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The rapid and sensitive detection of heavy metal ions is important for environment and human health. Hence, the rapid and sensitive detection of multiple heavy metals simultaneously has become a critical issue. Here, we propose a method based on laser-induced breakdown spectroscopy (LIBS) combined with filter paper modified with PtAg bimetallic nanoparticles (BNPs) (LIBS-FP-PtAgBNPs) for the ultrasensitive detection of Hgsup2+/sup, Crsup3+/sup, and Pbsup2+/sup. The PtAgBNPs-modified filter paper was used to efficiently and specifically adsorb Hg, Cr, and Pb, and LIBS was used to detect the Hg, Cr, and Pb simultaneously. The limits of detection for Hg, Cr, and Pb were 0.5 μg/L (2.5 nM), 8 μg/L (0.15 μM), and 2 μg/L (9 nM), respectively. Furthermore, this method was successfully applied to determine the concentrations of Hg, Cr, and Pb in real spiked water samples. Compared with other methods based on nanoparticle sensing, LIBS-FP-PtAgBNPs is simpler to use and can achieve highly efficient enrichment, rapid separation, and sensitive detection of heavy metal ions. The optimal detections of Hg, Cr, and Pb were achieved in the pH range of 1-6. The developed method provides a new avenue to realize the rapid and sensitive detection of trace heavy metals in the environment.

The absolute dating of documents is still one of the most important challenges for forensic document examiners (FDE). The potential difference between the date on a questioned document and the actual year of production of the used paper can be only 1 to 5 years. Until now, there was no analytical method with this accuracy available. This study demonstrates a method for an absolute dating of paper by using the

In industrial paper production, online monitoring of a range of quality parameters is essential for ensuring that the performance and appearance of the final product is suitable for a given application. In this article, two optical sensing techniques are investigated for non-destructive, non-contact characterization of paper thickness, surface roughness, and production defects. The first technique is optical coherence tomography based on a mid-infrared supercontinuum laser, which can cover thicknesses from ~20–90 μm and provide information about the surface finish. Detection of subsurface voids, cuts, and oil contamination was also demonstrated. The second technique is terahertz time domain spectroscopy, which is used to measure paper thicknesses of up to 443 μm. A proof-of-concept thickness measurement in freely suspended paper was also demonstrated. These demonstrations highlight the added functionality and potential of tomographic optical sensing methods towards industrial non-contact quality monitoring.

Chemical and spectroscopic characterization of the mononuclear photosensitizers [(DPEPhos)Cu(I)(MPyrT)]0/+ (CuL, CuLH) and their dinuclear analogues (Cu2L’, Cu2L'H2 ), backed by (TD)DFT and high‐level GW‐Bethe‐Salpeter equation calculations, exemplifies the complex influence of charge, nuclearity and structural flexibility on UV‐induced photophysical pathways. Ultrafast transient absorption and step‐scan FTIR spectroscopy reveal flattening distortion in the triplet state of CuLH as controlled by charge, which also appears to have a large impact on the symmetry of the long‐lived triplet states in Cu2L’ and Cu2L'H2 . Time‐resolved luminescence spectroscopy (solid state), supported by transient photodissociation spectroscopy (gas phase), confirm a lifetime of some tens of μs for the respective triplet states, as well as the energetics of thermally activated delayed luminescence, both being essential parameters for application of these materials based on earth‐abundant copper in photocatalysis and luminescent devices., The comprehensive results on two mononuclear pyridyl‐triazole/DPEPhos based Cu(I) complexes and its extension to their two dinuclear analogues paves the road to addressing the complex coupling of the respective monomeric units, involving various physical and chemical properties as charge, (electronic) structure and (long‐lived) excited state properties, relevant for applications.

Banana (Musa acuminata) pseudostem cellulose was extracted and acetylated (CA) to prepare membranes with potential use as bio-packages. The CA membrane was embedded by Butia seed (CA-BS) or Butia pulp (CA-BP) extracts obtained from Butia catarinenses (Butia). The produced CA, CA-BS, and CA-BP membranes were evaluated for their physical-chemical, mechanical, thermal, and antibacterial properties. The process for obtaining the cellulose yielded a material with about 92.17% cellulose (DS = 2.85). The purity, cellulose degree acetylation, and the incorporation of Butia extracts into the membranes were confirmed by FTIR. The CA-BS and CA-BP membranes showed a smaller contact angle and higher swelling ratio than the CA membrane. Furthermore, Butia seed or pulp extracts reduced the elastic modulus and deformation at break compared to the CA membrane. The DSC analysis suggested the compatibility between sections and the CA matrix, whereas the TGA analysis confirmed the thermal stability of the membranes. Moreover, less than 1% of the Butia seed and pulp extracts were put into a food simulant media from the membrane. Finally, the CA-BS and CA-BP membranes could inhibit the growth of Staphylococcus aureus and Escherichia coli on their surface, confirming the potential use of these membranes as bio-packaging for food preservation.

In order to perform good kinetic experiments, not only the experimental conditions have to be optimized, but the evaluation procedure as well. The focus of this work is the in-depth comparison of different approaches and algorithms to determine kinetic rate constants for biomolecular interaction analysis (BIA). The different algorithms are applied not only to flawless simulated data, but also to real-world measurements. We compare five mathematical approaches for the evaluation of binding curves following pseudo-first-order kinetics with different noise levels. In addition, reflectometric interference spectroscopy (RIfS) measurements of two antibodies are evaluated to determine their binding kinetics. The advantages and disadvantages of the individual approach will be investigated and discussed in detail. In summary, we will raise awareness on how to evaluate and judge results from BIA by using different approaches rather than having to rely on “black box” closed (commercial) software packages. Supplementary Information The online version contains supplementary material available at 10.1007/s00216-021-03623-x.

Significance: Diffuse reflectance spectroscopy (DRS) allows discrimination of tissue type. Its application is limited by the inability to mark the scanned tissue and the lack of real-time measurements. Aim: This study aimed to develop a real-time tracking system to enable localization of a DRS probe to aid the classification of tumor and non-tumor tissue. Approach: A green-colored marker attached to the DRS probe was detected using hue-saturation-value (HSV) segmentation. A live, augmented view of tracked optical biopsy sites was recorded in real time. Supervised classifiers were evaluated in terms of sensitivity, specificity, and overall accuracy. A developed software was used for data collection, processing, and statistical analysis. Results: The measured root mean square error (RMSE) of DRS probe tip tracking was 1.18±0.58 mm and 1.05±0.28 mm for the x and y dimensions, respectively. The diagnostic accuracy of the system to classify tumor and non-tumor tissue in real time was 94% for stomach and 96% for the esophagus. Conclusions: We have successfully developed a real-time tracking and classification system for a DRS probe. When used on stomach and esophageal tissue for tumor detection, the accuracy derived demonstrates the strength and clinical value of the technique to aid margin assessment in cancer resection surgery.

