Search Results (141)

Several indicators are used in dairy farms to monitor health status during the puerperal period. Uterine disease complex is one of the compromised health issues during this period. This study mainly aims to evaluate the relationship between abnormal vaginal discharge scores (VDS), indicative of uterine health impairment (e.g., metritis), and reproductive and non-reproductive risk factors during the first three weeks postpartum of dairy cows. An ordinal logistic GLMM was used to evaluate the influence of vulvovaginal lacerations, fecal consistency, ketonuria, body condition, parity, day of reproductive evaluation and farm on normal (0–2 points; control group), moderate (3–4), and high (5–9) VDS from 2860 calvings in 14 Danish farms (2023–2025). Vulvar and vaginal lacerations (odds ratio, OR = 2.4 and 17.1, respectively; p < 0.001) and soft feces (OR = 1.7; p < 0.001), ketosis (OR = 1.8; p < 0.001), low body condition score (OR = 1.7; p < 0.01), and multiparous cows (OR = 2.1; p < 0.0001) were associated with moderate and high VDS. These results suggest that vulvovaginal lacerations, even if considered as a potential residual confounder regarding dystocia and other periparturient reproductive abnormalities, and non-reproductive factors, such as fecal consistency, should be included to assess uterine health during postpartum, regarding normal, moderate, and high VDS. A large study involving all relevant reproductive occurrences during puerperium and their impact on further fertility can provide additional information for reproductive herd health management. Full article

The ballistic impact behavior of soft body armor is governed by complex interactions between material architecture and projectile characteristics. This review provides a critical overview of the evolution of textile and composite-based armor materials developed for ballistic protection. Emphasis is placed on experimental and analytical methodologies used to elucidate impact energy dissipation, deformation mechanisms, and failure modes. Key material-related parameters influencing ballistic performance including areal density, weave architecture, yarn crimp, twist, and thread density are systematically discussed, along with assembly variables such as ply orientation, layer number, and hybrid configurations. In parallel, the influence of projectile mass, velocity, and geometry on impact resistance is examined. The review also summarizes internationally adopted ballistic and stab-resistance standards employed for soft armor evaluation. Various assessment techniques, including yarn–yarn friction analysis, puncture resistance testing, ballistic limit velocity determination, and back-face signature measurement, are critically reviewed. Strategies aimed at enhancing impact performance, such as rubber or latex impregnation, fiber surface modification, and the incorporation of shear thickening fluids, are comprehensively discussed. Attention is given to shear thickening fluids due to their significant role in improving energy absorption and flexibility. The fundamental mechanisms governing shear thickening behavior and the parameters affecting their performance are analyzed. Overall, this review highlights emerging material design strategies and performance optimization approaches for next-generation soft body armor systems. Full article

Gait refers to an individual’s unique walking pattern and is a promising biometric for age and gender estimation. Human gait exhibits inherent bilateral symmetry arising from the coordinated movement of the left and right sides of the body. However, occlusion remains a major challenge that disrupts the symmetric structure of gait patterns and degrades recognition performance. This paper investigates the impact of different occlusion types on gait-based age and gender estimation and proposes a Generative Adversarial Network (GAN)-based image restoration model to mitigate occlusion effects. Two occlusion types, namely block-wise and component-specific, are examined. A self-collected dataset of 715 side-walking gait energy images (GEIs) from 120 subjects was synthetically occluded to simulate real-life scenarios. Block-wise occlusion was applied both vertically and horizontally across GEI silhouettes, while component-specific occlusion targeted individual body parts. GAN-based restoration was subsequently applied to occluded images prior to model training. Experimental results confirm that occlusion significantly degrades recognition accuracy, with larger occluded regions causing greater performance drops. Shoulder occlusion most severely impacted age estimation, while head occlusion had the greatest effect on gender estimation. GAN-based restoration substantially recovered lost accuracy, demonstrating the potential of restoration techniques in compensating for missing body information. These findings highlight the importance of upper-body regions in gait-based soft biometrics and demonstrate the need to address occlusion in real-world gait recognition systems. Full article

