Subjects: Biology >> Botany >> Applied botany submitted time 2019-01-30 Cooperative journals: 《广西植物》
Abstract：植物功能性状与环境之间的关系是功能性状研究的重点。海岛作为独特的生态系统，其植物功能性状必然和大陆存在差异。以平潭岛森林群落为研究对象，通过测定茎、叶 10个功能性状，以及地形和土壤 9 个环境因子，探讨植物功能性状之间的权衡关系，分析境因子对海岛植物功能性状的影响。研究结果表明：（1）比叶面积（SLA）与叶氮含量（LNC）、叶磷含量（LPC）呈正相关，与叶厚度（LT）、叶干物质（LDMC）、茎组织密度（STD）、叶碳含量（LCC）呈负相关；LDMC 与 LNC、茎氮含量（SNC）呈负相关；LT 与 STD 呈正相关，与 LNC 和 LPC 呈负相关；LPC 与 LNC、SNC 呈正相关；茎和叶 C、N 含量均呈正相关。（2）土壤有机质和 pH 是海岛植物功能性状的主要土壤影响因子。然而，由于土壤中磷含量的缺乏，LNC、LPC、SNC 均与土壤全磷呈正相关；LDMC、STD 与土壤有机质和土壤全氮含量呈正相关；SLA 随着土壤 pH 的增加而增加；（3）坡位和坡度是海岛植物功能性状主要的地形影响因子。SLA、茎磷含量（SPC）随着海拔上升而下降；STD、LDMC随着海拔和坡度增大而增大；LNC、LPC 阴坡大于阳坡。该研究明确了海岛植被的生态适应机制，旨在为海岛植被修复和重建提供参考依据。
Subjects: Biology >> Botany >> Applied botany submitted time 2019-01-30 Cooperative journals: 《广西植物》
Abstract：描述了发现自西藏南部的毛茛科毛茛属二新种：隆子毛茛 Ranunculus longziensis 与睫毛毛茛 R. densiciliatus W. T. Wang 在亲缘关系上甚为相近，与后者不同的是此新种的茎无毛，叶也无毛，基生叶不分裂，多具 5 条脉，茎生叶呈披针状条形；单根毛茛 R. uniradicatus与聂拉木毛茛 R. nyalamensis W. T. Wang 在体态上稍微相似，与后者不同的是此新种为一年生草本植物，只具一条须根，茎无毛，花瓣呈狭卵形，子房被短柔毛。
Subjects: Biology >> Botany >> Applied botany submitted time 2019-01-30 Cooperative journals: 《广西植物》
Abstract：为了提高基因表达效率从而利用叶绿体基因工程改良巨桉重要性状，该文以巨桉叶绿体基因组序列为材料，选取其中长于 300nt 且以 AUG 为起始密码子的 43 个非重复基因为研究对象，采用 CodonW1.4.2 软件分析巨桉叶绿体基因组的密码子使用偏好性。分析结果表明：第 3 位密码子的平均 GC 含量为 27.97%；ENC 的变化范围为 39.49~61.00，平均为 47.04；RSCU>1 的密码子有 31 个，其中 29 个以 A/U 结尾；中性分析显示 GC12 与 GC3 无显著相关，回归分析也未达到显著性水平；ENC-plot 分析发现大部分基因落在曲线上或附近；对应分析表明第一轴的贡献率为 17.68%，第二轴的贡献率为 11.49%，第三、四轴的贡献率分别为 8.00%和 5.76%，前四轴累计贡献率达 42.93%，第一轴与 GC、ENC、CAI 达到极显著相关；上述分析结果表明，巨桉叶绿体基因组的密码子偏好较弱，密码子第 3 位偏好以 A或 U 结尾；选择和突变在巨桉叶绿体基因组密码子偏好中起相对均衡的作用；最终确定UUG、CUU、GUU、UCC、UCA、ACA、UAU、UAA、CAU、AAU、AGA 和 GGA 12 个高频高表达密码子为最优密码子。该研究为转化叶绿体基因密码子优化从而提高表达效率改良巨桉目标性状奠定了坚实基础。
Subjects: Biology >> Botany >> Applied botany submitted time 2019-01-30 Cooperative journals: 《广西植物》
Abstract：为厘清芸香科（Rutaceae）九里香属（Murraya）中大叶九里香 M. kwangsiensis (C. C. Huang) C. C. Huang var. macrophylla C. C. Huang 与 其 原 变 种 广 西 九 里 香 M. kwangsiensis (C. C. Huang) C. C. Huang var. kwangsiensis 间的系统关系及其分类学地位，综合文献查阅、标本鉴定、野外实地调查、栽培观察及显微解剖等多种研究方法对九里香属植物数个种类进行分类学相关研究。结果发现：大叶九里香在叶片、花、果实等形态特征方面与广西九里香间的差异极大，故将其处理为一个独立的种，并提出新等级组合 Murraya macrophylla (C. C. Huang) F. J. Mou；首次对大叶九里香的形态特征及分布进行详尽描述；该物种的羽状复叶及小叶均为九里香属中最大者，表现更接近仅分布于越南的光叶九里香 M. glabra (Guillaumin) Swingle，但其较大的小叶、叶面叶脉下凹且叶片皱缩等特征表现使其明显不同于九里香属其他种类。大叶九里香是一个独立种而非广西九里香的变种，此关于大叶九里香分类地位的新观点有助于整个九里香属的系统发育关系重建及种间系统关系探索。
Subjects: Biology >> Botany >> Applied botany submitted time 2019-01-30 Cooperative journals: 《广西植物》
Abstract：介绍了自 2006 年以来我国省市级以及跨省区的 19 种地方植物志的出版信息，包括出版年代、页码、收载类群的科属种、线描图及彩图等信息，其中《昆仑植物志》为跨青海、甘肃、四川、新疆和西藏等五省区的地方植物志。
Subjects: Biology >> Botany >> Applied botany submitted time 2019-01-30 Cooperative journals: 《广西植物》
Abstract：采用气相色谱和比色法测定了十种不同来源马齿觅茎、叶中脂肪酸和草酸含量。结果表明，脂肪酸和草酸在10个不同类型马齿觅茎、叶中的含量均表现出一定的差异显著性。与叶片相比，茎中的脂肪酸含量相对较低。马齿觅茎、叶中以多元不饱和脂肪酸为主。测出两种多元不饱和脂肪酸，分别是亚麻酸(c}-3脂肪酸)和亚油酸(c}-6脂肪酸)。不同类型马齿觅叶片和茎中。-3和。_6脂肪酸分别占脂肪酸总量的62.71%^'70.91%和9.30%^ 13.31%，以及26.04%^36.02%和31.61%^43.19%0‘金湖’和‘南阳’马齿觅叶片和‘金湖’马齿觅茎中。-3脂肪酸含量显著高于其它类型。国产马齿觅类型，尤其是茎中的。6/} 3比例明显小于国外马齿觅类型。马齿觅茎中的草酸含量明显高于叶。除‘山东’、`Iran’和‘Pakistan’马齿觅茎中的草酸显著积累外，其它类型马齿觅茎中的草酸含量差异不显著。因此，马齿觅适宜早采收。‘金湖’和‘南阳’，尤其是‘金湖’类型的马齿觅是一种值得研究和推荐的马齿觅类型。
Subjects: Biology >> Botany >> Applied botany submitted time 2019-01-30 Cooperative journals: 《广西植物》
Abstract：杂交带是研究物种形成及进化的天然实验室，为探究棱果沙棘自然杂交带三种沙棘的生理生态适应性，在光照充足的 7 月中旬分别测定了该区域三种沙棘雌、雄株的光合特性及相关环境因子的日变化，以期为杂交带的维持机制提供理论依据。结果表明：同种沙棘雌、雄株间光合日变化规律基本一致；不同沙棘光合特性的日变化规律差异主要表现在：中国沙棘（Hippophae rhamnoides ssp. sinensis）Pn 日变化呈明显的双峰曲线，峰值出现在 PAR 和Ta 相对较高的 10:00 和 14:00，最高达到 19.53±5.35 μmol·m-2·s-1，棱果沙棘（Hippophae goniocarpa）和肋果沙棘（Hippophae neurocarpa ssp. neurocarpa）Pn 日变化均呈近双峰曲线，在 PAR 和 Ta 相对较低的 8:00 和 16:00 有较高的值，最高值分别为 13.43±3.43 和 15.27±2.43μmol·m-2·s-1；三种沙棘 WUE 与 Pn 的日变化规律一致，但中国沙棘具有最高的 WUE，达到6.72±0.95 μmol·mmol-1，棱果沙棘和肋果沙棘的 WUE 日变化最高分别为 4.03±1.08 和4.93±0.86 μmol·mmol-1；三种沙棘 Tr、Gs、Ci 和 Ls 的日变化规律相似，其中 Gs 均在 10:00后一致下降，在 12:00 左右均出现不同程度的气孔关闭的现象，这也是其发生光合午休的主要原因之一；杂交带三种沙棘光合特性日变化差异主要表现在中国沙棘和其它两种沙棘之间，而杂交种棱果沙棘与亲本种肋果沙棘的变化规律基本一致，其 Pn 与 WUE 可能受到了Ta、PAR 和 RH 等环境因子的影响。
