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

As a fascinating conjugated polymer, graphitic carbon nitride (g-C3N4) has become a new research hotspot and drawn broad interdisciplinary attention as a metal-free and visible-light-responsive photocatalyst in the arena of solar energy conversion and environmental remediation. This is due to its appealing electronic band structure, high physicochemical stability, and “earth-abundant” nature. This critical review summarizes a panorama of the latest progress related to the design and construction of pristine g-C3N4 and g-C3N4-based nanocomposites, including (1) nanoarchitecture design of bare g-C3N4, such as hard and soft templating approaches, supramolecular preorganization assembly, exfoliation, and template-free synthesis routes, (2) functionalization of g-C3N4 at an atomic level (elemental doping) and molecular level (copolymerization), and (3) modification of g-C3N4 with well-matched energy levels of another semiconductor or a metal as a cocatalyst to form heterojunction nanostructures. The constructi...

Graphitic Carbon Nitride (g-C3N4)-Based Photocatalysts for Artificial Photosynthesis and Environmental Remediation: Are We a Step Closer To Achieving Sustainability?

日本物理学会誌及びJournal of the Physical Society of Japanの月刊について

Materials research has driven the development of modern nano-electronic devices. In particular, research in magnetic thin films has revolutionized the development of spintronic devices1,2 because identifying new magnetic materials is key to better device performance and design. Van der Waals crystals retain their chemical stability and structural integrity down to the monolayer and, being atomically thin, are readily tuned by various kinds of gate modulation3,4. Recent experiments have demonstrated that it is possible to obtain two-dimensional ferromagnetic order in insulating Cr2Ge2Te6 (ref. 5) and CrI3 (ref. 6) at low temperatures. Here we develop a device fabrication technique and isolate monolayers from the layered metallic magnet Fe3GeTe2 to study magnetotransport. We find that the itinerant ferromagnetism persists in Fe3GeTe2 down to the monolayer with an out-of-plane magnetocrystalline anisotropy. The ferromagnetic transition temperature, Tc, is suppressed relative to the bulk Tc of 205 kelvin in pristine Fe3GeTe2 thin flakes. An ionic gate, however, raises Tc to room temperature, much higher than the bulk Tc. The gate-tunable room-temperature ferromagnetism in two-dimensional Fe3GeTe2 opens up opportunities for potential voltage-controlled magnetoelectronics7-11 based on atomically thin van der Waals crystals.

Gate-tunable Room-temperature Ferromagnetism in Two-dimensional Fe 3 GeTe 2

https://shell.cas.usf.edu/~phanm//PMS.pdf

Giant magnetoimpedance materials: Fundamentals and applications

TGF-β signaling is shown to be involved in cardiac remodeling, but the detailed function and underlying mechanism are still incompletely understood. In this study, we generated cardiomyocyte-specific TGF-β type 2 receptor (TβR2) knockout mice to study the function of TGF-β signaling in cardiac hypertrophy. Although the mutant mice displayed no obvious physiological abnormality, they developed severer cardiac hypertrophy in response to isoproterenol (ISO) stimulation than control mice did. The expression of p-Smad2 was markedly reduced, while the concentration of p-ERK was increased in the hearts of mutant mice. In addition, we also found that cardiomyocyte-specific Smad2 knockout mice did not demonstrate cardiac phenotype as observed on TβR2 knockout mice, while inhibition of MEK-1-mediated activation of MAPK using PD98059 partially rescued the phenotype of TβR2-deleted cardiomyocytes, indicating that activation of TGF-β noncanonical signaling might contribute to cardiac phenotype observed in TβR2 knockout mice. Thus, our data provided the first in vivo genetic evidence to show that TβR2 may function as an anti-hypertrophic factor of cardiac hypertrophy subjected to adrenergic stimulation, suggesting the complex role of TβR2 in cardiac hypertrophy under stimulation of different stresses.

Cardiomyocyte-specific TβR2 knockout mice are more susceptible to cardiac hypertrophy induced by adrenergic agonist stimulation

Immeasurable information sharing network (IISN) has been proposed for improving information sharing service in remote rural. How to ensure information security becomes a very important issue for the new network. In this paper, we propose a new conditional access system (CAS) model and a key management scheme for IISN. In the model, we place emphasis on making the CAS more suitable for IISN; we change the traditional two-layer CAS to three-layer CAS based on the architecture of IISN. Besides, we propose a novel 4-level key management scheme for our CAS model. Performance analysis shows that our proposed scheme is highly secure and has outperformance on key management cost.

