The development of the solid-state polymer electrolytes (SPEs) for Li-ion batteries (LIBs) can effectively address the hidden safety issues of commercially used liquid electrolytes.Nevertheless,the unsatisfactory room...The development of the solid-state polymer electrolytes (SPEs) for Li-ion batteries (LIBs) can effectively address the hidden safety issues of commercially used liquid electrolytes.Nevertheless,the unsatisfactory room temperature ion conductivity and inferior mechanical strength for linear PEO-based SPEs are still the immense obstacles impeding the further applications of SPEs for large-scale commercialization.Herein,we fabricate a series of semi-interpenetrating-network (semi-IPN) polymer electrolytes based on a novel liquid crystal (C6M LC) and poly(ethylene glycol) diglycidyl ether (PEGDE) via UV-irradiation at the first time.The LCs not only highly improve the mechanical properties of electrolyte membranes via the construction of network structure with PEGDE,but also create stable ion transport channels for ion conduction.As a result,a free-standing flexible SPE shows outstanding ionic conductivity(5.93×10^(-5) S cm^(-1) at 30℃),a very wide electrochemical stability window of 5.5 V,and excellent thermal stability at thermal decomposition temperatures above 360℃ as well as the capacity of suppressing lithium dendrite growth.Moreover,the LiFePO_(4)/Li battery assembled with the semi-IPN electrolyte membranes exhibits good cycle performance and admirable reversible specific capacity.This work highlights the obvious advantages of LCs applied to the electrolyte for the advanced solid lithium battery.展开更多
In this study,the Stokes formula is used to analyze the separation effect of three-phase separators used in a Oilfield Central Processing Facility.The considered main influencing factors include(but are not limited to...In this study,the Stokes formula is used to analyze the separation effect of three-phase separators used in a Oilfield Central Processing Facility.The considered main influencing factors include(but are not limited to)the typical size of oil and water droplets,the residence time and temperature of fluid and the dosage of demulsifier.Using the“Specification for Oil and Gas Separators”as a basis,the control loops and operating parameters of each separator are optimized Considering the Halfaya Oilfield as a testbed,it is shown that the proposed approach can lead to good results in the production stage.展开更多
Objective To investigate the relationship between the expression of S100A7 protein and prediction of recurrence and prognosis of breast cancer in patients undergoing breast-conserving surgery combined with radiotherap...Objective To investigate the relationship between the expression of S100A7 protein and prediction of recurrence and prognosis of breast cancer in patients undergoing breast-conserving surgery combined with radiotherapy.Methods 349 samples of carcinoma tissue wax blocks were selected from January 2011 to January 2014 in Qingdao Central Hospital.All the patients had undergone breast-conserving surgery.We analyzed S100A7 expression in tumor tissue by immunohistochemical staining.Using univariate and multivariate analyses,we evaluated the relationship between S100A7 and clinical results,to explore independent risk factors for local regional recurrence(LRR).Results The positive expression of S100A7 in the recurrence group(66.7%)was significantly higher than in the non-recurrence group(38.4%),P=0.025.A log-rank test showed that high S100A7 expression was significantly correlated with 5-year regional recurrence free survival rate(RFS)(94.9%vs 89.5%,P=0.0408),distant metastasis free survival rate(DFS)(95.4%vs 83.5%,P<0.001),and overall survival rate(OS)(99.0%vs 92.5%,P=0.0011).Histological grade,vessel carcinoma embolus,lymph node metastasis,S100A7 expression,and tumor size were factors that influenced RFS.Multivariate analysis of the Cox proportional hazard model showed that high S100A7 expression was an independent risk factor that affected breast cancer RFS(HR=6.864,95%CI:1.575-29.915,P=0.01).Thus,we concluded that high S100A7 expression is associated with increased risk of LRR and distant metastasis of breast cancer after breast-conserving surgery and postoperative radiotherapy.S100A7 can be used as a molecular marker to screen for patients with high recurrence risk after breast-conserving surgery.展开更多
