Objective:This study was conducted to explore the relationships among sedentary behavior(SB),electronic product addiction(EPA),and depression(D)in adolescents during the COVID-19 epidemic.Methods:A total of 604 adoles...Objective:This study was conducted to explore the relationships among sedentary behavior(SB),electronic product addiction(EPA),and depression(D)in adolescents during the COVID-19 epidemic.Methods:A total of 604 adolescents(including 309 girls and 295 boys aged 12-18)were selected from Qufu City,Shandong Province,China for three rounds of investigation.The model was constructed using AMOS 23.0 software,and cross-lagged analysis was conducted.Results:SB at T1 can significantly positively predict SB and EPA at T2(p<0.05).EPA at T1 can significantly positively predict SB and D at T2(p<0.05).Physical activity level and SB at T2 can significantly predict SB and EPA at T3(p<0.05).EPA at T2 can significantly predict SB,EPA,and D at T3(p<0.05).Conclusions:SB and EPA are predictive factors for D.Moreover,SB can significantly positively predict D and indirectly predict D through the mediating effect of EPA.展开更多
The intensity non-stationarity is one of the most important features of earthquake records.Modeling of this feature is significant to the generation of artificial earthquake waves.Based on the theory of phase differen...The intensity non-stationarity is one of the most important features of earthquake records.Modeling of this feature is significant to the generation of artificial earthquake waves.Based on the theory of phase difference spectrum,an intensity non-stationary envelope function with log-normal form is proposed.Through a tremendous amount of earthquake records downloaded on Kik-net,a parameter fitting procedure using the genetic algorithm is conducted to obtain the value of model parameters under different magnitudes,epicenter distances and site conditions.A numerical example is presented to describe the procedure of generating fully non-stationary ground motions via spectral representation,and the mean EPSD(evolutionary power spectral density)of simulated waves is proved to agree well with the target EPSD.The results show that the proposed model is capable of describing the intensity non-stationary features of ground motions,and it can be used in structural anti-seismic analysis and ground motion simulation.展开更多
Objective:To study the dynamic changes of inflammation in rat models of periodontitis induced by ligation.Methods:Twenty-one healthy male SD rats were selected and randomly divided into 7 groups,namely normal control ...Objective:To study the dynamic changes of inflammation in rat models of periodontitis induced by ligation.Methods:Twenty-one healthy male SD rats were selected and randomly divided into 7 groups,namely normal control group and ligation group A-F(the ligation group A-F were ligated 1,3,5,7,14 and 21 days respectively,and then sacrificed).In addition to the normal control group,ligature was used to ligate the neck of the right maxillary first molar.The experimental periodontitis model was established in rats.By observing the changes in rat body weight within 21 days,we explored the intervention of ligature wires on inflammation.The impact of the process,through monitoring the debris index simplified(DIS),Sulcus Bleeding Index(SBI),Tooth Mobility(TM),to evaluate the periodontal inflammation of the target tooth within 21 days of ligation.In addition,in order to more accurately assess the dynamic changes of the alveolar bone during the inflammatory phase,we use CBCT Observe the alveolar bone resorption.Results:The body weight of the ligation group decreased during the 3 days after ligation,and compared with the normal control group,there was no statistically significant difference in body weight growth rate in the ligation group from 3 to 21 days(P≥0.05),indicating that due to the intervention of the ligation wire,the rat will have a 3-day adaptability phenomenon.The ligation of silk after day will not affect the growth and development of rats.The DIS on the ligated side was higher than that of the normal control on the first,third,fifth,and seventh days after the ligation.The side increased significantly(P<0.05),and the DIS value increased in the first 3 days,and gradually decreased on the 5th day,until the 21st day after ligation,compared with the normal control group,the difference was not statistically significant(P≥0.05);SDI on the ligation side increased significantly on the 5th day,and gradually decreased after reaching the peak on the 7th day(P<0.05),until there was no statistical difference between the ligation side and the normal control group on the 21st day(P≥0.05);The day began to change and gradually increased until the 21st day,which was statistically significant compared with the normal control group(P<0.05);the CEJ-ABC distance of the ligation group A,B,and C was not statistically significant compared with the normal controlgroup(P>0.05),the CEJ-ABC distance of the ligated group D,E,and F was significantly higher than that of the normal control group(P<0.05),and bone resorption was more significant in group F compared with D and E groups(P<0.01).Conclusion:Three days after the ligation of the ligature,it affects the molar eating in rats,and induces inflammation.Ligation-induced experimental periodontitis is in the acute inflammatory phase during 3-7 days of ligation,and turns to chronic inflammatory phase in 14-21 days.Our study provides a more precise definition of the occurrence and development of ligation-induced periodontitis in rats,which provides a new direction for the subsequent study of periodontitis models and provides a basis for better and more accurate clinical research.展开更多
