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Sample records for accurate cellular networks

  1. MSAT and cellular hybrid networking

    NASA Technical Reports Server (NTRS)

    Baranowsky, Patrick W., II

    1993-01-01

    Westinghouse Electric Corporation is developing both the Communications Ground Segment and the Series 1000 Mobile Phone for American Mobile Satellite Corporation's (AMSC's) Mobile Satellite (MSAT) system. The success of the voice services portion of this system depends, to some extent, upon the interoperability of the cellular network and the satellite communication circuit switched communication channels. This paper will describe the set of user-selectable cellular interoperable modes (cellular first/satellite second, etc.) provided by the Mobile Phone and described how they are implemented with the ground segment. Topics including roaming registration and cellular-to-satellite 'seamless' call handoff will be discussed, along with the relevant Interim Standard IS-41 Revision B Cellular Radiotelecommunications Intersystem Operations and IOS-553 Mobile Station - Land Station Compatibility Specification.

  2. Retinal Connectomics: Towards Complete, Accurate Networks

    PubMed Central

    Marc, Robert E.; Jones, Bryan W.; Watt, Carl B.; Anderson, James R.; Sigulinsky, Crystal; Lauritzen, Scott

    2013-01-01

    Connectomics is a strategy for mapping complex neural networks based on high-speed automated electron optical imaging, computational assembly of neural data volumes, web-based navigational tools to explore 1012–1015 byte (terabyte to petabyte) image volumes, and annotation and markup tools to convert images into rich networks with cellular metadata. These collections of network data and associated metadata, analyzed using tools from graph theory and classification theory, can be merged with classical systems theory, giving a more completely parameterized view of how biologic information processing systems are implemented in retina and brain. Networks have two separable features: topology and connection attributes. The first findings from connectomics strongly validate the idea that the topologies complete retinal networks are far more complex than the simple schematics that emerged from classical anatomy. In particular, connectomics has permitted an aggressive refactoring of the retinal inner plexiform layer, demonstrating that network function cannot be simply inferred from stratification; exposing the complex geometric rules for inserting different cells into a shared network; revealing unexpected bidirectional signaling pathways between mammalian rod and cone systems; documenting selective feedforward systems, novel candidate signaling architectures, new coupling motifs, and the highly complex architecture of the mammalian AII amacrine cell. This is but the beginning, as the underlying principles of connectomics are readily transferrable to non-neural cell complexes and provide new contexts for assessing intercellular communication. PMID:24016532

  3. Micromechanics of cellularized biopolymer networks

    PubMed Central

    Jones, Christopher A. R.; Cibula, Matthew; Feng, Jingchen; Krnacik, Emma A.; McIntyre, David H.; Levine, Herbert; Sun, Bo

    2015-01-01

    Collagen gels are widely used in experiments on cell mechanics because they mimic the extracellular matrix in physiological conditions. Collagen gels are often characterized by their bulk rheology; however, variations in the collagen fiber microstructure and cell adhesion forces cause the mechanical properties to be inhomogeneous at the cellular scale. We study the mechanics of type I collagen on the scale of tens to hundreds of microns by using holographic optical tweezers to apply pN forces to microparticles embedded in the collagen fiber network. We find that in response to optical forces, particle displacements are inhomogeneous, anisotropic, and asymmetric. Gels prepared at 21 °C and 37 °C show qualitative difference in their micromechanical characteristics. We also demonstrate that contracting cells remodel the micromechanics of their surrounding extracellular matrix in a strain- and distance-dependent manner. To further understand the micromechanics of cellularized extracellular matrix, we have constructed a computational model which reproduces the main experiment findings. PMID:26324923

  4. Complexity, dynamic cellular network, and tumorigenesis.

    PubMed

    Waliszewski, P

    1997-01-01

    A holistic approach to tumorigenesis is proposed. The main element of the model is the existence of dynamic cellular network. This network comprises a molecular and an energetistic structure of a cell connected through the multidirectional flow of information. The interactions within dynamic cellular network are complex, stochastic, nonlinear, and also involve quantum effects. From this non-reductionist perspective, neither tumorigenesis can be limited to the genetic aspect, nor the initial event must be of molecular nature, nor mutations and epigenetic factors are mutually exclusive, nor a link between cause and effect can be established. Due to complexity, an unstable stationary state of dynamic cellular network rather than a group of unrelated genes determines the phenotype of normal and transformed cells. This implies relativity of tumor suppressor genes and oncogenes. A bifurcation point is defined as an unstable state of dynamic cellular network leading to the other phenotype-stationary state. In particular, the bifurcation point may be determined by a change of expression of a single gene. Then, the gene is called bifurcation point gene. The unstable stationary state facilitates the chaotic dynamics. This may result in a fractal dimension of both normal and tumor tissues. The co-existence of chaotic dynamics and complexity is the essence of cellular processes and shapes differentiation, morphogenesis, and tumorigenesis. In consequence, tumorigenesis is a complex, unpredictable process driven by the interplay between self-organisation and selection.

  5. Inferring cellular networks using probabilistic graphical models.

    PubMed

    Friedman, Nir

    2004-02-06

    High-throughput genome-wide molecular assays, which probe cellular networks from different perspectives, have become central to molecular biology. Probabilistic graphical models are useful for extracting meaningful biological insights from the resulting data sets. These models provide a concise representation of complex cellular networks by composing simpler submodels. Procedures based on well-understood principles for inferring such models from data facilitate a model-based methodology for analysis and discovery. This methodology and its capabilities are illustrated by several recent applications to gene expression data.

  6. Inferring cellular networks – a review

    PubMed Central

    Markowetz, Florian; Spang, Rainer

    2007-01-01

    In this review we give an overview of computational and statistical methods to reconstruct cellular networks. Although this area of research is vast and fast developing, we show that most currently used methods can be organized by a few key concepts. The first part of the review deals with conditional independence models including Gaussian graphical models and Bayesian networks. The second part discusses probabilistic and graph-based methods for data from experimental interventions and perturbations. PMID:17903286

  7. Accurate multiple network alignment through context-sensitive random walk

    PubMed Central

    2015-01-01

    Background Comparative network analysis can provide an effective means of analyzing large-scale biological networks and gaining novel insights into their structure and organization. Global network alignment aims to predict the best overall mapping between a given set of biological networks, thereby identifying important similarities as well as differences among the networks. It has been shown that network alignment methods can be used to detect pathways or network modules that are conserved across different networks. Until now, a number of network alignment algorithms have been proposed based on different formulations and approaches, many of them focusing on pairwise alignment. Results In this work, we propose a novel multiple network alignment algorithm based on a context-sensitive random walk model. The random walker employed in the proposed algorithm switches between two different modes, namely, an individual walk on a single network and a simultaneous walk on two networks. The switching decision is made in a context-sensitive manner by examining the current neighborhood, which is effective for quantitatively estimating the degree of correspondence between nodes that belong to different networks, in a manner that sensibly integrates node similarity and topological similarity. The resulting node correspondence scores are then used to predict the maximum expected accuracy (MEA) alignment of the given networks. Conclusions Performance evaluation based on synthetic networks as well as real protein-protein interaction networks shows that the proposed algorithm can construct more accurate multiple network alignments compared to other leading methods. PMID:25707987

  8. Network motifs modulate druggability of cellular targets

    PubMed Central

    Wu, Fan; Ma, Cong; Tan, Cheemeng

    2016-01-01

    Druggability refers to the capacity of a cellular target to be modulated by a small-molecule drug. To date, druggability is mainly studied by focusing on direct binding interactions between a drug and its target. However, druggability is impacted by cellular networks connected to a drug target. Here, we use computational approaches to reveal basic principles of network motifs that modulate druggability. Through quantitative analysis, we find that inhibiting self-positive feedback loop is a more robust and effective treatment strategy than inhibiting other regulations, and adding direct regulations to a drug-target generally reduces its druggability. The findings are explained through analytical solution of the motifs. Furthermore, we find that a consensus topology of highly druggable motifs consists of a negative feedback loop without any positive feedback loops, and consensus motifs with low druggability have multiple positive direct regulations and positive feedback loops. Based on the discovered principles, we predict potential genetic targets in Escherichia coli that have either high or low druggability based on their network context. Our work establishes the foundation toward identifying and predicting druggable targets based on their network topology. PMID:27824147

  9. Optimal Prediction by Cellular Signaling Networks

    NASA Astrophysics Data System (ADS)

    Becker, Nils B.; Mugler, Andrew; ten Wolde, Pieter Rein

    2015-12-01

    Living cells can enhance their fitness by anticipating environmental change. We study how accurately linear signaling networks in cells can predict future signals. We find that maximal predictive power results from a combination of input-noise suppression, linear extrapolation, and selective readout of correlated past signal values. Single-layer networks generate exponential response kernels, which suffice to predict Markovian signals optimally. Multilayer networks allow oscillatory kernels that can optimally predict non-Markovian signals. At low noise, these kernels exploit the signal derivative for extrapolation, while at high noise, they capitalize on signal values in the past that are strongly correlated with the future signal. We show how the common motifs of negative feedback and incoherent feed-forward can implement these optimal response functions. Simulations reveal that E. coli can reliably predict concentration changes for chemotaxis, and that the integration time of its response kernel arises from a trade-off between rapid response and noise suppression.

  10. Heterogeneous Force Chains in Cellularized Biopolymer Network

    NASA Astrophysics Data System (ADS)

    Liang, Long; Jones, Christopher Allen Rucksack; Sun, Bo; Jiao, Yang

    Biopolymer Networks play an important role in coordinating and regulating collective cellular dynamics via a number of signaling pathways. Here, we investigate the mechanical response of a model biopolymer network due to the active contraction of embedded cells. Specifically, a graph (bond-node) model derived from confocal microscopy data is used to represent the network microstructure, and cell contraction is modeled by applying correlated displacements at specific nodes, representing the focal adhesion sites. A force-based stochastic relaxation method is employed to obtain force-balanced network under cell contraction. We find that the majority of the forces are carried by a small number of heterogeneous force chains emerged from the contracting cells. The force chains consist of fiber segments that either possess a high degree of alignment before cell contraction or are aligned due to the reorientation induced by cell contraction. Large fluctuations of the forces along different force chains are observed. Importantly, the decay of the forces along the force chains is significantly slower than the decay of radially averaged forces in the system, suggesting that the fibreous nature of biopolymer network structure could support long-range mechanical signaling between cells.

  11. Optimal flux patterns in cellular metabolic networks

    SciTech Connect

    Almaas, E

    2007-01-20

    The availability of whole-cell level metabolic networks of high quality has made it possible to develop a predictive understanding of bacterial metabolism. Using the optimization framework of flux balance analysis, I investigate metabolic response and activity patterns to variations in the availability of nutrient and chemical factors such as oxygen and ammonia by simulating 30,000 random cellular environments. The distribution of reaction fluxes is heavy-tailed for the bacteria H. pylori and E. coli, and the eukaryote S. cerevisiae. While the majority of flux balance investigations have relied on implementations of the simplex method, it is necessary to use interior-point optimization algorithms to adequately characterize the full range of activity patterns on metabolic networks. The interior-point activity pattern is bimodal for E. coli and S. cerevisiae, suggesting that most metabolic reaction are either in frequent use or are rarely active. The trimodal activity pattern of H. pylori indicates that a group of its metabolic reactions (20%) are active in approximately half of the simulated environments. Constructing the high-flux backbone of the network for every environment, there is a clear trend that the more frequently a reaction is active, the more likely it is a part of the backbone. Finally, I briefly discuss the predicted activity patterns of the central-carbon metabolic pathways for the sample of random environments.

  12. Optimal flux patterns in cellular metabolic networks

    NASA Astrophysics Data System (ADS)

    Almaas, Eivind

    2007-06-01

    The availability of whole-cell-level metabolic networks of high quality has made it possible to develop a predictive understanding of bacterial metabolism. Using the optimization framework of flux balance analysis, I investigate the metabolic response and activity patterns to variations in the availability of nutrient and chemical factors such as oxygen and ammonia by simulating 30 000 random cellular environments. The distribution of reaction fluxes is heavy tailed for the bacteria H. pylori and E. coli, and the eukaryote S. cerevisiae. While the majority of flux balance investigations has relied on implementations of the simplex method, it is necessary to use interior-point optimization algorithms to adequately characterize the full range of activity patterns on metabolic networks. The interior-point activity pattern is bimodal for E. coli and S. cerevisiae, suggesting that most metabolic reactions are either in frequent use or are rarely active. The trimodal activity pattern of H. pylori indicates that a group of its metabolic reactions (20%) are active in approximately half of the simulated environments. Constructing the high-flux backbone of the network for every environment, there is a clear trend that the more frequently a reaction is active, the more likely it is a part of the backbone. Finally, I briefly discuss the predicted activity patterns of the central carbon metabolic pathways for the sample of random environments.

  13. A Wireless Communications Laboratory on Cellular Network Planning

    ERIC Educational Resources Information Center

    Dawy, Z.; Husseini, A.; Yaacoub, E.; Al-Kanj, L.

    2010-01-01

    The field of radio network planning and optimization (RNPO) is central for wireless cellular network design, deployment, and enhancement. Wireless cellular operators invest huge sums of capital on deploying, launching, and maintaining their networks in order to ensure competitive performance and high user satisfaction. This work presents a lab…

  14. Country-wide rainfall maps from cellular communication networks

    PubMed Central

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2013-01-01

    Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal’s attenuation between transmitter and receiver. Here, we show how one such a network can be used to retrieve the space–time dynamics of rainfall for an entire country (The Netherlands, ∼35,500 km2), based on an unprecedented number of links (∼2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrates the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent. PMID:23382210

  15. Supporting performance and configuration management of GTE cellular networks

    SciTech Connect

    Tan, Ming; Lafond, C.; Jakobson, G.; Young, G.

    1996-12-31

    GTE Laboratories, in cooperation with GTE Mobilnet, has developed and deployed PERFFEX (PERFormance Expert), an intelligent system for performance and configuration management of cellular networks. PERFEX assists cellular network performance and radio engineers in the analysis of large volumes of cellular network performance and configuration data. It helps them locate and determine the probable causes of performance problems, and provides intelligent suggestions about how to correct them. The system combines an expert cellular network performance tuning capability with a map-based graphical user interface, data visualization programs, and a set of special cellular engineering tools. PERFEX is in daily use at more than 25 GTE Mobile Switching Centers. Since the first deployment of the system in late 1993, PERFEX has become a major GTE cellular network performance optimization tool.

  16. Countrywide rainfall maps from a commercial cellular telecommunication network

    NASA Astrophysics Data System (ADS)

    Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2012-12-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information. Many countries do not have continuously operating weather radars, and have no or few rain gauges. A new development is rainfall estimation from microwave links of commercial cellular telecommunication networks. Such networks cover large parts of the land surface of the earth and have a high density, especially in urban areas. The estimation of rainfall using commercial microwave links could therefore become a valuable source of information. The data produced by microwave links is essentially a by-product of the communication between mobile telephones. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. A dataset from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (1500) covering the land surface of the Netherlands (35500 km2). This dataset consists of 24 days with substantial rainfall in June - September 2011. A rainfall retrieval algorithm is presented to derive rainfall intensities from the microwave link data, which have a temporal resolution of 15 min. Rainfall maps (1 km spatial resolution) are generated from these rainfall intensities using Kriging. This algorithm is suited for real-time application, and is calibrated on a subset (12 days) of the dataset. The other 12 days in the dataset are used to validate the algorithm. Both calibration and validation are done using gauge-adjusted radar data

  17. Heterogeneous force network in 3D cellularized collagen networks.

    PubMed

    Liang, Long; Jones, Christopher; Chen, Shaohua; Sun, Bo; Jiao, Yang

    2016-10-25

    Collagen networks play an important role in coordinating and regulating collective cellular dynamics via a number of signaling pathways. Here, we investigate the transmission of forces generated by contractile cells in 3D collagen-I networks. Specifically, the graph (bond-node) representations of collagen networks with collagen concentrations of 1, 2 and 4 mg ml(-1) are derived from confocal microscopy data and used to model the network microstructure. Cell contraction is modeled by applying correlated displacements at specific nodes of the network, representing the focal adhesion sites. A nonlinear elastic model is employed to characterize the mechanical behavior of individual fiber bundles including strain hardening during stretching and buckling under compression. A force-based relaxation method is employed to obtain equilibrium network configurations under cell contraction. We find that for all collagen concentrations, the majority of the forces are carried by a small number of heterogeneous force chains emitted from the contracting cells, which is qualitatively consistent with our experimental observations. The force chains consist of fiber segments that either possess a high degree of alignment before cell contraction or are aligned due to fiber reorientation induced by cell contraction. The decay of the forces along the force chains is significantly slower than the decay of radially averaged forces in the system, suggesting that the fibreous nature of biopolymer network structure can support long-range force transmission. The force chains emerge even at very small cell contractions, and the number of force chains increases with increasing cell contraction. At large cell contractions, the fibers close to the cell surface are in the nonlinear regime, and the nonlinear region is localized in a small neighborhood of the cell. In addition, the number of force chains increases with increasing collagen concentration, due to the larger number of focal adhesion sites

  18. Heterogeneous force network in 3D cellularized collagen networks

    NASA Astrophysics Data System (ADS)

    Liang, Long; Jones, Christopher; Chen, Shaohua; Sun, Bo; Jiao, Yang

    2016-12-01

    Collagen networks play an important role in coordinating and regulating collective cellular dynamics via a number of signaling pathways. Here, we investigate the transmission of forces generated by contractile cells in 3D collagen-I networks. Specifically, the graph (bond-node) representations of collagen networks with collagen concentrations of 1, 2 and 4 mg ml-1 are derived from confocal microscopy data and used to model the network microstructure. Cell contraction is modeled by applying correlated displacements at specific nodes of the network, representing the focal adhesion sites. A nonlinear elastic model is employed to characterize the mechanical behavior of individual fiber bundles including strain hardening during stretching and buckling under compression. A force-based relaxation method is employed to obtain equilibrium network configurations under cell contraction. We find that for all collagen concentrations, the majority of the forces are carried by a small number of heterogeneous force chains emitted from the contracting cells, which is qualitatively consistent with our experimental observations. The force chains consist of fiber segments that either possess a high degree of alignment before cell contraction or are aligned due to fiber reorientation induced by cell contraction. The decay of the forces along the force chains is significantly slower than the decay of radially averaged forces in the system, suggesting that the fibreous nature of biopolymer network structure can support long-range force transmission. The force chains emerge even at very small cell contractions, and the number of force chains increases with increasing cell contraction. At large cell contractions, the fibers close to the cell surface are in the nonlinear regime, and the nonlinear region is localized in a small neighborhood of the cell. In addition, the number of force chains increases with increasing collagen concentration, due to the larger number of focal adhesion sites

  19. Sources of Uncertainty in Rainfall Maps from Cellular Communication Networks

    NASA Astrophysics Data System (ADS)

    Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2015-04-01

    Accurate measurements of rainfall are important in many hydrological applications, for instance, flash-flood early-warning systems, hydraulic structures design, agriculture, weather forecasting, and climate modelling. Rainfall intensities can be retrieved from (commercial) microwave link networks. Whenever possible, link networks measure and store the decrease in power of the electromagnetic signal at regular intervals. The decrease in power is largely due to the attenuation by raindrops along the link paths. Such an alternative technique fulfills the continuous strive for measurements of rainfall in time and space at higher resolutions, especially in places where traditional rain gauge networks are scarce or poorly maintained. Rainfall maps from microwave link networks have recently been introduced at country-wide scales. Despite their potential in rainfall estimation at high spatiotemporal resolutions, the uncertainties present in rainfall maps from link networks are not yet fully comprehended. The aim of this work is to identify and quantify the sources of uncertainty present in interpolated rainfall maps from link rainfall depths. In order to disentangle these sources of uncertainty, we classified them into two categories: (1) those associated with the individual microwave link measurements, i.e., the physics involved in the measurements such as wet antenna attenuation, sampling interval of measurements, wet/dry period classification, drop size distribution (DSD), and multi-path propagation; (2) those associated with mapping, i.e., the combined effect of the interpolation methodology, the spatial density of the network, and the availability of link measurements. We computed ~ 3500 rainfall maps from real and simulated link rainfall depths for 12 days for the land surface of The Netherlands. These rainfall maps were compared against quality-controlled gauge-adjusted radar rainfall fields (assumed to be the ground truth). Thus, we were able to not only identify

  20. Accurate and efficient maximal ball algorithm for pore network extraction

    NASA Astrophysics Data System (ADS)

    Arand, Frederick; Hesser, Jürgen

    2017-04-01

    The maximal ball (MB) algorithm is a well established method for the morphological analysis of porous media. It extracts a network of pores and throats from volumetric data. This paper describes structural modifications to the algorithm, while the basic concepts are preserved. Substantial improvements to accuracy and efficiency are achieved as follows: First, all calculations are performed on a subvoxel accurate distance field, and no approximations to discretize balls are made. Second, data structures are simplified to keep memory usage low and improve algorithmic speed. Third, small and reasonable adjustments increase speed significantly. In volumes with high porosity, memory usage is improved compared to classic MB algorithms. Furthermore, processing is accelerated more than three times. Finally, the modified MB algorithm is verified by extracting several network properties from reference as well as real data sets. Runtimes are measured and compared to literature.

  1. Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning.

    PubMed

    Sohn, Insoo; Liu, Huaping; Ansari, Nirwan

    2015-01-01

    An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction.

  2. Extracting insight from noisy cellular networks.

    PubMed

    Landry, Christian R; Levy, Emmanuel D; Abd Rabbo, Diala; Tarassov, Kirill; Michnick, Stephen W

    2013-11-21

    Network biologists attempt to extract meaningful relationships among genes or their products from very noisy data. We argue that what we categorize as noisy data may sometimes reflect noisy biology and therefore may shield a hidden meaning about how networks evolve and how matter is organized in the cell. We present practical solutions, based on existing evolutionary and biophysical concepts, through which our understanding of cell biology can be enormously enriched.

  3. Energy efficiency analysis of relay-assisted cellular networks

    NASA Astrophysics Data System (ADS)

    Yu, Huan; Li, Yunzhou; Kountouris, Marios; Xu, Xibin; Wang, Jing

    2014-12-01

    To meet the demand for higher throughput, improved coverage and enhanced reliability, future wireless cellular networks face significant technical challenges. One promising solution is to place relay stations between transmitters and receivers in the cellular network. Meanwhile, as energy consumption reduction has been an important concern for the wireless industry, energy-efficient communications is of prime interest for future networks. In this paper, we study whether and how relays can improve the energy efficiency of cellular networks. Specifically, the energy efficiency of relay-assisted cellular networks is analyzed using tools of stochastic geometry. We first derive the coverage probability for the macro base station (MBS) to user (UE), the MBS to relay station (RS), and the RS to UE links, and then we model the power consumption at the MBS and RS. Based on the analytical model and expressions, the energy efficiency of relay-assisted cellular networks is then evaluated and is shown to be strictly quasi-concave on the transmit power for MBS to UE link or the RS to UE link. Numerical results show that the energy efficiency first improves while it hits a ceiling as the MBS density increases.

  4. A versatile assay for the accurate, time-resolved determination of cellular viability.

    PubMed

    Amano, Toyoki; Hirasawa, Ken ichi; O'Donohue, Michael J; Pernolle, Jean Claude; Shioi, Yuzo

    2003-03-01

    A convenient and versatile method for the accurate, time-resolved determination of cellular viability has been developed. The conventional viability indicator fluorescein diacetate (FDA), which is converted to the fluorescent compound fluorescein in living cells, was employed as a viability probe. Fluorescence emission from cells was measured using a spectrofluorimeter equipped with a magnetic stirrer. Using this assay cell suspensions exhibiting densities in the range 0.5 x 10(5) to 2.0 x 10(5) cells displayed a linear response when FDA concentrations less than 12 micro M were employed. To calibrate the method, viability standards were elaborated using different proportions of living and dead cells, and a correlation coefficient for the viability of tobacco BY-2 suspensions was calculated as 0.998. This viability assay was also found to be applicable to Chlamydomonas reinhardtii and Arabidopsis thaliana cultured cells. Using this cell viability assay, kinetic analyses of cell death could be performed. Using the proteinaceous elicitor from Phytophthora cryptogea, cryptogein, to induce cell death in tobacco cell suspensions, values for the maximum velocity of death induction rate (V(max)) and the LD50 (half-maximal velocity or k(1/2)) were calculated as 17.2 (% death/h) and 65 nM, respectively.

  5. Environmental Monitoring using Measurements from Cellular Network Infrastructure

    NASA Astrophysics Data System (ADS)

    David, N.; Gao, O. H.

    2015-12-01

    Accurate measurements of atmospheric parameters at ground level are fundamentally essential for hazard warning, meteorological forecasting and for various applications in agriculture, hydrology, transportation and more. The accuracy of existing instruments, however, is often limited as a result of technical and practical constraints. Existing technologies such as satellite systems cover large areas but may experience lack of precision at near surface level. On the other hand, ground based in-situ sensors often suffer from low spatial representativity. In addition, these conventional monitoring instruments are costly to implement and maintain. At frequencies of tens of GHz, various atmospheric hydrometeors affect microwave beams, causing perturbations to radio signals. Consequently, commercial wireless links that constitute the infrastructure for data transport between cellular base stations can be considered as a built in environmental monitoring facility (Messer et al., Science, 2006). These microwave links are widely deployed worldwide at surface level altitudes and can provide measurements of various atmospheric phenomena. The implementation costs are minimal since the infrastructure is already situated in the field. This technique has been shown to be applicable for 2D rainfall monitoring (e.g. Overeem et al., PNAS, 2013; Liberman et al., AMT, 2014) and potentially for water vapor observations (David et al., ACP, 2009; Chwala et al., Atmos. Res., 2013). Moreover, it has been recently shown that the technology has strong potential for detection of fog and estimation of its intensity (David et al., JGR-Atmos., 2013; David et al., BAMS, 2014). The research conducted to this point forms the basis for the initiation of a research project in this newly emerging field at the School of Civil and Environmental Engineering of Cornell University. The presentation will provide insights into key capabilities of the novel approach. The potential to monitor various

  6. Sources of uncertainty in rainfall maps from cellular communication networks

    NASA Astrophysics Data System (ADS)

    Rios Gaona, M. F.; Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-03-01

    Accurate measurements of rainfall are important in many hydrological and meteorological applications, for instance, flash-flood early-warning systems, hydraulic structures design, irrigation, weather forecasting, and climate modelling. Whenever possible, link networks measure and store the received power of the electromagnetic signal at regular intervals. The decrease in power can be converted to rainfall intensity, and is largely due to the attenuation by raindrops along the link paths. Such alternative technique fulfills the continuous strive for measurements of rainfall in time and space at higher resolutions, especially in places where traditional rain gauge networks are scarce or poorly maintained. Rainfall maps from microwave link networks have recently been introduced at country-wide scales. Despite their potential in rainfall estimation at high spatiotemporal resolutions, the uncertainties present in rainfall maps from link networks are not yet fully comprehended. The aim of this work is to identify and quantify the sources of uncertainty present in interpolated rainfall maps from link rainfall depths. In order to disentangle these sources of uncertainty, we classified them into two categories: (1) those associated with the individual microwave link measurements, i.e., the errors involved in single-link rainfall retrievals such as wet antenna attenuation, sampling interval of measurements, wet/dry period classification, quantization of the received power, drop size distribution (DSD), and multi-path propagation; (2) those associated with mapping, i.e., the combined effect of the interpolation methodology and the spatial density of link measurements. We computed ~3500 rainfall maps from real and simulated link rainfall depths for 12 days for the land surface of the Netherlands. Simulated link rainfall depths were obtained from radar data. These rainfall maps were compared against quality-controlled gauge-adjusted radar rainfall fields (assumed to be the

  7. Personal communication in traditional cellular networks

    NASA Astrophysics Data System (ADS)

    Neuer, Ellwood I.

    1996-01-01

    The purpose of this paper is to describe the flow of calls through the mobile network as it applies to the operation of Basic and Enhanced Services. Included in the discussion is the overall network layout, the physical connections between the network entities, and the signaling protocols which allow the entities to be integrated. The specific functionality of the applications and services are not detailed as the specific implementation varies from vendor to vendor and from service provider to service provider. The Enhanced Services Platform is installed in a service providers network in order to offer mobile subscribers services and applications which would otherwise not be available. The service providers' objective is to increase revenue/subscriber, increase subscriber loyalty/decrease churn, and build competitive advantages through differentiation. The services provided on the Enhanced Services platform can be viewed as either Basic or Enhanced. For the purpose of this paper, Basic Services refers to Numeric Paging, Call Answering, and Voice Messaging while Enhanced Services refers to FAX Messaging, One Number Service, Voice Dialing and other Voice Recognition applications, Information Services including FAX on Demand, and Automated Call Routing.

  8. An entropic characterization of protein interaction networks and cellular robustness.

    PubMed

    Manke, Thomas; Demetrius, Lloyd; Vingron, Martin

    2006-12-22

    The structure of molecular networks is believed to determine important aspects of their cellular function, such as the organismal resilience against random perturbations. Ultimately, however, cellular behaviour is determined by the dynamical processes, which are constrained by network topology. The present work is based on a fundamental relation from dynamical systems theory, which states that the macroscopic resilience of a steady state is correlated with the uncertainty in the underlying microscopic processes, a property that can be measured by entropy. Here, we use recent network data from large-scale protein interaction screens to characterize the diversity of possible pathways in terms of network entropy. This measure has its origin in statistical mechanics and amounts to a global characterization of both structural and dynamical resilience in terms of microscopic elements. We demonstrate how this approach can be used to rank network elements according to their contribution to network entropy and also investigate how this suggested ranking reflects on the functional data provided by gene knockouts and RNAi experiments in yeast and Caenorhabditis elegans. Our analysis shows that knockouts of proteins with large contribution to network entropy are preferentially lethal. This observation is robust with respect to several possible errors and biases in the experimental data. It underscores the significance of entropy as a fundamental invariant of the dynamical system, and as a measure of structural and dynamical properties of networks. Our analytical approach goes beyond the phenomenological studies of cellular robustness based on local network observables, such as connectivity. One of its principal achievements is to provide a rationale to study proxies of cellular resilience and rank proteins according to their importance within the global network context.

  9. Widrow-cellular neural network and optoelectronic implementation

    NASA Astrophysics Data System (ADS)

    Bal, Abdullah

    A new type of optoelectronic cellular neural network has been developed by providing the capability of coefficients adjusment of cellular neural network (CNN) using Widrow based perceptron learning algorithm. The new supervised cellular neural network is called Widrow-CNN. Despite the unsupervised CNN, the proposed learning algorithm allows to use the Widrow-CNN for various image processing applications easily. Also, the capability of CNN for image processing and feature extraction has been improved using basic joint transform correlation architecture. This hardware application presents high speed processing capability compared to digital applications. The optoelectronic Widrow-CNN has been tested for classic CNN feature extraction problems. It yields the best results even in case of hard feature extraction problems such as diagonal line detection and vertical line determination.

  10. Cellular and network mechanisms of electrographic seizures

    PubMed Central

    Bazhenov, Maxim; Timofeev, Igor; Fröhlich, Flavio; Sejnowski, Terrence J.

    2008-01-01

    Epileptic seizures constitute a complex multiscale phenomenon that is characterized by synchronized hyperexcitation of neurons in neuronal networks. Recent progress in understanding pathological seizure dynamics provides crucial insights into underlying mechanisms and possible new avenues for the development of novel treatment modalities. Here we review some recent work that combines in vivo experiments and computational modeling to unravel the pathophysiology of seizures of cortical origin. We particularly focus on how activity-dependent changes in extracellular potassium concentration affects the intrinsic dynamics of neurons involved in cortical seizures characterized by spike/wave complexes and fast runs. PMID:19190736

  11. TRANSWESD: inferring cellular networks with transitive reduction

    PubMed Central

    Klamt, Steffen; Flassig, Robert J.; Sundmacher, Kai

    2010-01-01

    Motivation: Distinguishing direct from indirect influences is a central issue in reverse engineering of biological networks because it facilitates detection and removal of false positive edges. Transitive reduction is one approach for eliminating edges reflecting indirect effects but its use in reconstructing cyclic interaction graphs with true redundant structures is problematic. Results: We present TRANSWESD, an elaborated variant of TRANSitive reduction for WEighted Signed Digraphs that overcomes conceptual problems of existing versions. Major changes and improvements concern: (i) new statistical approaches for generating high-quality perturbation graphs from systematic perturbation experiments; (ii) the use of edge weights (association strengths) for recognizing true redundant structures; (iii) causal interpretation of cycles; (iv) relaxed definition of transitive reduction; and (v) approximation algorithms for large networks. Using standardized benchmark tests, we demonstrate that our method outperforms existing variants of transitive reduction and is, despite its conceptual simplicity, highly competitive with other reverse engineering methods. Contact: klamt@mpi-magdeburg.mpg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20605927

  12. Modeling Integrated Cellular Machinery Using Hybrid Petri-Boolean Networks

    PubMed Central

    Berestovsky, Natalie; Zhou, Wanding; Nagrath, Deepak; Nakhleh, Luay

    2013-01-01

    The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them using such more

  13. Modeling integrated cellular machinery using hybrid Petri-Boolean networks.

    PubMed

    Berestovsky, Natalie; Zhou, Wanding; Nagrath, Deepak; Nakhleh, Luay

    2013-01-01

    The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them using such more

  14. Designed Proteins To Modulate Cellular Networks

    PubMed Central

    Cortajarena, Aitziber L.; Liu, Tina Y.; Hochstrasser, Mark; Regan, Lynne

    2012-01-01

    A major challenge of protein design is to create useful new proteins that interact specifically with biological targets in living cells. Such binding modules have many potential applications, including the targeted perturbation of protein networks. As a general approach to create such modules, we designed a library with approximately 109 different binding specificities based on a small 3-tetratricopeptide repeat (TPR) motif framework. We employed a novel strategy, based on split GFP reassembly, to screen the library for modules with the desired binding specificity. Using this approach, we identified modules that bind tightly and specifically to Dss1, a small human protein that interacts with the tumor suppressor protein BRCA2. We showed that these modules also bind the yeast homologue of Dss1, Sem1. Furthermore, we demonstrated that these modules inhibit Sem1 activity in yeast. This strategy will be generally applicable to make novel genetically encoded tools for systems/synthetic biology applications. PMID:20020775

  15. The community structure of human cellular signaling network.

    PubMed

    Diao, Yuanbo; Li, Menglong; Feng, Zinan; Yin, Jiajian; Pan, Yi

    2007-08-21

    Living cell is highly responsive to specific chemicals in its environment, such as hormones and molecules in food or aromas. The reason is ascribed to the existence of widespread and diverse signal transduction pathways, between which crosstalks usually exist, thus constitute a complex signaling network. Evidently, knowledge of topology characteristic of this network could contribute a lot to the understanding of diverse cellular behaviors and life phenomena thus come into being. In this presentation, signal transduction data is extracted from KEGG to construct a cellular signaling network of Homo sapiens, which has 931 nodes and 6798 links in total. Computing the degree distribution, we find it is not a random network, but a scale-free network following a power-law of P(K) approximately K(-gamma), with gamma approximately equal to 2.2. Among three graph partition algorithms, the Guimera's simulated annealing method is chosen to study the details of topology structure and other properties of this cellular signaling network, as it shows the best performance. To reveal the underlying biological implications, further investigation is conducted on ad hoc community and sketch map of individual community is drawn accordingly. The involved experiment data can be found in the supplementary material.

  16. From molecules to cellular networks: past and future outlook.

    PubMed

    Fang, Xiaona; Wang, Jin

    2017-02-16

    Cellular networks have been the focus of studies in modern systems biology. They are crucial in understanding cell functions and related diseases. We review some past progress in both the theory and experiments, and we also provide several future perspectives for the field.

  17. From molecules to cellular networks: past and future outlook

    NASA Astrophysics Data System (ADS)

    Fang, Xiaona; Wang, Jin

    2017-02-01

    Cellular networks have been the focus of studies in modern systems biology. They are crucial in understanding cell functions and related diseases. We review some past progress in both the theory and experiments, and we also provide several future perspectives for the field.

  18. Millimeter-Wave Evolution for 5G Cellular Networks

    NASA Astrophysics Data System (ADS)

    Sakaguchi, Kei; Tran, Gia Khanh; Shimodaira, Hidekazu; Nanba, Shinobu; Sakurai, Toshiaki; Takinami, Koji; Siaud, Isabelle; Strinati, Emilio Calvanese; Capone, Antonio; Karls, Ingolf; Arefi, Reza; Haustein, Thomas

    Triggered by the explosion of mobile traffic, 5G (5th Generation) cellular network requires evolution to increase the system rate 1000 times higher than the current systems in 10 years. Motivated by this common problem, there are several studies to integrate mm-wave access into current cellular networks as multi-band heterogeneous networks to exploit the ultra-wideband aspect of the mm-wave band. The authors of this paper have proposed comprehensive architecture of cellular networks with mm-wave access, where mm-wave small cell basestations and a conventional macro basestation are connected to Centralized-RAN (C-RAN) to effectively operate the system by enabling power efficient seamless handover as well as centralized resource control including dynamic cell structuring to match the limited coverage of mm-wave access with high traffic user locations via user-plane/control-plane splitting. In this paper, to prove the effectiveness of the proposed 5G cellular networks with mm-wave access, system level simulation is conducted by introducing an expected future traffic model, a measurement based mm-wave propagation model, and a centralized cell association algorithm by exploiting the C-RAN architecture. The numerical results show the effectiveness of the proposed network to realize 1000 times higher system rate than the current network in 10 years which is not achieved by the small cells using commonly considered 3.5 GHz band. Furthermore, the paper also gives latest status of mm-wave devices and regulations to show the feasibility of using mm-wave in the 5G systems.

  19. A competitive layer model for cellular neural networks.

    PubMed

    Zhou, Wei; Zurada, Jacek M

    2012-09-01

    This paper discusses a Competitive Layer Model (CLM) for a class of recurrent Cellular Neural Networks (CNNs) from continuous-time type to discrete-time type. The objective of the CLM is to partition a set of input features into salient groups. The complete convergence of such networks in continuous-time type has been discussed first. We give a necessary condition, and a necessary and sufficient condition, which allow the CLM performance existence in our networks. We also discuss the properties of such networks of discrete-time type, and propose a novel CLM iteration method. Such method shows similar performance and storage allocation but faster convergence compared with the previous CLM iteration method (Wersing, Steil, & Ritter, 2001a). Especially for a large scale network with many features and layers, it can significantly reduce the computing time. Examples and simulation results are used to illustrate the developed theory, the comparison between two CLM iteration methods, and the application in image segmentation.

  20. The role of actin networks in cellular mechanosensing

    NASA Astrophysics Data System (ADS)

    Azatov, Mikheil

    Physical processes play an important role in many biological phenomena, such as wound healing, organ development, and tumor metastasis. During these processes, cells constantly interact with and adapt to their environment by exerting forces to mechanically probe the features of their surroundings and generating appropriate biochemical responses. The mechanisms underlying how cells sense the physical properties of their environment are not well understood. In this thesis, I present my studies to investigate cellular responses to the stiffness and topography of the environment. In order to sense the physical properties of their environment, cells dynamically reorganize the structure of their actin cytoskeleton, a dynamic network of biopolymers, altering the shape and spatial distribution of protein assemblies. Several observations suggest that proteins that crosslink actin filaments may play an important role in cellular mechanosensitivity. Palladin is an actin-crosslinking protein that is found in the lamellar actin network, stress fibers and focal adhesions, cellular structures that are critical for mechanosensing of the physical environment. By virtue of its close interactions with these structures in the cell, palladin may play an important role in cell mechanics. However, the role of actin crosslinkers in general, and palladin in particular, in cellular force generation and mechanosensing is not well known. I have investigated the role of palladin in regulating the plasticity of the actin cytoskeleton and cellular force generation in response to alterations in substrate stiffness. I have shown that the expression levels of palladin modulate the forces exerted by cells and their ability to sense substrate stiffness. Perturbation experiments also suggest that palladin levels in cells altered myosin motor activity. These results suggest that the actin crosslinkers, such as palladin, and myosin motors coordinate for optimal cell function and to prevent aberrant

  1. Channel modeling for fifth generation cellular networks and wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Torabi, Amir

    In view of exponential growth in data traffic demand, the wireless communications industry has aimed to increase the capacity of existing networks by 1000 times over the next 20 years. A combination of extreme cell densification, more bandwidth, and higher spectral efficiency is needed to support the data traffic requirements for fifth generation (5G) cellular communications. In this research, the potential improvements achieved by using three major 5G enabling technologies (i.e., small cells, millimeter-wave spectrum, and massive MIMO) in rural and urban environments are investigated. This work develops SPM and KA-based ray models to investigate the impact of geometrical parameters on terrain-based multiuser MIMO channel characteristic. Moreover, a new directional 3D channel model is developed for urban millimeter-wave (mmW) small cells. Path-loss, spatial correlation, coverage distance, and coherence length are studied in urban areas. Exploiting physical optics (PO) and geometric optics (GO) solutions, closed form expressions are derived for spatial correlation. Achievable spatial diversity is evaluated using horizontal and vertical linear arrays as well as planar 2D arrays. In another study, a versatile near-ground field prediction model is proposed to facilitate accurate wireless sensor network (WSN) simulations. Monte Carlo simulations are used to investigate the effects of antenna height, frequency of operation, polarization, and terrain dielectric and roughness properties on WSNs performance.

  2. Cellular-based modeling of oscillatory dynamics in brain networks.

    PubMed

    Skinner, Frances K

    2012-08-01

    Oscillatory, population activities have long been known to occur in our brains during different behavioral states. We know that many different cell types exist and that they contribute in distinct ways to the generation of these activities. I review recent papers that involve cellular-based models of brain networks, most of which include theta, gamma and sharp wave-ripple activities. To help organize the modeling work, I present it from a perspective of three different types of cellular-based modeling: 'Generic', 'Biophysical' and 'Linking'. Cellular-based modeling is taken to encompass the four features of experiment, model development, theory/analyses, and model usage/computation. The three modeling types are shown to include these features and interactions in different ways.

  3. Cellular Automata with network incubation in information technology diffusion

    NASA Astrophysics Data System (ADS)

    Guseo, Renato; Guidolin, Mariangela

    2010-06-01

    Innovation diffusion of network goods determines direct network externalities that depress sales for long periods and delay full benefits. We model this effect through a multiplicative dynamic market potential driven by a latent individual threshold embedded in a special Cellular Automata representation. The corresponding mean field approximation of its aggregate version is a Riccati equation with a closed form solution. This allows the detection of a change-point time separating an incubation period from a subsequent take-off due to a collective threshold (critical mass). Weighted nonlinear least squares are the main inferential methodology. An application is analysed with reference to USA fax machine diffusion.

  4. Sensitivity analysis of FBMC-based multi-cellular networks to synchronization errors and HPA nonlinearities

    NASA Astrophysics Data System (ADS)

    Elmaroud, Brahim; Faqihi, Ahmed; Aboutajdine, Driss

    2017-01-01

    In this paper, we study the performance of asynchronous and nonlinear FBMC-based multi-cellular networks. The considered system includes a reference mobile perfectly synchronized with its reference base station (BS) and K interfering BSs. Both synchronization errors and high-power amplifier (HPA) distortions will be considered and a theoretical analysis of the interference signal will be conducted. On the basis of this analysis, we will derive an accurate expression of signal-to-noise-plus-interference ratio (SINR) and bit error rate (BER) in the presence of a frequency-selective channel. In order to reduce the computational complexity of the BER expression, we applied an interesting lemma based on the moment generating function of the interference power. Finally, the proposed model is evaluated through computer simulations which show a high sensitivity of the asynchronous FBMC-based multi-cellular network to HPA nonlinear distortions.

  5. Protein Kinase CK2: Intricate Relationships within Regulatory Cellular Networks.

    PubMed

    Nuñez de Villavicencio-Diaz, Teresa; Rabalski, Adam J; Litchfield, David W

    2017-03-05

    Protein kinase CK2 is a small family of protein kinases that has been implicated in an expanding array of biological processes. While it is widely accepted that CK2 is a regulatory participant in a multitude of fundamental cellular processes, CK2 is often considered to be a constitutively active enzyme which raises questions about how it can be a regulatory participant in intricately controlled cellular processes. To resolve this apparent paradox, we have performed a systematic analysis of the published literature using text mining as well as mining of proteomic databases together with computational assembly of networks that involve CK2. These analyses reinforce the notion that CK2 is involved in a broad variety of biological processes and also reveal an extensive interplay between CK2 phosphorylation and other post-translational modifications. The interplay between CK2 and other post-translational modifications suggests that CK2 does have intricate roles in orchestrating cellular events. In this respect, phosphorylation of specific substrates by CK2 could be regulated by other post-translational modifications and CK2 could also have roles in modulating other post-translational modifications. Collectively, these observations suggest that the actions of CK2 are precisely coordinated with other constituents of regulatory cellular networks.

  6. Protein Kinase CK2: Intricate Relationships within Regulatory Cellular Networks

    PubMed Central

    Nuñez de Villavicencio-Diaz, Teresa; Rabalski, Adam J.; Litchfield, David W.

    2017-01-01

    Protein kinase CK2 is a small family of protein kinases that has been implicated in an expanding array of biological processes. While it is widely accepted that CK2 is a regulatory participant in a multitude of fundamental cellular processes, CK2 is often considered to be a constitutively active enzyme which raises questions about how it can be a regulatory participant in intricately controlled cellular processes. To resolve this apparent paradox, we have performed a systematic analysis of the published literature using text mining as well as mining of proteomic databases together with computational assembly of networks that involve CK2. These analyses reinforce the notion that CK2 is involved in a broad variety of biological processes and also reveal an extensive interplay between CK2 phosphorylation and other post-translational modifications. The interplay between CK2 and other post-translational modifications suggests that CK2 does have intricate roles in orchestrating cellular events. In this respect, phosphorylation of specific substrates by CK2 could be regulated by other post-translational modifications and CK2 could also have roles in modulating other post-translational modifications. Collectively, these observations suggest that the actions of CK2 are precisely coordinated with other constituents of regulatory cellular networks. PMID:28273877

  7. Digital implementation of shunting-inhibitory cellular neural network

    NASA Astrophysics Data System (ADS)

    Hammadou, Tarik; Bouzerdoum, Abdesselam; Bermak, Amine

    2000-05-01

    Shunting inhibition is a model of early visual processing which can provide contrast and edge enhancement, and dynamic range compression. An architecture of digital Shunting Inhibitory Cellular Neural Network for real time image processing is presented. The proposed architecture is intended to be used in a complete vision system for edge detection and image enhancement. The present hardware architecture, is modeled and simulated in VHDL. Simulation results show the functional validity of the proposed architecture.

  8. Network Medicine: From Cellular Networks to the Human Diseasome

    NASA Astrophysics Data System (ADS)

    Barabasi, Albert-Laszlo

    2014-03-01

    Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The tools of network science offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction not only enrich our understanding of complex systems, but are also essential to identify new disease genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases.

  9. Tensegrity II. How structural networks influence cellular information processing networks

    NASA Technical Reports Server (NTRS)

    Ingber, Donald E.

    2003-01-01

    The major challenge in biology today is biocomplexity: the need to explain how cell and tissue behaviors emerge from collective interactions within complex molecular networks. Part I of this two-part article, described a mechanical model of cell structure based on tensegrity architecture that explains how the mechanical behavior of the cell emerges from physical interactions among the different molecular filament systems that form the cytoskeleton. Recent work shows that the cytoskeleton also orients much of the cell's metabolic and signal transduction machinery and that mechanical distortion of cells and the cytoskeleton through cell surface integrin receptors can profoundly affect cell behavior. In particular, gradual variations in this single physical control parameter (cell shape distortion) can switch cells between distinct gene programs (e.g. growth, differentiation and apoptosis), and this process can be viewed as a biological phase transition. Part II of this article covers how combined use of tensegrity and solid-state mechanochemistry by cells may mediate mechanotransduction and facilitate integration of chemical and physical signals that are responsible for control of cell behavior. In addition, it examines how cell structural networks affect gene and protein signaling networks to produce characteristic phenotypes and cell fate transitions during tissue development.

  10. ATR inhibition rewires cellular signaling networks induced by replication stress.

    PubMed

    Wagner, Sebastian A; Oehler, Hannah; Voigt, Andrea; Dalic, Denis; Freiwald, Anja; Serve, Hubert; Beli, Petra

    2016-02-01

    The slowing down or stalling of replication forks is commonly known as replication stress and arises from multiple causes such as DNA lesions, nucleotide depletion, RNA-DNA hybrids, and oncogene activation. The ataxia telangiectasia and Rad3-related kinase (ATR) plays an essential role in the cellular response to replication stress and inhibition of ATR has emerged as therapeutic strategy for the treatment of cancers that exhibit high levels of replication stress. However, the cellular signaling induced by replication stress and the substrate spectrum of ATR has not been systematically investigated. In this study, we employed quantitative MS-based proteomics to define the cellular signaling after nucleotide depletion-induced replication stress and replication fork collapse following ATR inhibition. We demonstrate that replication stress results in increased phosphorylation of a subset of proteins, many of which are involved in RNA splicing and transcription and have previously not been associated with the cellular replication stress response. Furthermore, our data reveal the ATR-dependent phosphorylation following replication stress and discover novel putative ATR target sites on MCM6, TOPBP1, RAD51AP1, and PSMD4. We establish that ATR inhibition rewires cellular signaling networks induced by replication stress and leads to the activation of the ATM-driven double-strand break repair signaling.

  11. Reverse Engineering Cellular Networks with Information Theoretic Methods

    PubMed Central

    Villaverde, Alejandro F.; Ross, John; Banga, Julio R.

    2013-01-01

    Building mathematical models of cellular networks lies at the core of systems biology. It involves, among other tasks, the reconstruction of the structure of interactions between molecular components, which is known as network inference or reverse engineering. Information theory can help in the goal of extracting as much information as possible from the available data. A large number of methods founded on these concepts have been proposed in the literature, not only in biology journals, but in a wide range of areas. Their critical comparison is difficult due to the different focuses and the adoption of different terminologies. Here we attempt to review some of the existing information theoretic methodologies for network inference, and clarify their differences. While some of these methods have achieved notable success, many challenges remain, among which we can mention dealing with incomplete measurements, noisy data, counterintuitive behaviour emerging from nonlinear relations or feedback loops, and computational burden of dealing with large data sets. PMID:24709703

  12. Mechanics of composite actin networks: in vitro and cellular perspectives

    NASA Astrophysics Data System (ADS)

    Upadhyaya, Arpita

    2014-03-01

    Actin filaments and associated actin binding proteins play an essential role in governing the mechanical properties of eukaryotic cells. Even though cells have multiple actin binding proteins (ABPs) that exist simultaneously to maintain the structural and mechanical integrity of the cellular cytoskeleton, how these proteins work together to determine the properties of actin networks is not well understood. The ABP, palladin, is essential for the integrity of cell morphology and movement during development. Palladin coexists with alpha-actinin in stress fibers and focal adhesions and binds to both actin and alpha-actinin. To obtain insight into how mutually interacting actin crosslinking proteins modulate the properties of actin networks, we have characterized the micro-structure and mechanics of actin networks crosslinked with palladin and alpha-actinin. Our studies on composite networks of alpha-actinin/palladin/actin show that palladin and alpha-actinin synergistically determine network viscoelasticity. We have further examined the role of palladin in cellular force generation and mechanosensing. Traction force microscopy revealed that TAFs are sensitive to substrate stiffness as they generate larger forces on substrates of increased stiffness. Contrary to expectations, knocking down palladin increased the forces generated by cells, and also inhibited the ability to sense substrate stiffness for very stiff gels. This was accompanied by significant differences in the actin organization and adhesion dynamics of palladin knock down cells. Perturbation experiments also suggest altered myosin activity in palladin KD cells. Our results suggest that the actin crosslinkers such as palladin and myosin motors coordinate for optimal cell function and to prevent aberrant behavior as in cancer metastasis.

  13. Study and Simulation of Traffic Behavior in Cellular Network

    NASA Astrophysics Data System (ADS)

    Madhup, D. K.; Shrestha, C. L.; Sharma, R. K.

    2007-07-01

    Cellular radio systems accommodate a large number of users with a limited radio spectrum. The concept of trunking allows a large number of users to share the relatively small number of channels in a cell by providing access to each user, on demand, from a pool of available channels. Traffic engineering deals with provisioning of communication circuits in a given area for a number of subscribers with a required grade of service. Traffic in any cell depends upon the number of users, the average request rate and average call duration. Certain number of channels is required for the required GOS. To design an optimum capacity cellular system, traffic behavior on that system is important. The number of channel required can be estimated by using Erlang formula and Erlang table. Erlang table is not always useful to calculate the probability of blocking in various complex scenarios such as channel borrowing strategies. When the total number of channel available in a given cell are divided to serve partly for newly generated calls and partly for handover calls, and if they use dynamic channel assignment strategies like channel borrowing, then the probability of blocking can't be calculated from Erlang table. Simulation model of the behavior help us to determine the blocking and the channel utilization while using various channel assignment strategies. The title "Study and Simulation of Traffic Behavior in Cellular Network" entail the study of the blocking probability of traffic in cellular network for static channel assignment strategies and dynamic channel borrowing strategies through MATLAB programming language and graphic user interface (GUI). The result shows that the dynamic scheme can perform better than static maximizing the overall utilization of the circuits and minimizing the overall blocking.

  14. Cutting the Wires: Modularization of Cellular Networks for Experimental Design

    PubMed Central

    Lang, Moritz; Summers, Sean; Stelling, Jörg

    2014-01-01

    Understanding naturally evolved cellular networks requires the consecutive identification and revision of the interactions between relevant molecular species. In this process, initially often simplified and incomplete networks are extended by integrating new reactions or whole subnetworks to increase consistency between model predictions and new measurement data. However, increased consistency with experimental data alone is not sufficient to show the existence of biomolecular interactions, because the interplay of different potential extensions might lead to overall similar dynamics. Here, we present a graph-based modularization approach to facilitate the design of experiments targeted at independently validating the existence of several potential network extensions. Our method is based on selecting the outputs to measure during an experiment, such that each potential network extension becomes virtually insulated from all others during data analysis. Each output defines a module that only depends on one hypothetical network extension, and all other outputs act as virtual inputs to achieve insulation. Given appropriate experimental time-series measurements of the outputs, our modules can be analyzed, simulated, and compared to the experimental data separately. Our approach exemplifies the close relationship between structural systems identification and modularization, an interplay that promises development of related approaches in the future. PMID:24411264

  15. GPM ground validation via commercial cellular networks: an exploratory approach

    NASA Astrophysics Data System (ADS)

    Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Brasjen, Noud; Uijlenhoet, Remko

    2016-04-01

    The suitability of commercial microwave link networks for ground validation of GPM (Global Precipitation Measurement) data is evaluated here. Two state-of-the-art rainfall products are compared over the land surface of the Netherlands for a period of 7 months, i.e., rainfall maps from commercial cellular communication networks and Integrated Multi-satellite Retrievals for GPM (IMERG). Commercial microwave link networks are nowadays the core component in telecommunications worldwide. Rainfall rates can be retrieved from measurements of attenuation between transmitting and receiving antennas. If adequately set up, these networks enable rainfall monitoring tens of meters above the ground at high spatiotemporal resolutions (temporal sampling of seconds to tens of minutes, and spatial sampling of hundreds of meters to tens of kilometers). The GPM mission is the successor of TRMM (Tropical Rainfall Measurement Mission). For two years now, IMERG offers rainfall estimates across the globe (180°W - 180°E and 60°N - 60°S) at spatiotemporal resolutions of 0.1° x 0.1° every 30 min. These two data sets are compared against a Dutch gauge-adjusted radar data set, considered to be the ground truth given its accuracy, spatiotemporal resolution and availability. The suitability of microwave link networks in satellite rainfall evaluation is of special interest, given the independent character of this technique, its high spatiotemporal resolutions and availability. These are valuable assets for water management and modeling of floods, landslides, and weather extremes; especially in places where rain gauge networks are scarce or poorly maintained, or where weather radar networks are too expensive to acquire and/or maintain.

  16. Cellular telephone-based wide-area radiation detection network

    DOEpatents

    Craig, William W.; Labov, Simon E.

    2009-06-09

    A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

  17. Segmentation algorithm via Cellular Neural/Nonlinear Network: implementation on Bio-inspired hardware platform

    NASA Astrophysics Data System (ADS)

    Karabiber, Fethullah; Vecchio, Pietro; Grassi, Giuseppe

    2011-12-01

    The Bio-inspired (Bi-i) Cellular Vision System is a computing platform consisting of sensing, array sensing-processing, and digital signal processing. The platform is based on the Cellular Neural/Nonlinear Network (CNN) paradigm. This article presents the implementation of a novel CNN-based segmentation algorithm onto the Bi-i system. Each part of the algorithm, along with the corresponding implementation on the hardware platform, is carefully described through the article. The experimental results, carried out for Foreman and Car-phone video sequences, highlight the feasibility of the approach, which provides a frame rate of about 26 frames/s. Comparisons with existing CNN-based methods show that the conceived approach is more accurate, thus representing a good trade-off between real-time requirements and accuracy.

  18. Perturbation biology: inferring signaling networks in cellular systems.

    PubMed

    Molinelli, Evan J; Korkut, Anil; Wang, Weiqing; Miller, Martin L; Gauthier, Nicholas P; Jing, Xiaohong; Kaushik, Poorvi; He, Qin; Mills, Gordon; Solit, David B; Pratilas, Christine A; Weigt, Martin; Braunstein, Alfredo; Pagnani, Andrea; Zecchina, Riccardo; Sander, Chris

    2013-01-01

    We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology.

  19. Assessing the weather monitoring capabilities of cellular microwave link networks

    NASA Astrophysics Data System (ADS)

    Fencl, Martin; Vrzba, Miroslav; Rieckermann, Jörg; Bareš, Vojtěch

    2016-04-01

    Using of microwave links for rainfall monitoring was suggested already by (Atlas and Ulbrich, 1977). However, this technique attracted broader attention of scientific community only in the recent decade, with the extensive growth of cellular microwave link (CML) networks, which form the backbone of today's cellular telecommunication infrastructure. Several studies have already shown that CMLs can be conveniently used as weather sensors and have potential to provide near-ground path-integrated observations of rainfall but also humidity or fog. However, although research is still focusing on algorithms to improve the weather sensing capabilities (Fencl et al., 2015), it is not clear how to convince cellular operators to provide the power levels of their network. One step in this direction is to show in which regions or municipalities the networks are sufficiently dense to provide/develop good services. In this contribution we suggest a standardized approach to evaluate CML networks in terms of rainfall observation and to identify suitable regions for CML rainfall monitoring. We estimate precision of single CML based on its sensitivity to rainfall, i.e. as a function of frequency, polarization and path length. Capability of a network to capture rainfall spatial patterns is estimated from the CML coverage and path lengths considering that single CML provides path-integrated rain rates. We also search for suitable predictors for regions where no network topologies are available. We test our approach on several European networks and discuss the results. Our results show that CMLs are very dense in urban areas (> 1 CML/km2), but less in rural areas (< 0.02 CML/km2). We found a strong correlation between a population and CML network density (e.g. R2 = 0.97 in Czech Republic), thus population could be a simple proxy to identify suitable regions for CML weather monitoring. To enable a simple and efficient assessment of the CML monitoring potential for any region worldwide

  20. Multi-casting approach for vascular networks in cellularized hydrogels.

    PubMed

    Justin, Alexander W; Brooks, Roger A; Markaki, Athina E

    2016-12-01

    Vascularization is essential for living tissue and remains a major challenge in the field of tissue engineering. A lack of a perfusable channel network within a large and densely populated tissue engineered construct leads to necrotic core formation, preventing fabrication of functional tissues and organs. We report a new method for producing a hierarchical, three-dimensional (3D) and perfusable vasculature in a large, cellularized fibrin hydrogel. Bifurcating channels, varying in size from 1 mm to 200-250 µm, are formed using a novel process in which we convert a 3D printed thermoplastic material into a gelatin network template, by way of an intermediate alginate hydrogel. This enables a CAD-based model design, which is highly customizable, reproducible, and which can yield highly complex architectures, to be made into a removable material, which can be used in cellular environments. Our approach yields constructs with a uniform and high density of cells in the bulk, made from bioactive collagen and fibrin hydrogels. Using standard cell staining and immuno-histochemistry techniques, we showed good cell seeding and the presence of tight junctions between channel endothelial cells, and high cell viability and cell spreading in the bulk hydrogel.

  1. Multi-casting approach for vascular networks in cellularized hydrogels

    PubMed Central

    Justin, Alexander W.; Brooks, Roger A.

    2016-01-01

    Vascularization is essential for living tissue and remains a major challenge in the field of tissue engineering. A lack of a perfusable channel network within a large and densely populated tissue engineered construct leads to necrotic core formation, preventing fabrication of functional tissues and organs. We report a new method for producing a hierarchical, three-dimensional (3D) and perfusable vasculature in a large, cellularized fibrin hydrogel. Bifurcating channels, varying in size from 1 mm to 200–250 µm, are formed using a novel process in which we convert a 3D printed thermoplastic material into a gelatin network template, by way of an intermediate alginate hydrogel. This enables a CAD-based model design, which is highly customizable, reproducible, and which can yield highly complex architectures, to be made into a removable material, which can be used in cellular environments. Our approach yields constructs with a uniform and high density of cells in the bulk, made from bioactive collagen and fibrin hydrogels. Using standard cell staining and immuno-histochemistry techniques, we showed good cell seeding and the presence of tight junctions between channel endothelial cells, and high cell viability and cell spreading in the bulk hydrogel. PMID:27928031

  2. Three Years of Country-Wide Rainfall Maps from Cellular Communication Networks

    NASA Astrophysics Data System (ADS)

    Uijlenhoet, R.; Overeem, A.; Leijnse, H.; Rios Gaona, M. F.

    2014-12-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information and the number of rain gauges is even severely declining in Europe, South-America, and Africa. This calls for alternative sources of rainfall information. Various studies have shown that microwave links from operational cellular communication networks may be used for rainfall monitoring. Such networks cover 20% of the land surface of the earth and have a high density, especially in urban areas. The basic principle of rainfall estimation using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated, which can be converted to average rainfall intensities over the length of a link. This is particularly interesting for those countries where few surface rainfall observations are available. A data set from a commercial microwave link network over the Netherlands is analyzed. The data set runs from January 2011 - January 2014 and consists of roughly 2000 links covering the land surface of the Netherlands (35,500 square kilometers). From this 3-year data set country-wide rainfall maps are retrieved, which are compared to a gauge-adjusted radar data set. The ability of cellular communication networks to estimate rainfall is studied for different temporal and spatial scales, as well as for several air temperature classes. Case studies are presented to investigate the performance of the algorithm during snow and sleet and to show the influence of dew formation on the antennas on the received signal levels. To summarize, the results further confirm the potential of these networks for rainfall monitoring.

  3. Myosin lever arm directs collective motion on cellular actin network.

    PubMed

    Hariadi, Rizal F; Cale, Mario; Sivaramakrishnan, Sivaraj

    2014-03-18

    The molecular motor myosin teams up to drive muscle contraction, membrane traffic, and cell division in biological cells. Myosin function in cells emerges from the interaction of multiple motors tethered to a scaffold, with surrounding actin filaments organized into 3D networks. Despite the importance of myosin function, the influence of intermotor interactions on collective motion remains poorly understood. In this study, we used precisely engineered myosin assemblies to examine emergence in collective myosin movement. We report that tethering multiple myosin VI motors, but not myosin V motors, modifies their movement trajectories on keratocyte actin networks. Single myosin V and VI dimers display similar skewed trajectories, albeit in opposite directions, when traversing the keratocyte actin network. In contrast, tethering myosin VI motors, but not myosin V motors, progressively straightens the trajectories with increasing myosin number. Trajectory shape of multimotor scaffolds positively correlates with the stiffness of the myosin lever arm. Swapping the flexible myosin VI lever arm for the relatively rigid myosin V lever increases trajectory skewness, and vice versa. A simplified model of coupled motor movement demonstrates that the differences in flexural rigidity of the two myosin lever arms is sufficient to account for the differences in observed behavior of groups of myosin V and VI motors. In accordance with this model trajectory, shapes for scaffolds containing both myosin V and VI are dominated by the myosin with a stiffer lever arm. Our findings suggest that structural features unique to each myosin type may confer selective advantages in cellular functions.

