Extraction of Acoustic Normal Mode Depth Functions Using Range-Difference Method with Vertical Linear Array Data

Data-derived normal mode extraction is an effective method for extracting normal mode depth functions in the absence of marine environmental data.However,when the corresponding singular vectors become nonunique when two or more singular values obtained from the cross-spectral density matrix diagonalization are nearly equal,this results in unsatisfactory extraction outcomes for the normal mode depth functions.To address this issue,we introduced in this paper a range-difference singular value decomposition method for the extraction of normal mode depth functions.We performed the mode extraction by conducting singular value decomposition on the individual frequency components of the signal's cross-spectral density matrix.This was achieved by using pressure and its range-difference matrices constructed from vertical line array data.The proposed method was validated using simulated data.In addition,modes were successfully extracted from ambient noise.

Normalized Ground State Solutions of Nonlinear Choquard Equations with Nonconstant Potential

In this paper,we mainly focus on the following Choquard equation-{△u-V(x)(I_(a*)|u|^(p))|u|^(p-2)u=λu,x∈R^(N),u∈H^(1)(R^(N))where N≥1,λ∈R will arise as a Lagrange multiplier,0<a<N and N+a/N<p<N+a+2/N Under appropriate hypotheses on V(x),we prove that the above Choquard equation has a normalized ground state solution by utilizing variational methods.

Design Method Based on Normalized Functions for a Toroidal Inductor Applied to Power-Quality Evaluation

The design method for a low-cost toroidal inductor is proposed as an alternative to power-quality evaluation. The method is based on well-known tools by the engineers in which is presented the relationships that exist between equivalent circuit and transfer function of a toroidal inductor. The proposed design method has been explained with normalized functions based on physical parameters of a toroidal inductor. This work presents the main arguments of the suggested methodology and as demonstration of the design method as function of normalized parameters, is developed a current-signal sensor which has been validated in the laboratory by the EN-50160-2-2 standard to evaluate the power quality in home use loads.

The Bivariate Normal Integral via Owen’s T Function as a Modified Euler’s Arctangent Series

The Owen’s T function is presented in four new ways, one of them as a series similar to the Euler’s arctangent series divided by 2π, which is its majorant series. All possibilities enable numerically stable and fast convergent computation of the bivariate normal integral with simple recursion. When tested computation on a random sample of one million parameter triplets with uniformly distributed components and using double precision arithmetic, the maximum absolute error was 3.45 × 10-16. In additional testing, focusing on cases with correlation coefficients close to one in absolute value, when the computation may be very sensitive to small rounding errors, the accuracy was retained. In rare potentially critical cases, a simple adjustment to the computation procedure was performed—one potentially critical computation was replaced with two equivalent non-critical ones. All new series are suitable for vector and high-precision computation, assuming they are supplemented with appropriate efficient and accurate computation of the arctangent and standard normal cumulative distribution functions. They are implemented by the R package Phi2rho, available on CRAN. Its functions allow vector arguments and are ready to work with the Rmpfr package, which enables the use of arbitrary precision instead of double precision numbers. A special test with up to 1024-bit precision computation is also presented.

VARIATIONAL ANALYSIS FOR THE MAXIMAL TIME FUNCTION IN NORMED SPACES

For a general normed vector space,a special optimal value function called a maximal time function is considered.This covers the farthest distance function as a special case,and has a close relationship with the smallest enclosing ball problem.Some properties of the maximal time function are proven,including the convexity,the lower semicontinuity,and the exact characterizations of its subdifferential formulas.

NORMALITY AND THE NUMBER OF ZEROS

In this paper,we study normal families of meromorphic functions.By using the idea in[11],we obtain some normality criteria for families of meromorphic functions that concern the number of zeros of the differential polynomial,which extends the related result of Li,and Chen et al..An example is given to show that the hypothesis on the zeros of a(z)is necessary.

