Statistical Dynamics of Clustering in the Genome Structure

Clustering and long-range correlations in the nucleotide sequences of different categories of organisms are discussed. Clustering, mostly observed in higher eucaryotes, can be found at different length scales in DNA and Central Limit Theorems are used as links between these length scales. Several dynamical, statistical, mean-field models are proposed based on biologically motivated dynamical mechanisms and they successfully reproduce both the short range behavior observed in coding DNA and the long range, out-of-equilibrium features of non-coding DNA. Such dynamical mechanisms include aggregation of oligonucleotides, influx and DNA length reduction schemes, transpositions, and fusions of large DNA macromolecules. Fractality can be inferred from the short and long range correlations observed in the sequence structure of higher eucaryotes, where the non-coding part is relatively extended. In these organisms the DNA coding/non-coding alternation has the characteristics of finite size, fractal, random sets.     

Two general models that generate long range correlation

In this paper we study two models that generate sequences with LRC (long range correlation). For the IFT (inverse Fourier transform) model, our conclusion is the low frequency part leads to LRC, while the high frequency part tends to eliminate it. Therefore, a typical method to generate a sequence with LRC is multiplying the spectrum of a white noise sequence by a decaying function. A special case is analyzed: the linear combination of a smooth curve and a white noise sequence, in which the DFA plot consists of two line segments. For the patch model, our conclusion is long subsequences leads to LRC, while short subsequences tend to eliminate it. Therefore, we can generate a sequence with LRC by using a fat-tailed PDF (probability distribution function) of the length of the subsequences. A special case is also analyzed: if a patch model with long subsequences is mixed with a white noise sequence, the DFA plot will consist of two line segments. We have checked known models and actual data, and found they are all consistent with this study.     

The Composition,Sequence Analysis,and Crystallization Characterization of Poly(Trimethylene‐co‐Butylene Terephthalate) Copolymer

A series of poly(trimethylene‐co‐butylene terephthalate) (PTBT) copolymers were prepared by direct esterification followed by polycondensation. The composition and sequence distribution of the copolymers were investigated by nuclear magnetic resonance (NMR). The results demonstrate that the synthesized PTBT copolymers are block copolymers and the content of poly(butylene terephthalate) (PBT) units incorporated into the copolymers is always less than that in the polymerization feed. The 1,4‐butanediol consumption by a side reaction leads to a relatively lower content of PBT units in the resultant copolymers. At the same time, the PBT and poly(trimethylene terephthalate) (PTT) sequence length distributions in the copolymers are different. The PBT segments favor a longer sequence length than do the PTT segments in their corresponding enriched copolymers. The crystallization rate of the copolymers becomes lower than the homopolymers, especially for PTT‐enriched copolymers. Compared with the PTT segment, the presence of PBT segments in the copolymers seems to accelerate crystallization. A wide‐angle X‐ray diffraction (WAXD) analysis indicates PTT and PBT units do not co‐crystallize. The reduced melting temperatures of the copolymers may be attributed to a smaller lamellar thickness and lateral size due to short sequence lengths.     

Repeat Sequences and Base Correlations in Human Y ChromosomePalindromes

利用信息论和统计学的方法并结合生物学的特征研究人类Y染色体回文序列的互信息、“n字”熵、条件熵,定量分析了回文序列的长程关联和短程关联,发现其中既存在长程关联也存在短程关联,并且它们主要是由序列中的重复序列引起的. 研究表明重复序列含量越高碱基之间的关联越强.     

Semi-randomly constructed optical orthogonal codes

Optical orthogonal code (OOC) sequences are assigned to optical code-division multiple-access (OCDMA) network users, who are able to transmit data asynchronously. In this work, we propose a semi-random OOC design technique based on extended sets, where the input parameters are the sequence weight, number of sequences (i.e., users), and a target sequence length. The design method under consideration is able to converge to the desired short OOC lengths given the number of iterations during the execution of the algorithm is sufficiently large.     

Geometry and topology of escape. II. Homotopic lobe dynamics

We continue our study of the fractal structure of escape-time plots for chaotic maps. In the preceding paper, we showed that the escape-time plot contains regular sequences of successive escape segments, called epistrophes, which converge geometrically upon each end point of every escape segment. In the present paper, we use topological techniques to: (1) show that there exists a minimal required set of escape segments within the escape-time plot; (2) develop an algorithm which computes this minimal set; (3) show that the minimal set eventually displays a recursive structure governed by an "Epistrophe Start Rule:" a new epistrophe is spawned Delta=D+1 iterates after the segment to which it converges, where D is the minimum delay time of the complex.     