CAS-based key management scheme for immeasurable information sharing network

Smart environment sensing and other applications play a more and more important role along with the rapid growth of device-free sensing-based services, and extracting parameters contained in channel state information (CSI) accurately is the basis of these applications. However, antenna arrays in wireless devices are all planar arrays whose antenna spacing does not meet the spatial sampling theorem while the existing parameter estimation methods are almost based on the array satisfying the spatial sampling theorem. In this paper, we propose a parameter estimation algorithm to estimate the signal parameters of angle of arrival (AoA), time of flight (ToF), and Doppler frequency shift (DFS) based on the service antenna array, which does not satisfy the spatial sampling theorem. Firstly, the service antenna array is mapped to a virtual linear array and the array manifold of the virtual linear array is calculated. Secondly, the virtual linear array is applied to estimate the multi-dimensional parameters of the signal. Finally, by calculating the geometric relationship between the service antenna and the virtual linear array, the parameters of the signal incident on the service antenna can be obtained. Therefore, the service antenna can not only use the communication channel for information communication, but also sense the surrounding environment and provide related remote sensing and other wireless sensing application services. Simulation results show that the proposed parameter estimation algorithm can accurately estimate the signal parameters when the array antenna spacing does not meet the spatial sampling theorem. Compared with TWPalo, the proposed algorithm can estimate AoA within 3∘, while the error of ToF and DFS parameter estimation is within 1 ns and 1 m/s.

/pdf/channel-state-information-based-multi-dimensional-parameter-181sehnrjd.pdf

Channel state information-based multi-dimensional parameter estimation for massive RF data in smart environments

This paper has reported the research of a scalable wavelength division multiplexing (WDM) optical routing system applied to the interconnection between CPU and MEM of distributed parallel computer. This system is built on DWDM and the optical switch array, which can connect CPUs and MEMs in a multigigabit WDM fiber, and so take advantage of high throughput, low-latency, error-free parallel transmission. And the paper has analyzed the performances degradation arising from super-speed and multi-wavelength, and put forward practical improvement measures. Furthermore the paper has designed a dual-window DWDM experimental system, and tested the data exchange between CPU and MEM. The purpose of this paper lies in exploring an optical WDM interconnection routing system which can not only be super-capacity, and reduce the complexity in implementation technologies, and also optimize the internal structures, or even external communication mechanisms of parallel computer.

Optical wavelength-division multiplexing (WDM) routing system for parallel computer

Human activity recognition (HAR) based on Channel State Information (CSI) has been widely concerned in recent years due to its properties of low cost and privacy protection. Whats more, unlike vision-based and sensor-based HAR systems, it is not sensitive to illumination intensity and does not need any accessory equipment. The detection threshold in existing HAR system is set manually thus require researchers to reset the threshold when environment changes or a new activity needs to be recognized. The utilization of single classifier with poor robustness cannot achieve a high recognition accuracy. We propose a CSI-based Device-free HAR (CDHAR) system to recognize common human activities, such as ‘Walk’, ‘Run’, ‘Sit down’, ‘Squat’ and ‘Fall down’. First of all, CDHAR obtain an adaptive detection threshold to complete the extraction of activity durations. Second, it proposes a random subspace classifier ensemble method for classification. At last, we prototype CDHAR on commodity WiFi devices and evaluate its performance both in typical indoor and outdoor environments. Our results show even experimental site changes, the extraction accuracy rate can achieve 99.80% and 99.60% in outdoor and indoor environment, respectively. Based on the extracted data, the recognition accuracy rate can reach 91.2and 90.2% in outdoor and indoor environment, respectively. CDHAR solves the problem of setting the detection threshold manually and overcomes the low robustness of the single classifier at the same time. Furthermore, the results in above two scenarios demonstrate that CDHAR can also achieve slightly recognition accuracy improvement over existing recognition methods.

Xiaolong Yang

Papers

Cardiomyocyte-specific TβR2 knockout mice are more susceptible to cardiac hypertrophy induced by adrenergic agonist stimulation

CAS-based key management scheme for immeasurable information sharing network

Channel state information-based multi-dimensional parameter estimation for massive RF data in smart environments

Optical wavelength-division multiplexing (WDM) routing system for parallel computer

Human Activity Recognition System Based on Channel State Information