Search Results (7,145)

Rapid and non-destructive detection of nitrogen content in greenhouse cucumber leaves is essential for precision fertilization, yet traditional chemical methods are destructive and time-consuming, and existing spectral technologies suffer from high cost and poor field adaptability. This study aims to propose a high-precision detection scheme for cucumber leaf nitrogen content based on a lightweight model, suitable for complex scenarios. A total of 698 cucumber leaf images covering three growth stages were collected to build a segmentation dataset. Four categories and eight types of deep learning segmentation models were optimized and compared, and the optimal one was selected to extract leaf regions. Nine color features were extracted and combined with Kjeldahl-measured nitrogen content to construct and optimize three machine learning models, forming a deep learning segmentation–color feature extraction–machine learning prediction process. The results showed that YOLOv11n achieved the best segmentation accuracy, with an IoU of 0.9212 and AP of 0.9998 for high-resolution images. The optimized XGBoost had the highest prediction accuracy, with an MAE of 0.469, MSE of 0.461, and RMSE of 0.679, which are 10.15%, 8.71%, and 4.36% lower than Support Vector Regression with Radial Basis Function kernel (SVR_RBF) respectively, and its predicted nitrogen content aligned well with true values. The proposed scheme integrating YOLOv11n and XGBoost offers a lightweight technical solution for nitrogen nutrition diagnosis and precise fertilization of greenhouse cucumbers. Full article

Stevia (Stevia rebaudiana Bertoni) is an important source of natural sweeteners. Since its commercial value depends on steviol glycosides, quality assessment primarily involves quantifying these compounds in leaves and shoots. While chromatography is the standard analytical method, it is labor-intensive and time-consuming; it involves multiple processing steps that may cumulatively introduce errors and remains relatively expensive. Although chromatography remains the most accurate method, this exploratory study evaluates the potential of using spectroscopy as an auxiliary method for the approximate assessment of steviol glycoside content. Leaf reflectance spectroscopy could be a simpler and more cost-effective approach. However, relationships between leaf reflectance and steviol glycoside content are indirect and mediated by physiological processes. To account for these indirect dependencies, cumulative UVB exposure was included as an additional feature because it influences both leaf optical properties and plant metabolic processes. A low-cost spectrometer was utilized as the measuring instrument. The study was conducted over a period of three months on 77 S. rebaudiana clones, divided into four groups based on their level of UVB irradiance (control without irradiation, 400, 600, and 800 μW m⁻²). Based on the collected data, linear and polynomial regression, Random Forest, XGBoost, PLSR, and ElasticNetCV models were trained. Cumulative UVB exposure was found to be the most important feature. Of the spectral features, the most informative for assessing the content of steviol glycosides were spectral indicators in the far-red and near-infrared (NIR) ranges. Our results indicate a detectable relationship, with Random Forest being the best-performing model and achieving a moderate predictive performance (R² = 0.66). Despite their limited predictive performance, the models demonstrate that leaf reflectance spectra combined with cumulative UVB exposure contain information related to steviol glycoside content. These findings support further investigation of remote sensing approaches for crop quality assessment. Full article

This study demonstrates single-channel fiber Bragg grating (FBG) sensing for relative vibration-state monitoring of a motor–support system under angle-dependent boundary conditions. A packaged FBG accelerometer-type sensing unit was mounted on the motor–support structure, and the reflected Bragg wavelength was recorded as a one-dimensional optical vibration response. Because the sensor was installed away from the rotating shaft, the measured wavelength fluctuation was interpreted as a coupled vibration-sensitive response of the motor, fixture, sensor package, bonding condition, and changing boundary state, rather than as a calibrated shaft speed or absolute acceleration signal. Adaptive variational mode decomposition (AVMD) was applied to track the time-varying narrowband spectral-response trajectory of the Bragg-wavelength signal. In parallel, raw wavelength windows were supplied to LSTM, 1D-CNN, and CNN–LSTM autoencoders to evaluate waveform departures from learned nominal fixed-angle behavior. The fixed-angle results showed stable but distinguishable optical vibration responses under different boundary states, whereas the dynamic angle-transition records produced local trajectory changes and alarm-candidate intervals. Baseline and autoencoder comparisons further clarified the trade-off between transition coverage and false-alarm tendency. The RMS threshold baseline was more sensitive to transition-related amplitude changes but produced more false alarms, whereas the CNN–LSTM autoencoder provided the most selective response among the tested autoencoder branches. The results are interpreted as task-specific evidence for relative vibration-state transition monitoring rather than as general motor fault diagnosis. Overall, the framework demonstrates a compact FBG-based route for relative vibration-state transition monitoring when speed references, dense sensor layouts, and labeled fault data are unavailable. Full article