The influences of large earthquake signals on the recovery of surface waves from ambient noise cross-correlation functions

Ambient noise tomography(ANT)has been widely used to image crust and upmost mantle structures.ANT assumes that sources of ambient noise are diffuse and evenly distributed in space and the energy of different modes is equipartitioned.At present,the sources of the primary and the secondary microseisms are well studied,but there are only a few on the studies of long-period ambient noise sources.In this study,we study the effects of large earthquake signals on the recovery of surface waves from seismic ambient noise data recorded by seismic stations from the US permanent networks and Global Seismographic Network(GSN).Our results show that large earthquake signals play an important role on the recovery of long-period surface waves from ambient noise cross-correlation functions.Our results are consistent with previous studies that suggest the contribution of earthquake signals to the recovery of surface waves from cross-correlations of ambient noise is dominant at periods larger than 20–40 s.

Stroke Patients’ Reintegration into Normal Living Post-Discharge from Inpatient Rehabilitation: An Integrative Review

Background: Stroke rehabilitation professionals have historically focused rehabilitation on physical functions and overlooked the concept of community reintegration after discharge from inpatient rehabilitation. The lack of focus on psychosocial functions post-stroke may lead to lower levels of satisfaction during community reintegration. Methods: This integrative review synthesized findings from research literature on stroke patients’ reintegration into the community after inpatient rehabilitation to address three research questions: a) What specific physical and psychosocial functions have been identified as predictors of successful reintegration into normal living after stroke?, b) How do physical and psychosocial functions promote successful reintegration into normal living after stroke?, and c) What factors have been identified that hinder stroke patients’ reintegration into normal living after stroke? Results: A systematic search of literature identified sixteen studies that provided significant context for the research questions. What physical and psychosocial functions of stroke patients included, for example, improved mobility, independence in daily activities, reduced disability, psychological well-being, self-efficacy, social support, and personal relationships. How physical and psychosocial functions promote reintegration included, for example, disability management, emotional well-being, self-care independence, sense of purpose, and employment influence. Factors that hinder stroke patients’ reintegration consisted of longer stride time, impaired balance/mobility, activities limitation, severe stroke, presence of comorbidity, depressive symptoms, speech and language challenges, inadequate self-efficacy, fear of falling, older age, low educational level, lack of social support, and social isolation. Conclusion: Successful community reintegration after stroke requires a shift of focus from rehabilitation interventions that target physical functions to include interventions that address psychosocial functions.

Mathematical Wave Functions and 3D Finite Element Modelling of the Electron and Positron

The wave/particle duality of particles in Physics is well known. Particles have properties that uniquely characterize them from one another, such as mass, charge and spin. Charged particles have associated Electric and Magnetic fields. Also, every moving particle has a De Broglie wavelength determined by its mass and velocity. This paper shows that all of these properties of a particle can be derived from a single wave function equation for that particle. Wave functions for the Electron and the Positron are presented and principles are provided that can be used to calculate the wave functions of all the fundamental particles in Physics. Fundamental particles such as electrons and positrons are considered to be point particles in the Standard Model of Physics and are not considered to have a structure. This paper demonstrates that they do indeed have structure and that this structure extends into the space around the particle’s center (in fact, they have infinite extent), but with rapidly diminishing energy density with the distance from that center. The particles are formed from Electromagnetic standing waves, which are stable solutions to the Schrödinger and Classical wave equations. This stable structure therefore accounts for both the wave and particle nature of these particles. In fact, all of their properties such as mass, spin and electric charge, can be accounted for from this structure. These particle properties appear to originate from a single point at the center of the wave function structure, in the same sort of way that the Shell theorem of gravity causes the gravity of a body to appear to all originate from a central point. This paper represents the first two fully characterized fundamental particles, with a complete description of their structure and properties, built up from the underlying Electromagnetic waves that comprise these and all fundamental particles.

*-normal Functions on the Plane

We introduce a new class of meromorphic functions on the plane, *_ normal functions say, their properties are very similarly as the normal functions in the unit disk and give three necessary conditions in judging it. Further we prove that each Julia exceptional function is *_normal and that there exists a *_normal function which has Julia aline.