Dementias such as Alzheimer disease(AD)and mild cognitive impairment(MCI)lead to problems with memory,language,and daily activities resulting from damage to neurons in the brain.Given the irreversibility of this neuro...Dementias such as Alzheimer disease(AD)and mild cognitive impairment(MCI)lead to problems with memory,language,and daily activities resulting from damage to neurons in the brain.Given the irreversibility of this neuronal damage,it is crucial to find a biomarker to distinguish individuals with these diseases from healthy people.In this study,we construct a brain function network based on electroencephalography data to study changes in AD and MCI patients.Using a graph-theoretical approach,we examine connectivity features and explore their contributions to dementia recognition at edge,node,and network levels.We find that connectivity is reduced in AD and MCI patients compared with healthy controls.We also find that the edge-level features give the best performance when machine learning models are used to recognize dementia.The results of feature selection identify the top 50 ranked edge-level features constituting an optimal subset,which is mainly connected with the frontal nodes.A threshold analysis reveals that the performance of edge-level features is more sensitive to the threshold for the connection strength than that of node-and network-level features.In addition,edge-level features with a threshold of 0 provide the most effective dementia recognition.The K-nearest neighbors(KNN)machine learning model achieves the highest accuracy of 0.978 with the optimal subset when the threshold is 0.Visualization of edge-level features suggests that there are more long connections linking the frontal region with the occipital and parietal regions in AD and MCI patients compared with healthy controls.Our codes are publicly available at https://github.com/Debbie-85/eeg-connectivity.展开更多
Chronic obstructive pulmonary disease(COPD)is a major chronic disease with high global mortality,and capnography offers a noninvasive method for testing lungs function under natural breathing.Reported here is the best...Chronic obstructive pulmonary disease(COPD)is a major chronic disease with high global mortality,and capnography offers a noninvasive method for testing lungs function under natural breathing.Reported here is the best paradigm for COPD diagnosis and airflow obstruction severity assessment based on capnography as achieved by comparing the performance of five machine learning methods.In this study,1007 subjects underwent capnography and pulmonary function tests,then segment-fitted capnography was used to extract quantitative features.Using a hybrid scoring strategy to identify the head features,XGBoost performed the best,with accuracy,precision,recall,and F1 score of 90.08%,90.33%,90.08%,and 89.72%,respectively.This work shows for the first time the feasibility of using capnography to evaluate ventilation dysfunction in COPD patients.The proposed XGBoost-based method offers support to clinicians for assessing patients’ventilatory function by capnography,which has considerable potential as an alternative to traditional pulmonary function tests for respiratory diseases.展开更多
To scientifically and objectively monitor the fermentation quality of black tea,a computer vision system(CVS)and electronic nose(e-nose)were employed to analyze the black tea image and odor eigenvalues of Yinghong No....To scientifically and objectively monitor the fermentation quality of black tea,a computer vision system(CVS)and electronic nose(e-nose)were employed to analyze the black tea image and odor eigenvalues of Yinghong No.9 black tea.First,the variation trends of tea polyphenols,volatile substances,image eigenvalues and odor eigenvalues with the extension of fermentation time were analyzed,and the fermentation process was categorized into three stages for classification.Second,principal component analysis(PCA)was employed on the image and odor eigenvalues obtained by CVS and e-nose.Partial least squares discriminant analysis(PLS-DA)was performed on 117 volatile components,and 51 differential volatiles were screened out based on variable importance in projection(VIP≥1)and one-way analysis of variance(P<0.05),including geraniol,linalool,nerolidol,and α-ionone.Then,image features and odor features are fused by using a data fusion strategy.Finally,the image,smell and fusion information were combined with random forest(RF),K-nearest neighbor(KNN)and support vector machine(SVM)to establish the classification models of different fermentation stages and to compare them.The results show that the feature-level fusion strategy integrating the SVM was the most efficient approach,with classification accuracy rates of 100%for the training sets and 95.6%for the testing sets.The performance of Support Vector Regression(SVR)prediction models for tea polyphenol content based on feature-level fusion data outperformed data-level models(Rc,RMSEC,Rp and RMSEP of 0.96,0.48 mg/g,0.94,0.6 mg/g).展开更多
