Publikationen

cite arxiv:1202.3146 Comment: 15 pages, 4 figures: Cai, X.; Ying, Y. A.; Staley, N. E.; Xin, Y.; Fobes, D.; Liu, T.; Mao, Z. Q. & Liu, Y. (2012): Quantum oscillations in nanofabricated rings of spin-triplet

superconductor Sr2RuO4.
[Volltext] [Kurzfassung] [BibTeX] [Endnote]

MacKenzie, R.; Hawkey, K.; Booth, K. S.; Liu, Z.; Perswain, P. & Dhillon, S. S. (2012): LACOME: a multi-user collaboration system for shared large displays.. In: CSCW, [Volltext]

2011

Liu, J.; Ren, F. Y.; Miao, L. M. & Lin, C. (2011): A-ADHOC: An Adaptive Real-time Distributed MAC Protocol for Vehicular Ad Hoc Networks. In: Mobile Networks & Applications, Ausgabe/Number: 5, Vol. 16, Verlag/Publisher: Springer. Erscheinungsjahr/Year: 2011. Seiten/Pages: 576-585.

Zhang, C.; Bailey, D. K.; Awad, T.; Liu, G.; Xing, G.; Cao, M.; Valmeekam, V.; Retief, J.; Matsuzaki, H.; Taub, M.; Seielstad, M. & Kennedy, G. C. (2006): A whole genome long-range haplotype (WGLRH) test for detecting imprints of positive selection in human populations. In: Bioinformatics, Ausgabe/Number: 17, Vol. 22, Erscheinungsjahr/Year: 2006. Seiten/Pages: 2122-2128. [Volltext]

Motivation: The identification of signatures of positive selection can provide important insights into recent evolutionary history in human populations. Current methods mostly rely on allele frequency determination or focus on one or a small number of candidate chromosomal regions per study. With the availability of large-scale genotype data, efficient approaches for an unbiased whole genome scan are becoming necessary.Methods: We have developed a new method, the whole genome long-range haplotype test (WGLRH), which uses genome-wide distributions to test for recent positive selection. Adapted from the long-range haplotype (LRH) test, the WGLRH test uses patterns of linkage disequilibrium (LD) to identify regions with extremely low historic recombination. Common haplotypes with significantly longer than expected ranges of LD given their frequencies are identified as putative signatures of recent positive selection. In addition, we have also determined the ancestral alleles of SNPs by genotyping chimpanzee and gorilla DNA, and have identified SNPs where the non-ancestral alleles have risen to extremely high frequencies in human populations, termed ‘flipped SNPs’. Combining the haplotype test and the flipped SNPs determination, the WGLRH test serves as an unbiased genome-wide screen for regions under putative selection, and is potentially applicable to the study of other human populations.Results: Using WGLRH and high-density oligonucleotide arrays interrogating 116 204 SNPs, we rapidly identified putative regions of positive selection in three populations (Asian, Caucasian, African-American), and extended these observations to a fourth population, Yoruba, with data obtained from the International HapMap consortium. We mapped significant regions to annotated genes. While some regions overlap with genes previously suggested to be under positive selection, many of the genes have not been previously implicated in natural selection and offer intriguing possibilities for further study.Availability: the programs for the WGLRH algorithm are freely available and can be downloaded at http://www.affymetrix.com/support/supplement/WGLRH_program.zipContact:Giulia_Kennedy@affymetrix.comSupplementary Material: Three Supplementary tables

@article{zhang2006whole,
  author = {Zhang, Chun and Bailey, Dione K. and Awad, Tarif and Liu, Guoying and Xing, Guoliang and Cao, Manqiu and Valmeekam, Venu and Retief, Jacques and Matsuzaki, Hajime and Taub, Margaret and Seielstad, Mark and Kennedy, Giulia C.},
  title = {A whole genome long-range haplotype (WGLRH) test for detecting imprints of positive selection in human populations},
  journal = {Bioinformatics},
  year = {2006},
  volume = {22},
  number = {17},
  pages = {2122-2128},
  url = {http://bioinformatics.oxfordjournals.org/content/22/17/2122.abstract},
  doi = {10.1093/bioinformatics/btl365},
  keywords = {haplotype_length GWAS},
  abstract = {Motivation: The identification of signatures of positive selection can provide important insights into recent evolutionary history in human populations. Current methods mostly rely on allele frequency determination or focus on one or a small number of candidate chromosomal regions per study. With the availability of large-scale genotype data, efficient approaches for an unbiased whole genome scan are becoming necessary.Methods: We have developed a new method, the whole genome long-range haplotype test (WGLRH), which uses genome-wide distributions to test for recent positive selection. Adapted from the long-range haplotype (LRH) test, the WGLRH test uses patterns of linkage disequilibrium (LD) to identify regions with extremely low historic recombination. Common haplotypes with significantly longer than expected ranges of LD given their frequencies are identified as putative signatures of recent positive selection. In addition, we have also determined the ancestral alleles of SNPs by genotyping chimpanzee and gorilla DNA, and have identified SNPs where the non-ancestral alleles have risen to extremely high frequencies in human populations, termed ‘flipped SNPs’. Combining the haplotype test and the flipped SNPs determination, the WGLRH test serves as an unbiased genome-wide screen for regions under putative selection, and is potentially applicable to the study of other human populations.Results: Using WGLRH and high-density oligonucleotide arrays interrogating 116 204 SNPs, we rapidly identified putative regions of positive selection in three populations (Asian, Caucasian, African-American), and extended these observations to a fourth population, Yoruba, with data obtained from the International HapMap consortium. We mapped significant regions to annotated genes. While some regions overlap with genes previously suggested to be under positive selection, many of the genes have not been previously implicated in natural selection and offer intriguing possibilities for further study.Availability: the programs for the WGLRH algorithm are freely available and can be downloaded at http://www.affymetrix.com/support/supplement/WGLRH_program.zipContact:Giulia_Kennedy@affymetrix.comSupplementary Material: Three Supplementary tables}
  }