结合图论Normalized Cut方法的彩色图像分割研究

归一化彩色图像分割中高斯核函数的参数选择直接影响到分割效果.为了寻找无参数的权值计算方法,提出将彩色图像中的像素点视为RGB空间的三维向量,使用向量的方向和幅值差异来衡量像素点的相似性,再使用Normalized Cut方法进行分割.实验结果表明,该方法能有效区分不同的颜色信息,计算复杂度不大,兼顾了算法的运算时间及分割效果,对不同的彩色图像均能得到准确的分割结果.

NORMAL FAMILIES OF MEROMORPHIC FUNCTIONS SHARING A HOLOMORPHIC FUNCTION AND THE CONVERSE OF THE BLOCH PRINCIPLE

In this paper, we investigate normal families of meromorphic functions, prove some theorems of normal families sharing a holomorphic function, and give a counterex- ample to the converse of the Bloch principle based on the theorems.

SOME NORMALITY CRITERIA OF MEROMORPHIC FUNCTIONS

Let F be a family of functions meromorphic in a domain D, let n ≥ 2 be a positive integer, and let a ≠ 0, b be two finite complex numbers. If, for each f ∈ F, all of whose zeros have multiplicity at least k ＋ 1, and f ＋ a（f^（k））^n≠b in D, then F is normal in D.

Increased international normalized ratio level in hepatocellular carcinoma patients with diabetes mellitus

AIM: To determine the association of diabetes mellitus (DM) and international normalized ratio (INR) level in hepatocellular carcinoma (HCC) patients. METHODS: Our present study included 375 HCC patients who were treated at the China-Japan Friendship Hospital, Ministry of Health (Beijing, China), in the period from January 2003 to April 2012, and with a hospital discharge diagnosis of HCC. The demographic, clinical, laboratory, metabolic and instrumental features were analyzed. χ2 test, Student's t test and Mann-Whitney U test were used to compare the differences between HCC patients with and without DM. Unconditional multivariable logistic regression analysis was used to determine the association of DM and INR level in HCC patients. A sub-group analysis was performed to assess the effect of liver cirrhosis or hepatitis B virus (HBV) infection on the results. The Pearson correlation test was used to determine the relationship between INR level and fasting glucose. In addition, association between diabetes duration, and diabetes treatment and INR level was determined considering the potentially different effects. RESULTS: Of the total, 63 (16.8%) patients were diabetic (diabetic group) and 312 (83.2%) patients were diagnosed without diabetes (non-diabetic group). Their mean age was 56.4 ± 11.0 years and 312 (83.2%) patients were male. Compared with patients without DM, the HCC patients with diabetes were older (59.5 ± 10.3 vs 55.8 ± 11.1, P=0.015), had a lower incidence of HBV infection (79.4% vs 89.1%, P=0.033), had increased levels of systolic blood pressure (SBP) (133 ± 17 vs 129 ± 16 mmHg, P=0.048) and INR (1.31 ± 0.44 vs 1.18 ± 0.21, P=0.001), had lower values of hemoglobin (124.4 ± 23.9 vs 134.2 ± 23.4, P=0.003) and had a platelet count (median/interquartile-range: 113/64-157 vs 139/89-192, P=0.020). There was no statistically significant difference in the percentages of males, overweight or obesity, drinking, smoking, cirrhosis and Child classification. After controlling for the confounding effects of age, systolic blood pressure, hemoglobin, platelet count and HBV infection by logistic analyses, INR was shown as an independent variable [odds ratio (OR)=3.650; 95%CI: 1.372-9.714, P=0.010]. Considering the effect of liver cirrhosis on results, a sub-group analysis was performed and the study population was restricted to those patients with cirrhosis. Univariate analysis showed that diabetic patients had a higher INR than non-diabetic patients (1.43 ± 0.51 vs 1.25 ± 0.23, P=0.041). After controlling for confounding effect of age, SBP, hemoglobin, platelet count and HBV infection by logistic analyses, INR level remained as the sole independent variable (OR=5.161; 95%CI: 1.618-16.455, P=0.006). No significant difference in the relationship between INR level and fasting glucose was shown by Pearson test (r=0.070, P=0.184). Among the 63 diabetic patients, 35 (55.6%) patients had been diagnosed with DM for more than 5 years, 23 (36.5%) received oral anti-diabetic regimens, 11 (17.5%) received insulin, and 30 (47.6%) reported relying on diet alone to control serum glucose levels. No significant differences were found for the association between DM duration/treatment and INR level, except for the age at diabetes diagnosis. CONCLUSION: The INR level was increased in HCC patients with DM and these patients should be monitored for the coagulation function in clinical practice.

