Silicon Modulators, Switches and Sub-systems for Optical Interconnect

NASA Astrophysics Data System (ADS)

Li, Qi

Silicon photonics is emerging as a promising platform for manufacturing and integrating photonic devices for light generation, modulation, switching and detection. The compatibility with existing CMOS microelectronic foundries and high index contrast in silicon could enable low cost and high performance photonic systems, which find many applications in optical communication, data center networking and photonic network-on-chip. This thesis first develops and demonstrates several experimental work on high speed silicon modulators and switches with record performance and novel functionality. A 8x40 Gb/s transmitter based on silicon microrings is first presented. Then an end-to-end link using microrings for Binary Phase Shift Keying (BPSK) modulation and demodulation is shown, and its performance with conventional BPSK modulation/ demodulation techniques is compared. Next, a silicon traveling-wave Mach- Zehnder modulator is demonstrated at data rate up to 56 Gb/s for OOK modulation and 48 Gb/s for BPSK modulation, showing its capability at high speed communication systems. Then a single silicon microring is shown with 2x2 full crossbar switching functionality, enabling optical interconnects with ultra small footprint. Then several other experiments in the silicon platform are presented, including a fully integrated in-band Optical Signal to Noise Ratio (OSNR) monitor, characterization of optical power upper bound in a silicon microring modulator, and wavelength conversion in a dispersion-engineered waveguide. The last part of this thesis is on network-level application of photonics, specically a broadcast-and-select network based on star coupler is introduced, and its scalability performance is studied. Finally a novel switch architecture for data center networks is discussed, and its benefits as a disaggregated network are presented.

Solar thermal power systems point-focusing distributed receiver technology project. Volume 2: Detailed report

NASA Technical Reports Server (NTRS)

1980-01-01

The accomplishments of the Point-Focusing Distributed Receiver Technology Project during fiscal year 1979 are detailed. Present studies involve designs of modular units that collect and concentrate solar energy via highly reflective, parabolic-shaped dishes. The concentrated energy is then converted to heat in a working fluid, such as hot gas. In modules designed to produce heat for industrial applications, a flexible line conveys the heated fluid from the module to a heat transfer network. In modules designed to produce electricity the fluid carries the heat directly to an engine in a power conversion unit located at the focus of the concentrator. The engine is mechanically linked to an electric generator. A Brayton-cycle engine is currently being developed as the most promising electrical energy converter to meet near-future needs.

Engineering a Blood Vessel Network Module for Body-on-a-Chip Applications.

PubMed

Ryu, Hyunryul; Oh, Soojung; Lee, Hyun Jae; Lee, Jin Young; Lee, Hae Kwang; Jeon, Noo Li

2015-06-01

The blood circulatory system links all organs from one to another to support and maintain each organ's functions consistently. Therefore, blood vessels have been considered as a vital unit. Engineering perfusable functional blood vessels in vitro has been challenging due to difficulties in designing the connection between rigid macroscale tubes and fragile microscale ones. Here, we propose a generalizable method to engineer a "long" perfusable blood vessel network. To form millimeter-scale vessels, fibroblasts were co-cultured with human umbilical vein endothelial cells (HUVECs) in close proximity. In contrast to previous works, in which all cells were permanently placed within the device, we developed a novel method to culture paracrine factor secreting fibroblasts on an O-ring-shaped guide that can be transferred in and out. This approach affords flexibility in co-culture, where the effects of secreted factors can be decoupled. Using this, blood vessels with length up to 2 mm were successfully produced in a reproducible manner (>90%). Because the vessels form a perfusable network within the channel, simple links to inlets and outlets of the device allowed connections to the outside world. The robust and reproducible formation of in vitro engineered vessels can be used as a module to link various organ components as parts of future body-on-a-chip applications. © 2014 Society for Laboratory Automation and Screening.

Model-based diagnostics of gas turbine engine lubrication systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Byington, C.S.

1998-09-01

The objective of the current research was to develop improved methodology for diagnosing anomalies and maintaining oil lubrication systems for gas turbine engines. The effort focused on the development of reasoning modules that utilize the existing, inexpensive sensors and are applicable to on-line monitoring within the full-authority digital engine controller (FADEC) of the engine. The target application is the Enhanced TF-40B gas turbine engine that powers the Landing Craft Air Cushion (LCAC) platform. To accomplish the development of the requisite data fusion algorithms and automated reasoning for the diagnostic modules, Penn State ARL produced a generic Turbine Engine Lubrication Systemmore » Simulator (TELSS) and Data Fusion Workbench (DFW). TELSS is a portable simulator code that calculates lubrication system parameters based upon one-dimensional fluid flow resistance network equations. Validation of the TF- 40B modules was performed using engineering and limited test data. The simulation model was used to analyze operational data from the LCAC fleet. The TELSS, as an integral portion of the DFW, provides the capability to experiment with combinations of variables and feature vectors that characterize normal and abnormal operation of the engine lubrication system. The model-based diagnostics approach is applicable to all gas turbine engines and mechanical transmissions with similar pressure-fed lubrication systems.« less

Commensal bacteria modulate the tumor microenvironment.

PubMed

Poutahidis, Theofilos; Erdman, Susan E

2016-09-28

It has been recently shown that gut microbes modulate whole host immune and hormonal factors impacting the fate of distant preneoplastic lesions toward malignancy or regression. This raises the possibility that the tumor microenvironment interacts with broader systemic microbial-immune networks. These accumulated findings suggest novel therapeutic opportunities for holobiont engineering in emerging tumor microenvironments. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Reconfigurable Robust Routing for Mobile Outreach Network

NASA Technical Reports Server (NTRS)

Lin, Ching-Fang

2010-01-01

The Reconfigurable Robust Routing for Mobile Outreach Network (R3MOO N) provides advanced communications networking technologies suitable for the lunar surface environment and applications. The R3MOON techn ology is based on a detailed concept of operations tailored for luna r surface networks, and includes intelligent routing algorithms and wireless mesh network implementation on AGNC's Coremicro Robots. The product's features include an integrated communication solution inco rporating energy efficiency and disruption-tolerance in a mobile ad h oc network, and a real-time control module to provide researchers an d engineers a convenient tool for reconfiguration, investigation, an d management.

SAFSIM theory manual: A computer program for the engineering simulation of flow systems

NASA Astrophysics Data System (ADS)

Dobranich, Dean

1993-12-01

SAFSIM (System Analysis Flow SIMulator) is a FORTRAN computer program for simulating the integrated performance of complex flow systems. SAFSIM provides sufficient versatility to allow the engineering simulation of almost any system, from a backyard sprinkler system to a clustered nuclear reactor propulsion system. In addition to versatility, speed and robustness are primary SAFSIM development goals. SAFSIM contains three basic physics modules: (1) a fluid mechanics module with flow network capability; (2) a structure heat transfer module with multiple convection and radiation exchange surface capability; and (3) a point reactor dynamics module with reactivity feedback and decay heat capability. Any or all of the physics modules can be implemented, as the problem dictates. SAFSIM can be used for compressible and incompressible, single-phase, multicomponent flow systems. Both the fluid mechanics and structure heat transfer modules employ a one-dimensional finite element modeling approach. This document contains a description of the theory incorporated in SAFSIM, including the governing equations, the numerical methods, and the overall system solution strategies.

Protein Network Signatures Associated with Exogenous Biofuels Treatments in Cyanobacterium Synechocystis sp. PCC 6803

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pei, Guangsheng; Chen, Lei; Wang, Jiangxin

2014-11-03

Although recognized as a promising microbial cell factory for producing biofuels, current productivity in cyanobacterial systems is low. To make the processes economically feasible, one of the hurdles, which need to be overcome is the low tolerance of hosts to toxic biofuels. Meanwhile, little information is available regarding the cellular responses to biofuels stress in cyanobacteria, which makes it challenging for tolerance engineering. Using large proteomic datasets of Synechocystis under various biofuels stress and environmental perturbation, a protein co-expression network was first constructed and then combined with the experimentally determined protein–protein interaction network. Proteins with statistically higher topological overlap inmore » the integrated network were identified as common responsive proteins to both biofuels stress and environmental perturbations. In addition, a weighted gene co-expression network analysis was performed to distinguish unique responses to biofuels from those to environmental perturbations and to uncover metabolic modules and proteins uniquely associated with biofuels stress. The results showed that biofuel-specific proteins and modules were enriched in several functional categories, including photosynthesis, carbon fixation, and amino acid metabolism, which may represent potential key signatures for biofuels stress responses in Synechocystis. Network-based analysis allowed determination of the responses specifically related to biofuels stress, and the results constituted an important knowledge foundation for tolerance engineering against biofuels in Synechocystis.« less

Modularity Induced Gating and Delays in Neuronal Networks

PubMed Central

Shein-Idelson, Mark; Cohen, Gilad; Hanein, Yael

2016-01-01

Neural networks, despite their highly interconnected nature, exhibit distinctly localized and gated activation. Modularity, a distinctive feature of neural networks, has been recently proposed as an important parameter determining the manner by which networks support activity propagation. Here we use an engineered biological model, consisting of engineered rat cortical neurons, to study the role of modular topology in gating the activity between cell populations. We show that pairs of connected modules support conditional propagation (transmitting stronger bursts with higher probability), long delays and propagation asymmetry. Moreover, large modular networks manifest diverse patterns of both local and global activation. Blocking inhibition decreased activity diversity and replaced it with highly consistent transmission patterns. By independently controlling modularity and disinhibition, experimentally and in a model, we pose that modular topology is an important parameter affecting activation localization and is instrumental for population-level gating by disinhibition. PMID:27104350

A network engineering perspective on probing and perturbing cognition with neurofeedback

PubMed Central

Khambhati, Ankit N.

2017-01-01

Network science and engineering provide a flexible and generalizable tool set to describe and manipulate complex systems characterized by heterogeneous interaction patterns among component parts. While classically applied to social systems, these tools have recently proven to be particularly useful in the study of the brain. In this review, we describe the nascent use of these tools to understand human cognition, and we discuss their utility in informing the meaningful and predictable perturbation of cognition in combination with the emerging capabilities of neurofeedback. To blend these disparate strands of research, we build on emerging conceptualizations of how the brain functions (as a complex network) and how we can develop and target interventions or modulations (as a form of network control). We close with an outline of current frontiers that bridge neurofeedback, connectomics, and network control theory to better understand human cognition. PMID:28445589

FROMS3D: New Software for 3-D Visualization of Fracture Network System in Fractured Rock Masses

NASA Astrophysics Data System (ADS)

Noh, Y. H.; Um, J. G.; Choi, Y.

2014-12-01

A new software (FROMS3D) is presented to visualize fracture network system in 3-D. The software consists of several modules that play roles in management of borehole and field fracture data, fracture network modelling, visualization of fracture geometry in 3-D and calculation and visualization of intersections and equivalent pipes between fractures. Intel Parallel Studio XE 2013, Visual Studio.NET 2010 and the open source VTK library were utilized as development tools to efficiently implement the modules and the graphical user interface of the software. The results have suggested that the developed software is effective in visualizing 3-D fracture network system, and can provide useful information to tackle the engineering geological problems related to strength, deformability and hydraulic behaviors of the fractured rock masses.

Modeling genome-wide dynamic regulatory network in mouse lungs with influenza infection using high-dimensional ordinary differential equations.

PubMed

Wu, Shuang; Liu, Zhi-Ping; Qiu, Xing; Wu, Hulin

2014-01-01

The immune response to viral infection is regulated by an intricate network of many genes and their products. The reverse engineering of gene regulatory networks (GRNs) using mathematical models from time course gene expression data collected after influenza infection is key to our understanding of the mechanisms involved in controlling influenza infection within a host. A five-step pipeline: detection of temporally differentially expressed genes, clustering genes into co-expressed modules, identification of network structure, parameter estimate refinement, and functional enrichment analysis, is developed for reconstructing high-dimensional dynamic GRNs from genome-wide time course gene expression data. Applying the pipeline to the time course gene expression data from influenza-infected mouse lungs, we have identified 20 distinct temporal expression patterns in the differentially expressed genes and constructed a module-based dynamic network using a linear ODE model. Both intra-module and inter-module annotations and regulatory relationships of our inferred network show some interesting findings and are highly consistent with existing knowledge about the immune response in mice after influenza infection. The proposed method is a computationally efficient, data-driven pipeline bridging experimental data, mathematical modeling, and statistical analysis. The application to the influenza infection data elucidates the potentials of our pipeline in providing valuable insights into systematic modeling of complicated biological processes.

Control and protection system for an installation for the combined production of electrical and thermal energy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agazzone, U.; Ausiello, F.P.

1981-06-23

A power-generating installation comprises a plurality of modular power plants each comprised of an internal combustion engine connected to an electric machine. The electric machine is used to start the engine and thereafter operates as a generator supplying power to an electrical network common to all the modular plants. The installation has a control and protection system comprising a plurality of control modules each associated with a respective plant, and a central unit passing control signals to the modules to control starting and stopping of the individual power plants. Upon the detection of abnormal operation or failure of its associatedmore » power plant, each control module transmits an alarm signal back to the central unit which thereupon stops, or prevents the starting, of the corresponding power plant. Parameters monitored by each control module include generated current and inter-winding leakage current of the electric machine.« less

Encouraging the pursuit of advanced degrees in science and engineering: Top-down and bottom-up methodologies

NASA Technical Reports Server (NTRS)

Maddox, Anthony B.; Smith-Maddox, Renee P.; Penick, Benson E.

1989-01-01

The MassPEP/NASA Graduate Research Development Program (GRDP) whose objective is to encourage Black Americans, Mexican Americans, American Indians, Puerto Ricans, and Pacific Islanders to pursue graduate degrees in science and engineering is described. The GRDP employs a top-down or goal driven methodology through five modules which focus on research, graduate school climate, technical writing, standardized examinations, and electronic networking. These modules are designed to develop and reinforce some of the skills necessary to seriously consider the goal of completing a graduate education. The GRDP is a community-based program which seeks to recruit twenty participants from a pool of Boston-area undergraduates enrolled in engineering and science curriculums and recent graduates with engineering and science degrees. The program emphasizes that with sufficient information, its participants can overcome most of the barriers perceived as preventing them from obtaining graduate science and engineering degrees. Experience has shown that the top-down modules may be complemented by a more bottom-up or event-driven methodology. This approach considers events in the academic and professional experiences of participants in order to develop the personal and leadership skills necessary for graduate school and similar endeavors.

Design and engineering analysis of material procurement mobile operation platform

NASA Astrophysics Data System (ADS)

Ding, H.; Li, J.

2014-03-01

The material procurement mobile operation platform (MPMOP) consists of six modules, including network operation, truck transportation, remote communication, satellite positioning, power supply and environment regulation. The MPMOP is designed to have six major functions, including online procurement, command control, remote communication, satellite positioning, information management and auxiliary decision. The paper implements an engineering analysis on the MPMOP from three aspects, including transportation transfinite, centroid, and power dissipation.

Engineering Devices to Treat Epilepsy: A Clinical Perspective

DTIC Science & Technology

2001-10-25

Research over the next three decades reinforced the idea that seizures likely spread through discrete, functional neuronal networks [2]. Over the last...15 years, researchers have demonstrated that it is possible to modulate the activity of functional neuronal networks in animal models of epilepsy by...hypothalamus [5], mamillary bodies [6], cerebellum [7], basal ganglia [8], locus ceruleus [9] and the substantia nigra [10]. At the same time some

Dynamic regulation of metabolic flux in engineered bacteria using a pathway-independent quorum-sensing circuit

PubMed Central

Gupta, Apoorv; Brockman Reizman, Irene M.; Reisch, Christopher R.; Prather, Kristala L. J.

2017-01-01

Metabolic engineering of microorganisms to produce desirable products on an industrial scale can result in unbalanced cellular metabolic networks that reduce productivity and yield. Metabolic fluxes can be rebalanced using dynamic pathway regulation, but few broadly applicable tools are available to achieve this. We present a pathway-independent genetic control module that can be used to dynamically regulate the expression of target genes. We applied our module to identify the optimal point to redirect glycolytic flux into heterologous engineered pathways in Escherichia coli, resulting in 5.5-fold increased titres of myo-inositol and titers of glucaric acid that improved from unmeasurable quantities to >0.8 g/L. Scaled-up production in benchtop bioreactors resulted in almost 10-fold and 5-fold increases in titers of myo-inositol and glucaric acid. We also used our module to control flux into aromatic amino acid biosynthesis to increase titers of shikimate in E. coli from unmeasurable quantities to >100 mg/L. PMID:28191902

Computer-aided design of biological circuits using TinkerCell

PubMed Central

Bergmann, Frank T; Sauro, Herbert M

2010-01-01

Synthetic biology is an engineering discipline that builds on modeling practices from systems biology and wet-lab techniques from genetic engineering. As synthetic biology advances, efficient procedures will be developed that will allow a synthetic biologist to design, analyze and build biological networks. In this idealized pipeline, computer-aided design (CAD) is a necessary component. The role of a CAD application would be to allow efficient transition from a general design to a final product. TinkerCell is a design tool for serving this purpose in synthetic biology. In TinkerCell, users build biological networks using biological parts and modules. The network can be analyzed using one of several functions provided by TinkerCell or custom programs from third-party sources. Since best practices for modeling and constructing synthetic biology networks have not yet been established, TinkerCell is designed as a flexible and extensible application that can adjust itself to changes in the field. PMID:21327060

GLOBECOM '87 - Global Telecommunications Conference, Tokyo, Japan, Nov. 15-18, 1987, Conference Record. Volumes 1, 2, & 3

NASA Astrophysics Data System (ADS)

The present conference on global telecommunications discusses topics in the fields of Integrated Services Digital Network (ISDN) technology field trial planning and results to date, motion video coding, ISDN networking, future network communications security, flexible and intelligent voice/data networks, Asian and Pacific lightwave and radio systems, subscriber radio systems, the performance of distributed systems, signal processing theory, satellite communications modulation and coding, and terminals for the handicapped. Also discussed are knowledge-based technologies for communications systems, future satellite transmissions, high quality image services, novel digital signal processors, broadband network access interface, traffic engineering for ISDN design and planning, telecommunications software, coherent optical communications, multimedia terminal systems, advanced speed coding, portable and mobile radio communications, multi-Gbit/second lightwave transmission systems, enhanced capability digital terminals, communications network reliability, advanced antimultipath fading techniques, undersea lightwave transmission, image coding, modulation and synchronization, adaptive signal processing, integrated optical devices, VLSI technologies for ISDN, field performance of packet switching, CSMA protocols, optical transport system architectures for broadband ISDN, mobile satellite communications, indoor wireless communication, echo cancellation in communications, and distributed network algorithms.

Coarse-graining and self-dissimilarity of complex networks

NASA Astrophysics Data System (ADS)

Itzkovitz, Shalev; Levitt, Reuven; Kashtan, Nadav; Milo, Ron; Itzkovitz, Michael; Alon, Uri

2005-01-01

Can complex engineered and biological networks be coarse-grained into smaller and more understandable versions in which each node represents an entire pattern in the original network? To address this, we define coarse-graining units as connectivity patterns which can serve as the nodes of a coarse-grained network and present algorithms to detect them. We use this approach to systematically reverse-engineer electronic circuits, forming understandable high-level maps from incomprehensible transistor wiring: first, a coarse-grained version in which each node is a gate made of several transistors is established. Then the coarse-grained network is itself coarse-grained, resulting in a high-level blueprint in which each node is a circuit module made of many gates. We apply our approach also to a mammalian protein signal-transduction network, to find a simplified coarse-grained network with three main signaling channels that resemble multi-layered perceptrons made of cross-interacting MAP-kinase cascades. We find that both biological and electronic networks are “self-dissimilar,” with different network motifs at each level. The present approach may be used to simplify a variety of directed and nondirected, natural and designed networks.

A network engineering perspective on probing and perturbing cognition with neurofeedback.

PubMed

Bassett, Danielle S; Khambhati, Ankit N

2017-05-01

Network science and engineering provide a flexible and generalizable tool set to describe and manipulate complex systems characterized by heterogeneous interaction patterns among component parts. While classically applied to social systems, these tools have recently proven to be particularly useful in the study of the brain. In this review, we describe the nascent use of these tools to understand human cognition, and we discuss their utility in informing the meaningful and predictable perturbation of cognition in combination with the emerging capabilities of neurofeedback. To blend these disparate strands of research, we build on emerging conceptualizations of how the brain functions (as a complex network) and how we can develop and target interventions or modulations (as a form of network control). We close with an outline of current frontiers that bridge neurofeedback, connectomics, and network control theory to better understand human cognition. © 2017 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals Inc. on behalf of The New York Academy of Sciences.

A Subject Matter Expert View of Curriculum Development.

NASA Astrophysics Data System (ADS)

Milazzo, M. P.; Anderson, R. B.; Edgar, L. A.; Gaither, T. A.; Vaughan, R. G.

2017-12-01

In 2015, NASA selected for funding the PLANETS project: Planetary Learning that Advances the Nexus of Engineering, Technology, and Science. The PLANETS partnership develops planetary science and engineering curricula for out of classroom time (OST) education settings. This partnership is between planetary science Subject Matter Experts (SMEs) at the US Geological Survey (USGS), curriculum developers at the Boston Museum of Science (MOS) Engineering is Everywhere (EiE), science and engineering teacher professional development experts at Northern Arizona University (NAU) Center for Science Teaching and Learning (CSTL), and OST teacher networks across the world. For the 2016 and 2017 Fiscal Years, our focus was on creating science material for two OST modules designed for middle school students. We have begun development of a third module for elementary school students. The first model teaches about the science and engineering of the availability of water in the Solar System, finding accessible water, evaluating it for quality, treating it for impurities, initial use, a cycle of greywater treatment and re-use, and final treatment of blackwater. This module is described in more detail in the abstract by L. Edgar et al., Water in the Solar System: The Development of Science Education Curriculum Focused on Planetary Exploration (233008) The second module involves the science and engineering of remote sensing in planetary exploration. This includes discussion and activities related to the electromagnetic spectrum, spectroscopy and various remote sensing systems and techniques. In these activities and discussions, we include observation and measurement techniques and tools as well as collection and use of specific data of interest to scientists. This module is described in more detail in the abstract by R. Anderson et al., Remote Sensing Mars Landing Sites: An Out-of-School Time Planetary Science Education Activity for Middle School Students (232683) The third module, described by R.G. Vaughan, Hazards in the Solar System: Out-of-School Time Student Activities Focused on Engineering Protective Space Gloves (262143), focuses on hazards in the Solar System and the engineering approach to designing space gloves to protect against those hazards.

Altering the swelling pressures within in vitro engineered cartilage is predicted to modulate the configuration of the collagen network and hence improve tissue mechanical properties.

PubMed

Nagel, Thomas; Kelly, Daniel J

2013-06-01

Prestress in the collagen network has a significant impact on the material properties of cartilaginous tissues. It is closely related to the recruitment configuration of the collagen network which defines the transition from lax collagen fibres to uncrimped, load-bearing collagen fibres. This recruitment configuration can change in response to alterations in the external environmental conditions. In this study, the influence of changes in external salt concentration or sequential proteoglycan digestion on the configuration of the collagen network of tissue engineered cartilage is investigated using a previously developed computational model. Collagen synthesis and network assembly are assumed to occur in the tissue configuration present during in vitro culture. The model assumes that if this configuration is more compact due to changes in tissue swelling, the collagen network will adapt by lowering its recruitment stretch. When returned to normal physiological conditions, these tissues will then have a higher prestress in the collagen network. Based on these assumptions, the model demonstrates that proteoglycan digestion at discrete time points during culture as well as culture in a hypertonic medium can improve the functionality of tissue engineered cartilage, while culture in hypotonic solution is detrimental to the apparent mechanical properties of the graft. Copyright © 2013 Elsevier Ltd. All rights reserved.

On the application of neural networks to the classification of phase modulated waveforms

NASA Astrophysics Data System (ADS)

Buchenroth, Anthony; Yim, Joong Gon; Nowak, Michael; Chakravarthy, Vasu

2017-04-01

Accurate classification of phase modulated radar waveforms is a well-known problem in spectrum sensing. Identification of such waveforms aids situational awareness enabling radar and communications spectrum sharing. While various feature extraction and engineering approaches have sought to address this problem, the use of a machine learning algorithm that best utilizes these features is becomes foremost. In this effort, a comparison of a standard shallow and a deep learning approach are explored. Experiments provide insights into classifier architecture, training procedure, and performance.

A bridge role metric model for nodes in software networks.

PubMed

Li, Bo; Feng, Yanli; Ge, Shiyu; Li, Dashe

2014-01-01

A bridge role metric model is put forward in this paper. Compared with previous metric models, our solution of a large-scale object-oriented software system as a complex network is inherently more realistic. To acquire nodes and links in an undirected network, a new model that presents the crucial connectivity of a module or the hub instead of only centrality as in previous metric models is presented. Two previous metric models are described for comparison. In addition, it is obvious that the fitting curve between the Bre results and degrees can well be fitted by a power law. The model represents many realistic characteristics of actual software structures, and a hydropower simulation system is taken as an example. This paper makes additional contributions to an accurate understanding of module design of software systems and is expected to be beneficial to software engineering practices.

A Bridge Role Metric Model for Nodes in Software Networks

PubMed Central

Li, Bo; Feng, Yanli; Ge, Shiyu; Li, Dashe

2014-01-01

A bridge role metric model is put forward in this paper. Compared with previous metric models, our solution of a large-scale object-oriented software system as a complex network is inherently more realistic. To acquire nodes and links in an undirected network, a new model that presents the crucial connectivity of a module or the hub instead of only centrality as in previous metric models is presented. Two previous metric models are described for comparison. In addition, it is obvious that the fitting curve between the results and degrees can well be fitted by a power law. The model represents many realistic characteristics of actual software structures, and a hydropower simulation system is taken as an example. This paper makes additional contributions to an accurate understanding of module design of software systems and is expected to be beneficial to software engineering practices. PMID:25364938

Design of cognitive engine for cognitive radio based on the rough sets and radial basis function neural network

NASA Astrophysics Data System (ADS)

Yang, Yanchao; Jiang, Hong; Liu, Congbin; Lan, Zhongli

2013-03-01

Cognitive radio (CR) is an intelligent wireless communication system which can dynamically adjust the parameters to improve system performance depending on the environmental change and quality of service. The core technology for CR is the design of cognitive engine, which introduces reasoning and learning methods in the field of artificial intelligence, to achieve the perception, adaptation and learning capability. Considering the dynamical wireless environment and demands, this paper proposes a design of cognitive engine based on the rough sets (RS) and radial basis function neural network (RBF_NN). The method uses experienced knowledge and environment information processed by RS module to train the RBF_NN, and then the learning model is used to reconfigure communication parameters to allocate resources rationally and improve system performance. After training learning model, the performance is evaluated according to two benchmark functions. The simulation results demonstrate the effectiveness of the model and the proposed cognitive engine can effectively achieve the goal of learning and reconfiguration in cognitive radio.

Interferometric modulation of quantum cascade interactions

NASA Astrophysics Data System (ADS)

Cusumano, Stefano; Mari, Andrea; Giovannetti, Vittorio

2018-05-01

We consider many-body quantum systems dissipatively coupled by a cascade network, i.e., a setup in which interactions are mediated by unidirectional environmental modes propagating through a linear optical interferometer. In particular we are interested in the possibility of inducing different effective interactions by properly engineering an external dissipative network of beam splitters and phase shifters. In this work we first derive the general structure of the master equation for a symmetric class of translation-invariant cascade networks. Then we show how, by tuning the parameters of the interferometer, one can exploit interference effects to tailor a large variety of many-body interactions.

Reverse and forward engineering of protein pattern formation.

PubMed

Kretschmer, Simon; Harrington, Leon; Schwille, Petra

2018-05-26

Living systems employ protein pattern formation to regulate important life processes in space and time. Although pattern-forming protein networks have been identified in various prokaryotes and eukaryotes, their systematic experimental characterization is challenging owing to the complex environment of living cells. In turn, cell-free systems are ideally suited for this goal, as they offer defined molecular environments that can be precisely controlled and manipulated. Towards revealing the molecular basis of protein pattern formation, we outline two complementary approaches: the biochemical reverse engineering of reconstituted networks and the de novo design, or forward engineering, of artificial self-organizing systems. We first illustrate the reverse engineering approach by the example of the Escherichia coli Min system, a model system for protein self-organization based on the reversible and energy-dependent interaction of the ATPase MinD and its activating protein MinE with a lipid membrane. By reconstituting MinE mutants impaired in ATPase stimulation, we demonstrate how large-scale Min protein patterns are modulated by MinE activity and concentration. We then provide a perspective on the de novo design of self-organizing protein networks. Tightly integrated reverse and forward engineering approaches will be key to understanding and engineering the intriguing phenomenon of protein pattern formation.This article is part of the theme issue 'Self-organization in cell biology'. © 2018 The Author(s).

Computer-aided design of biological circuits using TinkerCell.

PubMed

Chandran, Deepak; Bergmann, Frank T; Sauro, Herbert M

2010-01-01

Synthetic biology is an engineering discipline that builds on modeling practices from systems biology and wet-lab techniques from genetic engineering. As synthetic biology advances, efficient procedures will be developed that will allow a synthetic biologist to design, analyze, and build biological networks. In this idealized pipeline, computer-aided design (CAD) is a necessary component. The role of a CAD application would be to allow efficient transition from a general design to a final product. TinkerCell is a design tool for serving this purpose in synthetic biology. In TinkerCell, users build biological networks using biological parts and modules. The network can be analyzed using one of several functions provided by TinkerCell or custom programs from third-party sources. Since best practices for modeling and constructing synthetic biology networks have not yet been established, TinkerCell is designed as a flexible and extensible application that can adjust itself to changes in the field. © 2010 Landes Bioscience

Protocol standards and implementation within the digital engineering laboratory computer network (DELNET) using the universal network interface device (UNID). Part 2

NASA Astrophysics Data System (ADS)

Phister, P. W., Jr.

1983-12-01

Development of the Air Force Institute of Technology's Digital Engineering Laboratory Network (DELNET) was continued with the development of an initial draft of a protocol standard for all seven layers as specified by the International Standards Organization's (ISO) Reference Model for Open Systems Interconnections. This effort centered on the restructuring of the Network Layer to perform Datagram routing and to conform to the developed protocol standards and actual software module development of the upper four protocol layers residing within the DELNET Monitor (Zilog MCZ 1/25 Computer System). Within the guidelines of the ISO Reference Model the Transport Layer was developed utilizing the Internet Header Format (IHF) combined with the Transport Control Protocol (TCP) to create a 128-byte Datagram. Also a limited Application Layer was created to pass the Gettysburg Address through the DELNET. This study formulated a first draft for the DELNET Protocol Standard and designed, implemented, and tested the Network, Transport, and Application Layers to conform to these protocol standards.

A systems-genetics approach and data mining tool to assist in the discovery of genes underlying complex traits in Oryza sativa.

PubMed

Ficklin, Stephen P; Feltus, Frank Alex

2013-01-01

Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with significant overlap with blast disease resistance.

A Systems-Genetics Approach and Data Mining Tool to Assist in the Discovery of Genes Underlying Complex Traits in Oryza sativa

PubMed Central

Ficklin, Stephen P.; Feltus, Frank Alex

2013-01-01

Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with significant overlap with blast disease resistance. PMID:23874666

Research of Modulation of Bilateral Frequency Difference Based on Load Mode

NASA Astrophysics Data System (ADS)

Lin, Shenghong; Mao, Chizu; Zhu, Jianquan; Lu, Junyu

2017-05-01

Owning to high reliability, simple operation and easy acquirement of signals, modulation of bilateral frequency difference (MBFD) in HVDC is worthy for application in practical engineering. With the example of an AC/DC hybrid network and the software PSD-BPA, this paper analyses the effect of MBFD to DC block. The modulators parameters are setting by means of simulation. Two types of loads modes are considered to research the impact of them on simulation. The results indicate that in cooperation with operation modes adjusting at AC system, MBFD will effectively release the impact from DC block and shortage of reactive power caused by rapid variation of DC power owning to modulation. To achieve the best effect, only modulators of some HVDC systems instead of all of them are opened.

Enzymatic regulation of functional vascular networks using gelatin hydrogels

PubMed Central

Chuang, Chia-Hui; Lin, Ruei-Zeng; Tien, Han-Wen; Chu, Ya-Chun; Li, Yen-Cheng; Melero-Martin, Juan M.; Chen, Ying-Chieh

2015-01-01

To manufacture tissue engineering-based functional tissues, scaffold materials that can be sufficiently vascularized to mimic the functionality and complexity of native tissues are needed. Currently, vascular network bioengineering is largely carried out using natural hydrogels as embedding scaffolds, but most natural hydrogels have poor mechanical stability and durability, factors that critically limit their widespread use. In this study, we examined the suitability of gelatin-phenolic hydroxyl (gelatin-Ph) hydrogels that can be enzymatically crosslinked, allowing tuning of the storage modulus and the proteolytic degradation rate, for use as injectable hydrogels to support the human progenitor cell-based formation of a stable and mature vascular network. Porcine gelatin-Ph hydrogels were found to be cytocompatible with human blood-derived endothelial colony-forming cells and white adipose tissue-derived mesenchymal stem cells, resulting in >87% viability, and cell proliferation and spreading could be modulated by using hydrogels with different proteolytic degradability and stiffness. In addition, gelatin was extracted from mouse dermis and murine gelatin-Ph hydrogels were prepared. Importantly, implantation of human cell-laden porcine or murine gelatin-Ph hydrogels into immunodeficient mice resulted in the rapid formation of functional anastomoses between the bioengineered human vascular network and the mouse vasculature. Furthermore, the degree of enzymatic crosslinking of the gelatin-Ph hydrogels could be used to modulate cell behavior and the extent of vascular network formation in vivo. Our report details a technique for the synthesis of gelatin-Ph hydrogels from allogeneic or xenogeneic dermal skin and suggests that these hydrogels can be used for biomedical applications that require the formation of microvascular networks, including the development of complex engineered tissues. PMID:25749296

Use of Soft Computing Technologies for a Qualitative and Reliable Engine Control System for Propulsion Systems

NASA Technical Reports Server (NTRS)

Trevino, Luis; Brown, Terry; Crumbley, R. T. (Technical Monitor)

2001-01-01

The problem to be addressed in this paper is to explore how the use of Soft Computing Technologies (SCT) could be employed to improve overall vehicle system safety, reliability, and rocket engine performance by development of a qualitative and reliable engine control system (QRECS). Specifically, this will be addressed by enhancing rocket engine control using SCT, innovative data mining tools, and sound software engineering practices used in Marshall's Flight Software Group (FSG). The principle goals for addressing the issue of quality are to improve software management, software development time, software maintenance, processor execution, fault tolerance and mitigation, and nonlinear control in power level transitions. The intent is not to discuss any shortcomings of existing engine control methodologies, but to provide alternative design choices for control, implementation, performance, and sustaining engineering, all relative to addressing the issue of reliability. The approaches outlined in this paper will require knowledge in the fields of rocket engine propulsion (system level), software engineering for embedded flight software systems, and soft computing technologies (i.e., neural networks, fuzzy logic, data mining, and Bayesian belief networks); some of which are briefed in this paper. For this effort, the targeted demonstration rocket engine testbed is the MC-1 engine (formerly FASTRAC) which is simulated with hardware and software in the Marshall Avionics & Software Testbed (MAST) laboratory that currently resides at NASA's Marshall Space Flight Center, building 4476, and is managed by the Avionics Department. A brief plan of action for design, development, implementation, and testing a Phase One effort for QRECS is given, along with expected results. Phase One will focus on development of a Smart Start Engine Module and a Mainstage Engine Module for proper engine start and mainstage engine operations. The overall intent is to demonstrate that by employing soft computing technologies, the quality and reliability of the overall scheme to engine controller development is further improved and vehicle safety is further insured. The final product that this paper proposes is an approach to development of an alternative low cost engine controller that would be capable of performing in unique vision spacecraft vehicles requiring low cost advanced avionics architectures for autonomous operations from engine pre-start to engine shutdown.

Enhanced isoprene biosynthesis in Saccharomyces cerevisiae by engineering of the native acetyl-CoA and mevalonic acid pathways with a push-pull-restrain strategy.

PubMed

Lv, Xiaomei; Xie, Wenping; Lu, Wenqiang; Guo, Fei; Gu, Jiali; Yu, Hongwei; Ye, Lidan

2014-09-30

To explore the capacity of isoprene production in Saccharomyces cerevisiae, a rational push-pull-restrain strategy was proposed to engineer the mevalonic acid (MVA) and acetyl-CoA pathways. The strategy can be decomposed into the up-regulation of precursor supply in the acetyl-CoA module and the MVA pathway (push-strategy), increase of the isoprene branch flux (pull-strategy), and down-regulation of the competing pathway (restrain-strategy). Furthermore, to reduce the production cost arising from galactose addition and meanwhile maintain the high expression of Gal promoters, the galactose regulatory network was modulated by Gal80p deletion. Finally, the engineered strain YXM10-ispS-ispS could accumulate up to 37 mg/L isoprene (about 782-fold increase compared to the parental strain) under aerobic conditions with glycerol-sucrose as carbon source. In this way, a new potential platform for isoprene production was established via metabolic engineering of the yeast native pathways. Copyright © 2014 Elsevier B.V. All rights reserved.

Genome-wide inference of regulatory networks in Streptomyces coelicolor.

PubMed

Castro-Melchor, Marlene; Charaniya, Salim; Karypis, George; Takano, Eriko; Hu, Wei-Shou

2010-10-18

The onset of antibiotics production in Streptomyces species is co-ordinated with differentiation events. An understanding of the genetic circuits that regulate these coupled biological phenomena is essential to discover and engineer the pharmacologically important natural products made by these species. The availability of genomic tools and access to a large warehouse of transcriptome data for the model organism, Streptomyces coelicolor, provides incentive to decipher the intricacies of the regulatory cascades and develop biologically meaningful hypotheses. In this study, more than 500 samples of genome-wide temporal transcriptome data, comprising wild-type and more than 25 regulatory gene mutants of Streptomyces coelicolor probed across multiple stress and medium conditions, were investigated. Information based on transcript and functional similarity was used to update a previously-predicted whole-genome operon map and further applied to predict transcriptional networks constituting modules enriched in diverse functions such as secondary metabolism, and sigma factor. The predicted network displays a scale-free architecture with a small-world property observed in many biological networks. The networks were further investigated to identify functionally-relevant modules that exhibit functional coherence and a consensus motif in the promoter elements indicative of DNA-binding elements. Despite the enormous experimental as well as computational challenges, a systems approach for integrating diverse genome-scale datasets to elucidate complex regulatory networks is beginning to emerge. We present an integrated analysis of transcriptome data and genomic features to refine a whole-genome operon map and to construct regulatory networks at the cistron level in Streptomyces coelicolor. The functionally-relevant modules identified in this study pose as potential targets for further studies and verification.

Multiscale Modulation of Nanocrystalline Cellulose Hydrogel via Nanocarbon Hybridization for 3D Neuronal Bilayer Formation.

PubMed

Kim, Dongyoon; Park, Subeom; Jo, Insu; Kim, Seong-Min; Kang, Dong Hee; Cho, Sung-Pyo; Park, Jong Bo; Hong, Byung Hee; Yoon, Myung-Han

2017-07-01

Bacterial biopolymers have drawn much attention owing to their unconventional three-dimensional structures and interesting functions, which are closely integrated with bacterial physiology. The nongenetic modulation of bacterial (Acetobacter xylinum) cellulose synthesis via nanocarbon hybridization, and its application to the emulation of layered neuronal tissue, is reported. The controlled dispersion of graphene oxide (GO) nanoflakes into bacterial cellulose (BC) culture media not only induces structural changes within a crystalline cellulose nanofibril, but also modulates their 3D collective association, leading to substantial reduction in Young's modulus (≈50%) and clear definition of water-hydrogel interfaces. Furthermore, real-time investigation of 3D neuronal networks constructed in this GO-incorporated BC hydrogel with broken chiral nematic ordering revealed the vertical locomotion of growth cones, the accelerated neurite outgrowth (≈100 µm per day) with reduced backward travel length, and the efficient formation of synaptic connectivity with distinct axonal bifurcation abundancy at the ≈750 µm outgrowth from a cell body. In comparison with the pristine BC, GO-BC supports the formation of well-defined neuronal bilayer networks with flattened interfacial profiles and vertical axonal outgrowth, apparently emulating the neuronal development in vivo. We envisioned that our findings may contribute to various applications of engineered BC hydrogel to fundamental neurobiology studies and neural engineering. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Simulator of Space Communication Networks

NASA Technical Reports Server (NTRS)

Clare, Loren; Jennings, Esther; Gao, Jay; Segui, John; Kwong, Winston

2005-01-01

Multimission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) is a suite of software tools that simulates the behaviors of communication networks to be used in space exploration, and predict the performance of established and emerging space communication protocols and services. MACHETE consists of four general software systems: (1) a system for kinematic modeling of planetary and spacecraft motions; (2) a system for characterizing the engineering impact on the bandwidth and reliability of deep-space and in-situ communication links; (3) a system for generating traffic loads and modeling of protocol behaviors and state machines; and (4) a system of user-interface for performance metric visualizations. The kinematic-modeling system makes it possible to characterize space link connectivity effects, including occultations and signal losses arising from dynamic slant-range changes and antenna radiation patterns. The link-engineering system also accounts for antenna radiation patterns and other phenomena, including modulations, data rates, coding, noise, and multipath fading. The protocol system utilizes information from the kinematic-modeling and link-engineering systems to simulate operational scenarios of space missions and evaluate overall network performance. In addition, a Communications Effect Server (CES) interface for MACHETE has been developed to facilitate hybrid simulation of space communication networks with actual flight/ground software/hardware embedded in the overall system.

Knowledge Engineering as a Component of the Curriculum for Medical Cybernetists.

PubMed

Karas, Sergey; Konev, Arthur

2017-01-01

According to a new state educational standard, students who have chosen medical cybernetics as their major must develop a knowledge engineering competency. Previously, in the course "Clinical cybernetics" while practicing project-based learning students were designing automated workstations for medical personnel using client-server technology. The purpose of the article is to give insight into the project of a new educational module "Knowledge engineering". Students will acquire expert knowledge by holding interviews and conducting surveys, and then they will formalize it. After that, students will form declarative expert knowledge in a network model and analyze the knowledge graph. Expert decision making methods will be applied in software on the basis of a production model of knowledge. Project implementation will result not only in the development of analytical competencies among students, but also creation of a practically useful expert system based on student models to support medical decisions. Nowadays, this module is being tested in the educational process.

SMC: SCENIC Model Control

NASA Technical Reports Server (NTRS)

Srivastava, Priyaka; Kraus, Jeff; Murawski, Robert; Golden, Bertsel, Jr.

2015-01-01

NASAs Space Communications and Navigation (SCaN) program manages three active networks: the Near Earth Network, the Space Network, and the Deep Space Network. These networks simultaneously support NASA missions and provide communications services to customers worldwide. To efficiently manage these resources and their capabilities, a team of student interns at the NASA Glenn Research Center is developing a distributed system to model the SCaN networks. Once complete, the system shall provide a platform that enables users to perform capacity modeling of current and prospective missions with finer-grained control of information between several simulation and modeling tools. This will enable the SCaN program to access a holistic view of its networks and simulate the effects of modifications in order to provide NASA with decisional information. The development of this capacity modeling system is managed by NASAs Strategic Center for Education, Networking, Integration, and Communication (SCENIC). Three primary third-party software tools offer their unique abilities in different stages of the simulation process. MagicDraw provides UMLSysML modeling, AGIs Systems Tool Kit simulates the physical transmission parameters and de-conflicts scheduled communication, and Riverbed Modeler (formerly OPNET) simulates communication protocols and packet-based networking. SCENIC developers are building custom software extensions to integrate these components in an end-to-end space communications modeling platform. A central control module acts as the hub for report-based messaging between client wrappers. Backend databases provide information related to mission parameters and ground station configurations, while the end user defines scenario-specific attributes for the model. The eight SCENIC interns are working under the direction of their mentors to complete an initial version of this capacity modeling system during the summer of 2015. The intern team is composed of four students in Computer Science, two in Computer Engineering, one in Electrical Engineering, and one studying Space Systems Engineering.

Design and implementation of a random neural network routing engine.

PubMed

Kocak, T; Seeber, J; Terzioglu, H

2003-01-01

Random neural network (RNN) is an analytically tractable spiked neural network model that has been implemented in software for a wide range of applications for over a decade. This paper presents the hardware implementation of the RNN model. Recently, cognitive packet networks (CPN) is proposed as an alternative packet network architecture where there is no routing table, instead the RNN based reinforcement learning is used to route packets. Particularly, we describe implementation details for the RNN based routing engine of a CPN network processor chip: the smart packet processor (SPP). The SPP is a dual port device that stores, modifies, and interprets the defining characteristics of multiple RNN models. In addition to hardware design improvements over the software implementation such as the dual access memory, output calculation step, and reduced output calculation module, this paper introduces a major modification to the reinforcement learning algorithm used in the original CPN specification such that the number of weight terms are reduced from 2n/sup 2/ to 2n. This not only yields significant memory savings, but it also simplifies the calculations for the steady state probabilities (neuron outputs in RNN). Simulations have been conducted to confirm the proper functionality for the isolated SPP design as well as for the multiple SPP's in a networked environment.

Engineering Proteins for Thermostability with iRDP Web Server

PubMed Central

Ghanate, Avinash; Ramasamy, Sureshkumar; Suresh, C. G.

2015-01-01

Engineering protein molecules with desired structure and biological functions has been an elusive goal. Development of industrially viable proteins with improved properties such as stability, catalytic activity and altered specificity by modifying the structure of an existing protein has widely been targeted through rational protein engineering. Although a range of factors contributing to thermal stability have been identified and widely researched, the in silico implementation of these as strategies directed towards enhancement of protein stability has not yet been explored extensively. A wide range of structural analysis tools is currently available for in silico protein engineering. However these tools concentrate on only a limited number of factors or individual protein structures, resulting in cumbersome and time-consuming analysis. The iRDP web server presented here provides a unified platform comprising of iCAPS, iStability and iMutants modules. Each module addresses different facets of effective rational engineering of proteins aiming towards enhanced stability. While iCAPS aids in selection of target protein based on factors contributing to structural stability, iStability uniquely offers in silico implementation of known thermostabilization strategies in proteins for identification and stability prediction of potential stabilizing mutation sites. iMutants aims to assess mutants based on changes in local interaction network and degree of residue conservation at the mutation sites. Each module was validated using an extensively diverse dataset. The server is freely accessible at http://irdp.ncl.res.in and has no login requirements. PMID:26436543

Engineering Proteins for Thermostability with iRDP Web Server.

PubMed

Panigrahi, Priyabrata; Sule, Manas; Ghanate, Avinash; Ramasamy, Sureshkumar; Suresh, C G

2015-01-01

Engineering protein molecules with desired structure and biological functions has been an elusive goal. Development of industrially viable proteins with improved properties such as stability, catalytic activity and altered specificity by modifying the structure of an existing protein has widely been targeted through rational protein engineering. Although a range of factors contributing to thermal stability have been identified and widely researched, the in silico implementation of these as strategies directed towards enhancement of protein stability has not yet been explored extensively. A wide range of structural analysis tools is currently available for in silico protein engineering. However these tools concentrate on only a limited number of factors or individual protein structures, resulting in cumbersome and time-consuming analysis. The iRDP web server presented here provides a unified platform comprising of iCAPS, iStability and iMutants modules. Each module addresses different facets of effective rational engineering of proteins aiming towards enhanced stability. While iCAPS aids in selection of target protein based on factors contributing to structural stability, iStability uniquely offers in silico implementation of known thermostabilization strategies in proteins for identification and stability prediction of potential stabilizing mutation sites. iMutants aims to assess mutants based on changes in local interaction network and degree of residue conservation at the mutation sites. Each module was validated using an extensively diverse dataset. The server is freely accessible at http://irdp.ncl.res.in and has no login requirements.

SENSE IT: Student Enabled Network of Sensors for the Environment using Innovative Technology

NASA Astrophysics Data System (ADS)

Hotaling, L. A.; Stolkin, R.; Kirkey, W.; Bonner, J. S.; Lowes, S.; Lin, P.; Ojo, T.

2010-12-01

SENSE IT is a project funded by the National Science Foundation (NSF) which strives to enrich science, technology, engineering and mathematics (STEM) education by providing teacher professional development and classroom projects in which high school students build from first principles, program, test and deploy sensors for water quality monitoring. Sensor development is a broad and interdisciplinary area, providing motivating scenarios in which to teach a multitude of STEM subjects, from mathematics and physics to biology and environmental science, while engaging students with hands on problems that reinforce conventional classroom learning by re-presenting theory as practical tools for building real-life working devices. The SENSE IT program is currently developing and implementing a set of high school educational modules which teach environmental science and basic engineering through the lens of fundamental STEM principles, at the same time introducing students to a new set of technologies that are increasingly important in the world of environmental research. Specifically, the project provides students with the opportunity to learn the engineering design process through the design, construction, programming and testing of a student-implemented water monitoring network in the Hudson and St. Lawrence Rivers in New York. These educational modules are aligned to state and national technology and science content standards and are designed to be compatible with standard classroom curricula to support a variety of core science, technology and mathematics classroom material. For example, while designing, programming and calibrating the sensors, the students are led through a series of tasks in which they must use core mathematics and physics theory to solve the real problems of making their sensors work. In later modules, students can explore environmental science and environmental engineering curricula while deploying and monitoring their sensors in local rivers. This presentation will provide an overview of the educational modules. A variety of sensors will be described, which are suitably simple for design and construction from first principles by high school students while being accurate enough for students to make meaningful environmental measurements. The presentation will also describe how the sensor building activities can be tied to core curricula classroom theory, enabling the modules to be utilized in regular classes by mathematics, science and computing teachers without disrupting their semester’s teaching goals. Furthermore, the presentation will address of the first two years of the SENSE IT project, during which 39 teachers have been equipped, trained on these materials, and have implemented the modules with around approximately 2,000 high school students.

Planetary Exploration Education: As Seen From the Point of View of Subject Matter Experts

NASA Astrophysics Data System (ADS)

Milazzo, M. P.; Anderson, R. B.; Gaither, T. A.; Vaughan, R. G.

2016-12-01

Planetary Learning that Advances the Nexus of Engineering, Technology, and Science (PLANETS) was selected as one of 27 new projects to support the NASA Science Mission Directorate's Science Education Cooperative Agreement Notice. Our goal is to develop and disseminate out-of-school time (OST) curricular and related educator professional development modules that integrate planetary science, technology, and engineering. We are a partnership between planetary science Subject Matter Experts (SMEs), curriculum developers, science and engineering teacher professional development experts and OST teacher networks. The PLANETS team includes the Center for Science Teaching and Learning (CSTL) at Northern Arizona University (NAU); the U.S. Geological Survey (USGS) Astrogeology Science Center (Astrogeology), and the Boston Museum of Science (MOS). Here, we present the work and approach by the SMEs at Astrogeology. As part of this overarching project, we will create a model for improved integration of SMEs, curriculum developers, professional development experts, and educators. For the 2016 and 2017 Fiscal Years, our focus is on creating science material for two OST modules designed for middle school students. We will begin development of a third module for elementary school students in the latter part of FY2017. The first module focuses on water conservation and treatment as applied on Earth, the International Space Station, and at a fictional Mars base. This unit involves the science and engineering of finding accessible water, evaluating it for quality, treating it for impurities (i.e., dissolved and suspended), initial use, a cycle of greywater treatment and re-use, and final treatment of blackwater. The second module involves the science and engineering of remote sensing as it is related to Earth and planetary exploration. This includes discussion and activities related to the electromagnetic spectrum, spectroscopy and various remote sensing systems and techniques. In these activities and discussions we include observation and measurement techniques and tools, as well as collection and use of specific data of interest to scientists. These two modules will be tested and refined based on educator and student feedback, with expected final release in late summer of 2017.

78 FR 775 - Goodman Networks, Inc. Core Network Engineering (Deployment Engineering) Division Alpharetta, GA...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-04

...,846B; TA-W-81,846C; TA-W-81,846D] Goodman Networks, Inc. Core Network Engineering (Deployment Engineering) Division Alpharetta, GA; Goodman Networks, Inc. Core Network Engineering (Deployment Engineering) Division Hunt Valley, MD; Goodman Networks, Inc. Core Network Engineering (Deployment Engineering) Division...

Evanescent-field-modulated two-qubit entanglement in an emitters-plasmon coupled system.

PubMed

Zhang, Fan; Ren, Juanjuan; Duan, Xueke; Zhao, Chen; Gong, Qihuang; Gu, Ying

2018-06-13

Scalable integrated quantum information networks calls for controllable entanglement modulation at subwavelength scale. To reduce laser disturbance among adjacent nanostructures, here we theoretically demonstrate two-qubit entanglement modulated by an evanescent field of a dielectric nanowire in an emitter-AgNP coupled system. This coupled system is considered as a nano-cavity system embedded in an evanescent vacuum. Through varying the amplitude of evanescent field, the concurrence of steady-state entanglement can be modified from 0 to 0.75. Because the interaction between emitters and the nanowire is much weaker than that inside the coupled system, the range of modulation for two-qubit entanglement is insensitive to their distance. The evanescent field controlled entangled state engineering provides the possibility to avoid optical crosstalk for on-chip steady-state entanglement. © 2018 IOP Publishing Ltd.

A conceptual review on systems biology in health and diseases: from biological networks to modern therapeutics.

PubMed

Somvanshi, Pramod Rajaram; Venkatesh, K V

2014-03-01

Human physiology is an ensemble of various biological processes spanning from intracellular molecular interactions to the whole body phenotypic response. Systems biology endures to decipher these multi-scale biological networks and bridge the link between genotype to phenotype. The structure and dynamic properties of these networks are responsible for controlling and deciding the phenotypic state of a cell. Several cells and various tissues coordinate together to generate an organ level response which further regulates the ultimate physiological state. The overall network embeds a hierarchical regulatory structure, which when unusually perturbed can lead to undesirable physiological state termed as disease. Here, we treat a disease diagnosis problem analogous to a fault diagnosis problem in engineering systems. Accordingly we review the application of engineering methodologies to address human diseases from systems biological perspective. The review highlights potential networks and modeling approaches used for analyzing human diseases. The application of such analysis is illustrated in the case of cancer and diabetes. We put forth a concept of cell-to-human framework comprising of five modules (data mining, networking, modeling, experimental and validation) for addressing human physiology and diseases based on a paradigm of system level analysis. The review overtly emphasizes on the importance of multi-scale biological networks and subsequent modeling and analysis for drug target identification and designing efficient therapies.

TinkerCell: modular CAD tool for synthetic biology.

PubMed

Chandran, Deepak; Bergmann, Frank T; Sauro, Herbert M

2009-10-29

Synthetic biology brings together concepts and techniques from engineering and biology. In this field, computer-aided design (CAD) is necessary in order to bridge the gap between computational modeling and biological data. Using a CAD application, it would be possible to construct models using available biological "parts" and directly generate the DNA sequence that represents the model, thus increasing the efficiency of design and construction of synthetic networks. An application named TinkerCell has been developed in order to serve as a CAD tool for synthetic biology. TinkerCell is a visual modeling tool that supports a hierarchy of biological parts. Each part in this hierarchy consists of a set of attributes that define the part, such as sequence or rate constants. Models that are constructed using these parts can be analyzed using various third-party C and Python programs that are hosted by TinkerCell via an extensive C and Python application programming interface (API). TinkerCell supports the notion of a module, which are networks with interfaces. Such modules can be connected to each other, forming larger modular networks. TinkerCell is a free and open-source project under the Berkeley Software Distribution license. Downloads, documentation, and tutorials are available at http://www.tinkercell.com. An ideal CAD application for engineering biological systems would provide features such as: building and simulating networks, analyzing robustness of networks, and searching databases for components that meet the design criteria. At the current state of synthetic biology, there are no established methods for measuring robustness or identifying components that fit a design. The same is true for databases of biological parts. TinkerCell's flexible modeling framework allows it to cope with changes in the field. Such changes may involve the way parts are characterized or the way synthetic networks are modeled and analyzed computationally. TinkerCell can readily accept third-party algorithms, allowing it to serve as a platform for testing different methods relevant to synthetic biology.

TinkerCell: modular CAD tool for synthetic biology

PubMed Central

Chandran, Deepak; Bergmann, Frank T; Sauro, Herbert M

2009-01-01

Background Synthetic biology brings together concepts and techniques from engineering and biology. In this field, computer-aided design (CAD) is necessary in order to bridge the gap between computational modeling and biological data. Using a CAD application, it would be possible to construct models using available biological "parts" and directly generate the DNA sequence that represents the model, thus increasing the efficiency of design and construction of synthetic networks. Results An application named TinkerCell has been developed in order to serve as a CAD tool for synthetic biology. TinkerCell is a visual modeling tool that supports a hierarchy of biological parts. Each part in this hierarchy consists of a set of attributes that define the part, such as sequence or rate constants. Models that are constructed using these parts can be analyzed using various third-party C and Python programs that are hosted by TinkerCell via an extensive C and Python application programming interface (API). TinkerCell supports the notion of a module, which are networks with interfaces. Such modules can be connected to each other, forming larger modular networks. TinkerCell is a free and open-source project under the Berkeley Software Distribution license. Downloads, documentation, and tutorials are available at . Conclusion An ideal CAD application for engineering biological systems would provide features such as: building and simulating networks, analyzing robustness of networks, and searching databases for components that meet the design criteria. At the current state of synthetic biology, there are no established methods for measuring robustness or identifying components that fit a design. The same is true for databases of biological parts. TinkerCell's flexible modeling framework allows it to cope with changes in the field. Such changes may involve the way parts are characterized or the way synthetic networks are modeled and analyzed computationally. TinkerCell can readily accept third-party algorithms, allowing it to serve as a platform for testing different methods relevant to synthetic biology. PMID:19874625

Wireless Acoustic Measurement System

NASA Technical Reports Server (NTRS)

Anderson, Paul D.; Dorland, Wade D.; Jolly, Ronald L.

2007-01-01

A prototype wireless acoustic measurement system (WAMS) is one of two main subsystems of the Acoustic Prediction/ Measurement Tool, which comprises software, acoustic instrumentation, and electronic hardware combined to afford integrated capabilities for predicting and measuring noise emitted by rocket and jet engines. The other main subsystem is described in the article on page 8. The WAMS includes analog acoustic measurement instrumentation and analog and digital electronic circuitry combined with computer wireless local-area networking to enable (1) measurement of sound-pressure levels at multiple locations in the sound field of an engine under test and (2) recording and processing of the measurement data. At each field location, the measurements are taken by a portable unit, denoted a field station. There are ten field stations, each of which can take two channels of measurements. Each field station is equipped with two instrumentation microphones, a micro- ATX computer, a wireless network adapter, an environmental enclosure, a directional radio antenna, and a battery power supply. The environmental enclosure shields the computer from weather and from extreme acoustically induced vibrations. The power supply is based on a marine-service lead-acid storage battery that has enough capacity to support operation for as long as 10 hours. A desktop computer serves as a control server for the WAMS. The server is connected to a wireless router for communication with the field stations via a wireless local-area network that complies with wireless-network standard 802.11b of the Institute of Electrical and Electronics Engineers. The router and the wireless network adapters are controlled by use of Linux-compatible driver software. The server runs custom Linux software for synchronizing the recording of measurement data in the field stations. The software includes a module that provides an intuitive graphical user interface through which an operator at the control server can control the operations of the field stations for calibration and for recording of measurement data. A test engineer positions and activates the WAMS. The WAMS automatically establishes the wireless network. Next, the engineer performs pretest calibrations. Then the engineer executes the test and measurement procedures. After the test, the raw measurement files are copied and transferred, through the wireless network, to a hard disk in the control server. Subsequently, the data are processed into 1.3-octave spectrograms.

Wireless Acoustic Measurement System

NASA Technical Reports Server (NTRS)

Anderson, Paul D.; Dorland, Wade D.

