AIM:To explore the correlation between diabetic retinopathy(DR)and Helicobacter pylori(Hp)infection,based on data from a physical examination population.METHODS:This cross-sectional retrospective analysis included dat...AIM:To explore the correlation between diabetic retinopathy(DR)and Helicobacter pylori(Hp)infection,based on data from a physical examination population.METHODS:This cross-sectional retrospective analysis included data of 73824 health examination participants from December 2018 to December 2019.Participants were divided into the diabetic group and non-diabetic group,nondiabetic retinopathy(NDR)group,non-proliferative diabetic retinopathy(NPDR)group,proliferative diabetic retinopathy(PDR)group,and Hp infection group.Gender,age,body mass index(BMI),systolic blood pressure(SBP),diastolic blood pressure(DBP),fasting plasma glucose(FPG),glycated hemoglobin A1c(HbA1c),triglycerides(TG),total cholesterol(TC),low-density lipoprotein cholesterol(LDL-C),high-density lipoprotein cholesterol(HDL-C),and Hp data were recorded to compare the degree of DR lesions and Hp infection.Logistic regression analysis was used to evaluate the correlation between DR and Hp infection.RESULTS:There was a statistically significant difference between the diabetic and non-diabetic group(χ2=94.17,P<0.0001).Logistic regression analysis showed that male sex,age,BMI,SBP,TG,LDL-C,and Hp infection were independent risk factors for DR.There was no correlation between the degree of DR lesions and Hp infection(ρ=-0.00339,P=0.7753).Age[odds ratio(OR)=1.035,95%CI:1.024,1.046,P<0.0001]and SBP(OR=1.009,95%CI:1.004,1.015,P=0.0013)were independent risk factors for the degree of DR.CONCLUSION:There is a significant correlation between DR and Hp infection in the physical examination population.Hp infection is a risk factor for DR,and there is no significant difference between Hp infection and DR of different pathological degrees.Actively eradicating Hp may be of help to prevent DR.展开更多
The cyclic soft stimulation(CSS)is a new method of reservoir reforming for which the mechanism of fracturing crack propagation is ambiguous with regard to the alternating fluid pressure.This study aims to provide a co...The cyclic soft stimulation(CSS)is a new method of reservoir reforming for which the mechanism of fracturing crack propagation is ambiguous with regard to the alternating fluid pressure.This study aims to provide a comprehensive understanding of the fracturing mechanical characterizations of CSS under different magnitudes and amplitudes of the alternating fluid pressure.Acoustic emission(AE)is recorded to investigate the damage evolution under CSS based on the b value analysis of AE.Experimental results reveal the difference of pressure in a crack under different cyclic fluid pressure conditions.The AE results show that the maximum radiated energy under CSS tends to be reduced with the increase in the amplitude and magnitude of the alternating fluid pressure.The finishing crucial touch is that the crack extending criterion under CSS is proposed,which combines the injection parameters,the rock properties and in-situ stress.According to the crack extending criterion,the fluctuation fluid pressure causes the reduction of a critical crack extending pressure,and the CSS causes the crack to initiate and propagate under low fluid pressure.Under a higher-value magnitude of alternating fluid pressure,the cyclic times of CSS is less for the crack initiation.In supplement to the crack extending criterion,a distinct relationship between the radiated energy and the cyclic fluid pressure also is established based on the energy dissipation criterion.These new findings provide an insight into the determination of crack extending criterion under CSS for efficiently implementing shale fracturing.展开更多
Mobile edge computing(MEC)is an emerging technolohgy that extends cloud computing to the edge of a network.MEC has been applied to a variety of services.Specially,MEC can help to reduce network delay and improve the s...Mobile edge computing(MEC)is an emerging technolohgy that extends cloud computing to the edge of a network.MEC has been applied to a variety of services.Specially,MEC can help to reduce network delay and improve the service quality of recommendation systems.In a MEC-based recommendation system,users’rating data are collected and analyzed by the edge servers.If the servers behave dishonestly or break down,users’privacy may be disclosed.To solve this issue,we design a recommendation framework that applies local differential privacy(LDP)to collaborative filtering.In the proposed framework,users’rating data are perturbed to satisfy LDP and then released to the edge servers.The edge servers perform partial computing task by using the perturbed data.The cloud computing center computes the similarity between items by using the computing results generated by edge servers.We propose a data perturbation method to protect user’s original rating values,where the Harmony mechanism is modified so as to preserve the accuracy of similarity computation.And to enhance the protection of privacy,we propose two methods to protect both users’rating values and rating behaviors.Experimental results on real-world data demonstrate that the proposed methods perform better than existing differentially private recommendation methods.展开更多
