bluuebunny/crossref_metadata_2025 huggingface dataset:
Role of the PDZ Domain-Binding Motif of the Oncoprotein E6 in the Pathogenesis of Human Papillomavirus Type 31
Authors: Lee Choongho , Laimins Laimonis A.
Published: October 2004

A number of PDZ domain-containing proteins have been identified as binding partners for the oncoprotein E6 of the high-risk type human papillomaviruses (HPVs). These include hDlg, hScrib, MAGI-1, MAGI-2, MAGI-3, and MUPP1. The PDZ domain-binding motif (-X-T-X-V) at the carboxy terminus of E6 is essential for targeting PDZ proteins for proteasomal degradation. The presence of this motif only in the high-risk HPVs suggests its possible role in HPV-induced oncogenesis. To investigate the role of the PDZ domain-binding motif of E6 in the HPV life cycle, two mutant HPV31 genomes were constructed: E6ValΔ, with a deletion of the last amino acid residue of E6 (valine), and E6ETQVΔ, with a deletion of the entire PDZ domain-binding motif of E6 (ETQV). Three human foreskin keratinocyte (HFK) cell lines were established which maintained transfected wild-type HPV31 or either of two mutant genomes. Cells containing either of two mutant genomes were significantly retarded in their growth rates and reduced in their viral copy numbers compared to those transfected with wild-type genomes. Western analysis did not reveal any significant changes in the levels of PDZ proteins following stable transfection of any HPV31 genomes into HFKs. Although the E6ETQVΔ-transfected HFKs exhibited a pattern of morphological differentiation that appeared different from the HPV31 wild-type-transfected HFKs in organotypic raft cultures, immunohistochemical analysis failed to identify substantial changes in the differentiation-dependent membrane localization of hDlg proteins. These results suggest that binding of E6 to PDZ proteins modulates the early viral functions such as proliferation and maintenance of the viral copy number in undifferentiated cells.
Role of Murine Leukemia Virus Nucleocapsid Protein in Virus Assembly
Authors: Muriaux Delphine , Costes Sylvain , Nagashima Kunio , Mirro Jane , Cho Ed , Lockett Stephen , Rein Alan
Published: October 2004

The retroviral nucleocapsid protein (NC) originates by cleavage of the Gag polyprotein. It is highly basic and contains one or two zinc fingers. Mutations in either the basic residues or the zinc fingers can affect several events of the virus life cycle. They frequently prevent the specific packaging of the viral RNA, affect reverse transcription, and impair virion assembly. In this work, we explore the role of NC in murine leukemia virus (MLV) particle assembly and release. A panel of NC mutants, including mutants of the zinc finger and of a basic region, as well as truncations of the NC domain of Gag, were studied. Several of these mutations dramatically reduce the release of virus particles. A mutant completely lacking the NC domain is apparently incapable of assembling into particles, although its Gag protein is still targeted to the plasma membrane. By electron microscopy on thin sections of virus-producing cells, we observed that some NC mutants exhibit various stages of budding defects at the plasma membrane and have aberrant particle morphology; electron micrographs of cells expressing some of these mutants are strikingly similar to those of cells expressing “late-domain” mutants. However, the defects of NC mutants with respect to virus release and infectivity could be complemented by an MLV lacking the p12 domain. Therefore, the functions of NC in virus budding and infectivity are completely distinct from viral late-domain function.
Perforin and Fas Act Together in the Induction of Apoptosis, and Both Are Critical in the Clearance of Lymphocytic Choriomeningitis Virus Infection
Authors: Rode Miriam , Balkow Sandra , Sobek Vera , Brehm Reina , Martin Praxedis , Kersten Astrid , Dumrese Tilman , Stehle Thomas , Müllbacher Arno , Wallich Reinhard , Simon Markus M.
Published: October 2004

In this report we questioned the current view that the two principal cytotoxic pathways, the exocytosis and the Fas ligand (FasL)/Fas-mediated pathway, have largely nonoverlapping biological roles. For this purpose we have analyzed the response of mice that lack Fas as well as granzyme A (gzmA) and gzmB (FasxgzmAxB−/−) to infection with lymphocytic choriomeningitis virus (LCMV). We show that FasxgzmAxB−/−mice, in contrast to B6, Fas−/−, and gzmAxB−/−mice, do not recover from a primary infection with LCMV, in spite of the expression of comparable numbers of LCMV-immune and gamma interferon-producing cytotoxic T lymphocytes (CTL) in all mouse strains tested. Ex vivo-derived FasxgzmAxB−/−CTL lacked nucleolytic activity and expressed reduced cytolytic activity compared to B6 and Fas−/−CTL. Furthermore, virus-immune CTL with functional FasL and perforin (gzmAxB−/−) are more potent in causing target cell apoptosis in vitro than those expressing FasL alone (perfxgzmAxB−/−). This synergistic effect of perforin on Fas-mediated nucleolysis of target cells is indicated by the fact that, compared to perfxgzmAxB−/−CTL, gzmAxB−/−CTL induced (i) an accelerated decrease in mitochondrial transmembrane potential, (ii) increased generation of reactive oxygen species, and (iii) accelerated phosphatidylserine exposure on plasma membranes. We conclude that perforin does not mediate recovery from LCMV by itself but plays a vital role in both gzmA/B and FasL/Fas-mediated CTL activities, including apoptosis and control of viral infections.
Functions of the C-Terminal Domain of Varicella-Zoster Virus Glycoprotein E in Viral Replication In Vitro and Skin and T-Cell Tropism In Vivo
Authors: Moffat Jennifer , Mo Chengjun , Cheng Jason J. , Sommer Marvin , Zerboni Leigh , Stamatis Shaye , Arvin Ann M.
Published: October 2004