  4. A rigorous framework for multiscale simulation of stochastic cellular networks

    PubMed Central

    Chevalier, Michael W.; El-Samad, Hana

    2009-01-01

    Noise and stochasticity are fundamental to biology and derive from the very nature of biochemical reactions where thermal motion of molecules translates into randomness in the sequence and timing of reactions. This randomness leads to cell-cell variability even in clonal populations. Stochastic biochemical networks are modeled as continuous time discrete state Markov processes whose probability density functions evolve according to a chemical master equation (CME). The CME is not solvable but for the simplest cases, and one has to resort to kinetic Monte Carlo techniques to simulate the stochastic trajectories of the biochemical network under study. A commonly used such algorithm is the stochastic simulation algorithm (SSA). Because it tracks every biochemical reaction that occurs in a given system, the SSA presents computational difficulties especially when there is a vast disparity in the timescales of the reactions or in the number of molecules involved in these reactions. This is common in cellular networks, and many approximation algorithms have evolved to alleviate the computational burdens of the SSA. Here, we present a rigorously derived modified CME framework based on the partition of a biochemically reacting system into restricted and unrestricted reactions. Although this modified CME decomposition is as analytically difficult as the original CME, it can be naturally used to generate a hierarchy of approximations at different levels of accuracy. Most importantly, some previously derived algorithms are demonstrated to be limiting cases of our formulation. We apply our methods to biologically relevant test systems to demonstrate their accuracy and efficiency. PMID:19673546

  5. Cellular Neural Network for Real Time Image Processing

    SciTech Connect

    Vagliasindi, G.; Arena, P.; Fortuna, L.; Mazzitelli, G.; Murari, A.

    2008-03-12

    Since their introduction in 1988, Cellular Nonlinear Networks (CNNs) have found a key role as image processing instruments. Thanks to their structure they are able of processing individual pixels in a parallel way providing fast image processing capabilities that has been applied to a wide range of field among which nuclear fusion. In the last years, indeed, visible and infrared video cameras have become more and more important in tokamak fusion experiments for the twofold aim of understanding the physics and monitoring the safety of the operation. Examining the output of these cameras in real-time can provide significant information for plasma control and safety of the machines. The potentiality of CNNs can be exploited to this aim. To demonstrate the feasibility of the approach, CNN image processing has been applied to several tasks both at the Frascati Tokamak Upgrade (FTU) and the Joint European Torus (JET)

  6. Cellular Neural Network for Real Time Image Processing

    NASA Astrophysics Data System (ADS)

    Vagliasindi, G.; Arena, P.; Fortuna, L.; Mazzitelli, G.; Murari, A.

    2008-03-01

    Since their introduction in 1988, Cellular Nonlinear Networks (CNNs) have found a key role as image processing instruments. Thanks to their structure they are able of processing individual pixels in a parallel way providing fast image processing capabilities that has been applied to a wide range of field among which nuclear fusion. In the last years, indeed, visible and infrared video cameras have become more and more important in tokamak fusion experiments for the twofold aim of understanding the physics and monitoring the safety of the operation. Examining the output of these cameras in real-time can provide significant information for plasma control and safety of the machines. The potentiality of CNNs can be exploited to this aim. To demonstrate the feasibility of the approach, CNN image processing has been applied to several tasks both at the Frascati Tokamak Upgrade (FTU) and the Joint European Torus (JET).

  7. Separation of Bouguer anomaly map using cellular neural network

    NASA Astrophysics Data System (ADS)

    Albora, A. Muhittin; Ucan, Osman N.; Ozmen, Atilla; Ozkan, Tulay

    2001-02-01

    In this paper, a modern image-processing technique, the Cellular Neural Network (CNN) has been firstly applied to Bouguer anomaly map of synthetic examples and then to data from the Sivas-Divrigi Akdag region. CNN is an analog parallel computing paradigm defined in space and characterized by the locality of connections between processing neurons. The behaviour of the CNN is defined by two template matrices and a template vector. We have optimised the weight coefficients of these templates using the Recurrent Perceptron Learning Algorithm (RPLA). After testing CNN performance on synthetic examples, the CNN approach has been applied to the Bouguer anomaly of Sivas-Divrigi Akdag region and the results match drilling logs done by Mineral Research and Exploration (MTA).

  8. Joint accurate time and stable frequency distribution infrastructure sharing fiber footprint with research network

    NASA Astrophysics Data System (ADS)

    Vojtech, Josef; Slapak, Martin; Skoda, Pavel; Radil, Jan; Havlis, Ondrej; Altmann, Michal; Munster, Petr; Smotlacha, Vladimir; Kundrat, Jan; Velc, Radek; Altmannova, Lada; Hula, Miloslav

    2016-09-01

    In this paper, we present infrastructure for accurate time and stable frequency distribution. It is based on sharing of fibers of research and educational network carrying data traffic. Accurate time and stable frequency transmission uses mainly created dark channels amplified by special bidirectional amplifiers with the same propagation path for both directions. Paper also targets challenges joined with bidirectional transmission, which represents directional non-reciprocities and interaction with parallel data transmissions.

  9. Cellular computational networks--a scalable architecture for learning the dynamics of large networked systems.

    PubMed

    Luitel, Bipul; Venayagamoorthy, Ganesh Kumar

    2014-02-01

    Neural networks for implementing large networked systems such as smart electric power grids consist of multiple inputs and outputs. Many outputs lead to a greater number of parameters to be adapted. Each additional variable increases the dimensionality of the problem and hence learning becomes a challenge. Cellular computational networks (CCNs) are a class of sparsely connected dynamic recurrent networks (DRNs). By proper selection of a set of input elements for each output variable in a given application, a DRN can be modified into a CCN which significantly reduces the complexity of the neural network and allows use of simple training methods for independent learning in each cell thus making it scalable. This article demonstrates this concept of developing a CCN using dimensionality reduction in a DRN for scalability and better performance. The concept has been analytically explained and empirically verified through application.

  10. Using cellular network diagrams to interpret large-scale datasets: past progress and future challenges

    NASA Astrophysics Data System (ADS)

    Karp, Peter D.; Latendresse, Mario; Paley, Suzanne

    2011-03-01

    Cellular networks are graphs of molecular interactions within the cell. Thanks to the confluence of genome sequencing and bioinformatics, scientists are now able to reconstruct cellular network models for more than 1,000 organisms. A variety of bioinformatics tools have been developed to support the visualization and navigation of cellular network data. Another important application is the use of cellular network diagrams to visualize and interpret large-scale datasets, such as gene-expression data. We present the Cellular Overview, a network visualization tool developed at SRI International (SRI) to support visualization, navigation, and interpretation of large-scale datasets on metabolic networks. Different variations of the diagram have been generated algorithmically for more than 1,000 organisms. We discuss the graphical design of the diagram and its interactive capabilities.

  11. Radio Resource Allocation on Complex 4G Wireless Cellular Networks

    NASA Astrophysics Data System (ADS)

    Psannis, Kostas E.

    2015-09-01

    In this article we consider the heuristic algorithm which improves step by step wireless data delivery over LTE cellular networks by using the total transmit power with the constraint on users’ data rates, and the total throughput with the constraints on the total transmit power as well as users’ data rates, which are jointly integrated into a hybrid-layer design framework to perform radio resource allocation for multiple users, and to effectively decide the optimal system parameter such as modulation and coding scheme (MCS) in order to adapt to the varying channel quality. We propose new heuristic algorithm which balances the accessible data rate, the initial data rates of each user allocated by LTE scheduler, the priority indicator which signals delay- throughput- packet loss awareness of the user, and the buffer fullness by achieving maximization of radio resource allocation for multiple users. It is noted that the overall performance is improved with the increase in the number of users, due to multiuser diversity. Experimental results illustrate and validate the accuracy of the proposed methodology.

  12. Hierarchical Interference Mitigation for Massive MIMO Cellular Networks

    NASA Astrophysics Data System (ADS)

    Liu, An; Lau, Vincent

    2014-09-01

    We propose a hierarchical interference mitigation scheme for massive MIMO cellular networks. The MIMO precoder at each base station (BS) is partitioned into an inner precoder and an outer precoder. The inner precoder controls the intra-cell interference and is adaptive to local channel state information (CSI) at each BS (CSIT). The outer precoder controls the inter-cell interference and is adaptive to channel statistics. Such hierarchical precoding structure reduces the number of pilot symbols required for CSI estimation in massive MIMO downlink and is robust to the backhaul latency. We study joint optimization of the outer precoders, the user selection, and the power allocation to maximize a general concave utility which has no closed-form expression. We first apply random matrix theory to obtain an approximated problem with closed-form objective. We show that the solution of the approximated problem is asymptotically optimal with respect to the original problem as the number of antennas per BS grows large. Then using the hidden convexity of the problem, we propose an iterative algorithm to find the optimal solution for the approximated problem. We also obtain a low complexity algorithm with provable convergence. Simulations show that the proposed design has significant gain over various state-of-the-art baselines.

  13. A More Accurate Characterization of UH-60A Pitch Link Loads Using Neural Networks

    NASA Technical Reports Server (NTRS)

    Kottapalli, Sesi; Aiken, Ed (Technical Monitor)

    1998-01-01

    A more accurate, neural-network-based characterization of the full-scale UH-60A maximum, vibratory pitch link loads (MXVPLL) was obtained. The MXVPLL data were taken from the NASA/Army UH-60A Airloads Program flight test database. This database includes data from level flights, and both simple and "complex" maneuvers. In the present context, a complex maneuver was defined as one which involved simultaneous, non-zero aircraft angle-of-bank (associated with turns) and aircraft pitch-rate (associated with a pull-up or a push-over). The present approach combines physical insight followed by the neural networks application. Since existing load factors do not represent the above-defined complex maneuver, a new, combined load factor ('p resent-load-factor') was introduced. A back-propagation type of neural network with five inputs and one output was used to characterize the UH-60A MXVPLL. The neural network inputs were as follows: rotor advance ratio, aircraft gross weight, rotor RPM, air density ratio, and the present-load-factor. The neural network output was the maximum, vibratory pitch link load (MXVPLL). It was shown that a more accurate characterization of the full-scale flight test pitch link loads can be obtained by combining physical insight with a neural-network-based approach.

  14. Accurate path integration in continuous attractor network models of grid cells.

    PubMed

    Burak, Yoram; Fiete, Ila R

    2009-02-01

    Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of approximately 10-100 meters and approximately 1-10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other.

  15. Network signatures of cellular immortalization in human lymphoblastoid cell lines

    SciTech Connect

    Shim, Sung-Mi; Jung, So-Young; Nam, Hye-Young; Kim, Hye-Ryun; Lee, Mee-Hee; Kim, Jun-Woo; Han, Bok-Ghee; Jeon, Jae-Pil

    2013-11-15

    Highlights: •We identified network signatures of LCL immortalization from transcriptomic profiles. •More than 41% of DEGs are possibly regulated by miRNAs in LCLs. •MicroRNA target genes in LCLs are involved in apoptosis and immune-related functions. •This approach is useful to find functional miRNA targets in specific cell conditions. -- Abstract: Human lymphoblastoid cell line (LCL) has been used as an in vitro cell model in genetic and pharmacogenomic studies, as well as a good model for studying gene expression regulatory machinery using integrated genomic analyses. In this study, we aimed to identify biological networks of LCL immortalization from transcriptomic profiles of microRNAs and their target genes in LCLs. We first selected differentially expressed genes (DEGs) and microRNAs (DEmiRs) between early passage LCLs (eLCLs) and terminally differentiated late passage LCLs (tLCLs). The in silico and correlation analysis of these DEGs and DEmiRs revealed that 1098 DEG–DEmiR pairs were found to be positively (n = 591 pairs) or negatively (n = 507 pairs) correlated with each other. More than 41% of DEGs are possibly regulated by miRNAs in LCL immortalizations. The target DEGs of DEmiRs were enriched for cellular functions associated with apoptosis, immune response, cell death, JAK–STAT cascade and lymphocyte activation while non-miRNA target DEGs were over-represented for basic cell metabolisms. The target DEGs correlated negatively with miR-548a-3p and miR-219-5p were significantly associated with protein kinase cascade, and the lymphocyte proliferation and apoptosis, respectively. In addition, the miR-106a and miR-424 clusters located in the X chromosome were enriched in DEmiR–mRNA pairs for LCL immortalization. In this study, the integrated transcriptomic analysis of LCLs could identify functional networks of biologically active microRNAs and their target genes involved in LCL immortalization.

  16. Network motifs in integrated cellular networks of transcription-regulation and protein-protein interaction

    NASA Astrophysics Data System (ADS)

    Yeger-Lotem, Esti; Sattath, Shmuel; Kashtan, Nadav; Itzkovitz, Shalev; Milo, Ron; Pinter, Ron Y.; Alon, Uri; Margalit, Hanah

    2004-04-01

    Genes and proteins generate molecular circuitry that enables the cell to process information and respond to stimuli. A major challenge is to identify characteristic patterns in this network of interactions that may shed light on basic cellular mechanisms. Previous studies have analyzed aspects of this network, concentrating on either transcription-regulation or protein-protein interactions. Here we search for composite network motifs: characteristic network patterns consisting of both transcription-regulation and protein-protein interactions that recur significantly more often than in random networks. To this end we developed algorithms for detecting motifs in networks with two or more types of interactions and applied them to an integrated data set of protein-protein interactions and transcription regulation in Saccharomyces cerevisiae. We found a two-protein mixed-feedback loop motif, five types of three-protein motifs exhibiting coregulation and complex formation, and many motifs involving four proteins. Virtually all four-protein motifs consisted of combinations of smaller motifs. This study presents a basic framework for detecting the building blocks of networks with multiple types of interactions.

  17. Assigning numbers to the arrows: Parameterizing a gene regulation network by using accurate expression kinetics

    NASA Astrophysics Data System (ADS)

    Ronen, Michal; Rosenberg, Revital; Shraiman, Boris I.; Alon, Uri

    2002-08-01

    A basic challenge in systems biology is to understand the dynamical behavior of gene regulation networks. Current approaches aim at determining the network structure based on genomic-scale data. However, the network connectivity alone is not sufficient to define its dynamics; one needs to also specify the kinetic parameters for the regulation reactions. Here, we ask whether effective kinetic parameters can be assigned to a transcriptional network based on expression data. We present a combined experimental and theoretical approach based on accurate high temporal-resolution measurement of promoter activities from living cells by using green fluorescent protein (GFP) reporter plasmids. We present algorithms that use these data to assign effective kinetic parameters within a mathematical model of the network. To demonstrate this, we employ a well defined network, the SOS DNA repair system of Escherichia coli. We find a strikingly detailed temporal program of expression that correlates with the functional role of the SOS genes and is driven by a hierarchy of effective kinetic parameter strengths for the various promoters. The calculated parameters can be used to determine the kinetics of all SOS genes given the expression profile of just one representative, allowing a significant reduction in complexity. The concentration profile of the master SOS transcriptional repressor can be calculated, demonstrating that relative protein levels may be determined from purely transcriptional data. This finding opens the possibility of assigning kinetic parameters to transcriptional networks on a genomic scale.

  18. Predict drug-protein interaction in cellular networking.

    PubMed

    Xiao, Xuan; Min, Jian-Liang; Wang, Pu; Chou, Kuo-Chen

    2013-01-01

    Involved with many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, GPCRs (G-protein-coupled receptors) are the most frequent targets for drug development: over 50% of all prescription drugs currently on the market are actually acting by targeting GPCRs directly or indirectly. Found in every living thing and nearly all cells, ion channels play crucial roles for many vital functions in life, such as heartbeat, sensory transduction, and central nervous system response. Their dysfunction may have significant impact to human health, and hence ion channels are deemed as "the next GPCRs". To develop GPCR-targeting or ion-channel-targeting drugs, the first important step is to identify the interactions between potential drug compounds with the two kinds of protein receptors in the cellular networking. In this minireview, we are to introduce two predictors. One is called iGPCR-Drug accessible at http://www.jci-bioinfo.cn/iGPCR-Drug/; the other called iCDI-PseFpt at http://www.jci-bioinfo.cn/iCDI-PseFpt. The former is for identifying the interactions of drug compounds with GPCRs; while the latter for that with ion channels. In both predictors, the drug compound was formulated by the two-dimensional molecular fingerprint, and the protein receptor by the pseudo amino acid composition generated with the grey model theory, while the operation engine was the fuzzy K-nearest neighbor algorithm. For the convenience of most experimental pharmaceutical and medical scientists, a step-bystep guide is provided on how to use each of the two web-servers to get the desired results without the need to follow the complicated mathematics involved originally for their establishment.

  19. Implementation of a cellular neural network-based segmentation algorithm on the bio-inspired vision system

    NASA Astrophysics Data System (ADS)

    Karabiber, Fethullah; Grassi, Giuseppe; Vecchio, Pietro; Arik, Sabri; Yalcin, M. Erhan

    2011-01-01

    Based on the cellular neural network (CNN) paradigm, the bio-inspired (bi-i) cellular vision system is a computing platform consisting of state-of-the-art sensing, cellular sensing-processing and digital signal processing. This paper presents the implementation of a novel CNN-based segmentation algorithm onto the bi-i system. The experimental results, carried out for different benchmark video sequences, highlight the feasibility of the approach, which provides a frame rate of about 26 frame/sec. Comparisons with existing CNN-based methods show that, even though these methods are from two to six times faster than the proposed one, the conceived approach is more accurate and, consequently, represents a satisfying trade-off between real-time requirements and accuracy.

  20. Country-wide rainfall maps from a commercial cellular telephone network

    NASA Astrophysics Data System (ADS)

    Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2012-04-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for many applications, for instance, as input for hydrological models. Weather radars often provide data with sufficient spatial and temporal resolution, but usually need adjustment. In general, only few rain gauge measurements are available to adjust the radar data in real-time, for example, each hour. Physically based methods, such as a VPR correction, can be valuable and hold a promise. However, they are not always performed in real-time yet and can be difficult to implement. The estimation of rainfall using microwave links from commercial cellular telephone networks is a new and potentially valuable source of information. Such networks cover large parts of the land surface of the earth and have a high density. The data produced by the microwave links in such networks is essentially a by-product of the communication between mobile telephones. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. A recent study of us shows that urban rainfall can be estimated from commercial microwave link data for the Rotterdam region, a densely-populated delta city in the Netherlands. A data set from a commercial microwave link network over the Netherlands is analyzed, containing approximately 1500 links covering the land surface of the Netherlands (35500 km2). This data set consists of several days with extreme rainfall in June, July and August 2011. A methodology is presented to derive rainfall intensities and daily rainfall depths from the microwave link data, which have a temporal resolution of 15 min. The magnitude and dynamics of these rainfall intensities

  1. Design mobile satellite system architecture as an integral part of the cellular access digital network

    NASA Technical Reports Server (NTRS)

    Chien, E. S. K.; Marinho, J. A.; Russell, J. E., Sr.

    1988-01-01

    The Cellular Access Digital Network (CADN) is the access vehicle through which cellular technology is brought into the mainstream of the evolving integrated telecommunications network. Beyond the integrated end-to-end digital access and per call network services provisioning of the Integrated Services Digital Network (ISDN), the CADN engenders the added capability of mobility freedom via wireless access. One key element of the CADN network architecture is the standard user to network interface that is independent of RF transmission technology. Since the Mobile Satellite System (MSS) is envisioned to not only complement but also enhance the capabilities of the terrestrial cellular telecommunications network, compatibility and interoperability between terrestrial cellular and mobile satellite systems are vitally important to provide an integrated moving telecommunications network of the future. From a network standpoint, there exist very strong commonalities between the terrestrial cellular system and the mobile satellite system. Therefore, the MSS architecture should be designed as an integral part of the CADN. This paper describes the concept of the CADN, the functional architecture of the MSS, and the user-network interface signaling protocols.

  2. Analysis of blocking rate and bandwidth usage of mobile IPTV services in wireless cellular networks.

    PubMed

    Li, Mingfu

    2014-01-01

    Mobile IPTV services over wireless cellular networks become more and more popular, owing to the significant growth in access bandwidth of wireless cellular networks such as 3G/4G and WiMAX. However, the spectrum resources of wireless cellular networks is rare. How to enhance the spectral efficiency of mobile networks becomes an important issue. Unicast, broadcast, and multicast are the most important transport schemes for offering mobile IPTV services over wireless cellular networks. Therefore, bandwidth usages and blocking rates of unicast, broadcast, and multicast IPTV services were analyzed and compared in this paper. Simulations were also conducted to validate the analytical results. Numerical results demonstrate that the presented analysis is correct, and multicast scheme achieves the best bandwidth usage and blocking rate performance, relative to the other two schemes.

  3. Analysis of Blocking Rate and Bandwidth Usage of Mobile IPTV Services in Wireless Cellular Networks

    PubMed Central

    Li, Mingfu

    2014-01-01

    Mobile IPTV services over wireless cellular networks become more and more popular, owing to the significant growth in access bandwidth of wireless cellular networks such as 3G/4G and WiMAX. However, the spectrum resources of wireless cellular networks is rare. How to enhance the spectral efficiency of mobile networks becomes an important issue. Unicast, broadcast, and multicast are the most important transport schemes for offering mobile IPTV services over wireless cellular networks. Therefore, bandwidth usages and blocking rates of unicast, broadcast, and multicast IPTV services were analyzed and compared in this paper. Simulations were also conducted to validate the analytical results. Numerical results demonstrate that the presented analysis is correct, and multicast scheme achieves the best bandwidth usage and blocking rate performance, relative to the other two schemes. PMID:25379521

  4. Traffic Driven Analysis of Cellular and WiFi Networks

    ERIC Educational Resources Information Center

    Paul, Utpal Kumar

    2012-01-01

    Since the days Internet traffic proliferated, measurement, monitoring and analysis of network traffic have been critical to not only the basic understanding of large networks, but also to seek improvements in resource management, traffic engineering and security. At the current times traffic in wireless local and wide area networks are facing…

  5. Image-based quantitative analysis of gold immunochromatographic strip via cellular neural network approach.

    PubMed

    Zeng, Nianyin; Wang, Zidong; Zineddin, Bachar; Li, Yurong; Du, Min; Xiao, Liang; Liu, Xiaohui; Young, Terry

    2014-05-01

    Gold immunochromatographic strip assay provides a rapid, simple, single-copy and on-site way to detect the presence or absence of the target analyte. This paper aims to develop a method for accurately segmenting the test line and control line of the gold immunochromatographic strip (GICS) image for quantitatively determining the trace concentrations in the specimen, which can lead to more functional information than the traditional qualitative or semi-quantitative strip assay. The canny operator as well as the mathematical morphology method is used to detect and extract the GICS reading-window. Then, the test line and control line of the GICS reading-window are segmented by the cellular neural network (CNN) algorithm, where the template parameters of the CNN are designed by the switching particle swarm optimization (SPSO) algorithm for improving the performance of the CNN. It is shown that the SPSO-based CNN offers a robust method for accurately segmenting the test and control lines, and therefore serves as a novel image methodology for the interpretation of GICS. Furthermore, quantitative comparison is carried out among four algorithms in terms of the peak signal-to-noise ratio. It is concluded that the proposed CNN algorithm gives higher accuracy and the CNN is capable of parallelism and analog very-large-scale integration implementation within a remarkably efficient time.

  6. Effects of cellular homeostatic intrinsic plasticity on dynamical and computational properties of biological recurrent neural networks.

    PubMed

    Naudé, Jérémie; Cessac, Bruno; Berry, Hugues; Delord, Bruno

    2013-09-18

    Homeostatic intrinsic plasticity (HIP) is a ubiquitous cellular mechanism regulating neuronal activity, cardinal for the proper functioning of nervous systems. In invertebrates, HIP is critical for orchestrating stereotyped activity patterns. The functional impact of HIP remains more obscure in vertebrate networks, where higher order cognitive processes rely on complex neural dynamics. The hypothesis has emerged that HIP might control the complexity of activity dynamics in recurrent networks, with important computational consequences. However, conflicting results about the causal relationships between cellular HIP, network dynamics, and computational performance have arisen from machine-learning studies. Here, we assess how cellular HIP effects translate into collective dynamics and computational properties in biological recurrent networks. We develop a realistic multiscale model including a generic HIP rule regulating the neuronal threshold with actual molecular signaling pathways kinetics, Dale's principle, sparse connectivity, synaptic balance, and Hebbian synaptic plasticity (SP). Dynamic mean-field analysis and simulations unravel that HIP sets a working point at which inputs are transduced by large derivative ranges of the transfer function. This cellular mechanism ensures increased network dynamics complexity, robust balance with SP at the edge of chaos, and improved input separability. Although critically dependent upon balanced excitatory and inhibitory drives, these effects display striking robustness to changes in network architecture, learning rates, and input features. Thus, the mechanism we unveil might represent a ubiquitous cellular basis for complex dynamics in neural networks. Understanding this robustness is an important challenge to unraveling principles underlying self-organization around criticality in biological recurrent neural networks.

  7. Cues for cellular assembly of vascular elastin networks

    NASA Astrophysics Data System (ADS)

    Kothapalli, Chandrasekhar R.

    Elastin, a structural protein distributed in the extracellular matrix of vascular tissues is critical to the maintenance of vascular mechanics, besides regulation of cell-signaling pathways involved in injury response and morphogenesis. Thus, congenital absence or disease-mediated degradation of vascular elastin and its malformation within native vessels due to innately poor elastin synthesis by adult vascular cells compromise vascular homeostasis. Current elastin regenerative strategies using tissue engineering principles are limited by the progressive destabilization of tropoelastin mRNA expression in adult vascular cells and the unavailability of scaffolds that can provide cellular cues necessary to up-regulate elastin synthesis and regenerate faithful mimics of native elastin. Since our earlier studies demonstrated the elastogenic utility of hyaluronan (HA)-based cues, we have currently sought to identify a unique set of culture conditions based on HA fragments (0.756-2000 kDa), growth factors (TGF-beta1, IGF-1) and other biomolecules (Cu2+ ions, LOX), which will together enhance synthesis, crosslinking, maturation and fibrous elastin matrix formation by adult SMCs, under both healthy and inflammatory conditions. It was observed that TGF-beta1 (1 ng/mL) together with HA oligomers (0.2 microg/mL) synergistically suppressed SMC proliferation, enhanced tropoelastin (8-fold) and matrix elastin synthesis (5.5-fold), besides improving matrix yield (4.5-fold), possibly by increasing production and activity of lysyl oxidase (LOX). Though addition of IGF-1 alone did not offer any advantage, HA fragments (20-200 kDa) in the presence of IGF-1 stimulated tropoelastin and soluble elastin synthesis more than 2.2-fold, with HMW HA contributing for ˜5-fold increase in crosslinked matrix elastin synthesis. Similarly, 0.1 M of Cu2+ ions, alone or together with HA fragments stimulated synthesis of tropoelastin (4-fold) and crosslinked matrix elastin (4.5-fold), via increases in

  8. A metabolic-transcriptional network links sleep and cellular energetics in the brain.

    PubMed

    Wisor, Jonathan P

    2012-01-01

    This review proposes a mechanistic link between cellular metabolic status, transcriptional regulatory changes and sleep. Sleep loss is associated with changes in cellular metabolic status in the brain. Metabolic sensors responsive to cellular metabolic status regulate the circadian clock transcriptional network. Modifications of the transcriptional activity of circadian clock genes affect sleep/wake state changes. Changes in sleep state reverse sleep loss-induced changes in cellular metabolic status. It is thus proposed that the regulation of circadian clock genes by cellular metabolic sensors is a critical intermediate step in the link between cellular metabolic status and sleep. Studies of this regulatory relationship may offer insights into the function of sleep at the cellular level.

  9. Accurate Identification of MCI Patients via Enriched White-Matter Connectivity Network

    NASA Astrophysics Data System (ADS)

    Wee, Chong-Yaw; Yap, Pew-Thian; Brownyke, Jeffery N.; Potter, Guy G.; Steffens, David C.; Welsh-Bohmer, Kathleen; Wang, Lihong; Shen, Dinggang

    Mild cognitive impairment (MCI), often a prodromal phase of Alzheimer's disease (AD), is frequently considered to be a good target for early diagnosis and therapeutic interventions of AD. Recent emergence of reliable network characterization techniques have made understanding neurological disorders at a whole brain connectivity level possible. Accordingly, we propose a network-based multivariate classification algorithm, using a collection of measures derived from white-matter (WM) connectivity networks, to accurately identify MCI patients from normal controls. An enriched description of WM connections, utilizing six physiological parameters, i.e., fiber penetration count, fractional anisotropy (FA), mean diffusivity (MD), and principal diffusivities (λ 1, λ 2, λ 3), results in six connectivity networks for each subject to account for the connection topology and the biophysical properties of the connections. Upon parcellating the brain into 90 regions-of-interest (ROIs), the average statistics of each ROI in relation to the remaining ROIs are extracted as features for classification. These features are then sieved to select the most discriminant subset of features for building an MCI classifier via support vector machines (SVMs). Cross-validation results indicate better diagnostic power of the proposed enriched WM connection description than simple description with any single physiological parameter.

  10. Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles

    EPA Science Inventory

    With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate t...

  11. Tools and Models for Integrating Multiple Cellular Networks

    SciTech Connect

    Gerstein, Mark

    2015-11-06

    In this grant, we have systematically investigated the integrated networks, which are responsible for the coordination of activity between metabolic pathways in prokaryotes. We have developed several computational tools to analyze the topology of the integrated networks consisting of metabolic, regulatory, and physical interaction networks. The tools are all open-source, and they are available to download from Github, and can be incorporated in the Knowledgebase. Here, we summarize our work as follow. Understanding the topology of the integrated networks is the first step toward understanding its dynamics and evolution. For Aim 1 of this grant, we have developed a novel algorithm to determine and measure the hierarchical structure of transcriptional regulatory networks [1]. The hierarchy captures the direction of information flow in the network. The algorithm is generally applicable to regulatory networks in prokaryotes, yeast and higher organisms. Integrated datasets are extremely beneficial in understanding the biology of a system in a compact manner due to the conflation of multiple layers of information. Therefore for Aim 2 of this grant, we have developed several tools and carried out analysis for integrating system-wide genomic information. To make use of the structural data, we have developed DynaSIN for protein-protein interactions networks with various dynamical interfaces [2]. We then examined the association between network topology with phenotypic effects such as gene essentiality. In particular, we have organized E. coli and S. cerevisiae transcriptional regulatory networks into hierarchies. We then correlated gene phenotypic effects by tinkering with different layers to elucidate which layers were more tolerant to perturbations [3]. In the context of evolution, we also developed a workflow to guide the comparison between different types of biological networks across various species using the concept of rewiring [4], and Furthermore, we have developed

  12. Caenorhabditis elegans metabolic gene regulatory networks govern the cellular economy.

    PubMed

    Watson, Emma; Walhout, Albertha J M

    2014-10-01

    Diet greatly impacts metabolism in health and disease. In response to the presence or absence of specific nutrients, metabolic gene regulatory networks sense the metabolic state of the cell and regulate metabolic flux accordingly, for instance by the transcriptional control of metabolic enzymes. Here, we discuss recent insights regarding metazoan metabolic regulatory networks using the nematode Caenorhabditis elegans as a model, including the modular organization of metabolic gene regulatory networks, the prominent impact of diet on the transcriptome and metabolome, specialized roles of nuclear hormone receptors (NHRs) in responding to dietary conditions, regulation of metabolic genes and metabolic regulators by miRNAs, and feedback between metabolic genes and their regulators.

  13. Almost automorphic solutions for shunting inhibitory cellular neural networks with time-varying delays.

    PubMed

    Xu, Changjin; Liao, Maoxin

    2015-01-01

    This paper is concerned with the shunting inhibitory cellular neural networks with time-varying delays. Under some suitable conditions, we establish some criteria on the existence and global exponential stability of the almost automorphic solutions of the networks. Numerical simulations are given to support the theoretical findings.

  14. Accurate and interpretable classification of microspectroscopy pixels using artificial neural networks.

    PubMed

    Manescu, Petru; Jong Lee, Young; Camp, Charles; Cicerone, Marcus; Brady, Mary; Bajcsy, Peter

    2017-04-01

    This paper addresses the problem of classifying materials from microspectroscopy at a pixel level. The challenges lie in identifying discriminatory spectral features and obtaining accurate and interpretable models relating spectra and class labels. We approach the problem by designing a supervised classifier from a tandem of Artificial Neural Network (ANN) models that identify relevant features in raw spectra and achieve high classification accuracy. The tandem of ANN models is meshed with classification rule extraction methods to lower the model complexity and to achieve interpretability of the resulting model. The contribution of the work is in designing each ANN model based on the microspectroscopy hypothesis about a discriminatory feature of a certain target class being composed of a linear combination of spectra. The novelty lies in meshing ANN and decision rule models into a tandem configuration to achieve accurate and interpretable classification results. The proposed method was evaluated using a set of broadband coherent anti-Stokes Raman scattering (BCARS) microscopy cell images (600 000  pixel-level spectra) and a reference four-class rule-based model previously created by biochemical experts. The generated classification rule-based model was on average 85% accurate measured by the DICE pixel label similarity metric, and on average 96% similar to the reference rules measured by the vector cosine metric.

  15. Networking with noise at the molecular, cellular, and population level

    NASA Astrophysics Data System (ADS)

    Vilar, Jose

    2002-03-01

    The intrinsic stochastic nature of biochemical reactions affects enzymatic and transcriptional networks at different levels. Yet, cells are able to function effectively and consistently amidst such random fluctuations. I will discuss some molecular mechanisms that are able to reduce the intrinsic noise of chemical reactions, how suitable designs can make networks resistant to noise, and what strategies can be used by populations to achieve precise functions.

  16. Detection of silent cells, synchronization and modulatory activity in developing cellular networks.

    PubMed

    Hjorth, Johannes J J; Dawitz, Julia; Kroon, Tim; Pires, Johny; Dassen, Valerie J; Berkhout, Janna A; Emperador Melero, Javier; Nadadhur, Aish G; Alevra, Mihai; Toonen, Ruud F; Heine, Vivi M; Mansvelder, Huibert D; Meredith, Rhiannon M

    2016-04-01

    Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell migration, to the refinement of synapses, topographic maps, and the mature composition of ion channels. These emergent activity patterns are not present in all cells simultaneously within the network and more immature "silent" cells, potentially correlated with the presence of silent synapses, are prominent in different networks during early developmental periods. Many current network analyses for detection of synchronous cellular activity utilize activity-based pixel correlations to identify cellular-based regions of interest (ROIs) and coincident cell activity. However, using activity-based correlations, these methods first underestimate or ignore the inactive silent cells within the developing network and second, are difficult to apply within cell-dense regions commonly found in developing brain networks. In addition, previous methods may ignore ROIs within a network that shows transient activity patterns comprising both inactive and active periods. We developed analysis software to semi-automatically detect cells within developing neuronal networks that were imaged using calcium-sensitive reporter dyes. Using an iterative threshold, modulation of activity was tracked within individual cells across the network. The distribution pattern of both inactive and active, including synchronous cells, could be determined based on distance measures to neighboring cells and according to different anatomical layers.

  17. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    NASA Astrophysics Data System (ADS)

    Overeem, Aart; Uijlenhoet, Remko; Leijnse, Hidde

    2016-04-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. We present a rainfall retrieval algorithm, which is employed to obtain rainfall maps from microwave links in a cellular communication network. We compare these rainfall maps to gauge-adjusted radar rainfall maps. The microwave link data set, as well as the developed code, a package in the open source scripting language "R", are freely available at GitHub (https://github.com/overeem11/RAINLINK). The purpose of this presentation is to promote rainfall mapping utilizing microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

  18. Measurement and interpolation uncertainties in rainfall maps from cellular communication networks

    NASA Astrophysics Data System (ADS)

    Rios Gaona, M. F.; Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-08-01

    Accurate measurements of rainfall are important in many hydrological and meteorological applications, for instance, flash-flood early-warning systems, hydraulic structures design, irrigation, weather forecasting, and climate modelling. Whenever possible, link networks measure and store the received power of the electromagnetic signal at regular intervals. The decrease in power can be converted to rainfall intensity, and is largely due to the attenuation by raindrops along the link paths. Such an alternative technique fulfils the continuous effort to obtain measurements of rainfall in time and space at higher resolutions, especially in places where traditional rain gauge networks are scarce or poorly maintained. Rainfall maps from microwave link networks have recently been introduced at country-wide scales. Despite their potential in rainfall estimation at high spatiotemporal resolutions, the uncertainties present in rainfall maps from link networks are not yet fully comprehended. The aim of this work is to identify and quantify the sources of uncertainty present in interpolated rainfall maps from link rainfall depths. In order to disentangle these sources of uncertainty, we classified them into two categories: (1) those associated with the individual microwave link measurements, i.e. the errors involved in link rainfall retrievals, such as wet antenna attenuation, sampling interval of measurements, wet/dry period classification, dry weather baseline attenuation, quantization of the received power, drop size distribution (DSD), and multi-path propagation; and (2) those associated with mapping, i.e. the combined effect of the interpolation methodology and the spatial density of link measurements. We computed ~ 3500 rainfall maps from real and simulated link rainfall depths for 12 days for the land surface of the Netherlands. Simulated link rainfall depths refer to path-averaged rainfall depths obtained from radar data. The ~ 3500 real and simulated rainfall maps were

  19. Application of Cellular Automata to Detection of Malicious Network Packets

    ERIC Educational Resources Information Center

    Brown, Robert L.

    2014-01-01

    A problem in computer security is identification of attack signatures in network packets. An attack signature is a pattern of bits that characterizes a particular attack. Because there are many kinds of attacks, there are potentially many attack signatures. Furthermore, attackers may seek to avoid detection by altering the attack mechanism so that…

  20. Resource Management in QoS-Aware Wireless Cellular Networks

    ERIC Educational Resources Information Center

    Zhang, Zhi

    2011-01-01

    Emerging broadband wireless networks that support high speed packet data with heterogeneous quality of service (QoS) requirements demand more flexible and efficient use of the scarce spectral resource. Opportunistic scheduling exploits the time-varying, location-dependent channel conditions to achieve multiuser diversity. In this work, we study…

  1. Cellular neural networks, the Navier-Stokes equation, and microarray image reconstruction.

    PubMed

    Zineddin, Bachar; Wang, Zidong; Liu, Xiaohui

    2011-11-01

    Although the last decade has witnessed a great deal of improvements achieved for the microarray technology, many major developments in all the main stages of this technology, including image processing, are still needed. Some hardware implementations of microarray image processing have been proposed in the literature and proved to be promising alternatives to the currently available software systems. However, the main drawback of those proposed approaches is the unsuitable addressing of the quantification of the gene spot in a realistic way without any assumption about the image surface. Our aim in this paper is to present a new image-reconstruction algorithm using the cellular neural network that solves the Navier-Stokes equation. This algorithm offers a robust method for estimating the background signal within the gene-spot region. The MATCNN toolbox for Matlab is used to test the proposed method. Quantitative comparisons are carried out, i.e., in terms of objective criteria, between our approach and some other available methods. It is shown that the proposed algorithm gives highly accurate and realistic measurements in a fully automated manner within a remarkably efficient time.

  2. Frequency-dependent micromechanics of cellularized biopolymer networks

    NASA Astrophysics Data System (ADS)

    Jones, Chris; Kim, Jihan; McIntyre, David; Sun, Bo

    Mechanical interactions between cells and the extracellular matrix (ECM) influence many cellular behaviors such as growth, differentiation, and migration. These are dynamic processes in which the cells actively remodel the ECM. Reconstituted collagen gel is a common model ECM for studying cell-ECM interactions in vitro because collagen is the most abundant component of mammalian ECM and gives the ECM its material stiffness. We embed micron-sized particles in collagen and use holographic optical tweezers to apply forces to the particles in multiple directions and over a range of frequencies up to 10 Hz. We calculate the local compliance and show that it is dependent on both the direction and frequency of the applied force. Performing the same measurement on many particles allows us to characterize the spatial inhomogeneity of the mechanical properties and shows that the compliance decreases at higher frequencies. Performing these measurements on cell-populated collagen gels shows that cellular remodeling of the ECM changes the mechanical properties of the collagen and we investigate whether this change is dependent on the local strain and distance from nearby cells.

  3. Object-Oriented NeuroSys: Parallel Programs for Simulating Large Networks of Biologically Accurate Neurons

    SciTech Connect

    Pacheco, P; Miller, P; Kim, J; Leese, T; Zabiyaka, Y

    2003-05-07

    Object-oriented NeuroSys (ooNeuroSys) is a collection of programs for simulating very large networks of biologically accurate neurons on distributed memory parallel computers. It includes two principle programs: ooNeuroSys, a parallel program for solving the large systems of ordinary differential equations arising from the interconnected neurons, and Neurondiz, a parallel program for visualizing the results of ooNeuroSys. Both programs are designed to be run on clusters and use the MPI library to obtain parallelism. ooNeuroSys also includes an easy-to-use Python interface. This interface allows neuroscientists to quickly develop and test complex neuron models. Both ooNeuroSys and Neurondiz have a design that allows for both high performance and relative ease of maintenance.

  4. High-performance computing and networking as tools for accurate emission computed tomography reconstruction.

    PubMed

    Passeri, A; Formiconi, A R; De Cristofaro, M T; Pupi, A; Meldolesi, U

    1997-04-01

    It is well known that the quantitative potential of emission computed tomography (ECT) relies on the ability to compensate for resolution, attenuation and scatter effects. Reconstruction algorithms which are able to take these effects into account are highly demanding in terms of computing resources. The reported work aimed to investigate the use of a parallel high-performance computing platform for ECT reconstruction taking into account an accurate model of the acquisition of single-photon emission tomographic (SPET) data. An iterative algorithm with an accurate model of the variable system response was ported on the MIMD (Multiple Instruction Multiple Data) parallel architecture of a 64-node Cray T3D massively parallel computer. The system was organized to make it easily accessible even from low-cost PC-based workstations through standard TCP/IP networking. A complete brain study of 30 (64x64) slices could be reconstructed from a set of 90 (64x64) projections with ten iterations of the conjugate gradients algorithm in 9 s, corresponding to an actual speed-up factor of 135. This work demonstrated the possibility of exploiting remote high-performance computing and networking resources from hospital sites by means of low-cost workstations using standard communication protocols without particular problems for routine use. The achievable speed-up factors allow the assessment of the clinical benefit of advanced reconstruction techniques which require a heavy computational burden for the compensation effects such as variable spatial resolution, scatter and attenuation. The possibility of using the same software on the same hardware platform with data acquired in different laboratories with various kinds of SPET instrumentation is appealing for software quality control and for the evaluation of the clinical impact of the reconstruction methods.

  5. Double Cluster Heads Model for Secure and Accurate Data Fusion in Wireless Sensor Networks

    PubMed Central

    Fu, Jun-Song; Liu, Yun

    2015-01-01

    Secure and accurate data fusion is an important issue in wireless sensor networks (WSNs) and has been extensively researched in the literature. In this paper, by combining clustering techniques, reputation and trust systems, and data fusion algorithms, we propose a novel cluster-based data fusion model called Double Cluster Heads Model (DCHM) for secure and accurate data fusion in WSNs. Different from traditional clustering models in WSNs, two cluster heads are selected after clustering for each cluster based on the reputation and trust system and they perform data fusion independently of each other. Then, the results are sent to the base station where the dissimilarity coefficient is computed. If the dissimilarity coefficient of the two data fusion results exceeds the threshold preset by the users, the cluster heads will be added to blacklist, and the cluster heads must be reelected by the sensor nodes in a cluster. Meanwhile, feedback is sent from the base station to the reputation and trust system, which can help us to identify and delete the compromised sensor nodes in time. Through a series of extensive simulations, we found that the DCHM performed very well in data fusion security and accuracy. PMID:25608211

  6. Accurate Monitoring and Fault Detection in Wind Measuring Devices through Wireless Sensor Networks

    PubMed Central

    Khan, Komal Saifullah; Tariq, Muhammad

    2014-01-01

    Many wind energy projects report poor performance as low as 60% of the predicted performance. The reason for this is poor resource assessment and the use of new untested technologies and systems in remote locations. Predictions about the potential of an area for wind energy projects (through simulated models) may vary from the actual potential of the area. Hence, introducing accurate site assessment techniques will lead to accurate predictions of energy production from a particular area. We solve this problem by installing a Wireless Sensor Network (WSN) to periodically analyze the data from anemometers installed in that area. After comparative analysis of the acquired data, the anemometers transmit their readings through a WSN to the sink node for analysis. The sink node uses an iterative algorithm which sequentially detects any faulty anemometer and passes the details of the fault to the central system or main station. We apply the proposed technique in simulation as well as in practical implementation and study its accuracy by comparing the simulation results with experimental results to analyze the variation in the results obtained from both simulation model and implemented model. Simulation results show that the algorithm indicates faulty anemometers with high accuracy and low false alarm rate when as many as 25% of the anemometers become faulty. Experimental analysis shows that anemometers incorporating this solution are better assessed and performance level of implemented projects is increased above 86% of the simulated models. PMID:25421739

  7. Accurate monitoring and fault detection in wind measuring devices through wireless sensor networks.

    PubMed

    Khan, Komal Saifullah; Tariq, Muhammad

    2014-11-24

    Many wind energy projects report poor performance as low as 60% of the predicted performance. The reason for this is poor resource assessment and the use of new untested technologies and systems in remote locations. Predictions about the potential of an area for wind energy projects (through simulated models) may vary from the actual potential of the area. Hence, introducing accurate site assessment techniques will lead to accurate predictions of energy production from a particular area. We solve this problem by installing a Wireless Sensor Network (WSN) to periodically analyze the data from anemometers installed in that area. After comparative analysis of the acquired data, the anemometers transmit their readings through a WSN to the sink node for analysis. The sink node uses an iterative algorithm which sequentially detects any faulty anemometer and passes the details of the fault to the central system or main station. We apply the proposed technique in simulation as well as in practical implementation and study its accuracy by comparing the simulation results with experimental results to analyze the variation in the results obtained from both simulation model and implemented model. Simulation results show that the algorithm indicates faulty anemometers with high accuracy and low false alarm rate when as many as 25% of the anemometers become faulty. Experimental analysis shows that anemometers incorporating this solution are better assessed and performance level of implemented projects is increased above 86% of the simulated models.

  8. Cellular network entropy as the energy potential in Waddington's differentiation landscape.

    PubMed

    Banerji, Christopher R S; Miranda-Saavedra, Diego; Severini, Simone; Widschwendter, Martin; Enver, Tariq; Zhou, Joseph X; Teschendorff, Andrew E

    2013-10-24

    Differentiation is a key cellular process in normal tissue development that is significantly altered in cancer. Although molecular signatures characterising pluripotency and multipotency exist, there is, as yet, no single quantitative mark of a cellular sample's position in the global differentiation hierarchy. Here we adopt a systems view and consider the sample's network entropy, a measure of signaling pathway promiscuity, computable from a sample's genome-wide expression profile. We demonstrate that network entropy provides a quantitative, in-silico, readout of the average undifferentiated state of the profiled cells, recapitulating the known hierarchy of pluripotent, multipotent and differentiated cell types. Network entropy further exhibits dynamic changes in time course differentiation data, and in line with a sample's differentiation stage. In disease, network entropy predicts a higher level of cellular plasticity in cancer stem cell populations compared to ordinary cancer cells. Importantly, network entropy also allows identification of key differentiation pathways. Our results are consistent with the view that pluripotency is a statistical property defined at the cellular population level, correlating with intra-sample heterogeneity, and driven by the degree of signaling promiscuity in cells. In summary, network entropy provides a quantitative measure of a cell's undifferentiated state, defining its elevation in Waddington's landscape.

  9. Logical Modeling and Dynamical Analysis of Cellular Networks

    PubMed Central

    Abou-Jaoudé, Wassim; Traynard, Pauline; Monteiro, Pedro T.; Saez-Rodriguez, Julio; Helikar, Tomáš; Thieffry, Denis; Chaouiya, Claudine

    2016-01-01

    The logical (or logic) formalism is increasingly used to model regulatory and signaling networks. Complementing these applications, several groups contributed various methods and tools to support the definition and analysis of logical models. After an introduction to the logical modeling framework and to several of its variants, we review here a number of recent methodological advances to ease the analysis of large and intricate networks. In particular, we survey approaches to determine model attractors and their reachability properties, to assess the dynamical impact of variations of external signals, and to consistently reduce large models. To illustrate these developments, we further consider several published logical models for two important biological processes, namely the differentiation of T helper cells and the control of mammalian cell cycle. PMID:27303434

  10. Dynamical modeling and analysis of large cellular regulatory networks

    NASA Astrophysics Data System (ADS)

    Bérenguier, D.; Chaouiya, C.; Monteiro, P. T.; Naldi, A.; Remy, E.; Thieffry, D.; Tichit, L.

    2013-06-01

    The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

  11. In-Band Asymmetry Compensation for Accurate Time/Phase Transport over Optical Transport Network

    PubMed Central

    Siu, Sammy; Hu, Hsiu-fang; Lin, Shinn-Yan; Liao, Chia-Shu; Lai, Yi-Liang

    2014-01-01

    The demands of precise time/phase synchronization have been increasing recently due to the next generation of telecommunication synchronization. This paper studies the issues that are relevant to distributing accurate time/phase over optical transport network (OTN). Each node and link can introduce asymmetry, which affects the adequate time/phase accuracy over the networks. In order to achieve better accuracy, protocol level full timing support is used (e.g., Telecom-Boundary clock). Due to chromatic dispersion, the use of different wavelengths consequently causes fiber link delay asymmetry. The analytical result indicates that it introduces significant time error (i.e., phase offset) within 0.3397 ns/km in C-band or 0.3943 ns/km in L-band depending on the wavelength spacing. With the proposed scheme in this paper, the fiber link delay asymmetry can be compensated relying on the estimated mean fiber link delay by the Telecom-Boundary clock, while the OTN control plane is responsible for processing the fiber link delay asymmetry to determine the asymmetry compensation in the timing chain. PMID:24982948

  12. Mechanical models of the cellular cytoskeletal network for the analysis of intracellular mechanical properties and force distributions: a review.

    PubMed

    Chen, Ting-Jung; Wu, Chia-Ching; Su, Fong-Chin

    2012-12-01

    The cytoskeleton, which is the major mechanical component of cells, supports the cell body and regulates the cellular motility to assist the cell in performing its biological functions. Several cytoskeletal network models have been proposed to investigate the mechanical properties of cells. This review paper summarizes these models with a focus on the prestressed cable network, the semi-flexible chain network, the open-cell foam, the tensegrity, and the granular models. The components, material parameters, types of connection joints, tension conditions, and the advantages and disadvantages of each model are evaluated from a structural and biological point of view. The underlying mechanisms that are associated with the morphological changes of spreading cells are expected to be simulated using a cytoskeletal model; however, it is still paid less attention most likely due to the lack of a suitable cytoskeletal model that can accurately model the spreading process. In this review article, the established cytoskeletal models are hoped to provide useful information for the development of future cytoskeletal models with different degrees of cell attachment for the study of the mechanical mechanisms underlying the cellular behaviors in response to external stimulations.

  13. Molecular Signaling Network Motifs Provide a Mechanistic Basis for Cellular Threshold Responses

    PubMed Central

    Bhattacharya, Sudin; Conolly, Rory B.; Clewell, Harvey J.; Kaminski, Norbert E.; Andersen, Melvin E.

    2014-01-01

    Background: Increasingly, there is a move toward using in vitro toxicity testing to assess human health risk due to chemical exposure. As with in vivo toxicity testing, an important question for in vitro results is whether there are thresholds for adverse cellular responses. Empirical evaluations may show consistency with thresholds, but the main evidence has to come from mechanistic considerations. Objectives: Cellular response behaviors depend on the molecular pathway and circuitry in the cell and the manner in which chemicals perturb these circuits. Understanding circuit structures that are inherently capable of resisting small perturbations and producing threshold responses is an important step towards mechanistically interpreting in vitro testing data. Methods: Here we have examined dose–response characteristics for several biochemical network motifs. These network motifs are basic building blocks of molecular circuits underpinning a variety of cellular functions, including adaptation, homeostasis, proliferation, differentiation, and apoptosis. For each motif, we present biological examples and models to illustrate how thresholds arise from specific network structures. Discussion and Conclusion: Integral feedback, feedforward, and transcritical bifurcation motifs can generate thresholds. Other motifs (e.g., proportional feedback and ultrasensitivity)produce responses where the slope in the low-dose region is small and stays close to the baseline. Feedforward control may lead to nonmonotonic or hormetic responses. We conclude that network motifs provide a basis for understanding thresholds for cellular responses. Computational pathway modeling of these motifs and their combinations occurring in molecular signaling networks will be a key element in new risk assessment approaches based on in vitro cellular assays. Citation: Zhang Q, Bhattacharya S, Conolly RB, Clewell HJ III, Kaminski NE, Andersen ME. 2014. Molecular signaling network motifs provide a

  14. A new cellular automaton model for urban two-way road networks.

    PubMed

    Shi, Junqing; Cheng, Lin; Long, Jiancheng; Liu, Yuanlin

    2014-01-01

    A new cellular automaton (CA) model is proposed to simulate traffic dynamics in urban two-way road network systems. The NaSch rule is adopted to represent vehicle movements on road sections. Two novel rules are proposed to move the vehicles in intersection areas, and an additional rule is developed to avoid the "gridlock" phenomenon. Simulation results show that the network fundamental diagram is very similar to that of road traffic flow. We found that the randomization probability and the maximum vehicle speed have significant impact on network traffic mobility for free-flow state. Their effect may be weak when the network is congested.

  15. A New Cellular Automaton Model for Urban Two-Way Road Networks

    PubMed Central

    Shi, Junqing; Cheng, Lin; Liu, Yuanlin

    2014-01-01

    A new cellular automaton (CA) model is proposed to simulate traffic dynamics in urban two-way road network systems. The NaSch rule is adopted to represent vehicle movements on road sections. Two novel rules are proposed to move the vehicles in intersection areas, and an additional rule is developed to avoid the “gridlock” phenomenon. Simulation results show that the network fundamental diagram is very similar to that of road traffic flow. We found that the randomization probability and the maximum vehicle speed have significant impact on network traffic mobility for free-flow state. Their effect may be weak when the network is congested. PMID:25435868

  16. Intrinsic Cellular Properties and Connectivity Density Determine Variable Clustering Patterns in Randomly Connected Inhibitory Neural Networks.

    PubMed

    Rich, Scott; Booth, Victoria; Zochowski, Michal

    2016-01-01

    The plethora of inhibitory interneurons in the hippocampus and cortex play a pivotal role in generating rhythmic activity by clustering and synchronizing cell firing. Results of our simulations demonstrate that both the intrinsic cellular properties of neurons and the degree of network connectivity affect the characteristics of clustered dynamics exhibited in randomly connected, heterogeneous inhibitory networks. We quantify intrinsic cellular properties by the neuron's current-frequency relation (IF curve) and Phase Response Curve (PRC), a measure of how perturbations given at various phases of a neurons firing cycle affect subsequent spike timing. We analyze network bursting properties of networks of neurons with Type I or Type II properties in both excitability and PRC profile; Type I PRCs strictly show phase advances and IF curves that exhibit frequencies arbitrarily close to zero at firing threshold while Type II PRCs display both phase advances and delays and IF curves that have a non-zero frequency at threshold. Type II neurons whose properties arise with or without an M-type adaptation current are considered. We analyze network dynamics under different levels of cellular heterogeneity and as intrinsic cellular firing frequency and the time scale of decay of synaptic inhibition are varied. Many of the dynamics exhibited by these networks diverge from the predictions of the interneuron network gamma (ING) mechanism, as well as from results in all-to-all connected networks. Our results show that randomly connected networks of Type I neurons synchronize into a single cluster of active neurons while networks of Type II neurons organize into two mutually exclusive clusters segregated by the cells' intrinsic firing frequencies. Networks of Type II neurons containing the adaptation current behave similarly to networks of either Type I or Type II neurons depending on network parameters; however, the adaptation current creates differences in the cluster dynamics

  17. Intrinsic Cellular Properties and Connectivity Density Determine Variable Clustering Patterns in Randomly Connected Inhibitory Neural Networks

    PubMed Central

    Rich, Scott; Booth, Victoria; Zochowski, Michal

    2016-01-01

    The plethora of inhibitory interneurons in the hippocampus and cortex play a pivotal role in generating rhythmic activity by clustering and synchronizing cell firing. Results of our simulations demonstrate that both the intrinsic cellular properties of neurons and the degree of network connectivity affect the characteristics of clustered dynamics exhibited in randomly connected, heterogeneous inhibitory networks. We quantify intrinsic cellular properties by the neuron's current-frequency relation (IF curve) and Phase Response Curve (PRC), a measure of how perturbations given at various phases of a neurons firing cycle affect subsequent spike timing. We analyze network bursting properties of networks of neurons with Type I or Type II properties in both excitability and PRC profile; Type I PRCs strictly show phase advances and IF curves that exhibit frequencies arbitrarily close to zero at firing threshold while Type II PRCs display both phase advances and delays and IF curves that have a non-zero frequency at threshold. Type II neurons whose properties arise with or without an M-type adaptation current are considered. We analyze network dynamics under different levels of cellular heterogeneity and as intrinsic cellular firing frequency and the time scale of decay of synaptic inhibition are varied. Many of the dynamics exhibited by these networks diverge from the predictions of the interneuron network gamma (ING) mechanism, as well as from results in all-to-all connected networks. Our results show that randomly connected networks of Type I neurons synchronize into a single cluster of active neurons while networks of Type II neurons organize into two mutually exclusive clusters segregated by the cells' intrinsic firing frequencies. Networks of Type II neurons containing the adaptation current behave similarly to networks of either Type I or Type II neurons depending on network parameters; however, the adaptation current creates differences in the cluster dynamics

  18. Antenna modeling considerations for accurate SAR calculations in human phantoms in close proximity to GSM cellular base station antennas.

    PubMed

    van Wyk, Marnus J; Bingle, Marianne; Meyer, Frans J C

    2005-09-01

    International bodies such as International Commission on Non-Ionizing Radiation Protection (ICNIRP) and the Institute for Electrical and Electronic Engineering (IEEE) make provision for human exposure assessment based on SAR calculations (or measurements) and basic restrictions. In the case of base station exposure this is mostly applicable to occupational exposure scenarios in the very near field of these antennas where the conservative reference level criteria could be unnecessarily restrictive. This study presents a variety of critical aspects that need to be considered when calculating SAR in a human body close to a mobile phone base station antenna. A hybrid FEM/MoM technique is proposed as a suitable numerical method to obtain accurate results. The verification of the FEM/MoM implementation has been presented in a previous publication; the focus of this study is an investigation into the detail that must be included in a numerical model of the antenna, to accurately represent the real-world scenario. This is accomplished by comparing numerical results to measurements for a generic GSM base station antenna and appropriate, representative canonical and human phantoms. The results show that it is critical to take the disturbance effect of the human phantom (a large conductive body) on the base station antenna into account when the antenna-phantom spacing is less than 300 mm. For these small spacings, the antenna structure must be modeled in detail. The conclusion is that it is feasible to calculate, using the proposed techniques and methodology, accurate occupational compliance zones around base station antennas based on a SAR profile and basic restriction guidelines.

  19. [Construction and structural analysis of integrated cellular network of Corynebacterium glutamicum].

    PubMed

    Jiang, Jinguo; Song, Lifu; Zheng, Ping; Jia, Shiru; Sun, Jibin

    2012-05-01

    Corynebacterium glutamicum is one of the most important traditional industrial microorganisms and receiving more and more attention towards a novel cellular factory due to the recently rapid development in genomics and genetic operation toolboxes for Corynebacterium. However, compared to other model organisms such as Escherichia coli, there were few studies on its metabolic regulation, especially a genome-scale integrated cellular network model currently missing for Corynebacterium, which hindered the systematic study of Corynebacterium glutamicum and large-scale rational design and optimization for strains. Here, by gathering relevant information from a number of public databases, we successfully constructed an integrated cellular network, which was composed of 1384 reactions, 1276 metabolites, 88 transcriptional factors and 999 pairs of transcriptional regulatory relationships. The transcriptional regulatory sub-network could be arranged into five layers and the metabolic sub-network presented a clear bow-tie structure. We proposed a new method to extract complex metabolic and regulatory sub-network for product-orientated study taking lysine biosynthesis as an example. The metabolic and regulatory sub-network extracted by our method was more close to the real functional network than the simplex biochemical pathways. The results would be greatly helpful for understanding the high-yielding biomechanism for amino acids and the re-design of the industrial strains.

  20. Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks.

    PubMed

    Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

    2016-11-22

    Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

  1. Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

    NASA Astrophysics Data System (ADS)

    Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

    2016-11-01

    Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

  2. Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

    PubMed Central

    Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

    2016-01-01

    Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability. PMID:27874024

  3. Modeling psychiatric disorders at the cellular and network levels.

    PubMed

    Brennand, K J; Simone, A; Tran, N; Gage, F H

    2012-12-01

    Although psychiatric disorders such as autism spectrum disorders, schizophrenia and bipolar disorder affect a number of brain regions and produce a complex array of clinical symptoms, basic phenotypes likely exist at the level of single neurons and simple networks. Being highly heritable, it is hypothesized that these disorders are amenable to cell-based studies in vitro. Using induced pluripotent stem cell-derived neurons and/or induced neurons from fibroblasts, limitless numbers of live human neurons can now be generated from patients with a genetic background permissive to the disease state. We predict that cell-based studies will ultimately contribute to our understanding of the initiation, progression and treatment of these psychiatric disorders.

  4. Accurate prediction of cellular co-translational folding indicates proteins can switch from post- to co-translational folding

    NASA Astrophysics Data System (ADS)

    Nissley, Daniel A.; Sharma, Ajeet K.; Ahmed, Nabeel; Friedrich, Ulrike A.; Kramer, Günter; Bukau, Bernd; O'Brien, Edward P.

    2016-02-01

    The rates at which domains fold and codons are translated are important factors in determining whether a nascent protein will co-translationally fold and function or misfold and malfunction. Here we develop a chemical kinetic model that calculates a protein domain's co-translational folding curve during synthesis using only the domain's bulk folding and unfolding rates and codon translation rates. We show that this model accurately predicts the course of co-translational folding measured in vivo for four different protein molecules. We then make predictions for a number of different proteins in yeast and find that synonymous codon substitutions, which change translation-elongation rates, can switch some protein domains from folding post-translationally to folding co-translationally--a result consistent with previous experimental studies. Our approach explains essential features of co-translational folding curves and predicts how varying the translation rate at different codon positions along a transcript's coding sequence affects this self-assembly process.

  5. Characterization of one-dimensional cellular automata rules through topological network features

    NASA Astrophysics Data System (ADS)

    D'Alotto, Lou; Pizzuti, Clara

    2016-10-01

    The paper investigates the relationship between the classification schemes, defined by Wolfram and Gilman, of one-dimensional cellular automata through concepts coming from network theory. An automaton is represented with a network, generated from the elementary rule defining its behavior. Characteristic features of this graph are computed and machine learning classification models are built. Such models allow to classify automaton rules and to compare Wolfram's and Gilman's classes by comparing the classes predicted by these models.

  6. A mathematical model to study the dynamics of epithelial cellular networks.

    PubMed

    Abate, Alessandro; Vincent, Stéphane; Dobbe, Roel; Silletti, Alberto; Master, Neal; Axelrod, Jeffrey D; Tomlin, Claire J

    2012-01-01

    Epithelia are sheets of connected cells that are essential across the animal kingdom. Experimental observations suggest that the dynamical behavior of many single-layered epithelial tissues has strong analogies with that of specific mechanical systems, namely large networks consisting of point masses connected through spring-damper elements and undergoing the influence of active and dissipating forces. Based on this analogy, this work develops a modeling framework to enable the study of the mechanical properties and of the dynamic behavior of large epithelial cellular networks. The model is built first by creating a network topology that is extracted from the actual cellular geometry as obtained from experiments, then by associating a mechanical structure and dynamics to the network via spring-damper elements. This scalable approach enables running simulations of large network dynamics: the derived modeling framework in particular is predisposed to be tailored to study general dynamics (for example, morphogenesis) of various classes of single-layered epithelial cellular networks. In this contribution, we test the model on a case study of the dorsal epithelium of the Drosophila melanogaster embryo during early dorsal closure (and, less conspicuously, germband retraction).

  7. Accurate prediction of cellular co-translational folding indicates proteins can switch from post- to co-translational folding

    PubMed Central

    Nissley, Daniel A.; Sharma, Ajeet K.; Ahmed, Nabeel; Friedrich, Ulrike A.; Kramer, Günter; Bukau, Bernd; O'Brien, Edward P.

    2016-01-01

    The rates at which domains fold and codons are translated are important factors in determining whether a nascent protein will co-translationally fold and function or misfold and malfunction. Here we develop a chemical kinetic model that calculates a protein domain's co-translational folding curve during synthesis using only the domain's bulk folding and unfolding rates and codon translation rates. We show that this model accurately predicts the course of co-translational folding measured in vivo for four different protein molecules. We then make predictions for a number of different proteins in yeast and find that synonymous codon substitutions, which change translation-elongation rates, can switch some protein domains from folding post-translationally to folding co-translationally—a result consistent with previous experimental studies. Our approach explains essential features of co-translational folding curves and predicts how varying the translation rate at different codon positions along a transcript's coding sequence affects this self-assembly process. PMID:26887592

  8. Multi-Cell Cooperation with Fairness Constraint in the Downlink OFDMA Cellular Networks

    NASA Astrophysics Data System (ADS)

    Li, Hongxing; Luo, Hanwen; Chen, Wen; Guo, Jia

    In this letter, we study cell cooperation in the downlink OFDMA cellular networks. The proposed cooperation scheme is based on fractional frequency reuse (FFR), where a cooperation group consists of three sector antennas from three adjacent cells and the subchannels of each cooperation group are allocated coordinately to users. Simulation results demonstrate the effectiveness of the proposed schemes in terms of throughput and fairness.