Phylogenetic study of the spatial distribution of protein-coding and control segments in DNA chains

We examine the size and spatial distributions of the protein-coding and control segments of genes in DNA nucleotide sequences from GenBank. Phylogenetic analysis of these data suggests the presence of spatial order in sequences of higher organisms, irrespective of the nature of nucleotide base content. This is characterized by defined two-point correlation functions and measured by fractal dimensions and singularity spectrum.     

A comparison of magnetization prepared 3D gradientecho (MP-RAGE) sequences for imaging of intracranial lesions

In a pilot study including 64 patients with different types of brain tumors we investigated four types of MP-RAGE sequences. The sequences differ in the length of the recovery period and the data acquisition mode (sequential vs. centric phase-encoding). The sequence with sequential encoding and a short recovery period provided images that reached the quality and reliability of spin-echo images. The other MP-RAGE sequences failed in providing equivalent information. In particular, a considerable number of small lesions identified in spin-echo images were not detected in MP-RAGE images. The impact of the evolving magnetization on the point spread function was analyzed by performing simulation calculations. It was found that lesions with short T₁ times are rendered with low spatial resolution when sequence parameters are not set appropriately. The low overall quality of images obtained by sequences applying centric encoding may be explained by eddy current effects as reported in other recently published studies.     

Investigation of determinism in heart rate variability

The article searches for the possible presence of determinism in heart rate variability (HRV) signals by using a new approach based on NARMA (nonlinear autoregressive moving average) modeling and free-run prediction. Thirty-three 256-point HRV time series obtained from Wistar rats submitted to different autonomic blockade protocols are considered, and a collection of surrogate data sets are generated from each one of them. These surrogate sequences are assumed to be nondeterministic and therefore they may not be predictable. The original HRV time series and related surrogates are submitted to NARMA modeling and prediction. Special attention has been paid to the problem of stationarity. The results consistently show that the surrogate data sets cannot be predicted better than the trivial predictor-the mean-while most of the HRV control sequences are predictable to a certain degree. This suggests that the normal HRV signals have a deterministic signature. The HRV time series derived from the autonomic blockade segments of the experimental protocols do not show the same predictability performance, albeit the physiological interpretation is not obvious. These results have important implications to the methodology of HRV analysis, indicating that techniques from nonlinear dynamics and deterministic chaos may be applied to elicit more information about the autonomic modulation of the cardiovascular activity. (c) 2000 American Institute of Physics.     

Amino acid type identification in NMR spectra of proteins via beta- and gamma-carbon edited experiments

In this work, we introduce a set of pulse sequences that provide amino acid type identification of the NH correlation signals of proteins. The first pulse sequence is a modification of the CBCA(CO)NH experiment that exploits spin-coupling topologies to differentiate between amino acid types. A set of eight 2D ¹H–¹⁵N correlation spectra is recorded where the sign of the cross-peaks change from one spectrum to another according to the amino acid type of the preceding residue in the protein sequence. Linear combination of these eight data sets produces four subspectra. Taking also into account the sign of the correlation signals, this method allows the classification of the NH signals into six different groups, depending on the character of the preceding residue. This sequence is complemented with a (CGCBCACO)NH experiment that allows the subdivision of the largest of these groups into two smaller ones. Finally, a modification of the CBCANH experiment led to a similar classification of NH signals into six different groups, but now depending on the type of its own amino acid. The set of pulse sequences is demonstrated with two proteins of small to moderate size.     

Toward a model for lexical access based on acoustic landmarks and distinctive features

This article describes a model in which the acoustic speech signal is processed to yield a discrete representation of the speech stream in terms of a sequence of segments, each of which is described by a set (or bundle) of binary distinctive features. These distinctive features specify the phonemic contrasts that are used in the language, such that a change in the value of a feature can potentially generate a new word. This model is a part of a more general model that derives a word sequence from this feature representation, the words being represented in a lexicon by sequences of feature bundles. The processing of the signal proceeds in three steps: (1) Detection of peaks, valleys, and discontinuities in particular frequency ranges of the signal leads to identification of acoustic landmarks. The type of landmark provides evidence for a subset of distinctive features called articulator-free features (e.g., [vowel], [consonant], [continuant]). (2) Acoustic parameters are derived from the signal near the landmarks to provide evidence for the actions of particular articulators, and acoustic cues are extracted by sampling selected attributes of these parameters in these regions. The selection of cues that are extracted depends on the type of landmark and on the environment in which it occurs. (3) The cues obtained in step (2) are combined, taking context into account, to provide estimates of "articulator-bound" features associated with each landmark (e.g., [lips], [high], [nasal]). These articulator-bound features, combined with the articulator-free features in (1), constitute the sequence of feature bundles that forms the output of the model. Examples of cues that are used, and justification for this selection, are given, as well as examples of the process of inferring the underlying features for a segment when there is variability in the signal due to enhancement gestures (recruited by a speaker to make a contrast more salient) or due to overlap of gestures from neighboring segments.     

