Background:As the digital age progresses,fear of missing out(FoMO)is becoming increasingly common,and the impact factor of FOMO needs to be further investigated.This study aims to explore the relationship between psyc...Background:As the digital age progresses,fear of missing out(FoMO)is becoming increasingly common,and the impact factor of FOMO needs to be further investigated.This study aims to explore the relationship between psychological security(PS)and FoMO by analyzing the mediating role of social networking addiction(SNA)and the moderating role of social self-efficacy(SSE).Methods:We collected a sample of 1181 college students(with a mean age of 19.671.38 years)from five universities in a province of China's Mainland through cluster sampling.Data±were gathered using the psychological security questionnaire(PSQ),the FoMO scale,the SNA scale,and the perceived social self-efficacy(PSSE)scale.Data analysis employed independent-sample t-tests,one-way analysis of variance(ANOVA),Harman’s single-factor test,confirmatory factor analysis,and moderated mediation analysis.Results:The results of the mediation model and moderated mediation model analyses showed the following key findings:(1)PS is significantly negatively correlated with FoMO;(2)SNA mediates the relationship between PS and FoMO;(3)SSE positively moderates the relationship between PS and FoMO;and(4)SSE also positively moderates the relationship between PS and SNA.Conclusion:University students’PS not only directly impacts FoMO but also indirectly influences it through SNA.Additionally,SSE positively moderates both the direct path and the first half of the mediation path,indicating that enhancing students’PS and SSE can help alleviate their SNA and FoMO,promoting their psychological and behavioral well-being.展开更多
BACKGROUND Recent studies have indicated that triglyceride glucose(TyG)-waist height ratio(WHtR)and TyG-waist circumference(TyG-WC)are effective indicators for evaluating insulin resistance.However,research on the ass...BACKGROUND Recent studies have indicated that triglyceride glucose(TyG)-waist height ratio(WHtR)and TyG-waist circumference(TyG-WC)are effective indicators for evaluating insulin resistance.However,research on the association in TyG-WHtR,TyG-WC,and the risk and prognosis of major adverse cardiovascular events(MACEs)in type 2 diabetes mellitus(T2DM)cases are limited.AIM To clarify the relation in TyG-WHtR,TyG-WC,and the risk of MACEs and overall mortality in T2DM patients.METHODS Information for this investigation was obtained from Action to Control Cardiovascular Risk in Diabetes(ACCORD)/ACCORD Follow-On(ACCORDION)study database.The Cox regression model was applied to assess the relation among TyG-WHtR,TyG-WC and future MACEs risk and overall mortality in T2DM cases.The RCS analysis was utilized to explore the nonlinear correlation.Subgroup and interaction analyses were conducted to prove the robustness.The receiver operating characteristic curves were applied to analysis the additional predicting value of TyG-WHtR and TyG-WC.RESULTS After full adjustment for confounding variables,the highest baseline TyG-WHtR cohort respectively exhibited a 1.353-fold and 1.420-fold higher risk for MACEs and overall mortality,than the lowest quartile group.Similarly,the highest baseline TyG-WC cohort showed a 1.314-fold and 1.480-fold higher risk for MACEs and overall mortality,respectively.Each 1 SD increase in TyG-WHtR was significantly related to an 11.7%increase in MACEs and a 14.9%enhance in overall mortality.Each 1 SD increase in TyG-WC corresponded to an 11.5%in MACEs and a 16.6%increase in overall mortality.Including these two indexes in conventional models significantly improved the predictive power for MACEs and overall mortality.CONCLUSION TyG-WHtR and TyG-WC were promising predictors of MACEs and overall mortality risk in T2DM cases.展开更多
