中国海南果实蝇属三新种记述(双翅目,实蝇科,寡鬃实蝇亚科)(英文)

系2005～2010年海南省实蝇监测和野外调查的部分研究结果,记述实蝇科Tephritidae果实蝇属Bactrocera Macquart 3新种,并附其形态特征图。模式标本保存于海南出入境检验检疫局热带植物隔离检疫中心昆虫标本馆。     

番石榴果实蝇与桃实蝇的形态区别

介绍我国口岸截获频率较高的2种形态相似的实蝇---番石榴果实蝇Bactrocera (Bactrocera) correcta(Bezzi) 和桃实蝇Bactrocera zonata Saunders的鉴别特征。两者主要区别在于桃实蝇具1对卵圆形黑色颜斑,中胸背板红褐色。     

中国果实蝇属一新种记述(双翅目,实蝇科,寡鬃实蝇亚科)(英文)

记述采自中国云南的果实蝇属(双翅目,实蝇科)1新种,陈氏果实蝇Bactrocera (Bactrocera) cheni sp.nov.,模式标本保存于福建农林大学益虫研究所。     

广东南岭国家级自然保护区实蝇多样性研究

2011年对南岭国家级自然保护区实蝇科昆虫进行了诱集采集,得到实蝇科昆虫标本1640号,隶属于2亚科11属19种。不同海拔高度实蝇科昆虫群落组成不同,在6个采样地中海拔最高点实蝇科昆虫种类和数量发生都较少。不同时间实蝇科群落组成及数量也呈现一定的差异。调查发现,7、8月份诱集的数量最多,分别为525头和537头。不同采样地和不同时间实蝇科昆虫的总体优势度指数（D）、多样性指数（H′）、物种丰富度指数（E）、均匀度指数（J）随时间的变化趋势基本一致。     

中国果实蝇属一新纪录种(双翅目,实蝇科)(英文)

记述中国果实蝇属(双翅目,实蝇科)1新纪录种:泰国果实蝇Bactrocera thailandica Drew & Hancock,1994(图1～7).研究标本保存于云南大学生命科学学院.     

中国突蜣蝇属一新种（双翅目：蜣蝇科）

记述中国蜣蝇科1新记录属:突蜣蝇属Tylotrypes及该属1新种:长毛突蜣蝇Tylotrypes longipilosasp.nov.。新种的鉴别特征为:体棕色,头浅棕色不具斑,胸深黄色具大量浅色毛,翅半透明具不规则灰色阴影,腹末第9背板宽阔,尾须短圆。     

离腹寡毛果实蝇性别决定基因transformer 2及其在昆虫中的进化

对离腹寡毛果实蝇性别决定基因transformer 2(tra-2)进行多角度的进化分析,为研究离腹寡毛果实蝇性别决定分子机制奠定基础。通过PCR结合RACE技术克隆瓜实蝇Bactrocera cucurbitae同源transformer 2基因的c DNA全长和内含子序列,并对该基因进行序列和进化分析。克隆得到瓜实蝇tra-2基因c DNA全长1467 bp,开放读码框753 bp,编码250个氨基酸残基,Gen Bank登录号为KR056217。瓜实蝇tra-2基因与其他6种离腹寡毛果实蝇的基因结构相似,均包含8个外显子和7个内含子。7种离腹寡毛果实蝇与实蝇科的地中海实蝇和按实蝇、蝇科的家蝇和丽蝇科的铜绿蝇为单一起源,而果蝇Tra-2表现出明显的分异。分子进化分析结果表明tra-2基因核苷酸变异主要来源于同义变异,接受净化选择压力。本研究明确了瓜实蝇tra-2的c DNA和基因组DNA结构特征,离腹寡毛果实蝇tra-2蛋白高度保守,主要接受净化选择压力。     

基于深度学习的蝴蝶科级标本图像自动识别

【目的】本研究旨在探讨深度学习模型在蝴蝶科级标本图像自动识别中的可行性和泛化能力。【方法】为了提高识别模型的鲁棒性和泛化能力,将锤角亚目中6个科1 117种蝴蝶标本图像通过水平翻转、增加图像对比度与亮度以及添加噪声的方式增强图像数据集。在Caffe框架下,利用迁移学习方法,首先使用Image Net数据集中的图像训练Caffe Net模型,迭代31万次后得到初始化的网络权值;然后利用蝴蝶图像训练已预训练好的Caffe Net模型,通过参数微调,获得一个蝴蝶科级标本图像自动识别的卷积神经网络模型。为了比较深度学习和传统模式识别两种方法建立的模型的泛化能力,对相同训练样本提取全局特征和局部特征,训练支持向量机(support vector machine,SVM)分类器。所有的模型在与训练样本图像来源一致和不一致的两个测试样本集上进行测试。【结果】当测试样本与训练样本来源一致,均为蝴蝶标本图像时,基于Caffe Net的蝴蝶识别模型对6个科的蝴蝶识别准确率平均达到95.8%,基于Gabor的SVM分类器也获得了94.8%的识别率。当测试样本与训练样本来源不一致,为自然环境下拍摄的蝴蝶图像时,两种方法获得的识别率均下降,但Caffe Net模型对蝴蝶自然图像的平均识别率仍能达到65.6%,而基于Gabor的SVM分类器的识别率仅为38.9%。【结论】利用Caffe Net模型进行蝴蝶科级标本图像识别是可行的,相比较传统模式识别方法,基于深度学习的蝴蝶识别模型具有更好的泛化能力。     