Significance: Tissue-like solid phantoms with identical optical properties, known within tolerant uncertainty, are of crucial importance in diffuse optics for instrumentation assessment, interlaboratory comparison studies, industrial standards, and multicentric clinical trials. Aim: The reproducibility in fabrication of homogeneous solid phantoms is focused based on spectra measurements by instrument comparisons grounded on the time-resolved diffuse optics. Approach: Epoxy-resin and silicone phantoms are considered as matrices and both employ three different instruments for time-resolved diffuse spectroscopy within the spectral range of 540 to 1100 nm. In particular, we fabricated two batches of five phantoms each in epoxy resin and silicone. Then, we evaluated the intra- and interbatch variability with respect to the instrument precision, by considering the coefficient of variation (CV) of absorption and reduced scattering coefficients. Results: We observed a similar precision for the three instruments, within 2% for repeated measurements on the same phantom. For epoxy-resin phantoms, the intra- and the interbatch variability reached the instrument precision limit, demonstrating a very good phantom reproducibility. For the silicone phantoms, we observed larger values for intra- and interbatch variability. In particular, at worst, for reduced scattering coefficient interbatch CV was about 5%. Conclusions: Results suggest that the fabrication of solid phantoms, especially considering epoxy-resin matrix, is highly reproducible, even if they come from different batch fabrications and are measured using different instruments.

Abstract An open hardware design and implementation for a transient absorption spectrometer are presented that has microsecond time resolution and measures full difference spectra in the visible spectral region from 380 to 750 nm. The instrument has been designed to allow transient absorption spectroscopy measurements of either low or high quantum yield processes by combining intense sub-microsecond excitation flashes using a xenon lamp together with stroboscopic non-actinic white light probing using LED sources driven under high pulsed current from a capacitor bank. The instrument is sensitive to resolve 0.15 mOD flash-induced differences within 1000 measurements at 20 Hz repetition rate using an inexpensive CCD sensor with 200 μm pixel dimension, 40 K electrons full well capacity and a dynamic range of 1800. The excitation flash has 230 ns pulse duration and the 2 mJ flash energy allows spectral filtering while retaining high power density with focussing to generate mOD signals in the 10–4–10–1 ΔOD range. We present the full electronics design and construction of the flash and probe sources, the optics as well as the timing electronics and CCD spectrometer operation and modification for internal signal referencing. The performance characterisation and example measurements are demonstrated using microsecond TAS of Congo red dye, as an example of a low quantum yield photoreaction at 2% with up to 78% of molecules excited. The instrument is fully open hardware and combines inexpensive selection of commercial components, optics and electronics and allows linear response measurements of photoinduced reactions for the purpose of accurate global analysis of chemical dynamics. Graphical abstract

Significance: Current methods for analyzing pathological muscle tissue are time consuming and rarely quantitative, and they involve invasive biopsies. Faster and less invasive diagnosis of muscle disease may be achievable using marker-free in vivo optical sensing methods. Aim: It was speculated that changes in the biochemical composition and structure of muscle associated with pathology could be measured quantitatively using visible wavelength optical spectroscopy techniques enabling automated classification. Approach: A fiber-optic autofluorescence (AF) and diffuse reflectance (DR) spectroscopy device was manufactured. The device and data processing techniques based on principal component analysis were validated using in situ measurements on healthy skeletal and cardiac muscle. These methods were then applied to two mouse models of genetic muscle disease: a type 1 neurofibromatosis (NF1) limb-mesenchyme knockout (Nf1Prx1−/−) and a muscular dystrophy mouse (mdx). Results: Healthy skeletal and cardiac muscle specimens were separable using AF and DR with receiver operator curve areas (ROC-AUC) of >0.79. AF and DR analyses showed optically separable changes in Nf1Prx1−/− quadriceps muscle (ROC-AUC >0.97) with no differences detected in the heart (ROC-AUC

Significance Prostate cancer is the most common cancer among men. An accurate diagnosis of its severity at detection plays a major role in improving their survival. Recently, machine learning models using biomarkers identified from Raman micro-spectroscopy discriminated intraductal carcinoma of the prostate (IDC-P) from cancer tissue with a ≥85 % detection accuracy and differentiated high-grade prostatic intraepithelial neoplasia (HGPIN) from IDC-P with a ≥97.8 % accuracy. Aim To improve the classification performance of machine learning models identifying different types of prostate cancer tissue using a new dimensional reduction technique. Approach A radial basis function (RBF) kernel support vector machine (SVM) model was trained on Raman spectra of prostate tissue from a 272-patient cohort (Centre hospitalier de l'Universite de Montreal, CHUM) and tested on two independent cohorts of 76 patients [University Health Network (UHN)] and 135 patients (Centre hospitalier universitaire de Quebec-Universite Laval, CHUQc-UL). Two types of engineered features were used. Individual intensity features, i.e., Raman signal intensity measured at particular wavelengths and novel Raman spectra fitted peak features consisting of peak heights and widths. Results Combining engineered features improved classification performance for the three aforementioned classification tasks. The improvements for IDC-P/cancer classification for the UHN and CHUQc-UL testing sets in accuracy, sensitivity, specificity, and area under the curve (AUC) are (numbers in parenthesis are associated with the CHUQc-UL testing set): +4 % (+8 % ), +7 % (+9 % ), +2 % (6%), +9 (+9) with respect to the current best models. Discrimination between HGPIN and IDC-P was also improved in both testing cohorts: +2.2 % (+1.7 % ), +4.5 % (+3.6 % ), +0 % (+0 % ), +2.3 (+0). While no global improvements were obtained for the normal versus cancer classification task [+0 % (-2 % ), +0 % (-3 % ), +2 % (-2 % ), +4 (+3)], the AUC was improved in both testing sets. Conclusions Combining individual intensity features and novel Raman fitted peak features, improved the classification performance on two independent and multicenter testing sets in comparison to using only individual intensity features.

Significance: Complementary absorption and fluorescence contrast could prove useful for a wide range of biomedical applications. However, current absorption-based photoacoustic microscopy systems require the ultrasound transducers to physically touch the samples, thereby increasing contamination and limiting strong optical focusing in reflection mode. Aim: We sought to develop an all-optical system for imaging cells and tissues using the three combined imaging modalities: photoacoustic remote sensing (PARS), epifluorescence, and confocal laser scanning microscopy (CLSM). Approach: A PARS subsystem with ultraviolet excitation was used to obtain label-free absorption-contrast images of nucleic acids in ex vivo tissue samples. Co-integrated epifluorescence and CLSM subsystems were used to verify the 2D and 3D nuclei distribution. Results: Complementary absorption and fluorescence contrast were demonstrated in phantom imaging experiments and subsequent cell and tissue imaging experiments. Lateral and axial resolution of ultraviolet-PARS (UV-PARS) is shown to be 0.39 and 1.6 μm, respectively, with 266-nm light. CLSM lateral and axial resolution was measured as 0.97 and 2.0 μm, respectively. This resolution is sufficient to image individual cell layers with fine optical sectioning. UV-PARS images of cell nuclei are validated in thick tissue using CLSM. Conclusions: Multimodal absorption and fluorescence contrast are obtained with a non-contact all-optical microscopy system for the first time and utilized to obtain images of cells and tissues with subcellular resolution.

