Search Results (537)

The rapid evolution of deep learning (DL) has fundamentally transformed the paradigm for detecting special components in agricultural products, addressing critical challenges in food safety, quality control, and precision agriculture. This comprehensive review systematically analyzes many seminal studies to evaluate cutting-edge DL applications across three core domains: contaminant surveillance (heavy metals, pesticides, and mycotoxins), nutritional component quantification (soluble solids, polyphenols, and pigments), and structural/biomarker assessment (disease symptoms, gel properties, and physiological traits). Emerging hybrid architectures—including attention-enhanced convolutional neural networks (CNNs) for lesion localization, wavelet-coupled autoencoders for spectral denoising, and multi-task learning frameworks for joint parameter prediction—demonstrate unprecedented accuracy in decoding complex agricultural matrices. Particularly noteworthy are sensor fusion strategies integrating hyperspectral imaging (HSI), Raman spectroscopy, and microwave detection with deep feature extraction, achieving industrial-grade performance ($RPD$ > 3.0) while reducing detection time by 30–100× versus conventional methods. Nevertheless, persistent barriers in the “black-box” nature of complex models, severe lack of standardized data and protocols, computational inefficiency, and poor field robustness hinder the reliable deployment and adoption of DL for detecting special components in agricultural products. This review provides an essential foundation and roadmap for future research to bridge the gap between laboratory DL models and their effective, trusted application in real-world agricultural settings. Full article

White-light-emitting diodes (wLEDs) are central to next-generation lighting technologies, yet their reliance on critical raw materials (CRMs), such as rare-earth elements, raises concerns regarding sustainability and supply security. In this work, we present a simple, low-cost method to produce photoluminescent carbon-based nanostructures—known as oxidative debris (OD)—via alkaline treatment of graphene oxide (GO) using KOH solutions ranging from 0.04 M to 1.78 M. The resulting OD, isolated from the supernatant after acid precipitation, exhibits strong and tunable photoluminescence (PL) across the visible spectrum. Emission peaks shift from blue (~440 nm) to green (~500 nm) and yellow (~565 nm) as a function of treatment conditions, with excitation wavelengths between 300 and 390 nm. Optical, morphological. and compositional analyses were performed using UV-Vis, AFM, FTIR, and Raman spectroscopy, confirming the presence of highly oxidized aromatic domains. The blue-emitting (S2) and green/yellow-emitting (R2) fractions were successfully separated and characterized, demonstrating potential color tuning by adjusting KOH concentration and treatment time. This study highlights the feasibility of reusing GO-derived byproducts as sustainable phosphor alternatives in wLEDs, reducing reliance on CRMs and aligning with green chemistry principles. Full article

This paper focuses on the switching and modulation techniques of terahertz waves, develops ${\mathrm{VO}}_2$ thin-film materials with an SPP structure, and uses terahertz time-domain spectroscopy (THz-TDS) to study the semiconductor–metal phase transition characteristics of ${\mathrm{VO}}_2$ thin films, especially the photoinduced semiconductor–metal phase transition characteristics of silicon-based ${\mathrm{VO}}_2$ thin films. The optical modulation characteristics of silicon-based ${\mathrm{VO}}_2$ thin films to terahertz waves under different light excitation modes, such as continuous light irradiation at different wavelengths and femtosecond pulsed laser irradiation, were analyzed. Combining the optical modulation characteristics of silicon-based ${\mathrm{VO}}_2$ thin films with the filtering characteristics of SPP structures, composite structures of ${\mathrm{VO}}_2$ thin films with metal hole arrays, composite structures of ${\mathrm{VO}}_2$ thin films with metal block arrays, and silicon-based ${\mathrm{VO}}_2$ microstructure arrays were designed. The characteristics of this dual-function device were tested experimentally. The experiment proves that the ${\mathrm{VO}}_2$ film material with an SPP structure has a transmission rate dropping sharply from 32% to 1% under light excitation; the resistivity changes by more than six orders of magnitude, and the modulation effect is remarkable. By applying the SPP structure to the ${\mathrm{VO}}_2$ material, the material can simultaneously possess modulation and filtering functions, enhancing its optical performance in the terahertz band. Full article

