A new method and instrument for accurately measuring interval between ultrashort pulses

Using second-order autocorrelation conception, a novel method and instrument for accurately measuring interval between two linearly polarized ultrashort pulses with real time were presented. The experiment demonstrated that the measuring method and instrument were simple and accurate (the measurement error <5 fs). During measuring, there was no moving element resulting in dynamic measurement error.

Effects of rhFSH regimen and time interval on ovarian responses to repeated stimulation cycles in rhesus monkeys during a physiologic breeding season

We studied the effects of repeated stimulation by recombinant human FSH (rhFSH) at various time intervals during a physiologic breeding season in rhesus monkeys. Ovarian recovery and responses were assessed by ultrasonography, serum steroid concentrations

Birth seasonality and interbirth interval of captive Rhinopithecus bieti

This study, which is based on 10 years of birth records, shows that black-and-white snub-nosed monkeys (Rhinopithecus bieti) in captivity display marked birth seasonality. The birth season starts in December and ends in June, with a peak from March to May

Cardioviral RNA structure logo analysis: entropy, correlations, and prediction

In recent years, there has been an increased number of sequenced RNAs leading to the development of new RNA databases. Thus, predicting RNA structure from multiple alignments is an important issue to understand its function. Since RNA secondary structures are often conserved in evolution, developing methods to identify covariate sites in an alignment can be essential for discovering structural elements. Structure Logo is a technique established on the basis of entropy and mutual information measured to analyze RNA sequences from an alignment. We proposed an efficient Structure Logo approach to analyze conservations and correlations in a set of Cardioviral RNA sequences. The entropy and mutual information content were measured to examine the conservations and correlations, respectively. The conserved secondary structure motifs were predicted on the basis of the conservation and correlation analyses. Our predictive motifs were similar to the ones observed in the viral RNA structure database, and the correlations between bases also corresponded to the secondary structure in the database.

Prediction and elucidation of the population dynamics of Microcystis spp. in Lake Dianchi (China) by means of artificial neural networks

Lake Dianchi is a shallow and turbid lake, located in Southwest China. Since 1985, Lake Dianchi has experienced severe cyanabacterial blooms (dominated by Microcystis spp.). In extreme cases, the algal cell densities have exceeded three billion cells per liter. To predict and elucidate the population dynamics ofMicrocystis spp. in Lake Dianchi, a neural network based model was developed. The correlation coefficient (R 2) between the predicted algal concentrations by the model and the observed values was 0.911. Sensitivity analysis was performed to clarify the algal dynamics to the changes of environmental factors. The results of a sensitivity analysis of the neural network model suggested that small increases in pH could cause significantly reduced algal abundance. Further investigations on raw data showed that the response of Microcystis spp. concentration to pH increase was dependent on algal biomass and pH level. When Microcystis spp. population and pH were moderate or low, the response of Microcystis spp. population would be more likely to be positive in Lake Dianchi; contrarily, Microcystis spp. population in Lake Dianchi would be more likely to show negative response to pH increase when Microcystis spp. population and pH were high. The paper concluded that the extremely high concentration of algal population and high pH could explain the distinctive response of Microcystis spp. population to +1 SD (standard deviation) pH increase in Lake Dianchi. And the paper also elucidated the algal dynamics to changes of other environmental factors. One SD increase of water temperature (WT) had strongest positive relationship with Microcystis spp. biomass. Chemical oxygen demand (COD) and total phosphorus (TP) had strong positive effect on Microcystis spp. abundance while total nitrogen (TN), biological oxygen demand in five days (BOD5), and dissolved oxygen had only weak relationship with Microcystis spp. concentration. And transparency (Tr) had moderate positive relationship with Microcystis spp. concentration.

Prediction of the retentions of polybrominated dibenzo-p-dioxins (PBDDs) by using the retentions of polychlorinated dibenzo-p-dioxins (PCDDs)

The retention equations ln k' = A + B/T of 49 polychlorinated dibenzo-p-dioxins (PCDDs) and 4 polybrominated dibenzo-p-dioxins (PBDDs) in gas chromatography (GC) have been investigated to evaluate the properties of regression coefficients A and B. The quantitative relationships between A and B values of PCDDs and those of PBDDs are found. The regression equations derived have correlation coefficients greater than 0.997. The A, B values of any PBDD can be predicted by using the A, B values of the PCDD according to these relationships. Using these predicted A and B values, the retention times of all PBDDs can be predicted at any temperature program. It is very useful to identify the peak position of any PBDD because at present there are only a few standards of PBDDs available. (C) 2000 Elsevier Science Ltd. All rights reserved.