2005-01-01

A prototype wireless acoustic measurement system (WAMS) is one of two main subsystems of the Acoustic Prediction/Measurement Tool, which comprises software, acoustic instrumentation, and electronic hardware combined to afford integrated capabilities for predicting and measuring noise emitted by rocket and jet engines. The other main subsystem is described in "Predicting Rocket or Jet Noise in Real Time" (SSC-00215-1), which appears elsewhere in this issue of NASA Tech Briefs. The WAMS includes analog acoustic measurement instrumentation and analog and digital electronic circuitry combined with computer wireless local-area networking to enable (1) measurement of sound-pressure levels at multiple locations in the sound field of an engine under test and (2) recording and processing of the measurement data. At each field location, the measurements are taken by a portable unit, denoted a field station. There are ten field stations, each of which can take two channels of measurements. Each field station is equipped with two instrumentation microphones, a micro-ATX computer, a wireless network adapter, an environmental enclosure, a directional radio antenna, and a battery power supply. The environmental enclosure shields the computer from weather and from extreme acoustically induced vibrations. The power supply is based on a marine-service lead-acid storage battery that has enough capacity to support operation for as long as 10 hours. A desktop computer serves as a control server for the WAMS. The server is connected to a wireless router for communication with the field stations via a wireless local-area network that complies with wireless-network standard 802.11b of the Institute of Electrical and Electronics Engineers. The router and the wireless network adapters are controlled by use of Linux-compatible driver software. The server runs custom Linux software for synchronizing the recording of measurement data in the field stations. The software includes a module that provides an intuitive graphical user interface through which an operator at the control server can control the operations of the field stations for calibration and for recording of measurement data. A test engineer positions and activates the WAMS. The WAMS automatically establishes the wireless network. Next, the engineer performs pretest calibrations. Then the engineer executes the test and measurement procedures. After the test, the raw measurement files are copied and transferred, through the wireless network, to a hard disk in the control server. Subsequently, the data are processed into 1/3-octave spectrograms.

Regulatory Snapshots: integrative mining of regulatory modules from expression time series and regulatory networks.

PubMed

Gonçalves, Joana P; Aires, Ricardo S; Francisco, Alexandre P; Madeira, Sara C

2012-01-01

Explaining regulatory mechanisms is crucial to understand complex cellular responses leading to system perturbations. Some strategies reverse engineer regulatory interactions from experimental data, while others identify functional regulatory units (modules) under the assumption that biological systems yield a modular organization. Most modular studies focus on network structure and static properties, ignoring that gene regulation is largely driven by stimulus-response behavior. Expression time series are key to gain insight into dynamics, but have been insufficiently explored by current methods, which often (1) apply generic algorithms unsuited for expression analysis over time, due to inability to maintain the chronology of events or incorporate time dependency; (2) ignore local patterns, abundant in most interesting cases of transcriptional activity; (3) neglect physical binding or lack automatic association of regulators, focusing mainly on expression patterns; or (4) limit the discovery to a predefined number of modules. We propose Regulatory Snapshots, an integrative mining approach to identify regulatory modules over time by combining transcriptional control with response, while overcoming the above challenges. Temporal biclustering is first used to reveal transcriptional modules composed of genes showing coherent expression profiles over time. Personalized ranking is then applied to prioritize prominent regulators targeting the modules at each time point using a network of documented regulatory associations and the expression data. Custom graphics are finally depicted to expose the regulatory activity in a module at consecutive time points (snapshots). Regulatory Snapshots successfully unraveled modules underlying yeast response to heat shock and human epithelial-to-mesenchymal transition, based on regulations documented in the YEASTRACT and JASPAR databases, respectively, and available expression data. Regulatory players involved in functionally enriched processes related to these biological events were identified. Ranking scores further suggested ability to discern the primary role of a gene (target or regulator). Prototype is available at: http://kdbio.inesc-id.pt/software/regulatorysnapshots.

Regulatory Snapshots: Integrative Mining of Regulatory Modules from Expression Time Series and Regulatory Networks

PubMed Central

Gonçalves, Joana P.; Aires, Ricardo S.; Francisco, Alexandre P.; Madeira, Sara C.

2012-01-01

Explaining regulatory mechanisms is crucial to understand complex cellular responses leading to system perturbations. Some strategies reverse engineer regulatory interactions from experimental data, while others identify functional regulatory units (modules) under the assumption that biological systems yield a modular organization. Most modular studies focus on network structure and static properties, ignoring that gene regulation is largely driven by stimulus-response behavior. Expression time series are key to gain insight into dynamics, but have been insufficiently explored by current methods, which often (1) apply generic algorithms unsuited for expression analysis over time, due to inability to maintain the chronology of events or incorporate time dependency; (2) ignore local patterns, abundant in most interesting cases of transcriptional activity; (3) neglect physical binding or lack automatic association of regulators, focusing mainly on expression patterns; or (4) limit the discovery to a predefined number of modules. We propose Regulatory Snapshots, an integrative mining approach to identify regulatory modules over time by combining transcriptional control with response, while overcoming the above challenges. Temporal biclustering is first used to reveal transcriptional modules composed of genes showing coherent expression profiles over time. Personalized ranking is then applied to prioritize prominent regulators targeting the modules at each time point using a network of documented regulatory associations and the expression data. Custom graphics are finally depicted to expose the regulatory activity in a module at consecutive time points (snapshots). Regulatory Snapshots successfully unraveled modules underlying yeast response to heat shock and human epithelial-to-mesenchymal transition, based on regulations documented in the YEASTRACT and JASPAR databases, respectively, and available expression data. Regulatory players involved in functionally enriched processes related to these biological events were identified. Ranking scores further suggested ability to discern the primary role of a gene (target or regulator). Prototype is available at: http://kdbio.inesc-id.pt/software/regulatorysnapshots. PMID:22563474

Functional Module Analysis for Gene Coexpression Networks with Network Integration.

PubMed

Zhang, Shuqin; Zhao, Hongyu; Ng, Michael K

2015-01-01

Network has been a general tool for studying the complex interactions between different genes, proteins, and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases, a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with three complete subgraphs, and 11 modules with two complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.

Reverse engineering a mouse embryonic stem cell-specific transcriptional network reveals a new modulator of neuronal differentiation.

PubMed

De Cegli, Rossella; Iacobacci, Simona; Flore, Gemma; Gambardella, Gennaro; Mao, Lei; Cutillo, Luisa; Lauria, Mario; Klose, Joachim; Illingworth, Elizabeth; Banfi, Sandro; di Bernardo, Diego

2013-01-01

Gene expression profiles can be used to infer previously unknown transcriptional regulatory interaction among thousands of genes, via systems biology 'reverse engineering' approaches. We 'reverse engineered' an embryonic stem (ES)-specific transcriptional network from 171 gene expression profiles, measured in ES cells, to identify master regulators of gene expression ('hubs'). We discovered that E130012A19Rik (E13), highly expressed in mouse ES cells as compared with differentiated cells, was a central 'hub' of the network. We demonstrated that E13 is a protein-coding gene implicated in regulating the commitment towards the different neuronal subtypes and glia cells. The overexpression and knock-down of E13 in ES cell lines, undergoing differentiation into neurons and glia cells, caused a strong up-regulation of the glutamatergic neurons marker Vglut2 and a strong down-regulation of the GABAergic neurons marker GAD65 and of the radial glia marker Blbp. We confirmed E13 expression in the cerebral cortex of adult mice and during development. By immuno-based affinity purification, we characterized protein partners of E13, involved in the Polycomb complex. Our results suggest a role of E13 in regulating the division between glutamatergic projection neurons and GABAergic interneurons and glia cells possibly by epigenetic-mediated transcriptional regulation.

The Waukesha Turbocharger Control Module: A tool for improved engine efficiency and response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zurlo, J.R.; Reinbold, E.O.; Mueller, J.

1996-12-31

The Waukesha Turbocharger Control Module allows optimum control of turbochargers on lean burn gaseous fueled engines. The Turbocharger Control Module is user programmed to provide either maximum engine efficiency or best engine response to load changes. In addition, the Turbocharger Control Module prevents undesirable turbocharger surge. The Turbocharger Control Module consists of an electronic control box, engine speed, intake manifold pressure, ambient temperature sensors, and electric actuators driving compressor bypass and wastegate valves. The Turbocharger Control Module expands the steady state operational environment of the Waukesha AT27GL natural gas engine from sea level to 1,525 m altitude with one turbochargermore » match and improves the engine speed turn down by 80 RPM. Finally, the Turbocharger Control Module improves engine response to load changes.« less

78 FR 12359 - Goodman Networks, Inc., Core Network Engineering (Deployment Engineering) Division Including...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-22

...., Core Network Engineering (Deployment Engineering) Division Including Workers in the Core Network Engineering (Deployment Engineering) Division in Alpharetta, GA, Hunt Valley, MD, Naperville, IL, and St... Reconsideration applicable to workers and former workers of Goodman Networks, Inc., Core Network Engineering...

Development of the updated system of city underground pipelines based on Visual Studio

NASA Astrophysics Data System (ADS)

Zhang, Jianxiong; Zhu, Yun; Li, Xiangdong

2009-10-01

Our city has owned the integrated pipeline network management system with ArcGIS Engine 9.1 as the bottom development platform and with Oracle9i as basic database for storaging data. In this system, ArcGIS SDE9.1 is applied as the spatial data engine, and the system was a synthetic management software developed with Visual Studio visualization procedures development tools. As the pipeline update function of the system has the phenomenon of slower update and even sometimes the data lost, to ensure the underground pipeline data can real-time be updated conveniently and frequently, and the actuality and integrity of the underground pipeline data, we have increased a new update module in the system developed and researched by ourselves. The module has the powerful data update function, and can realize the function of inputting and outputting and rapid update volume of data. The new developed module adopts Visual Studio visualization procedures development tools, and uses access as the basic database to storage data. We can edit the graphics in AutoCAD software, and realize the database update using link between the graphics and the system. Practice shows that the update module has good compatibility with the original system, reliable and high update efficient of the database.

Hierarchical thinking in network biology: the unbiased modularization of biochemical networks.

PubMed

Papin, Jason A; Reed, Jennifer L; Palsson, Bernhard O

2004-12-01

As reconstructed biochemical reaction networks continue to grow in size and scope, there is a growing need to describe the functional modules within them. Such modules facilitate the study of biological processes by deconstructing complex biological networks into conceptually simple entities. The definition of network modules is often based on intuitive reasoning. As an alternative, methods are being developed for defining biochemical network modules in an unbiased fashion. These unbiased network modules are mathematically derived from the structure of the whole network under consideration.

Impact of Multimedia and Network Services on an Introductory Level Course

NASA Technical Reports Server (NTRS)

Russ, John C.

1996-01-01

We will demonstrate and describe the impact of our use of multimedia and network connectivity on a sophomore-level introductory course in materials science. This class services all engineering students, resulting in large (more than 150) class sections with no hands-on laboratory. In 1990 we began to develop computer graphics that might substitute for some laboratory or real-world experiences, and demonstrate relationships hard to show with static textbook images or chalkboard drawings. We created a comprehensive series of modules that cover the entire course content. Called VIMS (Visualizations in Materials Science), these are available in the form of a CD-ROM and also via the internet.

Improvements in algal lipid production: a systems biology and gene editing approach.

PubMed

Banerjee, Avik; Banerjee, Chiranjib; Negi, Sangeeta; Chang, Jo-Shu; Shukla, Pratyoosh

2018-05-01

In the wake of rising energy demands, microalgae have emerged as potential sources of sustainable and renewable carbon-neutral fuels, such as bio-hydrogen and bio-oil. For rational metabolic engineering, the elucidation of metabolic pathways in fine detail and their manipulation according to requirements is the key to exploiting the use of microalgae. Emergence of site-specific nucleases have revolutionized applied research leading to biotechnological gains. Genome engineering as well as modulation of the endogenous genome with high precision using CRISPR systems is being gradually employed in microalgal research. Further, to optimize and produce better algal platforms, use of systems biology network analysis and integration of omics data is required. This review discusses two important approaches: systems biology and gene editing strategies used on microalgal systems with a focus on biofuel production and sustainable solutions. It also emphasizes that the integration of such systems would contribute and compliment applied research on microalgae. Recent advances in microalgae are discussed, including systems biology, gene editing approaches in lipid bio-synthesis, and antenna engineering. Lastly, it has been attempted here to showcase how CRISPR/Cas systems are a better editing tool than existing techniques that can be utilized for gene modulation and engineering during biofuel production.

Rapidly Characterizing the Fast Dynamics of RNA Genetic Circuitry with Cell-Free Transcription–Translation (TX-TL) Systems

PubMed Central

2014-01-01

RNA regulators are emerging as powerful tools to engineer synthetic genetic networks or rewire existing ones. A potential strength of RNA networks is that they may be able to propagate signals on time scales that are set by the fast degradation rates of RNAs. However, a current bottleneck to verifying this potential is the slow design-build-test cycle of evaluating these networks in vivo. Here, we adapt an Escherichia coli-based cell-free transcription-translation (TX-TL) system for rapidly prototyping RNA networks. We used this system to measure the response time of an RNA transcription cascade to be approximately five minutes per step of the cascade. We also show that this response time can be adjusted with temperature and regulator threshold tuning. Finally, we use TX-TL to prototype a new RNA network, an RNA single input module, and show that this network temporally stages the expression of two genes in vivo. PMID:24621257

Foundations and Emerging Paradigms for Computing in Living Cells.

PubMed

Ma, Kevin C; Perli, Samuel D; Lu, Timothy K

2016-02-27

Genetic circuits, composed of complex networks of interacting molecular machines, enable living systems to sense their dynamic environments, perform computation on the inputs, and formulate appropriate outputs. By rewiring and expanding these circuits with novel parts and modules, synthetic biologists have adapted living systems into vibrant substrates for engineering. Diverse paradigms have emerged for designing, modeling, constructing, and characterizing such artificial genetic systems. In this paper, we first provide an overview of recent advances in the development of genetic parts and highlight key engineering approaches. We then review the assembly of these parts into synthetic circuits from the perspectives of digital and analog logic, systems biology, and metabolic engineering, three areas of particular theoretical and practical interest. Finally, we discuss notable challenges that the field of synthetic biology still faces in achieving reliable and predictable forward-engineering of artificial biological circuits. Copyright © 2016. Published by Elsevier Ltd.

Directed network modules

NASA Astrophysics Data System (ADS)

Palla, Gergely; Farkas, Illés J.; Pollner, Péter; Derényi, Imre; Vicsek, Tamás

2007-06-01

A search technique locating network modules, i.e. internally densely connected groups of nodes in directed networks is introduced by extending the clique percolation method originally proposed for undirected networks. After giving a suitable definition for directed modules we investigate their percolation transition in the Erdos-Rényi graph both analytically and numerically. We also analyse four real-world directed networks, including Google's own web-pages, an email network, a word association graph and the transcriptional regulatory network of the yeast Saccharomyces cerevisiae. The obtained directed modules are validated by additional information available for the nodes. We find that directed modules of real-world graphs inherently overlap and the investigated networks can be classified into two major groups in terms of the overlaps between the modules. Accordingly, in the word-association network and Google's web-pages, overlaps are likely to contain in-hubs, whereas the modules in the email and transcriptional regulatory network tend to overlap via out-hubs.

78 FR 42758 - 36(b)(1) Arms Sales Notification

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-17

... aircraft, to include: Inlet/Fan Modules, Core Engine Modules, Rear Compressor Drive Turbines, Fan Drive...-PW-229 engines for the Hellenic Air Force F-16 aircraft, to include: Inlet/Fan Modules, Core Engine Modules, Rear Compressor Drive Turbines, Fan Drive Turbine Modules, Augmentor Duct and Nozzle Modules, and...

Compression of Flow Can Reveal Overlapping-Module Organization in Networks

NASA Astrophysics Data System (ADS)

Viamontes Esquivel, Alcides; Rosvall, Martin

2011-10-01

To better understand the organization of overlapping modules in large networks with respect to flow, we introduce the map equation for overlapping modules. In this information-theoretic framework, we use the correspondence between compression and regularity detection. The generalized map equation measures how well we can compress a description of flow in the network when we partition it into modules with possible overlaps. When we minimize the generalized map equation over overlapping network partitions, we detect modules that capture flow and determine which nodes at the boundaries between modules should be classified in multiple modules and to what degree. With a novel greedy-search algorithm, we find that some networks, for example, the neural network of the nematode Caenorhabditis elegans, are best described by modules dominated by hard boundaries, but that others, for example, the sparse European-roads network, have an organization of highly overlapping modules.

The middleware architecture supports heterogeneous network systems for module-based personal robot system

NASA Astrophysics Data System (ADS)

Choo, Seongho; Li, Vitaly; Choi, Dong Hee; Jung, Gi Deck; Park, Hong Seong; Ryuh, Youngsun

2005-12-01

On developing the personal robot system presently, the internal architecture is every module those occupy separated functions are connected through heterogeneous network system. This module-based architecture supports specialization and division of labor at not only designing but also implementation, as an effect of this architecture, it can reduce developing times and costs for modules. Furthermore, because every module is connected among other modules through network systems, we can get easy integrations and synergy effect to apply advanced mutual functions by co-working some modules. In this architecture, one of the most important technologies is the network middleware that takes charge communications among each modules connected through heterogeneous networks systems. The network middleware acts as the human nerve system inside of personal robot system; it relays, transmits, and translates information appropriately between modules that are similar to human organizations. The network middleware supports various hardware platform, heterogeneous network systems (Ethernet, Wireless LAN, USB, IEEE 1394, CAN, CDMA-SMS, RS-232C). This paper discussed some mechanisms about our network middleware to intercommunication and routing among modules, methods for real-time data communication and fault-tolerant network service. There have designed and implemented a layered network middleware scheme, distributed routing management, network monitoring/notification technology on heterogeneous networks for these goals. The main theme is how to make routing information in our network middleware. Additionally, with this routing information table, we appended some features. Now we are designing, making a new version network middleware (we call 'OO M/W') that can support object-oriented operation, also are updating program sources itself for object-oriented architecture. It is lighter, faster, and can support more operation systems and heterogeneous network systems, but other general purposed middlewares like CORBA, UPnP, etc. can support only one network protocol or operating system.

Is My Network Module Preserved and Reproducible?

PubMed Central

Langfelder, Peter; Luo, Rui; Oldham, Michael C.; Horvath, Steve

2011-01-01

In many applications, one is interested in determining which of the properties of a network module change across conditions. For example, to validate the existence of a module, it is desirable to show that it is reproducible (or preserved) in an independent test network. Here we study several types of network preservation statistics that do not require a module assignment in the test network. We distinguish network preservation statistics by the type of the underlying network. Some preservation statistics are defined for a general network (defined by an adjacency matrix) while others are only defined for a correlation network (constructed on the basis of pairwise correlations between numeric variables). Our applications show that the correlation structure facilitates the definition of particularly powerful module preservation statistics. We illustrate that evaluating module preservation is in general different from evaluating cluster preservation. We find that it is advantageous to aggregate multiple preservation statistics into summary preservation statistics. We illustrate the use of these methods in six gene co-expression network applications including 1) preservation of cholesterol biosynthesis pathway in mouse tissues, 2) comparison of human and chimpanzee brain networks, 3) preservation of selected KEGG pathways between human and chimpanzee brain networks, 4) sex differences in human cortical networks, 5) sex differences in mouse liver networks. While we find no evidence for sex specific modules in human cortical networks, we find that several human cortical modules are less preserved in chimpanzees. In particular, apoptosis genes are differentially co-expressed between humans and chimpanzees. Our simulation studies and applications show that module preservation statistics are useful for studying differences between the modular structure of networks. Data, R software and accompanying tutorials can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/ModulePreservation. PMID:21283776

How electrostatic networks modulate specificity and stability of collagen.

PubMed

Zheng, Hongning; Lu, Cheng; Lan, Jun; Fan, Shilong; Nanda, Vikas; Xu, Fei

2018-06-12

One-quarter of the 28 types of natural collagen exist as heterotrimers. The oligomerization state of collagen affects the structure and mechanics of the extracellular matrix, providing essential cues to modulate biological and pathological processes. A lack of high-resolution structural information limits our mechanistic understanding of collagen heterospecific self-assembly. Here, the 1.77-Å resolution structure of a synthetic heterotrimer demonstrates the balance of intermolecular electrostatics and hydrogen bonding that affects collagen stability and heterospecificity of assembly. Atomistic simulations and mutagenesis based on the solved structure are used to explore the contributions of specific interactions to energetics. A predictive model of collagen stability and specificity is developed for engineering novel collagen structures.

Reverse-engineering the genetic circuitry of a cancer cell with predicted intervention in chronic lymphocytic leukemia.

PubMed

Vallat, Laurent; Kemper, Corey A; Jung, Nicolas; Maumy-Bertrand, Myriam; Bertrand, Frédéric; Meyer, Nicolas; Pocheville, Arnaud; Fisher, John W; Gribben, John G; Bahram, Seiamak

2013-01-08

Cellular behavior is sustained by genetic programs that are progressively disrupted in pathological conditions--notably, cancer. High-throughput gene expression profiling has been used to infer statistical models describing these cellular programs, and development is now needed to guide orientated modulation of these systems. Here we develop a regression-based model to reverse-engineer a temporal genetic program, based on relevant patterns of gene expression after cell stimulation. This method integrates the temporal dimension of biological rewiring of genetic programs and enables the prediction of the effect of targeted gene disruption at the system level. We tested the performance accuracy of this model on synthetic data before reverse-engineering the response of primary cancer cells to a proliferative (protumorigenic) stimulation in a multistate leukemia biological model (i.e., chronic lymphocytic leukemia). To validate the ability of our method to predict the effects of gene modulation on the global program, we performed an intervention experiment on a targeted gene. Comparison of the predicted and observed gene expression changes demonstrates the possibility of predicting the effects of a perturbation in a gene regulatory network, a first step toward an orientated intervention in a cancer cell genetic program.

Arabidopsis Ensemble Reverse-Engineered Gene Regulatory Network Discloses Interconnected Transcription Factors in Oxidative Stress[W

PubMed Central

Vermeirssen, Vanessa; De Clercq, Inge; Van Parys, Thomas; Van Breusegem, Frank; Van de Peer, Yves

2014-01-01

The abiotic stress response in plants is complex and tightly controlled by gene regulation. We present an abiotic stress gene regulatory network of 200,014 interactions for 11,938 target genes by integrating four complementary reverse-engineering solutions through average rank aggregation on an Arabidopsis thaliana microarray expression compendium. This ensemble performed the most robustly in benchmarking and greatly expands upon the availability of interactions currently reported. Besides recovering 1182 known regulatory interactions, cis-regulatory motifs and coherent functionalities of target genes corresponded with the predicted transcription factors. We provide a valuable resource of 572 abiotic stress modules of coregulated genes with functional and regulatory information, from which we deduced functional relationships for 1966 uncharacterized genes and many regulators. Using gain- and loss-of-function mutants of seven transcription factors grown under control and salt stress conditions, we experimentally validated 141 out of 271 predictions (52% precision) for 102 selected genes and mapped 148 additional transcription factor-gene regulatory interactions (49% recall). We identified an intricate core oxidative stress regulatory network where NAC13, NAC053, ERF6, WRKY6, and NAC032 transcription factors interconnect and function in detoxification. Our work shows that ensemble reverse-engineering can generate robust biological hypotheses of gene regulation in a multicellular eukaryote that can be tested by medium-throughput experimental validation. PMID:25549671

Arabidopsis ensemble reverse-engineered gene regulatory network discloses interconnected transcription factors in oxidative stress.

PubMed

Vermeirssen, Vanessa; De Clercq, Inge; Van Parys, Thomas; Van Breusegem, Frank; Van de Peer, Yves

2014-12-01

The abiotic stress response in plants is complex and tightly controlled by gene regulation. We present an abiotic stress gene regulatory network of 200,014 interactions for 11,938 target genes by integrating four complementary reverse-engineering solutions through average rank aggregation on an Arabidopsis thaliana microarray expression compendium. This ensemble performed the most robustly in benchmarking and greatly expands upon the availability of interactions currently reported. Besides recovering 1182 known regulatory interactions, cis-regulatory motifs and coherent functionalities of target genes corresponded with the predicted transcription factors. We provide a valuable resource of 572 abiotic stress modules of coregulated genes with functional and regulatory information, from which we deduced functional relationships for 1966 uncharacterized genes and many regulators. Using gain- and loss-of-function mutants of seven transcription factors grown under control and salt stress conditions, we experimentally validated 141 out of 271 predictions (52% precision) for 102 selected genes and mapped 148 additional transcription factor-gene regulatory interactions (49% recall). We identified an intricate core oxidative stress regulatory network where NAC13, NAC053, ERF6, WRKY6, and NAC032 transcription factors interconnect and function in detoxification. Our work shows that ensemble reverse-engineering can generate robust biological hypotheses of gene regulation in a multicellular eukaryote that can be tested by medium-throughput experimental validation. © 2014 American Society of Plant Biologists. All rights reserved.

The behaviour of basic autocatalytic signalling modules in isolation and embedded in networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnan, J.; Mois, Kristina; Suwanmajo, Thapanar

2014-11-07

In this paper, we examine the behaviour of basic autocatalytic feedback modules involving a species catalyzing its own production, either directly or indirectly. We first perform a systematic study of the autocatalytic feedback module in isolation, examining the effect of different factors, showing how this module is capable of exhibiting monostable threshold and bistable switch-like behaviour. We then study the behaviour of this module embedded in different kinds of basic networks including (essentially) irreversible cycles, open and closed reversible chains, and networks with additional feedback. We study the behaviour of the networks deterministically and also stochastically, using simulations, analytical work,more » and bifurcation analysis. We find that (i) there are significant differences between the behaviour of this module in isolation and in a network: thresholds may be altered or destroyed and bistability may be destroyed or even induced, even when the ambient network is simple. The global characteristics and topology of this network and the position of the module in the ambient network can play important and unexpected roles. (ii) There can be important differences between the deterministic and stochastic dynamics of the module embedded in networks, which may be accentuated by the ambient network. This provides new insights into the functioning of such enzymatic modules individually and as part of networks, with relevance to other enzymatic signalling modules as well.« less

The behaviour of basic autocatalytic signalling modules in isolation and embedded in networks

NASA Astrophysics Data System (ADS)

Krishnan, J.; Mois, Kristina; Suwanmajo, Thapanar

2014-11-01

In this paper, we examine the behaviour of basic autocatalytic feedback modules involving a species catalyzing its own production, either directly or indirectly. We first perform a systematic study of the autocatalytic feedback module in isolation, examining the effect of different factors, showing how this module is capable of exhibiting monostable threshold and bistable switch-like behaviour. We then study the behaviour of this module embedded in different kinds of basic networks including (essentially) irreversible cycles, open and closed reversible chains, and networks with additional feedback. We study the behaviour of the networks deterministically and also stochastically, using simulations, analytical work, and bifurcation analysis. We find that (i) there are significant differences between the behaviour of this module in isolation and in a network: thresholds may be altered or destroyed and bistability may be destroyed or even induced, even when the ambient network is simple. The global characteristics and topology of this network and the position of the module in the ambient network can play important and unexpected roles. (ii) There can be important differences between the deterministic and stochastic dynamics of the module embedded in networks, which may be accentuated by the ambient network. This provides new insights into the functioning of such enzymatic modules individually and as part of networks, with relevance to other enzymatic signalling modules as well.

Revealing the Hidden Relationship by Sparse Modules in Complex Networks with a Large-Scale Analysis

PubMed Central

Jiao, Qing-Ju; Huang, Yan; Liu, Wei; Wang, Xiao-Fan; Chen, Xiao-Shuang; Shen, Hong-Bin

2013-01-01

One of the remarkable features of networks is module that can provide useful insights into not only network organizations but also functional behaviors between their components. Comprehensive efforts have been devoted to investigating cohesive modules in the past decade. However, it is still not clear whether there are important structural characteristics of the nodes that do not belong to any cohesive module. In order to answer this question, we performed a large-scale analysis on 25 complex networks with different types and scales using our recently developed BTS (bintree seeking) algorithm, which is able to detect both cohesive and sparse modules in the network. Our results reveal that the sparse modules composed by the cohesively isolated nodes widely co-exist with the cohesive modules. Detailed analysis shows that both types of modules provide better characterization for the division of a network into functional units than merely cohesive modules, because the sparse modules possibly re-organize the nodes in the so-called cohesive modules, which lack obvious modular significance, into meaningful groups. Compared with cohesive modules, the sizes of sparse ones are generally smaller. Sparse modules are also found to have preferences in social and biological networks than others. PMID:23762457

An iterative network partition algorithm for accurate identification of dense network modules

PubMed Central

Sun, Siqi; Dong, Xinran; Fu, Yao; Tian, Weidong

2012-01-01

A key step in network analysis is to partition a complex network into dense modules. Currently, modularity is one of the most popular benefit functions used to partition network modules. However, recent studies suggested that it has an inherent limitation in detecting dense network modules. In this study, we observed that despite the limitation, modularity has the advantage of preserving the primary network structure of the undetected modules. Thus, we have developed a simple iterative Network Partition (iNP) algorithm to partition a network. The iNP algorithm provides a general framework in which any modularity-based algorithm can be implemented in the network partition step. Here, we tested iNP with three modularity-based algorithms: multi-step greedy (MSG), spectral clustering and Qcut. Compared with the original three methods, iNP achieved a significant improvement in the quality of network partition in a benchmark study with simulated networks, identified more modules with significantly better enrichment of functionally related genes in both yeast protein complex network and breast cancer gene co-expression network, and discovered more cancer-specific modules in the cancer gene co-expression network. As such, iNP should have a broad application as a general method to assist in the analysis of biological networks. PMID:22121225

Non-Markovian quantum feedback networks II: Controlled flows

NASA Astrophysics Data System (ADS)

Gough, John E.

2017-06-01

The concept of a controlled flow of a dynamical system, especially when the controlling process feeds information back about the system, is of central importance in control engineering. In this paper, we build on the ideas presented by Bouten and van Handel [Quantum Stochastics and Information: Statistics, Filtering and Control (World Scientific, 2008)] and develop a general theory of quantum feedback. We elucidate the relationship between the controlling processes, Z, and the measured processes, Y, and to this end we make a distinction between what we call the input picture and the output picture. We should note that the input-output relations for the noise fields have additional terms not present in the standard theory but that the relationship between the control processes and measured processes themselves is internally consistent—we do this for the two main cases of quadrature measurement and photon-counting measurement. The theory is general enough to include a modulating filter which post-processes the measurement readout Y before returning to the system. This opens up the prospect of applying very general engineering feedback control techniques to open quantum systems in a systematic manner, and we consider a number of specific modulating filter problems. Finally, we give a brief argument as to why most of the rules for making instantaneous feedback connections [J. Gough and M. R. James, Commun. Math. Phys. 287, 1109 (2009)] ought to apply for controlled dynamical networks as well.

Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network

PubMed Central

2011-01-01

Background Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. Results We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism’s metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. Conclusions After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis. PMID:22784571

Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network.

PubMed

Kim, Hyun Uk; Kim, Tae Yong; Lee, Sang Yup

2011-01-01

Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism's metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

Engineering of a synthetic quadrastable gene network to approach Waddington landscape and cell fate determination.

PubMed

Wu, Fuqing; Su, Ri-Qi; Lai, Ying-Cheng; Wang, Xiao

2017-04-11

The process of cell fate determination has been depicted intuitively as cells travelling and resting on a rugged landscape, which has been probed by various theoretical studies. However, few studies have experimentally demonstrated how underlying gene regulatory networks shape the landscape and hence orchestrate cellular decision-making in the presence of both signal and noise. Here we tested different topologies and verified a synthetic gene circuit with mutual inhibition and auto-activations to be quadrastable, which enables direct study of quadruple cell fate determination on an engineered landscape. We show that cells indeed gravitate towards local minima and signal inductions dictate cell fates through modulating the shape of the multistable landscape. Experiments, guided by model predictions, reveal that sequential inductions generate distinct cell fates by changing landscape in sequence and hence navigating cells to different final states. This work provides a synthetic biology framework to approach cell fate determination and suggests a landscape-based explanation of fixed induction sequences for targeted differentiation.

An Offload NIC for NASA, NLR, and Grid Computing

NASA Technical Reports Server (NTRS)

Awrach, James

2013-01-01

This work addresses distributed data management and access dynamically configurable high-speed access to data distributed and shared over wide-area high-speed network environments. An offload engine NIC (network interface card) is proposed that scales at nX10-Gbps increments through 100-Gbps full duplex. The Globus de facto standard was used in projects requiring secure, robust, high-speed bulk data transport. Novel extension mechanisms were derived that will combine these technologies for use by GridFTP, bandwidth management resources, and host CPU (central processing unit) acceleration. The result will be wire-rate encrypted Globus grid data transactions through offload for splintering, encryption, and compression. As the need for greater network bandwidth increases, there is an inherent need for faster CPUs. The best way to accelerate CPUs is through a network acceleration engine. Grid computing data transfers for the Globus tool set did not have wire-rate encryption or compression. Existing technology cannot keep pace with the greater bandwidths of backplane and network connections. Present offload engines with ports to Ethernet are 32 to 40 Gbps f-d at best. The best of ultra-high-speed offload engines use expensive ASICs (application specific integrated circuits) or NPUs (network processing units). The present state of the art also includes bonding and the use of multiple NICs that are also in the planning stages for future portability to ASICs and software to accommodate data rates at 100 Gbps. The remaining industry solutions are for carrier-grade equipment manufacturers, with costly line cards having multiples of 10-Gbps ports, or 100-Gbps ports such as CFP modules that interface to costly ASICs and related circuitry. All of the existing solutions vary in configuration based on requirements of the host, motherboard, or carriergrade equipment. The purpose of the innovation is to eliminate data bottlenecks within cluster, grid, and cloud computing systems, and to add several more capabilities while reducing space consumption and cost. Provisions were designed for interoperability with systems used in the NASA HEC (High-End Computing) program. The new acceleration engine consists of state-ofthe- art FPGA (field-programmable gate array) core IP, C, and Verilog code; novel communication protocol; and extensions to the Globus structure. The engine provides the functions of network acceleration, encryption, compression, packet-ordering, and security added to Globus grid or for cloud data transfer. This system is scalable in nX10-Gbps increments through 100-Gbps f-d. It can be interfaced to industry-standard system-side or network-side devices or core IP in increments of 10 GigE, scaling to provide IEEE 40/100 GigE compliance.

Modulation of high frequency noise by engine tones of small boats.

PubMed

Pollara, Alexander; Sutin, Alexander; Salloum, Hady

2017-07-01

The effect of modulation of high frequency ship noise by propeller rotation frequencies is well known. This modulation is observed with the Detection of Envelope Modulation on Noise (DEMON) algorithm. Analysis of the DEMON spectrum allows the revolutions per minute and number of blades of the propeller to be determined. This work shows that the high frequency noise of a small boat can also be modulated by engine frequencies. Prior studies have not reported high frequency noise amplitude modulated at engine frequencies. This modulation is likely produced by bubbles from the engine exhaust system.

Topological Alterations and Symptom-Relevant Modules in the Whole-Brain Structural Network in Semantic Dementia.

PubMed

Ding, Junhua; Chen, Keliang; Zhang, Weibin; Li, Ming; Chen, Yan; Yang, Qing; Lv, Yingru; Guo, Qihao; Han, Zaizhu

2017-01-01

Semantic dementia (SD) is characterized by a selective decline in semantic processing. Although the neuropsychological pattern of this disease has been identified, its topological global alterations and symptom-relevant modules in the whole-brain anatomical network have not been fully elucidated. This study aims to explore the topological alteration of anatomical network in SD and reveal the modules associated with semantic deficits in this disease. We first constructed the whole-brain white-matter networks of 20 healthy controls and 19 patients with SD. Then, the network metrics of graph theory were compared between these two groups. Finally, we separated the network of SD patients into different modules and correlated the structural integrity of each module with the severity of the semantic deficits across patients. The network of the SD patients presented a significantly reduced global efficiency, indicating that the long-distance connections were damaged. The network was divided into the following four distinctive modules: the left temporal/occipital/parietal, frontal, right temporal/occipital, and frontal/parietal modules. The first two modules were associated with the semantic deficits of SD. These findings illustrate the skeleton of the neuroanatomical network of SD patients and highlight the key role of the left temporal/occipital/parietal module and the left frontal module in semantic processing.

Continuous adjustment of threshold voltage in carbon nanotube field-effect transistors through gate engineering

NASA Astrophysics Data System (ADS)

Zhong, Donglai; Zhao, Chenyi; Liu, Lijun; Zhang, Zhiyong; Peng, Lian-Mao

2018-04-01

In this letter, we report a gate engineering method to adjust threshold voltage of carbon nanotube (CNT) based field-effect transistors (FETs) continuously in a wide range, which makes the application of CNT FETs especially in digital integrated circuits (ICs) easier. Top-gated FETs are fabricated using solution-processed CNT network films with stacking Pd and Sc films as gate electrodes. By decreasing the thickness of the lower layer metal (Pd) from 20 nm to zero, the effective work function of the gate decreases, thus tuning the threshold voltage (Vt) of CNT FETs from -1.0 V to 0.2 V. The continuous adjustment of threshold voltage through gate engineering lays a solid foundation for multi-threshold technology in CNT based ICs, which then can simultaneously provide high performance and low power circuit modules on one chip.

Engineering Lipases: walking the fine line between activity and stability

NASA Astrophysics Data System (ADS)

Dasetty, Siva; Blenner, Mark A.; Sarupria, Sapna

2017-11-01

Lipases are enzymes that hydrolyze lipids and have several industrial applications. There is a tremendous effort in engineering the activity, specificity and stability of lipases to render them functional in a variety of environmental conditions. In this review, we discuss the recent experimental and simulation studies focused on engineering lipases. Experimentally, mutagenesis studies have demonstrated that the activity, stability, and specificity of lipases can be modulated by mutations. It has been particularly challenging however, to elucidate the underlying mechanisms through which these mutations affect the lipase properties. We summarize results from experiments and molecular simulations highlighting the emerging picture to this end. We end the review with suggestions for future research which underscores the delicate balance of various facets in the lipase that affect their activity and stability necessitating the consideration of the enzyme as a network of interactions.

Secure Control Systems for the Energy Sector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Rhett; Campbell, Jack; Hadley, Mark

2012-03-31

Schweitzer Engineering Laboratories (SEL) will conduct the Hallmark Project to address the need to reduce the risk of energy disruptions because of cyber incidents on control systems. The goals is to develop solutions that can be both applied to existing control systems and designed into new control systems to add the security measures needed to mitigate energy network vulnerabilities. The scope of the Hallmark Project contains four primary elements: 1. Technology transfer of the Secure Supervisory Control and Data Acquisition (SCADA) Communications Protocol (SSCP) from Pacific Northwest National Laboratories (PNNL) to Schweitzer Engineering Laboratories (SEL). The project shall use thismore » technology to develop a Federal Information Processing Standard (FIPS) 140-2 compliant original equipment manufacturer (OEM) module to be called a Cryptographic Daughter Card (CDC) with the ability to directly connect to any PC enabling that computer to securely communicate across serial to field devices. Validate the OEM capabilities with another vendor. 2. Development of a Link Authenticator Module (LAM) using the FIPS 140-2 validated Secure SCADA Communications Protocol (SSCP) CDC module with a central management software kit. 3. Validation of the CDC and Link Authenticator modules via laboratory and field tests. 4. Creation of documents that record the impact of the Link Authenticator to the operators of control systems and on the control system itself. The information in the documents can assist others with technology deployment and maintenance.« less

Dynamic Control of Adsorption Sensitivity for Photo-EMF-Based Ammonia Gas Sensors Using a Wireless Network

PubMed Central

Vashpanov, Yuriy; Choo, Hyunseung; Kim, Dongsoo Stephen

2011-01-01

This paper proposes an adsorption sensitivity control method that uses a wireless network and illumination light intensity in a photo-electromagnetic field (EMF)-based gas sensor for measurements in real time of a wide range of ammonia concentrations. The minimum measurement error for a range of ammonia concentration from 3 to 800 ppm occurs when the gas concentration magnitude corresponds with the optimal intensity of the illumination light. A simulation with LabView-engineered modules for automatic control of a new intelligent computer system was conducted to improve measurement precision over a wide range of gas concentrations. This gas sensor computer system with wireless network technology could be useful in the chemical industry for automatic detection and measurement of hazardous ammonia gas levels in real time. PMID:22346680

Scalable Hierarchical Network Management System for Displaying Network Information in Three Dimensions

NASA Technical Reports Server (NTRS)

George, Jude (Inventor); Schlecht, Leslie (Inventor); McCabe, James D. (Inventor); LeKashman, John Jr. (Inventor)

1998-01-01

A network management system has SNMP agents distributed at one or more sites, an input output module at each site, and a server module located at a selected site for communicating with input output modules, each of which is configured for both SNMP and HNMP communications. The server module is configured exclusively for HNMP communications, and it communicates with each input output module according to the HNMP. Non-iconified, informationally complete views are provided of network elements to aid in network management.

SeaDataNet network services monitoring: Definition and Implementation of Service availability index

NASA Astrophysics Data System (ADS)

Lykiardopoulos, Angelos; Mpalopoulou, Stavroula; Vavilis, Panagiotis; Pantazi, Maria; Iona, Sissy

2014-05-01

SeaDataNet (SDN) is a standardized system for managing large and diverse data sets collected by the oceanographic fleets and the automatic observation systems. The SeaDataNet network is constituted of national oceanographic data centres of 35 countries, active in data collection. SeaDataNetII project's objective is to upgrade the present SeaDataNet infrastructure into an operationally robust and state-of-the-art infrastructure; therefore Network Monitoring is a step to this direction. The term Network Monitoring describes the use of system that constantly monitors a computer network for slow or failing components and that notifies the network administrator in case of outages. Network monitoring is crucial when implementing widely distributed systems over the Internet and in real-time systems as it detects malfunctions that may occur and notifies the system administrator who can immediately respond and correct the problem. In the framework of SeaDataNet II project a monitoring system was developed in order to monitor the SeaDataNet components. The core system is based on Nagios software. Some plug-ins were developed to support SeaDataNet modules. On the top of Nagios Engine a web portal was developed in order to give access to local administrators of SeaDataNet components, to view detailed logs of their own service(s). Currently the system monitors 35 SeaDataNet Download Managers, 9 SeaDataNet Services, 25 GeoSeas Download Managers and 23 UBSS Download Managers . Taking advantage of the continuous monitoring of SeaDataNet system components a total availability index will be implemented. The term availability can be defined as the ability of a functional unit to be in a state to perform a required function under given conditions at a given instant of time or over a given time interval, assuming that the required external resources are provided. Availability measures can be considered as a are very important benefit becauseT - The availability trends that can be extracted from the stored availability measurements will give an indication of the condition of the service modules. - Will help in planning upgrades planning - and the maintenance of the network service. - It is a prerequisite in case of signing a Service Level Agreement. To construct the service availability index, a method for measuring availability of SeaDataNet network is developed and a database is implemented to store the measured values. Although the measurements of availability of a single component in a network service can be considered as simple (is a percentage of time in a year that the service is available to the users), the ipmlementation of a method to measure the total availability of a composite system can be complicated and there is no a standardized method to deal with it. The method followed to calculate the total availability index in case of SeaDataNet can be described as follows: The whole system was divided in operational modules providing a single service in which the availability can be measured by monitoring portal. Next the dependences between these modules were defined in order to formulate the influence of availability of each module against the whole system. For each module a weight coefficient depending on module's involvement in total system productivity was defined. A mathematical formula was developed to measure the index.

Engineering naturally occurring trans-acting non-coding RNAs to sense molecular signals

PubMed Central

Qi, Lei; Lucks, Julius B.; Liu, Chang C.; Mutalik, Vivek K.; Arkin, Adam P.

2012-01-01

Non-coding RNAs (ncRNAs) are versatile regulators in cellular networks. While most trans-acting ncRNAs possess well-defined mechanisms that can regulate transcription or translation, they generally lack the ability to directly sense cellular signals. In this work, we describe a set of design principles for fusing ncRNAs to RNA aptamers to engineer allosteric RNA fusion molecules that modulate the activity of ncRNAs in a ligand-inducible way in Escherichia coli. We apply these principles to ncRNA regulators that can regulate translation (IS10 ncRNA) and transcription (pT181 ncRNA), and demonstrate that our design strategy exhibits high modularity between the aptamer ligand-sensing motif and the ncRNA target-recognition motif, which allows us to reconfigure these two motifs to engineer orthogonally acting fusion molecules that respond to different ligands and regulate different targets in the same cell. Finally, we show that the same ncRNA fused with different sensing domains results in a sensory-level NOR gate that integrates multiple input signals to perform genetic logic. These ligand-sensing ncRNA regulators provide useful tools to modulate the activity of structurally related families of ncRNAs, and building upon the growing body of RNA synthetic biology, our ability to design aptamer–ncRNA fusion molecules offers new ways to engineer ligand-sensing regulatory circuits. PMID:22383579

Polycyclic aromatic hydrocarbon metabolic network in Mycobacterium vanbaalenii PYR-1.

PubMed

Kweon, Ohgew; Kim, Seong-Jae; Holland, Ricky D; Chen, Hongyan; Kim, Dae-Wi; Gao, Yuan; Yu, Li-Rong; Baek, Songjoon; Baek, Dong-Heon; Ahn, Hongsik; Cerniglia, Carl E

2011-09-01

This study investigated a metabolic network (MN) from Mycobacterium vanbaalenii PYR-1 for polycyclic aromatic hydrocarbons (PAHs) from the perspective of structure, behavior, and evolution, in which multilayer omics data are integrated. Initially, we utilized a high-throughput proteomic analysis to assess the protein expression response of M. vanbaalenii PYR-1 to seven different aromatic compounds. A total of 3,431 proteins (57.38% of the genome-predicted proteins) were identified, which included 160 proteins that seemed to be involved in the degradation of aromatic hydrocarbons. Based on the proteomic data and the previous metabolic, biochemical, physiological, and genomic information, we reconstructed an experiment-based system-level PAH-MN. The structure of PAH-MN, with 183 metabolic compounds and 224 chemical reactions, has a typical scale-free nature. The behavior and evolution of the PAH-MN reveals a hierarchical modularity with funnel effects in structure/function and intimate association with evolutionary modules of the functional modules, which are the ring cleavage process (RCP), side chain process (SCP), and central aromatic process (CAP). The 189 commonly upregulated proteins in all aromatic hydrocarbon treatments provide insights into the global adaptation to facilitate the PAH metabolism. Taken together, the findings of our study provide the hierarchical viewpoint from genes/proteins/metabolites to the network via functional modules of the PAH-MN equipped with the engineering-driven approaches of modularization and rationalization, which may expand our understanding of the metabolic potential of M. vanbaalenii PYR-1 for bioremediation applications.

Communications Effects Server (CES) Model for Systems Engineering Research

DTIC Science & Technology

2012-01-31

Visualization Tool Interface «logical» HLA Tool Interface «logical» DIS Tool Interface «logical» STK Tool Interface «module» Execution Kernels «logical...interoperate with STK when running simulations. GUI Components  Architect – The Architect represents the main network design and visualization ...interest» CES «block» Third Party Visualization Tool «block» Third Party Analysis Tool «block» Third Party Text Editor «block» HLA Tools Analyst User Army

Time-Reversal Based Range Extension Technique for Ultra-wideband (UWB) Sensors and Applications in Tactical Communications and Networking

DTIC Science & Technology

2008-04-16

Zhen (Edward) Hu Peng (Peter) Zhang Yu Song Amanpreet Singh Saini Corey Cooke April 16, 2006 Department of Electrical and Computer Engineering Center...and RF frequency agility is the most challenging issue for spectrum sensing. The radio under development is an ultra-wideband software -defined radio...PC USB programming cable and accom- panying PC software as well as download test vectors to the waveform memory module, as shown in Figure 3.25,3I

Upgrade of optical WDM transport systems introducing linerates at 40 Gbit/s per channel

NASA Astrophysics Data System (ADS)

Schneiders, Malte; Vorbeck, Sascha; Aust, Nora

2006-10-01

Driven by high growth rates of internet traffic the question of upgrading existing optical metro-, regio- and long haul transport networks introducing 40 Gbit/s/λ is one of the most important questions today and in the near future. Current WDM Systems in photonic networks are commonly operated at linerates of 2.5 and 10 Gbit/s/λ. Induced by market analyses and the historical development of transport systems some work has already been carried out to evaluate update scenarios from 10 to 40 Gbit/s channel data rates. Due to the inherent quadruplication of the bandwidth per channel, limitations due to linear and non-linear transmission impairments become stronger resulting in a highly increased complexity of link engineering, potentially increasing the capital and operational expenditures. A lot of work is therefore in progress, which targets at the relaxation of constraints for 40 Gbit/s transmission to find the most efficient upgrade strategies. One approach towards an increased robustness against signal distortions is the introduction of more advanced modulation formats. Different modulation schemes show strongly different optical WDM transmission characteristics. The choice of the appropriate format does not only depend on the technical requirements, but also on economical considerations as an increased transmitter- and receiver-complexity will drive the transponder price. This article presents investigations on different modulation formats for the upgrade of existing metro-/ regio and long haul transport networks. Tolerances and robustness against the main degrading effects dispersion, noise and nonlinearities are considered together with mitigation strategies like the adaptation of dispersion maps. Results from numerical simulations are provided for some of the most promising modulation formats like NRZ, RZ, CS-RZ, Optical Duobinary and DPSK.

Experimental study on the thrust modulation performance of powdered magnesium and CO2 bipropellant engine

NASA Astrophysics Data System (ADS)

Li, Chao; Hu, Chunbo; Zhu, Xiaofei; Hu, Jiaming; Li, Yue; Hu, Xu

2018-06-01

Powdered Mg and CO2 bipropellant engine providing a practical demonstration of in situ resource utilization (ISRU) for Mars Sample Return (MSR) mission seems to be feasible by current investigations. However, essential functions of the engine to satisfy the complicated ballistics requirements such as thrust modulation and multiple pulse have not been established yet. The aim of this experimental study is to evaluate the engine's thrust modulation feasibility and to investigate its thrust modulation characteristics. A powdered Mg and CO2 bipropellant engine construction aiming to achieve thrust modulation ability was proposed. A mass flow rate calibration experiment to evaluate the gas-solid mass flow rate regulating performance was conducted before fire tests. Fire test result shows that the engine achieved successful ignition as well as self-sustaining combustion; Thrust modulation of the engine is feasible, detail thrust estimating result of the test shows that maximum thrust is 135.91 N and the minimum is 5.65 N with a 22.11 thrust modulation ratio, moreover, the transportation period is quick and the thrust modulation ratio is adjustable. At the same time, the powder feed system reaches a two-step flow rate regulating with a modulation ratio of 4.5-5. What' more, caused by the uneven engine working conditions, there is an obvious difference in combustion efficiency value, maximum combustion efficiency of the powdered Mg and CO2 bipropellant engine is 80.20%.

Finding Correlation between Protein Protein Interaction Modules Using Semantic Web Techniques

NASA Astrophysics Data System (ADS)

Kargar, Mehdi; Moaven, Shahrouz; Abolhassani, Hassan

Many complex networks such as social networks and computer show modular structures, where edges between nodes are much denser within modules than between modules. It is strongly believed that cellular networks are also modular, reflecting the relative independence and coherence of different functional units in a cell. In this paper we used a human curated dataset. In this paper we consider each module in the PPI network as ontology. Using techniques in ontology alignment, we compare each pair of modules in the network. We want to see that is there a correlation between the structure of each module or they have totally different structures. Our results show that there is no correlation between proteins in a protein protein interaction network.

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT VII, ENGINE TUNE-UP--DETROIT DIESEL ENGINE.

ERIC Educational Resources Information Center

Human Engineering Inst., Cleveland, OH.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF TUNE-UP PROCEDURES FOR DIESEL ENGINES. TOPICS ARE SCHEDULING TUNE-UPS, AND TUNE-UP PROCEDURES. THE MODULE CONSISTS OF A SELF-INSTRUCTIONAL BRANCH PROGRAMED TRAINING FILM "ENGINE TUNE-UP--DETROIT DIESEL ENGINE" AND OTHER MATERIALS. SEE VT 005 655 FOR FURTHER INFORMATION.…

Test results of a Stirling engine utilizing heat exchanger modules with an integral heat pipe

NASA Astrophysics Data System (ADS)

Skupinski, Robert C.; Tower, Leonard K.; Madi, Frank J.; Brusk, Kevin D.

1993-04-01

The Heat Pipe Stirling Engine (HP-1000), a free-piston Stirling engine incorporating three heat exchanger modules, each having a sodium filled heat pipe, has been tested at the NASA-Lewis Research Center as part of the Civil Space Technology Initiative (CSTI). The heat exchanger modules were designed to reduce the number of potential flow leak paths in the heat exchanger assembly and incorporate a heat pipe as the link between the heat source and the engine. An existing RE-1000 free-piston Stirling engine was modified to operate using the heat exchanger modules. This paper describes heat exchanger module and engine performance during baseline testing. Condenser temperature profiles, brake power, and efficiency are presented and discussed.

Test results of a Stirling engine utilizing heat exchanger modules with an integral heat pipe

NASA Technical Reports Server (NTRS)

Skupinski, Robert C.; Tower, Leonard K.; Madi, Frank J.; Brusk, Kevin D.

1993-01-01

The Heat Pipe Stirling Engine (HP-1000), a free-piston Stirling engine incorporating three heat exchanger modules, each having a sodium filled heat pipe, has been tested at the NASA-Lewis Research Center as part of the Civil Space Technology Initiative (CSTI). The heat exchanger modules were designed to reduce the number of potential flow leak paths in the heat exchanger assembly and incorporate a heat pipe as the link between the heat source and the engine. An existing RE-1000 free-piston Stirling engine was modified to operate using the heat exchanger modules. This paper describes heat exchanger module and engine performance during baseline testing. Condenser temperature profiles, brake power, and efficiency are presented and discussed.

The design and fabrication of a Stirling engine heat exchanger module with an integral heat pipe

NASA Technical Reports Server (NTRS)

Schreiber, Jeffrey G.

1988-01-01

The conceptual design of a free-piston Stirling Space Engine (SSE) intended for space power applications has been generated. The engine was designed to produce 25 kW of electric power with heat supplied by a nuclear reactor. A novel heat exchanger module was designed to reduce the number of critical joints in the heat exchanger assembly while also incorporating a heat pipe as the link between the engine and the heat source. Two inexpensive verification tests are proposed. The SSE heat exchanger module is described and the operating conditions for the module are outlined. The design process of the heat exchanger modules, including the sodium heat pipe, is briefly described. Similarities between the proposed SSE heat exchanger modules and the LeRC test modules for two test engines are presented. The benefits and weaknesses of using a sodium heat pipe to transport heat to a Stirling engine are discussed. Similarly, the problems encountered when using a true heat pipe, as opposed to a more simple reflux boiler, are described. The instruments incorporated into the modules and the test program are also outlined.

Forecasting of the development of professional medical equipment engineering based on neuro-fuzzy algorithms

NASA Astrophysics Data System (ADS)

Vaganova, E. V.; Syryamkin, M. V.

2015-11-01

The purpose of the research is the development of evolutionary algorithms for assessments of promising scientific directions. The main attention of the present study is paid to the evaluation of the foresight possibilities for identification of technological peaks and emerging technologies in professional medical equipment engineering in Russia and worldwide on the basis of intellectual property items and neural network modeling. An automated information system consisting of modules implementing various classification methods for accuracy of the forecast improvement and the algorithm of construction of neuro-fuzzy decision tree have been developed. According to the study result, modern trends in this field will focus on personalized smart devices, telemedicine, bio monitoring, «e-Health» and «m-Health» technologies.

AUTOMOTIVE DIESEL MAINTENANCE L. UNIT XII, PART I--MAINTAINING THE FUEL SYSTEM (PART II), CUMMINS DIESEL ENGINE, PART II--UNIT INSTALLATION (ENGINE).

ERIC Educational Resources Information Center

Human Engineering Inst., Cleveland, OH.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF THE OPERATION AND MAINTENANCE OF THE DIESEL ENGINE FUEL SYSTEM AND THE PROCEDURES FOR DIESEL ENGINE INSTALLATION. TOPICS ARE FUEL FLOW CHARACTERISTICS, PTG FUEL PUMP, PREPARATION FOR INSTALLATION, AND INSTALLING ENGINE. THE MODULE CONSISTS OF A SELF-INSTRUCTIONAL BRANCH…

Bayesian module identification from multiple noisy networks.

PubMed

Zamani Dadaneh, Siamak; Qian, Xiaoning

2016-12-01

Module identification has been studied extensively in order to gain deeper understanding of complex systems, such as social networks as well as biological networks. Modules are often defined as groups of vertices in these networks that are topologically cohesive with similar interaction patterns with the rest of the vertices. Most of the existing module identification algorithms assume that the given networks are faithfully measured without errors. However, in many real-world applications, for example, when analyzing protein-protein interaction networks from high-throughput profiling techniques, there is significant noise with both false positive and missing links between vertices. In this paper, we propose a new model for more robust module identification by taking advantage of multiple observed networks with significant noise so that signals in multiple networks can be strengthened and help improve the solution quality by combining information from various sources. We adopt a hierarchical Bayesian model to integrate multiple noisy snapshots that capture the underlying modular structure of the networks under study. By introducing a latent root assignment matrix and its relations to instantaneous module assignments in all the observed networks to capture the underlying modular structure and combine information across multiple networks, an efficient variational Bayes algorithm can be derived to accurately and robustly identify the underlying modules from multiple noisy networks. Experiments on synthetic and protein-protein interaction data sets show that our proposed model enhances both the accuracy and resolution in detecting cohesive modules, and it is less vulnerable to noise in the observed data. In addition, it shows higher power in predicting missing edges compared to individual-network methods.

Shrink Wrapping Cells in a Defined Extracellular Matrix to Modulate the Chemo-Mechanical Microenvironment.

PubMed

Palchesko, Rachelle N; Szymanski, John M; Sahu, Amrita; Feinberg, Adam W

2014-09-01

Cell-matrix interactions are important for the physical integration of cells into tissues and the function of insoluble, mechanosensitive signaling networks. Studying these interactions in vitro can be difficult because the extracellular matrix (ECM) proteins that adsorb to in vitro cell culture surfaces do not fully recapitulate the ECM-dense basement membranes to which cells such as cardiomyocytes and endothelial cells adhere to in vivo . Towards addressing this limitation, we have developed a surface-initiated assembly process to engineer ECM proteins into nanostructured, microscale sheets that can be shrink wrapped around single cells and small cell ensembles to provide a functional and instructive matrix niche. Unlike current cell encapsulation technology using alginate, fibrin or other hydrogels, our engineered ECM is similar in density and thickness to native basal lamina and can be tailored in structure and composition using the proteins fibronectin, laminin, fibrinogen, and/or collagen type IV. A range of cells including C2C12 myoblasts, bovine corneal endothelial cells and cardiomyocytes survive the shrink wrapping process with high viability. Further, we demonstrate that, compared to non-encapsulated controls, the engineered ECM modulates cytoskeletal structure, stability of cell-matrix adhesions and cell behavior in 2D and 3D microenvironments.

Shrink Wrapping Cells in a Defined Extracellular Matrix to Modulate the Chemo-Mechanical Microenvironment

PubMed Central

Palchesko, Rachelle N.; Szymanski, John M.; Sahu, Amrita; Feinberg, Adam W.