基金Supported by The Project of National Key Research and Development(No.2018YFC1106103)。
文摘AIM:To explore the correlation between diabetic retinopathy(DR)and Helicobacter pylori(Hp)infection,based on data from a physical examination population.METHODS:This cross-sectional retrospective analysis included data of 73824 health examination participants from December 2018 to December 2019.Participants were divided into the diabetic group and non-diabetic group,nondiabetic retinopathy(NDR)group,non-proliferative diabetic retinopathy(NPDR)group,proliferative diabetic retinopathy(PDR)group,and Hp infection group.Gender,age,body mass index(BMI),systolic blood pressure(SBP),diastolic blood pressure(DBP),fasting plasma glucose(FPG),glycated hemoglobin A1c(HbA1c),triglycerides(TG),total cholesterol(TC),low-density lipoprotein cholesterol(LDL-C),high-density lipoprotein cholesterol(HDL-C),and Hp data were recorded to compare the degree of DR lesions and Hp infection.Logistic regression analysis was used to evaluate the correlation between DR and Hp infection.RESULTS:There was a statistically significant difference between the diabetic and non-diabetic group(χ2=94.17,P<0.0001).Logistic regression analysis showed that male sex,age,BMI,SBP,TG,LDL-C,and Hp infection were independent risk factors for DR.There was no correlation between the degree of DR lesions and Hp infection(ρ=-0.00339,P=0.7753).Age[odds ratio(OR)=1.035,95%CI:1.024,1.046,P<0.0001]and SBP(OR=1.009,95%CI:1.004,1.015,P=0.0013)were independent risk factors for the degree of DR.CONCLUSION:There is a significant correlation between DR and Hp infection in the physical examination population.Hp infection is a risk factor for DR,and there is no significant difference between Hp infection and DR of different pathological degrees.Actively eradicating Hp may be of help to prevent DR.
基金supported by the National Natural Science Foundation of China(Grant No.41302124,No.52078494)Open Funding by Hubei Intelligent Geological Equipment Engineering Technology Research Center(Grant No.DZZB202002)+1 种基金Open Funding by Engineering Research Center of Rock Soil Drilling&Excavation and Protection(Grant No.PL202001)the Independent Innovation Project of Central South University(Grant No.2019zzts634)
文摘The cyclic soft stimulation(CSS)is a new method of reservoir reforming for which the mechanism of fracturing crack propagation is ambiguous with regard to the alternating fluid pressure.This study aims to provide a comprehensive understanding of the fracturing mechanical characterizations of CSS under different magnitudes and amplitudes of the alternating fluid pressure.Acoustic emission(AE)is recorded to investigate the damage evolution under CSS based on the b value analysis of AE.Experimental results reveal the difference of pressure in a crack under different cyclic fluid pressure conditions.The AE results show that the maximum radiated energy under CSS tends to be reduced with the increase in the amplitude and magnitude of the alternating fluid pressure.The finishing crucial touch is that the crack extending criterion under CSS is proposed,which combines the injection parameters,the rock properties and in-situ stress.According to the crack extending criterion,the fluctuation fluid pressure causes the reduction of a critical crack extending pressure,and the CSS causes the crack to initiate and propagate under low fluid pressure.Under a higher-value magnitude of alternating fluid pressure,the cyclic times of CSS is less for the crack initiation.In supplement to the crack extending criterion,a distinct relationship between the radiated energy and the cyclic fluid pressure also is established based on the energy dissipation criterion.These new findings provide an insight into the determination of crack extending criterion under CSS for efficiently implementing shale fracturing.
基金supported by National Natural Science Foundation of China(No.61871037)supported by Natural Science Foundation of Beijing(No.M21035).
文摘Mobile edge computing(MEC)is an emerging technolohgy that extends cloud computing to the edge of a network.MEC has been applied to a variety of services.Specially,MEC can help to reduce network delay and improve the service quality of recommendation systems.In a MEC-based recommendation system,users’rating data are collected and analyzed by the edge servers.If the servers behave dishonestly or break down,users’privacy may be disclosed.To solve this issue,we design a recommendation framework that applies local differential privacy(LDP)to collaborative filtering.In the proposed framework,users’rating data are perturbed to satisfy LDP and then released to the edge servers.The edge servers perform partial computing task by using the perturbed data.The cloud computing center computes the similarity between items by using the computing results generated by edge servers.We propose a data perturbation method to protect user’s original rating values,where the Harmony mechanism is modified so as to preserve the accuracy of similarity computation.And to enhance the protection of privacy,we propose two methods to protect both users’rating values and rating behaviors.Experimental results on real-world data demonstrate that the proposed methods perform better than existing differentially private recommendation methods.
