Near Infrared Spectroscopy (NIRS) Model-Based Prediction for Protein Content in Cowpea

Cowpea (Vigna unguiculata L. Walp) is a multi-purpose legume with high quality protein for human consumption and livestock. The objective of this work was to develop near-infrared spectroscopy (NIRS) prediction models to estimate protein content in cowpea. A total of 116 cowpea breeding lines with a wide range of protein contents (19.28 % to 32.04%) were selected to build the model using whole seed and ground seed samples. Partial least-squares discriminant analysis (PLS-DA) regression technique with different pre-treatments (derivatives, standard normal variate, and multiplicative scatter correction) were carried out to develop the protein prediction model. Results showed: 1) spectral plots of both the whole seed and ground seed showed higher spectral scatter at higher wavelengths (>1450 nm), 2) data pre-processing affects prediction accuracy for bot whole seed and ground seed samples, 3) prediction using ground seed samples (0.64 R2 0.85) is better than the whole seed (0.33 R2 0.78), and 4) the data pre-processing second derivative with standard normal variate has the best prediction (R2_whole seed = 0.78, R2_ground seed = 0.85). The results will be of interest in cowpea breeding programs aimed at improving total seed protein content.

Noninvasive Detection of Cerebral Blood Flow and Blood Oxygen Based on Inductive Sensing Technology and Near Infrared Spectroscopy

The synchronous monitoring of cerebral blood flow and blood oxygen levels plays a pivotal role in the prevention,diagnosis,and treatment of cerebrovascular diseases.This study introduces a novel noninvasive device utilizing inductive sensing and near-infrared spectroscopy technology to facilitate simultaneous monitoring of cerebral blood flow and blood oxygen levels.The device consists of modules for cerebral blood flow monitoring,cerebral blood oxygen monitoring,control,communication,and a host machine.Through experiments conducted on healthy subjects,it was confirmed that the device can effectively achieve synchronous monitoring and recording of cerebral blood flow and blood oxygen signals.The results demonstrate the device’s capability to accurately measure these signals simultaneously.This technology enables dynamic monitoring of cerebral blood flow and blood oxygen signals with potential clinical applications in preventing,diagnosing,treating cerebrovascular diseases while reducing their associated harm.

Simulation and Modelling of near Infrared Spectroscopy (NIRS) as Brain Monitor

Near infrared spectroscopy (NIRS) is a method for non-invasive monitoring of cerebral oxygenation and haemodynamics. Different devices provide information on changes of oxygenated (HbO2) and deoxygenated haemoglobin (HHb), oxidized cytochrome aa3 (CytOx) or regional oxygen saturation (rSO2). NIRS has been used during adult and paediatric cardiac surgery.

Investigation of Prefrontal Cortex Activity in University Students with Presenteeism: A Near-Infrared Spectroscopy (NIRS) Study

Presenteeism refers to impaired performance attributed to attending work with health problems. There has been no study examining the state of presenteeism with objective measures. We compared cerebral hemodynamic changes, measured by near-infrared spectroscopy (NIRS), during neuropsychological tests conducted by university students with presenteeism and healthy controls. Twenty-two university students participated in the study;11 of them with impaired performance caused by mental health problem were allocated to the presenteeism group and 11 without health problems to the control group. Presenteeism was assessed by the Presenteeism Scale for Students. To evoke hemodynamics changes, the participants completed a Word Fluency Test (WFT) and a Trail Making Test (TMT). The NIRS probes were located over the bilateral prefrontal area. Students with presenteeism had significantly higher incidences of depression than controls. However, there was no significant difference in behavioral performance examinations between the two groups. With regard to hemodynamics changes, the repeated measures analysis of covariance of the NIRS signals revealed significant interactions between group and task activation. Although we observed a significant increase in oxygenated hemoglobin concentration during the WFT among controls (simple main effect;left channel, F(1, 19) = 27.34, P F(1, 19) = 22.05, P < 0.001), no changes were found in students with presenteeism during either the WFT (simple main effect;left channel, F(1, 19) = 0.12, P F(1, 19) = 0.08, P t = ﹣0.94, P with Bonferroni correction = 0.745;right channel, t = ﹣2.19, P with Bonferroni correction < 0.113). This is the first study to reveal differences in activity in the cerebral cortex associated with presenteeism. The fact that students with presenteeism have prefrontal dysfunction might reinforce the concept of presenteeism.

