Search Results (3,721)

The growing demand for precision and consistency in the forging industry has heightened the need for predictive simulation tools. While extensive research has focused on parameters such as flow stress, die wear, billet fracture, and residual stresses, the phenomenon of billet buckling, especially during cold upset forging, remains underexplored. Most existing models address only elastic buckling for slender billets using classical approaches like Euler and Rankine-Gordon formulae, which are not suitable for inelastic deformation in shorter billets. This study presents a numerical model developed to analyze inelastic buckling during cold forging and to determine associated stresses and deflection characteristics. The model was validated through finite element simulations across a range of billet geometries (10–40 mm diameter, 120 mm length), materials (aluminum, stainless steel, and copper), and friction coefficients (µ = 0.12, 0.16, and 0.35). Stress distributions were evaluated against die stroke, with particular emphasis on the influence of strain hardening and geometry. The results showed that billet geometry and strain-hardening exponent significantly affect buckling behavior, whereas friction had a secondary effect, mainly altering overall stress levels. A nonlinear regression approach incorporating material properties, geometric parameters, and friction was used to formulate the numerical model. The developed model effectively estimated buckling stresses across various conditions but could not precisely predict buckling points based on stress differentials. This work contributes a novel framework for integrating material, geometric, and process variables into stress prediction during forging, advancing defect control strategies in industrial metal forming. Full article

US food regulatory agencies have adopted a preference for researchers and testing labs to use ‘acid adapted challenge cultures’ when performing inoculated validation studies of food processes that involve acidic treatments to accustom the cultures to acidic pH so that they will not be easily affected during processing. We evaluated acid adaptation in regard to the processing of South African style air-dried beef, notably biltong and droëwors, using a mixture of five serovars of Salmonella as well as a unique serovar isolated from dried beef (Salmonella Typhimurium 1,4,[5],12:i:-). Acid adaptation was obtained by growing cultures in tryptic soy (TS) broth containing 1% glucose. Non adapted cultures were obtained by growth in TS broth without glucose or in TS broth with 1% glucose but buffered with 0.2 M phosphate buffer. Processes included biltong (dried solid beef) and droëwors (ground, sausage-style). Each trial was performed twice and triplicate samples were examined at each sampling point (i.e., n = 6). Statistical analysis was applied using analysis of variance (ANOVA) or one-way repeated measures (RM-ANOVA) and the Holm–Sidak test for pairwise multiple comparisons to determine significant differences (p < 0.05). We observed that in all processes examined (eight trials), treatments using acid adapted cultures were more sensitive to the biltong and droëwors processes, giving greater reductions (5.3-log reduction) than when non-adapted cultures were used (3.8-log reduction). Acid adaptation leads to stressed conditions in Salmonella resulting in sensitization to the multiple hurdles found in biltong and droëwors processing (acid/vinegar, salt, desiccation). Based on our data, the use of non adapted Salmonella cultures to achieve desired challenge culture process lethality could result in more robust processing conditions and a greater level of safety in these products as intended by US regulatory guidance. Full article

This paper proposes a multi-sensor data-fusion-based method for real-scene 3D reconstruction and digital twin visualization of coal mine tunnels, aiming to address issues such as low accuracy in non-photorealistic modeling and difficulties in feature object recognition during traditional coal mine digitization processes. The research employs cubemap-based mapping technology to project acquired real-time tunnel images onto six faces of a cube, combined with navigation information, pose data, and synchronously acquired point cloud data to achieve spatial alignment and data fusion. On this basis, inner/outer corner detection algorithms are utilized for precise image segmentation, and a point cloud region growing algorithm integrated with information entropy optimization is proposed to realize complete recognition and segmentation of tunnel planes (e.g., roof, floor, left/right sidewalls) and high-curvature feature objects (e.g., ventilation ducts). Furthermore, geometric dimensions extracted from segmentation results are used to construct 3D models, and real-scene images are mapped onto model surfaces via UV (U and V axes of texture coordinate) texture mapping technology, generating digital twin models with authentic texture details. Experimental validation demonstrates that the method performs excellently in both simulated and real coal mine environments, with models capable of faithfully reproducing tunnel spatial layouts and detailed features while supporting multi-view visualization (e.g., bottom view, left/right rotated views, front view). This approach provides efficient and precise technical support for digital twin construction, fine-grained structural modeling, and safety monitoring of coal mine tunnels, significantly enhancing the accuracy and practicality of photorealistic 3D modeling in intelligent mining applications. Full article