Objectives: This study evaluates the protocol-level image quality and quantitative diffusion metrics of a clinically implemented deep-learning–reconstructed readout-segmented echo-planar imaging protocol with water-excitation spectral fat saturation (DL-rs-EPI with WEXfs) compared with conventional rs-EPI using spectral attenuated inversion recovery (SPAIR) at 3 T. Methods: Overall, 80 patients underwent breast magnetic resonance imaging (MRI) with both conventional rs-EPI with SPAIR and DL-rs-EPI with WEXfs protocols (b-values: 0, 800, and 1200 s/mm²). ROI-based relative image-quality metrics, including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and lesion contrast, were assessed at b = 800 and b = 1200 s/mm²; apparent diffusion coefficient (ADC) values were calculated using multi-b-value data. Fat suppression, background diffusion signal, lesion conspicuity, and artifact severity were qualitatively evaluated. A temperature-controlled diffusion phantom (CaliberMRI) was scanned; ADC values were compared with reference values at 24 °C. Results: DL-rs-EPI with WEXfs demonstrated higher ROI-based relative SNR estimates (b800: 5.79 vs. 5.28; b1200: 5.41 vs. 4.94; p < 0.001) and CNR estimates (b800: 3.35 vs. 3.12, p = 0.024; b1200: 3.67 vs. 3.37, p = 0.001), with unchanged lesion contrast. Tumor ADC values were comparable between protocols, whereas normal fibroglandular tissue ADC values were slightly higher, and ADC contrast increased with DL-rs-EPI with WEXfs. Phantom ADC values from both protocols closely matched reference values at 24 °C, without significant differences. DL-rs-EPI with WEXfs demonstrated more homogeneous fat suppression and reduced background diffusion signal, with comparable lesion conspicuity and artifact severity. Conclusions: The combined DL-rs-EPI with WEXfs protocol demonstrated improved qualitative and relative quantitative image quality while preserving tumor ADC measurements. As a protocol-level evaluation, these composite improvements support its clinical feasibility for high-quality breast DWI without implying the isolated effect of DL reconstruction alone. Full article

Emissivity is a parameter allowing the assessment of thermal/optical properties of active pharmaceutical ingredients (APIs). ε reflects radiative properties, changes with product aging, and correlates with surface characteristics. This study analyzed the thermal emissivity of commercial tablets—extended-release tablets with metformin hydrochloride (from two manufacturers: XR I and XR II), coated (Co) tablets with ibuprofen, and chewable (Ch) tablets with sodium aluminum dihydroxycarbonate—and compared unexpired vs. expired products. We used the ET 100 emissometer (Surface Optics Corporation, USA; IR range 1.5–21 µm) to measure directional–hemispherical reflectance (DHR) at 300 K, and on the basis of these values, directional thermal emissivity at 20° (DTE20) and 60° (DTE60) and hemispherical thermal emissivity (HTE) were calculated. Then, emissivity parameters were evaluated at 500 K, 800 K, and 1200 K. The DHR values at a 60° angle differed between unexpired and expired XR II tablets across all spectral bands and for XR I tablets, except in the 3.0–4.0 micron range. In turn, for DHR at 20°, high effect sizes were demonstrated between unexpired and expired Ch tablets for 1.5–2.0, 2.0–3.5, 4.0–5.0, and 5.0–10.5 microns. For the DHR at 60°, the high effect size between unexpired and expired Ch tablets was found at 1.5–2.0, 2.0–3.5, and 4.0–5.0 microns. At 300 K, XR I and XR II tablets showed comparable DTE20, DTE60, and HTE. The Ch tablets had higher DTE20 than XR I and XR II (0.968 vs. 0.954 and 0.958, respectively; p < 0.001) and Co tablets (0.968 vs. 0.930; p < 0.001). The Co tablets had the highest DTE60 mean values (0.941 vs. 0.926 for Ch, p < 0.001; 0.926 for XR I, p < 0.001; 0.932 for XR II, p = 0.001). The HTE value was the highest for Ch tablets (p < 0.001 vs. others). During thermal modeling of the emissivity parameters, all DTE20, DTE60, and HTE values decreased with temperature, reaching their lowest values at 1200 K. The largest relative decrease in HTE values (over 15%) between the standard measurement temperature of 300 K and the modeled temperature of 1200 K was found for Ch tablets. Tablets with different release profiles show distinct DTE20, DTE60, and HTE values, suggesting that emissivity may serve as a rapid, non-destructive screening tool that could support further pharmaceutical evaluation during storage. However, emissivity alone does not establish pharmaceutical quality, and the present findings should be interpreted as proof-of-concept rather than as validation of a stand-alone quality-control method. Full article

