Search Results (685)

This study develops an analytical model for the plastic bending of anisotropic sheet materials, incorporating strain-hardening effects. The model, experimentally validated with aluminum alloy samples and digital image correlation, accurately predicts stress–strain distributions, bending moments, and thinning behavior in the bending processes. The results reveal that while plastic anisotropy significantly increases the strain intensity, enhancing it by up to 15% on the inner surface relative to the outer under identical bending radius, it does not affect the position of the neutral layer. Strain hardening, on the other hand, raises the bending moment by approximately 12% and contributes to material thinning, which can reach 3% at smaller bend radii. Furthermore, quantitative analysis shows that decreasing the bend radius intensifies the strain, impacting the final geometry of the workpiece. These findings provide valuable insights for optimizing die design and material selection in forming processes involving anisotropic materials, enabling engineers to more precisely control the force requirements and product dimensions in applications where accurate bending characteristics are critical. Full article

Objectives: The aim of this study is to assess the oxidative stress status in patients requiring intensive care unit (ICU) admission before initiating ICU treatment, by measuring the total oxidant level (TOS) and total antioxidant level (TAS) and oxidative stress index (OSI) levels. Additionally, we aim to explore the correlation between these oxidative stress markers and biochemical and hematological parameters. Materials and Methods: A total of 153 patients treated in intensive care units were included in the study. Patients who met the patient admission criteria of the ethics committee of the intensive care medicine association were included in the study. Blood samples were taken at the first moment the patients were admitted to the intensive care unit (before starting treatment). In total, 60 healthy volunteers who were compatible with the patient group in terms of age and gender were included in the study as a control group. Patients who had previously received antioxidant treatment and cancer patients were excluded from the study. Results: The TOS was significantly higher in the patient group (13.4 ± 7.5) compared to controls (1.8 ± 4.4) (p = 0.021). TOS > 12.00 means a “very high oxidant level”. OSI was significantly higher in the patient group (689.8 ± 693.9) compared to the control group (521.7 ± 546.6) (p = 0.035). Ferritin levels were significantly higher in the patient group (546.5 ± 440.8 ng/mL) compared to controls (45.5 ± 46.5 ng/mL) (p < 0.001). Patients had significantly higher levels of C-reactive protein (CRP), procalcitonin (PCT), white blood cells (WBCs), immature granulocytes (IGs), zinc, and copper compared to the control group, indicating elevated inflammation and oxidative stress. CRP levels were 76.6 ± 85.9 mg/L in patients versus 5.6 ± 15.1 mg/L in controls (p < 0.001). PCT levels were 15.8 ± 8.6 ng/L in patients versus 2.3 ± 7.2 ng/L in controls (p = 0.012). Zinc and copper were also significantly elevated (p = 0.012 and p = 0.002, respectively). Conclusions: Our study provides valuable insights into the relationship between oxidative stress, inflammation, and trace elements, contributing to the growing understanding of oxidative stress as a prognostic tool in critical care. This could help to tailor therapeutic strategies aimed at reducing oxidative damage in ICU patients, enhancing patient outcomes. Full article

This study investigates the impact of soil–structure interaction (SSI) and foundation–soil–foundation interaction (FSFI) on the dynamic behaviour of jacket substructures founded on buckets for offshore wind turbines. A parametric analysis was conducted, focusing on critical load cases for conservative foundation design. Different load configurations were examined: collinear wind and wave (fluid–structure interaction) loads, along with misaligned configurations at 45° and 90°, to assess the impact of different loading directions. The dynamic response was evaluated through key structural parameters, including axial forces, shear forces, bending moments, and stresses on the jacket. Simulations employed the National Renewable Energy Laboratory (NREL) 5MW offshore wind turbine mounted on the OC4 project jacket founded on suction buckets. An additional optimised jacket design was also studied for comparison. An OpenFAST model incorporating SSI and FSFI considering a homogeneous soil profile was employed for the dynamic analysis. The results highlight the significant role of the FSFI on the dynamic behaviour of multi-supported jacket substructure, affecting the natural frequency, acceleration responses, and internal forces. Full article

