Near-infrared Spectrophotometer Research Articles

Classification of Kudoa thyrsites infected and uninfected fish using a handheld near-infrared spectrophotometer, SIMCA and PLS-DA.

Kudoa thyrsites infection of marine fish typically results in myoliquefaction, which is only apparent 24 to 56 h post-mortem. The traditional methods for the detection of K. thyrsites infected fish are time-consuming and destructive, reducing its marketability. This poses a challenge for the fish industry to remove infected fish before it reaches the market or further processing activities. This study investigated the use of near-infrared (NIR) spectroscopy, in combination with soft independent modelling of class analogy (SIMCA) and partial least square discriminant analysis (PLS-DA), for discriminating K. thyrsites infected fish from uninfected fish. Performance of the classification models was evaluated by calculating the sensitivity, specificity and precision. A total of 334 fish samples (200 sardine, 64 hake and 70 kingklip) were used for this study. Infection of K. thyrsites was determined with the use of qPCR assays. Ninety per cent (90%) of the sardine samples, 78% of the hake samples and 37% of the kingklip samples were infected. Class groups of infected and uninfected fish samples were created for the purpose of generating SIMCA and PLS-DA classification models for each species of fish, as well as for a species independent data set. Principal component analysis (PCA) of NIR spectra did not show any clustering for infected and uninfected samples. Calibration and test sample sets were generated for the purpose of building and testing the SIMCA and PLD-DA classification models. SIMCA and PLS-DA were unable to classify test samples correctly into the two classes. The number of misclassifications (NMC) was higher for the SIMCA models than for the PLS-DA models, with more than 60% incorrectly classified. SIMCA classified most of the test samples into both classes. The precision for PLS-DA were 89% for sardine, 81% for hake, 0% for kingklip and 87% for species independent models, however, most samples were classified at infected. The use of NIR spectroscopy and classification models such as SIMCA and PLS-DA showed limited use as a method to distinguish between K. thyrsites infected and uninfected fish samples. Textural and chemical changes during extended frozen storage of the fish samples may have masked the effects associated with K. thyrsites infection. Further studies are suggested where NIR spectroscopy is used in combination with texture analysis and image spectroscopy.

SIMULATION OF AN AUTOMATIC CONTROL SYSTEM FOR A GRINDING MACHINE

This article discusses the MATLAB and MasterSCADA programs and the possibility of their joint application. To solve this problem, we used packages Fuzzy Logic Toolbox, Neural Network Toolbox, used in MATLAB that allow us to implement a process control model. The program implements the possibility of providing communication with the OPC Toolbox SCADA system, which allows for the interaction of system components using the OPC protocol. A block diagram of the control system of the pulverised unit has been developed, which acts on the control object through actuators. To implement an automated control system for the crumpling process, the following are offered: MATRIX-E/DUPLEX Q412/A near-infrared spectrophotometer, ARIES PLK controller, ARIES KIPPRIBO frequency converters

Non-destructive authentication of melon seed (Cucumeropsis mannii) powder using a pocket-sized near-infrared (NIR) spectrophotometer with multiple spectral preprocessing

Increasing demand for plant-based proteins has elicited suspicions of fraudulent practices among some producers of melon seed powder. The powder is suspected to be adulterated with carbohydrate-rich foods including maize, dried-milled cassava (gari) and soy flour to boost its quantity for increased profit. This study aimed to develop robust models using near-infrared spectroscopy (NIRS) for rapid authentication of melon seed powder. Melon seed powder samples containing 0–50 %w/w maize, gari and soy were prepared in triplicates and scanned using a handheld NIRS device. Proximate composition and color were significantly (p<0.05) affected by adulterant presence in melon seed powder. Classification models using linear discriminant analysis yielded accuracies of adulterant classification that were further confirmed by the high sensitivity, specificity and precision of the models (higher than 80 % in all cases). Low errors (RMSEC 3.28, RMSECV 3.92, RMSEP 6.87) % w/w, limits of detection and quantification and high coefficients (R2 0.96, R2CV 0.94, R2PRED 0.81) % w/w, indicative of reliable partial least squares models were obtained for the prediction of adulterants, protein, carbohydrate, total colour change, fat and lightness. Overall, Savitisky-Golay smoothing filter yield the best results in all LDA analysis. NIRS is a viable option for rapid non-invasive authentication of melon seed powder. The handheld device presents an added advantage of remote analysis. Instruments with other wavelength ranges can be explored in a similar approach study but with a higher sample size for more rigorous applications.

