Search Results (291)

Aircraft structures are highly susceptible to fatigue damage, particularly in thin-walled aluminum alloy components such as skin panels. Damage in the form of holes or material loss drastically reduces fatigue life and compromises structural safety, which makes effective repair strategies essential. This study presents an experimental investigation into the fatigue performance of EN AW-2024-T3 aluminum alloy plates with central openings subjected to uniform shear. Repair nodes were applied using two approaches: conventional riveted metal patches and adhesively bonded composite patches. Variants of patch geometry, thickness, and diameter were evaluated to determine their influence on load transfer, buckling response, and fatigue life. The results show that central holes significantly shorten fatigue life, with a 20 mm hole causing a 67% reduction and a 50 mm hole causing a 95% reduction when compared with undamaged plates. Riveted metal patches restored only part of the lost performance, as stress concentrators introduced by fastener holes initiated new fatigue cracks. In contrast, adhesively bonded composite patches provided a substantial improvement, extending fatigue life beyond that of the riveted solutions, improving buckling shape, and delaying crack initiation. Larger patches, particularly those combined with metallic inserts, proved most effective in restoring structural functionality. The findings confirm the effectiveness of bonded composite repairs as a lightweight and reliable method for extending fatigue life and enhancing the safety of damaged aircraft structures. The study highlights the importance of patch geometry and stiffness in the design of repair nodes. Full article

Efficiently separating propene and propane is paramount for the chemical industry but notoriously difficult due to their minimal size and volatility differences. Here, an efficient strategy to overcome this separation challenge was demonstrated through the design of bimetallic zeolitic imidazolate framework (ZIF)-based mixed-matrix membranes (MMMs). Thin-film composite (TFC) membranes were fabricated by integrating monometallic ZIF-8, ZIF-67, and a synergistic bimetallic ZIF-8-67 into a uniquely formulated ionic liquid–cellulose acetate (IL–CA) polymer matrix. Structural and morphological analyses confirmed the high crystallinity of the ZIF fillers and their seamless integration within the polymer. The resultant ZIF-8-67/IL-CA membrane exhibited notable separation performance, surpassing its monometallic counterparts by a threefold increase in both C₃H₆ permeance and C₃H₆/C₃H₈ ideal selectivity relative to the base membrane. Under industrially relevant mixed-gas testing, the membrane achieved a competitive separation factor of eight for propene over propane. These findings reveal that the strategic integration of bimetallic nodes in ZIFs can unlock synergistic properties unattainable with single-metal frameworks. This work presents a robust and scalable platform for developing next-generation membranes that defy conventional performance trade-offs, paving the way for efficient membrane-based olefin/paraffin separations. Full article

Gas sensors are essential in areas such as environmental monitoring, industrial safety, and healthcare, where the accurate detection of hazardous and volatile gases is crucial for ensuring safety and well-being. Metal–organic frameworks (MOFs), which are crystalline porous materials composed of metal nodes and organic linkers, have recently emerged as a versatile platform for gas sensing due to their adjustable porosity, high surface area, and diverse chemical functionality. This review provides a detailed overview of MOF-based gas sensors, beginning with the fundamental sensing mechanisms of physisorption, chemisorption, and charge transfer interactions with gas molecules. We explore design strategies, including functionalization and the use of composites, which improve sensitivity, selectivity, response speed, and durability. Particular attention is given to the influence of MOF morphology, pore size engineering, and framework flexibility on adsorption behavior. Recent developments are showcased across various applications, including the detection of volatile organic compounds (VOCs), greenhouse gases, toxic industrial chemicals, and biomedical markers. Finally, we address practical challenges such as humidity interference, scalability, and integration into portable platforms, while outlining future opportunities for real-world deployment of MOF-based sensors in environmental, industrial, and medical fields. This review highlights the potential of MOFs to transform next-generation gas sensing technology by integrating foundational material design with real-world applications. Full article