A novel local PCA-based method for detecting activation signals in fMRI.

A novel local principal component analysis (LPCA) technique is presented for activation signal detection in functional magnetic resonance imaging (fMRI) without explicit knowledge about the shape of the model activation signal. Unlike the traditional PCA methods, our LPCA algorithm is based on a measure of separation between two clusters formed by the signal segments in active periods and inactive periods, which is computed in an eigen-subspace. In addition, we only applied PCA to the temporal sequence of each individual voxel instead of applying PCA to the fMRI data set. In our algorithm, we first applied a linear regression procedure to alleviate the baseline drift artifact. Then, the baseline-corrected temporal signals were partitioned into active and inactive segments according to the paradigm used for the fMRI data acquisition. Principal components were computed from all these segments for each voxel by PCA. By projecting the segments of each voxel onto a linear subspace formed by the corresponding most dominant principal components, two separate clusters were formed from active and inactive segments. An activation measure was defined based on the degree of separation between these two clusters in the projection space. We show experimental results on the activation signal detection from various sets of fMRI data with different types of stimulation by using the proposed LPCA algorithm and the standard t-test method for comparison. Our experiments indicate that the LPCA algorithm in general provides substantial signal-to-noise ratio improvement over the t-test method.     

Physical random access signal design for 5G mobile satellite communication systems

In view of the distinctive characteristics of satellite communication, the physical random access signals used in the terrestrial mobile communication system have to be modified or redesigned for the satellite communication system. In this paper, we boost the random access signal energy by repeating the short Zadoff–Chu (ZC) sequence based preamble signal used in the terrestrial system. Different long ZC sequences are used to scramble this cascaded sequence to distinguish different random access signals for multiple random access user equipments. For correlation performance optimization, properties of the roots for both the short and long ZC sequences are mathematically analyzed and derived. Finally, we illustrate how to construct a root set for these different long ZC sequences based on the obtained propositions in a practical way. This analytical framework provides a useful insight into ZC sequence-based random access signal design and performance analysis in mobile satellite communication systems.     

基于WGAN的不均衡太赫兹光谱识别

物质的太赫兹光谱具有唯一性。目前,结合先进的机器学习方法,研究基于规模光谱数据库的太赫兹光谱识别技术已成为太赫兹应用技术领域的重点。考虑到由于实验条件及实验设备的影响,很难收集到多物质均衡光谱数据,而这又是对太赫兹光谱数据进行分类的基础。针对这一问题,提出一种基于WGAN的不均衡太赫兹光谱识别方法。WGAN作为生成数据的一种新方法,将模型达到纳什均衡条件下的生成数据用来补充数据集,使其达到类别均衡。生成数据可以有效映射真实数据分布,通过将生成数据与真实数据混合训练可以提高识别不均衡光谱数据的准确率。采用三种特征谱较为相似的麦芽糖化合物的太赫兹透射光谱数据进行验证,首先利用S-G滤波和三次样条插值法对三种物质的光谱数据进行归一化处理,然后通过构建WGAN模型对三种物质的不均衡太赫兹光谱数据进行扩展,使其达到类别均衡。实验在同一测试集下进行验证,并利用三组对比实验证明WGAN在不均衡数据集处理中的效果。首先利用WGAN生成数据,随着迭代次数的增加,生成数据逐渐符合真实数据分布。实验结果证明,使用WGAN扩展后的数据集训练SVM模型,可以解决模型在测试集上小样本数据（Maltotriose,Malthexaose）偏向大样本数据（Maltoheptaose）的问题。在将WGAN与传统处理不均衡数据集方法FWSVM和COPY对比后发现,三种分类算法在dataset-1数据集上的训练集准确率都能达到90%以上。但是由于模型泛化能力的限制,传统方法在测试集上的效果并不是很理想,而使用WGAN后的测试集准确率却能达到91.54%。在不同不均衡度方面,采用不均衡度为16,81和256的数据集进行验证,其三个测试集上的准确率分别为92.08%,91.54%和90.27%,可满足实际工作中处理不同不均衡度的要求。     

