Search Results (139)

Ensuring long-term agricultural sustainability depends heavily on preserving soil health, a process fundamentally governed by humic substances (HSs) and their vital physicochemical and biological functions. However, because intensive farming rapidly degrades natural HSs reserves, external replenishment has become essential, driving the expansion of the humic preparations market. This article constitutes a comprehensive review of the entire technological chain of humic preparations: from the identification of raw materials, through advanced extraction techniques, up to agrochemical mechanisms in the soil–plant system. Both traditional fossil deposits (leonardite, brown coal, peat) and renewable waste sources fitting into the concept of the circular economy were discussed. Classical alkaline extraction was confronted with green methods such as ultrasound-assisted (UAE), microwave-assisted (MAE) or high voltage electrical discharge (HVED) extraction, which allow for shortening the operation time and reducing the consumption of reagents. Strategies of integrating HSs with mineral fertilizers (coating, liquid formulas, organo-mineral products) and their direct impact on improving nutrient use efficiency (NUE), mitigating plant abiotic stress, agricultural performance, and environmental impact were described in detail. Research perspectives were also presented, including, among others, economic aspects of scaling up humic technologies and an assessment of the development potential of innovative nanofertilizers functionalized with HSs. Full article

Sparse antenna arrays are attractive for compact microwave and millimeter-wave front ends because they can achieve prescribed radiation performance with fewer radiating elements, thereby reducing the number of feeding channels, hardware cost, weight, and power consumption. However, the joint optimization of element positions and complex excitations remains challenging, since the element positions enter the array factor nonlinearly and the element-count objective is inherently combinatorial. This paper presents an iterative reweighted ℓ₁ synthesis framework for sparse antenna arrays with continuous element positions. At each iteration, position perturbations are introduced and the array factor is linearized using a first-order Taylor expansion within a trust region. The resulting non-convex sparse synthesis problem is then approximated by convex programing through an iteratively reweighted ℓ₁ relaxation, allowing the excitation amplitudes, phases, and element positions to be updated simultaneously. Additional aperture, minimum-spacing, and minimum-directivity requirements are formulated as convex constraints and incorporated when required, enabling joint control of sparsity, sidelobe level, physical layout, and radiation performance. The proposed method is validated through four representative examples, including a shaped-beam linear array, a tri-pattern reconfigurable linear array, a planar pencil-beam array, and a directivity-constrained planar array. Compared with fixed-grid reweighted ℓ₁ methods under the same specifications, the proposed approach produces sparser layouts while avoiding the grid-resolution limitation. In the directivity-constrained benchmark, it also achieves competitive element reduction while enforcing a prescribed minimum element spacing. These results indicate that the proposed framework provides a flexible and practical synthesis tool for compact and integrated sparse antenna-array design. Full article

The rapid expansion of microwave and millimeter-wave telecommunication systems has intensified the need for precise dielectric material characterization at high frequencies. As operating frequencies increase, small uncertainties in permittivity and loss tangent significantly degrade resonance stability, bandwidth control, and quality factor, directly affecting RF system reliability and performance. However, the growing diversity of resonator architectures and extraction methodologies has led to fragmentation in the literature, making it difficult to identify optimal solutions for telecommunication-oriented applications. This review provides a structured and application-driven assessment of high-frequency resonator-based dielectric characterization techniques relevant to modern telecommunication systems. Resonator topologies—including cavity, planar, substrate-integrated, metamaterial-inspireds—are systematically classified and critically compared. Their sensing mechanisms and parameter-extraction approaches are analyzed in terms of frequency-shift sensitivity, Q-factor performance, scalability toward millimeter-wave bands, integration capability, and measurement robustness. By synthesizing performance trade-offs, practical limitations, and emerging research directions, this review establishes clear design guidelines and a forward-looking framework for advancing dielectric metrology in next-generation high-frequency telecommunication technologies. Full article

Microwave imaging of objects embedded in multilayer cylindrical structures is of practical importance in applications where inaccessible targets are surrounded by a known inhomogeneous host. In such problems, incorporating the known multilayer structure into the background model can improve reconstruction accuracy and reduce the complexity of the inverse problem. This paper presents an efficient imaging method for dielectric objects embedded in two-dimensional multilayer cylindrical structures with arbitrarily shaped layer boundaries. The proposed approach integrates the contrast source inversion method with a recursive eigenfunction expansion technique for noncircular geometries. The known multilayer host is treated as the background medium, while the inversion is restricted to the embedded scatterers. The recursive formulation is derived to compute the inhomogeneous-background Green’s function and the required cell-integrated Green’s functions in a semi-analytical and discretization-free manner. Numerical results suggest that the method is capable of providing satisfactory reconstructions of embedded objects under various host configurations, including cases with a Perfect Electric Conductor (PEC) core. Comparisons with Method of Moments reference solutions confirm the accuracy of the forward modeling and the reliability of the inversion, while demonstrating a significant reduction in computational cost. Full article