2003

2002

Davis, G. M.; Wu, W.-P.; Liu, H.-Y.; Williams, G.; Lu, S.-B.; Chen, H.-G. & Seto, E. (2002): Applying GIS and Remote Sensing to the Epidemiology of Schistosomiasis in Poyang Lake, Jiangxi Province, China.. In: Annals of GIS, Ausgabe/Number: 2, Vol. 8, Erscheinungsjahr/Year: 2002. Seiten/Pages: 67-77. [Volltext]

Este ensayo presenta la aproximación mas cercana de simulación de trafico inteligente con agentes. Exponen un modelo BDI para dicha simulacion: Rossetti, R. J. F.; Bordini, R. H.; Bazzan, A. L. C.; Bampi, S.; Liu, R. & Van Vliet, D. (2002): Using BDI agents to improve driver modelling in a commuter scenario. In: Transportation Research Part C-emerging Technologies, Ausgabe/Number: 5-6, Vol. 10, Verlag/Publisher: Pergamon-elsevier Science Ltd. Erscheinungsjahr/Year: 2002. Seiten/Pages: 373-398.

The use of multi-agent systems to model and to simulate real systems consisting of intelligent entities capable of autonomously co-operating with each other has emerged as an important field of research. This has been applied to a variety of areas, such as social sciences, engineering, and mathematical and physical theories. In this work, we address the complex task of modelling drivers' behaviour through the use of agent-based techniques. Contemporary traffic systems have experienced considerable changes in the last few years, and the rapid growth of urban areas has challenged scientific and technical communities. Influencing drivers' behaviour appears as an alternative to traditional approaches to cope with the potential problem of traffic congestion, such as the physical modification of road infrastructures and the improvement of control systems. It arises as one of the underlying ideas of intelligent transportation systems. In order to offer a good means to evaluate the impact that exogenous information may exert on drivers' decision making, we propose an extension to an existing microscopic simulation model called Dynamic Route Assignment Combining User Learning and microsimulAtion (DRACULA). In this extension, the traffic domain is viewed as a multi-agent world and drivers are endowed with mental attitudes, which allow rational decisions about route choice and departure time. This work is divided into two main parts. The first part describes the original DRACULA framework and the extension proposed to support our agent-based traffic model. The second part is concerned with the reasoning mechanism of drivers modelled by means of a Beliefs, Desires, and Intentions (BDI) architecture. In this part, we use AgentSpeak(L) to specify commuter scenarios and special emphasis is given to departure time and route choices. This paper contributes in that respect by showing a practical way of representing and assessing drivers' behaviour and the adequacy of using AgentSpeak(L) as a modelling language, as it provides clear and elegant specifications of BDI agents. (C) 2002 Elsevier Science Ltd. All rights reserved.

@article{Rossetti2002,
  author = {Rossetti, R. J. F. and Bordini, R. H. and Bazzan, A. L. C. and Bampi, S. and Liu, R. and Van Vliet, D.},
  title = {Using BDI agents to improve driver modelling in a commuter scenario},
  journal = {Transportation Research Part C-emerging Technologies},
  publisher = {Pergamon-elsevier Science Ltd},
  year = {2002},
  volume = {10},
  number = {5-6},
  pages = {373--398},
  note = {Este ensayo presenta la aproximación mas cercana de simulación de trafico inteligente con agentes. Exponen un modelo BDI para dicha simulacion},
  doi = {10.1016/S0968-090X(02)00027-X},
  keywords = {INFORMATION},
  abstract = {The use of multi-agent systems to model and to simulate real systems consisting of intelligent entities capable of autonomously co-operating with each other has emerged as an important field of research. This has been applied to a variety of areas, such as social sciences, engineering, and mathematical and physical theories. In this work, we address the complex task of modelling drivers' behaviour through the use of agent-based techniques. Contemporary traffic systems have experienced considerable changes in the last few years, and the rapid growth of urban areas has challenged scientific and technical communities. Influencing drivers' behaviour appears as an alternative to traditional approaches to cope with the potential problem of traffic congestion, such as the physical modification of road infrastructures and the improvement of control systems. It arises as one of the underlying ideas of intelligent transportation systems. In order to offer a good means to evaluate the impact that exogenous information may exert on drivers' decision making, we propose an extension to an existing microscopic simulation model called Dynamic Route Assignment Combining User Learning and microsimulAtion (DRACULA). In this extension, the traffic domain is viewed as a multi-agent world and drivers are endowed with mental attitudes, which allow rational decisions about route choice and departure time. This work is divided into two main parts. The first part describes the original DRACULA framework and the extension proposed to support our agent-based traffic model. The second part is concerned with the reasoning mechanism of drivers modelled by means of a Beliefs, Desires, and Intentions (BDI) architecture. In this part, we use AgentSpeak(L) to specify commuter scenarios and special emphasis is given to departure time and route choices. This paper contributes in that respect by showing a practical way of representing and assessing drivers' behaviour and the adequacy of using AgentSpeak(L) as a modelling language, as it provides clear and elegant specifications of BDI agents. (C) 2002 Elsevier Science Ltd. All rights reserved.}
  }