Evaluating a common semi-mechanistic mathematical model of gene-regulatory networks

PubMed Central

2015-01-01

Modeling and simulation of gene-regulatory networks (GRNs) has become an important aspect of modern systems biology investigations into mechanisms underlying gene regulation. A key challenge in this area is the automated inference (reverse-engineering) of dynamic, mechanistic GRN models from gene expression time-course data. Common mathematical formalisms for representing such models capture two aspects simultaneously within a single parameter: (1) Whether or not a gene is regulated, and if so, the type of regulator (activator or repressor), and (2) the strength of influence of the regulator (if any) on the target or effector gene. To accommodate both roles, "generous" boundaries or limits for possible values of this parameter are commonly allowed in the reverse-engineering process. This approach has several important drawbacks. First, in the absence of good guidelines, there is no consensus on what limits are reasonable. Second, because the limits may vary greatly among different reverse-engineering experiments, the concrete values obtained for the models may differ considerably, and thus it is difficult to compare models. Third, if high values are chosen as limits, the search space of the model inference process becomes very large, adding unnecessary computational load to the already complex reverse-engineering process. In this study, we demonstrate that restricting the limits to the [−1, +1] interval is sufficient to represent the essential features of GRN systems and offers a reduction of the search space without loss of quality in the resulting models. To show this, we have carried out reverse-engineering studies on data generated from artificial and experimentally determined from real GRN systems. PMID:26356485

Reverse engineering time discrete finite dynamical systems: a feasible undertaking?

PubMed

Delgado-Eckert, Edgar

2009-01-01

With the advent of high-throughput profiling methods, interest in reverse engineering the structure and dynamics of biochemical networks is high. Recently an algorithm for reverse engineering of biochemical networks was developed by Laubenbacher and Stigler. It is a top-down approach using time discrete dynamical systems. One of its key steps includes the choice of a term order, a technicality imposed by the use of Gröbner-bases calculations. The aim of this paper is to identify minimal requirements on data sets to be used with this algorithm and to characterize optimal data sets. We found minimal requirements on a data set based on how many terms the functions to be reverse engineered display. Furthermore, we identified optimal data sets, which we characterized using a geometric property called "general position". Moreover, we developed a constructive method to generate optimal data sets, provided a codimensional condition is fulfilled. In addition, we present a generalization of their algorithm that does not depend on the choice of a term order. For this method we derived a formula for the probability of finding the correct model, provided the data set used is optimal. We analyzed the asymptotic behavior of the probability formula for a growing number of variables n (i.e. interacting chemicals). Unfortunately, this formula converges to zero as fast as , where and . Therefore, even if an optimal data set is used and the restrictions in using term orders are overcome, the reverse engineering problem remains unfeasible, unless prodigious amounts of data are available. Such large data sets are experimentally impossible to generate with today's technologies.

Reverse-engineering of gene networks for regulating early blood development from single-cell measurements.

PubMed

Wei, Jiangyong; Hu, Xiaohua; Zou, Xiufen; Tian, Tianhai

2017-12-28

Recent advances in omics technologies have raised great opportunities to study large-scale regulatory networks inside the cell. In addition, single-cell experiments have measured the gene and protein activities in a large number of cells under the same experimental conditions. However, a significant challenge in computational biology and bioinformatics is how to derive quantitative information from the single-cell observations and how to develop sophisticated mathematical models to describe the dynamic properties of regulatory networks using the derived quantitative information. This work designs an integrated approach to reverse-engineer gene networks for regulating early blood development based on singel-cell experimental observations. The wanderlust algorithm is initially used to develop the pseudo-trajectory for the activities of a number of genes. Since the gene expression data in the developed pseudo-trajectory show large fluctuations, we then use Gaussian process regression methods to smooth the gene express data in order to obtain pseudo-trajectories with much less fluctuations. The proposed integrated framework consists of both bioinformatics algorithms to reconstruct the regulatory network and mathematical models using differential equations to describe the dynamics of gene expression. The developed approach is applied to study the network regulating early blood cell development. A graphic model is constructed for a regulatory network with forty genes and a dynamic model using differential equations is developed for a network of nine genes. Numerical results suggests that the proposed model is able to match experimental data very well. We also examine the networks with more regulatory relations and numerical results show that more regulations may exist. We test the possibility of auto-regulation but numerical simulations do not support the positive auto-regulation. In addition, robustness is used as an importantly additional criterion to select candidate networks. The research results in this work shows that the developed approach is an efficient and effective method to reverse-engineer gene networks using single-cell experimental observations.

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.

Reverse engineering of TLX oncogenic transcriptional networks identifies RUNX1 as tumor suppressor in T-ALL.

PubMed

Della Gatta, Giusy; Palomero, Teresa; Perez-Garcia, Arianne; Ambesi-Impiombato, Alberto; Bansal, Mukesh; Carpenter, Zachary W; De Keersmaecker, Kim; Sole, Xavier; Xu, Luyao; Paietta, Elisabeth; Racevskis, Janis; Wiernik, Peter H; Rowe, Jacob M; Meijerink, Jules P; Califano, Andrea; Ferrando, Adolfo A

2012-02-26

The TLX1 and TLX3 transcription factor oncogenes have a key role in the pathogenesis of T cell acute lymphoblastic leukemia (T-ALL). Here we used reverse engineering of global transcriptional networks to decipher the oncogenic regulatory circuit controlled by TLX1 and TLX3. This systems biology analysis defined T cell leukemia homeobox 1 (TLX1) and TLX3 as master regulators of an oncogenic transcriptional circuit governing T-ALL. Notably, a network structure analysis of this hierarchical network identified RUNX1 as a key mediator of the T-ALL induced by TLX1 and TLX3 and predicted a tumor-suppressor role for RUNX1 in T cell transformation. Consistent with these results, we identified recurrent somatic loss-of-function mutations in RUNX1 in human T-ALL. Overall, these results place TLX1 and TLX3 at the top of an oncogenic transcriptional network controlling leukemia development, show the power of network analyses to identify key elements in the regulatory circuits governing human cancer and identify RUNX1 as a tumor-suppressor gene in T-ALL.

Life's attractors : understanding developmental systems through reverse engineering and in silico evolution.

PubMed

Jaeger, Johannes; Crombach, Anton

2012-01-01

We propose an approach to evolutionary systems biology which is based on reverse engineering of gene regulatory networks and in silico evolutionary simulations. We infer regulatory parameters for gene networks by fitting computational models to quantitative expression data. This allows us to characterize the regulatory structure and dynamical repertoire of evolving gene regulatory networks with a reasonable amount of experimental and computational effort. We use the resulting network models to identify those regulatory interactions that are conserved, and those that have diverged between different species. Moreover, we use the models obtained by data fitting as starting points for simulations of evolutionary transitions between species. These simulations enable us to investigate whether such transitions are random, or whether they show stereotypical series of regulatory changes which depend on the structure and dynamical repertoire of an evolving network. Finally, we present a case study-the gap gene network in dipterans (flies, midges, and mosquitoes)-to illustrate the practical application of the proposed methodology, and to highlight the kind of biological insights that can be gained by this approach.

Towards a portal and search engine to facilitate academic and research collaboration in engineering and education

NASA Astrophysics Data System (ADS)

Bonilla Villarreal, Isaura Nathaly

While international academic and research collaborations are of great importance at this time, it is not easy to find researchers in the engineering field that publish in languages other than English. Because of this disconnect, there exists a need for a portal to find Who's Who in Engineering Education in the Americas. The objective of this thesis is to built an object-oriented architecture for this proposed portal. The Unified Modeling Language (UML) model developed in this thesis incorporates the basic structure of a social network for academic purposes. Reverse engineering of three social networks portals yielded important aspects of their structures that have been incorporated in the proposed UML model. Furthermore, the present work includes a pattern for academic social networks..

Reverse Engineering Cellular Networks with Information Theoretic Methods

PubMed Central

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

2013-01-01

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

Genetic Network Inference: From Co-Expression Clustering to Reverse Engineering

NASA Technical Reports Server (NTRS)

Dhaeseleer, Patrik; Liang, Shoudan; Somogyi, Roland

2000-01-01

Advances in molecular biological, analytical, and computational technologies are enabling us to systematically investigate the complex molecular processes underlying biological systems. In particular, using high-throughput gene expression assays, we are able to measure the output of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of co-expression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various aspects of clustering, ranging from distance measures to clustering algorithms and multiple-duster memberships. More advanced analysis aims to infer causal connections between genes directly, i.e., who is regulating whom and how. We discuss several approaches to the problem of reverse engineering of genetic networks, from discrete Boolean networks, to continuous linear and non-linear models. We conclude that the combination of predictive modeling with systematic experimental verification will be required to gain a deeper insight into living organisms, therapeutic targeting, and bioengineering.

Comparison of De Novo Network Reverse Engineering Methods with Applications to Ecotoxicology

EPA Science Inventory

The DREAM competitions for network modeling comparisons have made several points clear: 1) incorporating knowledge beyond gene expression data may improve modeling (e.g., data from knock-out organisms), 2) most techniques do not perform better than random, and 3) more complex met...

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.

Identifying interactions in the time and frequency domains in local and global networks - A Granger Causality Approach.

PubMed

Zou, Cunlu; Ladroue, Christophe; Guo, Shuixia; Feng, Jianfeng

2010-06-21

Reverse-engineering approaches such as Bayesian network inference, ordinary differential equations (ODEs) and information theory are widely applied to deriving causal relationships among different elements such as genes, proteins, metabolites, neurons, brain areas and so on, based upon multi-dimensional spatial and temporal data. There are several well-established reverse-engineering approaches to explore causal relationships in a dynamic network, such as ordinary differential equations (ODE), Bayesian networks, information theory and Granger Causality. Here we focused on Granger causality both in the time and frequency domain and in local and global networks, and applied our approach to experimental data (genes and proteins). For a small gene network, Granger causality outperformed all the other three approaches mentioned above. A global protein network of 812 proteins was reconstructed, using a novel approach. The obtained results fitted well with known experimental findings and predicted many experimentally testable results. In addition to interactions in the time domain, interactions in the frequency domain were also recovered. The results on the proteomic data and gene data confirm that Granger causality is a simple and accurate approach to recover the network structure. Our approach is general and can be easily applied to other types of temporal data.

Engineering and Evolution of Molecular Chaperones and Protein Disaggregases with Enhanced Activity

PubMed Central

Mack, Korrie L.; Shorter, James

2016-01-01

Cells have evolved a sophisticated proteostasis network to ensure that proteins acquire and retain their native structure and function. Critical components of this network include molecular chaperones and protein disaggregases, which function to prevent and reverse deleterious protein misfolding. Nevertheless, proteostasis networks have limits, which when exceeded can have fatal consequences as in various neurodegenerative disorders, including Parkinson's disease and amyotrophic lateral sclerosis. A promising strategy is to engineer proteostasis networks to counter challenges presented by specific diseases or specific proteins. Here, we review efforts to enhance the activity of individual molecular chaperones or protein disaggregases via engineering and directed evolution. Remarkably, enhanced global activity or altered substrate specificity of various molecular chaperones, including GroEL, Hsp70, ClpX, and Spy, can be achieved by minor changes in primary sequence and often a single missense mutation. Likewise, small changes in the primary sequence of Hsp104 yield potentiated protein disaggregases that reverse the aggregation and buffer toxicity of various neurodegenerative disease proteins, including α-synuclein, TDP-43, and FUS. Collectively, these advances have revealed key mechanistic and functional insights into chaperone and disaggregase biology. They also suggest that enhanced chaperones and disaggregases could have important applications in treating human disease as well as in the purification of valuable proteins in the pharmaceutical sector. PMID:27014702

Learning Biological Networks via Bootstrapping with Optimized GO-based Gene Similarity

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

Taylor, Ronald C.; Sanfilippo, Antonio P.; McDermott, Jason E.

2010-08-02

Microarray gene expression data provide a unique information resource for learning biological networks using "reverse engineering" methods. However, there are a variety of cases in which we know which genes are involved in a given pathology of interest, but we do not have enough experimental evidence to support the use of fully-supervised/reverse-engineering learning methods. In this paper, we explore a novel semi-supervised approach in which biological networks are learned from a reference list of genes and a partial set of links for these genes extracted automatically from PubMed abstracts, using a knowledge-driven bootstrapping algorithm. We show how new relevant linksmore » across genes can be iteratively derived using a gene similarity measure based on the Gene Ontology that is optimized on the input network at each iteration. We describe an application of this approach to the TGFB pathway as a case study and show how the ensuing results prove the feasibility of the approach as an alternate or complementary technique to fully supervised methods.« less

Reverse engineering highlights potential principles of large gene regulatory network design and learning.

PubMed

Carré, Clément; Mas, André; Krouk, Gabriel

2017-01-01

Inferring transcriptional gene regulatory networks from transcriptomic datasets is a key challenge of systems biology, with potential impacts ranging from medicine to agronomy. There are several techniques used presently to experimentally assay transcription factors to target relationships, defining important information about real gene regulatory networks connections. These techniques include classical ChIP-seq, yeast one-hybrid, or more recently, DAP-seq or target technologies. These techniques are usually used to validate algorithm predictions. Here, we developed a reverse engineering approach based on mathematical and computer simulation to evaluate the impact that this prior knowledge on gene regulatory networks may have on training machine learning algorithms. First, we developed a gene regulatory networks-simulating engine called FRANK (Fast Randomizing Algorithm for Network Knowledge) that is able to simulate large gene regulatory networks (containing 10 4 genes) with characteristics of gene regulatory networks observed in vivo. FRANK also generates stable or oscillatory gene expression directly produced by the simulated gene regulatory networks. The development of FRANK leads to important general conclusions concerning the design of large and stable gene regulatory networks harboring scale free properties (built ex nihilo). In combination with supervised (accepting prior knowledge) support vector machine algorithm we (i) address biologically oriented questions concerning our capacity to accurately reconstruct gene regulatory networks and in particular we demonstrate that prior-knowledge structure is crucial for accurate learning, and (ii) draw conclusions to inform experimental design to performed learning able to solve gene regulatory networks in the future. By demonstrating that our predictions concerning the influence of the prior-knowledge structure on support vector machine learning capacity holds true on real data ( Escherichia coli K14 network reconstruction using network and transcriptomic data), we show that the formalism used to build FRANK can to some extent be a reasonable model for gene regulatory networks in real cells.

Reverse-engineering the Arabidopsis thaliana transcriptional network under changing environmental conditions

PubMed Central

Carrera, Javier; Rodrigo, Guillermo; Jaramillo, Alfonso; Elena, Santiago F

2009-01-01

Background Understanding the molecular mechanisms plants have evolved to adapt their biological activities to a constantly changing environment is an intriguing question and one that requires a systems biology approach. Here we present a network analysis of genome-wide expression data combined with reverse-engineering network modeling to dissect the transcriptional control of Arabidopsis thaliana. The regulatory network is inferred by using an assembly of microarray data containing steady-state RNA expression levels from several growth conditions, developmental stages, biotic and abiotic stresses, and a variety of mutant genotypes. Results We show that the A. thaliana regulatory network has the characteristic properties of hierarchical networks. We successfully applied our quantitative network model to predict the full transcriptome of the plant for a set of microarray experiments not included in the training dataset. We also used our model to analyze the robustness in expression levels conferred by network motifs such as the coherent feed-forward loop. In addition, the meta-analysis presented here has allowed us to identify regulatory and robust genetic structures. Conclusions These data suggest that A. thaliana has evolved high connectivity in terms of transcriptional regulation among cellular functions involved in response and adaptation to changing environments, while gene networks constitutively expressed or less related to stress response are characterized by a lower connectivity. Taken together, these findings suggest conserved regulatory strategies that have been selected during the evolutionary history of this eukaryote. PMID:19754933

Adaptable Hydrogel Networks with Reversible Linkages for Tissue Engineering

PubMed Central

Wang, Huiyuan

2015-01-01

Adaptable hydrogels have recently emerged as a promising platform for three-dimensional (3D) cell encapsulation and culture. In conventional, covalently crosslinked hydrogels, degradation is typically required to allow complex cellular functions to occur, leading to bulk material degradation. In contrast, adaptable hydrogels are formed by reversible crosslinks. Through breaking and re-forming of the reversible linkages, adaptable hydrogels can be locally modified to permit complex cellular functions while maintaining their long-term integrity. In addition, these adaptable materials can have biomimetic viscoelastic properties that make them well suited for several biotechnology and medical applications. In this review, adaptable hydrogel design considerations and linkage selections are overviewed, with a focus on various cell compatible crosslinking mechanisms that can be exploited to form adaptable hydrogels for tissue engineering. PMID:25989348

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

Cancer.gov

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

Petri Nets with Fuzzy Logic (PNFL): Reverse Engineering and Parametrization

PubMed Central

Küffner, Robert; Petri, Tobias; Windhager, Lukas; Zimmer, Ralf

2010-01-01

Background The recent DREAM4 blind assessment provided a particularly realistic and challenging setting for network reverse engineering methods. The in silico part of DREAM4 solicited the inference of cycle-rich gene regulatory networks from heterogeneous, noisy expression data including time courses as well as knockout, knockdown and multifactorial perturbations. Methodology and Principal Findings We inferred and parametrized simulation models based on Petri Nets with Fuzzy Logic (PNFL). This completely automated approach correctly reconstructed networks with cycles as well as oscillating network motifs. PNFL was evaluated as the best performer on DREAM4 in silico networks of size 10 with an area under the precision-recall curve (AUPR) of 81%. Besides topology, we inferred a range of additional mechanistic details with good reliability, e.g. distinguishing activation from inhibition as well as dependent from independent regulation. Our models also performed well on new experimental conditions such as double knockout mutations that were not included in the provided datasets. Conclusions The inference of biological networks substantially benefits from methods that are expressive enough to deal with diverse datasets in a unified way. At the same time, overly complex approaches could generate multiple different models that explain the data equally well. PNFL appears to strike the balance between expressive power and complexity. This also applies to the intuitive representation of PNFL models combining a straightforward graphical notation with colloquial fuzzy parameters. PMID:20862218

Inferring Broad Regulatory Biology from Time Course Data: Have We Reached an Upper Bound under Constraints Typical of In Vivo Studies?

PubMed Central

Craddock, Travis J. A.; Fletcher, Mary Ann; Klimas, Nancy G.

2015-01-01

There is a growing appreciation for the network biology that regulates the coordinated expression of molecular and cellular markers however questions persist regarding the identifiability of these networks. Here we explore some of the issues relevant to recovering directed regulatory networks from time course data collected under experimental constraints typical of in vivo studies. NetSim simulations of sparsely connected biological networks were used to evaluate two simple feature selection techniques used in the construction of linear Ordinary Differential Equation (ODE) models, namely truncation of terms versus latent vector projection. Performance was compared with ODE-based Time Series Network Identification (TSNI) integral, and the information-theoretic Time-Delay ARACNE (TD-ARACNE). Projection-based techniques and TSNI integral outperformed truncation-based selection and TD-ARACNE on aggregate networks with edge densities of 10-30%, i.e. transcription factor, protein-protein cliques and immune signaling networks. All were more robust to noise than truncation-based feature selection. Performance was comparable on the in silico 10-node DREAM 3 network, a 5-node Yeast synthetic network designed for In vivo Reverse-engineering and Modeling Assessment (IRMA) and a 9-node human HeLa cell cycle network of similar size and edge density. Performance was more sensitive to the number of time courses than to sample frequency and extrapolated better to larger networks by grouping experiments. In all cases performance declined rapidly in larger networks with lower edge density. Limited recovery and high false positive rates obtained overall bring into question our ability to generate informative time course data rather than the design of any particular reverse engineering algorithm. PMID:25984725

Reverse engineering a gene network using an asynchronous parallel evolution strategy

PubMed Central

2010-01-01

Background The use of reverse engineering methods to infer gene regulatory networks by fitting mathematical models to gene expression data is becoming increasingly popular and successful. However, increasing model complexity means that more powerful global optimisation techniques are required for model fitting. The parallel Lam Simulated Annealing (pLSA) algorithm has been used in such approaches, but recent research has shown that island Evolutionary Strategies can produce faster, more reliable results. However, no parallel island Evolutionary Strategy (piES) has yet been demonstrated to be effective for this task. Results Here, we present synchronous and asynchronous versions of the piES algorithm, and apply them to a real reverse engineering problem: inferring parameters in the gap gene network. We find that the asynchronous piES exhibits very little communication overhead, and shows significant speed-up for up to 50 nodes: the piES running on 50 nodes is nearly 10 times faster than the best serial algorithm. We compare the asynchronous piES to pLSA on the same test problem, measuring the time required to reach particular levels of residual error, and show that it shows much faster convergence than pLSA across all optimisation conditions tested. Conclusions Our results demonstrate that the piES is consistently faster and more reliable than the pLSA algorithm on this problem, and scales better with increasing numbers of nodes. In addition, the piES is especially well suited to further improvements and adaptations: Firstly, the algorithm's fast initial descent speed and high reliability make it a good candidate for being used as part of a global/local search hybrid algorithm. Secondly, it has the potential to be used as part of a hierarchical evolutionary algorithm, which takes advantage of modern multi-core computing architectures. PMID:20196855

Conservation of Information: Reverse Engineering Dark Social Systems

DTIC Science & Technology

2010-01-01

Factbook, retrieved 5/20/10 from www.cia.gov). 25 For example, Air- America , a politically liberal talk radio network, said that it would cease operations...attractive targets than mid- America ; see Reding, 2009). Obama Clinton Clinton Obama Lawless et al.: Conservation of Information 13 approached it...indefinitely sustain the control of the Communist Party--i.e., censoring Google--is increasingly at odds with Network China, which is thriving by

Statistical Inference and Reverse Engineering of Gene Regulatory Networks from Observational Expression Data

PubMed Central

Emmert-Streib, Frank; Glazko, Galina V.; Altay, Gökmen; de Matos Simoes, Ricardo

2012-01-01

In this paper, we present a systematic and conceptual overview of methods for inferring gene regulatory networks from observational gene expression data. Further, we discuss two classic approaches to infer causal structures and compare them with contemporary methods by providing a conceptual categorization thereof. We complement the above by surveying global and local evaluation measures for assessing the performance of inference algorithms. PMID:22408642

HiDi: an efficient reverse engineering schema for large-scale dynamic regulatory network reconstruction using adaptive differentiation.

PubMed

Deng, Yue; Zenil, Hector; Tegnér, Jesper; Kiani, Narsis A

2017-12-15

The use of differential equations (ODE) is one of the most promising approaches to network inference. The success of ODE-based approaches has, however, been limited, due to the difficulty in estimating parameters and by their lack of scalability. Here, we introduce a novel method and pipeline to reverse engineer gene regulatory networks from gene expression of time series and perturbation data based upon an improvement on the calculation scheme of the derivatives and a pre-filtration step to reduce the number of possible links. The method introduces a linear differential equation model with adaptive numerical differentiation that is scalable to extremely large regulatory networks. We demonstrate the ability of this method to outperform current state-of-the-art methods applied to experimental and synthetic data using test data from the DREAM4 and DREAM5 challenges. Our method displays greater accuracy and scalability. We benchmark the performance of the pipeline with respect to dataset size and levels of noise. We show that the computation time is linear over various network sizes. The Matlab code of the HiDi implementation is available at: www.complexitycalculator.com/HiDiScript.zip. hzenilc@gmail.com or narsis.kiani@ki.se. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures

NASA Technical Reports Server (NTRS)

Liang, Shoudan; Fuhrman, Stefanie; Somogyi, Roland

1998-01-01

Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.

Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks.

PubMed

Werhli, Adriano V; Grzegorczyk, Marco; Husmeier, Dirk

2006-10-15

An important problem in systems biology is the inference of biochemical pathways and regulatory networks from postgenomic data. Various reverse engineering methods have been proposed in the literature, and it is important to understand their relative merits and shortcomings. In the present paper, we compare the accuracy of reconstructing gene regulatory networks with three different modelling and inference paradigms: (1) Relevance networks (RNs): pairwise association scores independent of the remaining network; (2) graphical Gaussian models (GGMs): undirected graphical models with constraint-based inference, and (3) Bayesian networks (BNs): directed graphical models with score-based inference. The evaluation is carried out on the Raf pathway, a cellular signalling network describing the interaction of 11 phosphorylated proteins and phospholipids in human immune system cells. We use both laboratory data from cytometry experiments as well as data simulated from the gold-standard network. We also compare passive observations with active interventions. On Gaussian observational data, BNs and GGMs were found to outperform RNs. The difference in performance was not significant for the non-linear simulated data and the cytoflow data, though. Also, we did not observe a significant difference between BNs and GGMs on observational data in general. However, for interventional data, BNs outperform GGMs and RNs, especially when taking the edge directions rather than just the skeletons of the graphs into account. This suggests that the higher computational costs of inference with BNs over GGMs and RNs are not justified when using only passive observations, but that active interventions in the form of gene knockouts and over-expressions are required to exploit the full potential of BNs. Data, software and supplementary material are available from http://www.bioss.sari.ac.uk/staff/adriano/research.html

Nonlinearities in reservoir engineering: Enhancing quantum correlations

NASA Astrophysics Data System (ADS)

Hu, Xiangming; Hu, Qingping; Li, Lingchao; Huang, Chen; Rao, Shi

2017-12-01

There are two decisive factors for quantum correlations in reservoir engineering, but they are strongly reversely dependent on the atom-field nonlinearities. One is the squeezing parameter for the Bogoliubov modes-mediated collective interactions, while the other is the dissipative rates for the engineered collective dissipations. Exemplifying two-level atomic ensembles, we show that the moderate nonlinearities can compromise these two factors and thus enhance remarkably two-mode squeezing and entanglement of different spin atomic ensembles or different optical fields. This suggests that the moderate nonlinearities of the two-level systems are more advantageous for applications in quantum networks associated with reservoir engineering.

Systems and methods for modeling and analyzing networks

DOEpatents

Hill, Colin C; Church, Bruce W; McDonagh, Paul D; Khalil, Iya G; Neyarapally, Thomas A; Pitluk, Zachary W

2013-10-29

The systems and methods described herein utilize a probabilistic modeling framework for reverse engineering an ensemble of causal models, from data and then forward simulating the ensemble of models to analyze and predict the behavior of the network. In certain embodiments, the systems and methods described herein include data-driven techniques for developing causal models for biological networks. Causal network models include computational representations of the causal relationships between independent variables such as a compound of interest and dependent variables such as measured DNA alterations, changes in mRNA, protein, and metabolites to phenotypic readouts of efficacy and toxicity.

Reconfigurable RF Systems Using Commercially Available Digital Capacitor Arrays

DTIC Science & Technology

2013-03-01

for changing antenna loading. Note that for the receiver circuitry, the path through the FEM is reversed and the wideband RF engine is given...Network A tunable impedance-matching network is commonly used to match variable antenna impedance to the transmitter output or receiver input [1...2]. There are multiple utilities for this device. In one, the so-called static mode, the antenna can be matched to the rest of the system before

How to turn a genetic circuit into a synthetic tunable oscillator, or a bistable switch.

PubMed

Marucci, Lucia; Barton, David A W; Cantone, Irene; Ricci, Maria Aurelia; Cosma, Maria Pia; Santini, Stefania; di Bernardo, Diego; di Bernardo, Mario

2009-12-07

Systems and Synthetic Biology use computational models of biological pathways in order to study in silico the behaviour of biological pathways. Mathematical models allow to verify biological hypotheses and to predict new possible dynamical behaviours. Here we use the tools of non-linear analysis to understand how to change the dynamics of the genes composing a novel synthetic network recently constructed in the yeast Saccharomyces cerevisiae for In-vivo Reverse-engineering and Modelling Assessment (IRMA). Guided by previous theoretical results that make the dynamics of a biological network depend on its topological properties, through the use of simulation and continuation techniques, we found that the network can be easily turned into a robust and tunable synthetic oscillator or a bistable switch. Our results provide guidelines to properly re-engineering in vivo the network in order to tune its dynamics.

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.

An approach for reduction of false predictions in reverse engineering of gene regulatory networks.

PubMed

Khan, Abhinandan; Saha, Goutam; Pal, Rajat Kumar

2018-05-14

A gene regulatory network discloses the regulatory interactions amongst genes, at a particular condition of the human body. The accurate reconstruction of such networks from time-series genetic expression data using computational tools offers a stiff challenge for contemporary computer scientists. This is crucial to facilitate the understanding of the proper functioning of a living organism. Unfortunately, the computational methods produce many false predictions along with the correct predictions, which is unwanted. Investigations in the domain focus on the identification of as many correct regulations as possible in the reverse engineering of gene regulatory networks to make it more reliable and biologically relevant. One way to achieve this is to reduce the number of incorrect predictions in the reconstructed networks. In the present investigation, we have proposed a novel scheme to decrease the number of false predictions by suitably combining several metaheuristic techniques. We have implemented the same using a dataset ensemble approach (i.e. combining multiple datasets) also. We have employed the proposed methodology on real-world experimental datasets of the SOS DNA Repair network of Escherichia coli and the IMRA network of Saccharomyces cerevisiae. Subsequently, we have experimented upon somewhat larger, in silico networks, namely, DREAM3 and DREAM4 Challenge networks, and 15-gene and 20-gene networks extracted from the GeneNetWeaver database. To study the effect of multiple datasets on the quality of the inferred networks, we have used four datasets in each experiment. The obtained results are encouraging enough as the proposed methodology can reduce the number of false predictions significantly, without using any supplementary prior biological information for larger gene regulatory networks. It is also observed that if a small amount of prior biological information is incorporated here, the results improve further w.r.t. the prediction of true positives. Copyright © 2018 Elsevier Ltd. All rights reserved.

Reverse Engineering a Signaling Network Using Alternative Inputs

PubMed Central

Tanaka, Hiromasa; Yi, Tau-Mu

2009-01-01

One of the goals of systems biology is to reverse engineer in a comprehensive fashion the arrow diagrams of signal transduction systems. An important tool for ordering pathway components is genetic epistasis analysis, and here we present a strategy termed Alternative Inputs (AIs) to perform systematic epistasis analysis. An alternative input is defined as any genetic manipulation that can activate the signaling pathway instead of the natural input. We introduced the concept of an “AIs-Deletions matrix” that summarizes the outputs of all combinations of alternative inputs and deletions. We developed the theory and algorithms to construct a pairwise relationship graph from the AIs-Deletions matrix capturing both functional ordering (upstream, downstream) and logical relationships (AND, OR), and then interpreting these relationships into a standard arrow diagram. As a proof-of-principle, we applied this methodology to a subset of genes involved in yeast mating signaling. This experimental pilot study highlights the robustness of the approach and important technical challenges. In summary, this research formalizes and extends classical epistasis analysis from linear pathways to more complex networks, facilitating computational analysis and reconstruction of signaling arrow diagrams. PMID:19898612

Unraveling gene regulatory networks from time-resolved gene expression data -- a measures comparison study

PubMed Central

2011-01-01

Background Inferring regulatory interactions between genes from transcriptomics time-resolved data, yielding reverse engineered gene regulatory networks, is of paramount importance to systems biology and bioinformatics studies. Accurate methods to address this problem can ultimately provide a deeper insight into the complexity, behavior, and functions of the underlying biological systems. However, the large number of interacting genes coupled with short and often noisy time-resolved read-outs of the system renders the reverse engineering a challenging task. Therefore, the development and assessment of methods which are computationally efficient, robust against noise, applicable to short time series data, and preferably capable of reconstructing the directionality of the regulatory interactions remains a pressing research problem with valuable applications. Results Here we perform the largest systematic analysis of a set of similarity measures and scoring schemes within the scope of the relevance network approach which are commonly used for gene regulatory network reconstruction from time series data. In addition, we define and analyze several novel measures and schemes which are particularly suitable for short transcriptomics time series. We also compare the considered 21 measures and 6 scoring schemes according to their ability to correctly reconstruct such networks from short time series data by calculating summary statistics based on the corresponding specificity and sensitivity. Our results demonstrate that rank and symbol based measures have the highest performance in inferring regulatory interactions. In addition, the proposed scoring scheme by asymmetric weighting has shown to be valuable in reducing the number of false positive interactions. On the other hand, Granger causality as well as information-theoretic measures, frequently used in inference of regulatory networks, show low performance on the short time series analyzed in this study. Conclusions Our study is intended to serve as a guide for choosing a particular combination of similarity measures and scoring schemes suitable for reconstruction of gene regulatory networks from short time series data. We show that further improvement of algorithms for reverse engineering can be obtained if one considers measures that are rooted in the study of symbolic dynamics or ranks, in contrast to the application of common similarity measures which do not consider the temporal character of the employed data. Moreover, we establish that the asymmetric weighting scoring scheme together with symbol based measures (for low noise level) and rank based measures (for high noise level) are the most suitable choices. PMID:21771321

Towards a Rigorous Assessment of Systems Biology Models: The DREAM3 Challenges

PubMed Central

Prill, Robert J.; Marbach, Daniel; Saez-Rodriguez, Julio; Sorger, Peter K.; Alexopoulos, Leonidas G.; Xue, Xiaowei; Clarke, Neil D.; Altan-Bonnet, Gregoire; Stolovitzky, Gustavo

2010-01-01

Background Systems biology has embraced computational modeling in response to the quantitative nature and increasing scale of contemporary data sets. The onslaught of data is accelerating as molecular profiling technology evolves. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) is a community effort to catalyze discussion about the design, application, and assessment of systems biology models through annual reverse-engineering challenges. Methodology and Principal Findings We describe our assessments of the four challenges associated with the third DREAM conference which came to be known as the DREAM3 challenges: signaling cascade identification, signaling response prediction, gene expression prediction, and the DREAM3 in silico network challenge. The challenges, based on anonymized data sets, tested participants in network inference and prediction of measurements. Forty teams submitted 413 predicted networks and measurement test sets. Overall, a handful of best-performer teams were identified, while a majority of teams made predictions that were equivalent to random. Counterintuitively, combining the predictions of multiple teams (including the weaker teams) can in some cases improve predictive power beyond that of any single method. Conclusions DREAM provides valuable feedback to practitioners of systems biology modeling. Lessons learned from the predictions of the community provide much-needed context for interpreting claims of efficacy of algorithms described in the scientific literature. PMID:20186320

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.

Reverse Ecology: from systems to environments and back.

PubMed

Levy, Roie; Borenstein, Elhanan

2012-01-01

The structure of complex biological systems reflects not only their function but also the environments in which they evolved and are adapted to. Reverse Ecology-an emerging new frontier in Evolutionary Systems Biology-aims to extract this information and to obtain novel insights into an organism's ecology. The Reverse Ecology framework facilitates the translation of high-throughput genomic data into large-scale ecological data, and has the potential to transform ecology into a high-throughput field. In this chapter, we describe some of the pioneering work in Reverse Ecology, demonstrating how system-level analysis of complex biological networks can be used to predict the natural habitats of poorly characterized microbial species, their interactions with other species, and universal patterns governing the adaptation of organisms to their environments. We further present several studies that applied Reverse Ecology to elucidate various aspects of microbial ecology, and lay out exciting future directions and potential future applications in biotechnology, biomedicine, and ecological engineering.

Political science. Reverse-engineering censorship in China: randomized experimentation and participant observation.

PubMed

King, Gary; Pan, Jennifer; Roberts, Margaret E

2014-08-22

Existing research on the extensive Chinese censorship organization uses observational methods with well-known limitations. We conducted the first large-scale experimental study of censorship by creating accounts on numerous social media sites, randomly submitting different texts, and observing from a worldwide network of computers which texts were censored and which were not. We also supplemented interviews with confidential sources by creating our own social media site, contracting with Chinese firms to install the same censoring technologies as existing sites, and--with their software, documentation, and even customer support--reverse-engineering how it all works. Our results offer rigorous support for the recent hypothesis that criticisms of the state, its leaders, and their policies are published, whereas posts about real-world events with collective action potential are censored. Copyright © 2014, American Association for the Advancement of Science.

Automated smoother for the numerical decoupling of dynamics models.

PubMed

Vilela, Marco; Borges, Carlos C H; Vinga, Susana; Vasconcelos, Ana Tereza R; Santos, Helena; Voit, Eberhard O; Almeida, Jonas S

2007-08-21

Structure identification of dynamic models for complex biological systems is the cornerstone of their reverse engineering. Biochemical Systems Theory (BST) offers a particularly convenient solution because its parameters are kinetic-order coefficients which directly identify the topology of the underlying network of processes. We have previously proposed a numerical decoupling procedure that allows the identification of multivariate dynamic models of complex biological processes. While described here within the context of BST, this procedure has a general applicability to signal extraction. Our original implementation relied on artificial neural networks (ANN), which caused slight, undesirable bias during the smoothing of the time courses. As an alternative, we propose here an adaptation of the Whittaker's smoother and demonstrate its role within a robust, fully automated structure identification procedure. In this report we propose a robust, fully automated solution for signal extraction from time series, which is the prerequisite for the efficient reverse engineering of biological systems models. The Whittaker's smoother is reformulated within the context of information theory and extended by the development of adaptive signal segmentation to account for heterogeneous noise structures. The resulting procedure can be used on arbitrary time series with a nonstationary noise process; it is illustrated here with metabolic profiles obtained from in-vivo NMR experiments. The smoothed solution that is free of parametric bias permits differentiation, which is crucial for the numerical decoupling of systems of differential equations. The method is applicable in signal extraction from time series with nonstationary noise structure and can be applied in the numerical decoupling of system of differential equations into algebraic equations, and thus constitutes a rather general tool for the reverse engineering of mechanistic model descriptions from multivariate experimental time series.

MoCha: Molecular Characterization of Unknown Pathways.

PubMed

Lobo, Daniel; Hammelman, Jennifer; Levin, Michael

2016-04-01

Automated methods for the reverse-engineering of complex regulatory networks are paving the way for the inference of mechanistic comprehensive models directly from experimental data. These novel methods can infer not only the relations and parameters of the known molecules defined in their input datasets, but also unknown components and pathways identified as necessary by the automated algorithms. Identifying the molecular nature of these unknown components is a crucial step for making testable predictions and experimentally validating the models, yet no specific and efficient tools exist to aid in this process. To this end, we present here MoCha (Molecular Characterization), a tool optimized for the search of unknown proteins and their pathways from a given set of known interacting proteins. MoCha uses the comprehensive dataset of protein-protein interactions provided by the STRING database, which currently includes more than a billion interactions from over 2,000 organisms. MoCha is highly optimized, performing typical searches within seconds. We demonstrate the use of MoCha with the characterization of unknown components from reverse-engineered models from the literature. MoCha is useful for working on network models by hand or as a downstream step of a model inference engine workflow and represents a valuable and efficient tool for the characterization of unknown pathways using known data from thousands of organisms. MoCha and its source code are freely available online under the GPLv3 license.

Brain in situ hybridization maps as a source for reverse-engineering transcriptional regulatory networks: Alzheimer's disease insights

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

Acquaah-Mensah, George K.; Taylor, Ronald C.

Microarray data have been a valuable resource for identifying transcriptional regulatory relationships among genes. As an example, brain region-specific transcriptional regulatory events have the potential of providing etiological insights into Alzheimer Disease (AD). However, there is often a paucity of suitable brain-region specific expression data obtained via microarrays or other high throughput means. The Allen Brain Atlas in situ hybridization (ISH) data sets (Jones et al., 2009) represent a potentially valuable alternative source of high-throughput brain region-specific gene expression data for such purposes. In this study, Allen BrainAtlasmouse ISH data in the hippocampal fields were extracted, focusing on 508 genesmore » relevant to neurodegeneration. Transcriptional regulatory networkswere learned using three high-performing network inference algorithms. Only 17% of regulatory edges from a network reverse-engineered based on brain region-specific ISH data were also found in a network constructed upon gene expression correlations inmousewhole brain microarrays, thus showing the specificity of gene expression within brain sub-regions. Furthermore, the ISH data-based networks were used to identify instructive transcriptional regulatory relationships. Ncor2, Sp3 and Usf2 form a unique three-party regulatory motif, potentially affecting memory formation pathways. Nfe2l1, Egr1 and Usf2 emerge among regulators of genes involved in AD (e.g. Dhcr24, Aplp2, Tia1, Pdrx1, Vdac1, andSyn2). Further, Nfe2l1, Egr1 and Usf2 are sensitive to dietary factors and could be among links between dietary influences and genes in the AD etiology. Thus, this approach of harnessing brain region-specific ISH data represents a rare opportunity for gleaning unique etiological insights for diseases such as AD.« less

Dose and Time Dependencies in Stress Pathway Responses during Chemical Exposure: Novel Insights from Gene Regulatory Networks.

PubMed

Souza, Terezinha M; Kleinjans, Jos C S; Jennen, Danyel G J

2017-01-01

Perturbation of biological networks is often observed during exposure to xenobiotics, and the identification of disturbed processes, their dynamic traits, and dose-response relationships are some of the current challenges for elucidating the mechanisms determining adverse outcomes. In this scenario, reverse engineering of gene regulatory networks (GRNs) from expression data may provide a system-level snapshot embedded within accurate molecular events. Here, we investigate the composition of GRNs inferred from groups of chemicals with two distinct outcomes, namely carcinogenicity [azathioprine (AZA) and cyclophosphamide (CYC)] and drug-induced liver injury (DILI; diclofenac, nitrofurantoin, and propylthiouracil), and a non-carcinogenic/non-DILI group (aspirin, diazepam, and omeprazole). For this, we analyzed publicly available exposed in vitro human data, taking into account dose and time dependencies. Dose-Time Network Identification (DTNI) was applied to gene sets from exposed primary human hepatocytes using four stress pathways, namely endoplasmic reticulum (ER), NF-κB, NRF2, and TP53. Inferred GRNs suggested case specificity, varying in interactions, starting nodes, and target genes across groups. DILI and carcinogenic compounds were shown to directly affect all pathway-based GRNs, while non-DILI/non-carcinogenic chemicals only affected NF-κB. NF-κB-based GRNs clearly illustrated group-specific disturbances, with the cancer-related casein kinase CSNK2A1 being a target gene only in the carcinogenic group, and opposite regulation of NF-κB subunits being observed in DILI and non-DILI/non-carcinogenic groups. Target genes in NRF2-based GRNs shared by DILI and carcinogenic compounds suggested markers of hepatotoxicity. Finally, we indicate several of these group-specific interactions as potentially novel. In summary, our reversed-engineered GRNs are capable of revealing dose dependent, chemical-specific mechanisms of action in stress-related biological networks.

cGRNB: a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets.

PubMed

Xu, Huayong; Yu, Hui; Tu, Kang; Shi, Qianqian; Wei, Chaochun; Li, Yuan-Yuan; Li, Yi-Xue

2013-01-01

We are witnessing rapid progress in the development of methodologies for building the combinatorial gene regulatory networks involving both TFs (Transcription Factors) and miRNAs (microRNAs). There are a few tools available to do these jobs but most of them are not easy to use and not accessible online. A web server is especially needed in order to allow users to upload experimental expression datasets and build combinatorial regulatory networks corresponding to their particular contexts. In this work, we compiled putative TF-gene, miRNA-gene and TF-miRNA regulatory relationships from forward-engineering pipelines and curated them as built-in data libraries. We streamlined the R codes of our two separate forward-and-reverse engineering algorithms for combinatorial gene regulatory network construction and formalized them as two major functional modules. As a result, we released the cGRNB (combinatorial Gene Regulatory Networks Builder): a web server for constructing combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. The cGRNB enables two major network-building modules, one for MPGE (miRNA-perturbed gene expression) datasets and the other for parallel miRNA/mRNA expression datasets. A miRNA-centered two-layer combinatorial regulatory cascade is the output of the first module and a comprehensive genome-wide network involving all three types of combinatorial regulations (TF-gene, TF-miRNA, and miRNA-gene) are the output of the second module. In this article we propose cGRNB, a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. Since parallel miRNA/mRNA expression datasets are rapidly accumulated by the advance of next-generation sequencing techniques, cGRNB will be very useful tool for researchers to build combinatorial gene regulatory networks based on expression datasets. The cGRNB web-server is free and available online at http://www.scbit.org/cgrnb.

Reverse engineering gene regulatory networks from measurement with missing values.

PubMed

Ogundijo, Oyetunji E; Elmas, Abdulkadir; Wang, Xiaodong

2016-12-01

Gene expression time series data are usually in the form of high-dimensional arrays. Unfortunately, the data may sometimes contain missing values: for either the expression values of some genes at some time points or the entire expression values of a single time point or some sets of consecutive time points. This significantly affects the performance of many algorithms for gene expression analysis that take as an input, the complete matrix of gene expression measurement. For instance, previous works have shown that gene regulatory interactions can be estimated from the complete matrix of gene expression measurement. Yet, till date, few algorithms have been proposed for the inference of gene regulatory network from gene expression data with missing values. We describe a nonlinear dynamic stochastic model for the evolution of gene expression. The model captures the structural, dynamical, and the nonlinear natures of the underlying biomolecular systems. We present point-based Gaussian approximation (PBGA) filters for joint state and parameter estimation of the system with one-step or two-step missing measurements . The PBGA filters use Gaussian approximation and various quadrature rules, such as the unscented transform (UT), the third-degree cubature rule and the central difference rule for computing the related posteriors. The proposed algorithm is evaluated with satisfying results for synthetic networks, in silico networks released as a part of the DREAM project, and the real biological network, the in vivo reverse engineering and modeling assessment (IRMA) network of yeast Saccharomyces cerevisiae . PBGA filters are proposed to elucidate the underlying gene regulatory network (GRN) from time series gene expression data that contain missing values. In our state-space model, we proposed a measurement model that incorporates the effect of the missing data points into the sequential algorithm. This approach produces a better inference of the model parameters and hence, more accurate prediction of the underlying GRN compared to when using the conventional Gaussian approximation (GA) filters ignoring the missing data points.

Computational discovery and in vivo validation of hnf4 as a regulatory gene in planarian regeneration.

PubMed

Lobo, Daniel; Morokuma, Junji; Levin, Michael

2016-09-01

Automated computational methods can infer dynamic regulatory network models directly from temporal and spatial experimental data, such as genetic perturbations and their resultant morphologies. Recently, a computational method was able to reverse-engineer the first mechanistic model of planarian regeneration that can recapitulate the main anterior-posterior patterning experiments published in the literature. Validating this comprehensive regulatory model via novel experiments that had not yet been performed would add in our understanding of the remarkable regeneration capacity of planarian worms and demonstrate the power of this automated methodology. Using the Michigan Molecular Interactions and STRING databases and the MoCha software tool, we characterized as hnf4 an unknown regulatory gene predicted to exist by the reverse-engineered dynamic model of planarian regeneration. Then, we used the dynamic model to predict the morphological outcomes under different single and multiple knock-downs (RNA interference) of hnf4 and its predicted gene pathway interactors β-catenin and hh Interestingly, the model predicted that RNAi of hnf4 would rescue the abnormal regenerated phenotype (tailless) of RNAi of hh in amputated trunk fragments. Finally, we validated these predictions in vivo by performing the same surgical and genetic experiments with planarian worms, obtaining the same phenotypic outcomes predicted by the reverse-engineered model. These results suggest that hnf4 is a regulatory gene in planarian regeneration, validate the computational predictions of the reverse-engineered dynamic model, and demonstrate the automated methodology for the discovery of novel genes, pathways and experimental phenotypes. michael.levin@tufts.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Myths and realities: Defining re-engineering for a large organization

NASA Technical Reports Server (NTRS)

Yin, Sandra; Mccreary, Julia

1992-01-01

This paper describes the background and results of three studies concerning software reverse engineering, re-engineering, and reuse (R3) hosted by the Internal Revenue Service in 1991 and 1992. The situation at the Internal Revenue--aging, piecemeal computer systems and outdated technology maintained by a large staff--is familiar to many institutions, especially among management information systems. The IRS is distinctive for the sheer magnitude and diversity of its problems; the country's tax records are processed using assembly language and COBOL and spread across tape and network DBMS files. How do we proceed with replacing legacy systems? The three software re-engineering studies looked at methods, CASE tool support, and performed a prototype project using re-engineering methods and tools. During the course of these projects, we discovered critical issues broader than the mechanical definitions of methods and tool technology.

14 CFR 25.934 - Turbojet engine thrust reverser system tests.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Turbojet engine thrust reverser system... TRANSPORTATION AIRCRAFT AIRWORTHINESS STANDARDS: TRANSPORT CATEGORY AIRPLANES Powerplant General § 25.934 Turbojet engine thrust reverser system tests. Thrust reversers installed on turbojet engines must meet the...

Mass Conservation and Inference of Metabolic Networks from High-Throughput Mass Spectrometry Data

PubMed Central

Bandaru, Pradeep; Bansal, Mukesh

2011-01-01

Abstract We present a step towards the metabolome-wide computational inference of cellular metabolic reaction networks from metabolic profiling data, such as mass spectrometry. The reconstruction is based on identification of irreducible statistical interactions among the metabolite activities using the ARACNE reverse-engineering algorithm and on constraining possible metabolic transformations to satisfy the conservation of mass. The resulting algorithms are validated on synthetic data from an abridged computational model of Escherichia coli metabolism. Precision rates upwards of 50% are routinely observed for identification of full metabolic reactions, and recalls upwards of 20% are also seen. PMID:21314454

A reverse engineering approach to optimize experiments for the construction of biological regulatory networks.

PubMed

Zhang, Xiaomeng; Shao, Bin; Wu, Yangle; Qi, Ouyang

2013-01-01

One of the major objectives in systems biology is to understand the relation between the topological structures and the dynamics of biological regulatory networks. In this context, various mathematical tools have been developed to deduct structures of regulatory networks from microarray expression data. In general, from a single data set, one cannot deduct the whole network structure; additional expression data are usually needed. Thus how to design a microarray expression experiment in order to get the most information is a practical problem in systems biology. Here we propose three methods, namely, maximum distance method, trajectory entropy method, and sampling method, to derive the optimal initial conditions for experiments. The performance of these methods is tested and evaluated in three well-known regulatory networks (budding yeast cell cycle, fission yeast cell cycle, and E. coli. SOS network). Based on the evaluation, we propose an efficient strategy for the design of microarray expression experiments.

Reconstructing the regulatory network controlling commitment and sporulation in Physarum polycephalum based on hierarchical Petri Net modelling and simulation.

PubMed

Marwan, Wolfgang; Sujatha, Arumugam; Starostzik, Christine

2005-10-21

We reconstruct the regulatory network controlling commitment and sporulation of Physarum polycephalum from experimental results using a hierarchical Petri Net-based modelling and simulation framework. The stochastic Petri Net consistently describes the structure and simulates the dynamics of the molecular network as analysed by genetic, biochemical and physiological experiments within a single coherent model. The Petri Net then is extended to simulate time-resolved somatic complementation experiments performed by mixing the cytoplasms of mutants altered in the sporulation response, to systematically explore the network structure and to probe its dynamics. This reverse engineering approach presumably can be employed to explore other molecular or genetic signalling systems where the activity of genes or their products can be experimentally controlled in a time-resolved manner.

Recovering time-varying networks of dependencies in social and biological studies.

PubMed

Ahmed, Amr; Xing, Eric P

2009-07-21

A plausible representation of the relational information among entities in dynamic systems such as a living cell or a social community is a stochastic network that is topologically rewiring and semantically evolving over time. Although there is a rich literature in modeling static or temporally invariant networks, little has been done toward recovering the network structure when the networks are not observable in a dynamic context. In this article, we present a machine learning method called TESLA, which builds on a temporally smoothed l(1)-regularized logistic regression formalism that can be cast as a standard convex-optimization problem and solved efficiently by using generic solvers scalable to large networks. We report promising results on recovering simulated time-varying networks and on reverse engineering the latent sequence of temporally rewiring political and academic social networks from longitudinal data, and the evolving gene networks over >4,000 genes during the life cycle of Drosophila melanogaster from a microarray time course at a resolution limited only by sample frequency.

