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...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 R<sup>2</sup> 0.85) is better than the whole seed (0.33 R<sup>2</sup> 0.78), and 4) the data pre-processing second derivative with standard normal variate has the best prediction (R<sup>2</sup>_whole seed = 0.78, R<sup>2</sup>_ground seed = 0.85). The results will be of interest in cowpea breeding programs aimed at improving total seed protein content.展开更多
After stroke,even high-functioning individuals may experience compromised bimanual coordination and fine motor dexterity,leading to reduced functional independence.Bilateral arm training has been proposed as a promisi...After stroke,even high-functioning individuals may experience compromised bimanual coordination and fine motor dexterity,leading to reduced functional independence.Bilateral arm training has been proposed as a promising intervention to address these deficits.However,the neural basis of the impairment of functional fine motor skills and their relationship to bimanual coordination performance in stroke patients remains unclear,limiting the development of more targeted interventions.To address this gap,our study employed functional near-infrared spectroscopy to investigate cortical responses in patients after stroke as they perform functional tasks that engage fine motor control and coordination.Twenty-four high-functioning patients with ischemic stroke(7 women,17 men;mean age 64.75±10.84 years)participated in this cross-sectional observational study and completed four subtasks from the Purdue Pegboard Test,which measures unimanual and bimanual finger and hand dexterity.We found significant bilateral activation of the sensorimotor cortices during all Purdue Pegboard Test subtasks,with bimanual tasks inducing higher cortical activation than the assembly subtask.Importantly,patients with better bimanual coordination exhibited lower cortical activation during the other three Purdue Pegboard Test subtasks.Notably,the observed neural response patterns varied depending on the specific subtask.In the unaffected hand task,the differences were primarily observed in the ipsilesional hemisphere.In contrast,the bilateral sensorimotor cortices and the contralesional hemisphere played a more prominent role in the bimanual task and assembly task,respectively.While significant correlations were found between cortical activation and unimanual tasks,no significant correlations were observed with bimanual tasks.This study provides insights into the neural basis of bimanual coordination and fine motor skills in high-functioning patients after stroke,highlighting task-dependent neural responses.The findings also suggest that patients who exhibit better bimanual performance demonstrate more efficient cortical activation.Therefore,incorporating bilateral arm training in post-stroke rehabilitation is important for better outcomes.The combination of functional near-infrared spectroscopy with functional motor paradigms is valuable for assessing skills and developing targeted interventions in stroke rehabilitation.展开更多
Non-invasive cerebral neuromodulation technologies are essential for the reorganization of cerebral neural networks,which have been widely applied in the field of central neurological diseases,such as stroke,Parkinson...Non-invasive cerebral neuromodulation technologies are essential for the reorganization of cerebral neural networks,which have been widely applied in the field of central neurological diseases,such as stroke,Parkinson’s disease,and mental disorders.Although significant advances have been made in neuromodulation technologies,the identification of optimal neurostimulation paramete rs including the co rtical target,duration,and inhibition or excitation pattern is still limited due to the lack of guidance for neural circuits.Moreove r,the neural mechanism unde rlying neuromodulation for improved behavioral performance remains poorly understood.Recently,advancements in neuroimaging have provided insight into neuromodulation techniques.Functional near-infrared spectroscopy,as a novel non-invasive optical brain imaging method,can detect brain activity by measuring cerebral hemodynamics with the advantages of portability,high motion tole rance,and anti-electromagnetic interference.Coupling functional near-infra red spectroscopy with neuromodulation technologies offe rs an opportunity to monitor the cortical response,provide realtime feedbac k,and establish a closed-loop strategy integrating evaluation,feedbac k,and intervention for neurostimulation,which provides a theoretical basis for development of individualized precise neuro rehabilitation.We aimed to summarize the advantages of functional near-infra red spectroscopy and provide an ove rview of the current research on functional near-infrared spectroscopy in transcranial magnetic stimulation,transcranial electrical stimulation,neurofeedback,and braincomputer interfaces.Furthermore,the future perspectives and directions for the application of functional near-infrared spectroscopy in neuromodulation are summarized.In conclusion,functional near-infrared spectroscopy combined with neuromodulation may promote the optimization of central pellral reorganization to achieve better functional recovery form central nervous system diseases.展开更多
One of the most pressing concerns for the consumer market is the detection of adulteration in meat products due to their preciousness.The rapid and accurate identification mechanism for lard adulteration in meat produ...One of the most pressing concerns for the consumer market is the detection of adulteration in meat products due to their preciousness.The rapid and accurate identification mechanism for lard adulteration in meat products is highly necessary,for developing a mechanism trusted by consumers and that can be used to make a definitive diagnosis.Fourier Transform Infrared Spectroscopy(FTIR)is used in this work to identify lard adulteration in cow,lamb,and chicken samples.A simplified extraction method was implied to obtain the lipids from pure and adulterated meat.Adulterated samples were obtained by mixing lard with chicken,lamb,and beef with different concentrations(10%–50%v/v).Principal component analysis(PCA)and partial least square(PLS)were used to develop a calibration model at 800–3500 cm^(−1).Three-dimension PCA was successfully used by dividing the spectrum in three regions to classify lard meat adulteration in chicken,lamb,and beef samples.The corresponding FTIR peaks for the lard have been observed at 1159.6,1743.4,2853.1,and 2922.5 cm−1,which differentiate chicken,lamb,and beef samples.The wavenumbers offer the highest determination coefficient R2 value of 0.846 and lowest root mean square error of calibration(RMSEC)and root mean square error prediction(RMSEP)with an accuracy of 84.6%.Even the tiniest fat adulteration up to 10%can be reliably discovered using this methodology.展开更多
