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

▪ Abstract Plant responses to salinity stress are reviewed with emphasis on molecular mechanisms of signal transduction and on the physiological consequences of altered gene expression that affect biochemical reactions downstream of stress sensing. We make extensive use of comparisons with model organisms, halophytic plants, and yeast, which provide a paradigm for many responses to salinity exhibited by stress-sensitive plants. Among biochemical responses, we emphasize osmolyte biosynthesis and function, water flux control, and membrane transport of ions for maintenance and re-establishment of homeostasis. The advances in understanding the effectiveness of stress responses, and distinctions between pathology and adaptive advantage, are increasingly based on transgenic plant and mutant analyses, in particular the analysis of Arabidopsis mutants defective in elements of stress signal transduction pathways. We summarize evidence for plant stress signaling systems, some of which have components analogous to t...

Plant cellular and molecular responses to high salinity.

A fast-Fourier-transform method of topography and interferometry is proposed. By computer processing of a noncontour type of fringe pattern, automatic discrimination is achieved between elevation and depression of the object or wave-front form, which has not been possible by the fringe-contour-generation techniques. The method has advantages over moire topography and conventional fringe-contour interferometry in both accuracy and sensitivity. Unlike fringe-scanning techniques, the method is easy to apply because it uses no moving components.

Fourier-transform method of fringe-pattern analysis for computer-based topography and interferometry

Abiotic Stress Signaling and Responses in Plants

Nonpathogenic rhizobacteria can induce a systemic resistance in plants that is phenotypically similar to pathogen-induced systemic acquired resistance (SAR). Rhizobacteria-mediated induced systemic resistance (ISR) has been demonstrated against fungi, bacteria, and viruses in Arabidopsis, bean, carnation, cucumber, radish, tobacco, and tomato under conditions in which the inducing bacteria and the challenging pathogen remained spatially separated. Bacterial strains differ in their ability to induce resistance in different plant species, and plants show variation in the expression of ISR upon induction by specific bacterial strains. Bacterial determinants of ISR include lipopolysaccharides, siderophores, and salicylic acid (SA). Whereas some of the rhizobacteria induce resistance through the SA-dependent SAR pathway, others do not and require jasmonic acid and ethylene perception by the plant for ISR to develop. No consistent host plant alterations are associated with the induced state, but upon challenge inoculation, resistance responses are accelerated and enhanced. ISR is effective under field conditions and offers a natural mechanism for biological control of plant disease.

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Systemic resistance induced by rhizosphere bacteria

Particulate Organic Carbon (POC) plays an important role in sink of atmospheric CO2, global carbon cycle, etc. Around river estuary, POC is sourced from terrestrial ecosystem and aquatic ecosystem; its distribution features might be complex and likely to change with time. Based on in-situ samples from four seasonal cruises, we discussed spatial-temporal distribution and remote sensing monitoring of POC concentration in the Pearl River Estuary (PRE). Being affected by larger discharge from the Pearl River, surface POC concentrations in summer were usually higher than those in other three seasons, similar, in the PRE. However, because of sediment resuspension, POC concentrations at the bottom layer were higher than those at the surface layer. Taking the PRE as an example, remote sensing monitoring of POC concentration in case II water around estuary was also discussed. On the one hand, on the basis of Chlorophyll-a (Chl-a) and Total Suspended Matter (TSM) concentrations inversed by published algorithms, we can estimate surface POC concentration through multiple linear regression equation: POC=0.042*Chl-a+0.014*TSM+0.1595, R=0.9156. On the other hand, great relationships between surface POC concentrations and total particle absorption coefficient at 667nm (TPabs(667)) and 678nm (TPabs(678)) were also found: POC=3.813*TPabs(667)+0.0684, R=0.8769 and POC=3.9175*TPabs(678)+0.0624, R=0.8745. They implied the possibility of estuarine POC monitoring from space through remote sensing reflectance at 667nm or 678nm.

The spatial-temporal distribution of particulate organic carbon in the Pearl River Estuary

A spherical optical element surface defect evaluation system and a method therefor. The evaluation system (100) comprises a defect imaging sub-system (200) and a control sub-system (700); the defect imaging sub-system (200) is used for acquiring a microscopic scattering dark field image applicable to digital image processing; the control sub-system (700) is used for controlling the motion of various components in the defect imaging sub-system to achieve the collection of a spherical optical element surface image; the defect imaging sub-system (200) comprises an illumination unit (300), a microscopic scattering dark field imaging unit (400), a space pose adjustment unit (500) and a spherical centring unit (600); and the motion and adjustment of the illumination unit (300), the microscopic scattering dark field imaging unit (400), the space pose adjustment unit (500) and the spherical centring unit (600) are all completed under the driving and control of the control sub-system (700). Therefore, the automated quantitative detection of a spherical optical element surface defect is achieved, and the detection efficiency and detection accuracy are improved.