2014-01-01

Cell-matrix interactions are important for the physical integration of cells into tissues and the function of insoluble, mechanosensitive signaling networks. Studying these interactions in vitro can be difficult because the extracellular matrix (ECM) proteins that adsorb to in vitro cell culture surfaces do not fully recapitulate the ECM-dense basement membranes to which cells such as cardiomyocytes and endothelial cells adhere to in vivo. Towards addressing this limitation, we have developed a surface-initiated assembly process to engineer ECM proteins into nanostructured, microscale sheets that can be shrink wrapped around single cells and small cell ensembles to provide a functional and instructive matrix niche. Unlike current cell encapsulation technology using alginate, fibrin or other hydrogels, our engineered ECM is similar in density and thickness to native basal lamina and can be tailored in structure and composition using the proteins fibronectin, laminin, fibrinogen, and/or collagen type IV. A range of cells including C2C12 myoblasts, bovine corneal endothelial cells and cardiomyocytes survive the shrink wrapping process with high viability. Further, we demonstrate that, compared to non-encapsulated controls, the engineered ECM modulates cytoskeletal structure, stability of cell-matrix adhesions and cell behavior in 2D and 3D microenvironments. PMID:25530816

Western Pyrenees geodetic deformation study using the Guipuzcoa GNSS network

NASA Astrophysics Data System (ADS)

Martín, Adriana; Sevilla, Miguel; Zurutuza, Joaquín

2018-07-01

The Basque Country in the north of Spain is located inside the Basque-Cantabrian basin of the western Pyrenees which remarkable seismic-tectonic implications justify the need of geodetic control in the area. In order to perform a crustal deformation study we have analysed all daily observations from the GNSS permanent network of Guipuzcoa and external IGS stations, from January 2007 to November 2011. We have carried out the data processing applying double differences methodology in the automatic processing module BPE (Bernese Processing Engine) from Bernese GNSS software version 5.0. Solution was aligned to geodetic reference framework ITRF2008, by using the IGS08 solution and updated satellite and terrestrial antennas calibration. This five years network study results: Coordinate time series, velocities and baseline lengths variations show internal stability among inner stations and from them with respect to outer IGS stations, concluding that no deformations have been observed.

A reusability and efficiency oriented software design method for mobile land inspection

NASA Astrophysics Data System (ADS)

Cai, Wenwen; He, Jun; Wang, Qing

2008-10-01

Aiming at the requirement from the real-time land inspection domain, a land inspection handset system was presented in this paper. In order to increase the reusability of the system, a design pattern based framework was presented. Encapsulation for command like actions by applying COMMAND pattern was proposed for the problem of complex UI interactions. Integrating several GPS-log parsing engines into a general parsing framework was archived by introducing STRATEGY pattern. A network transmission module based network middleware was constructed. For mitigating the high coupling of complex network communication programs, FACTORY pattern was applied to facilitate the decoupling. Moreover, in order to efficiently manipulate huge GIS datasets, a VISITOR pattern and Quad-tree based multi-scale representation method was presented. It had been proved practically that these design patterns reduced the coupling between the subsystems, and improved the expansibility.

UltraNet Target Parameters. Chapter 1

NASA Technical Reports Server (NTRS)

Kislitzin, Katherine T.; Blaylock, Bruce T. (Technical Monitor)

1992-01-01

The UltraNet is a high speed network capable of rates up to one gigabit per second. It is a hub based network with four optical fiber links connecting each hub. Each link can carry up to 256 megabits of data, and the hub backplane is capable of one gigabit aggregate throughput. Host connections to the hub may be fiber, coax, or channel based. Bus based machines have adapter boards that connect to transceivers in the hub, while channel based machines use a personality module in the hub. One way that the UltraNet achieves its high transfer rates is by off-loading the protocol processing from the hosts to special purpose protocol engines in the UltraNet hubs. In addition, every hub has a PC connected to it by StarLAN for network management purposes. Although there is hub resident and PC resident UltraNet software, this document treats only the host resident UltraNet software.

Crossing boundaries: the design of an interdisciplinary training program to improve care for the frail elderly.

PubMed

Kolomitro, Klodiana; Stockley, Denise; Egan, Rylan; MacDonald, Michelle L

2015-01-01

The Technology Evaluation in the Elderly Network (TVN) was funded in July 2012 under the Canadian Networks of Centres of Excellence program. This article highlights the development and preliminary evaluation of the TVN Interdisciplinary Training Program. This program is based on an experiential learning approach that crosses a multitude of disciplines including health sciences, law, social sciences, and ethical aspects of working with the frail elderly. Opportunities within the program include mentorship, interdisciplinary online collaborative projects, external placements, academic products, pre-grant submission, trainee-driven requirements, Network meetings, online modules/webinars, and most importantly active involvement with patients, families, and their support systems. The authors have 120 trainees from approximately 23 different disciplines including law, ethics, public policy, social work, and engineering engaged in the program. Based on our evaluation this program has been perceived as highly valuable by the participants and the community.

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT XX, CUMMINS DIESEL ENGINE, MAINTENANCE SUMMARY.

ERIC Educational Resources Information Center

Minnesota State Dept. of Education, St. Paul. Div. of Vocational and Technical Education.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO PROVIDE A SUMMARY OF THE REASONS AND PROCEDURES FOR DIESEL ENGINE MAINTENANCE. TOPICS ARE WHAT ENGINE BREAK-IN MEANS, ENGINE BREAK-IN, TORQUING BEARINGS (TEMPLATE METHOD), AND THE NEED FOR MAINTENANCE. THE MODULE CONSISTS OF A SELF-INSTRUCTIONAL BRANCH PROGRAMED TRAINING FILM "CUMMINS DIESEL ENGINE…

Disentangling the co-structure of multilayer interaction networks: degree distribution and module composition in two-layer bipartite networks.

PubMed

Astegiano, Julia; Altermatt, Florian; Massol, François

2017-11-13

Species establish different interactions (e.g. antagonistic, mutualistic) with multiple species, forming multilayer ecological networks. Disentangling network co-structure in multilayer networks is crucial to predict how biodiversity loss may affect the persistence of multispecies assemblages. Existing methods to analyse multilayer networks often fail to consider network co-structure. We present a new method to evaluate the modular co-structure of multilayer networks through the assessment of species degree co-distribution and network module composition. We focus on modular structure because of its high prevalence among ecological networks. We apply our method to two Lepidoptera-plant networks, one describing caterpillar-plant herbivory interactions and one representing adult Lepidoptera nectaring on flowers, thereby possibly pollinating them. More than 50% of the species established either herbivory or visitation interactions, but not both. These species were over-represented among plants and lepidopterans, and were present in most modules in both networks. Similarity in module composition between networks was high but not different from random expectations. Our method clearly delineates the importance of interpreting multilayer module composition similarity in the light of the constraints imposed by network structure to predict the potential indirect effects of species loss through interconnected modular networks.

Simultaneously firing two cylinders of an even firing camless engine

DOEpatents

Brennan, Daniel G

2014-03-11

A valve control system includes an engine speed control module that determines an engine speed and a desired engine stop position. A piston position module determines a desired stopping position of a first piston based on the desired engine stop position. A valve control module receives the desired stopping position, commands a set of valves to close at the desired stopping position if the engine speed is less than a predetermined shutdown threshold, and commands the set of valves to reduce the engine speed if the engine speed is greater than the predetermined shutdown threshold.

Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena.

PubMed

De Domenico, Manlio

2017-04-21

Collective phenomena emerge from the interaction of natural or artificial units with a complex organization. The interplay between structural patterns and dynamics might induce functional clusters that, in general, are different from topological ones. In biological systems, like the human brain, the overall functionality is often favored by the interplay between connectivity and synchronization dynamics, with functional clusters that do not coincide with anatomical modules in most cases. In social, sociotechnical, and engineering systems, the quest for consensus favors the emergence of clusters. Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their interconnectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us. Here, we propose an approach based on random walk dynamics to define the diffusion distance between any pair of units in a networked system. Such a metric allows us to exploit the underlying diffusion geometry to provide a unifying framework for the intimate relationship between metastable synchronization, consensus, and random search dynamics in complex networks, pinpointing the functional mesoscale organization of synthetic and biological systems.

Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena

NASA Astrophysics Data System (ADS)

De Domenico, Manlio

2017-04-01

Collective phenomena emerge from the interaction of natural or artificial units with a complex organization. The interplay between structural patterns and dynamics might induce functional clusters that, in general, are different from topological ones. In biological systems, like the human brain, the overall functionality is often favored by the interplay between connectivity and synchronization dynamics, with functional clusters that do not coincide with anatomical modules in most cases. In social, sociotechnical, and engineering systems, the quest for consensus favors the emergence of clusters. Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their interconnectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us. Here, we propose an approach based on random walk dynamics to define the diffusion distance between any pair of units in a networked system. Such a metric allows us to exploit the underlying diffusion geometry to provide a unifying framework for the intimate relationship between metastable synchronization, consensus, and random search dynamics in complex networks, pinpointing the functional mesoscale organization of synthetic and biological systems.

Identification of common coexpression modules based on quantitative network comparison.

PubMed

Jo, Yousang; Kim, Sanghyeon; Lee, Doheon

2018-06-13

Finding common molecular interactions from different samples is essential work to understanding diseases and other biological processes. Coexpression networks and their modules directly reflect sample-specific interactions among genes. Therefore, identification of common coexpression network or modules may reveal the molecular mechanism of complex disease or the relationship between biological processes. However, there has been no quantitative network comparison method for coexpression networks and we examined previous methods for other networks that cannot be applied to coexpression network. Therefore, we aimed to propose quantitative comparison methods for coexpression networks and to find common biological mechanisms between Huntington's disease and brain aging by the new method. We proposed two similarity measures for quantitative comparison of coexpression networks. Then, we performed experiments using known coexpression networks. We showed the validity of two measures and evaluated threshold values for similar coexpression network pairs from experiments. Using these similarity measures and thresholds, we quantitatively measured the similarity between disease-specific and aging-related coexpression modules and found similar Huntington's disease-aging coexpression module pairs. We identified similar Huntington's disease-aging coexpression module pairs and found that these modules are related to brain development, cell death, and immune response. It suggests that up-regulated cell signalling related cell death and immune/ inflammation response may be the common molecular mechanisms in the pathophysiology of HD and normal brain aging in the frontal cortex.

CUFID-query: accurate network querying through random walk based network flow estimation.

PubMed

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2017-12-28

Functional modules in biological networks consist of numerous biomolecules and their complicated interactions. Recent studies have shown that biomolecules in a functional module tend to have similar interaction patterns and that such modules are often conserved across biological networks of different species. As a result, such conserved functional modules can be identified through comparative analysis of biological networks. In this work, we propose a novel network querying algorithm based on the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) framework combined with an efficient seed-and-extension approach. The proposed algorithm, CUFID-query, can accurately detect conserved functional modules as small subnetworks in the target network that are expected to perform similar functions to the given query functional module. The CUFID framework was recently developed for probabilistic pairwise global comparison of biological networks, and it has been applied to pairwise global network alignment, where the framework was shown to yield accurate network alignment results. In the proposed CUFID-query algorithm, we adopt the CUFID framework and extend it for local network alignment, specifically to solve network querying problems. First, in the seed selection phase, the proposed method utilizes the CUFID framework to compare the query and the target networks and to predict the probabilistic node-to-node correspondence between the networks. Next, the algorithm selects and greedily extends the seed in the target network by iteratively adding nodes that have frequent interactions with other nodes in the seed network, in a way that the conductance of the extended network is maximally reduced. Finally, CUFID-query removes irrelevant nodes from the querying results based on the personalized PageRank vector for the induced network that includes the fully extended network and its neighboring nodes. Through extensive performance evaluation based on biological networks with known functional modules, we show that CUFID-query outperforms the existing state-of-the-art algorithms in terms of prediction accuracy and biological significance of the predictions.

Tracking the Reorganization of Module Structure in Time-Varying Weighted Brain Functional Connectivity Networks.

PubMed

Schmidt, Christoph; Piper, Diana; Pester, Britta; Mierau, Andreas; Witte, Herbert

2018-05-01

Identification of module structure in brain functional networks is a promising way to obtain novel insights into neural information processing, as modules correspond to delineated brain regions in which interactions are strongly increased. Tracking of network modules in time-varying brain functional networks is not yet commonly considered in neuroscience despite its potential for gaining an understanding of the time evolution of functional interaction patterns and associated changing degrees of functional segregation and integration. We introduce a general computational framework for extracting consensus partitions from defined time windows in sequences of weighted directed edge-complete networks and show how the temporal reorganization of the module structure can be tracked and visualized. Part of the framework is a new approach for computing edge weight thresholds for individual networks based on multiobjective optimization of module structure quality criteria as well as an approach for matching modules across time steps. By testing our framework using synthetic network sequences and applying it to brain functional networks computed from electroencephalographic recordings of healthy subjects that were exposed to a major balance perturbation, we demonstrate the framework's potential for gaining meaningful insights into dynamic brain function in the form of evolving network modules. The precise chronology of the neural processing inferred with our framework and its interpretation helps to improve the currently incomplete understanding of the cortical contribution for the compensation of such balance perturbations.

Android platform based smartphones for a logistical remote association repair framework.

PubMed

Lien, Shao-Fan; Wang, Chun-Chieh; Su, Juhng-Perng; Chen, Hong-Ming; Wu, Chein-Hsing

2014-06-25

The maintenance of large-scale systems is an important issue for logistics support planning. In this paper, we developed a Logistical Remote Association Repair Framework (LRARF) to aid repairmen in keeping the system available. LRARF includes four subsystems: smart mobile phones, a Database Management System (DBMS), a Maintenance Support Center (MSC) and wireless networks. The repairman uses smart mobile phones to capture QR-codes and the images of faulty circuit boards. The captured QR-codes and images are transmitted to the DBMS so the invalid modules can be recognized via the proposed algorithm. In this paper, the Linear Projective Transform (LPT) is employed for fast QR-code calibration. Moreover, the ANFIS-based data mining system is used for module identification and searching automatically for the maintenance manual corresponding to the invalid modules. The inputs of the ANFIS-based data mining system are the QR-codes and image features; the output is the module ID. DBMS also transmits the maintenance manual back to the maintenance staff. If modules are not recognizable, the repairmen and center engineers can obtain the relevant information about the invalid modules through live video. The experimental results validate the applicability of the Android-based platform in the recognition of invalid modules. In addition, the live video can also be recorded synchronously on the MSC for later use.

Develop railway engineering modules in UTK civil engineering undergraduate and graduate courses.

DOT National Transportation Integrated Search

2015-05-31

The importance of railway transport has long been recognized. However, no railway : engineering courses have been provided in the UTK civil engineering curricula. The : objective of this education project is to develop some railway engineering module...

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT XXX, I--CATERPILLAR DIESEL ENGINE MAINTENANCE SUMMARY, II--REIEWING FACTS ABOUT ALTERNATORS.

ERIC Educational Resources Information Center

Minnesota State Dept. of Education, St. Paul. Div. of Vocational and Technical Education.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO PROVIDE A SUMMARY OF DIESEL ENGINE MAINTENANCE FACTORS AND A REVIEW OF DIESEL ENGINE ALTERNATOR OPERATION. THE SEVEN SECTIONS COVER DIESEL ENGINE TROUBLESHOOTING AND THE OPERATION, TESTING, AND ADJUSTING OF ALTERNATORS. THE MODULE CONSISTS OF A SELF-INSTRUCTIONAL BRANCH PROGRAMED TRAINING FILM…

Expanding Metabolic Engineering Algorithms Using Feasible Space and Shadow Price Constraint Modules

PubMed Central

Tervo, Christopher J.; Reed, Jennifer L.

2014-01-01

While numerous computational methods have been developed that use genome-scale models to propose mutants for the purpose of metabolic engineering, they generally compare mutants based on a single criteria (e.g., production rate at a mutant’s maximum growth rate). As such, these approaches remain limited in their ability to include multiple complex engineering constraints. To address this shortcoming, we have developed feasible space and shadow price constraint (FaceCon and ShadowCon) modules that can be added to existing mixed integer linear adaptive evolution metabolic engineering algorithms, such as OptKnock and OptORF. These modules allow strain designs to be identified amongst a set of multiple metabolic engineering algorithm solutions that are capable of high chemical production while also satisfying additional design criteria. We describe the various module implementations and their potential applications to the field of metabolic engineering. We then incorporated these modules into the OptORF metabolic engineering algorithm. Using an Escherichia coli genome-scale model (iJO1366), we generated different strain designs for the anaerobic production of ethanol from glucose, thus demonstrating the tractability and potential utility of these modules in metabolic engineering algorithms. PMID:25478320

PRiME: integrating professional responsibility into the engineering curriculum.

PubMed

Moore, Christy; Hart, Hillary; Randall, D'Arcy; Nichols, Steven P

2006-04-01

Engineering educators have long discussed the need to teach professional responsibility and the social context of engineering without adding to overcrowded curricula. One difficulty we face is the lack of appropriate teaching materials that can fit into existing courses. The PRiME (Professional Responsibility Modules for Engineering) Project (http://www.engr.utexas.edu/ethics/primeModules.cfm) described in this paper was initiated at the University of Texas, Austin to provide web-based modules that could be integrated into any undergraduate engineering class. Using HPL (How People Learn) theory, PRiME developed and piloted four modules during the academic year 2004-2005. This article introduces the modules and the pilot, outlines the assessment process, analyzes the results, and describes how the modules are being revised in light of the initial assessment. In its first year of development and testing, PRiME made significant progress towards meeting its objectives. The PRiME Project can strengthen engineering education by providing faculty with an effective system for engaging students in learning about professional responsibility.

Electronic Communication in Engineering Work.

ERIC Educational Resources Information Center

Bishop, Ann P.

1992-01-01

Discusses the role of electronic networks in engineering work; reviews selected literature on engineering work, knowledge, and communication; describes current uses of electronic networks; and presents results from a study of the use of networks by engineers in the aerospace industry, including their perceptions of networks. (67 references) (LRW)

Engineering of a synthetic quadrastable gene network to approach Waddington landscape and cell fate determination

PubMed Central

Wu, Fuqing; Su, Ri-Qi; Lai, Ying-Cheng; Wang, Xiao

2017-01-01

The process of cell fate determination has been depicted intuitively as cells travelling and resting on a rugged landscape, which has been probed by various theoretical studies. However, few studies have experimentally demonstrated how underlying gene regulatory networks shape the landscape and hence orchestrate cellular decision-making in the presence of both signal and noise. Here we tested different topologies and verified a synthetic gene circuit with mutual inhibition and auto-activations to be quadrastable, which enables direct study of quadruple cell fate determination on an engineered landscape. We show that cells indeed gravitate towards local minima and signal inductions dictate cell fates through modulating the shape of the multistable landscape. Experiments, guided by model predictions, reveal that sequential inductions generate distinct cell fates by changing landscape in sequence and hence navigating cells to different final states. This work provides a synthetic biology framework to approach cell fate determination and suggests a landscape-based explanation of fixed induction sequences for targeted differentiation. DOI: http://dx.doi.org/10.7554/eLife.23702.001 PMID:28397688

Understanding network concepts in modules

PubMed Central

2007-01-01

Background Network concepts are increasingly used in biology and genetics. For example, the clustering coefficient has been used to understand network architecture; the connectivity (also known as degree) has been used to screen for cancer targets; and the topological overlap matrix has been used to define modules and to annotate genes. Dozens of potentially useful network concepts are known from graph theory. Results Here we study network concepts in special types of networks, which we refer to as approximately factorizable networks. In these networks, the pairwise connection strength (adjacency) between 2 network nodes can be factored into node specific contributions, named node 'conformity'. The node conformity turns out to be highly related to the connectivity. To provide a formalism for relating network concepts to each other, we define three types of network concepts: fundamental-, conformity-based-, and approximate conformity-based concepts. Fundamental concepts include the standard definitions of connectivity, density, centralization, heterogeneity, clustering coefficient, and topological overlap. The approximate conformity-based analogs of fundamental network concepts have several theoretical advantages. First, they allow one to derive simple relationships between seemingly disparate networks concepts. For example, we derive simple relationships between the clustering coefficient, the heterogeneity, the density, the centralization, and the topological overlap. The second advantage of approximate conformity-based network concepts is that they allow one to show that fundamental network concepts can be approximated by simple functions of the connectivity in module networks. Conclusion Using protein-protein interaction, gene co-expression, and simulated data, we show that a) many networks comprised of module nodes are approximately factorizable and b) in these types of networks, simple relationships exist between seemingly disparate network concepts. Our results are implemented in freely available R software code, which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/ModuleConformity/ModuleNetworks PMID:17547772

SoftLab: A Soft-Computing Software for Experimental Research with Commercialization Aspects

NASA Technical Reports Server (NTRS)

Akbarzadeh-T, M.-R.; Shaikh, T. S.; Ren, J.; Hubbell, Rob; Kumbla, K. K.; Jamshidi, M

1998-01-01

SoftLab is a software environment for research and development in intelligent modeling/control using soft-computing paradigms such as fuzzy logic, neural networks, genetic algorithms, and genetic programs. SoftLab addresses the inadequacies of the existing soft-computing software by supporting comprehensive multidisciplinary functionalities from management tools to engineering systems. Furthermore, the built-in features help the user process/analyze information more efficiently by a friendly yet powerful interface, and will allow the user to specify user-specific processing modules, hence adding to the standard configuration of the software environment.

Attenuation correction for brain PET imaging using deep neural network based on dixon and ZTE MR images.

PubMed

Gong, Kuang; Yang, Jaewon; Kim, Kyungsang; El Fakhri, Georges; Seo, Youngho; Li, Quanzheng

2018-05-23

Positron Emission Tomography (PET) is a functional imaging modality widely used in neuroscience studies. To obtain meaningful quantitative results from PET images, attenuation correction is necessary during image reconstruction. For PET/MR hybrid systems, PET attenuation is challenging as Magnetic Resonance (MR) images do not reflect attenuation coefficients directly. To address this issue, we present deep neural network methods to derive the continuous attenuation coefficients for brain PET imaging from MR images. With only Dixon MR images as the network input, the existing U-net structure was adopted and analysis using forty patient data sets shows it is superior than other Dixon based methods. When both Dixon and zero echo time (ZTE) images are available, we have proposed a modified U-net structure, named GroupU-net, to efficiently make use of both Dixon and ZTE information through group convolution modules when the network goes deeper. Quantitative analysis based on fourteen real patient data sets demonstrates that both network approaches can perform better than the standard methods, and the proposed network structure can further reduce the PET quantification error compared to the U-net structure. © 2018 Institute of Physics and Engineering in Medicine.

DiME: A Scalable Disease Module Identification Algorithm with Application to Glioma Progression

PubMed Central

Liu, Yunpeng; Tennant, Daniel A.; Zhu, Zexuan; Heath, John K.; Yao, Xin; He, Shan

2014-01-01

Disease module is a group of molecular components that interact intensively in the disease specific biological network. Since the connectivity and activity of disease modules may shed light on the molecular mechanisms of pathogenesis and disease progression, their identification becomes one of the most important challenges in network medicine, an emerging paradigm to study complex human disease. This paper proposes a novel algorithm, DiME (Disease Module Extraction), to identify putative disease modules from biological networks. We have developed novel heuristics to optimise Community Extraction, a module criterion originally proposed for social network analysis, to extract topological core modules from biological networks as putative disease modules. In addition, we have incorporated a statistical significance measure, B-score, to evaluate the quality of extracted modules. As an application to complex diseases, we have employed DiME to investigate the molecular mechanisms that underpin the progression of glioma, the most common type of brain tumour. We have built low (grade II) - and high (GBM) - grade glioma co-expression networks from three independent datasets and then applied DiME to extract potential disease modules from both networks for comparison. Examination of the interconnectivity of the identified modules have revealed changes in topology and module activity (expression) between low- and high- grade tumours, which are characteristic of the major shifts in the constitution and physiology of tumour cells during glioma progression. Our results suggest that transcription factors E2F4, AR and ETS1 are potential key regulators in tumour progression. Our DiME compiled software, R/C++ source code, sample data and a tutorial are available at http://www.cs.bham.ac.uk/~szh/DiME. PMID:24523864

Synthesizing a novel genetic sequential logic circuit: a push-on push-off switch

PubMed Central

Lou, Chunbo; Liu, Xili; Ni, Ming; Huang, Yiqi; Huang, Qiushi; Huang, Longwen; Jiang, Lingli; Lu, Dan; Wang, Mingcong; Liu, Chang; Chen, Daizhuo; Chen, Chongyi; Chen, Xiaoyue; Yang, Le; Ma, Haisu; Chen, Jianguo; Ouyang, Qi

2010-01-01

Design and synthesis of basic functional circuits are the fundamental tasks of synthetic biologists. Before it is possible to engineer higher-order genetic networks that can perform complex functions, a toolkit of basic devices must be developed. Among those devices, sequential logic circuits are expected to be the foundation of the genetic information-processing systems. In this study, we report the design and construction of a genetic sequential logic circuit in Escherichia coli. It can generate different outputs in response to the same input signal on the basis of its internal state, and ‘memorize' the output. The circuit is composed of two parts: (1) a bistable switch memory module and (2) a double-repressed promoter NOR gate module. The two modules were individually rationally designed, and they were coupled together by fine-tuning the interconnecting parts through directed evolution. After fine-tuning, the circuit could be repeatedly, alternatively triggered by the same input signal; it functions as a push-on push-off switch. PMID:20212522

Synthesizing a novel genetic sequential logic circuit: a push-on push-off switch.

PubMed

Lou, Chunbo; Liu, Xili; Ni, Ming; Huang, Yiqi; Huang, Qiushi; Huang, Longwen; Jiang, Lingli; Lu, Dan; Wang, Mingcong; Liu, Chang; Chen, Daizhuo; Chen, Chongyi; Chen, Xiaoyue; Yang, Le; Ma, Haisu; Chen, Jianguo; Ouyang, Qi

2010-01-01

Design and synthesis of basic functional circuits are the fundamental tasks of synthetic biologists. Before it is possible to engineer higher-order genetic networks that can perform complex functions, a toolkit of basic devices must be developed. Among those devices, sequential logic circuits are expected to be the foundation of the genetic information-processing systems. In this study, we report the design and construction of a genetic sequential logic circuit in Escherichia coli. It can generate different outputs in response to the same input signal on the basis of its internal state, and 'memorize' the output. The circuit is composed of two parts: (1) a bistable switch memory module and (2) a double-repressed promoter NOR gate module. The two modules were individually rationally designed, and they were coupled together by fine-tuning the interconnecting parts through directed evolution. After fine-tuning, the circuit could be repeatedly, alternatively triggered by the same input signal; it functions as a push-on push-off switch.

System and method for controlling hydraulic pressure in electro-hydraulic valve actuation systems

DOEpatents

Brennan, Daniel G; Marriott, Craig D; Cowgill, Joel; Wiles, Matthew A; Patton, Kenneth James

2014-09-23

A control system for an engine includes a first lift control module and a second lift control module. The first lift control module increases lift of M valves of the engine to a predetermined valve lift during a period before disabling or re-enabling N valves of the engine. The second lift control module decreases the lift of the M valves to a desired valve lift during a period after enabling or re-enabling the N valves of the engine, wherein N and M are integers greater than or equal to one.

Metabolic engineering of Bacillus subtilis fueled by systems biology: Recent advances and future directions.

PubMed

Liu, Yanfeng; Li, Jianghua; Du, Guocheng; Chen, Jian; Liu, Long

By combining advanced omics technology and computational modeling, systems biologists have identified and inferred thousands of regulatory events and system-wide interactions of the bacterium Bacillus subtilis, which is commonly used both in the laboratory and in industry. This dissection of the multiple layers of regulatory networks and their interactions has provided invaluable information for unraveling regulatory mechanisms and guiding metabolic engineering. In this review, we discuss recent advances in the systems biology and metabolic engineering of B. subtilis and highlight current gaps in our understanding of global metabolism and global pathway engineering in this organism. We also propose future perspectives in the systems biology of B. subtilis and suggest ways that this approach can be used to guide metabolic engineering. Specifically, although hundreds of regulatory events have been identified or inferred via systems biology approaches, systematic investigation of the functionality of these events in vivo has lagged, thereby preventing the elucidation of regulatory mechanisms and further rational pathway engineering. In metabolic engineering, ignoring the engineering of multilayer regulation hinders metabolic flux redistribution. Post-translational engineering, allosteric engineering, and dynamic pathway analyses and control will also contribute to the modulation and control of the metabolism of engineered B. subtilis, ultimately producing the desired cellular traits. We hope this review will aid metabolic engineers in making full use of available systems biology datasets and approaches for the design and perfection of microbial cell factories through global metabolism optimization. Copyright © 2016 Elsevier Inc. All rights reserved.

Motivation but not valence modulates neuroticism-dependent cingulate cortex and insula activity.

PubMed

Deng, Yaling; Li, Shijia; Zhou, Renlai; Walter, Martin

2018-04-01

Neuroticism has been found to specifically modulate amygdala activations during differential processing of valence and motivation while other brain networks yet are unexplored for associated effects. The main purpose of this study was to investigate whether neural mechanisms processing valence or motivation are prone to neuroticism in the salience network (SN), a network that is anchored in the anterior cingulate cortex (ACC) and the anterior insula. This study used functional magnetic resonance imaging (fMRI) and an approach/avoid emotional pictures task to investigate brain activations modulated by pictures' valence or motivational status between high and low neurotic individuals. We found that neuroticism-dependent SN and the parahippocampal-fusiform area activations were modulated by motivation but not valence. Valence in contrast interacted with neuroticism in the lateral orbitofrontal cortex. We suggested that neuroticism modulated valence and motivation processing, however, under the influence of the two distinct networks. Neuroticism modulated the motivation through the SN while it modulated the valence through the orbitofrontal networks. © 2018 Wiley Periodicals, Inc.

Dense module enumeration in biological networks

NASA Astrophysics Data System (ADS)

Tsuda, Koji; Georgii, Elisabeth

2009-12-01

Analysis of large networks is a central topic in various research fields including biology, sociology, and web mining. Detection of dense modules (a.k.a. clusters) is an important step to analyze the networks. Though numerous methods have been proposed to this aim, they often lack mathematical rigorousness. Namely, there is no guarantee that all dense modules are detected. Here, we present a novel reverse-search-based method for enumerating all dense modules. Furthermore, constraints from additional data sources such as gene expression profiles or customer profiles can be integrated, so that we can systematically detect dense modules with interesting profiles. We report successful applications in human protein interaction network analyses.

Unstart coupling mechanism analysis of multiple-modules hypersonic inlet.

PubMed

Hu, Jichao; Chang, Juntao; Wang, Lei; Cao, Shibin; Bao, Wen

2013-01-01

The combination of multiplemodules in parallel manner is an important way to achieve the much higher thrust of scramjet engine. For the multiple-modules scramjet engine, when inlet unstarted oscillatory flow appears in a single-module engine due to high backpressure, how to interact with each module by massflow spillage, and whether inlet unstart occurs in other modules are important issues. The unstarted flowfield and coupling characteristic for a three-module hypersonic inlet caused by center module II and side module III were, conducted respectively. The results indicate that the other two hypersonic inlets are forced into unstarted flow when unstarted phenomenon appears on a single-module hypersonic inlet due to high backpressure, and the reversed flow in the isolator dominates the formation, expansion, shrinkage, and disappearance of the vortexes, and thus, it is the major factor of unstart coupling of multiple-modules hypersonic inlet. The coupling effect among multiple modules makes hypersonic inlet be more likely unstarted.

A Novel Modulation Classification Approach Using Gabor Filter Network

PubMed Central

Ghauri, Sajjad Ahmed; Qureshi, Ijaz Mansoor; Cheema, Tanveer Ahmed; Malik, Aqdas Naveed

2014-01-01

A Gabor filter network based approach is used for feature extraction and classification of digital modulated signals by adaptively tuning the parameters of Gabor filter network. Modulation classification of digitally modulated signals is done under the influence of additive white Gaussian noise (AWGN). The modulations considered for the classification purpose are PSK 2 to 64, FSK 2 to 64, and QAM 4 to 64. The Gabor filter network uses the network structure of two layers; the first layer which is input layer constitutes the adaptive feature extraction part and the second layer constitutes the signal classification part. The Gabor atom parameters are tuned using Delta rule and updating of weights of Gabor filter using least mean square (LMS) algorithm. The simulation results show that proposed novel modulation classification algorithm has high classification accuracy at low signal to noise ratio (SNR) on AWGN channel. PMID:25126603

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT XXIX, REVIEWING THE CONSTRUCTION OF ENGINE COMPONENTS.

ERIC Educational Resources Information Center

Human Engineering Inst., Cleveland, OH.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO PROVIDE A REVIEW OF THE CONSTRUCTION AND OPERATION OF DIESEL ENGINE COMPONENTS. TOPICS ARE STATIONARY PARTS, ENGINE MOVING PARTS, PISTON RINGS, AND CONNECTING RODS AND PISTON PINS. THE MODULE CONSISTS OF AN INSTRUCTOR'S GUIDE, TRANSPARENCIES, A LIST OF SUGGESTED SUPPLEMENTARY MATERIALS, AND TRAINEE…

A system's view of metro and regional optical networks

NASA Astrophysics Data System (ADS)

Lam, Cedric F.; Way, Winston I.

2009-01-01

Developments in fiber optic communications have been rejuvenated after the glut of the overcapacity at the turn of the century. The boom of video-centric network applications finally resulted in another wave of vast build-outs of broadband access networks such as FTTH, DOCSIS 3.0 and WI-FI systems, which in turn also drove up the bandwidth demands in metro and regional WDM networks. These new developments have rekindled research interests on technologies not only to meet the surging demand, but also to upgrade legacy network infrastructures in an evolutionary manner without disrupting existing services and incurring significant capital penalties. Standard bodies such as IEEE, ITU and OIF have formed task forces to ratify 100Gb/s interface standards. Thanks to the seemingly unlimited bandwidth in single-mode fibers, advances in optical networks has traditionally been fueled by more capable physical components such as more powerful laser, cleaner and wider bandwidth optical amplifier, faster modulator and photo-detectors, etc. In the meanwhile, the mainstream modulation technique for fiber optic communication systems has remained the most rudimentary form of on-off keying (OOK) and direct power detection for a very long period of time because spectral efficiency had never been a concern. This scenario, however, is no longer valid as demand for bandwidth is pushing the limit of current of current WDM technologies. In terms of spectral use, all the 100-GHz ITU grids in the C-band have been populated with 10Gb/s wavelengths in most of the WDM transport networks, and we are exhausting the power and bandwidth offered on existing fiber plant EDFAs. Beyond 10Gb/s, increasing the transmission to 40Gb/s by brute force OOK approach incurs significant penalties due to chromatic and polarization mode dispersion. With conventional modulation schemes, transmission impairments at 40Gb/s speed and above already become such difficult challenges that the efforts to manage these problem have severely hindered the rate of return on the investment from an economical viewpoint, let alone 100Gb/s transmission. In addition, to enable fast turn-up of new services and reduce network operation costs, carriers are also deploying reconfigurable optical add/drop multiplexers (ROADMs) and transparent optical networks. ROADMs impose more impairments to transmitted signals and are important considerations in designing backbone transmission links. Recently, advanced modulation schemes have been investigated in both the academia and industry as ways to improve the spectral efficiency and alleviate transmission impairments. Signal processing techniques familiar to traditional telecommunication engineers are also playing more and more important roles in optical communications because of the fast advance in mixed signal processing and growing abundance of computational power. In this invited talk, we review the current challenges faced in upgrading existing 10Gb/s metro and regional WDM networks and the potential solutions to enable 40 and 100Gb/s wavelength services.

Construct mine environment monitoring system based on wireless mesh network

NASA Astrophysics Data System (ADS)

Chen, Xin; Ge, Gengyu; Liu, Yinmei; Cheng, Aimin; Wu, Jun; Fu, Jun

2018-04-01

The system uses wireless Mesh network as a network transmission medium, and strive to establish an effective and reliable underground environment monitoring system. The system combines wireless network technology and embedded technology to monitor the internal data collected in the mine and send it to the processing center for analysis and environmental assessment. The system can be divided into two parts: the main control network module and the data acquisition terminal, and the SPI bus technology is used for mutual communication between them. Multi-channel acquisition and control interface design Data acquisition and control terminal in the analog signal acquisition module, digital signal acquisition module, and digital signal output module. The main control network module running Linux operating system, in which the transplant SPI driver, USB card driver and AODV routing protocol. As a result, the internal data collection and reporting of the mine are realized.

Integrated Module and Gene-Specific Regulatory Inference Implicates Upstream Signaling Networks

PubMed Central

Roy, Sushmita; Lagree, Stephen; Hou, Zhonggang; Thomson, James A.; Stewart, Ron; Gasch, Audrey P.

2013-01-01

Regulatory networks that control gene expression are important in diverse biological contexts including stress response and development. Each gene's regulatory program is determined by module-level regulation (e.g. co-regulation via the same signaling system), as well as gene-specific determinants that can fine-tune expression. We present a novel approach, Modular regulatory network learning with per gene information (MERLIN), that infers regulatory programs for individual genes while probabilistically constraining these programs to reveal module-level organization of regulatory networks. Using edge-, regulator- and module-based comparisons of simulated networks of known ground truth, we find MERLIN reconstructs regulatory programs of individual genes as well or better than existing approaches of network reconstruction, while additionally identifying modular organization of the regulatory networks. We use MERLIN to dissect global transcriptional behavior in two biological contexts: yeast stress response and human embryonic stem cell differentiation. Regulatory modules inferred by MERLIN capture co-regulatory relationships between signaling proteins and downstream transcription factors thereby revealing the upstream signaling systems controlling transcriptional responses. The inferred networks are enriched for regulators with genetic or physical interactions, supporting the inference, and identify modules of functionally related genes bound by the same transcriptional regulators. Our method combines the strengths of per-gene and per-module methods to reveal new insights into transcriptional regulation in stress and development. PMID:24146602

Parametric Model of an Aerospike Rocket Engine

NASA Technical Reports Server (NTRS)

Korte, J. J.

2000-01-01

A suite of computer codes was assembled to simulate the performance of an aerospike engine and to generate the engine input for the Program to Optimize Simulated Trajectories. First an engine simulator module was developed that predicts the aerospike engine performance for a given mixture ratio, power level, thrust vectoring level, and altitude. This module was then used to rapidly generate the aerospike engine performance tables for axial thrust, normal thrust, pitching moment, and specific thrust. Parametric engine geometry was defined for use with the engine simulator module. The parametric model was also integrated into the iSIGHTI multidisciplinary framework so that alternate designs could be determined. The computer codes were used to support in-house conceptual studies of reusable launch vehicle designs.

Parametric Model of an Aerospike Rocket Engine

NASA Technical Reports Server (NTRS)

Korte, J. J.

2000-01-01

A suite of computer codes was assembled to simulate the performance of an aerospike engine and to generate the engine input for the Program to Optimize Simulated Trajectories. First an engine simulator module was developed that predicts the aerospike engine performance for a given mixture ratio, power level, thrust vectoring level, and altitude. This module was then used to rapidly generate the aerospike engine performance tables for axial thrust, normal thrust, pitching moment, and specific thrust. Parametric engine geometry was defined for use with the engine simulator module. The parametric model was also integrated into the iSIGHT multidisciplinary framework so that alternate designs could be determined. The computer codes were used to support in-house conceptual studies of reusable launch vehicle designs.

Environmental versatility promotes modularity in genome-scale metabolic networks.

PubMed

Samal, Areejit; Wagner, Andreas; Martin, Olivier C

2011-08-24

The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks. Using recently developed techniques to randomly sample large numbers of viable metabolic networks from a vast space of metabolic networks, we use flux balance analysis to study in silico metabolic networks that differ in their versatility. We find that highly versatile networks are also highly modular. They contain more modules and more reactions that are organized into modules. Most or all reactions in a module are associated with the same biochemical pathways. Modules that arise in highly versatile networks generally involve reactions that process nutrients or closely related chemicals. We also observe that the metabolism of E. coli is significantly more modular than even our most versatile networks. Our work shows that modularity in metabolic networks can be a by-product of functional constraints, e.g., the need to sustain life in multiple environments. This organizational principle is insensitive to the environments we consider and to the number of reactions in a metabolic network. Because we observe this principle not just in one or few biological networks, but in large random samples of networks, we propose that it may be a generic principle of metabolic network organization.

Can enzyme engineering benefit from the modulation of protein motions? Lessons learned from NMR relaxation dispersion experiments.

PubMed

Doucet, Nicolas

2011-04-01

Despite impressive progress in protein engineering and design, our ability to create new and efficient enzyme activities remains a laborious and time-consuming endeavor. In the past few years, intricate combinations of rational mutagenesis, directed evolution and computational methods have paved the way to exciting engineering examples and are now offering a new perspective on the structural requirements of enzyme activity. However, these structure-function analyses are usually guided by the time-averaged static models offered by enzyme crystal structures, which often fail to describe the functionally relevant 'invisible states' adopted by proteins in space and time. To alleviate such limitations, NMR relaxation dispersion experiments coupled to mutagenesis studies have recently been applied to the study of enzyme catalysis, effectively complementing 'structure-function' analyses with 'flexibility-function' investigations. In addition to offering quantitative, site-specific information to help characterize residue motion, these NMR methods are now being applied to enzyme engineering purposes, providing a powerful tool to help characterize the effects of controlling long-range networks of flexible residues affecting enzyme function. Recent advancements in this emerging field are presented here, with particular attention to mutagenesis reports highlighting the relevance of NMR relaxation dispersion tools in enzyme engineering.

Detecting Solenoid Valve Deterioration in In-Use Electronic Diesel Fuel Injection Control Systems

PubMed Central

Tsai, Hsun-Heng; Tseng, Chyuan-Yow

2010-01-01

The diesel engine is the main power source for most agricultural vehicles. The control of diesel engine emissions is an important global issue. Fuel injection control systems directly affect fuel efficiency and emissions of diesel engines. Deterioration faults, such as rack deformation, solenoid valve failure, and rack-travel sensor malfunction, are possibly in the fuel injection module of electronic diesel control (EDC) systems. Among these faults, solenoid valve failure is most likely to occur for in-use diesel engines. According to the previous studies, this failure is a result of the wear of the plunger and sleeve, based on a long period of usage, lubricant degradation, or engine overheating. Due to the difficulty in identifying solenoid valve deterioration, this study focuses on developing a sensor identification algorithm that can clearly classify the usability of the solenoid valve, without disassembling the fuel pump of an EDC system for in-use agricultural vehicles. A diagnostic algorithm is proposed, including a feedback controller, a parameter identifier, a linear variable differential transformer (LVDT) sensor, and a neural network classifier. Experimental results show that the proposed algorithm can accurately identify the usability of solenoid valves. PMID:22163597

Detecting solenoid valve deterioration in in-use electronic diesel fuel injection control systems.

PubMed

Tsai, Hsun-Heng; Tseng, Chyuan-Yow

2010-01-01

The diesel engine is the main power source for most agricultural vehicles. The control of diesel engine emissions is an important global issue. Fuel injection control systems directly affect fuel efficiency and emissions of diesel engines. Deterioration faults, such as rack deformation, solenoid valve failure, and rack-travel sensor malfunction, are possibly in the fuel injection module of electronic diesel control (EDC) systems. Among these faults, solenoid valve failure is most likely to occur for in-use diesel engines. According to the previous studies, this failure is a result of the wear of the plunger and sleeve, based on a long period of usage, lubricant degradation, or engine overheating. Due to the difficulty in identifying solenoid valve deterioration, this study focuses on developing a sensor identification algorithm that can clearly classify the usability of the solenoid valve, without disassembling the fuel pump of an EDC system for in-use agricultural vehicles. A diagnostic algorithm is proposed, including a feedback controller, a parameter identifier, a linear variable differential transformer (LVDT) sensor, and a neural network classifier. Experimental results show that the proposed algorithm can accurately identify the usability of solenoid valves.

Discovering Multimodal Behavior in Ms. Pac-Man through Evolution of Modular Neural Networks.

PubMed

Schrum, Jacob; Miikkulainen, Risto

2016-03-12

Ms. Pac-Man is a challenging video game in which multiple modes of behavior are required: Ms. Pac-Man must escape ghosts when they are threats and catch them when they are edible, in addition to eating all pills in each level. Past approaches to learning behavior in Ms. Pac-Man have treated the game as a single task to be learned using monolithic policy representations. In contrast, this paper uses a framework called Modular Multi-objective NEAT (MM-NEAT) to evolve modular neural networks. Each module defines a separate behavior. The modules are used at different times according to a policy that can be human-designed (i.e. Multitask) or discovered automatically by evolution. The appropriate number of modules can be fixed or discovered using a genetic operator called Module Mutation. Several versions of Module Mutation are evaluated in this paper. Both fixed modular networks and Module Mutation networks outperform monolithic networks and Multitask networks. Interestingly, the best networks dedicate modules to critical behaviors (such as escaping when surrounded after luring ghosts near a power pill) that do not follow the customary division of the game into chasing edible and escaping threat ghosts. The results demonstrate that MM-NEAT can discover interesting and effective behavior for agents in challenging games.

Discovering Multimodal Behavior in Ms. Pac-Man through Evolution of Modular Neural Networks

PubMed Central

Schrum, Jacob; Miikkulainen, Risto

2015-01-01

Ms. Pac-Man is a challenging video game in which multiple modes of behavior are required: Ms. Pac-Man must escape ghosts when they are threats and catch them when they are edible, in addition to eating all pills in each level. Past approaches to learning behavior in Ms. Pac-Man have treated the game as a single task to be learned using monolithic policy representations. In contrast, this paper uses a framework called Modular Multi-objective NEAT (MM-NEAT) to evolve modular neural networks. Each module defines a separate behavior. The modules are used at different times according to a policy that can be human-designed (i.e. Multitask) or discovered automatically by evolution. The appropriate number of modules can be fixed or discovered using a genetic operator called Module Mutation. Several versions of Module Mutation are evaluated in this paper. Both fixed modular networks and Module Mutation networks outperform monolithic networks and Multitask networks. Interestingly, the best networks dedicate modules to critical behaviors (such as escaping when surrounded after luring ghosts near a power pill) that do not follow the customary division of the game into chasing edible and escaping threat ghosts. The results demonstrate that MM-NEAT can discover interesting and effective behavior for agents in challenging games. PMID:27030803

A multi-port 10GbE PCIe NIC featuring UDP offload and GPUDirect capabilities.

NASA Astrophysics Data System (ADS)

Ammendola, Roberto; Biagioni, Andrea; Frezza, Ottorino; Lamanna, Gianluca; Lo Cicero, Francesca; Lonardo, Alessandro; Martinelli, Michele; Stanislao Paolucci, Pier; Pastorelli, Elena; Pontisso, Luca; Rossetti, Davide; Simula, Francesco; Sozzi, Marco; Tosoratto, Laura; Vicini, Piero

2015-12-01

NaNet-10 is a four-ports 10GbE PCIe Network Interface Card designed for low-latency real-time operations with GPU systems. To this purpose the design includes an UDP offload module, for fast and clock-cycle deterministic handling of the transport layer protocol, plus a GPUDirect P2P/RDMA engine for low-latency communication with NVIDIA Tesla GPU devices. A dedicated module (Multi-Stream) can optionally process input UDP streams before data is delivered through PCIe DMA to their destination devices, re-organizing data from different streams guaranteeing computational optimization. NaNet-10 is going to be integrated in the NA62 CERN experiment in order to assess the suitability of GPGPU systems as real-time triggers; results and lessons learned while performing this activity will be reported herein.

Apparatus for fixing latency

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hall, David R; Bartholomew, David B; Moon, Justin

2009-09-08

An apparatus for fixing computational latency within a deterministic region on a network comprises a network interface modem, a high priority module and at least one deterministic peripheral device. The network interface modem is in communication with the network. The high priority module is in communication with the network interface modem. The at least one deterministic peripheral device is connected to the high priority module. The high priority module comprises a packet assembler/disassembler, and hardware for performing at least one operation. Also disclosed is an apparatus for executing at least one instruction on a downhole device within a deterministic region,more » the apparatus comprising a control device, a downhole network, and a downhole device. The control device is near the surface of a downhole tool string. The downhole network is integrated into the tool string. The downhole device is in communication with the downhole network.« less

Android Platform Based Smartphones for a Logistical Remote Association Repair Framework

PubMed Central

Lien, Shao-Fan; Wang, Chun-Chieh; Su, Juhng-Perng; Chen, Hong-Ming; Wu, Chein-Hsing

2014-01-01

The maintenance of large-scale systems is an important issue for logistics support planning. In this paper, we developed a Logistical Remote Association Repair Framework (LRARF) to aid repairmen in keeping the system available. LRARF includes four subsystems: smart mobile phones, a Database Management System (DBMS), a Maintenance Support Center (MSC) and wireless networks. The repairman uses smart mobile phones to capture QR-codes and the images of faulty circuit boards. The captured QR-codes and images are transmitted to the DBMS so the invalid modules can be recognized via the proposed algorithm. In this paper, the Linear Projective Transform (LPT) is employed for fast QR-code calibration. Moreover, the ANFIS-based data mining system is used for module identification and searching automatically for the maintenance manual corresponding to the invalid modules. The inputs of the ANFIS-based data mining system are the QR-codes and image features; the output is the module ID. DBMS also transmits the maintenance manual back to the maintenance staff. If modules are not recognizable, the repairmen and center engineers can obtain the relevant information about the invalid modules through live video. The experimental results validate the applicability of the Android-based platform in the recognition of invalid modules. In addition, the live video can also be recorded synchronously on the MSC for later use. PMID:24967603

Fuel premixing module for gas turbine engine combustor

NASA Technical Reports Server (NTRS)

Chin, Jushan (Inventor); Rizk, Nader K. (Inventor); Razdan, Mohan K. (Inventor); Marshall, Andre W. (Inventor)

2005-01-01

A fuel-air premixing module is designed to reduce emissions from a gas turbine engine. In one form, the premixing module includes a central pilot premixer module with a main premixer module positioned thereround. Each of the portions of the fuel-air premixing module include an axial inflow swirler with a plurality of fixed swirler vanes. Fuel is injected into the main premixer module between the swirler vanes of the axial inflow swirler and at an acute angle relative to the centerline of the premixing module.

Stationary Engineers Apprenticeship. Related Training Modules. 20.1-23.1 Miscellaneous.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This learning module, one in a series of 20 related training modules for apprentice stationary engineers, deals with miscellaneous job skills needed by persons working in power plants. Addressed in the individual instructional packages included in the module are the following topics: transformers, circuit protection, construction of foundations…

Biomedical and Biochemical Engineering for K-12 Students

ERIC Educational Resources Information Center

Madihally, Sundararajan V.; Maase, Eric L.

2006-01-01

REACH (Reaching Engineering and Architectural Career Heights) is a weeklong summer academy outreach program for high school students interested in engineering, architecture, or technology. Through module-­based instruction, students are introduced to various engineering fields. This report describes one of the modules focused on introducing…

Reservoir characterization using core, well log, and seismic data and intelligent software

NASA Astrophysics Data System (ADS)

Soto Becerra, Rodolfo

We have developed intelligent software, Oilfield Intelligence (OI), as an engineering tool to improve the characterization of oil and gas reservoirs. OI integrates neural networks and multivariate statistical analysis. It is composed of five main subsystems: data input, preprocessing, architecture design, graphics design, and inference engine modules. More than 1,200 lines of programming code as M-files using the language MATLAB been written. The degree of success of many oil and gas drilling, completion, and production activities depends upon the accuracy of the models used in a reservoir description. Neural networks have been applied for identification of nonlinear systems in almost all scientific fields of humankind. Solving reservoir characterization problems is no exception. Neural networks have a number of attractive features that can help to extract and recognize underlying patterns, structures, and relationships among data. However, before developing a neural network model, we must solve the problem of dimensionality such as determining dominant and irrelevant variables. We can apply principal components and factor analysis to reduce the dimensionality and help the neural networks formulate more realistic models. We validated OI by obtaining confident models in three different oil field problems: (1) A neural network in-situ stress model using lithology and gamma ray logs for the Travis Peak formation of east Texas, (2) A neural network permeability model using porosity and gamma ray and a neural network pseudo-gamma ray log model using 3D seismic attributes for the reservoir VLE 196 Lamar field located in Block V of south-central Lake Maracaibo (Venezuela), and (3) Neural network primary ultimate oil recovery (PRUR), initial waterflooding ultimate oil recovery (IWUR), and infill drilling ultimate oil recovery (IDUR) models using reservoir parameters for San Andres and Clearfork carbonate formations in west Texas. In all cases, we compared the results from the neural network models with the results from regression statistical and non-parametric approach models. The results show that it is possible to obtain the highest cross-correlation coefficient between predicted and actual target variables, and the lowest average absolute errors using the integrated techniques of multivariate statistical analysis and neural networks in our intelligent software.

Silicon photonic Mach Zehnder modulators for next-generation short-reach optical communication networks

NASA Astrophysics Data System (ADS)

Lacava, C.; Liu, Z.; Thomson, D.; Ke, Li; Fedeli, J. M.; Richardson, D. J.; Reed, G. T.; Petropoulos, P.

2016-02-01

Communication traffic grows relentlessly in today's networks, and with ever more machines connected to the network, this trend is set to continue for the foreseeable future. It is widely accepted that increasingly faster communications are required at the point of the end users, and consequently optical transmission plays a progressively greater role even in short- and medium-reach networks. Silicon photonic technologies are becoming increasingly attractive for such networks, due to their potential for low cost, energetically efficient, high-speed optical components. A representative example is the silicon-based optical modulator, which has been actively studied. Researchers have demonstrated silicon modulators in different types of structures, such as ring resonators or slow light based devices. These approaches have shown remarkably good performance in terms of modulation efficiency, however their operation could be severely affected by temperature drifts or fabrication errors. Mach-Zehnder modulators (MZM), on the other hand, show good performance and resilience to different environmental conditions. In this paper we present a CMOS-compatible compact silicon MZM. We study the application of the modulator to short-reach interconnects by realizing data modulation using some relevant advanced modulation formats, such as 4-level Pulse Amplitude Modulation (PAM-4) and Discrete Multi-Tone (DMT) modulation and compare the performance of the different systems in transmission.

Preparing for a Career as a Network Engineer

ERIC Educational Resources Information Center

Morris, Gerard; Fustos, Janos; Haga, Wayne

2012-01-01

A network engineer is an Information Technology (IT) professional who designs, implements, maintains, and troubleshoots computer networks. While the United States is still experiencing relatively high unemployment, demand for network engineers remains strong. To determine what skills employers are looking for, data was collected and analyzed from…

System and method for controlling engine knock using electro-hydraulic valve actuation

DOEpatents

Brennan, Daniel G

2013-12-10

A control system for an engine includes a knock control module and a valve control module. The knock control module adjusts a period that one or more of an intake valve and an exhaust valve of a cylinder are open based on engine knock corresponding to the cylinder. The valve control module, based on the adjusted period, controls the one or more of the intake valve and the exhaust valve using one or more hydraulic actuators.

77 FR 65767 - Petition for Exemption From the Federal Motor Vehicle Theft Prevention Standard; Chrysler

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-30

... (RFHM), Ignition Node Module (IGNM), Engine Control Module, Body Controller Module, Sentry Key... disable engine operation and immobilize the vehicle after two seconds of running. This process is also...

Effective Engineering Outreach through an Undergraduate Mentoring Team and Module Database

ERIC Educational Resources Information Center

Young, Colin; Butterfield, Anthony E.

2014-01-01

The rising need for engineers has led to increased interest in community outreach in engineering departments nationwide. We present a sustainable outreach model involving trained undergraduate mentors to build ties with K-12 teachers and students. An associated online module database of chemical engineering demonstrations, available to educators…

Fault-tolerant battery system employing intra-battery network architecture

DOEpatents

Hagen, Ronald A.; Chen, Kenneth W.; Comte, Christophe; Knudson, Orlin B.; Rouillard, Jean

2000-01-01

A distributed energy storing system employing a communications network is disclosed. A distributed battery system includes a number of energy storing modules, each of which includes a processor and communications interface. In a network mode of operation, a battery computer communicates with each of the module processors over an intra-battery network and cooperates with individual module processors to coordinate module monitoring and control operations. The battery computer monitors a number of battery and module conditions, including the potential and current state of the battery and individual modules, and the conditions of the battery's thermal management system. An over-discharge protection system, equalization adjustment system, and communications system are also controlled by the battery computer. The battery computer logs and reports various status data on battery level conditions which may be reported to a separate system platform computer. A module transitions to a stand-alone mode of operation if the module detects an absence of communication connectivity with the battery computer. A module which operates in a stand-alone mode performs various monitoring and control functions locally within the module to ensure safe and continued operation.

ARC-2001-ACD01-0018

NASA Image and Video Library

2001-02-16

New Center Network Deployment ribbon Cutting: from left to right: Maryland Edwards, Code JT upgrade project deputy task manager; Ed Murphy, foundry networks systems engineer; Bohdan Cmaylo, Code JT upgrade project task manager, Scott Santiago, Division Chief, Code JT; Greg Miller, Raytheon Network engineer and Frank Daras, Raytheon network engineering manager.

Enhancing biological relevance of a weighted gene co-expression network for functional module identification.

PubMed

Prom-On, Santitham; Chanthaphan, Atthawut; Chan, Jonathan Hoyin; Meechai, Asawin

2011-02-01

Relationships among gene expression levels may be associated with the mechanisms of the disease. While identifying a direct association such as a difference in expression levels between case and control groups links genes to disease mechanisms, uncovering an indirect association in the form of a network structure may help reveal the underlying functional module associated with the disease under scrutiny. This paper presents a method to improve the biological relevance in functional module identification from the gene expression microarray data by enhancing the structure of a weighted gene co-expression network using minimum spanning tree. The enhanced network, which is called a backbone network, contains only the essential structural information to represent the gene co-expression network. The entire backbone network is decoupled into a number of coherent sub-networks, and then the functional modules are reconstructed from these sub-networks to ensure minimum redundancy. The method was tested with a simulated gene expression dataset and case-control expression datasets of autism spectrum disorder and colorectal cancer studies. The results indicate that the proposed method can accurately identify clusters in the simulated dataset, and the functional modules of the backbone network are more biologically relevant than those obtained from the original approach.

Microarray and network-based identification of functional modules and pathways of active tuberculosis.

PubMed

Bian, Zhong-Rui; Yin, Juan; Sun, Wen; Lin, Dian-Jie

2017-04-01

Diagnose of active tuberculosis (TB) is challenging and treatment response is also difficult to efficiently monitor. The aim of this study was to use an integrated analysis of microarray and network-based method to the samples from publically available datasets to obtain a diagnostic module set and pathways in active TB. Towards this goal, background protein-protein interactions (PPI) network was generated based on global PPI information and gene expression data, following by identification of differential expression network (DEN) from the background PPI network. Then, ego genes were extracted according to the degree features in DEN. Next, module collection was conducted by ego gene expansion based on EgoNet algorithm. After that, differential expression of modules between active TB and controls was evaluated using random permutation test. Finally, biological significance of differential modules was detected by pathways enrichment analysis based on Reactome database, and Fisher's exact test was implemented to extract differential pathways for active TB. Totally, 47 ego genes and 47 candidate modules were identified from the DEN. By setting the cutoff-criteria of gene size >5 and classification accuracy ≥0.9, 7 ego modules (Module 4, Module 7, Module 9, Module 19, Module 25, Module 38 and Module 43) were extracted, and all of them had the statistical significance between active TB and controls. Then, Fisher's exact test was conducted to capture differential pathways for active TB. Interestingly, genes in Module 4, Module 25, Module 38, and Module 43 were enriched in the same pathway, formation of a pool of free 40S subunits. Significant pathway for Module 7 and Module 9 was eukaryotic translation termination, and for Module 19 was nonsense mediated decay enhanced by the exon junction complex (EJC). Accordingly, differential modules and pathways might be potential biomarkers for treating active TB, and provide valuable clues for better understanding of molecular mechanism of active TB. Copyright © 2017 Elsevier Ltd. All rights reserved.

atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

PubMed

Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

2012-07-20

Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model.

PubMed

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2016-10-06

Comparative analysis of protein-protein interaction (PPI) networks provides an effective means of detecting conserved functional network modules across different species. Such modules typically consist of orthologous proteins with conserved interactions, which can be exploited to computationally predict the modules through network comparison. In this work, we propose a novel probabilistic framework for comparing PPI networks and effectively predicting the correspondence between proteins, represented as network nodes, that belong to conserved functional modules across the given PPI networks. The basic idea is to estimate the steady-state network flow between nodes that belong to different PPI networks based on a Markov random walk model. The random walker is designed to make random moves to adjacent nodes within a PPI network as well as cross-network moves between potential orthologous nodes with high sequence similarity. Based on this Markov random walk model, we estimate the steady-state network flow - or the long-term relative frequency of the transitions that the random walker makes - between nodes in different PPI networks, which can be used as a probabilistic score measuring their potential correspondence. Subsequently, the estimated scores can be used for detecting orthologous proteins in conserved functional modules through network alignment. Through evaluations based on multiple real PPI networks, we demonstrate that the proposed scheme leads to improved alignment results that are biologically more meaningful at reduced computational cost, outperforming the current state-of-the-art algorithms. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/CUFID .

