浅析基于电子商务网络安全PKI技术的角色访问控制模型

文本提出了一种区别于传统自主访问控制策略和强制访问控制策略的RBAC网络安全策略,并提出了RBAC的面向对象模型,实现用户身份认证与访问权限的逻辑分离,且易于控制,既能有效的改进系统安全性能,又极大地减少了权限管理的负担。     

Finding finer functions for partially characterized proteins by protein-protein interaction networks

Based on high-throughput data, numerous algorithms have been designed to find functions of novel proteins. However, the effectiveness of such algorithms is currently limited by some fundamental factors, including (1) the low a-priori probability of novel proteins participating in a detailed function; (2) the huge false data present in high-throughput datasets; (3) the incomplete data coverage of functional classes; (4) the abundant but heterogeneous negative samples for training the algorithms; and (5) the lack of detailed functional knowledge for training algorithms. Here, for partially characterized proteins, we suggest an approach to finding their finer functions based on protein interaction sub-networks or gene expression patterns, defined in function-specific subspaces. The proposed approach can lessen the above-mentioned problems by properly defining the prediction range and functionally filtering the noisy data, and thus can efficiently find proteins’ novel functions. For thousands of yeast and human proteins partially characterized, it is able to reliably find their finer functions (e.g., the translational functions) with more than 90% precision. The predicted finer functions are highly valuable both for guiding the follow-up wet-lab validation and for providing the necessary data for training algorithms to learn other proteins.     

Mechanism for the learning deficits in a mouse model of neurofibromatosis type 1.

Neurofibromatosis type I (NF1) is one of the most common single-gene disorders that causes learning deficits in humans. Mice carrying a heterozygous null mutation of the Nfl gene (Nfl(+/-) show important features of the learning deficits associated with NF1 (ref. 2). Although neurofibromin has several known properties and functions, including Ras GTPase-activating protein activity, adenylyl cyclase modulation and microtubule binding, it is unclear which of these are essential for learning in mice and humans. Here we show that the learning deficits of Nf1(+/-) mice can be rescued by genetic and pharmacological manipulations that decrease Ras function. We also show that the Nf1(+/-) mice have increased GABA (gamma-amino butyric acid)-mediated inhibition and specific deficits in long-term potentiation, both of which can be reversed by decreasing Ras function. Our results indicate that the learning deficits associated with NF1 may be caused by excessive Ras activity, which leads to impairments in long-term potentiation caused by increased GABA-mediated inhibition. Our findings have implications for the development of treatments for learning deficits associated with NF1.     

走出科学教育的现代迷茫

科学与人文之争已历经上百年，在以知识为主导的新时代，科学教育倍爱世人的青睐。科学教育既是科学人才的产床，也是人性异化等扼杀人类文明、威胁人类生存的制造之所。科学教育必须走上与人文教育相结合的道路才能走出现代迷惘，并最终使科学真正带给人类以福祉而不是灾难。     

反思的现代性与技术理性的解构--海德格尔和福柯论现代技术问题

海德格尔和福柯对于现代技术问题的思考属于某种反思的现代性立场：无论前者对机械技术的本质的追问，还是后者对自我技术的谱系学分析，都没有简单地否定现代技术，而是揭示了现代技术的解蔽和遮蔽双重性。这样的立场告诉我们：面对现代技术的极度张扬，哲学应该坚持一种保守主义姿态，应该在更新的意义上恢复经验的地位。     

从民营企业发展中存在的问题看会计监管

由于中国民营企业本身成长于国有大中型企业和外资企业的夹缝中,先天资本积累不足,后天管理条件欠缺,导致其发展困难重重,面临严峻的生存压力。基于此,提出了我国民营企业会计监管体系的设计与构想。     

系统结构模型分部的底层要素法

本文从系统的底层要素出发，提出并证明了底层要素存在性、底层要素后果集并集的完全性以及它们在同一部分的充分必要条件，由此导出了系统结构模型分部的算法，实际应用进一步说明了这一方法的有效性。     

稀土高碳当量灰口铸铁组织与性能的研究

本文研究了利用稀土合金改善高碳当量灰口铸铁质量的可能性,稀土合金对高碳当 量灰口铸铁组织和性能影响的规律,以及稀土夹杂物在铸铁各相中分布的规律．发现了 稀土合金加入量与铸铁的机械性能之间明显的对应关系——“双峰值效应”。对稀土高 碳当量灰口铸铁的某些高温机械、物理、化学性能进行了研究。结果表明稀土合金加入 到高碳当量灰口铸铁中以后能净化铁水,改善组织,并提高其性能．     

神经网络在橡胶硫化温度预测中的应用

本文针对难以通过在线测温实现等效硫化控制的情况,在确定硫化条件的直接测温实验基础上,提出了用神经网络模型预测实际生产过程中硫化制品内部温度的方法．在该方法中将所测温度值作为样本提供给神经网络学习,温度采集时刻及易测外部温度作为网络输入,输出值则是在硫化时制品难测温点处不同时刻的内温．神经网络通过学习取得了良好的效果,网络输出的温度值将成为等效硫化计算和硫化质量智能控制的有价值的依据．     

半刚接非线性钢框架的优化设计

介绍了半刚性梁柱节点的特性和Frye—Morris模型，列出了考虑P-△效应的半刚性连接构件的单元刚度，将遗传算法应用于钢框架的优化设计中．编制了程序GASEF，进行了算例计算，得到了一些有价值的结论．