Thorium dioxide(ThO_(2))fibers exhibit exceptional structural stability,low density and superior flexibility,coupled with a remarkably high melting point,positioning them as promising candidates for thermal protection...Thorium dioxide(ThO_(2))fibers exhibit exceptional structural stability,low density and superior flexibility,coupled with a remarkably high melting point,positioning them as promising candidates for thermal protection applications.Additionally,their commendable secondary processing characteristics enable the development of diverse composite materials when integrated with other materials,significantly broadening the potential utilization of ThO_(2)materials and thorium resources in industrial fields.In this work,the ThO_(2)fiber was fabricated by the sol-gel precursor method,and the precursor with good spinnability and excellent stability was synthesized for the first time.The ThO_(2)fiber with a mean diameter of 868 nm is both highly flexible and strong(max.tensile strength 2.21 MPa),capable of bending freely across a wide temperature range from-196℃(in liquid nitrogen)to 1200℃.Meanwhile,it exhibits excellent temperature stability and heat insulation properties.The ThO_(2)nanofiber membranes with layered structure have low density(32-37 mg·cm^(-3)),low thermal conductivity(27.3-30.1 mW·m^(-1)·K^(-1)@25℃).The ThO_(2)nanofiber membranes with 15 mm thickness can reduce the temperature from 1200 to 282℃and maintain a high aspect ratio and bendability after 1200℃@90 min.The results show that the ThO_(2)fiber can be used as a new kind of high-temperature resistant material.展开更多
Stellar classification is a fundamental task in astronomical data analysis.Photometric data offer a significant advantage over spectral data in terms of data volume.Their lower acquisition cost and broader coverage ma...Stellar classification is a fundamental task in astronomical data analysis.Photometric data offer a significant advantage over spectral data in terms of data volume.Their lower acquisition cost and broader coverage make them more suitable for stellar classification applications.This study selects photometric data from the SDSS DR18.Instead of using traditional RGB image formats,a series of preprocessing steps were applied to generate five-channel Numpy files as the data set.To enhance stellar classification performance,we propose a deep learning model based on photometric feature fusion–Stellar Photometric Features Fusion Network.Additionally,we introduce the Dynamic Enhanced Stellar Squeeze-and-Excitation module,designed to optimize the weight allocation of different photometric bands in the classification task,and investigate the impact of each band's features on classification performance.Ultimately,we found that the information from the r and z bands played a more crucial role in the stellar classification task,achieving a final classification accuracy of 87.47%,thereby demonstrating the effectiveness of photometric data in stellar classification.展开更多
本研究旨在应用康奈尔绵羊净碳水化合物和蛋白质体系(Cornell sheep net carbohydrate and protein system,CNCPS-S)的瘤胃降解预测模型预测日粮碳水化合物(CHO)瘤胃有效降解率,并实测验证CNCPS-S模型预测值的准确性。选取3只安装瘤胃...本研究旨在应用康奈尔绵羊净碳水化合物和蛋白质体系(Cornell sheep net carbohydrate and protein system,CNCPS-S)的瘤胃降解预测模型预测日粮碳水化合物(CHO)瘤胃有效降解率,并实测验证CNCPS-S模型预测值的准确性。选取3只安装瘤胃瘘管、体重分别为(38.03±1.56)kg的哈萨克公羊作为试验动物,配制3种精粗比分别为30∶70、35∶65、40∶60的全混合日粮(TMR),利用瘤胃灌注试验和尼龙袋试验实测3种日粮CHO的瘤胃外流速度(Kp)和降解率,同时利用CNCPS-S模型预测3种日粮CHO的Kp与降解率,对CHO的降解率预测值和实测值进行线性回归分析,评价模型预测的准确性。结果表明:3种TMR的瘤胃食糜Kp随精料比例增加而依次升高(P<0.01),分别为3.58%/h、3.83%/h、4.05%/h,据此计算而得的CHO的降解率分别为42.7%、43.1%、42.3%(P>0.05);随精料比例的增加,3种TMR的瘤胃食糜Kp的模型预测值依次升高(P>0.05),分别为1.62%/h、1.63%/h、1.64%/h,CHO瘤胃降解率的预测值分别为39.5%、39.1%、39.6%(P>0.05);3种日粮CHO瘤胃降解率的预测值与实测值之间的平均偏差比较小(≤4 g/100 g CHO),相关性较高(R2≥0.86),均方根误差也较低(RMSE≤1.93 g/100 g CHO)。以上结果说明,CNCPS-S瘤胃降解预测模型对日粮CHO的降解率具有较好的预测能力。展开更多