Stationary Engineers Apprenticeship. Related Training Modules. 13.1-13.7 Pumps.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This learning module, one in a series of 20 related training modules for apprentice stationary engineers, deals with pumps. Addressed in the individual instructional packages included in the module are the following topics: types, classifications, and applications of pumps; pump construction; procedures for calculating pump heat and pump flow;…

Stationary Engineers Apprenticeship. Related Training Modules. 3.1-3.4 Drawing.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of four learning modules on drawing is one of 20 such packets developed for apprenticeship training for stationary engineers. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study guide (a…

Stationary Engineers Apprenticeship. Related Training Modules. 10.1-10.5 Machine Components.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of five learning modules on machine components is one of 20 such packets developed for apprenticeship training for stationary engineers. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, statement…

Stationary Engineers Apprenticeship. Related Training Modules. 15.1-15.5 Turbines.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This learning module, one in a series of 20 related training modules for apprentice stationary engineers, deals with turbines. addressed in the individual instructional packages included in the module are the following topics: types and components of steam turbines, steam turbine auxiliaries, operation and maintenance of steam turbines, and gas…

Stationary Engineers Apprenticeship. Related Training Modules. 8.1-8.13 Hydraulics.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of 13 learning modules on hydraulics is one of 20 such packets developed for apprenticeship training for stationary engineers. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study guide (a…

Stationary Engineers Apprenticeship. Related Training Modules. 9.1-9.6 Refrigeration.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of six learning modules on refrigeration is one of 20 such packets developed for apprenticeship training for stationary engineers. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, statement of…

Stationary Engineers Apprenticeship. Related Training Modules. 12.1-12.9. Boilers.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This learning module, one in a series of 20 related training modules for apprentice stationary engineers, deals with boilers. Addressed in the individual instructional packages included in the module are the following topics: firetube and watertube boilers; boiler construction; procedures for operating and cleaning boilers; and boiler fittings,…

Stationary Engineers Apprenticeship. Related Training Modules. 16.1-16.5 Combustion.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This learning module, one in a series of 20 related training modules for apprentice stationary engineers, deals with combustion. Addressed in the individual instructional packages included in the module are the following topics: the combustion process, types of fuel, air and flue gases, heat transfer during combustion, and wood combustion. Each…

Stationary Engineers Apprenticeship. Related Training Modules. 5.1-5.17 Electricity/Electronics.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of 17 learning modules on electricity/electronics is one of 20 such packets developed for apprenticeship training for stationary engineers. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators,…

Stationary Engineers Apprenticeship. Related Training Modules. 4.1-4.5 Tools.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of five learning modules on tools is one of 20 such packets developed for apprenticeship training for stationary engineers. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: a lesson goal, performance indicators, study guide…

Container-code recognition system based on computer vision and deep neural networks

NASA Astrophysics Data System (ADS)

Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

2018-04-01

Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

Short-term performance deterioration in JT9D-7A(SP) engine 695743

NASA Technical Reports Server (NTRS)

Bouchard, R. J.; Beyerly, W. R.; Sallee, G. P.

1978-01-01

The level of performance deterioration that occurred during early service was studied and also the contribution of each engine module to the overall level of engine performance deterioration. To assist in the distribution of the performance losses to the module level, testing with expanded experimental instrumentation was accomplished to permit direct measurement of module performance. An analytical teardown of the engine was accomplished to permit assignment of module performance losses to individual mechanical damage mechanisms including blade and seal wear, roughness, and thermal distortion of turbine parts. The results of the testing show that the engine deteriorated 1.5 percent in thrust specific fuel consumption from its performance when new. Initial testing, which included water washing, showed that 0.2 percent in performance deterioration was due to surface contamination (dirt) and 0.1 percent was due to drift of the engine vane control system, leaving 1.2 percent in basic TSFC deterioration. This 1.2 percent TSFC loss was distributed among the engine modules with 0.6 percent caused by clearance changes, 0.4 percent loss due to thermal distortion, and 0.2 percent loss due to increased roughness of the fan and low-pressure compressor airfoils.

76 FR 68260 - Petition for Exemption From the Federal Motor Vehicle Theft Prevention Standard; Chrysler

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-03

...), Ignition Node Module (IGNM), Engine Control Module (ECM), Body Controller Module (BCM), Sentry Key..., Chrysler stated that the RFHM sends an invalid key message to the ECM, which will disable engine operation...

Hierarchical surface code for network quantum computing with modules of arbitrary size

NASA Astrophysics Data System (ADS)

Li, Ying; Benjamin, Simon C.

2016-10-01

The network paradigm for quantum computing involves interconnecting many modules to form a scalable machine. Typically it is assumed that the links between modules are prone to noise while operations within modules have a significantly higher fidelity. To optimize fault tolerance in such architectures we introduce a hierarchical generalization of the surface code: a small "patch" of the code exists within each module and constitutes a single effective qubit of the logic-level surface code. Errors primarily occur in a two-dimensional subspace, i.e., patch perimeters extruded over time, and the resulting noise threshold for intermodule links can exceed ˜10 % even in the absence of purification. Increasing the number of qubits within each module decreases the number of qubits necessary for encoding a logical qubit. But this advantage is relatively modest, and broadly speaking, a "fine-grained" network of small modules containing only about eight qubits is competitive in total qubit count versus a "course" network with modules containing many hundreds of qubits.

Network Analysis Implicates Alpha-Synuclein (Snca) in the Regulation of Ovariectomy-Induced Bone Loss

PubMed Central

Calabrese, Gina; Mesner, Larry D.; Foley, Patricia L.; Rosen, Clifford J.; Farber, Charles R.

2016-01-01

The postmenopausal period in women is associated with decreased circulating estrogen levels, which accelerate bone loss and increase the risk of fracture. Here, we gained novel insight into the molecular mechanisms mediating bone loss in ovariectomized (OVX) mice, a model of human menopause, using co-expression network analysis. Specifically, we generated a co-expression network consisting of 53 gene modules using expression profiles from intact and OVX mice from a panel of inbred strains. The expression of four modules was altered by OVX, including module 23 whose expression was decreased by OVX across all strains. Module 23 was enriched for genes involved in the response to oxidative stress, a process known to be involved in OVX-induced bone loss. Additionally, module 23 homologs were co-expressed in human bone marrow. Alpha synuclein (Snca) was one of the most highly connected “hub” genes in module 23. We characterized mice deficient in Snca and observed a 40% reduction in OVX-induced bone loss. Furthermore, protection was associated with the altered expression of specific network modules, including module 23. In summary, the results of this study suggest that Snca regulates bone network homeostasis and ovariectomy-induced bone loss. PMID:27378017

Unstart Coupling Mechanism Analysis of Multiple-Modules Hypersonic Inlet

PubMed Central

Wang, Lei; Cao, Shibin

2013-01-01

The combination of multiplemodules in parallel manner is an important way to achieve the much higher thrust of scramjet engine. For the multiple-modules scramjet engine, when inlet unstarted oscillatory flow appears in a single-module engine due to high backpressure, how to interact with each module by massflow spillage, and whether inlet unstart occurs in other modules are important issues. The unstarted flowfield and coupling characteristic for a three-module hypersonic inlet caused by center module II and side module III were, conducted respectively. The results indicate that the other two hypersonic inlets are forced into unstarted flow when unstarted phenomenon appears on a single-module hypersonic inlet due to high backpressure, and the reversed flow in the isolator dominates the formation, expansion, shrinkage, and disappearance of the vortexes, and thus, it is the major factor of unstart coupling of multiple-modules hypersonic inlet. The coupling effect among multiple modules makes hypersonic inlet be more likely unstarted. PMID:24348146

Applied Graph-Mining Algorithms to Study Biomolecular Interaction Networks

PubMed Central

2014-01-01

Protein-protein interaction (PPI) networks carry vital information on the organization of molecular interactions in cellular systems. The identification of functionally relevant modules in PPI networks is one of the most important applications of biological network analysis. Computational analysis is becoming an indispensable tool to understand large-scale biomolecular interaction networks. Several types of computational methods have been developed and employed for the analysis of PPI networks. Of these computational methods, graph comparison and module detection are the two most commonly used strategies. This review summarizes current literature on graph kernel and graph alignment methods for graph comparison strategies, as well as module detection approaches including seed-and-extend, hierarchical clustering, optimization-based, probabilistic, and frequent subgraph methods. Herein, we provide a comprehensive review of the major algorithms employed under each theme, including our recently published frequent subgraph method, for detecting functional modules commonly shared across multiple cancer PPI networks. PMID:24800226

Modeling complexity in engineered infrastructure system: Water distribution network as an example

NASA Astrophysics Data System (ADS)

Zeng, Fang; Li, Xiang; Li, Ke

2017-02-01

The complex topology and adaptive behavior of infrastructure systems are driven by both self-organization of the demand and rigid engineering solutions. Therefore, engineering complex systems requires a method balancing holism and reductionism. To model the growth of water distribution networks, a complex network model was developed following the combination of local optimization rules and engineering considerations. The demand node generation is dynamic and follows the scaling law of urban growth. The proposed model can generate a water distribution network (WDN) similar to reported real-world WDNs on some structural properties. Comparison with different modeling approaches indicates that a realistic demand node distribution and co-evolvement of demand node and network are important for the simulation of real complex networks. The simulation results indicate that the efficiency of water distribution networks is exponentially affected by the urban growth pattern. On the contrary, the improvement of efficiency by engineering optimization is limited and relatively insignificant. The redundancy and robustness, on another aspect, can be significantly improved through engineering methods.

78 FR 52605 - Announcing the Twenty First Public Meeting of the Crash Injury Research and Engineering Network...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-23

... First Public Meeting of the Crash Injury Research and Engineering Network (CIREN) AGENCY: National... announces the Twenty First Public Meeting of members of the Crash Injury Research and Engineering Network... of centers, medical and engineering. Medical centers are based at Level I Trauma Centers that admit...

76 FR 46359 - Announcing the Nineteenth Public Meeting of the Crash Injury Research and Engineering Network...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-02

... Nineteenth Public Meeting of the Crash Injury Research and Engineering Network (CIREN) AGENCY: National... announces the Nineteenth Public Meeting of members of the Crash Injury Research and Engineering Network... of centers, medical and engineering. Medical centers are based at Level I Trauma Centers that admit...

77 FR 46154 - Announcing the Twentieth Public Meeting of the Crash Injury Research and Engineering Network (CIREN)

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-02

... Twentieth Public Meeting of the Crash Injury Research and Engineering Network (CIREN) AGENCY: National... announces the Twentieth Public Meeting of members of the Crash Injury Research and Engineering Network... of centers, medical and engineering. Medical centers are based at Level I Trauma Centers that admit...

GMPLS-based control plane for optical networks: early implementation experience

NASA Astrophysics Data System (ADS)

Liu, Hang; Pendarakis, Dimitrios; Komaee, Nooshin; Saha, Debanjan

2002-07-01

Generalized Multi-Protocol Label Switching (GMPLS) extends MPLS signaling and Internet routing protocols to provide a scalable, interoperable, distributed control plane, which is applicable to multiple network technologies such as optical cross connects (OXCs), photonic switches, IP routers, ATM switches, SONET and DWDM systems. It is intended to facilitate automatic service provisioning and dynamic neighbor and topology discovery across multi-vendor intelligent transport networks, as well as their clients. Efforts to standardize such a distributed common control plane have reached various stages in several bodies such as the IETF, ITU and OIF. This paper describes the design considerations and architecture of a GMPLS-based control plane that we have prototyped for core optical networks. Functional components of GMPLS signaling and routing are integrated in this architecture with an application layer controller module. Various requirements including bandwidth, network protection and survivability, traffic engineering, optimal utilization of network resources, and etc. are taken into consideration during path computation and provisioning. Initial experiments with our prototype demonstrate the feasibility and main benefits of GMPLS as a distributed control plane for core optical networks. In addition to such feasibility results, actual adoption and deployment of GMPLS as a common control plane for intelligent transport networks will depend on the successful completion of relevant standardization activities, extensive interoperability testing as well as the strengthening of appropriate business drivers.

Automatic decomposition of kinetic models of signaling networks minimizing the retroactivity among modules.

PubMed

Saez-Rodriguez, Julio; Gayer, Stefan; Ginkel, Martin; Gilles, Ernst Dieter

2008-08-15

The modularity of biochemical networks in general, and signaling networks in particular, has been extensively studied over the past few years. It has been proposed to be a useful property to analyze signaling networks: by decomposing the network into subsystems, more manageable units are obtained that are easier to analyze. While many powerful algorithms are available to identify modules in protein interaction networks, less attention has been paid to signaling networks de.ned as chemical systems. Such a decomposition would be very useful as most quantitative models are de.ned using the latter, more detailed formalism. Here, we introduce a novel method to decompose biochemical networks into modules so that the bidirectional (retroactive) couplings among the modules are minimized. Our approach adapts a method to detect community structures, and applies it to the so-called retroactivity matrix that characterizes the couplings of the network. Only the structure of the network, e.g. in SBML format, is required. Furthermore, the modularized models can be loaded into ProMoT, a modeling tool which supports modular modeling. This allows visualization of the models, exploiting their modularity and easy generation of models of one or several modules for further analysis. The method is applied to several relevant cases, including an entangled model of the EGF-induced MAPK cascade and a comprehensive model of EGF signaling, demonstrating its ability to uncover meaningful modules. Our approach can thus help to analyze large networks, especially when little a priori knowledge on the structure of the network is available. The decomposition algorithms implemented in MATLAB (Mathworks, Inc.) are freely available upon request. ProMoT is freely available at http://www.mpi-magdeburg.mpg.de/projects/promot. Supplementary data are available at Bioinformatics online.

Functional modules by relating protein interaction networks and gene expression.

PubMed

Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Functional modules by relating protein interaction networks and gene expression

PubMed Central

Tornow, Sabine; Mewes, H. W.

2003-01-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships. PMID:14576317

Meteorology Meets Engineering: An Interdisciplinary STEM Module for Middle and Early Secondary School Students

ERIC Educational Resources Information Center

Barrett, Bradford S.; Moran, Angela L.; Woods, John E.

2014-01-01

Background: Given the continued need to educate the public on both the meteorological and engineering hazards posed by the severe winds of a tornado, an interdisciplinary science, technology, engineering, and mathematics (STEM) module designed by the faculty from the Oceanography and Mechanical Engineering Departments at the United States Naval…

Ecological modules and roles of species in heathland plant-insect flower visitor networks.

PubMed

Dupont, Yoko L; Olesen, Jens M

2009-03-01

1. Co-existing plants and flower-visiting animals often form complex interaction networks. A long-standing question in ecology and evolutionary biology is how to detect nonrandom subsets (compartments, blocks, modules) of strongly interacting species within such networks. Here we use a network analytical approach to (i) detect modularity in pollination networks, (ii) investigate species composition of modules, and (iii) assess the stability of modules across sites. 2. Interactions between entomophilous plants and their flower-visitors were recorded throughout the flowering season at three heathland sites in Denmark, separated by >or= 10 km. Among sites, plant communities were similar, but composition of flower-visiting insect faunas differed. Visitation frequencies of visitor species were recorded as a measure of insect abundance. 3. Qualitative (presence-absence) interaction networks were tested for modularity. Modules were identified, and species classified into topological roles (peripherals, connectors, or hubs) using 'functional cartography by simulated annealing', a method recently developed by Guimerà & Amaral (2005a). 4. All networks were significantly modular. Each module consisted of 1-6 plant species and 18-54 insect species. Interactions aggregated around one or two hub plant species, which were largely identical at the three study sites. 5. Insect species were categorized in taxonomic groups, mostly at the level of orders. When weighted by visitation frequency, each module was dominated by one or few insect groups. This pattern was consistent across sites. 6. Our study adds support to the conclusion that certain plant species and flower-visitor groups are nonrandomly and repeatedly associated. Within a network, these strongly interacting subgroups of species may exert reciprocal selection pressures on each other. Thus, modules may be candidates for the long-sought key units of co-evolution.

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 39: The role of computer networks in aerospace engineering

NASA Technical Reports Server (NTRS)

Bishop, Ann P.; Pinelli, Thomas E.

1994-01-01

This paper presents selected results from an empirical investigation into the use of computer networks in aerospace engineering. Such networks allow aerospace engineers to communicate with people and access remote resources through electronic mail, file transfer, and remote log-in. The study drew its subjects from private sector, government and academic organizations in the U.S. aerospace industry. Data presented here were gathered in a mail survey, conducted in Spring 1993, that was distributed to aerospace engineers performing a wide variety of jobs. Results from the mail survey provide a snapshot of the current use of computer networks in the aerospace industry, suggest factors associated with the use of networks, and identify perceived impacts of networks on aerospace engineering work and communication.

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT XI, PART I--MAINTAINING THE FUEL SYSTEM (PART I), CUMMINS DIESEL ENGINES, PART II--UNIT REPLACEMENT (ENGINE).

ERIC Educational Resources Information Center

Human Engineering Inst., Cleveland, OH.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF DIFFERENCES BETWEEN TWO AND FOUR CYCLE ENGINES, THE OPERATION AND MAINTENANCE OF THE DIESEL ENGINE FUEL SYSTEM, AND THE PROCEDURES FOR DIESEL ENGINE REMOVAL. TOPICS ARE (1) REVIEW OF TWO CYCLE AND FOUR CYCLE CONCEPT, (2) SOME BASIC CHARACTERISTICS OF FOUR CYCLE ENGINES,…

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT XIX, I--ENGINE TUNE-UP--CUMMINS DIESEL ENGINE, II--FRONT END SUSPENSION AND AXLES.

ERIC Educational Resources Information Center

Minnesota State Dept. of Education, St. Paul. Div. of Vocational and Technical Education.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF DIESEL ENGINE TUNE-UP PROCEDURES AND THE DESIGN OF FRONT END SUSPENSION AND AXLES USED ON DIESEL ENGINE EQUIPMENT. TOPICS ARE (1) PRE-TUNE-UP CHECKS, (2) TIMING THE ENGINE, (3) INJECTOR PLUNGER AND VALVE ADJUSTMENTS, (4) FUEL PUMP ADJUSTMENTS ON THE ENGINE (PTR AND PTG),…

Simulation and Spectrum Extraction in the Spectroscopic Channel of the SNAP Experiment

NASA Astrophysics Data System (ADS)

Tilquin, Andre; Bonissent, A.; Gerdes, D.; Ealet, A.; Prieto, E.; Macaire, C.; Aumenier, M. H.

2007-05-01

A pixel-level simulation software is described. It is composed of two modules. The first module applies Fourier optics at each active element of the system to construct the PSF at a large variety of wavelengths and spatial locations of the point source. The input is provided by the engineer's design program (Zemax). It describes the optical path and the distortions. The PSF properties are compressed and interpolated using shapelets decomposition and neural network techniques. A second module is used for production jobs. It uses the output of the first module to reconstruct the relevant PSF and integrate it on the detector pixels. Extended and polychromatic sources are approximated by a combination of monochromatic point sources. For the spectrum extraction, we use a fast simulator based on a multidimensional linear interpolation of the pixel response tabulated on a grid of values of wavelength, position on sky and slice number. The prediction of the fast simulator is compared to the observed pixel content, and a chi-square minimization where the parameters are the bin contents is used to build the extracted spectrum. The visible and infrared arms are combined in the same chi-square, providing a single spectrum.

MINE: Module Identification in Networks

PubMed Central

2011-01-01

Background Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of functionally related gene products, is an important challenge in analyzing biological networks. However, existing tools to identify modules are insufficient when applied to dense networks of experimentally derived interaction data. To address this problem, we have developed an agglomerative clustering method that is able to identify highly modular sets of gene products within highly interconnected molecular interaction networks. Results MINE outperforms MCODE, CFinder, NEMO, SPICi, and MCL in identifying non-exclusive, high modularity clusters when applied to the C. elegans protein-protein interaction network. The algorithm generally achieves superior geometric accuracy and modularity for annotated functional categories. In comparison with the most closely related algorithm, MCODE, the top clusters identified by MINE are consistently of higher density and MINE is less likely to designate overlapping modules as a single unit. MINE offers a high level of granularity with a small number of adjustable parameters, enabling users to fine-tune cluster results for input networks with differing topological properties. Conclusions MINE was created in response to the challenge of discovering high quality modules of gene products within highly interconnected biological networks. The algorithm allows a high degree of flexibility and user-customisation of results with few adjustable parameters. MINE outperforms several popular clustering algorithms in identifying modules with high modularity and obtains good overall recall and precision of functional annotations in protein-protein interaction networks from both S. cerevisiae and C. elegans. PMID:21605434

Detecting phenotype-driven transitions in regulatory network structure.

PubMed

Padi, Megha; Quackenbush, John

2018-01-01

Complex traits and diseases like human height or cancer are often not caused by a single mutation or genetic variant, but instead arise from functional changes in the underlying molecular network. Biological networks are known to be highly modular and contain dense "communities" of genes that carry out cellular processes, but these structures change between tissues, during development, and in disease. While many methods exist for inferring networks and analyzing their topologies separately, there is a lack of robust methods for quantifying differences in network structure. Here, we describe ALPACA (ALtered Partitions Across Community Architectures), a method for comparing two genome-scale networks derived from different phenotypic states to identify condition-specific modules. In simulations, ALPACA leads to more nuanced, sensitive, and robust module discovery than currently available network comparison methods. As an application, we use ALPACA to compare transcriptional networks in three contexts: angiogenic and non-angiogenic subtypes of ovarian cancer, human fibroblasts expressing transforming viral oncogenes, and sexual dimorphism in human breast tissue. In each case, ALPACA identifies modules enriched for processes relevant to the phenotype. For example, modules specific to angiogenic ovarian tumors are enriched for genes associated with blood vessel development, and modules found in female breast tissue are enriched for genes involved in estrogen receptor and ERK signaling. The functional relevance of these new modules suggests that not only can ALPACA identify structural changes in complex networks, but also that these changes may be relevant for characterizing biological phenotypes.

Engine Performance (Section C: Emission Control Systems). Auto Mechanics Curriculum Guide. Module 3. Instructor's Guide.

ERIC Educational Resources Information Center

Rains, Larry

This engine performance (emission control systems) module is one of a series of competency-based modules in the Missouri Auto Mechanics Curriculum Guide. Topics of this module's five units are: positive crankcase ventilation (PCV) and evaporative emission control systems; exhaust gas recirculation (EGR); air injection and catalytic converters;…

Graph coarse-graining reveals differences in the module-level structure of functional brain networks.

PubMed

Kujala, Rainer; Glerean, Enrico; Pan, Raj Kumar; Jääskeläinen, Iiro P; Sams, Mikko; Saramäki, Jari

2016-11-01

Networks have become a standard tool for analyzing functional magnetic resonance imaging (fMRI) data. In this approach, brain areas and their functional connections are mapped to the nodes and links of a network. Even though this mapping reduces the complexity of the underlying data, it remains challenging to understand the structure of the resulting networks due to the large number of nodes and links. One solution is to partition networks into modules and then investigate the modules' composition and relationship with brain functioning. While this approach works well for single networks, understanding differences between two networks by comparing their partitions is difficult and alternative approaches are thus necessary. To this end, we present a coarse-graining framework that uses a single set of data-driven modules as a frame of reference, enabling one to zoom out from the node- and link-level details. As a result, differences in the module-level connectivity can be understood in a transparent, statistically verifiable manner. We demonstrate the feasibility of the method by applying it to networks constructed from fMRI data recorded from 13 healthy subjects during rest and movie viewing. While independently partitioning the rest and movie networks is shown to yield little insight, the coarse-graining framework enables one to pinpoint differences in the module-level structure, such as the increased number of intra-module links within the visual cortex during movie viewing. In addition to quantifying differences due to external stimuli, the approach could also be applied in clinical settings, such as comparing patients with healthy controls. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

78 FR 7464 - Large Scale Networking (LSN) ; Joint Engineering Team (JET)

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-01

... NATIONAL SCIENCE FOUNDATION Large Scale Networking (LSN) ; Joint Engineering Team (JET) AGENCY: The Networking and Information Technology Research and Development (NITRD) National Coordination...://www.nitrd.gov/nitrdgroups/index.php?title=Joint_Engineering_Team_ (JET)#title. SUMMARY: The JET...

A mean field neural network for hierarchical module placement

NASA Technical Reports Server (NTRS)

Unaltuna, M. Kemal; Pitchumani, Vijay

1992-01-01

This paper proposes a mean field neural network for the two-dimensional module placement problem. An efficient coding scheme with only O(N log N) neurons is employed where N is the number of modules. The neurons are evolved in groups of N in log N iteration steps such that the circuit is recursively partitioned in alternating vertical and horizontal directions. In our simulations, the network was able to find optimal solutions to all test problems with up to 128 modules.

Mapping, Awareness, And Virtualization Network Administrator Training Tool Virtualization Module

DTIC Science & Technology

2016-03-01

AND VIRTUALIZATION NETWORK ADMINISTRATOR TRAINING TOOL VIRTUALIZATION MODULE by Erik W. Berndt March 2016 Thesis Advisor: John Gibson...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE MAPPING, AWARENESS, AND VIRTUALIZATION NETWORK ADMINISTRATOR TRAINING TOOL... VIRTUALIZATION MODULE 5. FUNDING NUMBERS 6. AUTHOR(S) Erik W. Berndt 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Postgraduate School

Circuit-Host Coupling Induces Multifaceted Behavioral Modulations of a Gene Switch.

PubMed

Blanchard, Andrew E; Liao, Chen; Lu, Ting

2018-02-06

Quantitative modeling of gene circuits is fundamentally important to synthetic biology, as it offers the potential to transform circuit engineering from trial-and-error construction to rational design and, hence, facilitates the advance of the field. Currently, typical models regard gene circuits as isolated entities and focus only on the biochemical processes within the circuits. However, such a standard paradigm is getting challenged by increasing experimental evidence suggesting that circuits and their host are intimately connected, and their interactions can potentially impact circuit behaviors. Here we systematically examined the roles of circuit-host coupling in shaping circuit dynamics by using a self-activating gene switch as a model circuit. Through a combination of deterministic modeling, stochastic simulation, and Fokker-Planck equation formalism, we found that circuit-host coupling alters switch behaviors across multiple scales. At the single-cell level, it slows the switch dynamics in the high protein production regime and enlarges the difference between stable steady-state values. At the population level, it favors cells with low protein production through differential growth amplification. Together, the two-level coupling effects induce both quantitative and qualitative modulations of the switch, with the primary component of the effects determined by the circuit's architectural parameters. This study illustrates the complexity and importance of circuit-host coupling in modulating circuit behaviors, demonstrating the need for a new paradigm-integrated modeling of the circuit-host system-for quantitative understanding of engineered gene networks. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

A new multi-scale method to reveal hierarchical modular structures in biological networks.

PubMed

Jiao, Qing-Ju; Huang, Yan; Shen, Hong-Bin

2016-11-15

Biological networks are effective tools for studying molecular interactions. Modular structure, in which genes or proteins may tend to be associated with functional modules or protein complexes, is a remarkable feature of biological networks. Mining modular structure from biological networks enables us to focus on a set of potentially important nodes, which provides a reliable guide to future biological experiments. The first fundamental challenge in mining modular structure from biological networks is that the quality of the observed network data is usually low owing to noise and incompleteness in the obtained networks. The second problem that poses a challenge to existing approaches to the mining of modular structure is that the organization of both functional modules and protein complexes in networks is far more complicated than was ever thought. For instance, the sizes of different modules vary considerably from each other and they often form multi-scale hierarchical structures. To solve these problems, we propose a new multi-scale protocol for mining modular structure (named ISIMB) driven by a node similarity metric, which works in an iteratively converged space to reduce the effects of the low data quality of the observed network data. The multi-scale node similarity metric couples both the local and the global topology of the network with a resolution regulator. By varying this resolution regulator to give different weightings to the local and global terms in the metric, the ISIMB method is able to fit the shape of modules and to detect them on different scales. Experiments on protein-protein interaction and genetic interaction networks show that our method can not only mine functional modules and protein complexes successfully, but can also predict functional modules from specific to general and reveal the hierarchical organization of protein complexes.

Wrinkling of graphene membranes supported by silica nanoparticles on substrates

NASA Astrophysics Data System (ADS)

Yamamoto, Mahito; Cullen, William; Fuhrer, Michael; Einstein, Theodore; Department of Physics, University of Maryland Team

2011-03-01

The challenging endeavor of modulating the morphology of graphene via a patterned substrate to produce a controlled deformation has great potential importance for strain engineering the electronic properties of graphene. An essential step in this direction is to understand the response of graphene to substrate features of known geometry. Here we employ silica nanoparticles with a diameter of 10-100 nm to uniformly decorate Si O2 and mica substrates before depositing graphene, to promote nanoscale modulation of graphene geometry. The morphology of graphene on this modified substrate is then characterized by atomic force spectroscopy. We find that graphene on the substrate is locally raised by the supporting nanoparticles, and wrinkling propagates radially from the protrusions to form a ridge network which links the protrusions. We discuss the dependence of the wrinkled morphology on nanoparticle diameter and graphene thickness in terms of graphene elasticity and adhesion energy. Supported by NSF-MRSEC, Grant DMR 05-20471

State-dependent, bidirectional modulation of neural network activity by endocannabinoids.

PubMed

Piet, Richard; Garenne, André; Farrugia, Fanny; Le Masson, Gwendal; Marsicano, Giovanni; Chavis, Pascale; Manzoni, Olivier J

2011-11-16

The endocannabinoid (eCB) system and the cannabinoid CB1 receptor (CB1R) play key roles in the modulation of brain functions. Although actions of eCBs and CB1Rs are well described at the synaptic level, little is known of their modulation of neural activity at the network level. Using microelectrode arrays, we have examined the role of CB1R activation in the modulation of the electrical activity of rat and mice cortical neural networks in vitro. We find that exogenous activation of CB1Rs expressed on glutamatergic neurons decreases the spontaneous activity of cortical neural networks. Moreover, we observe that the net effect of the CB1R antagonist AM251 inversely correlates with the initial level of activity in the network: blocking CB1Rs increases network activity when basal network activity is low, whereas it depresses spontaneous activity when its initial level is high. Our results reveal a complex role of CB1Rs in shaping spontaneous network activity, and suggest that the outcome of endogenous neuromodulation on network function might be state dependent.

Using experimental design modules for process characterization in manufacturing/materials processes laboratories

NASA Technical Reports Server (NTRS)

Ankenman, Bruce; Ermer, Donald; Clum, James A.

1994-01-01

Modules dealing with statistical experimental design (SED), process modeling and improvement, and response surface methods have been developed and tested in two laboratory courses. One course was a manufacturing processes course in Mechanical Engineering and the other course was a materials processing course in Materials Science and Engineering. Each module is used as an 'experiment' in the course with the intent that subsequent course experiments will use SED methods for analysis and interpretation of data. Evaluation of the modules' effectiveness has been done by both survey questionnaires and inclusion of the module methodology in course examination questions. Results of the evaluation have been very positive. Those evaluation results and details of the modules' content and implementation are presented. The modules represent an important component for updating laboratory instruction and to provide training in quality for improved engineering practice.

RM-SORN: a reward-modulated self-organizing recurrent neural network.

PubMed

Aswolinskiy, Witali; Pipa, Gordon

2015-01-01

Neural plasticity plays an important role in learning and memory. Reward-modulation of plasticity offers an explanation for the ability of the brain to adapt its neural activity to achieve a rewarded goal. Here, we define a neural network model that learns through the interaction of Intrinsic Plasticity (IP) and reward-modulated Spike-Timing-Dependent Plasticity (STDP). IP enables the network to explore possible output sequences and STDP, modulated by reward, reinforces the creation of the rewarded output sequences. The model is tested on tasks for prediction, recall, non-linear computation, pattern recognition, and sequence generation. It achieves performance comparable to networks trained with supervised learning, while using simple, biologically motivated plasticity rules, and rewarding strategies. The results confirm the importance of investigating the interaction of several plasticity rules in the context of reward-modulated learning and whether reward-modulated self-organization can explain the amazing capabilities of the brain.

77 FR 58415 - Large Scale Networking (LSN); Joint Engineering Team (JET)

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-20

... NATIONAL SCIENCE FOUNDATION Large Scale Networking (LSN); Joint Engineering Team (JET) AGENCY: The Networking and Information Technology Research and Development (NITRD) National Coordination Office (NCO..._Engineering_Team_ (JET). SUMMARY: The JET, established in 1997, provides for information sharing among Federal...

78 FR 70076 - Large Scale Networking (LSN)-Joint Engineering Team (JET)

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-22

... NATIONAL SCIENCE FOUNDATION Large Scale Networking (LSN)--Joint Engineering Team (JET) AGENCY: The Networking and Information Technology Research and Development (NITRD) National Coordination Office (NCO..._Engineering_Team_ (JET)#title. SUMMARY: The JET, established in 1997, provides for information sharing among...

The Future of Metabolic Engineering and Synthetic Biology: Towards a Systematic Practice

PubMed Central

Yadav, Vikramaditya G.; De Mey, Marjan; Lim, Chin Giaw; Ajikumar, Parayil Kumaran; Stephanopoulos, Gregory

2012-01-01

Industrial biotechnology promises to revolutionize conventional chemical manufacturing in the years ahead, largely owing to the excellent progress in our ability to re-engineer cellular metabolism. However, most successes of metabolic engineering have been confined to over-producing natively synthesized metabolites in E. coli and S. cerevisiae. A major reason for this development has been the descent of metabolic engineering, particularly secondary metabolic engineering, to a collection of demonstrations rather than a systematic practice with generalizable tools. Synthetic biology, a more recent development, faces similar criticisms. Herein, we attempt to lay down a framework around which bioreaction engineering can systematize itself just like chemical reaction engineering. Central to this undertaking is a new approach to engineering secondary metabolism known as ‘multivariate modular metabolic engineering’ (MMME), whose novelty lies in its assessment and elimination of regulatory and pathway bottlenecks by re-defining the metabolic network as a collection of distinct modules. After introducing the core principles of MMME, we shall then present a number of recent developments in secondary metabolic engineering that could potentially serve as its facilitators. It is hoped that the ever-declining costs of de novo gene synthesis; the improved use of bioinformatic tools to mine, sort and analyze biological data; and the increasing sensitivity and sophistication of investigational tools will make the maturation of microbial metabolic engineering an autocatalytic process. Encouraged by these advances, research groups across the world would take up the challenge of secondary metabolite production in simple hosts with renewed vigor, thereby adding to the range of products synthesized using metabolic engineering. PMID:22629571

Dynamic Neural Networks Supporting Memory Retrieval

PubMed Central

St. Jacques, Peggy L.; Kragel, Philip A.; Rubin, David C.

2011-01-01

How do separate neural networks interact to support complex cognitive processes such as remembrance of the personal past? Autobiographical memory (AM) retrieval recruits a consistent pattern of activation that potentially comprises multiple neural networks. However, it is unclear how such large-scale neural networks interact and are modulated by properties of the memory retrieval process. In the present functional MRI (fMRI) study, we combined independent component analysis (ICA) and dynamic causal modeling (DCM) to understand the neural networks supporting AM retrieval. ICA revealed four task-related components consistent with the previous literature: 1) Medial Prefrontal Cortex (PFC) Network, associated with self-referential processes, 2) Medial Temporal Lobe (MTL) Network, associated with memory, 3) Frontoparietal Network, associated with strategic search, and 4) Cingulooperculum Network, associated with goal maintenance. DCM analysis revealed that the medial PFC network drove activation within the system, consistent with the importance of this network to AM retrieval. Additionally, memory accessibility and recollection uniquely altered connectivity between these neural networks. Recollection modulated the influence of the medial PFC on the MTL network during elaboration, suggesting that greater connectivity among subsystems of the default network supports greater re-experience. In contrast, memory accessibility modulated the influence of frontoparietal and MTL networks on the medial PFC network, suggesting that ease of retrieval involves greater fluency among the multiple networks contributing to AM. These results show the integration between neural networks supporting AM retrieval and the modulation of network connectivity by behavior. PMID:21550407

Principles of Biomimetic Vascular Network Design Applied to a Tissue-Engineered Liver Scaffold

PubMed Central

Hoganson, David M.; Pryor, Howard I.; Spool, Ira D.; Burns, Owen H.; Gilmore, J. Randall

2010-01-01

Branched vascular networks are a central component of scaffold architecture for solid organ tissue engineering. In this work, seven biomimetic principles were established as the major guiding technical design considerations of a branched vascular network for a tissue-engineered scaffold. These biomimetic design principles were applied to a branched radial architecture to develop a liver-specific vascular network. Iterative design changes and computational fluid dynamic analysis were used to optimize the network before mold manufacturing. The vascular network mold was created using a new mold technique that achieves a 1:1 aspect ratio for all channels. In vitro blood flow testing confirmed the physiologic hemodynamics of the network as predicted by computational fluid dynamic analysis. These results indicate that this biomimetic liver vascular network design will provide a foundation for developing complex vascular networks for solid organ tissue engineering that achieve physiologic blood flow. PMID:20001254

Principles of biomimetic vascular network design applied to a tissue-engineered liver scaffold.

PubMed

Hoganson, David M; Pryor, Howard I; Spool, Ira D; Burns, Owen H; Gilmore, J Randall; Vacanti, Joseph P

2010-05-01

Branched vascular networks are a central component of scaffold architecture for solid organ tissue engineering. In this work, seven biomimetic principles were established as the major guiding technical design considerations of a branched vascular network for a tissue-engineered scaffold. These biomimetic design principles were applied to a branched radial architecture to develop a liver-specific vascular network. Iterative design changes and computational fluid dynamic analysis were used to optimize the network before mold manufacturing. The vascular network mold was created using a new mold technique that achieves a 1:1 aspect ratio for all channels. In vitro blood flow testing confirmed the physiologic hemodynamics of the network as predicted by computational fluid dynamic analysis. These results indicate that this biomimetic liver vascular network design will provide a foundation for developing complex vascular networks for solid organ tissue engineering that achieve physiologic blood flow.

A Modularity-Based Method Reveals Mixed Modules from Chemical-Gene Heterogeneous Network

PubMed Central

Song, Jianglong; Tang, Shihuan; Liu, Xi; Gao, Yibo; Yang, Hongjun; Lu, Peng

2015-01-01

For a multicomponent therapy, molecular network is essential to uncover its specific mode of action from a holistic perspective. The molecular system of a Traditional Chinese Medicine (TCM) formula can be represented by a 2-class heterogeneous network (2-HN), which typically includes chemical similarities, chemical-target interactions and gene interactions. An important premise of uncovering the molecular mechanism is to identify mixed modules from complex chemical-gene heterogeneous network of a TCM formula. We thus proposed a novel method (MixMod) based on mixed modularity to detect accurate mixed modules from 2-HNs. At first, we compared MixMod with Clauset-Newman-Moore algorithm (CNM), Markov Cluster algorithm (MCL), Infomap and Louvain on benchmark 2-HNs with known module structure. Results showed that MixMod was superior to other methods when 2-HNs had promiscuous module structure. Then these methods were tested on a real drug-target network, in which 88 disease clusters were regarded as real modules. MixMod could identify the most accurate mixed modules from the drug-target 2-HN (normalized mutual information 0.62 and classification accuracy 0.4524). In the end, MixMod was applied to the 2-HN of Buchang naoxintong capsule (BNC) and detected 49 mixed modules. By using enrichment analysis, we investigated five mixed modules that contained primary constituents of BNC intestinal absorption liquid. As a matter of fact, the findings of in vitro experiments using BNC intestinal absorption liquid were found to highly accord with previous analysis. Therefore, MixMod is an effective method to detect accurate mixed modules from chemical-gene heterogeneous networks and further uncover the molecular mechanism of multicomponent therapies, especially TCM formulae. PMID:25927435

Human connectome module pattern detection using a new multi-graph MinMax cut model.

PubMed

De, Wang; Wang, Yang; Nie, Feiping; Yan, Jingwen; Cai, Weidong; Saykin, Andrew J; Shen, Li; Huang, Heng

2014-01-01

Many recent scientific efforts have been devoted to constructing the human connectome using Diffusion Tensor Imaging (DTI) data for understanding the large-scale brain networks that underlie higher-level cognition in human. However, suitable computational network analysis tools are still lacking in human connectome research. To address this problem, we propose a novel multi-graph min-max cut model to detect the consistent network modules from the brain connectivity networks of all studied subjects. A new multi-graph MinMax cut model is introduced to solve this challenging computational neuroscience problem and the efficient optimization algorithm is derived. In the identified connectome module patterns, each network module shows similar connectivity patterns in all subjects, which potentially associate to specific brain functions shared by all subjects. We validate our method by analyzing the weighted fiber connectivity networks. The promising empirical results demonstrate the effectiveness of our method.

Dispatching packets on a global combining network of a parallel computer

DOEpatents

Almasi, Gheorghe [Ardsley, NY; Archer, Charles J [Rochester, MN

2011-07-19

Methods, apparatus, and products are disclosed for dispatching packets on a global combining network of a parallel computer comprising a plurality of nodes connected for data communications using the network capable of performing collective operations and point to point operations that include: receiving, by an origin system messaging module on an origin node from an origin application messaging module on the origin node, a storage identifier and an operation identifier, the storage identifier specifying storage containing an application message for transmission to a target node, and the operation identifier specifying a message passing operation; packetizing, by the origin system messaging module, the application message into network packets for transmission to the target node, each network packet specifying the operation identifier and an operation type for the message passing operation specified by the operation identifier; and transmitting, by the origin system messaging module, the network packets to the target node.

Large liquid rocket engine transient performance simulation system

NASA Technical Reports Server (NTRS)

Mason, J. R.; Southwick, R. D.

1989-01-01

Phase 1 of the Rocket Engine Transient Simulation (ROCETS) program consists of seven technical tasks: architecture; system requirements; component and submodel requirements; submodel implementation; component implementation; submodel testing and verification; and subsystem testing and verification. These tasks were completed. Phase 2 of ROCETS consists of two technical tasks: Technology Test Bed Engine (TTBE) model data generation; and system testing verification. During this period specific coding of the system processors was begun and the engineering representations of Phase 1 were expanded to produce a simple model of the TTBE. As the code was completed, some minor modifications to the system architecture centering on the global variable common, GLOBVAR, were necessary to increase processor efficiency. The engineering modules completed during Phase 2 are listed: INJTOO - main injector; MCHBOO - main chamber; NOZLOO - nozzle thrust calculations; PBRNOO - preburner; PIPE02 - compressible flow without inertia; PUMPOO - polytropic pump; ROTROO - rotor torque balance/speed derivative; and TURBOO - turbine. Detailed documentation of these modules is in the Appendix. In addition to the engineering modules, several submodules were also completed. These submodules include combustion properties, component performance characteristics (maps), and specific utilities. Specific coding was begun on the system configuration processor. All functions necessary for multiple module operation were completed but the SOLVER implementation is still under development. This system, the Verification Checkout Facility (VCF) allows interactive comparison of module results to store data as well as provides an intermediate checkout of the processor code. After validation using the VCF, the engineering modules and submodules were used to build a simple TTBE.

Efficient Parallel Engineering Computing on Linux Workstations

NASA Technical Reports Server (NTRS)

Lou, John Z.

2010-01-01

A C software module has been developed that creates lightweight processes (LWPs) dynamically to achieve parallel computing performance in a variety of engineering simulation and analysis applications to support NASA and DoD project tasks. The required interface between the module and the application it supports is simple, minimal and almost completely transparent to the user applications, and it can achieve nearly ideal computing speed-up on multi-CPU engineering workstations of all operating system platforms. The module can be integrated into an existing application (C, C++, Fortran and others) either as part of a compiled module or as a dynamically linked library (DLL).

Default Network Modulation and Large-Scale Network Interactivity in Healthy Young and Old Adults

PubMed Central

Schacter, Daniel L.

2012-01-01

We investigated age-related changes in default, attention, and control network activity and their interactions in young and old adults. Brain activity during autobiographical and visuospatial planning was assessed using multivariate analysis and with intrinsic connectivity networks as regions of interest. In both groups, autobiographical planning engaged the default network while visuospatial planning engaged the attention network, consistent with a competition between the domains of internalized and externalized cognition. The control network was engaged for both planning tasks. In young subjects, the control network coupled with the default network during autobiographical planning and with the attention network during visuospatial planning. In old subjects, default-to-control network coupling was observed during both planning tasks, and old adults failed to deactivate the default network during visuospatial planning. This failure is not indicative of default network dysfunction per se, evidenced by default network engagement during autobiographical planning. Rather, a failure to modulate the default network in old adults is indicative of a lower degree of flexible network interactivity and reduced dynamic range of network modulation to changing task demands. PMID:22128194

Electronics and Software Engineer for Robotics Project Intern

NASA Technical Reports Server (NTRS)

Teijeiro, Antonio

2017-01-01

I was assigned to mentor high school students for the 2017 First Robotics Competition. Using a team based approach, I worked with the students to program the robot and applied my electrical background to build the robot from start to finish. I worked with students who had an interest in electrical engineering to teach them about voltage, current, pulse width modulation, solenoids, electromagnets, relays, DC motors, DC motor controllers, crimping and soldering electrical components, Java programming, and robotic simulation. For the simulation, we worked together to generate graphics files, write simulator description format code, operate Linux, and operate SOLIDWORKS. Upon completion of the FRC season, I transitioned over to providing full time support for the LCS hardware team. During this phase of my internship I helped my co-intern write test steps for two networking hardware DVTs , as well as run cables and update cable running lists.

Application of neural networks to software quality modeling of a very large telecommunications system.

PubMed

Khoshgoftaar, T M; Allen, E B; Hudepohl, J P; Aud, S J

1997-01-01

Society relies on telecommunications to such an extent that telecommunications software must have high reliability. Enhanced measurement for early risk assessment of latent defects (EMERALD) is a joint project of Nortel and Bell Canada for improving the reliability of telecommunications software products. This paper reports a case study of neural-network modeling techniques developed for the EMERALD system. The resulting neural network is currently in the prototype testing phase at Nortel. Neural-network models can be used to identify fault-prone modules for extra attention early in development, and thus reduce the risk of operational problems with those modules. We modeled a subset of modules representing over seven million lines of code from a very large telecommunications software system. The set consisted of those modules reused with changes from the previous release. The dependent variable was membership in the class of fault-prone modules. The independent variables were principal components of nine measures of software design attributes. We compared the neural-network model with a nonparametric discriminant model and found the neural-network model had better predictive accuracy.

Gene co-expression network analysis in Rhodobacter capsulatus and application to comparative expression analysis of Rhodobacter sphaeroides

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pena-Castillo, Lourdes; Mercer, Ryan; Gurinovich, Anastasia

2014-08-28

The genus Rhodobacter contains purple nonsulfur bacteria found mostly in freshwater environments. Representative strains of two Rhodobacter species, R. capsulatus and R. sphaeroides, have had their genomes fully sequenced and both have been the subject of transcriptional profiling studies. Gene co-expression networks can be used to identify modules of genes with similar expression profiles. Functional analysis of gene modules can then associate co-expressed genes with biological pathways, and network statistics can determine the degree of module preservation in related networks. In this paper, we constructed an R. capsulatus gene co-expression network, performed functional analysis of identified gene modules, and investigatedmore » preservation of these modules in R. capsulatus proteomics data and in R. sphaeroides transcriptomics data. Results: The analysis identified 40 gene co-expression modules in R. capsulatus. Investigation of the module gene contents and expression profiles revealed patterns that were validated based on previous studies supporting the biological relevance of these modules. We identified two R. capsulatus gene modules preserved in the protein abundance data. We also identified several gene modules preserved between both Rhodobacter species, which indicate that these cellular processes are conserved between the species and are candidates for functional information transfer between species. Many gene modules were non-preserved, providing insight into processes that differentiate the two species. In addition, using Local Network Similarity (LNS), a recently proposed metric for expression divergence, we assessed the expression conservation of between-species pairs of orthologs, and within-species gene-protein expression profiles. Conclusions: Our analyses provide new sources of information for functional annotation in R. capsulatus because uncharacterized genes in modules are now connected with groups of genes that constitute a joint functional annotation. We identified R. capsulatus modules enriched with genes for ribosomal proteins, porphyrin and bacteriochlorophyll anabolism, and biosynthesis of secondary metabolites to be preserved in R. sphaeroides whereas modules related to RcGTA production and signalling showed lack of preservation in R. sphaeroides. In addition, we demonstrated that network statistics may also be applied within-species to identify congruence between mRNA expression and protein abundance data for which simple correlation measurements have previously had mixed results.« less

Semantic integration to identify overlapping functional modules in protein interaction networks

PubMed Central

Cho, Young-Rae; Hwang, Woochang; Ramanathan, Murali; Zhang, Aidong

2007-01-01

Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO) annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification. PMID:17650343

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT XXVIII, I--CATERPILLAR STARTING (PONEY) ENGINE (PART II), II--UNDERSTANDING MORE ABOUT STARTING DEVICES.

ERIC Educational Resources Information Center

Human Engineering Inst., Cleveland, OH.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF THE OPERATION AND MAINTENANCE OF DIESEL ENGINE STARTING ENGINES. TOPICS ARE (1) STARTING ENGINE MAGNETO (WICO), (2) MAGNETO MAINTENANCE, (3) SPARK PLUGS, (4) GENERAL DESCRIPTION (STARTING DEVICES), (5) OPERATING (STARTING DEVICES), (6) LUBRICATION (STARTING DEVICES), (7)…

The Thermoanaerobacter Glycobiome Reveals Mechanisms of Pentose and Hexose Co-Utilization in Bacteria

PubMed Central

Tu, Qichao; Qin, Yujia; Zhou, Aifen; Liu, Wenbin; He, Zhili; Zhou, Jizhong; Xu, Jian

2011-01-01

Thermoanaerobic bacteria are of interest in cellulosic-biofuel production, due to their simultaneous pentose and hexose utilization (co-utilization) and thermophilic nature. In this study, we experimentally reconstructed the structure and dynamics of the first genome-wide carbon utilization network of thermoanaerobes. The network uncovers numerous novel pathways and identifies previously unrecognized but crucial pathway interactions and the associated key junctions. First, glucose, xylose, fructose, and cellobiose catabolism are each featured in distinct functional modules; the transport systems of hexose and pentose are apparently both regulated by transcriptional antiterminators of the BglG family, which is consistent with pentose and hexose co-utilization. Second, glucose and xylose modules cooperate in that the activity of the former promotes the activity of the latter via activating xylose transport and catabolism, while xylose delays cell lysis by sustaining coenzyme and ion metabolism. Third, the vitamin B12 pathway appears to promote ethanologenesis through ethanolamine and 1, 2-propanediol, while the arginine deiminase pathway probably contributes to cell survival in stationary phase. Moreover, by experimentally validating the distinct yet collaborative nature of glucose and xylose catabolism, we demonstrated that these novel network-derived features can be rationally exploited for product-yield enhancement via optimized timing and balanced loading of the carbon supply in a substrate-specific manner. Thus, this thermoanaerobic glycobiome reveals novel genetic features in carbon catabolism that may have immediate industrial implications and provides novel strategies and targets for fermentation and genome engineering. PMID:22022280

Oxytocin receptors modulate a social salience neural network in male prairie voles.

PubMed

Johnson, Zachary V; Walum, Hasse; Xiao, Yao; Riefkohl, Paula C; Young, Larry J

2017-01-01

Social behavior is regulated by conserved neural networks across vertebrates. Variation in the organization of neuropeptide systems across these networks is thought to contribute to individual and species diversity in network function during social contexts. For example, oxytocin (OT) is an ancient neuropeptide that binds to OT receptors (OTRs) in the brain and modulates social and reproductive behavior across vertebrate species, including humans. Central OTRs exhibit extraordinarily diverse expression patterns that are associated with individual and species differences in social behavior. In voles, OTR density in the nucleus accumbens (NAc)-a region important for social and reward learning-is associated with individual and species variation in social attachment behavior. Here we test whether OTRs in the NAc modulate a social salience network (SSN)-a network of interconnected brain nuclei thought to encode valence and incentive salience of sociosensory cues-during a social context in the socially monogamous male prairie vole. Using a selective OTR antagonist, we test whether activation of OTRs in the NAc during sociosexual interaction and mating modulates expression of the immediate early gene product Fos across nuclei of the SSN. We show that blockade of endogenous OTR signaling in the NAc during sociosexual interaction and mating does not strongly modulate levels of Fos expression in individual nodes of the network, but strongly modulates patterns of correlated Fos expression between the NAc and other SSN nuclei. Published by Elsevier Inc.

Multi-equilibrium property of metabolic networks: SSI module.

PubMed

Lei, Hong-Bo; Zhang, Ji-Feng; Chen, Luonan

2011-06-20

Revealing the multi-equilibrium property of a metabolic network is a fundamental and important topic in systems biology. Due to the complexity of the metabolic network, it is generally a difficult task to study the problem as a whole from both analytical and numerical viewpoint. On the other hand, the structure-oriented modularization idea is a good choice to overcome such a difficulty, i.e. decomposing the network into several basic building blocks and then studying the whole network through investigating the dynamical characteristics of the basic building blocks and their interactions. Single substrate and single product with inhibition (SSI) metabolic module is one type of the basic building blocks of metabolic networks, and its multi-equilibrium property has important influence on that of the whole metabolic networks. In this paper, we describe what the SSI metabolic module is, characterize the rates of the metabolic reactions by Hill kinetics and give a unified model for SSI modules by using a set of nonlinear ordinary differential equations with multi-variables. Specifically, a sufficient and necessary condition is first given to describe the injectivity of a class of nonlinear systems, and then, the sufficient condition is used to study the multi-equilibrium property of SSI modules. As a main theoretical result, for the SSI modules in which each reaction has no more than one inhibitor, a sufficient condition is derived to rule out multiple equilibria, i.e. the Jacobian matrix of its rate function is nonsingular everywhere. In summary, we describe SSI modules and give a general modeling framework based on Hill kinetics, and provide a sufficient condition for ruling out multiple equilibria of a key type of SSI module.

Multi-equilibrium property of metabolic networks: SSI module

PubMed Central

2011-01-01

Background Revealing the multi-equilibrium property of a metabolic network is a fundamental and important topic in systems biology. Due to the complexity of the metabolic network, it is generally a difficult task to study the problem as a whole from both analytical and numerical viewpoint. On the other hand, the structure-oriented modularization idea is a good choice to overcome such a difficulty, i.e. decomposing the network into several basic building blocks and then studying the whole network through investigating the dynamical characteristics of the basic building blocks and their interactions. Single substrate and single product with inhibition (SSI) metabolic module is one type of the basic building blocks of metabolic networks, and its multi-equilibrium property has important influence on that of the whole metabolic networks. Results In this paper, we describe what the SSI metabolic module is, characterize the rates of the metabolic reactions by Hill kinetics and give a unified model for SSI modules by using a set of nonlinear ordinary differential equations with multi-variables. Specifically, a sufficient and necessary condition is first given to describe the injectivity of a class of nonlinear systems, and then, the sufficient condition is used to study the multi-equilibrium property of SSI modules. As a main theoretical result, for the SSI modules in which each reaction has no more than one inhibitor, a sufficient condition is derived to rule out multiple equilibria, i.e. the Jacobian matrix of its rate function is nonsingular everywhere. Conclusions In summary, we describe SSI modules and give a general modeling framework based on Hill kinetics, and provide a sufficient condition for ruling out multiple equilibria of a key type of SSI module. PMID:21689474

Defining and Exposing Privacy Issues with Social Media

DTIC Science & Technology

2012-06-11

Twitter, and Linked In[ I 0). VI. SEARCH ENGINES In addition to social networking sites, search engines pose new issues to privacy. As...networking, search engines , and storing personal information online in general have been accepted worldwide due to the benefits they provide. Social...networking provides even more communication in an information-demanding age, allowing users to interact across great distances. Search engines allow

Hybrid Neural-Network: Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics Developed and Demonstrated

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2002-01-01

As part of the NASA Aviation Safety Program, a unique model-based diagnostics method that employs neural networks and genetic algorithms for aircraft engine performance diagnostics has been developed and demonstrated at the NASA Glenn Research Center against a nonlinear gas turbine engine model. Neural networks are applied to estimate the internal health condition of the engine, and genetic algorithms are used for sensor fault detection, isolation, and quantification. This hybrid architecture combines the excellent nonlinear estimation capabilities of neural networks with the capability to rank the likelihood of various faults given a specific sensor suite signature. The method requires a significantly smaller data training set than a neural network approach alone does, and it performs the combined engine health monitoring objectives of performance diagnostics and sensor fault detection and isolation in the presence of nominal and degraded engine health conditions.

Network Performance Evaluation Model for assessing the impacts of high-occupancy vehicle facilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Janson, B.N.; Zozaya-Gorostiza, C.; Southworth, F.

1986-09-01

A model to assess the impacts of major high-occupancy vehicle (HOV) facilities on regional levels of energy consumption and vehicle air pollution emissions in urban aeas is developed and applied. This model can be used to forecast and compare the impacts of alternative HOV facility design and operation plans on traffic patterns, travel costs, model choice, travel demand, energy consumption and vehicle emissions. The model is designed to show differences in the overall impacts of alternative HOV facility types, locations and operation plans rather than to serve as a tool for detailed engineering design and traffic planning studies. The Networkmore » Performance Evaluation Model (NETPEM) combines several urban transportation planning models within a multi-modal network equilibrium framework including modules with which to define the type, location and use policy of the HOV facility to be tested, and to assess the impacts of this facility.« less

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT IX, ENGINE COMPONENTS.

ERIC Educational Resources Information Center

Human Engineering Inst., Cleveland, OH.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF THE CONSTRUCTION, FUNCTION, AND MAINTENANCE OF DIESEL ENGINE CRANKSHAFTS, CAMSHAFTS, AND ASSOCIATED BEARINGS. TOPICS ARE SHAFTS AND BEARINGS, CAMSHAFTS, BEARINGS AND THEIR MAINTENANCE, AND DETECTING FAILURE. THE MODULE CONSISTS OF A SELF-INSTRUCTIONAL BRANCH PROGRAMED…

Exploring novel key regulators in breast cancer network.

PubMed

Ali, Shahnawaz; Malik, Md Zubbair; Singh, Soibam Shyamchand; Chirom, Keilash; Ishrat, Romana; Singh, R K Brojen

2018-01-01

The breast cancer network constructed from 70 experimentally verified genes is found to follow hierarchical scale free nature with heterogeneous modular organization and diverge leading hubs. The topological parameters (degree distributions, clustering co-efficient, connectivity and centralities) of this network obey fractal rules indicating absence of centrality lethality rule, and efficient communication among the components. From the network theoretical approach, we identified few key regulators out of large number of leading hubs, which are deeply rooted from top to down of the network, serve as backbone of the network, and possible target genes. However, p53, which is one of these key regulators, is found to be in low rank and keep itself at low profile but directly cross-talks with important genes BRCA2 and BRCA3. The popularity of these hubs gets changed in unpredictable way at various levels of organization thus showing disassortive nature. The local community paradigm approach in this network shows strong correlation of nodes in majority of modules/sub-modules (fast communication among nodes) and weak correlation of nodes only in few modules/sub-modules (slow communication among nodes) at various levels of network organization.

Optical interconnect for large-scale systems

NASA Astrophysics Data System (ADS)

Dress, William

2013-02-01

This paper presents a switchless, optical interconnect module that serves as a node in a network of identical distribution modules for large-scale systems. Thousands to millions of hosts or endpoints may be interconnected by a network of such modules, avoiding the need for multi-level switches. Several common network topologies are reviewed and their scaling properties assessed. The concept of message-flow routing is discussed in conjunction with the unique properties enabled by the optical distribution module where it is shown how top-down software control (global routing tables, spanning-tree algorithms) may be avoided.

A reverse engineering algorithm for neural networks, applied to the subthalamopallidal network of basal ganglia.

