Search Results (2,090)

China’s liquor industry continues to steadily expand and develop. The industry is currently transforming, shifting its focus from scale to quality and efficiency. This transformation is significantly increasing the demand for quality and safety testing. Currently, the testing system relies mainly on manual operation or traditional mechanical equipment. Technical bottlenecks include low testing efficiency, a significant imbalance in the cost–benefit ratio, and difficulty meeting the modern industry’s dual technical index requirements of testing accuracy and systematicity. In this context, the innovative research and development of new detection technology is key to promoting technological upgrades in the liquor industry. Near-infrared (NIR) spectroscopy is a core, competitive analytical method for non-destructive wine quality testing due to its technical advantages, such as non-destructive analysis, real-time online detection, and the absence of sample pretreatment requirements. This study systematically elaborates on the optical principle and detection mechanism of NIR spectroscopy and explores the application paradigm of chemometrics in spectral data analysis. This study covers the quantitative analysis of alcoholic strength, the determination of main ingredient content (sugar, acidity, esters, etc.), the construction of trace flavor substance fingerprints, the authentication and origin tracing of alcoholic products, and the monitoring of wine aging quality dynamics, among other key technology areas. Additionally, we review the fusion and innovation trends of artificial intelligence and big data technology, the R&D progress of miniaturized testing equipment, and the technical bottlenecks of spectral modeling and algorithm optimization. We also make scientific predictions about the evolution path of this technology and its industrial application prospects. Full article

In this work, a unique approach was used to synthesise black coatings on aluminium alloys (AA) 6061 and 7075 for applications in the aerospace field. In detail, plasma electrolytic oxidation (PEO) technology was used, maintaining the voltage constant at a relatively low value (V_max ≤ 292 V) during the process. NaVO₃ additive was used in the silicate-based electrolyte to obtain a black colour. The coatings were characterised by SEM-EDS, XPS, XRD, VIS-NIR spectroscopy, and EIS. The presence of vanadium oxides in the PEO coatings was detected by EDS, XPS, and XRD analyses. PEO coatings on AA7075 produced with 10 g/L of NaVO₃ exhibited exceptional optical characteristics, with a solar absorptance value of 95.3% in the VIS-NIR spectrum (wavelength range of 400–2000 nm). All the coatings improved the corrosion performances of the tested AA6061 and AA7075 by two or three orders of magnitude in 3.5 wt. % aqueous NaCl. Moreover, there was no sign of delamination, cracks, or any visible changes on coatings after thermal shock, performed by cycling samples between two extreme temperatures, −196 °C and 150 °C, respectively. Full article

Traditional culture plays a vital role in shaping national identity and emotional belonging, making it imperative to explore innovative strategies for its digital preservation and engagement. This study investigates how interaction design in cultural digital games influences users’ emotional experiences and cultural understanding. Centering on the Chinese intangible cultural heritage puppet manipulation, we developed an interactive cultural game with three modes: gesture-based interaction via Leap Motion, keyboard control, and passive video viewing. A multimodal evaluation framework was employed, integrating subjective questionnaires with physiological indicators, including Functional Near-Infrared Spectroscopy (fNIRS), infrared thermography (IRT), and electrodermal activity (EDA), to assess users’ emotional responses, immersion, and perception of cultural content. Results demonstrated that gesture-based interaction, which aligns closely with the embodied cultural behavior of puppet manipulation, significantly enhanced users’ emotional engagement and cultural comprehension compared to the other two modes. Moreover, fNIRS data revealed broader activation in brain regions associated with emotion regulation and cognitive control during gesture interaction. These findings underscore the importance of culturally congruent interaction design in enhancing user experience and emotional resonance in digital cultural applications. This study provides empirical evidence supporting the integration of cultural context into interaction strategies, offering valuable insights for the development of emotionally immersive systems for intangible cultural heritage preservation. Full article