Quantification of fetal heart rate regularity using symbolic dynamics

Fetal heart rate complexity was examined on the basis of RR interval time series obtained in the second and third trimester of pregnancy. In each fetal RR interval time series, short term beat-to-beat heart rate changes were coded in 8 bit binary sequences. Redundancies of the 2(8) different binary patterns were reduced by two different procedures. The complexity of these sequences was quantified using the approximate entropy (ApEn), resulting in discrete ApEn values which were used for classifying the sequences into 17 pattern sets. Also, the sequences were grouped into 20 pattern classes with respect to identity after rotation or inversion of the binary value. There was a specific, nonuniform distribution of the sequences in the pattern sets and this differed from the distribution found in surrogate data. In the course of gestation, the number of sequences increased in seven pattern sets, decreased in four and remained unchanged in six. Sequences that occurred less often over time, both regular and irregular, were characterized by patterns reflecting frequent beat-to-beat reversals in heart rate. They were also predominant in the surrogate data, suggesting that these patterns are associated with stochastic heart beat trains. Sequences that occurred more frequently over time were relatively rare in the surrogate data. Some of these sequences had a high degree of regularity and corresponded to prolonged heart rate accelerations or decelerations which may be associated with directed fetal activity or movement or baroreflex activity. Application of the pattern classes revealed that those sequences with a high degree of irregularity correspond to heart rate patterns resulting from complex physiological activity such as fetal breathing movements. The results suggest that the development of the autonomic nervous system and the emergence of fetal behavioral states lead to increases in not only irregular but also regular heart rate patterns. Using symbolic dynamics to examine the cardiovascular system may thus lead to new insight with respect to fetal development.     

Xe and Kr adsorption on the Si(111) 7 × 7 surface

A study of adsorption of Xe and Kr on the Si(111) 7 × 7 surface is presented. Low energy electron diffraction indicates the substrate structure is not appreciably modified by the adsorption. The data consist primarily of isobars, i.e. the amount adsorbed as a function of temperature at fixed pressure. The stepwise adsorption of each of the first several adatoms per surface unit mesh is resolved. This indicates a sequence of distinguishable adsorption sites in the mesh each of which can be occupied by a single atom. There are appreciable differences in the measured binding energies between the various sites. Pairwise sums of 6–12 potentials have been used to estimate binding energies expected for sites presented by proposed structural models of the surface. The observed sequence of sites seems to exclude buckled models and those models which involve only arrays of identical entities. No presently published model is consistent with these data in detail. The triangular island models with some modifications might present sufficiently large binding energies and rich sequences of sites. Whatever the actual structure, it must be more complex than those which have usually been considered.     

Locating of Nucleic Acid Intercalators in Yeast Cells by Image Analysis Combined Fluorescence Microscopy

Intracellular distribution in the intact (not fixed) Saccharomyces cerevisiae cells of the nucleic acid intercalators (NAI) was studied using fluorescence microscopy combined with computer image analysis (ImageJ software, NIH, USA). Three NAI—the anthracycline anticancer drug doxorubicin (DR) along with the nucleic acid dyes ethidium (E) and 4′,6-diamidino-2-phenylindole (DAPI)—were used. Staining pattern and ImageJ quantitative analysis data provided evidence that all three NAI were located in the nuclei and in the mitochondria. DR and E, in contrast to DAPI, may be bound to not only DNA, but to the mitochondrial membranes as well. Experiments on the combined application of DR+DAPI and E+DAPI have shown potential competition of DAPI with DR and E for binding sites in the nuclear and mitochondrial DNA. With the approach presented herein, the yeast cells of S. cerevisiae can be used as a model for locating intracellular sites of the fluorescing nucleic acid intercalators. This model may be of help in designing new DNA-targeted drugs and in preliminary studies of their interaction with eukaryotic cells.     

Entropy and Fractal Dimension Study of the TDP-43 Protein Low Complexity Domain Sequence in ALS Disease Severity and SARS-CoV-2 Gene Sequences in Virulence Variability

The low complexity domain (LCD) sequence has been defined in terms of entropy using a 12 amino acid sliding window along a protein sequence in the study of disease-related genes. The amyotrophic lateral sclerosis (ALS)-related TDP-43 protein sequence with intra-LCD structural information based on cryo-EM data was published recently. An application of entropy and Higuchi fractal dimension calculations was described using the Znf521 and HAR1 sequences. A computational analysis of the intra-LCD sequence entropy and Higuchi fractal dimension values at the amino acid level and at the ATCG nucleotide level were conducted without the sliding window requirement. The computational results were consistent in predicting the intermediate entropy/fractal dimension value produced when two subsequences at two different entropy/fractal dimension values were combined. The computational method without the application of a sliding-window was extended to an analysis of the recently reported virulent genes—Orf6, Nsp6, and Orf7a—in SARS-CoV-2. The relationship between the virulence functionality and entropy values was found to have correlation coefficients between 0.84 and 0.99, using a 5% uncertainty on the cell viability data. The analysis found that the most virulent Orf6 gene sequence had the lowest nucleotide entropy and the highest protein fractal dimension, in line with extreme value theory. The Orf6 codon usage bias in relation to vaccine design was discussed.