For optimization of production processes and product quality,often knowledge of the factors influencing the process outcome is compulsory.Thus,process analytical technology(PAT)that allows deeper insight into the proc...For optimization of production processes and product quality,often knowledge of the factors influencing the process outcome is compulsory.Thus,process analytical technology(PAT)that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality.The present study aims at characterizing a well-known industrial process,the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters(FAME)for usage as biodiesel in a continuous micro reactor set-up.To this end,a design of experiment approach is applied,where the effects of two process factors,the molar ratio and the total flow rate of the reactants,are investigated.The optimized process target response is the FAME mass fraction in the purified nonpolar phase of the product as a measure of reaction yield.The quantification is performed using attenuated total reflection infrared spectroscopy in combination with partial least squares regression.The data retrieved during the conduction of the DoE experimental plan were used for statistical analysis.A non-linear model indicating a synergistic interaction between the studied factors describes the reactor behavior with a high coefficient of determination(R^(2))of 0.9608.Thus,we applied a PAT approach to generate further insight into this established industrial process.展开更多
The strength of water-bearing rock cannot be obtained in real time and by nondestructive experiments,which is an issue at cultural relics protection sites such as grotto temples.To solve this problem,we conducted a ne...The strength of water-bearing rock cannot be obtained in real time and by nondestructive experiments,which is an issue at cultural relics protection sites such as grotto temples.To solve this problem,we conducted a near-infrared spectrum acquisition experiment in the field and laboratory uniaxial compression strength tests on sandstone that had different water saturation levels.The correlations between the peak height and peak area of the nearinfrared absorption bands of the water-bearing sandstone and uniaxial compressive strength were analyzed.On this basis,a strength prediction model for water-bearing sandstone was established using the long short-term memory full convolutional network(LSTM-FCN)method.Subsequently,a field engineering test was carried out.The results showed that:(1)The sandstone samples had four distinct characteristic absorption peaks at 1400,1900,2200,and 2325 nm.The peak height and peak area of the absorption bands near 1400 nm and 1900 nm had a negative correlation with uniaxial compressive strength.The peak height and peak area of the absorption bands near 2200 nm and 2325 nm had nonlinear positive correlations with uniaxial compressive strength.(2)The LSTM-FCN method was used to establish a strength prediction model for water-bearing sandstone based on near-infrared spectroscopy,and the model achieved an accuracy of up to 97.52%.(3)The prediction model was used to realize non-destructive,quantitative,and real-time determination of uniaxial compressive strength;this represents a new method for the non-destructive testing of grotto rock mass at sites of cultural relics protection.展开更多
In situ and operando infrared spectroscopies are powerful techniques to support the design of novel materials for batteries and the development of new battery systems.These techniques can support the study of batterie...In situ and operando infrared spectroscopies are powerful techniques to support the design of novel materials for batteries and the development of new battery systems.These techniques can support the study of batteries by identifying the formation of new species and monitoring electrochemical energy stability.However,few works have employed these techniques,which can be used to investigate various materials,including systems beyond lithium-ion technology,in the research of batteries.Therefore,this review presents a comprehensive overview focusing on the main contributions of in situ and operando infrared spectroscopy for lithium-ion batteries(LIBs)and other battery systems.These techniques can successfully identify the formation of species during the electrolyte reduction,electrode degradation,and the formation of the solid-electrolyte interphase(SEI)layer.From these outcomes,it is possible to conclude that this characterization approach should be employed as a protocol to overcome remaining issues in batteries,consequently supporting battery research.This review aims to be a guide on how infrared spectroscopy can contribute to monitoring battery systems and to lead researchers interested in applying this technique.展开更多
Visible and near-infrared(vis-NIR)spectroscopy technique allows for fast and efficient determination of soil organic matter(SOM).However,a prior requirement for the vis-NIR spectroscopy technique to predict SOM is the...Visible and near-infrared(vis-NIR)spectroscopy technique allows for fast and efficient determination of soil organic matter(SOM).However,a prior requirement for the vis-NIR spectroscopy technique to predict SOM is the effective removal of redundant information.Therefore,this study aims to select three wavelength selection strategies for obtaining the spectral response characteristics of SOM.The SOM content and spectral information of 110 soil samples from the Ogan-Kuqa River Oasis were measured under laboratory conditions in July 2017.Pearson correlation analysis was introduced to preselect spectral wavelengths from the preprocessed spectra that passed the 0.01 level significance test.The successive projection algorithm(SPA),competitive adaptive reweighted sampling(CARS),and Boruta algorithm were used to detect the optimal variables from the preselected wavelengths.Finally,partial least squares regression(PLSR)and random forest(RF)models combined with the optimal wavelengths were applied to develop a quantitative estimation model of the SOM content.The results demonstrate that the optimal variables selected were mainly located near the range of spectral absorption features(i.e.,1400.0,1900.0,and 2200.0 nm),and the CARS and Boruta algorithm also selected a few visible wavelengths located in the range of 480.0–510.0 nm.Both models can achieve a more satisfactory prediction of the SOM content,and the RF model had better accuracy than the PLSR model.The SOM content prediction model established by Boruta algorithm combined with the RF model performed best with 23 variables and the model achieved the coefficient of determination(R2)of 0.78 and the residual prediction deviation(RPD)of 2.38.The Boruta algorithm effectively removed redundant information and optimized the optimal wavelengths to improve the prediction accuracy of the estimated SOM content.Therefore,combining vis-NIR spectroscopy with machine learning to estimate SOM content is an important method to improve the accuracy of SOM prediction in arid land.展开更多
