Chaos game representation of functional protein sequences,and simulation and multifractal analysis of induced measures

Investigating the biological function of proteins is a key aspect of protein studies. Bioinformatic methods become important for studying the biological function of proteins. In this paper, we first give the chaos game representation （CGR） of randomly-linked functional protein sequences, then propose the use of the recurrent iterated function systems （RIFS） in fractal theory to simulate the measure based on their chaos game representations. This method helps to extract some features of functional protein sequences, and furthermore the biological functions of these proteins. Then multifractal analysis of the measures based on the CGRs of randomly-linked functional protein sequences are performed. We find that the CGRs have clear fractal patterns. The numerical results show that the RIFS can simulate the measure based on the CGR very well. The relative standard error and the estimated probability matrix in the RIFS do not depend on the order to link the functional protein sequences. The estimated probability matrices in the RIFS with different biological functions are evidently different. Hence the estimated probability matrices in the RIFS can be used to characterise the difference among linked functional protein sequences with different biological functions. From the values of the Dq curves, one sees that these functional protein sequences are not completely random. The Dq of all linked functional proteins studied are multifractal-like and sufficiently smooth for the Cq （analogous to specific heat） curves to be meaningful. Furthermore, the Dq curves of the measure μ based on their CCRs for different orders to link the functional protein sequences are almost identical if q 〉 0. Finally, the Ca curves of all linked functional proteins resemble a classical phase transition at a critical point.

Effects of restoration modes on the spatial distribution of soil physical properties after land consolidation: a multifractal analysis

Soil physical properties(SPP)are considered to be important indices that reflect soil structure,hydrological conditions and soil quality.It is of substantial interest to study the spatial distribution of SPP owing to the high spatial variability caused by land consolidation under various land restoration modes in excavated farmland in the loess hilly area of China.In our study,three land restoration modes were selected including natural restoration land(NR),alfalfa land(AL)and maize land(ML).Soil texture composition,including the contents of clay,silt and sand,field capacity(FC),saturated conductivity(Ks)and bulk density(BD)were determined using a multifractal analysis.SPP were found to possess variable characteristics,although land consolidation destroyed the soil structure and decreased the spatial autocorrelation.Furthermore,SPP varied with land restoration and could be illustrated by the multifractal parameters of D1,ΔD,ΔαandΔf in different modes of land restoration.Owing to multiple compaction from large machinery in the surface soil,soil particles were fine-grained and increased the spatial variability in soil texture composition under all the land restoration modes.Plough numbers and vegetative root characteristics had the most significant impacts on the improvement in SPP,which resulted in the best spatial distribution characteristics of SPP found in ML compared with those in AL and NR.In addition,compared with ML,Δαvalues of NR and AL were 4.9-and 3.0-fold that of FC,respectively,andΔαvalues of NR and AL were 2.3-and 1.5-fold higher than those of Ks,respectively.These results indicate that SPP can be rapidly improved by increasing plough numbers and planting vegetation types after land consolidation.Thus,we conclude that ML is an optimal land restoration mode that results in favorable conditions to rapidly improve SPP.

Protein structural classification and family identification by multifractal analysis and wavelet spectrum

Family identification is helpful for predicting protein functions. It has been known from the literature that longer sequences of base pairs or amino acids are required to study patterns in biological sequences. Since most protein sequences are relatively short, we randomly concatenate or link the protein sequences from the same family or superfamily together to form longer protein sequences. The 6-letter model, 12-letter model, 20-letter model, the revised Schneider and Wrede scale hydrophobicity, solvent accessibility and stochastic standard state accessibility are used to convert linked protein sequences into numerical sequences. Then multifractal analyses and wavelet analysis are performed on these numerical sequences. The parameters from these analyses can be used to construct parameter spaces where each linked protein is represented by a point. The four classes of proteins, namely the α/β, α＋β and α/β classes, are then distinguished in these parameter spaces. The Fisher linear discriminant algorithm is used to assess the discriminant accuracy. Numerical results indicate that the discriminant accuracies are satisfactory in separating these classes. We find that the linked proteins from the same family or superfamily tend to group together and can be separated from other linked proteins. The methods are helpful for identifying the family of an unknown protein.