Subjects: Biology >> Botany >> Applied botany submitted time 2019-01-30 Cooperative journals: 《广西植物》
Abstract： Based on the specimens collected from Yunnan Province, the lichen genus Schizotrema Mangold &Lumbsch is reported as new to China, with the species S. guadeloupense (Hale) Mangold & Lumbsch. Among Graphidaceae, the genus is characterized by its ascomata with concentrically layered margins composed of carbonized excipular remnants of older hymenia; the proper exciple is fused to indistinctly free, periphysoids are usually present, and the ascospores are transversely septate to muriform. The species also is new to Asia. Notes of other five species in the genus are given, also with ecology and distribution. World-wide key to species of Schizotrema be presence in the present paper. This study provides the basic data for the taxonomy of the family Graphidaceae.
Subjects: Psychology >> Management Psychology submitted time 2019-01-29
Abstract： " Collective psychological ownership has been studies as the latest issue in the field of psychology. Existing studies have not yet explored the mechanism of how collective psychological ownership affects team creativity. This study aims to address the above gaps by examining whether, when and how Collective psychological ownership has impacted on team creativity. Based on the Motived Information Processing in Group Model, this paper first empirically explores the mechanism of collective psychological ownership on team creativity. This study theorizes that collective psychological ownership could affect information elaboration, and in turn enhanced team creativity. At the same time, criteria for status promotion would moderated the positive relationship that collective psychological ownership affects team creativity through information elaboration. In order to test our hypothesized model, we invited 101 Knowledge–based team leaders and their 800 subordinates who came from 16 big companies located in Wuhan, Zhengzhou and Guangzhou to participate in this research survey. In the end, we got 91 leader–followers dyads. As for scale to measure criteria for status promotion, we learned from Liu et al. (2013) measurement method of how to measure criteria for status promotion. Also, we adopte two items which are Adapted from the scale of Pierce et al (2004) to measure collective psychological ownership ,as well as other measurements were well–established scales. Confirmatory factor analyses showed satisfactory model fit indices. Inter–rated agreement(Rwg) and intra–class correlation (ICC) value justified the aggregation of team information elaboration, Collective psychological ownership, Relationship conflict, Team Learning Behavior and Team Creativity. A hierarchical regression analysis method is adopted to test the hypothesized model. Results showed that collective psychology ownership has a positive impact on team creativity, and information elaboration mediates the relationship between collective psychological ownership and team creativity. Criteria for status promotion moderates the relationship between collective psychological ownership and information elaboration. However, criteria for status promotion does not significantly moderates the relationship between collective psychological ownership and team creativity through information elaboration. The present research makes some contributions to the Existing literature. First, by examining the positive effect of Collective psychological ownership on team creativity, this research proves the effectiveness of Collective psychological ownership beyond past literatures. Second, this study indicates the mediating role of information elaboration as well as its boundary conditions. For the practical implications, this research suggests that strengthening awareness of collective psychological ownership is conducive to the promotion of information elaboration and team creativity, also leaders should realize that criteria for status promotion will lead to different levels of competition, which impacts the relationship between collective psychological ownership and information elaboration. "
