This study reports on developing a simple, cost-effective, highly sensitive spectrophotometric method for measuring mesalazine (MSZ). The method utilizes the oxidative coupling of MSZ with syringic acid (4-hydroxy 3,5-dimethoxybenzoic acid) in the presence of dissolved oxygen under alkaline conditions to form a stable indophenol dye with a characteristic blue color, which can be measured at 615 nm. Beer’s law was found to be obeyed over the range of 1.25–50 µg·mL−1, with a molar absorptivity of 0.53 × 104 mol−1·L−1·cm−1. Moreover, the method exhibited excellent sensitivity, with a limit of detection (LOD) of 0.093 µg·mL−1 and a limit of quantitation (LOQ) of 0.282 µg·mL−1. The proposed method was found to be selective, as it could effectively detect MSZ in the presence of certain interfering species. The proposed method was validated according to current ICH guidelines and demonstrated good accuracy, with recoveries ranging between 98 and 100% and a relative standard deviation of less than 0.6%. Overall, this method provides a promising tool for the sensitive and accurate determination of MSZ in its pure form, pharmaceutical formulations, and biological samples.

It is important to assess the nutritional concentrations of forage before it can be used for tremendous improvements in the dairy industry. This improvement requires a rapid, accurate, and portable method for detecting nutrient values, instead of traditional laboratory analysis. Fourier-transform infrared (ATR-FTIR) spectroscopy technology was applied, and partial least squares regression (PLSR) and backpropagation artificial neural network (BP-ANN) algorithms were used in the current study. The objective of this study was to estimate the discrepancy in nutritional content and rumen degradation in WPCS grown in various regions and to propose a novel analytical method for predicting the nutrient content of whole plant corn silage (WPCS). The Zhengdan 958 cultivar of WPCS was selected from eight different sites to compare the discrepancies in nutrients and rumen degradation. A total of 974 WPCS samples from 235 dairy farms scattered across five Chinese regions were collected, and nutritional indicators were modeled. As a result, substantial discrepancies in nutritional concentrations and rumen degradation of WPCS were found when they were cultivated in different growing regions. The WPCS in Wuxi showed 1.14% higher dry matter (DM) content than that in Jinan. Lanzhou had 11.57% and 8.25% lower neutral detergent fiber (NDF) and acid detergent fiber (ADF) concentrations than Jinan, respectively. The DM degradability of WPCS planted in Bayannur was considerably higher than that in Jinan (6 h degradability: Bayannur vs. Jinan = 49.85% vs. 33.96%), and the starch of WPCS from Bayannur (71.79%) was also the highest after 6 h in the rumen. The results indicated that the contents of NDF, ADF, and starch were estimated precisely based on ATR-FTIR combined with PLSR or the BP-ANN algorithm (R2 ≥ 0.91). This was followed by crude protein (CP), DM (0.82 ≤ R2 ≤ 0.90), ether extract (EE), and ash (0.66 ≤ R2 ≤ 0.81). The BP-ANN algorithm had a higher prediction performance than PLSR (R2PLSR ≤ R2BP-ANN; RMSEPLSR ≥ RMSEBP-ANN). The same WPCS cultivar grown in different regions had various nutrient concentrations and rumen degradation. ATR-FTIR technology combined with the BP-ANN algorithm could effectively evaluate the CP, NDF, ADF, and starch contents of WPCS.

Constant-height scanning tunneling microscopy (STM) images of a C60 molecule adsorbed onto a surface were calculated using symmetry-adapted Hückel molecular orbitals (HMOs). Three adsorption orientations of C60 are considered. The interaction between the C60 molecule and the surface was treated using symmetry arguments only. Projection operators were used to generate symmetry-adapted HMOs of the molecule. These orbitals were then used to construct idealized constant-height STM images using the simple tunneling theory of Tersoff and Hamann. A comparison is made with published experimental STM maps. The results show that, for each orientation of C60, split orbitals of the same symmetry have similar appearances in the constant-height maps. They also show that the map of a molecular orbital of a complete degeneracy is dominated by only one or two of its components.

