Objective To analyze the influence of segmental pedicle screws versus hybrid instrumentation on the correction results in adolescent idiopathic scoliosis patients undergoing posterior selective thoracic fusion. Metho...Objective To analyze the influence of segmental pedicle screws versus hybrid instrumentation on the correction results in adolescent idiopathic scoliosis patients undergoing posterior selective thoracic fusion. Methods By reviewing the medical records and roentgenograms of adolescent idiopathic scoliosis patients who underwent selective thoracic fusion from February 2000 to January 2007 in our hospital, the patients were divided into 2 groups according to different instrumentation fashions： Group A was hook-screw-rod （hybrid） internal fixation type, Group B was screw-rod （all pedicle screws） internal fixation type, and the screws were used in every segment on the concave side of the thoracic curve. The parameters of the scoliosis were measured and the correction results were analyzed. Results Totally, 48 patients （7 males, 41 females） were included, with an average age of 14.4 years old and a mean follow-up time of 12.3 months. Thirty and 18 patients were assigned to group A and group B, respectively. The mean preoperative coronal Cobb angles of the thoracic curve were 48.8° and 47.4°, respectively. After surgery, they were corrected to 13.7° and 6.8°, respectively. At final follow-up, they were 17.0° and 9.5°, with an average correction rate of 64.6% and 79.0%, respectively, and the correction rate of group B was significantly higher than that of group A （P=0.003）. The mean preoperative coronal Cobb angles of the lumbar curve were 32.6° and 35.2°, respectively. After surgery, they were corrected to 8.6° and 8.3°, respectively. At final follow-up, they were 10.3° and 11.1°, with an average correction rate of 66.8% and 69.9%, respectively, and the correction rate of group B was significantly higher than that of group A （P=0.003）. The correction loss of the thoracic curve and lumbar curve in the 2 groups were 3.1° and 1.8°, 2.4° and 2.4°, respectively. No significant difference was noted （both P〉0.05）. The decompensation rate at final follow-up in these 2 groups were 4% （1/25） and 7.1% （1/14） respectively, with no significant difference （P〉0.05）.展开更多
To define the criteria of posterior selective thoracic fusion in patients with adolescent idiopathic scoliosis. Methods By reviewing the medical records and roentgenograms of 17 patients with adolescent idiopathic sco...To define the criteria of posterior selective thoracic fusion in patients with adolescent idiopathic scoliosis. Methods By reviewing the medical records and roentgenograms of 17 patients with adolescent idiopathic scoliosis who un-derwent posterior selective thoracic fusion, the curve type, Cobb angle, apical vertebral rotation and translation, trunk shift, and thoracolumbar kyphosis were measured and analyzed. Results There were 17 King type Ⅱ patients (PUMC type: Ⅱb1 13, Ⅱc3 4). The coronal Cobb angle of thoracic curve be-fore and after operation were 56.9°and 21.6° respectively, the mean correction rate was 60.1%. The coronal Cobb angle of lumbar curve before and after operation were 34.8° and 12.1° respectively, and the mean spontaneous correction rate was 64.8%. At final follow-up, the coronal Cobb angle of thoracic and lumbar curve were 23.5° and 15.2° respectively, there were no significant changes in the coronal Cobb angle, apical vertebral translation and rotation compared with that after operation. One patient had 12° of thoracolumbar kyphosis after operation, no progression was noted at final follow-up. There was no trunk decompensation or deterioration of the lumbar curve. In this group, 3.9 levels were saved compared with fusing both the th-oracic and lumbar curves. Conclusion Posterior selective thoracic fusion can be safely and effectively performed in King type Ⅱ patients with a mo-derate and flexible lumbar curve, which can save more mobile segments and at the same time can maintain a good coronal and sagittal balance.展开更多