  9. Efficient construction of robust artificial neural networks for accurate determination of superficial sample optical properties.

    PubMed

    Chen, Yu-Wen; Tseng, Sheng-Hao

    2015-03-01

    In general, diffuse reflectance spectroscopy (DRS) systems work with photon diffusion models to determine the absorption coefficient μa and reduced scattering coefficient μs' of turbid samples. However, in some DRS measurement scenarios, such as using short source-detector separations to investigate superficial tissues with comparable μa and μs', photon diffusion models might be invalid or might not have analytical solutions. In this study, a systematic workflow of constructing a rapid, accurate photon transport model that is valid at short source-detector separations (SDSs) and at a wide range of sample albedo is revealed. To create such a model, we first employed a GPU (Graphic Processing Unit) based Monte Carlo model to calculate the reflectance at various sample optical property combinations and established a database at high speed. The database was then utilized to train an artificial neural network (ANN) for determining the sample absorption and reduced scattering coefficients from the reflectance measured at several SDSs without applying spectral constraints. The robustness of the produced ANN model was rigorously validated. We evaluated the performance of a successfully trained ANN using tissue simulating phantoms. We also determined the 500-1000 nm absorption and reduced scattering spectra of in-vivo skin using our ANN model and found that the values agree well with those reported in several independent studies.

  10. Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network

    NASA Astrophysics Data System (ADS)

    Ben Ali, Jaouher; Chebel-Morello, Brigitte; Saidi, Lotfi; Malinowski, Simon; Fnaiech, Farhat

    2015-05-01

    Accurate remaining useful life (RUL) prediction of critical assets is an important challenge in condition based maintenance to improve reliability and decrease machine's breakdown and maintenance's cost. Bearing is one of the most important components in industries which need to be monitored and the user should predict its RUL. The challenge of this study is to propose an original feature able to evaluate the health state of bearings and to estimate their RUL by Prognostics and Health Management (PHM) techniques. In this paper, the proposed method is based on the data-driven prognostic approach. The combination of Simplified Fuzzy Adaptive Resonance Theory Map (SFAM) neural network and Weibull distribution (WD) is explored. WD is used just in the training phase to fit measurement and to avoid areas of fluctuation in the time domain. SFAM training process is based on fitted measurements at present and previous inspection time points as input. However, the SFAM testing process is based on real measurements at present and previous inspections. Thanks to the fuzzy learning process, SFAM has an important ability and a good performance to learn nonlinear time series. As output, seven classes are defined; healthy bearing and six states for bearing degradation. In order to find the optimal RUL prediction, a smoothing phase is proposed in this paper. Experimental results show that the proposed method can reliably predict the RUL of rolling element bearings (REBs) based on vibration signals. The proposed prediction approach can be applied to prognostic other various mechanical assets.

  11. Identification of driving network of cellular differentiation from single sample time course gene expression data

    NASA Astrophysics Data System (ADS)

    Chen, Ye; Wolanyk, Nathaniel; Ilker, Tunc; Gao, Shouguo; Wang, Xujing

    Methods developed based on bifurcation theory have demonstrated their potential in driving network identification for complex human diseases, including the work by Chen, et al. Recently bifurcation theory has been successfully applied to model cellular differentiation. However, there one often faces a technical challenge in driving network prediction: time course cellular differentiation study often only contains one sample at each time point, while driving network prediction typically require multiple samples at each time point to infer the variation and interaction structures of candidate genes for the driving network. In this study, we investigate several methods to identify both the critical time point and the driving network through examination of how each time point affects the autocorrelation and phase locking. We apply these methods to a high-throughput sequencing (RNA-Seq) dataset of 42 subsets of thymocytes and mature peripheral T cells at multiple time points during their differentiation (GSE48138 from GEO). We compare the predicted driving genes with known transcription regulators of cellular differentiation. We will discuss the advantages and limitations of our proposed methods, as well as potential further improvements of our methods.

  12. Cooperative Game-Based Energy Efficiency Management over Ultra-Dense Wireless Cellular Networks

    PubMed Central

    Li, Ming; Chen, Pengpeng; Gao, Shouwan

    2016-01-01

    Ultra-dense wireless cellular networks have been envisioned as a promising technique for handling the explosive increase of wireless traffic volume. With the extensive deployment of small cells in wireless cellular networks, the network spectral efficiency (SE) is improved with the use of limited frequency. However, the mutual inter-tier and intra-tier interference between or among small cells and macro cells becomes serious. On the other hand, more chances for potential cooperation among different cells are introduced. Energy efficiency (EE) has become one of the most important problems for future wireless networks. This paper proposes a cooperative bargaining game-based method for comprehensive EE management in an ultra-dense wireless cellular network, which highlights the complicated interference influence on energy-saving challenges and the power-coordination process among small cells and macro cells. Especially, a unified EE utility with the consideration of the interference mitigation is proposed to jointly address the SE, the deployment efficiency (DE), and the EE. In particular, closed-form power-coordination solutions for the optimal EE are derived to show the convergence property of the algorithm. Moreover, a simplified algorithm is presented to reduce the complexity of the signaling overhead, which is significant for ultra-dense small cells. Finally, numerical simulations are provided to illustrate the efficiency of the proposed cooperative bargaining game-based and simplified schemes. PMID:27649170

  13. Cooperative Game-Based Energy Efficiency Management over Ultra-Dense Wireless Cellular Networks.

    PubMed

    Li, Ming; Chen, Pengpeng; Gao, Shouwan

    2016-09-13

    Ultra-dense wireless cellular networks have been envisioned as a promising technique for handling the explosive increase of wireless traffic volume. With the extensive deployment of small cells in wireless cellular networks, the network spectral efficiency (SE) is improved with the use of limited frequency. However, the mutual inter-tier and intra-tier interference between or among small cells and macro cells becomes serious. On the other hand, more chances for potential cooperation among different cells are introduced. Energy efficiency (EE) has become one of the most important problems for future wireless networks. This paper proposes a cooperative bargaining game-based method for comprehensive EE management in an ultra-dense wireless cellular network, which highlights the complicated interference influence on energy-saving challenges and the power-coordination process among small cells and macro cells. Especially, a unified EE utility with the consideration of the interference mitigation is proposed to jointly address the SE, the deployment efficiency (DE), and the EE. In particular, closed-form power-coordination solutions for the optimal EE are derived to show the convergence property of the algorithm. Moreover, a simplified algorithm is presented to reduce the complexity of the signaling overhead, which is significant for ultra-dense small cells. Finally, numerical simulations are provided to illustrate the efficiency of the proposed cooperative bargaining game-based and simplified schemes.

  14. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    NASA Astrophysics Data System (ADS)

    Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-08-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm and provide the corresponding code. Moreover, the code (in the scripting language "R") is made available including a data set of commercial microwave links. The purpose of this paper is to promote rainfall monitoring utilizing microwave links from cellular communication networks as an alternative or complementary means for global, continental-scale rainfall monitoring.

  15. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    NASA Astrophysics Data System (ADS)

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2016-06-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide (≈ 35 500 km2) 15 min rainfall maps can be derived from the signal attenuations of approximately 2400 microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm. Moreover, the documented, modular, and user-friendly code (a package in the scripting language "R") is made available, including a 2-day data set of approximately 2600 commercial microwave links from the Netherlands. The purpose of this paper is to promote rainfall mapping utilising microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

  16. Almost Periodic Dynamics for Memristor-Based Shunting Inhibitory Cellular Neural Networks with Leakage Delays

    PubMed Central

    Lu, Lin

    2016-01-01

    We investigate a class of memristor-based shunting inhibitory cellular neural networks with leakage delays. By applying a new Lyapunov function method, we prove that the neural network which has a unique almost periodic solution is globally exponentially stable. Moreover, the theoretical findings of this paper on the almost periodic solution are applied to prove the existence and stability of periodic solution for memristor-based shunting inhibitory cellular neural networks with leakage delays and periodic coefficients. An example is given to illustrate the effectiveness of the theoretical results. The results obtained in this paper are completely new and complement the previously known studies of Wu (2011) and Chen and Cao (2002). PMID:27840634

  17. Hardware Implementation of a Desktop Supercomputer for High Performance Image Processing. Color Image Processing Using Cellular Neural Networks

    DTIC Science & Technology

    1994-11-01

    This report addresses the functional behavior of Cellular Neural Networks (CNN). The impact of variable convergence times on the proper operation of...The report discusses the new fault model, presents the algorithmic procedures and shows simulated testing results. Cellular neural Networks , Testing.

  18. Quantum complexity: Quantum mutual information, complex networks, and emergent phenomena in quantum cellular automata

    NASA Astrophysics Data System (ADS)

    Vargas, David L.

    Emerging quantum simulator technologies provide a new challenge to quantum many body theory. Quantifying the emergent order in and predicting the dynamics of such complex quantum systems requires a new approach. We develop such an approach based on complex network analysis of quantum mutual information. First, we establish the usefulness of quantum mutual information complex networks by reproducing the phase diagrams of transverse Ising and Bose-Hubbard models. By quantifying the complexity of quantum cellular automata we then demonstrate the applicability of complex network theory to non-equilibrium quantum dynamics. We conclude with a study of student collaboration networks, correlating a student's role in a collaboration network with their grades. This work thus initiates a quantitative theory of quantum complexity and provides a new tool for physics education research. (Abstract shortened by ProQuest.).

  19. Cellular automata with object-oriented features for parallel molecular network modeling.

    PubMed

    Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

    2005-06-01

    Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

  20. Network Biomarkers Constructed from Gene Expression and Protein-Protein Interaction Data for Accurate Prediction of Leukemia

    PubMed Central

    Yuan, Xuye; Chen, Jiajia; Lin, Yuxin; Li, Yin; Xu, Lihua; Chen, Luonan; Hua, Haiying; Shen, Bairong

    2017-01-01

    Leukemia is a leading cause of cancer deaths in the developed countries. Great efforts have been undertaken in search of diagnostic biomarkers of leukemia. However, leukemia is highly complex and heterogeneous, involving interaction among multiple molecular components. Individual molecules are not necessarily sensitive diagnostic indicators. Network biomarkers are considered to outperform individual molecules in disease characterization. We applied an integrative approach that identifies active network modules as putative biomarkers for leukemia diagnosis. We first reconstructed the leukemia-specific PPI network using protein-protein interactions from the Protein Interaction Network Analysis (PINA) and protein annotations from GeneGo. The network was further integrated with gene expression profiles to identify active modules with leukemia relevance. Finally, the candidate network-based biomarker was evaluated for the diagnosing performance. A network of 97 genes and 400 interactions was identified for accurate diagnosis of leukemia. Functional enrichment analysis revealed that the network biomarkers were enriched in pathways in cancer. The network biomarkers could discriminate leukemia samples from the normal controls more effectively than the known biomarkers. The network biomarkers provide a useful tool to diagnose leukemia and also aids in further understanding the molecular basis of leukemia. PMID:28243332

  1. The role of field coupling in nano-scale cellular nonlinear networks.

    PubMed

    Porod, Wolfgang; Csaba, Gyorgy; Csurgay, Arpad

    2003-12-01

    We review some of our previous work on field-coupling in nano-scale cellular arrays. Electronic devices based on metallic and magnetic nanoscale dots and molecular structures have been suggested, however, no technologically viable architecture for nanoelectronic circuit integration has emerged so far. A natural architecture on the nanoscale appears to be near-neighbor cellular networking, and we explore promising alternative ways of integrating nanodevices by direct physical field coupling, i.e. either by Coulomb or by magnetic interactions. We review new architectures for such field-coupled nanocircuits.

  2. Position and Velocity Tracking in Cellular Networks Using the Kalman Filter

    SciTech Connect

    Olama, Mohammed M; Djouadi, Seddik M; Kuruganti, Phani Teja

    2009-01-01

    Access to the right information anytime, anywhere is becoming the new driving force for the information technology revolution. The 'right' information's relevance is based on the user's profile and his/her current geographical position and/or time. Location Based Service (LBS) is an innovative technology that provides information or makes information available based on the geographical location of the mobile user. Analysts predict that LBSs will lead to new applications, generating billions of US dollars worldwide (Leite, 2001; Searle, 2001). The need for an efficient and accurate mobile station (MS) positioning system is growing day by day. The ability to pinpoint the location of an individual has an obvious and vital value in the context of emergency services (Chan, 2003; Olama et al., 2008). Pinpointing the location of people and other valuable assets also opens the door to a new world of previously unimagined information services and m-commerce probabilities. For example, availability of services like 'Where is the nearest ATM?', 'Check traffic conditions on the highway on my route', 'Find a parking lot nearby', as well as answers to 'Where is my advisor?', and 'Where is my car?' will be an everyday rule in our lives (Charalambous & Panayiotou, 2004). A technology independent LBS architecture can be considered as comprised by three main parts (Girodon, 2002): A user requesting information, a mobile network operator and its partners, and several content providers (e.g. data, maps). The subscriber requests a personalized service dependant on his geographic location. The system will ask the Location Services Manager (which is in charge of handling requests, i.e., send/receive to the Location Calculator and the Content Providers) to pinpoint the location of the mobile. The Location Services Manager (LSM), using the Location Calculator, will ask the Content Provider (CP) to supply qualified information according to the mobile's geographical position. The LSM will

  3. Cellular and Network Contributions to Excitability of Layer 5 Neocortical Pyramidal Neurons in the Rat

    PubMed Central

    Bar-Yehuda, Dan; Korngreen, Alon

    2007-01-01

    There is a considerable gap between investigating the dynamics of single neurons and the computational aspects of neural networks. A growing number of studies have attempted to overcome this gap using the excitation in brain slices elicited by various chemical manipulations of the bath solution. However, there has been no quantitative study on the effects of these manipulations on the cellular and network factors controlling excitability. Using the whole-cell configuration of the patch-clamp technique we recorded the membrane potential from the soma of layer 5 pyramidal neurons in acute brain slices from the somatosensory cortex of young rats at 22°C and 35°C. Using blockers of synaptic transmission, we show distinct changes in cellular properties following modification of the ionic composition of the artificial cerebrospinal fluid (ACSF). Thus both cellular and network changes may contribute to the observed effects of slice excitation solutions on the physiology of single neurons. Furthermore, our data suggest that the difference in the ionic composition of current standard ACSF from that of CSF measured in vivo cause ACSF to depress network activity in acute brain slices. This may affect outcomes of experiments investigating biophysical and physiological properties of neurons in such preparations. Our results strongly advocate the necessity of redesigning experiments routinely carried out in the quiescent acute brain slice preparation. PMID:18030343

  4. Joint Mode Selection and Resource Allocation for Cellular Controlled Short-Range Communication in OFDMA Networks

    NASA Astrophysics Data System (ADS)

    Deng, Hui; Tao, Xiaoming; Ge, Ning; Lu, Jianhua

    This letter studies cellular controlled short-range communication in OFDMA networks. The network needs to decide when to allow direct communication between a closely located device-to-device (D2D) pair instead of conveying data from one device to the other via the base station and when not to, in addition to subchannel and power allocation. Our goal is to maximize the total network throughput while guaranteeing the rate requirements of all users. For that purpose, we formulate an optimization problem subject to subchannel and power constraints. A scheme which combines a joint mode selection and subchannel allocation algorithm based on equal power allocation with a power reallocation scheme is proposed. Simulation results show that our proposed scheme can improve the network throughput and outage probability compared with other schemes.

  5. Adding learning to cellular genetic algorithms for training recurrent neural networks.

    PubMed

    Ku, K W; Mak, M W; Siu, W C

    1999-01-01

    This paper proposes a hybrid optimization algorithm which combines the efforts of local search (individual learning) and cellular genetic algorithms (GA's) for training recurrent neural networks (RNN's). Each weight of an RNN is encoded as a floating point number, and a concatenation of the numbers forms a chromosome. Reproduction takes place locally in a square grid with each grid point representing a chromosome. Two approaches, Lamarckian and Baldwinian mechanisms, for combining cellular GA's and learning have been compared. Different hill-climbing algorithms are incorporated into the cellular GA's as learning methods. These include the real-time recurrent learning (RTRL) and its simplified versions, and the delta rule. The RTRL algorithm has been successively simplified by freezing some of the weights to form simplified versions. The delta rule, which is the simplest form of learning, has been implemented by considering the RNN's as feedforward networks during learning. The hybrid algorithms are used to train the RNN's to solve a long-term dependency problem. The results show that Baldwinian learning is inefficient in assisting the cellular GA. It is conjectured that the more difficult it is for genetic operations to produce the genotypic changes that match the phenotypic changes due to learning, the poorer is the convergence of Baldwinian learning. Most of the combinations using the Lamarckian mechanism show an improvement in reducing the number of generations required for an optimum network; however, only a few can reduce the actual time taken. Embedding the delta rule in the cellular GA's has been found to be the fastest method. It is also concluded that learning should not be too extensive if the hybrid algorithm is to be benefit from learning.

  6. Complete stability of cellular neural networks with unbounded time-varying delays.

    PubMed

    Wang, Lili; Chen, Tianping

    2012-12-01

    In this paper, we are concerned with the delayed cellular neural networks (DCNNs) in the case that the time-varying delays are unbounded. Under some conditions, it shows that the DCNNs can exhibit 3(n) equilibrium points. Then, we track the dynamics of u(t)(t>0) in two cases with respect to different types of subset regions in which u(0) is located. It concludes that every solution trajectory u(t) would converge to one of the equilibrium points despite the time-varying delays, that is, the delayed cellular neural networks are completely stable. The method is novel and the results obtained extend the existing ones. In addition, two illustrative examples are presented to verify the effectiveness of our results.

  7. Two programmed replicative lifespans of Saccharomyces cerevisiae formed by the endogenous molecular-cellular network.

    PubMed

    Hu, Jie; Zhu, Xiaomei; Wang, Xinan; Yuan, Ruoshi; Zheng, Wei; Xu, Minjuan; Ao, Ping

    2014-12-07

    Cellular replicative capacity is a therapeutic target for regenerative medicine as well as cancer treatment. The mechanism of replicative senescence and cell immortality is still unclear. We investigated the diauxic growth of Saccharomyces cerevisiae and demonstrate that the replicative capacity revealed by the yeast growth curve can be understood by using the dynamical property of the molecular-cellular network regulating S. cerevisiae. The endogenous network we proposed has a limit cycle when pheromone signaling is disabled, consistent with the exponential growth phase with an infinite replicative capacity. In the post-diauxic phase, the cooperative effect of the pheromone activated mitogen-activated protein kinase (MAPK) signaling pathway with the cell cycle leads to a fixed point attractor instead of the limit cycle. The cells stop dividing after several generations counting from the beginning of the post-diauxic growth. By tuning the MAPK pathway, S. cerevisiae therefore programs the number of offsprings it replicates.

  8. Application of neural networks to channel assignment for cellular CDMA networks with multiple services and mobile base stations

    NASA Astrophysics Data System (ADS)

    Hortos, William S.

    1996-03-01

    The use of artificial neural networks to the channel assignment problem for cellular code- division multiple access (CDMA) telecommunications systems is considered. CDMA takes advantage of voice activity and spatial isolation because its capacity is only interference limited, unlike time-division multiple access (TDMA) and frequency-division multiple access (FDMA) where capacities are bandwidth limited. Any reduction in interference in CDMA translates linearly into increased capacity. FDMA and TDMA use a frequency reuse pattern as a method to increase capacity, while CDMA reuses the same frequency for all cells and gains a reuse efficiency by means of orthogonal codes. The latter method can improve system capacity by factors of four to six over digital TDMA or FDMA. Cellular carriers are planning to provide multiple communication services using CDMA in the next generation cellular system infrastructure. The approach of this study is the use of neural network methods for automatic and local network control, based on traffic behavior in specific cell cites and demand history. The goal is to address certain problems associated with the management of mobile and personal communication services in a cellular radio communications environment. In planning a cellular radio network, the operator assigns channels to the radio cells so that the probability of the processed carrier-to-interference ratio, CII, exceeding a predefined value is sufficiently low. The RF propagation, determined from the topography and infrastructure in the operating area, is used in conjunction with the densities of expected communications traffic to formulate interference constraints. These constraints state which radio cells may use the same code (channel) or adjacent channels at a time. The traffic loading and the number of service grades can also be used to calculate the number of required channels (codes) for each cell. The general assignment problem is the task of assigning the required number

  9. Cellular neural network implementation using a phase-only joint transform correlator

    NASA Astrophysics Data System (ADS)

    Zhang, Shuqun; Karim, Mohammad A.

    1999-04-01

    A phase-only joint transform correlator (JTC) is used to realize cellular neural networks (CNNs). The operation of summing cross-correlations of bipolar data in CNNs can be realized in parallel by phase-encoding bipolar data. Compared to other optical systems for implementing CNNs, the proposed method offers the advantages of easier implementation and robustness in terms of system alignment, and requires neither electronic precalculation nor data rearrangement. Simulation results of the proposed optical CNNs for edge detection are provided.

  10. Exponential stability of delayed and impulsive cellular neural networks with partially Lipschitz continuous activation functions.

    PubMed

    Song, Xueli; Xin, Xing; Huang, Wenpo

    2012-05-01

    The paper discusses exponential stability of distributed delayed and impulsive cellular neural networks with partially Lipschitz continuous activation functions. By relative nonlinear measure method, some novel criteria are obtained for the uniqueness and exponential stability of the equilibrium point. Our method abandons usual assumptions on global Lipschitz continuity, boundedness and monotonicity of activation functions. Our results are generalization and improvement of some existing ones. Finally, two examples and their simulations are presented to illustrate the correctness of our analysis.

  11. Cellular Neural Network Models of Growth and Immune of Effector Cells Response to Cancer

    NASA Astrophysics Data System (ADS)

    Su, Yongmei; Min, Lequan

    Four reaction-diffusion cellular neural network (R-D CNN) models are set up based on the differential equation models for the growths of effector cells and cancer cells, and the model of the immune response to cancer proposed by Allison et al. The CNN models have different reaction-diffusion coefficients and coupling parameters. The R-D CNN models may provide possible quantitative interpretations, and are good in agreement with the in vitro experiment data reported by Allison et al.

  12. Measuring information flow in cellular networks by the systems biology method through microarray data.

    PubMed

    Chen, Bor-Sen; Li, Cheng-Wei

    2015-01-01

    In general, it is very difficult to measure the information flow in a cellular network directly. In this study, based on an information flow model and microarray data, we measured the information flow in cellular networks indirectly by using a systems biology method. First, we used a recursive least square parameter estimation algorithm to identify the system parameters of coupling signal transduction pathways and the cellular gene regulatory network (GRN). Then, based on the identified parameters and systems theory, we estimated the signal transductivities of the coupling signal transduction pathways from the extracellular signals to each downstream protein and the information transductivities of the GRN between transcription factors in response to environmental events. According to the proposed method, the information flow, which is characterized by signal transductivity in coupling signaling pathways and information transductivity in the GRN, can be estimated by microarray temporal data or microarray sample data. It can also be estimated by other high-throughput data such as next-generation sequencing or proteomic data. Finally, the information flows of the signal transduction pathways and the GRN in leukemia cancer cells and non-leukemia normal cells were also measured to analyze the systematic dysfunction in this cancer from microarray sample data. The results show that the signal transductivities of signal transduction pathways change substantially from normal cells to leukemia cancer cells.

  13. Measuring information flow in cellular networks by the systems biology method through microarray data

    PubMed Central

    Chen, Bor-Sen; Li, Cheng-Wei

    2015-01-01

    In general, it is very difficult to measure the information flow in a cellular network directly. In this study, based on an information flow model and microarray data, we measured the information flow in cellular networks indirectly by using a systems biology method. First, we used a recursive least square parameter estimation algorithm to identify the system parameters of coupling signal transduction pathways and the cellular gene regulatory network (GRN). Then, based on the identified parameters and systems theory, we estimated the signal transductivities of the coupling signal transduction pathways from the extracellular signals to each downstream protein and the information transductivities of the GRN between transcription factors in response to environmental events. According to the proposed method, the information flow, which is characterized by signal transductivity in coupling signaling pathways and information transductivity in the GRN, can be estimated by microarray temporal data or microarray sample data. It can also be estimated by other high-throughput data such as next-generation sequencing or proteomic data. Finally, the information flows of the signal transduction pathways and the GRN in leukemia cancer cells and non-leukemia normal cells were also measured to analyze the systematic dysfunction in this cancer from microarray sample data. The results show that the signal transductivities of signal transduction pathways change substantially from normal cells to leukemia cancer cells. PMID:26082788

  14. An Asynchronous Recurrent Network of Cellular Automaton-Based Neurons and Its Reproduction of Spiking Neural Network Activities.

    PubMed

    Matsubara, Takashi; Torikai, Hiroyuki

    2016-04-01

    Modeling and implementation approaches for the reproduction of input-output relationships in biological nervous tissues contribute to the development of engineering and clinical applications. However, because of high nonlinearity, the traditional modeling and implementation approaches encounter difficulties in terms of generalization ability (i.e., performance when reproducing an unknown data set) and computational resources (i.e., computation time and circuit elements). To overcome these difficulties, asynchronous cellular automaton-based neuron (ACAN) models, which are described as special kinds of cellular automata that can be implemented as small asynchronous sequential logic circuits have been proposed. This paper presents a novel type of such ACAN and a theoretical analysis of its excitability. This paper also presents a novel network of such neurons, which can mimic input-output relationships of biological and nonlinear ordinary differential equation model neural networks. Numerical analyses confirm that the presented network has a higher generalization ability than other major modeling and implementation approaches. In addition, Field-Programmable Gate Array-implementations confirm that the presented network requires lower computational resources.

  15. A New Cellular Architecture for Information Retrieval from Sensor Networks through Embedded Service and Security Protocols.

    PubMed

    Shahzad, Aamir; Landry, René; Lee, Malrey; Xiong, Naixue; Lee, Jongho; Lee, Changhoon

    2016-06-14

    Substantial changes have occurred in the Information Technology (IT) sectors and with these changes, the demand for remote access to field sensor information has increased. This allows visualization, monitoring, and control through various electronic devices, such as laptops, tablets, i-Pads, PCs, and cellular phones. The smart phone is considered as a more reliable, faster and efficient device to access and monitor industrial systems and their corresponding information interfaces anywhere and anytime. This study describes the deployment of a protocol whereby industrial system information can be securely accessed by cellular phones via a Supervisory Control And Data Acquisition (SCADA) server. To achieve the study goals, proprietary protocol interconnectivity with non-proprietary protocols and the usage of interconnectivity services are considered in detail. They support the visualization of the SCADA system information, and the related operations through smart phones. The intelligent sensors are configured and designated to process real information via cellular phones by employing information exchange services between the proprietary protocol and non-proprietary protocols. SCADA cellular access raises the issue of security flaws. For these challenges, a cryptography-based security method is considered and deployed, and it could be considered as a part of a proprietary protocol. Subsequently, transmission flows from the smart phones through a cellular network.

  16. A New Cellular Architecture for Information Retrieval from Sensor Networks through Embedded Service and Security Protocols

    PubMed Central

    Shahzad, Aamir; Landry, René; Lee, Malrey; Xiong, Naixue; Lee, Jongho; Lee, Changhoon

    2016-01-01

    Substantial changes have occurred in the Information Technology (IT) sectors and with these changes, the demand for remote access to field sensor information has increased. This allows visualization, monitoring, and control through various electronic devices, such as laptops, tablets, i-Pads, PCs, and cellular phones. The smart phone is considered as a more reliable, faster and efficient device to access and monitor industrial systems and their corresponding information interfaces anywhere and anytime. This study describes the deployment of a protocol whereby industrial system information can be securely accessed by cellular phones via a Supervisory Control And Data Acquisition (SCADA) server. To achieve the study goals, proprietary protocol interconnectivity with non-proprietary protocols and the usage of interconnectivity services are considered in detail. They support the visualization of the SCADA system information, and the related operations through smart phones. The intelligent sensors are configured and designated to process real information via cellular phones by employing information exchange services between the proprietary protocol and non-proprietary protocols. SCADA cellular access raises the issue of security flaws. For these challenges, a cryptography-based security method is considered and deployed, and it could be considered as a part of a proprietary protocol. Subsequently, transmission flows from the smart phones through a cellular network. PMID:27314351

  17. Profile-QSAR: a novel meta-QSAR method that combines activities across the kinase family to accurately predict affinity, selectivity, and cellular activity.

    PubMed

    Martin, Eric; Mukherjee, Prasenjit; Sullivan, David; Jansen, Johanna

    2011-08-22

    Profile-QSAR is a novel 2D predictive model building method for kinases. This "meta-QSAR" method models the activity of each compound against a new kinase target as a linear combination of its predicted activities against a large panel of 92 previously studied kinases comprised from 115 assays. Profile-QSAR starts with a sparse incomplete kinase by compound (KxC) activity matrix, used to generate Bayesian QSAR models for the 92 "basis-set" kinases. These Bayesian QSARs generate a complete "synthetic" KxC activity matrix of predictions. These synthetic activities are used as "chemical descriptors" to train partial-least squares (PLS) models, from modest amounts of medium-throughput screening data, for predicting activity against new kinases. The Profile-QSAR predictions for the 92 kinases (115 assays) gave a median external R²(ext) = 0.59 on 25% held-out test sets. The method has proven accurate enough to predict pairwise kinase selectivities with a median correlation of R²(ext) = 0.61 for 958 kinase pairs with at least 600 common compounds. It has been further expanded by adding a "C(k)XC" cellular activity matrix to the KxC matrix to predict cellular activity for 42 kinase driven cellular assays with median R²(ext) = 0.58 for 24 target modulation assays and R²(ext) = 0.41 for 18 cell proliferation assays. The 2D Profile-QSAR, along with the 3D Surrogate AutoShim, are the foundations of an internally developed iterative medium-throughput screening (IMTS) methodology for virtual screening (VS) of compound archives as an alternative to experimental high-throughput screening (HTS). The method has been applied to 20 actual prospective kinase projects. Biological results have so far been obtained in eight of them. Q² values ranged from 0.3 to 0.7. Hit-rates at 10 uM for experimentally tested compounds varied from 25% to 80%, except in K5, which was a special case aimed specifically at finding "type II" binders, where none of the compounds were predicted to be

  18. A double herd krill based algorithm for location area optimization in mobile wireless cellular network.

    PubMed

    Vincylloyd, F; Anand, B

    2015-01-01

    In wireless communication systems, mobility tracking deals with determining a mobile subscriber (MS) covering the area serviced by the wireless network. Tracking a mobile subscriber is governed by the two fundamental components called location updating (LU) and paging. This paper presents a novel hybrid method using a krill herd algorithm designed to optimize the location area (LA) within available spectrum such that total network cost, comprising location update (LU) cost and cost for paging, is minimized without compromise. Based on various mobility patterns of users and network architecture, the design of the LR area is formulated as a combinatorial optimization problem. Numerical results indicate that the proposed model provides a more accurate update boundary in real environment than that derived from a hexagonal cell configuration with a random walk movement pattern. The proposed model allows the network to maintain a better balance between the processing incurred due to location update and the radio bandwidth utilized for paging between call arrivals.

  19. Hybrid RF and Digital Beamformer for Cellular Networks: Algorithms, Microwave Architectures, and Measurements

    NASA Astrophysics Data System (ADS)

    Venkateswaran, Vijay; Pivit, Florian; Guan, Lei

    2016-07-01

    Modern wireless communication networks, particularly cellular networks utilize multiple antennas to improve the capacity and signal coverage. In these systems, typically an active transceiver is connected to each antenna. However, this one-to-one mapping between transceivers and antennas will dramatically increase the cost and complexity of a large phased antenna array system. In this paper, firstly we propose a \\emph{partially adaptive} beamformer architecture where a reduced number of transceivers with a digital beamformer (DBF) is connected to an increased number of antennas through an RF beamforming network (RFBN). Then, based on the proposed architecture, we present a methodology to derive the minimum number of transceivers that are required for marco-cell and small-cell base stations, respectively. Subsequently, in order to achieve optimal beampatterns with given cellular standard requirements and RF operational constraints, we propose efficient algorithms to jointly design DBF and RFBN. Starting from the proposed algorithms, we specify generic microwave RFBNs for optimal marco-cell and small-cell networks. In order to verify the proposed approaches, we compare the performance of RFBN using simulations and anechoic chamber measurements. Experimental measurement results confirm the robustness and performance of the proposed hybrid DBF-RFBN concept eventually ensuring that theoretical multi-antenna capacity and coverage are achieved at a little incremental cost.

  20. Motion adaptive vertical handoff in cellular/WLAN heterogeneous wireless network.

    PubMed

    Li, Limin; Ma, Lin; Xu, Yubin; Fu, Yunhai

    2014-01-01

    In heterogeneous wireless network, vertical handoff plays an important role for guaranteeing quality of service and overall performance of network. Conventional vertical handoff trigger schemes are mostly developed from horizontal handoff in homogeneous cellular network. Basically, they can be summarized as hysteresis-based and dwelling-timer-based algorithms, which are reliable on avoiding unnecessary handoff caused by the terminals dwelling at the edge of WLAN coverage. However, the coverage of WLAN is much smaller compared with cellular network, while the motion types of terminals can be various in a typical outdoor scenario. As a result, traditional algorithms are less effective in avoiding unnecessary handoff triggered by vehicle-borne terminals with various speeds. Besides that, hysteresis and dwelling-timer thresholds usually need to be modified to satisfy different channel environments. For solving this problem, a vertical handoff algorithm based on Q-learning is proposed in this paper. Q-learning can provide the decider with self-adaptive ability for handling the terminals' handoff requests with different motion types and channel conditions. Meanwhile, Neural Fuzzy Inference System (NFIS) is embedded to retain a continuous perception of the state space. Simulation results verify that the proposed algorithm can achieve lower unnecessary handoff probability compared with the other two conventional algorithms.

  1. Motion Adaptive Vertical Handoff in Cellular/WLAN Heterogeneous Wireless Network

    PubMed Central

    Ma, Lin; Xu, Yubin; Fu, Yunhai

    2014-01-01

    In heterogeneous wireless network, vertical handoff plays an important role for guaranteeing quality of service and overall performance of network. Conventional vertical handoff trigger schemes are mostly developed from horizontal handoff in homogeneous cellular network. Basically, they can be summarized as hysteresis-based and dwelling-timer-based algorithms, which are reliable on avoiding unnecessary handoff caused by the terminals dwelling at the edge of WLAN coverage. However, the coverage of WLAN is much smaller compared with cellular network, while the motion types of terminals can be various in a typical outdoor scenario. As a result, traditional algorithms are less effective in avoiding unnecessary handoff triggered by vehicle-borne terminals with various speeds. Besides that, hysteresis and dwelling-timer thresholds usually need to be modified to satisfy different channel environments. For solving this problem, a vertical handoff algorithm based on Q-learning is proposed in this paper. Q-learning can provide the decider with self-adaptive ability for handling the terminals' handoff requests with different motion types and channel conditions. Meanwhile, Neural Fuzzy Inference System (NFIS) is embedded to retain a continuous perception of the state space. Simulation results verify that the proposed algorithm can achieve lower unnecessary handoff probability compared with the other two conventional algorithms. PMID:24741347

  2. Phase transitions in pancreatic islet cellular networks and implications for type-1 diabetes

    NASA Astrophysics Data System (ADS)

    Stamper, I. J.; Jackson, Elais; Wang, Xujing

    2014-01-01

    In many aspects the onset of a chronic disease resembles a phase transition in a complex dynamic system: Quantitative changes accumulate largely unnoticed until a critical threshold is reached, which causes abrupt qualitative changes of the system. In this study we examine a special case, the onset of type-1 diabetes (T1D), a disease that results from loss of the insulin-producing pancreatic islet β cells. Within each islet, the β cells are electrically coupled to each other via gap-junctional channels. This intercellular coupling enables the β cells to synchronize their insulin release, thereby generating the multiscale temporal rhythms in blood insulin that are critical to maintaining blood glucose homeostasis. Using percolation theory we show how normal islet function is intrinsically linked to network connectivity. In particular, the critical amount of β-cell death at which the islet cellular network loses site percolation is consistent with laboratory and clinical observations of the threshold loss of β cells that causes islet functional failure. In addition, numerical simulations confirm that the islet cellular network needs to be percolated for β cells to synchronize. Furthermore, the interplay between site percolation and bond strength predicts the existence of a transient phase of islet functional recovery after onset of T1D and introduction of treatment, potentially explaining the honeymoon phenomenon. Based on these results, we hypothesize that the onset of T1D may be the result of a phase transition of the islet β-cell network.

  3. A Memristive Multilayer Cellular Neural Network With Applications to Image Processing.

    PubMed

    Hu, Xiaofang; Feng, Gang; Duan, Shukai; Liu, Lu

    2016-05-13

    The memristor has been extensively studied in electrical engineering and biological sciences as a means to compactly implement the synaptic function in neural networks. The cellular neural network (CNN) is one of the most implementable artificial neural network models and capable of massively parallel analog processing. In this paper, a novel memristive multilayer CNN (Mm-CNN) model is presented along with its performance analysis and applications. In this new CNN design, the memristor crossbar circuit acts as the synapse, which realizes one signed synaptic weight with a pair of memristors and performs the synaptic weighting compactly and linearly. Moreover, the complex weighted summation is executed in an efficient way with a proper design of Mm-CNN cell circuits. The proposed Mm-CNN has several merits, such as compactness, nonvolatility, versatility, and programmability of synaptic weights. Its performance in several image processing applications is illustrated through simulations.

  4. Micro-connectomics: probing the organization of neuronal networks at the cellular scale.

    PubMed

    Schröter, Manuel; Paulsen, Ole; Bullmore, Edward T

    2017-03-01

    Defining the organizational principles of neuronal networks at the cellular scale, or micro-connectomics, is a key challenge of modern neuroscience. In this Review, we focus on graph theoretical parameters of micro-connectome topology, often informed by economical principles that conceptually originated with Ramón y Cajal's conservation laws. First, we summarize results from studies in intact small organisms and in samples from larger nervous systems. We then evaluate the evidence for an economical trade-off between biological cost and functional value in the organization of neuronal networks. Various results suggest that many aspects of neuronal network organization are indeed the outcome of competition between these two fundamental selection pressures.

  5. The translational machinery is an optimized molecular network that affects cellular homoeostasis and disease.

    PubMed

    Kazana, Eleanna; von der Haar, Tobias

    2014-02-01

    Translation involves interactions between mRNAs, ribosomes, tRNAs and a host of translation factors. Emerging evidence on the eukaryotic translational machinery indicates that these factors are organized in a highly optimized network, in which the levels of the different factors are finely matched to each other. This optimal factor network is essential for producing proteomes that result in optimal fitness, and perturbations to the optimal network that significantly affect translational activity therefore result in non-optimal proteomes, fitness losses and disease. On the other hand, experimental evidence indicates that translation and cell growth are relatively robust to perturbations, and viability can be maintained even upon significant damage to individual translation factors. How the eukaryotic translational machinery is optimized, and how it can maintain optimization in the face of changing internal parameters, are open questions relevant to the interaction between translation and cellular disease states.

  6. Increasing the coverage area through relay node deployment in long term evolution advanced cellular networks

    NASA Astrophysics Data System (ADS)

    Aldhaibani, Jaafar A.; Ahmad, R. B.; Yahya, A.; Azeez, Suzan A.

    2015-05-01

    Wireless multi-hop relay networks have become very important technologies in mobile communications. These networks ensure high throughput and coverage extension with a low cost. The poor capacity at cell edges is not enough to meet with growing demand of high capacity and throughput irrespective of user's placement in the cellular network. In this paper we propose optimal placement of relay node that provides maximum achievable rate at users and enhances the throughput and coverage at cell edge region. The proposed scheme is based on the outage probability at users and taken on account the interference between nodes. Numerical analyses along with simulation results indicated there are an improvement in capacity for users at the cell edge is 40% increment from all cell capacity.

  7. A global genetic interaction network maps a wiring diagram of cellular function.

    PubMed

    Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D; Pelechano, Vicent; Styles, Erin B; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F; Li, Sheena C; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; San Luis, Bryan-Joseph; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M; Moore, Claire L; Rosebrock, Adam P; Caudy, Amy A; Myers, Chad L; Andrews, Brenda; Boone, Charles

    2016-09-23

    We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell.

  8. Issues for the integration of satellite and terrestrial cellular networks for mobile communications

    NASA Astrophysics Data System (ADS)

    Delre, Enrico; Mistretta, Ignazio; Dellipriscoli, Francesco; Settimo, Franco

    1991-09-01

    Satellite and terrestrial cellular systems naturally complement each other for land mobile communications, even though present systems have been developed independently. The main advantages of the integrated system are a faster wide area coverage, a better management of overloading traffic conditions, an extension to geographical areas not covered by the terrestrial network and, in perspective, the provision of only one integrated system for all mobile communications (land, aeronautical, and maritime). To achieve these goals, as far as possible the same protocols of the terrestrial network should be used also for the satellite network. Discussed here are the main issues arising from the requirements of the main integrated system. Some results are illustrated, and possible future improvements due to technical solutions are presented.

  9. Cellular pulse-coupled neural network with adaptive weights for image segmentation and its VLSI implementation

    NASA Astrophysics Data System (ADS)

    Schreiter, Juerg; Ramacher, Ulrich; Heittmann, Arne; Matolin, Daniel; Schuffny, Rene

    2004-05-01

    We present a cellular pulse coupled neural network with adaptive weights and its analog VLSI implementation. The neural network operates on a scalar image feature, such as grey scale or the output of a spatial filter. It detects segments and marks them with synchronous pulses of the corresponding neurons. The network consists of integrate-and-fire neurons, which are coupled to their nearest neighbors via adaptive synaptic weights. Adaptation follows either one of two empirical rules. Both rules lead to spike grouping in wave like patterns. This synchronous activity binds groups of neurons and labels the corresponding image segments. Applications of the network also include feature preserving noise removal, image smoothing, and detection of bright and dark spots. The adaptation rules are insensitive for parameter deviations, mismatch and non-ideal approximation of the implied functions. That makes an analog VLSI implementation feasible. Simulations showed no significant differences in the synchronization properties between networks using the ideal adaptation rules and networks resembling implementation properties such as randomly distributed parameters and roughly implemented adaptation functions. A prototype is currently being designed and fabricated using an Infineon 130nm technology. It comprises a 128 × 128 neuron array, analog image memory, and an address event representation pulse output.

  10. A rapid and accurate quantification method for real-time dynamic analysis of cellular lipids during microalgal fermentation processes in Chlorella protothecoides with low field nuclear magnetic resonance.

    PubMed

    Wang, Tao; Liu, Tingting; Wang, Zejian; Tian, Xiwei; Yang, Yi; Guo, Meijin; Chu, Ju; Zhuang, Yingping

    2016-05-01

    The rapid and real-time lipid determination can provide valuable information on process regulation and optimization in the algal lipid mass production. In this study, a rapid, accurate and precise quantification method of in vivo cellular lipids of Chlorella protothecoides using low field nuclear magnetic resonance (LF-NMR) was newly developed. LF-NMR was extremely sensitive to the algal lipids with the limits of the detection (LOD) of 0.0026g and 0.32g/L in dry lipid samples and algal broth, respectively, as well as limits of quantification (LOQ) of 0.0093g and 1.18g/L. Moreover, the LF-NMR signal was specifically proportional to the cellular lipids of C. protothecoides, thus the superior regression curves existing in a wide detection range from 0.02 to 0.42g for dry lipids and from 1.12 to 8.97gL(-1) of lipid concentration for in vivo lipid quantification were obtained with all R(2) higher than 0.99, irrespective of the lipid content and fatty acids profile variations. The accuracy of this novel method was further verified to be reliable by comparing lipid quantification results to those obtained by GC-MS. And the relative standard deviation (RSD) of LF-NMR results were smaller than 2%, suggesting the precision of this method. Finally, this method was successfully used in the on-line lipid monitoring during the algal lipid fermentation processes, making it possible for better understanding of the lipid accumulation mechanism and dynamic bioprocess control.

  11. Multifunctional Superelastic Foam-Like Boron Nitride Nanotubular Cellular-Network Architectures.

    PubMed

    Xue, Yanming; Dai, Pengcheng; Zhou, Min; Wang, Xi; Pakdel, Amir; Zhang, Chao; Weng, Qunhong; Takei, Toshiaki; Fu, Xiuwei; Popov, Zakhar I; Sorokin, Pavel B; Tang, Chengchun; Shimamura, Kiyoshi; Bando, Yoshio; Golberg, Dmitri

    2017-01-24

    Construction of cellular architectures has been expected to enhance materials' mechanical tolerance and to stimulate and broaden their efficient utilizations in many potential fields. However, hitherto, there have been rather scarce developments in boron nitride (BN)-type cellular architectures because of well-known difficulties in the syntheses of BN-based structures. Herein, cellular-network multifunctional foams made of interconnective nanotubular hexagonal BN (h-BN) architectures are developed using carbothermal reduction-assisted in situ chemical vapor deposition conversion from N-doped tubular graphitic cellular foams. These ultralight, chemically inert, thermally stable, and robust-integrity (supporting about 25,000 times of their own weight) three-dimensional-BN foams exhibit a 98.5% porosity, remarkable shape recovery (even after cycling compressions with 90% deformations), excellent resistance to water intrusion, thermal diffusion stability, and high strength and stiffness. They remarkably reduce the coefficient of thermal expansion and dielectric constant of polymeric poly(methyl methacrylate) composites, greatly contribute to their thermal conductivity improvement, and effectively limit polymeric composite softening at elevated temperatures. The foams also demonstrate high-capacity adsorption-separation and removal ability for a wide range of oils and organic chemicals in oil/water systems and reliable recovery under their cycling usage as organic adsorbers. These created multifunctional foams should be valuable in many high-end practical applications.

  12. Cellular Signaling Networks Function as Generalized Wiener-Kolmogorov Filters to Suppress Noise

    NASA Astrophysics Data System (ADS)

    Hinczewski, Michael; Thirumalai, D.

    2014-10-01

    Cellular signaling involves the transmission of environmental information through cascades of stochastic biochemical reactions, inevitably introducing noise that compromises signal fidelity. Each stage of the cascade often takes the form of a kinase-phosphatase push-pull network, a basic unit of signaling pathways whose malfunction is linked with a host of cancers. We show that this ubiquitous enzymatic network motif effectively behaves as a Wiener-Kolmogorov optimal noise filter. Using concepts from umbral calculus, we generalize the linear Wiener-Kolmogorov theory, originally introduced in the context of communication and control engineering, to take nonlinear signal transduction and discrete molecule populations into account. This allows us to derive rigorous constraints for efficient noise reduction in this biochemical system. Our mathematical formalism yields bounds on filter performance in cases important to cellular function—such as ultrasensitive response to stimuli. We highlight features of the system relevant for optimizing filter efficiency, encoded in a single, measurable, dimensionless parameter. Our theory, which describes noise control in a large class of signal transduction networks, is also useful both for the design of synthetic biochemical signaling pathways and the manipulation of pathways through experimental probes such as oscillatory input.

  13. High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels.

    PubMed

    Müller, Jan; Ballini, Marco; Livi, Paolo; Chen, Yihui; Radivojevic, Milos; Shadmani, Amir; Viswam, Vijay; Jones, Ian L; Fiscella, Michele; Diggelmann, Roland; Stettler, Alexander; Frey, Urs; Bakkum, Douglas J; Hierlemann, Andreas

    2015-07-07

    Studies on information processing and learning properties of neuronal networks would benefit from simultaneous and parallel access to the activity of a large fraction of all neurons in such networks. Here, we present a CMOS-based device, capable of simultaneously recording the electrical activity of over a thousand cells in in vitro neuronal networks. The device provides sufficiently high spatiotemporal resolution to enable, at the same time, access to neuronal preparations on subcellular, cellular, and network level. The key feature is a rapidly reconfigurable array of 26 400 microelectrodes arranged at low pitch (17.5 μm) within a large overall sensing area (3.85 × 2.10 mm(2)). An arbitrary subset of the electrodes can be simultaneously connected to 1024 low-noise readout channels as well as 32 stimulation units. Each electrode or electrode subset can be used to electrically stimulate or record the signals of virtually any neuron on the array. We demonstrate the applicability and potential of this device for various different experimental paradigms: large-scale recordings from whole networks of neurons as well as investigations of axonal properties of individual neurons.

  14. Functional recognition imaging using artificial neural networks: applications to rapid cellular identification via broadband electromechanical response

    NASA Astrophysics Data System (ADS)

    Nikiforov, M. P.; Reukov, V. V.; Thompson, G. L.; Vertegel, A. A.; Guo, S.; Kalinin, S. V.; Jesse, S.

    2009-10-01

    Functional recognition imaging in scanning probe microscopy (SPM) using artificial neural network identification is demonstrated. This approach utilizes statistical analysis of complex SPM responses at a single spatial location to identify the target behavior, which is reminiscent of associative thinking in the human brain, obviating the need for analytical models. We demonstrate, as an example of recognition imaging, rapid identification of cellular organisms using the difference in electromechanical activity over a broad frequency range. Single-pixel identification of model Micrococcus lysodeikticus and Pseudomonas fluorescens bacteria is achieved, demonstrating the viability of the method.

  15. A new method for the re-implementation of threshold logic functions with cellular neural networks.

    PubMed

    Bénédic, Y; Wira, P; Mercklé, J

    2008-08-01

    A new strategy is presented for the implementation of threshold logic functions with binary-output Cellular Neural Networks (CNNs). The objective is to optimize the CNNs weights to develop a robust implementation. Hence, the concept of generative set is introduced as a convenient representation of any linearly separable Boolean function. Our analysis of threshold logic functions leads to a complete algorithm that automatically provides an optimized generative set. New weights are deduced and a more robust CNN template assuming the same function can thus be implemented. The strategy is illustrated by a detailed example.

  16. Moving object segmentation algorithm based on cellular neural networks in the H.264 compressed domain

    NASA Astrophysics Data System (ADS)

    Feng, Jie; Chen, Yaowu; Tian, Xiang

    2009-07-01

    A cellular neural network (CNN)-based moving object segmentation algorithm in the H.264 compressed domain is proposed. This algorithm mainly utilizes motion vectors directly extracted from H.264 bitstreams. To improve the robustness of the motion vector information, the intramodes in I-frames are used for smooth and nonsmooth region classification, and the residual coefficient energy of P-frames is used to update the classification results first. Then, an adaptive motion vector filter is used according to interpartition modes. Finally, many CNN models are applied to implement moving object segmentation based on motion vector fields. Experiment results are presented to verify the efficiency and the robustness of this algorithm.

  17. Evolving Transport Networks With Cellular Automata Models Inspired by Slime Mould.

    PubMed

    Tsompanas, Michail-Antisthenis I; Sirakoulis, Georgios Ch; Adamatzky, Andrew I

    2015-09-01

    Man-made transport networks and their design are closely related to the shortest path problem and considered amongst the most debated problems of computational intelligence. Apart from using conventional or bio-inspired computer algorithms, many researchers tried to solve this kind of problem using biological computing substrates, gas-discharge solvers, prototypes of a mobile droplet, and hot ice computers. In this aspect, another example of biological computer is the plasmodium of acellular slime mould Physarum polycephalum (P. polycephalum), which is a large single cell visible by an unaided eye and has been proven as a reliable living substrate for implementing biological computing devices for computational geometry, graph-theoretical problems, and optimization and imitation of transport networks. Although P. polycephalum is easy to experiment with, computing devices built with the living slime mould are extremely slow; it takes slime mould days to execute a computation. Consequently, mapping key computing mechanisms of the slime mould onto silicon would allow us to produce efficient bio-inspired computing devices to tackle with hard to solve computational intelligence problems like the aforementioned. Toward this direction, a cellular automaton (CA)-based, Physarum-inspired, network designing model is proposed. This novel CA-based model is inspired by the propagating strategy, the formation of tubular networks, and the computing abilities of the plasmodium of P. polycephalum. The results delivered by the CA model demonstrate a good match with several previously published results of experimental laboratory studies on imitation of man-made transport networks with P. polycephalum. Consequently, the proposed CA model can be used as a virtual, easy-to-access, and biomimicking laboratory emulator that will economize large time periods needed for biological experiments while producing networks almost identical to the tubular networks of the real-slime mould.

  18. Using prior knowledge from cellular pathways and molecular networks for diagnostic specimen classification

    PubMed Central

    2016-01-01

    For many complex diseases, an earlier and more reliable diagnosis is considered a key prerequisite for developing more effective therapies to prevent or delay disease progression. Classical statistical learning approaches for specimen classification using omics data, however, often cannot provide diagnostic models with sufficient accuracy and robustness for heterogeneous diseases like cancers or neurodegenerative disorders. In recent years, new approaches for building multivariate biomarker models on omics data have been proposed, which exploit prior biological knowledge from molecular networks and cellular pathways to address these limitations. This survey provides an overview of these recent developments and compares pathway- and network-based specimen classification approaches in terms of their utility for improving model robustness, accuracy and biological interpretability. Different routes to translate omics-based multifactorial biomarker models into clinical diagnostic tests are discussed, and a previous study is presented as example. PMID:26141830

  19. Cellular telephone-based radiation sensor and wide-area detection network

    DOEpatents

    Craig, William W.; Labov, Simon E.

    2006-12-12

    A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

  20. Modeling Immune Network Through Cellular Automata:. a Unified Mechanism of Immunological Memory

    NASA Astrophysics Data System (ADS)

    Chowdhury, Debashish; Deshpande, Varsha; Stauffer, Dietrich

    The populations of the various types of immunocompetent cells in the immune system are described as cellular automata and the population dynamics of these cells are formulated in terms of dynamical maps in discrete time. Both intra-clonal interactions (i.e., interactions among the cell types belonging to the same clone) and inter-clonal interactions (i.e., interactions among the cell types belonging to different clones) are included in the models proposed here. While the intra-clonal interactions are shown to play a crucial role in the primary response of some clones and in the formation of the immunological memory, the inter-clonal interactions are responsible for retaining the memory through a dynamical process driven by the mutual stimulation of the clones. We present the results for two different types of connectivity, namely, a “necklace” network and a network in “shape space”.

  1. Modeling of Diffusion through a Network: A New Approach using Cellular Automata and Network Science Techniques

    DTIC Science & Technology

    2010-05-01

    to Professor Chris Arney and LTC Donovan Phillips for providing valuable feedback on this project. vii MODELING OF DIFFUSION THROUGH A...only does the study of networks afford the U.S. Army greater information sharing abilities, it could also give a better understanding of enemy...These models are named for the conditions by which a node changes state. The first model gives each node its own threshold which must be reached before

  2. The Influence of Cold Temperature on Cellular Excitability of Hippocampal Networks

    PubMed Central

    Vara, Hugo; Caires, Rebeca; Ballesta, Juan J.; Belmonte, Carlos; Viana, Felix

    2012-01-01

    The hippocampus plays an important role in short term memory, learning and spatial navigation. A characteristic feature of the hippocampal region is its expression of different electrical population rhythms and activities during different brain states. Physiological fluctuations in brain temperature affect the activity patterns in hippocampus, but the underlying cellular mechanisms are poorly understood. In this work, we investigated the thermal modulation of hippocampal activity at the cellular network level. Primary cell cultures of mouse E17 hippocampus displayed robust network activation upon light cooling of the extracellular solution from baseline physiological temperatures. The activity generated was dependent on action potential firing and excitatory glutamatergic synaptic transmission. Involvement of thermosensitive channels from the transient receptor potential (TRP) family in network activation by temperature changes was ruled out, whereas pharmacological and immunochemical experiments strongly pointed towards the involvement of temperature-sensitive two-pore-domain potassium channels (K2P), TREK/TRAAK family. In hippocampal slices we could show an increase in evoked and spontaneous synaptic activity produced by mild cooling in the physiological range that was prevented by chloroform, a K2P channel opener. We propose that cold-induced closure of background TREK/TRAAK family channels increases the excitability of some hippocampal neurons, acting as a temperature-sensitive gate of network activation. Our findings in the hippocampus open the possibility that small temperature variations in the brain in vivo, associated with metabolism or blood flow oscillations, act as a switch mechanism of neuronal activity and determination of firing patterns through regulation of thermosensitive background potassium channel activity. PMID:23300680

  3. Separation of Benign and Malicious Network Events for Accurate Malware Family Classification

    DTIC Science & Technology

    2015-09-28

    malware at runtime, including memory access patterns, network traces, OS system calls, file system changes, and registry modifica- tions. Static...statistical features extracted from either static bi- naries [2–4], or from artifacts collected during the execution of the binary [5, 6]. These traces...same features extracted from mixed traffic that is collected on user machines, since these machines generate traffic containing both malware- and

  4. Effect of crystals and fibrous network polymer additives on cellular morphology of microcellular foams

    NASA Astrophysics Data System (ADS)

    Miyamoto, Ryoma; Utano, Tatsumi; Yasuhara, Shunya; Ishihara, Shota; Ohshima, Masahiro

    2015-05-01

    In this study, the core-back foam injection molding was used for preparing microcelluar polypropylene (PP) foam with either a 1,3:2,4 bis-O-(4-methylbenzylidene)-D-sorbitol gelling agent (Gel-all MD) or a fibros network polymer additive (Metablen 3000). Both agent and addiive could effectively control the celluar morphology in foams but somehow different ways. In course of cooling the polymer with Gel-all MD in the mold caity, the agent enhanced the crystal nucleation and resulted in the large number of small crystals. The crystals acted as effective bubble nucleation agent in foaming process. Thus, the agent reduced the cell size and increased the cell density, drastically. Furthermore, the small crystals provided an inhomogenuity to the expanding cell wall and produced the high open cell content with nano-scale fibril structure. Gell-all as well as Metablene 3000 formed a gel-like fibrous network in melt. The network increased the elongational viscosity and tended to prevent the cell wall from breaking up. The foaming temperature window was widened by the presence of the network. Especially, the temperature window where the macro-fibrous structure was formed was expanded to the higher temperature. The effects of crystal nucleating agent and PTFE on crystals' size and number, viscoelsticity, rheological propreties of PP and cellular morphology were compared and thorougly investigated.

  5. ComPPI: a cellular compartment-specific database for protein-protein interaction network analysis.

    PubMed

    Veres, Daniel V; Gyurkó, Dávid M; Thaler, Benedek; Szalay, Kristóf Z; Fazekas, Dávid; Korcsmáros, Tamás; Csermely, Peter

    2015-01-01

    Here we present ComPPI, a cellular compartment-specific database of proteins and their interactions enabling an extensive, compartmentalized protein-protein interaction network analysis (URL: http://ComPPI.LinkGroup.hu). ComPPI enables the user to filter biologically unlikely interactions, where the two interacting proteins have no common subcellular localizations and to predict novel properties, such as compartment-specific biological functions. ComPPI is an integrated database covering four species (S. cerevisiae, C. elegans, D. melanogaster and H. sapiens). The compilation of nine protein-protein interaction and eight subcellular localization data sets had four curation steps including a manually built, comprehensive hierarchical structure of >1600 subcellular localizations. ComPPI provides confidence scores for protein subcellular localizations and protein-protein interactions. ComPPI has user-friendly search options for individual proteins giving their subcellular localization, their interactions and the likelihood of their interactions considering the subcellular localization of their interacting partners. Download options of search results, whole-proteomes, organelle-specific interactomes and subcellular localization data are available on its website. Due to its novel features, ComPPI is useful for the analysis of experimental results in biochemistry and molecular biology, as well as for proteome-wide studies in bioinformatics and network science helping cellular biology, medicine and drug design.

  6. Condition monitoring of 3G cellular networks through competitive neural models.

    PubMed

    Barreto, Guilherme A; Mota, João C M; Souza, Luis G M; Frota, Rewbenio A; Aguayo, Leonardo

    2005-09-01

    We develop an unsupervised approach to condition monitoring of cellular networks using competitive neural algorithms. Training is carried out with state vectors representing the normal functioning of a simulated CDMA2000 network. Once training is completed, global and local normality profiles (NPs) are built from the distribution of quantization errors of the training state vectors and their components, respectively. The global NP is used to evaluate the overall condition of the cellular system. If abnormal behavior is detected, local NPs are used in a component-wise fashion to find abnormal state variables. Anomaly detection tests are performed via percentile-based confidence intervals computed over the global and local NPs. We compared the performance of four competitive algorithms [winner-take-all (WTA), frequency-sensitive competitive learning (FSCL), self-organizing map (SOM), and neural-gas algorithm (NGA)] and the results suggest that the joint use of global and local NPs is more efficient and more robust than current single-threshold methods.

  7. ComPPI: a cellular compartment-specific database for protein–protein interaction network analysis

    PubMed Central

    Veres, Daniel V.; Gyurkó, Dávid M.; Thaler, Benedek; Szalay, Kristóf Z.; Fazekas, Dávid; Korcsmáros, Tamás; Csermely, Peter

    2015-01-01

    Here we present ComPPI, a cellular compartment-specific database of proteins and their interactions enabling an extensive, compartmentalized protein–protein interaction network analysis (URL: http://ComPPI.LinkGroup.hu). ComPPI enables the user to filter biologically unlikely interactions, where the two interacting proteins have no common subcellular localizations and to predict novel properties, such as compartment-specific biological functions. ComPPI is an integrated database covering four species (S. cerevisiae, C. elegans, D. melanogaster and H. sapiens). The compilation of nine protein–protein interaction and eight subcellular localization data sets had four curation steps including a manually built, comprehensive hierarchical structure of >1600 subcellular localizations. ComPPI provides confidence scores for protein subcellular localizations and protein–protein interactions. ComPPI has user-friendly search options for individual proteins giving their subcellular localization, their interactions and the likelihood of their interactions considering the subcellular localization of their interacting partners. Download options of search results, whole-proteomes, organelle-specific interactomes and subcellular localization data are available on its website. Due to its novel features, ComPPI is useful for the analysis of experimental results in biochemistry and molecular biology, as well as for proteome-wide studies in bioinformatics and network science helping cellular biology, medicine and drug design. PMID:25348397

  8. Tuning-free controller to accurately regulate flow rates in a microfluidic network

    PubMed Central

    Heo, Young Jin; Kang, Junsu; Kim, Min Jun; Chung, Wan Kyun

    2016-01-01

    We describe a control algorithm that can improve accuracy and stability of flow regulation in a microfluidic network that uses a conventional pressure pump system. The algorithm enables simultaneous and independent control of fluid flows in multiple micro-channels of a microfluidic network, but does not require any model parameters or tuning process. We investigate robustness and optimality of the proposed control algorithm and those are verified by simulations and experiments. In addition, the control algorithm is compared with a conventional PID controller to show that the proposed control algorithm resolves critical problems induced by the PID control. The capability of the control algorithm can be used not only in high-precision flow regulation in the presence of disturbance, but in some useful functions for lab-on-a-chip devices such as regulation of volumetric flow rate, interface position control of two laminar flows, valveless flow switching, droplet generation and particle manipulation. We demonstrate those functions and also suggest further potential biological applications which can be accomplished by the proposed control framework. PMID:26987587

  9. Neural network and SVM classifiers accurately predict lipid binding proteins, irrespective of sequence homology.

    PubMed

    Bakhtiarizadeh, Mohammad Reza; Moradi-Shahrbabak, Mohammad; Ebrahimi, Mansour; Ebrahimie, Esmaeil

    2014-09-07

    Due to the central roles of lipid binding proteins (LBPs) in many biological processes, sequence based identification of LBPs is of great interest. The major challenge is that LBPs are diverse in sequence, structure, and function which results in low accuracy of sequence homology based methods. Therefore, there is a need for developing alternative functional prediction methods irrespective of sequence similarity. To identify LBPs from non-LBPs, the performances of support vector machine (SVM) and neural network were compared in this study. Comprehensive protein features and various techniques were employed to create datasets. Five-fold cross-validation (CV) and independent evaluation (IE) tests were used to assess the validity of the two methods. The results indicated that SVM outperforms neural network. SVM achieved 89.28% (CV) and 89.55% (IE) overall accuracy in identification of LBPs from non-LBPs and 92.06% (CV) and 92.90% (IE) (in average) for classification of different LBPs classes. Increasing the number and the range of extracted protein features as well as optimization of the SVM parameters significantly increased the efficiency of LBPs class prediction in comparison to the only previous report in this field. Altogether, the results showed that the SVM algorithm can be run on broad, computationally calculated protein features and offers a promising tool in detection of LBPs classes. The proposed approach has the potential to integrate and improve the common sequence alignment based methods.