研究旨在应用康奈尔绵羊净碳水化合物和蛋白质体系(Cornell sheep net carbohydrate and protein system,CNCPS-S)的预测模型预测日粮瘤胃pH值与微生物蛋白质(MCP)合成量,并通过实测验证模型预测值的准确性。选取3只安装瘤胃和十二指肠...研究旨在应用康奈尔绵羊净碳水化合物和蛋白质体系(Cornell sheep net carbohydrate and protein system,CNCPS-S)的预测模型预测日粮瘤胃pH值与微生物蛋白质(MCP)合成量,并通过实测验证模型预测值的准确性。选取3只安装瘤胃和十二指肠瘘管的哈萨克公羊为试验动物,配制3种精粗比为30:70、35:65、40:60的全混合日粮(TMR)。采用3×3拉丁方设计,共3期试验,每期18 d,其中10 d为预试期,8 d为样品采集,测定瘤胃液pH和MCP合成量。同时利用CNCPS-S模型预测3种日粮的MCP合成量,评价模型预测的准确性。结果表明:①3种TMR的瘤胃液pH的实测值分别在6.38~6.71、6.01~6.59、5.81~6.41之间,模型预测pH为固定值6.46;②随着精料水平增加,3种TMR均为瘤胃能氮负平衡型,瘤胃能氮平衡(RENB)值均呈下降趋势(P<0.05),3种TMR的MCP的模型预测值依次升高,分别为210.29、215.31、246.94 g/d(P>0.05),实测值也依次升高,分别为93.83、97.33、100.27 g/d(P<0.05);③经线性回归分析,3种日粮MCP的预测值与十二指肠MCP实测值之间的平均偏差比较大(平均偏差≥116 g/d),相关性低(R^2≤0.75),误差均方根(RMSE)都较高。以上结果说明,CNCPS-S对我国绵羊瘤胃pH值具有较好的预测能力,但对MCP合成量具有较低的预测能力。展开更多
Objective:To build GPC3 gene short hairpin interference RNA(shRNA)slow virus veclor.observe expression of Huh-7 GPC3 gene in human liver cell line proliferation apoptosis and the effect of GPC3 gene influencing on liv...Objective:To build GPC3 gene short hairpin interference RNA(shRNA)slow virus veclor.observe expression of Huh-7 GPC3 gene in human liver cell line proliferation apoptosis and the effect of GPC3 gene influencing on liver cancer cell growth,and provide theoretical basis for genc therapy of liver cancer.Methods:Hepatocellular carcinoma cell line Huh-7 wsa transfected by a RNA interference technique.GPC3 gene expression in a variety of liver cancer cell lines was detected by fluorescence quantitative PCR.Targeted GPC3 gene seqnences of small interfering RNA(siRNA)PGC-shRNA-GPC3 were restructured.Stable expression cell linse of siRNA were screened and established with the heplp of liposomes(lipofectamine^(TM2000))as carrier transfcetion of human liver cell lines.In order to validate siRNA interference efficiency.GPC3 siRNA mRNA expression was detected after transfection by using RT-PCR and Western blot.The absorbance value of the cells of blank group,untransfection group and transfection group,the cell cycle and cell apoptosis were calculated,and effects of GPC3 gene nn Huh-7 cell proliferation and apoptosis were observed.Results:In the liver cancer cell lines Huh-7 GPC3 gene showed high expression.PGC-shRNA-GPC3 recombinant plasmid was constructde successfully via sequencing validation.Stable recombinant plasmid transfected into liver cancer cell linse Huh-7can obviously inhibit GPC3 mRNA expression level.Conclusions:The targeted GPC3 siRNA can effectively inhibit the expression of GPC3.展开更多
Spintronics,exploiting the spin degree of electrons as the information vector,is an attractive field for implementing the beyond Complemetary metal-oxide-semiconductor(CMOS)devices.Recently,two-dimensional(2D)material...Spintronics,exploiting the spin degree of electrons as the information vector,is an attractive field for implementing the beyond Complemetary metal-oxide-semiconductor(CMOS)devices.Recently,two-dimensional(2D)materials have been drawing tremendous attention in spintronics owing to their distinctive spin-dependent properties,such as the ultralong spin relaxation time of graphene and the spin-valley locking of transition metal dichalcogenides.Moreover,the related heterostructures provide an unprecedented probability of combining the di erent characteristics via proximity e ect,which could remedy the limitation of individual 2D materials.Hence,the proximity engineering has been growing extremely fast and has made significant achievements in the spin injection and manipulation.Nevertheless,there are still challenges toward practical application;for example,the mechanism of spin relaxation in 2D materials is unclear,and the high-effciency spin gating is not yet achieved.In this review,we focus on 2D materials and related heterostructures to systematically summarize the progress of the spin injection,transport,manipulation,and application for information storage and processing.We also highlight the current challenges and future perspectives on the studies of spintronic devices based on 2D materials.展开更多