Field assessment of active ingredient quantity in pharmaceutical tablets with limited calibration of near infrared spectra: An application to ciprofloxacin tablets

Portable near-infrared (NIR) spectrophotometers have emerged as valuable tools for identifying substandard and falsified pharmaceuticals (SFPs). Integration of these devices with chemometric and machine learning models enhances their ability to provide quantitative chemical insights. However, different NIR spectrophotometer models vary in resolution, sensitivity, and responses to environmental factors such as temperature and humidity, necessitating instrument-specific libraries that hinder the wider adoption of NIR technology. This study addresses these challenges and seeks to establish a robust approach to promote the use of NIR technology in post-market pharmaceutical analysis. We developed support vector machine and partial least squares regression models based on binary mixtures of lab-made ciprofloxacin and microcrystalline cellulose, then applied the models to ciprofloxacin dosage forms that were assayed with high performance liquid chromatography (HPLC). A receiver operating characteristic (ROC) analysis was performed to set spectrophotometer independent NIR metrics to evaluate ciprofloxacin dosage forms as “meets standard,” “needs HPLC assay,” or “fails standard.” Over 200 ciprofloxacin tablets representing 50 different brands were evaluated using spectra acquired from three types of NIR spectrophotometer with 85% of the prediction agreeing with HPLC testing. This study shows that non-brand-specific predictive models can be applied across multiple spectrophotometers for rapid screening of the conformity of pharmaceutical active ingredients to regulatory standard.

Validation of a handheld near-infrared spectrophotometer for measurement of chemical intramuscular fat in Australian lamb

The objective of the study was to independently validate a calibrated commercial handheld near infrared (NIR) spectroscopic device and test its repeatability over time using phenotypically diverse populations of Australian lamb. Validation testing in eight separate data sub-groups (n = 1591 carcasses overall) demonstrated that the NIR device had moderate precision (R2 = 0.4–0.64, RMSEP = 0.70–1.22%) but fluctuated in accuracy between experimental site demonstrated by variable slopes (0.50–0.94) and biases (−0.86–0.02). The repeatability experiment (n = 10 carcasses) showed that time to scan post quartering affected NIR measurement from 0 to 24 h (P < 0.001). On average, NIR IMF% was 0.97% lower (P < 0.001) at 24 h (4.01% ± 0.166), compared to 0 h. There was no difference (P > 0.05) between Time 0 and 1 h or Time 0 and 4 h or between replicate scans within each time point. This study demonstrated the SOMA NIR device could predict lamb chemical IMF% with moderate precision and accuracy, however additional work is required to understand how loin preparation, blooming and surface hydration affect NIR measurement.

Determining Moisture Content of Basil Using Handheld Near-Infrared Spectroscopy

Accurate and rapid determination of moisture content is essential in crop production and decision-making for irrigation. Near-infrared (NIR) spectroscopy has been shown to be a promising method for determining moisture content in various agricultural products, including herbs and vegetables. This study tested the hypothesis that NIR spectroscopy is effective in accurately measuring the moisture content of Genovese basil (Ocimum basilicum L.), with the objective of developing a respective calibration model. Spectral data were obtained from a total of 120 basil leaf samples over a period of six days. These included freshly harvested and detached leaves, as well as those left in ambient air for 1–6 days. Five spectra were taken from each leaf using a handheld NIR spectrophotometer, which covers the first and second overtones of the NIR spectral region: 950–1650 nm. After the spectral acquisition, the leaves were weighed for fresh mass and then put in an oven for 72 h at 80 °C to determine the dry weight and calculate the reference moisture content. The calibration model was developed using multivariate analysis in MATLAB, including preprocessing and regression modeling. The data obtained from 75% of the samples were used for model training and 25% for validation. The final model demonstrates strong performance metrics. The root mean square error of calibration (RMSEC) is 2.9908, the root mean square error of cross-validation (RMSECV) is 3.2368, and the root mean square error of prediction (RMSEP) reaches 2.4675. The coefficients of determination for calibration (R2C) and cross-validation (R2CV) are consistent, with values of 0.829 and 0.80, respectively. The model’s predictive ability is indicated by a coefficient of determination for prediction (R2P) of 0.86. The range error ratio (RER) stands at 11.045—highlighting its predictive performance. Our investigation, using handheld NIR spectrophotometry, confirms NIR’s usefulness in basil moisture determination. The rapid determination offers valuable insights for irrigation and crop management.

