Formation of multiple networks

DEFF Research Database (Denmark)

Magnani, Matteo; Rossi, Luca

2013-01-01

we introduce the first network formation model for multiple networks. Network formation models are among the most popular tools in traditional network studies, because of both their practical and theoretical impact. However, existing models are not sufficient to describe the generation of multiple...

An optics-based variable-temperature assay system for characterizing thermodynamics of biomolecular reactions on solid support

Energy Technology Data Exchange (ETDEWEB)

Fei, Yiyan; Landry, James P.; Zhu, X. D., E-mail: xdzhu@physics.ucdavis.edu [Department of Physics, University of California, One Shields Avenue, Davis, California 95616 (United States); Li, Yanhong; Yu, Hai; Lau, Kam; Huang, Shengshu; Chokhawala, Harshal A.; Chen, Xi [Department of Chemistry, University of California, One Shields Avenue, Davis, California 95616 (United States)

2013-11-15

A biological state is equilibrium of multiple concurrent biomolecular reactions. The relative importance of these reactions depends on physiological temperature typically between 10 °C and 50 °C. Experimentally the temperature dependence of binding reaction constants reveals thermodynamics and thus details of these biomolecular processes. We developed a variable-temperature opto-fluidic system for real-time measurement of multiple (400–10 000) biomolecular binding reactions on solid supports from 10 °C to 60 °C within ±0.1 °C. We illustrate the performance of this system with investigation of binding reactions of plant lectins (carbohydrate-binding proteins) with 24 synthetic glycans (i.e., carbohydrates). We found that the lectin-glycan reactions in general can be enthalpy-driven, entropy-driven, or both, and water molecules play critical roles in the thermodynamics of these reactions.

Prediction of Biomolecular Complexes

KAUST Repository

Vangone, Anna; Oliva, Romina; Cavallo, Luigi; Bonvin, Alexandre M. J. J.

2017-01-01

Almost all processes in living organisms occur through specific interactions between biomolecules. Any dysfunction of those interactions can lead to pathological events. Understanding such interactions is therefore a crucial step in the investigation of biological systems and a starting point for drug design. In recent years, experimental studies have been devoted to unravel the principles of biomolecular interactions; however, due to experimental difficulties in solving the three-dimensional (3D) structure of biomolecular complexes, the number of available, high-resolution experimental 3D structures does not fulfill the current needs. Therefore, complementary computational approaches to model such interactions are necessary to assist experimentalists since a full understanding of how biomolecules interact (and consequently how they perform their function) only comes from 3D structures which provide crucial atomic details about binding and recognition processes. In this chapter we review approaches to predict biomolecular complexesBiomolecular complexes, introducing the concept of molecular dockingDocking, a technique which uses a combination of geometric, steric and energetics considerations to predict the 3D structure of a biological complex starting from the individual structures of its constituent parts. We provide a mini-guide about docking concepts, its potential and challenges, along with post-docking analysis and a list of related software.

Prediction of Biomolecular Complexes

KAUST Repository

Vangone, Anna

2017-04-12

Almost all processes in living organisms occur through specific interactions between biomolecules. Any dysfunction of those interactions can lead to pathological events. Understanding such interactions is therefore a crucial step in the investigation of biological systems and a starting point for drug design. In recent years, experimental studies have been devoted to unravel the principles of biomolecular interactions; however, due to experimental difficulties in solving the three-dimensional (3D) structure of biomolecular complexes, the number of available, high-resolution experimental 3D structures does not fulfill the current needs. Therefore, complementary computational approaches to model such interactions are necessary to assist experimentalists since a full understanding of how biomolecules interact (and consequently how they perform their function) only comes from 3D structures which provide crucial atomic details about binding and recognition processes. In this chapter we review approaches to predict biomolecular complexesBiomolecular complexes, introducing the concept of molecular dockingDocking, a technique which uses a combination of geometric, steric and energetics considerations to predict the 3D structure of a biological complex starting from the individual structures of its constituent parts. We provide a mini-guide about docking concepts, its potential and challenges, along with post-docking analysis and a list of related software.

Biomolecular Science (Fact Sheet)

Energy Technology Data Exchange (ETDEWEB)

2012-04-01

A brief fact sheet about NREL Photobiology and Biomolecular Science. The research goal of NREL's Biomolecular Science is to enable cost-competitive advanced lignocellulosic biofuels production by understanding the science critical for overcoming biomass recalcitrance and developing new product and product intermediate pathways. NREL's Photobiology focuses on understanding the capture of solar energy in photosynthetic systems and its use in converting carbon dioxide and water directly into hydrogen and advanced biofuels.

Converting biomolecular modelling data based on an XML representation.

Science.gov (United States)

Sun, Yudong; McKeever, Steve

2008-08-25

Biomolecular modelling has provided computational simulation based methods for investigating biological processes from quantum chemical to cellular levels. Modelling such microscopic processes requires atomic description of a biological system and conducts in fine timesteps. Consequently the simulations are extremely computationally demanding. To tackle this limitation, different biomolecular models have to be integrated in order to achieve high-performance simulations. The integration of diverse biomolecular models needs to convert molecular data between different data representations of different models. This data conversion is often non-trivial, requires extensive human input and is inevitably error prone. In this paper we present an automated data conversion method for biomolecular simulations between molecular dynamics and quantum mechanics/molecular mechanics models. Our approach is developed around an XML data representation called BioSimML (Biomolecular Simulation Markup Language). BioSimML provides a domain specific data representation for biomolecular modelling which can effciently support data interoperability between different biomolecular simulation models and data formats.

Converting Biomolecular Modelling Data Based on an XML Representation

Directory of Open Access Journals (Sweden)

Sun Yudong

2008-06-01

Full Text Available Biomolecular modelling has provided computational simulation based methods for investigating biological processes from quantum chemical to cellular levels. Modelling such microscopic processes requires atomic description of a biological system and conducts in fine timesteps. Consequently the simulations are extremely computationally demanding. To tackle this limitation, different biomolecular models have to be integrated in order to achieve high-performance simulations. The integration of diverse biomolecular models needs to convert molecular data between different data representations of different models. This data conversion is often non-trivial, requires extensive human input and is inevitably error prone. In this paper we present an automated data conversion method for biomolecular simulations between molecular dynamics and quantum mechanics/molecular mechanics models. Our approach is developed around an XML data representation called BioSimML (Biomolecular Simulation Markup Language. BioSimML provides a domain specific data representation for biomolecular modelling which can effciently support data interoperability between different biomolecular simulation models and data formats.

Design of an embedded inverse-feedforward biomolecular tracking controller for enzymatic reaction processes.

Science.gov (United States)

Foo, Mathias; Kim, Jongrae; Sawlekar, Rucha; Bates, Declan G

2017-04-06

Feedback control is widely used in chemical engineering to improve the performance and robustness of chemical processes. Feedback controllers require a 'subtractor' that is able to compute the error between the process output and the reference signal. In the case of embedded biomolecular control circuits, subtractors designed using standard chemical reaction network theory can only realise one-sided subtraction, rendering standard controller design approaches inadequate. Here, we show how a biomolecular controller that allows tracking of required changes in the outputs of enzymatic reaction processes can be designed and implemented within the framework of chemical reaction network theory. The controller architecture employs an inversion-based feedforward controller that compensates for the limitations of the one-sided subtractor that generates the error signals for a feedback controller. The proposed approach requires significantly fewer chemical reactions to implement than alternative designs, and should have wide applicability throughout the fields of synthetic biology and biological engineering.

A model system for targeted drug release triggered by biomolecular signals logically processed through enzyme logic networks.

Science.gov (United States)

Mailloux, Shay; Halámek, Jan; Katz, Evgeny

2014-03-07

A new Sense-and-Act system was realized by the integration of a biocomputing system, performing analytical processes, with a signal-responsive electrode. A drug-mimicking release process was triggered by biomolecular signals processed by different logic networks, including three concatenated AND logic gates or a 3-input OR logic gate. Biocatalytically produced NADH, controlled by various combinations of input signals, was used to activate the electrochemical system. A biocatalytic electrode associated with signal-processing "biocomputing" systems was electrically connected to another electrode coated with a polymer film, which was dissolved upon the formation of negative potential releasing entrapped drug-mimicking species, an enzyme-antibody conjugate, operating as a model for targeted immune-delivery and consequent "prodrug" activation. The system offers great versatility for future applications in controlled drug release and personalized medicine.

A variational approach to moment-closure approximations for the kinetics of biomolecular reaction networks

Science.gov (United States)

Bronstein, Leo; Koeppl, Heinz

2018-01-01

Approximate solutions of the chemical master equation and the chemical Fokker-Planck equation are an important tool in the analysis of biomolecular reaction networks. Previous studies have highlighted a number of problems with the moment-closure approach used to obtain such approximations, calling it an ad hoc method. In this article, we give a new variational derivation of moment-closure equations which provides us with an intuitive understanding of their properties and failure modes and allows us to correct some of these problems. We use mixtures of product-Poisson distributions to obtain a flexible parametric family which solves the commonly observed problem of divergences at low system sizes. We also extend the recently introduced entropic matching approach to arbitrary ansatz distributions and Markov processes, demonstrating that it is a special case of variational moment closure. This provides us with a particularly principled approximation method. Finally, we extend the above approaches to cover the approximation of multi-time joint distributions, resulting in a viable alternative to process-level approximations which are often intractable.

Biomolecular engineering for nanobio/bionanotechnology

Science.gov (United States)

Nagamune, Teruyuki

2017-04-01

Biomolecular engineering can be used to purposefully manipulate biomolecules, such as peptides, proteins, nucleic acids and lipids, within the framework of the relations among their structures, functions and properties, as well as their applicability to such areas as developing novel biomaterials, biosensing, bioimaging, and clinical diagnostics and therapeutics. Nanotechnology can also be used to design and tune the sizes, shapes, properties and functionality of nanomaterials. As such, there are considerable overlaps between nanotechnology and biomolecular engineering, in that both are concerned with the structure and behavior of materials on the nanometer scale or smaller. Therefore, in combination with nanotechnology, biomolecular engineering is expected to open up new fields of nanobio/bionanotechnology and to contribute to the development of novel nanobiomaterials, nanobiodevices and nanobiosystems. This review highlights recent studies using engineered biological molecules (e.g., oligonucleotides, peptides, proteins, enzymes, polysaccharides, lipids, biological cofactors and ligands) combined with functional nanomaterials in nanobio/bionanotechnology applications, including therapeutics, diagnostics, biosensing, bioanalysis and biocatalysts. Furthermore, this review focuses on five areas of recent advances in biomolecular engineering: (a) nucleic acid engineering, (b) gene engineering, (c) protein engineering, (d) chemical and enzymatic conjugation technologies, and (e) linker engineering. Precisely engineered nanobiomaterials, nanobiodevices and nanobiosystems are anticipated to emerge as next-generation platforms for bioelectronics, biosensors, biocatalysts, molecular imaging modalities, biological actuators, and biomedical applications.

Smartphones for cell and biomolecular detection.

Science.gov (United States)

Liu, Xiyuan; Lin, Tung-Yi; Lillehoj, Peter B

2014-11-01

Recent advances in biomedical science and technology have played a significant role in the development of new sensors and assays for cell and biomolecular detection. Generally, these efforts are aimed at reducing the complexity and costs associated with diagnostic testing so that it can be performed outside of a laboratory or hospital setting, requiring minimal equipment and user involvement. In particular, point-of-care (POC) testing offers immense potential for many important applications including medical diagnosis, environmental monitoring, food safety, and biosecurity. When coupled with smartphones, POC systems can offer portability, ease of use and enhanced functionality while maintaining performance. This review article focuses on recent advancements and developments in smartphone-based POC systems within the last 6 years with an emphasis on cell and biomolecular detection. These devices typically comprise multiple components, such as detectors, sample processors, disposable chips, batteries, and software, which are integrated with a commercial smartphone. One of the most important aspects of developing these systems is the integration of these components onto a compact and lightweight platform that requires minimal power. Researchers have demonstrated several promising approaches employing various detection schemes and device configurations, and it is expected that further developments in biosensors, battery technology and miniaturized electronics will enable smartphone-based POC technologies to become more mainstream tools in the scientific and biomedical communities.

A statistical nanomechanism of biomolecular patterning actuated by surface potential

Science.gov (United States)

Lin, Chih-Ting; Lin, Chih-Hao

2011-02-01

Biomolecular patterning on a nanoscale/microscale on chip surfaces is one of the most important techniques used in vitro biochip technologies. Here, we report upon a stochastic mechanics model we have developed for biomolecular patterning controlled by surface potential. The probabilistic biomolecular surface adsorption behavior can be modeled by considering the potential difference between the binding and nonbinding states. To verify our model, we experimentally implemented a method of electroactivated biomolecular patterning technology and the resulting fluorescence intensity matched the prediction of the developed model quite well. Based on this result, we also experimentally demonstrated the creation of a bovine serum albumin pattern with a width of 200 nm in 5 min operations. This submicron noncovalent-binding biomolecular pattern can be maintained for hours after removing the applied electrical voltage. These stochastic understandings and experimental results not only prove the feasibility of submicron biomolecular patterns on chips but also pave the way for nanoscale interfacial-bioelectrical engineering.

Thermodynamic properties of water solvating biomolecular surfaces

Science.gov (United States)

Heyden, Matthias

Changes in the potential energy and entropy of water molecules hydrating biomolecular interfaces play a significant role for biomolecular solubility and association. Free energy perturbation and thermodynamic integration methods allow calculations of free energy differences between two states from simulations. However, these methods are computationally demanding and do not provide insights into individual thermodynamic contributions, i.e. changes in the solvent energy or entropy. Here, we employ methods to spatially resolve distributions of hydration water thermodynamic properties in the vicinity of biomolecular surfaces. This allows direct insights into thermodynamic signatures of the hydration of hydrophobic and hydrophilic solvent accessible sites of proteins and small molecules and comparisons to ideal model surfaces. We correlate dynamic properties of hydration water molecules, i.e. translational and rotational mobility, to their thermodynamics. The latter can be used as a guide to extract thermodynamic information from experimental measurements of site-resolved water dynamics. Further, we study energy-entropy compensations of water at different hydration sites of biomolecular surfaces. This work is supported by the Cluster of Excellence RESOLV (EXC 1069) funded by the Deutsche Forschungsgemeinschaft.

Biomolecular EPR spectroscopy

CERN Document Server

Hagen, Wilfred Raymond

2008-01-01

Comprehensive, Up-to-Date Coverage of Spectroscopy Theory and its Applications to Biological SystemsAlthough a multitude of books have been published about spectroscopy, most of them only occasionally refer to biological systems and the specific problems of biomolecular EPR (bioEPR). Biomolecular EPR Spectroscopy provides a practical introduction to bioEPR and demonstrates how this remarkable tool allows researchers to delve into the structural, functional, and analytical analysis of paramagnetic molecules found in the biochemistry of all species on the planet. A Must-Have Reference in an Intrinsically Multidisciplinary FieldThis authoritative reference seamlessly covers all important bioEPR applications, including low-spin and high-spin metalloproteins, spin traps and spin lables, interaction between active sites, and redox systems. It is loaded with practical tricks as well as do's and don'ts that are based on the author's 30 years of experience in the field. The book also comes with an unprecedented set of...

Evaluation of Network Reliability for Computer Networks with Multiple Sources

Directory of Open Access Journals (Sweden)

Yi-Kuei Lin

2012-01-01

Full Text Available Evaluating the reliability of a network with multiple sources to multiple sinks is a critical issue from the perspective of quality management. Due to the unrealistic definition of paths of network models in previous literature, existing models are not appropriate for real-world computer networks such as the Taiwan Advanced Research and Education Network (TWAREN. This paper proposes a modified stochastic-flow network model to evaluate the network reliability of a practical computer network with multiple sources where data is transmitted through several light paths (LPs. Network reliability is defined as being the probability of delivering a specified amount of data from the sources to the sink. It is taken as a performance index to measure the service level of TWAREN. This paper studies the network reliability of the international portion of TWAREN from two sources (Taipei and Hsinchu to one sink (New York that goes through a submarine and land surface cable between Taiwan and the United States.

Multiple-Access Quantum-Classical Networks

Science.gov (United States)

Razavi, Mohsen

2011-10-01

A multi-user network that supports both classical and quantum communication is proposed. By relying on optical code-division multiple access techniques, this system offers simultaneous key exchange between multiple pairs of network users. A lower bound on the secure key generation rate will be derived for decoy-state quantum key distribution protocols.

Dynamic and label-free high-throughput detection of biomolecular interactions based on phase-shift interferometry

Science.gov (United States)

Li, Qiang; Huang, Guoliang; Gan, Wupeng; Chen, Shengyi

2009-08-01

Biomolecular interactions can be detected by many established technologies such as fluorescence imaging, surface plasmon resonance (SPR)[1-4], interferometry and radioactive labeling of the analyte. In this study, we have designed and constructed a label-free, real-time sensing platform and its operating imaging instrument that detects interactions using optical phase differences from the accumulation of biological material on solid substrates. This system allows us to monitor biomolecular interactions in real time and quantify concentration changes during micro-mixing processes by measuring the changes of the optical path length (OPD). This simple interferometric technology monitors the optical phase difference resulting from accumulated biomolecular mass. A label-free protein chip that forms a 4×4 probe array was designed and fabricated using a commercial microarray robot spotter on solid substrates. Two positive control probe lines of BSA (Bovine Serum Albumin) and two experimental human IgG and goat IgG was used. The binding of multiple protein targets was performed and continuously detected by using this label-free and real-time sensing platform.

Biomolecular condensates: organizers of cellular biochemistry.

Science.gov (United States)

Banani, Salman F; Lee, Hyun O; Hyman, Anthony A; Rosen, Michael K

2017-05-01

Biomolecular condensates are micron-scale compartments in eukaryotic cells that lack surrounding membranes but function to concentrate proteins and nucleic acids. These condensates are involved in diverse processes, including RNA metabolism, ribosome biogenesis, the DNA damage response and signal transduction. Recent studies have shown that liquid-liquid phase separation driven by multivalent macromolecular interactions is an important organizing principle for biomolecular condensates. With this physical framework, it is now possible to explain how the assembly, composition, physical properties and biochemical and cellular functions of these important structures are regulated.

Programming in biomolecular computation

DEFF Research Database (Denmark)

Hartmann, Lars Røeboe; Jones, Neil; Simonsen, Jakob Grue

2011-01-01

Our goal is to provide a top-down approach to biomolecular computation. In spite of widespread discussion about connections between biology and computation, one question seems notable by its absence: Where are the programs? We identify a number of common features in programming that seem...... conspicuously absent from the literature on biomolecular computing; to partially redress this absence, we introduce a model of computation that is evidently programmable, by programs reminiscent of low-level computer machine code; and at the same time biologically plausible: its functioning is defined...... by a single and relatively small set of chemical-like reaction rules. Further properties: the model is stored-program: programs are the same as data, so programs are not only executable, but are also compilable and interpretable. It is universal: all computable functions can be computed (in natural ways...

Improvements to the APBS biomolecular solvation software suite.

Science.gov (United States)

Jurrus, Elizabeth; Engel, Dave; Star, Keith; Monson, Kyle; Brandi, Juan; Felberg, Lisa E; Brookes, David H; Wilson, Leighton; Chen, Jiahui; Liles, Karina; Chun, Minju; Li, Peter; Gohara, David W; Dolinsky, Todd; Konecny, Robert; Koes, David R; Nielsen, Jens Erik; Head-Gordon, Teresa; Geng, Weihua; Krasny, Robert; Wei, Guo-Wei; Holst, Michael J; McCammon, J Andrew; Baker, Nathan A

2018-01-01

The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that have provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses the three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this article, we discuss the models and capabilities that have recently been implemented within the APBS software package including a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory-based algorithm for determining pK a values, and an improved web-based visualization tool for viewing electrostatics. © 2017 The Protein Society.

Synthetic tetracycline-inducible regulatory networks: computer-aided design of dynamic phenotypes

Directory of Open Access Journals (Sweden)

Kaznessis Yiannis N

2007-01-01

Full Text Available Abstract Background Tightly regulated gene networks, precisely controlling the expression of protein molecules, have received considerable interest by the biomedical community due to their promising applications. Among the most well studied inducible transcription systems are the tetracycline regulatory expression systems based on the tetracycline resistance operon of Escherichia coli, Tet-Off (tTA and Tet-On (rtTA. Despite their initial success and improved designs, limitations still persist, such as low inducer sensitivity. Instead of looking at these networks statically, and simply changing or mutating the promoter and operator regions with trial and error, a systematic investigation of the dynamic behavior of the network can result in rational design of regulatory gene expression systems. Sophisticated algorithms can accurately capture the dynamical behavior of gene networks. With computer aided design, we aim to improve the synthesis of regulatory networks and propose new designs that enable tighter control of expression. Results In this paper we engineer novel networks by recombining existing genes or part of genes. We synthesize four novel regulatory networks based on the Tet-Off and Tet-On systems. We model all the known individual biomolecular interactions involved in transcription, translation, regulation and induction. With multiple time-scale stochastic-discrete and stochastic-continuous models we accurately capture the transient and steady state dynamics of these networks. Important biomolecular interactions are identified and the strength of the interactions engineered to satisfy design criteria. A set of clear design rules is developed and appropriate mutants of regulatory proteins and operator sites are proposed. Conclusion The complexity of biomolecular interactions is accurately captured through computer simulations. Computer simulations allow us to look into the molecular level, portray the dynamic behavior of gene regulatory

Design of an embedded inverse-feedforward biomolecular tracking controller for enzymatic reaction processes

OpenAIRE

Foo, Mathias; Kim, Jongrae; Sawlekar, Rucha; Bates, Declan G.

2017-01-01

Feedback control is widely used in chemical engineering to improve the performance and robustness of chemical processes. Feedback controllers require a ‘subtractor’ that is able to compute the error between the process output and the reference signal. In the case of embedded biomolecular control circuits, subtractors designed using standard chemical reaction network theory can only realise one-sided subtraction, rendering standard controller design approaches inadequate. Here, we show how a b...

Biomolecular electrostatics and solvation: a computational perspective.

Science.gov (United States)

Ren, Pengyu; Chun, Jaehun; Thomas, Dennis G; Schnieders, Michael J; Marucho, Marcelo; Zhang, Jiajing; Baker, Nathan A

2012-11-01

An understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzyme catalysis, and dynamics. Electrostatics, therefore, are of central importance to understanding biomolecular structure and modeling interactions within and among biological molecules. This review discusses the solvation of biomolecules with a computational biophysics view toward describing the phenomenon. While our main focus lies on the computational aspect of the models, we provide an overview of the basic elements of biomolecular solvation (e.g. solvent structure, polarization, ion binding, and non-polar behavior) in order to provide a background to understand the different types of solvation models.

Concurrent conditional clustering of multiple networks: COCONETS.

Directory of Open Access Journals (Sweden)

Sabrina Kleessen

Full Text Available The accumulation of high-throughput data from different experiments has facilitated the extraction of condition-specific networks over the same set of biological entities. Comparing and contrasting of such multiple biological networks is in the center of differential network biology, aiming at determining general and condition-specific responses captured in the network structure (i.e., included associations between the network components. We provide a novel way for comparison of multiple networks based on determining network clustering (i.e., partition into communities which is optimal across the set of networks with respect to a given cluster quality measure. To this end, we formulate the optimization-based problem of concurrent conditional clustering of multiple networks, termed COCONETS, based on the modularity. The solution to this problem is a clustering which depends on all considered networks and pinpoints their preserved substructures. We present theoretical results for special classes of networks to demonstrate the implications of conditionality captured by the COCONETS formulation. As the problem can be shown to be intractable, we extend an existing efficient greedy heuristic and applied it to determine concurrent conditional clusters on coexpression networks extracted from publically available time-resolved transcriptomics data of Escherichia coli under five stresses as well as on metabolite correlation networks from metabolomics data set from Arabidopsis thaliana exposed to eight environmental conditions. We demonstrate that the investigation of the differences between the clustering based on all networks with that obtained from a subset of networks can be used to quantify the specificity of biological responses. While a comparison of the Escherichia coli coexpression networks based on seminal properties does not pinpoint biologically relevant differences, the common network substructures extracted by COCONETS are supported by

Multiple Social Networks, Data Models and Measures for

DEFF Research Database (Denmark)

Magnani, Matteo; Rossi, Luca

2017-01-01

Multiple Social Network Analysis is a discipline defining models, measures, methodologies, and algorithms to study multiple social networks together as a single social system. It is particularly valuable when the networks are interconnected, e.g., the same actors are present in more than one...

Conducting polymer based biomolecular electronic devices

Indian Academy of Sciences (India)

Conducting polymers; LB films; biosensor microactuators; monolayers. ... have been projected for applications for a wide range of biomolecular electronic devices such as optical, electronic, drug-delivery, memory and biosensing devices.

Diversity Performance Analysis on Multiple HAP Networks

Science.gov (United States)

Dong, Feihong; Li, Min; Gong, Xiangwu; Li, Hongjun; Gao, Fengyue

2015-01-01

One of the main design challenges in wireless sensor networks (WSNs) is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP) is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO) techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO) model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV). In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF) and cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) are derived. In addition, the average symbol error rate (ASER) with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI) and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques. PMID:26134102

Diversity Performance Analysis on Multiple HAP Networks

Directory of Open Access Journals (Sweden)

Feihong Dong

2015-06-01

Full Text Available One of the main design challenges in wireless sensor networks (WSNs is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV. In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF and cumulative distribution function (CDF of the received signal-to-noise ratio (SNR are derived. In addition, the average symbol error rate (ASER with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques.

Biomolecular simulation: historical picture and future perspectives.

Science.gov (United States)

van Gunsteren, Wilfred F; Dolenc, Jozica

2008-02-01

Over the last 30 years, computation based on molecular models is playing an increasingly important role in biology, biological chemistry and biophysics. Since only a very limited number of properties of biomolecular systems are actually accessible to measurement by experimental means, computer simulation complements experiments by providing not only averages, but also distributions and time series of any definable, observable or non-observable, quantity. Biomolecular simulation may be used (i) to interpret experimental data, (ii) to provoke new experiments, (iii) to replace experiments and (iv) to protect intellectual property. Progress over the last 30 years is sketched and perspectives are outlined for the future.

Innovation in Multiple Networks and Networks of Networks: The Case of the Fruit Sector in Emilia‐Romagna

Directory of Open Access Journals (Sweden)

Davide Viaggi

2013-02-01

Full Text Available In the paper we examine the issue of food systems in which farms participate in multiple networks that, for their part, tend also to be members of networks of networks. The issue is addressed through a descriptive analysis of the fruit sector in Emilia‐Romagna (Italy. The farms in the area tend to join a different network for each product/product type. Innovation networks are embedded in commercialization or input provider networks, but separate (parallel networks also exist, particularly for basic research activities. Networks of networks are largely a product of the cooperative system. The paper concludes by emphasising the need for further research in multiple networking strategies and the connection betweencommercialisation networks and innovation.

Networks amid multiple logics

DEFF Research Database (Denmark)

Bergenholtz, Carsten; Bjerregaard, Toke

The present study investigates how a high-tech-small-firm (HTSF) can carry out an inter-organizational search of actors located at universities. Responding to calls to study how firms navigate multiple institutional norms, this research examines the different strategies used by a HTSF to balance...... adopted academic norm-sets, commercial imperatives and formal regulations to support formation of networks and collaborations with universities. The findings show how the significance of weak and strong ties for the formation of collaborations and networks with universities is relative...

Application of Nanodiamonds in Biomolecular Mass Spectrometry

Directory of Open Access Journals (Sweden)

Ping Cheng

2010-03-01

Full Text Available The combination of nanodiamond (ND with biomolecular mass spectrometry (MS makes rapid, sensitive detection of biopolymers from complex biosamples feasible. Due to its chemical inertness, optical transparency and biocompatibility, the advantage of NDs in MS study is unique. Furthermore, functionalization on the surfaces of NDs expands their application in the fields of proteomics and genomics for specific requirements greatly. This review presents methods of MS analysis based on solid phase extraction and elution on NDs and different application examples including peptide, protein, DNA, glycan and others. Owing to the quick development of nanotechnology, surface chemistry, new MS methods and the intense interest in proteomics and genomics, a huge increase of their applications in biomolecular MS analysis in the near future can be predicted.

Laser photodissociation and spectroscopy of mass-separated biomolecular ions

CERN Document Server

Polfer, Nicolas C

2014-01-01

This lecture notes book presents how enhanced structural information of biomolecular ions can be obtained from interaction with photons of specific frequency - laser light. The methods described in the book ""Laser photodissociation and spectroscopy of mass-separated biomolecular ions"" make use of the fact that the discrete energy and fast time scale of photoexcitation can provide more control in ion activation. This activation is the crucial process producing structure-informative product ions that cannot be generated with more conventional heating methods, such as collisional activation. Th

PREFACE: Radiation Damage in Biomolecular Systems (RADAM07)

Science.gov (United States)

McGuigan, Kevin G.

2008-03-01

, which include: theoretical, experimental, medical and computational physicists, radiation chemists, radiation biologists and microbiologists, among others. An important aspect of the previous 3 conferences in this series was to remove barriers between the different working groups and to encourage a more interdisciplinary approach to research collaborations. During RADAM_07 we could observe the success of these efforts. A large number of presentations were based on new collaborations, many funded under the COST STSM programme, and all presentations led to lively discussions. It is clear from the discussions following many of the presentations and at the poster sessions that Radiation Damage in Biomolecular Systems remains a topic of increasing interest, relevance and importance. The success of this conference as well as of the whole RADAM conference series reflects the growing international interest in the area of interactions of ionizing radiation with biomolecules. Despite the scheduled conclusion in September 2007 of COST Action P9 which has part-funded this, and previous RADAM meetings, the nature of the cross-disciplinary interactions and opportunities for collaborative research was deemed so successful and valuable by the assembled delegates that it was agreed that another such meeting should be held in Debrecen in Hungary from 13-15 June 2008 http://www.isa.au.dk/meetings/radam2008/programme.html. Additional information about RADAM07 programme is available on the conference web-page http://www.isa.au.dk/networks/cost/radam07/index.html. The Organizing Committee would like to thank all speakers, contributors, session chairs, referees and meeting staff for their efforts in making the RADAM07 successful. The local Organization Committee would like to thank Lorraine Monard and Margaret Nolan for their invaluable expertise in conference management. We also gratefully acknowledge the financial support of our sponsors - The Royal, College of Surgeons in Ireland (RCSI

Protocol for multiple node network

Science.gov (United States)

Kirkham, Harold (Inventor)

1995-01-01

The invention is a multiple interconnected network of intelligent message-repeating remote nodes which employs an antibody recognition message termination process performed by all remote nodes and a remote node polling process performed by other nodes which are master units controlling remote nodes in respective zones of the network assigned to respective master nodes. Each remote node repeats only those messages originated in the local zone, to provide isolation among the master nodes.

Perspective: Watching low-frequency vibrations of water in biomolecular recognition by THz spectroscopy

Science.gov (United States)

Xu, Yao; Havenith, Martina

2015-11-01

Terahertz (THz) spectroscopy has turned out to be a powerful tool which is able to shed new light on the role of water in biomolecular processes. The low frequency spectrum of the solvated biomolecule in combination with MD simulations provides deep insights into the collective hydrogen bond dynamics on the sub-ps time scale. The absorption spectrum between 1 THz and 10 THz of solvated biomolecules is sensitive to changes in the fast fluctuations of the water network. Systematic studies on mutants of antifreeze proteins indicate a direct correlation between biological activity and a retardation of the (sub)-ps hydration dynamics at the protein binding site, i.e., a "hydration funnel." Kinetic THz absorption studies probe the temporal changes of THz absorption during a biological process, and give access to the kinetics of the coupled protein-hydration dynamics. When combined with simulations, the observed results can be explained in terms of a two-tier model involving a local binding and a long range influence on the hydration bond dynamics of the water around the binding site that highlights the significance of the changes in the hydration dynamics at recognition site for biomolecular recognition. Water is shown to assist molecular recognition processes.

Multiple routes transmitted epidemics on multiplex networks

International Nuclear Information System (INIS)

Zhao, Dawei; Li, Lixiang; Peng, Haipeng; Luo, Qun; Yang, Yixian

2014-01-01

This letter investigates the multiple routes transmitted epidemic process on multiplex networks. We propose detailed theoretical analysis that allows us to accurately calculate the epidemic threshold and outbreak size. It is found that the epidemic can spread across the multiplex network even if all the network layers are well below their respective epidemic thresholds. Strong positive degree–degree correlation of nodes in multiplex network could lead to a much lower epidemic threshold and a relatively smaller outbreak size. However, the average similarity of neighbors from different layers of nodes has no obvious effect on the epidemic threshold and outbreak size. -- Highlights: •We studies multiple routes transmitted epidemic process on multiplex networks. •SIR model and bond percolation theory are used to analyze the epidemic processes. •We derive equations to accurately calculate the epidemic threshold and outbreak size. •ASN has no effect on the epidemic threshold and outbreak size. •Strong positive DDC leads to a lower epidemic threshold and a smaller outbreak size.

Multiple routes transmitted epidemics on multiplex networks

Energy Technology Data Exchange (ETDEWEB)

Zhao, Dawei [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China); National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China); Shandong Provincial Key Laboratory of Computer Network, Shandong Computer Science Center, Jinan 250014 (China); Li, Lixiang [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China); National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China); Peng, Haipeng, E-mail: penghaipeng@bupt.edu.cn [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China); National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China); Luo, Qun; Yang, Yixian [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China); National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China)

2014-02-01

This letter investigates the multiple routes transmitted epidemic process on multiplex networks. We propose detailed theoretical analysis that allows us to accurately calculate the epidemic threshold and outbreak size. It is found that the epidemic can spread across the multiplex network even if all the network layers are well below their respective epidemic thresholds. Strong positive degree–degree correlation of nodes in multiplex network could lead to a much lower epidemic threshold and a relatively smaller outbreak size. However, the average similarity of neighbors from different layers of nodes has no obvious effect on the epidemic threshold and outbreak size. -- Highlights: •We studies multiple routes transmitted epidemic process on multiplex networks. •SIR model and bond percolation theory are used to analyze the epidemic processes. •We derive equations to accurately calculate the epidemic threshold and outbreak size. •ASN has no effect on the epidemic threshold and outbreak size. •Strong positive DDC leads to a lower epidemic threshold and a smaller outbreak size.

NMRbox: A Resource for Biomolecular NMR Computation.

Science.gov (United States)

Maciejewski, Mark W; Schuyler, Adam D; Gryk, Michael R; Moraru, Ion I; Romero, Pedro R; Ulrich, Eldon L; Eghbalnia, Hamid R; Livny, Miron; Delaglio, Frank; Hoch, Jeffrey C

2017-04-25

Advances in computation have been enabling many recent advances in biomolecular applications of NMR. Due to the wide diversity of applications of NMR, the number and variety of software packages for processing and analyzing NMR data is quite large, with labs relying on dozens, if not hundreds of software packages. Discovery, acquisition, installation, and maintenance of all these packages is a burdensome task. Because the majority of software packages originate in academic labs, persistence of the software is compromised when developers graduate, funding ceases, or investigators turn to other projects. To simplify access to and use of biomolecular NMR software, foster persistence, and enhance reproducibility of computational workflows, we have developed NMRbox, a shared resource for NMR software and computation. NMRbox employs virtualization to provide a comprehensive software environment preconfigured with hundreds of software packages, available as a downloadable virtual machine or as a Platform-as-a-Service supported by a dedicated compute cloud. Ongoing development includes a metadata harvester to regularize, annotate, and preserve workflows and facilitate and enhance data depositions to BioMagResBank, and tools for Bayesian inference to enhance the robustness and extensibility of computational analyses. In addition to facilitating use and preservation of the rich and dynamic software environment for biomolecular NMR, NMRbox fosters the development and deployment of a new class of metasoftware packages. NMRbox is freely available to not-for-profit users. Copyright © 2017 Biophysical Society. All rights reserved.

Insights Into the Bifunctional Aphidicolan-16-ß-ol Synthase Through Rapid Biomolecular Modeling Approaches

Directory of Open Access Journals (Sweden)

Max Hirte

2018-04-01

Full Text Available Diterpene synthases catalyze complex, multi-step C-C coupling reactions thereby converting the universal, aliphatic precursor geranylgeranyl diphosphate into diverse olefinic macrocylces that form the basis for the structural diversity of the diterpene natural product family. Since catalytically relevant crystal structures of diterpene synthases are scarce, homology based biomolecular modeling techniques offer an alternative route to study the enzyme's reaction mechanism. However, precise identification of catalytically relevant amino acids is challenging since these models require careful preparation and refinement techniques prior to substrate docking studies. Targeted amino acid substitutions in this protein class can initiate premature quenching of the carbocation centered reaction cascade. The structural characterization of those alternative cyclization products allows for elucidation of the cyclization reaction cascade and provides a new source for complex macrocyclic synthons. In this study, new insights into structure and function of the fungal, bifunctional Aphidicolan-16-ß-ol synthase were achieved using a simplified biomolecular modeling strategy. The applied refinement methodologies could rapidly generate a reliable protein-ligand complex, which provides for an accurate in silico identification of catalytically relevant amino acids. Guided by our modeling data, ACS mutations lead to the identification of the catalytically relevant ACS amino acid network I626, T657, Y658, A786, F789, and Y923. Moreover, the ACS amino acid substitutions Y658L and D661A resulted in a premature termination of the cyclization reaction cascade en-route from syn-copalyl diphosphate to Aphidicolan-16-ß-ol. Both ACS mutants generated the diterpene macrocycle syn-copalol and a minor, non-hydroxylated labdane related diterpene, respectively. Our biomolecular modeling and mutational studies suggest that the ACS substrate cyclization occurs in a spatially

Insights Into the Bifunctional Aphidicolan-16-ß-ol Synthase Through Rapid Biomolecular Modeling Approaches.

Science.gov (United States)

Hirte, Max; Meese, Nicolas; Mertz, Michael; Fuchs, Monika; Brück, Thomas B

2018-01-01

Diterpene synthases catalyze complex, multi-step C-C coupling reactions thereby converting the universal, aliphatic precursor geranylgeranyl diphosphate into diverse olefinic macrocylces that form the basis for the structural diversity of the diterpene natural product family. Since catalytically relevant crystal structures of diterpene synthases are scarce, homology based biomolecular modeling techniques offer an alternative route to study the enzyme's reaction mechanism. However, precise identification of catalytically relevant amino acids is challenging since these models require careful preparation and refinement techniques prior to substrate docking studies. Targeted amino acid substitutions in this protein class can initiate premature quenching of the carbocation centered reaction cascade. The structural characterization of those alternative cyclization products allows for elucidation of the cyclization reaction cascade and provides a new source for complex macrocyclic synthons. In this study, new insights into structure and function of the fungal, bifunctional Aphidicolan-16-ß-ol synthase were achieved using a simplified biomolecular modeling strategy. The applied refinement methodologies could rapidly generate a reliable protein-ligand complex, which provides for an accurate in silico identification of catalytically relevant amino acids. Guided by our modeling data, ACS mutations lead to the identification of the catalytically relevant ACS amino acid network I626, T657, Y658, A786, F789, and Y923. Moreover, the ACS amino acid substitutions Y658L and D661A resulted in a premature termination of the cyclization reaction cascade en-route from syn-copalyl diphosphate to Aphidicolan-16-ß-ol. Both ACS mutants generated the diterpene macrocycle syn-copalol and a minor, non-hydroxylated labdane related diterpene, respectively. Our biomolecular modeling and mutational studies suggest that the ACS substrate cyclization occurs in a spatially restricted location of

Insights into the bifunctional Aphidicolan-16-ß-ol synthase through rapid biomolecular modelling approaches

Science.gov (United States)

Hirte, Max; Meese, Nicolas; Mertz, Michael; Fuchs, Monika; Brück, Thomas B.

2018-04-01

Diterpene synthases catalyze complex, multi-step C-C coupling reactions thereby converting the universal, aliphatic precursor geranylgeranyl diphosphate into diverse olefinic macrocylces that form the basis for the structural diversity of the diterpene natural product family. Since catalytically relevant crystal structures of diterpene synthases are scarce, homology based biomolecular modelling techniques offer an alternative route to study the enzyme’s reaction mechanism. However, precise identification of catalytically relevant amino acids is challenging since these models require careful preparation and refinement techniques prior to substrate docking studies. Targeted amino acid substitutions in this protein class can initiate premature quenching of the carbocation centered reaction cascade. The structural characterization of those alternative cyclization products allows for elucidation of the cyclization reaction cascade and provides a new source for complex macrocyclic synthons. In this study, new insights into structure and function of the fungal, bifunctional Aphidicolan-16-ß-ol synthase were achieved using a simplified biomolecular modelling strategy. The applied refinement methodologies could rapidly generate a reliable protein-ligand complex, which provides for an accurate in silico identification of catalytically relevant amino acids. Guided by our modelling data, ACS mutations lead to the identification of the catalytically relevant ACS amino acid network I626, T657, Y658, A786, F789 and Y923. Moreover, the ACS amino acid substitutions Y658L and D661A resulted in a premature termination of the cyclization reaction cascade en-route from syn-copalyl diphosphate to Aphidicolan-16-ß-ol. Both ACS mutants generated the diterpene macrocycle syn-copalol and a minor, non-hydroxylated labdane related diterpene, respectively. Our biomolecular modelling and mutational studies suggest that the ACS substrate cyclization occurs in a spatially restricted location

Perfect quantum multiple-unicast network coding protocol

Science.gov (United States)

Li, Dan-Dan; Gao, Fei; Qin, Su-Juan; Wen, Qiao-Yan

2018-01-01

In order to realize long-distance and large-scale quantum communication, it is natural to utilize quantum repeater. For a general quantum multiple-unicast network, it is still puzzling how to complete communication tasks perfectly with less resources such as registers. In this paper, we solve this problem. By applying quantum repeaters to multiple-unicast communication problem, we give encoding-decoding schemes for source nodes, internal ones and target ones, respectively. Source-target nodes share EPR pairs by using our encoding-decoding schemes over quantum multiple-unicast network. Furthermore, quantum communication can be accomplished perfectly via teleportation. Compared with existed schemes, our schemes can reduce resource consumption and realize long-distance transmission of quantum information.

Allosteric transitions of supramolecular systems explored by network models: application to chaperonin GroEL.

Directory of Open Access Journals (Sweden)

Zheng Yang

2009-04-01

Full Text Available Identification of pathways involved in the structural transitions of biomolecular systems is often complicated by the transient nature of the conformations visited across energy barriers and the multiplicity of paths accessible in the multidimensional energy landscape. This task becomes even more challenging in exploring molecular systems on the order of megadaltons. Coarse-grained models that lend themselves to analytical solutions appear to be the only possible means of approaching such cases. Motivated by the utility of elastic network models for describing the collective dynamics of biomolecular systems and by the growing theoretical and experimental evidence in support of the intrinsic accessibility of functional substates, we introduce a new method, adaptive anisotropic network model (aANM, for exploring functional transitions. Application to bacterial chaperonin GroEL and comparisons with experimental data, results from action minimization algorithm, and previous simulations support the utility of aANM as a computationally efficient, yet physically plausible, tool for unraveling potential transition pathways sampled by large complexes/assemblies. An important outcome is the assessment of the critical inter-residue interactions formed/broken near the transition state(s, most of which involve conserved residues.

Multiple network alignment on quantum computers

Science.gov (United States)

Daskin, Anmer; Grama, Ananth; Kais, Sabre

2014-12-01

Comparative analyses of graph-structured datasets underly diverse problems. Examples of these problems include identification of conserved functional components (biochemical interactions) across species, structural similarity of large biomolecules, and recurring patterns of interactions in social networks. A large class of such analyses methods quantify the topological similarity of nodes across networks. The resulting correspondence of nodes across networks, also called node alignment, can be used to identify invariant subgraphs across the input graphs. Given graphs as input, alignment algorithms use topological information to assign a similarity score to each -tuple of nodes, with elements (nodes) drawn from each of the input graphs. Nodes are considered similar if their neighbors are also similar. An alternate, equivalent view of these network alignment algorithms is to consider the Kronecker product of the input graphs and to identify high-ranked nodes in the Kronecker product graph. Conventional methods such as PageRank and HITS (Hypertext-Induced Topic Selection) can be used for this purpose. These methods typically require computation of the principal eigenvector of a suitably modified Kronecker product matrix of the input graphs. We adopt this alternate view of the problem to address the problem of multiple network alignment. Using the phase estimation algorithm, we show that the multiple network alignment problem can be efficiently solved on quantum computers. We characterize the accuracy and performance of our method and show that it can deliver exponential speedups over conventional (non-quantum) methods.

Quantifying the topography of the intrinsic energy landscape of flexible biomolecular recognition

Science.gov (United States)

Chu, Xiakun; Gan, Linfeng; Wang, Erkang; Wang, Jin

2013-01-01

Biomolecular functions are determined by their interactions with other molecules. Biomolecular recognition is often flexible and associated with large conformational changes involving both binding and folding. However, the global and physical understanding for the process is still challenging. Here, we quantified the intrinsic energy landscapes of flexible biomolecular recognition in terms of binding–folding dynamics for 15 homodimers by exploring the underlying density of states, using a structure-based model both with and without considering energetic roughness. By quantifying three individual effective intrinsic energy landscapes (one for interfacial binding, two for monomeric folding), the association mechanisms for flexible recognition of 15 homodimers can be classified into two-state cooperative “coupled binding–folding” and three-state noncooperative “folding prior to binding” scenarios. We found that the association mechanism of flexible biomolecular recognition relies on the interplay between the underlying effective intrinsic binding and folding energy landscapes. By quantifying the whole global intrinsic binding–folding energy landscapes, we found strong correlations between the landscape topography measure Λ (dimensionless ratio of energy gap versus roughness modulated by the configurational entropy) and the ratio of the thermodynamic stable temperature versus trapping temperature, as well as between Λ and binding kinetics. Therefore, the global energy landscape topography determines the binding–folding thermodynamics and kinetics, crucial for the feasibility and efficiency of realizing biomolecular function. We also found “U-shape” temperature-dependent kinetic behavior and a dynamical cross-over temperature for dividing exponential and nonexponential kinetics for two-state homodimers. Our study provides a unique way to bridge the gap between theory and experiments. PMID:23754431

Biomolecular modelling and simulations

CERN Document Server

Karabencheva-Christova, Tatyana

2014-01-01

Published continuously since 1944, the Advances in Protein Chemistry and Structural Biology series is the essential resource for protein chemists. Each volume brings forth new information about protocols and analysis of proteins. Each thematically organized volume is guest edited by leading experts in a broad range of protein-related topics. Describes advances in biomolecular modelling and simulations Chapters are written by authorities in their field Targeted to a wide audience of researchers, specialists, and students The information provided in the volume is well supported by a number of high quality illustrations, figures, and tables.

Biomolecular structure refinement using the GROMOS simulation software

International Nuclear Information System (INIS)

Schmid, Nathan; Allison, Jane R.; Dolenc, Jožica; Eichenberger, Andreas P.; Kunz, Anna-Pitschna E.; Gunsteren, Wilfred F. van

2011-01-01

For the understanding of cellular processes the molecular structure of biomolecules has to be accurately determined. Initial models can be significantly improved by structure refinement techniques. Here, we present the refinement methods and analysis techniques implemented in the GROMOS software for biomolecular simulation. The methodology and some implementation details of the computation of NMR NOE data, 3 J-couplings and residual dipolar couplings, X-ray scattering intensities from crystals and solutions and neutron scattering intensities used in GROMOS is described and refinement strategies and concepts are discussed using example applications. The GROMOS software allows structure refinement combining different types of experimental data with different types of restraining functions, while using a variety of methods to enhance conformational searching and sampling and the thermodynamically calibrated GROMOS force field for biomolecular simulation.

Biomolecular structure refinement using the GROMOS simulation software

Energy Technology Data Exchange (ETDEWEB)

Schmid, Nathan; Allison, Jane R.; Dolenc, Jozica; Eichenberger, Andreas P.; Kunz, Anna-Pitschna E.; Gunsteren, Wilfred F. van, E-mail: wfvgn@igc.phys.chem.ethz.ch [Swiss Federal Institute of Technology ETH, Laboratory of Physical Chemistry (Switzerland)

2011-11-15

For the understanding of cellular processes the molecular structure of biomolecules has to be accurately determined. Initial models can be significantly improved by structure refinement techniques. Here, we present the refinement methods and analysis techniques implemented in the GROMOS software for biomolecular simulation. The methodology and some implementation details of the computation of NMR NOE data, {sup 3}J-couplings and residual dipolar couplings, X-ray scattering intensities from crystals and solutions and neutron scattering intensities used in GROMOS is described and refinement strategies and concepts are discussed using example applications. The GROMOS software allows structure refinement combining different types of experimental data with different types of restraining functions, while using a variety of methods to enhance conformational searching and sampling and the thermodynamically calibrated GROMOS force field for biomolecular simulation.

A compact hard X-ray source for medical imaging and biomolecular studies

International Nuclear Information System (INIS)

Cline, D.B.; Green, M.A.; Kolonko, J.

1995-01-01

There are a large number of synchrotron light sources in the world. However, these sources are designed for physics, chemistry, and engineering studies. To our knowledge, none have been optimized for either medical imaging or biomolecular studies. There are special needs for these applications. We present here a preliminary design of a very compact source, small enough for a hospital or a biomolecular laboratory, that is suitable for these applications. (orig.)

Microfluidic Devices for Studying Biomolecular Interactions

Science.gov (United States)

Wilson, Wilbur W.; Garcia, Carlos d.; Henry, Charles S.

2006-01-01

Microfluidic devices for monitoring biomolecular interactions have been invented. These devices are basically highly miniaturized liquid-chromatography columns. They are intended to be prototypes of miniature analytical devices of the laboratory on a chip type that could be fabricated rapidly and inexpensively and that, because of their small sizes, would yield analytical results from very small amounts of expensive analytes (typically, proteins). Other advantages to be gained by this scaling down of liquid-chromatography columns may include increases in resolution and speed, decreases in the consumption of reagents, and the possibility of performing multiple simultaneous and highly integrated analyses by use of multiple devices of this type, each possibly containing multiple parallel analytical microchannels. The principle of operation is the same as that of a macroscopic liquid-chromatography column: The column is a channel packed with particles, upon which are immobilized molecules of the protein of interest (or one of the proteins of interest if there are more than one). Starting at a known time, a solution or suspension containing molecules of the protein or other substance of interest is pumped into the channel at its inlet. The liquid emerging from the outlet of the channel is monitored to detect the molecules of the dissolved or suspended substance(s). The time that it takes these molecules to flow from the inlet to the outlet is a measure of the degree of interaction between the immobilized and the dissolved or suspended molecules. Depending on the precise natures of the molecules, this measure can be used for diverse purposes: examples include screening for solution conditions that favor crystallization of proteins, screening for interactions between drugs and proteins, and determining the functions of biomolecules.

Multiple-predators-based capture process on complex networks

International Nuclear Information System (INIS)

Sharafat, Rajput Ramiz; Pu Cunlai; Li Jie; Chen Rongbin; Xu Zhongqi

2017-01-01

The predator/prey (capture) problem is a prototype of many network-related applications. We study the capture process on complex networks by considering multiple predators from multiple sources. In our model, some lions start from multiple sources simultaneously to capture the lamb by biased random walks, which are controlled with a free parameter α . We derive the distribution of the lamb’s lifetime and the expected lifetime 〈 T 〉. Through simulation, we find that the expected lifetime drops substantially with the increasing number of lions. Moreover, we study how the underlying topological structure affects the capture process, and obtain that locating on small-degree nodes is better than on large-degree nodes to prolong the lifetime of the lamb. The dense or homogeneous network structures are against the survival of the lamb. We also discuss how to improve the capture efficiency in our model. (paper)

Predicting Protein Function via Semantic Integration of Multiple Networks.

Science.gov (United States)

Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

2016-01-01

Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

Improvements to the APBS biomolecular solvation software suite: Improvements to the APBS Software Suite

Energy Technology Data Exchange (ETDEWEB)

Jurrus, Elizabeth [Pacific Northwest National Laboratory, Richland Washington; Engel, Dave [Pacific Northwest National Laboratory, Richland Washington; Star, Keith [Pacific Northwest National Laboratory, Richland Washington; Monson, Kyle [Pacific Northwest National Laboratory, Richland Washington; Brandi, Juan [Pacific Northwest National Laboratory, Richland Washington; Felberg, Lisa E. [University of California, Berkeley California; Brookes, David H. [University of California, Berkeley California; Wilson, Leighton [University of Michigan, Ann Arbor Michigan; Chen, Jiahui [Southern Methodist University, Dallas Texas; Liles, Karina [Pacific Northwest National Laboratory, Richland Washington; Chun, Minju [Pacific Northwest National Laboratory, Richland Washington; Li, Peter [Pacific Northwest National Laboratory, Richland Washington; Gohara, David W. [St. Louis University, St. Louis Missouri; Dolinsky, Todd [FoodLogiQ, Durham North Carolina; Konecny, Robert [University of California San Diego, San Diego California; Koes, David R. [University of Pittsburgh, Pittsburgh Pennsylvania; Nielsen, Jens Erik [Protein Engineering, Novozymes A/S, Copenhagen Denmark; Head-Gordon, Teresa [University of California, Berkeley California; Geng, Weihua [Southern Methodist University, Dallas Texas; Krasny, Robert [University of Michigan, Ann Arbor Michigan; Wei, Guo-Wei [Michigan State University, East Lansing Michigan; Holst, Michael J. [University of California San Diego, San Diego California; McCammon, J. Andrew [University of California San Diego, San Diego California; Baker, Nathan A. [Pacific Northwest National Laboratory, Richland Washington; Brown University, Providence Rhode Island

2017-10-24

The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that has provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this manuscript, we discuss the models and capabilities that have recently been implemented within the APBS software package including: a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory based algorithm for determining pKa values, and an improved web-based visualization tool for viewing electrostatics.

Nanogap biosensors for electrical and label-free detection of biomolecular interactions

International Nuclear Information System (INIS)

Kyu Kim, Sang; Cho, Hyunmin; Park, Hye-Jung; Kwon, Dohyoung; Min Lee, Jeong; Hyun Chung, Bong

2009-01-01

We demonstrate nanogap biosensors for electrical and label-free detection of biomolecular interactions. Parallel fabrication of nanometer distance gaps has been achieved using a silicon anisotropic wet etching technique on a silicon-on-insulator (SOI) wafer with a finely controllable silicon device layer. Since silicon anisotropic wet etching resulted in a trapezoid-shaped structure whose end became narrower during the etching, the nanogap structure was simply fabricated on the device layer of a SOI wafer. The nanogap devices were individually addressable and a gap size of less than 60 nm was obtained. We demonstrate that the nanogap biosensors can electrically detect biomolecular interactions such as biotin/streptavidin and antigen/antibody pairs. The nanogap devices show a current increase when the proteins are bound to the surface. The current increases proportionally depending upon the concentrations of the molecules in the range of 100 fg ml -1 -100 ng ml -1 at 1 V bias. It is expected that the nanogap developed here could be a highly sensitive biosensor platform for label-free detection of biomolecular interactions.

Development of an informatics infrastructure for data exchange of biomolecular simulations: Architecture, data models and ontology.

Science.gov (United States)

Thibault, J C; Roe, D R; Eilbeck, K; Cheatham, T E; Facelli, J C

2015-01-01

Biomolecular simulations aim to simulate structure, dynamics, interactions, and energetics of complex biomolecular systems. With the recent advances in hardware, it is now possible to use more complex and accurate models, but also reach time scales that are biologically significant. Molecular simulations have become a standard tool for toxicology and pharmacology research, but organizing and sharing data - both within the same organization and among different ones - remains a substantial challenge. In this paper we review our recent work leading to the development of a comprehensive informatics infrastructure to facilitate the organization and exchange of biomolecular simulations data. Our efforts include the design of data models and dictionary tools that allow the standardization of the metadata used to describe the biomedical simulations, the development of a thesaurus and ontology for computational reasoning when searching for biomolecular simulations in distributed environments, and the development of systems based on these models to manage and share the data at a large scale (iBIOMES), and within smaller groups of researchers at laboratory scale (iBIOMES Lite), that take advantage of the standardization of the meta data used to describe biomolecular simulations.