PubMed

Floares, Alexandru George

2008-01-01

Modeling neural networks with ordinary differential equations systems is a sensible approach, but also very difficult. This paper describes a new algorithm based on linear genetic programming which can be used to reverse engineer neural networks. The RODES algorithm automatically discovers the structure of the network, including neural connections, their signs and strengths, estimates its parameters, and can even be used to identify the biophysical mechanisms involved. The algorithm is tested on simulated time series data, generated using a realistic model of the subthalamopallidal network of basal ganglia. The resulting ODE system is highly accurate, and results are obtained in a matter of minutes. This is because the problem of reverse engineering a system of coupled differential equations is reduced to one of reverse engineering individual algebraic equations. The algorithm allows the incorporation of common domain knowledge to restrict the solution space. To our knowledge, this is the first time a realistic reverse engineering algorithm based on linear genetic programming has been applied to neural networks.

NASA/DOD Aerospace Knowledge Diffusion Research Project. Report 35: The use of computer networks in aerospace engineering

NASA Technical Reports Server (NTRS)

Bishop, Ann P.; Pinelli, Thomas E.

1995-01-01

This research used survey research to explore and describe the use of computer networks by aerospace engineers. The study population included 2000 randomly selected U.S. aerospace engineers and scientists who subscribed to Aerospace Engineering. A total of 950 usable questionnaires were received by the cutoff date of July 1994. Study results contribute to existing knowledge about both computer network use and the nature of engineering work and communication. We found that 74 percent of mail survey respondents personally used computer networks. Electronic mail, file transfer, and remote login were the most widely used applications. Networks were used less often than face-to-face interactions in performing work tasks, but about equally with reading and telephone conversations, and more often than mail or fax. Network use was associated with a range of technical, organizational, and personal factors: lack of compatibility across systems, cost, inadequate access and training, and unwillingness to embrace new technologies and modes of work appear to discourage network use. The greatest positive impacts from networking appear to be increases in the amount of accurate and timely information available, better exchange of ideas across organizational boundaries, and enhanced work flexibility, efficiency, and quality. Involvement with classified or proprietary data and type of organizational structure did not distinguish network users from nonusers. The findings can be used by people involved in the design and implementation of networks in engineering communities to inform the development of more effective networking systems, services, and policies.

Modular Aero-Propulsion System Simulation

NASA Technical Reports Server (NTRS)

Parker, Khary I.; Guo, Ten-Huei

2006-01-01

The Modular Aero-Propulsion System Simulation (MAPSS) is a graphical simulation environment designed for the development of advanced control algorithms and rapid testing of these algorithms on a generic computational model of a turbofan engine and its control system. MAPSS is a nonlinear, non-real-time simulation comprising a Component Level Model (CLM) module and a Controller-and-Actuator Dynamics (CAD) module. The CLM module simulates the dynamics of engine components at a sampling rate of 2,500 Hz. The controller submodule of the CAD module simulates a digital controller, which has a typical update rate of 50 Hz. The sampling rate for the actuators in the CAD module is the same as that of the CLM. MAPSS provides a graphical user interface that affords easy access to engine-operation, engine-health, and control parameters; is used to enter such input model parameters as power lever angle (PLA), Mach number, and altitude; and can be used to change controller and engine parameters. Output variables are selectable by the user. Output data as well as any changes to constants and other parameters can be saved and reloaded into the GUI later.

Re-modulated technology of WDM-PON employing different DQPSK downstream signals

NASA Astrophysics Data System (ADS)

Gao, Chao; Xin, Xiang-jun; Yu, Chong-xiu

2012-11-01

This paper proposes a kind of modulation architecture for wavelength-division-multiplexing passive optical network (WDMPON) employing optical differential quadrature phase shift keying (DQPSK) downstream signals and two different modulation formats of re-modulated upstream signals. At the optical line terminal (OLT), 10 Gbit/s signal is modulated with DQPSK. At the optical network unit (ONU), part of the downstream signal is re-modulated with on-off keying (OOK) or inverse-return-to-zero (IRZ). Simulation results show the impact on the system employing NRZ, RZ and carrier-suppressed return-to-zero (CSRZ). The analyses also reflect that the architecture can restrain chromatic dispersion and channel crosstalk, which makes it the best architecture of access network in the future.

INfORM: Inference of NetwOrk Response Modules.

PubMed

Marwah, Veer Singh; Kinaret, Pia Anneli Sofia; Serra, Angela; Scala, Giovanni; Lauerma, Antti; Fortino, Vittorio; Greco, Dario

2018-06-15

Detecting and interpreting responsive modules from gene expression data by using network-based approaches is a common but laborious task. It often requires the application of several computational methods implemented in different software packages, forcing biologists to compile complex analytical pipelines. Here we introduce INfORM (Inference of NetwOrk Response Modules), an R shiny application that enables non-expert users to detect, evaluate and select gene modules with high statistical and biological significance. INfORM is a comprehensive tool for the identification of biologically meaningful response modules from consensus gene networks inferred by using multiple algorithms. It is accessible through an intuitive graphical user interface allowing for a level of abstraction from the computational steps. INfORM is freely available for academic use at https://github.com/Greco-Lab/INfORM. Supplementary data are available at Bioinformatics online.

Neural Network-Based Sensor Validation for Turboshaft Engines

NASA Technical Reports Server (NTRS)

Moller, James C.; Litt, Jonathan S.; Guo, Ten-Huei

1998-01-01

Sensor failure detection, isolation, and accommodation using a neural network approach is described. An auto-associative neural network is configured to perform dimensionality reduction on the sensor measurement vector and provide estimated sensor values. The sensor validation scheme is applied in a simulation of the T700 turboshaft engine in closed loop operation. Performance is evaluated based on the ability to detect faults correctly and maintain stable and responsive engine operation. The set of sensor outputs used for engine control forms the network input vector. Analytical redundancy is verified by training networks of successively smaller bottleneck layer sizes. Training data generation and strategy are discussed. The engine maintained stable behavior in the presence of sensor hard failures. With proper selection of fault determination thresholds, stability was maintained in the presence of sensor soft failures.

Engineering Design Modules as Physics Teaching Tools

ERIC Educational Resources Information Center

Oliver, Douglas L.; Kane, Jackie

2011-01-01

Pre-engineering is increasingly being taught as a high school subject. This development presents challenges as well as opportunities for the physics education community. If pre-engineering is taught as a separate class, it may divert resources and students from traditional physics classes. However, design modules can be used as physics teaching…

Noncoherent Physical-Layer Network Coding with FSK Modulation: Relay Receiver Design Issues

DTIC Science & Technology

2011-03-01

222 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 59, NO. 9, SEPTEMBER 2011 2595 Noncoherent Physical-Layer Network Coding with FSK Modulation: Relay... noncoherent reception, channel estima- tion. I. INTRODUCTION IN the two-way relay channel (TWRC), a pair of sourceterminals exchange information...2011 4. TITLE AND SUBTITLE Noncoherent Physical-Layer Network Coding with FSK Modulation:Relay Receiver Design Issues 5a. CONTRACT NUMBER 5b

WGCNA: an R package for weighted correlation network analysis.

PubMed

Langfelder, Peter; Horvath, Steve

2008-12-29

Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.

Slotline fed microstrip antenna array modules

NASA Technical Reports Server (NTRS)

Lo, Y. T.; Oberhart, M. L.; Brenneman, J. S.; Aoyagi, P.; Moore, J.; Lee, R. Q. H.

1988-01-01

A feed network comprised of a combination of coplanar waveguide and slot transmission line is described for use in an array module of four microstrip elements. Examples of the module incorporating such networks are presented as well as experimentally obtained impedance and radiation characteristics.

ARTIST CONCEPT - APOLLO XI - LUNAR SURFACE

NASA Image and Video Library

1969-07-11

S69-39011 (July 1969) --- TRW Incorporated's artist concept depicting the Apollo 11 Lunar Module (LM) descending to the surface of the moon. Inside the LM will be astronauts Neil A. Armstrong, commander, and Edwin E. Aldrin Jr., lunar module pilot. Astronaut Michael Collins, command module pilot, will remain with the Command and Service Modules (CSM) in lunar orbit. TRW's LM descent engine will brake Apollo 11's descent to the lunar surface. The throttle-able rocket engine will be fired continuously the last 10 miles of the journey to the moon, slowing the LM to a speed of two miles per hour at touchdown. TRW Incorporated designed and built the unique engine at Redondo Beach, California under subcontract to the Grumman Aircraft Engineering Corporation, Bethpage, New York, the LM prime contractor.

Altered brain network modules induce helplessness in major depressive disorder.

PubMed

Peng, Daihui; Shi, Feng; Shen, Ting; Peng, Ziwen; Zhang, Chen; Liu, Xiaohua; Qiu, Meihui; Liu, Jun; Jiang, Kaida; Fang, Yiru; Shen, Dinggang

2014-10-01

The abnormal brain functional connectivity (FC) has been assumed to be a pathophysiological aspect of major depressive disorder (MDD). However, it is poorly understood, regarding the underlying patterns of global FC network and their relationships with the clinical characteristics of MDD. Resting-state functional magnetic resonance imaging data were acquired from 16 first episode, medication-naïve MDD patients and 16 healthy control subjects. The global FC network was constructed using 90 brain regions. The global topological patterns, e.g., small-worldness and modularity, and their relationships with depressive characteristics were investigated. Furthermore, the participant coefficient and module degree of MDD patients were measured to reflect the regional roles in module network, and the impairment of FC was examined by network based statistic. Small-world property was not altered in MDD. However, MDD patients exhibited 5 atypically reorganized modules compared to the controls. A positive relationship was also found among MDD patients between the intra-module I and helplessness factor evaluated via the Hamilton Depression Scale. Specifically, eight regions exhibited the abnormal participant coefficient or module degree, e.g., left superior orbital frontal cortex and right amygdala. The decreased FC was identified among the sub-network of 24 brain regions, e.g., frontal cortex, supplementary motor area, amygdala, thalamus, and hippocampus. The limited size of MDD samples precluded meaningful study of distinct clinical characteristics in relation to aberrant FC. The results revealed altered patterns of brain module network at the global level in MDD patients, which might contribute to the feelings of helplessness. Copyright © 2014 Elsevier B.V. All rights reserved.

Altered brain network modules induce helplessness in major depressive disorder

PubMed Central

Peng, Daihui; Shi, Feng; Shen, Ting; Peng, Ziwen; Zhang, Chen; Liu, Xiaohua; Qiu, Meihui; Liu, Jun; Jiang, Kaida; Shen, Dinggang

2017-01-01

Objective The abnormal brain functional connectivity (FC) has been assumed to be a pathophysiological aspect of major depressive disorder (MDD). However, it is poorly understood, regarding the underlying patterns of global FC network and their relationships with the clinical characteristics of MDD. Methods Resting-state functional magnetic resonance imaging data were acquired from 16 first episode, medication-naïve MDD patients and 16 healthy control subjects. The global FC network was constructed using 90 brain regions. The global topological patterns, e.g., small-worldness and modularity, and their relationships with depressive characteristics were investigated. Furthermore, the participant coefficient and module degree of MDD patients were measured to reflect the regional roles in module network, and the impairment of FC was examined by network based statistic. Results Small-world property was not altered in MDD. However, MDD patients exhibited 5 atypically reorganized modules compared to the controls. A positive relationship was also found among MDD patients between the intra-module I and helplessness factor evaluated via the Hamilton Depression Scale. Specifically, eight regions exhibited the abnormal participant coefficient or module degree, e.g., left superior orbital frontal cortex and right amygdala. The decreased FC was identified among the sub-network of 24 brain regions, e.g., frontal cortex, supplementary motor area, amygdala, thalamus, and hippocampus. Limitation The limited size of MDD samples precluded meaningful study of distinct clinical characteristics in relation to aberrant FC. Conclusions The results revealed altered patterns of brain module network at the global level in MDD patients, which might contribute to the feelings of helplessness. PMID:25033474

Geometric control of capillary architecture via cell-matrix mechanical interactions.

PubMed

Sun, Jian; Jamilpour, Nima; Wang, Fei-Yue; Wong, Pak Kin

2014-03-01

Capillary morphogenesis is a multistage, multicellular activity that plays a pivotal role in various developmental and pathological situations. In-depth understanding of the regulatory mechanism along with the capability of controlling the morphogenic process will have direct implications on tissue engineering and therapeutic angiogenesis. Extensive research has been devoted to elucidate the biochemical factors that regulate capillary morphogenesis. The roles of geometric confinement and cell-matrix mechanical interactions on the capillary architecture, nevertheless, remain largely unknown. Here, we show geometric control of endothelial network topology by creating physical confinements with microfabricated fences and wells. Decreasing the thickness of the matrix also results in comparable modulation of the network architecture, supporting the boundary effect is mediated mechanically. The regulatory role of cell-matrix mechanical interaction on the network topology is further supported by alternating the matrix stiffness by a cell-inert PEG-dextran hydrogel. Furthermore, reducing the cell traction force with a Rho-associated protein kinase inhibitor diminishes the boundary effect. Computational biomechanical analysis delineates the relationship between geometric confinement and cell-matrix mechanical interaction. Collectively, these results reveal a mechanoregulation scheme of endothelial cells to regulate the capillary network architecture via cell-matrix mechanical interactions. Copyright © 2014 Elsevier Ltd. All rights reserved.

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT XXVII, I--CATERPILLAR STARTING (PONEY) ENGINE (PART I), II--LEARNING ABOUT BRAKES (PART II).

ERIC Educational Resources Information Center

Minnesota State Dept. of Education, St. Paul. Div. of Vocational and Technical Education.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF THE CONSTRUCTION AND OPERATION OF DIESEL ENGINE STARTING ENGINES AND BRAKE SYSTEMS USED ON DIESEL POWERED VEHICLES. TOPICS ARE (1) GENERAL DESCRIPTION, (2) OPERATION, (3) COMBUSTION SPACE AND VALVE ARRANGEMENT (STARTING ENGINES), (4) TYPES OF BRAKES, AND (5) DOUBLE…

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT XVIII, I--UNDERSTAND ENGINE GEARS AND GEARING PRINCIPLES, II--MACK INTER-AXLE POWER DIVIDER.

ERIC Educational Resources Information Center

Minnesota State Dept. of Education, St. Paul. Div. of Vocational and Technical Education.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF DIESEL ENGINE GEARS AND GEARING PRINCIPLES AND THE OPERATING PRINCIPLES AND MAINTENANCE OF POWER DIVIDERS (GEAR BOXES) USED IN DIESEL ENGINE POWER TRANSMISSION. TOPICS ARE (1) THE PURPOSE OF THE ENGINE GEARS, (2) INSPECTING FOR GEAR FAILURES, (3) INSPECTING FOR SHAFT…

Plume Impingement Analysis for the European Service Module Propulsion System

NASA Technical Reports Server (NTRS)

Yim, John Tamin; Sibe, Fabien; Ierardo, Nicola

2014-01-01

Plume impingement analyses were performed for the European Service Module (ESM) propulsion system Orbital Maneuvering System engine (OMS-E), auxiliary engines, and reaction control system (RCS) engines. The heat flux from plume impingement on the solar arrays and other surfaces are evaluated. This information is used to provide inputs for the ESM thermal analyses and help determine the optimal configuration for the RCS engines.

Currently available medical engineering degrees in the UK. Part 1: Undergraduate degrees.

PubMed

Joyce, T

2009-05-01

This paper reviews mechanical-engineering-based medical engineering degrees which are currently provided at undergraduate level in the UK. At present there are 14 undergraduate degree programmes in medical engineering, offered by the University of Bath, University of Birmingham, University of Bradford, Cardiff University, University of Hull, Imperial College London, University of Leeds, University of Nottingham, University of Oxford, Queen Mary University of London, University of Sheffield, University of Southampton, University of Surrey, and Swansea University. All these undergraduate courses are delivered on a full-time basis, both 3 year BEng and 4 year MEng degrees. Half of the 14 degree courses share a core first 2 years with a mechanical engineering stream. The other seven programmes include medical engineering modules earlier in their degrees. Within the courses, a very wide range of medical-engineering-related modules are offered, although more common modules include biomaterials, biomechanics, and anatomy and physiology.

Development of a novel SCADA system for laboratory testing.

PubMed

Patel, M; Cole, G R; Pryor, T L; Wilmot, N A

2004-07-01

This document summarizes the supervisory control and data acquisition (SCADA) system that allows communication with, and controlling the output of, various I/O devices in the renewable energy systems and components test facility RESLab. This SCADA system differs from traditional SCADA systems in that it supports a continuously changing operating environment depending on the test to be performed. The SCADA System is based on the concept of having one Master I/O Server and multiple client computer systems. This paper describes the main features and advantages of this dynamic SCADA system, the connections of various field devices to the master I/O server, the device servers, and numerous software features used in the system. The system is based on the graphical programming language "LabVIEW" and its "Datalogging and Supervisory Control" (DSC) module. The DSC module supports a real-time database called the "tag engine," which performs the I/O operations with all field devices attached to the master I/O server and communications with the other tag engines running on the client computers connected via a local area network. Generic and detailed communication block diagrams illustrating the hierarchical structure of this SCADA system are presented. The flow diagram outlining a complete test performed using this system in one of its standard configurations is described.

Modules for in vitro metabolic engineering: Pathway assembly for bio-based production of value-added chemicals.

PubMed

Taniguchi, Hironori; Okano, Kenji; Honda, Kohsuke

2017-06-01

Bio-based chemical production has drawn attention regarding the realization of a sustainable society. In vitro metabolic engineering is one of the methods used for the bio-based production of value-added chemicals. This method involves the reconstitution of natural or artificial metabolic pathways by assembling purified/semi-purified enzymes in vitro . Enzymes from distinct sources can be combined to construct desired reaction cascades with fewer biological constraints in one vessel, enabling easier pathway design with high modularity. Multiple modules have been designed, built, tested, and improved by different groups for different purpose. In this review, we focus on these in vitro metabolic engineering modules, especially focusing on the carbon metabolism, and present an overview of input modules, output modules, and other modules related to cofactor management.

Virtual and flexible digital signal processing system based on software PnP and component works

NASA Astrophysics Data System (ADS)

He, Tao; Wu, Qinghua; Zhong, Fei; Li, Wei

2005-05-01

An idea about software PnP (Plug & Play) is put forward according to the hardware PnP. And base on this idea, a virtual flexible digital signal processing system (FVDSPS) is carried out. FVDSPS is composed of a main control center, many sub-function modules and other hardware I/O modules. Main control center sends out commands to sub-function modules, and manages running orders, parameters and results of sub-functions. The software kernel of FVDSPS is DSP (Digital Signal Processing) module, which communicates with the main control center through some protocols, accept commands or send requirements. The data sharing and exchanging between the main control center and the DSP modules are carried out and managed by the files system of the Windows Operation System through the effective communication. FVDSPS real orients objects, orients engineers and orients engineering problems. With FVDSPS, users can freely plug and play, and fast reconfigure a signal process system according to engineering problems without programming. What you see is what you get. Thus, an engineer can orient engineering problems directly, pay more attention to engineering problems, and promote the flexibility, reliability and veracity of testing system. Because FVDSPS orients TCP/IP protocol, through Internet, testing engineers, technology experts can be connected freely without space. Engineering problems can be resolved fast and effectively. FVDSPS can be used in many fields such as instruments and meter, fault diagnosis, device maintenance and quality control.

Distributed Finite Element Analysis Using a Transputer Network

NASA Technical Reports Server (NTRS)

Watson, James; Favenesi, James; Danial, Albert; Tombrello, Joseph; Yang, Dabby; Reynolds, Brian; Turrentine, Ronald; Shephard, Mark; Baehmann, Peggy

1989-01-01

The principal objective of this research effort was to demonstrate the extraordinarily cost effective acceleration of finite element structural analysis problems using a transputer-based parallel processing network. This objective was accomplished in the form of a commercially viable parallel processing workstation. The workstation is a desktop size, low-maintenance computing unit capable of supercomputer performance yet costs two orders of magnitude less. To achieve the principal research objective, a transputer based structural analysis workstation termed XPFEM was implemented with linear static structural analysis capabilities resembling commercially available NASTRAN. Finite element model files, generated using the on-line preprocessing module or external preprocessing packages, are downloaded to a network of 32 transputers for accelerated solution. The system currently executes at about one third Cray X-MP24 speed but additional acceleration appears likely. For the NASA selected demonstration problem of a Space Shuttle main engine turbine blade model with about 1500 nodes and 4500 independent degrees of freedom, the Cray X-MP24 required 23.9 seconds to obtain a solution while the transputer network, operated from an IBM PC-AT compatible host computer, required 71.7 seconds. Consequently, the $80,000 transputer network demonstrated a cost-performance ratio about 60 times better than the $15,000,000 Cray X-MP24 system.

Kinetic modeling of plant metabolism and its predictive power: peppermint essential oil biosynthesis as an example.

PubMed

Lange, Bernd Markus; Rios-Estepa, Rigoberto

2014-01-01

The integration of mathematical modeling with analytical experimentation in an iterative fashion is a powerful approach to advance our understanding of the architecture and regulation of metabolic networks. Ultimately, such knowledge is highly valuable to support efforts aimed at modulating flux through target pathways by molecular breeding and/or metabolic engineering. In this article we describe a kinetic mathematical model of peppermint essential oil biosynthesis, a pathway that has been studied extensively for more than two decades. Modeling assumptions and approximations are described in detail. We provide step-by-step instructions on how to run simulations of dynamic changes in pathway metabolites concentrations.

Reverse Engineering Validation using a Benchmark Synthetic Gene Circuit in Human Cells

PubMed Central

Kang, Taek; White, Jacob T.; Xie, Zhen; Benenson, Yaakov; Sontag, Eduardo; Bleris, Leonidas

2013-01-01

Multi-component biological networks are often understood incompletely, in large part due to the lack of reliable and robust methodologies for network reverse engineering and characterization. As a consequence, developing automated and rigorously validated methodologies for unraveling the complexity of biomolecular networks in human cells remains a central challenge to life scientists and engineers. Today, when it comes to experimental and analytical requirements, there exists a great deal of diversity in reverse engineering methods, which renders the independent validation and comparison of their predictive capabilities difficult. In this work we introduce an experimental platform customized for the development and verification of reverse engineering and pathway characterization algorithms in mammalian cells. Specifically, we stably integrate a synthetic gene network in human kidney cells and use it as a benchmark for validating reverse engineering methodologies. The network, which is orthogonal to endogenous cellular signaling, contains a small set of regulatory interactions that can be used to quantify the reconstruction performance. By performing successive perturbations to each modular component of the network and comparing protein and RNA measurements, we study the conditions under which we can reliably reconstruct the causal relationships of the integrated synthetic network. PMID:23654266

Reverse engineering validation using a benchmark synthetic gene circuit in human cells.

PubMed

Kang, Taek; White, Jacob T; Xie, Zhen; Benenson, Yaakov; Sontag, Eduardo; Bleris, Leonidas

2013-05-17

Multicomponent biological networks are often understood incompletely, in large part due to the lack of reliable and robust methodologies for network reverse engineering and characterization. As a consequence, developing automated and rigorously validated methodologies for unraveling the complexity of biomolecular networks in human cells remains a central challenge to life scientists and engineers. Today, when it comes to experimental and analytical requirements, there exists a great deal of diversity in reverse engineering methods, which renders the independent validation and comparison of their predictive capabilities difficult. In this work we introduce an experimental platform customized for the development and verification of reverse engineering and pathway characterization algorithms in mammalian cells. Specifically, we stably integrate a synthetic gene network in human kidney cells and use it as a benchmark for validating reverse engineering methodologies. The network, which is orthogonal to endogenous cellular signaling, contains a small set of regulatory interactions that can be used to quantify the reconstruction performance. By performing successive perturbations to each modular component of the network and comparing protein and RNA measurements, we study the conditions under which we can reliably reconstruct the causal relationships of the integrated synthetic network.

Puzzles in modern biology. V. Why are genomes overwired?

PubMed

Frank, Steven A

2017-01-01

Many factors affect eukaryotic gene expression. Transcription factors, histone codes, DNA folding, and noncoding RNA modulate expression. Those factors interact in large, broadly connected regulatory control networks. An engineer following classical principles of control theory would design a simpler regulatory network. Why are genomes overwired? Neutrality or enhanced robustness may lead to the accumulation of additional factors that complicate network architecture. Dynamics progresses like a ratchet. New factors get added. Genomes adapt to the additional complexity. The newly added factors can no longer be removed without significant loss of fitness. Alternatively, highly wired genomes may be more malleable. In large networks, most genomic variants tend to have a relatively small effect on gene expression and trait values. Many small effects lead to a smooth gradient, in which traits may change steadily with respect to underlying regulatory changes. A smooth gradient may provide a continuous path from a starting point up to the highest peak of performance. A potential path of increasing performance promotes adaptability and learning. Genomes gain by the inductive process of natural selection, a trial and error learning algorithm that discovers general solutions for adapting to environmental challenge. Similarly, deeply and densely connected computational networks gain by various inductive trial and error learning procedures, in which the networks learn to reduce the errors in sequential trials. Overwiring alters the geometry of induction by smoothing the gradient along the inductive pathways of improving performance. Those overwiring benefits for induction apply to both natural biological networks and artificial deep learning networks.

Earthquake Monitoring: SeisComp3 at the Swiss National Seismic Network

NASA Astrophysics Data System (ADS)

Clinton, J. F.; Diehl, T.; Cauzzi, C.; Kaestli, P.

2011-12-01

The Swiss Seismological Service (SED) has an ongoing responsibility to improve the seismicity monitoring capability for Switzerland. This is a crucial issue for a country with low background seismicity but where a large M6+ earthquake is expected in the next decades. With over 30 stations with spacing of ~25km, the SED operates one of the densest broadband networks in the world, which is complimented by ~ 50 realtime strong motion stations. The strong motion network is expected to grow with an additional ~80 stations over the next few years. Furthermore, the backbone of the network is complemented by broadband data from surrounding countries and temporary sub-networks for local monitoring of microseismicity (e.g. at geothermal sites). The variety of seismic monitoring responsibilities as well as the anticipated densifications of our network demands highly flexible processing software. We are transitioning all software to the SeisComP3 (SC3) framework. SC3 is a fully featured automated real-time earthquake monitoring software developed by GeoForschungZentrum Potsdam in collaboration with commercial partner, gempa GmbH. It is in its core open source, and becoming a community standard software for earthquake detection and waveform processing for regional and global networks across the globe. SC3 was originally developed for regional and global rapid monitoring of potentially tsunamagenic earthquakes. In order to fulfill the requirements of a local network recording moderate seismicity, SED has tuned configurations and added several modules. In this contribution, we present our SC3 implementation strategy, focusing on the detection and identification of seismicity on different scales. We operate several parallel processing "pipelines" to detect and locate local, regional and global seismicity. Additional pipelines with lower detection thresholds can be defined to monitor seismicity within dense subnets of the network. To be consistent with existing processing procedures, the nonlinloc algorithm was implemented for manual and automatic locations using 1D and 3D velocity models; plugins for improved automatic phase picking and Ml computation were developed; and the graphical user interface for manual review was extended (including pick uncertainty definition; first motion focal mechanisms; interactive review of station magnitude waveforms; full inclusion of strong motion data). SC3 locations are fully compatible with those derived from the existing in-house processing tools and are stored in a database derived from the QuakeML data model. The database is shared with the SED alerting software, which merges origins from both SC3 and external sources in realtime and handles the alerting procedure. With the monitoring software being transitioned to SeisComp3, acquisition, archival and dissemination of SED waveform data now conforms to the seedlink and ArcLink protocols and continuous archives can be accessed via SED and all EIDA (European Integrated Data Archives) web-sites. Further, a SC3 module for waveform parameterisation has been developed, allowing rapid computation of peak values of ground motion and other engineering parameters within minutes of a new event. An output of this module is USGS ShakeMap XML. n minutes of a new event. An output of this module is USGS ShakeMap XML.

Engineering evaluation of a sodium hydroxide thermal energy storage module

NASA Technical Reports Server (NTRS)

Perdue, D. G.; Gordon, L. H.

1980-01-01

An engineering evaluation of thermal energy storage prototypes was performed in order to assess the development status of latent heat storage media. The testing and the evaluation of a prototype sodium hydroxide module is described. This module stored off-peak electrical energy as heat for later conversion to domestic hot water needs.

Automobile Engine: Basic Ignition Timing. Fordson Bilingual Demonstration Project.

ERIC Educational Resources Information Center

Vick, James E.

These two vocational instructional modules on basic automobile ignition timing and on engine operation, four-stroke cycle, are two of eight such modules designed to assist recently arrived Arab students, limited in English proficiency (LEP), in critical instructional areas in a comprehensive high school. Goal stated for this module is for the…

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT VIII. ENGINE COMPONENTS--PART I.

ERIC Educational Resources Information Center

Human Engineering Inst., Cleveland, OH.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF THE CONSTRUCTION AND MAINTENANCE OF DIESEL ENGINE CYLINDER HEADS AND CYLINDER ASSEMBLIES. TOPICS ARE CYLINDER ASSEMBLY (LINERS), CYLINDER HEADS, VALVES AND VALVE MECHANISMS, AND PISTON AND PISTON RINGS. THE MODULE CONSISTS OF A SELF-INSTRUCTIONAL BRANCH PROGRAMED TRAINING…

AUTOMOTIVE DIESEL MAINTENANCE, UNIT V, MAINTAINING THE LUBRICATION SYSTEM--DETROIT DIESEL ENGINE.

ERIC Educational Resources Information Center

Human Engineering Inst., Cleveland, OH.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF THE OPERATION AND MAINTENANCE OF THE DIESEL ENGINE LUBRICATION SYSTEM. TOPICS ARE LUBE OILS USED, MAINTENANCE OF THE LUBRICATION SYSTEM, AND CRANKCASE VENTILATION COMPONENTS. THE MODULE CONSISTS OF A SELF-INSTRUCTIONAL BRANCH PROGRAMED TRAINING FILM "BASIC ENGINE…

A Photovoltaics Module for Incoming Science, Technology, Engineering and Mathematics Undergraduates

ERIC Educational Resources Information Center

Dark, Marta L.

2011-01-01

Photovoltaic-cell-based projects have been used to train eight incoming undergraduate women who were part of a residential summer programme at a women's college. A module on renewable energy and photovoltaic cells was developed in the physics department. The module's objectives were to introduce women in science, technology, engineering and…

Engine Performance (Section B: Fuel and Exhaust Systems). Auto Mechanics Curriculum Guide. Module 3. Instructor's Guide.

ERIC Educational Resources Information Center

Rains, Larry

This module is the third of nine modules in the competency-based Missouri Auto Mechanics Curriculum Guide. Six units cover: fuel supply systems; carburetion; carburetor service; gasoline engine electronic fuel injection; diesel fuel injection; and exhaust systems and turbochargers. Introductory materials include a competency profile and…

Dual regulation of gene expression mediated by extended MAPK activation and salicylic acid contributes to robust innate immunity in Arabidopsis thaliana.

PubMed

Tsuda, Kenichi; Mine, Akira; Bethke, Gerit; Igarashi, Daisuke; Botanga, Christopher J; Tsuda, Yayoi; Glazebrook, Jane; Sato, Masanao; Katagiri, Fumiaki

2013-01-01

Network robustness is a crucial property of the plant immune signaling network because pathogens are under a strong selection pressure to perturb plant network components to dampen plant immune responses. Nevertheless, modulation of network robustness is an area of network biology that has rarely been explored. While two modes of plant immunity, Effector-Triggered Immunity (ETI) and Pattern-Triggered Immunity (PTI), extensively share signaling machinery, the network output is much more robust against perturbations during ETI than PTI, suggesting modulation of network robustness. Here, we report a molecular mechanism underlying the modulation of the network robustness in Arabidopsis thaliana. The salicylic acid (SA) signaling sector regulates a major portion of the plant immune response and is important in immunity against biotrophic and hemibiotrophic pathogens. In Arabidopsis, SA signaling was required for the proper regulation of the vast majority of SA-responsive genes during PTI. However, during ETI, regulation of most SA-responsive genes, including the canonical SA marker gene PR1, could be controlled by SA-independent mechanisms as well as by SA. The activation of the two immune-related MAPKs, MPK3 and MPK6, persisted for several hours during ETI but less than one hour during PTI. Sustained MAPK activation was sufficient to confer SA-independent regulation of most SA-responsive genes. Furthermore, the MPK3 and SA signaling sectors were compensatory to each other for inhibition of bacterial growth as well as for PR1 expression during ETI. These results indicate that the duration of the MAPK activation is a critical determinant for modulation of robustness of the immune signaling network. Our findings with the plant immune signaling network imply that the robustness level of a biological network can be modulated by the activities of network components.

WGCNA: an R package for weighted correlation network analysis

PubMed Central

Langfelder, Peter; Horvath, Steve

2008-01-01

Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at . PMID:19114008

Active module identification in intracellular networks using a memetic algorithm with a new binary decoding scheme.

PubMed

Li, Dong; Pan, Zhisong; Hu, Guyu; Zhu, Zexuan; He, Shan

2017-03-14

Active modules are connected regions in biological network which show significant changes in expression over particular conditions. The identification of such modules is important since it may reveal the regulatory and signaling mechanisms that associate with a given cellular response. In this paper, we propose a novel active module identification algorithm based on a memetic algorithm. We propose a novel encoding/decoding scheme to ensure the connectedness of the identified active modules. Based on the scheme, we also design and incorporate a local search operator into the memetic algorithm to improve its performance. The effectiveness of proposed algorithm is validated on both small and large protein interaction networks.

Modular sensor network node

DOEpatents

Davis, Jesse Harper Zehring [Berkeley, CA; Stark, Jr., Douglas Paul; Kershaw, Christopher Patrick [Hayward, CA; Kyker, Ronald Dean [Livermore, CA

2008-06-10

A distributed wireless sensor network node is disclosed. The wireless sensor network node includes a plurality of sensor modules coupled to a system bus and configured to sense a parameter. The parameter may be an object, an event or any other parameter. The node collects data representative of the parameter. The node also includes a communication module coupled to the system bus and configured to allow the node to communicate with other nodes. The node also includes a processing module coupled to the system bus and adapted to receive the data from the sensor module and operable to analyze the data. The node also includes a power module connected to the system bus and operable to generate a regulated voltage.

Multiple supervised residual network for osteosarcoma segmentation in CT images.

PubMed

Zhang, Rui; Huang, Lin; Xia, Wei; Zhang, Bo; Qiu, Bensheng; Gao, Xin

2018-01-01

Automatic and accurate segmentation of osteosarcoma region in CT images can help doctor make a reasonable treatment plan, thus improving cure rate. In this paper, a multiple supervised residual network (MSRN) was proposed for osteosarcoma image segmentation. Three supervised side output modules were added to the residual network. The shallow side output module could extract image shape features, such as edge features and texture features. The deep side output module could extract semantic features. The side output module could compute the loss value between output probability map and ground truth and back-propagate the loss information. Then, the parameters of residual network could be modified by gradient descent method. This could guide the multi-scale feature learning of the network. The final segmentation results were obtained by fusing the results output by the three side output modules. A total of 1900 CT images from 15 osteosarcoma patients were used to train the network and a total of 405 CT images from another 8 osteosarcoma patients were used to test the network. Results indicated that MSRN enabled a dice similarity coefficient (DSC) of 89.22%, a sensitivity of 88.74% and a F1-measure of 0.9305, which were larger than those obtained by fully convolutional network (FCN) and U-net. Thus, MSRN for osteosarcoma segmentation could give more accurate results than FCN and U-Net. Copyright © 2018 Elsevier Ltd. All rights reserved.

Performance deterioration based on existing (historical) data; JT9D jet engine diagnostics program

NASA Technical Reports Server (NTRS)

Sallee, G. P.

1978-01-01

The results of the collection and analysis of historical data pertaining to the deterioration of JT9D engine performance are presented. The results of analyses of prerepair and postrepair engine test stand performance data from a number of airlines to establish the individual as well as average losses in engine performance with respect to service use are included. Analysis of the changes in mechanical condition of parts, obtained by inspection of used gas-path parts of varying age, allowed preliminary assessments of component performance deterioration levels and identification of the causitive factors. These component performance estimates, refined by data from special engine back-to-back testing related to module performance restoration, permitted the development of preliminary models of engine component/module performance deterioration with respect to usage. The preliminary assessment of the causes of module performance deterioration and the trends with usage are explained, along with the role each module plays in overall engine performance deterioration. Preliminary recommendations with respect to operating and maintenance practices which could be adopted to control the level of performance deterioration are presented. The needs for additional component sensitivity testing as well as outstanding issues are discussed.

Effects of Web-Based Interactive Modules on Engineering Students' Learning Motivations

ERIC Educational Resources Information Center

Bai, Haiyan; Aman, Amjad; Xu, Yunjun; Orlovskaya, Nina; Zhou, Mingming

2016-01-01

The purpose of this study is to assess the impact of a newly developed modules, Interactive Web-Based Visualization Tools for Gluing Undergraduate Fuel Cell Systems Courses system (IGLU), on learning motivations of engineering students using two samples (n[subscript 1] = 144 and n[subscript 2] = 135) from senior engineering classes. The…

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT VI, MAINTAINING MECHANICAL GOVERNORS--DETROIT DIESEL ENGINES.

ERIC Educational Resources Information Center

Human Engineering Inst., Cleveland, OH.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF THE OPERATION AND MAINTENANCE OF MECHANICAL GOVERNORS USED ON DIESEL ENGINES. TOPICS ARE (1) TYPES OF GOVERNORS AND ENGINE LOCATION, (2) GOVERNOR APPLICATIONS, (3) LIMITING SPEED MECHANICAL GOVERNOR, (4) VARIABLE SPEED MECHANICAL GOVERNOR, AND (5) CONSTANT SPEED…

Disease networks. Uncovering disease-disease relationships through the incomplete interactome.

PubMed

Menche, Jörg; Sharma, Amitabh; Kitsak, Maksim; Ghiassian, Susan Dina; Vidal, Marc; Loscalzo, Joseph; Barabási, Albert-László

2015-02-20

According to the disease module hypothesis, the cellular components associated with a disease segregate in the same neighborhood of the human interactome, the map of biologically relevant molecular interactions. Yet, given the incompleteness of the interactome and the limited knowledge of disease-associated genes, it is not obvious if the available data have sufficient coverage to map out modules associated with each disease. Here we derive mathematical conditions for the identifiability of disease modules and show that the network-based location of each disease module determines its pathobiological relationship to other diseases. For example, diseases with overlapping network modules show significant coexpression patterns, symptom similarity, and comorbidity, whereas diseases residing in separated network neighborhoods are phenotypically distinct. These tools represent an interactome-based platform to predict molecular commonalities between phenotypically related diseases, even if they do not share primary disease genes. Copyright © 2015, American Association for the Advancement of Science.

Design and development of the Waukesha Custom Engine Control Air/Fuel Module

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moss, D.W.

1996-12-31

The Waukesha Custom Engine Control Air/Fuel Module (AFM) is designed to control the air-fuel ratio for all Waukesha carbureted, gaseous fueled, industrial engine. The AFM is programmed with a personal computer to run in one of four control modes: catalyst, best power, best economy, or lean-burn. One system can control naturally aspirated, turbocharged, in-line or vee engines. The basic system consists of an oxygen sensing system, intake manifold pressure transducer, electronic control module, actuator and exhaust thermocouple. The system permits correct operation of Waukesha engines in spite of changes in fuel pressure or temperature, engine load or speed, and fuelmore » composition. The system utilizes closed loop control and is centered about oxygen sensing technology. An innovative approach to applying oxygen sensors to industrial engines provides very good performance, greatly prolongs sensor life, and maintains sensor accuracy. Design considerations and operating results are given for application of the system to stationary, industrial engines operating on fuel gases of greatly varying composition.« less

Linear motif-mediated interactions have contributed to the evolution of modularity in complex protein interaction networks.

PubMed

Kim, Inhae; Lee, Heetak; Han, Seong Kyu; Kim, Sanguk

2014-10-01

The modular architecture of protein-protein interaction (PPI) networks is evident in diverse species with a wide range of complexity. However, the molecular components that lead to the evolution of modularity in PPI networks have not been clearly identified. Here, we show that weak domain-linear motif interactions (DLIs) are more likely to connect different biological modules than strong domain-domain interactions (DDIs). This molecular division of labor is essential for the evolution of modularity in the complex PPI networks of diverse eukaryotic species. In particular, DLIs may compensate for the reduction in module boundaries that originate from increased connections between different modules in complex PPI networks. In addition, we show that the identification of biological modules can be greatly improved by including molecular characteristics of protein interactions. Our findings suggest that transient interactions have played a unique role in shaping the architecture and modularity of biological networks over the course of evolution.

Network module detection: Affinity search technique with the multi-node topological overlap measure

PubMed Central

Li, Ai; Horvath, Steve

2009-01-01

Background Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. Findings We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Conclusion Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: PMID:19619323

Network module detection: Affinity search technique with the multi-node topological overlap measure.

PubMed

Li, Ai; Horvath, Steve

2009-07-20

Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/MTOM/

BinTree Seeking: A Novel Approach to Mine Both Bi-Sparse and Cohesive Modules in Protein Interaction Networks

PubMed Central

Shen, Hong-Bin

2011-01-01

Modern science of networks has brought significant advances to our understanding of complex systems biology. As a representative model of systems biology, Protein Interaction Networks (PINs) are characterized by a remarkable modular structures, reflecting functional associations between their components. Many methods were proposed to capture cohesive modules so that there is a higher density of edges within modules than those across them. Recent studies reveal that cohesively interacting modules of proteins is not a universal organizing principle in PINs, which has opened up new avenues for revisiting functional modules in PINs. In this paper, functional clusters in PINs are found to be able to form unorthodox structures defined as bi-sparse module. In contrast to the traditional cohesive module, the nodes in the bi-sparse module are sparsely connected internally and densely connected with other bi-sparse or cohesive modules. We present a novel protocol called the BinTree Seeking (BTS) for mining both bi-sparse and cohesive modules in PINs based on Edge Density of Module (EDM) and matrix theory. BTS detects modules by depicting links and nodes rather than nodes alone and its derivation procedure is totally performed on adjacency matrix of networks. The number of modules in a PIN can be automatically determined in the proposed BTS approach. BTS is tested on three real PINs and the results demonstrate that functional modules in PINs are not dominantly cohesive but can be sparse. BTS software and the supporting information are available at: www.csbio.sjtu.edu.cn/bioinf/BTS/. PMID:22140454

Identification of Unstable Network Modules Reveals Disease Modules Associated with the Progression of Alzheimer’s Disease

PubMed Central

Kikuchi, Masataka; Ogishima, Soichi; Miyamoto, Tadashi; Miyashita, Akinori; Kuwano, Ryozo; Nakaya, Jun; Tanaka, Hiroshi

2013-01-01

Alzheimer’s disease (AD), the most common cause of dementia, is associated with aging, and it leads to neuron death. Deposits of amyloid β and aberrantly phosphorylated tau protein are known as pathological hallmarks of AD, but the underlying mechanisms have not yet been revealed. A high-throughput gene expression analysis previously showed that differentially expressed genes accompanying the progression of AD were more down-regulated than up-regulated in the later stages of AD. This suggested that the molecular networks and their constituent modules collapsed along with AD progression. In this study, by using gene expression profiles and protein interaction networks (PINs), we identified the PINs expressed in three brain regions: the entorhinal cortex (EC), hippocampus (HIP) and superior frontal gyrus (SFG). Dividing the expressed PINs into modules, we examined the stability of the modules with AD progression and with normal aging. We found that in the AD modules, the constituent proteins, interactions and cellular functions were not maintained between consecutive stages through all brain regions. Interestingly, the modules were collapsed with AD progression, specifically in the EC region. By identifying the modules that were affected by AD pathology, we found the transcriptional regulation-associated modules that interact with the proteasome-associated module via UCHL5 hub protein, which is a deubiquitinating enzyme. Considering PINs as a system made of network modules, we found that the modules relevant to the transcriptional regulation are disrupted in the EC region, which affects the ubiquitin-proteasome system. PMID:24348898

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT XVII, I--MAINTAINING THE LUBRICATION SYSTEM--CUMMINS DIESEL ENGINE, II--UNIT INSTALLATION AND REMOVAL--DRIVE LINES.

ERIC Educational Resources Information Center

Minnesota State Dept. of Education, St. Paul. Div. of Vocational and Technical Education.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF THE DIESEL ENGINE LUBRICATION SYSTEM AND THE PROCEDURES FOR REMOVAL AND INSTALLATION OF THE DRIVE LINE USED IN DIESEL ENGINE POWER DISTRIBUTION. TOPICS ARE (1) PROLONGING ENGINE LIFE, (2) FUNCTIONS OF THE LUBRICATING SYSTEM, (3) TRACING THE LUBRICANT FLOW, (4) DETERMINING…

An Integrated Systems Biology Approach Identifies TRIM25 as a Key Determinant of Breast Cancer Metastasis.

PubMed

Walsh, Logan A; Alvarez, Mariano J; Sabio, Erich Y; Reyngold, Marsha; Makarov, Vladimir; Mukherjee, Suranjit; Lee, Ken-Wing; Desrichard, Alexis; Turcan, Şevin; Dalin, Martin G; Rajasekhar, Vinagolu K; Chen, Shuibing; Vahdat, Linda T; Califano, Andrea; Chan, Timothy A

2017-08-15

At the root of most fatal malignancies are aberrantly activated transcriptional networks that drive metastatic dissemination. Although individual metastasis-associated genes have been described, the complex regulatory networks presiding over the initiation and maintenance of metastatic tumors are still poorly understood. There is untapped value in identifying therapeutic targets that broadly govern coordinated transcriptional modules dictating metastatic progression. Here, we reverse engineered and interrogated a breast cancer-specific transcriptional interaction network (interactome) to define transcriptional control structures causally responsible for regulating genetic programs underlying breast cancer metastasis in individual patients. Our analyses confirmed established pro-metastatic transcription factors, and they uncovered TRIM25 as a key regulator of metastasis-related transcriptional programs. Further, in vivo analyses established TRIM25 as a potent regulator of metastatic disease and poor survival outcome. Our findings suggest that identifying and targeting keystone proteins, like TRIM25, can effectively collapse transcriptional hierarchies necessary for metastasis formation, thus representing an innovative cancer intervention strategy. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Innovative second-generation wavelets construction with recurrent neural networks for solar radiation forecasting.

PubMed

Capizzi, Giacomo; Napoli, Christian; Bonanno, Francesco

2012-11-01

Solar radiation prediction is an important challenge for the electrical engineer because it is used to estimate the power developed by commercial photovoltaic modules. This paper deals with the problem of solar radiation prediction based on observed meteorological data. A 2-day forecast is obtained by using novel wavelet recurrent neural networks (WRNNs). In fact, these WRNNS are used to exploit the correlation between solar radiation and timescale-related variations of wind speed, humidity, and temperature. The input to the selected WRNN is provided by timescale-related bands of wavelet coefficients obtained from meteorological time series. The experimental setup available at the University of Catania, Italy, provided this information. The novelty of this approach is that the proposed WRNN performs the prediction in the wavelet domain and, in addition, also performs the inverse wavelet transform, giving the predicted signal as output. The obtained simulation results show a very low root-mean-square error compared to the results of the solar radiation prediction approaches obtained by hybrid neural networks reported in the recent literature.

A nanobiosensor for dynamic single cell analysis during microvascular self-organization.

PubMed

Wang, S; Sun, J; Zhang, D D; Wong, P K

2016-10-14

The formation of microvascular networks plays essential roles in regenerative medicine and tissue engineering. Nevertheless, the self-organization mechanisms underlying the dynamic morphogenic process are poorly understood due to a paucity of effective tools for mapping the spatiotemporal dynamics of single cell behaviors. By establishing a single cell nanobiosensor along with live cell imaging, we perform dynamic single cell analysis of the morphology, displacement, and gene expression during microvascular self-organization. Dynamic single cell analysis reveals that endothelial cells self-organize into subpopulations with specialized phenotypes to form microvascular networks and identifies the involvement of Notch1-Dll4 signaling in regulating the cell subpopulations. The cell phenotype correlates with the initial Dll4 mRNA expression level and each subpopulation displays a unique dynamic Dll4 mRNA expression profile. Pharmacological perturbations and RNA interference of Notch1-Dll4 signaling modulate the cell subpopulations and modify the morphology of the microvascular network. Taken together, a nanobiosensor enables a dynamic single cell analysis approach underscoring the importance of Notch1-Dll4 signaling in microvascular self-organization.

The biometric-based module of smart grid system

NASA Astrophysics Data System (ADS)

Engel, E.; Kovalev, I. V.; Ermoshkina, A.

2015-10-01

Within Smart Grid concept the flexible biometric-based module base on Principal Component Analysis (PCA) and selective Neural Network is developed. The formation of the selective Neural Network the biometric-based module uses the method which includes three main stages: preliminary processing of the image, face localization and face recognition. Experiments on the Yale face database show that (i) selective Neural Network exhibits promising classification capability for face detection, recognition problems; and (ii) the proposed biometric-based module achieves near real-time face detection, recognition speed and the competitive performance, as compared to some existing subspaces-based methods.

To cut or not to cut? Assessing the modular structure of brain networks.

PubMed

Chang, Yu-Teng; Pantazis, Dimitrios; Leahy, Richard M

2014-05-01

A wealth of methods has been developed to identify natural divisions of brain networks into groups or modules, with one of the most prominent being modularity. Compared with the popularity of methods to detect community structure, only a few methods exist to statistically control for spurious modules, relying almost exclusively on resampling techniques. It is well known that even random networks can exhibit high modularity because of incidental concentration of edges, even though they have no underlying organizational structure. Consequently, interpretation of community structure is confounded by the lack of principled and computationally tractable approaches to statistically control for spurious modules. In this paper we show that the modularity of random networks follows a transformed version of the Tracy-Widom distribution, providing for the first time a link between module detection and random matrix theory. We compute parametric formulas for the distribution of modularity for random networks as a function of network size and edge variance, and show that we can efficiently control for false positives in brain and other real-world networks. Copyright © 2014 Elsevier Inc. All rights reserved.

Distinct sets of locomotor modules control the speed and modes of human locomotion

PubMed Central

Yokoyama, Hikaru; Ogawa, Tetsuya; Kawashima, Noritaka; Shinya, Masahiro; Nakazawa, Kimitaka

2016-01-01

Although recent vertebrate studies have revealed that different spinal networks are recruited in locomotor mode- and speed-dependent manners, it is unknown whether humans share similar neural mechanisms. Here, we tested whether speed- and mode-dependence in the recruitment of human locomotor networks exists or not by statistically extracting locomotor networks. From electromyographic activity during walking and running over a wide speed range, locomotor modules generating basic patterns of muscle activities were extracted using non-negative matrix factorization. The results showed that the number of modules changed depending on the modes and speeds. Different combinations of modules were extracted during walking and running, and at different speeds even during the same locomotor mode. These results strongly suggest that, in humans, different spinal locomotor networks are recruited while walking and running, and even in the same locomotor mode different networks are probably recruited at different speeds. PMID:27805015

Protein complexes and functional modules in molecular networks

NASA Astrophysics Data System (ADS)

Spirin, Victor; Mirny, Leonid A.

2003-10-01

Proteins, nucleic acids, and small molecules form a dense network of molecular interactions in a cell. Molecules are nodes of this network, and the interactions between them are edges. The architecture of molecular networks can reveal important principles of cellular organization and function, similarly to the way that protein structure tells us about the function and organization of a protein. Computational analysis of molecular networks has been primarily concerned with node degree [Wagner, A. & Fell, D. A. (2001) Proc. R. Soc. London Ser. B 268, 1803-1810; Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N. & Barabasi, A. L. (2000) Nature 407, 651-654] or degree correlation [Maslov, S. & Sneppen, K. (2002) Science 296, 910-913], and hence focused on single/two-body properties of these networks. Here, by analyzing the multibody structure of the network of protein-protein interactions, we discovered molecular modules that are densely connected within themselves but sparsely connected with the rest of the network. Comparison with experimental data and functional annotation of genes showed two types of modules: (i) protein complexes (splicing machinery, transcription factors, etc.) and (ii) dynamic functional units (signaling cascades, cell-cycle regulation, etc.). Discovered modules are highly statistically significant, as is evident from comparison with random graphs, and are robust to noise in the data. Our results provide strong support for the network modularity principle introduced by Hartwell et al. [Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. (1999) Nature 402, C47-C52], suggesting that found modules constitute the "building blocks" of molecular networks.

Developing research competencies through a project-based tissue-engineering module in the biomedical engineering undergraduate curriculum.

PubMed

Wallen, M; Pandit, A

2009-05-01

In addressing the task of developing an undergraduate module in the field of tissue engineering, the greatest challenge lies in managing to capture what is a growing and rapidly changing field. Acknowledging the call for the development of greater critical thinking and interpersonal skills among the next generation of engineers as well as encouraging students to engage actively with the dynamic nature of research in the field, the module was developed to include both project-based and cooperative-learning experiences. These learning activities include developing hypotheses for the application of newly introduced laboratory procedures, a collaborative mock grant submission, and debates on ethical issues in which students are assigned roles as various stakeholders. Feedback from module evaluations has indicated that, while students find the expectations challenging, they are able to gain an advanced insight into a dynamic field. More importantly, students develop research competencies by engaging in activities that require them to link current research directions with their own development of hypotheses for future tissue-engineering applications.

Object-oriented approach for gas turbine engine simulation

NASA Technical Reports Server (NTRS)

Curlett, Brian P.; Felder, James L.

1995-01-01

An object-oriented gas turbine engine simulation program was developed. This program is a prototype for a more complete, commercial grade engine performance program now being proposed as part of the Numerical Propulsion System Simulator (NPSS). This report discusses architectural issues of this complex software system and the lessons learned from developing the prototype code. The prototype code is a fully functional, general purpose engine simulation program, however, only the component models necessary to model a transient compressor test rig have been written. The production system will be capable of steady state and transient modeling of almost any turbine engine configuration. Chief among the architectural considerations for this code was the framework in which the various software modules will interact. These modules include the equation solver, simulation code, data model, event handler, and user interface. Also documented in this report is the component based design of the simulation module and the inter-component communication paradigm. Object class hierarchies for some of the code modules are given.

Currently available medical engineering degrees in the UK. Part 2: Postgraduate degrees.

PubMed

Joyce, T

2009-05-01

This paper considers taught medical engineering MSc degrees, based on mechanical engineering, which are provided in the UK. Currently there are 19 institutions which provide such postgraduate degree programmes. These are the University of Aberdeen, University of Bath, University of Bradford, Brunel University, University of Dundee, University of Hull, Imperial College London, Keele University, King's College London, University of Leeds, University of Liverpool, University of Nottingham, University of Oxford, Queen Mary University of London, University of Southampton, University of Strathclyde, University of Surrey, University of Ulster, and University of Warwick. While most courses are delivered on a 1 year full-time basis, other delivery modes are also available. Relatively few modules are offered as distance learning or short courses. A wide range of modules are offered by the various universities for the different taught MSc degrees. Common modules include biomaterials and biomechanics. The medical-engineering-related modules offered by a number of universities are also made available to students on allied MSc programmes and undergraduate degrees in medical engineering.

Network-dependent modulation of brain activity during sleep.

PubMed

Watanabe, Takamitsu; Kan, Shigeyuki; Koike, Takahiko; Misaki, Masaya; Konishi, Seiki; Miyauchi, Satoru; Miyahsita, Yasushi; Masuda, Naoki

2014-09-01

Brain activity dynamically changes even during sleep. A line of neuroimaging studies has reported changes in functional connectivity and regional activity across different sleep stages such as slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep. However, it remains unclear whether and how the large-scale network activity of human brains changes within a given sleep stage. Here, we investigated modulation of network activity within sleep stages by applying the pairwise maximum entropy model to brain activity obtained by functional magnetic resonance imaging from sleeping healthy subjects. We found that the brain activity of individual brain regions and functional interactions between pairs of regions significantly increased in the default-mode network during SWS and decreased during REM sleep. In contrast, the network activity of the fronto-parietal and sensory-motor networks showed the opposite pattern. Furthermore, in the three networks, the amount of the activity changes throughout REM sleep was negatively correlated with that throughout SWS. The present findings suggest that the brain activity is dynamically modulated even in a sleep stage and that the pattern of modulation depends on the type of the large-scale brain networks. Copyright © 2014 Elsevier Inc. All rights reserved.

PyPathway: Python Package for Biological Network Analysis and Visualization.

PubMed

Xu, Yang; Luo, Xiao-Chun

2018-05-01

Life science studies represent one of the biggest generators of large data sets, mainly because of rapid sequencing technological advances. Biological networks including interactive networks and human curated pathways are essential to understand these high-throughput data sets. Biological network analysis offers a method to explore systematically not only the molecular complexity of a particular disease but also the molecular relationships among apparently distinct phenotypes. Currently, several packages for Python community have been developed, such as BioPython and Goatools. However, tools to perform comprehensive network analysis and visualization are still needed. Here, we have developed PyPathway, an extensible free and open source Python package for functional enrichment analysis, network modeling, and network visualization. The network process module supports various interaction network and pathway databases such as Reactome, WikiPathway, STRING, and BioGRID. The network analysis module implements overrepresentation analysis, gene set enrichment analysis, network-based enrichment, and de novo network modeling. Finally, the visualization and data publishing modules enable users to share their analysis by using an easy web application. For package availability, see the first Reference.

Community Landscapes: An Integrative Approach to Determine Overlapping Network Module Hierarchy, Identify Key Nodes and Predict Network Dynamics

PubMed Central

Kovács, István A.; Palotai, Robin; Szalay, Máté S.; Csermely, Peter

2010-01-01

Background Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. Methodology/Principal Findings Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1) determine pervasively overlapping modules with high resolution; (2) uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3) allow the determination of key network nodes and (4) help to predict network dynamics. Conclusions/Significance The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction. PMID:20824084

Transparent superstrate terrestrial solar cell module

NASA Technical Reports Server (NTRS)

1977-01-01

The design, development, fabrication, and testing of the transparent solar cell module were examined. Cell performance and material process characteristics were determined by extensive tests and design modifications were made prior to preproduction fabrication. These tests included three cell submodules and two full size engineering modules. Along with hardware and test activity, engineering documentation was prepared and submitted.

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT IV, MAINTAINING THE COOLING SYSTEM--DETROIT DIESEL ENGINES.

ERIC Educational Resources Information Center

Human Engineering Inst., Cleveland, OH.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF THE OPERATION AND MAINTENANCE OF THE DIESEL ENGINE COOLING SYSTEM. TOPICS ARE PURPOSE OF THE COOLING SYSTEM, CARE MAINTENANCE OF THE COOLING SYSTEM, COOLING SYSTEM COMPONENTS, AND TROUBLESHOOTING TIPS. THE MODULE CONSISTS OF A SELF-INSTRUCTIONAL BRANCH PROGRAMED TRAINING…

Light Activated Escape Circuits: A Behavior and Neurophysiology Lab Module using Drosophila Optogenetics

PubMed Central

Titlow, Josh S.; Johnson, Bruce R.; Pulver, Stefan R.

2015-01-01

The neural networks that control escape from predators often show very clear relationships between defined sensory inputs and stereotyped motor outputs. This feature provides unique opportunities for researchers, but it also provides novel opportunities for neuroscience educators. Here we introduce new teaching modules using adult Drosophila that have been engineered to express csChrimson, a red-light sensitive channelrhodopsin, in specific sets of neurons and muscles mediating visually guided escape behaviors. This lab module consists of both behavior and electrophysiology experiments that explore the neural basis of flight escape. Three preparations are described that demonstrate photo-activation of the giant fiber circuit and how to quantify these behaviors. One of the preparations is then used to acquire intracellular electrophysiology recordings from different flight muscles. The diversity of action potential waveforms and firing frequencies observed in the flight muscles make this a rich preparation to study the ionic basic of cellular excitability. By activating different cells within the giant fiber pathway we also demonstrate principles of synaptic transmission and neural circuits. Beyond conveying core neurobiological concepts it is also expected that using these cutting edge techniques will enhance student motivation and attitudes towards biological research. Data collected from students and educators who have been involved in development of the module are presented to support this notion. PMID:26240526

Ad hoc Laser networks component technology for modular spacecraft

NASA Astrophysics Data System (ADS)

Huang, Xiujun; Shi, Dele; Ma, Zongfeng; Shen, Jingshi

2016-03-01

Distributed reconfigurable satellite is a new kind of spacecraft system, which is based on a flexible platform of modularization and standardization. Based on the module data flow analysis of the spacecraft, this paper proposes a network component of ad hoc Laser networks architecture. Low speed control network with high speed load network of Microwave-Laser communication mode, no mesh network mode, to improve the flexibility of the network. Ad hoc Laser networks component technology was developed, and carried out the related performance testing and experiment. The results showed that ad hoc Laser networks components can meet the demand of future networking between the module of spacecraft.

