Search Results (20,307)

Carbonation-induced pH reduction is a key factor triggering steel depassivation and corrosion initiation in reinforced concrete. However, the influence of pore solution chemistry on passive film (PF) stability remains unclear. In this study, ordinary Portland cement simulated pore solution (OPC-SCP) and ferrite-aluminate cement simulated pore solution (FAC-SCP) were used to investigate the evolution of PF formed at pH 12.5 and subsequently exposed to pH 11.0 and 9.5 environments. Electrochemical and microscopic techniques were employed to investigate the degradation behavior of PF under reduced alkalinity. The results show that PF in both systems degraded with decreasing pH, but exhibited markedly different stability. In the OPC-SCP system, the PF resistance decreased slightly from 4.24 × 10⁶ to 2.85 × 10⁵ Ω·cm², indicating that the steel remained in a highly passive state. In contrast, the PF resistance in the FAC-SCP system dropped significantly from 1.13 × 10⁶ to 5.57 × 10³ Ω·cm². AFM and SEM observations further revealed greater surface roughness and more severe local damage in the FAC-SCP system. The superior stability of PF in OPC-SCP may be attributed to the higher Ca²⁺ concentration, which is likely beneficial for the formation of a relatively dense and protective film. Conversely, the higher SO₄²⁻ concentration and lower Ca²⁺ content in FAC-SCP may facilitate defect growth and local dissolution, thereby contributing to depassivation. These findings highlight the critical role of pore solution chemistry in regulating PF stability under reduced alkalinity conditions. Full article

Oxygen-free copper wires are widely required in advanced electronic and electrical systems. However, the relationship between deformation-induced microstructure evolution and property variation during severe cold drawing is not fully understood. In this study, oxygen-free copper rods with a diameter of φ20 mm were fabricated by upward continuous casting, followed by multi-pass cold drawing with deformation degrees up to 99.75%. The microstructure evolution, texture transformation, and property changes during drawing and annealing were systematically investigated. It found that increasing drawing deformation progressively elongated, fragmented, and refined the grains, reducing the average grain size from 339.18 μm to 2.12 μm. Dense dislocation cells, substructures, and nanoscale twins were generated during severe deformation, while the texture gradually evolved from random orientations to preferred <111> and <100> textures. After annealing, fine recrystallized equiaxed grains with abundant annealing twins formed together with recrystallization <101> texture. At 99.75% deformation, the tensile strength reached 486 MPa, with an electrical conductivity of 96.7% IACS (International Annealed Copper Standard). After annealing, the electrical conductivity recovered to 101.5% IACS, while the tensile strength decreased to 187 MPa. This work establishes the relationship between severe deformation microstructure evolution and property response in oxygen-free copper, providing guidance for the fabrication of high-strength and high-conductivity copper conductors. Full article

This review covers literature published up to June 2026. Detecting various water pollutants quickly and reliably remains a challenge. Boron-doped diamond (BDD) electrodes, particularly when fabricated as nanostructured thin films such as nanocones or nanowalls, offer a wide electrochemical window, low background current, and excellent chemical stability, making them promising tools for electrochemical sensing. However, unmodified BDD electrodes face an inherent trade-off among conductivity, active site density, and interfacial stability, a phenomenon termed herein the “sensitivity-selectivity-stability triangle bottleneck”, which severely limits practical performance. In this review, we demonstrate how multi-scale structural regulation can circumvent this bottleneck. Specifically, a triple strategy comprising boron doping, surface modification, and post-annealing treatment is proposed and evaluated. First, the effect of boron doping level on conductivity and active site density is discussed. Second, two common surface modification approaches are examined: carbon nanomaterials (which increase surface area and form conductive networks) and metal nanoparticles (which enhance catalytic activity and interfacial charge transfer). Third, post-annealing is highlighted as a key synergistic step that locks the modified layer and stabilizes the interface. Together, these three components form an integrated framework. To provide concrete guidance, the performance of each strategy is compared for representative water pollutants, including heavy metal ions, phenolic compounds, and emerging contaminants such as antibiotics and pesticides, with emphasis on sensitivity, selectivity, and stability. Representative detection limits achieved include 0.01 μg/L for Pb²⁺, 5 nM for acetaminophen, and 0.32 fM for PCB-77, demonstrating the effectiveness of the triple structural regulation strategy. Finally, in line with the theme of this Nanomaterials Special Issue on nanostructured thin films, current challenges in structural regulation are summarized, and future directions, including multi-parameter optimization, AI-assisted high-throughput screening, and real-world testing, are outlined. The goal is to offer practical structure-performance guidelines for designing BDD-based electrochemical sensors that are both high-performing and durable. Full article