Glycogen,amino acids,fatty acids,and other nutrient components affect the flavor and nutritional quality of oysters.Methods based on near-infrared reflectance spectroscopy(NIRS)were developed to rapidly and proximatel...Glycogen,amino acids,fatty acids,and other nutrient components affect the flavor and nutritional quality of oysters.Methods based on near-infrared reflectance spectroscopy(NIRS)were developed to rapidly and proximately determine the nutrient content of the Pacific oyster Crassostreagigas.Samples of C.gigas from 19 costal sites were freeze-dried,ground,and scanned for spectral data collection using a Fourier transform NIR spectrometer(Thermo Fisher Scientific).NIRS models of glycogen and other nutrients were established using partial least squares,multiplication scattering correction first-order derivation,and Norris smoothing.The R_(C) values of the glycogen,fatty acids,amino acids,and taurine NIRS models were 0.9678,0.9312,0.9132,and 0.8928,respectively,and the residual prediction deviation(RPD)values of these components were 3.15,2.16,3.11,and 1.59,respectively,indicating a high correlation between the predicted and observed values,and that the models can be used in practice.The models were used to evaluate the nutrient compositions of 1278 oyster samples.Glycogen content was found to be positively correlated with fatty acids and negatively correlated with amino acids.The glycogen,amino acid,and taurine levels of C.gigas cultured in the subtidal and intertidal zones were also significantly different.This study suggests that C.gigas NIRS models can be a cost-effective alternative to traditional methods for the rapid and proximate analysis of various slaughter traits and may also contribute to future genetic and breeding-related studies in Pacific oysters.展开更多
Mild cognitive impairment(MCI)is a precursor to Alzheimer’s disease.It is imperative to develop a proper treatment for this neurological disease in the aging society.This observational study investigated the effects ...Mild cognitive impairment(MCI)is a precursor to Alzheimer’s disease.It is imperative to develop a proper treatment for this neurological disease in the aging society.This observational study investigated the effects of acupuncture therapy on MCI patients.Eleven healthy individuals and eleven MCI patients were recruited for this study.Oxy-and deoxy-hemoglobin signals in the prefrontal cortex during working-memory tasks were monitored using functional near-infrared spectroscopy.Before acupuncture treatment,working-memory experiments were conducted for healthy control(HC)and MCI groups(MCI-0),followed by 24 sessions of acupuncture for the MCI group.The acupuncture sessions were initially carried out for 6 weeks(two sessions per week),after which experiments were performed again on the MCI group(MCI-1).This was followed by another set of acupuncture sessions that also lasted for 6 weeks,after which the experiments were repeated on the MCI group(MCI-2).Statistical analyses of the signals and classifications based on activation maps as well as temporal features were performed.The highest classification accuracies obtained using binary connectivity maps were 85.7%HC vs.MCI-0,69.5%HC vs.MCI-1,and 61.69%HC vs.MCI-2.The classification accuracies using the temporal features mean from 5 seconds to 28 seconds and maximum(i.e,max(5:28 seconds))values were 60.6%HC vs.MCI-0,56.9%HC vs.MCI-1,and 56.4%HC vs.MCI-2.The results reveal that there was a change in the temporal characteristics of the hemodynamic response of MCI patients due to acupuncture.This was reflected by a reduction in the classification accuracy after the therapy,indicating that the patients’brain responses improved and became comparable to those of healthy subjects.A similar trend was reflected in the classification using the image feature.These results indicate that acupuncture can be used for the treatment of MCI patients.展开更多
Near infrared spectrometer technology under a wavelength range of 918-1045 nm was used to rapidly detect paddy rice that was stored at 5℃, 15℃ and 25℃. A total of 121 paddy rice samples were collected from artifici...Near infrared spectrometer technology under a wavelength range of 918-1045 nm was used to rapidly detect paddy rice that was stored at 5℃, 15℃ and 25℃. A total of 121 paddy rice samples were collected from artificial infection with moulds to build the calibration models to calculate the total number colony of moulds based on the principal component regression method and multiple linear regression method. The results of statistical analysis indicated that multiple linear regression method was applicable to the detection of the total number colony of moulds. The correlation of calibration data set was 0.943. The correlation of prediction data set was 0.897. Therefore, the result showed that near infrared spectroscopy could be a useful instrumental method for determining the total number colony of moulds in paddy rice. The near infrared spectroscopy methodology could be applied for monitoring mould contamination in postharvest paddy rice during storage and might become a powerful tool for monitoring the safety of the grain.展开更多
The prickly pear fruit helps in combating viral based infections.It is used to treat diabetes and declared to possess hypoglycemic effects.There is also record of the usage of the fruit in the olden days as a remedy f...The prickly pear fruit helps in combating viral based infections.It is used to treat diabetes and declared to possess hypoglycemic effects.There is also record of the usage of the fruit in the olden days as a remedy for diabetes,lipid disorders,inflammation,ulcers,and pharmacologic side effects.The chemical composition and nutritional values of skin,flesh and seed of prickly pear fruit were investigated and discussed on a dry weight situation.The infrared spectra as well as scanning electron microscopy(SEM)techniques were used to identify the functional groups of carbohydrates,amino acids,and protein.The infrared spectral data of all three(skin,flesh,and seeds)species were recorded and assigned to the presence of distinguish peaks that referred to the three different sugars(glucose,fructose and saccharose)and cyclic aliphatic hydrocarbons moieties.On the other hand,the SEM is a powerful tool to investigate the morphological features of the components.SEM assays were examined on the surfaces of skin,flesh and seed branches showing a small particle that tends to form clusters with different shapes compared to each other.The Energy-dispersive X-ray spectroscopy(EDX)is an analytical technique used for the elemental analysis or chemical characterization of a sample.The EDX spectral technique of the skin,flesh and seeds were confirmed the presence of different essential and useful elements such as carbon,oxygen,magnesium,calcium,potassium,sulfur,aluminum,silicon,chloride,and phosphorus.展开更多