Varicella-zoster virus (VZV) glycoprotein E (gE) is essential for VZV replication. To further analyze the functions of gE in VZV replication, a full deletion and point mutations were made in the 62-amino-acid (aa) C-terminal domain. Targeted mutations were introduced in YAGL (aa 582 to 585), which mediates gE endocytosis, AYRV (aa 568 to 571), which targets gE to the
trans
-Golgi network (TGN), and SSTT, an “acid cluster” comprising a phosphorylation motif (aa 588 to 601). Substitutions Y582G in YAGL, Y569A in AYRV, and S593A, S595A, T596A, and T598A in SSTT were introduced into the viral genome by using VZV cosmids. These experiments demonstrated a hierarchy in the contributions of these C-terminal motifs to VZV replication and virulence. Deletion of the gE C terminus and mutation of YAGL were lethal for VZV replication in vitro. Mutations of AYRV and SSTT were compatible with recovery of VZV, but the AYRV mutation resulted in rapid virus spread in vitro and the SSTT mutation resulted in higher virus titers than were observed for the parental rOka strain. When the rOka-gE-AYRV and rOka-gE-SSTT mutants were evaluated in skin and T-cell xenografts in SCIDhu mice, interference with TGN targeting was associated with substantial attenuation, especially in skin, whereas the SSTT mutation did not alter VZV infectivity in vivo. These results provide the first information about how targeted mutations of this essential VZV glycoprotein affect viral replication in vitro and VZV virulence in dermal and epidermal cells and T cells within intact tissue microenvironments in vivo.
Emergence of a Drug-Dependent Human Immunodeficiency Virus Type 1 Variant during Therapy with the T20 Fusion Inhibitor
Authors: Baldwin Chris E. , Sanders Rogier W. , Deng Yiqun , Jurriaans Suzanne , Lange Joep M. , Lu Min , Berkhout Ben
Published: October 2004

The fusion inhibitor T20 belongs to a new class of anti-human immunodeficiency virus type 1 (HIV-1) drugs designed to block entry of the virus into the host cell. However, the success of T20 has met with the inevitable emergence of drug-resistant HIV-1 variants. We describe an evolutionary pathway taken by HIV-1 to escape from the selective pressure of T20 in a treated patient. Besides the appearance of T20-resistant variants, we report for the first time the emergence of drug-dependent viruses with mutations in both the HR1 and HR2 domains of envelope glycoprotein 41. We propose a mechanistic model for the dependence of HIV-1 entry on the T20 peptide. The T20-dependent mutant is more prone to undergo the conformational switch that results in the formation of the fusogenic six-helix bundle structure in gp41. A premature switch will generate nonfunctional envelope glycoproteins (dead spikes) on the surface of the virion, and T20 prevents this abortive event by acting as a safety pin that preserves an earlier prefusion conformation.
Molecular Epidemiology of Human Immunodeficiency Virus Type 1 Sub-Subtype A3 in Senegal from 1988 to 2001
Authors: Meloni Seema Thakore , Sankalé Jean-Louis , Hamel Donald J. , Eisen Geoffrey , Guéye-Ndiaye Aissatou , Mboup Souleymane , Kanki Phyllis J.
Published: October 2004

The global human immunodeficiency virus (HIV)epidemic is characterized by significant genetic diversity in circulating viruses. We have recently characterized a group of viruses that form a distinct sub-subtype within the subtype A radiation, which we have designated HIV type 1 (HIV-1) sub-subtype A, circulating in West Africa. A prospective study of a cohort of female sex workers (FSW) in Dakar, Senegal over an 18-year period indicated that an A3-specific sequence in the C2-V3 region of the env gene was found in 46 HIV-1-infected women. HIV-1 sub-subtype A3 appeared in the FSW population as early as 1988 and continued to be transmitted as of 2001. We also found that HIV-1 A3 is not confined to the FSW cohort in Senegal but is also circulating in the general population in Dakar. Furthermore, analyses of viral sequences from a few other West and Central African countries also demonstrated evidence of HIV-1 A3 sequence in isolates from HIV-1-infected people in Ivory Coast, Nigeria, Niger, Guinea Bissau, Benin, and Equatorial Guinea. Overall, because of the evidence of sub-subtype A3 in the general population in Senegal, as well as in a few neighboring West and Central African countries, along with the increasing incidence of infection with A3-containing viruses in the Dakar high-risk FSW population, we feel that HIV-1 sub-subtype A3 viruses are important to distinguish and monitor.
The Herpes Simplex Virus Type 1 Latency-Associated Transcript (LAT) Enhancer/
rcr
Is Hyperacetylated during Latency Independently of LAT Transcription
Authors: Kubat Nicole J. , Amelio Antonio L. , Giordani Nicole V. , Bloom David C.
Published: October 2004