Lodging is one of the major problems in rice production. However, few genes that can explain the culm strength within the temperate japonica subspecies have been identified. In this study, we identified OsRLCK191, which encodes receptor-like cytoplasmic kinase and plays critical roles in culm strength. OsRLCK191 mutants were produced by the CRISPR-Cas9 DNA-editing system. Compared with wild types (WTs), the bending moment of the whole plant (WP), the bending moment at breaking (BM), and the section modulus (SM) were decreased in rlck191 significantly. Although there is no significant decrease in the culm length of rlck191 compared with the WT; in the mutant, except the length of the fourth internode being significantly increased, the lengths of other internodes are significantly shortened. In addition, the yield traits of panicle length, thousand-seed weight, and seed setting rate decreased significantly in rlck191. Moreover, RNA-seq experiments were performed at an early stage of rice panicle differentiation in shoot apex. The differentially expressed genes (DEGs) are mainly involved in cell wall biogenesis, cell wall polysaccharide metabolic processes, cellar component biogenesis, and DNA-binding transcription factors. Transcriptome analysis of the cell wall biological process pathways showed that major genes that participated in the cytokinin oxidase/dehydrogenase family, cellulose synthase catalytic subunit genes, and ethylene response factor family transcription factor were related to culm strength. Our research provides an important theoretical basis for analyzing the lodging resistance mechanism and lodging resistance breeding of temperate japonica. Full article

In modern infrastructure construction, the socket joint of concrete pipelines is a critical component in ensuring the overall stability and safety of the pipeline system. This study conducted monotonic and cyclic bending loading tests on DN300 concrete pipeline socket joints to thoroughly analyse their bending mechanical properties. The experimental results indicated that during monotonic loading, the relationship between the joint angle and bending moment exhibited nonlinear growth, with the stress state of the socket joint transitioning from the initial contact between the rubber ring and the socket to the eventual contact between the spigot and socket concrete. During the cyclic loading phase, the accumulated joint angle, secant stiffness, and bending stiffness of the pipeline interface significantly increased within the first 1 to 7 cycles and stabilised between the 8th and 40th cycles. After 40 cycles of loading, the bending stiffness of the joint reached 1.5 kN·m², while the stiffness of the pipeline was approximately 8500 times that of the joint. Additionally, a finite element model for the monotonic loading of the concrete pipeline socket joint was established, and the simulation results showed good agreement with the experimental data, providing a reliable basis for further simulation and analysis of the joint’s mechanical performance under higher loads. This study fills the gap in research on the mechanical properties of concrete pipeline socket joints, particularly under bending loads, and offers valuable references for related engineering applications. Full article

The objective of this paper is to investigate the influence of earthmoving vehicle load position on the deformation and internal force characteristics of a deep excavation (DE) support structure. The position of the earthmoving vehicle load near a DE is described by the horizontal distance between the earthmoving vehicle load and the DE. A two-dimensional finite element model is established for simulating DE engineering under the earthmoving vehicle load. The load of the earthmoving vehicle is treated as the static load, and the influence of the earthmoving vehicle load on the excavation support structure is considered from the static point of view. The numerical results of the finite element model agree well with the measured data from the field, which verifies the validity of the model. On the basis of this model, multiple models are established by changing the horizontal distance (D) between the earthmoving vehicle and the DE. The influence of D on the support structure and its critical magnitude for ensuring safety were studied. The results show that the underground diaphragm wall (UDW) is the main component for which horizontal displacement occurs under the earthmoving vehicle load. The horizontal displacements of the support structure exhibit an asymmetric distribution. When D decreases from 20 m to 0.5 m, the horizontal displacement of the UDW near the loading side increases, and the maximum horizontal displacement occurs at the top of the excavation support structure. The critical magnitude of D for ensuring safety is found to be 1 m. When D is less than 1 m, the DE is in an unsafe state. The UDW is the main component subject to the bending component. The bending moment distribution exhibits an “S” shape. The maximum bending moment increases with the decrease in D, and it occurs at the intersection of the second support and the UDW. As D decreases, the axial force in the first internal support changes from pressure to tension. The axial forces in the second and third internal supports are both pressures. The axial force in the third internal support is the largest. The research results have a positive effect on the design and optimization of DE support structures under the earthmoving vehicle load. Full article