  10. Accurate High-Temperature Reaction Networks for Alternative Fuels: Butanol Isomers

    SciTech Connect

    Van Geem, K. M.; Pyl, S. P.; Marin, G. B.; Harper, M. R.; Green, W. H.

    2010-11-03

    Oxygenated hydrocarbons, particularly alcohol compounds, are being studied extensively as alternatives and additives to conventional fuels due to their propensity of decreasing soot formation and improving the octane number of gasoline. However, oxygenated fuels also increase the production of toxic byproducts, such as formaldehyde. To gain a better understanding of the oxygenated functional group’s influence on combustion properties—e.g., ignition delay at temperatures above the negative temperature coefficient regime, and the rate of benzene production, which is the common precursor to soot formation—a detailed pressure-dependent reaction network for n-butanol, sec-butanol, and tert-butanol consisting of 281 species and 3608 reactions is presented. The reaction network is validated against shock tube ignition delays and doped methane flame concentration profiles reported previously in the literature, in addition to newly acquired pyrolysis data. Good agreement between simulated and experimental data is achieved in all cases. Flux and sensitivity analyses for each set of experiments have been performed, and high-pressure-limit reaction rate coefficients for important pathways, e.g., the dehydration reactions of the butanol isomers, have been computed using statistical mechanics and quantum chemistry. The different alcohol decomposition pathways, i.e., the pathways from primary, secondary, and tertiary alcohols, are discussed. Furthermore, comparisons between ethanol and n-butanol, two primary alcohols, are presented, as they relate to ignition delay.

  11. Tuning-free controller to accurately regulate flow rates in a microfluidic network

    NASA Astrophysics Data System (ADS)

    Heo, Young Jin; Kang, Junsu; Kim, Min Jun; Chung, Wan Kyun

    2016-03-01

    We describe a control algorithm that can improve accuracy and stability of flow regulation in a microfluidic network that uses a conventional pressure pump system. The algorithm enables simultaneous and independent control of fluid flows in multiple micro-channels of a microfluidic network, but does not require any model parameters or tuning process. We investigate robustness and optimality of the proposed control algorithm and those are verified by simulations and experiments. In addition, the control algorithm is compared with a conventional PID controller to show that the proposed control algorithm resolves critical problems induced by the PID control. The capability of the control algorithm can be used not only in high-precision flow regulation in the presence of disturbance, but in some useful functions for lab-on-a-chip devices such as regulation of volumetric flow rate, interface position control of two laminar flows, valveless flow switching, droplet generation and particle manipulation. We demonstrate those functions and also suggest further potential biological applications which can be accomplished by the proposed control framework.

  12. Tuning-free controller to accurately regulate flow rates in a microfluidic network.

    PubMed

    Heo, Young Jin; Kang, Junsu; Kim, Min Jun; Chung, Wan Kyun

    2016-03-18

    We describe a control algorithm that can improve accuracy and stability of flow regulation in a microfluidic network that uses a conventional pressure pump system. The algorithm enables simultaneous and independent control of fluid flows in multiple micro-channels of a microfluidic network, but does not require any model parameters or tuning process. We investigate robustness and optimality of the proposed control algorithm and those are verified by simulations and experiments. In addition, the control algorithm is compared with a conventional PID controller to show that the proposed control algorithm resolves critical problems induced by the PID control. The capability of the control algorithm can be used not only in high-precision flow regulation in the presence of disturbance, but in some useful functions for lab-on-a-chip devices such as regulation of volumetric flow rate, interface position control of two laminar flows, valveless flow switching, droplet generation and particle manipulation. We demonstrate those functions and also suggest further potential biological applications which can be accomplished by the proposed control framework.

  13. A highly accurate absolute gravimetric network for Albania, Kosovo and Montenegro

    NASA Astrophysics Data System (ADS)

    Ullrich, Christian; Ruess, Diethard; Butta, Hubert; Qirko, Kristaq; Pavicevic, Bozidar; Murat, Meha

    2016-04-01

    The objective of this project is to establish a basic gravity network in Albania, Kosovo and Montenegro to enable further investigations in geodetic and geophysical issues. Therefore the first time in history absolute gravity measurements were performed in these countries. The Norwegian mapping authority Kartverket is assisting the national mapping authorities in Kosovo (KCA) (Kosovo Cadastral Agency - Agjencia Kadastrale e Kosovës), Albania (ASIG) (Autoriteti Shtetëror i Informacionit Gjeohapësinor) and in Montenegro (REA) (Real Estate Administration of Montenegro - Uprava za nekretnine Crne Gore) in improving the geodetic frameworks. The gravity measurements are funded by Kartverket. The absolute gravimetric measurements were performed from BEV (Federal Office of Metrology and Surveying) with the absolute gravimeter FG5-242. As a national metrology institute (NMI) the Metrology Service of the BEV maintains the national standards for the realisation of the legal units of measurement and ensures their international equivalence and recognition. Laser and clock of the absolute gravimeter were calibrated before and after the measurements. The absolute gravimetric survey was carried out from September to October 2015. Finally all 8 scheduled stations were successfully measured: there are three stations located in Montenegro, two stations in Kosovo and three stations in Albania. The stations are distributed over the countries to establish a gravity network for each country. The vertical gradients were measured at all 8 stations with the relative gravimeter Scintrex CG5. The high class quality of some absolute gravity stations can be used for gravity monitoring activities in future. The measurement uncertainties of the absolute gravity measurements range around 2.5 micro Gal at all stations (1 microgal = 10-8 m/s2). In Montenegro the large gravity difference of 200 MilliGal between station Zabljak and Podgorica can be even used for calibration of relative gravimeters

  14. Improved Object Localization Using Accurate Distance Estimation in Wireless Multimedia Sensor Networks.

    PubMed

    Ur Rehman, Yasar Abbas; Tariq, Muhammad; Khan, Omar Usman

    2015-01-01

    Object localization plays a key role in many popular applications of Wireless Multimedia Sensor Networks (WMSN) and as a result, it has acquired a significant status for the research community. A significant body of research performs this task without considering node orientation, object geometry and environmental variations. As a result, the localized object does not reflect the real world scenarios. In this paper, a novel object localization scheme for WMSN has been proposed that utilizes range free localization, computer vision, and principle component analysis based algorithms. The proposed approach provides the best possible approximation of distance between a wmsn sink and an object, and the orientation of the object using image based information. Simulation results report 99% efficiency and an error ratio of 0.01 (around 1 ft) when compared to other popular techniques.

  15. Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data

    PubMed Central

    Liu, Hui; Zhang, Fan; Mishra, Shital Kumar; Zhou, Shuigeng; Zheng, Jie

    2016-01-01

    Modeling of signaling pathways is crucial for understanding and predicting cellular responses to drug treatments. However, canonical signaling pathways curated from literature are seldom context-specific and thus can hardly predict cell type-specific response to external perturbations; purely data-driven methods also have drawbacks such as limited biological interpretability. Therefore, hybrid methods that can integrate prior knowledge and real data for network inference are highly desirable. In this paper, we propose a knowledge-guided fuzzy logic network model to infer signaling pathways by exploiting both prior knowledge and time-series data. In particular, the dynamic time warping algorithm is employed to measure the goodness of fit between experimental and predicted data, so that our method can model temporally-ordered experimental observations. We evaluated the proposed method on a synthetic dataset and two real phosphoproteomic datasets. The experimental results demonstrate that our model can uncover drug-induced alterations in signaling pathways in cancer cells. Compared with existing hybrid models, our method can model feedback loops so that the dynamical mechanisms of signaling networks can be uncovered from time-series data. By calibrating generic models of signaling pathways against real data, our method supports precise predictions of context-specific anticancer drug effects, which is an important step towards precision medicine. PMID:27774993

  16. A quantitative chaperone interaction network reveals the architecture of cellular protein homeostasis pathways

    PubMed Central

    Taipale, Mikko; Tucker, George; Peng, Jian; Krykbaeva, Irina; Lin, Zhen-Yuan; Larsen, Brett; Choi, Hyungwon; Berger, Bonnie; Gingras, Anne-Claude; Lindquist, Susan

    2014-01-01

    Chaperones are abundant cellular proteins that promote the folding and function of their substrate proteins (clients). In vivo, chaperones also associate with a large and diverse set of co-factors (co-chaperones) that regulate their specificity and function. However, how these co-chaperones regulate protein folding and whether they have chaperone-independent biological functions is largely unknown. We have combined mass spectrometry and quantitative high-throughput LUMIER assays to systematically characterize the chaperone/co-chaperone/client interaction network in human cells. We uncover hundreds of novel chaperone clients, delineate their participation in specific co-chaperone complexes, and establish a surprisingly distinct network of protein/protein interactions for co-chaperones. As a salient example of the power of such analysis, we establish that NUDC family co-chaperones specifically associate with structurally related but evolutionarily distinct β-propeller folds. We provide a framework for deciphering the proteostasis network, its regulation in development and disease, and expand the use of chaperones as sensors for drug/target engagement. PMID:25036637

  17. Proof-of-Concept of a Millimeter-Wave Integrated Heterogeneous Network for 5G Cellular.

    PubMed

    Okasaka, Shozo; Weiler, Richard J; Keusgen, Wilhelm; Pudeyev, Andrey; Maltsev, Alexander; Karls, Ingolf; Sakaguchi, Kei

    2016-08-25

    The fifth-generation mobile networks (5G) will not only enhance mobile broadband services, but also enable connectivity for a massive number of Internet-of-Things devices, such as wireless sensors, meters or actuators. Thus, 5G is expected to achieve a 1000-fold or more increase in capacity over 4G. The use of the millimeter-wave (mmWave) spectrum is a key enabler to allowing 5G to achieve such enhancement in capacity. To fully utilize the mmWave spectrum, 5G is expected to adopt a heterogeneous network (HetNet) architecture, wherein mmWave small cells are overlaid onto a conventional macro-cellular network. In the mmWave-integrated HetNet, splitting of the control plane (CP) and user plane (UP) will allow continuous connectivity and increase the capacity of the mmWave small cells. mmWave communication can be used not only for access linking, but also for wireless backhaul linking, which will facilitate the installation of mmWave small cells. In this study, a proof-of-concept (PoC) was conducted to demonstrate the practicality of a prototype mmWave-integrated HetNet, using mmWave technologies for both backhaul and access.

  18. Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data

    NASA Astrophysics Data System (ADS)

    Liu, Hui; Zhang, Fan; Mishra, Shital Kumar; Zhou, Shuigeng; Zheng, Jie

    2016-10-01

    Modeling of signaling pathways is crucial for understanding and predicting cellular responses to drug treatments. However, canonical signaling pathways curated from literature are seldom context-specific and thus can hardly predict cell type-specific response to external perturbations; purely data-driven methods also have drawbacks such as limited biological interpretability. Therefore, hybrid methods that can integrate prior knowledge and real data for network inference are highly desirable. In this paper, we propose a knowledge-guided fuzzy logic network model to infer signaling pathways by exploiting both prior knowledge and time-series data. In particular, the dynamic time warping algorithm is employed to measure the goodness of fit between experimental and predicted data, so that our method can model temporally-ordered experimental observations. We evaluated the proposed method on a synthetic dataset and two real phosphoproteomic datasets. The experimental results demonstrate that our model can uncover drug-induced alterations in signaling pathways in cancer cells. Compared with existing hybrid models, our method can model feedback loops so that the dynamical mechanisms of signaling networks can be uncovered from time-series data. By calibrating generic models of signaling pathways against real data, our method supports precise predictions of context-specific anticancer drug effects, which is an important step towards precision medicine.

  19. Proof-of-Concept of a Millimeter-Wave Integrated Heterogeneous Network for 5G Cellular

    PubMed Central

    Okasaka, Shozo; Weiler, Richard J.; Keusgen, Wilhelm; Pudeyev, Andrey; Maltsev, Alexander; Karls, Ingolf; Sakaguchi, Kei

    2016-01-01

    The fifth-generation mobile networks (5G) will not only enhance mobile broadband services, but also enable connectivity for a massive number of Internet-of-Things devices, such as wireless sensors, meters or actuators. Thus, 5G is expected to achieve a 1000-fold or more increase in capacity over 4G. The use of the millimeter-wave (mmWave) spectrum is a key enabler to allowing 5G to achieve such enhancement in capacity. To fully utilize the mmWave spectrum, 5G is expected to adopt a heterogeneous network (HetNet) architecture, wherein mmWave small cells are overlaid onto a conventional macro-cellular network. In the mmWave-integrated HetNet, splitting of the control plane (CP) and user plane (UP) will allow continuous connectivity and increase the capacity of the mmWave small cells. mmWave communication can be used not only for access linking, but also for wireless backhaul linking, which will facilitate the installation of mmWave small cells. In this study, a proof-of-concept (PoC) was conducted to demonstrate the practicality of a prototype mmWave-integrated HetNet, using mmWave technologies for both backhaul and access. PMID:27571074

  20. Network, cellular, and molecular mechanisms underlying long-term memory formation.

    PubMed

    Carasatorre, Mariana; Ramírez-Amaya, Víctor

    2013-01-01

    The neural network stores information through activity-dependent synaptic plasticity that occurs in populations of neurons. Persistent forms of synaptic plasticity may account for long-term memory storage, and the most salient forms are the changes in the structure of synapses. The theory proposes that encoding should use a sparse code and evidence suggests that this can be achieved through offline reactivation or by sparse initial recruitment of the network units. This idea implies that in some cases the neurons that underwent structural synaptic plasticity might be a subpopulation of those originally recruited; However, it is not yet clear whether all the neurons recruited during acquisition are the ones that underwent persistent forms of synaptic plasticity and responsible for memory retrieval. To determine which neural units underlie long-term memory storage, we need to characterize which are the persistent forms of synaptic plasticity occurring in these neural ensembles and the best hints so far are the molecular signals underlying structural modifications of the synapses. Structural synaptic plasticity can be achieved by the activity of various signal transduction pathways, including the NMDA-CaMKII and ACh-MAPK. These pathways converge with the Rho family of GTPases and the consequent ERK 1/2 activation, which regulates multiple cellular functions such as protein translation, protein trafficking, and gene transcription. The most detailed explanation may come from models that allow us to determine the contribution of each piece of this fascinating puzzle that is the neuron and the neural network.

  1. Wi-GIM system: a new wireless sensor network (WSN) for accurate ground instability monitoring

    NASA Astrophysics Data System (ADS)

    Mucchi, Lorenzo; Trippi, Federico; Schina, Rosa; Fornaciai, Alessandro; Gigli, Giovanni; Nannipieri, Luca; Favalli, Massimiliano; Marturia Alavedra, Jordi; Intrieri, Emanuele; Agostini, Andrea; Carnevale, Ennio; Bertolini, Giovanni; Pizziolo, Marco; Casagli, Nicola

    2016-04-01

    Landslides are among the most serious and common geologic hazards around the world. Their impact on human life is expected to increase in the next future as a consequence of human-induced climate change as well as the population growth in proximity of unstable slopes. Therefore, developing better performing technologies for monitoring landslides and providing local authorities with new instruments able to help them in the decision making process, is becoming more and more important. The recent progresses in Information and Communication Technologies (ICT) allow us to extend the use of wireless technologies in landslide monitoring. In particular, the developments in electronics components have permitted to lower the price of the sensors and, at the same time, to actuate more efficient wireless communications. In this work we present a new wireless sensor network (WSN) system, designed and developed for landslide monitoring in the framework of EU Wireless Sensor Network for Ground Instability Monitoring - Wi-GIM project (LIFE12 ENV/IT/001033). We show the preliminary performance of the Wi-GIM system after the first period of monitoring on the active Roncovetro Landslide and on a large subsiding area in the neighbourhood of Sallent village. The Roncovetro landslide is located in the province of Reggio Emilia (Italy) and moved an inferred volume of about 3 million cubic meters. Sallent village is located at the centre of the Catalan evaporitic basin in Spain. The Wi-GIM WSN monitoring system consists of three levels: 1) Master/Gateway level coordinates the WSN and performs data aggregation and local storage; 2) Master/Server level takes care of acquiring and storing data on a remote server; 3) Nodes level that is based on a mesh of peripheral nodes, each consisting in a sensor board equipped with sensors and wireless module. The nodes are located in the landslide ground perimeter and are able to create an ad-hoc WSN. The location of each sensor on the ground is

  2. Dynamic Bayesian Network for Accurate Detection of Peptides from Tandem Mass Spectra.

    PubMed

    Halloran, John T; Bilmes, Jeff A; Noble, William S

    2016-08-05

    A central problem in mass spectrometry analysis involves identifying, for each observed tandem mass spectrum, the corresponding generating peptide. We present a dynamic Bayesian network (DBN) toolkit that addresses this problem by using a machine learning approach. At the heart of this toolkit is a DBN for Rapid Identification (DRIP), which can be trained from collections of high-confidence peptide-spectrum matches (PSMs). DRIP's score function considers fragment ion matches using Gaussians rather than fixed fragment-ion tolerances and also finds the optimal alignment between the theoretical and observed spectrum by considering all possible alignments, up to a threshold that is controlled using a beam-pruning algorithm. This function not only yields state-of-the art database search accuracy but also can be used to generate features that significantly boost the performance of the Percolator postprocessor. The DRIP software is built upon a general purpose DBN toolkit (GMTK), thereby allowing a wide variety of options for user-specific inference tasks as well as facilitating easy modifications to the DRIP model in future work. DRIP is implemented in Python and C++ and is available under Apache license at http://melodi-lab.github.io/dripToolkit .

  3. Viral Replication Protein Inhibits Cellular Cofilin Actin Depolymerization Factor to Regulate the Actin Network and Promote Viral Replicase Assembly

    PubMed Central

    Kovalev, Nikolay; de Castro Martín, Isabel Fernández; Barajas, Daniel; Risco, Cristina; Nagy, Peter D.

    2016-01-01

    RNA viruses exploit host cells by co-opting host factors and lipids and escaping host antiviral responses. Previous genome-wide screens with Tomato bushy stunt virus (TBSV) in the model host yeast have identified 18 cellular genes that are part of the actin network. In this paper, we show that the p33 viral replication factor interacts with the cellular cofilin (Cof1p), which is an actin depolymerization factor. Using temperature-sensitive (ts) Cof1p or actin (Act1p) mutants at a semi-permissive temperature, we find an increased level of TBSV RNA accumulation in yeast cells and elevated in vitro activity of the tombusvirus replicase. We show that the large p33 containing replication organelle-like structures are located in the close vicinity of actin patches in yeast cells or around actin cable hubs in infected plant cells. Therefore, the actin filaments could be involved in VRC assembly and the formation of large viral replication compartments containing many individual VRCs. Moreover, we show that the actin network affects the recruitment of viral and cellular components, including oxysterol binding proteins and VAP proteins to form membrane contact sites for efficient transfer of sterols to the sites of replication. Altogether, the emerging picture is that TBSV, via direct interaction between the p33 replication protein and Cof1p, controls cofilin activities to obstruct the dynamic actin network that leads to efficient subversion of cellular factors for pro-viral functions. In summary, the discovery that TBSV interacts with cellular cofilin and blocks the severing of existing filaments and the formation of new actin filaments in infected cells opens a new window to unravel the way by which viruses could subvert/co-opt cellular proteins and lipids. By regulating the functions of cofilin and the actin network, which are central nodes in cellular pathways, viruses could gain supremacy in subversion of cellular factors for pro-viral functions. PMID:26863541

  4. System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network of soybean (Glycine max).

    PubMed

    Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

    2014-01-01

    Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome

  5. Global detection of live virtual machine migration based on cellular neural networks.

    PubMed

    Xie, Kang; Yang, Yixian; Zhang, Ling; Jing, Maohua; Xin, Yang; Li, Zhongxian

    2014-01-01

    In order to meet the demands of operation monitoring of large scale, autoscaling, and heterogeneous virtual resources in the existing cloud computing, a new method of live virtual machine (VM) migration detection algorithm based on the cellular neural networks (CNNs), is presented. Through analyzing the detection process, the parameter relationship of CNN is mapped as an optimization problem, in which improved particle swarm optimization algorithm based on bubble sort is used to solve the problem. Experimental results demonstrate that the proposed method can display the VM migration processing intuitively. Compared with the best fit heuristic algorithm, this approach reduces the processing time, and emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI) implementation allowing the VM migration detection to be performed better.

  6. Modeling of trophospheric ozone concentrations using genetically trained multi-level cellular neural networks

    NASA Astrophysics Data System (ADS)

    Ozcan, H. Kurtulus; Bilgili, Erdem; Sahin, Ulku; Ucan, O. Nuri; Bayat, Cuma

    2007-09-01

    Tropospheric ozone concentrations, which are an important air pollutant, are modeled by the use of an artificial intelligence structure. Data obtained from air pollution measurement stations in the city of Istanbul are utilized in constituting the model. A supervised algorithm for the evaluation of ozone concentration using a genetically trained multi-level cellular neural network (ML-CNN) is introduced, developed, and applied to real data. A genetic algorithm is used in the optimization of CNN templates. The model results and the actual measurement results are compared and statistically evaluated. It is observed that seasonal changes in ozone concentrations are reflected effectively by the concentrations estimated by the multilevel-CNN model structure, with a correlation value of 0.57 ascertained between actual and model results. It is shown that the multilevel-CNN modeling technique is as satisfactory as other modeling techniques in associating the data in a complex medium in air pollution applications.

  7. A novel method to assess human population exposure induced by a wireless cellular network.

    PubMed

    Varsier, Nadège; Plets, David; Corre, Yoann; Vermeeren, Günter; Joseph, Wout; Aerts, Sam; Martens, Luc; Wiart, Joe

    2015-09-01

    This paper presents a new metric to evaluate electromagnetic exposure induced by wireless cellular networks. This metric takes into account the exposure induced by base station antennas as well as exposure induced by wireless devices to evaluate average global exposure of the population in a specific geographical area. The paper first explains the concept and gives the formulation of the Exposure Index (EI). Then, the EI computation is illustrated through simple phone call scenarios (indoor office, in train) and a complete macro urban data long-term evolution scenario showing how, based on simulations, radio-planning predictions, realistic population statistics, user traffic data, and specific absorption rate calculations can be combined to assess the index. Bioelectromagnetics. 36:451-463, 2015. © 2015 Wiley Periodicals, Inc.

  8. Parallelism on the Intel 860 Hypercube:. Ising Magnets, Hydrodynamical Cellular Automata and Neural Networks

    NASA Astrophysics Data System (ADS)

    Kohring, G. A.; Stauffer, D.

    Geometric parallelization was tested on the Intel Hypercube with 32 MIMD processors of 1860 type, each with 16 Mbytes of distributed memory. We applied it to Ising models in two and three dimensions as well as to neural networks and two-dimensional hydrodynamic cellular automata. For system sizes suited to this machine, up to 60960*60960 and 1410*1410*1408 Ising spins, we found nearly hundred percent parallel efficiency in spite of the needed inter-processor communications. For small systems, the observed deviations from full efficiency were compared with the scaling concepts of Heermann and Burkitt and of Jakobs and Gerling. For Ising models, we determined the Glauber kinetic exponent z≃2.18 in two dimensions and confirmed the stretched exponential relaxation of the magnetization towards the spontaneous magnetization below Tc. For three dimensions we found z≃2.09 and simple exponential relaxation.

  9. Spike integration and cellular memory in a rhythmic network from Na+/K+ pump current dynamics

    PubMed Central

    Pulver, Stefan R.

    2009-01-01

    The output of a neural circuit results from an interaction between the intrinsic properties of neurons within the circuit and the features of the synaptic connections between them. The plasticity of intrinsic properties has been primarily attributed to modification of ion channel function and/or number. In this study, we demonstrate a mechanism for intrinsic plasticity in rhythmically active Drosophila neurons that is not conductance-based. Larval motor neurons show a long lasting sodium-dependent afterhyperpolarization (AHP) following bursts of action potentials that is mediated by the electrogenic activity of Na+/K+ ATPase. This AHP persists for multiple seconds following volleys of action potentials and is able to function as a pattern-insensitive integrator of spike number that is independent of external calcium. This current also interacts with endogenous Shal K+ conductances to modulate spike timing for multiple seconds following rhythmic activity, providing a cellular memory of network activity on a behaviorally relevant time scale. PMID:19966842

  10. Adaptive call admission control and resource allocation in multi server wireless/cellular network

    NASA Astrophysics Data System (ADS)

    Jain, Madhu; Mittal, Ragini

    2016-11-01

    The ever increasing demand of the subscribers has put pressure on the capacity of wireless networks around the world. To utilize the scare resources, in the present paper we propose an optimal allocation scheme for an integrated wireless/cellular model with handoff priority and handoff guarantee services. The suggested algorithm optimally allocates the resources in each cell and dynamically adjust threshold to control the admission. To give the priority to handoff calls over the new calls, the provision of guard channels and subrating scheme is taken into consideration. The handoff voice call may balk and renege from the system while waiting in the buffer. An iterative algorithm is implemented to generate the arrival rate of the handoff calls in each cell. Various performance indices are established in term of steady state probabilities. The sensitivity analysis has also been carried out to examine the tractability of algorithms and to explore the effects of system descriptors on the performance indices.

  11. Smart-Pixel Array Processors Based on Optimal Cellular Neural Networks for Space Sensor Applications

    NASA Technical Reports Server (NTRS)

    Fang, Wai-Chi; Sheu, Bing J.; Venus, Holger; Sandau, Rainer

    1997-01-01

    A smart-pixel cellular neural network (CNN) with hardware annealing capability, digitally programmable synaptic weights, and multisensor parallel interface has been under development for advanced space sensor applications. The smart-pixel CNN architecture is a programmable multi-dimensional array of optoelectronic neurons which are locally connected with their local neurons and associated active-pixel sensors. Integration of the neuroprocessor in each processor node of a scalable multiprocessor system offers orders-of-magnitude computing performance enhancements for on-board real-time intelligent multisensor processing and control tasks of advanced small satellites. The smart-pixel CNN operation theory, architecture, design and implementation, and system applications are investigated in detail. The VLSI (Very Large Scale Integration) implementation feasibility was illustrated by a prototype smart-pixel 5x5 neuroprocessor array chip of active dimensions 1380 micron x 746 micron in a 2-micron CMOS technology.

  12. BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling

    PubMed Central

    Feng, Song; Ollivier, Julien F.; Swain, Peter S.; Soyer, Orkun S.

    2015-01-01

    Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx. PMID:26101250

  13. Roadmap to cellular reprogramming--manipulating transcriptional networks with DNA, RNA, proteins and small molecules.

    PubMed

    Wörsdörfer, P; Thier, M; Kadari, A; Edenhofer, F

    2013-06-01

    Recent reports demonstrate that the plasticity of mammalian somatic cells is much higher than previously assumed and that ectopic expression of transcription factors may have the potential to induce the conversion of any cell type into another. Fibroblast cells can be converted into embryonic stem cell-like cells, neural cells, cardiomyocytes, macrophage-like cells as well as blood progenitors. Additionally, the conversion of astrocytes into neurons or neural stem cells into monocytes has been demonstrated. Nowadays, in the era of systems biology, continuously growing holistic data sets are providing increasing insights into core transcriptional networks and cellular signaling pathways. This knowledge enables cell biologists to understand how cellular fate is determined and how it could be manipulated. As a consequence for biomedical applications, it might be soon possible to convert patient specific somatic cells directly into desired transplantable other cell types. The clinical value, however, of such reprogrammed cells is currently limited due to the invasiveness of methods applied to induce reprogramming factor activity. This review will focus on experimental strategies to ectopically induce cell fate modulators. We will emphasize those strategies that enable efficient and robust overexpression of transcription factors by minimal genetic alterations of the host genome. Furthermore, we will discuss procedures devoid of any genomic manipulation, such as the direct delivery of mRNA, proteins, or the use of small molecules. By this, we aim to give a comprehensive overview on state of the art techniques that harbor the potential to generate safe reprogrammed cells for clinical applications.

  14. Intragranular cellular segregation network structure strengthening 316L stainless steel prepared by selective laser melting

    NASA Astrophysics Data System (ADS)

    Zhong, Yuan; Liu, Leifeng; Wikman, Stefan; Cui, Daqing; Shen, Zhijian

    2016-03-01

    A feasibility study was performed to fabricate ITER In-Vessel components by Selective Laser Melting (SLM) supported by Fusion for Energy (F4E). Almost fully dense 316L stainless steel (SS316L) components were prepared from gas-atomized powder and with optimized SLM processing parameters. Tensile tests and Charpy-V tests were carried out at 22 °C and 250 °C and the results showed that SLM SS316L fulfill the RCC-MR code. Microstructure characterization reveals the presence of hierarchical macro-, micro- and nano-structures in as-built samples that were very different from SS316L microstructures prepared by other established methods. The formation of a characteristic intragranular cellular segregation network microstructure appears to contribute to the increase of yield strength without losing ductility. Silicon oxide nano-inclusions were formed during the SLM process that generated a micro-hardness fluctuation in the building direction. The combined influence of a cellular microstructure and the nano-inclusions constraints the size of ductile dimples to nano-scale. The crack propagation is hindered by a pinning effect that improves the defect-tolerance of the SLM SS316L. This work proves that it was possible to manufacture SS316L with properties suitable for ITER First Wall panels. Further studies on irradiation properties of SLM SS316L and manufacturing of larger real-size components are needed.

  15. Computerized detection of pulmonary nodules using cellular neural networks in CT images

    NASA Astrophysics Data System (ADS)

    Zhang, Xiangwei; McLennan, Geoffrey; Hoffman, Eric A.; Sonka, Milan

    2004-05-01

    The purpose of this study is to develop a computer-aided diagnosis (CAD) system to detect small-sized (from 2mm to 10mm) non-pleural pulmonary nodules in high resolution helical CT scans. A new 3D automated scheme using cellular neural networks is presented. Different from most previous methods, this scheme employed the local shape property to perform voxel classification. The shape index feature successfully captured the local shape difference between nodules and non-nodules, especially vessels. A 3D discrete-time cellular neural network (DTCNN) was constructed to give a reliable voxel classification by collecting information in a neighborhood. To tailor it for lung nodule detection, this DTCNN was trained using genetic algorithms (GAs) to derive the shape index variation pattern of nodules. 19 clinical thoracic CT cases involving a total of 4838 sectional images were used in this work, with 2 scans forming the training set, and the remaining 17 cases being the testing set. The evaluation was composed of two stages. During the first stage, a pulmonologist and our CAD system independently detected nodules in the testing set. Then, the suspected nodule areas located by the computer were reviewed by the pulmonologist to confirm nodules missed by the human in the first review. There were 32 true nodules detected by the computer but missed by the pulmonologist in the first review, in which 30 non-juxtapleural nodules were found. Considering the nodules detected by the pulmonologist during the first and second reviews as the truth, 52 of 62 non-pleural nodules were detected by the CAD system (sensitivity being 83.9%), with the number of false positives being 3.47 per case.

  16. Input-dependent wave propagations in asymmetric cellular automata: possible behaviors of feed-forward loop in biological reaction network.

    PubMed

    Awazu, Akinori

    2008-07-01

    Dynamical aspects of the asymmetric cellular automata were investigated to consider the signaling processes in biological systems. As a meta-model of the cascade of feed-forward loop type network motifs in biological reaction networks, we consider the one dimensional asymmetric cellular automata where the state of each cell is controlled by a trio of cells, the cell itself, the nearest upstream cell and the next nearest upstream cell. Through the systematic simulations, some novel input-dependent wave propagations were found in certain asymmetric CA, which may be useful for the signaling processes like the distinction, the filtering and the memory of external stimuli.

  17. Energy-Efficient Crowdsensing of Human Mobility and Signal Levels in Cellular Networks

    PubMed Central

    Foremski, Paweł; Gorawski, Michał; Grochla, Krzysztof; Polys, Konrad

    2015-01-01

    The paper presents a practical application of the crowdsensing idea to measure human mobility and signal coverage in cellular networks. Currently, virtually everyone is carrying a mobile phone, which may be used as a sensor to gather research data by measuring, e.g., human mobility and radio signal levels. However, many users are unwilling to participate in crowdsensing experiments. This work begins with the analysis of the barriers for engaging people in crowdsensing. A survey showed that people who agree to participate in crowdsensing expect a minimum impact on their battery lifetime and phone usage habits. To address these requirements, this paper proposes an application for measuring the location and signal strength data based on energy-efficient GPS tracking, which allows one to perform the measurements of human mobility and radio signal levels with minimum energy utilization and without any engagement of the user. The method described combines measurements from the accelerometer with effective management of the GPS to monitor the user mobility with the decrease in battery lifetime by approximately 20%. To show the applicability of the proposed platform, the sample results of signal level distribution and coverage maps gathered for an LTE network and representing human mobility are shown. PMID:26340633

  18. Inter-cellular signaling network reveals a mechanistic transition in tumor microenvironment

    PubMed Central

    Wu, Yu; Garmire, Lana X.; Fan, Rong

    2012-01-01

    We conducted inter-cellular cytokine correlation and network analysis based upon a stochastic population dynamics model that comprises five cell types and fifteen signaling molecules inter-connected through a large number of cell-cell communication pathways. We observed that the signaling molecules are tightly correlated even at very early stages (e.g. the first month) of human glioma, but such correlation rapidly diminishes when tumor grows to a size that can be clinically detected. Further analysis suggests that paracrine is shown to be the dominant force during tumor initiation and priming, while autocrine supersedes it and supports a robust tumor expansion. In correspondence, the cytokine correlation network evolves through an increasing to decreasing complexity. This study indicates a possible mechanistic transition from the microenvironment-controlled, paracrine-based regulatory mechanism to self-sustained rapid progression to fetal malignancy. It also reveals key nodes that are responsible for such transition and can be potentially harnessed for the design of new anti-cancer therapies. PMID:23080410

  19. Trans-species learning of cellular signaling systems with bimodal deep belief networks

    PubMed Central

    Chen, Lujia; Cai, Chunhui; Chen, Vicky; Lu, Xinghua

    2015-01-01

    Motivation: Model organisms play critical roles in biomedical research of human diseases and drug development. An imperative task is to translate information/knowledge acquired from model organisms to humans. In this study, we address a trans-species learning problem: predicting human cell responses to diverse stimuli, based on the responses of rat cells treated with the same stimuli. Results: We hypothesized that rat and human cells share a common signal-encoding mechanism but employ different proteins to transmit signals, and we developed a bimodal deep belief network and a semi-restricted bimodal deep belief network to represent the common encoding mechanism and perform trans-species learning. These ‘deep learning’ models include hierarchically organized latent variables capable of capturing the statistical structures in the observed proteomic data in a distributed fashion. The results show that the models significantly outperform two current state-of-the-art classification algorithms. Our study demonstrated the potential of using deep hierarchical models to simulate cellular signaling systems. Availability and implementation: The software is available at the following URL: http://pubreview.dbmi.pitt.edu/TransSpeciesDeepLearning/. The data are available through SBV IMPROVER website, https://www.sbvimprover.com/challenge-2/overview, upon publication of the report by the organizers. Contact: xinghua@pitt.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25995230

  20. Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

    PubMed Central

    Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

    2015-01-01

    Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases. PMID:26608097

  1. Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

    NASA Astrophysics Data System (ADS)

    Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

    2015-11-01

    Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

  2. Examining the limits of cellular adaptation bursting mechanisms in biologically-based excitatory networks of the hippocampus.

    PubMed

    Ferguson, K A; Njap, F; Nicola, W; Skinner, F K; Campbell, S A

    2015-12-01

    Determining the biological details and mechanisms that are essential for the generation of population rhythms in the mammalian brain is a challenging problem. This problem cannot be addressed either by experimental or computational studies in isolation. Here we show that computational models that are carefully linked with experiment provide insight into this problem. Using the experimental context of a whole hippocampus preparation in vitro that spontaneously expresses theta frequency (3-12 Hz) population bursts in the CA1 region, we create excitatory network models to examine whether cellular adaptation bursting mechanisms could critically contribute to the generation of this rhythm. We use biologically-based cellular models of CA1 pyramidal cells and network sizes and connectivities that correspond to the experimental context. By expanding our mean field analyses to networks with heterogeneity and non all-to-all coupling, we allow closer correspondence with experiment, and use these analyses to greatly extend the range of parameter values that are explored. We find that our model excitatory networks can produce theta frequency population bursts in a robust fashion.Thus, even though our networks are limited by not including inhibition at present, our results indicate that cellular adaptation in pyramidal cells could be an important aspect for the occurrence of theta frequency population bursting in the hippocampus. These models serve as a starting framework for the inclusion of inhibitory cells and for the consideration of additional experimental features not captured in our present network models.

  3. Anisotropic cellular network formation in engineered muscle tissue through the self-organization of neurons and endothelial cells.

    PubMed

    Takahashi, Hironobu; Shimizu, Tatsuya; Nakayama, Masamichi; Yamato, Masayuki; Okano, Teruo

    2015-02-18

    Tissue anisotropy directed by cell sheets: Aligned myoblasts can be harvested as an anisotropic cell sheet using a micropatterned thermoresponsive substrate. Neurons and endothelial cells sandwiched between multiple anisotropic cell sheets self-organize oriented cellular networks in the tissue construct. This simple tissue engineering technique is useful for the creation of biomimetic microstructures in complex tissue, required for future advances in regenerative medicine.

  4. DNA-damage response network at the crossroads of cell-cycle checkpoints, cellular senescence and apoptosis.

    PubMed

    Schmitt, Estelle; Paquet, Claudie; Beauchemin, Myriam; Bertrand, Richard

    2007-06-01

    Tissue homeostasis requires a carefully-orchestrated balance between cell proliferation, cellular senescence and cell death. Cells proliferate through a cell cycle that is tightly regulated by cyclin-dependent kinase activities. Cellular senescence is a safeguard program limiting the proliferative competence of cells in living organisms. Apoptosis eliminates unwanted cells by the coordinated activity of gene products that regulate and effect cell death. The intimate link between the cell cycle, cellular senescence, apoptosis regulation, cancer development and tumor responses to cancer treatment has become eminently apparent. Extensive research on tumor suppressor genes, oncogenes, the cell cycle and apoptosis regulatory genes has revealed how the DNA damage-sensing and -signaling pathways, referred to as the DNA-damage response network, are tied to cell proliferation, cell-cycle arrest, cellular senescence and apoptosis. DNA-damage responses are complex, involving "sensor" proteins that sense the damage, and transmit signals to "transducer" proteins, which, in turn, convey the signals to numerous "effector" proteins implicated in specific cellular pathways, including DNA repair mechanisms, cell-cycle checkpoints, cellular senescence and apoptosis. The Bcl-2 family of proteins stands among the most crucial regulators of apoptosis and performs vital functions in deciding whether a cell will live or die after cancer chemotherapy and irradiation. In addition, several studies have now revealed that members of the Bcl-2 family also interface with the cell cycle, DNA repair/recombination and cellular senescence, effects that are generally distinct from their function in apoptosis. In this review, we report progress in understanding the molecular networks that regulate cell-cycle checkpoints, cellular senescence and apoptosis after DNA damage, and discuss the influence of some Bcl-2 family members on cell-cycle checkpoint regulation.

  5. Astrocytic gap junctional networks suppress cellular damage in an in vitro model of ischemia

    SciTech Connect

    Shinotsuka, Takanori; Yasui, Masato; Nuriya, Mutsuo

    2014-02-07

    Highlights: • Astrocytes exhibit characteristic changes in [Ca{sup 2+}]{sub i} under OGD. • Astrocytic [Ca{sup 2+}]{sub i} increase is synchronized with a neuronal anoxic depolarization. • Gap junctional couplings protect neurons as well as astrocytes during OGD. - Abstract: Astrocytes play pivotal roles in both the physiology and the pathophysiology of the brain. They communicate with each other via extracellular messengers as well as through gap junctions, which may exacerbate or protect against pathological processes in the brain. However, their roles during the acute phase of ischemia and the underlying cellular mechanisms remain largely unknown. To address this issue, we imaged changes in the intracellular calcium concentration ([Ca{sup 2+}]{sub i}) in astrocytes in mouse cortical slices under oxygen/glucose deprivation (OGD) condition using two-photon microscopy. Under OGD, astrocytes showed [Ca{sup 2+}]{sub i} oscillations followed by larger and sustained [Ca{sup 2+}]{sub i} increases. While the pharmacological blockades of astrocytic receptors for glutamate and ATP had no effect, the inhibitions of gap junctional intercellular coupling between astrocytes significantly advanced the onset of the sustained [Ca{sup 2+}]{sub i} increase after OGD exposure. Interestingly, the simultaneous recording of the neuronal membrane potential revealed that the onset of the sustained [Ca{sup 2+}]{sub i} increase in astrocytes was synchronized with the appearance of neuronal anoxic depolarization. Furthermore, the blockade of gap junctional coupling resulted in a concurrent faster appearance of neuronal depolarizations, which remain synchronized with the sustained [Ca{sup 2+}]{sub i} increase in astrocytes. These results indicate that astrocytes delay the appearance of the pathological responses of astrocytes and neurons through their gap junction-mediated intercellular network under OGD. Thus, astrocytic gap junctional networks provide protection against tissue damage

  6. A universal concept based on cellular neural networks for ultrafast and flexible solving of differential equations.

    PubMed

    Chedjou, Jean Chamberlain; Kyamakya, Kyandoghere

    2015-04-01

    This paper develops and validates a comprehensive and universally applicable computational concept for solving nonlinear differential equations (NDEs) through a neurocomputing concept based on cellular neural networks (CNNs). High-precision, stability, convergence, and lowest-possible memory requirements are ensured by the CNN processor architecture. A significant challenge solved in this paper is that all these cited computing features are ensured in all system-states (regular or chaotic ones) and in all bifurcation conditions that may be experienced by NDEs.One particular quintessence of this paper is to develop and demonstrate a solver concept that shows and ensures that CNN processors (realized either in hardware or in software) are universal solvers of NDE models. The solving logic or algorithm of given NDEs (possible examples are: Duffing, Mathieu, Van der Pol, Jerk, Chua, Rössler, Lorenz, Burgers, and the transport equations) through a CNN processor system is provided by a set of templates that are computed by our comprehensive templates calculation technique that we call nonlinear adaptive optimization. This paper is therefore a significant contribution and represents a cutting-edge real-time computational engineering approach, especially while considering the various scientific and engineering applications of this ultrafast, energy-and-memory-efficient, and high-precise NDE solver concept. For illustration purposes, three NDE models are demonstratively solved, and related CNN templates are derived and used: the periodically excited Duffing equation, the Mathieu equation, and the transport equation.

  7. Residual Separation of Magnetic Fields Using a Cellular Neural Network Approach

    NASA Astrophysics Data System (ADS)

    Albora, A. M.; Özmen, A.; Uçan, O. N.

    - In this paper, a Cellular Neural Network (CNN) has been applied to a magnetic regional/residual anomaly separation problem. CNN is an analog parallel computing paradigm defined in space and characterized by the locality of connections between processing neurons. The behavior of the CNN is defined by the template matrices A, B and the template vector I. We have optimized weight coefficients of these templates using Recurrent Perceptron Learning Algorithm (RPLA). The advantages of CNN as a real-time stochastic method are that it introduces little distortion to the shape of the original image and that it is not effected significantly by factors such as the overlap of power spectra of residual fields. The proposed method is tested using synthetic examples and the average depth of the buried objects has been estimated by power spectrum analysis. Next the CNN approach is applied to magnetic data over the Golalan chromite mine in Elazig which lies East of Turkey. This area is among the largest and richest chromite masses of the world. We compared the performance of CNN to classical derivative approaches.

  8. Early warning of illegal development for protected areas by integrating cellular automata with neural networks.

    PubMed

    Li, Xia; Lao, Chunhua; Liu, Yilun; Liu, Xiaoping; Chen, Yimin; Li, Shaoying; Ai, Bing; He, Zijian

    2013-11-30

    Ecological security has become a major issue under fast urbanization in China. As the first two cities in this country, Shenzhen and Dongguan issued the ordinance of Eco-designated Line of Control (ELC) to "wire" ecologically important areas for strict protection in 2005 and 2009 respectively. Early warning systems (EWS) are a useful tool for assisting the implementation ELC. In this study, a multi-model approach is proposed for the early warning of illegal development by integrating cellular automata (CA) and artificial neural networks (ANN). The objective is to prevent the ecological risks or catastrophe caused by such development at an early stage. The integrated model is calibrated by using the empirical information from both remote sensing and handheld GPS (global positioning systems). The MAR indicator which is the ratio of missing alarms to all the warnings is proposed for better assessment of the model performance. It is found that the fast urban development has caused significant threats to natural-area protection in the study area. The integration of CA, ANN and GPS provides a powerful tool for describing and predicting illegal development which is in highly non-linear and fragmented forms. The comparison shows that this multi-model approach has much better performances than the single-model approach for the early warning. Compared with the single models of CA and ANN, this integrated multi-model can improve the value of MAR by 65.48% and 5.17% respectively.

  9. Adiponectin fine-tuning of liver regeneration dynamics revealed through cellular network modeling.

    PubMed

    Correnti, Jason M; Cook, Daniel; Aksamitiene, Edita; Swarup, Aditi; Ogunnaike, Babatunde; Vadigepalli, Rajanikanth; Hoek, Jan B

    2014-11-10

    Following partial hepatectomy, the liver initiates a regenerative program involving hepatocyte priming and replication driven by coordinated cytokine and growth factor actions. We investigated the mechanisms underlying Adiponectin's (Adn) regulation of liver regeneration through modulation of these mediators. Adn-/- mice showed delayed onset of hepatocyte replication, but accelerated cell cycle progression relative to wild-type mice, suggesting Adn has multiple effects fine-tuning the kinetics of liver regeneration. We developed a computational model describing the molecular and physiological kinetics of liver regeneration in Adn-/- mice. We employed this computational model to evaluate the underlying regulatory mechanisms. Our analysis predicted that Adn is required for an efficient early cytokine response to partial hepatectomy, but is inhibitory to later growth factor actions. Consistent with this prediction, Adn knockout reduced hepatocyte responses to IL-6 during the priming phase, but enhanced growth factor levels through peak hepatocyte replication. By contrast, supraphysiological concentrations of Adn resulting from rosiglitazone treatment suppressed regeneration by reducing growth factor levels during S phase, consistent with computational predictions. Together, these results revealed that Adn fine-tunes the progression of liver regeneration through dynamically modulating molecular mediator networks and cellular interactions within the liver. This article is protected by copyright. All rights reserved.

  10. Adiponectin fine-tuning of liver regeneration dynamics revealed through cellular network modelling.

    PubMed

    Correnti, Jason M; Cook, Daniel; Aksamitiene, Edita; Swarup, Aditi; Ogunnaike, Babatunde; Vadigepalli, Rajanikanth; Hoek, Jan B

    2015-01-15

    Following partial hepatectomy, the liver initiates a regenerative programme involving hepatocyte priming and replication driven by the coordinated actions of cytokine and growth factors. We investigated the mechanisms underlying adiponectin's (Adn) regulation of liver regeneration through modulation of these mediators. Adn(-/-) mice showed delayed onset of hepatocyte replication, but accelerated cell cycle progression relative to wild-type mice, suggesting Adn has multiple effects fine-tuning the kinetics of liver regeneration. We developed a computational model describing the molecular and physiological kinetics of liver regeneration in Adn(-/-) mice. We employed this computational model to evaluate the underlying regulatory mechanisms. Our analysis predicted that Adn is required for an efficient early cytokine response to partial hepatectomy, but is inhibitory to later growth factor actions. Consistent with this prediction, Adn knockout reduced hepatocyte responses to interleukin-6 during the priming phase, but enhanced growth factor levels through peak hepatocyte replication. By contrast, supraphysiological concentrations of Adn resulting from rosiglitazone treatment suppressed regeneration by reducing growth factor levels during S phase, consistent with computational predictions. Together, these results revealed that Adn fine-tunes the progression of liver regeneration through dynamically modulating molecular mediator networks and cellular interactions within the liver.

  11. Memristor-based cellular nonlinear/neural network: design, analysis, and applications.

    PubMed

    Duan, Shukai; Hu, Xiaofang; Dong, Zhekang; Wang, Lidan; Mazumder, Pinaki

    2015-06-01

    Cellular nonlinear/neural network (CNN) has been recognized as a powerful massively parallel architecture capable of solving complex engineering problems by performing trillions of analog operations per second. The memristor was theoretically predicted in the late seventies, but it garnered nascent research interest due to the recent much-acclaimed discovery of nanocrossbar memories by engineers at the Hewlett-Packard Laboratory. The memristor is expected to be co-integrated with nanoscale CMOS technology to revolutionize conventional von Neumann as well as neuromorphic computing. In this paper, a compact CNN model based on memristors is presented along with its performance analysis and applications. In the new CNN design, the memristor bridge circuit acts as the synaptic circuit element and substitutes the complex multiplication circuit used in traditional CNN architectures. In addition, the negative differential resistance and nonlinear current-voltage characteristics of the memristor have been leveraged to replace the linear resistor in conventional CNNs. The proposed CNN design has several merits, for example, high density, nonvolatility, and programmability of synaptic weights. The proposed memristor-based CNN design operations for implementing several image processing functions are illustrated through simulation and contrasted with conventional CNNs. Monte-Carlo simulation has been used to demonstrate the behavior of the proposed CNN due to the variations in memristor synaptic weights.

  12. Interaction of cellular and network mechanisms for efficient pheromone coding in moths

    PubMed Central

    Belmabrouk, Hana; Nowotny, Thomas; Rospars, Jean-Pierre; Martinez, Dominique

    2011-01-01

    Sensory systems, both in the living and in machines, have to be optimized with respect to their environmental conditions. The pheromone subsystem of the olfactory system of moths is a particularly well-defined example in which rapid variations of odor content in turbulent plumes require fast, concentration-invariant neural representations. It is not clear how cellular and network mechanisms in the moth antennal lobe contribute to coding efficiency. Using computational modeling, we show that intrinsic potassium currents (IA and ISK) in projection neurons may combine with extrinsic inhibition from local interneurons to implement a dual latency code for both pheromone identity and intensity. The mean latency reflects stimulus intensity, whereas latency differences carry concentration-invariant information about stimulus identity. In accordance with physiological results, the projection neurons exhibit a multiphasic response of inhibition–excitation–inhibition. Together with synaptic inhibition, intrinsic currents IA and ISK account for the first and second inhibitory phases and contribute to a rapid encoding of pheromone information. The first inhibition plays the role of a reset to limit variability in the time to first spike. The second inhibition prevents responses of excessive duration to allow tracking of intermittent stimuli. PMID:22109556

  13. Data fusion and classification using a hybrid intrinsic cellular inference network

    NASA Astrophysics Data System (ADS)

    Woodley, Robert; Walenz, Brett; Seiffertt, John; Robinette, Paul; Wunsch, Donald

    2010-04-01

    Hybrid Intrinsic Cellular Inference Network (HICIN) is designed for battlespace decision support applications. We developed an automatic method of generating hypotheses for an entity-attribute classifier. The capability and effectiveness of a domain specific ontology was used to generate automatic categories for data classification. Heterogeneous data is clustered using an Adaptive Resonance Theory (ART) inference engine on a sample (unclassified) data set. The data set is the Lahman baseball database. The actual data is immaterial to the architecture, however, parallels in the data can be easily drawn (i.e., "Team" maps to organization, "Runs scored/allowed" to Measure of organization performance (positive/negative), "Payroll" to organization resources, etc.). Results show that HICIN classifiers create known inferences from the heterogonous data. These inferences are not explicitly stated in the ontological description of the domain and are strictly data driven. HICIN uses data uncertainty handling to reduce errors in the classification. The uncertainty handling is based on subjective logic. The belief mass allows evidence from multiple sources to be mathematically combined to increase or discount an assertion. In military operations the ability to reduce uncertainty will be vital in the data fusion operation.

  14. A streamline splitting pore-network approach for computationally inexpensive and accurate simulation of transport in porous media

    SciTech Connect

    Mehmani, Yashar; Oostrom, Martinus; Balhoff, Matthew

    2014-03-20

    Several approaches have been developed in the literature for solving flow and transport at the pore-scale. Some authors use a direct modeling approach where the fundamental flow and transport equations are solved on the actual pore-space geometry. Such direct modeling, while very accurate, comes at a great computational cost. Network models are computationally more efficient because the pore-space morphology is approximated. Typically, a mixed cell method (MCM) is employed for solving the flow and transport system which assumes pore-level perfect mixing. This assumption is invalid at moderate to high Peclet regimes. In this work, a novel Eulerian perspective on modeling flow and transport at the pore-scale is developed. The new streamline splitting method (SSM) allows for circumventing the pore-level perfect mixing assumption, while maintaining the computational efficiency of pore-network models. SSM was verified with direct simulations and excellent matches were obtained against micromodel experiments across a wide range of pore-structure and fluid-flow parameters. The increase in the computational cost from MCM to SSM is shown to be minimal, while the accuracy of SSM is much higher than that of MCM and comparable to direct modeling approaches. Therefore, SSM can be regarded as an appropriate balance between incorporating detailed physics and controlling computational cost. The truly predictive capability of the model allows for the study of pore-level interactions of fluid flow and transport in different porous materials. In this paper, we apply SSM and MCM to study the effects of pore-level mixing on transverse dispersion in 3D disordered granular media.

  15. Spatio-temporal analysis of brain electrical activity in epilepsy based on cellular nonlinear networks

    NASA Astrophysics Data System (ADS)

    Gollas, Frank; Tetzlaff, Ronald

    2009-05-01

    Epilepsy is the most common chronic disorder of the nervous system. Generally, epileptic seizures appear without foregoing sign or warning. The problem of detecting a possible pre-seizure state in epilepsy from EEG signals has been addressed by many authors over the past decades. Different approaches of time series analysis of brain electrical activity already are providing valuable insights into the underlying complex dynamics. But the main goal the identification of an impending epileptic seizure with a sufficient specificity and reliability, has not been achieved up to now. An algorithm for a reliable, automated prediction of epileptic seizures would enable the realization of implantable seizure warning devices, which could provide valuable information to the patient and time/event specific drug delivery or possibly a direct electrical nerve stimulation. Cellular Nonlinear Networks (CNN) are promising candidates for future seizure warning devices. CNN are characterized by local couplings of comparatively simple dynamical systems. With this property these networks are well suited to be realized as highly parallel, analog computer chips. Today available CNN hardware realizations exhibit a processing speed in the range of TeraOps combined with low power consumption. In this contribution new algorithms based on the spatio-temporal dynamics of CNN are considered in order to analyze intracranial EEG signals and thus taking into account mutual dependencies between neighboring regions of the brain. In an identification procedure Reaction-Diffusion CNN (RD-CNN) are determined for short segments of brain electrical activity, by means of a supervised parameter optimization. RD-CNN are deduced from Reaction-Diffusion Systems, which usually are applied to investigate complex phenomena like nonlinear wave propagation or pattern formation. The Local Activity Theory provides a necessary condition for emergent behavior in RD-CNN. In comparison linear spatio

  16. Impedance matching network for high frequency ultrasonic transducer for cellular applications.

    PubMed

    Kim, Min Gon; Yoon, Sangpil; Kim, Hyung Ham; Shung, K Kirk

    2016-02-01

    An approach for the design of an impedance matching network (IMN) for high frequency ultrasonic transducers with large apertures based on impedance analysis for cellular applications is presented in this paper. The main objectives were to maximize energy transmission from the excitation source to the ultrasonic transducers for cell manipulation and to achieve low input parameters for the safe operation of an ultrasonic transducer because the piezoelectric material in high frequency ultrasonic transducers is prone to breakage due to its being extremely thin. Two ultrasonic transducers, which were made of lithium niobate single crystal with the thickness of 15 μm, having apertures of 4.3 mm (fnumber=1.23) and 2.6mm (fnumber=0.75) were tested. L-type IMN was selected for high sensitivity and compact design of the ultrasonic transducers. The target center frequency was chosen as the frequency where the electrical admittance (|Y|) and phase angle (θz) from impedance analysis was maximal and zero, respectively. The reference center frequency and reference echo magnitude were selected as the center frequency and echo magnitude, measured by pulse-echo testing, of the ultrasonic transducer without IMN. Initial component values and topology of IMN were determined using the Smith chart, and pulse-echo testing was analyzed to verify the performance of the ultrasonic transducers with and without IMN. After several iterations between changing component values and topology of IMN, and pulse-echo measurement of the ultrasonic transducer with IMN, optimized component values and topology of IMN were chosen when the measured center frequency from pulse-echo testing was comparable to the target frequency, and the measured echo magnitude was at least 30% larger than the reference echo magnitude. Performance of an ultrasonic transducer with and without IMN was tested by observing a tangible dent on the surface of a plastic petridish and single cell response after an acoustic pulse was

  17. Impedance Matching Network for High Frequency Ultrasonic Transducer for Cellular Applications

    PubMed Central

    Kim, Min Gon; Yoon, Sangpil; Kim, Hyung Ham; Shung, K. Kirk

    2015-01-01

    An approach for the design of an impedance matching network (IMN) for high frequency ultrasonic transducers with large apertures based on impedance analysis for cellular applications is presented in this paper. The main objectives were to maximize energy transmission from the excitation source to the ultrasonic transducers for cell manipulation and to achieve low input parameters for the safe operation of an ultrasonic transducer because the piezoelectric material in high frequency ultrasonic transducers is prone to breakage due to its being extremely thin. Two ultrasonic transducers, which were made of lithium niobate single crystal with the thickness of 15 μm, having apertures of 4.3 mm (fnumber = 1.23) and 2.6 mm (fnumber = 0.75) were tested. L-type IMN was selected for high sensitivity and compact design of the ultrasonic transducers. The target center frequency was chosen as the frequency where the electrical admittance (∣Y∣) and phase angle (θz) from impedance analysis was maximal and zero, respectively. The reference center frequency and reference echo magnitude were selected as the center frequency and echo magnitude, measured by pulse-echo testing, of the ultrasonic transducer without IMN. Initial component values and topology of IMN were determined using the Smith chart, and pulse-echo testing was analyzed to verify the performance of the ultrasonic transducers with and without IMN. After several iterations between changing component values and topology of IMN, and pulse-echo measurement of the ultrasonic transducer with IMN, optimized component values and topology of IMN were chosen when the measured center frequency from pulse-echo testing was comparable to the target frequency, and the measured echo magnitude was at least 30% larger than the reference echo magnitude. Performance of an ultrasonic transducer with and without IMN was tested by observing a tangible dent on the surface of a plastic petridish and single cell response after an acoustic

  18. Assessment of General Public Exposure to LTE signals compared to other Cellular Networks Present in Thessaloniki, Greece.

    PubMed

    Gkonis, Fotios; Boursianis, Achilles; Samaras, Theodoros

    2016-12-15

    To assess general public exposure to electromagnetic fields from Long Term Evolution (LTE) base stations, measurements at 10 sites in Thessaloniki, Greece were performed. Results are compared with other mobile cellular networks currently in use. All exposure values satisfy the guidelines for general public exposure of the International Commission on Non-Ionizing Radiation Protection (ICNIRP), as well as the reference levels by the Greek legislation at all sites. LTE electric field measurements were recorded up to 0.645 V/m. By applying the ICNIRP guidelines, the exposure ratio for all LTE signals is between 2.9 × 10(-5) and 2.8 × 10(-2) From the measurements results it is concluded that the average and maximum power density contribution of LTE downlink signals to the overall cellular networks signals are 7.8% and 36.7%, respectively.

  19. Geometric phase transition in the cellular network of the pancreatic islets may underlie the onset of type 1diabetes

    NASA Astrophysics Data System (ADS)

    Wang, Xujing

    Living systems are characterized by complexity in structure and emergent dynamic orders. In many aspects the onset of a chronic disease resembles phase transition in a dynamic system: quantitative changes accumulate largely unnoticed until a critical threshold is reached, which causes abrupt qualitative changes of the system. In this study we investigate this idea in a real example, the insulin-producing pancreatic islet β-cells and the onset of type 1 diabetes. Within each islet, the β-cells are electrically coupled to each other, and function as a network with synchronized actions. Using percolation theory we show how normal islet function is intrinsically linked to network connectivity, and the critical point where the islet cellular network loses site percolation, is consistent with laboratory and clinical observations of the threshold β-cell loss that causes islet functional failure. Numerical simulations confirm that the islet cellular network needs to be percolated for β-cells to synchronize. Furthermore, the interplay between site percolation and bond strength predicts the existence of a transient phase of islet functional recovery after disease onset and introduction of treatment, potentially explaining a long time mystery in the clinical study of type 1 diabetes: the honeymoon phenomenon. Based on these results, we hypothesized that the onset of T1D may be the result of a phase transition of the islet β-cell network. We further discuss the potential applications in identifying disease-driving factors, and the critical parameters that are predictive of disease onset.

  20. A new electromagnetic induction sensor using Vector Network Analyzer technology for accurate characterisation of soil electrical properties

    NASA Astrophysics Data System (ADS)

    André, F.; Lambot, S.; Moghadas, D.; Vereecken, H.

    2009-04-01

    Electromagnetic induction (EMI) has been widely used since the 70s to retrieve soil physico-chemical properties through the measurement of soil electrical conductivity. Soil electrical conductivity integrates several factors, mainly soil water content, salinity, clay content and temperature, and to a lesser extent, mineralogy, porosity, structure, cation exchange capacity, organic matter and bulk density. EMI has been shown to be useful for a wide range of environmental applications. EMI is non invasive and individual measurements are almost instantaneous, which permits to characterise large areas with fine spatial and/or temporal resolutions. Nevertheless, current EMI systems present some limitations. First, EMI usually operates at a single or at a limited number of fixed frequencies, which limits the information that can be retrieved from the subsurface. In addition, the calibration of existing commercial sensors is generally rather empirical and not accurate, which reduces the reliability of the data. Finally, the data processing techniques that are used to retrieve the soil electrical properties from EMI data often rely on strong simplifying assumptions with respect to wave propagation through the antenna-air-soil system. Performing EMI measurements with Vector Network Analyzer (VNA) technology would overcome a part of these limitations, allowing to work simultaneously at a wide range of frequencies and to readily perform robust calibrations, which are defined as an international standard. On that basis, we have developed a new algorithm for off-ground, zero-offset, frequency domain EMI based on full-waveform inverse modelling. The EMI forward model is based on a linear system of complex transfer functions for describing the loop antenna and its interactions with soil and an exact solution of Maxwell's equations for wave propagation in three-dimensional multilayered media. The approach has been validated in laboratory conditions for measurements at different

  1. New Markov-Shannon Entropy models to assess connectivity quality in complex networks: from molecular to cellular pathway, Parasite-Host, Neural, Industry, and Legal-Social networks.

    PubMed

    Riera-Fernández, Pablo; Munteanu, Cristian R; Escobar, Manuel; Prado-Prado, Francisco; Martín-Romalde, Raquel; Pereira, David; Villalba, Karen; Duardo-Sánchez, Aliuska; González-Díaz, Humberto

    2012-01-21

    Graph and Complex Network theory is expanding its application to different levels of matter organization such as molecular, biological, technological, and social networks. A network is a set of items, usually called nodes, with connections between them, which are called links or edges. There are many different experimental and/or theoretical methods to assign node-node links depending on the type of network we want to construct. Unfortunately, the use of a method for experimental reevaluation of the entire network is very expensive in terms of time and resources; thus the development of cheaper theoretical methods is of major importance. In addition, different methods to link nodes in the same type of network are not totally accurate in such a way that they do not always coincide. In this sense, the development of computational methods useful to evaluate connectivity quality in complex networks (a posteriori of network assemble) is a goal of major interest. In this work, we report for the first time a new method to calculate numerical quality scores S(L(ij)) for network links L(ij) (connectivity) based on the Markov-Shannon Entropy indices of order k-th (θ(k)) for network nodes. The algorithm may be summarized as follows: (i) first, the θ(k)(j) values are calculated for all j-th nodes in a complex network already constructed; (ii) A Linear Discriminant Analysis (LDA) is used to seek a linear equation that discriminates connected or linked (L(ij)=1) pairs of nodes experimentally confirmed from non-linked ones (L(ij)=0); (iii) the new model is validated with external series of pairs of nodes; (iv) the equation obtained is used to re-evaluate the connectivity quality of the network, connecting/disconnecting nodes based on the quality scores calculated with the new connectivity function. This method was used to study different types of large networks. The linear models obtained produced the following results in terms of overall accuracy for network reconstruction

  2. Systematic reverse engineering of network topologies: a case study of resettable bistable cellular responses.

    PubMed

    Mondal, Debasish; Dougherty, Edward; Mukhopadhyay, Abhishek; Carbo, Adria; Yao, Guang; Xing, Jianhua

    2014-01-01

    A focused theme in systems biology is to uncover design principles of biological networks, that is, how specific network structures yield specific systems properties. For this purpose, we have previously developed a reverse engineering procedure to identify network topologies with high likelihood in generating desired systems properties. Our method searches the continuous parameter space of an assembly of network topologies, without enumerating individual network topologies separately as traditionally done in other reverse engineering procedures. Here we tested this CPSS (continuous parameter space search) method on a previously studied problem: the resettable bistability of an Rb-E2F gene network in regulating the quiescence-to-proliferation transition of mammalian cells. From a simplified Rb-E2F gene network, we identified network topologies responsible for generating resettable bistability. The CPSS-identified topologies are consistent with those reported in the previous study based on individual topology search (ITS), demonstrating the effectiveness of the CPSS approach. Since the CPSS and ITS searches are based on different mathematical formulations and different algorithms, the consistency of the results also helps cross-validate both approaches. A unique advantage of the CPSS approach lies in its applicability to biological networks with large numbers of nodes. To aid the application of the CPSS approach to the study of other biological systems, we have developed a computer package that is available in Information S1.