In this paper, L1 phonemic systems are discussed in the context of their impact on the pronunciation and perception of English diphthongs in PE, drawing on World Englishes and phonetic analysis. The study focuses on speakers whose native languages are Punjabi, Seraiki, Pashto, and Urdu, and examines how changes in local vowel inventories and glide processes influence diphthong production. The controlled production and perception tasks were done on eight English diphthongs by 40 adult speakers (10 speakers per L1 group). The formant trajectories (F1, F2), duration, and intensity were recorded by acoustic analyses, which are used to measure the variation that occurs as the articulatory glide occurs between vowel targets. Perception was measured using diphthong identification tasks to assess listeners’ sensitivity to dynamic spectral movement. The results indicate systematic L1-conditioned restructuring. Deviations were the most pronounced in diphthongs with significant vowel gliding, especially centering diphthongs, characterized by a decrease in spectral movement, a constriction in vowel space, and a general tendency toward monophthongization. Closing diphthongs were generally more stable in production; however, they still exhibited systematic L1-conditioned variation, particularly in glide magnitude, spectral direction, and temporal realization. These patterns of production were highly consistent with the results of perceptual production: the diphthongs with lesser acoustic movement were also found to be less accurately recognized, and diphthongs in their L1s and speakers of phonemically richer vowel systems had partial glide contrasts. The findings demonstrate that the variation in diphthongs in PE is systematic, reflecting predictable relationships between the L1 phonemic system, perceptual assimilation, and sociolinguistic experience. The findings highlight the pedagogical value of L1-sensitive pronunciation instruction and contribute to the phonetic description of Pakistani English as a systematic contact variety. Full article

Strawberry greenhouse cultivation is increasingly supported by sensing technologies, artificial intelligence (AI), and decision-support infrastructure, but their horticultural value depends on whether heterogeneous measurements can be translated into biologically meaningful crop states and practical management decisions. This review synthesizes strawberry phenotyping, multimodal sensing, AI-based crop-state interpretation, and supervised agentic coordination as a phenotyping-to-action framework for greenhouse strawberry cultivation. The reviewed studies show substantial progress in measuring and interpreting vegetative, reproductive, fruit-quality, stress-related, and environmental crop states through imaging, spectral, environmental, root-zone, and modeling approaches. However, much of the literature still emphasizes measurement accuracy, model performance, or infrastructure capability, whereas fewer studies validate whether AI-derived outputs improve crop response, management decisions, workflow, resource use, or production outcomes. The review therefore distinguishes sensing technologies for data acquisition and measurement from AI-based methods for interpretation and prediction, and examines how crop-state information can be connected to practical greenhouse decision making. It also compares established decision technologies, including expert systems, model predictive control, digital twins, and closed-loop coordination, with supervised agentic coordination as bounded decision-support concepts rather than as evidence of unrestricted autonomous control. Future work should emphasize phenotype-to-action validation, domain-aware benchmarking, and supervised deployment studies that connect model outputs with decision rules, crop outcomes, operational constraints, and grower oversight. By grounding sensing technologies and AI-based interpretation methods in crop-response validation, strawberry greenhouse systems can progress toward supervised, crop-state-driven decision support. Full article