A systems biology model of the regulatory network in Populus leaves reveals interacting regulators and conserved regulation

PubMed Central

2011-01-01

Background Green plant leaves have always fascinated biologists as hosts for photosynthesis and providers of basic energy to many food webs. Today, comprehensive databases of gene expression data enable us to apply increasingly more advanced computational methods for reverse-engineering the regulatory network of leaves, and to begin to understand the gene interactions underlying complex emergent properties related to stress-response and development. These new systems biology methods are now also being applied to organisms such as Populus, a woody perennial tree, in order to understand the specific characteristics of these species. Results We present a systems biology model of the regulatory network of Populus leaves. The network is reverse-engineered from promoter information and expression profiles of leaf-specific genes measured over a large set of conditions related to stress and developmental. The network model incorporates interactions between regulators, such as synergistic and competitive relationships, by evaluating increasingly more complex regulatory mechanisms, and is therefore able to identify new regulators of leaf development not found by traditional genomics methods based on pair-wise expression similarity. The approach is shown to explain available gene function information and to provide robust prediction of expression levels in new data. We also use the predictive capability of the model to identify condition-specific regulation as well as conserved regulation between Populus and Arabidopsis. Conclusions We outline a computationally inferred model of the regulatory network of Populus leaves, and show how treating genes as interacting, rather than individual, entities identifies new regulators compared to traditional genomics analysis. Although systems biology models should be used with care considering the complexity of regulatory programs and the limitations of current genomics data, methods describing interactions can provide hypotheses about the underlying cause of emergent properties and are needed if we are to identify target genes other than those constituting the "low hanging fruit" of genomic analysis. PMID:21232107

Rational Design of an Ultrasensitive Quorum-Sensing Switch.

PubMed

Zeng, Weiqian; Du, Pei; Lou, Qiuli; Wu, Lili; Zhang, Haoqian M; Lou, Chunbo; Wang, Hongli; Ouyang, Qi

2017-08-18

One of the purposes of synthetic biology is to develop rational methods that accelerate the design of genetic circuits, saving time and effort spent on experiments and providing reliably predictable circuit performance. We applied a reverse engineering approach to design an ultrasensitive transcriptional quorum-sensing switch. We want to explore how systems biology can guide synthetic biology in the choice of specific DNA sequences and their regulatory relations to achieve a targeted function. The workflow comprises network enumeration that achieves the target function robustly, experimental restriction of the obtained candidate networks, global parameter optimization via mathematical analysis, selection and engineering of parts based on these calculations, and finally, circuit construction based on the principles of standardization and modularization. The performance of realized quorum-sensing switches was in good qualitative agreement with the computational predictions. This study provides practical principles for the rational design of genetic circuits with targeted functions.

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

PubMed Central

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. PMID:23180766

Genetic networks and soft computing.

PubMed

Mitra, Sushmita; Das, Ranajit; Hayashi, Yoichi

2011-01-01

The analysis of gene regulatory networks provides enormous information on various fundamental cellular processes involving growth, development, hormone secretion, and cellular communication. Their extraction from available gene expression profiles is a challenging problem. Such reverse engineering of genetic networks offers insight into cellular activity toward prediction of adverse effects of new drugs or possible identification of new drug targets. Tasks such as classification, clustering, and feature selection enable efficient mining of knowledge about gene interactions in the form of networks. It is known that biological data is prone to different kinds of noise and ambiguity. Soft computing tools, such as fuzzy sets, evolutionary strategies, and neurocomputing, have been found to be helpful in providing low-cost, acceptable solutions in the presence of various types of uncertainties. In this paper, we survey the role of these soft methodologies and their hybridizations, for the purpose of generating genetic networks.

Wisdom of crowds for robust gene network inference

PubMed Central

Marbach, Daniel; Costello, James C.; Küffner, Robert; Vega, Nicci; Prill, Robert J.; Camacho, Diogo M.; Allison, Kyle R.; Kellis, Manolis; Collins, James J.; Stolovitzky, Gustavo

2012-01-01

Reconstructing gene regulatory networks from high-throughput data is a long-standing problem. Through the DREAM project (Dialogue on Reverse Engineering Assessment and Methods), we performed a comprehensive blind assessment of over thirty network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae, and in silico microarray data. We characterize performance, data requirements, and inherent biases of different inference approaches offering guidelines for both algorithm application and development. We observe that no single inference method performs optimally across all datasets. In contrast, integration of predictions from multiple inference methods shows robust and high performance across diverse datasets. Thereby, we construct high-confidence networks for E. coli and S. aureus, each comprising ~1700 transcriptional interactions at an estimated precision of 50%. We experimentally test 53 novel interactions in E. coli, of which 23 were supported (43%). Our results establish community-based methods as a powerful and robust tool for the inference of transcriptional gene regulatory networks. PMID:22796662

A Bayesian Active Learning Experimental Design for Inferring Signaling Networks.

PubMed

Ness, Robert O; Sachs, Karen; Mallick, Parag; Vitek, Olga

2018-06-21

Machine learning methods for learning network structure are applied to quantitative proteomics experiments and reverse-engineer intracellular signal transduction networks. They provide insight into the rewiring of signaling within the context of a disease or a phenotype. To learn the causal patterns of influence between proteins in the network, the methods require experiments that include targeted interventions that fix the activity of specific proteins. However, the interventions are costly and add experimental complexity. We describe an active learning strategy for selecting optimal interventions. Our approach takes as inputs pathway databases and historic data sets, expresses them in form of prior probability distributions on network structures, and selects interventions that maximize their expected contribution to structure learning. Evaluations on simulated and real data show that the strategy reduces the detection error of validated edges as compared with an unguided choice of interventions and avoids redundant interventions, thereby increasing the effectiveness of the experiment.

Dynamic network reconstruction from gene expression data applied to immune response during bacterial infection.

PubMed

Guthke, Reinhard; Möller, Ulrich; Hoffmann, Martin; Thies, Frank; Töpfer, Susanne

2005-04-15

The immune response to bacterial infection represents a complex network of dynamic gene and protein interactions. We present an optimized reverse engineering strategy aimed at a reconstruction of this kind of interaction networks. The proposed approach is based on both microarray data and available biological knowledge. The main kinetics of the immune response were identified by fuzzy clustering of gene expression profiles (time series). The number of clusters was optimized using various evaluation criteria. For each cluster a representative gene with a high fuzzy-membership was chosen in accordance with available physiological knowledge. Then hypothetical network structures were identified by seeking systems of ordinary differential equations, whose simulated kinetics could fit the gene expression profiles of the cluster-representative genes. For the construction of hypothetical network structures singular value decomposition (SVD) based methods and a newly introduced heuristic Network Generation Method here were compared. It turned out that the proposed novel method could find sparser networks and gave better fits to the experimental data. Reinhard.Guthke@hki-jena.de.

Rewiring the severe acute respiratory syndrome coronavirus (SARS-CoV) transcription circuit: Engineering a recombination-resistant genome

NASA Astrophysics Data System (ADS)

Yount, Boyd; Roberts, Rhonda S.; Lindesmith, Lisa; Baric, Ralph S.

2006-08-01

Live virus vaccines provide significant protection against many detrimental human and animal diseases, but reversion to virulence by mutation and recombination has reduced appeal. Using severe acute respiratory syndrome coronavirus as a model, we engineered a different transcription regulatory circuit and isolated recombinant viruses. The transcription network allowed for efficient expression of the viral transcripts and proteins, and the recombinant viruses replicated to WT levels. Recombinant genomes were then constructed that contained mixtures of the WT and mutant regulatory circuits, reflecting recombinant viruses that might occur in nature. Although viable viruses could readily be isolated from WT and recombinant genomes containing homogeneous transcription circuits, chimeras that contained mixed regulatory networks were invariantly lethal, because viable chimeric viruses were not isolated. Mechanistically, mixed regulatory circuits promoted inefficient subgenomic transcription from inappropriate start sites, resulting in truncated ORFs and effectively minimize viral structural protein expression. Engineering regulatory transcription circuits of intercommunicating alleles successfully introduces genetic traps into a viral genome that are lethal in RNA recombinant progeny viruses. regulation | systems biology | vaccine design

Myxobacteria, Polarity, and Multicellular Morphogenesis

PubMed Central

Kaiser, Dale; Robinson, Mark; Kroos, Lee

2010-01-01

Myxobacteria are renowned for the ability to sporulate within fruiting bodies whose shapes are species-specific. The capacity to build those multicellular structures arises from the ability of M. xanthus to organize high cell-density swarms, in which the cells tend to be aligned with each other while constantly in motion. The intrinsic polarity of rod-shaped cells lays the foundation, and each cell uses two polar engines for gliding on surfaces. It sprouts retractile type IV pili from the leading cell pole and secretes capsular polysaccharide through nozzles from the trailing pole. Regularly periodic reversal of the gliding direction was found to be required for swarming. Those reversals are generated by a G-protein switch which is driven by a sharply tuned oscillator. Starvation induces fruiting body development, and systematic reductions in the reversal frequency are necessary for the cells to aggregate rather than continue to swarm. Developmental gene expression is regulated by a network that is connected to the suppression of reversals. PMID:20610548

Roles of beta-turns in protein folding: from peptide models to protein engineering.

PubMed

Marcelino, Anna Marie C; Gierasch, Lila M

2008-05-01

Reverse turns are a major class of protein secondary structure; they represent sites of chain reversal and thus sites where the globular character of a protein is created. It has been speculated for many years that turns may nucleate the formation of structure in protein folding, as their propensity to occur will favor the approximation of their flanking regions and their general tendency to be hydrophilic will favor their disposition at the solvent-accessible surface. Reverse turns are local features, and it is therefore not surprising that their structural properties have been extensively studied using peptide models. In this article, we review research on peptide models of turns to test the hypothesis that the propensities of turns to form in short peptides will relate to the roles of corresponding sequences in protein folding. Turns with significant stability as isolated entities should actively promote the folding of a protein, and by contrast, turn sequences that merely allow the chain to adopt conformations required for chain reversal are predicted to be passive in the folding mechanism. We discuss results of protein engineering studies of the roles of turn residues in folding mechanisms. Factors that correlate with the importance of turns in folding indeed include their intrinsic stability, as well as their topological context and their participation in hydrophobic networks within the protein's structure.

Roles of β-Turns in Protein Folding: From Peptide Models to Protein Engineering

PubMed Central

Marcelino, Anna Marie C.; Gierasch, Lila M.

2010-01-01

Reverse turns are a major class of protein secondary structure; they represent sites of chain reversal and thus sites where the globular character of a protein is created. It has been speculated for many years that turns may nucleate the formation of structure in protein folding, as their propensity to occur will favor the approximation of their flanking regions and their general tendency to be hydrophilic will favor their disposition at the solvent-accessible surface. Reverse turns are local features, and it is therefore not surprising that their structural properties have been extensively studied using peptide models. In this article, we review research on peptide models of turns to test the hypothesis that the propensities of turns to form in short peptides will relate to the roles of corresponding sequences in protein folding. Turns with significant stability as isolated entities should actively promote the folding of a protein, and by contrast, turn sequences that merely allow the chain to adopt conformations required for chain reversal are predicted to be passive in the folding mechanism. We discuss results of protein engineering studies of the roles of turn residues in folding mechanisms. Factors that correlate with the importance of turns in folding indeed include their intrinsic stability, as well as their topological context and their participation in hydrophobic networks within the protein’s structure. PMID:18275088

Reconstruction of network topology using status-time-series data

NASA Astrophysics Data System (ADS)

Pandey, Pradumn Kumar; Badarla, Venkataramana

2018-01-01

Uncovering the heterogeneous connection pattern of a networked system from the available status-time-series (STS) data of a dynamical process on the network is of great interest in network science and known as a reverse engineering problem. Dynamical processes on a network are affected by the structure of the network. The dependency between the diffusion dynamics and structure of the network can be utilized to retrieve the connection pattern from the diffusion data. Information of the network structure can help to devise the control of dynamics on the network. In this paper, we consider the problem of network reconstruction from the available status-time-series (STS) data using matrix analysis. The proposed method of network reconstruction from the STS data is tested successfully under susceptible-infected-susceptible (SIS) diffusion dynamics on real-world and computer-generated benchmark networks. High accuracy and efficiency of the proposed reconstruction procedure from the status-time-series data define the novelty of the method. Our proposed method outperforms compressed sensing theory (CST) based method of network reconstruction using STS data. Further, the same procedure of network reconstruction is applied to the weighted networks. The ordering of the edges in the weighted networks is identified with high accuracy.

Advancing reversible shape memory by tuning the polymer network architecture

DOE PAGES

Li, Qiaoxi; Zhou, Jing; Vatankhah-Varnoosfaderani, Mohammad; ...

2016-02-02

Because of counteraction of a chemical network and a crystalline scaffold, semicrystalline polymer networks exhibit a peculiar behavior—reversible shape memory (RSM), which occurs naturally without applying any external force and particular structural design. There are three RSM properties: (i) range of reversible strain, (ii) rate of strain recovery, and (iii) decay of reversibility with time, which can be improved by tuning the architecture of the polymer network. Different types of poly(octylene adipate) networks were synthesized, allowing for control of cross-link density and network topology, including randomly cross-linked network by free-radical polymerization, thiol–ene clicked network with enhanced mesh uniformity, and loosemore » network with deliberately incorporated dangling chains. It is shown that the RSM properties are controlled by average cross-link density and crystal size, whereas topology of a network greatly affects its extensibility. In conclusion, we have achieved 80% maximum reversible range, 15% minimal decrease in reversibility, and fast strain recovery rate up to 0.05 K –1, i.e., ca. 5% per 10 s at a cooling rate of 5 K/min.« less

14 CFR 23.934 - Turbojet and turbofan engine thrust reverser systems tests.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Turbojet and turbofan engine thrust... CATEGORY AIRPLANES Powerplant General § 23.934 Turbojet and turbofan engine thrust reverser systems tests. Thrust reverser systems of turbojet or turbofan engines must meet the requirements of § 33.97 of this...

14 CFR 23.1155 - Turbine engine reverse thrust and propeller pitch settings below the flight regime.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Turbine engine reverse thrust and propeller... COMMUTER CATEGORY AIRPLANES Powerplant Powerplant Controls and Accessories § 23.1155 Turbine engine reverse thrust and propeller pitch settings below the flight regime. For turbine engine installations, each...

14 CFR 23.1155 - Turbine engine reverse thrust and propeller pitch settings below the flight regime.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Turbine engine reverse thrust and propeller... COMMUTER CATEGORY AIRPLANES Powerplant Powerplant Controls and Accessories § 23.1155 Turbine engine reverse thrust and propeller pitch settings below the flight regime. For turbine engine installations, each...

14 CFR 23.1155 - Turbine engine reverse thrust and propeller pitch settings below the flight regime.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Turbine engine reverse thrust and propeller... COMMUTER CATEGORY AIRPLANES Powerplant Powerplant Controls and Accessories § 23.1155 Turbine engine reverse thrust and propeller pitch settings below the flight regime. For turbine engine installations, each...

14 CFR 23.1155 - Turbine engine reverse thrust and propeller pitch settings below the flight regime.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Turbine engine reverse thrust and propeller... COMMUTER CATEGORY AIRPLANES Powerplant Powerplant Controls and Accessories § 23.1155 Turbine engine reverse thrust and propeller pitch settings below the flight regime. For turbine engine installations, each...

14 CFR 23.1155 - Turbine engine reverse thrust and propeller pitch settings below the flight regime.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Turbine engine reverse thrust and propeller... COMMUTER CATEGORY AIRPLANES Powerplant Powerplant Controls and Accessories § 23.1155 Turbine engine reverse thrust and propeller pitch settings below the flight regime. For turbine engine installations, each...

Expectation propagation for large scale Bayesian inference of non-linear molecular networks from perturbation data.

PubMed

Narimani, Zahra; Beigy, Hamid; Ahmad, Ashar; Masoudi-Nejad, Ali; Fröhlich, Holger

2017-01-01

Inferring the structure of molecular networks from time series protein or gene expression data provides valuable information about the complex biological processes of the cell. Causal network structure inference has been approached using different methods in the past. Most causal network inference techniques, such as Dynamic Bayesian Networks and ordinary differential equations, are limited by their computational complexity and thus make large scale inference infeasible. This is specifically true if a Bayesian framework is applied in order to deal with the unavoidable uncertainty about the correct model. We devise a novel Bayesian network reverse engineering approach using ordinary differential equations with the ability to include non-linearity. Besides modeling arbitrary, possibly combinatorial and time dependent perturbations with unknown targets, one of our main contributions is the use of Expectation Propagation, an algorithm for approximate Bayesian inference over large scale network structures in short computation time. We further explore the possibility of integrating prior knowledge into network inference. We evaluate the proposed model on DREAM4 and DREAM8 data and find it competitive against several state-of-the-art existing network inference methods.

Bayesian network prior: network analysis of biological data using external knowledge

PubMed Central

Isci, Senol; Dogan, Haluk; Ozturk, Cengizhan; Otu, Hasan H.

2014-01-01

Motivation: Reverse engineering GI networks from experimental data is a challenging task due to the complex nature of the networks and the noise inherent in the data. One way to overcome these hurdles would be incorporating the vast amounts of external biological knowledge when building interaction networks. We propose a framework where GI networks are learned from experimental data using Bayesian networks (BNs) and the incorporation of external knowledge is also done via a BN that we call Bayesian Network Prior (BNP). BNP depicts the relation between various evidence types that contribute to the event ‘gene interaction’ and is used to calculate the probability of a candidate graph (G) in the structure learning process. Results: Our simulation results on synthetic, simulated and real biological data show that the proposed approach can identify the underlying interaction network with high accuracy even when the prior information is distorted and outperforms existing methods. Availability: Accompanying BNP software package is freely available for academic use at http://bioe.bilgi.edu.tr/BNP. Contact: hasan.otu@bilgi.edu.tr Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:24215027

Thermodynamic Constraints Improve Metabolic Networks.

PubMed

Krumholz, Elias W; Libourel, Igor G L

2017-08-08

In pursuit of establishing a realistic metabolic phenotypic space, the reversibility of reactions is thermodynamically constrained in modern metabolic networks. The reversibility constraints follow from heuristic thermodynamic poise approximations that take anticipated cellular metabolite concentration ranges into account. Because constraints reduce the feasible space, draft metabolic network reconstructions may need more extensive reconciliation, and a larger number of genes may become essential. Notwithstanding ubiquitous application, the effect of reversibility constraints on the predictive capabilities of metabolic networks has not been investigated in detail. Instead, work has focused on the implementation and validation of the thermodynamic poise calculation itself. With the advance of fast linear programming-based network reconciliation, the effects of reversibility constraints on network reconciliation and gene essentiality predictions have become feasible and are the subject of this study. Networks with thermodynamically informed reversibility constraints outperformed gene essentiality predictions compared to networks that were constrained with randomly shuffled constraints. Unconstrained networks predicted gene essentiality as accurately as thermodynamically constrained networks, but predicted substantially fewer essential genes. Networks that were reconciled with sequence similarity data and strongly enforced reversibility constraints outperformed all other networks. We conclude that metabolic network analysis confirmed the validity of the thermodynamic constraints, and that thermodynamic poise information is actionable during network reconciliation. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Digital photocontrol of the network of live excitable cells

NASA Astrophysics Data System (ADS)

Erofeev, I. S.; Magome, N.; Agladze, K. I.

2011-11-01

Recent development of tissue engineering techniques allows creating and maintaining almost indefinitely networks of excitable cells with desired architecture. We coupled the network of live excitable cardiac cells with a common computer by sensitizing them to light, projecting a light pattern on the layer of cells, and monitoring excitation with the aid of fluorescent probes (optical mapping). As a sensitizing substance we used azobenzene trimethylammonium bromide (AzoTAB). This substance undergoes cis-trans-photoisomerization and trans-isomer of AzoTAB inhibits excitation in the cardiac cells, while cis-isomer does not. AzoTAB-mediated sensitization allows, thus, reversible and dynamic control of the excitation waves through the entire cardiomyocyte network either uniformly, or in a preferred spatial pattern. Technically, it was achieved by coupling a common digital projector with a macroview microscope and using computer graphic software for creating the projected pattern of conducting pathways. This approach allows real time interactive photocontrol of the heart tissue.

Snoopy--a unifying Petri net framework to investigate biomolecular networks.

PubMed

Rohr, Christian; Marwan, Wolfgang; Heiner, Monika

2010-04-01

To investigate biomolecular networks, Snoopy provides a unifying Petri net framework comprising a family of related Petri net classes. Models can be hierarchically structured, allowing for the mastering of larger networks. To move easily between the qualitative, stochastic and continuous modelling paradigms, models can be converted into each other. We get models sharing structure, but specialized by their kinetic information. The analysis and iterative reverse engineering of biomolecular networks is supported by the simultaneous use of several Petri net classes, while the graphical user interface adapts dynamically to the active one. Built-in animation and simulation are complemented by exports to various analysis tools. Snoopy facilitates the addition of new Petri net classes thanks to its generic design. Our tool with Petri net samples is available free of charge for non-commercial use at http://www-dssz.informatik.tu-cottbus.de/snoopy.html; supported operating systems: Mac OS X, Windows and Linux (selected distributions).

Extending the boundaries of reverse engineering

NASA Astrophysics Data System (ADS)

Lawrie, Chris

2002-04-01

In today's market place the potential of Reverse Engineering as a time compression tool is commonly lost under its traditional definition. The term Reverse Engineering was coined way back at the advent of CMM machines and 3D CAD systems to describe the process of fitting surfaces to captured point data. Since these early beginnings, downstream hardware scanning and digitising systems have evolved in parallel with an upstream demand, greatly increasing the potential of a point cloud data set within engineering design and manufacturing processes. The paper will discuss the issues surrounding Reverse Engineering at the turn of the millennium.

Large-Scale Wind-Tunnel Tests of Exhaust Ingestion Due to Thrust Reversal on a Four-Engine Jet Transport during Ground Roll

NASA Technical Reports Server (NTRS)

Tolhurst, William H., Jr.; Hickey, David H.; Aoyagi, Kiyoshi

1961-01-01

Wind-tunnel tests have been conducted on a large-scale model of a swept-wing jet transport type airplane to study the factors affecting exhaust gas ingestion into the engine inlets when thrust reversal is used during ground roll. The model was equipped with four small jet engines mounted in nacelles beneath the wing. The tests included studies of both cascade and target type reversers. The data obtained included the free-stream velocity at the occurrence of exhaust gas ingestion in the outboard engine and the increment of drag due to thrust reversal for various modifications of thrust reverser configuration. Motion picture films of smoke flow studies were also obtained to supplement the data. The results show that the free-stream velocity at which ingestion occurred in the outboard engines could be reduced considerably, by simple modifications to the reversers, without reducing the effective drag due to reversed thrust.

Reverse thrust performance of the QCSEE variable pitch turbofan engine

NASA Technical Reports Server (NTRS)

Samanich, N. E.; Reemsnyder, D. C.; Blodmer, H. E.

1980-01-01

Results of steady state reverse and forward to reverse thrust transient performance tests are presented. The original quiet, clean, short haul, experimental engine four segment variable fan nozzle was retested in reverse and compared with a continuous, 30 deg half angle conical exlet. Data indicated that the significantly more stable, higher pressure recovery flow with the fixed 30 deg exlet resulted in lower engine vibrations, lower fan blade stress, and approximately a 20 percent improvement in reverse thrust. Objective reverse thrust of 35 percent of takeoff thrust was reached. Thrust response of less than 1.5 sec was achieved for the approach and the takeoff to reverse thrust transients.

14 CFR 23.933 - Reversing systems.

Code of Federal Regulations, 2013 CFR

2013-01-01

... analysis and testing completed by the engine and propeller manufacturers. [Doc. No. 26344, 58 FR 18971, Apr... only must be designed so that, during any reversal in flight, the engine will produce no more than... engine from producing more than idle thrust when the reversing system malfunctions; except that it may...

14 CFR 23.933 - Reversing systems.

Code of Federal Regulations, 2014 CFR

2014-01-01

... analysis and testing completed by the engine and propeller manufacturers. [Doc. No. 26344, 58 FR 18971, Apr... only must be designed so that, during any reversal in flight, the engine will produce no more than... engine from producing more than idle thrust when the reversing system malfunctions; except that it may...

14 CFR 23.933 - Reversing systems.

Code of Federal Regulations, 2012 CFR

2012-01-01

... analysis and testing completed by the engine and propeller manufacturers. [Doc. No. 26344, 58 FR 18971, Apr... only must be designed so that, during any reversal in flight, the engine will produce no more than... engine from producing more than idle thrust when the reversing system malfunctions; except that it may...

14 CFR 23.933 - Reversing systems.

Code of Federal Regulations, 2011 CFR

2011-01-01

... analysis and testing completed by the engine and propeller manufacturers. [Doc. No. 26344, 58 FR 18971, Apr... only must be designed so that, during any reversal in flight, the engine will produce no more than... engine from producing more than idle thrust when the reversing system malfunctions; except that it may...

14 CFR 23.933 - Reversing systems.

Code of Federal Regulations, 2010 CFR

2010-01-01

... analysis and testing completed by the engine and propeller manufacturers. [Doc. No. 26344, 58 FR 18971, Apr... only must be designed so that, during any reversal in flight, the engine will produce no more than... engine from producing more than idle thrust when the reversing system malfunctions; except that it may...

Engineering Solid-State Materials. Strategies for Modeling and Packing Control of Molecular Assemblies into 3-D Networks

DTIC Science & Technology

1993-04-22

cocrystal /materials design/hydrogen bonding 19 ABSTRACT (Continue on reverse if necessary and identify by block number) The crystal structure and...proterties of a number of urea cocrystals are studied with regard to symmetry of the hydrogen-bonded molecular assemblies. The logical consequences of...symmetry element A or M. ¶/or 2 Results: Our specific goals are to design and synthesize urea based cocrystals in which the twofold symmetry and hydrogen

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

Computational Analysis of Molecular Interaction Networks Underlying Change of HIV-1 Resistance to Selected Reverse Transcriptase Inhibitors

PubMed Central

Kierczak, Marcin; Dramiński, Michał; Koronacki, Jacek; Komorowski, Jan

2010-01-01

Motivation Despite more than two decades of research, HIV resistance to drugs remains a serious obstacle in developing efficient AIDS treatments. Several computational methods have been developed to predict resistance level from the sequence of viral proteins such as reverse transcriptase (RT) or protease. These methods, while powerful and accurate, give very little insight into the molecular interactions that underly acquisition of drug resistance/hypersusceptibility. Here, we attempt at filling this gap by using our Monte Carlo feature selection and interdependency discovery method (MCFS-ID) to elucidate molecular interaction networks that characterize viral strains with altered drug resistance levels. Results We analyzed a number of HIV-1 RT sequences annotated with drug resistance level using the MCFS-ID method. This let us expound interdependency networks that characterize change of drug resistance to six selected RT inhibitors: Abacavir, Lamivudine, Stavudine, Zidovudine, Tenofovir and Nevirapine. The networks consider interdependencies at the level of physicochemical properties of mutating amino acids, eg,: polarity. We mapped each network on the 3D structure of RT in attempt to understand the molecular meaning of interacting pairs. The discovered interactions describe several known drug resistance mechanisms and, importantly, some previously unidentified ones. Our approach can be easily applied to a whole range of problems from the domain of protein engineering. Availability A portable Java implementation of our MCFS-ID method is freely available for academic users and can be obtained at: http://www.ipipan.eu/staff/m.draminski/software.htm. PMID:21234299

Computational Analysis of Molecular Interaction Networks Underlying Change of HIV-1 Resistance to Selected Reverse Transcriptase Inhibitors.

PubMed

Kierczak, Marcin; Dramiński, Michał; Koronacki, Jacek; Komorowski, Jan

2010-12-12

Despite more than two decades of research, HIV resistance to drugs remains a serious obstacle in developing efficient AIDS treatments. Several computational methods have been developed to predict resistance level from the sequence of viral proteins such as reverse transcriptase (RT) or protease. These methods, while powerful and accurate, give very little insight into the molecular interactions that underly acquisition of drug resistance/hypersusceptibility. Here, we attempt at filling this gap by using our Monte Carlo feature selection and interdependency discovery method (MCFS-ID) to elucidate molecular interaction networks that characterize viral strains with altered drug resistance levels. We analyzed a number of HIV-1 RT sequences annotated with drug resistance level using the MCFS-ID method. This let us expound interdependency networks that characterize change of drug resistance to six selected RT inhibitors: Abacavir, Lamivudine, Stavudine, Zidovudine, Tenofovir and Nevirapine. The networks consider interdependencies at the level of physicochemical properties of mutating amino acids, eg,: polarity. We mapped each network on the 3D structure of RT in attempt to understand the molecular meaning of interacting pairs. The discovered interactions describe several known drug resistance mechanisms and, importantly, some previously unidentified ones. Our approach can be easily applied to a whole range of problems from the domain of protein engineering. A portable Java implementation of our MCFS-ID method is freely available for academic users and can be obtained at: http://www.ipipan.eu/staff/m.draminski/software.htm.

φ-evo: A program to evolve phenotypic models of biological networks.

PubMed

Henry, Adrien; Hemery, Mathieu; François, Paul

2018-06-01

Molecular networks are at the core of most cellular decisions, but are often difficult to comprehend. Reverse engineering of network architecture from their functions has proved fruitful to classify and predict the structure and function of molecular networks, suggesting new experimental tests and biological predictions. We present φ-evo, an open-source program to evolve in silico phenotypic networks performing a given biological function. We include implementations for evolution of biochemical adaptation, adaptive sorting for immune recognition, metazoan development (somitogenesis, hox patterning), as well as Pareto evolution. We detail the program architecture based on C, Python 3, and a Jupyter interface for project configuration and network analysis. We illustrate the predictive power of φ-evo by first recovering the asymmetrical structure of the lac operon regulation from an objective function with symmetrical constraints. Second, we use the problem of hox-like embryonic patterning to show how a single effective fitness can emerge from multi-objective (Pareto) evolution. φ-evo provides an efficient approach and user-friendly interface for the phenotypic prediction of networks and the numerical study of evolution itself.

Impact of environmental inputs on reverse-engineering approach to network structures.

PubMed

Wu, Jianhua; Sinfield, James L; Buchanan-Wollaston, Vicky; Feng, Jianfeng

2009-12-04

Uncovering complex network structures from a biological system is one of the main topic in system biology. The network structures can be inferred by the dynamical Bayesian network or Granger causality, but neither techniques have seriously taken into account the impact of environmental inputs. With considerations of natural rhythmic dynamics of biological data, we propose a system biology approach to reveal the impact of environmental inputs on network structures. We first represent the environmental inputs by a harmonic oscillator and combine them with Granger causality to identify environmental inputs and then uncover the causal network structures. We also generalize it to multiple harmonic oscillators to represent various exogenous influences. This system approach is extensively tested with toy models and successfully applied to a real biological network of microarray data of the flowering genes of the model plant Arabidopsis Thaliana. The aim is to identify those genes that are directly affected by the presence of the sunlight and uncover the interactive network structures associating with flowering metabolism. We demonstrate that environmental inputs are crucial for correctly inferring network structures. Harmonic causal method is proved to be a powerful technique to detect environment inputs and uncover network structures, especially when the biological data exhibit periodic oscillations.

Programming temporal shapeshifting

NASA Astrophysics Data System (ADS)

Hu, Xiaobo; Zhou, Jing; Vatankhah-Varnosfaderani, Mohammad; Daniel, William F. M.; Li, Qiaoxi; Zhushma, Aleksandr P.; Dobrynin, Andrey V.; Sheiko, Sergei S.

2016-09-01

Shapeshifting enables a wide range of engineering and biomedical applications, but until now transformations have required external triggers. This prerequisite limits viability in closed or inert systems and puts forward the challenge of developing materials with intrinsically encoded shape evolution. Herein we demonstrate programmable shape-memory materials that perform a sequence of encoded actuations under constant environment conditions without using an external trigger. We employ dual network hydrogels: in the first network, covalent crosslinks are introduced for elastic energy storage, and in the second one, temporary hydrogen-bonds regulate the energy release rate. Through strain-induced and time-dependent reorganization of the reversible hydrogen-bonds, this dual network allows for encoding both the rate and pathway of shape transformations on timescales from seconds to hours. This generic mechanism for programming trigger-free shapeshifting opens new ways to design autonomous actuators, drug-release systems and active implants.

Experimental Study of Quantum Graphs With and Without Time-Reversal Invariance

NASA Astrophysics Data System (ADS)

Anlage, Steven Mark; Fu, Ziyuan; Koch, Trystan; Antonsen, Thomas; Ott, Edward

An experimental setup consisting of a microwave network is used to simulate quantum graphs. The random coupling model (RCM) is applied to describe the universal statistical properties of the system with and without time-reversal invariance. The networks which are large compared to the wavelength, are constructed from coaxial cables connected by T junctions, and by making nodes with circulators time-reversal invariance for microwave propagation in the networks can be broken. The results of experimental study of microwave networks with and without time-reversal invariance are presented both in frequency domain and time domain. With the measured S-parameter data of two-port networks, the impedance statistics and the nearest-neighbor spacing statistics are examined. Moreover, the experiments of time reversal mirrors for networks demonstrate that the reconstruction quality can be used to quantify the degree of the time-reversal invariance for wave propagation. Numerical models of networks are also presented to verify the time domain experiments. We acknowledge support under contract AFOSR COE Grant FA9550-15-1-0171 and the ONR Grant N000141512134.

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...

Automated reverse engineering of nonlinear dynamical systems.

PubMed

Bongard, Josh; Lipson, Hod

2007-06-12

Complex nonlinear dynamics arise in many fields of science and engineering, but uncovering the underlying differential equations directly from observations poses a challenging task. The ability to symbolically model complex networked systems is key to understanding them, an open problem in many disciplines. Here we introduce for the first time a method that can automatically generate symbolic equations for a nonlinear coupled dynamical system directly from time series data. This method is applicable to any system that can be described using sets of ordinary nonlinear differential equations, and assumes that the (possibly noisy) time series of all variables are observable. Previous automated symbolic modeling approaches of coupled physical systems produced linear models or required a nonlinear model to be provided manually. The advance presented here is made possible by allowing the method to model each (possibly coupled) variable separately, intelligently perturbing and destabilizing the system to extract its less observable characteristics, and automatically simplifying the equations during modeling. We demonstrate this method on four simulated and two real systems spanning mechanics, ecology, and systems biology. Unlike numerical models, symbolic models have explanatory value, suggesting that automated "reverse engineering" approaches for model-free symbolic nonlinear system identification may play an increasing role in our ability to understand progressively more complex systems in the future.

Study of time-reversal-based signal processing applied to polarimetric GPR detection of elongated targets

NASA Astrophysics Data System (ADS)

Santos, Vinicius Rafael N.; Teixeira, Fernando L.

2017-04-01

Ground penetrating radar (GPR) is a useful sensing modality for mapping and identification of underground infrastructure networks, such as metal and concrete pipes (gas, water or sewer), phone conduits or cables, and other buried objects. Due to the polarization-dependent response of typical targets, it is of interest to investigate the optimum antenna arrangement and/or combination of arrangements that maximize the detection and classification capabilities of polarimetric GPR imaging systems. Here, we provide a preliminary study of time-reversal-based techniques applied to target detection by GPR utilizing different relative orientations of linear-polarized antenna elements (with respect to each other, as well as to the targets). We modeled three different pipe materials (metallic, plastic and concrete) and GPR systems operating at center frequencies of 100 MHz and 200 MHz. Full-wave numerical simulations are adopted to account for mutual coupling between targets. This type of assessment study may contribute to the improvement of GPR data interpretation of infrastructure networks in urban area surveys and in other engineering studies.

14 CFR 25.933 - Reversing systems.

Code of Federal Regulations, 2014 CFR

2014-01-01

... reversal in flight the engine will produce no more than flight idle thrust. In addition, it must be shown... kind of failure is extremely remote. (3) Each system must have means to prevent the engine from... alone, under the most critical reversing condition expected in operation. (b) For propeller reversing...

14 CFR 25.933 - Reversing systems.

Code of Federal Regulations, 2012 CFR

2012-01-01

... reversal in flight the engine will produce no more than flight idle thrust. In addition, it must be shown... kind of failure is extremely remote. (3) Each system must have means to prevent the engine from... alone, under the most critical reversing condition expected in operation. (b) For propeller reversing...

14 CFR 25.933 - Reversing systems.

Code of Federal Regulations, 2011 CFR

2011-01-01

... reversal in flight the engine will produce no more than flight idle thrust. In addition, it must be shown... kind of failure is extremely remote. (3) Each system must have means to prevent the engine from... alone, under the most critical reversing condition expected in operation. (b) For propeller reversing...

DIC-CAM recipe for reverse engineering

NASA Astrophysics Data System (ADS)

Romero-Carrillo, P.; Lopez-Alba, E.; Dorado, R.; Diaz-Garrido, F. A.

2012-04-01

Reverse engineering (RE) tries to model and manufacture an object from measurements one of a reference object. Modern optical measurement systems and computer aided engineering software have improved reverse engineering procedures. We detail the main RE steps from 3D digitalization by Digital Image Correlation to manufacturing. The previous description is complemented with an application example, which portrays the performance of RE. The differences between original and manufactured objects are less than 2 mm (close to the tool radius).

Flight Measurements of the Effect of a Controllable Thrust Reverser on the Flight Characteristics of a Single-Engine Jet Airplane

NASA Technical Reports Server (NTRS)

Anderson, Seth B.; Cooper, George E.; Faye, Alan E., Jr.

1959-01-01

A flight investigation was undertaken to determine the effect of a fully controllable thrust reverser on the flight characteristics of a single-engine jet airplane. Tests were made using a cylindrical target-type reverser actuated by a hydraulic cylinder through a "beep-type" cockpit control mounted at the base of the throttle. The thrust reverser was evaluated as an in-flight decelerating device, as a flight path control and airspeed control in landing approach, and as a braking device during the ground roll. Full deflection of the reverser for one reverser configuration resulted in a reverse thrust ratio of as much as 85 percent, which at maximum engine power corresponded to a reversed thrust of 5100 pounds. Use of the reverser in landing approach made possible a wide selection of approach angles, a large reduction in approach speed at steep approach angles, improved control of flight path angle, and more accuracy in hitting a given touchdown point. The use of the reverser as a speed brake at lower airspeeds was compromised by a longitudinal trim change. At the lower airspeeds and higher engine powers there was insufficient elevator power to overcome the nose-down trim change at full reverser deflection.

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

Hu, Xiaobo; Zhou, Jing; Vatankhah-Varnosfaderani, Mohammad

Shapeshifting enables a wide range of engineering and biomedical applications, but until now transformations have required external triggers. This prerequisite limits viability in closed or inert systems and puts forward the challenge of developing materials with intrinsically encoded shape evolution. Herein we demonstrate programmable shape-memory materials that perform a sequence of encoded actuations under constant environment conditions without using an external trigger. We employ dual network hydrogels: in the first network, covalent crosslinks are introduced for elastic energy storage, and in the second one, temporary hydrogen-bonds regulate the energy release rate. Through strain-induced and time-dependent reorganization of the reversible hydrogen-bonds,more » this dual network allows for encoding both the rate and pathway of shape transformations on timescales from seconds to hours. In conclusion, this generic mechanism for programming trigger-free shapeshifting opens new ways to design autonomous actuators, drug-release systems and active implants.« less

Programming temporal shapeshifting

DOE PAGES

Hu, Xiaobo; Zhou, Jing; Vatankhah-Varnosfaderani, Mohammad; ...

2016-09-27

Shapeshifting enables a wide range of engineering and biomedical applications, but until now transformations have required external triggers. This prerequisite limits viability in closed or inert systems and puts forward the challenge of developing materials with intrinsically encoded shape evolution. Herein we demonstrate programmable shape-memory materials that perform a sequence of encoded actuations under constant environment conditions without using an external trigger. We employ dual network hydrogels: in the first network, covalent crosslinks are introduced for elastic energy storage, and in the second one, temporary hydrogen-bonds regulate the energy release rate. Through strain-induced and time-dependent reorganization of the reversible hydrogen-bonds,more » this dual network allows for encoding both the rate and pathway of shape transformations on timescales from seconds to hours. In conclusion, this generic mechanism for programming trigger-free shapeshifting opens new ways to design autonomous actuators, drug-release systems and active implants.« less

A Change in the Ion Selectivity of Ligand-Gated Ion Channels Provides a Mechanism to Switch Behavior.

PubMed

Pirri, Jennifer K; Rayes, Diego; Alkema, Mark J

2015-01-01

Behavioral output of neural networks depends on a delicate balance between excitatory and inhibitory synaptic connections. However, it is not known whether network formation and stability is constrained by the sign of synaptic connections between neurons within the network. Here we show that switching the sign of a synapse within a neural circuit can reverse the behavioral output. The inhibitory tyramine-gated chloride channel, LGC-55, induces head relaxation and inhibits forward locomotion during the Caenorhabditis elegans escape response. We switched the ion selectivity of an inhibitory LGC-55 anion channel to an excitatory LGC-55 cation channel. The engineered cation channel is properly trafficked in the native neural circuit and results in behavioral responses that are opposite to those produced by activation of the LGC-55 anion channel. Our findings indicate that switches in ion selectivity of ligand-gated ion channels (LGICs) do not affect network connectivity or stability and may provide an evolutionary and a synthetic mechanism to change behavior.

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...

Engineering Encounters: Reverse Engineering

ERIC Educational Resources Information Center

McGowan, Veronica Cassone; Ventura, Marcia; Bell, Philip

2017-01-01

This column presents ideas and techniques to enhance your science teaching. This month's issue shares information on how students' everyday experiences can support science learning through engineering design. In this article, the authors outline a reverse-engineering model of instruction and describe one example of how it looked in our fifth-grade…

Construction of Gene Regulatory Networks Using Recurrent Neural Networks and Swarm Intelligence.

PubMed

Khan, Abhinandan; Mandal, Sudip; Pal, Rajat Kumar; Saha, Goutam

2016-01-01

We have proposed a methodology for the reverse engineering of biologically plausible gene regulatory networks from temporal genetic expression data. We have used established information and the fundamental mathematical theory for this purpose. We have employed the Recurrent Neural Network formalism to extract the underlying dynamics present in the time series expression data accurately. We have introduced a new hybrid swarm intelligence framework for the accurate training of the model parameters. The proposed methodology has been first applied to a small artificial network, and the results obtained suggest that it can produce the best results available in the contemporary literature, to the best of our knowledge. Subsequently, we have implemented our proposed framework on experimental (in vivo) datasets. Finally, we have investigated two medium sized genetic networks (in silico) extracted from GeneNetWeaver, to understand how the proposed algorithm scales up with network size. Additionally, we have implemented our proposed algorithm with half the number of time points. The results indicate that a reduction of 50% in the number of time points does not have an effect on the accuracy of the proposed methodology significantly, with a maximum of just over 15% deterioration in the worst case.

Un-Building Blocks: A Model of Reverse Engineering and Applicable Heuristics

DTIC Science & Technology

2015-12-01

CONCLUSIONS The machine does not isolate man from the great problems of nature but plunges him more deeply into them. Antoine de Saint-Exupery— Wind ...DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) Reverse engineering is the problem -solving activity that ensues when one takes a...Douglas Moses, Vice Provost for Academic Affairs iv THIS PAGE INTENTIONALLY LEFT BLANK v ABSTRACT Reverse engineering is the problem -solving

Reverse engineering of aircraft wing data using a partial differential equation surface model

NASA Astrophysics Data System (ADS)

Huband, Jacalyn Mann

Reverse engineering is a multi-step process used in industry to determine a production representation of an existing physical object. This representation is in the form of mathematical equations that are compatible with computer-aided design and computer-aided manufacturing (CAD/CAM) equipment. The four basic steps to the reverse engineering process are data acquisition, data separation, surface or curve fitting, and CAD/CAM production. The surface fitting step determines the design representation of the object, and thus is critical to the success or failure of the reverse engineering process. Although surface fitting methods described in the literature are used to model a variety of surfaces, they are not suitable for reversing aircraft wings. In this dissertation, we develop and demonstrate a new strategy for reversing a mathematical representation of an aircraft wing. The basis of our strategy is to take an aircraft design model and determine if an inverse model can be derived. A candidate design model for this research is the partial differential equation (PDE) surface model, proposed by Bloor and Wilson and used in the Rapid Airplane Parameter Input Design (RAPID) tool at the NASA-LaRC Geolab. There are several basic mathematical problems involved in reversing the PDE surface model: (i) deriving a computational approximation of the surface function; (ii) determining a radial parametrization of the wing; (iii) choosing mathematical models or classes of functions for representation of the boundary functions; (iv) fitting the boundary data points by the chosen boundary functions; and (v) simultaneously solving for the axial parameterization and the derivative boundary functions. The study of the techniques to solve the above mathematical problems has culminated in a reverse PDE surface model and two reverse PDE surface algorithms. One reverse PDE surface algorithm recovers engineering design parameters for the RAPID tool from aircraft wing data and the other generates a PDE surface model with spline boundary functions from an arbitrary set of grid points. Our numerical tests show that the reverse PDE surface model and the reverse PDE surface algorithms can be used for the reverse engineering of aircraft wing data.

14 CFR 33.97 - Thrust reversers.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Thrust reversers. 33.97 Section 33.97 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION AIRCRAFT AIRWORTHINESS STANDARDS: AIRCRAFT ENGINES Block Tests; Turbine Aircraft Engines § 33.97 Thrust reversers. (a) If the...

14 CFR 33.97 - Thrust reversers.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Thrust reversers. 33.97 Section 33.97 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION AIRCRAFT AIRWORTHINESS STANDARDS: AIRCRAFT ENGINES Block Tests; Turbine Aircraft Engines § 33.97 Thrust reversers. (a) If the...

14 CFR 33.97 - Thrust reversers.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Thrust reversers. 33.97 Section 33.97 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION AIRCRAFT AIRWORTHINESS STANDARDS: AIRCRAFT ENGINES Block Tests; Turbine Aircraft Engines § 33.97 Thrust reversers. (a) If the...

14 CFR 33.97 - Thrust reversers.

Code of Federal Regulations, 2012 CFR

2012-01-01

... STANDARDS: AIRCRAFT ENGINES Block Tests; Turbine Aircraft Engines § 33.97 Thrust reversers. (a) If the... this subpart must be run with the reverser installed. In complying with this section, the power control... regimes of control operations are incorporated necessitating scheduling of the power-control lever motion...

14 CFR 33.97 - Thrust reversers.

Code of Federal Regulations, 2010 CFR

2010-01-01

... STANDARDS: AIRCRAFT ENGINES Block Tests; Turbine Aircraft Engines § 33.97 Thrust reversers. (a) If the... this subpart must be run with the reverser installed. In complying with this section, the power control... regimes of control operations are incorporated necessitating scheduling of the power-control lever motion...

Reverse Core Engine with Thrust Reverser

NASA Technical Reports Server (NTRS)

Chandler, Jesse M. (Inventor); Suciu, Gabriel L. (Inventor)

2017-01-01

An engine system has a gas generator, a bi-fi wall surrounding at least a portion of the gas generator, a casing surrounding a fan, and the casing having first and second thrust reverser doors which in a deployed position abut each other and the bi-fi wall.

Analysis of Ten Reverse Engineering Tools

NASA Astrophysics Data System (ADS)

Koskinen, Jussi; Lehmonen, Tero

Reverse engineering tools can be used in satisfying the information needs of software maintainers. Especially in case of maintaining large-scale legacy systems tool support is essential. Reverse engineering tools provide various kinds of capabilities to provide the needed information to the tool user. In this paper we analyze the provided capabilities in terms of four aspects: provided data structures, visualization mechanisms, information request specification mechanisms, and navigation features. We provide a compact analysis of ten representative reverse engineering tools for supporting C, C++ or Java: Eclipse Java Development Tools, Wind River Workbench (for C and C++), Understand (for C++), Imagix 4D, Creole, Javadoc, Javasrc, Source Navigator, Doxygen, and HyperSoft. The results of the study supplement the earlier findings in this important area.

Reverse logistics in the Brazilian construction industry.

PubMed

Nunes, K R A; Mahler, C F; Valle, R A

2009-09-01

In Brazil most Construction and Demolition Waste (C&D waste) is not recycled. This situation is expected to change significantly, since new federal regulations oblige municipalities to create and implement sustainable C&D waste management plans which assign an important role to recycling activities. The recycling organizational network and its flows and components are fundamental to C&D waste recycling feasibility. Organizational networks, flows and components involve reverse logistics. The aim of this work is to introduce the concepts of reverse logistics and reverse distribution channel networks and to study the Brazilian C&D waste case.

Contact mechanics of reverse engineered distal humeral hemiarthroplasty implants.

PubMed

Willing, Ryan; King, Graham J W; Johnson, James A

2015-11-26

Erosion of articular cartilage is a concern following distal humeral hemiarthroplasty, because native cartilage surfaces are placed in contact with stiff metallic implant components, which causes decreases in contact area and increases in contact stresses. Recently, reverse engineered implants have been proposed which are intended to promote more natural contact mechanics by reproducing the native bone or cartilage shape. In this study, finite element modeling is used in order to calculate changes in cartilage contact areas and stresses following distal humeral hemiarthroplasty with commercially available and reverse engineered implant designs. At the ulna, decreases in contact area were -34±3% (p=0.002), -27±1% (p<0.001) and -14±2% (p=0.008) using commercially available, bone reverse engineered and cartilage reverse engineered designs, respectively. Peak contact stresses increased by 461±57% (p=0.008), 387±127% (p=0.229) and 165±16% (p=0.003). At the radius, decreases in contact area were -21±3% (p=0.013), -13±2% (p<0.006) and -6±1% (p=0.020), and peak contact stresses increased by 75±52% (p>0.999), 241±32% (p=0.010) and 61±10% (p=0.021). Between the three different implant designs, the cartilage reverse engineered design yielded the largest contact areas and lowest contact stresses, but was still unable to reproduce the contact mechanics of the native joint. These findings align with a growing body of evidence indicating that although reverse engineered hemiarthroplasty implants can provide small improvements in contact mechanics when compared with commercially available designs, further optimization of shape and material properties is required in order reproduce native joint contact mechanics. Copyright © 2015 Elsevier Ltd. All rights reserved.

The 727 airplane target thrust reverser static performance model test for refanned JT8D engines

NASA Technical Reports Server (NTRS)

Chow, C. T. P.; Atkey, E. N.

1974-01-01

The results of a scale model static performance test of target thrust reverser configurations for the Pratt and Whitney Aircraft JT8D-100 series engine are presented. The objective of the test was to select a series of suitable candidate reverser configurations for the subsequent airplane model wind tunnel ingestion and flight controls tests. Test results indicate that adequate reverse thrust performance with compatible engine airflow match is achievable for the selected configurations. Tapering of the lips results in loss of performance and only minimal flow directivity. Door pressure surveys were conducted on a selected number of lip and fence configurations to obtain data to support the design of the thrust reverser system.

Time reversibility of quantum diffusion in small-world networks

NASA Astrophysics Data System (ADS)

Han, Sung-Guk; Kim, Beom Jun

2012-02-01

We study the time-reversal dynamics of a tight-binding electron in the Watts-Strogatz (WS) small-world networks. The localized initial wave packet at time t = 0 diffuses as time proceeds until the time-reversal operation, together with the momentum perturbation of the strength η, is made at the reversal time T. The time irreversibility is measured by I = |Π( t = 2 T) - Π( t = 0)|, where Π is the participation ratio gauging the extendedness of the wavefunction and for convenience, t is measured forward even after the time reversal. When η = 0, the time evolution after T makes the wavefunction at t = 2 T identical to the one at t = 0, and we find I = 0, implying a null irreversibility or a complete reversibility. On the other hand, as η is increased from zero, the reversibility becomes weaker, and we observe enhancement of the irreversibility. We find that I linearly increases with increasing η in the weakly-perturbed region, and that the irreversibility is much stronger in the WS network than in the local regular network.

14 CFR 25.1305 - Powerplant instruments.

Code of Federal Regulations, 2013 CFR

2013-01-01

... reverse pitch, for each reversing propeller. (c) For turbine engine-powered airplanes. In addition to the... required: (1) A gas temperature indicator for each engine. (2) A fuel flowmeter indicator for each engine... operated continuously but that is neither designed for continuous operation nor designed to prevent hazard...