The Vehicle Routing Problem with Time Windows (VRPTW) takes on a structurally distinct form when the goods being routed undergo first-order quality decay during transport. In this setting, distance minimisation alone underestimates the true economic cost. A per-customer minimum-quality acceptance constraint further introduces a non-linear feasibility condition that does not appear in the classical formulation. This paper addresses such a setting in the context of loose-skin citrus fruit (e.g., mandarins) distribution, where stock has already undergone several days of cold storage at the origin warehouse, and remaining shelf life makes retail time windows binding rather than decorative. We formulate a Maturity-Aware Multi-Echelon Dynamic Reallocation Vehicle Routing Problem with Time Windows (MA-MEDR-VRPTW) on a three-echelon network (origin warehouse → distribution centres → stores) over a seven-day rolling horizon. A first contribution shows that the minimum-quality acceptance constraint admits an analytic transformation into a time-window tightening, which removes per-extension exponential evaluations from the subproblem solver. The algorithmic contribution is a proximal alternating direction method of multipliers (ADMM) with NG-route relaxation (padmm-ma) whose quality-loss weight is updated by a residual-balancing rule and is decoupled from the outer reallocation linear program (LP) through approximate dynamic-programming-style marginal costs. On twelve Solomon-derived mandarin instances (72 feasible algorithm–instance combinations), padmm-ma returns a mean seven-day cost of 12,638 CNY against 11,753 CNY for a subgradient baseline ($+7.5\%$) at statistically indistinguishable arrival quality (paired Wilcoxon $p=0.077$ for ${\overline{q}}_{\mathrm{arr}}$), while cutting mean wall-clock time from 350 to 23 seconds (about $15\times$). The method, therefore, reads as a fast operational heuristic for daily re-planning. An ablation, an exact-MIP benchmark on tractable subproblems, and a scale extension to $n=100$ customers round out the validation. Full article

Carbon nanotube (CNT) films prepared via floating catalyst chemical vapor deposition generally suffer from residual iron impurities, structural defects, and weak inter-tube interfaces, which severely limit their mechanical performance. Here, we propose a post-treatment approach, which is dominated by Joule heating, to substantially improve the mechanical properties of CNT films. Acid washing after Joule heating effectively removes iron catalyst and amorphous carbon, increasing the specific strength from 0.64 N/tex to 2.96 N/tex. Pre-stretching induces alignment of the CNTs along the stretching direction, further raising the specific strength to 5.57 N/tex. Subsequent Joule heating not only raises graphitization degree and repairs lattice defects but also transforms the weak van der Waals contacts between tubes into continuous carbon networks, leading to network densification and locking of the aligned structure. The final specific strength reaches 7.04 N/tex and true tensile strength 8.05 GPa, surpassing previous representative carbon materials. The purification mechanism of Joule heating depends on the initial iron content of the film: for high-iron films, iron melts, migrates and forms Fe/Fe₃C@C core–shell particles, which can be converted into hollow carbon shells via acid etching; for low-iron films, iron is removed via atomic diffusion and evaporation. This work provides a fast, controllable and synergistic technical route for the preparation of high-performance CNT macrostructures. Full article

