36 resultados para Cellular automata model


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In this paper, we describe SpeedNet, a GSM network variant which resembles an ad hoc wireless mobile network where base stations keep track of the velocities of mobile users (cars). SpeedNet is intended to track mobile users and their speed passively for both speed policing and control of traffic. The speed of the vehicle is controlled in a speed critical zone by means of an electro-mechanical control system, suitably referred to as VVLS (Vehicular Velocity Limiting System). VVLS is mounted on the vehicle and responds to the command signals generated by the base station. It also determines the next base station to handoff, in order to improve the connection reliability and bandwidth efficiency of the underlying network. Robust Extended Kalman Filter (REKF) is used as a passive velocity estimator of the mobile user with the widely used proportional and integral controller speed control. We demonstrate through simulation and analysis that our prediction algorithm can successfully estimate the mobile user’s velocity with low system complexity as it requires two closest mobile base station measurements and also it is robust against system uncertainties due to the inherent deterministic nature in the mobility model.

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This paper provides mobility estimation and prediction for a variant of GSM network which resembles an adhoc wireless mobile network where base stations and users are both mobile. We propose using Robust Extended Kalman Filter (REKF)as a location heading altitude estimator of mobile user for next node (mobile-base station)in order to improve the connection reliability and bandwidth efficiency of the underlying system. Through analysis we demonstrate that our algorithm can successfully track the mobile users with less system complexity as it requires either one or two closest mobile-basestation measurements. Further, the technique is robust against system uncertainties due to inherent deterministic nature in the mobility model. Through simulation, we show the accuracy and simplicity in implementation of our prediction algorithm.

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In this paper, we describe SpeedNet, a GSM network variant which resembles an ad hoc wireless mobile network where base stations (possibly other vehicles in the network) keep track of the velocities of mobile users (cars). SpeedNet is intended to track mobile users and their speed passively for both speed policing and control of traffic. The speed of the vehicle is controlled in a speed critical zone by means of an electro-mechanical control system, suitably referred to as VVLS (vehicular velocity limiting system). VVLS is mounted in the vehicle and responds to the command signals generated by the base station. It also determines the next basestation to handoff, in order to improve the connection reliability and bandwidth efficiency of the underlying network. Robust extended Kalman filter (REKF) is used as a passive velocity estimator of the mobile user with the widely used proportional and integral controller speed control. We demonstrate through simulation and analysis that our prediction algorithm can successfully estimate the mobile users velocity with low system complexity as it requires two closet mobile-base station measurement and also it is robust against system uncertainties due to the inherent deterministic nature in the mobility model.

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This paper provides location estimation based power control strategy for cellular radio systems via a location based interference management scheme. Our approach considers the carrier-to-interference as dependent on the transmitter and receiver separation distance and therefore an accurate estimation of the precise locations can provide the power critical mobile user to control the transition power accordingly. In this fully
distributed algorithms, we propose using a Robust Extended Kalman Filter (REKF) to derive an estimate of the mobile user’s closest mobile base station from the user’s location, heading and altitude. Our analysis demonstrates that this algorithm can successfully track the mobile users with less system complexity, as it requires measurements from only one or two closest mobile base stations and hence enable the user to transmit at the rate that is sufficient for the interference management. Our power control
algorithms based on this estimation converges to the desired power trajectory. Further, the technique is robust against system uncertainties caused by the inherent deterministic nature of the mobility model. Through simulation, we show the accuracy of our prediction algorithm and the simplicity of its implementation.

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The AMP-activated protein kinase (AMPK) acts as a metabolic master switch regulating several intracellular systems. The effect of AMPK on muscle cellular energy status makes this protein a promising pharmacological target for disease treatment. With increasingly available AMPK regulation data, it is critical to develop an efficient way to analyze the data since this assists in further understanding AMPK pathways. Bayesian networks can play an important role in expressing the dependency and causality in the data. This paper aims to analyse the regulation data using B-Course, a powerful analysis tool to exploit several theoretically elaborate results in the fields of Bayesian and causal modelling, and discover a certain type of multivariate probabilistic dependencies. The identified dependency models are easier to understand in comparison with the traditional frequent patterns.

