On quantum vertex algebras and their modules

We give a survey on the developments in a certain theory of quantum vertex algebras, including a conceptual construction of quantum vertex algebras and their modules and a connection of double Yangians and Zamolodchikov-Faddeev algebras with quantum vertex algebras.Comment: 18 pages; contribution to the proceedings of the conference in honor of Professor Geoffrey Maso

Modules-at-infinity for quantum vertex algebras

This is a sequel to \cite{li-qva1} and \cite{li-qva2} in a series to study vertex algebra-like structures arising from various algebras such as quantum affine algebras and Yangians. In this paper, we study two versions of the double Yangian $DY_{\hbar}(sl_{2})$, denoted by $DY_{q}(sl_{2})$ and $DY_{q}^{\infty}(sl_{2})$ with $q$ a nonzero complex number. For each nonzero complex number $q$, we construct a quantum vertex algebra $V_{q}$ and prove that every $DY_{q}(sl_{2})$-module is naturally a $V_{q}$-module. We also show that $DY_{q}^{\infty}(sl_{2})$-modules are what we call $V_{q}$-modules-at-infinity. To achieve this goal, we study what we call $\S$-local subsets and quasi-local subsets of \Hom (W,W((x^{-1}))) for any vector space $W$, and we prove that any $\S$-local subset generates a (weak) quantum vertex algebra and that any quasi-local subset generates a vertex algebra with $W$ as a (left) quasi module-at-infinity. Using this result we associate the Lie algebra of pseudo-differential operators on the circle with vertex algebras in terms of quasi modules-at-infinity.Comment: Latex, 48 page

Using Microsatellites to Assess Genetic Variation in a Selective Breeding Program of Chinese Bay Scallop (Argopecten irradians irradians)

This study aimed to improve our understanding of the genetics of the Chinese bay scallop (Argopecten irradians irradians), one of the most important maricultured shellfish in China. Ten polymorphic microsatellite loci were examined to assess the allelic diversity, heterozygosity, and genetic variation between two domesticated populations selected for fast growth in breeding programs, and their base population. Forty-one alleles were found throughout the loci and the mean number of alleles per locus ranged 3.30-3.50. The average heterozygosity ranged 0.38-0.45, whereas the polyamorphic information content ranged 0.1504-0.7518. Genetic differences between the three populations were detected based on the number of alleles per locus, effective number of alleles, Shannon index, inbreeding coefficient (Fis), p values, genetic distance, and pairwise Fst values. There was no significant loss of genetic variability in the breeding program but changes in gene frequencies were detectable over the populations, implying that thea loci were saffected by the pressures of selective culture

A guided Monte Carlo method for optimization problems

We introduce a new Monte Carlo method by incorporating a guided distribution function to the conventional Monte Carlo method. In this way, the efficiency of Monte Carlo methods is drastically improved. To further speed up the algorithm, we include two more ingredients into the algorithm. First, we freeze the sub-patterns that have high probability of appearance during the search for optimal solution, resulting in a reduction of the phase space of the problem. Second, we perform the simulation at a temperature which is within the optimal temperature range of the optimization search in our algorithm. We use this algorithm to search for the optimal path of the traveling salesman problem and the ground state energy of the spin glass model and demonstrate that its performance is comparable with more elaborate and heuristic methods.Comment: 4 pages, ReVTe

A sequence based genetic algorithm with local search for the travelling salesman problem

The standard Genetic Algorithm often suffers from slow convergence for solving combinatorial optimization problems. In this study, we present a sequence based genetic algorithm (SBGA) for the symmetric travelling salesman problem (TSP). In our proposed method, a set of sequences are extracted from the best individuals, which are used to guide the search of SBGA. Additionally, some procedures are applied to maintain the diversity by breaking the selected sequences into sub tours if the best individual of the population does not improve. SBGA is compared with the inver-over operator, a state-of-the-art algorithm for the TSP, on a set of benchmark TSPs. Experimental results show that the convergence speed of SBGA is very promising and much faster than that of the inver-over algorithm and that SBGA achieves a similar solution quality on all test TSPs

Induced junction solar cell and method of fabrication

An induced junction solar cell is fabricated on a p-type silicon substrate by first diffusing a grid of criss-crossed current collecting n+ stripes and thermally growing a thin SiO2 film, and then, using silicon-rich chemical vapor deposition (CVD), producing a layer of SiO2 having inherent defects, such as silicon interstices, which function as deep traps for spontaneous positive charges. Ion implantation increases the stable positive charge distribution for a greater inversion layer in the p-type silicon near the surface. After etching through the oxide to parallel collecting stripes, a pattern of metal is produced consisting of a set of contact stripes over the exposed collecting stripes and a diamond shaped pattern which functions as a current collection bus. Then the reverse side is metallized