Dough and bread made from high- and low-protein flours by vacuum mixing: Part 1: Gluten network formation

The effects of reduced headspace pressure on the development of gluten network in doughs made from both high-protein flour (HPF) and low-protein flour (LPF) were investigated. The effect of vacuum mixing was found to be dependent on both flour-type and mixing-time. A significant increase in dough extensibility was observed when the HPF dough was mixed under moderate vacuum of −0.04 MPa for 3 min as compared to the one mixed under atmospheric pressure for the same duration. This was attributed to the formation of a more extensive gluten network associated with an increased disulphide bond density and a significantly higher β-sheet to β-turn ratio. On the other hand, over-mixing was observed in the LPF dough that was mixed for 5 min under atmospheric pressure. Applying moderate vacuum of −0.04 MPa allowed the LPF dough to withstand longer mixing time, as indicated by its increased disulphide bond density and biaxial extensibility compared to the control dough mixed under atmospheric pressure. Results of this study suggest the potential of applying vacuum to reduce the mixing time required for high protein flour and to prevent the over-mixing of low protein flour.     

Turbid water induces refuge behaviour of a commercially important ayu: A field experiment for interstream movement using multiple artificial streams

Riverine systems are inherently dendritic in nature, and turbid water may not necessarily flow equally throughout an entire catchment. Tributaries have the potential to serve as refugia from temporarily turbid water in the main stem. As ayu (Plecoglossus altivelis) are one of the important species for the inland fisheries industry and recreational fishing, their behaviour in a branched river network is a primary concern. We released ayu with radio‐transmitting tags into two experimental streams that joined at a downstream pool. Turbid water was released into one of the streams, and we identified whether avoidance movement of ayu between the two experimental streams was triggered by flowing turbid water. The suspended solid concentration elevated rapidly after adding the turbid water and was maintained at more than 400 mg/L for 3 hr. Avoidance movement of ayu was triggered when the suspended solid concentration exceeded approximately 200 mg/L. Then, most ayu moved from the turbid stream to the nonturbid one, leading to a difference in ayu density between the two streams. Therefore, we demonstrated that turbid water induced interstream movement of a commercially important ayu as refuge behaviour, suggesting that river connectivity is important for the persistence of the ayu.     

Examining horizontal and vertical social ties to achieve social–ecological fit in an emerging marine reserve network

1. Most MPA networks are designed only with ecological processes in mind to increase their conservation utility. However, since MPA networks often involve large geographic areas, they also affect and involve multiple actors, institutions, and policy sectors.
2. A key challenge when establishing an effective MPA network is to align the ‘social system’ with the biophysical MPA network (the ‘ecological system’). This challenge is often denoted as ‘social–ecological fit’.
3. Facilitating collaborative social interactions among various actors and stakeholders (social connectivity) is equally as important as accomplishing ecological connectivity. New analytical approaches are required to effectively examine this ‘social’ dimension of fit.
4. An emerging marine reserve network in Jamaica and the recent invasion of Indo‐Pacific lionfish are used as a case study to: (1) examine the extent to which horizontal and vertical social ties bring local and national actors together to collaborate, coordinate, and share knowledge; and (2) assess the extent to which different attributes and features of such multilevel social networks may enhance or inhibit particular aspects of social–ecological fit.
5. Findings suggest that multilevel linkages have played the greatest role in relation to enhancing fit in the marine reserve network in the context of the recent lionfish invasion. However, the long‐term propensity of the multi‐actor and multilevel networks to enhance social–ecological fit is uncertain given the prevalence of weak social ties, lack of a culture of information sharing and collaboration, and limited financial resources.

     

基于多能互补的光伏木耳大棚智慧控制系统设计

【目的】针对光伏木耳大棚的智能化管理和现代设施农业资源高效利用问题,设计光伏农业大棚供能系统和改造传统大棚控制方式。【方法】设计一种以光伏发电为主的光、水、热、储微能源网络和物联网智慧控制系统,建立数学模型分析能源需求和供应,同时利用控制系统为木耳生产、管理提供远程客户端服务。【结果】微能源网络系统中,光伏发电量为13 654 (kW·h)/a,占年总发电量的92%,直接用于需求侧负荷;水轮机发电量为1 108 (kW·h)/a,占年总发电量的8%,用于无光环境下的系统补能;盈余电能为5 109 (kW·h)/a,占年总发电量的34.6%,用于相变储热和蓄电池储能,或者送入配电网。控制系统采集点温度正常值设置为20～25℃,预警值设置为15～32℃,采集点空气相对湿度正常值设置为90%～95%,预警值设置为80%～98%,测试过程中通风系统、供热装置和报警系统正常工作。【结论】通过不同状态下微能源网络系统的功率调配,能够提高光伏大棚能源利用率,同时自动调控大棚环境参数,满足了木耳大棚远程遥控和预警要求。     

