Search Results (7,501)

With the rapid development of unmanned surface vessels (USVs), a vector thruster was designed in this paper to meet their evolving operational demands. The anti-impact capability of the vector thruster, in which the universal joint plays a critical role in attenuating impact loads, directly governs the stability and security of power transmission in USVs. A mechanical model of the vector thruster with a universal joint was established, incorporating length and stiffness ratio coefficients to characterize its key dynamics. Based on this model, numerical simulation using the Newmark method was conducted to systematically evaluate the thruster’s mechanical characteristics, particularly the dynamic variation of the inclination angle, under various working conditions and impact loads. The results indicate that an increase in stiffness ratio amplifies the angular displacement amplitude of the driven shaft but shortens the vibration stabilization time. During the operation of the vector thruster, an increase in the inclination angle leads to greater vibration amplitude. Furthermore, systems with a higher, longer ratio exhibit a more pronounced tendency for amplitude growth as the inclination angle increases. Finally, the theoretical model was validated through a test bench, and the variation pattern of dynamic thrust under impact load was revealed. These results emphasize that the stiffness and dimensional parameters must be carefully considered in the design and control optimization of vector thrusters to ensure reliable performance under demanding operational conditions. Full article

Introduction: Patellofemoral instability (PFI) is most prevalent in adolescents aged 10–17 years, yet disease-specific functional assessment tools validated for pediatric populations are limited. The Banff Patellofemoral Instability Instrument (BPII) 2.0 and the Norwich Patellar Instability (NPI) scores are disease-specific tools that have previously been validated in adults. The purpose of this study was to translate, culturally adapt, and validate the BPII 2.0 and NPI scores for Polish-speaking pediatric patients with PFI. Methods: The Polish versions of the BPII 2.0 and NPI were developed following Beaton’s cross-cultural adaptation guidelines. Patients aged 12–18 years with surgically treated recurrent patellofemoral joint instability completed the BPII 2.0, NPI, Anterior Knee Pain Scale (Kujala), Lysholm Knee Score, and Pedi-IKDC at a clinic visit and again 7–14 days later. The following psychometric properties were assessed: face validity, floor and ceiling effects, test–retest reliability (ICC), internal consistency (Cronbach’s α), and construct validity (Spearman Correlation Coefficients). Results: A total of 57 postoperative patients (19 males, 38 females; median age 16 years, range 12.25–18 years) participated 24–36 months after surgical stabilization. No floor or ceiling effects were observed. The test–retest reliability was excellent (ICC = 0.988 for BPII 2.0 (95% CI 0.977–0.994, p < 0.001); ICC = 0.997 for NPI (95% CI 0.995–0.998, p < 0.001)). Both instruments demonstrated excellent internal consistency (Cronbach’s α = 0.95 for BPII 2.0; α = 0.93 for NPI). The BPII 2.0 showed moderate to strong positive correlations with Lysholm (ρ = 0.69), Kujala (ρ = 0.69), and Pedi-IKDC (ρ = 0.57) and moderate negative correlation with NPI (ρ = −0.62), all of which were statistically significant (p < 0.001). Conclusion: The Polish versions of the BPII 2.0 and NPI scores demonstrated excellent reliability (ICC = 0.988 and 0.997, respectively), internal consistency (Cronbach’s α = 0.95 and 0.93, respectively), and construct validity in Polish-speaking adolescent patients with surgically treated recurrent patellofemoral instability. This is the first validation of the NPI in an exclusively pediatric population. These tools are suitable for clinical assessment and research in this specific population. Limitations include the postoperative-only cohort and absence of structural validity assessment. Full article

This paper introduces an adaptive impedance control strategy for robotic manipulators, developed through the extremum seeking technique. A model-based disturbance observer (DOB) is employed to estimate contact forces, removing the dependency on torque sensors. An impedance vector is constructed to correct the errors arising from motor uncertainties and unknown couplings, without considering the threshold value of the control parameters. Joint tracking errors and fluctuations in contact force are incorporated into the cost function. For various tasks, suitable control parameters are adaptively optimized in real time using an extremum seeking approach, which continuously evaluates the cost function. A rigorous analysis is conducted on the stability of the proposed controller. Compared to conventional approaches, the proposed adaptive impedance control offers a more streamlined design for adjusting the manipulator’s contact impedance. Experimental results confirm that the extremum seeking strategy successfully tuned the controller parameters online according to variations in the cost function. Full article

