应用事件分析法对林业企业发行绿色债券市场效应的评价

在系统梳理绿色债券相关理论基础上,以16个二级行业为研究对象,运用事件分析法分析林业企业上市公司发行绿色债券与股价相关性、林业企业发行绿色债券的市场价值,探索发行绿色债券的林业企业市场效应。结果表明:绿色债券融资对提升公司长短期的市场价值具有重大影响,绿色债券融资是经济实体发展绿色经济的表现,是符合经济趋势和其自身发展趋势的行为。林业企业对绿色债券的发行,持积极股价效应,提升公司市场价值;由于其项目投融资的绿色性,对市场效应有更好的显著性和持续性,对绿色债券的发行表现出积极市场效应,提升企业市场价值。依据绿色债券理论和实践,并结合林业企业自身的生态特性,从林业企业发行绿色债券的政策制度、融资优势、自身特征三个方面,在详细阐述林业企业发行绿色债券可行性基础上,提出林业企业推动绿色债券发行相关建议:构建林业企业绿色债券制度规范、增强林业企业绿色债券融资意识、提高林业企业绿色债券运营能力、加强林业企业绿色债券人才建设。     

Molecular characterization of Ascaridia galli from Bangladesh and development of a PCR method for distinguishing A. galli from Heterakis spp.

We analyzed the nuclear ribosomal internal transcribed spacer (ITS) 1 and ITS2 sequences for Bangladesh isolates of Ascaridia galli, and we determined that the sequences were unreliable as molecular markers for distinguishing A. galli from other Ascaridia species, because the sequences showed high identity with that of A. columbae. However, the ITS1 sequences were available for designing PCR primers distinguishable between Ascaridia galli and Heterakis spp. Bangladesh isolates of A. galli constituted a monophyletic clade along with other geographical isolates in the cytochrome c oxidase subunit I (COI) phylogenetic tree, however, we could not clarify the phylogenetic relationships between A. galli and other Ascaridia spp., because their available sequences in GenBank were very few. The developed PCR method using DNA from A. galli and Heterakis spp. eggs would enable differential diagnosis of the individual infections in the future.     

绿肥影响农田土传病害的研究进展

土传病害是制约我国农业可持续发展的因素之一。绿肥作为高效清洁的有机肥源,与主作物合理搭配,可有效降低主作物土传病害的发生和危害,是减少化学药剂使用的重要措施。因此,综述绿肥对土传病害的防控效果与机制,对于绿肥推广应用和土传病害绿色防控具有重要意义。绿肥影响作物土传病害的研究主要集中于土传真菌病害和线虫病害,且大多数研究表明,绿肥可通过增强主作物整体抗病水平,对病原菌的化感抑制作用和改善土壤理化性质,增加土壤微生物中拮抗菌多样性和丰富度等,显著降低主作物土传病害发病率和严重程度。然而,绿肥影响主作物病害的作用机制研究不够深入,绿肥-主作物搭配模式和绿肥调控主作物病害的社会经济学效益仍需探究。同时,加强绿肥-主作物病害一体化防控及绿肥与根际促生菌、生防菌等其他有机改良剂或与适当的化学防控措施之间协同作用的研究,是未来需要加强的研究方向。     

绵羊BMP15基因B2突变可视化检测技术的建立

骨形态发生蛋白15（bone morphogenetic protein 15,BMP15）基因突变对绵羊排卵率、产仔数以及繁殖力有很大影响,本研究旨在建立快速可视化检测BMP15基因B2突变的技术。将改良的扩增阻滞突变系统（amplification refractory mutation system,ARMS）与核酸染料SYBR Green Ⅰ结合,针对BMP15基因B2突变设计ARMS特异性引物,使引物下游3'端的最后一个碱基为A,并在下游引物3'端的第3位碱基处设计额外的错配,以提高引物的特异性;经ARMS PCR扩增后,向产物中加入SYBR Green Ⅰ,通过肉眼观察PCR管内的颜色变化来检测BMP15基因的B2突变。经测序发现所采集的样本均为野生型,因此,利用重叠延伸PCR构建BMP15基因B2突变型模板,测序结果显示BMP15基因B2突变型模板构建成功。ARMS PCR结果显示,ARMS特异性引物能够只扩增突变型模板,而不会扩增野生型模板,且扩增效果良好。ARMS PCR扩增后加入SYBR Green Ⅰ发现已知野生型模板与阴性对照一致,呈SYBR Green Ⅰ原始颜色橙黄色,而已知突变型模板呈亮绿色,且色差明显,肉眼可辨。用建立的可视化检测BMP15基因B2突变的技术检测50个小尾寒羊基因组DNA （随机向其中20个样本中加入构建的BMP15基因B2突变型模板）,将可视化检测的突变型样本编号与混合样本时记录的编号对比,结果表明该技术能够准确检测绵羊BMP15基因的B2突变,且准确率高达100%。将构建的BMP15基因B2突变型的模板进行梯度稀释,对本试验可视化检测体系的灵敏度进行检测,发现ARMS可视化检测技术的灵敏度达到0.006 ng/μL。因此,本研究建立的技术能够可视化地检测绵羊BMP15基因B2突变,且准确率高,有望为高繁殖力绵羊的选育提供技术支持。     

Green tea polyphenols supplementation alters immunometabolism and oxidative stress in dairy cows with hyperketonemia