Raymond Williams’s concept of the “structure of feeling” aims to describe the shared experiences, attitudes, and emotions of social groups at specific historical moments. However, this theory has been criticized for lacking a rigorous theoretical framework, clear definitions, and boundaries, as well as for failing to adequately explain its interaction with mainstream ideology. This paper attempts to address these issues through the lens of the Brazilian Liberation Theology movement. The “structure of feeling” established by Brazilian Liberation Theology departed from the traditional hierarchical system of the Church, aligning itself instead with emerging cultures and the practices of grassroots church communities. Under the repression of the military government, the mainstream Church began to accept certain aspects of Liberation Theology rather than viewing it solely as radical and threatening. Although Liberation Theology gradually waned after the fall of the military regime, its adjusted “structure of feeling”—devoid of its radical elements but still focused on social justice and poverty—profoundly impacted the global Catholic Church. The experience of the Brazilian Liberation Theology movement illustrates that a “structure of feeling” can transcend the dichotomy between consciousness and materiality and the crux lies in individuals discovering and asserting their own existence; such a “structure of feeling” can either emerge from within existing ideologies or challenge them directly; its relationship with mainstream ideology is significantly shaped by specific historical contexts; certain facets of emerging emotions are selectively incorporated into mainstream ideology, typically in ways that mitigate their more radical implications. Full article

Throughout this article, an alternative depreciation method for electric vehicles (EVs) is presented, addressing the challenge of information asymmetry—a common issue in secondary markets. The proposed method is contrasted with traditional models, such as the Straight-Line Method (SLM), the Declining Balance Method, and the Sum-of-Years Digits (SYD) method, as these classic approaches fail to adequately consider key factors such as mileage and secondary aspects like battery degradation and rapid technological obsolescence, which critically impact the residual value of used EVs. The presented approach employs an adverse selection model that incorporates buyers’ and sellers’ perceptions of vehicle quality from the information recorded on e-commerce platforms, improving the depreciation estimation. The results show that the proposed method offers greater accuracy by leveraging asymmetric information extracted from web portals. Specifically, the method identifies a characteristic intersection point, marking the moment when the model aligns most closely with the data obtained through traditional methods in terms of precision. The analysis through the density of price estimations by vehicle model year indicates that, beyond 1.8 months, the proposed model provides more reliable results than traditional methods. The proposed model allows buyers to identify undervalued assets and sellers to obtain a fair market value, mitigating the risks associated with adverse selection, reducing uncertainty, and increasing market transparency and trust. It fosters equitable pricing between buyers and sellers by addressing the implications of adverse selection, where sellers—possessing more information about the vehicle’s condition than buyers—can dominate market transactions. This model restores balance by ensuring fairer valuation based on vehicle usage, primarily addressing the lack of critical data available on e-commerce platforms, such as battery certifications, among others. Full article

Wave-induced forces pose significant challenges to marine structures, especially pile groups, where cap structures and pile spacings play critical roles in load distribution and structural stability. A physical wave flume experiment was conducted to investigate the influences of cap structures and pile spacings on wave load distributions under different wave conditions. Spatial and temporal variations in wave load distributions, including temporal variations in horizontal force, were measured as wave pressure rather than force. The results demonstrate that cap structures significantly alter the distributions of wave loads on pile groups. The integration of the cap increases the horizontal forces on the front pile and slightly reduces the vertical pressures across the pile group, particularly on the rear pile at relatively low elevations. The cap also delays the peak moment of horizontal force, especially in shallow water depths, where impact loads are more prominent and the cap induces water splash-back. Additionally, reducing pile spacing mitigates interference effects, optimizing the load distribution across piles by modulating flow velocity and pressure. The vertical pressure distribution exhibits a tiered pattern, with lower sections experiencing consistent loading, middle sections being subjected to higher loads at larger spacings, and upper sections being more affected by the cap at smaller spacings. As wave velocity and water depth increase, the differences in pressure intensity between pile groups with and without cap structures decrease, indicating the stabilizing effect of wave characteristics on structural response. This study provides insights into the design of marine pile group structures to optimize their performance characteristics under dynamic wave loading conditions. Full article