This study introduces a generic framework for geotechnical subsurface modeling, which accounts for spatial autocorrelation with local mapping machine learning(ML) methods. Instead of using XY coordinate fields directl...This study introduces a generic framework for geotechnical subsurface modeling, which accounts for spatial autocorrelation with local mapping machine learning(ML) methods. Instead of using XY coordinate fields directly as model input, a series of autocorrelated geotechnical distance fields(GDFs) is designed to enable the ML models to infer the spatial relationship between the sampled locations and unknown locations. The whole framework using GDF with ML methods is named GDF-ML. This framework is purely data-driven which avoids the tedious work in the scale of fluctuations(SOFs)estimating and data detrending in the conventional spatial interpolation methods. Six local mapping ML methods(extra trees(ETs), gradient boosting(GB), extreme gradient boosting(XGBoost), random forest(RF), general regression neural network(GRNN) and k-nearest neighbors(KNN)) are compared in the GDF-ML framework. The results show that the GDFs are better than the conventional XY coordinate fields based ML methods in both accuracy and spatial continuity. GDF-ML is flexible which can be applied to high-dimensional, multi-variable and incomplete datasets. Among these six methods, GDF with ET method(GDF-ET) clearly shows the best accuracy and best spatial continuity. The proposed GDF-ET method can provide a fast and accurate interpretation of the soil property profile. Sensitivity analysis shows that this method is applicable to very small training dataset size. The associated statistical uncertainty can also be quantified so that the reliability of the subsurface modeling results can be estimated objectively and explicitly. The uncertainty results clearly show that the prediction becomes more accurate when more sampled data are available.展开更多
基金supported by the Jiangxi Province Think Tank Research Project(ZK202406)the 2023 Jiangxi Provincial Health Commission Research Project(52524010)。
文摘Background:As the digital age progresses,fear of missing out(FoMO)is becoming increasingly common,and the impact factor of FOMO needs to be further investigated.This study aims to explore the relationship between psychological security(PS)and FoMO by analyzing the mediating role of social networking addiction(SNA)and the moderating role of social self-efficacy(SSE).Methods:We collected a sample of 1181 college students(with a mean age of 19.671.38 years)from five universities in a province of China's Mainland through cluster sampling.Data±were gathered using the psychological security questionnaire(PSQ),the FoMO scale,the SNA scale,and the perceived social self-efficacy(PSSE)scale.Data analysis employed independent-sample t-tests,one-way analysis of variance(ANOVA),Harman’s single-factor test,confirmatory factor analysis,and moderated mediation analysis.Results:The results of the mediation model and moderated mediation model analyses showed the following key findings:(1)PS is significantly negatively correlated with FoMO;(2)SNA mediates the relationship between PS and FoMO;(3)SSE positively moderates the relationship between PS and FoMO;and(4)SSE also positively moderates the relationship between PS and SNA.Conclusion:University students’PS not only directly impacts FoMO but also indirectly influences it through SNA.Additionally,SSE positively moderates both the direct path and the first half of the mediation path,indicating that enhancing students’PS and SSE can help alleviate their SNA and FoMO,promoting their psychological and behavioral well-being.
