Search Results (297)

Autophagy is an intracellular process that recycles and degrades cytoplasmic components, including organelles and macromolecules, to provide energy and basic components for cell survival, maintain cellular homeostasis, and avoid self-damage. It is currently not fully known if mouse sperm undergoes the autophagy process, nor is the subcellular distribution, protein levels of autophagy-related proteins, and the biological role of autophagy in epididymal mouse sperm physiology fully understood. We aimed to investigate key autophagy markers, including LC3 (microtubule-associated protein 1A/1B-light chain 3), p62/SQSTM1 (Sequestosome 1), and mTOR (mechanistic Target of Rapamycin), in epididymal mouse sperm under capacitation (Cap) or non-capacitation (NC) conditions. Furthermore, we evaluated the possible role of these autophagy-related proteins on sperm viability, motility, intracellular pH (pHi), intracellular calcium concentrations [Ca²⁺]i, mitochondrial membrane potential, and acrosome reaction (AR) induction in the presence or absence of chloroquine (CQ), K67, and rapamycin. Our results suggest a dynamic re-localization of the autophagy-related proteins LC3, p62/SQSTM1, and mTOR under capacitation conditions. Moreover, treatment with specific autophagy inhibitors, such as CQ and K67, resulted in decreased LC3-II and p62/SQSTM1 protein levels. Additionally, rapamycin did not increase mTOR levels. Interestingly, treatment with these inhibitors also resulted in decreased motility, reduced mitochondrial membrane potential and hindered AR induction without affecting sperm viability. Overall, the presence and dynamic re-localization of LC3, p62/SQSTM1, and mTOR suggest that mouse epididymal sperm could perform initial steps of autophagy under capacitation conditions, and results of the pharmacological treatment could be associated with an important role of these autophagy-related proteins in sperm motility and AR induction. Full article

We are witnessing a global commitment to sustainable mobility that requires advanced materials and manufacturing techniques, such as fused filament fabrication (FFF), to create lightweight, durable, and recyclable machine components. Acknowledging that friction and wear significantly contribute to energy loss globally, developing high-performance polymeric materials with customizable properties is essential for greener mechanical systems. FFF inherently drives resource efficiency and offers the geometric freedom necessary to engineer complex internal structures, such as the gyroid pattern, enabling substantial mass reduction. This study evaluates the tribological performance of FFF-printed thermoplastic polyurethane (TPU 82A) specimens fabricated with three distinct gyroid infill densities (10%, 50%, and 100%). Ball-on-disc testing was conducted under dry sliding conditions against a 100Cr6 spherical ball, with a constant normal load of 5 N, resulting in an initial maximum theoretical Hertz contact pressure of 231 MPa, over a total sliding distance of 300 m. Shore A hardness and surface roughness (R_a) were also measured to correlate mechanical and structural characteristics with frictional response. Results reveal a non-monotonic relationship between infill density and friction, with a particular absence of quantifiable mass loss across all samples. The intermediate 50% infill (75.9 ± 1.80 Shore A) exhibited the peak mean friction coefficient of $\overline{\mu }=1.002$ (${\mu }_{\max }=1.057$), which can be attributed to its balanced structural stiffness that promotes localized surface indentation and an increased real contact area during sliding. By contrast, the rigid 100% infill (86.3 ± 1.92 Shore A) yielded the lowest mean friction ($\overline{\mu }$ = 0.465), while the highly compliant 10% infill (44.3 ± 1.94 Shore A) demonstrated viscoelastic energy damping, stabilizing at $\overline{\mu }$ = 0.504. This work highlights the novelty of using FFF gyroid architectures to precisely tune TPU 82A’s tribological behavior, offering design pathways for sustainable mobility. The ability to tailor components for low-friction operations (e.g., μ ≈ 0.465 for bushings) or high-grip requirements (e.g., μ ≈ 1.002 for anti-slip systems) provides eco-efficient solutions for automotive, railway, and micromobility applications, while the exceptional wear resistance supports extended service life and material circularity. Full article

