Search Results (69,918)

Miniaturized pressure sensors fabricated via micro-electro-mechanical systems (MEMSs) technology are ubiquitous in modern applications. However, the massively produced MEMS pressure sensors, prior to being practically used, need to be calibrated one by one to eliminate or minimize nonlinearity and zero drift. This paper presents a systematic design for the testing and calibration process of MEMS-based absolute pressure sensors. Firstly, a numerical analysis is carried out using finite element method (FEM) simulation, which verifies the accuracy of the temperature control of the physical calibration system. The simulation results reveal a slight non-uniformity of temperature distribution, which is then taken into consideration in the calibration algorithm. Secondly, deploying a home-made calibration system, the MEMS pressure sensors are tested automatically and rapidly. The experimental results show that each batch, which consists of nine sensors, can be calibrated in 80 min. The linearity and temperature coefficient (TC) of the pressure sensors are reduced from 46.5% full-scale (FS) and −1.35 × 10⁻⁴ V·K⁻¹ to 1.5% FS and −8.8 × 10⁻⁷ V·K⁻¹. Full article

Farmers’ land transfer practices optimize the allocation of agricultural resources by transferring them to more efficient operators. This enhances agricultural productivity and advances rural revitalization. However, due to the lack of financial institution outlets in rural areas, the availability of financial services in rural areas is limited, which in turn hinders the transfer of rural land. This study examines the impact of digital financial inclusion, characterized by the deep integration of internet technology and financial services, on farmers’ land transfer behavior in China. The study uses data from the China Family Panel Studies (2012–2022) and provincial digital financial inclusion data. The results show that digital financial inclusion significantly promotes rural land transfer-out. The mechanisms reveal two pathways: (1) digital financial inclusion expands non-agricultural entrepreneurship by easing credit constraints and reducing reliance on land livelihoods; (2) it increases participation in commercial insurance, mitigating risks of land abandonment. Heterogeneity analysis reveals stronger effects in eastern China and among educated households. Theoretically, the study identifies the dual role of financial technology in reshaping rural land markets through credit access and risk management. Practically, it reveals how DFI influences land transfer behavior, providing a basis for the government to formulate policies that combine the two, ultimately enhancing the production capacity, operational efficiency, and market competitiveness of smallholder farmers. The findings offer global insights for developing countries that are leveraging digital finance to activate rural land markets and achieve digital financial inclusion. Full article

Background: Vancomycin-resistant Enterococcus faecium (VREfm), particularly vanA-positive strains, represents a growing threat in hospital settings worldwide. These bacteria are able to survive under severe environmental conditions, including high temperatures and saline concentrations. High genome plasticity and advanced ability of inheriting antimicrobial resistance determinants defined the success of E. faecium as a hospital pathogen. Methods: This study presents the whole genomic characterization of vanA-positive VREfm isolates, analyzing 10 clinical isolates collected from three tertiary care hospitals in Moscow, Russia. Several typing approaches, including two MLST schemes and cgMLST profiles, were used to elucidate the relationship between the isolates. Phylogenetic analysis placed the isolates in context with global VREfm populations, demonstrating both local clonal expansion and possible international connections. Phenotypic and genomic antimicrobial resistance profiles were obtained, as well as data regarding the repertoire of virulence factors and plasmid content. Results: Whole genome sequencing revealed that all isolates belonged to the clinically significant CC17 lineage, specifically sequence types ST80 and ST552. Notably, two isolates possessed truncated Tn1546-type transposons lacking vanY and vanZ genes, representing a potentially emerging variant of the vanA operon in Russian clinical settings. A plasmid carrying a truncated vanA operon was reconstructed using long-read sequencing. Conclusions: The study highlights the utility of genomic investigation for tracking resistance mechanisms and strain dissemination, providing crucial baseline data for epidemiological surveillance of infections caused by VREfm in Russia. These findings emphasize the need for continued genomic monitoring to understand the evolution and spread of antimicrobial resistance in clinically important enterococcal lineages. Full article