Poly(ethylene oxide)(PEO)-based solid polymer electrolytes(SPEs)are commonly used in lithium metal batteries(LMBs)for their good Li-salt solvating ability and easy processability.However,the relatively low Li-ion cond...Poly(ethylene oxide)(PEO)-based solid polymer electrolytes(SPEs)are commonly used in lithium metal batteries(LMBs)for their good Li-salt solvating ability and easy processability.However,the relatively low Li-ion conduction ability hinders their further development.In this work,a novel hyperbranched-polyether-type composite solid polymer electrolyte(CSPE)is prepared via a quick cross-linking reaction between aldehyde-terminated polyethylene glycol(PEG)and hyperbranched poly(ethylene imine)(HPEI)in the presence of lithium salt and fluorine-containing Zr-based metal–organic framework(MOF)UiO-66-(F)_(4).The hydrogen bonds between the fluorine atoms and amino groups in the electrolyte help to the better dispersion of UiO-66-(F)_(4) in the polymer matrix,which is beneficial to solving the problem of aggregation of nanofillers.Besides,the CSPEs with the functional MOF fillers show improvements in both electrochemical and mechanical properties.Notably,the Li-ion transference number(t)is considerably enhanced from 0.23 to 0.54.All-solid-state LMBs based on the CSPE also present good cycling performances.A high specific discharge capacity of 141.4 mAh·g^(−1) is remained after 200 cycles at 0.2 C.This study not only provides an effective synthesis method of the cross-linked hyperbranched polymer electrolyte,but also puts forward a new strategy for uniform dispersion of inorganic fillers in CSPEs.展开更多
An intelligent control system is designed in green tea fixation,which can automatically and continuously adjust the fixation parameters for quality improvement.Aroma is detected with PEN-3 electronic nose,and signals ...An intelligent control system is designed in green tea fixation,which can automatically and continuously adjust the fixation parameters for quality improvement.Aroma is detected with PEN-3 electronic nose,and signals are sent to the computer.With the aroma signals,the fixation process is separated into two stages:in the first stage,the key purpose is enzymatic reaction,which can be suppressed with high temperature;it is the oxidation re-action which should be concentrated on in the second stage,and a middle temperature is a good choice.With the designed fuzzy logic algorithm,the pot temperature is kept at a high level at the beginning,and the enzymatic reaction can be successfully reduced.In the second stage,the temperature is kept at a middle value to decrease oxidation.With the designed intelligent control,the green tea product quality is improved for aroma,taste,appearance,liquor color,and residues.展开更多
基金supported by the National Natural Science Foundation of China(No.52073285 and No.11975238)。
文摘The development of the solid-state polymer electrolytes (SPEs) for Li-ion batteries (LIBs) can effectively address the hidden safety issues of commercially used liquid electrolytes.Nevertheless,the unsatisfactory room temperature ion conductivity and inferior mechanical strength for linear PEO-based SPEs are still the immense obstacles impeding the further applications of SPEs for large-scale commercialization.Herein,we fabricate a series of semi-interpenetrating-network (semi-IPN) polymer electrolytes based on a novel liquid crystal (C6M LC) and poly(ethylene glycol) diglycidyl ether (PEGDE) via UV-irradiation at the first time.The LCs not only highly improve the mechanical properties of electrolyte membranes via the construction of network structure with PEGDE,but also create stable ion transport channels for ion conduction.As a result,a free-standing flexible SPE shows outstanding ionic conductivity(5.93×10^(-5) S cm^(-1) at 30℃),a very wide electrochemical stability window of 5.5 V,and excellent thermal stability at thermal decomposition temperatures above 360℃ as well as the capacity of suppressing lithium dendrite growth.Moreover,the LiFePO_(4)/Li battery assembled with the semi-IPN electrolyte membranes exhibits good cycle performance and admirable reversible specific capacity.This work highlights the obvious advantages of LCs applied to the electrolyte for the advanced solid lithium battery.
基金This study was supported by the Natural Science Foundation of Shandong Province(Grant No.ZR2021QE030).
文摘In this study,the Stokes formula is used to analyze the separation effect of three-phase separators used in a Oilfield Central Processing Facility.The considered main influencing factors include(but are not limited to)the typical size of oil and water droplets,the residence time and temperature of fluid and the dosage of demulsifier.Using the“Specification for Oil and Gas Separators”as a basis,the control loops and operating parameters of each separator are optimized Considering the Halfaya Oilfield as a testbed,it is shown that the proposed approach can lead to good results in the production stage.
