Cultivation of the intertidal brown alga Hizikia fusiformis (Harvey) Okamura: mass production of zygote-derived seedlings under commercial cultivation conditions, a case study experience

Mariculture of the brown alga Hizikia fusiformis (Harvey) Okamura as an export-oriented human food has been there more for than 20 years in China. It is now one of the five major farmed algal species along the Chinese coast. Stable and sufficient supply of young seedlings for scaling up the cultivation has been a problem throughout the farming history of this species due to the unique dioecious life cycle and relatively short time window of sexual reproduction in nature. These two factors led to a practical difficulty in obtaining zygotes at identical developmental stage in viable amounts for seedling production. A key solution to this problem is to control the synchronization of the receptacle development and to realize the simultaneous discharge of male and female gametes, such that the fertilization rate could be greatly enhanced. Focusing on one of the farmed populations in this report, we present our results on mass production of seedlings using the synchronization technique on a large scale performed in 2007. Totally 5.5 hundred million embryos were obtained from 100 kg female sporophytes. The seedlings were raised up to 3.5 mm in length in greenhouse tanks over a month and were further grown in open sea for over 3 months at two experimental sites. The success of mass production of seedlings in this alga helped to lay the basis for future trials in other species in the genus of Sargassum that have identical life cycle.

反假频重建理论及其在储层预测中的应用

To extend the cross-hole seismic 2D data to outside 3D seismic data, reconstructing the low frequency data to high frequency data is necessary. Blind deconvolution method is a key technology. In this paper, an implementation of Blind deconvolution is introduced. And optimized precondition conjugate gradient method is used to improve the stability of the algorithm and reduce the computation. Then high-frequency retrieved Seismic data and the cross-hole seismic data is combined for constraint inversion. Real data processing proved the method is effective. To solve the problem that the seismic data resolution can’t meet the request of reservoir prediction in the river face thin-layers in Chinese eastern oil fields, a high frequency data reconstruction method is proposed. The extrema of the seismic data are used to get the modulation function which operated with the original seismic data to get the high frequency part of the reconstruction data to rebuild the wide band data. This method greatly saves the computation, and easy to adjust the parameters. In the output profile, the original features of the seismic events are kept, the common feint that breaking the events and adding new zeros to produce alias is avoided. And the interbeded details are enhanced compared to the original profiles. The effective band of seismic data is expended and the method is approved by the processing of the field data. Aim to the problem in the exploration and development of Chinese eastern oil field that the high frequency log data and the relative low frequency seismic data can’t be merged, a workflow of log data extrapolation constrained by time-phase model based on local wave decomposition is raised. The seismic instantaneous phase is resolved by local wave decomposition to build time-phase model, the layers beside the well is matched to build the relation of log and seismic data, multiple log info is extrapolated constrained by seismic equiphase map, high precision attributes inverse sections are produced. In the course of resolve the instantaneous phase, a new method of local wave decomposition --Hilbert transform mean mode decomposition(HMMD) is raised to improve the computation speed and noise immunity. The method is applied in the high resolution reservoir prediction in Mao2 survey of Daqing oil field, Multiple attributes profiles of wave impedance, gamma-ray, electrical resistivity, sand membership degree are produced, of which the resolution is high and the horizontal continuous is good. It’s proved to be a effective method for reservoir prediction and estimation.

Effects of organic modifiers on solute retention and electrokinetic migrations in micellar electrokinetic capillary chromatography

Influences of seven organic modifiers, including urea, methanol (MeOH), dioxane (DIO), tetrahydrofuran (THF), acetonitrile (ACN), 1-propanol (1-PrOH) and 2-propanol (2-PrOH), on the solute retention and the electrokinetic migrations in micellar electrokinetic capillary chromatography (MEKC) are investigated with sodium dodecyl sulfate (SDS) micelle as pseudostationary phase. It is observed that in the limited concentration ranges used in the MEKC systems the effect of organic modifier concentration on the retention can be described by the equation logk'=logk'(w)-SC for most binary aqueous-organic buffer, but deviations from this retention equation are observed at ACN and particularly THF as organic modifiers. With parameter S as a measure of the elutropic strength, the elutropic strength of the organic modifiers is found to follow a general order urea window is expanded by the use of organic modifiers. Urea and MeOH have the least expanding strength while ACN, DIO, THF, 1-PrOH and 2-PrOH have the highest expanding strength on the migration time window.