Predictive maintenance (PdM) is a cornerstone of smart manufacturing, enabling the early detection of equipment degradation and reducing unplanned downtimes. This study proposes an advanced machine learning framework that integrates the Extreme Learning Machine (ELM) with a novel hybrid metaheuristic optimization algorithm, the Polar Lights Salp Cooperative Optimizer (PLSCO), to enhance predictive modeling in manufacturing processes. PLSCO combines the strengths of the Polar Light Optimizer (PLO), Competitive Swarm Optimization (CSO), and Salp Swarm Algorithm (SSA), utilizing a cooperative strategy that adaptively balances exploration and exploitation. In this mechanism, particles engage in a competitive division process, where winners intensify search via PLO and losers diversify using SSA, effectively avoiding local optima and premature convergence. The performance of PLSCO was validated on CEC2015 and CEC2020 benchmark functions, demonstrating superior convergence behavior and global search capabilities. When applied to a real-world predictive maintenance dataset, the ELM-PLSCO model achieved a high prediction accuracy of 95.4%, outperforming baseline and other optimization-assisted models. Feature importance analysis revealed that torque and tool wear are dominant indicators of machine failure, offering interpretable insights for condition monitoring. The proposed approach presents a robust, interpretable, and computationally efficient solution for predictive maintenance in intelligent manufacturing environments. Full article

Driven by the urgent need to decarbonize the logistics sector—where conventional vehicles exhibit high energy consumption and emissions, posing significant environmental sustainability challenges—electrification represents a pivotal strategy for reducing emissions and achieving sustainable urban freight transport. Despite rising global electric vehicle sales, the penetration rate of electric logistics vehicles (ELVs) remains comparatively low, impeding progress toward sustainable logistics objectives. Battery-swapping mode (BSM) has emerged as a potential solution to enhance operational efficiency and economic viability, thereby accelerating sustainable adoption. This model improves ELV operational efficiency through rapid battery swaps at centralized stations. This study constructs a tripartite evolutionary game model involving government, consumers, and BSM-ELV manufacturers to analyze market dynamics under diverse strategies. Key considerations include market scale, government environmental benefits, battery leasing/purchasing costs, lifecycle cost analysis (via discount rates), and resource efficiency (reserve battery ratio $\lambda$). MATLAB-2021b-based simulations predict participant strategy evolution paths. Findings reveal that market size and manufacturer expectations significantly influence governmental and manufacturing strategies. Crucially, incorporating discount rates demonstrates that battery leasing reduces consumer enterprises’ initial investment, enhancing economic sustainability and cash flow while offering superior total cost of ownership. Furthermore, gradual reduction of government subsidies effectively stimulates market self-regulation, incentivizes leasing adoption, and bolsters long-term economic/operational sustainability. Market feedback can guide policy adjustments toward fiscally sustainable support mechanisms. This study proposes the following management implications for advancing sustainable logistics: 1. Governments should phase out subsidies systematically to foster market resilience; 2. Manufacturers must invest in BSM R&D to improve efficiency and resource circularity; 3. Consumer enterprises can achieve economic benefits and emission reductions by adopting BSM-ELVs. Full article