Positioning technology based on 5G networks has been deeply integrated into everyday life. Despite this, severe non-line-of-sight (NLOS) conditions in wireless signal environments can cause signal obstructions, negatively impacting the precision and dependability of positioning services. This paper introduces an innovative algorithm called Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface Non-Line-of-Sight Angle of Arrival (STAR-RIS NLOS AOA) to address these challenges. The algorithm initially develops a system model named 5G STAR-RIS localization (GSL). By integrating STAR-RIS into the system, the model effectively overcomes the challenges of positioning in NLOS scenarios. The inclusion of STAR-RIS not only boosts the system’s adaptability but also meets the positioning requirements for users on both sides of the reflective surface simultaneously. The algorithm then utilizes the Root-MUSIC algorithm for estimating user coordinates. An optimization problem is formulated based on these estimations, with the goal of reducing the gap between estimated and real coordinates. To address this optimization, the Inertia Weight Whale Optimization Algorithm is employed, providing high-precision estimations of users’ three-dimensional positions. Simulations reveal that the proposed Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface Non-Line-of-Sight Angle of Arrival (SRNA) algorithm substantially outperforms conventional algorithms in positioning performance across different signal-to-noise ratio contexts. Specifically, in challenging NLOS situations, the SRNA algorithm can cut positioning errors by 50% to 62%, demonstrating its outstanding capability and efficiency in addressing the difficulties presented by NLOS conditions within 5G-based positioning systems. Full article

Background/Objectives: For decades, only native allergen extracts with a high incidence of adverse drug reactions (ADRs) were available for allergen-specific immunotherapy (AIT)—generally administered subcutaneously—to treat allergy to feline epithelia. Modified allergen extracts are a promising alternative to reduce the number of ADRs. The purpose of this study was to collect data on the safety of a depigmented–polymerised cat allergoid under real-world conditions in clinical routine. Methods: This study was designed as a voluntary non-interventional post-authorisation safety study (NIS-PASS), specifically focusing on adverse events (AEs)—including ADRs—that occur upon injection and assessing the influence on quality of life (QoL). The observation period was the initial phase (up-dosing) of the AIT. Results: Of 101 included patients, 91 patients were treated with the depigmented–polymerised cat allergoid. Regardless of the age group, around 50% of patients reported ADRs, which were mainly delayed local reactions (LRs). Other ADRs occurred only sporadically without persistent patient impairment. The ADR incidence did not differ significantly between quick and conventional up-dosing regimens or between adult and adolescent patient groups. The QoL data revealed no significant changes in any domains of the SF-12 questionnaire during the 12-week observation period. Conclusions: Overall, subcutaneous allergen immunotherapy (SCIT) with the depigmented–polymerised cat allergoid is a well-tolerated and safe treatment option for patients with cat allergy. Full article

With the advancement of construction development, urban renewal, and urbanization, engineering appraisal and structural reinforcement will become crucial tasks in the construction industry, thus presenting both significant challenges and long-term responsibilities. The concept of “partial strengthening and replacement composite shear walls without support roof” refers to a structural system that utilizes the existing load-bearing capacity of RC shear walls. In this method, high-performance materials are used to locally remove and replace critical load-bearing sections of the wall to be strengthened, resulting in a “composite shear wall” structure composed of both strengthened replacement areas and non-replaced sections. This study proposes the concept of composite shear walls, conducts simulation analysis and exploratory research on their bearing performance, and explores engineering applications based on engineering examples. The research conclusions include the following: Compared to only one batch of replacement reinforcement, partial strengthening and replacement in batches can significantly improve the bearing performance of composite shear walls. The use of steel-reinforced concrete for local strengthening and replacement can significantly improve the bearing performance of composite shear walls, and the magnitude of the improvement in bearing performance decreases with the increase in the initial vertical stress level of the components. The overall structural stress condition after local strengthening and replacement reinforcement is good, and its vertical and horizontal bearing capacity can meet the original design requirements (after reinforcement, the vertical bearing capacity of the overall structure increased by about 6.3% compared to the original design, and the horizontal ultimate bearing capacity is about 1.4 times larger compared to the elastic–plastic “large earthquake” effect of the original design). Compared with conventional replacement methods, the unsupported-roof local reinforcement replacement method has the advantages of using high-performance materials, reducing reinforcement engineering, minimizing resource waste, and simplifying construction procedures, and has good application prospects. Full article

