声音与耳病

目的统计分析毓璜顶医院听力检查结果,为了我们有一个美好的有声环境,噪音的大小对听力的损伤有着内在的联系。方法统计了2000年1月至2011年1月的300个因外界原因造成听力损害的图进行分析。结果在噪音大的地方对耳朵损害多于安静的环境,大多数患者感觉在噪音大的地方呆过或者工作过。结论听力损害是在99%以上。

Isolation of Rice EPSP Synthase cDNA and Its Sequence Analysis and Copy Number Determination

In order to isolate the total cDNA of rice (Oryza sativa L.) epsps gene, RT-PCR was carried out with template of rice first-strand cDNA and primers designed according to rice EPSP synthase genomic sequence obtained in previous study. A 1 585-bp cDNA fragment was amplified and cloned. The 1 585-bp cDNA contains an open reading frame (ORF) comprising of 1 533 nucleotides (nt) which encodes a 511 residue polypepetides, including 67 amino acids chloroplast transit peptide and 444 amino acids EPSP synthase mature peptide. A comparison between the EPSP synthase of different sources indicates that the mature peptide shows more than 51% identity except for the fungi EPSP synthase and the transit peptide shows considerably less sequence conservation. The copy number of rice epsps gene is estimated to be one copy per haploid rice genome using southern blot. RT-PCR indicated that rice epsps gene is expressed in rice leaves, endosperms and roots and has the highest expression level in leaves.

An amplitude suppression method based on the decibel criterion

To suppress the strong noise in seismic data with wide range of amplitudes, commonly used methods often yield unsatisfactory denoising results owing to inappropriate thresholds and require parametric testing as well as iterations to achieve the anticipated results. To overcome these problems, a data-driven strong amplitude suppression method based on the decibel criterion in the wavelet domain （ISANA） is proposed. The method determines the denoising threshold based on the decibel criterion and statistically analyzes the amplitude index rather than the abnormally high amplitudes. The method distinguishes the frequency band distributions of the valid signals in the time-frequency domain based on the wavelet transformation and then calculates thresholds in selected time windows, eventually achieving frequency-divided noise attenuation for better denoising. Simulations based on theoretical and real-world data verify the adaptability and low dependence of the method on the size of the time window. The method suppresses noise without energy loss in the signals.

Agricultural Product Quality Mining Based on Bayesian Classification

Combined with the characteristics of crop growth and environmental data and the basic principle of Bayesian algorithm,the crop product quality is analyzed and forecasted in this study.Test with a randomly selected sample group ensures high forecasting accuracy,which shows that the algorithm is effective.

为今天的光纤网选择合适的OTDR设备

工程师在选择试仪器时必须评估其特性和成本

混响室空间相关特性研究与测量

该文主要研究混响室内场分布的空间特性统计模型,对自制的混响室内场分布的空间相关特性进行测量,与理论模型空间相关函数SCF进行对比分析。研究结果是在一定频率范围内观察得到的,即从不理想,欠模状态到理想,多模或过模状态的操作。从这些实验结果中可以得到混响室操作的低频限制标准,研究了特征参数M值,即3dB带宽下的模式数,它是混响室的低频限制标准的重要特征量。

Minimax Estimation of the Function of Parameters in Normal Distribution

The estimation of the functionθ=exp{αμ+bσ2} of parameters (μ,σ2) in normal distribution N(μ,σ2) is discussed. And when the prior distributions ofμandσ2 are independent, under the loss function L(θ,δ)=(θ-1×δ-1)2, the Bayesian estimation and the existence and computing method on minimax estimation are deeply discussed.

Improved seismoacoustic analysis model and its application to source parameter inversion of near-surface small-yield chemical explosions

The seismoacoustic analysis method has broad potential applications to source parameter estimation for near-surface explosion events such as industrial explosions and terrorist attacks.In this study,current models were improved by modifying the acoustic model and adopting the Bayesian Markov-chain-Monte-Carlo inversion method.The source parameters of near-surface small-yield chemical explosions were analyzed via the improved seismoacoustic analysis model and by the estimation accuracy of seismoacoustic joint inversion.Estimation and analysis results showed that the improved seismoacoustic analysis model considered ground shock coupling and the impact of explosion products ejecting from the surface so that the improved acoustic impulse relation was more consistent with the measured data than the Ford impulse relation.It is suitable for deep-burial,shallow-burial,and near-surface aerial explosions.Furthermore,trade-off relationships were declined through the application of the improved model to source parameter inversion for near-surface small-yield chemical explosions,and source parameter estimation accuracy was improved.