A fast mollified impulse method for biomolecular atomistic simulations

Energy Technology Data Exchange (ETDEWEB)

Fath, L., E-mail: lukas.fath@kit.edu [Institute for App. and Num. Mathematics, Karlsruhe Institute of Technology (Germany); Hochbruck, M., E-mail: marlis.hochbruck@kit.edu [Institute for App. and Num. Mathematics, Karlsruhe Institute of Technology (Germany); Singh, C.V., E-mail: chandraveer.singh@utoronto.ca [Department of Materials Science & Engineering, University of Toronto (Canada)

2017-03-15

Classical integration methods for molecular dynamics are inherently limited due to resonance phenomena occurring at certain time-step sizes. The mollified impulse method can partially avoid this problem by using appropriate filters based on averaging or projection techniques. However, existing filters are computationally expensive and tedious in implementation since they require either analytical Hessians or they need to solve nonlinear systems from constraints. In this work we follow a different approach based on corotation for the construction of a new filter for (flexible) biomolecular simulations. The main advantages of the proposed filter are its excellent stability properties and ease of implementation in standard softwares without Hessians or solving constraint systems. By simulating multiple realistic examples such as peptide, protein, ice equilibrium and ice–ice friction, the new filter is shown to speed up the computations of long-range interactions by approximately 20%. The proposed filtered integrators allow step sizes as large as 10 fs while keeping the energy drift less than 1% on a 50 ps simulation.

Attractor controllability of Boolean networks by flipping a subset of their nodes

Science.gov (United States)

Rafimanzelat, Mohammad Reza; Bahrami, Fariba

2018-04-01

The controllability analysis of Boolean networks (BNs), as models of biomolecular regulatory networks, has drawn the attention of researchers in recent years. In this paper, we aim at governing the steady-state behavior of BNs using an intervention method which can easily be applied to most real system, which can be modeled as BNs, particularly to biomolecular regulatory networks. To this end, we introduce the concept of attractor controllability of a BN by flipping a subset of its nodes, as the possibility of making a BN converge from any of its attractors to any other one, by one-time flipping members of a subset of BN nodes. Our approach is based on the algebraic state-space representation of BNs using semi-tensor product of matrices. After introducing some new matrix tools, we use them to derive necessary and sufficient conditions for the attractor controllability of BNs. A forward search algorithm is then suggested to identify the minimal perturbation set for attractor controllability of a BN. Next, a lower bound is derived for the cardinality of this set. Two new indices are also proposed for quantifying the attractor controllability of a BN and the influence of each network variable on the attractor controllability of the network and the relationship between them is revealed. Finally, we confirm the efficiency of the proposed approach by applying it to the BN models of some real biomolecular networks.

Infinite Multiple Membership Relational Modeling for Complex Networks

DEFF Research Database (Denmark)

Mørup, Morten; Schmidt, Mikkel Nørgaard; Hansen, Lars Kai

Learning latent structure in complex networks has become an important problem fueled by many types of networked data originating from practically all fields of science. In this paper, we propose a new non-parametric Bayesian multiplemembership latent feature model for networks. Contrary to existing...... multiplemembership models that scale quadratically in the number of vertices the proposedmodel scales linearly in the number of links admittingmultiple-membership analysis in large scale networks. We demonstrate a connection between the single membership relational model and multiple membership models and show...

Selected topics in solution-phase biomolecular NMR spectroscopy

Science.gov (United States)

Kay, Lewis E.; Frydman, Lucio

2017-05-01

Solution bio-NMR spectroscopy continues to enjoy a preeminent role as an important tool in elucidating the structure and dynamics of a range of important biomolecules and in relating these to function. Equally impressive is how NMR continues to 'reinvent' itself through the efforts of many brilliant practitioners who ask increasingly demanding and increasingly biologically relevant questions. The ability to manipulate spin Hamiltonians - almost at will - to dissect the information of interest contributes to the success of the endeavor and ensures that the NMR technology will be well poised to contribute to as yet unknown frontiers in the future. As a tribute to the versatility of solution NMR in biomolecular studies and to the continued rapid advances in the field we present a Virtual Special Issue (VSI) that includes over 40 articles on various aspects of solution-state biomolecular NMR that have been published in the Journal of Magnetic Resonance in the past 7 years. These, in total, help celebrate the achievements of this vibrant field.

Quantum key distribution network for multiple applications

Science.gov (United States)

Tajima, A.; Kondoh, T.; Ochi, T.; Fujiwara, M.; Yoshino, K.; Iizuka, H.; Sakamoto, T.; Tomita, A.; Shimamura, E.; Asami, S.; Sasaki, M.

2017-09-01

The fundamental architecture and functions of secure key management in a quantum key distribution (QKD) network with enhanced universal interfaces for smooth key sharing between arbitrary two nodes and enabling multiple secure communication applications are proposed. The proposed architecture consists of three layers: a quantum layer, key management layer and key supply layer. We explain the functions of each layer, the key formats in each layer and the key lifecycle for enabling a practical QKD network. A quantum key distribution-advanced encryption standard (QKD-AES) hybrid system and an encrypted smartphone system were developed as secure communication applications on our QKD network. The validity and usefulness of these systems were demonstrated on the Tokyo QKD Network testbed.

Deep convolutional neural network based antenna selection in multiple-input multiple-output system

Science.gov (United States)

Cai, Jiaxin; Li, Yan; Hu, Ying

2018-03-01

Antenna selection of wireless communication system has attracted increasing attention due to the challenge of keeping a balance between communication performance and computational complexity in large-scale Multiple-Input MultipleOutput antenna systems. Recently, deep learning based methods have achieved promising performance for large-scale data processing and analysis in many application fields. This paper is the first attempt to introduce the deep learning technique into the field of Multiple-Input Multiple-Output antenna selection in wireless communications. First, the label of attenuation coefficients channel matrix is generated by minimizing the key performance indicator of training antenna systems. Then, a deep convolutional neural network that explicitly exploits the massive latent cues of attenuation coefficients is learned on the training antenna systems. Finally, we use the adopted deep convolutional neural network to classify the channel matrix labels of test antennas and select the optimal antenna subset. Simulation experimental results demonstrate that our method can achieve better performance than the state-of-the-art baselines for data-driven based wireless antenna selection.

Application of neural networks to multiple alarm processing and diagnosis in nuclear power plants

International Nuclear Information System (INIS)

Cheon, Se Woo; Chang Soon Heung; Chung, Hak Yeong

1992-01-01

This paper presents feasibility studies of multiple alarm processing and diagnosis using neural networks. The back-propagation neural network model is applied to the training of multiple alarm patterns for the identification of failure in a reactor coolant pump (RCP) system. The general mapping capability of the neural network enables to identify a fault easily. The case studies are performed with emphasis on the applicability of the neural network to pattern recognition problems. It is revealed that the neural network model can identify the cause of multiple alarms properly, even when untrained or sensor-failed alarm symptoms are given. It is also shown that multiple failures are easily identified using the symptoms of multiple alarms

Ordering, materiality, and multiplicity: Enacting Actor–Network Theory in tourism

NARCIS (Netherlands)

Duim, van der R.; Ren, C.; Johannesson, G.T.

2013-01-01

In this article, we demonstrate how Actor–Network Theory has been translated into tourism research. The article presents and discusses three concepts integral to the Actor–Network Theory approach: ordering, materiality, and multiplicity. We first briefly introduce Actor–Network Theory and draw

DNA algorithms of implementing biomolecular databases on a biological computer.

Science.gov (United States)

Chang, Weng-Long; Vasilakos, Athanasios V

2015-01-01

In this paper, DNA algorithms are proposed to perform eight operations of relational algebra (calculus), which include Cartesian product, union, set difference, selection, projection, intersection, join, and division, on biomolecular relational databases.

The HADDOCK web server for data-driven biomolecular docking

NARCIS (Netherlands)

de Vries, S.J.|info:eu-repo/dai/nl/304837717; van Dijk, M.|info:eu-repo/dai/nl/325811113; Bonvin, A.M.J.J.|info:eu-repo/dai/nl/113691238

2010-01-01

Computational docking is the prediction or modeling of the three-dimensional structure of a biomolecular complex, starting from the structures of the individual molecules in their free, unbound form. HADDOC K is a popular docking program that takes a datadriven approach to docking, with support for

Multiple k Nearest Neighbor Query Processing in Spatial Network Databases

DEFF Research Database (Denmark)

Xuegang, Huang; Jensen, Christian Søndergaard; Saltenis, Simonas

2006-01-01

This paper concerns the efficient processing of multiple k nearest neighbor queries in a road-network setting. The assumed setting covers a range of scenarios such as the one where a large population of mobile service users that are constrained to a road network issue nearest-neighbor queries...... for points of interest that are accessible via the road network. Given multiple k nearest neighbor queries, the paper proposes progressive techniques that selectively cache query results in main memory and subsequently reuse these for query processing. The paper initially proposes techniques for the case...... where an upper bound on k is known a priori and then extends the techniques to the case where this is not so. Based on empirical studies with real-world data, the paper offers insight into the circumstances under which the different proposed techniques can be used with advantage for multiple k nearest...

The US Network of Pediatric Multiple Sclerosis Centers: Development, Progress, and Next Steps

Science.gov (United States)

Casper, T. Charles; Rose, John W.; Roalstad, Shelly; Waubant, Emmanuelle; Aaen, Gregory; Belman, Anita; Chitnis, Tanuja; Gorman, Mark; Krupp, Lauren; Lotze, Timothy E.; Ness, Jayne; Patterson, Marc; Rodriguez, Moses; Weinstock-Guttman, Bianca; Browning, Brittan; Graves, Jennifer; Tillema, Jan-Mendelt; Benson, Leslie; Harris, Yolanda

2014-01-01

Multiple sclerosis and other demyelinating diseases in the pediatric population have received an increasing level of attention by clinicians and researchers. The low incidence of these diseases in children creates a need for the involvement of multiple clinical centers in research efforts. The Network of Pediatric Multiple Sclerosis Centers was created initially in 2006 to improve the diagnosis and care of children with demyelinating diseases. In 2010, the Network shifted its focus to multicenter research while continuing to advance the care of patients. The Network has obtained support from the National Multiple Sclerosis Society, the Guthy-Jackson Charitable Foundation, and the National Institutes of Health. The Network will continue to serve as a platform for conducting impactful research in pediatric demyelinating diseases of the central nervous system. This article provides a description of the history and development, organization, mission, research priorities, current studies, and future plans of the Network. PMID:25270659

GROMOS++Software for the Analysis of Biomolecular Simulation Trajectories

NARCIS (Netherlands)

Eichenberger, A.P.; Allison, J.R.; Dolenc, J.; Geerke, D.P.; Horta, B.A.C.; Meier, K; Oostenbrink, B.C.; Schmid, N.; Steiner, D; Wang, D.; van Gunsteren, W.F.

2011-01-01

GROMOS++ is a set of C++ programs for pre- and postprocessing of molecular dynamics simulation trajectories and as such is part of the GROningen MOlecular Simulation software for (bio)molecular simulation. It contains more than 70 programs that can be used to prepare data for the production of

Unique temporal and spatial biomolecular emission profile on individual zinc oxide nanorods

Science.gov (United States)

Singh, Manpreet; Song, Sheng; Hahm, Jong-In

2013-12-01

Zinc oxide nanorods (ZnO NRs) have emerged in recent years as extremely useful, optical signal-enhancing platforms in DNA and protein detection. Although the use of ZnO NRs in biodetection has been demonstrated so far in systems involving many ZnO NRs per detection element, their future applications will likely take place in a miniaturized setting while exploiting single ZnO NRs in a low-volume, high-throughput bioanalysis. In this paper, we investigate temporal and spatial characteristics of the biomolecular fluorescence on individual ZnO NR systems. Quantitative and qualitative examinations of the biomolecular intensity and photostability are carried out as a function of two important criteria, the time and position along the long axis (length) of NRs. Photostability profiles are also measured with respect to the position on NRs and compared to those characteristics of biomolecules on polymeric control platforms. Unlike the uniformly distributed signal observed on the control platforms, both the fluorescence intensity and photostability are position-dependent on individual ZnO NRs. We have identified a unique phenomenon of highly localized, fluorescence intensification on the nanorod ends (FINE) of well-characterized, individual ZnO nanostructures. When compared to the polymeric controls, the biomolecular fluorescence intensity and photostability are determined to be higher on individual ZnO NRs regardless of the position on NRs. We have also carried out finite-difference time-domain simulations the results of which are in good agreement with the observed FINE. The outcomes of our investigation will offer a much needed basis for signal interpretation for biodetection devices and platforms consisting of single ZnO NRs and, at the same time, contribute significantly to provide insight in understanding the biomolecular fluorescence observed from ZnO NR ensemble-based systems.Zinc oxide nanorods (ZnO NRs) have emerged in recent years as extremely useful, optical

Embedding multiple self-organisation functionalities in future radio access networks

NARCIS (Netherlands)

Jansen, T.; Amirijoo, M.; Türke, U.; Jorguseski, L.; Zetterberg, K.; Nascimento, J.R.V. do; Schmelz, L.C.; Turk, J.; Balan, I.

2009-01-01

Wireless network operators today allocate considerable manual effort in managing their networks. A viable solution for lowering the manual effort is to introduce self-organisation functionalities. In this paper we discuss the challenges that are encountered when embedding multiple self-organisation

Partial Interference and Its Performance Impact on Wireless Multiple Access Networks

Directory of Open Access Journals (Sweden)

Lau WingCheong

2010-01-01

Full Text Available To determine the capacity of wireless multiple access networks, the interference among the wireless links must be accurately modeled. In this paper, we formalize the notion of the partial interference phenomenon observed in many recent wireless measurement studies and establish analytical models with tractable solutions for various types of wireless multiple access networks. In particular, we characterize the stability region of IEEE 802.11 networks under partial interference with two potentially unsaturated links numerically. We also provide a closed-form solution for the stability region of slotted ALOHA networks under partial interference with two potentially unsaturated links and obtain a partial characterization of the boundary of the stability region for the general M-link case. Finally, we derive a closed-form approximated solution for the stability region for general M-link slotted ALOHA system under partial interference effects. Based on our results, we demonstrate that it is important to model the partial interference effects while analyzing wireless multiple access networks. This is because such considerations can result in not only significant quantitative differences in the predicted system capacity but also fundamental qualitative changes in the shape of the stability region of the systems.

Sexual networks and social capital: multiple and concurrent sexual ...

African Journals Online (AJOL)

Multiple and concurrent sexual partnerships (MCP) are prevalent in southern Africa and have been identified as a primary cause of high HIV prevalence in this region. Sexual liaisons with multiple partners serve to increase the size and diversity of an individual's sexual — and social — network and therefore to increase their ...

Radio Access Sharing Strategies for Multiple Operators in Cellular Networks

DEFF Research Database (Denmark)

Popovska Avramova, Andrijana; Iversen, Villy Bæk

2015-01-01

deployments (required for coverage enhancement), increased base station utilization, and reduced overall power consumption. Today, network sharing in the radio access part is passive and limited to cell sites. With the introduction of Cloud Radio Access Network and Software Defined Networking adoption...... to the radio access network, the possibility for sharing baseband processing and radio spectrum becomes an important aspect of network sharing. This paper investigates strategies for active sharing of radio access among multiple operators, and analyses the individual benefits depending on the sharing degree...

Physics at the biomolecular interface fundamentals for molecular targeted therapy

CERN Document Server

Fernández, Ariel

2016-01-01

This book focuses primarily on the role of interfacial forces in understanding biological phenomena at the molecular scale. By providing a suitable statistical mechanical apparatus to handle the biomolecular interface, the book becomes uniquely positioned to address core problems in molecular biophysics. It highlights the importance of interfacial tension in delineating a solution to the protein folding problem, in unravelling the physico-chemical basis of enzyme catalysis and protein associations, and in rationally designing molecular targeted therapies. Thus grounded in fundamental science, the book develops a powerful technological platform for drug discovery, while it is set to inspire scientists at any level in their careers determined to address the major challenges in molecular biophysics. The acknowledgment of how exquisitely the structure and dynamics of proteins and their aqueous environment are related attests to the overdue recognition that biomolecular phenomena cannot be effectively understood w...

Electron-correlated fragment-molecular-orbital calculations for biomolecular and nano systems.

Science.gov (United States)

Tanaka, Shigenori; Mochizuki, Yuji; Komeiji, Yuto; Okiyama, Yoshio; Fukuzawa, Kaori

2014-06-14

Recent developments in the fragment molecular orbital (FMO) method for theoretical formulation, implementation, and application to nano and biomolecular systems are reviewed. The FMO method has enabled ab initio quantum-mechanical calculations for large molecular systems such as protein-ligand complexes at a reasonable computational cost in a parallelized way. There have been a wealth of application outcomes from the FMO method in the fields of biochemistry, medicinal chemistry and nanotechnology, in which the electron correlation effects play vital roles. With the aid of the advances in high-performance computing, the FMO method promises larger, faster, and more accurate simulations of biomolecular and related systems, including the descriptions of dynamical behaviors in solvent environments. The current status and future prospects of the FMO scheme are addressed in these contexts.

Cooperative and Adaptive Network Coding for Gradient Based Routing in Wireless Sensor Networks with Multiple Sinks

Directory of Open Access Journals (Sweden)

M. E. Migabo

2017-01-01

Full Text Available Despite its low computational cost, the Gradient Based Routing (GBR broadcast of interest messages in Wireless Sensor Networks (WSNs causes significant packets duplications and unnecessary packets transmissions. This results in energy wastage, traffic load imbalance, high network traffic, and low throughput. Thanks to the emergence of fast and powerful processors, the development of efficient network coding strategies is expected to enable efficient packets aggregations and reduce packets retransmissions. For multiple sinks WSNs, the challenge consists of efficiently selecting a suitable network coding scheme. This article proposes a Cooperative and Adaptive Network Coding for GBR (CoAdNC-GBR technique which considers the network density as dynamically defined by the average number of neighbouring nodes, to efficiently aggregate interest messages. The aggregation is performed by means of linear combinations of random coefficients of a finite Galois Field of variable size GF(2S at each node and the decoding is performed by means of Gaussian elimination. The obtained results reveal that, by exploiting the cooperation of the multiple sinks, the CoAdNC-GBR not only improves the transmission reliability of links and lowers the number of transmissions and the propagation latency, but also enhances the energy efficiency of the network when compared to the GBR-network coding (GBR-NC techniques.

hPDB – Haskell library for processing atomic biomolecular structures in protein data bank format

OpenAIRE

Gajda, Michał Jan

2013-01-01

Background Protein DataBank file format is used for the majority of biomolecular data available today. Haskell is a lazy functional language that enjoys a high-level class-based type system, a growing collection of useful libraries and a reputation for efficiency. Findings I present a fast library for processing biomolecular data in the Protein Data Bank format. I present benchmarks indicating that this library is faster than other frequently used Protein Data Bank parsing programs. The propo...

Optical code-division multiple-access networks

Science.gov (United States)

Andonovic, Ivan; Huang, Wei

1999-04-01

This review details the approaches adopted to implement classical code division multiple access (CDMA) principles directly in the optical domain, resulting in all optical derivatives of electronic systems. There are a number of ways of realizing all-optical CDMA systems, classified as incoherent and coherent based on spreading in the time and frequency dimensions. The review covers the basic principles of optical CDMA (OCDMA), the nature of the codes used in these approaches and the resultant limitations on system performance with respect to the number of stations (code cardinality), the number of simultaneous users (correlation characteristics of the families of codes), concluding with consideration of network implementation issues. The latest developments will be presented with respect to the integration of conventional time spread codes, used in the bulk of the demonstrations of these networks to date, with wavelength division concepts, commonplace in optical networking. Similarly, implementations based on coherent correlation with the aid of a local oscillator will be detailed and comparisons between approaches will be drawn. Conclusions regarding the viability of these approaches allowing the goal of a large, asynchronous high capacity optical network to be realized will be made.

Robustness Analysis of Real Network Topologies Under Multiple Failure Scenarios

DEFF Research Database (Denmark)

Manzano, M.; Marzo, J. L.; Calle, E.

2012-01-01

on topological characteristics. Recently approaches also consider the services supported by such networks. In this paper we carry out a robustness analysis of five real backbone telecommunication networks under defined multiple failure scenarios, taking into account the consequences of the loss of established......Nowadays the ubiquity of telecommunication networks, which underpin and fulfill key aspects of modern day living, is taken for granted. Significant large-scale failures have occurred in the last years affecting telecommunication networks. Traditionally, network robustness analysis has been focused...... connections. Results show which networks are more robust in response to a specific type of failure....

The influence of single neuron dynamics and network topology on time delay-induced multiple synchronous behaviors in inhibitory coupled network

International Nuclear Information System (INIS)

Zhao, Zhiguo; Gu, Huaguang

2015-01-01

Highlights: • Time delay-induced multiple synchronous behaviors was simulated in neuronal networks. • Multiple behaviors appear at time delays shorter than a bursting period of neurons. • The more spikes per burst of bursting, the more synchronous regions of time delay. • From regular to random via small-world networks, synchronous degree becomes weak. • An interpretation of the multiple behaviors and the influence of network are provided. - Abstract: Time delay induced-multiple synchronous behaviors are simulated in neuronal network composed of many inhibitory neurons and appear at different time delays shorter than a period of endogenous bursting of individual neurons. It is different from previous investigations wherein only one of multiple synchronous behaviors appears at time delay shorter than a period of endogenous firing and others appear at time delay longer than the period duration. The bursting patterns of the synchronous behaviors are identified based on the dynamics of an individual neuron stimulated by a signal similar to the inhibitory coupling current, which is applied at the decaying branch of a spike and suitable phase within the quiescent state of the endogenous bursting. If a burst of endogenous bursting contains more spikes, the synchronous behaviors appear at more regions of time delay. As the coupling strength increases, the multiple synchronous behaviors appear in a sequence because the different threshold of coupling current or strength is needed to achieve synchronous behaviors. From regular, to small-world, and to random networks, synchronous degree of the multiple synchronous behaviors becomes weak, and synchronous bursting patterns with lower spikes per burst disappear, which is properly interpreted by the difference of coupling current between neurons induced by different degree and the high threshold of coupling current to achieve synchronization for the absent synchronous bursting patterns. The results of the influence of

Multiplicative Attribute Graph Model of Real-World Networks

Energy Technology Data Exchange (ETDEWEB)

Kim, Myunghwan [Stanford Univ., CA (United States); Leskovec, Jure [Stanford Univ., CA (United States)

2010-10-20

Large scale real-world network data, such as social networks, Internet andWeb graphs, is ubiquitous in a variety of scientific domains. The study of such social and information networks commonly finds patterns and explain their emergence through tractable models. In most networks, especially in social networks, nodes also have a rich set of attributes (e.g., age, gender) associatedwith them. However, most of the existing network models focus only on modeling the network structure while ignoring the features of nodes in the network. Here we present a class of network models that we refer to as the Multiplicative Attribute Graphs (MAG), which naturally captures the interactions between the network structure and node attributes. We consider a model where each node has a vector of categorical features associated with it. The probability of an edge between a pair of nodes then depends on the product of individual attributeattribute similarities. The model yields itself to mathematical analysis as well as fit to real data. We derive thresholds for the connectivity, the emergence of the giant connected component, and show that the model gives rise to graphs with a constant diameter. Moreover, we analyze the degree distribution to show that the model can produce networks with either lognormal or power-law degree distribution depending on certain conditions.

Synchronization in networks with multiple interaction layers

Science.gov (United States)

del Genio, Charo I.; Gómez-Gardeñes, Jesús; Bonamassa, Ivan; Boccaletti, Stefano

2016-01-01

The structure of many real-world systems is best captured by networks consisting of several interaction layers. Understanding how a multilayered structure of connections affects the synchronization properties of dynamical systems evolving on top of it is a highly relevant endeavor in mathematics and physics and has potential applications in several socially relevant topics, such as power grid engineering and neural dynamics. We propose a general framework to assess the stability of the synchronized state in networks with multiple interaction layers, deriving a necessary condition that generalizes the master stability function approach. We validate our method by applying it to a network of Rössler oscillators with a double layer of interactions and show that highly rich phenomenology emerges from this. This includes cases where the stability of synchronization can be induced even if both layers would have individually induced unstable synchrony, an effect genuinely arising from the true multilayer structure of the interactions among the units in the network. PMID:28138540

An Overview of Biomolecular Event Extraction from Scientific Documents.

Science.gov (United States)

Vanegas, Jorge A; Matos, Sérgio; González, Fabio; Oliveira, José L

2015-01-01

This paper presents a review of state-of-the-art approaches to automatic extraction of biomolecular events from scientific texts. Events involving biomolecules such as genes, transcription factors, or enzymes, for example, have a central role in biological processes and functions and provide valuable information for describing physiological and pathogenesis mechanisms. Event extraction from biomedical literature has a broad range of applications, including support for information retrieval, knowledge summarization, and information extraction and discovery. However, automatic event extraction is a challenging task due to the ambiguity and diversity of natural language and higher-level linguistic phenomena, such as speculations and negations, which occur in biological texts and can lead to misunderstanding or incorrect interpretation. Many strategies have been proposed in the last decade, originating from different research areas such as natural language processing, machine learning, and statistics. This review summarizes the most representative approaches in biomolecular event extraction and presents an analysis of the current state of the art and of commonly used methods, features, and tools. Finally, current research trends and future perspectives are also discussed.

An Overview of Biomolecular Event Extraction from Scientific Documents

Directory of Open Access Journals (Sweden)

Jorge A. Vanegas

2015-01-01

Full Text Available This paper presents a review of state-of-the-art approaches to automatic extraction of biomolecular events from scientific texts. Events involving biomolecules such as genes, transcription factors, or enzymes, for example, have a central role in biological processes and functions and provide valuable information for describing physiological and pathogenesis mechanisms. Event extraction from biomedical literature has a broad range of applications, including support for information retrieval, knowledge summarization, and information extraction and discovery. However, automatic event extraction is a challenging task due to the ambiguity and diversity of natural language and higher-level linguistic phenomena, such as speculations and negations, which occur in biological texts and can lead to misunderstanding or incorrect interpretation. Many strategies have been proposed in the last decade, originating from different research areas such as natural language processing, machine learning, and statistics. This review summarizes the most representative approaches in biomolecular event extraction and presents an analysis of the current state of the art and of commonly used methods, features, and tools. Finally, current research trends and future perspectives are also discussed.

Photochirogenesis: Photochemical Models on the Origin of Biomolecular Homochirality

Directory of Open Access Journals (Sweden)

Cornelia Meinert

2010-05-01

Full Text Available Current research focuses on a better understanding of the origin of biomolecular asymmetry by the identification and detection of the possibly first chiral molecules that were involved in the appearance and evolution of life on Earth. We have reasons to assume that these molecules were specific chiral amino acids. Chiral amino acids have been identified in both chondritic meteorites and simulated interstellar ices. Present research reasons that circularly polarized electromagnetic radiation was identified in interstellar environments and an asymmetric interstellar photon-molecule interaction might have triggered biomolecular symmetry breaking. We review on the possible prebiotic interaction of ‘chiral photons’ in the form of circularly polarized light, with early chiral organic molecules. We will highlight recent studies on enantioselective photolysis of racemic amino acids by circularly polarized light and experiments on the asymmetric photochemical synthesis of amino acids from only one C and one N containing molecules by simulating interstellar environments. Both approaches are based on circular dichroic transitions of amino acids that will be presented as well.

CyLineUp: A Cytoscape app for visualizing data in network small multiples.

Science.gov (United States)

Costa, Maria Cecília D; Slijkhuis, Thijs; Ligterink, Wilco; Hilhorst, Henk W M; de Ridder, Dick; Nijveen, Harm

2016-01-01

CyLineUp is a Cytoscape 3 app for the projection of high-throughput measurement data from multiple experiments/samples on a network or pathway map using "small multiples". This visualization method allows for easy comparison of different experiments in the context of the network or pathway. The user can import various kinds of measurement data and select any appropriate Cytoscape network or WikiPathways pathway map. CyLineUp creates small multiples by replicating the loaded network as many times as there are experiments/samples (e.g. time points, stress conditions, tissues, etc.). The measurement data for each experiment are then mapped onto the nodes (genes, proteins etc.) of the corresponding network using a color gradient. Each step of creating the visualization can be customized to the user's needs. The results can be exported as a high quality vector image.

AC Power Local Network with Multiple Power Routers

Directory of Open Access Journals (Sweden)

Ryo Takahashi

2013-12-01

Full Text Available Controlling power flow and achieving appropriate matching between power sources and loads according to the quality of energy is expected to be one of the approaches to reduce wasted energy consumption. A power router, proposed recently, has the capability of realizing circuit switching in a power distribution network. This study focuses on the feasibility of an AC power routing network system composed of multiple power routers. To evaluate the feasibility, we experimentally confirm the circuit switching operation of the parallel and series configurations of the power routers, so that the network system can be designed by the combination of parallel and series configurations.

Micro and Nanotechnologies Enhanced Biomolecular Sensing

Directory of Open Access Journals (Sweden)

Tza-Huei Wang

2013-07-01

Full Text Available This editorial summarizes some of the recent advances of micro and nanotechnology-based tools and devices for biomolecular detection. These include the incorporation of nanomaterials into a sensor surface or directly interfacing with molecular probes to enhance target detection via more rapid and sensitive responses, and the use of self-assembled organic/inorganic nanocomposites that inhibit exceptional spectroscopic properties to enable facile homogenous assays with efficient binding kinetics. Discussions also include some insight into microfluidic principles behind the development of an integrated sample preparation and biosensor platform toward a miniaturized and fully functional system for point of care applications.

From dynamics to structure and function of model biomolecular systems

NARCIS (Netherlands)

Fontaine-Vive-Curtaz, F.

2007-01-01

The purpose of this thesis was to extend recent works on structure and dynamics of hydrogen bonded crystals to model biomolecular systems and biological processes. The tools that we have used are neutron scattering (NS) and density functional theory (DFT) and force field (FF) based simulation

Single-molecule imaging and manipulation of biomolecular machines and systems.

Science.gov (United States)

Iino, Ryota; Iida, Tatsuya; Nakamura, Akihiko; Saita, Ei-Ichiro; You, Huijuan; Sako, Yasushi

2018-02-01

Biological molecular machines support various activities and behaviors of cells, such as energy production, signal transduction, growth, differentiation, and migration. We provide an overview of single-molecule imaging methods involving both small and large probes used to monitor the dynamic motions of molecular machines in vitro (purified proteins) and in living cells, and single-molecule manipulation methods used to measure the forces, mechanical properties and responses of biomolecules. We also introduce several examples of single-molecule analysis, focusing primarily on motor proteins and signal transduction systems. Single-molecule analysis is a powerful approach to unveil the operational mechanisms both of individual molecular machines and of systems consisting of many molecular machines. Quantitative, high-resolution single-molecule analyses of biomolecular systems at the various hierarchies of life will help to answer our fundamental question: "What is life?" This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato. Copyright © 2017 Elsevier B.V. All rights reserved.

Changes in biomolecular profile in a single nucleolus during cell fixation.

Science.gov (United States)

Kuzmin, Andrey N; Pliss, Artem; Prasad, Paras N

2014-11-04

Fixation of biological sample is an essential technique applied in order to "freeze" in time the intracellular molecular content. However, fixation induces changes of the cellular molecular structure, which mask physiological distribution of biomolecules and bias interpretation of results. Accurate, sensitive, and comprehensive characterization of changes in biomolecular composition, occurring during fixation, is crucial for proper analysis of experimental data. Here we apply biomolecular component analysis for Raman spectra measured in the same nucleoli of HeLa cells before and after fixation by either formaldehyde solution or by chilled ethanol. It is found that fixation in formaldehyde does not strongly affect the Raman spectra of nucleolar biomolecular components, but may significantly decrease the nucleolar RNA concentration. At the same time, ethanol fixation leads to a proportional increase (up to 40%) in concentrations of nucleolar proteins and RNA, most likely due to cell shrinkage occurring in the presence of coagulant fixative. Ethanol fixation also triggers changes in composition of nucleolar proteome, as indicated by an overall reduction of the α-helical structure of proteins and increase in the concentration of proteins containing the β-sheet conformation. We conclude that cross-linking fixation is a more appropriate protocol for mapping of proteins in situ. At the same time, ethanol fixation is preferential for studies of RNA-containing macromolecules. We supplemented our quantitative Raman spectroscopic measurements with mapping of the protein and lipid macromolecular groups in live and fixed cells using coherent anti-Stokes Raman scattering nonlinear optical imaging.

Comparison of a Ring On-Chip Network and a Code-Division Multiple-Access On-Chip Network

Directory of Open Access Journals (Sweden)

Xin Wang

2007-01-01

Full Text Available Two network-on-chip (NoC designs are examined and compared in this paper. One design applies a bidirectional ring connection scheme, while the other design applies a code-division multiple-access (CDMA connection scheme. Both of the designs apply globally asynchronous locally synchronous (GALS scheme in order to deal with the issue of transferring data in a multiple-clock-domain environment of an on-chip system. The two NoC designs are compared with each other by their network structures, data transfer principles, network node structures, and their asynchronous designs. Both the synchronous and the asynchronous designs of the two on-chip networks are realized using a hardware-description language (HDL in order to make the entire designs suit the commonly used synchronous design tools and flow. The performance estimation and comparison of the two NoC designs which are based on the HDL realizations are addressed. By comparing the two NoC designs, the advantages and disadvantages of applying direct connection and CDMA connection schemes in an on-chip communication network are discussed.

Electrochemical sensor for multiplex screening of genetically modified DNA: identification of biotech crops by logic-based biomolecular analysis.

Science.gov (United States)

Liao, Wei-Ching; Chuang, Min-Chieh; Ho, Ja-An Annie

2013-12-15

Genetically modified (GM) technique, one of the modern biomolecular engineering technologies, has been deemed as profitable strategy to fight against global starvation. Yet rapid and reliable analytical method is deficient to evaluate the quality and potential risk of such resulting GM products. We herein present a biomolecular analytical system constructed with distinct biochemical activities to expedite the computational detection of genetically modified organisms (GMOs). The computational mechanism provides an alternative to the complex procedures commonly involved in the screening of GMOs. Given that the bioanalytical system is capable of processing promoter, coding and species genes, affirmative interpretations succeed to identify specified GM event in terms of both electrochemical and optical fashions. The biomolecular computational assay exhibits detection capability of genetically modified DNA below sub-nanomolar level and is found interference-free by abundant coexistence of non-GM DNA. This bioanalytical system, furthermore, sophisticates in array fashion operating multiplex screening against variable GM events. Such a biomolecular computational assay and biosensor holds great promise for rapid, cost-effective, and high-fidelity screening of GMO. Copyright © 2013 Elsevier B.V. All rights reserved.

Affinity Capillary Electrophoresis – A Powerful Tool to Investigate Biomolecular Interactions

Czech Academy of Sciences Publication Activity Database

Kašička, Václav

2017-01-01

Roč. 30, č. 5 (2017), s. 248 ISSN 1471-6577 Institutional support: RVO:61388963 Keywords : capillary affinity electrophoresis * biomolecular interactions * binding constants Subject RIV: CB - Analytical Chemistry, Separation OBOR OECD: Analytical chemistry Impact factor: 0.663, year: 2016

GraphAlignment: Bayesian pairwise alignment of biological networks

Directory of Open Access Journals (Sweden)

Kolář Michal

2012-11-01

Full Text Available Abstract Background With increased experimental availability and accuracy of bio-molecular networks, tools for their comparative and evolutionary analysis are needed. A key component for such studies is the alignment of networks. Results We introduce the Bioconductor package GraphAlignment for pairwise alignment of bio-molecular networks. The alignment incorporates information both from network vertices and network edges and is based on an explicit evolutionary model, allowing inference of all scoring parameters directly from empirical data. We compare the performance of our algorithm to an alternative algorithm, Græmlin 2.0. On simulated data, GraphAlignment outperforms Græmlin 2.0 in several benchmarks except for computational complexity. When there is little or no noise in the data, GraphAlignment is slower than Græmlin 2.0. It is faster than Græmlin 2.0 when processing noisy data containing spurious vertex associations. Its typical case complexity grows approximately as O(N2.6. On empirical bacterial protein-protein interaction networks (PIN and gene co-expression networks, GraphAlignment outperforms Græmlin 2.0 with respect to coverage and specificity, albeit by a small margin. On large eukaryotic PIN, Græmlin 2.0 outperforms GraphAlignment. Conclusions The GraphAlignment algorithm is robust to spurious vertex associations, correctly resolves paralogs, and shows very good performance in identification of homologous vertices defined by high vertex and/or interaction similarity. The simplicity and generality of GraphAlignment edge scoring makes the algorithm an appropriate choice for global alignment of networks.

Revealing Pathway Dynamics in Heart Diseases by Analyzing Multiple Differential Networks.

Directory of Open Access Journals (Sweden)

Xiaoke Ma

2015-06-01

Full Text Available Development of heart diseases is driven by dynamic changes in both the activity and connectivity of gene pathways. Understanding these dynamic events is critical for understanding pathogenic mechanisms and development of effective treatment. Currently, there is a lack of computational methods that enable analysis of multiple gene networks, each of which exhibits differential activity compared to the network of the baseline/healthy condition. We describe the iMDM algorithm to identify both unique and shared gene modules across multiple differential co-expression networks, termed M-DMs (multiple differential modules. We applied iMDM to a time-course RNA-Seq dataset generated using a murine heart failure model generated on two genotypes. We showed that iMDM achieves higher accuracy in inferring gene modules compared to using single or multiple co-expression networks. We found that condition-specific M-DMs exhibit differential activities, mediate different biological processes, and are enriched for genes with known cardiovascular phenotypes. By analyzing M-DMs that are present in multiple conditions, we revealed dynamic changes in pathway activity and connectivity across heart failure conditions. We further showed that module dynamics were correlated with the dynamics of disease phenotypes during the development of heart failure. Thus, pathway dynamics is a powerful measure for understanding pathogenesis. iMDM provides a principled way to dissect the dynamics of gene pathways and its relationship to the dynamics of disease phenotype. With the exponential growth of omics data, our method can aid in generating systems-level insights into disease progression.

Robustness Assessment of Urban Road Network with Consideration of Multiple Hazard Events.

Science.gov (United States)

Zhou, Yaoming; Sheu, Jiuh-Biing; Wang, Junwei

2017-08-01

Robustness measures a system's ability of being insensitive to disturbances. Previous studies assessed the robustness of transportation networks to a single disturbance without considering simultaneously happening multiple events. The purpose of this article is to address this problem and propose a new framework to assess the robustness of an urban transportation network. The framework consists of two layers. The upper layer is to define the robustness index based on the impact evaluation in different scenarios obtained from the lower layer, whereas the lower layer is to evaluate the performance of each hypothetical disrupted road network given by the upper layer. The upper layer has two varieties, that is, robustness against random failure and robustness against intentional attacks. This robustness measurement framework is validated by application to a real-world urban road network in Hong Kong. The results show that the robustness of a transport network with consideration of multiple events is quite different from and more comprehensive than that with consideration of only a single disruption. We also propose a Monte Carlo method and a heuristic algorithm to handle different scenarios with multiple hazard events, which is proved to be quite efficient. This methodology can also be applied to conduct risk analysis of other systems where multiple failures or disruptions exist. © 2017 Society for Risk Analysis.

Modeling evolution of crosstalk in noisy signal transduction networks

Science.gov (United States)

Tareen, Ammar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

2018-02-01

Signal transduction networks can form highly interconnected systems within cells due to crosstalk between constituent pathways. To better understand the evolutionary design principles underlying such networks, we study the evolution of crosstalk for two parallel signaling pathways that arise via gene duplication. We use a sequence-based evolutionary algorithm and evolve the network based on two physically motivated fitness functions related to information transmission. We find that one fitness function leads to a high degree of crosstalk while the other leads to pathway specificity. Our results offer insights on the relationship between network architecture and information transmission for noisy biomolecular networks.

HPDB-Haskell library for processing atomic biomolecular structures in Protein Data Bank format.

Science.gov (United States)

Gajda, Michał Jan

2013-11-23

Protein DataBank file format is used for the majority of biomolecular data available today. Haskell is a lazy functional language that enjoys a high-level class-based type system, a growing collection of useful libraries and a reputation for efficiency. I present a fast library for processing biomolecular data in the Protein Data Bank format. I present benchmarks indicating that this library is faster than other frequently used Protein Data Bank parsing programs. The proposed library also features a convenient iterator mechanism, and a simple API modeled after BioPython. I set a new standard for convenience and efficiency of Protein Data Bank processing in a Haskell library, and release it to open source.

Implementing multiple intervention strategies in Dutch public health-related policy networks

NARCIS (Netherlands)

Harting, Janneke; Peters, Dorothee; Grêaux, Kimberly; van Assema, Patricia; Verweij, Stefan; Stronks, Karien; Klijn, Erik-Hans

2017-01-01

Improving public health requires multiple intervention strategies. Implementing such an intervention mix is supposed to require a multisectoral policy network. As evidence to support this assumption is scarce, we examined under which conditions public health-related policy networks were able to

Computer Programming and Biomolecular Structure Studies: A Step beyond Internet Bioinformatics

Science.gov (United States)

Likic, Vladimir A.

2006-01-01

This article describes the experience of teaching structural bioinformatics to third year undergraduate students in a subject titled "Biomolecular Structure and Bioinformatics." Students were introduced to computer programming and used this knowledge in a practical application as an alternative to the well established Internet bioinformatics…

Efficient Routing in Wireless Sensor Networks with Multiple Sessions

OpenAIRE

Dianjie Lu; Guijuan Zhang; Ren Han; Xiangwei Zheng; Hong Liu

2014-01-01

Wireless Sensor Networks (WSNs) are subject to node failures because of limited energy and link unreliability which makes the design of routing protocols in such networks a challenging task. The multipath routing scheme is an optimal alternative to address this problem which splits the traffic across multiple paths instead of routing all the traffic along a single path. However, using more paths introduces more contentions which degrade energy efficiency. The problem becomes even more difficu...

Effects of multiple spreaders in community networks

Science.gov (United States)

Hu, Zhao-Long; Ren, Zhuo-Ming; Yang, Guang-Yong; Liu, Jian-Guo

2014-12-01

Human contact networks exhibit the community structure. Understanding how such community structure affects the epidemic spreading could provide insights for preventing the spreading of epidemics between communities. In this paper, we explore the spreading of multiple spreaders in community networks. A network based on the clustering preferential mechanism is evolved, whose communities are detected by the Girvan-Newman (GN) algorithm. We investigate the spreading effectiveness by selecting the nodes as spreaders in the following ways: nodes with the largest degree in each community (community hubs), the same number of nodes with the largest degree from the global network (global large-degree) and randomly selected one node within each community (community random). The experimental results on the SIR model show that the spreading effectiveness based on the global large-degree and community hubs methods is the same in the early stage of the infection and the method of community random is the worst. However, when the infection rate exceeds the critical value, the global large-degree method embodies the worst spreading effectiveness. Furthermore, the discrepancy of effectiveness for the three methods will decrease as the infection rate increases. Therefore, we should immunize the hubs in each community rather than those hubs in the global network to prevent the outbreak of epidemics.

Scanning probe and optical tweezer investigations of biomolecular interactions

International Nuclear Information System (INIS)

Rigby-Singleton, Shellie

2002-01-01

A complex array of intermolecular forces controls the interactions between and within biological molecules. The desire to empirically explore the fundamental forces has led to the development of several biophysical techniques. Of these, the atomic force microscope (AFM) and the optical tweezers have been employed throughout this thesis to monitor the intermolecular forces involved in biomolecular interactions. The AFM is a well-established force sensing technique capable of measuring biomolecular interactions at a single molecule level. However, its versatility has not been extrapolated to the investigation of a drug-enzyme complex. The energy landscape for the force induced dissociation of the DHFR-methotrexate complex was studied. Revealing an energy barrier to dissociation located ∼0.3 nm from the bound state. Unfortunately, the AFM has a limited range of accessible loading rates and in order to profile the complete energy landscape alternative force sensing instrumentation should be considered, for example the BFP and optical tweezers. Thus, this thesis outlines the development and construction an optical trap capable of measuring intermolecular forces between biomolecules at the single molecule level. To demonstrate the force sensing abilities of the optical set up, proof of principle measurements were performed which investigate the interactions between proteins and polymer surfaces subjected to varying degrees of argon plasma treatment. Complementary data was gained from measurements performed independently by the AFM. Changes in polymer resistance to proteins as a response to changes in polymer surface chemistry were detected utilising both AFM and optical tweezers measurements. Finally, the AFM and optical tweezers were employed as ultrasensitive biosensors. Single molecule investigations of the antibody-antigen interaction between the cardiac troponin I marker and its complementary antibody, reveals the impact therapeutic concentrations of heparin have

Allocation and management issues in multiple-transaction open access transmission networks

Science.gov (United States)

Tao, Shu

This thesis focuses on some key issues related to allocation and management by the independent grid operator (IGO) of unbundled services in multiple-transaction open access transmission networks. The three unbundled services addressed in the thesis are transmission real power losses, reactive power support requirements from generation sources, and transmission congestion management. We develop the general framework that explicitly represents multiple transactions undertaken simultaneously in the transmission grid. This framework serves as the basis for formulating various problems treated in the thesis. We use this comprehensive framework to develop a physical-flow-based mechanism to allocate the total transmission losses to each transaction using the system. An important property of the allocation scheme is its capability to effectively deal with counter flows that result in the presence of specific transactions. Using the loss allocation results as the basis, we construct the equivalent loss compensation concept and apply it to develop flexible and effective procedures for compensating losses in multiple-transaction networks. We present a new physical-flow-based mechanism for allocating the reactive power support requirements provided by generators in multiple-transaction networks. The allocatable reactive support requirements are formulated as the sum of two specific components---the voltage magnitude variation component and the voltage angle variation component. The formulation utilizes the multiple-transaction framework and makes use of certain simplifying approximations. The formulation leads to a natural allocation as a function of the amount of each transaction. The physical interpretation of each allocation as a sensitivity of the reactive output of a generator is discussed. We propose a congestion management allocation scheme for multiple-transaction networks. The proposed scheme determines the allocation of congestion among the transactions on a physical

Whitelists Based Multiple Filtering Techniques in SCADA Sensor Networks

Directory of Open Access Journals (Sweden)

DongHo Kang

2014-01-01

Full Text Available Internet of Things (IoT consists of several tiny devices connected together to form a collaborative computing environment. Recently IoT technologies begin to merge with supervisory control and data acquisition (SCADA sensor networks to more efficiently gather and analyze real-time data from sensors in industrial environments. But SCADA sensor networks are becoming more and more vulnerable to cyber-attacks due to increased connectivity. To safely adopt IoT technologies in the SCADA environments, it is important to improve the security of SCADA sensor networks. In this paper we propose a multiple filtering technique based on whitelists to detect illegitimate packets. Our proposed system detects the traffic of network and application protocol attacks with a set of whitelists collected from normal traffic.

Augmented lagrange hopfield network for economic dispatch with multiple fuel options

International Nuclear Information System (INIS)

Dieu, Vo Ngoc; Ongsakul, Weerakorn; Polprasert, Jirawadee

2011-01-01

This paper proposes an augmented Lagrange Hopfield network (ALHN) for solving economic dispatch (ED) problem with multiple fuel options. The proposed ALHN method is a continuous Hopfield neural network with its energy function based on augmented Lagrangian function. The advantages of ALHN over the conventional Hopfield neural network are easier use, more general applications, faster convergence, better optimal solution, and larger scale of problem implementation. The method solves the problem by directly searching the most suitable fuel among the available fuels of each unit and finding the optimal solution for the problem based on minimization of the energy function of the continuous Hopfield neural network. The proposed method is tested on systems up to 100 units and the obtained results are compared to those from other methods in the literature. The results have shown that the proposed method is efficient for solving the ED problem with multiple fuel options and favorable for implementation in large scale problems.

Anti-synchronization control of BAM memristive neural networks with multiple proportional delays and stochastic perturbations

Science.gov (United States)

Wang, Weiping; Yuan, Manman; Luo, Xiong; Liu, Linlin; Zhang, Yao

2018-01-01

Proportional delay is a class of unbounded time-varying delay. A class of bidirectional associative memory (BAM) memristive neural networks with multiple proportional delays is concerned in this paper. First, we propose the model of BAM memristive neural networks with multiple proportional delays and stochastic perturbations. Furthermore, by choosing suitable nonlinear variable transformations, the BAM memristive neural networks with multiple proportional delays can be transformed into the BAM memristive neural networks with constant delays. Based on the drive-response system concept, differential inclusions theory and Lyapunov stability theory, some anti-synchronization criteria are obtained. Finally, the effectiveness of proposed criteria are demonstrated through numerical examples.

Relative camera localisation in non-overlapping camera networks using multiple trajectories

NARCIS (Netherlands)

John, V.; Englebienne, G.; Kröse, B.J.A.

2012-01-01

In this article we present an automatic camera calibration algorithm using multiple trajectories in a multiple camera network with non-overlapping field-of-views (FOV). Visible trajectories within a camera FOV are assumed to be measured with respect to the camera local co-ordinate system.

Application of biomolecular recognition via magnetic nanoparticle in nanobiotechnology

Science.gov (United States)

Shen, Wei-Zheng; Cetinel, Sibel; Montemagno, Carlo

2018-05-01

The marriage of biomolecular recognition and magnetic nanoparticle creates tremendous opportunities in the development of advanced technology both in academic research and in industrial sectors. In this paper, we review current progress on the magnetic nanoparticle-biomolecule hybrid systems, particularly employing the recognition pairs of DNA-DNA, DNA-protein, protein-protein, and protein-inorganics in several nanobiotechnology application areas, including molecular biology, diagnostics, medical treatment, industrial biocatalysts, and environmental separations.

ODMBP: Behavior Forwarding for Multiple Property Destinations in Mobile Social Networks

Directory of Open Access Journals (Sweden)

Jia Xu

2016-01-01

Full Text Available The smartphones are widely available in recent years. Wireless networks and personalized mobile devices are deeply integrated and embedded in our lives. The behavior based forwarding has become a new transmission paradigm for supporting many novel applications. However, the commodities, services, and individuals usually have multiple properties of their interests and behaviors. In this paper, we profile these multiple properties and propose an Opportunistic Dissemination Protocol based on Multiple Behavior Profile, ODMBP, in mobile social networks. We first map the interest space to the behavior space and extract the multiple behavior profiles from the behavior space. Then, we propose the correlation computing model based on the principle of BM25 to calculate the correlation metric of multiple behavior profiles. The correlation metric is used to forward the message to the users who are more similar to the target in our protocol. ODMBP consists of three stages: user initialization, gradient ascent, and group spread. Through extensive simulations, we demonstrate that the proposed multiple behavior profile and correlation computing model are correct and efficient. Compared to other classical routing protocols, ODMBP can significantly improve the performance in the aspect of delivery ratio, delay, and overhead ratio.

Scalable Molecular Dynamics for Large Biomolecular Systems

Directory of Open Access Journals (Sweden)

Robert K. Brunner

2000-01-01

Full Text Available We present an optimized parallelization scheme for molecular dynamics simulations of large biomolecular systems, implemented in the production-quality molecular dynamics program NAMD. With an object-based hybrid force and spatial decomposition scheme, and an aggressive measurement-based predictive load balancing framework, we have attained speeds and speedups that are much higher than any reported in literature so far. The paper first summarizes the broad methodology we are pursuing, and the basic parallelization scheme we used. It then describes the optimizations that were instrumental in increasing performance, and presents performance results on benchmark simulations.

Performance analysis of quantum access network using code division multiple access model

International Nuclear Information System (INIS)

Hu Linxi; Yang Can; He Guangqiang

2017-01-01

A quantum access network has been implemented by frequency division multiple access and time division multiple access, while code division multiple access is limited for its difficulty to realize the orthogonality of the code. Recently, the chaotic phase shifters were proposed to guarantee the orthogonality by different chaotic signals and spread the spectral content of the quantum states. In this letter, we propose to implement the code division multiple access quantum network by using chaotic phase shifters and synchronization. Due to the orthogonality of the different chaotic phase shifter, every pair of users can faithfully transmit quantum information through a common channel and have little crosstalk between different users. Meanwhile, the broadband spectra of chaotic signals efficiently help the quantum states to defend against channel loss and noise. (paper)

Efficient Routing in Wireless Sensor Networks with Multiple Sessions

Directory of Open Access Journals (Sweden)

Dianjie Lu

2014-05-01

Full Text Available Wireless Sensor Networks (WSNs are subject to node failures because of limited energy and link unreliability which makes the design of routing protocols in such networks a challenging task. The multipath routing scheme is an optimal alternative to address this problem which splits the traffic across multiple paths instead of routing all the traffic along a single path. However, using more paths introduces more contentions which degrade energy efficiency. The problem becomes even more difficult in the scenario of multiple sessions since different source-destination pairs may pass the same link which makes the flow distribution of each link uncertain. Our goal is to minimize the energy cost and provide the robust transmission by choosing the optimal paths. We first study the problem from a theoretical standpoint by mapping it to the multi-commodity network design problem. Since it is hard to build a global addressing scheme due to the great number of sensor nodes, we propose a Distributed Energy Efficient Routing protocol (D2ER. In D2ER, we employ the transportation method which can optimize the flow distribution with minimal energy consumption. Simulation results demonstrate that our optimal algorithm can save energy drastically.

Synthetic Approach to biomolecular science by cyborg supramolecular chemistry.

Science.gov (United States)

Kurihara, Kensuke; Matsuo, Muneyuki; Yamaguchi, Takumi; Sato, Sota

2018-02-01

To imitate the essence of living systems via synthetic chemistry approaches has been attempted. With the progress in supramolecular chemistry, it has become possible to synthesize molecules of a size and complexity close to those of biomacromolecules. Recently, the combination of precisely designed supramolecules with biomolecules has generated structural platforms for designing and creating unique molecular systems. Bridging between synthetic chemistry and biomolecular science is also developing methodologies for the creation of artificial cellular systems. This paper provides an overview of the recently expanding interdisciplinary research to fuse artificial molecules with biomolecules, that can deepen our understanding of the dynamical ordering of biomolecules. Using bottom-up approaches based on the precise chemical design, synthesis and hybridization of artificial molecules with biological materials have been realizing the construction of sophisticated platforms having the fundamental functions of living systems. The effective hybrid, molecular cyborg, approaches enable not only the establishment of dynamic systems mimicking nature and thus well-defined models for biophysical understanding, but also the creation of those with highly advanced, integrated functions. This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato. Copyright © 2017 Elsevier B.V. All rights reserved.

Maximizing the Lifetime of Wireless Sensor Networks Using Multiple Sets of Rendezvous

Directory of Open Access Journals (Sweden)

Bo Li

2015-01-01

Full Text Available In wireless sensor networks (WSNs, there is a “crowded center effect” where the energy of nodes located near a data sink drains much faster than other nodes resulting in a short network lifetime. To mitigate the “crowded center effect,” rendezvous points (RPs are used to gather data from other nodes. In order to prolong the lifetime of WSN further, we propose using multiple sets of RPs in turn to average the energy consumption of the RPs. The problem is how to select the multiple sets of RPs and how long to use each set of RPs. An optimal algorithm and a heuristic algorithm are proposed to address this problem. The optimal algorithm is highly complex and only suitable for small scale WSN. The performance of the proposed algorithms is evaluated through simulations. The simulation results indicate that the heuristic algorithm approaches the optimal one and that using multiple RP sets can significantly prolong network lifetime.

Synergy of Two Highly Specific Biomolecular Recognition Events

DEFF Research Database (Denmark)

Ejlersen, Maria; Christensen, Niels Johan; Sørensen, Kasper K

2018-01-01

Two highly specific biomolecular recognition events, nucleic acid duplex hybridization and DNA-peptide recognition in the minor groove, were coalesced in a miniature ensemble for the first time by covalently attaching a natural AT-hook peptide motif to nucleic acid duplexes via a 2'-amino......-LNA scaffold. A combination of molecular dynamics simulations and ultraviolet thermal denaturation studies revealed high sequence-specific affinity of the peptide-oligonucleotide conjugates (POCs) when binding to complementary DNA strands, leveraging the bioinformation encrypted in the minor groove of DNA...

MPBEC, a Matlab Program for Biomolecular Electrostatic Calculations.