  3. Comparative analysis of Salmonella susceptibility and tolerance to the biocide chlorhexidine identifies a complex cellular defense network

    PubMed Central

    Condell, Orla; Power, Karen A.; Händler, Kristian; Finn, Sarah; Sheridan, Aine; Sergeant, Kjell; Renaut, Jenny; Burgess, Catherine M.; Hinton, Jay C. D.; Nally, Jarlath E.; Fanning, Séamus

    2014-01-01

    Chlorhexidine is one of the most widely used biocides in health and agricultural settings as well as in the modern food industry. It is a cationic biocide of the biguanide class. Details of its mechanism of action are largely unknown. The frequent use of chlorhexidine has been questioned recently, amidst concerns that an overuse of this compound may select for bacteria displaying an altered susceptibility to antimicrobials, including clinically important anti-bacterial agents. We generated a Salmonella enterica serovar Typhimurium isolate (ST24CHX) that exhibited a high-level tolerant phenotype to chlorhexidine, following several rounds of in vitro selection, using sub-lethal concentrations of the biocide. This mutant showed altered suceptibility to a panel of clinically important antimicrobial compounds. Here we describe a genomic, transcriptomic, proteomic, and phenotypic analysis of the chlorhexidine tolerant S. Typhimurium compared with its isogenic sensitive progenitor. Results from this study describe a chlorhexidine defense network that functions in both the reference chlorhexidine sensitive isolate and the tolerant mutant. The defense network involved multiple cell targets including those associated with the synthesis and modification of the cell wall, the SOS response, virulence, and a shift in cellular metabolism toward anoxic pathways, some of which were regulated by CreB and Fur. In addition, results indicated that chlorhexidine tolerance was associated with more extensive modifications of the same cellular processes involved in this proposed network, as well as a divergent defense response involving the up-regulation of additional targets such as the flagellar apparatus and an altered cellular phosphate metabolism. These data show that sub-lethal concentrations of chlorhexidine induce distinct changes in exposed Salmonella, and our findings provide insights into the mechanisms of action and tolerance to this biocidal agent. PMID:25136333

  4. Mechanisms of stochastic focusing and defocusing in biological reaction networks: insight from accurate chemical master equation (ACME) solutions.

    PubMed

    Gursoy, Gamze; Terebus, Anna; Youfang Cao; Jie Liang

    2016-08-01

    Stochasticity plays important roles in regulation of biochemical reaction networks when the copy numbers of molecular species are small. Studies based on Stochastic Simulation Algorithm (SSA) has shown that a basic reaction system can display stochastic focusing (SF) by increasing the sensitivity of the network as a result of the signal noise. Although SSA has been widely used to study stochastic networks, it is ineffective in examining rare events and this becomes a significant issue when the tails of probability distributions are relevant as is the case of SF. Here we use the ACME method to solve the exact solution of the discrete Chemical Master Equations and to study a network where SF was reported. We showed that the level of SF depends on the degree of the fluctuations of signal molecule. We discovered that signaling noise under certain conditions in the same reaction network can lead to a decrease in the system sensitivities, thus the network can experience stochastic defocusing. These results highlight the fundamental role of stochasticity in biological reaction networks and the need for exact computation of probability landscape of the molecules in the system.

  5. A novel spatter detection algorithm based on typical cellular neural network operations for laser beam welding processes

    NASA Astrophysics Data System (ADS)

    Nicolosi, L.; Abt, F.; Blug, A.; Heider, A.; Tetzlaff, R.; Höfler, H.

    2012-01-01

    Real-time monitoring of laser beam welding (LBW) has increasingly gained importance in several manufacturing processes ranging from automobile production to precision mechanics. In the latter, a novel algorithm for the real-time detection of spatters was implemented in a camera based on cellular neural networks. The latter can be connected to the optics of commercially available laser machines leading to real-time monitoring of LBW processes at rates up to 15 kHz. Such high monitoring rates allow the integration of other image evaluation tasks such as the detection of the full penetration hole for real-time control of process parameters.

  6. Impact of Network Structure and Cellular Response on Spike Time Correlations

    PubMed Central

    Trousdale, James; Hu, Yu; Shea-Brown, Eric; Josić, Krešimir

    2012-01-01

    Novel experimental techniques reveal the simultaneous activity of larger and larger numbers of neurons. As a result there is increasing interest in the structure of cooperative – or correlated – activity in neural populations, and in the possible impact of such correlations on the neural code. A fundamental theoretical challenge is to understand how the architecture of network connectivity along with the dynamical properties of single cells shape the magnitude and timescale of correlations. We provide a general approach to this problem by extending prior techniques based on linear response theory. We consider networks of general integrate-and-fire cells with arbitrary architecture, and provide explicit expressions for the approximate cross-correlation between constituent cells. These correlations depend strongly on the operating point (input mean and variance) of the neurons, even when connectivity is fixed. Moreover, the approximations admit an expansion in powers of the matrices that describe the network architecture. This expansion can be readily interpreted in terms of paths between different cells. We apply our results to large excitatory-inhibitory networks, and demonstrate first how precise balance – or lack thereof – between the strengths and timescales of excitatory and inhibitory synapses is reflected in the overall correlation structure of the network. We then derive explicit expressions for the average correlation structure in randomly connected networks. These expressions help to identify the important factors that shape coordinated neural activity in such networks. PMID:22457608

  7. The dynamic and geometric phase transition in the cellular network of pancreatic islet

    NASA Astrophysics Data System (ADS)

    Wang, Xujing

    2013-03-01

    The pancreatic islet is a micro-organ that contains several thousands of endocrine cells, majority of which being the insulin releasing β - cells . - cellsareexcitablecells , andarecoupledtoeachother through gap junctional channels. Here, using percolation theory, we investigate the role of network structure in determining the dynamics of the β-cell network. We show that the β-cell synchronization depends on network connectivity. More specifically, as the site occupancy is reducing, initially the β-cell synchronization is barely affected, until it reaches around a critical value, where the synchronization exhibit a sudden rapid decline, followed by an slow exponential tail. This critical value coincides with the critical site open probability for percolation transition. The dependence over bond strength is similar, exhibiting critical-behavior like dependence around a certain value of bond strength. These results suggest that the β-cell network undergoes a dynamic phase transition when the network is percolated. We further apply the findings to study diabetes. During the development of diabetes, the β - cellnetworkconnectivitydecreases . Siteoccupancyreducesfromthe reducing β-cell mass, and the bond strength is increasingly impaired from β-cell stress and chronic hyperglycemia. We demonstrate that the network dynamics around the percolation transition explain the disease dynamics around onset, including a long time mystery in diabetes, the honeymoon phenomenon.

  8. Discrimination of liver cancer in cellular level based on backscatter micro-spectrum with PCA algorithm and BP neural network

    NASA Astrophysics Data System (ADS)

    Yang, Jing; Wang, Cheng; Cai, Gan; Dong, Xiaona

    2016-10-01

    The incidence and mortality rate of the primary liver cancer are very high and its postoperative metastasis and recurrence have become important factors to the prognosis of patients. Circulating tumor cells (CTC), as a new tumor marker, play important roles in the early diagnosis and individualized treatment. This paper presents an effective method to distinguish liver cancer based on the cellular scattering spectrum, which is a non-fluorescence technique based on the fiber confocal microscopic spectrometer. Combining the principal component analysis (PCA) with back propagation (BP) neural network were utilized to establish an automatic recognition model for backscatter spectrum of the liver cancer cells from blood cell. PCA was applied to reduce the dimension of the scattering spectral data which obtained by the fiber confocal microscopic spectrometer. After dimensionality reduction by PCA, a neural network pattern recognition model with 2 input layer nodes, 11 hidden layer nodes, 3 output nodes was established. We trained the network with 66 samples and also tested it. Results showed that the recognition rate of the three types of cells is more than 90%, the relative standard deviation is only 2.36%. The experimental results showed that the fiber confocal microscopic spectrometer combining with the algorithm of PCA and BP neural network can automatically identify the liver cancer cell from the blood cells. This will provide a better tool for investigating the metastasis of liver cancers in vivo, the biology metabolic characteristics of liver cancers and drug transportation. Additionally, it is obviously referential in practical application.

  9. Beta Cell Formation in vivo Through Cellular Networking, Integration and Processing (CNIP) in Wild Type Adult Mice.

    PubMed

    Doiron, Bruno; Hu, Wenchao; DeFronzo, Ralph A

    2016-01-01

    Insulin replacement therapy is essential in type 1 diabetic individuals and is required in ~40- 50% of type 2 diabetics during their lifetime. Prior attempts at beta cell regeneration have relied upon pancreatic injury to induce beta cell proliferation, dedifferentiation and activation of the embryonic pathway, or stem cell replacement. We report an alternative method to transform adult non-stem (somatic) cells into pancreatic beta cells. The Cellular Networking, Integration and Processing (CNIP) approach targets cellular mechanisms involved in pancreatic function in the organ's adult state and utilizes a synergistic mechanism that integrates three important levels of cellular regulation to induce beta cell formation: (i) glucose metabolism, (ii) membrane receptor function, and (iii) gene transcription. The aim of the present study was to induce pancreatic beta cell formation in vivo in adult animals without stem cells and without dedifferentiating cells to recapitulate the embryonic pathway as previously published (1-3). Our results employing CNIP demonstrate that: (i) insulin secreting cells can be generated in adult pancreatic tissue in vivo and circumvent the problem of generating endocrine (glucagon and somatostatin) cells that exert deleterious effects on glucose homeostasis, and (ii) longterm normalization of glucose tolerance and insulin secretion can be achieved in a wild type diabetic mouse model. The CNIP cocktail has the potential to be used as a preventative or therapeutic treatment or cure for both type 1 and type 2 diabetes.

  10. A cardiac electrical activity model based on a cellular automata system in comparison with neural network model.

    PubMed

    Khan, Muhammad Sadiq Ali; Yousuf, Sidrah

    2016-03-01

    Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each electrical activity during cardiac cycle should be monitor non-invasively for the assessment of "Action Potential" (regular) and "Arrhythmia" (irregular) rhythms. Many heart diseases can easily be examined through Automata model like Cellular Automata concepts. This paper deals with the different states of cardiac rhythms using cellular automata with the comparison of neural network also provides fast and highly effective stimulation for the contraction of cardiac muscles on the Atria in the result of genesis of electrical spark or wave. The specific formulated model named as "States of automaton Proposed Model for CEA (Cardiac Electrical Activity)" by using Cellular Automata Methodology is commonly shows the three states of cardiac tissues conduction phenomena (i) Resting (Relax and Excitable state), (ii) ARP (Excited but Absolutely refractory Phase i.e. Excited but not able to excite neighboring cells) (iii) RRP (Excited but Relatively Refractory Phase i.e. Excited and able to excite neighboring cells). The result indicates most efficient modeling with few burden of computation and it is Action Potential during the pumping of blood in cardiac cycle.

  11. Coverage extension and balancing the transmitted power of the moving relay node at LTE-A cellular network.

    PubMed

    Aldhaibani, Jaafar A; Yahya, Abid; Ahmad, R Badlishah

    2014-01-01

    The poor capacity at cell boundaries is not enough to meet the growing demand and stringent design which required high capacity and throughput irrespective of user's location in the cellular network. In this paper, we propose new schemes for an optimum fixed relay node (RN) placement in LTE-A cellular network to enhance throughput and coverage extension at cell edge region. The proposed approach mitigates interferences between all nodes and ensures optimum utilization with the optimization of transmitted power. Moreover, we proposed a new algorithm to balance the transmitted power of moving relay node (MR) over cell size and providing required SNR and throughput at the users inside vehicle along with reducing the transmitted power consumption by MR. The numerical analysis along with the simulation results indicates that an improvement in capacity for users is 40% increment at downlink transmission from cell capacity. Furthermore, the results revealed that there is saving nearly 75% from transmitted power in MR after using proposed balancing algorithm. ATDI simulator was used to verify the numerical results, which deals with real digital cartographic and standard formats for terrain.

  12. Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits.

    PubMed

    Kanner, Sivan; Bisio, Marta; Cohen, Gilad; Goldin, Miri; Tedesco, Marieteresa; Hanein, Yael; Ben-Jacob, Eshel; Barzilai, Ari; Chiappalone, Michela; Bonifazi, Paolo

    2015-04-15

    The brain operates through the coordinated activation and the dynamic communication of neuronal assemblies. A major open question is how a vast repertoire of dynamical motifs, which underlie most diverse brain functions, can emerge out of a fixed topological and modular organization of brain circuits. Compared to in vivo studies of neuronal circuits which present intrinsic experimental difficulties, in vitro preparations offer a much larger possibility to manipulate and probe the structural, dynamical and chemical properties of experimental neuronal systems. This work describes an in vitro experimental methodology which allows growing of modular networks composed by spatially distinct, functionally interconnected neuronal assemblies. The protocol allows controlling the two-dimensional (2D) architecture of the neuronal network at different levels of topological complexity. A desired network patterning can be achieved both on regular cover slips and substrate embedded micro electrode arrays. Micromachined structures are embossed on a silicon wafer and used to create biocompatible polymeric stencils, which incorporate the negative features of the desired network architecture. The stencils are placed on the culturing substrates during the surface coating procedure with a molecular layer for promoting cellular adhesion. After removal of the stencils, neurons are plated and they spontaneously redirected to the coated areas. By decreasing the inter-compartment distance, it is possible to obtain either isolated or interconnected neuronal circuits. To promote cell survival, cells are co-cultured with a supporting neuronal network which is located at the periphery of the culture dish. Electrophysiological and optical recordings of the activity of modular networks obtained respectively by using substrate embedded micro electrode arrays and calcium imaging are presented. While each module shows spontaneous global synchronizations, the occurrence of inter-module synchronization

  13. The role of glutathione reductase and related enzymes on cellular redox homoeostasis network.

    PubMed

    Couto, Narciso; Wood, Jennifer; Barber, Jill

    2016-06-01

    In this review article we examine the role of glutathione reductase in the regulation, modulation and maintenance of cellular redox homoeostasis. Glutathione reductase is responsible for maintaining the supply of reduced glutathione; one of the most abundant reducing thiols in the majority of cells. In its reduced form, glutathione plays key roles in the cellular control of reactive oxygen species. Reactive oxygen species act as intracellular and extracellular signalling molecules and complex cross talk between levels of reactive oxygen species, levels of oxidised and reduced glutathione and other thiols, and antioxidant enzymes such as glutathione reductase determine the most suitable conditions for redox control within a cell or for activation of programmed cell death. Additionally, we discuss the translation and expression of glutathione reductase in a number of organisms including yeast and humans. In yeast and human cells, a single gene expresses more than one form of glutathione reductase, destined for residence in the cytoplasm or for translocation to different organelles; in plants, however, two genes encoding this protein have been described. In general, insects and kinetoplastids (a group of protozoa, including Plasmodia and Trypanosoma) do not express glutathione reductase or glutathione biosynthetic enzymes. Instead, they express either the thioredoxin system or the trypanothione system. The thioredoxin system is also present in organisms that have the glutathione system and there may be overlapping functions with cross-talk between the two systems. Finally we evaluate therapeutic targets to overcome oxidative stress associated cellular disorders.

  14. Fast, Simple and Accurate Handwritten Digit Classification by Training Shallow Neural Network Classifiers with the 'Extreme Learning Machine' Algorithm.

    PubMed

    McDonnell, Mark D; Tissera, Migel D; Vladusich, Tony; van Schaik, André; Tapson, Jonathan

    2015-01-01

    Recent advances in training deep (multi-layer) architectures have inspired a renaissance in neural network use. For example, deep convolutional networks are becoming the default option for difficult tasks on large datasets, such as image and speech recognition. However, here we show that error rates below 1% on the MNIST handwritten digit benchmark can be replicated with shallow non-convolutional neural networks. This is achieved by training such networks using the 'Extreme Learning Machine' (ELM) approach, which also enables a very rapid training time (∼ 10 minutes). Adding distortions, as is common practise for MNIST, reduces error rates even further. Our methods are also shown to be capable of achieving less than 5.5% error rates on the NORB image database. To achieve these results, we introduce several enhancements to the standard ELM algorithm, which individually and in combination can significantly improve performance. The main innovation is to ensure each hidden-unit operates only on a randomly sized and positioned patch of each image. This form of random 'receptive field' sampling of the input ensures the input weight matrix is sparse, with about 90% of weights equal to zero. Furthermore, combining our methods with a small number of iterations of a single-batch backpropagation method can significantly reduce the number of hidden-units required to achieve a particular performance. Our close to state-of-the-art results for MNIST and NORB suggest that the ease of use and accuracy of the ELM algorithm for designing a single-hidden-layer neural network classifier should cause it to be given greater consideration either as a standalone method for simpler problems, or as the final classification stage in deep neural networks applied to more difficult problems.

  15. Cellular and network-level adaptations to in utero methadone exposure along the ventral respiratory column in the neonate rat.

    PubMed

    Gourévitch, Boris; Cai, Jun; Mellen, Nicholas

    2016-03-20

    Neonatal abstinence syndrome (NAS) occurs in babies chronically exposed to opioids during pregnancy. NAS shares features with opioid withdrawal symptoms seen in adults, including autonomic dysregulation. Here, the effect of low-dose in utero methadone (MTD) exposure on respiration-modulated networks along the ventral respiratory column (VRC) in ventrolateral medulla was investigated in the neonate Sprague-Dawley rat. MTD was administered via drinking water (3mg/kg/day in drinking water of the mother E7-E21). Lower expression levels of myelin-associated proteins phosphorylated axonal neurofilament subunit H (pNFH), 2',3'-Cyclicnucleotide 3'-phosphodiesterase (CNPase) and myelin basic protein (MBP), in MTD-exposed pups compared to controls at P3, P6 and P10 indicated MTD transport across the placenta. We investigated whether in utero MTD exposure led to network-level excitability changes consistent with tolerance, and also probed for changes in endogenous opioid modulation of respiratory networks. To this end, high-speed (45.5Hz) optical recordings of respiratory network activity in control and MTD-exposed neonate (P0-P2) pups before and during administration of the μ-opioid receptor antagonist naloxone (NAL; 10μM) were carried out. Spike rate was estimated from optical traces via deconvolution, and coupling between all neuron pairs in recorded networks was quantified using the normalized transfer entropy (NTE). Recordings of local networks along the VRC, together with recordings of respiratory output from ventral root C1 did not reveal changes in respiratory activity at the system level, but cellular and network changes in MTD-exposed pups were consistent with the development of opioid tolerance. MTD-exposed pups were found to have i. higher neuronal firing rates; ii. higher covariance between neuronal activity and motor output; iii. more bidirectionally and unidirectionally coupled neurons, and fewer uncoupled neurons; iv. stronger coupling and shorter

  16. Reconstruction of cellular signal transduction networks using perturbation assays and linear programming.

    PubMed

    Knapp, Bettina; Kaderali, Lars

    2013-01-01

    Perturbation experiments for example using RNA interference (RNAi) offer an attractive way to elucidate gene function in a high throughput fashion. The placement of hit genes in their functional context and the inference of underlying networks from such data, however, are challenging tasks. One of the problems in network inference is the exponential number of possible network topologies for a given number of genes. Here, we introduce a novel mathematical approach to address this question. We formulate network inference as a linear optimization problem, which can be solved efficiently even for large-scale systems. We use simulated data to evaluate our approach, and show improved performance in particular on larger networks over state-of-the art methods. We achieve increased sensitivity and specificity, as well as a significant reduction in computing time. Furthermore, we show superior performance on noisy data. We then apply our approach to study the intracellular signaling of human primary nave CD4(+) T-cells, as well as ErbB signaling in trastuzumab resistant breast cancer cells. In both cases, our approach recovers known interactions and points to additional relevant processes. In ErbB signaling, our results predict an important role of negative and positive feedback in controlling the cell cycle progression.

  17. Accurate protein structure annotation through competitive diffusion of enzymatic functions over a network of local evolutionary similarities.

    PubMed

    Venner, Eric; Lisewski, Andreas Martin; Erdin, Serkan; Ward, R Matthew; Amin, Shivas R; Lichtarge, Olivier

    2010-12-13

    High-throughput Structural Genomics yields many new protein structures without known molecular function. This study aims to uncover these missing annotations by globally comparing select functional residues across the structural proteome. First, Evolutionary Trace Annotation, or ETA, identifies which proteins have local evolutionary and structural features in common; next, these proteins are linked together into a proteomic network of ETA similarities; then, starting from proteins with known functions, competing functional labels diffuse link-by-link over the entire network. Every node is thus assigned a likelihood z-score for every function, and the most significant one at each node wins and defines its annotation. In high-throughput controls, this competitive diffusion process recovered enzyme activity annotations with 99% and 97% accuracy at half-coverage for the third and fourth Enzyme Commission (EC) levels, respectively. This corresponds to false positive rates 4-fold lower than nearest-neighbor and 5-fold lower than sequence-based annotations. In practice, experimental validation of the predicted carboxylesterase activity in a protein from Staphylococcus aureus illustrated the effectiveness of this approach in the context of an increasingly drug-resistant microbe. This study further links molecular function to a small number of evolutionarily important residues recognizable by Evolutionary Tracing and it points to the specificity and sensitivity of functional annotation by competitive global network diffusion. A web server is at http://mammoth.bcm.tmc.edu/networks.

  18. Rainfall measurements from cellular networks microwave links : an alternative ground reference for satellite validation and hydrology in Africa .

    NASA Astrophysics Data System (ADS)

    Gosset, Marielle; cazenave, frederic; Zougmore, françois; Doumounia, Ali; kacou, Modeste

    2015-04-01

    In many part of the Tropics the ground based gauge networks are sparse, often degrading and accessing this data for monitoring rainfall or for validating satellite products is sometime difficult. Here, an alternative rainfall measuring technique is proposed and tested in West Africa. It is based on using commercial microwave links from cellular telephone networks to detect and quantify rainfall. Rainfall monitoring based on commercial terrestrial microwave links has been tested for the first time in Burkina Faso, in Sahel. The rainfall regime is characterized by intense rainfall intensities brought by mesoscale Convective systems (MCS), generated by deep organized convection. The region is subjected to drought as well as dramatic floods associated with the intense rainfall provided by a few MCSs. The hydrometeorological risk is increasing and need to be monitored. In collaboration with the national cellular phone operator, Telecel Faso, the attenuation on 29 km long microwave links operating at 7 GHz was monitored at 1s time rate for the monsoon season 2012. The time series of attenuation is transformed into rain rates and compared with rain gauge data. The method is successful in quantifying rainfall: 95% of the rainy days are detected. The correlation with the daily raingauge series is 0.8 and the season bias is 5%. The correlation at the 5 min time step within each event is also high. We will present the quantitative results, discuss the uncertainties and compare the time series and the 2D maps with those derived from a polarimetric radar. The results demonstrate the potential interest of exploiting national and regional wireless telecommunication networks to provide rainfall maps for various applications : urban hydrology, agro-hydrological risk monitoring, satellite validation and development of combined rainfall products. We will also present the outcome of the first international Rain Cell Africa workshop held in Ouagadougou early 2015.

  19. From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

    PubMed Central

    Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

    2016-01-01

    The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains. PMID:26972968

  20. From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

    NASA Astrophysics Data System (ADS)

    Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

    2016-03-01

    The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

  1. Cell Edge Capacity Improvement by Using Adaptive Base Station Cooperation in Cellular Networks with Fractional Frequency Reuse

    NASA Astrophysics Data System (ADS)

    Xu, Liang; Yamamoto, Koji; Murata, Hidekazu; Yoshida, Susumu

    The present paper focuses on the application of the base station cooperation (BSC) technique in fractional frequency reuse (FFR) networks. Fractional frequency reuse is considered to be a promising scheme for avoiding the inter-cell interference problem in OFDMA cellular systems, such as WiMAX, in which the edge mobile stations (MSs) of adjacent cells use different subchannels for separate transmission. However, the problem of FFR is that the cell edge spectral efficiency (SE) is much lower than that of the cell center. The BSC technique, in which adjacent BSs perform cooperative transmission for one cell edge MS with the same channel, may improve the cell edge SE. However, since more BSs transmit signals for one cell edge MS, the use of BSC can also increase the inter-cell interference, which might degrade the network performance. In this paper, with a focus on this tradeoff, we propose an adaptive BSC scheme in which BSC is only performed for the cell edge MSs that can achieve a significant capacity increase with only a slight increase in inter-cell interference. Moreover, a channel reallocation scheme is proposed in order to further improve the performance of the adaptive BSC scheme. The simulation results reveal that, compared to the conventional FFR scheme, the proposed schemes are effective for improving the performance of FFR networks.

  2. The potential of cellular technology to mediate social networks for support of chronic disease self-management.

    PubMed

    Roblin, Douglas W

    2011-01-01

    Productive interactions among patients, friends/family, and health care providers, as outlined by the Chronic Care Model, are important for promoting adherence to recommended care and good health outcomes among adults with a chronic illness. Characteristics of these interactions--active participation, collaboration, and data sharing among constituents--are the same as those of social networks organized around Web 2.0 principles and technology. Thus, the Web 2.0 framework can be used to configure social networks without the inherent spatiotemporal constraints of face-to-face interactions that remain prevalent in health care delivery. In this article, the author outlines various design principles and decisions for a pilot study in which cellular technology was used to mediate interactions between adults with Type 2 diabetes and supporters (i.e., family members or friends selected by the patients who agree provide support) to motivate regular self-monitoring of blood glucose (among the diabetes participants). Participants generally found the network to be relatively easy to use. Some diabetes patients reported improved attention to self-monitoring; and, patient-selected supporters indicated improvements in emotional and instrumental support that should benefit diabetes patients' lifestyle and health.

  3. Mobility-Aware Caching and Computation Offloading in 5G Ultra-Dense Cellular Networks

    PubMed Central

    Chen, Min; Hao, Yixue; Qiu, Meikang; Song, Jeungeun; Wu, Di; Humar, Iztok

    2016-01-01

    Recent trends show that Internet traffic is increasingly dominated by content, which is accompanied by the exponential growth of traffic. To cope with this phenomena, network caching is introduced to utilize the storage capacity of diverse network devices. In this paper, we first summarize four basic caching placement strategies, i.e., local caching, Device-to-Device (D2D) caching, Small cell Base Station (SBS) caching and Macrocell Base Station (MBS) caching. However, studies show that so far, much of the research has ignored the impact of user mobility. Therefore, taking the effect of the user mobility into consideration, we proposes a joint mobility-aware caching and SBS density placement scheme (MS caching). In addition, differences and relationships between caching and computation offloading are discussed. We present a design of a hybrid computation offloading and support it with experimental results, which demonstrate improved performance in terms of energy cost. Finally, we discuss the design of an incentive mechanism by considering network dynamics, differentiated user’s quality of experience (QoE) and the heterogeneity of mobile terminals in terms of caching and computing capabilities. PMID:27347975

  4. Hierarchical random cellular neural networks for system-level brain-like signal processing.

    PubMed

    Kozma, Robert; Puljic, Marko

    2013-09-01

    Sensory information processing and cognition in brains are modeled using dynamic systems theory. The brain's dynamic state is described by a trajectory evolving in a high-dimensional state space. We introduce a hierarchy of random cellular automata as the mathematical tools to describe the spatio-temporal dynamics of the cortex. The corresponding brain model is called neuropercolation which has distinct advantages compared to traditional models using differential equations, especially in describing spatio-temporal discontinuities in the form of phase transitions. Phase transitions demarcate singularities in brain operations at critical conditions, which are viewed as hallmarks of higher cognition and awareness experience. The introduced Monte-Carlo simulations obtained by parallel computing point to the importance of computer implementations using very large-scale integration (VLSI) and analog platforms.

  5. An asymmetric image cryptosystem based on the adaptive synchronization of an uncertain unified chaotic system and a cellular neural network

    NASA Astrophysics Data System (ADS)

    Cheng, Chao-Jung; Cheng, Chi-Bin

    2013-10-01

    Chaotic dynamics provide a fast and simple means to create an excellent image cryptosystem, because it is extremely sensitive to initial conditions and system parameters, pseudorandomness, and non-periodicity. However, most chaos-based image encryption schemes are symmetric cryptographic techniques, which have been proven to be more vulnerable, compared to an asymmetric cryptosystem. This paper develops an asymmetric image cryptosystem, based on the adaptive synchronization of two different chaotic systems, namely a unified chaotic system and a cellular neural network. An adaptive controller with parameter update laws is formulated, using the Lyapunov stability theory, to asymptotically synchronize the two chaotic systems. The synchronization controller is embedded in the image cryptosystem and generates a pair of asymmetric keys, for image encryption and decryption. Using numerical simulations, three sets of experiments are conducted to evaluate the feasibility and reliability of the proposed chaos-based image cryptosystem.

  6. Transparent and accurate reporting increases reliability, utility, and impact of your research: reporting guidelines and the EQUATOR Network.

    PubMed

    Simera, Iveta; Moher, David; Hirst, Allison; Hoey, John; Schulz, Kenneth F; Altman, Douglas G

    2010-04-26

    Although current electronic methods of scientific publishing offer increased opportunities for publishing all research studies and describing them in sufficient detail, health research literature still suffers from many shortcomings. These shortcomings seriously undermine the value and utility of the literature and waste scarce resources invested in the research. In recent years there have been several positive steps aimed at improving this situation, such as a strengthening of journals' policies on research publication and the wide requirement to register clinical trials.The EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Network is an international initiative set up to advance high quality reporting of health research studies; it promotes good reporting practices including the wider implementation of reporting guidelines. EQUATOR provides free online resources http://www.equator-network.org supported by education and training activities and assists in the development of robust reporting guidelines. This paper outlines EQUATOR's goals and activities and offers suggestions for organizations and individuals involved in health research on how to strengthen research reporting.

  7. Transparent and accurate reporting increases reliability, utility, and impact of your research: reporting guidelines and the EQUATOR Network

    PubMed Central

    2010-01-01

    Although current electronic methods of scientific publishing offer increased opportunities for publishing all research studies and describing them in sufficient detail, health research literature still suffers from many shortcomings. These shortcomings seriously undermine the value and utility of the literature and waste scarce resources invested in the research. In recent years there have been several positive steps aimed at improving this situation, such as a strengthening of journals' policies on research publication and the wide requirement to register clinical trials. The EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Network is an international initiative set up to advance high quality reporting of health research studies; it promotes good reporting practices including the wider implementation of reporting guidelines. EQUATOR provides free online resources http://www.equator-network.org supported by education and training activities and assists in the development of robust reporting guidelines. This paper outlines EQUATOR's goals and activities and offers suggestions for organizations and individuals involved in health research on how to strengthen research reporting. PMID:20420659

  8. An Integrative Model of the Cardiovascular System Coupling Heart Cellular Mechanics with Arterial Network Hemodynamics

    PubMed Central

    Kim, Young-Tae; Lee, Jeong Sang; Youn, Chan-Hyun; Choi, Jae-Sung

    2013-01-01

    The current study proposes a model of the cardiovascular system that couples heart cell mechanics with arterial hemodynamics to examine the physiological role of arterial blood pressure (BP) in left ventricular hypertrophy (LVH). We developed a comprehensive multiphysics and multiscale cardiovascular model of the cardiovascular system that simulates physiological events, from membrane excitation and the contraction of a cardiac cell to heart mechanics and arterial blood hemodynamics. Using this model, we delineated the relationship between arterial BP or pulse wave velocity and LVH. Computed results were compared with existing clinical and experimental observations. To investigate the relationship between arterial hemodynamics and LVH, we performed a parametric study based on arterial wall stiffness, which was obtained in the model. Peak cellular stress of the left ventricle and systolic blood pressure (SBP) in the brachial and central arteries also increased; however, further increases were limited for higher arterial stiffness values. Interestingly, when we doubled the value of arterial stiffness from the baseline value, the percentage increase of SBP in the central artery was about 6.7% whereas that of the brachial artery was about 3.4%. It is suggested that SBP in the central artery is more critical for predicting LVH as compared with other blood pressure measurements. PMID:23960442

  9. Cellular and neurochemical basis of sleep stages in the thalamocortical network.

    PubMed

    Krishnan, Giri P; Chauvette, Sylvain; Shamie, Isaac; Soltani, Sara; Timofeev, Igor; Cash, Sydney S; Halgren, Eric; Bazhenov, Maxim

    2016-11-16

    The link between the combined action of neuromodulators in the brain and global brain states remains a mystery. In this study, using biophysically realistic models of the thalamocortical network, we identified the critical intrinsic and synaptic mechanisms, associated with the putative action of acetylcholine (ACh), GABA and monoamines, which lead to transitions between primary brain vigilance states (waking, non-rapid eye movement sleep [NREM] and REM sleep) within an ultradian cycle. Using ECoG recordings from humans and LFP recordings from cats and mice, we found that during NREM sleep the power of spindle and delta oscillations is negatively correlated in humans and positively correlated in animal recordings. We explained this discrepancy by the differences in the relative level of ACh. Overall, our study revealed the critical intrinsic and synaptic mechanisms through which different neuromodulators acting in combination result in characteristic brain EEG rhythms and transitions between sleep stages.

  10. Transcriptional regulatory networks in cellular responses and tolerance to dehydration and cold stresses.

    PubMed

    Yamaguchi-Shinozaki, Kazuko; Shinozaki, Kazuo

    2006-01-01

    Plant growth and productivity are greatly affected by environmental stresses such as drought, high salinity, and low temperature. Expression of a variety of genes is induced by these stresses in various plants. The products of these genes function not only in stress tolerance but also in stress response. In the signal transduction network from perception of stress signals to stress-responsive gene expression, various transcription factors and cis-acting elements in the stress-responsive promoters function for plant adaptation to environmental stresses. Recent progress has been made in analyzing the complex cascades of gene expression in drought and cold stress responses, especially in identifying specificity and cross talk in stress signaling. In this review article, we highlight transcriptional regulation of gene expression in response to drought and cold stresses, with particular emphasis on the role of transcription factors and cis-acting elements in stress-inducible promoters.

  11. Multimode fibers in millimeter-wave evolution for 5G cellular networks

    NASA Astrophysics Data System (ADS)

    Vázquez, C.; Montero, D. S.; Ponce, W.; Lallana, P. C.; Larrabeiti, D.; Montalvo, J.; Tapetado, A.; Pinzón, P. J.

    2016-02-01

    Small-cell and cloud-RAN systems along with the use of the millimeter-wave band have been considered as promising solutions to meet the capacity demand of the future wireless access networks. Radio over Multimode fibers (RoMMF) can play a role in the integrated optical-wireless access systems for next-generation wireless communications, mainly in within-building environments. The numerical results show the effectiveness of MMF to transmit at 60 GHz band with 7- GHz bandwidth for different link lengths and refractive index profiles under restricted mode launching and using narrow linewidth sources. The integration with optically powered remote antenna units is also proposed based on the large core effective area of MMF. Temperature impairments and graded index plastic optical fiber transmission are also discussed.

  12. Evolving gene regulatory networks into cellular networks guiding adaptive behavior: an outline how single cells could have evolved into a centralized neurosensory system.

    PubMed

    Fritzsch, Bernd; Jahan, Israt; Pan, Ning; Elliott, Karen L

    2015-01-01

    Understanding the evolution of the neurosensory system of man, able to reflect on its own origin, is one of the major goals of comparative neurobiology. Details of the origin of neurosensory cells, their aggregation into central nervous systems and associated sensory organs and their localized patterning leading to remarkably different cell types aggregated into variably sized parts of the central nervous system have begun to emerge. Insights at the cellular and molecular level have begun to shed some light on the evolution of neurosensory cells, partially covered in this review. Molecular evidence suggests that high mobility group (HMG) proteins of pre-metazoans evolved into the definitive Sox [SRY (sex determining region Y)-box] genes used for neurosensory precursor specification in metazoans. Likewise, pre-metazoan basic helix-loop-helix (bHLH) genes evolved in metazoans into the group A bHLH genes dedicated to neurosensory differentiation in bilaterians. Available evidence suggests that the Sox and bHLH genes evolved a cross-regulatory network able to synchronize expansion of precursor populations and their subsequent differentiation into novel parts of the brain or sensory organs. Molecular evidence suggests metazoans evolved patterning gene networks early, which were not dedicated to neuronal development. Only later in evolution were these patterning gene networks tied into the increasing complexity of diffusible factors, many of which were already present in pre-metazoans, to drive local patterning events. It appears that the evolving molecular basis of neurosensory cell development may have led, in interaction with differentially expressed patterning genes, to local network modifications guiding unique specializations of neurosensory cells into sensory organs and various areas of the central nervous system.

  13. Evolving gene regulation networks into cellular networks guiding adaptive behavior: an outline how single cells could have evolved into a centralized neurosensory system

    PubMed Central

    Fritzsch, Bernd; Jahan, Israt; Pan, Ning; Elliott, Karen L.

    2014-01-01

    Understanding the evolution of the neurosensory system of man, able to reflect on its own origin, is one of the major goals of comparative neurobiology. Details of the origin of neurosensory cells, their aggregation into central nervous systems and associated sensory organs, their localized patterning into remarkably different cell types aggregated into variably sized parts of the central nervous system begin to emerge. Insights at the cellular and molecular level begin to shed some light on the evolution of neurosensory cells, partially covered in this review. Molecular evidence suggests that high mobility group (HMG) proteins of pre-metazoans evolved into the definitive Sox [SRY (sex determining region Y)-box] genes used for neurosensory precursor specification in metazoans. Likewise, pre-metazoan basic helix-loop-helix (bHLH) genes evolved in metazoans into the group A bHLH genes dedicated to neurosensory differentiation in bilaterians. Available evidence suggests that the Sox and bHLH genes evolved a cross-regulatory network able to synchronize expansion of precursor populations and their subsequent differentiation into novel parts of the brain or sensory organs. Molecular evidence suggests metazoans evolved patterning gene networks early and not dedicated to neuronal development. Only later in evolution were these patterning gene networks tied into the increasing complexity of diffusible factors, many of which were already present in pre-metazoans, to drive local patterning events. It appears that the evolving molecular basis of neurosensory cell development may have led, in interaction with differentially expressed patterning genes, to local network modifications guiding unique specializations of neurosensory cells into sensory organs and various areas of the central nervous system. PMID:25416504

  14. Coupling 1D Navier Stokes equation with autoregulation lumped parameter networks for accurate cerebral blood flow modeling

    NASA Astrophysics Data System (ADS)

    Ryu, Jaiyoung; Hu, Xiao; Shadden, Shawn C.

    2014-11-01

    The cerebral circulation is unique in its ability to maintain blood flow to the brain under widely varying physiologic conditions. Incorporating this autoregulatory response is critical to cerebral blood flow modeling, as well as investigations into pathological conditions. We discuss a one-dimensional nonlinear model of blood flow in the cerebral arteries that includes coupling of autoregulatory lumped parameter networks. The model is tested to reproduce a common clinical test to assess autoregulatory function - the carotid artery compression test. The change in the flow velocity at the middle cerebral artery (MCA) during carotid compression and release demonstrated strong agreement with published measurements. The model is then used to investigate vasospasm of the MCA, a common clinical concern following subarachnoid hemorrhage. Vasospasm was modeled by prescribing vessel area reduction in the middle portion of the MCA. Our model showed similar increases in velocity for moderate vasospasms, however, for serious vasospasm (~ 90% area reduction), the blood flow velocity demonstrated decrease due to blood flow rerouting. This demonstrates a potentially important phenomenon, which otherwise would lead to false-negative decisions on clinical vasospasm if not properly anticipated.

  15. Mapping the cellular network of the circadian clock in two cockroach species.

    PubMed

    Wen, Chih-Jen; Lee, How-Jing

    2008-08-01

    The German cockroach, Blattella germanica, and the double-striped cockroach, B. bisignata, are sibling species with a similar period sequence but a distinctive circadian rhythm in locomotion. The cell distribution of immunoreactivity (ir) against three clock-related proteins, Period (PER), Pigment Dispersing Factor (PDF), and Corazonin (CRZ), was compared between the species. The PER-ir cells tend to form clusters and are sprayed out in the central nervous system. Three major PER-ir cells are located in the optic lobes, which are the sites of the major circadian clock. They are interconnected with PER-ir axon bundles. Interestingly, the potential output signal of the circadian clock, PDF, is co-localized with PER in all three groups of cells. However, only two CRZ-ir cells and their axons are found in the optic lobes and they are not co-localized with PER-ir or PDF-ir cells and axons. Since only one circadian rhythm is expressed in locomotion, the time signals from both major clocks in optic lobes are coupled by connection with PDF-ir axons. A group of 3-4 PER-ir cells in the protocerebrum display typical characteristics of neurosecretary cells. In addition, there are numerous, small PER-ir and PDF-ir co-localized cells in the pars intercerebralis (PI), which have direct connections with the neurohemoorgan, corpora cardiaca, through PER-ir and PDF-ir axons. Based on these findings, the cellular connection shows a circadian control through the endocrine route. For the rest of central nervous system, only a few PER-ir and PDF-ir cells or axons are detected. This finding implies the circadian clock for locomotion is not located in subesophageal ganglion, thoracic or abdominal ganglia, but may use other neural messengers to pass on circadian signals. Since the overall distribution pattern of the clock cells are the same for B. germanica and B. bisignata, the possible explanation for the different expressions of locomotion between the species depends on genes downstream

  16. A Dynamic Programming Approach for Base Station Sleeping in Cellular Networks

    NASA Astrophysics Data System (ADS)

    Gong, Jie; Zhou, Sheng; Niu, Zhisheng

    The energy consumption of the information and communication technology (ICT) industry, which has become a serious problem, is mostly due to the network infrastructure rather than the mobile terminals. In this paper, we focus on reducing the energy consumption of base stations (BSs) by adjusting their working modes (active or sleep). Specifically, the objective is to minimize the energy consumption while satisfying quality of service (QoS, e.g., blocking probability) requirement and, at the same time, avoiding frequent mode switching to reduce signaling and delay overhead. The problem is modeled as a dynamic programming (DP) problem, which is NP-hard in general. Based on cooperation among neighboring BSs, a low-complexity algorithm is proposed to reduce the size of state space as well as that of action space. Simulations demonstrate that, with the proposed algorithm, the active BS pattern well meets the time variation and the non-uniform spatial distribution of system traffic. Moreover, the tradeoff between the energy saving from BS sleeping and the cost of switching is well balanced by the proposed scheme.

  17. Ultra-Porous Nanoparticle Networks: A Biomimetic Coating Morphology for Enhanced Cellular Response and Infiltration

    PubMed Central

    Nasiri, Noushin; Ceramidas, Anthony; Mukherjee, Shayanti; Panneerselvan, Anitha; Nisbet, David R.; Tricoli, Antonio

    2016-01-01

    Orthopedic treatments are amongst the most common cause of surgery and are responsible for a large share of global healthcare expenditures. Engineering materials that can hasten bone integration will improve the quality of life of millions of patients per year and reduce associated medical costs. Here, we present a novel hierarchical biomimetic coating that mimics the inorganic constituent of mammalian bones with the aim of improving osseointegration of metallic implants. We exploit the thermally-driven self-organization of metastable core-shell nanoparticles during their aerosol self-assembly to rapidly fabricate robust, ultra-porous nanoparticle networks (UNN) of crystalline hydroxyapatite (HAp). Comparative analysis of the response of osteoblast cells to the ultra-porous nanostructured HAp surfaces and to the spin coated HAp surfaces revealed superior osseointegrative properties of the UNN coatings with significant cell and filopodia infiltration. This flexible synthesis approach for the engineering of UNN HAp coatings on titanium implants provides a platform technology to study the bone-implant interface for improved osseointegration and osteoconduction. PMID:27076035

  18. Mapping global sensitivity of cellular network dynamics: sensitivity heat maps and a global summation law.

    PubMed

    Rand, D A

    2008-08-06

    The dynamical systems arising from gene regulatory, signalling and metabolic networks are strongly nonlinear, have high-dimensional state spaces and depend on large numbers of parameters. Understanding the relation between the structure and the function for such systems is a considerable challenge. We need tools to identify key points of regulation, illuminate such issues as robustness and control and aid in the design of experiments. Here, I tackle this by developing new techniques for sensitivity analysis. In particular, I show how to globally analyse the sensitivity of a complex system by means of two new graphical objects: the sensitivity heat map and the parameter sensitivity spectrum. The approach to sensitivity analysis is global in the sense that it studies the variation in the whole of the model's solution rather than focusing on output variables one at a time, as in classical sensitivity analysis. This viewpoint relies on the discovery of local geometric rigidity for such systems, the mathematical insight that makes a practicable approach to such problems feasible for highly complex systems. In addition, we demonstrate a new summation theorem that substantially generalizes previous results for oscillatory and other dynamical phenomena. This theorem can be interpreted as a mathematical law stating the need for a balance between fragility and robustness in such systems.

  19. Cellular and neurochemical basis of sleep stages in the thalamocortical network

    PubMed Central

    Krishnan, Giri P; Chauvette, Sylvain; Shamie, Isaac; Soltani, Sara; Timofeev, Igor; Cash, Sydney S; Halgren, Eric; Bazhenov, Maxim

    2016-01-01

    The link between the combined action of neuromodulators in the brain and global brain states remains a mystery. In this study, using biophysically realistic models of the thalamocortical network, we identified the critical intrinsic and synaptic mechanisms, associated with the putative action of acetylcholine (ACh), GABA and monoamines, which lead to transitions between primary brain vigilance states (waking, non-rapid eye movement sleep [NREM] and REM sleep) within an ultradian cycle. Using ECoG recordings from humans and LFP recordings from cats and mice, we found that during NREM sleep the power of spindle and delta oscillations is negatively correlated in humans and positively correlated in animal recordings. We explained this discrepancy by the differences in the relative level of ACh. Overall, our study revealed the critical intrinsic and synaptic mechanisms through which different neuromodulators acting in combination result in characteristic brain EEG rhythms and transitions between sleep stages. DOI: http://dx.doi.org/10.7554/eLife.18607.001 PMID:27849520

  20. Structurally Dynamic Cellular Networks as Models for Planck Scale Physics and the Quantum Vacuum

    NASA Astrophysics Data System (ADS)

    Requardt, Manfred

    Starting from the working hypothesis that both physics and the corresponding mathematics have to be described by means of discrete concepts on the Planck scale, one of the many problems one has to face in this enterprise is to find the discrete protoforms of the building blocks of our ordinary continuum physics and mathematics. We regard these continuum concepts and continuum space-time (S-T) in particular as being emergent, coarse-grained and derived relative to an underlying erratic and disordered microscopic substratum which is expected to play by quite different rules. A central role in our analysis is played by a geometric renormalization group which creates (among other things) a kind of sparse translocal network of correlations in classical continuous space-time and underlies in our view such mysterious phenomena as holography and the black hole entropy-area law. The same point of view holds for quantum theory which we also regard as a low-energy, coarse-grained continuum theory, being emergent from something more fundamental.

  1. A 181 GOPS AKAZE Accelerator Employing Discrete-Time Cellular Neural Networks for Real-Time Feature Extraction.

    PubMed

    Jiang, Guangli; Liu, Leibo; Zhu, Wenping; Yin, Shouyi; Wei, Shaojun

    2015-09-04

    This paper proposes a real-time feature extraction VLSI architecture for high-resolution images based on the accelerated KAZE algorithm. Firstly, a new system architecture is proposed. It increases the system throughput, provides flexibility in image resolution, and offers trade-offs between speed and scaling robustness. The architecture consists of a two-dimensional pipeline array that fully utilizes computational similarities in octaves. Secondly, a substructure (block-serial discrete-time cellular neural network) that can realize a nonlinear filter is proposed. This structure decreases the memory demand through the removal of data dependency. Thirdly, a hardware-friendly descriptor is introduced in order to overcome the hardware design bottleneck through the polar sample pattern; a simplified method to realize rotation invariance is also presented. Finally, the proposed architecture is designed in TSMC 65 nm CMOS technology. The experimental results show a performance of 127 fps in full HD resolution at 200 MHz frequency. The peak performance reaches 181 GOPS and the throughput is double the speed of other state-of-the-art architectures.

  2. A cellular nonlinear network: real-time technology for the analysis of microfluidic phenomena in blood vessels

    NASA Astrophysics Data System (ADS)

    Sapuppo, F.; Bucolo, M.; Intaglietta, M.; Fortuna, L.; Arena, P.

    2006-02-01

    A new approach to the observation and analysis of dynamic structural and functional parameters in the microcirculation is described. The new non-invasive optical system is based on cellular nonlinear networks (CNNs), highly integrated analogue processor arrays whose processing elements, the cells, interact directly within a finite local neighbourhood. CNNs, thanks to their parallel processing feature and spatially distributed structure, are widely used to solve high-speed image processing and recognition problems and in the description and modelling of biological dynamics through the solution of time continuous partial differential equations (PDEs). They are therefore considered extremely suitable for spatial-temporal dynamic characterization of fluidic phenomena at micrometric to nanometric scales, such as blood flow in microvessels and its interaction with the cells of the vessel wall. A CNN universal machine (CNN-UM) structure was used to implement, via simulation and hardware (ACE16k), the algorithms to determine the functional capillarity density (FCD) and red blood cell velocity (RBCV) in capillaries obtained by intravital microscopy during in vivo experiments on hamsters. The system exploits the moving particles to distinguish the functional capillaries from the stationary background. This information is used to reconstruct a map and to calculate the velocity of the moving objects.

  3. Modeling land use and land cover changes in a vulnerable coastal region using artificial neural networks and cellular automata.

    PubMed

    Qiang, Yi; Lam, Nina S N

    2015-03-01

    As one of the most vulnerable coasts in the continental USA, the Lower Mississippi River Basin (LMRB) region has endured numerous hazards over the past decades. The sustainability of this region has drawn great attention from the international, national, and local communities, wanting to understand how the region as a system develops under intense interplay between the natural and human factors. A major problem in this deltaic region is significant land loss over the years due to a combination of natural and human factors. The main scientific and management questions are what factors contribute to the land use land cover (LULC) changes in this region, can we model the changes, and how would the LULC look like in the future given the current factors? This study analyzed the LULC changes of the region between 1996 and 2006 by utilizing an artificial neural network (ANN) to derive the LULC change rules from 15 human and natural variables. The rules were then used to simulate future scenarios in a cellular automation model. A stochastic element was added in the model to represent factors that were not included in the current model. The analysis was conducted for two sub-regions in the study area for comparison. The results show that the derived ANN models could simulate the LULC changes with a high degree of accuracy (above 92 % on average). A total loss of 263 km(2) in wetlands from 2006 to 2016 was projected, whereas the trend of forest loss will cease. These scenarios provide useful information to decision makers for better planning and management of the region.

  4. Two and a half years of country-wide rainfall maps using radio links from commercial cellular telecommunication networks

    NASA Astrophysics Data System (ADS)

    Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2016-10-01

    Although rainfall estimation employing microwave links from cellular telecommunication networks is recognized as a new promising measurement technique, its potential for long-term large-scale operational rainfall monitoring remains to be demonstrated. This study contributes to this endeavor by deriving a continuous series of rainfall maps from a large 2.5 year microwave link data set of, on average, 3383 links (2044 link paths) covering Netherlands (˜3.5 × 104 km2), a midlatitude country (˜5°E, ˜52°N) with a temperate climate. Maps are extensively verified against an independent gauge-adjusted radar rainfall data set for different temporal (15 min, 1 h, 1 day, 1 month) and spatial (0.9, 74 km2) scales. The usefulness of different steps in the rainfall retrieval algorithm, i.e., a wet-dry classification method and a filter to remove outliers, is systematically assessed. A novel dew filter is developed to correct for dew-induced wet antenna attenuation, which, although a relative underestimation of 6% to 9% is found, generally yields good results. The microwave link rainfall estimation technique performs well for the summer months (June, July, August), even outperforming interpolation of automatic rain gauge data (with a density of ˜1 gauge per 1000 km2), but large deviations are found for the winter months (December, January, February). These deviations are generally expected to be related to frozen or melting precipitation. Hence, our results show the potential of commercial microwave links for long-term large-scale operational rainfall monitoring.

  5. Murine Hyperglycemic Vasculopathy and Cardiomyopathy: Whole-Genome Gene Expression Analysis Predicts Cellular Targets and Regulatory Networks Influenced by Mannose Binding Lectin

    PubMed Central

    Zou, Chenhui; La Bonte, Laura R.; Pavlov, Vasile I.; Stahl, Gregory L.

    2012-01-01

    Hyperglycemia, in the absence of type 1 or 2 diabetes, is an independent risk factor for cardiovascular disease. We have previously demonstrated a central role for mannose binding lectin (MBL)-mediated cardiac dysfunction in acute hyperglycemic mice. In this study, we applied whole-genome microarray data analysis to investigate MBL’s role in systematic gene expression changes. The data predict possible intracellular events taking place in multiple cellular compartments such as enhanced insulin signaling pathway sensitivity, promoted mitochondrial respiratory function, improved cellular energy expenditure and protein quality control, improved cytoskeleton structure, and facilitated intracellular trafficking, all of which may contribute to the organismal health of MBL null mice against acute hyperglycemia. Our data show a tight association between gene expression profile and tissue function which might be a very useful tool in predicting cellular targets and regulatory networks connected with in vivo observations, providing clues for further mechanistic studies. PMID:22375142

  6. Proceedings of International Workshop on Cellular Neural Networks and their Applications (2nd) held in Munich, Germany, October 14 -16, 1992.

    DTIC Science & Technology

    1992-10-16

    Galias, Univ. of Mining and Metallurgy , Krakow, Poland 23 12.10 Template Synthesis of Cellular Neural Networks for Information Coding and Decoding M...Laboratory and Department of Electrical Engineering and Computer Science, University of California at Berkeley, Berkeley CA 94720 and the + Dual and...with continuous Signals Stephan Schwarz and Wolfgang Mathis University of Wuppertal Department of Electrical Engineering Institute for Computer Aided

  7. Existence and stability of pseudo almost periodic solutions for shunting inhibitory cellular neural networks with neutral type delays and time-varying leakage delays.

    PubMed

    Xu, Changjin; Zhang, Qiming; Wu, Yusen

    2014-01-01

    In this paper, shunting inhibitory cellular neural networks(SICNNs) with neutral type delays and time-varying leakage delays are investigated. By applying Lyapunov functional method and differential inequality techniques, a set of sufficient conditions are obtained for the existence and exponential stability of pseudo almost periodic solutions of the model. An example is given to support the theoretical findings. Our results improve and generalize those of the previous studies.

  8. Stackelberg Game Based Power Allocation for Physical Layer Security of Device-to-device Communication Underlaying Cellular Networks

    NASA Astrophysics Data System (ADS)

    Qu, Junyue; Cai, Yueming; Wu, Dan; Chen, Hualiang

    2014-05-01

    The problem of power allocation for device-to-device (D2D) underlay communication to improve physical layer security is addressed. Specifically, to improve the secure communication of the cellular users, we introduce a Stackelberg game for allocating the power of the D2D link under a total power constraint and a rate constraint at the D2D pair. In the introduced Stackelberg game the D2D pair works as a seller and the cellular UEs work as buyers. Firstly, because the interference signals from D2D pair are unknown to both the legitimate receiver and the illegitimate eavesdropper, it is possible that a cellular UE decline to participate in the introduced Stackelberg game. So the condition under which a legitimate user will participate in the introduced Stackelberg game is discussed. Then, based on the Stackelberg game, we propose a semi-distributed power allocation algorithm, which is proved to conclude after finite-time iterations. In the end, some simulations are presented to verify the performance improvement in the physical layer security of cellular UEs using the proposed power allocation algorithm. We can determine that with the proposed algorithm, while the D2D pair's communication demand is met, the physical layer security of cellular UEs can be improved.

  9. Multiscale modeling of cellular epigenetic states: stochasticity in molecular networks, chromatin folding in cell nuclei, and tissue pattern formation of cells

    PubMed Central

    Liang, Jie; Cao, Youfang; Gürsoy, Gamze; Naveed, Hammad; Terebus, Anna; Zhao, Jieling

    2016-01-01

    Genome sequences provide the overall genetic blueprint of cells, but cells possessing the same genome can exhibit diverse phenotypes. There is a multitude of mechanisms controlling cellular epigenetic states and that dictate the behavior of cells. Among these, networks of interacting molecules, often under stochastic control, depending on the specific wirings of molecular components and the physiological conditions, can have a different landscape of cellular states. In addition, chromosome folding in three-dimensional space provides another important control mechanism for selective activation and repression of gene expression. Fully differentiated cells with different properties grow, divide, and interact through mechanical forces and communicate through signal transduction, resulting in the formation of complex tissue patterns. Developing quantitative models to study these multi-scale phenomena and to identify opportunities for improving human health requires development of theoretical models, algorithms, and computational tools. Here we review recent progress made in these important directions. PMID:27480462

  10. Global Exponential Stability of Almost Periodic Solution for Neutral-Type Cohen-Grossberg Shunting Inhibitory Cellular Neural Networks with Distributed Delays and Impulses

    PubMed Central

    Xu, Lijun; Jiang, Qi; Gu, Guodong

    2016-01-01

    A kind of neutral-type Cohen-Grossberg shunting inhibitory cellular neural networks with distributed delays and impulses is considered. Firstly, by using the theory of impulsive differential equations and the contracting mapping principle, the existence and uniqueness of the almost periodic solution for the above system are obtained. Secondly, by constructing a suitable Lyapunov functional, the global exponential stability of the unique almost periodic solution is also investigated. The work in this paper improves and extends some results in recent years. As an application, an example and numerical simulations are presented to demonstrate the feasibility and effectiveness of the main results. PMID:27190502

  11. Existence and global exponential stability of almost periodic solution for cellular neural networks with variable coefficients and time-varying delays.

    PubMed

    Jiang, Haijun; Zhang, Long; Teng, Zhidong

    2005-11-01

    In this paper, we study cellular neural networks with almost periodic variable coefficients and time-varying delays. By using the existence theorem of almost periodic solution for general functional differential equations, introducing many real parameters and applying the Lyapunov functional method and the technique of Young inequality, we obtain some sufficient conditions to ensure the existence, uniqueness, and global exponential stability of almost periodic solution. The results obtained in this paper are new, useful, and extend and improve the existing ones in previous literature.

  12. Global Exponential Stability of Almost Periodic Solution for Neutral-Type Cohen-Grossberg Shunting Inhibitory Cellular Neural Networks with Distributed Delays and Impulses.

    PubMed

    Xu, Lijun; Jiang, Qi; Gu, Guodong

    2016-01-01

    A kind of neutral-type Cohen-Grossberg shunting inhibitory cellular neural networks with distributed delays and impulses is considered. Firstly, by using the theory of impulsive differential equations and the contracting mapping principle, the existence and uniqueness of the almost periodic solution for the above system are obtained. Secondly, by constructing a suitable Lyapunov functional, the global exponential stability of the unique almost periodic solution is also investigated. The work in this paper improves and extends some results in recent years. As an application, an example and numerical simulations are presented to demonstrate the feasibility and effectiveness of the main results.

  13. Interaction between cellular voltage-sensitive conductance and network parameters in a model of neocortex can generate epileptiform bursting.

    SciTech Connect

    van Drongelen, W.; Lee, H. C.; Koch, H.; Elsen, F.; Carroll, M. S.; Hereld, M.; Stevens, R. L.; Mathematics and Computer Science; Univ. of Chicago

    2004-01-01

    We examined the effects of both intrinsic neuronal membrane properties and network parameters on oscillatory activity in a model of neocortex. A scalable network model with six different cell types was built with the pGENESIS neural simulator. The neocortical network consisted of two types of pyramidal cells and four types of inhibitory interneurons. All cell types contained both fast sodium and delayed rectifier potassium channels for generation of action potentials. A subset of the pyramidal neurons contained an additional slow inactivating (persistent) sodium current (NaP). The neurons with the NaP current showed spontaneous bursting activity in the absence of external stimulation. The model also included a routine to calculate a simulated electroencephalogram (EEG) trace from the population activity. This revealed emergent network behavior which ranged from desynchronized activity to different types of seizure-like bursting patterns. At settings with weaker excitatory network effects, the propensity to generate seizure-like behavior increased. Strong excitatory network connectivity destroyed oscillatory behavior, whereas weak connectivity enhanced the relative importance of the spontaneously bursting cells. Our findings are in contradiction with the general opinion that strong excitatory synaptic and/or insufficient inhibition effects are associated with seizure initiation, but are in agreement with previously reported behavior in neocortex.

  14. Cellular and network properties in the functioning of the nervous system: from central pattern generators to cognition.

    PubMed

    Arshavsky, Yuri I

    2003-03-01

    The relation between individual neurons and neuronal networks in performing brain functions is one of the central questions in modern neuroscience. Most of the current literature suggests that the role of individual neurons is negligible and neural networks play a dominant role in the functioning of the nervous system. Individual neurons are usually viewed as network elements whose functions are limited to generating electrical signals and releasing neurotransmitters. Here I summarize experimental evidence that challenges this concept and argue that the unique, intrinsic properties of highly specialized individual neurons are as important for the functioning of the brain as the network properties. I first discuss the studies of relatively 'simple' functions of the nervous system, such as the control of rhythmic 'automatic' movements and generation of circadian rhythm, which indicate that individual neurons may continue performing their functions after being separated from corresponding networks. I then argue that the complex cognitive functions, such as declarative memory, language processing, and face recognition, are likely to be underlain by the properties of groups of highly specialized neurons. These neurons appear to be genetically predisposed to perform cognitive functions and their dysfunctions cannot be compensated by other elements of the nervous system. Under this concept, the electrical signals circulating within and between neural networks are considered to be a means of forming coordinated dynamic ensembles of neurons involved in performing specific functions. While still speculative, this hypothesis may provoke new approaches to studies of neural mechanisms underpinning cognitive functions of the brain.

  15. Probing Cellular and Molecular Mechanisms of Cigarette Smoke-Induced Immune Response in the Progression of Chronic Obstructive Pulmonary Disease Using Multiscale Network Modeling.

    PubMed

    Pan, Zhichao; Yu, Haishan; Liao, Jie-Lou

    Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disorder characterized by progressive destruction of lung tissues and airway obstruction. COPD is currently the third leading cause of death worldwide and there is no curative treatment available so far. Cigarette smoke (CS) is the major risk factor for COPD. Yet, only a relatively small percentage of smokers develop the disease, showing that disease susceptibility varies significantly among smokers. As smoking cessation can prevent the disease in some smokers, quitting smoking cannot halt the progression of COPD in others. Despite extensive research efforts, cellular and molecular mechanisms of COPD remain elusive. In particular, the disease susceptibility and smoking cessation effects are poorly understood. To address these issues in this work, we develop a multiscale network model that consists of nodes, which represent molecular mediators, immune cells and lung tissues, and edges describing the interactions between the nodes. Our model study identifies several positive feedback loops and network elements playing a determinant role in the CS-induced immune response and COPD progression. The results are in agreement with clinic and laboratory measurements, offering novel insight into the cellular and molecular mechanisms of COPD. The study in this work also provides a rationale for targeted therapy and personalized medicine for the disease in future.

  16. Probing Cellular and Molecular Mechanisms of Cigarette Smoke-Induced Immune Response in the Progression of Chronic Obstructive Pulmonary Disease Using Multiscale Network Modeling

    PubMed Central

    Pan, Zhichao; Yu, Haishan; Liao, Jie-Lou

    2016-01-01

    Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disorder characterized by progressive destruction of lung tissues and airway obstruction. COPD is currently the third leading cause of death worldwide and there is no curative treatment available so far. Cigarette smoke (CS) is the major risk factor for COPD. Yet, only a relatively small percentage of smokers develop the disease, showing that disease susceptibility varies significantly among smokers. As smoking cessation can prevent the disease in some smokers, quitting smoking cannot halt the progression of COPD in others. Despite extensive research efforts, cellular and molecular mechanisms of COPD remain elusive. In particular, the disease susceptibility and smoking cessation effects are poorly understood. To address these issues in this work, we develop a multiscale network model that consists of nodes, which represent molecular mediators, immune cells and lung tissues, and edges describing the interactions between the nodes. Our model study identifies several positive feedback loops and network elements playing a determinant role in the CS-induced immune response and COPD progression. The results are in agreement with clinic and laboratory measurements, offering novel insight into the cellular and molecular mechanisms of COPD. The study in this work also provides a rationale for targeted therapy and personalized medicine for the disease in future. PMID:27669518

  17. The importance of accurately modelling human interactions. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

    NASA Astrophysics Data System (ADS)

    Rosati, Dora P.; Molina, Chai; Earn, David J. D.