14 CFR 25.1305 - Powerplant instruments.

Code of Federal Regulations, 2014 CFR

2014-01-01

... reverse pitch, for each reversing propeller. (c) For turbine engine-powered airplanes. In addition to the... required: (1) A gas temperature indicator for each engine. (2) A fuel flowmeter indicator for each engine... operated continuously but that is neither designed for continuous operation nor designed to prevent hazard...

14 CFR 25.1305 - Powerplant instruments.

Code of Federal Regulations, 2012 CFR

2012-01-01

... reverse pitch, for each reversing propeller. (c) For turbine engine-powered airplanes. In addition to the... required: (1) A gas temperature indicator for each engine. (2) A fuel flowmeter indicator for each engine... operated continuously but that is neither designed for continuous operation nor designed to prevent hazard...

14 CFR 25.1305 - Powerplant instruments.

Code of Federal Regulations, 2011 CFR

2011-01-01

... reverse pitch, for each reversing propeller. (c) For turbine engine-powered airplanes. In addition to the... required: (1) A gas temperature indicator for each engine. (2) A fuel flowmeter indicator for each engine... operated continuously but that is neither designed for continuous operation nor designed to prevent hazard...

14 CFR 25.1305 - Powerplant instruments.

Code of Federal Regulations, 2010 CFR

2010-01-01

... reverse pitch, for each reversing propeller. (c) For turbine engine-powered airplanes. In addition to the... required: (1) A gas temperature indicator for each engine. (2) A fuel flowmeter indicator for each engine... operated continuously but that is neither designed for continuous operation nor designed to prevent hazard...

Reverse engineering and identification in systems biology: strategies, perspectives and challenges.

PubMed

Villaverde, Alejandro F; Banga, Julio R

2014-02-06

The interplay of mathematical modelling with experiments is one of the central elements in systems biology. The aim of reverse engineering is to infer, analyse and understand, through this interplay, the functional and regulatory mechanisms of biological systems. Reverse engineering is not exclusive of systems biology and has been studied in different areas, such as inverse problem theory, machine learning, nonlinear physics, (bio)chemical kinetics, control theory and optimization, among others. However, it seems that many of these areas have been relatively closed to outsiders. In this contribution, we aim to compare and highlight the different perspectives and contributions from these fields, with emphasis on two key questions: (i) why are reverse engineering problems so hard to solve, and (ii) what methods are available for the particular problems arising from systems biology?

Reverse Engineering of Modified Genes by Bayesian Network Analysis Defines Molecular Determinants Critical to the Development of Glioblastoma

PubMed Central

Kunkle, Brian W.; Yoo, Changwon; Roy, Deodutta

2013-01-01

In this study we have identified key genes that are critical in development of astrocytic tumors. Meta-analysis of microarray studies which compared normal tissue to astrocytoma revealed a set of 646 differentially expressed genes in the majority of astrocytoma. Reverse engineering of these 646 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I–IV), and ‘key genes’ within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. All of these genes were up-regulated, except MPP2 (down regulated). These 10 genes were able to predict tumor status with 96–100% confidence when using logistic regression, cross validation, and the support vector machine analysis. Markov genes interact with NFkβ, ERK, MAPK, VEGF, growth hormone and collagen to produce a network whose top biological functions are cancer, neurological disease, and cellular movement. Three of the 10 genes - EGFR, COL4A1, and CDK4, in particular, seemed to be potential ‘hubs of activity’. Modified expression of these 10 Markov Blanket genes increases lifetime risk of developing glioblastoma compared to the normal population. The glioblastoma risk estimates were dramatically increased with joint effects of 4 or more than 4 Markov Blanket genes. Joint interaction effects of 4, 5, 6, 7, 8, 9 or 10 Markov Blanket genes produced 9, 13, 20.9, 26.7, 52.8, 53.2, 78.1 or 85.9%, respectively, increase in lifetime risk of developing glioblastoma compared to normal population. In summary, it appears that modified expression of several ‘key genes’ may be required for the development of glioblastoma. Further studies are needed to validate these ‘key genes’ as useful tools for early detection and novel therapeutic options for these tumors. PMID:23737970

Research on reverse logistics location under uncertainty environment based on grey prediction

NASA Astrophysics Data System (ADS)

Zhenqiang, Bao; Congwei, Zhu; Yuqin, Zhao; Quanke, Pan

This article constructs reverse logistic network based on uncertain environment, integrates the reverse logistics network and distribution network, and forms a closed network. An optimization model based on cost is established to help intermediate center, manufacturing center and remanufacturing center make location decision. A gray model GM (1, 1) is used to predict the product holdings of the collection points, and then prediction results are carried into the cost optimization model and a solution is got. Finally, an example is given to verify the effectiveness and feasibility of the model.

Controlling Hydrogel Mechanics via Bio-Inspired Polymer-Nanoparticle Bond Dynamics.

PubMed

Li, Qiaochu; Barrett, Devin G; Messersmith, Phillip B; Holten-Andersen, Niels

2016-01-26

Interactions between polymer molecules and inorganic nanoparticles can play a dominant role in nanocomposite material mechanics, yet control of such interfacial interaction dynamics remains a significant challenge particularly in water. This study presents insights on how to engineer hydrogel material mechanics via nanoparticle interface-controlled cross-link dynamics. Inspired by the adhesive chemistry in mussel threads, we have incorporated iron oxide nanoparticles (Fe3O4 NPs) into a catechol-modified polymer network to obtain hydrogels cross-linked via reversible metal-coordination bonds at Fe3O4 NP surfaces. Unique material mechanics result from the supra-molecular cross-link structure dynamics in the gels; in contrast to the previously reported fluid-like dynamics of transient catechol-Fe(3+) cross-links, the catechol-Fe3O4 NP structures provide solid-like yet reversible hydrogel mechanics. The structurally controlled hierarchical mechanics presented here suggest how to develop hydrogels with remote-controlled self-healing dynamics.

Hamilton Standard Q-fan demonstrator dynamic pitch change test program, volume 1

NASA Technical Reports Server (NTRS)

Demers, W. J.; Nelson, D. J.; Wainauski, H. S.

1975-01-01

Tests of a full scale variable pitch fan engine to obtain data on the structural characteristics, response times, and fan/core engine compatibility during transient changes in blade angle, fan rpm, and engine power is reported. Steady state reverse thrust tests with a take off nozzle configuration were also conducted. The 1.4 meter diameter, 13 bladed controllable pitch fan was driven by a T55 L 11A engine with power and blade angle coordinated by a digital computer. The tests demonstrated an ability to change from full forward thrust to reverse thrust in less than one (1) second. Reverse thrust was effected through feather and through flat pitch; structural characteristics and engine/fan compatibility were within satisfactory limits.

Statistical inference approach to structural reconstruction of complex networks from binary time series

NASA Astrophysics Data System (ADS)

Ma, Chuang; Chen, Han-Shuang; Lai, Ying-Cheng; Zhang, Hai-Feng

2018-02-01

Complex networks hosting binary-state dynamics arise in a variety of contexts. In spite of previous works, to fully reconstruct the network structure from observed binary data remains challenging. We articulate a statistical inference based approach to this problem. In particular, exploiting the expectation-maximization (EM) algorithm, we develop a method to ascertain the neighbors of any node in the network based solely on binary data, thereby recovering the full topology of the network. A key ingredient of our method is the maximum-likelihood estimation of the probabilities associated with actual or nonexistent links, and we show that the EM algorithm can distinguish the two kinds of probability values without any ambiguity, insofar as the length of the available binary time series is reasonably long. Our method does not require any a priori knowledge of the detailed dynamical processes, is parameter-free, and is capable of accurate reconstruction even in the presence of noise. We demonstrate the method using combinations of distinct types of binary dynamical processes and network topologies, and provide a physical understanding of the underlying reconstruction mechanism. Our statistical inference based reconstruction method contributes an additional piece to the rapidly expanding "toolbox" of data based reverse engineering of complex networked systems.

Statistical inference approach to structural reconstruction of complex networks from binary time series.

PubMed

Ma, Chuang; Chen, Han-Shuang; Lai, Ying-Cheng; Zhang, Hai-Feng

2018-02-01

Complex networks hosting binary-state dynamics arise in a variety of contexts. In spite of previous works, to fully reconstruct the network structure from observed binary data remains challenging. We articulate a statistical inference based approach to this problem. In particular, exploiting the expectation-maximization (EM) algorithm, we develop a method to ascertain the neighbors of any node in the network based solely on binary data, thereby recovering the full topology of the network. A key ingredient of our method is the maximum-likelihood estimation of the probabilities associated with actual or nonexistent links, and we show that the EM algorithm can distinguish the two kinds of probability values without any ambiguity, insofar as the length of the available binary time series is reasonably long. Our method does not require any a priori knowledge of the detailed dynamical processes, is parameter-free, and is capable of accurate reconstruction even in the presence of noise. We demonstrate the method using combinations of distinct types of binary dynamical processes and network topologies, and provide a physical understanding of the underlying reconstruction mechanism. Our statistical inference based reconstruction method contributes an additional piece to the rapidly expanding "toolbox" of data based reverse engineering of complex networked systems.

Reverse engineering and identification in systems biology: strategies, perspectives and challenges

PubMed Central

Villaverde, Alejandro F.; Banga, Julio R.

2014-01-01

The interplay of mathematical modelling with experiments is one of the central elements in systems biology. The aim of reverse engineering is to infer, analyse and understand, through this interplay, the functional and regulatory mechanisms of biological systems. Reverse engineering is not exclusive of systems biology and has been studied in different areas, such as inverse problem theory, machine learning, nonlinear physics, (bio)chemical kinetics, control theory and optimization, among others. However, it seems that many of these areas have been relatively closed to outsiders. In this contribution, we aim to compare and highlight the different perspectives and contributions from these fields, with emphasis on two key questions: (i) why are reverse engineering problems so hard to solve, and (ii) what methods are available for the particular problems arising from systems biology? PMID:24307566

Static Performance of a Wing-Mounted Thrust Reverser Concept

NASA Technical Reports Server (NTRS)

Asbury, Scott C.; Yetter, Jeffrey A.

1998-01-01

An experimental investigation was conducted in the Jet-Exit Test Facility at NASA Langley Research Center to study the static aerodynamic performance of a wing-mounted thrust reverser concept applicable to subsonic transport aircraft. This innovative engine powered thrust reverser system is designed to utilize wing-mounted flow deflectors to produce aircraft deceleration forces. Testing was conducted using a 7.9%-scale exhaust system model with a fan-to-core bypass ratio of approximately 9.0, a supercritical left-hand wing section attached via a pylon, and wing-mounted flow deflectors attached to the wing section. Geometric variations of key design parameters investigated for the wing-mounted thrust reverser concept included flow deflector angle and chord length, deflector edge fences, and the yaw mount angle of the deflector system (normal to the engine centerline or parallel to the wing trailing edge). All tests were conducted with no external flow and high pressure air was used to simulate core and fan engine exhaust flows. Test results indicate that the wing-mounted thrust reverser concept can achieve overall thrust reverser effectiveness levels competitive with (parallel mount), or better than (normal mount) a conventional cascade thrust reverser system. By removing the thrust reverser system from the nacelle, the wing-mounted concept offers the nacelle designer more options for improving nacelle aero dynamics and propulsion-airframe integration, simplifying nacelle structural designs, reducing nacelle weight, and improving engine maintenance access.

Limitations of a metabolic network-based reverse ecology method for inferring host-pathogen interactions.

PubMed

Takemoto, Kazuhiro; Aie, Kazuki

2017-05-25

Host-pathogen interactions are important in a wide range of research fields. Given the importance of metabolic crosstalk between hosts and pathogens, a metabolic network-based reverse ecology method was proposed to infer these interactions. However, the validity of this method remains unclear because of the various explanations presented and the influence of potentially confounding factors that have thus far been neglected. We re-evaluated the importance of the reverse ecology method for evaluating host-pathogen interactions while statistically controlling for confounding effects using oxygen requirement, genome, metabolic network, and phylogeny data. Our data analyses showed that host-pathogen interactions were more strongly influenced by genome size, primary network parameters (e.g., number of edges), oxygen requirement, and phylogeny than the reserve ecology-based measures. These results indicate the limitations of the reverse ecology method; however, they do not discount the importance of adopting reverse ecology approaches altogether. Rather, we highlight the need for developing more suitable methods for inferring host-pathogen interactions and conducting more careful examinations of the relationships between metabolic networks and host-pathogen interactions.

PREMER: a Tool to Infer Biological Networks.

PubMed

Villaverde, Alejandro F; Becker, Kolja; Banga, Julio R

2017-10-04

Inferring the structure of unknown cellular networks is a main challenge in computational biology. Data-driven approaches based on information theory can determine the existence of interactions among network nodes automatically. However, the elucidation of certain features - such as distinguishing between direct and indirect interactions or determining the direction of a causal link - requires estimating information-theoretic quantities in a multidimensional space. This can be a computationally demanding task, which acts as a bottleneck for the application of elaborate algorithms to large-scale network inference problems. The computational cost of such calculations can be alleviated by the use of compiled programs and parallelization. To this end we have developed PREMER (Parallel Reverse Engineering with Mutual information & Entropy Reduction), a software toolbox that can run in parallel and sequential environments. It uses information theoretic criteria to recover network topology and determine the strength and causality of interactions, and allows incorporating prior knowledge, imputing missing data, and correcting outliers. PREMER is a free, open source software tool that does not require any commercial software. Its core algorithms are programmed in FORTRAN 90 and implement OpenMP directives. It has user interfaces in Python and MATLAB/Octave, and runs on Windows, Linux and OSX (https://sites.google.com/site/premertoolbox/).

Reverse Flow Engine Core Having a Ducted Fan with Integrated Secondary Flow Blades

NASA Technical Reports Server (NTRS)

Kisska, Michael K. (Inventor); Princen, Norman H. (Inventor); Kuehn, Mark S. (Inventor); Cosentino, Gary B. (Inventor)

2014-01-01

Secondary air flow is provided for a ducted fan having a reverse flow turbine engine core driving a fan blisk. The fan blisk incorporates a set of thrust fan blades extending from an outer hub and a set of integral secondary flow blades extending intermediate an inner hub and the outer hub. A nacelle provides an outer flow duct for the thrust fan blades and a secondary flow duct carries flow from the integral secondary flow blades as cooling air for components of the reverse flow turbine engine.

Application of reverse engineering in the medical industry.

NASA Astrophysics Data System (ADS)

Kaleev, A. A.; Kashapov, L. N.; Kashapov, N. F.; Kashapov, R. N.

2017-09-01

The purpose of this research is to develop on the basis of existing analogs new design of ophthalmologic microsurgical tweezers by using reverse engineering techniques. Virtual model was obtained by using a three-dimensional scanning system Solutionix Rexcan 450 MP. Geomagic Studio program was used to remove defects and inaccuracies of the obtained parametric model. A prototype of the finished model was made on the installation of laser stereolithography Projet 6000. Total time of the creation was 16 hours from the reverse engineering procedure to 3D-printing of the prototype.

Tough Self-Healing Elastomers by Molecular Enforced Integration of Covalent and Reversible Networks.

PubMed

Wu, Jinrong; Cai, Li-Heng; Weitz, David A

2017-10-01

Self-healing polymers crosslinked by solely reversible bonds are intrinsically weaker than common covalently crosslinked networks. Introducing covalent crosslinks into a reversible network would improve mechanical strength. It is challenging, however, to apply this concept to "dry" elastomers, largely because reversible crosslinks such as hydrogen bonds are often polar motifs, whereas covalent crosslinks are nonpolar motifs. These two types of bonds are intrinsically immiscible without cosolvents. Here, we design and fabricate a hybrid polymer network by crosslinking randomly branched polymers carrying motifs that can form both reversible hydrogen bonds and permanent covalent crosslinks. The randomly branched polymer links such two types of bonds and forces them to mix on the molecular level without cosolvents. This enables a hybrid "dry" elastomer that is very tough with fracture energy 13500 Jm -2 comparable to that of natural rubber. Moreover, the elastomer can self-heal at room temperature with a recovered tensile strength 4 MPa, which is 30% of its original value, yet comparable to the pristine strength of existing self-healing polymers. The concept of forcing covalent and reversible bonds to mix at molecular scale to create a homogenous network is quite general and should enable development of tough, self-healing polymers of practical usage. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

GRASP/Ada (Graphical Representations of Algorithms, Structures, and Processes for Ada): The development of a program analysis environment for Ada. Reverse engineering tools for Ada, task 1, phase 2

NASA Technical Reports Server (NTRS)

Cross, James H., II

1990-01-01

The study, formulation, and generation of structures for Ada (GRASP/Ada) are discussed in this second phase report of a three phase effort. Various graphical representations that can be extracted or generated from source code are described and categorized with focus on reverse engineering. The overall goal is to provide the foundation for a CASE (computer-aided software design) environment in which reverse engineering and forward engineering (development) are tightly coupled. Emphasis is on a subset of architectural diagrams that can be generated automatically from source code with the control structure diagram (CSD) included for completeness.

Transcriptional network inference from functional similarity and expression data: a global supervised approach.

PubMed

Ambroise, Jérôme; Robert, Annie; Macq, Benoit; Gala, Jean-Luc

2012-01-06

An important challenge in system biology is the inference of biological networks from postgenomic data. Among these biological networks, a gene transcriptional regulatory network focuses on interactions existing between transcription factors (TFs) and and their corresponding target genes. A large number of reverse engineering algorithms were proposed to infer such networks from gene expression profiles, but most current methods have relatively low predictive performances. In this paper, we introduce the novel TNIFSED method (Transcriptional Network Inference from Functional Similarity and Expression Data), that infers a transcriptional network from the integration of correlations and partial correlations of gene expression profiles and gene functional similarities through a supervised classifier. In the current work, TNIFSED was applied to predict the transcriptional network in Escherichia coli and in Saccharomyces cerevisiae, using datasets of 445 and 170 affymetrix arrays, respectively. Using the area under the curve of the receiver operating characteristics and the F-measure as indicators, we showed the predictive performance of TNIFSED to be better than unsupervised state-of-the-art methods. TNIFSED performed slightly worse than the supervised SIRENE algorithm for the target genes identification of the TF having a wide range of yet identified target genes but better for TF having only few identified target genes. Our results indicate that TNIFSED is complementary to the SIRENE algorithm, and particularly suitable to discover target genes of "orphan" TFs.

GeneNetWeaver: in silico benchmark generation and performance profiling of network inference methods.

PubMed

Schaffter, Thomas; Marbach, Daniel; Floreano, Dario

2011-08-15

Over the last decade, numerous methods have been developed for inference of regulatory networks from gene expression data. However, accurate and systematic evaluation of these methods is hampered by the difficulty of constructing adequate benchmarks and the lack of tools for a differentiated analysis of network predictions on such benchmarks. Here, we describe a novel and comprehensive method for in silico benchmark generation and performance profiling of network inference methods available to the community as an open-source software called GeneNetWeaver (GNW). In addition to the generation of detailed dynamical models of gene regulatory networks to be used as benchmarks, GNW provides a network motif analysis that reveals systematic prediction errors, thereby indicating potential ways of improving inference methods. The accuracy of network inference methods is evaluated using standard metrics such as precision-recall and receiver operating characteristic curves. We show how GNW can be used to assess the performance and identify the strengths and weaknesses of six inference methods. Furthermore, we used GNW to provide the international Dialogue for Reverse Engineering Assessments and Methods (DREAM) competition with three network inference challenges (DREAM3, DREAM4 and DREAM5). GNW is available at http://gnw.sourceforge.net along with its Java source code, user manual and supporting data. Supplementary data are available at Bioinformatics online. dario.floreano@epfl.ch.

Dynamics of high-bypass-engine thrust reversal using a variable-pitch fan

NASA Technical Reports Server (NTRS)

Schaefer, J. W.; Sagerser, D. R.; Stakolich, E. G.

1977-01-01

The test program demonstrated that successful and rapid forward-to reverse-thrust transients can be performed without any significant engine operational limitations for fan blade pitch changes through either feather pitch or flat pitch. For through-feather-pitch operation with a flight inlet, fan stall problems were encountered, and a fan blade overshoot technique was used to establish reverse thrust.

Automated reverse engineering of nonlinear dynamical systems

PubMed Central

Bongard, Josh; Lipson, Hod

2007-01-01

Complex nonlinear dynamics arise in many fields of science and engineering, but uncovering the underlying differential equations directly from observations poses a challenging task. The ability to symbolically model complex networked systems is key to understanding them, an open problem in many disciplines. Here we introduce for the first time a method that can automatically generate symbolic equations for a nonlinear coupled dynamical system directly from time series data. This method is applicable to any system that can be described using sets of ordinary nonlinear differential equations, and assumes that the (possibly noisy) time series of all variables are observable. Previous automated symbolic modeling approaches of coupled physical systems produced linear models or required a nonlinear model to be provided manually. The advance presented here is made possible by allowing the method to model each (possibly coupled) variable separately, intelligently perturbing and destabilizing the system to extract its less observable characteristics, and automatically simplifying the equations during modeling. We demonstrate this method on four simulated and two real systems spanning mechanics, ecology, and systems biology. Unlike numerical models, symbolic models have explanatory value, suggesting that automated “reverse engineering” approaches for model-free symbolic nonlinear system identification may play an increasing role in our ability to understand progressively more complex systems in the future. PMID:17553966

Evolutionary optimization with data collocation for reverse engineering of biological networks.

PubMed

Tsai, Kuan-Yao; Wang, Feng-Sheng

2005-04-01

Modern experimental biology is moving away from analyses of single elements to whole-organism measurements. Such measured time-course data contain a wealth of information about the structure and dynamic of the pathway or network. The dynamic modeling of the whole systems is formulated as a reverse problem that requires a well-suited mathematical model and a very efficient computational method to identify the model structure and parameters. Numerical integration for differential equations and finding global parameter values are still two major challenges in this field of the parameter estimation of nonlinear dynamic biological systems. We compare three techniques of parameter estimation for nonlinear dynamic biological systems. In the proposed scheme, the modified collocation method is applied to convert the differential equations to the system of algebraic equations. The observed time-course data are then substituted into the algebraic system equations to decouple system interactions in order to obtain the approximate model profiles. Hybrid differential evolution (HDE) with population size of five is able to find a global solution. The method is not only suited for parameter estimation but also can be applied for structure identification. The solution obtained by HDE is then used as the starting point for a local search method to yield the refined estimates.

Demonstration of Efficient Nonreciprocity in a Microwave Optomechanical Circuit*

NASA Astrophysics Data System (ADS)

Peterson, G. A.; Lecocq, F.; Cicak, K.; Simmonds, R. W.; Aumentado, J.; Teufel, J. D.

2017-07-01

The ability to engineer nonreciprocal interactions is an essential tool in modern communication technology as well as a powerful resource for building quantum networks. Aside from large reverse isolation, a nonreciprocal device suitable for applications must also have high efficiency (low insertion loss) and low output noise. Recent theoretical and experimental studies have shown that nonreciprocal behavior can be achieved in optomechanical systems, but performance in these last two attributes has been limited. Here, we demonstrate an efficient, frequency-converting microwave isolator based on the optomechanical interactions between electromagnetic fields and a mechanically compliant vacuum-gap capacitor. We achieve simultaneous reverse isolation of more than 20 dB and insertion loss less than 1.5 dB. We characterize the nonreciprocal noise performance of the device, observing that the residual thermal noise from the mechanical environments is routed solely to the input of the isolator. Our measurements show quantitative agreement with a general coupled-mode theory. Unlike conventional isolators and circulators, these compact nonreciprocal devices do not require a static magnetic field, and they allow for dynamic control of the direction of isolation. With these advantages, similar devices could enable programmable, high-efficiency connections between disparate nodes of quantum networks, even efficiently bridging the microwave and optical domains.

Reverse engineering biomolecular systems using -omic data: challenges, progress and opportunities.

PubMed

Quo, Chang F; Kaddi, Chanchala; Phan, John H; Zollanvari, Amin; Xu, Mingqing; Wang, May D; Alterovitz, Gil

2012-07-01

Recent advances in high-throughput biotechnologies have led to the rapid growing research interest in reverse engineering of biomolecular systems (REBMS). 'Data-driven' approaches, i.e. data mining, can be used to extract patterns from large volumes of biochemical data at molecular-level resolution while 'design-driven' approaches, i.e. systems modeling, can be used to simulate emergent system properties. Consequently, both data- and design-driven approaches applied to -omic data may lead to novel insights in reverse engineering biological systems that could not be expected before using low-throughput platforms. However, there exist several challenges in this fast growing field of reverse engineering biomolecular systems: (i) to integrate heterogeneous biochemical data for data mining, (ii) to combine top-down and bottom-up approaches for systems modeling and (iii) to validate system models experimentally. In addition to reviewing progress made by the community and opportunities encountered in addressing these challenges, we explore the emerging field of synthetic biology, which is an exciting approach to validate and analyze theoretical system models directly through experimental synthesis, i.e. analysis-by-synthesis. The ultimate goal is to address the present and future challenges in reverse engineering biomolecular systems (REBMS) using integrated workflow of data mining, systems modeling and synthetic biology.

Reconfigurable engineered motile semiconductor microparticles.

PubMed

Ohiri, Ugonna; Shields, C Wyatt; Han, Koohee; Tyler, Talmage; Velev, Orlin D; Jokerst, Nan

2018-05-03

Locally energized particles form the basis for emerging classes of active matter. The design of active particles has led to their controlled locomotion and assembly. The next generation of particles should demonstrate robust control over their active assembly, disassembly, and reconfiguration. Here we introduce a class of semiconductor microparticles that can be comprehensively designed (in size, shape, electric polarizability, and patterned coatings) using standard microfabrication tools. These custom silicon particles draw energy from external electric fields to actively propel, while interacting hydrodynamically, and sequentially assemble and disassemble on demand. We show that a number of electrokinetic effects, such as dielectrophoresis, induced charge electrophoresis, and diode propulsion, can selectively power the microparticle motions and interactions. The ability to achieve on-demand locomotion, tractable fluid flows, synchronized motility, and reversible assembly using engineered silicon microparticles may enable advanced applications that include remotely powered microsensors, artificial muscles, reconfigurable neural networks and computational systems.

HamSCI: The Ham Radio Science Citizen Investigation

NASA Astrophysics Data System (ADS)

Frissell, N. A.; Moses, M. L.; Earle, G. D.; McGwier, R. W.; Miller, E. S.; Kaeppler, S. R.; Silver, H. W.; Ceglia, F.; Pascoe, D.; Sinanis, N.; Smith, P.; Williams, R.; Shovkoplyas, A.; Gerrard, A. J.

2016-12-01

Amateur (or "ham") radio operators are individuals with a non-pecuniary interest in radio technology, engineering, communications, science, and public service. They are licensed by their national governments to transmit on amateur radio frequencies. In many jurisdictions, there is no age requirement for a ham radio license, and operators from diverse backgrounds participate. There are more than 740,000 hams in the US, and over 3 million (estimated) worldwide. Many amateur communications are conducted using transionospheric links and thus affected by space weather and ionospheric processes. Recent technological advances have enabled the development of automated ham radio observation networks (e.g. the Reverse Beacon Network, www.reversebeacon.net) and specialized operating modes for the study of weak-signal propagation. The data from these networks have been shown to be useful for the study of ionospheric processes. In order to connect professional researchers with the volunteer-based ham radio community, HamSCI (Ham Radio Science Citizen Investigation, www.hamsci.org) has been established. HamSCI is a platform for publicizing and promoting projects that are consistent with the following objectives: (1) Advance scientific research and understanding through amateur radio activities. (2) Encourage the development of new technologies to support this research. (3) Provide educational opportunities for the amateur community and the general public. HamSCI researchers are working with the American Radio Relay League (ARRL, www.arrl.org) to publicize these objectives and recruit interested hams. The ARRL is the US national organization for amateur radio with a membership of over 170,000 and a monthly magazine, QST. HamSCI is currently preparing to support ionospheric research connected to the 21 Aug 2017 Total Solar Eclipse by expanding coverage of the Reverse Beacon Network and organizing a large-scale ham radio operating event ("QSO Party") to generate data during the eclipse.

Nested effects models for learning signaling networks from perturbation data.

PubMed

Fröhlich, Holger; Tresch, Achim; Beissbarth, Tim

2009-04-01

Targeted gene perturbations have become a major tool to gain insight into complex cellular processes. In combination with the measurement of downstream effects via DNA microarrays, this approach can be used to gain insight into signaling pathways. Nested Effects Models were first introduced by Markowetz et al. as a probabilistic method to reverse engineer signaling cascades based on the nested structure of downstream perturbation effects. The basic framework was substantially extended later on by Fröhlich et al., Markowetz et al., and Tresch and Markowetz. In this paper, we present a review of the complete methodology with a detailed comparison of so far proposed algorithms on a qualitative and quantitative level. As an application, we present results on estimating the signaling network between 13 genes in the ER-alpha pathway of human MCF-7 breast cancer cells. Comparison with the literature shows a substantial overlap.

Reverse logistics network for municipal solid waste management: The inclusion of waste pickers as a Brazilian legal requirement.

PubMed

Ferri, Giovane Lopes; Chaves, Gisele de Lorena Diniz; Ribeiro, Glaydston Mattos

2015-06-01

This study proposes a reverse logistics network involved in the management of municipal solid waste (MSW) to solve the challenge of economically managing these wastes considering the recent legal requirements of the Brazilian Waste Management Policy. The feasibility of the allocation of MSW material recovery facilities (MRF) as intermediate points between the generators of these wastes and the options for reuse and disposal was evaluated, as well as the participation of associations and cooperatives of waste pickers. This network was mathematically modelled and validated through a scenario analysis of the municipality of São Mateus, which makes the location model more complete and applicable in practice. The mathematical model allows the determination of the number of facilities required for the reverse logistics network, their location, capacities, and product flows between these facilities. The fixed costs of installation and operation of the proposed MRF were balanced with the reduction of transport costs, allowing the inclusion of waste pickers to the reverse logistics network. The main contribution of this study lies in the proposition of a reverse logistics network for MSW simultaneously involving legal, environmental, economic and social criteria, which is a very complex goal. This study can guide practices in other countries that have realities similar to those in Brazil of accelerated urbanisation without adequate planning for solid waste management, added to the strong presence of waste pickers that, through the characteristic of social vulnerability, must be included in the system. In addition to the theoretical contribution to the reverse logistics network problem, this study aids in decision-making for public managers who have limited technical and administrative capacities for the management of solid wastes. Copyright © 2015 Elsevier Ltd. All rights reserved.

28. MESTA STEAM ENGINE, INSTALLED BY THE CORRIGAN, McKINNEY COMPANY ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

28. MESTA STEAM ENGINE, INSTALLED BY THE CORRIGAN, McKINNEY COMPANY IN 1916, STILL DRIVES THE 44-INCH REVERSING BLOOMING MILL. THE TWIN TANDAM, COMPOUND CONDENSING, REVERSING STEAM ENGINE HAS A RATED CAPACITY OF 35,000 H.P. IT WAS BUILT BY THE MESTA MACHINE COMPANY OF PITTSBURGH. - Corrigan, McKinney Steel Company, 3100 East Forty-fifth Street, Cleveland, Cuyahoga County, OH

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)

Analysis and documentation of QCSEE (Quiet Clean Short-haul Experimental Engine) over-the-wing exhaust system development

NASA Technical Reports Server (NTRS)

Ammer, R. C.; Kutney, J. T.

1977-01-01

A static scale model test program was conducted in the static test area of the NASA-Langley 9.14- by 18.29 m(30- by 60-ft) Full-Scale Wind Tunnel Facility to develop an over-the-wing (OTW) nozzle and reverser configuration for the Quiet Clean Short-Haul Experimental Engine (QCSEE). Three nozzles and one basic reverser configuration were tested over the QCSEE takeoff and approach power nozzle pressure ratio range between 1.1 and 1.3. The models were scaled to 8.53% of QCSEE engine size and tested behind two 13.97-cm (5.5-in.) diameter tip-turbine-driven fan simulators coupled in tandem. An OTW nozzle and reverser configuration was identified which satisfies the QCSEE experimental engine requirements in terms of nozzle cycle area variation capability and reverse thrust level, and provides good jet flow spreading over a wing upper surface for achievement of high propulsive lift performance.

Reverse logistics network for municipal solid waste management: The inclusion of waste pickers as a Brazilian legal requirement

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

Ferri, Giovane Lopes, E-mail: giovane.ferri@aluno.ufes.br; Diniz Chaves, Gisele de Lorena, E-mail: gisele.chaves@ufes.br; Ribeiro, Glaydston Mattos, E-mail: glaydston@pet.coppe.ufrj.br

Highlights: • We propose a reverse logistics network for MSW involving waste pickers. • A generic facility location mathematical model was validated in a Brazilian city. • The results enable to predict the capacity for screening and storage centres (SSC). • We minimise the costs for transporting MSW with screening and storage centres. • The use of SSC can be a potential source of revenue and a better use of MSW. - Abstract: This study proposes a reverse logistics network involved in the management of municipal solid waste (MSW) to solve the challenge of economically managing these wastes considering themore » recent legal requirements of the Brazilian Waste Management Policy. The feasibility of the allocation of MSW material recovery facilities (MRF) as intermediate points between the generators of these wastes and the options for reuse and disposal was evaluated, as well as the participation of associations and cooperatives of waste pickers. This network was mathematically modelled and validated through a scenario analysis of the municipality of São Mateus, which makes the location model more complete and applicable in practice. The mathematical model allows the determination of the number of facilities required for the reverse logistics network, their location, capacities, and product flows between these facilities. The fixed costs of installation and operation of the proposed MRF were balanced with the reduction of transport costs, allowing the inclusion of waste pickers to the reverse logistics network. The main contribution of this study lies in the proposition of a reverse logistics network for MSW simultaneously involving legal, environmental, economic and social criteria, which is a very complex goal. This study can guide practices in other countries that have realities similar to those in Brazil of accelerated urbanisation without adequate planning for solid waste management, added to the strong presence of waste pickers that, through the characteristic of social vulnerability, must be included in the system. In addition to the theoretical contribution to the reverse logistics network problem, this study aids in decision-making for public managers who have limited technical and administrative capacities for the management of solid wastes.« less

Quantum engine efficiency bound beyond the second law of thermodynamics.

PubMed

Niedenzu, Wolfgang; Mukherjee, Victor; Ghosh, Arnab; Kofman, Abraham G; Kurizki, Gershon

2018-01-11

According to the second law, the efficiency of cyclic heat engines is limited by the Carnot bound that is attained by engines that operate between two thermal baths under the reversibility condition whereby the total entropy does not increase. Quantum engines operating between a thermal and a squeezed-thermal bath have been shown to surpass this bound. Yet, their maximum efficiency cannot be determined by the reversibility condition, which may yield an unachievable efficiency bound above unity. Here we identify the fraction of the exchanged energy between a quantum system and a bath that necessarily causes an entropy change and derive an inequality for this change. This inequality reveals an efficiency bound for quantum engines energised by a non-thermal bath. This bound does not imply reversibility, unless the two baths are thermal. It cannot be solely deduced from the laws of thermodynamics.

Numerical Prediction of the Influence of Thrust Reverser on Aeroengine's Aerodynamic Stability

NASA Astrophysics Data System (ADS)

Zhiqiang, Wang; Xigang, Shen; Jun, Hu; Xiang, Gao; Liping, Liu

2017-11-01

A numerical method was developed to predict the aerodynamic stability of a high bypass ratio turbofan engine, at the landing stage of a large transport aircraft, when the thrust reverser was deployed. 3D CFD simulation and 2D aeroengine aerodynamic stability analysis code were performed in this work, the former is to achieve distortion coefficient for the analysis of engine stability. The 3D CFD simulation was divided into two steps, the single engine calculation and the integrated aircraft and engine calculation. Results of the CFD simulation show that with the decreasing of relative wind Mach number, the engine inlet will suffer more severe flow distortion. The total pressure and total temperature distortion coefficients at the inlet of the engines were obtained from the results of the numerical simulation. Then an aeroengine aerodynamic stability analysis program was used to quantitatively analyze the aerodynamic stability of the high bypass ratio turbofan engine. The results of the stability analysis show that the engine can work stably, when the reverser flow is re-ingested. But the anti-distortion ability of the booster is weaker than that of the fan and high pressure compressor. It is a weak link of engine stability.

Wind tunnel test of model target thrust reversers for the Pratt and Whitney aircraft JT8D-100 series engines installed on a 727-200 airplane

NASA Technical Reports Server (NTRS)

Hambly, D.

1974-01-01

The results of a low speed wind tunnel test of 0.046 scale model target thrust reversers installed on a 727-200 model airplane are presented. The full airplane model was mounted on a force balance, except for the nacelles and thrust reversers, which were independently mounted and isolated from it. The installation had the capability of simulating the inlet airflows and of supplying the correct proportions of primary and secondary air to the nozzles. The objectives of the test were to assess the compatibility of the thrust reversers target door design with the engine and airplane. The following measurements were made: hot gas ingestion at the nacelle inlets; model lift, drag, and pitching moment; hot gas impingement on the airplane structure; and qualitative assessment of the rudder effectiveness. The major parameters controlling hot gas ingestion were found to be thrust reverser orientation, engine power setting, and the lip height of the bottom thrust reverser doors on the side nacelles. The thrust reversers tended to increase the model lift, decrease the drag, and decrease the pitching moment.

Reverse engineering systems models of regulation: discovery, prediction and mechanisms.

PubMed

Ashworth, Justin; Wurtmann, Elisabeth J; Baliga, Nitin S

2012-08-01

Biological systems can now be understood in comprehensive and quantitative detail using systems biology approaches. Putative genome-scale models can be built rapidly based upon biological inventories and strategic system-wide molecular measurements. Current models combine statistical associations, causative abstractions, and known molecular mechanisms to explain and predict quantitative and complex phenotypes. This top-down 'reverse engineering' approach generates useful organism-scale models despite noise and incompleteness in data and knowledge. Here we review and discuss the reverse engineering of biological systems using top-down data-driven approaches, in order to improve discovery, hypothesis generation, and the inference of biological properties. Copyright © 2011 Elsevier Ltd. All rights reserved.

Multiscale approach for the construction of equilibrated all-atom models of a poly(ethylene glycol)-based hydrogel

PubMed Central

Li, Xianfeng; Murthy, N. Sanjeeva; Becker, Matthew L.; Latour, Robert A.

2016-01-01

A multiscale modeling approach is presented for the efficient construction of an equilibrated all-atom model of a cross-linked poly(ethylene glycol) (PEG)-based hydrogel using the all-atom polymer consistent force field (PCFF). The final equilibrated all-atom model was built with a systematic simulation toolset consisting of three consecutive parts: (1) building a global cross-linked PEG-chain network at experimentally determined cross-link density using an on-lattice Monte Carlo method based on the bond fluctuation model, (2) recovering the local molecular structure of the network by transitioning from the lattice model to an off-lattice coarse-grained (CG) model parameterized from PCFF, followed by equilibration using high performance molecular dynamics methods, and (3) recovering the atomistic structure of the network by reverse mapping from the equilibrated CG structure, hydrating the structure with explicitly represented water, followed by final equilibration using PCFF parameterization. The developed three-stage modeling approach has application to a wide range of other complex macromolecular hydrogel systems, including the integration of peptide, protein, and/or drug molecules as side-chains within the hydrogel network for the incorporation of bioactivity for tissue engineering, regenerative medicine, and drug delivery applications. PMID:27013229

Reverse engineering the gap gene network of Drosophila melanogaster.

PubMed

Perkins, Theodore J; Jaeger, Johannes; Reinitz, John; Glass, Leon

2006-05-01

A fundamental problem in functional genomics is to determine the structure and dynamics of genetic networks based on expression data. We describe a new strategy for solving this problem and apply it to recently published data on early Drosophila melanogaster development. Our method is orders of magnitude faster than current fitting methods and allows us to fit different types of rules for expressing regulatory relationships. Specifically, we use our approach to fit models using a smooth nonlinear formalism for modeling gene regulation (gene circuits) as well as models using logical rules based on activation and repression thresholds for transcription factors. Our technique also allows us to infer regulatory relationships de novo or to test network structures suggested by the literature. We fit a series of models to test several outstanding questions about gap gene regulation, including regulation of and by hunchback and the role of autoactivation. Based on our modeling results and validation against the experimental literature, we propose a revised network structure for the gap gene system. Interestingly, some relationships in standard textbook models of gap gene regulation appear to be unnecessary for or even inconsistent with the details of gap gene expression during wild-type development.

Reverse engineering GTPase programming languages with reconstituted signaling networks.

PubMed

Coyle, Scott M

2016-07-02

The Ras superfamily GTPases represent one of the most prolific signaling currencies used in Eukaryotes. With these remarkable molecules, evolution has built GTPase networks that control diverse cellular processes such as growth, morphology, motility and trafficking. (1-4) Our knowledge of the individual players that underlie the function of these networks is deep; decades of biochemical and structural data has provided a mechanistic understanding of the molecules that turn GTPases ON and OFF, as well as how those GTPase states signal by controlling the assembly of downstream effectors. However, we know less about how these different activities work together as a system to specify complex dynamic signaling outcomes. Decoding this molecular "programming language" would help us understand how different species and cell types have used the same GTPase machinery in different ways to accomplish different tasks, and would also provide new insights as to how mutations to these networks can cause disease. We recently developed a bead-based microscopy assay to watch reconstituted H-Ras signaling systems at work under arbitrary configurations of regulators and effectors. (5) Here we highlight key observations and insights from this study and propose extensions to our method to further study this and other GTPase signaling systems.

Reverse preferential spread in complex networks

NASA Astrophysics Data System (ADS)

Toyoizumi, Hiroshi; Tani, Seiichi; Miyoshi, Naoto; Okamoto, Yoshio

2012-08-01

Large-degree nodes may have a larger influence on the network, but they can be bottlenecks for spreading information since spreading attempts tend to concentrate on these nodes and become redundant. We discuss that the reverse preferential spread (distributing information inversely proportional to the degree of the receiving node) has an advantage over other spread mechanisms. In large uncorrelated networks, we show that the mean number of nodes that receive information under the reverse preferential spread is an upper bound among any other weight-based spread mechanisms, and this upper bound is indeed a logistic growth independent of the degree distribution.

Reverse logistics system planning for recycling computers hardware: A case study

NASA Astrophysics Data System (ADS)

Januri, Siti Sarah; Zulkipli, Faridah; Zahari, Siti Meriam; Shamsuri, Siti Hajar

2014-09-01

This paper describes modeling and simulation of reverse logistics networks for collection of used computers in one of the company in Selangor. The study focuses on design of reverse logistics network for used computers recycling operation. Simulation modeling, presented in this work allows the user to analyze the future performance of the network and to understand the complex relationship between the parties involved. The findings from the simulation suggest that the model calculates processing time and resource utilization in a predictable manner. In this study, the simulation model was developed by using Arena simulation package.

A framework to find the logic backbone of a biological network.

PubMed

Maheshwari, Parul; Albert, Réka

2017-12-06

Cellular behaviors are governed by interaction networks among biomolecules, for example gene regulatory and signal transduction networks. An often used dynamic modeling framework for these networks, Boolean modeling, can obtain their attractors (which correspond to cell types and behaviors) and their trajectories from an initial state (e.g. a resting state) to the attractors, for example in response to an external signal. The existing methods however do not elucidate the causal relationships between distant nodes in the network. In this work, we propose a simple logic framework, based on categorizing causal relationships as sufficient or necessary, as a complement to Boolean networks. We identify and explore the properties of complex subnetworks that are distillable into a single logic relationship. We also identify cyclic subnetworks that ensure the stabilization of the state of participating nodes regardless of the rest of the network. We identify the logic backbone of biomolecular networks, consisting of external signals, self-sustaining cyclic subnetworks (stable motifs), and output nodes. Furthermore, we use the logic framework to identify crucial nodes whose override can drive the system from one steady state to another. We apply these techniques to two biological networks: the epithelial-to-mesenchymal transition network corresponding to a developmental process exploited in tumor invasion, and the network of abscisic acid induced stomatal closure in plants. We find interesting subnetworks with logical implications in these networks. Using these subgraphs and motifs, we efficiently reduce both networks to succinct backbone structures. The logic representation identifies the causal relationships between distant nodes and subnetworks. This knowledge can form the basis of network control or used in the reverse engineering of networks.

PageRank and rank-reversal dependence on the damping factor

NASA Astrophysics Data System (ADS)

Son, S.-W.; Christensen, C.; Grassberger, P.; Paczuski, M.

2012-12-01

PageRank (PR) is an algorithm originally developed by Google to evaluate the importance of web pages. Considering how deeply rooted Google's PR algorithm is to gathering relevant information or to the success of modern businesses, the question of rank stability and choice of the damping factor (a parameter in the algorithm) is clearly important. We investigate PR as a function of the damping factor d on a network obtained from a domain of the World Wide Web, finding that rank reversal happens frequently over a broad range of PR (and of d). We use three different correlation measures, Pearson, Spearman, and Kendall, to study rank reversal as d changes, and we show that the correlation of PR vectors drops rapidly as d changes from its frequently cited value, d0=0.85. Rank reversal is also observed by measuring the Spearman and Kendall rank correlation, which evaluate relative ranks rather than absolute PR. Rank reversal happens not only in directed networks containing rank sinks but also in a single strongly connected component, which by definition does not contain any sinks. We relate rank reversals to rank pockets and bottlenecks in the directed network structure. For the network studied, the relative rank is more stable by our measures around d=0.65 than at d=d0.

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.

Inventing the Invented for STEM Understanding

ERIC Educational Resources Information Center

Stansell, Alicia; Tyler-Wood, Tandra; Stansell, Christina

2016-01-01

The reverse engineering of simple inventions that were of historic significance is now possible in a classroom by using digital models provided by places like the Smithsonian. The digital models can facilitate the mastery of students' STEM learning by utilizing digital fabrication in maker spaces to provide an opportunity for reverse engineer and…

Reconstruction of the temporal signaling network in Salmonella-infected human cells.

PubMed

Budak, Gungor; Eren Ozsoy, Oyku; Aydin Son, Yesim; Can, Tolga; Tuncbag, Nurcan

2015-01-01

Salmonella enterica is a bacterial pathogen that usually infects its host through food sources. Translocation of the pathogen proteins into the host cells leads to changes in the signaling mechanism either by activating or inhibiting the host proteins. Given that the bacterial infection modifies the response network of the host, a more coherent view of the underlying biological processes and the signaling networks can be obtained by using a network modeling approach based on the reverse engineering principles. In this work, we have used a published temporal phosphoproteomic dataset of Salmonella-infected human cells and reconstructed the temporal signaling network of the human host by integrating the interactome and the phosphoproteomic dataset. We have combined two well-established network modeling frameworks, the Prize-collecting Steiner Forest (PCSF) approach and the Integer Linear Programming (ILP) based edge inference approach. The resulting network conserves the information on temporality, direction of interactions, while revealing hidden entities in the signaling, such as the SNARE binding, mTOR signaling, immune response, cytoskeleton organization, and apoptosis pathways. Targets of the Salmonella effectors in the host cells such as CDC42, RHOA, 14-3-3δ, Syntaxin family, Oxysterol-binding proteins were included in the reconstructed signaling network although they were not present in the initial phosphoproteomic data. We believe that integrated approaches, such as the one presented here, have a high potential for the identification of clinical targets in infectious diseases, especially in the Salmonella infections.

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

CLEANER-Hydrologic Observatory Joint Science Plan

NASA Astrophysics Data System (ADS)

Welty, C.; Dressler, K.; Hooper, R.

2005-12-01

The CLEANER-Hydrologic Observatory* initiative is a distributed network for research on complex environmental systems that focuses on the intersecting water-related issues of both the CUAHSI and CLEANER communities. It emphasizes research on the nation's water resources related to human-dominated natural and built environments. The network will be comprised of: interacting field sites with an integrated cyberinfrastructure; a centralized technical resource staff and management infrastructure to support interdisciplinary research through data collection from advanced sensor systems, data mining and aggregation from multiple sources and databases; cyber-tools for analysis, visualization, and predictive multi-scale modeling that is dynamically driven. As such, the network will transform 21st century workforce development in the water-related intersection of environmental science and engineering, as well as enable substantial educational and engagement opportunities for all age levels. The scientific goal and strategic intent of the CLEANER-Hydrologic Observatory Network is to transform our understanding of the earth's water cycle and associated biogeochemical cycles across spatial and temporal scales-enabling quantitative forecasts of critical water-related processes, especially those that affect and are affected by human activities. This strategy will develop scientific and engineering tools that will enable more effective adaptive approaches for resource management. The need for the network is based on three critical deficiencies in current abilities to understand large-scale environmental processes and thereby develop more effective management strategies. First we lack basic data and the infrastructure to collect them at the needed resolution. Second, we lack the means to integrate data across scales from different media (paper records, electronic worksheets, web-based) and sources (observations, experiments, simulations). Third, we lack sufficiently accurate modeling and decision-support tools to predict the underlying processes or subsequently forecast the effects of different management strategies. Water is a critical driver for the functioning of all ecosystems and development of human society, and it is a key ingredient for the success of industry, agriculture and, national economy. CLEANER-Hydrologic Observatories will foster cutting-edge science and engineering research that addresses major national needs (public and governmental) related to water and include, for example: (i) water resource problems, such as impaired surface waters, contaminated ground water, water availability for human use and ecosystem needs, floods and floodplain management, urban storm water, agricultural runoff, and coastal hypoxia; (ii) understanding environmental impacts on public health; (iii) achieving a balance of economic and environmental sustainability; (iv) reversing environmental degradation; and (v) protecting against chemical and biological threats. CLEANER (Collaborative Large-scale Engineering Analysis Network for Environmental Research) is an ENG initiative; the Hydrologic Observatory Network is GEO initiative through CUAHSI (Consortium of Universities for the Advancement of Hydrologic Science, Inc.). The two initiatives were merged into a joint, bi-directorate program in December 2004.

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.

Computer-aided dental prostheses construction using reverse engineering.

PubMed

Solaberrieta, E; Minguez, R; Barrenetxea, L; Sierra, E; Etxaniz, O

2014-01-01

The implementation of computer-aided design/computer-aided manufacturing (CAD/CAM) systems with virtual articulators, which take into account the kinematics, constitutes a breakthrough in the construction of customised dental prostheses. This paper presents a multidisciplinary protocol involving CAM techniques to produce dental prostheses. This protocol includes a step-by-step procedure using innovative reverse engineering technologies to transform completely virtual design processes into customised prostheses. A special emphasis is placed on a novel method that permits a virtual location of the models. The complete workflow includes the optical scanning of the patient, the use of reverse engineering software and, if necessary, the use of rapid prototyping to produce CAD temporary prostheses.

External Dependencies-Driven Architecture Discovery and Analysis of Implemented Systems

NASA Technical Reports Server (NTRS)

Ganesan, Dharmalingam; Lindvall, Mikael; Ron, Monica

2014-01-01

A method for architecture discovery and analysis of implemented systems (AIS) is disclosed. The premise of the method is that architecture decisions are inspired and influenced by the external entities that the software system makes use of. Examples of such external entities are COTS components, frameworks, and ultimately even the programming language itself and its libraries. Traces of these architecture decisions can thus be found in the implemented software and is manifested in the way software systems use such external entities. While this fact is often ignored in contemporary reverse engineering methods, the AIS method actively leverages and makes use of the dependencies to external entities as a starting point for the architecture discovery. The AIS method is demonstrated using the NASA's Space Network Access System (SNAS). The results show that, with abundant evidence, the method offers reusable and repeatable guidelines for discovering the architecture and locating potential risks (e.g. low testability, decreased performance) that are hidden deep in the implementation. The analysis is conducted by using external dependencies to identify, classify and review a minimal set of key source code files. Given the benefits of analyzing external dependencies as a way to discover architectures, it is argued that external dependencies deserve to be treated as first-class citizens during reverse engineering. The current structure of a knowledge base of external entities and analysis questions with strategies for getting answers is also discussed.

