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| 1 | Smoking Behavior Among Secondary School Students--China, 2021显示文摘Summary What is already known about this topic?In 2019,China CDC conducted the National Youth Tobacco Survey among secondary school students,and the prevalence rates of ever,current,and frequent smoking were 17.9%,5.9%,and 1.8%,respectively.What is added by this report?The prevalence rate of cigarette use in males decreased largely from 2019 to 2021 in China,while it increased in 18 provincial-level administrative divisions(PLADs)for females.The tobacco control situation remains challenging among vocational senior high school(VSHS)students.Significant geographical disparities existed in cigarette use.What are the implications for public health practice?Targeted tobacco control policies aimed at VSHS students are needed,specifically those PLADs with higher smoking rates.Additionally,close attention should be paid to female smokers. | Xinying Zeng Xinbo Di Shiwei Liu Huiyu Xie Zida Meng Lin Xiao | 2022 | China CDC weekly2022，4，21： | 5 |
| 2 | Intelligent rockburst prediction model with sample category balance using feedforward neural network and Bayesian optimization显示文摘The rockburst prediction becomes more and more challenging due to the development of deep underground projects and constructions.Increasing numbers of intelligent algorithms are used to predict and prevent rockburst.This paper investigated the drawbacks of neural networks in rockburst prediction,and aimed at these shortcomings,Bayesian optimization and the synthetic minority oversampling technique+Tomek Link(SMOTETomek)were applied to efficiently develop the feedforward neural network(FNN)model for rockburst prediction.In this regard,314 real rockburst cases were collected to establish a database for modeling.The database was divided into a training set(80%)and a test set(20%).The maximum tangential stress,uniaxial compressive strength,tensile strength,stress ratio,brittleness ratio,and elastic strain energy were selected as input parameters.Bayesian optimization was implemented to find the optimal hyperparameters in FNN.To eliminate the effects of imbalanced category,SMOTETomek was adopted to process the training set to obtain a balanced training set.The FNN developed by the balanced training set received 90.48% accuracy in the test set,and the accuracy improved 12.7% compared to the imbalanced training set.For interpreting the FNN model,the permutation importance algorithm was introduced to analyze the relative importance of input variables.The elastic strain energy was the most essential variable,and some measures were proposed to prevent rockburst.To validate the practicability,the FNN developed by the balanced training set was utilized to predict rockburst in Sanshandao Gold Mine,China,and it had outstanding performance(accuracy 100%). | Diyuan Li Zida Liu Peng Xiao Jian Zhou Danial Jahed Armaghani | 2022 | Underground Space2022，7，5： | 2 |
| 3 | Research and development of intelligent control system of automatic transmission for wheel loader显示文摘 | YUAN Zhou LIU Mingshan ZHANG Zida | 2009 | IEEE AESS Systems Magazine2009，，2： | 1 |
| 4 | Utilization of Smoking Cessation Support Among Adults-18 PLADs,China,2020显示文摘Summary What is already known about this topic?In 2018,unassisted smoking cessation(USC)was the predominant method for quitting smoking among Chinese adult smokers,accounting for 90.1%of cases.The utilization of professional smoking cessation support was comparatively low in this population.What was added by this report?In 2020,the prevalence of USC methods increased to 93.1%.Concurrently,there was a slight increase in the utilization of pharmaceuticals(from 4.6%in 2018 to 5.5%in 2020)and counseling and quit line services(from 3.2%in 2018 to 7.5%in 2020).On the other hand,the use of e-cigarettes as a cessation aid decreased from 14.9%in 2018 to 9.8%in 2020.Smokers aged 15–24 years old were more likely to rely on pharmaceutical interventions(7.9%),and less likely to choose USC methods(79.0%).What are the implications for public health practice?The promotion of professional cessation support is essential for enhancing smoking cessation rates. | Yongfu Yan Bingliang Lin Qingqing Xu Huiyu Xie Xinying Zeng Xinbo Di Zida Meng Lin Xiao Shiwei Liu | 2023 | China CDC weekly2023，5，21： | 1 |