Rapid, accurate, and sustainable methods for assessing soil properties are essential for environmental management. This study proposes a green analytical approach for the direct determination of soil texture and organic matter using benchtop (1250–2500 nm) and portable (900–1700 nm) near-infrared (NIR) spectrophotometers combined with multivariate calibration. Partial least squares (PLS1 and PLS2) regression models were developed using regional calibration samples and applied to additional samples from the same area. Both individual (PLS1) and simultaneous (PLS2) predictions of clay, sand, silt, and organic matter contents were evaluated. Synergy interval PLS (siPLS) algorithms were used to optimize variable selection. For clay, RMSEP was 2.1% (benchtop) and 2.0% (portable), with RPD values around 2.0. Simultaneous prediction of sand content yielded better results (RPD = 1.3 benchtop; 0.8 portable). Silt prediction showed low accuracy (RPD < 1.0). Organic matter was best predicted by siPLS1 using the benchtop device (RPD = 1.5), followed by portable PLS2 (RPD = 1.2). Benchtop and portable NIR approaches proved satisfactory for direct determination of soil properties. PLS1 models offered greater specificity, while siPLS enhanced accuracy through variable selection. PLS2 models enabled efficient simultaneous predictions. Both devices meet white analytical chemistry principles, aligning performance with sustainability, thus demonstrating that accurate and environmentally responsible soil analysis can be achieved without compromising analytical efficiency. Full article

Chronic pain is a dynamic, brain-wide condition that eludes effective management by conventional, static treatment approaches. Transcutaneous Electrical Nerve Stimulation (TENS), traditionally perceived as a simple and generic modality, is on the verge of a significant transformation. Guided by advances in brain-state decoding and adaptive algorithms, TENS can evolve into a precision neuromodulation system tailored to individual needs. By integrating multimodal neuroimaging—including the spatial resolution of functional magnetic resonance imaging (fMRI), the temporal sensitivity of an Electroencephalogram (EEG), and the ecological validity of functional near-infrared spectroscopy (fNIRS)—with real-time machine learning, we envision a paradigm shift from fixed stimulation protocols to personalized, closed-loop modulation. This comprehensive review outlines a translational framework to reengineer TENS from an open-loop device into a responsive, intelligent therapeutic platform. We examine the underlying neurophysiological mechanisms, artificial intelligence (AI)-driven infrastructures, and ethical considerations essential for implementing this vision in clinical practice—not only for chronic pain management but also for broader neuroadaptive healthcare applications. Full article

Focusing on the characteristic tea resource Zijuan tea, this study addresses the difficulty of grading on production lines and the complexity of quality evaluation. On the basis of the fusion of near-infrared (NIR) spectroscopy and visual features, a novel method is proposed for classifying different tenderness levels and quantitatively assessing key anthocyanin components in Zijuan tea fresh leaves. First, NIR spectra and visual feature data were collected, and anthocyanin components were quantitatively analyzed using UHPLC-Q-Exactive/MS. Then, four preprocessing techniques and three wavelength selection methods were applied to both individual and fused datasets. Tenderness classification models were developed using Particle Swarm Optimization–Support Vector Machine (PSO-SVM), Random Forest (RF), and Convolutional Neural Networks (CNNs). Additionally, prediction models for key anthocyanin content were established using linear Partial Least Squares Regression (PLSR), nonlinear Support Vector Regression (SVR) and RF. The results revealed significant differences in NIR spectral characteristics across different tenderness levels. Model combinations such as TEX + Medfilt + RF and NIR + Medfilt + CNN achieved 100% accuracy in both training and testing sets, demonstrating robust classification performance. The optimal models for predicting key anthocyanin contents also exhibited excellent predictive accuracy, enabling the rapid and nondestructive detection of six major anthocyanin components. This study provides a reliable and efficient method for intelligent tenderness classification and the rapid, nondestructive detection of key anthocyanin compounds in Zijuan tea, holding promising potential for quality control and raw material grading in the specialty tea industry. Full article