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This paper provides a procedure to address all three phases of the design for cellular manufacturing namely parts/machines grouping, intra-cell and inter-cell layout designs concurrently. It provides a platform to investigate the impact of the cell formation method on intracell and inter-cell layout designs and vice versa by generating multiple efficient layout designs for different cell partitioning strategies. This approach enables the decision maker to have wider choices with regard to the different number of cells and to assess various criteria such as travelling cost, duplication of machines, space requirement against each alternative. The performance of the model is demonstrated by applying it to an example selected from literature.

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Purpose: The disintegrin metalloprotease ADAM-10 is a multidomain metalloprotease that is potentially significant in tumor progression due to its extracellular matrix-degrading properties. Previously, ADAM-10 mRNA was detected in prostate cancer (PCa) cell lines; however, the presence of ADAM-10 protein and its cellular localization, regulation, and role have yet to be described. We hypothesized that ADAM-10 mRNA and protein may be regulated by growth factors such as 5α-dihydrotestosterone, insulin-like growth factor I, and epidermal growth factor, known modulators of PCa cell growth and invasion.

Experimental Design: ADAM-10 expression was analyzed by in situ hybridization and immunohistochemistry in prostate tissues obtained from 23 patients with prostate disease. ADAM-10 regulation was assessed using quantitative reverse transcription-PCR and Western blot analysis in the PCa cell line LNCaP.

Results: ADAM-10 expression was localized to the secretory cells of prostate glands, with additional basal cell expression in benign glands. ADAM-10 protein was predominantly membrane bound in benign glands but showed marked nuclear localization in cancer glands. By Western blot, the 100-kDa proform and the 60-kDa active form of ADAM-10 were synergistically up-regulated in LNCaP cells treated with insulin-like growth factor I plus 5α-dihydrotestosterone. Epidermal growth factor also up-regulated both ADAM-10 mRNA and protein.

Conclusions: This study describes for the first time the expression, regulation, and cellular localization of ADAM-10 protein in PCa. The regulation and membrane localization of ADAM-10 support our hypothesis that ADAM-10 has a role in extracellular matrix maintenance and cell invasion, although the potential role of nuclear ADAM-10 is not yet known.

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According to the Intergovernmental Panel on Climate Change the buildings sector has the largest mitigation potential for CO2 emissions. Especially in office buildings, where internal heat loads and a relatively high occupant density occur at the same time with solar heat gains, overheating has become a common problem. In Europe the adaptive thermal comfort model according to EN 15251 provides a method to evaluate thermal comfort in naturally ventilated buildings. However, especially in the context of the climate change and the occurrence of heat waves within the last decade, the question arises, how thermal comfort can be maintained without additional cooling, especially in warm climates. In this paper a parametric study for a typical cellular naturally ventilated office room has been conducted, using the building simulation software EnergyPlus. It is based on the Mediterranean climate of Athens, Greece. Adaptive thermal comfort is evaluated according to EN 15251. Variations refer to different building design priorities, and they consider the variability of occupant behaviour and internal heat loads by using an ideal and worst case scenario. The influence of heat waves is considered by comparing measured temperatures for an average and an exceptionally hot year within the last decade. Since the use of building controls for shading affects thermal as well as visual comfort, daylighting and view are evaluated as well. Conclusions are drawn regarding the influence and interaction of building design, occupants and heat waves on comfort and greenhouse gas emissions in naturally ventilated offices, and related optimisation potential.

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The plant pathogen Phytophthora cinnamomi causes devastating disease in natural and agricultural systems worldwide. While some plants can survive, little is known about the underlying mechanisms of resistance. This research used histochemical and genome-wide analysis to identify key cellular and molecular defence mechanisms within the resistant plant Zea mays.

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Nitric oxide is implicated in the pathogenesis of various neuropathologies characterized by oxidative stress. Although nitric oxide has been reported to be involved in the exacerbation of oxidative stress observed in several neuropathologies, existent data fail to provide a holistic description of how nitrergic pathobiology elicits neuronal injury. Here we provide a comprehensive description of mechanisms contributing to nitric oxide induced neuronal injury by global transcriptomic profiling. Microarray analyses were undertaken on RNA from murine primary cortical neurons treated with the nitric oxide generator DETA-NONOate (NOC-18, 0.5 mM) for 8–24 hrs. Biological pathway analysis focused upon 3672 gene probes which demonstrated at least a ±1.5-fold expression in a minimum of one out of three time-points and passed statistical analysis (one-way anova, P < 0.05). Numerous enriched processes potentially determining nitric oxide mediated neuronal injury were identified from the transcriptomic profile: cell death, developmental growth and survival, cell cycle, calcium ion homeostasis, endoplasmic reticulum stress, oxidative stress, mitochondrial homeostasis, ubiquitin-mediated proteolysis, and GSH and nitric oxide metabolism. Our detailed time-course study of nitric oxide induced neuronal injury allowed us to provide the first time a holistic description of the temporal sequence of cellular events contributing to nitrergic injury. These data form a foundation for the development of screening platforms and define targets for intervention in nitric oxide neuropathologies where nitric oxide mediated injury is causative.