Subjects: Biology >> Virology submitted time 2019-01-29
Chen, Ze
Xu, Xiaofeng
Yang, Xiaojun
Dou, Weihao
Jin, Xiufeng
Ji, Haishuo
Liu, Guangyuan
Luo, Jianxun
Yin, Hong
Gao, Shan
Abstract： In this study, we aimed to detect viruses in hard ticks using the small RNA sequencing based method. A 235-bp DNA segment was detected in Dermacentor nuttalli (hard ticks) and D. silvarum (hard ticks) from sheep and bovine, respectively. The detected 235-bp segment had an identity of 99% to a 235-bp DNA segment of African Swine Fever Virus (ASFV) and contained three single nucleotide mutations (C38T, C76T and A108C). C38T, resulting in an single amino acid mutation G66D, suggests the existence of a new ASFV strain, which is different from all reported ASFV strains in NCBI GenBank database. These results also suggest that ASFV could have a wide range of hosts or vectors, beyond the well known Suidae family and soft ticks. Our findings pave the way toward further studies of ASFV transmission and development of prevention and control measures." " "
Peer Review Status:
Awaiting Review
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-28 Cooperative journals: 《计算机应用研究》
Abstract： The existing algorithms can't enhance the details of image edges and effectively control the enhancement degree of each scale information. Aiming at the problem, this paper proposed a multi-level decomposition Retinex low-light image enhancement algorithm. On the basis of Retinex decomposition model and bilateral filtering, the algorithm can obtain the multi-level reflection components and illumination component by setting different filtering parameters. Using the exponential function to enhance the multi-level reflection components, the algorithm can effectively enhance the expression ability of the image edge details. And using the S-type function to process the final luminance component, the algorithm can improve the overall brightness of the low-light image while suppressing the high-luminance area. By processing the color restoration function as post-processing, the algorithm can further avoid the problems of color deviation and distortion. The experimental results show that the proposed algorithm can improve the visual quality of low light images and is superior to the existing algorithms in terms of clarity, information entropy, and contrast.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-28 Cooperative journals: 《计算机应用研究》
Abstract： In recent years, open source software has frequently exposed high-risk vulnerabilities, posing a huge threat to the security of enterprise information system. Aiming at the open source software vulnerability, this paper proposed a software source code vulnerability detection method based on deep clustering algorithm. This method uses code graph model to construct the code attribute map and traverses the key code nodes to extract the application programming interfaces (API) sequence, then takes the key sequence as the center to cluster and calculates the outliers of the function in each clustering to generate a test report, matches the vulnerability library to detect vulnerabilities in the source code. The experimental results show that the proposed method can locate the key code segments of the vulnerability in open source software and detect the vulnerability.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-28 Cooperative journals: 《计算机应用研究》