Accurate monitoring of mastectomy skin flap (MSF) perfusion is critical, especially in patients with darker skin pigmentation at higher risk of misdiagnosed tissue ischemia. Near-infrared spectroscopy (NIRS) devices, such as SnapshotNIR, offer real-time tissue oxygen saturation measurements (StO₂), but their accuracy across skin pigmentation levels remains unexplored. This quasi-experimental study included 33 patients undergoing mastectomy. MSF edge ΔStO₂, defined as preoperative minus postoperative StO_2, was measured using SnapshotNIR device (Kent Imaging, Calgary, AB, Canada) pre- and post-mastectomy. By definition, a positive ΔStO₂ indicates a decrease in tissue oxygenation, while a negative ΔStO₂ indicates an increase relative to baseline. ΔStO₂ was analyzed against Fitzpatrick scores to assess skin pigmentation impact on measurement accuracy. ΔStO₂ (mean ± SD) progressively decreased with increasing Fitzpatrick score: 14.0 ± 22.98 for score 1, 6.87 ± 17.45 for score 2, −3.13 ± 6.89 for score 3, and −40.75 ± 22.27 for score 5, indicating a shift from positive to negative O₂ change. Fitzpatrick scores significantly correlated with ΔStO₂ (ρ = −0.392, p = 0.016). ANOVA confirmed differences (p = 0.008), with Tukey’s post hoc testing showing significant differences between Fitzpatrick scores 1 and 5 (p = 0.022), and 2 and 5 (p = 0.006). SnapshotNIR technology demonstrated measurable sensitivity for detecting changes in StO₂ and predicting ischemia; however, NIRS-based devices may overestimate oxygenation in darker skin pigmentation, highlighting a need for device calibration to improve accuracy across skin tones. Full article

Non-invasive, continuous monitoring of carotid artery hemodynamics may provide valuable insights on cerebral blood perfusion (CBP). Near-infrared spectroscopy (NIRS) is a non-invasive modality that may be a good candidate for real-time carotid artery monitoring. We designed a wearable NIRS system to monitor the left and right radial and carotid arteries in 20 healthy subjects. The changes in total hemoglobin concentration (HbT) and tissue oxygen saturation (StO₂) in all 80 arteries were continuously monitored in response to changes in oxygen supply. Wilcoxon non-parametric equivalence testing was used to compare changes in the radial (reference) and carotid arteries. The system-derived HbT and StO₂ trends matched the expected physiological responses over time in the radial and carotid arteries. The mean peak-to-peak amplitude [uM] of HbT during sustained deep breathing was practically equivalent between the left radial (0.9 ± 0.8) and left carotid (1.6 ± 1.1) arteries (p = 0.01). The mean peak-to-peak amplitude [%] of StO₂ was practically equivalent between the left radial (0.3 ± 0.2) and left carotid (0.3 ± 0.2) arteries (p < 0.001) and the right radial (0.4 ± 0.5) and right carotid (0.5 ± 0.4) arteries (p = 0.001). These findings indicate that NIRS may be a good option for monitoring the carotid arteries to track changes in CBP. Full article

Equine-assisted services (EAS) are used for civilian and military trauma survivors to reduce depression and posttraumatic stress symptoms. While early scientific evidence supports the benefits of EAS, the neurophysiological mechanisms underlying these benefits are unknown. The specific aims of this exploratory study were to determine (1) whether functional near-infrared spectroscopy (fNIRS) neuroimaging can be used to explore neural responses of EAS veteran participants and (2) the correlation between neural responses and psychological outcomes of the participants interacting with equines. Fifteen veterans participated in a 2-day EAS program consisting of four randomized activities. An fNIRS sensor cap was used to measure the oxygenated (O₂Hb), deoxygenated (hHb), and total hemoglobin (tHb) of the participants during each activity. The results indicated no significant differences for O₂Hb and tHb across the visits or activities, however, a significant difference in hHb was observed. There was an increase in hHb during the activities that included an equine, which indicated a greater cognitive load and attention. Further, data from pre-/post-psychometric assessments showed a significant improvement in participants’ trait anxiety, psychological flexibility, and positive and negative affect after interacting with the horse. Preliminary data revealed a potential association between the cognitive attention and psychological health of participants during an EAS session. Full article