Science.gov (United States)

Vergara-Perez, Sandra; Marucho, Marcelo

2016-01-01

One of the most used and efficient approaches to compute electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation. There are several software packages available that solve the PB equation for molecules in aqueous electrolyte solutions. Most of these software packages are useful for scientists with specialized training and expertise in computational biophysics. However, the user is usually required to manually take several important choices, depending on the complexity of the biological system, to successfully obtain the numerical solution of the PB equation. This may become an obstacle for researchers, experimentalists, even students with no special training in computational methodologies. Aiming to overcome this limitation, in this article we present MPBEC, a free, cross-platform, open-source software that provides non-experts in the field an easy and efficient way to perform biomolecular electrostatic calculations on single processor computers. MPBEC is a Matlab script based on the Adaptative Poisson Boltzmann Solver, one of the most popular approaches used to solve the PB equation. MPBEC does not require any user programming, text editing or extensive statistical skills, and comes with detailed user-guide documentation. As a unique feature, MPBEC includes a useful graphical user interface (GUI) application which helps and guides users to configure and setup the optimal parameters and approximations to successfully perform the required biomolecular electrostatic calculations. The GUI also incorporates visualization tools to facilitate users pre- and post- analysis of structural and electrical properties of biomolecules.

MPBEC, a Matlab Program for Biomolecular Electrostatic Calculations

Science.gov (United States)

Vergara-Perez, Sandra; Marucho, Marcelo

2016-01-01

One of the most used and efficient approaches to compute electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation. There are several software packages available that solve the PB equation for molecules in aqueous electrolyte solutions. Most of these software packages are useful for scientists with specialized training and expertise in computational biophysics. However, the user is usually required to manually take several important choices, depending on the complexity of the biological system, to successfully obtain the numerical solution of the PB equation. This may become an obstacle for researchers, experimentalists, even students with no special training in computational methodologies. Aiming to overcome this limitation, in this article we present MPBEC, a free, cross-platform, open-source software that provides non-experts in the field an easy and efficient way to perform biomolecular electrostatic calculations on single processor computers. MPBEC is a Matlab script based on the Adaptative Poisson-Boltzmann Solver, one of the most popular approaches used to solve the PB equation. MPBEC does not require any user programming, text editing or extensive statistical skills, and comes with detailed user-guide documentation. As a unique feature, MPBEC includes a useful graphical user interface (GUI) application which helps and guides users to configure and setup the optimal parameters and approximations to successfully perform the required biomolecular electrostatic calculations. The GUI also incorporates visualization tools to facilitate users pre- and post-analysis of structural and electrical properties of biomolecules.

Modified-hybrid optical neural network filter for multiple object recognition within cluttered scenes

Science.gov (United States)

Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.

2009-08-01

Motivated by the non-linear interpolation and generalization abilities of the hybrid optical neural network filter between the reference and non-reference images of the true-class object we designed the modifiedhybrid optical neural network filter. We applied an optical mask to the hybrid optical neural network's filter input. The mask was built with the constant weight connections of a randomly chosen image included in the training set. The resulted design of the modified-hybrid optical neural network filter is optimized for performing best in cluttered scenes of the true-class object. Due to the shift invariance properties inherited by its correlator unit the filter can accommodate multiple objects of the same class to be detected within an input cluttered image. Additionally, the architecture of the neural network unit of the general hybrid optical neural network filter allows the recognition of multiple objects of different classes within the input cluttered image by modifying the output layer of the unit. We test the modified-hybrid optical neural network filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. The filter is shown to exhibit with a single pass over the input data simultaneously out-of-plane rotation, shift invariance and good clutter tolerance. It is able to successfully detect and classify correctly the true-class objects within background clutter for which there has been no previous training.

Computing all hybridization networks for multiple binary phylogenetic input trees.

Science.gov (United States)

Albrecht, Benjamin

2015-07-30

The computation of phylogenetic trees on the same set of species that are based on different orthologous genes can lead to incongruent trees. One possible explanation for this behavior are interspecific hybridization events recombining genes of different species. An important approach to analyze such events is the computation of hybridization networks. This work presents the first algorithm computing the hybridization number as well as a set of representative hybridization networks for multiple binary phylogenetic input trees on the same set of taxa. To improve its practical runtime, we show how this algorithm can be parallelized. Moreover, we demonstrate the efficiency of the software Hybroscale, containing an implementation of our algorithm, by comparing it to PIRNv2.0, which is so far the best available software computing the exact hybridization number for multiple binary phylogenetic trees on the same set of taxa. The algorithm is part of the software Hybroscale, which was developed specifically for the investigation of hybridization networks including their computation and visualization. Hybroscale is freely available(1) and runs on all three major operating systems. Our simulation study indicates that our approach is on average 100 times faster than PIRNv2.0. Moreover, we show how Hybroscale improves the interpretation of the reported hybridization networks by adding certain features to its graphical representation.

Application of Hidden Markov Models in Biomolecular Simulations.

Science.gov (United States)

Shukla, Saurabh; Shamsi, Zahra; Moffett, Alexander S; Selvam, Balaji; Shukla, Diwakar

2017-01-01

Hidden Markov models (HMMs) provide a framework to analyze large trajectories of biomolecular simulation datasets. HMMs decompose the conformational space of a biological molecule into finite number of states that interconvert among each other with certain rates. HMMs simplify long timescale trajectories for human comprehension, and allow comparison of simulations with experimental data. In this chapter, we provide an overview of building HMMs for analyzing bimolecular simulation datasets. We demonstrate the procedure for building a Hidden Markov model for Met-enkephalin peptide simulation dataset and compare the timescales of the process.

Biomolecular solid state NMR with magic-angle spinning at 25K.

Science.gov (United States)

Thurber, Kent R; Tycko, Robert

2008-12-01

A magic-angle spinning (MAS) probe has been constructed which allows the sample to be cooled with helium, while the MAS bearing and drive gases are nitrogen. The sample can be cooled to 25K using roughly 3 L/h of liquid helium, while the 4-mm diameter rotor spins at 6.7 kHz with good stability (+/-5 Hz) for many hours. Proton decoupling fields up to at least 130 kHz can be applied. This helium-cooled MAS probe enables a variety of one-dimensional and two-dimensional NMR experiments on biomolecular solids and other materials at low temperatures, with signal-to-noise proportional to 1/T. We show examples of low-temperature (13)C NMR data for two biomolecular samples, namely the peptide Abeta(14-23) in the form of amyloid fibrils and the protein HP35 in frozen glycerol/water solution. Issues related to temperature calibration, spin-lattice relaxation at low temperatures, paramagnetic doping of frozen solutions, and (13)C MAS NMR linewidths are discussed.

Investigating biomolecular recognition at the cell surface using atomic force microscopy.

Science.gov (United States)

Wang, Congzhou; Yadavalli, Vamsi K

2014-05-01

Probing the interaction forces that drive biomolecular recognition on cell surfaces is essential for understanding diverse biological processes. Force spectroscopy has been a widely used dynamic analytical technique, allowing measurement of such interactions at the molecular and cellular level. The capabilities of working under near physiological environments, combined with excellent force and lateral resolution make atomic force microscopy (AFM)-based force spectroscopy a powerful approach to measure biomolecular interaction forces not only on non-biological substrates, but also on soft, dynamic cell surfaces. Over the last few years, AFM-based force spectroscopy has provided biophysical insight into how biomolecules on cell surfaces interact with each other and induce relevant biological processes. In this review, we focus on describing the technique of force spectroscopy using the AFM, specifically in the context of probing cell surfaces. We summarize recent progress in understanding the recognition and interactions between macromolecules that may be found at cell surfaces from a force spectroscopy perspective. We further discuss the challenges and future prospects of the application of this versatile technique. Copyright © 2014 Elsevier Ltd. All rights reserved.

Optically transparent multiple access networks employing incoherent spectral codes

NARCIS (Netherlands)

Huiszoon, B.

2008-01-01

This Ph.D. thesis is divided into 7 chapters to provide the reader an overview of the main results achieved in di®erent sub-topics of the study towards optically transparent multiple access networks employing incoherent spectral codes taking into account wireless transmission aspects. The work

Non-Orthogonal Multiple Access for Ubiquitous Wireless Sensor Networks.

Science.gov (United States)

Anwar, Asim; Seet, Boon-Chong; Ding, Zhiguo

2018-02-08

Ubiquitous wireless sensor networks (UWSNs) have become a critical technology for enabling smart cities and other ubiquitous monitoring applications. Their deployment, however, can be seriously hampered by the spectrum available to the sheer number of sensors for communication. To support the communication needs of UWSNs without requiring more spectrum resources, the power-domain non-orthogonal multiple access (NOMA) technique originally proposed for 5th Generation (5G) cellular networks is investigated for UWSNs for the first time in this paper. However, unlike 5G networks that operate in the licensed spectrum, UWSNs mostly operate in unlicensed spectrum where sensors also experience cross-technology interferences from other devices sharing the same spectrum. In this paper, we model the interferences from various sources at the sensors using stochastic geometry framework. To evaluate the performance, we derive a theorem and present new closed form expression for the outage probability of the sensors in a downlink scenario under interference limited environment. In addition, diversity analysis for the ordered NOMA users is performed. Based on the derived outage probability, we evaluate the average link throughput and energy consumption efficiency of NOMA against conventional orthogonal multiple access (OMA) technique in UWSNs. Further, the required computational complexity for the NOMA users is presented.

U.S. Department of Defense Multiple-Parameter Biodosimetry Network

International Nuclear Information System (INIS)

Blakely, William F.; Hoefer, Matthew H.; Huff, L. Andrew; Romanyukha, Alexander; Hayes, Selena M.; Williams, Anthony; Sharp, Thad; Reyes, Ricardo A.; Stewart, H. Michael Jr

2016-01-01

The U.S. Department of Defense (US-DOD) service members are at risk of exposure to ionizing radiation due to radiation accidents, terrorist attacks and national defense activities. The use of biodosimetry is a standard of care for the triage and treatment of radiation injuries. Resources and procedures need to be established to implement a multiple-parameter biodosimetry system coupled with expert medial guidance to provide an integrated radiation diagnostic system to meet US-DOD requirements. Current US-DOD biodosimetry capabilities were identified and recommendations to fill the identified gaps are provided. A US-DOD Multi-parametric Biodosimetry Network, based on the expertise that resides at the Armed Forces Radiobiology Research Institute and the Naval Dosimetry Center, was designed. This network based on the use of multiple biodosimetry modalities would provide diagnostic and triage capabilities needed to meet US-DOD requirements. These are not available with sufficient capacity elsewhere but could be needed urgently after a major radiological/nuclear event. (authors)

Integrative NMR for biomolecular research

International Nuclear Information System (INIS)

Lee, Woonghee; Cornilescu, Gabriel; Dashti, Hesam; Eghbalnia, Hamid R.; Tonelli, Marco; Westler, William M.; Butcher, Samuel E.; Henzler-Wildman, Katherine A.; Markley, John L.

2016-01-01

NMR spectroscopy is a powerful technique for determining structural and functional features of biomolecules in physiological solution as well as for observing their intermolecular interactions in real-time. However, complex steps associated with its practice have made the approach daunting for non-specialists. We introduce an NMR platform that makes biomolecular NMR spectroscopy much more accessible by integrating tools, databases, web services, and video tutorials that can be launched by simple installation of NMRFAM software packages or using a cross-platform virtual machine that can be run on any standard laptop or desktop computer. The software package can be downloaded freely from the NMRFAM software download page ( http://pine.nmrfam.wisc.edu/download-packages.html http://pine.nmrfam.wisc.edu/download_packages.html ), and detailed instructions are available from the Integrative NMR Video Tutorial page ( http://pine.nmrfam.wisc.edu/integrative.html http://pine.nmrfam.wisc.edu/integrative.html ).

Integrative NMR for biomolecular research

Energy Technology Data Exchange (ETDEWEB)

Lee, Woonghee, E-mail: whlee@nmrfam.wisc.edu; Cornilescu, Gabriel; Dashti, Hesam; Eghbalnia, Hamid R.; Tonelli, Marco; Westler, William M.; Butcher, Samuel E.; Henzler-Wildman, Katherine A.; Markley, John L., E-mail: markley@nmrfam.wisc.edu [University of Wisconsin-Madison, National Magnetic Resonance Facility at Madison and Biochemistry Department (United States)

2016-04-15

NMR spectroscopy is a powerful technique for determining structural and functional features of biomolecules in physiological solution as well as for observing their intermolecular interactions in real-time. However, complex steps associated with its practice have made the approach daunting for non-specialists. We introduce an NMR platform that makes biomolecular NMR spectroscopy much more accessible by integrating tools, databases, web services, and video tutorials that can be launched by simple installation of NMRFAM software packages or using a cross-platform virtual machine that can be run on any standard laptop or desktop computer. The software package can be downloaded freely from the NMRFAM software download page ( http://pine.nmrfam.wisc.edu/download-packages.html http://pine.nmrfam.wisc.edu/download{sub p}ackages.html ), and detailed instructions are available from the Integrative NMR Video Tutorial page ( http://pine.nmrfam.wisc.edu/integrative.html http://pine.nmrfam.wisc.edu/integrative.html ).

Optical Multiple Access Network (OMAN) for advanced processing satellite applications

Science.gov (United States)

Mendez, Antonio J.; Gagliardi, Robert M.; Park, Eugene; Ivancic, William D.; Sherman, Bradley D.

1991-01-01

An OMAN breadboard for exploring advanced processing satellite circuit switch applications is introduced. Network architecture, hardware trade offs, and multiple user interference issues are presented. The breadboard test set up and experimental results are discussed.

Simulation of noise-assisted transport via optical cavity networks

International Nuclear Information System (INIS)

Caruso, Filippo; Plenio, Martin B.; Spagnolo, Nicolo; Vitelli, Chiara; Sciarrino, Fabio

2011-01-01

Recently, the presence of noise has been found to play a key role in assisting the transport of energy and information in complex quantum networks and even in biomolecular systems. Here we propose an experimentally realizable optical network scheme for the demonstration of the basic mechanisms underlying noise-assisted transport. The proposed system consists of a network of coupled quantum-optical cavities, injected with a single photon, whose transmission efficiency can be measured. Introducing dephasing in the photon path, this system exhibits a characteristic enhancement of the transport efficiency that can be observed with presently available technology.

Multiple-point statistical prediction on fracture networks at Yucca Mountain

International Nuclear Information System (INIS)

Liu, X.Y; Zhang, C.Y.; Liu, Q.S.; Birkholzer, J.T.

2009-01-01

In many underground nuclear waste repository systems, such as at Yucca Mountain, water flow rate and amount of water seepage into the waste emplacement drifts are mainly determined by hydrological properties of fracture network in the surrounding rock mass. Natural fracture network system is not easy to describe, especially with respect to its connectivity which is critically important for simulating the water flow field. In this paper, we introduced a new method for fracture network description and prediction, termed multi-point-statistics (MPS). The process of the MPS method is to record multiple-point statistics concerning the connectivity patterns of a fracture network from a known fracture map, and to reproduce multiple-scale training fracture patterns in a stochastic manner, implicitly and directly. It is applied to fracture data to study flow field behavior at the Yucca Mountain waste repository system. First, the MPS method is used to create a fracture network with an original fracture training image from Yucca Mountain dataset. After we adopt a harmonic and arithmetic average method to upscale the permeability to a coarse grid, THM simulation is carried out to study near-field water flow in the surrounding waste emplacement drifts. Our study shows that connectivity or patterns of fracture networks can be grasped and reconstructed by MPS methods. In theory, it will lead to better prediction of fracture system characteristics and flow behavior. Meanwhile, we can obtain variance from flow field, which gives us a way to quantify model uncertainty even in complicated coupled THM simulations. It indicates that MPS can potentially characterize and reconstruct natural fracture networks in a fractured rock mass with advantages of quantifying connectivity of fracture system and its simulation uncertainty simultaneously.

Study on multiple-hops performance of MOOC sequences-based optical labels for OPS networks

Science.gov (United States)

Zhang, Chongfu; Qiu, Kun; Ma, Chunli

2009-11-01

In this paper, we utilize a new study method that is under independent case of multiple optical orthogonal codes to derive the probability function of MOOCS-OPS networks, discuss the performance characteristics for a variety of parameters, and compare some characteristics of the system employed by single optical orthogonal code or multiple optical orthogonal codes sequences-based optical labels. The performance of the system is also calculated, and our results verify that the method is effective. Additionally it is found that performance of MOOCS-OPS networks would, negatively, be worsened, compared with single optical orthogonal code-based optical label for optical packet switching (SOOC-OPS); however, MOOCS-OPS networks can greatly enlarge the scalability of optical packet switching networks.

3D Filament Network Segmentation with Multiple Active Contours

Science.gov (United States)

Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

2014-03-01

Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and microtubules. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we developed a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D TIRF Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy.

Robustness analysis of uncertain dynamical neural networks with multiple time delays.

Science.gov (United States)

Senan, Sibel

2015-10-01

This paper studies the problem of global robust asymptotic stability of the equilibrium point for the class of dynamical neural networks with multiple time delays with respect to the class of slope-bounded activation functions and in the presence of the uncertainties of system parameters of the considered neural network model. By using an appropriate Lyapunov functional and exploiting the properties of the homeomorphism mapping theorem, we derive a new sufficient condition for the existence, uniqueness and global robust asymptotic stability of the equilibrium point for the class of neural networks with multiple time delays. The obtained stability condition basically relies on testing some relationships imposed on the interconnection matrices of the neural system, which can be easily verified by using some certain properties of matrices. An instructive numerical example is also given to illustrate the applicability of our result and show the advantages of this new condition over the previously reported corresponding results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Adaptive multi-node multiple input and multiple output (MIMO) transmission for mobile wireless multimedia sensor networks.

Science.gov (United States)

Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo

2013-10-02

Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase.

Multiple leakage localization and leak size estimation in water networks

NARCIS (Netherlands)

Abbasi, N.; Habibi, H.; Hurkens, C.A.J.; Klabbers, M.D.; Tijsseling, A.S.; Eijndhoven, van S.J.L.

2012-01-01

Water distribution networks experience considerable losses due to leakage, often at multiple locations simultaneously. Leakage detection and localization based on sensor placement and online pressure monitoring could be fast and economical. Using the difference between estimated and measured

Versatile single-molecule multi-color excitation and detection fluorescence setup for studying biomolecular dynamics

KAUST Repository

Sobhy, M. A.; Elshenawy, M. M.; Takahashi, Masateru; Whitman, B. H.; Walter, N. G.; Hamdan, S. M.

2011-01-01

Single-molecule fluorescence imaging is at the forefront of tools applied to study biomolecular dynamics both in vitro and in vivo. The ability of the single-molecule fluorescence microscope to conduct simultaneous multi-color excitation

SPATKIN: a simulator for rule-based modeling of biomolecular site dynamics on surfaces.

Science.gov (United States)

Kochanczyk, Marek; Hlavacek, William S; Lipniacki, Tomasz

2017-11-15

Rule-based modeling is a powerful approach for studying biomolecular site dynamics. Here, we present SPATKIN, a general-purpose simulator for rule-based modeling in two spatial dimensions. The simulation algorithm is a lattice-based method that tracks Brownian motion of individual molecules and the stochastic firing of rule-defined reaction events. Because rules are used as event generators, the algorithm is network-free, meaning that it does not require to generate the complete reaction network implied by rules prior to simulation. In a simulation, each molecule (or complex of molecules) is taken to occupy a single lattice site that cannot be shared with another molecule (or complex). SPATKIN is capable of simulating a wide array of membrane-associated processes, including adsorption, desorption and crowding. Models are specified using an extension of the BioNetGen language, which allows to account for spatial features of the simulated process. The C ++ source code for SPATKIN is distributed freely under the terms of the GNU GPLv3 license. The source code can be compiled for execution on popular platforms (Windows, Mac and Linux). An installer for 64-bit Windows and a macOS app are available. The source code and precompiled binaries are available at the SPATKIN Web site (http://pmbm.ippt.pan.pl/software/spatkin). spatkin.simulator@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Ion induced fragmentation of biomolecular systems at low collision energies

International Nuclear Information System (INIS)

Bernigaud, V; Adoui, L; Chesnel, J Y; Rangama, J; Huber, B A; Manil, B; Alvarado, F; Bari, S; Hoekstra, R; Postma, J; Schlathoelter, T

2009-01-01

In this paper, we present results of different collision experiments between multiply charged ions at low collision energies (in the keV-region) and biomolecular systems. This kind of interaction allows to remove electrons form the biomolecule without transferring a large amount of vibrational excitation energy. Nevertheless, following the ionization of the target, fragmentation of biomolecular species may occur. It is the main objective of this work to study the physical processes involved in the dissociation of highly electronically excited systems. In order to elucidate the intrinsic properties of certain biomolecules (porphyrins and amino acids) we have performed experiments in the gas phase with isolated systems. The obtained results demonstrate the high stability of porphyrins after electron removal. Furthermore, a dependence of the fragmentation pattern produced by multiply charged ions on the isomeric structure of the alanine molecule has been shown. By considering the presence of other surrounding biomolecules (clusters of nucleobases), a strong influence of the environment of the biomolecule on the fragmentation channels and their modification, has been clearly proven. This result is explained, in the thymine and uracil case, by the formation of hydrogen bonds between O and H atoms, which is known to favor planar cluster geometries.

Biomolecular simulations on petascale: promises and challenges

International Nuclear Information System (INIS)

Agarwal, Pratul K; Alam, Sadaf R

2006-01-01

Proteins work as highly efficient machines at the molecular level and are responsible for a variety of processes in all living cells. There is wide interest in understanding these machines for implications in biochemical/biotechnology industries as well as in health related fields. Over the last century, investigations of proteins based on a variety of experimental techniques have provided a wealth of information. More recently, theoretical and computational modeling using large scale simulations is providing novel insights into the functioning of these machines. The next generation supercomputers with petascale computing power, hold great promises as well as challenges for the biomolecular simulation scientists. We briefly discuss the progress being made in this area

Downlink Non-Orthogonal Multiple Access (NOMA) in Poisson Networks

KAUST Repository

Ali, Konpal S.

2018-03-21

A network model is considered where Poisson distributed base stations transmit to $N$ power-domain non-orthogonal multiple access (NOMA) users (UEs) each that employ successive interference cancellation (SIC) for decoding. We propose three models for the clustering of NOMA UEs and consider two different ordering techniques for the NOMA UEs: mean signal power-based and instantaneous signal-to-intercell-interference-and-noise-ratio-based. For each technique, we present a signal-to-interference-and-noise ratio analysis for the coverage of the typical UE. We plot the rate region for the two-user case and show that neither ordering technique is consistently superior to the other. We propose two efficient algorithms for finding a feasible resource allocation that maximize the cell sum rate $\\\\mathcal{R}_{\\ m tot}$, for general $N$, constrained to: 1) a minimum rate $\\\\mathcal{T}$ for each UE, 2) identical rates for all UEs. We show the existence of: 1) an optimum $N$ that maximizes the constrained $\\\\mathcal{R}_{\\ m tot}$ given a set of network parameters, 2) a critical SIC level necessary for NOMA to outperform orthogonal multiple access. The results highlight the importance in choosing the network parameters $N$, the constraints, and the ordering technique to balance the $\\\\mathcal{R}_{\\ m tot}$ and fairness requirements. We also show that interference-aware UE clustering can significantly improve performance.

Downlink Non-Orthogonal Multiple Access (NOMA) in Poisson Networks

KAUST Repository

Ali, Konpal S.; Haenggi, Martin; Elsawy, Hesham; Chaaban, Anas; Alouini, Mohamed-Slim

2018-01-01

A network model is considered where Poisson distributed base stations transmit to $N$ power-domain non-orthogonal multiple access (NOMA) users (UEs) each that employ successive interference cancellation (SIC) for decoding. We propose three models for the clustering of NOMA UEs and consider two different ordering techniques for the NOMA UEs: mean signal power-based and instantaneous signal-to-intercell-interference-and-noise-ratio-based. For each technique, we present a signal-to-interference-and-noise ratio analysis for the coverage of the typical UE. We plot the rate region for the two-user case and show that neither ordering technique is consistently superior to the other. We propose two efficient algorithms for finding a feasible resource allocation that maximize the cell sum rate $\\mathcal{R}_{\\rm tot}$, for general $N$, constrained to: 1) a minimum rate $\\mathcal{T}$ for each UE, 2) identical rates for all UEs. We show the existence of: 1) an optimum $N$ that maximizes the constrained $\\mathcal{R}_{\\rm tot}$ given a set of network parameters, 2) a critical SIC level necessary for NOMA to outperform orthogonal multiple access. The results highlight the importance in choosing the network parameters $N$, the constraints, and the ordering technique to balance the $\\mathcal{R}_{\\rm tot}$ and fairness requirements. We also show that interference-aware UE clustering can significantly improve performance.

Survey of Network-Based Approaches to Research of Cardiovascular Diseases

Directory of Open Access Journals (Sweden)

Anida Sarajlić

2014-01-01

Full Text Available Cardiovascular diseases (CVDs are the leading health problem worldwide. Investigating causes and mechanisms of CVDs calls for an integrative approach that would take into account its complex etiology. Biological networks generated from available data on biomolecular interactions are an excellent platform for understanding interconnectedness of all processes within a living cell, including processes that underlie diseases. Consequently, topology of biological networks has successfully been used for identifying genes, pathways, and modules that govern molecular actions underlying various complex diseases. Here, we review approaches that explore and use relationships between topological properties of biological networks and mechanisms underlying CVDs.

Zwitterionic Silane Copolymer for Ultra-Stable and Bright Biomolecular Probes Based on Fluorescent Quantum Dot Nanoclusters.

Science.gov (United States)

Dembele, Fatimata; Tasso, Mariana; Trapiella-Alfonso, Laura; Xu, Xiangzhen; Hanafi, Mohamed; Lequeux, Nicolas; Pons, Thomas

2017-05-31

Fluorescent semiconductor quantum dots (QDs) exhibit several unique properties that make them suitable candidates for biomolecular sensing, including high brightness, photostability, broad excitation, and narrow emission spectra. Assembling these QDs into robust and functionalizable nanosized clusters (QD-NSCs) can provide fluorescent probes that are several orders of magnitude brighter than individual QDs, thus allowing an even greater sensitivity of detection with simplified instrumentation. However, the formation of compact, antifouling, functionalizable, and stable QD-NSCs remains a challenging task, especially for a use at ultralow concentrations for single-molecule detection. Here, we describe the development of fluorescent QD-NSCs envisioned as a tool for fast and sensitive biomolecular recognition. First, QDs were assembled into very compact 100-150 nm diameter spherical aggregates; the final QD-NSCs were obtained by growing a cross-linked silica shell around these aggregates. Hydrolytic stability in several concentration and pH conditions is a key requirement for a potential and efficient single-molecule detection tool. However, the hydrolysis of Si-O-Si bonds leads to desorption of monosilane-based surface groups at very low silica concentrations or in a slightly basic medium. Thus, we designed a novel multidentate copolymer composed of multiple silane as well as zwitterionic monomers. Coating silica beads with this multidentate copolymer provided a robust surface chemistry that was demonstrated to be stable against hydrolysis, even at low concentrations. Copolymer-coated silica beads also showed low fouling properties and high colloidal stability in saline solutions. Furthermore, incorporation of additional azido-monomers enabled easy functionalization of QD-NSCs using copper-free bio-orthogonal cyclooctyne-azide click chemistry, as demonstrated by a biotin-streptavidin affinity test.

Electrostatics in biomolecular simulations : where are we now and where are we heading?

NARCIS (Netherlands)

Karttunen, M.E.J.; Rottler, J.; Vattulainen, I.; Sagui, C.

2008-01-01

Chapter 2. In this review, we discuss current methods and developments in the treatment of electrostatic interactions in biomolecular and soft matter simulations. We review the current ‘work horses’, namely, Ewald summation based methods such the Particle-Mesh Ewald, and others, and also newer

Lower Bounds on the Maximum Energy Benefit of Network Coding for Wireless Multiple Unicast

NARCIS (Netherlands)

Goseling, J.; Matsumoto, R.; Uyematsu, T.; Weber, J.H.

2010-01-01

We consider the energy savings that can be obtained by employing network coding instead of plain routing in wireless multiple unicast problems. We establish lower bounds on the benefit of network coding, defined as the maximum of the ratio of the minimum energy required by routing and network coding

Lower bounds on the maximum energy benefit of network coding for wireless multiple unicast

NARCIS (Netherlands)

Goseling, Jasper; Matsumoto, Ryutaroh; Uyematsu, Tomohiko; Weber, Jos H.

2010-01-01

We consider the energy savings that can be obtained by employing network coding instead of plain routing in wireless multiple unicast problems. We establish lower bounds on the benefit of network coding, defined as the maximum of the ratio of the minimum energy required by routing and network coding

Default mode network links to visual hallucinations: A comparison between Parkinson's disease and multiple system atrophy.

Science.gov (United States)

Franciotti, Raffaella; Delli Pizzi, Stefano; Perfetti, Bernardo; Tartaro, Armando; Bonanni, Laura; Thomas, Astrid; Weis, Luca; Biundo, Roberta; Antonini, Angelo; Onofrj, Marco

2015-08-01

Studying default mode network activity or connectivity in different parkinsonisms, with or without visual hallucinations, could highlight its roles in clinical phenotypes' expression. Multiple system atrophy is the archetype of parkinsonism without visual hallucinations, variably appearing instead in Parkinson's disease (PD). We aimed to evaluate default mode network functions in multiple system atrophy in comparison with PD. Functional magnetic resonance imaging evaluated default mode network activity and connectivity in 15 multiple system atrophy patients, 15 healthy controls, 15 early PD patients matched for disease duration, 30 severe PD patients (15 with and 15 without visual hallucinations), matched with multiple system atrophy for disease severity. Cortical thickness and neuropsychological evaluations were also performed. Multiple system atrophy had reduced default mode network activity compared with controls and PD with hallucinations, and no differences with PD (early or severe) without hallucinations. In PD with visual hallucinations, activity and connectivity was preserved compared with controls and higher than in other groups. In early PD, connectivity was lower than in controls but higher than in multiple system atrophy and severe PD without hallucinations. Cortical thickness was reduced in severe PD, with and without hallucinations, and correlated only with disease duration. Higher anxiety scores were found in patients without hallucinations. Default mode network activity and connectivity was higher in PD with visual hallucinations and reduced in multiple system atrophy and PD without visual hallucinations. Cortical thickness comparisons suggest that functional, rather than structural, changes underlie the activity and connectivity differences. © 2015 International Parkinson and Movement Disorder Society.

Motor network efficiency and disability in multiple sclerosis

Science.gov (United States)

Yaldizli, Özgür; Sethi, Varun; Muhlert, Nils; Liu, Zheng; Samson, Rebecca S.; Altmann, Daniel R.; Ron, Maria A.; Wheeler-Kingshott, Claudia A.M.; Miller, David H.; Chard, Declan T.

2015-01-01

Objective: To develop a composite MRI-based measure of motor network integrity, and determine if it explains disability better than conventional MRI measures in patients with multiple sclerosis (MS). Methods: Tract density imaging and constrained spherical deconvolution tractography were used to identify motor network connections in 22 controls. Fractional anisotropy (FA), magnetization transfer ratio (MTR), and normalized volume were computed in each tract in 71 people with relapse onset MS. Principal component analysis was used to distill the FA, MTR, and tract volume data into a single metric for each tract, which in turn was used to compute a composite measure of motor network efficiency (composite NE) using graph theory. Associations were investigated between the Expanded Disability Status Scale (EDSS) and the following MRI measures: composite motor NE, NE calculated using FA alone, FA averaged in the combined motor network tracts, brain T2 lesion volume, brain parenchymal fraction, normal-appearing white matter MTR, and cervical cord cross-sectional area. Results: In univariable analysis, composite motor NE explained 58% of the variation in EDSS in the whole MS group, more than twice that of the other MRI measures investigated. In a multivariable regression model, only composite NE and disease duration were independently associated with EDSS. Conclusions: A composite MRI measure of motor NE was able to predict disability substantially better than conventional non-network-based MRI measures. PMID:26320199

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks.

Science.gov (United States)

Shen, Yiwen; Hattink, Maarten H N; Samadi, Payman; Cheng, Qixiang; Hu, Ziyiz; Gazman, Alexander; Bergman, Keren

2018-04-16

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. We present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly network testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 µs control plane latency for data-center and high performance computing platforms.

Stability Properties of Network Diversity Multiple Access with Multiple-Antenna Reception and Imperfect Collision Multiplicity Estimation

Directory of Open Access Journals (Sweden)

Ramiro Samano-Robles

2013-01-01

Full Text Available In NDMA (network diversity multiple access, protocol-controlled retransmissions are used to create a virtual MIMO (multiple-input multiple-output system, where collisions can be resolved via source separation. By using this retransmission diversity approach for collision resolution, NDMA is the family of random access protocols with the highest potential throughput. However, several issues remain open today in the modeling and design of this type of protocol, particularly in terms of dynamic stable performance and backlog delay. This paper attempts to partially fill this gap by proposing a Markov model for the study of the dynamic-stable performance of a symmetrical and non-blind NDMA protocol assisted by a multiple-antenna receiver. The model is useful in the study of stability aspects in terms of the backlog-user distribution and average backlog delay. It also allows for the investigation of the different states of the system and the transition probabilities between them. Unlike previous works, the proposed approach considers the imperfect estimation of the collision multiplicity, which is a crucial process to the performance of NDMA. The results suggest that NDMA improves not only the throughput performance over previous solutions, but also the average number of backlogged users, the average backlog delay and, in general, the stability of random access protocols. It is also shown that when multiuser detection conditions degrade, ALOHA-type backlog retransmission becomes relevant to the stable operation of NDMA.

A compact imaging spectroscopic system for biomolecular detections on plasmonic chips.

Science.gov (United States)

Lo, Shu-Cheng; Lin, En-Hung; Wei, Pei-Kuen; Tsai, Wan-Shao

2016-10-17

In this study, we demonstrate a compact imaging spectroscopic system for high-throughput detection of biomolecular interactions on plasmonic chips, based on a curved grating as the key element of light diffraction and light focusing. Both the curved grating and the plasmonic chips are fabricated on flexible plastic substrates using a gas-assisted thermal-embossing method. A fiber-coupled broadband light source and a camera are included in the system. Spectral resolution within 1 nm is achieved in sensing environmental index solutions and protein bindings. The detected sensitivities of the plasmonic chip are comparable with a commercial spectrometer. An extra one-dimensional scanning stage enables high-throughput detection of protein binding on a designed plasmonic chip consisting of several nanoslit arrays with different periods. The detected resonance wavelengths match well with the grating equation under an air environment. Wavelength shifts between 1 and 9 nm are detected for antigens of various concentrations binding with antibodies. A simple, mass-productive and cost-effective method has been demonstrated on the imaging spectroscopic system for real-time, label-free, highly sensitive and high-throughput screening of biomolecular interactions.

Rapid prototyping of nanofluidic systems using size-reduced electrospun nanofibers for biomolecular analysis.

Science.gov (United States)

Park, Seung-Min; Huh, Yun Suk; Szeto, Kylan; Joe, Daniel J; Kameoka, Jun; Coates, Geoffrey W; Edel, Joshua B; Erickson, David; Craighead, Harold G

2010-11-05

Biomolecular transport in nanofluidic confinement offers various means to investigate the behavior of biomolecules in their native aqueous environments, and to develop tools for diverse single-molecule manipulations. Recently, a number of simple nanofluidic fabrication techniques has been demonstrated that utilize electrospun nanofibers as a backbone structure. These techniques are limited by the arbitrary dimension of the resulting nanochannels due to the random nature of electrospinning. Here, a new method for fabricating nanofluidic systems from size-reduced electrospun nanofibers is reported and demonstrated. As it is demonstrated, this method uses the scanned electrospinning technique for generation of oriented sacrificial nanofibers and exposes these nanofibers to harsh, but isotropic etching/heating environments to reduce their cross-sectional dimension. The creation of various nanofluidic systems as small as 20 nm is demonstrated, and practical examples of single biomolecular handling, such as DNA elongation in nanochannels and fluorescence correlation spectroscopic analysis of biomolecules passing through nanochannels, are provided.

Performance of an opportunistic multi-user cognitive network with multiple primary users

KAUST Repository

Khan, Fahd Ahmed

2014-04-01

Consider a multi-user underlay cognitive network where multiple cognitive users, having limited peak transmit power, concurrently share the spectrum with a primary network with multiple users. The channel between the secondary network is assumed to have independent but not identical Nakagami-m fading. The interference channel between the secondary users and the primary users is assumed to have Rayleigh fading. The uplink scenario is considered where a single secondary user is selected for transmission. This opportunistic selection depends on the transmission channel power gain and the interference channel power gain as well as the power allocation policy adopted at the users. Exact closed form expressions for the momentgenerating function, outage performance and the symbol-error-rate performance are derived. The outage performance is also studied in the asymptotic regimes and the generalized diversity gain of this scheduling scheme is derived. Numerical results corroborate the derived analytical results.

DETECTION AND LOCALIZATION OF MULTIPLE SPOOFING ATTACKERS FOR MOBILE WIRELESS NETWORKS

Directory of Open Access Journals (Sweden)

R. Maivizhi

2015-06-01

Full Text Available The openness nature of wireless networks allows adversaries to easily launch variety of spoofing attacks and causes havoc in network performance. Recent approaches used Received Signal Strength (RSS traces, which only detect spoofing attacks in mobile wireless networks. However, it is not always desirable to use these methods as RSS values fluctuate significantly over time due to distance, noise and interference. In this paper, we discusses a novel approach, Mobile spOofing attack DEtection and Localization in WIireless Networks (MODELWIN system, which exploits location information about nodes to detect identity-based spoofing attacks in mobile wireless networks. Also, this approach determines the number of attackers who used the same node identity to masquerade as legitimate device. Moreover, multiple adversaries can be localized accurately. By eliminating attackers the proposed system enhances network performance. We have evaluated our technique through simulation using an 802.11 (WiFi network and an 802.15.4 (Zigbee networks. The results prove that MODELWIN can detect spoofing attacks with a very high detection rate and localize adversaries accurately.

Instrumental biosensors: new perspectives for the analysis of biomolecular interactions.

Science.gov (United States)

Nice, E C; Catimel, B

1999-04-01

The use of instrumental biosensors in basic research to measure biomolecular interactions in real time is increasing exponentially. Applications include protein-protein, protein-peptide, DNA-protein, DNA-DNA, and lipid-protein interactions. Such techniques have been applied to, for example, antibody-antigen, receptor-ligand, signal transduction, and nuclear receptor studies. This review outlines the principles of two of the most commonly used instruments and highlights specific operating parameters that will assist in optimising experimental design, data generation, and analysis.

AIR POLLUITON INDEX PREDICTION USING MULTIPLE NEURAL NETWORKS

Directory of Open Access Journals (Sweden)

Zainal Ahmad

2017-05-01

Full Text Available Air quality monitoring and forecasting tools are necessary for the purpose of taking precautionary measures against air pollution, such as reducing the effect of a predicted air pollution peak on the surrounding population and ecosystem. In this study a single Feed-forward Artificial Neural Network (FANN is shown to be able to predict the Air Pollution Index (API with a Mean Squared Error (MSE and coefficient determination, R2, of 0.1856 and 0.7950 respectively. However, due to the non-robust nature of single FANN, a selective combination of Multiple Neural Networks (MNN is introduced using backward elimination and a forward selection method. The results show that both selective combination methods can improve the robustness and performance of the API prediction with the MSE and R2 of 0.1614 and 0.8210 respectively. This clearly shows that it is possible to reduce the number of networks combined in MNN for API prediction, without losses of any information in terms of the performance of the final API prediction model.

Biana: a software framework for compiling biological interactions and analyzing networks.

Science.gov (United States)

Garcia-Garcia, Javier; Guney, Emre; Aragues, Ramon; Planas-Iglesias, Joan; Oliva, Baldo

2010-01-27

The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein-protein interactions. Without good integration strategies, it is difficult to analyze the whole set of available data and its properties. We introduce BIANA (Biologic Interactions and Network Analysis), a tool for biological information integration and network management. BIANA is a Python framework designed to achieve two major goals: i) the integration of multiple sources of biological information, including biological entities and their relationships, and ii) the management of biological information as a network where entities are nodes and relationships are edges. Moreover, BIANA uses properties of proteins and genes to infer latent biomolecular relationships by transferring edges to entities sharing similar properties. BIANA is also provided as a plugin for Cytoscape, which allows users to visualize and interactively manage the data. A web interface to BIANA providing basic functionalities is also available. The software can be downloaded under GNU GPL license from http://sbi.imim.es/web/BIANA.php. BIANA's approach to data unification solves many of the nomenclature issues common to systems dealing with biological data. BIANA can easily be extended to handle new specific data repositories and new specific data types. The unification protocol allows BIANA to be a flexible tool suitable for different user requirements: non-expert users can use a suggested unification protocol while expert users can define their own specific unification rules.

Multivariate Multiple Regression Models for a Big Data-Empowered SON Framework in Mobile Wireless Networks

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Yoonsu Shin

2016-01-01

Full Text Available In the 5G era, the operational cost of mobile wireless networks will significantly increase. Further, massive network capacity and zero latency will be needed because everything will be connected to mobile networks. Thus, self-organizing networks (SON are needed, which expedite automatic operation of mobile wireless networks, but have challenges to satisfy the 5G requirements. Therefore, researchers have proposed a framework to empower SON using big data. The recent framework of a big data-empowered SON analyzes the relationship between key performance indicators (KPIs and related network parameters (NPs using machine-learning tools, and it develops regression models using a Gaussian process with those parameters. The problem, however, is that the methods of finding the NPs related to the KPIs differ individually. Moreover, the Gaussian process regression model cannot determine the relationship between a KPI and its various related NPs. In this paper, to solve these problems, we proposed multivariate multiple regression models to determine the relationship between various KPIs and NPs. If we assume one KPI and multiple NPs as one set, the proposed models help us process multiple sets at one time. Also, we can find out whether some KPIs are conflicting or not. We implement the proposed models using MapReduce.

NIMEFI: gene regulatory network inference using multiple ensemble feature importance algorithms.

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Joeri Ruyssinck

Full Text Available One of the long-standing open challenges in computational systems biology is the topology inference of gene regulatory networks from high-throughput omics data. Recently, two community-wide efforts, DREAM4 and DREAM5, have been established to benchmark network inference techniques using gene expression measurements. In these challenges the overall top performer was the GENIE3 algorithm. This method decomposes the network inference task into separate regression problems for each gene in the network in which the expression values of a particular target gene are predicted using all other genes as possible predictors. Next, using tree-based ensemble methods, an importance measure for each predictor gene is calculated with respect to the target gene and a high feature importance is considered as putative evidence of a regulatory link existing between both genes. The contribution of this work is twofold. First, we generalize the regression decomposition strategy of GENIE3 to other feature importance methods. We compare the performance of support vector regression, the elastic net, random forest regression, symbolic regression and their ensemble variants in this setting to the original GENIE3 algorithm. To create the ensemble variants, we propose a subsampling approach which allows us to cast any feature selection algorithm that produces a feature ranking into an ensemble feature importance algorithm. We demonstrate that the ensemble setting is key to the network inference task, as only ensemble variants achieve top performance. As second contribution, we explore the effect of using rankwise averaged predictions of multiple ensemble algorithms as opposed to only one. We name this approach NIMEFI (Network Inference using Multiple Ensemble Feature Importance algorithms and show that this approach outperforms all individual methods in general, although on a specific network a single method can perform better. An implementation of NIMEFI has been made

NMR paves the way for atomic level descriptions of sparsely populated, transiently formed biomolecular conformers.

Science.gov (United States)

Sekhar, Ashok; Kay, Lewis E

2013-08-06

The importance of dynamics to biomolecular function is becoming increasingly clear. A description of the structure-function relationship must, therefore, include the role of motion, requiring a shift in paradigm from focus on a single static 3D picture to one where a given biomolecule is considered in terms of an ensemble of interconverting conformers, each with potentially diverse activities. In this Perspective, we describe how recent developments in solution NMR spectroscopy facilitate atomic resolution studies of sparsely populated, transiently formed biomolecular conformations that exchange with the native state. Examples of how this methodology is applied to protein folding and misfolding, ligand binding, and molecular recognition are provided as a means of illustrating both the power of the new techniques and the significant roles that conformationally excited protein states play in biology.

Energy-Aware Routing in Multiple Domains Software-Defined Networks

Directory of Open Access Journals (Sweden)

Adriana FERNÁNDEZ-FERNÁNDEZ

2016-12-01

Full Text Available The growing energy consumption of communication networks has attracted the attention of the networking researchers in the last decade. In this context, the new architecture of Software-Defined Networks (SDN allows a flexible programmability, suitable for the power-consumption optimization problem. In this paper we address the issue of designing a novel distributed routing algorithm that optimizes the power consumption in large scale SDN with multiple domains. The solution proposed, called DEAR (Distributed Energy-Aware Routing, tackles the problem of minimizing the number of links that can be used to satisfy a given data traffic demand under performance constraints such as control traffic delay and link utilization. To this end, we present a complete formulation of the optimization problem that considers routing requirements for control and data plane communications. Simulation results confirm that the proposed solution enables the achievement of significant energy savings.

Image transmission in multicore-fiber code-division multiple access network

Science.gov (United States)

Yang, Guu-Chang; Kwong, Wing C.

1997-01-01

Recently, two-dimensional (2-D) signature patterns were proposed to encode binary digitized image pixels in optical code-division multiple-access (CDMA) networks with 'multicore' fiber. The new technology enables parallel transmission and simultaneous access of 2-D images in multiple-access environment, where these signature patterns are defined as optical orthogonal signature pattern codes (OOSPCs). However, previous work on OOSPCs assumed that the weight of each signature pattern was the same. In this paper, we construct a new family of OOSPCs with the removal of this assumption. Since varying the weight of a user's signature pattern affects that user's performance, this approach is useful for CDMA optical systems with multiple performance requirements.

Energy efficient design for MIMO two-way AF multiple relay networks

KAUST Repository

Alsharoa, Ahmad M.; Ghazzai, Hakim; Alouini, Mohamed-Slim

2014-01-01

This paper studies the energy efficient transmission and the power allocation problem for multiple two-way relay networks equipped with multi-input multi-output antennas where each relay employs an amplify-and-forward strategy. The goal

Tools and Models for Integrating Multiple Cellular Networks

Energy Technology Data Exchange (ETDEWEB)

Gerstein, Mark [Yale Univ., New Haven, CT (United States). Gerstein Lab.

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

Fast Construction of Near Parsimonious Hybridization Networks for Multiple Phylogenetic Trees.

Science.gov (United States)

Mirzaei, Sajad; Wu, Yufeng

2016-01-01

Hybridization networks represent plausible evolutionary histories of species that are affected by reticulate evolutionary processes. An established computational problem on hybridization networks is constructing the most parsimonious hybridization network such that each of the given phylogenetic trees (called gene trees) is "displayed" in the network. There have been several previous approaches, including an exact method and several heuristics, for this NP-hard problem. However, the exact method is only applicable to a limited range of data, and heuristic methods can be less accurate and also slow sometimes. In this paper, we develop a new algorithm for constructing near parsimonious networks for multiple binary gene trees. This method is more efficient for large numbers of gene trees than previous heuristics. This new method also produces more parsimonious results on many simulated datasets as well as a real biological dataset than a previous method. We also show that our method produces topologically more accurate networks for many datasets.

Biomolecular surface construction by PDE transform.

Science.gov (United States)

Zheng, Qiong; Yang, Siyang; Wei, Guo-Wei

2012-03-01

This work proposes a new framework for the surface generation based on the partial differential equation (PDE) transform. The PDE transform has recently been introduced as a general approach for the mode decomposition of images, signals, and data. It relies on the use of arbitrarily high-order PDEs to achieve the time-frequency localization, control the spectral distribution, and regulate the spatial resolution. The present work provides a new variational derivation of high-order PDE transforms. The fast Fourier transform is utilized to accomplish the PDE transform so as to avoid stringent stability constraints in solving high-order PDEs. As a consequence, the time integration of high-order PDEs can be done efficiently with the fast Fourier transform. The present approach is validated with a variety of test examples in two-dimensional and three-dimensional settings. We explore the impact of the PDE transform parameters, such as the PDE order and propagation time, on the quality of resulting surfaces. Additionally, we utilize a set of 10 proteins to compare the computational efficiency of the present surface generation method and a standard approach in Cartesian meshes. Moreover, we analyze the present method by examining some benchmark indicators of biomolecular surface, that is, surface area, surface-enclosed volume, solvation free energy, and surface electrostatic potential. A test set of 13 protein molecules is used in the present investigation. The electrostatic analysis is carried out via the Poisson-Boltzmann equation model. To further demonstrate the utility of the present PDE transform-based surface method, we solve the Poisson-Nernst-Planck equations with a PDE transform surface of a protein. Second-order convergence is observed for the electrostatic potential and concentrations. Finally, to test the capability and efficiency of the present PDE transform-based surface generation method, we apply it to the construction of an excessively large biomolecule, a

Construction of Individual Morphological Brain Networks with Multiple Morphometric Features

Directory of Open Access Journals (Sweden)

Chunlan Yang

2017-04-01

Full Text Available In recent years, researchers have increased attentions to the morphological brain network, which is generally constructed by measuring the mathematical correlation across regions using a certain morphometric feature, such as regional cortical thickness and voxel intensity. However, cerebral structure can be characterized by various factors, such as regional volume, surface area, and curvature. Moreover, most of the morphological brain networks are population-based, which has limitations in the investigations of individual difference and clinical applications. Hence, we have extended previous studies by proposing a novel method for realizing the construction of an individual-based morphological brain network through a combination of multiple morphometric features. In particular, interregional connections are estimated using our newly introduced feature vectors, namely, the Pearson correlation coefficient of the concatenation of seven morphometric features. Experiments were performed on a healthy cohort of 55 subjects (24 males aged from 20 to 29 and 31 females aged from 20 to 28 each scanned twice, and reproducibility was evaluated through test–retest reliability. The robustness of morphometric features was measured firstly to select the more reproducible features to form the connectomes. Then the topological properties were analyzed and compared with previous reports of different modalities. Small-worldness was observed in all the subjects at the range of the entire network sparsity (20–40%, and configurations were comparable with previous findings at the sparsity of 23%. The spatial distributions of the hub were found to be significantly influenced by the individual variances, and the hubs obtained by averaging across subjects and sparsities showed correspondence with previous reports. The intraclass coefficient of graphic properties (clustering coefficient = 0.83, characteristic path length = 0.81, betweenness centrality = 0.78 indicates

Spatial heterogeneity regulates plant-pollinator networks across multiple landscape scales.

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Eduardo Freitas Moreira

Full Text Available Mutualistic plant-pollinator interactions play a key role in biodiversity conservation and ecosystem functioning. In a community, the combination of these interactions can generate emergent properties, e.g., robustness and resilience to disturbances such as fluctuations in populations and extinctions. Given that these systems are hierarchical and complex, environmental changes must have multiple levels of influence. In addition, changes in habitat quality and in the landscape structure are important threats to plants, pollinators and their interactions. However, despite the importance of these phenomena for the understanding of biological systems, as well as for conservation and management strategies, few studies have empirically evaluated these effects at the network level. Therefore, the objective of this study was to investigate the influence of local conditions and landscape structure at multiple scales on the characteristics of plant-pollinator networks. This study was conducted in agri-natural lands in Chapada Diamantina, Bahia, Brazil. Pollinators were collected in 27 sampling units distributed orthogonally along a gradient of proportion of agriculture and landscape diversity. The Akaike information criterion was used to select models that best fit the metrics for network characteristics, comparing four hypotheses represented by a set of a priori candidate models with specific combinations of the proportion of agriculture, the average shape of the landscape elements, the diversity of the landscape and the structure of local vegetation. The results indicate that a reduction of habitat quality and landscape heterogeneity can cause species loss and decrease of networks nestedness. These structural changes can reduce robustness and resilience of plant-pollinator networks what compromises the reproductive success of plants, the maintenance of biodiversity and the pollination service stability. We also discuss the possible explanations for

Spatial heterogeneity regulates plant-pollinator networks across multiple landscape scales.

Science.gov (United States)

Moreira, Eduardo Freitas; Boscolo, Danilo; Viana, Blandina Felipe

2015-01-01

Mutualistic plant-pollinator interactions play a key role in biodiversity conservation and ecosystem functioning. In a community, the combination of these interactions can generate emergent properties, e.g., robustness and resilience to disturbances such as fluctuations in populations and extinctions. Given that these systems are hierarchical and complex, environmental changes must have multiple levels of influence. In addition, changes in habitat quality and in the landscape structure are important threats to plants, pollinators and their interactions. However, despite the importance of these phenomena for the understanding of biological systems, as well as for conservation and management strategies, few studies have empirically evaluated these effects at the network level. Therefore, the objective of this study was to investigate the influence of local conditions and landscape structure at multiple scales on the characteristics of plant-pollinator networks. This study was conducted in agri-natural lands in Chapada Diamantina, Bahia, Brazil. Pollinators were collected in 27 sampling units distributed orthogonally along a gradient of proportion of agriculture and landscape diversity. The Akaike information criterion was used to select models that best fit the metrics for network characteristics, comparing four hypotheses represented by a set of a priori candidate models with specific combinations of the proportion of agriculture, the average shape of the landscape elements, the diversity of the landscape and the structure of local vegetation. The results indicate that a reduction of habitat quality and landscape heterogeneity can cause species loss and decrease of networks nestedness. These structural changes can reduce robustness and resilience of plant-pollinator networks what compromises the reproductive success of plants, the maintenance of biodiversity and the pollination service stability. We also discuss the possible explanations for these relationships and

Phase sensitive spectral domain interferometry for label free biomolecular interaction analysis and biosensing applications

Science.gov (United States)

Chirvi, Sajal

-channel label-free biosensing applications is introduced. Simultaneous interrogation of multiple biosensors is achievable with a single spectral domain phase sensitive interferometer by coding the individual sensograms in coherence-multiplexed channels. Experimental results demonstrating multiplexed quantitative biomolecular interaction analysis of antibodies binding to antigen coated functionalized biosensor chip surfaces on different platforms are presented.

Pareto evolution of gene networks: an algorithm to optimize multiple fitness objectives

International Nuclear Information System (INIS)

Warmflash, Aryeh; Siggia, Eric D; Francois, Paul

2012-01-01

The computational evolution of gene networks functions like a forward genetic screen to generate, without preconceptions, all networks that can be assembled from a defined list of parts to implement a given function. Frequently networks are subject to multiple design criteria that cannot all be optimized simultaneously. To explore how these tradeoffs interact with evolution, we implement Pareto optimization in the context of gene network evolution. In response to a temporal pulse of a signal, we evolve networks whose output turns on slowly after the pulse begins, and shuts down rapidly when the pulse terminates. The best performing networks under our conditions do not fall into categories such as feed forward and negative feedback that also encode the input–output relation we used for selection. Pareto evolution can more efficiently search the space of networks than optimization based on a single ad hoc combination of the design criteria. (paper)

Pareto evolution of gene networks: an algorithm to optimize multiple fitness objectives.

Science.gov (United States)

Warmflash, Aryeh; Francois, Paul; Siggia, Eric D

2012-10-01

The computational evolution of gene networks functions like a forward genetic screen to generate, without preconceptions, all networks that can be assembled from a defined list of parts to implement a given function. Frequently networks are subject to multiple design criteria that cannot all be optimized simultaneously. To explore how these tradeoffs interact with evolution, we implement Pareto optimization in the context of gene network evolution. In response to a temporal pulse of a signal, we evolve networks whose output turns on slowly after the pulse begins, and shuts down rapidly when the pulse terminates. The best performing networks under our conditions do not fall into categories such as feed forward and negative feedback that also encode the input-output relation we used for selection. Pareto evolution can more efficiently search the space of networks than optimization based on a single ad hoc combination of the design criteria.

A new approach to implement absorbing boundary condition in biomolecular electrostatics.

Science.gov (United States)

Goni, Md Osman

2013-01-01

This paper discusses a novel approach to employ the absorbing boundary condition in conjunction with the finite-element method (FEM) in biomolecular electrostatics. The introduction of Bayliss-Turkel absorbing boundary operators in electromagnetic scattering problem has been incorporated by few researchers. However, in the area of biomolecular electrostatics, this boundary condition has not been investigated yet. The objective of this paper is twofold. First, to solve nonlinear Poisson-Boltzmann equation using Newton's method and second, to find an efficient and acceptable solution with minimum number of unknowns. In this work, a Galerkin finite-element formulation is used along with a Bayliss-Turkel absorbing boundary operator that explicitly accounts for the open field problem by mapping the Sommerfeld radiation condition from the far field to near field. While the Bayliss-Turkel condition works well when the artificial boundary is far from the scatterer, an acceptable tolerance of error can be achieved with the second order operator. Numerical results on test case with simple sphere show that the treatment is able to reach the same level of accuracy achieved by the analytical method while using a lower grid density. Bayliss-Turkel absorbing boundary condition (BTABC) combined with the FEM converges to the exact solution of scattering problems to within discretization error.