Correlation of prefrontal activity measured by near-infrared spectroscopy (NIRS) with mood, BDNF genotype and serum BDNF level in healthy individuals

Depression has been known to reduce the prefrontal activity associated with the execution of certain cognitive tasks, although whether a temporarily depressed or anxious mood in healthy individuals affects the prefrontal blood oxygen level during cognitive tasks is unknown. Combining the measurement of prefrontal activity with near-infrared spectroscopy (NIRS) and the two cognitive tasks, namely the letter version of the verbal fluency test (VFT-l) and the Stroop test, we measured the effect of a depressed or anxious mood and gender on the changes in the prefrontal oxygenated hemoglobin (Oxy-Hb) levels during those cognitive tests in healthy individuals. Depressed mood or anxious mood was assessed by the Hospital Anxiety and Depression Scale (HADS). Thereby we aimed to explore the possibility of NIRS measurement for detecting the early subclinical manifestation of major depression. Moreover, we examined the possible relationships between prefrontal activation and the functional Val66Met polymorphisms of the brain derived neurotropic factor (BDNF) gene and serum BDNF level. As a result, the increased prefrontal Oxy-Hb levels during cognitive tasks were significantly correlated with the severity of depressed mood in males. The course of the prefrontal Oxy-Hb increase was different depending on the cognitive tasks, i.e., the VFT-l or the Stroop test, in both genders. Correlations of BDNF genotype and serum BDNF level with the prefrontal Oxy-Hb levels during those cognitive tasks were negative. Our results suggest that the early subclinical manifestation of depressed mood in males might be detected by the NIRS measurement, which is not correlated with the individual properties of BDNF.

NIRS-XRF联用的煤炭发热量高稳定检测

实时获知煤炭发热量对于及时调整电站锅炉风粉配比和提高煤炭燃烧效率具有重要意义,为了实现电力生产中发热量的稳定快速检测,提出了一种近红外光谱(Near Infrared Spectroscopy, NIRS)与X射线荧光光谱(X-ray Fluorescence, XRF)联用的煤炭发热量高稳定检测方法,它结合了NIRS能高稳定检测煤中与发热量正相关的有机基团的优势与XRF能高稳定检测与发热量负相关的成灰元素的特点,大大提高了对煤炭发热量的测量重复性。在光谱预处理中,先将两套光谱融合作为偏最小二乘回归的输入变量进行全谱初步建模,依据回归系数选择NIRS光谱中的有效波段,再将它与XRF光谱中的成灰元素谱线一并融合进行归一化处理。建模时将预处理后的融合光谱数据作为输入变量,利用偏最小二乘回归对煤炭发热量进行建模。实验结果表明,NIRS-XRF联用方法对定标集煤样发热量预测的线性相关度系数(R^(2))为0.995,对验证集煤样发热量预测的最小均方根误差、平均相对误差和标准偏差分别为0.24 MJ/kg,0.61%和0.05 MJ/kg,测量重复性满足小于0.12 MJ/kg的国家标准。NIRS-XRF联用的煤炭发热量高稳定检测方法有望推广应用于火力发电、煤化工、冶金、水泥和焦化等“高碳”行业,助力我国按期实现碳中和目标。

Infrared Spectra of La_(0.65)Ba_xMnO_(3-δ) Oxides

The infrared spectra of La_(0.65)Ba_xMnO_(3-|?￡(c) (x = 0.35, 0.33 and 0.30) were investigated experimentally. The result shows that the sample La_(0.65)Ba_xMnO_(3-|?￡(c) has the largest Curie temperature and the smallest resistivity and wave number of the stretching vibration mode of MnO_6 octaheUron at 300 K among the investigated samples. However, the absorption strength for the stretching vibration mode of Mn0_6 octahedron in La_(0.65)Ba_xMnO_(3-|?￡(c) is stronger for parainagnetic phase than that for ferromagnelic phase, which may be connected with the reducing of the dynamic in- coherent Jahn-Teller distortion below Curie temperature. In addition, the large shift of wave number for the stretching mode at the temperatures from 293 to 423 K has been observed in La_(0.65)Ba_xMnO_(3-|?￡(c), which may be due to the in- crease of the Mn-O bond length with temperature increasing.

