Search Results (637)

Seismic responses of Nuclear Island (NI) structures have great significance in the foundation adaptability analysis and the seismic design of equipment. However, with the increasing complexity of nuclear power site conditions, establishing a reasonable and effective soil–pile–structure dynamic interaction model has become the key technical problem that needs to be solved. In this study, a pseudo three-dimensional soil–pile–structure dynamic interaction model considering soil nonlinearity and heterogeneity is developed for seismic response analysis of NI structures. Specifically, the nonlinearity of the near-field soil is described via the equivalent linear method, the radiation damping effect of half space is simulated through viscous boundary, and the displacement/stress conditions at lateral boundaries of the heterogeneous site are derived from free-field response analysis. Meanwhile, an equivalent stiffness–mass principle is established to simplify NI superstructures, while pile group effects are incorporated via a node-coupling scheme within the finite-element framework. Two validation examples are presented to demonstrate the accuracy and efficiency of the proposed model. Finally, seismic response analysis of two typical NI structure of reactor types (CPR1000 and AP1000) based on the actual complex site conditions in China is also presented to study the effect of radiation damping, soil conditions, and pile foundation. Key findings demonstrate the necessity of integrating SSI effects and nonlinear characteristics of non-rock foundations. While the rock-socketed pile exhibits superior performance compared to the CFG pile alternative; this advantage is offset by higher costs and construction complexity. The research findings can serve as a valuable reference for the foundation adaptability analysis and optimizing the design of equipment under the similar complex condition of the soil site. Full article

Early medical traditions include those of ancient Babylonia, China, Egypt, and India. The roots of modern Western medicine, however, go back to ancient Greece. During the Renaissance, physicians increasingly relied on observation and experimentation to understand the human body and develop new techniques for diagnosis and treatment. The discovery of antibiotics, antiseptics, and other drugs in the 19th century accelerated the development of modern medicine, the latter being fueled further by advances in technology, research, a better understanding of the human body, and, most recently, the introduction of evidence-based medicine (EBM). The EBM model de-emphasized intuition, unsystematic clinical experience, and pathophysiologic rationale as sufficient grounds for clinical decision-making and stressed the examination of evidence from clinical research. A later EBM model additionally incorporated clinical expertise and the latest model of EBM patients’ preferences and actions. In this review article, we argue that in the era of precision medicine, major EBM principles must be based on (a) the systematic identification, analysis, and utility of big data using artificial intelligence; (b) the magnifying effect of medical interventions by means of the physician–patient interaction, the latter being guided by the physician’s expertise, intuition, and philosophical beliefs; and (c) the patient preferences, since, in healthcare under precision medicine, the patient will be a central stakeholder contributing data and actively participating in shared decision-making. Full article

Measuring the small tree trunk variations during the day–night cycle, seasonal cycles, as well as those caused by the plant’s growth and health regime is a very important action in horticulture or forestry because by analyzing the collected data, assessments can be made on the health of the trees, but also on the climatic conditions and changes in a certain region. This can be performed with devices called dendrometers. This paper presents a new type of approach to these measurement types in which the trunk volume changes are highly sensitively converted into the axial stress on sensitive elements made of magnetic materials in wire form in which the giant stress impedance effect occurs. Finally, by electronic processing of the signals provided by the sensitive elements, digital words with a decimal value proportional to the diameter variations are obtained. This paper presents the operating principle, the constructive details and the experimental results obtained by testing the device in the laboratory and in-field. The proposed dendrometer, compared to those available commercially, has the advantage of good resolution and sensitivity, good immunity to temperature variations, the possibility of transmitting the result remotely, robustness and low price. Some metrological parameters obtained from the experimental testing are the following: resolution 1.6 µm, linearity 1.4%, measurement range 0 to 5 mm, temperature coefficient 0.012%/°C. Full article