A compact Fourier-transform near-infrared spectrophotometer and chemometrics for characterizing a comprehensive set of seized ecstasy samples

A comprehensive data set of ecstasy samples containing MDMA (N-methyl-3,4-methylenedioxyamphetamine) and MDA (3,4-methylenedioxyamphetamine) seized by the Brazilian Federal Police was characterized using spectral data obtained by a compact, low-cost, near-infrared Fourier-transform based spectrophotometer. Qualitative and quantitative characterization was accomplished using soft independent modeling of class analogy (SIMCA), linear discriminant analysis (LDA) classification, discriminating partial least square (PLS-DA), and regression models based on partial least square (PLS). By applying chemometric analysis, a protocol can be proposed for the in-field screening of seized ecstasy samples. The validation led to an efficiency superior to 96 % for ecstasy classification and estimating total actives, MDMA, and MDA content in the samples with a root mean square error of validation of 4.4, 4.2, and 2.7 % (m/m), respectively. The feasibility and drawbacks of the NIR technology applied to ecstasy characterization and the compromise between false positives and false negatives rate achieved by the classification models are discussed and a new approach to improve the classification robustness was proposed considering the forensic context.

Application of a short-wave pocket-sized near-infrared spectrophotometer to predict milk quality traits

Portable-hand-held devices based on near-infrared (NIR) technology have improved and are gaining popularity, even if their implementation in milk has been barely evaluated. Thus, the aim of the present study was to assess short-wave pocket-sized NIR devices' feasibility to predict milk quality. A total of 331 individual milk samples from different cow breeds and herds were collected in 2 consecutive days for chemical determination and spectral collection by using 2 pocket-sized NIR spectrophotometers working in the range of 740-1070 nm. The reference data was matched with the corresponding spectrum and modified-partial least-squares regression models were developed. A 5-fold cross-validation was applied to evaluate individual devices' performance and an external-validation with 25% of the data set as the validation set was applied for the final models. Results revealed that both devices' absorbance was highly correlated but greater for instrument A than B. Thus, the final models were built by averaging the spectra from both devices for each sample. The fat content prediction model was adequate for quality control with a coefficient of determination (R2ExV) and a residual predictive deviation (RPDExV) in external validation of 0.93 and 3.73, respectively. Protein and casein content as well as fat-to-protein ratio prediction models might be used for a rough screening (R2ExV > 0.70; RPDExV > 1.73). However, poor prediction models were obtained for all the other traits with an R2ExV between 0.43 (urea) and 0.03 (somatic cell count), and a RPDExV between 1.18 (urea) and 0.22 (somatic cell count). In conclusion, short-wave portable-hand-held NIR devices accurately predicted milk fat content, and protein, casein, and fat-to-protein ratio might be applied for rough screening. It seems that there is not enough information in this NIR region to develop adequate prediction models for lactose, somatic cell count, urea, and freezing point.

Sustainable reutilization of ion-adsorbed rare earth tailings: Preparation of low-cost functionalized pigments

In order to alleviate the ecological pressure caused by rare earth tailings, this study focuses on the application of ion-adsorbed rare earth tailings in the preparation of functional pigments. By using mechanical grinding and high-temperature calcination, 33 new functionalized red pigments were successfully prepared by doping iron and lanthanum elements. X-ray diffraction (XRD), scanning electron microscopy (SEM), CIE 1976 color space system, and ultraviolet–visible–near-infrared spectrophotometer were used for characterization. The synthesized pigment exhibits a rich color range from light yellow to reddish brown. Compared with commercially available iron red pigments, it exhibits significantly enhanced near-infrared reflectance, excellent acid and alkali resistance, and strong thermal stability up to 900 °C. It is worth noting that pigment P-1-2-1 achieved the best red value (L* = 43.73, a* = +24.07, b* = +15.65) with a maximum near-infrared reflectance of 91 %. Therefore, the utilization of rare earth tailings as raw materials for the preparation of functional pigments has significant effects. This study provides valuable insights for the development of eco-friendly pigments, which not only helps alleviate the urban heat island effect but also promotes the sustainable utilization of rare earth tailing resources, contributing to the achievement of carbon neutrality goals.

