Influencer-defaulter mutation-based optimization algorithms for predicting electricity prices

Efficient electricity price forecasting plays a significant role in our society. In this paper, a novel influencer-defaulter mutation (IDM) mutation operator has been proposed. The IDM operator has been combined with six well-known optimization algorithms to create mutated optimization algorithms whose performance has been tested on twenty-four standard benchmark functions. Further, the artificial neural network is integrated with mutated optimization algorithms to solve the electricity price prediction problem. The policymakers can identify appropriate variables based on the predicted prices to help future market planning. The statistical results prove the efficacy of the IDM operator on the recent optimization algorithms.     

盖子环替换及定点突变提高菜豆环氧化物水解酶对邻甲基苯基缩水甘油醚的催化性能

菜豆环氧化物水解酶1和2（PvEH1、PvEH2）能够动力学拆分外消旋邻甲基苯基缩水甘油醚（rac-oMGE），从而保留(R)-oMGE。基于对PvEH1和PvEH2结构的同源模拟和分析，发现二者分子中的盖子环差异较大，故本文选择盖子环作为研究目标。经融合聚合酶链式反应（FPCR），获得了PvEH2的盖子环区域被PvEH1对应区域替换的杂合酶Pv2Pv1。用全细胞酶E. coli/pv2pv1催化rac-oMGE，当(S)-oMGE刚好水解完全时，产物(S)-3-邻甲苯基-1,2-丙二醇（(S)-oTPD）的ee_p由PvEH2的58.3%提高至75.5%。为进一步提高酶的性质，在Pv2Pv1中选取11个氨基酸位点进行丙氨酸(A)突变，获得最优突变子E. coli/pv2pv1^K176A，活性为E. coli/pv2pv1（4.2U/g）的2.1倍，且当S构型的底物刚好完全水解时，(S)-oTPD的ee_p进一步提高为80.3%。分子对接分析发现，盖子环替换和K176位点突变为A，均使(R)-oMGE环氧环中的C_α更易受到酶中D101位点的攻击。利用E. coli/pv2pv1^K176A催化150mmol/L rac-oMGE水解制备(R)-oMGE（ee_s＞99%）和(S)-oTPD（ee_p=80.4%），二者的产率Y_S和Y_P分别为32.7%和60.1%，时空产率STY_S和STY_P为1.6g/(L·h)和3.3g/(L·h)。本实验为改善EH的催化性质提供了一种有效策略。     

基于变异算子和邻域值自适应的MOEA/D算法

基于分解的多目标进化算法（MOEA/D）在解决多目标问题时，具有简单有效的特点。但多数MOEA/D采用固定的控制参数，导致全局搜索能力差，难以平衡收敛性和多样性。针对以上问题提出一种基于变异算子和邻域值自适应的多目标优化算法。该算法根据种群中个体适应度值的分散或集中程度进行判断，并据此对变异算子进行自适应的调节，从而增强算法的全局搜索能力；根据进化所处的阶段以及个体适应度值的集中程度，自适应地调节邻域值大小，保证每个个体在不同的进化代数都有一个邻域值大小；在子问题邻域中，统计子问题对应个体的被支配数，通过判断被支配数是否超过设定的上限，来决定是否将Pareto支配关系也作为邻域内判断个体好坏的准则之一。将提出的算法与传统的MOEA/D在标准测试问题上进行对比。实验结果表明，提出的算法求得的解集具有更好的收敛性和多样性，在求解性能上具有一定的优势。     

Stationary and Progressive Phenotypes Caused by the p.G90D Mutation in Rhodopsin Gene

Mutations in rhodopsin gene (RHO) are a frequent cause of retinitis pigmentosa (RP) and less often, congenital stationary night blindness (CSNB). Mutation p.G90D has previously been associated with CSNB based on the examination of one family. This study screened 60 patients. Out of these 60 patients, 32 were affected and a full characterization was conducted in 15 patients. We described the clinical characteristics of these 15 patients (12 male, median age 42 years, range 8–71) from three families including visual field (Campus Goldmann), fundus autofluorescence (FAF), optical coherence tomography (OCT) and electrophysiology. Phenotypes were classified into four categories: CSNB (N = 3, 20%) sector RP (N = 3, 20%), pericentral RP (N = 1, 6.7%) and classic RP (N = 8, 53.3% (8/15)). The phenotypes were not associated with family, sex or age (Kruskal–Wallis, p > 0.05), however, cystoid macular edema (CME) was observed only in one family. Among the subjects reporting nyctalopia, 69% (22/32) were male. The clinical characteristics of the largest p.G90D cohort so far showed a large frequency of progressive retinal degeneration with 53.3% developing RP, contrary to the previous report.     

An improved cuckoo search algorithm and its application in vibration fault diagnosis for a hydroelectric generating unit

This article presents an improved cuckoo search (ICS) algorithm based on the parametric adaptation mechanism and non-uniform mutation. In the ICS algorithm, the biased random walk operator is modified to take advantage of the neighbourhood information of the current solution, and then the control parameters of step size, discovery probability and scaling factor are directly integrated into the optimized problems. Meanwhile, the non-uniform mutation operation is used to adaptively tune the search step of the current optimal solution. To evaluate the feasibility and efficiency of the presented algorithm, three groups of benchmark test functions are employed to perform the validation analysis. Subsequently, to diagnose the vibration fault of a hydroelectric generating unit, a combinational model is built, which combines ICS with a back-propagation neural network (ICSBP). The experimental results indicate that ICS is competitive on the optimization problems, and the ICSBP approach can effectively improve the accuracy of vibration fault diagnosis for a hydroelectric generating unit.     

