Search Results (3,638)

Dengue fever remains a major mosquito–borne disease worldwide, with over 400 million infections annually and a high risk of severe complications such as dengue hemorrhagic fever. The disease is prevalent in tropical and subtropical regions, where population density and limited vector control accelerate transmission, making early and reliable diagnosis essential for outbreak prevention and disease management. Conventional diagnostic methods, including virus isolation, reverse transcription polymerase chain reaction (RT–PCR), enzyme–linked immunosorbent assays (ELISA), and serological testing, are accurate but often constrained by high cost, labor–intensive procedures, centralized laboratory requirements, and delayed turnaround times. This review examines current dengue diagnostic technologies by outlining their working principles, performance characteristics, and practical limitations, with emphasis on key target analytes such as viral RNA; nonstructural protein 1 (NS1), including DENV–2 NS1; and host antibodies. Diagnostic approaches across commonly used biofluids, including whole blood, serum, plasma, and urine, are discussed. Recent advances in biosensing technologies are reviewed, including optical, electrochemical, microwave, microfluidic, and CRISPR–based platforms, along with the integration of artificial intelligence for data analysis and diagnostic enhancement. Overall, this review highlights the need for accurate, scalable, and field–deployable diagnostic solutions to support early dengue detection and reduce the global disease burden. Full article

This study focuses on the optimization of modern extraction techniques for selected by-product materials, including apple, lemon, and tangerine peels, and onion skins, using artificial neural network (ANN) models. The extraction methods included ultrasound-assisted extraction (UAE) and microwave-assisted extraction (MAE) with water as the extractant, as well as maceration (MAC) with natural deep eutectic solvents (NADES). Key parameters, such as total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activities, including reducing power (EC₅₀) and free radical scavenging capacity (IC₅₀), were evaluated to compare the efficiency of each method. Among the techniques, UAE outperformed both MAE and MAC in extracting bioactive compounds, especially from onion skins and tangerine peels, as reflected in the highest TPC, TFC, and antioxidant activity. UAE of onion skins showed the best performance, yielding the highest TPC (5.735 ± 0.558 mg CAE/g) and TFC (1.973 ± 0.112 mg RE/g), along with the strongest antioxidant activity (EC₅₀ = 0.549 ± 0.076 mg/mL; IC₅₀ = 0.108 ± 0.049 mg/mL). Tangerine peel extracts obtained by UAE also exhibited high phenolic content (TPC up to 5.399 ± 0.325 mg CAE/g) and strong radical scavenging activity (IC₅₀ 0.118 ± 0.099 mg/mL). ANN models using multilayer perceptron architectures with high coefficients of determination (r² > 0.96) were developed to predict and optimize the extraction results. Sensitivity and error analyses confirmed the robustness of the models and emphasized the influence of the extraction technique and by-product type on the antioxidant parameters. Principal component and cluster analyses showed clear grouping patterns by extraction method, with UAE and MAE showing similar performance profiles. Overall, these results underline the potential of UAE- and ANN-based modeling for the optimal utilization of agricultural by-products. Full article

Non-invasive glucose monitoring remains a significant challenge in diabetes management, with existing approaches often limited by poor accuracy, high cost, or patient discomfort. Microwave-based biosensors offer a promising label-free alternative by exploiting the dielectric contrast between glucose and water. This paper presents a compact, dual-band concentric square-shaped split-ring resonator (SRR-type) biosensor fabricated on a low-cost FR-4 substrate for aqueous glucose detection. The sensor leverages electric field confinement in inter-ring gaps to transduce glucose-induced permittivity changes into measurable shifts in resonance frequency and reflection coefficient. Experimental results demonstrate a linear, monotonic response across the clinical range up to 250 mg/dL, with a frequency-domain sensitivity of 1.964 MHz/(mg/dL) and amplitude-domain sensitivity of 0.0332 dB/(mg/dL), achieving high coefficients of determination (R² = 0.9956 and 0.9927, respectively). The design achieves a normalized size of 0.137 λ_g², combining high sensitivity and compact size within a scalable platform. Operating in the UWB-adjacent band (2.76–3.25 GHz), the proposed biosensor provides a practical, reproducible, and PCB-compatible solution for next-generation label-free glucose monitoring. Full article

This work introduces a dual-capacitance upper and lower T-electrode structure for high-performance silicon-based thin-film lithium niobate electro-optic modulators. Employing this structure reduces the distributed capacitance per unit length, suppresses the slow light effect, and lowers the microwave refractive index, consequently achieving group velocity matching between optical and microwave waves. For a 1 cm long device, this design simulates a half-wave voltage of 1.18 V, an electro-optic bandwidth exceeding 70 GHz, and an optical loss of 0.1 dB/cm. Furthermore, the proposed modulator demonstrates compatibility with standard photonic integrated circuit fabrication processes, indicating strong potential for large-scale manufacturing. Full article