During herpes simplex virus type 1 (HSV-1) latency, only one region of the viral genome is actively transcribed: the region encoding the latency-associated transcript (LAT). A previous study demonstrated that during latency the LAT promoter is hyperacetylated at histone H3 (K9, K14) relative to lytic genes examined. In the present study, we examine the acetylation profile of regions downstream of the LAT promoter during a latent infection of murine dorsal root ganglia. These analyses revealed the following: (i) the region of the genome containing the 5′ exon of the LAT primary transcript was at least as enriched in acetylated H3 as the LAT promoter, and (ii) the region of hyperacetylation does not extend to the ICP0 promoter. In order to assess the contribution of LAT transcription to the acetylation of the 5′ exon region, the acetylation profile of KOS/29, a recombinant with a deletion of the LAT promoter, was examined. The region containing the 5′ exon of KOS/29 was hyperacetylated relative to lytic gene regions in the absence of detectable LAT transcription. These results indicate that the region containing the 5′ exon of LAT, known to contain enhancer activities and to be critical for induced reactivation (
rcr
), exists in a chromatin structure during latency that is distinct from other lytic gene regions. This result suggests a role for the 5′ exon LAT enhancer region as a
cis
-acting regulator of transcription that maintains a transcriptionally permissive chromatin domain in the HSV-1 latent episome.
A Cyclooxygenase-2 Homologue Encoded by Rhesus Cytomegalovirus Is a Determinant for Endothelial Cell Tropism
Authors: Rue Cary A. , Jarvis Michael A. , Knoche Amber J. , Meyers Heather L. , DeFilippis Victor R. , Hansen Scott G. , Wagner Markus , Früh Klaus , Anders David G. , Wong Scott W. , Barry Peter A. , Nelson Jay A.
Published: October 2004

Cyclooxygenase-2 (COX-2) is a cellular enzyme in the eicosanoid synthetic pathway that mediates the synthesis of prostaglandins from arachidonic acid. The eicosanoids function as critical regulators of a number of cellular processes, including the acute and chronic inflammatory response, hemostasis, and the innate immune response. Human cytomegalovirus (HCMV), which does not encode a viral COX-2 isoform, has been shown to induce cellular COX-2 expression. Importantly, although the precise role of COX-2 in CMV replication is unknown, COX-2 induction was shown to be critical for normal HCMV replication. In an earlier study, we identified an open reading frame (Rh10) within the rhesus cytomegalovirus (RhCMV) genome that encoded a putative protein (designated vCOX-2) with high homology to cellular COX-2. In the current study, we show that vCOX-2 is expressed with early-gene kinetics during RhCMV infection, resulting in production of a 70-kDa protein. Consistent with the expression of a viral COX-2 isoform, cellular COX-2 expression was not induced during RhCMV infection. Finally, analysis of growth of recombinant RhCMV with vCOX-2 deleted identified vCOX-2 as a critical determinant for replication in endothelial cells.
Functional Genomics Analysis of Singapore Grouper Iridovirus: Complete Sequence Determination and Proteomic Analysis
Authors: Song Wen Jun , Qin Qi Wei , Qiu Jin , Huang Can Hua , Wang Fan , Hew Choy Leong
Published: October 2004

Here we report the complete genome sequence of Singapore grouper iridovirus (SGIV). Sequencing of the random shotgun and restriction endonuclease genomic libraries showed that the entire SGIV genome consists of 140,131 nucleotide bp. One hundred sixty-two open reading frames (ORFs) from the sense and antisense DNA strands, coding for lengths varying from 41 to 1,268 amino acids, were identified. Computer-assisted analyses of the deduced amino acid sequences revealed that 77 of the ORFs exhibited homologies to known virus genes, 23 of which matched functional iridovirus proteins. Forty-two putative conserved domains or signatures were detected in the National Center for Biotechnology Information CD-Search database and PROSITE database. An assortment of enzyme activities involved in DNA replication, transcription, nucleotide metabolism, cell signaling, etc., were identified. Viruses were cultured on a cell line derived from the embryonated egg of the grouper
Epinephelus tauvina
, isolated, and purified by sucrose gradient ultracentrifugation. The protein extract from the purified virions was analyzed by polyacrylamide gel electrophoresis followed by in-gel digestion of protein bands. Matrix-assisted laser desorption ionization-time of flight mass spectrometry and database searching led to identification of 26 proteins. Twenty of these represented novel or previously unidentified genes, which were further confirmed by reverse transcription-PCR (RT-PCR) and DNA sequencing of their respective RT-PCR products.
Epstein-Barr Virus Infection in Ex Vivo Tonsil Epithelial Cell Cultures of Asymptomatic Carriers
Authors: Pegtel Dirk M. , Middeldorp Jaap , Thorley-Lawson David A.
Published: October 2004

Epstein-Barr virus (EBV) is found frequently in certain epithelial pathologies, such as nasopharyngeal carcinoma and oral hairy leukoplakia, indicating that the virus can infect epithelial cells in vivo. Recent studies of cell lines imply that epithelial cells may also play a role in persistent EBV infection in vivo. In this report, we show the establishment and characterization of an ex vivo culture model of tonsil epithelial cells, a likely site for EBV infection in vivo. Primary epithelial-cell cultures, generated from tonsil explants, contained a heterogeneous mixture of cells with an ongoing process of differentiation. Keratin expression profiles were consistent with the presence of cells from both surface and crypt epithelia. A small subset of cells could be latently infected by coculture with EBV-releasing cell lines, but not with cell-free virus. We also detected viral-DNA, -mRNA, and -protein expression in cultures from EBV-positive tonsil donors prior to in vitro infection. We conclude that these cells were either already infected at the time of explantation or soon after through cell-to-cell contact with B cells replicating EBV in the explant. Taken together, these findings suggest that the tonsil epithelium of asymptomatic virus carriers is able to sustain EBV infection in vivo. This provides an explanation for the presence of EBV in naso- and oropharyngeal pathologies and is consistent with epithelial cells playing a role in the egress of EBV during persistent infection.
Identification of TAZ as a Binding Partner of the Polyomavirus T Antigens
Authors: Tian Yu , Li Dawei , Dahl Jean , You John , Benjamin Thomas
Published: October 2004