To address traditional methods’ limitations in neglecting the interaction between random shock loads and progressive degradation, as well as failure correlations, this study proposes a dynamic reliability framework integrating Gamma processes, homogeneous Poisson processes (HPP), and mixed Copula functions. The framework develops a wind turbine gearbox reliability model under shock–degradation coupling while quantifying failure correlations. Gamma processes characterize continuous degradation, with parameters estimated from P-S-N curves. Based on stress–strength interference theory, random shocks within damage thresholds are integrated to form a coupled reliability model. A Gumbel–Clayton–Frank mixed Copula with a multi-layer nested algorithm quantifies failure correlations, with correlation parameters estimated via the RSS principle and genetic algorithms. Validation using a 2 MW gearbox’s planetary gear-stage system covers four scenarios: natural degradation, shock–degradation coupling, and both scenarios with failure correlations. The results show that compared to independent assumptions, the model accelerates reliability decline, increasing failure rates by >37%. Relative to natural degradation-only models, failure rates rise by >60%, validating the model’s effectiveness and alignment with real-world operational conditions. Full article

This work presents a multiscale, microstructure-aware framework for predicting fatigue strength distributions in additively manufactured (AM) alloys—specifically, laser powder bed fusion (L-PBF) AlSi10Mg and Ti-6Al-4V—by integrating density functional theory (DFT), instrumented indentation, and Bayesian inference. The methodology leverages principles common to all 3D printing (additive manufacturing) processes: layer-wise material deposition, process-induced defect formation (such as porosity and residual stress), and microstructural tailoring through parameter control, which collectively differentiate AM from conventional manufacturing. By linking DFT-derived cohesive energies with indentation-based modulus measurements and a MAP-based statistical model, we quantify the effect of additive-manufactured microstructural heterogeneity on fatigue performance. Quantitative validation demonstrates that the predicted fatigue strength distributions agree with experimental high-cycle and very-high-cycle fatigue (HCF/VHCF) data, with posterior modes and 95 % credible intervals of ${\widehat{\sigma }}_f^{\mathrm{AlSi}10\mathrm{Mg}}={86}_{-7}^{+8}\mathrm{MPa}$ and ${\widehat{\sigma }}_f^{\mathrm{Ti}–6\mathrm{Al}–4\mathrm{V}}={115}_{-9}^{+10}\mathrm{MPa}$, respectively. The resulting Woehler (S–N) curves and Paris crack-growth parameters envelop more than 92 % of the measured coupon data, confirming both accuracy and robustness. Furthermore, global sensitivity analysis reveals that volumetric porosity and residual stress account for over 70 % of the fatigue strength variance, highlighting the central role of process–structure relationships unique to AM. The presented framework thus provides a predictive, physically interpretable, and data-efficient pathway for microstructure-informed fatigue design in additively manufactured metals, and is readily extensible to other AM alloys and process variants. Full article

The current study demonstrates the buckling properties of composite laminates reinforced with MWCNT fillers using a novel higher-order shear and normal deformation theory (HSNDT), which considers the effect of thickness in its mathematical formulation. The hybrid HSNDT combines polynomial and hyperbolic functions that ensure the parabolic shear stress profile and zero shear stress boundary condition at the upper and lower surface of the plate, hence removing the need for a shear correction factor. The plate is made up of carbon fiber bounded together with polymer resin matrix reinforced with MWCNT fibers. The mechanical properties are homogenized by a Halpin–Tsai scheme. The MATLAB R2019a code was developed in-house for a finite element model using C⁰ continuity nine-node Lagrangian isoparametric shape functions. The geometric nonlinear and linear stiffness matrices are derived using the principle of virtual work. The solution of the eigenvalue problem enables estimation of the critical buckling loads. A convergence study was carried out and model efficiency was corroborated with the existing literature. The model contains only seven degrees of freedom, which significantly reduces computation time, facilitating the comprehensive parametric studies for the buckling stability of the plate. Full article

With the acceleration of industrialization, deformable mechanisms that can adapt to complex environments have gained widespread applications. Joints serve as carriers for transmitting forces and motions between components, and their stiffness significantly influences the static and dynamic characteristics of deformable mechanisms. A variable stiffness joint is crucial for ensuring the safety and reliability of the system, as well as for enhancing environmental adaptability. However, existing variable stiffness joints fail to meet the requirements for miniaturization, lightweight construction, and fast response. This paper proposes a piezoelectric-actuated variable stiffness miniature rotary joint featuring a compact structure, monitorable loading state, and rapid response. Given that the piezoelectric stack expands and contracts when energized, this paper proposes a transmission principle for stiffness adjustment by varying the pressure and friction between active and passive components. This joint utilizes a flexible hinge mechanism for displacement amplification and incorporates a torque sensor based on strain monitoring. A static model is developed based on piezoelectric equations and displacement amplification characteristics, and simulations confirm the feasibility of the stiffness adjustment scheme. The mechanical characteristics of various flexible hinge structures are analyzed, and the effects of piezoelectric actuation capability and external load on stiffness adjustment are examined. The experimental results demonstrate that the joint can adjust stiffness, and the sensor is calibrated using the least squares algorithm to monitor the stress state of the joint in real time. Full article

