基于ANP-GIS的长春市城市建设用地生态适宜性评价

基于城市建设用地的生态适宜性对建设用地资源进行合理有效开发利用是缓解城市化进程与土地资源有限性矛盾的根本途径。因此,在前人研究的基础上,提出了结合网络分析法（Analytic Network Process,ANP）与GIS的城市建设用地生态适宜性耦合评价模型,并结合长春市的自然、社会和经济特点对长春市城市建设用地生态适宜性进行案例研究,最终获得了可视化的长春市城市建设用地生态适宜性空间分布图（5个适宜度）。结果表明:对于长春市建设用地的选取最适宜的土地面积约为1 289.3 km²,适宜区域6 662.7 km²,较适宜区域9 461.4 km²,一般适宜区域2 848.2 km²,不适宜区域303.4 km²,而且长春市建设用地生态适宜性较高的地区（最适宜区域和适宜区域）分布在长春区域的腹地,处于长春市市区以及九台区、德惠市、农安县的交汇的区域,该地区自然、社会和经济各项指标的生态适宜性度均相对较高,表明长春市未来的城市发展以及城市建设的重点可以向生态适宜度较高的中部地区偏移。研究结果说明了ANP-GIS耦合模型的可靠性,同时也为长春市的建筑用地的选取和长春市的城市规划提供决策依据。     

麦麸超微粉碎对面团流变学特性与网络结构的影响

为阐明麦麸粒度影响全麦产品品质的内在机理,将不同粒度的麦麸（粗麦麸、细麦麸和超微麦麸）以20%的添加量添加于低筋和中筋面粉中。利用Mixolab测定面团的流变学特性,采用低场核磁（LF-NMR）分析面团中水分的存在状态,运用傅里叶红外（FT-IR）分析面筋蛋白二级结构和扫描电镜（SEM）观察面团面筋网络微观结构。结果表明,与粗麦麸和细麦麸相比,添加超微麦麸后,面团的吸水率、峰值黏度和淀粉热凝胶稳定性显著增加,面团形成时间减少;随着麦麸粒径的减小,面团T₂弛豫时间显著缩短,自由水含量逐渐降低;减小麦麸粒径,蛋白质二级结构中α-螺旋和β-折叠含量上升,β-转角和无规则卷曲含量下降;面团微观结构观察显示,随着麦麸粒径的减小,面筋网络的连续性和致密性得到改善。     

地下LoRa无线传感器网络的传输测试系统研究

【目的】以智能手机为核心,研制成本低、使用简单的面向LoRa地下无线数据传输的测试系统。【方法】该测试系统由安装了测试用的App智能手机和与之匹配的地下测试节点组成。利用该系统进行场景测试,测定影响土壤中LoRa无线数据传输效果的因素并讨论对应的数据传输方法。【结果】测试结果表明,该系统运行可靠、使用方便灵活,LoRa低功耗广域网技术亦可以较为可靠地满足土壤介质中的无线传感器网络数据传输需求。【结论】本系统可为未来地下LoRa无线传感器网络的工程应用提供相应的测试手段。     

Application of modified Deep Belief Network in Forecasting Cotton Diseases and Insect Pests

[Objective] The occurrence and development of cotton diseases and insect pests are mainly related to environmental information. Because this environmental information is various, complex and unstable, the study on the prediction methods of cotton diseases and insect pests is a certain challenge. This study aims to establish a forecasting model for the timely and accurate prediction of cotton diseases and insect pests. [Method] A forecasting model of cotton diseases and insect pests is proposed based on environmental information and a modified Deep Belief Network (DBN) that is constructed by a three-layer restricted Boltzmann machine (RBM) and a supervised back-propagation (BP) network. In the method, the RBM is used to transform the original environmental information vectors into a new feature space related to the diseases and pests; the BP network is trained to classify and forecast the features generated by the last RBM layer and two rules of dynamic learning and comparison and dispersion are adopted to accelerate the training process of RBM. The proposed model was validated on a dataset of cotton bollworm, aphids, spider, cotton Verticillium wilt, and Fusarium wilt in a recent six-year period. [Result] Compared with the traditional prediction models of cotton diseases and insect pests, the proposed model can deeply explore the extensive correlation between the occurrence of cotton diseases and pests and environmental information. The results show that the proposed model has a higher accuracy compared with the classical predictive models, and the average forecasting accuracy is above 83%. [Conclusion] The proposed method is an effective crop disease and pest forecasting method that can provide a technical support for preventing cotton disease and insect pests.     

