Search Results (2,957)

Non-destructive estimation of high-temperature stress effects on tobacco plants is crucial for both scientific research and practical applications. Normalized difference vegetation index (NDVI), chlorophyll index, and spectra in the range of 900–1700 nm of Burley, Oriental, and Virginia tobacco plants under control and high-temperature stress conditions were measured using portable instruments. NDVI and chlorophyll index measurements indicate that young leaves of all tobacco types are tolerant to high temperatures. In contrast, the older leaves (the fifth leaf) showed increased sensitivity to heat stress. The chlorophyll content of these leaves decreased by 40 to 60% after five days of stress, and by the seventh day, the reduction reached 80% or more in all plants. The vegetative index of the fifth leaf also decreased on the seventh day of stress in all tobacco types. Differences in near-infrared spectra were observed between control, stressed, and recovered plants, as well as among different stress days, and among tobacco lines. The most significant differences were in the 1300–1500 nm range. The first characterization of heat-induced changes in the molecular structure of water in tobacco leaves using an aquaphotomics approach was conducted. Models for determining days of high-temperature treatment based on near-infrared spectra achieved a standard error of cross-validation (SECV) from 0.49 to 0.62 days. The total accuracy of the Soft Independent Modeling of Class Analogy (SIMCA) classification models of control, stressed, and recovered plants ranged from 91.0 to 93.6% using leaves’ spectra of the first five days of high-temperature stress, and from 90.7 to 97.7% using spectra of only the fifth leaf. Similar accuracy was obtained using Partial Least Squares–Discriminant Analysis (PLS-DA). Near-infrared spectroscopy and aquaphotomics can be used as a fast and non-destructive approach for early detection of stress and additional tools for investigating high-temperature tolerance in tobacco plants. Full article

Diabetes is a developing global health concern that cannot be cured, necessitating frequent blood glucose monitoring and dietary management. Photoacoustic Spectroscopy (PAS) in the mid-infrared (MIR) region has recently emerged as a viable noninvasive blood glucose monitoring technique. However, MIR-PAS confronts significant challenges: (i) Water absorption, which reduces light penetration, and (ii) interference from other blood components. This paper systematically analyzes the background of photoacoustic signal generation and proposes a differential PAS (DPAS) in the MIR region for removing the background signals arising from water and other interfering components of blood, which improves the overall detection sensitivity. A detailed mathematical model with an explanation for choosing two suitable MIR quantum cascade lasers for this differential scheme is presented here. For single-wavelength PAS (SPAS), a detection sensitivity of $1.537$ µPa mg⁻¹ dL was obtained from the proposed model. Alternatively, $2.333$µPa mg⁻¹ dL detection sensitivity was found by implementing the DPAS scheme, which is about 1.5 times higher than SPAS. Moreover, DPAS facilitates an additional parameter, a differential phase shift between two laser responses, that has an effective correlation with the glucose concentration variation. Thus, MIR-based DPAS could be an effective way of monitoring blood glucose levels noninvasively in the near future. Full article

Resting-state functional connectivity (rsFC) provides insight into the intrinsic organization of brain networks and is increasingly recognized as a sensitive marker of age-related neural changes. Functional near-infrared spectroscopy (fNIRS) offers a portable and cost-effective approach to measuring rsFC, including in naturalistic settings. However, its sensitivity to age-related alterations in network topology remains poorly characterized. Here, we applied graph-based analysis to resting-state fNIRS data from 57 healthy participants, including 26 young adults (YA, 18–30 years) and 31 older adults (OA, 50–77 years). We observed that older adults exhibited a marked attenuation of low-frequency oscillation (LFO) power across all hemoglobin contrasts, corresponding to a 5–6-fold reduction in spectral power. In addition, network analysis revealed altered topological organization under matched sparsity conditions, characterized by reduced degree heterogeneity and increased segregation in older adults, with the strongest differences observed in the default mode (DMN), auditory, and frontoparietal control (FPC) networks. Network visualizations further indicated a shift toward more right-lateralized and posterior hub organization in older adults. Together, the coexistence of reduced oscillatory power and increased connectivity suggests that fNIRS-derived rsFC reflects combined neural and non-neural hemodynamic influences, including increased coherence arising from age-related vascular and systemic physiological processes. Overall, our findings demonstrate that fNIRS is sensitive to age-related changes in large-scale hemodynamic network organization. At the same time, sensitivity to non-neural hemodynamics highlights the need for cautious interpretation, but it may provide complementary, clinically relevant signatures of aging-related changes. Full article

