Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Within the space of a few years, hybrid organic–inorganic perovskite solar cells have emerged as one of the most exciting material platforms in the photovoltaic sector. This review describes the rapid progress that has been made in this area.

The emergence of perovskite solar cells

Perovskite photovoltaics are gaining increasing common ground to partner with or compete with silicon photovoltaics to reduce cost of solar energy. However, a cost-effective waste management for toxic lead (Pb), which might determine the fate of this technology, has not been developed yet. Here, we report an end-of-life material management for perovskite solar modules to recycle toxic lead and valuable transparent conductors to protect the environment and create dramatic economic benefits from recycled materials. Lead is separated from decommissioned modules by weakly acidic cation exchange resin, which could be released as soluble Pb(NO3)2 followed by precipitation as PbI2 for reuse, with a recycling efficiency of 99.2%. Thermal delamination disassembles the encapsulated modules with intact transparent conductors and cover glasses. The refabricated devices based on recycled lead iodide and recycled transparent conductors show comparable performance as devices based on fresh raw materials. Cost analysis shows this recycling technology is economically attractive. Perovskite photovoltaics has become more competitive against silicon counterpart in reducing cost of solar energy, yet the management of toxic lead hampers it application. Here, the authors propose a cost-effective environmental-friendly approach to recycle lead and transparent conductors.

/pdf/recycling-lead-and-transparent-conductors-from-perovskite-22weza56s4.pdf

Recycling lead and transparent conductors from perovskite solar modules.

Abstract Background Development of Pantana phyllostachysae , a moso bamboo pest, is affected by its diet. Understanding the mechanism underlying the different insect-resistant capacities of on- and off-year moso bamboo fed by P. phyllostachysae is crucial for managing pest outbreaks. As microbes were proven to influence plant immunity, we compared gut microbial communities of P. phyllostachysae with different diets by metabarcoding sequencing. By using sterilization assay, microbes were removed from leaf surfaces, and thus we confirmed that microbes inhabiting moso bamboo leaves impact the weight of P. phyllostachysae larva. Furthermore, the gut microbial communities of P. phyllostachysae fed on on- and off-year bamboo leaves were compared, to identify the functional microbial communities that impact the interaction between bamboo leaves and P. phyllostachysae . Results We found that species from orders Lactobacillales and Rickettsiales are most effective within functional microbiota. Functional prediction revealed that gut microbes of larva fed on on-year leaves were related to naphthalene degradation, while those fed on off-year leaves were related to biosynthesis of ansamycins, polyketide sugar unit biosynthesis, metabolism of xenobiotics, and tetracycline biosynthesis. Most functional microbes are beneficial to the development of larva that feed on on-year bamboo leaves, but damage the balance of intestinal microenvironment and immune systems of those larva that feed on off-year leaves. Conclusions This work developed an efficient strategy for microbiome research of Lepidopteran insects and provided insights into microbiota related to the interaction between host plants and P. phyllostachysae . We provided microbial candidates for the ecological control of P. phyllostachysae according to the function of effective microbiota. 

/pdf/the-functional-microbiota-of-on-and-off-year-moso-bamboo-2ozl5b9j.pdf

The functional microbiota of on- and off-year moso bamboo (Phyllostachys edulis) influences the development of the bamboo pest Pantana phyllostachysae

A growing number of researchers are interested in deploying unmanned surface vehicles (USVs) in support of ocean environmental monitoring. To accomplish these missions efficiently, multiple-waypoint path planning strategies for survey USVs are still a key challenge. The multiple-waypoint path planning problem, mathematically equivalent to the traveling salesman problem (TSP), is addressed in this paper using a discrete group teaching optimization algorithm (DGTOA). Generally, the algorithm consists of three phases. In the initialization phase, the DGTOA generates the initial sequence for students through greedy initialization. In the crossover phase, a new greedy crossover algorithm is introduced to increase diversity. In the mutation phase, to balance the exploration and exploitation, this paper proposes a dynamic adaptive neighborhood radius based on triangular probability selection to apply in the shift mutation algorithm, the inversion mutation algorithm, and the 3-opt mutation algorithm. To verify the performance of the DGTOA, fifteen benchmark cases from TSPLIB are implemented to compare the DGTOA with the discrete tree seed algorithm, discrete Jaya algorithm, artificial bee colony optimization, particle swarm optimization-ant colony optimization, and discrete shuffled frog-leaping algorithm. The results demonstrate that the DGTOA is a robust and competitive algorithm, especially for large-scale TSP problems. Meanwhile, the USV simulation results indicate that the DGTOA performs well in terms of exploration and exploitation.

/pdf/a-novel-discrete-group-teaching-optimization-algorithm-for-28gzj2sp.pdf

A Novel Discrete Group Teaching Optimization Algorithm for TSP Path Planning with Unmanned Surface Vehicles

Given a complex three-dimensional domain delimited by a closed and non-degenerate input triangle mesh without any self-intersection, a common geometry processing task consists in cutting up the domain into cells through a set of planar cuts, creating a "cut-cell mesh", i.e., a volumetric decomposition of the domain amenable to visualization (e.g., exploded views), animation (e.g., virtual surgery), or simulation (finite volume computations). A large number of methods have proposed either efficient or robust solutions, sometimes restricting the cuts to form a regular or adaptive grid for simplicity; yet, none can guarantee both properties, severely limiting their usefulness in practice. At the core of the difficulty is the determination of topological relationships among large numbers of vertices, edges, faces and cells in order to assemble a proper cut-cell mesh: while exact geometric computations provide a robust solution to this issue, their high computational cost has prompted a number of faster solutions based on, e.g., local floating-point angle sorting to significantly accelerate the process --- but losing robustness in doing so. In this paper, we introduce a new approach to planar cutting of 3D domains that substitutes topological inference for numerical ordering through a novel mesh data structure, and revert to exact numerical evaluations only in the few rare cases where it is strictly necessary. We show that our novel concept of topological cuts exploits the inherent structure of cut-cell mesh generation to save computational time while still guaranteeing exactness for, and robustness to, arbitrary cuts and surface geometry. We demonstrate the superiority of our approach over state-of-the-art methods on almost 10,000 meshes with a wide range of geometric and topological complexity. We also provide an open source implementation.

TopoCut

Solar Cells: Hot-Substrate Deposition of Hole- and Electron-Transport Layers for Enhanced Performance in Perovskite Solar Cells (Adv. Energy Mater. 2/2018)

Jinsong Huang

Papers

Recycling lead and transparent conductors from perovskite solar modules.

The functional microbiota of on- and off-year moso bamboo (Phyllostachys edulis) influences the development of the bamboo pest Pantana phyllostachysae

A Novel Discrete Group Teaching Optimization Algorithm for TSP Path Planning with Unmanned Surface Vehicles

TopoCut

Solar Cells: Hot-Substrate Deposition of Hole- and Electron-Transport Layers for Enhanced Performance in Perovskite Solar Cells (Adv. Energy Mater. 2/2018)