Background: Craniofacial growth is regulated by a complex interaction of genetic, functional, and systemic metabolic factors. Mechanical loading generated during mastication plays a fundamental role in mandibular development through bone modeling and remodeling mechanisms. In contrast, Type I diabetes mellitus is associated with impaired bone metabolism, which may compromise skeletal growth. Although the independent effects of functional loading and metabolic disorders on bone tissue have been widely investigated, their combined influence on mandibular development remains insufficiently understood. Objective: This study primarily aimed to evaluate the effect of Type I diabetes mellitus on mandibular growth in growing rats and, secondarily, to assess the impact of dietary consistency (hard versus soft food) on mandibular development under diabetic and non-diabetic conditions, as well as determine whether diabetes modifies the mandibular adaptive response to increased masticatory loading. Materials and Methods: An experimental animal study was conducted using twenty-four male Wistar rats aged one month. The animals were randomly allocated into four groups according to metabolic status (control or diabetic) and dietary consistency (hard or soft diet). Type I diabetes mellitus was experimentally induced in the relevant groups using streptozotocin. All animals underwent cone beam computed tomography (CBCT) scanning at baseline (Day 1) and at the end of the experimental period (Day 28). Linear measurements were obtained using specialized software following euthanasia. Two-way ANOVA was used to evaluate the effects of diabetes, diet, and their interaction, using appropriate post hoc tests for multiple comparisons. Categorical variables were analyzed using the chi-square test. A p-value < 0.05 was considered statistically significant. Results: Longitudinal morphometric analysis demonstrated that Type I diabetes mellitus significantly impaired mandibular growth. Diabetic animals exhibited reduced growth rates and smaller final mandibular dimensions compared with controls. Hard diet intake significantly enhanced mandibular development in control animals, reflecting a strong adaptive response to increased functional loading. However, this osteogenic response was markedly attenuated in diabetic rats. Under soft-diet conditions, differences between control and diabetic groups were diminished, indicating that reduced mechanical stimulation limits adaptive growth responses. Significant interaction effects between diabetes and dietary consistency were observed in several morphometric parameters, particularly those related to mandibular body length, ramus height, and condylar position. Conclusions: Type I diabetes mellitus exerts a detrimental effect on mandibular growth in growing rats and compromises the adaptive response of craniofacial structures to mechanical loading. Although a hard diet functions as a potent osteogenic stimulus, its growth-promoting effect is substantially reduced in the presence of metabolic dysfunction. Full article

The vertical landing of quadrotor unmanned aerial vehicles (UAVs) involves highly transient impact dynamics that generate significant vibrations on the UAV body, particularly under uncertain touchdown conditions such as uneven terrain, asymmetric ground contact, and high-impact landing. In this study, a robust semi-active vibration control framework is proposed for a quadrotor UAV equipped with a four-point soft landing gear system. The UAV is modeled as a three-degree-of-freedom rigid body including heave, pitch, and roll motions, while each landing gear leg is represented by an equivalent spring-damper mechanism with adaptively controllable damping characteristics. To evaluate the effectiveness of the proposed framework, PID (Proportional–Integral–Derivative), GA-PID (Genetic Algorithm-Based Proportional–Integral–Derivative), Fuzzy–PID (Fuzzy Logic-Based Proportional–Integral–Derivative), and ANFIS-PID (Adaptive Neuro-Fuzzy Inference System-Based Proportional–Integral–Derivative) controllers are comparatively investigated under five different landing scenarios. The nonlinear touchdown dynamics are implemented in the MATLAB/Simulink environment using a state-space-based simulation model. The results demonstrate that intelligent adaptive control methods significantly improve landing stability and vibration attenuation compared to the conventional PID controller. Among all methods, the ANFIS-PID controller achieved the best overall performance. Under the most severe landing condition, the peak vertical displacement was reduced from 0.114 m to 0.025 m, while the maximum pitch and roll angles decreased from approximately 11° to nearly 2°. Additionally, the settling time was reduced from nearly 10 s to below 3 s. Full article