Accurate acquisition of the distribution offlow parameters inside the supersonic combustor is of great significance for hypersonicflight control.It is an interesting attempt to introduce a data-driven model to a super...Accurate acquisition of the distribution offlow parameters inside the supersonic combustor is of great significance for hypersonicflight control.It is an interesting attempt to introduce a data-driven model to a supersonic combustor forflowfield prediction.This paper proposes a novel method for predicting theflowfield in a dual-mode combustor.Aflowfield prediction convolutional neural network with multiple branches is built.Numerical investiga-tions for a strut variable geometry combustor have been conducted to obtainflowfield data for training the network as aflowfield prediction model.Richflowfield data are obtained by changing the equivalent ratio,incomingflow condition and geometry of the supersonic combustor.The Mach number distribution can be obtained from the trainedflowfield prediction model using the combustor wall pressure as input with high accuracy.The accuracy offlowfield prediction is discussed in several aspects.Further,the combustion mode detection is im-plemented on the predictionflowfield.展开更多
Accurate measurements of physical parameters in a scramjet isolator are very important to promote the design and optimization of the isolator and even the scramjet.In a ground experiment,limited by the inherent charac...Accurate measurements of physical parameters in a scramjet isolator are very important to promote the design and optimization of the isolator and even the scramjet.In a ground experiment,limited by the inherent characteristics of measurement technology and equipment,it is a big challenge to obtain the velocity field inside an isolator.In this study,a deep learning approach was introduced to combine data obtained from ground experiments and numerical simulations,and a velocity field prediction model was developed for obtaining the velocity field inside an isolator based on experimental Schlieren images.The velocity field prediction model was designed with convolutional neural networks as the main structure.Ground experiments of a scramjet isolator under continuous Mach number variation were carried out,and Schlieren images of the flow field inside the isolator were collected.Numerical simulations of the isolator were also carried out,and the velocity fields inside the isolator under various Mach numbers were obtained.The velocity field prediction model was trained using flow field datasets containing experimental Schlieren images and velocity field,and the mapping relationship between the experimental Schlieren images and the predicted velocity field was successfully established.展开更多
In terms of multiple temporal and spatial scales, massive data from experiments, flow field measurements, and high-fidelity numerical simulations have greatly promoted the rapid development of fluid mechanics. Machine...In terms of multiple temporal and spatial scales, massive data from experiments, flow field measurements, and high-fidelity numerical simulations have greatly promoted the rapid development of fluid mechanics. Machine Learning(ML) provides a wealth of analysis methods to extract potential information from a large amount of data for in-depth understanding of the underlying flow mechanism or for further applications. Furthermore, machine learning algorithms can enhance flow information and automatically perform tasks that involve active flow control and optimization. This article provides an overview of the past history, current development, and promising prospects of machine learning in the field of fluid mechanics. In addition, to facilitate understanding, this article outlines the basic principles of machine learning methods and their applications in engineering practice, turbulence models, flow field representation problems, and active flow control. In short, machine learning provides a powerful and more intelligent data processing architecture, and may greatly enrich the existing research methods and industrial applications of fluid mechanics.展开更多