Sol-gel extended hydrothermal synthesis of BiFeO3 nano-beads for excellent photocatalytic and photo-electrochemical properties under natural light irradiation

The synthesized BiFeO3haslow cost,distinctive structure,large specific surface area, and outstanding electrical and mechanical properties, making itstable, non-toxic, and cost-effective material that can be used in photocatalytic applications. Here, we report the successful synthesis of a pure-phase BiFeO3nano-beads through a well-controlled sol–gel extended hydrothermal strategy. The structural, morphological, and optical properties of as-prepared BiFeO3nano-beads were studied by X-ray Diffractometer (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS), Brunauer-Emmett-Teller (BET) and Ultraviolet–visible–near-infrared (UV–vis–NIR) transmittance spectrophotometer. It was observed that BiFeO3nano-beads exhibit strong absorption in the UV and visible light region and the corresponding lowest band gap has been estimated to be 2.13 eV. The photo-electrochemical (PEC) properties of the prepared photo-anodes were analyzed with electrochemical impedance spectroscopy (EIS) and chronoamperometry analysis (CA). Electron transfer of the charge carriers and transient photo-current response were enhanced for BiFeO3nano-beads as studied by EIS and CA. The as-prepared BiFeO3nano-beads showed excellent photocatalytic and photo-electrochemical (PEC) properties for enhanced degradation of methylene blue (MB) and hydrogen evolution activity (14.7 mmol g−1h−1) in the presence of Platinum asco-catalyst were carried out under natural light irradiation at ambient temperature.

Assessment of bovine milk fatty acids using miniaturised near infrared spectrophotometer

Assessment of milk fatty acids has been proposed to support farm management practices including adjustment of feeding regimes and monitoring animal status. This study assessed the performance of a miniaturised near infrared (NIR) sensor for assessment of fatty acids in milk. Samples (n = 483) were from 114 farms, varying in lactation stages within two production seasons and included different dairy breeds. The fatty acids (C4:0, C6:0, C14:0, C16:0, C18:1 c9, SFA, MUFA, SCFA, BCFA) showed Ratio of performance to deviation values higher than two. The performance was equivalent to other independent studies utilising NIR. However, in this study, we used a low‐cost NIR spectrophotometer suitable for on‐the‐farm use.

Developments in analytical techniques for chemostratigraphy, chronostratigraphy, and geochemical fingerprinting studies: Current status and future trends

Chemostratigraphy utilizes the elemental, isotopic, and mineralogical compositions of sediments and rocks to understand the conditions of deposition and diagenesis, variations in paleo-redox conditions, climate, provenance, tectonic setting, and reservoir characteristics. This utility is based on the occurrences and stratigraphic variations of concentrations of certain elements, isotopes, minerals, and some organic compounds in sedimentary rocks. Significant progress has been made in the elemental, isotopic, and mineralogical determination techniques over the last couple of decades and this development is critically helpful to the applications of chemostratigraphy in widely varying fields including, but not limited to stratigraphy, depositional and diagenetic modelling, petroleum exploration, reservoir characterization, forensics, etc. Currently, highly precise data on about 60 elements in the range Li–U can be obtained very rapidly on a routine basis in different types of sediment samples such as drill cuttings, sediment cores, or hand specimens using various analytical techniques such as inductively coupled plasma mass spectrometry (ICP-MS), high resolution ICP-MS (HR-ICP-MS), and Mattauch–Herzog geometry ICP-MS (MH-ICP-MS). Elemental data as ratios of certain elements or proxy values in profile form with depth, isotope values, and certain ratios are used for understanding various geological processes in the earth's history. Mineralogical studies using techniques such as x-ray diffraction spectrometry (XRD) and Raman spectroscopy have proven to be very powerful for identifying different sedimentary successions belonging to different ages. There have been notable advances in the measurement of isotopic concentrations and isotopic ratios both in stable isotopes and radiogenic isotopes. Certain analytical techniques such as laser-induced breakdown spectroscopy (LIBS) are able to distinguish different rock types, their geographic sources, and the geological processes associated with their formation in a field setting in real-time. In addition to the instrumental developments, substantial progress is made in other critical areas such as sample preparation, sample decomposition, analytical protocols, development of international certified geochemical reference materials (CRMs), and quality issues in general. Until recently, the general approach in elemental and mineralogical chemostratigraphic studies was to follow time taking process of collecting the sediment/drill core samples in the field and bringing them to the laboratory to generate the analytical data. This is very expensive, time-consuming, and difficult for covering large areas. But, rapid advances in the area of analytical instrumentation saw some instruments such as x-ray fluorescence spectrometer (XRF), LIBS, visible and near-infrared spectrophotometer, and Raman spectrometer dramatically shrunk in size and have become portable, and changed this scenario completely and increased on-site applications in chemostratigraphy studies. In this review, these developments in analytical instrumentation in general together with some key applications in chemostratigraphy, chronostratigraphy, and geochemical fingerprinting have been summarized.

