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941.
The ecologically and socio-economically important marine ecosystems of Europe are facing severe threats from a variety of human impacts. To mitigate and potentially reverse some of these impacts, the European Union (EU) has mandated the implementation of the Marine Strategy Framework Directive (MSFD) in order to achieve Good Environmental Status (GES) in EU waters by 2020. The primary initiative for achieving GES is the implementation of coherent networks of marine protected areas (MPAs). Marine reserves are an important type of MPA in which no extraction is allowed, but their usefulness depends upon a number of ecological, management, and political factors. This paper provides a synthesis of the ecological effects of existing European marine reserves and the factors (social and ecological) underlying their effectiveness. Results show that existing European marine reserves foster significant positive increases in key biological variables (density, biomass, body size, and species richness) compared with areas receiving less protection, a pattern mirrored by marine reserves around the globe. For marine reserves to achieve their ecological and social goals, however, they must be designed, managed, and enforced properly. In addition, identifying whether protected areas are ecologically connected as a network, as well as where new MPAs should be established according to the MSFD, requires information on the connectivity of populations across large areas. The adoption of the MSFD demonstrates willingness to achieve the long-term protection of Europe's marine ecosystems, but whether the political will (local, regional, and continent wide) is strong enough to see its mandates through remains to be seen. Although the MSFD does not explicitly require marine reserves, an important step towards the protection of Europe's marine ecosystems is the establishment of marine reserves within wider-use MPAs as connected networks across large spatial scales.  相似文献   
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Rivers in the Mediterranean region often exhibit an intermittent character. An understanding and classification of the flow regimes of these rivers is needed, as flow patterns control both physicochemical and biological processes. This paper reports an attempt to classify flow regimes in Mediterranean rivers based on hydrological variables extracted from discharge time series. Long‐term discharge records from 60 rivers within the Mediterranean region were analysed in order to classify the streams into different flow regime groups. Hydrological indices (HIs) were derived for each stream and principal component analysis (PCA) and then applied to these indices to identify subsets of HIs describing the major sources of variations, while simultaneously minimizing redundancy. PCA was performed for two groups of streams (perennial and temporary) and for all streams combined. The results show that whereas perennial streams are mainly described by high‐flow indices, temporary streams are described by duration, variability and predictability indices. Agglomerative cluster analysis based on HIs identified six groups of rivers classified according to differences in intermittency and variability. A methodology allowing such a classification for ungauged catchments was also tested. Broad‐scale catchment characteristics based on digital elevation, climate, soil and land use data were derived for each long‐term station where these data were available. By using stepwise multiple regression analysis, statistically significant relationships were fitted, linking the three selected hydrological variables (mean annual number of zero‐flow days, predictability and flashiness) to the catchment characteristics. The method provides a means of simplifying the complexity of river systems and is thus useful for river basin management. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   
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Since the 1970s, multiple reconstruction techniques have been proposed and are currently used, to extrapolate and quantify eruptive parameters from sampled tephra fall deposit datasets. Atmospheric transport and deposition processes strongly control the spatial distribution of tephra deposit; therefore, a large uncertainty affects mass derived estimations especially for fall layer that are not well exposed. This paper has two main aims: the first is to analyse the sensitivity to the deposit sampling strategy of reconstruction techniques. The second is to assess whether there are differences between the modelled values for emitted mass and grainsize, versus values estimated from the deposits. We find significant differences and propose a new correction strategy. A numerical approach is demonstrated by simulating with a dispersal code a mild explosive event occurring at Mt. Etna on 24 November 2006. Eruptive parameters are reconstructed by an inversion information collected after the eruption. A full synthetic deposit is created by integrating the deposited mass computed by the model over the computational domain (i.e., an area of 7.5 × 104 km 2). A statistical analysis based on 2000 sampling tests of 50 sampling points shows a large variability, up to 50 % for all the reconstruction techniques. Moreover, for some test examples Power Law errors are larger than estimated uncertainty. A similar analysis, on simulated grain-size classes, shows how spatial sampling limitations strongly reduce the utility of available information on the total grain size distribution. For example, information on particles coarser than ?(?4) is completely lost when sampling at 1.5 km from the vent for all columns with heights less than 2000 m above the vent. To correct for this effect an optimal sampling strategy and a new reconstruction method are presented. A sensitivity study shows that our method can be extended to a wide range of eruptive scenarios including those in which aggregation processes are important. The new correction method allows an estimate of the deficiency for each simulated class in calculated mass deposited, providing reliable estimation of uncertainties in the reconstructed total (whole deposit) grainsize distribution.  相似文献   
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Masonry building aggregates are large parts of the Italian building heritage often designed without respecting seismic criteria. The current seismic Italian code does not foresee a clear calculation method to predict their static nonlinear behaviour. For this reason, in this paper firstly, a simple methodology to forecast the seismic response of masonry aggregates in San Pio delle Camere (L’Aquila, Italy) has been set up starting from the provisions of the Italian Guidelines on Cultural Heritage. The implemented procedure has been calibrated on the results of two FEM structural analysis programs used to investigate three masonry building compounds. As a result, a design chart used to correctly predict the base shear of aggregate masonry units starting from code provisions has been set up. Later on, the large-scale seismic vulnerability and damage appraisal of the inspected historical centre has been done on the basis of a quick methodology, already implemented and experienced by the author in some historical centres of the Campania region. The analysis result was a numerical correlation between vulnerability index and mean damage grade of examined building compounds. In particular, a damage forecast under numerical way has been firstly estimated and then compared with the real one. The post-earthquake scenario has represented an ideal term of comparison for effectively testing the reliability of the employed technique, which should be further extended to other Italian historical centres.  相似文献   
950.
Identifying the provenance of uranium‐rich materials is a critical objective of nuclear forensic analysis. Rare earth element (REE) distributions within uranium ores are well‐established forensic indicators, but quantifying and correlating trace element signatures for U ores to known deposits has thus far involved intricate statistical analyses. This study reports average chondrite normalized (CN)‐REE signatures for important U deposit types worldwide, which are then employed to evaluate U ore paragenesis using a simple linear regression analysis. This technique provides a straightforward method that can aid in determining the deposit type of U ores based on their REE abundances, and combined with other forensic indicators (e.g. radiogenic isotope signatures) can provide essential provenance information for nuclear materials.  相似文献   
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