To review the rockburst proneness(or tendency)criteria of rock materials and compare the judgment accuracy of them,twenty criteria were summarized,and their judgment accuracy was evaluated and compared based on the la...To review the rockburst proneness(or tendency)criteria of rock materials and compare the judgment accuracy of them,twenty criteria were summarized,and their judgment accuracy was evaluated and compared based on the laboratory tests on fourteen types of rocks.This study begins firstly by introducing the twenty rockburst proneness criteria,and their origins,definitions,calculation methods and grading standards were summarized in detail.Subsequently,to evaluate and compare the judgment accuracy of the twenty criteria,a series of laboratory tests were carried out on fourteen types of rocks,and the rockburst proneness judgment results of the twenty criteria for the fourteen types of rocks were obtained accordingly.Moreover,to provide a unified basis for the judgment accuracy evaluation of above criteria,a classification standard(obtained according to the actual failure results and phenomena of rock specimen)of rockburst proneness in laboratory tests was introduced.The judgment results of the twenty criteria were compared with the judgment results of this classification standard.The results show that the judgment results of the criterion based on residual elastic energy(REE)index are completely consistent with the actual rockburst proneness,and the other criteria have some inconsistent situations more or less.Moreover,the REE index is based on the linear energy storage law and defined in form of a difference value and considered the whole failure process,and these superior characteristics ensure its accuracy.It is believed that the criterion based on REE index is comparatively more accurate and scientific than other criteria,and it can be recommended to be applied to judge the rockburst proneness of rock materials.展开更多
Rock burst is a severe disaster in mining and underground engineering,and it is important to predict the rock burst risk for minimizing the loss during the constructing process.The rock burst proneness was connected w...Rock burst is a severe disaster in mining and underground engineering,and it is important to predict the rock burst risk for minimizing the loss during the constructing process.The rock burst proneness was connected with the acoustic emission(AE) parameter in this work,which contributes to predicting the rock burst risk using AE technique.Primarily,a rock burst proneness index is proposed,and it just depends on the heterogeneous degree of rock material.Then,the quantificational formula between the value of rock burst proneness index and the accumulative AE counts in rock sample under uniaxial compression with axial strain increases is developed.Finally,three kinds of rock samples,i.e.,granite,limestone and sandstone are tested about variation of the accumulative AE counts under uniaxial compression,and the test data are fitted well with the theoretic formula.展开更多
OBJECTIVE To investigate the effects of LW-AFC,a new formula derived fromLiuwei Dihuang decoction,on gut microbiota and the behavior of learning and memory of SAMP8 mice,a mouse model of Alzheimer Disease(AD),and iden...OBJECTIVE To investigate the effects of LW-AFC,a new formula derived fromLiuwei Dihuang decoction,on gut microbiota and the behavior of learning and memory of SAMP8 mice,a mouse model of Alzheimer Disease(AD),and identify the specific intestinal microbiota correlating with cognitive ability.METHODS Morris-water maze test,novel object recognition test and shuttle-box test were conducted to observe the ability of learning and memory.16S rRNA amplicon sequencing(Illumina,San Diego,CA,USA)was employed to investigate gut microbiota.RESULTS The treatment of LW-AFC improved cognitive impairments of SAMP8 mice,including spatial learning and memory ability,active avoidance response,and object recognition memory capability.Our data indicated that there were significantly 8 increased and 12 decreased operational taxonomic units(OTUs)in the gut microbiota of SAMP8 mice compared with senescence accelerated mouse resistant 1(SAMR1) strains,the control of SAMP8 mice.The treatment of LW-AFC altered 22(16 increased and 6 decreased)OTUs in SAMP8 mice and among them,15 OTUs could be reversed by LW-AFC treatment resulting in a microbial composition similar to that of SAMR1 mice.We further showed that there were7(3 negative and 4 positive correlation)OTUs significantly correlated with all the three types of cognitive abilities,at the order level,including Bacteroidales,Clostridiales,Desulfovibrionales,CW040,and two unclassified orders.LW-AFC had influences on bacterial taxa correlated with the abilities of learning and memory in SAMP8 mice and restored them to SAMR1 mice.CONCLUSION The effects of LW-AFC on improving cognitive impairments of SAMP8 mice might be via modulating intestinal microbiome and LW-AFC could be used as a potential anti-AD agent.展开更多
