Predicting the subcellular location of apoptosis proteins based on recurrence quantification analysis and the Hilbert Huang transform

Apoptosis proteins play an important role in the development and homeostasis of an organism. The elucidation of the subcellular locations and functions of these proteins is helpful for understanding the mechanism of programmed cell death. In this paper, the recurrent quantification analysis, Hilbert-Huang transform methods, the maximum relevance and minimum redundancy method and support vector machine are used to predict the subcellular location of apoptosis proteins. The validation of the jackknife test suggests that the proposed method can improve the prediction accuracy of the subcellular location of apoptosis proteins and its application may be promising in other fields.

Transport and transformation of nitrobenzene in Songhua River and calculation of flux and remnant based on quantification analysis

To evaluate the long-term environmental effect of the nitrobenzene precipitated into Songhua River caused by the explosion accident of CNPC Jilin Petrochemical Company, we have proved that three selected cross sections were all in a completely mixed state which was not affected by the neighborhood flow firstly. The research of the main flux of contaminants indicates that the nitrobenzene flux in all cross sections is less and less, and the attenuation trend is gradually slowing down. From the residual remnant of nitrobenzene in different segments calculated according to the related experimental data, we suppose that parts of nitrobenzene remnant are transferred by the bottom sludge adsorption and resolution. A general analysis model was set up from the one-dimensional counter-flow equation, and functions of atmosphere-water exchange process, deposit-water interaction, and river turbulent mixing and dissemination. The results of this quantification analysis are different from the real calculation, while the gross transformation trend is the same, which indicates that both analyses are based on reality and can reflect the transport and transformation of nitrobenzene actually.

Recurrence quantification analysis on pulse morphological changes in patients with coronary heart disease

OBJECTIVE： To show that the pulse diagnosis used in Traditional Chinese Medicine, combined with nonlinear dynamic analysis, can help identify car- diovascular diseases. METHODS： Recurrence quantification analysis （RQA） was used to study pulse morphological changes in 37 inpatients with coronary heart dis- ease （CHD） and 37 normal subjects （controls）. An in- dependent sample t-test detected significant differ- ences in RQA measures of their pulses. A support vector machine （SVM） classified the groups accord- ing to their RQA measures. Classic time-domain pa- rameters were used for comparison. RESULTS： RQA measures can be divided into two groups. One group of measures [ecurrence rate（RR）, determinism （DEL）, average diagonal line length （L）, maximum length of diagonal structures （Lmax）, Shannon entropy of the frequency distribu- tion of diagonal line lengths （ENTR）, laminarity （LAM）, average length of vertical structures （TT）, maximum length of vertical structures （Vmax）] showed significantly higher values for patients with CHD than for normal subjects （P〈0.0S）. The other measures （RR_std, L_std, Lmaxstd, TT_std, Vmax_std） showed significantly lower values for the CHD group than for normal subjects （P〈0.05）. SVM classification accuracy was higher with RQA measures： With RQA （16 parameters） accuracy was at 88.21%, and with RQA（12 parameters） accuracy was at 84.11%. In contrast, with classic time-do- main （15 parameters） accuracy was 75.73%, and with time-domain （7 parameters） accuracy was 74.7O%. CONCLUSION： Nonlinear dynamic methods such as RQA can be used to study functional and struc- tural changes in the pulse noninvasively. Pulse sig- nals of individuals with CHD have greater regulari- ty, determinism, and stability than normal subjects, and their pulse morphology displays less variabili- ty. RQA can distinguish the CHD pulse from the healthy pulse with an accuracy of 88.21%, thereby providing an early diagnosis of cardiovascular dis- eases such as CHD.

Characterization of various structures in gas-solid fluidized beds by recurrence quantification analysis

Gas-solid fluidized beds are widely considered as nonlinear and chaotic dynamic systems. Pressure fluc- tuations were measured in a fluidized bed of 0.15 m in diameter and were analyzed using multiple approaches： discrete Fourier transform （DFT）, discrete wavelet transform （DWT）, and nonlinear recur- rence quantification analysis （RQA）. Three different methods proposed that the complex dynamics of a fluidized bed system can be presented as macro, meso and micro structures. It was found from DFT and DWT that a minimum in wide band energy with an increase in the velocity corresponds to the transition between macro structures and finer structures of the fluidization system. Corresponding transition veloc- ity occurs at gas velocities of 0.3, 0.5 and 0.6 m]s for sands with mean diameters of 150, 280 and 490/~m, respectively. DFT, DWT, and RQA could determine frequency range of0-3.125 Hz for macro, 3. ! 25-50 Hz for meso, and 50-200 Hz for micro structures. The RQA showed that the micro structures have the least periodicity and consequently their determinism and laminarity are the lowest. The results show that a combination of DFT, DWT, and RQA can be used as an effective approach to characterize multi-scale flow behavior in gas-solid fluidized beds.