甘肃南部头蝇科一新种（双翅目）

本文描述了采自甘肃文县头蝇科,肾头蝇属（ＮｅｐｈｒｏｃｅｒｕｓＺｅｔ．）一新种,其主要特征：中胸背板两侧各具一耳状薄片突起物,后足转节后腹面具５枚短且粗的黑刺,第１腹节背板具“Ｙ”字形斑,第２及第３腹节背板具倒吊钟状斑     

云南边境地区果实蝇属种类DNA条形码鉴定

【目的】果实蝇属Bactrocera中有国际上重要的检疫性害虫, 基于形态的物种鉴定有一定的局限性。另一方面, 云南边境地区为东南亚地区实蝇入侵我国的重要通道。因此, 对该地区实蝇分子鉴定方法的研究对于该属物种的快速准确鉴定具有重要意义。本研究旨在探讨DNA条形码技术在果实蝇属物种鉴定中的有效性。【方法】使用线粒体基因COI和COII序列的通用引物对果实蝇属20个物种60份样品进行PCR扩增、测序和序列分析; 采取距离方法和建树方法评价2种序列的鉴别能力。【结果】COI和COII序列平均长度分别为682 bp和339 bp, 种内和种间遗传差异较大, 有较明显的遗传距离间隔（barcoding gap）, 鉴定成功率分别为91.2%和90.7%。另外, 分子系统树表明华实蝇亚属Sinodacus不是单系群。【结论】COI和COII序列均能够将绝大多数果实蝇属物种进行准确鉴别, 应用COI或COII序列进行果实蝇属物种鉴定具有一定的可行性。     

染色体易位重组位点的自动识别方法研究

染色体易位重组位点的识别对很多染色体遗传性疾病的诊断有着重要的意义。本文基于实际诊断中采集到的24类染色体数据和9号正常与异常染色体数据,构建了一套自动识别染色体易位重组位点的模型和方法。首先,对染色体图像进行预处理,得到了方向梯度直方图特征(HOG)和局部二值模式特征(LBP),构建了基于纹理特征的染色体24分类多通道网络模型,分类准确率达到了95.99%;再与ResNet18模型(分类准确率95.86%)进行模型融合,最终分类准确率达到97.08%。其次,将染色体密度谱作为正常和异常染色体的分类特征,采用投票的方法集成支持向量机、随机森林和XGBoost模型,构建了正常和异常染色体的集成分类器,正常和异常9号染色体的分类准确率达到了100%。最后,对于易位的异常染色体,我们提出了基于动态时间规划(DTW)的易位重组位点自动识别算法,在异常染色体的密度谱曲线上找到了重组位点,并映射至染色体G显带模式图,得到标准诊断结果,通过与临床专家的诊断结果进行比较说明了自动识别结果的有效性。本文设计的一套自动识别染色体易位重组位点的模型方法对临床辅助诊断有很大的帮助,有望完善成为一套软件系统应用于临床诊断,提升相关疾病的诊断效率和准确率。     

A Novel Method of Automatic Plant Species Identification Using Sparse Representation of Leaf Tooth Features

Automatic species identification has many advantages over traditional species identification. Currently, most plant automatic identification methods focus on the features of leaf shape, venation and texture, which are promising for the identification of some plant species. However, leaf tooth, a feature commonly used in traditional species identification, is ignored. In this paper, a novel automatic species identification method using sparse representation of leaf tooth features is proposed. In this method, image corners are detected first, and the abnormal image corner is removed by the PauTa criteria. Next, the top and bottom leaf tooth edges are discriminated to effectively correspond to the extracted image corners; then, four leaf tooth features (Leaf-num, Leaf-rate, Leaf-sharpness and Leaf-obliqueness) are extracted and concatenated into a feature vector. Finally, a sparse representation-based classifier is used to identify a plant species sample. Tests on a real-world leaf image dataset show that our proposed method is feasible for species identification.     

