity score matching analysis (1:1 matching; n = 15 per group) to compare the outcomes of patients receiving mAFP support with and without concomitant CytoSorb therapy. Baseline data (T0), including comorbidities and clinical status at ICU admission, were collected for all patients. In the CytoSorb group, data were collected at two additional time points: 24 h before the start of CytoSorb therapy (T1), and 24 h after its completion (T2). At these time points, laboratory values and parameters on respiratory, hemodynamic, and organ function were assessed. Corresponding data were also collected for matched patients in the non-CytoSorb group at equivalent time points relative to their matched counterparts. Results: In the propensity score-matched cohort, patients treated with CytoSorb exhibited significant improvements between T1 and T2. Specifically, reductions were observed in the vasoactive-inotropic score (p = 0.035), procalcitonin levels (p = 0.041), peak inspiratory pressure (p = 0.036), and positive end-expiratory pressure (p = 0.016). Flow rates through the mAFP declined significantly (p = 0.014), suggesting stabilization of hemodynamics. These changes were not observed in the non-CytoSorb group, where most parameters remained unchanged or exhibited less pronounced trends. We observed a lower in-hospital mortality rate in the CytoSorb group (33.3% versus 46.7%), though the difference was not significant, potentially due to limited statistical power. Conclusions: CytoSorb hemadsorption in mAFP-supported CS was associated with improved hemodynamic stability and reduced inflammatory burden. These findings suggest a potential therapeutic benefit of adjunctive hemadsorption in this high-risk population. Full article

The unique hollowed-out catamaran hulls and complex environmental conditions in lake areas hinder traditional ranging algorithms (combining target detection and stereo matching) from accurately obtaining depth information near the center of ships. This not only impairs the navigation of electric tourist boats but also leads to high computing resource consumption. To address this issue, this study proposes a ranging method integrating improved ORB (Oriented FAST and Rotated BRIEF) with stereo vision technology. Combined with traditional optimization techniques, the proposed method calculates target distance and angle based on the triangulation principle, providing a rough alternative solution for the “gap period” of stereo matching-based ranging. The method proceeds as follows: first, it acquires ORB feature points with relatively uniform global distribution from preprocessed binocular images via a local feature weighting approach; second, it further refines feature points within the ROI (Region of Interest) using a quadtree structure; third, it enhances matching accuracy by integrating the FLANN (Fast Library for Approximate Nearest Neighbors) and PROSAC (Progressive Sample Consensus) algorithms; finally, it applies the screened matching point pairs to the triangulation method to obtain the position and distance of the target ship. Experimental results show that the proposed algorithm improves processing speed by 6.5% compared with the ORB-PROSAC algorithm. Under ideal conditions, the ranging errors at 10m and 20m are 2.25% and 5.56%, respectively. This method can partially compensate for the shortcomings of stereo matching in ranging under the specified lake area scenario. Full article

Background: Latent myofascial trigger points (MTrPs) are clinically relevant because they lower local pressure pain thresholds (PPTs), can perturb motor control, and may sustain shoulder symptoms even when overt pain is absent. However, even if previous studies assessed stiffness and mechanosensitivity differences between MTrPs and asymptomatic regions, objective patient-level cut-offs and diagnostic-accuracy metrics to distinguish latent MTrPs from adjacent asymptomatic tissue are lacking. Objective: To quantify the diagnostic accuracy of pressure algometry (PPT) and shear-wave elastography (SWE) for distinguishing latent MTrPs from adjacent asymptomatic tissue. Methods: A single-center cross-sectional study was conducted including 76 volunteers with ≥1 latent infraspinatus MTrP (assessed by following the current Delphi consensus criteria). The most sensitive latent MTrP and a control site 2 cm cranial was measured on the dominant side infraspinatus muscle in each participant. PPT and SWE were acquired with a standardized protocol (long-axis imaging, anisotropy control, minimal probe pressure; three captures per site; 1 cm rectangular ROI; operator blinded to site type). ROC analyses estimated areas under the curve (AUCs), Youden-optimal cut-offs, sensitivity, specificity, and likelihood ratios (LR+/−). Results: Latent MTrPs showed lower PPTs than controls (p < 0.001) and higher stiffness (shear modulus: p = 0.009; shear-wave speed: p = 0.022). PPT yielded AUC = 0.704 with an optimal cut-off of 47.5 N (sensitivity 0.75; specificity 0.592; LR+ 1.84; LR− 0.42), outperforming SWE metrics (shear modulus AUC 0.611; cut-off 23.6 kPa; sensitivity 0.632; specificity 0.605; LR+ 1.60; LR− 0.61; shear-wave speed AUC 0.601; cut-off 2.55 m/s; sensitivity 0.592; specificity 0.632; LR+ 1.61; LR− 0.65). Conclusions: In the infraspinatus, PPT provides moderate discrimination between latent MTrPs and adjacent asymptomatic tissue, whereas resting SWE—despite small mean differences—exhibited lower accuracy. These findings support mechanosensitivity as a primary measurable signal and position SWE as an adjunct. External validation across devices and operators, and multivariable models integrating sensory, imaging, and clinical features, are warranted. Full article