The global output of organic solid residues (e.g., crop straw) is substantial, creating an urgent sustainability need for low-impact pathways that avoid open burning or disposal while recovering renewable energy. Dry anaerobic digestion (AD) offers a water-saving, high-solids valorization route for straw-rich substrates, but its deployment is often constrained by acidification that suppresses methanogenesis, reducing reliability and limiting practical adoption. Here, at laboratory scale, we formulated a co-digestion substrate dominated by wheat straw (50%) with swine manure and household organic waste, and evaluated whether co-supplementation of trace metals (Fe, Ni, Co) can enhance process stability and energy recovery, thereby strengthening the sustainability of high-solids straw treatment. System performance was assessed by pH, biogas production, volatile fatty acids (VFAs), functional genes, and microbial community profiles to elucidate micronutrient effects and microbial responses. Micronutrient addition stabilized pH (minimum 6.5) and enhanced biogas output. Specific yields in the supplemented digester were 260.64 ± 11.83 mL g⁻¹ TS and 319.89 ± 14.27 mL g⁻¹ VS, compared with 220.31 ± 9.45 mL g⁻¹ TS and 270.33 ± 11.72 mL g⁻¹ VS in the control; cumulative gas production was higher by 18.33%. Community analyses showed marked enrichment of Methanosarcina, increasing from 7.28% on day 10 to 44.00% on day 30. Molecular ecological network analysis indicated a transition from a sparse, fragmented configuration to a highly connected, centralized one: the number of nodes decreased from 74 to 70; the number of edges increased from 46 to 223 (a 4.85-fold rise); network density increased from 0.0170 to 0.0923; mean degree increased from 1.24 to 6.37; the number of modules declined from 39 to 5; and the proportion of positive versus negative links shifted from 85%/15% to 70%/30%, evidencing stronger interspecies coupling and functional robustness. Consistently, methyl-coenzyme reductase subunit A gene copy numbers were about 1.60-fold higher on day 30 and about 1.51-fold higher on day 50 than in the control. Overall, Fe-Ni-Co co-supplementation enhances methane potential and suppresses acidification in straw-rich dry anaerobic digestion, providing a low-input and practical strategy to stabilize high-solids systems. By improving microbial robustness, this approach enables efficient renewable energy recovery with reduced water demand and lower risk of process failure, thereby supporting scalable straw valorization and advancing circular bioeconomy pathways for agricultural and organic solid residues. Full article

Growing evidence highlights the role of heavy metals in driving the co-selection of an-tibiotic resistance genes (ARGs), and the human oral cavity is an important reservoir of ARGs. This cross-sectional study investigated the effects of heavy metal exposure on human oral microbiota and ARGs, collecting buccal mucosal and blood samples from residents in a heavy metal-contaminated area (Baiyin City) and a non-contaminated area (Yuzhong County, Lanzhou City). The results showed heavy metal exposure is associated with altered alpha and beta diversity of bacteria and ARGs in human oral cavities, with bacterial compositional shifts being the main factor in ARG variation. Metagenomic analysis revealed heavy metal exposure is linked to modifying the interactions in the bacterial community and between ARGs and metal resistance genes (MRGs), shown by simplified topological structures in bacterial and resistome networks, along with enhanced positive correlations among nodes. Neisseria, Haemophilus, Morococcus, Streptococcus, Staphylococcus, and Mycobacteroides as potential hosts for resistance genes in human oral cavity. Furthermore, blood metal quantification revealed distinct associations with resistance patterns. This study demonstrates significant associations between environmental heavy metal exposure and the oral resistome and emphasizes the role of bacterial community composition. Full article

The electrochemical capture and transformation of carbon dioxide (CO₂) (ECC) has recently emerged as a transformative alternative to conventional sorbent-based processes, enabling fully reversible operation under mild conditions and direct compatibility with renewable energy sources. This review focuses on redox-active metal–organic frameworks (MOFs) as electrosorbent materials for the electrochemical capture of CO₂. Rather than encompassing all electrochemical CO₂ capture technologies, we use molecular, polymeric, and COF-based systems as a framework to define what makes a MOF truly “redox-active” for CO₂ electrosorption and how its performance can be assessed. This includes capacitive versus faradic electrosorption mechanisms and design strategies based on the redox chemistry associated with metal nodes, π-conjugated ligands, and strongly redox-active units such as tetrathiafulvalene, viologen, and ferrocene. The way in which defects affect hybrid MOF composites was highlighted, and in situ and operando spectroscopic techniques have improved the understanding of the reaction mechanism in carbon dioxide capture and release under controlled potential. Research comparing carbonaceous materials, redox polymers, and hybrid structures has highlighted both the opportunities and limitations of MOFs, particularly in terms of energy efficiency, scalability, structural robustness, and reproducibility. From a broader perspective, redox-active MOFs occupy a unique position at the intersection of coordination chemistry, electrochemistry, and materials engineering for large-scale applications. In this review, we analyze how redox activity in MOFs—at the metal nodes, ligands, and extended structures—can be harnessed to design energy-efficient, cyclic electrochemical CO₂ capture systems. Furthermore, we propose cross-cutting metrics and design rules that enable meaningful comparisons between materials and device architecture. Full article