Quiet Clean Short-Haul Experimental Engine (QCSEE) acoustic and aerodynamic tests on a scale model over-the-wing thrust reverser and forward thrust nozzle

NASA Technical Reports Server (NTRS)

Stimpert, D. L.

1978-01-01

An acoustic and aerodynamic test program was conducted on a 1/6.25 scale model of the Quiet, Clean, Short-Haul Experimental Engine (QCSEE) forward thrust over-the-wing (OTW) nozzle and OTW thrust reverser. In reverse thrust, the effect of reverser geometry was studied by parametric variations in blocker spacing, blocker height, lip angle, and lip length. Forward thrust nozzle tests determined the jet noise levels of the cruise and takeoff nozzles, the effect of opening side doors to achieve takeoff thrust, and scrubbing noise of the cruise and takeoff jet on a simulated wing surface. Velocity profiles are presented for both forward and reverse thrust nozzles. An estimate of the reverse thrust was made utilizing the measured centerline turning angle.

26 CFR 1.861-18 - Classification of transactions involving computer programs.

Code of Federal Regulations, 2011 CFR

2011-04-01

... on a single disk for a one-time payment with restrictions on transfer and reverse engineering, which... license. The license is stated to be perpetual. Under the license no reverse engineering, decompilation... fee, on a World Wide Web home page on the Internet. P, the Country Z resident, in return for payment...

26 CFR 1.861-18 - Classification of transactions involving computer programs.

Code of Federal Regulations, 2010 CFR

2010-04-01

... on a single disk for a one-time payment with restrictions on transfer and reverse engineering, which... license. The license is stated to be perpetual. Under the license no reverse engineering, decompilation... fee, on a World Wide Web home page on the Internet. P, the Country Z resident, in return for payment...

Recognition vs Reverse Engineering in Boolean Concepts Learning

ERIC Educational Resources Information Center

Shafat, Gabriel; Levin, Ilya

2012-01-01

This paper deals with two types of logical problems--recognition problems and reverse engineering problems, and with the interrelations between these types of problems. The recognition problems are modeled in the form of a visual representation of various objects in a common pattern, with a composition of represented objects in the pattern.…

Reverse Engineering Course at Philadelphia University in Jordan

ERIC Educational Resources Information Center

Younis, M. Bani; Tutunji, T.

2012-01-01

Reverse engineering (RE) is the process of testing and analysing a system or a device in order to identify, understand and document its functionality. RE is an efficient tool in industrial benchmarking where competitors' products are dissected and evaluated for performance and costs. RE can play an important role in the re-configuration and…

Teach CAD and Measuring Skills through Reverse Engineering

ERIC Educational Resources Information Center

Board, Keith

2012-01-01

This article describes a reverse engineering activity that gives students hands-on, minds-on experience with measuring tools, machine parts, and CAD. The author developed this activity to give students an abundance of practical experience with measuring tools. Equally important, it provides a good interface between the virtual world of CAD 3D…

Eliciting design patterns for e-learning systems

NASA Astrophysics Data System (ADS)

Retalis, Symeon; Georgiakakis, Petros; Dimitriadis, Yannis

2006-06-01

Design pattern creation, especially in the e-learning domain, is a highly complex process that has not been sufficiently studied and formalized. In this paper, we propose a systematic pattern development cycle, whose most important aspects focus on reverse engineering of existing systems in order to elicit features that are cross-validated through the use of appropriate, authentic scenarios. However, an iterative pattern process is proposed that takes advantage of multiple data sources, thus emphasizing a holistic view of the teaching learning processes. The proposed schema of pattern mining has been extensively validated for Asynchronous Network Supported Collaborative Learning (ANSCL) systems, as well as for other types of tools in a variety of scenarios, with promising results.

UAV Mission Optimization through Hybrid-Electric Propulsion

NASA Astrophysics Data System (ADS)

Blackwelder, Philip Scott

Hybrid-electric powertrain leverages the superior range of petrol based systems with the quiet and emission free benefits of electric propulsion. The major caveat to hybrid-electric powertrain in an airplane is that it is inherently heavier than conventional petroleum powertrain due mostly to the low energy density of battery technology. The first goal of this research is to develop mission planning code to match powertrain components for a small-scale unmanned aerial vehicle (UAV) to complete a standard surveillance mission within a set of user input parameters. The second goal is to promote low acoustic profile loitering through mid-flight engine starting. The two means by which midmission engine starting will be addressed is through reverse thrust from the propeller and a servo actuated gear to couple and decouple the engine and motor. The mission planning code calculates the power required to complete a mission and assists the user in sourcing powertrain components including the propeller, motor, battery, motor controller, engine and fuel. Reverse thrust engine starting involves characterizing an off the shelf variable pitch propeller and using its torque coefficient to calculate the advance ratio required to provide sufficient torque and speed to start an engine. Geared engine starting works like the starter in a conventional automobile. A servo actuated gear will couple the motor to the engine to start it and decouple once the engine has started. Reverse thrust engine starting was unsuccessful due to limitations of available off the shelf variable pitch propellers. However, reverse thrust engine starting could be realized through a custom larger diameter propeller. Geared engine starting was a success, though the system was unable to run fully as intended. Due to counter-clockwise crank rotation of the engine and the right-hand threads on the crankshaft, cranking the engine resulted in the nut securing the engine starter gear to back off as the engine cranked. A second nut was added to secure the starter gear but at the expense of removing the engine drive pulley. Removing the engine pulley meant that the starter gear must remain engaged to transmit torque to the propeller shaft as opposed to the engine pulley. This issue can be resolved using different hardware, however changing the mounting hardware would require additional modifications to the associated component which time would not permit. Though battery technology still proves to be the main constraint of electrified powertrain, careful design and mission planning can help minimize the weight penalties incurred. The mission planning code complements previous research by comparing the weight penalties of a blended climb versus an engine only climb and selecting the lightest option. Though reverse thrust engine starting proved unsuccessful, the success of geared engine starting now allows the engine to be shut off during loiter reducing both acoustic profile and fuel consumption during loiter.

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…

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.

Reversible Quantum Brownian Heat Engines for Electrons

NASA Astrophysics Data System (ADS)

Humphrey, T. E.; Newbury, R.; Taylor, R. P.; Linke, H.

2002-08-01

Brownian heat engines use local temperature gradients in asymmetric potentials to move particles against an external force. The energy efficiency of such machines is generally limited by irreversible heat flow carried by particles that make contact with different heat baths. Here we show that, by using a suitably chosen energy filter, electrons can be transferred reversibly between reservoirs that have different temperatures and electrochemical potentials. We apply this result to propose heat engines based on mesoscopic semiconductor ratchets, which can quasistatically operate arbitrarily close to Carnot efficiency.

Reversible quantum heat engines for electrons

NASA Astrophysics Data System (ADS)

Linke, Heiner; Humphrey, Tammy E.; Newbury, Richard; Taylor, Richard P.

2002-03-01

Brownian heat engines use local temperature gradients in asymmetric potentials to move particles against an external force. The energy efficiency of such machines is generally limited by irreversible heat flow carried by particles that make contact with different heat baths. Here we show that, by using a suitably chosen energy filter, electrons can be transferred reversibly between reservoirs that have different temperatures and electrochemical potentials. We apply this result to propose heat engines based on quantum ratchets, which can quasistatically operate at Carnot efficiency.

Tissue-Engineered Skeletal Muscle Organoids for Reversible Gene Therapy

NASA Technical Reports Server (NTRS)

Vandenburgh, Herman; DelTatto, Michael; Shansky, Janet; Lemaire, Julie; Chang, Albert; Payumo, Francis; Lee, Peter; Goodyear, Amy; Raven, Latasha

1996-01-01

Genetically modified murine skeletal myoblasts were tissue engineered in vitro into organ-like structures (organoids) containing only postmitotic myoribers secreting pharmacological levels of recombinant human growth hormone (rhGH). Subcutaneous organoid implantation under tension led to the rapid and stable appearance of physiological sera levels of rhGH for up to 12 weeks, whereas surgical removal led to its rapid disappearance. Reversible delivery of bioactive compounds from postmitotic cells in tissue engineered organs has several advantages over other forms of muscle gene therapy.

Tissue-Engineered Skeletal Muscle Organoids for Reversible Gene Therapy

NASA Technical Reports Server (NTRS)

Vandenburgh, Herman; DelTatto, Michael; Shansky, Janet; Lemaire, Julie; Chang, Albert; Payumo, Francis; Lee, Peter; Goodyear, Amy; Raven, Latasha

1996-01-01

Genetically modified murine skeletal myoblasts were tissue engineered in vitro into organ-like structures (organoids) containing only postmitotic myofibers secreting pharmacological levels of recombinant human growth hormone (rhGH). Subcutaneous organoid Implantation under tension led to the rapid and stable appearance of physiological sera levels of rhGH for up to 12 weeks, whereas surgical removal led to its rapid disappearance. Reversible delivery of bioactive compounds from postimtotic cells in tissue engineered organs has several advantages over other forms of muscle gene therapy.

REAR DETAIL OF RIGHT ENGINE AND WING. THRUST REVERSER REMAINS ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

REAR DETAIL OF RIGHT ENGINE AND WING. THRUST REVERSER REMAINS OPEN. MECHANICS JONI BAINE (R) AND BILL THEODORE(L) OPEN FLAP CARRIAGE ACCESS WITH AN IMPACT GUN. THEY WILL CHECK TRANSMISSION FLUID AND OIL THE JACK SCREW. AT FAR LEFT UTILITY MECHANICS BEGIN BODY POLISHING. - Greater Buffalo International Airport, Maintenance Hangar, Buffalo, Erie County, NY

The Use of Reverse Engineering to Analyse Student Computer Programs.

ERIC Educational Resources Information Center

Vanneste, Philip; And Others

1996-01-01

Discusses how the reverse engineering approach can generate feedback on computer programs without the user having any prior knowledge of what the program was designed to do. This approach uses the cognitive model of programming knowledge to interpret both context independent and dependent errors in the same words and concepts as human programmers.…

An Application of Reverse Engineering to Automatic Item Generation: A Proof of Concept Using Automatically Generated Figures

ERIC Educational Resources Information Center

Lorié, William A.

2013-01-01

A reverse engineering approach to automatic item generation (AIG) was applied to a figure-based publicly released test item from the Organisation for Economic Cooperation and Development (OECD) Programme for International Student Assessment (PISA) mathematical literacy cognitive instrument as part of a proof of concept. The author created an item…

Over-the-wing model thrust reverser noise tests

NASA Technical Reports Server (NTRS)

Goodykoontz, J.; Gutierrez, O.

1977-01-01

Static acoustic tests were conducted on a 1/12 scale model over-the-wing target type thrust reverser. The model configuration simulates a design that is applicable to the over-the-wing short-haul advanced technology engine. Aerodynamic screening tests of a variety of reverser designs identified configurations that satisfied a reverse thrust requirement of 35 percent of forward thrust at a nozzle pressure ratio of 1.29. The variations in the reverser configuration included, blocker door angle, blocker door lip angle and shape, and side skirt shape. Acoustic data are presented and compared for the various configurations. The model data scaled to a single full size engine show that peak free field perceived noise (PN) levels at a 152.4 meter sideline distance range from 98 to 104 PNdb.

Engineering Hollow Carbon Architecture for High-Performance K-Ion Battery Anode.

PubMed

Bin, De-Shan; Lin, Xi-Jie; Sun, Yong-Gang; Xu, Yan-Song; Zhang, Ke; Cao, An-Min; Wan, Li-Jun

2018-05-31

K-ion batteries (KIBs) are now drawing increasing research interest as an inexpensive alternative to Li-ion batteries (LIBs). However, due to the large size of K + , stable electrode materials capable of sustaining the repeated K + intercalation/deintercalation cycles are extremely deficient especially if a satisfactory reversible capacity is expected. Herein, we demonstrated that the structural engineering of carbon into a hollow interconnected architecture, a shape similar to the neuron-cell network, promised high conceptual and technological potential for a high-performance KIB anode. Using melamine-formaldehyde resin as the starting material, we identify an interesting glass blowing effect of this polymeric precursor during its carbonization, which features a skeleton-softening process followed by its spontaneous hollowing. When used as a KIB anode, the carbon scaffold with interconnected hollow channels can ensure a resilient structure for a stable potassiation/depotassiation process and deliver an extraordinary capacity (340 mAh g -1 at 0.1 C) together with a superior cycling stability (no obvious fading over 150 cycles at 0.5 C).

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...

The Path to Convergence: Design, Coordination and Social Issues in the Implementation of a Middleware Data Broker.

NASA Astrophysics Data System (ADS)

Slota, S.; Khalsa, S. J. S.

2015-12-01

Infrastructures are the result of systems, networks, and inter-networks that accrete, overlay and segment one another over time. As a result, working infrastructures represent a broad heterogeneity of elements - data types, computational resources, material substrates (computing hardware, physical infrastructure, labs, physical information resources, etc.) as well as organizational and social functions which result in divergent outputs and goals. Cyber infrastructure's engineering often defaults to a separation of the social from the technical that results in the engineering succeeding in limited ways, or the exposure of unanticipated points of failure within the system. Studying the development of middleware intended to mediate interactions among systems within an earth systems science infrastructure exposes organizational, technical and standards-focused negotiations endemic to a fundamental trait of infrastructure: its characteristic invisibility in use. Intended to perform a core function within the EarthCube cyberinfrastructure, the development, governance and maintenance of an automated brokering system is a microcosm of large-scale infrastructural efforts. Points of potential system failure, regardless of the extent to which they are more social or more technical in nature, can be considered in terms of the reverse salient: a point of social and material configuration that momentarily lags behind the progress of an emerging or maturing infrastructure. The implementation of the BCube data broker has exposed reverse salients in regards to the overall EarthCube infrastructure (and the role of middleware brokering) in the form of organizational factors such as infrastructural alignment, maintenance and resilience; differing and incompatible practices of data discovery and evaluation among users and stakeholders; and a preponderance of local variations in the implementation of standards and authentication in data access. These issues are characterized by their role in increasing tension or friction among components that are on the path to convergence and may help to predict otherwise-occluded endogenous points of failure or non-adoption in the infrastructure.

Supercapacitors based on c-type cytochromes using conductive nanostructured networks of living bacteria.

PubMed

Malvankar, Nikhil S; Mester, Tünde; Tuominen, Mark T; Lovley, Derek R

2012-02-01

Supercapacitors have attracted interest in energy storage because they have the potential to complement or replace batteries. Here, we report that c-type cytochromes, naturally immersed in a living, electrically conductive microbial biofilm, greatly enhance the device capacitance by over two orders of magnitude. We employ genetic engineering, protein unfolding and Nernstian modeling for in vivo demonstration of charge storage capacity of c-type cytochromes and perform electrochemical impedance spectroscopy, cyclic voltammetry and charge-discharge cycling to confirm the pseudocapacitive, redox nature of biofilm capacitance. The biofilms also show low self-discharge and good charge/discharge reversibility. The superior electrochemical performance of the biofilm is related to its high abundance of cytochromes, providing large electron storage capacity, its nanostructured network with metallic-like conductivity, and its porous architecture with hydrous nature, offering prospects for future low cost and environmentally sustainable energy storage devices. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modeling T-cell activation using gene expression profiling and state-space models.

PubMed

Rangel, Claudia; Angus, John; Ghahramani, Zoubin; Lioumi, Maria; Sotheran, Elizabeth; Gaiba, Alessia; Wild, David L; Falciani, Francesco

2004-06-12

We have used state-space models to reverse engineer transcriptional networks from highly replicated gene expression profiling time series data obtained from a well-established model of T-cell activation. State space models are a class of dynamic Bayesian networks that assume that the observed measurements depend on some hidden state variables that evolve according to Markovian dynamics. These hidden variables can capture effects that cannot be measured in a gene expression profiling experiment, e.g. genes that have not been included in the microarray, levels of regulatory proteins, the effects of messenger RNA and protein degradation, etc. Bootstrap confidence intervals are developed for parameters representing 'gene-gene' interactions over time. Our models represent the dynamics of T-cell activation and provide a methodology for the development of rational and experimentally testable hypotheses. Supplementary data and Matlab computer source code will be made available on the web at the URL given below. http://public.kgi.edu/~wild/LDS/index.htm

Reverse engineering of gene regulatory networks.

PubMed

Cho, K H; Choo, S M; Jung, S H; Kim, J R; Choi, H S; Kim, J

2007-05-01

Systems biology is a multi-disciplinary approach to the study of the interactions of various cellular mechanisms and cellular components. Owing to the development of new technologies that simultaneously measure the expression of genetic information, systems biological studies involving gene interactions are increasingly prominent. In this regard, reconstructing gene regulatory networks (GRNs) forms the basis for the dynamical analysis of gene interactions and related effects on cellular control pathways. Various approaches of inferring GRNs from gene expression profiles and biological information, including machine learning approaches, have been reviewed, with a brief introduction of DNA microarray experiments as typical tools for measuring levels of messenger ribonucleic acid (mRNA) expression. In particular, the inference methods are classified according to the required input information, and the main idea of each method is elucidated by comparing its advantages and disadvantages with respect to the other methods. In addition, recent developments in this field are introduced and discussions on the challenges and opportunities for future research are provided.

L1000CDS2: LINCS L1000 characteristic direction signatures search engine.

PubMed

Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma'ayan, Avi

2016-01-01

The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS 2 . The L1000CDS 2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS 2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS 2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS 2 , we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS 2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS 2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource.

Cranioplasty prosthesis manufacturing based on reverse engineering technology

PubMed Central

Chrzan, Robert; Urbanik, Andrzej; Karbowski, Krzysztof; Moskała, Marek; Polak, Jarosław; Pyrich, Marek

2012-01-01

Summary Background Most patients with large focal skull bone loss after craniectomy are referred for cranioplasty. Reverse engineering is a technology which creates a computer-aided design (CAD) model of a real structure. Rapid prototyping is a technology which produces physical objects from virtual CAD models. The aim of this study was to assess the clinical usefulness of these technologies in cranioplasty prosthesis manufacturing. Material/Methods CT was performed on 19 patients with focal skull bone loss after craniectomy, using a dedicated protocol. A material model of skull deficit was produced using computer numerical control (CNC) milling, and individually pre-operatively adjusted polypropylene-polyester prosthesis was prepared. In a control group of 20 patients a prosthesis was manually adjusted to each patient by a neurosurgeon during surgery, without using CT-based reverse engineering/rapid prototyping. In each case, the prosthesis was implanted into the patient. The mean operating times in both groups were compared. Results In the group of patients with reverse engineering/rapid prototyping-based cranioplasty, the mean operating time was shorter (120.3 min) compared to that in the control group (136.5 min). The neurosurgeons found the new technology particularly useful in more complicated bone deficits with different curvatures in various planes. Conclusions Reverse engineering and rapid prototyping may reduce the time needed for cranioplasty neurosurgery and improve the prosthesis fitting. Such technologies may utilize data obtained by commonly used spiral CT scanners. The manufacturing of individually adjusted prostheses should be commonly used in patients planned for cranioplasty with synthetic material. PMID:22207125

In vitro assessment of the contact mechanics of reverse-engineered distal humeral hemiarthroplasty prostheses.

PubMed

Willing, Ryan; Lapner, Michael; King, Graham J W; Johnson, James A

2014-11-01

Distal humeral hemiarthroplasty alters cartilage contact mechanics, which may predispose to osteoarthritis. Current prostheses do not replicate the native anatomy, and therefore contribute to these changes. We hypothesized that prostheses reverse-engineered from the native bone shape would provide similar contact patterns as the native articulation. Reverse-engineered hemiarthroplasty prostheses were manufactured for five cadaveric elbows based on CT images of the distal humerus. Passive flexion trials with constant muscle forces were performed with the native articulation intact while bone motions were recorded using a motion tracking system. Motion trials were then repeated after the distal humerus was replaced with a corresponding reverse-engineered prosthesis. Contact areas and patterns were reconstructed using computer models created from CT scan images combined with the motion tracker data. The total contact areas, as well as the contact area within smaller sub-regions of the ulna and radius, were analyzed for changes resulting from hemiarthroplasty using repeated-measures ANOVAs. Contact area at the ulna and radius decreased on average 42% (SD 19%, P=.008) and 41% (SD 42%, P=.096), respectively. Contact area decreases were not uniform throughout the different sub-regions, suggesting that contact patterns were also altered. Reverse-engineered prostheses did not reproduce the same contact pattern as the native joints, possibly because the thickness of the distal humerus cartilage layer was neglected when generating the prosthesis shapes or as a consequence of the increased stiffness of the metallic implants. Alternative design strategies and materials for hemiarthroplasty should be considered in future work. Copyright © 2014 Elsevier Ltd. All rights reserved.

DNA-nanoparticle assemblies go organic: macroscopic polymeric materials with nanosized features.

PubMed

Mentovich, Elad D; Livanov, Konstantin; Prusty, Deepak K; Sowwan, Mukules; Richter, Shachar

2012-05-30

One of the goals in the field of structural DNA nanotechnology is the use of DNA to build up 2- and 3-D nanostructures. The research in this field is motivated by the remarkable structural features of DNA as well as by its unique and reversible recognition properties. Nucleic acids can be used alone as the skeleton of a broad range of periodic nanopatterns and nanoobjects and in addition, DNA can serve as a linker or template to form DNA-hybrid structures with other materials. This approach can be used for the development of new detection strategies as well as nanoelectronic structures and devices. Here we present a new method for the generation of unprecedented all-organic conjugated-polymer nanoparticle networks guided by DNA, based on a hierarchical self-assembly process. First, microphase separation of amphiphilic block copolymers induced the formation of spherical nanoobjects. As a second ordering concept, DNA base pairing has been employed for the controlled spatial definition of the conjugated-polymer particles within the bulk material. These networks offer the flexibility and the diversity of soft polymeric materials. Thus, simple chemical methodologies could be applied in order to tune the network's electrical, optical and mechanical properties. One- two- and three-dimensional networks have been successfully formed. Common to all morphologies is the integrity of the micelles consisting of DNA block copolymer (DBC), which creates an all-organic engineered network.

Boosting probabilistic graphical model inference by incorporating prior knowledge from multiple sources.

PubMed

Praveen, Paurush; Fröhlich, Holger

2013-01-01

Inferring regulatory networks from experimental data via probabilistic graphical models is a popular framework to gain insights into biological systems. However, the inherent noise in experimental data coupled with a limited sample size reduces the performance of network reverse engineering. Prior knowledge from existing sources of biological information can address this low signal to noise problem by biasing the network inference towards biologically plausible network structures. Although integrating various sources of information is desirable, their heterogeneous nature makes this task challenging. We propose two computational methods to incorporate various information sources into a probabilistic consensus structure prior to be used in graphical model inference. Our first model, called Latent Factor Model (LFM), assumes a high degree of correlation among external information sources and reconstructs a hidden variable as a common source in a Bayesian manner. The second model, a Noisy-OR, picks up the strongest support for an interaction among information sources in a probabilistic fashion. Our extensive computational studies on KEGG signaling pathways as well as on gene expression data from breast cancer and yeast heat shock response reveal that both approaches can significantly enhance the reconstruction accuracy of Bayesian Networks compared to other competing methods as well as to the situation without any prior. Our framework allows for using diverse information sources, like pathway databases, GO terms and protein domain data, etc. and is flexible enough to integrate new sources, if available.

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.

Effects of Edge Directions on the Structural Controllability of Complex Networks

PubMed Central

Xiao, Yandong; Lao, Songyang; Hou, Lvlin; Small, Michael; Bai, Liang

2015-01-01

Recent advances indicate that assigning or reversing edge direction can significantly improve the structural controllability of complex networks. For directed networks, approaching the optimal structural controllability can be achieved by detecting and reversing certain “inappropriate” edge directions. However, the existence of multiple sets of “inappropriate” edge directions suggests that different edges have different effects on optimal controllability—that is, different combinations of edges can be reversed to achieve the same structural controllability. Therefore, we classify edges into three categories based on their direction: critical, redundant and intermittent. We then investigate the effects of changing these edge directions on network controllability, and demonstrate that the existence of more critical edge directions implies not only a lower cost of modifying inappropriate edges but also better controllability. Motivated by this finding, we present a simple edge orientation method aimed at producing more critical edge directions—utilizing only local information—which achieves near optimal controllability. Furthermore, we explore the effects of edge direction on the controllability of several real networks. PMID:26281042

Effects of Edge Directions on the Structural Controllability of Complex Networks.

PubMed

Xiao, Yandong; Lao, Songyang; Hou, Lvlin; Small, Michael; Bai, Liang

2015-01-01

Recent advances indicate that assigning or reversing edge direction can significantly improve the structural controllability of complex networks. For directed networks, approaching the optimal structural controllability can be achieved by detecting and reversing certain "inappropriate" edge directions. However, the existence of multiple sets of "inappropriate" edge directions suggests that different edges have different effects on optimal controllability-that is, different combinations of edges can be reversed to achieve the same structural controllability. Therefore, we classify edges into three categories based on their direction: critical, redundant and intermittent. We then investigate the effects of changing these edge directions on network controllability, and demonstrate that the existence of more critical edge directions implies not only a lower cost of modifying inappropriate edges but also better controllability. Motivated by this finding, we present a simple edge orientation method aimed at producing more critical edge directions-utilizing only local information-which achieves near optimal controllability. Furthermore, we explore the effects of edge direction on the controllability of several real networks.

Reversible and irreversible heat engine and refrigerator cycles

NASA Astrophysics Data System (ADS)

Leff, Harvey S.

2018-05-01

Although no reversible thermodynamic cycles exist in nature, nearly all cycles covered in textbooks are reversible. This is a review, clarification, and extension of results and concepts for quasistatic, reversible and irreversible processes and cycles, intended primarily for teachers and students. Distinctions between the latter process types are explained, with emphasis on clockwise (CW) and counterclockwise (CCW) cycles. Specific examples of each are examined, including Carnot, Kelvin and Stirling cycles. For the Stirling cycle, potentially useful task-specific efficiency measures are proposed and illustrated. Whether a cycle behaves as a traditional refrigerator or heat engine can depend on whether it is reversible or irreversible. Reversible and irreversible-quasistatic CW cycles both satisfy Carnot's inequality for thermal efficiency, η ≤ η C a r n o t . Irreversible CCW cycles with two reservoirs satisfy the coefficient of performance inequality K ≤ K C a r n o t . However, an arbitrary reversible cycle satisfies K ≥ K C a r n o t when compared with a reversible Carnot cycle operating between its maximum and minimum temperatures, a potentially counterintuitive result.

The ATPG Attack for Reverse Engineering of Combinational Hybrid Custom-Programmable Circuits

DTIC Science & Technology

2017-03-23

The ATPG Attack for Reverse Engineering of Combinational Hybrid Custom- Programmable Circuits Raza Shafiq Hamid Mahmoodi Houman Homayoun Hassan... programmable circuits. While functionality of programmable cells are only known to trusted parties, effective techniques for activation and propagation...of the cells are introduced. The ATPG attack carefully studies dependency of programmable cells to develop their (partial) truth tables. Results

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...

Reverse engineering physical models employing a sensor integration between 3D stereo detection and contact digitization

NASA Astrophysics Data System (ADS)

Chen, Liang-Chia; Lin, Grier C. I.

1997-12-01

A vision-drive automatic digitization process for free-form surface reconstruction has been developed, with a coordinate measurement machine (CMM) equipped with a touch-triggered probe and a CCD camera, in reverse engineering physical models. The process integrates 3D stereo detection, data filtering, Delaunay triangulation, adaptive surface digitization into a single process of surface reconstruction. By using this innovative approach, surface reconstruction can be implemented automatically and accurately. Least-squares B- spline surface models with the controlled accuracy of digitization can be generated for further application in product design and manufacturing processes. One industrial application indicates that this approach is feasible, and the processing time required in reverse engineering process can be significantly reduced up to more than 85%.

Mobile Timekeeping Application Built on Reverse-Engineered JPL Infrastructure

NASA Technical Reports Server (NTRS)

Witoff, Robert J.

2013-01-01

Every year, non-exempt employees cumulatively waste over one man-year tracking their time and using the timekeeping Web page to save those times. This app eliminates this waste. The innovation is a native iPhone app. Libraries were built around a reverse- engineered JPL API. It represents a punch-in/punch-out paradigm for timekeeping. It is accessible natively via iPhones, and features ease of access. Any non-exempt employee can natively punch in and out, as well as save and view their JPL timecard. This app is built on custom libraries created by reverse-engineering the standard timekeeping application. Communication is through custom libraries that re-route traffic through BrowserRAS (remote access service). This has value at any center where employees track their time.

Covalent adaptable networks: smart, reconfigurable and responsive network systems.

PubMed

Kloxin, Christopher J; Bowman, Christopher N

2013-09-07

Covalently crosslinked materials, classically referred to as thermosets, represent a broad class of elastic materials that readily retain their shape and molecular architecture through covalent bonds that are ubiquitous throughout the network structure. These materials, in particular in their swollen gel state, have been widely used as stimuli responsive materials with their ability to change volume in response to changes in temperature, pH, or other solvent conditions and have also been used in shape memory applications. However, the existence of a permanent, unalterable shape and structure dictated by the covalently crosslinked structure has dramatically limited their abilities in this and many other areas. These materials are not generally reconfigurable, recyclable, reprocessable, and have limited ability to alter permanently their stress state, topography, topology, or structure. Recently, a new paradigm has been explored in crosslinked polymers - that of covalent adaptable networks (CANs) in which covalently crosslinked networks are formed such that triggerable, reversible chemical structures persist throughout the network. These reversible covalent bonds can be triggered through molecular triggers, light or other incident radiation, or temperature changes. Upon application of this stimulus, rather than causing a temporary shape change, the CAN structure responds by permanently adjusting its structure through either reversible addition/condensation or through reversible bond exchange mechanisms, either of which allow the material to essentially reequilibrate to its new state and condition. Here, we provide a tutorial review on these materials and their responsiveness to applied stimuli. In particular, we review the broad classification of these materials, the nature of the chemical bonds that enable the adaptable structure, how the properties of these materials depend on the reversible structure, and how the application of a stimulus causes these materials to alter their shape, topography, and properties.

Causal Interrogation of Neuronal Networks and Behavior through Virally Transduced Ivermectin Receptors.

PubMed

Obenhaus, Horst A; Rozov, Andrei; Bertocchi, Ilaria; Tang, Wannan; Kirsch, Joachim; Betz, Heinrich; Sprengel, Rolf

2016-01-01

The causal interrogation of neuronal networks involved in specific behaviors requires the spatially and temporally controlled modulation of neuronal activity. For long-term manipulation of neuronal activity, chemogenetic tools provide a reasonable alternative to short-term optogenetic approaches. Here we show that virus mediated gene transfer of the ivermectin (IVM) activated glycine receptor mutant GlyRα1 (AG) can be used for the selective and reversible silencing of specific neuronal networks in mice. In the striatum, dorsal hippocampus, and olfactory bulb, GlyRα1 (AG) promoted IVM dependent effects in representative behavioral assays. Moreover, GlyRα1 (AG) mediated silencing had a strong and reversible impact on neuronal ensemble activity and c-Fos activation in the olfactory bulb. Together our results demonstrate that long-term, reversible and re-inducible neuronal silencing via GlyRα1 (AG) is a promising tool for the interrogation of network mechanisms underlying the control of behavior and memory formation.

Using cyber vulnerability testing techniques to expose undocumented security vulnerabilities in DCS and SCADA equipment

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

Pollet, J.

2006-07-01

This session starts by providing an overview of typical DCS (Distributed Control Systems) and SCADA (Supervisory Control and Data Acquisition) architectures, and exposes cyber security vulnerabilities that vendors never admit, but are found through a comprehensive cyber testing process. A complete assessment process involves testing all of the layers and components of a SCADA or DCS environment, from the perimeter firewall all the way down to the end devices controlling the process, including what to look for when conducting a vulnerability assessment of real-time control systems. The following systems are discussed: 1. Perimeter (isolation from corporate IT or other non-criticalmore » networks) 2. Remote Access (third Party access into SCADA or DCS networks) 3. Network Architecture (switch, router, firewalls, access controls, network design) 4. Network Traffic Analysis (what is running on the network) 5. Host Operating Systems Hardening 6. Applications (how they communicate with other applications and end devices) 7. End Device Testing (PLCs, RTUs, DCS Controllers, Smart Transmitters) a. System Discovery b. Functional Discovery c. Attack Methodology i. DoS Tests (at what point does the device fail) ii. Malformed Packet Tests (packets that can cause equipment failure) iii. Session Hijacking (do anything that the operator can do) iv. Packet Injection (code and inject your own SCADA commands) v. Protocol Exploitation (Protocol Reverse Engineering / Fuzzing) This paper will provide information compiled from over five years of conducting cyber security testing on control systems hardware, software, and systems. (authors)« less

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...

Proactive malware detection

NASA Astrophysics Data System (ADS)

Gloster, Jonathan; Diep, Michael; Dredden, David; Mix, Matthew; Olsen, Mark; Price, Brian; Steil, Betty

2014-06-01

Small-to-medium sized businesses lack resources to deploy and manage high-end advanced solutions to deter sophisticated threats from well-funded adversaries, but evidence shows that these types of businesses are becoming key targets. As malicious code and network attacks become more sophisticated, classic signature-based virus and malware detection methods are less effective. To augment the current malware methods of detection, we developed a proactive approach to detect emerging malware threats using open source tools and intelligence to discover patterns and behaviors of malicious attacks and adversaries. Technical and analytical skills are combined to track adversarial behavior, methods and techniques. We established a controlled (separated domain) network to identify, monitor, and track malware behavior to increase understanding of the methods and techniques used by cyber adversaries. We created a suite of tools that observe the network and system performance looking for anomalies that may be caused by malware. The toolset collects information from open-source tools and provides meaningful indicators that the system was under or has been attacked. When malware is discovered, we analyzed and reverse engineered it to determine how it could be detected and prevented. Results have shown that with minimum resources, cost effective capabilities can be developed to detect abnormal behavior that may indicate malicious software.

Optimization of Actuating Origami Networks

NASA Astrophysics Data System (ADS)

Buskohl, Philip; Fuchi, Kazuko; Bazzan, Giorgio; Joo, James; Gregory, Reich; Vaia, Richard

2015-03-01

Origami structures morph between 2D and 3D conformations along predetermined fold lines that efficiently program the form, function and mobility of the structure. By leveraging design concepts from action origami, a subset of origami art focused on kinematic mechanisms, reversible folding patterns for applications such as solar array packaging, tunable antennae, and deployable sensing platforms may be designed. However, the enormity of the design space and the need to identify the requisite actuation forces within the structure places a severe limitation on design strategies based on intuition and geometry alone. The present work proposes a topology optimization method, using truss and frame element analysis, to distribute foldline mechanical properties within a reference crease pattern. Known actuating patterns are placed within a reference grid and the optimizer adjusts the fold stiffness of the network to optimally connect them. Design objectives may include a target motion, stress level, or mechanical energy distribution. Results include the validation of known action origami structures and their optimal connectivity within a larger network. This design suite offers an important step toward systematic incorporation of origami design concepts into new, novel and reconfigurable engineering devices. This research is supported under the Air Force Office of Scientific Research (AFOSR) funding, LRIR 13RQ02COR.

Developing weighted criteria to evaluate lean reverse logistics through analytical network process

NASA Astrophysics Data System (ADS)

Zagloel, Teuku Yuri M.; Hakim, Inaki Maulida; Krisnawardhani, Rike Adyartie

2017-11-01

Reverse logistics is a part of supply chain that bring materials from consumers back to manufacturer in order to gain added value or do a proper disposal. Nowadays, most companies are still facing several problems on reverse logistics implementation which leads to high waste along reverse logistics processes. In order to overcome this problem, Madsen [Framework for Reverse Lean Logistics to Enable Green Manufacturing, Eco Design 2009: 6th International Symposium on Environmentally Conscious Design and Inverse Manufacturing, Sapporo, 2009] has developed a lean reverse logistics framework as a step to eliminate waste by implementing lean on reverse logistics. However, the resulted framework sets aside criteria used to evaluate its performance. This research aims to determine weighted criteria that can be used as a base on reverse logistics evaluation by considering lean principles. The resulted criteria will ensure reverse logistics are kept off from waste, thus implemented efficiently. Analytical Network Process (ANP) is used in this research to determine the weighted criteria. The result shows that criteria used for evaluation lean reverse logistics are Innovation and Learning (35%), Economic (30%), Process Flow Management (14%), Customer Relationship Management (13%), Environment (6%), and Social (2%).

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.

Energy Efficient Engine program advanced turbofan nacelle definition study

NASA Technical Reports Server (NTRS)

Howe, David C.; Wynosky, T. A.

1985-01-01

Advanced, low drag, nacelle configurations were defined for some of the more promising propulsion systems identified in the earlier Benefit/Cost Study, to assess the benefits associated with these advanced technology nacelles and formulate programs for developing these nacelles and low volume thrust reversers/spoilers to a state of technology readiness in the early 1990's. The study results established the design feasibility of advanced technology, slim line nacelles applicable to advanced technology, high bypass ratio turbofan engines. Design feasibility was also established for two low volume thrust reverse/spoiler concepts that meet or exceed the required effectiveness for these engines. These nacelle and thrust reverse/spoiler designs were shown to be applicable in engines with takeoff thrust sizes ranging from 24,000 to 60,000 pounds. The reduced weight, drag, and cost of the advanced technology nacelle installations relative to current technology nacelles offer a mission fuel burn savings ranging from 3.0 to 4.5 percent and direct operating cost plus interest improvements from 1.6 to 2.2 percent.

Inferring microbial interactions in thermophilic and mesophilic anaerobic digestion of hog waste

PubMed Central

Shaw, Grace Tzun-Wen; Liu, An-Chi; Weng, Chieh-Yin; Chou, Chu-Yang

2017-01-01

Anaerobic digestion (AnD) is a microbiological process that converts organic waste materials into biogas. Because of its high methane content, biogas is a combustible energy source and serves as an important environmental technology commonly used in the management of animal waste generated on large animal farms. Much work has been done on hardware design and process engineering for the generation of biogas. However, little is known about the complexity of the microbiology in this process. In particular, how microbes interact in the digester and eventually breakdown and convert organic matter into biogas is still regarded as a “black box.” We used 16S rRNA sequencing as a tool to study the microbial community in laboratory hog waste digesters under tightly controlled conditions, and systematically unraveled the distinct interaction networks of two microbial communities from mesophilic (MAnD) and thermophilic anaerobic digestion (TAnD). Under thermophilic conditions, the well-known association between hydrogen-producing bacteria, e.g., Ruminococcaceae and Prevotellaceae, and hydrotrophic methanogens, Methanomicrobiaceae, was reverse engineered by their interactive topological niches. The inferred interaction network provides a sketch enabling the determination of microbial interactive relationships that conventional strategy of finding differential taxa was hard to achieve. This research is still in its infancy, but it can help to depict the dynamics of microbial ecosystems and to lay the groundwork for understanding how microorganisms cohabit in the anaerobic digester. PMID:28732056

Inferring microbial interactions in thermophilic and mesophilic anaerobic digestion of hog waste.

PubMed

Shaw, Grace Tzun-Wen; Liu, An-Chi; Weng, Chieh-Yin; Chou, Chu-Yang; Wang, Daryi

2017-01-01

Anaerobic digestion (AnD) is a microbiological process that converts organic waste materials into biogas. Because of its high methane content, biogas is a combustible energy source and serves as an important environmental technology commonly used in the management of animal waste generated on large animal farms. Much work has been done on hardware design and process engineering for the generation of biogas. However, little is known about the complexity of the microbiology in this process. In particular, how microbes interact in the digester and eventually breakdown and convert organic matter into biogas is still regarded as a "black box." We used 16S rRNA sequencing as a tool to study the microbial community in laboratory hog waste digesters under tightly controlled conditions, and systematically unraveled the distinct interaction networks of two microbial communities from mesophilic (MAnD) and thermophilic anaerobic digestion (TAnD). Under thermophilic conditions, the well-known association between hydrogen-producing bacteria, e.g., Ruminococcaceae and Prevotellaceae, and hydrotrophic methanogens, Methanomicrobiaceae, was reverse engineered by their interactive topological niches. The inferred interaction network provides a sketch enabling the determination of microbial interactive relationships that conventional strategy of finding differential taxa was hard to achieve. This research is still in its infancy, but it can help to depict the dynamics of microbial ecosystems and to lay the groundwork for understanding how microorganisms cohabit in the anaerobic digester.

CRISPR: a Versatile Tool for Both Forward and Reverse Genetics Research

PubMed Central

Gurumurthy, Channabasavaiah B.; Grati, M'hamed; Ohtsuka, Masato; Schilit, Samantha L.P.; Quadros, Rolen M.; Liu, Xue Zhong

2016-01-01

Human genetics research employs the two opposing approaches of forward and reverse genetics. While forward genetics identifies and links a mutation to an observed disease etiology, reverse genetics induces mutations in model organisms to study their role in disease. In most cases, causality for mutations identified by forward genetics is confirmed by reverse genetics through the development of genetically engineered animal models and an assessment of whether the model can recapitulate the disease. While many technological advances have helped improve these approaches, some gaps still remain. CRISPR/Cas (clustered regularly interspaced short palindromic repeats/CRISPR-associated) system, which has emerged as a revolutionary genetic engineering tool, holds great promise for closing such gaps. By combining the benefits of forward and reverse genetics, it has dramatically expedited human genetics research. We provide a perspective on the power of CRISPR-based forward and reverse genetics tools in human genetics and discuss its applications using some disease examples. PMID:27384229

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.

The results of a low-speed wind tunnel test to investigate the effects of the Refan JT8D engine target thrust reverser on the stability and control characteristics of the Boeing 727-200 airplane

NASA Technical Reports Server (NTRS)

Kupcis, E. A.

1974-01-01

The effects of the Refan JT8D side engine target thrust reverser on the stability and control characteristics of the Boeing 727-200 airplane were investigated using the Boeing-Vertol 20 x 20 ft Low-Speed Wind Tunnel. A powered model of the 727-200 was tested in groud effect in the landing configuration. The Refan target reverser configuration was evaluated relative to the basic production 727 airplane with its clamshell-deflector door thrust reverser design. The Refan configuration had slightly improved directional control characteristics relative to the basic airplane. Clocking the Refan thrust reversers 20 degrees outboard to direct the reverser flow away from the vertical tail, had little effect on directional control. However, clocking them 20 degrees inboard resulted in a complete loss of rudder effectiveness for speeds greater than 90 knots. Variations in Refan reverser lip/fence geometry had a minor effect on directional control.

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.

Reversible Thermoset Adhesives

NASA Technical Reports Server (NTRS)

Mac Murray, Benjamin C. (Inventor); Tong, Tat H. (Inventor); Hreha, Richard D. (Inventor)

2016-01-01

Embodiments of a reversible thermoset adhesive formed by incorporating thermally-reversible cross-linking units and a method for making the reversible thermoset adhesive are provided. One approach to formulating reversible thermoset adhesives includes incorporating dienes, such as furans, and dienophiles, such as maleimides, into a polymer network as reversible covalent cross-links using Diels Alder cross-link formation between the diene and dienophile. The chemical components may be selected based on their compatibility with adhesive chemistry as well as their ability to undergo controlled, reversible cross-linking chemistry.

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.

Quantum generalisation of feedforward neural networks

NASA Astrophysics Data System (ADS)

Wan, Kwok Ho; Dahlsten, Oscar; Kristjánsson, Hlér; Gardner, Robert; Kim, M. S.

2017-09-01

We propose a quantum generalisation of a classical neural network. The classical neurons are firstly rendered reversible by adding ancillary bits. Then they are generalised to being quantum reversible, i.e., unitary (the classical networks we generalise are called feedforward, and have step-function activation functions). The quantum network can be trained efficiently using gradient descent on a cost function to perform quantum generalisations of classical tasks. We demonstrate numerically that it can: (i) compress quantum states onto a minimal number of qubits, creating a quantum autoencoder, and (ii) discover quantum communication protocols such as teleportation. Our general recipe is theoretical and implementation-independent. The quantum neuron module can naturally be implemented photonically.

Reverse engineering of integrated circuits

DOEpatents

Chisholm, Gregory H.; Eckmann, Steven T.; Lain, Christopher M.; Veroff, Robert L.

2003-01-01

Software and a method therein to analyze circuits. The software comprises several tools, each of which perform particular functions in the Reverse Engineering process. The analyst, through a standard interface, directs each tool to the portion of the task to which it is most well suited, rendering previously intractable problems solvable. The tools are generally used iteratively to produce a successively more abstract picture of a circuit, about which incomplete a priori knowledge exists.

Efficient Green's Function Reaction Dynamics (GFRD) simulations for diffusion-limited, reversible reactions

NASA Astrophysics Data System (ADS)

Bashardanesh, Zahedeh; Lötstedt, Per

2018-03-01

In diffusion controlled reversible bimolecular reactions in three dimensions, a dissociation step is typically followed by multiple, rapid re-association steps slowing down the simulations of such systems. In order to improve the efficiency, we first derive an exact Green's function describing the rate at which an isolated pair of particles undergoing reversible bimolecular reactions and unimolecular decay separates beyond an arbitrarily chosen distance. Then the Green's function is used in an algorithm for particle-based stochastic reaction-diffusion simulations for prediction of the dynamics of biochemical networks. The accuracy and efficiency of the algorithm are evaluated using a reversible reaction and a push-pull chemical network. The computational work is independent of the rates of the re-associations.

Quantum Stirling heat engine and refrigerator with single and coupled spin systems

NASA Astrophysics Data System (ADS)

Huang, Xiao-Li; Niu, Xin-Ya; Xiu, Xiao-Ming; Yi, Xue-Xi

2014-02-01

We study the reversible quantum Stirling cycle with a single spin or two coupled spins as the working substance. With the single spin as the working substance, we find that under certain conditions the reversed cycle of a heat engine is NOT a refrigerator, this feature holds true for a Stirling heat engine with an ion trapped in a shallow potential as its working substance. The efficiency of quantum Stirling heat engine can be higher than the efficiency of the Carnot engine, but the performance coefficient of the quantum Stirling refrigerator is always lower than its classical counterpart. With two coupled spins as the working substance, we find that a heat engine can turn to a refrigerator due to the increasing of the coupling constant, this can be explained by the properties of the isothermal line in the magnetic field-entropy plane.

When global rule reversal meets local task switching: The neural mechanisms of coordinated behavioral adaptation to instructed multi-level demand changes.

PubMed

Shi, Yiquan; Wolfensteller, Uta; Schubert, Torsten; Ruge, Hannes

2018-02-01

Cognitive flexibility is essential to cope with changing task demands and often it is necessary to adapt to combined changes in a coordinated manner. The present fMRI study examined how the brain implements such multi-level adaptation processes. Specifically, on a "local," hierarchically lower level, switching between two tasks was required across trials while the rules of each task remained unchanged for blocks of trials. On a "global" level regarding blocks of twelve trials, the task rules could reverse or remain the same. The current task was cued at the start of each trial while the current task rules were instructed before the start of a new block. We found that partly overlapping and partly segregated neural networks play different roles when coping with the combination of global rule reversal and local task switching. The fronto-parietal control network (FPN) supported the encoding of reversed rules at the time of explicit rule instruction. The same regions subsequently supported local task switching processes during actual implementation trials, irrespective of rule reversal condition. By contrast, a cortico-striatal network (CSN) including supplementary motor area and putamen was increasingly engaged across implementation trials and more so for rule reversal than for nonreversal blocks, irrespective of task switching condition. Together, these findings suggest that the brain accomplishes the coordinated adaptation to multi-level demand changes by distributing processing resources either across time (FPN for reversed rule encoding and later for task switching) or across regions (CSN for reversed rule implementation and FPN for concurrent task switching). © 2017 Wiley Periodicals, Inc.

Metabolic engineering of plant oils and waxes for use as industrial feedstocks.

PubMed

Vanhercke, Thomas; Wood, Craig C; Stymne, Sten; Singh, Surinder P; Green, Allan G

2013-02-01

Society has come to rely heavily on mineral oil for both energy and petrochemical needs. Plant lipids are uniquely suited to serve as a renewable source of high-value fatty acids for use as chemical feedstocks and as a substitute for current petrochemicals. Despite the broad variety of acyl structures encountered in nature and the cloning of many genes involved in their biosynthesis, attempts at engineering economic levels of specialty industrial fatty acids in major oilseed crops have so far met with only limited success. Much of the progress has been hampered by an incomplete knowledge of the fatty acid biosynthesis and accumulation pathways. This review covers new insights based on metabolic flux and reverse engineering studies that have changed our view of plant oil synthesis from a mostly linear process to instead an intricate network with acyl fluxes differing between plant species. These insights are leading to new strategies for high-level production of industrial fatty acids and waxes. Furthermore, progress in increasing the levels of oil and wax structures in storage and vegetative tissues has the potential to yield novel lipid production platforms. The challenge and opportunity for the next decade will be to marry these technologies when engineering current and new crops for the sustainable production of oil and wax feedstocks. © 2012 CSIRO Plant Biotechnology Journal © 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd.

Network modeling for reverse flows of end-of-life vehicles

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

Ene, Seval; Öztürk, Nursel

2015-04-15

Highlights: • We developed a network model for reverse flows of end-of-life vehicles. • The model considers all recovery operations for end-of-life vehicles. • A scenario-based model is used for uncertainty to improve real case applications. • The model is adequate to real case applications for end-of-life vehicles recovery. • Considerable insights are gained from the model by sensitivity analyses. - Abstract: Product recovery operations are of critical importance for the automotive industry in complying with environmental regulations concerning end-of-life products management. Manufacturers must take responsibility for their products over the entire life cycle. In this context, there is amore » need for network design methods for effectively managing recovery operations and waste. The purpose of this study is to develop a mathematical programming model for managing reverse flows in end-of-life vehicles’ recovery network. A reverse flow is the collection of used products from consumers and the transportation of these products for the purpose of recycling, reuse or disposal. The proposed model includes all operations in a product recovery and waste management network for used vehicles and reuse for vehicle parts such as collection, disassembly, refurbishing, processing (shredding), recycling, disposal and reuse of vehicle parts. The scope of the network model is to determine the numbers and locations of facilities in the network and the material flows between these facilities. The results show the performance of the model and its applicability for use in the planning of recovery operations in the automotive industry. The main objective of recovery and waste management is to maximize revenue and minimize pollution in end-of-life product operations. This study shows that with an accurate model, these activities may provide economic benefits and incentives in addition to protecting the environment.« less

Validation of long-term primary neuronal cultures and network activity through the integration of reversibly bonded microbioreactors and MEA substrates.

PubMed

Biffi, Emilia; Menegon, Andrea; Piraino, Francesco; Pedrocchi, Alessandra; Fiore, Gianfranco B; Rasponi, Marco

2012-01-01

In vitro recording of neuronal electrical activity is a widely used technique to understand brain functions and to study the effect of drugs on the central nervous system. The integration of microfluidic devices with microelectrode arrays (MEAs) enables the recording of networks activity in a controlled microenvironment. In this work, an integrated microfluidic system for neuronal cultures was developed, reversibly coupling a PDMS microfluidic device with a commercial flat MEA through magnetic forces. Neurons from mouse embryos were cultured in a 100 µm channel and their activity was followed up to 18 days in vitro. The maturation of the networks and their morphological and functional characteristics were comparable with those of networks cultured in macro-environments and described in literature. In this work, we successfully demonstrated the ability of long-term culturing of primary neuronal cells in a reversible bonded microfluidic device (based on magnetism) that will be fundamental for neuropharmacological studies. Copyright © 2011 Wiley Periodicals, Inc.

Dynamic Perturbation of the Active Site Determines Reversible Thermal Inactivation in Glycoside Hydrolase Family 12.