基于深度学习的大豆生长期叶片缺素症状检测方法

为了检测作物叶片缺素,提出了一种基于神经网络的大豆叶片缺素视觉检测方法。在对大豆缺素叶片进行特征分析后,采用深度学习技术,利用Mask R-CNN模型对固定摄像头采集的叶片图像进行分割,以去除背景特征,并利用VGG16模型进行缺素分类。首先通过摄像头采集水培大豆叶片图像,对大豆叶片图像进行人工标记,建立大豆叶片图像分割任务的训练集和测试集,通过预训练确定模型的初始参数,并使用较低的学习率训练Mask RCNN模型,训练后的模型在测试集上对背景遮挡的大豆单叶片和多叶片分割的马修斯相关系数分别达到了0.847和0.788。通过预训练确定模型的初始参数,使用训练全连接层的方法训练VGG16模型,训练的模型在测试集上的分类准确率为89.42%。通过将特征明显的叶片归类为两类缺氮特征和4类缺磷特征,分析讨论了模型的不足之处。本文算法检测一幅100万像素的图像平均运行时间为0.8 s,且对复杂背景下大豆叶片缺素分类有较好的检测效果,可为农业自动化生产中植株缺素情况估计提供技术支持。     

高校科研合作网络及演化研究——以京津冀地区211及省部共建高校为例

[目的/意义]京津冀协同发展是党中央作出的重大战略决策,科研合作是京津冀协同创新发展的重要方面。[方法/过程]笔者基于CNKI检索京津冀地区211及省部共建的26所高校在2008年—2017年发表的合著论文数,运用定量分析、社会网络分析方法,借助Ucinet绘制科研合作网络图谱,从而探讨京津冀地区高校科研合作网络现状及演化规律。[结果/结论]研究结果发现,高校科研实力强劲是形成科研合作的基础,清华大学、北京大学、中国人民大学、北京师范大学、北京科技大学、北京航空航天大学和北京交通大学在科研合作网络中处于核心地位;地域聚集特性是影响科研合作关系强弱的主要因素;各类大学归属于不同的块模型,占据不同位置和角色,具有不同的结构功能和作用;京津冀地区高校科研合作经过10年间的发展,已经形成一个动态演化的网络。     

医学图像精细化分割方法研究

指出了深度学习方法在医学图像分割中取得较大的进展,但医学图像处理的复杂性使得全自动分割方法难以取得较好的分割效果。在卷积网络分割的基础上,结合应用场景使用适当的后处理手段来提升图像的分割效果是一种比较有临床意义的研究方法。主要研究了基于概率图的全连接条件随机场模型和基于用户交互的深度编辑网络,并分析总结了这两种方法的实现原理和各自优势,并对未来的研究工作进行了一些展望。     

工厂化水产养殖水质监测系统

工厂化水产养殖的密度高、风险大,养殖对象对pH、溶解氧、温度、氨氮、亚硝酸盐等水质参数的变化敏感,受影响严重,监测水质参数极为重要。本文针对工厂化水产养殖水质监测特点和需求,研发了工厂化水产养殖水质监测系统。分析研究pH、溶解氧、温度、亚硝酸盐等水质参数的阈值,设计水质监测数据无线采集节点和基于Zigbee的无线监测网络,建立水质监测系统软件平台。结果表明,该系统能够实现工厂化水产养殖水质实时监测,保证生产安全,提高水产养殖生产效率。     

基于卷积神经网络的小麦产量预估方法

小麦产量是评估农业生产力的重要指标之一,针对小麦产量人工预估困难,提出将卷积神经网络运用于小麦产量预估,为农业生产力的预估提供参考,指导农业生产管理决策。利用无人机分别在河南省新乡、漯河两地进行图片采集,并以之构建麦穗数据集,分为正样本(麦穗)和负样本(叶子和背景)。针对小麦常规的生理形态和生长环境,设计卷积神经网络识别模型,以图像金字塔构建多尺度滑动窗口,以非极大值抑制(NMS)去除重叠率较高的目标框,实现对单位面积内麦穗的计数,并利用随机采样的方式对大田麦穗进行单位面积图像采样,以采样图像中麦穗数量的平均值作为产量预估基准,进一步实现麦穗产量预估。随机抽取100幅不同小麦图片进行测试,与人工计数结果进行对比,准确率达到97.30%,漏检率为0.34%,误检率为2.36%,误差率为2.70%。试验结果表明,此方法能够克服环境中的多种噪声干扰,能够在不同光照条件下对麦穗进行计数和产量预估。     

基于BP神经网络模型的桂西资源富集区土地生态安全评价

【目的】科学客观地进行土地生态安全评价,提出可行有效的土地生态系统优化对策,为桂西资源富集区土地生态安全的维护及未来发展提供参考。【方法】基于BP神经网络方法构建土地生态安全评价模型,通过分析影响土地生态系统的自然、经济、社会3个主导因素,建立桂西资源富集区土地生态安全评价指标系统,对2008—2017年桂西资源富集区土地生态安全程度进行评价。【结果】桂西资源富集区2008—2017年土地生态安全程度均属于一般安全状态,且由一般安全状态逐步接近较安全状态;其中百色市、河池市、崇左市分别在不同因素下的土地生态安全程度存在较大差异,且差异在逐年增大。【结论】为了避免桂西资源富集区土地生态安全系统存在发展失衡的倾向,建议桂西资源富集区政府优化营商环境,坚持"绿水青山就是金山银山";制定合理的耕地保护政策,缓解人地矛盾关系。