Introduction: Biallelic pathogenic variants in DNAJC30 cause an autosomal recessive form of Leber hereditary optic neuropathy (LHONAR1), traditionally considered a mitochondrially transmitted disorder. The phenotypic spectrum of diseases linked to DNAJC30 includes isolated optic neuropathy, Leigh syndrome spectrum (LSS), and atypical LHON-plus. Case description: Here, we report a 13-year-old boy presenting symptoms of area postrema syndrome (APS), with recurrent vomiting, vertigo, nystagmus, and subacute visual deterioration with central scotoma. Ophthalmological examination revealed bilateral papilledema with telangiectatic vessels, while visual evoked potentials demonstrated severe bilateral optic pathway dysfunction. Brain magnetic resonance imaging (MRI) showed T2/FLAIR hyperintense lesions involving the area postrema and enhancement of the optic nerves, strongly suggesting seronegative neuromyelitis optica spectrum disorder (NMOSD). Extensive immunological and cerebrospinal fluid studies, including anti-aquaporin-4 (AQP4) and anti-MOG antibodies, were negative. High-dose corticosteroids and intravenous immunoglobulins resulted in only transient and incomplete improvement, followed by further visual decline. Additionally, laboratory tests detected elevated lactate plasma levels. Hence, whole-exome sequencing was performed, which identified a homozygous pathogenic DNAJC30 c.152A>G, p.(Tyr51Cys) variant, associated with LHONAR1. After initiation of idebenone therapy, the patient showed significant improvement in visual function, normalization of lactate levels, and complete resolution of the brainstem lesions on follow-up MRI. Conclusions: This case further expands the neuro-ophthalmic spectrum associated with DNAJC30 variants and suggests that DNAJC30-related disease may closely mimic seronegative NMOSD. We highlight that early genetic diagnosis is essential, as recognition of this mitochondrial etiology enables targeted therapy and may substantially improve clinical outcomes. Full article

The increasing demand for seafood over the years has led to an increase in by-products produced by the seafood processing sector. These by-products, which can represent up to 70% of processed products, are rich in nutrients and bioactive compounds, allowing them to be used in several sectors, such as food, packaging, cosmetics and pharmaceutics, provided that recovery occurs in an eco-friendly manner. In the present work, two lactic acid bacteria (Lactobacillus lactis and L. brevis) and the yeast Yarrowia lipolytica, which are organisms capable of producing organic acids and proteases during the fermentation process, were used separately to extract chitin from deep-water shrimp (Aristeus antennatus) by-products. The results showed that L. lactis was the most effective microorganism in removing both the mineral and protein fractions; therefore, it was chosen to optimize the chitin extraction technique, after which chitin was eventually converted into chitosan. The obtained chitosan showed a deacetylation degree (DDA%) of 82%, indicating good film-forming capacity. The developed biological technique allowed the valorization of shrimp by-products by recovering chitin and eventually chitosan, allowing us to produce biofilms that could help prolong seafood shelf life and, from a circular economy point of view, contributing further to promoting the sustainability of the production sector. Full article

Sample preparation is frequently a time-consuming process and can be a major bottleneck in many analytical techniques that involve some form of modification to a sample so that it can be analyzed without interference or to increase its sensitivity. As part of the movement towards “green analytical chemistry”, the reduction in organic solvent usage and toxicity via alternative solvents compared to those traditionally used in analytical chemistry has gained increasing interest. Although ionic liquids were thought to have limitations, deep eutectic solvents (DESs) are being looked at as alternatives to traditional organic solvents in analytical chemistry because of their ability to produce a “tunable” set of physico-chemical properties that enable the selective and efficient extraction of a wide variety of analytes from a very diverse array of matrices. Although deep eutectic solvents have attracted increasing attention in analytical extraction applications, a systematic comparison of their performance across various extraction techniques is still lacking. This review fills this gap by offering a comprehensive and integrated evaluation of DES-based extraction approaches, emphasizing the interdependence between solvent characteristics, extraction efficiency, selectivity, and sustainability. The insights presented herein are intended to support the rational selection of appropriate DES-based extraction strategies for diverse analytical purposes. Moreover, these findings are expected to contribute to the advancement of greener, more efficient sample preparation methodologies within the field of green analytical chemistry. In this review article, we describe several analytical chemistry techniques that utilize DESs, such as dispersive liquid–liquid microextraction, solid-phase extraction, ultrasound-assisted extraction, etc., and explain the basic principles and mechanisms behind each technique. Additionally, comparative evaluations are provided to identify the relative advantages and disadvantages of the techniques mentioned above in terms of extraction efficiency and selectivity, and speculation regarding future trends and challenges in DES-based extraction systems will also be included. By integrating recent advances and comparative performance assessments, this review serves as a reference for researchers and industry practitioners, fostering innovation and promoting the wider adoption of sustainable extraction technologies. Full article