Recent achievements in ultrafast spin physics have enabled the use of heterostructures composed of ferromagnetic (FM)/non-magnetic (NM) thin layers for terahertz (THz) generation. The mechanism of THz emission from FM/NM multilayers has been typically ascribed to the inverse spin Hall effect (ISHE). In this work, we probe the mechanism of the ISHE by inserting a second ferromagnetic layer in the form of an alloy between the FM/NM system. In particular, by utilizing the co-sputtering technique, we fabricate Fe/L1₀-FePt/Pt ultra-thin heterostructures. We successfully grow the tetragonal phase of FePt (L1₀-phase) as revealed by X-ray diffraction and reflection techniques. We show the strong magnetic coupling between Fe and L1₀-FePt using magneto-optical and Superconducting Quantum Interference Device (SQUID) magnetometry. Subsequently, by utilizing THz time domain spectroscopy technique, we record the THz emission and thus we the reveal the efficiency of spin-to-charge conversion in Fe/L1₀-FePt/Pt. We establish that Fe/L1₀-FePt/Pt configuration is significantly superior to the Fe/Pt bilayer structure, regarding THz emission amplitude. The unique trilayer structure opens new perspectives in terms of material choices for the future spintronic THz sources. Full article

Background/Objectives: Neurocognitive disorders (NCDs) encompass a spectrum of conditions that significantly impact cognitive domains, including attention, memory, and language. Mild NCD, increasingly prevalent with aging, represents an early stage of these disorders, characterized by cognitive deficits that do not interfere with daily functioning. Non-pharmacological therapies, especially cognitive stimulation, are widely recommended to preserve cognitive function of older adults. This study aimed to evaluate the effectiveness of a 12-week individual cognitive stimulation (iCS) program on cognitive performance, mood, and prefrontal cortex activation in older adults with mild NCD using a single-blind, randomized, parallel two-arm RCT. Methods: A sample of 36 older adults were selected from a central region of Portugal. The intervention group (n = 18) received 24 iCS sessions, twice weekly for 12 weeks. The control group (n = 18) completed their regularly scheduled activities. Outcomes included global cognitive function, executive functioning, and mood. All participants were assessed at baseline and after the intervention. Functional near infra-red spectroscopy (fNIRS) was also collected to measure prefrontal cortex activity at both time points in the intervention group. Results: The intervention group showed a significant improvement in global cognition and executive functions, and reduced depressive symptomatology compared to the control group. fNIRS data revealed enhanced activation and functional efficiency in the lateral prefrontal cortex following the iCS program. Adherence and degree of collaboration to the intervention were very high. Conclusions: These findings suggest that iCS is an effective approach to improving cognitive function and mood in mildly cognitively impaired older adults. Full article

Monolayer (ML) molybdenum disulfide (MoS₂) is a typical valleytronic material which has important applications in, for example, polarization optics and information technology. In this study, we examine the effect of continuous wave (CW) laser pumping on the basic optoelectronic properties of ML MoS₂ placed on a sapphire substrate, where the pump photon energy is larger than the bandgap of ML MoS₂. The pump laser source is provided by a compact semiconductor laser with a 445 nm wavelength. Through the measurement of THz time-domain spectroscopy, we obtain the complex optical conductivity for ML MoS₂, which are found to be fitted exceptionally well with the Drude–Smith formula. Therefore, we expect that the reduction in conductivity in ML MoS₂ is mainly due to the effect of electronic backscattering or localization in the presence of the substrate. Meanwhile, one can optically determine the key electronic parameters of ML MoS₂, such as the electron density n_e, the intra-band electronic relaxation time τ, and the photon-induced electronic localization factor c. The dependence of these parameters upon CW laser pump intensity is examined here at room temperature. We find that 445 nm CW laser pumping results in the larger n_e, shorter τ, and stronger c in ML MoS₂ indicating that laser excitation has a significant impact on the optoelectronic properties of ML MoS₂. The origin of the effects obtained is analyzed on the basis of solid-state optics. This study provides a unique and tractable technique for investigating photo-excited carriers in ML MoS₂. Full article

Time-domain (TD) diffuse reflectance can be modeled using diffusion theory (DT) to non-invasively estimate optical transport coefficients of biological media, which serve as markers of tissue physiology. We employ an optimized N-layer DT solver in cylindrical geometry to reconstruct optical coefficients of bilayered media from TD reflectance generated via Monte Carlo (MC) simulations. Optical properties for 384 bilayered tissue models representing human head or limb tissues were obtained from the literature at three near-infrared wavelengths. MC data were fit using the layered DT model to simultaneously recover transport coefficients in both layers. Bottom-layer absorption was recovered with errors under 0.02 cm⁻¹, and top-layer scattering was retrieved within 3 cm⁻¹ of input values. In contrast, recovered bottom-layer scattering had mean errors exceeding 50%. Total hemoglobin concentration and oxygen saturation were reconstructed for the bottom layer to within 10 μM and 5%, respectively. Extracted transport coefficients were significantly more accurate when obtained using layered DT compared to the conventional, semi-infinite DT model. Our results suggest using improved theoretical modeling to analyze TD reflectance analysis significantly improves recovery of deep-layer absorption. Full article

