Search Results (253)

Polymer–ceramic hybrid composites are emerging as attractive candidates for lightweight, corrosion-resistant absorber components in solar thermal collectors; however, their adoption is constrained by the intrinsically low thermal conductivity of polymers, processing-induced anisotropic heat transport, interfacial thermal resistance at tube/laminate joints, and durability challenges under outdoor exposure. This review provides a collector-centered synthesis of polymer–ceramic hybrid materials, emphasizing the translation of composite properties into collector-level outcomes rather than conductivity enhancement alone. A structure–property–performance mapping approach is presented to connect directional thermal conductivity ((k_in-plane), (k_perp)), thermal diffusivity, heat capacity, coefficient of thermal expansion, and service temperature with collector performance parameters such as heat removal effectiveness, overall heat losses, and stagnation behavior. Ceramic fillers (e.g., boron nitride, aluminum nitride, silicon carbide, alumina) are examined for stable conduction-network formation, coating compatibility, and long-term reliability, while carbon fillers (graphite, graphene nanoplatelets, carbon nanotubes) are evaluated for combined heat spreading and solar absorption benefits, with attention to emissivity penalties. Hybrid ceramic–carbon architectures and multilayer absorber designs are identified as the most promising routes to balance thermal transport, optical selectivity (high solar absorptance and low thermal emittance), manufacturability, and durability under UV, humidity, and thermal cycling. Full article

Plant diseases pose significant threats globally due to the high economic losses and effects on food security. Traditional disease identification methods usually have limitations regarding their accuracy and efficiency. This study discusses six advanced deep learning models: VGG19, DenseNet201, Xception, InceptionResNetV2, MobileNetV2, and EfficientNetV2B3. A dataset is used that is rich in diversity and contains high-quality images of diseased sections or parts of plants. These deep models are discussed and compared for studying their efficiencies in recognizing plant diseases accurately. EfficientNetV2B3 and Xception outperformed the rest of the models due to the ability of the model to capture major features from the image of the infected region. MobileNetV2 was also useful which provided a good trade-off between accuracy and computational efficiency. The study further applied transfer learning and image augmentation in boosting model performance and addressing the issue of class imbalance in the dataset. Results showed that the proposed approach proved much more reliable and efficient compared to conventional approaches to plant disease detection. Future efforts will be geared towards early detection of diseases to further assist farmers and researchers in order to upgrade the practices related to crop management. Additional data will be integrated, including hyperspectral images and environmental factors, for developing a robust and efficient system for plant disease detection. These models will be deployed in intelligent farming systems. Full article

Chronic myeloid leukemia (CML) has undergone a significant shift over the past two decades, transitioning from a fatal malignancy to a chronic, highly manageable disease with near-normal life expectancy for most patients. This transformation has been driven by the development of BCR-ABL1-targeted tyrosine kinase inhibitors (TKIs), which have enabled durable disease control and deep molecular responses (DMRs) in the majority of patients with chronic-phase CML. As long-term survival outcomes have plateaued across available agents, contemporary management has shifted beyond disease suppression toward optimizing long-term safety, quality of life, and the achievement of treatment-free remission (TFR). This review summarizes current evidence on molecular monitoring strategies, the comparative efficacy and toxicity profiles of first-, second-, and third-generation TKIs, and emerging advances in response assessment. Patient-centered TKI selection is discussed in the context of cardiovascular risk, comorbidities, treatment tolerability, and survivorship goals, reflecting the growing emphasis on individualized therapy in chronic-phase CML. Molecular monitoring strategies are examined in parallel, highlighting the clinical importance of early and sustained DMRs in guiding therapeutic decisions and TFR eligibility. Although RT-qPCR remains the standard for molecular monitoring, emerging high-sensitivity techniques such as digital droplet PCR and next-generation sequencing provide complementary value by improving the detection of low-level residual disease, refining risk stratification, and enabling earlier identification of resistance. Emerging therapeutic strategies and advances in response assessment further highlight ongoing efforts to enhance the depth and durability of remission while minimizing long-term toxicity. These developments support a more precise, individualized, and outcome-driven approach to modern CML management. Full article

