Effects of stocking density on the growth and immunity of Atlantic salmon salmo salar reared in recirculating aquaculture system(RAS)

Atlantic salmon reared in recirculating aquaculture system(RAS) may lead to inappropriately high stocking density, because ?sh live in a limited space. Finding the suitable stocking density of Atlantic salmon reared in RAS is very important for RAS industry. In this paper, the in?uence of stocking density on growth and some stress related physiological factors were investigated to evaluate the ef fects of stocking density. The ?sh were reared for 220 days at ?ve densities(A: 24 kg/m^3; B: 21 kg/m^3; C: 15 kg/m^3; D: 9 kg/m^3 and E: 6 kg/m^3). The results show that 30 kg/m^3 might be the maximum density which RAS can af ford in China. The stocking densities under 30 kg/m^3 have no ef fect on mortality of Atlantic salmon reared in RAS. However, the speci?c growth rate(SGR), ?nal weight and weight gain in the high density group were signi?cantly lower than the lower density groups and middle density groups. Moreover, feed conversion rate(FCR) had a negative correlation with density. Plasma hormone T_3 and GH showed signi?cant decrease with the increase of the stocking density of the experiment. Furthermore, thyroid hormone(T 3), GH(growth hormone) activities were decreased with stocking density increase. However, plasma cortisol, GOT(glutamic oxalacetic transaminase) and GPT(glutamic pyruvic transaminase) activities were increase with stocking density increase. And the stocking density has no ef fects on plasma lysozyme of Atlantic salmon reared in RAS. These investigations would also help devise effcient ways to rear adult Atlantic salmon in China and may, in a way, help spread salmon mariculture in China.     

面向双/多变量的连续面域拓扑图可视化方法

面域拓扑图是一种利用区域面积大小定量表达区域属性信息的可视化方法。由于其区域面积本身已经表示某一变量,因此这更有利于双/多变量的制图表达。针对目前基于面域拓扑图的双/多变量表达方法中存在的难以表达相邻区域之间基本状况和不利于不同地理现象的空间分布规律及差异表达的问题,本文提出一种面向双/多变量的连续面域拓扑图可视化方法。首先通过格网密度补偿和积分步长逐步试探的方法对基于扩散模型的连续面域拓扑图生成算法进行部分优化,完成基本变量的表达,然后分别通过空间内插和符号扩展完成第2和第3变量在连续面域拓扑图中的表达。最后以慕尼黑市人口密度和银行/ATM分布(双变量)数据以及奥格斯堡市人口密度数据、幼儿园分布以及规模数据(多变量)为试验数据进行可视化,并通过实证分析验证了该方法的有效性和优越性。     

Estimation of crowd density from UAVs images based on corner detection procedures and clustering analysis

With rapid developments in platforms and sensors technology in terms of digital cameras and video recordings, crowd monitoring has taken a considerable attentions in many disciplines such as psychology, sociology, engineering, and computer vision. This is due to the fact that, monitoring of the crowd is necessary to enhance safety and controllable movements to minimize the risk particularly in highly crowded incidents (e.g. sports). One of the platforms that have been extensively employed in crowd monitoring is unmanned aerial vehicles (UAVs), because UAVs have the capability to acquiring fast, low costs, high-resolution and real-time images over crowd areas. In addition, geo-referenced images can also be provided through integration of on-board positioning sensors (e.g. GPS/IMU) with vision sensors (digital cameras and laser scanner). In this paper, a new testing procedure based on feature from accelerated segment test (FAST) algorithms is introduced to detect the crowd features from UAV images taken from different camera orientations and positions. The proposed test started with converting a circle of 16 pixels surrounding the center pixel into a vector and sorting it in ascending/descending order. A single pixel which takes the ranking number 9 (for FAST-9) or 12 (for FAST-12) was then compared with the center pixel. Accuracy assessment in terms of completeness and correctness was used to assess the performance of the new testing procedure before and after filtering the crowd features. The results show that the proposed algorithms are able to extract crowd features from different UAV images. Overall, the values of Completeness range from 55 to 70 % whereas the range of correctness values was 91 to 94 %.     

A geospatial study of the drought impact on surface water reservoirs: study cases from Texas,USA

Satellite images have been used historically to measure and monitor fluctuations in the surface water reservoirs. This study integrates remote sensing and Geographic Information System (GIS) technologies to investigate the impact of drought on 10 selected surface water reservoirs in San Angelo and Dallas, Texas. Oscillations in summer and winter months throughout the 2005–2016 period were assessed using multispectral images from Landsat-5, ?7, and ?8, and changes in the reservoirs were characterized and correlated against local climate data of each reservoir. For quantitative comparisons of the time-series measurements, a robust density slicing approach was employed to classify the range of values of the raster cells in the near-infrared band of Landsat images for each lake into three desired classes (deep water, shallow water, and dry area) based on the natural breaks inherent in the dataset. Statistical analysis shows that the overall accuracy of the classification is about 94%, which demonstrates the efficiency of the density slicer to accurately estimate surface water area changes from an individual Landsat band. Shrinkage in the surface water area over the study period reveals the concrete impact that the drought along with other factors have on the 10 selected lakes. The San Angelo lakes located in west central Texas experienced a nearly consistent pattern of change during most of the study period; whereas the Dallas lakes in northeast Texas followed the oscillating pattern of drought and correlated closely to the local conditions. Shockingly, the extreme drought caused complete vanishing of several lakes, and consequently Texas had to remove them from its recreational plans. Our new findings can certainly help with the water resource management in Texas and our study approach can be adapted for monitoring lake oscillations in other areas across the world. This geospatial study demonstrates the societal benefits from incorporating remote sensing and GIS in investigating geo-environmental problems associated with severe climate changes.     

