Search Results (70,016)

Zr alloy-shaped charge liners (SCLs) offer broad application prospects due to their multiple post-penetration damage effects. However, research on these liners is still in its early stages. The mechanisms of jet formation and penetration for Zr alloys SCL remain unclear, and the specific contribution of different liner regions to the penetration process is not yet understood. This gap in knowledge has limited their structural design to a black-box correlation between global structural parameters and macroscopic penetration efficiency. To address this gap, a region-tracing Smoothed Particle Hydrodynamics (SPH) simulation was employed. Following a strategy of “wall thickness layering + axial segmentation,” the Zr alloy liner was partitioned into ten characteristic regions. This methodology facilitated the tracking of material transport from each region during jet formation and penetration into an AISI 1045 steel target. The contribution of each region to the penetration depth was then quantitatively assessed via post-processing. For the first time, the “critical region” contributing most to penetration depth was identified, and the influence of the liner’s cone angle and wall thickness on the contribution of each region was revealed. This study enhances the theoretical framework for understanding the damage effects of Zr alloy shaped charge liners. It not only advances the fundamental understanding of jet penetration mechanisms but also provides a theoretical basis for the refined design and performance optimization of these liners. Full article

As the key technology of space exploration, space power has been a major area of international research focus. A lot of research work has been carried out around the world for the space nuclear reactor using the heat pipe, liquid metal and gas cooling methods. With the development of molten salt reactor in the Generation IV reactor system, molten salt dissolving fissile material and acting as a coolant at the same time has become a new cooling scheme, which provides new ideas for the design of space nuclear reactors. In this study, a novel reactor, the liquid-solid dual-fuel space nuclear reactor (LSSNR) was preliminarily proposed, combining the molten salt fuel and cross-shaped spiral solid fuel to achieve the design goals of 30-year lifetime and an active core weight of less than 200 kg. Monte Carlo neutron transport code OpenMC based on ENDF/B-VII.1 library was employed for neutronics design in the aspect of fuel type, cladding material, reflector material and the spectral shift absorber. Then, the thickness of the control drum absorber was optimized to meet the requirement of the sufficient shutdown margin, lower solid fuel enrichment, and 30-effective-full power-years (EFPY) operation lifetime. Finally, UC solid fuel with U-235 enrichment of 80.98 wt.% and B₄C thickness of 0.75 cm were adopted in LSSNR, and BeO was adopted as the reflector and the matrix material of the control drum. A spectral shift absorber Gd₂O₃ was used to avoid the subcritical LSSNR returning to criticality in a launch accident. The k_eff with the control drum in the innermost position is 0.954949, and the k_eff reaches 1.00592 after 30 EFPY of operation. The total mass of the active core is 158.11 kg. In addition, the thermal-hydraulic feasibility of LSSNR using cross-shaped spiral fuel was analyzed based on a 4/61 reactor core model. The structure of cross-shaped spiral fuel achieves enhanced heat transfer by generating turbulence, which leads to a uniform temperature distribution of the coolant flow field and reduces local temperature peaks. Based on the LSSNR scheme, some neutronic characteristics were analyzed. Results demonstrate that the LSSNR has strongly negative reactivity coefficients due to the thermal expansion of liquid fuel, and the fission gas-induced pressure meets safety requirements. One hundred years after the end of core life, the total radioactivity of reactor core is reduced by 99% and is 7.1305 Ci. Full article

Multicomponent diffusion modeling based on the Maxwell–Stefan formulation is widely used in high-fidelity combustion simulations due to its superior physical accuracy compared with simplified diffusion models. However, the computational complexity of the Maxwell–Stefan model, which arises from the solution of coupled multicomponent transport equations, becomes a major performance bottleneck in large-scale CFD simulations. In this work, a high-performance computing optimization strategy for the Maxwell–Stefan diffusion model is developed within the OpenFOAM framework. The proposed method improves computational efficiency through block-based computation and vectorization-oriented data organization to better exploit modern CPU architectures and SIMD instruction capabilities. The optimized implementation enhances memory locality, increases data reuse efficiency, and reduces cache miss penalties. Numerical validation is performed using two-dimensional laminar counterflow flame cases and ammonia–hydrogen turbulent combustion cases, including both premixed and non-premixed jet flames. Results demonstrate that the optimized Maxwell–Stefan implementation preserves numerical accuracy while significantly improving computational performance. Speedups of 2.5×–4.5× are achieved depending on the number of chemical species. The developed approach provides an efficient solution for detailed combustion simulations involving large chemical mechanisms. The test cases and source code are openly shared. Full article