This study presents a novel computational framework for approximating solutions to time-fractional partial differential equations (TFPDEs) with variable coefficients, employing the Caputo definition of fractional derivatives. TFPDEs, distinguished by their fractional-order time derivatives, inherently capture the non-local and memory-dependent dynamics observed in a wide range of physical and engineering systems. The proposed method reformulates the TFPDE into a set of decoupled fractional-order ordinary differential equations (FODEs) via Fourier expansion strategy. This decomposition facilitates analytical tractability while preserving the essential features of the original system. The initial conditions of each resulting FODE are systematically obtained from the governing equation’s initial data. Auxiliary initial value problems are formulated for each FODE to facilitate the construction of explicit particular solutions. These solutions are then synthesized through a carefully designed linear superposition, optimized to minimize the residual error across the domain of interest. This residual minimization ensures that the composite solution closely approximates the behavior of the original TFPDE, offering both accuracy and computational efficiency. Theoretical analysis demonstrates that the method is convergent. A FLOP-based analysis confirms that the proposed method is computationally efficient. The validity and effectiveness of the proposed scheme are demonstrated through a set of benchmark problems. Empirical convergence rates are compared with those from existing numerical methods in each case. The findings confirm that the proposed approach consistently achieves superior accuracy and demonstrates robust performance under a wide range of scenarios. These findings highlight the method’s potential as a powerful and versatile tool for solving complex TFPDEs in mathematical modeling and applied sciences. Full article

Accurate remaining useful life (RUL) prediction of tantalum capacitors is essential for enhancing the reliability and maintainability of power electronic systems. However, online RUL prediction remains a challenging task due to the difficulty of accessing internal degradation states and the non-stationarity of operating conditions. This paper presents a novel CNN-LSTM-Attention-based deep learning framework for accurate online RUL prediction of tantalum capacitors, leveraging infrared surface temperature measurements and ambient thermal compensation. The proposed framework initiates with the collection of degradation temperature data under controlled accelerated aging experiments, where true degradation indicators are extracted by eliminating ambient temperature interference through dual-sensor compensation. The resulting preprocessed data are used to train a hybrid deep neural network model that integrates convolutional layers for local feature extraction, long short-term memory (LSTM) units for sequential dependency modeling, and a soft attention mechanism to selectively focus on the critical degradation patterns. A channel attention module is further embedded to adaptively optimize the importance of different feature channels. Experimental validation using three groups of aging data demonstrates the effectiveness and superiority of the proposed method over conventional LSTM and CNN-LSTM baselines. The CNN-LSTM-Attention model achieves a substantial improvement in prediction accuracy, with mean absolute percentage error (MAPE) reductions of up to 60.97%, root mean squared error (RMSE) reductions of up to 65.63%, and coefficient of determination (R²) increases of up to 68.67%. The results confirm the ability to deliver precise and robust online RUL predictions for tantalum capacitors under complex operational conditions. Full article

This paper presents the Gaussian conditional method (GCM) for the problem of frequency difference of arrival (FDOA)-only source localization under correlated noise. GCM identifies the source position through approximating its posterior distribution using a Gaussian mixture model (GMM) and applying successive conditioning to the measurement likelihood. The algorithm development leverages the fact that FDOA measurements follow a multivariate Gaussian distribution with a non-diagonal covariance. Simulation results demonstrate that GCM can achieve the Cramér–Rao lower bound (CRLB) under moderate noise levels, while having lower computational complexity than baseline techniques including the recently developed Gaussian division method (GDM). The proposed algorithm is particularly effective for passively locating narrowband sources, where the time difference of arrival (TDOA) measurements become unreliable, and it can operate without the need for accurate initialization. Full article

Fractional differential equations offer a natural framework for describing systems in which present states are influenced by the past. This work presents a nonlinear Caputo-type fractional differential equation (FDE) with a nonlocal initial condition and attempts to describe a model of memory-dependent behavioral adaptation. The proposed framework uses a fractional-order derivative $\eta \in (0,1)$ to discuss the long-term memory effects. The existence and uniqueness of solutions are demonstrated by Banach’s and Krasnoselskii’s fixed-point theorems. Stability is analyzed through Ulam–Hyers and Ulam–Hyers–Rassias benchmarks, supported by sensitivity results on the kernel structure and fractional order. The model is further employed for behavioral despair and learned helplessness, capturing the role of delayed stimulus feedback in shaping cognitive adaptation. Numerical simulations based on the convolution-based fractional linear multistep (FVI–CQ) and Adams–Bashforth–Moulton (ABM) schemes confirm convergence and accuracy. The proposed setup provides a compact computational and mathematical paradigm for analyzing systems characterized by nonlocal feedback and persistent memory. Full article