MULTIFRACTAL ANALYSIS OF THE CONVERGENCE EXPONENT IN CONTINUED FRACTIONS

Let x∈(0,1)be a real number with continued fraction expansion[a_(1)(x),a_(2)(x),a_(3)(x),⋯].This paper is concerned with the multifractal spectrum of the convergence exponent of{a_(n)(x)}_(n≥1) defined by τ(x):=inf{s≥0:∑n≥1an^(-s)(x)<∞}.

Relationships of exponents in multifractal detrended fluctuation analysis and conventional multifractal analysis

Multifractal detrended fluctuation analysis （MF-DFA） is a relatively new method of multifractal analysis. It is extended from detrended fluctuation analysis （DFA）, which was developed for detecting the long-range correlation and the fractal properties in stationary and non-stationary time series. Although MF-DFA has become a widely used method, some relationships among the exponents established in the original paper seem to be incorrect under the general situation. In this paper, we theoretically and experimentally demonstrate the invalidity of the expression r（q） = qh（q） - 1 stipulating the relationship between the multifractal exponent T（q） and the generalized Hurst exponent h（q）. As a replacement, a general relationship is established on the basis of the universal multifractal formalism for the stationary series as .t-（q） = qh（q） - qH - 1, where H is the nonconservation parameter in the universal multifractal formalism. The singular spectra, a and f（a）, are also derived according to this new relationship.

Joint multifractal analysis based on wavelet leaders

Mutually interacting components form complex systems and these components usually have long- range cross-correlated outputs. Using wavelet leaders, we propose a method for characterizing the joint multifractal nature of these long-range cross correlations; we call this method joint multifractal analysis based on wavelet leaders （MF-X-WL）. We test the validity of tile MF-X-WL method by performing extensive numerical experiments on dual binomial measures with multifractal cross correlations and bivariate fractional Brownian motions （bFBMs） with monofractal cross correlations. Both experiments indicate that MF-X-WL is capable of detecting cross correlations in synthetic data with acceptable estimating errors. We also apply the MF-X-WL method to pairs of series from financial markets （returns and volatilities） and online worlds （online numbers of different genders and different societies） and determine intriguing joint multifractal behavior.

Synchrotron X-ray microtomography and multifractal analysis for the characterization of pore structure and distribution in softwood pellet biochar

Biochar pores in the micrometer range(1-100μm)derive from cellular structures of the plant biomass subjected to pyrolysis or can be the result of mechanical processing,such as pelleting.In this study,synchrotron X-ray microtomography was used to investigate the internal pore structure of softwood pellet biochar produced by slow pyrolysis at 550 and 700°C.The microtomographic data sets consisted of 2025 images of 2560×2560 voxels with a voxel side length of 0.87μm.The three-dimensional reconstructions revealed that pelleting and pyrolysis significantly altered the pore structures of the wood feedstock,creating a network of connected pores between fragments that resembled the wood morphology.While higher pyrolysis temperature increased the specific surface area(as determined by BET nitrogen adsorption),it did not affect the total observed porosity.Multifractal analysis was applied to assess the characteristics of the frequency distribution of pores along each of the three dimensions of reconstructed images of five softwood pellet biochar samples.The resulting singular-ity and Rényi spectra(generalized dimensions)indicated that the distribution of porosity had monofractal scaling behavior,was homogeneous within the analyzed volumes and consistent between replicate samples.Moreover,the pore distributions were isotropic(direction-independent),which is in strong contrast with the anisotropic pore structure of wood.As pores at the scale analyzed in this study are relevant,for example,for the supply of plant accessible water and habitable space for microorganisms,our findings combined with the ability to reproduce biochar with such pore distribution offer substantial advantages in various biochar applications.

MULTIFRACTAL ANALYSIS OF PARTICLE-FLUID SYSTEM IN A CIRCULATING FLUIDIZED BED

In this paper, multifractal analysis together with wavelet transform modulus maxima (WTMM) method is used to analyze the fluctuating signals of circulating fluidized bed (CFB). Singularity spectrum shows that the gas-particle flow in CFB has multifractal character. Motion behavior of the particle-fluid system of CFB can be described by singularity spectrum. Intermittency index can be used to determine the transition of flow regime from fast fluidization to pneumatic conveying.