ADP-ribosylation of nucleic acids is a modification found in both eukaryotes and bacteria, where it contributes to genome maintenance but can also serve as a toxic mechanism used by bacterial toxins to disrupt essential cellular processes. This modification is catalysed by ADP-ribosyltransferases and can be reversed by antagonistic ADP-ribosylgylcohydrolase enzymes. To date, ADP-ribosylation of nucleic acid bases has been described only for adenosine, guanosine, and thymidine. Here we report the ADP-ribosylation of cytidine, catalysed by members of the pierisin family of bacterial toxins—ScARP (SCO5461) and Scabin. We also show that ADP-ribosylation of cytidine is reversible through removal by certain NADAR family proteins, including NADAR proteins from the bacterium Streptomyces coelicolor (SCO5665) and the sponge Amphimedon queenslandica, as well as YbiA-type NADAR proteins. The conservation of cytidine de-ADP-ribosylating activity of NADAR proteins across phylogenetically distant species suggests that this modification may have important physiological significance. Full article

Diabetes mellitus (DM) is a chronic metabolic disorder associated with hyperglycemia, oxidative stress, and dyslipidemia, leading to severe complications. Medicinal plants like Jatropha integerrima, known for their antioxidant and therapeutic properties, are being explored as potential alternatives for the management of diabetes. The present study aimed to evaluate the antidiabetic, antihyperlipidemic, and antioxidant effects of the methanolic extract of Jatropha integerrima (MEJI) in streptozotocin (STZ)-induced diabetic rats. Diabetes was induced in Wistar rats using STZ (45 mg/kg, i.p.), followed by oral treatment with MEJI (200 and 400 mg/kg) or metformin (200 mg/kg) for 21 days. Glycemic control was assessed through fasting blood glucose level (FBG), and the oral glucose tolerance test (OGTT), lipid profiling (TC, TG, LDL, HDL, and VLDL), and antioxidant (SOD and CAT) testing were outsourced to UNIQUE Biodiagnostics Vet. Path Lab, Parel, Maharashtra, while pancreatic histopathology was analyzed by evaluating islet morphology. Treatment with MEJI produced a dose-dependent reduction in fasting blood glucose levels. On day 21, MEJI at 200 and 400 mg/kg reduced blood glucose by 63.1% and 67.0%, respectively, compared to the diabetic control group. The standard drug showed the highest reduction (73.6%), restoring glucose levels close to normal values, compared with the diabetic control group, along with an improvement in glucose tolerance as reflected in OGTT outcomes. Moreover, the extract also favorably modulated the lipid profile by lowering TC, TG, LDL, and VLDL levels while enhancing HDL concentrations. Antioxidant enzyme activities improved notably, with significant elevations in SOD and CAT levels, indicating attenuation of oxidative stress. Furthermore, the histopathological examination of pancreatic sections revealed partial recovery of islet architecture in MEJI-treated rats, suggesting regenerative and protective effects on pancreatic β-cells. MEJI exhibited potent glucose-lowering, lipid-regulating, and antioxidant properties, along with pancreatic protection. These findings suggest that Jatropha integerrima may serve as a reservoir of bioactive compounds with promising potential for the management of diabetes. Full article

Polymer composites reinforced with nanofillers, synthetic fibers, and inorganic fillers have progressed rapidly, yet recent advances remain fragmented across filler-specific studies and often lack unified mechanistic interpretation. This review addresses this gap by presenting an interphase-centric, mechanism-driven framework linking processing routes, dispersion and functionalization requirements, interphase formation, and the resulting structure–property relationships. Representative quantitative datasets and mechanistic schematics are integrated to rationalize nonlinear mechanical reinforcement, percolation-controlled electrical/thermal transport, and thermal stabilization and barrier effects across major filler families. The review highlights how reinforcement efficiency is governed primarily by interfacial adhesion, filler connectivity, and processing-induced microstructural evolution rather than filler loading alone. Key challenges limiting scalability are critically discussed, including dispersion reproducibility, viscosity and processability constraints, interphase durability, and recycling compatibility. Finally, mechanism-based design rules and future outlook directions are provided to guide the development of high-performance, multifunctional, and sustainability-oriented polymer composite systems. Full article