Introduction: Malocclusion and dysfunctional or atypical swallowing are two conditions that significantly affect the health and well-being of the stomatognathic system, so much so that they often interact, influencing each other, and the presence of one can cause the onset or aggravation of the other. In this regard, over the years studies have been carried out that tried to discover the correlation between atypical swallowing and malocclusion. The aim is to evaluate the prevalence of dysfunctional swallowing in patients with malocclusion, to examine the pathophysiological mechanisms linking malocclusion and dysfunctional swallowing, and above all to investigate what potential risk factors may be. Materials and Methods: A sample of 60 patients aged between 6 and 16 years was analyzed at the Department of Dentistry of the University of L’Aquila. Some characteristics of the subjects’ face and posture were analyzed both from a frontal and lateral point of view. An orthodontic, temporomandibular joint, and masticatory muscle diagnosis was made. In addition, an examination of oral structures and functions was performed that allowed breathing, swallowing, chewing, and phono-articulation to be assessed. Results: It was observed that all the children had atypical swallowing, with significant postural abnormalities of the tongue; in fact, only 5% had a correct posture of the tongue at rest. In the analysis of occlusal characteristics, it emerged that with regard to the transverse plane, 21.67% of subjects have a condition of No Cross, while 10% show a Unilateral Cross. Finally, 68.33% show a Bilateral Cross. As far as the anterior–posterior plane is concerned, most of the subjects, equal to 76.67%, are placed in Class I, while 23.33% are in Class II. Finally, in relation to the vertical plane, 63.33% of subjects have normal occlusion, while 25% suffer from deep bite and 11.67% from open bite. The sample, stratified by presence or absence of alerts, shows significant differences for atypical swallowing (p = 0.031), for the presence of Class II malocclusion (p = 0.002), for low lingual posture, (p < 0.001), and for labial incompetence (p = 0.001). The multivariate logistic regression model showed that the presence of atypical swallowing (OR 1.04, 95% CI 1.04–1.07, p = 0.029), open bite malocclusion (OR 1.09, 95% CI 1.01–1.18, p = 0.013), low lingual posture (OR 1.11, 95% CI 1.04–1.18, p = 0.002), and the presence of labial incompetence (OR 1.06, 95% CI 1.02–1.10, p = 0.029) were significant clinical risk factors independently associated with the presence of alerts. Conclusions: The data collected confirm that atypical swallowing is a key element in the development of malocclusions, with a strong impact on posterior crossbite, anterior overjet, and other occlusal discrepancies. Among the data collected in the diagnostic phase, patients who presented at least one significant alert were also considered and atypical swallowing, low lingual posture, open bite malocclusion, and the presence of labial incompetence were statistically significant. Full article

Background: The development of CAD, FEA, and biomechanical models of the shoulder is challenging due to the joint’s complexity. The spatial relationships between bones, muscles and ligaments are difficult to parameterize, both statically and dynamically, because these structures move three-dimensionally and synergistically. Methods: An assembly of the shoulder joint was developed, including parameterisation of the positional relationships among the rotator cuff structures, with particular focus on the bone components: Humerus, Scapula, Clavicle, and Sternum. Discussion: The abundance of existing CAD models of the shoulder makes it difficult to compare numerical results. Variability in reference frames, positioning assumptions and geometric relationships often hinders reproducibility and cross-study interpretation. Conclusions: The presented methodology supports standardised assembly of a shoulder joint model, ensuring consistent assumptions about the relative positioning of the bony structures. This standardization enables more accurate numerical comparisons across studies and improves the reliability of biomechanical research on the shoulder. Full article