Over the last 100 years,significant advances have been made in the characterisation of milk composition for dairy cattle improvement programs.Technological progress has enabled a shift from labour intensive,on-farm co...Over the last 100 years,significant advances have been made in the characterisation of milk composition for dairy cattle improvement programs.Technological progress has enabled a shift from labour intensive,on-farm collection and processing of samples that assess yield and fat levels in milk,to large-scale processing of samples through centralised laboratories,with the scope extended to include quantification of other traits.Fourier-transform midinfrared(FT-MIR)spectroscopy has had a significant role in the transformation of milk composition phenotyping,with spectral-based predictions of major milk components already being widely used in milk payment and animal evaluation systems globally.Increasingly,there is interest in analysing the individual FT-MIR wavenumbers,and in utilising the FT-MIR data to predict other novel traits of importance to breeding programs.This includes traits related to the nutritional value of milk,the processability of milk into products such as cheese,and traits relevant to animal health and the environment.The ability to successfully incorporate these traits into breeding programs is dependent on the heritability of the FT-MIR predicted traits,and the genetic correlations between the FT-MIR predicted and actual trait values.Linking FT-MIR predicted traits to the underlying mutations responsible for their variation can be difficult because the phenotypic expression of these traits are a function of a diverse range of molecular and biological mechanisms that can obscure their genetic basis.The individual FT-MIR wavenumbers give insights into the chemical composition of milk and provide an additional layer of granularity that may assist with establishing causal links between the genome and observed phenotypes.Additionally,there are other molecular phenotypes such as those related to the metabolome,chromatin accessibility,and RNA editing that could improve our understanding of the underlying biological systems controlling traits of interest.Here we review topics of importance to phenotyping and genetic applications of FT-MIR spectra datasets,and discuss opportunities for consolidating FT-MIR datasets with other genomic and molecular data sources to improve future dairy cattle breeding programs.展开更多
Objective:To investigate the active components Zuogui Pill,a typical recipe for nourishing kidney essence in the traditional Chinese medicine.Methods:Adult male Sprague Dawley rats were treated with the traditional Ch...Objective:To investigate the active components Zuogui Pill,a typical recipe for nourishing kidney essence in the traditional Chinese medicine.Methods:Adult male Sprague Dawley rats were treated with the traditional Chinese herbal medicine Zuogui Pill and the active components found in the serum of the animals were analyzed by Fourier transform infrared(FTIR)spectroscopy.FTIR spectra of serum samples of treated and untreated rats were analyzed and the A2960/A2931 and A1540/A1080 ratios were calculated.Results:A2960/A2931 ratios of the serum samples collected following the administration of Zuogui Pill were significantly higher than those of the normal serum samples.FTIR data were then fitted using a Gaussian equation for wave numbers in the range of 1140e1000 cm1.ARNA/ADNA ratios in the serum of rats treated with Zuogui Pill were higher than those found in normal rat serum.Conclusion:FTIR spectroscopy could be used as an analytical tool to detect the activecomponents in serum of animals treated with Zuogui Pill.展开更多
Although near infrared (NIR) spectroscopy has been evaluated for numerous applications, the number of actual on-line or even on-site industrial applications seems to be very limited. In the present paper, the attempts...Although near infrared (NIR) spectroscopy has been evaluated for numerous applications, the number of actual on-line or even on-site industrial applications seems to be very limited. In the present paper, the attempts to produce online predictions of the chemical oxygen demand (COD) in wastewater from a pulp and paper mill using NIR spectroscopy are described. The task was perceived as very challenging, but with a root mean square error of prediction of 149 mg/l, roughly corresponding to 1/10 of the studied concentration interval, this attempt was deemed as successful. This result was obtained by using partial least squares model regression, interpolated reference values for calibration purposes, and by evenly distributing the calibration data in the concentration space. This work may also represent the first industrial application of online COD measurements in wastewater using NIR spectroscopy.展开更多
Using visible and near-infrared (Vis-NIR) spectroscopy combined with partial least squares (PLS) regression, the rapid reagent-free analysis model for chromium (Cr) content in tideland reclamation soil in the Pearl Ri...Using visible and near-infrared (Vis-NIR) spectroscopy combined with partial least squares (PLS) regression, the rapid reagent-free analysis model for chromium (Cr) content in tideland reclamation soil in the Pearl River Delta, China was established. Based on Savitzky-Golay (SG) smoothing and PLS regression, a multi-parameters optimization platform (SG-PLS) covering 264 modes was constructed to select the appropriately spectral preprocessing mode. The optimal SG-PLS model was determined according to the prediction effect. The selected optimal parameters <em>d, p, m</em> and LV were 2, 6, 23 and 8, respectively. Using the validation samples that were not involved in modeling, the root mean square error (SEP<sub>V</sub>), relative root mean square error (R-SEP<sub>V</sub>) and correlation coefficients (R<sub>P, V</sub>) of prediction were 11.66 mg<span style="white-space:nowrap;">·</span>kg<sup>-1</sup>, 10.7% and 0.722, respectively. The results indicated that the feasibility of using Vis-NIR spectroscopy combined with SG-PLS method to analyze soil Cr content. The constructed multi-parameters optimization platform with SG-PLS is expected to be applied to a wider field of analysis. The rapid detection method has important application values to large-scale agricultural production.展开更多
文摘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 R<sup>2</sup> 0.85) is better than the whole seed (0.33 R<sup>2</sup> 0.78), and 4) the data pre-processing second derivative with standard normal variate has the best prediction (R<sup>2</sup>_whole seed = 0.78, R<sup>2</sup>_ground seed = 0.85). The results will be of interest in cowpea breeding programs aimed at improving total seed protein content.