评审专家遴选是技术评审中的关键环节。鉴于颠覆性技术专家预判平台预判系统对时效性和智能型的要求,专家遴选对预判结果具有决定性影响。通过学术专长匹配和专业遴选来选择符合要求的专家,可以降低成本,提高推荐效率与准确度,完成颠覆...评审专家遴选是技术评审中的关键环节。鉴于颠覆性技术专家预判平台预判系统对时效性和智能型的要求,专家遴选对预判结果具有决定性影响。通过学术专长匹配和专业遴选来选择符合要求的专家,可以降低成本,提高推荐效率与准确度,完成颠覆性技术的预测任务。基于学术网络表示学习的方法既可以避免大量特征工程,又可以方便不同类型的特征进行融合。利用异质网络表示学习方法和标签排序的学术专长画像方法构建专家库,并使用融合专家综合评价指标特征的匹配方法对待预判的颠覆性技术和专家专长进行匹配,为专家遴选提供一份专业背景匹配的候选专家列表。这种方法在Academic Social Network数据集上进行模拟实验。实验结果表明,这种方法能提升项目评审专家学术专长匹配,在加入综合指标特征后,专家的综合指标特征能有效地反馈到实验结果中,从而提高评审系统的时效性和智能性。展开更多
In the realm of low-level vision tasks,such as image deraining and dehazing,restoring images distorted by adverse weather conditions remains a significant challenge.The emergence of abundant computational resources ha...In the realm of low-level vision tasks,such as image deraining and dehazing,restoring images distorted by adverse weather conditions remains a significant challenge.The emergence of abundant computational resources has driven the dominance of deep Convolutional Neural Networks(CNNs),supplanting traditional methods reliant on prior knowledge.However,the evolution of CNN architectures has tended towards increasing complexity,utilizing intricate structures to enhance performance,often at the expense of computational efficiency.In response,we propose the Selective Kernel Dense Residual M-shaped Network(SKDRMNet),a flexible solution adept at balancing computational efficiency with network accuracy.A key innovation is the incorporation of an M-shaped hierarchical structure,derived from the U-Net framework as M-Network(M-Net),within which the Selective Kernel Dense Residual Module(SDRM)is introduced to reinforce multi-scale semantic feature maps.Our methodology employs two sampling techniques-bilinear and pixel unshuffled and utilizes a multi-scale feature fusion approach to distil more robust spatial feature map information.During the reconstruction phase,feature maps of varying resolutions are seamlessly integrated,and the extracted features are effectively merged using the Selective Kernel Fusion Module(SKFM).Empirical results demonstrate the comprehensive superiority of SKDRMNet across both synthetic and real rain and haze datasets.展开更多
文摘Objective To analyze the influence of segmental pedicle screws versus hybrid instrumentation on the correction results in adolescent idiopathic scoliosis patients undergoing posterior selective thoracic fusion. Methods By reviewing the medical records and roentgenograms of adolescent idiopathic scoliosis patients who underwent selective thoracic fusion from February 2000 to January 2007 in our hospital, the patients were divided into 2 groups according to different instrumentation fashions： Group A was hook-screw-rod （hybrid） internal fixation type, Group B was screw-rod （all pedicle screws） internal fixation type, and the screws were used in every segment on the concave side of the thoracic curve. The parameters of the scoliosis were measured and the correction results were analyzed. Results Totally, 48 patients （7 males, 41 females） were included, with an average age of 14.4 years old and a mean follow-up time of 12.3 months. Thirty and 18 patients were assigned to group A and group B, respectively. The mean preoperative coronal Cobb angles of the thoracic curve were 48.8° and 47.4°, respectively. After surgery, they were corrected to 13.7° and 6.8°, respectively. At final follow-up, they were 17.0° and 9.5°, with an average correction rate of 64.6% and 79.0%, respectively, and the correction rate of group B was significantly higher than that of group A （P=0.003）. The mean preoperative coronal Cobb angles of the lumbar curve were 32.6° and 35.2°, respectively. After surgery, they were corrected to 8.6° and 8.3°, respectively. At final follow-up, they were 10.3° and 11.1°, with an average correction rate of 66.8% and 69.9%, respectively, and the correction rate of group B was significantly higher than that of group A （P=0.003）. The correction loss of the thoracic curve and lumbar curve in the 2 groups were 3.1° and 1.8°, 2.4° and 2.4°, respectively. No significant difference was noted （both P〉0.05）. The decompensation rate at final follow-up in these 2 groups were 4% （1/25） and 7.1% （1/14） respectively, with no significant difference （P〉0.05）.