The Italian grey partridge (Perdix perdix italica Hartert, 1917) is a subspecies endemic to the Italian peninsula, considered extinct in the wild, and it is included in Annex I of the EU Bird Directive. The aim of our project is to reintroduce a viable population of the endemic taxon into a protected area in north-east Italy, using genetically selected founder birds belonging to the original Italian genetic lineage. From 2021 to 2023, a total of 30,078 partridges were reintroduced to Valle del Mezzano using a soft-release method, and 241 of them were equipped with VHF transmitters to evaluate survival, dispersal and spacing behaviour of the released birds. Furthermore, male spring counts using the playback method were performed to assess the number of reproductive pairs. The overall survival was 21.86%; the Cox proportional hazards model, including time-dependent effects, showed that neither sex (HR = 1.20, p = 0.28) nor body mass significantly influenced survival. The release year was included as a stratification factor, and site-level heterogeneity was negligible. These results show that survival dynamics were not explained solely by individual traits. Dispersal distance and spatial behaviour were affected by the release year, while sex had only a minor effect and body mass had no impact. Local heterogeneity contributed to variability but did not override the strong temporal pattern. The number of calling males in spring ranged from 152 to 267, with variations between years. Overall, our findings suggest that post-release performance in reintroduced individuals is influenced more by environmental factors than by inherent individual traits. In conclusion, despite high mortality rates among reintroduced birds, the first breeding nucleus of Italian partridges since their extinction in the wild has been observed. Full article

This study conducts a comparative legal analysis of South Korea’s Framework Act on Artificial Intelligence (enacted January 2025, effective January 2026) and the EU AI Act (effective August 2024), focusing on the structural implications of their divergent regulatory philosophies for sustainable digital governance. Employing legal interpretive analysis (textual, systematic, and teleological) and comparative legal methodology, supplemented by risk-based regulation theory and the theory of hardening of soft norms, this paper examines three interconnected dimensions: the conceptual distinction between “high-impact” and “high-risk” AI, the legal nature of self-regulatory structures, and the potential distortion of civil liability attribution. The analysis reveals that Korea’s adoption of the “high-impact” concept, while strategically reducing compliance costs and avoiding stigma effects, generates significant legal gaps, including potential violations of the constitutional principle of clarity, a “liability lightning rod” phenomenon transferring responsibility from AI operators to frontline practitioners, and insufficient institutional prerequisites for effective self-regulation. In contrast, the EU’s ex-ante preventive framework provides greater legal certainty through direct enumeration of high-risk sectors and mandatory conformity assessments. Drawing on the growing body of EU AI Act scholarship, this paper proposes a five-step legislative model for dynamic regulatory adjustment tailored to Korea’s constitutional structure, encompassing statutory core criteria, periodic re-evaluation with parliamentary oversight, phased mandatory enforcement, and a presumption of conformity system, thereby offering a co-regulatory framework that balances innovation promotion with fundamental rights protection. Full article

Bird strikes are a key threat to aircraft wing leading edges. This investigation evaluates a honeycomb block reinforcement concept to improve bird strike resistance while maintaining structural efficiency. A validated simulation was developed using an explicit dynamic finite element approach, in which the bird was modeled as a soft body using smoothed particle hydrodynamics, and the wing leading edge was represented with a honeycomb block reinforcement concept. A design of experiments based on McKay Latin hypercube sampling was applied to comprehensively examine the effects of the geometric parameters on the maximum von Mises stress and maximum deformation. Response surface regression models were then constructed to approximate the impact responses and analyze the model correctness. These models were subsequently integrated into a constrained optimization methodology using sequential quadratic programming and population-based integrated learning to minimize deformation while limiting stress below the material yield threshold. The optimized honeycomb and skin configuration demonstrated a noticeable optimization of the maximum deformation within the yield stress limit compared with the baseline design. The results confirm that the proposed honeycomb block reinforcement concept, combined with a regression-based optimization strategy, constitutes a practical, computationally effective approach to improving bird strike resistance and provides a feasible design option for future impact-resistant wing leading-edge designs. Full article