基金supported by the National Key R&D Program of China,No.2020YFC2004202(to DX).
文摘After stroke,even high-functioning individuals may experience compromised bimanual coordination and fine motor dexterity,leading to reduced functional independence.Bilateral arm training has been proposed as a promising intervention to address these deficits.However,the neural basis of the impairment of functional fine motor skills and their relationship to bimanual coordination performance in stroke patients remains unclear,limiting the development of more targeted interventions.To address this gap,our study employed functional near-infrared spectroscopy to investigate cortical responses in patients after stroke as they perform functional tasks that engage fine motor control and coordination.Twenty-four high-functioning patients with ischemic stroke(7 women,17 men;mean age 64.75±10.84 years)participated in this cross-sectional observational study and completed four subtasks from the Purdue Pegboard Test,which measures unimanual and bimanual finger and hand dexterity.We found significant bilateral activation of the sensorimotor cortices during all Purdue Pegboard Test subtasks,with bimanual tasks inducing higher cortical activation than the assembly subtask.Importantly,patients with better bimanual coordination exhibited lower cortical activation during the other three Purdue Pegboard Test subtasks.Notably,the observed neural response patterns varied depending on the specific subtask.In the unaffected hand task,the differences were primarily observed in the ipsilesional hemisphere.In contrast,the bilateral sensorimotor cortices and the contralesional hemisphere played a more prominent role in the bimanual task and assembly task,respectively.While significant correlations were found between cortical activation and unimanual tasks,no significant correlations were observed with bimanual tasks.This study provides insights into the neural basis of bimanual coordination and fine motor skills in high-functioning patients after stroke,highlighting task-dependent neural responses.The findings also suggest that patients who exhibit better bimanual performance demonstrate more efficient cortical activation.Therefore,incorporating bilateral arm training in post-stroke rehabilitation is important for better outcomes.The combination of functional near-infrared spectroscopy with functional motor paradigms is valuable for assessing skills and developing targeted interventions in stroke rehabilitation.
文摘Non-invasive cerebral neuromodulation technologies are essential for the reorganization of cerebral neural networks,which have been widely applied in the field of central neurological diseases,such as stroke,Parkinson’s disease,and mental disorders.Although significant advances have been made in neuromodulation technologies,the identification of optimal neurostimulation paramete rs including the co rtical target,duration,and inhibition or excitation pattern is still limited due to the lack of guidance for neural circuits.Moreove r,the neural mechanism unde rlying neuromodulation for improved behavioral performance remains poorly understood.Recently,advancements in neuroimaging have provided insight into neuromodulation techniques.Functional near-infrared spectroscopy,as a novel non-invasive optical brain imaging method,can detect brain activity by measuring cerebral hemodynamics with the advantages of portability,high motion tole rance,and anti-electromagnetic interference.Coupling functional near-infra red spectroscopy with neuromodulation technologies offe rs an opportunity to monitor the cortical response,provide realtime feedbac k,and establish a closed-loop strategy integrating evaluation,feedbac k,and intervention for neurostimulation,which provides a theoretical basis for development of individualized precise neuro rehabilitation.We aimed to summarize the advantages of functional near-infra red spectroscopy and provide an ove rview of the current research on functional near-infrared spectroscopy in transcranial magnetic stimulation,transcranial electrical stimulation,neurofeedback,and braincomputer interfaces.Furthermore,the future perspectives and directions for the application of functional near-infrared spectroscopy in neuromodulation are summarized.In conclusion,functional near-infrared spectroscopy combined with neuromodulation may promote the optimization of central pellral reorganization to achieve better functional recovery form central nervous system diseases.
文摘One of the most pressing concerns for the consumer market is the detection of adulteration in meat products due to their preciousness.The rapid and accurate identification mechanism for lard adulteration in meat products is highly necessary,for developing a mechanism trusted by consumers and that can be used to make a definitive diagnosis.Fourier Transform Infrared Spectroscopy(FTIR)is used in this work to identify lard adulteration in cow,lamb,and chicken samples.A simplified extraction method was implied to obtain the lipids from pure and adulterated meat.Adulterated samples were obtained by mixing lard with chicken,lamb,and beef with different concentrations(10%–50%v/v).Principal component analysis(PCA)and partial least square(PLS)were used to develop a calibration model at 800–3500 cm^(−1).Three-dimension PCA was successfully used by dividing the spectrum in three regions to classify lard meat adulteration in chicken,lamb,and beef samples.The corresponding FTIR peaks for the lard have been observed at 1159.6,1743.4,2853.1,and 2922.5 cm−1,which differentiate chicken,lamb,and beef samples.The wavenumbers offer the highest determination coefficient R2 value of 0.846 and lowest root mean square error of calibration(RMSEC)and root mean square error prediction(RMSEP)with an accuracy of 84.6%.Even the tiniest fat adulteration up to 10%can be reliably discovered using this methodology.