Mild behavioral impairment (MBI) is a clinical syndrome characterized by the late-life onset and persistence of neuropsychiatric symptoms (NPSs), representing a change from longstanding behavior or personality and considered a potential prodrome of neurodegenerative disease. MBI is classified into five domains: decreased motivation, affective dysregulation, impulse dyscontrol, social inappropriateness, and psychotic symptoms. In this narrative review, we synthesize clinical, neuroanatomical, and molecular evidence linking MBI to the spectrum of tauopathies, including Alzheimer’s disease (AD), frontotemporal spectrum disorders (FTSDs), and primary four-repeat tauopathies such as progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD). Emerging evidence suggests that early behavioral symptoms associated with MBI may reflect the selective vulnerability of frontolimbic, salience, default mode, and frontostriatal networks to tau-mediated neurodegeneration. Mechanistically, converging findings support roles for tau-related synaptic dysfunction, including synaptotoxic soluble tau species, cytoskeletal and axonal transport disruption, monoaminergic neurotransmitter imbalance in brainstem systems, and neuroinflammatory and glial pathways. We also highlight genotype-related behavioral profiles in genetic frontotemporal lobar degeneration and discuss how scalable blood-based biomarkers, including neurofilament light chain, glial fibrillary acidic protein, and plasma phospho-tau species, may complement MBI-based phenotyping for differential diagnosis and prognostic stratification in clinical research. Full article

Terrestrial environments function as major sinks and dynamic sources of microplastics. Land use strongly influences inputs, accumulation, and transport pathways of these contaminants in the environment. Despite the extensive literature, few reviews have compared contamination levels and the potential impacting factors across land uses. To fill this gap, this review synthesizes current knowledge on the origins, occurrence, pathways, and ecological effects of microplastics across diverse land uses. The review revealed multiple interconnected pathways that drive microplastic contamination in terrestrial systems. Abundances are consistently higher in intensively managed croplands, urban areas and industrial vicinities. However, their detection in remote environments underscores the critical role of diffuse inputs and long-range atmospheric transport. Vertically, microplastics are enriched in topsoils, and their concentrations declines with depth. Horizontally, concentration declines with increasing distance from major hotspots like agricultural fields, industrial facilities, and road networks. Ecologically, microplastics alter soil physical properties, modify chemical conditions, and shift microbial community composition and enzyme activities. Furthermore, they stress soil fauna and plants through ingestion, toxicity, and physical blockage, with impacts contingent on polymer type, particle morphology, and concentration. Collectively, this review reveals consistent spatial patterns and widespread adverse ecological impacts, highlighting the clear need for integrated management strategies to mitigate terrestrial microplastic pollution. Full article

Globally, the transport sector accounts for almost a quarter of CO₂ emissions from fuel combustion and generates large amounts of pollutants, placing significant pressure on the environment and human health. By 2050, the European Green Deal requires a 90% reduction in transport-related emissions, making sustainability necessary across all modes of transport. Based on the relevant literature, this study examines the role and potential of railways in decarbonising the EU transport sector. Railway is highly efficient, consuming just 1.9% of transport sector energy while handling 16.9% of freight and 5.1% of passenger transport in the EU, yet is responsible for only 0.4% of total emissions. According to studies, greenhouse gas emissions can be reduced by improving energy efficiency, using low-carbon or renewable energy, and expanding train electrification. The greatest potential for decarbonisation lies in a modal shift to rail. However, this requires significant infrastructure investment: raising line speeds to at least 160 km/h, expanding networks, building terminals, digitalisation, and alignment with TEN-T standards. Although the EU supports the modal shift with funding programmes, the transition is not progressing as expected—the share of road freight transport increased from 74% in 2013 to 78% in 2023. Stronger investment is needed in Member States’ national policies for the development and modernisation of railways. The authors developed a Path Evaluation Matrix (PEM), a quantitative decision framework integrating the fields of energy, transport, politics, and economics. The PEM results indicate that BEMU (battery electric multiple units) is optimal for 68% of secondary lines in south-eastern Europe. Full article