Various events of edible oils adulteration with inferior ingredients were reported regularly in recent years. This review is aimed to provide an overview of edible oils adulteration practices, regulatory compliance and detection technologies. Many detection technologies for edible oils adulteration were developed in the past such as methods that are based on chromatography or spectroscopy. Electrochemical sensors like electric nose and tongue are also gaining popularity in the detection of adulterated virgin olive oil and virgin coconut oil. It can be concluded that these detection technologies are essential in the combat with food adulterers and can be improved.

Studies on polyphenols and flavonoids in natural products reveal benefits in the prevention of multiple diseases. Proper extraction, treatment of extracts, and quantification of polyphenols and flavonoids demand attention from the scientific community in order to report more specific biological action. Total polyphenol content (TPC) and total flavonoid content (TFC) (measured at three different times) of ethanol, methanol and acetone extracts of Mauritia flexuosa (aguaje) and Theobroma grandiflorum (copoazú) fresh pulp, from the Colombian Amazon region, were evaluated with the purpose of focusing in the polyphenol/flavonoid proportion and its effective antioxidant activity. This objective could help to explain specific flavonoid biological action based on higher flavonoid proportion rather than higher total polyphenol content. Differences in extracting solvents resulted in statistically significant different yields; the highest TPC was observed with acetone 70% in Mauritia flexuosa and ethanol 80% for T. grandiflorum. The best flavonoid/polyphenol ratio in M. flexuosa was about 1:2.4 and 1:12.8 in T. grandiflorum and the antioxidant efficacy was proportionally higher for flavonoids extracted from T. grandiflorum. HPLC analysis revealed 54 µg/g of the flavonoid kaempferol in M. Flexuosa and 29 µg/g in T. grandiflorum. Further studies evaluating this proportionality, in seeds or peel of fruits, as well as, other specific biological activities, could help to understand the detailed flavonoid action without focusing on the high total polyphenol content.

International audience; This paper addresses the problem of false positive alarm when using a continuous air monitor (CAM) in decommissioning sites of nuclear facilities. CAMs are used to measure airborne activity and play an important role in the radiation protection of workers likely to be exposed to radioactive aerosols. Monitors usually sample aerosols on a membrane filter. Radioactive particles sampled are detected through the alpha and beta decays that they emit. These latter ionizing particles are measured online by spectrometry thanks to a Passivated Implanted Planar Silicon detector (PIPS). Alpha and beta decays, in this context, come mainly from the natural radon progeny (218Po, 214Pb, and so on) and, in the case of radioactive contamination, also from artificial radionuclides such as 239Pu or 137Cs. The aim of the CAM is to alert the workers when the artificial airborne activity occurs, always considering the presence of a variable background due to the natural particulate airborne activity. The CAM-specific algorithm considers this background dynamically and continuously, often by using a constant parameter. However, non-radioactive aerosols are also sampled on the membrane filter. These latter make the discrimination more difficult as they lead to the deterioration of the alpha-energy spectrum. In this paper, the effect of coarse non-radioactive aerosols on the CAM response is highlighted with four aerosol size-distributions. The evolution of the background is characterized as a function of the aerosol mass sampled, with the example of a simple algorithm. Thus, in this paper, results show a positive correlation of the background with the aerosol mass sampled by the CAM. In addition, results highlight at least two different evolutionary trends according to the aerosol size distribution. An explanation of these evolutions is given by considering the penetration profile of the natural radioactive aerosols in the granular deposit above the CAM filter. The main consequence of these results is that the background could not be considered as proportional to radon progeny as it is currently used.

— This paper presents preliminary work on a method to increase the number of detection channels of a commercial 6-channel spectrometric sensor, by employing a set of multiplexed spectrally colored illumination sources. A demonstrator has been built and tested on a set of independent dyes. The results suggest successful enhancement of the number of detection channels. More tests are needed to provide quantitative performance evaluation, and to demonstrate viability in a clinical setting. Clinical Relevance— The technique presented in this paper shows promise to provide a viable method for multispectral sensing in highly-miniaturized systems, such as in-vivo sensing capsules.

The fast and reliable analysis of electrolytes such as K, Na, Ca in human blood serum has become an indispensable tool for diagnosing and preventing diseases. Laser-induced breakdown spectroscopy (LIBS) has been demonstrated as a powerful analytical technique on elements. To apply LIBS to the quantitative analysis of electrolyte elements in real time, a self-developed portable laser was used to measure blood serum samples supported by glass slides and filter paper in this work. The partial least squares regression (PLSR) method was employed for predicting the concentrations of K, Na, Ca from serum LIBS spectra. Great prediction accuracies with excellent linearity were obtained for the serum samples, both on glass slides and filter paper. For blood serum on glass slides, the prediction accuracies for K, Na, Ca were 1.45%, 0.61% and 3.80%. Moreover, for blood serum on filter paper, the corresponding prediction accuracies were 7.47%, 1.56% and 0.52%. The results show that LIBS using a portable laser with the assistance of PLSR can be used for accurate quantitative analysis of elements in blood serum in real time. This work reveals that the handheld LIBS instruments will be an excellent tool for real-time clinical practice.

There is an urgent need to reuse and recycle textile fibers, since today, low recycling rates are achieved. Accurate classification methods for post-consumer textile waste are needed in the short term for a higher circularity in the textile and fashion industries. This paper compares different spectroscopic data from textile samples in order to correctly classify the textile samples. The accurate classification of textile waste results in higher recycling rates and a better quality of the recycled materials. The data fusion of near- and mid-infrared spectra is compared with single-spectrum information. The classification results show that data fusion is a better option, providing more accurate classification results, especially for difficult classification problems where the classes are wide and close to one another. The experimental results presented in this paper prove that the data fusion of near- and mid-infrared spectra is a good option for accurate textile-waste classification, since this approach allows the classification results to be significantly improved. This research study was partially funded by Ministerio de Industria, Comercio y Turismo de España under grant number AEI-010400-2020-206 and by the Generalitat de Catalunya under grant numbers 2017 SGR 967 and 2017 SGR 828.

