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针对泵站普遍因存在供需不平衡、管理差等而造成大量能源浪费的问题,对泵站系统扬程、效率偏差情况进行分析,明确了系统供需间的差异情况,利用灰色关联度法,对泵站目标电耗的影响因素进行关联度分析,确定了扬程、效率、流量3个影响因素关联度大小。建立以单位产量电耗最小为目标函数的优化调度模型,并结合泵站实际情况,运用人工蜂群算法(Artificial Bee Colony,ABC)进行寻优计算,得出运行优化方案,得到系统在不同流量、扬程需求下的最佳开机台数及调速比,表明了ABC算法在泵站优化的实用价值。 相似文献
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Pancreatic ductal adenocarcinoma (PDAC) is a highly fatal disease with a 5-year survival rate of less than 10% following diagnosis. The aggressive and invasive properties of pancreatic cancer tumors coupled with poor diagnostic options contribute to the high mortality rate since most patients present with late-stage disease. Accordingly, PDAC is linked to the highest rate of cancer-associated venous thromboembolic disease of all solid tumor malignancies. However, in addition to promoting clot formation, recent studies suggest that the coagulation system in PDAC mediates a reciprocal relationship, whereby coagulation proteases and receptors promote PDAC tumor progression and dissemination. Here, upregulation of tissue factor (TF) by tumor cells can drive local generation of the central coagulation protease thrombin that promotes cell signaling activity through protease-activated receptors (PARs) expressed by both tumor cells and multiple stromal cell subsets. Moreover, the TF-thrombin-PAR1 signaling axis appears to be a major mechanism of cancer progression in general and PDAC in particular. Here, we summarize the current literature regarding the role of PAR1 in PDAC and review possibilities for pharmacologically targeting PAR1 as a PDAC therapeutic approach. 相似文献
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In recent years, artificial intelligence (AI) is being increasingly utilised in disaster management activities. The public is engaged with AI in various ways in these activities. For instance, crowdsourcing applications developed for disaster management to handle the tasks of collecting data through social media platforms, and increasing disaster awareness through serious gaming applications. Nonetheless, there are limited empirical investigations and understanding on public perceptions concerning AI for disaster management. Bridging this knowledge gap is the justification for this paper. The methodological approach adopted involved: Initially, collecting data through an online survey from residents (n = 605) of three major Australian cities; Then, analysis of the data using statistical modelling. The analysis results revealed that: (a) Younger generations have a greater appreciation of opportunities created by AI-driven applications for disaster management; (b) People with tertiary education have a greater understanding of the benefits of AI in managing the pre- and post-disaster phases, and; (c) Public sector administrative and safety workers, who play a vital role in managing disasters, place a greater value on the contributions by AI in disaster management. The study advocates relevant authorities to consider public perceptions in their efforts in integrating AI in disaster management. 相似文献
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计算机在酶工程中的应用使得酶的序列空间探索度不断被扩大。随着不同分子力场参数的建立,涌现出诸多以计算分子能量为基础的算法,并被用于酶的催化活性、稳定性、底物特异性等的改造与筛选。伴随计算机硬件的提升与算法的优化,从头设计全新功能的人工酶取得成功并得以发展。近年来,人工智能在蛋白质结构预测上不断获得突破,同时也被应用到酶的设计中。介绍了分子力场基础和酶设计与筛选的算法,重点阐述了从头设计的方法和成功案例,以及机器学习设计酶的流程和最新的研究进展,展望了人工智能在酶工程领域的未来发展,为酶的改造与全新功能的生物催化剂的设计助力。 相似文献
7.