Disruption of Structural and Functional Networks in Long-Standing Multiple Sclerosis

NARCIS (Netherlands)

Tewarie, P.; Steenwijk, M.D.; Tijms, B.M.; Daams, M.; Balk, L.J.; Stam, C.J.; Uitdehaag, B.M.J.; Polman, C.H.; Geurts, J.J.G.; Barkhof, F.; Pouwels, P.J.W.; Vrenken, H.; Hillebrand, A.

2014-01-01

Both gray matter atrophy and disruption of functional networks are important predictors for physical disability and cognitive impairment in multiple sclerosis (MS), yet their relationship is poorly understood. Graph theory provides a modality invariant framework to analyze patterns of gray matter

A Multiple Mobility Support Approach (MMSA Based on PEAS for NCW in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Bong-Joo Koo

2011-01-01

Full Text Available Wireless Sensor Networks (WSNs can be implemented as one of sensor systems in Network Centric Warfare (NCW. Mobility support and energy efficiency are key concerns for this application, due to multiple mobile users and stimuli in real combat field. However, mobility support approaches that can be adopted in this circumstance are rare. This paper proposes Multiple Mobility Support Approach (MMSA based on Probing Environment and Adaptive Sleeping (PEAS to support the simultaneous mobility of both multiple users and stimuli by sharing the information of stimuli in WSNs. Simulations using Qualnet are conducted, showing that MMSA can support multiple mobile users and stimuli with good energy efficiency. It is expected that the proposed MMSA can be applied to real combat field.

High-speed AFM for Studying Dynamic Biomolecular Processes

Science.gov (United States)

Ando, Toshio

2008-03-01

Biological molecules show their vital activities only in aqueous solutions. It had been one of dreams in biological sciences to directly observe biological macromolecules (protein, DNA) at work under a physiological condition because such observation is straightforward to understanding their dynamic behaviors and functional mechanisms. Optical microscopy has no sufficient spatial resolution and electron microscopy is not applicable to in-liquid samples. Atomic force microscopy (AFM) can visualize molecules in liquids at high resolution but its imaging rate was too low to capture dynamic biological processes. This slow imaging rate is because AFM employs mechanical probes (cantilevers) and mechanical scanners to detect the sample height at each pixel. It is quite difficult to quickly move a mechanical device of macroscopic size with sub-nanometer accuracy without producing unwanted vibrations. It is also difficult to maintain the delicate contact between a probe tip and fragile samples. Two key techniques are required to realize high-speed AFM for biological research; fast feedback control to maintain a weak tip-sample interaction force and a technique to suppress mechanical vibrations of the scanner. Various efforts have been carried out in the past decade to materialize high-speed AFM. The current high-speed AFM can capture images on video at 30-60 frames/s for a scan range of 250nm and 100 scan lines, without significantly disturbing week biomolecular interaction. Our recent studies demonstrated that this new microscope can reveal biomolecular processes such as myosin V walking along actin tracks and association/dissociation dynamics of chaperonin GroEL-GroES that occurs in a negatively cooperative manner. The capacity of nanometer-scale visualization of dynamic processes in liquids will innovate on biological research. In addition, it will open a new way to study dynamic chemical/physical processes of various phenomena that occur at the liquid-solid interfaces.

Tailoring the Variational Implicit Solvent Method for New Challenges: Biomolecular Recognition and Assembly

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Clarisse Gravina Ricci

2018-02-01

Full Text Available Predicting solvation free energies and describing the complex water behavior that plays an important role in essentially all biological processes is a major challenge from the computational standpoint. While an atomistic, explicit description of the solvent can turn out to be too expensive in large biomolecular systems, most implicit solvent methods fail to capture “dewetting” effects and heterogeneous hydration by relying on a pre-established (i.e., guessed solvation interface. Here we focus on the Variational Implicit Solvent Method, an implicit solvent method that adds water “plasticity” back to the picture by formulating the solvation free energy as a functional of all possible solvation interfaces. We survey VISM's applications to the problem of molecular recognition and report some of the most recent efforts to tailor VISM for more challenging scenarios, with the ultimate goal of including thermal fluctuations into the framework. The advances reported herein pave the way to make VISM a uniquely successful approach to characterize complex solvation properties in the recognition and binding of large-scale biomolecular complexes.

Tailoring the Variational Implicit Solvent Method for New Challenges: Biomolecular Recognition and Assembly

Science.gov (United States)

Ricci, Clarisse Gravina; Li, Bo; Cheng, Li-Tien; Dzubiella, Joachim; McCammon, J. Andrew

2018-01-01

Predicting solvation free energies and describing the complex water behavior that plays an important role in essentially all biological processes is a major challenge from the computational standpoint. While an atomistic, explicit description of the solvent can turn out to be too expensive in large biomolecular systems, most implicit solvent methods fail to capture “dewetting” effects and heterogeneous hydration by relying on a pre-established (i.e., guessed) solvation interface. Here we focus on the Variational Implicit Solvent Method, an implicit solvent method that adds water “plasticity” back to the picture by formulating the solvation free energy as a functional of all possible solvation interfaces. We survey VISM's applications to the problem of molecular recognition and report some of the most recent efforts to tailor VISM for more challenging scenarios, with the ultimate goal of including thermal fluctuations into the framework. The advances reported herein pave the way to make VISM a uniquely successful approach to characterize complex solvation properties in the recognition and binding of large-scale biomolecular complexes. PMID:29484300

Heirloom biodynamic seeds network rescue, conservation and multiplication of local seeds in Brazil

OpenAIRE

Jovchelevich, Pedro

2014-01-01

Structuring a network organic and biodynamic seed involving farmers in the central- southern Brazil. Training, participatory breeding, edition of publications, fairs of exchange seeds, a processing unit and assessment of seed quality, commercial seed multiplication with emphasis on vegetables. This network has garanteed the autonomy of farmers in seed production and enriched agrobiodiversity through exchanges of seed.

Channel capacity of TDD-OFDM-MIMO for multiple access points in a wireless single-frequency-network

DEFF Research Database (Denmark)

Takatori, Y.; Fitzek, Frank; Tsunekawa, K.

2005-01-01

MIMO data transmission scheme, which combines Single-Frequency-Network (SFN) with TDD-OFDM-MIMO applied for wireless LAN networks. In our proposal, we advocate to use SFN for multiple access points (MAP) MIMO data transmission. The goal of this approach is to achieve very high channel capacity in both......The multiple-input-multiple-output (MIMO) technique is the most attractive candidate to improve the spectrum efficiency in the next generation wireless communication systems. However, the efficiency of MIMO techniques reduces in the line of sight (LOS) environments. In this paper, we propose a new...

Multiple access protocol for supporting multimedia services in wireless ATM networks

DEFF Research Database (Denmark)

Liu, Hong; Dittmann, Lars; Gliese, Ulrik Bo

1999-01-01

The furture broadband wireless asynchronous transfer mode (ATM) networks must provide seamless extension of multimedia services from the wireline ATM networks. This requires an effecient wireless access protocol to fulfill varying Quality-og-Service (QoS) requirements for multimedia applications....... In this paper, we propose a multiple access protocol using centralized and distributed channel access control techniques to provide QoS guarantees for multimedia services by taking advantage of the characteristics of different kinds of ATM traffics. Multimedia traffic, including constant bit rate (CBR...

Multi-Destination Cognitive Radio Relay Network with SWIPT and Multiple Primary Receivers

KAUST Repository

Al-Habob, Ahmed A.; Salhab, Anas M.; Zummo, Salam A.; Alouini, Mohamed-Slim

2017-01-01

In this paper, we study the performance of simultaneous wireless information and power transfer (SWIPT) technique in a multi-destination dual-hop underlay cognitive relay network with multiple primary receivers. Information transmission from

Interacting with the biomolecular solvent accessible surface via a haptic feedback device

Directory of Open Access Journals (Sweden)

Hayward Steven

2009-10-01

Full Text Available Abstract Background From the 1950s computer based renderings of molecules have been produced to aid researchers in their understanding of biomolecular structure and function. A major consideration for any molecular graphics software is the ability to visualise the three dimensional structure of the molecule. Traditionally, this was accomplished via stereoscopic pairs of images and later realised with three dimensional display technologies. Using a haptic feedback device in combination with molecular graphics has the potential to enhance three dimensional visualisation. Although haptic feedback devices have been used to feel the interaction forces during molecular docking they have not been used explicitly as an aid to visualisation. Results A haptic rendering application for biomolecular visualisation has been developed that allows the user to gain three-dimensional awareness of the shape of a biomolecule. By using a water molecule as the probe, modelled as an oxygen atom having hard-sphere interactions with the biomolecule, the process of exploration has the further benefit of being able to determine regions on the molecular surface that are accessible to the solvent. This gives insight into how awkward it is for a water molecule to gain access to or escape from channels and cavities, indicating possible entropic bottlenecks. In the case of liver alcohol dehydrogenase bound to the inhibitor SAD, it was found that there is a channel just wide enough for a single water molecule to pass through. Placing the probe coincident with crystallographic water molecules suggests that they are sometimes located within small pockets that provide a sterically stable environment irrespective of hydrogen bonding considerations. Conclusion By using the software, named HaptiMol ISAS (available from http://www.haptimol.co.uk, one can explore the accessible surface of biomolecules using a three-dimensional input device to gain insights into the shape and water

Lifetime Optimization of a Multiple Sink Wireless Sensor Network through Energy Balancing

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Tapan Kumar Jain

2015-01-01

Full Text Available The wireless sensor network consists of small limited energy sensors which are connected to one or more sinks. The maximum energy consumption takes place in communicating the data from the nodes to the sink. Multiple sink WSN has an edge over the single sink WSN where very less energy is utilized in sending the data to the sink, as the number of hops is reduced. If the energy consumed by a node is balanced between the other nodes, the lifetime of the network is considerably increased. The network lifetime optimization is achieved by restructuring the network by modifying the neighbor nodes of a sink. Only those nodes are connected to a sink which makes the total energy of the sink less than the threshold. This energy balancing through network restructuring optimizes the network lifetime. This paper depicts this fact through simulations done in MATLAB.

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

Science.gov (United States)

Rai, Man Mohan

2006-01-01

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more

Engineering intracellular active transport systems as in vivo biomolecular tools.

Energy Technology Data Exchange (ETDEWEB)

Bachand, George David; Carroll-Portillo, Amanda

2006-11-01

Active transport systems provide essential functions in terms of cell physiology and metastasis. These systems, however, are also co-opted by invading viruses, enabling directed transport of the virus to and from the cell's nucleus (i.e., the site of virus replication). Based on this concept, fundamentally new approaches for interrogating and manipulating the inner workings of living cells may be achievable by co-opting Nature's active transport systems as an in vivo biomolecular tool. The overall goal of this project was to investigate the ability to engineer kinesin-based transport systems for in vivo applications, specifically the collection of effector proteins (e.g., transcriptional regulators) within single cells. In the first part of this project, a chimeric fusion protein consisting of kinesin and a single chain variable fragment (scFv) of an antibody was successfully produced through a recombinant expression system. The kinesin-scFv retained both catalytic and antigenic functionality, enabling selective capture and transport of target antigens. The incorporation of a rabbit IgG-specific scFv into the kinesin established a generalized system for functionalizing kinesin with a wide range of target-selective antibodies raised in rabbits. The second objective was to develop methods of isolating the intact microtubule network from live cells as a platform for evaluating kinesin-based transport within the cytoskeletal architecture of a cell. Successful isolation of intact microtubule networks from two distinct cell types was demonstrated using glutaraldehyde and methanol fixation methods. This work provides a platform for inferring the ability of kinesin-scFv to function in vivo, and may also serve as a three-dimensional scaffold for evaluating and exploiting kinesin-based transport for nanotechnological applications. Overall, the technology developed in this project represents a first-step in engineering active transport system for in vivo

Knowledge-Based Multiple Access Protocol in Broadband Wireless ATM Networks

DEFF Research Database (Denmark)

Liu, Hong; Gliese, Ulrik Bo; Dittmann, Lars

1999-01-01

In this paper, we propose a knowledge-based multiple access protocol for the extension of wireline ATM to wireless networks. The objective is to enable effecient transmission of all kinds of ATM traffic in the wireless channel with guaranteed QoS.The proposed protocol utilixes knowledge of the main...... guaranteed QoS requirements to a variety of ATM applications....

A new strategy for imaging biomolecular events through interactions between liquid crystals and oil-in-water emulsions.

Science.gov (United States)

Hu, Qiong-Zheng; Jang, Chang-Hyun

2012-11-21

In this study, we demonstrate a new strategy to image biomolecular events through interactions between liquid crystals (LCs) and oil-in-water emulsions. The optical response had a dark appearance when a nematic LC, 4-cyano-4'-pentylbiphenyl (5CB), is in contact with emulsion droplets of glyceryl trioleate (GT). In contrast, the optical response had a bright appearance when 5CB is in contact with GT emulsions decorated with surfactants such as sodium oleate. Since lipase can hydrolyze GT and produce oleic acid, the optical response also displays a bright appearance after 5CB has been in contact with a mixture of lipase and GT emulsions. These results indicate the feasibility of monitoring biomolecular events through interactions between LCs and oil-in-water emulsions.

The universal statistical distributions of the affinity, equilibrium constants, kinetics and specificity in biomolecular recognition.

Directory of Open Access Journals (Sweden)

Xiliang Zheng

2015-04-01

Full Text Available We uncovered the universal statistical laws for the biomolecular recognition/binding process. We quantified the statistical energy landscapes for binding, from which we can characterize the distributions of the binding free energy (affinity, the equilibrium constants, the kinetics and the specificity by exploring the different ligands binding with a particular receptor. The results of the analytical studies are confirmed by the microscopic flexible docking simulations. The distribution of binding affinity is Gaussian around the mean and becomes exponential near the tail. The equilibrium constants of the binding follow a log-normal distribution around the mean and a power law distribution in the tail. The intrinsic specificity for biomolecular recognition measures the degree of discrimination of native versus non-native binding and the optimization of which becomes the maximization of the ratio of the free energy gap between the native state and the average of non-native states versus the roughness measured by the variance of the free energy landscape around its mean. The intrinsic specificity obeys a Gaussian distribution near the mean and an exponential distribution near the tail. Furthermore, the kinetics of binding follows a log-normal distribution near the mean and a power law distribution at the tail. Our study provides new insights into the statistical nature of thermodynamics, kinetics and function from different ligands binding with a specific receptor or equivalently specific ligand binding with different receptors. The elucidation of distributions of the kinetics and free energy has guiding roles in studying biomolecular recognition and function through small-molecule evolution and chemical genetics.

Computational methods to study the structure and dynamics of biomolecules and biomolecular processes from bioinformatics to molecular quantum mechanics

CERN Document Server

2014-01-01

Since the second half of the 20th century machine computations have played a critical role in science and engineering. Computer-based techniques have become especially important in molecular biology, since they often represent the only viable way to gain insights into the behavior of a biological system as a whole. The complexity of biological systems, which usually needs to be analyzed on different time- and size-scales and with different levels of accuracy, requires the application of different approaches, ranging from comparative analysis of sequences and structural databases, to the analysis of networks of interdependence between cell components and processes, through coarse-grained modeling to atomically detailed simulations, and finally to molecular quantum mechanics. This book provides a comprehensive overview of modern computer-based techniques for computing the structure, properties and dynamics of biomolecules and biomolecular processes. The twenty-two chapters, written by scientists from all over t...

Micro- and nanodevices integrated with biomolecular probes.

Science.gov (United States)

Alapan, Yunus; Icoz, Kutay; Gurkan, Umut A

2015-12-01

Understanding how biomolecules, proteins and cells interact with their surroundings and other biological entities has become the fundamental design criterion for most biomedical micro- and nanodevices. Advances in biology, medicine, and nanofabrication technologies complement each other and allow us to engineer new tools based on biomolecules utilized as probes. Engineered micro/nanosystems and biomolecules in nature have remarkably robust compatibility in terms of function, size, and physical properties. This article presents the state of the art in micro- and nanoscale devices designed and fabricated with biomolecular probes as their vital constituents. General design and fabrication concepts are presented and three major platform technologies are highlighted: microcantilevers, micro/nanopillars, and microfluidics. Overview of each technology, typical fabrication details, and application areas are presented by emphasizing significant achievements, current challenges, and future opportunities. Copyright © 2015 Elsevier Inc. All rights reserved.

Smart Control of Multiple Evaporator Systems with Wireless Sensor and Actuator Networks

Directory of Open Access Journals (Sweden)

Apolinar González-Potes

2016-02-01

Full Text Available This paper describes the complete integration of a fuzzy control of multiple evaporator systems with the IEEE 802.15.4 standard, in which we study several important aspects for this kind of system, like a detailed analysis of the end-to-end real-time flows over wireless sensor and actuator networks (WSAN, a real-time kernel with an earliest deadline first (EDF scheduler, periodic and aperiodic tasking models for the nodes, lightweight and flexible compensation-based control algorithms for WSAN that exhibit packet dropouts, an event-triggered sampling scheme and design methodologies. We address the control problem of the multi-evaporators with the presence of uncertainties, which was tackled through a wireless fuzzy control approach, showing the advantages of this concept where it can easily perform the optimization for a set of multiple evaporators controlled by the same smart controller, which should have an intelligent and flexible architecture based on multi-agent systems (MAS that allows one to add or remove new evaporators online, without the need for reconfiguring, while maintaining temporal and functional restrictions in the system. We show clearly how we can get a greater scalability, the self-configuration of the network and the least overhead with a non-beacon or unslotted mode of the IEEE 802.15.4 protocol, as well as wireless communications and distributed architectures, which could be extremely helpful in the development process of networked control systems in large spatially-distributed plants, which involve many sensors and actuators. For this purpose, a fuzzy scheme is used to control a set of parallel evaporator air-conditioning systems, with temperature and relative humidity control as a multi-input and multi-output closed loop system; in addition, a general architecture is presented, which implements multiple control loops closed over a communication network, integrating the analysis and validation method for multi

The heat-shock protein/chaperone network and multiple stress resistance.

Science.gov (United States)

Jacob, Pierre; Hirt, Heribert; Bendahmane, Abdelhafid

2017-04-01

Crop yield has been greatly enhanced during the last century. However, most elite cultivars are adapted to temperate climates and are not well suited to more stressful conditions. In the context of climate change, stress resistance is a major concern. To overcome these difficulties, scientists may help breeders by providing genetic markers associated with stress resistance. However, multistress resistance cannot be obtained from the simple addition of single stress resistance traits. In the field, stresses are unpredictable and several may occur at once. Consequently, the use of single stress resistance traits is often inadequate. Although it has been historically linked with the heat stress response, the heat-shock protein (HSP)/chaperone network is a major component of multiple stress responses. Among the HSP/chaperone 'client proteins', many are primary metabolism enzymes and signal transduction components with essential roles for the proper functioning of a cell. HSPs/chaperones are controlled by the action of diverse heat-shock factors, which are recruited under stress conditions. In this review, we give an overview of the regulation of the HSP/chaperone network with a focus on Arabidopsis thaliana. We illustrate the role of HSPs/chaperones in regulating diverse signalling pathways and discuss several basic principles that should be considered for engineering multiple stress resistance in crops through the HSP/chaperone network. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Implementing multiple intervention strategies in Dutch public health-related policy networks.

Science.gov (United States)

Harting, Janneke; Peters, Dorothee; Grêaux, Kimberly; van Assema, Patricia; Verweij, Stefan; Stronks, Karien; Klijn, Erik-Hans

2017-10-13

Improving public health requires multiple intervention strategies. Implementing such an intervention mix is supposed to require a multisectoral policy network. As evidence to support this assumption is scarce, we examined under which conditions public health-related policy networks were able to implement an intervention mix. Data were collected (2009-14) from 29 Dutch public health policy networks. Surveys were used to identify the number of policy sectors, participation of actors, level of trust, networking by the project leader, and intervention strategies implemented. Conditions sufficient for an intervention mix (≥3 of 4 non-educational strategies present) were determined in a fuzzy-set qualitative comparative analysis. A multisectoral policy network (≥7 of 14 sectors present) was neither a necessary nor a sufficient condition. In multisectoral networks, additionally required was either the active participation of network actors (≥50% actively involved) or active networking by the project leader (≥monthly contacts with network actors). In policy networks that included few sectors, a high level of trust (positive perceptions of each other's intentions) was needed-in the absence though of any of the other conditions. If the network actors were also actively involved, an extra requirement was active networking by the project leader. We conclude that the multisectoral composition of policy networks can contribute to the implementation of a variety of intervention strategies, but not without additional efforts. However, policy networks that include only few sectors are also able to implement an intervention mix. Here, trust seems to be the most important condition. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Proceedings of the international advisory committee on 'biomolecular dynamics instrument DNA' and the workshop on 'biomolecular dynamics backscattering spectrometers'

International Nuclear Information System (INIS)

Arai, Masatoshi; Aizawa, Kazuya; Nakajima, Kenji; Shibata, Kaoru; Takahashi, Nobuaki

2008-08-01

A workshop entitled 'Biomolecular Dynamics Backscattering Spectrometers' was held on February 27th - 29th, 2008 at J-PARC Center, Japan Atomic Energy Agency. This workshop was planned to be held for aiming to realize an innovative neutron backscattering instrument, namely DNA, in the MLF and thus four leading scientists in the field of neutron backscattering instruments were invited as the International Advisory Committee (IAC member: Dr. Dan Neumann (Chair); Prof. Ferenc Mezei; Dr. Hannu Mutka; Dr. Philip Tregenna-Piggott) for DNA from institutes in the United States, France and Switzerland, where backscattering instruments are in-service. It was therefore held in the form of lecture anterior and then in the form of the committee posterior. This report includes the executive summary of the IAC and materials of the presentations in the IAC and the workshop. (author)

Raman spectroscopy detects biomolecular changes associated with nanoencapsulated hesperetin treatment in experimental oral carcinogenesis

International Nuclear Information System (INIS)

Gurushankar, K; Gohulkumar, M; Krishnakumar, N; Kumar, Piyush; Murali Krishna, C

2016-01-01

Recently it has been shown that Raman spectroscopy possesses great potential in the investigation of biomolecular changes of tumor tissues with therapeutic drug response in a non-invasive and label-free manner. The present study is designed to investigate the antitumor effect of hespertin-loaded nanoparticles (HETNPs) relative to the efficacy of native hesperetin (HET) in modifying the biomolecular changes during 7,12-dimethyl benz(a)anthracene (DMBA)-induced oral carcinogenesis using a Raman spectroscopic technique. Significant differences in the intensity and shape of the Raman spectra between the control and the experimental tissues at 1800–500 cm −1 were observed. Tumor tissues are characterized by an increase in the relative amount of proteins, nucleic acids, tryptophan and phenylalanine and a decrease in the percentage of lipids when compared to the control tissues. Further, oral administration of HET and its nanoparticulates restored the status of the lipids and significantly decreased the levels of protein and nucleic acid content. Treatment with HETNPs showed a more potent antitumor effect than treatment with native HET, which resulted in an overall reduction in the intensity of several biochemical Raman bands in DMBA-induced oral carcinogenesis being observed. Principal component and linear discriminant analysis (PC–LDA), together with leave-one-out cross validation (LOOCV) on Raman spectra yielded diagnostic sensitivities of 100%, 80%, 91.6% and 65% and specificities of 100%, 65%, 60% and 55% for classification of control versus DMBA, DMBA versus DMBA  +  HET, DMBA versus DMBA  +  HETNPs and DMBA  +  HET versus DMBA  +  HETNPs treated tissue groups, respectively. These results further demonstrate that Raman spectroscopy associated with multivariate statistical algorithms could be a valuable tool for developing a comprehensive understanding of the process of biomolecular changes, and could reveal the signatures of the

An energy efficient distance-aware routing algorithm with multiple mobile sinks for wireless sensor networks.

Science.gov (United States)

Wang, Jin; Li, Bin; Xia, Feng; Kim, Chang-Seob; Kim, Jeong-Uk

2014-08-18

Traffic patterns in wireless sensor networks (WSNs) usually follow a many-to-one model. Sensor nodes close to static sinks will deplete their limited energy more rapidly than other sensors, since they will have more data to forward during multihop transmission. This will cause network partition, isolated nodes and much shortened network lifetime. Thus, how to balance energy consumption for sensor nodes is an important research issue. In recent years, exploiting sink mobility technology in WSNs has attracted much research attention because it can not only improve energy efficiency, but prolong network lifetime. In this paper, we propose an energy efficient distance-aware routing algorithm with multiple mobile sink for WSNs, where sink nodes will move with a certain speed along the network boundary to collect monitored data. We study the influence of multiple mobile sink nodes on energy consumption and network lifetime, and we mainly focus on the selection of mobile sink node number and the selection of parking positions, as well as their impact on performance metrics above. We can see that both mobile sink node number and the selection of parking position have important influence on network performance. Simulation results show that our proposed routing algorithm has better performance than traditional routing ones in terms of energy consumption.

An Energy Efficient Distance-Aware Routing Algorithm with Multiple Mobile Sinks for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jin Wang

2014-08-01

Full Text Available Traffic patterns in wireless sensor networks (WSNs usually follow a many-to-one model. Sensor nodes close to static sinks will deplete their limited energy more rapidly than other sensors, since they will have more data to forward during multihop transmission. This will cause network partition, isolated nodes and much shortened network lifetime. Thus, how to balance energy consumption for sensor nodes is an important research issue. In recent years, exploiting sink mobility technology in WSNs has attracted much research attention because it can not only improve energy efficiency, but prolong network lifetime. In this paper, we propose an energy efficient distance-aware routing algorithm with multiple mobile sink for WSNs, where sink nodes will move with a certain speed along the network boundary to collect monitored data. We study the influence of multiple mobile sink nodes on energy consumption and network lifetime, and we mainly focus on the selection of mobile sink node number and the selection of parking positions, as well as their impact on performance metrics above. We can see that both mobile sink node number and the selection of parking position have important influence on network performance. Simulation results show that our proposed routing algorithm has better performance than traditional routing ones in terms of energy consumption.

Implementation of Multiple Host Nodes in Wireless Sensing Node Network System for Landslide Monitoring

International Nuclear Information System (INIS)

Bin Abas, Faizulsalihin; Takayama, Shigeru

2015-01-01

This paper proposes multiple host nodes in Wireless Sensing Node Network System (WSNNS) for landslide monitoring. As landslide disasters damage monitoring system easily, one major demand in landslide monitoring is the flexibility and robustness of the system to evaluate the current situation in the monitored area. For various reasons WSNNS can provide an important contribution to reach that aim. In this system, acceleration sensors and GPS are deployed in sensing nodes. Location information by GPS, enable the system to estimate network topology and enable the system to perceive the location in emergency by monitoring the node mode. Acceleration sensors deployment, capacitate this system to detect slow mass movement that can lead to landslide occurrence. Once deployed, sensing nodes self-organize into an autonomous wireless ad hoc network. The measurement parameter data from sensing nodes is transmitted to Host System via host node and ''Cloud'' System. The implementation of multiple host nodes in Local Sensing Node Network System (LSNNS), improve risk- management of the WSNNS for real-time monitoring of landslide disaster

Implementation of Multiple Host Nodes in Wireless Sensing Node Network System for Landslide Monitoring

Science.gov (United States)

Abas, Faizulsalihin bin; Takayama, Shigeru

2015-02-01

This paper proposes multiple host nodes in Wireless Sensing Node Network System (WSNNS) for landslide monitoring. As landslide disasters damage monitoring system easily, one major demand in landslide monitoring is the flexibility and robustness of the system to evaluate the current situation in the monitored area. For various reasons WSNNS can provide an important contribution to reach that aim. In this system, acceleration sensors and GPS are deployed in sensing nodes. Location information by GPS, enable the system to estimate network topology and enable the system to perceive the location in emergency by monitoring the node mode. Acceleration sensors deployment, capacitate this system to detect slow mass movement that can lead to landslide occurrence. Once deployed, sensing nodes self-organize into an autonomous wireless ad hoc network. The measurement parameter data from sensing nodes is transmitted to Host System via host node and "Cloud" System. The implementation of multiple host nodes in Local Sensing Node Network System (LSNNS), improve risk- management of the WSNNS for real-time monitoring of landslide disaster.

The HADDOCK2.2 Web Server: User-Friendly Integrative Modeling of Biomolecular Complexes.

Science.gov (United States)

van Zundert, G C P; Rodrigues, J P G L M; Trellet, M; Schmitz, C; Kastritis, P L; Karaca, E; Melquiond, A S J; van Dijk, M; de Vries, S J; Bonvin, A M J J

2016-02-22

The prediction of the quaternary structure of biomolecular macromolecules is of paramount importance for fundamental understanding of cellular processes and drug design. In the era of integrative structural biology, one way of increasing the accuracy of modeling methods used to predict the structure of biomolecular complexes is to include as much experimental or predictive information as possible in the process. This has been at the core of our information-driven docking approach HADDOCK. We present here the updated version 2.2 of the HADDOCK portal, which offers new features such as support for mixed molecule types, additional experimental restraints and improved protocols, all of this in a user-friendly interface. With well over 6000 registered users and 108,000 jobs served, an increasing fraction of which on grid resources, we hope that this timely upgrade will help the community to solve important biological questions and further advance the field. The HADDOCK2.2 Web server is freely accessible to non-profit users at http://haddock.science.uu.nl/services/HADDOCK2.2. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Multiple synchronization transitions in scale-free neuronal networks with electrical and chemical hybrid synapses

International Nuclear Information System (INIS)

Liu, Chen; Wang, Jiang; Wang, Lin; Yu, Haitao; Deng, Bin; Wei, Xile; Tsang, Kaiming; Chan, Wailok

2014-01-01

Highlights: • Synchronization transitions in hybrid scale-free neuronal networks are investigated. • Multiple synchronization transitions can be induced by the time delay. • Effect of synchronization transitions depends on the ratio of the electrical and chemical synapses. • Coupling strength and the density of inter-neuronal links can enhance the synchronization. -- Abstract: The impacts of information transmission delay on the synchronization transitions in scale-free neuronal networks with electrical and chemical hybrid synapses are investigated. Numerical results show that multiple appearances of synchronization regions transitions can be induced by different information transmission delays. With the time delay increasing, the synchronization of neuronal activities can be enhanced or destroyed, irrespective of the probability of chemical synapses in the whole hybrid neuronal network. In particular, for larger probability of electrical synapses, the regions of synchronous activities appear broader with stronger synchronization ability of electrical synapses compared with chemical ones. Moreover, it can be found that increasing the coupling strength can promote synchronization monotonously, playing the similar role of the increasing the probability of the electrical synapses. Interestingly, the structures and parameters of the scale-free neuronal networks, especially the structural evolvement plays a more subtle role in the synchronization transitions. In the network formation process, it is found that every new vertex is attached to the more old vertices already present in the network, the more synchronous activities will be emerge

Biomolecular Markers in Cancer of the Tongue

Directory of Open Access Journals (Sweden)

Daris Ferrari

2009-01-01

Full Text Available The incidence of tongue cancer is increasing worldwide, and its aggressiveness remains high regardless of treatment. Genetic changes and the expression of abnormal proteins have been frequently reported in the case of head and neck cancers, but the little information that has been published concerning tongue tumours is often contradictory. This review will concentrate on the immunohistochemical expression of biomolecular markers and their relationships with clinical behaviour and prognosis. Most of these proteins are associated with nodal stage, tumour progression and metastases, but there is still controversy concerning their impact on disease-free and overall survival, and treatment response. More extensive clinical studies are needed to identify the patterns of molecular alterations and the most reliable predictors in order to develop tailored anti-tumour strategies based on the targeting of hypoxia markers, vascular and lymphangiogenic factors, epidermal growth factor receptors, intracytoplasmatic signalling and apoptosis.

Towards sensitive, high-throughput, biomolecular assays based on fluorescence lifetime

Science.gov (United States)

Ioanna Skilitsi, Anastasia; Turko, Timothé; Cianfarani, Damien; Barre, Sophie; Uhring, Wilfried; Hassiepen, Ulrich; Léonard, Jérémie

2017-09-01

Time-resolved fluorescence detection for robust sensing of biomolecular interactions is developed by implementing time-correlated single photon counting in high-throughput conditions. Droplet microfluidics is used as a promising platform for the very fast handling of low-volume samples. We illustrate the potential of this very sensitive and cost-effective technology in the context of an enzymatic activity assay based on fluorescently-labeled biomolecules. Fluorescence lifetime detection by time-correlated single photon counting is shown to enable reliable discrimination between positive and negative control samples at a throughput as high as several hundred samples per second.

Small-angle X-ray scattering investigations of biomolecular confinement, loading, and release from liquid-crystalline nanochannel assemblies

Czech Academy of Sciences Publication Activity Database

Angelova, A.; Angelov, Borislav; Garamus, V. M.; Couvreur, P.; Lesieur, S.

2012-01-01

Roč. 3, č. 3 (2012), s. 445-457 ISSN 1948-7185 Institutional research plan: CEZ:AV0Z40500505 Keywords : nanochannels * biomolecular nanostructures * SAXS Subject RIV: CD - Macromolecular Chemistry Impact factor: 6.585, year: 2012

Enforcement of Privacy Policies over Multiple Online Social Networks for Collaborative Activities

Science.gov (United States)

Wu, Zhengping; Wang, Lifeng

Our goal is to tend to develop an enforcement architecture of privacy policies over multiple online social networks. It is used to solve the problem of privacy protection when several social networks build permanent or temporary collaboration. Theoretically, this idea is practical, especially due to more and more social network tend to support open source framework “OpenSocial”. But as we known different social network websites may have the same privacy policy settings based on different enforcement mechanisms, this would cause problems. In this case, we have to manually write code for both sides to make the privacy policy settings enforceable. We can imagine that, this is a huge workload based on the huge number of current social networks. So we focus on proposing a middleware which is used to automatically generate privacy protection component for permanent integration or temporary interaction of social networks. This middleware provide functions, such as collecting of privacy policy of each participant in the new collaboration, generating a standard policy model for each participant and mapping all those standard policy to different enforcement mechanisms of those participants.

Integration of biomolecular logic gates with field-effect transducers

Energy Technology Data Exchange (ETDEWEB)

Poghossian, A., E-mail: a.poghossian@fz-juelich.de [Institute of Nano- and Biotechnologies, Aachen University of Applied Sciences, Campus Juelich, Heinrich-Mussmann-Str. 1, D-52428 Juelich (Germany); Institute of Bio- and Nanosystems, Research Centre Juelich GmbH, D-52425 Juelich (Germany); Malzahn, K. [Institute of Nano- and Biotechnologies, Aachen University of Applied Sciences, Campus Juelich, Heinrich-Mussmann-Str. 1, D-52428 Juelich (Germany); Abouzar, M.H. [Institute of Nano- and Biotechnologies, Aachen University of Applied Sciences, Campus Juelich, Heinrich-Mussmann-Str. 1, D-52428 Juelich (Germany); Institute of Bio- and Nanosystems, Research Centre Juelich GmbH, D-52425 Juelich (Germany); Mehndiratta, P. [Institute of Nano- and Biotechnologies, Aachen University of Applied Sciences, Campus Juelich, Heinrich-Mussmann-Str. 1, D-52428 Juelich (Germany); Katz, E. [Department of Chemistry and Biomolecular Science, NanoBio Laboratory (NABLAB), Clarkson University, Potsdam, NY 13699-5810 (United States); Schoening, M.J. [Institute of Nano- and Biotechnologies, Aachen University of Applied Sciences, Campus Juelich, Heinrich-Mussmann-Str. 1, D-52428 Juelich (Germany); Institute of Bio- and Nanosystems, Research Centre Juelich GmbH, D-52425 Juelich (Germany)

2011-11-01

Highlights: > Enzyme-based AND/OR logic gates are integrated with a capacitive field-effect sensor. > The AND/OR logic gates compose of multi-enzyme system immobilised on sensor surface. > Logic gates were activated by different combinations of chemical inputs (analytes). > The logic output (pH change) produced by the enzymes was read out by the sensor. - Abstract: The integration of biomolecular logic gates with field-effect devices - the basic element of conventional electronic logic gates and computing - is one of the most attractive and promising approaches for the transformation of biomolecular logic principles into macroscopically useable electrical output signals. In this work, capacitive field-effect EIS (electrolyte-insulator-semiconductor) sensors based on a p-Si-SiO{sub 2}-Ta{sub 2}O{sub 5} structure modified with a multi-enzyme membrane have been used for electronic transduction of biochemical signals processed by enzyme-based OR and AND logic gates. The realised OR logic gate composes of two enzymes (glucose oxidase and esterase) and was activated by ethyl butyrate or/and glucose. The AND logic gate composes of three enzymes (invertase, mutarotase and glucose oxidase) and was activated by two chemical input signals: sucrose and dissolved oxygen. The developed integrated enzyme logic gates produce local pH changes at the EIS sensor surface as a result of biochemical reactions activated by different combinations of chemical input signals, while the pH value of the bulk solution remains unchanged. The pH-induced charge changes at the gate-insulator (Ta{sub 2}O{sub 5}) surface of the EIS transducer result in an electronic signal corresponding to the logic output produced by the immobilised enzymes. The logic output signals have been read out by means of a constant-capacitance method.

Integration of biomolecular logic gates with field-effect transducers

International Nuclear Information System (INIS)

Poghossian, A.; Malzahn, K.; Abouzar, M.H.; Mehndiratta, P.; Katz, E.; Schoening, M.J.

2011-01-01

Highlights: → Enzyme-based AND/OR logic gates are integrated with a capacitive field-effect sensor. → The AND/OR logic gates compose of multi-enzyme system immobilised on sensor surface. → Logic gates were activated by different combinations of chemical inputs (analytes). → The logic output (pH change) produced by the enzymes was read out by the sensor. - Abstract: The integration of biomolecular logic gates with field-effect devices - the basic element of conventional electronic logic gates and computing - is one of the most attractive and promising approaches for the transformation of biomolecular logic principles into macroscopically useable electrical output signals. In this work, capacitive field-effect EIS (electrolyte-insulator-semiconductor) sensors based on a p-Si-SiO 2 -Ta 2 O 5 structure modified with a multi-enzyme membrane have been used for electronic transduction of biochemical signals processed by enzyme-based OR and AND logic gates. The realised OR logic gate composes of two enzymes (glucose oxidase and esterase) and was activated by ethyl butyrate or/and glucose. The AND logic gate composes of three enzymes (invertase, mutarotase and glucose oxidase) and was activated by two chemical input signals: sucrose and dissolved oxygen. The developed integrated enzyme logic gates produce local pH changes at the EIS sensor surface as a result of biochemical reactions activated by different combinations of chemical input signals, while the pH value of the bulk solution remains unchanged. The pH-induced charge changes at the gate-insulator (Ta 2 O 5 ) surface of the EIS transducer result in an electronic signal corresponding to the logic output produced by the immobilised enzymes. The logic output signals have been read out by means of a constant-capacitance method.

Traffic Management by Using Admission Control Methods in Multiple Node IMS Network

Directory of Open Access Journals (Sweden)

Filip Chamraz

2016-01-01

Full Text Available The paper deals with Admission Control methods (AC as a possible solution for traffic management in IMS networks (IP Multimedia Subsystem - from the point of view of an efficient redistribution of the available network resources and keeping the parameters of Quality of Service (QoS. The paper specifically aims at the selection of the most appropriate method for the specific type of traffic and traffic management concept using AC methods on multiple nodes. The potential benefit and disadvantage of the used solution is evaluated.

Multiple-failure signal validation in nuclear power plants using artificial neural networks

International Nuclear Information System (INIS)

Fantoni, P.F.; Mazzola, A.

1996-01-01

The possibility of using a neural network to validate process signals during normal and abnormal plant conditions is explored. In boiling water reactor plants, signal validation is used to generate reliable thermal limits calculation and to supply reliable inputs to other computerized systems that support the operator during accident scenarios. The way that autoassociative neural networks can promptly detect faulty process signal measurements and produce a best estimate of the actual process values even in multifailure situations is shown. A method was developed to train the network for multiple sensor-failure detection, based on a random failure simulation algorithm. Noise was artificially added to the input to evaluate the network's ability to respond in a very low signal-to-noise ratio environment. Training and test data sets were simulated by the real-time transient simulator code APROS

Optimal assignment of multiple utilities in heat exchange networks

International Nuclear Information System (INIS)

Salama, A.I.A.

2009-01-01

Existing numerical geometry-based techniques, developed by [A.I.A. Salama, Numerical techniques for determining heat energy targets in pinch analysis, Computers and Chemical Engineering 29 (2005) 1861-1866; A.I.A. Salama, Determination of the optimal heat energy targets in heat pinch analysis using a geometry-based approach, Computers and Chemical Engineering 30 (2006) 758-764], have been extended to optimally assign multiple utilities in heat exchange network (HEN). These techniques utilize the horizontal shift between the cold composite curve (CC) and the stationary hot CC to determine the HEN optimal energy targets, grand composite curve (GCC), and the complement grand composite curve (CGCC). The proposed numerical technique developed in this paper is direct and simultaneously determines the optimal heat-energy targets and optimally assigns multiple utilities as compared with an existing technique based on sequential assignment of multiple utilities. The technique starts by arranging in an ascending order the HEN stream and target temperatures, and the resulting set is labelled T. Furthermore, the temperature sets where multiple utilities are introduced are arranged in an ascending order and are labelled T ic and T ih for the cold and hot sides, respectively. The graphical presentation of the results is facilitated by the insertion at each multiple-utility temperature a perturbed temperature equals the insertion temperature minus a small perturbation. Furthermore, using the heat exchanger network (HEN) minimum temperature-differential approach (ΔT min ) and stream heat-capacity flow rates, the presentation is facilitated by using the conventional temperature shift of the HEN CCs. The set of temperature-shifted stream and target temperatures and perturbed temperatures in the overlap range between the CCs is labelled T ol . Using T ol , a simple formula employing enthalpy-flow differences between the hot composite curve CC h and the cold composite curve CC c is

DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network.

Science.gov (United States)

Mistry, Divya; Wise, Roger P; Dickerson, Julie A

2017-01-01

Identification of central genes and proteins in biomolecular networks provides credible candidates for pathway analysis, functional analysis, and essentiality prediction. The DiffSLC centrality measure predicts central and essential genes and proteins using a protein-protein interaction network. Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures helped identify critical genes and proteins in biomolecular networks. The proposed centrality measure, DiffSLC, combines the number of interactions of a protein and the gene coexpression values of genes from which those proteins were translated, as a weighting factor to bias the identification of essential proteins in a protein interaction network. Potentially essential proteins with low node degree are promoted through eigenvector centrality. Thus, the gene coexpression values are used in conjunction with the eigenvector of the network's adjacency matrix and edge clustering coefficient to improve essentiality prediction. The outcome of this prediction is shown using three variations: (1) inclusion or exclusion of gene co-expression data, (2) impact of different coexpression measures, and (3) impact of different gene expression data sets. For a total of seven networks, DiffSLC is compared to other centrality measures using Saccharomyces cerevisiae protein interaction networks and gene expression data. Comparisons are also performed for the top ranked proteins against the known essential genes from the Saccharomyces Gene Deletion Project, which show that DiffSLC detects more essential proteins and has a higher area under the ROC curve than other compared methods. This makes DiffSLC a stronger alternative to other centrality methods for detecting essential genes using a protein-protein interaction network that obeys centrality-lethality principle. DiffSLC is implemented using the igraph package in R, and networkx package in Python. The python package can be

Perspective: Markov models for long-timescale biomolecular dynamics

International Nuclear Information System (INIS)

Schwantes, C. R.; McGibbon, R. T.; Pande, V. S.

2014-01-01

Molecular dynamics simulations have the potential to provide atomic-level detail and insight to important questions in chemical physics that cannot be observed in typical experiments. However, simply generating a long trajectory is insufficient, as researchers must be able to transform the data in a simulation trajectory into specific scientific insights. Although this analysis step has often been taken for granted, it deserves further attention as large-scale simulations become increasingly routine. In this perspective, we discuss the application of Markov models to the analysis of large-scale biomolecular simulations. We draw attention to recent improvements in the construction of these models as well as several important open issues. In addition, we highlight recent theoretical advances that pave the way for a new generation of models of molecular kinetics

Perspective: Markov models for long-timescale biomolecular dynamics

Energy Technology Data Exchange (ETDEWEB)

Schwantes, C. R.; McGibbon, R. T. [Department of Chemistry, Stanford University, Stanford, California 94305 (United States); Pande, V. S., E-mail: pande@stanford.edu [Department of Chemistry, Stanford University, Stanford, California 94305 (United States); Department of Computer Science, Stanford University, Stanford, California 94305 (United States); Department of Structural Biology, Stanford University, Stanford, California 94305 (United States); Biophysics Program, Stanford University, Stanford, California 94305 (United States)

2014-09-07

Molecular dynamics simulations have the potential to provide atomic-level detail and insight to important questions in chemical physics that cannot be observed in typical experiments. However, simply generating a long trajectory is insufficient, as researchers must be able to transform the data in a simulation trajectory into specific scientific insights. Although this analysis step has often been taken for granted, it deserves further attention as large-scale simulations become increasingly routine. In this perspective, we discuss the application of Markov models to the analysis of large-scale biomolecular simulations. We draw attention to recent improvements in the construction of these models as well as several important open issues. In addition, we highlight recent theoretical advances that pave the way for a new generation of models of molecular kinetics.

Techniques of biomolecular quantification through AMS detection of radiocarbon

International Nuclear Information System (INIS)

Vogel, S.J.; Turteltaub, K.W.; Frantz, C.; Felton, J.S.; Gledhill, B.L.

1992-01-01

Accelerator mass spectrometry offers a large gain over scintillation counting in sensitivity for detecting radiocarbon in biomolecular tracing. Application of this sensitivity requires new considerations of procedures to extract or isolate the carbon fraction to be quantified, to inventory all carbon in the sample, to prepare graphite from the sample for use in the spectrometer, and to derive a meaningful quantification from the measured isotope ratio. These procedures need to be accomplished without contaminating the sample with radiocarbon, which may be ubiquitous in laboratories and on equipment previously used for higher dose, scintillation experiments. Disposable equipment, materials and surfaces are used to control these contaminations. Quantification of attomole amounts of labeled substances are possible through these techniques

Nonadditivity of quantum capacities of quantum multiple-access channels and the butterfly network

International Nuclear Information System (INIS)

Huang Peng; He Guangqiang; Zhu Jun; Zeng Guihua

2011-01-01

Multipartite quantum information transmission without additional classical resources is investigated. We show purely quantum superadditivity of quantum capacity regions of quantum memoryless multiple-access (MA) channels, which are not entanglement breaking. Also, we find that the superadditivity holds when the MA channel extends to the quantum butterfly network, which can achieve quantum network coding. The present widespread effects for the channels which enable entanglement distribution have not been revealed for multipartite scenarios.

Programmable release of multiple protein drugs from aptamer-functionalized hydrogels via nucleic acid hybridization.

Science.gov (United States)

Battig, Mark R; Soontornworajit, Boonchoy; Wang, Yong

2012-08-01

Polymeric delivery systems have been extensively studied to achieve localized and controlled release of protein drugs. However, it is still challenging to control the release of multiple protein drugs in distinct stages according to the progress of disease or treatment. This study successfully demonstrates that multiple protein drugs can be released from aptamer-functionalized hydrogels with adjustable release rates at predetermined time points using complementary sequences (CSs) as biomolecular triggers. Because both aptamer-protein interactions and aptamer-CS hybridization are sequence-specific, aptamer-functionalized hydrogels constitute a promising polymeric delivery system for the programmable release of multiple protein drugs to treat complex human diseases.

A Context-Aware Adaptive Streaming Media Distribution System in a Heterogeneous Network with Multiple Terminals

Directory of Open Access Journals (Sweden)

Yepeng Ni

2016-01-01

Full Text Available We consider the problem of streaming media transmission in a heterogeneous network from a multisource server to home multiple terminals. In wired network, the transmission performance is limited by network state (e.g., the bandwidth variation, jitter, and packet loss. In wireless network, the multiple user terminals can cause bandwidth competition. Thus, the streaming media distribution in a heterogeneous network becomes a severe challenge which is critical for QoS guarantee. In this paper, we propose a context-aware adaptive streaming media distribution system (CAASS, which implements the context-aware module to perceive the environment parameters and use the strategy analysis (SA module to deduce the most suitable service level. This approach is able to improve the video quality for guarantying streaming QoS. We formulate the optimization problem of QoS relationship with the environment parameters based on the QoS testing algorithm for IPTV in ITU-T G.1070. We evaluate the performance of the proposed CAASS through 12 types of experimental environments using a prototype system. Experimental results show that CAASS can dynamically adjust the service level according to the environment variation (e.g., network state and terminal performances and outperforms the existing streaming approaches in adaptive streaming media distribution according to peak signal-to-noise ratio (PSNR.

Logarithmic r-θ mapping for hybrid optical neural network filter for multiple objects recognition within cluttered scenes

Science.gov (United States)

Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.; Birch, Phil M.

2009-04-01

θThe window unit in the design of the complex logarithmic r-θ mapping for hybrid optical neural network filter can allow multiple objects of the same class to be detected within the input image. Additionally, the architecture of the neural network unit of the complex logarithmic r-θ mapping for hybrid optical neural network filter becomes attractive for accommodating the recognition of multiple objects of different classes within the input image by modifying the output layer of the unit. We test the overall filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. Logarithmic r-θ mapping for hybrid optical neural network filter is shown to exhibit with a single pass over the input data simultaneously in-plane rotation, out-of-plane rotation, scale, log r-θ map translation and shift invariance, and good clutter tolerance by recognizing correctly the different objects within the cluttered scenes. We record in our results additional extracted information from the cluttered scenes about the objects' relative position, scale and in-plane rotation.

Parity-Check Network Coding for Multiple Access Relay Channel in Wireless Sensor Cooperative Communications

Directory of Open Access Journals (Sweden)

Du Bing

2010-01-01

Full Text Available A recently developed theory suggests that network coding is a generalization of source coding and channel coding and thus yields a significant performance improvement in terms of throughput and spatial diversity. This paper proposes a cooperative design of a parity-check network coding scheme in the context of a two-source multiple access relay channel (MARC model, a common compact model in hierarchical wireless sensor networks (WSNs. The scheme uses Low-Density Parity-Check (LDPC as the surrogate to build up a layered structure which encapsulates the multiple constituent LDPC codes in the source and relay nodes. Specifically, the relay node decodes the messages from two sources, which are used to generate extra parity-check bits by a random network coding procedure to fill up the rate gap between Source-Relay and Source-Destination transmissions. Then, we derived the key algebraic relationships among multidimensional LDPC constituent codes as one of the constraints for code profile optimization. These extra check bits are sent to the destination to realize a cooperative diversity as well as to approach MARC decode-and-forward (DF capacity.

Single or multiple synchronization transitions in scale-free neuronal networks with electrical or chemical coupling

International Nuclear Information System (INIS)

Hao Yinghang; Gong, Yubing; Wang Li; Ma Xiaoguang; Yang Chuanlu

2011-01-01

Research highlights: → Single synchronization transition for gap-junctional coupling. → Multiple synchronization transitions for chemical synaptic coupling. → Gap junctions and chemical synapses have different impacts on synchronization transition. → Chemical synapses may play a dominant role in neurons' information processing. - Abstract: In this paper, we have studied time delay- and coupling strength-induced synchronization transitions in scale-free modified Hodgkin-Huxley (MHH) neuron networks with gap-junctions and chemical synaptic coupling. It is shown that the synchronization transitions are much different for these two coupling types. For gap-junctions, the neurons exhibit a single synchronization transition with time delay and coupling strength, while for chemical synapses, there are multiple synchronization transitions with time delay, and the synchronization transition with coupling strength is dependent on the time delay lengths. For short delays we observe a single synchronization transition, whereas for long delays the neurons exhibit multiple synchronization transitions as the coupling strength is varied. These results show that gap junctions and chemical synapses have different impacts on the pattern formation and synchronization transitions of the scale-free MHH neuronal networks, and chemical synapses, compared to gap junctions, may play a dominant and more active function in the firing activity of the networks. These findings would be helpful for further understanding the roles of gap junctions and chemical synapses in the firing dynamics of neuronal networks.

Single or multiple synchronization transitions in scale-free neuronal networks with electrical or chemical coupling

Energy Technology Data Exchange (ETDEWEB)

Hao Yinghang [School of Physics, Ludong University, Yantai 264025 (China); Gong, Yubing, E-mail: gongyubing09@hotmail.co [School of Physics, Ludong University, Yantai 264025 (China); Wang Li; Ma Xiaoguang; Yang Chuanlu [School of Physics, Ludong University, Yantai 264025 (China)

2011-04-15

Research highlights: Single synchronization transition for gap-junctional coupling. Multiple synchronization transitions for chemical synaptic coupling. Gap junctions and chemical synapses have different impacts on synchronization transition. Chemical synapses may play a dominant role in neurons' information processing. - Abstract: In this paper, we have studied time delay- and coupling strength-induced synchronization transitions in scale-free modified Hodgkin-Huxley (MHH) neuron networks with gap-junctions and chemical synaptic coupling. It is shown that the synchronization transitions are much different for these two coupling types. For gap-junctions, the neurons exhibit a single synchronization transition with time delay and coupling strength, while for chemical synapses, there are multiple synchronization transitions with time delay, and the synchronization transition with coupling strength is dependent on the time delay lengths. For short delays we observe a single synchronization transition, whereas for long delays the neurons exhibit multiple synchronization transitions as the coupling strength is varied. These results show that gap junctions and chemical synapses have different impacts on the pattern formation and synchronization transitions of the scale-free MHH neuronal networks, and chemical synapses, compared to gap junctions, may play a dominant and more active function in the firing activity of the networks. These findings would be helpful for further understanding the roles of gap junctions and chemical synapses in the firing dynamics of neuronal networks.

ISAMBARD: an open-source computational environment for biomolecular analysis, modelling and design.

Science.gov (United States)

Wood, Christopher W; Heal, Jack W; Thomson, Andrew R; Bartlett, Gail J; Ibarra, Amaurys Á; Brady, R Leo; Sessions, Richard B; Woolfson, Derek N

2017-10-01

The rational design of biomolecules is becoming a reality. However, further computational tools are needed to facilitate and accelerate this, and to make it accessible to more users. Here we introduce ISAMBARD, a tool for structural analysis, model building and rational design of biomolecules. ISAMBARD is open-source, modular, computationally scalable and intuitive to use. These features allow non-experts to explore biomolecular design in silico. ISAMBARD addresses a standing issue in protein design, namely, how to introduce backbone variability in a controlled manner. This is achieved through the generalization of tools for parametric modelling, describing the overall shape of proteins geometrically, and without input from experimentally determined structures. This will allow backbone conformations for entire folds and assemblies not observed in nature to be generated de novo, that is, to access the 'dark matter of protein-fold space'. We anticipate that ISAMBARD will find broad applications in biomolecular design, biotechnology and synthetic biology. A current stable build can be downloaded from the python package index (https://pypi.python.org/pypi/isambard/) with development builds available on GitHub (https://github.com/woolfson-group/) along with documentation, tutorial material and all the scripts used to generate the data described in this paper. d.n.woolfson@bristol.ac.uk or chris.wood@bristol.ac.uk. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Adaptation of AMO-FBMC-OQAM in optical access network for accommodating asynchronous multiple access in OFDM-based uplink transmission

Science.gov (United States)

Jung, Sun-Young; Jung, Sang-Min; Han, Sang-Kook

2015-01-01

Exponentially expanding various applications in company with proliferation of mobile devices make mobile traffic exploded annually. For future access network, bandwidth efficient and asynchronous signals converged transmission technique is required in optical network to meet a huge bandwidth demand, while integrating various services and satisfying multiple access in perceived network resource. Orthogonal frequency division multiplexing (OFDM) is highly bandwidth efficient parallel transmission technique based on orthogonal subcarriers. OFDM has been widely studied in wired-/wireless communication and became a Long term evolution (LTE) standard. Consequently, OFDM also has been actively researched in optical network. However, OFDM is vulnerable frequency and phase offset essentially because of its sinc-shaped side lobes, therefore tight synchronism is necessary to maintain orthogonality. Moreover, redundant cyclic prefix (CP) is required in dispersive channel. Additionally, side lobes act as interference among users in multiple access. Thus, it practically hinders from supporting integration of various services and multiple access based on OFDM optical transmission In this paper, adaptively modulated optical filter bank multicarrier system with offset QAM (AMO-FBMC-OQAM) is introduced and experimentally investigated in uplink optical transmission to relax multiple access interference (MAI), while improving bandwidth efficiency. Side lobes are effectively suppressed by using FBMC, therefore the system becomes robust to path difference and imbalance among optical network units (ONUs), which increase bandwidth efficiency by reducing redundancy. In comparison with OFDM, a signal performance and an efficiency of frequency utilization are improved in the same experimental condition. It enables optical network to effectively support heterogeneous services and multiple access.

