多相滤波器组谱分析方法的性能讨论与天文观测应用

多相滤波器组(PFB)是均匀数字滤波器组的一种高效实现结构,用于信号的均匀子带分解和抽取,对应用多相滤波器组作为功率谱估计器的统计性能与计算量进行分析,与相关图与周期图方法进行比较,并通过仿真及FAST密云模型21cm中性氢谱线观测检验其应用效果。     

山东蓬莱沿海鱼类的初步调查

１９９３年７月至１９９８年８月对蓬莱沿海定置网渔获的鱼类进行初步调查,结果表明,蓬莱沿海鱼类共有１３７种,分别隶属于５９科１０８属。根据其适温类型可分为暖水性鱼类３４种,占总数的２４．８２％;暖温性鱼类８３种,占总数的６０．５８％;冷温性鱼类２０种,占总数的１４．６０％。根据食性类型,可分为３类,其中游泳动物食性的鱼类３６种,占总数的２６．２８％;浮游动物食性有２２种,占总数的１６．０６％;底栖动物食性７９种,占总数的５７．６６％．从栖息生境的多样性来看,可分为中上层鱼类３８种,占总数的２７．７４％;近底层鱼类２５种,占总数的１８．２５％;底层鱼类６４种,占总数的４６．７１％;岩礁性鱼类１０种,占总数的７．３０％。并就渔业开发与保护提出了建议。     

Jordan日照记录阈值分析

本文是通过10个月的日射、日照资料对比观测、统计的乔唐、康氏和光电式日照计记录阈值的平均值和标准偏差,分析了乔唐日照计进光孔径、涂药方式对感光迹线的影响,测定了感光药的吸收光谱,并根据日出日没时直接日射辐照度的平均变化率,估算了由阈值的不确定度引起的日照时数的误差,从而为我国几十年的乔唐日照资料的评价提供依据。     

鲜水河断裂带的构造大地测量

利用短边GPS点阵、短基线标石阵和精密激光测距 ,在与鲜水河断裂带的断层破裂带垂直的剖面上和构造盆地内进行构造大地测量 ,获得了断层软弱带和断层蠕变带上的最佳形变分布。综合利用相关地学成果和理论 ,揭示了构造形变所隐含的动力学信息 ,识别了断层应变带、塑性流变带和主断面在地面的分布范围。用外围GPS远场联测成果探讨了该断裂带的驱动力机制 ,匡正了其“左旋”运动和现今活动速度的含义。最后 ,评估了该断裂的地震活动趋势     

MONITORING POLYNUCLEAR AROMATIC HYDROCARBONS IN SEDIMENT POREWATER BY SPMD

A new mimic biological Semi-permeable Membrane Device (SPMD) introduced for sampling organic pollutants yielded satisfactory results when it was frrst used as a passive sampler to concentrate and determine 16 kinds of polynuclear aromatic hydrocarbons (PAHs) by means of capillary GC on an HP 5890 GC-FID in coastal sediment perewater. The concentration of PAHs in sediment porewater for naphthalene(N), acenaphthlene(AL), acenaphthene (AE), fluorene (F), phenaphthene(P), anthracene(A), fluoranthene(FA), pyrene(Py), benzo[a]anthracene(B[a]A), chrysene(Chr), benzo[b] fluor- anthene(B[b]F), benzo[k]fluoranthene(B[k]F), benzo[a]pyrene(B[a]P),indeno[1,2,3,-cd]-Pyrene(I[123]P), dibenz[a,h]anthracene(D[ab]A) and benzo[g,h,i] perylene(B[ghi]P) were:50.36, under detection limits(UD), 18.19, 8.41, 8.40, 1.44, UD, 8.01, 524.15, 168.47, 50.13,123.66, 63.48, 27.40, 82.04 and 58,81 ng/L, respectively.     

The Forming Conditions of and Ore-searching Direction for B, Mg,Pb, Zn and Au Deposits in the Liaoji Proterozoic Rift

The Proterozoic was the first of severa1 impor-tant transitional periods in the earth's evolutionaryhistory. Linear .rifts over1apped on the b4se ofArchean granite -- greenstone and high -- grade gneissregimes. Along with the formation and evolution ofthe…     

Temporal stability of apparent soil electrical conductivity measured by electromagnetic induction techniques

