The asymptotic relation between the first crossing point and the last exit time of Gaussian order statistics sequences

In this paper,we study the asymptotic relation between the first crossing point and the last exit time for Gaussian order statistics which are generated by stationary weakly and strongly dependent Gaussian sequences.It is shown that the first crossing point and the last exit time are asymptotically independent and dependent for weakly and strongly dependent cases,respectively.The asymptotic relations between the first crossing point and the last exit time for stationary weakly and strongly dependent Gaussian sequences are also obtained.

Probability Inequalities for Extended Negatively Dep endent Random Variables and Their Applications

Some probability inequalities are established for extended negatively dependent(END) random variables. The inequalities extend some corresponding ones for negatively associated random variables and negatively orthant dependent random variables. By using these probability inequalities, we further study the complete convergence for END random variables. We also obtain the convergence rate O(n-1/2ln1/2n) for the strong law of large numbers, which generalizes and improves the corresponding ones for some known results.

Comparisons of Short-Prefix Based Channel Estimation in Single-Carrier Communication Systems

In this paper, we compare the performance between channel estimation based on compressed sensing (CS) and time-domain least square (LS) for single-carrier (SC) communication system. Unlike the conventional channel estimation techniques such as frequency domain LS which is used in the condition that the length of pilot sequence is equal to data sequence, the estimation scheme based on CS requires smaller length of pilot sequence. In this paper, the corresponding system structure is presented. Zadoff-Chu sequence is used to generate the pilot sequence, which is shown to perform better in forming measurement matrix of CS than pseudo random sequence. Simulation results demonstrate that channel estimation based on CS achieves a better bit error rate (BER) performance than time domain LS with a smaller pilot sequence and thus raising data rate of the SC communication system.

Pseudo Almost Periodic Solutions of Nonlinear Hyperbolic Equations with Piecewise Constant Argument

In this paper, we investigate the pseudo almost periodicity of the unique bounded solution for a nonlinear hyperbolic equation with piecewise constant argument. The equation under consideration is a mathematical model for the dynamics of gas absorption,

Cubic Metric Reduction for Repetitive CAZAC Sequences in Frequency Domain

To meet the requirements of Occupied Channel Bandwidth(OCB)of unlicensed spectrum,in NR-based Access to Unlicensed Spectrum(NR-U)of 5G New Radio(NR)system,the channels of PRACH and PUCCH have to employ some frequency domain sequence repetition schemes.These repeti-tion schemes cause serious Cubic Metric(CM)prob-lems for these channels,although these two types of channels are composed of Constant Amplitude Zero Auto-correlation(CAZAC)sequences.Considering the properties of CAZAC sequences,which are used for PRACH and PUCCH(refer to PUCCH format 0 and format 1)in 5G NR system,in this paper,we pro-pose some new schemes of CM reduction for these two channels taking into account the design princi-ples to ensure the sequence performance of the auto-correlation and cross-correlation.Then the recom-mended CM reduction schemes are evaluated and the optimized parameters are further provided considering both CM performance and the complexity.

ADAPTIVE BLOCK QMRIOM（q）METHOD FOR SOLVING UNSYMMETRIC LINEAR SYSTEMS WITH MULTI

Many applications require the solution of large un-symmetric linear systems with multiple right-hand sides.Instead of applying an iterative method to each of these systems individually,it is often more efficient to use a block version of the method that generates iterates for all the systems simultaneously.This paper proposes a new adaptive block QMR version based on the incomplete or-thogomalization method(IOM(q))for solving large multi-ple nusymmetric linear systems.How to incorporate de-flation to drop comverged linear systems,and how to delete linearly and almost liearly dependent vectors in the underlying block Krylov sequences are discussed.Nu-merical experiments show that the new adaptive block method has better practical performance and less compu-tational cost and CPU time than block GMRES and other proposed methods for the solution of systems with multi- ple right-hand sides.

Paleogene Tectonic Evolution Controls on Sequence Stratigraphic Patterns in the Central Part of Deepwater Area of Qiongdongnan Basin, Northern South China Sea

In active rift basins, tectonism is extremely important for sequence stratigraphic patterns, affecting both the sequence architecture and internal makeup. Sequence stratigraphic framework of a Paleogene rift succession in Qiongdongnan Basin, northern South China Sea, was built using seismic profiles, complemented by well logs and cores. One first-order and three second-order sequences were identified on the basis of basin-scale unconformities, and seven third-order sequences are defined by unconformities along the basin margins and correlative conformities within the central basin. Through unconformity analysis and backstripping procedure, the Paleogene synrift tectonic evolution of deep- water area of Qiongdongnan Basin was proved to be episodic, which can be divided into rifting stage-I, rifting stage-II and rifting stage-III. Episodic rifting resulted in the formation of various types of struc- tural slope break belts, which controlled different architectures and internal makeup of sequences. This study enhances the understanding of the control of tectonic evolution on sequence stratigraphic pat- terns and establishes relevant patterns in a typical rift basin, and further proposes the favorable sand- stone reservoirs developing in different sequence stratigraphic patterns, which will be pretty helpful for subtle pool exploration in deepwater area of petroliferous basins.

