5,417 research outputs found

    Modulation of Natural Killer Cell Cytotoxicity in Human Cytomegalovirus Infection: The Role of Endogenous Class I Major Histocompatibility Complex and a Viral Class I Homolog

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    Natural killer (NK) cells have been implicated in early immune responses against certain viruses, including cytomegalovirus (CMV). CMV causes downregulation of class I major histocompatibility complex (MHC) expression in infected cells; however, it has been proposed that a class I MHC homolog encoded by CMV, UL18, may act as a surrogate ligand to prevent NK cell lysis of CMV-infected cells. In this study, we examined the role of UL18 in NK cell recognition and lysis using fibroblasts infected with either wild-type or UL18 knockout CMV virus, and by using cell lines transfected with the UL18 gene. In both systems, the expression of UL18 resulted in the enhanced killing of target cells. We also show that the enhanced killing is due to both UL18-dependent and -independent mechanisms, and that the killer cell inhibitory receptors (KIRs) and CD94/NKG2A inhibitory receptors for MHC class I do not play a role in affecting susceptibility of CMV-infected fibroblasts to NK cell–mediated cytotoxicity

    Discrete-Time Recurrent Neural Network and Its Application to Compression of Infra-Red Spectrum

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    We study the discrete-time recurrent neural network that derived from the Leaky-integrator model and its application to compression of infra-red spec- trum. Our results show that the discrete-time Leaky-integrator recurrent neural network (RNN) model can be used to approximate the continuous-time model and inherit its dynamical characters if a proper step size is chosen. Moreover, the discrete-time Leaky-integrator RNN model is absolutely stable. By developing the double discrete integral method and employing the state space search algorithm for the discrete-time recurrent neural network model, we demonstrate with quality spectra regenerated from the compressed data how to compress the infra-red spectrum effectively. The information we stored is the parameters of the system and its initial states. The method offers an ideal setting to carry out the recurrent neural network approach to chaotic cases of data compression

    Discrete-Time Recurrent Neural Network and Its Application to Compression of Infra-Red Spectrum

    Get PDF
    We study the discrete-time recurrent neural network that derived from the Leaky-integrator model and its application to compression of infra-red spec- trum. Our results show that the discrete-time Leaky-integrator recurrent neural network (RNN) model can be used to approximate the continuous-time model and inherit its dynamical characters if a proper step size is chosen. Moreover, the discrete-time Leaky-integrator RNN model is absolutely stable. By developing the double discrete integral method and employing the state space search algorithm for the discrete-time recurrent neural network model, we demonstrate with quality spectra regenerated from the compressed data how to compress the infra-red spectrum effectively. The information we stored is the parameters of the system and its initial states. The method offers an ideal setting to carry out the recurrent neural network approach to chaotic cases of data compression

    A Sequential Mixed Method Study of Employee Job Satisfaction in Upscale Restaurants, Malaysia

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    The study determines the main factors affecting job satisfaction in upscale restaurants and their degree of comparative influence. The research initially involves qualitative data analysis of 20 interviews with restaurant employees representing five upscale restaurants in Kuala Lumpur (KL), followed by structural equation modeling of data retrieved from 368 questionnaires from 16 KL restaurants. The impact variance of four main determinants of job satisfaction are revealed, where the “working environment” has the highest impact, followed by “payment and compensation,” “promotion”, and finally, “workplace fairness”. Crucially, “workplace relationships” have a moderating effect on the relationship between the “work environment” and job satisfaction, implicating industry-applied recommendations to strengthen job satisfaction levels

    Utilizing open source software running in inexpensive high performance computing system for cfd applications

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    The high cost of conducting research is a significant issue for the successfulness of any research project. For research activities involving flow simulation, the licensing fee for the numerical software and the cost to acquire powerful machine are the main factors contributing to the high cost. This paper reports our experiences in setting up a cost effective way of doing computational fluid dynamics (CFD). The actions involve two areas, i.e., software and hardware. For the software, open source softwares are utilized, particularly the OpenFOAM(r) as the CFD package. For the hardware, a parallel computer made from a cluster of inexpensive desktop computer is constructed. This architecture is found able to meet our requirement in investigating various flow problems that include aeroacoustics, vibration and wind engineering for ventilation

    Sub-Nyquist Field Trial Using Time Frequency Packed DP-QPSK Super-Channel Within Fixed ITU-T Grid

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    Sub-Nyquist time frequency packing technique was demonstrated for the first time in a super channel field trial transmission over long-haul distances. The technique allows a limited spectral occupancy even with low order modulation formats. The transmission was successfully performed on a deployed Australian link between Sydney and Melbourne which included 995 km of uncompensated SMF with coexistent traffic. 40 and 100 Gb/s co-propagating channels were transmitted together with the super-channel in a 50 GHz ITU-T grid without additional penalty. The super-channel consisted of eight sub-channels with low-level modulation format, i.e. DP-QPSK, guaranteeing better OSNR robustness and reduced complexity with respect to higher order formats. At the receiver side, coherent detection was used together with iterative maximum-a-posteriori (MAP) detection and decoding. A 975 Gb/s DP-QPSK super-channel was successfully transmitted between Sydney and Melbourne within four 50GHz WSS channels (200 GHz). A maximum potential SE of 5.58 bit/s/Hz was achieved with an OSNR=15.8 dB, comparable to the OSNR of the installed 100 Gb/s channels. The system reliability was proven through long term measurements. In addition, by closing the link in a loop back configuration, a potential SE*d product of 9254 bit/s/Hz*km was achieved