The aim of this study was to evaluate the effect of incorporating button mushroom (Agaricus bisporus) powder (5% and 10%, w/w) and two expansion methods (deep-fat frying and Fmicrowaving) on the nutritional, bioactive, sensory, and physical properties of third-generation snacks. Mushroom addition increased the contents of protein, raw fiber, ash and polyphenols compounds, particularly caffeic acid and chlorogenic acid derivatives. The highest nutritional value was observed in microwave-expanded snacks containing 10% mushroom powder, which showed increased protein (4.59%), ash (2.5%) and raw fiber (3.31%) contents combined with very low fat level (0.14%) Microwave expansion promoted better retention of bioactive compounds with the highest total polyphenol content reaching 195.48 mg/kg. Instrumental sensory analyses revealed that mushroom addition intensified bitter and metallic taste attributes and enhanced roasted and earthy aroma notes associated with increased levels of pyrazines, phenols, alcohols, and acids. Moreover, mushroom incorporation reduced expansion at higher inclusion levels, altered texture, and caused a darker color. Overall, dried mushroom powder proved to be an effective potential functional ingredient that improved the nutritional and antioxidant value of third-generation snacks, while microwave expansion offered superior retention of bioactive compounds and more favorable physical characteristics. Full article

Accurate characterisation of blood dielectric properties is essential for data-driven biomedical sensing, yet experimental datasets are often limited to a few discrete hemoglobin (Hb) concentrations. This constraint hinders the development of robust data-driven models. To address this, the present study introduces a framework for generating synthetic blood permittivity spectra from sparse measurements. Four data-generation strategies were investigated, combining interpolation-based techniques and probabilistic models to extend Hb-dependent spectral coverage across the measured frequency range. Model performance was evaluated using Earth Mover’s Distance (EMD) for spectral similarity, Cole–Cole parameter analysis for physical consistency, variance preservation metrics, and Hb prediction using XGBoost. The results indicate that interpolation-based approaches achieve the highest reconstruction accuracy, while Conditional Bayesian principal component analysis (Conditional BPCA) produces smooth and physically consistent spectra with stable variability characteristics. Across all methods, the generated datasets maintained sufficient Hb-related information to support reliable prediction. These findings demonstrate that the proposed framework enables effective expansion of limited dielectric datasets while supporting a multi-criteria evaluation of synthetic data quality, including fidelity, variability, and predictive relevance. Full article

Millions of tons of lignin waste are generated annually by the pulp and paper industries and by biofuel production. Current strategies for lignin valorization, biochars and hydrogels, often rely on time-costly and pollutant-generating processes and therefore fail to meet sustainability requirements nor are economically efficient. In this work, we address the challenge of transforming lignin into a valued-added material. We propose using microwave processing to convert lignin into a functional material that is carbon-rich, structured, hydrophilic, and highly porous. Unlike conventional methods, this process is rapid, occurring in approximately 30 s under normal conditions. It induces graphitization and up to a sixfold volumetric expansion of the lignin precursor sample, leading to the formation of a stable carbon material with high porosity in the form of capsules. The resulting material exhibits strong hydrophilicity, absorbing up to 90% of its volume in water within minutes while enabling controlled release over periods of up to 24 h. This unique combination of ultrafast processing, high water uptake capacity, and controlled-release performance positions the material as a promising alternative to the valorization of lignin. Its properties make it particularly suitable for water management applications in agriculture and urban environments. Full article

Real-time imaging processing for microwave interferometric radiometer (MIR) has great potential in various application fields, such as onboard data processing, onboard information fusion, and alternative visual applications. The primary challenge lies in the computational complexity of the entire processing chain, including both visibility function preprocessing and brightness temperature (TB) reconstruction. In this study, the real-time estimation of the normalized threshold level is identified as the key step for enabling real-time imaging of three-level quantized MIR systems. Three algorithms—Acklam’s algorithm (AKA), polynomial fitting algorithm (PFA), and Taylor expansion algorithm (TEA)—are proposed and evaluated. The PFA provides a favorable balance between estimation accuracy and computational efficiency. Leveraging the proposed algorithms, this paper further establishes an onboard real-time processing framework for three-level quantization MIRs, enabling real-time TB imaging and radio frequency interference (RFI) localization. A real-time imaging experiment was carried out with a 15-element, 50 GHz one-dimensional MIR system, which demonstrates real-time imaging of fast-moving vehicles on the expressway with greatly reduced computational latency (an imaging time of 570.9 μs for 159 baselines). A further flight experiment employing an L-band system verifies the feasibility of onboard RFI localization, and the proposed real-time RFI localization method shows an average angular deviation of 0.32° with respect to an offline MUSIC estimator, corresponding to 2.1% of the nominal spatial resolution. Full article