基于树木年轮径切特征的卷积神经网络树种识别

卷积神经网络可以通过树木年轮样本构造特征图像实现物种识别的自动化。本研究通过建立树木年轮样本构造特征图像集,选用LeNet、AlexNet、GoogLeNet和VGGNet 4个卷积神经网络模型,实现基于树木年轮横切面的计算机自动化树种精准识别,进而确定各模型的树种识别准确率,明晰不同树种在自动识别中的混淆情况,探测不同模型识别结果的差异。结果表明: 本研究训练的用于树种识别的卷积神经网络模型具有较好的可信度;4个模型中GoogLeNet模型树种识别准确率最高,为96.7%,LeNet模型识别准确率最低(66.4%);不同模型对于所选树种的识别结果具有一致性,表现为对蒙古栎识别准确率最高(AlexNet模型识别率达到100%),对臭冷杉的识别准确率最低。本研究中也存在类似结构树种的识别混淆情况。模型在科和属水平的识别准确率高于种水平;阔叶树种因其显著的结构差异容易区分,阔叶树树种的识别准确率高于针叶树。总体上,通过卷积神经网络,探测了树木年轮特征的深层信息,达到树种的精准识别,提供了一种快速便捷的自动树种初筛鉴定方法。     

The Correlation Between Texture Features and Fibrous Cap Thickness of Lipid-Rich Atheroma Based on Optical Coherence Tomography Imaging

Fibrous cap thickness (FCT) is seen as critical to plaque vulnerability. Therefore, the development of automatic algorithms for the quantification of FCT is for estimating cardiovascular risk of patients. Intravascular optical coherence tomography (IVOCT) is currently the only in vivo imaging modality with which FCT, the critical component of plaque vulnerability, can be assessed accurately. This study was aimed to discussion the correlation between the texture features of OCT images and the FCT in lipid-rich atheroma. Methods: Firstly, a full automatic segmentation algorithm based on unsupervised fuzzy c means (FCM) clustering with geometric constrains was developed to segment the ROIs of IVOCT images. Then, 32 features, which are associated with the structural and biochemical changes of tissue, were carried out to describe the properties of ROIs. The FCT in grayscale IVOCT images were manually measured by two independent observers. In order to analysis the correlation between IVOCT image features and manual FCT measurements, linear regression approach was performed. Results: Inter-observer agreement of the twice manual FCT measurements was excellent with an intraclass correlation coefficient (ICC) of 0.99. The correlation coefficient between each individual feature set and mean FCT of OCT images were 0.68 for FOS, 0.80 for GLCM, 0.74 for NGTDM, 0.72 for FD, 0.62 for IM and 0.58 for SP. The fusion image features of automatic segmented ROIs and FCT measurements improved the results significantly with a high correlation coefficient (r= 0.91, p<0.001). Conclusion The OCT images features demonstrated the perfect performances and could be used for automatic qualitative analysis and the identification of high-risk plaques instead manual FCT measurements.     

Lumbar muscle electromyographic dynamic topography during flexion-extension

The objective of this study is to introduce dynamic topography of surface electromyography (SEMG) to visualize lumbar muscle myoelectric activity and provides a new view to analyze muscle activity in vivo. A total of 20 healthy male subjects and 15 males LBP were enrolled. An electrode-array was applied to the lumbar region to collect SEMG. The root mean square (RMS) value was calculated for each channel, and then a 160×120 matrix was constructed using a linear cubic spline interpolation of each scan to create a 2-D color topographic image. Along a definite interval of action, a series of RMS topography matrices was concatenated as a function of position and time, to form a dynamic topographical video of lumbar muscle activity. Relative area (RA), relative width (RW), relative height (RH) and Width-to-Height Ratio (W/H) were chosen as the four quantitative parameters in measuring topographic features. Normal RMS dynamic topography was found to have a consistent, symmetric pattern with a high intensity area in the paraspinal area. LBP patients had a different RMS dynamic topography, with an asymmetric, broad, or disorganized distribution. Quantitative SEMG features were found significantly different between normal control and LBP. After physiotherapy rehabilitation, the dynamic topography images of LBP tended towards the normal pattern.There are obvious differences in lumbar muscle coordination between healthy subjects and LBP patients. The dynamic topography allows the continuous visualization of the distribution of surface EMG signals and the coordination of muscular contractions.     