Discrete event command and control for networked teams with multiple missions

Science.gov (United States)

Lewis, Frank L.; Hudas, Greg R.; Pang, Chee Khiang; Middleton, Matthew B.; McMurrough, Christopher

2009-05-01

During mission execution in military applications, the TRADOC Pamphlet 525-66 Battle Command and Battle Space Awareness capabilities prescribe expectations that networked teams will perform in a reliable manner under changing mission requirements, varying resource availability and reliability, and resource faults. In this paper, a Command and Control (C2) structure is presented that allows for computer-aided execution of the networked team decision-making process, control of force resources, shared resource dispatching, and adaptability to change based on battlefield conditions. A mathematically justified networked computing environment is provided called the Discrete Event Control (DEC) Framework. DEC has the ability to provide the logical connectivity among all team participants including mission planners, field commanders, war-fighters, and robotic platforms. The proposed data management tools are developed and demonstrated on a simulation study and an implementation on a distributed wireless sensor network. The results show that the tasks of multiple missions are correctly sequenced in real-time, and that shared resources are suitably assigned to competing tasks under dynamically changing conditions without conflicts and bottlenecks.

Multiple Spatial Coherence Resonances and Spatial Patterns in a Noise-Driven Heterogeneous Neuronal Network

International Nuclear Information System (INIS)

Li Yu-Ye; Ding Xue-Li

2014-01-01

Heterogeneity of the neurons and noise are inevitable in the real neuronal network. In this paper, Gaussian white noise induced spatial patterns including spiral waves and multiple spatial coherence resonances are studied in a network composed of Morris—Lecar neurons with heterogeneity characterized by parameter diversity. The relationship between the resonances and the transitions between ordered spiral waves and disordered spatial patterns are achieved. When parameter diversity is introduced, the maxima of multiple resonances increases first, and then decreases as diversity strength increases, which implies that the coherence degrees induced by noise are enhanced at an intermediate diversity strength. The synchronization degree of spatial patterns including ordered spiral waves and disordered patterns is identified to be a very low level. The results suggest that the nervous system can profit from both heterogeneity and noise, and the multiple spatial coherence resonances are achieved via the emergency of spiral waves instead of synchronization patterns. (interdisciplinary physics and related areas of science and technology)

Multiple Spatial Coherence Resonances and Spatial Patterns in a Noise-Driven Heterogeneous Neuronal Network

Science.gov (United States)

Li, Yu-Ye; Ding, Xue-Li

2014-12-01

Heterogeneity of the neurons and noise are inevitable in the real neuronal network. In this paper, Gaussian white noise induced spatial patterns including spiral waves and multiple spatial coherence resonances are studied in a network composed of Morris—Lecar neurons with heterogeneity characterized by parameter diversity. The relationship between the resonances and the transitions between ordered spiral waves and disordered spatial patterns are achieved. When parameter diversity is introduced, the maxima of multiple resonances increases first, and then decreases as diversity strength increases, which implies that the coherence degrees induced by noise are enhanced at an intermediate diversity strength. The synchronization degree of spatial patterns including ordered spiral waves and disordered patterns is identified to be a very low level. The results suggest that the nervous system can profit from both heterogeneity and noise, and the multiple spatial coherence resonances are achieved via the emergency of spiral waves instead of synchronization patterns.

Spiral Waves and Multiple Spatial Coherence Resonances Induced by Colored Noise in Neuronal Network

International Nuclear Information System (INIS)

Tang Zhao; Li Yuye; Xi Lei; Jia Bing; Gu Huaguang

2012-01-01

Gaussian colored noise induced spatial patterns and spatial coherence resonances in a square lattice neuronal network composed of Morris-Lecar neurons are studied. Each neuron is at resting state near a saddle-node bifurcation on invariant circle, coupled to its nearest neighbors by electronic coupling. Spiral waves with different structures and disordered spatial structures can be alternately induced within a large range of noise intensity. By calculating spatial structure function and signal-to-noise ratio (SNR), it is found that SNR values are higher when the spiral structures are simple and are lower when the spatial patterns are complex or disordered, respectively. SNR manifest multiple local maximal peaks, indicating that the colored noise can induce multiple spatial coherence resonances. The maximal SNR values decrease as the correlation time of the noise increases. These results not only provide an example of multiple resonances, but also show that Gaussian colored noise play constructive roles in neuronal network. (general)

Integrated Spintronic Platforms for Biomolecular Recognition Detection

Science.gov (United States)

Martins, V. C.; Cardoso, F. A.; Loureiro, J.; Mercier, M.; Germano, J.; Cardoso, S.; Ferreira, R.; Fonseca, L. P.; Sousa, L.; Piedade, M. S.; Freitas, P. P.

2008-06-01

This paper covers recent developments in magnetoresistive based biochip platforms fabricated at INESC-MN, and their application to the detection and quantification of pathogenic waterborn microorganisms in water samples for human consumption. Such platforms are intended to give response to the increasing concern related to microbial contaminated water sources. The presented results concern the development of biological active DNA chips and protein chips and the demonstration of the detection capability of the present platforms. Two platforms are described, one including spintronic sensors only (spin-valve based or magnetic tunnel junction based), and the other, a fully scalable platform where each probe site consists of a MTJ in series with a thin film diode (TFD). Two microfluidic systems are described, for cell separation and concentration, and finally, the read out and control integrated electronics are described, allowing the realization of bioassays with a portable point of care unit. The present platforms already allow the detection of complementary biomolecular target recognition with 1 pM concentration.

Parameter Diversity Induced Multiple Spatial Coherence Resonances and Spiral Waves in Neuronal Network with and Without Noise

International Nuclear Information System (INIS)

Li Yuye; Jia Bing; Gu Huaguang; An Shucheng

2012-01-01

Diversity in the neurons and noise are inevitable in the real neuronal network. In this paper, parameter diversity induced spiral waves and multiple spatial coherence resonances in a two-dimensional neuronal network without or with noise are simulated. The relationship between the multiple resonances and the multiple transitions between patterns of spiral waves are identified. The coherence degrees induced by the diversity are suppressed when noise is introduced and noise density is increased. The results suggest that natural nervous system might profit from both parameter diversity and noise, provided a possible approach to control formation and transition of spiral wave by the cooperation between the diversity and noise. (general)

A feedback control model for network flow with multiple pure time delays

Science.gov (United States)

Press, J.

1972-01-01

A control model describing a network flow hindered by multiple pure time (or transport) delays is formulated. Feedbacks connect each desired output with a single control sector situated at the origin. The dynamic formulation invokes the use of differential difference equations. This causes the characteristic equation of the model to consist of transcendental functions instead of a common algebraic polynomial. A general graphical criterion is developed to evaluate the stability of such a problem. A digital computer simulation confirms the validity of such criterion. An optimal decision making process with multiple delays is presented.

Performance analysis of an opportunistic multi-user cognitive network with multiple primary users

KAUST Repository

Khan, Fahd Ahmed

2014-03-01

Consider a multi-user underlay cognitive network where multiple cognitive users concurrently share the spectrum with a primary network with multiple users. The channel between the secondary network is assumed to have independent but not identical Nakagami-m fading. The interference channel between the secondary users (SUs) and the primary users is assumed to have Rayleigh fading. A power allocation based on the instantaneous channel state information is derived when a peak interference power constraint is imposed on the secondary network in addition to the limited peak transmit power of each SU. The uplink scenario is considered where a single SU is selected for transmission. This opportunistic selection depends on the transmission channel power gain and the interference channel power gain as well as the power allocation policy adopted at the users. Exact closed form expressions for the moment-generating function, outage performance, symbol error rate performance, and the ergodic capacity are derived. Numerical results corroborate the derived analytical results. The performance is also studied in the asymptotic regimes, and the generalized diversity gain of this scheduling scheme is derived. It is shown that when the interference channel is deeply faded and the peak transmit power constraint is relaxed, the scheduling scheme achieves full diversity and that increasing the number of primary users does not impact the diversity order. © 2014 John Wiley & Sons, Ltd.

A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design.

Science.gov (United States)

Alford, Rebecca F; Leaver-Fay, Andrew; Gonzales, Lynda; Dolan, Erin L; Gray, Jeffrey J

2017-12-01

Computational biology is an interdisciplinary field, and many computational biology research projects involve distributed teams of scientists. To accomplish their work, these teams must overcome both disciplinary and geographic barriers. Introducing new training paradigms is one way to facilitate research progress in computational biology. Here, we describe a new undergraduate program in biomolecular structure prediction and design in which students conduct research at labs located at geographically-distributed institutions while remaining connected through an online community. This 10-week summer program begins with one week of training on computational biology methods development, transitions to eight weeks of research, and culminates in one week at the Rosetta annual conference. To date, two cohorts of students have participated, tackling research topics including vaccine design, enzyme design, protein-based materials, glycoprotein modeling, crowd-sourced science, RNA processing, hydrogen bond networks, and amyloid formation. Students in the program report outcomes comparable to students who participate in similar in-person programs. These outcomes include the development of a sense of community and increases in their scientific self-efficacy, scientific identity, and science values, all predictors of continuing in a science research career. Furthermore, the program attracted students from diverse backgrounds, which demonstrates the potential of this approach to broaden the participation of young scientists from backgrounds traditionally underrepresented in computational biology.

A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design.

Directory of Open Access Journals (Sweden)

Rebecca F Alford

2017-12-01

Full Text Available Computational biology is an interdisciplinary field, and many computational biology research projects involve distributed teams of scientists. To accomplish their work, these teams must overcome both disciplinary and geographic barriers. Introducing new training paradigms is one way to facilitate research progress in computational biology. Here, we describe a new undergraduate program in biomolecular structure prediction and design in which students conduct research at labs located at geographically-distributed institutions while remaining connected through an online community. This 10-week summer program begins with one week of training on computational biology methods development, transitions to eight weeks of research, and culminates in one week at the Rosetta annual conference. To date, two cohorts of students have participated, tackling research topics including vaccine design, enzyme design, protein-based materials, glycoprotein modeling, crowd-sourced science, RNA processing, hydrogen bond networks, and amyloid formation. Students in the program report outcomes comparable to students who participate in similar in-person programs. These outcomes include the development of a sense of community and increases in their scientific self-efficacy, scientific identity, and science values, all predictors of continuing in a science research career. Furthermore, the program attracted students from diverse backgrounds, which demonstrates the potential of this approach to broaden the participation of young scientists from backgrounds traditionally underrepresented in computational biology.

An energy efficient multiple mobile sinks based routing algorithm for wireless sensor networks

Science.gov (United States)

Zhong, Peijun; Ruan, Feng

2018-03-01

With the fast development of wireless sensor networks (WSNs), more and more energy efficient routing algorithms have been proposed. However, one of the research challenges is how to alleviate the hot spot problem since nodes close to static sink (or base station) tend to die earlier than other sensors. The introduction of mobile sink node can effectively alleviate this problem since sink node can move along certain trajectories, causing hot spot nodes more evenly distributed. In this paper, we mainly study the energy efficient routing method with multiple mobile sinks support. We divide the whole network into several clusters and study the influence of mobile sink number on network lifetime. Simulation results show that the best network performance appears when mobile sink number is about 3 under our simulation environment.

Orientation of biomolecular assemblies in a microfluidic jet

International Nuclear Information System (INIS)

Priebe, M; Kalbfleisch, S; Tolkiehn, M; Salditt, T; Koester, S; Abel, B; Davies, R J

2010-01-01

We have investigated multilamellar lipid assemblies in a microfluidic jet, operating at high shear rates of the order of 10 7 s -1 . Compared to classical Couette cells or rheometers, the shear rate was increased by at least 2-3 orders of magnitude, and the sample volume was scaled down correspondingly. At the same time, the jet is characterized by high extensional stress due to elongational flow. A focused synchrotron x-ray beam was used to measure the structure and orientation of the lipid assemblies in the jet. The diffraction patterns indicate conventional multilamellar phases, aligned with the membrane normals oriented along the velocity gradient of the jet. The results indicate that the setup may be well suited for coherent diffractive imaging of oriented biomolecular assemblies and macromolecules at the future x-ray free electron laser (XFEL) sources.

ANCA: Anharmonic Conformational Analysis of Biomolecular Simulations.

Science.gov (United States)

Parvatikar, Akash; Vacaliuc, Gabriel S; Ramanathan, Arvind; Chennubhotla, S Chakra

2018-05-08

Anharmonicity in time-dependent conformational fluctuations is noted to be a key feature of functional dynamics of biomolecules. Although anharmonic events are rare, long-timescale (μs-ms and beyond) simulations facilitate probing of such events. We have previously developed quasi-anharmonic analysis to resolve higher-order spatial correlations and characterize anharmonicity in biomolecular simulations. In this article, we have extended this toolbox to resolve higher-order temporal correlations and built a scalable Python package called anharmonic conformational analysis (ANCA). ANCA has modules to: 1) measure anharmonicity in the form of higher-order statistics and its variation as a function of time, 2) output a storyboard representation of the simulations to identify key anharmonic conformational events, and 3) identify putative anharmonic conformational substates and visualization of transitions between these substates. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Introduction to a Protein Interaction System Used for Quantitative Evaluation of Biomolecular Interactions

OpenAIRE

Yamniuk, Aaron

2013-01-01

A central goal of molecular biology is the determination of biomolecular function. This comes largely from a knowledge of the non-covalent interactions that biological small and macro-molecules experience. The fundamental mission of the Molecular Interactions Research Group (MIRG) of the ABRF is to show how solution biophysical tools are used to quantitatively characterize molecular interactions, and to educate the ABRF members and scientific community on the utility and limitations of core t...

An Interference-Aware Traffic-Priority-Based Link Scheduling Algorithm for Interference Mitigation in Multiple Wireless Body Area Networks

Directory of Open Access Journals (Sweden)

Thien T. T. Le

2016-12-01

Full Text Available Currently, wireless body area networks (WBANs are effectively used for health monitoring services. However, in cases where WBANs are densely deployed, interference among WBANs can cause serious degradation of network performance and reliability. Inter-WBAN interference can be reduced by scheduling the communication links of interfering WBANs. In this paper, we propose an interference-aware traffic-priority-based link scheduling (ITLS algorithm to overcome inter-WBAN interference in densely deployed WBANs. First, we model a network with multiple WBANs as an interference graph where node-level interference and traffic priority are taken into account. Second, we formulate link scheduling for multiple WBANs as an optimization model where the objective is to maximize the throughput of the entire network while ensuring the traffic priority of sensor nodes. Finally, we propose the ITLS algorithm for multiple WBANs on the basis of the optimization model. High spatial reuse is also achieved in the proposed ITLS algorithm. The proposed ITLS achieves high spatial reuse while considering traffic priority, packet length, and the number of interfered sensor nodes. Our simulation results show that the proposed ITLS significantly increases spatial reuse and network throughput with lower delay by mitigating inter-WBAN interference.

Review of MEMS differential scanning calorimetry for biomolecular study

Science.gov (United States)

Yu, Shifeng; Wang, Shuyu; Lu, Ming; Zuo, Lei

2017-12-01

Differential scanning calorimetry (DSC) is one of the few techniques that allow direct determination of enthalpy values for binding reactions and conformational transitions in biomolecules. It provides the thermodynamics information of the biomolecules which consists of Gibbs free energy, enthalpy and entropy in a straightforward manner that enables deep understanding of the structure function relationship in biomolecules such as the folding/unfolding of protein and DNA, and ligand bindings. This review provides an up to date overview of the applications of DSC in biomolecular study such as the bovine serum albumin denaturation study, the relationship between the melting point of lysozyme and the scanning rate. We also introduce the recent advances of the development of micro-electro-mechanic-system (MEMS) based DSCs.

Global exponential stability for reaction-diffusion recurrent neural networks with multiple time varying delays

International Nuclear Information System (INIS)

Lou, X.; Cui, B.

2008-01-01

In this paper we consider the problem of exponential stability for recurrent neural networks with multiple time varying delays and reaction-diffusion terms. The activation functions are supposed to be bounded and globally Lipschitz continuous. By means of Lyapunov functional, sufficient conditions are derived, which guarantee global exponential stability of the delayed neural network. Finally, a numerical example is given to show the correctness of our analysis. (author)

Multiple effect of social influence on cooperation in interdependent network games

Science.gov (United States)

Jiang, Luo-Luo; Li, Wen-Jing; Wang, Zhen

2015-10-01

The social influence exists widely in the human society, where individual decision-making process (from congressional election to electronic commerce) may be affected by the attitude and behavior of others belonging to different social networks. Here, we couple the snowdrift (SD) game and the prisoner’s dilemma (PD) game on two interdependent networks, where strategies in both games are associated by social influence to mimick the majority rule. More accurately, individuals’ strategies updating refers to social learning (based on payoff difference) and above-mentioned social influence (related with environment of interdependent group), which is controlled by social influence strength s. Setting s = 0 decouples the networks and returns the traditional network game; while its increase involves the interactions between networks. By means of numerous Monte Carlo simulations, we find that such a mechanism brings multiple influence to the evolution of cooperation. Small s leads to unequal cooperation level in both games, because social learning is still the main updating rule for most players. Though intermediate and large s guarantees the synchronized evolution of strategy pairs, cooperation finally dies out and reaches a completely dominance in both cases. Interestingly, these observations are attributed to the expansion of cooperation clusters. Our work may provide a new understanding to the emergence of cooperation in intercorrelated social systems.

Multiple Time Series Forecasting Using Quasi-Randomized Functional Link Neural Networks

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Thierry Moudiki

2018-03-01

Full Text Available We are interested in obtaining forecasts for multiple time series, by taking into account the potential nonlinear relationships between their observations. For this purpose, we use a specific type of regression model on an augmented dataset of lagged time series. Our model is inspired by dynamic regression models (Pankratz 2012, with the response variable’s lags included as predictors, and is known as Random Vector Functional Link (RVFL neural networks. The RVFL neural networks have been successfully applied in the past, to solving regression and classification problems. The novelty of our approach is to apply an RVFL model to multivariate time series, under two separate regularization constraints on the regression parameters.

DMP: Detouring Using Multiple Paths against Jamming Attack for Ubiquitous Networking System

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Mihui Kim

2010-04-01

Full Text Available To successfully realize the ubiquitous network environment including home automation or industrial control systems, it is important to be able to resist a jamming attack. This has recently been considered as an extremely threatening attack because it can collapse the entire network, despite the existence of basic security protocols such as encryption and authentication. In this paper, we present a method of jamming attack tolerant routing using multiple paths based on zones. The proposed scheme divides the network into zones, and manages the candidate forward nodes of neighbor zones. After detecting an attack, detour nodes decide zones for rerouting, and detour packets destined for victim nodes through forward nodes in the decided zones. Simulation results show that our scheme increases the PDR (Packet Delivery Ratio and decreases the delay significantly in comparison with rerouting by a general routing protocol on sensor networks, AODV (Ad hoc On Demand Distance Vector, and a conventional JAM (Jammed Area Mapping service with one reroute.

DMP: detouring using multiple paths against jamming attack for ubiquitous networking system.

Science.gov (United States)

Kim, Mihui; Chae, Kijoon

2010-01-01

To successfully realize the ubiquitous network environment including home automation or industrial control systems, it is important to be able to resist a jamming attack. This has recently been considered as an extremely threatening attack because it can collapse the entire network, despite the existence of basic security protocols such as encryption and authentication. In this paper, we present a method of jamming attack tolerant routing using multiple paths based on zones. The proposed scheme divides the network into zones, and manages the candidate forward nodes of neighbor zones. After detecting an attack, detour nodes decide zones for rerouting, and detour packets destined for victim nodes through forward nodes in the decided zones. Simulation results show that our scheme increases the PDR (Packet Delivery Ratio) and decreases the delay significantly in comparison with rerouting by a general routing protocol on sensor networks, AODV (Ad hoc On Demand Distance Vector), and a conventional JAM (Jammed Area Mapping) service with one reroute.

Stability and attractive basins of multiple equilibria in delayed two-neuron networks

International Nuclear Information System (INIS)

Huang Yu-Jiao; Zhang Hua-Guang; Wang Zhan-Shan

2012-01-01

Multiple stability for two-dimensional delayed recurrent neural networks with piecewise linear activation functions of 2r (r ≥ 1) corner points is studied. Sufficient conditions are established for checking the existence of (2r + 1) 2 equilibria in delayed recurrent neural networks. Under these conditions, (r + 1) 2 equilibria are locally exponentially stable, and (2r + 1) 2 — (r + 1) 2 — r 2 equilibria are unstable. Attractive basins of stable equilibria are estimated, which are larger than invariant sets derived by decomposing state space. One example is provided to illustrate the effectiveness of our results. (general)

Lower Bounds on the Maximum Energy Benefit of Network Coding for Wireless Multiple Unicast

Directory of Open Access Journals (Sweden)

Matsumoto Ryutaroh

2010-01-01

Full Text Available We consider the energy savings that can be obtained by employing network coding instead of plain routing in wireless multiple unicast problems. We establish lower bounds on the benefit of network coding, defined as the maximum of the ratio of the minimum energy required by routing and network coding solutions, where the maximum is over all configurations. It is shown that if coding and routing solutions are using the same transmission range, the benefit in d-dimensional networks is at least . Moreover, it is shown that if the transmission range can be optimized for routing and coding individually, the benefit in 2-dimensional networks is at least 3. Our results imply that codes following a decode-and-recombine strategy are not always optimal regarding energy efficiency.

Cross-Layer Design for Two-Way Relaying Networks with Multiple Antennas

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zhuo wu

2015-10-01

Full Text Available In this paper, we developed a cross-layer design for two-way relaying (TWR networks with multiple antennas, where two single antenna source nodes exchange information with the aid of one multiple antenna relay node. The proposed cross-layer design considers adaptive modulation (AM and space-time block coding (STBC at the physical layer with an automatic repeat request (ARQ protocol at the data link layer, in order to maximize the spectral efficiency under specific delay and packet error ratio (PER constraints. An MMSE-interference cancellation (IC receiver is employed at the relay node, to remove the interference in the fist phase of the TWR transmission. The transmission mode is updated for each phase of the TWR transmission on a frame-by-frame basis, to match the time-varying channel conditions and exploit the system performance and throughput gain. Simulation results show that retransmission at the data link layer could alleviate rigorous error-control requirements at the physical layer, and thereby allows higher data transmission. As a result, cross-layer design helps to achieve considerable system spectral efficiency gain for TWR networks, compared to those without cross-layer design.

Multiscale Persistent Functions for Biomolecular Structure Characterization

Energy Technology Data Exchange (ETDEWEB)

Xia, Kelin [Nanyang Technological University (Singapore). Division of Mathematical Sciences, School of Physical, Mathematical Sciences and School of Biological Sciences; Li, Zhiming [Central China Normal University, Wuhan (China). Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics; Mu, Lin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division

2017-11-02

Here in this paper, we introduce multiscale persistent functions for biomolecular structure characterization. The essential idea is to combine our multiscale rigidity functions (MRFs) with persistent homology analysis, so as to construct a series of multiscale persistent functions, particularly multiscale persistent entropies, for structure characterization. To clarify the fundamental idea of our method, the multiscale persistent entropy (MPE) model is discussed in great detail. Mathematically, unlike the previous persistent entropy (Chintakunta et al. in Pattern Recognit 48(2):391–401, 2015; Merelli et al. in Entropy 17(10):6872–6892, 2015; Rucco et al. in: Proceedings of ECCS 2014, Springer, pp 117–128, 2016), a special resolution parameter is incorporated into our model. Various scales can be achieved by tuning its value. Physically, our MPE can be used in conformational entropy evaluation. More specifically, it is found that our method incorporates in it a natural classification scheme. This is achieved through a density filtration of an MRF built from angular distributions. To further validate our model, a systematical comparison with the traditional entropy evaluation model is done. Additionally, it is found that our model is able to preserve the intrinsic topological features of biomolecular data much better than traditional approaches, particularly for resolutions in the intermediate range. Moreover, by comparing with traditional entropies from various grid sizes, bond angle-based methods and a persistent homology-based support vector machine method (Cang et al. in Mol Based Math Biol 3:140–162, 2015), we find that our MPE method gives the best results in terms of average true positive rate in a classic protein structure classification test. More interestingly, all-alpha and all-beta protein classes can be clearly separated from each other with zero error only in our model. Finally, a special protein structure index (PSI) is proposed, for the first

Multiple-state based power control for multi-radio multi-channel wireless mesh networks

CSIR Research Space (South Africa)

Olwal, TO

2009-01-01

Full Text Available Multi-Radio Multi-Channel (MRMC) systems are key to power control problems in wireless mesh networks (WMNs). In this paper, we present asynchronous multiple-state based power control for MRMC WMNs. First, WMN is represented as a set of disjoint...

Systematic Analysis of the Multiple Bioactivities of Green Tea through a Network Pharmacology Approach

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Shoude Zhang

2014-01-01

Full Text Available During the past decades, a number of studies have demonstrated multiple beneficial health effects of green tea. Polyphenolics are the most biologically active components of green tea. Many targets can be targeted or affected by polyphenolics. In this study, we excavated all of the targets of green tea polyphenolics (GTPs though literature mining and target calculation and analyzed the multiple pharmacology actions of green tea comprehensively through a network pharmacology approach. In the end, a total of 200 Homo sapiens targets were identified for fifteen GTPs. These targets were classified into six groups according to their related disease, which included cancer, diabetes, neurodegenerative disease, cardiovascular disease, muscular disease, and inflammation. Moreover, these targets mapped into 143 KEGG pathways, 26 of which were more enriched, as determined though pathway enrichment analysis and target-pathway network analysis. Among the identified pathways, 20 pathways were selected for analyzing the mechanisms of green tea in these diseases. Overall, this study systematically illustrated the mechanisms of the pleiotropic activity of green tea by analyzing the corresponding “drug-target-pathway-disease” interaction network.

LAI inversion from optical reflectance using a neural network trained with a multiple scattering model

Science.gov (United States)

Smith, James A.

1992-01-01

The inversion of the leaf area index (LAI) canopy parameter from optical spectral reflectance measurements is obtained using a backpropagation artificial neural network trained using input-output pairs generated by a multiple scattering reflectance model. The problem of LAI estimation over sparse canopies (LAI 1000 percent for low LAI. Minimization methods applied to merit functions constructed from differences between measured reflectances and predicted reflectances using multiple-scattering models are unacceptably sensitive to a good initial guess for the desired parameter. In contrast, the neural network reported generally yields absolute percentage errors of <30 percent when weighting coefficients trained on one soil type were applied to predicted canopy reflectance at a different soil background.

Native fluorescence detection of biomolecular and pharmaceutical compounds in capillary electrophoresis: detector designs, performance and applications: A review

NARCIS (Netherlands)

de Kort, B.J.; de Jong, G.J.; Somsen, G.W.

2013-01-01

This review treats the coupling of capillary electrophoresis (CE) with fluorescence detection (Flu) for the analysis of natively fluorescent biomolecular and pharmaceutical compounds. CE-Flu combines the excellent separation efficiency of CE with the high selectivity and sensitivity of Flu. In

Nonadditivity of quantum and classical capacities for entanglement breaking multiple-access channels and the butterfly network

International Nuclear Information System (INIS)

Grudka, Andrzej; Horodecki, Pawel

2010-01-01

We analyze quantum network primitives which are entanglement breaking. We show superadditivity of quantum and classical capacity regions for quantum multiple-access channels and the quantum butterfly network. Since the effects are especially visible at high noise they suggest that quantum information effects may be particularly helpful in the case of the networks with occasional high noise rates. The present effects provide a qualitative borderline between superadditivities of bipartite and multipartite systems.

Multiple Distributed Smart Microgrids with a Self-Autonomous, Energy Harvesting Wireless Sensor Network

DEFF Research Database (Denmark)

Guerrero, Josep M.; Kheng Tan, Yen

2012-01-01

The chapter covers the smart wireless sensors for microgrids, as well as the energy harvesting technology used to sustain the operations of these sensors. Last, a case study on the multiple distributed smart microgrids with a self-autonomous, energy harvesting wireless sensor network is presented....

Tibialis anterior muscle needle biopsy and sensitive biomolecular methods: a useful tool in myotonic dystrophy type 1

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S. Iachettini

2015-10-01

Full Text Available Myotonic dystrophy type 1 (DM1 is a neuromuscular disorder caused by a CTG repeat expansion in 3’UTR of DMPK gene. This mutation causes accumulation of toxic RNA in nuclear foci leading to splicing misregulation of specific genes. In view of future clinical trials with antisense oligonucleotides in DM1 patients, it is important to set up sensitive and minimally-invasive tools to monitor the efficacy of treatments on skeletal muscle. A tibialis anterior (TA muscle sample of about 60 mg was obtained from 5 DM1 patients and 5 healthy subjects through a needle biopsy. A fragment of about 40 mg was used for histological examination and a fragment of about 20 mg was used for biomolecular analysis. The TA fragments obtained with the minimally-invasive needle biopsy technique is enough to perform all the histopathological and biomolecular evaluations useful to monitor a clinical trial on DM1 patients.

Hybrid organic semiconductor lasers for bio-molecular sensing.

Science.gov (United States)

Haughey, Anne-Marie; Foucher, Caroline; Guilhabert, Benoit; Kanibolotsky, Alexander L; Skabara, Peter J; Burley, Glenn; Dawson, Martin D; Laurand, Nicolas

2014-01-01

Bio-functionalised luminescent organic semiconductors are attractive for biophotonics because they can act as efficient laser materials while simultaneously interacting with molecules. In this paper, we present and discuss a laser biosensor platform that utilises a gain layer made of such an organic semiconductor material. The simple structure of the sensor and its operation principle are described. Nanolayer detection is shown experimentally and analysed theoretically in order to assess the potential and the limits of the biosensor. The advantage conferred by the organic semiconductor is explained, and comparisons to laser sensors using alternative dye-doped materials are made. Specific biomolecular sensing is demonstrated, and routes to functionalisation with nucleic acid probes, and future developments opened up by this achievement, are highlighted. Finally, attractive formats for sensing applications are mentioned, as well as colloidal quantum dots, which in the future could be used in conjunction with organic semiconductors.

ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining.

Science.gov (United States)

Huan, Tianxiao; Sivachenko, Andrey Y; Harrison, Scott H; Chen, Jake Y

2008-08-12

New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges

A genetic algorithm for multiple relay selection in two-way relaying cognitive radio networks

KAUST Repository

Alsharoa, Ahmad M.; Ghazzai, Hakim; Alouini, Mohamed-Slim

2013-01-01

In this paper, we investigate a multiple relay selection scheme for two-way relaying cognitive radio networks where primary users and secondary users operate on the same frequency band. More specifically, cooperative relays using Amplifyand- Forward

Symbolic dynamics and synchronization of coupled map networks with multiple delays

International Nuclear Information System (INIS)

Atay, Fatihcan M.; Jalan, Sarika; Jost, Juergen

2010-01-01

We use symbolic dynamics to study discrete-time dynamical systems with multiple time delays. We exploit the concept of avoiding sets, which arise from specific non-generating partitions of the phase space and restrict the occurrence of certain symbol sequences related to the characteristics of the dynamics. In particular, we show that the resulting forbidden sequences are closely related to the time delays in the system. We present two applications to coupled map lattices, namely (1) detecting synchronization and (2) determining unknown values of the transmission delays in networks with possibly directed and weighted connections and measurement noise. The method is applicable to multi-dimensional as well as set-valued maps, and to networks with time-varying delays and connection structure.

Design rules for biomolecular adhesion: lessons from force measurements.

Science.gov (United States)

Leckband, Deborah

2010-01-01

Cell adhesion to matrix, other cells, or pathogens plays a pivotal role in many processes in biomolecular engineering. Early macroscopic methods of quantifying adhesion led to the development of quantitative models of cell adhesion and migration. The more recent use of sensitive probes to quantify the forces that alter or manipulate adhesion proteins has revealed much greater functional diversity than was apparent from population average measurements of cell adhesion. This review highlights theoretical and experimental methods that identified force-dependent molecular properties that are central to the biological activity of adhesion proteins. Experimental and theoretical methods emphasized in this review include the surface force apparatus, atomic force microscopy, and vesicle-based probes. Specific examples given illustrate how these tools have revealed unique properties of adhesion proteins and their structural origins.

An Adaptive Time-Spread Multiple-Access Policy for Wireless Sensor Networks

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Konstantinos Oikonomou

2007-05-01

Full Text Available Sensor networks require a simple and efficient medium access control policy achieving high system throughput with no or limited control overhead in order to increase the network lifetime by minimizing the energy consumed during transmission attempts. Time-spread multiple-access (TSMA policies that have been proposed for ad hoc network environments, can also be employed in sensor networks, since no control overhead is introduced. However, they do not take advantage of any cross-layer information in order to exploit the idiosyncrasies of the particular sensor network environment such as the presence of typically static nodes and a common destination for the forwarded data. An adaptive probabilistic TSMA-based policy, that is proposed and analyzed in this paper, exploits these idiosyncrasies and achieves higher system throughput than the existing TSMA-based policies without any need for extra control overhead. As it is analytically shown in this paper, the proposed policy always outperforms the existing TSMA-based policies, if certain parameter values are properly set; the analysis also provides for these proper values. It is also shown that the proposed policy is characterized by a certain convergence period and that high system throughput is achieved for long convergence periods. The claims and expectations of the provided analysis are supported by simulation results presented in this paper.

A multiscale modeling approach for biomolecular systems

Energy Technology Data Exchange (ETDEWEB)

Bowling, Alan, E-mail: bowling@uta.edu; Haghshenas-Jaryani, Mahdi, E-mail: mahdi.haghshenasjaryani@mavs.uta.edu [The University of Texas at Arlington, Department of Mechanical and Aerospace Engineering (United States)

2015-04-15

This paper presents a new multiscale molecular dynamic model for investigating the effects of external interactions, such as contact and impact, during stepping and docking of motor proteins and other biomolecular systems. The model retains the mass properties ensuring that the result satisfies Newton’s second law. This idea is presented using a simple particle model to facilitate discussion of the rigid body model; however, the particle model does provide insights into particle dynamics at the nanoscale. The resulting three-dimensional model predicts a significant decrease in the effect of the random forces associated with Brownian motion. This conclusion runs contrary to the widely accepted notion that the motor protein’s movements are primarily the result of thermal effects. This work focuses on the mechanical aspects of protein locomotion; the effect ATP hydrolysis is estimated as internal forces acting on the mechanical model. In addition, the proposed model can be numerically integrated in a reasonable amount of time. Herein, the differences between the motion predicted by the old and new modeling approaches are compared using a simplified model of myosin V.

Applications of atomic force microscopy to the studies of biomaterials in biomolecular systems

Science.gov (United States)

Ma, Xiang

Atomic force microscopy (AFM) is a unique tool for the studies of nanoscale structures and interactions. In this dissertation, I applied AFM to study transitions among multiple states of biomaterials in three different microscopic biomolecular systems: MukB-dependent DNA condensation, holdfast adhesion, and virus elasticity. To elucidate the mechanism of MukB-dependent DNA condensation, I have studied the conformational changes of MukB proteins as indicators for the strength of interactions between MukB, DNA and other molecular factors, such as magnesium and ParC proteins, using high-resolution AFM imaging. To determine the physical origins of holdfast adhesion, I have investigated the dynamics of adhesive force development of the holdfast, employing AFM force spectroscopy. By measuring rupture forces between the holdfast and the substrate, I showed that the holdfast adhesion is strongly time-dependent and involves transformations at multiple time scales. Understanding the mechanisms of adhesion force development of the holdfast will be critical for future engineering of holdfasts properties for various applications. Finally, I have examined the elasticity of self-assembled hepatitis B virus-like particles (HBV VLPs) and brome mosaic virus (BMV) in response to changes of pH and salinity, using AFM nanoindentation. The distributions of elasticity were mapped on a single particle level and compared between empty, RNA- and gold-filled HBV VLPs. I found that a single HBV VLP showed heterogeneous distribution of elasticity and a two-step buckling transition, suggesting a discrete property of HBV capsids. For BMV, I have showed that viruses containing different RNA molecules can be distinguished by mechanical measurements, while they are indistinguishable by morphology. I also studied the effect of pH on the elastic behaviors of three-particle BMV and R3/4 BMV. This study can yield insights into RNA presentation/release mechanisms, and could help us to design novel drug

Efficient traffic grooming with dynamic ONU grouping for multiple-OLT-based access network

Science.gov (United States)

Zhang, Shizong; Gu, Rentao; Ji, Yuefeng; Wang, Hongxiang

2015-12-01

Fast bandwidth growth urges large-scale high-density access scenarios, where the multiple Passive Optical Networking (PON) system clustered deployment can be adopted as an appropriate solution to fulfill the huge bandwidth demands, especially for a future 5G mobile network. However, the lack of interaction between different optical line terminals (OLTs) results in part of the bandwidth resources waste. To increase the bandwidth efficiency, as well as reduce bandwidth pressure at the edge of a network, we propose a centralized flexible PON architecture based on Time- and Wavelength-Division Multiplexing PON (TWDM PON). It can provide flexible affiliation for optical network units (ONUs) and different OLTs to support access network traffic localization. Specifically, a dynamic ONU grouping algorithm (DGA) is provided to obtain the minimal OLT outbound traffic. Simulation results show that DGA obtains an average 25.23% traffic gain increment under different OLT numbers within a small ONU number situation, and the traffic gain will increase dramatically with the increment of the ONU number. As the DGA can be deployed easily as an application running above the centralized control plane, the proposed architecture can be helpful to improve the network efficiency for future traffic-intensive access scenarios.

ADNP-CSMA Random Multiple Access protocol application with the function of monitoring in Ad Hoc network

Directory of Open Access Journals (Sweden)

Zhan Gang

2016-01-01

Full Text Available In Ad Hoc networks,the net work of mobile nodes exchange information with their wireless transceiver equipment,the network throughput is in increased,compared to other such multiple hops network.Moreover along with the rapid development of modern information,communication business also will be increase.However,the access and adaptive of previous CSMA protocol are insufficient.According to these properties,this paper presents a kind of adaptive dual clock with monitoring function P-CSMA random multiple access protocol(ADNP-CSMA,and discusses two kinds of P-CSMA.ACK with monitoring function is introduced to maintain the stability of the whole system,and the introduction of dual clock mechanism reduces the channel of idle period.It calculate the system throughput expression through the method of average period,and the simulation results show that the system is constant in the case of high load throughput.

Unravelling Darwin's entangled bank: architecture and robustness of mutualistic networks with multiple interaction types.

Science.gov (United States)

Dáttilo, Wesley; Lara-Rodríguez, Nubia; Jordano, Pedro; Guimarães, Paulo R; Thompson, John N; Marquis, Robert J; Medeiros, Lucas P; Ortiz-Pulido, Raul; Marcos-García, Maria A; Rico-Gray, Victor

2016-11-30

Trying to unravel Darwin's entangled bank further, we describe the architecture of a network involving multiple forms of mutualism (pollination by animals, seed dispersal by birds and plant protection by ants) and evaluate whether this multi-network shows evidence of a structure that promotes robustness. We found that species differed strongly in their contributions to the organization of the multi-interaction network, and that only a few species contributed to the structuring of these patterns. Moreover, we observed that the multi-interaction networks did not enhance community robustness compared with each of the three independent mutualistic networks when analysed across a range of simulated scenarios of species extinction. By simulating the removal of highly interacting species, we observed that, overall, these species enhance network nestedness and robustness, but decrease modularity. We discuss how the organization of interlinked mutualistic networks may be essential for the maintenance of ecological communities, and therefore the long-term ecological and evolutionary dynamics of interactive, species-rich communities. We suggest that conserving these keystone mutualists and their interactions is crucial to the persistence of species-rich mutualistic assemblages, mainly because they support other species and shape the network organization. © 2016 The Author(s).

Multiple Resting-State Networks Are Associated With Tremors and Cognitive Features in Essential Tremor.

Science.gov (United States)

Fang, Weidong; Chen, Huiyue; Wang, Hansheng; Zhang, Han; Liu, Mengqi; Puneet, Munankami; Lv, Fajin; Cheng, Oumei; Wang, Xuefeng; Lu, Xiurong; Luo, Tianyou

2015-12-01

The heterogeneous clinical features of essential tremor indicate that the dysfunctions of this syndrome are not confined to motor networks, but extend to nonmotor networks. Currently, these neural network dysfunctions in essential tremor remain unclear. In this study, independent component analysis of resting-state functional MRI was used to study these neural network mechanisms. Thirty-five essential tremor patients and 35 matched healthy controls with clinical and neuropsychological tests were included, and eight resting-state networks were identified. After considering the structure and head-motion factors and testing the reliability of the selected resting-state networks, we assessed the functional connectivity changes within or between resting-state networks. Finally, image-behavior correlation analysis was performed. Compared to healthy controls, essential tremor patients displayed increased functional connectivity in the sensorimotor and salience networks and decreased functional connectivity in the cerebellum network. Additionally, increased functional network connectivity was observed between anterior and posterior default mode networks, and a decreased functional network connectivity was noted between the cerebellum network and the sensorimotor and posterior default mode networks. Importantly, the functional connectivity changes within and between these resting-state networks were correlated with the tremor severity and total cognitive scores of essential tremor patients. The findings of this study provide the first evidence that functional connectivity changes within and between multiple resting-state networks are associated with tremors and cognitive features of essential tremor, and this work demonstrates a potential approach for identifying the underlying neural network mechanisms of this syndrome. © 2015 International Parkinson and Movement Disorder Society.

The function of communities in protein interaction networks at multiple scales

Directory of Open Access Journals (Sweden)

Jones Nick S

2010-07-01

Full Text Available Abstract Background If biology is modular then clusters, or communities, of proteins derived using only protein interaction network structure should define protein modules with similar biological roles. We investigate the link between biological modules and network communities in yeast and its relationship to the scale at which we probe the network. Results Our results demonstrate that the functional homogeneity of communities depends on the scale selected, and that almost all proteins lie in a functionally homogeneous community at some scale. We judge functional homogeneity using a novel test and three independent characterizations of protein function, and find a high degree of overlap between these measures. We show that a high mean clustering coefficient of a community can be used to identify those that are functionally homogeneous. By tracing the community membership of a protein through multiple scales we demonstrate how our approach could be useful to biologists focusing on a particular protein. Conclusions We show that there is no one scale of interest in the community structure of the yeast protein interaction network, but we can identify the range of resolution parameters that yield the most functionally coherent communities, and predict which communities are most likely to be functionally homogeneous.

THz time domain spectroscopy of biomolecular conformational modes

International Nuclear Information System (INIS)

Markelz, Andrea; Whitmire, Scott; Hillebrecht, Jay; Birge, Robert

2002-01-01

We discuss the use of terahertz time domain spectroscopy for studies of conformational flexibility and conformational change in biomolecules. Protein structural dynamics are vital to biological function with protein flexibility affecting enzymatic reaction rates and sensory transduction cycling times. Conformational mode dynamics occur on the picosecond timescale and with the collective vibrational modes associated with these large scale structural motions in the 1-100 cm -1 range. We have performed THz time domain spectroscopy (TTDS) of several biomolecular systems to explore the sensitivity of TTDS to distinguish different molecular species, different mutations within a single species and different conformations of a given biomolecule. We compare the measured absorbances to normal mode calculations and find that the TTDS absorbance reflects the density of normal modes determined by molecular mechanics calculations, and is sensitive to both conformation and mutation. These early studies demonstrate some of the advantages and limitations of using TTDS for the study of biomolecules

Network Events on Multiple Space and Time Scales in Cultured Neural Networks and in a Stochastic Rate Model.

Directory of Open Access Journals (Sweden)

Guido Gigante

2015-11-01

Full Text Available Cortical networks, in-vitro as well as in-vivo, can spontaneously generate a variety of collective dynamical events such as network spikes, UP and DOWN states, global oscillations, and avalanches. Though each of them has been variously recognized in previous works as expression of the excitability of the cortical tissue and the associated nonlinear dynamics, a unified picture of the determinant factors (dynamical and architectural is desirable and not yet available. Progress has also been partially hindered by the use of a variety of statistical measures to define the network events of interest. We propose here a common probabilistic definition of network events that, applied to the firing activity of cultured neural networks, highlights the co-occurrence of network spikes, power-law distributed avalanches, and exponentially distributed 'quasi-orbits', which offer a third type of collective behavior. A rate model, including synaptic excitation and inhibition with no imposed topology, synaptic short-term depression, and finite-size noise, accounts for all these different, coexisting phenomena. We find that their emergence is largely regulated by the proximity to an oscillatory instability of the dynamics, where the non-linear excitable behavior leads to a self-amplification of activity fluctuations over a wide range of scales in space and time. In this sense, the cultured network dynamics is compatible with an excitation-inhibition balance corresponding to a slightly sub-critical regime. Finally, we propose and test a method to infer the characteristic time of the fatigue process, from the observed time course of the network's firing rate. Unlike the model, possessing a single fatigue mechanism, the cultured network appears to show multiple time scales, signalling the possible coexistence of different fatigue mechanisms.

Tunable optical frequency comb enabled scalable and cost-effective multiuser orthogonal frequency-division multiple access passive optical network with source-free optical network units.

Science.gov (United States)

Chen, Chen; Zhang, Chongfu; Liu, Deming; Qiu, Kun; Liu, Shuang

2012-10-01

We propose and experimentally demonstrate a multiuser orthogonal frequency-division multiple access passive optical network (OFDMA-PON) with source-free optical network units (ONUs), enabled by tunable optical frequency comb generation technology. By cascading a phase modulator (PM) and an intensity modulator and dynamically controlling the peak-to-peak voltage of a PM driven signal, a tunable optical frequency comb source can be generated. It is utilized to assist the configuration of a multiple source-free ONUs enhanced OFDMA-PON where simultaneous and interference-free multiuser upstream transmission over a single wavelength can be efficiently supported. The proposed multiuser OFDMA-PON is scalable and cost effective, and its feasibility is successfully verified by experiment.

A replica exchange transition interface sampling method with multiple interface sets for investigating networks of rare events

Science.gov (United States)

Swenson, David W. H.; Bolhuis, Peter G.

2014-07-01

The multiple state transition interface sampling (TIS) framework in principle allows the simulation of a large network of complex rare event transitions, but in practice suffers from convergence problems. To improve convergence, we combine multiple state TIS [J. Rogal and P. G. Bolhuis, J. Chem. Phys. 129, 224107 (2008)] with replica exchange TIS [T. S. van Erp, Phys. Rev. Lett. 98, 268301 (2007)]. In addition, we introduce multiple interface sets, which allow more than one order parameter to be defined for each state. We illustrate the methodology on a model system of multiple independent dimers, each with two states. For reaction networks with up to 64 microstates, we determine the kinetics in the microcanonical ensemble, and discuss the convergence properties of the sampling scheme. For this model, we find that the kinetics depend on the instantaneous composition of the system. We explain this dependence in terms of the system's potential and kinetic energy.

A neuromorphic implementation of multiple spike-timing synaptic plasticity rules for large-scale neural networks

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Runchun Mark Wang

2015-05-01

Full Text Available We present a neuromorphic implementation of multiple synaptic plasticity learning rules, which include both Spike Timing Dependent Plasticity (STDP and Spike Timing Dependent Delay Plasticity (STDDP. We present a fully digital implementation as well as a mixed-signal implementation, both of which use a novel dynamic-assignment time-multiplexing approach and support up to 2^26 (64M synaptic plasticity elements. Rather than implementing dedicated synapses for particular types of synaptic plasticity, we implemented a more generic synaptic plasticity adaptor array that is separate from the neurons in the neural network. Each adaptor performs synaptic plasticity according to the arrival times of the pre- and post-synaptic spikes assigned to it, and sends out a weighted and/or delayed pre-synaptic spike to the target synapse in the neural network. This strategy provides great flexibility for building complex large-scale neural networks, as a neural network can be configured for multiple synaptic plasticity rules without changing its structure. We validate the proposed neuromorphic implementations with measurement results and illustrate that the circuits are capable of performing both STDP and STDDP. We argue that it is practical to scale the work presented here up to 2^36 (64G synaptic adaptors on a current high-end FPGA platform.

A System for Acquisition, Processing and Visualization of Image Time Series from Multiple Camera Networks

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Cemal Melih Tanis

2018-06-01

Full Text Available A system for multiple camera networks is proposed for continuous monitoring of ecosystems by processing image time series. The system is built around the Finnish Meteorological Image PROcessing Toolbox (FMIPROT, which includes data acquisition, processing and visualization from multiple camera networks. The toolbox has a user-friendly graphical user interface (GUI for which only minimal computer knowledge and skills are required to use it. Images from camera networks are acquired and handled automatically according to the common communication protocols, e.g., File Transfer Protocol (FTP. Processing features include GUI based selection of the region of interest (ROI, automatic analysis chain, extraction of ROI based indices such as the green fraction index (GF, red fraction index (RF, blue fraction index (BF, green-red vegetation index (GRVI, and green excess (GEI index, as well as a custom index defined by a user-provided mathematical formula. Analysis results are visualized on interactive plots both on the GUI and hypertext markup language (HTML reports. The users can implement their own developed algorithms to extract information from digital image series for any purpose. The toolbox can also be run in non-GUI mode, which allows running series of analyses in servers unattended and scheduled. The system is demonstrated using an environmental camera network in Finland.

A biomolecular recognition approach for the functionalization of cellulose with gold nanoparticles.

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Almeida, A; Rosa, A M M; Azevedo, A M; Prazeres, D M F

2017-09-01

Materials with new and improved functionalities can be obtained by modifying cellulose with gold nanoparticles (AuNPs) via the in situ reduction of a gold precursor or the deposition or covalent immobilization of pre-synthesized AuNPs. Here, we present an alternative biomolecular recognition approach to functionalize cellulose with biotin-AuNPs that relies on a complex of 2 recognition elements: a ZZ-CBM3 fusion that combines a carbohydrate-binding module (CBM) with the ZZ fragment of the staphylococcal protein A and an anti-biotin antibody. Paper and cellulose microparticles with AuNPs immobilized via the ZZ-CBM3:anti-biotin IgG supramolecular complex displayed an intense red color, whereas essentially no color was detected when AuNPs were deposited over the unmodified materials. Scanning electron microscopy analysis revealed a homogeneous distribution of AuNPs when immobilized via ZZ-CBM3:anti-biotin IgG complexes and aggregation of AuNPs when deposited over paper, suggesting that color differences are due to interparticle plasmon coupling effects. The approach could be used to functionalize paper substrates and cellulose nanocrystals with AuNPs. More important, however, is the fact that the occurrence of a biomolecular recognition event between the CBM-immobilized antibody and its specific, AuNP-conjugated antigen is signaled by red color. This opens up the way for the development of simple and straightforward paper/cellulose-based tests where detection of a target analyte can be made by direct use of color signaling. Copyright © 2017 John Wiley & Sons, Ltd.

A study on the multiple dynamic wavelength distribution for gigabit capable passive optical networks

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Gustavo Adolfo Puerto Leguizamón

2014-04-01

Full Text Available This paper presents a data traffic based study aiming at evaluating the impact of dynamic wavelength allocation on a Gigabit capable Passive Optical Network (GPON. In Passive Optical Networks (PON, an Optical Line Terminal (OLT feeds different PONs in such a way that a given wavelength channel is evenly distributed between the Optical Network Units (ONU at each PON. However, PONs do not specify any kind of dynamic behavior on the way the wavelengths are allocated in the network, a completely static distribution is implemented instead. In thispaper we evaluate the network performance in terms of packet losses and throughput for a number of ONUs being out-of-profile while featuring a given percentage of traffic in excess for a fixed wavelength distribution and for multiple dynamic wavelength allocation. Results show that for a multichannel operation with four wavelengths, the network throughput increases up to a rough value of 19% while the packet losses drop from 22 % to 1.8 % as compared with a static wavelength distribution.

Structural networks involved in attention and executive functions in multiple sclerosis

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Sara Llufriu

2017-01-01

Full Text Available Attention and executive deficits are disabling symptoms in multiple sclerosis (MS that have been related to disconnection mechanisms. We aimed to investigate changes in structural connectivity in MS and their association with attention and executive performance applying an improved framework that combines high order probabilistic tractography and anatomical exclusion criteria postprocessing. We compared graph theory metrics of structural networks and fractional anisotropy (FA of white matter (WM connections or edges between 72 MS subjects and 38 healthy volunteers (HV and assessed their correlation with cognition. Patients displayed decreased network transitivity, global efficiency and increased path length compared with HV (p < 0.05, corrected. Also, nodal strength was decreased in 26 of 84 gray matter regions. The distribution of nodes with stronger connections or hubs of the network was similar among groups except for the right pallidum and left insula, which became hubs in patients. MS subjects presented reduced edge FA widespread in the network, while FA was increased in 24 connections (p < 0.05, corrected. Decreased integrity of frontoparietal networks, deep gray nuclei and insula correlated with worse attention and executive performance (r between 0.38 and 0.55, p < 0.05, corrected. Contrarily, higher strength in the right transverse temporal cortex and increased FA of several connections (mainly from cingulate, frontal and occipital cortices were associated with worse functioning (r between −0.40 and −0.47, p < 0.05 corrected. In conclusion, structural brain connectivity is disturbed in MS due to widespread impairment of WM connections and gray matter structures. The increased edge connectivity suggests the presence of reorganization mechanisms at the structural level. Importantly, attention and executive performance relates to frontoparietal networks, deep gray nuclei and insula. These results support the relevance of

Optimal number of coarse-grained sites in different components of large biomolecular complexes.

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Sinitskiy, Anton V; Saunders, Marissa G; Voth, Gregory A

2012-07-26

The computational study of large biomolecular complexes (molecular machines, cytoskeletal filaments, etc.) is a formidable challenge facing computational biophysics and biology. To achieve biologically relevant length and time scales, coarse-grained (CG) models of such complexes usually must be built and employed. One of the important early stages in this approach is to determine an optimal number of CG sites in different constituents of a complex. This work presents a systematic approach to this problem. First, a universal scaling law is derived and numerically corroborated for the intensity of the intrasite (intradomain) thermal fluctuations as a function of the number of CG sites. Second, this result is used for derivation of the criterion for the optimal number of CG sites in different parts of a large multibiomolecule complex. In the zeroth-order approximation, this approach validates the empirical rule of taking one CG site per fixed number of atoms or residues in each biomolecule, previously widely used for smaller systems (e.g., individual biomolecules). The first-order corrections to this rule are derived and numerically checked by the case studies of the Escherichia coli ribosome and Arp2/3 actin filament junction. In different ribosomal proteins, the optimal number of amino acids per CG site is shown to differ by a factor of 3.5, and an even wider spread may exist in other large biomolecular complexes. Therefore, the method proposed in this paper is valuable for the optimal construction of CG models of such complexes.

Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach.

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Chandrasekar, A; Rakkiyappan, R; Cao, Jinde

2015-10-01

This paper studies the impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. The array of neural networks are coupled in a random fashion which is governed by Bernoulli random variable. The aim of this paper is to obtain the synchronization criteria, which is suitable for both exactly known and partly unknown transition probabilities such that the coupled neural network is synchronized with mixed time-delay. The considered impulsive effects can be synchronized at partly unknown transition probabilities. Besides, a multiple integral approach is also proposed to strengthen the Markovian jumping randomly coupled neural networks with partly unknown transition probabilities. By making use of Kronecker product and some useful integral inequalities, a novel Lyapunov-Krasovskii functional was designed for handling the coupled neural network with mixed delay and then impulsive synchronization criteria are solvable in a set of linear matrix inequalities. Finally, numerical examples are presented to illustrate the effectiveness and advantages of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Investigation of the Human Disease Osteogenesis Imperfecta: A Research-Based Introduction to Concepts and Skills in Biomolecular Analysis

Science.gov (United States)

Mate, Karen; Sim, Alistair; Weidenhofer, Judith; Milward, Liz; Scott, Judith

2013-01-01

A blended approach encompassing problem-based learning (PBL) and structured inquiry was used in this laboratory exercise based on the congenital disease Osteogenesis imperfecta (OI), to introduce commonly used techniques in biomolecular analysis within a clinical context. During a series of PBL sessions students were presented with several…

Optimal power allocation of a single transmitter-multiple receivers channel in a cognitive sensor network

KAUST Repository

Ayala Solares, Jose Roberto; Rezki, Zouheir; Alouini, Mohamed-Slim

2012-01-01

The optimal transmit power of a wireless sensor network with one transmitter and multiple receivers in a cognitive radio environment while satisfying independent peak, independent average, sum of peak and sum of average transmission rate constraints

A Systematic Scheme for Multiple Access in Ethernet Passive Optical Access Networks

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Ma, Maode; Zhu, Yongqing; Hiang Cheng, Tee

2005-11-01

While backbone networks have experienced substantial changes in the last decade, access networks have not changed much. Recently, passive optical networks (PONs) seem to be ready for commercial deployment as access networks, due to the maturity of a number of enabling technologies. Among the PON technologies, Ethernet PON (EPON) standardized by the IEEE 802.3ah Ethernet in the First Mile (EFM) Task Force is the most attractive one because of its high speed, low cost, familiarity, interoperability, and low overhead. In this paper, we consider the issue of upstream channel sharing in the EPONs. We propose a novel multiple-access control scheme to provide bandwidth-guaranteed service for high-demand customers, while providing best effort service to low-demand customers according to the service level agreement (SLA). The analytical and simulation results prove that the proposed scheme performs best in what it is designed to do compared to another well-known scheme that has not considered providing differentiated services. With business customers preferring premium services with guaranteed bandwidth and residential users preferring low-cost best effort services, our scheme could benefit both groups of subscribers, as well as the operators.

