Xiaoling Wang

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David Seamon

Kansas State University

Armando Marques-Guedes

UNL - New University of Lisbon

Liliana Lo Presti

Università degli Studi di Palermo

Emma Black

Newcastle University

Alhayat Ali Mekonnen

LAAS-CNRS

Jorge Sequera

Universidad Nacional de Educación a Distancia

Marc Goergen

IE BUSINESS SCHOOL

Eckart Otto

Ludwig-Maximilians-Universität München

Abdelkarim Guendouz

King Faisal University

Vusat Azizov

Azerbaijan State University of Economics (UNEC)

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Papers by Xiaoling Wang

Ethnic Differences and Heritability of Heart Rate Variability in African and European American Youth

American Journal of Cardiology, 2005

This study investigated whether heart rate variability (HRV) in young African-Americans differed ... more This study investigated whether heart rate variability (HRV) in young African-Americans differed from that in young European Americans. It further examined the genetic and/or environmental sources of HRV variance and to what extent they depend on ethnicity or gender in young twins. Subjects were available from 1 data set including 166 subjects (mean age 16 +/- 2 years; 63 African-Americans) and another including 219 twins (11 singletons [4 African-Americans] and 104 pairs [42 African-Americans]; mean age 15 +/- 2 years). HRV was measured over 256 RR intervals in a supine position. Two time-domain variables, the SD of normal RR intervals (SDNN) and the root-mean-square of successive differences (RMSSD) of normal RR intervals, and 3 frequency-domain variables, high-frequency (HF) power, low-frequency (LF) power, and the LF power/HF power ratio, were used. African-Americans had higher RMSSDs (p &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;0.01) and HF power (p = 0.047) and lower LF power/HF power ratios (p &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;0.01) than European Americans. These differences remained significant after adjusting for covariates. All HRV parameters were heritable; estimated heritability ranged from 32% to 71%. Model fitting showed no ethnic or gender differences for any measure. SDNN, RMSSD, and HF power were strongly correlated (r values &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;0.8). One factor explaining &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;90% of the variance for all 3 measures was identified. The heritability of this combined HRV score was 70%. In conclusion, this study suggests that ethnic differences in HRV already exist in youth, with African-Americans having greater HRV than European Americans. High heritability estimates for HRV measures were observed, and no differences in HRV heritability estimates were noted for ethnicity or gender.

Obesity reveals an association between blood pressure and the G-protein ??3-subunit gene: a study of female dizygotic twins

Pharmacogenetics, 2004

The 825C&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;... more The 825C&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;T polymorphism of the G-protein beta3-subunit gene (GNB3) has been associated with hypertension, although results are not entirely consistent. In a sample of 282 female Caucasian dizygotic twins aged 21-80 years, we aimed to investigate the associations between blood pressure and five single nucleotide polymorphisms (SNPs) including the 825C&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;T and haplotypes of the GNB3 gene. The polymorphisms (-350A&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;G, 657A&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;T, 814G&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;A, 825C&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;T and 1429C&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;T) were genotyped by polymerase chain reaction-restriction enzyme assays. Regular association tests did not show a significant effect on blood pressure for any of the five SNPs. However, strongly significant interactions between the -350A&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;G, 825C&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;T and 1429C&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;T loci and adiposity (both body mass index and waist circumference) were observed for systolic blood pressure (Ps &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt; 0.01) as well as diastolic blood pressure (Ps &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt; 0.05), suggesting increases in adiposity amplify the effects of the SNPs on blood pressure. Haplotype analyses confirmed the effects of the GNB3 gene-obesity interaction on hypertension risk. Additionally, sib-transmission disequilibrium tests (sib-TDTs) showed significant associations with blood pressure for the 825C&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;T and 1429C&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;T loci. In summary, the presence of obesity reveals an…

Ethnic and Gender Differences in Ambulatory Blood Pressure Trajectories Results From a 15Year Longitudinal Study in Youth and Young Adults

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Multisensor Data Fusion in Distributed Sensor Networks Using Mobile Agents

Information Fusion, 2001

We describe the deployment of mobile agent in Distributed Sensor Networks (DSNs) to form an impro... more We describe the deployment of mobile agent in Distributed Sensor Networks (DSNs) to form an improved infrastructure for multisensor data fusion. Compared with the traditional client/server paradigm, mobile agent adopts a new computing model: data stay at the local site, while the execution code is moved to the data sites. Mobile-agent-based DSN (MADSN) saves the network bandwidth and provides an effective way to overcome network latency. It is used to integrate preprocessed data located at local sensor nodes. Progressive accuracy can be achieve during the agent migration. We take target classification as an example to show how MADSN supports high performance distributed integration.