UV–Visible–NIR camouflage textiles with natural plant based natural dyes on natural fibre against woodland combat background for defence protection

Woodland combat background (CB) is a common source of natural plant based natural dyes (NPND). Swietenia Macrophylla, Mangifera Indica, Terminalia Arjuna, Corchorus Capsularis, Camellia Sinensis, Azadirachta Indica, Acacia Acuminata, Areca Catechu and Cinnamomum Tamala were dried-grinded-powdered-extracted-polyaziridine encapsulated-dyed-coated-printed with leafy design on cotton fabric and tested against woodland CB under the reflection engineering of ultraviolet (UV)–visible (Vis)–near infrared (NIR) spectrums and photographic versus chromatic techniques of Vis imaging. The reflection properties of NPND treated and untreated cotton fabric were experimented by UV–Vis–NIR spectrophotometer from 220 to 1400 nm. Six segments of field trialling for NPND treated woodland camouflage textiles were also investigated for concealment, detection, recognition and identification of target signature against forest plants/herbs species; common tree of woodland CB such as Shorea Robusta Gaertn, Bamboo Vulgaris, Musa Acuminata; and a wooden bridge made by Eucalyptus Citriodora & Bamboo Vulgaris. The imaging properties such as CIE L*, a*, b* and RGB (red, green, blue) of NPND treated cotton-garments were captured by digital camera from 400 to 700 nm against tree stem/bark, dry leaves, green leaves and dry wood of woodland CB. Therefore, a colorful matching for concealment, detection, recognition and identification of target signature against woodland CB was verified by Vis camera imaging and UV–Vis–NIR reflection mechanism. UV-protection property of Swietenia Macrophylla treated cotton fabric was also investigated by diffuse reflection for defence clothing. Simultaneous ‘camouflage textiles in UV–Vis–NIR’ and ‘UV-protective’ property of Swietenia Macrophylla treated fabric have been investigated for NPND materials-based textiles coloration (dyeing-coating-printing) which is a new concept for camouflage formulation of NPND dyed-NPND mordanted-NPND coated-NPND printed textiles in terms of ecofriendly source of woodland camouflage materials. Therefore, technical properties of NPND materials and methodologies of camouflage textile assessment have been advanced in addition to coloration philosophy of natural dyed-coated-printed textiles.

Monitoring of Emulsion Polymerization in the Presence of Ionic Liquids Using NIR Spectroscopy

AbstractMuch effort has been done toward the development of new emulsifiers able to improve the latex stability. In this sense, ionic liquids based on imidazolium constitute a new category of stabilizer in study. Moreover, the near infrared (NIR) spectroscopy has been extensively investigated as a tool to follow the properties of polymerization reactions. In this study different ionic liquids are investigated as emulsifiers during the emulsion homopolymerization of the styrene and methyl methacrylate. A quantitative analysis method is developed to determine the properties of latex based on the joint use of the NIR spectra and partial least squares regression (PLS). Kinetic results indicate that the latex properties are greatly influenced by the type of ionic liquid. The current work shows that the NIR spectrophotometer can be successfully used for monitoring of the latex properties, enabling to track the polymerization dynamics even in the presence of ionic liquids.

Comparison of Hemodynamic and Cerebral Oxygenation Responses during Exercise between Normal-Weight and Overweight Men.

