Search Results (47)

Against the backdrop of the continuous advancement of high-quality development in road infrastructure and the growing demand for waste asphalt recycling, the application limitations of traditional petroleum-based asphalt rejuvenators have become increasingly prominent due to their high resource dependence, poor compatibility with aged asphalt, and high volatility. By contrast, bio-oil, characterized by wide feedstock availability, outstanding renewability, and the inherent potential to modulate the colloidal structure and properties of aged asphalt, has gradually emerged as a critical research direction in the field of asphalt rejuvenator development. This paper provides a comprehensive review on the research, development and engineering application of bio-based rejuvenators. Firstly, the main feedstock systems, including vegetable oils, lignin derivatives and algal oils, are introduced, and the core preparation technologies (e.g., pyrolysis and alkali-catalyzed transesterification) are discussed, along with the impacts of their key process parameters on the chemical composition and storage stability of the end products. Subsequently, the performance of various bio-based rejuvenators in optimizing the rheological properties, high- and low-temperature performance, as well as fatigue and cracking resistance of aged asphalt is summarized, and the underlying rejuvenation mechanisms are generalized. Finally, the prevailing technical bottlenecks, such as inconsistent quality of as-prepared products and insufficient understanding of the long-term aging mechanism, are analyzed. Future research directions including oriented molecular modification, interfacial regulation, and full life cycle assessment (LCA) are proposed, to provide a systematic reference for their large-scale engineering application. Full article

Tuned liquid dampers (TLDs) are widely used in structural vibration mitigation, but they are limited by their damping frequency to use as passive damping equipment. To enhance the damping performance of the conventional TLD, a unique layered tuned liquid damper (LTLD) filled with water and diesel is proposed. The interfacial wave coupling mechanism for broadband energy dissipation has not been previously explored in sloshing-type dampers. A series of frequency-sweeping tests were carried out in the laboratory to compare the vibration suppression performance of the proposed LTLD against conventional TLD. The dampers were installed on an elastic supporting structural platform (SSP) with a height of one meter, and the bottom was horizontally excited with different amplitudes and frequencies using a hexapod motion simulator. The results indicate that the LTLD showed a better damping performance than the TLD under small-amplitude excitation and achieved optimization at two peaks. The separation surface movement dissipated the liquid motion’s energy and enhanced the hydrodynamic force in the horizontal direction. However, the damping effect of the LTLD weakened when the two liquids were no longer immiscible under large-amplitude excitation. Therefore, we recommend utilizing the LTLD to improve structural damping performance when $d_{max}/L$< 0.04984. In addition, the LTLD reduced the maximum wall pressure by about 25% in the transient state under large-amplitude excitation. This study presents experimental evidence that a water–diesel LTLD achieves broadband damping through interfacial wave coupling. The stable interfacial waves enhance energy dissipation and excite new vibration mitigation frequencies, offering a novel approach to overcoming the narrow-band limitation of conventional TLD. Full article

To investigate the leakage characteristics of damaged double-hull oil tanks in still water, this study conducted both model tests and numerical simulations on the leakage process of a damaged double-hull oil tank model. Based on a 75,000 DWT oil tanker, a scaled model was designed according to similarity criteria. The effects of different damaged locations (side-shell and bottom) and various breach sizes on the tank’s leakage behavior were examined. The evolution of multiphase flow inside the tank and the surrounding flow field was captured, and the leakage pressure under fixed model conditions was measured. The model test results indicate that larger breach sizes lead to a more rapid stabilization of the pressure load during leakage and the liquid exchange process. For side shell breaches, after an initial phase of pressure-difference-driven leakage, a density-driven flow develops at the stable liquid interface. Bottom breaches cause flooding that results in an oil sealing phenomenon at the bottom, leading to a pronounced oil–water stratification. Corresponding numerical simulations of the model tests were performed, and the results were compared and validated against the model test data. Full article

Recent advances in single-cell RNA sequencing (scRNA-seq) have substantially deepened our understanding of adult hippocampal neurogenesis (AHN), enabling the detection of neural stem cells, progenitors, and immature neurons in postmortem human brain tissue and revealing how these populations are altered in neurological disease. Additionally, scRNA-seq enables the identification of disease-specific cell subtypes and distinct gene expression signatures associated with neurological disorders, many of which are linked to alterations in AHN and cognitive function. Such cellular- and molecular-level insights into neurological disease mechanisms provide a strong foundation for the development of targeted therapeutic strategies. Indeed, scRNA-seq has also emerged as a powerful tool in drug discovery and development across multiple disease areas, including cancer, cardiovascular disorders, and neurological conditions. In this review, we offer a comprehensive and integrative perspective on the cellular and molecular landscape of human hippocampal neurogenesis, the pathological mechanisms underlying neurological disorders, and their implications for therapeutic development. Full article