Medication-related osteonecrosis of the jaw (MRONJ) represents a major clinical challenge for oral and maxillofacial surgery departments as well as dental practices. With increasing life expectancy and the more frequent use of medications associated with osteonecrosis, the incidence of MRONJ continues to rise. To date, there are no uniform treatment standards with scientifically proven effectiveness for this condition. To evaluate the impact of platelet-rich fibrin (PRF) on the outcomes of MRONJ treatment and to identify factors that may influence the effectiveness of PRF therapy, we conducted a comparative prospective study including 22 patients divided into two groups: patients treated with PRF and patients treated without PRF. PRF was prepared according to the PRF Duo Quattro Process protocol for PRF (Nice, France). The study was registered at ClinicalTrials.gov (NCT07464678). The following parameters were assessed: age, smoking status, gender, lesion location, body mass index (BMI), C-reactive protein (CRP) concentration, pain intensity, presence or absence of fistulas, soft tissue healing and radiological findings. Patients were evaluated preoperatively and postoperatively at 14 days, 6 weeks, and 6 months. The study demonstrated a reduction in pain after surgery among patients treated with PRF. In addition, the use of PRF resulted in improved healing outcomes in patients with elevated CRP. Higher BMI was associated with poorer therapeutic response to PRF. Improvements in soft tissue healing and disease stage were observed in the PRF group; however, these differences did not reach statistical significance. All findings should be interpreted with caution due to the limited sample size. There is still no standardized treatment for MRONJ. The use of platelet-rich fibrin as an inexpensive and safe adjunctive therapy may provide clinical benefits for patients, particularly through a significant reduction in pain. Further large-scale, multicenter studies are required to confirm these findings. Full article

This paper develops a shock-absorbing asphalt mixture for pedestrian pavements that mitigates the impact of normal walking on pedestrians’ bodies by incorporating crumb rubber from recycled tires to produce a soft mixture. This aims to reduce injuries to vulnerable road users, enable the rethinking of urban pavement designs, and address the major challenges facing societies, ultimately achieving more sustainable, resilient, and safer cities. To promote land sustainability, the designed asphalt mixture should be pervious, allowing water to infiltrate into the underlying soil. The development of the asphalt mixture followed an experimental methodology that involved formulating asphalt mixtures with conventional bitumen, polymer-modified bitumen, and bituminous emulsion. The shock-absorbing capability was evaluated by measuring the deformation of the asphalt mixture over time in response to a falling weight from a Light Falling Weight Deflectometer. Permeability capabilities were assessed through the permeability test. Subsequently, the asphalt mixture was characterized according to its macrotexture, friction, air void content, rutting resistance, and stiffness to assess its suitability as a walking surface material. Results indicate that increasing rubber content enhances deformation capacity and improves cushioning but reduces stiffness. Among the solutions, mixtures with polymer-modified bitumen and intermediate rubber content achieved the balance between impact attenuation and mechanical performance. Full article