Background: Iodine-based antimicrobial systems remain highly attractive due to their broad-spectrum activity; however, the clinical application of free iodine is limited by its instability and cytotoxicity. This study aimed to develop polyethylene glycol (PEG)-based hydrophilic ointment formulations containing a dextrin/polyvinyl alcohol/iodine complex (D/PVA/I) and to evaluate their physicochemical properties, antimicrobial activity, and cytotoxicity. Methods: Hydrophilic ointment formulations containing 2.5%, 5.0%, and 10.0% D/PVA/I were prepared using a PEG-based matrix composed of PEG 4000, PEG 400, and glycerol. Physicochemical characterization included organoleptic evaluation, pH measurement, rheological analysis, and UV–visible (Ultraviolet–visible) spectroscopy. Antimicrobial activity was assessed using agar diffusion and minimum bactericidal concentration (MBC) assays against Staphylococcus aureus, Escherichia coli, Enterococcus hirae, and Pseudomonas aeruginosa. Cytotoxicity was evaluated in Madin–Darby Canine Kidney (MDCK) cells using the MTT assay. Results: All formulations exhibited homogeneous semisolid structure and physiologically acceptable pH values (4.94–5.45). Rheological analysis demonstrated non-Newtonian pseudoplastic (shear-thinning) behavior. The flow behavior index (n) ranged from 0.03 to 0.33 according to the Ostwald–de Waele model, confirming shear-thinning characteristics, while viscosity increased with increasing D/PVA/I concentration. UV–visible spectroscopy confirmed the presence of triiodide ions (I_3⁻), characterized by absorption maxima at approximately 287 and 350 nm, indicating preservation of active iodine species within the PEG matrix, while placebo (blank) formulation analysis confirmed the absence of corresponding absorption bands, demonstrating that the PEG-based matrix does not contribute to the characteristic spectral features. The formulations demonstrated broad-spectrum antimicrobial activity, with MBC values ranging from 0.01 to 0.02 µg/mL. Cytotoxicity studies revealed moderate toxicity of the D/PVA/I complex (CC₅₀ = 0.82%) (50% cytotoxic concentration (CC₅₀) and significantly lower toxicity of the PEG-based ointment base (CC₅₀ = 18.38%). Conclusions: The developed PEG-based hydrophilic ointment formulations containing the D/PVA/I complex demonstrated favorable physicochemical characteristics, stability of iodine species, pronounced antimicrobial activity, and acceptable cytotoxicity profiles. These findings highlight the potential for the developed systems to be promising topical antimicrobial formulations. Full article

Radio-frequency identification (RFID)-based asset tracking in cabinet environments often encounters unpredictable detection caused by multipath fading, metal-induced interference, and tag placement sensitivity, which can render single-band systems unreliable under real-world conditions. This paper proposes a dual-band detection approach combining 915 MHz and 2.45 GHz to address these challenges through frequency diversity. Unlike designs confined to closely spaced UHF bands, this method uses a larger spectral gap to benefit from uncorrelated fading and distinct propagation properties. Theoretical analysis shows that dual-band detection significantly reduces joint failure probability under independent fading. The proposed framework is implemented using commercially available passive UHF tags at 915 MHz and an active RFID tag/reader at 2.45 GHz. The two systems are operated sequentially along the same guided scan path, and their detected tag-ID sets are combined offline using an OR-fusion rule without hardware-level synchronization. Across trials with varied scan speeds, power levels, reader distances, and tag placements, single-band detection fell below 50% under double-speed scanning at 200 cm, while the dual-band method remained above 70% and, in many cases, reached 100% reliability. Performance trends are further analyzed across individual scenarios, showing that 2.45 GHz links are less affected by metallic shadowing at close range, whereas 915 MHz links maintain more stable detection at longer distances. These findings are discussed in terms of deployment feasibility, indicating that the additional hardware and configuration requirements are offset by the measurable improvement in detection consistency, making the approach applicable for inventory tracking in logistics, warehousing, and industrial automation. Full article