Near-infrared (NIR) spectroscopy has emerged as a pivotal non-destructive analytical technique within the cheese industry, offering rapid and precise insights into the chemical composition and quality attributes of various cheese types. This review explores the evolution of NIR spectral sensors, highlighting key technological advancements and their integration into cheese production processes as well as final products already in markets. In addition, the review discusses challenges such as calibration complexities, the influence of sample heterogeneity and the need for robust data and interpretation models through spectroscopy coupled with AI methods. The future potential of NIR spectral sensors, including real-time in-line monitoring and the development of portable devices for on-site analysis, is also examined. This review aims to provide a critical assessment of current NIR spectral sensors and their impact on the cheese industry, offering insights for researchers and industry professionals aiming to enhance quality control and innovation in cheese production, as well as authenticity and fraud studies. The review concludes that the integration of advanced NIR spectroscopy with AI represents a transformative approach for the cheese industry, enabling more accurate, efficient and sustainable quality assessment practices that can strengthen both production consistency and consumer trust. Full article

In this work, an archeological adhesive collected at Cantagrilli (near Florence) was chemically analyzed by applying gas chromatography/mass spectrometry, infrared spectroscopy, and nuclear magnetic resonance spectrometry combined with the archeobotanical investigations. Data identify triterpenes, aged anhydride, benzoyl resin, and gelatinized starch in the sample. The multi-analytical approach allowed us to identify some molecular compounds, as well as their state of chemical decomposition (especially by applying the mass spectrometry techniques). On the other hand, archeobotanical measurements have provided useful but not unequivocal information regarding the possible origin of triterpenes from some terrestrial plants, combined with the presence of microorganisms and transformed chemicals (such as starch modified into gelatin). All this information is very useful to Prehistoric Archeologists for understanding the cultural processes and technologies used by ancient populations. Full article

The Sar-e-Sang lapis lazuli deposit has a mining history exceeding 5000 years, producing the world’s finest lapis lazuli. Recently, gem-quality forsterite has been discovered in the marble containing spinel, dolomite, and phlogopite at the periphery of the lapis lazuli ore body at the Pitawak mine, located east of the Sar-e-Sang deposit. The mineral assemblage indicates that the protolith of this marble is dolomite with aluminous and siliceous components. These forsterite crystals occur as colorless, transparent anhedral grains, exhibiting distinct red fluorescence under 365 nm ultraviolet light. To investigate the gemological and spectroscopic characteristics of the Pitawak mine forsterite, this study conducted and analyzed data from basic gemological analysis, electron probe microanalysis (EPMA), Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), ultraviolet–visible absorption spectroscopy (UV-VIS), Fourier-transform infrared spectroscopy (FTIR), laser Raman spectroscopy (RAMAN), and photoluminescence spectroscopy (PL) on four forsterite samples from the Pitawak mine. The analysis results reveal that the samples indicate a composition close to ideal forsterite with a crystal chemical formula of (Mg_2.00Fe_0.02)_Σ2.02Si_0.99O₄. The trace elements present include Fe, Mn, Ca, and minor amounts of Cr and Ni. The UV-VIS spectroscopy results show that the samples possess high transmittance across the visible light range with very weak absorption bands, contributing to the colorless and transparent appearance of Pitawak mine forsterite. This phenomenon is attributed to the extremely low content of chromophoric elements, which have a negligible effect on the forsterite’s color. PL spectroscopy indicates that the red fluorescence of the samples is caused by an emission peak near 642 nm. This emission peak arises from the spin-forbidden ⁴T₁ → ⁶A₁ transition of Mn²⁺ ions situated in octahedral sites within the forsterite structure. Full article

