Isolation of protein from Chlorella sorokiniana CY1 using liquid biphasic flotation assisted with sonication through sugaring-out effect

Microalgae, a sustainable source of multi beneficial components has been discovered and could be utilised in pharmaceutical, bioenergy and food applications. This study aims to investigate the sugaring-out effect on the recovery of protein from wet green microalga, Chlorella sorokiniana CY1 which was assisted with sonication. A comparison of monosaccharides and disaccharides as one of the phaseforming constituents shows that the monosaccharides, glucose was the most suitable sugar in forming the phases with acetonitrile to enhance the production of protein(52% of protein). The protein productivity of microalgae was found to be significantly influenced by the volume ratio of both phases, as the yield of protein increased to 77%. The interval time between the sonication as well as the sonication modes were influencing the protein productivity as well. The optimum protein productivity was obtained with 10 s of resting time in between sonication. Pulse mode of sonication was suitable to break down the cell wall of microalgae compared to continuous mode as a lower protein yield was obtained with the application of continuous mode. The optimum condition for protein extraction were found as followed: 200 g/L glucose as bottom phase with volume ratio of I:1.25, 10 s of resting time for ultrasonication, 5 s of ultrasonication in pulse mode and 0.25 g of biomass weight. The high yield of protein about 81% could be obtained from microalgae which demonstrates the potential of this source and expected to play an important role in the future.     

基于KiK-net数据的偏振分析方法计算震中方位角影响因素分析

基于日本KiK-net强震动观测记录,以提高计算震中方位角的准确性为目标,研究记录参量(加速度、速度、位移)、计算时间窗和滤波频带对偏振分析方法计算震中方位角结果的影响。结果表明,在该研究的地震数据条件下,采用位移记录、计算时间窗为1s、滤波频带取0.1～20Hz时,可以获得最佳的震中方位角计算结果,震中方位角的计算偏差为45°时所占比例为88%。     

电解法处理船舶压载水的杀菌性能及机理研究

船舶压载水携带的微生物对目的海域的污染问题亟待解决。采用电解法,以渤海湾的海水为处理对象,以炭纤维材料为阴极,分别以碳棒、碳板和炭纤维为阳极,首先考察了施电2.00 V下3种阳极炭材料对应的杀菌效果,进而重点考查了碳板为阳极材料时施加不同槽压下的杀菌性能,并对其杀菌机理进行初步分析。结果表明,3种阳极材料对应的杀菌效果先后顺序为碳棒碳板炭纤维,各自的杀菌效果均较为明显,施电18 min时碳板对应的灭活率可达100%;以碳板为阳极时,施加槽压越高杀菌效果越显著,本研究范围内以1.81 V为佳,施电18 min时灭活率在99%以上;不同槽压下体系中氯离子浓度和p H都随时间整体呈减小趋势,一定程度上可用于解释杀菌作用过程。研究结果可为电解法处理船舶压载水提供参考和借鉴。     

我国经营性海洋牧场产业链延伸研究

我国经营性海洋牧场产业目前主要以育苗、养殖、捕捞、生产、加工的产业链形式存在,文章在分析经营性海洋牧场发展制约因素的基础上,对于海产品产业链的延伸进行研究并提出建议:在苗种培育产业的基础上延伸出"参与式观光业",在开展养殖业的同时兼并实施新产业"DIY养殖业",产品收获后进行"精深加工业"的同时开展"观光旅游业",销售行业采取线上线下与企业之间结合的"O2O+B2B"模式,面向客户方面鼓励新机构即"反馈机构"的建立与推广,拓展休闲渔业产业,发展新型休闲渔业。通过产业链延伸,旨在开拓海产品的市场空间,以期获取更多的经济效益,提升海洋牧场综合效益。     

ATS藻板与自然礁石上藻群生物多样性的比较

ATS(algal turf scrubber)系统是一种利用潮间带藻类高效去除富营养化水体中氮(N)、磷(P)元素的水质净化系统, 藻类是支持整个系统最重要的组成部分, 其群落结构与水质净化效果密切相关。该研究基于Illumina MiSeq平台的高通量测序技术对海水水族缸的ATS系统中藻板样品和自然礁石上的藻类进行多样性分析。18S rDNA研究结果表明, ATS系统中经筛选得到藻类优化序列21390条, 其中对丝藻属Antithamnion占主要地位, 占序列总数的22.79%, 其次19.07%序列归入斜纹藻属Psammodictyon; 宋井、展南亭、后宅3个地区的藻类经筛选分别得到88435、87129、106458条优化序列, 主要为分枝色指藻属Chroodactylon、宽果藻属Mastocarpus和日本马泽藻属Mazzaella。ATS系统和自然环境样品共有的优势藻为骨条藻属Skeletonema和仙菜属Ceramium。本实验在研究ATS系统与自然礁石上的藻类群落相似性的同时, 深入探究了其群落结构的差异性, 为进一步优化ATS系统的功能提供了理论依据。     

