Migration pattern of two salmon stocks in the Baltic Sea     

Kallio-Nyberg  I.; Ikonen  E. 《ICES Journal of Marine Science》1992,49(2):191-198

  相似文献   

Bowen数和东中国海Bowen数分布     

张淮水  汪园祥  楼顺里 《中国海洋大学学报(自然科学版)》1988,(3)

本文讨论Bowen数的意义、功能和计算法。同时,依据多年水文气象实测资料作统计,计算出东中国海的Bo值。其结果绘制成1月至12月的月平均分布图,从而对本海域的Bo分布特点作详细分析介绍。  相似文献   

融冰季节北极破碎冰区热通量的初步研究   总被引：5，自引：1，他引：5  

史久新  赵进平  矫玉田 《海洋科学进展》2002,20(3):35-43

利用航空遥感数字影像的解析结果和实测气象，海洋和海冰资料，定量研究了夏季融冰期北极破碎冰区的热通量，计算了海洋对大气的热贡献，结果表明，在北极夏季海冰融化时，短波辐射远远大于感热和潜热通量，是表面热通量的决定因素，海洋对大气的热贡献主要由长波辐射决定，在观测期间，海洋对大气的热贡献为38～104Wm^-2，这部分热量的大小与海冰的密集度有关，当海冰密集度小于0.8时，海洋对大气的热贡献随海冰密度度的增大而减小，而当海冰密集度超过0.8以后，该热通量将随海冰密集度的增大而增大。  相似文献   

沸石基储能基元的研究     

杨玉山  董发勤  段涛 《矿物岩石》2008,28(1):13-16

以酸活化沸石为载体,十二醇为储能工质.制备沸石基储能基元,并采用X射线衍射、红外光谱和差示扫描量热等对沸石基储能基元进行表征.结果表明:储能基元在2θ=22.50时的衍射峰变强,相变储能材料十二醇和沸石栽体之间仅仅是简单的嵌合关系.储能基元的相变温度有一定的降低,并且熔融峰变宽.  相似文献   

Estimating Influence of Crystallizing Latent Heat on Cooling-Crystallizing Process of a Granitic Melt and Its Geological Implications     

ZHANG Bangtong  WU Junqi  LING Hongfei  CHEN Peirong 《《地质学报》英文版》2008,82(2):438-443

Based on the theory of thermal conductivity, in this paper we derived a formula to estimate the prolongation period （AtL） of cooling-crystallization process of a granitic melt caused by latent heat of crystallization as follows：△tL=QL×△tcol/（TM-TC）×CP where TM is initial temperature of the granite melt, Tc crystallization temperature of the granite melt, Cp specific heat, △tcol cooling period of a granite melt from its initial temperature （TM） to its crystallization temperature （Tc）, QL latent heat of the granite melt.
The cooling period of the melt for the Fanshan granodiorite from its initial temperature （900℃） to crystallization temperature （600℃） could be estimated -210,000 years if latent heat was not considered. Calculation for the Fanshan melt using the above formula yields a AtL value of -190,000 years, which implies that the actual cooling period within the temperature range of 900°-600℃ should be 400,000 years. This demonstrates that the latent heat produced from crystallization of the granitic melt is a key factor influencing the cooling-crystallization process of a granitic melt, prolongating the period of crystallization and resulting in the large emplacement-crystallization time difference （ECTD） in granite batholith.  相似文献   

基于ArcIMS的城市小区信息发布系统的设计与实现   总被引：1，自引：0，他引：1  

马明  杨永国  邓彩群 《国土资源信息化》2008,(5):20-22,34

利用ESRI公司新一代Web GIS产品Arc IMS9.0,结合ASP及IIS6.0、SQL Serve、ArcSDE等网络、空间数据库方面技术,建立了城市小区信息发布系统。总结了ArcIMS的特点和体系结构,提出了基于ArcIMS的城市小区信息发布系统的设计思路和方案,阐述了系统的具体实现方法。  相似文献   