Obesity has negative impacts on cardiovascular function and may increase cerebrovascular complications during exercise. We compared hemodynamic and cerebral oxygen changes during high-intensity exercise between overweight (OW) and normal-weight (NW) individuals. Eighteen NW and fourteen OW male individuals performed high-intensity (70% of peak oxygen uptake, VO2peak) cycling exercises for 30 min. Hemodynamics were measured using a bioelectrical impedance device, and cerebral oxygenation status was measured using a near-infrared spectrophotometer during and after exercise. The VO2peak of NW individuals was significantly higher than that of OW individuals (41.3 ± 5.7 vs. 30.0 ± 5.0 mL/min/kg, respectively; p < 0.05). During the 30 min exercise, both groups exhibited an increase in oxygenated hemoglobin (O2Hb) (p < 0.001), deoxygenated hemoglobin (p < 0.001), and cardiac output with increasing time. Post-exercise, cardiac output and systemic vascular resistance were significantly higher in the OW group than in the NW group (p < 0.05). The O2Hb in the NW group was significantly higher at post-exercise times of 20 min (13.9 ± 7.0 μmol/L) and 30 min (12.3 ± 8.7 μmol/L) than that in the OW group (1.0 ± 13.1 μmol/L and 0.6 ± 10.0 μmol/L, respectively; p = 0.024 vs. 0.023, respectively). OW participants demonstrated lower cerebral oxygenation and higher vascular resistance in the post-exercise phase than non-OW subjects. These physiological responses should be considered while engaging OW and obese individuals in vigorous exercise.

Evaluating the Use of a Similarity Index (SI) Combined with near Infrared (NIR) Spectroscopy as Method in Meat Species Authenticity

A hand-held near infrared (NIR) spectrophotometer combined with a similarity index (SI) method was evaluated to identify meat samples sourced from exotic and traditional meat species. Fresh meat cuts of lamb (Ovis aries), emu (Dromaius novaehollandiae), camel (Camelus dromedarius), and beef (Bos taurus) sourced from a commercial abattoir were used and analyzed using a hand-held NIR spectrophotometer. The NIR spectra of the commercial and exotic meat samples were analyzed using principal component analysis (PCA), linear discriminant analysis (LDA), and a similarity index (SI). The overall accuracy of the LDA models was 87.8%. Generally, the results of this study indicated that SI combined with NIR spectroscopy can distinguish meat samples sourced from different animal species. In future, we can expect that methods such as SI will improve the implementation of NIR spectroscopy in the meat and food industries as this method can be rapid, handy, affordable, and easy to understand for users and customers.

Near-IR luminescence at 1.06 μm of Nd3+-Pr3+ co-doped lithium fluorophosphate (LFP) glasses

We report experimental investigations into the co-doping of Nd3+-Pr3+ ions in LFP glasses. The method used in this study is the melt quench technique. Several physical and structural properties were investigated in this work. The structural properties were investigated by FTIR (Fourier Transform infrared) and XANES (X-ray absorption near edge structure) spectroscopy. The location of the white line peak at ∼6210 eV and the intensity of L3-edge XANES of Nd depend on the ratio of O/Nd in the glass matrix. Several excitations exhibited the luminescence properties in the photo and near-infrared spectrophotometer. The excitation at 481 nm shows seven peaks in the Nd3+ and Pr3+ transitions in the visible region. Meanwhile, the near-infrared region shows three peaks of Nd3+ and Pr3+ transitions at ∼1.06 μm wavelength.

Acute Effects Of The Passive Static Stretching On Central And Peripheral Hemodynamics