The online rapid classification of multi-cultivar watermelon, including seedless and seeded types, has far-reaching significance for enhancing quality control in the watermelon industry. However, interference in one-dimensional spectra affects the high-accuracy classification of multi-cultivar watermelons with similar appearances. This study proposed an innovative method integrating Gramian Angular Field (GAF), feature fusion, and Squeeze-and-Excitation (SE)-guided convolutional neural networks (CNN) based on VIS-NIR transmittance spectroscopy. First, one-dimensional spectra of 163 seedless and 160 seeded watermelons were converted into two-dimensional Gramian Angular Summation Field (GASF) and Gramian Angular Difference Field (GADF) images. Subsequently, a dual-input CNN architecture was designed to fuse discriminative features from both GASF and GADF images. Feature visualization of high-weight channels of the input images in convolutional layer revealed distinct spectral features between seedless and seeded watermelons. With the fusion of distinguishing feature information, the developed CNN model achieved a classification accuracy of 95.1% on the prediction set, outperforming traditional models based on one-dimensional spectra. Remarkably, wavelength optimization through competitive adaptive reweighted sampling (CARS) reduced GAF image generation time to 55.19% of full-wavelength processing, while improving classification accuracy to 96.3%. A better generalization of the model was demonstrated using 17 seedless and 20 seeded watermelons from other origins, with a classification accuracy of 91.9%. These findings substantiated that GAF-enhanced feature fusion CNN can significantly improve the classification accuracy of multi-cultivar watermelons, casting innovative light on fruit quality based on VIS-NIR transmittance spectroscopy. Full article

The instability of many volatile organic compounds (VOCs) limits their usage in different fragrance carriers and products. In scratch-and-sniff applications, VOCs are bound so strongly that release cannot happen without an external trigger. On the other hand, other fixatives like cyclodextrins release unstable volatile molecules too rapidly. We engineered biodegradable gelatin films whose release profile can be tuned by glycerol plasticization and alkaline protease degradation. Digitalized VOC release profiles acquired with the described near-real-time analysis toolkit are digital twins that replicate the behavior of the evaluated films in silico. Seven formulations were cast from 10% gelatin containing D-limonene, glycerol (5%, 20%), protease-C 30 kU mL⁻¹, and samples with additional water to establish a higher hydromodule for protease catalytic activity. Release profiles were monitored for nine days at 23 ± 2 °C in parallel by metal-oxide semiconductor (MOS) e-noses, gravimetric weight loss, and near-infrared measurements (NIR). These continuous measurements were cross-checked with gel electrophoresis, FTIR spectroscopy, hardness tests, and sensory intensity ratings. Results showed acceleration of VOC release by enzymatic treatment during the first days, as well as overall impact on the release profile. Differences in low and high glycerol films were observed, and principal component analysis of NIR spectra separated low and high glycerol groups, mirroring the MOS and FTIR data. Usability of MOS data was explored in comparison to more biased and subjective intensity results from sensory panel evaluation. Overall, the created toolkit showed good cross-checked results and enabled the possibility for close to real-time analysis for bio-based VOC carriers. Full article

Honey is recognized as a nutritionally rich and functional option, often used as a natural sweetener due to its content of glucose, fructose, vitamins, minerals, enzymes and antioxidants. Its antioxidant, antibacterial and anti-inflammatory properties are well known. Recently, interest has grown in functional honey enriched with bioactive plant components, such as extracts of rosemary, lavender, oregano, and sage, which can enhance phenolic content and antioxidant capacity. However, such enrichment may alter honey’s sensory characteristics and introduce contaminants, including heavy metals, necessitating comprehensive quality assessment. This study aimed to evaluate the chemical and functional quality of honey enriched with aromatic plant extracts from Kosovo, Albania, and North Macedonia, using an integrated approach. The research included the quantification of total phenolic compounds (TPCs), analysis of heavy metal content, and the application of near-infrared (NIR) spectroscopy with two devices (laboratory and portable). The results showed that geographical origin and herbal additions significantly affect TPC and heavy metal concentrations. Honey from Kosovo had the highest TPC, while Albanian honey showed higher concentrations of iron and nickel. Enrichment with oregano and rosemary significantly increased TPC and, levels of heavy metals such as lead and nickel. These findings underscore both the nutritional potential and safety considerations of enriched honey products. Accurate, non-destructive techniques like NIR spectroscopy offer valuable tools for quality control; however, further work is needed to evaluate sensory acceptance and long-term safety of enriched honey. Full article