文摘To define the criteria of posterior selective thoracic fusion in patients with adolescent idiopathic scoliosis. Methods By reviewing the medical records and roentgenograms of 17 patients with adolescent idiopathic scoliosis who un-derwent posterior selective thoracic fusion, the curve type, Cobb angle, apical vertebral rotation and translation, trunk shift, and thoracolumbar kyphosis were measured and analyzed. Results There were 17 King type Ⅱ patients (PUMC type: Ⅱb1 13, Ⅱc3 4). The coronal Cobb angle of thoracic curve be-fore and after operation were 56.9°and 21.6° respectively, the mean correction rate was 60.1%. The coronal Cobb angle of lumbar curve before and after operation were 34.8° and 12.1° respectively, and the mean spontaneous correction rate was 64.8%. At final follow-up, the coronal Cobb angle of thoracic and lumbar curve were 23.5° and 15.2° respectively, there were no significant changes in the coronal Cobb angle, apical vertebral translation and rotation compared with that after operation. One patient had 12° of thoracolumbar kyphosis after operation, no progression was noted at final follow-up. There was no trunk decompensation or deterioration of the lumbar curve. In this group, 3.9 levels were saved compared with fusing both the th-oracic and lumbar curves. Conclusion Posterior selective thoracic fusion can be safely and effectively performed in King type Ⅱ patients with a mo-derate and flexible lumbar curve, which can save more mobile segments and at the same time can maintain a good coronal and sagittal balance.
文摘针对多基地水下小目标分类识别问题,本文提出了一种基于核空间联合稀疏表示和指数平滑的多基地水下小目标识别方法 .对水下目标多角度散射信号提取6种典型的具有信息互补性和关联性的特征,提出一种随机森林(Random Forest,RF)和最小冗余最大相关(minimum Redundancy and Maximum Relevance,mRMR)相结合的特征选择方法(RF-mRMR),得出综合的特征重要性排序结果 .通过实验得出分类模型所需的最优特征子集,达到降低数据处理复杂度和提高目标分类结果的目的 .为了捕捉到数据中的高阶结构,在联合稀疏表示模型的基础上,使用核函数将线性不可分的特征数据映射到高维核特征空间.为了充分挖掘稀疏重构后包含在残差波段中的有用信息,使用指数平滑公式对具有一定意义的残差信息进行再利用,最后由核特征空间下的最小误差准则判定目标的类别.应用本文提出的方法对4类目标的海试数据进行识别,结果表明,相较于其他7种对比算法,本文提出的改进方法具有更好的分类性能,而且大多数情况下,本文提出的算法在双基地声呐模式下具有比单基地声呐更高的识别准确率和更低的虚警率.
文摘评审专家遴选是技术评审中的关键环节。鉴于颠覆性技术专家预判平台预判系统对时效性和智能型的要求,专家遴选对预判结果具有决定性影响。通过学术专长匹配和专业遴选来选择符合要求的专家,可以降低成本,提高推荐效率与准确度,完成颠覆性技术的预测任务。基于学术网络表示学习的方法既可以避免大量特征工程,又可以方便不同类型的特征进行融合。利用异质网络表示学习方法和标签排序的学术专长画像方法构建专家库,并使用融合专家综合评价指标特征的匹配方法对待预判的颠覆性技术和专家专长进行匹配,为专家遴选提供一份专业背景匹配的候选专家列表。这种方法在Academic Social Network数据集上进行模拟实验。实验结果表明,这种方法能提升项目评审专家学术专长匹配,在加入综合指标特征后,专家的综合指标特征能有效地反馈到实验结果中,从而提高评审系统的时效性和智能性。
文摘In the realm of low-level vision tasks,such as image deraining and dehazing,restoring images distorted by adverse weather conditions remains a significant challenge.The emergence of abundant computational resources has driven the dominance of deep Convolutional Neural Networks(CNNs),supplanting traditional methods reliant on prior knowledge.However,the evolution of CNN architectures has tended towards increasing complexity,utilizing intricate structures to enhance performance,often at the expense of computational efficiency.In response,we propose the Selective Kernel Dense Residual M-shaped Network(SKDRMNet),a flexible solution adept at balancing computational efficiency with network accuracy.A key innovation is the incorporation of an M-shaped hierarchical structure,derived from the U-Net framework as M-Network(M-Net),within which the Selective Kernel Dense Residual Module(SDRM)is introduced to reinforce multi-scale semantic feature maps.Our methodology employs two sampling techniques-bilinear and pixel unshuffled and utilizes a multi-scale feature fusion approach to distil more robust spatial feature map information.During the reconstruction phase,feature maps of varying resolutions are seamlessly integrated,and the extracted features are effectively merged using the Selective Kernel Fusion Module(SKFM).Empirical results demonstrate the comprehensive superiority of SKDRMNet across both synthetic and real rain and haze datasets.