    2015-12-01

    Human behaviour and disease dynamics can greatly influence each other. In particular, people often engage in self-protective behaviours that affect epidemic patterns (e.g., vaccination, use of barrier precautions, isolation, etc.). Self-protective measures usually have a mitigating effect on an epidemic [16], but can in principle have negative impacts at the population level [12,15,18]. The structure of underlying social and biological contact networks can significantly influence the specific ways in which population-level effects are manifested. Using a different contact network in a disease dynamics model-keeping all else equal-can yield very different epidemic patterns. For example, it has been shown that when individuals imitate their neighbours' vaccination decisions with some probability, this can lead to herd immunity in some networks [9], yet for other networks it can preserve clusters of susceptible individuals that can drive further outbreaks of infectious disease [12].

  18. Cancer stem cells display extremely large evolvability: alternating plastic and rigid networks as a potential Mechanism: network models, novel therapeutic target strategies, and the contributions of hypoxia, inflammation and cellular senescence.

    PubMed

    Csermely, Peter; Hódsági, János; Korcsmáros, Tamás; Módos, Dezső; Perez-Lopez, Áron R; Szalay, Kristóf; Veres, Dániel V; Lenti, Katalin; Wu, Ling-Yun; Zhang, Xiang-Sun

    2015-02-01

    Cancer is increasingly perceived as a systems-level, network phenomenon. The major trend of malignant transformation can be described as a two-phase process, where an initial increase of network plasticity is followed by a decrease of plasticity at late stages of tumor development. The fluctuating intensity of stress factors, like hypoxia, inflammation and the either cooperative or hostile interactions of tumor inter-cellular networks, all increase the adaptation potential of cancer cells. This may lead to the bypass of cellular senescence, and to the development of cancer stem cells. We propose that the central tenet of cancer stem cell definition lies exactly in the indefinability of cancer stem cells. Actual properties of cancer stem cells depend on the individual "stress-history" of the given tumor. Cancer stem cells are characterized by an extremely large evolvability (i.e. a capacity to generate heritable phenotypic variation), which corresponds well with the defining hallmarks of cancer stem cells: the possession of the capacity to self-renew and to repeatedly re-build the heterogeneous lineages of cancer cells that comprise a tumor in new environments. Cancer stem cells represent a cell population, which is adapted to adapt. We argue that the high evolvability of cancer stem cells is helped by their repeated transitions between plastic (proliferative, symmetrically dividing) and rigid (quiescent, asymmetrically dividing, often more invasive) phenotypes having plastic and rigid networks. Thus, cancer stem cells reverse and replay cancer development multiple times. We describe network models potentially explaining cancer stem cell-like behavior. Finally, we propose novel strategies including combination therapies and multi-target drugs to overcome the Nietzschean dilemma of cancer stem cell targeting: "what does not kill me makes me stronger".

  19. Fast, Simple and Accurate Handwritten Digit Classification by Training Shallow Neural Network Classifiers with the ‘Extreme Learning Machine’ Algorithm

    PubMed Central

    McDonnell, Mark D.; Tissera, Migel D.; Vladusich, Tony; van Schaik, André; Tapson, Jonathan

    2015-01-01

    Recent advances in training deep (multi-layer) architectures have inspired a renaissance in neural network use. For example, deep convolutional networks are becoming the default option for difficult tasks on large datasets, such as image and speech recognition. However, here we show that error rates below 1% on the MNIST handwritten digit benchmark can be replicated with shallow non-convolutional neural networks. This is achieved by training such networks using the ‘Extreme Learning Machine’ (ELM) approach, which also enables a very rapid training time (∼ 10 minutes). Adding distortions, as is common practise for MNIST, reduces error rates even further. Our methods are also shown to be capable of achieving less than 5.5% error rates on the NORB image database. To achieve these results, we introduce several enhancements to the standard ELM algorithm, which individually and in combination can significantly improve performance. The main innovation is to ensure each hidden-unit operates only on a randomly sized and positioned patch of each image. This form of random ‘receptive field’ sampling of the input ensures the input weight matrix is sparse, with about 90% of weights equal to zero. Furthermore, combining our methods with a small number of iterations of a single-batch backpropagation method can significantly reduce the number of hidden-units required to achieve a particular performance. Our close to state-of-the-art results for MNIST and NORB suggest that the ease of use and accuracy of the ELM algorithm for designing a single-hidden-layer neural network classifier should cause it to be given greater consideration either as a standalone method for simpler problems, or as the final classification stage in deep neural networks applied to more difficult problems. PMID:26262687

  20. Stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks with mixed delays and the Wiener process based on sampled-data control

    NASA Astrophysics Data System (ADS)

    Kalpana, M.; Balasubramaniam, P.

    2013-07-01

    We investigate the stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks (MJFCNNs) with discrete, unbounded distributed delays, and the Wiener process based on sampled-data control using the linear matrix inequality (LMI) approach. The Lyapunov—Krasovskii functional combined with the input delay approach as well as the free-weighting matrix approach is employed to derive several sufficient criteria in terms of LMIs to ensure that the delayed MJFCNNs with the Wiener process is stochastic asymptotical synchronous. Restrictions (e.g., time derivative is smaller than one) are removed to obtain a proposed sampled-data controller. Finally, a numerical example is provided to demonstrate the reliability of the derived results.

  1. Examining the process of de novo gene birth: an educational primer on "integration of new genes into cellular networks, and their structural maturation".

    PubMed

    Frietze, Seth; Leatherman, Judith

    2014-03-01

    New genes that arise from modification of the noncoding portion of a genome rather than being duplicated from parent genes are called de novo genes. These genes, identified by their brief evolution and lack of parent genes, provide an opportunity to study the timeframe in which emerging genes integrate into cellular networks, and how the characteristics of these genes change as they mature into bona fide genes. An article by G. Abrusán provides an opportunity to introduce students to fundamental concepts in evolutionary and comparative genetics and to provide a technical background by which to discuss systems biology approaches when studying the evolutionary process of gene birth. Basic background needed to understand the Abrusán study and details on comparative genomic concepts tailored for a classroom discussion are provided, including discussion questions and a supplemental exercise on navigating a genome database.

  2. Examining the Process of de Novo Gene Birth: An Educational Primer on “Integration of New Genes into Cellular Networks, and Their Structural Maturation”

    PubMed Central

    Frietze, Seth; Leatherman, Judith

    2014-01-01

    SUMMARY New genes that arise from modification of the noncoding portion of a genome rather than being duplicated from parent genes are called de novo genes. These genes, identified by their brief evolution and lack of parent genes, provide an opportunity to study the timeframe in which emerging genes integrate into cellular networks, and how the characteristics of these genes change as they mature into bona fide genes. An article by G. Abrusán provides an opportunity to introduce students to fundamental concepts in evolutionary and comparative genetics and to provide a technical background by which to discuss systems biology approaches when studying the evolutionary process of gene birth. Basic background needed to understand the Abrusán study and details on comparative genomic concepts tailored for a classroom discussion are provided, including discussion questions and a supplemental exercise on navigating a genome database. PMID:24653207

  3. Smokeless Tobacco Extract (STE)-Induced Toxicity in Mammalian Cells is Mediated by the Disruption of Cellular Microtubule Network: A Key Mechanism of Cytotoxicity

    PubMed Central

    Chakrabarty, Subhendu; Ganguli, Arnab; Chakrabarti, Gopal

    2013-01-01

    Smokeless tobacco usage is a growing public health problem worldwide. The molecular mechanism(s) underlying smokeless tobacco associated tissue damage remain largely unidentified. In the present study we have tried to explore the effects of aqueous extract of smokeless tobacco (STE) on tubulin-microtubule, the major cytoskeleton protein that maintains cells morphology and participates in cell division. Exposure to STE resulted in dose-dependent cytotoxicity in a variety of mammalian transformed cell lines such as human lung epithelial cells A549, human liver epithelial cells HepG2, and mouse squamous epithelial cells HCC7, as well as non-tumorogenic human peripheral blood mononuclear cells PBMC. Cellular morphology of STE-treated cells was altered and the associated disruption of microtubule network indicates that STE targets tubulin-microtubule system in both cell lines. Furthermore it was also observed that STE-treatment resulted in the selective degradation of cellular tubulin, whereas actin remains unaltered. In vitro, polymerization of purified tubulin was inhibited by STE with the IC50 value∼150 µg/ml and this is associated with the loss of reactive cysteine residues of tubulin. Application of thiol-based antioxidant N-acetyl cysteine (NAC) significantly abrogates STE-mediated microtubule damage and associated cytotoxicity in both A549 and HepG2 cells. These results suggest that microtubule damage is one of the key mechanisms of STE-induced cytotoxity in mammalian cells. PMID:23874548

  4. Smokeless tobacco extract (STE)-induced toxicity in mammalian cells is mediated by the disruption of cellular microtubule network: a key mechanism of cytotoxicity.

    PubMed

    Das, Amlan; Bhattacharya, Abhijit; Chakrabarty, Subhendu; Ganguli, Arnab; Chakrabarti, Gopal

    2013-01-01

    Smokeless tobacco usage is a growing public health problem worldwide. The molecular mechanism(s) underlying smokeless tobacco associated tissue damage remain largely unidentified. In the present study we have tried to explore the effects of aqueous extract of smokeless tobacco (STE) on tubulin-microtubule, the major cytoskeleton protein that maintains cells morphology and participates in cell division. Exposure to STE resulted in dose-dependent cytotoxicity in a variety of mammalian transformed cell lines such as human lung epithelial cells A549, human liver epithelial cells HepG2, and mouse squamous epithelial cells SCC7, [corrected] as well as non-tumorogenic human peripheral blood mononuclear cells PBMC. Cellular morphology of STE-treated cells was altered and the associated disruption of microtubule network indicates that STE targets tubulin-microtubule system in both cell lines. Furthermore it was also observed that STE-treatment resulted in the selective degradation of cellular tubulin, whereas actin remains unaltered. In vitro, polymerization of purified tubulin was inhibited by STE with the IC50 value∼150 µg/ml and this is associated with the loss of reactive cysteine residues of tubulin. Application of thiol-based antioxidant N-acetyl cysteine (NAC) significantly abrogates STE-mediated microtubule damage and associated cytotoxicity in both A549 and HepG2 cells. These results suggest that microtubule damage is one of the key mechanisms of STE-induced cytotoxity in mammalian cells.

  5. Meta-analysis of retrograde signaling in Arabidopsis thaliana reveals a core module of genes embedded in complex cellular signaling networks.

    PubMed

    Gläßer, Christine; Haberer, Georg; Finkemeier, Iris; Pfannschmidt, Thomas; Kleine, Tatjana; Leister, Dario; Dietz, Karl-Josef; Häusler, Rainer Erich; Grimm, Bernhard; Mayer, Klaus Franz Xaver

    2014-07-01

    Plastid-to-nucleus signaling is essential for the coordination and adjustment of cellular metabolism in response to environmental and developmental cues of plant cells. A variety of operational retrograde signaling pathways have been described that are thought to be triggered by reactive oxygen species, photosynthesis redox imbalance, tetrapyrrole intermediates, and other metabolic traits. Here we report a meta-analysis based on transcriptome and protein interaction data. Comparing the output of these pathways reveals the commonalities and peculiarities stimulated by six different sources impinging on operational retrograde signaling. Our study provides novel insights into the interplay of these pathways, supporting the existence of an as-yet unknown core response module of genes being regulated under all conditions tested. Our analysis further highlights affiliated regulatory cis-elements and classifies abscisic acid and auxin-based signaling as secondary components involved in the response cascades following a plastidial signal. Our study provides a global analysis of structure and interfaces of different pathways involved in plastid-to-nucleus signaling and a new view on this complex cellular communication network.

  6. Practical demonstration of spectrally efficient FDM millimeter-wave radio over fiber systems for 5G cellular networking

    NASA Astrophysics Data System (ADS)

    Mikroulis, Spiros; Xu, Tongyang; Darwazeh, Izzat

    2016-02-01

    This work reports the first demonstration of spectrally efficient frequency division multiplexed (SEFDM) signal transmission based on mm-wave radio over fiber (RoF) technology. Such systems aim to satisfy the beyond 4G (5G) demands of low cost, low energy, millimeter-wave carrier frequencies and high spectral efficiency. The proposed radio over fiber topology, using passive optical network (PON) infrastructure and low-cost multimode fiber (MMF), is analyzed and a proof-of-concept SEFDM radio over 250m OM-1 MMF transmission with a 3m 60GHz wireless link is successfully demonstrated. Different systems are demonstrated, at raw data rates up to 3.7 Gb/s, showing SEFDM spectrum saving up to 40% relative to OFDM.

  7. Irregular Cellular Learning Automata.

    PubMed

    Esnaashari, Mehdi; Meybodi, Mohammad Reza

    2015-08-01

    Cellular learning automaton (CLA) is a recently introduced model that combines cellular automaton (CA) and learning automaton (LA). The basic idea of CLA is to use LA to adjust the state transition probability of stochastic CA. This model has been used to solve problems in areas such as channel assignment in cellular networks, call admission control, image processing, and very large scale integration placement. In this paper, an extension of CLA called irregular CLA (ICLA) is introduced. This extension is obtained by removing the structure regularity assumption in CLA. Irregularity in the structure of ICLA is needed in some applications, such as computer networks, web mining, and grid computing. The concept of expediency has been introduced for ICLA and then, conditions under which an ICLA becomes expedient are analytically found.

  8. Processing the Bouguer anomaly map of Biga and the surrounding area by the cellular neural network: application to the southwestern Marmara region

    NASA Astrophysics Data System (ADS)

    Aydogan, D.

    2007-04-01

    An image processing technique called the cellular neural network (CNN) approach is used in this study to locate geological features giving rise to gravity anomalies such as faults or the boundary of two geologic zones. CNN is a stochastic image processing technique based on template optimization using the neighborhood relationships of cells. These cells can be characterized by a functional block diagram that is typical of neural network theory. The functionality of CNN is described in its entirety by a number of small matrices (A, B and I) called the cloning template. CNN can also be considered to be a nonlinear convolution of these matrices. This template describes the strength of the nearest neighbor interconnections in the network. The recurrent perceptron learning algorithm (RPLA) is used in optimization of cloning template. The CNN and standard Canny algorithms were first tested on two sets of synthetic gravity data with the aim of checking the reliability of the proposed approach. The CNN method was compared with classical derivative techniques by applying the cross-correlation method (CC) to the same anomaly map as this latter approach can detect some features that are difficult to identify on the Bouguer anomaly maps. This approach was then applied to the Bouguer anomaly map of Biga and its surrounding area, in Turkey. Structural features in the area between Bandirma, Biga, Yenice and Gonen in the southwest Marmara region are investigated by applying the CNN and CC to the Bouguer anomaly map. Faults identified by these algorithms are generally in accordance with previously mapped surface faults. These examples show that the geologic boundaries can be detected from Bouguer anomaly maps using the cloning template approach. A visual evaluation of the outputs of the CNN and CC approaches is carried out, and the results are compared with each other. This approach provides quantitative solutions based on just a few assumptions, which makes the method more

  9. The corticotropin-releasing hormone network and the hypothalamic-pituitary-adrenal axis: molecular and cellular mechanisms involved.

    PubMed

    Bonfiglio, Juan José; Inda, Carolina; Refojo, Damián; Holsboer, Florian; Arzt, Eduardo; Silberstein, Susana

    2011-01-01

    Corticotropin-releasing hormone (CRH) plays a key role in adjusting the basal and stress-activated hypothalamic-pituitary-adrenal axis (HPA). CRH is also widely distributed in extrahypothalamic circuits, where it acts as a neuroregulator to integrate the complex neuroendocrine, autonomic, and behavioral adaptive response to stress. Hyperactive and/or dysregulated CRH circuits are involved in neuroendocrinological disturbances and stress-related mood disorders such as anxiety and depression. This review describes the main physiological features of the CRH network and summarizes recent relevant information concerning the molecular mechanism of CRH action obtained from signal transduction studies using cells and wild-type and transgenic mice lines. Special focus is placed on the MAPK signaling pathways triggered by CRH through the CRH receptor 1 that plays an essential role in CRH action in pituitary corticotrophs and in specific brain structures. Recent findings underpin the concept of specific CRH-signaling pathways restricted to specific anatomical areas. Understanding CRH action at molecular levels will not only provide insight into the precise CRH mechanism of action, but will also be instrumental in identifying novel targets for pharmacological intervention in neuroendocrine tissues and specific brain areas involved in CRH-related disorders.

  10. Molecular dynamics investigations of ozone on an ab initio potential energy surface with the utilization of pattern-recognition neural network for accurate determination of product formation.

    PubMed

    Le, Hung M; Dinh, Thach S; Le, Hieu V

    2011-10-13

    The singlet-triplet transformation and molecular dissociation of ozone (O(3)) gas is investigated by performing quasi-classical molecular dynamics (MD) simulations on an ab initio potential energy surface (PES) with visible and near-infrared excitations. MP4(SDQ) level of theory with the 6-311g(2d,2p) basis set is executed for three different electronic spin states (singlet, triplet, and quintet). In order to simplify the potential energy function, an approximation is adopted by ignoring the spin-orbit coupling and allowing the molecule to switch favorably and instantaneously to the spin state that is more energetically stable (lowest in energy among the three spin states). This assumption has previously been utilized to study the SiO(2) system as reported by Agrawal et al. (J. Chem. Phys. 2006, 124 (13), 134306). The use of such assumption in this study probably makes the upper limits of computed rate coefficients the true rate coefficients. The global PES for ozone is constructed by fitting 5906 ab initio data points using a 60-neuron two-layer feed-forward neural network. The mean-absolute error and root-mean-squared error of this fit are 0.0446 eV (1.03 kcal/mol) and 0.0756 eV (1.74 kcal/mol), respectively, which reveal very good fitting accuracy. The parameter coefficients of the global PES are reported in this paper. In order to identify the spin state with high confidence, we propose the use of a pattern-recognition neural network, which is trained to predict the spin state of a given configuration (with a prediction accuracy being 95.6% on a set of testing data points). To enhance the prediction effectiveness, a buffer series of five points are validated to confirm the spin state during the MD process to gain better confidence. Quasi-classical MD simulations from 1.2 to 2.4 eV of total internal energy (including zero-point energy) result in rate coefficients of singlet-triplet transformation in the range of 0.027 ps(-1) to 1.21 ps(-1). Also, we find very

  11. Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders

    PubMed Central

    Marquet, Pierre; Depeursinge, Christian; Magistretti, Pierre J.

    2014-01-01

    Abstract. Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed. PMID:26157976

  12. Design of cryptographically secure AES like S-Box using second-order reversible cellular automata for wireless body area network applications.

    PubMed

    Gangadari, Bhoopal Rao; Rafi Ahamed, Shaik

    2016-09-01

    In biomedical, data security is the most expensive resource for wireless body area network applications. Cryptographic algorithms are used in order to protect the information against unauthorised access. Advanced encryption standard (AES) cryptographic algorithm plays a vital role in telemedicine applications. The authors propose a novel approach for design of substitution bytes (S-Box) using second-order reversible one-dimensional cellular automata (RCA(2)) as a replacement to the classical look-up-table (LUT) based S-Box used in AES algorithm. The performance of proposed RCA(2) based S-Box and conventional LUT based S-Box is evaluated in terms of security using the cryptographic properties such as the nonlinearity, correlation immunity bias, strict avalanche criteria and entropy. Moreover, it is also shown that RCA(2) based S-Boxes are dynamic in nature, invertible and provide high level of security. Further, it is also found that the RCA(2) based S-Box have comparatively better performance than that of conventional LUT based S-Box.

  13. MARK4 is a novel microtubule-associated proteins/microtubule affinity-regulating kinase that binds to the cellular microtubule network and to centrosomes.

    PubMed

    Trinczek, Bernhard; Brajenovic, Miro; Ebneth, Andreas; Drewes, Gerard

    2004-02-13

    The MARK protein kinases were originally identified by their ability to phosphorylate a serine motif in the microtubule-binding domain of tau that is critical for microtubule binding. Here, we report the cloning and expression of a novel human paralog, MARK4, which shares 75% overall homology with MARK1-3 and is predominantly expressed in brain. Homology is most pronounced in the catalytic domain (90%), and MARK4 readily phosphorylates tau and the related microtubule-associated protein 2 (MAP2) and MAP4. In contrast to the three paralogs that all exhibit uniform cytoplasmic localization, MARK4 colocalizes with the centrosome and with microtubules in cultured cells. Overexpression of MARK4 causes thinning out of the microtubule network, concomitant with a reorganization of microtubules into bundles. In line with these findings, we show that a tandem affinity-purified MARK4 protein complex contains alpha-, beta-, and gamma-tubulin. In differentiated neuroblastoma cells, MARK4 is localized prominently at the tips of neurite-like processes. We suggest that although the four MARK/PAR-1 kinases might play multiple cellular roles in concert with different targets, MARK4 is likely to be directly involved in microtubule organization in neuronal cells and may contribute to the pathological phosphorylation of tau in Alzheimer's disease.

  14. Measurements of sediments loads in small, ungaged, basins may be required to accurately close sediment budgets: An example from a monitoring network on the southern Colorado Plateau

    NASA Astrophysics Data System (ADS)

    Griffiths, R. E.; Topping, D. J.

    2013-12-01

    Sediment supplied by small ungaged tributaries is often a crucial unknown for closing sediment budgets. Efforts to estimate the quantity of sediment provided by small tributaries can vary widely. Previous estimates of sediment-yield from small ungaged tributaries to the Colorado River downstream from Glen Canyon Dam vary by an order of magnitude; this range in sediment yields has resulted in different researchers reaching opposite conclusions on the state of sediment budgets in the Colorado River below Glen Canyon Dam. To better constrain the input of fine sediment (sand, silt, and clay) from these tributaries to the Colorado River, eight sediment-monitoring stations have been established on previously ungaged small tributaries in Glen, Marble, and Grand Canyons. These tributaries flow through canyons deeply incised into Paleozoic and Mesozoic sedimentary rocks. The drainage areas of these tributary range from 47 to 770 km2 and represent 54% of the drainage area of Glen Canyon and 69% of the previously ungaged area of upper Marble Canyon. This monitoring network was initially established on 7 ephemeral streams in 2000-2001 and then expanded in 2006 to include perennial Bright Angel Creek; Bright Angel Creek has a historic 1923-1993 gaging record used to provide long-term hydrologic context for the other tributaries. Measuring discharge and collecting conventional suspended-sediment samples at these remote ephemeral streams is essentially impossible. The majority of large floods are short-duration events (lasting minutes to hours) associated with summer thunderstorms. The remote locations of the streams and short duration of the floods make it prohibitively expensive, if not impossible, to directly measure the discharge of water or to collect conventional depth-integrated suspended-sediment samples. Discharge during flood events are therefore calculated using a stage-discharge relation developed from a series of modeled flows and a stage record from a downward

  15. Optimization of Stripping Voltammetric Sensor by a Back Propagation Artificial Neural Network for the Accurate Determination of Pb(II) in the Presence of Cd(II)

    PubMed Central

    Zhao, Guo; Wang, Hui; Liu, Gang; Wang, Zhiqiang

    2016-01-01

    An easy, but effective, method has been proposed to detect and quantify the Pb(II) in the presence of Cd(II) based on a Bi/glassy carbon electrode (Bi/GCE) with the combination of a back propagation artificial neural network (BP-ANN) and square wave anodic stripping voltammetry (SWASV) without further electrode modification. The effects of Cd(II) in different concentrations on stripping responses of Pb(II) was studied. The results indicate that the presence of Cd(II) will reduce the prediction precision of a direct calibration model. Therefore, a two-input and one-output BP-ANN was built for the optimization of a stripping voltammetric sensor, which considering the combined effects of Cd(II) and Pb(II) on the SWASV detection of Pb(II) and establishing the nonlinear relationship between the stripping peak currents of Pb(II) and Cd(II) and the concentration of Pb(II). The key parameters of the BP-ANN and the factors affecting the SWASV detection of Pb(II) were optimized. The prediction performance of direct calibration model and BP-ANN model were tested with regard to the mean absolute error (MAE), root mean square error (RMSE), average relative error (ARE), and correlation coefficient. The results proved that the BP-ANN model exhibited higher prediction accuracy than the direct calibration model. Finally, a real samples analysis was performed to determine trace Pb(II) in some soil specimens with satisfactory results. PMID:27657083

  16. Optimization of Stripping Voltammetric Sensor by a Back Propagation Artificial Neural Network for the Accurate Determination of Pb(II) in the Presence of Cd(II).

    PubMed

    Zhao, Guo; Wang, Hui; Liu, Gang; Wang, Zhiqiang

    2016-09-21

    An easy, but effective, method has been proposed to detect and quantify the Pb(II) in the presence of Cd(II) based on a Bi/glassy carbon electrode (Bi/GCE) with the combination of a back propagation artificial neural network (BP-ANN) and square wave anodic stripping voltammetry (SWASV) without further electrode modification. The effects of Cd(II) in different concentrations on stripping responses of Pb(II) was studied. The results indicate that the presence of Cd(II) will reduce the prediction precision of a direct calibration model. Therefore, a two-input and one-output BP-ANN was built for the optimization of a stripping voltammetric sensor, which considering the combined effects of Cd(II) and Pb(II) on the SWASV detection of Pb(II) and establishing the nonlinear relationship between the stripping peak currents of Pb(II) and Cd(II) and the concentration of Pb(II). The key parameters of the BP-ANN and the factors affecting the SWASV detection of Pb(II) were optimized. The prediction performance of direct calibration model and BP-ANN model were tested with regard to the mean absolute error (MAE), root mean square error (RMSE), average relative error (ARE), and correlation coefficient. The results proved that the BP-ANN model exhibited higher prediction accuracy than the direct calibration model. Finally, a real samples analysis was performed to determine trace Pb(II) in some soil specimens with satisfactory results.

  17. iCDI-PseFpt: identify the channel-drug interaction in cellular networking with PseAAC and molecular fingerprints.

    PubMed

    Xiao, Xuan; Min, Jian-Liang; Wang, Pu; Chou, Kuo-Chen

    2013-11-21

    Many crucial functions in life, such as heartbeat, sensory transduction and central nervous system response, are controlled by cell signalings via various ion channels. Therefore, ion channels have become an excellent drug target, and study of ion channel-drug interaction networks is an important topic for drug development. However, it is both time-consuming and costly to determine whether a drug and a protein ion channel are interacting with each other in a cellular network by means of experimental techniques. Although some computational methods were developed in this regard based on the knowledge of the 3D (three-dimensional) structure of protein, unfortunately their usage is quite limited because the 3D structures for most protein ion channels are still unknown. With the avalanche of protein sequences generated in the post-genomic age, it is highly desirable to develop the sequence-based computational method to address this problem. To take up the challenge, we developed a new predictor called iCDI-PseFpt, in which the protein ion-channel sample is formulated by the PseAAC (pseudo amino acid composition) generated with the gray model theory, the drug compound by the 2D molecular fingerprint, and the operation engine is the fuzzy K-nearest neighbor algorithm. The overall success rate achieved by iCDI-PseFpt via the jackknife cross-validation was 87.27%, which is remarkably higher than that by any of the existing predictors in this area. As a user-friendly web-server, iCDI-PseFpt is freely accessible to the public at the website http://www.jci-bioinfo.cn/iCDI-PseFpt/. Furthermore, for the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated math equations presented in the paper just for its integrity. It has not escaped our notice that the current approach can also be used to study other drug-target interaction networks.

  18. Accurate prediction of higher-level electronic structure energies for large databases using neural networks, Hartree-Fock energies, and small subsets of the database.

    PubMed

    Malshe, M; Pukrittayakamee, A; Raff, L M; Hagan, M; Bukkapatnam, S; Komanduri, R

    2009-09-28

    A novel method is presented that significantly reduces the computational bottleneck of executing high-level, electronic structure calculations of the energies and their gradients for a large database that adequately samples the configuration space of importance for systems containing more than four atoms that are undergoing multiple, simultaneous reactions in several energetically open channels. The basis of the method is the high-degree of correlation that generally exists between the Hartree-Fock (HF) and higher-level electronic structure energies. It is shown that if the input vector to a neural network (NN) includes both the configuration coordinates and the HF energies of a small subset of the database, MP4(SDQ) energies with the same basis set can be predicted for the entire database using only the HF and MP4(SDQ) energies for the small subset and the HF energies for the remainder of the database. The predictive error is shown to be less than or equal to the NN fitting error if a NN is fitted to the entire database of higher-level electronic structure energies. The general method is applied to the computation of MP4(SDQ) energies of 68,308 configurations that comprise the database for the simultaneous, unimolecular decomposition of vinyl bromide into six different reaction channels. The predictive accuracy of the method is investigated by employing successively smaller subsets of the database to train the NN to predict the MP4(SDQ) energies of the remaining configurations of the database. The results indicate that for this system, the subset can be as small as 8% of the total number of configurations in the database without loss of accuracy beyond that expected if a NN is employed to fit the higher-level energies for the entire database. The utilization of this procedure is shown to save about 78% of the total computational time required for the execution of the MP4(SDQ) calculations. The sampling error involved with selection of the subset is shown to be

  19. Accurate prediction of higher-level electronic structure energies for large databases using neural networks, Hartree-Fock energies, and small subsets of the database

    NASA Astrophysics Data System (ADS)

    Malshe, M.; Pukrittayakamee, A.; Raff, L. M.; Hagan, M.; Bukkapatnam, S.; Komanduri, R.

    2009-09-01

    A novel method is presented that significantly reduces the computational bottleneck of executing high-level, electronic structure calculations of the energies and their gradients for a large database that adequately samples the configuration space of importance for systems containing more than four atoms that are undergoing multiple, simultaneous reactions in several energetically open channels. The basis of the method is the high-degree of correlation that generally exists between the Hartree-Fock (HF) and higher-level electronic structure energies. It is shown that if the input vector to a neural network (NN) includes both the configuration coordinates and the HF energies of a small subset of the database, MP4(SDQ) energies with the same basis set can be predicted for the entire database using only the HF and MP4(SDQ) energies for the small subset and the HF energies for the remainder of the database. The predictive error is shown to be less than or equal to the NN fitting error if a NN is fitted to the entire database of higher-level electronic structure energies. The general method is applied to the computation of MP4(SDQ) energies of 68 308 configurations that comprise the database for the simultaneous, unimolecular decomposition of vinyl bromide into six different reaction channels. The predictive accuracy of the method is investigated by employing successively smaller subsets of the database to train the NN to predict the MP4(SDQ) energies of the remaining configurations of the database. The results indicate that for this system, the subset can be as small as 8% of the total number of configurations in the database without loss of accuracy beyond that expected if a NN is employed to fit the higher-level energies for the entire database. The utilization of this procedure is shown to save about 78% of the total computational time required for the execution of the MP4(SDQ) calculations. The sampling error involved with selection of the subset is shown to be

  20. Nodule Detection in a Lung Region that's Segmented with Using Genetic Cellular Neural Networks and 3D Template Matching with Fuzzy Rule Based Thresholding

    PubMed Central

    Osman, Onur; Ucan, Osman N.

    2008-01-01

    Objective The purpose of this study was to develop a new method for automated lung nodule detection in serial section CT images with using the characteristics of the 3D appearance of the nodules that distinguish themselves from the vessels. Materials and Methods Lung nodules were detected in four steps. First, to reduce the number of region of interests (ROIs) and the computation time, the lung regions of the CTs were segmented using Genetic Cellular Neural Networks (G-CNN). Then, for each lung region, ROIs were specified with using the 8 directional search; +1 or -1 values were assigned to each voxel. The 3D ROI image was obtained by combining all the 2-Dimensional (2D) ROI images. A 3D template was created to find the nodule-like structures on the 3D ROI image. Convolution of the 3D ROI image with the proposed template strengthens the shapes that are similar to those of the template and it weakens the other ones. Finally, fuzzy rule based thresholding was applied and the ROI's were found. To test the system's efficiency, we used 16 cases with a total of 425 slices, which were taken from the Lung Image Database Consortium (LIDC) dataset. Results The computer aided diagnosis (CAD) system achieved 100% sensitivity with 13.375 FPs per case when the nodule thickness was greater than or equal to 5.625 mm. Conclusion Our results indicate that the detection performance of our algorithm is satisfactory, and this may well improve the performance of computer-aided detection of lung nodules. PMID:18253070

  1. iDrug-Target: predicting the interactions between drug compounds and target proteins in cellular networking via benchmark dataset optimization approach.

    PubMed

    Xiao, Xuan; Min, Jian-Liang; Lin, Wei-Zhong; Liu, Zi; Cheng, Xiang; Chou, Kuo-Chen

    2015-01-01

    Information about the interactions of drug compounds with proteins in cellular networking is very important for drug development. Unfortunately, all the existing predictors for identifying drug-protein interactions were trained by a skewed benchmark data-set where the number of non-interactive drug-protein pairs is overwhelmingly larger than that of the interactive ones. Using this kind of highly unbalanced benchmark data-set to train predictors would lead to the outcome that many interactive drug-protein pairs might be mispredicted as non-interactive. Since the minority interactive pairs often contain the most important information for drug design, it is necessary to minimize this kind of misprediction. In this study, we adopted the neighborhood cleaning rule and synthetic minority over-sampling technique to treat the skewed benchmark datasets and balance the positive and negative subsets. The new benchmark datasets thus obtained are called the optimized benchmark datasets, based on which a new predictor called iDrug-Target was developed that contains four sub-predictors: iDrug-GPCR, iDrug-Chl, iDrug-Ezy, and iDrug-NR, specialized for identifying the interactions of drug compounds with GPCRs (G-protein-coupled receptors), ion channels, enzymes, and NR (nuclear receptors), respectively. Rigorous cross-validations on a set of experiment-confirmed datasets have indicated that these new predictors remarkably outperformed the existing ones for the same purpose. To maximize users' convenience, a public accessible Web server for iDrug-Target has been established at http://www.jci-bioinfo.cn/iDrug-Target/ , by which users can easily get their desired results. It has not escaped our notice that the aforementioned strategy can be widely used in many other areas as well.

  2. Integrating proteomics profiling data sets: a network perspective.

    PubMed

    Bhat, Akshay; Dakna, Mohammed; Mischak, Harald

    2015-01-01

    Understanding disease mechanisms often requires complex and accurate integration of cellular pathways and molecular networks. Systems biology offers the possibility to provide a comprehensive map of the cell's intricate wiring network, which can ultimately lead to decipher the disease phenotype. Here, we describe what biological pathways are, how they function in normal and abnormal cellular systems, limitations faced by databases for integrating data, and highlight how network models are emerging as a powerful integrative framework to understand and interpret the roles of proteins and peptides in diseases.

  3. Revisiting Cardiac Cellular Composition

    PubMed Central

    Pinto, Alexander R.; Ilinykh, Alexei; Ivey, Malina J.; Kuwabara, Jill T.; D'Antoni, Michelle L.; Debuque, Ryan; Chandran, Anjana; Wang, Lina; Arora, Komal; Rosenthal, Nadia; Tallquist, Michelle D.

    2015-01-01

    Rationale Accurate knowledge of the cellular composition of the heart is essential to fully understand the changes that occur during pathogenesis and to devise strategies for tissue engineering and regeneration. Objective To examine the relative frequency of cardiac endothelial cells, hematopoietic-derived cells and fibroblasts in the mouse and human heart. Methods and Results Using a combination of genetic tools and cellular markers, we examined the occurrence of the most prominent cell types in the adult mouse heart. Immunohistochemistry revealed that endothelial cells constitute over 60%, hematopoietic-derived cells 5–10%, and fibroblasts under 20% of the non-myocytes in the heart. A refined cell isolation protocol and an improved flow cytometry approach provided an independent means of determining the relative abundance of non-myocytes. High dimensional analysis and unsupervised clustering of cell populations confirmed that endothelial cells are the most abundant cell population. Interestingly, fibroblast numbers are smaller than previously estimated, and two commonly assigned fibroblast markers, Sca-1 and CD90, underrepresent fibroblast numbers. We also describe an alternative fibroblast surface marker that more accurately identifies the resident cardiac fibroblast population. Conclusions This new perspective on the abundance of different cell types in the heart demonstrates that fibroblasts comprise a relatively minor population. By contrast, endothelial cells constitute the majority of non-cardiomyocytes and are likely to play a greater role in physiologic function and response to injury than previously appreciated. PMID:26635390

  4. Accurate Finite Difference Algorithms

    NASA Technical Reports Server (NTRS)

    Goodrich, John W.

    1996-01-01

    Two families of finite difference algorithms for computational aeroacoustics are presented and compared. All of the algorithms are single step explicit methods, they have the same order of accuracy in both space and time, with examples up to eleventh order, and they have multidimensional extensions. One of the algorithm families has spectral like high resolution. Propagation with high order and high resolution algorithms can produce accurate results after O(10(exp 6)) periods of propagation with eight grid points per wavelength.

  5. Accurate monotone cubic interpolation

    NASA Technical Reports Server (NTRS)

    Huynh, Hung T.

    1991-01-01

    Monotone piecewise cubic interpolants are simple and effective. They are generally third-order accurate, except near strict local extrema where accuracy degenerates to second-order due to the monotonicity constraint. Algorithms for piecewise cubic interpolants, which preserve monotonicity as well as uniform third and fourth-order accuracy are presented. The gain of accuracy is obtained by relaxing the monotonicity constraint in a geometric framework in which the median function plays a crucial role.

  6. Preliminary Analysis of the efficacy of Artificial neural Network (ANN) and Cellular Automaton (CA) based Land Use Models in Urban Land-Use Planning

    NASA Astrophysics Data System (ADS)

    Harun, R.

    2013-05-01

    This research provides an opportunity of collaboration between urban planners and modellers by providing a clear theoretical foundations on the two most widely used urban land use models, and assessing the effectiveness of applying the models in urban planning context. Understanding urban land cover change is an essential element for sustainable urban development as it affects ecological functioning in urban ecosystem. Rapid urbanization due to growing inclination of people to settle in urban areas has increased the complexities in predicting that at what shape and size cities will grow. The dynamic changes in the spatial pattern of urban landscapes has exposed the policy makers and environmental scientists to great challenge. But geographic science has grown in symmetry to the advancements in computer science. Models and tools are developed to support urban planning by analyzing the causes and consequences of land use changes and project the future. Of all the different types of land use models available in recent days, it has been found by researchers that the most frequently used models are Cellular Automaton (CA) and Artificial Neural Networks (ANN) models. But studies have demonstrated that the existing land use models have not been able to meet the needs of planners and policy makers. There are two primary causes identified behind this prologue. First, there is inadequate understanding of the fundamental theories and application of the models in urban planning context i.e., there is a gap in communication between modellers and urban planners. Second, the existing models exclude many key drivers in the process of simplification of the complex urban system that guide urban spatial pattern. Thus the models end up being effective in assessing the impacts of certain land use policies, but cannot contribute in new policy formulation. This paper is an attempt to increase the knowledge base of planners on the most frequently used land use model and also assess the

  7. ARACNe-AP: Gene Network Reverse Engineering through Adaptive Partitioning inference of Mutual Information. | Office of Cancer Genomics

    Cancer.gov

    The accurate reconstruction of gene regulatory networks from large scale molecular profile datasets represents one of the grand challenges of Systems Biology. The Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) represents one of the most effective tools to accomplish this goal. However, the initial Fixed Bandwidth (FB) implementation is both inefficient and unable to deal with sample sets providing largely uneven coverage of the probability density space.

  8. Networks.

    ERIC Educational Resources Information Center

    Maughan, George R.; Petitto, Karen R.; McLaughlin, Don

    2001-01-01

    Describes the connectivity features and options of modern campus communication and information system networks, including signal transmission (wire-based and wireless), signal switching, convergence of networks, and network assessment variables, to enable campus leaders to make sound future-oriented decisions. (EV)

  9. Accurate quantum chemical calculations

    NASA Technical Reports Server (NTRS)

    Bauschlicher, Charles W., Jr.; Langhoff, Stephen R.; Taylor, Peter R.

    1989-01-01

    An important goal of quantum chemical calculations is to provide an understanding of chemical bonding and molecular electronic structure. A second goal, the prediction of energy differences to chemical accuracy, has been much harder to attain. First, the computational resources required to achieve such accuracy are very large, and second, it is not straightforward to demonstrate that an apparently accurate result, in terms of agreement with experiment, does not result from a cancellation of errors. Recent advances in electronic structure methodology, coupled with the power of vector supercomputers, have made it possible to solve a number of electronic structure problems exactly using the full configuration interaction (FCI) method within a subspace of the complete Hilbert space. These exact results can be used to benchmark approximate techniques that are applicable to a wider range of chemical and physical problems. The methodology of many-electron quantum chemistry is reviewed. Methods are considered in detail for performing FCI calculations. The application of FCI methods to several three-electron problems in molecular physics are discussed. A number of benchmark applications of FCI wave functions are described. Atomic basis sets and the development of improved methods for handling very large basis sets are discussed: these are then applied to a number of chemical and spectroscopic problems; to transition metals; and to problems involving potential energy surfaces. Although the experiences described give considerable grounds for optimism about the general ability to perform accurate calculations, there are several problems that have proved less tractable, at least with current computer resources, and these and possible solutions are discussed.

  10. Cellular automata for traffic simulations

    NASA Astrophysics Data System (ADS)

    Wolf, Dietrich E.

    1999-02-01

    Traffic phenomena such as the transition from free to congested flow, lane inversion and platoon formation can be accurately reproduced using cellular automata. Being computationally extremely efficient, they simulate large traffic systems many times faster than real time so that predictions become feasible. A riview of recent results is given. The presence of metastable states at the jamming transition is discussed in detail. A simple new cellular automation is introduced, in which the interaction between cars is Galilei-invariant. It is shown that this type of interaction accounts for metastable states in a very natural way.

  11. Energetic costs of cellular computation.

    PubMed

    Mehta, Pankaj; Schwab, David J

    2012-10-30

    Cells often perform computations in order to respond to environmental cues. A simple example is the classic problem, first considered by Berg and Purcell, of determining the concentration of a chemical ligand in the surrounding media. On general theoretical grounds, it is expected that such computations require cells to consume energy. In particular, Landauer's principle states that energy must be consumed in order to erase the memory of past observations. Here, we explicitly calculate the energetic cost of steady-state computation of ligand concentration for a simple two-component cellular network that implements a noisy version of the Berg-Purcell strategy. We show that learning about external concentrations necessitates the breaking of detailed balance and consumption of energy, with greater learning requiring more energy. Our calculations suggest that the energetic costs of cellular computation may be an important constraint on networks designed to function in resource poor environments, such as the spore germination networks of bacteria.

  12. Energetic costs of cellular computation

    PubMed Central

    Mehta, Pankaj; Schwab, David J.

    2012-01-01

    Cells often perform computations in order to respond to environmental cues. A simple example is the classic problem, first considered by Berg and Purcell, of determining the concentration of a chemical ligand in the surrounding media. On general theoretical grounds, it is expected that such computations require cells to consume energy. In particular, Landauer’s principle states that energy must be consumed in order to erase the memory of past observations. Here, we explicitly calculate the energetic cost of steady-state computation of ligand concentration for a simple two-component cellular network that implements a noisy version of the Berg–Purcell strategy. We show that learning about external concentrations necessitates the breaking of detailed balance and consumption of energy, with greater learning requiring more energy. Our calculations suggest that the energetic costs of cellular computation may be an important constraint on networks designed to function in resource poor environments, such as the spore germination networks of bacteria. PMID:23045633

  13. Investigating the specific core genetic-and-epigenetic networks of cellular mechanisms involved in human aging in peripheral blood mononuclear cells.

    PubMed

    Li, Cheng-Wei; Wang, Wen-Hsin; Chen, Bor-Sen

    2016-02-23

    Aging is an inevitable part of life for humans, and slowing down the aging process has become a main focus of human endeavor. Here, we applied a systems biology approach to construct protein-protein interaction networks, gene regulatory networks, and epigenetic networks, i.e. genetic and epigenetic networks (GENs), of elderly individuals and young controls. We then compared these GENs to extract aging mechanisms using microarray data in peripheral blood mononuclear cells, microRNA (miRNA) data, and database mining. The core GENs of elderly individuals and young controls were obtained by applying principal network projection to GENs based on Principal Component Analysis. By comparing the core networks, we identified that to overcome the accumulated mutation of genes in the aging process the transcription factor JUN can be activated by stress signals, including the MAPK signaling, T-cell receptor signaling, and neurotrophin signaling pathways through DNA methylation of BTG3, G0S2, and AP2B1 and the regulations of mir-223 let-7d, and mir-130a. We also address the aging mechanisms in old men and women. Furthermore, we proposed that drugs designed to target these DNA methylated genes or miRNAs may delay aging. A multiple drug combination comprising phenylalanine, cholesterol, and palbociclib was finally designed for delaying the aging process.

  14. Metadata Standard and Data Exchange Specifications to Describe, Model, and Integrate Complex and Diverse High-Throughput Screening Data from the Library of Integrated Network-based Cellular Signatures (LINCS).

    PubMed

    Vempati, Uma D; Chung, Caty; Mader, Chris; Koleti, Amar; Datar, Nakul; Vidović, Dušica; Wrobel, David; Erickson, Sean; Muhlich, Jeremy L; Berriz, Gabriel; Benes, Cyril H; Subramanian, Aravind; Pillai, Ajay; Shamu, Caroline E; Schürer, Stephan C

    2014-06-01

    The National Institutes of Health Library of Integrated Network-based Cellular Signatures (LINCS) program is generating extensive multidimensional data sets, including biochemical, genome-wide transcriptional, and phenotypic cellular response signatures to a variety of small-molecule and genetic perturbations with the goal of creating a sustainable, widely applicable, and readily accessible systems biology knowledge resource. Integration and analysis of diverse LINCS data sets depend on the availability of sufficient metadata to describe the assays and screening results and on their syntactic, structural, and semantic consistency. Here we report metadata specifications for the most important molecular and cellular components and recommend them for adoption beyond the LINCS project. We focus on the minimum required information to model LINCS assays and results based on a number of use cases, and we recommend controlled terminologies and ontologies to annotate assays with syntactic consistency and semantic integrity. We also report specifications for a simple annotation format (SAF) to describe assays and screening results based on our metadata specifications with explicit controlled vocabularies. SAF specifically serves to programmatically access and exchange LINCS data as a prerequisite for a distributed information management infrastructure. We applied the metadata specifications to annotate large numbers of LINCS cell lines, proteins, and small molecules. The resources generated and presented here are freely available.

  15. BIOACCESSIBILITY TESTS ACCURATELY ESTIMATE ...

    EPA Pesticide Factsheets

    Hazards of soil-borne Pb to wild birds may be more accurately quantified if the bioavailability of that Pb is known. To better understand the bioavailability of Pb to birds, we measured blood Pb concentrations in Japanese quail (Coturnix japonica) fed diets containing Pb-contaminated soils. Relative bioavailabilities were expressed by comparison with blood Pb concentrations in quail fed a Pb acetate reference diet. Diets containing soil from five Pb-contaminated Superfund sites had relative bioavailabilities from 33%-63%, with a mean of about 50%. Treatment of two of the soils with P significantly reduced the bioavailability of Pb. The bioaccessibility of the Pb in the test soils was then measured in six in vitro tests and regressed on bioavailability. They were: the “Relative Bioavailability Leaching Procedure” (RBALP) at pH 1.5, the same test conducted at pH 2.5, the “Ohio State University In vitro Gastrointestinal” method (OSU IVG), the “Urban Soil Bioaccessible Lead Test”, the modified “Physiologically Based Extraction Test” and the “Waterfowl Physiologically Based Extraction Test.” All regressions had positive slopes. Based on criteria of slope and coefficient of determination, the RBALP pH 2.5 and OSU IVG tests performed very well. Speciation by X-ray absorption spectroscopy demonstrated that, on average, most of the Pb in the sampled soils was sorbed to minerals (30%), bound to organic matter 24%, or present as Pb sulfate 18%. Ad

  16. Optofluidic Detection for Cellular Phenotyping

    PubMed Central

    Tung, Yi-Chung; Huang, Nien-Tsu; Oh, Bo-Ram; Patra, Bishnubrata; Pan, Chi-Chun; Qiu, Teng; Paul, K. Chu; Zhang, Wenjun; Kurabayashi, Katsuo

    2012-01-01

    Quantitative analysis of the output of processes and molecular interactions within a single cell is highly critical to the advancement of accurate disease screening and personalized medicine. Optical detection is one of the most broadly adapted measurement methods in biological and clinical assays and serves cellular phenotyping. Recently, microfluidics has obtained increasing attention due to several advantages, such as small sample and reagent volumes, very high throughput, and accurate flow control in the spatial and temporal domains. Optofluidics, which is the attempt to integrate optics with microfluidic, shows great promise to enable on-chip phenotypic measurements with high precision, sensitivity, specificity, and simplicity. This paper reviews the most recent developments of optofluidic technologies for cellular phenotyping optical detection. PMID:22854915

  17. Alterations of a Cellular Cholesterol Metabolism Network Are a Molecular Feature of Obesity-Related Type 2 Diabetes and Cardiovascular Disease

    PubMed Central

    Ding, Jingzhong; Reynolds, Lindsay M.; Zeller, Tanja; Müller, Christian; Lohman, Kurt; Nicklas, Barbara J.; Kritchevsky, Stephen B.; Huang, Zhiqing; de la Fuente, Alberto; Soranzo, Nicola; Settlage, Robert E.; Chuang, Chia-Chi; Howard, Timothy; Xu, Ning; Goodarzi, Mark O.; Chen, Y.-D. Ida; Rotter, Jerome I.; Siscovick, David S.; Parks, John S.; Murphy, Susan; Jacobs, David R.; Post, Wendy; Tracy, Russell P.; Wild, Philipp S.; Blankenberg, Stefan; Hoeschele, Ina; Herrington, David; McCall, Charles E.

    2015-01-01

    Obesity is linked to type 2 diabetes (T2D) and cardiovascular diseases; however, the underlying molecular mechanisms remain unclear. We aimed to identify obesity-associated molecular features that may contribute to obesity-related diseases. Using circulating monocytes from 1,264 Multi-Ethnic Study of Atherosclerosis (MESA) participants, we quantified the transcriptome and epigenome. We discovered that alterations in a network of coexpressed cholesterol metabolism genes are a signature feature of obesity and inflammatory stress. This network included 11 BMI-associated genes related to sterol uptake (↑LDLR, ↓MYLIP), synthesis (↑SCD, FADS1, HMGCS1, FDFT1, SQLE, CYP51A1, SC4MOL), and efflux (↓ABCA1, ABCG1), producing a molecular profile expected to increase intracellular cholesterol. Importantly, these alterations were associated with T2D and coronary artery calcium (CAC), independent from cardiometabolic factors, including serum lipid profiles. This network mediated the associations between obesity and T2D/CAC. Several genes in the network harbored C-phosphorus-G dinucleotides (e.g., ABCG1/cg06500161), which overlapped Encyclopedia of DNA Elements (ENCODE)-annotated regulatory regions and had methylation profiles that mediated the associations between BMI/inflammation and expression of their cognate genes. Taken together with several lines of previous experimental evidence, these data suggest that alterations of the cholesterol metabolism gene network represent a molecular link between obesity/inflammation and T2D/CAC. PMID:26153245

  18. Accurate spectral color measurements

    NASA Astrophysics Data System (ADS)

    Hiltunen, Jouni; Jaeaeskelaeinen, Timo; Parkkinen, Jussi P. S.

    1999-08-01

    Surface color measurement is of importance in a very wide range of industrial applications including paint, paper, printing, photography, textiles, plastics and so on. For a demanding color measurements spectral approach is often needed. One can measure a color spectrum with a spectrophotometer using calibrated standard samples as a reference. Because it is impossible to define absolute color values of a sample, we always work with approximations. The human eye can perceive color difference as small as 0.5 CIELAB units and thus distinguish millions of colors. This 0.5 unit difference should be a goal for the precise color measurements. This limit is not a problem if we only want to measure the color difference of two samples, but if we want to know in a same time exact color coordinate values accuracy problems arise. The values of two instruments can be astonishingly different. The accuracy of the instrument used in color measurement may depend on various errors such as photometric non-linearity, wavelength error, integrating sphere dark level error, integrating sphere error in both specular included and specular excluded modes. Thus the correction formulas should be used to get more accurate results. Another question is how many channels i.e. wavelengths we are using to measure a spectrum. It is obvious that the sampling interval should be short to get more precise results. Furthermore, the result we get is always compromise of measuring time, conditions and cost. Sometimes we have to use portable syste or the shape and the size of samples makes it impossible to use sensitive equipment. In this study a small set of calibrated color tiles measured with the Perkin Elmer Lamda 18 and the Minolta CM-2002 spectrophotometers are compared. In the paper we explain the typical error sources of spectral color measurements, and show which are the accuracy demands a good colorimeter should have.

  19. Integrative omics reveals MYCN as a global suppressor of cellular signalling and enables network-based therapeutic target discovery in neuroblastoma.

    PubMed

    Duffy, David J; Krstic, Aleksandar; Halasz, Melinda; Schwarzl, Thomas; Fey, Dirk; Iljin, Kristiina; Mehta, Jai Prakash; Killick, Kate; Whilde, Jenny; Turriziani, Benedetta; Haapa-Paananen, Saija; Fey, Vidal; Fischer, Matthias; Westermann, Frank; Henrich, Kai-Oliver; Bannert, Steffen; Higgins, Desmond G; Kolch, Walter

    2015-12-22

    Despite intensive study, many mysteries remain about the MYCN oncogene's functions. Here we focus on MYCN's role in neuroblastoma, the most common extracranial childhood cancer. MYCN gene amplification occurs in 20% of cases, but other recurrent somatic mutations are rare. This scarcity of tractable targets has hampered efforts to develop new therapeutic options. We employed a multi-level omics approach to examine MYCN functioning and identify novel therapeutic targets for this largely un-druggable oncogene. We used systems medicine based computational network reconstruction and analysis to integrate a range of omic techniques: sequencing-based transcriptomics, genome-wide chromatin immunoprecipitation, siRNA screening and interaction proteomics, revealing that MYCN controls highly connected networks, with MYCN primarily supressing the activity of network components. MYCN's oncogenic functions are likely independent of its classical heterodimerisation partner, MAX. In particular, MYCN controls its own protein interaction network by transcriptionally regulating its binding partners.Our network-based approach identified vulnerable therapeutically targetable nodes that function as critical regulators or effectors of MYCN in neuroblastoma. These were validated by siRNA knockdown screens, functional studies and patient data. We identified β-estradiol and MAPK/ERK as having functional cross-talk with MYCN and being novel targetable vulnerabilities of MYCN-amplified neuroblastoma. These results reveal surprising differences between the functioning of endogenous, overexpressed and amplified MYCN, and rationalise how different MYCN dosages can orchestrate cell fate decisions and cancerous outcomes. Importantly, this work describes a systems-level approach to systematically uncovering network based vulnerabilities and therapeutic targets for multifactorial diseases by integrating disparate omic data types.

  20. Networking.

    ERIC Educational Resources Information Center

    Duvall, Betty

    Networking is an information giving and receiving system, a support system, and a means whereby women can get ahead in careers--either in new jobs or in current positions. Networking information can create many opportunities: women can talk about how other women handle situations and tasks, and previously established contacts can be used in…

  1. Multifunctional periodic cellular metals.

    PubMed

    Wadley, Haydn N G

    2006-01-15

    Periodic cellular metals with honeycomb and corrugated topologies are widely used for the cores of light weight sandwich panel structures. Honeycombs have closed cell pores and are well suited for thermal protection while also providing efficient load support. Corrugated core structures provide less efficient and highly anisotropic load support, but enable cross flow heat exchange opportunities because their pores are continuous in one direction. Recent advances in topology design and fabrication have led to the emergence of lattice truss structures with open cell structures. These three classes of periodic cellular metals can now be fabricated from a wide variety of structural alloys. Many topologies are found to provide adequate stiffness and strength for structural load support when configured as the cores of sandwich panels. Sandwich panels with core relative densities of 2-10% and cell sizes in the millimetre range are being assessed for use as multifunctional structures. The open, three-dimensional interconnected pore networks of lattice truss topologies provide opportunities for simultaneously supporting high stresses while also enabling cross flow heat exchange. These highly compressible structures also provide opportunities for the mitigation of high intensity dynamic loads created by impacts and shock waves in air or water. By filling the voids with polymers and hard ceramics, these structures have also been found to offer significant resistance to penetration by projectiles.

  2. Integration of mobile satellite and cellular systems

    NASA Technical Reports Server (NTRS)

    Drucker, Elliott H.; Estabrook, Polly; Pinck, Deborah; Ekroot, Laura

    1993-01-01

    By integrating the ground based infrastructure component of a mobile satellite system with the infrastructure systems of terrestrial 800 MHz cellular service providers, a seamless network of universal coverage can be established. Users equipped for both cellular and satellite service can take advantage of a number of features made possible by such integration, including seamless handoff and universal roaming. To provide maximum benefit at lowest posible cost, the means by which these systems are integrated must be carefully considered. Mobile satellite hub stations must be configured to efficiently interface with cellular Mobile Telephone Switching Offices (MTSO's), and cost effective mobile units that provide both cellular and satellite capability must be developed.

  3. Functional Motifs in Biochemical Reaction Networks

    PubMed Central

    Tyson, John J.; Novák, Béla

    2013-01-01

    The signal-response characteristics of a living cell are determined by complex networks of interacting genes, proteins, and metabolites. Understanding how cells respond to specific challenges, how these responses are contravened in diseased cells, and how to intervene pharmacologically in the decision-making processes of cells requires an accurate theory of the information-processing capabilities of macromolecular regulatory networks. Adopting an engineer’s approach to control systems, we ask whether realistic cellular control networks can be decomposed into simple regulatory motifs that carry out specific functions in a cell. We show that such functional motifs exist and review the experimental evidence that they control cellular responses as expected. PMID:20055671

  4. Docking studies and network analyses reveal capacity of compounds from Kandelia rheedii to strengthen cellular immunity by interacting with host proteins during tuberculosis infection

    PubMed Central

    Zaman, Aubhishek

    2012-01-01

    Kandelia rheedii (locally known as Guria or Rasunia), widely found and used in Indian subcontinent, is a well-known herbal cure to tuberculosis. However, neither the mechanism nor the active components of the plant extract responsible for mediating this action has yet been confirmed. Here in this study, molecular interactions of three compounds (emodin, fusaric acid and skyrin) from the plant extract with the host protein targets (casein kinase (CSNK), estrogen receptor (ERBB), dopamine β-hydroxylase (DBH) and glucagon receptor (Gcgr)) has been found. These protein targets are known to be responsible for strengthening cellular immunity against Mycobacteria tuberculosis. The specific interactions of these three compounds with the respective protein targets have been discussed here. The insights from study should further help us designing molecular medicines against tuberculosis. PMID:23275699

  5. Cellular mechanics and motility

    NASA Astrophysics Data System (ADS)

    Hénon, Sylvie; Sykes, Cécile

    2015-10-01

    cross-linked or branched networks. It is a highly dynamical system in which filaments are able to elongate or slide one on the other with the contribution of very active cellular proteins like molecular motors. The versatile properties of this cytoskeleton ensure the diversity of mechanical behaviors to explain cell rigidity as well as cell motility.

  6. Protein N-glycosylation in oral cancer: dysregulated cellular networks among DPAGT1, E-cadherin adhesion and canonical Wnt signaling.

    PubMed

    Varelas, Xaralabos; Bouchie, Meghan P; Kukuruzinska, Maria A

    2014-07-01

    N-Linked glycosylation (N-glycosylation) of proteins has long been associated with oncogenesis, but not until recently have the molecular mechanisms underlying this relationship begun to be unraveled. Here, we review studies describing how dysregulation of the N-glycosylation-regulating gene, DPAGT1, drives oral cancer. DPAGT1 encodes the first and rate-limiting enzyme in the assembly of the lipid-linked oligosaccharide precursor in the endoplasmic reticulum and thus mediates N-glycosylation of many cancer-related proteins. DPAGT1 controls N-glycosylation of E-cadherin, the major epithelial cell-cell adhesion receptor and a tumor suppressor, thereby affecting intercellular adhesion and cytoskeletal dynamics. DPAGT1 also regulates and is regulated by Wnt/β-catenin signaling, impacting the balance between proliferation and adhesion in homeostatic tissues. Thus, aberrant induction of DPAGT1 promotes a positive feedback network with Wnt/β-catenin that represses E-cadherin-based adhesion and drives tumorigenic phenotypes. Further, modification of receptor tyrosine kinases (RTKs) with N-glycans is known to control their surface presentation via the galectin lattice, and thus increased DPAGT1 expression likely contributes to abnormal activation of RTKs in oral cancer. Collectively, these studies suggest that dysregulation of the DPAGT1/Wnt/E-cadherin network underlies the etiology and pathogenesis of oral cancer.

  7. Computational models of molecular self-organization in cellular environments.

    PubMed

    LeDuc, Philip; Schwartz, Russell

    2007-01-01

    The cellular environment creates numerous obstacles to efficient chemistry, as molecular components must navigate through a complex, densely crowded, heterogeneous, and constantly changing landscape in order to function at the appropriate times and places. Such obstacles are especially challenging to self-organizing or self-assembling molecular systems, which often need to build large structures in confined environments and typically have high-order kinetics that should make them exquisitely sensitive to concentration gradients, stochastic noise, and other non-ideal reaction conditions. Yet cells nonetheless manage to maintain a finely tuned network of countless molecular assemblies constantly forming and dissolving with a robustness and efficiency generally beyond what human engineers currently can achieve under even carefully controlled conditions. Significant advances in high-throughput biochemistry and genetics have made it possible to identify many of the components and interactions of this network, but its scale and complexity will likely make it impossible to understand at a global, systems level without predictive computational models. It is thus necessary to develop a clear understanding of how the reality of cellular biochemistry differs from the ideal models classically assumed by simulation approaches and how simulation methods can be adapted to accurately reflect biochemistry in the cell, particularly for the self-organizing systems that are most sensitive to these factors. In this review, we present approaches that have been undertaken from the modeling perspective to address various ways in which self-organization in the cell differs from idealized models.

  8. Female sex steroids and glia cells: Impact on multiple sclerosis lesion formation and fine tuning of the local neurodegenerative cellular network.

    PubMed

    Kipp, Markus; Hochstrasser, Tanja; Schmitz, Christoph; Beyer, Cordian

    2016-08-01

    Multiple sclerosis (MS) is a chronic inflammatory and demyelinating disease that shows a female-to-male gender prevalence and alleviation of disease activity during late stage pregnancy. In MS-related animal models, sex steroids ameliorate symptoms and protect from demyelination and neuronal damage. Underlying mechanisms of these protective avenues are continuously discovered, in part by using novel transgenic animal models. In this review article, we highlight the regulation of glia cell function by female sex steroids. We specifically focus on the relevance of glia cells for immune cell recruitment into the central nervous system and show how estrogen and progesterone can modulate these cell-cell communication pathways. Since MS is considered to have a strong neurodegenerative component, principal neuroprotective mechanisms, exerted by sex-steroids will be discussed as well. Activation of steroid receptors might not just act as immunosuppressant but at the same time harmonize brain-intrinsic networks to dampen neurodegeneration and, thus, disease progression in MS.

  9. Network Cosmology

    PubMed Central

    Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S.; Rideout, David; Meyer, David; Boguñá, Marián

    2012-01-01

    Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology. PMID:23162688

  10. Network cosmology.

    PubMed

    Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S; Rideout, David; Meyer, David; Boguñá, Marián

    2012-01-01

    Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology.

  11. The murine Nck SH2/SH3 adaptors are important for the development of mesoderm-derived embryonic structures and for regulating the cellular actin network.

    PubMed

    Bladt, Friedhelm; Aippersbach, Elke; Gelkop, Sigal; Strasser, Geraldine A; Nash, Piers; Tafuri, Anna; Gertler, Frank B; Pawson, Tony

    2003-07-01

    Mammalian Nck1 and Nck2 are closely related adaptor proteins that possess three SH3 domains, followed by an SH2 domain, and are implicated in coupling phosphotyrosine signals to polypeptides that regulate the actin cytoskeleton. However, the in vivo functions of Nck1 and Nck2 have not been defined. We have mutated the murine Nck1 and Nck2 genes and incorporated beta-galactosidase reporters into the mutant loci. In mouse embryos, the two Nck genes have broad and overlapping expression patterns. They are functionally redundant in the sense that mice deficient for either Nck1 or Nck2 are viable, whereas inactivation of both Nck1 and Nck2 results in profound defects in mesoderm-derived notochord and embryonic lethality at embryonic day 9.5. Fibroblast cell lines derived from Nck1(-/-) Nck2(-/-) embryos have defects in cell motility and in the organization of the lamellipodial actin network. These data suggest that the Nck SH2/SH3 adaptors have important functions in the development of mesodermal structures during embryogenesis, potentially linked to a role in cell movement and cytoskeletal organization.