Galloping of iced transmission lines under complex microclimates poses a severe threat to power grid security, whereas traditional full-span de-icing strategies suffer from excessive energy redundancy and limited spatial precision. To address the spatial uncertainty of actual ice accretion, a three-dimensional nonlinear aeroelastic finite element model is established by considering geometric nonlinearity and eccentric ice-induced added stiffness. A state-space Monte Carlo framework is then used to evaluate the galloping probability under different wind speed regimes and spatially non-uniform ice distributions. The results reveal a distinct non-monotonic instability characteristic: the galloping probability decreases to 33.0% at 8.0 m/s, forming a clear probability trough and indicating an aerodynamic self-stabilization effect associated with the shift in the baseline effective angle of attack. To map spatial ice heterogeneity to global dynamic instability, a galloping sensitivity index (GSI) based on the Spearman rank correlation coefficient is proposed to identify the dominant sensitive sections responsible for inducing galloping-prone responses. Based on this index, a GSI-guided targeted ultrasonic de-icing decision strategy is constructed. Under the assumption of identical rated power for each section, the proposed strategy activates only 40% of the physical sections and reduces the number of activated sections, as well as the associated operational energy demand, by 60% compared with the full-span de-icing strategy. This framework provides a quantitative basis for linking stochastic ice distribution, galloping probability evaluation, and energy-efficient targeted de-icing decisions. Full article

The Macaronesian archipelagos host exceptionally well-preserved coastal sedimentary deposits formed during the warmest period of the Last Interglacial episode, the Marine Isotope Substage 5e (MIS 5e). Numerous MIS 5e fossiliferous outcrops occur, scattered across several islands of the Canary Archipelago. Among these is San Juanito, a small outcrop located in the eastern sector of Punta del Hidalgo (northeast Tenerife Island), where MIS 5e sediments are distributed over an area of approximately 480 m². A multidisciplinary study was conducted, aiming to: (i) determine the age of the fossiliferous sediments; (ii) define the stratigraphic relationships between the sedimentary deposit and the underlying/overlying volcanic sequences; (iii) assess the taxonomic richness and the functional palaeobiodiversity of this palaeosite; and (iv) provide a comprehensive palaeoecological reconstruction of the MIS 5e environment. Based on two key ecostratigraphic indicator species for the Canarian MIS 5e, the San Juanito sequence is here assigned to the Last Interglacial. Qualitative sampling yielded forty mollusc taxa, including three gastropods that represent new records—Alvania johannae Moolenbeek & Hoenselaar, 1998, Krachia tiara (Monterosato, 1874), and Barleeia unifasciata (Montagu, 1803)—bringing the current MIS 5e checklist for the Canary Islands to 202 gastropods and 80 bivalves. The highly cemented matrix of the San Juanito deposits prevented the collection of standardized 1 kg bulk sediment samples. Nevertheless, we strongly recommend adopting this quantitative approach in future studies of suitable MIS 5e outcrops across the archipelago. The faunal assemblage indicates that the San Juanito region was dominated by rocky shores during the MIS 5e, much like today. This paleoenvironmental reconstruction is based on the high frequency of species associated with hard substrates—including echinoids, vermetids, fissurellids, and patellids—and the overwhelming dominance (95%) of epifaunal gastropods. Full article