The external floating roof of a large storage tank directly covers the liquid surface as the liquid level rises and falls, enhancing the tank’s safety and environmental performance. It is fabricated from thin SA516 Gr.70 steel plates, with a carbon equivalent of 0.37% calculated according to AWS standards, using single-sided butt welding. Such plates are susceptible to welding-induced deformations, resulting in irregular warping of the bottom plate. Current research on floating roofs for storage tanks mostly relies on idealized models that assume no deformation, thereby neglecting the actual deformation characteristics of the floating roof structure. To address this, the present study develops an automated modeling approach that reconstructs a three-dimensional floating roof model based on measured deformation data, accurately capturing the initial irregular geometry of the bottom plate. This method employs parametric numerical reconstruction and automatic finite element model generation techniques, enabling efficient creation of the irregular initial deformation caused by welding of the floating roof bottom plate and its automatic integration into the finite element analysis process. It overcomes the inefficiencies, inconsistent accuracy, and challenges associated with traditional manual modeling when conducting large-scale strength analyses under in-service conditions. Based on this research, a strength analysis of the deformed floating roof structure was conducted under in-service conditions, including normal floating, extreme rainfall, and outrigger contact scenarios. An idealized geometric model was also established for comparative analysis. The results indicate that under the normal floating condition, the initial irregular deformation increases the local stress peak of the floating roof bottom plate by 19%, while the maximum positive and negative displacements increase by 22% and 83%, respectively. Under extreme uniform rainfall conditions, it raises the stress peak of the bottom plate by 24%, with maximum positive and negative displacements increasing by 21% and 28%, respectively. Under the extreme non-uniform rainfall condition, it significantly elevates the stress peak of the bottom plate by 227%, and the maximum positive and negative displacements increase by 45% and 47%, respectively. Under the outrigger bottoming condition, it increases the local stress peak of the bottom plate by 25%, with maximum positive and negative displacements remaining similar. The initial irregular deformation not only significantly amplifies the stress and displacement responses of the floating roof bottom plate but also intensifies the deformation response of the top plate through structural stiffness weakening and deformation coupling, thereby reducing the safety margin of the floating roof structure. This study fills the knowledge gap regarding the effect of welding-induced irregular deformation on floating roof performance and provides a validated workflow for automated modeling and mechanical assessment of large-scale welded steel structures. Full article

In the cold extrusion forming of thin-walled, specially shaped holes in aviation motor brush boxes, non-uniform metal flow can easily induce local stress concentrations on the punch, thereby accelerating wear. Reducing the punch wear and equivalent stress is therefore critical for ensuring the forming quality of such thin-walled features and extending the service life of the mold. In this study, a slender punch with a specially shaped cross-section was selected as the research object. The Deform-3D Ver 11.0 software, incorporating the Archard wear model, was employed to investigate the effects of five process parameters—extrusion speed, punch cone angle, punch transition filet, friction coefficient, and punch hardness—on the wear depth and equivalent stress of the punch during the compound extrusion process. A total of 25 orthogonal experimental groups were designed, and the simulation results were analyzed using the Taguchi method combined with range analysis to determine the optimal parameter combination. Subsequently, a multi-objective correlation analysis of the signal-to-noise ratios for wear depth and equivalent stress was conducted using the TOPSIS approach. The analysis revealed that the optimal combination of process parameters was an extrusion speed of 12 mm·s⁻¹, a punch cone angle of 50°, a punch transition filet radius of 1.8 mm, a friction coefficient of 0.12, and a punch hardness of 55 HRC. Compared with the initial process conditions, the integrated application of the Taguchi–TOPSIS method reduced the punch wear depth and equivalent stress by 21.68% and 42.58%, respectively. Verification through actual production confirmed that the wear conditions of the primary worn areas were in good agreement with on-site production observations. Full article

