一种新的量子蚁群优化算法

 针对蚁群算法在求解连续空间优化问题时易于陷入局部最优和收敛速度慢的问题,提出了一种新的基于量子进化的蚁群优化算法。 该算法采用量子比特的概率幅表示蚂蚁当前位置信息;设计了一种新的量子旋转门更新蚂蚁位置, 完成蚂蚁的移动;最后采用量子 非门实现蚂蚁所在位置的变异, 增加位置的多样性。不仅从理论上证明了所提出算法的收敛性,而且通过仿真实验表明该算法可使 搜索空间加倍,比传统的蚁群算法具有更好的种群多样性,更快的收敛速度和全局寻优能力。     

Relationship between topology and functions in metabolic network evolution

What is the relationship between the topological connections among enzymes and their functions during metabolic network evolution? Does this relationship show similarity among closely related organisms? Here we investigated the relationship between enzyme connectivity and functions in metabolic networks of chloroplast and its endosymbiotic ancestor, cyanobacteria (Synechococcus sp. WH8102). Also several other species, including E. coli, Arabidopsis thaliana and Cyanidioschyzon merolae, were used for the comparison. We found that the average connectivity among different functional pathways and enzyme classifications (EC) was different in all the species examined. However, the average connectivity of enzymes in the same functional classification was quite similar between chloroplast and one representative of cyanobacteria, syw. In addition, the enzymes in the highly conserved modules between chloroplast and syw, such as amino acid metabolism, were highly connected compared with other modules. We also discovered that the isozymes of chloroplast and syw often had higher connectivity, corresponded to primary metabolism and also existed in conserved module. In conclusion, despite the drastic re-organization of metabolism in chloroplast during endosymbiosis, the relationship between network topology and functions is very similar between chloroplast and its precursor cyanobacteria, which demonstrates that the relationship may be used as an indicator of the closeness in evolution.     

Overexpression of OsRAA1 promotes flowering and hypocotyls elongation in Arabidopsis

Previously, OsRAA1, an AtFPF1 homologue gene, was found to play an important role in modulating rice root development. In the current study, OsRAA1 was overexpressed in Arabidopsis, and the transgenic plants showed early flowering and elongated hypocotyl phenotypes as compared with the wild-type under white-light conditions. The hypocotyls of transgenic lines were twice as long as those of wild-type plants under red-light conditions but were indistinguishable from those of the wild-type under blue and far-red light and darkness. In addition, the phenotypes of AtFPF1 transgenic lines were similar to those of OsRAA1 transgenic lines. These results suggested that OsRAAI/AtFPF1 protein is involved in regulating flowering time and plays an important role in the inhibition of hypocotyl elongation under continuous red light. The functions were preserved during the evolution.     

基于互补变异算子的自适应差分进化算法

在参数自适应的差分进化算法的基础上,同时采用DE/rand/1和DE/best/2两种具有互补特性的差分变异算子,提出了多种采用不同分配策略的新型差分变异算法.2种变异算子的分配分别采用随机分配、基于种群规模的单调分配、适应性随机分配以及基于种群规模的适应性分配4种策略.基于标准测试函数的数值优化结果表明:双变异模式的自适应差分进化算法总体上明显优于2种标准DE算法.在4种分配策略中,单调分配策略效果最佳.所提出的DE算法利用了DE/rand/1型变异在保持种群多样性方面的优势,并继承了DE/best/2型变异局部收敛速度快的优点,较好地实现了探索与利用的平衡,而且需要人工调节的参数较少,便于在实际中使用.     

医学知识流的诊疗服务架构设计与应用

为了解决医学知识交流匮乏,科室医生之间低效率协同分工诊病的状况,紧密结合医学诊疗服务的"重交流、频更新、使用密集"等特性,确立以知识流、知识获取和知识供应技术作为医学诊疗服务架构的核心模型,并提出知识更新、知识迁移和知识拓展三大知识流操作技术.在比较了医院信息管理与医院知识管理现状基础上,构建了基于知识流的医院诊疗服务架构方式,其重点在于追踪、监测和控制医院医学知识的全流动过程.最后给出了一个男科诊疗实例,分析了男科医学知识流动的全过程.     

基于进化策略的实数域准零相关区序列生成算法

该文提出实数域准零相关区序列的概念,当信道延迟和同步误差之和不超过零相关区长度时,可以较为理想地消除CDM A系统的码间干扰和多址干扰。同时,基于进化策略设计了实数域准零相关区序列的搜索算法,与传统零相关区序列的生成算法相比,该算法可以在全局解空间进行优化搜索,而且生成的序列在序列周期和零相关区长度等参数上较少受到构造方法的限制,更方便于实际应用。     

具有任意次非线性项的演化方程的有理函数积分法

引入了一种求解具有任意次非线性项的演化方程精确解的有理函数积分法,该方法将未知函数的一阶导数展开为未知函数的多项式,通过齐次平衡法确定多项式的次数,然后利用有理函数积分法求解未知函数.通过对Klein-Gordon 方程和广义 Fithugh-Nagumo方程求解,表明所引入的有理函数积分法的有效性与便捷性.     

论青年王阳明的思想演变历程

青年壬阳明的精神生活和内心世界是复杂而曲折的,经历了"遍求百家"、"出入佛老"、"五溺三变"的思想漫游历程.而青年王阳明的思想漫游所体现的实际上是从其少年时期就一直伴随着王阳明的"成圣"追求的心路历程.正是青年王阳明所经历的这种复杂而曲折的思想漫游,不但构成了其早期思想发展的一个重要内容和突出特点,而且对其以后成熟形态的思想格局的形成有着极为重要的影响,对我们解读阳明心学的奥秘也富有启发意义.     

基于并行优进策略的差分进化算法

差分进化算法是一种新颖的进化计算技术,为减少用户选择算法控制参数的盲目性和提高算法收敛速度,设计了一种基于并行优进策略的差分进化算法（DEPES算法）．算法随着搜索过程的进行随机动态调整缩放因子和选取差分进化模式;在进行差分操作的并行运算过程中,利用当前代最优个体产生新的试验向量参与竞争选择过程．几个复杂函数的数值实验结果表明,DEPES算法寻优效率高、收敛速度快、对初值具有很强的鲁棒性、对维数具有较好的适应性,尤其是具有避免局部极小的能力,其优化性能优于标准DE算法．     

生物多样性及其进化中的模糊问题研究

生物多样性是现代生物学研究的热门内容之一.根据现代生物学和古生物学研究成就,就生物多样性概念、生物多样性诞生、生物多样性进化中的模糊问题及解决途径进行了研究.