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

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

BACKGROUND Materials by design is an appealing idea that is very hard to realize in practice. Combining the best of different ingredients in one ultimate material is a task for which we currently have no general solution. However, we do have some successful examples to draw upon: Composite materials and III-V heterostructures have revolutionized many aspects of our lives. Still, we need a general strategy to solve the problem of mixing and matching crystals with different properties, creating combinations with predetermined attributes and functionalities. ADVANCES Two-dimensional (2D) materials offer a platform that allows creation of heterostructures with a variety of properties. One-atom-thick crystals now comprise a large family of these materials, collectively covering a very broad range of properties. The first material to be included was graphene, a zero-overlap semimetal. The family of 2D crystals has grown to includes metals (e.g., NbSe 2 ), semiconductors (e.g., MoS 2 ), and insulators [e.g., hexagonal boron nitride (hBN)]. Many of these materials are stable at ambient conditions, and we have come up with strategies for handling those that are not. Surprisingly, the properties of such 2D materials are often very different from those of their 3D counterparts. Furthermore, even the study of familiar phenomena (like superconductivity or ferromagnetism) in the 2D case, where there is no long-range order, raises many thought-provoking questions. A plethora of opportunities appear when we start to combine several 2D crystals in one vertical stack. Held together by van der Waals forces (the same forces that hold layered materials together), such heterostructures allow a far greater number of combinations than any traditional growth method. As the family of 2D crystals is expanding day by day, so too is the complexity of the heterostructures that could be created with atomic precision. When stacking different crystals together, the synergetic effects become very important. In the first-order approximation, charge redistribution might occur between the neighboring (and even more distant) crystals in the stack. Neighboring crystals can also induce structural changes in each other. Furthermore, such changes can be controlled by adjusting the relative orientation between the individual elements. Such heterostructures have already led to the observation of numerous exciting physical phenomena. Thus, spectrum reconstruction in graphene interacting with hBN allowed several groups to study the Hofstadter butterfly effect and topological currents in such a system. The possibility of positioning crystals in very close (but controlled) proximity to one another allows for the study of tunneling and drag effects. The use of semiconducting monolayers leads to the creation of optically active heterostructures. The extended range of functionalities of such heterostructures yields a range of possible applications. Now the highest-mobility graphene transistors are achieved by encapsulating graphene with hBN. Photovoltaic and light-emitting devices have been demonstrated by combining optically active semiconducting layers and graphene as transparent electrodes. OUTLOOK Currently, most 2D heterostructures are composed by direct stacking of individual monolayer flakes of different materials. Although this method allows ultimate flexibility, it is slow and cumbersome. Thus, techniques involving transfer of large-area crystals grown by chemical vapor deposition (CVD), direct growth of heterostructures by CVD or physical epitaxy, or one-step growth in solution are being developed. Currently, we are at the same level as we were with graphene 10 years ago: plenty of interesting science and unclear prospects for mass production. Given the fast progress of graphene technology over the past few years, we can expect similar advances in the production of the heterostructures, making the science and applications more achievable.

2D materials and van der Waals heterostructures

The hyper-commutators in effect algebras as a generalization of commutators in lattice effect algebras are defined, and their properties are studied We prove that a nonzero element is in some hyper-commutator if and only if it is a torsion element in effect algebras with the maximality property Thus, homogeneity can be characterized by hyper-commutators Some properties of Riesz ideals related to hyper-commutators are also studied As an application, we prove that commutators are sharp in lattice effect algebras and every block-finite lattice effect algebra is commutator-finite

Hyper-commutators in effect algebras

High pressure sintering of fully dense tantalum carbide ceramics with limited grain growth

Integrated preparation and enhanced performance of high-melting-point ZrC–Mo multilayer graded materials

Bioinformatics characteristics and expression analysis of TLR3 and its adaptor protein TRIF in Largemouth bass (Micropterus salmoides) upon Flavobacterium columnare infection.

Purpose This study aimed to explore the pharmacological mechanism of Dangshen (Codonopsis pilosula) against hepatocellular carcinoma (HCC) based on network pharmacology and bioinformatics, and to verify the anticancer effect of luteolin, the active ingredient of Codonopsis pilosula, on HCC cells. Methods The effective compounds and potential targets of Codonopsis pilosula were established using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database. The genes related to HCC were obtained through the GeneCards database. The interactive genes were imported into the Visualization and Integrated Discovery database for Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal enrichment, and the hub genes were screened out. The Cancer Genome Atlas database was used to construct a prognosis model, and the prognosis and clinicopathological correlation were analyzed. In in vitro experiments, we verified the effects of luteolin, an active compound of Codonopsis pilosula, on the proliferation, cell cycle, apoptosis and migration of HCC cells. Results A total of 21 effective compounds of Codonopsis pilosula and 98 potential downstream target genes were screened through the TCMSP database, and 1406 HCC target genes were obtained through the GeneCards database. Finally, 53 interacting genes between the two databases were obtained, among which, the 10 key node genes were CASP3, TP53, MDM2, AKT1, ESR1, BCL2L1, MCL1, HSP90AA1, CASP9, and CCND1, involving 77 typical GO terms and 72 KEGG signals. The Kaplan–Meier survival curve of the model group showed that the overall survival of the low-risk group was significantly higher than that of the high-risk group. Luteolin significantly inhibited the proliferation and migration of HCC cells, induced apoptosis, and increased the G2/M phase ratio. Mechanistically, luteolin significantly inhibited the phosphorylation of MAPK-JNK and Akt (Thr308) and subsequently led to upregulation of ESR1. Pharmacological inhibition of ESR1 with fulvestrant enhanced cell viability and migration and attenuated apoptosis. Conclusion Codonopsis pilosula has potential for clinical development due to its anti-HCC properties. Luteolin, the effective component of Codonopsis pilosula, plays anti-HCC role through AKT- or MAPK-JNK signaling mediated ESR1.

Integrating Network Pharmacology and Bioinformatics to Explore the Effects of Dangshen (Codonopsis pilosula) Against Hepatocellular Carcinoma: Validation Based on the Active Compound Luteolin

Wei Ji

Papers

Hyper-commutators in effect algebras

High pressure sintering of fully dense tantalum carbide ceramics with limited grain growth

Integrated preparation and enhanced performance of high-melting-point ZrC–Mo multilayer graded materials

Bioinformatics characteristics and expression analysis of TLR3 and its adaptor protein TRIF in Largemouth bass (Micropterus salmoides) upon Flavobacterium columnare infection.

Integrating Network Pharmacology and Bioinformatics to Explore the Effects of Dangshen (Codonopsis pilosula) Against Hepatocellular Carcinoma: Validation Based on the Active Compound Luteolin