A Multifractal Detrended Fluctuation Analysis of the Ising Financial Markets Model with Small World Topology

We present a multifractal detrended fluctuation analysis （MFDFA） of the time series of return generated by our recently-proposed Ising financial market model with underlying small world topology. The result of the MFDFA shows that there exists obvious multifractal scaling behavior in produced time series. We compare the MFDFA results for original time series with those for shuffled series, and find that its multifractal nature is due to two factors： broadness of probability density function of the series and different correlations in small- and large-scale fluctuations. This may provide new insight to the problem of the origin of multifractality in financial time series.

Analysis of normal human retinal vascular network architecture using multifractal geometry

AIM：To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina.METHODS：Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca,Romania,between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images,corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms,applying the standard boxcounting method. Statistical analyses were performed using the Graph Pad In Stat software.RESULTS：The architecture of normal human retinal microvascular network was able to be described using the multifractal geometry. The average of generalized dimensions（D_q）for q=0,1,2,the width of the multifractal spectrum（Δα=α_（max）-α_（min））and the spectrum arms＇ heights difference（│Δf│）of the normal images were expressed as mean±standard deviation（SD）：for segmented versions,D_0=1.7014±0.0057; D_1=1.6507±0.0058; D_2=1.5772±0.0059; Δα=0.92441±0.0085; │Δf│= 0.1453±0.0051; for skeletonised versions,D_0=1.6303±0.0051; D_1=1.6012±0.0059; D_2=1.5531± 0.0058; Δα=0.65032±0.0162; │Δf│= 0.0238±0.0161. The average of generalized dimensions（D_q）for q=0,1,2,the width of the multifractal spectrum（Δα）and the spectrum arms＇ heights difference（│Δf│）of the segmented versions was slightly greater than the skeletonised versions.CONCLUSION：The multifractal analysis of fundus photographs may be used as a quantitative parameter for the evaluation of the complex three-dimensional structure of the retinal microvasculature as a potential marker for early detection of topological changes associated with retinal diseases.

Correlation analysis between the Aral Sea shrinkage and the Amu Darya River

The shrinkage of the Aral Sea,which is closely related to the Amu Darya River,strongly affects the sustainability of the local natural ecosystem,agricultural production,and human well-being.In this study,we used the Bayesian Estimator of Abrupt change,Seasonal change,and Trend(BEAST)model to detect the historical change points in the variation of the Aral Sea and the Amu Darya River and analyse the causes of the Aral Sea shrinkage during the 1950–2016 period.Further,we applied multifractal detrend cross-correlation analysis(MF-DCCA)and quantitative analysis to investigate the responses of the Aral Sea to the runoff in the Amu Darya River,which is the main source of recharge to the Aral Sea.Our results showed that two significant trend change points in the water volume change of the Aral Sea occurred,in 1961 and 1974.Before 1961,the water volume in the Aral Sea was stable,after which it began to shrink,with a shrinkage rate fluctuating around 15.21 km3/a.After 1974,the water volume of the Aral Sea decreased substantially at a rate of up to 48.97 km3/a,which was the highest value recorded in this study.In addition,although the response of the Aral Sea's water volume to its recharge runoff demonstrated a complex non-linear relationship,the replenishment of the Aral Sea by the runoff in the lower reaches of the Amu Darya River was identified as the dominant factor affecting the Aral Sea shrinkage.Based on the scenario analyses,we concluded that it is possible to slow down the retreat of the Aral Sea and restore its ecosystem by increasing the efficiency of agricultural water use,decreasing agricultural water use in the middle and lower reaches,reducing ineffective evaporation from reservoirs and wetlands,and increasing the water coming from the lower reaches of the Amu Darya River to the 1961–1973 level.These measures would maintain and stabilise the water area and water volume of the Aral Sea in a state of ecological restoration.Therefore,this study focuses on how human consumption of recharge runoff affects the Aral Sea and provides scientific perspective on its ecological conservation and sustainable development.