Orbitrap mass spectrometers have been widely used in environmental component analysis . This paper presents an enhanced data acquisition system for in-situ detection of Orbitrap mass spectrometry, which enables in-suit real-time signal processing and analysis for atmospheric molecules with small mass numbers.During previous space atmospheric explorations, quadrupole mass spectrometry (QMS) was usually utilized for analyzing isotopic compositions and complicated compounds in the mixture. However, the inevitable ion scattering and drift during mass transfer, as well as the QMS attenuator loss, result in a relatively lower signal-to-noise ratio of the produced mass spectrum. In recent years, a novel mass spectrometer, called an Orbitrap mass spectrometer, has been gradually accepted and used because of its non-destructive detection ability, high mass resolution, and accuracy. Nevertheless, Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) is preferred over the Orbitrap mass spectrometry for ground applications, especially for detecting low-mass components (e.g. below 50 atomic mass units) due to the former’s superior resolution. As the mass number decreases, the detection system demands a higher sampling and processing rate. Additionally, in ground-based scenarios, mass spectrometry analysis software on computers is often employed to analyze the signals. Therefore, in order to achieve in-situ detection of the space atmospheric environment using the Orbitrap mass spectrometer, this paper proposes a real-time signal acquisition and processing system for mass spectrometry analysis. The system comprises of signal conditioning circuits, analog-to-digital conversion circuits, programmable logic circuits, and related software. These components perform spectrum analysis and process the signal in real-time on hardware components, allowing for high-speed acquisition and analysis of the signals produced by the Orbitrap mass spectrometer.

The rail conveyor is a new type of energy-saving system for the long-distance transportation of bulk materials. Operating noise is an urgent problem that the current model faces. It will cause noise pollution and affect the health of workers. In this paper, the factors causing vibration and noise are analyzed by modeling the wheel-rail system and the supporting truss structure. Based on the built test platform, the system vibration of the vertical steering wheel, the track support truss, and the track connection were measured, and the vibration characteristics at different positions were analyzed. Based on the established noise and vibration model, the distribution and occurrence rules of system noise under different operating speeds and fastener stiffness conditions were obtained. The experimental results show that the vibration amplitude of the frame near the head of the conveyor is the largest. The amplitude under the condition of 2 m/s running speed at the same position is 4 times that under the condition of 1 m/s. At different welds of the track, the width and depth of the rail gap have a great influence on the vibration impact, which is mainly due to the impact of the uneven impedance at the track gap, and the greater the running speed, the more obvious the vibration impact. The simulation results show the trend of noise generation, the speed of the trolley, and the stiffness of the track fasteners have a positive effect on the generation of noise in the low-frequency region. The research results of this paper will play an important role in the noise and vibration analysis of rail conveyors and help to optimize the structure design of the track transmission system.

Noninvasive detection of human blood components is the dream of human beings and the goal of clinical detection. From the perspective of mathematical analysis, based on the grey analysis system, the principle of spectral chemical quantitative analysis and the solution method of multivariate linear equation, this paper pioneers the spectrum elimination method, and obtains a complete, high-precision, synchronous and noninvasive detection system for a variety of human blood components. The spectral elimination method applies the principle of elimination method in mathematics to the noninvasive quantitative analysis of human blood components by spectral method, reduces the influence of non-target components on the detection of target components, and improves the accuracy of noninvasive quantitative analysis of human blood components. To demonstrate the effectiveness of the method, taking the analysis of the contents of seven blood components (hemoglobin, red blood cell count, neutrophils, lymphocytes, monocytes, eosinophils and basophils) in blood as an example, fourteen models were established by two different methods. From the comparison of modeling results, it can be concluded that when the seven models established by spectral elimination method predict the corresponding seven components of all samples, the predicted correlation coefficients are more than 0.9500. The experimental results show that the spectral elimination method and non-invasive detection system proposed can predict the content of human blood components with high accuracy. This paper studies a high-precision, simultaneous and noninvasive quantitative analysis system of multiple human blood components for the first time, which not only makes great progress in the non-invasive chemical quantitative analysis of human blood components by spectroscopy, but also has great application value for clinical medical treatment and disease diagnosis.

The non-invasive measurement of the blood component contents in humans using spectroscopic methods has important clinical application value. In the absorption spectrum of human blood, for a target component with a small content, the absorption spectrum line is low, the absorption spectrum line of the target component changes weakly at different wavelengths, and the absorption spectrum lines of the target and non-target components overlap. The above reasons cause the spectral line difference between the target and non-target components to be small. However, non-target components also have physical properties such as scattering, which will reduce the contribution of the target component in the absorption spectrum of blood, that is, the spectral line difference between the target and non-target components becomes smaller, thus making the accuracy of the target component model lower.To increase the accuracy of modeling analysis, according to the correlation between spectral data and the content of the target component, this paper proposes a spectral compensation method. The method compensates for the influence caused by the non-target components on the target components through the mathematical relations between the data of the spectrum and the contents of the target components. Thus, a high-precision, non-invasive quantitative analysis system of human blood components is obtained. Taking the analysis of the three components of urea nitrogen, creatinine, and uric acid as examples, the experiment used spectral data before and after spectral compensation and partial least squares (PLS) methods to build two models and used them to predict the content of the target component.When the models of different components established by the spectral compensation method respectively predict the all samples' contents of urea, creatinine, and uric acid, the three correlation coefficients can reach more than 0.9700.It can be obtained from the experimental results that the spectral compensation method can greatly increase the performance of each component model. Spectral compensation is a new and comprehensive method for improving the quality of spectral data. Therefore, this paper obtains a non-invasive quantitative analysis system of human blood components with higher precision, and can quantitatively analyze blood urea nitrogen, creatinine, and uric acid in human blood with high precision, which has great practical application value in clinical practice.

Bacterial cellulose (BC) is an emerging biological material with unique properties and structure, which has attracted more and more attention. In this study, Gluconacetobacter xylinus was used to convert sweet potato residues (SPR) hydrolysate to BC. SPR was directly used without pretreatment, and almost no inhibitors were generated, which was beneficial to subsequent glucan conversion and SPR-BC synthesis. SPR-BC production was 11.35 g/L under the optimized condition. The comprehensive structural characterization and mechanical analysis demonstrated that the crystallinity, maximum thermal degradation temperature, and tensile strength of SPR-BC were 87.39%, 263 °C, and 6.87 MPa, respectively, which were superior to those of BC produced with the synthetic medium. SPR-BC was added to rice straw pulp to enhance the bonding force between fibers and the indices of tensile, burst, and tear of rice straw paper. The indices were increased by 83.18%, 301.27%, and 169.58%, respectively. This research not only expanded the carbon source of BC synthesis, reduced BC production cost, but also improved the quality of rice straw paper.

Classical histological methods such as hematoxylin-eosin staining, have been, and in some areas still are, an important benchmark for the evaluation of biological tissues. However, the current method of assessment is primarily a qualitative assessment of the tissue under investigation. The aim of this paper is to contribute to the improvement of classical histological methods, by applying physical techniques that allow objective, quantitative data to be added to qualitative assessments, especially in areas where conflicting results are available. To this end, the effect of hypolipidemic medication on the callus formation process of normal bone and pathological osteoporotic bone was investigated. The study allowed us to associate UV-VIS spectroscopy wave number with specific hematoxylin-eosin staining of different types of bone tissue structures, the evolving structures in the callus formation process. This association allowed the quantitative assessment of the callusing process in ovariectomized (associated with pathological, osteoporotic bone) and non-ovariectomized (associated with normal bone) rats, with three groups - the control group, simvastatin-treated group, and fenofibrate-treated group. The study showed that in the non-ovariectomized groups both treatments delayed callus formation. In the ovariectomized groups, simvastatin delayed and fenofibrate promoted callus formation.