Background: Meniere’s disease (MD) is a rare inner ear disorder characterized by endolymphatic hydrops and symptoms such as vertigo and hearing loss, with no curative treatment currently available. XuanYunNing tablets (XYN) have been clinically used to treat MD, but their molecular mechanisms remain unclear. Objective: This study aimed to systematically evaluate the pharmacological effects of XYN in a guinea pig model of MD and to elucidate the underlying molecular mechanisms of both MD pathogenesis and XYN intervention through integrated multi-omics analyses, including transcriptomics, proteomics, and bioinformatics. Methods: A guinea pig model of endolymphatic hydrops was induced by intraperitoneal injection of desmopressin acetate (dDAVP). Pharmacodynamic efficacy was evaluated via behavioral scoring and histopathological analysis. The differentially expressed genes (DEGs) and differentially expressed proteins (DEPs) modulated by XYN treatment were identified using high-throughput transcriptomic and proteomic sequencing. These data were integrated through multi-omics bioinformatic analysis. Key molecular targets and signaling pathways were further validated using RT-qPCR and Western blotting. Results: Pharmacological evaluations showed that guinea pigs in the model group exhibited a 26% increase in endolymphatic hydrops area, while high-dose XYN treatment reduced this area by 19% and significantly improved functional parameters, including overall physiological condition (e.g., weight and general appearance), auricular reflexes to low-, medium-, and high-frequency sound stimuli, nystagmus, and the righting reflex. High-throughput sequencing combined with integrative omics analysis identified 513 potential molecular targets of XYN. Subsequent network and module analyses pinpointed the JAK-STAT signaling pathway as the central axis. Mendelian randomization (MR) analysis further supported a causal relationship between MD and metabolic, immune, and inflammatory traits, reinforcing the central role of JAK-STAT signaling in both MD progression and XYN-mediated intervention. Mechanistic studies confirmed that XYN downregulated IFNG, IFNGR1, JAK1, p-STAT3/STAT3, and AOX at both mRNA and protein levels, thereby inhibiting aberrant JAK-STAT pathway activation in MD model animals. In addition, a total of 125 chemical constituents were identified in XYN by UHPLC-MS analysis. ZBTB20 and other molecules were identified as potential blood-based biomarkers for MD. Conclusions: This study reveals that XYN alleviates MD symptoms by disrupting a pathological cycle driven by JAK-STAT signaling, inflammation, and metabolic dysfunction. These findings support the clinical potential of XYN in the treatment of Meniere’s disease and may inform the development of novel therapeutic strategies. Full article

The production of alumina produces red mud (RM), a highly alkaline solid waste. The majority of it is disposed of in landfills, which seriously pollutes the environment. It needs to be recycled and handled with care to protect the environment. RM is a promising raw material for wastewater and waste gas treatment owing to its high alkalinity and abundant metal compounds. It can efficiently remove diverse pollutants while facilitating large-scale utilization of RM resources. Reviews of the use of RM resources to create catalysts for environmental governance are, nevertheless, scarce. Therefore, this paper analyzes and summarizes the pertinent research on RM-based catalysts to remove pollutants from the environment based on journal literature related to RM resource utilization from 2015 to 2025. This study reviews the application of RM-based catalysts for degrading pollutants in wastewater and exhaust gases via advanced oxidation processes (AOPs)—including photocatalysis, Fenton-like catalysis, ozonation catalysis, and persulfate catalysis—as well as catalytic oxidation, chemical looping combustion (CLC), and selective catalytic reduction (SCR). The paper emphasizes the analysis of modification strategies and catalytic mechanisms of RM-based catalysts in environmental remediation and examines the environmental risks and corresponding mitigation measures related to their preparation from RM resources. Finally, it outlines that future research should prioritize green, low-energy modification processes; catalytic systems for the synergistic removal of multiple pollutants; and efficient, recyclable separation and recovery technologies. These directions aim to promote the sustainable application of RM in large-scale environmental remediation and to achieve the integrated advancement of resource utilization and ecological protection. Full article

Cobalt-based bulk metallic glasses (Co-based BMGs) offer a combination of high strength, corrosion resistance, and soft magnetic properties, yet their limited glass-forming ability (GFA) and poor room-temperature ductility restrict broader application. In this study, a microalloying strategy was applied to the Co₆₁Nb₈B₃₁ base composition to develop Co-Nb-B-Si and Co-Fe-Nb-B-Si systems. The effects of Si addition and Fe substitution on GFA, thermal stability, and mechanical properties were systematically investigated. Si doping combined with Co/B ratio tuning broadened the supercooled liquid region and increased the critical glass-forming diameter from 1 mm to 3 mm. Further addition of 5 at.% Fe expanded the supercooled liquid region and enabled the fabrication of a fully amorphous plate with 1 mm thickness. The optimized Co₆₃Nb₈B₂₇Si₂ alloy exhibited a compressive strength of 5.18 GPa and a plastic strain of 3.81%. Fracture surface analysis revealed ductile fracture features in the Si-containing alloy and brittle characteristics in Fe-rich compositions. These results demonstrate that microalloying is effective in optimizing the balance between GFA and mechanical performance of Co-based BMGs, offering guidance for composition and processing design. Full article