The residual elastic energy index is a scientific evaluation index for rockburst proneness.In laboratory test,it is sometimes difficult to obtain the post-peak curve or to test the rock sample several times,which make...The residual elastic energy index is a scientific evaluation index for rockburst proneness.In laboratory test,it is sometimes difficult to obtain the post-peak curve or to test the rock sample several times,which makes it impossible to calculate the residual elastic energy index accurately.Based on 241 sets of experimental data and four input indexes of density,elastic modulus,peak intensity and peak input strain energy,this study proposed a machine learning model combining k-means clustering algorithm and random forest regression model:cluster forest(CF)model.The research employed a stratified sampling method on the dataset to ensure the representativeness and balance of the samples.Subsequently,grid search and five-fold cross-validation were utilized to optimize the model’s hyperparameters,aiming to enhance its generalization capability and prediction accuracy.Finally,the performance of the optimal model was evaluated using a test set and compared with five other commonly used models.The results indicate that the CF model outperformed the other models on the testing set,with a mean absolute error of 6.6%,and an accuracy of 93.9%.The results of sensitivity analyses reveal the degree of influence of each variable on rockburst proneness and the applicability of the CF model when the input parameters are missing.The robustness and generalization ability of the model were verified by introducing experimental data from other studies,and the results confirmed the reliability and applicability of the model.Therefore,the model not only effectively simplifies the acquisition of the residual elastic energy index,but also shows excellent performance and wide applicability.展开更多
目的:探讨俯卧位通气对体外膜氧合(ECMO)支持患者的应用效果。方法:系统检索中国知网、万方数据库、中国生物医学文献数据库、PubMed、Embase、Cochrane图书馆、Web of Science等数据库自建库至2024年10月关于俯卧位通气治疗ECMO支持患...目的:探讨俯卧位通气对体外膜氧合(ECMO)支持患者的应用效果。方法:系统检索中国知网、万方数据库、中国生物医学文献数据库、PubMed、Embase、Cochrane图书馆、Web of Science等数据库自建库至2024年10月关于俯卧位通气治疗ECMO支持患者的所有研究,由2名研究者独立进行文献筛选、资料提取和文献质量评价,采用RevMan 5.4软件对数据进行Meta分析。结果:共纳入10篇文献,包括2项随机对照研究和8项队列研究;包含1513例患者,其中俯卧位通气组674例、仰卧位通气组839例。对6项研究的分析结果显示,与仰卧位通气相比,俯卧位通气可提高ECMO成功撤机率(OR=1.47,95%CI:1.07~2.01,P=0.02)。对8项研究的分析结果显示,与仰卧位通气相比,俯卧位通气可延长ECMO治疗时长[均数差(MD)=4.86 d,95%CI:0.95~8.77,P=0.01]。对6项研究的分析结果显示,俯卧位通气组的重症监护病房(ICU)住院时长较仰卧位通气组显著延长(MD=5.16 d,95%CI:1.08~9.25,P=0.01)。对5项研究的分析结果显示,俯卧位通气组的总住院时长明显长于仰卧位通气组(MD=7.72 d,95%CI:2.10~13.34,P<0.01)。对6项研究的分析结果显示,与仰卧位通气相比,俯卧位通气可延长机械通气时长(MD=6.06 d,95%CI:0.63~11.49,P=0.03)。俯卧位通气在提高患者生存率方面并无明显优势。结论:俯卧位通气有助于提高ECMO成功撤机率,延长ECMO治疗时长及机械通气时长,但对患者的生存率无明显影响。由于本Meta分析纳入研究的样本量普遍较小,需更大样本量的研究来确认俯卧位通气对ECMO支持患者的实际疗效。展开更多
基金Project(41877272)supported by the National Natural Science Foundation of ChinaProject(2020zzts715)supported by the Fundamental Research Funds for the Central Universities of Central South University,ChinaProject(2242020R10023)supported by the Fundamental Research Funds for the Central Universities of Southeast University,China。
文摘To review the rockburst proneness(or tendency)criteria of rock materials and compare the judgment accuracy of them,twenty criteria were summarized,and their judgment accuracy was evaluated and compared based on the laboratory tests on fourteen types of rocks.This study begins firstly by introducing the twenty rockburst proneness criteria,and their origins,definitions,calculation methods and grading standards were summarized in detail.Subsequently,to evaluate and compare the judgment accuracy of the twenty criteria,a series of laboratory tests were carried out on fourteen types of rocks,and the rockburst proneness judgment results of the twenty criteria for the fourteen types of rocks were obtained accordingly.Moreover,to provide a unified basis for the judgment accuracy evaluation of above criteria,a classification standard(obtained according to the actual failure results and phenomena of rock specimen)of rockburst proneness in laboratory tests was introduced.The judgment results of the twenty criteria were compared with the judgment results of this classification standard.The results show that the judgment results of the criterion based on residual elastic energy(REE)index are completely consistent with the actual rockburst proneness,and the other criteria have some inconsistent situations more or less.Moreover,the REE index is based on the linear energy storage law and defined in form of a difference value and considered the whole failure process,and these superior characteristics ensure its accuracy.It is believed that the criterion based on REE index is comparatively more accurate and scientific than other criteria,and it can be recommended to be applied to judge the rockburst proneness of rock materials.