| 5 | Tobacco Use and Cessation Among College Students--China, 2021显示文摘Summary What is already known about this topic?Previous studies about tobacco use among college students in China were conducted at the school level or city level,with fewer than 5,000 students participating.What is added by this report?In 2021,China CDC conducted a national tobacco survey targeting students enrolled in the public higher education system.Overall,124,119 students from 220 colleges and universities in 31 provincial-level administrative divisions participated in this survey.Current cigarette smoking,current daily smoking,willingness to quit,and smoking cessation among college students were explored.What are the implications for public health practice?The current daily cigarette smoking rate of college students was significantly higher than that of senior high school students,especially higher vocational college students.Tobacco control interventions,such as a smoke-free school policy and smoking cessation services,need to be reinforced on college campuses. | Huiyu Xie Xinbo Di Shiwei Liu Xinying Zeng Zida Meng Lin Xiao | 2022 | China CDC weekly2022，4，21： | 1 |
| 6 | Recent advances in understanding T cell activation and exhaustion during HBV infection显示文摘Chronic hepatitis B virus(HBV)infection remains a major public health concern globally,and T cell responses are widely believed to play a pivotal role in mediating HBV clearance.Accordingly,research on the characteristics of HBV-specific T cell responses,from activation to exhaustion,has advanced rapidly.Here,we summarize recent developments in characterizing T cell immunity in HBV infection by reviewing basic and clinical research published in the last five years.We provide a comprehensive summary of the mechanisms that induce effective anti-HBV T cell immunity,as well as the latest developments in understanding T cell dysfunction in chronic HBV infection.Furthermore,we briefly discuss current novel treatment strategies aimed at restoring anti-HBV T cell responses. | Lu Wang Xiaoqing Zeng Zida Wang Ling Fang Jia Liu | 2023 | Virologica Sinica2023，38，6： | 0 |
| 7 | Fabrication of adsorbents with enhanced CuⅠ stability: Creating a superhydrophobic microenvironment through grafting octadecylamine显示文摘In atmospheric conditions, CuⅠis easily oxidized to CuⅡdue to the coexistence of moisture and oxygen.The poor oxidation inhibition of CuⅠrestricts the practical application of CuⅠ-containing materials.Herein we introduce an approach to construct a superhydrophobic microenvironment in CuⅠfunctionalized metal–organic frameworks by coordinatedly grafting organic amine compounds onto open metal sites(OMSs), which can hinder the accessibility of moisture to pores thereby enhancing the stability of CuⅠ. As a proof of concept, MIL-101(Cr) with abundant OMSs and octadecylamine(OA)with long hydrophobic alkyl groups are used as carrier and surface coating. As superhydrophobic porous materials, the resultant CuⅠM-OA exhibits improved CuⅠstability in addition to retaining high crystallinity and intact porosity while almost all CuⅠis oxidized in hydrophilic CuⅠM upon exposure in a humid atmosphere for 30 h. CuⅠM-OA owns excellent adsorption desulfurization performance(ADS) with regard to thiophene, benzothiophene, and 4,6-dimethyl dibenzothiophene. Even from hydrated fuel, the adsorption performance of CuⅠM-OA maintains well while the adsorption capacity of CuⅠM decreases to 7% after4 cycles. The remarkable moisture resistance, CuⅠstability, and high porosity make the current adsorbent CuⅠM-OA highly promising for the practical ADS process. | Zida Ma Yuxia Li Mengmeng Jin Xiaoqin Liu Linbing Sun | 2023 | Chinese Journal of Chemical Engineering2023，55，3： | 0 |
| 8 | Dysfunctional resting-state EEG microstate correlated with the severity of cigarette exposure in nicotine addiction显示文摘Dear editor,Nicotine is a significant cause of severe physical and psychiatric disorders.Evidence suggests that smokers have poorer global cognitive functioning in later life,as well as lower average scores in several cognitive domains,including cognitive flexibility and memory [1]. | Yan CHENG Junjie BU Nan LI Jian LI Huixing GOU Shinan SUN Chang LIU Zida JIN Changle HE Chuan FAN Chialun LIU Xiaochu ZHANG | 2020 | Science China(Information Sciences)2020，63，7： | 0 |