Syntheses and Infrared Spectra of Rare Earth Complexes with Diethyl Phosphate

The title complexes Ln(DEP),(Ln=La,Sm,Eu,Ho and Yb)were synthesized by reaction of triethyl phosphate with trivalent rare earth chlorides.The mechanism of thermo-decomposition of the complexes has been studied.According to their IR spectra,the residues of the thermo-decomposition of the complexes were identified as Ln(PO_3)_3.Their IR spectra were measured and principal IR bands were assigned.The experimental results of the IR spectra of the complexes show that the title complexes have the same coordination form and mo- lecular configuration as rare earth,e.g.Sm,complex with dimethyl phosphate(Sm(DMP)_3).Each of the rare earth ion links three rare earth ions nearby through double“O-P-O”bridges to form a special network of rings-linking-rings,each of which consists of twenty-four atoms.The Ln-O bond is principally ionic.

Spectra selection methods:A novel optimization way for treating dynamic spectra and in-line near infrared modeling

Near infrared(NIR)spectroscopy is now widely used influidized bed granulation.However,there are still some demerits that should be overcome in practice.Valid spectra selection during modeling process is now a hard nut to crack.In this study,a novel NIR sensor and a cosine distance method were introduced to solve this problem in order to make thefluidized process into"visualization".A NIR sensor wasfixed on the side of the expansion chamber to acquire the NIR spectra.Then valid spectra were selected based on a cosine distance method to reduce the influence of dynamic disturbances.Finally,spectral pretreatment and wavelength selection methods were investigated to establish partial least squares(PLS)models to monitor the mois-ture content.The results showed that the root mean square error of prediction(RMSEP)was 0.124%for moisture content model,which was much lower than that without valid spectra selection treatment.All results demonstrated that with the help of valid spectra selection treatment,NIR sensor could be used for real-time determination of critical quality attributes(CQAs)more accurately.It makes the manufacturing easier to understand than the process parameter control.

Infrared Low-Resolution Spectra of HAEBE Stars

IRAS low-resolution spectra are presented for 36 HAEBE stars. It is found that silicate dust in amorphous or glassy form is common material in the circumstellar disks or/and shells of HAEBE stars. It is also found that the PAH feature is often appeared as well.

Characteristic wavelength selection of volatile organic compounds infrared spectra based on improved interval partial least squares

As important components of air pollutant,volatile organic compounds(VOCs)can cause great harm to environment and human body.The concentration change of VOCs should be focused on in real-time environment monitoring system.In order to solve the problem of wavelength redundancy in full spectrum partial least squares(PLS)modeling for VOCs concentration analysis,a new method based on improved interval PLS(iPLS)integrated with Monte-Carlo sampling,called iPLS-MC method,was proposed to select optimal characteristic wavelengths of VOCs spectra.This method uses iPLS modeling to preselect the characteristic wavebands of the spectra and generates random wavelength combinations from the selected wavebands by Monte-Carlo sampling.The wavelength combination with the best prediction result in regression model is selected as the characteristic wavelengths of the spectrum.Different wavelength selection methods were built,respectively,on Fourier transform infrared(FTIR)spectra of ethylene and ethanol gas at different concentrations obtained in the laboratory.When the interval number of iPLS model is set to 30 and the Monte-Carlo sampling runs 1000 times,the characteristic wavelengths selected by iPLS-MC method can reduce from 8916 to 10,which occupies only 0.22%of the full spectrum wavelengths.While the RMSECV and correlation coefficient(Rc)for ethylene are 0.2977 and 0.9999 ppm,and those for ethanol gas are 0.2977 ppm and 0.9999.The experimental results show that the iPLS-MC method can select the optimal characteristic wavelengths of VOCs FTIR spectra stably and effectively,and the prediction performance of the regression model can be significantly improved and simplified by using characteristic wavelengths.

The near-infrared spectra and distribution of excited states of electrodeless discharge rubidium vapour lamps

The population ratio between the excited states of rubidium in the electrodeless discharge rubidium vapour lamp is calculated according to the near-infrared spectra in the region of 780-1550 nm. By using a 1529 nm laser, we measure the density of natural rubidium atoms at the 5P3/2 level. The populations of different excited states are then clarified.