基于转录组测序挖掘仿刺参“化皮病”相关基因

为了寻找仿刺参(Apostichopus japonicus)养殖期间的"化皮病"关键调控基因,并分析这些基因所参与的信号通路,对本课题组前期已获得的仿刺参"化皮"I期(早期)、II期(中期)和III期(后期)3个阶段的病变及其同一个体正常体壁组织之间的差异表达基因(differentially expressed genes,DEGs)进行进一步分析。主成分分析(principal component analysis,PCA)结果显示,"化皮"II期病变组织与正常组织之间的差异最小,"化皮"I期与III期表达关系比较接近,"化皮"II期是一个"转折期"。KEGG富集分析结果显示,补体与凝血级联(Complement and coagulation cascades)通路和细胞外基质受体(ECM-receptor interaction)通路在"化皮"3个阶段都显著改变。通过构建"化皮"过程关键差异表达基因调控网络,发现Ig GFc-binding protein(Fc GBP)基因和Tenascin(TN)蛋白家族基因在"化皮"不同阶段参与到发生显著变化的信号通路。q RT-PCR验证结果显示,5个DEGs在仿刺参"化皮"不同阶段表达趋势与RNA-Seq结果一致,皮尔逊相关系数r值为0.7714。"化皮"过程关键调控基因的筛选将为抗逆品种选育以及"化皮病"的防控提供科学依据。     

Is it a hindrance for an invasive aquatic species to spread across scattered habitat patches?

1. Despite their importance for aquatic biodiversity, ponds are among the most vulnerable freshwater habitats. Owing to their isolation in terrestrial environments, ponds are expected to be relatively well protected from biological invasions, but this depends on many factors. 2. The purpose of this study was to examine the influence of a range of variables (water quality, habitat, and landscape attributes) on the colonization of discrete ponds by a widespread aquatic invader, the red swamp crayfish Procambarus clarkii, which can disperse overland. 3. Investigations were conducted in two networks of ponds, each located in close proximity to a large invaded marsh. The two marshes under study differed in the length of time since the crayfish were introduced. 4. The proportions of colonized ponds and crayfish abundances were moderate in both networks, but higher in the network that had been invaded first. In both networks the distance to the marsh was the main predictor of pond colonization, considering similar energy costs to cross aquatic and terrestrial habitats for the recently invaded network, but assuming that dispersal was 25 times costlier across the terrestrial matrix than via streams for the earlier invaded network. Pond characteristics had no influence on crayfish occurrence in either network. Furthermore, predictions of pond invasion were lower for the recently invaded network. 5. The importance of the distance to the marsh indicates that natural dispersal was the main process of pond colonization by crayfish. Findings also suggested that overland dispersal was rare and costly. By contrast, streams were probably significant in facilitating crayfish dispersal. Differences between the two networks might arise from an invasion process still in progress in the recently invaded network. 6. From a management viewpoint, local actions are encouraged to prevent the spread of crayfish via streams. In addition, broader‐scale actions to mitigate other human disturbances would improve the outlook for pond biodiversity.     