Point cloud processing of raw scan data is a critical step to enhance the accuracy and efficiency in computer-aided inspection and remanufacturing of damaged aero-engine blades. This paper presents a new methodology to obtain a noise-reduced and simplified dataset from the raw scan data while preserving the underlying geometry of the damaged blade in high-curvature and damaged regions. At first, outliers are removed from the scan data, and measurement noise is reduced through local least-squares quadric surface/plane fitting on the adaptive support domain of measured points under the measurement uncertainty constraint of inspection data. Then, a directed Hausdorff distance-based region growing scheme is developed to progressively search within the support domain of denoised data points to obtain a down-sampled dataset while preserving the local geometric shape of the surface. Numerical and experimental case studies have been conducted to evaluate the accuracy and computation time of scan-to-CAD rigid registration and CAD-to-scan non-rigid registration processes using the down-sampled dataset of damaged blades. The results have demonstrated that the proposed methodology effectively removes the measurement noise and outliers and provides a down-sampled dataset from the scan data that can significantly reduce the time complexity of the computer-aided inspection and remanufacturing process of the point cloud of damaged blades with a negligible loss of accuracy. Full article

This work has reviewed the recently published literature (last 8 years) about the effects caused by HPP on the antioxidant properties (A, C, and E vitamins and antioxidant activity) of F&V (fruits and vegetables) preparations in comparison to thermal treatments (TP). The methodology of this revision was performed mainly by using keywords related to HPP, F&V, and antioxidant compounds in the Scopus database. High-pressure technology was briefly described, considering its principles and historical milestones, and justifying that it can be applied as a green and sustainable preservation method (with pros and cons). It is also relevant for the present food market due to their growing tendency in F&V derivatives (especially juices). The main effects on vitamins and antioxidant compounds point to it as an emerging preservation method to maintain and avoid vitamin and bioactive substances loss in comparison with pasteurization by heat. Maximum efficiency, cost-effectiveness, and quality improvement are aspects to be improved in the future by HPP technologies. Full article

The rapid and reliable acquisition of canopy-related metrics is essential for improving decision support in viticultural management, particularly when monitoring individual vines for targeted interventions. This study presents a spatially explicit workflow that integrates Uncrewed Aerial System (UAS) imagery, 3D point-cloud analysis, and Object-Based Image Analysis (OBIA) to detect and monitor individual grapevines throughout the growing season. Vines are identified directly from 3D point clouds without the need for prior training data or predefined row structures, achieving a mean Euclidean distance of 10.7 cm to the reference points. The OBIA framework segments vine vegetation based on spectral and geometric features without requiring pre-clipping or manual masking. All non-vine elements—including soil, grass, and infrastructure—are automatically excluded, and detailed canopy masks are created for each plant. Vegetation indices are computed exclusively from vine canopy objects, ensuring that soil signals and internal canopy gaps do not bias the results. This enables accurate per-vine assessment of vigour. NDRE values were calculated at three phenological stages—flowering, veraison, and harvest—and analyzed using Local Indicators of Spatial Association (LISA) to detect spatial clusters and outliers. In contrast to value-based clustering methods, LISA accounts for spatial continuity and neighborhood effects, allowing the detection of stable low-vigour zones, expanding high-vigour clusters, and early identification of isolated stressed vines. A strong correlation (R² = 0.73) between per-vine NDRE values and actual yield demonstrates that NDRE-derived vigour reliably reflects vine productivity. The method provides a transferable, data-driven framework for site-specific vineyard management, enabling timely interventions at the individual plant level before stress propagates spatially. Full article