A polyomavirus mutant isolated by the tumor host range selection procedure (19) has a three-amino-acid deletion (Δ2-4) in the common N terminus of the T antigens. To search for a cellular protein bound by wild-type but not the mutant T antigen(s), a yeast two-hybrid screen of a mouse embryo cDNA library was carried out with a bait of wild-type small T antigen (sT) fused N terminally to the DNA-binding domain of Gal4. TAZ, a transcriptional coactivator with a WW domain and PDZ-binding motif (17), was identified as a binding partner. TAZ bound in vivo to all three T antigens with different apparent affinities estimated as 1:7:100 (large T antigen [lT]:middle T antigen [mT]:sT). The Δ2-4 mutant T antigens showed no detectable binding. The sT and mT of the host range transformation-defective (
hr-t
) mutant NG59 with an alteration in the common sT/mT region (179 D→NI) and a normal N terminus also failed to bind TAZ, while the unaltered lT bound but with reduced affinity compared to that seen in a wild-type virus infection. The WW domain but not the PDZ-binding motif of TAZ was essential for T antigen binding. The Δ2-4 mutant was defective in viral DNA replication. Forced overexpression of TAZ blocked wild-type DNA replication in a manner dependent on the binding site for the polyomavirus enhancer-binding protein 2α. Wild-type polyomavirus T antigens effectively block transactivation by TAZ. The functional significance of TAZ interactions with polyomavirus T antigens is discussed.
Neuraminidase Is Important for the Initiation of Influenza Virus Infection in Human Airway Epithelium
Authors: Matrosovich Mikhail N. , Matrosovich Tatyana Y. , Gray Thomas , Roberts Noel A. , Klenk Hans-Dieter
Published: October 2004

Influenza virus neuraminidase (NA) plays an essential role in release and spread of progeny virions, following the intracellular viral replication cycle. To test whether NA could also facilitate virus entry into cell, we infected cultures of human airway epithelium with human and avian influenza viruses in the presence of the NA inhibitor oseltamivir carboxylate. Twenty- to 500-fold less cells became infected in drug-treated versus nontreated cultures (
P
< 0.0001) 7 h after virus application, indicating that the drug suppressed the initiation of infection. These data demonstrate that viral NA plays a role early in infection, and they provide further rationale for the prophylactic use of NA inhibitors.
Immunization with Modified Vaccinia Virus Ankara-Based Recombinant Vaccine against Severe Acute Respiratory Syndrome Is Associated with Enhanced Hepatitis in Ferrets
Authors: Weingartl Hana , Czub Markus , Czub Stefanie , Neufeld James , Marszal Peter , Gren Jason , Smith Greg , Jones Shane , Proulx Roxanne , Deschambault Yvonne , Grudeski Elsie , Andonov Anton , He Runtao , Li Yan , Copps John , Grolla Allen , Dick Daryl , Berry Jody , Ganske Shelley , Manning Lisa , Cao Jingxin
Published: October 2004

Severe acute respiratory syndrome (SARS) caused by a newly identified coronavirus (SARS-CoV) is a serious emerging human infectious disease. In this report, we immunized ferrets (
Mustela putorius furo
) with recombinant modified vaccinia virus Ankara (rMVA) expressing the SARS-CoV spike (S) protein. Immunized ferrets developed a more rapid and vigorous neutralizing antibody response than control animals after challenge with SARS-CoV; however, they also exhibited strong inflammatory responses in liver tissue. Inflammation in control animals exposed to SARS-CoV was relatively mild. Thus, our data suggest that vaccination with rMVA expressing SARS-CoV S protein is associated with enhanced hepatitis.
A DUAL CRITERIA PREEMPTIVE SCHEDULING PROBLEM FOR MINIMAX ERROR OF IMPRECISE COMPUTATION TASKS
Authors: HO KEVIN I.-J. , LEUNG JOSEPH Y.-T.
Published: October 2004

We consider a hierarchical optimization problem for imprecise computation tasks, where each task is weighted with two weights, w and w'. The primary criterion is to minimize the total w-weighted error of all optional parts of tasks and the secondary criterion is to minimize the maximum w'-weighted error. An algorithm is given with time complexity O(kn3 log 2 n) for parallel and identical processors and O(kn2) for a single processor, where k is the number of distinct w-weights.
IMPROVED COMPETITIVE ALGORITHMS FOR TWO-PROCESSOR REAL-TIME SYSTEMS
Authors: LEUNG JOSEPH Y.-T.
Published: October 2004

The problem of competitive on-line scheduling in two-processor real-time environments is studied. The model of Koren and Shasha is followed: Every task has a deadline and a value that it obtains only if it completes by its deadline – the value being its computation time. The goal is to design on-line schedulers with worst-case guarantees compared with a clairvoyant scheduler. Koren and Shasha gave algorithms for the migration and no-migration models, with competitive multipliers of 2 and 3, respectively. In this article, we give an algorithm for the no-migration model with an improved competitive multiplier of [Formula: see text]. We also show that the competitive multiplier for the migration model can be lowered by using a fast processor and a slow processor, compared with using several parallel and identical processors with the same aggregate computing power.
A UNIFIED NEURAL BIGRADIENT ALGORITHM FOR ROBUST PCA AND MCA
Authors: WANG LIUYUE , KARHUNEN JUHA
Published: October 2004