(1) Background: Optimizing infill density in 3D-printed PLA parts reduces material usage, cost, and waste. This study examines mechanical behavior in the initial and hydration stages. The findings provide valuable data for numerical simulations and engineering applications in additive manufacturing. (2) Methods: PLA specimens were printed with infill densities of 100%, 75%, and 25%. Mechanical tests, including tensile and compression tests, and one-hour stress-relaxation at 2% strain were conducted. The digital image correlation method was used to obtain the strain fields on the samples’ surface under tensile loading. Mechanical properties, including the elastic modulus, strength values, and Poisson’s ratio, were assessed. Hydrolytic degradation effects over one month were also evaluated. (3) Results: Lowering the PLA infill density reduced the ultimate tensile strength (from 60.04 ± 2.24 MPa to 26.24 ± 0.77 MPa), Young’s modulus (from 2645.05 ± 204.15 MPa to 1245.41 ± 83.79 MPa), compressive strength (from 26.59 ± 0.80 MPa to 21.83 ± 1.01 MPa), and Poisson’s ratio (from 0.32 to 0.30). A 40% mass reduction (form 100% to 25% infill density) resulted in a 56% decrease in tensile strength and a 53% decrease in Young’s modulus. A 31% mass reduction was observed for compression samples. Stress relaxation decreased significantly from 100% to 75% density, with further reductions having minimal impact. Hydrated samples showed no mechanical changes compared to baseline specimens. (4) Conclusions: Optimizing infill density in 3D-printed PLA parts helps to balance mechanical performance with material efficiency. The best mechanical properties are typically achieved with an infill density of 100%, but results show that decreasing the mass of the part by a reduction in infill density from 75% to 25% does not significantly affect the ability to transfer tensile and compression loads. PLA’s biodegradability makes it a viable alternative to stable polymers. By minimizing material waste and enabling the efficient use of resources, additive manufacturing aligns with the principles of a closed-loop economy, supporting sustainable development. Full article

Magnetorheological (MR) foams represent a class of smart materials with unique tunable viscoelastic properties when subjected to external magnetic fields. Combining porous structures with embedded magnetic particles, these materials address challenges such as leakage and sedimentation, typically encountered in conventional MR fluids while offering advantages like lightweight design, acoustic absorption, high energy harvesting capability, and tailored mechanical responses. Despite their potential, challenges such as non-uniform particle dispersion, limited durability under cyclic loads, and suboptimal magneto-mechanical coupling continue to hinder their broader adoption. This review systematically addresses these issues by evaluating the synthesis methods (ex situ vs. in situ), microstructural design strategies, and the role of magnetic particle alignment under varying curing conditions. Special attention is given to the influence of material composition—including matrix types, magnetic fillers, and additives—on the mechanical and magnetorheological behaviors. While the primary focus of this review is on MR foams, relevant studies on MR elastomers, which share fundamental principles, are also considered to provide a broader context. Recent advancements are also discussed, including the growing use of artificial intelligence (AI) to predict the rheological and magneto-mechanical behavior of MR materials, model complex device responses, and optimize material composition and processing conditions. AI applications in MR systems range from estimating shear stress, viscosity, and storage/loss moduli to analyzing nonlinear hysteresis, magnetostriction, and mixed-mode loading behavior. These data-driven approaches offer powerful new capabilities for material design and performance optimization, helping overcome long-standing limitations in conventional modeling techniques. Despite significant progress in MR foams, several challenges remain to be addressed, including achieving uniform particle dispersion, enhancing viscoelastic performance (storage modulus and MR effect), and improving durability under cyclic loading. Addressing these issues is essential for unlocking the full potential of MR foams in demanding applications where consistent performance, mechanical reliability, and long-term stability are crucial for safety, effectiveness, and operational longevity. By bridging experimental methods, theoretical modeling, and AI-driven design, this work identifies pathways toward enhancing the functionality and reliability of MR foams for applications in vibration damping, energy harvesting, biomedical devices, and soft robotics. Full article