Identification of Complex Ions of Nb(V)in FLINAK-O^(2-)System by Infrared Spectra

The FT-IR spectra for K_2NbF_7-FLINAK-O^(2-) solution were measured and compared with the spectra of crystalline K_2NbF_7 and K_2NbOF_6.The results show that the niobium fluoro-complex and/or oxyfluoro-complex ions are presented in these solutions.NbF_7^(2-) complex ion is the predominant species in Nb(V)-FLINAK solution(not considering oxide impurity).The influence of O^(2-) on the oxyfluoro-complex ions shows that NbOF_6^(3-) as a stable monooxyfluoro-complex anion presented in FLINAK-O^(2-) systems and the number of NbOF_6^(3-) species are increased with increasing of O^(2-) when molar ratio of O^(2-)/Nb(V) is less than 1.

Alcohols＇ Classification by Infrared Spectra Segment Based on Support Vector Machines

This paper studies various classifiers to identify primary, secondary or tertiary alcohols by using segmental spectra and their combinations to support vector machines （SVMs）. The results showed that the O-H in-plane bending absorption contributed most to identification their substitute. This conclusion disagrees with related known research results.

Application of Embedded Zerotree Wavelet to the Compression of Infrared Spectra

In this paper the embedded zerotree wavelet (EZW) method and Huffman coding are proposed to compress infrared (IR) spectra. We found that this technique is much better than others in terms of efficiently coding wavelet coefficients because the zerotree quantization is an effective way of exploiting the self-similarities of wavelet coefficients at various resolutions.

Isotopic Shifts of the infrared Spectra of Cholic Acid and Sodium Cholate

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Substructure Prediction from Infrared Spectra by Using Support Vector Machines

The potential of support vector machines （SVMs） for the substructure elucidation of infrared spectra have been investigated. The trained SVMs can identify the 16 substructures with high accuracy.

The Splittings of p_± States in Infrared Spectra of Thermal Donors in Silicon

p -type CZ silicon crystals annealed at 450℃ have been investigated by low temperature infrared spectroscopy with high resolusion. It has been shown that the 2p± and 3p± bands of neutral thermal donors TD~° are all split into two bands, which have not been reported before. In addition, the concentrations ofindi- vidual TD_i and total TD have been derived from the heights of 2po bands, and the boron concentrations de- rived from that of 320 cm^(-1) band. The room temperature resistivities of samples have been evaluated and the comparison with practically measured resistivities have been made.

Study on Membrane Microstructures and Characteristics of Infrared Spectra and Nitrogen Release of Solid-Liquid Reaction Coated Urea

The membrane microstructures and the mechanism of two coated ureas formed through solid- liquid reaction were observed by scanning electron microscope and infrared spectra, the relation of the structural characteristics with the nitrogen release feature was also discussed by combining with nitrogen dissolution in water. The results showed that the membranes were made of solid particles tightly connected to each other and were piled up layer by layer through liquid glue. Porosity and aperture of membrane were determined by compactness of piled layers and the particles in a single layer and also related to the characteristics of coating materials. Research of the infrared spectra of membrane, made of a solid powder and a liquid glue, proved that O-H on the solid surface was bonded with the double bond of the liquid glue, thus forming membrane and keeping it stable. It was found that the two coated ureas showed obvious differences in nitrogen releasing due to their membrane structures, the porosity and aperture of membrane were the critical factors for nitrogen releasing.

Rapid, Non-Destructive, Textile Classification Using SIMCA on Diffuse Near-Infrared Reflectance Spectra

Soft independent modeling of class analogy (SIMCA) was successful in classifying a large library of 758 commercially available, non-blended samples of acetate, cotton, polyester, rayon, silk and wool 89% - 98% of the time at the 95% confidence level (p = 0.05 significance level). In the present study, cotton and silk had a 62% and 24% chance, respectively, of being classified with their own group and also with rayon. SIMCA correctly identified a counterfeit “silk” sample as polyester. When coupled with diffuse NIR reflectance spectroscopy and a large sample library, SIMCA shows considerable promise as a quick, non-destructive, multivariate method for fiber identification. A major advantage is simplicity. No sample pretreatment of any kind was required, and no adjust-ments were made for fiber origin, manufacturing process residues, topical finishes, weave pattern, or dye content. Increasing the sample library should make the models more robust and improve identification rates over those reported in this paper.