基于GA–BP神经网络的番茄应力松弛参数的估计

为了实现机械手在抓取过程中对番茄应力松弛参数的快速准确估计,提出以BP神经网络为核心,遗传算法(GA)对BP神经网络初始权值和阈值进行优化的番茄应力松弛参数的估计方法:以番茄为样本,利用质构仪进行番茄应力松弛试验,并利用三元件广义Maxwell模型来表征番茄的应力松弛特性,通过拟合获取样本数据集;再以抓取力F、变形量D、作用时间t为输入,松弛特性参数E、Ee、η为输出构建BP神经网络模型,使用遗传算法对初始连接权值和阈值进行优化,获取最优参数的GA–BP神经网络估计模型;将该估计模型应用到机械手抓取过程中对番茄应力松弛参数的估计验证。结果表明:番茄应力松弛特性参数E、Ee和η的估计相对误差都在15%以内,且趋于稳定,该估计模型可对番茄应力松弛参数进行在线估计。     

基于改进VGG卷积神经网络的棉花病害识别模型

为实现自然条件下棉花病害图像准确分类,提出基于改进VGG-16卷积神经网络的病害识别模型。该模型在VGG-16网络模型基础上,优化全连接层层数,并用6标签SoftMax分类器替换原有VGG-16网络中的SoftMax分类器,优化了模型结构和参数,通过微型迁移学习共享预训练模型中卷积层与池化层的权值参数。从构建的棉花病害图像库中随机抽取病害图像样本作为训练集和测试集,用以测试该方法的性能。试验结果表明:该模型能有效提取出棉花病害叶片图像的多层特征图像,并通过Relu激活函数的处理更能凸显棉花病害的边缘信息与纹理信息,分辨率为512像素×512像素图像在样本训练与验证试验效果最好。在平均识别准确率方面,本研究模型较BP神经网络、支持向量机、AlexNET、GoogleNET、VGG-16NET效果最好,达到89.51%,实现对棉花的褐斑病、炭疽病、黄萎病、枯萎病、轮纹病、正常叶片的准确区分。该模型在棉花病害识别领域具备良好的分类性能,可实现自然条件下棉花病害的准确识别。     

Fucoxanthin,a Marine Carotenoid,Reverses Scopolamine-Induced Cognitive Impairments in Mice and Inhibits Acetylcholinesterase in Vitro

Fucoxanthin, a natural carotenoid abundant in edible brown seaweeds, has been shown to possess anti-cancer, anti-oxidant, anti-obesity and anti-diabetic effects. In this study, we report for the first time that fucoxanthin effectively protects against scopolamine-induced cognitive impairments in mice. In addition, fucoxanthin significantly reversed the scopolamine-induced increase of acetylcholinesterase (AChE) activity and decreased both choline acetyltransferase activity and brain-derived neurotrophic factor (BDNF) expression. Using an in vitro AChE activity assay, we discovered that fucoxanthin directly inhibits AChE with an IC₅₀ value of 81.2 μM. Molecular docking analysis suggests that fucoxanthin likely interacts with the peripheral anionic site within AChE, which is in accordance with enzymatic activity results showing that fucoxanthin inhibits AChE in a non-competitive manner. Based on our current findings, we anticipate that fucoxanthin might exhibit great therapeutic efficacy for the treatment of Alzheimer’s disease by acting on multiple targets, including inhibiting AChE and increasing BDNF expression.     

不同类型农户对耕地保护的认知差异及影响因素分析——基于山东省227户农户的问卷调查

以山东省227户农户调查数据为依据,通过分组对比,分析不同类型农户耕地保护政策认知差异及其影响因素.结果表明:(1)不同类型农户对耕地数量变化的认知存在差异,但农户总体认为近年来耕地数量有所减少,减少的耕地主要作为建设用地使用;(2)农户对耕地价值及相关耕地保护政策的认知水平普遍较低,且不同类型农户对同一政策以及同一类型农户对不同政策的认知情况存在显著差异;(3)不同类型农户对于耕地保护的意愿均较高;(4)农户对耕地保护的认知差异受到农户的年龄、受教育程度及年限、家庭收入、信息获取途径以及宣传等多重因素的影响.研究认为当农户明确自身的主体地位,且其自身对耕地保护政策的认知程度与耕地保护政策目标相一致时,农户对于耕地保护的自觉性与积极性便会得到充分激发,从而实现耕地资源持续高效利用.