Cardiovascular diseases (CVDs) remain the leading cause of global mortality, with ischemic heart disease (IHD) being the most prevalent and deadly subtype. The growing burden of IHD underscores the urgent need for effective early detection methods that are scalable and non-invasive. Heart Rate Variability (HRV), a non-invasive physiological marker influenced by the autonomic nervous system (ANS), has shown clinical relevance in predicting adverse cardiac events. This study presents a photoplethysmography (PPG)-based Zhurek IoT device, a custom-developed Internet of Things (IoT) device for non-invasive HRV monitoring. The platform’s effectiveness was evaluated using HRV metrics from electrocardiography (ECG) and PPG signals, with machine learning (ML) models applied to the task of early IHD risk detection. ML classifiers were trained on HRV features, and the Random Forest (RF) model achieved the highest classification accuracy of 90.82%, precision of 92.11%, and recall of 91.00% when tested on real data. The model demonstrated excellent discriminative ability with an area under the ROC curve (AUC) of 0.98, reaching a sensitivity of 88% and specificity of 100% at its optimal threshold. The preliminary results suggest that data collected with the “Zhurek” IoT devices are promising for the further development of ML models for IHD risk detection. This study aimed to address the limitations of previous work, such as small datasets and a lack of validation, by utilizing real and synthetically augmented data (conditional tabular GAN (CTGAN)), as well as multi-sensor input (ECG and PPG). The findings of this pilot study can serve as a starting point for developing scalable, remote, and cost-effective screening systems. The further integration of wearable devices and intelligent algorithms is a promising direction for improving routine monitoring and advancing preventative cardiology. Full article

This paper investigates soliton solutions of the time-fractional Biswas–Arshed (BA) equation using the Extended Simplest Equation Method (ESEM). The model is analyzed under two distinct fractional derivative operators: the $\beta$-derivative and the M-truncated derivative. These approaches yield diverse solution types, including kink, singular, and periodic-singular forms. Also, in this work, a nonlinear second-order differential equation is reconstructed as a planar dynamical system in order to study its bifurcation structure. The stability and nature of equilibrium points are established using a conserved Hamiltonian and phase space analysis. A bifurcation parameter that determines the change from center to saddle-type behaviors is identified in the study. The findings provide insight into the fundamental dynamics of nonlinear wave propagation by showing how changes in model parameters induce qualitative changes in the phase portrait. The derived solutions are depicted via contour plots, along with two-dimensional (2D) and three-dimensional (3D) representations, utilizing Mathematica for computational validation and graphical illustration. This study is motivated by the growing role of fractional calculus in modeling nonlinear wave phenomena where memory and hereditary effects cannot be captured by classical integer-order approaches. The time-fractional Biswas–Arshed (BA) equation is investigated to obtain diverse soliton solutions using the Extended Simplest Equation Method (ESEM) under the $\beta$-derivative and M-truncated derivative operators. Beyond solution construction, a nonlinear second-order equation is reformulated as a planar dynamical system to analyze its bifurcation and stability properties. This dual approach highlights how parameter variations affect equilibrium structures and soliton behaviors, offering both theoretical insights and potential applications in physics and engineering. Full article

Pertussis is an infectious disease that contributes to hundreds of thousands of deaths worldwide each year. Despite the prevalence of preventive vaccination programs, there has been an increasing number of new cases of the disease over the past few decades. This poses a particular problem for the pediatric population among whom the highest mortality from the disease is recorded. Several reasons for this phenomenon can be mentioned, but what is particularly important from the microbiological point of view is the correlation of the increased number of pertussis cases with the introduction of a new form of vaccine—the acellular vaccine in place of the whole-cell vaccine. In this review, we summarized the current state of knowledge on potential factors that may contribute to the decline in immunization efficacy against the pathogen. The post-vaccination response profile, symptomatic of vaccination with vaccination-acellular, is characterized by recruitment of Th₂ and Th₁₇ lymphocytes; it has been reported that in the long term, this results in insufficient activation of B cells and low titers of antibodies to key bacterial antigens (hemagglutinin, pertactin). Moreover, the immune response proceeds by bypassing the recruitment of tissue-resident memory T cells, resulting in a lack of protection against colonization of the nasal cavity by the bacterium despite vaccination. The decline in vaccination efficacy should also be attributed to the phenotypic variability of Bordetella. The popularization of the PtxP3 strain, characterized by its ability to incompletely activate immune mechanisms, poses a real threat to public health. The growing resistance of B. pertussis to standardly used antibiotics including macrolides also remains a problem. This makes it difficult to eradicate pathogens from the nasal cavity area and increases the pool of bacterial carriers in the population area. The increasing prevalence of the disease prompts reflection on more effective methods of prevention. Particularly promising in this field seem to be new vaccines, especially mucosally implemented, e.g., intranasal, or developed on the basis of B. pertussis antigens other than those used so far. Full article