三峡库区消落区土壤磷释放的环境影响因子   总被引：2，自引：0，他引：2  

马利民  唐燕萍  滕衍行  赵建夫 《地学前缘》2008,15(5):235

以三峡库区消落区万州段为试验基地,选取释磷能力较强的紫色冲积土,根据三峡水库消落带的"干湿交替"空间和时间特征,进行万州断面土壤磷释放的影响因子的实验室模拟试验和万州江面淹没的对照试验。研究发现,随着淹水时间的变化,各种形态的磷在前5~10d各形态磷变化有相当的差异,随后变化趋势趋于稳定。TP有降低的趋势,土壤磷有一定的释放。野外研究表明Olsen-P在淹水10周左右到达最大值,以后缓慢降低。淹水时土壤Olsen-P增加,干燥后降低。多次淹水时每次淹水后土壤的有效磷水平都略有增加,落干后相较上次落干后有效磷水平降低,最后一次淹水后相较与初始时Olsen-P水平低16.7%。随着淹水深度增加,土壤的Olsen-P水平在淹水时由淹水前20.53mg/kg提高到43.23mg/kg,增加110.6%。当上覆水磷浓度较低时(<2mg/L),磷吸附到达平衡的时间较短,约需要6周。当上覆水磷浓度较高(>2mg/L)时,磷吸附到达平衡的时间较长。微生物活动对淹水土壤的磷释放有一定影响,有微生物时磷的释放高于无微生物者0.048mg/L。种植植物的土壤在淹水后Olsen-P含量大于土壤直接淹没时的释放量,种植狗牙根(Cynodondactylon)和野地瓜藤(Ficustikoua)的土壤中Olsen-P分别较未种植物土壤释放量高出21.5%和12.7%。  相似文献   

Heat flow and crustal thermal structure in the Late Archaean Closepet Granite batholith,south India     

Sukanta Roy  Labani Ray  Anurup Bhattacharya  R. Srinivasan 《International Journal of Earth Sciences》2008,97(2):245-256

The Late Archaean Closepet Granite batholith in south India is exposed at different crustal levels grading from greenschist facies in the north through amphibolite and granulite facies in the south along a ∼400 km long segment in the Dharwar craton. Two areas, Pavagada and Magadi, located in the Main Mass of the batholith, best represent the granitoid of the greenschist and amphibolite facies crustal levels respectively. Heat flow estimates of 38 mW m⁻² from Pavagada and 25 mW m⁻² from Magadi have been obtained through measurements in deep (430 and 445 m) and carefully sited boreholes. Measurements made in four boreholes of opportunity in Pavagada area yield a mean heat flow of 39 ± 4 (s.d.) mW m⁻², which is in good agreement with the estimate from deep borehole. The study, therefore, demonstrates a clear-cut heat flow variation concomitant with the crustal levels exposed in the two areas. The mean heat production estimates for the greenschist facies and amphibolite facies layers constituting the Main Mass of the batholith are 2.9 and 1.8 μW m⁻³, respectively. The enhanced heat flow in the Pavagada area is consistent with the occurrence of a radioelement-enriched 2-km-thick greenschist facies layer granitoid overlying the granitoid of the amphibolite facies layer which is twice as thick as represented in the Magadi area. The crustal heat production models indicate similar mantle heat flow estimates in the range 12–14 mW m⁻², consistent with the other parts of the greenstone-granite-gneiss terrain of the Dharwar craton.  相似文献   

Inferring hydro-geothermal parameters from advectively perturbed thermal logs     

M. Verdoya  V. Pasquale  P. Chiozzi 《International Journal of Earth Sciences》2008,97(2):333-344

  相似文献   

Automated Kerogen Classification in Microscope Images of Dispersed Kerogen Preparation     

L. I. Kuncheva  J. J. Charles  N. Miles  A. Collins  B. Wells  I. S. Lim 《Mathematical Geosciences》2008,40(6):639-652

We develop the classification part of a system that analyses transmitted light microscope images of dispersed kerogen preparation. The system automatically extracts kerogen pieces from the image and labels each piece as either inertinite or vitrinite. The image pre-processing analysis consists of background removal, identification of kerogen material, object segmentation, object extraction (individual images of pieces of kerogen) and feature calculation for each object. An expert palynologist was asked to label the objects into categories inertinite and vitrinite, which provided the ground truth for the classification experiment. Ten state-of-the-art classifiers and classifier ensembles were compared: Naïve Bayes, decision tree, nearest neighbour, the logistic classifier, multilayered perceptron (MLP), support vector machines (SVM), AdaBoost, Bagging, LogitBoost and Random Forest. The logistic classifier was singled out as the most accurate classifier, with an accuracy greater than 90. Using a 10 times 10-fold cross-validation provided within the Weka software, we found that the logistic classifier was significantly better than five classifiers (p<0.05) and indistinguishable from the other four classifiers. The initial set of 32 features was subsequently reduced to 6 features without compromising the classification accuracy. A further evaluation of the system alerted us to the possible sensitivity of the classification to the ground truth that might vary from one human expert to another. The analysis also revealed that the logistic classifier made most of the correct classifications with a high certainty.  相似文献