Modern on-premises threat detection increasingly relies on deep learning over network and system logs, yet organizations must balance infrastructure and resource constraints with maintainability and performance. We investigate how adopting MLOps influences deployment and runtime behavior of a recurrent-neural-network–based detector for malicious event sequences. Our investigation includes surveying modern open-source platforms to select a suitable candidate, its implementation over a two-node setup with a CPU-centric control server and a GPU worker and performance evaluation for a containerized MLOps-integrated setup vs. bare metal. For evaluation, we use four scenarios that cross the deployment model (bare metal vs. containerized) with two different versions of software stack, using a sizable training corpus and a held-out inference subset representative of operational traffic. For training and inference, we measured execution time, CPU and RAM utilization, and peak GPU memory to find notable patterns or correlations providing insights for organizations adopting the on-premises-first approach. Our findings prove that MLOps can be adopted even in resource-constrained environments without inherent performance penalties; thus, platform choice should be guided by operational concerns (reproducibility, scheduling, tracking), while performance tuning should prioritize pinning and validating the software stack, which has surprisingly large impact on resource utilization and execution process. Our study offers a reproducible blueprint for on-premises cyber-analytics and clarifies where optimization yields the greatest return. Full article

This paper presents a federated learning (FL) architecture tailored for anomaly detection in wire arc additive manufacturing (WAAM) that preserves data privacy while enabling secure and distributed model training across heterogeneous process units. WAAM’s inherent process complexity, characterized by high-dimensional and asynchronous sensor streams, including current, voltage, travel speed, and visual bead profiles, necessitates a decentralized learning paradigm capable of handling non-identical client distributions without raw data pooling. To this end, the proposed framework integrates reversible data hiding in the encrypted domain (RDHE) for the secure embedding of sensor-derived features into weld images, enabling confidential parameter transmission and tamper-evident federation. Each client node employs a domain-specific long short-term memory (LSTM)-based classifier trained on locally curated time-series or vision-derived features, with model updates embedded and transmitted securely to a central aggregator. Three FL strategies, FedAvg, FedProx, and FedPer, are systematically evaluated against four robust aggregation techniques, including KRUM, Multi KRUM, and Trimmed Mean, across 100 communication rounds using eight non-independent and identically distributed (non-IID) WAAM clients. Experimental results reveal that FedPer coupled with Trimmed Mean delivers the optimal configuration, achieving maximum F1-score (0.912), area under the curve (AUC) (0.939), and client-wise generalization stability under both geometric and temporal noise. The proposed approach demonstrates near-lossless RDHE encoding (PSNR > 90 dB) and robust convergence across adversarial conditions. By embedding encrypted intelligence within weld imagery and tailoring FL to WAAM-specific signal variability, this study introduces a scalable, secure, and generalizable framework for process monitoring. These findings establish a baseline for federated anomaly detection in metal additive manufacturing, with implications for deploying privacy-preserving intelligence across smart manufacturing (SM) networks. The federated pipeline is backbone-agnostic. We instantiate LSTM clients because the sequences are short (five steps) and edge compute is limited in WAAM. The same pipeline can host Transformer/TCN encoders for longer horizons without changing the FL or security flow. Full article

Optical sensing technologies are revolutionizing global food safety surveillance through exceptional sensitivity, rapid response, and high portability. This review systematically evaluates five major platforms, revealing unprecedented detection capabilities from sub-picomolar to single-cell resolution. Surface plasmon resonance achieves $0.021 \mathrm{ng}/\mathrm{mL}$ detection limits for veterinary drugs with superior molecular recognition. Quantum dot fluorescence sensors reach $0.17 \mathrm{nM}$ sensitivity for pesticides, enabling rapid on-site screening. Surface-enhanced Raman scattering attains $0.2 \mathrm{pM}$ sensitivity for heavy metals, ideal for trace contaminants. Laser-induced breakdown spectroscopy delivers multi-elemental analysis within seconds at $0.0011 \mathrm{mg}/\mathrm{L}$ detection limits. Colorimetric assays provide cost-effective preliminary screening in resource-limited settings. We propose a stratified detection framework that strategically allocates differentiated sensing technologies across food supply chain nodes, addressing heterogeneous demands while eliminating resource inefficiencies from deploying high-precision instruments for routine screening. Integration of microfluidics, artificial intelligence, and mobile platforms accelerates evolution toward multimodal fusion and decentralized deployment. Despite advances, critical challenges persist: matrix interference, environmental robustness, and standardized protocols. Future breakthroughs require interdisciplinary innovation in materials science, intelligent data processing, and system integration, transforming laboratory prototypes into intelligent early warning networks spanning the entire food supply chain. Full article