  12. Identification of a Protein Network Interacting with TdRF1, a Wheat RING Ubiquitin Ligase with a Protective Role against Cellular Dehydration1[C][W

    PubMed Central

    Guerra, Davide; Mastrangelo, Anna Maria; Lopez-Torrejon, Gema; Marzin, Stephan; Schweizer, Patrick; Stanca, Antonio Michele; del Pozo, Juan Carlos; Cattivelli, Luigi; Mazzucotelli, Elisabetta

    2012-01-01

    Plants exploit ubiquitination to modulate the proteome with the final aim to ensure environmental adaptation and developmental plasticity. Ubiquitination targets are specifically driven to degradation through the action of E3 ubiquitin ligases. Genetic analyses have indicated wide functions of ubiquitination in plant life; nevertheless, despite the large number of predicted E3s, only a few of them have been characterized so far, and only a few ubiquitination targets are known. In this work, we characterized durum wheat (Triticum durum) RING Finger1 (TdRF1) as a durum wheat nuclear ubiquitin ligase. Moreover, its barley (Hordeum vulgare) homolog was shown to protect cells from dehydration stress. A protein network interacting with TdRF1 has been defined. The transcription factor WHEAT BEL1-TYPE HOMEODOMAIN1 (WBLH1) was degraded in a TdRF1-dependent manner through the 26S proteasome in vivo, the mitogen-activated protein kinase TdWNK5 [for Triticum durum WITH NO LYSINE (K)5] was able to phosphorylate TdRF1 in vitro, and the RING-finger protein WHEAT VIVIPAROUS-INTERACTING PROTEIN2 (WVIP2) was shown to have a strong E3 ligase activity. The genes coding for the TdRF1 interactors were all responsive to cold and/or dehydration stress, and a negative regulative function in dehydration tolerance was observed for the barley homolog of WVIP2. A role in the control of plant development was previously known, or predictable based on homology, for wheat BEL1-type homeodomain1(WBLH1). Thus, TdRF1 E3 ligase might act regulating the response to abiotic stress and remodeling plant development in response to environmental constraints. PMID:22167118

  13. Hierarchical cellular materials

    SciTech Connect

    Gibson, L.J.

    1991-12-31

    In this paper a method for estimating the contributions of both the composite and the cellular microstructures to the overall material properties and the mechanical efficiency of natural cellular solids will be described. The method will be demonstrated by focusing on the Young`s modulus; similar techniques can be used for other material properties. The results suggest efficient microstructures for engineered cellular materials.

  14. Hierarchical cellular materials

    SciTech Connect

    Gibson, L.J.

    1991-01-01

    In this paper a method for estimating the contributions of both the composite and the cellular microstructures to the overall material properties and the mechanical efficiency of natural cellular solids will be described. The method will be demonstrated by focusing on the Young's modulus; similar techniques can be used for other material properties. The results suggest efficient microstructures for engineered cellular materials.

  15. Passive Noise Filtering by Cellular Compartmentalization.

    PubMed

    Stoeger, Thomas; Battich, Nico; Pelkmans, Lucas

    2016-03-10

    Chemical reactions contain an inherent element of randomness, which presents itself as noise that interferes with cellular processes and communication. Here we discuss the ability of the spatial partitioning of molecular systems to filter and, thus, remove noise, while preserving regulated and predictable differences between single living cells. In contrast to active noise filtering by network motifs, cellular compartmentalization is highly effective and easily scales to numerous systems without requiring a substantial usage of cellular energy. We will use passive noise filtering by the eukaryotic cell nucleus as an example of how this increases predictability of transcriptional output, with possible implications for the evolution of complex multicellularity.

  16. Accurate Evaluation of Quantum Integrals

    NASA Technical Reports Server (NTRS)

    Galant, D. C.; Goorvitch, D.; Witteborn, Fred C. (Technical Monitor)

    1995-01-01

    Combining an appropriate finite difference method with Richardson's extrapolation results in a simple, highly accurate numerical method for solving a Schrodinger's equation. Important results are that error estimates are provided, and that one can extrapolate expectation values rather than the wavefunctions to obtain highly accurate expectation values. We discuss the eigenvalues, the error growth in repeated Richardson's extrapolation, and show that the expectation values calculated on a crude mesh can be extrapolated to obtain expectation values of high accuracy.

  17. Peroxisome Metabolism and Cellular Aging

    PubMed Central

    Titorenko, Vladimir I.; Terlecky, Stanley R.

    2010-01-01

    The essential role of peroxisomes in fatty acid oxidation, anaplerotic metabolism, and hydrogen peroxide turnover is well established. Recent findings suggest these and other related biochemical processes governed by the organelle may also play a critical role in regulating cellular aging. The goal of this review is to summarize and integrate into a model, the evidence that peroxisome metabolism actually helps define the replicative and chronological age of a eukaryotic cell. In this model, peroxisomal reactive oxygen species (ROS) are seen as altering organelle biogenesis and function, and eliciting changes in the dynamic communication networks that exist between peroxisomes and other cellular compartments. At low levels, peroxisomal ROS activate an anti-aging program in the cell; at concentrations beyond a specific threshold, a pro-aging course is triggered. PMID:21083858

  18. CellNet: network biology applied to stem cell engineering.

    PubMed

    Cahan, Patrick; Li, Hu; Morris, Samantha A; Lummertz da Rocha, Edroaldo; Daley, George Q; Collins, James J

    2014-08-14

    Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering.

  19. A Cellular Biophysics Textbook

    NASA Astrophysics Data System (ADS)

    Wilder, Alan Joseph

    2011-12-01

    In the past two decades, great advances have been made in understanding of the biophysical mechanisms of the protein machines that carry out the fundamental processes of the cell. It is now known that all major eukaryotic cellular processes require a complicated assemblage of proteins acting via a series of concerted motions. In order to grasp current understanding of cellular mechanisms, the new generation of cell biologists needs to be trained in the general characteristics of these cellular properties and the methods with which to study them. This cellular biophysics textbook, to be used in conjunction with the cellular biophysics course (MCB143) at UC-Davis, provides a great tool in the instruction of the new generation of cellular biologists. It provides a hierarchical view of the cell, from atoms to protein machines and explains in depth the mechanisms of cytoskeletal force generators as an example of these principles.

  20. Fundamental Limits to Cellular Sensing

    NASA Astrophysics Data System (ADS)

    ten Wolde, Pieter Rein; Becker, Nils B.; Ouldridge, Thomas E.; Mugler, Andrew

    2016-03-01

    In recent years experiments have demonstrated that living cells can measure low chemical concentrations with high precision, and much progress has been made in understanding what sets the fundamental limit to the precision of chemical sensing. Chemical concentration measurements start with the binding of ligand molecules to receptor proteins, which is an inherently noisy process, especially at low concentrations. The signaling networks that transmit the information on the ligand concentration from the receptors into the cell have to filter this receptor input noise as much as possible. These networks, however, are also intrinsically stochastic in nature, which means that they will also add noise to the transmitted signal. In this review, we will first discuss how the diffusive transport and binding of ligand to the receptor sets the receptor correlation time, which is the timescale over which fluctuations in the state of the receptor, arising from the stochastic receptor-ligand binding, decay. We then describe how downstream signaling pathways integrate these receptor-state fluctuations, and how the number of receptors, the receptor correlation time, and the effective integration time set by the downstream network, together impose a fundamental limit on the precision of sensing. We then discuss how cells can remove the receptor input noise while simultaneously suppressing the intrinsic noise in the signaling network. We describe why this mechanism of time integration requires three classes (groups) of resources—receptors and their integration time, readout molecules, energy—and how each resource class sets a fundamental sensing limit. We also briefly discuss the scheme of maximum-likelihood estimation, the role of receptor cooperativity, and how cellular copy protocols differ from canonical copy protocols typically considered in the computational literature, explaining why cellular sensing systems can never reach the Landauer limit on the optimal trade

  1. Decisions on the fly in cellular sensory systems

    PubMed Central

    Siggia, Eric D.; Vergassola, Massimo

    2013-01-01

    Cells send and receive signals through pathways that have been defined in great detail biochemically, and it is often presumed that the signals convey only level information. Cell signaling in the presence of noise is extensively studied but only rarely is the speed required to make a decision considered. However, in the immune system, rapidly developing embryos, and cellular response to stress, fast and accurate actions are required. Statistical theory under the rubric of “exploit–explore” quantifies trade-offs between decision speed and accuracy and supplies rigorous performance bounds and algorithms that realize them. We show that common protein phosphorylation networks can implement optimal decision theory algorithms and speculate that the ubiquitous chemical modifications to receptors during signaling actually perform analog computations. We quantify performance trade-offs when the cellular system has incomplete knowledge of the data model. For the problem of sensing the time when the composition of a ligand mixture changes, we find a nonanalytic dependence on relative concentrations and specify the number of parameters needed for near-optimal performance and how to adjust them. The algorithms specify the minimal computation that has to take place on a single receptor before the information is pooled across the cell. PMID:24019464

  2. Three-dimensional morphology and gene expression in the Drosophila blastoderm at cellular resolution I: data acquisition pipeline

    PubMed Central

    Luengo Hendriks, Cris L; Keränen, Soile VE; Fowlkes, Charless C; Simirenko, Lisa; Weber, Gunther H; DePace, Angela H; Henriquez, Clara; Kaszuba, David W; Hamann, Bernd; Eisen, Michael B; Malik, Jitendra; Sudar, Damir; Biggin, Mark D; Knowles, David W

    2006-01-01

    Background To model and thoroughly understand animal transcription networks, it is essential to derive accurate spatial and temporal descriptions of developing gene expression patterns with cellular resolution. Results Here we describe a suite of methods that provide the first quantitative three-dimensional description of gene expression and morphology at cellular resolution in whole embryos. A database containing information derived from 1,282 embryos is released that describes the mRNA expression of 22 genes at multiple time points in the Drosophila blastoderm. We demonstrate that our methods are sufficiently accurate to detect previously undescribed features of morphology and gene expression. The cellular blastoderm is shown to have an intricate morphology of nuclear density patterns and apical/basal displacements that correlate with later well-known morphological features. Pair rule gene expression stripes, generally considered to specify patterning only along the anterior/posterior body axis, are shown to have complex changes in stripe location, stripe curvature, and expression level along the dorsal/ventral axis. Pair rule genes are also found to not always maintain the same register to each other. Conclusion The application of these quantitative methods to other developmental systems will likely reveal many other previously unknown features and provide a more rigorous understanding of developmental regulatory networks. PMID:17184546

  3. Developing a Resilient Green Cellular Network

    DTIC Science & Technology

    2013-12-01

    labor , and planning to deploy that subsequently detracts from conducting immediate response and recovery. This research is intended to propose a path...This mitigating strategy requires substantial time, labor , and planning to deploy that subsequently detracts from conducting immediate response and...29 A. KATRINA .......................................................................................................29 B. DERECHO

  4. Accurate radio positions with the Tidbinbilla interferometer

    NASA Technical Reports Server (NTRS)

    Batty, M. J.; Gulkis, S.; Jauncey, D. L.; Rayner, P. T.

    1979-01-01

    The Tidbinbilla interferometer (Batty et al., 1977) is designed specifically to provide accurate radio position measurements of compact radio sources in the Southern Hemisphere with high sensitivity. The interferometer uses the 26-m and 64-m antennas of the Deep Space Network at Tidbinbilla, near Canberra. The two antennas are separated by 200 m on a north-south baseline. By utilizing the existing antennas and the low-noise traveling-wave masers at 2.29 GHz, it has been possible to produce a high-sensitivity instrument with a minimum of capital expenditure. The north-south baseline ensures that a good range of UV coverage is obtained, so that sources lying in the declination range between about -80 and +30 deg may be observed with nearly orthogonal projected baselines of no less than about 1000 lambda. The instrument also provides high-accuracy flux density measurements for compact radio sources.

  5. Plasmonic Nanostructured Cellular Automata

    NASA Astrophysics Data System (ADS)

    Alkhazraji, Emad; Ghalib, A.; Manzoor, K.; Alsunaidi, M. A.

    2017-03-01

    In this work, we have investigated the scattering plasmonic resonance characteristics of silver nanospheres with a geometrical distribution that is modelled by Cellular Automata using time-domain numerical analysis. Cellular Automata are discrete mathematical structures that model different natural phenomena. Two binary one-dimensional Cellular Automata rules are considered to model the nanostructure, namely rule 30 and rule 33. The analysis produces three-dimensional scattering profiles of the entire plasmonic nanostructure. For the Cellular Automaton rule 33, the introduction of more Cellular Automata generations resulted only in slight red and blue shifts in the plasmonic modes with respect to the first generation. On the other hand, while rule 30 introduced significant red shifts in the resonance peaks at early generations, at later generations however, a peculiar effect is witnessed in the scattering profile as new peaks emerge as a feature of the overall Cellular Automata structure rather than the sum of the smaller parts that compose it. We strongly believe that these features that emerge as a result adopting the different 256 Cellular Automata rules as configuration models of nanostructures in different applications and systems might possess a great potential in enhancing their capability, sensitivity, efficiency, and power utilization.

  6. Cellular Reflectarray Antenna

    NASA Technical Reports Server (NTRS)

    Romanofsky, Robert R.

    2010-01-01

    The cellular reflectarray antenna is intended to replace conventional parabolic reflectors that must be physically aligned with a particular satellite in geostationary orbit. These arrays are designed for specified geographical locations, defined by latitude and longitude, each called a "cell." A particular cell occupies nominally 1,500 square miles (3,885 sq. km), but this varies according to latitude and longitude. The cellular reflectarray antenna designed for a particular cell is simply positioned to align with magnetic North, and the antenna surface is level (parallel to the ground). A given cellular reflectarray antenna will not operate in any other cell.

  7. Cellular aging and cancer

    PubMed Central

    Hornsby, Peter J.

    2010-01-01

    Aging is manifest in a variety of changes over time, including changes at the cellular level. Cellular aging acts primarily as a tumor suppressor mechanism, but also may enhance cancer development under certain circumstances. One important process of cellular aging is oncogene-induced senescence, which acts as an important anti-cancer mechanism. Cellular senescence resulting from damage caused by activated oncogenes prevents the growth or potentially neoplastic cells. Moreover, cells that have entered senescence appear to be targets for elimination by the innnate immune system. In another aspect of cellular aging, the absence of telomerase activity in normal tissues results in such cells lacking a telomere maintenance mechanism. One consequence is that in aging there is an increase in cells with shortened telomeres. In the presence of active oncogenes that cause expansion of a neoplastic clone, shortening of telomeres leading to telomere dysfunction prevents the indefinite expansion of the clone because the cells enter crisis. Crisis results from fusions and other defects caused by dysfunctional telomeres and is a terminal state of the neoplastic clone. In this way the absence of telomerase in human cells, while one cause of cellular aging, also acts as an anti-cancer mechanism. PMID:20705476

  8. Transient inter-cellular polymeric linker.

    PubMed

    Ong, Siew-Min; He, Lijuan; Thuy Linh, Nguyen Thi; Tee, Yee-Han; Arooz, Talha; Tang, Guping; Tan, Choon-Hong; Yu, Hanry

    2007-09-01

    Three-dimensional (3D) tissue-engineered constructs with bio-mimicry cell-cell and cell-matrix interactions are useful in regenerative medicine. In cell-dense and matrix-poor tissues of the internal organs, cells support one another via cell-cell interactions, supplemented by small amount of the extra-cellular matrices (ECM) secreted by the cells. Here we connect HepG2 cells directly but transiently with inter-cellular polymeric linker to facilitate cell-cell interaction and aggregation. The linker consists of a non-toxic low molecular-weight polyethyleneimine (PEI) backbone conjugated with multiple hydrazide groups that can aggregate cells within 30 min by reacting with the aldehyde handles on the chemically modified cell-surface glycoproteins. The cells in the cellular aggregates proliferated; and maintained the cortical actin distribution of the 3D cell morphology while non-aggregated cells died over 7 days of suspension culture. The aggregates lost distinguishable cell-cell boundaries within 3 days; and the ECM fibers became visible around cells from day 3 onwards while the inter-cellular polymeric linker disappeared from the cell surfaces over time. The transient inter-cellular polymeric linker can be useful for forming 3D cellular and tissue constructs without bulk biomaterials or extensive network of engineered ECM for various applications.

  9. On numerically accurate finite element

    NASA Technical Reports Server (NTRS)

    Nagtegaal, J. C.; Parks, D. M.; Rice, J. R.

    1974-01-01

    A general criterion for testing a mesh with topologically similar repeat units is given, and the analysis shows that only a few conventional element types and arrangements are, or can be made suitable for computations in the fully plastic range. Further, a new variational principle, which can easily and simply be incorporated into an existing finite element program, is presented. This allows accurate computations to be made even for element designs that would not normally be suitable. Numerical results are given for three plane strain problems, namely pure bending of a beam, a thick-walled tube under pressure, and a deep double edge cracked tensile specimen. The effects of various element designs and of the new variational procedure are illustrated. Elastic-plastic computation at finite strain are discussed.

  10. ACCURATE CHEMICAL MASTER EQUATION SOLUTION USING MULTI-FINITE BUFFERS

    PubMed Central

    Cao, Youfang; Terebus, Anna; Liang, Jie

    2016-01-01

    The discrete chemical master equation (dCME) provides a fundamental framework for studying stochasticity in mesoscopic networks. Because of the multi-scale nature of many networks where reaction rates have large disparity, directly solving dCMEs is intractable due to the exploding size of the state space. It is important to truncate the state space effectively with quantified errors, so accurate solutions can be computed. It is also important to know if all major probabilistic peaks have been computed. Here we introduce the Accurate CME (ACME) algorithm for obtaining direct solutions to dCMEs. With multi-finite buffers for reducing the state space by O(n!), exact steady-state and time-evolving network probability landscapes can be computed. We further describe a theoretical framework of aggregating microstates into a smaller number of macrostates by decomposing a network into independent aggregated birth and death processes, and give an a priori method for rapidly determining steady-state truncation errors. The maximal sizes of the finite buffers for a given error tolerance can also be pre-computed without costly trial solutions of dCMEs. We show exactly computed probability landscapes of three multi-scale networks, namely, a 6-node toggle switch, 11-node phage-lambda epigenetic circuit, and 16-node MAPK cascade network, the latter two with no known solutions. We also show how probabilities of rare events can be computed from first-passage times, another class of unsolved problems challenging for simulation-based techniques due to large separations in time scales. Overall, the ACME method enables accurate and efficient solutions of the dCME for a large class of networks. PMID:27761104

  11. ACCURATE CHEMICAL MASTER EQUATION SOLUTION USING MULTI-FINITE BUFFERS.

    PubMed

    Cao, Youfang; Terebus, Anna; Liang, Jie

    2016-01-01

    The discrete chemical master equation (dCME) provides a fundamental framework for studying stochasticity in mesoscopic networks. Because of the multi-scale nature of many networks where reaction rates have large disparity, directly solving dCMEs is intractable due to the exploding size of the state space. It is important to truncate the state space effectively with quantified errors, so accurate solutions can be computed. It is also important to know if all major probabilistic peaks have been computed. Here we introduce the Accurate CME (ACME) algorithm for obtaining direct solutions to dCMEs. With multi-finite buffers for reducing the state space by O(n!), exact steady-state and time-evolving network probability landscapes can be computed. We further describe a theoretical framework of aggregating microstates into a smaller number of macrostates by decomposing a network into independent aggregated birth and death processes, and give an a priori method for rapidly determining steady-state truncation errors. The maximal sizes of the finite buffers for a given error tolerance can also be pre-computed without costly trial solutions of dCMEs. We show exactly computed probability landscapes of three multi-scale networks, namely, a 6-node toggle switch, 11-node phage-lambda epigenetic circuit, and 16-node MAPK cascade network, the latter two with no known solutions. We also show how probabilities of rare events can be computed from first-passage times, another class of unsolved problems challenging for simulation-based techniques due to large separations in time scales. Overall, the ACME method enables accurate and efficient solutions of the dCME for a large class of networks.

  12. Triangles bridge the scales: Quantifying cellular contributions to tissue deformation

    NASA Astrophysics Data System (ADS)

    Merkel, Matthias; Etournay, Raphaël; Popović, Marko; Salbreux, Guillaume; Eaton, Suzanne; Jülicher, Frank

    2017-03-01

    In this article, we propose a general framework to study the dynamics and topology of cellular networks that capture the geometry of cell packings in two-dimensional tissues. Such epithelia undergo large-scale deformation during morphogenesis of a multicellular organism. Large-scale deformations emerge from many individual cellular events such as cell shape changes, cell rearrangements, cell divisions, and cell extrusions. Using a triangle-based representation of cellular network geometry, we obtain an exact decomposition of large-scale material deformation. Interestingly, our approach reveals contributions of correlations between cellular rotations and elongation as well as cellular growth and elongation to tissue deformation. Using this triangle method, we discuss tissue remodeling in the developing pupal wing of the fly Drosophila melanogaster.

  13. Fatigue of cellular materials

    SciTech Connect

    Huang, J.S.; Lin, J.Y.

    1996-01-01

    The fatigue of cellular materials is analyzed using dimensional arguments. When the first unbroken cell wall ahead of the macrocrack tip fails after some cycles of loading, the macrocrack advances one cell diameter, giving the macrocrack growth rate of cellular materials. Paris law for microcrack propagation, Basquin law for high cycle fatigue and Coffin-Manson law for low cycle fatigue are employed in calculating the number of cycles to failure of the first unbroken cell wall ahead of the macrocrack tip. It is found that fatigue of cellular materials depends on cyclic stress intensity range, cell size, relative density and the fatigue parameters of the solid from which they are made. Theoretical modelling of fatigue of foams is compared to data in polymer foams; agreement is good.

  14. Epigenetics and Cellular Metabolism

    PubMed Central

    Xu, Wenyi; Wang, Fengzhong; Yu, Zhongsheng; Xin, Fengjiao

    2016-01-01

    Living eukaryotic systems evolve delicate cellular mechanisms for responding to various environmental signals. Among them, epigenetic machinery (DNA methylation, histone modifications, microRNAs, etc.) is the hub in transducing external stimuli into transcriptional response. Emerging evidence reveals the concept that epigenetic signatures are essential for the proper maintenance of cellular metabolism. On the other hand, the metabolite, a main environmental input, can also influence the processing of epigenetic memory. Here, we summarize the recent research progress in the epigenetic regulation of cellular metabolism and discuss how the dysfunction of epigenetic machineries influences the development of metabolic disorders such as diabetes and obesity; then, we focus on discussing the notion that manipulating metabolites, the fuel of cell metabolism, can function as a strategy for interfering epigenetic machinery and its related disease progression as well. PMID:27695375

  15. Origins of cellular geometry

    PubMed Central

    2011-01-01

    Cells are highly complex and orderly machines, with defined shapes and a startling variety of internal organizations. Complex geometry is a feature of both free-living unicellular organisms and cells inside multicellular animals. Where does the geometry of a cell come from? Many of the same questions that arise in developmental biology can also be asked of cells, but in most cases we do not know the answers. How much of cellular organization is dictated by global cell polarity cues as opposed to local interactions between cellular components? Does cellular structure persist across cell generations? What is the relationship between cell geometry and tissue organization? What ensures that intracellular structures are scaled to the overall size of the cell? Cell biology is only now beginning to come to grips with these questions. PMID:21880160

  16. Approaches to Biosimulation of Cellular Processes

    PubMed Central

    Westerhoff, H. V.

    2006-01-01

    Modelling and simulation are at the heart of the rapidly developing field of systems biology. This paper reviews various types of models, simulation methods, and theoretical approaches that are presently being used in the quantitative description of cellular processes. We first describe how molecular interaction networks can be represented by means of stoichiometric, topological and kinetic models. We briefly discuss the formulation of kinetic models using mesoscopic (stochastic) or macroscopic (continuous) approaches, and we go on to describe how detailed models of molecular interaction networks (silicon cells) can be constructed on the basis of experimentally determined kinetic parameters for cellular processes. We show how theory can help in analyzing models by applying control analysis to a recently published silicon cell model. Finally, we review some of the theoretical approaches available to analyse kinetic models and experimental data, respectively. PMID:19669467

  17. Accurate ab Initio Spin Densities.

    PubMed

    Boguslawski, Katharina; Marti, Konrad H; Legeza, Ors; Reiher, Markus

    2012-06-12

    We present an approach for the calculation of spin density distributions for molecules that require very large active spaces for a qualitatively correct description of their electronic structure. Our approach is based on the density-matrix renormalization group (DMRG) algorithm to calculate the spin density matrix elements as a basic quantity for the spatially resolved spin density distribution. The spin density matrix elements are directly determined from the second-quantized elementary operators optimized by the DMRG algorithm. As an analytic convergence criterion for the spin density distribution, we employ our recently developed sampling-reconstruction scheme [J. Chem. Phys.2011, 134, 224101] to build an accurate complete-active-space configuration-interaction (CASCI) wave function from the optimized matrix product states. The spin density matrix elements can then also be determined as an expectation value employing the reconstructed wave function expansion. Furthermore, the explicit reconstruction of a CASCI-type wave function provides insight into chemically interesting features of the molecule under study such as the distribution of α and β electrons in terms of Slater determinants, CI coefficients, and natural orbitals. The methodology is applied to an iron nitrosyl complex which we have identified as a challenging system for standard approaches [J. Chem. Theory Comput.2011, 7, 2740].

  18. Cytoskeletal Mechanisms for Breaking Cellular Symmetry

    PubMed Central

    Mullins, R. Dyche

    2010-01-01

    Cytoskeletal systems are networks of polymers found in all eukaryotic and many prokaryotic cells. Their purpose is to transmit and integrate information across cellular dimensions and help turn a disorderly mob of macromolecules into a spatially organized, living cell. Information, in this context, includes physical and chemical properties relevant to cellular physiology, including: the number and activity of macromolecules, cell shape, and mechanical force. Most animal cells are 10–50 microns in diameter, whereas the macromolecules that comprise them are 10,000-fold smaller (2–20 nm). To establish long-range order over cellular length scales, individual molecules must, therefore, self-assemble into larger polymers, with lengths (0.1–20 m) comparable to the size of a cell. These polymers must then be cross-linked into organized networks that fill the cytoplasm. Such cell-spanning polymer networks enable different parts of the cytoplasm to communicate directly with each other, either by transmitting forces or by carrying cargo from one spot to another. PMID:20182610

  19. Accurate Energy Transaction Allocation using Path Integration and Interpolation

    NASA Astrophysics Data System (ADS)

    Bhide, Mandar Mohan

    This thesis investigates many of the popular cost allocation methods which are based on actual usage of the transmission network. The Energy Transaction Allocation (ETA) method originally proposed by A.Fradi, S.Brigonne and B.Wollenberg which gives unique advantage of accurately allocating the transmission network usage is discussed subsequently. Modified calculation of ETA based on simple interpolation technique is then proposed. The proposed methodology not only increase the accuracy of calculation but also decreases number of calculations to less than half of the number of calculations required in original ETAs.

  20. The New Cellular Immunology

    ERIC Educational Resources Information Center

    Claman, Henry N.

    1973-01-01

    Discusses the nature of the immune response and traces many of the discoveries that have led to the present state of knowledge in immunology. The new cellular immunology is directing its efforts toward improving health by proper manipulation of the immune mechanisms of the body. (JR)

  1. Cellular genetic therapy.

    PubMed

    Del Vecchio, F; Filareto, A; Spitalieri, P; Sangiuolo, F; Novelli, G

    2005-01-01

    Cellular genetic therapy is the ultimate frontier for those pathologies that are consequent to a specific nonfunctional cellular type. A viable cure for there kinds of diseases is the replacement of sick cells with healthy ones, which can be obtained from the same patient or a different donor. In fact, structures can be corrected and strengthened with the introduction of undifferentiated cells within specific target tissues, where they will specialize into the desired cellular types. Furthermore, consequent to the recent results obtained with the transdifferentiation experiments, a process that allows the in vitro differentiation of embryonic and adult stem cells, it has also became clear that many advantages may be obtained from the use of stem cells to produce drugs, vaccines, and therapeutic molecules. Since stem cells can sustain lineage potentials, the capacity for differentiation, and better tolerance for the introduction of exogenous genes, they are also considered as feasible therapeutic vehicles for gene therapy. In fact, it is strongly believed that the combination of cellular genetic and gene therapy approaches will definitely allow the development of new therapeutic strategies as well as the production of totipotent cell lines to be used as experimental models for the cure of genetic disorders.

  2. Genetic Dominance & Cellular Processes

    ERIC Educational Resources Information Center

    Seager, Robert D.

    2014-01-01

    In learning genetics, many students misunderstand and misinterpret what "dominance" means. Understanding is easier if students realize that dominance is not a mechanism, but rather a consequence of underlying cellular processes. For example, metabolic pathways are often little affected by changes in enzyme concentration. This means that…

  3. Fast and accurate automated cell boundary determination for fluorescence microscopy

    NASA Astrophysics Data System (ADS)

    Arce, Stephen Hugo; Wu, Pei-Hsun; Tseng, Yiider

    2013-07-01

    Detailed measurement of cell phenotype information from digital fluorescence images has the potential to greatly advance biomedicine in various disciplines such as patient diagnostics or drug screening. Yet, the complexity of cell conformations presents a major barrier preventing effective determination of cell boundaries, and introduces measurement error that propagates throughout subsequent assessment of cellular parameters and statistical analysis. State-of-the-art image segmentation techniques that require user-interaction, prolonged computation time and specialized training cannot adequately provide the support for high content platforms, which often sacrifice resolution to foster the speedy collection of massive amounts of cellular data. This work introduces a strategy that allows us to rapidly obtain accurate cell boundaries from digital fluorescent images in an automated format. Hence, this new method has broad applicability to promote biotechnology.

  4. Accurate Insertion Loss Measurements of the Juno Patch Array Antennas

    NASA Technical Reports Server (NTRS)

    Chamberlain, Neil; Chen, Jacqueline; Hodges, Richard; Demas, John

    2010-01-01

    This paper describes two independent methods for estimating the insertion loss of patch array antennas that were developed for the Juno Microwave Radiometer instrument. One method is based principally on pattern measurements while the other method is based solely on network analyzer measurements. The methods are accurate to within 0.1 dB for the measured antennas and show good agreement (to within 0.1dB) of separate radiometric measurements.

  5. Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli

    PubMed Central

    Kim, Minseung; Rai, Navneet; Zorraquino, Violeta; Tagkopoulos, Ilias

    2016-01-01

    A significant obstacle in training predictive cell models is the lack of integrated data sources. We develop semi-supervised normalization pipelines and perform experimental characterization (growth, transcriptional, proteome) to create Ecomics, a consistent, quality-controlled multi-omics compendium for Escherichia coli with cohesive meta-data information. We then use this resource to train a multi-scale model that integrates four omics layers to predict genome-wide concentrations and growth dynamics. The genetic and environmental ontology reconstructed from the omics data is substantially different and complementary to the genetic and chemical ontologies. The integration of different layers confers an incremental increase in the prediction performance, as does the information about the known gene regulatory and protein-protein interactions. The predictive performance of the model ranges from 0.54 to 0.87 for the various omics layers, which far exceeds various baselines. This work provides an integrative framework of omics-driven predictive modelling that is broadly applicable to guide biological discovery. PMID:27713404

  6. Mapping yeast transcriptional networks.

    PubMed

    Hughes, Timothy R; de Boer, Carl G

    2013-09-01

    The term "transcriptional network" refers to the mechanism(s) that underlies coordinated expression of genes, typically involving transcription factors (TFs) binding to the promoters of multiple genes, and individual genes controlled by multiple TFs. A multitude of studies in the last two decades have aimed to map and characterize transcriptional networks in the yeast Saccharomyces cerevisiae. We review the methodologies and accomplishments of these studies, as well as challenges we now face. For most yeast TFs, data have been collected on their sequence preferences, in vivo promoter occupancy, and gene expression profiles in deletion mutants. These systematic studies have led to the identification of new regulators of numerous cellular functions and shed light on the overall organization of yeast gene regulation. However, many yeast TFs appear to be inactive under standard laboratory growth conditions, and many of the available data were collected using techniques that have since been improved. Perhaps as a consequence, comprehensive and accurate mapping among TF sequence preferences, promoter binding, and gene expression remains an open challenge. We propose that the time is ripe for renewed systematic efforts toward a complete mapping of yeast transcriptional regulatory mechanisms.

  7. Reverse engineering and analysis of large genome-scale gene networks.

    PubMed

    Aluru, Maneesha; Zola, Jaroslaw; Nettleton, Dan; Aluru, Srinivas

    2013-01-07

    Reverse engineering the whole-genome networks of complex multicellular organisms continues to remain a challenge. While simpler models easily scale to large number of genes and gene expression datasets, more accurate models are compute intensive limiting their scale of applicability. To enable fast and accurate reconstruction of large networks, we developed Tool for Inferring Network of Genes (TINGe), a parallel mutual information (MI)-based program. The novel features of our approach include: (i) B-spline-based formulation for linear-time computation of MI, (ii) a novel algorithm for direct permutation testing and (iii) development of parallel algorithms to reduce run-time and facilitate construction of large networks. We assess the quality of our method by comparison with ARACNe (Algorithm for the Reconstruction of Accurate Cellular Networks) and GeneNet and demonstrate its unique capability by reverse engineering the whole-genome network of Arabidopsis thaliana from 3137 Affymetrix ATH1 GeneChips in just 9 min on a 1024-core cluster. We further report on the development of a new software Gene Network Analyzer (GeNA) for extracting context-specific subnetworks from a given set of seed genes. Using TINGe and GeNA, we performed analysis of 241 Arabidopsis AraCyc 8.0 pathways, and the results are made available through the web.

  8. 38 CFR 4.46 - Accurate measurement.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 38 Pensions, Bonuses, and Veterans' Relief 1 2013-07-01 2013-07-01 false Accurate measurement. 4... RATING DISABILITIES Disability Ratings The Musculoskeletal System § 4.46 Accurate measurement. Accurate measurement of the length of stumps, excursion of joints, dimensions and location of scars with respect...

  9. 38 CFR 4.46 - Accurate measurement.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 38 Pensions, Bonuses, and Veterans' Relief 1 2012-07-01 2012-07-01 false Accurate measurement. 4... RATING DISABILITIES Disability Ratings The Musculoskeletal System § 4.46 Accurate measurement. Accurate measurement of the length of stumps, excursion of joints, dimensions and location of scars with respect...

  10. 38 CFR 4.46 - Accurate measurement.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 38 Pensions, Bonuses, and Veterans' Relief 1 2010-07-01 2010-07-01 false Accurate measurement. 4... RATING DISABILITIES Disability Ratings The Musculoskeletal System § 4.46 Accurate measurement. Accurate measurement of the length of stumps, excursion of joints, dimensions and location of scars with respect...

  11. 38 CFR 4.46 - Accurate measurement.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 38 Pensions, Bonuses, and Veterans' Relief 1 2014-07-01 2014-07-01 false Accurate measurement. 4... RATING DISABILITIES Disability Ratings The Musculoskeletal System § 4.46 Accurate measurement. Accurate measurement of the length of stumps, excursion of joints, dimensions and location of scars with respect...

  12. 38 CFR 4.46 - Accurate measurement.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 38 Pensions, Bonuses, and Veterans' Relief 1 2011-07-01 2011-07-01 false Accurate measurement. 4... RATING DISABILITIES Disability Ratings The Musculoskeletal System § 4.46 Accurate measurement. Accurate measurement of the length of stumps, excursion of joints, dimensions and location of scars with respect...

  13. Predictability in cellular automata.

    PubMed

    Agapie, Alexandru; Andreica, Anca; Chira, Camelia; Giuclea, Marius

    2014-01-01

    Modelled as finite homogeneous Markov chains, probabilistic cellular automata with local transition probabilities in (0, 1) always posses a stationary distribution. This result alone is not very helpful when it comes to predicting the final configuration; one needs also a formula connecting the probabilities in the stationary distribution to some intrinsic feature of the lattice configuration. Previous results on the asynchronous cellular automata have showed that such feature really exists. It is the number of zero-one borders within the automaton's binary configuration. An exponential formula in the number of zero-one borders has been proved for the 1-D, 2-D and 3-D asynchronous automata with neighborhood three, five and seven, respectively. We perform computer experiments on a synchronous cellular automaton to check whether the empirical distribution obeys also that theoretical formula. The numerical results indicate a perfect fit for neighbourhood three and five, which opens the way for a rigorous proof of the formula in this new, synchronous case.

  14. Probabilistic cellular automata.

    PubMed

    Agapie, Alexandru; Andreica, Anca; Giuclea, Marius

    2014-09-01

    Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case-connecting the probability of a configuration in the stationary distribution to its number of zero-one borders-the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata.

  15. Cellular and circuit properties supporting different sensory coding strategies in electric fish and other systems.

    PubMed

    Marsat, Gary; Longtin, André; Maler, Leonard

    2012-08-01

    Neural codes often seem tailored to the type of information they must carry. Here we contrast the encoding strategies for two different communication signals in electric fish and describe the underlying cellular and network properties that implement them. We compare an aggressive signal that needs to be quickly detected, to a courtship signal whose quality needs to be evaluated. The aggressive signal is encoded by synchronized bursts and a predictive feedback input is crucial in separating background noise from the communication signal. The courtship signal is accurately encoded through a heterogenous population response allowing the discrimination of signal differences. Most importantly we show that the same strategies are used in other systems arguing that they evolved similar solutions because they faced similar tasks.

  16. A synthetic biology approach to understanding cellular information processing

    PubMed Central

    Riccione, Katherine A; Smith, Robert P; Lee, Anna J; You, Lingchong

    2012-01-01

    The survival of cells and organisms requires proper responses to environmental signals. These responses are governed by cellular networks, which serve to process diverse environmental cues. Biological networks often contain recurring network topologies called ‘motifs’. It has been recognized that the study of such motifs allows one to predict the response of a biological network, and thus cellular behavior. However, studying a single motif in complete isolation of all other network motifs in a natural setting is difficult. Synthetic biology has emerged as a powerful approach to understanding the dynamic properties of network motifs. In addition to testing existing theoretical predictions, construction and analysis of synthetic gene circuits has led to the discovery of novel motif dynamics such as how the combination of simple motifs can lead to autonomous dynamics or how noise in transcription and translation can affect the dynamics of a motif. Here, we review developments in synthetic biology as they pertain to increasing our understanding of cellular information processing. We highlight several types of dynamic behaviors that diverse motifs can generate, including the control of input/output responses, the generation of autonomous spatial and temporal dynamics, as well as the influence of noise in motif dynamics and cellular behavior. PMID:23411668

  17. Inter-Cellular Forces Orchestrate Contact Inhibition of Locomotion

    PubMed Central

    Davis, John R.; Luchici, Andrei; Mosis, Fuad; Thackery, James; Salazar, Jesus A.; Mao, Yanlan; Dunn, Graham A.; Betz, Timo; Miodownik, Mark; Stramer, Brian M.

    2015-01-01

    Summary Contact inhibition of locomotion (CIL) is a multifaceted process that causes many cell types to repel each other upon collision. During development, this seemingly uncoordinated reaction is a critical driver of cellular dispersion within embryonic tissues. Here, we show that Drosophila hemocytes require a precisely orchestrated CIL response for their developmental dispersal. Hemocyte collision and subsequent repulsion involves a stereotyped sequence of kinematic stages that are modulated by global changes in cytoskeletal dynamics. Tracking actin retrograde flow within hemocytes in vivo reveals synchronous reorganization of colliding actin networks through engagement of an inter-cellular adhesion. This inter-cellular actin-clutch leads to a subsequent build-up in lamellar tension, triggering the development of a transient stress fiber, which orchestrates cellular repulsion. Our findings reveal that the physical coupling of the flowing actin networks during CIL acts as a mechanotransducer, allowing cells to haptically sense each other and coordinate their behaviors. PMID:25799385

  18. [Cellular and molecular mechanisms of memory].

    PubMed

    Laroche, Serge

    2010-01-01

    A defining characteristic of the brain is its remarkable capacity to undergo activity-dependent functional and morphological remodelling via mechanisms of plasticity that form the basis of our capacity to encode and retain memories. Today, it is generally accepted that one key neurobiological mechanism underlying the formation of memories reside in activity-driven modifications of synaptic strength and structural remodelling of neural networks activated during learning. The discovery and detailed report of the phenomenon generally known as long-term potentiation, a long-lasting activity-dependent form of synaptic strengthening, opened a new chapter in the study of the neurobiological substrate of memory in the vertebrate brain, and this form of synaptic plasticity has now become the dominant model in the search for the cellular bases of learning and memory. To date, the key events in the cellular and molecular mechanisms underlying synaptic plasticity and memory formation are starting to be identified. They require the activation of specific receptors and of several molecular cascades to convert extracellular signals into persistent functional changes in neuronal connectivity. Accumulating evidence suggests that the rapid activation of neuronal gene programs is a key mechanism underlying the enduring modification of neural networks required for the laying down of memory. The recent developments in the search for the cellular and molecular mechanisms of memory storage are reviewed.

  19. [Cellular and molecular mechanisms of memory].

    PubMed

    Laroche, S

    2001-01-01

    There has been nearly a century of interest in the idea that information is encoded in the brain as specific spatio-temporal patterns of activity in distributed networks and stored as changes in the efficacy of synaptic connections on neurons that are activated during learning. The discovery and detailed report of the phenomenon generally known as long-term potentiation opened a new chapter in the study of synaptic plasticity in the vertebrate brain, and this form of synaptic plasticity has now become the dominant model in the search for the cellular bases of learning and memory. To date, the key events in the cellular and molecular mechanisms underlying synaptic plasticity are starting to be identified. They require the activation of specific receptors and of several molecular cascades to convert extracellular signals into persistent functional changes in neuronal connectivity. Accumulating evidence suggests that the rapid activation of the genetic machinery is a key mechanism underlying the enduring modification of neural networks required for the laying down of memory. The recent developments in the search for the cellular and molecular mechanisms of memory storage are reviewed.

  20. Capacity Limit, Link Scheduling and Power Control in Wireless Networks

    ERIC Educational Resources Information Center

    Zhou, Shan

    2013-01-01

    The rapid advancement of wireless technology has instigated the broad deployment of wireless networks. Different types of networks have been developed, including wireless sensor networks, mobile ad hoc networks, wireless local area networks, and cellular networks. These networks have different structures and applications, and require different…

  1. Formin’ cellular structures

    PubMed Central

    Bogdan, Sven; Schultz, Jörg; Grosshans, Jörg

    2014-01-01

    Members of the Diaphanous (Dia) protein family are key regulators of fundamental actin driven cellular processes, which are conserved from yeast to humans. Researchers have uncovered diverse physiological roles in cell morphology, cell motility, cell polarity, and cell division, which are involved in shaping cells into tissues and organs. The identification of numerous binding partners led to substantial progress in our understanding of the differential functions of Dia proteins. Genetic approaches and new microscopy techniques allow important new insights into their localization, activity, and molecular principles of regulation. PMID:24719676

  2. Oral Cellular Neurothekeoma

    PubMed Central

    Emami, Nader; Zawawi, Faisal; Ywakim, Rania; Daniel, Sam J.

    2013-01-01

    Cellular neurothekeoma is known as a cutaneous tumor with uncertain histogenesis. Very little involvement of mucosal membrane has been reported in the literature so far. This is a case report of an intraoral lesion in a 15-years-old girl. Histopathologic evaluation showed a tumor-consists of spindle to epitheloid cells forming micronodules in a concentric whorled shape pattern. Tumor cells were positive for CD63, vimentin, and NKI-C3. Total excision was performed and no recurrence happened after 16-month followup. PMID:23691398

  3. Cellular and molecular connections between sleep and synaptic plasticity.

    PubMed

    Benington, Joel H; Frank, Marcos G

    2003-02-01

    The hypothesis that sleep promotes learning and memory has long been a subject of active investigation. This hypothesis implies that sleep must facilitate synaptic plasticity in some way, and recent studies have provided evidence for such a function. Our knowledge of both the cellular neurophysiology of sleep states and of the cellular and molecular mechanisms underlying synaptic plasticity has expanded considerably in recent years. In this article, we review findings in these areas and discuss possible mechanisms whereby the neurophysiological processes characteristic of sleep states may serve to facilitate synaptic plasticity. We address this issue first on the cellular level, considering how activation of T-type Ca(2+) channels in nonREM sleep may promote either long-term depression or long-term potentiation, as well as how cellular events of REM sleep may influence these processes. We then consider how synchronization of neuronal activity in thalamocortical and hippocampal-neocortical networks in nonREM sleep and REM sleep could promote differential strengthening of synapses according to the degree to which activity in one neuron is synchronized with activity in other neurons in the network. Rather than advocating one specific cellular hypothesis, we have intentionally taken a broad approach, describing a range of possible mechanisms whereby sleep may facilitate synaptic plasticity on the cellular and/or network levels. We have also provided a general review of evidence for and against the hypothesis that sleep does indeed facilitate learning, memory, and synaptic plasticity.

  4. Information transduction capacity of noisy biochemical signaling networks

    PubMed Central

    Cheong, Raymond; Rhee, Alex; Wang, Chiaochun Joanne; Nemenman, Ilya; Levchenko, Andre

    2014-01-01

    Molecular noise restricts the ability of an individual cell to resolve input signals of different strengths and gather information about the external environment. Transmitting information through complex signaling networks with redundancies can overcome this limitation. We developed an integrative theoretical and experimental framework, based on the formalism of information theory, to quantitatively predict and measure the amount of information transduced by molecular and cellular networks. Analyzing tumor necrosis factor (TNF) signaling revealed that individual TNF signaling pathways transduce information sufficient for accurate binary decisions, and an upstream bottleneck limits the information gained via multiple pathways together. Negative feedback to this bottleneck could both alleviate and enhance its limiting effect, despite decreasing noise. Bottlenecks likewise constrain information attained by networks signaling through multiple genes or cells. PMID:21921160

  5. Cellular Array Processing Simulation

    NASA Astrophysics Data System (ADS)

    Lee, Harry C.; Preston, Earl W.

    1981-11-01

    The Cellular Array Processing Simulation (CAPS) system is a high-level image language that runs on a multiprocessor configuration. CAPS is interpretively decoded on a conventional minicomputer with all image operation instructions executed on an array processor. The synergistic environment that exists between the minicomputer and the array processor gives CAPS its high-speed throughput, while maintaining a convenient conversational user language. CAPS was designed to be both modular and table driven so that it can be easily maintained and modified. CAPS uses the image convolution operator as one of its primitives and performs this cellular operation by decomposing it into parallel image steps that are scheduled to be executed on the array processor. Among its features is the ability to observe the imagery in real time as a user's algorithm is executed. This feature reduces the need for image storage space, since it is feasible to retain only original images and produce resultant images when needed. CAPS also contains a language processor that permits users to develop re-entrant image processing subroutines or algorithms.

  6. Interconnectivity of human cellular metabolism and disease prevalence

    NASA Astrophysics Data System (ADS)

    Lee, Deok-Sun

    2010-12-01

    Fluctuations of metabolic reaction fluxes may cause abnormal concentrations of toxic or essential metabolites, possibly leading to metabolic diseases. The mutual binding of enzymatic proteins and ones involving common metabolites enforces distinct coupled reactions, by which local perturbations may spread through the cellular network. Such network effects at the molecular interaction level in human cellular metabolism can reappear in the patterns of disease occurrence. Here we construct the enzyme-reaction network and the metabolite-reaction network, capturing the flux coupling of metabolic reactions caused by the interacting enzymes and the shared metabolites, respectively. Diseases potentially caused by the failure of individual metabolic reactions can be identified by using the known disease-gene association, which allows us to derive the probability of an inactivated reaction causing diseases from the disease records at the population level. We find that the greater the number of proteins that catalyze a reaction, the higher the mean prevalence of its associated diseases. Moreover, the number of connected reactions and the mean size of the avalanches in the networks constructed are also shown to be positively correlated with the disease prevalence. These findings illuminate the impact of the cellular network topology on disease development, suggesting that the global organization of the molecular interaction network should be understood to assist in disease diagnosis, treatment, and drug discovery.

  7. Symphony: a framework for accurate and holistic WSN simulation.

    PubMed

    Riliskis, Laurynas; Osipov, Evgeny

    2015-02-25

    Research on wireless sensor networks has progressed rapidly over the last decade, and these technologies have been widely adopted for both industrial and domestic uses. Several operating systems have been developed, along with a multitude of network protocols for all layers of the communication stack. Industrial Wireless Sensor Network (WSN) systems must satisfy strict criteria and are typically more complex and larger in scale than domestic systems. Together with the non-deterministic behavior of network hardware in real settings, this greatly complicates the debugging and testing of WSN functionality. To facilitate the testing, validation, and debugging of large-scale WSN systems, we have developed a simulation framework that accurately reproduces the processes that occur inside real equipment, including both hardware- and software-induced delays. The core of the framework consists of a virtualized operating system and an emulated hardware platform that is integrated with the general purpose network simulator ns-3. Our framework enables the user to adjust the real code base as would be done in real deployments and also to test the boundary effects of different hardware components on the performance of distributed applications and protocols. Additionally we have developed a clock emulator with several different skew models and a component that handles sensory data feeds. The new framework should substantially shorten WSN application development cycles.

  8. Symphony: A Framework for Accurate and Holistic WSN Simulation

    PubMed Central

    Riliskis, Laurynas; Osipov, Evgeny

    2015-01-01

    Research on wireless sensor networks has progressed rapidly over the last decade, and these technologies have been widely adopted for both industrial and domestic uses. Several operating systems have been developed, along with a multitude of network protocols for all layers of the communication stack. Industrial Wireless Sensor Network (WSN) systems must satisfy strict criteria and are typically more complex and larger in scale than domestic systems. Together with the non-deterministic behavior of network hardware in real settings, this greatly complicates the debugging and testing of WSN functionality. To facilitate the testing, validation, and debugging of large-scale WSN systems, we have developed a simulation framework that accurately reproduces the processes that occur inside real equipment, including both hardware- and software-induced delays. The core of the framework consists of a virtualized operating system and an emulated hardware platform that is integrated with the general purpose network simulator ns-3. Our framework enables the user to adjust the real code base as would be done in real deployments and also to test the boundary effects of different hardware components on the performance of distributed applications and protocols. Additionally we have developed a clock emulator with several different skew models and a component that handles sensory data feeds. The new framework should substantially shorten WSN application development cycles. PMID:25723144

  9. The Cellular Building Blocks of Breathing

    PubMed Central

    Ramirez, J.M.; Doi, A.; Garcia, A.J.; Elsen, F.P.; Koch, H.; Wei, A.D.

    2013-01-01

    Respiratory brainstem neurons fulfill critical roles in controlling breathing: they generate the activity patterns for breathing and contribute to various sensory responses including changes in O2 and CO2. These complex sensorimotor tasks depend on the dynamic interplay between numerous cellular building blocks that consist of voltage-, calcium-, and ATP-dependent ionic conductances, various ionotropic and metabotropic synaptic mechanisms, as well as neuromodulators acting on G-protein coupled receptors and second messenger systems. As described in this review, the sensorimotor responses of the respiratory network emerge through the state-dependent integration of all these building blocks. There is no known respiratory function that involves only a small number of intrinsic, synaptic, or modulatory properties. Because of the complex integration of numerous intrinsic, synaptic, and modulatory mechanisms, the respiratory network is capable of continuously adapting to changes in the external and internal environment, which makes breathing one of the most integrated behaviors. Not surprisingly, inspiration is critical not only in the control of ventilation, but also in the context of “inspiring behaviors” such as arousal of the mind and even creativity. Far-reaching implications apply also to the underlying network mechanisms, as lessons learned from the respiratory network apply to network functions in general. PMID:23720262

  10. [Senescence and cellular immortality].

    PubMed

    Trentesaux, C; Riou, J-F

    2010-11-01

    Senescence was originally described from the observation of the limited ability of normal cells to grow in culture, and may be generated by telomere erosion, accumulation of DNA damages, oxidative stress and modulation of oncogenes or tumor suppressor genes. Senescence corresponds to a cellular response aiming to control tumor progression by limiting cell proliferation and thus constitutes an anticancer barrier. Senescence is observed in pre-malignant tumor stages and disappears from malignant tumors. Agents used in standard chemotherapy also have the potential to induce senescence, which may partly explain their therapeutic activities. It is possible to restore senescence in tumors using targeted therapies that triggers telomere dysfunction or reactivates suppressor genes functions, which are essential for the onset of senescence.

  11. Scaling behavior in probabilistic neuronal cellular automata.

    PubMed

    Manchanda, Kaustubh; Yadav, Avinash Chand; Ramaswamy, Ramakrishna

    2013-01-01

    We study a neural network model of interacting stochastic discrete two-state cellular automata on a regular lattice. The system is externally tuned to a critical point which varies with the degree of stochasticity (or the effective temperature). There are avalanches of neuronal activity, namely, spatially and temporally contiguous sites of activity; a detailed numerical study of these activity avalanches is presented, and single, joint, and marginal probability distributions are computed. At the critical point, we find that the scaling exponents for the variables are in good agreement with a mean-field theory.

  12. Cellular circadian clocks in mood disorders.

    PubMed

    McCarthy, Michael J; Welsh, David K

    2012-10-01

    Bipolar disorder (BD) and major depressive disorder (MDD) are heritable neuropsychiatric disorders associated with disrupted circadian rhythms. The hypothesis that circadian clock dysfunction plays a causal role in these disorders has endured for decades but has been difficult to test and remains controversial. In the meantime, the discovery of clock genes and cellular clocks has revolutionized our understanding of circadian timing. Cellular circadian clocks are located in the suprachiasmatic nucleus (SCN), the brain's primary circadian pacemaker, but also throughout the brain and peripheral tissues. In BD and MDD patients, defects have been found in SCN-dependent rhythms of body temperature and melatonin release. However, these are imperfect and indirect indicators of SCN function. Moreover, the SCN may not be particularly relevant to mood regulation, whereas the lateral habenula, ventral tegmentum, and hippocampus, which also contain cellular clocks, have established roles in this regard. Dysfunction in these non-SCN clocks could contribute directly to the pathophysiology of BD/MDD. We hypothesize that circadian clock dysfunction in non-SCN clocks is a trait marker of mood disorders, encoded by pathological genetic variants. Because network features of the SCN render it uniquely resistant to perturbation, previous studies of SCN outputs in mood disorders patients may have failed to detect genetic defects affecting non-SCN clocks, which include not only mood-regulating neurons in the brain but also peripheral cells accessible in human subjects. Therefore, reporters of rhythmic clock gene expression in cells from patients or mouse models could provide a direct assay of the molecular gears of the clock, in cellular clocks that are likely to be more representative than the SCN of mood-regulating neurons in patients. This approach, informed by the new insights and tools of modern chronobiology, will allow a more definitive test of the role of cellular circadian clocks

  13. An Accurate Link Correlation Estimator for Improving Wireless Protocol Performance

    PubMed Central

    Zhao, Zhiwei; Xu, Xianghua; Dong, Wei; Bu, Jiajun

    2015-01-01

    Wireless link correlation has shown significant impact on the performance of various sensor network protocols. Many works have been devoted to exploiting link correlation for protocol improvements. However, the effectiveness of these designs heavily relies on the accuracy of link correlation measurement. In this paper, we investigate state-of-the-art link correlation measurement and analyze the limitations of existing works. We then propose a novel lightweight and accurate link correlation estimation (LACE) approach based on the reasoning of link correlation formation. LACE combines both long-term and short-term link behaviors for link correlation estimation. We implement LACE as a stand-alone interface in TinyOS and incorporate it into both routing and flooding protocols. Simulation and testbed results show that LACE: (1) achieves more accurate and lightweight link correlation measurements than the state-of-the-art work; and (2) greatly improves the performance of protocols exploiting link correlation. PMID:25686314

  14. Modeling cellular deformations using the level set formalism

    PubMed Central

    Yang, Liu; Effler, Janet C; Kutscher, Brett L; Sullivan, Sarah E; Robinson, Douglas N; Iglesias, Pablo A

    2008-01-01

    Background Many cellular processes involve substantial shape changes. Traditional simulations of these cell shape changes require that grids and boundaries be moved as the cell's shape evolves. Here we demonstrate that accurate cell shape changes can be recreated using level set methods (LSM), in which the cellular shape is defined implicitly, thereby eschewing the need for updating boundaries. Results We obtain a viscoelastic model of Dictyostelium cells using micropipette aspiration and show how this viscoelastic model can be incorporated into LSM simulations to recreate the observed protrusion of cells into the micropipette faithfully. We also demonstrate the use of our techniques by simulating the cell shape changes elicited by the chemotactic response to an external chemoattractant gradient. Conclusion Our results provide a simple but effective means of incorporating cellular deformations into mathematical simulations of cell signaling. Such methods will be useful for simulating important cellular events such as chemotaxis and cytokinesis. PMID:18652669

  15. Cellular telephone-based radiation detection instrument

    DOEpatents

    Craig, William W.; Labov, Simon E.

    2011-06-14

    A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

  16. Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity.

    PubMed

    Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

    2017-01-01

    Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying

  17. Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity

    PubMed Central

    Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

    2017-01-01

    Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying

  18. Fibre based cellular transfection.

    PubMed

    Tsampoula, X; Taguchi, K; Cizmár, T; Garces-Chavez, V; Ma, N; Mohanty, S; Mohanty, K; Gunn-Moore, F; Dholakia, K

    2008-10-13

    Optically assisted transfection is emerging as a powerful and versatile method for the delivery of foreign therapeutic agents to cells at will. In particular the use of ultrashort pulse lasers has proved an important route to transiently permeating the cell membrane through a multiphoton process. Though optical transfection has been gaining wider usage to date, all incarnations of this technique have employed free space light beams. In this paper we demonstrate the first system to use fibre delivery for the optical transfection of cells. We engineer a standard optical fibre to generate an axicon tip with an enhanced intensity of the remote output field that delivers ultrashort (~ 800 fs) pulses without requiring the fibre to be placed in very close proximity to the cell sample. A theoretical model is also developed in order to predict the light propagation from axicon tipped and bare fibres, in both air and water environments. The model proves to be in good agreement with the experimental findings and can be used to establish the optimum fibre parameters for successful cellular transfection. We readily obtain efficiencies of up to 57 % which are comparable with free space transfection. This advance paves the way for optical transfection of tissue samples and endoscopic embodiments of this technique.

  19. Extending the Applicability of Graphlets to Directed Networks.

    PubMed

    Aparicio, David; Ribeiro, Pedro; Silva, Fernando

    2016-06-28

    With recent advances in high-throughput cell biology the amount of cellular biological data has grown drastically. Such data is often modeled as graphs (also called networks) and studying them can lead to new insights into molecule-level organization. A possible way to understand their structure is by analysing the smaller components that constitute them, namely network motifs and graphlets. Graphlets are particularly well suited to compare networks and to assess their level of similarity due to the rich topological information that they offer but are almost always used as small undirected graphs of up to five nodes, thus limiting their applicability in directed networks. However, a large set of interesting biological networks such as metabolic, cell signaling or transcriptional regulatory networks are intrinsically directional, and using metrics that ignore edge direction may gravely hinder information extraction. Our main purpose in this work is to extend the applicability of graphlets to directed networks by considering their edge direction, thus providing a powerful basis for the analysis of directed biological networks. We tested our approach on two network sets, one composed of synthetic graphs and another of real directed biological networks, and verified that they were more accurately grouped using directed graphlets than undirected graphlets. It is also evident that directed graphlets offer substantially more topological information than simple graph metrics such as degree distribution or reciprocity. However, enumerating graphlets in large networks is a computationally demanding task. Our implementation addresses this concern by using a state-of-the-art data structure, the g-trie, which is able to greatly reduce the necessary computation. We compared our tool to other state-of-the art methods and verified that it is the fastest general tool for graphlet counting.

  20. Deep brain stimulation of the center median-parafascicular complex of the thalamus has efficient anti-parkinsonian action associated with widespread cellular responses in the basal ganglia network in a rat model of Parkinson's disease.

    PubMed

    Jouve, Loréline; Salin, Pascal; Melon, Christophe; Kerkerian-Le Goff, Lydia

    2010-07-21

    The thalamic centromedian-parafascicular (CM/Pf) complex, mainly represented by Pf in rodents, is proposed as an interesting target for the neurosurgical treatment of movement disorders, including Parkinson's disease. In this study, we examined the functional impact of subchronic high-frequency stimulation (HFS) of Pf in the 6-hydroxydopamine-lesioned hemiparkinsonian rat model. Pf-HFS had significant anti-akinetic action, evidenced by alleviation of limb use asymmetry (cylinder test). Whereas this anti-akinetic action was moderate, Pf-HFS totally reversed lateralized neglect (corridor task), suggesting potent action on sensorimotor integration. At the cellular level, Pf-HFS partially reversed the dopamine denervation-induced increase in striatal preproenkephalin A mRNA levels, a marker of the neurons of the indirect pathway, without interfering with the markers of the direct pathway (preprotachykinin and preprodynorphin). Pf-HFS totally reversed the lesion-induced changes in the gene expression of cytochrome oxidase subunit I in the subthalamic nucleus, the globus pallidus, and the substantia nigra pars reticulata, and partially in the entopeduncular nucleus. Unlike HFS of the subthalamic nucleus, Pf-HFS did not induce per se dyskinesias and directly, although partially, alleviated L-3,4-dihydroxyphenylalanine (L-DOPA)-induced forelimb dyskinesia. Conversely, L-DOPA treatment negatively interfered with the anti-parkinsonian effect of Pf-HFS. Altogether, these data show that Pf-DBS, by recruiting a large basal ganglia circuitry, provides moderate to strong anti-parkinsonian benefits that might, however, be affected by L-DOPA. The widespread behavioral and cellular outcomes of Pf-HFS evidenced here demonstrate that CM/Pf is an important node for modulating the pathophysiological functioning of basal ganglia and related disorders.

  1. Using partial least squares regression to analyze cellular response data.

    PubMed

    Kreeger, Pamela K

    2013-04-16

    This Teaching Resource provides lecture notes, slides, and a problem set for a lecture introducing the mathematical concepts and interpretation of partial least squares regression (PLSR) that were part of a course entitled "Systems Biology: Mammalian Signaling Networks." PLSR is a multivariate regression technique commonly applied to analyze relationships between signaling or transcriptional data and cellular behavior.

  2. Mill profiler machines soft materials accurately

    NASA Technical Reports Server (NTRS)

    Rauschl, J. A.

    1966-01-01

    Mill profiler machines bevels, slots, and grooves in soft materials, such as styrofoam phenolic-filled cores, to any desired thickness. A single operator can accurately control cutting depths in contour or straight line work.

  3. Reprogramming cellular behavior with RNA controllers responsive to endogenous proteins.

    PubMed

    Culler, Stephanie J; Hoff, Kevin G; Smolke, Christina D

    2010-11-26

    Synthetic genetic devices that interface with native cellular pathways can be used to change natural networks to implement new forms of control and behavior. The engineering of gene networks has been limited by an inability to interface with native components. We describe a class of RNA control devices that overcome these limitations by coupling increased abundance of particular proteins to targeted gene expression events through the regulation of alternative RNA splicing. We engineered RNA devices that detect signaling through the nuclear factor κB and Wnt signaling pathways in human cells and rewire these pathways to produce new behaviors, thereby linking disease markers to noninvasive sensing and reprogrammed cellular fates. Our work provides a genetic platform that can build programmable sensing-actuation devices enabling autonomous control over cellular behavior.

  4. Physics of Cellular Movements

    NASA Astrophysics Data System (ADS)

    Sackmann, Erich; Keber, Felix; Heinrich, Doris

    2010-04-01

    The survival of cells depends on perpetual active motions, including (a) bending excitations of the soft cell envelopes, (b) the bidirectional transport of materials and organelles between the cell center and the periphery, and (c) the ongoing restructuring of the intracellular macromolecular scaffolds mediating global cell changes associated with cell adhesion locomotion and phagocytosis. Central questions addressed are the following: How can this bustling motion of extremely complex soft structures be characterized and measured? What are the major driving forces? Further topics include (a) the active dynamic control of global shape changes by the interactive coupling of the aster-like soft scaffold of microtubules and the network of actin filaments associated with the cell envelope (the actin cortex) and (b) the generation of propulsion forces by solitary actin gelation waves propagating within the actin cortex.

  5. Elements of the cellular metabolic structure

    PubMed Central

    De la Fuente, Ildefonso M.

