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Haloarchaea have evolved to thrive in hypersaline environments. Haloferax volcanii is of particular interest due to its genetic tractability; however, few in vivo reporters exist for halophiles. Haloarchaeal proteins evolved characteristics that promote proper folding and function at high salt concentrations, but many mesophilic reporter proteins lack these characteristics. Mesophilic proteins that acquire salt-stabilizing mutations, however, can lead to proper function in haloarchaea. Using laboratory-directed evolution, we developed and demonstrated an in vivo luciferase that functions in the hypersaline cytosol of H. volcanii.
相似文献A review of LCA process datasets is an important element of quality assurance for databases and for other systems to provide LCA datasets. Somewhat surprisingly, a broadly accepted and applicable set of criteria for a review of LCA process datasets was lacking so far. Different LCA databases and frameworks are proposing and using different criteria for reviewing datasets. To close this gap, a set of criteria for reviewing LCA dataset has been developed within the Life Cycle Initiative.
MethodsPrevious contributions to LCA dataset review have been analysed for a start, from ISO and various LCA databases. To avoid somewhat arbitrary review criteria, four basic rules are proposed which are to be fulfilled by any dataset. Further, concepts for assessing representativeness and relevance are introduced into the criteria set from established practices in statistics and materiality. To better structure the criteria and to ease their application, they are grouped into clusters. A first version of the developed review criteria was presented in two workshops with database providers and users on different levels of experience, and draft versions of the criteria were shared within the initiative. The current version of the criteria reflects feedback received from various stakeholders and has been applied and tested in a review for newly developed datasets in Brazil, Malaysia and Thailand.
Results and discussionOverall, 14 criteria are proposed, which are organised in clusters. The clusters are goal, model, value, relevance and procedure. For several criteria, a more science-based definition and evaluation is proposed in comparison to ‘traditional’ LCA. While most of the criteria depend on the goal and scope of dataset development, a core set of criteria are seen as essential and independent from specific LCA modelling. For all the criteria, value scales are developed, typically using an ordinal scale, following the pedigree approach.
ConclusionsReview criteria for LCI datasets are now defined based on a stringent approach. They aim to be globally acceptable, considering also database interoperability and database management aspects, as well as feedback received from various stakeholders, and thus close an important gap in LCA dataset quality assurance. The criteria take many elements of already existing criteria but are the first to fully reflect the implications of the ISO data quality definition, and add new concepts for representativeness and relevance with the idea to better reflect scientific practice outside of the LCA domain. A first application in a review showed to be feasible, with a level of effort similar to applying other review criteria. Aspects not addressed yet are the review procedure and the mutual recognition of dataset reviews, and their application for a very high number of datasets.
相似文献Reef monitoring programmes often focus on limited sites, predominantly on reef slope areas, which do not capture compositional variability across zones. This study assessed spatial and temporal changes in hard coral cover at four hierarchical spatial scales. ~ 55,000, geo-referenced photoquadrats were collected annually from 2002 to 2018 and analysed using artificial intelligence for 31 sites across reef flat and reef slope zones on Heron Reef, Southern Great Barrier Reef, Australia. Trends in hard coral cover were examined at three spatial scales: (1) “reef scale”, all data; (2) “geomorphic zone scale”—north/south reef slope, inner/outer reef flat; and (3) “site scale”—31 sites. Coral cover trajectories were also examined at: (4) “sub-site scale”—sub-division of sites into 567 sub-sites, to estimate variability in coral cover trajectories via spatial statistical modelling. At reef scale coral cover increased over time to 25.6 ± 0.4 SE % in 2018 but did not recover following disturbances caused by disease (2004–2008), cyclonic conditions (2009) or severe storms (2015) to the observed pre-disturbance level (44.0 ± 0.7 SE %) seen in 2004. At geomorphic zone scale, the reef slope had significantly higher coral cover than the reef flat. Trends of decline and increase were visible in the slope zones, and the southern slope recovered to pre-decline levels. Variable coral cover trends were visible at site scale. Furthermore, sub-site spatial modelling captured eight years of coral recovery that occurred at different times and magnitudes across the four geomorphic zones, effectively estimating variability in the trajectory of the reef’s coral community. Derived spatial predictions for the entire reef show patchy coral recovery, particularly on the southern slope, and that recovery hotspots are distributed across the reef. These findings suggest that to fully understand and interpret coral decline or recovery on a reef, more accurate assessment can be achieved by examining sites distributed within different geomorphic zones to capture variation in exposure, depth and consolidation.
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