Zihao Chen Long Hu Bao-Ting Zhang Aiping Lu Yaofeng Wang Yuanyuan Yu Ge Zhang 《International journal of molecular sciences》2021,22(7)
Aptamers are short single-stranded DNA, RNA, or synthetic Xeno nucleic acids (XNA) molecules that can interact with corresponding targets with high affinity. Owing to their unique features, including low cost of production, easy chemical modification, high thermal stability, reproducibility, as well as low levels of immunogenicity and toxicity, aptamers can be used as an alternative to antibodies in diagnostics and therapeutics. Systematic evolution of ligands by exponential enrichment (SELEX), an experimental approach for aptamer screening, allows the selection and identification of in vitro aptamers with high affinity and specificity. However, the SELEX process is time consuming and characterization of the representative aptamer candidates from SELEX is rather laborious. Artificial intelligence (AI) could help to rapidly identify the potential aptamer candidates from a vast number of sequences. This review discusses the advancements of AI pipelines/methods, including structure-based and machine/deep learning-based methods, for predicting the binding ability of aptamers to targets. Structure-based methods are the most used in computer-aided drug design. For this part, we review the secondary and tertiary structure prediction methods for aptamers, molecular docking, as well as molecular dynamic simulation methods for aptamer–target binding. We also performed analysis to compare the accuracy of different secondary and tertiary structure prediction methods for aptamers. On the other hand, advanced machine-/deep-learning models have witnessed successes in predicting the binding abilities between targets and ligands in drug discovery and thus potentially offer a robust and accurate approach to predict the binding between aptamers and targets. The research utilizing machine-/deep-learning techniques for prediction of aptamer–target binding is limited currently. Therefore, perspectives for models, algorithms, and implementation strategies of machine/deep learning-based methods are discussed. This review could facilitate the development and application of high-throughput and less laborious in silico methods in aptamer selection and characterization. 相似文献
8.
无刷直流电机(Brushless DC Motor,BLDCM)因具有寿命长、体积小、输出转矩大和功率密度高等优点,广泛应用于航空航天等领域。但使用传感器获取转子位置信号,存在着制造难度大、易受干扰、难以在高低温环境下工作和增加重量等缺点,极大地限制了其更加广泛应用。为很好解决此问题,本文介绍了无位置传感器BLDCM控制的反电动势法、状态观测器法和人工智能法,并针对反电动势法存在的零速或低速时无法自启动的问题,介绍了在低速时转子位置检测和如何加速到闭环控制状态等方法。 相似文献
9.
云计算、大数据、5G通信等技术的快速发展,有力的促进了计算机网络在多个领域的普及和使用,人们已经进入到了“互联网+”时代,实现了工作、生活和学习的数字化、智能化和共享化。计算机网络在为人们提供各种便利服务的同时也面临着许多的安全威胁,比如木马、病毒等,不法分子攻击网络数据中心,破坏用户服务终端及服务器,为人们带来严重的威胁。网络安全学者或企业机构也提出了许多安全防御技术,比如入侵检测技术、深度包过滤技术、防火墙技术、数据加密技术等,一定程度上提高了网络安全防御的能力,但是随着互联网数据流量的增多,需要引入更加先进的人工智能技术,以便能够快速的采集、分析网络数据流,确定数据流中是否存在病毒或木马,以便及时的对其进行查杀,进一步提高网络安全防御的主动性、积极性 相似文献
10.
赣南某钨矿矿体上下盘岩体多为板岩,结构面发育且岩体破碎,在留矿法放矿过程中,上盘岩体暴露后在次生应力的影响下极易发生板裂状滑落或溃曲破坏,使得采幅难以控制。针对此问题,提出了普通留矿法、静态留矿法、散体人工矿柱+锚固留矿法3种回采方法。通过分析上下盘板裂状围岩随开采过程的位移变形情况,最终选择散体人工矿柱+锚固留矿法作为试验采场回采方法。基于正交试验原理,进行了相似材料配比试验,最终确定的材料配比为ω(沙)∶ω(石膏)∶ω(水)=5.0∶1.0∶1.2。相似模拟试验结果表明:采高较小时,锚杆支护对控制围岩的稳定是有效的,然而随着采高的增大,采场出现应力集中,锚杆逐渐失去了作用,因此仅对围岩进行锚固支护并不足以改善地压环境;散体人工矿柱+锚固留矿法利用人工矿柱减小了回采跨度,提高了整个采场的稳定性。对比模拟结果可知,其上下盘及顶板的位移量远小于其他2种回采方法。 相似文献