Metal–organic frameworks (MOFs) have been increasingly recognized as promising platforms for enzyme modulation, owing to their tunable porosity, high surface area, and versatile chemical functionality. In this review, the potential of MOFs for the inhibition and modulation of protein kinases and phosphatases—key regulators of cellular signaling and disease progression—is examined. The structural fundamentals of MOFs are outlined, followed by a discussion of common synthesis strategies, including solvothermal, microwave-assisted, sonochemical, and mechanochemical methods. Emphasis is placed on how synthesis conditions influence critical features such as particle size, crystallinity, surface chemistry, and functional group accessibility, all of which impact biological performance. Four primary mechanisms of MOF–enzyme interaction are discussed: surface adsorption, active site coordination, catalytic mimicry, and allosteric modulation. Each mechanism is linked to distinct physicochemical parameters, including pore size, surface charge, and metal node identity. Special focus is given to biologically relevant metal centers such as Zr⁴⁺, Ce⁴⁺, Cu²⁺, Fe³⁺, and Ti⁴⁺, which have been shown to contribute to both MOF stability and enzymatic inhibition through Lewis acid or redox-mediated mechanisms. Recent in vitro studies are reviewed, in which MOFs demonstrated selective inhibition of disease-relevant enzymes with minimal cytotoxicity. Despite these advancements, several limitations have been identified, including scalability challenges, limited physiological stability, and potential off-target effects. Strategies such as post-synthetic modification, green synthesis, and biomimetic surface functionalization are being explored to overcome these barriers. Through an integration of materials science, coordination chemistry, and molecular biology, this review aims to provide a comprehensive perspective on the rational design of MOFs for targeted enzyme inhibition in therapeutic contexts. Full article

Perfluorooctanesulfonate (PFOS) is a typical persistent organic pollutant, which presents a significant risk to the ecosystem and human health. Therefore, the development of a highly sensitive and effective detection technique for PFOS has aroused wide concern. In this study, for the mesoporous metal–organic frameworks (MOFs), Cr-MIL-101 were used as the precursor. And the poly(3,4-ethylenedioxythiophene) (PEDOT) using as molecularly imprinted polymers (MIPs) was loaded on Cr-MIL-101 to form a core–shell structure. The obtained Cr-MIL-101@PEDOT/MIP composites integrate the high specific surface area of Cr-MIL-101 and the specific recognition capability of PEDOT/MIP. The glassy carbon electrode (GCE) interface modified by them can specifically adsorb PFOS through electrostatic interactions, coordination by Cr metal nodes, hydrophobic interaction, and hydrogen bonding, etc. The adsorbed PFOS molecules could block the active sites at the electrode interface, causing the current decay of the redox probe. Following the quantitative analysis of peak current decay values using the Langmuir model and the Freundlich–Langmuir model, a wide detection range (0.1–200 nM) and a low detection limit (0.025 nM) were obtained. Characterization techniques including scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET), X-ray photoelectron spectroscopy (XPS), and electrochemical methods were employed to validate the fabrication of the composites. Moreover, Cr-MIL-101@PEDOT/MIP/GCE showed satisfactory stability, repeatability, and selectivity, providing an effective method for the detection of PFOS in practical samples, showing a wide prospective application. Full article

In the post-Moore era, carbon nanotube field-effect transistors (CNTFETs) are a promising alternative to complementary metal-oxide-semiconductor (CMOS) technology at and below the 5 nm node. Compact models bridge circuit design and device physics, yet the electrostatic discharge (ESD) behavior of CNTFETs remains insufficiently captured. Focusing on the local bottom-gate (LBG) CNTFET structure, which offers enhanced gate control due to its bottom-gate configuration, this paper investigates three dominant ESD-triggering mechanisms—thermionic current, tunneling leakage current, and thermal failure breakdown. Then, a hybrid compact–behavioral ESD model for CNTFETs is established. After theoretical derivation and comparison with test results, the model parameters are optimized through fitting. The simulation results exhibit excellent agreement with CNTFET measurements, particularly capturing the Human Body Model (HBM) pre-charge threshold phenomenon at 72 V and accurately predicting the subsequent voltage collapse behavior. This validates the accuracy and effectiveness of the model, laying a theoretical and experimental foundation for further construction of carbon-based standard-cell and I/O libraries. Full article