Physalis peruviana L. is an Andean crop of high nutritional and commercial value; however, the limited availability of uniform planting material restricts its large-scale propagation. Indole-3-butyric acid (IBA) is widely used to promote adventitious rooting, although its concentration and application methods influence the response observed throughout the different stages of root development. This study evaluated how IBA concentration and explant origin influenced rooting-related traits and early vegetative growth of in vitro-regenerated P. peruviana shoots during a 30-day ex vitro acclimatization phase. The evaluated variables included rooting percentage, root number, longest root length, root fresh and dry mass, shoot length, leaf and node number, stem diameter, shoot fresh and dry mass, leaf area, and photosynthetic pigment contents. The experiment followed a completely randomized design with a 2 × 4 factorial arrangement consisting of two explant origins (cotyledon and hypocotyl) and four IBA concentrations (0, 400, 800, and 1600 mg L⁻¹), with five biological replicates per treatment combination. All shoots formed at least one visible root, resulting in 100% rooting across all treatment combinations. IBA concentration significantly affected root fresh and dry mass and several shoot-growth traits, whereas root number and longest root length were not significantly affected. Among the concentrations tested, 800 mg L⁻¹ produced the highest root biomass and favorable responses in selected shoot-growth traits, whereas 1600 mg L⁻¹ was associated with lower values for some growth variables. Hypocotyl-derived shoots had more leaves and nodes, greater stem diameter, and higher shoot dry mass than cotyledon-derived shoots. These results indicate a concentration- and trait-dependent response to IBA and identify 800 mg L⁻¹ as the most favorable concentration among those tested for increasing root biomass and selected shoot-growth traits under the evaluated acclimatization conditions. Full article

In the present work, we propose a simple analytical algorithm for unobscured two-mirror telescope designs. It is based on fitting of the closest aberration-free surface for each field position and allows for computation of the wave aberration distribution over a large aperture. All the equations necessary for the algorithm implementation are expressed in a general form allowing its application for complex freeform mirrors. It is shown using the example of a small telescope with $f^{\prime }=245$ mm, $F/\#=7$ and $2^{\circ }\times 0.{96}^{\circ }$ field of view, that the algorithm allows us to find a good starting point, and reach a high spatial resolution in comparison with off-axis Ritchey–Chrétien and Schiefspiegler telescopes. The algorithm can be of a specific interest for the development of highly specialized imaging systems of several types. Full article

Reinforced concrete frame structures (RCFSs) subjected to strong seismic excitation may enter a metastable semi-ruin state before global collapse, characterized by severe local damage, degraded stability, and high secondary collapse risk. However, systematic experimental investigations and quantitative identification techniques for this critical transitional state are still lacking in existing seismic engineering literature, forming a notable research gap for post-earthquake safety evaluation. To investigate this critical transition, a Digital Image Correlation (DIC)-assisted shaking table test was conducted on a 1/25-scale RCFS specimen derived from an earthquake-damaged exterior-corridor teaching building, using the Wolong ground motion recorded during the 2008 Wenchuan earthquake as input. DIC was employed to track the full-field evolution of cracking, through-crack development, and concrete cover spalling under incremental seismic loading. Four local damage indices—crack line density (CLD), crack propagation rate (CPR), through-crack ratio (TCR), and concrete spalling ratio (CSR)—were extracted and evaluated with the inter-story drift ratio (IDR) to quantify local-to-global degradation. The results show that visible cracks initiated at PGA = 0.3 g, while accelerated crack propagation occurred at 0.7–0.8 g, with CPR peaks of 1187.5 and 1140 mm/g, respectively. At 0.5–1.0 g, the crack number increased from 13 to 26, total crack length reached 0.443 m, CLD increased to 3.9 × 10⁻⁴, and TCR reached 37.04%. At 1.1–1.5 g, crack development approached saturation, with total crack length of 0.552 m, maximum TCR of 63.6%, and CLD of 4.8 × 10⁻⁴. Under ultimate excitation of 1.6–1.8 g, the crack number stabilized at 33–34, TCR remained around 63%, cumulative spalling area reached 1026 mm², CSR reached 0.015, and the third-floor IDR approached the 1/50 elastoplastic limit. Severe through-cracking, reinforcement exposure, concrete spalling, and residual inclination indicated the onset of the semi-ruin state. The proposed multi-index framework provides quantitative support for semi-ruin-state identification and post-earthquake secondary collapse risk assessment of RCFSs. Full article