A new instantaneous-gradient search algorithm for computing a principal component or minor component type solution is proposed. The algorithm can use normalized Hebbian or anti-Hebbian learning in a unified formula. Starting from one-unit rule, a multi-unit algorithm is developed which can simultaneously extract several robust counterparts of the principal or minor eigenvectors of the data covariance matrix. Standard principal or minor components emerge as special cases from the general non-quadratic criterion. The learning rule is analyzed mathematically, and the theoretical results are verified by simulations. The proposed bigradient approach can be applied to blind separation of independent source signals from their linear mixtures.
AN ADAPTIVE BOOLEAN AUTOMATON TO MODEL CIRCADIAN CYCLES
Authors: PERAZZO R.P.J. , SCHUSCHNY A.
Published: October 2004

We propose a Boolean cellular automaton to model an artificial adaptive living organism in order to investigate the development of cyclic vital functions during a simulated evolutionary process. The organism is endowed with a basic architecture consisting of several sensor (input), motor (output) and processing Boolean gates whose connectivity pattern is adapted with a genetic algorithm. Cyclic searching behaviors develop that are tuned to the spatial distribution of “food”. Under additional assumptions we also find that internal pacemakers can develop to adapt plastically to the alternance of “light” and “darkness”. These pacemakers coexist with a “free running” regime in which the circadian cycles persist even in the absence of external periodic stimuli.
CONSTRUCTIVE TRAINING METHODS FOR FEEDFORWARD NEURAL NETWORKS WITH BINARY WEIGHTS
Authors: MAYORAZ EDDY , AVIOLAT FRÉDÉRIC
Published: October 2004

Quantization of the parameters of a Perceptron is a central problem in hardware implementation of neural networks using a numerical technology. A neural model with each weight limited to a small integer range will require little surface of silicon. Moreover, according to Occam’s razor principle, better generalization abilities can be expected from a simpler computational model. The price to pay for these benefits lies in the difficulty to train these kind of networks. This paper proposes essentially two new ideas for constructive training algorithms, and demonstrates their efficiency for the generation of feedforward networks composed of Boolean threshold gates with discrete weights. A proof of the convergence of these algorithms is given. Some numerical experiments have been carried out and the results are presented in terms of the size of the generated networks and of their generalization abilities.
SIDE EFFECTS OF NORMALISING RADIAL BASIS FUNCTION NETWORKS
Authors: SHORTEN ROBERT , MURRAY-SMITH RODERICK
Published: October 2004

Normalisation of the basis function activations in a Radial Basis Function (RBF) network is a common way of achieving the partition of unity often desired for modelling applications. It results in the basis functions covering the whole of the input space to the same degree. However, normalisation of the basis functions can lead to other effects which are sometimes less desirable for modelling applications. This paper describes some side effects of normalisation which fundamentally alter properties of the basis functions, e.g. the shape is no longer uniform, maxima of basis functions can be shifted from their centres, and the basis functions are no longer guaranteed to decrease monotonically as distance from their centre increases—in many cases basis functions can ‘reactivate’, i.e. re-appear far from the basis function centre. This paper examines how these phenomena occur, discusses their relevance for non-linear function approximation and examines the effect of normalisation on the network condition number and weights.
IMPROVEMENT OF PROJECTION-TYPE ASSOCIATIVE MEMORIES BY USING A TWO-PHASE RECALLING PROCEDURE
Authors: LEE DONQ-LIANG , WANG WEN-JUNE
Published: October 2004

In this letter, we propose a Two-Phase Recalling Procedure (TPRP) to improve the recall capability of the projection-type associative memory. It is known that the conventional projection dynamic sometimes produces spurious states that do not belong to the space spanned by the prototype vectors (memory space). The proposed TPRP provides a trapped spurious state another chance to project onto the memory space such that the recall capability of the projection-type associative memories can be greatly improved. Finally a simulation result demonstrates the effectiveness of the TPRP.
NEURAL NETWORKS IN PETROLEUM ENGINEERING: A CASE STUDY
Authors: VUKELIC M.A. , MIRANDA E.N.
Published: October 2004

A multilayer neural network has been used for deciding which oil reservoir layer has to be perforated. Many network architectures were tested until we found those with the best generalization capability. The network performs better than human experts and its achievements are higher than the historical average in the test area. As in other applications of neural networks, the learning capability improves with more hidden neurons but the generalization does not.
NONLINEAR TIME SERIES ANALYSIS BY NEURAL NETWORKS: A CASE STUDY
Authors: SAXÉN HENRIK
Published: October 2004

This paper presents a neural network approach to time-series analysis of a univariate nonlinear system. Feedforward networks are studied, and an appropriate network size is determined by different criteria computed on the basis of the performance of the models on the training and test sets. The analysis and conclusions drawn are supported by studies of the phase portraits of the models. By a proper choice of network size, the problems of over-parameterization are demonstrated to be avoided. The overfitting observed for larger networks is analyzed and the underlying reasons for their worse generalization capabilities are explained. Finally, some observations are made on the approximation provided by an oversized network with weights determined by an incomplete (interrupted) training and that of the optimal-sized network.
CNN: A SPEAKER RECOGNITION SYSTEM USING A CASCADED NEURAL NETWORK
Authors: ZAKI M. , GHALWASH A. , ELKOUNY A.A.
Published: October 2004