With the continuous expansion of the expressway network and the rapid growth of traffic demand, traditional single-source traffic detection data is limited in spatial–temporal coverage and accuracy, which can hardly support the refined operation and management of intelligent expressways. Existing data preprocessing methods often fail to fully capture global spatiotemporal features, and traditional PSO-BP neural networks are prone to local optima. To address these issues, this study investigates multi-source traffic data fusion using ETC-DSRC and RTMS microwave data from the Jiangsu section of the G50 Shanghai-Chongqing Expressway. The HaLRTC tensor completion algorithm is adopted to repair missing and abnormal data, fully mining the spatial–temporal correlation characteristics of traffic flow. The beetle antennae search (BAS) mechanism is introduced into the particle swarm optimization (PSO) process to improve particle search behavior and population diversity. On this basis, a BAS-optimized PSO-BP neural network, referred to as BSO-BP in this study, is constructed for multi-source traffic data fusion. In this model, the improved PSO algorithm is used to optimize the initial weights and thresholds of the backpropagation (BP) neural network, thereby improving the global search capability and convergence stability of the fusion model. Taking the average road speed as the fusion target, MAE, RMSE and MAPE are used for accuracy verification. The results show that the proposed model has significantly higher accuracy than single-source data methods and BP, PSO-BP, and GA-PSO-BP models, and can reflect the real traffic state of road sections more accurately. Full article

The expansion of paper-based and wearable microwave electronics demands conductors that are highly conductive, finely patterned, mechanically robust, and compatible with low-cost, biodegradable substrates. This study reports a laser-scribing strategy for high-performance copper–liquid metal (Cu–LM) conductors on paper based on laser sintering of Cu–LM composite particles, with an auxiliary adhesive transfer step to facilitate integration on flexible substrates. Laser-induced reactive sintering creates a network wherein sintered liquid metal and CuGa₂ acts as a conductive bridge, interconnecting the dispersed Cu particles. This provides efficient electron transport pathways, achieving a high conductivity of 4.2 × 10⁶ S/m under optimal laser conditions, surpassing that of pure eutectic gallium–indium (EGaIn) alloys. The self-healing nature of LM enables exceptional mechanical flexibility and stable electrical performance under severe deformation. The utility of this platform is demonstrated by a miniaturized microwave liquid level sensor that provides multi-parameter water-level detection and sensor calibration. These results establish laser-scribed Cu–LM on paper as a low-cost and disposable option for high-performance microwave sensors and flexible wireless electronics. Full article

The large-scale generation of waste graphite not only poses environmental challenges but also provides an opportunity for resource recovery. This study proposes a sustainable strategy that utilizes the graphite cutting waste produced during the production of large graphite electrodes through chemical intercalation, microwave-assisted expansion, and in situ urea nitrogen doping techniques to prepare nitrogen-containing micro-expanded graphite (NMG) composite materials. Structural analysis reveals that the nitrogen-doped amorphous carbon layer formed on the expanded graphite (EG) matrix effectively suppresses excessive expansion while preserving its typical worm-like interlayer morphology and porous structure. XPS confirms successful nitrogen doping with predominant pyridinic-N configuration, introducing abundant defect sites and enhancing lithiophilicity. As an anode for LIBs, NMG delivers an exceptional initial discharge capacity of 1907.5 mAh g⁻¹ at 20 mA g⁻¹ and maintains 798.2 mAh g⁻¹ after 50 cycles, nearly twice that of purified waste graphite (G). Remarkably, after 1000 cycles at 1 A g⁻¹, it retains 650.4 mAh g⁻¹ with 89.9% capacity retention, indicating an electrochemical activation process. Kinetic analysis reveals that the superior performance originates from synergistic diffusion-controlled intercalation and surface-dominated pseudocapacitance, with nitrogen-doped defect sites and hierarchical pore architecture promoting rapid ion/electron transport and surface faradaic reactions. This work demonstrates a viable pathway for value-added upcycling of waste graphite while providing insights into designing high-performance anodes through integrated defect engineering and heteroatom doping. Full article