Reinforced concrete structures constitute a fundamental component of modern construction; however, the execution process is highly susceptible to construction errors that may reduce the safety and durability of structural elements. Despite numerous studies addressing failures and degradation mechanisms, there is a lack of methods enabling quantitative, multi-criteria assessment of the significance of individual execution errors. The aim of this article is to identify, evaluate, and prioritize execution errors occurring during the construction of reinforced concrete structures, considering their impact on safety, durability, and repair costs. A hybrid decision-making model combining the fuzzy WINGS and fuzzy TOPSIS methods was developed to enable the assessment of execution errors under uncertainty. The scientific novelty of this study lies in the application of a hybrid fuzzy approach to the evaluation of construction errors in reinforced concrete works, allowing for the simultaneous consideration of criterion importance and the intrinsic ambiguity of expert judgments. Fuzzy WINGS was used to determine the criterion weights, while fuzzy TOPSIS facilitated the development of error rankings. Within the reinforcement-related errors, the most critical were the following: insufficient concrete cover (0.89), non-compliant reinforcement layout (0.82), and reinforcement discontinuity (0.81). Among formwork errors, the highest importance was assigned to exceeding permissible geometric deviations (0.94), while for concreting errors, the most significant were discontinuity of concreting (0.35) and improper technological joints (0.34). The proposed model provides a practical decision support tool for technical supervision, quality management, and risk assessment in reinforced concrete construction. Due to the universal structure of the hybrid fuzzy WINGS–fuzzy TOPSIS methodology itself, the approach may also be adapted in future research to other decision-making problems, should their nature justify the use of fuzzy multi-criteria methods. Full article

The steering linkage represents a key subsystem of any automobile, playing a direct role in vehicle handling, driving safety, and overall comfort. Within this mechanism, the tie rod and tie rod end are crucial for transmitting steering forces from the gear to the wheel hub. A typical issue that gradually develops in these components is the clearance appearing in the spherical joint, caused by wear, corrosion, and repeated operational stresses. Even small clearances can noticeably reduce stiffness and natural frequencies, making the system more sensitive to vibration and premature failure. In this work, the effect of spherical joint clearance on the dynamic behavior of the tie rod-tie rod end assembly was analyzed through numerical simulation combined with experimental observation. Three-dimensional CAD models were meshed with tetrahedral elements and subjected to modal analysis under several clearance conditions, while boundary constraints were set to replicate real operating conditions. Experimental measurements on a dedicated test rig were used to assess joint clearance and wear in service parts. The results indicate a strong nonlinear relationship between clearance magnitude and modal response, with PTFE bushing degradation identified as the main source of clearance. These findings link the evolution of clearance to the change in vibration characteristics, providing useful insight for diagnostic approaches and predictive maintenance aimed at improving steering reliability and vehicle safety. Full article

Joints and other discontinuities in rock masses cause overbreak, underbreak, and instability during tunnel blasting. This paper reviews recent advances in damage control for jointed rock tunnels and validates key findings through numerical simulations. At the microscale, joints affect stress wave propagation, energy distribution, and crack growth patterns. We used ANSYS/LS-DYNA 19.0 to simulate 16 parametric cases and quantify the effects of joint geometry on blasting response. Results show that joint-to-borehole distance is the primary factor controlling damage distribution. A joint dip angle of 45° produces the most severe damage anisotropy, with cracks propagating preferentially along the joint plane. A three-dimensional tunnel model was then developed to assess water-pressure blasting. Compared with conventional methods, water-pressure blasting reduces damage depth by 20.4% and peak particle velocity by 57.6% in jointed rock. The paper also discusses parameter optimization methods, intelligent evaluation techniques, and dynamic control strategies. Engineering recommendations are provided for different geological conditions, including horizontally layered rock, inclined joints, and deep high-stress environments. This work offers both theoretical insights and practical guidance for precision blasting in jointed rock tunnels. Full article

Background: Functional imbalance within the stomatognathic system can develop long before clinical symptoms become evident. Subtle biological changes, such as low-grade inflammation or metabolic disturbance, may precede gingival inflammation, temporomandibular discomfort, or masticatory muscle sensitivity. This study introduces the BioRisk-S (Biological Risk–Stomatognathic System) algorithm, a predictive model designed to identify early systemic alterations associated with the subclinical stage of stomatognathic dysfunction. Methods: A total of 260 clinically healthy adults without apparent stomatognathic disorders were enrolled and evaluated at baseline (T0) and re-examined after six months (T1). Routine laboratory tests were performed to determine high-sensitivity C-reactive protein (hs-CRP), neutrophil-to-lymphocyte ratio (NLR), and 25-hydroxyvitamin D levels. These biomarkers were integrated into the BioRisk-S algorithm to estimate systemic biological imbalance. Follow-up examinations focused on detecting early functional changes, including gingival inflammation, signs of temporomandibular joint (TMJ) dysfunction, and masticatory muscle tenderness. Results: Participants with higher baseline BioRisk-S scores showed significantly higher hs-CRP and NLR values, as well as lower vitamin D levels, indicating a mild but persistent inflammatory profile. After six months, these individuals exhibited early gingival inflammation, muscle tenderness, or mild TMJ discomfort more frequently than those with low BioRisk-S values (p < 0.01). The predictive model demonstrated good accuracy for detecting early biological imbalance preceding clinical dysfunction, with an area under the curve (AUC) of 0.84 (95% CI: 0.78–0.89). Conclusions: The BioRisk-S algorithm represents a feasible, low-cost tool for early systemic screening of functional imbalance within the stomatognathic system. By integrating routine laboratory parameters, this method may help identify individuals at risk before the onset of visible symptoms, supporting preventive and personalized approaches in oral and systemic health management. Full article