SAR image denoising based on wavelet-fractal analysis

Wavelet-fractal based SAR （synthetic aperture radar） image processing is one of the advanced technologies in image processing. The main concept of analysis is that after wavelet transformation, multifractal spectrum of the signal is different from that of noise. This difference is used to alleviate the noise produced by SAR image.The method to denoise SAR image using the process based on wavelet-fractai analysis is discussed in detail. Essentially, the present method focuses on adjusting the Hoelder exponent α of multifractal spectrum. After simulation, α should be adjusted to 1.72-1.73. The more the value of α exceeds 1.73, the less distinctive the edges of SAR image become. According to the authors denoising is optimal at α=1.72-1.73. In other words, when α =1.72-1.73, a smooth and denoised SAR image is produced.

Image Analysis in Microbiology: A Review

This review is focused on using computer image analysis as a means of objective and quantitative characterizing optical images of the macroscopic (e.g. microbial colonies) and the microscopic (e.g. single cell) objects in the microbiological research. This is the way of making many visual inspection assays more objective and less time and labor consuming. Also, it can provide new visually inaccessible information on relation between some optical parameters and various biological features of the microbial cul-tures. Of special interest is application of image analysis in fluorescence microscopy as it opens new ways of using fluorescence based methodology for single microbial cell studies. Examples of using image analysis in the studies of both the macroscopic and the microscopic microbiological objects obtained by various imaging techniques are presented and discussed.

Morphology and multifractal features of a guyot in specific topographic vicinity in the Caroline Ridge,West Pacific

Massive seamounts have been surveyed and documented in the last decades.However,the morphologies of seamounts are usually described in qualitative manners,yet few quantitative detections have been carried out.Here,based on the high-re solution multi-beam bathymetric data,we report a recentlysurveyed guy ot on the Caroline Ridge in the West Pacific,and the large-scale volcanic structures and smallscale erosive-depositional landforms in the guyot area have been identified.The multifractal features of the guyot are characterized for the first time by applying multifractal detrended fluctuation analysis on the surveyed bathymetric data.The results indicate that the multifractal spectrum parameters of the seafloor have strong spatial dependency on the fluctuations of local landforms.Both small-and large-scale components contribute to the degree of asymmetry of the multifractal spectrum(B),while the fluctuations of B are mostly attributed to the changes in small-scale roughness.The maximum singularity strength(α0)correlates well with the roughness of large-scale landforms and likely reflects the large-scale topographic irregularity.Comparing to traditional roughness parameters or monofractal exponents,multifractal spectra are able to depict not only the multiscale characteristics of submarine landforms,but also the spatial variations of scaling behaviors.Although more comparative works are required for various seamounts,we hope this study,as a case of quantifying geomorphological characters and multiscale behaviors of seamounts,can encourage further studies on seamounts concerning geomorphological processes,ocean bottom circulations,and seamount ecosystems.

Modeling and forecasting time series of precious metals:a new approach to multifractal data

We introduce a novel approach to multifractal data in order to achieve transcended modeling and forecasting performances by extracting time series out of local Hurst exponent calculations at a specified scale.First,the long range and co-movement dependencies of the time series are scrutinized on time-frequency space using multiple wavelet coherence analysis.Then,the multifractal behaviors of the series are verified by multifractal de-trended fluctuation analysis and its local Hurst exponents are calculated.Additionally,root mean squares of residuals at the specified scale are procured from an intermediate step during local Hurst exponent calculations.These internally calculated series have been used to estimate the process with vector autoregressive fractionally integrated moving average(VARFIMA)model and forecasted accordingly.In our study,the daily prices of gold,silver and platinum are used for assessment.The results have shown that all metals do behave in phase movement on long term periods and possess multifractal features.Furthermore,the intermediate time series obtained during local Hurst exponent calculations still appertain the co-movement as well as multifractal characteristics of the raw data and may be successfully re-scaled,modeled and forecasted by using VARFIMA model.Conclusively,VARFIMA model have notably surpassed its univariate counterpart(ARFIMA)in all efficacious trials while re-emphasizing the importance of comovement procurement in modeling.Our study’s novelty lies in using a multifractal de-trended fluctuation analysis,along with multiple wavelet coherence analysis,for forecasting purposes to an extent not seen before.The results will be of particular significance to finance researchers and practitioners.