In aerospace, defense, and energy systems, ceramic matrix composites (CMCs) are smart structural materials designed to function continuously in harsh mechanical, thermal, and oxidative conditions. Using high-strength fiber reinforcements and tailored interphases that enable damage-tolerant behavior, their creation tackles the intrinsic brittleness and low fracture toughness of monolithic ceramics. With a focus on chemical vapor infiltration, polymer infiltration and pyrolysis, melt infiltration, and additive manufacturing, this paper critically analyzes current developments in microstructural design, processing technologies, and interfacial engineering. Toughening mechanisms are examined in connection to multiscale mechanical responses, including controlled debonding, fiber bridging, fracture deflection, and energy dissipation pathways. Cutting-edge environmental barrier coatings are assessed alongside environmental durability issues like oxidation, volatilization, and hot corrosion. High-performance braking, nuclear systems, hypersonic vehicles, and turbine propulsion are evaluated as emerging uses. Future directions emphasize self-healing systems, ultra-high-temperature design, and environmentally friendly production methods. Full article

Self-healing polymer nanocomposites are increasingly investigated as damage-tolerant materials for structural and functional applications; however, their engineering translation remains limited by the difficulty of achieving high mechanical reinforcement while retaining sufficient polymer mobility for effective repair. Previous reviews have largely summarized healing chemistries or nanofiller classes but have rarely established quantitative structure–property–healing relationships or resolved contradictory trends reported across studies. In this review, we develop an integrated framework that links polymer network architecture, nanofiller geometry/percolation behavior, and interfacial dynamics to healing kinetics, and we compile quantitative design windows for nanofiller loading, percolation thresholds, activation conditions, and durability metrics. The synthesis reveals that healing performance is maximized within intermediate filler contents near the percolation regime, whereas excessive nanofiller loading commonly suppresses healing by nanoscale confinement and interphase immobilization despite improving modulus and conductivity. Finally, we propose application-oriented design rules and benchmarking priorities, emphasizing standardized fracture/fatigue-based evaluation, multi-cycle healing retention, and scalable interphase engineering as the key pathways for translating self-healing nanocomposites from laboratory demonstrations to validated engineering systems. Full article

Friction Stir Processing (FSP) has emerged as an advanced solid-state surface engineering technique for tailoring high-performance surface architectures in metal matrix composites (MMCs). By combining localized thermo-mechanical deformation with controlled material flow, FSP enables grain refinement, homogeneous dispersion of reinforcement, and strong interfacial bonding without melting or altering bulk properties. This review critically examines the role of FSP in enhancing the mechanical, tribological, and corrosion performance of composites, with emphasis on process–structure–property relationships. Key strengthening mechanisms, including grain boundary strengthening, load transfer, particle pinning, and defect elimination, are systematically discussed, along with their implications for wear resistance, fatigue life, and durability. Special attention is given to corrosion and tribo-corrosion behavior, highlighting electrochemical mechanisms such as micro-galvanic interactions, passive film stability, and interfacial chemistry. Furthermore, the eco-efficiency, industrial viability, and sustainability advantages of FSP are evaluated in comparison with conventional surface modification techniques. The review concludes by identifying critical challenges and outlining future research directions for the scalable, multifunctional, and sustainable design of composite surfaces. Full article