We present E-CAHORS—a compact mid-infrared open-path diode-laser spectrometer designed for the simultaneous measurement of carbon dioxide, methane, and water vapor concentrations in the near-surface atmospheric layer. These measurements, combined with simultaneous data from a three-dimensional anemometer, can be used to determine fluxes using the eddy-covariance method. The instrument utilizes two interband cascade lasers operating at 2.78 µm and 3.24 µm within a novel four-pass M-shaped optical cell, which provides high signal power and long-term field operation without requiring active air sampling. Two detection techniques—tunable diode laser absorption spectroscopy (TDLAS) and a simplified wavelength modulation spectroscopy (sWMS)—were implemented and evaluated. Laboratory calibration demonstrated linear responses for all gases (R² ≈ 0.999) and detection precisions at 10 Hz of 311 ppb for CO₂, 8.87 ppb for CH₄, and 788 ppb for H₂O. Field tests conducted at a grassland site near Moscow showed strong correlations (R = 0.91 for CO₂ and H₂O, R = 0.74 for CH₄) with commercial LI-COR LI-7200 and LI-7700 analyzers. The TDLAS mode demonstrated lower noise and greater stability under outdoor conditions, while sWMS provided baseline-free spectra but was more sensitive to power fluctuations. E-CAHORS combines high precision, multi-species sensing capability with low power consumption (10 W) and a compact design (4.2 kg). Full article

Canagliflozin (CFZ), a sodium–glucose cotransporter 2 (SGLT2) inhibitor, is extensively utilized in the management of type 2 diabetes. Among its various polymorphic forms, the hemi-hydrate (Hemi-CFZ) has been selected as the active pharmaceutical ingredient (API) for CFZ tablets due to its superior solubility. However, during the production, storage, and transportation of CFZ tablets, Hemi-CFZ can undergo transformations into anhydrous (An-CFZ) and monohydrate (Mono-CFZ) forms under the influence of environmental factors such as temperature, humidity, and pressure, which may adversely impact the bioavailability and clinical efficacy of CFZ tablets. Therefore, it is imperative to develop rapid, accurate, non-destructive, and non-contact methods for quantifying An-CFZ and Mono-CFZ content in CFZ tablets to control polymorphic impurity levels and ensure product quality. This research evaluated the feasibility and reliability of using near-infrared spectroscopy (NIR) combined with partial least squares regression (PLSR) for simultaneous quantitative analysis of An-CFZ and Mono-CFZ in CFZ tablets, elucidating the quantifying mechanisms of the quantitative analysis model. Orthogonal experiments were designed to investigate the effects of different pretreatment methods and ant colony optimization (ACO) algorithms on the performance of quantitative models. An optimal PLSR model for simultaneous quantification of An-CFZ and Mono-CFZ in CFZ tablets was established and validated over a concentration range of 0.0000 to 10.0000 w/w%. The resulting model, Y_{An-CFZ/Mono-CFZ} = 0.0207 + 0.9919 X, achieved an R² value of 0.9919. By analyzing the relationship between the NIR spectral signals selected by the ACO algorithm and the molecular structure information of An-CFZ and Mono-CFZ, we demonstrated the feasibility and reliability of the NIR-PLSR approach for quantifying these polymorphic forms. Additionally, the mechanism of PLSR quantitative analysis was further explained through the variance contribution rates of latent variables (LVs), the correlations between LVs loadings and tablets composition, and the relationships between LV scores and An-CFZ/Mono-CFZ content. This study not only provides a robust method and theoretical foundation for monitoring An-CFZ and Mono-CFZ content in CFZ tablets throughout production, processing, storage, and transportation, but also offers a reliable methodological reference for the simultaneous quantitative analysis and quality control of multiple polymorphic impurities in other similar drugs. Full article