This research was intended to define and interpret cell wall attributes and other chemical composition of eight different varieties of tomato plants by utilizing fiber optic Fourier-transform near-infrared spectroscopy (FT-NIR) to acquire in situ chemical signatures of leaf, flower, fruit, and stem of tomato plant and cell wall at different developmental stages. Chemical spectral signatures of the tomato’s leaf, flower, fruit, and stem were only acquired during its session and in live mode such as green, yellow, and red in cell wall color. The spectral signature analysis of each tomato plant was performed to see substantial differences in chemical compositions using chemometric data modeling of FT-NIR spectra. In addition, principal component analysis (PCA) was performed to discriminate leaf, flower, fruit, and stem from the same variety. PCA was also performed to differentiate eight different varieties of tomato plants. The study showed how in situ FT-NIR could distinguish eight types of tomato leaf, flower, fruit, and stem chemical composition at different developmental stages related to cell wall and other attributes. This study has also demonstrated how in situ FT-NIR can discriminate between rusty vs. healthy leaf and intact fruit vs. off-the-plant fruit. The main objective of this study is to present the chemical signature differences in the live and developing tomato plants to improve crucial factors of tomatoes that would benefit plant breeding, tomato cell wall study, and ultimately human health.

This study is aimed to shed light on the electronic absorption and emission spectra of DBDMA (2-(1-(difluoroboraneyl)-1,2-dihydroquinolin-2-yl)-2-(1-methylquinoxalin-2-ylidene) acetonitrile) in different solvents. Both types of spectra were obtained theoretically and produced experimentally in different solvents. The photostability of dye was tested, and its energy transfer behavior in the presence of oxygen and hydrated copper sulfate quenchers was investigated. We also gave a qualitative estimation of the effect of acidic media on the absorption and emission spectra. There is good compatibility between the calculated and measured values of many photophysical parameters. DBDMA has a low chemical quantum yield in solvents of different polarities, and the fluorescence quantum yield is high enough, which confirms, together with the low values of the excited state lifetime, its efficiency as laser emitting dye in the range of wavelength emission maxima. The rigidity of the DBDMA molecule is the main reason for the photochemical stability and the absence of a considerable shift as a result of the change in the polarity of the solvents. Geometries of ground and excited states were optimized using the density functional theory (DFT) and the time-dependent density functional theory (TD-DFT), respectively. Upon using the TD-DFT method, the UV-Vis absorption and emission spectra of the DBDMA molecule in different solvents were illustrated. A slight change is observed in the position of the maximum emission and absorption wavelength with the change of the solvent due to the rigidity of the compound. There was no apparent effect of quenching by oxygen. Besides, no intersystem crossing (ISC) was observed for the excited state of the DBDMA as a result of aeration of a solution with O2 for 20 min, which was an explanation of the stability of peak emission intensity of dye after exposure to oxygen gas. The energy transfer rate constant has been calculated as well.

The structural alterations that may arise in boiled and nonboiled bones are often overlooked despite their critical importance in the development of defleshing techniques across various scientific disciplines. To elucidate the microstructural characteristics of bones following the removal of soft tissue through conventional methods, attenuated total reflectance Fourier-transform infrared (ATR-FTIR) and X-ray diffraction (XRD) spectroscopies were employed. Our findings indicate that the boiled water method resulted in higher crystallinity, as evidenced by the FTIR data, whereas the XRD data revealed the opposite. This underscores the notion that a direct comparison between these two techniques is unfeasible as they measure distinct crystallinity parameters. In addition, the cold water maceration method caused a significant reduction in collagen crosslinking, as evidenced by the lower index observed.