The alloying elements usually lead to the precipitation of second phases in steel, readily forming at grain boundaries, and the type and distribution of these phases significantly influence the mechanical properties of the matrix. In the present contribution, the austenitic matrix fcc-Fe, the precipitate NbN, and the interface properties between them are investigated by first-principles calculations in detail. The effects of vacancy and alloying element content on the interface performance are examined. The results indicate that the density of states (DOS) of the former is primarily contributed by the Fe d-orbitals, and both exhibit elastic anisotropy. Under a tensile strain of 20%, the maximum tensile strength of fcc-Fe reaches 32.6 GPa. For NbN, the maximum tensile strength comes to 29 GPa at a strain of 10%, after which the stress rapidly decreases with the increasing of strain. In the meantime, the uneven distribution of electron cloud density increases in both. Regarding the interface, the introduction of vacancies enhances atomic interaction and improves interface stability by altering electron cloud distribution. As the Co doping content increases, the covalent interactions between atoms strengthen at the interface, enhancing interface stability. However, excessive V doping may reduce the interface stability. Furthermore, when the vacancies coexist with alloying elements, the stronger covalent characteristics are observed due to shortened bond lengths and positive bond population values. These insights provide a data foundation and theoretical basis for designing high-performance austenitic stainless steels. Full article

Olive oil and its derivatives, particularly polyphenol-rich extracts, are valued for their antioxidant, anti-inflammatory, and regenerative properties. Olive mill wastewater (OMWW), a byproduct of olive oil production, traditionally seen as an environmental pollutant, has emerged as a promising source of high-value dermatological ingredients. Key polyphenols such as hydroxytyrosol, oleuropein, and tyrosol exhibit potent antioxidant, anti-inflammatory, antimicrobial, and photoprotective effects. These compounds mitigate oxidative stress, prevent collagen degradation, modulate NF-κB and MAPK signaling, and promote cellular repair and regeneration. Skin health is increasingly recognized as crucial to overall well-being, driving interest in cosmeceuticals that combine cosmetic benefits with dermatological activity. This review examines the cosmeceutical and dermatological potential of OMWW, highlighting its incorporation into innovative topical formulations like oil-in-water nanoemulsions, liposomes, and microneedles that enhance skin penetration and bioavailability. Additionally, OMWW fractions have shown selective antiproliferative effects on melanoma cells, suggesting potential for skin cancer prevention. Valorization of OMWW through biorefinery processes aligns with circular-economy principles, converting agro-industrial waste into sustainable cosmeceutical ingredients. This approach not only meets consumer demand for natural, effective products, but also reduces the ecological footprint of olive oil production, offering a scalable, eco-friendly strategy for next-generation dermatological applications. Full article

This paper presents a load spectrum acceleration editing method based on wavelet transform. The principle of the method is to decompose the target signal using wavelet transform to obtain high-frequency wavelet components, which are classified and combined based on their frequency components for accelerated editing. During the damage segment identification stage, a threshold selection method based on the pseudo-damage gradient of the segment identification results is proposed. An envelope-based damage identification method is used to extract high-damage segments from the original signal, which are then concatenated to form an accelerated signal. Using the stress signal on the chassis of a combine harvester as a case study, the effectiveness of various accelerated editing methods is compared, with a discussion on the selection of wavelet function parameters. The results indicate that, compared to the time-domain damage retention method and the traditional wavelet transform accelerated editing method, the proposed improvement enhances the acceleration effect of the time-domain signal by 7.76% and 15.92%, respectively. The accelerated signal is consistent with the original signal in terms of statistical parameters and power spectral density. Additionally, we also found that an appropriate selection of the wavelet function’s vanishing moment can further reduce the time-domain signal length of the accelerated result by 4.8%. This study can provide beneficial experiential references for load spectrum development in the accelerated durability testing of agricultural machinery. Full article