Rapid urbanization and frequent extreme events have made urban flooding a growing threat to residents. This issue is acute in old urban districts, where extremely limited land resources, outdated standards and poor infrastructure have led to inadequate drainage and uneven pipe settlement, heightening flood risk. This study applies InfoWorks ICM Ultimate (version 21.0.284) to simulate flooding in a typical old urban district for six return periods. A risk assessment was carried out, flood causes were analyzed, and mitigation strategies were evaluated to reduce inundation and cost. Results show that all combined schemes outperform single-measure solutions. Among them, the green roof combined with pipe optimization scheme eliminated high-risk and medium-risk areas, while reducing low-risk areas by over 78.23%. It also lowered the ponding depth at key waterlogging points by 70%, significantly improving the flood risk profile. The permeable pavement combined with pipe optimization scheme achieved similar results, reducing low-risk areas by 77.42% and completely eliminating ponding at key locations, although at a 50.8% higher cost. This study underscores the unique contribution of cost-considered gray-green infrastructure retrofitting in old urban areas characterized by land scarcity and aging pipeline networks. It provides a quantitative basis and optimization strategies for refined modeling and multi-strategy management of urban waterlogging in such regions, offering valuable references for other cities facing similar challenges. The findings hold significant implications for urban flood control planning and hydrological research, serving as an important resource for urban planners engaged in flood risk management and researchers in urban hydrology and stormwater management. Full article

Within the context of urban sustainability, the renewal and activation of communities have received growing attention. Public art, as a common approach to community revitalization, has long been regarded as an effective means of addressing urban and community issues. Basic human senses serve as a bridge between residents and community spaces, offering an effective entry point for creating human-oriented spaces. This study addresses the challenge of insufficient spatial vitality in community spaces by examining how sensory interventions can enhance residents’ participation in public art and thereby contribute to the revitalization of communities. To guide this inquiry, a theoretical framework was constructed based on sensory marketing theory and the Stimulus–Organism–Response (SOR) model, focusing on three core dimensions: sensory stimuli, perceptual responses, and behavioral intention. The study further investigated the relationship between public art and residents’ willingness to participate through five types of sensory stimuli, using a measurement scale and Structural Equation Modeling (SEM), with eight public art installations in Shanghai serving as case references. It also assessed the relative strength of each effect. Participant interviews and non-participatory observations were subsequently conducted for validation and supplementary analysis. The results show that residents’ participation willingness in community public art is directly influenced by perceptual responses (emotional fluctuations, cognitive memory, and physiological responses), and indirectly influenced by different sensory stimuli. Cognitive memory, shaped mainly by olfactory and visual stimuli, emerged as the most important factor in encouraging participation. Participation willingness also varies across generations, and different sensory stimuli are associated with distinct participation patterns. Based on empirical data from Shanghai’s community activation practices, the study proposes implementation strategies guided by the Theory of Planned Behavior (TPB) to enhance spatial vitality, promote community activation, and support sustainable development. Full article

Background/Objectives: Electrical threshold testing (ETT) offers a promising method for assessing somatosensory function. Despite its growing use, fundamental aspects such as the physiological recovery time required between repeated threshold measurements remain poorly understood. This gap is critical when evaluating sensory, motor, or pain thresholds (EST, EMT, EPT) in pre–post designs or rapid intra-session protocols. The aim is to investigate the short-term recovery dynamics of electrical thresholds following electrical threshold testing, and to determine the minimum interval required for values to return to a stable baseline. Methods: In this pilot, repeated-measures study, 10 healthy adults (20 upper limbs) underwent three progressive stimulation trials (sensory, motor, and pain). Electrical thresholds were assessed at fixed recovery intervals (0–120 s), with duplicate measurements at each time point. Stability was defined as the absence of significant differences between repeated measures. Results: EST stabilized rapidly after sensory or motor stimulation, showing no significant differences beyond 0 and 15 s, respectively. Within pain stimulation, EST recovered at 60 s. EMT showed immediate recovery with motor stimulation and required longer recovery with pain stimulation, with stabilization observed at 90 s. EPT exhibited the highest variability, with the smallest time-dependent differences observed immediately after the first assessment. Conclusion: Recovery time after electrical stimulation varies by threshold type and intensity of the stimuli. EST and EMT can be reliably reassessed immediately after sensory and motor stimulation, respectively. However, when stimulation reaches EPT level, EST requires 60 s to recover and EMT needs 90 s. EPT demonstrates higher variability, indicating the need for further investigation. These findings support the implementation of standardized recovery intervals in ETT and underscore the importance of interpreting EPT results with caution during rapid assessments. Full article