PubMed

Jiang, Xukai; Li, Wen; Chen, Guanjun; Wang, Lushan

2017-02-27

The temperature dependence of enzyme catalysis is highly debated. Specifically, how high temperatures induce enzyme inactivation has broad implications for both fundamental and applied science. Here, we explored the mechanism of the reversible thermal inactivation in glycoside hydrolase family 12 (GH12) using comparative molecular dynamics simulations. First, we investigated the distribution of structural flexibility over the enzyme and found that the active site was the general thermal-sensitive region in GH12 cellulases. The dynamic perturbation of the active site before enzyme denaturation was explored through principal-component analysis, which indicated that variations in the collective motion and conformational ensemble of the active site may precisely correspond to enzyme transition from its active form to the inactive form. Furthermore, the degree of dynamic perturbation of the active site was found to be negatively correlated with the melting temperatures of GH12 enzymes, further proving the importance of the dynamic stability of the active site. Additionally, analysis of the residue-interaction network revealed that the active site in thermophilic enzyme was capable of forming additional contacts with other amino acids than those observed in the mesophilic enzyme. These interactions are likely the key mechanisms underlying the differences in rigidity of the active site. These findings provide further biophysical insights into the reversible thermal inactivation of enzymes and potential applications in future protein engineering.

Recursive regularization for inferring gene networks from time-course gene expression profiles

PubMed Central

Shimamura, Teppei; Imoto, Seiya; Yamaguchi, Rui; Fujita, André; Nagasaki, Masao; Miyano, Satoru

2009-01-01

Background Inferring gene networks from time-course microarray experiments with vector autoregressive (VAR) model is the process of identifying functional associations between genes through multivariate time series. This problem can be cast as a variable selection problem in Statistics. One of the promising methods for variable selection is the elastic net proposed by Zou and Hastie (2005). However, VAR modeling with the elastic net succeeds in increasing the number of true positives while it also results in increasing the number of false positives. Results By incorporating relative importance of the VAR coefficients into the elastic net, we propose a new class of regularization, called recursive elastic net, to increase the capability of the elastic net and estimate gene networks based on the VAR model. The recursive elastic net can reduce the number of false positives gradually by updating the importance. Numerical simulations and comparisons demonstrate that the proposed method succeeds in reducing the number of false positives drastically while keeping the high number of true positives in the network inference and achieves two or more times higher true discovery rate (the proportion of true positives among the selected edges) than the competing methods even when the number of time points is small. We also compared our method with various reverse-engineering algorithms on experimental data of MCF-7 breast cancer cells stimulated with two ErbB ligands, EGF and HRG. Conclusion The recursive elastic net is a powerful tool for inferring gene networks from time-course gene expression profiles. PMID:19386091

DNA-nanoparticle assemblies go organic: Macroscopic polymeric materials with nanosized features

PubMed Central

2012-01-01

Background One of the goals in the field of structural DNA nanotechnology is the use of DNA to build up 2- and 3-D nanostructures. The research in this field is motivated by the remarkable structural features of DNA as well as by its unique and reversible recognition properties. Nucleic acids can be used alone as the skeleton of a broad range of periodic nanopatterns and nanoobjects and in addition, DNA can serve as a linker or template to form DNA-hybrid structures with other materials. This approach can be used for the development of new detection strategies as well as nanoelectronic structures and devices. Method Here we present a new method for the generation of unprecedented all-organic conjugated-polymer nanoparticle networks guided by DNA, based on a hierarchical self-assembly process. First, microphase separation of amphiphilic block copolymers induced the formation of spherical nanoobjects. As a second ordering concept, DNA base pairing has been employed for the controlled spatial definition of the conjugated-polymer particles within the bulk material. These networks offer the flexibility and the diversity of soft polymeric materials. Thus, simple chemical methodologies could be applied in order to tune the network's electrical, optical and mechanical properties. Results and conclusions One- two- and three-dimensional networks have been successfully formed. Common to all morphologies is the integrity of the micelles consisting of DNA block copolymer (DBC), which creates an all-organic engineered network. PMID:22646980

Boosting Probabilistic Graphical Model Inference by Incorporating Prior Knowledge from Multiple Sources

PubMed Central

Praveen, Paurush; Fröhlich, Holger

2013-01-01

Inferring regulatory networks from experimental data via probabilistic graphical models is a popular framework to gain insights into biological systems. However, the inherent noise in experimental data coupled with a limited sample size reduces the performance of network reverse engineering. Prior knowledge from existing sources of biological information can address this low signal to noise problem by biasing the network inference towards biologically plausible network structures. Although integrating various sources of information is desirable, their heterogeneous nature makes this task challenging. We propose two computational methods to incorporate various information sources into a probabilistic consensus structure prior to be used in graphical model inference. Our first model, called Latent Factor Model (LFM), assumes a high degree of correlation among external information sources and reconstructs a hidden variable as a common source in a Bayesian manner. The second model, a Noisy-OR, picks up the strongest support for an interaction among information sources in a probabilistic fashion. Our extensive computational studies on KEGG signaling pathways as well as on gene expression data from breast cancer and yeast heat shock response reveal that both approaches can significantly enhance the reconstruction accuracy of Bayesian Networks compared to other competing methods as well as to the situation without any prior. Our framework allows for using diverse information sources, like pathway databases, GO terms and protein domain data, etc. and is flexible enough to integrate new sources, if available. PMID:23826291

Using a Formal Approach for Reverse Engineering and Design Recovery to Support Software Reuse

NASA Technical Reports Server (NTRS)

Gannod, Gerald C.

2002-01-01

This document describes 3rd year accomplishments and summarizes overall project accomplishments. Included as attachments are all published papers from year three. Note that the budget for this project was discontinued after year two, but that a residual budget from year two allowed minimal continuance into year three. Accomplishments include initial investigations into log-file based reverse engineering, service-based software reuse, and a source to XML generator.

Variable Cycle Intake for Reverse Core Engine

NASA Technical Reports Server (NTRS)

Chandler, Jesse M (Inventor); Staubach, Joseph B (Inventor); Suciu, Gabriel L (Inventor)

2016-01-01

A gas generator for a reverse core engine propulsion system has a variable cycle intake for the gas generator, which variable cycle intake includes a duct system. The duct system is configured for being selectively disposed in a first position and a second position, wherein free stream air is fed to the gas generator when in the first position, and fan stream air is fed to the gas generator when in the second position.

A new digitized reverse correction method for hypoid gears based on a one-dimensional probe

NASA Astrophysics Data System (ADS)

Li, Tianxing; Li, Jubo; Deng, Xiaozhong; Yang, Jianjun; Li, Genggeng; Ma, Wensuo

2017-12-01

In order to improve the tooth surface geometric accuracy and transmission quality of hypoid gears, a new digitized reverse correction method is proposed based on the measurement data from a one-dimensional probe. The minimization of tooth surface geometrical deviations is realized from the perspective of mathematical analysis and reverse engineering. Combining the analysis of complex tooth surface generation principles and the measurement mechanism of one-dimensional probes, the mathematical relationship between the theoretical designed tooth surface, the actual machined tooth surface and the deviation tooth surface is established, the mapping relation between machine-tool settings and tooth surface deviations is derived, and the essential connection between the accurate calculation of tooth surface deviations and the reverse correction method of machine-tool settings is revealed. Furthermore, a reverse correction model of machine-tool settings is built, a reverse correction strategy is planned, and the minimization of tooth surface deviations is achieved by means of the method of numerical iterative reverse solution. On this basis, a digitized reverse correction system for hypoid gears is developed by the organic combination of numerical control generation, accurate measurement, computer numerical processing, and digitized correction. Finally, the correctness and practicability of the digitized reverse correction method are proved through a reverse correction experiment. The experimental results show that the tooth surface geometric deviations meet the engineering requirements after two trial cuts and one correction.

De novo reconstruction of gene regulatory networks from time series data, an approach based on formal methods.

PubMed

Ceccarelli, Michele; Cerulo, Luigi; Santone, Antonella

2014-10-01

Reverse engineering of gene regulatory relationships from genomics data is a crucial task to dissect the complex underlying regulatory mechanism occurring in a cell. From a computational point of view the reconstruction of gene regulatory networks is an undetermined problem as the large number of possible solutions is typically high in contrast to the number of available independent data points. Many possible solutions can fit the available data, explaining the data equally well, but only one of them can be the biologically true solution. Several strategies have been proposed in literature to reduce the search space and/or extend the amount of independent information. In this paper we propose a novel algorithm based on formal methods, mathematically rigorous techniques widely adopted in engineering to specify and verify complex software and hardware systems. Starting with a formal specification of gene regulatory hypotheses we are able to mathematically prove whether a time course experiment belongs or not to the formal specification, determining in fact whether a gene regulation exists or not. The method is able to detect both direction and sign (inhibition/activation) of regulations whereas most of literature methods are limited to undirected and/or unsigned relationships. We empirically evaluated the approach on experimental and synthetic datasets in terms of precision and recall. In most cases we observed high levels of accuracy outperforming the current state of art, despite the computational cost increases exponentially with the size of the network. We made available the tool implementing the algorithm at the following url: http://www.bioinformatics.unisannio.it. Copyright © 2014 Elsevier Inc. All rights reserved.

Predictive minimum description length principle approach to inferring gene regulatory networks.

PubMed

Chaitankar, Vijender; Zhang, Chaoyang; Ghosh, Preetam; Gong, Ping; Perkins, Edward J; Deng, Youping

2011-01-01

Reverse engineering of gene regulatory networks using information theory models has received much attention due to its simplicity, low computational cost, and capability of inferring large networks. One of the major problems with information theory models is to determine the threshold that defines the regulatory relationships between genes. The minimum description length (MDL) principle has been implemented to overcome this problem. The description length of the MDL principle is the sum of model length and data encoding length. A user-specified fine tuning parameter is used as control mechanism between model and data encoding, but it is difficult to find the optimal parameter. In this work, we propose a new inference algorithm that incorporates mutual information (MI), conditional mutual information (CMI), and predictive minimum description length (PMDL) principle to infer gene regulatory networks from DNA microarray data. In this algorithm, the information theoretic quantities MI and CMI determine the regulatory relationships between genes and the PMDL principle method attempts to determine the best MI threshold without the need of a user-specified fine tuning parameter. The performance of the proposed algorithm is evaluated using both synthetic time series data sets and a biological time series data set (Saccharomyces cerevisiae). The results show that the proposed algorithm produced fewer false edges and significantly improved the precision when compared to existing MDL algorithm.

Hydrophobic-Interaction-Induced Stiffening of α -Synuclein Fibril Networks

NASA Astrophysics Data System (ADS)

Semerdzhiev, Slav A.; Lindhoud, Saskia; Stefanovic, Anja; Subramaniam, Vinod; van der Schoot, Paul; Claessens, Mireille M. A. E.

2018-05-01

In water, networks of semiflexible fibrils of the protein α -synuclein stiffen significantly with increasing temperature. We make plausible that this reversible stiffening is a result of hydrophobic contacts between the fibrils that become more prominent with increasing temperature. The good agreement of our experimentally observed temperature dependence of the storage modulus of the network with a scaling theory linking network elasticity with reversible cross-linking enables us to quantify the endothermic binding enthalpy and estimate the effective size of hydrophobic patches on the fibril surface. Our findings may not only shed light on the role of amyloid deposits in disease conditions, but can also inspire new approaches for the design of thermoresponsive materials.

Hydrophobic-Interaction-Induced Stiffening of α-Synuclein Fibril Networks.

PubMed

Semerdzhiev, Slav A; Lindhoud, Saskia; Stefanovic, Anja; Subramaniam, Vinod; van der Schoot, Paul; Claessens, Mireille M A E

2018-05-18

In water, networks of semiflexible fibrils of the protein α-synuclein stiffen significantly with increasing temperature. We make plausible that this reversible stiffening is a result of hydrophobic contacts between the fibrils that become more prominent with increasing temperature. The good agreement of our experimentally observed temperature dependence of the storage modulus of the network with a scaling theory linking network elasticity with reversible cross-linking enables us to quantify the endothermic binding enthalpy and estimate the effective size of hydrophobic patches on the fibril surface. Our findings may not only shed light on the role of amyloid deposits in disease conditions, but can also inspire new approaches for the design of thermoresponsive materials.

Techniques utilized in the simulated altitude testing of a 2D-CD vectoring and reversing nozzle

NASA Technical Reports Server (NTRS)

Block, H. Bruce; Bryant, Lively; Dicus, John H.; Moore, Allan S.; Burns, Maureen E.; Solomon, Robert F.; Sheer, Irving

1988-01-01

Simulated altitude testing of a two-dimensional, convergent-divergent, thrust vectoring and reversing exhaust nozzle was accomplished. An important objective of this test was to develop test hardware and techniques to properly operate a vectoring and reversing nozzle within the confines of an altitude test facility. This report presents detailed information on the major test support systems utilized, the operational performance of the systems and the problems encountered, and test equipment improvements recommended for future tests. The most challenging support systems included the multi-axis thrust measurement system, vectored and reverse exhaust gas collection systems, and infrared temperature measurement systems used to evaluate and monitor the nozzle. The feasibility of testing a vectoring and reversing nozzle of this type in an altitude chamber was successfully demonstrated. Supporting systems performed as required. During reverser operation, engine exhaust gases were successfully captured and turned downstream. However, a small amount of exhaust gas spilled out the collector ducts' inlet openings when the reverser was opened more than 60 percent. The spillage did not affect engine or nozzle performance. The three infrared systems which viewed the nozzle through the exhaust collection system worked remarkably well considering the harsh environment.

77 FR 40026 - 36(b)(1) Arms Sales Notification

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-06

... and contractor logistics, Quality Assurance Team support services, engineering and technical support..., engineering and technical support, and other related elements of program support. The estimated cost is $49..., maintenance, or training is Confidential. Reverse engineering could reveal Confidential information...

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment.

PubMed

Lee, Wei-Po; Hsiao, Yu-Ting; Hwang, Wei-Che

2014-01-16

To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks.

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment

PubMed Central

2014-01-01

Background To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. Results This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Conclusions Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks. PMID:24428926

CONDENSED MATTER: ELECTRONIC STRUCTURE, ELECTRICAL, MAGNETIC, AND OPTICAL PROPERTIES: Research on reverse recovery characteristics of SiGeC p-i-n diodes

NASA Astrophysics Data System (ADS)

Gao, Yong; Liu, Jing; Yang, Yuan

2008-12-01

This paper analyses the reverse recovery characteristics and mechanism of SiGeC p-i-n diodes. Based on the integrated systems engineering (ISE) data, the critical physical models of SiGeC diodes are proposed. Based on hetero-junction band gap engineering, the softness factor increases over six times, reverse recovery time is over 30% short and there is a 20% decrease in peak reverse recovery current for SiGeC diodes with 20% of germanium and 0.5% of carbon, compared to Si diodes. Those advantages of SiGeC p-i-n diodes are more obvious at high temperature. Compared to lifetime control, SiGeC technique is more suitable for improving diode properties and the tradeoff between reverse recovery time and forward voltage drop can be easily achieved in SiGeC diodes. Furthermore, the high thermal-stability of SiGeC diodes reduces the costs of further process steps and offers more freedoms to device design.

A novel technique for presurgical nasoalveolar molding using computer-aided reverse engineering and rapid prototyping.

PubMed

Yu, Quan; Gong, Xin; Wang, Guo-Min; Yu, Zhe-Yuan; Qian, Yu-Fen; Shen, Gang

2011-01-01

To establish a new method of presurgical nasoalveolar molding (NAM) using computer-aided reverse engineering and rapid prototyping technique in infants with unilateral cleft lip and palate (UCLP). Five infants (2 males and 3 females with mean age of 1.2 w) with complete UCLP were recruited. All patients were subjected to NAM before the cleft lip repair. The upper denture casts were recorded using a three-dimensional laser scanner within 2 weeks after birth in UCLP infants. A digital model was constructed and analyzed to simulate the NAM procedure with reverse engineering software. The digital geometrical data were exported to print the solid model with rapid prototyping system. The whole set of appliances was fabricated based on these solid models. Laser scanning and digital model construction simplified the NAM procedure and estimated the treatment objective. The appliances were fabricated based on the rapid prototyping technique, and for each patient, the complete set of appliances could be obtained at one time. By the end of presurgical NAM treatment, the cleft was narrowed, and the malformation of nasoalveolar segments was aligned normally. We have developed a novel technique of presurgical NAM based on a computer-aided design. The accurate digital denture model of UCLP infants could be obtained with laser scanning. The treatment design and appliance fabrication could be simplified with a computer-aided reverse engineering and rapid prototyping technique.

A Multi-Stage Reverse Logistics Network Problem by Using Hybrid Priority-Based Genetic Algorithm

NASA Astrophysics Data System (ADS)

Lee, Jeong-Eun; Gen, Mitsuo; Rhee, Kyong-Gu

Today remanufacturing problem is one of the most important problems regarding to the environmental aspects of the recovery of used products and materials. Therefore, the reverse logistics is gaining become power and great potential for winning consumers in a more competitive context in the future. This paper considers the multi-stage reverse Logistics Network Problem (m-rLNP) while minimizing the total cost, which involves reverse logistics shipping cost and fixed cost of opening the disassembly centers and processing centers. In this study, we first formulate the m-rLNP model as a three-stage logistics network model. Following for solving this problem, we propose a Genetic Algorithm pri (GA) with priority-based encoding method consisting of two stages, and introduce a new crossover operator called Weight Mapping Crossover (WMX). Additionally also a heuristic approach is applied in the 3rd stage to ship of materials from processing center to manufacturer. Finally numerical experiments with various scales of the m-rLNP models demonstrate the effectiveness and efficiency of our approach by comparing with the recent researches.

A group LASSO-based method for robustly inferring gene regulatory networks from multiple time-course datasets.

PubMed

Liu, Li-Zhi; Wu, Fang-Xiang; Zhang, Wen-Jun

2014-01-01

As an abstract mapping of the gene regulations in the cell, gene regulatory network is important to both biological research study and practical applications. The reverse engineering of gene regulatory networks from microarray gene expression data is a challenging research problem in systems biology. With the development of biological technologies, multiple time-course gene expression datasets might be collected for a specific gene network under different circumstances. The inference of a gene regulatory network can be improved by integrating these multiple datasets. It is also known that gene expression data may be contaminated with large errors or outliers, which may affect the inference results. A novel method, Huber group LASSO, is proposed to infer the same underlying network topology from multiple time-course gene expression datasets as well as to take the robustness to large error or outliers into account. To solve the optimization problem involved in the proposed method, an efficient algorithm which combines the ideas of auxiliary function minimization and block descent is developed. A stability selection method is adapted to our method to find a network topology consisting of edges with scores. The proposed method is applied to both simulation datasets and real experimental datasets. It shows that Huber group LASSO outperforms the group LASSO in terms of both areas under receiver operating characteristic curves and areas under the precision-recall curves. The convergence analysis of the algorithm theoretically shows that the sequence generated from the algorithm converges to the optimal solution of the problem. The simulation and real data examples demonstrate the effectiveness of the Huber group LASSO in integrating multiple time-course gene expression datasets and improving the resistance to large errors or outliers.

Reversing the Trend of Engineering Enrollment Declines with Innovative Outreach, Recruiting, and Retention Programs

ERIC Educational Resources Information Center

Davis, C. E.; Yeary, M. B.; Sluss, J. J., Jr.

2012-01-01

This paper discusses an all-encompassing approach to increase the number of students in engineering through innovative outreach, recruiting, and retention programs. Prior to adopting these programs, the School of Electrical and Computer Engineering (ECE) at the University of Oklahoma (OU), Norman, experienced a reduction in engineering enrollment…

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.

Combining phage display with de novo protein sequencing for reverse engineering of monoclonal antibodies.

PubMed

Rickert, Keith W; Grinberg, Luba; Woods, Robert M; Wilson, Susan; Bowen, Michael A; Baca, Manuel

2016-01-01

The enormous diversity created by gene recombination and somatic hypermutation makes de novo protein sequencing of monoclonal antibodies a uniquely challenging problem. Modern mass spectrometry-based sequencing will rarely, if ever, provide a single unambiguous sequence for the variable domains. A more likely outcome is computation of an ensemble of highly similar sequences that can satisfy the experimental data. This outcome can result in the need for empirical testing of many candidate sequences, sometimes iteratively, to identity one which can replicate the activity of the parental antibody. Here we describe an improved approach to antibody protein sequencing by using phage display technology to generate a combinatorial library of sequences that satisfy the mass spectrometry data, and selecting for functional candidates that bind antigen. This approach was used to reverse engineer 2 commercially-obtained monoclonal antibodies against murine CD137. Proteomic data enabled us to assign the majority of the variable domain sequences, with the exception of 3-5% of the sequence located within or adjacent to complementarity-determining regions. To efficiently resolve the sequence in these regions, small phage-displayed libraries were generated and subjected to antigen binding selection. Following enrichment of antigen-binding clones, 2 clones were selected for each antibody and recombinantly expressed as antigen-binding fragments (Fabs). In both cases, the reverse-engineered Fabs exhibited identical antigen binding affinity, within error, as Fabs produced from the commercial IgGs. This combination of proteomic and protein engineering techniques provides a useful approach to simplifying the technically challenging process of reverse engineering monoclonal antibodies from protein material.

Combining phage display with de novo protein sequencing for reverse engineering of monoclonal antibodies

PubMed Central

Rickert, Keith W.; Grinberg, Luba; Woods, Robert M.; Wilson, Susan; Bowen, Michael A.; Baca, Manuel

2016-01-01

ABSTRACT The enormous diversity created by gene recombination and somatic hypermutation makes de novo protein sequencing of monoclonal antibodies a uniquely challenging problem. Modern mass spectrometry-based sequencing will rarely, if ever, provide a single unambiguous sequence for the variable domains. A more likely outcome is computation of an ensemble of highly similar sequences that can satisfy the experimental data. This outcome can result in the need for empirical testing of many candidate sequences, sometimes iteratively, to identity one which can replicate the activity of the parental antibody. Here we describe an improved approach to antibody protein sequencing by using phage display technology to generate a combinatorial library of sequences that satisfy the mass spectrometry data, and selecting for functional candidates that bind antigen. This approach was used to reverse engineer 2 commercially-obtained monoclonal antibodies against murine CD137. Proteomic data enabled us to assign the majority of the variable domain sequences, with the exception of 3–5% of the sequence located within or adjacent to complementarity-determining regions. To efficiently resolve the sequence in these regions, small phage-displayed libraries were generated and subjected to antigen binding selection. Following enrichment of antigen-binding clones, 2 clones were selected for each antibody and recombinantly expressed as antigen-binding fragments (Fabs). In both cases, the reverse-engineered Fabs exhibited identical antigen binding affinity, within error, as Fabs produced from the commercial IgGs. This combination of proteomic and protein engineering techniques provides a useful approach to simplifying the technically challenging process of reverse engineering monoclonal antibodies from protein material. PMID:26852694

Alzheimer's as a Systems-Level Disease Involving the Interplay of Multiple Cellular Networks.

PubMed

Castrillo, Juan I; Oliver, Stephen G

2016-01-01

Alzheimer's disease (AD), and many neurodegenerative disorders, are multifactorial in nature. They involve a combination of genomic, epigenomic, interactomic and environmental factors. Progress is being made, and these complex diseases are beginning to be understood as having their origin in altered states of biological networks at the cellular level. In the case of AD, genomic susceptibility and mechanisms leading to (or accompanying) the impairment of the central Amyloid Precursor Protein (APP) processing and tau networks are widely accepted as major contributors to the diseased state. The derangement of these networks may result in both the gain and loss of functions, increased generation of toxic species (e.g., toxic soluble oligomers and aggregates) and imbalances, whose effects can propagate to supra-cellular levels. Although well sustained by empirical data and widely accepted, this global perspective often overlooks the essential roles played by the main counteracting homeostatic networks (e.g., protein quality control/proteostasis, unfolded protein response, protein folding chaperone networks, disaggregases, ER-associated degradation/ubiquitin proteasome system, endolysosomal network, autophagy, and other stress-protective and clearance networks), whose relevance to AD is just beginning to be fully realized. In this chapter, an integrative perspective is presented. Alzheimer's disease is characterized to be a result of: (a) intrinsic genomic/epigenomic susceptibility and, (b) a continued dynamic interplay between the deranged networks and the central homeostatic networks of nerve cells. This interplay of networks will underlie both the onset and rate of progression of the disease in each individual. Integrative Systems Biology approaches are required to effect its elucidation. Comprehensive Systems Biology experiments at different 'omics levels in simple model organisms, engineered to recapitulate the basic features of AD may illuminate the onset and sequence of events underlying AD. Indeed, studies of models of AD in simple organisms, differentiated cells in culture and rodents are beginning to offer hope that the onset and progression of AD, if detected at an early stage, may be stopped, delayed, or even reversed, by activating or modulating networks involved in proteostasis and the clearance of toxic species. In practice, the incorporation of next-generation neuroimaging, high-throughput and computational approaches are opening the way towards early diagnosis well before irreversible cell death. Thus, the presence or co-occurrence of: (a) accumulation of toxic Aβ oligomers and tau species; (b) altered splicing and transcriptome patterns; (c) impaired redox, proteostatic, and metabolic networks together with, (d) compromised homeostatic capacities may constitute relevant 'AD hallmarks at the cellular level' towards reliable and early diagnosis. From here, preventive lifestyle changes and tailored therapies may be investigated, such as combined strategies aimed at both lowering the production of toxic species and potentiating homeostatic responses, in order to prevent or delay the onset, and arrest, alleviate, or even reverse the progression of the disease.

Static internal performance of a single-engine onaxisymmetric-nozzle vaned-thrust-reverser design with thrust modulation capabilities

NASA Technical Reports Server (NTRS)

Leavitt, L. D.; Burley, J. R., II

1985-01-01

An investigation has been conducted at wind-off conditions in the stati-test facility of the Langley 16-Foot Transonic Tunnel. The tests were conducted on a single-engine reverser configuration with partial and full reverse-thrust modulation capabilities. The reverser design had four ports with equal areas. These ports were angled outboard 30 deg from the vertical impart of a splay angle to the reverse exhaust flow. This splaying of reverser flow was intended to prevent impingement of exhaust flow on empennage surfaces and to help avoid inlet reingestion of exhaust gas when the reverser is integrated into an actual airplane configuration. External vane boxes were located directly over each of the four ports to provide variation of reverser efflux angle from 140 deg to 26 deg (measured forward from the horizontal reference axis). The reverser model was tested with both a butterfly-type inner door and an internal slider door to provide area control for each individual port. In addition, main nozzle throat area and vector angle were varied to examine various methods of modulating thrust levels. Other model variables included vane box configuration (four or six vanes per box), orientation of external vane boxes with respect to internal port walls (splay angle shims), and vane box sideplates. Nozzle pressure ratio was varied from 2.0 approximately 7.0.

"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.

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.

Morphing dynamics in light-triggered LC polymers (Conference Presentation)

NASA Astrophysics Data System (ADS)

Broer, Dirk J.

2017-02-01

Polymers that can change shape or surface topography in response to a trigger have a wide application potential varying from micro-robotics to avionics. Preferably this morphing proceeds fast and reversibly. We developed new morphing principles based on in-situ photopolymerized liquid crystal networks and on hybrid low molecular weight liquid crystals and liquid crystal networks. Commonly the triggers are temperature, light, pH or the presence of chemicals or other moisture. In the lecture we will focus on UV actuation and demonstrate that by accurate positioning of molecules over all three dimensions of a thin film or coating, the deformation figures can be pre-engineered. They can vary from simple gratings to very complex such as fingerprints that can be switched between off (flat surface) and on (corrugated surface) by light. The underlying principles are based on photo-induced changes in the degree of order of liquid crystal polymer networks and the accompanying changes in density by the formation of free volume. The surfaces can be switched with frequencies of the order of 0.1 Hz. In the lecture we will discuss several methods to fabricate the responsive layers as well as some of the most eye-catching properties. Also the mechanism of free volume generation will be addressed in terms of molecular dynamics and resonance.

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.

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

Quantifying fluctuations in reversible enzymatic cycles and clocks

NASA Astrophysics Data System (ADS)

Wierenga, Harmen; ten Wolde, Pieter Rein; Becker, Nils B.

2018-04-01

Biochemical reactions are fundamentally noisy at a molecular scale. This limits the precision of reaction networks, but it also allows fluctuation measurements that may reveal the structure and dynamics of the underlying biochemical network. Here, we study nonequilibrium reaction cycles, such as the mechanochemical cycle of molecular motors, the phosphorylation cycle of circadian clock proteins, or the transition state cycle of enzymes. Fluctuations in such cycles may be measured using either of two classical definitions of the randomness parameter, which we show to be equivalent in general microscopically reversible cycles. We define a stochastic period for reversible cycles and present analytical solutions for its moments. Furthermore, we associate the two forms of the randomness parameter with the thermodynamic uncertainty relation, which sets limits on the timing precision of the cycle in terms of thermodynamic quantities. Our results should prove useful also for the study of temporal fluctuations in more general networks.

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.

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.

L1000CDS2: LINCS L1000 characteristic direction signatures search engine

PubMed Central

Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma’ayan, Avi

2016-01-01

The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS2. The L1000CDS2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS2, we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource. PMID:28413689

Ionic Modification Turns Commercial Rubber into a Self-Healing Material.

PubMed

Das, Amit; Sallat, Aladdin; Böhme, Frank; Suckow, Marcus; Basu, Debdipta; Wiessner, Sven; Stöckelhuber, Klaus Werner; Voit, Brigitte; Heinrich, Gert

2015-09-23

Invented by Charles Goodyear, chemical cross-linking of rubbers by sulfur vulcanization is the only method by which modern automobile tires are manufactured. The formation of these cross-linked network structures leads to highly elastic properties, which substantially reduces the viscous properties of these materials. Here, we describe a simple approach to converting commercially available and widely used bromobutyl rubber (BIIR) into a highly elastic material with extraordinary self-healing properties without using conventional cross-linking or vulcanising agents. Transformation of the bromine functionalities of BIIR into ionic imidazolium bromide groups results in the formation of reversible ionic associates that exhibit physical cross-linking ability. The reversibility of the ionic association facilitates the healing processes by temperature- or stress-induced rearrangements, thereby enabling a fully cut sample to retain its original properties after application of the self-healing process. Other mechanical properties, such as the elastic modulus, tensile strength, ductility, and hysteresis loss, were found to be superior to those of conventionally sulfur-cured BIIR. This simple and easy approach to preparing a commercial rubber with self-healing properties offers unique development opportunities in the field of highly engineered materials, such as tires, for which safety, performance, and longer fatigue life are crucial factors.

A synthetic biology approach to engineer a functional reversal of the β-oxidation cycle.

PubMed

Clomburg, James M; Vick, Jacob E; Blankschien, Matthew D; Rodríguez-Moyá, María; Gonzalez, Ramon

2012-11-16

While we have recently constructed a functional reversal of the β-oxidation cycle as a platform for the production of fuels and chemicals by engineering global regulators and eliminating native fermentative pathways, the system-level approach used makes it difficult to determine which of the many deregulated enzymes are responsible for product synthesis. This, in turn, limits efforts to fine-tune the synthesis of specific products and prevents the transfer of the engineered pathway to other organisms. In the work reported here, we overcome the aforementioned limitations by using a synthetic biology approach to construct and functionally characterize a reversal of the β-oxidation cycle. This was achieved through the in vitro kinetic characterization of each functional unit of the core and termination pathways, followed by their in vivo assembly and functional characterization. With this approach, the four functional units of the core pathway, thiolase, 3-hydroxyacyl-CoA dehydrogenase, enoyl-CoA hydratase/3-hydroxyacyl-CoA dehydratase, and acyl-CoA dehydrogenase/trans-enoyl-CoA reductase, were purified and kinetically characterized in vitro. When these four functional units were assembled in vivo in combination with thioesterases as the termination pathway, the synthesis of a variety of 4-C carboxylic acids from a one-turn functional reversal of the β-oxidation cycle was realized. The individual expression and modular construction of these well-defined core components exerted the majority of control over product formation, with only highly selective termination pathways resulting in shifts in product formation. Further control over product synthesis was demonstrated by overexpressing a long-chain thiolase that enables the operation of multiple turns of the reversal of the β-oxidation cycle and hence the synthesis of longer-chain carboxylic acids. The well-defined and self-contained nature of each functional unit makes the engineered reversal of the β-oxidation cycle "chassis neutral" and hence transferrable to the host of choice for efficient fuel or chemical production.

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

Stem Cells and Scaffolds for Vascularizing Engineered Tissue Constructs

NASA Astrophysics Data System (ADS)

Luong, E.; Gerecht, S.

The clinical impact of tissue engineering depends upon our ability to direct cells to form tissues with characteristic structural and mechanical properties from the molecular level up to organized tissue. Induction and creation of functional vascular networks has been one of the main goals of tissue engineering either in vitro, for the transplantation of prevascularized constructs, or in vivo, for cellular organization within the implantation site. In most cases, tissue engineering attempts to recapitulate certain aspects of normal development in order to stimulate cell differentiation and functional tissue assembly. The induction of tissue growth generally involves the use of biodegradable and bioactive materials designed, ideally, to provide a mechanical, physical, and biochemical template for tissue regeneration. Human embryonic stem cells (hESCs), derived from the inner cell mass of a developing blastocyst, are capable of differentiating into all cell types of the body. Specifically, hESCs have the capability to differentiate and form blood vessels de novo in a process called vasculogenesis. Human ESC-derived endothelial progenitor cells (EPCs) and endothelial cells have substantial potential for microvessel formation, in vitro and in vivo. Human adult EPCs are being isolated to understand the fundamental biology of how these cells are regulated as a population and to explore whether these cells can be differentiated and reimplanted as a cellular therapy in order to arrest or even reverse damaged vasculature. This chapter focuses on advances made toward the generation and engineering of functional vascular tissue, focusing on both the scaffolds - the synthetic and biopolymer materials - and the cell sources - hESCs and hEPCs.

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

Quiet Clean Short-Haul Experimental Engine (QCSEE) Over-The-Wing (OTW) propulsion system test report. Volume 2: Aerodynamics and performance. [engine performance tests to define propulsion system performance on turbofan engines

NASA Technical Reports Server (NTRS)

1978-01-01

The design and testing of the over the wing engine, a high bypass, geared turbofan engine, are discussed. The propulsion system performance is examined for uninstalled performance and installed performance. The fan aerodynamic performance and the D nozzle and reverser thrust performance are evaluated.

The Science of Solubility: Using Reverse Engineering to Brew a Perfect Cup of Coffee

ERIC Educational Resources Information Center

West, Andrew B.; Sickel, Aaron J.; Cribbs, Jennifer D.

2015-01-01

The Next Generation Science Standards call for the integration of science and engineering. Often, the introduction of engineering activities occurs after instruction in the science content. That is, engineering is used as a way for students to elaborate on science ideas that have already been explored. However, using only this sequence of…

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)

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.

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.

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

Switching "on" and "off" the adhesion in stimuli-responsive elastomers.

PubMed

Kaiser, S; Radl, S V; Manhart, J; Ayalur-Karunakaran, S; Griesser, T; Moser, A; Ganser, C; Teichert, C; Kern, W; Schlögl, S

2018-03-28

The present work aims at the preparation of dry adhesives with switchable bonding properties by using the reversible nature of the [4πs+4πs] cycloaddition of anthracenes. Photo-responsive hydrogenated carboxylated nitrile butadiene rubber with photo-responsive pendant anthracene groups is prepared by one-pot synthesis. The formation of 3D networks relies on the photodimerization of the anthracene moieties upon UV exposure (λ > 300 nm). Controlled cleavage of the crosslink sites is achieved by either deep UV exposure (λ = 254 nm) or thermal dissociation at 70 °C. The kinetics of the optical and thermal cleavage routes are compared in thin films using UV-vis spectroscopy and their influence on the reversibility of the network is detailed. Going from thin films to free standing samples the modulation of the network structure and thermo-mechanical properties over repeated crosslinking and cleavage cycles are characterized by low-field NMR spectroscopy and dynamic mechanical analysis. The applicability of the stimuli-responsive networks as adhesives with reversible bonding properties is demonstrated. The results evidence that the reversibility of the crosslinking reaction enables a controlled switching "on" and "off" of adhesion properties. The recovery of the adhesion force amounts to 75 and 80% for photo- and thermal dissociation, respectively. Spatial control of adhesion properties is evidenced by adhesion force mapping experiments of photo-patterned films.

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.

Mitigation of reversible self-association and viscosity in a human IgG1 monoclonal antibody by rational, structure-guided Fv engineering

PubMed Central

Geoghegan, James C.; Fleming, Ryan; Damschroder, Melissa; Bishop, Steven M.; Sathish, Hasige A.; Esfandiary, Reza

2016-01-01

ABSTRACT Undesired solution behaviors such as reversible self-association (RSA), high viscosity, and liquid-liquid phase separation can introduce substantial challenges during development of monoclonal antibody formulations. Although a global mechanistic understanding of RSA (i.e., native and reversible protein-protein interactions) is sufficient to develop robust formulation controls, its mitigation via protein engineering requires knowledge of the sites of protein-protein interactions. In the study reported here, we coupled our previous hydrogen-deuterium exchange mass spectrometry findings with structural modeling and in vitro screening to identify the residues responsible for RSA of a model IgG1 monoclonal antibody (mAb-C), and rationally engineered variants with improved solution properties (i.e., reduced RSA and viscosity). Our data show that mutation of either solvent-exposed aromatic residues within the heavy and light chain variable regions or buried residues within the heavy chain/light chain interface can significantly mitigate RSA and viscosity by reducing the IgG's surface hydrophobicity. The engineering strategy described here highlights the utility of integrating complementary experimental and in silico methods to identify mutations that can improve developability, in particular, high concentration solution properties, of candidate therapeutic antibodies. PMID:27050875

Network modeling for reverse flows of end-of-life vehicles.

PubMed

Ene, Seval; Öztürk, Nursel

2015-04-01

Product recovery operations are of critical importance for the automotive industry in complying with environmental regulations concerning end-of-life products management. Manufacturers must take responsibility for their products over the entire life cycle. In this context, there is a need for network design methods for effectively managing recovery operations and waste. The purpose of this study is to develop a mathematical programming model for managing reverse flows in end-of-life vehicles' recovery network. A reverse flow is the collection of used products from consumers and the transportation of these products for the purpose of recycling, reuse or disposal. The proposed model includes all operations in a product recovery and waste management network for used vehicles and reuse for vehicle parts such as collection, disassembly, refurbishing, processing (shredding), recycling, disposal and reuse of vehicle parts. The scope of the network model is to determine the numbers and locations of facilities in the network and the material flows between these facilities. The results show the performance of the model and its applicability for use in the planning of recovery operations in the automotive industry. The main objective of recovery and waste management is to maximize revenue and minimize pollution in end-of-life product operations. This study shows that with an accurate model, these activities may provide economic benefits and incentives in addition to protecting the environment. Copyright © 2015 Elsevier Ltd. All rights reserved.

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).

Toward the automated generation of genome-scale metabolic networks in the SEED.

PubMed

DeJongh, Matthew; Formsma, Kevin; Boillot, Paul; Gould, John; Rycenga, Matthew; Best, Aaron

2007-04-26

Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis). We have implemented our tools and database within the SEED, an open-source software environment for comparative genome annotation and analysis. Our method sets the stage for the automated generation of substantially complete metabolic networks for over 400 complete genome sequences currently in the SEED. With each genome that is processed using our tools, the database of common components grows to cover more of the diversity of metabolic pathways. This increases the likelihood that components of reaction networks for subsequently processed genomes can be retrieved from the database, rather than assembled and verified manually.

An algebra-based method for inferring gene regulatory networks.

PubMed

Vera-Licona, Paola; Jarrah, Abdul; Garcia-Puente, Luis David; McGee, John; Laubenbacher, Reinhard

2014-03-26

The inference of gene regulatory networks (GRNs) from experimental observations is at the heart of systems biology. This includes the inference of both the network topology and its dynamics. While there are many algorithms available to infer the network topology from experimental data, less emphasis has been placed on methods that infer network dynamics. Furthermore, since the network inference problem is typically underdetermined, it is essential to have the option of incorporating into the inference process, prior knowledge about the network, along with an effective description of the search space of dynamic models. Finally, it is also important to have an understanding of how a given inference method is affected by experimental and other noise in the data used. This paper contains a novel inference algorithm using the algebraic framework of Boolean polynomial dynamical systems (BPDS), meeting all these requirements. The algorithm takes as input time series data, including those from network perturbations, such as knock-out mutant strains and RNAi experiments. It allows for the incorporation of prior biological knowledge while being robust to significant levels of noise in the data used for inference. It uses an evolutionary algorithm for local optimization with an encoding of the mathematical models as BPDS. The BPDS framework allows an effective representation of the search space for algebraic dynamic models that improves computational performance. The algorithm is validated with both simulated and experimental microarray expression profile data. Robustness to noise is tested using a published mathematical model of the segment polarity gene network in Drosophila melanogaster. Benchmarking of the algorithm is done by comparison with a spectrum of state-of-the-art network inference methods on data from the synthetic IRMA network to demonstrate that our method has good precision and recall for the network reconstruction task, while also predicting several of the dynamic patterns present in the network. Boolean polynomial dynamical systems provide a powerful modeling framework for the reverse engineering of gene regulatory networks, that enables a rich mathematical structure on the model search space. A C++ implementation of the method, distributed under LPGL license, is available, together with the source code, at http://www.paola-vera-licona.net/Software/EARevEng/REACT.html.

Project-Based Teaching-Learning Computer-Aided Engineering Tools

ERIC Educational Resources Information Center

Simoes, J. A.; Relvas, C.; Moreira, R.

2004-01-01

Computer-aided design, computer-aided manufacturing, computer-aided analysis, reverse engineering and rapid prototyping are tools that play an important key role within product design. These are areas of technical knowledge that must be part of engineering and industrial design courses' curricula. This paper describes our teaching experience of…

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

In-situ study of athermal reversible photocrystallization in a chalcogenide glass

NASA Astrophysics Data System (ADS)

Benekou, Vasiliki; Strizik, Lukas; Wagner, Tomas; Yannopoulos, Spyros N.; Greer, A. Lindsay; Orava, Jiri

2017-11-01

The time-resolved Raman measurements reveal a three-stage mechanism of the photostructural changes in Ge25.0Ga9.5Sb0.5S65.0 (containing 0.5 at. % of Er3+) glass under continuous-above-bandgap illumination. These changes are reversible and effectively athermal, in that the local temperature rises to about 60% of the glass-transition temperature and the phase transitions take place in the glass/crystal and not in an equilibrium liquid. In the early stages of illumination, the glassy-network dimensionality changes from a predominantly 3-D to a mixture of 2-D/1-D represented by an increase in the fraction of edge-sharing tetrahedra and the emergence of homonuclear (semi)metallic bonds. This incubation period of the structural rearrangements, weakly thermally activated with an energy of ˜0.16 eV, facilitates a reversible photocrystallization. The photocrystallization rate in the glass is comparable to that achieved by thermal crystallization from supercooled liquid at large supercooling. Almost complete re-amorphization can be achieved in about an hour by reducing the incident laser-power density by a factor of ten. Glass-ceramic composites—with varying glass-to-crystal fraction—can be obtained by ceasing the illumination during re-amorphization. Microstructural imaging reveals photoinduced mass transport and the formation of columnar-porous structures. This shows the potential for a bond-specific engineering of glassy structures for photonic applications with a spatial resolution unachievable by thermal annealing.

Integrated forward and reverse supply chain: A tire case study.

PubMed

Pedram, Ali; Yusoff, Nukman Bin; Udoncy, Olugu Ezutah; Mahat, Abu Bakar; Pedram, Payam; Babalola, Ayo

2017-02-01

This paper attempts to integrate both a forward and reverse supply chain to design a closed-loop supply chain network (CLSC). The problem in the design of a CLSC network is uncertainty in demand, return products and the quality of return products. Scenario analyses are generated to overcome this uncertainty. In contrast to the existing supply chain network design models, a new application of a CLSC network was studied in this paper to reduce waste. A multi-product, multi-tier mixed integer linear model is developed for a CLSC network design. The main objective is to maximize profit and provide waste management decision support in order to minimize pollution. The result shows applicability of the model in the tire industry. The model determines the number and the locations of facilities and the material flows between these facilities. Copyright © 2016 Elsevier Ltd. All rights reserved.

More than Just Hot Air: How Hairdryers and Role Models Inspire Girls in Engineering

ERIC Educational Resources Information Center

Kekelis, Linda; Larkin, Molly; Gomes, Lyn

2014-01-01

This article describes a reverse-engineering project where female students take a part a hair dryer--giving them an opportunity to see the many different kinds of engineering disciplines involved in making a hairdryer and that they work together. Mechanical Engineer, Lyn Gome, describes her experience leading a group of middle school girls through…

Profile of an Effective Engineering Manager at the Naval Avionics Center

DTIC Science & Technology

1991-06-01

GROUP Leadership ; Engineering Management Effectiveness; Engineers; Engineering Managers ; Naval Avionics Center 19 ABSTR. T (Continue on reverse if...Personnel. The purpose of the Institute is to support the implementation of the NAC Leadership / Management Principles throughout NAC. The Leadership ... Management Principles are as follows: - Develc 2 and Maintain a Corporate Outlook. - Communicate the Organizational Vision through Positive Leadership

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.

Applications of Time-Reversal Processing for Planetary Surface Communications

NASA Technical Reports Server (NTRS)

Barton, Richard J.

2007-01-01

Due to the power constraints imposed on wireless sensor and communication networks deployed on a planetary surface during exploration, energy efficient transfer of data becomes a critical issue. In situations where groups of nodes within a network are located in relatively close proximity, cooperative communication techniques can be utilized to improve the range, data rate, power efficiency, and lifetime of the network. In particular, if the point-to-point communication channels on the network are well modeled as frequency non-selective, distributed or cooperative beamforming can employed. For frequency-selective channels, beamforming itself is not generally appropriate, but a natural generalization of it, time-reversal communication (TRC), can still be effective. Time-reversal processing has been proposed and studied previously for other applications, including acoustical imaging, electromagnetic imaging, underwater acoustic communication, and wireless communication channels. In this paper, we study both the theoretical advantages and the experimental performance of cooperative TRC for wireless communication on planetary surfaces. We give a brief introduction to TRC and present several scenarios where TRC could be profitably employed during planetary exploration. We also present simulation results illustrating the performance of cooperative TRC employed in a complex multipath environment and discuss the optimality of cooperative TRC for data aggregation in wireless sensor networks

Analysis of the flow field generated near an aircraft engine operating in reverse thrust. M.S. Thesis

NASA Technical Reports Server (NTRS)

Ledwith, W. A., Jr.

1972-01-01

A computer solution is developed to the exhaust gas reingestion problem for aircraft operating in the reverse thrust mode on a crosswind-free runway. The computer program determines the location of the inlet flow pattern, whether the exhaust efflux lies within the inlet flow pattern or not, and if so, the approximate time before the reversed flow reaches the engine inlet. The program is written so that the user is free to select discrete runway speeds or to study the entire aircraft deceleration process for both the far field and cross-ingestion problems. While developed with STOL applications in mind, the solution is equally applicable to conventional designs. The inlet and reversed jet flow fields involved in the problem are assumed to be noninteracting. The nacelle model used in determining the inlet flow field is generated using an iterative solution to the Neuman problem from potential flow theory while the reversed jet flow field is adapted using an empirical correlation from the literature. Sample results obtained using the program are included.

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.

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.

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.

Combustion Light Gas Gun Technology Demonstration

DTIC Science & Technology

2007-01-23

J. G. Handbook of Cryogenic Engineering. Philadelphia: Taylor and Francis, 1998. ISBN 1-56032-332-9 Myth #2 from “Twenty Hydrogen Myths” by...the second using Helium-refrigerated reverse Brayton cycle manufactured by Linde. Neither system was designed specifically for naval applications...8 Since floor space is of a premium, the helium refrigerated reverse Brayton cycle is the system of primary current interest. The reverse Brayton

GRASP/Ada: Graphical Representations of Algorithms, Structures, and Processes for Ada. The development of a program analysis environment for Ada: Reverse engineering tools for Ada, task 2, phase 3

NASA Technical Reports Server (NTRS)

Cross, James H., II

1991-01-01

The main objective is the investigation, formulation, and generation of graphical representations of algorithms, structures, and processes for Ada (GRASP/Ada). The presented task, in which various graphical representations that can be extracted or generated from source code are described and categorized, is focused on reverse engineering. The following subject areas are covered: the system model; control structure diagram generator; object oriented design diagram generator; user interface; and the GRASP library.

Effects of an in-flight thrust reverser on the stability and control characteristics of a single-engine fighter airplane model

NASA Technical Reports Server (NTRS)

Mercer, C. E.; Maiden, D. L.

1972-01-01

The changes in thrust minus drag performance as well as longitudinal and directional stability and control characteristics of a single-engine jet aircraft attributable to an in-flight thrust reverser of the blocker-deflector door type were investigated in a 16-foot transonic wind tunnel. The longitudinal and directional stability data are presented. Test conditions simulated landing approach conditions as well as high speed maneuvering such as may be required for combat or steep descent from high altitude.

Development of high temperature liquid lubricants for low-heat rejection: Heavy duty diesel engines

NASA Technical Reports Server (NTRS)

Wiczynski, P. D.; Marolewski, T. A.

1993-01-01

The objective of this DOE program was to develop a liquid lubricant that will allow advanced diesel engines to operate at top ring reversal temperatures approaching 500 C and sump temperatures approaching 250 C. The lubricants developed demonstrated at marginal increase in sump temperature capability, approximately 15 C, and an increase in top ring reversal temperature. A 15W-40 synthetic lubricant designated HTL-4 was the best lubricant developed in terms of stability, wear control, deposit control dispersancy, and particulate emissions.

[Development of computer aided forming techniques in manufacturing scaffolds for bone tissue engineering].

PubMed

Wei, Xuelei; Dong, Fuhui

2011-12-01

To review recent advance in the research and application of computer aided forming techniques for constructing bone tissue engineering scaffolds. The literature concerning computer aided forming techniques for constructing bone tissue engineering scaffolds in recent years was reviewed extensively and summarized. Several studies over last decade have focused on computer aided forming techniques for bone scaffold construction using various scaffold materials, which is based on computer aided design (CAD) and bone scaffold rapid prototyping (RP). CAD include medical CAD, STL, and reverse design. Reverse design can fully simulate normal bone tissue and could be very useful for the CAD. RP techniques include fused deposition modeling, three dimensional printing, selected laser sintering, three dimensional bioplotting, and low-temperature deposition manufacturing. These techniques provide a new way to construct bone tissue engineering scaffolds with complex internal structures. With rapid development of molding and forming techniques, computer aided forming techniques are expected to provide ideal bone tissue engineering scaffolds.

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)

Two-Photon Imaging of Cortical Surface Microvessels Reveals a Robust Redistribution in Blood Flow after Vascular Occlusion

PubMed Central

Schaffer, Chris B; Friedman, Beth; Nishimura, Nozomi; Schroeder, Lee F; Tsai, Philbert S; Ebner, Ford F; Lyden, Patrick D

2006-01-01

A highly interconnected network of arterioles overlies mammalian cortex to route blood to the cortical mantle. Here we test if this angioarchitecture can ensure that the supply of blood is redistributed after vascular occlusion. We use rodent parietal cortex as a model system and image the flow of red blood cells in individual microvessels. Changes in flow are quantified in response to photothrombotic occlusions to individual pial arterioles as well as to physical occlusions of the middle cerebral artery (MCA), the primary source of blood to this network. We observe that perfusion is rapidly reestablished at the first branch downstream from a photothrombotic occlusion through a reversal in flow in one vessel. More distal downstream arterioles also show reversals in flow. Further, occlusion of the MCA leads to reversals in flow through approximately half of the downstream but distant arterioles. Thus the cortical arteriolar network supports collateral flow that may mitigate the effects of vessel obstruction, as may occur secondary to neurovascular pathology. PMID:16379497

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.