Power transformer insulation systems, composed of liquid and solid insulators, are continuously exposed to thermal and electrical stresses that degrade their performance over time and may lead to premature failure. Since these stresses are unavoidable during operation, selecting effective insulating materials is critical for long-term reliability. In this study, Kraft insulation paper was used as the solid insulator and impregnated with three different liquids: mineral oil and two natural esters (NE1204 and NE1215), to evaluate their stability under simultaneous thermal and electrical stress. The degradation behavior of the oil-impregnated papers was assessed using frequency-domain dielectric spectroscopy (FDS) and Fourier-transform infrared spectroscopy (FTIR), enabling early fault detection. Comparative analyses were conducted to evaluate the withstand capability of each liquid type during operation. Results revealed strong correlations between FTIR indicators (e.g., oxidation and hydroxyl group loss) and dielectric parameters (permittivity and loss factor), confirming the effectiveness of this combined diagnostic approach. Post-aging breakdown analysis showed that natural esters, particularly NE1215, offered superior preservation of insulation integrity compared to mineral oil. Differences between the two esters also highlight the role of chemical composition in insulation performance. This study reinforces the potential of natural esters as viable, eco-friendly alternatives in thermally and electrically stressed applications. Full article

We demonstrate a novel bidirectional mode-locked ultrafast fiber laser based on an asymmetric dual-cavity architecture that enables freely tunable repetition rate differentials at the kilohertz level, while maintaining inherent common-mode noise suppression through precision thermomechanical stabilization. Through cascaded amplification and nonlinear temporal compression, we obtained bidirectional pulse durations of 33.2 fs (clockwise) and 61.6 fs (counterclockwise), respectively. The developed source demonstrates exceptional capability for asynchronous optical sampling applications, particularly in enabling the compact implementation of real-time measurement systems such as terahertz time-domain spectroscopy (THz-TDS) systems. Full article

Functional near-infrared spectroscopy (fNIRS) is a non-invasive imaging technique that measures brain hemodynamic activity by detecting changes in oxyhemoglobin and deoxyhemoglobin concentrations using light in the near-infrared spectrum. This study aims to provide a comprehensive characterization of fNIRS signals acquired with a prototypal continuous-wave fNIRS device during a breath-holding task, to evaluate the impact of respiratory activity on scalp hemodynamics within the framework of Network Physiology. To this end, information-theoretic and spectral analysis methods were applied to characterize the dynamics of fNIRS signals. In the time domain, time-resolved information-theoretic measures, including entropy, conditional entropy and, information storage, were employed to assess the complexity and predictability of the fNIRS signals. These measures highlighted distinct informational dynamics across the breathing and apnea phases, with conditional entropy showing a significant modulation driven by respiratory activity. In the frequency domain, power spectral density was estimated using a parametric method, allowing the identification of distinct frequency bands related to vascular and respiratory components. The analysis revealed significant modulations in both the amplitude and frequency of oscillations during the task, particularly in the high-frequency band associated with respiratory activity. Our observations demonstrate that the proposed analysis provides novel insights into the characterization of fNIRS signals, enhancing the understanding of the impact of task-induced peripheral cardiovascular responses on NIRS hemodynamics. Full article

Precision thickness control in new energy electrode coatings is a critical determinant of battery performance characteristics. This study presents a non-destructive inspection methodology employing terahertz time-domain spectroscopy (THz-TDS) to achieve high-precision coating thickness measurement in lithium iron phosphate (LFP) battery manufacturing. Industrial THz-TDS systems mostly adopt fixed threshold filtering or Fourier filtering, making it disssssfficult to balance noise suppression and signal fidelity. The developed approach integrates three key technological advancements. Firstly, the refractive index of the material is determined through multi-peak amplitude analysis, achieving an error rate control within 1%. Secondly, a hybrid signal processing algorithm is applied, combining an optimized Savitzky–Golay filter for high-frequency noise suppression with an enhanced sinc function wavelet threshold technique for signal fidelity improvement. Thirdly, the time-of-flight method enables real-time online measurement of coating thickness under atmospheric conditions. Experimental validation demonstrates effective thickness measurement across a 35–425 μm range, achieving a 17.62% range extension and a 2.13% improvement in accuracy compared to conventional non-filtered methods. The integrated system offers a robust quality control solution for next-generation battery production lines. Full article