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Dynamic variations in channel behavior is considered in transmission power control design for cellular radio systems. It is well known that power control increases system capacity, improves Quality of Service (QoS), and reduces multiuser interference. In this paper, an adaptive power control design based on the identification of the underlying pathloss dynamics of the fading channel is presented. Formulating power control decisions based on the measured received power levels allows modeling the fading channel pathloss dynamics in terms of a Hidden Markov Model (HMM). Applying the online HMM identification algorithm enables accurate estimation of the real pathloss ensuring efficient performance of the suggested power control scheme.

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The understanding of cell manipulation, for example in microinjection, requires an accurate model of the cells. Motivated by this important requirement, a 3D particlebased mechanical model is derived for simulating the deformation of the fish egg membrane and the corresponding cellular forces during microrobotic cell injection. The model is formulated based on the kinematic and dynamic of spring- damper configuration with multi-particle joints considering the visco-elastic fluidic properties. It simulates the indentation force feedback as well as cell visual deformation during microinjection. A preliminary simulation study is conducted with different parameter configurations. The results indicate that the proposed particle-based model is able to provide similar deformation profiles as observed from a real microinjection experiment of the zebrafish embryo published in the literature. As a generic modelling approach is adopted, the proposed model also has the potential in applications with different types of manipulation such as micropipette cell aspiration.

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The traditional Cellular Automation-based Physarum model reveals the process of amoebic self-organized movement and self-adaptive network formation based on bubble transportation. However, a bubble in the traditional Physarum model often transports within active zones and has little change to explore newareas.And the efficiency of evolution is very low because there is only one bubble in the system. This paper proposes an improved model, named as Improved Bubble Transportation Model (IBTM). Our model adds a time label for each grid of environment in order to drive bubbles to explore newareas, and deploysmultiple bubbles in order to improve the evolving efficiency of Physarum network.We first evaluate the morphological characteristics of IBTM with the real Physarum, and then compare the evolving time between the traditional model and IBTM. The results show that IBTM can obtain higher efficiency and stability in the process of forming an adaptive network.

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The resurrection grass Sporobolus stapfianus Gandoger can rapidly recover from extended periods of time in the desiccated state (water potential equilibrated to 2% relative humidity) (Gaff and Ellis, Bothalia 11:305–308 1974; Gaff and Loveys, Transactions of the Malaysian Society of Plant Physiology 3:286–287 1993). Physiological studies have been conducted in S. stapfianus to investigate the responses utilised by these desiccation-tolerant plants to cope with severe water-deficit. In a number of instances, more recent gene expression analyses in S. stapfianus have shed light on the molecular and cellular mechanisms mediating these responses. S. stapfianus is a versatile research tool for investigating desiccation-tolerance in vegetative grass tissue, with several useful characteristics for differentiating desiccation-tolerance adaptive genes from the many dehydration-responsive genes present in plants. A number of genes orthologous to those isolated from dehydrating S. stapfianus have been successfully used to enhance drought and salt tolerance in model plants as well as important crop species. In addition to the ability to desiccate and rehydrate successfully, the survival of resurrection plants in regions experiencing short sporadic rainfall events may depend substantially on the ability to tightly down-regulate cell division and cell wall loosening activities with decreasing water availability and then grow rapidly after rainfall while water is plentiful. Hence, an analysis of gene transcripts present in the desiccated tissue of resurrection plants may reveal important growth-related genes. Recent findings support the proposition that, as well as being a versatile model for devising strategies for protecting plants from water-loss, resurrection plants may be a very useful tool for pinpointing genes to target for enhancing growth rate and biomass production.