The ongoing integration of quantum chemistry, statistical mechanics, and artificial intelligence is paving the route toward more effective and accurate strategies for the investigation of the spectroscopic properties of medium-to-large size chromo- phores in condensed phases. In this context we are developing a novel workflow aimed at improving the generality, reliability, and ease of use of the available computational tools. In this paper we report our latest developments with specific reference to unsupervised atomistic simulations employing non periodic boundary conditions (NPBC) followed by clustering of the trajectories employing optimized feature spaces. Next accurate variational computations are performed for a representative point of each cluster, whereas intracluster fluctuations are taken into account by a cheap yet reliable perturbative approach. A number of methodological improvements have been introduced including, e.g., more realistic reaction field effects at the outer boundary of the simulation sphere, automatic definition of the feature space by continuous perception of solute−solvent interactions, full account of polarization and charge transfer in the first solvation shell, and inclusion of vibronic contributions. After its validation, this new approach has been applied to the challenging case of solvatochromic effects on the UV−vis spectra of a prototypical nitroxide radical (TEMPO) in different solvents. The reliability, effectiveness, and robustness of the new platform is demonstrated by the remarkable agreement with experiment of the results obtained through an unsupervised approach characterized by a strongly reduced computational cost as compared to that of conventional quantum mechanics and molecular mechanics models without any accuracy reduction.

Vibrational sum frequency generation (SFG) spectroscopy can specifically probe molecular species non-centrosymmetrically arranged in a centrosymmetric or isotropic medium. This capability has been extensively utilized to detect and study molecular species present at the two-dimensional (2D) interface at which the centrosymmetry or isotropy of bulk phases is naturally broken. The same principle has been demonstrated to be very effective for the selective detection of non-centrosymmetric crystalline nanodomains interspersed in three-dimensional (3D) amorphous phases. However, the full spectral interpretation of SFG features has been difficult due to the complexity associated with the theoretical calculation of SFG responses of such 3D systems. This paper describes a numerical method to predict the relative SFG intensities of non-centrosymmetric nanodomains in 3D systems as functions of their size and concentration as well as their assembly patterns, i.e., the distributions of tilt, azimuth, and rotation angles with respect to the lab coordinate. We applied the developed method to predict changes in the CH and OH stretch modes characteristic to crystalline cellulose microfibrils distributed with various orders, which are relevant to plant cell wall structures. The same algorithm can also be applied to any SFG-active nanodomains interspersed in 3D amorphous matrices.

Most of scintillators used for radiation detection exhibit afterglow, which is emission of light with longer decay times than that of main light pulse. High signal from afterglow has usually negative influence on detection parameters, e.g. for energy resolution in spectrometry measurements. The paper deals with long-term afterglow of some types of scintillators, which is more significant in the case of integral measurement when current in the photodetector is measured. The range of studied decay times was in the order of tens of seconds to days. Seven types of scintillators were measured: BGO, CaF2(Eu), CdWO4, CsI(Tl), LiI(Eu), NaI(Tl) and plastic scintillator. Excitation of scintillators was made using a UV lamp. After UV irradiation, a scintillator was inserted to scintillation detection unit and the anode current of photomultiplier tube was measured with a picoammeter. As results, CaF2(Eu) and plastic scintillator have relatively low long-term afterglow signal compared with other measured scintillators.

The accuracy and precision of laser-induced breakdown spectroscopy (LIBS) quantitative analysis are significantly limited by the spectral noise. Normalization and ensemble averaging of multiple spectra were often used to preprocess spectra. However, these methods cannot completely remove the spectral noise. Data uncertainty due to the irremovable spectral noise will affect LIBS quantitative analysis. Therefore, this paper proposes a method using data uncertainty to improve the performance of LIBS quantitative analysis. The proposed method uses several spectra to characterize each sample to preserve some data uncertainty in the calibration data matrix. Thus, the data uncertainty is used to optimize the calibration model for improving the toleration to the spectral signal variation. As a result, the optimized calibration model had better accuracy and robustness than the calibration model trained by conventional method. The best root mean square error of prediction (RMSEP) of the ash content of coal was 1.152% for the optimized calibration model, while that for the conventional calibration model was 1.718%. The optimized calibration model also showed a lower relative standard deviation (RSD) value of repeated predictions. Moreover, the calibration model for predicting the ash content in biomass was also optimized by the proposed method. The optimized calibration model outperformed the conventional calibration model again, which demonstrated the extensive applicability of the proposed method.

The introduction of "deep learning" algorithms for feature identification in digital imaging has paved the way for artificial intelligence applications that up to a decade ago were considered technologically impossible to achieve, from the development of driverless vehicles to the fully automated diagnostics of cancer and other diseases from histological images. The success of deep learning applications has, in turn, attracted the attention of several researchers for the possible use of these methods in chemometrics, applied to the analysis of complex phenomena as, for example, the optical emission of laser-induced plasmas. In this paper, we will discuss the advantages and disadvantages of convolutional neural networks, one of the most diffused deep learning techniques, in laser-induced breakdown spectroscopy (LIBS) applications (classification and quantitative analysis), to understand the real potential of "deep LIBS" in practical everyday use. In particular, the comparison with the results obtained using "shallow" artificial neural networks will be presented and discussed, taking as a case study the analysis of six bronze samples of known composition. (Figure presented.).

In many areas, studying photostability or the mechanism of photodegradation is of high importance. Conventional methods to do so can be rather time-consuming, laborious, and prone to experimental errors. In this paper we evaluate an integrated and fully automated system for the study of light-induced degradation, comprising a liquid handler, an irradiation source and exposure cell with dedicated optics and spectrograph, and a liquid chromatography (LC) system. A liquid core waveguide (LCW) was used as an exposure cell, allowing efficient illumination of the sample over a 12 cm path length. This cell was coupled to a spectrograph, allowing in situ absorbance monitoring of the exposed sample during irradiation. The LCW is gas-permeable, permitting diffusion of air into the cell during light exposure. This unit was coupled online to LC with diode array detection for immediate and automated analysis of the composition of the light-exposed samples. The analytical performance of the new system was established by assessing linearity, limit of detection, and repeatability of the in-cell detection, sample recovery and carryover, and overall repeatability of light-induced degradation monitoring, using riboflavin as the test compound. The applicability of the system was demonstrated by recording a photodegradation time profile of riboflavin.

Fetal acidosis is one of the main concerns during labor. Currently, fetal blood sampling (FBS) has become the most accurate measurement of acidosis detection. However, it is invasive and does not provide a real time measurement due to laboratory procedures. Delays in diagnosis of acidosis have caused serious injury to the fetus, especially for the brain and the heart. This paper reviews the new technique in diagnosis of acidosis non-invasively. Magnetic Induction Spectroscopy (MIS) has been proposed to be a new device for acidosis detection in recent years. This paper explains the basic principle of MIS and outlines the design specifications and design considerations for a MIS pH probe. It is expected that readers will gain a basic understanding of the development of a MIS pH probe from this review.