Participation in sports and the presence of sports injuries have a lasting impact on youth athletes’ physical, cognitive, and emotional development and sense of self-identity. There is an ongoing growth in participation in sports for youth, as well as growing literature on the epidemiology and outcomes of sports-related injuries. However, there is a paucity of published research regarding the psychological aspects of sports injury, including psychosocial factors, stressors, and responses, from the perspective of young athletes. Key risk factors include the youth’s sex, the types of sports activity, and any previous injuries. Psychosocial models, such as the stress-injury model, help explore such risk factors and their relationship to outcomes of stress. Implications for sports injury outcomes vary within the pediatric population, and the recovery and rehabilitation process requires integrated healthcare to optimize health and mental health outcomes. This review aims to describe the psychosocial factors related to sports injuries in children and adolescents, provide an understanding of sports injury models for youth athletes, and point to recovery and prevention through integrated behavioral health interventions. Based on a literature search, we identified 40 articles most relevant to our aims to explore psychosocial factors and stressors, predisposing and risk factors, and developmental aspects of sports injuries in children and adolescents. Full article

Codex 462 of the Fondo Hortus Pisanus of the Biblioteca Universitaria of Pisa is a precious example of a 16th century illustrated herbal, Icones variarum plantarum, containing 35 tempera paintings by the German soldier Georg Dyckman, an amateur but highly talented artist. The manuscript was recently restored on the occasion of an international exhibition; the necessary preliminary studies for the restoration included a series of in situ diagnostic studies using contactless techniques (digital microscope, multispectral imaging, XRF, Raman and ER-FTIR). These analyses proved useful in deepening the knowledge of the materials and the execution technique of this type of illustrated herbals and in choosing the most appropriate solutions during the restoration phase. In view of the growing interest in this type of historical evidence, which involves both art history and the history of science, this study offers an interesting new perspective on the subject, useful both from a technical point of view for future conservation and for analytical and historical artistic studies. Full article

With the growing global deployment of Fiber-to-the-Home (FTTH) networks driven by the demand for ensuring high-capacity broadband services, mobile network operators (MNOs) face challenges of excessive energy consumption (EC) of wired optical access networks (OANs). This paper presents a comprehensive review of methods aimed at improving the energy efficiency (EE) of wired access passive optical networks (PONs) and active optical networks (AONs). The most important energy management and power-saving methods for Optical Line Terminals (OLTs) and Optical Network Units (ONUs), as key OAN components, are overviewed in the paper. Special attention in the paper is further given to analyzing the impact of a constant increase in the number of subscribers and average data rate per subscriber on global instantaneous power and annual energy consumption trends of FTTH Gigabit PONs (GPONs) and FTTH point-to-point (P-t-P) networks. The analysis combines the real ONU/OLT device-level power profiles and the number of installed OLT and ONU devices with data traffic and subscriber growth projections for the period 2025–2035. A comparative EE analysis is performed for different MNO FTTH OAN architectures and technologies, point-of-presence (PoP) subscriber capacities, and GPON-to-P-t-P subscriber distribution ratios. The findings indicate that different FTTH PON and AON architectures, FTTH technologies, and PON-to-AON subscriber distributions can yield significantly different EE gains in the future. This review paper can serve as a decision-making guide for MNOs in balancing performance and sustainability goals, and as a reference for researchers, engineers, and policymakers engaged in designing next-generation wired optical access networks with minimized environmental impact. Full article