基金Supported by a grant from The Medical Foundation of Wu Jieping(No.320.6750.16229)
文摘Objective To investigate the relationship between the expression of S100A7 protein and prediction of recurrence and prognosis of breast cancer in patients undergoing breast-conserving surgery combined with radiotherapy.Methods 349 samples of carcinoma tissue wax blocks were selected from January 2011 to January 2014 in Qingdao Central Hospital.All the patients had undergone breast-conserving surgery.We analyzed S100A7 expression in tumor tissue by immunohistochemical staining.Using univariate and multivariate analyses,we evaluated the relationship between S100A7 and clinical results,to explore independent risk factors for local regional recurrence(LRR).Results The positive expression of S100A7 in the recurrence group(66.7%)was significantly higher than in the non-recurrence group(38.4%),P=0.025.A log-rank test showed that high S100A7 expression was significantly correlated with 5-year regional recurrence free survival rate(RFS)(94.9%vs 89.5%,P=0.0408),distant metastasis free survival rate(DFS)(95.4%vs 83.5%,P<0.001),and overall survival rate(OS)(99.0%vs 92.5%,P=0.0011).Histological grade,vessel carcinoma embolus,lymph node metastasis,S100A7 expression,and tumor size were factors that influenced RFS.Multivariate analysis of the Cox proportional hazard model showed that high S100A7 expression was an independent risk factor that affected breast cancer RFS(HR=6.864,95%CI:1.575-29.915,P=0.01).Thus,we concluded that high S100A7 expression is associated with increased risk of LRR and distant metastasis of breast cancer after breast-conserving surgery and postoperative radiotherapy.S100A7 can be used as a molecular marker to screen for patients with high recurrence risk after breast-conserving surgery.
基金supported by the National Natural Science Foundation of China(Grant Nos.62071451,62331025,and U21A20447)the National Key Research and Development Project(Grant No.2021YFC3002204)the CAMS Innovation Fund for Medical Sciences(Grant No.2019-I2M-5-019).
文摘Dementias such as Alzheimer disease(AD)and mild cognitive impairment(MCI)lead to problems with memory,language,and daily activities resulting from damage to neurons in the brain.Given the irreversibility of this neuronal damage,it is crucial to find a biomarker to distinguish individuals with these diseases from healthy people.In this study,we construct a brain function network based on electroencephalography data to study changes in AD and MCI patients.Using a graph-theoretical approach,we examine connectivity features and explore their contributions to dementia recognition at edge,node,and network levels.We find that connectivity is reduced in AD and MCI patients compared with healthy controls.We also find that the edge-level features give the best performance when machine learning models are used to recognize dementia.The results of feature selection identify the top 50 ranked edge-level features constituting an optimal subset,which is mainly connected with the frontal nodes.A threshold analysis reveals that the performance of edge-level features is more sensitive to the threshold for the connection strength than that of node-and network-level features.In addition,edge-level features with a threshold of 0 provide the most effective dementia recognition.The K-nearest neighbors(KNN)machine learning model achieves the highest accuracy of 0.978 with the optimal subset when the threshold is 0.Visualization of edge-level features suggests that there are more long connections linking the frontal region with the occipital and parietal regions in AD and MCI patients compared with healthy controls.Our codes are publicly available at https://github.com/Debbie-85/eeg-connectivity.
基金supported by the National Natural Science Foundation of China(Grant Nos.62331025,62071451,and U21A20447)the National Key Research and Development Project(Grant No.2021YFC3002204)+1 种基金the Special Equipment Scientific Research Key Project(Grant No.LB2020LA060003)the CAMS Innovation Fund for Medical Sciences(Grant No.2019-I2M-5-019).
文摘Chronic obstructive pulmonary disease(COPD)is a major chronic disease with high global mortality,and capnography offers a noninvasive method for testing lungs function under natural breathing.Reported here is the best paradigm for COPD diagnosis and airflow obstruction severity assessment based on capnography as achieved by comparing the performance of five machine learning methods.In this study,1007 subjects underwent capnography and pulmonary function tests,then segment-fitted capnography was used to extract quantitative features.Using a hybrid scoring strategy to identify the head features,XGBoost performed the best,with accuracy,precision,recall,and F1 score of 90.08%,90.33%,90.08%,and 89.72%,respectively.This work shows for the first time the feasibility of using capnography to evaluate ventilation dysfunction in COPD patients.The proposed XGBoost-based method offers support to clinicians for assessing patients’ventilatory function by capnography,which has considerable potential as an alternative to traditional pulmonary function tests for respiratory diseases.