Recently, marketing authorizations were granted by the Federal Drug Administration (FDA) for pegcetacoplan and avacincaptad pegol, which inhibit C3 and C5 complement components, respectively. These two drugs were demonstrated to slow down the growth of atrophic areas in the retina. These authorizations represent a huge breakthrough for patients suffering from geographic atrophy (GA), the late stage of the dry form of Age-related Macular Degeneration (AMD). Until then, no treatment was available to treat this blinding disease. However, these two new compounds inhibiting the complement system are still not available for patients outside of the United States, and they are not devoid of drawbacks, including a poor effect on vision improvement, an increased risk of occurrence of the neovascular form of AMD and the burden of patients receiving recurrent intravitreal injections. Thus, the important medical need posed by GA remains incompletely answered, and new therapeutic options with alternative modes of action are still required. Oxidative stress and inflammation are two major potential targets to limit the progression of atrophic retinal lesions. Dimethyl fumarate, dimethyl itaconate and other activators of the transcription factor nuclear factor erythroid 2-related factor 2 (Nrf2) display antioxidants and immunomodulatory properties that have shown evidence of efficacy in in vitro and in vivo models of dry AMD. Tecfidera^®, whose active principle is dimethyl fumarate, is already commercialized for the treatment of autoimmune diseases such as multiple sclerosis and psoriasis. The aim of this review is to present the rationale and the design of the clinical trial we initiated to test the effectiveness and safety of repurposing Tecfidera^®, which could represent a new therapeutic alternative in patients with the dry form of AMD. Full article

The aim of this study is to establish an accurate calculation method for the deflection caused by the effect of pre-stress in a steel truss web–concrete composite girder bridge based on the energy variational principle, considering the influence of shear deformation and the shear lag effect of the steel truss web member on the accuracy of the deflection calculation. The pre-stress effect is determined by the equivalent load method, and the deflection analytical solution for a composite girder bridge under straight-line, broken-line, and curve pre-stressing tendon arrangements is established. The reliability of the formula is verified using ANSYS 2022 finite element numerical simulation. At the same time, the influence of shear deformation, the shear lag effect, and their combined (dual) effect on the deflection calculation accuracy is analyzed under different linear pre-stressed reinforcement arrangements and comprehensive arrangements of pre-stressed reinforcement. The analysis of the example shows that the analytical solution for the deflection of the steel truss web–concrete composite beam, when considering only the shear deformation and the dual effect, is more consistent with the finite element numerical solution. The shear deformation of the steel truss web member under the eccentric straight-line arrangement alone does not cause additional deflection, and the additional deflection caused by the shear lag effect can be ignored. The influence of shear deformation on deflection is higher than that of the shear lag effect. The contribution ratio of the additional deflection caused by the dual effect is greater than 14%, and the influence of the dual effect on deflection is more obvious under a broken-line arrangement. Under the comprehensive arrangement of pre-stressing tendons, the contribution rate of shear deformation to the total deflection is about 3.5 times that of shear lag. Compared with the deflection value of the primary beam, the mid-span deflection is increased by 3.0%, 11.0%, and 13.9% when only considering the shear lag effect, only considering shear deformation, and considering the dual effect, respectively. Therefore, shear deformation and the shear lag effect should be considered when calculating the camber of a steel truss web–concrete composite girder bridge to improve the calculation accuracy. Full article

Betaine, a naturally occurring compound primarily derived from sugar beet by-products, has attracted increasing attention for its multifaceted roles in human and animal nutrition. Acting as both an osmolyte and a methyl group donor, betaine contributes to cellular hydration, methylation balance, antioxidant defense, and metabolic regulation. This review provides a comprehensive overview of betaine’s biological functions and its health-promoting effects across species. In humans, betaine supports hepatic function, cardiovascular health, renal protection, and physical performance, mainly by modulating homocysteine metabolism, lipid profiles, and oxidative stress. In animal production systems, it enhances growth, feed efficiency, reproductive performance, and resilience to heat stress, with species-specific applications in monogastrics, ruminants, aquaculture species, and companion animals. The review also explores the molecular mechanisms underlying betaine’s effects, including epigenetic regulation and mitochondrial function, and presents updated evidence on its biosynthesis, bioavailability, and nutrient interactions. Furthermore, the use of betaine derived from agro-industrial by-products aligns with the principles of the circular economy, promoting the sustainable reuse of valuable compounds within the agri-food chain. Despite promising findings, further research is needed to standardize effective dosages and clarify species-specific responses under different physiological and environmental conditions. Overall, betaine emerges as a promising and sustainable functional ingredient with wide-ranging applications in nutrition and health. Full article