The development of compact, CMOS-compatible gas sensors is critical for advancing real-time environmental monitoring and industrial diagnostics. In this study, we present a detailed numerical investigation of integrated photonic waveguide designs—such as ridge and slot—optimized for overtone-based gas spectroscopy in the near-infrared range. By evaluating both the evanescent-field confinement and curvature-induced losses across multiple silicon-on-insulator platforms, we identify optimal geometries that maximize light–analyte interactions while minimizing bending attenuation. Our findings provide essential design guidelines for high-performance, low-footprint gas sensors. Full article

Background: In recent years, the use of compression garments has expanded into sports contexts to enhance performance and optimize post-exercise recovery. One of the most investigated physiological variables for evaluating their effectiveness has been peripheral muscle oxygenation, a crucial indicator of physical performance. However, studies regarding the effects of compression on the upper limbs remain limited and the topic is insufficiently explored. Therefore, the aim of this study was to analyze the effects of compression garments on muscle oxygen saturation (SmO₂) recovery in the biceps brachii after brief maximal isometric contractions. Specifically, physiological responses were compared between two conditions (with and without compression garments), hypothesizing that compression would promote faster and more efficient muscle reoxygenation compared to traditional clothing. Methods: Fourteen male participants (mean age: 24.4 years; mean height: 176.75 cm; mean body mass: 73 kg) performed three 10 s isometric contractions separated by 180 s passive recovery periods under compression (CG) and non-compression (noCG) conditions. SmO₂ was monitored using near-infrared spectroscopy (NIRS), assessing Half-Recovery Time (HRT), Overshoot Amplitude, Initial Slope, and the time constant τ. Results: The compression garment significantly reduced HRT (CG 8.52 s vs. noCG 10.21 s; p = 0.035), significantly increased Overshoot Amplitude (CG 21.40% vs. noCG 7.92%; p = 0.0014), resulted in a greater Initial Slope (CG 2.43%/s vs. noCG 2.09%/s; p = 0.027), and significantly reduced the time constant τ (CG 11.68 s vs. noCG 21.04 s; p < 0.001). Conclusions: The use of compression garments demonstrated significant improvements in post-exercise muscle oxygen saturation, suggesting potential advantages for muscle recovery and positive implications for athletic performance. Full article

Neurologic complications remain a major cause of morbidity in patients undergoing surgical repair of acute type A aortic dissection (ATAAD). Near-infrared spectroscopy (NIRS) is used for continuous, noninvasive monitoring of cerebral oxygenation during cardiopulmonary bypass; however, its utility in predicting perioperative stroke remains inadequately defined. A retrospective cohort study was conducted in 175 patients who underwent ATAAD repair between 2015 and 2023. Patients were stratified by the occurrence of perioperative stroke (n = 47, 26.9%). Intraoperative NIRS data, including cerebral regional oxygen saturation (crSO₂) values at key procedural timepoints and signal variability with band power and crest factor, were analyzed in conjunction with demographic, anatomic, and postoperative variables. Patients with stroke exhibited significantly lower minimum NIRS values during deep hypothermic circulatory arrest (DHCA) (left: 46.7 (15.7–69.4) vs. 52.2 (22.0–81.6); right: 47.0 (23.3–78.5) vs. 56.3 (20.2–85.0); p = 0.03 and p < 0.01). Within the stroke group, NIRS signal variability was significantly greater (crest factor and standard deviation; p < 0.05) and showed blunted recovery post-DHCA. crSO₂ values below 50% were more frequent in the stroke group (p = 0.04). Right common carotid artery dissection was more prevalent in the stroke group (40% vs. 23%, p = 0.04). ICU length of stay was significantly increased in patients with stroke. Cerebral desaturation and NIRS signal instability during DHCA are significantly associated with perioperative stroke in ATAAD repair. These findings support the prognostic value of intraoperative cerebral oximetry in detecting critical ischemic thresholds and identifying at-risk perfusion patterns. Full article