The environmental challenges posed by global warming have significantly increased the global pursuit of renewable and clean energy sources. Among these, solar energy stands out due to its abundance, renewability, low environmental impact, and favorable long-term economic viability. However, its intermittent nature and dependence on weather conditions hinder consistent and efficient utilization. To address these limitations, nanoparticle-enhanced phase change materials (NPCMs) have emerged as a promising solution for enhancing thermal energy storage in solar thermal systems. NPCMs incorporate superior-performance nanoparticles within traditional phase change material matrices, resulting in improved thermal conductivity, energy storage density, and phase change efficiency. This review systematically examines the recent advances in NPCMs for solar energy applications, covering their classification, structural characteristics, advantages, and limitations. It also explores in-depth analytical approaches, including mechanism-oriented analysis, simulation-based modelling, and algorithm-driven optimization, that explain the behavior of NPCMs at micro and macro scales. Furthermore, the techno-economic implications of NPCM integration are evaluated, with particular attention to cost-benefit analysis, policy incentives, and market growth potential, which collectively support broader adoption. Overall, the findings highlight NPCMs as a frontier in materials innovation and enabling technology for achieving low-carbon, environmentally responsible energy solutions, contributing significantly to global sustainable development goals. Full article

Drought stress caused by continuous global warming poses a severe challenge to the growth and development of Nitraria tangutorum. Abscisic acid has an important regulatory function in the process of plants responding to drought stress. This study took the N. tangutorum seedlings of Zhangye provenance 2-17-16 genealogy as the research object to explore the physiological mechanism of how different concentrations of exogenous ABA alleviate drought damage in N. tangutorum. The results showed that exogenous ABA could promote the growth and increase the leaf relative water content of N. tangutorum seedlings under drought stress. It alleviates the photosynthetic inhibition phenomenon of N. tangutorum seedlings under drought stress by regulating the photoprotective mechanism and energy distribution efficiency of photosystem II. It also alleviates the drought damage of N. tangutorum by increasing the content of osmotic-adjustment substance contents such as soluble sugar, soluble protein, proline, and starch, as well as enhancing the activity of antioxidant enzymes such as POD, SOD, and CAT. The comprehensive analysis showed that 20 μM and 30 μM ABA have the best alleviating effects on the drought damage of N. tangutorum seedlings. This study provides a theoretical basis for the restoration, propagation, and protection of N. tangutorum, and it is of great significance for maintaining the balance and stability of desert ecosystems. Full article

This study investigates the strength and microstructural evolution of SRX-stabilized aeolian sand–gravel mixtures for flexible base applications in desert roads. CBR, UPS (uniaxial penetration strength), and compressive resilient modulus tests were conducted under varying SRX dosages (0.4–1.0%) and aeolian sand contents (30–50%). The results show that increasing the SRX dosage significantly improves all three indices, with the 0.5% SRX and 30% aeolian sand mixture yielding the CBR (385.89%) and UPS (0.938 MPa) and achieving a compressive resilient modulus that meets the requirements for graded aggregate base layers. XRD FTIR and SEM–EDS analyses reveal that the SRX enhances material structure primarily through physical mechanisms, forming dense films and bonding networks without inducing significant chemical reactions. Extended curing improves structural integrity, while excessive aeolian sand reduces compactness. SRX-stabilized aeolian sand gravel is a viable base and subbase material for desert highways. Full article

Background: The thalamus, together with its associated nuclei and thalamocortical pathways, is crucial in understanding the neurobiological mechanisms underlying auditory verbal hallucinations (AVHs) in schizophrenia (SCZ). Purpose: The study investigates the role of thalamic nuclei in schizophrenia patients experiencing auditory verbal hallucinations (AVHs). Methods: A total of 21 healthy controls (HC), 22 schizophrenia patients without auditory verbal hallucinations (SCZ_AVH−), and 22 schizophrenia patients with auditory verbal hallucinations (SCZ_AVH+), aged between 19 and 65 years, were recruited. They underwent MRI scans, and participants in the SCZ_AVH+ group completed the assessment of the severity of different dimensions of auditory hallucinations and delusions using the psychotic symptom rating scale (PSYRATS). High-resolution T1-weighted imaging was utilized to analyze the volumes of the thalamic nuclei. Results: The volumetric analysis of the thalamic nuclei indicated a significant reduction (t = 2.64, P = 0.03) in the right medial geniculate nucleus (MGN) volume in the SCZ_AVH+ group (0.08 ± 0.01 cm³) compared to the SCZ_AVH− group (0.09 ± 0.01 cm³). Also, the SCZ_AVH− group (0.03 ± 0 cm³) showed a significant increase (t = −2.73, P = 0.02) in right habenular nucleus (HN) volume compared to the HC group (0.02 ± 0 cm³). Significant correlations were observed between the volume of the left MGN and psychotic ratings (r= −0.5), as well as between the volume of the right HN and psychotic ratings (r= 0.56). Conclusion: The volumetric changes are observed in both SCZ_AVH− and SCZ_AVH+ groups, mainly in the thalamic nuclei. Structural deficits in the MGN may distinguish schizophrenia patients with AVHs from those without. Full article