The high-cycle fatigue (HCF) strength of titanium alloy blades, particularly Ti-6Al-4V, is critical for the reliability and performance of aviation engine components. Foreign object damage (FOD), which introduces notches, microstructural alterations, and residual stresses, significantly degrades the fatigue performance of these blades. Of particular concern are tensile residual stresses, which, caused by factors such as FOD, notches, or non-uniform plastic deformation, lead to increased local tensile loads, promote crack initiation, and accelerate crack growth. This study investigates the effects of external damage, including the impact angle and the resultant residual stresses, on the high-cycle fatigue strength of Ti-6Al-4V titanium alloy blades. Blade simulation specimens with impact-induced damage were tested under high-cycle fatigue conditions to assess the influence of various impact angles and the resulting tensile residual stresses. A modified fatigue strength prediction model was developed, incorporating shear factors and tensile residual stresses, to improve the accuracy of fatigue life predictions. Compared with the Neuber model and Peterson model, the modified model increases the proportion of predictions falling within the 10% scatter band by 30%, resulting in a significant improvement in prediction accuracy. The experimental results demonstrated that the modified model more accurately predicted the high-cycle fatigue strength, particularly in the presence of external damage and tensile residual stresses. Full article

Precise fault localization is vital for enhancing power grid reliability, reducing outage duration, and lowering maintenance expenses. This paper presents a fast and effective method that utilizes the application of voltage pulses with opposing polarities and identical durations to the transmission line. Analysis of traveling wave propagation under both normal and fault conditions indicates that the initial voltage wave observed in the non-injected phase stems from reflections at the fault point. The arrival time of the wavefront is accurately determined using variational mode decomposition (VMD) combined with the Teager energy operator (TEO) to pinpoint the fault location. Simulations conducted in PSCAD validate the efficacy of the proposed approach. This method demonstrates advantages including straightforward implementation, swift response, and superior accuracy compared to conventional techniques. Full article

Mucosal drug delivery is gaining attention for its ability to provide localized treatment with reduced systemic side effects. The vaginal route has been proven effective for managing gynecological conditions, though it poses certain limitations. Biopolymers can help overcome these challenges by enhancing therapeutic efficiency and offering beneficial properties. This study aimed to develop and evaluate hydrogels and their freeze-dried forms (wafers) based on collagen, hydroxypropyl methylcellulose, and gellan gum. Initially, a collagen gel was obtained by extraction from calfskin, which was brought to a concentration of 1% and a physiological pH with 1 M sodium hydroxide solution. This gel was combined with either 2% hydroxypropyl methylcellulose gel, 1.2% gellan gum gel, or both, in different proportions. Thus, five mixed hydrogels were obtained, which, along with the three individual gels (controls), were lyophilized to obtain wafers. Furthermore, the hydrogels were assessed for rheological behavior, while the collagen structural integrity in the presence of the other biopolymers was evaluated using circular dichroism and FT-IR spectroscopy. The wafers were characterized for morphology, wettability, swelling capacity, enzymatic degradation resistance, and in vitro biocompatibility. All hydrogels exhibited non-Newtonian, pseudoplastic behavior and showed collagen structure preservation. The wafers’ characterization showed that gellan gum enhanced the hydrophilicity and enzymatic stability of the samples. In addition, the extracts from the tested samples maintained cell viability and did not affect actin cytoskeleton morphology, indicating a lack of cytotoxic effects. This study emphasizes the importance of evaluating both the physicochemical properties and biocompatibility of biopolymeric supports as a key preliminary step in the development of vaginal drug delivery platforms with biomedical applications in the management of gynecological conditions. Full article

This study presents an exact analytical investigation into the static response of helical single-walled carbon nanotube (SWCNT) beams based on Eringen’s differential nonlocal elasticity theory, which captures nanoscale effects arising from interatomic interactions. A key contribution of this work is the derivation of the governing equations for helical SWCNT beams, based on the nonlocal Euler–Bernoulli theory, followed by their exact analytical solution using the initial value method. To the best of the authors’ knowledge, this represents the first closed-form formulation for such complex nanostructures using this theoretical framework of nonlocal elasticity theory. The analysis considers both cantilevered and clamped–clamped boundary conditions, under various concentrated force and moment loadings applied at the ends and midpoint of the helical beam. Displacements and rotational components are expressed in the Frenet frame, enabling direction-specific evaluation of the deformation behaviour. Parametric studies are conducted to investigate the influence of geometric parameters—such as the winding angle ($\alpha$) and aspect ratio ($R/d$) and the nonlocal parameter ($R/\gamma$). Results show that nonlocal elasticity theory consistently predicts higher displacements and rotations than the classical local theory, revealing its importance for accurate modelling of nanoscale structures. The proposed analytical framework serves as a benchmark reference for the modelling and design of nanoscale helical structures such as nano-springs, actuators, and flexible nanodevices. Full article