The large-scale deployment of autonomous vehicles (AVs) in mixed-traffic environments raises an important question: how do human drivers evaluate safety when interacting with AVs under real-world uncertainty? This study aims to examine how drivers’ objective knowledge of AVs shapes their perceived safety when sharing the road with AVs in mixed-traffic environments. Using survey data from 905 licensed drivers in Wuhan, China, this study treats perceived road-sharing safety as an interaction-level evaluative outcome rather than merely a precursor of adoption intention. Latent class analysis was first used to identify knowledge-based driver segments, structural equation modeling was then applied to estimate Theory of Planned Behavior (TPB)-related psychological constructs, and ordered logit regression was finally employed to examine the determinants of perceived safety across segments. The results indicate that behavioral intention consistently shows a positive association with perceived safety; however, attitude toward AVs exhibits a significant negative association among high-knowledge drivers. This attitudinal reversal challenges the implicit homogeneity assumption embedded in conventional TPB applications and suggests that cognitive familiarity may recalibrate, rather than amplify, technological optimism. Overall, the findings show that knowledge-based heterogeneity changes the psychological mechanisms underlying safety appraisal in mixed traffic. These insights carry important implications for differentiated communication strategies and trust calibration in transitional automated mobility systems. Full article

Cyclodextrins (CDs) have gained increasing attention as versatile platforms for enhancing drug delivery to the central nervous system, particularly in overcoming the restrictive properties of the blood–brain barrier (BBB). Owing to their unique cyclic oligosaccharide structure, CDs are capable of forming inclusion complexes with a wide range of therapeutic agents, thereby improving their solubility, stability, and bioavailability. In addition to their role as excipients, growing evidence indicates that CDs can actively modulate biological processes, including membrane fluidity and cholesterol homeostasis, which are critical factors in neurological disorders. This review explores the application of CDs in facilitating drug transport across the BBB through multiple mechanisms, including carrier-mediated transport, receptor-mediated transcytosis, and nanoparticle-based delivery systems. Special emphasis is placed on their use in the treatment of neurodegenerative and neurological diseases, such as Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, Niemann–Pick type C disease, and other central nervous system disorders. In these contexts, CD-based formulations have demonstrated the ability to enhance brain targeting, reduce pathological protein aggregation, and improve therapeutic outcomes in preclinical models. This review uniquely integrates cyclodextrin’s physicochemical properties with specific blood–brain barrier transport mechanisms, proposing a structure–transport–therapy framework that enables a more predictive understanding of brain-targeted drug delivery. Full article

The intestinal mucosal barrier is a layered structure comprising fundamental components that play important roles in regulating paracellular permeability. Disruption of intestinal barrier homeostasis predisposes to infections, mucosal damage, and metabolic and allergic diseases. To provide protection against potential damage to the intestinal mucosa, agents such as prebiotics and probiotics are recommended due to their ability to secrete components and metabolites (e.g., bacteriocins, organic acids, enzymes) that can exert beneficial biological effects. The aim of this study is to comprehensively investigate the effects of a postbiotic derived from Pediococcus acidilactici on healthy rat intestinal tissue. A total of 78 Wistar Albino rats were used in this study. Following compositional analysis of the postbiotic, the animals were administered the postbiotic orally via gavage for different durations (7, 14, 21, 28 days) and at different doses (250 mg/Kg, 500 mg/Kg, 1000 mg/Kg). Characterization of the produced postbiotic revealed a diverse spectrum of biologically active compounds, including organic acids, phenolics, and volatile compounds. Histopathological examination of intestinal sections (duodenum, jejunum, ileum, cecum, colon, and rectum) showed no pathological lesions in any of the experimental groups. Conversely, immunohistochemical analysis revealed that the postbiotic increased the expression of CLDN3, OCLN, ZO1, AQP4, and AQP8, proteins involved in intestinal permeability and fluid transport, in a dose-dependent manner. These results highlight the potential of Pediococcus acidilactici as a supportive agent in a range of intestinal pathologies, including major intestinal diseases such as Crohn’s disease, ulcerative colitis, and inflammatory bowel disease (IBD). Full article