The main emphasis of this paper is to present an approach for combining supervised and unsupervised neural network models to the issue of speaker recognition. To enhance the overall operation and performance of recognition, the proposed strategy integrates the two techniques, forming one global model called the cascaded model. We first present a simple conventional technique based on the distance measured between a test vector and a reference vector for different speakers in the population. This particular distance metric has the property of weighting down the components in those directions along which the intraspeaker variance is large. The reason for presenting this method is to clarify the discrepancy in performance between the conventional and neural network approach. We then introduce the idea of using unsupervised learning technique, presented by the winner-take-all model, as a means of recognition. Due to several tests that have been conducted and in order to enhance the performance of this model, dealing with noisy patterns, we have preceded it with a supervised learning model—the pattern association model—which acts as a filtration stage. This work includes both the design and implementation of both conventional and neural network approaches to recognize the speakers templates—which are introduced to the system via a voice master card and preprocessed before extracting the features used in the recognition. The conclusion indicates that the system performance in case of neural network is better than that of the conventional one, achieving a smooth degradation in respect of noisy patterns, and higher performance in respect of noise-free patterns.
LEARNING MULTIPLE CAUSES BY COMPETITION ENHANCED LEAST MEAN SQUARE ERROR RECONSTRUCTION
Authors: ZHANG BAI-LING , XU LEI , FU MINYUE
Published: October 2004

In this paper we studied a self-organization principle that input should be best reconstructed from a factorial distributed hidden representation, which has been addressed in the literature recently. An auto-encoder network is trained by the Least Mean Square Error Reconstruction (LMSER) while the redundance in the representation is reduced by a proposed anti-Hebbian scheme, in which a penalty term called Receptive Field Overlapping Index (RFOI) is combined into the objective function for enhancing competition among nodes in the network. Our learning scheme provides a way for balancing the cooperation and competition necessary for the self-organization process thus realizes the multiple causes model, which accounts for an observed data by combining assertions from the discovered causes or features in the data. Our experiment results demonstrate again the powerful information processing capability inherent to the popular weighted sum followed by sigmoid squashing. Comparing with previous probability theory based multiple causes models, our scheme is much easier to implement and quite reliable.
DETERMINATION OF DEPENDENT AND INDEPENDENT COMMUNICATION PATHS USING NEURAL NETWORKS
Authors: HEMMINGER THOMAS L. , POMALAZA-RAEZ CARLOS A.
Published: October 2004

Efficient and timely computation of routing algorithms is very important for proper operation of multi-hop packet radio networks. When a network operates in the presence of jammers (a hostile environment) additional constraints must be considered when computing the routing tables. Insertion of those constraints in routing algorithms enables the determination of dependent and independent paths between source and destination nodes, thus fixing lower limits on the number of external jamming sources required to sever a transmission. An important measure of network reliability is also provided. This paper proposes a solution to the routing problem through the implementation of a Hopfield network and demonstrates that by proper selection of an energy function we can solve the problem rapidly and reliably.
A REGULARIZATION TERM TO AVOID THE SATURATION OF THE SIGMOIDS IN MULTILAYER NEURAL NETWORKS
Authors: GARRIDO LLUIS , GÓMEZ SERGIO , GAITÁN VICENS , SERRA-RICART MIQUEL
Published: October 2004

In this paper we propose a new method to prevent the saturation of any set of hidden units of a multilayer neural network. This method is implemented by adding a regularization term to the standard quadratic error function, which is based on a repulsive action between pairs of patterns.
EQUILIBRIUM AND ATTRACTIVITY ANALYSIS FOR A CLASS OF HETERO-ASSOCIATIVE NEURAL MEMORIES
Authors: LEE DONQ-LIANG , WANG WEN-JUNE
Published: October 2004

Based on the natural structure of Kosko’s Bidirectional Associative Memories (BAM), a high-performance, high-capacity associative neural model is proposed which is capable of simultaneous hetero-associative recall. The proposed model, Modified Bidirectional Decoding Strategy (MBDS), improves the recall rate by adding some association fascicles to Kosko’s BAM. The association fascicles are sparse coding neuron structures that provide activating strengths between two neuron fields (say, field X and field Y). The sufficient conditions for a state to become an equilibrium state of the MBDS network is derived. Based on these results, we discuss the basins of attraction of the training pairs in one iteration. The upper bound of the number of error bits which can be tolerated by MBDS is also derived. Because the attractivity of a stored training pair can be increased markedly with the aid of its corresponding association fascicles, we recommend a high capacity realization of MBDS, Bidirectional Holographic Memory (BHM), so that each training pair is stored uniquely and directly in the connection weights rather than encoded in a correlation matrix. Finally, computer simulations demonstrate the attractiveness of three different realizations of MBDS to verify our results.
DETECTING LOW DIMENSIONAL DYNAMICS IN BIOLOGICAL EXPERIMENTS
Authors: PEI XING , MOSS FRANK
Published: October 2004