New Insights into the Pathogenesis of Systemic Mastocytosis

Mastocytosis is a type of myeloid neoplasm characterized by the clonal, neoplastic proliferation of morphologically and immunophenotypically abnormal mast cells that infiltrate one or more organ systems. Systemic mastocytosis (SM) is a more aggressive variant of mastocytosis with extracutaneous involvement, which might be associated with multi-organ dysfunction or failure and shortened survival. Over 80% of patients with SM carry the KIT D816V mutation. However, the KIT D816V mutation serves as a weak oncogene and appears to be a late event in the pathogenesis of mastocytosis. The management of SM is highly individualized and was largely palliative for patients without a targeted form of therapy in past decades. Targeted therapy with midostaurin, a multiple kinase inhibitor that inhibits KIT, has demonstrated efficacy in patients with advanced SM. This led to the recent approval of midostaurin by the United States Food and Drug Administration and European Medicines Agency. However, the overall survival of patients treated with midostaurin remains unsatisfactory. The identification of genetic and epigenetic alterations and understanding their interactions and the molecular mechanisms involved in mastocytosis is necessary to develop rationally targeted therapeutic strategies. This review briefly summarizes recent developments in the understanding of SM pathogenesis and potential treatment strategies for patients with SM.     

Some Molecular and Cellular Stress Mechanisms Associated with Neurodegenerative Diseases and Atherosclerosis

Chronic stress is a combination of nonspecific adaptive reactions of the body to the influence of various adverse stress factors which disrupt its homeostasis, and it is also a corresponding state of the organism’s nervous system (or the body in general). We hypothesized that chronic stress may be one of the causes occurence of several molecular and cellular types of stress. We analyzed literary sources and considered most of these types of stress in our review article. We examined genes and mutations of nuclear and mitochondrial genomes and also molecular variants which lead to various types of stress. The end result of chronic stress can be metabolic disturbance in humans and animals, leading to accumulation of reactive oxygen species (ROS), oxidative stress, energy deficiency in cells (due to a decrease in ATP synthesis) and mitochondrial dysfunction. These changes can last for the lifetime and lead to severe pathologies, including neurodegenerative diseases and atherosclerosis. The analysis of literature allowed us to conclude that under the influence of chronic stress, metabolism in the human body can be disrupted, mutations of the mitochondrial and nuclear genome and dysfunction of cells and their compartments can occur. As a result of these processes, oxidative, genotoxic, and cellular stress can occur. Therefore, chronic stress can be one of the causes forthe occurrence and development of neurodegenerative diseases and atherosclerosis. In particular, chronic stress can play a large role in the occurrence and development of oxidative, genotoxic, and cellular types of stress.     

一种无线网络优化中挖掘LTE小区场景突变的方法研究

研究了一种检测无线网络优化中挖掘LTE小区场景突变的方法，通过筛选过滤出场景突变的LTE小区数据集，分析确认是否由于某些性能指标或者参数原因而导致的小区场景突变，最终挖掘得到发生场景突变的LTE小区。     

A directional mutation operator for differential evolution algorithms

Differential evolution (DE) is widely studied in the past decade. In its mutation operator, the random variations are derived from the difference of two randomly selected different individuals. Difference vector plays an important role in evolution. It is observed that the best fitness found so far by DE cannot be improved in every generation. In this article, a directional mutation operator is proposed. It attempts to recognize good variation directions and increase the number of generations having fitness improvement. The idea is to construct a pool of difference vectors calculated when fitness is improved at a generation. The difference vector pool will guide the mutation search in the next generation once only. The directional mutation operator can be applied into any DE mutation strategy. The purpose is to speed up the convergence of DE and improve its performance. The proposed method is evaluated experimentally on CEC 2005 test set with dimension 30 and on CEC 2008 test set with dimensions 100 and 1000. It is demonstrated that the proposed method can result in a larger number of generations having fitness improvement than classic DE. It is combined with eleven DE algorithms as examples of how to combine with other algorithms. After its incorporation, the performance of most of these DE algorithms is significantly improved. Moreover, simulation results show that the directional mutation operator is helpful for balancing the exploration and exploitation capacity of the tested DE algorithms. Furthermore, the directional mutation operator modifications can save computational time compared to the original algorithms. The proposed approach is compared with the proximity based mutation operator as both are claimed to be applicable to any DE mutation strategy. The directional mutation operator is shown to be better than the proximity based mutation operator on the five variants in the DE family. Finally, the applications of two real world engineering optimization problems verify the usefulness of the proposed method.     

An improved partheno genetic algorithm for multi-objective economic dispatch in cascaded hydropower systems

The multi-objective economic dispatch (MOED) problem in cascaded hydropower systems is a complicated nonlinear optimization problem with a group of complex constraints. In this paper, an improved partheno genetic algorithm (IPGA) for resolving the MOED problem in hydropower energy systems based on the non-uniform mutation operator is proposed. In the new algorithm, the crossover operator is removed and only mutation operation is made, which makes it simpler than GA in the genetic operations and not generate invalid offspring during evolution. With the help of incorporating greedy selection idea into the non-uniform mutation operator, IPGA searches the solution space uniformly at the early stage and very locally at the later stage, which makes it avoid the random blind jumping and stay at the promising solution areas. Finally, the proposed algorithm is applied to a realistic hydropower energy system with two giant scale cascaded hydropower plants in China. Compared with other algorithms, the results obtained using IPGA verify its superiority in both efficiency and precision.