文摘BACKGROUND Recent studies have indicated that triglyceride glucose(TyG)-waist height ratio(WHtR)and TyG-waist circumference(TyG-WC)are effective indicators for evaluating insulin resistance.However,research on the association in TyG-WHtR,TyG-WC,and the risk and prognosis of major adverse cardiovascular events(MACEs)in type 2 diabetes mellitus(T2DM)cases are limited.AIM To clarify the relation in TyG-WHtR,TyG-WC,and the risk of MACEs and overall mortality in T2DM patients.METHODS Information for this investigation was obtained from Action to Control Cardiovascular Risk in Diabetes(ACCORD)/ACCORD Follow-On(ACCORDION)study database.The Cox regression model was applied to assess the relation among TyG-WHtR,TyG-WC and future MACEs risk and overall mortality in T2DM cases.The RCS analysis was utilized to explore the nonlinear correlation.Subgroup and interaction analyses were conducted to prove the robustness.The receiver operating characteristic curves were applied to analysis the additional predicting value of TyG-WHtR and TyG-WC.RESULTS After full adjustment for confounding variables,the highest baseline TyG-WHtR cohort respectively exhibited a 1.353-fold and 1.420-fold higher risk for MACEs and overall mortality,than the lowest quartile group.Similarly,the highest baseline TyG-WC cohort showed a 1.314-fold and 1.480-fold higher risk for MACEs and overall mortality,respectively.Each 1 SD increase in TyG-WHtR was significantly related to an 11.7%increase in MACEs and a 14.9%enhance in overall mortality.Each 1 SD increase in TyG-WC corresponded to an 11.5%in MACEs and a 16.6%increase in overall mortality.Including these two indexes in conventional models significantly improved the predictive power for MACEs and overall mortality.CONCLUSION TyG-WHtR and TyG-WC were promising predictors of MACEs and overall mortality risk in T2DM cases.
基金supported by the National Natural Science Foundation of China(No.52202090)the Fundamental Research Funds for the Central Universities(No.2082019014).
文摘Thorium dioxide(ThO_(2))fibers exhibit exceptional structural stability,low density and superior flexibility,coupled with a remarkably high melting point,positioning them as promising candidates for thermal protection applications.Additionally,their commendable secondary processing characteristics enable the development of diverse composite materials when integrated with other materials,significantly broadening the potential utilization of ThO_(2)materials and thorium resources in industrial fields.In this work,the ThO_(2)fiber was fabricated by the sol-gel precursor method,and the precursor with good spinnability and excellent stability was synthesized for the first time.The ThO_(2)fiber with a mean diameter of 868 nm is both highly flexible and strong(max.tensile strength 2.21 MPa),capable of bending freely across a wide temperature range from-196℃(in liquid nitrogen)to 1200℃.Meanwhile,it exhibits excellent temperature stability and heat insulation properties.The ThO_(2)nanofiber membranes with layered structure have low density(32-37 mg·cm^(-3)),low thermal conductivity(27.3-30.1 mW·m^(-1)·K^(-1)@25℃).The ThO_(2)nanofiber membranes with 15 mm thickness can reduce the temperature from 1200 to 282℃and maintain a high aspect ratio and bendability after 1200℃@90 min.The results show that the ThO_(2)fiber can be used as a new kind of high-temperature resistant material.
文摘Stellar classification is a fundamental task in astronomical data analysis.Photometric data offer a significant advantage over spectral data in terms of data volume.Their lower acquisition cost and broader coverage make them more suitable for stellar classification applications.This study selects photometric data from the SDSS DR18.Instead of using traditional RGB image formats,a series of preprocessing steps were applied to generate five-channel Numpy files as the data set.To enhance stellar classification performance,we propose a deep learning model based on photometric feature fusion–Stellar Photometric Features Fusion Network.Additionally,we introduce the Dynamic Enhanced Stellar Squeeze-and-Excitation module,designed to optimize the weight allocation of different photometric bands in the classification task,and investigate the impact of each band's features on classification performance.Ultimately,we found that the information from the r and z bands played a more crucial role in the stellar classification task,achieving a final classification accuracy of 87.47%,thereby demonstrating the effectiveness of photometric data in stellar classification.