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Band Selection Using Independent Component Analysis for Hyperspectral Image Processing

Although hyperspectral images provide abundant information about objects, their high dimensionali... more Although hyperspectral images provide abundant information about objects, their high dimensionality also substantially increases computational burden. Dimensionality reduction offers one approach to Hyperspectral Image (HSI) analysis. Currently, there are two methods to reduce the dimension, band selection and feature extraction. In this paper, we present a band selection method based on Independent Component Analysis (ICA). This method, instead of transforming the original hyperspectral images, evaluates the weight matrix to observe how each band contributes to the ICA unmixing procedure. It compares the average absolute weight coefficients of individual spectral bands and selects bands that contain more information. As a significant benefit, the ICA-based band selection retains most physical features of the spectral profiles given only the observations of hyperspectral images. We compare this method with ICA transformation and Principal Component Analysis (PCA) transformation on classification accuracy. The experimental results show that ICA-based band selection is more effective in dimensionality reduction for HSI analysis.

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Mobile-agent-based collaborative signal and information processing in sensor networks

Proceedings of The IEEE, 2003

In this paper, we develop an energy-efficient, fault-tolerant approach for collaborative signal a... more In this paper, we develop an energy-efficient, fault-tolerant approach for collaborative signal and information processing (CSIP) among multiple sensor nodes using a mobile-agent-based computing model. In this model, instead of each sensor node sending local information to a processing center for integration, as is typical in client/server-based computing, the integration code is moved to the sensor nodes through mobile agents. The energy efficiency objective and the fault tolerance objective always conflict with each other and present unique challenge to the design of CSIP algorithms. In general, energy-efficient approaches try to limit the redundancy in the algorithm so that minimum amount of energy is required for fulfilling a certain task. On the other hand, redundancy is needed for providing fault tolerance since sensors might be faulty, malfunctioning, or even malicious. A balance has to be struck between these two objectives. We discuss the potential of mobile-agent-based collaborative processing in providing progressive accuracy while maintaining certain degree of fault tolerance. We evaluate its performance compared to the client/server-based collaboration from perspectives of energy consumption and execution time through both simulation and analytical study. Finally, we take collaborative target classification as an application example to show the effectiveness of the proposed approach.

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Face Recognition Using Optimal NonOrthogonal Wavelet Basis Evaluated by Information Complexity

Detecting and recognizing face images automatically is a difficult task due to the variability of... more

Comparative Study of VLSI Solutions to Independent Component Analysis

IEEE Transactions on Industrial Electronics, 2007

... An expandable modularized processor design for this ICA-based speech recognition system was e... more

Collaborative multi-modality target classification in distributed sensor networks

The University of Tennessee Knoxville, TN 37996, USA {xwang 1 ,hqi} @utk.edu ... Abstract - A new... more

High Performance Sensor Integration in Distributed Sensor Networks Using Mobile Agents

International Journal of High Performance Computing Applications, 2002

... 2002 16: 325 International Journal of High Performance Computing Applications Hairong Qi,Xiao... more

McGraw-Hill Education Pearson Education

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Ethnic Differences and Heritability of Heart Rate Variability in African and European American Youth

American Journal of Cardiology, 2005

Obesity reveals an association between blood pressure and the G-protein ??3-subunit gene: a study of female dizygotic twins

Pharmacogenetics, 2004

Ethnic and Gender Differences in Ambulatory Blood Pressure Trajectories Results From a 15Year Longitudinal Study in Youth and Young Adults

Download

Multisensor Data Fusion in Distributed Sensor Networks Using Mobile Agents

Information Fusion, 2001

Download

Band Selection Using Independent Component Analysis for Hyperspectral Image Processing

Download

Mobile-agent-based collaborative signal and information processing in sensor networks

Proceedings of The IEEE, 2003

Download

Face Recognition Using Optimal NonOrthogonal Wavelet Basis Evaluated by Information Complexity

Detecting and recognizing face images automatically is a difficult task due to the variability of... more

Comparative Study of VLSI Solutions to Independent Component Analysis

IEEE Transactions on Industrial Electronics, 2007

... An expandable modularized processor design for this ICA-based speech recognition system was e... more

Collaborative multi-modality target classification in distributed sensor networks

The University of Tennessee Knoxville, TN 37996, USA {xwang 1 ,hqi} @utk.edu ... Abstract - A new... more

High Performance Sensor Integration in Distributed Sensor Networks Using Mobile Agents

International Journal of High Performance Computing Applications, 2002

... 2002 16: 325 International Journal of High Performance Computing Applications Hairong Qi,Xiao... more

McGraw-Hill Education Pearson Education

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