文摘For optimization of production processes and product quality,often knowledge of the factors influencing the process outcome is compulsory.Thus,process analytical technology(PAT)that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality.The present study aims at characterizing a well-known industrial process,the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters(FAME)for usage as biodiesel in a continuous micro reactor set-up.To this end,a design of experiment approach is applied,where the effects of two process factors,the molar ratio and the total flow rate of the reactants,are investigated.The optimized process target response is the FAME mass fraction in the purified nonpolar phase of the product as a measure of reaction yield.The quantification is performed using attenuated total reflection infrared spectroscopy in combination with partial least squares regression.The data retrieved during the conduction of the DoE experimental plan were used for statistical analysis.A non-linear model indicating a synergistic interaction between the studied factors describes the reactor behavior with a high coefficient of determination(R^(2))of 0.9608.Thus,we applied a PAT approach to generate further insight into this established industrial process.
基金supported by the Zhejiang Provincial Collaborative Innovation Center of Mountain Geological Hazard Prevention(PCMGH-2021-05)the Special Fund for Fundamental Research Business Expenses of Central Universities(Grant No.600101110102)。
文摘The strength of water-bearing rock cannot be obtained in real time and by nondestructive experiments,which is an issue at cultural relics protection sites such as grotto temples.To solve this problem,we conducted a near-infrared spectrum acquisition experiment in the field and laboratory uniaxial compression strength tests on sandstone that had different water saturation levels.The correlations between the peak height and peak area of the nearinfrared absorption bands of the water-bearing sandstone and uniaxial compressive strength were analyzed.On this basis,a strength prediction model for water-bearing sandstone was established using the long short-term memory full convolutional network(LSTM-FCN)method.Subsequently,a field engineering test was carried out.The results showed that:(1)The sandstone samples had four distinct characteristic absorption peaks at 1400,1900,2200,and 2325 nm.The peak height and peak area of the absorption bands near 1400 nm and 1900 nm had a negative correlation with uniaxial compressive strength.The peak height and peak area of the absorption bands near 2200 nm and 2325 nm had nonlinear positive correlations with uniaxial compressive strength.(2)The LSTM-FCN method was used to establish a strength prediction model for water-bearing sandstone based on near-infrared spectroscopy,and the model achieved an accuracy of up to 97.52%.(3)The prediction model was used to realize non-destructive,quantitative,and real-time determination of uniaxial compressive strength;this represents a new method for the non-destructive testing of grotto rock mass at sites of cultural relics protection.
基金the financial support received from Kansas State University and the UNICAMP Development Foundation (FUNCAMP)the Brazilian Coordination for the Improvement of Higher Education Personnel–CAPES (Pr Int 88887.572651/2020-00+8 种基金88887.374731/2019-00)the financial support from the Brazilian National Council for Scientific and Technological Development–CNPq (310544/2019-0-PQ-2 grant)the S?o Paulo Research Foundation–FAPESP (2020/04431-02017/11958-12014/02163-7)the UNICAMP Development Foundation–FUNCAMP,Shellthe strategic importance of the support given by Brazil’s National Oil,Natural Gas,and Biofuels Agency–ANP via the R&D levy regulationNational Science Foundation Grant (1743701)CMMI NSF CAREER Grant (1454151)。
文摘In situ and operando infrared spectroscopies are powerful techniques to support the design of novel materials for batteries and the development of new battery systems.These techniques can support the study of batteries by identifying the formation of new species and monitoring electrochemical energy stability.However,few works have employed these techniques,which can be used to investigate various materials,including systems beyond lithium-ion technology,in the research of batteries.Therefore,this review presents a comprehensive overview focusing on the main contributions of in situ and operando infrared spectroscopy for lithium-ion batteries(LIBs)and other battery systems.These techniques can successfully identify the formation of species during the electrolyte reduction,electrode degradation,and the formation of the solid-electrolyte interphase(SEI)layer.From these outcomes,it is possible to conclude that this characterization approach should be employed as a protocol to overcome remaining issues in batteries,consequently supporting battery research.This review aims to be a guide on how infrared spectroscopy can contribute to monitoring battery systems and to lead researchers interested in applying this technique.
基金supported by the Key Project of Natural Science Foundation of Xinjiang Uygur Autonomous Region,China(2021D01D06)the National Natural Science Foundation of China(41961059)。
文摘Visible and near-infrared(vis-NIR)spectroscopy technique allows for fast and efficient determination of soil organic matter(SOM).However,a prior requirement for the vis-NIR spectroscopy technique to predict SOM is the effective removal of redundant information.Therefore,this study aims to select three wavelength selection strategies for obtaining the spectral response characteristics of SOM.The SOM content and spectral information of 110 soil samples from the Ogan-Kuqa River Oasis were measured under laboratory conditions in July 2017.Pearson correlation analysis was introduced to preselect spectral wavelengths from the preprocessed spectra that passed the 0.01 level significance test.The successive projection algorithm(SPA),competitive adaptive reweighted sampling(CARS),and Boruta algorithm were used to detect the optimal variables from the preselected wavelengths.Finally,partial least squares regression(PLSR)and random forest(RF)models combined with the optimal wavelengths were applied to develop a quantitative estimation model of the SOM content.The results demonstrate that the optimal variables selected were mainly located near the range of spectral absorption features(i.e.,1400.0,1900.0,and 2200.0 nm),and the CARS and Boruta algorithm also selected a few visible wavelengths located in the range of 480.0–510.0 nm.Both models can achieve a more satisfactory prediction of the SOM content,and the RF model had better accuracy than the PLSR model.The SOM content prediction model established by Boruta algorithm combined with the RF model performed best with 23 variables and the model achieved the coefficient of determination(R2)of 0.78 and the residual prediction deviation(RPD)of 2.38.The Boruta algorithm effectively removed redundant information and optimized the optimal wavelengths to improve the prediction accuracy of the estimated SOM content.Therefore,combining vis-NIR spectroscopy with machine learning to estimate SOM content is an important method to improve the accuracy of SOM prediction in arid land.