A study of shock train self-excited oscillation in an isolator with background waves was implemented through a wind tunnel experiment.Dynamic pressure data were captured by high-frequency pressure measurements and the...A study of shock train self-excited oscillation in an isolator with background waves was implemented through a wind tunnel experiment.Dynamic pressure data were captured by high-frequency pressure measurements and the flow field was recorded by the high-speed Schlieren technique.The shock train structure was mostly asymmetrical during self-excited oscillation,regardless of its oscillation mode.We found that the pressure discontinuity caused by background waves was responsible for the asymmetry.On the wall where the pressure at the leading edge of the shock train was lower,a large separation region formed and the shock train deflected toward to the other wall.The oscillation mode of the shock train was related to the change of wall pressure in the oscillation range of its leading edge.The oscillation range and oscillation intensity of the shock train leading edge were affected by the wall pressure gradient induced by background waves.When located in a negative pressure gradient region,the oscillation of the leading edge strengthened;when located in a positive pressure gradient region,the oscillation weakened.To find out the cause of self-excited oscillation,correlation and phase analyses were performed.The results indicated that the instability of the separation region induced by the leading shock was the source of perturbation that caused self-excited oscillation,regardless of the oscillation mode of the shock train.展开更多
Membrane-associated guanylate kinase(MAGUK)family protein MAGUK invert 2(MAGI-2)has been demonstrated to be involved in the tumorigenic mechanism of prostate cancer.The objective of this study was to investigate the e...Membrane-associated guanylate kinase(MAGUK)family protein MAGUK invert 2(MAGI-2)has been demonstrated to be involved in the tumorigenic mechanism of prostate cancer.The objective of this study was to investigate the expression of MAGI・2 at mRNA and protein levels.The prog no stic value of MAGI-2 in Han Chin ese patie nts with prostate cancer was also investigated.The expression data of MAGI・2 were assessed through database retrieval,analysis of sequencing data from our group,and tissue immunohistochemistry using digital scoring system(H・score).The clinical,pathological,and follow-up data were collected.The expression of MAGI-2 in prostate tumor tissues and prostate normal tissues was evaluated and compared.MAGI-2 expression was associated with clinical parameters including tumor stage,lymph node status,Gleason score,PSA level,and biochemical recurrenee of prostate cancer.The relative expression of MAGI-2 mRNA was lower in the tumor tissue in The Cancer Genome Atlas(TCGA)database and sequencing data(P<0.001).There was no difference in MAGI-2 protein expression between tumor and normal tissues in tissue microarray(TMA)results.MAGI-2 expression was associated with pathological tumor stage(P=0.02),Gleason score(P=0.05),and preoperation prostate-specific antigen(PSA;P=0.04).A positive correlation was identified between MAGI-2 and phosphatase and tensin homolog deleted on chromosome 10(PTEN)expressions through the analysis of TCGA and TMA data(P<0.0001).Patients with higher MAGI-2 expression had longer biochemical recurrence-free survival in the univariate analysis(P=0.005),which in dicates an optimal prog no stic value of MAGI-2 in Han Chin ese patie nts with prostate can cer.I n con elusion,MAGI-2 expressi on gradually decreases with tumor progression,and can be used as a predictor of tumor recurrence in Chinese patients.展开更多
基金supported by Youth Fund of Humanities and Social Sciences Research Project of Education Ministry(22YJC890025).
文摘Objective:This study was conducted to explore the relationships among sedentary behavior(SB),electronic product addiction(EPA),and depression(D)in adolescents during the COVID-19 epidemic.Methods:A total of 604 adolescents(including 309 girls and 295 boys aged 12-18)were selected from Qufu City,Shandong Province,China for three rounds of investigation.The model was constructed using AMOS 23.0 software,and cross-lagged analysis was conducted.Results:SB at T1 can significantly positively predict SB and EPA at T2(p<0.05).EPA at T1 can significantly positively predict SB and D at T2(p<0.05).Physical activity level and SB at T2 can significantly predict SB and EPA at T3(p<0.05).EPA at T2 can significantly predict SB,EPA,and D at T3(p<0.05).Conclusions:SB and EPA are predictive factors for D.Moreover,SB can significantly positively predict D and indirectly predict D through the mediating effect of EPA.
基金supported by the National Key R&D Program of China(2017YFC0703600)the National Foundation of China(Grant Nos.51678301 and 51678302).
文摘The intensity non-stationarity is one of the most important features of earthquake records.Modeling of this feature is significant to the generation of artificial earthquake waves.Based on the theory of phase difference spectrum,an intensity non-stationary envelope function with log-normal form is proposed.Through a tremendous amount of earthquake records downloaded on Kik-net,a parameter fitting procedure using the genetic algorithm is conducted to obtain the value of model parameters under different magnitudes,epicenter distances and site conditions.A numerical example is presented to describe the procedure of generating fully non-stationary ground motions via spectral representation,and the mean EPSD(evolutionary power spectral density)of simulated waves is proved to agree well with the target EPSD.The results show that the proposed model is capable of describing the intensity non-stationary features of ground motions,and it can be used in structural anti-seismic analysis and ground motion simulation.