Analysis of the Fractal Growth Characteristics and Nucleation Mechanism of Phosphogypsum-based Materials

Phosphogypsum-based materials (PBM) were synthesized with varied phase compositions of phosphogypsum,portland cement and fly ash.Effects of fractal growth characteristics on physicochemical properties,pore structure,compressive strength,as well as the hydration behaviour and mineralogical conversion of mortars were examined by a multitechnological approach,including mercury intrusion porosimetry,rietved phase analysis,thremal analysis,calorimetry and Fourier transforminfrared spectroscopy analysis.Expermental results indicate that the specimens cured with mosite resulted in higher strength and lower porosity compared with those cured in the drying chamber.In addition,a more complicated course of the aluminate and silicate reactions during the hydration process has been published,with the hydration products mainly consisting of calcium silicate hydrate (C-S-H),portlandite,ettringite,hemicarbonate,monocarboaluminate,calcite,quartz,a mixed AFm passed with carbonate,and hydroxide.After all,the nucleation process is a reaction that can be defined as a solid,liquid and gaseous phases that goes through the four stages of materialization mixing and modification,i e,hydration of low calcium content,secondary hydration,high calcium condensation and geoplymensation,respectively.The rupture,recombination,polymerization reactions of Si-O,Ca-O,Al-O bonds contribute to the nucleation mechanism that serves as the formation of C-S-H in hydration products.

Response analysis based on smallest interval-set of parameters for structures with uncertainty

An integral analytic process from quantification to propagation based on limited uncertain parameters is investigated to deal with practical engineering problems. A new method by use of the smallest interval-set/hyper-rectangle containing all exper- imental data is proposed to quantify the parameter uncertainties. With the smallest parameter interval-set, the uncertainty sponse and the least favorable response propagation evaluation of the most favorable re- of the structures is studied based on the interval analysis. The relationship between the proposed interval analysis method （IAM） and the classical IAM is discussed. Two numerical examples are presented to demonstrate the feasibility and validity of the proposed method.

Progress and prediction of multicomponent quantification in complex systems with practical LC-UV methods

Complex systems exist widely,including medicines from natural products,functional foods,and biological samples.The biological activity of complex systems is often the result of the synergistic effect of multiple components.In the quality evaluation of complex samples,multicomponent quantitative analysis(MCQA)is usually needed.To overcome the difficulty in obtaining standard products,scholars have proposed achieving MCQA through the“single standard to determine multiple components(SSDMC)”approach.This method has been used in the determination of multicomponent content in natural source drugs and the analysis of impurities in chemical drugs and has been included in the Chinese Pharmacopoeia.Depending on a convenient(ultra)high-performance liquid chromatography method,how can the repeatability and robustness of the MCQA method be improved?How can the chromatography conditions be optimized to improve the number of quantitative components?How can computer software technology be introduced to improve the efficiency of multicomponent analysis(MCA)?These are the key problems that remain to be solved in practical MCQA.First,this review article summarizes the calculation methods of relative correction factors in the SSDMC approach in the past five years,as well as the method robustness and accuracy evaluation.Second,it also summarizes methods to improve peak capacity and quantitative accuracy in MCA,including column selection and twodimensional chromatographic analysis technology.Finally,computer software technologies for predicting chromatographic conditions and analytical parameters are introduced,which provides an idea for intelligent method development in MCA.This paper aims to provide methodological ideas for the improvement of complex system analysis,especially MCQA.

Proteomic Analysis of Chrysanthemum Lateral Buds after Removing Apical Dominance Based on Label-Free Technology

Studying the genetic basis and regulatory mechanism of chrysanthemum lateral bud outgrowth is of great significance for reduction the production cost of cut chrysanthemum.To clarify the molecular basis of lateral bud elongation after removal of apical dominance in chrysanthemum,label-free quantification analysis was used to analyze the proteome changes after apical bud removal.Quantitative real-time PCR(qPCR)was used to analyze the changes in the expression of three plant hormone-related genes.A total of 440 differentially expressed proteins were successfully identified at three time points during the lateral bud elongation.The number of differentially expressed proteins in the three stages(24 h/0 h,48 h/0 h,48 h/24 h)were 219,332,and 97,respectively.The difference in expressed proteins in the three comparison stages mainly involves RNA processing and modification;translation,ribosomal structure and biogenesis;Posttranslational modification,protein turnover,and chaperones.Path analysis showed that there was various physiological activities in the process of lateral bud dormancy breaking and elongation,which involved energy metabolism,biosynthesis,signal transduction and stress response in the growth process of lateral buds.qPCR indicated that the expression of cytokinin synthesis related gene was significantly increased after the removal of apical dominance,while the expression of strigolactones synthesis related gene experiences a dramatic fall to promote the development of the lateral buds.However,there was a drop before a slight increase in the expression of the auxin synthesis related gene,which was mainly due to the removal of apical dominance that led to the loss of indoleacetic acid in the main stem.However,with formation of the new apical source,indoleacetic acid can be released again.

