To systematically evaluate the application of near-infrared spectroscopy technology in the study of the effect of Baduanjin exercise on cognitive function in elderly people.Relevant literature was retrieved from PubMe...To systematically evaluate the application of near-infrared spectroscopy technology in the study of the effect of Baduanjin exercise on cognitive function in elderly people.Relevant literature was retrieved from PubMed,Web of Science core database,ScienceDirect,Wanfang,VIP,and CNKI from 2014 to June 2023,and relevant data were extracted.A total of 1 valid literature was obtained,published in 2022,sourced from the medical journal“FRONTIERS IN PUBLIC HEALTH”,with an impact factor of 6.46.This journal belongs to JCR Q1 area,and the SCI basic version of the Chinese Academy of Sciences is in the Q3 area of medicine.The inclusion criteria for the subjects of this study were age≥60 years,experience of Baduanjin exercise for≥3 years,and MMSE score≥24 points.This study,based on functional near-infrared spectroscopy technology,explores the effects of Baduanjin imagery and Baduanjin exercise on cognitive function in elderly people.Baduanjin exercise can increase brain connectivity,improve brain structural connections,and enhance brain function in elderly people.These three factors are also the main reasons for Baduanjin exercise to promote the improvement of cognitive function,including increasing brain gray matter volume,brain functional area connections,etc.Baduanjin exercise can improve specific cognitive functions by increasing gray matter volume.Baduanjin exercise can regulate the functional connections of the cognitive control network in elderly people and improve their memory.展开更多
[Objectives]This study was conducted to realize the rapid and nondestructive identification of blueberry producing areas and protect benefits of high-quality blueberry brands.[Methods]Five types of blueberries from di...[Objectives]This study was conducted to realize the rapid and nondestructive identification of blueberry producing areas and protect benefits of high-quality blueberry brands.[Methods]Five types of blueberries from different regions were selected as experimental subjects,and spectral analysis techniques were combined with deep learning.Firstly,standard normal variable transform(SNV)and convolutional smoothing(SG)were used to deal with scattering noise and other issues in original spectral data.Secondly,due to a large amount of redundant information and high correlation between adjacent wavelengths in the collected spectra,continuous projection algorithm(SPA)and partial least squares regression(PLS)were combined for screening of features with RMSE as the indicator,and 40 feature variables were obtained.Finally,a convolutional network model CNN-SE integrating a Squeeze and Excitation(SE)attention mechanism module was constructed and compared with convolutional neural network(CNN),support vector machine(SVM),and BP neural network.[Results]The CNN-SE model had the best effect,with the accuracy and precision of the test set reaching 95%and 94.56%,respectively,and the recall and F 1 score reaching 93.94%and 94.24%,respectively.[Conclusions]The CNN-SE convolution network model can realize rapid,nondestructive and high-throughout identification of blueberry producing areas.展开更多
Near infrared spectroscopy （NIR） is now probably the most popular process analytical technology （PAT） for pharmaceutical and some other industries. However, unlike mid-IR, NIR is known to have difficulties in moni...Near infrared spectroscopy （NIR） is now probably the most popular process analytical technology （PAT） for pharmaceutical and some other industries. However, unlike mid-IR, NIR is known to have difficulties in monitoring crystallization or precipitation processes because the existence of solids could cause distortion of the spectra. This phenomenon, seen as unfavorable previously, is however an indication that NIR spectra contain rich information about both solids and liquids, giving the possibility of using the same instrument for multiple property characterization. In this study, transflectance NIR calibration data was obtained using solutions and slurries of varied solution concentration, particle size, solid concentration and temperature. The data was used to build calibration models for prediction of the multiple properties of both phases. Predictive models were developed for this challenging application using an approach that combines genetic algorithm （GA） and support vector machine （SVM）. GA is used for wavelength selection and SVM for mode building. The new GA-SVM approach is shown to outperform other methods including GA-PLS （partial least squares） and traditional SVM. NIR is thus successfully applied to monitoring seeded and unseeded cooling crystallization processes of L-glutamic acid.展开更多