Software engineering

NASA Technical Reports Server (NTRS)

Fridge, Ernest M., III; Hiott, Jim; Golej, Jim; Plumb, Allan

1993-01-01

Today's software systems generally use obsolete technology, are not integrated properly with other software systems, and are difficult and costly to maintain. The discipline of reverse engineering is becoming prominent as organizations try to move their systems up to more modern and maintainable technology in a cost effective manner. The Johnson Space Center (JSC) created a significant set of tools to develop and maintain FORTRAN and C code during development of the space shuttle. This tool set forms the basis for an integrated environment to reengineer existing code into modern software engineering structures which are then easier and less costly to maintain and which allow a fairly straightforward translation into other target languages. The environment will support these structures and practices even in areas where the language definition and compilers do not enforce good software engineering. The knowledge and data captured using the reverse engineering tools is passed to standard forward engineering tools to redesign or perform major upgrades to software systems in a much more cost effective manner than using older technologies. The latest release of the environment was in Feb. 1992.

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.

Hybrid algorithms for fuzzy reverse supply chain network design.

PubMed

Che, Z H; Chiang, Tzu-An; Kuo, Y C; Cui, Zhihua

2014-01-01

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. During a case study of a multi-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSO methods.

Hybrid Algorithms for Fuzzy Reverse Supply Chain Network Design

PubMed Central

Che, Z. H.; Chiang, Tzu-An; Kuo, Y. C.

2014-01-01

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. During a case study of a multi-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSO methods. PMID:24892057

Coding/decoding and reversibility of droplet trains in microfluidic networks.

PubMed

Fuerstman, Michael J; Garstecki, Piotr; Whitesides, George M

2007-02-09

Droplets of one liquid suspended in a second, immiscible liquid move through a microfluidic device in which a channel splits into two branches that reconnect downstream. The droplets choose a path based on the number of droplets that occupy each branch. The interaction among droplets in the channels results in complex sequences of path selection. The linearity of the flow through the microchannels, however, ensures that the behavior of the system can be reversed. This reversibility makes it possible to encrypt and decrypt signals coded in the intervals between droplets. The encoding/decoding device is a functional microfluidic system that requires droplets to navigate a network in a precise manner without the use of valves, switches, or other means of external control.

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

In-line stirling energy system

DOEpatents

Backhaus, Scott N [Espanola, NM; Keolian, Robert [State College, PA

2011-03-22

A high efficiency generator is provided using a Stirling engine to amplify an acoustic wave by heating the gas in the engine in a forward mode. The engine is coupled to an alternator to convert heat input to the engine into electricity. A plurality of the engines and respective alternators can be coupled to operate in a timed sequence to produce multi-phase electricity without the need for conversion. The engine system may be operated in a reverse mode as a refrigerator/heat pump.

Multidimensional adaptive evolution of a feed-forward network and the illusion of compensation

PubMed Central

Bullaughey, Kevin

2016-01-01

When multiple substitutions affect a trait in opposing ways, they are often assumed to be compensatory, not only with respect to the trait, but also with respect to fitness. This type of compensatory evolution has been suggested to underlie the evolution of protein structures and interactions, RNA secondary structures, and gene regulatory modules and networks. The possibility for compensatory evolution results from epistasis. Yet if epistasis is widespread, then it is also possible that the opposing substitutions are individually adaptive. I term this possibility an adaptive reversal. Although possible for arbitrary phenotype-fitness mappings, it has not yet been investigated whether such epistasis is prevalent in a biologically-realistic setting. I investigate a particular regulatory circuit, the type I coherent feed-forward loop, which is ubiquitous in natural systems and is accurately described by a simple mathematical model. I show that such reversals are common during adaptive evolution, can result solely from the topology of the fitness landscape, and can occur even when adaptation follows a modest environmental change and the network was well adapted to the original environment. The possibility of adaptive reversals warrants a systems perspective when interpreting substitution patterns in gene regulatory networks. PMID:23289561

Software For Graphical Representation Of A Network

NASA Technical Reports Server (NTRS)

Mcallister, R. William; Mclellan, James P.

1993-01-01

System Visualization Tool (SVT) computer program developed to provide systems engineers with means of graphically representing networks. Generates diagrams illustrating structures and states of networks defined by users. Provides systems engineers powerful tool simplifing analysis of requirements and testing and maintenance of complex software-controlled systems. Employs visual models supporting analysis of chronological sequences of requirements, simulation data, and related software functions. Applied to pneumatic, hydraulic, and propellant-distribution networks. Used to define and view arbitrary configurations of such major hardware components of system as propellant tanks, valves, propellant lines, and engines. Also graphically displays status of each component. Advantage of SVT: utilizes visual cues to represent configuration of each component within network. Written in Turbo Pascal(R), version 5.0.

Software reengineering

NASA Technical Reports Server (NTRS)

Fridge, Ernest M., III

1991-01-01

Today's software systems generally use obsolete technology, are not integrated properly with other software systems, and are difficult and costly to maintain. The discipline of reverse engineering is becoming prominent as organizations try to move their systems up to more modern and maintainable technology in a cost effective manner. JSC created a significant set of tools to develop and maintain FORTRAN and C code during development of the Space Shuttle. This tool set forms the basis for an integrated environment to re-engineer existing code into modern software engineering structures which are then easier and less costly to maintain and which allow a fairly straightforward translation into other target languages. The environment will support these structures and practices even in areas where the language definition and compilers do not enforce good software engineering. The knowledge and data captured using the reverse engineering tools is passed to standard forward engineering tools to redesign or perform major upgrades to software systems in a much more cost effective manner than using older technologies. A beta vision of the environment was released in Mar. 1991. The commercial potential for such re-engineering tools is very great. CASE TRENDS magazine reported it to be the primary concern of over four hundred of the top MIS executives.

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 47: The value of computer networks in aerospace

NASA Technical Reports Server (NTRS)

Bishop, Ann Peterson; Pinelli, Thomas E.

1995-01-01

This paper presents data on the value of computer networks that were obtained from a national survey of 2000 aerospace engineers that was conducted in 1993. Survey respondents reported the extent to which they used computer networks in their work and communication and offered their assessments of the value of various network types and applications. They also provided information about the positive impacts of networks on their work, which presents another perspective on value. Finally, aerospace engineers' recommendations on network implementation present suggestions for increasing the value of computer networks within aerospace organizations.

Reverse Engineering and Security Evaluation of Commercial Tags for RFID-Based IoT Applications.

PubMed

Fernández-Caramés, Tiago M; Fraga-Lamas, Paula; Suárez-Albela, Manuel; Castedo, Luis

2016-12-24

The Internet of Things (IoT) is a distributed system of physical objects that requires the seamless integration of hardware (e.g., sensors, actuators, electronics) and network communications in order to collect and exchange data. IoT smart objects need to be somehow identified to determine the origin of the data and to automatically detect the elements around us. One of the best positioned technologies to perform identification is RFID (Radio Frequency Identification), which in the last years has gained a lot of popularity in applications like access control, payment cards or logistics. Despite its popularity, RFID security has not been properly handled in numerous applications. To foster security in such applications, this article includes three main contributions. First, in order to establish the basics, a detailed review of the most common flaws found in RFID-based IoT systems is provided, including the latest attacks described in the literature. Second, a novel methodology that eases the detection and mitigation of such flaws is presented. Third, the latest RFID security tools are analyzed and the methodology proposed is applied through one of them (Proxmark 3) to validate it. Thus, the methodology is tested in different scenarios where tags are commonly used for identification. In such systems it was possible to clone transponders, extract information, and even emulate both tags and readers. Therefore, it is shown that the methodology proposed is useful for auditing security and reverse engineering RFID communications in IoT applications. It must be noted that, although this paper is aimed at fostering RFID communications security in IoT applications, the methodology can be applied to any RFID communications protocol.

Reverse Engineering and Security Evaluation of Commercial Tags for RFID-Based IoT Applications

PubMed Central

Fernández-Caramés, Tiago M.; Fraga-Lamas, Paula; Suárez-Albela, Manuel; Castedo, Luis

2016-01-01

The Internet of Things (IoT) is a distributed system of physical objects that requires the seamless integration of hardware (e.g., sensors, actuators, electronics) and network communications in order to collect and exchange data. IoT smart objects need to be somehow identified to determine the origin of the data and to automatically detect the elements around us. One of the best positioned technologies to perform identification is RFID (Radio Frequency Identification), which in the last years has gained a lot of popularity in applications like access control, payment cards or logistics. Despite its popularity, RFID security has not been properly handled in numerous applications. To foster security in such applications, this article includes three main contributions. First, in order to establish the basics, a detailed review of the most common flaws found in RFID-based IoT systems is provided, including the latest attacks described in the literature. Second, a novel methodology that eases the detection and mitigation of such flaws is presented. Third, the latest RFID security tools are analyzed and the methodology proposed is applied through one of them (Proxmark 3) to validate it. Thus, the methodology is tested in different scenarios where tags are commonly used for identification. In such systems it was possible to clone transponders, extract information, and even emulate both tags and readers. Therefore, it is shown that the methodology proposed is useful for auditing security and reverse engineering RFID communications in IoT applications. It must be noted that, although this paper is aimed at fostering RFID communications security in IoT applications, the methodology can be applied to any RFID communications protocol. PMID:28029119

Critical evaluation of reverse engineering tool Imagix 4D!

PubMed

Yadav, Rashmi; Patel, Ravindra; Kothari, Abhay

2016-01-01

The comprehension of legacy codes is difficult to understand. Various commercial reengineering tools are available that have unique working styles, and are equipped with their inherent capabilities and shortcomings. The focus of the available tools is in visualizing static behavior not the dynamic one. Therefore, it is difficult for people who work in software product maintenance, code understanding reengineering/reverse engineering. Consequently, the need for a comprehensive reengineering/reverse engineering tool arises. We found the usage of Imagix 4D to be good as it generates the maximum pictorial representations in the form of flow charts, flow graphs, class diagrams, metrics and, to a partial extent, dynamic visualizations. We evaluated Imagix 4D with the help of a case study involving a few samples of source code. The behavior of the tool was analyzed on multiple small codes and a large code gcc C parser. Large code evaluation was performed to uncover dead code, unstructured code, and the effect of not including required files at preprocessing level. The utility of Imagix 4D to prepare decision density and complexity metrics for a large code was found to be useful in getting to know how much reengineering is required. At the outset, Imagix 4D offered limitations in dynamic visualizations, flow chart separation (large code) and parsing loops. The outcome of evaluation will eventually help in upgrading Imagix 4D and posed a need of full featured tools in the area of software reengineering/reverse engineering. It will also help the research community, especially those who are interested in the realm of software reengineering tool building.

The Strength of the Strongest Ties in Collaborative Problem Solving

NASA Astrophysics Data System (ADS)

de Montjoye, Yves-Alexandre; Stopczynski, Arkadiusz; Shmueli, Erez; Pentland, Alex; Lehmann, Sune

2014-06-01

Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a function of both their within-team networks and their members' extended networks. We show that, while an assigned team's performance is strongly correlated with its networks of expressive and instrumental ties, only the strongest ties in both networks have an effect on performance. Both networks of strong ties explain more of the variance than other factors, such as measured or self-evaluated technical competencies, or the personalities of the team members. In fact, the inclusion of the network of strong ties renders these factors non-significant in the statistical analysis. Our results have consequences for the organization of teams of scientists, engineers, and other knowledge workers tackling today's most complex problems.

The strength of the strongest ties in collaborative problem solving.

PubMed

de Montjoye, Yves-Alexandre; Stopczynski, Arkadiusz; Shmueli, Erez; Pentland, Alex; Lehmann, Sune

2014-06-20

Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a function of both their within-team networks and their members' extended networks. We show that, while an assigned team's performance is strongly correlated with its networks of expressive and instrumental ties, only the strongest ties in both networks have an effect on performance. Both networks of strong ties explain more of the variance than other factors, such as measured or self-evaluated technical competencies, or the personalities of the team members. In fact, the inclusion of the network of strong ties renders these factors non-significant in the statistical analysis. Our results have consequences for the organization of teams of scientists, engineers, and other knowledge workers tackling today's most complex problems.

The Evaluation of Rekeying Protocols Within the Hubenko Architecture as Applied to Wireless Sensor Networks

DTIC Science & Technology

2009-03-01

SENSOR NETWORKS THESIS Presented to the Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and...hierarchical, and Secure Lock within a wireless sensor network (WSN) under the Hubenko architecture. Using a Matlab computer simulation, the impact of the...rekeying protocol should be applied given particular network parameters, such as WSN size. 10 1.3 Experimental Approach A computer simulation in

Reverse Engineering of Oxygen Transport in the Lung: Adaptation to Changing Demands and Resources through Space-Filling Networks

PubMed Central

Hou, Chen; Gheorghiu, Stefan; Huxley, Virginia H.; Pfeifer, Peter

2010-01-01

The space-filling fractal network in the human lung creates a remarkable distribution system for gas exchange. Landmark studies have illuminated how the fractal network guarantees minimum energy dissipation, slows air down with minimum hardware, maximizes the gas- exchange surface area, and creates respiratory flexibility between rest and exercise. In this paper, we investigate how the fractal architecture affects oxygen transport and exchange under varying physiological conditions, with respect to performance metrics not previously studied. We present a renormalization treatment of the diffusion-reaction equation which describes how oxygen concentrations drop in the airways as oxygen crosses the alveolar membrane system. The treatment predicts oxygen currents across the lung at different levels of exercise which agree with measured values within a few percent. The results exhibit wide-ranging adaptation to changing process parameters, including maximum oxygen uptake rate at minimum alveolar membrane permeability, the ability to rapidly switch from a low oxygen uptake rate at rest to high rates at exercise, and the ability to maintain a constant oxygen uptake rate in the event of a change in permeability or surface area. We show that alternative, less than space-filling architectures perform sub-optimally and that optimal performance of the space-filling architecture results from a competition between underexploration and overexploration of the surface by oxygen molecules. PMID:20865052

A shape-based inter-layer contours correspondence method for ICT-based reverse engineering

PubMed Central

Duan, Liming; Yang, Shangpeng; Zhang, Gui; Feng, Fei; Gu, Minghui

2017-01-01

The correspondence of a stack of planar contours in ICT (industrial computed tomography)-based reverse engineering, a key step in surface reconstruction, is difficult when the contours or topology of the object are complex. Given the regularity of industrial parts and similarity of the inter-layer contours, a specialized shape-based inter-layer contours correspondence method for ICT-based reverse engineering was presented to solve the above problem based on the vectorized contours. In this paper, the vectorized contours extracted from the slices consist of three graphical primitives: circles, arcs and segments. First, the correspondence of the inter-layer primitives is conducted based on the characteristics of the primitives. Second, based on the corresponded primitives, the inter-layer contours correspond with each other using the proximity rules and exhaustive search. The proposed method can make full use of the shape information to handle industrial parts with complex structures. The feasibility and superiority of this method have been demonstrated via the related experiments. This method can play an instructive role in practice and provide a reference for the related research. PMID:28489867

A shape-based inter-layer contours correspondence method for ICT-based reverse engineering.

PubMed

Duan, Liming; Yang, Shangpeng; Zhang, Gui; Feng, Fei; Gu, Minghui

2017-01-01

The correspondence of a stack of planar contours in ICT (industrial computed tomography)-based reverse engineering, a key step in surface reconstruction, is difficult when the contours or topology of the object are complex. Given the regularity of industrial parts and similarity of the inter-layer contours, a specialized shape-based inter-layer contours correspondence method for ICT-based reverse engineering was presented to solve the above problem based on the vectorized contours. In this paper, the vectorized contours extracted from the slices consist of three graphical primitives: circles, arcs and segments. First, the correspondence of the inter-layer primitives is conducted based on the characteristics of the primitives. Second, based on the corresponded primitives, the inter-layer contours correspond with each other using the proximity rules and exhaustive search. The proposed method can make full use of the shape information to handle industrial parts with complex structures. The feasibility and superiority of this method have been demonstrated via the related experiments. This method can play an instructive role in practice and provide a reference for the related research.

Cascade Optimization for Aircraft Engines With Regression and Neural Network Analysis - Approximators

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Guptill, James D.; Hopkins, Dale A.; Lavelle, Thomas M.

2000-01-01

The NASA Engine Performance Program (NEPP) can configure and analyze almost any type of gas turbine engine that can be generated through the interconnection of a set of standard physical components. In addition, the code can optimize engine performance by changing adjustable variables under a set of constraints. However, for engine cycle problems at certain operating points, the NEPP code can encounter difficulties: nonconvergence in the currently implemented Powell's optimization algorithm and deficiencies in the Newton-Raphson solver during engine balancing. A project was undertaken to correct these deficiencies. Nonconvergence was avoided through a cascade optimization strategy, and deficiencies associated with engine balancing were eliminated through neural network and linear regression methods. An approximation-interspersed cascade strategy was used to optimize the engine's operation over its flight envelope. Replacement of Powell's algorithm by the cascade strategy improved the optimization segment of the NEPP code. The performance of the linear regression and neural network methods as alternative engine analyzers was found to be satisfactory. This report considers two examples-a supersonic mixed-flow turbofan engine and a subsonic waverotor-topped engine-to illustrate the results, and it discusses insights gained from the improved version of the NEPP code.

Stroma-associated master regulators of molecular subtypes predict patient prognosis in ovarian cancer.

PubMed

Zhang, Shengzhe; Jing, Ying; Zhang, Meiying; Zhang, Zhenfeng; Ma, Pengfei; Peng, Huixin; Shi, Kaixuan; Gao, Wei-Qiang; Zhuang, Guanglei

2015-11-04

High-grade serous ovarian carcinoma (HGS-OvCa) has the lowest survival rate among all gynecologic cancers and is hallmarked by a high degree of heterogeneity. The Cancer Genome Atlas network has described a gene expression-based molecular classification of HGS-OvCa into Differentiated, Mesenchymal, Immunoreactive and Proliferative subtypes. However, the biological underpinnings and regulatory mechanisms underlying the distinct molecular subtypes are largely unknown. Here we showed that tumor-infiltrating stromal cells significantly contributed to the assignments of Mesenchymal and Immunoreactive clusters. Using reverse engineering and an unbiased interrogation of subtype regulatory networks, we identified the transcriptional modules containing master regulators that drive gene expression of Mesenchymal and Immunoreactive HGS-OvCa. Mesenchymal master regulators were associated with poor prognosis, while Immunoreactive master regulators positively correlated with overall survival. Meta-analysis of 749 HGS-OvCa expression profiles confirmed that master regulators as a prognostic signature were able to predict patient outcome. Our data unraveled master regulatory programs of HGS-OvCa subtypes with prognostic and potentially therapeutic relevance, and suggested that the unique transcriptional and clinical characteristics of ovarian Mesenchymal and Immunoreactive subtypes could be, at least partially, ascribed to tumor microenvironment.

Where Are All the Women Engineers? An Insider's View of Socialization and Power in Engineering Education

ERIC Educational Resources Information Center

Christman, Jeanne

2017-01-01

Despite more than thirty years of the underrepresentation of women in engineering being a persistent concern, research on the cause of the problem has not been successful in reversing the trend. A plethora of theories as to why females are not entering engineering exist, yet they only address issues on the surface and do not attend to a…

Natural tooth intrusion and reversal in implant-assisted prosthesis: evidence of and a hypothesis for the occurrence.

PubMed

Sheets, C G; Earthmann, J C

1993-12-01

Based on clinical observation, a hypothesis of the mechanism of intrusion of natural teeth in an implant-assisted prosthesis is suggested. Engineering principles are presented that establish an energy absorption model as it relates to the implant-assisted prosthesis. In addition, in the course of patient treatment it has been discovered that the intrusion of natural teeth can be reversed. Patient histories that demonstrate intrusion reversal are reviewed. The possible mechanisms for the intrusion/reversal phenomenon are presented and preventative recommendations are given.

EO-Performance relationships in Reverse Internationalization by Chinese Global Startup OEMs: Social Networks and Strategic Flexibility.

PubMed

Chin, Tachia; Tsai, Sang-Bing; Fang, Kai; Zhu, Wenzhong; Yang, Dongjin; Liu, Ren-Huai; Tsuei, Richard Ting Chang

2016-01-01

Due to the context-sensitive nature of entrepreneurial orientation (EO), it is imperative to in-depth explore the EO-performance mechanism in China at its critical, specific stage of economic reform. Under the context of "reverse internationalization" by Chinese global startup original equipment manufacturers (OEMs), this paper aims to manifest the unique links and complicated interrelationships between the individual EO dimensions and firm performance. Using structural equation modeling, we found that during reverse internationalization, proactiveness is positively related to performance; risk taking is not statistically associated with performance; innovativeness is negatively related to performance. The proactiveness-performance relationship is mediated by Strategic flexibility and moderated by social networking relationships. The dynamic and complex institutional setting, coupled with the issues of overcapacity and rising labor cost in China may explain why our distinctive results occur. This research advances the understanding of how contingent factors (social network relationships and strategic flexibility) facilitate entrepreneurial firms to break down institutional barriers and reap the most from EO. It brings new insights into how Chinese global startup OEMs draw on EO to undertake reverse internationalization, responding the calls for unraveling the heterogeneous characteristics of EO sub-dimensions and for more contextually-embedded treatment of EO-performance associations.

EO-Performance relationships in Reverse Internationalization by Chinese Global Startup OEMs: Social Networks and Strategic Flexibility

PubMed Central

Chin, Tachia; Tsai, Sang-Bing; Fang, Kai; Zhu, Wenzhong; Yang, Dongjin; Liu, Ren-huai; Tsuei, Richard Ting Chang

2016-01-01

Due to the context-sensitive nature of entrepreneurial orientation (EO), it is imperative to in-depth explore the EO-performance mechanism in China at its critical, specific stage of economic reform. Under the context of “reverse internationalization” by Chinese global startup original equipment manufacturers (OEMs), this paper aims to manifest the unique links and complicated interrelationships between the individual EO dimensions and firm performance. Using structural equation modeling, we found that during reverse internationalization, proactiveness is positively related to performance; risk taking is not statistically associated with performance; innovativeness is negatively related to performance. The proactiveness-performance relationship is mediated by Strategic flexibility and moderated by social networking relationships. The dynamic and complex institutional setting, coupled with the issues of overcapacity and rising labor cost in China may explain why our distinctive results occur. This research advances the understanding of how contingent factors (social network relationships and strategic flexibility) facilitate entrepreneurial firms to break down institutional barriers and reap the most from EO. It brings new insights into how Chinese global startup OEMs draw on EO to undertake reverse internationalization, responding the calls for unraveling the heterogeneous characteristics of EO sub-dimensions and for more contextually-embedded treatment of EO-performance associations. PMID:27631368

A Novel Modeling Method for Aircraft Engine Using Nonlinear Autoregressive Exogenous (NARX) Models Based on Wavelet Neural Networks

NASA Astrophysics Data System (ADS)

Yu, Bing; Shu, Wenjun; Cao, Can

2018-05-01

A novel modeling method for aircraft engine using nonlinear autoregressive exogenous (NARX) models based on wavelet neural networks is proposed. The identification principle and process based on wavelet neural networks are studied, and the modeling scheme based on NARX is proposed. Then, the time series data sets from three types of aircraft engines are utilized to build the corresponding NARX models, and these NARX models are validated by the simulation. The results show that all the best NARX models can capture the original aircraft engine's dynamic characteristic well with the high accuracy. For every type of engine, the relative identification errors of its best NARX model and the component level model are no more than 3.5 % and most of them are within 1 %.

TARGET's role in knowledge acquisition, engineering, validation, and documentation

NASA Technical Reports Server (NTRS)

Levi, Keith R.

1994-01-01

We investigate the use of the TARGET task analysis tool for use in the development of rule-based expert systems. We found TARGET to be very helpful in the knowledge acquisition process. It enabled us to perform knowledge acquisition with one knowledge engineer rather than two. In addition, it improved communication between the domain expert and knowledge engineer. We also found it to be useful for both the rule development and refinement phases of the knowledge engineering process. Using the network in these phases required us to develop guidelines that enabled us to easily translate the network into production rules. A significant requirement for TARGET remaining useful throughout the knowledge engineering process was the need to carefully maintain consistency between the network and the rule representations. Maintaining consistency not only benefited the knowledge engineering process, but also has significant payoffs in the areas of validation of the expert system and documentation of the knowledge in the system.

CellNet: Network Biology Applied to Stem Cell Engineering

PubMed Central

Cahan, Patrick; Li, Hu; Morris, Samantha A.; da Rocha, Edroaldo Lummertz; Daley, George Q.; Collins, James J.

2014-01-01

SUMMARY Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population, and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering. PMID:25126793

A Measure of Systems Engineering Effectiveness in Government Acquisition of Complex Information Systems: A Bayesian Belief Network-Based Approach

ERIC Educational Resources Information Center

Doskey, Steven Craig

2014-01-01

This research presents an innovative means of gauging Systems Engineering effectiveness through a Systems Engineering Relative Effectiveness Index (SE REI) model. The SE REI model uses a Bayesian Belief Network to map causal relationships in government acquisitions of Complex Information Systems (CIS), enabling practitioners to identify and…

Developmental engineering: a new paradigm for the design and manufacturing of cell-based products. Part II: from genes to networks: tissue engineering from the viewpoint of systems biology and network science.

PubMed

Lenas, Petros; Moos, Malcolm; Luyten, Frank P

2009-12-01

The field of tissue engineering is moving toward a new concept of "in vitro biomimetics of in vivo tissue development." In Part I of this series, we proposed a theoretical framework integrating the concepts of developmental biology with those of process design to provide the rules for the design of biomimetic processes. We named this methodology "developmental engineering" to emphasize that it is not the tissue but the process of in vitro tissue development that has to be engineered. To formulate the process design rules in a rigorous way that will allow a computational design, we should refer to mathematical methods to model the biological process taking place in vitro. Tissue functions cannot be attributed to individual molecules but rather to complex interactions between the numerous components of a cell and interactions between cells in a tissue that form a network. For tissue engineering to advance to the level of a technologically driven discipline amenable to well-established principles of process engineering, a scientifically rigorous formulation is needed of the general design rules so that the behavior of networks of genes, proteins, or cells that govern the unfolding of developmental processes could be related to the design parameters. Now that sufficient experimental data exist to construct plausible mathematical models of many biological control circuits, explicit hypotheses can be evaluated using computational approaches to facilitate process design. Recent progress in systems biology has shown that the empirical concepts of developmental biology that we used in Part I to extract the rules of biomimetic process design can be expressed in rigorous mathematical terms. This allows the accurate characterization of manufacturing processes in tissue engineering as well as the properties of the artificial tissues themselves. In addition, network science has recently shown that the behavior of biological networks strongly depends on their topology and has developed the necessary concepts and methods to describe it, allowing therefore a deeper understanding of the behavior of networks during biomimetic processes. These advances thus open the door to a transition for tissue engineering from a substantially empirical endeavor to a technology-based discipline comparable to other branches of engineering.

The NUONCE engine for LEO networks

NASA Technical Reports Server (NTRS)

Lo, Martin W.; Estabrook, Polly

1995-01-01

Typical LEO networks use constellations which provide a uniform coverage. However, the demand for telecom service is dynamic and unevenly distributed around the world. We examine a more efficient and cost effective design by matching the satellite coverage with the cyclical demand for service around the world. Our approach is to use a non-uniform satellite distribution for the network. We have named this constellation design NUONCE for Non Uniform Optimal Network Communications Engine.

Thermoelectric energy converters under a trade-off figure of merit with broken time-reversal symmetry

NASA Astrophysics Data System (ADS)

Iyyappan, I.; Ponmurugan, M.

2017-09-01

We study the performance of a three-terminal thermoelectric device such as heat engine and refrigerator with broken time-reversal symmetry by applying the unified trade-off figure of merit (\\dotΩ criterion) which accounts for both useful energy and losses. For the heat engine, we find that a thermoelectric device working under the maximum \\dotΩ criterion gives a significantly better performance than a device working at maximum power output. Within the framework of linear irreversible thermodynamics such a direct comparison is not possible for refrigerators, however, our study indicates that, for refrigerator, the maximum cooling load gives a better performance than the maximum \\dotΩ criterion for a larger asymmetry. Our results can be useful to choose a suitable optimization criterion for operating a real thermoelectric device with broken time-reversal symmetry.

A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells

PubMed Central

Trevino, Victor; Cassese, Alberto; Nagy, Zsuzsanna; Zhuang, Xiaodong; Herbert, John; Antzack, Philipp; Clarke, Kim; Davies, Nicholas; Rahman, Ayesha; Campbell, Moray J.; Bicknell, Roy; Vannucci, Marina; Falciani, Francesco

2016-01-01

Abstract The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell communication networks in a wide spectrum of biological systems. PMID:27124473

A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells.

PubMed

Trevino, Victor; Cassese, Alberto; Nagy, Zsuzsanna; Zhuang, Xiaodong; Herbert, John; Antczak, Philipp; Clarke, Kim; Davies, Nicholas; Rahman, Ayesha; Campbell, Moray J; Guindani, Michele; Bicknell, Roy; Vannucci, Marina; Falciani, Francesco

2016-04-01

The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell communication networks in a wide spectrum of biological systems.

Hydrogen adsorption and desorption with 3D silicon nanotube-network and film-network structures: Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Li, Ming; Huang, Xiaobo; Kang, Zhan

2015-08-01

Hydrogen is clean, sustainable, and renewable, thus is viewed as promising energy carrier. However, its industrial utilization is greatly hampered by the lack of effective hydrogen storage and release method. Carbon nanotubes (CNTs) were viewed as one of the potential hydrogen containers, but it has been proved that pure CNTs cannot attain the desired target capacity of hydrogen storage. In this paper, we present a numerical study on the material-driven and structure-driven hydrogen adsorption of 3D silicon networks and propose a deformation-driven hydrogen desorption approach based on molecular simulations. Two types of 3D nanostructures, silicon nanotube-network (Si-NN) and silicon film-network (Si-FN), are first investigated in terms of hydrogen adsorption and desorption capacity with grand canonical Monte Carlo simulations. It is revealed that the hydrogen storage capacity is determined by the lithium doping ratio and geometrical parameters, and the maximum hydrogen uptake can be achieved by a 3D nanostructure with optimal configuration and doping ratio obtained through design optimization technique. For hydrogen desorption, a mechanical-deformation-driven-hydrogen-release approach is proposed. Compared with temperature/pressure change-induced hydrogen desorption method, the proposed approach is so effective that nearly complete hydrogen desorption can be achieved by Si-FN nanostructures under sufficient compression but without structural failure observed. The approach is also reversible since the mechanical deformation in Si-FN nanostructures can be elastically recovered, which suggests a good reusability. This study may shed light on the mechanism of hydrogen adsorption and desorption and thus provide useful guidance toward engineering design of microstructural hydrogen (or other gas) adsorption materials.

Inferring Regulatory Networks from Experimental Morphological Phenotypes: A Computational Method Reverse-Engineers Planarian Regeneration

PubMed Central

Lobo, Daniel; Levin, Michael

2015-01-01

Transformative applications in biomedicine require the discovery of complex regulatory networks that explain the development and regeneration of anatomical structures, and reveal what external signals will trigger desired changes of large-scale pattern. Despite recent advances in bioinformatics, extracting mechanistic pathway models from experimental morphological data is a key open challenge that has resisted automation. The fundamental difficulty of manually predicting emergent behavior of even simple networks has limited the models invented by human scientists to pathway diagrams that show necessary subunit interactions but do not reveal the dynamics that are sufficient for complex, self-regulating pattern to emerge. To finally bridge the gap between high-resolution genetic data and the ability to understand and control patterning, it is critical to develop computational tools to efficiently extract regulatory pathways from the resultant experimental shape phenotypes. For example, planarian regeneration has been studied for over a century, but despite increasing insight into the pathways that control its stem cells, no constructive, mechanistic model has yet been found by human scientists that explains more than one or two key features of its remarkable ability to regenerate its correct anatomical pattern after drastic perturbations. We present a method to infer the molecular products, topology, and spatial and temporal non-linear dynamics of regulatory networks recapitulating in silico the rich dataset of morphological phenotypes resulting from genetic, surgical, and pharmacological experiments. We demonstrated our approach by inferring complete regulatory networks explaining the outcomes of the main functional regeneration experiments in the planarian literature; By analyzing all the datasets together, our system inferred the first systems-biology comprehensive dynamical model explaining patterning in planarian regeneration. This method provides an automated, highly generalizable framework for identifying the underlying control mechanisms responsible for the dynamic regulation of growth and form. PMID:26042810

Thrust reverser design studies for an over-the-wing STOL transport

NASA Technical Reports Server (NTRS)

Ammer, R. C.; Sowers, H. D.

1977-01-01

Aerodynamic and acoustics analytical studies were conducted to evaluate three thrust reverser designs for potential use on commercial over-the-wing STOL transports. The concepts were: (1) integral D nozzle/target reverser, (2) integral D nozzle/top arc cascade reverser, and (3) post exit target reverser integral with wing. Aerodynamic flowpaths and kinematic arrangements for each concept were established to provide a 50% thrust reversal capability. Analytical aircraft stopping distance/noise trade studies conducted concurrently with flow path design showed that these high efficiency reverser concepts are employed at substantially reduced power settings to meet noise goals of 100 PNdB on a 152.4 m sideline and still meet 609.6 m landing runway length requirements. From an overall installation standpoint, only the integral D nozzle/target reverser concept was found to penalize nacelle cruise performance; for this concept a larger nacelle diameter was required to match engine cycle effective area demand in reverse thrust.

Molecular communication and networking: opportunities and challenges.

PubMed

Nakano, Tadashi; Moore, Michael J; Wei, Fang; Vasilakos, Athanasios V; Shuai, Jianwei

2012-06-01

The ability of engineered biological nanomachines to communicate with biological systems at the molecular level is anticipated to enable future applications such as monitoring the condition of a human body, regenerating biological tissues and organs, and interfacing artificial devices with neural systems. From the viewpoint of communication theory and engineering, molecular communication is proposed as a new paradigm for engineered biological nanomachines to communicate with the natural biological nanomachines which form a biological system. Distinct from the current telecommunication paradigm, molecular communication uses molecules as the carriers of information; sender biological nanomachines encode information on molecules and release the molecules in the environment, the molecules then propagate in the environment to receiver biological nanomachines, and the receiver biological nanomachines biochemically react with the molecules to decode information. Current molecular communication research is limited to small-scale networks of several biological nanomachines. Key challenges to bridge the gap between current research and practical applications include developing robust and scalable techniques to create a functional network from a large number of biological nanomachines. Developing networking mechanisms and communication protocols is anticipated to introduce new avenues into integrating engineered and natural biological nanomachines into a single networked system. In this paper, we present the state-of-the-art in the area of molecular communication by discussing its architecture, features, applications, design, engineering, and physical modeling. We then discuss challenges and opportunities in developing networking mechanisms and communication protocols to create a network from a large number of bio-nanomachines for future applications.

Dynamic actuation of glassy polymersomes through isomerization of a single azobenzene unit at the block copolymer interface

NASA Astrophysics Data System (ADS)

Molla, Mijanur Rahaman; Rangadurai, Poornima; Antony, Lucas; Swaminathan, Subramani; de Pablo, Juan J.; Thayumanavan, S.

2018-06-01

Nature has engineered exquisitely responsive systems where molecular-scale information is transferred across an interface and propagated over long length scales. Such systems rely on multiple interacting, signalling and adaptable molecular and supramolecular networks that are built on dynamic, non-equilibrium structures. Comparable synthetic systems are still in their infancy. Here, we demonstrate that the light-induced actuation of a molecularly thin interfacial layer, assembled from a hydrophilic- azobenzene -hydrophobic diblock copolymer, can result in a reversible, long-lived perturbation of a robust glassy membrane across a range of over 500 chemical bonds. We show that the out-of-equilibrium actuation is caused by the photochemical trans-cis isomerization of the azo group, a single chemical functionality, in the middle of the interfacial layer. The principles proposed here are implemented in water-dispersed nanocapsules, and have implications for on-demand release of embedded cargo molecules.

Cell-Free Optogenetic Gene Expression System.

PubMed

Jayaraman, Premkumar; Yeoh, Jing Wui; Jayaraman, Sudhaghar; Teh, Ai Ying; Zhang, Jingyun; Poh, Chueh Loo

2018-04-20

Optogenetic tools provide a new and efficient way to dynamically program gene expression with unmatched spatiotemporal precision. To date, their vast potential remains untapped in the field of cell-free synthetic biology, largely due to the lack of simple and efficient light-switchable systems. Here, to bridge the gap between cell-free systems and optogenetics, we studied our previously engineered one component-based blue light-inducible Escherichia coli promoter in a cell-free environment through experimental characterization and mathematical modeling. We achieved >10-fold dynamic expression and demonstrated rapid and reversible activation of the target gene to generate oscillatory response. The deterministic model developed was able to recapitulate the system behavior and helped to provide quantitative insights to optimize dynamic response. This in vitro optogenetic approach could be a powerful new high-throughput screening technology for rapid prototyping of complex biological networks in both space and time without the need for chemical induction.

Hybrid grammar-based approach to nonlinear dynamical system identification from biological time series

NASA Astrophysics Data System (ADS)

McKinney, B. A.; Crowe, J. E., Jr.; Voss, H. U.; Crooke, P. S.; Barney, N.; Moore, J. H.

2006-02-01

We introduce a grammar-based hybrid approach to reverse engineering nonlinear ordinary differential equation models from observed time series. This hybrid approach combines a genetic algorithm to search the space of model architectures with a Kalman filter to estimate the model parameters. Domain-specific knowledge is used in a context-free grammar to restrict the search space for the functional form of the target model. We find that the hybrid approach outperforms a pure evolutionary algorithm method, and we observe features in the evolution of the dynamical models that correspond with the emergence of favorable model components. We apply the hybrid method to both artificially generated time series and experimentally observed protein levels from subjects who received the smallpox vaccine. From the observed data, we infer a cytokine protein interaction network for an individual’s response to the smallpox vaccine.

Ethical Guidelines for Computer Security Researchers: "Be Reasonable"

NASA Astrophysics Data System (ADS)

Sassaman, Len

For most of its existence, the field of computer science has been lucky enough to avoid ethical dilemmas by virtue of its relatively benign nature. The subdisciplines of programming methodology research, microprocessor design, and so forth have little room for the greater questions of human harm. Other, more recently developed sub-disciplines, such as data mining, social network analysis, behavioral profiling, and general computer security, however, open the door to abuse of users by practitioners and researchers. It is therefore the duty of the men and women who chart the course of these fields to set rules for themselves regarding what sorts of actions on their part are to be considered acceptable and what should be avoided or handled with caution out of ethical concerns. This paper deals solely with the issues faced by computer security researchers, be they vulnerability analysts, privacy system designers, malware experts, or reverse engineers.

Quiet Clean Short-haul Experimental Engine (QCSEE) Under-The-Wing (UTW) engine composite nacelle test report. Volume 1: Summary, aerodynamic and mechanical performance

NASA Technical Reports Server (NTRS)

1979-01-01

The performance test results of the final under-the-wing engine configuration are presented. One hundred and six hours of engine operation were completed, including mechanical and performance checkout, baseline acoustic testing with a bellmouth inlet, reverse thrust testing, acoustic technology tests, and limited controls testing. The engine includes a variable pitch fan having advanced composite fan blades and using a ball-spline pitch actuation system.

A systems biology-based investigation into the therapeutic effects of Gansui Banxia Tang on reversing the imbalanced network of hepatocellular carcinoma

NASA Astrophysics Data System (ADS)

Zhang, Yanqiong; Guo, Xiaodong; Wang, Danhua; Li, Ruisheng; Li, Xiaojuan; Xu, Ying; Liu, Zhenli; Song, Zhiqian; Lin, Ya; Li, Zhiyan; Lin, Na

2014-02-01

Several complex molecular events are involved in tumorigenesis of hepatocellular carcinoma (HCC). The interactions of these molecules may constitute the HCC imbalanced network. Gansui Banxia Tang (GSBXT), as a classic Chinese herbal formula, is a popular complementary and alternative medicine modality for treating HCC. In order to investigate the therapeutic effects and the pharmacological mechanisms of GSBXT on reversing HCC imbalanced network, we in the current study developed a comprehensive systems approach of integrating disease-specific and drug-specific networks, and successfully revealed the relationships of the ingredients in GSBXT with their putative targets, and with HCC significant molecules and HCC related pathway systems for the first time. Meanwhile, further experimental validation also demonstrated the preventive effects of GSBXT on tumor growth in mice and its regulatory effects on potential targets.

MIDER: Network Inference with Mutual Information Distance and Entropy Reduction

PubMed Central

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

2014-01-01

The prediction of links among variables from a given dataset is a task referred to as network inference or reverse engineering. It is an open problem in bioinformatics and systems biology, as well as in other areas of science. Information theory, which uses concepts such as mutual information, provides a rigorous framework for addressing it. While a number of information-theoretic methods are already available, most of them focus on a particular type of problem, introducing assumptions that limit their generality. Furthermore, many of these methods lack a publicly available implementation. Here we present MIDER, a method for inferring network structures with information theoretic concepts. It consists of two steps: first, it provides a representation of the network in which the distance among nodes indicates their statistical closeness. Second, it refines the prediction of the existing links to distinguish between direct and indirect interactions and to assign directionality. The method accepts as input time-series data related to some quantitative features of the network nodes (such as e.g. concentrations, if the nodes are chemical species). It takes into account time delays between variables, and allows choosing among several definitions and normalizations of mutual information. It is general purpose: it may be applied to any type of network, cellular or otherwise. A Matlab implementation including source code and data is freely available (http://www.iim.csic.es/~gingproc/mider.html). The performance of MIDER has been evaluated on seven different benchmark problems that cover the main types of cellular networks, including metabolic, gene regulatory, and signaling. Comparisons with state of the art information–theoretic methods have demonstrated the competitive performance of MIDER, as well as its versatility. Its use does not demand any a priori knowledge from the user; the default settings and the adaptive nature of the method provide good results for a wide range of problems without requiring tuning. PMID:24806471

MIDER: network inference with mutual information distance and entropy reduction.

PubMed

Villaverde, Alejandro F; Ross, John; Morán, Federico; Banga, Julio R

2014-01-01

The prediction of links among variables from a given dataset is a task referred to as network inference or reverse engineering. It is an open problem in bioinformatics and systems biology, as well as in other areas of science. Information theory, which uses concepts such as mutual information, provides a rigorous framework for addressing it. While a number of information-theoretic methods are already available, most of them focus on a particular type of problem, introducing assumptions that limit their generality. Furthermore, many of these methods lack a publicly available implementation. Here we present MIDER, a method for inferring network structures with information theoretic concepts. It consists of two steps: first, it provides a representation of the network in which the distance among nodes indicates their statistical closeness. Second, it refines the prediction of the existing links to distinguish between direct and indirect interactions and to assign directionality. The method accepts as input time-series data related to some quantitative features of the network nodes (such as e.g. concentrations, if the nodes are chemical species). It takes into account time delays between variables, and allows choosing among several definitions and normalizations of mutual information. It is general purpose: it may be applied to any type of network, cellular or otherwise. A Matlab implementation including source code and data is freely available (http://www.iim.csic.es/~gingproc/mider.html). The performance of MIDER has been evaluated on seven different benchmark problems that cover the main types of cellular networks, including metabolic, gene regulatory, and signaling. Comparisons with state of the art information-theoretic methods have demonstrated the competitive performance of MIDER, as well as its versatility. Its use does not demand any a priori knowledge from the user; the default settings and the adaptive nature of the method provide good results for a wide range of problems without requiring tuning.

Increasing Scalability of Researcher Network Extraction from the Web

NASA Astrophysics Data System (ADS)

Asada, Yohei; Matsuo, Yutaka; Ishizuka, Mitsuru

Social networks, which describe relations among people or organizations as a network, have recently attracted attention. With the help of a social network, we can analyze the structure of a community and thereby promote efficient communications within it. We investigate the problem of extracting a network of researchers from the Web, to assist efficient cooperation among researchers. Our method uses a search engine to get the cooccurences of names of two researchers and calculates the streangth of the relation between them. Then we label the relation by analyzing the Web pages in which these two names cooccur. Research on social network extraction using search engines as ours, is attracting attention in Japan as well as abroad. However, the former approaches issue too many queries to search engines to extract a large-scale network. In this paper, we propose a method to filter superfluous queries and facilitates the extraction of large-scale networks. By this method we are able to extract a network of around 3000-nodes. Our experimental results show that the proposed method reduces the number of queries significantly while preserving the quality of the network as compared to former methods.

System Re-engineering Project Executive Summary

DTIC Science & Technology

1991-11-01

Management Information System (STAMIS) application. This project involved reverse engineering, evaluation of structured design and object-oriented design, and re- implementation of the system in Ada. This executive summary presents the approach to re-engineering the system, the lessons learned while going through the process, and issues to be considered in future tasks of this nature.... Computer-Aided Software Engineering (CASE), Distributed Software, Ada, COBOL, Systems Analysis, Systems Design, Life Cycle Development, Functional Decomposition, Object-Oriented

Frontal Hyperconnectivity Related to Discounting and Reversal Learning in Cocaine Subjects

PubMed Central

Camchong, Jazmin; MacDonald, Angus W; Nelson, Brent; Bell, Christopher; Mueller, Bryon A; Specker, Sheila; Lim, Kelvin O

2011-01-01

BACKGROUND Functional neuroimaging studies suggest that chronic cocaine use is associated with frontal lobe abnormalities. Functional connectivity (FC) alterations of cocaine dependent individuals (CD), however, are not yet clear. This is the first study to our knowledge that examines resting FC of anterior cingulate cortex (ACC) in CD. Because ACC is known to integrate inputs from different brain regions to regulate behavior, we hypothesize that CD will have connectivity abnormalities in ACC networks. In addition, we hypothesized that abnormalities would be associated with poor performance in delayed discounting and reversal learning tasks. METHODS Resting functional magnetic resonance imaging data were collected to look for FC differences between twenty-seven cocaine dependent individuals (CD) (5 females, age: M=39.73, SD=6.14) and twenty-four controls (5 females, age: M=39.76, SD = 7.09). Participants were assessed with delayed discounting and reversal learning tasks. Using seed-based FC measures, we examined FC in CD and controls within five ACC connectivity networks with seeds in subgenual, caudal, dorsal, rostral, and perigenual ACC. RESULTS CD showed increased FC within the perigenual ACC network in left middle frontal gyrus, ACC and middle temporal gyrus when compared to controls. FC abnormalities were significantly positively correlated with task performance in delayed discounting and reversal learning tasks in CD. CONCLUSIONS The present study shows that participants with chronic cocaine-dependency have hyperconnectivity within an ACC network known to be involved in social processing and mentalizing. In addition, FC abnormalities found in CD were associated with difficulties with delay rewards and slower adaptive learning. PMID:21371689

Gender Differences in the Consistency of Middle School Students' Interest in Engineering and Science Careers

ERIC Educational Resources Information Center

Ing, Marsha; Aschbacher, Pamela R.; Tsai, Sherry M.

2014-01-01

This longitudinal study analyzes survey responses in seventh, eighth, and ninth grade from diverse public school students (n = 482) to explore gender differences in engineering and science career preferences. Females were far more likely to express interest in a science career (31%) than an engineering career (13%), while the reverse was true for…

Reverse Engineering and Software Products Reuse to Teach Collaborative Web Portals: A Case Study with Final-Year Computer Science Students

ERIC Educational Resources Information Center

Medina-Dominguez, Fuensanta; Sanchez-Segura, Maria-Isabel; Mora-Soto, Arturo; Amescua, Antonio

2010-01-01

The development of collaborative Web applications does not follow a software engineering methodology. This is because when university students study Web applications in general, and collaborative Web portals in particular, they are not being trained in the use of software engineering techniques to develop collaborative Web portals. This paper…

Systems Biology as an Integrated Platform for Bioinformatics, Systems Synthetic Biology, and Systems Metabolic Engineering

PubMed Central

Chen, Bor-Sen; Wu, Chia-Chou

2013-01-01

Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii) system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv) systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering. PMID:24709875

Systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

PubMed

Chen, Bor-Sen; Wu, Chia-Chou

2013-10-11

Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii) system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv) systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

Spreading out of perturbations in reversible reaction networks

NASA Astrophysics Data System (ADS)

Maslov, Sergei; Sneppen, Kim; Ispolatov, I.

2007-08-01

Using an example of physical interactions between proteins, we study how a perturbation propagates in the equilibrium of a network of reversible reactions governed by the law of mass action. We introduce a matrix formalism to describe the linear response of all equilibrium concentrations to shifts in total abundances of individual reactants, and reveal its heuristic analogy to the flow of electric current in a network of resistors. Our main conclusion is that, on average, the induced changes in equilibrium concentrations decay exponentially as a function of network distance from the source of perturbation. We analyze how this decay is influenced by such factors as the topology of a network, binding strength, and correlations between concentrations of neighboring nodes. We find that the minimal branching of the network, small values of dissociation constants, and low equilibrium free (unbound) concentrations of reacting substances all decrease the decay constant and thus increase the range of propagation. Exact analytic expressions for the decay constant are obtained for the case of equally strong interactions and uniform as well as oscillating concentrations on the Bethe lattice. Our general findings are illustrated using a real network of protein-protein interactions in baker's yeast with experimentally determined protein concentrations.

Envisioning engineering education and practice in the coming intelligence convergence era — a complex adaptive systems approach

NASA Astrophysics Data System (ADS)

Noor, Ahmed K.

2013-12-01

Some of the recent attempts for improving and transforming engineering education are reviewed. The attempts aim at providing the entry level engineers with the skills needed to address the challenges of future large-scale complex systems and projects. Some of the frontier sectors and future challenges for engineers are outlined. The major characteristics of the coming intelligence convergence era (the post-information age) are identified. These include the prevalence of smart devices and environments, the widespread applications of anticipatory computing and predictive / prescriptive analytics, as well as a symbiotic relationship between humans and machines. Devices and machines will be able to learn from, and with, humans in a natural collaborative way. The recent game changers in learnscapes (learning paradigms, technologies, platforms, spaces, and environments) that can significantly impact engineering education in the coming era are identified. Among these are open educational resources, knowledge-rich classrooms, immersive interactive 3D learning, augmented reality, reverse instruction / flipped classroom, gamification, robots in the classroom, and adaptive personalized learning. Significant transformative changes in, and mass customization of, learning are envisioned to emerge from the synergistic combination of the game changers and other technologies. The realization of the aforementioned vision requires the development of a new multidisciplinary framework of emergent engineering for relating innovation, complexity and cybernetics, within the future learning environments. The framework can be used to treat engineering education as a complex adaptive system, with dynamically interacting and communicating components (instructors, individual, small, and large groups of learners). The emergent behavior resulting from the interactions can produce progressively better, and continuously improving, learning environment. As a first step towards the realization of the vision, intelligent adaptive cyber-physical ecosystems need to be developed to facilitate collaboration between the various stakeholders of engineering education, and to accelerate the development of a skilled engineering workforce. The major components of the ecosystems include integrated knowledge discovery and exploitation facilities, blended learning and research spaces, novel ultra-intelligent software agents, multimodal and autonomous interfaces, and networked cognitive and tele-presence robots.

Large-scale coupling dynamics of instructed reversal learning.

PubMed

Mohr, Holger; Wolfensteller, Uta; Ruge, Hannes

2018-02-15

The ability to rapidly learn from others by instruction is an important characteristic of human cognition. A recent study found that the rapid transfer from initial instructions to fluid behavior is supported by changes of functional connectivity between and within several large-scale brain networks, and particularly by the coupling of the dorsal attention network (DAN) with the cingulo-opercular network (CON). In the present study, we extended this approach to investigate how these brain networks interact when stimulus-response mappings are altered by novel instructions. We hypothesized that residual stimulus-response associations from initial practice might negatively impact the ability to implement novel instructions. Using functional imaging and large-scale connectivity analysis, we found that functional coupling between the CON and DAN was generally at a higher level during initial than reversal learning. Examining the learning-related connectivity dynamics between the CON and DAN in more detail by means of multivariate patterns analyses, we identified a specific subset of connections which showed a particularly high increase in connectivity during initial learning compared to reversal learning. This finding suggests that the CON-DAN connections can be separated into two functionally dissociable yet spatially intertwined subsystems supporting different aspects of short-term task automatization. Copyright © 2017 Elsevier Inc. All rights reserved.