Rapid and onsite determination of the soil status and quality parameters holds a brighter potential for improving food security, and minimizing waste of the excessive application of soil amendments hence reducing environmental pollution. In this study, a pocket-sized shortwave NIR spectroscopy (740–1070 nm) and multivariate statistics were used to classify soil from different land-use types and simultaneously predict nitrogen (N), phosphorus (P), potassium (K), calcium (Ca2+), magnesium (Mg2+), and pH in Ghana. Different Algorithms. Linear discriminant analysis (LDA), support vector machine (SVM), and partial least squares algorithms (full-range partial least square, FrPLS; interval partial least squares, IPLS; synergy interval partial least squares, Si-PLS) were attempted for building a suitable classification and quantification model. The models were assessed by the classification rate, coefficient of determination (Rp2), and root mean square error of prediction (RMSEP) in the prediction set. A total of 110 soil samples from 0 to 15 cm, 15 to 30 cm, and 30 to 45 cm layers were collected from the field of different land-use cropping systems. The results obtained showed that SVM had a 98.61% classification rate of the soil from the cropping system. While Si-PLS was superior in predicting N, P, K, Mg2+, Ca2+, and pH. The performance of the Si-PLS model for N, P, K, Mg2+, Ca2+, and pH were 0.571, 0.779, 0.910, 0.778, 0.826, and 0.904 for Rp2 and 0.033%, 0.738 mg·kg−1, 0.117 cmol·kg−1, 0.654 cmol·kg−1, 3.0219 cmol·kg−1, and 0.4760 pH unit for RMSEP, respectively. The results revealed that the portable NIR spectroscopic technique could be used to measure the soil status and some quality parameters. However, further studies are needed to proof its application. This could lead to improving the yield and saving the cost of fertilizer application.

The effect of laser (532 nm line of Verdi G) heating during the Raman measurements, on partial decomposition of Bi12SiO20 single crystal, was addressed in this study. The degree of decomposition directly depends on the power density and duration of the laser treatment, which are registered by the phonon Raman spectra. After laser treatment, AFM measurements register additional small spherical islands on the surface. Analysis performed on irradiated and unirradiated samples showed significant changes in transmission spectra, X-ray diffraction (XRD) pattern, Verdet constant, magneto-optical property, and absorption coefficient. The material obtained after laser irradiation can be described as specific nanocomposite consisting of bismuth oxide and silicon oxide-based nano-objects (dimensions below 15 nm in diameter), which are arranged in a matrix of Bi12SiO20.

Engineered wood products, such as cross-laminated timber (CLT), are becoming more popular in the designs of modern sustainable buildings. This increased production of CLT requires more robust, yet less labour-intensive means to assess the material characteristics of whole CLT panels. In exploring ways of improving efficiency, this study explores multivariate image analysis (MIA) via partial least squares discriminant analysis (PLS-DA) machine learning as a means to classify CLT material features. CLT panels underwent nondestructive testing using near-infrared (NIR) hyperspectral imaging and X-ray computed tomography (CT) analysis. MIA was performed on these results to build predictive models for wood features, such as fibre alignment and knot type. The models showed that it was possible to classify material features on the surface of CLT using NIR alone; whilst when combined with X-ray data, it enhanced the predictive ability of material features throughout the CLT volume. These first results from such modelling have the potential to help map the chemical and physical material properties of CLT, improving the manufacturing efficiency of the product and allowing greater sustainability of engineered wood products.

To achieve perfect teeth color reproduction, we propose the design of a snapshot hyperspectral imaging spectrometer that can accurately measure the teeth spectrum. In this paper, the optical system of a snapshot hyperspectral dental imaging spectrometer is designed. In particular, to encode images in both the spatial and spectral dimensions, a one-dimensional random coding mask rotated 45 degrees around the optical axis is used. The system has a spectral resolution of approximately 2.2∼10 nm in the 450∼700 nm spectral range, and the total length of the system is less than 150 mm. The whole design can be used as a miniaturized handheld instrument. To verify the feasibility of whiteness measuring, a simulation experiment is carried out. The target spectral information is reconstructed through the reconstruction algorithm. The simulation result shows that spectral imaging has the potential to improve the accuracy and precision of teeth whiteness measurements.