Noninvasive detection of blood components is the most ideal and effective method to prevent and detect many clinical diseases. However, the accuracy of noninvasive detection based on the spectrum is not always satisfactory. The influence of various interferences in measurement limits the accuracy of the analysis. The dynamic spectrum theory can theoretically eliminate the individual differences and measurement environment influence and improve measurement accuracy. The concentration of globulin is closely related to the status of the immune system, which is of great significance for clinical diagnosis. This paper improves the signal-to-noise ratio from all links of dynamic spectrum data processing to realize the noninvasive detection of globulin. Through reasonable pretreatment, extraction, quality evaluation, and variable screening, the valid information of the spectrum gets maximum utilization. Finally, using the partial least squares prediction model to predict globulin concentration. The results show that the model established by dynamic spectrum treated by this method has a good predictive performance for globulin. The correlation coefficient of the prediction set is 0.962, the root-mean-square error of the prediction set is only 1.058 g/L, the correlation coefficient of the calibration set is 0.996, and the root-mean-square error of the calibration set is 0.332 g/L. The experimental results show that reasonable data processing of dynamic spectrum can effectively improve the signal-to-noise ratio of the data, make the established model have good prediction accuracy and performance, and realize the high-precision prediction globulin. This paper provides a complete research idea and method for the noninvasive detection of blood components. It is hopeful to realize the noninvasive quantitative detection of trace components in blood.

International audience; We investigated the non-uniformity of the response of the photocathodes of some PMTs and their potential influence on the results of scintillation measurements. We have developed an experimental system which allows us to study the non-uniformity of the photocathode response and its influence on the shape of alpha spectra obtained after pulse-shape discrimination. The system is presented together with the first tests of a Hamamatsu R7600U-200 PMT. A degradation of the counting efficiency and a shift of the peak position towards small values was identified in the measurements near the edges of the photocathode where the energy resolution is significantly worse than the energy resolution at the central region of the PMT. Such non-uniformity also affects absolute activity measurements based on the free parameter model, i.e., the Triple to Double coincidence Ratio (TDCR) method and the CIEMAT/NIST efficiency tracing method. The traditional free parameter model assumes a Poisson distribution of the number of emitted photons but the non-uniformity leads to a compound Poisson distribution, where the mean value of the distribution is a random variable. This introduces an extra variance of the calculated detection efficiency which should be taken into account in the measurement uncertainty budget. Experimental results are presented in the paper, together with their practical influence in scintillation measurements and absolute calibration of radionuclides.

Single particle inductively coupled plasma-mass spectrometry (spICP-MS) is an emerging technique that is capable of simultaneous measurement of the size and number concentration of metal-containing nanoparticles (NPs) at environmentally relevant levels. Although spICP-MS is widely applied to different fields, challenges remain in obtaining accurate and consistent particle number concentration (PNC) measurements. This paper presents, for the first time, a rigorous assessment of spICP-MS capabilities for measuring the PNC of gold NP (AuNP) suspensions of different sizes and coatings. The calibration of spICP-MS was accomplished with the National Institute of Standards and Technology (NIST) AuNP reference material (RM) 8013. The comparability of both spICP-MS direct and derived determination of PNC and reference PNC derived based on the mean particle size or the particle size distribution obtained by different reference sizing techniques was first assessed for NIST AuNP RM 8012, nominal diameter 30 nm. To enable a proper assessment of the accuracy of the spICP-MS results, a comprehensive estimation of the expanded uncertainty for PNC determination was carried out. Regardless of NP size or coating, a good agreement (90–110%) between spICP-MS direct determination of PNC and reported PNCs was obtained for all of the suspensions studied only when reliable in-house Au mass fractions and thorough mean particle size determinations were included in the calculation of the derived PNCs. The use of the particle size distribution over the mean size to derive PNCs resulted in larger differences for materials with a low contribution (

At present, in the chemical quantitative analysis of complex solutions based on spectroscopy, the accuracy of the content analysis of complex solution is difficult to meet the requirements due to the overlapping spectral lines, low signal-to-noise ratio, and scattering characteristics of various components of complex solution. In this paper, the logarithmic method is used to preprocess the spectral data in the spectral preprocessing stage, and the two-position and multi-mode joint spectral strategy of "M plus N" theory is applied to the quantitative analysis of serum components. The serum samples are illuminated by dual-position ultraviolet LED light source, and the two spectra of the vertical position and the coaxial facing position of the light source and the optical fiber are collected respectively. Then the partial least square (PLS) method was used to establish models to analyze the concentration of total bilirubin in serum by the spectrum of vertical position, the spectrum of coaxial facing position, and the spectrum of the combination of the former two. Among the experimental results, the model established by the combination of the two spectra collected by two positions has a good result. The correlation coefficient of all samples predicted by this model is 0.971223, and the root mean square error is 1.96645 μmol/L. This study shows that the method of the logarithmic, collecting spectra and analyzing the composition content of complex solutions by using the multi-location and multi-mode strategy of "M + N" theory can effectively improve the prediction accuracy of the model and has practical significance for the chemical quantitative analysis of complex solutions based on spectroscopy.

Durable chitosan-based coating material used as a barrier for slow-release fertilizers in the agricultural soil. This approach decreases the intense usage of fertilizer and works on their accessibility for the plants' necessities. In present paper, the proposed coating material was prepared on the basis of chitosan-kaolinite composite (CS-Gl-K). Fourier transform infrared spectroscopy analysis (FTIR), Scanning Electron Microscopy (SEM), thermogravimetric analysis (ATG), XRD, swelling degree and biodegradability studies were used to analyze the influence of the kaolinite clay incorporation in chitosan film properties. The characterization of the chitosan composites has been thoroughly studied. The NPK mineral fertilizer was coated according to the dip-immersing process of chitosan-kaolinite composites. Slow-release efficiency was evaluated by determining the rate of phosphorus release from the covered granules into water and soil. Moreover, phosphorus release from coated NPK/CS-Gl-K granules was generally delayed contrasted with NPK/uncoated. In addition, the biodegradation investigation of the composite material (CS-Gl-K) in soil was affirmed its durability. The proposed coating material has good slow-release properties, low cost and is environmentally friendly. The FTIR, ATG and XRD spectra revealed a good intercalation between the kaolinite-clay pores and chitosan chains.

Acridone and its derivatives have potential application as emitters for highly efficient blue organic light-emitting diodes (OLEDs). In this paper, we demonstrated ultrafast access of a solvent-independent singlet-triplet equilibrium state in acridone solutions by using femtosecond time-resolved spectroscopy. Our spectral data show that due to highly effective forward and reverse intersystem crossing (both kISC and krISC over 1010 s-1), a singlet-triplet equilibrium state is always populated in acridone in all solvents studied. However, the lifetimes of the equilibrium state varied a lot in different solvent environments and the final decay pathway of this state can switch between high quantum yield fluorescence emission and further internal conversion to the lowest triplet state. These findings provide direct experimental evidence to understand the distinct photophysical behaviors of acridone and also provide guidance for further design of acridone and its derivatives as blue OLED emitters.