基金Supported by the Shandong Province Key R&D Program Project(No.2021LZGC029)the Major Scientific and Technological Innovation Project of Shandong Province(No.2019JZZY010813)+2 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA24030105)the Qingdao Key Technology and Industrialization Demonstration Project(No.22-3-3-hygg-2-hy)the Earmarked Fund for China Agriculture Research System(No.CARS-49)。
文摘Glycogen,amino acids,fatty acids,and other nutrient components affect the flavor and nutritional quality of oysters.Methods based on near-infrared reflectance spectroscopy(NIRS)were developed to rapidly and proximately determine the nutrient content of the Pacific oyster Crassostreagigas.Samples of C.gigas from 19 costal sites were freeze-dried,ground,and scanned for spectral data collection using a Fourier transform NIR spectrometer(Thermo Fisher Scientific).NIRS models of glycogen and other nutrients were established using partial least squares,multiplication scattering correction first-order derivation,and Norris smoothing.The R_(C) values of the glycogen,fatty acids,amino acids,and taurine NIRS models were 0.9678,0.9312,0.9132,and 0.8928,respectively,and the residual prediction deviation(RPD)values of these components were 3.15,2.16,3.11,and 1.59,respectively,indicating a high correlation between the predicted and observed values,and that the models can be used in practice.The models were used to evaluate the nutrient compositions of 1278 oyster samples.Glycogen content was found to be positively correlated with fatty acids and negatively correlated with amino acids.The glycogen,amino acid,and taurine levels of C.gigas cultured in the subtidal and intertidal zones were also significantly different.This study suggests that C.gigas NIRS models can be a cost-effective alternative to traditional methods for the rapid and proximate analysis of various slaughter traits and may also contribute to future genetic and breeding-related studies in Pacific oysters.
基金supported by National Research Foundation(NRF)of Korea under the auspices of the Ministry of Science and ICT,Republic of Korea(No.NRF-2020R1A2B5B03096000,to KSH).
文摘Mild cognitive impairment(MCI)is a precursor to Alzheimer’s disease.It is imperative to develop a proper treatment for this neurological disease in the aging society.This observational study investigated the effects of acupuncture therapy on MCI patients.Eleven healthy individuals and eleven MCI patients were recruited for this study.Oxy-and deoxy-hemoglobin signals in the prefrontal cortex during working-memory tasks were monitored using functional near-infrared spectroscopy.Before acupuncture treatment,working-memory experiments were conducted for healthy control(HC)and MCI groups(MCI-0),followed by 24 sessions of acupuncture for the MCI group.The acupuncture sessions were initially carried out for 6 weeks(two sessions per week),after which experiments were performed again on the MCI group(MCI-1).This was followed by another set of acupuncture sessions that also lasted for 6 weeks,after which the experiments were repeated on the MCI group(MCI-2).Statistical analyses of the signals and classifications based on activation maps as well as temporal features were performed.The highest classification accuracies obtained using binary connectivity maps were 85.7%HC vs.MCI-0,69.5%HC vs.MCI-1,and 61.69%HC vs.MCI-2.The classification accuracies using the temporal features mean from 5 seconds to 28 seconds and maximum(i.e,max(5:28 seconds))values were 60.6%HC vs.MCI-0,56.9%HC vs.MCI-1,and 56.4%HC vs.MCI-2.The results reveal that there was a change in the temporal characteristics of the hemodynamic response of MCI patients due to acupuncture.This was reflected by a reduction in the classification accuracy after the therapy,indicating that the patients’brain responses improved and became comparable to those of healthy subjects.A similar trend was reflected in the classification using the image feature.These results indicate that acupuncture can be used for the treatment of MCI patients.
基金Supported by the National 12th Five-year Plan for Science&Technology Support Fund(2012BAK08B04-02)the Heilongjiang Science and Technology Plan(GC12B404)
文摘Near infrared spectrometer technology under a wavelength range of 918-1045 nm was used to rapidly detect paddy rice that was stored at 5℃, 15℃ and 25℃. A total of 121 paddy rice samples were collected from artificial infection with moulds to build the calibration models to calculate the total number colony of moulds based on the principal component regression method and multiple linear regression method. The results of statistical analysis indicated that multiple linear regression method was applicable to the detection of the total number colony of moulds. The correlation of calibration data set was 0.943. The correlation of prediction data set was 0.897. Therefore, the result showed that near infrared spectroscopy could be a useful instrumental method for determining the total number colony of moulds in paddy rice. The near infrared spectroscopy methodology could be applied for monitoring mould contamination in postharvest paddy rice during storage and might become a powerful tool for monitoring the safety of the grain.