This paper proposes and experimentally demonstrates a fiber ring laser (FRL) salinity sensing system based on a Sagnac loop (SL) formed by a tapered polarization-maintaining fiber (TPMF). The operating principle is that salinity modulates the birefringence of the polarization-maintaining fiber (PMF), causing a shift in the interference wavelength of the SL transmission spectrum, while the FRL narrows the optical spectrum and enhances the signal-to-noise ratio (SNR). In the experiment, the SL consists of a 20-cm-long PMF with a tapered waist diameter of 10.86 μm. Over the salinity range of 0‰ to 30‰, the sensitivity of the laser-based sensing system is 97 pm/‰, which agrees well with the 93 pm/‰ sensitivity obtained using a broadband light source (BBS), and the salinity exhibits a good linear relationship with the wavelength shift, with a coefficient of determination (R²) of 0.997. Meanwhile, the ring laser cavity improves the SNR of the sensing system from 22 dB to approximately 54 dB, and compresses the 3-dB bandwidth from 1.75 nm to 0.06 nm. Further adopting the support vector regression (SVR) algorithm for linear regression modeling of the spectral data, the results show that the mean absolute error (MAE) decreases from 0.50‰ to 0.04‰, the root mean square error (RMSE) decreases from 0.54‰ to 0.11‰, and R² reaches as high as 0.99988. To the best of our knowledge, this is the first work that combines salinity laser sensing with an artificial intelligence algorithm. The proposed sensor leverages the narrow linewidth and high SNR advantages of the FRL together with the high-precision linear fitting capability of the SVR algorithm, achieving significantly improved accuracy for salinity measurement compared to conventional spectral demodulation. Full article

A compact, low-profile dual-band feed network operating at 37–40 GHz (Ka-band) and 70–86 GHz (E-band) is presented for millimeter-wave backhaul applications. The proposed network integrates a quad-ridged orthomode transducer (OMT) and four ridge-waveguide diplexers into a three-layer all-metal stacked architecture, eliminating the cascaded inter-stage flanges of conventional feed chains and yielding a monolithic-like assembly that is mechanically robust and CNC-friendly for mass production. Stepped-impedance matching stubs in the OMT junction provide broadband matching across the widely separated bands, while compact ridge-waveguide T-junction diplexers, comprising stepped-impedance low-pass filters and rectangular high-pass paths, perform the spectral separation. Back-to-back measurements of the fabricated prototype demonstrate an insertion loss below 0.6 dB across both bands. The measured VSWR at the four output ports remains below 1.5 across both bands, and the port-to-port isolation exceeds 32 dB at the Ka-band and 45 dB at the E-band. The proposed network thus offers a highly integrated, low-loss solution for next-generation dual-band mmWave links. Full article

Background/Objectives: With the increasing incidence of drug counterfeiting and the emergence of personalized medicine, the need for unique marking of solid dosage forms, e.g., tablets, has attracted considerable interest in the current research and development landscape. Besides traditional printing methods, laser marking offers several advantages, as it eliminates the need for organic solvents and enables the generation of precise patterns. However, laser exposure may raise safety concerns regarding the stability of photosensitive drugs in the irradiated dosage forms. Therefore, the aim of the present study was to test the photoprotective effect of titanium dioxide (TiO₂) and its various alternatives, e.g., talc, calcium carbonate (CaCO₃), zinc oxide (ZnO), and black iron oxide (Fe₃O₄), alongside a ready-to-use reference formulation, Opadry^® Brown, which contains TiO₂ (titanium-containing, TC) on nifedipine, a light-sensitive model drug. Methods: Laser marking or short-term laser ablation at different wavelengths (193 nm, 248 nm, 532 nm, and 781 nm) was applied to different coating formulations. As a positive control, prolonged exposure to daylight was applied. The properties and photostability of these formulations were evaluated using several analytical methods (i.e., surface profilometry, Raman spectroscopy, and high-performance liquid chromatography (HPLC)). Results: The TiO₂, ZnO, Fe₃O₄, and Opadry^® TC Brown coatings maintained their color during the long-term study under all conditions. Furthermore, the prepared formulations exhibited different ablation depths and morphological changes depending on the coating and laser type. HPLC measurements confirmed significant differences in the protective ability of various pigments against sunlight and different types of lasers. Nevertheless, the obtained Raman spectra were not in complete agreement with HPLC results, which can be attributed to spectral overlap between key nifedipine degradation markers and excipient signals in the tablet core. Conclusions: Overall, laser treatment of tablets containing photosensitive drugs may induce API decomposition; however, this effect can be minimized or avoided by careful selection of the appropriate combination of laser type and photoprotective pigment. Under the applied experimental conditions, Ti:Sa laser treatment was associated with the lowest degree of nifedipine degradation among all formulations, while ZnO-containing coatings demonstrated the most consistent photoprotective performance against the majority of the tested laser types, while Fe₃O₄-containing coatings provided superior protection during prolonged sunlight exposure and Nd:YAG laser irradiation. Full article