In recent years, with the advancement of urbanization and the increase in traffic congestion, the demand for autonomous driving has been steadily growing in order to promote sustainable urban development. The evolution of automotive autonomous driving systems significantly influences the progress of sustainable urban development. As these systems advance, user evaluations of their performance vary widely. Autonomous driving systems present both technological advantages and controversies, along with challenges. To foster the development of autonomous driving systems and facilitate transformative changes in urban traffic sustainability, this research aims to explore user behavior regarding the continued use of autonomous driving systems. It is based on an extended technology acceptance model, examining the impacts of user scale, perceived importance, post-experience regret, user driving habits, and external factors on the intention to continue using these systems. The conclusions are as follows. (1) A model design is constructed that uses user scale, perceived importance, and regret after experience as antecedent variables, with user driving habits as a mediating variable to explain the intention to continue using autonomous driving systems, demonstrating a degree of innovation. (2) It is verified that user driving habits are a key factor determining the intention to continue using these systems, highlighting the importance of user habits in the application of autonomous driving systems. (3) Perceived importance significantly affects both user driving habits and the intention to continue using the system, while regret after experience has a significant negative correlation only with habit formation and does not directly affect the intention to continue use, indicating that users are more concerned with the actual functionality and practicality of the system. (4) User scale is shown to indirectly influence the intention to continue using through various pathways, providing a new perspective for related theoretical research. (5) Aside from safety capabilities, other external factors such as economic benefits and technological stability significantly influence the intention to continue using, while the lack of significance for safety capabilities may be due to users trusting their own driving skills in critical moments. (6) The research results offer valuable references for the improvement and promotion of autonomous driving systems, emphasizing the practicality and usability of the system. (7) This study provides a new theoretical framework for the application of habit theory and regret theory in related fields. Therefore, through empirical analysis, this research delves into the key factors influencing the intention to continue using autonomous driving systems, offering certain reference value for the development of autonomous driving systems and contributing to their theoretical development and practical application. Full article

Introduction: Performance in a single step has been suggested to be a sensitive measure of movement quality in pediatric clinical populations. Although there is less information available in children with typical development, researchers have postulated the importance of analyzing the effect of body weight modulation on the initiation of stair ascent, especially during single-limb stance where upright stability is most critical. The purpose of this study was to investigate the effect of load modulation from −20% to +15% of body weight on typical pediatric lower limb joint moments during a step-up task. Methods: Fourteen participants between 5 and 21 years who did not have any neurological or musculoskeletal concerns were recruited to perform multiple step-up trials. Peak extensor support and hip abduction moments were identified during the push-off and pull-up stance phases. Linear regressions were used to determine the relationship between peak moments and load. Mixed-effects models were used to estimate the effect of load on hip, knee, and ankle percent contributions to peak support moments. Results: There was a positive linear relationship between peak support moments and load in both stance phases, where these moments scaled with load. There was no relationship between peak hip abduction moments and load. While the ankle and knee were the primary contributors to the support moments, the hip contributed more than expected in the pull-up phase. Discussion: Clinicians can use these results to contextualize movement differences in pediatric clinical populations, including in those with cerebral palsy, and highlight potential target areas for rehabilitation for populations such as adolescent athletes. Full article

The Korean Peninsula, characterized by low-to-moderate seismicity, faces a shortage of strong ground motion records, posing challenges for the seismic safety assessment of critical infrastructures. Given the rarity of large-magnitude earthquakes, generating a variety of earthquakes with rational values of Peak Ground Acceleration (PGA) is essential for robust seismic fragility and risk analysis. To address this, a new stochastic approach is proposed to simulate artificial earthquakes at multiple source-to-site distances and derive the probability distribution of PGA based on recorded data from a single seismic event. Two key source parameters, seismic moment and corner frequency, are treated as random variables with a negative correlation, reflecting their uncertainties and dependence on source-to-site distance. The Monte Carlo simulation with copula sampling of the key source parameters generates Fourier spectra for artificial earthquakes, which are transformed into the time domain to yield PGA distributions at various distances. A comparison with recorded data shows that the proposed method effectively simulates ground motion intensities, with no statistically significant differences between the simulated results and recorded data ($p>0.05$). The present method of determining PGA distributions provides a robust framework to enhance seismic risk analysis for the safety assessment of structures. Full article