In this paper, the first demonstration of direct ultratrace determination of lead in a single human hair by direct current-atmospheric pressure glow discharge-atomic emission spectrometry (DC-APGD-AES) coupled with electromagnetic heating vaporization (EMV) was described. Only the ultramicro mass of a human hair sample (about 0.15 mg, often a single human hair) was required during the analysis, and fast detection was implemented without tedious pretreatment processes, such as grinding and digestion. A limit of detection (LOD) of 30.8 μg kg-1 (4.8 pg) for Pb was obtained under optimized conditions, which was even equivalent to that of conventional LA-ICP-MS/ETV-ICP-MS/GFAAS. EMV-APGD-AES, meanwhile, can facilitate miniaturization and portability with low power and small size. The accuracy and practicality of the method were verified by the analysis of certified reference materials (CRMs) GBW09101b (human hair) and human hair samples from three volunteers. A simple, efficient, and low-cost method for detecting Pb in human hair has been developed.

Digital restoration is a rapidly growing methodology within the field of heritage conservation, especially for early cinematic films which have intrinsically unstable dye colourants that suffer from irreversible colour fading. Although numerous techniques to restore film digitally have emerged recently, complex degradation remains a challenging problem. This paper proposes a novel vector quantization (VQ) algorithm for restoring movie frames based on the acquisition of spectroscopic data with a custom-made push-broom VNIR hyperspectral camera (380–780 nm). The VQ algorithm utilizes what we call a multi-codebook that correlates degraded areas with corresponding non-degraded ones selected from reference frames. The spectral-codebook was compared with a professional commercially available film restoration software (DaVinci Resolve 17) tested both on RGB and on hyperspectral providing better results in terms of colour reconstruction.

Through pharmacological activity research, an increasing number of natural products and their derivatives are being recognized for their therapeutic value. In recent years, studies have been conducted on Corydalis yanhusuo W.T. Wang, a valuable medicinal herb listed in the Chinese Pharmacopoeia. Protopine, one of its components, has also become a research hotspot. To illustrate the identification, metabolism, and broad pharmacological activity of protopine and the botanical preparations containing it for further scientific studies and clinical applications, an in-depth and detailed review of protopine is required. We collected data on the identification and quantification, metabolism and pharmacokinetics, pharmacological activities, and botanical preparations of protopine from 1986 to 2021 from the PubMed database using “protopine” as a keyword. It has been shown that protopine as an active ingredient of many botanical preparations can be rapidly screened and quantified by a large number of methods (such as the LC-ESI-MS/MS and the TLC/GC-MS), and the possible metabolic pathways of protopine in vivo have been proposed. In addition, protopine possesses a wide range of pharmacological activities such as anti-inflammatory, anti-platelet aggregation, anti-cancer, analgesic, vasodilatory, anticholinesterase, anti-addictive, anticonvulsant, antipathogenic, antioxidant, hepatoprotective, neuroprotective, and cytotoxic and anti-proliferative activities. In this paper, the identification and quantification, metabolism and pharmacokinetics, pharmacological activities, and botanical preparations of protopine are reviewed in detail to lay a foundation for further scientific research and clinical applications of protopine.

Acknowledgements: This work is part of a project that has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 813786 (EVOdrops). This work reflects only the author's view, and the Research Executive Agency is not responsible for any use that may be made of the information it contains. It was supported by a studentship from the BBSRC Doctoral Training Account, (E. J. M., BB/M011194/1), a Trinity College/Benn W Levy SBS DTP PhD Studentship (M. G.) and an H2020 ERC Advanced Investigator Award (F. H., 695669)., Droplet microfluidics allows one to address the ever-increasing demand to screen large libraries of biological samples. Absorbance spectroscopy complements the golden standard of fluorescence detection by label free target identification and providing more quantifiable data. However, this is limited by speed and sensitivity. In this paper we increase the speed of sorting by including acoustofluidics, achieving sorting rates of target droplets of 1 kHz. We improved the device design for detection of absorbance using fibre-based interrogation of samples with integrated lenses in the microfluidic PDMS device for focusing and collimation of light. This optical improvement reduces the scattering and refraction artefacts, improving the signal quality and sensitivity. The novel design allows us to overcome limitations based on dielectrophoresis sorting, such as droplet size dependency, material and dielectric properties of samples. Our acoustic activated absorbance sorter removes the need for offset dyes or matching oils and sorts about a magnitude faster than current absorbance sorters.

In this paper, we propose the combined procedure of noble metal (NM) determination, including fire assay, acid digestion, and reversible dynamic sorptive preconcentration, followed by flow-injection ICP-MS. Reversible preconcentration of all NMs was carried out using micro-column packed new PVBC-VP sorbent and elution with a mixture of thiourea, potassium thiocyanate, and HCl, which recovers Pd, Ir, Pt, and Au by 95% and Ru, and Rh by 90%. The proposed procedure was approved using certified reference materials.

Through equipment monitoring, the uptimes of machines are enhanced in the industrial applications. The unpredicted failures risks are minimized by the proper equipment monitoring. The machine vibrations are increased caused by the failure modes. The vibration data requires effective analysis by the accurate assessment of the machine equipment. For fault feature selection and detection of faults in rotating equipment, the empirical knowledge is required. Low efficiency of the methods and motor speed control are the main drawbacks of the existing techniques. So the basic aim of this paper is the detection of rotating equipment faults by utilizing the vibration analysis. The motor vibration is analyzed and monitored using spectrum analysis. The spectral content are extracted and fed into the classifier like k-Nearest neighbors (KNN), back-propagation neural network BPNN, Sparse Representation Classifier (SRC), Support vector machine (SVM) and Random Forest (RF) for the type of failure prediction and analyze the unbalance condition (UNB), bearing faults (BDF), and broken rotor bars (BRB) faults. The RF classifier is better as compared to other classifiers in terms of accuracy, precision and recalls values by approximately 10.92 %, 11.03 % and 20.13 % respectively.

Atmospheric aerosols have effects on atmospheric radiation assessments, global climate change, local air quality and visibility. In particular, aerosols are more likely transformed and accumulated in winter. In this paper, we used the Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument to study the characteristics of aerosol type and contributions of PM2.5 chemical components to aerosol extinction (AE), vertical distribution of aerosols, and source. From December 30, 2018 to January 27, 2019, we conducted MAX-DOAS observations on Sanmenxia. The proportion of PM2.5 to PM10 was 69.48%–95.39%, indicating that the aerosol particles were mainly fine particles. By analyzing the ion data and modifying Interagency Monitoring of Protected Visual Environments (IMPROVE) method, we found that nitrate was the largest contributor to AE, accounting for 31.51%, 28.98%, and 27.95% of AE on heavily polluted, polluted, and clean days, respectively. NH4+, OC, and SO42− were also major contributors to AE. The near-surface aerosol extinction retrieved from MAX-DOAS measurement the PM2.5 and PM10 concentrations measured by an Unmanned Aerial Vehicle (UAV) have the same trend in vertical distribution. AE increased about 3 times from surface to 500 m. With the backward trajectory of the air mass during the haze, we also found that the continuous heavy pollution was mainly caused by transport of polluted air from the northeast, then followed by local industrial emissions and other sources of emissions under continuous and steady weather conditions.