Column switching-back flushing technique for the analysis of aromatic compounds in gasoline

A simple method, based on the technique of capillary column switching-back flushing, has been developed for the detailed analysis of aromatic compounds in gasoline. The sample was first separated on a 30-m long OV-2330 polar precolumn and then backflushed onto a nonpolar analytical column. The early eluting components from the precolumn and the components of interest (aromatic compounds plus heavier compounds) eluting from the analytical column are all directed to the same flame ionization detection system through a T piece, which permits the quantitative analysis of aromatic hydrocarbons in gasoline by a normalization method using correcting factors. The switching time window of the method is +/-5 s, resulting in easier operation and higher reliability. The reproducibility of the quantitative analysis was less than or equal to3% RSD for real gasoline samples. (C) 2002 Elsevier Science B.V. All rights reserved.

Time-Frequency Analysis of Nonlinear Systems: The Skeleton Linear Model and the Skeleton Curves

The joint time-frequency analysis method is adopted to study the nonlinear behavior varying with the instantaneous response for a class of S.D.O.F nonlinear system. A time-frequency masking operator, together with the conception of effective time-frequency region of the asymptotic signal are defined here. Based on these mathematical foundations, a so-called skeleton linear model (SLM) is constructed which has similar nonlinear characteristics with the nonlinear system. Two skeleton curves are deduced which can indicate the stiffness and damping in the nonlinear system. The relationship between the SLM and the nonlinear system, both parameters and solutions, is clarified. Based on this work a new identification technique of nonlinear systems using the nonstationary vibration data will be proposed through time-frequency filtering technique and wavelet transform in the following paper.

A time-varying controllable fault-tolerant field associative memory model and its simulation

A time-varying controllable fault-tolerant field associative memory model and the realization algorithms are proposed. On the one hand, this model simulates the time-dependent changeability character of the fault-tolerant field of human brain's associative memory. On the other hand, fault-tolerant fields of the memory samples of the model can be controlled, and we can design proper fault-tolerant fields for memory samples at different time according to the essentiality of memory samples. Moreover, the model has realized the nonlinear association of infinite value pattern from n dimension space to m dimension space. And the fault-tolerant fields of the memory samples are full of the whole real space R-n. The simulation shows that the model has the above characters and the speed of associative memory about the model is faster.

Determination of ethenzamide and acetoaminophen in quaternary powdered samples by near infrared spectroscopy and searching combination moving window partial least squares algorithm: effects of spectral resolution and signal-to-noise ratio

The present study reports an application of the searching combination moving window partial least squares (SCMWPLS) algorithm to the determination of ethenzamide and acetoaminophen in quaternary powdered samples by near infrared (NIR) spectroscopy. Another purpose of the study was to examine the instrumentation effects of spectral resolution and signal-to-noise ratio of the Buchi NIRLab N-200 FT-NIR spectrometer equipped with an InGaAs detector. The informative spectral intervals of NIR spectra of a series of quaternary powdered mixture samples were first located for ethenzamide and acetoaminophen by use of moving window partial least squares regression (MWPLSR). Then, these located spectral intervals were further optimised by SCMWPLS for subsequent partial least squares (PLS) model development. The improved results are attributed to both the less complex PLS models and to higher accuracy of predicted concentrations of ethenzamide and acetoaminophen in the optimised informative spectral intervals that are featured by NIR bands. At the same time, SCMWPLS is also demonstrated as a viable route for wavelength selection.

Temperature dependence of the distribution of the first passage time: Results from discontinuous molecular dynamics simulations of an all-atom model of the second beta-hairpin fragment of protein G

More than 22 000 folding kinetic simulations were performed to study the temperature dependence of the distribution of first passage time (FPT) for the folding of an all-atom Go-like model of the second beta-hairpin fragment of protein G. We find that the mean FPT (MFPT) for folding has a U (or V)-shaped dependence on the temperature with a minimum at a characteristic optimal folding temperature T-opt*. The optimal folding temperature T-opt* is located between the thermodynamic folding transition temperature and the solidification temperature based on the Lindemann criterion for the solid. Both the T-opt* and the MFPT decrease when the energy bias gap against nonnative contacts increases. The high-order moments are nearly constant when the temperature is higher than T-opt* and start to diverge when the temperature is lower than T-opt*. The distribution of FPT is close to a log-normal-like distribution at T* greater than or equal to T-opt*. At even lower temperatures, the distribution starts to develop long power-law-like tails, indicating the non-self-averaging intermittent behavior of the folding dynamics. It is demonstrated that the distribution of FPT can also be calculated reliably from the derivative of the fraction not folded (or fraction folded), a measurable quantity by routine ensemble-averaged experimental techniques at dilute protein concentrations.