We discuss the well-known problems associated with efforts to detect and characterize chaos and other low dimensional dynamics in biological settings. We propose a new method which shows promise for addressing these problems, and we demonstrate its effectiveness in an experiment with the crayfish sensory system. Recordings of action potentials in this system are the data. We begin with a pair of assumptions: that the times of firings of neural action potentials are largely determined by high dimensional random processes or “noise”; and that most biological files are non stationary, so that only relatively short files can be obtained under approximately constant conditions. The method is thus statistical in nature. It is designed to recognize individual “events” in the form of particular sequences of time intervals between action potentials which are the signatures of certain well defined dynamical behaviors. We show that chaos can be distinguished from limit cycles, even when the dynamics is heavily contaminated with noise. Extracellular recordings from the crayfish caudal photoreceptor, obtained while hydrodynamically stimulating the array of hair receptors on the tailfan, are used to illustrate the method.
BRAIN CHAOS AND COMPUTATION
Authors: BABLOYANTZ AGNESSA , LOURENÇO CARLOS
Published: October 2004

A model cortex comprising two interconnected spatiotemporal chaotic networks is considered. The system is able to discriminate between different patterns presented as input, and also detect motion and measure its velocity. Such cognitive processes are only possible if an “attentive” state arises in one of the networks, as a result of the stabilization of a periodic orbit out of the chaotic dynamics.
THE IMPORTANCE OF NOISE FOR SEGMENTATION AND BINDING IN DYNAMICAL NEURAL SYSTEMS
Authors: HORN DAVID , OPHER IRIT
Published: October 2004

Segmentation and binding are cognitive operations that underlie the process of perception. They can be understood as taking place in the temporal domain. In models of nonlinear oscillatory neurons and neuronal cell assemblies, we represent binding by phase locking of assemblies in different networks, and segmentation by phase separation of assemblies in the same network, leading to waveforms of staggered oscillations. Both processes can be facilitated if the inputs to the system, representing simultaneously activated memories, possess noisy components. In the binding problem they serve as a tagging device, driving phase locking between assemblies that belong to different networks but carry the same inputs. In the segmentation problem they allow us to overcome an inherent limitation on segmentation that, otherwise, cannot accommodate more than a few commonly excited memories.
A FUZZY ADAPTIVE LEARNING CONTROL NETWORK WITH ON-LINE STRUCTURE AND PARAMETER LEARNING
Authors: LIN CHENG-JIAN
Published: October 2004

This paper addresses a general connectionist model, called Fuzzy Adaptive Learning Control Network (FALCON), for the realization of a fuzzy logic control system. An on-line supervised structure/parameter learning algorithm is proposed for constructing the FALCON dynamically. It combines the backpropagation learning scheme for parameter learning and the fuzzy ART algorithm for structure learning. The supervised learning algorithm has some important features. First of all, it partitions the input state space and output control space using irregular fuzzy hyperboxes according to the distribution of training data. In many existing fuzzy or neural fuzzy control systems, the input and output spaces are always partitioned into “grids”. As the number of input/output variables increase, the number of partitioned grids will grow combinatorially. To avoid the problem of combinatorial growing of partitioned grids in some complex systems, the proposed learning algorithm partitions the input/output spaces in a flexible way based on the distribution of training data.

Second, the proposed learning algorithm can create and train the FALCON in a highly autonomous way. In its initial form, there is no membership function, fuzzy partition, and fuzzy logic rule. They are created and begin to grow as the first training pattern arrives. The users thus need not give it any a priori knowledge or even any initial information on these. In some real-time applications, exact training data may be expensive or even impossible to obtain.

To solve this problem, a Reinforcement Fuzzy Adaptive Learning Control Network (RFALCON) is further proposed. The proposed RFALCON is constructed by integrating two FALCONs, one FALCON as a critic network, and the other as an action network. By combining temporal difference techniques, stochastic exploration, and a proposed on-line supervised structure/parameter learning algorithm, a reinforcement structure/parameter learning algorithm is proposed, which can construct a RFALCON dynamically through a reward/penalty signal. The ball and beam balancing system is presented to illustrate the performance and applicability of the proposed models and learning algorithms.
LIA: A LOCATION-INDEPENDENT TRANSFORMATION FOR ASOCS ADAPTIVE ALGORITHM 2
Authors: RUDOLPH GEORGE L. , MARTINEZ TONY R.
Published: October 2004

Most Artificial Neural Networks (ANNs) have a fixed topology during learning, and often suffer from a number of short-comings as a result. ANNs that use dynamic topologies have shown the ability to overcome many of these problems. Adaptive Self-Organizing Concurrent Systems (ASOCS) are a class of learning models with inherently dynamic topologies. This paper introduces Location-Independent Transformations (LITs) as a general strategy for implementing learning models that use dynamic topologies efficiently in parallel hardware. An LIT creates a set of location-independent nodes, where each node computes its part of the network output independent of other nodes, using local information. This type of transformation allows efficient support for adding and deleting nodes dynamically during learning. In particular, this paper presents the Location-Independent ASOCS (LIA) model as an LIT for ASOCS Adaptive Algorithm 2. The description of LIA gives formal definitions for LIA algorithms. Because LIA implements basic ASOCS mechanisms, these definitions provide a formal description of basic ASOCS mechanisms in general, in addition to LIA.
OPTIMAL NONLINEAR TRAINING IN THE MULTI-CLASS PROXIMITY PROBLEM
Authors: BOLLÉ D. , JONGEN G. , SHIM G.M.
Published: October 2004

Using a signal-to-noise analysis, the effects of nonlinear modulation of the Hebbian learning rule in the multi-class proximity problem are investigated. Both random classification and classification provided by a Gaussian and a binary teacher are treated. Analytic expressions are derived for the learning and generalization rates around an old and a new prototype. For the proximity problem with binary inputs but Q′-state outputs, it is shown that the optimal modulation is a combination of a hyperbolic tangent and a linear function. As an illustration, numerical results are presented for the two-class and the Q′=3 multi-class problem.
DEFINITION OF NEW 3D INVARIANTS — APPLICATIONS TO PATTERN RECOGNITION PROBLEMS WITH NEURAL NETWORKS
Authors: PRORIOL J.
Published: October 2004

