Variability in the performance of juvenile Chinook salmon is explained primarily by when and where they resided in estuarine habitats

Estuarine habitats provide rearing opportunities for the juvenile life stage of anadromous fishes. Because survival is positively correlated with juvenile performance, these estuarine habitats play an important role in population abundance and productivity. To provide information for the recovery of several depressed stocks of Chinook salmon in the Columbia River Basin, we sought to identify the factors that explain variability in performance. Using otolith‐derived estimates of juvenile somatic growth rate as an index of recent performance, we observed a negative nonlinear relationship between growth rate and day of year, and a decreasing and increasing trend of growth rate over the 8 years of this study and distance from the river mouth respectively. Using a generalised linear modelling approach, we found that variability in juvenile somatic growth rate was best explained by where and when individuals were collected, their body size, contaminant loads, stock of origin, and whether a fish was hatchery produced or unmarked. Lastly, we argue that a considerable improvement to the growth rate of juveniles in estuarine habitats is physiologically possible. The results of this 8‐year study provide a baseline of the performance of juvenile Chinook salmon to evaluate habitat restoration programs and to compare against future anthropogenic conditions.     

基于卷积神经网络的拖拉机工况识别

农机工况识别在细化农机作业状态和帮助掌握区域污染物排放趋势方面有着重要的研究价值。基于拖拉机不同运行状态下的行驶速度、发动机转速以及实时油耗等时间序列,首次提出将图像识别方法引入到拖拉机工况识别中的思路,并分别应用参数优化的支持向量机与卷积神经网络对实际作业拖拉机工况进行研究。结果表明:(1)基于参数优化的支持向量机可以较好地实现样本点的工况识别且识别准确度达到99.851 9%,但无法实现农机工况的连续性识别,同时无法对农机工况转换阶段进行有效识别。(2)以拖拉机运行速度与发动机转速等信息构建样本图像来描述农机工况变化的数据表达,并在此基础上应用卷积神经网络可以有效实现农机工况的连续性识别,且识别准确率可以达到93.3%。本研究在农机工况识别方面具有一定参考价值,并为后续农机不同工况下区域污染物排放研究提供技术支持。     

Identification of an H1N1 subtype of swine influenza virus and serological analysis

To investigate the epizootic of swine influenza virus(SIV), 60 nasal swabs were collected from a clinical cases of pig farm in Tai'an City, Shandong Province of China in April 2017. SIV was isolated by inoculating into 10-day-old Special Pathogen Free embryonated eggs and the whole genome was sequenced. An H1N1 subtype SIV was isolated and designated as A/swine/Shandong/TA04/2017(H1N1). Phylogenetic analysis showed that apart from the polymerase A(PA) fragment belonging to the 2009 pandemic H1N1 branch, seven genome segments belonged to avian-like H1N1 influenza virus lineage. The cleavage site sequence of the hemagglutinin(HA) protein was PSIQSR↓G, which is a typical molecular biological characteristic. Five potential N-glycosylation sites(N14, N26, N277, N484 and N543) were found in the HA gene. To further investigate the epidemiology of SIV in this farm, the 995 serum samples were assessed with EAH1N1 2009 pandemic H1N1 and H3 N2 antigens. The results showed that the total positive rate was 65.43%. The positive rates of single virus infection detected by EAH1N1, 2009 pdmH1N1 and H3 N2 for serum HI(Hemagglutination inhibition) were 48.35, 30.85 and 7.47%, respectively. The results showed that SIV in Shandong Province has been reassorted in some segments and the SIV-positive rate was high on the SIV outbreak farm. These data provide evidence of an epizootic of SIV.     

面向养殖水体分布差异的COD光谱法检测研究

面向养殖水体，传统光谱法对化学需氧量（Chemical Oxygen Demand，COD）检测模型构建的基础：源域（现有样本库）与目标域（检测地水体）间光谱数据独立同分布。但是当源域与目标域分布间存在差异时，由源域得到的低误差模型常在目标域上表现下滑。针对该问题，提出面向UV Vis光谱的域对抗训练网络（DAUVwpNet），将分布不同的源域和目标域数据映射至相同分布的特征空间中，使其在该空间的分布距离尽可能接近，从而在特征空间中对源域训练的目标函数也可以迁移至目标域上，以降低模型在目标域的误差。试验表明：面向同一批测试数据，DAUVwpNet的预测误差为0.78，要低于传统模型的预测误差（0.85）；DAUVwpNet预测值与实测值间相关系数为0.95，要高于传统模型的相关系数（0.89）。表明了该网络能够较好对齐两域特征空间数据分布，降低因分布差异带来的COD检测误差。     

“互联网+"背景下农村网络扶贫新思路的探讨

本文通过分析“互联网+”时代下网络扶贫的三种新模式，指出了政府、企业、农户三方力量 各自在网络扶贫中的定位和职责，进一步夯实网络扶贫基础，从而提高扶贫治理成效。     

人工神经网络在电力系统短期负荷预测中的应用

根据电力系统短期负荷变化的特性，提出BP模型在实际负荷预测应用中的方法和步骤．对BP网络结构、样本空间、收敛性等作了有针对性的研究．结果表明：多层神经网络应用于电力系统短期负荷预测是可行和有效的．其预报结果比传统的负荷预测方法更准确、经济、效果更好．     

论电子阅览室的知识导航与信息服务

本文立足于知识导航与信息服务，对网络环境下电子阅览室的服务内容、服务保障、目前面临的现状进行了论述，并提出了服务对策。     

基于模糊建模的混炼胶粘度测量

提出了一种在线测量混炼胶粘度的新方法．该方法以模糊建模技术为基础，综合考虑混炼过程各因素对胶料粘度的影响，建立起胶料粘度的在线测量模型．在模糊建模中，采用T-S模型描述胶料粘度变化的非线性过程，提出了一种基于相似性判别的模糊聚类算法以自动确定合适的聚类组数目，并用实数编码的遗传算法优化全局参数，从而获得了规则简化的、具有较高精度的模糊模型．根据此方法，设计了测量装置，并进行了现场试验．试验结果表明模糊模型输出与实验室测量值基本一致，平均误差较低且最大误差未超过1门尼．该方法较大地提高了橡胶混炼的生产效率，为粘度最优控制奠定了基础．     

岭西电网经济分析

本文对岭西电网的经济运行调整进行了分析、总结。并应用《岭西电网经济运行计算》系统的计算结果，提出了岭西电网的经济运行调整办法。