Hidden Sequence Repeats: Additional Evidence for the Origin of TIM-Barrel Family

Most proteins adopt an approximate structural symmetry. However, they have no symmetry detectable in their sequences and it is unclear for most of these proteins whether their structural symmetry originates from duplication. As one of the six popular folds (super-folds) possessing an approximate structural symmetry, the triosephosphate isomerase barrel (TIM-barrel) domain has been widely studied. Using modified recurrent quantification analysis of primary sequences, we identified the same 2-, 3-, and 4-fold symmetry pattern as their tertiary structures. This result indicates that the symmetry in tertiary structure is coded by symmetry in the primary sequence and that the TIM-barrel adopts a 2-, 3-, or 4-fold repeat pattern during evolution. This discovery will be useful for understanding the evolutionary mechanisms of this protein family and the symmetry pattern that may be a clue into the ancient origin of duplication of half-barrels or the β a unit.

Automatic Assessment of Expanded Disability Status Scale (EDSS) in Multiple Sclerosis Using a Decision Tree

The expanded disability status scale (EDSS) is frequently used to classify the patients with multiple sclerosis (MS). We presented in this paper a novel method to automatically assess the EDSS score from posturologic data (center of pres-sure signals) using a decision tree. Two groups of participants (one for learning and the other for test) with EDSS rang-ing from 0 to 4.5 performed our balance experiment with eyes closed. Two linear measures (the length and the surface) and twelve non-linear measures (the recurrence rate, the Shannon entropy, the averaged diagonal line length and the trapping time for the position, the instantaneous velocity and the instantaneous acceleration of the center of pressure respectively) were calculated for all the participants. Several decision trees were constructed with learning data and tested with test data. By comparing clinical and estimated EDSS scores in the test group, we selected one decision tree with five measures which revealed a 75% of agreement. The results have signified that our tree model is able to auto-matically assess the EDSS scores and that it is possible to distinguish the EDSS scores by using linear and non-linear postural sway measures.

Parametric sensitivity analysis of precipitation and temperature based on multi-uncertainty quantification methods in the Weather Research and Forecasting model

Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.

Multiscale characterization of nanoparticles in a magnetically assisted fluidized bed

Pressure fluctuations of a fluidized bed of nanoparticles were measured during the fluidization of nanoparticles with and without a magnetic field at a frequency of 50 Hz.Recurrence quantification analysis(RQA)and wavelet transform were used to determine the frequency range of various flow structures in the bed at three scales.The frequency ranges of the macro-,meso-,and micro-structures were determined to be 0-49Hz,49-781 Hz,and 781+Hz,respectively.Comparison of the determinisms of the sub-signals with and without the external field revealed that in the presence the field,breakage of larger agglomerates occurs faster than re-agglomeration of small agglomerates into larger ones.The power spectral density function of the pressure fluctuations indicated that with an external magnetic field,the power and the frequency range of the pressure signal of macro-structures do not change noticeably.However,the power of the meso-structure signal increases and its frequency range is widened toward higher frequencies,confirming that the number of small bubbles and agglomerates increase in the bed.ln addition,the energy of signal analysis indicated that the external field significantly increases the share of meso-structures in the bed,confirming the RQA results.

Quantitative evaluation of model consistency evolution in compositional service-oriented simulation using a connected hyper-digraph

Appropriate maintenance technologies that facilitate model consistency in distributed simulation systems are relevant but generally unavailable.To resolve this problem,we analyze the main factors that cause model inconsistency.The analysis methods used for traditional distributed simulations are mostly empirical and qualitative,and disregard the dynamic characteristics of factor evolution in model operational running.Furthermore,distributed simulation applications(DSAs)are rapidly evolving in terms of large-scale,distributed,service-oriented,compositional,and dynamic features.Such developments present difficulty in the use of traditional analysis methods in DSAs,for the analysis of factorial effects on simulation models.To solve these problems,we construct a dynamic evolution mechanism of model consistency,called the connected model hyper-digraph(CMH).CMH is developed using formal methods that accurately specify the evolutional processes and activities of models(i.e.,self-evolution,interoperability,compositionality,and authenticity).We also develop an algorithm of model consistency evolution(AMCE)based on CMH to quantitatively and dynamically evaluate influencing factors.Experimental results demonstrate that non-combination(33.7%on average)is the most influential factor,non-single-directed understanding(26.6%)is the second most influential,and non-double-directed understanding(5.0%)is the least influential.Unlike previous analysis methods,AMCE provides good feasibility and effectiveness.This research can serve as guidance for designers of consistency maintenance technologies toward achieving a high level of consistency in future DSAs.