| 9 | Rock Strength Estimation Using Several Tree-Based ML Techniques显示文摘The uniaxial compressive strength(UCS)of rock is an essential property of rock material in different relevant applications,such as rock slope,tunnel construction,and foundation.It takes enormous time and effort to obtain the UCS values directly in the laboratory.Accordingly,an indirect determination of UCS through conducting several rock index tests that are easy and fast to carry out is of interest and importance.This study presents powerful boosting trees evaluation framework,i.e.,adaptive boosting machine,extreme gradient boosting machine(XGBoost),and category gradient boosting machine,for estimating the UCS of sandstone.Schmidt hammer rebound number,P-wave velocity,and point load index were chosen as considered factors to forecast UCS values of sandstone samples.Taylor diagrams and five regression metrics,including coefficient of determination(R2),root mean square error,mean absolute error,variance account for,and A-20 index,were used to evaluate and compare the performance of these boosting trees.The results showed that the proposed boosting trees are able to provide a high level of prediction capacity for the prepared database.In particular,itwas worth noting that XGBoost is the best model to predict sandstone strength and it achieved 0.999 training R^(2) and 0.958 testing R^(2).The proposed model had more outstanding capability than neural network with optimization techniques during training and testing phases.The performed variable importance analysis reveals that the point load index has a significant influence on predicting UCS of sandstone. | Zida Liu Danial Jahed Armaghani Pouyan Fakharian Diyuan Li Dmitrii Vladimirovich Ulrikh Natalia Nikolaevna Orekhova Khaled Mohamed Khedher | 2022 | Computer Modeling in Engineering & Sciences2022，，12： | 0 |
| 10 | Intelligent method to experimentally identify the fracture mechanism of red sandstone显示文摘Tensile and shear fractures are significant mechanisms for rock failure.Understanding the fractures that occur in rock can reveal rock failure mechanisms.Scanning electron microscopy(SEM)has been widely used to analyze tensile and shear fractures of rock on a mesoscopic scale.To quantify tensile and shear fractures,this study proposed an innovative method composed of SEM images and deep learning techniques to identify tensile and shear fractures in red sandstone.First,direct tensile and preset angle shear tests were performed for red sandstone to produce representative tensile and shear fracture surfaces,which were then observed by SEM.Second,these obtained SEM images were applied to develop deep learning models(AlexNet,VGG13,and SqueezeNet).Model evaluation showed that VGG13 was the best model,with a testing accuracy of 0.985.Third,the features of tensile and shear fractures of red sandstone learned by VGG13 were analyzed by the integrated gradient algorithm.VGG13 was then implemented to identify the distribution and proportion of tensile and shear fractures on the failure surfaces of rock fragments caused by uniaxial compression and Brazilian splitting tests.Results demonstrated the model feasibility and suggested that the proposed method can reveal rock failure mechanisms. | Zida Liu Diyuan Li Quanqi Zhu Chenxi Zhang Jinyin Ma Junjie Zhao | 2023 | International Journal of Minerals,Metallurgy and Materials2023，30，11： | 0 |
| 11 | Prediction of uniaxial compressive strength of rock based on lithology using stacking models显示文摘Uniaxial compressive strength(UCS)of rock is an essential parameter in geotechnical engineering.Point load strength(PLS),P-wave velocity,and Schmidt hammer rebound number(SH)are more easily obtained than UCS and are extensively applied for the indirect estimation of UCS.This study collected 1080 datasets consisting of SH,P-wave velocity,PLS,and UCS.All datasets were integrated into three categories(sedimentary,igneous,and metamorphic rocks)according to lithology.Stacking models combined with tree-based models and linear regression were developed based on the datasets of three rock types.Model evaluation showed that the stacking model combined with random forest and linear regression was the optimal model for three rock types.UCS of metamorphic rocks was less predictable than that of sedimentary and igneous rocks.Nonetheless,the proposed stacking models can improve the predictive performance for UCS of metamorphic rocks.The developed predictive models can be applied to quickly predict UCS at engineering sites,which benefits the rapid and intelligent classification of rock masses.Moreover,the importance of SH,P-wave velocity,and PLS were analyzed for the estimation of UCS.SH was a reliable indicator for UCS evaluation across various rock types.P-wave velocity was a valid parameter for evaluating the UCS of igneous rocks,but it was not reliable for assessing the UCS of metamorphic rocks. | Zida Liu Diyuan Li Yongping Liu Bo Yang Zong-Xian Zhang | 2023 | Rock Mechanics Bulletin2023，2，4： | 0 |
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