Spherical optical element surface defect evaluation system and method therefor

Light detection and ranging (LIDAR) is an active remote sensing system. Lidar echo signal is non-linear and non-stationary, which is often accompanied by various noises. In order to filter out the noise and extract valid signal information, a suitable method should be chosen for noise reduction. Some denoising methods are commonly used, such as the wavelet transform (WT), the empirical mode decomposition (EMD), the variational mode decomposition (VMD), and their improved algorithms. In this paper, a new denoising method named the WT-VMD joint algorithm based on the sparrow search algorithm (SSA), for lidar signal is selected by comparative experiment analysis. It is shown that this method is the most suitable one with the maximum signal-to-noise ratio (SNR), the minimum root-mean-square error (RMSE), and a relatively small indicator of smoothness when it is used in three kinds (50, 100, and 1000 pulses) of simulate lidar signals. The SNR is increased by 138.5%, 77.8% and 42.8% and the RMSE is decreased by 81.8%, 72.0% and 68.8% when being used to the three kinds of cumulative signal without pollution. Then, the SNR is increased by 83.3%, 60.4% and 24.0% and the RMSE is decreased by 70.8%, 66.0% and 50.5% when being used to the three kinds of cumulative signal with aerosol and clouds. The WT-VMD joint algorithm based on SSA is used in the denoising process for the actual lidar signal, showing extraordinary denoising effect and will improve the inversion accuracy of the lidar signal.

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New Denoising Method for Lidar Signal by the WT-VMD Joint Algorithm

The effects of the upward-increasing gradient magnetic field on soot properties are experimentally investigated in ethylene inverse diffusion flames with different oxygen concentrations. The soot morphology, nanostructure, graphitization degree, and oxidation reactivity are obtained by high-resolution transmission electron spectroscopy (HRTEM), X-ray diffractometer (XRD), and thermogravimetric analyzer (TGA), respectively. The upward-increasing gradient magnetic field is induced by two Nd-Fe-B permanent magnets with different thicknesses. The results show that the magnetic field influences the soot properties mainly by affecting the distributions of paramagnetic O2 and OH radicals in the flames. The soot samples are more graphitized in the flame with higher O2 concentration, which contains a longer fringe length and smaller fringe tortuosity. Fullerene-like structures are more apparent with increasing oxygen content. The soot fringe length decreases and fringe tortuosity increases when the upward-increasing gradient magnetic field is applied. The application of the magnetic field enhances the soot oxidation reactivity, and it shows the greatest effect on the oxidation reactivity of soot produced in the flame with 21% O2 content.

Effects of the upward-increasing gradient magnetic field on soot properties in ethylene inverse diffusion flames with different oxygen concentrations

Dielectric materials with excellent energy storage performance are crucial to the development of renewable energy. In this work, we prepared 0.95NaNbO 3 –0.05Bi(Zn[Formula: see text]Zr[Formula: see text])O 3 (0.95NN–0.05BZZ) ceramics using solid state sintering and investigated the effect of sintering temperature on phase structure. We find that the phase transformation of ceramics occurs with the change of sintering temperature. The cubic phase (Pm -3[Formula: see text]) and the antiferroelectric phase (Pbma) coexist at 1150[Formula: see text]C, the ferroelectric phase ([Formula: see text]21ma) appears at 1200[Formula: see text]C and its phase proportion decreases with the sintering temperature increasing from 1200[Formula: see text]C to 1280[Formula: see text]C. Finally, we achieve the high recoverable energy storage density ([Formula: see text]) 0.74 J/cm 3 and efficiency ([Formula: see text]) 71% (at 140 kV/cm) at 1150[Formula: see text]C. 

Dong Liu

Papers

The spatial-temporal distribution of particulate organic carbon in the Pearl River Estuary

Spherical optical element surface defect evaluation system and method therefor

New Denoising Method for Lidar Signal by the WT-VMD Joint Algorithm

Effects of the upward-increasing gradient magnetic field on soot properties in ethylene inverse diffusion flames with different oxygen concentrations

Effect of sintering temperature on phase transformation and energy storage properties of 0.95NaNbO3-0.05Bi(Zn0.5Zr0.5)O3 ceramics