Tutorial: Determination of Thermal Boundary Resistance by Molecular Dynamics Simulations

Due to the High Surface-To-Volume Ratio of Nanostructured Components in Microelectronics and Other Advanced Devices, the Thermal Resistance at Material Interfaces Can Strongly Affect the overall Thermal Behavior in These Devices. Therefore, the Thermal Boundary Resistance, R, Must Be Taken into Account in the Thermal Analysis of Nanoscale Structures and Devices. This Article is a Tutorial on the Determination of R and the Analysis of Interfacial Thermal Transport Via Molecular Dynamics (MD) Simulations. in Addition to Reviewing the Commonly Used Equilibrium and Non-Equilibrium MD Models for the Determination of R, We Also Discuss Several MD Simulation Methods Which Can Be Used to Understand Interfacial Thermal Transport Behavior. to Illustrate How These MD Models Work for Various Interfaces, We Will Show Several Examples of MD Simulation Results on Thermal Transport Across Solid-Solid, Solid-Liquid, and Solid-Gas Interfaces. the Advantages and Drawbacks of a Few Other MD Models Such as Approach-To-Equilibrium MD and First-Principles MD Are Also Discussed

Detecting Majorana fermions by nonlocal entanglement between quantum dots

Nonlocal entanglement between two quantum dots can be generated through Majorana fermions. The two Majorana fermions at the ends of an one-dimensional topological superconductor form a nonlocal fermion level, coupling to the occupation states of two quantum dots put close to the two ends, and the entire system will come into an entangled state. After introducing a charging energy by a capacitor, entanglement of the entire system can manifest itself through the nonlocal entanglement between the two quantum dots. That is, when measuring the electron occupations of the quantum dots, the measurement result of one quantum dot will influence the measurement result of the other quantum dot. This nonlocal entanglement between the two quantum dots is a strong evidence of the nonlocal nature of the fermion level constructed by two Majorana fermions.Comment: 4 pages, 4 figure

Designing Software to Locate Differences in the Shrimp Genome

In order to determine where important differences in the genomic sequence of Pacific White Shrimp occur, many copies each of multiple regions of DNA sequence are needed. Then similar sequences can be aligned so that almost all of the bases are identical between the sequences and differences are easy to notice. One of the major issues with predicting single base position differences (SNPs) in this manner is that DNA sequencing techniques are not 100% consistent in most cases. Consequently, it needs to be determined whether a particular base is different because the true genetic sequence is variable at that position or because the sequencing process resulted in the base position being incorrectly called. SNPidentifier is a newly developed computer program that takes into account the unreliability of sequence data and tries to use only the more reliable sequences to predict where true SNPs are located. The goal of locating SNPs in Pacific White Shrimp is to identify base positions that can possibly be used in the future as molecular markers for traits of interest to shrimp breeders

Developmental progress and current status of the Animal QTLdb

The Animal QTL Database (QTLdb; http://www.animalgenome.org/QTLdb) has undergone dramatic growth in recent years in terms of new data curated, data downloads and new functions and tools. We have focused our development efforts to cope with challenges arising from rapid growth of newly published data and end users’ data demands, and to optimize data retrieval and analysis to facilitate users’ research. Evidenced by the 27 releases in the past 11 years, the growth of the QTLdb has been phenomenal. Here we report our recent progress which is highlighted by addition of one new species, four new data types, four new user tools, a new API tool set, numerous new functions and capabilities added to the curator tool set, expansion of our data alliance partners and more than 20 other improvements. In this paper we present a summary of our progress to date and an outlook regarding future directions

Building a livestock genetic and genomic information knowledgebase through integrative developments of Animal QTLdb and CorrDB

Successful development of biological databases requires accommodation of the burgeoning amounts of data from high-throughput genomics pipelines. As the volume of curated data in Animal QTLdb (https://www.animalgenome.org/QTLdb) increases exponentially, the resulting challenges must be met with rapid infrastructure development to effectively accommodate abundant data curation and make metadata analysis more powerful. The development of Animal QTLdb and CorrDB for the past 15 years has provided valuable tools for researchers to utilize a wealth of phenotype/genotype data to study the genetic architecture of livestock traits. We have focused our efforts on data curation, improved data quality maintenance, new tool developments, and database co-developments, in order to provide convenient platforms for users to query and analyze data. The database currently has 158 499 QTL/associations, 10 482 correlations and 1977 heritability data as a result of an average 32% data increase per year. In addition, we have made \u3e14 functional improvements or new tool implementations since our last report. Our ultimate goals of database development are to provide infrastructure for data collection, curation, and annotation, and more importantly, to support innovated data structure for new types of data mining, data reanalysis, and networked genetic analysis that lead to the generation of new knowledge