The expansion of the global agri-food industry has led to the generation of large volumes of processing by-products that, although traditionally treated as waste, represent valuable sources of bioactive phytochemicals with potential for sustainable valorisation. This review critically examines the integration of fruit, vegetable, cereal, and dairy processing side streams into functional dairy products. Particular attention is given to recent advances in green and emerging extraction technologies, including ultrasound-assisted extraction, microwave-assisted extraction, and supercritical fluid extraction, with emphasis on their efficiency, environmental performance, and effects on the stability and recovery of phytochemicals. The review also discusses the health-related properties of these bioactive compounds, including antioxidant, anti-inflammatory, and metabolic regulatory effects, in relation to their incorporation into milk, yogurt, cheese, and ice cream matrices. In addition, key barriers to industrial implementation are assessed, including compound stability, sensory constraints, bioavailability, and current regulatory limitations. Beyond direct fortification, the review also considers broader valorisation pathways, such as the biotechnological production of microbial enzymes from agro-industrial biomass, as relevant strategies for supporting circularity. Overall, this review highlights how sustainable extraction approaches and functional dairy innovation can contribute to improving the nutritional value, resource efficiency, and circularity of the dairy sector. Full article

This study investigated the effects of microwave irradiation on the particle size distribution, rheological properties, fluorescent characteristics, and sensory characteristics of wine. Wine samples were treated under varying microwave power (100–500 W), temperature (20–60 °C), and time (1–5 min). Results indicated that microwave treatment modified the particle size distribution, especially the proportion of particles in the range of 0.3–0.5 μm, which increased with microwave power, temperature, and time. Rheological analysis indicated that the behaviour followed the Power-law model, with all samples exhibiting expansion fluid properties (n > 1). Fitting with the Casson model revealed that microwave treatment increased the yield stress (τ₀) and viscosity coefficient (K), with optimal improvements observed at 300 W, 30 °C, and 3 min (τ₀ = 0.7769 Pa, K = 2.9367 × 10⁻³ Pa s^0.5). These changes contributed to enhanced leg phenomenon and thickening effect. Furthermore, microwave treatment elevated the fluorescence intensity of wine, indicating accelerated formation of fluorescent substances. Sensory evaluation demonstrated that microwave treatment, particularly at 400 W, 40 °C, and 3 min, significantly improved colour, clarity, and mouthfeel while reducing astringency and bitterness. In conclusion, microwave treatment effectively modifies the sensory characteristics of wine, offering a viable technological approach to accelerate wine ageing and supporting its potential application in winemaking. Full article

We investigate whether late-time modifications of gravity in the teleparallel framework can impact the current tension in the Hubble constant $H_0$, focusing on $f\left(T\right)$ cosmology as a minimal and well-controlled extension of General Relativity. We consider three representative $f\left(T\right)$ parametrisations that recover the teleparallel equivalent of General Relativity at early times and deviate from it only in late epochs. The models are confronted with unanchored Pantheon+ Type Ia supernovae, DESI DR2 baryon acoustic oscillations, compressed Planck cosmic microwave background distance priors, and redshift-space distortion data, allowing us to jointly probe the background expansion and the growth of cosmic structures. Two of the three models partially shift the inferred value of $H_0$ towards local measurements, while the third worsens the discrepancy. This behaviour is directly linked to the effective torsional dynamics, with phantom-like regimes favouring higher $H_0$ values and quintessence-like regimes producing the opposite effect. A global statistical comparison shows that the minimal $f\left(T\right)$ extensions considered here are not favoured over ΛCDM by the combined data. Nevertheless, our results demonstrate that late-time torsional modifications can non-trivially redistribute current cosmological tensions among the background and growth sectors. Full article

High-performance difference patterns (DPs) are critical for compact and integrated microwave array systems, particularly in monopulse tracking and beam-scanning applications. However, the design of monopulse phased arrays with steep slopes, high directivity, low sidelobes, and symmetric main lobes remains challenging due to constraints imposed by the array aperture and radome structure. In this paper, a novel design method is proposed to maximize the DP directivities for monopulse linear and planar phased arrays composed of microstrip patch antennas. The DP synthesis problem is first formulated as a nonconvex optimization model for directivity maximization. By fixing the reference phase of the DP slope and applying a first-order Taylor expansion of the quadratic function, the original problem is decomposed into a sequence of convex subproblems that can be solved efficiently. The proposed method fully exploits the flexibility of the phased array feed network, enabling directivity enhancement without altering the geometric configuration of the monopulse array. Finally, three numerical examples employing a radome-enclosed linear array, a uniform planar array, and a radome-enclosed planar array are presented to demonstrate the effectiveness of the proposed method in achieving the monopulse array DP synthesis with high directivity and symmetric main lobes. Full article