Experimental research on combined effect of obstacle and local spraying water fog on hydrogen/air premixed explosion

In order to reveal the mechanism of water fog explosion suppression and research the combined effect of water fog and obstacle on hydrogen/air deflagration, multiple sets of experiments were set up. The results show that the instability of thermal diffusion under lean combustion conditions is the main influencing factor of hydrogen/air flame surface instability, and the existence of water fog will aggravate the hydrogen/air flame surface instability. When obstacle is not considered, 8 μm, 15 μm, 30 μm water fog can significantly reduce the flame velocity and explosion overpressure of hydrogen/air, 45 μm fine water fog plays the opposite role. When considering the relative position of the water fog release position and the obstacle, the 8 μm, 15 μm, 30 μm water fog has almost no suppression effect when released near the obstacle, but a significant suppression effect occur, when using the 45 μm water fog. In the field of theoretical research, the research results not only provide an experimental basis for the fine water fog to reduce the consequences of hydrogen explosion accidents, and the optimal diameter range used by the water fog, but also provide experimental reference for the numerical simulation of hydrogen/air explosion suppression in semi-open space, and promote the development of hydrogen explosion suppression theory. In terms of engineering applications, this study can provide a theoretical basis for the layout of fire fighting equipment in the engine room of nuclear power plants or hydrogen-powered ships.     

WSN低功耗低时延路径式协同计算方法

针对云计算应用于无线传感器网络(Wireless Sensor Network,WSN)时延敏感型业务时存在的高传输时延问题,提出了一种WSN低功耗低时延路径式协同计算方法。该方法基于一种云雾网络架构开展研究,该架构利用汇聚节点组成雾计算层;在数据传输过程中基于雾计算层的计算能力分步骤完成任务计算,降低任务处理时延;由于汇聚节点计算能力较弱,时延降低将导致能耗增加,WSN工作寿命减短,为此提出能耗约束下的任务映射策略,并利用离散二进制粒子群优化(Binary Particle Swarm Optimization,BPSO)算法解决能耗约束下的时延优化问题。仿真结果表明,在相同的能耗约束下,对比其他算法,基于BPSO算法得出的映射方案能有效降低业务处理时延,满足时延敏感型业务的需求。     

仿生雾水收集材料：从基础研究到性能提升策略

由于水资源污染、淡水资源日益匮乏，水危机已经严重影响到人们的日常生活。从晨雾中捕获水气则可以缓解干旱地区的缺水问题。受纳米布沙漠甲虫、仙人掌、蜘蛛丝等动植物自发捕集雾水的启发，构建特殊润湿性的仿生雾水收集材料备受关注。详细总结了仿生雾水收集材料的最新研究进展，讨论了仿生集水材料的设计和制备方法，并从雾水收集的四大仿生策略出发，介绍了提升雾水收集效率的设计方案。在此基础上，分析了当前仿生雾水收集过程存在的问题，展望了此类材料未来的发展趋势和方向。     

秦皇岛海域食用贝类重金属污染情况分析

为了解秦皇岛海域食用贝类中重金属的污染水平及其存在的健康风险。采用电感耦合等离子体发射质谱法(ICP-MS)和原子荧光光谱法测定了该地区15种常见贝类肌肉和内脏中As(无机砷和总砷)、Pb(铅)、Cr(铬)、Cd(镉)、Hg(甲基汞)的含量,并采用污染指数法、系统聚类法评价了各重金属的污染特征和分类。结果表明:海虹(贻贝,Mytilus edulis)、栉孔贝(Chlamys farreri)、生蚝(Ostrea gigas thunberg)和毛蚶子(Scapharca subcrenata)等的重金属综合污染(MPI)较高。根据NY 5073-2006 无公害食品水产品中有毒有害物质限量标准进行重金属评价。秦皇岛海域食用贝类六种重金属含量最高为Cd,均值为1.129 mg/kg,超出NY 5073-2006 无公害食品水产品中有毒有害物质限量标准,污染较严重,总As和无机As均值分别为0.161、0.021 mg/kg。Cr和Hg均值分别为0.107和0.013 mg/kg,均未受污染,Pb均值为0.188 mg/kg,污染较轻。但部分贝类Cd污染比较严重。其中内脏污染比肌肉部分严重,尤其是大小海螺(Busycon canaliculatu)。因此,需进一步研究秦皇岛海域可食用贝类中Pb和Cd的污染来源并进行有效防治。     