The rational design of cost-effective and highly active electrocatalysts for overall water splitting remains a critical challenge for sustainable hydrogen production. Herein, we report a two-dimensional reduced graphene oxide (rGO)-supported Mo₂S₃ nanohybrid catalyst with a tunable electronic structure engineered through interfacial coupling. The intimate integration of Mo₂S₃ nanoflakes with conductive rGO nanosheet facilitates rapid electron transport, enhanced active site exposure, and optimized adsorption energetics for reaction intermediates. Structural and spectroscopic analyses confirm strong electronic interaction between Mo₂S₃ and rGO, leading to modulated charge density distribution and improved intrinsic catalytic activity. Electrochemical evaluations reveal significantly reduced overpotentials for oxygen evolution reaction (OER) with 166 mV overpotential at 10 mA cm⁻² current density, along with favorable Tafel kinetics with 38.1 mV dec⁻¹ and long-term operational stability in alkaline electrolyte. The rGO-Mo₂S₃-2||Pt-C cell delivers 10 mA cm⁻² at 1.64 V, indicating efficient alkaline water splitting. The enhanced performance is attributed to synergistic effects arising from electronic modulation, enhanced active sites, and accelerated interfacial charge transfer. Full article

Lithium sulfide (Li₂S) is indispensable for lithium–sulfur batteries and sulfide solid-state batteries. However, its high preparation cost and strict process conditions represent core bottlenecks restricting large-scale commercial application. To address this issue, a novel process featuring a low-cost, high-safety, and controllable reaction is proposed in this work. Compared with the commercial H₂S-based route for Li₂S production, the developed process presents distinct advantages, including accessible raw materials, high safety, low overall cost, and low environmental load. Using Li₂SO₄·H₂O as the raw material and Ti as the reducing agent, high-purity T-Li₂S (>99.9%) is successfully synthesized via solid-state sintering and purification, yielding a higher purity level than that of commercial C-Li₂S (>99.7%). Furthermore, sulfide all-solid-state electrolytes T-Li_5.3PS_4.3ClBr_0.7 and C-Li_5.3PS_4.3ClBr_0.7 are prepared using the as-obtained T-Li₂S and commercial C-Li₂S as precursors, respectively. The room-temperature Li-ion conductivities are determined to be 14.5 mS/cm and 11.0 mS/cm, revealing faster ion migration and efficient ion transport in T-Li_5.3PS_4.3ClBr_0.7 without high-temperature assistance, which fully validates the feasibility of the proposed strategy. Overall, this work provides a new technical route for the preparation of high-purity Li₂S, showing promising application prospects. Full article

The safety and reliability of intelligent transportation systems (ITSs) can be greatly enhanced through adding redundancy in the information-sharing network of the vehicles. In this paper, we first model the mixed traffic of human-driven and autonomous vehicles as a distributed system observability problem using a network of communicating vehicles. We clearly show that a strongly connected network with a minimum of $n$ links (with $n$ as the network size) is sufficient for the observability of a mixed-traffic network. Then, we present graph-theoretic results on adding redundancy to the changing network of vehicles to make it resilient to the failure of a certain number of vehicles/sensors or their data-sharing links. Finally, we employ a distributed observer design to validate our results using a simple mixed-traffic example. Full article

Non-cohesive earth dams are widely distributed in natural and semi-engineering scenarios, and overtopping-induced breaches are their most catastrophic failure mode. Accurate prediction of the overtopping failure process and breach evolution is critical for risk assessment, emergency management, and dam design optimization. In this study, an improved 3D numerical method is developed to simulate the coupled hydrodynamic–erosion–breach evolution processes of non-cohesive earth dams. The model based on the finite volume method integrates three core modules: a hydrodynamic module based on the Reynolds-Averaged Navier–Stokes equations with the Volume of Fluid method for free surface tracking, a dam material erosion module considering particle entrainment and transport mechanisms of non-cohesive soils, and a breach development module coupling erosion and gravitational collapse. To validate the model, two levels of verification are conducted: first, a classic benchmark dam break case is employed to confirm the feasibility of the hydrodynamic and breach evolution algorithms; second, published flume experimental data of non-cohesive earth dam overtopping failures are adopted to evaluate the model accuracy in predicting breach hydrographs and spatiotemporal evolution of breach geometry. The results demonstrate that the proposed model accurately reproduces the key characteristics of overtopping failure with high fidelity. The predicted breach flow rates and flow depths are in excellent agreement with experimental observations, with relative errors less than 5% for both peak discharge and time to peak. Consequently, this study provides a reliable numerical tool for detailed simulation of non-cohesive earth dam breaches and offers scientific support for emergency management. Full article