Electro-optical time gating based on Mach-Zehnder modulator for multiple access interference elimination in optical code-division multiple access networks

Science.gov (United States)

Chen, Yinfang; Wang, Rong; Fang, Tao; Pu, Tao; Xiang, Peng; Zheng, Jilin; Zhu, Huatao

2014-05-01

An electro-optical time gating technique, which is based on an electrical return-to-zero (RZ) pulse driven Mach-Zehnder modulator (MZM) for eliminating multiple access interference (MAI) in optical code-division multiple access (OCDMA) networks is proposed. This technique is successfully simulated in an eight-user two-dimensional wavelength-hopping time-spreading system, as well as in a three-user temporal phase encoding system. Results show that in both systems the MAI noise is efficiently removed and the average received power penalty improved. Both achieve error-free transmissions at a bit rate of 2.5 Gb/s. In addition, we also individually discuss effects of parameters in two systems, such as the extinction ratio of the MZM, the duty cycle of the driven RZ pulse, and the time misalignment between the driven pulse and the decoded autocorrelation peak, on the output bit error rate performance. Our work shows that employing a common MZM as a thresholder provides another probability and an interesting cost-effective choice for a smart size, low energy, and less complex thresholding technique for integrated detection in OCDMA networks.

Use of multiple dispersal pathways facilitates amphibian persistence in stream networks

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Campbell, Grant E.H.; Nichols, J.D.; Lowe, W.H.; Fagan, W.F.

2010-01-01

Although populations of amphibians are declining worldwide, there is no evidence that salamanders occupying small streams are experiencing enigmatic declines, and populations of these species seem stable. Theory predicts that dispersal through multiple pathways can stabilize populations, preventing extinction in habitat networks. However, empirical data to support this prediction are absent for most species, especially those at risk of decline. Our mark-recapture study of stream salamanders reveals both a strong upstream bias in dispersal and a surprisingly high rate of overland dispersal to adjacent headwater streams. This evidence of route-dependent variation in dispersal rates suggests a spatial mechanism for population stability in headwater-stream salamanders. Our results link the movement behavior of stream salamanders to network topology, and they underscore the importance of identifying and protecting critical dispersal pathways when addressing region-wide population declines.

Use of multiple dispersal pathways facilitates amphibian persistence in stream networks.

Science.gov (United States)

Campbell Grant, Evan H; Nichols, James D; Lowe, Winsor H; Fagan, William F

2010-04-13

Although populations of amphibians are declining worldwide, there is no evidence that salamanders occupying small streams are experiencing enigmatic declines, and populations of these species seem stable. Theory predicts that dispersal through multiple pathways can stabilize populations, preventing extinction in habitat networks. However, empirical data to support this prediction are absent for most species, especially those at risk of decline. Our mark-recapture study of stream salamanders reveals both a strong upstream bias in dispersal and a surprisingly high rate of overland dispersal to adjacent headwater streams. This evidence of route-dependent variation in dispersal rates suggests a spatial mechanism for population stability in headwater-stream salamanders. Our results link the movement behavior of stream salamanders to network topology, and they underscore the importance of identifying and protecting critical dispersal pathways when addressing region-wide population declines.

A space weather forecasting system with multiple satellites based on a self-recognizing network.

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Tokumitsu, Masahiro; Ishida, Yoshiteru

2014-05-05

This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

Sequential interrogation of multiple FBG sensors using LPG modulation and an artificial neural network

International Nuclear Information System (INIS)

Basu, Mainak; Ghorai, S K

2015-01-01

Interrogating multiple fiber Bragg gratings (FBG) requires highly sensitive spectrum scanning equipment such as optical spectrum analyzers, tunable filters, acousto-optic tunable filters etc, which are expensive, bulky and time consuming. In this paper, we present a new approach for multiple FBG sensor interrogation using long-period gratings and an artificial neural network. The reflection spectra of the multiplexed FBGs are modulated by two long period gratings separately and the modulated optical intensities were detected by two photodetectors. The outputs of the detectors are then used as input in a previously trained artificial neural network to interrogate the FBG sensors. Simulations have been performed to determine the strain and wavelength shift using two and four sensors. The interrogation system has also been demonstrated experimentally for two sensors using simply supported beams in the range of 0–350 μstrain. The proposed interrogation scheme has been found to identify the perturbed FBG, and to determine strain and wavelength shift with reasonable accuracy. (paper)

A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network

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Masahiro Tokumitsu

2014-05-01

Full Text Available This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV. The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

Poisson-Nernst-Planck Equations for Simulating Biomolecular Diffusion-Reaction Processes I: Finite Element Solutions.

Science.gov (United States)

Lu, Benzhuo; Holst, Michael J; McCammon, J Andrew; Zhou, Y C

2010-09-20

In this paper we developed accurate finite element methods for solving 3-D Poisson-Nernst-Planck (PNP) equations with singular permanent charges for electrodiffusion in solvated biomolecular systems. The electrostatic Poisson equation was defined in the biomolecules and in the solvent, while the Nernst-Planck equation was defined only in the solvent. We applied a stable regularization scheme to remove the singular component of the electrostatic potential induced by the permanent charges inside biomolecules, and formulated regular, well-posed PNP equations. An inexact-Newton method was used to solve the coupled nonlinear elliptic equations for the steady problems; while an Adams-Bashforth-Crank-Nicolson method was devised for time integration for the unsteady electrodiffusion. We numerically investigated the conditioning of the stiffness matrices for the finite element approximations of the two formulations of the Nernst-Planck equation, and theoretically proved that the transformed formulation is always associated with an ill-conditioned stiffness matrix. We also studied the electroneutrality of the solution and its relation with the boundary conditions on the molecular surface, and concluded that a large net charge concentration is always present near the molecular surface due to the presence of multiple species of charged particles in the solution. The numerical methods are shown to be accurate and stable by various test problems, and are applicable to real large-scale biophysical electrodiffusion problems.

Multiscale virtual particle based elastic network model (MVP-ENM) for normal mode analysis of large-sized biomolecules.

Science.gov (United States)

Xia, Kelin

2017-12-20

In this paper, a multiscale virtual particle based elastic network model (MVP-ENM) is proposed for the normal mode analysis of large-sized biomolecules. The multiscale virtual particle (MVP) model is proposed for the discretization of biomolecular density data. With this model, large-sized biomolecular structures can be coarse-grained into virtual particles such that a balance between model accuracy and computational cost can be achieved. An elastic network is constructed by assuming "connections" between virtual particles. The connection is described by a special harmonic potential function, which considers the influence from both the mass distributions and distance relations of the virtual particles. Two independent models, i.e., the multiscale virtual particle based Gaussian network model (MVP-GNM) and the multiscale virtual particle based anisotropic network model (MVP-ANM), are proposed. It has been found that in the Debye-Waller factor (B-factor) prediction, the results from our MVP-GNM with a high resolution are as good as the ones from GNM. Even with low resolutions, our MVP-GNM can still capture the global behavior of the B-factor very well with mismatches predominantly from the regions with large B-factor values. Further, it has been demonstrated that the low-frequency eigenmodes from our MVP-ANM are highly consistent with the ones from ANM even with very low resolutions and a coarse grid. Finally, the great advantage of MVP-ANM model for large-sized biomolecules has been demonstrated by using two poliovirus virus structures. The paper ends with a conclusion.

LARGE-SCALE TOPOLOGICAL PROPERTIES OF MOLECULAR NETWORKS.

Energy Technology Data Exchange (ETDEWEB)

MASLOV,S.SNEPPEN,K.

2003-11-17

Bio-molecular networks lack the top-down design. Instead, selective forces of biological evolution shape them from raw material provided by random events such as gene duplications and single gene mutations. As a result individual connections in these networks are characterized by a large degree of randomness. One may wonder which connectivity patterns are indeed random, while which arose due to the network growth, evolution, and/or its fundamental design principles and limitations? Here we introduce a general method allowing one to construct a random null-model version of a given network while preserving the desired set of its low-level topological features, such as, e.g., the number of neighbors of individual nodes, the average level of modularity, preferential connections between particular groups of nodes, etc. Such a null-model network can then be used to detect and quantify the non-random topological patterns present in large networks. In particular, we measured correlations between degrees of interacting nodes in protein interaction and regulatory networks in yeast. It was found that in both these networks, links between highly connected proteins are systematically suppressed. This effect decreases the likelihood of cross-talk between different functional modules of the cell, and increases the overall robustness of a network by localizing effects of deleterious perturbations. It also teaches us about the overall computational architecture of such networks and points at the origin of large differences in the number of neighbors of individual nodes.

Parity Violation in Chiral Molecules: From Theory towards Spectroscopic Experiment and the Evolution of Biomolecular Homochirality

CERN Multimedia

CERN. Geneva

2016-01-01

The observation of biomolecular homochirality can be considered as a quasi-fossil of the evolution of life [1], the interpretation of which has been an open question for more than a century, with numerous related hypotheses, but no definitive answers. We shall briefly discuss the current status and the relation to the other two questions. The discovery of parity violation led to important developm...

A developmental systems perspective on epistasis: computational exploration of mutational interactions in model developmental regulatory networks.

Directory of Open Access Journals (Sweden)

Jayson Gutiérrez

2009-09-01

Full Text Available The way in which the information contained in genotypes is translated into complex phenotypic traits (i.e. embryonic expression patterns depends on its decoding by a multilayered hierarchy of biomolecular systems (regulatory networks. Each layer of this hierarchy displays its own regulatory schemes (i.e. operational rules such as +/- feedback and associated control parameters, resulting in characteristic variational constraints. This process can be conceptualized as a mapping issue, and in the context of highly-dimensional genotype-phenotype mappings (GPMs epistatic events have been shown to be ubiquitous, manifested in non-linear correspondences between changes in the genotype and their phenotypic effects. In this study I concentrate on epistatic phenomena pervading levels of biological organization above the genetic material, more specifically the realm of molecular networks. At this level, systems approaches to studying GPMs are specially suitable to shed light on the mechanistic basis of epistatic phenomena. To this aim, I constructed and analyzed ensembles of highly-modular (fully interconnected networks with distinctive topologies, each displaying dynamic behaviors that were categorized as either arbitrary or functional according to early patterning processes in the Drosophila embryo. Spatio-temporal expression trajectories in virtual syncytial embryos were simulated via reaction-diffusion models. My in silico mutational experiments show that: 1 the average fitness decay tendency to successively accumulated mutations in ensembles of functional networks indicates the prevalence of positive epistasis, whereas in ensembles of arbitrary networks negative epistasis is the dominant tendency; and 2 the evaluation of epistatic coefficients of diverse interaction orders indicates that, both positive and negative epistasis are more prevalent in functional networks than in arbitrary ones. Overall, I conclude that the phenotypic and fitness effects of

Prediction Approach of Critical Node Based on Multiple Attribute Decision Making for Opportunistic Sensor Networks

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Qifan Chen

2016-01-01

Full Text Available Predicting critical nodes of Opportunistic Sensor Network (OSN can help us not only to improve network performance but also to decrease the cost in network maintenance. However, existing ways of predicting critical nodes in static network are not suitable for OSN. In this paper, the conceptions of critical nodes, region contribution, and cut-vertex in multiregion OSN are defined. We propose an approach to predict critical node for OSN, which is based on multiple attribute decision making (MADM. It takes RC to present the dependence of regions on Ferry nodes. TOPSIS algorithm is employed to find out Ferry node with maximum comprehensive contribution, which is a critical node. The experimental results show that, in different scenarios, this approach can predict the critical nodes of OSN better.

Autapse-induced multiple stochastic resonances in a modular neuronal network

Science.gov (United States)

Yang, XiaoLi; Yu, YanHu; Sun, ZhongKui

2017-08-01

This study investigates the nontrivial effects of autapse on stochastic resonance in a modular neuronal network subjected to bounded noise. The resonance effect of autapse is detected by imposing a self-feedback loop with autaptic strength and autaptic time delay to each constituent neuron. Numerical simulations have demonstrated that bounded noise with the proper level of amplitude can induce stochastic resonance; moreover, the noise induced resonance dynamics can be significantly shaped by the autapse. In detail, for a specific range of autaptic strength, multiple stochastic resonances can be induced when the autaptic time delays are appropriately adjusted. These appropriately adjusted delays are detected to nearly approach integer multiples of the period of the external weak signal when the autaptic strength is very near zero; otherwise, they do not match the period of the external weak signal when the autaptic strength is slightly greater than zero. Surprisingly, in both cases, the differences between arbitrary two adjacent adjusted autaptic delays are always approximately equal to the period of the weak signal. The phenomenon of autaptic delay induced multiple stochastic resonances is further confirmed to be robust against the period of the external weak signal and the intramodule probability of subnetwork. These findings could have important implications for weak signal detection and information propagation in realistic neural systems.

A Suboptimal Power-Saving Transmission Scheme in Multiple Component Carrier Networks

Science.gov (United States)

Chung, Yao-Liang; Tsai, Zsehong

Power consumption due to transmissions in base stations (BSs) has been a major contributor to communication-related CO2 emissions. A power optimization model is developed in this study with respect to radio resource allocation and activation in a multiple Component Carrier (CC) environment. We formulate and solve the power-minimization problem of the BS transceivers for multiple-CC networks with carrier aggregation, while maintaining the overall system and respective users' utilities above minimum levels. The optimized power consumption based on this model can be viewed as a lower bound of that of other algorithms employed in practice. A suboptimal scheme with low computation complexity is proposed. Numerical results show that the power consumption of our scheme is much better than that of the conventional one in which all CCs are always active, if both schemes maintain the same required utilities.

Distributed Containment Control for Multiple Unknown Second-Order Nonlinear Systems With Application to Networked Lagrangian Systems.

Science.gov (United States)

Mei, Jie; Ren, Wei; Li, Bing; Ma, Guangfu

2015-09-01

In this paper, we consider the distributed containment control problem for multiagent systems with unknown nonlinear dynamics. More specifically, we focus on multiple second-order nonlinear systems and networked Lagrangian systems. We first study the distributed containment control problem for multiple second-order nonlinear systems with multiple dynamic leaders in the presence of unknown nonlinearities and external disturbances under a general directed graph that characterizes the interaction among the leaders and the followers. A distributed adaptive control algorithm with an adaptive gain design based on the approximation capability of neural networks is proposed. We present a necessary and sufficient condition on the directed graph such that the containment error can be reduced as small as desired. As a byproduct, the leaderless consensus problem is solved with asymptotical convergence. Because relative velocity measurements between neighbors are generally more difficult to obtain than relative position measurements, we then propose a distributed containment control algorithm without using neighbors' velocity information. A two-step Lyapunov-based method is used to study the convergence of the closed-loop system. Next, we apply the ideas to deal with the containment control problem for networked unknown Lagrangian systems under a general directed graph. All the proposed algorithms are distributed and can be implemented using only local measurements in the absence of communication. Finally, simulation examples are provided to show the effectiveness of the proposed control algorithms.

A Neural Network Model to Learn Multiple Tasks under Dynamic Environments

Science.gov (United States)

Tsumori, Kenji; Ozawa, Seiichi

When environments are dynamically changed for agents, the knowledge acquired in an environment might be useless in future. In such dynamic environments, agents should be able to not only acquire new knowledge but also modify old knowledge in learning. However, modifying all knowledge acquired before is not efficient because the knowledge once acquired may be useful again when similar environment reappears and some knowledge can be shared among different environments. To learn efficiently in such environments, we propose a neural network model that consists of the following modules: resource allocating network, long-term & short-term memory, and environment change detector. We evaluate the model under a class of dynamic environments where multiple function approximation tasks are sequentially given. The experimental results demonstrate that the proposed model possesses stable incremental learning, accurate environmental change detection, proper association and recall of old knowledge, and efficient knowledge transfer.

Foreword [IJEGMBE 2015: India-Japan expert group meeting on biomolecular electronics and organic nanotechnology for environment preservation, Fukuoka (Japan), 23-26 December 2015

International Nuclear Information System (INIS)

2016-01-01

There is increased interest in organic nanotechnology and biomolecular electronics for environmental preservation, and in their anticipated impact on the economics of both the developing and the developed world. Keeping this in mind, the Department of Biological Functions, Graduate School of Life Sciences and Systems Engineering, Kyushu Institute of Technology (KIT), Kitakyushu, Japan, and the Department of Science and Technology Centre on Biomolecular Electronics (DSTCBE), National Physical Laboratory (NPL) jointly organized the India-Japan Workshop on Biomolecular Electronics and Organic Nanotechnology for Environmental Preservation (IJWBME 2009) at NPL, New Delhi from 17 th - 19 th December 2009, IJWBME 2011 at EGRET Himeji, Himeji, from 7 th - 10 th December, Japan, and IJWBME 2013 at Delhi Technological University, New Delhi, from 13 th - 15 th December. The India-Japan Expert Group Meeting on Biomolecular Electronics and Organic Nanotechnology for Environment Preservation (IJEGMBE) will be held from 22 th – 25 th , December, 2015, at Nakamura Centenary Memorial Hall, Kyushu Institute of Technology, Kitakyushu, Japan in association with Delhi Technological University, Delhi, India. Recent years have seen rapid growth in the area of Biomolecular Electronics involving the association and expertise of physicists, biologists, chemists, electronics engineers and information technologists. There is increasing interest in the development of nanotechnology and biomolecular electronic devices for the preservation of our precious environment. In this context, the world of the electronics, which developed on Si semiconductors, is going to change drastically. A paradigm shift towards organic or printed electronics is more likely in the future. The field of organic electronics promises exciting new technologies based on inexpensive and mechanically flexible electronic devices, and is now starting to see commercial success. On the sidelines of this increasingly well

Constraints on signaling network logic reveal functional subgraphs on Multiple Myeloma OMIC data.

Science.gov (United States)

Miannay, Bertrand; Minvielle, Stéphane; Magrangeas, Florence; Guziolowski, Carito

2018-03-21

The integration of gene expression profiles (GEPs) and large-scale biological networks derived from pathways databases is a subject which is being widely explored. Existing methods are based on network distance measures among significantly measured species. Only a small number of them include the directionality and underlying logic existing in biological networks. In this study we approach the GEP-networks integration problem by considering the network logic, however our approach does not require a prior species selection according to their gene expression level. We start by modeling the biological network representing its underlying logic using Logic Programming. This model points to reachable network discrete states that maximize a notion of harmony between the molecular species active or inactive possible states and the directionality of the pathways reactions according to their activator or inhibitor control role. Only then, we confront these network states with the GEP. From this confrontation independent graph components are derived, each of them related to a fixed and optimal assignment of active or inactive states. These components allow us to decompose a large-scale network into subgraphs and their molecular species state assignments have different degrees of similarity when compared to the same GEP. We apply our method to study the set of possible states derived from a subgraph from the NCI-PID Pathway Interaction Database. This graph links Multiple Myeloma (MM) genes to known receptors for this blood cancer. We discover that the NCI-PID MM graph had 15 independent components, and when confronted to 611 MM GEPs, we find 1 component as being more specific to represent the difference between cancer and healthy profiles.

Report from the European myeloma network on interphase FISH in multiple myeloma and related disorders

NARCIS (Netherlands)

F. Ross (F.); H. Avet-Loiseau; G. Ameye (Geneviève); N. Gutierrez (Norma); G. Liebisch (Gerhard); S. O'Connor (Sheila); K. Dalva (Klara); F. Fabris (Federica Margherita); A.M. Testi (Adele); M. Jarosova (M.); C. Hodkinson (Clare); A. Collin (Anna); G. Kerndrup (Gitte); P. Kuglik (Petr); D. Ladon (Dariusz); P. Bernasconi (Paolo); B. Maes (Bart); Z. Zemanova (Zuzana); K. Michalova (Kyra); L. Michau (Lucienne); K. Neben (Kai); N.E.U. Hermansen (N. Emil); K. Rack (Katrina); A. Rocci (Alberto); R. Protheroe (Rebecca); L. Chiecchio (Laura); H.A. Poirel (Hélène A); P. Sonneveld (Pieter); M. Nyegaard (M.); H.E. Johnsen (Hans)

2012-01-01

textabstractThe European Myeloma Network has organized two workshops on fluorescence in situ hybridization in multiple myeloma. The first aimed to identify specific indications and consensus technical approaches of current practice. A second workshop followed a quality control exercise in which 21

Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

Directory of Open Access Journals (Sweden)

Recep Colak

2010-10-01

Full Text Available Computational prediction of functionally related groups of genes (functional modules from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented.We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB, by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples.We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely

Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

Science.gov (United States)

Colak, Recep; Moser, Flavia; Chu, Jeffrey Shih-Chieh; Schönhuth, Alexander; Chen, Nansheng; Ester, Martin

2010-10-25

Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense) regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented. We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB), by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples. We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely available large

Multiple network interface core apparatus and method

Science.gov (United States)

Underwood, Keith D [Albuquerque, NM; Hemmert, Karl Scott [Albuquerque, NM

2011-04-26

A network interface controller and network interface control method comprising providing a single integrated circuit as a network interface controller and employing a plurality of network interface cores on the single integrated circuit.

Securing optical code-division multiple-access networks with a postswitching coding scheme of signature reconfiguration

Science.gov (United States)

Huang, Jen-Fa; Meng, Sheng-Hui; Lin, Ying-Chen

2014-11-01

The optical code-division multiple-access (OCDMA) technique is considered a good candidate for providing optical layer security. An enhanced OCDMA network security mechanism with a pseudonoise (PN) random digital signals type of maximal-length sequence (M-sequence) code switching to protect against eavesdropping is presented. Signature codes unique to individual OCDMA-network users are reconfigured according to the register state of the controlling electrical shift registers. Examples of signature reconfiguration following state switching of the controlling shift register for both the network user and the eavesdropper are numerically illustrated. Dynamically changing the PN state of the shift register to reconfigure the user signature sequence is shown; this hinders eavesdroppers' efforts to decode correct data sequences. The proposed scheme increases the probability of eavesdroppers committing errors in decoding and thereby substantially enhances the degree of an OCDMA network's confidentiality.

Networking Multiple Autonomous Air and Ocean Vehicles for Oceanographic Research and Monitoring

Science.gov (United States)

McGillivary, P. A.; Borges de Sousa, J.; Rajan, K.

2013-12-01

Autonomous underwater and surface vessels (AUVs and ASVs) are coming into wider use as components of oceanographic research, including ocean observing systems. Unmanned airborne vehicles (UAVs) are now available at modest cost, allowing multiple UAVs to be deployed with multiple AUVs and ASVs. For optimal use good communication and coordination among vehicles is essential. We report on the use of multiple AUVs networked in communication with multiple UAVs. The UAVs are augmented by inferential reasoning software developed at MBARI that allows UAVs to recognize oceanographic fronts and change their navigation and control. This in turn allows UAVs to automatically to map frontal features, as well as to direct AUVs and ASVs to proceed to such features and conduct sampling via onboard sensors to provide validation for airborne mapping. ASVs can also act as data nodes for communication between UAVs and AUVs, as well as collecting data from onboard sensors, while AUVs can sample the water column vertically. This allows more accurate estimation of phytoplankton biomass and productivity, and can be used in conjunction with UAV sampling to determine air-sea flux of gases (e.g. CO2, CH4, DMS) affecting carbon budgets and atmospheric composition. In particular we describe tests in July 2013 conducted off Sesimbra, Portugal in conjunction with the Portuguese Navy by the University of Porto and MBARI with the goal of tracking large fish in the upper water column with coordinated air/surface/underwater measurements. A thermal gradient was observed in the infrared by a low flying UAV, which was used to dispatch an AUV to obtain ground truth to demonstrate the event-response capabilities using such autonomous platforms. Additional field studies in the future will facilitate integration of multiple unmanned systems into research vessel operations. The strength of hardware and software tools described in this study is to permit fundamental oceanographic measurements of both ocean

Dose controlled low energy electron irradiator for biomolecular films.

Science.gov (United States)

Kumar, S V K; Tare, Satej T; Upalekar, Yogesh V; Tsering, Thupten

2016-03-01

We have developed a multi target, Low Energy Electron (LEE), precise dose controlled irradiator for biomolecular films. Up to seven samples can be irradiated one after another at any preset electron energy and dose under UHV conditions without venting the chamber. In addition, one more sample goes through all the steps except irradiation, which can be used as control for comparison with the irradiated samples. All the samples are protected against stray electron irradiation by biasing them at -20 V during the entire period, except during irradiation. Ethernet based communication electronics hardware, LEE beam control electronics and computer interface were developed in house. The user Graphical User Interface to control the irradiation and dose measurement was developed using National Instruments Lab Windows CVI. The working and reliability of the dose controlled irradiator has been fully tested over the electron energy range of 0.5 to 500 eV by studying LEE induced single strand breaks to ΦX174 RF1 dsDNA.

DNA-assisted swarm control in a biomolecular motor system.

Science.gov (United States)

Keya, Jakia Jannat; Suzuki, Ryuhei; Kabir, Arif Md Rashedul; Inoue, Daisuke; Asanuma, Hiroyuki; Sada, Kazuki; Hess, Henry; Kuzuya, Akinori; Kakugo, Akira

2018-01-31

In nature, swarming behavior has evolved repeatedly among motile organisms because it confers a variety of beneficial emergent properties. These include improved information gathering, protection from predators, and resource utilization. Some organisms, e.g., locusts, switch between solitary and swarm behavior in response to external stimuli. Aspects of swarming behavior have been demonstrated for motile supramolecular systems composed of biomolecular motors and cytoskeletal filaments, where cross-linkers induce large scale organization. The capabilities of such supramolecular systems may be further extended if the swarming behavior can be programmed and controlled. Here, we demonstrate that the swarming of DNA-functionalized microtubules (MTs) propelled by surface-adhered kinesin motors can be programmed and reversibly regulated by DNA signals. Emergent swarm behavior, such as translational and circular motion, can be selected by tuning the MT stiffness. Photoresponsive DNA containing azobenzene groups enables switching between solitary and swarm behavior in response to stimulation with visible or ultraviolet light.

Dose controlled low energy electron irradiator for biomolecular films

Energy Technology Data Exchange (ETDEWEB)

Kumar, S. V. K., E-mail: svkk@tifr.res.in; Tare, Satej T.; Upalekar, Yogesh V.; Tsering, Thupten [Tata Institute of Fundamental Research, Homi Bhabha Road, Colaba, Mumbai 400 005 (India)

2016-03-15

We have developed a multi target, Low Energy Electron (LEE), precise dose controlled irradiator for biomolecular films. Up to seven samples can be irradiated one after another at any preset electron energy and dose under UHV conditions without venting the chamber. In addition, one more sample goes through all the steps except irradiation, which can be used as control for comparison with the irradiated samples. All the samples are protected against stray electron irradiation by biasing them at −20 V during the entire period, except during irradiation. Ethernet based communication electronics hardware, LEE beam control electronics and computer interface were developed in house. The user Graphical User Interface to control the irradiation and dose measurement was developed using National Instruments Lab Windows CVI. The working and reliability of the dose controlled irradiator has been fully tested over the electron energy range of 0.5 to 500 eV by studying LEE induced single strand breaks to ΦX174 RF1 dsDNA.

Ultrafast all-optical code-division multiple-access networks

Science.gov (United States)

Kwong, Wing C.; Prucnal, Paul R.; Liu, Yanming

1992-12-01

In optical code-division multiple access (CDMA), the architecture of optical encoders/decoders is another important factor that needs to be considered, besides the correlation properties of those already extensively studied optical codes. The architecture of optical encoders/decoders affects, for example, the amount of power loss and length of optical delays that are associated with code sequence generation and correlation, which, in turn, affect the power budget, size, and cost of an optical CDMA system. Various CDMA coding architectures are studied in the paper. In contrast to the encoders/decoders used in prime networks (i.e., prime encodes/decoders), which generate, select, and correlate code sequences by a parallel combination of fiber-optic delay-lines, and in 2n networks (i.e., 2n encoders/decoders), which generate and correlate code sequences by a serial combination of 2 X 2 passive couplers and fiber delays with sequence selection performed in a parallel fashion, the modified 2n encoders/decoders generate, select, and correlate code sequences by a serial combination of directional couplers and delays. The power and delay- length requirements of the modified 2n encoders/decoders are compared to that of the prime and 2n encoders/decoders. A 100 Mbit/s optical CDMA experiment in free space demonstrating the feasibility of the all-serial coding architecture using a serial combination of 50/50 beam splitters and retroreflectors at 10 Tchip/s (i.e., 100,000 chip/bit) with 100 fs laser pulses is reported.

Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks.

Science.gov (United States)

Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S

2017-08-03

Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a = ( u , v ) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages.

Stable isotope applications in biomolecular structure and mechanisms. A meeting to bring together producers and users of stable-isotope-labeled compounds to assess current and future needs

International Nuclear Information System (INIS)

Trewhella, J.; Cross, T.A.; Unkefer, C.J.

1994-12-01

Knowledge of biomolecular structure is a prerequisite for understanding biomolecular function, and stable isotopes play an increasingly important role in structure determination of biological molecules. The first Conference on Stable Isotope Applications in Biomolecular Structure and Mechanisms was held in Santa Fe, New Mexico, March 27--31, 1994. More than 120 participants from 8 countries and 44 institutions reviewed significant developments, discussed the most promising applications for stable isotopes, and addressed future needs and challenges. Participants focused on applications of stable isotopes for studies of the structure and function of proteins, peptides, RNA, and DNA. Recent advances in NMR techniques neutron scattering, EPR, and vibrational spectroscopy were highlighted in addition to the production and synthesis of labeled compounds. This volume includes invited speaker and poster presentations as well as a set of reports from discussion panels that focused on the needs of the scientific community and the potential roles of private industry, the National Stable Isotope Resource, and the National High Magnetic Field Laboratory in serving those needs. This is the leading abstract. Individual papers are processed separately for the database

Stable isotope applications in biomolecular structure and mechanisms. A meeting to bring together producers and users of stable-isotope-labeled compounds to assess current and future needs

Energy Technology Data Exchange (ETDEWEB)

Trewhella, J.; Cross, T.A.; Unkefer, C.J. [eds.

1994-12-01

Knowledge of biomolecular structure is a prerequisite for understanding biomolecular function, and stable isotopes play an increasingly important role in structure determination of biological molecules. The first Conference on Stable Isotope Applications in Biomolecular Structure and Mechanisms was held in Santa Fe, New Mexico, March 27--31, 1994. More than 120 participants from 8 countries and 44 institutions reviewed significant developments, discussed the most promising applications for stable isotopes, and addressed future needs and challenges. Participants focused on applications of stable isotopes for studies of the structure and function of proteins, peptides, RNA, and DNA. Recent advances in NMR techniques neutron scattering, EPR, and vibrational spectroscopy were highlighted in addition to the production and synthesis of labeled compounds. This volume includes invited speaker and poster presentations as well as a set of reports from discussion panels that focused on the needs of the scientific community and the potential roles of private industry, the National Stable Isotope Resource, and the National High Magnetic Field Laboratory in serving those needs. This is the leading abstract. Individual papers are processed separately for the database.

Estimating Single and Multiple Target Locations Using K-Means Clustering with Radio Tomographic Imaging in Wireless Sensor Networks

Science.gov (United States)

2015-03-26

clustering is an algorithm that has been used in data mining applications such as machine learning applications , pattern recognition, hyper-spectral imagery...42 3.7.2 Application of K-means Clustering . . . . . . . . . . . . . . . . . 42 3.8 Experiment Design...Tomographic Imaging WLAN Wireless Local Area Networks WSN Wireless Sensor Network xx ESTIMATING SINGLE AND MULTIPLE TARGET LOCATIONS USING K-MEANS CLUSTERING

The use of gold nanoparticle aggregation for DNA computing and logic-based biomolecular detection

International Nuclear Information System (INIS)

Lee, In-Hee; Yang, Kyung-Ae; Zhang, Byoung-Tak; Lee, Ji-Hoon; Park, Ji-Yoon; Chai, Young Gyu; Lee, Jae-Hoon

2008-01-01

The use of DNA molecules as a physical computational material has attracted much interest, especially in the area of DNA computing. DNAs are also useful for logical control and analysis of biological systems if efficient visualization methods are available. Here we present a quick and simple visualization technique that displays the results of the DNA computing process based on a colorimetric change induced by gold nanoparticle aggregation, and we apply it to the logic-based detection of biomolecules. Our results demonstrate its effectiveness in both DNA-based logical computation and logic-based biomolecular detection

Conformation of bovine submaxillary mucin layers on hydrophobic surface as studied by biomolecular probes

DEFF Research Database (Denmark)

Pakkanen, Kirsi I.; Madsen, Jan Busk; Lee, Seunghwan

2015-01-01

In the present study, the conformational changes of bovine submaxillary mucin (BSM) adsorbed on a hydrophobic surface (polystyrene (PS)) as a function of concentration in bulk solution (up to 2mg/mL) have been investigated with biomolecular probe-based approaches, including bicinchoninic acid (BCA),enzyme-linkedimmunosorbentassay(EIA...... solution. Adsorbed masses of BSM onto hydrophobic surface, as probe by BCA, showed a continuously increasing trend up to 2mg/mL. But, the signals from EIA and ELLA, which probe the concentration of available unglycosylatedC-terminals and the central glycosylated regions, respectively, showed complicated...

Rock property estimates using multiple seismic attributes and neural networks; Pegasus Field, West Texas

Energy Technology Data Exchange (ETDEWEB)

Schuelke, J.S.; Quirein, J.A.; Sarg, J.F.

1998-12-31

This case study shows the benefit of using multiple seismic trace attributes and the pattern recognition capabilities of neural networks to predict reservoir architecture and porosity distribution in the Pegasus Field, West Texas. The study used the power of neural networks to integrate geologic, borehole and seismic data. Illustrated are the improvements between the new neural network approach and the more traditional method of seismic trace inversion for porosity estimation. Comprehensive statistical methods and interpretational/subjective measures are used in the prediction of porosity from seismic attributes. A 3-D volume of seismic derived porosity estimates for the Devonian reservoir provide a very detailed estimate of porosity, both spatially and vertically, for the field. The additional reservoir porosity detail provided, between the well control, allows for optimal placement of horizontal wells and improved field development. 6 refs., 2 figs.

Sequence co-evolutionary information is a natural partner to minimally-frustrated models of biomolecular dynamics [version 1; referees: 3 approved

Directory of Open Access Journals (Sweden)

Jeffrey K Noel

2016-01-01

Full Text Available Experimentally derived structural constraints have been crucial to the implementation of computational models of biomolecular dynamics. For example, not only does crystallography provide essential starting points for molecular simulations but also high-resolution structures permit for parameterization of simplified models. Since the energy landscapes for proteins and other biomolecules have been shown to be minimally frustrated and therefore funneled, these structure-based models have played a major role in understanding the mechanisms governing folding and many functions of these systems. Structural information, however, may be limited in many interesting cases. Recently, the statistical analysis of residue co-evolution in families of protein sequences has provided a complementary method of discovering residue-residue contact interactions involved in functional configurations. These functional configurations are often transient and difficult to capture experimentally. Thus, co-evolutionary information can be merged with that available for experimentally characterized low free-energy structures, in order to more fully capture the true underlying biomolecular energy landscape.

Stochastic lumping analysis for linear kinetics and its application to the fluctuation relations between hierarchical kinetic networks

Energy Technology Data Exchange (ETDEWEB)

Deng, De-Ming; Chang, Cheng-Hung [Institute of Physics, National Chiao Tung University, Hsinchu 300, Taiwan (China)

2015-05-14

Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems.

Stochastic lumping analysis for linear kinetics and its application to the fluctuation relations between hierarchical kinetic networks.

Science.gov (United States)

Deng, De-Ming; Chang, Cheng-Hung

2015-05-14

Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems.

White matter tract network disruption explains reduced conscientiousness in multiple sclerosis.

Science.gov (United States)

Fuchs, Tom A; Dwyer, Michael G; Kuceyeski, Amy; Choudhery, Sanjeevani; Carolus, Keith; Li, Xian; Mallory, Matthew; Weinstock-Guttman, Bianca; Jakimovski, Dejan; Ramasamy, Deepa; Zivadinov, Robert; Benedict, Ralph H B

2018-05-08

Quantifying white matter (WM) tract disruption in people with multiple sclerosis (PwMS) provides a novel means for investigating the relationship between defective network connectivity and clinical markers. PwMS exhibit perturbations in personality, where decreased Conscientiousness is particularly prominent. This trait deficit influences disease trajectory and functional outcomes such as work capacity. We aimed to identify patterns of WM tract disruption related to decreased Conscientiousness in PwMS. Personality assessment and brain MRI were obtained in 133 PwMS and 49 age- and sex-matched healthy controls (HC). Lesion maps were applied to determine the severity of WM tract disruption between pairs of gray matter regions. Next, the Network-Based-Statistics tool was applied to identify structural networks whose disruption negatively correlates with Conscientiousness. Finally, to determine whether these networks explain unique variance above conventional MRI measures and cognition, regression models were applied controlling for age, sex, brain volume, T2-lesion volume, and cognition. Relative to HCs, PwMS exhibited lower Conscientiousness and slowed cognitive processing speed (p = .025, p = .006). Lower Conscientiousness in PwMS was significantly associated with WM tract disruption between frontal, frontal-parietal, and frontal-cingulate pathways in the left (p = .02) and right (p = .01) hemisphere. The mean disruption of these pathways explained unique additive variance in Conscientiousness, after accounting for conventional MRI markers of pathology and cognition (ΔR 2  = .049, p = .029). Damage to WM tracts between frontal, frontal-parietal, and frontal-cingulate cortical regions is significantly correlated with reduced Conscientiousness in PwMS. Tract disruption within these networks explains decreased Conscientiousness observed in PwMS as compared with HCs. © 2018 Wiley Periodicals, Inc.

Joint multiple fully connected convolutional neural network with extreme learning machine for hepatocellular carcinoma nuclei grading.

Science.gov (United States)

Li, Siqi; Jiang, Huiyan; Pang, Wenbo

2017-05-01

Accurate cell grading of cancerous tissue pathological image is of great importance in medical diagnosis and treatment. This paper proposes a joint multiple fully connected convolutional neural network with extreme learning machine (MFC-CNN-ELM) architecture for hepatocellular carcinoma (HCC) nuclei grading. First, in preprocessing stage, each grayscale image patch with the fixed size is obtained using center-proliferation segmentation (CPS) method and the corresponding labels are marked under the guidance of three pathologists. Next, a multiple fully connected convolutional neural network (MFC-CNN) is designed to extract the multi-form feature vectors of each input image automatically, which considers multi-scale contextual information of deep layer maps sufficiently. After that, a convolutional neural network extreme learning machine (CNN-ELM) model is proposed to grade HCC nuclei. Finally, a back propagation (BP) algorithm, which contains a new up-sample method, is utilized to train MFC-CNN-ELM architecture. The experiment comparison results demonstrate that our proposed MFC-CNN-ELM has superior performance compared with related works for HCC nuclei grading. Meanwhile, external validation using ICPR 2014 HEp-2 cell dataset shows the good generalization of our MFC-CNN-ELM architecture. Copyright © 2017 Elsevier Ltd. All rights reserved.

Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular networks

NARCIS (Netherlands)

R. Colak; F. Moser; J. Shu; A. Schönhuth (Alexander); N. Chen; M. Ester

2010-01-01

htmlabstractBackground Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not

Mitigating Inter-Network Interference in LoRa Networks

OpenAIRE

Voigt, Thiemo; Bor, Martin; Roedig, Utz; Alonso, Juan

2017-01-01

Long Range (LoRa) is a popular technology used to construct Low-Power Wide-Area Network (LPWAN) networks. Given the popularity of LoRa it is likely that multiple independent LoRa networks are deployed in close proximity. In this situation, neighbouring networks interfere and methods have to be found to combat this interference. In this paper we investigate the use of directional antennae and the use of multiple base stations as methods of dealing with inter-network interference. Directional a...

Optimal multiple-information integration inherent in a ring neural network

International Nuclear Information System (INIS)

Takiyama, Ken

2017-01-01

Although several behavioral experiments have suggested that our neural system integrates multiple sources of information based on the certainty of each type of information in the manner of maximum-likelihood estimation, it is unclear how the maximum-likelihood estimation is implemented in our neural system. Here, I investigate the relationship between maximum-likelihood estimation and a widely used ring-type neural network model that is used as a model of visual, motor, or prefrontal cortices. Without any approximation or ansatz, I analytically demonstrate that the equilibrium of an order parameter in the neural network model exactly corresponds to the maximum-likelihood estimation when the strength of the symmetrical recurrent synaptic connectivity within a neural population is appropriately stronger than that of asymmetrical connectivity, that of local and external inputs, and that of symmetrical or asymmetrical connectivity between different neural populations. In this case, strengths of local and external inputs or those of symmetrical connectivity between different neural populations exactly correspond to the input certainty in maximum-likelihood estimation. Thus, my analysis suggests appropriately strong symmetrical recurrent connectivity as a possible candidate for implementing the maximum-likelihood estimation within our neural system. (paper)

AIM for Allostery: Using the Ising Model to Understand Information Processing and Transmission in Allosteric Biomolecular Systems.

Science.gov (United States)

LeVine, Michael V; Weinstein, Harel

2015-05-01

In performing their biological functions, molecular machines must process and transmit information with high fidelity. Information transmission requires dynamic coupling between the conformations of discrete structural components within the protein positioned far from one another on the molecular scale. This type of biomolecular "action at a distance" is termed allostery . Although allostery is ubiquitous in biological regulation and signal transduction, its treatment in theoretical models has mostly eschewed quantitative descriptions involving the system's underlying structural components and their interactions. Here, we show how Ising models can be used to formulate an approach to allostery in a structural context of interactions between the constitutive components by building simple allosteric constructs we termed Allosteric Ising Models (AIMs). We introduce the use of AIMs in analytical and numerical calculations that relate thermodynamic descriptions of allostery to the structural context, and then show that many fundamental properties of allostery, such as the multiplicative property of parallel allosteric channels, are revealed from the analysis of such models. The power of exploring mechanistic structural models of allosteric function in more complex systems by using AIMs is demonstrated by building a model of allosteric signaling for an experimentally well-characterized asymmetric homodimer of the dopamine D2 receptor.

Priority and Negotiation Based Dynamic Spectrum Allocation Scheme for Multiple Radio Access Network Operators

Science.gov (United States)

Kim, Hoon; Hyon, Taein; Lee, Yeonwoo

Most of previous works have presented the dynamic spectrum allocation (DSA) gain achieved by utilizing the time or regional variations in traffic demand between multi-network operators (NOs). In this paper, we introduce the functionalities required for the entities related with the spectrum sharing and allocation and propose a spectrum allocation algorithm while considering the long-term priority between NOs, the priority between multiple class services, and the urgent bandwidth request. To take into account the priorities among the NOs and the priorities of multiple class services, a spectrum sharing metric (SSM) is proposed, while a negotiation procedure is proposed to treat the urgent bandwidth request.

Exploiting deep neural networks and head movements for binaural localisation of multiple speakers in reverberant conditions

DEFF Research Database (Denmark)

Ma, Ning; Brown, Guy J.; May, Tobias

2015-01-01

This paper presents a novel machine-hearing system that exploits deep neural networks (DNNs) and head movements for binaural localisation of multiple speakers in reverberant conditions. DNNs are used to map binaural features, consisting of the complete crosscorrelation function (CCF) and interaural...

Biomolecular ions in superfluid helium nanodroplets

Energy Technology Data Exchange (ETDEWEB)

Gonzalez Florez, Ana Isabel

2016-07-01

The function of a biological molecule is closely related to its structure. As a result, understanding and predicting biomolecular structure has become the focus of an extensive field of research. However, the investigation of molecular structure can be hampered by two main difficulties: the inherent complications that may arise from studying biological molecules in their native environment, and the potential congestion of the experimental results as a consequence of the large number of degrees of freedom present in these molecules. In this work, a new experimental setup has been developed and established in order to overcome the afore mentioned limitations combining structure-sensitive gas-phase methods with superfluid helium droplets. First, biological molecules are ionised and brought into the gas phase, often referred to as a clean-room environment, where the species of interest are isolated from their surroundings and, thus, intermolecular interactions are absent. The mass-to-charge selected biomolecules are then embedded inside clusters of superfluid helium with an equilibrium temperature of ∝0.37 K. As a result, the internal energy of the molecules is lowered, thereby reducing the number of populated quantum states. Finally, the local hydrogen bonding patterns of the molecules are investigated by probing specific vibrational modes using the Fritz Haber Institute's free electron laser as a source of infrared radiation. Although the structure of a wide variety of molecules has been studied making use of the sub-Kelvin environment provided by superfluid helium droplets, the suitability of this method for the investigation of biological molecular ions was still unclear. However, the experimental results presented in this thesis demonstrate the applicability of this experimental approach in order to study the structure of intact, large biomolecular ions and the first vibrational spectrum of the protonated pentapeptide leu-enkephalin embedded in helium

Biomolecular ions in superfluid helium nanodroplets

International Nuclear Information System (INIS)

Gonzalez Florez, Ana Isabel

2016-01-01

The function of a biological molecule is closely related to its structure. As a result, understanding and predicting biomolecular structure has become the focus of an extensive field of research. However, the investigation of molecular structure can be hampered by two main difficulties: the inherent complications that may arise from studying biological molecules in their native environment, and the potential congestion of the experimental results as a consequence of the large number of degrees of freedom present in these molecules. In this work, a new experimental setup has been developed and established in order to overcome the afore mentioned limitations combining structure-sensitive gas-phase methods with superfluid helium droplets. First, biological molecules are ionised and brought into the gas phase, often referred to as a clean-room environment, where the species of interest are isolated from their surroundings and, thus, intermolecular interactions are absent. The mass-to-charge selected biomolecules are then embedded inside clusters of superfluid helium with an equilibrium temperature of ∝0.37 K. As a result, the internal energy of the molecules is lowered, thereby reducing the number of populated quantum states. Finally, the local hydrogen bonding patterns of the molecules are investigated by probing specific vibrational modes using the Fritz Haber Institute's free electron laser as a source of infrared radiation. Although the structure of a wide variety of molecules has been studied making use of the sub-Kelvin environment provided by superfluid helium droplets, the suitability of this method for the investigation of biological molecular ions was still unclear. However, the experimental results presented in this thesis demonstrate the applicability of this experimental approach in order to study the structure of intact, large biomolecular ions and the first vibrational spectrum of the protonated pentapeptide leu-enkephalin embedded in helium

Oscillation-Driven Spike-Timing Dependent Plasticity Allows Multiple Overlapping Pattern Recognition in Inhibitory Interneuron Networks

DEFF Research Database (Denmark)

Garrido, Jesús A.; Luque, Niceto R.; Tolu, Silvia

2016-01-01

The majority of operations carried out by the brain require learning complex signal patterns for future recognition, retrieval and reuse. Although learning is thought to depend on multiple forms of long-term synaptic plasticity, the way this latter contributes to pattern recognition is still poorly...... and at the inhibitory interneuron-interneuron synapses, the interneurons rapidly learned complex input patterns. Interestingly, induction of plasticity required that the network be entrained into theta-frequency band oscillations, setting the internal phase-reference required to drive STDP. Inhibitory plasticity...... effectively distributed multiple patterns among available interneurons, thus allowing the simultaneous detection of multiple overlapping patterns. The addition of plasticity in intrinsic excitability made the system more robust allowing self-adjustment and rescaling in response to a broad range of input...

Novel global robust stability criteria for interval neural networks with multiple time-varying delays

International Nuclear Information System (INIS)

Xu Shengyuan; Lam, James; Ho, Daniel W.C.

2005-01-01

This Letter is concerned with the problem of robust stability analysis for interval neural networks with multiple time-varying delays and parameter uncertainties. The parameter uncertainties are assumed to be bounded in given compact sets and the activation functions are supposed to be bounded and globally Lipschitz continuous. A sufficient condition is obtained by means of Lyapunov functionals, which guarantees the existence, uniqueness and global asymptotic stability of the delayed neural network for all admissible uncertainties. This condition is in terms of a linear matrix inequality (LMI), which can be easily checked by using recently developed algorithms in solving LMIs. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method

A hydrogel-based versatile screening platform for specific biomolecular recognition in a well plate format.

Science.gov (United States)

Beer, Meike V; Rech, Claudia; Diederichs, Sylvia; Hahn, Kathrin; Bruellhoff, Kristina; Möller, Martin; Elling, Lothar; Groll, Jürgen

2012-04-01

Precise determination of biomolecular interactions in high throughput crucially depends on a surface coating technique that allows immobilization of a variety of interaction partners in a non-interacting environment. We present a one-step hydrogel coating system based on isocyanate functional six-arm poly(ethylene oxide)-based star polymers for commercially available 96-well microtiter plates that combines a straightforward and robust coating application with versatile bio-functionalization. This system generates resistance to unspecific protein adsorption and cell adhesion, as demonstrated with fluorescently labeled bovine serum albumin and primary human dermal fibroblasts (HDF), and high specificity for the assessment of biomolecular recognition processes when ligands are immobilized on this surface. One particular advantage is the wide range of biomolecules that can be immobilized and convert the per se inert coating into a specifically interacting surface. We here demonstrate the immobilization and quantification of a broad range of biochemically important ligands, such as peptide sequences GRGDS and GRGDSK-biotin, the broadly applicable coupler molecule biocytin, the protein fibronectin, and the carbohydrates N-acetylglucosamine and N-acetyllactosamine. A simplified protocol for an enzyme-linked immunosorbent assay was established for the detection and quantification of ligands on the coating surface. Cell adhesion on the peptide and protein-modified surfaces was assessed using HDF. All coatings were applied using a one-step preparation technique, including bioactivation, which makes the system suitable for high-throughput screening in a format that is compatible with the most routinely used testing systems.

Position paper: cognitive radio networking for multiple sensor network interoperability in mines

CSIR Research Space (South Africa)

Kagize, BM

2008-01-01

Full Text Available . These commercially available networks are purported to be self-organizing and self correcting, though the software behind these networks are proprietary with the caveat of inter-operability difficulties with other networks [5]. There is a non-propriety and open...: Research challenges,” - Ad Hoc Networks, 2006 – Elsevier [4] V Mhatre, C Rosenberg, “Homogeneous vs heterogeneous clustered sensor networks: a comparative study,” - Communications, 2004 IEEE International Conference on, 2004 - ieeexplore.ieee.org [5...

Real-time multiple networked viewer capability of the DIII-D EC data acquisition system

International Nuclear Information System (INIS)

Ponce, D.; Gorelov, I.A.; Chiu, H.K.; Baity, F.W.

2005-01-01

A data acquisition system (DAS) which permits real-time viewing by multiple locally networked operators is being implemented for the electron cyclotron (EC) heating and current drive system at DIII-D. The DAS is expected to demonstrate performance equivalent to standalone oscilloscopes. Participation by remote viewers, including throughout the greater DIII-D facility, can also be incorporated. The real-time system uses one computer-controlled DAS per gyrotron. The DAS computers send their data to a central data server using individual and dedicated 200 Mbps fully duplexed Ethernet connections. The server has a dedicated 10 krpm hard drive for each gyrotron DAS. Selected channels can then be reprocessed and distributed to viewers over a standard local area network (LAN). They can also be bridged from the LAN to the internet. Calculations indicate that the hardware will support real-time writing of each channel at full resolution to the server hard drives. The data will be re-sampled for distribution to multiple viewers over the LAN in real-time. The hardware for this system is in place. The software is under development. This paper will present the design details and up-to-date performance metrics of the system

New results for global robust stability of bidirectional associative memory neural networks with multiple time delays

International Nuclear Information System (INIS)

Senan, Sibel; Arik, Sabri

2009-01-01

This paper presents some new sufficient conditions for the global robust asymptotic stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with multiple time delays. The results we obtain impose constraint conditions on the network parameters of neural system independently of the delay parameter, and they are applicable to all bounded continuous non-monotonic neuron activation functions. We also give some numerical examples to demonstrate the applicability and effectiveness of our results, and compare the results with the previous robust stability results derived in the literature.

Three-Way Channels With Multiple Unicast Sessions: Capacity Approximation via Network Transformation

KAUST Repository

Chaaban, Anas

2016-09-28

A network of three nodes mutually communicating with each other is studied. This multi-way network is a suitable model for three-user device-to-device communications. The main goal of this paper is to characterize the capacity region of the underlying Gaussian three-way channel (3WC) within a constant gap. To this end, a capacity outer bound is derived using cut-set bounds and genie-aided bounds. For achievability, the 3WC is first transformed into an equivalent star channel. This latter is then decomposed into a set of “successive” sub-channels, leading to a sub-channel allocation problem. Using backward decoding, interference neutralization, and known results on the capacity of the star-channel relying of physical-layer network coding, an achievable rate region for the 3WC is obtained. It is then shown that the achievable rate region is within a constant gap of the developed outer bound, leading to the desired capacity approximation. Interestingly, in contrast to the Gaussian two-way channel (TWC), adaptation is necessary in the 3WC. Furthermore, message splitting is another ingredient of the developed scheme for the 3WC, which is not required in the TWC. The two setups are, however, similar in terms of their sum-capacity pre-log, which is equal to 2. Finally, some interesting networks and their approximate capacities are recovered as special cases of the 3WC, such as the cooperative broadcast channel and multiple access channel.

Improving the Reliability of Optimised Link State Routing in a Smart Grid Neighbour Area Network based Wireless Mesh Network Using Multiple Metrics

Directory of Open Access Journals (Sweden)

Yakubu Tsado

2017-02-01

Full Text Available Reliable communication is the backbone of advanced metering infrastructure (AMI. Within the AMI, the neighbourhood area network (NAN transports a multitude of traffic, each with unique requirements. In order to deliver an acceptable level of reliability and latency, the underlying network, such as the wireless mesh network(WMN, must provide or guarantee the quality-of-service (QoS level required by the respective application traffic. Existing WMN routing protocols, such as optimised link state routing (OLSR, typically utilise a single metric and do not consider the requirements of individual traffic; hence, packets are delivered on a best-effort basis. This paper presents a QoS-aware WMN routing technique that employs multiple metrics in OLSR optimal path selection for AMI applications. The problems arising from this approach are non deterministic polynomial time (NP-complete in nature, which were solved through the combined use of the analytical hierarchy process (AHP algorithm and pruning techniques. For smart meters transmitting Internet Protocol (IP packets of varying sizes at different intervals, the proposed technique considers the constraints of NAN and the applications’ traffic characteristics. The technique was developed by combining multiple OLSR path selection metrics with the AHP algorithminns-2. Compared with the conventional link metric in OLSR, the results show improvements of about 23% and 45% in latency and Packet Delivery Ratio (PDR, respectively, in a 25-node grid NAN.

Understanding large multiprotein complexes: applying a multiple allosteric networks model to explain the function of the Mediator transcription complex.

Science.gov (United States)

Lewis, Brian A

2010-01-15

The regulation of transcription and of many other cellular processes involves large multi-subunit protein complexes. In the context of transcription, it is known that these complexes serve as regulatory platforms that connect activator DNA-binding proteins to a target promoter. However, there is still a lack of understanding regarding the function of these complexes. Why do multi-subunit complexes exist? What is the molecular basis of the function of their constituent subunits, and how are these subunits organized within a complex? What is the reason for physical connections between certain subunits and not others? In this article, I address these issues through a model of network allostery and its application to the eukaryotic RNA polymerase II Mediator transcription complex. The multiple allosteric networks model (MANM) suggests that protein complexes such as Mediator exist not only as physical but also as functional networks of interconnected proteins through which information is transferred from subunit to subunit by the propagation of an allosteric state known as conformational spread. Additionally, there are multiple distinct sub-networks within the Mediator complex that can be defined by their connections to different subunits; these sub-networks have discrete functions that are activated when specific subunits interact with other activator proteins.