文摘本研究旨在应用康奈尔绵羊净碳水化合物和蛋白质体系(Cornell sheep net carbohydrate and protein system,CNCPS-S)的瘤胃降解预测模型预测日粮碳水化合物(CHO)瘤胃有效降解率,并实测验证CNCPS-S模型预测值的准确性。选取3只安装瘤胃瘘管、体重分别为(38.03±1.56)kg的哈萨克公羊作为试验动物,配制3种精粗比分别为30∶70、35∶65、40∶60的全混合日粮(TMR),利用瘤胃灌注试验和尼龙袋试验实测3种日粮CHO的瘤胃外流速度(Kp)和降解率,同时利用CNCPS-S模型预测3种日粮CHO的Kp与降解率,对CHO的降解率预测值和实测值进行线性回归分析,评价模型预测的准确性。结果表明:3种TMR的瘤胃食糜Kp随精料比例增加而依次升高(P<0.01),分别为3.58%/h、3.83%/h、4.05%/h,据此计算而得的CHO的降解率分别为42.7%、43.1%、42.3%(P>0.05);随精料比例的增加,3种TMR的瘤胃食糜Kp的模型预测值依次升高(P>0.05),分别为1.62%/h、1.63%/h、1.64%/h,CHO瘤胃降解率的预测值分别为39.5%、39.1%、39.6%(P>0.05);3种日粮CHO瘤胃降解率的预测值与实测值之间的平均偏差比较小(≤4 g/100 g CHO),相关性较高(R2≥0.86),均方根误差也较低(RMSE≤1.93 g/100 g CHO)。以上结果说明,CNCPS-S瘤胃降解预测模型对日粮CHO的降解率具有较好的预测能力。
文摘研究旨在应用康奈尔绵羊净碳水化合物和蛋白质体系(Cornell sheep net carbohydrate and protein system,CNCPS-S)的预测模型预测日粮瘤胃pH值与微生物蛋白质(MCP)合成量,并通过实测验证模型预测值的准确性。选取3只安装瘤胃和十二指肠瘘管的哈萨克公羊为试验动物,配制3种精粗比为30:70、35:65、40:60的全混合日粮(TMR)。采用3×3拉丁方设计,共3期试验,每期18 d,其中10 d为预试期,8 d为样品采集,测定瘤胃液pH和MCP合成量。同时利用CNCPS-S模型预测3种日粮的MCP合成量,评价模型预测的准确性。结果表明:①3种TMR的瘤胃液pH的实测值分别在6.38~6.71、6.01~6.59、5.81~6.41之间,模型预测pH为固定值6.46;②随着精料水平增加,3种TMR均为瘤胃能氮负平衡型,瘤胃能氮平衡(RENB)值均呈下降趋势(P<0.05),3种TMR的MCP的模型预测值依次升高,分别为210.29、215.31、246.94 g/d(P>0.05),实测值也依次升高,分别为93.83、97.33、100.27 g/d(P<0.05);③经线性回归分析,3种日粮MCP的预测值与十二指肠MCP实测值之间的平均偏差比较大(平均偏差≥116 g/d),相关性低(R^2≤0.75),误差均方根(RMSE)都较高。以上结果说明,CNCPS-S对我国绵羊瘤胃pH值具有较好的预测能力,但对MCP合成量具有较低的预测能力。
基金supported by Wuhan Municipal Science and Technology Bureau of applied basic research project(No.2013062301010823)Wuhan City health planning medieal research project(No.WX14A11)
文摘Objective:To build GPC3 gene short hairpin interference RNA(shRNA)slow virus veclor.observe expression of Huh-7 GPC3 gene in human liver cell line proliferation apoptosis and the effect of GPC3 gene influencing on liver cancer cell growth,and provide theoretical basis for genc therapy of liver cancer.Methods:Hepatocellular carcinoma cell line Huh-7 wsa transfected by a RNA interference technique.GPC3 gene expression in a variety of liver cancer cell lines was detected by fluorescence quantitative PCR.Targeted GPC3 gene seqnences of small interfering RNA(siRNA)PGC-shRNA-GPC3 were restructured.Stable expression cell linse of siRNA were screened and established with the heplp of liposomes(lipofectamine^(TM2000))as carrier transfcetion of human liver cell lines.In order to validate siRNA interference efficiency.GPC3 siRNA mRNA expression was detected after transfection by using RT-PCR and Western blot.The absorbance value of the cells of blank group,untransfection group and transfection group,the cell cycle and cell apoptosis were calculated,and effects of GPC3 gene nn Huh-7 cell proliferation and apoptosis were observed.Results:In the liver cancer cell lines Huh-7 GPC3 gene showed high expression.PGC-shRNA-GPC3 recombinant plasmid was constructde successfully via sequencing validation.Stable recombinant plasmid transfected into liver cancer cell linse Huh-7can obviously inhibit GPC3 mRNA expression level.Conclusions:The targeted GPC3 siRNA can effectively inhibit the expression of GPC3.