The optimal performance of direct current (DC) motors is intrinsically linked to their mathematical models’ precision and their controllers’ effectiveness. However, the limited availability of motor characteristic information poses significant challenges to achieving accurate modeling and robust control. This study introduces an approach employing artificial neural networks (ANNs) to estimate critical DC motor parameters by defining practical constraints that simplify the estimation process. A mathematical model was introduced for optimal parameter estimation, and two advanced learning algorithms were proposed to efficiently train the ANN. The performance of the algorithms was thoroughly analyzed using metrics such as the mean squared error, epoch count, and execution time to ensure the reliability of dynamic priority arbitration and data integrity. Dynamic priority arbitration involves automatically assigning tasks in real-time depending on their relevance for smooth operations, whereas data integrity ensures that information remains accurate, consistent, and reliable throughout the entire process. The ANN-based estimator successfully predicts electromechanical and electrical characteristics, such as back-EMF, moment of inertia, viscous friction coefficient, armature inductance, and armature resistance. Compared to conventional methods, which are often resource-intensive and time-consuming, the proposed solution offers superior accuracy, significantly reduced estimation time, and lower computational costs. The simulation results validated the effectiveness of the proposed ANN under diverse real-world operating conditions, making it a powerful tool for enhancing DC motor performance with practical applications in industrial automation and control systems. Full article

Background: Serum albumin is crucial for critically ill patients. To date, several reports have focused on the influence of lower albumin levels on poorer prognosis and disease outcome in different subsets of critical clinical conditions varying from sepsis, to cirrhosis, renal failure, and cancer. In the last few years, investigators reported the role of serum albumin levels in predicting the thrombotic risk in patients with nephrotic syndrome, and, in particular, the degree of hypoalbuminemia seemed to influence the risk of thromboembolism. Decreased serum albumin has been associated with the risk of venous thromboembolism and mortality in adult cancer patients after ending chemotherapy for different malignancies. Aims: We aimed to investigate the role of serum albumin in a cohort of children diagnosed as having VTE (venous thromboembolism) during their treatment for acute lymphoblastic leukemia (ALL) compared to ALL children who did not experience VTE. Methods: A nested case-control study was conducted at the Pediatric Oncology and Hematology Department, University Hospital of Bari. A total of 167 patients were diagnosed as having ALL and treated according to AIEOP-BFM ALL 2000-R2006 protocol. Among these, 12 cases of VTE were recorded and matched to 31 controls, for a total of 43 ALL patients (30 males, aged 1.2–16.6 years) enrolled in the present study. Serum albumin level was collected at diagnosis—before the start of any treatment—(time point 0) and at the moment of the VTE or corresponding time point of the protocol (time point 1). Information on inherited thrombophilia genotype were also recorded. Results: Patients presenting VTE showed a marked reduction of average albumin levels as compared to the control children: t0–t1 1.1 IC (95%) = (0.55, 1.65) vs. 0.31 IC (95%) = (0.08, 0.55); p < 0.005. Conclusions: The reduction of serum albumin levels in our cohort might be an expression of altered vascular and endothelial homeostasis, likely predisposing to VTE. This important clinical observation warrants further larger studies. Full article

Tool wear in machining is inevitable, and determining the precise moment to change the tool is challenging, as the tool transitions from the steady wear phase to the rapid wear phase, where wear accelerates significantly. If the tool is not replaced correctly, it can result in poor machining performance. On the other hand, changing the tool too early can lead to unnecessary downtime and increased tooling costs. This makes it critical to closely monitor tool wear and utilize predictive maintenance strategies, such as tool condition monitoring systems, to optimize tool life and maintain machining efficiency. Acoustic emission (AE) is a widely used technique for indirect monitoring. This study investigated the use of Short-Time Fourier Transform (STFT) for real-time monitoring of tool wear in machining AISI 4340 steel using carbide tools. The research aimed to identify specific wear mechanisms, such as abrasive and adhesive ones, through AE signals, providing deeper insights into the temporal evolution of these phenomena. Machining tests were conducted at various cutting speeds, feed rates, and depths of cut, utilizing uncoated and AlCrN-coated carbide tools. AE signals were acquired and analyzed using STFT to isolate wear-related signals from those associated with material deformation. The results showed that STFT effectively identified key frequencies related to wear, such as abrasive between 200 and 1000 kHz and crack propagation between 350 and 550 kHz, enabling a precise characterization of wear mechanisms. Comparative analysis of uncoated and coated tools revealed that AlCrN coatings reduced tool wear extending tool life, demonstrating superior performance in severe cutting conditions. The findings highlight the potential of STFT as a robust tool for monitoring tool wear in machining operations, offering valuable information to optimize tool maintenance and enhance machining efficiency. Full article