We present the results of long-term photometric and spectroscopic monitoring of the Seyfert galaxy NGC 4151 based on new observational data complemented by archival material spanning several decades. NGC 4151 is one of the most extensively studied active galactic nuclei, exhibiting pronounced variability in both optical continuum and emission-line fluxes, which makes it a key object for investigating physical processes in the central engine and the broad-line region. Our study covers the optical and near-infrared wavelength ranges, including the Ic band and the standard BVRc photometric filters. Using multi-band optical photometry and optical spectroscopy, we construct light curves of the continuum and emission lines and perform a comparative analysis of their temporal behavior during different activity states of the galaxy. The analysis focuses on variability amplitudes, long-term trends, and correlations between photometric and spectral characteristics, allowing us to examine the relationship between continuum variations and the line-emitting regions. Full article

For high-value-added products such as matcha, scientific confirmation of the origin is essential for quality assurance and fraud prevention. In this study, three nondestructive analytical techniques, specifically fluorescence (FF), near-infrared (NIR), and Fourier transform infrared (FT-IR) spectroscopy, were combined with machine learning algorithms to accurately identify the origin of Japanese matcha. FF data were analyzed using convolutional neural networks (CNNs), whereas NIR and FT-IR spectral data were analyzed using k-nearest neighbors (KNNs), random forest (RF), logistic regression (LR), and support vector machine (SVM) models. The FT-IR–RF model demonstrated the highest accuracy (99.0%), followed by the NIR–KNN (98.7%) and FF–CNN (95.7%) models. Functional group absorption in FT-IR, moisture and carbohydrates in NIR, and amino acid and polyphenol fluorescence in FF contributed to the identification. These findings indicate that the selection of an algorithm appropriate for the characteristics of the spectroscopic data is effective for improving accuracy. This method can quickly and nondestructively identify the origin of matcha and is expected to be applicable to other teas and agricultural products. This new approach contributes to the verification of the authenticity of food and improvement in its traceability. Full article

This study evaluates the feasibility of Near-Infrared (NIR) spectroscopy combined with chemometric modeling for monitoring twin-screw melt granulation. Lactose monohydrate was used as a model excipient and polyethylene glycol (PEG 6000) (Sistemas Analíticos S.A, Buenos Aires, Argentina) as a meltable binder. Granules were produced under different processing conditions by varying binder content, screw configuration (kneading or conveying elements), and measurement temperature. NIR spectra were acquired on-line on a conveyor belt and analyzed using Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression. The regression models showed excellent predictive performance for PEG 6000 content in lactose-based granules, with coefficients of determination higher than 0.998 for both raw and preprocessed spectral data. PCA successfully discriminated between granulated and non-granulated materials, as well as between granules produced with different screw configurations, demonstrating the sensitivity of the technique to processing conditions and granule formation mechanisms. In addition, spectral differences associated with measurement temperature were detected, with derivative-based preprocessing improving the discrimination between warm and cooled granules. Overall, the results demonstrate that NIR spectroscopy, coupled with multivariate analysis, is a robust and non-invasive tool for real-time monitoring of twin-screw melt granulation, with strong potential to enhance process understanding, control, and product consistency in continuous pharmaceutical manufacturing. Full article

Functional Near-Infrared Spectroscopy (fNIRS), a non-invasive neuroimaging technique, has demonstrated unique advantages in linguistic research in recent years. By monitoring changes in the concentrations of oxygenated and deoxygenated hemoglobin during cortical activation, fNIRS provides new insights into the mechanisms underlying language processing. Its ecological validity and high compatibility enable seamless integration into real-world environments, minimizing interference and ensuring the authenticity of the collected data. In the realm of linguistics, fNIRS has been applied to studies on language perception, function, acquisition, cross-linguistic processing, and the assessment of language disorders, revealing the intricate mechanisms of language processing and showcasing its potential for clinical applications. This article reviews the latest advancements in the utilization of fNIRS in linguistic research, aiming to provide valuable references for researchers and to foster deeper exploration and innovative development in this field. Meanwhile, this article systematically examines the limitations of fNIRS in current research, provides a critical assessment of its methodological and applicative value, and, on this basis, outlines future directions and potential breakthroughs for this technology in the field of language research. Full article