Accurate detection of plant leaf diseases is essential for enhancing crop productivity and supporting global food security. In addition to disease classification, understanding how environmental and soil conditions affect model performance is important for developing robust real-world agricultural monitoring systems. Although deep learning (DL) models achieve high accuracy on benchmark datasets, their performance in real-world settings is often limited by variations in illumination, background complexity, and environmental conditions. This study proposes a smart DL framework for detecting and classifying multiple leaf diseases in tomato, potato, and pepper plants. The framework combines U²-Net-based leaf segmentation with a Convolutional Neural Network–Bidirectional Gated Recurrent Unit (CNN–Bi-GRU) architecture. MobileNetV2 is employed as the feature extraction backbone to capture spatial characteristics, while Bi-GRU layers model sequential feature dependencies, forming a spatio-temporal network whose architectural design prioritizes parameter efficiency through depthwise separable convolutions and reduced gating complexity. The model was trained and validated using the PlantVillage benchmark dataset and achieved a classification accuracy of 99.8% with a macro-averaged F1-score of 94%, outperforming several state-of-the-art architectures. To assess robustness under real-world conditions, the trained model was further tested on leaf images collected from open-field environments near Eluru, South India. The field evaluation revealed a reduction in classification accuracy to 61.97%, indicating the impact of domain shift and environmental variability. To investigate potential contributing factors, soil parameters, including pH, temperature, moisture, and NPK levels, were monitored using an IoT-based Arduino sensing system over ten consecutive days. Rather than serving as direct inputs to the disease classification model, these environmental measurements were analyzed to assess their potential influence on disease symptom expression and the observed reduction in model performance under field conditions. The results suggest that environmental conditions may influence disease symptom expression and model transferability. This study highlights the importance of integrating DL-based disease recognition with environmental monitoring for reliable field-level agricultural applications. Nevertheless, computational complexity metrics, including inference latency and memory footprint, were not evaluated in the present work and are identified as a priority for future edge deployment studies. Full article

Interpretable feature-group fusion for tabular regression remains challenging because strong predictive models often lack explicit group-level attribution, complexity control, and attribution-stability guarantees. This paper proposes SHAP-Weighted Feature Fusion with Residual Mixing (SWFF-R), a closed-form convex fusion framework that combines a full-feature predictor with a SHAP-weighted blend of group-specific expert models. Group weights are obtained from temperature-controlled softmax transformations of group-level TreeSHAP importances, and the residual mixing coefficient is selected on a validation set to preserve predictive robustness. To avoid terminological confusion, we stress that these weights are derived from aggregated TreeSHAP importance scores of the full-feature model, not from group-level Shapley values recomputed by treating each feature group as a single player; the construction is therefore best described as TreeSHAP-importance-weighted feature-group fusion. Under fixed fusion weights and explicit centering, the proposed attribution satisfies Shapley-consistency properties for the induced centered additive group decomposition. We derive a Rademacher complexity upper bound for SWFF-R, provide a complementary minimax lower-bound calculation on a simplified linear subclass, and establish guarantees for temperature search and fixed-coefficient Lipschitz stability. Experiments on seven real-world tabular regression datasets and a separate synthetic 500K scalability stress test show that SWFF-R preserves predictive performance, yields point-estimate RMSE improvements on several datasets, and provides stable group-level attribution. Overall, SWFF-R offers a theoretically grounded framework for interpretable feature-group fusion in tabular regression. Full article