基金The authors gratefully acknowledge financial support from the Open Project of Guangdong Provincial Key Laboratory of Tea Plant Resources Innovation and Utilization(2020KF02)Guangzhou Science and Technology Program Project(202002020079)+1 种基金Guangdong Provincial Special Fund for Modern Agriculture Industry Technology Innovation Teams(2022KJ120)Qingyuan Science and Technology Program Project(2022KJJH065).
文摘To scientifically and objectively monitor the fermentation quality of black tea,a computer vision system(CVS)and electronic nose(e-nose)were employed to analyze the black tea image and odor eigenvalues of Yinghong No.9 black tea.First,the variation trends of tea polyphenols,volatile substances,image eigenvalues and odor eigenvalues with the extension of fermentation time were analyzed,and the fermentation process was categorized into three stages for classification.Second,principal component analysis(PCA)was employed on the image and odor eigenvalues obtained by CVS and e-nose.Partial least squares discriminant analysis(PLS-DA)was performed on 117 volatile components,and 51 differential volatiles were screened out based on variable importance in projection(VIP≥1)and one-way analysis of variance(P<0.05),including geraniol,linalool,nerolidol,and α-ionone.Then,image features and odor features are fused by using a data fusion strategy.Finally,the image,smell and fusion information were combined with random forest(RF),K-nearest neighbor(KNN)and support vector machine(SVM)to establish the classification models of different fermentation stages and to compare them.The results show that the feature-level fusion strategy integrating the SVM was the most efficient approach,with classification accuracy rates of 100%for the training sets and 95.6%for the testing sets.The performance of Support Vector Regression(SVR)prediction models for tea polyphenol content based on feature-level fusion data outperformed data-level models(Rc,RMSEC,Rp and RMSEP of 0.96,0.48 mg/g,0.94,0.6 mg/g).
基金supported by the National Natural Science Foundation of China(Nos.52073285 and 11975238)the authors also express gratitude for the help from the analysis and testing center at the University of Chinese Academy of Sciences.
文摘Poly(ethylene oxide)(PEO)-based solid polymer electrolytes(SPEs)are commonly used in lithium metal batteries(LMBs)for their good Li-salt solvating ability and easy processability.However,the relatively low Li-ion conduction ability hinders their further development.In this work,a novel hyperbranched-polyether-type composite solid polymer electrolyte(CSPE)is prepared via a quick cross-linking reaction between aldehyde-terminated polyethylene glycol(PEG)and hyperbranched poly(ethylene imine)(HPEI)in the presence of lithium salt and fluorine-containing Zr-based metal–organic framework(MOF)UiO-66-(F)_(4).The hydrogen bonds between the fluorine atoms and amino groups in the electrolyte help to the better dispersion of UiO-66-(F)_(4) in the polymer matrix,which is beneficial to solving the problem of aggregation of nanofillers.Besides,the CSPEs with the functional MOF fillers show improvements in both electrochemical and mechanical properties.Notably,the Li-ion transference number(t)is considerably enhanced from 0.23 to 0.54.All-solid-state LMBs based on the CSPE also present good cycling performances.A high specific discharge capacity of 141.4 mAh·g^(−1) is remained after 200 cycles at 0.2 C.This study not only provides an effective synthesis method of the cross-linked hyperbranched polymer electrolyte,but also puts forward a new strategy for uniform dispersion of inorganic fillers in CSPEs.
基金financial support from Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment&Technology(FMZ202002)the Open Fund of Yunnan Provincial Key Laboratory of Tea Science(2021YNCX004).
文摘An intelligent control system is designed in green tea fixation,which can automatically and continuously adjust the fixation parameters for quality improvement.Aroma is detected with PEN-3 electronic nose,and signals are sent to the computer.With the aroma signals,the fixation process is separated into two stages:in the first stage,the key purpose is enzymatic reaction,which can be suppressed with high temperature;it is the oxidation re-action which should be concentrated on in the second stage,and a middle temperature is a good choice.With the designed fuzzy logic algorithm,the pot temperature is kept at a high level at the beginning,and the enzymatic reaction can be successfully reduced.In the second stage,the temperature is kept at a middle value to decrease oxidation.With the designed intelligent control,the green tea product quality is improved for aroma,taste,appearance,liquor color,and residues.