基于GPS新型L5信号的地表雪深反演研究

利用GPS多路径反射信号测量地表雪深具有全天候和高时空分辨率的特点,因此其可作为一种代替气象站监测雪深的新手段。然而,先前大多数研究仅使用了GPS L1和L2C波段信噪比数据探测积雪深度。为验证新型的L5信号在雪深反演方面的优越性,本文阐述了GPS-R技术反演雪深的原理,利用Lomb-Scargle周期图法所处理的受积雪表层影响的信噪比数据计算了频谱振幅强度,通过获取频谱特征值与天线高度的关系求解雪深值,最后分别与L1反演结果和实测雪深数据进行了对比。试验结果表明：与现有的GPS-R测量雪深结果相比,利用新型的L5反射信号反演地表雪深的精度更佳;采用GPS-R技术探测雪深对把握测站区域内的雪深变化情况和淡水资源储量具有重要价值。     

机载LiDAR点云获取与高精度DEM建设关键技术探讨

结合广东省机载LiDAR点云获取与高精度DEM建设项目,介绍了项目总体技术路线,针对项目难点,从设备选择、点云密度设计、植被覆盖密集山区数据获取方法、点云数据分类组合算法、空白区处理等5个方面的关键技术进行了探讨,并提出解决方案,为同类项目的设计与实施提供参考。     

我国南方西南和中东部区域两次持续性低温雨雪过程与关键环流系统的关系研究

利用NCEP再分析资料和国家气象信息中心提供的753站逐日气温和降水资料,对比分析了我国南方西南和中东部区域两次持续10 d以上的低温雨雪过程,结果表明:(1)两次过程中欧亚大陆中高纬东亚大槽均加深,但环流形势有差异。西南过程呈现"北高南低"形势,关键脊区在贝加尔湖,而中东部区域过程"北高南低"和"西高东低"形势共存,关键脊区从乌拉尔山延伸至贝加尔湖。两次过程异常的环流与北大西洋向东传播的波列有关。(2)西南过程关键脊区提前过程3 d发展并东移至贝加尔湖,形成稳定形势;而中东部区域过程关键脊区提前过程一周发展,在开始日达最强。两次过程均伴随蒙古高压东移南压使地面降温,500 hPa关键脊区超前蒙古高压2 d变化。西南过程降温主要受到冷平流和绝热冷却影响,而中东部区域过程主要受到冷平流的影响。(3)西南过程水汽来自孟加拉湾,只受南支槽支配。中东部区域过程水汽来自孟加拉湾、南海和西太平洋,由南支槽和西太平副热带高压的共同影响。两次过程水汽正收支主要来自南边界。     

1961—2017年新疆积雪期时空变化特征及其与气象因子的关系

利用新疆89个地面站逐日积雪深度观测资料,研究探讨了1961—2017年新疆区域积雪期、积雪初日、积雪终日的时空变化规律,分析了北疆和天山山区积雪期的年代际和周期变化特征及其与气温、降水的关系.结果表明:新疆各地积雪期、积雪初日和终日存在明显的差异,积雪期以天山为界北多南少;从空间分布看,天山山区和新疆北部阿勒泰、塔城...     

Density profiles and luminosity functions of the globular clusters M3 and M92

Tautenburg Schmidt plates with the globular clusters M3 and M92 were measured on the APM facility in Cambridge, mainly for astrometric purposes. The data were used to derive the radial density profiles and the luminosity functions of these clusters. There is a good agreement of our results with formerly ones derived by other authors. In both clusters effects of mass segregation are observed.     

超临界态甲烷密度研究

超临界甲烷密度不仅是非常规天然气资源量计算与吸附能力测定的重要参数,同时也是衡量超临界甲烷扩散效率与溶解有机物能力的主要指标。通过对比分析各种气体状态方程的适用性,认为基于亥姆霍兹能量基本状态方程可以准确计算0~30 MPa、270~360 K条件下甲烷的密度。利用Microsoft Office Excel编写了甲烷密度的计算程序,与NIST （美国国家标准与技术研究院）商业软件计算结果相比,误差小于0.05%。分析了0~100 MPa、270~360 K范围内甲烷密度的变化规律。结果表明,甲烷密度随压力增大而增大,在低于30 MPa时增速较大且对温度的敏感性较强,高于30 MPa时增速逐渐变缓,且敏感性减弱。在煤层原位条件下随着埋深的增大,甲烷密度随温度升高而减小,随压力增大而增大;在温度与压力共同作用下,甲烷密度呈先增速不变、近似线性增加,后增速逐渐减小、凸曲线形增加的变化规律。游离态甲烷密度受温度的影响比吸附态甲烷小,是深部煤层气资源增量的主要贡献者。研究结果为深部煤层气赋存及其潜力预测提供了基础参数。