Self-adaptive simulated binary crossover for real-parameter optimization

Simulated binary crossover (SBX) is a real-parameter recombinationoperator which is commonly used in the evolutionary algorithm (EA) literature. The operatorinvolves a parameter which dictates the spread of offspring solutionsvis-a-vis that of the parent solutions. In all applications of SBX sofar, researchers have kept a fixed value throughout a simulation run. In this paper, we suggest a self-adaptive procedure of updating theparameter so as to allow a smooth navigation over the functionlandscape with iteration. Some basic principles of classicaloptimization literature are utilized for this purpose. The resultingEAs are found to produce remarkable and much better results comparedto the original operator having a fixed value of the parameter. Studieson both single and multiple objective optimization problems are madewith success

Identification and Disruption of Sperm-Specific Angiotensin Converting Enzyme-3 (ACE3) in Mouse

Background: IZUMO1 is the only sperm protein which is proven to be essential for sperm-egg fusion. However, the IZUMO1 is a structurally simple protein with single Ig domain and seems not to include either a ‘‘fusogenic peptide’ ’ or a fusion machinery domain. This led us to assume the existence of an IZUMO1-interacting protein(s) which makes a functional fusion machine interacting with IZUMO1. Methodology/Principal Findings: We produced a transgenic mouse line which expresses His-tagged IZUMO1 in the Izumo1 2/2 genetic background. After solubilization of sperm membranes, we purified His-tagged IZUMO1 using anti-His affinity chromatography and found a protein that interacts with IZUMO1. After being separated on SDS-PAGE gel, the IZUMO1-interacting protein was subjected to LC-MS/MS analysis and from the partial fragments, we identified the protein as ACE3. We raised the antibody against ACE3 and found that ACE3 is localized on the acrosomal cap area as in the case of IZUMO1. However, ACE3 disappeared from sperm after acrosome reaction while IZUMO1 remained on sperm. In order to investigate the role of ACE3 in vivo, we generated Ace3-deficient mice by homologous recombination and examined the fertilizing ability of the males. Unexpectedly, the male mice showed no defect in fertilizing ability in in vivo or in an in vitro fertilization system. Conclusions/Significance: We identified an IZUMO1-interacting protein in sperm, which we identified as testis specific AC

Mirtazapine has a therapeutic potency in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced mice model of Parkinson’s disease

Background: Mirtazapine, a noradrenergic and specific serotonergic antidepressant (NaSSA), shows multiple pharmacological actions such as inhibiting presynaptic α2 noradrenaline receptor (NAR) and selectively activating 5-hydroxytriptamine (5-HT) 1A receptor (5-HT1AR). Mirtazapine was also reported to increase dopamine release in the cortical neurons with 5-HT dependent manner. To examine whether mirtazapine has a therapeutic potency in Parkinson’s disease (PD), we examined this compound in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated mice model of PD. Results: Male C57BL/6 mice were subjected to MPTP treatment to establish a PD model. Mirtazapine was administered once a day for 3 days after MPTP treatment. MPTP-induced motor dysfunction, assessed by beam-walking and rota-rod tests, was significantly improved by administration of mirtazapine. Biochemical examinations by high performance liquid chromatography and western blot analysis suggested mirtazapine facilitated utilization of dopamine by increasing turnover and protein expression of transporters, without affecting on neurodegenerative process by MPTP. These therapeutic effects of mirtazapine were reduced by administration of WAY100635, an inhibitor for 5HT1AR, or of clonidine, a selective agonist for α2-NAR, or of prazosin, an inhibitor for α1-NAR, respectively. Conclusion: Our results showed mirtazapine had a therapeutic potency against PD in a mouse model. Because PD patients sometimes show depression together, it will be a useful drug for a future PD treatment

Continuous Flow Synthesis of ZSM-5 Zeolite on the Order of Seconds

Zeolites have typically been synthesized via hydrothermal treatment, a process designed to artificially mimic the geological formation conditions of natural zeolites. This synthesis route, typically carried out in batch reactors like autoclaves, takes a time so long (typically, on the order of days) that the crystallization of zeolites had long been believed to be very slow in nature. Long periods of hydrothermal treatment also cause a burden on both energy efficiency and operational costs. Recently, we have reported the ultrafast syntheses of a class of industrially important zeolites within several minutes.[1,2] Further shortening the crystallization time to the order of seconds would be a great challenge but can significantly benefit the mass product of zeolites as well as the fundamental understanding of the crystallization mechanism

Large-scale analysis of full-length cDNAs from the tomato (Solanum lycopersicum) cultivar Micro-Tom, a reference system for the Solanaceae genomics