This study aims to develop effective screening tools for cognitive impairment by integrating optimised speech classification features with various machine learning models. A total of 65 patients diagnosed with early-stage Mild Cognitive Impairment (MCI) and 55 healthy controls (HCs) were included. Audio data were collected through a picture description task and processed using the Python-based Librosa library for speech feature extraction. Three machine learning models were constructed: the Random Forest (RF) and Support Vector Machine (SVM) models utilised speech classification features optimised via the Sequential Forward Selection (SFS) algorithm, while the Extreme Gradient Boosting (XGBoost) model was trained on preprocessed speech data. After parameter tuning, the Librosa library successfully extracted 41 speech classification features from all participants. The application of the SFS optimisation strategy and the use of preprocessed data significantly improved identification accuracy. The SVM model achieved an accuracy of 0.825 (AUC: 0.91), the RF model reached 0.88 (AUC: 0.86), and the XGBoost model attained 0.92 (AUC: 0.91). These results suggest that speech-based machine learning models markedly improve the accuracy of distinguishing MCI patients from healthy older adults, providing reliable support for early cognitive deficit identification. Full article

Designing high-speed aircraft for wide-speed-range operation remains a major aerodynamic challenge. This study investigates the unsteady aerodynamics of a continuously morphing airfoil from transonic to hypersonic regimes. A smooth morphing trajectory is constructed among transonic, supersonic, and hypersonic baseline shapes, and analyzed via high-fidelity unsteady Reynolds-averaged Navier–Stokes (URANS) simulations with a radial basis function (RBF) dynamic mesh. Two processes are examined: pure geometric morphing at fixed Mach numbers (Ma), and morphing coupled with flight acceleration. Key findings reveal two distinct adaptation features: (1) Transonic flow is highly sensitive to morphing (28.8% drop in lift-to-drag ratio), while supersonic flow is robust (<5% variation). (2) During coupled acceleration, the flow transitions smoothly—the shock evolves from a detached bow wave to an attached oblique structure, and the adaptive airfoil maintains a lift-to-drag ratio above 4 across Ma = 0.8–6. Additionally, wake vorticity transitions from organized shear layers to multi-scale clusters. These results elucidate the flow physics mechanism of continuous morphing and provide a framework for designing adaptive wide-speed-range aircraft. Full article

Background: Hand, foot, and mouth disease (HFMD) remains a major public-health concern in China. While the monovalent EV-A71 vaccine has effectively reduced EV-A71–associated cases, it offers no protection against CV-A16. The introduction of a bivalent EV-A71/CV-A16 vaccine may offer broader protection, but its economic viability under different immunization strategies remains uncertain. Methods: We developed a dynamic transmission model integrated with cost-effectiveness analysis to assess the epidemiological and economic impact of a hypothetical bivalent EV-A71/CV-A16 vaccine in China. Based on the immunization program policy, seven vaccination strategies, vaccine effectiveness (VE) levels ranging from 50–95% against EV-A71/CV-A16, and coverage levels from 0–95% were evaluated. The threshold vaccine price (TVP) was derived based on incremental cost-effectiveness ratio (ICER) calculations. Cost-effectiveness was assessed using willingness-to-pay (WTP) thresholds defined as 1–3 times the gross domestic product (GDP) per capita. Results: The mean cost of two doses of the monovalent EV-A71 vaccine was USD133.0 (95% CI: 126.9–139.1). Strategy 2, which targeted individuals unvaccinated with the monovalent EV-A71 vaccine, demonstrated the most favorable cost-effectiveness. At 45% coverage and 85% vaccine effectiveness, the estimated threshold price per dose was USD 107.7 (95% CI: 103.4–112.0), with threshold vaccine prices increasing as coverage declined. When vaccination coverage exceeded 80%, the threshold vaccine price decreased substantially, falling below USD 45.9 (95% CI: 43.5–48.3) per dose. Conclusions: Large-scale inclusion in the national immunization program may not be economically justified at current cost levels. Targeted voluntary vaccination of unvaccinated, susceptible populations represents a more cost-effective and practical strategy during the early stage of vaccine introduction. Full article