基金Project(2010CB226804)supported by the National Basic Research Program(973 Program)of ChinaProject(11202108)supported by the National Natural Science Foundation of ChinaProject(BK20130189)supported by the Natural Science Foundation of Jiangsu Province,China
文摘Rock burst is a severe disaster in mining and underground engineering,and it is important to predict the rock burst risk for minimizing the loss during the constructing process.The rock burst proneness was connected with the acoustic emission(AE) parameter in this work,which contributes to predicting the rock burst risk using AE technique.Primarily,a rock burst proneness index is proposed,and it just depends on the heterogeneous degree of rock material.Then,the quantificational formula between the value of rock burst proneness index and the accumulative AE counts in rock sample under uniaxial compression with axial strain increases is developed.Finally,three kinds of rock samples,i.e.,granite,limestone and sandstone are tested about variation of the accumulative AE counts under uniaxial compression,and the test data are fitted well with the theoretic formula.
基金supported by National Science and Technology Major Project(2013ZX09508104,2012ZX09301003-002-001)
文摘OBJECTIVE To investigate the effects of LW-AFC,a new formula derived fromLiuwei Dihuang decoction,on gut microbiota and the behavior of learning and memory of SAMP8 mice,a mouse model of Alzheimer Disease(AD),and identify the specific intestinal microbiota correlating with cognitive ability.METHODS Morris-water maze test,novel object recognition test and shuttle-box test were conducted to observe the ability of learning and memory.16S rRNA amplicon sequencing(Illumina,San Diego,CA,USA)was employed to investigate gut microbiota.RESULTS The treatment of LW-AFC improved cognitive impairments of SAMP8 mice,including spatial learning and memory ability,active avoidance response,and object recognition memory capability.Our data indicated that there were significantly 8 increased and 12 decreased operational taxonomic units(OTUs)in the gut microbiota of SAMP8 mice compared with senescence accelerated mouse resistant 1(SAMR1) strains,the control of SAMP8 mice.The treatment of LW-AFC altered 22(16 increased and 6 decreased)OTUs in SAMP8 mice and among them,15 OTUs could be reversed by LW-AFC treatment resulting in a microbial composition similar to that of SAMR1 mice.We further showed that there were7(3 negative and 4 positive correlation)OTUs significantly correlated with all the three types of cognitive abilities,at the order level,including Bacteroidales,Clostridiales,Desulfovibrionales,CW040,and two unclassified orders.LW-AFC had influences on bacterial taxa correlated with the abilities of learning and memory in SAMP8 mice and restored them to SAMR1 mice.CONCLUSION The effects of LW-AFC on improving cognitive impairments of SAMP8 mice might be via modulating intestinal microbiome and LW-AFC could be used as a potential anti-AD agent.
基金Project(42077244)supported by the National Natural Science Foundation of ChinaProject(SDGZK2431)supported by the State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering,Sichuan University,China。
文摘The residual elastic energy index is a scientific evaluation index for rockburst proneness.In laboratory test,it is sometimes difficult to obtain the post-peak curve or to test the rock sample several times,which makes it impossible to calculate the residual elastic energy index accurately.Based on 241 sets of experimental data and four input indexes of density,elastic modulus,peak intensity and peak input strain energy,this study proposed a machine learning model combining k-means clustering algorithm and random forest regression model:cluster forest(CF)model.The research employed a stratified sampling method on the dataset to ensure the representativeness and balance of the samples.Subsequently,grid search and five-fold cross-validation were utilized to optimize the model’s hyperparameters,aiming to enhance its generalization capability and prediction accuracy.Finally,the performance of the optimal model was evaluated using a test set and compared with five other commonly used models.The results indicate that the CF model outperformed the other models on the testing set,with a mean absolute error of 6.6%,and an accuracy of 93.9%.The results of sensitivity analyses reveal the degree of influence of each variable on rockburst proneness and the applicability of the CF model when the input parameters are missing.The robustness and generalization ability of the model were verified by introducing experimental data from other studies,and the results confirmed the reliability and applicability of the model.Therefore,the model not only effectively simplifies the acquisition of the residual elastic energy index,but also shows excellent performance and wide applicability.