Ad hoc laser networks component technology for modular spacecraft

NASA Astrophysics Data System (ADS)

Huang, Xiujun; Shi, Dele; Shen, Jingshi

2017-10-01

Distributed reconfigurable satellite is a new kind of spacecraft system, which is based on a flexible platform of modularization and standardization. Based on the module data flow analysis of the spacecraft, this paper proposes a network component of ad hoc Laser networks architecture. Low speed control network with high speed load network of Microwave-Laser communication mode, no mesh network mode, to improve the flexibility of the network. Ad hoc Laser networks component technology was developed, and carried out the related performance testing and experiment. The results showed that ad hoc Laser networks components can meet the demand of future networking between the module of spacecraft.

Human Machine Interface Programming and Testing

NASA Technical Reports Server (NTRS)

Foster, Thomas Garrison

2013-01-01

Human Machine Interface (HMI) Programming and Testing is about creating graphical displays to mimic mission critical ground control systems in order to provide NASA engineers with the ability to monitor the health management of these systems in real time. The Health Management System (HMS) is an online interactive human machine interface system that monitors all Kennedy Ground Control Subsystem (KGCS) hardware in the field. The Health Management System is essential to NASA engineers because it allows remote control and monitoring of the health management systems of all the Programmable Logic Controllers (PLC) and associated field devices. KGCS will have equipment installed at the launch pad, Vehicle Assembly Building, Mobile Launcher, as well as the Multi-Purpose Processing Facility. I am designing graphical displays to monitor and control new modules that will be integrated into the HMS. The design of the display screen will closely mimic the appearance and functionality of the actual modules. There are many different field devices used to monitor health management and each device has its own unique set of health management related data, therefore each display must also have its own unique way to display this data. Once the displays are created, the RSLogix5000 application is used to write software that maps all the required data read from the hardware to the graphical display. Once this data is mapped to its corresponding display item, the graphical display and hardware device will be connected through the same network in order to test all possible scenarios and types of data the graphical display was designed to receive. Test Procedures will be written to thoroughly test out the displays and ensure that they are working correctly before being deployed to the field. Additionally, the Kennedy Ground Controls Subsystem's user manual will be updated to explain to the NASA engineers how to use the new module displays.

Intrinsic functional network architecture of human semantic processing: Modules and hubs.

PubMed

Xu, Yangwen; Lin, Qixiang; Han, Zaizhu; He, Yong; Bi, Yanchao

2016-05-15

Semantic processing entails the activation of widely distributed brain areas across the temporal, parietal, and frontal lobes. To understand the functional structure of this semantic system, we examined its intrinsic functional connectivity pattern using a database of 146 participants. Focusing on areas consistently activated during semantic processing generated from a meta-analysis of 120 neuroimaging studies (Binder et al., 2009), we found that these regions were organized into three stable modules corresponding to the default mode network (Module DMN), the left perisylvian network (Module PSN), and the left frontoparietal network (Module FPN). These three dissociable modules were integrated by multiple connector hubs-the left angular gyrus (AG) and the left superior/middle frontal gyrus linking all three modules, the left anterior temporal lobe linking Modules DMN and PSN, the left posterior portion of dorsal intraparietal sulcus (IPS) linking Modules DMN and FPN, and the left posterior middle temporal gyrus (MTG) linking Modules PSN and FPN. Provincial hubs, which converge local information within each system, were also identified: the bilateral posterior cingulate cortices/precuneus, the bilateral border area of the posterior AG and the superior lateral occipital gyrus for Module DMN; the left supramarginal gyrus, the middle part of the left MTG and the left orbital inferior frontal gyrus (IFG) for Module FPN; and the left triangular IFG and the left IPS for Module FPN. A neuro-functional model for semantic processing was derived based on these findings, incorporating the interactions of memory, language, and control. Copyright © 2016 Elsevier Inc. All rights reserved.

Efficient and accurate Greedy Search Methods for mining functional modules in protein interaction networks.

PubMed

He, Jieyue; Li, Chaojun; Ye, Baoliu; Zhong, Wei

2012-06-25

Most computational algorithms mainly focus on detecting highly connected subgraphs in PPI networks as protein complexes but ignore their inherent organization. Furthermore, many of these algorithms are computationally expensive. However, recent analysis indicates that experimentally detected protein complexes generally contain Core/attachment structures. In this paper, a Greedy Search Method based on Core-Attachment structure (GSM-CA) is proposed. The GSM-CA method detects densely connected regions in large protein-protein interaction networks based on the edge weight and two criteria for determining core nodes and attachment nodes. The GSM-CA method improves the prediction accuracy compared to other similar module detection approaches, however it is computationally expensive. Many module detection approaches are based on the traditional hierarchical methods, which is also computationally inefficient because the hierarchical tree structure produced by these approaches cannot provide adequate information to identify whether a network belongs to a module structure or not. In order to speed up the computational process, the Greedy Search Method based on Fast Clustering (GSM-FC) is proposed in this work. The edge weight based GSM-FC method uses a greedy procedure to traverse all edges just once to separate the network into the suitable set of modules. The proposed methods are applied to the protein interaction network of S. cerevisiae. Experimental results indicate that many significant functional modules are detected, most of which match the known complexes. Results also demonstrate that the GSM-FC algorithm is faster and more accurate as compared to other competing algorithms. Based on the new edge weight definition, the proposed algorithm takes advantages of the greedy search procedure to separate the network into the suitable set of modules. Experimental analysis shows that the identified modules are statistically significant. The algorithm can reduce the computational time significantly while keeping high prediction accuracy.

Situation-Dependent Medical Device Risk Estimation: Design and Evaluation of an Equipment Management Center For Vendor-Independent Integrated Operating Rooms.

PubMed

Maktabi, Marianne; Neumuth, Thomas

2017-12-22

The complexity of surgical interventions and the number of technologies involved are constantly rising. Hospital staff has to learn how to handle new medical devices efficiently. However, if medical device-related incidents occur, the patient treatment is delayed. Patient safety could therefore be supported by an optimized assistance system that helps improve the management of technical equipment by nonmedical hospital staff. We developed a system for the optimal monitoring of networked medical device activity and maintenance requirements, which works in conjunction with a vendor-independent integrated operating room and an accurate surgical intervention Time And Resource Management System. An integrated situation-dependent risk assessment system gives the medical engineers optimal awareness of the medical devices in the operating room. A qualitative and quantitative survey among ten medical engineers from three different hospitals was performed to evaluate the approach. A series of 25 questions was used to evaluate various aspects of our system as well as the system currently used. Moreover, the respondents were asked to perform five tasks related to system supervision and incident handling. Our system received a very positive feedback. The evaluation studies showed that the integration of information, the structured presentation of information, and the assistance modules provide valuable support to medical engineers. An automated operating room monitoring system with an integrated risk assessment and Time And Resource Management System module is a new way to assist the staff being outside of a vendor-independent integrated operating room, who are nevertheless involved in processes in the operating room.

NCC: A Multidisciplinary Design/Analysis Tool for Combustion Systems

NASA Technical Reports Server (NTRS)

Liu, Nan-Suey; Quealy, Angela

1999-01-01

A multi-disciplinary design/analysis tool for combustion systems is critical for optimizing the low-emission, high-performance combustor design process. Based on discussions between NASA Lewis Research Center and the jet engine companies, an industry-government team was formed in early 1995 to develop the National Combustion Code (NCC), which is an integrated system of computer codes for the design and analysis of combustion systems. NCC has advanced features that address the need to meet designer's requirements such as "assured accuracy", "fast turnaround", and "acceptable cost". The NCC development team is comprised of Allison Engine Company (Allison), CFD Research Corporation (CFDRC), GE Aircraft Engines (GEAE), NASA Lewis Research Center (LeRC), and Pratt & Whitney (P&W). This development team operates under the guidance of the NCC steering committee. The "unstructured mesh" capability and "parallel computing" are fundamental features of NCC from its inception. The NCC system is composed of a set of "elements" which includes grid generator, main flow solver, turbulence module, turbulence and chemistry interaction module, chemistry module, spray module, radiation heat transfer module, data visualization module, and a post-processor for evaluating engine performance parameters. Each element may have contributions from several team members. Such a multi-source multi-element system needs to be integrated in a way that facilitates inter-module data communication, flexibility in module selection, and ease of integration.

Modulation aware cluster size optimisation in wireless sensor networks

NASA Astrophysics Data System (ADS)

Sriram Naik, M.; Kumar, Vinay

2017-07-01

Wireless sensor networks (WSNs) play a great role because of their numerous advantages to the mankind. The main challenge with WSNs is the energy efficiency. In this paper, we have focused on the energy minimisation with the help of cluster size optimisation along with consideration of modulation effect when the nodes are not able to communicate using baseband communication technique. Cluster size optimisations is important technique to improve the performance of WSNs. It provides improvement in energy efficiency, network scalability, network lifetime and latency. We have proposed analytical expression for cluster size optimisation using traditional sensing model of nodes for square sensing field with consideration of modulation effects. Energy minimisation can be achieved by changing the modulation schemes such as BPSK, 16-QAM, QPSK, 64-QAM, etc., so we are considering the effect of different modulation techniques in the cluster formation. The nodes in the sensing fields are random and uniformly deployed. It is also observed that placement of base station at centre of scenario enables very less number of modulation schemes to work in energy efficient manner but when base station placed at the corner of the sensing field, it enable large number of modulation schemes to work in energy efficient manner.

Array processor architecture connection network

NASA Technical Reports Server (NTRS)

Barnes, George H. (Inventor); Lundstrom, Stephen F. (Inventor); Shafer, Philip E. (Inventor)

1982-01-01

A connection network is disclosed for use between a parallel array of processors and a parallel array of memory modules for establishing non-conflicting data communications paths between requested memory modules and requesting processors. The connection network includes a plurality of switching elements interposed between the processor array and the memory modules array in an Omega networking architecture. Each switching element includes a first and a second processor side port, a first and a second memory module side port, and control logic circuitry for providing data connections between the first and second processor ports and the first and second memory module ports. The control logic circuitry includes strobe logic for examining data arriving at the first and the second processor ports to indicate when the data arriving is requesting data from a requesting processor to a requested memory module. Further, connection circuitry is associated with the strobe logic for examining requesting data arriving at the first and the second processor ports for providing a data connection therefrom to the first and the second memory module ports in response thereto when the data connection so provided does not conflict with a pre-established data connection currently in use.

A novel network module for medical devices.

PubMed

Chen, Ping-Yu

2008-01-01

In order to allow medical devices to upload the vital signs to a server on a network without manually configuring for end-users, a new network module is proposed. The proposed network module, called Medical Hub (MH), functions as a bridge to fetch the data from all connecting medical devices, and then upload these data to the server. When powering on, the MH can immediately establish network configuration automatically. Network Address Translation (NAT) traversal is also supported by the MH with the UPnP Internet Gateway Device (IGD) methodology. Besides the network configuration, other configuration in the MH is automatically established by using the remote management protocol TR-069. On the other hand, a mechanism for updating software automatically according to the variant connected medical device is proposed. With this mechanism, newcome medical devices can be detected and supported by the MH without manual operation.

Low frequency steady-state brain responses modulate large scale functional networks in a frequency-specific means.

PubMed

Wang, Yi-Feng; Long, Zhiliang; Cui, Qian; Liu, Feng; Jing, Xiu-Juan; Chen, Heng; Guo, Xiao-Nan; Yan, Jin H; Chen, Hua-Fu

2016-01-01

Neural oscillations are essential for brain functions. Research has suggested that the frequency of neural oscillations is lower for more integrative and remote communications. In this vein, some resting-state studies have suggested that large scale networks function in the very low frequency range (<1 Hz). However, it is difficult to determine the frequency characteristics of brain networks because both resting-state studies and conventional frequency tagging approaches cannot simultaneously capture multiple large scale networks in controllable cognitive activities. In this preliminary study, we aimed to examine whether large scale networks can be modulated by task-induced low frequency steady-state brain responses (lfSSBRs) in a frequency-specific pattern. In a revised attention network test, the lfSSBRs were evoked in the triple network system and sensory-motor system, indicating that large scale networks can be modulated in a frequency tagging way. Furthermore, the inter- and intranetwork synchronizations as well as coherence were increased at the fundamental frequency and the first harmonic rather than at other frequency bands, indicating a frequency-specific modulation of information communication. However, there was no difference among attention conditions, indicating that lfSSBRs modulate the general attention state much stronger than distinguishing attention conditions. This study provides insights into the advantage and mechanism of lfSSBRs. More importantly, it paves a new way to investigate frequency-specific large scale brain activities. © 2015 Wiley Periodicals, Inc.

Preservation affinity in consensus modules among stages of HIV-1 progression.

PubMed

Mosaddek Hossain, Sk Md; Ray, Sumanta; Mukhopadhyay, Anirban

2017-03-20

Analysis of gene expression data provides valuable insights into disease mechanism. Investigating relationship among co-expression modules of different stages is a meaningful tool to understand the way in which a disease progresses. Identifying topological preservation of modular structure also contributes to that understanding. HIV-1 disease provides a well-documented progression pattern through three stages of infection: acute, chronic and non-progressor. In this article, we have developed a novel framework to describe the relationship among the consensus (or shared) co-expression modules for each pair of HIV-1 infection stages. The consensus modules are identified to assess the preservation of network properties. We have investigated the preservation patterns of co-expression networks during HIV-1 disease progression through an eigengene-based approach. We discovered that the expression patterns of consensus modules have a strong preservation during the transitions of three infection stages. In particular, it is noticed that between acute and non-progressor stages the preservation is slightly more than the other pair of stages. Moreover, we have constructed eigengene networks for the identified consensus modules and observed the preservation structure among them. Some consensus modules are marked as preserved in two pairs of stages and are analyzed further to form a higher order meta-network consisting of a group of preserved modules. Additionally, we observed that module membership (MM) values of genes within a module are consistent with the preservation characteristics. The MM values of genes within a pair of preserved modules show strong correlation patterns across two infection stages. We have performed an extensive analysis to discover preservation pattern of co-expression network constructed from microarray gene expression data of three different HIV-1 progression stages. The preservation pattern is investigated through identification of consensus modules in each pair of infection stages. It is observed that the preservation of the expression pattern of consensus modules remains more prominent during the transition of infection from acute stage to non-progressor stage. Additionally, we observed that the module membership values of genes are coherent with preserved modules across the HIV-1 progression stages.

Synthetic biology: new engineering rules for an emerging discipline

PubMed Central

Andrianantoandro, Ernesto; Basu, Subhayu; Karig, David K; Weiss, Ron

2006-01-01

Synthetic biologists engineer complex artificial biological systems to investigate natural biological phenomena and for a variety of applications. We outline the basic features of synthetic biology as a new engineering discipline, covering examples from the latest literature and reflecting on the features that make it unique among all other existing engineering fields. We discuss methods for designing and constructing engineered cells with novel functions in a framework of an abstract hierarchy of biological devices, modules, cells, and multicellular systems. The classical engineering strategies of standardization, decoupling, and abstraction will have to be extended to take into account the inherent characteristics of biological devices and modules. To achieve predictability and reliability, strategies for engineering biology must include the notion of cellular context in the functional definition of devices and modules, use rational redesign and directed evolution for system optimization, and focus on accomplishing tasks using cell populations rather than individual cells. The discussion brings to light issues at the heart of designing complex living systems and provides a trajectory for future development. PMID:16738572

Synthetic biology: new engineering rules for an emerging discipline.

PubMed

Andrianantoandro, Ernesto; Basu, Subhayu; Karig, David K; Weiss, Ron

2006-01-01

Synthetic biologists engineer complex artificial biological systems to investigate natural biological phenomena and for a variety of applications. We outline the basic features of synthetic biology as a new engineering discipline, covering examples from the latest literature and reflecting on the features that make it unique among all other existing engineering fields. We discuss methods for designing and constructing engineered cells with novel functions in a framework of an abstract hierarchy of biological devices, modules, cells, and multicellular systems. The classical engineering strategies of standardization, decoupling, and abstraction will have to be extended to take into account the inherent characteristics of biological devices and modules. To achieve predictability and reliability, strategies for engineering biology must include the notion of cellular context in the functional definition of devices and modules, use rational redesign and directed evolution for system optimization, and focus on accomplishing tasks using cell populations rather than individual cells. The discussion brings to light issues at the heart of designing complex living systems and provides a trajectory for future development.

Identification of functional modules using network topology and high-throughput data.

PubMed

Ulitsky, Igor; Shamir, Ron

2007-01-26

With the advent of systems biology, biological knowledge is often represented today by networks. These include regulatory and metabolic networks, protein-protein interaction networks, and many others. At the same time, high-throughput genomics and proteomics techniques generate very large data sets, which require sophisticated computational analysis. Usually, separate and different analysis methodologies are applied to each of the two data types. An integrated investigation of network and high-throughput information together can improve the quality of the analysis by accounting simultaneously for topological network properties alongside intrinsic features of the high-throughput data. We describe a novel algorithmic framework for this challenge. We first transform the high-throughput data into similarity values, (e.g., by computing pairwise similarity of gene expression patterns from microarray data). Then, given a network of genes or proteins and similarity values between some of them, we seek connected sub-networks (or modules) that manifest high similarity. We develop algorithms for this problem and evaluate their performance on the osmotic shock response network in S. cerevisiae and on the human cell cycle network. We demonstrate that focused, biologically meaningful and relevant functional modules are obtained. In comparison with extant algorithms, our approach has higher sensitivity and higher specificity. We have demonstrated that our method can accurately identify functional modules. Hence, it carries the promise to be highly useful in analysis of high throughput data.

Correlation between Academic and Skills-Based Tests in Computer Networks

ERIC Educational Resources Information Center

Buchanan, William

2006-01-01

Computing-related programmes and modules have many problems, especially related to large class sizes, large-scale plagiarism, module franchising, and an increased requirement from students for increased amounts of hands-on, practical work. This paper presents a practical computer networks module which uses a mixture of online examinations and a…

Generation of oscillating gene regulatory network motifs

NASA Astrophysics Data System (ADS)

van Dorp, M.; Lannoo, B.; Carlon, E.

2013-07-01

Using an improved version of an evolutionary algorithm originally proposed by François and Hakim [Proc. Natl. Acad. Sci. USAPNASA60027-842410.1073/pnas.0304532101 101, 580 (2004)], we generated small gene regulatory networks in which the concentration of a target protein oscillates in time. These networks may serve as candidates for oscillatory modules to be found in larger regulatory networks and protein interaction networks. The algorithm was run for 105 times to produce a large set of oscillating modules, which were systematically classified and analyzed. The robustness of the oscillations against variations of the kinetic rates was also determined, to filter out the least robust cases. Furthermore, we show that the set of evolved networks can serve as a database of models whose behavior can be compared to experimentally observed oscillations. The algorithm found three smallest (core) oscillators in which nonlinearities and number of components are minimal. Two of those are two-gene modules: the mixed feedback loop, already discussed in the literature, and an autorepressed gene coupled with a heterodimer. The third one is a single gene module which is competitively regulated by a monomer and a dimer. The evolutionary algorithm also generated larger oscillating networks, which are in part extensions of the three core modules and in part genuinely new modules. The latter includes oscillators which do not rely on feedback induced by transcription factors, but are purely of post-transcriptional type. Analysis of post-transcriptional mechanisms of oscillation may provide useful information for circadian clock research, as recent experiments showed that circadian rhythms are maintained even in the absence of transcription.

SABRE: a method for assessing the stability of gene modules in complex tissues and subject populations.

PubMed

Shannon, Casey P; Chen, Virginia; Takhar, Mandeep; Hollander, Zsuzsanna; Balshaw, Robert; McManus, Bruce M; Tebbutt, Scott J; Sin, Don D; Ng, Raymond T

2016-11-14

Gene network inference (GNI) algorithms can be used to identify sets of coordinately expressed genes, termed network modules from whole transcriptome gene expression data. The identification of such modules has become a popular approach to systems biology, with important applications in translational research. Although diverse computational and statistical approaches have been devised to identify such modules, their performance behavior is still not fully understood, particularly in complex human tissues. Given human heterogeneity, one important question is how the outputs of these computational methods are sensitive to the input sample set, or stability. A related question is how this sensitivity depends on the size of the sample set. We describe here the SABRE (Similarity Across Bootstrap RE-sampling) procedure for assessing the stability of gene network modules using a re-sampling strategy, introduce a novel criterion for identifying stable modules, and demonstrate the utility of this approach in a clinically-relevant cohort, using two different gene network module discovery algorithms. The stability of modules increased as sample size increased and stable modules were more likely to be replicated in larger sets of samples. Random modules derived from permutated gene expression data were consistently unstable, as assessed by SABRE, and provide a useful baseline value for our proposed stability criterion. Gene module sets identified by different algorithms varied with respect to their stability, as assessed by SABRE. Finally, stable modules were more readily annotated in various curated gene set databases. The SABRE procedure and proposed stability criterion may provide guidance when designing systems biology studies in complex human disease and tissues.

The deep space network, Volume 11

NASA Technical Reports Server (NTRS)

1972-01-01

Deep Space Network progress in flight project support, Tracking and Data Acquisition research and technology, network engineering, hardware and software implementation, and operations are presented. Material is presented in each of the following categories: description of DSN; mission support; radio science; support research and technology; network engineering and implementation; and operations and facilities.

Excavation of attractor modules for nasopharyngeal carcinoma via integrating systemic module inference with attract method.

PubMed

Jiang, T; Jiang, C-Y; Shu, J-H; Xu, Y-J

2017-07-10

The molecular mechanism of nasopharyngeal carcinoma (NPC) is poorly understood and effective therapeutic approaches are needed. This research aimed to excavate the attractor modules involved in the progression of NPC and provide further understanding of the underlying mechanism of NPC. Based on the gene expression data of NPC, two specific protein-protein interaction networks for NPC and control conditions were re-weighted using Pearson correlation coefficient. Then, a systematic tracking of candidate modules was conducted on the re-weighted networks via cliques algorithm, and a total of 19 and 38 modules were separately identified from NPC and control networks, respectively. Among them, 8 pairs of modules with similar gene composition were selected, and 2 attractor modules were identified via the attract method. Functional analysis indicated that these two attractor modules participate in one common bioprocess of cell division. Based on the strategy of integrating systemic module inference with the attract method, we successfully identified 2 attractor modules. These attractor modules might play important roles in the molecular pathogenesis of NPC via affecting the bioprocess of cell division in a conjunct way. Further research is needed to explore the correlations between cell division and NPC.

Identification of a gene module associated with BMD through the integration of network analysis and genome-wide association data.

PubMed

Farber, Charles R

2010-11-01

Bone mineral density (BMD) is influenced by a complex network of gene interactions; therefore, elucidating the relationships between genes and how those genes, in turn, influence BMD is critical for developing a comprehensive understanding of osteoporosis. To investigate the role of transcriptional networks in the regulation of BMD, we performed a weighted gene coexpression network analysis (WGCNA) using microarray expression data on monocytes from young individuals with low or high BMD. WGCNA groups genes into modules based on patterns of gene coexpression. and our analysis identified 11 gene modules. We observed that the overall expression of one module (referred to as module 9) was significantly higher in the low-BMD group (p = .03). Module 9 was highly enriched for genes belonging to the immune system-related gene ontology (GO) category "response to virus" (p = 7.6 × 10(-11)). Using publically available genome-wide association study data, we independently validated the importance of module 9 by demonstrating that highly connected module 9 hubs were more likely, relative to less highly connected genes, to be genetically associated with BMD. This study highlights the advantages of systems-level analyses to uncover coexpression modules associated with bone mass and suggests that particular monocyte expression patterns may mediate differences in BMD. © 2010 American Society for Bone and Mineral Research.

ModuleRole: a tool for modulization, role determination and visualization in protein-protein interaction networks.

PubMed

Li, Guipeng; Li, Ming; Zhang, Yiwei; Wang, Dong; Li, Rong; Guimerà, Roger; Gao, Juntao Tony; Zhang, Michael Q

2014-01-01

Rapidly increasing amounts of (physical and genetic) protein-protein interaction (PPI) data are produced by various high-throughput techniques, and interpretation of these data remains a major challenge. In order to gain insight into the organization and structure of the resultant large complex networks formed by interacting molecules, using simulated annealing, a method based on the node connectivity, we developed ModuleRole, a user-friendly web server tool which finds modules in PPI network and defines the roles for every node, and produces files for visualization in Cytoscape and Pajek. For given proteins, it analyzes the PPI network from BioGRID database, finds and visualizes the modules these proteins form, and then defines the role every node plays in this network, based on two topological parameters Participation Coefficient and Z-score. This is the first program which provides interactive and very friendly interface for biologists to find and visualize modules and roles of proteins in PPI network. It can be tested online at the website http://www.bioinfo.org/modulerole/index.php, which is free and open to all users and there is no login requirement, with demo data provided by "User Guide" in the menu Help. Non-server application of this program is considered for high-throughput data with more than 200 nodes or user's own interaction datasets. Users are able to bookmark the web link to the result page and access at a later time. As an interactive and highly customizable application, ModuleRole requires no expert knowledge in graph theory on the user side and can be used in both Linux and Windows system, thus a very useful tool for biologist to analyze and visualize PPI networks from databases such as BioGRID. ModuleRole is implemented in Java and C, and is freely available at http://www.bioinfo.org/modulerole/index.php. Supplementary information (user guide, demo data) is also available at this website. API for ModuleRole used for this program can be obtained upon request.

"I'm just a boy with girl parts": Understanding gender perception and negotiation in an undergraduate engineering program

NASA Astrophysics Data System (ADS)

Dickinson Skaggs, Jennifer Anne

The number of women being enrolled and retained in engineering programs has steadily decreased since 1999, even with increased efforts and funding of initiatives to counteract this trend. Why are women not persisting or even choosing to pursue engineering? This qualitative research examines how undergraduate female engineering students perceive and negotiate their gender identities to successfully persist in engineering education. Narrative inquiry including semi-structured interviews, participant observation, and data analysis was conducted at a Research I institution. Participants were recruited through purposeful network sampling. Criteria for inclusion include students who have been in the American K-12 educational pipeline at least eight years and are junior or senior level academic standing and academic eligibility. By including male students in the collection of data, perceptions of the issues for women could be seen in context when compared to the perceptions of men in the same engineering discipline. The study focuses on the individual, institutional, and cultural perceptions of gender performativity within a network and the strategies and negotiations employed by undergraduate female engineering students to achieve their educational goals regarding each of these perspectives. Findings reveal female students utilize strategies of camouflage and costume, as well as internal and external support to persist in engineering education. Also, female engineering students are being prepared to only become engineering-students-in-the-making and kept from the larger engineering network, while male students are becoming engineers-in-the-making automatically connected to the larger engineering network based on gender. This lack of association with the network influences female engineering students in their decisions to pursue a career in professional engineering, or to pursue more traditionally gendered careers after graduation. This research is significant in its use of feminist theory and methodology to study engineering education. It is also significant in its use of qualitative methods allowing students to articulate their experiences in their own words and voices thus allowing for nuanced of meaning and understanding to emerge. Butler's theory of gender performativity in conjunction with Nespor's actor-network theory provides the conceptual framework with inductive analysis used as the primary tool for data analysis.

Cellular level models as tools for cytokine design.

PubMed

Radhakrishnan, Mala L; Tidor, Bruce

2010-01-01

Cytokines and growth factors are critical regulators that connect intracellular and extracellular environments through binding to specific cell-surface receptors. They regulate a wide variety of immunological, growth, and inflammatory response processes. The overall signal initiated by a population of cytokine molecules over long time periods is controlled by the subtle interplay of binding, signaling, and trafficking kinetics. Building on the work of others, we abstract a simple kinetic model that captures relevant features from cytokine systems as well as related growth factor systems. We explore a large range of potential biochemical behaviors, through systematic examination of the model's parameter space. Different rates for the same reaction topology lead to a dramatic range of biochemical network properties and outcomes. Evolution might productively explore varied and different portions of parameter space to create beneficial behaviors, and effective human therapeutic intervention might be achieved through altering network kinetic properties. Quantitative analysis of the results reveals the basis for tensions among a number of different network characteristics. For example, strong binding of cytokine to receptor can increase short-term receptor activation and signal initiation but decrease long-term signaling due to internalization and degradation. Further analysis reveals the role of specific biochemical processes in modulating such tensions. For instance, the kinetics of cytokine binding and receptor activation modulate whether ligand-receptor dissociation can generally occur before signal initiation or receptor internalization. Beyond analysis, the same models and model behaviors provide an important basis for the design of more potent cytokine therapeutics by providing insight into how binding kinetics affect ligand potency. (c) 2010 American Institute of Chemical Engineers

Mapping networks of light-dark transition in LOV photoreceptors.

PubMed

Kaur Grewal, Rajdeep; Mitra, Devrani; Roy, Soumen

2015-11-15

In optogenetics, designing modules of long or short signaling state lifetime is necessary for control over precise cellular events. A critical parameter for designing artificial or synthetic photoreceptors is the signaling state lifetime of photosensor modules. Design and engineering of biologically relevant artificial photoreceptors is based on signaling mechanisms characteristic of naturally occurring photoreceptors. Therefore identifying residues important for light-dark transition is a definite first step towards rational design of synthetic photoreceptors. A thorough grasp of detailed mechanisms of photo induced signaling process would be immensely helpful in understanding the behaviour of organisms. Herein, we introduce the technique of differential networks. We identify key biological interactions, using light-oxygen-voltage domains of all organisms whose dark and light state crystal structures are simultaneously available. Even though structural differences between dark and light states are subtle (other than the covalent bond formation between flavin chromophore and active site Cysteine), our results successfully capture functionally relevant residues and are in complete agreement with experimental findings from literature. Additionally, using sequence-structure alignments, we predict functional significance of interactions found to be important from network perspective yet awaiting experimental validation. Our approach would not only help in minimizing extensive photo-cycle kinetics procedure but is also helpful in providing first-hand information on the fundamentals of photo-adaptation and rational design of synthetic photoreceptors in optogenetics. devrani.dbs@presiuniv.ac.in or soumen@jcbose.ac.in Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Cloud Engineering Principles and Technology Enablers for Medical Image Processing-as-a-Service.

PubMed

Bao, Shunxing; Plassard, Andrew J; Landman, Bennett A; Gokhale, Aniruddha

2017-04-01

Traditional in-house, laboratory-based medical imaging studies use hierarchical data structures (e.g., NFS file stores) or databases (e.g., COINS, XNAT) for storage and retrieval. The resulting performance from these approaches is, however, impeded by standard network switches since they can saturate network bandwidth during transfer from storage to processing nodes for even moderate-sized studies. To that end, a cloud-based "medical image processing-as-a-service" offers promise in utilizing the ecosystem of Apache Hadoop, which is a flexible framework providing distributed, scalable, fault tolerant storage and parallel computational modules, and HBase, which is a NoSQL database built atop Hadoop's distributed file system. Despite this promise, HBase's load distribution strategy of region split and merge is detrimental to the hierarchical organization of imaging data (e.g., project, subject, session, scan, slice). This paper makes two contributions to address these concerns by describing key cloud engineering principles and technology enhancements we made to the Apache Hadoop ecosystem for medical imaging applications. First, we propose a row-key design for HBase, which is a necessary step that is driven by the hierarchical organization of imaging data. Second, we propose a novel data allocation policy within HBase to strongly enforce collocation of hierarchically related imaging data. The proposed enhancements accelerate data processing by minimizing network usage and localizing processing to machines where the data already exist. Moreover, our approach is amenable to the traditional scan, subject, and project-level analysis procedures, and is compatible with standard command line/scriptable image processing software. Experimental results for an illustrative sample of imaging data reveals that our new HBase policy results in a three-fold time improvement in conversion of classic DICOM to NiFTI file formats when compared with the default HBase region split policy, and nearly a six-fold improvement over a commonly available network file system (NFS) approach even for relatively small file sets. Moreover, file access latency is lower than network attached storage.

Adaptive critic learning techniques for engine torque and air-fuel ratio control.

PubMed

Liu, Derong; Javaherian, Hossein; Kovalenko, Olesia; Huang, Ting

2008-08-01

A new approach for engine calibration and control is proposed. In this paper, we present our research results on the implementation of adaptive critic designs for self-learning control of automotive engines. A class of adaptive critic designs that can be classified as (model-free) action-dependent heuristic dynamic programming is used in this research project. The goals of the present learning control design for automotive engines include improved performance, reduced emissions, and maintained optimum performance under various operating conditions. Using the data from a test vehicle with a V8 engine, we developed a neural network model of the engine and neural network controllers based on the idea of approximate dynamic programming to achieve optimal control. We have developed and simulated self-learning neural network controllers for both engine torque (TRQ) and exhaust air-fuel ratio (AFR) control. The goal of TRQ control and AFR control is to track the commanded values. For both control problems, excellent neural network controller transient performance has been achieved.

An Alternative Educational Approach for an Inorganic Chemistry Laboratory Course in Industrial and Chemical Engineering

ERIC Educational Resources Information Center

Garces, Andres; Sanchez-Barba, Luis Fernando

2011-01-01

We describe an alternative educational approach for an inorganic chemistry laboratory module named "Experimentation in Chemistry", which is included in Industrial Engineering and Chemical Engineering courses. The main aims of the new approach were to reduce the high levels of failure and dropout on the module and to make the content match the…

Hubless satellite communications networks

NASA Technical Reports Server (NTRS)

Robinson, Peter Alan

1994-01-01

Frequency Comb Multiple Access (FCMA) is a new combined modulation and multiple access method which will allow cheap hubless Very Small Aperture Terminal (VSAT) networks to be constructed. Theoretical results show bandwidth efficiency and power efficiency improvements over other modulation and multiple access methods. Costs of the VSAT network are reduced dramatically since a hub station is not required.

Topographical maps as complex networks

NASA Astrophysics Data System (ADS)

da Fontoura Costa, Luciano; Diambra, Luis

2005-02-01

The neuronal networks in the mammalian cortex are characterized by the coexistence of hierarchy, modularity, short and long range interactions, spatial correlations, and topographical connections. Particularly interesting, the latter type of organization implies special demands on developing systems in order to achieve precise maps preserving spatial adjacencies, even at the expense of isometry. Although the object of intensive biological research, the elucidation of the main anatomic-functional purposes of the ubiquitous topographical connections in the mammalian brain remains an elusive issue. The present work reports on how recent results from complex network formalism can be used to quantify and model the effect of topographical connections between neuronal cells over the connectivity of the network. While the topographical mapping between two cortical modules is achieved by connecting nearest cells from each module, four kinds of network models are adopted for implementing intramodular connections, including random, preferential-attachment, short-range, and long-range networks. It is shown that, though spatially uniform and simple, topographical connections between modules can lead to major changes in the network properties in some specific cases, depending on intramodular connections schemes, fostering more effective intercommunication between the involved neuronal cells and modules. The possible implications of such effects on cortical operation are discussed.

Multidisciplinary Design Optimization for Aeropropulsion Engines and Solid Modeling/Animation via the Integrated Forced Methods

NASA Technical Reports Server (NTRS)

2004-01-01

The grant closure report is organized in the following four chapters: Chapter describes the two research areas Design optimization and Solid mechanics. Ten journal publications are listed in the second chapter. Five highlights is the subject matter of chapter three. CHAPTER 1. The Design Optimization Test Bed CometBoards. CHAPTER 2. Solid Mechanics: Integrated Force Method of Analysis. CHAPTER 3. Five Highlights: Neural Network and Regression Methods Demonstrated in the Design Optimization of a Subsonic Aircraft. Neural Network and Regression Soft Model Extended for PX-300 Aircraft Engine. Engine with Regression and Neural Network Approximators Designed. Cascade Optimization Strategy with Neural network and Regression Approximations Demonstrated on a Preliminary Aircraft Engine Design. Neural Network and Regression Approximations Used in Aircraft Design.

A software sensor model based on hybrid fuzzy neural network for rapid estimation water quality in Guangzhou section of Pearl River, China.

PubMed

Zhou, Chunshan; Zhang, Chao; Tian, Di; Wang, Ke; Huang, Mingzhi; Liu, Yanbiao

2018-01-02

In order to manage water resources, a software sensor model was designed to estimate water quality using a hybrid fuzzy neural network (FNN) in Guangzhou section of Pearl River, China. The software sensor system was composed of data storage module, fuzzy decision-making module, neural network module and fuzzy reasoning generator module. Fuzzy subtractive clustering was employed to capture the character of model, and optimize network architecture for enhancing network performance. The results indicate that, on basis of available on-line measured variables, the software sensor model can accurately predict water quality according to the relationship between chemical oxygen demand (COD) and dissolved oxygen (DO), pH and NH 4 + -N. Owing to its ability in recognizing time series patterns and non-linear characteristics, the software sensor-based FNN is obviously superior to the traditional neural network model, and its R (correlation coefficient), MAPE (mean absolute percentage error) and RMSE (root mean square error) are 0.8931, 10.9051 and 0.4634, respectively.

Large-Scale Network Analysis of Whole-Brain Resting-State Functional Connectivity in Spinal Cord Injury: A Comparative Study.

PubMed

Kaushal, Mayank; Oni-Orisan, Akinwunmi; Chen, Gang; Li, Wenjun; Leschke, Jack; Ward, Doug; Kalinosky, Benjamin; Budde, Matthew; Schmit, Brian; Li, Shi-Jiang; Muqeet, Vaishnavi; Kurpad, Shekar

2017-09-01

Network analysis based on graph theory depicts the brain as a complex network that allows inspection of overall brain connectivity pattern and calculation of quantifiable network metrics. To date, large-scale network analysis has not been applied to resting-state functional networks in complete spinal cord injury (SCI) patients. To characterize modular reorganization of whole brain into constituent nodes and compare network metrics between SCI and control subjects, fifteen subjects with chronic complete cervical SCI and 15 neurologically intact controls were scanned. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI). Correlation analysis was performed between every ROI pair to construct connectivity matrices and ROIs were categorized into distinct modules. Subsequently, local efficiency (LE) and global efficiency (GE) network metrics were calculated at incremental cost thresholds. The application of a modularity algorithm organized the whole-brain resting-state functional network of the SCI and the control subjects into nine and seven modules, respectively. The individual modules differed across groups in terms of the number and the composition of constituent nodes. LE demonstrated statistically significant decrease at multiple cost levels in SCI subjects. GE did not differ significantly between the two groups. The demonstration of modular architecture in both groups highlights the applicability of large-scale network analysis in studying complex brain networks. Comparing modules across groups revealed differences in number and membership of constituent nodes, indicating modular reorganization due to neural plasticity.

Rapid cell-free forward engineering of novel genetic ring oscillators

PubMed Central

Niederholtmeyer, Henrike; Sun, Zachary Z; Hori, Yutaka; Yeung, Enoch; Verpoorte, Amanda; Murray, Richard M; Maerkl, Sebastian J

2015-01-01

While complex dynamic biological networks control gene expression in all living organisms, the forward engineering of comparable synthetic networks remains challenging. The current paradigm of characterizing synthetic networks in cells results in lengthy design-build-test cycles, minimal data collection, and poor quantitative characterization. Cell-free systems are appealing alternative environments, but it remains questionable whether biological networks behave similarly in cell-free systems and in cells. We characterized in a cell-free system the ‘repressilator’, a three-node synthetic oscillator. We then engineered novel three, four, and five-gene ring architectures, from characterization of circuit components to rapid analysis of complete networks. When implemented in cells, our novel 3-node networks produced population-wide oscillations and 95% of 5-node oscillator cells oscillated for up to 72 hr. Oscillation periods in cells matched the cell-free system results for all networks tested. An alternate forward engineering paradigm using cell-free systems can thus accurately capture cellular behavior. DOI: http://dx.doi.org/10.7554/eLife.09771.001 PMID:26430766

Design and Benchmarking of a Network-In-the-Loop Simulation for Use in a Hardware-In-the-Loop System

NASA Technical Reports Server (NTRS)

Aretskin-Hariton, Eliot; Thomas, George; Culley, Dennis; Kratz, Jonathan

2017-01-01

Distributed engine control (DEC) systems alter aircraft engine design constraints because of fundamental differences in the input and output communication between DEC and centralized control architectures. The change in the way communication is implemented may create new optimum engine-aircraft configurations. This paper continues the exploration of digital network communication by demonstrating a Network-In-the-Loop simulation at the NASA Glenn Research Center. This simulation incorporates a real-time network protocol, the Engine Area Distributed Interconnect Network Lite (EADIN Lite), with the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k) software. The objective of this study is to assess digital control network impact to the control system. Performance is evaluated relative to a truth model for large transient maneuvers and a typical flight profile for commercial aircraft. Results show that a decrease in network bandwidth from 250 Kbps (sampling all sensors every time step) to 40 Kbps, resulted in very small differences in control system performance.

Design and Benchmarking of a Network-In-the-Loop Simulation for Use in a Hardware-In-the-Loop System

NASA Technical Reports Server (NTRS)

Aretskin-Hariton, Eliot D.; Thomas, George Lindsey; Culley, Dennis E.; Kratz, Jonathan L.

2017-01-01

Distributed engine control (DEC) systems alter aircraft engine design constraints be- cause of fundamental differences in the input and output communication between DEC and centralized control architectures. The change in the way communication is implemented may create new optimum engine-aircraft configurations. This paper continues the exploration of digital network communication by demonstrating a Network-In-the-Loop simulation at the NASA Glenn Research Center. This simulation incorporates a real-time network protocol, the Engine Area Distributed Interconnect Network Lite (EADIN Lite), with the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k) software. The objective of this study is to assess digital control network impact to the control system. Performance is evaluated relative to a truth model for large transient maneuvers and a typical flight profile for commercial aircraft. Results show that a decrease in network bandwidth from 250 Kbps (sampling all sensors every time step) to 40 Kbps, resulted in very small differences in control system performance.

The Applied Mathematics for Power Systems (AMPS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chertkov, Michael

2012-07-24

Increased deployment of new technologies, e.g., renewable generation and electric vehicles, is rapidly transforming electrical power networks by crossing previously distinct spatiotemporal scales and invalidating many traditional approaches for designing, analyzing, and operating power grids. This trend is expected to accelerate over the coming years, bringing the disruptive challenge of complexity, but also opportunities to deliver unprecedented efficiency and reliability. Our Applied Mathematics for Power Systems (AMPS) Center will discover, enable, and solve emerging mathematics challenges arising in power systems and, more generally, in complex engineered networks. We will develop foundational applied mathematics resulting in rigorous algorithms and simulation toolboxesmore » for modern and future engineered networks. The AMPS Center deconstruction/reconstruction approach 'deconstructs' complex networks into sub-problems within non-separable spatiotemporal scales, a missing step in 20th century modeling of engineered networks. These sub-problems are addressed within the appropriate AMPS foundational pillar - complex systems, control theory, and optimization theory - and merged or 'reconstructed' at their boundaries into more general mathematical descriptions of complex engineered networks where important new questions are formulated and attacked. These two steps, iterated multiple times, will bridge the growing chasm between the legacy power grid and its future as a complex engineered network.« less

Biologically inspired highly efficient buoyancy engine

NASA Astrophysics Data System (ADS)

Akle, Barbar; Habchi, Wassim; Abdelnour, Rita; Blottman, John, III; Leo, Donald

2012-04-01

Undersea distributed networked sensor systems require a miniaturization of platforms and a means of both spatial and temporal persistence. One aspect of this system is the necessity to modulate sensor depth for optimal positioning and station-keeping. Current approaches involve pneumatic bladders or electrolysis; both require mechanical subsystems and consume significant power. These are not suitable for the miniaturization of sensor platforms. Presented in this study is a novel biologically inspired method that relies on ionic motion and osmotic pressures to displace a volume of water from the ocean into and out of the proposed buoyancy engine. At a constant device volume, the displaced water will alter buoyancy leading to either sinking or floating. The engine is composed of an enclosure sided on the ocean's end by a Nafion ionomer and by a flexible membrane separating the water from a gas enclosure. Two electrodes are placed one inside the enclosure and the other attached to the engine on the outside. The semi-permeable membrane Nafion allows water motion in and out of the enclosure while blocking anions from being transferred. The two electrodes generate local concentration changes of ions upon the application of an electrical field; these changes lead to osmotic pressures and hence the transfer of water through the semi-permeable membrane. Some aquatic organisms such as pelagic crustacean perform this buoyancy control using an exchange of ions through their tissue to modulate its density relative to the ambient sea water. In this paper, the authors provide an experimental proof of concept of this buoyancy engine. The efficiency of changing the engine's buoyancy is calculated and optimized as a function of electrode surface area. For example electrodes made of a 3mm diameter Ag/AgCl proved to transfer approximately 4mm3 of water consuming 4 Joules of electrical energy. The speed of displacement is optimized as a function of the surface area of the Nafion membrane and its thickness. The 4mm3 displaced volume obtained with the Ag/AgCl electrodes required approximately 380 seconds. The thickness of the Nafion membrane is 180μm and it has an area of 133mm3.

Stability and performance of propulsion control systems with distributed control architectures and failures

NASA Astrophysics Data System (ADS)

Belapurkar, Rohit K.

Future aircraft engine control systems will be based on a distributed architecture, in which, the sensors and actuators will be connected to the Full Authority Digital Engine Control (FADEC) through an engine area network. Distributed engine control architecture will allow the implementation of advanced, active control techniques along with achieving weight reduction, improvement in performance and lower life cycle cost. The performance of a distributed engine control system is predominantly dependent on the performance of the communication network. Due to the serial data transmission policy, network-induced time delays and sampling jitter are introduced between the sensor/actuator nodes and the distributed FADEC. Communication network faults and transient node failures may result in data dropouts, which may not only degrade the control system performance but may even destabilize the engine control system. Three different architectures for a turbine engine control system based on a distributed framework are presented. A partially distributed control system for a turbo-shaft engine is designed based on ARINC 825 communication protocol. Stability conditions and control design methodology are developed for the proposed partially distributed turbo-shaft engine control system to guarantee the desired performance under the presence of network-induced time delay and random data loss due to transient sensor/actuator failures. A fault tolerant control design methodology is proposed to benefit from the availability of an additional system bandwidth and from the broadcast feature of the data network. It is shown that a reconfigurable fault tolerant control design can help to reduce the performance degradation in presence of node failures. A T-700 turbo-shaft engine model is used to validate the proposed control methodology based on both single input and multiple-input multiple-output control design techniques.

FMRI connectivity analysis of acupuncture effects on an amygdala-associated brain network

PubMed Central

Qin, Wei; Tian, Jie; Bai, Lijun; Pan, Xiaohong; Yang, Lin; Chen, Peng; Dai, Jianping; Ai, Lin; Zhao, Baixiao; Gong, Qiyong; Wang, Wei; von Deneen, Karen M; Liu, Yijun

2008-01-01

Background Recently, increasing evidence has indicated that the primary acupuncture effects are mediated by the central nervous system. However, specific brain networks underpinning these effects remain unclear. Results In the present study using fMRI, we employed a within-condition interregional covariance analysis method to investigate functional connectivity of brain networks involved in acupuncture. The fMRI experiment was performed before, during and after acupuncture manipulations on healthy volunteers at an acupuncture point, which was previously implicated in a neural pathway for pain modulation. We first identified significant fMRI signal changes during acupuncture stimulation in the left amygdala, which was subsequently selected as a functional reference for connectivity analyses. Our results have demonstrated that there is a brain network associated with the amygdala during a resting condition. This network encompasses the brain structures that are implicated in both pain sensation and pain modulation. We also found that such a pain-related network could be modulated by both verum acupuncture and sham acupuncture. Furthermore, compared with a sham acupuncture, the verum acupuncture induced a higher level of correlations among the amygdala-associated network. Conclusion Our findings indicate that acupuncture may change this amygdala-specific brain network into a functional state that underlies pain perception and pain modulation. PMID:19014532

Performance Parameters Analysis of an XD3P Peugeot Engine Using Artificial Neural Networks (ANN) Concept in MATLAB

NASA Astrophysics Data System (ADS)

Rangaswamy, T.; Vidhyashankar, S.; Madhusudan, M.; Bharath Shekar, H. R.

2015-04-01

The current trends of engineering follow the basic rule of innovation in mechanical engineering aspects. For the engineers to be efficient, problem solving aspects need to be viewed in a multidimensional perspective. One such methodology implemented is the fusion of technologies from other disciplines in order to solve the problems. This paper mainly deals with the application of Neural Networks in order to analyze the performance parameters of an XD3P Peugeot engine (used in Ministry of Defence). The basic propaganda of the work is divided into two main working stages. In the former stage, experimentation of an IC engine is carried out in order to obtain the primary data. In the latter stage the primary database formed is used to design and implement a predictive neural network in order to analyze the output parameters variation with respect to each other. A mathematical governing equation for the neural network is obtained. The obtained polynomial equation describes the characteristic behavior of the built neural network system. Finally, a comparative study of the results is carried out.

Regenerative medicine as applied to solid organ transplantation: current status and future challenges

PubMed Central

Orlando, Giuseppe; Baptista, Pedro; Birchall, Martin; De Coppi, Paolo; Farney, Alan; Guimaraes-Souza, Nadia K.; Opara, Emmanuel; Rogers, Jeffrey; Seliktar, Dror; Shapira-Schweitzer, Keren; Stratta, Robert J.; Atala, Anthony; Wood, Kathryn J.; Soker, Shay

2013-01-01

Summary In the last two decades, regenerative medicine has shown the potential for “bench-to-bedside” translational research in specific clinical settings. Progress made in cell and stem cell biology, material sciences and tissue engineering enabled researchers to develop cutting-edge technology which has lead to the creation of nonmodular tissue constructs such as skin, bladders, vessels and upper airways. In all cases, autologous cells were seeded on either artificial or natural supporting scaffolds. However, such constructs were implanted without the reconstruction of the vascular supply, and the nutrients and oxygen were supplied by diffusion from adjacent tissues. Engineering of modular organs (namely, organs organized in functioning units referred to as modules and requiring the reconstruction of the vascular supply) is more complex and challenging. Models of functioning hearts and livers have been engineered using “natural tissue” scaffolds and efforts are underway to produce kidneys, pancreata and small intestine. Creation of custom-made bioengineered organs, where the cellular component is exquisitely autologous and have an internal vascular network, will theoretically overcome the two major hurdles in transplantation, namely the shortage of organs and the toxicity deriving from lifelong immuno-suppression. This review describes recent advances in the engineering of several key tissues and organs. PMID:21062367

Identifying module biomarkers from gastric cancer by differential correlation network

PubMed Central

Liu, Xiaoping; Chang, Xiao

2016-01-01

Gastric cancer (stomach cancer) is a severe disease caused by dysregulation of many functionally correlated genes or pathways instead of the mutation of individual genes. Systematic identification of gastric cancer biomarkers can provide insights into the mechanisms underlying this deadly disease and help in the development of new drugs. In this paper, we present a novel network-based approach to predict module biomarkers of gastric cancer that can effectively distinguish the disease from normal samples. Specifically, by assuming that gastric cancer has mainly resulted from dysfunction of biomolecular networks rather than individual genes in an organism, the genes in the module biomarkers are potentially related to gastric cancer. Finally, we identified a module biomarker with 27 genes, and by comparing the module biomarker with known gastric cancer biomarkers, we found that our module biomarker exhibited a greater ability to diagnose the samples with gastric cancer. PMID:27703371

Optimal design of reverse osmosis module networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maskan, F.; Wiley, D.E.; Johnston, L.P.M.

2000-05-01

The structure of individual reverse osmosis modules, the configuration of the module network, and the operating conditions were optimized for seawater and brackish water desalination. The system model included simple mathematical equations to predict the performance of the reverse osmosis modules. The optimization problem was formulated as a constrained multivariable nonlinear optimization. The objective function was the annual profit for the system, consisting of the profit obtained from the permeate, capital cost for the process units, and operating costs associated with energy consumption and maintenance. Optimization of several dual-stage reverse osmosis systems were investigated and compared. It was found thatmore » optimal network designs are the ones that produce the most permeate. It may be possible to achieve economic improvements by refining current membrane module designs and their operating pressures.« less

Phonological experience modulates voice discrimination: Evidence from functional brain networks analysis.

PubMed

Hu, Xueping; Wang, Xiangpeng; Gu, Yan; Luo, Pei; Yin, Shouhang; Wang, Lijun; Fu, Chao; Qiao, Lei; Du, Yi; Chen, Antao

2017-10-01

Numerous behavioral studies have found a modulation effect of phonological experience on voice discrimination. However, the neural substrates underpinning this phenomenon are poorly understood. Here we manipulated language familiarity to test the hypothesis that phonological experience affects voice discrimination via mediating the engagement of multiple perceptual and cognitive resources. The results showed that during voice discrimination, the activation of several prefrontal regions was modulated by language familiarity. More importantly, the same effect was observed concerning the functional connectivity from the fronto-parietal network to the voice-identity network (VIN), and from the default mode network to the VIN. Our findings indicate that phonological experience could bias the recruitment of cognitive control and information retrieval/comparison processes during voice discrimination. Therefore, the study unravels the neural substrates subserving the modulation effect of phonological experience on voice discrimination, and provides new insights into studying voice discrimination from the perspective of network interactions. Copyright © 2017. Published by Elsevier Inc.

Resilience of networks formed of interdependent modular networks

NASA Astrophysics Data System (ADS)

Shekhtman, Louis M.; Shai, Saray; Havlin, Shlomo

2015-12-01

Many infrastructure networks have a modular structure and are also interdependent with other infrastructures. While significant research has explored the resilience of interdependent networks, there has been no analysis of the effects of modularity. Here we develop a theoretical framework for attacks on interdependent modular networks and support our results through simulations. We focus, for simplicity, on the case where each network has the same number of communities and the dependency links are restricted to be between pairs of communities of different networks. This is particularly realistic for modeling infrastructure across cities. Each city has its own infrastructures and different infrastructures are dependent only within the city. However, each infrastructure is connected within and between cities. For example, a power grid will connect many cities as will a communication network, yet a power station and communication tower that are interdependent will likely be in the same city. It has previously been shown that single networks are very susceptible to the failure of the interconnected nodes (between communities) (Shai et al 2014 arXiv:1404.4748) and that attacks on these nodes are even more crippling than attacks based on betweenness (da Cunha et al 2015 arXiv:1502.00353). In our example of cities these nodes have long range links which are more likely to fail. For both treelike and looplike interdependent modular networks we find distinct regimes depending on the number of modules, m. (i) In the case where there are fewer modules with strong intraconnections, the system first separates into modules in an abrupt first-order transition and then each module undergoes a second percolation transition. (ii) When there are more modules with many interconnections between them, the system undergoes a single transition. Overall, we find that modular structure can significantly influence the type of transitions observed in interdependent networks and should be considered in attempts to make interdependent networks more resilient.

A Synthetic Fibrin-Crosslinking Polymer for Modulating Clot Properties and Inducing Hemostasis

PubMed Central

Chan, Leslie W.-G.; Wang, Xu; Wei, Hua; Pozzo, Lilo D.; White, Nathan J.; Pun, Suzie H.

2015-01-01

Clotting factor replacement is the standard management of acute bleeding in congenital and acquired bleeding disorders. We present a synthetic approach to hemostasis using an engineered hemostatic polymer (PolySTAT) that circulates innocuously in the blood, identifies sites of vascular injury, and promotes clot formation to stop bleeding. PolySTAT induces hemostasis by crosslinking the fibrin matrix within clots, mimicking the function of the transglutaminase Factor XIII. Furthermore, synthetic PolySTAT binds specifically to fibrin monomers and is uniformly integrated into fibrin fibers during fibrin polymerization, resulting in a fortified, hybrid polymer network with enhanced resistance to enzymatic degradation. In vivo hemostatic activity was confirmed in a rat model of trauma and fluid resuscitation in which intravenous administration of PolySTAT improved survival by reducing blood loss and resuscitation fluid requirements. PolySTAT-induced fibrin crosslinking is a novel approach to hemostasis utilizing synthetic polymers for non-invasive modulation of clot architecture with potentially wide-ranging therapeutic applications. PMID:25739763

A parallel implementation of the network identification by multiple regression (NIR) algorithm to reverse-engineer regulatory gene networks.

PubMed

Gregoretti, Francesco; Belcastro, Vincenzo; di Bernardo, Diego; Oliva, Gennaro

2010-04-21

The reverse engineering of gene regulatory networks using gene expression profile data has become crucial to gain novel biological knowledge. Large amounts of data that need to be analyzed are currently being produced due to advances in microarray technologies. Using current reverse engineering algorithms to analyze large data sets can be very computational-intensive. These emerging computational requirements can be met using parallel computing techniques. It has been shown that the Network Identification by multiple Regression (NIR) algorithm performs better than the other ready-to-use reverse engineering software. However it cannot be used with large networks with thousands of nodes--as is the case in biological networks--due to the high time and space complexity. In this work we overcome this limitation by designing and developing a parallel version of the NIR algorithm. The new implementation of the algorithm reaches a very good accuracy even for large gene networks, improving our understanding of the gene regulatory networks that is crucial for a wide range of biomedical applications.

Modular architecture for robotics and teleoperation

DOEpatents

Anderson, Robert J.

1996-12-03

Systems and methods for modularization and discretization of real-time robot, telerobot and teleoperation systems using passive, network based control laws. Modules consist of network one-ports and two-ports. Wave variables and position information are passed between modules. The behavior of each module is decomposed into uncoupled linear-time-invariant, and coupled, nonlinear memoryless elements and then are separately discretized.

Design of robotic cells based on relative handling modules with use of SolidWorks system

NASA Astrophysics Data System (ADS)

Gaponenko, E. V.; Anciferov, S. I.

2018-05-01

The article presents a diagramed engineering solution for a robotic cell with six degrees of freedom for machining of complex details, consisting of the base with a tool installation module and a detail machining module made as parallel structure mechanisms. The output links of the detail machining module and the tool installation module can move along X-Y-Z coordinate axes each. A 3D-model of the complex is designed in the SolidWorks system. It will be used further for carrying out engineering calculations and mathematical analysis and obtaining all required documentation.

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT XXIII, I--MAINTAINING THE FUEL SYSTEM, PART II--CATERPILLAR DIESEL ENGINE, II--UNDERSTANDING STEERING SYSTEMS.

ERIC Educational Resources Information Center

Minnesota State Dept. of Education, St. Paul. Div. of Vocational and Technical Education.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF THE OPERATION AND MAINTENANCE OF THE DIESEL ENGINE FUEL INJECTION SYSTEM AND THE STEERING SYSTEM OF DIESEL POWERED VEHICLES. TOPICS ARE FUEL INJECTION SECTION, AND DESCRIPTION OF THE STEERING SYSTEM. THE MODULE CONSISTS OF A SELF-INSTRUCTIONAL BRANCH PROGRAMED TRAINING…

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT II, MAINTAINING THE AIR SYSTEM--DETROIT DIESEL ENGINES.

ERIC Educational Resources Information Center

Human Engineering Inst., Cleveland, OH.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF THE OPERATION AND MAINTENANCE OF THE DIESEL ENGINE AIR SYSTEM. TOPICS ARE (1) OPERATION AND FUNCTION, (2) AIR CLEANER, (3) AIR SHUT-DOWN HOUSING, (4) EXHAUST SYSTEM, (5) BLOWER, (6) TURBOCHARGER, AND (7) TROUBLE-SHOOTING TIPS ON THE AIR SYSTEM. THE MODULE CONSISTS OF A…

Development of Power Supply Management Module for Radio Signal Repeaters of Automatic Metering Reading System in Variable Solar Density Conditions

NASA Astrophysics Data System (ADS)

Kondratjevs, K.; Zabasta, A.; Selmanovs-Pless, V.