Advanced Computational Techniques for Power Tube Design.

DTIC Science & Technology

1986-07-01

fixturing applications, in addition to the existing computer-aided engineering capabilities. o Helix TWT Manufacturing has Implemented a tooling and fixturing...illustrates the ajor features of this computer network. ) The backbone of our system is a Sytek Broadband Network (LAN) which Interconnects terminals and...automatic network analyzer (FANA) which electrically characterizes the slow-wave helices of traveling-wave tubes ( TWTs ) -- both for engineering design

Detecting a subsurface cylinder by a Time Reversal MUSIC like method

NASA Astrophysics Data System (ADS)

Solimene, Raffaele; Dell'Aversano, Angela; Leone, Giovanni

2014-05-01

In this contribution the problem of imaging a buried homogeneous circular cylinder is dealt with for a two-dimensional scalar geometry. Though the addressed geometry is extremely simple as compared to real world scenarios, it can be considered of interest for a classical GPR civil engineering applicative context: that is the subsurface prospecting of urban area in order to detect and locate buried utilities. A large body of methods for subsurface imaging have been presented in literature [1], ranging from migration algorithms to non-linear inverse scattering approaches. More recently, also spectral estimation methods, which benefit from sub-array data arrangement, have been proposed and compared in [2].Here a Time Reversal MUSIC (TRM) like method is employed. TRM has been initially conceived to detect point-like scatterers and then generalized to the case of extended scatterers [3]. In the latter case, no a priori information about the scatterers is exploited. However, utilities often can be schematized as circular cylinders. Here, we develop a TRM variant which use this information to properly tailor the steering vector while implementing TRM. Accordingly, instead of a spatial map [3], the imaging procedure returns the scatterer's parameters such as its center position, radius and dielectric permittivity. The study is developed by numerical simulations. First the free-space case is considered in order to more easily introduce the idea and the problem mathematical structure. Then the analysis is extended to the half-space case. In both situations a FDTD forward solver is used to generate the synthetic data. As usual in TRM, a multi-view/multi-static single-frequency configuration is considered and emphasis is put on the role played by the number of available sensors. Acknowledgement This work benefited from networking activities carried out within the EU funded COST Action TU1208 "Civil Engineering Applications of Ground Penetrating Radar." [1] A. Randazzo and R. Solimene, 'Development Of New Methods For The Solution Of Inverse Electromagnetic Scattering Problems By Buried Structures: State of the Art and Open Issues ,'in COST ACTION TU1208: CIVIL ENGINEERING APPLICATIONS OF GROUND PENETRATING RADAR, Proceedings of first Action's General Meeting, 2013. ISBN: 978-88-548-6191-6. [2] S. Meschino, L. Pajewski, M. Pastorino, A. Randazzo, G. Schettini, "Detection of subsurface metallic utilities by means of a SAP technique: Comparing MUSIC- and SVM-based approaches, Journal of Applied Geophysics, vol. 97, pp. 60-68, 2013. [3] E. A. Marengo, F. K. Gruber, F. Simonetti, 'Time-reversal MUSIC imaging of extended targets,' IEEE Trans Image Process. vol. 16, pp. 1967-84, 2007

Three-Dimensional SnS Decorated Carbon Nano-Networks as Anode Materials for Lithium and Sodium Ion Batteries.

PubMed

Zhou, Yanli; Wang, Qi; Zhu, Xiaotao; Jiang, Fuyi

2018-02-28

The three-dimensional (3D) SnS decorated carbon nano-networks (SnS@C) were synthesized via a facile two-step method of freeze-drying combined with post-heat treatment. The lithium and sodium storage performances of above composites acting as anode materials were investigated. As anode materials for lithium ion batteries, a high reversible capacity of 780 mAh·g -1 for SnS@C composites can be obtained at 100 mA·g -1 after 100 cycles. Even cycled at a high current density of 2 A·g -1 , the reversible capacity of this composite can be maintained at 610 mAh·g -1 after 1000 cycles. The initial charge capacity for sodium ion batteries can reach 333 mAh·g -1 , and it retains a reversible capacity of 186 mAh·g -1 at 100 mA·g -1 after 100 cycles. The good lithium or sodium storage performances are likely attributed to the synergistic effects of the conductive carbon nano-networks and small SnS nanoparticles.

How social networks influence female students' choices to major in engineering

NASA Astrophysics Data System (ADS)

Weinland, Kathryn Ann

Scope and Method of Study: This study examined how social influence plays a part in female students' choices of college major, specifically engineering instead of science, technology, and math. Social influence may show itself through peers, family members, and teachers and may encompass resources under the umbrella of social capital. The purpose of this study was to examine how female students' social networks, through the lens of social capital, influence her major choice of whether or not to study engineering. The variables of peer influence, parental influence, teacher/counselor influence, perception of engineering, and academic background were addressed in a 52 question, Likert scale survey. This survey has been modified from an instrument previously used by Reyer (2007) at Bradley University. Data collection was completed using the Dillman (2009) tailored design model. Responses were grouped into four main scales of the dependent variables of social influence, encouragement, perceptions of engineering and career motivation. A factor analysis was completed on the four factors as a whole, and individual questions were not be analyzed. Findings and Conclusions: This study addressed the differences in social network support for female freshmen majoring in engineering versus female freshmen majoring in science, technology, or math. Social network support, when working together from all angles of peers, teachers, parents, and teachers/counselors, transforms itself into a new force that is more powerful than the summation of the individual parts. Math and science preparation also contributed to female freshmen choosing to major in engineering instead of choosing to major in science, technology, or math. The STEM pipeline is still weak and ways in which to reinforce it should be examined. Social network support is crucial for female freshmen who are majoring in science, technology, engineering, and math.

An algebra-based method for inferring gene regulatory networks

PubMed Central

2014-01-01

Background The inference of gene regulatory networks (GRNs) from experimental observations is at the heart of systems biology. This includes the inference of both the network topology and its dynamics. While there are many algorithms available to infer the network topology from experimental data, less emphasis has been placed on methods that infer network dynamics. Furthermore, since the network inference problem is typically underdetermined, it is essential to have the option of incorporating into the inference process, prior knowledge about the network, along with an effective description of the search space of dynamic models. Finally, it is also important to have an understanding of how a given inference method is affected by experimental and other noise in the data used. Results This paper contains a novel inference algorithm using the algebraic framework of Boolean polynomial dynamical systems (BPDS), meeting all these requirements. The algorithm takes as input time series data, including those from network perturbations, such as knock-out mutant strains and RNAi experiments. It allows for the incorporation of prior biological knowledge while being robust to significant levels of noise in the data used for inference. It uses an evolutionary algorithm for local optimization with an encoding of the mathematical models as BPDS. The BPDS framework allows an effective representation of the search space for algebraic dynamic models that improves computational performance. The algorithm is validated with both simulated and experimental microarray expression profile data. Robustness to noise is tested using a published mathematical model of the segment polarity gene network in Drosophila melanogaster. Benchmarking of the algorithm is done by comparison with a spectrum of state-of-the-art network inference methods on data from the synthetic IRMA network to demonstrate that our method has good precision and recall for the network reconstruction task, while also predicting several of the dynamic patterns present in the network. Conclusions Boolean polynomial dynamical systems provide a powerful modeling framework for the reverse engineering of gene regulatory networks, that enables a rich mathematical structure on the model search space. A C++ implementation of the method, distributed under LPGL license, is available, together with the source code, at http://www.paola-vera-licona.net/Software/EARevEng/REACT.html. PMID:24669835

Generation of recombinant rotaviruses expressing fluorescent proteins using an optimized reverse genetics system.

PubMed

Komoto, Satoshi; Fukuda, Saori; Ide, Tomihiko; Ito, Naoto; Sugiyama, Makoto; Yoshikawa, Tetsushi; Murata, Takayuki; Taniguchi, Koki

2018-04-18

An entirely plasmid-based reverse genetics system for rotaviruses was established very recently. We improved the reverse genetics system to generate recombinant rotavirus by transfecting only 11 cDNA plasmids for its 11 gene segments under the condition of increasing the ratio of the cDNA plasmids for NSP2 and NSP5 genes. Utilizing this highly efficient system, we then engineered infectious recombinant rotaviruses expressing bioluminescent (NanoLuc luciferase) and fluorescent (EGFP and mCherry) reporters. These recombinant rotaviruses expressing reporters remained genetically stable during serial passages. Our reverse genetics approach and recombinant rotaviruses carrying reporter genes will be great additions to the tool kit for studying the molecular virology of rotavirus, and for developing future next-generation vaccines and expression vectors. IMPORTANCE Rotavirus is one of the most important pathogens causing severe gastroenteritis in young children worldwide. In this paper, we describe a robust and simple reverse genetics system based on only rotavirus cDNAs, and its application for engineering infectious recombinant rotaviruses harboring bioluminescent (NanoLuc) and fluorescent (EGFP and mCherry) protein genes. This highly efficient reverse genetics system and recombinant RVAs expressing reporters could be powerful tools for the study of different aspects of rotavirus replication. Furthermore, they may be useful for next-generation vaccine production for this medically important virus. Copyright © 2018 American Society for Microbiology.

The response of dense dry granular material to the shear reversal

NASA Astrophysics Data System (ADS)

Zhang, Jie; Ren, Jie; Farhadi, Somayeh; Behringer, Robert

2008-11-01

We have performed two dimensional granular experiments under pure shear using bidisperse photo-elastic disks. Starting from a stress free state, a square box filled with granular particles is subject to shear. The forward shears involved various number of steps, leading to maximum strains between 0.1 and 0.3. The area is kept constant during the shear. The network of force chains gradually built up as the strain increased, leading to increased pressure and shear stress. Reverse shear was then applied to the system. Depending on the initial packing fraction and the strain at which the shear is reversed, the force chain network built prior to the shear reversal may be destroyed completely or partially destroyed. Following the force chain weakening, when the reserve shear is continuously applied to the system, there is a force chain strengthening. Following each change of the system, contact forces of individual disks were measured by applying an inverse algorithm. We also kept track of the displacement and angle of rotation of every particle from frame to frame. We present the results for the structure failure and reconstruction during shear reversals. We also present data for stresses, contact force distributions and other statistical measures.

Yield of reversible colloidal gels during flow start-up: release from kinetic arrest.

PubMed

Johnson, Lilian C; Landrum, Benjamin J; Zia, Roseanna N

2018-06-05

Yield of colloidal gels during start-up of shear flow is characterized by an overshoot in shear stress that accompanies changes in network structure. Prior studies of yield of reversible colloidal gels undergoing strong flow model the overshoot as the point at which network rupture permits fluidization. However, yield under weak flow, which is of interest in many biological and industrial fluids shows no such disintegration. The mechanics of reversible gels are influenced by bond strength and durability, where ongoing rupture and re-formation impart aging that deepens kinetic arrest [Zia et al., J. Rheol., 2014, 58, 1121], suggesting that yield be viewed as release from kinetic arrest. To explore this idea, we study reversible colloidal gels during start-up of shear flow via dynamic simulation, connecting rheological yield to detailed measurements of structure, bond dynamics, and potential energy. We find that pre-yield stress grows temporally with the changing roles of microscopic transport processes: early time behavior is set by Brownian diffusion; later, advective displacements permit relative particle motion that stretches bonds and stores energy. Stress accumulates in stretched, oriented bonds until yield, which is a tipping point to energy release, and is passed with a fully intact network, where the loss of very few bonds enables relaxation of many, easing glassy arrest. This is immediately followed by a reversal to growth in potential energy during bulk plastic deformation and condensation into larger particle domains, supporting the view that yield is an activated release from kinetic arrest. The continued condensation of dense domains and shrinkage of network surfaces, along with a decrease in the potential energy, permit the gel to evolve toward more complete phase separation, supporting our view that yield of weakly sheared gels is a 'non-equilibrium phase transition'. Our findings may be particularly useful for industrial or other coatings, where weak, slow application via shear may lead to phase separation, inhibiting smooth distribution.

A General Tool for Engineering the NAD/NADP Cofactor Preference of Oxidoreductases.

PubMed

Cahn, Jackson K B; Werlang, Caroline A; Baumschlager, Armin; Brinkmann-Chen, Sabine; Mayo, Stephen L; Arnold, Frances H

2017-02-17

The ability to control enzymatic nicotinamide cofactor utilization is critical for engineering efficient metabolic pathways. However, the complex interactions that determine cofactor-binding preference render this engineering particularly challenging. Physics-based models have been insufficiently accurate and blind directed evolution methods too inefficient to be widely adopted. Building on a comprehensive survey of previous studies and our own prior engineering successes, we present a structure-guided, semirational strategy for reversing enzymatic nicotinamide cofactor specificity. This heuristic-based approach leverages the diversity and sensitivity of catalytically productive cofactor binding geometries to limit the problem to an experimentally tractable scale. We demonstrate the efficacy of this strategy by inverting the cofactor specificity of four structurally diverse NADP-dependent enzymes: glyoxylate reductase, cinnamyl alcohol dehydrogenase, xylose reductase, and iron-containing alcohol dehydrogenase. The analytical components of this approach have been fully automated and are available in the form of an easy-to-use web tool: Cofactor Specificity Reversal-Structural Analysis and Library Design (CSR-SALAD).

Cheaper Adjoints by Reversing Address Computations

DOE PAGES

Hascoët, L.; Utke, J.; Naumann, U.

2008-01-01

The reverse mode of automatic differentiation is widely used in science and engineering. A severe bottleneck for the performance of the reverse mode, however, is the necessity to recover certain intermediate values of the program in reverse order. Among these values are computed addresses, which traditionally are recovered through forward recomputation and storage in memory. We propose an alternative approach for recovery that uses inverse computation based on dependency information. Address storage constitutes a significant portion of the overall storage requirements. An example illustrates substantial gains that the proposed approach yields, and we show use cases in practical applications.

14 CFR 25.933 - Reversing systems.

Code of Federal Regulations, 2010 CFR

2010-01-01

... analysis or testing, or both, for propeller systems that allow propeller blades to move from the flight low... reversal in flight the engine will produce no more than flight idle thrust. In addition, it must be shown... position; and (ii) The airplane is capable of continued safe flight and landing under any possible position...

14 CFR 25.933 - Reversing systems.

Code of Federal Regulations, 2013 CFR

2013-01-01

... analysis or testing, or both, for propeller systems that allow propeller blades to move from the flight low... reversal in flight the engine will produce no more than flight idle thrust. In addition, it must be shown... position; and (ii) The airplane is capable of continued safe flight and landing under any possible position...

Self-Healing of Unentangled Polymer Networks with Reversible Bonds

PubMed Central

Stukalin, Evgeny B.; Cai, Li-Heng; Kumar, N. Arun; Leibler, Ludwik; Rubinstein, Michael

2013-01-01

Self-healing polymeric materials are systems that after damage can revert to their original state with full or partial recovery of mechanical strength. Using scaling theory we study a simple model of autonomic self-healing of unentangled polymer networks. In this model one of the two end monomers of each polymer chain is fixed in space mimicking dangling chains attachment to a polymer network, while the sticky monomer at the other end of each chain can form pairwise reversible bond with the sticky end of another chain. We study the reaction kinetics of reversible bonds in this simple model and analyze the different stages in the self-repair process. The formation of bridges and the recovery of the material strength across the fractured interface during the healing period occur appreciably faster after shorter waiting time, during which the fractured surfaces are kept apart. We observe the slowest formation of bridges for self-adhesion after bringing into contact two bare surfaces with equilibrium (very low) density of open stickers in comparison with self-healing. The primary role of anomalous diffusion in material self-repair for short waiting times is established, while at long waiting times the recovery of bonds across fractured interface is due to hopping diffusion of stickers between different bonded partners. Acceleration in bridge formation for self-healing compared to self-adhesion is due to excess non-equilibrium concentration of open stickers. Full recovery of reversible bonds across fractured interface (formation of bridges) occurs after appreciably longer time than the equilibration time of the concentration of reversible bonds in the bulk. PMID:24347684

Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers.

PubMed

Borchani, Hanen; Bielza, Concha; Toro, Carlos; Larrañaga, Pedro

2013-03-01

Our aim is to use multi-dimensional Bayesian network classifiers in order to predict the human immunodeficiency virus type 1 (HIV-1) reverse transcriptase and protease inhibitors given an input set of respective resistance mutations that an HIV patient carries. Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models especially designed to solve multi-dimensional classification problems, where each input instance in the data set has to be assigned simultaneously to multiple output class variables that are not necessarily binary. In this paper, we introduce a new method, named MB-MBC, for learning MBCs from data by determining the Markov blanket around each class variable using the HITON algorithm. Our method is applied to both reverse transcriptase and protease data sets obtained from the Stanford HIV-1 database. Regarding the prediction of antiretroviral combination therapies, the experimental study shows promising results in terms of classification accuracy compared with state-of-the-art MBC learning algorithms. For reverse transcriptase inhibitors, we get 71% and 11% in mean and global accuracy, respectively; while for protease inhibitors, we get more than 84% and 31% in mean and global accuracy, respectively. In addition, the analysis of MBC graphical structures lets us gain insight into both known and novel interactions between reverse transcriptase and protease inhibitors and their respective resistance mutations. MB-MBC algorithm is a valuable tool to analyze the HIV-1 reverse transcriptase and protease inhibitors prediction problem and to discover interactions within and between these two classes of inhibitors. Copyright © 2012 Elsevier B.V. All rights reserved.

Traffic engineering and regenerator placement in GMPLS networks with restoration

NASA Astrophysics Data System (ADS)

Yetginer, Emre; Karasan, Ezhan

2002-07-01

In this paper we study regenerator placement and traffic engineering of restorable paths in Generalized Multipro-tocol Label Switching (GMPLS) networks. Regenerators are necessary in optical networks due to transmission impairments. We study a network architecture where there are regenerators at selected nodes and we propose two heuristic algorithms for the regenerator placement problem. Performances of these algorithms in terms of required number of regenerators and computational complexity are evaluated. In this network architecture with sparse regeneration, offline computation of working and restoration paths is studied with bandwidth reservation and path rerouting as the restoration scheme. We study two approaches for selecting working and restoration paths from a set of candidate paths and formulate each method as an Integer Linear Programming (ILP) prob-lem. Traffic uncertainty model is developed in order to compare these methods based on their robustness with respect to changing traffic patterns. Traffic engineering methods are compared based on number of additional demands due to traffic uncertainty that can be carried. Regenerator placement algorithms are also evaluated from a traffic engineering point of view.

Supply Chain Engineering and the Use of a Supporting Knowledge Management Application

NASA Astrophysics Data System (ADS)

Laakmann, Frank

The future competition in markets will happen between logistics networks and no longer between enterprises. A new approach for supporting the engineering of logistics networks is developed by this research as a part of the Collaborative Research Centre (SFB) 559: "Modeling of Large Networks in Logistics" at the University of Dortmund together with the Fraunhofer-Institute of Material Flow and Logistics founded by Deutsche Forschungsgemeinschaft (DFG). Based on a reference model for logistics processes, the process chain model, a guideline for logistics engineers is developed to manage the different types of design tasks of logistics networks. The technical background of this solution is a collaborative knowledge management application. This paper will introduce how new Internet-based technologies support supply chain design projects.

Investigation of two-dimensional wedge exhaust nozzles for advanced aircraft

NASA Technical Reports Server (NTRS)

Maiden, D. L.; Petit, J. E.

1975-01-01

Two-dimensional wedge nozzle performance characteristics were investigated in a series of wind-tunnel tests. An isolated single-engine/nozzle model was used to study the effects of internal expansion area ratio, aftbody cowl boattail angle, and wedge length. An integrated twin-engine/nozzle model, tested with and without empenage surfaces, included cruise, acceleration, thrust vectoring and thrust reversing nozzle operating modes. Results indicate that the thrust-minus-aftbody drag performance of the twin two-dimensional nozzle integration is significantly higher, for speeds greater than Mach 0.8, than the performance achieved with twin axisymmetric nozzle installations. Significant jet-induced lift was obtained on an aft-mounted lifting surface using a cambered wedge center body to vector thrust. The thrust reversing capabilities of reverser panels installed on the two-dimensional wedge center body were very effective for static or in-flight operation.

Crossbar Switches For Optical Data-Communication Networks

NASA Technical Reports Server (NTRS)

Monacos, Steve P.

1994-01-01

Optoelectronic and electro-optical crossbar switches called "permutation engines" (PE's) developed to route packets of data through fiber-optic communication networks. Basic network concept described in "High-Speed Optical Wide-Area Data-Communication Network" (NPO-18983). Nonblocking operation achieved by decentralized switching and control scheme. Each packet routed up or down in each column of this 5-input/5-output permutation engine. Routing algorithm ensures each packet arrives at its designated output port without blocking any other packet that does not contend for same output port.

Reverse engineering the mechanical and molecular pathways in stem cell morphogenesis.

PubMed

Lu, Kai; Gordon, Richard; Cao, Tong

2015-03-01

The formation of relevant biological structures poses a challenge for regenerative medicine. During embryogenesis, embryonic cells differentiate into somatic tissues and undergo morphogenesis to produce three-dimensional organs. Using stem cells, we can recapitulate this process and create biological constructs for therapeutic transplantation. However, imperfect imitation of nature sometimes results in in vitro artifacts that fail to recapitulate the function of native organs. It has been hypothesized that developing cells may self-organize into tissue-specific structures given a correct in vitro environment. This proposition is supported by the generation of neo-organoids from stem cells. We suggest that morphogenesis may be reverse engineered to uncover its interacting mechanical pathway and molecular circuitry. By harnessing the latent architecture of stem cells, novel tissue-engineering strategies may be conceptualized for generating self-organizing transplants. Copyright © 2013 John Wiley & Sons, Ltd.

Pollution Reduction Technology Program, Turboprop Engines, Phase 1

NASA Technical Reports Server (NTRS)

Anderson, R. D.; Herman, A. S.; Tomlinson, J. G.; Vaught, J. M.; Verdouw, A. J.

1976-01-01

Exhaust pollutant emissions were measured from a 501-D22A turboprop engine combustor and three low emission combustor types -- reverse flow, prechamber, and staged fuel, operating over a fuel-air ratio range of .0096 to .020. The EPAP LTO cycle data were obtained for a total of nineteen configurations. Hydrocarbon emissions were reduced from 15.0 to .3 lb/1000 Hp-Hr/cycle, CO from 31.5 to 4.6 lb/1000 Hp-Hr/cycle with an increase in NOx of 17 percent, which is still 25% below the program goal. The smoke number was reduced from 59 to 17. Emissions given here are for the reverse flow Mod. IV combustor which is the best candidate for further development into eventual use with the 501-D22A turboprop engine. Even lower emissions were obtained with the advanced technology combustors.

Elucidation of the transcription network governing mammalian sex determination by exploiting strain-specific susceptibility to sex reversal

PubMed Central

Munger, Steven C.; Aylor, David L.; Syed, Haider Ali; Magwene, Paul M.; Threadgill, David W.; Capel, Blanche

2009-01-01

Despite the identification of some key genes that regulate sex determination, most cases of disorders of sexual development remain unexplained. Evidence suggests that the sexual fate decision in the developing gonad depends on a complex network of interacting factors that converge on a critical threshold. To elucidate the transcriptional network underlying sex determination, we took the first expression quantitative trait loci (eQTL) approach in a developing organ. We identified reproducible differences in the transcriptome of the embryonic day 11.5 (E11.5) XY gonad between C57BL/6J (B6) and 129S1/SvImJ (129S1), indicating that the reported sensitivity of B6 to sex reversal is consistent with a higher expression of a female-like transcriptome in B6. Gene expression is highly variable in F2 XY gonads from B6 and 129S1 intercrosses, yet strong correlations emerged. We estimated the F2 coexpression network and predicted roles for genes of unknown function based on their connectivity and position within the network. A genetic analysis of the F2 population detected autosomal regions that control the expression of many sex-related genes, including Sry (sex-determining region of the Y chromosome) and Sox9 (Sry-box containing gene 9), the key regulators of male sex determination. Our results reveal the complex transcription architecture underlying sex determination, and provide a mechanism by which individuals may be sensitized for sex reversal. PMID:19884258

Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications

PubMed Central

Verma, Arjun; Fratto, Brian E.; Privman, Vladimir; Katz, Evgeny

2016-01-01

We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s) as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed. PMID:27399702

Self-assembly of amphiphilic molecules in organic liquids

NASA Astrophysics Data System (ADS)

Tung, Shih-Huang

2007-12-01

Amphiphilic molecules are well-known for their ability to self-assemble in water to form structures such as micelles and vesicles. In comparison, much less is known about amphiphilic self-assembly in nonpolar organic liquids. Such "reverse" self assembly can produce many of the counterparts to structures found in water. In this dissertation, we focus on the formation and dynamics of such reverse structures. We seek to obtain fundamental insight into the driving forces for reverse self-assembly processes. Three specific types of reverse structures are studied: (a) reverse wormlike micelles, i.e., long, flexible micellar chains; (b) reverse vesicles, i.e., hollow containers enclosed by reverse bilayers; and (c) organogel networks. While our focus is on the fundamentals, we note that reverse structures can be useful in a variety of applications ranging from drug delivery, controlled release, hosts for enzymatic reactions, and templates for nanomaterials synthesis. In the first part of this study, we describe a new route for forming reverse wormlike micelles in nonpolar organic liquids. This route involves the addition of trace amounts of a bile salt to solutions of the phospholipid, lecithin. We show that bile salts, due to their unique "facially amphiphilic" structure, can promote the aggregation of lecithin molecules into these reverse micellar chains. The resulting samples are viscoelastic and show interesting rheological properties. Unusual trends are seen in the temperature dependence of their rheology, which indicates the importance of hydrogen-bonding interactions in the formation of these micelles. Another remarkable feature of their rheology is the presence of strain-stiffening, where the material becomes stiffer at high deformations. Strain-stiffening has been seen before for elastic gels of biopolymers; here, we demonstrate the same properties for viscoelastic micellar solutions. The second reverse aggregate we deal with is the reverse vesicle. We present a new route for forming stable unilamellar reverse vesicles, and this involves mixing short- and long-chain lipids (lecithins) with a trace of sodium chloride. The ratio of the short to long-chain lipid controls the type and size of self-assembled structure formed, and as this ratio is increased, a transition from reverse micelles to vesicles occurs. The structural changes can be explained in terms of molecular geometry, with the sodium chloride acting as a "glue" in binding lipid headgroups together through electrostatic interactions. The final part of this dissertation focuses on organogels. The two-tailed anionic surfactant, AOT, is well-known to form spherical reverse micelles in organic solvents. We have found that trace amounts (e.g., less than 1 mM) of the dihydroxy bile salt, sodium deoxycholate (SDC) can transform these dilute micellar solutions into self-supporting, transparent organogels. The structure and rheology of these organogels is reminiscent of the self-assembled networks formed by proteins such as actin in water. The organogels are based on networks of long, rigid, cylindrical filaments, with SDC molecules stacked together in the filament core.

NASA/DOD Aerospace Knowledge Diffusion Research Project. Report 14: Engineering work and information use in aerospace: Results of a telephone survey

NASA Technical Reports Server (NTRS)

Pinelli, Thomas E.; Kennedy, John M.; White, Terry F.

1992-01-01

A telephone survey of U.S. aerospace engineers and scientists who were on the Society of Automotive Engineers (SAE) mailing list was conducted between August 14-26, 1991. The survey was undertaken to obtain information on the daily work activities of aerospace engineers and scientists, to measure various practices used by aerospace engineers and scientists to obtain STI, and to ask aerospace engineers and scientists about their use of electronic networks. Co-workers were found important sources of information. Co-workers are used to obtain technical information because the information they have is relevant, not because co-workers are accessible. As technical uncertainty increases, so does the need for information internal and external to the organization. Electronic networks enjoy widespread use within the aerospace community. These networks are accessible and they are used to contact people at remote sites. About 80 percent of the respondents used electronic mail, file transfer, and information or data retrieval to commercial or in-house data bases.

Cascade Optimization Strategy with Neural Network and Regression Approximations Demonstrated on a Preliminary Aircraft Engine Design

NASA Technical Reports Server (NTRS)

Hopkins, Dale A.; Patnaik, Surya N.

2000-01-01

A preliminary aircraft engine design methodology is being developed that utilizes a cascade optimization strategy together with neural network and regression approximation methods. The cascade strategy employs different optimization algorithms in a specified sequence. The neural network and regression methods are used to approximate solutions obtained from the NASA Engine Performance Program (NEPP), which implements engine thermodynamic cycle and performance analysis models. The new methodology is proving to be more robust and computationally efficient than the conventional optimization approach of using a single optimization algorithm with direct reanalysis. The methodology has been demonstrated on a preliminary design problem for a novel subsonic turbofan engine concept that incorporates a wave rotor as a cycle-topping device. Computations of maximum thrust were obtained for a specific design point in the engine mission profile. The results (depicted in the figure) show a significant improvement in the maximum thrust obtained using the new methodology in comparison to benchmark solutions obtained using NEPP in a manual design mode.

CellNet: network biology applied to stem cell engineering.

PubMed

Cahan, Patrick; Li, Hu; Morris, Samantha A; Lummertz da Rocha, Edroaldo; Daley, George Q; Collins, James J

2014-08-14

Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering. Copyright © 2014 Elsevier Inc. All rights reserved.

Topology reconstruction for B-Rep modeling from 3D mesh in reverse engineering applications

NASA Astrophysics Data System (ADS)

Bénière, Roseline; Subsol, Gérard; Gesquière, Gilles; Le Breton, François; Puech, William

2012-03-01

Nowadays, most of the manufactured objects are designed using CAD (Computer-Aided Design) software. Nevertheless, for visualization, data exchange or manufacturing applications, the geometric model has to be discretized into a 3D mesh composed of a finite number of vertices and edges. But, in some cases, the initial model may be lost or unavailable. In other cases, the 3D discrete representation may be modified, for example after a numerical simulation, and does not correspond anymore to the initial model. A reverse engineering method is then required to reconstruct a 3D continuous representation from the discrete one. In previous work, we have presented a new approach for 3D geometric primitive extraction. In this paper, to complete our automatic and comprehensive reverse engineering process, we propose a method to construct the topology of the retrieved object. To reconstruct a B-Rep model, a new formalism is now introduced to define the adjacency relations. Then a new process is used to construct the boundaries of the object. The whole process is tested on 3D industrial meshes and bring a solution to recover B-Rep models.

Data and Analysis Center for Software: An IAC in Transition.

DTIC Science & Technology

1983-06-01

reviewed and is approved for publication. * APPROVEDt Proj ect Engineer . JOHN J. MARCINIAK, Colonel, USAF Chief, Command and Control Division . FOR THE CO...SUPPLEMENTARY NOTES RADC Project Engineer : John Palaimo (COEE) It. KEY WORDS (Conilnuo n rever*e aide if necessary and identify by block numober...Software Engineering Software Technology Information Analysis Center Database Scientific and Technical Information 20. ABSTRACT (Continue on reverse side It

Understanding Biological Regulation Through Synthetic Biology.

PubMed

Bashor, Caleb J; Collins, James J

2018-05-20

Engineering synthetic gene regulatory circuits proceeds through iterative cycles of design, building, and testing. Initial circuit designs must rely on often-incomplete models of regulation established by fields of reductive inquiry-biochemistry and molecular and systems biology. As differences in designed and experimentally observed circuit behavior are inevitably encountered, investigated, and resolved, each turn of the engineering cycle can force a resynthesis in understanding of natural network function. Here, we outline research that uses the process of gene circuit engineering to advance biological discovery. Synthetic gene circuit engineering research has not only refined our understanding of cellular regulation but furnished biologists with a toolkit that can be directed at natural systems to exact precision manipulation of network structure. As we discuss, using circuit engineering to predictively reorganize, rewire, and reconstruct cellular regulation serves as the ultimate means of testing and understanding how cellular phenotype emerges from systems-level network function.

Using Inspiration from Synaptic Plasticity Rules to Optimize Traffic Flow in Distributed Engineered Networks.

PubMed

Suen, Jonathan Y; Navlakha, Saket

2017-05-01

Controlling the flow and routing of data is a fundamental problem in many distributed networks, including transportation systems, integrated circuits, and the Internet. In the brain, synaptic plasticity rules have been discovered that regulate network activity in response to environmental inputs, which enable circuits to be stable yet flexible. Here, we develop a new neuro-inspired model for network flow control that depends only on modifying edge weights in an activity-dependent manner. We show how two fundamental plasticity rules, long-term potentiation and long-term depression, can be cast as a distributed gradient descent algorithm for regulating traffic flow in engineered networks. We then characterize, both by simulation and analytically, how different forms of edge-weight-update rules affect network routing efficiency and robustness. We find a close correspondence between certain classes of synaptic weight update rules derived experimentally in the brain and rules commonly used in engineering, suggesting common principles to both.

TRANSMISSION NETWORK PLANNING METHOD FOR COMPARATIVE STUDIES (JOURNAL VERSION)

EPA Science Inventory

An automated transmission network planning method for comparative studies is presented. This method employs logical steps that may closely parallel those taken in practice by the planning engineers. Use is made of a sensitivity matrix to simulate the engineers' experience in sele...

A synthetic mammalian network to compute population borders based on engineered reciprocal cell-cell communication.

PubMed

Kolar, Katja; Wischhusen, Hanna M; Müller, Konrad; Karlsson, Maria; Weber, Wilfried; Zurbriggen, Matias D

2015-12-30

Multicellular organisms depend on the exchange of information between specialized cells. This communication is often difficult to decipher in its native context, but synthetic biology provides tools to engineer well-defined systems that allow the convenient study and manipulation of intercellular communication networks. Here, we present the first mammalian synthetic network for reciprocal cell-cell communication to compute the border between a sender/receiver and a processing cell population. The two populations communicate via L-tryptophan and interleukin-4 to highlight the population border by the production of a fluorescent protein. The sharpness of that visualized edge can be adjusted by modulating key parameters of the network. We anticipate that this network will on the one hand be a useful tool to gain deeper insights into the mechanisms of tissue formation in nature and will on the other hand contribute to our ability to engineer artificial tissues.

Enzyme engineering through evolution: thermostable recombinant group II intron reverse transcriptases provide new tools for RNA research and biotechnology.

PubMed

Collins, Kathleen; Nilsen, Timothy W

2013-08-01

Current investigation of RNA transcriptomes relies heavily on the use of retroviral reverse transcriptases. It is well known that these enzymes have many limitations because of their intrinsic properties. This commentary highlights the recent biochemical characterization of a new family of reverse transcriptases, those encoded by group II intron retrohoming elements. The novel properties of these enzymes endow them with the potential to revolutionize how we approach RNA analyses.

Agent-based re-engineering of ErbB signaling: a modeling pipeline for integrative systems biology.

PubMed

Das, Arya A; Ajayakumar Darsana, T; Jacob, Elizabeth

2017-03-01

Experiments in systems biology are generally supported by a computational model which quantitatively estimates the parameters of the system by finding the best fit to the experiment. Mathematical models have proved to be successful in reverse engineering the system. The data generated is interpreted to understand the dynamics of the underlying phenomena. The question we have sought to answer is that - is it possible to use an agent-based approach to re-engineer a biological process, making use of the available knowledge from experimental and modelling efforts? Can the bottom-up approach benefit from the top-down exercise so as to create an integrated modelling formalism for systems biology? We propose a modelling pipeline that learns from the data given by reverse engineering, and uses it for re-engineering the system, to carry out in-silico experiments. A mathematical model that quantitatively predicts co-expression of EGFR-HER2 receptors in activation and trafficking has been taken for this study. The pipeline architecture takes cues from the population model that gives the rates of biochemical reactions, to formulate knowledge-based rules for the particle model. Agent-based simulations using these rules, support the existing facts on EGFR-HER2 dynamics. We conclude that, re-engineering models, built using the results of reverse engineering, opens up the possibility of harnessing the power pack of data which now lies scattered in literature. Virtual experiments could then become more realistic when empowered with the findings of empirical cell biology and modelling studies. Implemented on the Agent Modelling Framework developed in-house. C ++ code templates available in Supplementary material . liz.csir@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Water deficit-induced changes in transcription factor expression in maize seedlings

USDA-ARS?s Scientific Manuscript database

Plants tolerate water deficits by regulating gene networks controlling cellular and physiological traits to modify growth and development. Transcription factor (TFs) directed regulation of transcription within these gene networks is key to eliciting appropriate responses. In this study, reverse tran...

Defense Acquisitions: Assessments of Selected Weapon Programs

DTIC Science & Technology

2017-03-01

PAC-3 MSE) 81 Warfighter Information Network-Tactical (WIN-T) Increment 2 83 Improved Turbine Engine Program (ITEP) 85 Long Range Precision Fires...Unmanned Air System 05/2018 —- O  Joint Surveillance Target Attack Radar System Recapitalization 10/2017 —- O  Improved Turbine Engine Program TBD...Network-Tactical (WIN-T) Increment 2 83 1-page assessments Improved Turbine Engine Program (ITEP) 85 Long Range Precision Fires (LRPF) 86

Systems Engineering Approach and Metrics for Evaluating Network-Centric Operations for U.S. Army Battle Command

DTIC Science & Technology

2013-07-01

Systems Engineering Approach and Metrics for Evaluating Network-Centric Operations for U.S. Army Battle Command by Jock O. Grynovicki and...Battle Command Jock O. Grynovicki and Teresa A. Branscome Human Research and Engineering Directorate, ARL...NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Jock O. Grynovicki and Teresa A. Branscome 5d. PROJECT NUMBER 622716H70 5e. TASK NUMBER

Mechano-responsive hydrogels crosslinked by reactive block copolymer micelles

NASA Astrophysics Data System (ADS)

Xiao, Longxi

Hydrogels are crosslinked polymeric networks that can swell in water without dissolution. Owing to their structural similarity to the native extracelluar matrices, hydrogels have been widely used in biomedical applications. Synthetic hydrogels have been designed to respond to various stimuli, but mechanical signals have not incorporated into hydrogel matrices. Because most tissues in the body are subjected to various types of mechanical forces, and cells within these tissues have sophisticated mechano-transduction machinery, this thesis is focused on developing hydrogel materials with built-in mechano-sensing mechanisms for use as tissue engineering scaffolds or drug release devices. Self-assembled block copolymer micelles (BCMs) with reactive handles were employed as the nanoscopic crosslinkers for the construction of covalently crosslinked networks. BCMs were assembled from amphiphilic diblock copolymers of poly(n-butyl acrylate) and poly(acrylic acid) partially modified with acrylate. Radical polymerization of acrylamide in the presence of micellar crosslinkers gave rise to elastomeric hydrogels whose mechanical properties can be tuned by varying the BCM composition and concentration. TEM imaging revealed that the covalently integrated BCMs underwent strain-dependent reversible deformation. A model hydrophobic drug, pyrene, loaded into the core of BCMs prior to the hydrogel formation, was dynamically released in response to externally applied mechanical forces, through force-induced reversible micelle deformation and the penetration of water molecules into the micelle core. The mechano-responsive hydrogel has been studied for tissue repair and regeneration purposes. Glycidyl methacrylate (GMA)-modified hyaluronic acid (HA) was photochemically crosslinked in the presence of dexamethasone (DEX)-loaded crosslinkable BCMs. The resultant HA gels (HAxBCM) contain covalently integrated micellar compartments with DEX being sequestered in the hydrophobic core. Compared to the traditional HA gels prepared by radical crosslinking of HAGMA, HAxBCM gels exhibited improved drug loading and release capacity. Moreover, compressive forces exerted on the gels were transmitted to the crosslinked BCMs, resulting in a force-modulated DEX release on demand. Micelle mobility in the crosslinked networks was analyzed by fluorescence correlation spectroscopy using nile red loaded BCMs. The anti-inflammatory activities of DEX-releasing HAxBCM gels were evaluated via the in vitro culture of lipopolysaccharide-activated macrophages.

Investigating the Performance of One- and Two-dimensional Flood Models in a Channelized River Network: A Case Study of the Obion River System

NASA Astrophysics Data System (ADS)

Kalyanapu, A. J.; Dullo, T. T.; Thornton, J. C.; Auld, L. A.

2015-12-01

Obion River, is located in the northwestern Tennessee region, and discharges into the Mississippi River. In the past, the river system was largely channelized for agricultural purposes that resulted in increased erosion, loss of wildlife habitat and downstream flood risks. These impacts are now being slowly reversed mainly due to wetland restoration. The river system is characterized by a large network of "loops" around the main channels that hold water either from excess flows or due to flow diversions. Without data on each individual channel, levee, canal, or pond it is not known where the water flows from or to. In some segments along the river, the natural channel has been altered and rerouted by the farmers for their irrigation purposes. Satellite imagery can aid in identifying these features, but its spatial coverage is temporally sparse. All the alterations that have been done to the watershed make it difficult to develop hydraulic models, which could predict flooding and droughts. This is especially true when building one-dimensional (1D) hydraulic models compared to two-dimensional (2D) models, as the former cannot adequately simulate lateral flows in the floodplain and in complex terrains. The objective of this study therefore is to study the performance of 1D and 2D flood models in this complex river system, evaluate the limitations of 1D models and highlight the advantages of 2D models. The study presents the application of HEC-RAS and HEC-2D models developed by the Hydrologic Engineering Center (HEC), a division of the US Army Corps of Engineers. The broader impacts of this study is the development of best practices for developing flood models in channelized river systems and in agricultural watersheds.

Smart Sensing and Recognition Based on Models of Neural Networks

DTIC Science & Technology

1990-11-15

9P-o ,yY𔄃-’. AD-A230 701 University of Pensylvania Philadelphia, PA 19104-6390 SMART SENSING AND RECOGNITION BASED ON MODELS OF NEURAL NETWORKS ... networks , photonic 1 implementations, nonlinear dynamical signal processing 9 ABSTRACT (Continue on reverse if necessary and identify by block number...not develop in isolation but in synergism with sensory organs and their feature forming networks . This means that development of artificial pattern

Systems analysis reveals a transcriptional reversal of the mesenchymal phenotype induced by SNAIL-inhibitor GN-25

PubMed Central

2013-01-01

Background HMLEs (HMLE-SNAIL and Kras-HMLE, Kras-HMLE-SNAIL pairs) serve as excellent model system to interrogate the effect of SNAIL targeted agents that reverse epithelial-to-mesenchymal transition (EMT). We had earlier developed a SNAIL-p53 interaction inhibitor (GN-25) that was shown to suppress SNAIL function. In this report, using systems biology and pathway network analysis, we show that GN-25 could cause reversal of EMT leading to mesenchymal-to-epithelial transition (MET) in a well-recognized HMLE-SNAIL and Kras-HMLE-SNAIL models. Results GN-25 induced MET was found to be consistent with growth inhibition, suppression of spheroid forming capacity and induction of apoptosis. Pathway network analysis of mRNA expression using microarrays from GN-25 treated Kras-HMLE-SNAIL cells showed an orchestrated global re-organization of EMT network genes. The expression signatures were validated at the protein level (down-regulation of mesenchymal markers such as TWIST1 and TWIST2 that was concurrent with up-regulation of epithelial marker E-Cadherin), and RNAi studies validated SNAIL dependent mechanism of action of the drug. Most importantly, GN-25 modulated many major transcription factors (TFs) such as inhibition of oncogenic TFs Myc, TBX2, NR3C1 and led to enhancement in the expression of tumor suppressor TFs such as SMAD7, DD1T3, CEBPA, HOXA5, TFEB, IRF1, IRF7 and XBP1, resulting in MET as well as cell death. Conclusions Our systems and network investigations provide convincing pre-clinical evidence in support of the clinical application of GN-25 for the reversal of EMT and thereby reducing cancer cell aggressiveness. PMID:24004452

Frontal hyperconnectivity related to discounting and reversal learning in cocaine subjects.

PubMed

Camchong, Jazmin; MacDonald, Angus W; Nelson, Brent; Bell, Christopher; Mueller, Bryon A; Specker, Sheila; Lim, Kelvin O

2011-06-01

Functional neuroimaging studies suggest that chronic cocaine use is associated with frontal lobe abnormalities. Functional connectivity (FC) alterations of cocaine-dependent individuals (CD), however, are not yet clear. This is the first study to our knowledge that examines resting FC of anterior cingulate cortex (ACC) in CD. Because ACC is known to integrate inputs from different brain regions to regulate behavior, we hypothesized that CD will have connectivity abnormalities in ACC networks. In addition, we hypothesized that abnormalities would be associated with poor performance in delayed discounting and reversal learning tasks. Resting functional magnetic resonance imaging data were collected to look for FC differences between 27 CD (5 women, age: M = 39.73, SD = 6.14 years) and 24 control subjects (5 women, age: M = 39.76, SD = 7.09 years). Participants were assessed with delayed discounting and reversal learning tasks. With seed-based FC measures, we examined FC in CD and control subjects within five ACC connectivity networks with seeds in subgenual, caudal, dorsal, rostral, and perigenual ACC. The CD showed increased FC within the perigenual ACC network in left middle frontal gyrus, ACC, and middle temporal gyrus when compared with control subjects. The FC abnormalities were significantly positively correlated with task performance in delayed discounting and reversal learning tasks in CD. The present study shows that participants with chronic cocaine-dependency have hyperconnectivity within an ACC network known to be involved in social processing and "mentalizing." In addition, FC abnormalities found in CD were associated with difficulties with delay rewards and slower adaptive learning. Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

NASA Researcher Examines an Aircraft Model with a Four-Fan Thrust Reverser

NASA Image and Video Library

1972-03-21

National Aeronautics and Space Administration (NASA) researcher John Carpenter inspects an aircraft model with a four-fan thrust reverser which would be studied in the 9- by 15-Foot Low Speed Wind Tunnel at the Lewis Research Center. Thrust reversers were introduced in the 1950s as a means for slowing high-speed jet aircraft during landing. Engineers sought to apply the technology to Vertical and Short Takeoff and Landing (VSTOL) aircraft in the 1970s. The new designs would have to take into account shorter landing areas, noise levels, and decreased thrust levels. A balance was needed between the thrust reverser’s efficiency, its noise generation, and the engine’s power setting. This model underwent a series of four tests in the 9- by 15-foot tunnel during April and May 1974. The model, with a high-wing configuration and no tail, was equipped with four thrust-reverser engines. The investigations included static internal aerodynamic tests on a single fan/reverser, wind tunnel isolated fan/reverser thrust tests, installation effects on a four-fan airplane model in a wind tunnel, and single reverser acoustic tests. The 9-by 15 was built inside the return leg of the 8- by 6-Foot Supersonic Wind Tunnel in 1968. The facility generates airspeeds from 0 to 175 miles per hour to evaluate the aerodynamic performance and acoustic characteristics of nozzles, inlets, and propellers, and investigate hot gas re-ingestion of advanced VSTOL concepts. John Carpenter was a technician in the Wind Tunnels Service Section of the Test Installations Division.

Reversible stress softening of collagen based networks from the jumbo squid mantle (Dosidicus gigas).

PubMed

Torres, F G; Troncoso, O P; Rivas, E R; Gomez, C G; Lopez, D

2014-04-01

Dosidicus gigas is the largest and one of the most abundant jumbo squids in the eastern Pacific Ocean. In this paper we have studied the muscle of the mantle of D. gigas (DGM). Morphological, thermal and rheological properties were assessed by means of atomic force microscopy, scanning electron microscopy, energy-dispersive X-ray spectroscopy, differential scanning calorimetry, thermogravimetry and oscillatory rheometry. This study allowed us to assess the morphological and rheological properties of a collagen based network occurring in nature. The results showed that the DGM network displays a nonlinear effect called reversible stress softening (RSS) that has been previously described for other types of biological structures such as naturally occurring cellulose networks and actin networks. We propose that the RSS could play a key role on the way jumbo squids withstand hydrostatic pressure. The results presented here confirm that this phenomenon occurs in a wider number of materials than previously thought, all of them exhibiting different size scales as well as physical conformation. Copyright © 2013 Elsevier B.V. All rights reserved.

Operationalizing Offensive Social Engineering for the Air Force

DTIC Science & Technology

2008-03-01

some concerns 2 of their members. The information was posted to a social networking site billing itself as military only but with no military ties. In...70 viii List of Figures Figure Page 1.1. Member Profile on a Social Networking Website [26] . . . . . . 3...Profile on a Social Networking Website [26] 1.3 Purpose Recognizing the advantages of social engineering and its current lack of incor- poration in the

The Integrated Distributed Virtual Research Network: An Introduction

DTIC Science & Technology

2014-06-01

Tom Kile , Theron Trout, and Gary Cohn for their extensive contribution to this document to include reviews, comments, and edits, which contributed...to the quality of the document. The ARL Integrated Distributed Virtual Research Testbed (IDVRT) team, consisting of Alex Tarantin, Khoa Bui, Tom Kile ...n. Network Engineer (non-voting member) Tom Kile o. Network Engineer (non-voting member) Theron Trout p. Non-voting members (serving at the

77 FR 7518 - Airworthiness Directives; The Boeing Company Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-13

... report that the top 3 inches of the aero/fire seals of the blocker doors on the thrust reverser torque... aero/fire seals of the blocker doors on the thrust reverser torque boxes on the engines, and replacing affected aero/fire seals with new, improved aero/fire seals. We are issuing this AD to prevent a fire in...

Teaching Mass Transfer and Filtration Using Crossflow Reverse Osmosis and Nanofiltration: An Experiment for the Undergraduate Unit Operations Lab

ERIC Educational Resources Information Center

Anastasio, Daniel; McCutcheon, Jeffrey

2012-01-01

A crossflow reverse osmosis (RO) system was built for a senior-level chemical engineering unit operations laboratory course. Intended to teach students mass transfer fundamentals related to membrane separations, students tested several commercial desalination membranes, measuring water flux and salt rejections at various pressures, flow rates, and…

Physics at the International Science and Engineering Fair.

ERIC Educational Resources Information Center

Walker, Jearl

1979-01-01

A judge for the physics projects for the 1979 International Science and Engineering Fair describes many of the more popular science projects. Projects described include the following: carbon dioxide and helium-neon lasers, reverse flame investigations, holography, construction of a magnetic bottle to confine plasma, and aerodynamic drag. (BT)

Towards the Engineering of Dependable P2P-Based Network Control — The Case of Timely Routing Control Messages

NASA Astrophysics Data System (ADS)

Tutschku, Kurt; Nakao, Akihiro

This paper introduces a methodology for engineering best-effort P2P algorithms into dependable P2P-based network control mechanism. The proposed method is built upon an iterative approach consisting of improving the original P2P algorithm by appropriate mechanisms and of thorough performance assessment with respect to dependability measures. The potential of the methodology is outlined by the example of timely routing control for vertical handover in B3G wireless networks. In detail, the well-known Pastry and CAN algorithms are enhanced to include locality. By showing how to combine algorithmic enhancements with performance indicators, this case study paves the way for future engineering of dependable network control mechanisms through P2P algorithms.

Incorporating time-delays in S-System model for reverse engineering genetic networks.

PubMed

Chowdhury, Ahsan Raja; Chetty, Madhu; Vinh, Nguyen Xuan

2013-06-18

In any gene regulatory network (GRN), the complex interactions occurring amongst transcription factors and target genes can be either instantaneous or time-delayed. However, many existing modeling approaches currently applied for inferring GRNs are unable to represent both these interactions simultaneously. As a result, all these approaches cannot detect important interactions of the other type. S-System model, a differential equation based approach which has been increasingly applied for modeling GRNs, also suffers from this limitation. In fact, all S-System based existing modeling approaches have been designed to capture only instantaneous interactions, and are unable to infer time-delayed interactions. In this paper, we propose a novel Time-Delayed S-System (TDSS) model which uses a set of delay differential equations to represent the system dynamics. The ability to incorporate time-delay parameters in the proposed S-System model enables simultaneous modeling of both instantaneous and time-delayed interactions. Furthermore, the delay parameters are not limited to just positive integer values (corresponding to time stamps in the data), but can also take fractional values. Moreover, we also propose a new criterion for model evaluation exploiting the sparse and scale-free nature of GRNs to effectively narrow down the search space, which not only reduces the computation time significantly but also improves model accuracy. The evaluation criterion systematically adapts the max-min in-degrees and also systematically balances the effect of network accuracy and complexity during optimization. The four well-known performance measures applied to the experimental studies on synthetic networks with various time-delayed regulations clearly demonstrate that the proposed method can capture both instantaneous and delayed interactions correctly with high precision. The experiments carried out on two well-known real-life networks, namely IRMA and SOS DNA repair network in Escherichia coli show a significant improvement compared with other state-of-the-art approaches for GRN modeling.