Material considerations are often neglected when developing digital twins, particularly at the relevant length scales that drive material and structural performance. For reinforced composite materials, the microscale has the largest impact on nonlinear material behavior and progressive damage, and thus accurately representing the disordered microstructure of a composite due to processing and manufacturing is critical to developing the material digital twin in the multiscale hierarchy. Automating microstructure characterization is typically done by either training convolutional neural network models using a pretrained encoder or using prompt-based segmentation tools. In this work, a toolset for developing segmentation models is presented, combining these two methods to enable rapid annotation, training, and deployment of microscopy segmentation models for automated material digital twin development without user knowledge of machine learning. Additionally, a Bayesian optimization framework is developed for generating statistically equivalent representative volume elements (SRVE) to a segmented microstructure using a random microstructure generator that implements soft body dynamics. Progressive failure analysis of random, statistically equivalent, and ordered microstructures is compared to the segmented microstructure subject to transverse loading to demonstrate the importance of accurately representing the driving material length scale of a composite digital twin. Ordered microstructures over-predicted crack initiation and ultimate strength and strain. Random and optimized RVE microstructures better agreed with the segmented simulation results, with no significant difference observed between the two methodologies. The improvement in predicted macroscale behavior for models that capture disordered microstructures due to manufacturing processes demonstrates the importance of capturing microstructure features in composites modeling and indicates that SRVEs that capture microstructural features of the physical material can be used in material digital twin development. Further, the toolsets provided in this work allow for rapid development of composite material digital twins without user expertise in machine learning. This has enabled the development of an integrated workflow to automatically characterize and idealize composite microstructures and generate representative geometric models for efficient micromechanics analysis. Full article

Mechanical harvesting damage is a critical factor constraining potato quality and storage performance. Field curing is a commonly employed pre-treatment prior to mechanical picking of potatoes, which promotes skin suberization and reduces mechanical damage; however, the determination of optimal curing duration lacks a theoretical basis. This study investigated ‘Xisen No. 6’ potatoes at harvest maturity. Curing was performed by field sun-drying (open-air exposure) immediately after mechanical excavation, with five duration gradients (0, 1, 2, 3, and 4 h) established under the recorded meteorological conditions. Twenty-two physical–mechanical and damage parameters were measured, and principal component analysis (PCA) was employed for comprehensive evaluation. The results demonstrated that curing induced a transformation of tubers from “soft-elastic bodies” to “hard-brittle bodies”. This study first revealed the contradictory evolution pattern between skin abrasion damage and tissue impact damage, which exhibited a strong negative correlation (r = −0.89, p < 0.01). PCA indicated that a 3 h curing duration could effectively balance the control of both damage types. These findings provide a quantitative solution to the dilemma of reducing skin damage while controlling impact damage during mechanical potato harvesting, offering significant guidance for optimizing harvesting process parameters and reducing postharvest losses. Full article

The growing demand for marine resource development and in-depth exploration of the marine environment has positioned soft biomimetic underwater vehicles (SBUVs) as a research hotspot in the fields of underwater equipment and soft robotics. SBUVs are characterized by bodies made of flexible and extensible materials, integrating the dual advantages of softness and biomimetics. They can achieve muscle-like continuous deformation to efficiently absorb collision energy, while mimicking the propulsion mechanisms of marine organisms—such as fish and jellyfish—through undulating body movements or cavity contraction and relaxation. Such biomimetic propulsion is highly compatible with the flexible actuation of soft materials, enabling excellent environmental adaptability while maintaining favorable propulsion efficiency. Compared with traditional rigid underwater vehicles, SBUVs offer higher degrees of freedom, superior environmental adaptability, enhanced impact resistance and greater motion flexibility. This review systematically summarizes typical actuation methods for SBUVs—including fluid-powered actuation, shape memory alloy actuation, and electroactive polymer actuation—elaborating on their working principles, key technological advances, and representative application cases on SBUVs. These actuation mechanisms each offer distinct advantages. Fluid-powered systems are valued for high power density and precise motion control through direct fluidic force transmission. Shape memory alloys provide high force output and accurate positional recovery via controlled thermal phase changes. Meanwhile, electroactive polymers stand out for their rapid (often millisecond-scale) dynamic response, low hysteresis, and fine, muscle-like deformation under electrical stimuli. Current challenges are also analyzed, such as limited actuation efficiency, material durability issues, and system integration difficulties. Despite these constraints, SBUVs show broad application prospects in marine resource exploration, ecological monitoring, and underwater engineering operations. Future research should prioritize the development of novel materials, coordinated optimization of actuation and control systems, and breakthroughs in core technologies to accelerate the practical implementation and industrialization of SBUVs. Full article