2016-02-01

In recent years, there has been significant research focus that revolves around harvesting and minimising energy consumption by wireless sensor network nodes. When a sensor node is depleted of energy, it becomes unresponsive and disconnected from the network that can significantly influence the performance of the whole network. The purpose of the present research is to create a power supply management module in order to provide stable operating voltage for autonomous operations of radio signal repeaters, sensors or gateways of WSN. The developed management module is composed of a solar panel, lithium battery and power supply management module. The novelty of the research is the management module, which ensures stable and uninterrupted operations of electronic equipment in various power supply modes in different situations, simultaneously ensuring energy protection and sustainability of the module components. The management module is able to provide power supply of 5 V for electronics scheme independently, without power interruption switching between power sources and power flows in different directions.

Apparatus, system and method for providing cryptographic key information with physically unclonable function circuitry

DOEpatents

Areno, Matthew

2015-12-08

Techniques and mechanisms for providing a value from physically unclonable function (PUF) circuitry for a cryptographic operation of a security module. In an embodiment, a cryptographic engine receives a value from PUF circuitry and based on the value, outputs a result of a cryptographic operation to a bus of the security module. The bus couples the cryptographic engine to control logic or interface logic of the security module. In another embodiment, the value is provided to the cryptographic engine from the PUF circuitry via a signal line which is distinct from the bus, where any exchange of the value by either of the cryptographic engine and the PUF circuitry is for communication of the first value independent of the bus.

Speed And Power Control Of An Engine By Modulation Of The Load Torque

DOEpatents

Ziph, Benjamin; Strodtman, Scott; Rose, Thomas K

1999-01-26

A system and method of speed and power control for an engine in which speed and power of the engine is controlled by modulation of the load torque. The load torque is manipulated in order to cause engine speed, and hence power to be changed. To accomplish such control, the load torque undergoes a temporary excursion in the opposite direction of the desired speed and power change. The engine and the driven equipment will accelerate or decelerate accordingly as the load torque is decreased or increased, relative to the essentially fixed or constant engine torque. As the engine accelerates or decelerates, its power increases or decreases in proportion.

Design of Distributed Engine Control Systems with Uncertain Delay.

PubMed

Liu, Xiaofeng; Li, Yanxi; Sun, Xu

Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) is dependent on the network performance. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS). Typical turboshaft engine-distributed controllers are designed based on the NCCS framework with a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method.

Design of Distributed Engine Control Systems with Uncertain Delay

PubMed Central

Li, Yanxi; Sun, Xu

2016-01-01

Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) is dependent on the network performance. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS). Typical turboshaft engine-distributed controllers are designed based on the NCCS framework with a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method. PMID:27669005

A synthetic mammalian electro-genetic transcription circuit.

PubMed

Weber, Wilfried; Luzi, Stefan; Karlsson, Maria; Sanchez-Bustamante, Carlota Diaz; Frey, Urs; Hierlemann, Andreas; Fussenegger, Martin

2009-03-01

Electric signal processing has evolved to manage rapid information transfer in neuronal networks and muscular contraction in multicellular organisms and controls the most sophisticated man-built devices. Using a synthetic biology approach to assemble electronic parts with genetic control units engineered into mammalian cells, we designed an electric power-adjustable transcription control circuit able to integrate the intensity of a direct current over time, to translate the amplitude or frequency of an alternating current into an adjustable genetic readout or to modulate the beating frequency of primary heart cells. Successful miniaturization of the electro-genetic devices may pave the way for the design of novel hybrid electro-genetic implants assembled from electronic and genetic parts.

A synthetic mammalian electro-genetic transcription circuit

PubMed Central

Weber, Wilfried; Luzi, Stefan; Karlsson, Maria; Sanchez-Bustamante, Carlota Diaz; Frey, Urs; Hierlemann, Andreas; Fussenegger, Martin

2009-01-01

Electric signal processing has evolved to manage rapid information transfer in neuronal networks and muscular contraction in multicellular organisms and controls the most sophisticated man-built devices. Using a synthetic biology approach to assemble electronic parts with genetic control units engineered into mammalian cells, we designed an electric power-adjustable transcription control circuit able to integrate the intensity of a direct current over time, to translate the amplitude or frequency of an alternating current into an adjustable genetic readout or to modulate the beating frequency of primary heart cells. Successful miniaturization of the electro-genetic devices may pave the way for the design of novel hybrid electro-genetic implants assembled from electronic and genetic parts. PMID:19190091

A Legal Negotiatiton Support System Based on A Diagram

NASA Astrophysics Data System (ADS)

Nitta, Katsumi; Shibasaki, Masato; Yasumura, Yoshiaki; Hasegawa, Ryuzo; Fujita, Hiroshi; Koshimura, Miyuki; Inoue, Katsumi; Shirai, Yasuyuki; Komatsu, Hiroshi

We present an overview of a legal negotiation support system, ANS (Argumentation based Negotiation support System). ANS consists of a user interface, three inference engines, a database of old cases, and two decision support modules. The ANS users negotiates or disputes with others via a computer network. The negotiation status is managed in the form of the negotiation diagram. The negotiation diagram is an extension of Toulmin’s argument diagram, and it contains all arguments insisted by participants. The negotiation protocols are defined as operations to the negotiation diagram. By exchanging counter arguments each other, the negotiation diagram grows up. Nonmonotonic reasoning using rule priorities are applied to the negotiation diagram.

Terahertz wireless communications based on photonics technologies.

PubMed

Nagatsuma, Tadao; Horiguchi, Shogo; Minamikata, Yusuke; Yoshimizu, Yasuyuki; Hisatake, Shintaro; Kuwano, Shigeru; Yoshimoto, Naoto; Terada, Jun; Takahashi, Hiroyuki

2013-10-07

There has been an increasing interest in the application of terahertz (THz) waves to broadband wireless communications. In particular, use of frequencies above 275 GHz is one of the strong concerns among radio scientists and engineers, because these frequency bands have not yet been allocated at specific active services, and there is a possibility to employ extremely large bandwidths for ultra-broadband wireless communications. Introduction of photonics technologies for signal generation, modulation and detection is effective not only to enhance the bandwidth and/or the data rate, but also to combine fiber-optic (wired) and wireless networks. This paper reviews recent progress in THz wireless communications using telecom-based photonics technologies towards 100 Gbit/s.

Protocol vulnerability detection based on network traffic analysis and binary reverse engineering.

PubMed

Wen, Shameng; Meng, Qingkun; Feng, Chao; Tang, Chaojing

2017-01-01

Network protocol vulnerability detection plays an important role in many domains, including protocol security analysis, application security, and network intrusion detection. In this study, by analyzing the general fuzzing method of network protocols, we propose a novel approach that combines network traffic analysis with the binary reverse engineering method. For network traffic analysis, the block-based protocol description language is introduced to construct test scripts, while the binary reverse engineering method employs the genetic algorithm with a fitness function designed to focus on code coverage. This combination leads to a substantial improvement in fuzz testing for network protocols. We build a prototype system and use it to test several real-world network protocol implementations. The experimental results show that the proposed approach detects vulnerabilities more efficiently and effectively than general fuzzing methods such as SPIKE.

A bio-inspired system for spatio-temporal recognition in static and video imagery

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Moore, Christopher K.; Chelian, Suhas

2007-04-01

This paper presents a bio-inspired method for spatio-temporal recognition in static and video imagery. It builds upon and extends our previous work on a bio-inspired Visual Attention and object Recognition System (VARS). The VARS approach locates and recognizes objects in a single frame. This work presents two extensions of VARS. The first extension is a Scene Recognition Engine (SCE) that learns to recognize spatial relationships between objects that compose a particular scene category in static imagery. This could be used for recognizing the category of a scene, e.g., office vs. kitchen scene. The second extension is the Event Recognition Engine (ERE) that recognizes spatio-temporal sequences or events in sequences. This extension uses a working memory model to recognize events and behaviors in video imagery by maintaining and recognizing ordered spatio-temporal sequences. The working memory model is based on an ARTSTORE1 neural network that combines an ART-based neural network with a cascade of sustained temporal order recurrent (STORE)1 neural networks. A series of Default ARTMAP classifiers ascribes event labels to these sequences. Our preliminary studies have shown that this extension is robust to variations in an object's motion profile. We evaluated the performance of the SCE and ERE on real datasets. The SCE module was tested on a visual scene classification task using the LabelMe2 dataset. The ERE was tested on real world video footage of vehicles and pedestrians in a street scene. Our system is able to recognize the events in this footage involving vehicles and pedestrians.

Integrative Analysis of Many Weighted Co-Expression Networks Using Tensor Computation

PubMed Central

Li, Wenyuan; Liu, Chun-Chi; Zhang, Tong; Li, Haifeng; Waterman, Michael S.; Zhou, Xianghong Jasmine

2011-01-01

The rapid accumulation of biological networks poses new challenges and calls for powerful integrative analysis tools. Most existing methods capable of simultaneously analyzing a large number of networks were primarily designed for unweighted networks, and cannot easily be extended to weighted networks. However, it is known that transforming weighted into unweighted networks by dichotomizing the edges of weighted networks with a threshold generally leads to information loss. We have developed a novel, tensor-based computational framework for mining recurrent heavy subgraphs in a large set of massive weighted networks. Specifically, we formulate the recurrent heavy subgraph identification problem as a heavy 3D subtensor discovery problem with sparse constraints. We describe an effective approach to solving this problem by designing a multi-stage, convex relaxation protocol, and a non-uniform edge sampling technique. We applied our method to 130 co-expression networks, and identified 11,394 recurrent heavy subgraphs, grouped into 2,810 families. We demonstrated that the identified subgraphs represent meaningful biological modules by validating against a large set of compiled biological knowledge bases. We also showed that the likelihood for a heavy subgraph to be meaningful increases significantly with its recurrence in multiple networks, highlighting the importance of the integrative approach to biological network analysis. Moreover, our approach based on weighted graphs detects many patterns that would be overlooked using unweighted graphs. In addition, we identified a large number of modules that occur predominately under specific phenotypes. This analysis resulted in a genome-wide mapping of gene network modules onto the phenome. Finally, by comparing module activities across many datasets, we discovered high-order dynamic cooperativeness in protein complex networks and transcriptional regulatory networks. PMID:21698123

Handheld portable real-time tracking and communications device

DOEpatents

Wiseman, James M [Albuquerque, NM; Riblett, Jr., Loren E.; Green, Karl L [Albuquerque, NM; Hunter, John A [Albuquerque, NM; Cook, III, Robert N.; Stevens, James R [Arlington, VA

2012-05-22

Portable handheld real-time tracking and communications devices include; a controller module, communications module including global positioning and mesh network radio module, data transfer and storage module, and a user interface module enclosed in a water-resistant enclosure. Real-time tracking and communications devices can be used by protective force, security and first responder personnel to provide situational awareness allowing for enhance coordination and effectiveness in rapid response situations. Such devices communicate to other authorized devices via mobile ad-hoc wireless networks, and do not require fixed infrastructure for their operation.

Analysing the Correlation between Social Network Analysis Measures and Performance of Students in Social Network-Based Engineering Education

ERIC Educational Resources Information Center

Putnik, Goran; Costa, Eric; Alves, Cátia; Castro, Hélio; Varela, Leonilde; Shah, Vaibhav

2016-01-01

Social network-based engineering education (SNEE) is designed and implemented as a model of Education 3.0 paradigm. SNEE represents a new learning methodology, which is based on the concept of social networks and represents an extended model of project-led education. The concept of social networks was applied in the real-life experiment,…

Airborne Network Optimization with Dynamic Network Update

DTIC Science & Technology

2015-03-26

Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and Management Air Force Institute of Technology Air University...Member Dr. Barry E. Mullins Member AFIT-ENG-MS-15-M-030 Abstract Modern networks employ congestion and routing management algorithms that can perform...airborne networks. Intelligent agents can make use of Kalman filter predictions to make informed decisions to manage communication in airborne networks. The

Technology Requirements and Development for Affordable High-Temperature Distributed Engine Controls

DTIC Science & Technology

2012-06-04

long lasting, high temperature modules is to use high temperature electronics on ceramic modules. The electronic components are “ brazed ” onto the...Copyright © 2012 by ISA Technology Requirements and Development for Affordable High - Temperature Distributed Engine Controls Alireza Behbahani 1...with regards to high temperature capability. The Government and Industry Distributed Engine Controls Working Group (DECWG) [5] has been established

The University of Michigan's Computer-Aided Engineering Network.

ERIC Educational Resources Information Center

Atkins, D. E.; Olsen, Leslie A.

1986-01-01

Presents an overview of the Computer-Aided Engineering Network (CAEN) of the University of Michigan. Describes its arrangement of workstations, communication networks, and servers. Outlines the factors considered in hardware and software decision making. Reviews the program's impact on students. (ML)

Engineering Translational Activators with CRISPR-Cas System.

PubMed

Du, Pei; Miao, Chensi; Lou, Qiuli; Wang, Zefeng; Lou, Chunbo

2016-01-15

RNA parts often serve as critical components in genetic engineering. Here we report a design of translational activators which is composed of an RNA endoribonuclease (Csy4) and two exchangeable RNA modules. Csy4, a member of Cas endoribonuclease, cleaves at a specific recognition site; this cleavage releases a cis-repressive RNA module (crRNA) from the masked ribosome binding site (RBS), which subsequently allows the downstream translation initiation. Unlike small RNA as a translational activator, the endoribonuclease-based activator is able to efficiently unfold the perfect RBS-crRNA pairing. As an exchangeable module, the crRNA-RBS duplex was forwardly and reversely engineered to modulate the dynamic range of translational activity. We further showed that Csy4 and its recognition site, together as a module, can also be replaced by orthogonal endoribonuclease-recognition site homologues. These modularly structured, high-performance translational activators would endow the programming of gene expression in the translation level with higher feasibility.

A Network-Based Classification Model for Deriving Novel Drug-Disease Associations and Assessing Their Molecular Actions

PubMed Central

Oh, Min; Ahn, Jaegyoon; Yoon, Youngmi

2014-01-01

The growing number and variety of genetic network datasets increases the feasibility of understanding how drugs and diseases are associated at the molecular level. Properly selected features of the network representations of existing drug-disease associations can be used to infer novel indications of existing drugs. To find new drug-disease associations, we generated an integrative genetic network using combinations of interactions, including protein-protein interactions and gene regulatory network datasets. Within this network, network adjacencies of drug-drug and disease-disease were quantified using a scored path between target sets of them. Furthermore, the common topological module of drugs or diseases was extracted, and thereby the distance between topological drug-module and disease (or disease-module and drug) was quantified. These quantified scores were used as features for the prediction of novel drug-disease associations. Our classifiers using Random Forest, Multilayer Perceptron and C4.5 showed a high specificity and sensitivity (AUC score of 0.855, 0.828 and 0.797 respectively) in predicting novel drug indications, and displayed a better performance than other methods with limited drug and disease properties. Our predictions and current clinical trials overlap significantly across the different phases of drug development. We also identified and visualized the topological modules of predicted drug indications for certain types of cancers, and for Alzheimer’s disease. Within the network, those modules show potential pathways that illustrate the mechanisms of new drug indications, including propranolol as a potential anticancer agent and telmisartan as treatment for Alzheimer’s disease. PMID:25356910

Molecular Correlates of Cortical Network Modulation by Long-Term Sensory Experience in the Adult Rat Barrel Cortex

ERIC Educational Resources Information Center

Vallès, Astrid; Granic, Ivica; De Weerd, Peter; Martens, Gerard J. M.

2014-01-01

Modulation of cortical network connectivity is crucial for an adaptive response to experience. In the rat barrel cortex, long-term sensory stimulation induces cortical network modifications and neuronal response changes of which the molecular basis is unknown. Here, we show that long-term somatosensory stimulation by enriched environment…

Multichip module technology for automotive application

NASA Astrophysics Data System (ADS)

Johnson, R. Wayne; Evans, John L.; Bosley, Larry

1995-01-01

Advancements in multichip module technology are creating design freedoms previously unavailable to design engineers. These advancements are opening new markets for laminate based multichip module products. In particular, material improvements in laminate printed wiring boards are allowing multichip module technology to meet more stringent environmental conditions. In addition, improvements in encapsulants and adhesives are enhancing the capabilities of multichip module technology to meet harsh environment. Furthermore, improvements in manufacturing techniques are providing the reliability improvements necessary for use in high quality electronic systems. These advances are making multichip module technology viable for high volume, harsh environment applications like under-the-hood automotive electronics. This paper will provide a brief review of multichip module technology, a discussion of specific research activities with Chrysler for use of multichip modules in automotive engine controllers and finally a discussion of prototype multichip modules fabricated and tested.

Computational Tools for Metabolic Engineering

PubMed Central

Copeland, Wilbert B.; Bartley, Bryan A.; Chandran, Deepak; Galdzicki, Michal; Kim, Kyung H.; Sleight, Sean C.; Maranas, Costas D.; Sauro, Herbert M.

2012-01-01

A great variety of software applications are now employed in the metabolic engineering field. These applications have been created to support a wide range of experimental and analysis techniques. Computational tools are utilized throughout the metabolic engineering workflow to extract and interpret relevant information from large data sets, to present complex models in a more manageable form, and to propose efficient network design strategies. In this review, we present a number of tools that can assist in modifying and understanding cellular metabolic networks. The review covers seven areas of relevance to metabolic engineers. These include metabolic reconstruction efforts, network visualization, nucleic acid and protein engineering, metabolic flux analysis, pathway prospecting, post-structural network analysis and culture optimization. The list of available tools is extensive and we can only highlight a small, representative portion of the tools from each area. PMID:22629572

Integrated Engineering Information Technology, FY93 accommplishments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, R.N.; Miller, D.K.; Neugebauer, G.L.

1994-03-01

The Integrated Engineering Information Technology (IEIT) project is providing a comprehensive, easy-to-use computer network solution or communicating with coworkers both inside and outside Sandia National Laboratories. IEIT capabilities include computer networking, electronic mail, mechanical design, and data management. These network-based tools have one fundamental purpose: to help create a concurrent engineering environment that will enable Sandia organizations to excel in today`s increasingly competitive business environment.

Implementation of quantum key distribution network simulation module in the network simulator NS-3

NASA Astrophysics Data System (ADS)

Mehic, Miralem; Maurhart, Oliver; Rass, Stefan; Voznak, Miroslav

2017-10-01

As the research in quantum key distribution (QKD) technology grows larger and becomes more complex, the need for highly accurate and scalable simulation technologies becomes important to assess the practical feasibility and foresee difficulties in the practical implementation of theoretical achievements. Due to the specificity of the QKD link which requires optical and Internet connection between the network nodes, to deploy a complete testbed containing multiple network hosts and links to validate and verify a certain network algorithm or protocol would be very costly. Network simulators in these circumstances save vast amounts of money and time in accomplishing such a task. The simulation environment offers the creation of complex network topologies, a high degree of control and repeatable experiments, which in turn allows researchers to conduct experiments and confirm their results. In this paper, we described the design of the QKD network simulation module which was developed in the network simulator of version 3 (NS-3). The module supports simulation of the QKD network in an overlay mode or in a single TCP/IP mode. Therefore, it can be used to simulate other network technologies regardless of QKD.

Differential network as an indicator of osteoporosis with network entropy.

PubMed

Ma, Lili; Du, Hongmei; Chen, Guangdong

2018-07-01

Osteoporosis is a common skeletal disorder characterized by a decrease in bone mass and density. The peak bone mass (PBM) is a significant determinant of osteoporosis. To gain insights into the indicating effect of PBM to osteoporosis, this study focused on characterizing the PBM networks and identifying key genes. One biological data set with 12 monocyte low PBM samples and 11 high PBM samples was derived to construct protein-protein interaction networks (PPINs). Based on clique-merging, module-identification algorithm was used to identify modules from PPINs. The systematic calculation and comparison were performed to test whether the network entropy can discriminate the low PBM network from high PBM network. We constructed 32 destination networks with 66 modules divided from monocyte low and high PBM networks. Among them, network 11 was the only significantly differential one (P<0.05) with 8 nodes and 28 edges. All genes belonged to precursors of osteoclasts, which were related to calcium transport as well as blood monocytes. In conclusion, based on the entropy in PBM PPINs, the differential network appears to be a novel therapeutic indicator for osteoporosis during the bone monocyte progression; these findings are helpful in disclosing the pathogenetic mechanisms of osteoporosis.

Prospects of engineering thermotolerance in crops through modulation of heat stress transcription factor and heat shock protein networks.

PubMed

Fragkostefanakis, Sotirios; Röth, Sascha; Schleiff, Enrico; Scharf, Klaus-Dieter

2015-09-01

Cell survival under high temperature conditions involves the activation of heat stress response (HSR), which in principle is highly conserved among different organisms, but shows remarkable complexity and unique features in plant systems. The transcriptional reprogramming at higher temperatures is controlled by the activity of the heat stress transcription factors (Hsfs). Hsfs allow the transcriptional activation of HSR genes, among which heat shock proteins (Hsps) are best characterized. Hsps belong to multigene families encoding for molecular chaperones involved in various processes including maintenance of protein homeostasis as a requisite for optimal development and survival under stress conditions. Hsfs form complex networks to activate downstream responses, but are concomitantly subjected to cell-type-dependent feedback regulation through factor-specific physical and functional interactions with chaperones belonging to Hsp90, Hsp70 and small Hsp families. There is increasing evidence that the originally assumed specialized function of Hsf/chaperone networks in the HSR turns out to be a complex central stress response system that is involved in the regulation of a broad variety of other stress responses and may also have substantial impact on various developmental processes. Understanding in detail the function of such regulatory networks is prerequisite for sustained improvement of thermotolerance in important agricultural crops. © 2014 John Wiley & Sons Ltd.

Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens

PubMed Central

Chasman, Deborah; Walters, Kevin B.; Lopes, Tiago J. S.; Eisfeld, Amie J.; Kawaoka, Yoshihiro; Roy, Sushmita

2016-01-01

Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection. PMID:27403523

Research on virtual network load balancing based on OpenFlow

NASA Astrophysics Data System (ADS)

Peng, Rong; Ding, Lei

2017-08-01

The Network based on OpenFlow technology separate the control module and data forwarding module. Global deployment of load balancing strategy through network view of control plane is fast and of high efficiency. This paper proposes a Weighted Round-Robin Scheduling algorithm for virtual network and a load balancing plan for server load based on OpenFlow. Load of service nodes and load balancing tasks distribution algorithm will be taken into account.

Bringing simulation to engineers in the field: a Web 2.0 approach.

PubMed

Haines, Robert; Khan, Kashif; Brooke, John

2009-07-13

Field engineers working on water distribution systems have to implement day-to-day operational decisions. Since pipe networks are highly interconnected, the effects of such decisions are correlated with hydraulic and water quality conditions elsewhere in the network. This makes the provision of predictive decision support tools (DSTs) for field engineers critical to optimizing the engineering work on the network. We describe how we created DSTs to run on lightweight mobile devices by using the Web 2.0 technique known as Software as a Service. We designed our system following the architectural style of representational state transfer. The system not only displays static geographical information system data for pipe networks, but also dynamic information and prediction of network state, by invoking and displaying the results of simulations running on more powerful remote resources.

Submillisecond-response polymer network liquid crystal phase modulators at 1.06-μm wavelength

NASA Astrophysics Data System (ADS)

Sun, Jie; Xianyu, Haiqing; Chen, Yuan; Wu, Shin-Tson

2011-07-01

A fast-response and scattering-free polymer network liquid crystal (PNLC) light modulator is demonstrated at λ = 1.06 μm wavelength. A decay time of 117 μs for 2π phase modulation is obtained at 70 °C, which is ˜ 650 × faster than that of the host nematic LCs. The major tradeoff is the increased operating voltage. Potential applications include spatial light modulators and adaptive optics.

NRL Fact Book

DTIC Science & Technology

2002-11-01

CRADAs) under which NRL scientists and engineers work together with industry , academia, state or local governments, or other Federal agencies to... industrial hygiene, and environ- mental safety. The Division provides engineering and technical assistance to research divisions in the installation...The NRL Women in Science and Engineer - ing (WISE) Network is an open-membership network group of scientists and engineers who meet periodically to

Network analysis reveals that bacteria and fungi form modules that correlate independently with soil parameters.

PubMed

de Menezes, Alexandre B; Prendergast-Miller, Miranda T; Richardson, Alan E; Toscas, Peter; Farrell, Mark; Macdonald, Lynne M; Baker, Geoff; Wark, Tim; Thrall, Peter H

2015-08-01

Network and multivariate statistical analyses were performed to determine interactions between bacterial and fungal community terminal restriction length polymorphisms as well as soil properties in paired woodland and pasture sites. Canonical correspondence analysis (CCA) revealed that shifts in woodland community composition correlated with soil dissolved organic carbon, while changes in pasture community composition correlated with moisture, nitrogen and phosphorus. Weighted correlation network analysis detected two distinct microbial modules per land use. Bacterial and fungal ribotypes did not group separately, rather all modules comprised of both bacterial and fungal ribotypes. Woodland modules had a similar fungal : bacterial ribotype ratio, while in the pasture, one module was fungal dominated. There was no correspondence between pasture and woodland modules in their ribotype composition. The modules had different relationships to soil variables, and these contrasts were not detected without the use of network analysis. This study demonstrated that fungi and bacteria, components of the soil microbial communities usually treated as separate functional groups as in a CCA approach, were co-correlated and formed distinct associations in these adjacent habitats. Understanding these distinct modular associations may shed more light on their niche space in the soil environment, and allow a more realistic description of soil microbial ecology and function. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

CommWalker: correctly evaluating modules in molecular networks in light of annotation bias.

PubMed

Luecken, M D; Page, M J T; Crosby, A J; Mason, S; Reinert, G; Deane, C M

2018-03-15

Detecting novel functional modules in molecular networks is an important step in biological research. In the absence of gold standard functional modules, functional annotations are often used to verify whether detected modules/communities have biological meaning. However, as we show, the uneven distribution of functional annotations means that such evaluation methods favor communities of well-studied proteins. We propose a novel framework for the evaluation of communities as functional modules. Our proposed framework, CommWalker, takes communities as inputs and evaluates them in their local network environment by performing short random walks. We test CommWalker's ability to overcome annotation bias using input communities from four community detection methods on two protein interaction networks. We find that modules accepted by CommWalker are similarly co-expressed as those accepted by current methods. Crucially, CommWalker performs well not only in well-annotated regions, but also in regions otherwise obscured by poor annotation. CommWalker community prioritization both faithfully captures well-validated communities and identifies functional modules that may correspond to more novel biology. The CommWalker algorithm is freely available at opig.stats.ox.ac.uk/resources or as a docker image on the Docker Hub at hub.docker.com/r/lueckenmd/commwalker/. deane@stats.ox.ac.uk. Supplementary data are available at Bioinformatics online.

Differential network analysis reveals the genome-wide landscape of estrogen receptor modulation in hormonal cancers

PubMed Central

Hsiao, Tzu-Hung; Chiu, Yu-Chiao; Hsu, Pei-Yin; Lu, Tzu-Pin; Lai, Liang-Chuan; Tsai, Mong-Hsun; Huang, Tim H.-M.; Chuang, Eric Y.; Chen, Yidong

2016-01-01

Several mutual information (MI)-based algorithms have been developed to identify dynamic gene-gene and function-function interactions governed by key modulators (genes, proteins, etc.). Due to intensive computation, however, these methods rely heavily on prior knowledge and are limited in genome-wide analysis. We present the modulated gene/gene set interaction (MAGIC) analysis to systematically identify genome-wide modulation of interaction networks. Based on a novel statistical test employing conjugate Fisher transformations of correlation coefficients, MAGIC features fast computation and adaption to variations of clinical cohorts. In simulated datasets MAGIC achieved greatly improved computation efficiency and overall superior performance than the MI-based method. We applied MAGIC to construct the estrogen receptor (ER) modulated gene and gene set (representing biological function) interaction networks in breast cancer. Several novel interaction hubs and functional interactions were discovered. ER+ dependent interaction between TGFβ and NFκB was further shown to be associated with patient survival. The findings were verified in independent datasets. Using MAGIC, we also assessed the essential roles of ER modulation in another hormonal cancer, ovarian cancer. Overall, MAGIC is a systematic framework for comprehensively identifying and constructing the modulated interaction networks in a whole-genome landscape. MATLAB implementation of MAGIC is available for academic uses at https://github.com/chiuyc/MAGIC. PMID:26972162

Development of engineering prototype of Life Support Module (LSM)

NASA Technical Reports Server (NTRS)

1984-01-01

The development of an engineering prototype of a life support system is discussed. The module consists of an electrocardiogram, a defibrillator, a resuscitator, and an aspirator, as well as body temperature and blood pressure measuring instruments. A drug kit is included.

L-Cysteine Production in Escherichia coli Based on Rational Metabolic Engineering and Modular Strategy.

PubMed

Liu, Han; Fang, Guochen; Wu, Hui; Li, Zhimin; Ye, Qin

2018-05-01

L-cysteine is an amino acid with important physiological functions and has a wide range of applications in medicine, food, animal feed, and cosmetics industry. In this study, the L-cysteine synthesis in Escherichia coliEscherichia coli is divided into four modules: the transport module, sulfur module, precursor module, and degradation module. The engineered strain LH03 (overexpression of the feedback-insensitive cysE and the exporter ydeD in JM109) accumulated 45.8 mg L -1 of L-cysteine in 48 hr with yield of 0.4% g/g glucose. Further modifications of strains and culture conditions which based on the rational metabolic engineering and modular strategy improved the L-cysteine biosynthesis significantly. The engineered strain LH06 (with additional overexpression of serA, serC, and serB and double mutant of tnaA and sdaA in LH03) produced 620.9 mg L -1 of L-cysteine with yield of 6.0% g/g glucose, which increased the production by 12 times and the yield by 14 times more than those of LH03 in the original condition. In fed-batch fermentation performed in a 5-L reactor, the concentration of L-cysteine achieved 5.1 g L -1 in 32 hr. This work demonstrates that the combination of rational metabolic engineering and module strategy is a promising approach for increasing the L-cysteine production in E. coli. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Applying Model Based Systems Engineering to NASA's Space Communications Networks

NASA Technical Reports Server (NTRS)

Bhasin, Kul; Barnes, Patrick; Reinert, Jessica; Golden, Bert

2013-01-01

System engineering practices for complex systems and networks now require that requirement, architecture, and concept of operations product development teams, simultaneously harmonize their activities to provide timely, useful and cost-effective products. When dealing with complex systems of systems, traditional systems engineering methodology quickly falls short of achieving project objectives. This approach is encumbered by the use of a number of disparate hardware and software tools, spreadsheets and documents to grasp the concept of the network design and operation. In case of NASA's space communication networks, since the networks are geographically distributed, and so are its subject matter experts, the team is challenged to create a common language and tools to produce its products. Using Model Based Systems Engineering methods and tools allows for a unified representation of the system in a model that enables a highly related level of detail. To date, Program System Engineering (PSE) team has been able to model each network from their top-level operational activities and system functions down to the atomic level through relational modeling decomposition. These models allow for a better understanding of the relationships between NASA's stakeholders, internal organizations, and impacts to all related entities due to integration and sustainment of existing systems. Understanding the existing systems is essential to accurate and detailed study of integration options being considered. In this paper, we identify the challenges the PSE team faced in its quest to unify complex legacy space communications networks and their operational processes. We describe the initial approaches undertaken and the evolution toward model based system engineering applied to produce Space Communication and Navigation (SCaN) PSE products. We will demonstrate the practice of Model Based System Engineering applied to integrating space communication networks and the summary of its results and impact. We will highlight the insights gained by applying the Model Based System Engineering and provide recommendations for its applications and improvements.

Multimedia explorer: image database, image proxy-server and search-engine.

PubMed Central

Frankewitsch, T.; Prokosch, U.

1999-01-01

Multimedia plays a major role in medicine. Databases containing images, movies or other types of multimedia objects are increasing in number, especially on the WWW. However, no good retrieval mechanism or search engine currently exists to efficiently track down such multimedia sources in the vast of information provided by the WWW. Secondly, the tools for searching databases are usually not adapted to the properties of images. HTML pages do not allow complex searches. Therefore establishing a more comfortable retrieval involves the use of a higher programming level like JAVA. With this platform independent language it is possible to create extensions to commonly used web browsers. These applets offer a graphical user interface for high level navigation. We implemented a database using JAVA objects as the primary storage container which are then stored by a JAVA controlled ORACLE8 database. Navigation depends on a structured vocabulary enhanced by a semantic network. With this approach multimedia objects can be encapsulated within a logical module for quick data retrieval. PMID:10566463

Multimedia explorer: image database, image proxy-server and search-engine.

PubMed

Frankewitsch, T; Prokosch, U

1999-01-01

Multimedia plays a major role in medicine. Databases containing images, movies or other types of multimedia objects are increasing in number, especially on the WWW. However, no good retrieval mechanism or search engine currently exists to efficiently track down such multimedia sources in the vast of information provided by the WWW. Secondly, the tools for searching databases are usually not adapted to the properties of images. HTML pages do not allow complex searches. Therefore establishing a more comfortable retrieval involves the use of a higher programming level like JAVA. With this platform independent language it is possible to create extensions to commonly used web browsers. These applets offer a graphical user interface for high level navigation. We implemented a database using JAVA objects as the primary storage container which are then stored by a JAVA controlled ORACLE8 database. Navigation depends on a structured vocabulary enhanced by a semantic network. With this approach multimedia objects can be encapsulated within a logical module for quick data retrieval.

The role of microscaffold properties in controlling the collagen assembly in 3D dermis equivalent using modular tissue engineering.

PubMed

Imparato, Giorgia; Urciuolo, Francesco; Casale, Costantino; Netti, Paolo A

2013-10-01

The realization of thick and viable tissues equivalents in vitro is one of the mayor challenges in tissue engineering, in particular for their potential use in tissue-on-chip technology. In the present study we succeeded in creating 3D viable dermis equivalent tissue, via a bottom-up method, and proved that the final properties, in terms of collagen assembly and organization of the 3D tissue, are tunable and controllable by micro-scaffold properties and degradation rate. Gelatin porous microscaffolds with controlled stiffness and degradation rate were realized by changing the crosslinking density through different concentrations of glyceraldehyde. Results showed that by modulating the crosslinking density of the gelatin microscaffolds it is possible to guide the process of collagen deposition and assembly within the extracellular space and match the processes of scaffold degradation, cell traction and tissue maturation to obtain firmer collagen network able to withstand the effect of contraction. © 2013 Published by Elsevier Ltd.

Germ Cell-less Promotes Centrosome Segregation to Induce Germ Cell Formation.

PubMed

Lerit, Dorothy A; Shebelut, Conrad W; Lawlor, Kristen J; Rusan, Nasser M; Gavis, Elizabeth R; Schedl, Paul; Deshpande, Girish

2017-01-24

The primordial germ cells (PGCs) specified during embryogenesis serve as progenitors to the adult germline stem cells. In Drosophila, the proper specification and formation of PGCs require both centrosomes and germ plasm, which contains the germline determinants. Centrosomes are microtubule (MT)-organizing centers that ensure the faithful segregation of germ plasm into PGCs. To date, mechanisms that modulate centrosome behavior to engineer PGC development have remained elusive. Only one germ plasm component, Germ cell-less (Gcl), is known to play a role in PGC formation. Here, we show that Gcl engineers PGC formation by regulating centrosome dynamics. Loss of gcl leads to aberrant centrosome separation and elaboration of the astral MT network, resulting in inefficient germ plasm segregation and aborted PGC cellularization. Importantly, compromising centrosome separation alone is sufficient to mimic the gcl loss-of-function phenotypes. We conclude Gcl functions as a key regulator of centrosome separation required for proper PGC development. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Mineralized alginate hydrogels using marine carbonates for bone tissue engineering applications.

PubMed

Diaz-Rodriguez, P; Garcia-Triñanes, P; Echezarreta López, M M; Santoveña, A; Landin, M

2018-09-01

The search for an ideal bone tissue replacement has led to the development of new composite materials designed to simulate the complex inorganic/organic structure of bone. The present work is focused on the development of mineralized calcium alginate hydrogels by the addition of marine derived calcium carbonate biomineral particles. Following a novel approach, we were able to obtain calcium carbonate particles of high purity and complex micro and nanostructure dependent on the source material. Three different types of alginates were selected to develop inorganic/organic scaffolds in order to correlate alginate composition with scaffold properties and cell behavior. The incorporation of calcium carbonates into alginate networks was able to promote extracellular matrix mineralization and osteoblastic differentiation of mesenchymal stem cells when added at 7 mg/ml. We demonstrated that the selection of the alginate type and calcium carbonate origin is crucial to obtain adequate systems for bone tissue engineering as they modulate the mechanical properties and cell differentiation. Copyright © 2018 Elsevier Ltd. All rights reserved.

Networked vision system using a Prolog controller

NASA Astrophysics Data System (ADS)

Batchelor, B. G.; Caton, S. J.; Chatburn, L. T.; Crowther, R. A.; Miller, J. W. V.

2005-11-01

Prolog offers a very different style of programming compared to conventional languages; it can define object properties and abstract relationships in a way that Java, C, C++, etc. find awkward. In an accompanying paper, the authors describe how a distributed web-based vision systems can be built using elements that may even be located on different continents. One particular system of this general type is described here. The top-level controller is a Prolog program, which operates one, or more, image processing engines. This type of function is natural to Prolog, since it is able to reason logically using symbolic (non-numeric) data. Although Prolog is not suitable for programming image processing functions directly, it is ideal for analysing the results derived by an image processor. This article describes the implementation of two systems, in which a Prolog program controls several image processing engines, a simple robot, a pneumatic pick-and-place arm), LED illumination modules and a various mains-powered devices.

Prior knowledge based mining functional modules from Yeast PPI networks with gene ontology

PubMed Central

2010-01-01

Background In the literature, there are fruitful algorithmic approaches for identification functional modules in protein-protein interactions (PPI) networks. Because of accumulation of large-scale interaction data on multiple organisms and non-recording interaction data in the existing PPI database, it is still emergent to design novel computational techniques that can be able to correctly and scalably analyze interaction data sets. Indeed there are a number of large scale biological data sets providing indirect evidence for protein-protein interaction relationships. Results The main aim of this paper is to present a prior knowledge based mining strategy to identify functional modules from PPI networks with the aid of Gene Ontology. Higher similarity value in Gene Ontology means that two gene products are more functionally related to each other, so it is better to group such gene products into one functional module. We study (i) to encode the functional pairs into the existing PPI networks; and (ii) to use these functional pairs as pairwise constraints to supervise the existing functional module identification algorithms. Topology-based modularity metric and complex annotation in MIPs will be used to evaluate the identified functional modules by these two approaches. Conclusions The experimental results on Yeast PPI networks and GO have shown that the prior knowledge based learning methods perform better than the existing algorithms. PMID:21172053

Innovation Online Teaching Module Plus Digital Engineering Kit with Proteus Software through Hybrid Learning Method to Improve Student Skills

NASA Astrophysics Data System (ADS)

Kholis, Nur; Syariffuddien Zuhrie, Muhamad; Rahmadian, Reza

2018-04-01

Demands the competence (competence) needs of the industry today is a competent workforce to the field of work. However, during this lecture material Digital Engineering (Especially Digital Electronics Basics and Digital Circuit Basics) is limited to the delivery of verbal form of lectures (classical method) is dominated by the Lecturer (Teacher Centered). Though the subject of Digital Engineering requires learning tools and is required understanding of electronic circuits, digital electronics and high logic circuits so that learners can apply in the world of work. One effort to make it happen is by creating an online teaching module and educational aids (Kit) with the help of Proteus software that can improve the skills of learners. This study aims to innovate online teaching modules plus kits in Proteus-assisted digital engineering courses through hybrid learning approaches to improve the skills of learners. The process of innovation is done by considering the skills and mastery of the technology of students (students) Department of Electrical Engineering - Faculty of Engineering – Universitas Negeri Surabaya to produce quality graduates Use of online module plus Proteus software assisted kit through hybrid learning approach. In general, aims to obtain adequate results with affordable cost of investment, user friendly, attractive and interactive (easily adapted to the development of Information and Communication Technology). With the right design, implementation and operation, both in the form of software both in the form of Online Teaching Module, offline teaching module, Kit (Educational Viewer), and e-learning learning content (both online and off line), the use of the three tools of the expenditure will be able to adjust the standard needs of Information and Communication Technology world, both nationally and internationally.

Tweaked residual convolutional network for face alignment

NASA Astrophysics Data System (ADS)

Du, Wenchao; Li, Ke; Zhao, Qijun; Zhang, Yi; Chen, Hu

2017-08-01

We propose a novel Tweaked Residual Convolutional Network approach for face alignment with two-level convolutional networks architecture. Specifically, the first-level Tweaked Convolutional Network (TCN) module predicts the landmark quickly but accurately enough as a preliminary, by taking low-resolution version of the detected face holistically as the input. The following Residual Convolutional Networks (RCN) module progressively refines the landmark by taking as input the local patch extracted around the predicted landmark, particularly, which allows the Convolutional Neural Network (CNN) to extract local shape-indexed features to fine tune landmark position. Extensive evaluations show that the proposed Tweaked Residual Convolutional Network approach outperforms existing methods.

Field-effect Flow Control in Polymer Microchannel Networks

NASA Technical Reports Server (NTRS)

Sniadecki, Nathan; Lee, Cheng S.; Beamesderfer, Mike; DeVoe, Don L.

2003-01-01

A new Bio-MEMS electroosmotic flow (EOF) modulator for plastic microchannel networks has been developed. The EOF modulator uses field-effect flow control (FEFC) to adjust the zeta potential at the Parylene C microchannel wall. By setting a differential EOF pumping rate in two of the three microchannels at a T-intersection with EOF modulators, the induced pressure at the intersection generated pumping in the third, field-free microchannel. The EOF modulators are able to change the magnitude and direction of the pressure pumping by inducing either a negative or positive pressure at the intersection. The flow velocity is tracked by neutralized fluorescent microbeads in the microchannels. The proof-of-concept of the EOF modulator described here may be applied to complex plastic ,microchannel networks where individual microchannel flow rates are addressable by localized induced-pressure pumping.

Modularity, pollination systems, and interaction turnover in plant-pollinator networks across space.

PubMed

Carstensen, Daniel W; Sabatino, Malena; Morellato, Leonor Patricia C

2016-05-01

Mutualistic interaction networks have been shown to be structurally conserved over space and time while pairwise interactions show high variability. In such networks, modularity is the division of species into compartments, or modules, where species within modules share more interactions with each other than they do with species from other modules. Such a modular structure is common in mutualistic networks and several evolutionary and ecological mechanisms have been proposed as underlying drivers. One prominent explanation is the existence of pollination syndromes where flowers tend to attract certain pollinators as determined by a set of traits. We investigate the modularity of seven community level plant-pollinator networks sampled in rupestrian grasslands, or campos rupestres, in SE Brazil. Defining pollination systems as corresponding groups of flower syndromes and pollinator functional groups, we test the two hypotheses that (1) interacting species from the same pollination system are more often assigned to the same module than interacting species from different pollination systems and; that (2) interactions between species from the same pollination system are more consistent across space than interactions between species from different pollination systems. Specifically we ask (1) whether networks are consistently modular across space; (2) whether interactions among species of the same pollination system occur more often inside modules, compared to interactions among species of different pollination systems, and finally; (3) whether the spatial variation in interaction identity, i.e., spatial interaction rewiring, is affected by trait complementarity among species as indicated by pollination systems. We confirm that networks are consistently modular across space and that interactions within pollination systems principally occur inside modules. Despite a strong tendency, we did not find a significant effect of pollination systems on the spatial consistency of pairwise interactions. These results indicate that the spatial rewiring of interactions could be constrained by pollination systems, resulting in conserved network structures in spite of high variation in pairwise interactions. Our findings suggest a relevant role of pollination systems in structuring plant-pollinator networks and we argue that structural patterns at the sub-network level can help us to fully understand how and why interactions vary across space and time.

Engine With Regression and Neural Network Approximators Designed

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Hopkins, Dale A.

2001-01-01

At the NASA Glenn Research Center, the NASA engine performance program (NEPP, ref. 1) and the design optimization testbed COMETBOARDS (ref. 2) with regression and neural network analysis-approximators have been coupled to obtain a preliminary engine design methodology. The solution to a high-bypass-ratio subsonic waverotor-topped turbofan engine, which is shown in the preceding figure, was obtained by the simulation depicted in the following figure. This engine is made of 16 components mounted on two shafts with 21 flow stations. The engine is designed for a flight envelope with 47 operating points. The design optimization utilized both neural network and regression approximations, along with the cascade strategy (ref. 3). The cascade used three algorithms in sequence: the method of feasible directions, the sequence of unconstrained minimizations technique, and sequential quadratic programming. The normalized optimum thrusts obtained by the three methods are shown in the following figure: the cascade algorithm with regression approximation is represented by a triangle, a circle is shown for the neural network solution, and a solid line indicates original NEPP results. The solutions obtained from both approximate methods lie within one standard deviation of the benchmark solution for each operating point. The simulation improved the maximum thrust by 5 percent. The performance of the linear regression and neural network methods as alternate engine analyzers was found to be satisfactory for the analysis and operation optimization of air-breathing propulsion engines (ref. 4).

Fast Fragmentation of Networks Using Module-Based Attacks

PubMed Central

Requião da Cunha, Bruno; González-Avella, Juan Carlos; Gonçalves, Sebastián

2015-01-01

In the multidisciplinary field of Network Science, optimization of procedures for efficiently breaking complex networks is attracting much attention from a practical point of view. In this contribution, we present a module-based method to efficiently fragment complex networks. The procedure firstly identifies topological communities through which the network can be represented using a well established heuristic algorithm of community finding. Then only the nodes that participate of inter-community links are removed in descending order of their betweenness centrality. We illustrate the method by applying it to a variety of examples in the social, infrastructure, and biological fields. It is shown that the module-based approach always outperforms targeted attacks to vertices based on node degree or betweenness centrality rankings, with gains in efficiency strongly related to the modularity of the network. Remarkably, in the US power grid case, by deleting 3% of the nodes, the proposed method breaks the original network in fragments which are twenty times smaller in size than the fragments left by betweenness-based attack. PMID:26569610

Detection of Significant Pneumococcal Meningitis Biomarkers by Ego Network.

PubMed

Wang, Qian; Lou, Zhifeng; Zhai, Liansuo; Zhao, Haibin

2017-06-01

To identify significant biomarkers for detection of pneumococcal meningitis based on ego network. Based on the gene expression data of pneumococcal meningitis and global protein-protein interactions (PPIs) data recruited from open access databases, the authors constructed a differential co-expression network (DCN) to identify pneumococcal meningitis biomarkers in a network view. Here EgoNet algorithm was employed to screen the significant ego networks that could accurately distinguish pneumococcal meningitis from healthy controls, by sequentially seeking ego genes, searching candidate ego networks, refinement of candidate ego networks and significance analysis to identify ego networks. Finally, the functional inference of the ego networks was performed to identify significant pathways for pneumococcal meningitis. By differential co-expression analysis, the authors constructed the DCN that covered 1809 genes and 3689 interactions. From the DCN, a total of 90 ego genes were identified. Starting from these ego genes, three significant ego networks (Module 19, Module 70 and Module 71) that could predict clinical outcomes for pneumococcal meningitis were identified by EgoNet algorithm, and the corresponding ego genes were GMNN, MAD2L1 and TPX2, respectively. Pathway analysis showed that these three ego networks were related to CDT1 association with the CDC6:ORC:origin complex, inactivation of APC/C via direct inhibition of the APC/C complex pathway, and DNA strand elongation, respectively. The authors successfully screened three significant ego modules which could accurately predict the clinical outcomes for pneumococcal meningitis and might play important roles in host response to pathogen infection in pneumococcal meningitis.

Network architecture of the cerebral nuclei (basal ganglia) association and commissural connectome.

PubMed

Swanson, Larry W; Sporns, Olaf; Hahn, Joel D

2016-10-04

The cerebral nuclei form the ventral division of the cerebral hemisphere and are thought to play an important role in neural systems controlling somatic movement and motivation. Network analysis was used to define global architectural features of intrinsic cerebral nuclei circuitry in one hemisphere (association connections) and between hemispheres (commissural connections). The analysis was based on more than 4,000 reports of histologically defined axonal connections involving all 45 gray matter regions of the rat cerebral nuclei and revealed the existence of four asymmetrically interconnected modules. The modules form four topographically distinct longitudinal columns that only partly correspond to previous interpretations of cerebral nuclei structure-function organization. The network of connections within and between modules in one hemisphere or the other is quite dense (about 40% of all possible connections), whereas the network of connections between hemispheres is weak and sparse (only about 5% of all possible connections). Particularly highly interconnected regions (rich club and hubs within it) form a topologically continuous band extending through two of the modules. Connection path lengths among numerous pairs of regions, and among some of the network's modules, are relatively long, thus accounting for low global efficiency in network communication. These results provide a starting point for reexamining the connectional organization of the cerebral hemispheres as a whole (right and left cerebral cortex and cerebral nuclei together) and their relation to the rest of the nervous system.

Ganoderma lucidum polysaccharides in human monocytic leukemia cells: from gene expression to network construction

PubMed Central

Cheng, Kun-Chieh; Huang, Hsuan-Cheng; Chen, Jenn-Han; Hsu, Jia-Wei; Cheng, Hsu-Chieh; Ou, Chern-Han; Yang, Wen-Bin; Chen, Shui-Tein; Wong, Chi-Huey; Juan, Hsueh-Fen

2007-01-01

Background Ganoderma lucidum has been widely used as a herbal medicine for promoting health and longevity in China and other Asian countries. Polysaccharide extracts from Ganoderma lucidum have been reported to exhibit immuno-modulating and anti-tumor activities. In previous studies, F3, the active component of the polysaccharide extract, was found to activate various cytokines such as IL-1, IL-6, IL-12, and TNF-α. This gave rise to our investigation on how F3 stimulates immuno-modulating or anti-tumor effects in human leukemia THP-1 cells. Results Here, we integrated time-course DNA microarray analysis, quantitative PCR assays, and bioinformatics methods to study the F3-induced effects in THP-1 cells. Significantly disturbed pathways induced by F3 were identified with statistical analysis on microarray data. The apoptosis induction through the DR3 and DR4/5 death receptors was found to be one of the most significant pathways and play a key role in THP-1 cells after F3 treatment. Based on time-course gene expression measurements of the identified pathway, we reconstructed a plausible regulatory network of the involved genes using reverse-engineering computational approach. Conclusion Our results showed that F3 may induce death receptor ligands to initiate signaling via receptor oligomerization, recruitment of specialized adaptor proteins and activation of caspase cascades. PMID:17996095

Ganoderma lucidum polysaccharides in human monocytic leukemia cells: from gene expression to network construction.

PubMed

Cheng, Kun-Chieh; Huang, Hsuan-Cheng; Chen, Jenn-Han; Hsu, Jia-Wei; Cheng, Hsu-Chieh; Ou, Chern-Han; Yang, Wen-Bin; Chen, Shui-Tein; Wong, Chi-Huey; Juan, Hsueh-Fen

2007-11-09

Ganoderma lucidum has been widely used as a herbal medicine for promoting health and longevity in China and other Asian countries. Polysaccharide extracts from Ganoderma lucidum have been reported to exhibit immuno-modulating and anti-tumor activities. In previous studies, F3, the active component of the polysaccharide extract, was found to activate various cytokines such as IL-1, IL-6, IL-12, and TNF-alpha. This gave rise to our investigation on how F3 stimulates immuno-modulating or anti-tumor effects in human leukemia THP-1 cells. Here, we integrated time-course DNA microarray analysis, quantitative PCR assays, and bioinformatics methods to study the F3-induced effects in THP-1 cells. Significantly disturbed pathways induced by F3 were identified with statistical analysis on microarray data. The apoptosis induction through the DR3 and DR4/5 death receptors was found to be one of the most significant pathways and play a key role in THP-1 cells after F3 treatment. Based on time-course gene expression measurements of the identified pathway, we reconstructed a plausible regulatory network of the involved genes using reverse-engineering computational approach. Our results showed that F3 may induce death receptor ligands to initiate signaling via receptor oligomerization, recruitment of specialized adaptor proteins and activation of caspase cascades.

Network based management for multiplexed electric vehicle charging

DOEpatents

Gadh, Rajit; Chung, Ching Yen; Qui, Li

2017-04-11

A system for multiplexing charging of electric vehicles, comprising a server coupled to a plurality of charging control modules over a network. Each of said charging modules being connected to a voltage source such that each charging control module is configured to regulate distribution of voltage from the voltage source to an electric vehicle coupled to the charging control module. Data collection and control software is provided on the server for identifying a plurality of electric vehicles coupled to the plurality of charging control modules and selectively distributing charging of the plurality of charging control modules to multiplex distribution of voltage to the plurality of electric vehicles.

Using a network modularity analysis to inform management of a rare endemic plant in the northern Great Plains, USA

USGS Publications Warehouse

Larson, Diane L.; Droege, Sam; Rabie, Paul A.; Larson, Jennifer L.; Devalez, Jelle; Haar, Milton; McDermott-Kubeczko, Margaret

2014-01-01

1. Analyses of flower-visitor interaction networks allow application of community-level information to conservation problems, but management recommendations that ensue from such analyses are not well characterized. Results of modularity analyses, which detect groups of species (modules) that interact more with each other than with species outside their module, may be particularly applicable to management concerns. 2. We conducted modularity analyses of networks surrounding a rare endemic annual plant, Eriogonum visheri, at Badlands National Park, USA, in 2010 and 2011. Plant species visited were determined by pollen on insect bodies and by flower species upon which insects were captured. Roles within modules (network hub, module hub, connector and peripheral, in decreasing order of network structural importance) were determined for each species. 3. Relationships demonstrated by the modularity analysis, in concert with knowledge of pollen species carried by insects, allowed us to infer effects of two invasive species on E. visheri. Sharing a module increased risk of interspecific pollen transfer to E. visheri. Control of invasive Salsola tragus, which shared a module with E. visheri, is therefore a prudent management objective, but lack of control of invasive Melilotus officinalis, which occupied a different module, is unlikely to negatively affect pollination of E. visheri. Eriogonum pauciflorum may occupy a key position in this network, supporting insects from the E. visheri module when E. visheri is less abundant. 4. Year-to-year variation in species' roles suggests management decisions must be based on observations over several years. Information on pollen deposition on stigmas would greatly strengthen inferences made from the modularity analysis. 5. Synthesis and applications: Assessing the consequences of pollination, whether at the community or individual level, is inherently time-consuming. A trade-off exists: rather than an estimate of fitness effects, the network approach provides a broad understanding of the relationships among insect visitors and other plant species that may affect the focal rare plant. Knowledge of such relationships allows managers to detect, target and prioritize control of only the important subset of invasive species present and identify other species that may augment a rare species' population stability, such as E. pauciflorum in our study.

A gene network simulator to assess reverse engineering algorithms.

PubMed

Di Camillo, Barbara; Toffolo, Gianna; Cobelli, Claudio

2009-03-01

In the context of reverse engineering of biological networks, simulators are helpful to test and compare the accuracy of different reverse-engineering approaches in a variety of experimental conditions. A novel gene-network simulator is presented that resembles some of the main features of transcriptional regulatory networks related to topology, interaction among regulators of transcription, and expression dynamics. The simulator generates network topology according to the current knowledge of biological network organization, including scale-free distribution of the connectivity and clustering coefficient independent of the number of nodes in the network. It uses fuzzy logic to represent interactions among the regulators of each gene, integrated with differential equations to generate continuous data, comparable to real data for variety and dynamic complexity. Finally, the simulator accounts for saturation in the response to regulation and transcription activation thresholds and shows robustness to perturbations. It therefore provides a reliable and versatile test bed for reverse engineering algorithms applied to microarray data. Since the simulator describes regulatory interactions and expression dynamics as two distinct, although interconnected aspects of regulation, it can also be used to test reverse engineering approaches that use both microarray and protein-protein interaction data in the process of learning. A first software release is available at http://www.dei.unipd.it/~dicamill/software/netsim as an R programming language package.

Saturn Apollo Program

NASA Image and Video Library

1968-01-01

This is a cutaway illustration of the Saturn V service module configuration. Packed with plumbing and tanks, the service module was the command module's constant companion until just before reentry. All components not needed during the last few minutes of flight, and therefore requiring no protection against reentry heat, were transported in this module. It carried oxygen for most of the trip, fuel cells to generate electricity (along with the oxygen and hydrogen to run them); small engines to control pitch, roll, and yaw; and a large engine to propel the spacecraft into, and out of, lunar orbit.

Pharmacological modulation of pulvinar resting-state regional oscillations and network dynamics in major depression

PubMed Central

Tadayonnejad, Reza; Ajilore, Olusola; Mickey, Brian J.; Crane, Natania A.; Hsu, David T.; Kumar, Anand; Zubieta, Jon-Kar; Langenecker, Scott A.

2016-01-01

The pulvinar, the largest thalamus nucleus, has rich anatomical connections with several different cortical and subcortical regions suggesting its important involvement in high-level cognitive and emotional functions. Unfortunately, pulvinar dysfunction in psychiatric disorders particularly major depression disorder has not been thoroughly examined to date. In this study we explored the alterations in the baseline regional and network activities of the pulvinar in MDD by applying spectral analysis of resting-state oscillatory activity, functional connectivity and directed (effective) connectivity on resting-state fMRI data acquired from 20 healthy controls and 19 participants with MDD. Furthermore, we tested how pharmacological treatment with duloxetine can modulate the measured local and network variables in ten participants who completed treatment. Our results revealed a frequency-band dependent modulation of power spectrum characteristics of pulvinar regional oscillatory activity. At the network level, we found MDD is associated with aberrant causal interactions between pulvinar and several systems including default-mode and posterior insular networks. It was also shown that duloxetine treatment can correct or overcompensate the pathologic network behavior of the pulvinar. In conclusion, we suggest that pulvinar regional baseline oscillatory activity and its resting-state network dynamics are compromised in MDD and can be modulated therapeutically by pharmacological treatment. PMID:27148894

Stability and structural properties of gene regulation networks with coregulation rules.

PubMed

Warrell, Jonathan; Mhlanga, Musa

2017-05-07

Coregulation of the expression of groups of genes has been extensively demonstrated empirically in bacterial and eukaryotic systems. Such coregulation can arise through the use of shared regulatory motifs, which allow the coordinated expression of modules (and module groups) of functionally related genes across the genome. Coregulation can also arise through the physical association of multi-gene complexes through chromosomal looping, which are then transcribed together. We present a general formalism for modeling coregulation rules in the framework of Random Boolean Networks (RBN), and develop specific models for transcription factor networks with modular structure (including module groups, and multi-input modules (MIM) with autoregulation) and multi-gene complexes (including hierarchical differentiation between multi-gene complex members). We develop a mean-field approach to analyse the dynamical stability of large networks incorporating coregulation, and show that autoregulated MIM and hierarchical gene-complex models can achieve greater stability than networks without coregulation whose rules have matching activation frequency. We provide further analysis of the stability of small networks of both kinds through simulations. We also characterize several general properties of the transients and attractors in the hierarchical coregulation model, and show using simulations that the steady-state distribution factorizes hierarchically as a Bayesian network in a Markov Jump Process analogue of the RBN model. Copyright © 2017. Published by Elsevier Ltd.

Network Analysis of Reconnaissance and Intrusion of an Industrial Control System

DTIC Science & Technology

2016-09-01

simulated a plant engineer using the engineering workstation web browser to authenticate to the vegetable cooker HMI. While the engineer established the...observed the vegetable cooker HMI web display, the attacker stopped capturing network traffic. Acting as the attacker, we searched the attacker’s pcap...manually controlled by human activity. In this testbed network, only web browser traffic (HTTP) is created by an operator to view an HMI status

10th International Conference of Computational Methods in Sciences and Engineering

DTIC Science & Technology

2014-12-22

Density Modulation ", in the 10th International Conference of Computational Methods in Sciences and Engineering (ICCMSE 2014), April 4-7, 2014, Athens...ENGINEERING We organized the symposium, “Electronic Transport Properties in the Presence of Density Modulation ,” in the 10th International...Superlattices by Coplanar Waveguide Dr. Endo reported his recent experimental work on thermoelectric power of two-dimensional electron gases in the quantum

Network-Based Disease Module Discovery by a Novel Seed Connector Algorithm with Pathobiological Implications.