Gas sensors are vital tools in areas such as environmental monitoring, industrial safety, and personal healthcare. Among various sensing materials, semiconductor metal oxides (SMOs) are widely studied owing to their high sensitivity, good stability, and notable catalytic activity. To overcome inherent drawbacks of pure SMOs—such as high operating temperatures, limited selectivity, sluggish response/recovery behavior, and inadequate long-term stability—functionalization with noble metals has emerged as a powerful modification strategy. This review systematically outlines the primary mechanisms through which noble metals enhance gas sensing performance and analyzes the key factors influencing sensor behavior. Finally, we discuss the current challenges and future directions in the development of noble metal-modified SMO gas sensors. Full article

Debris flow erosion is key to the escalation of potential hazards, which may jeopardize the sustainable development of nearby human habitats. However, studies pertaining to this issue are impeded by the intricate interactions of flow and sediment. Thus, this study introduces an unresolved CFD-DEM coupled simulation primarily relying on a classical numerical simulation and a physical experiment to study the critical erosion process of debris flows on a dry basal sediment under laboratory scale. Results indicate that three layers of substrate bed can be verified during the erosion process, and there is a positive correlation between the erosion depth and the particle size with the Froude number of debris flow, as well as between the erosion length and the critical entrainment transport with the total mass of debris flow. In addition, thresholds for the collisional point load and the impact energy of debris flow head, which are essential for predicting the attenuating rates of erosive depth and the critical entrainment transport, have been proposed based on data regressions derived from power functions. The coupled numerical approach is capable of accurately simulating the erosion behavior of debris flows similarly to physical model experiments, thereby providing both theoretical and practical insights into the dynamics of erosion. Full article

Desmodesmus spinosus (Chodat) E.Hegewald is a common freshwater green microalgae widely distributed in various aquatic environments. Owing to its pollution tolerance and rapid growth characteristics, it is often used in bioremediation and biofuel studies. Here, we report the draft chloroplast (cp) genome of this species here for the first time to facilitate its genomic features and phylogenetic position in Scenedesmaceae. The whole chloroplast genome was 167, 203 base pairs in length, with 104 annotated genes, including 69 protein-coding genes, 29 tRNAs, and 6 rRNAs. The introns identified among them were: rbcL, psaA, and petD, each containing 1 intron; atpB with 2 introns; and psbA with 3 introns. A total of 106 SSRs with 16 motif classes, 50 dispersed repeats, and 17 long tandem repeats were identified in this genome. A total of 221 RNA-editing sites were distributed across 46 protein-coding genes in this genome. In IR boundaries, the position of genes was found to be remarkable in differentiating species, such as trnH and ycf1 at JLB and JSA, cemA, psbC, and rpl22 at JS, and cemA, psbC and rrs at JSB. Notably, psbA-rps11, psbH-psbK, and trnR-ACG-psbM were highly variable regions. Phylogenetic analysis revealed a sister relationship between D. spinosus and D. abundans. Chloroplast genomic data and findings from phylogenetic studies of D. spinosus could provide useful information and shed light on in-depth studies on the evolution pattern of the understudied species, as well as that of Scenedesmaceae. Full article

Although exercise is known to exert anti-inflammatory effects in neurodegenerative diseases, its specific impact and underlying mechanisms in Parkinson’s disease (PD) remain poorly understood. This study explores the effects of exercise on microglia-mediated neuroinflammation and apoptosis in a PD model, focusing on the role of irisin signaling in mediating these effects. Using a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mouse model, we found that a 10-week treadmill exercise regimen significantly enhanced motor function, reduced dopaminergic neuron loss, attenuated neuronal apoptosis, and alleviated neuroinflammation. Exercise also shifted microglia from a pro-inflammatory to an anti-inflammatory phenotype. Notably, levels of irisin, phosphorylated AMP-activated protein kinase (p-AMPK), and sirtuin 1 (Sirt1), which were decreased in the PD brain, were significantly increased following exercise. These beneficial effects were abolished by blocking the irisin receptor with cyclic arginine–glycine–aspartic acid–tyrosine–lysine (cycloRGDyk). Our results indicate that exercise promotes neuroprotection in PD by modulating microglial activation and the AMPK/Sirt1 pathway through irisin signaling, offering new insights into exercise-based therapeutic approaches for PD. Full article