Parallel naive Bayes algorithm for large-scale Chinese text classification based on spark

The sharp increase of the amount of Internet Chinese text data has significantly prolonged the processing time of classification on these data.In order to solve this problem,this paper proposes and implements a parallel naive Bayes algorithm(PNBA)for Chinese text classification based on Spark,a parallel memory computing platform for big data.This algorithm has implemented parallel operation throughout the entire training and prediction process of naive Bayes classifier mainly by adopting the programming model of resilient distributed datasets(RDD).For comparison,a PNBA based on Hadoop is also implemented.The test results show that in the same computing environment and for the same text sets,the Spark PNBA is obviously superior to the Hadoop PNBA in terms of key indicators such as speedup ratio and scalability.Therefore,Spark-based parallel algorithms can better meet the requirement of large-scale Chinese text data mining.

A model for automatic identification of human pulse signals

This paper presents a quantitative method for automatic identification of human pulse signals. The idea is to start with the extraction of characteristic parameters and then to construct the recognition model based on Bayesian networks. To identify depth, frequency and rhythm, several parameters are proposed. To distinguish the strength and shape, which cannot be represented by one or several parameters and are hard to recognize, the main time-domain feature parameters are computed based on the feature points of the pulse signal. Then the extracted parameters are taken as the input and five models for automatic pulse signal identification are constructed based on Bayesian networks. Experimental results demonstrate that the method is feasible and effective in recognizing depth, frequency, rhythm, strength and shape of pulse signals, which can be expected to facilitate the modernization of pulse diagnosis.

Prediction of early-stage hepatocellular carcinoma using Onco Scan chromosomal copy number aberration data

AIM To identify chromosomal copy number aberrations(CNAs) in early-stage hepatocellular carcinoma(HCC) and analyze whether they are correlated with patient prognosis.METHODS One hundred and twenty patients with early-stage HCC were enrolled in our study, with the collection of formalin fixed, paraffin-embedded(FFPE) specimens and clinicopathological data. Tumor areas were marked by certified pathologists on a hematoxylin and eosinstained slide, and cancer and adjacent non-cancerous tissues underwent extraction of DNA, which was analyzed with the Affymetrix Onco Scan platform to assess CNAs and loss of heterozygosity(LOH). Ten individuals with nonmalignant disease were used as the control group. Another cohort consisting of 40 patients with stage Ⅰ/Ⅱ HCC were enrolled to analyze gene expression and to correlate findings with the Onco Scan data.RESULTS Copy number amplifications occurred at chromosomes 1 q21.1-q44 and 8 q12.3-24.3 and deletions were found at 4 q13.1-q35.2, 8 p 23.2-21.1, 16 q23.3-24.3, and 17 p13.3-12, while LOH commonly occurred at 1 p32.3, 3 p21.31, 8 p23.2-21.1, 16 q22.1-24.3, and 17 p 13.3-11 in early-stage HCC. Using Cox regression analysis, we also found that a higher percentage of genome change(≥ 60%) was an independent factor for worse prognosis in early-stage HCC(P = 0.031). Among the 875 genes in the Onco Scan Gene Chip, six were independent predictors of worse disease-free survival, of which three were amplified(MYC, ELAC2, and SYK) and three were deleted(GAK, MECOM, and WRN). Further, patients with HCC who exhibited ≥ 3 CNAs involving these six genes have worse outcomes compared to those who had < 3 CNAs(P < 0.001). Similarly, Asian patients with stage I HCC from The Cancer Genome Atlas harboring CNAs with these genes were also predicted to have poorer outcomes.CONCLUSION Patients with early-stage HCC and increased genome change or CNAs involving MYC, ELAC2, SYK, GAK, MECOM, or WRN are at risk for poorer outcome after resection.

Discrete AKNS-D Hierarchy

In this paper, we consider the discrete AKNS-D hierarchy, make the construction of the hierarchy, prove the bilinear identity and give the construction of the τ-functions of this hierarchy.

The Estimation of the Number of Zeros of the Abelian Integrals for a Class of Hamiltonian Systems

In this paper, we discuss the estimation of the number of zeros of the Abelian integral for the quadratic system which has a periodic region with a parabola and a straight line as its boundary when we perturb the system inside the class of all polynomial systems of degree n. The main result is that the upper bound for the number of zeros of the Abelian integral associated to this system is 3n-1.

Application of Bayesian approach to hydrological frequency analysis

An existing Bayesian flood frequency analysis method is applied to quantile estimation for Pearson type three (P-III) probability distribution. The method couples prior and sample information under the framework of Bayesian formula, and the Markov Chain Monte Carlo (MCMC) sampling approach is used to estimate posterior distributions of parameters. Different from the original sampling algorithm (i.e. the important sampling) used in the existing approach, we use the adaptive metropolis (AM) sampling technique to generate a large number of parameter sets from Bayesian parameter posterior distributions in this paper. Consequently, the sampling distributions for quantiles or the hydrological design values are constructed. The sampling distributions of quantiles are estimated as the Bayesian method can provide not only various kinds of point estimators for quantiles, e.g. the expectation estimator, but also quantitative evaluation on uncertainties of these point estimators. Therefore, the Bayesian method brings more useful information to hydrological frequency analysis. As an example, the flood extreme sample series at a gauge are used to demonstrate the procedure of application.