Detection of meso-micro scale surface features based on microcanonical multifractal formalism

Synthetic aperture radar （SAR） is an effective tool to analyze the features of the ocean. In this paper, the microcanon- ical multifractal formalism is used to analyze SAR images to obtain meso-micro scale surface features. We use the Sobel operator to calculate the gradient of each point in the image, then operate continuous variable scale wavelet transform on this gradient matrix. The relationship between the wavelet coefficient and scale is built by linear regression. This relation- ship decides the singular exponents of every point in the image which contain local and global features. The manifolds in the ocean can be revealed by analyzing these exponents. The most singular manifold, which is related to the streamlines in the SAR images, can be obtained with a suitable threshold of the singular exponents. Experiments verify that application of the microcanonical multifractal formalism to SAR image analysis is effective for detecting the meso-micro scale surface information.

Multifractal modeling of the production of concentrated sugar syrup crystal

High quality, concentrated sugar syrup crystal is produced in a critical step in cane sugar production： the clarification process. It is characterized by two variables： the color of the produced sugar and its clarity degree. We show that the temporal variations of these variables follow power-law distributions and can be well modeled by multiplicative cascade multifractal processes. These interesting properties suggest that the degradation in color and clarity degree has a systemwide cause. In particular, the cascade multifractal model suggests that the degradation in color and clarity degree can be equivalently accounted for by the initial ＂impurities＂ in the sugarcane. Hence, more effective cleaning of the sugarcane before the clarification stage may lead to substantial improvement in the effect of clarification.

Argument on the magnitude-frequency relation

The complexity of seismicity and the relation of magnitude and frequency are discussed in this paper on the basis of nonlinear dynamics and multifractal theory. We argue that seismic active systems normally have multifractal characteristics, either for the spatial-temporal distribution or the intensity distribution of events. In the view of multifractal theory the nonlinear characteristics of the magnitude-frequency relation are discussed and the formulation is revised. Also, one example of the variance of bq estimated based on the recent New Zealand catalogue is enumerated.

A new protection scheme for PV-wind based DC-ring microgrid by using modified multifractal detrended fluctuation analysis

This paper presents fault detection,classification,and location for a PV-Wind-based DC ring microgrid in the MATLAB/SIMULINK platform.Initially,DC fault signals are collected from local measurements to examine the outcomes of the proposed system.Accurate detection is carried out for all faults,(i.e.,cable and arc faults)under two cases of fault resistance and distance variation,with the assistance of primary and secondary detection techniques,i.e.second-order differential current derivatived2I3 dt2and sliding mode window-based Pearson’s correlation coefficient.For fault classification a novel approach using modified multifractal detrended fluctuation analysis(M-MFDFA)is presented.The advantage of this method is its ability to estimate the local trends of any order polynomial function with the help of polynomial and trigonometric functions.It also doesn’t require any signal processing algorithm for decomposition resulting and this results in a reduction of computational burden.The detected fault signals are directly passed through the M-MFDFA classifier for fault type classification.To enhance the performance of the proposed classifier,statistical data is obtained from the M-MFDFA feature vectors,and the obtained data is plotted in 2-D and 3-D scatter plots for better visualization.Accurate fault distance estimation is carried out for all types of faults in the DC ring bus microgrid with the assistance of recursive least squares with a forgetting factor(FF-RLS).To verify the performance and superiority of the proposed classifier,it is compared with existing classifiers in terms of features,classification accuracy(CA),and relative computational time(RCT).

SINGULAR BOUNDARY PROPERTIES OF HARMONIC FUNCTIONS AND FRACTAL ANALYSIS

This paper shows an important relation between the fractal analysis and the boundary properties of harmonic functions.It is proved that the multifractal analysis of a finite measureμonIR^(d)determines the(non-tangential)boundary increasing properties ofPμ,the Poisson integral ofμwhich is harmonic onIR^(d+1)_(+).Some examples are given.