Background/Objectives: This study investigates the effect of mild cyclic loads on the stress state of degenerative knee joint cartilages using a combination of experimental data and numerical modeling. Methods: A three-dimensional finite element model of the knee joint was developed based on CT scans, incorporating key components such as the femur, tibia, cartilage layers, and meniscus. Special attention was given to the mechanical properties of cartilages, which were determined through high-sensitivity dynamometer tests of cartilage samples. The experimentally obtained force–displacement curves for cartilage samples affected by third-degree gonarthrosis were integrated into the numerical model. This allowed for an in-depth investigation of the interactions between neighboring tissues of the knee joint under cyclic loading and unloading conditions. Results: Experimental data revealed nonlinear mechanical behavior of cartilage under loading and unloading conditions, characterized by an elastic hysteresis loop. Experimental results demonstrated that degenerated cartilage, under small stresses (up to 0.13 MPa), retains an elastic hysteresis behavior. The numerical simulation provided insights into the stress distribution within the knee joint components, revealing that even in cases of cartilage degeneration, as long as its structural integrity is maintained, mild loads do not cause sufficient stress concentrators, while the longitudinal tears in the same conditions cause the increment of stress values up to 20%. Conclusions: Findings contribute to a better understanding of the mechanical response of degenerative cartilage and offer valuable guidance for the development of therapeutic and rehabilitation strategies for patients with degenerative tissue diseases. Full article

A receipt information extraction task requires both textual and spatial analyses. Early receipt analysis systems primarily relied on template matching to extract data from spatially structured documents. However, these methods lack generalizability across various document layouts and require defining the specific spatial characteristics of unseen document sources. The advent of convolutional and recurrent neural networks has led to models that generalize better over unseen document layouts, and more recently, multi-modal transformer-based models, which consider a combination of text, visual, and layout inputs, have led to an even more significant boost in document-understanding capabilities. This work focuses on the joint use of a neural multi-modal transformer and a rule-based model and studies whether this combination achieves higher performance levels than the transformer on its own. A comprehensively annotated dataset, comprising real-world and synthetic receipts, was specifically developed for this study. The open source optical character recognition model DocTR was used to textually scan receipts and, together with an image, provided input to the classifier model. The open-source pre-trained LayoutLMv3 transformer-based model was augmented with a classifier model head, which was trained for classifying textual data into 12 predefined labels, such as date, price, and shop name. The methods implemented in the rule-based model were manually designed and consisted of four types: pattern-matching rules based on regular expressions and logic, database search-based methods for named entities, spatial pattern discovery guided by statistical metrics, and error correcting mechanisms based on confidence scores and local distance metrics. Following hyperparameter tuning of the classifier head and the integration of a rule-based model, the system achieved an overall F1 score of 0.98 in classifying textual data, including line items, from receipts. Full article

Background: One of the main goals of rehabilitation after stroke is the restoration of motor function. Understanding movement patterns and compensatory strategies is essential to optimize therapy. This study analyzes upper limb kinematics during the Box and Block Test (BBT) to identify and quantify typical post-stroke compensation strategies. Methods: Thirty-one sub-acute stroke participants and thirty-one healthy controls were included. Kinematic data were collected using a 7-IMU system. Joint angles were analyzed with MATLAB R2023a, and 3D trajectories were reconstructed from calibrated quaternions and anthropometric data. Group differences were assessed with the Mann–Whitney test. Compensation strategies were quantified in percentage terms relative to healthy subjects. Results: Significant intergroup differences were observed in mean joint angles and ranges of motion. On the paretic side, participants overused the wrist and shoulder to compensate for reduced elbow and trunk activity. Similar overuse was also observed on the unaffected side. Quantification showed that 83.9% and 80.6% compensate, respectively, with wrist and trunk and 67.7% with the shoulder. Conclusions: Using IMUs during the BBT, this study identified specific compensation strategies that may hinder recovery. It also contributed to developing a quantification scale, supporting more personalized rehabilitation and improved quality of life. Full article