文摘To systematically evaluate the application of near-infrared spectroscopy technology in the study of the effect of Baduanjin exercise on cognitive function in elderly people.Relevant literature was retrieved from PubMed,Web of Science core database,ScienceDirect,Wanfang,VIP,and CNKI from 2014 to June 2023,and relevant data were extracted.A total of 1 valid literature was obtained,published in 2022,sourced from the medical journal“FRONTIERS IN PUBLIC HEALTH”,with an impact factor of 6.46.This journal belongs to JCR Q1 area,and the SCI basic version of the Chinese Academy of Sciences is in the Q3 area of medicine.The inclusion criteria for the subjects of this study were age≥60 years,experience of Baduanjin exercise for≥3 years,and MMSE score≥24 points.This study,based on functional near-infrared spectroscopy technology,explores the effects of Baduanjin imagery and Baduanjin exercise on cognitive function in elderly people.Baduanjin exercise can increase brain connectivity,improve brain structural connections,and enhance brain function in elderly people.These three factors are also the main reasons for Baduanjin exercise to promote the improvement of cognitive function,including increasing brain gray matter volume,brain functional area connections,etc.Baduanjin exercise can improve specific cognitive functions by increasing gray matter volume.Baduanjin exercise can regulate the functional connections of the cognitive control network in elderly people and improve their memory.
基金Supported by Natural Science Foundation of Heilongjiang Province(LH2022E099)Daqing Guidance Fund for Science and Technology Planning Project(zd-2023-63)San Heng San Zong Support Program of Heilongjiang Bayi Agricultural University(ZRCPY202216).
文摘[Objectives]This study was conducted to realize the rapid and nondestructive identification of blueberry producing areas and protect benefits of high-quality blueberry brands.[Methods]Five types of blueberries from different regions were selected as experimental subjects,and spectral analysis techniques were combined with deep learning.Firstly,standard normal variable transform(SNV)and convolutional smoothing(SG)were used to deal with scattering noise and other issues in original spectral data.Secondly,due to a large amount of redundant information and high correlation between adjacent wavelengths in the collected spectra,continuous projection algorithm(SPA)and partial least squares regression(PLS)were combined for screening of features with RMSE as the indicator,and 40 feature variables were obtained.Finally,a convolutional network model CNN-SE integrating a Squeeze and Excitation(SE)attention mechanism module was constructed and compared with convolutional neural network(CNN),support vector machine(SVM),and BP neural network.[Results]The CNN-SE model had the best effect,with the accuracy and precision of the test set reaching 95%and 94.56%,respectively,and the recall and F 1 score reaching 93.94%and 94.24%,respectively.[Conclusions]The CNN-SE convolution network model can realize rapid,nondestructive and high-throughout identification of blueberry producing areas.
基金UK Engineering and Physical Sciences Research Council for funding the research (EPSRCGrant Reference: EP/C001788/1)
文摘Near infrared spectroscopy （NIR） is now probably the most popular process analytical technology （PAT） for pharmaceutical and some other industries. However, unlike mid-IR, NIR is known to have difficulties in monitoring crystallization or precipitation processes because the existence of solids could cause distortion of the spectra. This phenomenon, seen as unfavorable previously, is however an indication that NIR spectra contain rich information about both solids and liquids, giving the possibility of using the same instrument for multiple property characterization. In this study, transflectance NIR calibration data was obtained using solutions and slurries of varied solution concentration, particle size, solid concentration and temperature. The data was used to build calibration models for prediction of the multiple properties of both phases. Predictive models were developed for this challenging application using an approach that combines genetic algorithm （GA） and support vector machine （SVM）. GA is used for wavelength selection and SVM for mode building. The new GA-SVM approach is shown to outperform other methods including GA-PLS （partial least squares） and traditional SVM. NIR is thus successfully applied to monitoring seeded and unseeded cooling crystallization processes of L-glutamic acid.