Acute one-legged intermittent static stretching reduces arterial stiffness only in the stretched leg. Continuous high shear stress (e.g., shear rate) on endothelial cells induces vasodilation with increased endothelial-derived relaxation factor. Our recent study showed that shear rate and blood flow in the posterior tibial artery of the stretched leg was increased after acute passive one-legged calf intermittent stretching. Thus, the static stretching increases shear rate after stretching and may consequently decreases arterial stiffness. However, it remains unclear whether changes in central and peripheral circulation are related to a mechanism of static stretching-induced decrease in arterial stiffness. PURPOSE: This study aimed to clarify the time-course of changes in central and peripheral circulation on the acute static stretching-induced increase in shear rate. METHODS: The changes in cardiac output as central hemodynamics and blood flow and shear rate in the posterior tibial artery as peripheral hemodynamics by using echocardiography and doppler ultrasound, and blood volume in the calf muscle as peripheral hemodynamics by using near-infrared spectrophotometer were measured during recovery (0-60s) from a single bout of one-legged passive calf stretching (0-30s) in 12 healthy young men (22.8 ± 1.1 years). Blood pressure was measured before and after stretching session. RESULTS: The stretched leg’s blood flow and shear rate in posterior tibial artery significantly increased from 0 to 10th s after stretching (each P < 0.05). The muscle blood volume in the stretched leg significantly reduced during stretching, and then significantly increased during the recovery period after stretching (each P < 0.05); however, blood pressure and cardiac output remained unchanged during stretching and recovery. CONCLUSION: These findings indicate that mild ischemia-reperfusion was caused mechanically by the stretching calf muscles rather than by central hemodynamics, and consequently, it may have induced the increases in blood flow and shear rate in the posterior tibial artery of the stretched leg.

Synthesis of tungsten oxide films at low processing temperature and their electrochromic properties

Tungsten oxide films with electrochromic properties were prepared by spin coating WCl6 ethanol solution on indium tin oxide (ITO) glass and polyethylene terephthalate (PET) substrate, and followed heat treatment at 60–400 °C in air for 1 h. The films were characterized by X-ray powder diffraction, scanning electron microscopy, energy spectrum analysis, electrochemistry and ultraviolet–visible–near-infrared (UV–Vis–NIR) spectrophotometer. Tungsten oxide films with different components can be obtained at different heat treatment temperatures. With the increase of heat treatment temperature, the products gradually lose the crystal water from WO3·2H2O to WO3·H2O and finally to WO3. The as-prepared film has many tiny cracks, which is beneficial for effective electrolyte penetration. The tungsten oxide PET films also show good electrochromic properties, and the coloring and bleaching processes are consistent with that of tungsten oxide device. The treatment at low temperature is no damage to the substrate and maintains the flexibility of the films. The method provides a simple, low-cost and large-scale practical scheme for the flexible electrochromic films.

Dual Wavelength based Approach with Partial Least Square Regression for the Prediction of Glucose Concentration

Diabetes mellitus is a group of metabolic disorder characterized by high blood sugar levels. Monitoring of blood glucose levels at regular intervals plays a crucial role in the management of diabetes. The non-invasive real-time monitoring of glucose using near-infrared (NIR), Raman, acoustic and bio-impedance techniques have an edge over available invasive techniques but suffers from low Signal to Noise ratio (S/N) and other interferences. In the present work, we have attempted to improve S/N for the efficient detection of feeble signals corresponding to the physiological glucose concentrations. Investigations were carried out in the NIR region particularly from 800-1400 nm for the identification of the unique absorption features of glucose using UV-Vis NIR spectrophotometer with different ranges of glucose concentrations including 5 g/dl- 45 g/dl, 1400 mg/dl -2500 mg/dl, 35 mg/dl-650 mg/dl . Savitzky Golay (SG) pre-processing filter was applied on the raw data for enhancing the S/N for better prediction of glucose concentrations. The absorption spectra of glucose revealed the presence of a peak at 960 nm. Therefore, considering the absorbance at 960 nm, provided an enhancement in the S/N ratio from 17 dB to 27 dB. Further, partial least square regression (PLSR), has been applied on SG filtered data for a better prediction of glucose concentration with a correlation coefficient ( R 2 ) value of 0.99 and root mean square error of prediction (RMSE) of 2.29 mg/dl. Further, based on the NIR spectral data, we have developed a measurement technique using two LED sources of 950 nm and 860 nm, and a wide detector (700 - 1100 nm) which converts obtained optical signal into voltage. It has been observed that by considering dual wavelength detection points the prediction of glucose concentration is improved. Furthermore, with increase in the test glucose concentrations, the voltage signal decreased corresponding to the 950 nm LED. This is attributed to reduced signal intensities reaching the photodiode as a result of the increase in glucose absorption. Incorporating dual wavelengths for PLSR reduced the RMSE from 8.98 mg/dl to 6.49 mg/dl and also improved the R 2 value from 0.97 to 0.99.