Peripartal cows often experience negative energy balance, and are therefore prone to suffering from metabolic diseases such as hyperketonemia, which causes financial losses in dairy farms. This study aimed to investigate the effect of green tea polyphenol (GTP) supplementation during the periparturient period on production performance, oxidative stress and immunometabolism in dairy cows with hyperketonemia. One hundred Holstein cows were assigned to GTP (0.2 g/kg DM; n = 50) or control (without GTP; n = 50) group based on body weight, previous milk yield, and parity on d 15 before expected parturition. Subsequently, 10 cows with hyperketonemia were selected from each group, according to blood β-hydroxybutyric acid (BHBA) concentration between 1.2 and 2.9 mmol/L from 2 to 3 d postpartum. All cows were fed a close-up diet and a lactation diet with or without GTP supply from 15 d prepartum until 30 d postpartum. Milk and blood samples were obtained from 20 cows selected with hyperketonemia on 10, 20, and 30 d postpartum. Compared with control cows, greater milk yield and lower somatic cell count were observed in GTP cows. The GTP group had lower concentrations of BHBA, free fatty acids, cholesterol, triglyceride, reactive oxygen species, malondialdehyde, and hydrogen peroxide, greater concentrations of glucose, lower activities of aspartate aminotransferase, alanine aminotransferase, and glutamyl transpeptidase, alongside greater activities of superoxide dismutase, glutathione peroxidase, and total antioxidant capacity. Additionally, GTP supplementation up-regulated concentrations of interleukin-6 and interleukin-10, but down-regulated concentrations of tumor necrosis factor-α, interleukin-1β, interleukin-2, interleukin-8, and interferon-γ in plasma. Greater concentrations of plasma immunoglobulin G were also detected in the GTP group. Overall, the data suggested that GTP supplementation from 15 d prepartum to 30 d postpartum improved the milk yield and health status in cows with hyperketonemia during early lactation.     

THE REIMPROVEMENT FOR IMPULSE OF G. I. TAYLOR THEORY OF PLASTIC DEFORMATION IN IMPACT OF CYL1NDICAL PROJECTILES

In this paper the reimprovement for G. I. Taylor theory of plastic deformation in impact of cylindical projectiles is done. The impulse in the reimproved theory is G. I. Taylor' s 1/2, and 3/4 of G. I. Taylor' s improved theory. The analytical solution of the reimproved theory shows that it gives better agreement with exprimental results than those of the original Taylor' s theory and, the improved theory.     

高效数据库应用研究

效率是数据库应用开发过程中经常遇到的问题。为此，对数据库应用中影响效率的相关因素(如大事务、数据库连接等)进行分析，并针对实际电子商务数据库0RACE9I与JAVA应用中出现的问题，提出了解决方案。     

黄土高原半干旱区退耕还林对土壤微量元素的影响

为了探明黄土高原半干旱区退耕还林对土壤微量元素(Cu、Zn、Mn、Mo、Fe)含量的影响及其与影响因子间的关系,以甘肃省关川河流域退耕还林地和农地为研究对象,使用有效性评价、通径分析等方法研究土壤微量元素与土壤环境变量间的关系。结果表明:退耕后土壤微量元素含量随土层深度增加而减少,在表层土壤中呈一定的富集现象。退耕地Cu、Mn、Mo的有效性指数高于Zn、Fe,侧柏林地有效性综合指数高于云杉林地。偏相关分析显示,退耕还林区土壤微量元素有效态含量的主要影响因素为土壤有机质、全钾、全氮与土壤含水率;回归分析显示,土壤环境因子可解释38.1%~73.8%有关土壤微量元素含量的变异;通径分析表明,土壤全钾对土壤微量元素的直接作用最大,土壤全氮对微量元素的间接作用最大;决策分析表明,土壤全钾与土壤有机质是退耕还林区微量元素含量的决策变量,而土壤含水率是土壤微量元素的限制变量。     

扭振减振器对曲轴弯曲和纵向振动的影响研究

以一台多缸柴油机为例,采用结合有限元法(FEM)的多体系统仿真(MSS)方法,研究了扭转振动减振器振动对曲轴弯曲、纵向振动的影响;实验测量了有无扭振减振器时的曲轴自由端的弯曲和纵向振动,其与计算结果吻合得较好。     

基于优化Transformer网络的绿色目标果实高效检测模型

果园环境中,检测目标果实易受复杂背景、果实姿态和颜色等因素影响,为提高绿色目标果实检测的精度与效率,满足果园智能测产和自动化采摘要求,本研究针对不同光照环境和果实姿态,提出一种适于样本数量不足的绿色目标果实高效检测模型。该模型采用优化Transformer结构,首先借助卷积神经网络(Convolutional Neural Network,CNN)网络提取图像特征;然后输入编码-解码器生成一组目标果实预测框,最后通过前馈神经网络(Feed-forward Network,FFN)结构预测检测结果。在训练过程中,引入重采样法扩充样本数量,解决样本数量不足问题;引入迁移学习,加速网络收敛。分别制作苹果、柿子数据集用于模型训练。试验结果表明,经迁移学习后该模型训练效率大幅提高;与流行的目标检测模型相比,优化后的模型在检测绿色柿子与绿色苹果时,精度分别为93.27%和91.35%。该方法可为其他果蔬绿色目标检测提供理论借鉴。