Assessing and managing the spatial variability of hydropedological properties are important in environmental,agricultural,and geological sciences.The spatial variability of soil apparent electrical conductivity（ECa） measured by electromagnetic induction（EMI） techniques has been widely used to infer the spatial variability of hydrological and pedological properties.In this study,temporal stability analysis was conducted for measuring repeatedly soil ECa in an agricultural landscape in 2008.Such temporal stability was statistically compared with the soil moisture,terrain indices（slope,topographic wetness index（TWI）,and profile curvature）,and soil properties（particle size distribution,depth to bedrock,Mn mottle content,and soil type）.Locations with great and temporally unstable soil ECa were also associated with great and unstable soil moisture,respectively.Soil ECa were greater and more unstable in the areas with great TWI（TWI 〉 8）,gentle and concave slope（slope 〈 3%; profile curvature 〉 0.2）.Soil ECa exponentially increased with depth to bedrock,and soil profile silt and Mn mottle contents（R2= 0.57）,quadratically（R2 = 0.47）,and linearly（R 2 = 0.47）,respectively.Soil ECa was greater and more unstable in Gleysol and Nitosol soils,which were distributed in areas with low elevation（〈 380 m）,thick soil solum（〉 3 m）,and fluctuated water table（shallow in winter and spring but deep in summer and fall）.In contrast,Acrisol,Luvisol,and Cambisol soils,which are distributed in the upper slope areas,had lower and more stable soil ECa.Through these observations,we concluded that the temporal stability of soil ECa can be used to interpret the spatial and temporal variability of these hydropedological properties.     

Nitrogen and Phosphorus Budget of a Polyculture System of Sea Cucumber （Apostichopus japonicus）, Jellyfish （Rhopilema esculenta） and Shrimp （Fenneropenaeus chinensis）

The nitrogen(N) and phosphorus(P) budget and the ecological efficiency of a polyculture system of sea cucumber(Apostichopus japonicus), jellyfish(Rhopilema esculenta) and shrimp(Fenneropenaeus chinensis) were studied in a cofferdam, 120.2 ha in size. The nutrients were supplied by spring tide inflow. In total, 139600 kg N yr-1 and 9730 kg P yr-1 input to the system; while 118900 kg N yr-1 and 2840 kg P yr-1 outflowed from the system concurrently, thus the outflow was 85.7%(N) and 29.2%(P) of inflow. The production of N and P was 889.5 kg yr-1 and 49.28 kg yr-1(sea cucumber) and 204 kg yr-1 and 18.03 kg yr-1(jellyfish and shrimp), respectively. The utilization rate of N and P by polycultured animals was 7.8‰ and 6.9‰, respectively, 21.9% and 38% higher than that of monocultured sea cucumber. Our results indicated that the polyculture system was an efficient culture system of animals and a remediation system of coastal environment as well; it scavenged 14.3% and 70.8% of N and P, respectively. Such an ecological efficiency may be improved further by increasing either the stocking density or the size of sea cucumber or both.     

Community structure and seasonal variation of soil arthropods in the forest-steppe ecotone of the mountainous region in Northern Hebei,China

Soil fauna have been receiving more and more attention because they play an important role in nutrient cycling. However, there is a lack of information on soil arthropods in the forest-steppe ecotone in the mountainous region of northern Hebei, which makes it difficult to meet the need of protecting biodiversity in this area. Soil arthropod communities were investigated in the forest-steppe ecotone in northern Hebei province to provide basic information on changes in mountain soil fertility, which could promote the development of soil arthropod communities in mountain ecotones. From the preliminary identification, a total of 7994 individual soil arthropods were collected, which belonged to 25 groups, 6 classes and 24 orders. Acarina, Hymenoptera and Collembola were the dominant groups in the ecotone. The number of Acarina was higher than Collembola, and this phenomenon was obviously different from other areas in the same climate zone. The increased abundance of rare groups in the Forest zone with the richer vegetation, higher arthropod abundance and more substantial litter depth, could be interpreted as a reaction to the suitable soil environment and food supply. And these rare groups were sensitive to environmental changes, which could be regarded as biotic indicators for evaluating soil quality. The analysis of community diversity showed that the abundance index (d), the Shannon-Wiener index (H′), the evenness index (J) and the density-group index (DG) were significantly higher in the forest zone, lower in the forest-steppe zone, and lowest in the meadow-steppe zone. Seasonal variations in community composition correlated with changes in average air temperature and precipitation in this ecotone. Groups and individuals of soil arthropod communities in the three zones were present in greater numbers in the middle of the rainy season than in the early or late periods of the rainy season as a whole. At the same time, seasonal changes in soil arthropod communities from different plots were also influenced by habitat condition.     

Solar flare forecasting based on sequential sunspot data

It is widely believed that the evolution of solar active regions leads to solar flares. However, information about the evolution of solar active regions is not employed in most existing solar flare forecasting models. In the current work, a shortterm solar flare forecasting model is proposed, in which sequential sunspot data, including three days of information about evolution from active regions, are taken as one of the basic predictors. The sunspot area, the McIntosh classification, the magnetic classification and the radio flux are extracted and converted to a numerical format that is suitable for the current forecasting model. Based on these parameters, the sliding-window method is used to form the sequential data by adding three days of information about evolution. Then, multi-layer perceptron and learning vector quantization are employed to predict the flare level within 48 h. Experimental results indicate that the performance of the proposed flare forecasting model works better than previous models.