In side-impact collisions, the occupant in the non-impacted far-side position faces a high risk of death and serious injury. However, current research on injury to far-side occupants remains limited. This study utilized 40 real-world side collision cases to extract dynamic boundary condition parameters of the impacted vehicle through kinematic reconstruction. These parameters were input into a simplified finite element (FE) vehicle model equipped with a human body FE model in the far-side position. Simulation calculations were performed to obtain head and chest injury parameters for the far-side occupant and assess their injury risk. Finally, the study focused on analyzing the effect of vehicle motion boundary conditions on far-side occupant’s injury risk. The assessment based on the head injury criterion HIC₁₅ shows a low head injury risk for the far-side occupant. However, using the BrIC metric, which accounts for head rotational motion, reveals a significant risk of severe traumatic brain injury in some cases. Regarding chest injury, analysis based on the effective plastic strain of ribs indicated a low risk of rib fractures. However, results from the chest viscosity criterion (VC) and internal organ strain analysis suggested a high risk of soft tissue injury in the chest. This computational investigation, leveraging biofidelic human models, underscores that the human body’s response to complex, multi-directional impacts is not fully captured by traditional metrics. This study concludes that addressing the protection of the far-side occupant is essential in side-impact safety design, with particular emphasis on the unique injury risks posed by vehicle rotational motion, potentially inspiring biomimetic safety systems that better adapt to these complex loading conditions. Full article

Objective: To evaluate the impact of the menopausal transition on body composition across different body mass categories and to identify menopause-related changes in lean and fat tissue distribution. Methods: This retrospective cross-sectional study included 325 women whose clinical and body composition data were extracted from existing records. Participants were classified as premenopausal (controls), perimenopausal, or postmenopausal and further stratified by body mass index (BMI) into normal-weight, overweight, and obesity groups. Body composition had been assessed using bioelectrical impedance analysis. Results: Across all BMI categories, postmenopausal women demonstrated significantly lower lean body mass, soft lean mass, skeletal muscle mass, total body water, protein, and mineral content compared with premenopausal and perimenopausal women (p < 0.05). Total and visceral fat area (VFA), body fat percentage (BF), and waist-to-hip ratio were significantly higher, indicating a shift toward central adiposity. These changes were most pronounced in normal-weight women (VFA: 36.4 ± 17.0, 48.3 ± 22.3, and 55.7 ± 23.5 cm²; BF: 24.8 ± 5.3%, 27.2 ± 5.2%, and 28.8 ± 4.6% in pre-, peri-, and postmenopause, respectively), and less marked among overweight women (VFA: 91.5 ± 36.3, 106.1 ± 38.2, and 111.7 ± 28.6 cm²; BF: 36.0 ± 3.6%, 36.4 ± 3.9%, and 37.2 ± 3.2%) and with obesity (VFA: 180.3 ± 62.4, 212.6 ± 96.2, and 175.5 ± 54.4 cm²; BF: 44.5 ± 4.5%, 44.5 ± 5.7%, and 41.9 ± 3.3%), suggesting a relative attenuation of muscle loss at higher BMI. Conclusions: Postmenopausal women showed a clear shift toward lower lean mass and greater central adiposity across BMI categories. These patterns indicate a consistent deterioration in body composition during the menopausal transition. Assessment of visceral fat in postmenopausal women is crucial, as its accumulation is closely linked to cardiometabolic risk. Menopause-related hormonal changes favor central adiposity, supporting the use of visceral fat as a key indicator for early risk stratification and preventive interventions in midlife women. Full article