A Self-Reconstructing Algorithm for Single and Multiple-Sensor Fault Isolation Based on Auto-Associative Neural Networks

Directory of Open Access Journals (Sweden)

Hamidreza Mousavi

2017-01-01

Full Text Available Recently different approaches have been developed in the field of sensor fault diagnostics based on Auto-Associative Neural Network (AANN. In this paper we present a novel algorithm called Self reconstructing Auto-Associative Neural Network (S-AANN which is able to detect and isolate single faulty sensor via reconstruction. We have also extended the algorithm to be applicable in multiple fault conditions. The algorithm uses a calibration model based on AANN. AANN can reconstruct the faulty sensor using non-faulty sensors due to correlation between the process variables, and mean of the difference between reconstructed and original data determines which sensors are faulty. The algorithms are tested on a Dimerization process. The simulation results show that the S-AANN can isolate multiple faulty sensors with low computational time that make the algorithm appropriate candidate for online applications.

Evolução biomolecular homoquiral: a origem e a amplificação da quiralidade nas moléculas da vida Homochiral biomolecular evolution: the origin and the amplification of chirality in life molecules

Directory of Open Access Journals (Sweden)

José Augusto R. Rodrigues

2010-01-01

Full Text Available The fact that biologically relevant molecules exist only as one of the two enantiomers is a fascinating example of complete symmetry breaking of chirality and has long intrigued our curiosity. The origin of this selective chirality has remained a fundamental enigma with regard to the origin of life since the time of Pasteur, 160 years ago. The symmetry breaking processes, which include autocatalytic crystallization, asymmetric autocatalysis, spontaneous crystallization, adsorption and polymerization of amino acids on mineral surfaces, provide new insights into the origin of biomolecular homochirality.

The heat shock protein/chaperone network and multiple stress resistance

KAUST Repository

Jacob, Pierre; Hirt, Heribert; Bendahmane, Abdelhafid

2016-01-01

Crop yield has been greatly enhanced during the last century. However, most elite cultivars are adapted to temperate climates and are not well suited to more stressful conditions. In the context of climate change, stress resistance is a major concern. To overcome these difficulties, scientists may help breeders by providing genetic markers associated with stress resistance. However, multi-stress resistance cannot be obtained from the simple addition of single stress resistance traits. In the field, stresses are unpredictable and several may occur at once. Consequently, the use of single stress resistance traits is often inadequate. Although it has been historically linked with the heat stress response, the heat shock protein (HSP)/chaperone network is a major component of multiple stress responses. Among the HSP/chaperone

The heat shock protein/chaperone network and multiple stress resistance

KAUST Repository

Jacob, Pierre

2016-11-15

Crop yield has been greatly enhanced during the last century. However, most elite cultivars are adapted to temperate climates and are not well suited to more stressful conditions. In the context of climate change, stress resistance is a major concern. To overcome these difficulties, scientists may help breeders by providing genetic markers associated with stress resistance. However, multi-stress resistance cannot be obtained from the simple addition of single stress resistance traits. In the field, stresses are unpredictable and several may occur at once. Consequently, the use of single stress resistance traits is often inadequate. Although it has been historically linked with the heat stress response, the heat shock protein (HSP)/chaperone network is a major component of multiple stress responses. Among the HSP/chaperone

Biomolecular Structure Information from High-Speed Quantum Mechanical Electronic Spectra Calculation.

Science.gov (United States)

Seibert, Jakob; Bannwarth, Christoph; Grimme, Stefan

2017-08-30

A fully quantum mechanical (QM) treatment to calculate electronic absorption (UV-vis) and circular dichroism (CD) spectra of typical biomolecules with thousands of atoms is presented. With our highly efficient sTDA-xTB method, spectra averaged along structures from molecular dynamics (MD) simulations can be computed in a reasonable time frame on standard desktop computers. This way, nonequilibrium structure and conformational, as well as purely quantum mechanical effects like charge-transfer or exciton-coupling, are included. Different from other contemporary approaches, the entire system is treated quantum mechanically and neither fragmentation nor system-specific adjustment is necessary. Among the systems considered are a large DNA fragment, oligopeptides, and even entire proteins in an implicit solvent. We propose the method in tandem with experimental spectroscopy or X-ray studies for the elucidation of complex (bio)molecular structures including metallo-proteins like myoglobin.

Performance of Non-Orthogonal Multiple Access (NOMA) in mmWave wireless communications for 5G networks

DEFF Research Database (Denmark)

Marcano, Andrea; Christiansen, Henrik Lehrmann

2017-01-01

Among the key technologies that have been identified as capacity boosters for fifth generation - 5G - mobile networks, are millimeter wave (mmWave) transmissions and non-orthogonal multiple access (NOMA). The large amount of spectrum available at mmWave frequencies combined with a more effective...... use of available resources, helps improving the overall capacity. NOMA, unlike orthogonal multiple access (OMA) methods, allows sharing the same frequency resources at the same time, by implementing adaptive power allocation. In this paper we present a performance analysis of NOMA in mmWave cells...

Information processing speed and attention in multiple sclerosis: Reconsidering the Attention Network Test (ANT).

Science.gov (United States)

Roth, Alexandra K; Denney, Douglas R; Lynch, Sharon G

2015-01-01

The Attention Network Test (ANT) assesses attention in terms of discrepancies between response times to items that differ in the burden they place on some facet of attention. However, simple arithmetic difference scores commonly used to capture these discrepancies fail to provide adequate control for information processing speed, leading to distorted findings when patient and control groups differ markedly in the speed with which they process and respond to stimulus information. This study examined attention networks in patients with multiple sclerosis (MS) using simple difference scores, proportional scores, and residualized scores that control for processing speed through statistical regression. Patients with relapsing-remitting (N = 20) or secondary progressive (N = 20) MS and healthy controls (N = 40) of similar age, education, and gender completed the ANT. Substantial differences between patients and controls were found on all measures of processing speed. Patients exhibited difficulties in the executive control network, but only when difference scores were considered. When deficits in information processing speed were adequately controlled using proportional or residualized score, deficits in the alerting network emerged. The effect sizes for these deficits were notably smaller than those for overall information processing speed and were also limited to patients with secondary progressive MS. Deficits in processing speed are more prominent in MS than those involving attention, and when the former are properly accounted for, differences in the latter are confined to the alerting network.

Theoretical restrictions on longest implicit time scales in Markov state models of biomolecular dynamics

Science.gov (United States)

Sinitskiy, Anton V.; Pande, Vijay S.

2018-01-01

Markov state models (MSMs) have been widely used to analyze computer simulations of various biomolecular systems. They can capture conformational transitions much slower than an average or maximal length of a single molecular dynamics (MD) trajectory from the set of trajectories used to build the MSM. A rule of thumb claiming that the slowest implicit time scale captured by an MSM should be comparable by the order of magnitude to the aggregate duration of all MD trajectories used to build this MSM has been known in the field. However, this rule has never been formally proved. In this work, we present analytical results for the slowest time scale in several types of MSMs, supporting the above rule. We conclude that the slowest implicit time scale equals the product of the aggregate sampling and four factors that quantify: (1) how much statistics on the conformational transitions corresponding to the longest implicit time scale is available, (2) how good the sampling of the destination Markov state is, (3) the gain in statistics from using a sliding window for counting transitions between Markov states, and (4) a bias in the estimate of the implicit time scale arising from finite sampling of the conformational transitions. We demonstrate that in many practically important cases all these four factors are on the order of unity, and we analyze possible scenarios that could lead to their significant deviation from unity. Overall, we provide for the first time analytical results on the slowest time scales captured by MSMs. These results can guide further practical applications of MSMs to biomolecular dynamics and allow for higher computational efficiency of simulations.

Study and development of the data transfer for the NA50 experiment: transputer network of the multiplicity detector

International Nuclear Information System (INIS)

Capony, V.

1996-01-01

This thesis presents the works performed for the experiment NA50 at CERN, in he framework of the development of its multiplicity detector. The two first chapters describe the physical aims of the experiment and the apparatus used. The remaining part of this document shows the data readout device, developed for the multiplicity detector. Built on a T8 transputer network, this system is able to treat 8 Mbytes of data at each SPS accelerator cycle. It integrates an on-line event-builder. A filtering algorithm estimates the validity of the information and allows the flagging of all the data. The last function of this transputers network is to transfer data from the detector to the data acquisition system. Our system is able to control a data rate transfer of 35 Gbytes per day. (author)

Urban networks and Arctic outlands: Craft specialists and reindeer antler in Viking towns

DEFF Research Database (Denmark)

Ashby, Steven P.; Coutu, Ashley N.; Sindbæk, Søren Michael

2015-01-01

This paper presents the results of the use of a minimally destructive biomolecular technique to explore the resource networks behind one of the first specialized urban crafts in early mediaeval northern Europe: the manufacture of composite combs of deer antler. The research incorporates the largest...... the 780s ad at the latest, presenting the earliest unambiguous evidence for exchange-links between urban markets in the southern North Sea region and the Scandinavian Peninsula. The results demonstrate that the common conceptual distinction between urban hinterlands and long-distance trade conceals...... a vital continuity. Long-range networks were vital to urban activities from the first appearance of towns in this part of the world, preceding the historically documented maritime expansion of the Viking Age. We consequently suggest that urbanism is more appropriately defined and researched in terms...

Nonorthogonal multiple access and carrierless amplitude phase modulation for flexible multiuser provisioning in 5G mobile networks

NARCIS (Netherlands)

Altabas, J.A.; Rommel, S.; Puerta, R.; Izquierdo, D.; Ignacio Garces, J.; Antonio Lazaro, J.; Vegas Olmos, J.J.; Tafur Monroy, I.

2017-01-01

In this paper, a combined nonorthogonal multiple access (NOMA) and multiband carrierless amplitude phase modulation (multiCAP) scheme is proposed for capacity enhancement of and flexible resource provisioning in 5G mobile networks. The proposed scheme is experimentally evaluated over a W-band

Featuring Multiple Local Optima to Assist the User in the Interpretation of Induced Bayesian Network Models

DEFF Research Database (Denmark)

Dalgaard, Jens; Pena, Jose; Kocka, Tomas

2004-01-01

We propose a method to assist the user in the interpretation of the best Bayesian network model indu- ced from data. The method consists in extracting relevant features from the model (e.g. edges, directed paths and Markov blankets) and, then, assessing the con¯dence in them by studying multiple...

Non-Orthogonal Multiple Access for Large-Scale 5G Networks: Interference Aware Design

KAUST Repository

Ali, Konpal S.

2017-09-18

Non-orthogonal multiple access (NOMA) is promoted as a key component of 5G cellular networks. As the name implies, NOMA operation introduces intracell interference (i.e., interference arising within the cell) to the cellular operation. The intracell interference is managed by careful NOMA design (e.g., user clustering and resource allocation) along with successive interference cancellation. However, most of the proposed NOMA designs are agnostic to intercell interference (i.e., interference from outside the cell), which is a major performance limiting parameter in 5G networks. This article sheds light on the drastic negative-impact of intercell interference on the NOMA performance and advocates interference-aware NOMA design that jointly accounts for both intracell and intercell interference. To this end, a case study for fair NOMA operation is presented and intercell interference mitigation techniques for NOMA networks are discussed. This article also investigates the potential of integrating NOMA with two important 5G transmission schemes, namely, full duplex and device-to-device communication. This is important since the ambitious performance defined by the 3rd Generation Partnership Project (3GPP) for 5G is foreseen to be realized via seamless integration of several new technologies and transmission techniques.

A distributed Synchronous reservation multiple access control protocol for mobile Ad hoc networks

Institute of Scientific and Technical Information of China (English)

ZHANG Yanling; SUN Xianpu; LI Jiandong

2007-01-01

This study proposes a new multiple access control protocol named distributed synchronous reservation multiple access control protocol.in which the hidden and exposed terminal problems are solved,and the quality of service(QoS)requirements for real-time traffic are guaranteed.The protocol is founded on time division multiplex address and a different type of traffic is assigned to difierent priority,according to which a node should compete for and reserve the free slots in a different method.Moreover,there is a reservation acknowledgement process before data transmit in each reserved slot,so that the intruded terminal problem is solved.The throughput and average packets drop probability of this protocol are analyzed and simulated in a fully connected network.the results of which indicate that this protocol is efficient enough to support the real-time traffic.and it is more suitable to MANETs.

Power Allocation in Multiple Access Networks: Implementation Aspects via Verhulst and Perron-Frobenius Models

Directory of Open Access Journals (Sweden)

Fábio Engel de Camargo

2012-11-01

Full Text Available In this work, the Verhulst model and the Perron-Frobenius theorem are applied on the power control problem which is a concern in multiple access communication networks due to the multiple access interference. This paper deals with the performance versus complexity tradeoff of both power control algorithm (PCA, as well as highlights the computational cost aspects regarding the implementability of distributed PCA (DPCA version for both algorithms. As a proof-of-concept the DPCA implementation is carried out deploying a commercial point-floating DSP platform. Numerical results in terms of DSP cycles and computational time as well indicate a feasibility of implementing the PCA-Verhulst model in 2G and 3G cellular systems; b high computational cost for the PCA-Perron-Frobenius model.

Interaction of multiple networks modulated by the working memory training based on real-time fMRI

Science.gov (United States)

Shen, Jiahui; Zhang, Gaoyan; Zhu, Chaozhe; Yao, Li; Zhao, Xiaojie

2015-03-01

Neuroimaging studies of working memory training have identified the alteration of brain activity as well as the regional interactions within the functional networks such as central executive network (CEN) and default mode network (DMN). However, how the interaction within and between these multiple networks is modulated by the training remains unclear. In this paper, we examined the interaction of three training-induced brain networks during working memory training based on real-time functional magnetic resonance imaging (rtfMRI). Thirty subjects assigned to the experimental and control group respectively participated in two times training separated by seven days. Three networks including silence network (SN), CEN and DMN were identified by the training data with the calculated function connections within each network. Structural equation modeling (SEM) approach was used to construct the directional connectivity patterns. The results showed that the causal influences from the percent signal changes of target ROI to the SN were positively changed in both two groups, as well as the causal influence from the SN to CEN was positively changed in experimental group but negatively changed in control group from the SN to DMN. Further correlation analysis of the changes in each network with the behavioral improvements showed that the changes in SN were stronger positively correlated with the behavioral improvement of letter memory task. These findings indicated that the SN was not only a switch between the target ROI and the other networks in the feedback training but also an essential factor to the behavioral improvement.

Energy efficient design for MIMO two-way AF multiple relay networks

KAUST Repository

Alsharoa, Ahmad M.

2014-04-01

This paper studies the energy efficient transmission and the power allocation problem for multiple two-way relay networks equipped with multi-input multi-output antennas where each relay employs an amplify-and-forward strategy. The goal is to minimize the total power consumption without degrading the quality of service of the terminals. In our analysis, we start by deriving closed-form expressions of the optimal powers allocated to terminals. We then employ a strong optimization tool based on the particle swarm optimization technique to find the optimal power allocated at each relay antenna. Our numerical results illustrate the performance of the proposed scheme and show that it achieves a sub-optimal solution very close to the optimal one.

Network-based identification of biomarkers coexpressed with multiple pathways.

Science.gov (United States)

Guo, Nancy Lan; Wan, Ying-Wooi

2014-01-01

Unraveling complex molecular interactions and networks and incorporating clinical information in modeling will present a paradigm shift in molecular medicine. Embedding biological relevance via modeling molecular networks and pathways has become increasingly important for biomarker identification in cancer susceptibility and metastasis studies. Here, we give a comprehensive overview of computational methods used for biomarker identification, and provide a performance comparison of several network models used in studies of cancer susceptibility, disease progression, and prognostication. Specifically, we evaluated implication networks, Boolean networks, Bayesian networks, and Pearson's correlation networks in constructing gene coexpression networks for identifying lung cancer diagnostic and prognostic biomarkers. The results show that implication networks, implemented in Genet package, identified sets of biomarkers that generated an accurate prediction of lung cancer risk and metastases; meanwhile, implication networks revealed more biologically relevant molecular interactions than Boolean networks, Bayesian networks, and Pearson's correlation networks when evaluated with MSigDB database.

Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

Science.gov (United States)

Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.

2013-01-01

Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887

Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems.

Science.gov (United States)

Chylek, Lily A; Harris, Leonard A; Tung, Chang-Shung; Faeder, James R; Lopez, Carlos F; Hlavacek, William S

2014-01-01

Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and posttranslational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). © 2013 Wiley Periodicals, Inc.

Coordination of networked systems on digraphs with multiple leaders via pinning control

Science.gov (United States)

Chen, Gang; Lewis, Frank L.

2012-02-01

It is well known that achieving consensus among a group of multi-vehicle systems by local distributed control is feasible if and only if all nodes in the communication digraph are reachable from a single (root) node. In this article, we take into account a more general case that the communication digraph of the networked multi-vehicle systems is weakly connected and has two or more zero-in-degree and strongly connected subgraphs, i.e. there are two or more leader groups. Based on the pinning control strategy, the feasibility problem of achieving second-order controlled consensus is studied. At first, a necessary and sufficient condition is given when the topology is fixed. Then the method to design the controller and the rule to choose the pinned vehicles are discussed. The proposed approach allows us to extend several existing results for undirected graphs to directed balanced graphs. A sufficient condition is proposed in the case where the coupling topology is variable. As an illustrative example, a second-order controlled consensus scheme is applied to coordinate the movement of networked multiple mobile robots.

Power Flow Calculation for Weakly Meshed Distribution Networks with Multiple DGs Based on Generalized Chain-table Storage Structure

DEFF Research Database (Denmark)

Chen, Shuheng; Hu, Weihao; Chen, Zhe

2014-01-01

Based on generalized chain-table storage structure (GCTSS), a novel power flow method is proposed, which can be used to solve the power flow of weakly meshed distribution networks with multiple distributed generators (DGs). GCTSS is designed based on chain-table technology and its target is to de......Based on generalized chain-table storage structure (GCTSS), a novel power flow method is proposed, which can be used to solve the power flow of weakly meshed distribution networks with multiple distributed generators (DGs). GCTSS is designed based on chain-table technology and its target...... is to describe the topology of radial distribution networks with a clear logic and a small memory size. The strategies of compensating the equivalent currents of break-point branches and the reactive power outputs of PV-type DGs are presented on the basis of superposition theorem. Their formulations...... are simplified to be the final multi-variable linear functions. Furthermore, an accelerating factor is applied to the outer-layer reactive power compensation for improving the convergence procedure. Finally, the proposed power flow method is performed in program language VC++ 6.0, and numerical tests have been...

Optical coherence tomography angiography retinal vascular network assessment in multiple sclerosis.

Science.gov (United States)

Lanzillo, Roberta; Cennamo, Gilda; Criscuolo, Chiara; Carotenuto, Antonio; Velotti, Nunzio; Sparnelli, Federica; Cianflone, Alessandra; Moccia, Marcello; Brescia Morra, Vincenzo

2017-09-01

Optical coherence tomography (OCT) angiography is a new method to assess the density of the vascular networks. Vascular abnormalities are considered involved in multiple sclerosis (MS) pathology. To assess the presence of vascular abnormalities in MS and to evaluate their correlation to disease features. A total of 50 MS patients with and without history of optic neuritis (ON) and 46 healthy subjects were included. All underwent spectral domain (SD)-OCT and OCT angiography. Clinical history, Expanded Disability Status Scale (EDSS), Multiple Sclerosis Severity Score (MSSS) and disease duration were collected. Angio-OCT showed a vessel density reduction in eyes of MS patients when compared to controls. A statistically significant reduction in all SD-OCT and OCT angiography parameters was noticed both in eyes with and without ON when compared with control eyes. We found an inverse correlation between SD-OCT parameters and MSSS ( p = 0.003) and between vessel density parameters and EDSS ( p = 0.007). We report a vessel density reduction in retina of MS patients. We highlight the clinical correlation between vessel density and EDSS, suggesting that angio-OCT could be a good marker of disease and of disability in MS.

Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes.

Science.gov (United States)

Achana, Felix A; Cooper, Nicola J; Bujkiewicz, Sylwia; Hubbard, Stephanie J; Kendrick, Denise; Jones, David R; Sutton, Alex J

2014-07-21

Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes. The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations. Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on

Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design.

Science.gov (United States)

Maguire, Jack B; Boyken, Scott E; Baker, David; Kuhlman, Brian

2018-05-08

Hydrogen bond networks play a critical role in determining the stability and specificity of biomolecular complexes, and the ability to design such networks is important for engineering novel structures, interactions, and enzymes. One key feature of hydrogen bond networks that makes them difficult to rationally engineer is that they are highly cooperative and are not energetically favorable until the hydrogen bonding potential has been satisfied for all buried polar groups in the network. Existing computational methods for protein design are ill-equipped for creating these highly cooperative networks because they rely on energy functions and sampling strategies that are focused on pairwise interactions. To enable the design of complex hydrogen bond networks, we have developed a new sampling protocol in the molecular modeling program Rosetta that explicitly searches for sets of amino acid mutations that can form self-contained hydrogen bond networks. For a given set of designable residues, the protocol often identifies many alternative sets of mutations/networks, and we show that it can readily be applied to large sets of residues at protein-protein interfaces or in the interior of proteins. The protocol builds on a recently developed method in Rosetta for designing hydrogen bond networks that has been experimentally validated for small symmetric systems but was not extensible to many larger protein structures and complexes. The sampling protocol we describe here not only recapitulates previously validated designs with performance improvements but also yields viable hydrogen bond networks for cases where the previous method fails, such as the design of large, asymmetric interfaces relevant to engineering protein-based therapeutics.

A genetic algorithm for multiple relay selection in two-way relaying cognitive radio networks

KAUST Repository

Alsharoa, Ahmad M.

2013-09-01

In this paper, we investigate a multiple relay selection scheme for two-way relaying cognitive radio networks where primary users and secondary users operate on the same frequency band. More specifically, cooperative relays using Amplifyand- Forward (AF) protocol are optimally selected to maximize the sum rate of the secondary users without degrading the Quality of Service (QoS) of the primary users by respecting a tolerated interference threshold. A strong optimization tool based on genetic algorithm is employed to solve our formulated optimization problem where discrete relay power levels are considered. Our simulation results show that the practical heuristic approach achieves almost the same performance of the optimal multiple relay selection scheme either with discrete or continuous power distributions. Copyright © 2013 by the Institute of Electrical and Electronic Engineers, Inc.

Cancer genetics meets biomolecular mechanism-bridging an age-old gulf.

Science.gov (United States)

González-Sánchez, Juan Carlos; Raimondi, Francesco; Russell, Robert B

2018-02-01

Increasingly available genomic sequencing data are exploited to identify genes and variants contributing to diseases, particularly cancer. Traditionally, methods to find such variants have relied heavily on allele frequency and/or familial history, often neglecting to consider any mechanistic understanding of their functional consequences. Thus, while the set of known cancer-related genes has increased, for many, their mechanistic role in the disease is not completely understood. This issue highlights a wide gap between the disciplines of genetics, which largely aims to correlate genetic events with phenotype, and molecular biology, which ultimately aims at a mechanistic understanding of biological processes. Fortunately, new methods and several systematic studies have proved illuminating for many disease genes and variants by integrating sequencing with mechanistic data, including biomolecular structures and interactions. These have provided new interpretations for known mutations and suggested new disease-relevant variants and genes. Here, we review these approaches and discuss particular examples where these have had a profound impact on the understanding of human cancers. © 2018 Federation of European Biochemical Societies.

Overcoming the solubility limit with solubility-enhancement tags: successful applications in biomolecular NMR studies

International Nuclear Information System (INIS)

Zhou Pei; Wagner, Gerhard

2010-01-01

Although the rapid progress of NMR technology has significantly expanded the range of NMR-trackable systems, preparation of NMR-suitable samples that are highly soluble and stable remains a bottleneck for studies of many biological systems. The application of solubility-enhancement tags (SETs) has been highly effective in overcoming solubility and sample stability issues and has enabled structural studies of important biological systems previously deemed unapproachable by solution NMR techniques. In this review, we provide a brief survey of the development and successful applications of the SET strategy in biomolecular NMR. We also comment on the criteria for choosing optimal SETs, such as for differently charged target proteins, and recent new developments on NMR-invisible SETs.

Network hydraulics inclusion in water quality event detection using multiple sensor stations data.

Science.gov (United States)

Oliker, Nurit; Ostfeld, Avi

2015-09-01

Event detection is one of the current most challenging topics in water distribution systems analysis: how regular on-line hydraulic (e.g., pressure, flow) and water quality (e.g., pH, residual chlorine, turbidity) measurements at different network locations can be efficiently utilized to detect water quality contamination events. This study describes an integrated event detection model which combines multiple sensor stations data with network hydraulics. To date event detection modelling is likely limited to single sensor station location and dataset. Single sensor station models are detached from network hydraulics insights and as a result might be significantly exposed to false positive alarms. This work is aimed at decreasing this limitation through integrating local and spatial hydraulic data understanding into an event detection model. The spatial analysis complements the local event detection effort through discovering events with lower signatures by exploring the sensors mutual hydraulic influences. The unique contribution of this study is in incorporating hydraulic simulation information into the overall event detection process of spatially distributed sensors. The methodology is demonstrated on two example applications using base runs and sensitivity analyses. Results show a clear advantage of the suggested model over single-sensor event detection schemes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Solving the 0/1 Knapsack Problem by a Biomolecular DNA Computer

Directory of Open Access Journals (Sweden)

Hassan Taghipour

2013-01-01

Full Text Available Solving some mathematical problems such as NP-complete problems by conventional silicon-based computers is problematic and takes so long time. DNA computing is an alternative method of computing which uses DNA molecules for computing purposes. DNA computers have massive degrees of parallel processing capability. The massive parallel processing characteristic of DNA computers is of particular interest in solving NP-complete and hard combinatorial problems. NP-complete problems such as knapsack problem and other hard combinatorial problems can be easily solved by DNA computers in a very short period of time comparing to conventional silicon-based computers. Sticker-based DNA computing is one of the methods of DNA computing. In this paper, the sticker based DNA computing was used for solving the 0/1 knapsack problem. At first, a biomolecular solution space was constructed by using appropriate DNA memory complexes. Then, by the application of a sticker-based parallel algorithm using biological operations, knapsack problem was resolved in polynomial time.

Piezoelectric tuning fork biosensors for the quantitative measurement of biomolecular interactions

International Nuclear Information System (INIS)

Gonzalez, Laura; Maria Benito, Angel; Puig-Vidal, Manel; Otero, Jorge; Rodrigues, Mafalda; Pérez-García, Lluïsa

2015-01-01

The quantitative measurement of biomolecular interactions is of great interest in molecular biology. Atomic force microscopy (AFM) has proved its capacity to act as a biosensor and determine the affinity between biomolecules of interest. Nevertheless, the detection scheme presents certain limitations when it comes to developing a compact biosensor. Recently, piezoelectric quartz tuning forks (QTFs) have been used as laser-free detection sensors for AFM. However, only a few studies along these lines have considered soft biological samples, and even fewer constitute quantified molecular recognition experiments. Here, we demonstrate the capacity of QTF probes to perform specific interaction measurements between biotin–streptavidin complexes in buffer solution. We propose in this paper a variant of dynamic force spectroscopy based on representing adhesion energies E (aJ) against pulling rates v (nm s"–"1). Our results are compared with conventional AFM measurements and show the great potential of these sensors in molecular interaction studies. (paper)

XML-based approaches for the integration of heterogeneous bio-molecular data.

Science.gov (United States)

Mesiti, Marco; Jiménez-Ruiz, Ernesto; Sanz, Ismael; Berlanga-Llavori, Rafael; Perlasca, Paolo; Valentini, Giorgio; Manset, David

2009-10-15

The today's public database infrastructure spans a very large collection of heterogeneous biological data, opening new opportunities for molecular biology, bio-medical and bioinformatics research, but raising also new problems for their integration and computational processing. In this paper we survey the most interesting and novel approaches for the representation, integration and management of different kinds of biological data by exploiting XML and the related recommendations and approaches. Moreover, we present new and interesting cutting edge approaches for the appropriate management of heterogeneous biological data represented through XML. XML has succeeded in the integration of heterogeneous biomolecular information, and has established itself as the syntactic glue for biological data sources. Nevertheless, a large variety of XML-based data formats have been proposed, thus resulting in a difficult effective integration of bioinformatics data schemes. The adoption of a few semantic-rich standard formats is urgent to achieve a seamless integration of the current biological resources.

H++ 3.0: automating pK prediction and the preparation of biomolecular structures for atomistic molecular modeling and simulations.

Science.gov (United States)

Anandakrishnan, Ramu; Aguilar, Boris; Onufriev, Alexey V

2012-07-01

The accuracy of atomistic biomolecular modeling and simulation studies depend on the accuracy of the input structures. Preparing these structures for an atomistic modeling task, such as molecular dynamics (MD) simulation, can involve the use of a variety of different tools for: correcting errors, adding missing atoms, filling valences with hydrogens, predicting pK values for titratable amino acids, assigning predefined partial charges and radii to all atoms, and generating force field parameter/topology files for MD. Identifying, installing and effectively using the appropriate tools for each of these tasks can be difficult for novice and time-consuming for experienced users. H++ (http://biophysics.cs.vt.edu/) is a free open-source web server that automates the above key steps in the preparation of biomolecular structures for molecular modeling and simulations. H++ also performs extensive error and consistency checking, providing error/warning messages together with the suggested corrections. In addition to numerous minor improvements, the latest version of H++ includes several new capabilities and options: fix erroneous (flipped) side chain conformations for HIS, GLN and ASN, include a ligand in the input structure, process nucleic acid structures and generate a solvent box with specified number of common ions for explicit solvent MD.

Hybrid Quantum Mechanics/Molecular Mechanics/Coarse Grained Modeling: A Triple-Resolution Approach for Biomolecular Systems.

Science.gov (United States)

Sokkar, Pandian; Boulanger, Eliot; Thiel, Walter; Sanchez-Garcia, Elsa

2015-04-14

We present a hybrid quantum mechanics/molecular mechanics/coarse-grained (QM/MM/CG) multiresolution approach for solvated biomolecular systems. The chemically important active-site region is treated at the QM level. The biomolecular environment is described by an atomistic MM force field, and the solvent is modeled with the CG Martini force field using standard or polarizable (pol-CG) water. Interactions within the QM, MM, and CG regions, and between the QM and MM regions, are treated in the usual manner, whereas the CG-MM and CG-QM interactions are evaluated using the virtual sites approach. The accuracy and efficiency of our implementation is tested for two enzymes, chorismate mutase (CM) and p-hydroxybenzoate hydroxylase (PHBH). In CM, the QM/MM/CG potential energy scans along the reaction coordinate yield reaction energies that are too large, both for the standard and polarizable Martini CG water models, which can be attributed to adverse effects of using large CG water beads. The inclusion of an atomistic MM water layer (10 Å for uncharged CG water and 5 Å for polarizable CG water) around the QM region improves the energy profiles compared to the reference QM/MM calculations. In analogous QM/MM/CG calculations on PHBH, the use of the pol-CG description for the outer water does not affect the stabilization of the highly charged FADHOOH-pOHB transition state compared to the fully atomistic QM/MM calculations. Detailed performance analysis in a glycine-water model system indicates that computation times for QM energy and gradient evaluations at the density functional level are typically reduced by 40-70% for QM/MM/CG relative to fully atomistic QM/MM calculations.

Robust adaptive synchronization of general dynamical networks ...

Indian Academy of Sciences (India)

Robust adaptive synchronization; dynamical network; multiple delays; multiple uncertainties. ... Networks such as neural networks, communication transmission networks, social rela- tionship networks etc. ..... a very good effect. Pramana – J.

Optimal power allocation of a single transmitter-multiple receivers channel in a cognitive sensor network

KAUST Repository

Ayala Solares, Jose Roberto

2012-08-01

The optimal transmit power of a wireless sensor network with one transmitter and multiple receivers in a cognitive radio environment while satisfying independent peak, independent average, sum of peak and sum of average transmission rate constraints is derived. A suboptimal scheme is proposed to overcome the frequency of outages for the independent peak transmission rate constraint. In all cases, numerical results are provided for Rayleigh fading channels. © 2012 IEEE.

Neural Networks for Segregation of Multiple Objects: Visual Figure-Ground Separation and Auditory Pitch Perception.

Science.gov (United States)

Wyse, Lonce

An important component of perceptual object recognition is the segmentation into coherent perceptual units of the "blooming buzzing confusion" that bombards the senses. The work presented herein develops neural network models of some key processes of pre-attentive vision and audition that serve this goal. A neural network model, called an FBF (Feature -Boundary-Feature) network, is proposed for automatic parallel separation of multiple figures from each other and their backgrounds in noisy images. Figure-ground separation is accomplished by iterating operations of a Boundary Contour System (BCS) that generates a boundary segmentation of a scene, and a Feature Contour System (FCS) that compensates for variable illumination and fills-in surface properties using boundary signals. A key new feature is the use of the FBF filling-in process for the figure-ground separation of connected regions, which are subsequently more easily recognized. The new CORT-X 2 model is a feed-forward version of the BCS that is designed to detect, regularize, and complete boundaries in up to 50 percent noise. It also exploits the complementary properties of on-cells and off -cells to generate boundary segmentations and to compensate for boundary gaps during filling-in. In the realm of audition, many sounds are dominated by energy at integer multiples, or "harmonics", of a fundamental frequency. For such sounds (e.g., vowels in speech), the individual frequency components fuse, so that they are perceived as one sound source with a pitch at the fundamental frequency. Pitch is integral to separating auditory sources, as well as to speaker identification and speech understanding. A neural network model of pitch perception called SPINET (SPatial PItch NETwork) is developed and used to simulate a broader range of perceptual data than previous spectral models. The model employs a bank of narrowband filters as a simple model of basilar membrane mechanics, spectral on-center off-surround competitive

Daily Suspended Sediment Discharge Prediction Using Multiple Linear Regression and Artificial Neural Network

Science.gov (United States)

Uca; Toriman, Ekhwan; Jaafar, Othman; Maru, Rosmini; Arfan, Amal; Saleh Ahmar, Ansari

2018-01-01

Prediction of suspended sediment discharge in a catchments area is very important because it can be used to evaluation the erosion hazard, management of its water resources, water quality, hydrology project management (dams, reservoirs, and irrigation) and to determine the extent of the damage that occurred in the catchments. Multiple Linear Regression analysis and artificial neural network can be used to predict the amount of daily suspended sediment discharge. Regression analysis using the least square method, whereas artificial neural networks using Radial Basis Function (RBF) and feedforward multilayer perceptron with three learning algorithms namely Levenberg-Marquardt (LM), Scaled Conjugate Descent (SCD) and Broyden-Fletcher-Goldfarb-Shanno Quasi-Newton (BFGS). The number neuron of hidden layer is three to sixteen, while in output layer only one neuron because only one output target. The mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2 ) and coefficient of efficiency (CE) of the multiple linear regression (MLRg) value Model 2 (6 input variable independent) has the lowest the value of MAE and RMSE (0.0000002 and 13.6039) and highest R2 and CE (0.9971 and 0.9971). When compared between LM, SCG and RBF, the BFGS model structure 3-7-1 is the better and more accurate to prediction suspended sediment discharge in Jenderam catchment. The performance value in testing process, MAE and RMSE (13.5769 and 17.9011) is smallest, meanwhile R2 and CE (0.9999 and 0.9998) is the highest if it compared with the another BFGS Quasi-Newton model (6-3-1, 9-10-1 and 12-12-1). Based on the performance statistics value, MLRg, LM, SCG, BFGS and RBF suitable and accurately for prediction by modeling the non-linear complex behavior of suspended sediment responses to rainfall, water depth and discharge. The comparison between artificial neural network (ANN) and MLRg, the MLRg Model 2 accurately for to prediction suspended sediment discharge (kg

Comparison of multiple linear regression and artificial neural network in developing the objective functions of the orthopaedic screws.

Science.gov (United States)

Hsu, Ching-Chi; Lin, Jinn; Chao, Ching-Kong

2011-12-01

Optimizing the orthopaedic screws can greatly improve their biomechanical performances. However, a methodical design optimization approach requires a long time to search the best design. Thus, the surrogate objective functions of the orthopaedic screws should be accurately developed. To our knowledge, there is no study to evaluate the strengths and limitations of the surrogate methods in developing the objective functions of the orthopaedic screws. Three-dimensional finite element models for both the tibial locking screws and the spinal pedicle screws were constructed and analyzed. Then, the learning data were prepared according to the arrangement of the Taguchi orthogonal array, and the verification data were selected with use of a randomized selection. Finally, the surrogate objective functions were developed by using either the multiple linear regression or the artificial neural network. The applicability and accuracy of those surrogate methods were evaluated and discussed. The multiple linear regression method could successfully construct the objective function of the tibial locking screws, but it failed to develop the objective function of the spinal pedicle screws. The artificial neural network method showed a greater capacity of prediction in developing the objective functions for the tibial locking screws and the spinal pedicle screws than the multiple linear regression method. The artificial neural network method may be a useful option for developing the objective functions of the orthopaedic screws with a greater structural complexity. The surrogate objective functions of the orthopaedic screws could effectively decrease the time and effort required for the design optimization process. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Network features and pathway analyses of a signal transduction cascade

Directory of Open Access Journals (Sweden)

Ryoji Yanashima

2009-05-01

Full Text Available The scale-free and small-world network models reflect the functional units of networks. However, when we investigated the network properties of a signaling pathway using these models, no significant differences were found between the original undirected graphs and the graphs in which inactive proteins were eliminated from the gene expression data. We analyzed signaling networks by focusing on those pathways that best reflected cellular function. Therefore, our analysis of pathways started from the ligands and progressed to transcription factors and cytoskeletal proteins. We employed the Python module to assess the target network. This involved comparing the original and restricted signaling cascades as a directed graph using microarray gene expression profiles of late onset Alzheimer's disease. The most commonly used method of shortest-path analysis neglects to consider the influences of alternative pathways that can affect the activation of transcription factors or cytoskeletal proteins. We therefore introduced included k-shortest paths and k-cycles in our network analysis using the Python modules, which allowed us to attain a reasonable computational time and identify k-shortest paths. This technique reflected results found in vivo and identified pathways not found when shortest path or degree analysis was applied. Our module enabled us to comprehensively analyse the characteristics of biomolecular networks and also enabled analysis of the effects of diseases considering the feedback loop and feedforward loop control structures as an alternative path.

Brain Interaction during Cooperation: Evaluating Local Properties of Multiple-Brain Network.

Science.gov (United States)

Sciaraffa, Nicolina; Borghini, Gianluca; Aricò, Pietro; Di Flumeri, Gianluca; Colosimo, Alfredo; Bezerianos, Anastasios; Thakor, Nitish V; Babiloni, Fabio

2017-07-21

Subjects' interaction is the core of most human activities. This is the reason why a lack of coordination is often the cause of missing goals, more than individual failure. While there are different subjective and objective measures to assess the level of mental effort required by subjects while facing a situation that is getting harder, that is, mental workload, to define an objective measure based on how and if team members are interacting is not so straightforward. In this study, behavioral, subjective and synchronized electroencephalographic data were collected from couples involved in a cooperative task to describe the relationship between task difficulty and team coordination, in the sense of interaction aimed at cooperatively performing the assignment. Multiple-brain connectivity analysis provided information about the whole interacting system. The results showed that averaged local properties of a brain network were affected by task difficulty. In particular, strength changed significantly with task difficulty and clustering coefficients strongly correlated with the workload itself. In particular, a higher workload corresponded to lower clustering values over the central and parietal brain areas. Such results has been interpreted as less efficient organization of the network when the subjects' activities, due to high workload tendencies, were less coordinated.

Using large-scale Granger causality to study changes in brain network properties in the Clinically Isolated Syndrome (CIS) stage of multiple sclerosis

Science.gov (United States)

Abidin, Anas Z.; Chockanathan, Udaysankar; DSouza, Adora M.; Inglese, Matilde; Wismüller, Axel

2017-03-01

Clinically Isolated Syndrome (CIS) is often considered to be the first neurological episode associated with Multiple sclerosis (MS). At an early stage the inflammatory demyelination occurring in the CNS can manifest as a change in neuronal metabolism, with multiple asymptomatic white matter lesions detected in clinical MRI. Such damage may induce topological changes of brain networks, which can be captured by advanced functional MRI (fMRI) analysis techniques. We test this hypothesis by capturing the effective relationships of 90 brain regions, defined in the Automated Anatomic Labeling (AAL) atlas, using a large-scale Granger Causality (lsGC) framework. The resulting networks are then characterized using graph-theoretic measures that quantify various network topology properties at a global as well as at a local level. We study for differences in these properties in network graphs obtained for 18 subjects (10 male and 8 female, 9 with CIS and 9 healthy controls). Global network properties captured trending differences with modularity and clustering coefficient (pdifferences in some regions of the inferior frontal and parietal lobe. We conclude that multivariate analysis of fMRI time-series can reveal interesting information about changes occurring in the brain in early stages of MS.

Robustness analysis of interdependent networks under multiple-attacking strategies

Science.gov (United States)

Gao, Yan-Li; Chen, Shi-Ming; Nie, Sen; Ma, Fei; Guan, Jun-Jie

2018-04-01

The robustness of complex networks under attacks largely depends on the structure of a network and the nature of the attacks. Previous research on interdependent networks has focused on two types of initial attack: random attack and degree-based targeted attack. In this paper, a deliberate attack function is proposed, where six kinds of deliberate attacking strategies can be derived by adjusting the tunable parameters. Moreover, the robustness of four types of interdependent networks (BA-BA, ER-ER, BA-ER and ER-BA) with different coupling modes (random, positive and negative correlation) is evaluated under different attacking strategies. Interesting conclusions could be obtained. It can be found that the positive coupling mode can make the vulnerability of the interdependent network to be absolutely dependent on the most vulnerable sub-network under deliberate attacks, whereas random and negative coupling modes make the vulnerability of interdependent network to be mainly dependent on the being attacked sub-network. The robustness of interdependent network will be enhanced with the degree-degree correlation coefficient varying from positive to negative. Therefore, The negative coupling mode is relatively more optimal than others, which can substantially improve the robustness of the ER-ER network and ER-BA network. In terms of the attacking strategies on interdependent networks, the degree information of node is more valuable than the betweenness. In addition, we found a more efficient attacking strategy for each coupled interdependent network and proposed the corresponding protection strategy for suppressing cascading failure. Our results can be very useful for safety design and protection of interdependent networks.

Enzyme-Based Logic Gates and Networks with Output Signals Analyzed by Various Methods.

Science.gov (United States)

Katz, Evgeny

2017-07-05

The paper overviews various methods that are used for the analysis of output signals generated by enzyme-based logic systems. The considered methods include optical techniques (optical absorbance, fluorescence spectroscopy, surface plasmon resonance), electrochemical techniques (cyclic voltammetry, potentiometry, impedance spectroscopy, conductivity measurements, use of field effect transistor devices, pH measurements), and various mechanoelectronic methods (using atomic force microscope, quartz crystal microbalance). Although each of the methods is well known for various bioanalytical applications, their use in combination with the biomolecular logic systems is rather new and sometimes not trivial. Many of the discussed methods have been combined with the use of signal-responsive materials to transduce and amplify biomolecular signals generated by the logic operations. Interfacing of biocomputing logic systems with electronics and "smart" signal-responsive materials allows logic operations be extended to actuation functions; for example, stimulating molecular release and switchable features of bioelectronic devices, such as biofuel cells. The purpose of this review article is to emphasize the broad variability of the bioanalytical systems applied for signal transduction in biocomputing processes. All bioanalytical systems discussed in the article are exemplified with specific logic gates and multi-gate networks realized with enzyme-based biocatalytic cascades. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multimodal wireless sensor network-based ambient assisted living in real homes with multiple residents.

Science.gov (United States)

Tunca, Can; Alemdar, Hande; Ertan, Halil; Incel, Ozlem Durmaz; Ersoy, Cem

2014-05-30

Human activity recognition and behavior monitoring in a home setting using wireless sensor networks (WSNs) provide a great potential for ambient assisted living (AAL) applications, ranging from health and wellbeing monitoring to resource consumption monitoring. However, due to the limitations of the sensor devices, challenges in wireless communication and the challenges in processing large amounts of sensor data in order to recognize complex human activities, WSN-based AAL systems are not effectively integrated in the home environment. Additionally, given the variety of sensor types and activities, selecting the most suitable set of sensors in the deployment is an important task. In order to investigate and propose solutions to such challenges, we introduce a WSN-based multimodal AAL system compatible for homes with multiple residents. Particularly, we focus on the details of the system architecture, including the challenges of sensor selection, deployment, networking and data collection and provide guidelines for the design and deployment of an effective AAL system. We also present the details of the field study we conducted, using the systems deployed in two different real home environments with multiple residents. With these systems, we are able to collect ambient sensor data from multiple homes. This data can be used to assess the wellbeing of the residents and identify deviations from everyday routines, which may be indicators of health problems. Finally, in order to elaborate on the possible applications of the proposed AAL system and to exemplify directions for processing the collected data, we provide the results of several human activity inference experiments, along with examples on how such results could be interpreted. We believe that the experiences shared in this work will contribute towards accelerating the acceptance of WSN-based AAL systems in the home setting.

Multimodal Wireless Sensor Network-Based Ambient Assisted Living in Real Homes with Multiple Residents

Directory of Open Access Journals (Sweden)

Can Tunca

2014-05-01

Full Text Available Human activity recognition and behavior monitoring in a home setting using wireless sensor networks (WSNs provide a great potential for ambient assisted living (AAL applications, ranging from health and wellbeing monitoring to resource consumption monitoring. However, due to the limitations of the sensor devices, challenges in wireless communication and the challenges in processing large amounts of sensor data in order to recognize complex human activities, WSN-based AAL systems are not effectively integrated in the home environment. Additionally, given the variety of sensor types and activities, selecting the most suitable set of sensors in the deployment is an important task. In order to investigate and propose solutions to such challenges, we introduce a WSN-based multimodal AAL system compatible for homes with multiple residents. Particularly, we focus on the details of the system architecture, including the challenges of sensor selection, deployment, networking and data collection and provide guidelines for the design and deployment of an effective AAL system. We also present the details of the field study we conducted, using the systems deployed in two different real home environments with multiple residents. With these systems, we are able to collect ambient sensor data from multiple homes. This data can be used to assess the wellbeing of the residents and identify deviations from everyday routines, which may be indicators of health problems. Finally, in order to elaborate on the possible applications of the proposed AAL system and to exemplify directions for processing the collected data, we provide the results of several human activity inference experiments, along with examples on how such results could be interpreted. We believe that the experiences shared in this work will contribute towards accelerating the acceptance of WSN-based AAL systems in the home setting.

Frequency-scanning MALDI linear ion trap mass spectrometer for large biomolecular ion detection.

Science.gov (United States)

Lu, I-Chung; Lin, Jung Lee; Lai, Szu-Hsueh; Chen, Chung-Hsuan

2011-11-01

This study presents the first report on the development of a matrix-assisted laser desorption ionization (MALDI) linear ion trap mass spectrometer for large biomolecular ion detection by frequency scan. We designed, installed, and tested this radio frequency (RF) scan linear ion trap mass spectrometer and its associated electronics to dramatically extend the mass region to be detected. The RF circuit can be adjusted from 300 to 10 kHz with a set of operation amplifiers. To trap the ions produced by MALDI, a high pressure of helium buffer gas was employed to quench extra kinetic energy of the heavy ions produced by MALDI. The successful detection of the singly charged secretory immunoglobulin A ions indicates that the detectable mass-to-charge ratio (m/z) of this system can reach ~385 000 or beyond.

A framework to find the logic backbone of a biological network.

Science.gov (United States)

Maheshwari, Parul; Albert, Réka

2017-12-06

Cellular behaviors are governed by interaction networks among biomolecules, for example gene regulatory and signal transduction networks. An often used dynamic modeling framework for these networks, Boolean modeling, can obtain their attractors (which correspond to cell types and behaviors) and their trajectories from an initial state (e.g. a resting state) to the attractors, for example in response to an external signal. The existing methods however do not elucidate the causal relationships between distant nodes in the network. In this work, we propose a simple logic framework, based on categorizing causal relationships as sufficient or necessary, as a complement to Boolean networks. We identify and explore the properties of complex subnetworks that are distillable into a single logic relationship. We also identify cyclic subnetworks that ensure the stabilization of the state of participating nodes regardless of the rest of the network. We identify the logic backbone of biomolecular networks, consisting of external signals, self-sustaining cyclic subnetworks (stable motifs), and output nodes. Furthermore, we use the logic framework to identify crucial nodes whose override can drive the system from one steady state to another. We apply these techniques to two biological networks: the epithelial-to-mesenchymal transition network corresponding to a developmental process exploited in tumor invasion, and the network of abscisic acid induced stomatal closure in plants. We find interesting subnetworks with logical implications in these networks. Using these subgraphs and motifs, we efficiently reduce both networks to succinct backbone structures. The logic representation identifies the causal relationships between distant nodes and subnetworks. This knowledge can form the basis of network control or used in the reverse engineering of networks.

Universal principles governing multiple random searchers on complex networks: The logarithmic growth pattern and the harmonic law

Science.gov (United States)

Weng, Tongfeng; Zhang, Jie; Small, Michael; Harandizadeh, Bahareh; Hui, Pan

2018-03-01

We propose a unified framework to evaluate and quantify the search time of multiple random searchers traversing independently and concurrently on complex networks. We find that the intriguing behaviors of multiple random searchers are governed by two basic principles—the logarithmic growth pattern and the harmonic law. Specifically, the logarithmic growth pattern characterizes how the search time increases with the number of targets, while the harmonic law explores how the search time of multiple random searchers varies relative to that needed by individual searchers. Numerical and theoretical results demonstrate these two universal principles established across a broad range of random search processes, including generic random walks, maximal entropy random walks, intermittent strategies, and persistent random walks. Our results reveal two fundamental principles governing the search time of multiple random searchers, which are expected to facilitate investigation of diverse dynamical processes like synchronization and spreading.

Network on Target: Remotely Configured Adaptive Tactical Networks

National Research Council Canada - National Science Library

Bordetsky, Alex; Bourakov, Eugene

2006-01-01

The emerging tactical networks represent complex network-centric systems, in which multiple sensors, unmanned vehicles, and geographically distributed units of highly mobile decision makers, transfer...

MONGKIE: an integrated tool for network analysis and visualization for multi-omics data.

Science.gov (United States)

Jang, Yeongjun; Yu, Namhee; Seo, Jihae; Kim, Sun; Lee, Sanghyuk

2016-03-18

Network-based integrative analysis is a powerful technique for extracting biological insights from multilayered omics data such as somatic mutations, copy number variations, and gene expression data. However, integrated analysis of multi-omics data is quite complicated and can hardly be done in an automated way. Thus, a powerful interactive visual mining tool supporting diverse analysis algorithms for identification of driver genes and regulatory modules is much needed. Here, we present a software platform that integrates network visualization with omics data analysis tools seamlessly. The visualization unit supports various options for displaying multi-omics data as well as unique network models for describing sophisticated biological networks such as complex biomolecular reactions. In addition, we implemented diverse in-house algorithms for network analysis including network clustering and over-representation analysis. Novel functions include facile definition and optimized visualization of subgroups, comparison of a series of data sets in an identical network by data-to-visual mapping and subsequent overlaying function, and management of custom interaction networks. Utility of MONGKIE for network-based visual data mining of multi-omics data was demonstrated by analysis of the TCGA glioblastoma data. MONGKIE was developed in Java based on the NetBeans plugin architecture, thus being OS-independent with intrinsic support of module extension by third-party developers. We believe that MONGKIE would be a valuable addition to network analysis software by supporting many unique features and visualization options, especially for analysing multi-omics data sets in cancer and other diseases. .

Biomolecular bases of the senescence process and cancer. A new approach to oncological treatment linked to ageing.

Science.gov (United States)

Badiola, Iker; Santaolalla, Francisco; Garcia-Gallastegui, Patricia; Ana, Sánchez-Del Rey; Unda, Fernando; Ibarretxe, Gaskon

2015-09-01

Human ageing is associated with a gradual decline in the physiological functions of the body at multiple levels and it is a key risk factor for many diseases, including cancer. Ageing process is intimately related to widespread cellular senescence, characterised by an irreversible loss of proliferative capacity and altered functioning associated with telomere attrition, accumulation of DNA damage and compromised mitochondrial and metabolic function. Tumour and senescent cells may be generated in response to the same stimuli, where either cellular senescence or transformation would constitute two opposite outcomes of the same degenerative process. This paper aims to review the state of knowledge on the biomolecular relationship between cellular senescence, ageing and cancer. Importantly, many of the cell signalling pathways that are found to be altered during both cellular senescence and tumourigenesis are regulated through shared epigenetic mechanisms and, therefore, they are potentially reversible. MicroRNAs are emerging as pivotal players linking ageing and cancer. These small RNA molecules have generated great interest from the point of view of future clinical therapy for cancer because successful experimental results have been obtained in animal models. Micro-RNA therapies for cancer are already being tested in clinical phase trials. These findings have potential importance in cancer treatment in aged people although further research-based knowledge is needed to convert them into an effective molecular therapies for cancer linked to ageing. Copyright © 2015 Elsevier B.V. All rights reserved.

Association between resting-state brain network topological organization and creative ability: Evidence from a multiple linear regression model.

Science.gov (United States)

Jiao, Bingqing; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Li, Junchao; Cai, Yuxuan; Gao, Mengxia; Gao, Zhenni; Chang, Song; Huang, Ruiwang; Liu, Ming

2017-10-01

Previous studies have indicated a tight linkage between resting-state functional connectivity of the human brain and creative ability. This study aimed to further investigate the association between the topological organization of resting-state brain networks and creativity. Therefore, we acquired resting-state fMRI data from 22 high-creativity participants and 22 low-creativity participants (as determined by their Torrance Tests of Creative Thinking scores). We then constructed functional brain networks for each participant and assessed group differences in network topological properties before exploring the relationships between respective network topological properties and creative ability. We identified an optimized organization of intrinsic brain networks in both groups. However, compared with low-creativity participants, high-creativity participants exhibited increased global efficiency and substantially decreased path length, suggesting increased efficiency of information transmission across brain networks in creative individuals. Using a multiple linear regression model, we further demonstrated that regional functional integration properties (i.e., the betweenness centrality and global efficiency) of brain networks, particularly the default mode network (DMN) and sensorimotor network (SMN), significantly predicted the individual differences in creative ability. Furthermore, the associations between network regional properties and creative performance were creativity-level dependent, where the difference in the resource control component may be important in explaining individual difference in creative performance. These findings provide novel insights into the neural substrate of creativity and may facilitate objective identification of creative ability. Copyright © 2017 Elsevier B.V. All rights reserved.

Efficient Cancer Detection Using Multiple Neural Networks.

Science.gov (United States)

Shell, John; Gregory, William D

2017-01-01

The inspection of live excised tissue specimens to ascertain malignancy is a challenging task in dermatopathology and generally in histopathology. We introduce a portable desktop prototype device that provides highly accurate neural network classification of malignant and benign tissue. The handheld device collects 47 impedance data samples from 1 Hz to 32 MHz via tetrapolar blackened platinum electrodes. The data analysis was implemented with six different backpropagation neural networks (BNN). A data set consisting of 180 malignant and 180 benign breast tissue data files in an approved IRB study at the Aurora Medical Center, Milwaukee, WI, USA, were utilized as a neural network input. The BNN structure consisted of a multi-tiered consensus approach autonomously selecting four of six neural networks to determine a malignant or benign classification. The BNN analysis was then compared with the histology results with consistent sensitivity of 100% and a specificity of 100%. This implementation successfully relied solely on statistical variation between the benign and malignant impedance data and intricate neural network configuration. This device and BNN implementation provides a novel approach that could be a valuable tool to augment current medical practice assessment of the health of breast, squamous, and basal cell carcinoma and other excised tissue without requisite tissue specimen expertise. It has the potential to provide clinical management personnel with a fast non-invasive accurate assessment of biopsied or sectioned excised tissue in various clinical settings.