Financial fraud, as a salient manifestation of corporate governance failure, erodes investor confidence and threatens the long-term sustainability of capital markets. This study aims to develop and validate SFG-2DCNN, a multimodal deep learning framework that adopts a configurational perspective to diagnose financial fraud under class-imbalanced conditions and support sustainable corporate governance. Conventional diagnostic approaches struggle to capture the higher-order interactions within covert fraud patterns due to scarce fraud samples and complex multimodal signals. To overcome these limitations, SFG-2DCNN adopts a systematic two-stage mechanism. First, to ensure a logically consistent data foundation, the framework builds a domain-adaptive generative model (SMOTE-FraudGAN) that enforces joint distribution alignment to fundamentally resolve the issue of economic logic coherence in synthetic samples. Subsequently, the framework pioneers a feature topology mapping strategy that spatializes extracted multimodal covert signals, including non-traditional indicators (e.g., Total Liabilities/Operating Costs) and affective dissonance in managerial narratives, into an ordered two-dimensional matrix, enabling a two-dimensional Convolutional Neural Network (2D-CNN) to efficiently identify potential governance failure patterns through deep spatial fusion. Experiments on Chinese A-share listed firms demonstrate that SFG-2DCNN achieves an F1-score of 0.917 and an AUC of 0.942, significantly outperforming baseline models. By advancing the analytical paradigm from isolated variable assessment to holistic multimodal configurational analysis, this research provides a high-fidelity tool for strengthening sustainable corporate governance and market transparency. Full article

With the increasing functional and geometric complexity of modern steel buildings, irregular-shaped beam-to-column joints are becoming common in engineering practice. However, their seismic behavior remains insufficiently understood, particularly for configurations with geometric asymmetry and complex stress transfer mechanisms. This study experimentally investigates the seismic performance of irregular steel-beam-to-concrete-filled steel tube (CFST) column joints incorporating inclined internal diaphragms (IIDs), taking unequal-depth beam (UDB) and staggered beam (SB) joints as representative cases. Two full-scale joint specimens were designed and tested under cyclic loading to evaluate their failure modes, load-bearing capacity, stiffness/strength degradation, energy dissipation capacity, strain distribution, and panel zone shear behavior. Both joints exhibited satisfactory strength and initial stiffness. Although diaphragm fracture occurred at approximately 3% drift, the joints retained 45–60% of their peak load capacity, based on the average strength of several loading cycles at the same drift level after diaphragm failure, and maintained stable hysteresis with average equivalent damping ratios above 0.20. Final failure was governed by successive diaphragm fracture followed by the tearing of the column wall, indicating that the adopted diaphragm thickness (equal to the beam flange thickness) was insufficient and that welding quality significantly affected joint performance. Refined finite element (FE) models were developed and validated against the test responses, reasonably capturing global strength, initial stiffness, and the stress concentration patterns prior to diaphragm fracture. The findings of this study provide a useful reference for the seismic design and further development of internal-diaphragm irregular steel-beam-to-CFST column joints. Full article

Unmanned Aerial Vehicles (UAVs) are playing an increasingly crucial role in large-scale Wireless Sensor Networks (WSNs) due to their high mobility and flexible deployment capabilities. To enhance network sustainability and profitability, this paper proposes a coordinated charging and data-collection system that integrates a green energy base station, Wireless Charging Vehicles (WCVs), and UAVs, ensuring full coverage of all sensor nodes in the target region. On the other hand, the economic feasibility of charging strategies is an essential factor, which is usually neglected. Thus, we further design a joint optimization algorithm to simultaneously maximize system profit and node survivability. To this end, we design a cylindrical-sector-based charging sequence for WCVs. In particular, we develop a dynamic cluster head selection algorithm that accounts for buffer size, residual energy, and inter-node distance. This scheme prevents cluster-head running out of energy before the charging devices arrive, thereby ensuring reliable data transmission. Simulation results demonstrate that the proposed strategy not only maximizes overall profit but also significantly improves node survivability and enhances the sustainability of the wireless sensor network. Full article