基金partially supported by the National Natural Science Foundation of China(Grant No.61775241)the Youth Innovation Team(Grant No:2019012)of CSU+3 种基金the Hunan province key research and development project(Grant No:2019GK2233)Hunan Province Graduate Research and Innovation Project(Grant No:CX20190177)the Science and Technology Innovation Basic Research Project of Shenzhen(Grant No.JCYJ20180307151237242)the funding support from the Australian Research Council(ARC Discovery Project,DP180102976).
文摘Spintronics,exploiting the spin degree of electrons as the information vector,is an attractive field for implementing the beyond Complemetary metal-oxide-semiconductor(CMOS)devices.Recently,two-dimensional(2D)materials have been drawing tremendous attention in spintronics owing to their distinctive spin-dependent properties,such as the ultralong spin relaxation time of graphene and the spin-valley locking of transition metal dichalcogenides.Moreover,the related heterostructures provide an unprecedented probability of combining the di erent characteristics via proximity e ect,which could remedy the limitation of individual 2D materials.Hence,the proximity engineering has been growing extremely fast and has made significant achievements in the spin injection and manipulation.Nevertheless,there are still challenges toward practical application;for example,the mechanism of spin relaxation in 2D materials is unclear,and the high-effciency spin gating is not yet achieved.In this review,we focus on 2D materials and related heterostructures to systematically summarize the progress of the spin injection,transport,manipulation,and application for information storage and processing.We also highlight the current challenges and future perspectives on the studies of spintronic devices based on 2D materials.
基金funded by the Australian Government through the Australian Research Council’s Discovery Projects funding scheme (Project DP190101592)the National Natural Science Foundation of China (Grant Nos. 41972280 and 52179103)。
文摘This study introduces a generic framework for geotechnical subsurface modeling, which accounts for spatial autocorrelation with local mapping machine learning(ML) methods. Instead of using XY coordinate fields directly as model input, a series of autocorrelated geotechnical distance fields(GDFs) is designed to enable the ML models to infer the spatial relationship between the sampled locations and unknown locations. The whole framework using GDF with ML methods is named GDF-ML. This framework is purely data-driven which avoids the tedious work in the scale of fluctuations(SOFs)estimating and data detrending in the conventional spatial interpolation methods. Six local mapping ML methods(extra trees(ETs), gradient boosting(GB), extreme gradient boosting(XGBoost), random forest(RF), general regression neural network(GRNN) and k-nearest neighbors(KNN)) are compared in the GDF-ML framework. The results show that the GDFs are better than the conventional XY coordinate fields based ML methods in both accuracy and spatial continuity. GDF-ML is flexible which can be applied to high-dimensional, multi-variable and incomplete datasets. Among these six methods, GDF with ET method(GDF-ET) clearly shows the best accuracy and best spatial continuity. The proposed GDF-ET method can provide a fast and accurate interpretation of the soil property profile. Sensitivity analysis shows that this method is applicable to very small training dataset size. The associated statistical uncertainty can also be quantified so that the reliability of the subsurface modeling results can be estimated objectively and explicitly. The uncertainty results clearly show that the prediction becomes more accurate when more sampled data are available.