Abstract： It proposed a new segmentation method of thyroid ultrasonic image based on T-Snake model. Firstly, a window-based anisotropic diffusion filter, combined with an adaptive weighted median filter, effectively eliminated speckle noise in thyroid ultrasonic images. Secondly, the method, based on the traditional T-Snake model and the adaptive region energy and expansion force, extracted the discontinuous boundary and weak boundary effectively, and realized the automatic segmentation of thyroid ultrasonic image. Finally, it set the model parameters and experimented with the clinical data. The results showed that the average relative difference is less than 5% and the average relative overlap is more than 91%. It verifies the feasibility of the proposed method.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-28 Cooperative journals: 《计算机应用研究》
Abstract： Pedestrian detection is a task which is necessary among all tasks leveraged in automatic driving domain. Traditional pedestrian detection algorithms took fully advantage of image data, unable to obtain depth of objects. To address aforementioned issue, this paper proposed a method based on raw LiDAR point cloud data. The proposed method combines traditional moving object detection in LiDAR data and point cloud recognition by deep learning, and is capable of perception and pedestrian detection without images, obtaining 3d location of pedestrian, therefore helping central control system make reasonable decisions. This method experimented in 3d object detection task of KITTI dataset, obtained 33.37% AP (Average Precision) on moderate cases. The results showed that proposed method performed better than other algorithm based on LiDAR data, which hence indicated the effectiveness of proposed method.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-28 Cooperative journals: 《计算机应用研究》
Abstract： Aimed at the problems of over- fitting of mapping function and insufficient convergence of loss function in convolution neural network image super- resolution algorithm, combined existing vision recognition algorithm and depth learning theory, this paper proposed an improvement on it. Firstly, the original SRCNN network increased layer number from 3 to 13 layers, and proposed a form of self- gated activation function Swish to replace the usual network model Sigmoi, ReLU and other activation functions, and fully utilized the advantages of Swish function to effectively avoid Over-fitting problems, better to learn and use the mapping relationship between low-resolution and high-resolution images to guide image reconstruction. Then introduced the Newton-Raphson method into the traditional network loss function, which further accelerates the convergence speed. Finally, experiments show that the improved network model can effectively improve the image definition, and improve the visual effect and objective parameter evaluation index.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-28 Cooperative journals: 《计算机应用研究》
Abstract： Due to the complexity and variety of glyphs, offline handwritten Chinese character recognition has always been a difficult problem of pattern recognition. The development of deep convolutional neural networks provides a direct and effective solution to this problem. This paper studied offline handwritten Chinese character recognition based on Inceptions neural network.It proposed an improved Inception structure, which took the advantages of simpler structure, easier network depth expansion and less training parameters. The method used the proposed structure to verifiy on dataset CISIA-HWDB1.1. The model achieved an average accuracy of 96.95%, by using stochastic gradient descent optimization algorithm. Experimental result shows that the improved Inception structure has better generalization performance and robustness in image classification, and can be easily extended to other applications.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-28 Cooperative journals: 《计算机应用研究》