不同烹饪方式对海参体壁营养成分变化的对比分析

为了探究不同烹饪方式对海参体壁营养成分的影响,将鲜活海参分别使用常压烹饪、高压烹饪、重汤烹饪方式进行烹饪。对比不同烹饪方式下海参外观、体壁组织变化、海参失水率、失重率、收缩率、海参体壁营养成分及海参体壁质构变化。研究结果显示,高压烹饪组海参体壁水分、水溶性蛋白、胶原蛋白、多糖含量分别为84.27%、0.58%、1.73%、0.76%、2.73%,常压烹饪组海参体壁水分、水溶性蛋白、胶原蛋白、多糖含量分别87.58%、0.36%、1.92%、1.92%,重汤烹饪组海参体壁水分、水溶性蛋白、胶原蛋白、多糖含量分别为86.62%、0.46%、1.82%、0.81%。重汤烹饪组在海参体壁水分、水溶性蛋白、胶原蛋白、多糖含量上介于高压烹饪组、常压烹饪组之间,具有统计学差异(p<0.05)。结果表明重汤烹饪下的海参体壁组织较为完整,体壁营养成分保留较多,且对海参体壁的质构影响较小,符合海参烹饪的要求。     

基于深度语义分割的多源遥感图像海面溢油监测

针对遥感图像海面溢油区域通常受到斑噪声以及强度不均等因素的影响,从而导致溢油区域监测效果较差的问题,本文引入了深度语义分割的方法,将深度卷积神经网络与全连接条件随机场相结合,形成端对端连接。以Resnet结构为基础,首先通过深度卷积神经网络对多源遥感图像粗分割并作为输入,然后经过改进的全连接条件随机场,利用高斯成对势和平均场近似定理,建立条件随机场形成递归神经网络作为输出。通过多源遥感图像对海面溢油区域进行监测,并利用可见光图像估计溢油区域面积。实验在所建立的多源遥感图像数据集上与其它先进模型进行对比,结果表明本文方法提高了溢油区域的分割精度以及精细细节程度,平均交并比为82.1%,监测效果具有明显地改善。     

Bio-economic modelling for marine spatial planning application in North Sea shrimp and flatfish fisheries

Marine activities have been increasingly competing for space and reducing areas for fishing. The use of spatially explicit tools can assist the decision making process on defining the optimal location of closures for fishing due to these emerging activities.This paper presents the Spatial Integrated bio-economic Model for FISHeries (SIMFISH). In this model fishers behaviour is simulated based on optimal effort allocation. The added value of this model compared to other existing spatial management tools lies in the presence of (i) short and long term fishers behaviour (ii) spatial explicit stock and fleet dynamics and (iii) relatively low data requirements.As an illustration, SIMFISH is applied in this paper to estimate the impact of area closures in the North Sea. Overall area closures have a negative impact on the profitability of the fleets. This would be worsened with higher fuel prices and decreased stock productivity.     

The control of sea lice in Atlantic salmon by selective breeding

Sea lice threaten the welfare of farmed Atlantic salmon and the sustainability of fish farming across the world. Chemical treatments are the major method of control but drug resistance means that alternatives are urgently needed. Selective breeding can be a cheap and effective alternative. Here, we combine experimental trials and diagnostics to provide a practical protocol for quantifying resistance to sea lice. We then combined quantitative genetics with epidemiological modelling to make the first prediction of the response to selection, quantified in terms of reduced need for chemical treatments. We infected over 1400 young fish with Lepeophtheirus salmonis, the most important species in the Northern Hemisphere. Mechanisms of resistance were expressed early in infection. Consequently, the number of lice per fish and the ranking of families were very similar at 7 and 17 days post infection, providing a stable window for assessing susceptibility to infection. The heritability of lice numbers within this time window was moderately high at 0.3, confirming that selective breeding is viable. We combined an epidemiological model of sea lice infection and control on a salmon farm with genetic variation in susceptibility among individuals. We simulated 10 generations of selective breeding and examined the frequency of treatments needed to control infection. Our model predicted that substantially fewer chemical treatments are needed to control lice outbreaks in selected populations and chemical treatment could be unnecessary after 10 generations of selection. Selective breeding for sea lice resistance should reduce the impact of sea lice on fish health and thus substantially improve the sustainability of Atlantic salmon production.     

FogMed: A Fog-Based Framework for Disease Prognosis Based Medical Sensor Data Streams

Recently, an increasing number of works start investigating the combination of fog computing and electronic health (ehealth) applications. However, there are still numerous unresolved issues worth to be explored. For instance, there is a lack of investigation on the disease prediction in fog environment and only limited studies show, how the Quality of Service (QoS) levels of fog services and the data stream mining techniques influence each other to improve the disease prediction performance (e.g., accuracy and time efficiency). To address these issues, we propose a fog-based framework for disease prediction based on Medical sensor data streams, named FogMed. This framework aims to improve the disease prediction accuracy by achieving two objectives: QoS guarantee of fog services and anomaly prediction of Medical data streams. We build a virtual FogMed environment and conduct comprehensive experiments on the public ECG dataset to validate the performance of FogMed. The experiment results show that it performs better than the cloud computing model for processing tasks with different complexities in terms of time efficiency.