The prosperity of enzyme-mimicking catalysis has promoted the development of nanozymes with diversified activities, mainly including catalase-like, oxidase-like, peroxidase-like, and superoxide dismutase-like characteristics. Thus far, the reported nanozymes can be roughly divided into five categories, comprising noble metals, metal oxides, carbon-based nanostructures, metal–organic frameworks, and covalent organic frameworks. This review systematically summarizes the research progress of nanozymes for improving catalytic activity toward sensing applications in food safety monitoring. Specifically, we highlight the unique advantages of nanozymes in enhancing the performance of colorimetric, fluorescence, and electrochemical sensors, which are crucial for detecting various food contaminants. Moreover, this review addresses the challenges faced in food safety detection, such as the need for high sensitivity, selectivity, and stability under complex food matrices. Nanozymes offer promising solutions by providing robust catalytic activity, adjustable enzyme-like properties, and excellent stability, even in harsh environments. However, practical implementation challenges remain, including the need for a deeper understanding of nanozyme catalytic mechanisms, improving substrate selectivity, and ensuring long-term stability and large-scale production. By focusing on these aspects, this review aims to provide a comprehensive overview of the current state of nanozyme-based sensors for food safety detection and to inspire future research directions. Full article

Thermal-processed foods like baked, smoked, and fried products are popular for their unique aroma, taste, and color. However, thermal processing can generate various contaminants via Maillard reaction, lipid oxidation, and thermal degradation, negatively impacting human health. This review summarizes the formation pathways, influencing factors, and tracing approaches of potential hazards in thermally processed foods, such as polycyclic aromatic hydrocarbons (PAHs), heterocyclic aromatic amines (HAAs), furan, acrylamide (AA), trans fatty acids (TFAs), advanced glycation end-products (AGEs), sterol oxide. The formation pathways are explored through understanding high free radical activity and multiple active intermediates. Control patterns are uncovered by adjusting processing conditions and food composition and adding antioxidants, aiming to inhibit hazards and enhance the safety of thermal-processed foods. Full article

Maize is a staple crop in China, playing a crucial role in agriculture and food security. However, current planting densities are suboptimal, leading to lower yields and unrealized potential. This study explores the potential to maximize maize yields by optimizing planting density and implementing region-specific agronomic measures across China’s diverse agro-ecological zones. We compiled a dataset consisting of 1974 independent field trials from 720 publications across China’s main maize-growing areas, spanning the period from 2000 to 2023, to assess the impact of optimal planting density and agronomic practices on China’s maize production. Our findings reveal that increasing the planting density to optimal levels—49.34% higher than current farmer practices—can significantly boost national maize yields by 16.28%. Furthermore, adopting agronomic techniques like precision irrigation, soil tillage, and plant growth regulators enhances this effect, raising planting density by 69.91% and yield by 27.26%. Notably, the irrigated maize-growing areas in Northwest China showed the highest yield potential, whereas the southern hilly regions had the lowest. This underscores the significance of tailoring optimal density and agronomic practices to each region. Combining agronomic measures with adjusted planting densities can reduce this disparity. Precision irrigation, soil tillage, and plant growth regulators were particularly effective in optimizing planting density and maximizing yield potential, especially in Northwest China and the North China Plain. In contrast, plant growth regulators proved most effective in Southwest China and Southern China. This study underscores the potential of integrating optimized planting density with agronomic measures to significantly improve maize productivity, thereby supporting sustainable agriculture. It provides a scientific basis for regionalized agricultural management. Full article

Food safety is directly related to human health and has attracted intense attention all over the world. Surface-enhanced Raman scattering (SERS), as a rapid and selective technique, has been widely applied in monitoring food safety. SERS substrates, as an essential factor for sensing design, greatly influence the analytical performance. Currently, nanostructure-based SERS substrates have garnered significant interest due to their excellent merits in improving the sensitivity, specificity, and stability, holding great potential for the rapid and accurate sensing of food contaminants in complex matrices. This review summarizes the fundamentals of Raman spectroscopy and the used nanostructures for designing the SERS platform, including precious metal nanoparticles, metal–organic frameworks, polymers, and semiconductors. Moreover, it introduces the mechanisms and applications of nanostructures for enhancing SERS signals for monitoring hazardous substances, such as foodborne bacteria, pesticide and veterinary drug residues, food additives, illegal adulterants, and packaging material contamination. Finally, with the continuous progress of nanostructure technology and the continuous improvement of SERS technology, its application prospect in food safety testing will be broader. Full article