First-principles prediction of the magnetism of 3d transition-metal-doped Rocksalt MgO

Using first-principles band structure methods, we have systematically studied the electronic structures, magnetic stabilities, and half-metal properties of 3d transition-metal (TM) doped Rocksalt MgO compounds TMMg3O4 (TM = V, Cr, Mn, Fe, Co, and Ni). The calculations reveal that only CrMg3O4 has a ferromagnetic stability among the six compounds, which is explained by double-exchange mechanism. The magnetic stability is affected by the doping concentration of TM if the top valance band is composed of partially occupied t(2g) states. In addition, CrMg3O4 is a half-metallic ferromagnet. The origins of half-metallic and ferromagnetic properties are explored. The Curie temperature (T-c) of CrMg3O4 is 182 K. And it is hard for CrMg3O4 to deform due to the large bulk modulus and shear modulus, so it is a promising spintronic material. Our calculations provide the first available information on the magnetic properties of 3d TM-doped MgO.

Prediction and suppression of strong dispersive coupling in microracetrack channel drop filters

For a four-port microracetrack channel drop filter, unexpected transmission characteristics due to strong dispersive coupling are demonstrated by the light tunneling between the input-output waveguides and the resonator, where a large dropping transmission at off-resonance wavelengths is observed by finite-difference time-domain simulation. It causes a severe decline of the extinction ratio and finesse. An appropriate decrease of the coupling strength is found to suppress the dispersive coupling and greately increase the extinction ratio and finesse, a decreased coupling strength can be realized by the application of an asymmetrical coupling waveguide structure. In addition, the profile of the coupling dispersion in the transmission spectra can be predicted based on a coupled mode theory analysis of an equivalent system consisting of two coupling straight waveguides. The effects of structure parameters on the transmission spectra obtained by this method agree well with the numerical results. It is useful to avoid the strong dispersive coupling region in the filter design. (c) 2007 Optical Society of America.

Measurement of gain spectrum for semiconductor lasers utilizing integrations of product of emission spectrum and a phase function over one mode interval

A technique based on the integrations of the product of amplified spontaneous emission spectrum and a phase function over one mode interval is proposed for measuring gain spectrum for Fabry-Perot semiconductor lasers, and a gain correction factor related to the response function of the optical spectrum analyzer (OSA) is obtained for improving the accuracy of measured gain spectrum. The gain spectra with a difference less than 1.3 cm(-1) from 1500 to 1600 nm are obtained for a 250-mum-long semiconductor laser at the OSA resolution of 0.06, 0.1, 0.2, and 0.5 nm. The corresponding gain correction factor is about 9 cm(-1) at the resolution of 0.5 nm. The gain spectrum measured at the resolution of 0.5 nm has the same accuracy as that obtained by the Hakki-Paoli method at the resolution of 0.06 nm for the laser with the mode interval of 1.3 nm.

An Accurate and Fast Behavioral Model for PLL Frequency Synthesizer Phase Noise/Spurs Prediction

This paper presents a behavior model for PLL Frequency Synthesizer. All the noise sources are modeled with noise voltages or currents in time-domain. An accurate VCO noise model is introduced, including both thermal noise and 1/f noise. The behavioral model can be co-simulated with transistor level circuits with fast speed and provides more accurate phase noise and spurs prediction. Comparison shows that simulation results match very well with measurement results.

Comparing the Performance of Biomimetic Pattern Recognition with W8 and SVM on Prediction of Horizontal Gene Transfers in Bacteria Genomes

National Natural Science Foundation of China 60753001

A Structured Prediction Approach for Statistical Machine Translation

We propose a new formally syntax-based method for statistical machine translation. Transductions between parsing trees are transformed into a problem of sequence tagging, which is then tackled by a search- based structured prediction method. This allows us to automatically acquire transla- tion knowledge from a parallel corpus without the need of complex linguistic parsing. This method can achieve compa- rable results with phrase-based method (like Pharaoh), however, only about ten percent number of translation table is used. Experiments show that the structured pre- diction approach for SMT is promising for its strong ability at combining words.

Species transformation of trace elements and their distribution prediction in dyestuff residue incineration

The release of heavy metals from the combustion of hazardous wastes is an environmental issue of increasing concern. The species transformation characteristics of toxic heavy metals and their distribution are considered to be a complex problem of mechanism. The behavior of hazardous dyestuff residue is investigated in a tubular furnace under the general condition of hazardous waste pyrolysis and gasfication. Data interpretation has been aided by parallel theoretical study based on a thermodynamic equilibrium model based on the principle of Gibbs free energy minimization. The results show that Ni, Zn, Mn, and Cr are more enriched in dyestuff residue incineration than other heavy metals (Hg, As, and Se) subjected to volatilization. The thermodynamic model calculation is used for explaining the experiment data at 800 degrees C and analyzing species transformation of heavy metals. These results of species transformation are used to predict the distribution and emission characteristics of trace elements. Although most trace element predictions are validated by the measurements, cautions are in order due to the complexity of incineration systems.