Nickel (Ni) ultrathin films exhibit phase-dependent electrical, magnetic, and optical characteristics that are significantly influenced by deposition methods. However, these films are inherently prone to rapid oxidation, with the oxidation rate dependent on substrate, temperature, and deposition parameters. The focus of this research is to investigate the temporal oxidation of RF-sputtered Ni ultrathin films on Corning glass under ambient atmospheric conditions and its impact on their structural, surface, and optical characteristics. Controlled film thicknesses were achieved through precise manipulation of deposition parameters, enabling the analysis of oxidation-induced modifications. Atomic force microscopy (AFM) revealed that films with high structural integrity and surface uniformity are exhibiting roughness values (Rq) from 0.679 to 4.379 nm of corresponding thicknesses ranging from 4 to 85 nm. Scanning electron microscopy (SEM) validated the formation of Ni grains interspersed with NiO phases, facilitating SPR-like effects. UV-visible spectroscopy is demonstrating thickness-dependent spectral (plasmonic peak) shifts. Finite Difference Time Domain (FDTD) simulations corroborate the observed thickness-dependent optical absorbance and the resultant shifts in the absorbance-induced plasmonic peak position and bandgap. Increased NiO presence primarily drives the enhancement of electromagnetic (EM) field localization and the direct impact on power absorption efficiency, which are modulated by the tunability of the plasmonic peak position. Our work demonstrates that controlled fabrication conditions and optimal film thickness selection allow for accurate manipulation of the Ni oxidation process, significantly altering their optical properties. This enables the tailoring of these Ni films for applications in transparent conductive electrodes (TCEs), magneto-optic (MO) devices, spintronics, wear-resistant coatings, microelectronics, and photonics. Full article

Thickness inspection of thermal barrier coatings is crucial to safeguard the reliability of high-temperature components of aero-engines, but traditional destructive inspection methods are difficult to meet the demand for rapid assessment in the field. In this study, a new non-destructive testing method integrating terahertz time-domain spectroscopy and machine learning algorithms is proposed to systematically study the thickness inspection of 8YSZ coatings prepared by two processes, namely atmospheric plasma spraying (APS) and electron beam physical vapor deposition (EB-PVD). By optimizing the preparation process parameters, 620 sets of specimens with thicknesses of 100–400 μm are prepared, and three types of characteristic parameters, namely, time delay Δt, frequency shift Δf, and energy decay η, are extracted by combining wavelet threshold denoising and time-frequency joint analysis. A CNN-RF cascade model is constructed to realize coating process classification, and an attention-LSTM and SVR weighted fusion model is developed for thickness regression prediction. The results show that the multimodal feature fusion reduces the root-mean-square error of thickness prediction to 8.9 μm, which further improves the accuracy over the single feature model. The classification accuracy reaches 96.8%, of which the feature importance of time delay Δt accounts for 62%. The hierarchical modeling strategy reduces the detection mean absolute error from 6.2 μm to 4.1 μm. the method provides a high-precision solution for intelligent quality assessment of thermal barrier coatings, which is of great significance in promoting the progress of intelligent manufacturing technology for high-end equipment. Full article

Cross-linked polyethylene (XLPE) cables will gradually experience aging under various stresses during long-term operation, which may lead to faults and seriously affect the safe and stable operation of the power system. This article prepares aged cable samples by accelerating the thermal aging of XLPE cables, and combines frequency-domain dielectric spectroscopy (FDS) and the polarization–depolarization current method (PDC) for detection and analysis. By measuring the dielectric loss of aged cables using frequency-domain dielectric spectroscopy, it was found that the dielectric loss value in the low-frequency region significantly increases with aging time, indicating that aging leads to an increase in polarity groups and polarization loss. The high-frequency dielectric loss also significantly increases with the strengthening of dipole polarization. At the same time, using the polarization–depolarization current method to measure the polarization current and depolarization current of cables, it was found that the stable value of polarization current increases with aging time, further verifying the changes in the conductivity and polarization characteristics of insulation materials. Combining the broadband dielectric response characteristics of FDS (0.001 Hz–1 kHz) with the time-domain charge transfer analysis of PDC, the molecular structure degradation (dipole polarization enhancement) and interface defect accumulation (space charge effect) of cable aging are revealed from both frequency- and time-domain perspectives. The experimental results show that the integral value of the low-frequency region of the frequency-domain dielectric spectrum and the stable value of the polarization depolarization current are positively correlated with the aging time, and can make use of effective indicators to evaluate the aging state of XLPE cables. Full article