基金Jilin Province Science and Technology Development Plan Project(No.20190303183SF)Jilin University Undergraduate Teaching Reform Research Project(No.2019XYB318)。
文摘Objective:To study the dynamic changes of inflammation in rat models of periodontitis induced by ligation.Methods:Twenty-one healthy male SD rats were selected and randomly divided into 7 groups,namely normal control group and ligation group A-F(the ligation group A-F were ligated 1,3,5,7,14 and 21 days respectively,and then sacrificed).In addition to the normal control group,ligature was used to ligate the neck of the right maxillary first molar.The experimental periodontitis model was established in rats.By observing the changes in rat body weight within 21 days,we explored the intervention of ligature wires on inflammation.The impact of the process,through monitoring the debris index simplified(DIS),Sulcus Bleeding Index(SBI),Tooth Mobility(TM),to evaluate the periodontal inflammation of the target tooth within 21 days of ligation.In addition,in order to more accurately assess the dynamic changes of the alveolar bone during the inflammatory phase,we use CBCT Observe the alveolar bone resorption.Results:The body weight of the ligation group decreased during the 3 days after ligation,and compared with the normal control group,there was no statistically significant difference in body weight growth rate in the ligation group from 3 to 21 days(P≥0.05),indicating that due to the intervention of the ligation wire,the rat will have a 3-day adaptability phenomenon.The ligation of silk after day will not affect the growth and development of rats.The DIS on the ligated side was higher than that of the normal control on the first,third,fifth,and seventh days after the ligation.The side increased significantly(P<0.05),and the DIS value increased in the first 3 days,and gradually decreased on the 5th day,until the 21st day after ligation,compared with the normal control group,the difference was not statistically significant(P≥0.05);SDI on the ligation side increased significantly on the 5th day,and gradually decreased after reaching the peak on the 7th day(P<0.05),until there was no statistical difference between the ligation side and the normal control group on the 21st day(P≥0.05);The day began to change and gradually increased until the 21st day,which was statistically significant compared with the normal control group(P<0.05);the CEJ-ABC distance of the ligation group A,B,and C was not statistically significant compared with the normal controlgroup(P>0.05),the CEJ-ABC distance of the ligated group D,E,and F was significantly higher than that of the normal control group(P<0.05),and bone resorption was more significant in group F compared with D and E groups(P<0.01).Conclusion:Three days after the ligation of the ligature,it affects the molar eating in rats,and induces inflammation.Ligation-induced experimental periodontitis is in the acute inflammatory phase during 3-7 days of ligation,and turns to chronic inflammatory phase in 14-21 days.Our study provides a more precise definition of the occurrence and development of ligation-induced periodontitis in rats,which provides a new direction for the subsequent study of periodontitis models and provides a basis for better and more accurate clinical research.
基金supported by the National Natural Science Foundation of China (Grant No.11972139 and 52125603)the Fundamental Research Funds for the Central Universities (HIT.BRET.2021006 and FRFCU5710094620).
文摘Accurate acquisition of the distribution offlow parameters inside the supersonic combustor is of great significance for hypersonicflight control.It is an interesting attempt to introduce a data-driven model to a supersonic combustor forflowfield prediction.This paper proposes a novel method for predicting theflowfield in a dual-mode combustor.Aflowfield prediction convolutional neural network with multiple branches is built.Numerical investiga-tions for a strut variable geometry combustor have been conducted to obtainflowfield data for training the network as aflowfield prediction model.Richflowfield data are obtained by changing the equivalent ratio,incomingflow condition and geometry of the supersonic combustor.The Mach number distribution can be obtained from the trainedflowfield prediction model using the combustor wall pressure as input with high accuracy.The accuracy offlowfield prediction is discussed in several aspects.Further,the combustion mode detection is im-plemented on the predictionflowfield.
基金supported by the National Natural Science Foundation of China(No.52125603).
文摘Accurate measurements of physical parameters in a scramjet isolator are very important to promote the design and optimization of the isolator and even the scramjet.In a ground experiment,limited by the inherent characteristics of measurement technology and equipment,it is a big challenge to obtain the velocity field inside an isolator.In this study,a deep learning approach was introduced to combine data obtained from ground experiments and numerical simulations,and a velocity field prediction model was developed for obtaining the velocity field inside an isolator based on experimental Schlieren images.The velocity field prediction model was designed with convolutional neural networks as the main structure.Ground experiments of a scramjet isolator under continuous Mach number variation were carried out,and Schlieren images of the flow field inside the isolator were collected.Numerical simulations of the isolator were also carried out,and the velocity fields inside the isolator under various Mach numbers were obtained.The velocity field prediction model was trained using flow field datasets containing experimental Schlieren images and velocity field,and the mapping relationship between the experimental Schlieren images and the predicted velocity field was successfully established.