MIMO Communication for Cellular Networks

CERN Document Server

Huang, Howard; Venkatesan, Sivarama

2012-01-01

As the theoretical foundations of multiple-antenna techniques evolve and as these multiple-input multiple-output (MIMO) techniques become essential for providing high data rates in wireless systems, there is a growing need to understand the performance limits of MIMO in practical networks. To address this need, MIMO Communication for Cellular Networks presents a systematic description of MIMO technology classes and a framework for MIMO system design that takes into account the essential physical-layer features of practical cellular networks. In contrast to works that focus on the theoretical performance of abstract MIMO channels, MIMO Communication for Cellular Networks emphasizes the practical performance of realistic MIMO systems. A unified set of system simulation results highlights relative performance gains of different MIMO techniques and provides insights into how best to use multiple antennas in cellular networks under various conditions. MIMO Communication for Cellular Networks describes single-user,...

An effective hierarchical model for the biomolecular covalent bond: an approach integrating artificial chemistry and an actual terrestrial life system.

Science.gov (United States)

Oohashi, Tsutomu; Ueno, Osamu; Maekawa, Tadao; Kawai, Norie; Nishina, Emi; Honda, Manabu

2009-01-01

Under the AChem paradigm and the programmed self-decomposition (PSD) model, we propose a hierarchical model for the biomolecular covalent bond (HBCB model). This model assumes that terrestrial organisms arrange their biomolecules in a hierarchical structure according to the energy strength of their covalent bonds. It also assumes that they have evolutionarily selected the PSD mechanism of turning biological polymers (BPs) into biological monomers (BMs) as an efficient biomolecular recycling strategy We have examined the validity and effectiveness of the HBCB model by coordinating two complementary approaches: biological experiments using existent terrestrial life, and simulation experiments using an AChem system. Biological experiments have shown that terrestrial life possesses a PSD mechanism as an endergonic, genetically regulated process and that hydrolysis, which decomposes a BP into BMs, is one of the main processes of such a mechanism. In simulation experiments, we compared different virtual self-decomposition processes. The virtual species in which the self-decomposition process mainly involved covalent bond cleavage from a BP to BMs showed evolutionary superiority over other species in which the self-decomposition process involved cleavage from BP to classes lower than BM. These converging findings strongly support the existence of PSD and the validity and effectiveness of the HBCB model.

ECOMICS: a web-based toolkit for investigating the biomolecular web in ecosystems using a trans-omics approach.

Directory of Open Access Journals (Sweden)

Yoshiyuki Ogata

Full Text Available Ecosystems can be conceptually thought of as interconnected environmental and metabolic systems, in which small molecules to macro-molecules interact through diverse networks. State-of-the-art technologies in post-genomic science offer ways to inspect and analyze this biomolecular web using omics-based approaches. Exploring useful genes and enzymes, as well as biomass resources responsible for anabolism and catabolism within ecosystems will contribute to a better understanding of environmental functions and their application to biotechnology. Here we present ECOMICS, a suite of web-based tools for ECosystem trans-OMICS investigation that target metagenomic, metatranscriptomic, and meta-metabolomic systems, including biomacromolecular mixtures derived from biomass. ECOMICS is made of four integrated webtools. E-class allows for the sequence-based taxonomic classification of eukaryotic and prokaryotic ribosomal data and the functional classification of selected enzymes. FT2B allows for the digital processing of NMR spectra for downstream metabolic or chemical phenotyping. Bm-Char allows for statistical assignment of specific compounds found in lignocellulose-based biomass, and HetMap is a data matrix generator and correlation calculator that can be applied to trans-omics datasets as analyzed by these and other web tools. This web suite is unique in that it allows for the monitoring of biomass metabolism in a particular environment, i.e., from macromolecular complexes (FT2DB and Bm-Char to microbial composition and degradation (E-class, and makes possible the understanding of relationships between molecular and microbial elements (HetMap. This website is available to the public domain at: https://database.riken.jp/ecomics/.

Modeling stochasticity in biochemical reaction networks

International Nuclear Information System (INIS)

Constantino, P H; Vlysidis, M; Smadbeck, P; Kaznessis, Y N

2016-01-01

Small biomolecular systems are inherently stochastic. Indeed, fluctuations of molecular species are substantial in living organisms and may result in significant variation in cellular phenotypes. The chemical master equation (CME) is the most detailed mathematical model that can describe stochastic behaviors. However, because of its complexity the CME has been solved for only few, very small reaction networks. As a result, the contribution of CME-based approaches to biology has been very limited. In this review we discuss the approach of solving CME by a set of differential equations of probability moments, called moment equations. We present different approaches to produce and to solve these equations, emphasizing the use of factorial moments and the zero information entropy closure scheme. We also provide information on the stability analysis of stochastic systems. Finally, we speculate on the utility of CME-based modeling formalisms, especially in the context of synthetic biology efforts. (topical review)

Multiple Transcoding Impact on Speech Quality in Ideal Network Conditions

Directory of Open Access Journals (Sweden)

Martin Mikulec

2015-01-01

Full Text Available This paper deals with the impact of transcoding on the speech quality. We have focused mainly on the transcoding between codecs without the negative influence of the network parameters such as packet loss and delay. It has ensured objective and repeatable results from our measurement. The measurement was performed on the Transcoding Measuring System developed especially for this purpose. The system is based on the open source projects and is useful as a design tool for VoIP system administrators. The paper compares the most used codecs from the transcoding perspective. The multiple transcoding between G711, GSM and G729 codecs were performed and the speech quality of these calls was evaluated. The speech quality was measured by Perceptual Evaluation of Speech Quality method, which provides results in Mean Opinion Score used to describe the speech quality on a scale from 1 to 5. The obtained results indicate periodical speech quality degradation on every transcoding between two codecs.

Identification of Multiple-Mode Linear Models Based on Particle Swarm Optimizer with Cyclic Network Mechanism

Directory of Open Access Journals (Sweden)

Tae-Hyoung Kim

2017-01-01

Full Text Available This paper studies the metaheuristic optimizer-based direct identification of a multiple-mode system consisting of a finite set of linear regression representations of subsystems. To this end, the concept of a multiple-mode linear regression model is first introduced, and its identification issues are established. A method for reducing the identification problem for multiple-mode models to an optimization problem is also described in detail. Then, to overcome the difficulties that arise because the formulated optimization problem is inherently ill-conditioned and nonconvex, the cyclic-network-topology-based constrained particle swarm optimizer (CNT-CPSO is introduced, and a concrete procedure for the CNT-CPSO-based identification methodology is developed. This scheme requires no prior knowledge of the mode transitions between subsystems and, unlike some conventional methods, can handle a large amount of data without difficulty during the identification process. This is one of the distinguishing features of the proposed method. The paper also considers an extension of the CNT-CPSO-based identification scheme that makes it possible to simultaneously obtain both the optimal parameters of the multiple submodels and a certain decision parameter involved in the mode transition criteria. Finally, an experimental setup using a DC motor system is established to demonstrate the practical usability of the proposed metaheuristic optimizer-based identification scheme for developing a multiple-mode linear regression model.

ATR-FTIR Spectroscopic Evidence for Biomolecular Phosphorus and Carboxyl Groups Facilitating Bacterial Adhesion to Iron Oxides

Science.gov (United States)

Parikh, Sanjai J.; Mukome, Fungai N.D.; Zhang, Xiaoming

2014-01-01

Attenuated total reflectance (ATR) Fourier transform infrared (FTIR) spectroscopy has been used to probe the binding of bacteria to hematite (α-Fe2O3) and goethite (α-FeOOH). In situ ATR-FTIR experiments with bacteria (Pseudomonas putida, P. aeruginosa, Escherichia coli), mixed amino acids, polypeptide extracts, deoxyribonucleic acid (DNA), and a suite of model compounds were conducted. These compounds represent carboxyl, catecholate, amide, and phosphate groups present in siderophores, amino acids, polysaccharides, phospholipids, and DNA. Due in part to the ubiquitous presence of carboxyl groups in biomolecules, numerous IR peaks corresponding to outer-sphere or unbound (1400 cm−1) and inner-sphere (1310-1320 cm−1) coordinated carboxyl groups are noted following reaction of bacteria and biomolecules with α-Fe2O3 and α-FeOOH. However, the data also reveal that the presence of low-level amounts (i.e., 0.45-0.79%) of biomolecular phosphorous groups result in strong IR bands at ~1043 cm−1, corresponding to inner-sphere Fe-O-P bonds, underscoring the importance of bacteria associated P-containing groups in biomolecule and cell adhesion. Spectral comparisons also reveal slightly greater P-O-Fe contributions for bacteria (Pseudomonad, E. coli) deposited on α-FeOOH, as compared to α-Fe2O3. This data demonstrates that slight differences in bacterial adhesion to Fe oxides can be attributed to bacterial species and Fe-oxide minerals. However, more importantly, the strong binding affinity of phosphate in all bacteria samples to both Fe-oxides results in the formation of inner-sphere Fe-O-P bonds, signifying the critical role of biomolecular P in the initiation of bacterial adhesion. PMID:24859052

Multiple Hub Network Choice in the Liberalized European Market

Science.gov (United States)

Berechman, Joseph; deWit, Jaap

1997-01-01

. In the meantime, open skies agreements have been concluded between the USA and most of the EU member states to facilitate strategic alliances between airlines of the states involved. As a result of this on-going liberalization the model of the single 'national' carrier using the national home base as its single hub for the designated third, fourth and sixth freedom operations will stepwise disappear. Within the EU the concept of the national carrier has already been replaced by that of the community carrier. State ownership in more and more European carriers is reduced. On the longer run mergers or even bankruptcy will further undermine the "single national carrier - single national hub" model in Europe. In the meantime, strategic alliances between national carriers in Europe will already reduce the airlines' loyalty to a single airport. Profit maximization and accountability to share holders will supersede the loyalty of these newly emerging alliances, probably looking for the opportunities of a multiple hub network to adequately cover the whole European market. As a consequence, some European airports might see a substantial decline in arriving, departing and transfer traffic, thus in revenues and financial solvency, as well as in their connection to other inter-continental and intra-European destinations. At the same time, other airports might realize a significant increase in traffic as they will be sought after by the profit maximizing airlines as their major gateway hubs. Which will be the losing airports and which will be the winning ones? Can airports anticipate the actions of airlines in deregulated markets and utilize policies which will improve their relative position? If so, what should be these anticipatory policies? These questions become the more urgent, since an increasing number of major European airports will be privatized in the near future. Although increasing airport congestion in Europe will also be reflected in a growing demand pressure for

Single-shot secure quantum network coding on butterfly network with free public communication

Science.gov (United States)

Owari, Masaki; Kato, Go; Hayashi, Masahito

2018-01-01

Quantum network coding on the butterfly network has been studied as a typical example of quantum multiple cast network. We propose a secure quantum network code for the butterfly network with free public classical communication in the multiple unicast setting under restricted eavesdropper’s power. This protocol certainly transmits quantum states when there is no attack. We also show the secrecy with shared randomness as additional resource when the eavesdropper wiretaps one of the channels in the butterfly network and also derives the information sending through public classical communication. Our protocol does not require verification process, which ensures single-shot security.

A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network

Directory of Open Access Journals (Sweden)

Ji She

2016-12-01

Full Text Available Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance.

REVIEW ARTICLE: How do biomolecular systems speed up and regulate rates?

Science.gov (United States)

Zhou, Huan-Xiang

2005-09-01

The viability of a biological system depends upon careful regulation of the rates of various processes. These rates have limits imposed by intrinsic chemical or physical steps (e.g., diffusion). These limits can be expanded by interactions and dynamics of the biomolecules. For example, (a) a chemical reaction is catalyzed when its transition state is preferentially bound to an enzyme; (b) the folding of a protein molecule is speeded up by specific interactions within the transition-state ensemble and may be assisted by molecular chaperones; (c) the rate of specific binding of a protein molecule to a cellular target can be enhanced by mechanisms such as long-range electrostatic interactions, nonspecific binding and folding upon binding; (d) directional movement of motor proteins is generated by capturing favorable Brownian motion through intermolecular binding energy; and (e) conduction and selectivity of ions through membrane channels are controlled by interactions and the dynamics of channel proteins. Simple physical models are presented here to illustrate these processes and provide a unifying framework for understanding speed attainment and regulation in biomolecular systems.

Uma abordagem visual para análise comparativa de redes biomoleculares com apoio de diagramas de Venn

OpenAIRE

Henry Heberle

2014-01-01

Sistemas biológicos podem ser representados por redes que armazenam não apenas informações de conectividade, mas também informações de características de seus nós. No contexto biomolecular, esses nós podem representar proteínas, metabólitos, entre outros tipos de moléculas. Cada molécula possui características anotadas e armazenadas em bases de dados como o Gene Ontology. A comparação visual dessas redes depende de ferramentas que permitam o usuário identificar diferenças e semelhanças entre ...

Global robust stability of neural networks with multiple discrete delays and distributed delays

International Nuclear Information System (INIS)

Gao Ming; Cui Baotong

2009-01-01

The problem of global robust stability is investigated for a class of uncertain neural networks with both multiple discrete time-varying delays and distributed time-varying delays. The uncertainties are assumed to be of norm-bounded form and the activation functions are supposed to be bounded and globally Lipschitz continuous. Based on the Lyapunov stability theory and linear matrix inequality technique, some robust stability conditions guaranteeing the global robust convergence of the equilibrium point are derived. The proposed LMI-based criteria are computationally efficient as they can be easily checked by using recently developed algorithms in solving LMIs. Two examples are given to show the effectiveness of the proposed results.

Elastic tracking versus neural network tracking for very high multiplicity problems

International Nuclear Information System (INIS)

Harlander, M.; Gyulassy, M.

1991-04-01

A new Elastic Tracking (ET) algorithm is proposed for finding tracks in very high multiplicity and noisy environments. It is based on a dynamical reinterpretation and generalization of the Radon transform and is related to elastic net algorithms for geometrical optimization. ET performs an adaptive nonlinear fit to noisy data with a variable number of tracks. Its numerics is more efficient than that of the traditional Radon or Hough transform method because it avoids binning of phase space and the costly search for valid minima. Spurious local minima are avoided in ET by introducing a time-dependent effective potential. The method is shown to be very robust to noise and measurement error and extends tracking capabilities to much higher track densities than possible via local road finding or even the novel Denby-Peterson neural network tracking algorithms. 12 refs., 2 figs

A comparison of multiple regression and neural network techniques for mapping in situ pCO2 data

International Nuclear Information System (INIS)

Lefevre, Nathalie; Watson, Andrew J.; Watson, Adam R.

2005-01-01

Using about 138,000 measurements of surface pCO 2 in the Atlantic subpolar gyre (50-70 deg N, 60-10 deg W) during 1995-1997, we compare two methods of interpolation in space and time: a monthly distribution of surface pCO 2 constructed using multiple linear regressions on position and temperature, and a self-organizing neural network approach. Both methods confirm characteristics of the region found in previous work, i.e. the subpolar gyre is a sink for atmospheric CO 2 throughout the year, and exhibits a strong seasonal variability with the highest undersaturations occurring in spring and summer due to biological activity. As an annual average the surface pCO 2 is higher than estimates based on available syntheses of surface pCO 2 . This supports earlier suggestions that the sink of CO 2 in the Atlantic subpolar gyre has decreased over the last decade instead of increasing as previously assumed. The neural network is able to capture a more complex distribution than can be well represented by linear regressions, but both techniques agree relatively well on the average values of pCO 2 and derived fluxes. However, when both techniques are used with a subset of the data, the neural network predicts the remaining data to a much better accuracy than the regressions, with a residual standard deviation ranging from 3 to 11 μatm. The subpolar gyre is a net sink of CO 2 of 0.13 Gt-C/yr using the multiple linear regressions and 0.15 Gt-C/yr using the neural network, on average between 1995 and 1997. Both calculations were made with the NCEP monthly wind speeds converted to 10 m height and averaged between 1995 and 1997, and using the gas exchange coefficient of Wanninkhof

Versatile single-molecule multi-color excitation and detection fluorescence setup for studying biomolecular dynamics

KAUST Repository

Sobhy, M. A.

2011-11-07

Single-molecule fluorescence imaging is at the forefront of tools applied to study biomolecular dynamics both in vitro and in vivo. The ability of the single-molecule fluorescence microscope to conduct simultaneous multi-color excitation and detection is a key experimental feature that is under continuous development. In this paper, we describe in detail the design and the construction of a sophisticated and versatile multi-color excitation and emission fluorescence instrument for studying biomolecular dynamics at the single-molecule level. The setup is novel, economical and compact, where two inverted microscopes share a laser combiner module with six individual laser sources that extend from 400 to 640 nm. Nonetheless, each microscope can independently and in a flexible manner select the combinations, sequences, and intensities of the excitation wavelengths. This high flexibility is achieved by the replacement of conventional mechanical shutters with acousto-optic tunable filter (AOTF). The use of AOTF provides major advancement by controlling the intensities, duration, and selection of up to eight different wavelengths with microsecond alternation time in a transparent and easy manner for the end user. To our knowledge this is the first time AOTF is applied to wide-field total internal reflection fluorescence (TIRF) microscopy even though it has been commonly used in multi-wavelength confocal microscopy. The laser outputs from the combiner module are coupled to the microscopes by two sets of four single-mode optic fibers in order to allow for the optimization of the TIRF angle for each wavelength independently. The emission is split into two or four spectral channels to allow for the simultaneous detection of up to four different fluorophores of wide selection and using many possible excitation and photoactivation schemes. We demonstrate the performance of this new setup by conducting two-color alternating excitation single-molecule fluorescence resonance energy

Adaptive Code Division Multiple Access Protocol for Wireless Network-on-Chip Architectures

Science.gov (United States)

Vijayakumaran, Vineeth

Massive levels of integration following Moore's Law ushered in a paradigm shift in the way on-chip interconnections were designed. With higher and higher number of cores on the same die traditional bus based interconnections are no longer a scalable communication infrastructure. On-chip networks were proposed enabled a scalable plug-and-play mechanism for interconnecting hundreds of cores on the same chip. Wired interconnects between the cores in a traditional Network-on-Chip (NoC) system, becomes a bottleneck with increase in the number of cores thereby increasing the latency and energy to transmit signals over them. Hence, there has been many alternative emerging interconnect technologies proposed, namely, 3D, photonic and multi-band RF interconnects. Although they provide better connectivity, higher speed and higher bandwidth compared to wired interconnects; they also face challenges with heat dissipation and manufacturing difficulties. On-chip wireless interconnects is one other alternative proposed which doesn't need physical interconnection layout as data travels over the wireless medium. They are integrated into a hybrid NOC architecture consisting of both wired and wireless links, which provides higher bandwidth, lower latency, lesser area overhead and reduced energy dissipation in communication. However, as the bandwidth of the wireless channels is limited, an efficient media access control (MAC) scheme is required to enhance the utilization of the available bandwidth. This thesis proposes using a multiple access mechanism such as Code Division Multiple Access (CDMA) to enable multiple transmitter-receiver pairs to send data over the wireless channel simultaneously. It will be shown that such a hybrid wireless NoC with an efficient CDMA based MAC protocol can significantly increase the performance of the system while lowering the energy dissipation in data transfer. In this work it is shown that the wireless NoC with the proposed CDMA based MAC protocol

Modelling of multiple short-length-scale stall cells in an axial compressor using evolved GMDH neural networks

International Nuclear Information System (INIS)

Amanifard, N.; Nariman-Zadeh, N.; Farahani, M.H.; Khalkhali, A.

2008-01-01

Over the past 15 years there have been several research efforts to capture the stall inception nature in axial flow compressors. However previous analytical models could not explain the formation of short-length-scale stall cells. This paper provides a new model based on evolved GMDH neural network for transient evolution of multiple short-length-scale stall cells in an axial compressor. Genetic Algorithms (GAs) are also employed for optimal design of connectivity configuration of such GMDH-type neural networks. In this way, low-pass filter (LPF) pressure trace near the rotor leading edge is modelled with respect to the variation of pressure coefficient, flow rate coefficient, and number of rotor rotations which are defined as inputs

A Hybrid Fuzzy Time Series Approach Based on Fuzzy Clustering and Artificial Neural Network with Single Multiplicative Neuron Model

Directory of Open Access Journals (Sweden)

Ozge Cagcag Yolcu

2013-01-01

Full Text Available Particularly in recent years, artificial intelligence optimization techniques have been used to make fuzzy time series approaches more systematic and improve forecasting performance. Besides, some fuzzy clustering methods and artificial neural networks with different structures are used in the fuzzification of observations and determination of fuzzy relationships, respectively. In approaches considering the membership values, the membership values are determined subjectively or fuzzy outputs of the system are obtained by considering that there is a relation between membership values in identification of relation. This necessitates defuzzification step and increases the model error. In this study, membership values were obtained more systematically by using Gustafson-Kessel fuzzy clustering technique. The use of artificial neural network with single multiplicative neuron model in identification of fuzzy relation eliminated the architecture selection problem as well as the necessity for defuzzification step by constituting target values from real observations of time series. The training of artificial neural network with single multiplicative neuron model which is used for identification of fuzzy relation step is carried out with particle swarm optimization. The proposed method is implemented using various time series and the results are compared with those of previous studies to demonstrate the performance of the proposed method.

Multiple Score Comparison: a network meta-analysis approach to comparison and external validation of prognostic scores

Directory of Open Access Journals (Sweden)

Sarah R. Haile

2017-12-01

Full Text Available Abstract Background Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them. Methods Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined. Results We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small. Conclusions We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties

Multi-Destination Cognitive Radio Relay Network with SWIPT and Multiple Primary Receivers

KAUST Repository

Al-Habob, Ahmed A.

2017-05-12

In this paper, we study the performance of simultaneous wireless information and power transfer (SWIPT) technique in a multi-destination dual-hop underlay cognitive relay network with multiple primary receivers. Information transmission from the secondary source to destinations is performed entirely via a decode- and-forward (DF) relay. The relay is assumed to have no embedded power source and to harvest energy from the source signal using a power splitting (PS) protocol and employing opportunistic scheduling to forward the information to the selected destination. We derive analytical expressions for the outage probability assuming Rayleigh fading channels and considering the energy harvesting efficiency at relay, the source maximum transmit power and primary receivers interference constraints. The system performance is also studied at high signal-to-noise ratio (SNR) values where approximate expressions for the outage probability are provided and analyzed in terms of diversity order and coding gain. Monte-Carlo simulations and some numerical examples are provided to validate the derived expressions and to illustrate the effect of various system parameters on the system performance. In contrast to their conventional counterparts where a multi- destination diversity is usually achieved, the results show that the multi-destination cognitive radio relay networks with the SWIPT technique achieve a constant diversity order of one.

Optimization of Multiple Related Negotiation through Multi-Negotiation Network

Science.gov (United States)

Ren, Fenghui; Zhang, Minjie; Miao, Chunyan; Shen, Zhiqi

In this paper, a Multi-Negotiation Network (MNN) and a Multi- Negotiation Influence Diagram (MNID) are proposed to optimally handle Multiple Related Negotiations (MRN) in a multi-agent system. Most popular, state-of-the-art approaches perform MRN sequentially. However, a sequential procedure may not optimally execute MRN in terms of maximizing the global outcome, and may even lead to unnecessary losses in some situations. The motivation of this research is to use a MNN to handle MRN concurrently so as to maximize the expected utility of MRN. Firstly, both the joint success rate and the joint utility by considering all related negotiations are dynamically calculated based on a MNN. Secondly, by employing a MNID, an agent's possible decision on each related negotiation is reflected by the value of expected utility. Lastly, through comparing expected utilities between all possible policies to conduct MRN, an optimal policy is generated to optimize the global outcome of MRN. The experimental results indicate that the proposed approach can improve the global outcome of MRN in a successful end scenario, and avoid unnecessary losses in an unsuccessful end scenario.

Multiple Regions of a Cortical Network Commonly Encode the Meaning of Words in Multiple Grammatical Positions of Read Sentences.

Science.gov (United States)

Anderson, Andrew James; Lalor, Edmund C; Lin, Feng; Binder, Jeffrey R; Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Raizada, Rajeev D S; Grimm, Scott; Wang, Xixi

2018-05-16

Deciphering how sentence meaning is represented in the brain remains a major challenge to science. Semantically related neural activity has recently been shown to arise concurrently in distributed brain regions as successive words in a sentence are read. However, what semantic content is represented by different regions, what is common across them, and how this relates to words in different grammatical positions of sentences is weakly understood. To address these questions, we apply a semantic model of word meaning to interpret brain activation patterns elicited in sentence reading. The model is based on human ratings of 65 sensory/motor/emotional and cognitive features of experience with words (and their referents). Through a process of mapping functional Magnetic Resonance Imaging activation back into model space we test: which brain regions semantically encode content words in different grammatical positions (e.g., subject/verb/object); and what semantic features are encoded by different regions. In left temporal, inferior parietal, and inferior/superior frontal regions we detect the semantic encoding of words in all grammatical positions tested and reveal multiple common components of semantic representation. This suggests that sentence comprehension involves a common core representation of multiple words' meaning being encoded in a network of regions distributed across the brain.

Multiple dynamical time-scales in networks with hierarchically ...

Indian Academy of Sciences (India)

cists from resistor networks to polymer contact structure to spin interactions in disordered ... the intracellular signalling system to neuronal networks to ecological food ... tion of the key players can be used to develop drugs targeted specifically ...

Comparison of Multiple Linear Regressions and Neural Networks based QSAR models for the design of new antitubercular compounds.

Science.gov (United States)

Ventura, Cristina; Latino, Diogo A R S; Martins, Filomena

2013-01-01

The performance of two QSAR methodologies, namely Multiple Linear Regressions (MLR) and Neural Networks (NN), towards the modeling and prediction of antitubercular activity was evaluated and compared. A data set of 173 potentially active compounds belonging to the hydrazide family and represented by 96 descriptors was analyzed. Models were built with Multiple Linear Regressions (MLR), single Feed-Forward Neural Networks (FFNNs), ensembles of FFNNs and Associative Neural Networks (AsNNs) using four different data sets and different types of descriptors. The predictive ability of the different techniques used were assessed and discussed on the basis of different validation criteria and results show in general a better performance of AsNNs in terms of learning ability and prediction of antitubercular behaviors when compared with all other methods. MLR have, however, the advantage of pinpointing the most relevant molecular characteristics responsible for the behavior of these compounds against Mycobacterium tuberculosis. The best results for the larger data set (94 compounds in training set and 18 in test set) were obtained with AsNNs using seven descriptors (R(2) of 0.874 and RMSE of 0.437 against R(2) of 0.845 and RMSE of 0.472 in MLRs, for test set). Counter-Propagation Neural Networks (CPNNs) were trained with the same data sets and descriptors. From the scrutiny of the weight levels in each CPNN and the information retrieved from MLRs, a rational design of potentially active compounds was attempted. Two new compounds were synthesized and tested against M. tuberculosis showing an activity close to that predicted by the majority of the models. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Bayesian state space models for dynamic genetic network construction across multiple tissues.

Science.gov (United States)

Liang, Yulan; Kelemen, Arpad

2016-08-01

Construction of gene-gene interaction networks and potential pathways is a challenging and important problem in genomic research for complex diseases while estimating the dynamic changes of the temporal correlations and non-stationarity are the keys in this process. In this paper, we develop dynamic state space models with hierarchical Bayesian settings to tackle this challenge for inferring the dynamic profiles and genetic networks associated with disease treatments. We treat both the stochastic transition matrix and the observation matrix time-variant and include temporal correlation structures in the covariance matrix estimations in the multivariate Bayesian state space models. The unevenly spaced short time courses with unseen time points are treated as hidden state variables. Hierarchical Bayesian approaches with various prior and hyper-prior models with Monte Carlo Markov Chain and Gibbs sampling algorithms are used to estimate the model parameters and the hidden state variables. We apply the proposed Hierarchical Bayesian state space models to multiple tissues (liver, skeletal muscle, and kidney) Affymetrix time course data sets following corticosteroid (CS) drug administration. Both simulation and real data analysis results show that the genomic changes over time and gene-gene interaction in response to CS treatment can be well captured by the proposed models. The proposed dynamic Hierarchical Bayesian state space modeling approaches could be expanded and applied to other large scale genomic data, such as next generation sequence (NGS) combined with real time and time varying electronic health record (EHR) for more comprehensive and robust systematic and network based analysis in order to transform big biomedical data into predictions and diagnostics for precision medicine and personalized healthcare with better decision making and patient outcomes.

Community Detection for Multiplex Social Networks Based on Relational Bayesian Networks

DEFF Research Database (Denmark)

Jiang, Jiuchuan; Jaeger, Manfred

2014-01-01

Many techniques have been proposed for community detection in social networks. Most of these techniques are only designed for networks defined by a single relation. However, many real networks are multiplex networks that contain multiple types of relations and different attributes on the nodes...

Biomolecular Nano-Flow-Sensor to Measure Near-Surface Flow

Directory of Open Access Journals (Sweden)

Noji Hiroyuki

2009-01-01

Full Text Available Abstract We have proposed and experimentally demonstrated that the measurement of the near-surface flow at the interface between a liquid and solid using a 10 nm-sized biomolecular motor of F1-ATPase as a nano-flow-sensor. For this purpose, we developed a microfluidic test-bed chip to precisely control the liquid flow acting on the F1-ATPase. In order to visualize the rotation of F1-ATPase, several hundreds nanometer-sized particle was immobilized at the rotational axis of F1-ATPase to enhance the rotation to be detected by optical microscopy. The rotational motion of F1-ATPase, which was immobilized on an inner surface of the test-bed chip, was measured to obtain the correlation between the near-surface flow and the rotation speed of F1-ATPase. As a result, we obtained the relationship that the rotation speed of F1-ATPase was linearly decelerated with increasing flow velocity. The mechanism of the correlation between the rotation speed and the near-surface flow remains unclear, however the concept to use biomolecule as a nano-flow-sensor was proofed successfully. (See supplementary material 1 Electronic supplementary material The online version of this article (doi:10.1007/s11671-009-9479-3 contains supplementary material, which is available to authorized users. Click here for file

WMAXC: a weighted maximum clique method for identifying condition-specific sub-network.

Directory of Open Access Journals (Sweden)

Bayarbaatar Amgalan

Full Text Available Sub-networks can expose complex patterns in an entire bio-molecular network by extracting interactions that depend on temporal or condition-specific contexts. When genes interact with each other during cellular processes, they may form differential co-expression patterns with other genes across different cell states. The identification of condition-specific sub-networks is of great importance in investigating how a living cell adapts to environmental changes. In this work, we propose the weighted MAXimum clique (WMAXC method to identify a condition-specific sub-network. WMAXC first proposes scoring functions that jointly measure condition-specific changes to both individual genes and gene-gene co-expressions. It then employs a weaker formula of a general maximum clique problem and relates the maximum scored clique of a weighted graph to the optimization of a quadratic objective function under sparsity constraints. We combine a continuous genetic algorithm and a projection procedure to obtain a single optimal sub-network that maximizes the objective function (scoring function over the standard simplex (sparsity constraints. We applied the WMAXC method to both simulated data and real data sets of ovarian and prostate cancer. Compared with previous methods, WMAXC selected a large fraction of cancer-related genes, which were enriched in cancer-related pathways. The results demonstrated that our method efficiently captured a subset of genes relevant under the investigated condition.

FODA: a novel efficient multiple access protocol for highly dynamic self-organizing networks

Science.gov (United States)

Li, Hantao; Liu, Kai; Zhang, Jun

2005-11-01

Based on the concept of contention reservation for polling transmission and collision prevention strategy for collision resolution, a fair on-demand access (FODA) protocol for supporting node mobility and multihop architecture in highly dynamic self-organizing networks is proposed. In the protocol, a distributed clustering network architecture formed by self-organizing algorithm and a main idea of reserving channel resources to get polling service are adopted, so that the hidden terminal (HT) and exposed terminal (ET) problems existed in traffic transmission due to multihop architecture and wireless transmission can be eliminated completely. In addition, an improved collision prevention scheme based on binary countdown algorithm (BCA), called fair collision prevention (FCP) algorithm, is proposed to greatly eliminate unfair phenomena existed in contention access of newly active ordinary nodes and completely resolve access collisions. Finally, the performance comparison of the FODA protocol with carrier sense multiple access with collision avoidance (CSMA/CA) and polling protocols by OPNET simulation are presented. Simulation results show that the FODA protocol can overcome the disadvantages of CSMA/CA and polling protocols, and achieve higher throughput, lower average message delay and less average message dropping rate.

Identifying multiple influential spreaders by a heuristic clustering algorithm

International Nuclear Information System (INIS)

Bao, Zhong-Kui; Liu, Jian-Guo; Zhang, Hai-Feng

2017-01-01

The problem of influence maximization in social networks has attracted much attention. However, traditional centrality indices are suitable for the case where a single spreader is chosen as the spreading source. Many times, spreading process is initiated by simultaneously choosing multiple nodes as the spreading sources. In this situation, choosing the top ranked nodes as multiple spreaders is not an optimal strategy, since the chosen nodes are not sufficiently scattered in networks. Therefore, one ideal situation for multiple spreaders case is that the spreaders themselves are not only influential but also they are dispersively distributed in networks, but it is difficult to meet the two conditions together. In this paper, we propose a heuristic clustering (HC) algorithm based on the similarity index to classify nodes into different clusters, and finally the center nodes in clusters are chosen as the multiple spreaders. HC algorithm not only ensures that the multiple spreaders are dispersively distributed in networks but also avoids the selected nodes to be very “negligible”. Compared with the traditional methods, our experimental results on synthetic and real networks indicate that the performance of HC method on influence maximization is more significant. - Highlights: • A heuristic clustering algorithm is proposed to identify the multiple influential spreaders in complex networks. • The algorithm can not only guarantee the selected spreaders are sufficiently scattered but also avoid to be “insignificant”. • The performance of our algorithm is generally better than other methods, regardless of real networks or synthetic networks.

Identifying multiple influential spreaders by a heuristic clustering algorithm

Energy Technology Data Exchange (ETDEWEB)

Bao, Zhong-Kui [School of Mathematical Science, Anhui University, Hefei 230601 (China); Liu, Jian-Guo [Data Science and Cloud Service Research Center, Shanghai University of Finance and Economics, Shanghai, 200133 (China); Zhang, Hai-Feng, E-mail: haifengzhang1978@gmail.com [School of Mathematical Science, Anhui University, Hefei 230601 (China); Department of Communication Engineering, North University of China, Taiyuan, Shan' xi 030051 (China)

2017-03-18

The problem of influence maximization in social networks has attracted much attention. However, traditional centrality indices are suitable for the case where a single spreader is chosen as the spreading source. Many times, spreading process is initiated by simultaneously choosing multiple nodes as the spreading sources. In this situation, choosing the top ranked nodes as multiple spreaders is not an optimal strategy, since the chosen nodes are not sufficiently scattered in networks. Therefore, one ideal situation for multiple spreaders case is that the spreaders themselves are not only influential but also they are dispersively distributed in networks, but it is difficult to meet the two conditions together. In this paper, we propose a heuristic clustering (HC) algorithm based on the similarity index to classify nodes into different clusters, and finally the center nodes in clusters are chosen as the multiple spreaders. HC algorithm not only ensures that the multiple spreaders are dispersively distributed in networks but also avoids the selected nodes to be very “negligible”. Compared with the traditional methods, our experimental results on synthetic and real networks indicate that the performance of HC method on influence maximization is more significant. - Highlights: • A heuristic clustering algorithm is proposed to identify the multiple influential spreaders in complex networks. • The algorithm can not only guarantee the selected spreaders are sufficiently scattered but also avoid to be “insignificant”. • The performance of our algorithm is generally better than other methods, regardless of real networks or synthetic networks.

Optimal use of data in parallel tempering simulations for the construction of discrete-state Markov models of biomolecular dynamics.

Science.gov (United States)

Prinz, Jan-Hendrik; Chodera, John D; Pande, Vijay S; Swope, William C; Smith, Jeremy C; Noé, Frank

2011-06-28

Parallel tempering (PT) molecular dynamics simulations have been extensively investigated as a means of efficient sampling of the configurations of biomolecular systems. Recent work has demonstrated how the short physical trajectories generated in PT simulations of biomolecules can be used to construct the Markov models describing biomolecular dynamics at each simulated temperature. While this approach describes the temperature-dependent kinetics, it does not make optimal use of all available PT data, instead estimating the rates at a given temperature using only data from that temperature. This can be problematic, as some relevant transitions or states may not be sufficiently sampled at the temperature of interest, but might be readily sampled at nearby temperatures. Further, the comparison of temperature-dependent properties can suffer from the false assumption that data collected from different temperatures are uncorrelated. We propose here a strategy in which, by a simple modification of the PT protocol, the harvested trajectories can be reweighted, permitting data from all temperatures to contribute to the estimated kinetic model. The method reduces the statistical uncertainty in the kinetic model relative to the single temperature approach and provides estimates of transition probabilities even for transitions not observed at the temperature of interest. Further, the method allows the kinetics to be estimated at temperatures other than those at which simulations were run. We illustrate this method by applying it to the generation of a Markov model of the conformational dynamics of the solvated terminally blocked alanine peptide.

Network formation under heterogeneous costs: The multiple group model

NARCIS (Netherlands)

Kamphorst, J.J.A.; van der Laan, G.

2007-01-01

It is widely recognized that the shape of networks influences both individual and aggregate behavior. This raises the question which types of networks are likely to arise. In this paper we investigate a model of network formation, where players are divided into groups and the costs of a link between

Single-Cell Biomolecular Analysis of Coral Algal Symbionts Reveals Opposing Metabolic Responses to Heat Stress and Expulsion

Directory of Open Access Journals (Sweden)

Katherina Petrou

2018-03-01

Full Text Available The success of corals in nutrient poor environments is largely attributed to the symbiosis between the cnidarian host and its intracellular alga. Warm water anomalies have been shown to destabilize this symbiosis, yet detailed analysis of the effect of temperature and expulsion on cell-specific carbon and nutrient allocation in the symbiont is limited. Here, we exposed colonies of the hard coral Acropora millepora to heat stress and using synchrotron-based infrared microspectroscopy measured the biomolecular profiles of individual in hospite and expelled symbiont cells at an acute state of bleaching. Our results showed symbiont metabolic profiles to be remarkably distinct with heat stress and expulsion, where the two effectors elicited opposing metabolic adjustments independent of treatment or cell type. Elevated temperature resulted in biomolecular changes reflecting cellular stress, with relative increases in free amino acids and phosphorylation of molecules and a concomitant decline in protein content, suggesting protein modification and degradation. This contrasted with the metabolic profiles of expelled symbionts, which showed relative decreases in free amino acids and phosphorylated molecules, but increases in proteins and lipids, suggesting expulsion lessens the overall effect of heat stress on the metabolic signature of the algal symbionts. Interestingly, the combined effects of expulsion and thermal stress were additive, reducing the overall shifts in all biomolecules, with the notable exception of the significant accumulation of lipids and saturated fatty acids. This first use of a single-cell metabolomics approach on the coral symbiosis provides novel insight into coral bleaching and emphasizes the importance of a single-cell approach to demark the cell-to-cell variability in the physiology of coral cellular populations.

H∞ Filtering for Networked Markovian Jump Systems with Multiple Stochastic Communication Delays

Directory of Open Access Journals (Sweden)

Hui Dong

2015-01-01

Full Text Available This paper is concerned with the H∞ filtering for a class of networked Markovian jump systems with multiple communication delays. Due to the existence of communication constraints, the measurement signal cannot arrive at the filter completely on time, and the stochastic communication delays are considered in the filter design. Firstly, a set of stochastic variables is introduced to model the occurrence probabilities of the delays. Then based on the stochastic system approach, a sufficient condition is obtained such that the filtering error system is stable in the mean-square sense and with a prescribed H∞ disturbance attenuation level. The optimal filter gain parameters can be determined by solving a convex optimization problem. Finally, a simulation example is given to show the effectiveness of the proposed filter design method.

Parallel computing and networking; Heiretsu keisanki to network

Energy Technology Data Exchange (ETDEWEB)

Asakawa, E; Tsuru, T [Japan National Oil Corp., Tokyo (Japan); Matsuoka, T [Japan Petroleum Exploration Co. Ltd., Tokyo (Japan)

1996-05-01

This paper describes the trend of parallel computers used in geophysical exploration. Around 1993 was the early days when the parallel computers began to be used for geophysical exploration. Classification of these computers those days was mainly MIMD (multiple instruction stream, multiple data stream), SIMD (single instruction stream, multiple data stream) and the like. Parallel computers were publicized in the 1994 meeting of the Geophysical Exploration Society as a `high precision imaging technology`. Concerning the library of parallel computers, there was a shift to PVM (parallel virtual machine) in 1993 and to MPI (message passing interface) in 1995. In addition, the compiler of FORTRAN90 was released with support implemented for data parallel and vector computers. In 1993, networks used were Ethernet, FDDI, CDDI and HIPPI. In 1995, the OC-3 products under ATM began to propagate. However, ATM remains to be an interoffice high speed network because the ATM service has not spread yet for the public network. 1 ref.

A low complexity algorithm for multiple relay selection in two-way relaying Cognitive Radio networks

KAUST Repository

Alsharoa, Ahmad M.

2013-06-01

In this paper, a multiple relay selection scheme for two-way relaying cognitive radio network is investigated. We consider a cooperative Cognitive Radio (CR) system with spectrum sharing scenario using Amplify-and-Forward (AF) protocol, where licensed users and unlicensed users operate on the same frequency band. The main objective is to maximize the sum rate of the unlicensed users allowed to share the spectrum with the licensed users by respecting a tolerated interference threshold. A practical low complexity heuristic approach is proposed to solve our formulated optimization problem. Selected numerical results show that the proposed algorithm reaches a performance close to the performance of the optimal multiple relay selection scheme either with discrete or continuous power distributions while providing a considerable saving in terms of computational complexity. In addition, these results show that our proposed scheme significantly outperforms the single relay selection scheme. © 2013 IEEE.

Review of Transducer Principles for Label-Free Biomolecular Interaction Analysis

Directory of Open Access Journals (Sweden)

Janos Vörös

2011-07-01

Full Text Available Label-free biomolecular interaction analysis is an important technique to study the chemical binding between e.g., protein and protein or protein and small molecule in real-time. The parameters obtained with this technique, such as the affinity, are important for drug development. While the surface plasmon resonance (SPR instruments are most widely used, new types of sensors are emerging. These developments are generally driven by the need for higher throughput, lower sample consumption or by the need of complimentary information to the SPR data. This review aims to give an overview about a wide range of sensor transducers, the working principles and the peculiarities of each technology, e.g., concerning the set-up, sensitivity, sensor size or required sample volume. Starting from optical technologies like the SPR and waveguide based sensors, acoustic sensors like the quartz crystal microbalance (QCM and the film bulk acoustic resonator (FBAR, calorimetric and electrochemical sensors are covered. Technologies long established in the market are presented together with those newly commercially available and with technologies in the early development stage. Finally, the commercially available instruments are summarized together with their sensitivity and the number of sensors usable in parallel and an outlook for potential future developments is given.

A Spectrum Handoff Scheme for Optimal Network Selection in NEMO Based Cognitive Radio Vehicular Networks

Directory of Open Access Journals (Sweden)

Krishan Kumar

2017-01-01

Full Text Available When a mobile network changes its point of attachments in Cognitive Radio (CR vehicular networks, the Mobile Router (MR requires spectrum handoff. Network Mobility (NEMO in CR vehicular networks is concerned with the management of this movement. In future NEMO based CR vehicular networks deployment, multiple radio access networks may coexist in the overlapping areas having different characteristics in terms of multiple attributes. The CR vehicular node may have the capability to make call for two or more types of nonsafety services such as voice, video, and best effort simultaneously. Hence, it becomes difficult for MR to select optimal network for the spectrum handoff. This can be done by performing spectrum handoff using Multiple Attributes Decision Making (MADM methods which is the objective of the paper. The MADM methods such as grey relational analysis and cost based methods are used. The application of MADM methods provides wider and optimum choice among the available networks with quality of service. Numerical results reveal that the proposed scheme is effective for spectrum handoff decision for optimal network selection with reduced complexity in NEMO based CR vehicular networks.

Phylogeny and evolutionary histories of Pyrus L. revealed by phylogenetic trees and networks based on data from multiple DNA sequences

Science.gov (United States)

Reconstructing the phylogeny of Pyrus has been difficult due to the wide distribution of the genus and lack of informative data. In this study, we collected 110 accessions representing 25 Pyrus species and constructed both phylogenetic trees and phylogenetic networks based on multiple DNA sequence d...

Optimal planning of multiple distributed generation sources in distribution networks: A new approach

Energy Technology Data Exchange (ETDEWEB)

AlRashidi, M.R., E-mail: malrash2002@yahoo.com [Department of Electrical Engineering, College of Technological Studies, Public Authority for Applied Education and Training (PAAET) (Kuwait); AlHajri, M.F., E-mail: mfalhajri@yahoo.com [Department of Electrical Engineering, College of Technological Studies, Public Authority for Applied Education and Training (PAAET) (Kuwait)

2011-10-15

Highlights: {yields} A new hybrid PSO for optimal DGs placement and sizing. {yields} Statistical analysis to fine tune PSO parameters. {yields} Novel constraint handling mechanism to handle different constraints types. - Abstract: An improved particle swarm optimization algorithm (PSO) is presented for optimal planning of multiple distributed generation sources (DG). This problem can be divided into two sub-problems: the DG optimal size (continuous optimization) and location (discrete optimization) to minimize real power losses. The proposed approach addresses the two sub-problems simultaneously using an enhanced PSO algorithm capable of handling multiple DG planning in a single run. A design of experiment is used to fine tune the proposed approach via proper analysis of PSO parameters interaction. The proposed algorithm treats the problem constraints differently by adopting a radial power flow algorithm to satisfy the equality constraints, i.e. power flows in distribution networks, while the inequality constraints are handled by making use of some of the PSO features. The proposed algorithm was tested on the practical 69-bus power distribution system. Different test cases were considered to validate the proposed approach consistency in detecting optimal or near optimal solution. Results are compared with those of Sequential Quadratic Programming.

Optimal planning of multiple distributed generation sources in distribution networks: A new approach

International Nuclear Information System (INIS)

AlRashidi, M.R.; AlHajri, M.F.

2011-01-01

Highlights: → A new hybrid PSO for optimal DGs placement and sizing. → Statistical analysis to fine tune PSO parameters. → Novel constraint handling mechanism to handle different constraints types. - Abstract: An improved particle swarm optimization algorithm (PSO) is presented for optimal planning of multiple distributed generation sources (DG). This problem can be divided into two sub-problems: the DG optimal size (continuous optimization) and location (discrete optimization) to minimize real power losses. The proposed approach addresses the two sub-problems simultaneously using an enhanced PSO algorithm capable of handling multiple DG planning in a single run. A design of experiment is used to fine tune the proposed approach via proper analysis of PSO parameters interaction. The proposed algorithm treats the problem constraints differently by adopting a radial power flow algorithm to satisfy the equality constraints, i.e. power flows in distribution networks, while the inequality constraints are handled by making use of some of the PSO features. The proposed algorithm was tested on the practical 69-bus power distribution system. Different test cases were considered to validate the proposed approach consistency in detecting optimal or near optimal solution. Results are compared with those of Sequential Quadratic Programming.

Pre-Clinical Tests of an Integrated CMOS Biomolecular Sensor for Cardiac Diseases Diagnosis.

Science.gov (United States)

Lee, Jen-Kuang; Wang, I-Shun; Huang, Chi-Hsien; Chen, Yih-Fan; Huang, Nien-Tsu; Lin, Chih-Ting

2017-11-26

Coronary artery disease and its related complications pose great threats to human health. In this work, we aim to clinically evaluate a CMOS field-effect biomolecular sensor for cardiac biomarkers, cardiac-specific troponin-I (cTnI), N -terminal prohormone brain natriuretic peptide (NT-proBNP), and interleukin-6 (IL-6). The CMOS biosensor is implemented via a standard commercialized 0.35 μm CMOS process. To validate the sensing characteristics, in buffer conditions, the developed CMOS biosensor has identified the detection limits of IL-6, cTnI, and NT-proBNP as being 45 pM, 32 pM, and 32 pM, respectively. In clinical serum conditions, furthermore, the developed CMOS biosensor performs a good correlation with an enzyme-linked immuno-sorbent assay (ELISA) obtained from a hospital central laboratory. Based on this work, the CMOS field-effect biosensor poses good potential for accomplishing the needs of a point-of-care testing (POCT) system for heart disease diagnosis.

Safe design and operation of tank reactors for multiple-reaction networks: uniqueness and multiplicity

NARCIS (Netherlands)

Westerterp, K.R.; Westerink, E.J.

1990-01-01

A method is developed to design a tank reactor in which a network of reactions is carried out. The network is a combination of parallel and consecutive reactions. The method ensures unique operation. Dimensionless groups are used which are either representative of properties of the reaction system

Robust multiple frequency multiple power localization schemes in the presence of multiple jamming attacks.

Directory of Open Access Journals (Sweden)

Ahmed Abdulqader Hussein

Full Text Available Localization of the wireless sensor network is a vital area acquiring an impressive research concern and called upon to expand more with the rising of its applications. As localization is gaining prominence in wireless sensor network, it is vulnerable to jamming attacks. Jamming attacks disrupt communication opportunity among the sender and receiver and deeply impact the localization process, leading to a huge error of the estimated sensor node position. Therefore, detection and elimination of jamming influence are absolutely indispensable. Range-based techniques especially Received Signal Strength (RSS is facing severe impact of these attacks. This paper proposes algorithms based on Combination Multiple Frequency Multiple Power Localization (C-MFMPL and Step Function Multiple Frequency Multiple Power Localization (SF-MFMPL. The algorithms have been tested in the presence of multiple types of jamming attacks including capture and replay, random and constant jammers over a log normal shadow fading propagation model. In order to overcome the impact of random and constant jammers, the proposed method uses two sets of frequencies shared by the implemented anchor nodes to obtain the averaged RSS readings all over the transmitted frequencies successfully. In addition, three stages of filters have been used to cope with the replayed beacons caused by the capture and replay jammers. In this paper the localization performance of the proposed algorithms for the ideal case which is defined by without the existence of the jamming attack are compared with the case of jamming attacks. The main contribution of this paper is to achieve robust localization performance in the presence of multiple jamming attacks under log normal shadow fading environment with a different simulation conditions and scenarios.

RPYFMM: Parallel adaptive fast multipole method for Rotne-Prager-Yamakawa tensor in biomolecular hydrodynamics simulations

Science.gov (United States)

Guan, W.; Cheng, X.; Huang, J.; Huber, G.; Li, W.; McCammon, J. A.; Zhang, B.

2018-06-01

RPYFMM is a software package for the efficient evaluation of the potential field governed by the Rotne-Prager-Yamakawa (RPY) tensor interactions in biomolecular hydrodynamics simulations. In our algorithm, the RPY tensor is decomposed as a linear combination of four Laplace interactions, each of which is evaluated using the adaptive fast multipole method (FMM) (Greengard and Rokhlin, 1997) where the exponential expansions are applied to diagonalize the multipole-to-local translation operators. RPYFMM offers a unified execution on both shared and distributed memory computers by leveraging the DASHMM library (DeBuhr et al., 2016, 2018). Preliminary numerical results show that the interactions for a molecular system of 15 million particles (beads) can be computed within one second on a Cray XC30 cluster using 12,288 cores, while achieving approximately 54% strong-scaling efficiency.

The use of artificial neural network analysis and multiple regression for trap quality evaluation: a case study of the Northern Kuqa Depression of Tarim Basin in western China

Energy Technology Data Exchange (ETDEWEB)

Guangren Shi; Xingxi Zhou; Guangya Zhang; Xiaofeng Shi; Honghui Li [Research Institute of Petroleum Exploration and Development, Beijing (China)

2004-03-01

Artificial neural network analysis is found to be far superior to multiple regression when applied to the evaluation of trap quality in the Northern Kuqa Depression, a gas-rich depression of Tarim Basin in western China. This is because this technique can correlate the complex and non-linear relationship between trap quality and related geological factors, whereas multiple regression can only describe a linear relationship. However, multiple regression can work as an auxiliary tool, as it is suited to high-speed calculations and can indicate the degree of dependence between the trap quality and its related geological factors which artificial neural network analysis cannot. For illustration, we have investigated 30 traps in the Northern Kuqa Depression. For each of the traps, the values of 14 selected geological factors were all known. While geologists were also able to assign individual trap quality values to 27 traps, they were less certain about the values for the other three traps. Multiple regression and artificial neural network analysis were, therefore, respectively used to ascertain these values. Data for the 27 traps were used as known sample data, while the three traps were used as prediction candidates. Predictions from artificial neural network analysis are found to agree with exploration results: where simulation predicted high trap quality, commercial quality flows were afterwards found, and where low trap quality is indicated, no such discoveries have yet been made. On the other hand, multiple regression results indicate the order of dependence of the trap quality on geological factors, which reconciles with what geologists have commonly recognized. We can conclude, therefore, that the application of artificial neural network analysis with the aid of multiple regression to trap evaluation in the Northern Kuqa Depression has been quite successful. To ensure the precision of the above mentioned geological factors and their related parameters for each

Hybrid-Lambda: simulation of multiple merger and Kingman gene genealogies in species networks and species trees.

Science.gov (United States)

Zhu, Sha; Degnan, James H; Goldstien, Sharyn J; Eldon, Bjarki

2015-09-15

There has been increasing interest in coalescent models which admit multiple mergers of ancestral lineages; and to model hybridization and coalescence simultaneously. Hybrid-Lambda is a software package that simulates gene genealogies under multiple merger and Kingman's coalescent processes within species networks or species trees. Hybrid-Lambda allows different coalescent processes to be specified for different populations, and allows for time to be converted between generations and coalescent units, by specifying a population size for each population. In addition, Hybrid-Lambda can generate simulated datasets, assuming the infinitely many sites mutation model, and compute the F ST statistic. As an illustration, we apply Hybrid-Lambda to infer the time of subdivision of certain marine invertebrates under different coalescent processes. Hybrid-Lambda makes it possible to investigate biogeographic concordance among high fecundity species exhibiting skewed offspring distribution.

A New Prime Code for Synchronous Optical Code Division Multiple-Access Networks

Directory of Open Access Journals (Sweden)

Huda Saleh Abbas

2018-01-01

Full Text Available A new spreading code based on a prime code for synchronous optical code-division multiple-access networks that can be used in monitoring applications has been proposed. The new code is referred to as “extended grouped new modified prime code.” This new code has the ability to support more terminal devices than other prime codes. In addition, it patches subsequences with “0s” leading to lower power consumption. The proposed code has an improved cross-correlation resulting in enhanced BER performance. The code construction and parameters are provided. The operating performance, using incoherent on-off keying modulation and incoherent pulse position modulation systems, has been analyzed. The performance of the code was compared with other prime codes. The results demonstrate an improved performance, and a BER floor of 10−9 was achieved.

Collaborative networks: Reference modeling

NARCIS (Netherlands)

Camarinha-Matos, L.M.; Afsarmanesh, H.

2008-01-01

Collaborative Networks: Reference Modeling works to establish a theoretical foundation for Collaborative Networks. Particular emphasis is put on modeling multiple facets of collaborative networks and establishing a comprehensive modeling framework that captures and structures diverse perspectives of

Raman spectroscopy differentiates between sensitive and resistant multiple myeloma cell lines

Science.gov (United States)

Franco, Domenico; Trusso, Sebastiano; Fazio, Enza; Allegra, Alessandro; Musolino, Caterina; Speciale, Antonio; Cimino, Francesco; Saija, Antonella; Neri, Fortunato; Nicolò, Marco S.; Guglielmino, Salvatore P. P.

2017-12-01

Current methods for identifying neoplastic cells and discerning them from their normal counterparts are often nonspecific and biologically perturbing. Here, we show that single-cell micro-Raman spectroscopy can be used to discriminate between resistant and sensitive multiple myeloma cell lines based on their highly reproducible biomolecular spectral signatures. In order to demonstrate robustness of the proposed approach, we used two different cell lines of multiple myeloma, namely MM.1S and U266B1, and their counterparts MM.1R and U266/BTZ-R subtypes, resistant to dexamethasone and bortezomib, respectively. Then, micro-Raman spectroscopy provides an easily accurate and noninvasive method for cancer detection for both research and clinical environments. Characteristic peaks, mostly due to different DNA/RNA ratio, nucleic acids, lipids and protein concentrations, allow for discerning the sensitive and resistant subtypes. We also explored principal component analysis (PCA) for resistant cell identification and classification. Sensitive and resistant cells form distinct clusters that can be defined using just two principal components. The identification of drug-resistant cells by confocal micro-Raman spectroscopy is thus proposed as a clinical tool to assess the development of resistance to glucocorticoids and proteasome inhibitors in myeloma cells.