<p>Abstract</p> <p>Background</p> <p>The Solanaceae family includes several economically important vegetable crops. The tomato (<it>Solanum lycopersicum</it>) is regarded as a model plant of the Solanaceae family. Recently, a number of tomato resources have been developed in parallel with the ongoing tomato genome sequencing project. In particular, a miniature cultivar, Micro-Tom, is regarded as a model system in tomato genomics, and a number of genomics resources in the Micro-Tom-background, such as ESTs and mutagenized lines, have been established by an international alliance.</p> <p>Results</p> <p>To accelerate the progress in tomato genomics, we developed a collection of fully-sequenced 13,227 Micro-Tom full-length cDNAs. By checking redundant sequences, coding sequences, and chimeric sequences, a set of 11,502 non-redundant full-length cDNAs (nrFLcDNAs) was generated. Analysis of untranslated regions demonstrated that tomato has longer 5'- and 3'-untranslated regions than most other plants but rice. Classification of functions of proteins predicted from the coding sequences demonstrated that nrFLcDNAs covered a broad range of functions. A comparison of nrFLcDNAs with genes of sixteen plants facilitated the identification of tomato genes that are not found in other plants, most of which did not have known protein domains. Mapping of the nrFLcDNAs onto currently available tomato genome sequences facilitated prediction of exon-intron structure. Introns of tomato genes were longer than those of Arabidopsis and rice. According to a comparison of exon sequences between the nrFLcDNAs and the tomato genome sequences, the frequency of nucleotide mismatch in exons between Micro-Tom and the genome-sequencing cultivar (Heinz 1706) was estimated to be 0.061%.</p> <p>Conclusion</p> <p>The collection of Micro-Tom nrFLcDNAs generated in this study will serve as a valuable genomic tool for plant biologists to bridge the gap between basic and applied studies. The nrFLcDNA sequences will help annotation of the tomato whole-genome sequence and aid in tomato functional genomics and molecular breeding. Full-length cDNA sequences and their annotations are provided in the database KaFTom <url>http://www.pgb.kazusa.or.jp/kaftom/</url> via the website of the National Bioresource Project Tomato <url>http://tomato.nbrp.jp</url>.</p

Evolutionary MultiObjective Optimisation with a Hybrid Representation

Abstract- For tackling multi-objective optimisation (MOO) problem, many methods are available in the field of evolutionary computation (EC). To use the proposed method(s), the choice of the representation should be considered first. In EC, often binary representation and real-valued representation are used. In this paper, we propose a hybrid representation, composed of binary and real-valued representations for multi-objective optimisation problems. Several issues such as discretisation error in the binary representation, self-adaptation of strategy parameters and adaptive switching of representations are addressed. Experiments are conducted on five test functions using six different performance indices, which shows that the hybrid representation exhibits better and more stable performance than the single binary or real-valued representation.

Theoretical Comparisons of Search Dynamics of Genetic Algorithms and Evolution Strategies

Abstract- Genetic algorithms (GAs) and evolution strategies (ESs) are two widely used evolutionary algorithms. The main differences between GAs and ESs lie in their representations and variation operators, which result in very different search dynamics. In this paper, we compare the search dynamics of GAs and ESs theoretically using a theoretical framework for analyzing the search dynamics of evolution strategies proposed in this paper and a framework for genetic algorithms we suggested in [Oka05]. Based on the theoretical analysis, interesting aspects of the search dynamics of GAs and ESs for single objective optimization are revealed. As an extension, preliminary results on the search dynamics of GAs for multi-objective optimization are also presented.

A New Approach to Dynamics Analysis of Genetic Algorithms without

Abstract- Theoretical analysis of the dynamics of evolutionary algorithms is believed to be very important to understand the search behavior of evolutionary algorithms and to develop more efficient algorithms. We investigate the dynamics of a canonical genetic algorithm with one-point crossover and mutation theoretically. To this end, a new theoretical framework has been suggested in which the probability of each chromosome in the offspring population can be calculated from the probability distribution of the parent population after crossover and mutation. Empirical studies are conducted to verify the theoretical analysis. The finite population effect is also discussed. Compared to existing approaches to dynamics analysis, our theoretical framework is able to provide richer information on population dynamics and is computationally more efficient.

A Critical Survey of Performance Indices for Multi-Objective Optimisation

A large.number of methods for solving multi-objective optimisation (MOO) problems have been developed. To compare these methods rigorously, or to measure the performance of a particular MOO algorithm quantitatively, a variety of performance indices (PIs) have been proposed. This paper provides an overview of the various PIs and attempts to categorise them into a certain number of classes according to their properties. Comparative studies have been conducted using a group of artificial solution sets and a group of solution sets obtained by various MOO solvers to show the advantages and disadvantages of the PIs. The comparative studies show that many PIs may he misleading in that they fail to truly reflect the quality of solution sets. Thus, it may not he a good practice to evaluate the performance of MOO solvers based on PIs only