目的分析冠向复位瓣术、侧向转位瓣术、双乳头瓣术修复牙龈瘤切除术后软组织缺损的临床疗效。方法临床收集23例牙龈瘤患者,术中切除牙龈瘤后,根据软组织缺损情况分别采用冠向复位瓣术、侧向转位瓣术、双乳头瓣术行软组织修复。术前及术...目的分析冠向复位瓣术、侧向转位瓣术、双乳头瓣术修复牙龈瘤切除术后软组织缺损的临床疗效。方法临床收集23例牙龈瘤患者,术中切除牙龈瘤后,根据软组织缺损情况分别采用冠向复位瓣术、侧向转位瓣术、双乳头瓣术行软组织修复。术前及术后6个月测量牙龈指数(gingival index,GI)、角化龈宽度(keratinized gingival width,KGW)、牙龈退缩(gingival re⁃cession,GR)、龈乳头充填指数(papilla fill index,PFI),记录牙龈瘤切除术后形成的牙龈退缩类型及术后2周患者自主疼痛评分(visual analog scale,VAS),以评价3组修复方式的临床疗效。结果术后6个月3组患者牙龈瘤均无复发。与术前相比,采用3种带蒂瓣修复后GI、GR均显著改善(P<0.05);KGW均显著增加(P<0.05),其中侧向转位瓣组及双乳头瓣组术后KGW明显宽于冠向复位瓣组(P<0.05);冠向复位瓣组及侧向转位瓣组PFI较术前明显增加(P<0.05);其他指标差异无统计学差异(P>0.05)。结论3种带蒂瓣修复软组织缺损均取得了良好的临床和美学效果,术后角化龈明显增宽,其中侧向转位瓣术及双乳头瓣术优于冠向复位瓣术。展开更多
For high-speed mobile MIMO-OFDM system,a low-complexity deep learning(DL) based timevarying channel estimation scheme is proposed.To reduce the number of estimated parameters,the basis expansion model(BEM) is employed...For high-speed mobile MIMO-OFDM system,a low-complexity deep learning(DL) based timevarying channel estimation scheme is proposed.To reduce the number of estimated parameters,the basis expansion model(BEM) is employed to model the time-varying channel,which converts the channel estimation into the estimation of the basis coefficient.Specifically,the initial basis coefficients are firstly used to train the neural network in an offline manner,and then the high-precision channel estimation can be obtained by small number of inputs.Moreover,the linear minimum mean square error(LMMSE) estimated channel is considered for the loss function in training phase,which makes the proposed method more practical.Simulation results show that the proposed method has a better performance and lower computational complexity compared with the available schemes,and it is robust to the fast time-varying channel in the high-speed mobile scenarios.展开更多
文摘目的分析冠向复位瓣术、侧向转位瓣术、双乳头瓣术修复牙龈瘤切除术后软组织缺损的临床疗效。方法临床收集23例牙龈瘤患者,术中切除牙龈瘤后,根据软组织缺损情况分别采用冠向复位瓣术、侧向转位瓣术、双乳头瓣术行软组织修复。术前及术后6个月测量牙龈指数(gingival index,GI)、角化龈宽度(keratinized gingival width,KGW)、牙龈退缩(gingival re⁃cession,GR)、龈乳头充填指数(papilla fill index,PFI),记录牙龈瘤切除术后形成的牙龈退缩类型及术后2周患者自主疼痛评分(visual analog scale,VAS),以评价3组修复方式的临床疗效。结果术后6个月3组患者牙龈瘤均无复发。与术前相比,采用3种带蒂瓣修复后GI、GR均显著改善(P<0.05);KGW均显著增加(P<0.05),其中侧向转位瓣组及双乳头瓣组术后KGW明显宽于冠向复位瓣组(P<0.05);冠向复位瓣组及侧向转位瓣组PFI较术前明显增加(P<0.05);其他指标差异无统计学差异(P>0.05)。结论3种带蒂瓣修复软组织缺损均取得了良好的临床和美学效果,术后角化龈明显增宽,其中侧向转位瓣术及双乳头瓣术优于冠向复位瓣术。
基金Supported by the National Science Foundation Program of Jiangsu Province (No.BK20191378)the National Science Research Project of Jiangsu Higher Education Institutions (No.18KJB510034)+2 种基金China Postdoctoral Science Fund Special Funding Project (No.2018T110530)the Key Technologies R&D Program of Jiangsu Province (No.BE2022067,BE2022067-2)Major Research Program Key Project(No.92067201)。
文摘For high-speed mobile MIMO-OFDM system,a low-complexity deep learning(DL) based timevarying channel estimation scheme is proposed.To reduce the number of estimated parameters,the basis expansion model(BEM) is employed to model the time-varying channel,which converts the channel estimation into the estimation of the basis coefficient.Specifically,the initial basis coefficients are firstly used to train the neural network in an offline manner,and then the high-precision channel estimation can be obtained by small number of inputs.Moreover,the linear minimum mean square error(LMMSE) estimated channel is considered for the loss function in training phase,which makes the proposed method more practical.Simulation results show that the proposed method has a better performance and lower computational complexity compared with the available schemes,and it is robust to the fast time-varying channel in the high-speed mobile scenarios.