昆虫图像分割方法及其应用

昆虫图像自动鉴定是一种快速鉴定昆虫的方法,图像分割则是其中关键步骤。通过搜集和整理国内外近年来针对昆虫图像的分割方法和研究,发现对昆虫图像分割的研究日趋增多。随着计算机图像技术的发展,昆虫图像分割方法吸收了许多图像分割领域中新兴的方法, 诸如采用水平集、边缘流以及结合形状、纹理、色彩等多种要素的智能分割(如JSEG方法)等。虽然大量的图像分割方法被引入到昆虫图像研究中,但是目前分割技术依然是阻碍昆虫图像广泛应用的关键。本文经过总结和分析,发现目前昆虫图像分割研究的往往在各自的测试集上有良好表现, 但是缺乏统一的评价标准, 因此很多方法在昆虫图像中应用难以推广。针对研究中的存在的这些问题,需建立良好的昆虫图像分割评价体系,本文建议通过建立统一的昆虫图像库以及对昆虫图像分割的评价方法深入研究,并且这些工作是当前昆虫图像分割研究亟待完善任务。     

Isolation and sequence analysis of promoter DNA fragments of the Luciferin-binding protein gene inGonyaulax polyedra

To understand the unusual features of the genes and genomes fromGonyaulax polyedra, we isolated the promoter portions of the luciferin binding protein (LBP) gene, using IPCR methods, and characterized their sequences. Five LBP genomic clones were classified into a group of genes from the LBPα family, based on the sequence homology of the coding portion of the LBP gene. They were subdivided into two groups. Southern analysis implied that the promoter region is conserved well in most LBP genes. The comparison of the promoter regions from the LBP and luciferase genes showed that, although some portions of their sequences were well conserved, these two genes did not share common features of promoter region, as is normally found in eukaryotes or prokaryotes.     

Multiview Locally Linear Embedding for Effective Medical Image Retrieval

Content-based medical image retrieval continues to gain attention for its potential to assist radiological image interpretation and decision making. Many approaches have been proposed to improve the performance of medical image retrieval system, among which visual features such as SIFT, LBP, and intensity histogram play a critical role. Typically, these features are concatenated into a long vector to represent medical images, and thus traditional dimension reduction techniques such as locally linear embedding (LLE), principal component analysis (PCA), or laplacian eigenmaps (LE) can be employed to reduce the “curse of dimensionality”. Though these approaches show promising performance for medical image retrieval, the feature-concatenating method ignores the fact that different features have distinct physical meanings. In this paper, we propose a new method called multiview locally linear embedding (MLLE) for medical image retrieval. Following the patch alignment framework, MLLE preserves the geometric structure of the local patch in each feature space according to the LLE criterion. To explore complementary properties among a range of features, MLLE assigns different weights to local patches from different feature spaces. Finally, MLLE employs global coordinate alignment and alternating optimization techniques to learn a smooth low-dimensional embedding from different features. To justify the effectiveness of MLLE for medical image retrieval, we compare it with conventional spectral embedding methods. We conduct experiments on a subset of the IRMA medical image data set. Evaluation results show that MLLE outperforms state-of-the-art dimension reduction methods.     

Identification and immunolocalization of the laminin binding protein from embryonic avian corneal epithelial cells

We report the identification of a 65-kDa laminin-binding protein (LBP) on the basal cell surface of embryonic corneal epithelium in chicken. The 65-kDa LBP was isolated by affinity chromatography with laminin-Sepharose. When reconstituted with lipid vesicles, it demonstrated specific binding for laminin. We produced monoclonal antibodies (MAbs) against 65-k Da LBP; these MAbs immunohistochemically localized to the basal epithelial cell surface. One MAb interfered with the binding of laminin to isolated epithelia and purified 65-k Da LBP. It appears that we have identified, at least in part, a cell-surface binding site for laminin. This site would provide the important link between the extracellular laminin and the intracellular cytoskeleton, and potentially the metabolic machinery of the corneal epithelial cell.     

Individuals with non-specific low back pain use a trunk stiffening strategy to maintain upright posture

There is increasing evidence that individuals with non-specific low back pain (LBP) have altered movement coordination. However, the relationship of this neuromotor impairment to recurrent pain episodes is unknown. To assess coordination while minimizing the confounding influences of pain we characterized automatic postural responses to multi-directional support surface translations in individuals with a history of LBP who were not in an active episode of their pain. Twenty subjects with and 21 subjects without non-specific LBP stood on a platform that was translated unexpectedly in 12 directions. Net joint torques of the ankles, knees, hips, and trunk in the frontal and sagittal planes as well as surface electromyographs of 12 lower leg and trunk muscles were compared across perturbation directions to determine if individuals with LBP responded using a trunk stiffening strategy. Individuals with LBP demonstrated reduced peak trunk torques, and enhanced activation of the trunk and ankle muscle responses following perturbations. These results suggest that individuals with LBP use a strategy of trunk stiffening achieved through co-activation of trunk musculature, aided by enhanced distal responses, to respond to unexpected support surface perturbations. Notably, these neuromotor alterations persisted between active pain periods and could represent either movement patterns that have developed in response to pain or could reflect underlying impairments that may contribute to recurrent episodes of LBP.