A new family of highly uniform, cubic-shaped Cu₃VS_xSe_4−x (CVSSe; 0 ≤ x ≤ 4) nanocrystals based on earth-abundant materials with intermediate bandgaps (IB) in the visible range is reported, synthesized via a hot-injection method. The IB transitions and optical band gap of the novel CVSSe nanocrystals are investigated using ultraviolet-visible spectroscopy, revealing tunable band gaps that span the visible and near-infrared regimes. The composition-dependent relationships among the crystal phase, optical band gap, and photoluminescence properties of the novel IB semiconductors with progressive substitution of Se by S are examined in detail. High-resolution transmission electron microscopy and scanning electron microscopy characterization confirm the high crystallinity and uniform size (~19.7 nm × 17.2 nm for Cu₃VS₄) of the cubic-shaped nanocrystals. Density functional theory (DFT) calculations based on virtual crystal approximation support the experimental findings, showing good agreement in lattice parameters and band gaps across the CVSSe series and lending confidence that the targeted phases and compositions have been successfully realized. A current conversion efficiency, i.e., incident photon-to-current efficiency, of 14.7% was achieved with the p-type IB semiconductor Cu₃VS₄. These novel p-type IB semiconductor nanocrystals hold promise for enabling thin film solar cells with efficiencies beyond the Shockley–Queisser limit by allowing sub-band-gap photon absorption through intermediate-band transitions, in addition to the conventional direct-band-gap transition. Full article

Introduction: Stroke is a leading cause of adult-onset disability. Non-invasive brain stimulation (NIBS) techniques such as repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS), and transcutaneous vagus nerve stimulation (tVNS) are promising adjuncts to upper limb rehabilitation. The use of functional neuroimaging through task functional MRI (fMRI) or functional near-infrared spectroscopy (fNIRS) allows the visualisation of cortical activation patterns associated with stroke-related impairment and recovery. The present study comprehensively reviews the evidence base for the effects of NIBS on clinical and functional neuroimaging outcomes after stroke. Methods: Systematic searches were carried out in MEDLINE and EMBASE via Ovid. Inclusion criteria were clinical trials of adults with stroke and arm weakness undergoing NIBS, with clinical measures of arm function and neuroimaging outcome measures that included either task fMRI or task fNIRS. Two authors independently carried out study screening, risk of bias assessments, and data collection for clinical and neuroimaging outcomes pre- and post-intervention. Results: A total of 17 studies (12 rTMS, 5 tDCS), including 495 participants, met the inclusion criteria. Fifteen studies used task fMRI and four used task fNIRS. Improvements in arm-related motor activity were observed following both rTMS and tDCS. Most studies reported increased activation in ipsilesional sensorimotor areas alongside reductions in contralesional activation. Discussion: rTMS and tDCS may improve upper limb recovery in people with stroke. The increase in the laterality index towards activation of the ipsilesional hemisphere suggests that these NIBS techniques may facilitate neural reorganisation and restoration of motor networks in the affected hemisphere. Full article

Infrared (IR) spectroscopy has emerged as a rapid, cost-effective, and reliable alternative to traditional methods, enabling real-time, indirect monitoring of nutrients. Most reviews have discussed visible-near-infrared (Vis-NIR) and mid-infrared (MIR) spectroscopy individually for soil analysis. This review highlights the application of IR spectroscopy, particularly Vis-NIR, MIR spectroscopy, and their data fusion, coupled with chemometrics and spectral preprocessing for estimating soil attributes. Additionally, the crucial functions of assessing model accuracy and validating model estimates of soil properties are discussed. Partial least squares regression (PLSR) was used in more than 100 studies in 2022. Based on the literature published from 2020 to 2025, the data fusion method predicts soil properties more accurately. This review also sheds light on recent advances in spectroscopic methods, including improvements in speed (e.g., MIR spectroscopy is up to 12 times faster than traditional methods), instrument miniaturization, and integration with portable devices, which can make field analysis more affordable. However, the sensitivity of IR spectroscopy to soil moisture, sample heterogeneity, vegetation cover, and calibration transfer issues remains a significant challenge in certain studies. Therefore, a discussion on the challenges in implementing this technique is included in this review, and future perspectives, such as integration of various sensors and portable devices for real-time soil assessment, are successively discussed. Full article