基金Taif University Researches Supporting Project number(TURSP-2020/01),Taif University,Taif,Saudi Arabia。
文摘The prickly pear fruit helps in combating viral based infections.It is used to treat diabetes and declared to possess hypoglycemic effects.There is also record of the usage of the fruit in the olden days as a remedy for diabetes,lipid disorders,inflammation,ulcers,and pharmacologic side effects.The chemical composition and nutritional values of skin,flesh and seed of prickly pear fruit were investigated and discussed on a dry weight situation.The infrared spectra as well as scanning electron microscopy(SEM)techniques were used to identify the functional groups of carbohydrates,amino acids,and protein.The infrared spectral data of all three(skin,flesh,and seeds)species were recorded and assigned to the presence of distinguish peaks that referred to the three different sugars(glucose,fructose and saccharose)and cyclic aliphatic hydrocarbons moieties.On the other hand,the SEM is a powerful tool to investigate the morphological features of the components.SEM assays were examined on the surfaces of skin,flesh and seed branches showing a small particle that tends to form clusters with different shapes compared to each other.The Energy-dispersive X-ray spectroscopy(EDX)is an analytical technique used for the elemental analysis or chemical characterization of a sample.The EDX spectral technique of the skin,flesh and seeds were confirmed the presence of different essential and useful elements such as carbon,oxygen,magnesium,calcium,potassium,sulfur,aluminum,silicon,chloride,and phosphorus.
基金funded by Livestock Improvement Corporation(LIC)the New Zealand Ministry for Primary Industries,through the Sustainable Food&Fibre Futures programme.
文摘Over the last 100 years,significant advances have been made in the characterisation of milk composition for dairy cattle improvement programs.Technological progress has enabled a shift from labour intensive,on-farm collection and processing of samples that assess yield and fat levels in milk,to large-scale processing of samples through centralised laboratories,with the scope extended to include quantification of other traits.Fourier-transform midinfrared(FT-MIR)spectroscopy has had a significant role in the transformation of milk composition phenotyping,with spectral-based predictions of major milk components already being widely used in milk payment and animal evaluation systems globally.Increasingly,there is interest in analysing the individual FT-MIR wavenumbers,and in utilising the FT-MIR data to predict other novel traits of importance to breeding programs.This includes traits related to the nutritional value of milk,the processability of milk into products such as cheese,and traits relevant to animal health and the environment.The ability to successfully incorporate these traits into breeding programs is dependent on the heritability of the FT-MIR predicted traits,and the genetic correlations between the FT-MIR predicted and actual trait values.Linking FT-MIR predicted traits to the underlying mutations responsible for their variation can be difficult because the phenotypic expression of these traits are a function of a diverse range of molecular and biological mechanisms that can obscure their genetic basis.The individual FT-MIR wavenumbers give insights into the chemical composition of milk and provide an additional layer of granularity that may assist with establishing causal links between the genome and observed phenotypes.Additionally,there are other molecular phenotypes such as those related to the metabolome,chromatin accessibility,and RNA editing that could improve our understanding of the underlying biological systems controlling traits of interest.Here we review topics of importance to phenotyping and genetic applications of FT-MIR spectra datasets,and discuss opportunities for consolidating FT-MIR datasets with other genomic and molecular data sources to improve future dairy cattle breeding programs.
基金the National International Cooperation Science and Technology Support Program of the Ministry of Science and Technology of the People’s Republic of China(2012DFA31330).
文摘Objective:To investigate the active components Zuogui Pill,a typical recipe for nourishing kidney essence in the traditional Chinese medicine.Methods:Adult male Sprague Dawley rats were treated with the traditional Chinese herbal medicine Zuogui Pill and the active components found in the serum of the animals were analyzed by Fourier transform infrared(FTIR)spectroscopy.FTIR spectra of serum samples of treated and untreated rats were analyzed and the A2960/A2931 and A1540/A1080 ratios were calculated.Results:A2960/A2931 ratios of the serum samples collected following the administration of Zuogui Pill were significantly higher than those of the normal serum samples.FTIR data were then fitted using a Gaussian equation for wave numbers in the range of 1140e1000 cm1.ARNA/ADNA ratios in the serum of rats treated with Zuogui Pill were higher than those found in normal rat serum.Conclusion:FTIR spectroscopy could be used as an analytical tool to detect the activecomponents in serum of animals treated with Zuogui Pill.
文摘Although near infrared (NIR) spectroscopy has been evaluated for numerous applications, the number of actual on-line or even on-site industrial applications seems to be very limited. In the present paper, the attempts to produce online predictions of the chemical oxygen demand (COD) in wastewater from a pulp and paper mill using NIR spectroscopy are described. The task was perceived as very challenging, but with a root mean square error of prediction of 149 mg/l, roughly corresponding to 1/10 of the studied concentration interval, this attempt was deemed as successful. This result was obtained by using partial least squares model regression, interpolated reference values for calibration purposes, and by evenly distributing the calibration data in the concentration space. This work may also represent the first industrial application of online COD measurements in wastewater using NIR spectroscopy.
文摘Using visible and near-infrared (Vis-NIR) spectroscopy combined with partial least squares (PLS) regression, the rapid reagent-free analysis model for chromium (Cr) content in tideland reclamation soil in the Pearl River Delta, China was established. Based on Savitzky-Golay (SG) smoothing and PLS regression, a multi-parameters optimization platform (SG-PLS) covering 264 modes was constructed to select the appropriately spectral preprocessing mode. The optimal SG-PLS model was determined according to the prediction effect. The selected optimal parameters <em>d, p, m</em> and LV were 2, 6, 23 and 8, respectively. Using the validation samples that were not involved in modeling, the root mean square error (SEP<sub>V</sub>), relative root mean square error (R-SEP<sub>V</sub>) and correlation coefficients (R<sub>P, V</sub>) of prediction were 11.66 mg<span style="white-space:nowrap;">·</span>kg<sup>-1</sup>, 10.7% and 0.722, respectively. The results indicated that the feasibility of using Vis-NIR spectroscopy combined with SG-PLS method to analyze soil Cr content. The constructed multi-parameters optimization platform with SG-PLS is expected to be applied to a wider field of analysis. The rapid detection method has important application values to large-scale agricultural production.