Click chemistry, and particularly the Cu-catalyzed Azide Alkyne Cycloaddition (CuAAC) reaction has gained increased attention in recent years as an invaluable tool for synthesizing pharmaceutical active organic compounds. In this study, quinolinones and triazoles, two bioactive heterocyclic moieties amenable to various substitutions, were employed to design and synthesize novel quinolinone–triazole hybrid molecules via the CuAAC click reaction under microwave irradiation. The synthesized hybrid molecules and their alkyne precursors were structurally characterized and evaluated for their antioxidant capacity, lipoxygenase (LOX) inhibitory activity, cell viability using HaCaT epithelial cells, and cytotoxicity against two cancer lines. The results indicated that, among the precursors, alkyne 4c exhibits the best combined antioxidant and anti-inflammatory activity (100% lipid peroxidation inhibition, IC₅₀ = 22.5 μM for LOX inhibition); among the hybrid molecules, compound 5a was the most potent (98.0% lipid peroxidation inhibition, IC₅₀ = 10.0 μM for LOX inhibition). Regarding the assessment of HaCaT cell viability, all studied compounds showed encouraging results, with cell viability rates between 61.5% and 100%. Moreover, based on the results of the cytotoxicity against cancer lines A549 and A375, it emerged that the tested compounds exhibited moderate–low or no cytotoxicity. These results highlight the potential of quinolinone–triazole hybrids as valuable candidates in drug discovery. Full article

Microwaves have been used as a heat source in various chemical processes, and their application range is expanding to include high-temperature processes. Existing microwave-based methods for glass syntheses predominantly involve coating and drying. Moreover, microwaves have rarely been applied to glass melting, which consumes a large amount of energy. In this study, the raw materials required for preparing optical glass were heated using microwaves to reduce the energy consumption of the glass-melting process. Microwaves were applied to the raw materials of a typical optical glass, i.e., borosilicate crown glass (BK7). The results indicated that the raw materials rapidly reached the target temperature of 1000 °C and were heated particularly well at temperatures above 500 °C. This was reflected in the high microwave absorption of BK7 above 500 °C, as confirmed by dielectric-constant measurements in the high-temperature range using resonance perturbation. Additionally, BK7 was heated on a 100 g scale in a large microwave-concentrated hexagonal furnace. The obtained glass exhibited a refractive index of 1.5155 (d-line of helium: λ = 587.56 nm), which is comparable to that obtained via conventional heating. Our findings are expected to help reduce the time needed for glass melting considerably and conserve energy, thus contributing to a sustainable society. Full article

Dietary fiber is an essential component of the human diet, and insoluble dietary fiber (IDF) accounts for a significant proportion. However, its poor solubility and rigid structure limit its high-value applications. In recent years, modification technologies have become key strategies for enhancing the functional properties of IDF and expanding its applications. This review systematically summarizes the latest advances in the field of IDF modification, emphasizing how different modification strategies precisely regulate the multilevel structure of IDF to selectively improve its physicochemical properties and physiological functions. The principles and mechanisms of physical, chemical, biological, and combined modification methods are explained, and the unique advantages and limitations of each method in terms of structural changes, functional enhancement, and application scenarios are compared. Using high-pressure hydrostatic pressure-assisted cellulase treatment on potato dietary fiber can effectively disrupt fiber rigidity, increase soluble dietary fiber (SDF), and markedly enhance cholesterol and glucose adsorption capacities, outperforming single-treatment approaches. Microwave-assisted enzymatic treatment of millet bran IDF raises its intestinal fermentation rate from 36% to 59% and doubles butyrate production, significantly boosting prebiotic activity and offering a new pathway for targeted modulation of gut microbiota; combined modification strategies further demonstrate synergistic benefits. Modified IDF can serve not only as a low-calorie fat replacer in foods but also, through specific structural alterations, be incorporated into plant-based meat products to improve their fiber attributes and nutritional density. Moreover, this review explores the emerging potential of modified IDF in pharmaceutical carriers and gut microecology regulation. The aim is to provide theoretical guidance for selecting and optimizing IDF modification strategies, thereby promoting the high-value utilization of agricultural processing by-products and the development of high-quality dietary fiber products. Full article

