植物miR172家族成员进化与分子特性分析

为了解植物miR172家族成员的进化与分子特性,对mi Rbase数据库中37个物种的161个miR172前体序列和196个miR172成熟体序列进行进化规律分析,并对植物miR172家族的保守基序、二级结构和靶基因进行预测分析。结果表明:miR172家族成员分布的37个物种都是被子植物,被子植物很可能是miR172家族进化来源的祖先。进化分析表明,植物miR172家族成员序列相似性是其聚类的首要影响因素,其次才是物种差异的影响。植物miR172家族成员成熟体序列分析表明,5p臂上形成的成熟体序列特异性较大,3p臂上形成的成熟体序列保守性较高。二级结构分析发现,植物miR172家族成员具有典型的茎环二级结构,且茎序列的保守性较环序列高。植物miR172前体序列包含1个UNCG环。靶基因预测分析发现,同一物种不同miR172成员的靶基因可能不同;不同物种miR172的靶基因也可能不同,AP2或AP2-like出现频率最高,其次还有arginine decarboxylase 1、Pathogenesis-related、MYB84等靶基因,表明其靶基因功能的多样性。     

昆虫对双酰胺类杀虫剂抗性机制研究进展

双酰胺类杀虫剂是以昆虫鱼尼丁受体为作用靶标的新型杀虫剂,由于其作用机制独特,对多种鳞翅目害虫具有良好的防治效果而得到广泛应用。但已经有多种害虫的田间种群对该类药剂产生了抗性,甚至导致田间防治失败。本文在综述昆虫对双酰胺类杀虫剂抗性现状的基础上,重点总结了抗性机制方面的最新研究进展,并对今后的研究方向进行了展望,以期为进一步深入研究双酰胺类杀虫剂的抗性机制提供借鉴。     

新生代农民工职业生涯规划探讨

新生代农民工就业能力问题．对我国经济建设和社会发展意义重大？从新生代农民工职业生涯规划角度出发,阐述了职业生涯规划对新生代农民工事业成长的作用。并提出新生代农民工职业生涯规划须把握的几项重点工作。     

加快实现宁夏中部干旱带生态建设与草畜产业发展目标

宁夏中部干旱带干旱少雨,生态环境极为恶劣和脆弱,已成为宁夏经济发展与实施可持续发展战略的主要制约因素.分析中部干旱带的生态气候条件和资源禀赋,提出注重产业结构调整、坚持生态优先、加快培养特色林业产业和加快实施防沙治沙工程等生态恢复措施,旨在为中部干旱带生态建设与草畜产业实现"双赢"的发展目标提出发展思路和对策建议.     

甘蓝型油菜Bn19070的表达与同源基因At2G19070的amiRNAi研究

基于原芯片杂交结果,油菜杂合双显性雄性核不育系差异表达基因Bn19070与拟南芥At2G19070基因高度同源,在油菜可育株雄蕊中高量表达,不育株雄蕊中表达量极低。从雄性不育基因At2G19070入手,利用amiRNAi (人工微RNA干扰)技术对其两个RNA区段分别设计靶标,转化拟南芥。在多个转基因拟南芥植株和后代中普遍观察到小孢子数量减少、成熟花粉萎缩失去活力、不结实或者少结实的不育表型。两个靶标的干扰使转基因拟南芥出现了类似的表型,基因表达抑制率都在90%以上,干扰效果好,暗示amiRNAi技术在靶标选择上具有一定的灵活性。At2G19070基因的干扰对Bn19070的功能研究有借鉴作用。     

AdaBoost classifiers for pecan defect classification

One of the constraints in the adoption of machine vision inspection systems for food products is low classification accuracy. This study attempts to improve pecan defect classification accuracy by using machine learning classifiers: AdaBoost and support vector machine (SVM). X-ray images of good and defective pecans, 100 each, were segmented and features were extracted. Twenty classification runs were made to adjust parameters and 300 classification runs to compare classifiers. The Real AdaBoost classifier gave average classification accuracy of 92.2% for the Reverse water flow segmentation method and 92.3% for the Twice Otsu segmentation method. The Linear SVM classifier gave average classification accuracy of 90.1% for the Reverse water flow method and 92.7% for the Twice Otsu method. Computational time for the classifiers varied by two orders of magnitude: Bayesian (10⁻⁴ s), SVM (10⁻⁵ s), and AdaBoost (10⁻⁶ s). AdaBoost classifiers improved classification accuracy by 7% when Bayesian accuracy was poor (less than 89%). The AdaBoost classifiers also adapted well to data variability and segmentation methods. A minimalist AdaBoost classifier, more suitable for real time applications, using fewer features can be built. Overall, the selected AdaBoost classifiers improved classification accuracy, reduced classification time, and performed consistently better for pecan defect classification.     

Feature extraction and recognition technique for human pulse signals

In Chinese traditional medicine, the pulse signal plays an important role for diagnosis. To investigate the effective technique for identifying heroin druggers through the pulse signal, the feature extraction algorithm based on the biocepstrum and the third-order cepstrum entropy of the pulse signal is studied. On the basis of concise and rigorous discussion for the algorithm, the biocepstrum-based diagonal slice components are estimated for human pulse signals of 20 heroin druggers and 20 healthy normal subjects. The magnitude of the sample value of diagonal slice at m=n=1 and the third-order cepstrum entropy of magnitudes of sample values of the diagonal slice within a particular region are used as two feature parameters for every human pulse signal to form a feature vector. A classifier based on the criterion of squared Mahalanobis distance is successfully designed. Applying the designed classifier to 40 feature vectors, the correct identification rate reaches 87.5%. The research result shows that the method of the feature extraction and classifier design presented in is valuable for identifying the human pulse signals of heroin druggers.     

综合气候条件的变量施肥决策支持系统研究

实施精准农业是促进农业可持续发展的有效途径,而变量施肥是精准农业的核心.介绍了一种基于养分平衡法的变量施肥决策支持系统的功能及其组成,并将气候条件考虑到参数的确定中,初次利用气候条件确定其中一个参数-"目标产量",从而使施肥量更加合理.系统综合考虑了气候条件对目标产量的影响,比传统的以地定产法更贴近实际;以ASP.NE...     

基于改进Faster R-CNN的苹果叶部病害识别方法

针对苹果叶片图像中小尺度病斑和复杂背景带来的病斑目标难以精确定位和识别的问题,以苹果的斑点落叶病、黑星病、灰斑病、雪松锈病和花叶病为研究对象,提出一种基于改进Faster R-CNN的苹果叶片病害识别方法.先通过数据增广操作对训练集数据进行扩充以增强模型鲁棒性,再通过对增广训练集图像进行训练来得到一个可靠的病害识别模型...