培育密度和投饵量对长牡蛎壳黑选育品系幼虫生长存活及附着变态的影响

为探究长牡蛎(Crassostrea gigas)壳黑选育品系规模化繁育适宜的培育密度和投饵量,本研究以长牡蛎野生群体幼虫为对照组,分析了不同培育密度(3、7和15个/mL)和不同初始投饵量(0.4、0.8和1.6×10~3cells·ind^-1·d^-1)对长牡蛎壳黑选育品系幼虫生长、存活及附着的影响。研究显示,培育密度和投饵量对长牡蛎幼虫的生长速率、存活率和附着率有显著交互作用(P<0.05)。在培育密度3和7个/mL实验组,长牡蛎幼虫生长速率随投饵量增加而显著增大(P<0.05),并在培育密度7个/mL、投饵量1.6×10~3cells·ind^-1·d^-1实验组达到最大值。而在培育密度15个/mL实验组,投饵量增加对长牡蛎幼虫的生长速率无显著影响(P> 0.05)。且在培育密度15个/mL、投饵量1.6×10~3cells·ind^-1·d^-1实验组长牡蛎壳黑品系幼虫存活率和附着率最低。但在培育密度15个/mL实验组长牡蛎壳黑选育品系幼虫的壳高始终高于野生群体幼虫。且除投饵量0.4×10~3cells·ind^-1·d^-1实验组外,长牡蛎壳黑选育品系幼虫生长速率、存活率和附着率均高于野生群体幼虫。研究结果表明,长牡蛎壳黑选育品系幼虫最适培育条件为培育密度7个/mL、投饵量1.6×10~3cells·ind^-1·d^-1,增加投饵量可促进长牡蛎幼虫生长,但过高的培育密度会与投饵量产生拮抗作用,抑制幼虫生长,不利于幼虫存活和附着。与长牡蛎野生群体相比,壳黑选育品系幼虫能适应更高的培育密度环境,在饵料充足的条件下,其幼虫的生长、存活及附着性状均优于野生群体。     

利用改进型MODIS火点探测算法实现河北省秸秆焚烧火点识别

为准确地了解河北省秸秆焚烧火点的空间分布,为秸秆焚烧监测的实现、禁烧工作的开展、环境质量改善提供支持.基于MODIS L1B数据、MODIS标准火点产品MOD14、全国秸秆焚烧火点日报数据为基础,采用改进型MODIS火灾探测算法,并通过IDL语言实现,得到秸秆焚烧火点空间分布信息,并进行空间与定量精度分析.研究表明:火点大部分位于河北省南部的一些地区,其中尤以邢台、石家庄、邯郸火点数量最为突出;该算法运算速度快,获取的秸秆焚烧火点数据具有一定检测精度和可靠性,对秸秆焚烧的监测具有一定的实用价值.     

CORS网区域重力场变化与地面稳定性跟踪监测方法

为了实现地面稳定性降低时间与地点、持续作用时间与空间影响分布的全面跟踪监测,该文基于卫星定位连续运行站(CORS)站网观测数据,结合地表水、大气及海平面变化资料,提出了CORS站网时变重力场及负荷形变场精化的已知负荷移去恢复法,建立了基于时变重力场的确定性地面稳定性变化定量辨识准则。以丽水温州地区为例,利用2015-2017年CORS网及有关水文观测数据进行计算分析,根据40起已发生的历史地质灾害(险情)事件对结果进行验证:丽水温州地区的CORS网具备区域重力场变化与地面稳定性跟踪监测能力,具备地质灾害灾变过程追踪与前兆捕获能力,CORS站网的地质灾害前兆提前捕获率可达92.5%。     

Understanding geographical patterns of a city’s diurnal rhythm from aggregate data of location‐aware services

Do collective behaviors of the daily routine of a city's inhabitants form the periodical cycling of human activity at the city level (here termed the “city's diurnal rhythm”)? If the answer is yes, do there exist geographical patterns in the city's diurnal rhythm? Using a nationwide dataset of observed uses of location‐aware services in the largest Chinese social media platform, we first confirm the significant periodicity in city‐level human activity from the perspective of the aggregate degree of social media uses over a day. We then investigate geographical changes in the diurnal rhythm of human activity and its local variations in different parts of the city, and between weekdays and weekend days, over 340 Chinese cities. Our results show that a city's diurnal rhythm across the whole country exhibits both regular, nationally conspicuous shifts along geographical gradients and locally distinct spatiotemporal changes within the city. Our findings could provide insights into the characterization of the daily routine of city‐level human activity and its geographical patterns, and have potential for several issues in terms of planning, management, and decision‐making related to human population dynamics.     

A high-precision heuristic model to detect home and work locations from smart card data

Smart card-automated fare collection systems now routinely record large volumes of data comprising the origins and destinations of travelers. Processing and analyzing these data open new opportunities in urban modeling and travel behavior research. This study seeks to develop an accurate framework for the study of urban mobility from smart card data by developing a heuristic primary location model to identify the home and work locations. The model uses journey counts as an indicator of usage regularity, visit-frequency to identify activity locations for regular commuters, and stay-time for the classification of work and home locations and activities. London is taken as a case study, and the model results were validated against survey data from the London Travel Demand Survey and volunteer survey. Results demonstrate that the proposed model is able to detect meaningful home and work places with high precision. This study offers a new and cost-effective approach to travel behavior and demand research.