首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   14559篇
  免费   913篇
  国内免费   2篇
  2021年   146篇
  2019年   103篇
  2018年   144篇
  2017年   116篇
  2016年   217篇
  2015年   348篇
  2014年   377篇
  2013年   901篇
  2012年   707篇
  2011年   667篇
  2010年   378篇
  2009年   408篇
  2008年   635篇
  2007年   626篇
  2006年   627篇
  2005年   625篇
  2004年   663篇
  2003年   629篇
  2002年   600篇
  2001年   561篇
  2000年   543篇
  1999年   447篇
  1998年   187篇
  1997年   169篇
  1996年   155篇
  1995年   128篇
  1994年   140篇
  1993年   137篇
  1992年   336篇
  1991年   315篇
  1990年   319篇
  1989年   286篇
  1988年   244篇
  1987年   247篇
  1986年   224篇
  1985年   196篇
  1984年   144篇
  1983年   148篇
  1982年   121篇
  1981年   120篇
  1980年   92篇
  1979年   123篇
  1978年   96篇
  1977年   89篇
  1976年   90篇
  1975年   80篇
  1974年   99篇
  1973年   104篇
  1971年   69篇
  1969年   67篇
排序方式: 共有10000条查询结果,搜索用时 15 毫秒
11.
Whole cells of Chlorella vulgaris and Clostridium butyricum were co-immobilized in 2% agar gel. NADP was suitable as an electron carrier. The rate of hydrogen evolution increased with increasing NADP concentration. The optimum conditions for hydrogen evolution were pH 7.0 and 37°C. The immobilized C. vulgaris-NADP-immobilized Cl. butyricum system continuously evolved hydrogen at a rate of 0.29–1.34 μmol/h per mg Chl for 6 days. On the other hand, the system without NADP evolved only a trace amount of hydrogen.  相似文献   
12.
13.
14.
In order to control visually-guided voluntary movements, the central nervous system (CNS) must solve the following three computational problems at different levels: (1) determination of a desired trajectory in the visual coordinates, (2) transformation of the coordinates of the desired trajectory to the body coordinates and (3) generation of motor command. In this paper, the second and the third problems are treated at computational, representational and hardware levels of Marr. We first study the problems at the computational level, and then propose an iterative learning scheme as a possible algorithm. This is a trial and error type learning such as repetitive training of golf swing. The amount of motor command needed to coordinate activities of many muscles is not determined at once, but in a step-wise, trial and error fashion in the course of a set of repetitions. Actually, the motor command in the (n+1)-th iteration is a sum of the motor command in then-th iteration plus two modification terms which are, respectively, proportional to acceleration and speed errors between the desired trajectory and the realized trajectory in then-th iteration. We mathematically formulate this iterative learning control as a Newton-like method in functional spaces and prove its convergence under appropriate mathematical conditions with use of dynamical system theory and functional analysis. Computer simulations of this iterative learning control of a robotic manipulator in the body or visual coordinates are shown. Finally, we propose that areas 2, 5, and 7 of the sensory association cortex are possible sites of this learning control. Further we propose neural network model which acquires transformation matrices from acceleration or velocity to motor command, which are used in these schemes.  相似文献   
15.
The position of the N terminus of myosin light chain 1 (LC1) and myosin light chain 2 (LC2) of rabbit skeletal muscle was mapped on the myosin head with a monoclonal antibody (SI304), which recognized the amino acid sequence N-trimethylalanyl-prolyl-lysyl-lysyl at the N terminus of LC1 and LC2. The complex of the antibody and myosin was observed by electron microscopy. By selective cleavage of the N terminus of LC1 or LC2 with papain or chymotrypsin, the position of the N terminus of LC1 and LC2 was determined separately. The N terminus of LC2 is located at the head-rod junction. The N terminus of LC1 is 11 nm (+/- 3 nm, standard deviation) from the head-rod junction. This position is near the actin-binding site of the myosin head.  相似文献   
16.
17.
18.
19.
We have recently reported the presence of IgG which has a potent inhibitory activity against IL-1 alpha in some sera from patients with rheumatoid arthritis. The mechanism of this inhibition by IgG against IL-1 alpha is now elucidated. IgG with IL-1 alpha-inhibitory activity inhibited the binding of 125I-IL-1 alpha to receptors on rheumatoid synovial cells. In addition, preincubation of synovial cells with the inhibitory IgG did not block the binding of 125I-IL-1 alpha to receptors, suggesting a direct interaction between IgG and IL-1 alpha. To examine which region of the IgG, namely Fab or Fc region, has the inhibitory activity, the IgG was digested with papain, and Fab and Fc fragments were purified. Fab fragments, but not Fc fragments, inhibited both IL-1 alpha-induced thymocyte-proliferation and the binding of 125I-IL-1 alpha to receptors. We further demonstrated that the inhibitory IgG which was bound to protein A Sepharose could bind a significant amount of 125I-IL-1 alpha, whereas only a negligible binding of the radiolabeled ligand was detected when IgG without the inhibitory activity was used as control. Moreover, the binding of 125I-IL-1 alpha to IgG with the inhibitory activity was clearly blocked by Fab fragments of IgG having the inhibitory activity. Finally, affinity-purified IgG over an IL-alpha affinity column showed approximately 100-fold more potent inhibitory activity on IL-1 alpha-induced thymocyte proliferation compared with untreated IgG. From these results, we conclude that IgG molecules with IL-1-alpha-inhibitory activity are neutralizing autoantibodies against IL-1 alpha.  相似文献   
20.
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号