Xinfeng County, Shaoguan City, Guangdong Province, China, is a typical vegetation-covered area that suffers from severe attenuation of rock and mineral spectral information in remote sensing images owing to dense vegetation. This situation limits the accuracy of traditional lithological mapping methods, making them unable to meet geological mapping demands under complex conditions, and thus necessitating a tailored lithological identification model. To address this issue, in this study, the penetration capability of microwave remote sensing (for extracting indirect textural features of lithology) was combined with the spectral superiority of hyperspectral remote sensing (for capturing lithological spectral features), resulting in a dual-branch deep-learning framework for lithological classification based on multisource remote sensing data. The framework independently extracts features from Sentinel-1 imagery and Gaofen-5 data, integrating three key modules: texture feature extraction, spatial–spectral feature extraction, and attention-based adaptive feature fusion, to realize deep and efficient fusion of heterogeneous remote sensing information. Ablation and comparative experiments were conducted to evaluate each module’s contribution. The results show that the dual-branch architecture effectively captures the complementary and discriminative characteristics of multimodal data, and that the encoder–decoder structure demonstrates strong robustness under complex conditions such as dense vegetation. The final model achieved 97.24% overall accuracy and 90.43% mean intersection-over-union score, verifying its effectiveness and generalizability in complex geological environments. The proposed multi-source remote sensing–based lithological classification model overcomes the limitations of single-source data by integrating indirect lithological texture features containing vegetation structural information with spectral features, thereby providing a viable approach for lithological mapping in vegetated regions. Full article

The global population is rising sharply and is expected to be 10 billion by 2050. Nutrition security, especially protein, is a major concern, as it is one of the essential ingredients for body growth. However, consumption of meat is unsustainable, as the use of natural resources and greenhouse gas (GHG) emissions are relatively high compared to plant-based protein sources. Aquatic plants like duckweed, Azolla, and water spinach, as well as macroalgae and microalgae, contain good amounts of protein, ranging from 25% to 60% dry weight (DW) and comprising major essential amino acids (EAAs). These plants are rich in vitamins and minerals and possess antimicrobial, anti-inflammatory, antidiabetic, and anti-fatigue properties. In addition, green food processing (GFP) technologies minimize the antinutritional factors, which in turn increase the bioaccessibility and biodigestibility of aquatic plants. Fermentation is one of the oldest known GFP methods. Recent advances include high-pressure processing, pulsed electric field, ultrasound-assisted, and microwave-assisted extraction, which are among the most promising techniques. Hence, government initiatives, as well as research and private sector collaboration for cultivation, processing, and advocating for such nutrient-dense food, are necessary. This will ensure sustainable production and consumption. Full article

This study developed a process for producing prebiotic-fortified instant rice macaroni to diversify rice-based convenience foods. Resistant starch (RS) rice flour from three varieties—IR504 and two pigmented, anthocyanidin-rich rice cultivars (Huyet Rong and MS2019)—was blended with wheat flour and fixed ingredients (tapioca starch, salt, and vegetable oil at a ratio of 9g:1g:1g), together with hot water. The instant rice macaroni with the highest RS content (11.64%) was obtained using IR504 RS and wheat flour (44:6), gelatinized at 100 °C for 20 min, microwaved at 36 W/g for 30 s, retrograded at 4 °C for 24 h, and sterilized at 115 °C for 15 min. For anthocyanidin-containing macaroni, the combination of Huyet Rong RS and wheat flour (39:11) yielded 9.47% RS under similar retrogradation and sterilization conditions, but with a shorter gelatinization step (100 °C, 15 min) and longer microwave treatment (50 s at 27 W/g). The other optimized colored-RS formulation was based on MS2019 RS and wheat flour (21:29) processed under similar conditions. All optimized formulations exhibited lower estimated glycemic index (eGI) values of 64.1, 65.7, and 68.2, which were significantly lower than those of the control instant rice macaroni (78.2–85.9, p < 0.05). This study confirms the potential of developing instant rice macaroni rich in RS to enhance prebiotic effects that support the growth of beneficial intestinal bacteria, strengthen immune function, and improve nutritional quality through the incorporation of anthocyanidin-rich rice varieties and a processing procedure combining heat–moisture treatment with microwave heating. Full article

In recent years, the scientific community has increasingly focused on state-of-the-art techniques, such as MIMO and mmWave transmission, aimed at enhancing the performance of telecommunication channels both quantitatively and qualitatively through various approaches. These efforts often rely on channel models designed to more accurately represent real-world conditions, thereby ensuring that the results are objective and practically applicable. In the present study, we employ one of the most scientifically reliable system- level simulators, Vienna SLS Simulator, to evaluate the performance of a wireless channel that we configure based on the latest standards (3GPP TR 36.873). We take into account the well-known non-symmetrical behavior of mMIMOs, where m stands for microwave MIMOs, in wireless communication systems and analyze the resulting changes in key performance metrics including average cell throughput, average user spectral efficiency and signal-to-interference-plus-noise ratio (SINR). We vary specific parameters such as transmission power, antenna polarization, ratio of indoor to outdoor users, and others with the aim of validating or challenging existing scientific assumptions. Particular attention is given to studying how variations in the aforementioned factors affect channel geometry and spatial uniformity, emphasizing the role of antenna geometry, polarization and user distribution in shaping channel asymmetries in mmWave MU-MIMO systems. Overall, this study provides insights into designing more balanced and efficient wireless systems in realistic urban environments. Full article