Sequence variations of the S7 ribosomal protein gene in primitive cyprinid fishes: Implication on phylogenetic analysis

Cyprinidae is the largest fish family in the world and contains about 210 genera and 2010 species. Appropriate DNA markers must be selected for the phylogenetic analyses of Cyprinidae. In present study, the 1st intron of the S7 ribosomal protein (r-protein) gene is first used to examine the relationships among cyprinid fishes. The length of the 1st intron obtained by PCR amplification ranges from 655 to 859 bp in the 16 cyprinid species investigated, and is 602 bp in Myxocyprinus asiaticus. Out of the alignment of 925 nucleotide sites obtained, the parsimony informative sites are 499 and occupy 54% of the total sites. The results indicate that the 1st intron sequences of the S7 r-protein gene in cyprinids are rich in informative sites and vary remarkably in sequence divergence from 2.3% between close species to 66.6% between distant species. The bootstrap values of the interior nodes in the NJ (neighbor-joining) and MP (most-parsimony) trees based on the present S7 r-protein gene data are higher than

Differential expression of immune-related genes between healthy volunteers and type 2 diabetic patients with spleen-deficiency pattern

OBJECTIVE: To investigate the clinical differentiation of spleen-deficiency pattern(SDP), a group of symptoms and signs defined in terms of Traditional Chinese Medicine for its clinical practice.METHODS: Peripheral venous blood(> 3 m L) was collected from each of six type 2 diabetes mellitus(T2DM)-SDP patients and six healthy volunteers. After the isolation of peripheral white blood cells(PWBCs), total RNA was extracted, and quality control was performed on all RNA samples. Microarray experiments were conducted using the Agilent human whole genome gene chip, and genes demonstrating differential expression were screened. Bioinformatics analysis was conducted on these genes using several online databases.RESULTS: We screened a total of 175 differentially expressed genes(DEGs), of which 111(63%) were down-regulated and 64(37%) were up-regulated in T2DM-SDP patients compared with healthy controls. Among the 175 genes, 158 had biological function annotations: 46(29%) were directly related to an individual's immune regulation or response, 25(16%) were associated with substance and energy metabolism of PWBCs which could also indirectly influence immunity, and the remaining87(55%) were involved in a variety of PWBC biological processes that might eventually influence the immune function. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed that the DEGs were predominantly enriched in seven immune-related pathways. Hierarchical cluster analysis identified gene expression patterns that were distinguishable between the two study groups.CONCLUSION: Our results suggest that T2DM-SDP patients experience significant hypoimmunity and/or immune dysfunctions, and possess a specific gene expression profile. These findings offer new insights into SDP and the clinical pattern differentiation of T2DM-SDP.

Pedestrian detection algorithm based on video sequences and laser point cloud

Pedestrian detection is a critical problem in the field of computer vision. Although most existing algorithms are able to detect pedestrians well in controlled environ- ments, it is often difficult to achieve accurate pedestrian de- tection from video sequences alone, especially in pedestrian- intensive scenes wherein pedestrians may cause mutual oc- clusion and thus incomplete detection. To surmount these dif- ficulties, this paper presents pedestrian detection algorithm based on video sequences and laser point cloud. First, laser point cloud is interpreted and classified to separate pedes- trian data and vehicle data. Then a fusion of video image data and laser point cloud data is achieved by calibration. The re- gion of interest after fusion is determined using feature in- formation contained in video image and three-dimensional information of laser point cloud to remove false detection of pedestrian and thus to achieve pedestrian detection in inten- sive scenes. Experimental verification and analysis in video sequences demonstrate that fusion of two data improves the performance of pedestrian detection and has better detection results.

On a general class of quadratic hopping sequences

Based upon quadratic polynomials over the finite field, a new class of frequency hopping sequences with large family size suitable for applications in time/frequency hopping CDMA systems, multi-user radar and sonar systems is proposed and investigated. It is shown that the new time/frequency hopping sequences have at most one hit in their autocorrelation functions and at most two hits in their crosscorrelation functions except for a special case, and their family size is much larger than the conventional quadratic hopping sequences. The percentage of full collisions for the new quadratic hopping sequences is discussed. In addition, the average number of hits for the new quadratic hopping sequences, quadratic congruence sequences, extended quadratic congruence sequences and the general linear hopping sequences are also derived.

Convergence in Law to Operator Fractional Brownian Motion of Riemann-Liouville Type

In this paper, we extend the well-studied fractional Brownian motion of Riemann-Liouville type to the multivariate case, and the corresponding processes are called operator fractional Brownian motions of Riemann-Liouville type. We also provide two results on approximation to operator fractional Brownian motions of Riemann-Liouville type. The first approximation is based on a Poisson process, and the second one is based on a sequence of I.I.D. random variables.

On essential topics of BYY harmony learning： Current status, challenging issues, and gene analysis applications

As a supplementary of [Xu L. Front. Electr. Electron. Eng. China, 2010, 5（3）： 281-328], this paper outlines current status of efforts made on Bayesian Ying- Yang （BYY） harmony learning, plus gene analysis appli- cations. At the beginning, a bird＇s-eye view is provided via Gaussian mixture in comparison with typical learn- ing algorithms and model selection criteria. Particularly, semi-supervised learning is covered simply via choosing a scalar parameter. Then, essential topics and demand- ing issues about BYY system design and BYY harmony learning are systematically outlined, with a modern per- spective on Yin-Yang viewpoint discussed, another Yang factorization addressed, and coordinations across and within Ying-Yang summarized. The BYY system acts as a unified framework to accommodate unsupervised, su- pervised, and semi-supervised learning all in one formu- lation, while the best harmony learning provides novelty and strength to automatic model selection. Also, mathe- matical formulation of harmony functional has been ad- dressed as a unified scheme for measuring the proximity to be considered in a BYY system, and used as the best choice among others. Moreover, efforts are made on a number of learning tasks, including a mode-switching factor analysis proposed as a semi-blind learning frame- work for several types of independent factor analysis, a hidden Markov model （HMM） gated temporal fac- tor analysis suggested for modeling piecewise stationary temporal dependence, and a two-level hierarchical Gaus- sian mixture extended to cover semi-supervised learning, as well as a manifold learning modified to facilitate au- tomatic model selection. Finally, studies are applied to the problems of gene analysis, such as genome-wide asso- ciation, exome sequencing analysis, and gene transcrip- tional regulation.