We propose a definition of new 3D invariants. Usual pattern recognition methods use 2D descriptions of 3D objects, we propose a 2D approximation of the defined 3D invariants which can be used with neural networks to solve pattern recognition problems. We describe some methods of using the 2D approximants.
SELF-ORGANIZING MULTI-RESOLUTION GRID FOR MOTION PLANNING AND CONTROL
Authors: FOMIN TIBOR , ROZGONYI TAMÁS , SZEPESVÁRI CSABA , LŐRINCZ ANDRÁS
Published: October 2004

A fully self-organizing neural network approach to low-dimensional control problems is described. We consider the problem of learning to control an object and solving the path planning problem at the same time. Control is based on the path planning model that follows the gradient of the stationary solution of a diffusion process working in the state space. Previous works are extended by introducing a self-organizing multigrid-like discretizing structure to represent the external world. Diffusion is simulated within a recurrent neural network built on this multigrid system. The novelty of the approach is that the diffusion on the multigrid is fast. Moreover, the diffusion process on the multigrid fits well the requirements of the path planning: it accelerates the diffusion in large free space regions while still keeps the resolution in small bottleneck-like labyrinths along the path. Control is achieved in the usual way: associative learning identifies the inverse dynamics of the system in a direct fashion. To this end there are introduced interneurons between neighboring discretizing units that detect the strength of the steady-state diffusion and forward control commands to the control neurons via modifiable connections. This architecture forms the Multigrid Position-and-Direction-to-Action (MPDA) map. The architecture integrates reactive path planning and continuous motion control. It is also shown that the scheme leads to population coding for the actual command vector.
A HIGHER ORDER BAYESIAN NEURAL NETWORK WITH SPIKING UNITS
Authors: LANSNER ANDERS , HOLST ANDERS
Published: October 2004

We treat a Bayesian confidence propagation neural network, primarily in a classifier context. The onelayer version of the network implements a naive Bayesian classifier, which requires the input attributes to be independent. This limitation is overcome by a higher order network. The higher order Bayesian neural network is evaluated on a real world task of diagnosing a telephone exchange computer. By introducing stochastic spiking units, and soft interval coding, it is also possible to handle uncertain as well as continuous valued inputs.
DYNAMICAL EXPLANATION FOR THE EMERGENCE OF POWER LAW IN A STOCK MARKET MODEL
Authors: LEVY MOSHE , SOLOMON SORIN , RAM GIVAT
Published: October 2004

Power laws are found in a wide range of different systems: From sand piles to word occurrence frequencies and to the size distribution of cities. The natural emergence of these power laws in so many different systems, which has been called self-organized criticality, seems rather mysterious and awaits a rigorous explanation. In this letter we study the stationary regime of a previously introduced dynamical microscopic model of the stock market. We find that the wealth distribution among investors spontaneously converges to a power law. We are able to explain this phenomenon by simple general considerations. We suggest that similar considerations may explain self-organized criticality in many other systems. They also explain the Levy distribution.
CONFORMATION OF AMPHIPHILIC MOLECULES GRAFTED OR ADSORBED ON A SOLID SUBSTRATE: MONTE CARLO SIMULATION
Authors: CHOWDHURY DEBASHISH , BERNARDES AMERICO T. , STAUFFER DIETRICH
Published: October 2004

We develop a novel algorithm for Monte Carlo (MC) simulation of two microscopic models for monolayers of amphiphilic molecules; in the first model polar heads of the amphiphiles are grafted on to a solid substrate whereas in the second the polar heads are adsorbed on a solid substrate. In both models the hydrophobic tails are in the air above the substrate. Carrying out extensive MC simulations of these models, we compute several quantities which characterise various aspects of the conformations of the amphiphiles. We compare our results with the corresponding results of earlier MC and molecular dynamics simulations as well as laboratory experiments.
MAGNETIZATION DECAY IN THE DILUTED ISING MODEL
Authors: GRASSBERGER PETER
Published: October 2004

Using Monte Carlo techniques, we study the decay of magnetization in diluted two-dimensional Ising models at and below the critical temperature Tc of the undiluted Ising model, but above the critical temperature of the diluted system. Using damage spreading (or rather damage "healing"), we are able to measure down to much lower final magnetizations (10–9) and to much larger times than previous authors. Nevertheless, we do not yet find the predicted asymptotic behavior in the Griffiths phase T < Tc. But we can at least exclude a stretched exponential decay as found in previous papers, for T < Tc. Finally, we discuss the case T = Tc where a stretched exponential decay can be proven to hold, at least for p < pc. We indeed do see a stretched exponential for p = pc (and T = Tc), but we show that it cannot describe the asymptotic behavior either.
HIGH-SPEED ISING MONTE CARLO AND ELASTIC PARTICLE MOLECULAR DYNAMICS SIMULATIONS
Authors: ITO NOBUYASU
Published: October 2004

The performance of Cray T3D and some other processors was measured with FORTRAN programs for two kinds of statistical mechanical simulation. One is the Monte Carlo simulation of ferromagnetic Ising model on square and cubic lattices with up to 1010 updates per second. The other is the molecular dynamics simulation for two-dimensional elastic disk system.