NORMAL FAMILIES AND SHARED VALUES OF HOLOMORPHIC FUNCTIONS

Let F be a family of holomorphic functions in a domain D, k be a positive integer, a, b（≠0）, c（≠0） and d be finite complex numbers. If, for each f∈F, all zeros of f-d have multiplicity at least k, f^（k） = a whenever f=0, and f=c whenever f^（k） = b, then F is normal in D. This result extends the well-known normality criterion of Miranda and improves some results due to Chen-Fang, Pang and Xu. Some examples are provided to show that our result is sharp.

THE NORMALITY OF ALGEBROID MULTIFUNCTIONS AND THEIR COEFFICIENT FUNCTIONS

In this paper, we investigate the normality relationship between algebroid multifunctions and their coefficient functions. We prove that the normality of a k-valued entire algebroid multifunctions family is equivalent to their coefficient functions in some conditions. Furthermore, we obtain some new normality criteria for algebroid multifunctions families based on these results. We also provide some examples to expound that some restricted conditions of our main results are necessary.

NORMAL FAMILIES OF MEROMORPHIC FUNCTIONS WITH SHARED VALUES

We obtain some normality criteria of families of meromorphic functions sharing values related to Hayman conjecture, which improves some earlier related results.

Reconstruction of sub cross-correlation cancellation technique for unambiguous acquisition of BOC(kn, n) signals

In order to solve the problem of ambiguous acquisition of BOC signals caused by its property of multiple peaks,an unambiguous acquisition algorithm named reconstruction of sub cross-correlation cancellation technique(RSCCT)for BOC(kn,n)signals is proposed.In this paper,the principle of signal decomposition is combined with the traditional acquisition algorithm structure,and then based on the method of reconstructing the correlation function.The method firstly gets the sub-pseudorandom noise(PRN)code by decomposing the local PRN code,then uses BOC(kn,n)and the sub-PRN code cross-correlation to get the sub cross-correlation function.Finally,the correlation peak with a single peak is obtained by reconstructing the sub cross-correlation function so that the ambiguities of BOC acquisition are removed.The simulation shows that RSCCT can completely eliminate the side peaks of BOC(kn,n)group signals while maintaining the narrow correlation of BOC,and its computational complexity is equivalent to sub carrier phase cancellation(SCPC)and autocorrelation side-peak cancellation technique(ASPeCT),and it reduces the computational complexity relative to BPSK-like.For BOC(n,n),the acquisition sensitivity of RSCCT is 3.25 dB,0.81 dB and 0.25 dB higher than binary phase shift keying(BPSK)-like,SCPC and ASPeCT at the acquisition probability of 90%,respectively.The peak to average power ratio is 1.91,3.0 and 3.7 times higher than ASPeCT,SCPC and BPSK-like at SNR=–20 dB,respectively.For BOC(2n,n),the acquisition sensitivity of RSCCT is 5.5 dB,1.25 dB and 2.69 dB higher than BPSK-like,SCPC and ASPeCT at the acquisition probability of 90%,respectively.The peak to average power ratio is 1.02,1.68 and 2.12 times higher than ASPeCT,SCPC and BPSK-like at SNR=–20 dB,respectively.

Temporal-spatial cross-correlation analysis of non-stationary near-surface wind speed time series

Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.

Detrended cross-correlation analysis of electroencephalogram

In the paper we use detrended cross-correlation analysis （DCCA） to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject＇s brain function is healthy or not.