    Disruption of a Yeast ADE6 Gene Homolog in Ustilago maydis

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    A putative homolog of the Sacharromyces cereviseae ADE6 and Escherichia coli purL genes is identified near a multigenic complex, which contains two genes, sid1 and sid2, involved in a siderophore biosynthetic pathway inUstilago maydis. The putative ADE6 homolog was mutated by targeted gene disruption. The resulting mutant strains demonstrated a requirement for exogenous adenine, indicating that the U. maydis ade6 homolog is required for purine biosynthesis

    Extending Feynman's Formalisms for Modelling Human Joint Action Coordination

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    The recently developed Life-Space-Foam approach to goal-directed human action deals with individual actor dynamics. This paper applies the model to characterize the dynamics of co-action by two or more actors. This dynamics is modelled by: (i) a two-term joint action (including cognitive/motivatonal potential and kinetic energy), and (ii) its associated adaptive path integral, representing an infinite--dimensional neural network. Its feedback adaptation loop has been derived from Bernstein's concepts of sensory corrections loop in human motor control and Brooks' subsumption architectures in robotics. Potential applications of the proposed model in human--robot interaction research are discussed. Keywords: Psycho--physics, human joint action, path integralsComment: 6 pages, Late

    Seasonal and spatial dynamics of the primary vector of plasmodium knowlesi within a major transmission focus in Sabah, Malaysia

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    Background The simian malaria parasite Plasmodium knowlesi is emerging as a public health problem in Southeast Asia, particularly in Malaysian Borneo where it now accounts for the greatest burden of malaria cases and deaths. Control is hindered by limited understanding of the ecology of potential vector species. Methodology/Principal Findings We conducted a one year longitudinal study of P. knowlesi vectors in three sites within an endemic area of Sabah, Malaysia. All mosquitoes were captured using human landing catch. Anopheles mosquitoes were dissected to determine, oocyst, sporozoites and parous rate. Anopheles balabacensis is confirmed as the primary vector of. P. knowlesi (using nested PCR) in Sabah for the first time. Vector densities were significantly higher and more seasonally variable in the village than forest or small scale farming site. However An. balabacensis survival and P. knowlesi infection rates were highest in forest and small scale farm sites. Anopheles balabacensis mostly bites humans outdoors in the early evening between 1800 to 2000hrs. Conclusions/Significance This study indicates transmission is unlikely to be prevented by bednets. This combined with its high vectorial capacity poses a threat to malaria elimination programmes within the region. Author Summary The first natural infection of Plasmodium knowlesi was reported 40 years ago. At that time it was perceived that the infection would not affect humans. However, now P. knowlesi is the predominant malaria species (38% of the cases) infecting people in Malaysia and is a notable obstacle to malaria elimination in the country. Plasmodium knowlesi has also been reported from all countries in Southeast Asia with the exception of Lao PDR and Timor Leste. In Sabah, Malaysian Borneo cases of human P. knowlesi are increasing. Thus, a comprehensive understanding of the bionomics of the vectors is required so as to enable proper control strategies. Here, we conducted a longitudinal study in Kudat district, Sabah, to determine and characterize the vectors of P. knowlesi within this transmission foci. Anopheles balabacensis was the predominant mosquito in all study sites and is confirmed as vector for P. knowlesi and other simian malaria parasites. The peak biting time was in the early part of the evening between1800 to 2000. Thus, breaking the chain of transmission is an extremely challenging task for the malaria elimination programme

    Multimodal hyperscanning reveals that synchrony of body and mind are distinct in mother-child dyads

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    Hyperscanning studies have begun to unravel the brain mechanisms underlying social interaction, indicating a functional role for interpersonal neural synchronization (INS), yet the mechanisms that drive INS are poorly understood. The current study, thus, addresses whether INS is functionally-distinct from synchrony in other systems – specifically the autonomic nervous system and motor behavior. To test this, we used concurrent functional near-infrared spectroscopy - electrocardiography recordings, while N = 34 mother-child and stranger-child dyads engaged in cooperative and competitive tasks. Only in the neural domain was a higher synchrony for mother-child compared to stranger-child dyads observed. Further, autonomic nervous system and neural synchrony were positively related during competition but not during cooperation. These results suggest that synchrony in different behavioral and biological systems may reflect distinct processes. Furthermore, they show that increased mother-child INS is unlikely to be explained solely by shared arousal and behavioral similarities, supporting recent theories that postulate that INS is higher in close relationships
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