目的通过网状Meta分析评价不同干预措施对阴道产后盆底肌力恢复的效果。方法计算机检索Pubmed、Embase、Web of Science、中国知网、万方数据库和中国生物医学文献服务系统,搜集有关阴道分娩产妇产后早期康复的文献,检索时限设定为建库...目的通过网状Meta分析评价不同干预措施对阴道产后盆底肌力恢复的效果。方法计算机检索Pubmed、Embase、Web of Science、中国知网、万方数据库和中国生物医学文献服务系统,搜集有关阴道分娩产妇产后早期康复的文献,检索时限设定为建库至2021年11月,采用Cochrance手册对纳入的文献进行风险评估,然后采用StataMP 14.2进行网状Meta分析。结果共纳入研究20项,涉及研究对象3537名产妇。网状Meta分析结果显示,对提高阴道分娩产妇盆底肌肌力临床效果排序依次为生物反馈训练+阴道哑铃训练、产后盆底功能锻炼(PFMT)+产后康复教育、PFMT+电刺激+生物反馈训练、PFMT+Bobath球训练、阴道哑铃训练、PFMT+电刺激、电刺激、PFMT+生活干预、PFMT、PFMT+产后瑜伽锻炼+会阴部按摩、产后常规护理。结论生物反馈训练+阴道哑铃训练对提高阴道分娩产妇产后盆底肌肌力效果最佳。展开更多
Failure depth of coal seam floors is one of the important considerations that must be kept in mind when mining is carried out above a confined aquifer. In order to study the factors that affect the failure depth of co...Failure depth of coal seam floors is one of the important considerations that must be kept in mind when mining is carried out above a confined aquifer. In order to study the factors that affect the failure depth of coal seam floors such as mining depth, coal seam pitch, mining thickness, workface length and faults, we propose a combined artificial neural networks (ANN) prediction model for failure depth of coal seam floors on the basis of existing engineering data by using genetic algorithms to train the ANN. A practical engineering application at the Taoyuan Coal Mine indicates that this method can effectively determine the network struc- ture and training parameters, with the predicted results agreeing with practical measurements. Therefore, this method can be applied to relevant engineering projects with satisfactory results.展开更多
The present article investigates the physical phenomena associated with the wave passage effect into a building considering the ground floor as the soft floor with the conformity of the up-to-date scenario of the cons...The present article investigates the physical phenomena associated with the wave passage effect into a building considering the ground floor as the soft floor with the conformity of the up-to-date scenario of the construction of high rise buildings, due to shear excitation of the base. The aim of the study is to analyse the post-earthquake situation of the building in respect to its health. With this vision, the ensuing problem on two-dimensional building models, non-incorporating soil-structure interaction, is being tackled by both analytical and neural network approaches. Computational results from both ends (of the approaches) show that the wave energy does not always propagate from the ground into the building, but for lower frequency range it sails to the building without any disturbances. However, for higher frequency range, the computational results show that the building experiences large “torsional” deformations, as a result the building may collapse. Finally, both the approaches maintain a good agreement among themselves. The present investigation may lead to a long way in contributing to better and more rational, simplified design criteria.展开更多
文摘目的通过网状Meta分析评价不同干预措施对阴道产后盆底肌力恢复的效果。方法计算机检索Pubmed、Embase、Web of Science、中国知网、万方数据库和中国生物医学文献服务系统,搜集有关阴道分娩产妇产后早期康复的文献,检索时限设定为建库至2021年11月,采用Cochrance手册对纳入的文献进行风险评估,然后采用StataMP 14.2进行网状Meta分析。结果共纳入研究20项,涉及研究对象3537名产妇。网状Meta分析结果显示,对提高阴道分娩产妇盆底肌肌力临床效果排序依次为生物反馈训练+阴道哑铃训练、产后盆底功能锻炼(PFMT)+产后康复教育、PFMT+电刺激+生物反馈训练、PFMT+Bobath球训练、阴道哑铃训练、PFMT+电刺激、电刺激、PFMT+生活干预、PFMT、PFMT+产后瑜伽锻炼+会阴部按摩、产后常规护理。结论生物反馈训练+阴道哑铃训练对提高阴道分娩产妇产后盆底肌肌力效果最佳。
基金Projects 50874103 supported by the National Natural Science Foundation of China2006CB202210 by the National Basic Research Program of China+1 种基金BK2008135 by the Natural Science Foundation of Jiangsu Provincethe Qing-lan Project of Jiangsu Province
文摘Failure depth of coal seam floors is one of the important considerations that must be kept in mind when mining is carried out above a confined aquifer. In order to study the factors that affect the failure depth of coal seam floors such as mining depth, coal seam pitch, mining thickness, workface length and faults, we propose a combined artificial neural networks (ANN) prediction model for failure depth of coal seam floors on the basis of existing engineering data by using genetic algorithms to train the ANN. A practical engineering application at the Taoyuan Coal Mine indicates that this method can effectively determine the network struc- ture and training parameters, with the predicted results agreeing with practical measurements. Therefore, this method can be applied to relevant engineering projects with satisfactory results.
文摘The present article investigates the physical phenomena associated with the wave passage effect into a building considering the ground floor as the soft floor with the conformity of the up-to-date scenario of the construction of high rise buildings, due to shear excitation of the base. The aim of the study is to analyse the post-earthquake situation of the building in respect to its health. With this vision, the ensuing problem on two-dimensional building models, non-incorporating soil-structure interaction, is being tackled by both analytical and neural network approaches. Computational results from both ends (of the approaches) show that the wave energy does not always propagate from the ground into the building, but for lower frequency range it sails to the building without any disturbances. However, for higher frequency range, the computational results show that the building experiences large “torsional” deformations, as a result the building may collapse. Finally, both the approaches maintain a good agreement among themselves. The present investigation may lead to a long way in contributing to better and more rational, simplified design criteria.