Surface solar ultraviolet (UV) radiation represents an essential component of shortwave solar radiation, with important implications for atmospheric chemistry and climate studies. Reliable, high-quality records of surface solar UV radiation are essential for UV-related research and applications; however, ground-based UV observations remain sparse worldwide. This study presents a novel broadband parametric model, based on physical principles, for estimating solar UV irradiance ($0.280–0.400 \mu \mathrm{m}$) under clear-sky conditions. The model is computationally efficient and suitable for practical applications. The proposed approach is based on the SMARTS2 spectral radiative transfer model and employs an interdependent integration scheme to derive broadband UV irradiance from spectrally resolved shortwave radiation. The model performance is evaluated against high-quality measurements from the Baseline Surface Radiation Network (BSRN) and compared with an established parameterization. The proposed model demonstrates improved performance at both validation sites, reducing the mean nRMSE from 8.88% to 7.64% at Izaña and from 60.69% to 29.24% at Payerne, while also substantially decreasing the bias under more challenging atmospheric conditions, although the nRMSE at Payerne remains relatively high. These results highlight the potential of the proposed approach as an efficient and physically consistent tool for clear-sky UV irradiance estimation. Full article

Surface-enhanced Raman scattering (SERS) offers a powerful route for biomolecular detection because it combines molecular specificity with high sensitivity, rapid optical readout, and multiplexing capability. In real biological samples, however, analytical performance is rarely determined by signal enhancement alone. Biofluids such as serum, plasma, saliva, urine, and interstitial fluid contain complex biomolecular mixtures that interfere with target capture, spectral response, and data interpretation. A practical SERS biosensor must therefore localize targets, stabilize spectral responses, tolerate matrix-induced variation, and convert complex spectra into reliable analytical information. This review discusses recent progress in SERS biosensing from an integrated system perspective, with particular focus on artificial intelligence/machine learning (AI/ML)-assisted interpretation. Direct label-free SERS provides chemically transparent readouts but is limited by stochastic adsorption, hotspot heterogeneity, and spectral variation in complex samples. Bio-recognition interfaces improve target localization, while signal-transduction strategies based on nanotags, immunoassays, clustered regularly interspaced short palindromic repeats (CRISPR) systems, nanozymes, and lateral-flow formats decouple molecular recognition from spectral generation. Digital SERS further improves measurement robustness by converting fluctuating intensities into countable, event-based outputs. AI/ML-assisted analysis can support full-spectrum classification, calibration transfer, explainability, and patient-level decision-making. We frame AI/ML-assisted SERS biosensing as an integrated architecture connecting substrate design, interface engineering, signal transduction, digital measurement, and clinical validation. Future progress will depend as much on validation-ready workflows as on plasmonic enhancement itself, especially for systems intended to operate across different samples, instruments, and clinical settings. Full article

Full-duplex acoustic telemetry is important for real-time bidirectional measurement and control in intelligent coiled-tubing operations, but its reliability in deep horizontal wells is limited by long-range dispersion, asymmetric flow-induced noise, and severe near-end self-interference. This study proposes an orthogonal frequency-band planning and synergistic interference suppression method for full-duplex acoustic communication in coiled tubing. A dispersion model and an asymmetric attenuation model were first established for a fluid-filled coiled-tubing cylindrical-shell waveguide to characterize the physical transmission constraints. A multiphysics multi-objective cost function was then formulated by considering dispersion flatness, channel attenuation, asymmetric noise adaptability, and spectral isolation, and an improved simulated annealing algorithm was used to optimize the uplink and downlink frequency bands. In addition, a three-stage suppression architecture integrating mechanical decoupling, physical-layer frequency isolation, and CEEMDAN–wavelet denoising was developed to reduce self-interference and residual nonstationary noise. Full-scale experiments on a 457.2 m coiled-tubing surface circulation system showed that the proposed method improved the output signal-to-interference-plus-noise ratio from −15 dB to 18.5 dB and maintained a bit error rate below 1.2 × 10⁻⁴ at 400 L/min. These results indicate that the proposed approach can enhance the robustness of full-duplex acoustic telemetry under strong flow-induced noise. Full article