Carbon nanotube (CNT) and graphene-reinforced nanocomposites have become exceptional multifunctional materials because of their exceptional mechanical, thermal, and electrical properties. Recent developments in synthesis methods, dispersion strategies, and interfacial engineering have effectively overcome agglomeration-related limitations by significantly improving filler distribution, matrix compatibility, and load-transfer efficiency. These nanocomposites have better wear durability, corrosion resistance, and surface properties like super-hydrophobicity. A comparative analysis of polymer, metal, and ceramic matrices finds benefits for applications in biomedical, construction, energy, defense, and aeronautics. Functionally graded architecture, energy-harvesting nanogenerators, and additive manufacturing are some of the new fabrication processes that enhance design flexibility and functional integration. In recent years, scalability, life-cycle evaluation, and environmentally friendly processing have all gained increased attention. The development of next-generation, high-performance graphene and carbon nanotube (CNT)-based nanocomposites is critically reviewed in this work, along with significant obstacles and potential next steps. Full article

This research examines the Lyapunov-based criterion for global asymptotic stability of Bidirectional Associative Memory (BAM) neural networks that have mixed-interval time-varying delays. Using a second-order reciprocally convex approach, this paper introduces a novel stability criterion for BAM neural networks with time delays. The literature has recently incorporated a few triple integral expressions in the Lyapunov–Krasovskii functional to lessen conservatism in the analysis of system stability with interval time-varying delays using a second-order reciprocally convex combination strategy. This research work establishes the negative definiteness of the Lyapunov–Krasovskii functional derivative and is formulated using Linear Matrix Inequalities (LMIs). The effectiveness of the proposed result is demonstrated through numerical examples. Full article

Travel-time delays due to recurring congestion cause productivity loss, increase the likelihood of accidents, and lead to environmental pollution due to greenhouse gas emissions. The National Highway Traffic Safety Administration in the United States has listed several driver assistance technologies that are now common in most newer vehicles. While these technologies can help reduce the likelihood of traffic-related accidents, they do little to reduce recurring congestion in urban areas. Recurring congestion during rush hours is prevalent, for example, along Interstate 95 and Capital Beltway 495 in the Baltimore-Washington area. Such congestion also enhances the likelihood of crashes. Previous approaches to hotspot identification are primarily theoretical, which limits their practical applicability. In this paper, we develop a Machine Learning (ML) approach that integrates geospatial data with artificial neural networks to predict traffic congestion hotspots during rush hour. The approach uses live traffic sensor data. A case study from Maryland is presented. The result shows top hotspot segments across Maryland. Using a snapshot of hotspots at eight different time periods, the likelihood of hotspot locations is predicted using an artificial neural network. The framework is validated using live loop detector data (speed and volume) from Maryland freeways, particularly I-495 and I-95. The research can serve as a valuable tool for traffic congestion hotspot identification and travel-time prediction. Full article

Chronic wounds present a major clinical challenge, often aggravated by infection and rising antimicrobial resistance. This study investigated the wound-healing efficacy of Lobelia alsinoides Lam., an ethnomedicinal herb, formulated as a topical ointment containing its ethanolic extract (LT). Phytochemical profiling identified high levels of phenolics, terpenoids, and tannins, while in vitro assays demonstrated strong antioxidant, broad-spectrum antimicrobial, and cytocompatible properties. Wound-healing potential was evaluated using excision and incision wound models in rats treated with 5% or 10% LT ointments, with Silverex™ as the reference standard. The 10% LT formulation significantly outperformed Silverex™, accelerating wound contraction (99.33 ± 0.55% by Day 16), shortening epithelialization time (16.1 ± 0.8 days), and enhancing tensile strength (837.36 ± 16.37 g; p < 0.001). Biochemical and histological analyses confirmed improved collagen deposition, extracellular matrix remodeling, and angiogenesis, without hepatic or renal toxicity. Overall, LT exhibited statistically superior wound-healing efficacy compared with Silverex™, supporting its potential as a safe, affordable, and sustainable phytotherapeutic alternative. These findings provide strong scientific validation for L. alsinoides as an evidence-based herbal candidate for integration into modern wound care, with future studies warranted to establish mechanistic and clinical efficacy in chronic and infected wounds. Full article