SELF-CANCELLATION OF MODULES HAVING THE FINITE EXCHANGE PROPERTY

Self-cancellation of modules having the finite exchange property is introduced. If a right R-module M has the finite exchange property, it is shown that M has selfcancellation if and only if EndR(M) is a strongly separative ring. Using this result,some new characterizations of strong separativity are obtained.

Shannon-type sampling for multivariate non-bandlimited signals

In this paper, starting from a function analytic in a neighborhood of the unit disk and based on Bessel functions, we construct a family of generalized multivariate sinc functions, which are radial and named radial Bessel-sinc (RBS) functions being time-frequency atoms with nonlinear phase. We obtain a recursive formula for the RBS functions in R d with d being odd. Based on the RBS function, a corresponding sampling theorem for a class of non-bandlimited signals is established. We investigate a class of radial functions and prove that each of these functions can be extended to become a monogenic function between two parallel planes, where the monogencity is taken to be of the Clifford analysis sense.

Fast integral equation solver for Maxwell's equations in layered media with FMM for Bessel functions

The paper presents a new fast integral equation solver for Maxwell＇s equations in 3-D layered media. First, the spectral domain dyadic Green＇s function is derived, and the 0-th and the 1-st order Hankel transforms or Sommerfeld-type integrals are used to recover all components of the dyadic Green＇s function in real space. The Hankel transforms are performed with the adaptive generalized Gaussian quadrature points and window functions to minimize the computational cost. Subsequently, a fast integral equation solver with O（N2zNxNy log（NzNy）） in layered media is developed by rewriting the layered media integral operator in terms of Hankel transforms and using the new fast multipole method for the n-th order Bessel function in 2-D. Computational cost and parallel efficiency of the new algorithm are presented.

Dynamic effective elastic modulus of polymer matrix composites with dense piezoelectric nano-fibers considering surface/interface effect

Based on effective field method,the dynamic effective elastic modulus of polymer matrix composites embedded with dense piezoelectric nano-fibers is obtained,and the interacting effect of piezoelectric surfaces/interfaces around the nano-fibers is considered.The multiple scattering effects of harmonic anti-plane shear waves between the piezoelectric nano-fibers with surface/interface are averaged by effective field method.To analyze the interacting results among the random nano-fibers,the problem of two typical piezoelectric nano-fibers is introduced by employing the addition theorem of Bessel functions.Through numerical calculations,the influence of the distance between the randomly distributed piezoelectric nano-fibers under different surface/interface parameters is analyzed.The effect of piezoelectric property of surface/interface on the effective shear modulus under different volume fractions is also examined.Comparison with the simplified cases is given to validate this dynamic electro-elastic model.

The art and science of species delimitation

DNA-based approaches to systematics have changed dramatically during the last two decades with the rise of DNA barcoding methods and newer multi-locus methods for species delimitation. During the last half-decade, partly driven by the new sequencing technologies, the focus has shifted to multi-locus sequence data and the identification of species within the frame-work of the multi-species coalescent （MSC）. In this paper, I discuss model-based Bayesian methods for species delimitation that have been developed in recent years using the MSC. Several approximate methods for species delimitation （and their limitations） are also discussed. Explicit species delimitation models have the advantage of clarifying more precisely what is being delimited and what assumptions we are making in doing so. Moreover, the methods can be very powerful when applied to large multi-locus datasets and thus take full advantage of data generated using today＇s technologies [Current Zoology 61 （5）： 846-853,2015].

Cyprinid phylogeny based on Bayesian and maximum likelihood analyses of partitioned data:implications for Cyprinidae systematics

Cyprinidae is the biggest family of freshwater fish, but the phylogenetic relationships among its higher-level taxa are not yet fully resolved. In this study, we used the nuclear recombination activating gene 2 and the mitochondrial 16S ribosomal RNA and cytochrome b genes to reconstruct cyprinid phylogeny. Our aims were to （i） demonstrate the effects of partitioned phylo- genetic analyses on phylogeny reconstruction of cyprinid fishes; （ii） provide new insights into the phylogeny of cyprinids. Our study indicated that unpartitioned strategy was optimal for our analyses; partitioned analyses did not provide better-resolved or -supported estimates of cyprinid phylogeny. Bayesian analyses support the following relationships among the major mono- phyletic groups within Cyprinidae： （Cyprininae, Labeoninae）, （（Acheilognathinae, （（Leuciscinae, Tincinae）, Gobioninae））, Xenocyprirlinae）. The placement of Danioninae was poorly resolved. Estimates of divergence dates within the family showed that radiation of the major cyprinid groups occurred during the Late Oligocene through the Late Miocene. Our phylogenetic analyses improved our understanding of the evolutionary history of this important fish family.