Abstract： In order to apply neural network to urban LiDAR point clouds data classification, and to decrease large computation and long time consuming in the training process of large scale point clouds data, this paper improved the original Point-Net neural network by adding neighborhood characteristics of point clouds, and it proposed a new classification algorithm for point clouds based on the improved Point-Net. This algorithm compressed the original point clouds data volume through grid clustering and resampling, and then it extracted multi-scale neighborhood point clouds data and classified urban point clouds by using improved Point-Net. This paper verified the classification algorithm with data from different regions. The results show that the algorithm has good classification effect, high classification accuracy and less calculation. Therefore, the algorithm can realize effective classification of airborne LiDAR data in urban areas.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-28 Cooperative journals: 《计算机应用研究》
Abstract： This paper developed a method about voxel template construction for guiding the doctor to determine the type of damaged bone quickly, which could solve the problem that damaged bone have difficult in judging. Firstly, this method constructed the minimum bounding box based on the skeleton averaging point cloud model, and divided the box according the spatial resolution. Therefore it could generate the voxel template after traversing and judging the bounding box. Then, establishing the corresponding information between the damaged type and the voxel template generated a damaged type library. Finally, it mapped the target bone to the template, and the doctor could judge according to the damaged voxel area on the template to determine the type of damage. The experimental results show that the method can assist the doctor to directly and quickly determine the type of target bone damage, which is beneficial to the automatic discrimination research of the target bone in the later stage.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-28 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the problem that lightweight deep neural network MobileNet can reduce classification accuracy, this paper proposed an D-MobileNet (dilated convolution MobileNet) model based on local receptive field expansion by introducing dilated convolution kernel into a convolution layer of MobileNet model. The models consisted of three structures according to the location of the dilated convolution kernel. Without increasing the number of parameters, it could expand the local receptive field of the layer convolution kernel and improve the classification accuracy. This paper carried out the experiments on Caltech-101 database, Caltech-256 database and Uebingen animals with attributes database. The results show that the D-MobileNet model can achieve better classification accuracy than that of MobileNet, and can improve the classification accuracy by up to 2%.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-28 Cooperative journals: 《计算机应用研究》
Abstract： The existing mainstream methods use the pre-trained convolutional neural networks to extract image features and usually have the following limitations: a）Only using a single layer of pre-trained features to represent image; b）Inconsistency between the pre-trained task and the actual research task. These limitations result in that the existing methods of image-text matching cannot make full use of image features and is easily influenced by the noises. To solve the above limitations, this paper used multi-layer features from a pre-trained network and proposed a fusion algorithm of multi-level image features accordingly. Under the guidance of the image-text matching objective function, the proposed algorithm fused the multi-level pre-trained image features and reduced their dimensionality using a multi-layer perceptron to generate fusion features. It is able to make full use of pre-trained features and successfully reduce the influences of noises. The experimental results show that the proposed fusion algorithm makes better use of pre-trained image features and outperforms the methods using single-level features in the image-text matching task.
Hits
Hits
Downloads
Comment