基金supported by the National Natural Science Foundation of China(No.11972139)。
文摘In terms of multiple temporal and spatial scales, massive data from experiments, flow field measurements, and high-fidelity numerical simulations have greatly promoted the rapid development of fluid mechanics. Machine Learning(ML) provides a wealth of analysis methods to extract potential information from a large amount of data for in-depth understanding of the underlying flow mechanism or for further applications. Furthermore, machine learning algorithms can enhance flow information and automatically perform tasks that involve active flow control and optimization. This article provides an overview of the past history, current development, and promising prospects of machine learning in the field of fluid mechanics. In addition, to facilitate understanding, this article outlines the basic principles of machine learning methods and their applications in engineering practice, turbulence models, flow field representation problems, and active flow control. In short, machine learning provides a powerful and more intelligent data processing architecture, and may greatly enrich the existing research methods and industrial applications of fluid mechanics.
基金supported by the National Natural Science Foundation of China(Nos.11972139 and 51676204)。
文摘A study of shock train self-excited oscillation in an isolator with background waves was implemented through a wind tunnel experiment.Dynamic pressure data were captured by high-frequency pressure measurements and the flow field was recorded by the high-speed Schlieren technique.The shock train structure was mostly asymmetrical during self-excited oscillation,regardless of its oscillation mode.We found that the pressure discontinuity caused by background waves was responsible for the asymmetry.On the wall where the pressure at the leading edge of the shock train was lower,a large separation region formed and the shock train deflected toward to the other wall.The oscillation mode of the shock train was related to the change of wall pressure in the oscillation range of its leading edge.The oscillation range and oscillation intensity of the shock train leading edge were affected by the wall pressure gradient induced by background waves.When located in a negative pressure gradient region,the oscillation of the leading edge strengthened;when located in a positive pressure gradient region,the oscillation weakened.To find out the cause of self-excited oscillation,correlation and phase analyses were performed.The results indicated that the instability of the separation region induced by the leading shock was the source of perturbation that caused self-excited oscillation,regardless of the oscillation mode of the shock train.
基金The authors acknowledge the contribution of Dr.Lin Zhao,Dr.Ya-Sheng Zhu,Dr.Zhe-Xu Cao,and Dr.Chen Ye from the Department of Urology,Changhai Hospital,Naval Medical University(the Second Military Medical University),for their kind help during the experimental process.This study was supported by the National Natural Science Foundation of China(No.81430058)Shanghai Key Laboratory of Cell Engineering(No.14DZ2272300).
文摘Membrane-associated guanylate kinase(MAGUK)family protein MAGUK invert 2(MAGI-2)has been demonstrated to be involved in the tumorigenic mechanism of prostate cancer.The objective of this study was to investigate the expression of MAGI・2 at mRNA and protein levels.The prog no stic value of MAGI-2 in Han Chin ese patie nts with prostate cancer was also investigated.The expression data of MAGI・2 were assessed through database retrieval,analysis of sequencing data from our group,and tissue immunohistochemistry using digital scoring system(H・score).The clinical,pathological,and follow-up data were collected.The expression of MAGI-2 in prostate tumor tissues and prostate normal tissues was evaluated and compared.MAGI-2 expression was associated with clinical parameters including tumor stage,lymph node status,Gleason score,PSA level,and biochemical recurrenee of prostate cancer.The relative expression of MAGI-2 mRNA was lower in the tumor tissue in The Cancer Genome Atlas(TCGA)database and sequencing data(P<0.001).There was no difference in MAGI-2 protein expression between tumor and normal tissues in tissue microarray(TMA)results.MAGI-2 expression was associated with pathological tumor stage(P=0.02),Gleason score(P=0.05),and preoperation prostate-specific antigen(PSA;P=0.04).A positive correlation was identified between MAGI-2 and phosphatase and tensin homolog deleted on chromosome 10(PTEN)expressions through the analysis of TCGA and TMA data(P<0.0001).Patients with higher MAGI-2 expression had longer biochemical recurrence-free survival in the univariate analysis(P=0.005),which in dicates an optimal prog no stic value of MAGI-2 in Han Chin ese patie nts with prostate can cer.I n con elusion,MAGI-2 expressi on gradually decreases with tumor progression,and can be used as a predictor of tumor recurrence in Chinese patients.