Social media networking: YouTube and search engine optimization.

PubMed

Jackson, Rem; Schneider, Andrew; Baum, Neil

2011-01-01

This is the third part of a three-part article on social media networking. This installment will focus on YouTube and search engine optimization. This article will explore the application of YouTube to the medical practice and how YouTube can help a practice retain its existing patients and attract new patients to the practice. The article will also describe the importance of search engine optimization and how to make your content appear on the first page of the search engines such as Google, Yahoo, and YouTube.

The logic of the floral transition: Reverse-engineering the switch controlling the identity of lateral organs.

PubMed

Dinh, Jean-Louis; Farcot, Etienne; Hodgman, Charlie

2017-09-01

Much laboratory work has been carried out to determine the gene regulatory network (GRN) that results in plant cells becoming flowers instead of leaves. However, this also involves the spatial distribution of different cell types, and poses the question of whether alternative networks could produce the same set of observed results. This issue has been addressed here through a survey of the published intercellular distribution of expressed regulatory genes and techniques both developed and applied to Boolean network models. This has uncovered a large number of models which are compatible with the currently available data. An exhaustive exploration had some success but proved to be unfeasible due to the massive number of alternative models, so genetic programming algorithms have also been employed. This approach allows exploration on the basis of both data-fitting criteria and parsimony of the regulatory processes, ruling out biologically unrealistic mechanisms. One of the conclusions is that, despite the multiplicity of acceptable models, an overall structure dominates, with differences mostly in alternative fine-grained regulatory interactions. The overall structure confirms the known interactions, including some that were not present in the training set, showing that current data are sufficient to determine the overall structure of the GRN. The model stresses the importance of relative spatial location, through explicit references to this aspect. This approach also provides a quantitative indication of how likely some regulatory interactions might be, and can be applied to the study of other developmental transitions.

Dynamic Coordination of Eu-Iminodiacetate to Control Fluorochromic Response of Polymer Hydrogels to Multistimuli.

PubMed

Weng, Gengsheng; Thanneeru, Srinivas; He, Jie

2018-03-01

New fluorochromic materials that reversibly change their emission properties in response to their environment are of interest for the development of sensors and light-emitting materials. A new design of Eu-containing polymer hydrogels showing fast self-healing and tunable fluorochromic properties in response to five different stimuli, including pH, temperature, metal ions, sonication, and force, is reported. The polymer hydrogels are fabricated using Eu-iminodiacetate (IDA) coordination in a hydrophilic poly(N,N-dimethylacrylamide) matrix. Dynamic metal-ligand coordination allows reversible formation and disruption of hydrogel networks under various stimuli which makes hydrogels self-healable and injectable. Such hydrogels show interesting switchable ON/OFF luminescence along with the sol-gel transition through the reversible formation and dissociation of Eu-IDA complexes upon various stimuli. It is demonstrated that Eu-containing hydrogels display fast and reversible mechanochromic response as well in hydrogels having interpenetrating polymer network. Those multistimuli responsive fluorochromic hydrogels illustrate a new pathway to make smart optical materials, particularly for biological sensors where multistimuli response is required. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Transonic Fan/Compressor Rotor Design Study. Volume 5

DTIC Science & Technology

1982-02-01

Fan Aircraft Engines Compressor Blade Thickness Rotor Camber Distribution Aerodesign Throat Margin Aerodynamics 20. ABStTRACT (Continue n reverse...Technology Branch FOR THE COMNANDER H. IV N BUS Director, Turbine Engine Division A If your address has changed, if you wish to be removed from our...ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK General Electric Ctmpany AREA & WORK UNIT NUMBERS Aircraft Engine Business Group Project 2307

Quiet Clean Short-haul Experimental Engine (QCSEE) Over-The-Wing (OTW) propulsion systems test report. Volume 4: Acoustic performance

NASA Technical Reports Server (NTRS)

Stimpert, D. L.

1979-01-01

A series of acoustic tests were conducted on the over the wing engine. These tests evaluated the fully suppressed noise levels in forward and reverse thrust operation and provided insight into the component noise sources of the engine plus the suppression achieved by various components. System noise levels using the contract specified calculation procedure indicate that the in-flight noise level on a 152 m sideline at takeoff and approach are 97.2 and 94.6 EPNdB, respectively, compared to a goal of 95.0 EPNdB. In reverse thrust, the system noise level was 106.1 PNdB compared to a goal of 100 PNdB. Baseline source noise levels agreed very well with pretest predictions. Inlet-radiated noise suppression of 14 PNdB was demonstrated with the high throat Mach number inlet at 0.79 throat Mach number.

Tensor network method for reversible classical computation

NASA Astrophysics Data System (ADS)

Yang, Zhi-Cheng; Kourtis, Stefanos; Chamon, Claudio; Mucciolo, Eduardo R.; Ruckenstein, Andrei E.

2018-03-01

We develop a tensor network technique that can solve universal reversible classical computational problems, formulated as vertex models on a square lattice [Nat. Commun. 8, 15303 (2017), 10.1038/ncomms15303]. By encoding the truth table of each vertex constraint in a tensor, the total number of solutions compatible with partial inputs and outputs at the boundary can be represented as the full contraction of a tensor network. We introduce an iterative compression-decimation (ICD) scheme that performs this contraction efficiently. The ICD algorithm first propagates local constraints to longer ranges via repeated contraction-decomposition sweeps over all lattice bonds, thus achieving compression on a given length scale. It then decimates the lattice via coarse-graining tensor contractions. Repeated iterations of these two steps gradually collapse the tensor network and ultimately yield the exact tensor trace for large systems, without the need for manual control of tensor dimensions. Our protocol allows us to obtain the exact number of solutions for computations where a naive enumeration would take astronomically long times.

Learning Data Set Influence on Identification Accuracy of Gas Turbine Neural Network Model

NASA Astrophysics Data System (ADS)

Kuznetsov, A. V.; Makaryants, G. M.

2018-01-01

There are many gas turbine engine identification researches via dynamic neural network models. It should minimize errors between model and real object during identification process. Questions about training data set processing of neural networks are usually missed. This article presents a study about influence of data set type on gas turbine neural network model accuracy. The identification object is thermodynamic model of micro gas turbine engine. The thermodynamic model input signal is the fuel consumption and output signal is the engine rotor rotation frequency. Four types input signals was used for creating training and testing data sets of dynamic neural network models - step, fast, slow and mixed. Four dynamic neural networks were created based on these types of training data sets. Each neural network was tested via four types test data sets. In the result 16 transition processes from four neural networks and four test data sets from analogous solving results of thermodynamic model were compared. The errors comparison was made between all neural network errors in each test data set. In the comparison result it was shown error value ranges of each test data set. It is shown that error values ranges is small therefore the influence of data set types on identification accuracy is low.

Using Long-Short-Term-Memory Recurrent Neural Networks to Predict Aviation Engine Vibrations

NASA Astrophysics Data System (ADS)

ElSaid, AbdElRahman Ahmed

This thesis examines building viable Recurrent Neural Networks (RNN) using Long Short Term Memory (LSTM) neurons to predict aircraft engine vibrations. The different networks are trained on a large database of flight data records obtained from an airline containing flights that suffered from excessive vibration. RNNs can provide a more generalizable and robust method for prediction over analytical calculations of engine vibration, as analytical calculations must be solved iteratively based on specific empirical engine parameters, and this database contains multiple types of engines. Further, LSTM RNNs provide a "memory" of the contribution of previous time series data which can further improve predictions of future vibration values. LSTM RNNs were used over traditional RNNs, as those suffer from vanishing/exploding gradients when trained with back propagation. The study managed to predict vibration values for 1, 5, 10, and 20 seconds in the future, with 2.84% 3.3%, 5.51% and 10.19% mean absolute error, respectively. These neural networks provide a promising means for the future development of warning systems so that suitable actions can be taken before the occurrence of excess vibration to avoid unfavorable situations during flight.

Network topology and parameter estimation: from experimental design methods to gene regulatory network kinetics using a community based approach

PubMed Central

2014-01-01

Background Accurate estimation of parameters of biochemical models is required to characterize the dynamics of molecular processes. This problem is intimately linked to identifying the most informative experiments for accomplishing such tasks. While significant progress has been made, effective experimental strategies for parameter identification and for distinguishing among alternative network topologies remain unclear. We approached these questions in an unbiased manner using a unique community-based approach in the context of the DREAM initiative (Dialogue for Reverse Engineering Assessment of Methods). We created an in silico test framework under which participants could probe a network with hidden parameters by requesting a range of experimental assays; results of these experiments were simulated according to a model of network dynamics only partially revealed to participants. Results We proposed two challenges; in the first, participants were given the topology and underlying biochemical structure of a 9-gene regulatory network and were asked to determine its parameter values. In the second challenge, participants were given an incomplete topology with 11 genes and asked to find three missing links in the model. In both challenges, a budget was provided to buy experimental data generated in silico with the model and mimicking the features of different common experimental techniques, such as microarrays and fluorescence microscopy. Data could be bought at any stage, allowing participants to implement an iterative loop of experiments and computation. Conclusions A total of 19 teams participated in this competition. The results suggest that the combination of state-of-the-art parameter estimation and a varied set of experimental methods using a few datasets, mostly fluorescence imaging data, can accurately determine parameters of biochemical models of gene regulation. However, the task is considerably more difficult if the gene network topology is not completely defined, as in challenge 2. Importantly, we found that aggregating independent parameter predictions and network topology across submissions creates a solution that can be better than the one from the best-performing submission. PMID:24507381

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

Wilson, Mark A.; Baljon, Arlette R. C.

The response of associating polymers with oscillatory shear is studied through large-scale simulations. A hybrid molecular dynamics (MD), Monte Carlo (MC) algorithm is employed. Polymer chains are modeled as a coarse-grained bead-spring system. Functionalized end groups, at both ends of the polymer chains, can form reversible bonds according to MC rules. Stress-strain curves show nonlinearities indicated by a non-ellipsoidal shape. We consider two types of nonlinearities. Type I occurs at a strain amplitude much larger than one, type II at a frequency at which the elastic storage modulus dominates the viscous loss modulus. In this last case, the network topologymore » resembles that of the system at rest. The reversible bonds are broken and chains stretch when the system moves away from the zero-strain position. For type I, the chains relax and the number of reversible bonds peaks when the system is near an extreme of the motion. During the movement to the other extreme of the cycle, first a stress overshoot occurs, then a yield accompanied by shear-banding. Lastly, the network restructures. Interestingly, the system periodically restores bonds between the same associating groups. Even though major restructuring occurs, the system remembers previous network topologies.« less

Copolymer Networks From Oligo(ε-caprolactone) and n-Butyl Acrylate Enable a Reversible Bidirectional Shape-Memory Effect at Human Body Temperature.

PubMed

Saatchi, Mersa; Behl, Marc; Nöchel, Ulrich; Lendlein, Andreas

2015-05-01

Exploiting the tremendous potential of the recently discovered reversible bidirectional shape-memory effect (rbSME) for biomedical applications requires switching temperatures in the physiological range. The recent strategy is based on the reduction of the melting temperature range (ΔT m ) of the actuating oligo(ε-caprolactone) (OCL) domains in copolymer networks from OCL and n-butyl acrylate (BA), where the reversible effect can be adjusted to the human body temperature. In addition, it is investigated whether an rbSME in the temperature range close or even above Tm,offset (end of the melting transition) can be obtained. Two series of networks having mixtures of OCLs reveal broad ΔTm s from 2 °C to 50 °C and from -10 °C to 37 °C, respectively. In cyclic, thermomechanical experiments the rbSME can be tailored to display pronounced actuation in a temperature interval between 20 °C and 37 °C. In this way, the application spectrum of the rbSME can be extended to biomedical applications. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cultured Neuronal Networks Express Complex Patterns of Activity and Morphological Memory

NASA Astrophysics Data System (ADS)

Raichman, Nadav; Rubinsky, Liel; Shein, Mark; Baruchi, Itay; Volman, Vladislav; Ben-Jacob, Eshel

The following sections are included: * Cultured Neuronal Networks * Recording the Network Activity * Network Engineering * The Formation of Synchronized Bursting Events * The Characterization of the SBEs * Highly-Active Neurons * Function-Form Relations in Cultured Networks * Analyzing the SBEs Motifs * Network Repertoire * Network under Hypothermia * Summary * Acknowledgments * References

Poly(Capro-Lactone) Networks as Actively Moving Polymers

NASA Astrophysics Data System (ADS)

Meng, Yuan

Shape-memory polymers (SMPs), as a subset of actively moving polymers, form an exciting class of materials that can store and recover elastic deformation energy upon application of an external stimulus. Although engineering of SMPs nowadays has lead to robust materials that can memorize multiple temporary shapes, and can be triggered by various stimuli such as heat, light, moisture, or applied magnetic fields, further commercialization of SMPs is still constrained by the material's incapability to store large elastic energy, as well as its inherent one-way shape-change nature. This thesis develops a series of model semi-crystalline shape-memory networks that exhibit ultra-high energy storage capacity, with accurately tunable triggering temperature; by introducing a second competing network, or reconfiguring the existing network under strained state, configurational chain bias can be effectively locked-in, and give rise to two-way shape-actuators that, in the absence of an external load, elongates upon cooling and reversibly contracts upon heating. We found that well-defined network architecture plays essential role on strain-induced crystallization and on the performance of cold-drawn shape-memory polymers. Model networks with uniform molecular weight between crosslinks, and specified functionality of each net-point, results in tougher, more elastic materials with a high degree of crystallinity and outstanding shape-memory properties. The thermal behavior of the model networks can be finely modified by introducing non-crystalline small molecule linkers that effectively frustrates the crystallization of the network strands. This resulted in shape-memory networks that are ultra-sensitive to heat, as deformed materials can be efficiently triggered to revert to its permanent state upon only exposure to body temperature. We also coupled the same reaction adopted to create the model network with conventional free-radical polymerization to prepare a dual-cure "double network" that behaves as a real thermal "actuator". This approach places sub-chains under different degrees of configurational bias within the network to utilize the material's propensity to undergo stress-induced crystallization. Reconfiguration of model shape-memory networks containing photo-sensitive linkages can also be employed to program two-way actuator. Chain reshuffling of a partially reconfigurable network is initiated upon exposure to light under specific strains. Interesting photo-induced creep and stress relaxation behaviors were demonstrated and understood based on a novel transient network model we derived. In summary, delicate manipulation of shape-memory network architectures addressed critical issues constraining the application of this type of functional polymer material. Strategies developed in this thesis may provide new opportunity to the field of shape-memory polymers.

Reliable design of a closed loop supply chain network under uncertainty: An interval fuzzy possibilistic chance-constrained model

NASA Astrophysics Data System (ADS)

Vahdani, Behnam; Tavakkoli-Moghaddam, Reza; Jolai, Fariborz; Baboli, Arman

2013-06-01

This article seeks to offer a systematic approach to establishing a reliable network of facilities in closed loop supply chains (CLSCs) under uncertainties. Facilities that are located in this article concurrently satisfy both traditional objective functions and reliability considerations in CLSC network designs. To attack this problem, a novel mathematical model is developed that integrates the network design decisions in both forward and reverse supply chain networks. The model also utilizes an effective reliability approach to find a robust network design. In order to make the results of this article more realistic, a CLSC for a case study in the iron and steel industry has been explored. The considered CLSC is multi-echelon, multi-facility, multi-product and multi-supplier. Furthermore, multiple facilities exist in the reverse logistics network leading to high complexities. Since the collection centres play an important role in this network, the reliability concept of these facilities is taken into consideration. To solve the proposed model, a novel interactive hybrid solution methodology is developed by combining a number of efficient solution approaches from the recent literature. The proposed solution methodology is a bi-objective interval fuzzy possibilistic chance-constraint mixed integer linear programming (BOIFPCCMILP). Finally, computational experiments are provided to demonstrate the applicability and suitability of the proposed model in a supply chain environment and to help decision makers facilitate their analyses.

Discovering novel phenotypes with automatically inferred dynamic models: a partial melanocyte conversion in Xenopus

NASA Astrophysics Data System (ADS)

Lobo, Daniel; Lobikin, Maria; Levin, Michael

2017-01-01

Progress in regenerative medicine requires reverse-engineering cellular control networks to infer perturbations with desired systems-level outcomes. Such dynamic models allow phenotypic predictions for novel perturbations to be rapidly assessed in silico. Here, we analyzed a Xenopus model of conversion of melanocytes to a metastatic-like phenotype only previously observed in an all-or-none manner. Prior in vivo genetic and pharmacological experiments showed that individual animals either fully convert or remain normal, at some characteristic frequency after a given perturbation. We developed a Machine Learning method which inferred a model explaining this complex, stochastic all-or-none dataset. We then used this model to ask how a new phenotype could be generated: animals in which only some of the melanocytes converted. Systematically performing in silico perturbations, the model predicted that a combination of altanserin (5HTR2 inhibitor), reserpine (VMAT inhibitor), and VP16-XlCreb1 (constitutively active CREB) would break the all-or-none concordance. Remarkably, applying the predicted combination of three reagents in vivo revealed precisely the expected novel outcome, resulting in partial conversion of melanocytes within individuals. This work demonstrates the capability of automated analysis of dynamic models of signaling networks to discover novel phenotypes and predictively identify specific manipulations that can reach them.

The August 1st, 2014 ( M w 5.3) Moderate Earthquake: Evidence for an Active Thrust Fault in the Bay of Algiers (Algeria)

NASA Astrophysics Data System (ADS)

Benfedda, A.; Abbes, K.; Bouziane, D.; Bouhadad, Y.; Slimani, A.; Larbes, S.; Haddouche, D.; Bezzeghoud, M.

2017-03-01

On August 1st, 2014, a moderate-sized earthquake struck the capital city of Algiers at 05:11:17.6 (GMT+1). The earthquake caused the death of six peoples and injured 420, mainly following a panic movement among the population. Following the main shock, we surveyed the aftershock activity using a portable seismological network (short period), installed from August 2nd, 2014 to August 21st, 2015. In this work, first, we determined the main shock epicenter using the accelerograms recorded by the Algerian accelerograph network (under the coordination of the National Center of Applied Research in Earthquake Engineering-CGS). We calculated the focal mechanism of the main shock, using the inversion of the accelerograph waveforms in displacement that provides a reverse fault with a slight right-lateral component of slip and a compression axis striking NNW-SSE. The obtained scalar seismic moment ( M o = 1.25 × 1017 Nm) corresponds to a moment magnitude of M w = 5.3. Second, the analysis of the obtained aftershock swarm, of the survey, suggests an offshore ENE-WSW, trending and NNW dipping, causative active fault in the bay of Algiers, which may likely correspond to an offshore unknown segment of the Sahel active fault.

Angelman syndrome: current understanding and research prospects.

PubMed

Dan, Bernard

2009-11-01

Angelman syndrome is a neurogenetic disorder characterized by developmental delay, severe intellectual disability, absent speech, exuberant behavior with happy demeanor, motor impairment, and epilepsy, due to deficient UBE3A gene expression that may be caused by various abnormalities of chromosome 15. Recent findings in animal models demonstrated altered dendritic spine formation as well as both synaptic [including gamma-aminobutyric acid (GABA)(A) and N-methyl-D-aspartate (NMDA) transmission] and nonsynaptic (including gap junction) influences in various brain regions, including hippocampus and cerebellar cortex. Reversal of selected abnormalities in rescue genetically engineered animal models is encouraging, although it should not be misinterpreted as promising "cure" for affected patients. Much research is still required to fully understand the functional links between lack of UBE3A expression and clinical manifestations of Angelman syndrome. Studies of regulation of UBE3A expression, including imprinting-related methylation, may point to possibilities of therapeutic upregulation. Understanding relevant roles of the gene product might lead to targeted intervention. Further documentation of brain network dynamics, with particular emphasis on hippocampus, thalamocortical, and cerebellar networks is needed, including in a developmental perspective. There is also a need for further clinical research for improving management of problems such as epilepsy, behavior, communication, learning, motor impairment, and sleep disturbances.

An ensemble of dynamic neural network identifiers for fault detection and isolation of gas turbine engines.

PubMed

Amozegar, M; Khorasani, K

2016-04-01

In this paper, a new approach for Fault Detection and Isolation (FDI) of gas turbine engines is proposed by developing an ensemble of dynamic neural network identifiers. For health monitoring of the gas turbine engine, its dynamics is first identified by constructing three separate or individual dynamic neural network architectures. Specifically, a dynamic multi-layer perceptron (MLP), a dynamic radial-basis function (RBF) neural network, and a dynamic support vector machine (SVM) are trained to individually identify and represent the gas turbine engine dynamics. Next, three ensemble-based techniques are developed to represent the gas turbine engine dynamics, namely, two heterogeneous ensemble models and one homogeneous ensemble model. It is first shown that all ensemble approaches do significantly improve the overall performance and accuracy of the developed system identification scheme when compared to each of the stand-alone solutions. The best selected stand-alone model (i.e., the dynamic RBF network) and the best selected ensemble architecture (i.e., the heterogeneous ensemble) in terms of their performances in achieving an accurate system identification are then selected for solving the FDI task. The required residual signals are generated by using both a single model-based solution and an ensemble-based solution under various gas turbine engine health conditions. Our extensive simulation studies demonstrate that the fault detection and isolation task achieved by using the residuals that are obtained from the dynamic ensemble scheme results in a significantly more accurate and reliable performance as illustrated through detailed quantitative confusion matrix analysis and comparative studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Enhancement of Teaching and Learning of the Fundamentals of Nuclear Engineering Using Multimedia Courseware.

ERIC Educational Resources Information Center

Keyvan, Shahla A.; Pickard, Rodney; Song, Xiaolong

1997-01-01

Computer-aided instruction incorporating interactive multimedia and network technologies can boost teaching effectiveness and student learning. This article describes the development and implementation of network server-based interactive multimedia courseware for a fundamental course in nuclear engineering. A student survey determined that 80% of…

Small-scale heat detection using catalytic microengines irradiated by laser

NASA Astrophysics Data System (ADS)

Liu, Zhaoqian; Li, Jinxing; Wang, Jiao; Huang, Gaoshan; Liu, Ran; Mei, Yongfeng

2013-01-01

We demonstrate a novel approach to modulating the motion speed of catalytic microtubular engines via laser irradiation/heating with regard to small-scale heat detection. Laser irradiation on the engines leads to a thermal heating effect and thus enhances the engine speed. During a laser on/off period, the motion behaviour of a microengine can be repeatable and reversible, demonstrating a regulation of motion speeds triggered by laser illumination. Also, the engine velocity exhibits a linear dependence on laser power in various fuel concentrations, which implies an application potential as local heat sensors. Our work may hold great promise in applications such as lab on a chip, micro/nano factories, and environmental detection.We demonstrate a novel approach to modulating the motion speed of catalytic microtubular engines via laser irradiation/heating with regard to small-scale heat detection. Laser irradiation on the engines leads to a thermal heating effect and thus enhances the engine speed. During a laser on/off period, the motion behaviour of a microengine can be repeatable and reversible, demonstrating a regulation of motion speeds triggered by laser illumination. Also, the engine velocity exhibits a linear dependence on laser power in various fuel concentrations, which implies an application potential as local heat sensors. Our work may hold great promise in applications such as lab on a chip, micro/nano factories, and environmental detection. Electronic supplementary information (ESI) available. See DOI: 10.1039/c2nr32494f

The deep space network

NASA Technical Reports Server (NTRS)

1977-01-01

Presented is Deep Space Network (DSN) progress in flight project support, tracking and data acquisition (TDA) research and technology, network engineering, hardware and software implementation, and operations.

The deep space network

NASA Technical Reports Server (NTRS)

1975-01-01

Summaries are given of Deep Space Network progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations.

[Veneer computer aided design based on reverse engineering technology].

PubMed

Liu, Ming-li; Chen, Xiao-dong; Wang, Yong

2012-03-01

To explore the computer aided design (CAD) method of veneer restoration, and to assess if the solution can help prosthesis meet morphology esthetics standard. A volunteer's upper right central incisor needed to be restored with veneer. Super hard stone models of patient's dentition (before and after tooth preparation) were scanned with the three-dimensional laser scanner. The veneer margin was designed as butt-to-butt type. The veneer was constructed using reverse engineering (RE) software. The technique guideline of veneers CAD was explore based on RE software, and the veneers was smooth, continuous and symmetrical, which met esthetics construction needs. It was a feasible method to reconstruct veneer restoration based on RE technology.

GUI Type Fault Diagnostic Program for a Turboshaft Engine Using Fuzzy and Neural Networks

NASA Astrophysics Data System (ADS)

Kong, Changduk; Koo, Youngju

2011-04-01

The helicopter to be operated in a severe flight environmental condition must have a very reliable propulsion system. On-line condition monitoring and fault detection of the engine can promote reliability and availability of the helicopter propulsion system. A hybrid health monitoring program using Fuzzy Logic and Neural Network Algorithms can be proposed. In this hybrid method, the Fuzzy Logic identifies easily the faulted components from engine measuring parameter changes, and the Neural Networks can quantify accurately its identified faults. In order to use effectively the fault diagnostic system, a GUI (Graphical User Interface) type program is newly proposed. This program is composed of the real time monitoring part, the engine condition monitoring part and the fault diagnostic part. The real time monitoring part can display measuring parameters of the study turboshaft engine such as power turbine inlet temperature, exhaust gas temperature, fuel flow, torque and gas generator speed. The engine condition monitoring part can evaluate the engine condition through comparison between monitoring performance parameters the base performance parameters analyzed by the base performance analysis program using look-up tables. The fault diagnostic part can identify and quantify the single faults the multiple faults from the monitoring parameters using hybrid method.

Update of GRASP/Ada reverse engineering tools for Ada

NASA Technical Reports Server (NTRS)

Cross, James H., II

1992-01-01

The GRASP/Ada project (Graphical Representations of Algorithms, Structures, and Processes for Ada) has successfully created and prototyped a new algorithmic level graphical representation of Ada software, the Control Structure Diagram (CSD). The primary impetus for creation of the CSD was to improve the comprehension efficiency of Ada software and, as a result, improve reliability and reduce costs. The emphasis was on the automatic generation of the CSD from Ada PDL or source code to support reverse engineering and maintenance. The CSD has the potential to replace traditional prettyprinted Ada source code. In Phase 1 of the GRASP/Ada project, the CSD graphical constructs were created and applied manually to several small Ada programs. A prototype (Version 1) was designed and implemented using FLEX and BISON running under VMS on a VAS 11-780. In Phase 2, the prototype was improved and ported to the Sun 4 platform under UNIX. A user interface was designed and partially implemented using the HP widget toolkit and the X Windows System. In Phase 3, the user interface was extensively reworked using the Athena widget toolkit and X Windows. The prototype was applied successfully to numerous Ada programs ranging in size from several hundred to several thousand lines of source code. Following Phase 3, the prototype was evaluated by software engineering students at Auburn University and then updated with significant enhancements to the user interface including editing capabilities. Version 3.2 of the prototype was prepared for limited distribution to facilitate further evaluation. The current prototype provides the capability for the user to generate CSD's from Ada PDL or source code in a reverse engineering as well as forward engineering mode with a level of flexibility suitable for practical application.

Angiogenesis in tissue engineering: from concept to the vascularization of scaffold construct

NASA Astrophysics Data System (ADS)

Amirah Ishak, Siti; Pangestu Djuansjah, J. R.; Kadir, M. R. Abdul; Sukmana, Irza

2014-06-01

Angiogenesis, the formation of micro-vascular network from the preexisting vascular vessels, has been studied in the connection to the normal developmental process as well as numerous diseases. In tissue engineering research, angiogenesis is also essential to promote micro-vascular network inside engineered tissue constructs, mimicking a functional blood vessel in vivo. Micro-vascular network can be used to maintain adequate tissue oxygenation, nutrient transfer and waste removal. One of the problems faced by angiogenesis researchers is to find suitable in vitro assays and methods for assessing the effect of regulators on angiogenesis and micro-vessel formation. The assay would be reliable and repeatable with easily quantifiable with physiologically relevant. This review aims to highlights recent advanced and future challenges in developing and using an in vitro angiogenesis assay for the application on biomedical and tissue engineering research.

Dynamic traffic grooming with Spectrum Engineering (TG-SE) in flexible grid optical networks

NASA Astrophysics Data System (ADS)

Yu, Xiaosong; Zhao, Yongli; Zhang, Jiawei; Wang, Jianping; Zhang, Guoying; Chen, Xue; Zhang, Jie

2015-12-01

Flexible grid has emerged as an evolutionary technology to satisfy the ever increasing demand for higher spectrum efficiency and operational flexibility. To optimize the spectrum resource utilization, this paper introduces the concept of Spectrum Engineering in flex-grid optical networks. The sliceable optical transponder has been proposed to offload IP traffic to the optical layer and reduce the number of IP router ports and transponders. We discuss the impact of sliceable transponder in traffic grooming and propose several traffic-grooming schemes with Spectrum Engineering (TG-SE). Our results show that there is a tradeoff among different traffic grooming policies, which should be adopted based on the network operator's objectives. The proposed traffic grooming with Spectrum Engineering schemes can reduce OPEX as well as increase spectrum efficiency by efficiently utilizing the bandwidth variability and capability of sliceable optical transponders.

'can i get your Email': Gender, Networking and Social Capital in AN Undergraduate Bioengineering Classroom

NASA Astrophysics Data System (ADS)

Erickson, Shelley K.

Based on observations and interviews, this article explores how female and male biomedical engineering students network and generate social capital (who one knows) in an undergraduate classroom. Stark differences were observed between female and male students and their interactions with a series of guest lecturers. Although women engineering students may be differentially affected by how they raise their social capital, this study does not suggest that women engineering students are wholly incapable of raising their social capital. Rather, a disconnect occurs between the student population receiving information about networking and women students acting on informal and spontaneous opportunities as they arise. Institutional and departmental support (i.e., internship programs and discussion in the classroom and at orientation) appears to favor those who rely on more formal means of networking.

Hydrogen adsorption and desorption with 3D silicon nanotube-network and film-network structures: Monte Carlo simulations

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

Li, Ming; Kang, Zhan, E-mail: zhankang@dlut.edu.cn; Huang, Xiaobo

2015-08-28

Hydrogen is clean, sustainable, and renewable, thus is viewed as promising energy carrier. However, its industrial utilization is greatly hampered by the lack of effective hydrogen storage and release method. Carbon nanotubes (CNTs) were viewed as one of the potential hydrogen containers, but it has been proved that pure CNTs cannot attain the desired target capacity of hydrogen storage. In this paper, we present a numerical study on the material-driven and structure-driven hydrogen adsorption of 3D silicon networks and propose a deformation-driven hydrogen desorption approach based on molecular simulations. Two types of 3D nanostructures, silicon nanotube-network (Si-NN) and silicon film-networkmore » (Si-FN), are first investigated in terms of hydrogen adsorption and desorption capacity with grand canonical Monte Carlo simulations. It is revealed that the hydrogen storage capacity is determined by the lithium doping ratio and geometrical parameters, and the maximum hydrogen uptake can be achieved by a 3D nanostructure with optimal configuration and doping ratio obtained through design optimization technique. For hydrogen desorption, a mechanical-deformation-driven-hydrogen-release approach is proposed. Compared with temperature/pressure change-induced hydrogen desorption method, the proposed approach is so effective that nearly complete hydrogen desorption can be achieved by Si-FN nanostructures under sufficient compression but without structural failure observed. The approach is also reversible since the mechanical deformation in Si-FN nanostructures can be elastically recovered, which suggests a good reusability. This study may shed light on the mechanism of hydrogen adsorption and desorption and thus provide useful guidance toward engineering design of microstructural hydrogen (or other gas) adsorption materials.« less

Coupling of protein localization and cell movements by a dynamically localized response regulator in Myxococcus xanthus

PubMed Central

Leonardy, Simone; Freymark, Gerald; Hebener, Sabrina; Ellehauge, Eva; Søgaard-Andersen, Lotte

2007-01-01

Myxococcus xanthus cells harbor two motility machineries, type IV pili (Tfp) and the A-engine. During reversals, the two machineries switch polarity synchronously. We present a mechanism that synchronizes this polarity switching. We identify the required for motility response regulator (RomR) as essential for A-motility. RomR localizes in a bipolar, asymmetric pattern with a large cluster at the lagging cell pole. The large RomR cluster relocates to the new lagging pole in parallel with cell reversals. Dynamic RomR localization is essential for cell reversals, suggesting that RomR relocalization induces the polarity switching of the A-engine. The analysis of RomR mutants shows that the output domain targets RomR to the poles and the receiver domain is essential for dynamic localization. The small GTPase MglA establishes correct RomR polarity, and the Frz two-component system regulates dynamic RomR localization. FrzS localizes with Tfp at the leading pole and relocates in an Frz-dependent manner to the opposite pole during reversals; FrzS and RomR localize and oscillate independently. The Frz system synchronizes these oscillations and thus the synchronous polarity switching of the motility machineries. PMID:17932488

Adaptive significance of right hemisphere activation in aphasic language comprehension

PubMed Central

Meltzer, Jed A.; Wagage, Suraji; Ryder, Jennifer; Solomon, Beth; Braun, Allen R.

2013-01-01

Aphasic patients often exhibit increased right hemisphere activity during language tasks. This may represent takeover of function by regions homologous to the left-hemisphere language networks, maladaptive interference, or adaptation of alternate compensatory strategies. To distinguish between these accounts, we tested language comprehension in 25 aphasic patients using an online sentence-picture matching paradigm while measuring brain activation with MEG. Linguistic conditions included semantically irreversible (“The boy is eating the apple”) and reversible (“The boy is pushing the girl”) sentences at three levels of syntactic complexity. As expected, patients performed well above chance on irreversible sentences, and at chance on reversible sentences of high complexity. Comprehension of reversible non-complex sentences ranged from nearly perfect to chance, and was highly correlated with offline measures of language comprehension. Lesion analysis revealed that comprehension deficits for reversible sentences were predicted by damage to the left temporal lobe. Although aphasic patients activated homologous areas in the right temporal lobe, such activation was not correlated with comprehension performance. Rather, patients with better comprehension exhibited increased activity in dorsal fronto-parietal regions. Correlations between performance and dorsal network activity occurred bilaterally during perception of sentences, and in the right hemisphere during a post-sentence memory delay. These results suggest that effortful reprocessing of perceived sentences in short-term memory can support improved comprehension in aphasia, and that strategic recruitment of alternative networks, rather than homologous takeover, may account for some findings of right hemisphere language activation in aphasia. PMID:23566891

The application of neural networks to the SSME startup transient

NASA Technical Reports Server (NTRS)

Meyer, Claudia M.; Maul, William A.

1991-01-01

Feedforward neural networks were used to model three parameters during the Space Shuttle Main Engine startup transient. The three parameters were the main combustion chamber pressure, a controlled parameter, the high pressure oxidizer turbine discharge temperature, a redlined parameter, and the high pressure fuel pump discharge pressure, a failure-indicating performance parameter. Network inputs consisted of time windows of data from engine measurements that correlated highly to the modeled parameter. A standard backpropagation algorithm was used to train the feedforward networks on two nominal firings. Each trained network was validated with four additional nominal firings. For all three parameters, the neural networks were able to accurately predict the data in the validation sets as well as the training set.

Architectural and engineering issues for building an optical Internet

NASA Astrophysics Data System (ADS)

St. Arnaud, Bill

1998-10-01

Recent developments in high density Wave Division Multiplexing fiber systems allows for the deployment of a dedicated optical Internet network for large volume backbone pipes that does not require an underlying multi-service SONET/SDH and ATM transport protocol. Some intrinsic characteristics of Internet traffic such as its self similar nature, server bound congestion, routing and data asymmetry allow for highly optimized traffic engineered networks using individual wavelengths. By transmitting GigaBit Ethernet or SONET/SDH frames natively over WDM wavelengths that directly interconnect high performance routers the original concept of the Internet as an intrinsically survivable datagram network is possible. Traffic engineering, restoral, protection and bandwidth management of the network must now be carried out at the IP layer and so new routing or switching protocols such as MPLS that allow for uni- directional paths with fast restoral and protection at the IP layer become essential for a reliable production network. The deployment of high density WDM municipal and campus networks also gives carriers and ISPs the flexibility to offer customers as integrated and seamless set of optical Internet services.

A function approximation approach to anomaly detection in propulsion system test data

NASA Technical Reports Server (NTRS)

Whitehead, Bruce A.; Hoyt, W. A.

1993-01-01

Ground test data from propulsion systems such as the Space Shuttle Main Engine (SSME) can be automatically screened for anomalies by a neural network. The neural network screens data after being trained with nominal data only. Given the values of 14 measurements reflecting external influences on the SSME at a given time, the neural network predicts the expected nominal value of a desired engine parameter at that time. We compared the ability of three different function-approximation techniques to perform this nominal value prediction: a novel neural network architecture based on Gaussian bar basis functions, a conventional back propagation neural network, and linear regression. These three techniques were tested with real data from six SSME ground tests containing two anomalies. The basis function network trained more rapidly than back propagation. It yielded nominal predictions with, a tight enough confidence interval to distinguish anomalous deviations from the nominal fluctuations in an engine parameter. Since the function-approximation approach requires nominal training data only, it is capable of detecting unknown classes of anomalies for which training data is not available.

Bile Salt Mediated Growth of Reverse Wormlike Micelles in Nonpolar Liquids

NASA Astrophysics Data System (ADS)

Tung, Shih-Huang; Huang, Yi-En; Raghavan, Srinivasa

2006-03-01

We report the growth of reverse wormlike micelles induced by the addition of a bile salt in trace amounts to solutions of the phospholipid, lecithin in nonpolar organic solvents. Previous recipes for reverse wormlike micelles have usually required the addition of water to induce reverse micellar growth; here, we show that bile salts, due to their unique ``facially amphiphilic'' structure, can play a role analogous to water and promote the longitudinal aggregation of lecithin molecules into reverse micellar chains. The formation of transient entangled networks of these reverse micelles transforms low-viscosity lecithin organosols into strongly viscoelastic fluids. The zero-shear viscosity increases by more than five orders of magnitude, and it is the molar ratio of bile salt to lecithin that controls this viscosity enhancement. The growth of reverse wormlike micelles is also confirmed by small-angle neutron scattering (SANS) experiments on these fluids.

14 CFR 25.1103 - Induction system ducts and air duct systems.

Code of Federal Regulations, 2013 CFR

2013-01-01

... between which relative motion could exist must have means for flexibility. (d) For turbine engine and... stage of the engine supercharger and of the auxiliary power unit compressor must have a drain to prevent... compartment to prevent hot gas reverse flow from burning through auxiliary power unit ducts and entering any...

DC-9 Flight Demonstration Program with Refanned JT8D Engines. Volume 3; Performance and Analysis

NASA Technical Reports Server (NTRS)

1975-01-01

The JT8D-109 engine has a sea level static, standard day bare engine takeoff thrust of 73,840 N. At sea level standard day conditions the additional thrust of the JT8D-109 results in 2,040 kg additional takeoff gross weight capability for a given field length. Range loss of the DC-9 Refan airplane for long range cruise was determined. The Refan airplane demonstrated stall, static longitudinal stability, longitudinal control, longitudinal trim, minimum control speeds, and directional control characteristics similar to the DC-9-30 production airplane and complied with airworthiness requirements. Cruise, climb, and thrust reverser performance were evaluated. Structural and dynamic ground test, flight test and analytical results substantiate Refan Program requirements that the nacelle, thrust reverser hardware, and the airplane structural modifications are flightworthy and certifiable and that the airplane meets flutter speed margins. Estimated unit cost of a DC-9 Refan retrofit program is 1.338 million in mid-1975 dollars with about an equal split in cost between airframe and engine.

Using Web 2.0 Techniques in NASA's Ares Engineering Operations Network (AEON) Environment - First Impressions

NASA Technical Reports Server (NTRS)

Scott, David W.

2010-01-01

The Mission Operations Laboratory (MOL) at Marshall Space Flight Center (MSFC) is responsible for Engineering Support capability for NASA s Ares rocket development and operations. In pursuit of this, MOL is building the Ares Engineering and Operations Network (AEON), a web-based portal to support and simplify two critical activities: Access and analyze Ares manufacturing, test, and flight performance data, with access to Shuttle data for comparison Establish and maintain collaborative communities within the Ares teams/subteams and with other projects, e.g., Space Shuttle, International Space Station (ISS). AEON seeks to provide a seamless interface to a) locally developed engineering applications and b) a Commercial-Off-The-Shelf (COTS) collaborative environment that includes Web 2.0 capabilities, e.g., blogging, wikis, and social networking. This paper discusses how Web 2.0 might be applied to the typically conservative engineering support arena, based on feedback from Integration, Verification, and Validation (IV&V) testing and on searching for their use in similar environments.

An airline study of advanced technology requirements for advanced high speed commercial transport engines. 1: Engine design study assessment

NASA Technical Reports Server (NTRS)

Sallee, G. P.

1973-01-01

The advanced technology requirements for an advanced high speed commercial tranport engine are presented. The results of the phase 1 study effort cover the following areas: (1) statement of an airline's major objectives for future transport engines, (2) airline's method of evaluating engine proposals, (3) description of an optimum engine for a long range subsonic commercial transport including installation and critical design features, (4) discussion of engine performance problems and experience with performance degradation, (5) trends in engine and pod prices with increasing technology and objectives for the future, (6) discussion of the research objectives for composites, reversers, advanced components, engine control systems, and devices to reduce the impact of engine stall, and (7) discussion of the airline objectives for noise and pollution reduction.

Optical interconnections and networks; Proceedings of the Meeting, The Hague, Netherlands, Mar. 14, 15, 1990

NASA Technical Reports Server (NTRS)

Bartelt, Hartmut (Editor)

1990-01-01

The conference presents papers on interconnections, clock distribution, neural networks, and components and materials. Particular attention is given to a comparison of optical and electrical data interconnections at the board and backplane levels, a wafer-level optical interconnection network layout, an analysis and simulation of photonic switch networks, and the integration of picosecond GaAs photoconductive devices with silicon circuits for optical clocking and interconnects. Consideration is also given to the optical implementation of neural networks, invariance in an optoelectronic implementation of neural networks, and the recording of reversible patterns in polymer lightguides.

Complex systems in metabolic engineering.

PubMed

Winkler, James D; Erickson, Keesha; Choudhury, Alaksh; Halweg-Edwards, Andrea L; Gill, Ryan T

2015-12-01

Metabolic engineers manipulate intricate biological networks to build efficient biological machines. The inherent complexity of this task, derived from the extensive and often unknown interconnectivity between and within these networks, often prevents researchers from achieving desired performance. Other fields have developed methods to tackle the issue of complexity for their unique subset of engineering problems, but to date, there has not been extensive and comprehensive examination of how metabolic engineers use existing tools to ameliorate this effect on their own research projects. In this review, we examine how complexity affects engineering at the protein, pathway, and genome levels within an organism, and the tools for handling these issues to achieve high-performing strain designs. Quantitative complexity metrics and their applications to metabolic engineering versus traditional engineering fields are also discussed. We conclude by predicting how metabolic engineering practices may advance in light of an explicit consideration of design complexity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neural network application to comprehensive engine diagnostics

NASA Technical Reports Server (NTRS)

Marko, Kenneth A.

1994-01-01

We have previously reported on the use of neural networks for detection and identification of faults in complex microprocessor controlled powertrain systems. The data analyzed in those studies consisted of the full spectrum of signals passing between the engine and the real-time microprocessor controller. The specific task of the classification system was to classify system operation as nominal or abnormal and to identify the fault present. The primary concern in earlier work was the identification of faults, in sensors or actuators in the powertrain system as it was exercised over its full operating range. The use of data from a variety of sources, each contributing some potentially useful information to the classification task, is commonly referred to as sensor fusion and typifies the type of problems successfully addressed using neural networks. In this work we explore the application of neural networks to a different diagnostic problem, the diagnosis of faults in newly manufactured engines and the utility of neural networks for process control.

A Network Scheduling Model for Distributed Control Simulation

NASA Technical Reports Server (NTRS)

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

2016-01-01

Distributed engine control is a hardware technology that radically alters the architecture for aircraft engine control systems. Of its own accord, it does not change the function of control, rather it seeks to address the implementation issues for weight-constrained vehicles that can limit overall system performance and increase life-cycle cost. However, an inherent feature of this technology, digital communication networks, alters the flow of information between critical elements of the closed-loop control. Whereas control information has been available continuously in conventional centralized control architectures through virtue of analog signaling, moving forward, it will be transmitted digitally in serial fashion over the network(s) in distributed control architectures. An underlying effect is that all of the control information arrives asynchronously and may not be available every loop interval of the controller, therefore it must be scheduled. This paper proposes a methodology for modeling the nominal data flow over these networks and examines the resulting impact for an aero turbine engine system simulation.

MX Resident Engineer Networking Guide.

DTIC Science & Technology

1982-04-01

FIGURES 6 INTRODUCTION ............................................................ 11 Background Approach Purpose Scope 2 SYSTEM OVERVIEW...RESIDENT ENGINEER NETWORKING GUIDE 1 INTRODUCTION Background The Network Analysis System (NAS) is not a new planning method. It has been used for more than...DEVELOPMENT RUN DATE 19MAY7’ 2359MRS S U M M A R I P A Y N L N T S S T A I I M E N I PROJECT START jAUG ?? PROJECT EXR 4 L1 SAMPLE PNOPLEM *ACTIVITT-YN

The deep space network

NASA Technical Reports Server (NTRS)

1977-01-01

A Deep Space Network progress report is presented dealing with in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations.

Application of Fuzzy-Logic Controller and Neural Networks Controller in Gas Turbine Speed Control and Overheating Control and Surge Control on Transient Performance

NASA Astrophysics Data System (ADS)

Torghabeh, A. A.; Tousi, A. M.

2007-08-01

This paper presents Fuzzy Logic and Neural Networks approach to Gas Turbine Fuel schedules. Modeling of non-linear system using feed forward artificial Neural Networks using data generated by a simulated gas turbine program is introduced. Two artificial Neural Networks are used , depicting the non-linear relationship between gas generator speed and fuel flow, and turbine inlet temperature and fuel flow respectively . Off-line fast simulations are used for engine controller design for turbojet engine based on repeated simulation. The Mamdani and Sugeno models are used to expression the Fuzzy system . The linguistic Fuzzy rules and membership functions are presents and a Fuzzy controller will be proposed to provide an Open-Loop control for the gas turbine engine during acceleration and deceleration . MATLAB Simulink was used to apply the Fuzzy Logic and Neural Networks analysis. Both systems were able to approximate functions characterizing the acceleration and deceleration schedules . Surge and Flame-out avoidance during acceleration and deceleration phases are then checked . Turbine Inlet Temperature also checked and controls by Neural Networks controller. This Fuzzy Logic and Neural Network Controllers output results are validated and evaluated by GSP software . The validation results are used to evaluate the generalization ability of these artificial Neural Networks and Fuzzy Logic controllers.

Engineering technology for networks

NASA Technical Reports Server (NTRS)

Paul, Arthur S.; Benjamin, Norman

1991-01-01

Space Network (SN) modeling and evaluation are presented. The following tasks are included: Network Modeling (developing measures and metrics for SN, modeling of the Network Control Center (NCC), using knowledge acquired from the NCC to model the SNC, and modeling the SN); and Space Network Resource scheduling.

Reverse engineering of an affinity-switchable molecular interaction characterized by atomic force microscopy single-molecule force spectroscopy.

PubMed

Anselmetti, Dario; Bartels, Frank Wilco; Becker, Anke; Decker, Björn; Eckel, Rainer; McIntosh, Matthew; Mattay, Jochen; Plattner, Patrik; Ros, Robert; Schäfer, Christian; Sewald, Norbert

2008-02-19

Tunable and switchable interaction between molecules is a key for regulation and control of cellular processes. The translation of the underlying physicochemical principles to synthetic and switchable functional entities and molecules that can mimic the corresponding molecular functions is called reverse molecular engineering. We quantitatively investigated autoinducer-regulated DNA-protein interaction in bacterial gene regulation processes with single atomic force microscopy (AFM) molecule force spectroscopy in vitro, and developed an artificial bistable molecular host-guest system that can be controlled and regulated by external signals (UV light exposure and thermal energy). The intermolecular binding functionality (affinity) and its reproducible and reversible switching has been proven by AFM force spectroscopy at the single-molecule level. This affinity-tunable optomechanical switch will allow novel applications with respect to molecular manipulation, nanoscale rewritable molecular memories, and/or artificial ion channels, which will serve for the controlled transport and release of ions and neutral compounds in the future.

Reversible S-nitrosylation in an engineered azurin

DOE PAGES

Tian, Shiliang; Liu, Jing; Cowley, Ryan E.; ...

2016-04-25

Here, S-Nitrosothiols are known as reagents for NO storage and transportation and as regulators in many physiological processes. Although the S-nitrosylation catalysed by haem proteins is well known, no direct evidence of S-nitrosylation in copper proteins has been reported. Here, we report reversible insertion of NO into a copper–thiolate bond in an engineered copper centre in Pseudomonas aeruginosa azurin by rational design of the primary coordination sphere and tuning its reduction potential by deleting a hydrogen bond in the secondary coordination sphere. The results not only provide the first direct evidence of S-nitrosylation of Cu(II)-bound cysteine in metalloproteins, but alsomore » shed light on the reaction mechanism and structural features responsible for stabilizing the elusive Cu(I)–S(Cys)NO species. The fast, efficient and reversible S-nitrosylation reaction is used to demonstrate its ability to prevent NO inhibition of cytochrome bo 3 oxidase activity by competing for NO binding with the native enzyme under physiologically relevant conditions.« less

Rho-associated kinase (ROCK) inhibition reverses low cell activity on hydrophobic surfaces.

PubMed

Tian, Yu Shun; Kim, Hyun Jung; Kim, Hyun-Man

2009-08-28

Hydrophobic polymers do not offer an adequate scaffold surface for cells to attach, migrate, proliferate, and differentiate. Thus, hydrophobic scaffolds for tissue engineering have traditionally been physicochemically modified to enhance cellular activity. However, modifying the surface by chemical or physical treatment requires supplementary engineering procedures. In the present study, regulation of a cell signal transduction pathway reversed the low cellular activity on a hydrophobic surface without surface modification. Inhibition of Rho-associated kinase (ROCK) by Y-27632 markedly enhanced adhesion, migration, and proliferation of osteoblastic cells cultured on a hydrophobic polystyrene surface. ROCK inhibition regulated cell-cycle-related molecules on the hydrophobic surface. This inhibition also decreased expression of the inhibitors of cyclin-dependent kinases such as p21(cip1) and p27(kip1) and increased expression of cyclin A and D. These results indicate that defective cellular activity on the hydrophobic surface can be reversed by the control of a cell signal transduction pathway without physicochemical surface modification.

Space shuttle main engine fault detection using neural networks

NASA Technical Reports Server (NTRS)

Bishop, Thomas; Greenwood, Dan; Shew, Kenneth; Stevenson, Fareed

1991-01-01

A method for on-line Space Shuttle Main Engine (SSME) anomaly detection and fault typing using a feedback neural network is described. The method involves the computation of features representing time-variance of SSME sensor parameters, using historical test case data. The network is trained, using backpropagation, to recognize a set of fault cases. The network is then able to diagnose new fault cases correctly. An essential element of the training technique is the inclusion of randomly generated data along with the real data, in order to span the entire input space of potential non-nominal data.