With the rapid advancement of detection technologies, traditional static electromagnetic absorbers increasingly struggle to meet controllable stealth requirements across diverse dynamic environments. To achieve active and controllable modulation of electromagnetic reflection characteristics, this paper proposes a transparent reconfigurable metamaterial absorber based on an origami structure. By adjusting the folding angles of the indium tin oxide (ITO)-polyethylene terephthalate (PET) film, the structure achieves reversible deformation from the vertical state to the horizontal state. This enables continuous modulation of the reflectance from below −10 dB (absorbing state) to nearly 0 dB (reflecting state) within the 4–18.9 GHz frequency range, with a relative bandwidth exceeding 130% and excellent angular stability. The energy loss and current distribution under different states are analyzed, revealing the mechanisms behind broadband absorption and deep modulation. Experimental measurements of the fabricated metamaterial align well with simulation results. Leveraging its flexible structure, reversible modulation capability, and angular stability, this origami-inspired reconfigurable metamaterial demonstrates promising application potential in the fields of adaptive electromagnetic camouflage and stealth protection. Full article

This paper presents a high-sensitivity microwave sensor based on a modified Complementary Split Ring Resonator (CSRR) architecture, integrated with inductive stubs, for non-invasive blood glucose monitoring. The proposed sensor is designed to enhance the electric field localization and coupling efficiency by introducing inductive elements that strengthen the perturbation effect caused by glucose concentration changes in the blood. Numerical simulations were conducted using a multilayer finger model to evaluate the sensor’s performance under various glucose levels ranging from 0 to 500 mg/dL. The modified sensor exhibits dual-resonance characteristics and outperforms the conventional CSRR in both frequency and amplitude sensitivity. At an optimized stub gap of 2 mm, which effectively minimizes the capacitive coupling effect of the transmission line and thereby improves the quality factor, the sensor achieves a frequency shift sensitivity of 0.086 MHz/mg/dL and an amplitude sensitivity of 0.02 dB/mg/dL, compared to 0.032 MHz/mg/dL and 0.0116 dB/mg/dL observed in the standard CSRR structure. This confirms a significant enhancement in sensing performance and field confinement due to the optimized inductive loading. These results represent significant enhancements of approximately 168% and 72%, respectively. With its compact design, increased sensitivity, and potential for wearable implementation, the proposed sensor offers a promising platform for continuous, real-time, and non-invasive glucose monitoring in biomedical applications. Full article

The complexity of land types and the limited spatial resolution of Synthetic Aperture Radar (SAR) imagery have led to widespread mixed-pixel contamination in radar backscatter images. The radar backscatter echo signals from a mixed pixel are often a combination of backscattering contributions from multiple endmembers. The signal mixture of endmembers within mixed pixels hinders the establishment of accurate relationships between pure endmembers’ parameters and the corresponding backscatter coefficient, thereby significantly reducing the accuracy of surface parameter inversion. However, few studies have focused on decomposing and estimating the pure backscatter signals within mixed pixels. This paper proposes a novel approach based on hyperspectral unmixing techniques and the microwave backscatter contribution decomposition (MBCD) model to estimate the pure backscatter coefficients of all Endmembers within mixed pixels. Experimental results demonstrate that the model performance varied significantly with endmember abundance. Specifically, high accuracy was achieved in estimating soil backscattering coefficients when vegetation coverage was below 25% ($R^2\approx 0.88$, with 98% of pixels showing relative errors within 0–20%); however, this accuracy declined as vegetation coverage increased. For grass endmembers, the model maintained high estimation precision across the entire grassland area (vegetation coverage 0.2–0.8), yielding an of 0.80 with 83% of pixels falling within the 0–20% relative error range. In addition, the model performance is influenced by the number of endmembers. Full article

Fill level control is one of the strict checks required when inspecting industrially packaged products. The purpose is both to ensure the content conformity according to the declared label information and to preserve the reliability of brand trust, strongly influenced by the customer’s evenness perception of the marketed items. To this aim, choosing the right technology is not an easy task: content and packaging material properties are essential to establish the suitability of a product to the fill level machine type. In this paper, we propose a novel approach, based on microwaves, to address this issue. The designed microwave inspection system consists of two Vivaldi antennas working between 1 and 18 GHz. We show its applicability to water, oil and alcohol-based products moving on conveyor belts at production speed. The performed experiments demonstrate good accuracy and efficiency of level classification and fault rejection in real-time processing. Full article