Due to structural characteristics and connection dimensions, the dynamic characteristics of dual metal rubber clamps (DMRCs) show significant differences in bolt connection direction and opening direction. Accurately identifying the dynamic parameters of DMRC in different directions is of great significance for analyzing the dynamic characteristics and vibration control of aero-engine piping systems. This paper takes a DMRC-double straight pipe structure as the research object and establishes a dynamic model of this structure based on the finite element method as the mechanical parameter identification model of DMRCs. A refined simulation mechanism is adopted in the model to reflect the dynamic characteristics of the DMRC. The DMRC is simplified into four concentrated mass blocks and four spring-damping groups to simulate its mass, stiffness, and damping effects. Each spring-damping group consists of a linear spring, a rotational spring, and a damper. The four groups of springs are further divided into two directional groups to simulate the stiffness and damping effects in the opening direction and bolt connection direction, respectively. Four concentrated mass blocks are applied to the four nodes of the pipe to simulate the mass effect of DMRCs. Based on the dynamic model of the pipeline structure mentioned above, the synchronous identification algorithms and procedures for multiple mechanical parameters of DMRCs are proposed, aiming to minimize the deviation of natural characteristic indicators (natural frequency and peak of frequency response function) obtained through testing and model simulation. This method can synchronously identify linear stiffness, rotational stiffness, and damping in different directions. Finally, the effectiveness of the identification method is verified through experiments. Full article

Efficient allocation of mineral nutrients and photoassimilates is essential for grain development in rice. However, the transcriptional programs governing nutrient transport at key reproductive stages remain largely unresolved. Here, we performed a comprehensive transcriptome analysis of rice (Oryza sativa L.) across spatial (nodes, roots, and five other tissues) and temporal (seven reproductive stages) dimensions to elucidate the molecular basis of nutrient transport and allocation. RNA-seq profiling of node I identified stage-specific gene expression patterns, with the grain filling stage marked by strong induction of transporters involved in mineral allocation (e.g., OsYSL2, OsZIP3, OsSULTR3;3, SPDT) and carbohydrate distribution (e.g., OsSWEET13, OsSWEET14, OsMST6). Comparative analysis with the neck-panicle node (NPN) and root revealed tissue-specific regulatory networks, including nitrate (OsNRT1.1A, OsNRT2.3) and phosphate (OsPHT1;4, OsPHO1;3) transporters enriched at the grain filling stage. Root expression of Cd/As-related transporters (OsNRAMP5, OsCd1, OsLsi1, OsLsi2, OsLsi3) during grain filling highlights the contribution of belowground uptake to grain metal accumulation. Together, our study establishes a spatiotemporal atlas of nutrient transporter gene activity during rice reproductive development and identifies candidate genes regulating upward and lateral nutrient allocation. These findings provide insights into improving nutrient use efficiency and reducing toxic metal accumulation in rice grains through targeted manipulation of nodal and root transport systems. Full article

Excess Cd in soils can be accumulated in rice, presenting a serious human health risk. The effect of foliar transpiration inhibitors (TIs) on the Cd content and the endophytic bacterial community in rice plants was unclear. We evaluated the key part of the rice plant to control the Cd translocation and the profile of the endophytic bacterium structure after spraying with foliar reagents; some possible typical endophytes were induced by the TIs to inhibit the Cd translocation in the rice plant. The rice plants in three sites with different available Cd content were sprayed with foliar TIs. We assessed the Cd, N, P, K and water-soluble saccharide (WSS) in different parts of the rice plant and the endophytic bacteria community in the stem. Foliar application of TIs reduced Cd translocation factor (TF_Cd) by ~20% from the root to the grain compared with that of CK. The TI can increase the adsorptive site concentration of stem nodes from 5.10 to 6.83 mmol/g. The diversity of the endophytic bacteria community was enhanced after application of TI, and the Shannon index increased from 3.29 to 3.92. The endophytic bacterial community induced by TI showed higher potentiality on the biofilm and stress-tolerant and metal-transport functions than that of CK, respectively. The relative abundances of Burkholderiaceae and Bacterium_g_Anaeromyxobacter were significantly negatively correlated (p < 0.05), with TF_Cd and positively correlated (p < 0.05), with water-solution saccharide content, simultaneously. The TI enhanced the endophytic diversity and amount. A high abundance of special endophytic bacteria induced by TI might decrease the TF_Cd. Full article