PubMed

Wang, Rui-Sheng; Loscalzo, Joseph

2018-05-20

Understanding the genetic basis of complex diseases is challenging. Prior work shows that disease-related proteins do not typically function in isolation. Rather, they often interact with each other to form a network module that underlies dysfunctional mechanistic pathways. Identifying such disease modules will provide insights into a systems-level understanding of molecular mechanisms of diseases. Owing to the incompleteness of our knowledge of disease proteins and limited information on the biological mediators of pathobiological processes, the key proteins (seed proteins) for many diseases appear scattered over the human protein-protein interactome and form a few small branches, rather than coherent network modules. In this paper, we develop a network-based algorithm, called the Seed Connector algorithm (SCA), to pinpoint disease modules by adding as few additional linking proteins (seed connectors) to the seed protein pool as possible. Such seed connectors are hidden disease module elements that are critical for interpreting the functional context of disease proteins. The SCA aims to connect seed disease proteins so that disease mechanisms and pathways can be decoded based on predicted coherent network modules. We validate the algorithm using a large corpus of 70 complex diseases and binding targets of over 200 drugs, and demonstrate the biological relevance of the seed connectors. Lastly, as a specific proof of concept, we apply the SCA to a set of seed proteins for coronary artery disease derived from a meta-analysis of large-scale genome-wide association studies and obtain a coronary artery disease module enriched with important disease-related signaling pathways and drug targets not previously recognized. Copyright © 2018 Elsevier Ltd. All rights reserved.

Prior knowledge guided active modules identification: an integrated multi-objective approach.

PubMed

Chen, Weiqi; Liu, Jing; He, Shan

2017-03-14

Active module, defined as an area in biological network that shows striking changes in molecular activity or phenotypic signatures, is important to reveal dynamic and process-specific information that is correlated with cellular or disease states. A prior information guided active module identification approach is proposed to detect modules that are both active and enriched by prior knowledge. We formulate the active module identification problem as a multi-objective optimisation problem, which consists two conflicting objective functions of maximising the coverage of known biological pathways and the activity of the active module simultaneously. Network is constructed from protein-protein interaction database. A beta-uniform-mixture model is used to estimate the distribution of p-values and generate scores for activity measurement from microarray data. A multi-objective evolutionary algorithm is used to search for Pareto optimal solutions. We also incorporate a novel constraints based on algebraic connectivity to ensure the connectedness of the identified active modules. Application of proposed algorithm on a small yeast molecular network shows that it can identify modules with high activities and with more cross-talk nodes between related functional groups. The Pareto solutions generated by the algorithm provides solutions with different trade-off between prior knowledge and novel information from data. The approach is then applied on microarray data from diclofenac-treated yeast cells to build network and identify modules to elucidate the molecular mechanisms of diclofenac toxicity and resistance. Gene ontology analysis is applied to the identified modules for biological interpretation. Integrating knowledge of functional groups into the identification of active module is an effective method and provides a flexible control of balance between pure data-driven method and prior information guidance.

Technology Developments Integrating a Space Network Communications Testbed

NASA Technical Reports Server (NTRS)

Kwong, Winston; Jennings, Esther; Clare, Loren; Leang, Dee

2006-01-01

As future manned and robotic space explorations missions involve more complex systems, it is essential to verify, validate, and optimize such systems through simulation and emulation in a low cost testbed environment. The goal of such a testbed is to perform detailed testing of advanced space and ground communications networks, technologies, and client applications that are essential for future space exploration missions. We describe the development of new technologies enhancing our Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) that enable its integration in a distributed space communications testbed. MACHETE combines orbital modeling, link analysis, and protocol and service modeling to quantify system performance based on comprehensive considerations of different aspects of space missions. It can simulate entire networks and can interface with external (testbed) systems. The key technology developments enabling the integration of MACHETE into a distributed testbed are the Monitor and Control module and the QualNet IP Network Emulator module. Specifically, the Monitor and Control module establishes a standard interface mechanism to centralize the management of each testbed component. The QualNet IP Network Emulator module allows externally generated network traffic to be passed through MACHETE to experience simulated network behaviors such as propagation delay, data loss, orbital effects and other communications characteristics, including entire network behaviors. We report a successful integration of MACHETE with a space communication testbed modeling a lunar exploration scenario. This document is the viewgraph slides of the presentation.

Conserved Non-Coding Regulatory Signatures in Arabidopsis Co-Expressed Gene Modules

PubMed Central

Spangler, Jacob B.; Ficklin, Stephen P.; Luo, Feng; Freeling, Michael; Feltus, F. Alex

2012-01-01

Complex traits and other polygenic processes require coordinated gene expression. Co-expression networks model mRNA co-expression: the product of gene regulatory networks. To identify regulatory mechanisms underlying coordinated gene expression in a tissue-enriched context, ten Arabidopsis thaliana co-expression networks were constructed after manually sorting 4,566 RNA profiling datasets into aerial, flower, leaf, root, rosette, seedling, seed, shoot, whole plant, and global (all samples combined) groups. Collectively, the ten networks contained 30% of the measurable genes of Arabidopsis and were circumscribed into 5,491 modules. Modules were scrutinized for cis regulatory mechanisms putatively encoded in conserved non-coding sequences (CNSs) previously identified as remnants of a whole genome duplication event. We determined the non-random association of 1,361 unique CNSs to 1,904 co-expression network gene modules. Furthermore, the CNS elements were placed in the context of known gene regulatory networks (GRNs) by connecting 250 CNS motifs with known GRN cis elements. Our results provide support for a regulatory role of some CNS elements and suggest the functional consequences of CNS activation of co-expression in specific gene sets dispersed throughout the genome. PMID:23024789

Conserved non-coding regulatory signatures in Arabidopsis co-expressed gene modules.

PubMed

Spangler, Jacob B; Ficklin, Stephen P; Luo, Feng; Freeling, Michael; Feltus, F Alex

2012-01-01

Complex traits and other polygenic processes require coordinated gene expression. Co-expression networks model mRNA co-expression: the product of gene regulatory networks. To identify regulatory mechanisms underlying coordinated gene expression in a tissue-enriched context, ten Arabidopsis thaliana co-expression networks were constructed after manually sorting 4,566 RNA profiling datasets into aerial, flower, leaf, root, rosette, seedling, seed, shoot, whole plant, and global (all samples combined) groups. Collectively, the ten networks contained 30% of the measurable genes of Arabidopsis and were circumscribed into 5,491 modules. Modules were scrutinized for cis regulatory mechanisms putatively encoded in conserved non-coding sequences (CNSs) previously identified as remnants of a whole genome duplication event. We determined the non-random association of 1,361 unique CNSs to 1,904 co-expression network gene modules. Furthermore, the CNS elements were placed in the context of known gene regulatory networks (GRNs) by connecting 250 CNS motifs with known GRN cis elements. Our results provide support for a regulatory role of some CNS elements and suggest the functional consequences of CNS activation of co-expression in specific gene sets dispersed throughout the genome.

Orbit Transfer Rocket Engine Technology Program: Advanced engine study, task D.1/D.3

NASA Technical Reports Server (NTRS)

Martinez, A.; Erickson, C.; Hines, B.

1986-01-01

Concepts for space maintainability of OTV engines were examined. An engine design was developed which was driven by space maintenance requirements and by a failure mode and effects (FME) analysis. Modularity within the engine was shown to offer cost benefits and improved space maintenance capabilities. Space operable disconnects were conceptualized for both engine change-out and for module replacement. Through FME mitigation the modules were conceptualized to contain the least reliable and most often replaced engine components. A preliminary space maintenance plan was developed around a controls and condition monitoring system using advanced sensors, controls, and condition monitoring concepts. A complete engine layout was prepared satisfying current vehicle requirements and utilizing projected component advanced technologies. A technology plan for developing the required technology was assembled.

Overview of the NCC

NASA Technical Reports Server (NTRS)

Liu, Nan-Suey

2001-01-01

A multi-disciplinary design/analysis tool for combustion systems is critical for optimizing the low-emission, high-performance combustor design process. Based on discussions between then NASA Lewis Research Center and the jet engine companies, an industry-government team was formed in early 1995 to develop the National Combustion Code (NCC), which is an integrated system of computer codes for the design and analysis of combustion systems. NCC has advanced features that address the need to meet designer's requirements such as "assured accuracy", "fast turnaround", and "acceptable cost". The NCC development team is comprised of Allison Engine Company (Allison), CFD Research Corporation (CFDRC), GE Aircraft Engines (GEAE), NASA Glenn Research Center (LeRC), and Pratt & Whitney (P&W). The "unstructured mesh" capability and "parallel computing" are fundamental features of NCC from its inception. The NCC system is composed of a set of "elements" which includes grid generator, main flow solver, turbulence module, turbulence and chemistry interaction module, chemistry module, spray module, radiation heat transfer module, data visualization module, and a post-processor for evaluating engine performance parameters. Each element may have contributions from several team members. Such a multi-source multi-element system needs to be integrated in a way that facilitates inter-module data communication, flexibility in module selection, and ease of integration. The development of the NCC beta version was essentially completed in June 1998. Technical details of the NCC elements are given in the Reference List. Elements such as the baseline flow solver, turbulence module, and the chemistry module, have been extensively validated; and their parallel performance on large-scale parallel systems has been evaluated and optimized. However the scalar PDF module and the Spray module, as well as their coupling with the baseline flow solver, were developed in a small-scale distributed computing environment. As a result, the validation of the NCC beta version as a whole was quite limited. Current effort has been focused on the validation of the integrated code and the evaluation/optimization of its overall performance on large-scale parallel systems.

Real-time sensor data validation

NASA Technical Reports Server (NTRS)

Bickmore, Timothy W.

1994-01-01

This report describes the status of an on-going effort to develop software capable of detecting sensor failures on rocket engines in real time. This software could be used in a rocket engine controller to prevent the erroneous shutdown of an engine due to sensor failures which would otherwise be interpreted as engine failures by the control software. The approach taken combines analytical redundancy with Bayesian belief networks to provide a solution which has well defined real-time characteristics and well-defined error rates. Analytical redundancy is a technique in which a sensor's value is predicted by using values from other sensors and known or empirically derived mathematical relations. A set of sensors and a set of relations among them form a network of cross-checks which can be used to periodically validate all of the sensors in the network. Bayesian belief networks provide a method of determining if each of the sensors in the network is valid, given the results of the cross-checks. This approach has been successfully demonstrated on the Technology Test Bed Engine at the NASA Marshall Space Flight Center. Current efforts are focused on extending the system to provide a validation capability for 100 sensors on the Space Shuttle Main Engine.

Multi-agent based control of large-scale complex systems employing distributed dynamic inference engine

NASA Astrophysics Data System (ADS)

Zhang, Daili

Increasing societal demand for automation has led to considerable efforts to control large-scale complex systems, especially in the area of autonomous intelligent control methods. The control system of a large-scale complex system needs to satisfy four system level requirements: robustness, flexibility, reusability, and scalability. Corresponding to the four system level requirements, there arise four major challenges. First, it is difficult to get accurate and complete information. Second, the system may be physically highly distributed. Third, the system evolves very quickly. Fourth, emergent global behaviors of the system can be caused by small disturbances at the component level. The Multi-Agent Based Control (MABC) method as an implementation of distributed intelligent control has been the focus of research since the 1970s, in an effort to solve the above-mentioned problems in controlling large-scale complex systems. However, to the author's best knowledge, all MABC systems for large-scale complex systems with significant uncertainties are problem-specific and thus difficult to extend to other domains or larger systems. This situation is partly due to the control architecture of multiple agents being determined by agent to agent coupling and interaction mechanisms. Therefore, the research objective of this dissertation is to develop a comprehensive, generalized framework for the control system design of general large-scale complex systems with significant uncertainties, with the focus on distributed control architecture design and distributed inference engine design. A Hybrid Multi-Agent Based Control (HyMABC) architecture is proposed by combining hierarchical control architecture and module control architecture with logical replication rings. First, it decomposes a complex system hierarchically; second, it combines the components in the same level as a module, and then designs common interfaces for all of the components in the same module; third, replications are made for critical agents and are organized into logical rings. This architecture maintains clear guidelines for complexity decomposition and also increases the robustness of the whole system. Multiple Sectioned Dynamic Bayesian Networks (MSDBNs) as a distributed dynamic probabilistic inference engine, can be embedded into the control architecture to handle uncertainties of general large-scale complex systems. MSDBNs decomposes a large knowledge-based system into many agents. Each agent holds its partial perspective of a large problem domain by representing its knowledge as a Dynamic Bayesian Network (DBN). Each agent accesses local evidence from its corresponding local sensors and communicates with other agents through finite message passing. If the distributed agents can be organized into a tree structure, satisfying the running intersection property and d-sep set requirements, globally consistent inferences are achievable in a distributed way. By using different frequencies for local DBN agent belief updating and global system belief updating, it balances the communication cost with the global consistency of inferences. In this dissertation, a fully factorized Boyen-Koller (BK) approximation algorithm is used for local DBN agent belief updating, and the static Junction Forest Linkage Tree (JFLT) algorithm is used for global system belief updating. MSDBNs assume a static structure and a stable communication network for the whole system. However, for a real system, sub-Bayesian networks as nodes could be lost, and the communication network could be shut down due to partial damage in the system. Therefore, on-line and automatic MSDBNs structure formation is necessary for making robust state estimations and increasing survivability of the whole system. A Distributed Spanning Tree Optimization (DSTO) algorithm, a Distributed D-Sep Set Satisfaction (DDSSS) algorithm, and a Distributed Running Intersection Satisfaction (DRIS) algorithm are proposed in this dissertation. Combining these three distributed algorithms and a Distributed Belief Propagation (DBP) algorithm in MSDBNs makes state estimations robust to partial damage in the whole system. Combining the distributed control architecture design and the distributed inference engine design leads to a process of control system design for a general large-scale complex system. As applications of the proposed methodology, the control system design of a simplified ship chilled water system and a notional ship chilled water system have been demonstrated step by step. Simulation results not only show that the proposed methodology gives a clear guideline for control system design for general large-scale complex systems with dynamic and uncertain environment, but also indicate that the combination of MSDBNs and HyMABC can provide excellent performance for controlling general large-scale complex systems.

System for adjusting frequency of electrical output pulses derived from an oscillator

DOEpatents

Bartholomew, David B.

2006-11-14

A system for setting and adjusting a frequency of electrical output pulses derived from an oscillator in a network is disclosed. The system comprises an accumulator module configured to receive pulses from an oscillator and to output an accumulated value. An adjustor module is configured to store an adjustor value used to correct local oscillator drift. A digital adder adds values from the accumulator module to values stored in the adjustor module and outputs their sums to the accumulator module, where they are stored. The digital adder also outputs an electrical pulse to a logic module. The logic module is in electrical communication with the adjustor module and the network. The logic module may change the value stored in the adjustor module to compensate for local oscillator drift or change the frequency of output pulses. The logic module may also keep time and calculate drift.

New tools for non-invasive exploration of collagen network in cartilaginous tissue-engineered substitute.

PubMed

Henrionnet, Christel; Dumas, Dominique; Hupont, Sébastien; Stoltz, Jean François; Mainard, Didier; Gillet, Pierre; Pinzano, Astrid

2017-01-01

In tissue engineering approaches, the quality of substitutes is a key element to determine its ability to treat cartilage defects. However, in clinical practice, the evaluation of tissue-engineered cartilage substitute quality is not possible due to the invasiveness of the standard procedure, which is to date histology. The aim of this work was to validate a new innovative system performed from two-photon excitation laser adapted to an optical macroscope to evaluate at macroscopic scale the collagen network in cartilage tissue-engineered substitutes in confrontation with gold standard histologic techniques or immunohistochemistry to visualize type II collagen. This system permitted to differentiate the quality of collagen network between ITS and TGF-β1 treatments. Multiscale large field imaging combined to multimodality approaches (SHG-TCSPC) at macroscopical scale represent an innovative and non-invasive technique to monitor the quality of collagen network in cartilage tissue-engineered substitutes before in vivo implantation.

Analysis of bHLH coding genes using gene co-expression network approach.

PubMed

Srivastava, Swati; Sanchita; Singh, Garima; Singh, Noopur; Srivastava, Gaurava; Sharma, Ashok

2016-07-01

Network analysis provides a powerful framework for the interpretation of data. It uses novel reference network-based metrices for module evolution. These could be used to identify module of highly connected genes showing variation in co-expression network. In this study, a co-expression network-based approach was used for analyzing the genes from microarray data. Our approach consists of a simple but robust rank-based network construction. The publicly available gene expression data of Solanum tuberosum under cold and heat stresses were considered to create and analyze a gene co-expression network. The analysis provide highly co-expressed module of bHLH coding genes based on correlation values. Our approach was to analyze the variation of genes expression, according to the time period of stress through co-expression network approach. As the result, the seed genes were identified showing multiple connections with other genes in the same cluster. Seed genes were found to be vary in different time periods of stress. These analyzed seed genes may be utilized further as marker genes for developing the stress tolerant plant species.

The Missing Part of Seed Dispersal Networks: Structure and Robustness of Bat-Fruit Interactions

PubMed Central

Mello, Marco Aurelio Ribeiro; Marquitti, Flávia Maria Darcie; Guimarães, Paulo Roberto; Kalko, Elisabeth Klara Viktoria; Jordano, Pedro; de Aguiar, Marcus Aloizio Martinez

2011-01-01

Mutualistic networks are crucial to the maintenance of ecosystem services. Unfortunately, what we know about seed dispersal networks is based only on bird-fruit interactions. Therefore, we aimed at filling part of this gap by investigating bat-fruit networks. It is known from population studies that: (i) some bat species depend more on fruits than others, and (ii) that some specialized frugivorous bats prefer particular plant genera. We tested whether those preferences affected the structure and robustness of the whole network and the functional roles of species. Nine bat-fruit datasets from the literature were analyzed and all networks showed lower complementary specialization (H2' = 0.37±0.10, mean ± SD) and similar nestedness (NODF = 0.56±0.12) than pollination networks. All networks were modular (M = 0.32±0.07), and had on average four cohesive subgroups (modules) of tightly connected bats and plants. The composition of those modules followed the genus-genus associations observed at population level (Artibeus-Ficus, Carollia-Piper, and Sturnira-Solanum), although a few of those plant genera were dispersed also by other bats. Bat-fruit networks showed high robustness to simulated cumulative removals of both bats (R = 0.55±0.10) and plants (R = 0.68±0.09). Primary frugivores interacted with a larger proportion of the plants available and also occupied more central positions; furthermore, their extinction caused larger changes in network structure. We conclude that bat-fruit networks are highly cohesive and robust mutualistic systems, in which redundancy is high within modules, although modules are complementary to each other. Dietary specialization seems to be an important structuring factor that affects the topology, the guild structure and functional roles in bat-fruit networks. PMID:21386981

The missing part of seed dispersal networks: structure and robustness of bat-fruit interactions.

PubMed

Mello, Marco Aurelio Ribeiro; Marquitti, Flávia Maria Darcie; Guimarães, Paulo Roberto; Kalko, Elisabeth Klara Viktoria; Jordano, Pedro; de Aguiar, Marcus Aloizio Martinez

2011-02-28

Mutualistic networks are crucial to the maintenance of ecosystem services. Unfortunately, what we know about seed dispersal networks is based only on bird-fruit interactions. Therefore, we aimed at filling part of this gap by investigating bat-fruit networks. It is known from population studies that: (i) some bat species depend more on fruits than others, and (ii) that some specialized frugivorous bats prefer particular plant genera. We tested whether those preferences affected the structure and robustness of the whole network and the functional roles of species. Nine bat-fruit datasets from the literature were analyzed and all networks showed lower complementary specialization (H(2)' = 0.37±0.10, mean ± SD) and similar nestedness (NODF = 0.56±0.12) than pollination networks. All networks were modular (M = 0.32±0.07), and had on average four cohesive subgroups (modules) of tightly connected bats and plants. The composition of those modules followed the genus-genus associations observed at population level (Artibeus-Ficus, Carollia-Piper, and Sturnira-Solanum), although a few of those plant genera were dispersed also by other bats. Bat-fruit networks showed high robustness to simulated cumulative removals of both bats (R = 0.55±0.10) and plants (R = 0.68±0.09). Primary frugivores interacted with a larger proportion of the plants available and also occupied more central positions; furthermore, their extinction caused larger changes in network structure. We conclude that bat-fruit networks are highly cohesive and robust mutualistic systems, in which redundancy is high within modules, although modules are complementary to each other. Dietary specialization seems to be an important structuring factor that affects the topology, the guild structure and functional roles in bat-fruit networks.

In-situ trainable intrusion detection system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Symons, Christopher T.; Beaver, Justin M.; Gillen, Rob

A computer implemented method detects intrusions using a computer by analyzing network traffic. The method includes a semi-supervised learning module connected to a network node. The learning module uses labeled and unlabeled data to train a semi-supervised machine learning sensor. The method records events that include a feature set made up of unauthorized intrusions and benign computer requests. The method identifies at least some of the benign computer requests that occur during the recording of the events while treating the remainder of the data as unlabeled. The method trains the semi-supervised learning module at the network node in-situ, such thatmore » the semi-supervised learning modules may identify malicious traffic without relying on specific rules, signatures, or anomaly detection.« less

Scientific Cluster Deployment and Recovery - Using puppet to simplify cluster management

NASA Astrophysics Data System (ADS)

Hendrix, Val; Benjamin, Doug; Yao, Yushu

2012-12-01

Deployment, maintenance and recovery of a scientific cluster, which has complex, specialized services, can be a time consuming task requiring the assistance of Linux system administrators, network engineers as well as domain experts. Universities and small institutions that have a part-time FTE with limited time for and knowledge of the administration of such clusters can be strained by such maintenance tasks. This current work is the result of an effort to maintain a data analysis cluster (DAC) with minimal effort by a local system administrator. The realized benefit is the scientist, who is the local system administrator, is able to focus on the data analysis instead of the intricacies of managing a cluster. Our work provides a cluster deployment and recovery process (CDRP) based on the puppet configuration engine allowing a part-time FTE to easily deploy and recover entire clusters with minimal effort. Puppet is a configuration management system (CMS) used widely in computing centers for the automatic management of resources. Domain experts use Puppet's declarative language to define reusable modules for service configuration and deployment. Our CDRP has three actors: domain experts, a cluster designer and a cluster manager. The domain experts first write the puppet modules for the cluster services. A cluster designer would then define a cluster. This includes the creation of cluster roles, mapping the services to those roles and determining the relationships between the services. Finally, a cluster manager would acquire the resources (machines, networking), enter the cluster input parameters (hostnames, IP addresses) and automatically generate deployment scripts used by puppet to configure it to act as a designated role. In the event of a machine failure, the originally generated deployment scripts along with puppet can be used to easily reconfigure a new machine. The cluster definition produced in our CDRP is an integral part of automating cluster deployment in a cloud environment. Our future cloud efforts will further build on this work.

Integration of systems biology with bioprocess engineering: L: -threonine production by systems metabolic engineering of Escherichia coli.

PubMed

Lee, Sang Yup; Park, Jin Hwan

2010-01-01

Random mutation and selection or targeted metabolic engineering without consideration of its impact on the entire metabolic and regulatory networks can unintentionally cause genetic alterations in the region, which is not directly related to the target metabolite. This is one of the reasons why strategies for developing industrial strains are now shifted towards targeted metabolic engineering based on systems biology, which is termed systems metabolic engineering. Using systems metabolic engineering strategies, all the metabolic engineering works are conducted in systems biology framework, whereby entire metabolic and regulatory networks are thoroughly considered in an integrated manner. The targets for purposeful engineering are selected after all possible effects on the entire metabolic and regulatory networks are thoroughly considered. Finally, the strain, which is capable of producing the target metabolite to a high level close to the theoretical maximum value, can be constructed. Here we review strategies and applications of systems biology successfully implemented on bioprocess engineering, with particular focus on developing L: -threonine production strains of Escherichia coli.

Features and heterogeneities in growing network models

NASA Astrophysics Data System (ADS)

Ferretti, Luca; Cortelezzi, Michele; Yang, Bin; Marmorini, Giacomo; Bianconi, Ginestra

2012-06-01

Many complex networks from the World Wide Web to biological networks grow taking into account the heterogeneous features of the nodes. The feature of a node might be a discrete quantity such as a classification of a URL document such as personal page, thematic website, news, blog, search engine, social network, etc., or the classification of a gene in a functional module. Moreover the feature of a node can be a continuous variable such as the position of a node in the embedding space. In order to account for these properties, in this paper we provide a generalization of growing network models with preferential attachment that includes the effect of heterogeneous features of the nodes. The main effect of heterogeneity is the emergence of an “effective fitness” for each class of nodes, determining the rate at which nodes acquire new links. The degree distribution exhibits a multiscaling behavior analogous to the the fitness model. This property is robust with respect to variations in the model, as long as links are assigned through effective preferential attachment. Beyond the degree distribution, in this paper we give a full characterization of the other relevant properties of the model. We evaluate the clustering coefficient and show that it disappears for large network size, a property shared with the Barabási-Albert model. Negative degree correlations are also present in this class of models, along with nontrivial mixing patterns among features. We therefore conclude that both small clustering coefficients and disassortative mixing are outcomes of the preferential attachment mechanism in general growing networks.

An agent-based hydroeconomic model to evaluate water policies in Jordan

NASA Astrophysics Data System (ADS)

Yoon, J.; Gorelick, S.

2014-12-01

Modern water systems can be characterized by a complex network of institutional and private actors that represent competing sectors and interests. Identifying solutions to enhance water security in such systems calls for analysis that can adequately account for this level of complexity and interaction. Our work focuses on the development of a hierarchical, multi-agent, hydroeconomic model that attempts to realistically represent complex interactions between hydrologic and multi-faceted human systems. The model is applied to Jordan, one of the most water-poor countries in the world. In recent years, the water crisis in Jordan has escalated due to an ongoing drought and influx of refugees from regional conflicts. We adopt a modular approach in which biophysical modules simulate natural and engineering phenomena, and human modules represent behavior at multiple scales of decision making. The human modules employ agent-based modeling, in which agents act as autonomous decision makers at the transboundary, state, organizational, and user levels. A systematic nomenclature and conceptual framework is used to characterize model agents and modules. Concepts from the Unified Modeling Language (UML) are adopted to promote clear conceptualization of model classes and process sequencing, establishing a foundation for full deployment of the integrated model in a scalable object-oriented programming environment. Although the framework is applied to the Jordanian water context, it is generalizable to other regional human-natural freshwater supply systems.

Expedition Two crew share dessert in Zvezda module

NASA Image and Video Library

2001-06-10

ISS002-E-6534 (10 June 2001) --- Expedition Two crewmembers Yury V. Usachev (left), mission commander, James S. Voss, flight engineer, and Susan J. Helms, flight engineer, share a dessert in the Zvezda Service Module. Usachev represents Rosaviakosmos. The image was recorded with a digital still camera.

Tyurin and Williams in Zvezda Service module

NASA Image and Video Library

2007-04-21

ISS014-E-19924 (21 April 2007) --- Cosmonaut Mikhail Tyurin (left), Expedition 14 flight engineer representing Russia's Federal Space Agency, and astronaut Sunita L. Williams, Expedition 15 flight engineer, drink beverages as they pose for a photo in the Zvezda Service Module of the International Space Station.

Distributed parallel messaging for multiprocessor systems

DOEpatents

Chen, Dong; Heidelberger, Philip; Salapura, Valentina; Senger, Robert M; Steinmacher-Burrow, Burhard; Sugawara, Yutaka

2013-06-04

A method and apparatus for distributed parallel messaging in a parallel computing system. The apparatus includes, at each node of a multiprocessor network, multiple injection messaging engine units and reception messaging engine units, each implementing a DMA engine and each supporting both multiple packet injection into and multiple reception from a network, in parallel. The reception side of the messaging unit (MU) includes a switch interface enabling writing of data of a packet received from the network to the memory system. The transmission side of the messaging unit, includes switch interface for reading from the memory system when injecting packets into the network.

A fault tolerant 80960 engine controller

NASA Technical Reports Server (NTRS)

Reichmuth, D. M.; Gage, M. L.; Paterson, E. S.; Kramer, D. D.

1993-01-01

The paper describes the design of the 80960 Fault Tolerant Engine Controller for the supervision of engine operations, which was designed for the NASA Marshall Space Center. Consideration is given to the major electronic components of the controller, including the engine controller, effectors, and the sensors, as well as to the controller hardware, the controller module and the communications module, and the controller software. The architecture of the controller hardware allows modifications to be made to fit the requirements of any new propulsion systems. Multiple flow diagrams are presented illustrating the controller's operations.

Microgravity

NASA Image and Video Library

2000-01-30

Engineers from NASA's Glenn Research Center, demonstrate access to one of the experiment racks planned for the U.S. Destiny laboratory module on the International Space Station. This mockup has the full diameter, full corridor width, and half the length of the module. The mockup includes engineering mockups of the Fluids and Combustion Facility being developed by NASA's Glenn Research Center. (The full module will be six racks long; the mockup is three rack long) Photo credit: NASA/Marshall Space Flight Center

Dynamic Imbalance Would Counter Offcenter Thrust

NASA Technical Reports Server (NTRS)

Mccanna, Jason

1994-01-01

Dynamic imbalance generated by offcenter thrust on rotating body eliminated by shifting some of mass of body to generate opposing dynamic imbalance. Technique proposed originally for spacecraft including massive crew module connected via long, lightweight intermediate structure to massive engine module, such that artificial gravitation in crew module generated by rotating spacecraft around axis parallel to thrust generated by engine. Also applicable to dynamic balancing of rotating terrestrial equipment to which offcenter forces applied.

a Webgis to Support Gpr 3d Data Acquisition: a First Step for the Integration of Underground Utility Networks in 3d City Models

NASA Astrophysics Data System (ADS)

Tabarro, P. G.; Pouliot, J.; Fortier, R.; Losier, L.-M.

2017-10-01

For the planning and sustainable development of large cities, it is critical to accurately locate and map, in 3D, existing underground utility networks (UUN) such as pipelines, cables, ducts, and channels. An emerging non-invasive instrument for collecting underground data such as UUN is the ground-penetrating radar (GPR). Although its capabilities, handling GPR and extracting relevant information from its data are not trivial tasks. For instance, both GPR and its complimentary software stack provide very few capabilities to co-visualize GPR collected data and other sources of spatial data such as orthophotography, DEM or road maps. Furthermore, the GPR interface lacks functionalities for adding annotation, editing geometric objects or querying attributes. A new approach to support GPR survey is proposed in this paper. This approach is based on the integration of multiple sources of geospatial datasets and the use of a Web-GIS system and relevant functionalities adapted to interoperable GPR data acquisition. The Web-GIS is developed as an improved module in an existing platform called GVX. The GVX-GPR module provides an interactive visualization of multiple layers of structured spatial data, including GPR profiles. This module offers new features when compared to traditional GPR surveys such as geo-annotated points of interest for identifying spatial clues in the GPR profiles, integration of city contextual data, high definition drone and satellite pictures, as-built, and more. The paper explains the engineering approach used to design and develop the Web GIS and tests for this survey approach, mapping and recording UUN as part of 3D city model.

From Saccharomyces cerevisiae to human: The important gene co-expression modules.

PubMed

Liu, Wei; Li, Li; Ye, Hua; Chen, Haiwei; Shen, Weibiao; Zhong, Yuexian; Tian, Tian; He, Huaqin

2017-08-01

Network-based systems biology has become an important method for analyzing high-throughput gene expression data and gene function mining. Yeast has long been a popular model organism for biomedical research. In the current study, a weighted gene co-expression network analysis algorithm was applied to construct a gene co-expression network in Saccharomyces cerevisiae . Seventeen stable gene co-expression modules were detected from 2,814 S. cerevisiae microarray data. Further characterization of these modules with the Database for Annotation, Visualization and Integrated Discovery tool indicated that these modules were associated with certain biological processes, such as heat response, cell cycle, translational regulation, mitochondrion oxidative phosphorylation, amino acid metabolism and autophagy. Hub genes were also screened by intra-modular connectivity. Finally, the module conservation was evaluated in a human disease microarray dataset. Functional modules were identified in budding yeast, some of which are associated with patient survival. The current study provided a paradigm for single cell microorganisms and potentially other organisms.

Soft-Input Soft-Output Modules for the Construction and Distributed Iterative Decoding of Code Networks

NASA Technical Reports Server (NTRS)

Benedetto, S.; Divsalar, D.; Montorsi, G.; Pollara, F.

1998-01-01

Soft-input soft-output building blocks (modules) are presented to construct and iteratively decode in a distributed fashion code networks, a new concept that includes, and generalizes, various forms of concatenated coding schemes.

Home Care Nursing via Computer Networks: Justification and Design Specifications

PubMed Central

Brennan, Patricia Flatley

1988-01-01

High-tech home care includes the use of information technologies, such as computer networks, to provide direct care to patients in the home. This paper presents the justification and design of a project using a free, public access computer network to deliver home care nursing. The intervention attempts to reduce isolation and improve problem solving among home care patients and their informal caregivers. Three modules comprise the intervention: a decision module, a communications module, and an information data base. This paper describes the experimental evaluation of the project, and discusses issues in the delivery of nursing care via computers.

Distributed multisensory integration in a recurrent network model through supervised learning

NASA Astrophysics Data System (ADS)

Wang, He; Wong, K. Y. Michael

Sensory integration between different modalities has been extensively studied. It is suggested that the brain integrates signals from different modalities in a Bayesian optimal way. However, how the Bayesian rule is implemented in a neural network remains under debate. In this work we propose a biologically plausible recurrent network model, which can perform Bayesian multisensory integration after trained by supervised learning. Our model is composed of two modules, each for one modality. We assume that each module is a recurrent network, whose activity represents the posterior distribution of each stimulus. The feedforward input on each module is the likelihood of each modality. Two modules are integrated through cross-links, which are feedforward connections from the other modality, and reciprocal connections, which are recurrent connections between different modules. By stochastic gradient descent, we successfully trained the feedforward and recurrent coupling matrices simultaneously, both of which resembles the Mexican-hat. We also find that there are more than one set of coupling matrices that can approximate the Bayesian theorem well. Specifically, reciprocal connections and cross-links will compensate each other if one of them is removed. Even though trained with two inputs, the network's performance with only one input is in good accordance with what is predicted by the Bayesian theorem.

Green Engineering Textbook and Training Modules

EPA Pesticide Factsheets

EPA's Green Engineering textbook, Green Engineering: Environmentally Conscious Design of Chemical Processes, is a college senior-to-graduate-level engineering textbook. The primary authors are Dr. David Allen and Dr. David Shonnard.

Intelligent deflection routing in buffer-less networks.

PubMed

Haeri, Soroush; Trajković, Ljiljana

2015-02-01

Deflection routing is employed to ameliorate packet loss caused by contention in buffer-less architectures such as optical burst-switched networks. The main goal of deflection routing is to successfully deflect a packet based only on a limited knowledge that network nodes possess about their environment. In this paper, we present a framework that introduces intelligence to deflection routing (iDef). iDef decouples the design of the signaling infrastructure from the underlying learning algorithm. It consists of a signaling and a decision-making module. Signaling module implements a feedback management protocol while the decision-making module implements a reinforcement learning algorithm. We also propose several learning-based deflection routing protocols, implement them in iDef using the ns-3 network simulator, and compare their performance.

Analysis of global gene expression in Brachypodium distachyon reveals extensive network plasticity in response to abiotic stress.

PubMed

Priest, Henry D; Fox, Samuel E; Rowley, Erik R; Murray, Jessica R; Michael, Todd P; Mockler, Todd C

2014-01-01

Brachypodium distachyon is a close relative of many important cereal crops. Abiotic stress tolerance has a significant impact on productivity of agriculturally important food and feedstock crops. Analysis of the transcriptome of Brachypodium after chilling, high-salinity, drought, and heat stresses revealed diverse differential expression of many transcripts. Weighted Gene Co-Expression Network Analysis revealed 22 distinct gene modules with specific profiles of expression under each stress. Promoter analysis implicated short DNA sequences directly upstream of module members in the regulation of 21 of 22 modules. Functional analysis of module members revealed enrichment in functional terms for 10 of 22 network modules. Analysis of condition-specific correlations between differentially expressed gene pairs revealed extensive plasticity in the expression relationships of gene pairs. Photosynthesis, cell cycle, and cell wall expression modules were down-regulated by all abiotic stresses. Modules which were up-regulated by each abiotic stress fell into diverse and unique gene ontology GO categories. This study provides genomics resources and improves our understanding of abiotic stress responses of Brachypodium.

Evaluation of LED vehicular and pedestrian modules.

DOT National Transportation Integrated Search

2009-04-01

This study was conducted to verify the compliance of vehicular and pedestrian LED traffic signal modules with the Institute : of Transportation Engineers specifications; and to assess drivers preferences of the LED modules. Four vehicular modules ...

Dynamics of neuromodulatory feedback determines frequency modulation in a reduced respiratory network: a computational study.

PubMed

Toporikova, Natalia; Butera, Robert J

2013-02-01

Neuromodulators, such as amines and neuropeptides, alter the activity of neurons and neuronal networks. In this work, we investigate how neuromodulators, which activate G(q)-protein second messenger systems, can modulate the bursting frequency of neurons in a critical portion of the respiratory neural network, the pre-Bötzinger complex (preBötC). These neurons are a vital part of the ponto-medullary neuronal network, which generates a stable respiratory rhythm whose frequency is regulated by neuromodulator release from the nearby Raphe nucleus. Using a simulated 50-cell network of excitatory preBötC neurons with a heterogeneous distribution of persistent sodium conductance and Ca(2+), we determined conditions for frequency modulation in such a network by simulating interaction between Raphe and preBötC nuclei. We found that the positive feedback between the Raphe excitability and preBötC activity induces frequency modulation in the preBötC neurons. In addition, the frequency of the respiratory rhythm can be regulated via phasic release of excitatory neuromodulators from the Raphe nucleus. We predict that the application of a G(q) antagonist will eliminate this frequency modulation by the Raphe and keep the network frequency constant and low. In contrast, application of a G(q) agonist will result in a high frequency for all levels of Raphe stimulation. Our modeling results also suggest that high [K(+)] requirement in respiratory brain slice experiments may serve as a compensatory mechanism for low neuromodulatory tone. Copyright © 2012 Elsevier B.V. All rights reserved.

Emergence of system roles in normative neurodevelopment

PubMed Central

Gu, Shi; Satterthwaite, Theodore D.; Medaglia, John D.; Yang, Muzhi; Gur, Raquel E.; Gur, Ruben C.; Bassett, Danielle S.

2015-01-01

Adult human cognition is supported by systems of brain regions, or modules, that are functionally coherent at rest and collectively activated by distinct task requirements. However, an understanding of how the formation of these modules supports evolving cognitive capabilities has not been delineated. Here, we quantify the formation of network modules in a sample of 780 youth (aged 8–22 y) who were studied as part of the Philadelphia Neurodevelopmental Cohort. We demonstrate that the brain’s functional network organization changes in youth through a process of modular evolution that is governed by the specific cognitive roles of each system, as defined by the balance of within- vs. between-module connectivity. Moreover, individual variability in these roles is correlated with cognitive performance. Collectively, these results suggest that dynamic maturation of network modules in youth may be a critical driver for the development of cognition. PMID:26483477

Filter Bank Multicarrier (FBMC) for long-reach intensity modulated optical access networks

NASA Astrophysics Data System (ADS)

Saljoghei, Arsalan; Gutiérrez, Fernando A.; Perry, Philip; Barry, Liam P.

2017-04-01

Filter Bank Multi Carrier (FBMC) is a modulation scheme which has recently attracted significant interest in both wireless and optical communications. The interest in optical communications arises due to FBMC's capability to operate without a Cyclic Prefix (CP) and its high resilience to synchronisation errors. However, the operation of FBMC in optical access networks has not been extensively studied either in downstream or upstream. In this work we use experimental work to investigate the operation of FBMC in intensity modulated Passive Optical Networks (PONs) employing direct detection in conjunction with both direct and external modulation schemes. The data rates and propagation lengths employed here vary from 8.4 to 14.8 Gb/s and 0-75 km. The results suggest that by using FBMC it is possible to accomplish CP-Less transmission up to 75 km of SSMF in passive links using cost effective intensity modulation and detection schemes.

Photonic Quantum Networks formed from NV− centers

PubMed Central

Nemoto, Kae; Trupke, Michael; Devitt, Simon J.; Scharfenberger, Burkhard; Buczak, Kathrin; Schmiedmayer, Jörg; Munro, William J.

2016-01-01

In this article we present a simple repeater scheme based on the negatively-charged nitrogen vacancy centre in diamond. Each repeater node is built from modules comprising an optical cavity containing a single NV−, with one nuclear spin from 15N as quantum memory. The module uses only deterministic processes and interactions to achieve high fidelity operations (>99%), and modules are connected by optical fiber. In the repeater node architecture, the processes between modules by photons can be in principle deterministic, however current limitations on optical components lead the processes to be probabilistic but heralded. Our resource-modest repeater architecture contains two modules at each node, and the repeater nodes are then connected by entangled photon pairs. We discuss the performance of such a quantum repeater network with modest resources and then incorporate more resource-intense strategies step by step. Our architecture should allow large-scale quantum information networks with existing or near future technology. PMID:27215433

Photonic Quantum Networks formed from NV(-) centers.

PubMed

Nemoto, Kae; Trupke, Michael; Devitt, Simon J; Scharfenberger, Burkhard; Buczak, Kathrin; Schmiedmayer, Jörg; Munro, William J

2016-05-24

In this article we present a simple repeater scheme based on the negatively-charged nitrogen vacancy centre in diamond. Each repeater node is built from modules comprising an optical cavity containing a single NV(-), with one nuclear spin from (15)N as quantum memory. The module uses only deterministic processes and interactions to achieve high fidelity operations (>99%), and modules are connected by optical fiber. In the repeater node architecture, the processes between modules by photons can be in principle deterministic, however current limitations on optical components lead the processes to be probabilistic but heralded. Our resource-modest repeater architecture contains two modules at each node, and the repeater nodes are then connected by entangled photon pairs. We discuss the performance of such a quantum repeater network with modest resources and then incorporate more resource-intense strategies step by step. Our architecture should allow large-scale quantum information networks with existing or near future technology.

Garrett solar Brayton engine/generator status

NASA Astrophysics Data System (ADS)

Anson, B.

1982-07-01

The solar advanced gas turbine (SAGT-1) is being developed by the Garrett Turbine Engine Company, for use in a Brayton cycle power conversion module. The engine is derived from the advanced gas turbine (AGT101) now being developd by Garrett and Ford Motor Company for automotive use. The SAGT Program is presently funded for the design, fabrication and test of one engine at Garrett's Phoenix facility. The engine when mated with a solar receiver is called a power conversion module (PCU). The PCU is scheduled to be tested on JPL's test bed concentrator under a follow on phase of the program. Approximately 20 kw of electrical power will be generated.

Ubiquitous health monitoring system for multiple users using a ZigBee and WLAN dual-network.

PubMed

Cha, Yong Dae; Yoon, Gilwon

2009-11-01

A ubiquitous health monitoring system for multiple users was developed based on a ZigBee and wireless local area network (WLAN) dual-network. A compact biosignal monitoring unit (BMU) for measuring electrocardiogram (ECG), photoplethysmogram (PPG), and temperature was also developed. A single 8-bit microcontroller operated the BMU including most of digital filtering and wireless communication. The BMU with its case was reduced to 55 x 35 x 15 mm and 33 g. In routine use, vital signs of 6 bytes/sec (heart rate, temperature, pulse transit time) per each user were transmitted through a ZigBee module even though all the real-time data were recorded in a secure digital memory of the BMU. In an emergency or when need arises, a channel of a particular user was switched to another ZigBee module, called the emergency module, that sent all ECG and PPG waveforms in real time. Each emergency ZigBee module handled up to a few users. Data from multiple users were wirelessly received by the ZigBee receiver modules in a controller called ZigBee-WLAN gateway, where the ZigBee modules were connected to a WLAN module. This WLAN module sent all data wirelessly to a monitoring center. Operating the dual modes of ZigBee/WLAN utilized an advantage of ZigBee by handling multiple users with minimum power consumption, and overcame the ZigBee limitation of low data rate. This dual-network system for LAN is economically competitive and reliable.

SNE Industrial Fieldbus Interface

NASA Technical Reports Server (NTRS)

Lucena, Angel; Raines, Matthew; Oostdyk, Rebecca; Mata, Carlos

2011-01-01

Programmable logic controllers (PLCs) have very limited diagnostic and no prognostic capabilities, while current smart sensor designs do not have the capability to communicate over Fieldbus networks. The aim is to interface smart sensors with PLCs so that health and status information, such as failure mode identification and measurement tolerance, can be communicated via an industrial Fieldbus such as ControlNet. The SNE Industrial Fieldbus Interface (SIFI) is an embedded device that acts as a communication module in a networked smart sensor. The purpose is to enable a smart sensor to communicate health and status information to other devices, such as PLCs, via an industrial Fieldbus networking protocol. The SNE (Smart Network Element) is attached to a commercial off-the-shelf Any bus-S interface module through the SIFI. Numerous Anybus-S modules are available, each one designed to interface with a specific Fieldbus. Development of the SIFI focused on communications using the ControlNet protocol, but any of the Anybus-S modules can be used. The SIFI communicates with the Any-bus module via a data buffer and mailbox system on the Anybus module, and supplies power to the module. The Anybus module transmits and receives data on the Fieldbus using the proper protocol. The SIFI is intended to be connected to other existing SNE modules in order to monitor the health and status of a transducer. The SIFI can also monitor aspects of its own health using an onboard watchdog timer and voltage monitors. The SIFI also has the hardware to drive a touchscreen LCD (liquid crystal display) unit for manual configuration and status monitoring.

ImNet: a fiber optic network with multistar topology for high-speed data transmission

NASA Astrophysics Data System (ADS)

Vossebuerger, F.; Keizers, Andreas; Soederman, N.; Meyer-Ebrecht, Dietrich

1993-10-01

ImNet is a fiber-optic local area network, which has been developed for high speed image communication in Picture Archiving and Communication Systems (PACS). A comprehensive analysis of image communication requirements in hospitals led to the conclusion that there is a need for networks which are optimized for the transmission of large datafiles. ImNet is optimized for this application in contrast to current-state LANs. ImNet consists of two elements: a link module and a switch module. The point-to-point link module can be up to 4 km by using fiber optic cable. For short distances up to 100 m a cheaper module using shielded twisted pair cable is available. The link module works bi-directionally and handles all protocols up to OSI-Level 3. The data rate per link is up to 140 MBit/s (clock rate 175 MHz). The switch module consists of the control unit and the cross-point-switch array. The array has up to fourteen interfaces for link modules. Up to fourteen data transfers each with a maximal transfer rate of 400 MBit/s can be handled at the same time. Thereby the maximal throughput of a switch module is 5.6 GBit/s. Out of these modules a multi-star network can be built i.e., an arbitrary tree structure of stars. This topology allows multiple transmissions at the same time as long as they do not require identical links. Therefore the overall throughput of ImNet can be a multiple of the datarate per link.

Predicting Engineering Student Attrition Risk Using a Probabilistic Neural Network and Comparing Results with a Backpropagation Neural Network and Logistic Regression

ERIC Educational Resources Information Center

Mason, Cindi; Twomey, Janet; Wright, David; Whitman, Lawrence

2018-01-01

As the need for engineers continues to increase, a growing focus has been placed on recruiting students into the field of engineering and retaining the students who select engineering as their field of study. As a result of this concentration on student retention, numerous studies have been conducted to identify, understand, and confirm…

Systems engineering technology for networks

NASA Technical Reports Server (NTRS)

1994-01-01

The report summarizes research pursued within the Systems Engineering Design Laboratory at Virginia Polytechnic Institute and State University between May 16, 1993 and January 31, 1994. The project was proposed in cooperation with the Computational Science and Engineering Research Center at Howard University. Its purpose was to investigate emerging systems engineering tools and their applicability in analyzing the NASA Network Control Center (NCC) on the basis of metrics and measures.

The Role of Computer Networks in Aerospace Engineering.

ERIC Educational Resources Information Center

Bishop, Ann Peterson

1994-01-01

Presents selected results from an empirical investigation into the use of computer networks in aerospace engineering based on data from a national mail survey. The need for user-based studies of electronic networking is discussed, and a copy of the questionnaire used in the survey is appended. (Contains 46 references.) (LRW)

Design of Intelligent Hydraulic Excavator Control System Based on PID Method

NASA Astrophysics Data System (ADS)

Zhang, Jun; Jiao, Shengjie; Liao, Xiaoming; Yin, Penglong; Wang, Yulin; Si, Kuimao; Zhang, Yi; Gu, Hairong

Most of the domestic designed hydraulic excavators adopt the constant power design method and set 85%~90% of engine power as the hydraulic system adoption power, it causes high energy loss due to mismatching of power between the engine and the pump. While the variation of the rotational speed of engine could sense the power shift of the load, it provides a new method to adjust the power matching between engine and pump through engine speed. Based on negative flux hydraulic system, an intelligent hydraulic excavator control system was designed based on rotational speed sensing method to improve energy efficiency. The control system was consisted of engine control module, pump power adjusted module, engine idle module and system fault diagnosis module. Special PLC with CAN bus was used to acquired the sensors and adjusts the pump absorption power according to load variation. Four energy saving control strategies with constant power method were employed to improve the fuel utilization. Three power modes (H, S and L mode) were designed to meet different working status; Auto idle function was employed to save energy through two work status detected pressure switches, 1300rpm was setting as the idle speed according to the engine consumption fuel curve. Transient overload function was designed for deep digging within short time without spending extra fuel. An increasing PID method was employed to realize power matching between engine and pump, the rotational speed's variation was taken as the PID algorithm's input; the current of proportional valve of variable displacement pump was the PID's output. The result indicated that the auto idle could decrease fuel consumption by 33.33% compared to work in maximum speed of H mode, the PID control method could take full use of maximum engine power at each power mode and keep the engine speed at stable range. Application of rotational speed sensing method provides a reliable method to improve the excavator's energy efficiency and realize power match between pump and engine.

Operation, analysis, and design of signalized intersections : a module for the introductory course in transportation engineering.

DOT National Transportation Integrated Search

2014-02-01

This report presents materials that can be used as the basis for a module on signalized intersections in the introductory : course in transportation engineering. The materials were developed based on studies of the work of students who took : this in...

Slope Stability. CEGS Programs Publication Number 15.

ERIC Educational Resources Information Center

Pestrong, Raymond

Slope Stability is one in a series of single-topic problem modules intended for use in undergraduate and earth science courses. The module, also appropriate for use in undergraduate civil engineering and engineering geology courses, is a self-standing introduction to studies of slope stability. It has been designed to supplement standard…

10 CFR 431.223 - Materials incorporated by reference.

Code of Federal Regulations, 2011 CFR

2011-01-01

... AND INDUSTRIAL EQUIPMENT Traffic Signal Modules and Pedestrian Modules Test Procedures § 431.223... for Traffic Signals,” Version 1.1 issued February 4, 2003. (2) Institute of Transportation Engineers...) 272-0167 or at http://www.epa.gov. (ii) Institute of Transportation Engineers, 1099 14th Street, NW...

10 CFR 431.223 - Materials incorporated by reference.

Code of Federal Regulations, 2010 CFR

2010-01-01

... AND INDUSTRIAL EQUIPMENT Traffic Signal Modules and Pedestrian Modules Test Procedures § 431.223... for Traffic Signals,” Version 1.1 issued February 4, 2003. (2) Institute of Transportation Engineers...) 272-0167 or at http://www.epa.gov. (ii) Institute of Transportation Engineers, 1099 14th Street, NW...

Middle School Engineering Problem Solving Using Traditional vs. E-PBL Module Instruction

ERIC Educational Resources Information Center

Baele, Loren C.

2017-01-01

This multiple methods (Denzin, 1978) study investigated two instructional approaches, traditional module and electronic Problem-Based Learning instruction (e-PBL), used within a middle school engineering classroom focused on the variables of engagement, content knowledge, student self-assessment and teacher assessment of problem solving solutions.…

FIR Light Microscopy Module Set Up

NASA Image and Video Library

2009-11-09

ISS021-E-022460 (9 Nov. 2009) --- Canadian Space Agency astronaut Robert Thirsk, Expedition 21 flight engineer, installs the Light Microscopy Module (LMM) Spindle Bracket Assembly in the Fluids Integrated Rack (FIR) in the Destiny laboratory of the International Space Station. NASA astronaut Nicole Stott (out of frame), flight engineer, assisted Thirsk.

Network analysis of the genomic basis of the placebo effect

PubMed Central

Wang, Rui-Sheng; Hall, Kathryn T.; Giulianini, Franco; Passow, Dani; Kaptchuk, Ted J.

2017-01-01

The placebo effect is a phenomenon in which patients who are given an inactive treatment (e.g., inert pill) show a perceived or actual improvement in a medical condition. Placebo effects in clinical trials have been investigated for many years especially because placebo treatments often serve as the control arm of randomized clinical trial designs. Recent observations suggest that placebo effects may be modified by genetics. This observation has given rise to the term “placebome,” which refers to a group of genome-related mediators that affect an individual’s response to placebo treatments. In this study, we conduct a network analysis of the placebome and identify a placebome module in the comprehensive human interactome using a seed-connector algorithm. The placebome module is significantly enriched with neurotransmitter signaling pathways and brain-specific proteins. We validate the placebome module using a large cohort of the Women’s Genome Health Study (WGHS) trial and demonstrate that the placebome module is significantly enriched with genes whose SNPs modify the outcome in the placebo arm of the trial. To gain insights into placebo effects in different diseases and drug treatments, we use a network proximity measure to examine the closeness of the placebome module to different disease modules and drug target modules. The results demonstrate that the network proximity of the placebome module to disease modules in the interactome significantly correlates with the strength of the placebo effect in the corresponding diseases. The proximity of the placebome module to molecular pathways affected by certain drug classes indicates the existence of placebo-drug interactions. This study is helpful for understanding the molecular mechanisms mediating the placebo response, and sets the stage for minimizing its effects in clinical trials and for developing therapeutic strategies that intentionally engage it. PMID:28570268

A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2001-01-01

In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.

Adaptive Optimization of Aircraft Engine Performance Using Neural Networks

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Long, Theresa W.

1995-01-01

Preliminary results are presented on the development of an adaptive neural network based control algorithm to enhance aircraft engine performance. This work builds upon a previous National Aeronautics and Space Administration (NASA) effort known as Performance Seeking Control (PSC). PSC is an adaptive control algorithm which contains a model of the aircraft's propulsion system which is updated on-line to match the operation of the aircraft's actual propulsion system. Information from the on-line model is used to adapt the control system during flight to allow optimal operation of the aircraft's propulsion system (inlet, engine, and nozzle) to improve aircraft engine performance without compromising reliability or operability. Performance Seeking Control has been shown to yield reductions in fuel flow, increases in thrust, and reductions in engine fan turbine inlet temperature. The neural network based adaptive control, like PSC, will contain a model of the propulsion system which will be used to calculate optimal control commands on-line. Hopes are that it will be able to provide some additional benefits above and beyond those of PSC. The PSC algorithm is computationally intensive, it is valid only at near steady-state flight conditions, and it has no way to adapt or learn on-line. These issues are being addressed in the development of the optimal neural controller. Specialized neural network processing hardware is being developed to run the software, the algorithm will be valid at steady-state and transient conditions, and will take advantage of the on-line learning capability of neural networks. Future plans include testing the neural network software and hardware prototype against an aircraft engine simulation. In this paper, the proposed neural network software and hardware is described and preliminary neural network training results are presented.

Probabilistic QoS Analysis In Wireless Sensor Networks

DTIC Science & Technology

2012-04-01

and A.O. Fapojuwo. TDMA scheduling with optimized energy efficiency and minimum delay in clustered wireless sensor networks . IEEE Trans. on Mobile...Research Computer Science and Engineering, Department of 5-1-2012 Probabilistic QoS Analysis in Wireless Sensor Networks Yunbo Wang University of...Wang, Yunbo, "Probabilistic QoS Analysis in Wireless Sensor Networks " (2012). Computer Science and Engineering: Theses, Dissertations, and Student

Remembering the Giants: Apollo Rocket Propulsion Development

NASA Technical Reports Server (NTRS)

Fisher, Steven C. (Editor); Rahman, Shamim A. (Editor)

2009-01-01

Topics discussed include: Rocketdyne - F-1 Saturn V First Stage Engine; Rocketdyne - J-2 Saturn V 2nd & 3rd Stage Engine; Rocketdyne - SE-7 & SE-8 Engines; Aerojet - AJ10-137 Apollo Service Module Engine; Aerojet - Attitude Control Engines; TRW - Lunar Descent Engine; and Rocketdyne - Lunar Ascent Engine.

Efficient Reverse-Engineering of a Developmental Gene Regulatory Network

PubMed Central

Cicin-Sain, Damjan; Ashyraliyev, Maksat; Jaeger, Johannes

2012-01-01

Understanding the complex regulatory networks underlying development and evolution of multi-cellular organisms is a major problem in biology. Computational models can be used as tools to extract the regulatory structure and dynamics of such networks from gene expression data. This approach is called reverse engineering. It has been successfully applied to many gene networks in various biological systems. However, to reconstitute the structure and non-linear dynamics of a developmental gene network in its spatial context remains a considerable challenge. Here, we address this challenge using a case study: the gap gene network involved in segment determination during early development of Drosophila melanogaster. A major problem for reverse-engineering pattern-forming networks is the significant amount of time and effort required to acquire and quantify spatial gene expression data. We have developed a simplified data processing pipeline that considerably increases the throughput of the method, but results in data of reduced accuracy compared to those previously used for gap gene network inference. We demonstrate that we can infer the correct network structure using our reduced data set, and investigate minimal data requirements for successful reverse engineering. Our results show that timing and position of expression domain boundaries are the crucial features for determining regulatory network structure from data, while it is less important to precisely measure expression levels. Based on this, we define minimal data requirements for gap gene network inference. Our results demonstrate the feasibility of reverse-engineering with much reduced experimental effort. This enables more widespread use of the method in different developmental contexts and organisms. Such systematic application of data-driven models to real-world networks has enormous potential. Only the quantitative investigation of a large number of developmental gene regulatory networks will allow us to discover whether there are rules or regularities governing development and evolution of complex multi-cellular organisms. PMID:22807664

Neural control of fast nonlinear systems--application to a turbocharged SI engine with VCT.

PubMed

Colin, Guillaume; Chamaillard, Yann; Bloch, Gérard; Corde, Gilles

2007-07-01

Today, (engine) downsizing using turbocharging appears as a major way in reducing fuel consumption and pollutant emissions of spark ignition (SI) engines. In this context, an efficient control of the air actuators [throttle, turbo wastegate, and variable camshaft timing (VCT)] is needed for engine torque control. This paper proposes a nonlinear model-based control scheme which combines separate, but coordinated, control modules. Theses modules are based on different control strategies: internal model control (IMC), model predictive control (MPC), and optimal control. It is shown how neural models can be used at different levels and included in the control modules to replace physical models, which are too complex to be online embedded, or to estimate nonmeasured variables. The results obtained from two different test benches show the real-time applicability and good control performance of the proposed methods.

Aircraft Noise Prediction Program (ANOPP) Fan Noise Prediction for Small Engines

NASA Technical Reports Server (NTRS)

Hough, Joe W.; Weir, Donald S.

1996-01-01

The Fan Noise Module of ANOPP is used to predict the broadband noise and pure tones for axial flow compressors or fans. The module, based on the method developed by M. F. Heidmann, uses empirical functions to predict fan noise spectra as a function of frequency and polar directivity. Previous studies have determined the need to modify the module to better correlate measurements of fan noise from engines in the 3000- to 6000-pound thrust class. Additional measurements made by AlliedSignal have confirmed the need to revise the ANOPP fan noise method for smaller engines. This report describes the revisions to the fan noise method which have been verified with measured data from three separate AlliedSignal fan engines. Comparisons of the revised prediction show a significant improvement in overall and spectral noise predictions.