    2015-01-01

    A large number of studies have demonstrated the existence of metabolic covalent modifications in different molecular structures, which are able to store biochemical information that is not encoded by DNA. Some of these covalent mark patterns can be transmitted across generations (epigenetic changes). Recently, the emergence of Hopfield-like attractor dynamics has been observed in self-organized enzymatic networks, which have the capacity to store functional catalytic patterns that can be correctly recovered by specific input stimuli. Hopfield-like metabolic dynamics are stable and can be maintained as a long-term biochemical memory. In addition, specific molecular information can be transferred from the functional dynamics of the metabolic networks to the enzymatic activity involved in covalent post-translational modulation, so that determined functional memory can be embedded in multiple stable molecular marks. The metabolic dynamics governed by Hopfield-type attractors (functional processes), as well as the enzymatic covalent modifications of specific molecules (structural dynamic processes) seem to represent the two stages of the dynamical memory of cellular metabolism (metabolic memory). Epigenetic processes appear to be the structural manifestation of this cellular metabolic memory. Here, a new framework for molecular information storage in the cell is presented, which is characterized by two functionally and molecularly interrelated systems: a dynamic, flexible and adaptive system (metabolic memory) and an essentially conservative system (genetic memory). The molecular information of both systems seems to coordinate the physiological development of the whole cell. PMID:25988183

  6. 47 CFR 22.909 - Cellular markets.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 2 2010-10-01 2010-10-01 false Cellular markets. 22.909 Section 22.909... Cellular Radiotelephone Service § 22.909 Cellular markets. Cellular markets are standard geographic areas used by the FCC for administrative convenience in the licensing of cellular systems. Cellular...

  7. 47 CFR 22.909 - Cellular markets.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 2 2011-10-01 2011-10-01 false Cellular markets. 22.909 Section 22.909... Cellular Radiotelephone Service § 22.909 Cellular markets. Cellular markets are standard geographic areas used by the FCC for administrative convenience in the licensing of cellular systems. Cellular...

  8. 47 CFR 22.909 - Cellular markets.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 47 Telecommunication 2 2012-10-01 2012-10-01 false Cellular markets. 22.909 Section 22.909... Cellular Radiotelephone Service § 22.909 Cellular markets. Cellular markets are standard geographic areas used by the FCC for administrative convenience in the licensing of cellular systems. Cellular...

  9. 47 CFR 22.909 - Cellular markets.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 47 Telecommunication 2 2014-10-01 2014-10-01 false Cellular markets. 22.909 Section 22.909... Cellular Radiotelephone Service § 22.909 Cellular markets. Cellular markets are standard geographic areas used by the FCC for administrative convenience in the licensing of cellular systems. Cellular...

  10. 47 CFR 22.909 - Cellular markets.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 47 Telecommunication 2 2013-10-01 2013-10-01 false Cellular markets. 22.909 Section 22.909... Cellular Radiotelephone Service § 22.909 Cellular markets. Cellular markets are standard geographic areas used by the FCC for administrative convenience in the licensing of cellular systems. Cellular...

  11. Mouse models of human AML accurately predict chemotherapy response

    PubMed Central

    Zuber, Johannes; Radtke, Ina; Pardee, Timothy S.; Zhao, Zhen; Rappaport, Amy R.; Luo, Weijun; McCurrach, Mila E.; Yang, Miao-Miao; Dolan, M. Eileen; Kogan, Scott C.; Downing, James R.; Lowe, Scott W.

    2009-01-01

    The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients. PMID:19339691

  12. Mouse models of human AML accurately predict chemotherapy response.

    PubMed

    Zuber, Johannes; Radtke, Ina; Pardee, Timothy S; Zhao, Zhen; Rappaport, Amy R; Luo, Weijun; McCurrach, Mila E; Yang, Miao-Miao; Dolan, M Eileen; Kogan, Scott C; Downing, James R; Lowe, Scott W

    2009-04-01

    The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients.

  13. Strategy for tactical cellular connectivity

    NASA Astrophysics Data System (ADS)

    Carlson, Frederick R.

    2011-06-01

    This paper proposes a strategy to unify four disparate networks under an Internet Protocol (IP) umbrella. The first network is the Army Warfighter Information Network - Tactical (WIN-T) area common user system. The second network is an extension to the area common user system using the Mobile Ad Hoc Interoperability Networking Gateway (MAINGATE) system. The third network is the Worldwide Interoperability for Microwave Access (WiMax) based wireless access network and the forth network is the 802.11 WiFi Network. It is the intent of this paper to propose a skeletal wireless strategy that at its core will create everything over IP (EoIP) and "Everything over IEEE" ("EoIEEE") standards at the tactical level of the battlefield.

  14. A Highly Accurate Face Recognition System Using Filtering Correlation

    NASA Astrophysics Data System (ADS)

    Watanabe, Eriko; Ishikawa, Sayuri; Kodate, Kashiko

    2007-09-01

    The authors previously constructed a highly accurate fast face recognition optical correlator (FARCO) [E. Watanabe and K. Kodate: Opt. Rev. 12 (2005) 460], and subsequently developed an improved, super high-speed FARCO (S-FARCO), which is able to process several hundred thousand frames per second. The principal advantage of our new system is its wide applicability to any correlation scheme. Three different configurations were proposed, each depending on correlation speed. This paper describes and evaluates a software correlation filter. The face recognition function proved highly accurate, seeing that a low-resolution facial image size (64 × 64 pixels) has been successfully implemented. An operation speed of less than 10 ms was achieved using a personal computer with a central processing unit (CPU) of 3 GHz and 2 GB memory. When we applied the software correlation filter to a high-security cellular phone face recognition system, experiments on 30 female students over a period of three months yielded low error rates: 0% false acceptance rate and 2% false rejection rate. Therefore, the filtering correlation works effectively when applied to low resolution images such as web-based images or faces captured by a monitoring camera.

  15. Multiscale modeling of droplet interface bilayer membrane networks

    PubMed Central

    Freeman, Eric C.; Farimani, Amir B.; Aluru, Narayana R.; Philen, Michael K.

    2015-01-01

    Droplet interface bilayer (DIB) networks are considered for the development of stimuli-responsive membrane-based materials inspired by cellular mechanics. These DIB networks are often modeled as combinations of electrical circuit analogues, creating complex networks of capacitors and resistors that mimic the biomolecular structures. These empirical models are capable of replicating data from electrophysiology experiments, but these models do not accurately capture the underlying physical phenomena and consequently do not allow for simulations of material functionalities beyond the voltage-clamp or current-clamp conditions. The work presented here provides a more robust description of DIB network behavior through the development of a hierarchical multiscale model, recognizing that the macroscopic network properties are functions of their underlying molecular structure. The result of this research is a modeling methodology based on controlled exchanges across the interfaces of neighboring droplets. This methodology is validated against experimental data, and an extension case is provided to demonstrate possible future applications of droplet interface bilayer networks. PMID:26594262

  16. Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics

    PubMed Central

    Li, Zheng-Wei; You, Zhu-Hong; Chen, Xing; Gui, Jie; Nie, Ru

    2016-01-01

    Protein-protein interactions (PPIs) occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental techniques have been developed to identify PPIs, existing PPI pairs by experimental approaches only cover a small fraction of the whole PPI networks, and further, those approaches hold inherent disadvantages, such as being time-consuming, expensive, and having high false positive rate. Therefore, it is urgent and imperative to develop automatic in silico approaches to predict PPIs efficiently and accurately. In this article, we propose a novel mixture of physicochemical and evolutionary-based feature extraction method for predicting PPIs using our newly developed discriminative vector machine (DVM) classifier. The improvements of the proposed method mainly consist in introducing an effective feature extraction method that can capture discriminative features from the evolutionary-based information and physicochemical characteristics, and then a powerful and robust DVM classifier is employed. To the best of our knowledge, it is the first time that DVM model is applied to the field of bioinformatics. When applying the proposed method to the Yeast and Helicobacter pylori (H. pylori) datasets, we obtain excellent prediction accuracies of 94.35% and 90.61%, respectively. The computational results indicate that our method is effective and robust for predicting PPIs, and can be taken as a useful supplementary tool to the traditional experimental methods for future proteomics research. PMID:27571061

  17. Network Characterization Service (NCS)

    SciTech Connect

    Jin, Guojun; Yang, George; Crowley, Brian; Agarwal, Deborah

    2001-06-06

    Distributed applications require information to effectively utilize the network. Some of the information they require is the current and maximum bandwidth, current and minimum latency, bottlenecks, burst frequency, and congestion extent. This type of information allows applications to determine parameters like optimal TCP buffer size. In this paper, we present a cooperative information-gathering tool called the network characterization service (NCS). NCS runs in user space and is used to acquire network information. Its protocol is designed for scalable and distributed deployment, similar to DNS. Its algorithms provide efficient, speedy and accurate detection of bottlenecks, especially dynamic bottlenecks. On current and future networks, dynamic bottlenecks do and will affect network performance dramatically.

  18. Four faces of cellular senescence

    PubMed Central

    Rodier, Francis

    2011-01-01

    Cellular senescence is an important mechanism for preventing the proliferation of potential cancer cells. Recently, however, it has become apparent that this process entails more than a simple cessation of cell growth. In addition to suppressing tumorigenesis, cellular senescence might also promote tissue repair and fuel inflammation associated with aging and cancer progression. Thus, cellular senescence might participate in four complex biological processes (tumor suppression, tumor promotion, aging, and tissue repair), some of which have apparently opposing effects. The challenge now is to understand the senescence response well enough to harness its benefits while suppressing its drawbacks. PMID:21321098

  19. Drawing networks of rejection - a systems biological approach to the identification of candidate genes in heart transplantation.

    PubMed

    Cadeiras, Martin; von Bayern, Manuel; Sinha, Anshu; Shahzad, Khurram; Latif, Farhana; Lim, Wei Keat; Grenett, Hernan; Tabak, Esteban; Klingler, Tod; Califano, Andrea; Deng, Mario C

    2011-04-01

    Technological development led to an increased interest in systems biological approaches to characterize disease mechanisms and candidate genes relevant to specific diseases. We suggested that the human peripheral blood mononuclear cells (PBMC) network can be delineated by cellular reconstruction to guide identification of candidate genes. Based on 285 microarrays (7370 genes) from 98 heart transplant patients enrolled in the Cardiac Allograft Rejection Gene Expression Observational study, we used an information-theoretic, reverse-engineering algorithm called ARACNe (algorithm for the reconstruction of accurate cellular networks) and chromatin immunoprecipitation assay to reconstruct and validate a putative gene PBMC interaction network. We focused our analysis on transcription factor (TF) genes and developed a priority score to incorporate aspects of network dynamics and information from published literature to supervise gene discovery. ARACNe generated a cellular network and predicted interactions for each TF during rejection and quiescence. Genes ranked highest by priority score included those related to apoptosis, humoural and cellular immune response such as GA binding protein transcription factor (GABP), nuclear factor of κ light polypeptide gene enhancer in B-cells (NFκB), Fas (TNFRSF6)-associated via death domain (FADD) and c-AMP response element binding protein. We used the TF CREB to validate our network. ARACNe predicted 29 putative first-neighbour genes of CREB. Eleven of these (37%) were previously reported. Out of the 18 unknown predicted interactions, 14 primers were identified and 11 could be immunoprecipitated (78.6%). Overall, 75% (n= 22) inferred CREB targets were validated, a significantly higher fraction than randomly expected (P < 0.001, Fisher's exact test). Our results confirm the accuracy of ARACNe to reconstruct the PBMC transcriptional network and show the utility of systems biological approaches to identify possible molecular targets

  20. Mobile Virtual Private Networking

    NASA Astrophysics Data System (ADS)

    Pulkkis, Göran; Grahn, Kaj; Mårtens, Mathias; Mattsson, Jonny

    Mobile Virtual Private Networking (VPN) solutions based on the Internet Security Protocol (IPSec), Transport Layer Security/Secure Socket Layer (SSL/TLS), Secure Shell (SSH), 3G/GPRS cellular networks, Mobile IP, and the presently experimental Host Identity Protocol (HIP) are described, compared and evaluated. Mobile VPN solutions based on HIP are recommended for future networking because of superior processing efficiency and network capacity demand features. Mobile VPN implementation issues associated with the IP protocol versions IPv4 and IPv6 are also evaluated. Mobile VPN implementation experiences are presented and discussed.

  1. Accurate pointing of tungsten welding electrodes

    NASA Technical Reports Server (NTRS)

    Ziegelmeier, P.

    1971-01-01

    Thoriated-tungsten is pointed accurately and quickly by using sodium nitrite. Point produced is smooth and no effort is necessary to hold the tungsten rod concentric. The chemically produced point can be used several times longer than ground points. This method reduces time and cost of preparing tungsten electrodes.

  2. Origami interleaved tube cellular materials

    NASA Astrophysics Data System (ADS)

    Cheung, Kenneth C.; Tachi, Tomohiro; Calisch, Sam; Miura, Koryo

    2014-09-01

    A novel origami cellular material based on a deployable cellular origami structure is described. The structure is bi-directionally flat-foldable in two orthogonal (x and y) directions and is relatively stiff in the third orthogonal (z) direction. While such mechanical orthotropicity is well known in cellular materials with extruded two dimensional geometry, the interleaved tube geometry presented here consists of two orthogonal axes of interleaved tubes with high interfacial surface area and relative volume that changes with fold-state. In addition, the foldability still allows for fabrication by a flat lamination process, similar to methods used for conventional expanded two dimensional cellular materials. This article presents the geometric characteristics of the structure together with corresponding kinematic and mechanical modeling, explaining the orthotropic elastic behavior of the structure with classical dimensional scaling analysis.

  3. A Course in Cellular Bioengineering.

    ERIC Educational Resources Information Center

    Lauffenburger, Douglas A.

    1989-01-01

    Gives an overview of a course in chemical engineering entitled "Cellular Bioengineering," dealing with how chemical engineering principles can be applied to molecular cell biology. Topics used are listed and some key references are discussed. Listed are 85 references. (YP)

  4. Mathematical Modeling of Cellular Metabolism.

    PubMed

    Berndt, Nikolaus; Holzhütter, Hermann-Georg

    Cellular metabolism basically consists of the conversion of chemical compounds taken up from the extracellular environment into energy (conserved in energy-rich bonds of organic phosphates) and a wide array of organic molecules serving as catalysts (enzymes), information carriers (nucleic acids), and building blocks for cellular structures such as membranes or ribosomes. Metabolic modeling aims at the construction of mathematical representations of the cellular metabolism that can be used to calculate the concentration of cellular molecules and the rates of their mutual chemical interconversion in response to varying external conditions as, for example, hormonal stimuli or supply of essential nutrients. Based on such calculations, it is possible to quantify complex cellular functions as cellular growth, detoxification of drugs and xenobiotic compounds or synthesis of exported molecules. Depending on the specific questions to metabolism addressed, the methodological expertise of the researcher, and available experimental information, different conceptual frameworks have been established, allowing the usage of computational methods to condense experimental information from various layers of organization into (self-) consistent models. Here, we briefly outline the main conceptual frameworks that are currently exploited in metabolism research.

  5. Numerical simulation of premixed H2-air cellular tubular flames

    NASA Astrophysics Data System (ADS)

    Hall, Carl Alan; Wendell Pitz, Robert

    2016-03-01

    The detailed flame structure of laminar premixed cellular flames in the tubular domain is simulated in 2D using a fully-implicit primitive variable finite difference formulation that includes multicomponent transport and detailed chemical kinetics. Numerical results for H2/air flames are presented and compared against spatially resolved experimental measurements of temperature and chemical species including atomic H and OH. The experimental results compare well for flame structure and cell number, despite the numerical model under-predicting the peak temperature by 200 K. Numerical experiments were performed to assess the ability for cellular tubular flames to impact experimental and numerical investigations of practical flames. The cellular flame structure is found to provide a highly sensitive geometry that is useful for validating diffusive transport modelling approximations. This capability is exemplified through the development of a simple and accurate approximation for thermal diffusion (i.e. the Soret effect) that is suitable for practical combustion codes.

  6. Feedback about More Accurate versus Less Accurate Trials: Differential Effects on Self-Confidence and Activation

    ERIC Educational Resources Information Center

    Badami, Rokhsareh; VaezMousavi, Mohammad; Wulf, Gabriele; Namazizadeh, Mahdi

    2012-01-01

    One purpose of the present study was to examine whether self-confidence or anxiety would be differentially affected by feedback from more accurate rather than less accurate trials. The second purpose was to determine whether arousal variations (activation) would predict performance. On Day 1, participants performed a golf putting task under one of…

  7. Optimal temporal patterns for dynamical cellular signaling

    NASA Astrophysics Data System (ADS)

    Hasegawa, Yoshihiko

    2016-11-01

    Cells use temporal dynamical patterns to transmit information via signaling pathways. As optimality with respect to the environment plays a fundamental role in biological systems, organisms have evolved optimal ways to transmit information. Here, we use optimal control theory to obtain the dynamical signal patterns for the optimal transmission of information, in terms of efficiency (low energy) and reliability (low uncertainty). Adopting an activation-deactivation decoding network, we reproduce several dynamical patterns found in actual signals, such as steep, gradual, and overshooting dynamics. Notably, when minimizing the energy of the input signal, the optimal signals exhibit overshooting, which is a biphasic pattern with transient and steady phases; this pattern is prevalent in actual dynamical patterns. We also identify conditions in which these three patterns (steep, gradual, and overshooting) confer advantages. Our study shows that cellular signal transduction is governed by the principle of minimizing free energy dissipation and uncertainty; these constraints serve as selective pressures when designing dynamical signaling patterns.

  8. Traffic jam dynamics in stochastic cellular automata

    SciTech Connect

    Nagel, K. |; Schreckenberg, M.

    1995-09-01

    Simple models for particles hopping on a grid (cellular automata) are used to simulate (single lane) traffic flow. Despite their simplicity, these models are astonishingly realistic in reproducing start-stop-waves and realistic fundamental diagrams. One can use these models to investigate traffic phenomena near maximum flow. A so-called phase transition at average maximum flow is visible in the life-times of jams. The resulting dynamic picture is consistent with recent fluid-dynamical results by Kuehne/Kerner/Konhaeuser, and with Treiterer`s hysteresis description. This places CA models between car-following models and fluid-dynamical models for traffic flow. CA models are tested in projects in Los Alamos (USA) and in NRW (Germany) for large scale microsimulations of network traffic.

  9. Signal Approximation with a Wavelet Neural Network

    DTIC Science & Technology

    1992-12-01

    specialized electronic devices like the Intel Electronically Trainable Analog Neural Network (ETANN) chip. The WNN representation allows the...accurately approximated with a WNN trained with irregularly sampled data. Signal approximation, Wavelet neural network .

  10. Cellular basis for QT dispersion.

    PubMed

    Antzelevitch, C; Shimizu, W; Yan, G X; Sicouri, S

    1998-01-01

    The cellular basis for the dispersion of the QT interval recorded at the body surface is incompletely understood. Contributing to QT dispersion are heterogeneities of repolarization time in the three-dimensional structure of the ventricular myocardium, which are secondary to regional differences in action potential duration (APD) and activation time. While differences in APD occur along the apicobasal and anteroposterior axes in both epicardium and endocardium of many species, transitions are usually gradual. Recent studies have also demonstrated important APD gradients along the transmural axis. Because transmural heterogeneities in repolarization time are more abrupt than those recorded along the surfaces of the heart, they may represent a more onerous substrate for the development of arrhythmias, and their quantitation may provide a valuable tool for evaluation of arrhythmia risk. Our data, derived from the arterially perfused canine left ventricular wedge preparation, suggest that transmural gradients of voltage during repolarization contribute importantly to the inscription of the T wave. The start of the T wave is caused by a more rapid decline of the plateau, or phase 2 of the epicardial action potential, creating a voltage gradient across the wall. The gradient increases as the epicardial action potential continues to repolarize, reaching a maximum with full repolarization of epicardium; this juncture marks the peak of the T wave. The next region to repolarize is endocardium, giving rise to the initial descending limb of the upright T wave. The last region to repolarize is the M region, contributing to the final segment of the T wave. Full repolarization of the M region marks the end of the T wave. The time interval between the peak and the end of the T wave therefore represents the transmural dispersion of repolarization. Conditions known to augment QTc dispersion, including acquired long QT syndrome (class IA or III antiarrhythmics) lead to augmentation

  11. Accurate Guitar Tuning by Cochlear Implant Musicians

    PubMed Central

    Lu, Thomas; Huang, Juan; Zeng, Fan-Gang

    2014-01-01

    Modern cochlear implant (CI) users understand speech but find difficulty in music appreciation due to poor pitch perception. Still, some deaf musicians continue to perform with their CI. Here we show unexpected results that CI musicians can reliably tune a guitar by CI alone and, under controlled conditions, match simultaneously presented tones to <0.5 Hz. One subject had normal contralateral hearing and produced more accurate tuning with CI than his normal ear. To understand these counterintuitive findings, we presented tones sequentially and found that tuning error was larger at ∼30 Hz for both subjects. A third subject, a non-musician CI user with normal contralateral hearing, showed similar trends in performance between CI and normal hearing ears but with less precision. This difference, along with electric analysis, showed that accurate tuning was achieved by listening to beats rather than discriminating pitch, effectively turning a spectral task into a temporal discrimination task. PMID:24651081

  12. New model accurately predicts reformate composition

    SciTech Connect

    Ancheyta-Juarez, J.; Aguilar-Rodriguez, E. )

    1994-01-31

    Although naphtha reforming is a well-known process, the evolution of catalyst formulation, as well as new trends in gasoline specifications, have led to rapid evolution of the process, including: reactor design, regeneration mode, and operating conditions. Mathematical modeling of the reforming process is an increasingly important tool. It is fundamental to the proper design of new reactors and revamp of existing ones. Modeling can be used to optimize operating conditions, analyze the effects of process variables, and enhance unit performance. Instituto Mexicano del Petroleo has developed a model of the catalytic reforming process that accurately predicts reformate composition at the higher-severity conditions at which new reformers are being designed. The new AA model is more accurate than previous proposals because it takes into account the effects of temperature and pressure on the rate constants of each chemical reaction.

  13. Accurate colorimetric feedback for RGB LED clusters

    NASA Astrophysics Data System (ADS)

    Man, Kwong; Ashdown, Ian

    2006-08-01

    We present an empirical model of LED emission spectra that is applicable to both InGaN and AlInGaP high-flux LEDs, and which accurately predicts their relative spectral power distributions over a wide range of LED junction temperatures. We further demonstrate with laboratory measurements that changes in LED spectral power distribution with temperature can be accurately predicted with first- or second-order equations. This provides the basis for a real-time colorimetric feedback system for RGB LED clusters that can maintain the chromaticity of white light at constant intensity to within +/-0.003 Δuv over a range of 45 degrees Celsius, and to within 0.01 Δuv when dimmed over an intensity range of 10:1.

  14. Accurate guitar tuning by cochlear implant musicians.

    PubMed

    Lu, Thomas; Huang, Juan; Zeng, Fan-Gang

    2014-01-01

    Modern cochlear implant (CI) users understand speech but find difficulty in music appreciation due to poor pitch perception. Still, some deaf musicians continue to perform with their CI. Here we show unexpected results that CI musicians can reliably tune a guitar by CI alone and, under controlled conditions, match simultaneously presented tones to <0.5 Hz. One subject had normal contralateral hearing and produced more accurate tuning with CI than his normal ear. To understand these counterintuitive findings, we presented tones sequentially and found that tuning error was larger at ∼ 30 Hz for both subjects. A third subject, a non-musician CI user with normal contralateral hearing, showed similar trends in performance between CI and normal hearing ears but with less precision. This difference, along with electric analysis, showed that accurate tuning was achieved by listening to beats rather than discriminating pitch, effectively turning a spectral task into a temporal discrimination task.

  15. Efficient and Accurate Indoor Localization Using Landmark Graphs

    NASA Astrophysics Data System (ADS)

    Gu, F.; Kealy, A.; Khoshelham, K.; Shang, J.

    2016-06-01

    Indoor localization is important for a variety of applications such as location-based services, mobile social networks, and emergency response. Fusing spatial information is an effective way to achieve accurate indoor localization with little or with no need for extra hardware. However, existing indoor localization methods that make use of spatial information are either too computationally expensive or too sensitive to the completeness of landmark detection. In this paper, we solve this problem by using the proposed landmark graph. The landmark graph is a directed graph where nodes are landmarks (e.g., doors, staircases, and turns) and edges are accessible paths with heading information. We compared the proposed method with two common Dead Reckoning (DR)-based methods (namely, Compass + Accelerometer + Landmarks and Gyroscope + Accelerometer + Landmarks) by a series of experiments. Experimental results show that the proposed method can achieve 73% accuracy with a positioning error less than 2.5 meters, which outperforms the other two DR-based methods.

  16. Cellular and molecular approaches to memory storage.

    PubMed

    Laroche, S

    2000-01-01

    There has been nearly a century of interest in the idea that information is stored in the brain as changes in the efficacy of synaptic connections on neurons that are activated during learning. The discovery and detailed report of the phenomenon generally known as long-term potentiation opened a new chapter in the study of synaptic plasticity in the vertebrate brain, and this form of synaptic plasticity has now become the dominant model in the search for the cellular bases of learning and memory. To date, considerable progress has been made in understanding the cellular and molecular mechanisms underlying synaptic plasticity and in identifying the neural systems which express it. In parallel, the hypothesis that the mechanisms underlying synaptic plasticity are activated during learning and serve learning and memory has gained much empirical support. Accumulating evidence suggests that the rapid activation of the genetic machinery is a key mechanism underlying the enduring modification of neural networks required for the laying down of memory. These advances are reviewed below.

  17. An Accurate, Simplified Model Intrabeam Scattering

    SciTech Connect

    Bane, Karl LF

    2002-05-23

    Beginning with the general Bjorken-Mtingwa solution for intrabeam scattering (IBS) we derive an accurate, greatly simplified model of IBS, valid for high energy beams in normal storage ring lattices. In addition, we show that, under the same conditions, a modified version of Piwinski's IBS formulation (where {eta}{sub x,y}{sup 2}/{beta}{sub x,y} has been replaced by {Eta}{sub x,y}) asymptotically approaches the result of Bjorken-Mtingwa.

  18. An accurate registration technique for distorted images

    NASA Technical Reports Server (NTRS)

    Delapena, Michele; Shaw, Richard A.; Linde, Peter; Dravins, Dainis

    1990-01-01

    Accurate registration of International Ultraviolet Explorer (IUE) images is crucial because the variability of the geometrical distortions that are introduced by the SEC-Vidicon cameras ensures that raw science images are never perfectly aligned with the Intensity Transfer Functions (ITFs) (i.e., graded floodlamp exposures that are used to linearize and normalize the camera response). A technique for precisely registering IUE images which uses a cross correlation of the fixed pattern that exists in all raw IUE images is described.

  19. On accurate determination of contact angle

    NASA Technical Reports Server (NTRS)

    Concus, P.; Finn, R.

    1992-01-01

    Methods are proposed that exploit a microgravity environment to obtain highly accurate measurement of contact angle. These methods, which are based on our earlier mathematical results, do not require detailed measurement of a liquid free-surface, as they incorporate discontinuous or nearly-discontinuous behavior of the liquid bulk in certain container geometries. Physical testing is planned in the forthcoming IML-2 space flight and in related preparatory ground-based experiments.

  20. A Conserved Circular Network of Coregulated Lipids Modulates Innate Immune Responses.

    PubMed

    Köberlin, Marielle S; Snijder, Berend; Heinz, Leonhard X; Baumann, Christoph L; Fauster, Astrid; Vladimer, Gregory I; Gavin, Anne-Claude; Superti-Furga, Giulio

    2015-07-02

    Lipid composition affects the biophysical properties of membranes that provide a platform for receptor-mediated cellular signaling. To study the regulatory role of membrane lipid composition, we combined genetic perturbations of sphingolipid metabolism with the quantification of diverse steps in Toll-like receptor (TLR) signaling and mass spectrometry-based lipidomics. Membrane lipid composition was broadly affected by these perturbations, revealing a circular network of coregulated sphingolipids and glycerophospholipids. This evolutionarily conserved network architecture simultaneously reflected membrane lipid metabolism, subcellular localization, and adaptation mechanisms. Integration of the diverse TLR-induced inflammatory phenotypes with changes in lipid abundance assigned distinct functional roles to individual lipid species organized across the network. This functional annotation accurately predicted the inflammatory response of cells derived from patients suffering from lipid storage disorders, based solely on their altered membrane lipid composition. The analytical strategy described here empowers the understanding of higher-level organization of membrane lipid function in diverse biological systems.

  1. Alteration of ceramide synthase 6/C16-ceramide induces activating transcription factor 6-mediated endoplasmic reticulum (ER) stress and apoptosis via perturbation of cellular Ca2+ and ER/Golgi membrane network.

    PubMed

    Senkal, Can E; Ponnusamy, Suriyan; Manevich, Yefim; Meyers-Needham, Marisa; Saddoughi, Sahar A; Mukhopadyay, Archana; Dent, Paul; Bielawski, Jacek; Ogretmen, Besim

    2011-12-09

    Mechanisms that regulate endoplasmic reticulum (ER) stress-induced apoptosis in cancer cells remain enigmatic. Recent data suggest that ceramide synthase1-6 (CerS1-6)-generated ceramides, containing different fatty acid chain lengths, might exhibit distinct and opposing functions, such as apoptosis versus survival in a context-dependent manner. Here, we investigated the mechanisms involved in the activation of one of the major ER stress response proteins, ATF-6, and subsequent apoptosis by alterations of CerS6/C(16)-ceramide. Induction of wild type (WT), but not the catalytically inactive mutant CerS6, increased tumor growth in SCID mice, whereas siRNA-mediated knockdown of CerS6 induced ATF-6 activation and apoptosis in multiple human cancer cells. Down-regulation of CerS6/C(16)-ceramide, and not its further metabolism to glucosylceramide or sphingomyelin, activated ATF-6 upon treatment with ER stress inducers tunicamycin or SAHA (suberoylanilide hydroxamic acid). Induction of WT-CerS6 expression, but not its mutant, or ectopic expression of the dominant-negative mutant form of ATF-6 protected cells from apoptosis in response to CerS6 knockdown and tunicamycin or SAHA treatment. Mechanistically, ATF-6 activation was regulated by a concerted two-step process involving the release of Ca(2+) from the ER stores ([Ca(2+)](ER)), which resulted in the fragmentation of Golgi membranes in response to CerS6/C(16)-ceramide alteration. This resulted in the accumulation of pro-ATF-6 in the disrupted ER/Golgi membrane network, where pro-ATF6 is activated. Accordingly, ectopic expression of a Ca(2+) chelator calbindin prevented the Golgi fragmentation, ATF-6 activation, and apoptosis in response to CerS6/C(16)-ceramide down-regulation. Overall, these data suggest a novel mechanism of how CerS6/C(16)-ceramide alteration activates ATF6 and induces ER-stress-mediated apoptosis in squamous cell carcinomas.

  2. A new approach to compute accurate velocity of meteors

    NASA Astrophysics Data System (ADS)

    Egal, Auriane; Gural, Peter; Vaubaillon, Jeremie; Colas, Francois; Thuillot, William

    2016-10-01

    The CABERNET project was designed to push the limits of meteoroid orbit measurements by improving the determination of the meteors' velocities. Indeed, despite of the development of the cameras networks dedicated to the observation of meteors, there is still an important discrepancy between the measured orbits of meteoroids computed and the theoretical results. The gap between the observed and theoretic semi-major axis of the orbits is especially significant; an accurate determination of the orbits of meteoroids therefore largely depends on the computation of the pre-atmospheric velocities. It is then imperative to dig out how to increase the precision of the measurements of the velocity.In this work, we perform an analysis of different methods currently used to compute the velocities and trajectories of the meteors. They are based on the intersecting planes method developed by Ceplecha (1987), the least squares method of Borovicka (1990), and the multi-parameter fitting (MPF) method published by Gural (2012).In order to objectively compare the performances of these techniques, we have simulated realistic meteors ('fakeors') reproducing the different error measurements of many cameras networks. Some fakeors are built following the propagation models studied by Gural (2012), and others created by numerical integrations using the Borovicka et al. 2007 model. Different optimization techniques have also been investigated in order to pick the most suitable one to solve the MPF, and the influence of the geometry of the trajectory on the result is also presented.We will present here the results of an improved implementation of the multi-parameter fitting that allow an accurate orbit computation of meteors with CABERNET. The comparison of different velocities computation seems to show that if the MPF is by far the best method to solve the trajectory and the velocity of a meteor, the ill-conditioning of the costs functions used can lead to large estimate errors for noisy

  3. Policy-Enabled Handoffs Across Heterogeneous Wireless Networks

    DTIC Science & Technology

    1998-12-17

    infrared, radio wireless LAN, cellular and satellite networks as an overlaid structure of room-size, building- 1 Report Documentation Page Form... Cellular Modem. Nonetheless, it is net- work independent. Any network in any numbers can be used in the system. We choose these networks because they...and GSM Cellular are on the third overlay with similar bandwidth but lower than WaveLAN’s bandwidth, and both have wide area coverage. The rest of the

  4. Continuum representations of cellular solids

    NASA Astrophysics Data System (ADS)

    Neilsen, M. K.

    1993-09-01

    Cellular materials consist of interconnected struts or plates which form cells. The struts or plates are constructed from a variety of metals, polymers, ceramics, and wood products. Cellular materials are often used in impact limiters for shipping containers to protect the contents from accidental impact events. These materials exhibit a variety of complex behavior when subjected to crushing loads. This research focuses on the development of continuum representations of cellular solids that can be used in the finite element analysis of shipping container accidents. A significant portion of this work is the development of a new methodology to relate localized deformations to appropriate constitutive descriptions. This methodology provides the insight needed to select constitutive descriptions for cellular solids that capture the localized deformations that are observed experimentally. Constitutive relations are developed for two different cellular materials, aluminum honeycomb and polyurethane foam. These constitutive relations are based on plasticity and continuum damage theories. Plasticity is used to describe the permanent deformation exhibited by both aluminum honeycomb and polyurethane foam. Continuum damage is needed to capture the change in elastic parameters due to cracking of the polyurethane cell wall materials. The new constitutive description of polyurethane foam is implemented in both static and dynamic finite element codes, and analytical and numerical predictions are compared with available experimental data.

  5. Classifying cellular automata using grossone

    NASA Astrophysics Data System (ADS)

    D'Alotto, Louis

    2016-10-01

    This paper proposes an application of the Infinite Unit Axiom and grossone, introduced by Yaroslav Sergeyev (see [7] - [12]), to the development and classification of one and two-dimensional cellular automata. By the application of grossone, new and more precise nonarchimedean metrics on the space of definition for one and two-dimensional cellular automata are established. These new metrics allow us to do computations with infinitesimals. Hence configurations in the domain space of cellular automata can be infinitesimally close (but not equal). That is, they can agree at infinitely many places. Using the new metrics, open disks are defined and the number of points in each disk computed. The forward dynamics of a cellular automaton map are also studied by defined sets. It is also shown that using the Infinite Unit Axiom, the number of configurations that follow a given configuration, under the forward iterations of cellular automaton maps, can now be computed and hence a classification scheme developed based on this computation.

  6. Continuum representations of cellular solids

    SciTech Connect

    Neilsen, M.K.

    1993-09-01

    Cellular materials consist of interconnected struts or plates which form cells. The struts or plates are constructed from a variety of metals, polymers, ceramics and wood products. Cellular materials are often used in impact limiters for shipping containers to protect the contents from accidental impact events. These materials exhibit a variety of complex behavior when subjected to crushing loads. This research focuses on the development of continuum representations of cellular solids that can be used in the finite element analysis of shipping container accidents. A significant portion of this work is the development of a new methodology to relate localized deformations to appropriate constitutive descriptions. This methodology provides the insight needed to select constitutive descriptions for cellular solids that capture the localized deformations that are observed experimentally. Constitutive relations are developed for two different cellular materials, aluminum honeycomb and polyurethane foam. These constitutive relations are based on plasticity and continuum damage theories. Plasticity is used to describe the permanent deformation exhibited by both aluminum honeycomb and polyurethane foam. Continuum damage is needed to capture the change in elastic parameters due to cracking of the polyurethane cell wall materials. The new constitutive description of polyurethane foam is implemented in both static and dynamic finite element codes, and analytical and numerical predictions are compared with available experimental data.

  7. High Frequency QRS ECG Accurately Detects Cardiomyopathy

    NASA Technical Reports Server (NTRS)

    Schlegel, Todd T.; Arenare, Brian; Poulin, Gregory; Moser, Daniel R.; Delgado, Reynolds

    2005-01-01

    High frequency (HF, 150-250 Hz) analysis over the entire QRS interval of the ECG is more sensitive than conventional ECG for detecting myocardial ischemia. However, the accuracy of HF QRS ECG for detecting cardiomyopathy is unknown. We obtained simultaneous resting conventional and HF QRS 12-lead ECGs in 66 patients with cardiomyopathy (EF = 23.2 plus or minus 6.l%, mean plus or minus SD) and in 66 age- and gender-matched healthy controls using PC-based ECG software recently developed at NASA. The single most accurate ECG parameter for detecting cardiomyopathy was an HF QRS morphological score that takes into consideration the total number and severity of reduced amplitude zones (RAZs) present plus the clustering of RAZs together in contiguous leads. This RAZ score had an area under the receiver operator curve (ROC) of 0.91, and was 88% sensitive, 82% specific and 85% accurate for identifying cardiomyopathy at optimum score cut-off of 140 points. Although conventional ECG parameters such as the QRS and QTc intervals were also significantly longer in patients than controls (P less than 0.001, BBBs excluded), these conventional parameters were less accurate (area under the ROC = 0.77 and 0.77, respectively) than HF QRS morphological parameters for identifying underlying cardiomyopathy. The total amplitude of the HF QRS complexes, as measured by summed root mean square voltages (RMSVs), also differed between patients and controls (33.8 plus or minus 11.5 vs. 41.5 plus or minus 13.6 mV, respectively, P less than 0.003), but this parameter was even less accurate in distinguishing the two groups (area under ROC = 0.67) than the HF QRS morphologic and conventional ECG parameters. Diagnostic accuracy was optimal (86%) when the RAZ score from the HF QRS ECG and the QTc interval from the conventional ECG were used simultaneously with cut-offs of greater than or equal to 40 points and greater than or equal to 445 ms, respectively. In conclusion 12-lead HF QRS ECG employing

  8. Overview of molecular, cellular, and genetic neurotoxicology.

    PubMed

    Wallace, David R

    2005-05-01

    It has become increasingly evident that the field of neurotoxicology is not only rapidly growing but also rapidly evolving, especially over the last 20 years. As the number of drugs and environmental and bacterial/viral agents with potential neurotoxic properties has grown, the need for additional testing has increased. Only recently has the technology advanced to a level that neurotoxicologic studies can be performed without operating in a "black box." Examination of the effects of agents that are suspected of being toxic can occur on the molecular (protein-protein), cellular (biomarkers, neuronal function), and genetic (polymorphisms) level. Together, these areas help to elucidate the potential toxic profiles of unknown (and in some cases, known) agents. The area of proteomics is one of the fastest growing areas in science and particularly applicable to neurotoxicology. Lubec et al, provide a review of the potential and limitations of proteomics. Proteomics focuses on a more comprehensive view of cellular proteins and provides considerably more information about the effects of toxins on the CNS. Proteomics can be classified into three different focuses: post-translational modification, protein-expression profiling, and protein-network mapping. Together, these methods represent a more complete and powerful image of protein modifications following potential toxin exposure. Cellular neurotoxicology involves many cellular processes including alterations in cellular energy homeostasis, ion homeostasis, intracellular signaling function, and neurotransmitter release, uptake, and storage. The greatest hurdle in cellular neurotoxicology has been the discovery of appropriate biomarkers that are reliable, reproducible, and easy to obtain. There are biomarkers of exposure effect, and susceptibility. Finding the appropriate biomarker for a particular toxin is a daunting task. The appropriate biomarker for a particular toxin is a daunting task. The advantage to biomarker

  9. A nexus for cellular homeostasis: the interplay between metabolic and signal transduction pathways.

    PubMed

    Gomes, Ana P; Blenis, John

    2015-08-01

    In multicellular organisms, individual cells have evolved to sense external and internal cues in order to maintain cellular homeostasis and survive under different environmental conditions. Cells efficiently adjust their metabolism to reflect the abundance of nutrients, energy and growth factors. The ability to rewire cellular metabolism between anabolic and catabolic processes is crucial for cells to thrive. Thus, cells have developed, through evolution, metabolic networks that are highly plastic and tightly regulated to meet the requirements necessary to maintain cellular homeostasis. The plasticity of these cellular systems is tightly regulated by complex signaling networks that integrate the intracellular and extracellular information. The coordination of signal transduction and metabolic pathways is essential in maintaining a healthy and rapidly responsive cellular state.

  10. Arrayed cellular environments for stem cells and regenerative medicine.

    PubMed

    Titmarsh, Drew M; Chen, Huaying; Wolvetang, Ernst J; Cooper-White, Justin J

    2013-02-01

    The behavior and composition of both multipotent and pluripotent stem cell populations are exquisitely controlled by a complex, spatiotemporally variable interplay of physico-chemical, extracellular matrix, cell-cell interaction, and soluble factor cues that collectively define the stem cell niche. The push for stem cell-based regenerative medicine models and therapies has fuelled demands for increasingly accurate cellular environmental control and enhanced experimental throughput, driving an evolution of cell culture platforms away from conventional culture formats toward integrated systems. Arrayed cellular environments typically provide a set of discrete experimental elements with variation of one or several classes of stimuli across elements of the array. These are based on high-content/high-throughput detection, small sample volumes, and multiplexing of environments to increase experimental parameter space, and can be used to address a range of biological processes at the cell population, single-cell, or subcellular level. Arrayed cellular environments have the capability to provide an unprecedented understanding of the molecular and cellular events that underlie expansion and specification of stem cell and therapeutic cell populations, and thus generate successful regenerative medicine outcomes. This review focuses on recent key developments of arrayed cellular environments and their contribution and potential in stem cells and regenerative medicine.

  11. Fracture mechanics of cellular glass

    NASA Technical Reports Server (NTRS)

    Zwissler, J. G.; Adams, M. A.

    1981-01-01

    The fracture mechanics of cellular glasses (for the structural substrate of mirrored glass for solr concentrator reflecting panels) are discussed. Commercial and developmental cellular glasses were tested and analyzed using standard testing techniques and models developed from linear fracture mechanics. Two models describing the fracture behavior of these materials were developed. Slow crack growth behavior in cellular glass was found to be more complex than that encountered in dense glasses or ceramics. The crack velocity was found to be strongly dependent upon water vapor transport to the tip of the moving crack. The existence of a static fatigue limit was not conclusively established, however, it is speculated that slow crack growth behavior in Region 1 may be slower, by orders of magnitude, than that found in dense glasses.

  12. Cellular-based preemption system

    NASA Technical Reports Server (NTRS)

    Bachelder, Aaron D. (Inventor)

    2011-01-01

    A cellular-based preemption system that uses existing cellular infrastructure to transmit preemption related data to allow safe passage of emergency vehicles through one or more intersections. A cellular unit in an emergency vehicle is used to generate position reports that are transmitted to the one or more intersections during an emergency response. Based on this position data, the one or more intersections calculate an estimated time of arrival (ETA) of the emergency vehicle, and transmit preemption commands to traffic signals at the intersections based on the calculated ETA. Additional techniques may be used for refining the position reports, ETA calculations, and the like. Such techniques include, without limitation, statistical preemption, map-matching, dead-reckoning, augmented navigation, and/or preemption optimization techniques, all of which are described in further detail in the above-referenced patent applications.

  13. Percolation on Sparse Networks

    NASA Astrophysics Data System (ADS)

    Karrer, Brian; Newman, M. E. J.; Zdeborová, Lenka

    2014-11-01

    We study percolation on networks, which is used as a model of the resilience of networked systems such as the Internet to attack or failure and as a simple model of the spread of disease over human contact networks. We reformulate percolation as a message passing process and demonstrate how the resulting equations can be used to calculate, among other things, the size of the percolating cluster and the average cluster size. The calculations are exact for sparse networks when the number of short loops in the network is small, but even on networks with many short loops we find them to be highly accurate when compared with direct numerical simulations. By considering the fixed points of the message passing process, we also show that the percolation threshold on a network with few loops is given by the inverse of the leading eigenvalue of the so-called nonbacktracking matrix.

  14. Cellular models for Parkinson's disease.

    PubMed

    Falkenburger, Björn H; Saridaki, Theodora; Dinter, Elisabeth

    2016-10-01

    Developing new therapeutic strategies for Parkinson's disease requires cellular models. Current models reproduce the two most salient changes found in the brains of patients with Parkinson's disease: The degeneration of dopaminergic neurons and the existence of protein aggregates consisting mainly of α-synuclein. Cultured cells offer many advantages over studying Parkinson's disease directly in patients or in animal models. At the same time, the choice of a specific cellular model entails the requirement to focus on one aspect of the disease while ignoring others. This article is intended for researchers planning to use cellular models for their studies. It describes for commonly used cell types the aspects of Parkinson's disease they model along with technical advantages and disadvantages. It might also be helpful for researchers from other fields consulting literature on cellular models of Parkinson's disease. Important models for the study of dopaminergic neuron degeneration include Lund human mesencephalic cells and primary neurons, and a case is made for the use of non-dopaminergic cells to model pathogenesis of non-motor symptoms of Parkinson's disease. With regard to α-synuclein aggregates, this article describes strategies to induce and measure aggregates with a focus on fluorescent techniques. Cellular models reproduce the two most salient changes of Parkinson's disease, the degeneration of dopaminergic neurons and the existence of α-synuclein aggregates. This article is intended for researchers planning to use cellular models for their studies. It describes for commonly used cell types and treatments the aspects of Parkinson's disease they model along with technical advantages and disadvantages. Furthermore, this article describes strategies to induce and measure aggregates with a focus on fluorescent techniques. This article is part of a special issue on Parkinson disease.

  15. Methods for Determining the Cellular Functions of Vimentin Intermediate Filaments

    PubMed Central

    Ridge, Karen M.; Shumaker, Dale; Robert, Amélie; Hookway, Caroline; Gelfand, Vladimir I.; Janmey, Paul A.; Lowery, Jason; Guo, Ming; Weitz, David A.; Kuczmarski, Edward; Goldman, Robert D.

    2016-01-01

    The type III intermediate filament protein vimentin was once thought to function mainly as a static structural protein in the cytoskeleton of cells of mesenchymal origin. Now, however, vimentin is known to form a dynamic, flexible network that plays an important role in a number of signaling pathways. Here, we describe various methods that have been developed to investigate the cellular functions of the vimentin protein and intermediate filament network, including chemical disruption, photoactivation and photoconversion, biolayer interferometry, soluble bead binding assay, three-dimensional substrate experiments, collagen gel contraction, optical-tweezer active microrheology, and force spectrum microscopy. Using these techniques, the contributions of vimentin to essential cellular processes can be probed in ever further detail. PMID:26795478

  16. Cellular automaton for chimera states

    NASA Astrophysics Data System (ADS)

    García-Morales, Vladimir

    2016-04-01

    A minimalistic model for chimera states is presented. The model is a cellular automaton (CA) which depends on only one adjustable parameter, the range of the nonlocal coupling, and is built from elementary cellular automata and the majority (voting) rule. This suggests the universality of chimera-like behavior from a new point of view: Already simple CA rules based on the majority rule exhibit this behavior. After a short transient, we find chimera states for arbitrary initial conditions, the system spontaneously splitting into stable domains separated by static boundaries, some synchronously oscillating and the others incoherent. When the coupling range is local, nontrivial coherent structures with different periodicities are formed.

  17. Synthetic biology in cellular immunotherapy

    PubMed Central

    Chakravarti, Deboki; Wong, Wilson W.

    2015-01-01

    The adoptive transfer of genetically engineered T cells with cancer-targeting receptors has shown tremendous promise for eradicating tumors in clinical trials. This form of cellular immunotherapy presents a unique opportunity to incorporate advanced systems and synthetic biology approaches to create cancer therapeutics with novel functions. Here, we first review the development of synthetic receptors, switches, and circuits to control the location, duration, and strength of T cell activity against tumors. In addition, we discuss the cellular engineering and genome editing of host cells (or the chassis) to improve the efficacy of cell-based cancer therapeutics, and to reduce the time and cost of manufacturing. PMID:26088008

  18. Cellular basis of Alzheimer's disease.

    PubMed

    Bali, Jitin; Halima, Saoussen Ben; Felmy, Boas; Goodger, Zoe; Zurbriggen, Sebastian; Rajendran, Lawrence

    2010-12-01

    Alzheimer's disease (AD) is the most common form of neurodegenerative disease. A characteristic feature of the disease is the presence of amyloid-β (Aβ) which either in its soluble oligomeric form or in the plaque-associated form is causally linked to neurodegeneration. Aβ peptide is liberated from the membrane-spanning -amyloid precursor protein by sequential proteolytic processing employing β- and γ-secretases. All these proteins involved in the production of Aβ peptide are membrane associated and hence, membrane trafficking and cellular compartmentalization play important roles. In this review, we summarize the key cellular events that lead to the progression of AD.

  19. Cellular-resolution connectomics: challenges of dense neural circuit reconstruction.

    PubMed

    Helmstaedter, Moritz

    2013-06-01

    Neuronal networks are high-dimensional graphs that are packed into three-dimensional nervous tissue at extremely high density. Comprehensively mapping these networks is therefore a major challenge. Although recent developments in volume electron microscopy imaging have made data acquisition feasible for circuits comprising a few hundreds to a few thousands of neurons, data analysis is massively lagging behind. The aim of this perspective is to summarize and quantify the challenges for data analysis in cellular-resolution connectomics and describe current solutions involving online crowd-sourcing and machine-learning approaches.

  20. Accurate upwind methods for the Euler equations

    NASA Technical Reports Server (NTRS)

    Huynh, Hung T.

    1993-01-01

    A new class of piecewise linear methods for the numerical solution of the one-dimensional Euler equations of gas dynamics is presented. These methods are uniformly second-order accurate, and can be considered as extensions of Godunov's scheme. With an appropriate definition of monotonicity preservation for the case of linear convection, it can be shown that they preserve monotonicity. Similar to Van Leer's MUSCL scheme, they consist of two key steps: a reconstruction step followed by an upwind step. For the reconstruction step, a monotonicity constraint that preserves uniform second-order accuracy is introduced. Computational efficiency is enhanced by devising a criterion that detects the 'smooth' part of the data where the constraint is redundant. The concept and coding of the constraint are simplified by the use of the median function. A slope steepening technique, which has no effect at smooth regions and can resolve a contact discontinuity in four cells, is described. As for the upwind step, existing and new methods are applied in a manner slightly different from those in the literature. These methods are derived by approximating the Euler equations via linearization and diagonalization. At a 'smooth' interface, Harten, Lax, and Van Leer's one intermediate state model is employed. A modification for this model that can resolve contact discontinuities is presented. Near a discontinuity, either this modified model or a more accurate one, namely, Roe's flux-difference splitting. is used. The current presentation of Roe's method, via the conceptually simple flux-vector splitting, not only establishes a connection between the two splittings, but also leads to an admissibility correction with no conditional statement, and an efficient approximation to Osher's approximate Riemann solver. These reconstruction and upwind steps result in schemes that are uniformly second-order accurate and economical at smooth regions, and yield high resolution at discontinuities.

  1. Accurate measurement of unsteady state fluid temperature

    NASA Astrophysics Data System (ADS)

    Jaremkiewicz, Magdalena

    2017-03-01

    In this paper, two accurate methods for determining the transient fluid temperature were presented. Measurements were conducted for boiling water since its temperature is known. At the beginning the thermometers are at the ambient temperature and next they are immediately immersed into saturated water. The measurements were carried out with two thermometers of different construction but with the same housing outer diameter equal to 15 mm. One of them is a K-type industrial thermometer widely available commercially. The temperature indicated by the thermometer was corrected considering the thermometers as the first or second order inertia devices. The new design of a thermometer was proposed and also used to measure the temperature of boiling water. Its characteristic feature is a cylinder-shaped housing with the sheath thermocouple located in its center. The temperature of the fluid was determined based on measurements taken in the axis of the solid cylindrical element (housing) using the inverse space marching method. Measurements of the transient temperature of the air flowing through the wind tunnel using the same thermometers were also carried out. The proposed measurement technique provides more accurate results compared with measurements using industrial thermometers in conjunction with simple temperature correction using the inertial thermometer model of the first or second order. By comparing the results, it was demonstrated that the new thermometer allows obtaining the fluid temperature much faster and with higher accuracy in comparison to the industrial thermometer. Accurate measurements of the fast changing fluid temperature are possible due to the low inertia thermometer and fast space marching method applied for solving the inverse heat conduction problem.

  2. The first accurate description of an aurora

    NASA Astrophysics Data System (ADS)

    Schröder, Wilfried

    2006-12-01

    As technology has advanced, the scientific study of auroral phenomena has increased by leaps and bounds. A look back at the earliest descriptions of aurorae offers an interesting look into how medieval scholars viewed the subjects that we study.Although there are earlier fragmentary references in the literature, the first accurate description of the aurora borealis appears to be that published by the German Catholic scholar Konrad von Megenberg (1309-1374) in his book Das Buch der Natur (The Book of Nature). The book was written between 1349 and 1350.

  3. Determining accurate distances to nearby galaxies

    NASA Astrophysics Data System (ADS)

    Bonanos, Alceste Zoe

    2005-11-01

    Determining accurate distances to nearby or distant galaxies is a very simple conceptually, yet complicated in practice, task. Presently, distances to nearby galaxies are only known to an accuracy of 10-15%. The current anchor galaxy of the extragalactic distance scale is the Large Magellanic Cloud, which has large (10-15%) systematic uncertainties associated with it, because of its morphology, its non-uniform reddening and the unknown metallicity dependence of the Cepheid period-luminosity relation. This work aims to determine accurate distances to some nearby galaxies, and subsequently help reduce the error in the extragalactic distance scale and the Hubble constant H 0 . In particular, this work presents the first distance determination of the DIRECT Project to M33 with detached eclipsing binaries. DIRECT aims to obtain a new anchor galaxy for the extragalactic distance scale by measuring direct, accurate (to 5%) distances to two Local Group galaxies, M31 and M33, with detached eclipsing binaries. It involves a massive variability survey of these galaxies and subsequent photometric and spectroscopic follow-up of the detached binaries discovered. In this work, I also present a catalog of variable stars discovered in one of the DIRECT fields, M31Y, which includes 41 eclipsing binaries. Additionally, we derive the distance to the Draco Dwarf Spheroidal galaxy, with ~100 RR Lyrae found in our first CCD variability study of this galaxy. A "hybrid" method of discovering Cepheids with ground-based telescopes is described next. It involves applying the image subtraction technique on the images obtained from ground-based telescopes and then following them up with the Hubble Space Telescope to derive Cepheid period-luminosity distances. By re-analyzing ESO Very Large Telescope data on M83 (NGC 5236), we demonstrate that this method is much more powerful for detecting variability, especially in crowded fields. I finally present photometry for the Wolf-Rayet binary WR 20a

  4. New law requires 'medically accurate' lesson plans.

    PubMed

    1999-09-17

    The California Legislature has passed a bill requiring all textbooks and materials used to teach about AIDS be medically accurate and objective. Statements made within the curriculum must be supported by research conducted in compliance with scientific methods, and published in peer-reviewed journals. Some of the current lesson plans were found to contain scientifically unsupported and biased information. In addition, the bill requires material to be "free of racial, ethnic, or gender biases." The legislation is supported by a wide range of interests, but opposed by the California Right to Life Education Fund, because they believe it discredits abstinence-only material.

  5. The effect of extrinsic noise on cellular decision making

    NASA Astrophysics Data System (ADS)

    Roberts, Elijah; Assaf, Michael; Luthey-Schulten, Zaida; Goldenfeld, Nigel

    2013-03-01

    Many cellular processes are not deterministic, i.e., genetically identical cells can display different phenotypic behavior even in identical environments. Such processes involve cellular decision making, in which individual cells randomly make choices determining their fate. One view is that the stochastic nature of cellular decision making is due to noise present in the biomolecular interaction networks. Most previous work has focused on the role of intrinsic noise of these networks. Yet, especially in the high copy-number regime, extrinsic noise may be much more significant, likely governing the overall dynamics. Here we develop a theoretical framework describing the combined effect of intrinsic and extrinsic noise on the stochastic dynamics of genetic switches responsible for cellular decision making. We do so by devising a semi-classical theory accounting for extrinsic noise as an effective species. Our theory, corroborated by extensive Monte-Carlo simulations, is tested on a simple bistable self-regulating gene model, and is then generalized to gain insight on the behavior of the lac genetic switch under extrinsic noise. We show that extrinsic noise not only significantly lowers the escape time from a phenotypic state, but can fundamentally change the actual escape process.

  6. A class of cellular automata modeling winnerless competition

    NASA Astrophysics Data System (ADS)

    Afraimovich, V.; Ordaz, F. C.; Urías, J.

    2002-06-01

    Neural units introduced by Rabinovich et al. ("Sensory coding with dynamically competitive networks," UCSD and CIT, February 1999) motivate a class of cellular automata (CA) where spatio-temporal encoding is feasible. The spatio-temporal information capacity of a CA is estimated by the information capacity of the attractor set, which happens to be finitely specified. Two-dimensional CA are studied in detail. An example is given for which the attractor is not a subshift.

  7. Attractor Metabolic Networks

    PubMed Central

    De la Fuente, Ildefonso M.; Cortes, Jesus M.; Pelta, David A.; Veguillas, Juan

    2013-01-01

    Background The experimental observations and numerical studies with dissipative metabolic networks have shown that cellular enzymatic activity self-organizes spontaneously leading to the emergence of a Systemic Metabolic Structure in the cell, characterized by a set of different enzymatic reactions always locked into active states (metabolic core) while the rest of the catalytic processes are only intermittently active. This global metabolic structure was verified for Escherichia coli, Helicobacter pylori and Saccharomyces cerevisiae, and it seems to be a common key feature to all cellular organisms. In concordance with these observations, the cell can be considered a complex metabolic network which mainly integrates a large ensemble of self-organized multienzymatic complexes interconnected by substrate fluxes and regulatory signals, where multiple autonomous oscillatory and quasi-stationary catalytic patterns simultaneously emerge. The network adjusts the internal metabolic activities to the external change by means of flux plasticity and structural plasticity. Methodology/Principal Findings In order to research the systemic mechanisms involved in the regulation of the cellular enzymatic activity we have studied different catalytic activities of a dissipative metabolic network under different external stimuli. The emergent biochemical data have been analysed using statistical mechanic tools, studying some macroscopic properties such as the global information and the energy of the system. We have also obtained an equivalent Hopfield network using a Boltzmann machine. Our main result shows that the dissipative metabolic network can behave as an attractor metabolic network. Conclusions/Significance We have found that the systemic enzymatic activities are governed by attractors with capacity to store functional metabolic patterns which can be correctly recovered from specific input stimuli. The network attractors regulate the catalytic patterns, modify the efficiency

  8. Inferring network mechanisms: the Drosophila melanogaster protein interaction network.

    PubMed

    Middendorf, Manuel; Ziv, Etay; Wiggins, Chris H

    2005-03-01

    Naturally occurring networks exhibit quantitative features revealing underlying growth mechanisms. Numerous network mechanisms have recently been proposed to reproduce specific properties such as degree distributions or clustering coefficients. We present a method for inferring the mechanism most accurately capturing a given network topology, exploiting discriminative tools from machine learning. The Drosophila melanogaster protein network is confidently and robustly (to noise and training data subsampling) classified as a duplication-mutation-complementation network over preferential attachment, small-world, and a duplication-mutation mechanism without complementation. Systematic classification, rather than statistical study of specific properties, provides a discriminative approach to understand the design of complex networks.

  9. Quantitative Analysis of Cellular Metabolic Dissipative, Self-Organized Structures

    PubMed Central

    de la Fuente, Ildefonso Martínez

    2010-01-01

    One of the most important goals of the postgenomic era is understanding the metabolic dynamic processes and the functional structures generated by them. Extensive studies during the last three decades have shown that the dissipative self-organization of the functional enzymatic associations, the catalytic reactions produced during the metabolite channeling, the microcompartmentalization of these metabolic processes and the emergence of dissipative networks are the fundamental elements of the dynamical organization of cell metabolism. Here we present an overview of how mathematical models can be used to address the properties of dissipative metabolic structures at different organizational levels, both for individual enzymatic associations and for enzymatic networks. Recent analyses performed with dissipative metabolic networks have shown that unicellular organisms display a singular global enzymatic structure common to all living cellular organisms, which seems to be an intrinsic property of the functional metabolism as a whole. Mathematical models firmly based on experiments and their corresponding computational approaches are needed to fully grasp the molecular mechanisms of metabolic dynamical processes. They are necessary to enable the quantitative and qualitative analysis of the cellular catalytic reactions and also to help comprehend the conditions under which the structural dynamical phenomena and biological rhythms arise. Understanding the molecular mechanisms responsible for the metabolic dissipative structures is crucial for unraveling the dynamics of cellular life. PMID:20957111

  10. Accurate taxonomic assignment of short pyrosequencing reads.

    PubMed

    Clemente, José C; Jansson, Jesper; Valiente, Gabriel

    2010-01-01

    Ambiguities in the taxonomy dependent assignment of pyrosequencing reads are usually resolved by mapping each read to the lowest common ancestor in a reference taxonomy of all those sequences that match the read. This conservative approach has the drawback of mapping a read to a possibly large clade that may also contain many sequences not matching the read. A more accurate taxonomic assignment of short reads can be made by mapping each read to the node in the reference taxonomy that provides the best precision and recall. We show that given a suffix array for the sequences in the reference taxonomy, a short read can be mapped to the node of the reference taxonomy with the best combined value of precision and recall in time linear in the size of the taxonomy subtree rooted at the lowest common ancestor of the matching sequences. An accurate taxonomic assignment of short reads can thus be made with about the same efficiency as when mapping each read to the lowest common ancestor of all matching sequences in a reference taxonomy. We demonstrate the effectiveness of our approach on several metagenomic datasets of marine and gut microbiota.

  11. Accurate shear measurement with faint sources

    SciTech Connect

    Zhang, Jun; Foucaud, Sebastien; Luo, Wentao E-mail: walt@shao.ac.cn

    2015-01-01

    For cosmic shear to become an accurate cosmological probe, systematic errors in the shear measurement method must be unambiguously identified and corrected for. Previous work of this series has demonstrated that cosmic shears can be measured accurately in Fourier space in the presence of background noise and finite pixel size, without assumptions on the morphologies of galaxy and PSF. The remaining major source of error is source Poisson noise, due to the finiteness of source photon number. This problem is particularly important for faint galaxies in space-based weak lensing measurements, and for ground-based images of short exposure times. In this work, we propose a simple and rigorous way of removing the shear bias from the source Poisson noise. Our noise treatment can be generalized for images made of multiple exposures through MultiDrizzle. This is demonstrated with the SDSS and COSMOS/ACS data. With a large ensemble of mock galaxy images of unrestricted morphologies, we show that our shear measurement method can achieve sub-percent level accuracy even for images of signal-to-noise ratio less than 5 in general, making it the most promising technique for cosmic shear measurement in the ongoing and upcoming large scale galaxy surveys.

  12. Accurate pose estimation for forensic identification

    NASA Astrophysics Data System (ADS)

    Merckx, Gert; Hermans, Jeroen; Vandermeulen, Dirk

    2010-04-01

    In forensic authentication, one aims to identify the perpetrator among a series of suspects or distractors. A fundamental problem in any recognition system that aims for identification of subjects in a natural scene is the lack of constrains on viewing and imaging conditions. In forensic applications, identification proves even more challenging, since most surveillance footage is of abysmal quality. In this context, robust methods for pose estimation are paramount. In this paper we will therefore present a new pose estimation strategy for very low quality footage. Our approach uses 3D-2D registration of a textured 3D face model with the surveillance image to obtain accurate far field pose alignment. Starting from an inaccurate initial estimate, the technique uses novel similarity measures based on the monogenic signal to guide a pose optimization process. We will illustrate the descriptive strength of the introduced similarity measures by using them directly as a recognition metric. Through validation, using both real and synthetic surveillance footage, our pose estimation method is shown to be accurate, and robust to lighting changes and image degradation.

  13. Sparse and accurate high resolution SAR imaging

    NASA Astrophysics Data System (ADS)

    Vu, Duc; Zhao, Kexin; Rowe, William; Li, Jian

    2012-05-01

    We investigate the usage of an adaptive method, the Iterative Adaptive Approach (IAA), in combination with a maximum a posteriori (MAP) estimate to reconstruct high resolution SAR images that are both sparse and accurate. IAA is a nonparametric weighted least squares algorithm that is robust and user parameter-free. IAA has been shown to reconstruct SAR images with excellent side lobes suppression and high resolution enhancement. We first reconstruct the SAR images using IAA, and then we enforce sparsity by using MAP with a sparsity inducing prior. By coupling these two methods, we can produce a sparse and accurate high resolution image that are conducive for feature extractions and target classification applications. In addition, we show how IAA can be made computationally efficient without sacrificing accuracies, a desirable property for SAR applications where the size of the problems is quite large. We demonstrate the success