Change detection technology holds significant importance in disciplines such as urban planning, land utilization tracking, and hazard evaluation, as it can efficiently and accurately reveal dynamic regional change processes, providing crucial support for scientific decision-making and refined management. Although deep learning methods based on computer vision have achieved remarkable progress in change detection, they still face challenges including reducing dynamic background interference, capturing subtle changes, and effectively fusing multi-temporal data features. To address these issues, this paper proposes a novel change detection model called OFNet. Building upon existing Siamese network architectures, we introduce an optical flow branch module that supplements pixel-level dynamic information. By incorporating motion features to guide the network’s attention to potential change regions, we enhance the model’s ability to characterize and discriminate genuine changes in cross-temporal remote sensing images. Additionally, we innovatively propose a dual-domain attention mechanism that simultaneously models discriminative features in both spatial and frequency domains for change detection tasks. The spatial attention focuses on capturing edge and structural changes, while the frequency-domain attention strengthens responses to key frequency components. The synergistic fusion of these two attention mechanisms effectively improves the model’s sensitivity to detailed changes and enhances the overall robustness of detection. Experimental results demonstrate that OFNet achieves an IoU of 83.03 on the LEVIR-CD dataset and 82.86 on the WHU-CD dataset, outperforming current mainstream approaches and validating its superior detection performance and generalization capability. This presents a novel technical method for environmental observation and urban transformation analysis tasks. Full article

Efficient urban land use is a cornerstone of sustainable city development, yet the drivers of such efficiency are increasingly complex in an era of spatial transformation. As industrial specialization and collaboration deepen, cities are becoming interconnected through complex networks. These “invisible threads” are redefining the dynamics of land use and spatial efficiency. This study examines the influence of intercity industrial networks on urban land use efficiency by constructing urban networks from multi-regional input–output data and evaluating city performance using a super-SBM model. We employed Tobit regression and mediation analysis to identify the mechanisms. Results indicate that both the quantity and quality of urban network connections significantly enhance land use efficiency, with notable differences across city types. The positive effect of industrial network centrality is most pronounced in large cities. In growing cities, both the number and quality of industrial linkages promote efficiency, whereas in shrinking cities, connection quality is more critical than quantity. Mechanism analysis reveals that industrial networks improve land use efficiency primarily by expanding intermediate goods markets and fostering technological innovation. Full article

This paper presents a novel large-span ring deployable perimeter truss for the mesh reflector deployable antennas, which is made up of two parts including a single-mobility driving mechanism and a ring deployable metamorphic mechanism. The mechanism design employs polygon approximation, and each side is treated as a basic unit using a modular design approach. By reasonable assembly, a ring deployable metamorphic mechanism with a small folded state and a large deployed state can be formed. Here, multiple singular positions, the axis of its three revolute joints being parallel and coplanar, are used in the fully deployed state, which forms multiple dead-center positions and changes the constraint conditions. The metamorphic motion is thus achieved, and a stable self-locking state is established that greatly enhances the stability. The paper first introduces the mechanism design and evaluation method; the kinematic and dynamic analysis is then conducted, and the simulation validation is also performed. Moreover, a principle design for cable-net structural setting and connection is illustrated. Finally, with the design of a driving system and the fabrication of a physical prototype, the deployable experiments are carried out, and the results show that the perimeter truss can efficiently act as the mesh reflector deployable antennas. Full article