This review aims to demonstrate abilities to analyze Big (Bio)Chemical Data (BBCD) with multivariate chemometric methods and to show some of the more important challenges of modern analytical researches. In this review, the capabilities and versatility of chemometric methods will be discussed in light of the BBCD challenges that are being encountered in chromatographic, spectroscopic and hyperspectral imaging measurements, with an emphasis on their application to omics sciences. In addition, insights and perspectives on how to address the analysis of BBCD are provided along with a discussion of the procedures necessary to obtain more reliable qualitative and quantitative results. In this review, the importance of Big Data and of their relevance to (bio)chemistry are first discussed. Then, analytical tools which can produce BBCD are presented as well as some basics needed to understand prospects and limitations of chemometric techniques when they are applied to BBCD are given. Finally, the significance of the combination of chemometric approaches with BBCD analysis in different chemical disciplines is highlighted with some examples. In this paper, we have tried to cover some of the applications of big data analysis in the (bio)chemistry field. However, this coverage is not extensive covering everything done in the field., Hadi Parastar would like to thank Sharif University of Technology (SUT) of Iran for financial support for a short sabbatical leave at IDAEA-CSIC of Barcelona. Roma Tauler would like to thank the European Research Council for the European Union’s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement no. 320737.

Starting from Quartz-Enhanced Photo-Acoustic Spectroscopy (QEPAS), we have explored the potential of a tightly linked method of gas/vapor sensing, from now on referred to as Tuning-Fork-Enhanced Photo-Acoustic Spectroscopy (TFEPAS). TFEPAS utilizes a non-piezoelectric metal or dielectric tuning fork to transduce the photoacoustic excitation and an optical interferometric readout to measure the amplitude of the tuning fork vibration. In particular, we have devised a solution based on Additive Manufacturing (AM) for the Absorption Detection Module (ADM). The novelty of our solution is that the ADM is entirely built monolithically by Micro-Metal Laser Sintering (MMLS) or other AM techniques to achieve easier and more cost-effective customization, extreme miniaturization of internal volumes, automatic alignment of the tuning fork with the acoustic micro-resonators, and operation at high temperature. This paper reports on preliminary experimental results achieved with ammonia at parts-per-million concentration in nitrogen to demonstrate the feasibility of the proposed solution. Prospectively, the proposed TFEPAS solution appears particularly suited for hyphenation to micro-Gas Chromatography and for the analysis of complex solid and liquid traces samples, including compounds with low volatility such as illicit drugs, explosives, and persistent chemical warfare agents.

During industrial operations and in confined places, carbon monoxide (CO) may collect in harmful proportions if ventilation is insufficient or appliances are not properly maintained. When the concentration of CO is too high, it might result in suffocation, coma, or even death. The detection of tiny concentrations of CO plays an important role in safe production. Due to the selective absorption of specific wavelengths of light by gas molecules, lasers have a wide range of applications in the field of gas detection. In this paper, a tunable diode laser absorption spectroscopy (TDLAS) system for CO detection was constructed using an interband cascaded laser (ICL) with a central wavelength of 4.625 μm. The modulated signal generated by the FPGA module was output to the laser controller to modulate the laser. The signal received by the detector was input to the FPGA module. After lock-in amplification, the second harmonic signal of high frequency modulation was output. Several concentrations of CO that were dispersed via static gas distribution were identified. A CO detection system with an open optical path was constructed, and the detection distance was about 8 m. The minimum detectable concentration is around 10.32 ppmm. The concentration of CO in the open optical path was 510.6 ppmm, according to the calibration of the detected concentration. The remote detection system based on TDLAS using an ICL can be used to monitor CO in the open optical path.

This paper reports the application of a low-cost diagnostic modality for fat analysis in a liver phantom as well as human liver donors. The device works on the principle of diffuse reflectance spectroscopy, which absorbs and/or scatters depending upon the molecules that compose a tissue. Here, we describe the development of liver phantom of varying fat concentration using saturated fat mimicking liver steatosis. Followed by a pilot study in the human liver donor setting. Later, handheld device based on Infrared-LED and Photodetector for real-time time assessment of live donor liver and fat assessment. Clinical Relevance- This device can be used in the development of an accurate and non-invasive for quantification of liver fat in the deceased donor selection process. It has an error margin of 10% in the quantification of fat which is comparable to a standard biopsy technique.

Medicinal and food homology materials are a group of drugs in herbal medicine that have nutritional value and can be used as functional food, with great potential for development and application. Flavonoids are one of the major groups of components in pharmaceutical and food materials that have been found to possess a variety of biological activities and pharmacological effects. More and more analytical techniques are being used in the study of flavonoid components of medicinal and food homology materials. Compared to traditional analytical methods, spectroscopic analysis has the advantages of being rapid, economical and free of chemical waste. It is therefore widely used for the identification and analysis of herbal components. This paper reviews the application of spectroscopic techniques in the study of flavonoid components in medicinal and food homology materials, including structure determination, content determination, quality identification, interaction studies, and the corresponding chemometrics. This review may provide some reference and assistance for future studies on the flavonoid composition of other medicinal and food homology materials.

Accurately quantifying unsteady methane venting from key oil and gas sector sources such as storage tanks and well casing vents is a critical challenge. Recently, we presented an optical sensor to meet this need that combines volume fraction and Doppler shift measurements using wavelength modulation spectroscopy with 2f harmonic detection to quantify mass flux of methane through a vent line. This paper extends the previous effort through a methodical component-by-component investigation of potential sources of thermally-induced measurement drift to guide the design of an updated sensor. Test data were analyzed using an innovative signal processing technique that permitted quantification of background wavelength modulation spectroscopy signal drift linked to specific components, and the results were successfully used to design a drift-resistant sensor. In the updated sensor, background signal strength was reduced, and stability improved, such that the empirical methane-fraction dependent velocity correction necessary in the original sensor was no longer required. The revised sensor improves previously reported measurement uncertainties on flow velocity from 0.15 to 0.10 m/s, while markedly reducing thermally-induced velocity drift from 0.44 m/s/K to 0.015 m/s/K. In the most general and challenging application, where both flow velocity and methane fraction are independently varying, the updated design reduces the methane mass flow rate uncertainty by more than a factor of six, from ±2.55 kg/h to ±0.40 kg/h. This new design also maintains the intrinsic safety of the original sensor and is ideally suited for unsteady methane vent measurements within hazardous locations typical of oil and gas facilities.