Integrative network alignment reveals large regions of global network similarity in yeast and human.

PubMed

Kuchaiev, Oleksii; Przulj, Natasa

2011-05-15

High-throughput methods for detecting molecular interactions have produced large sets of biological network data with much more yet to come. Analogous to sequence alignment, efficient and reliable network alignment methods are expected to improve our understanding of biological systems. Unlike sequence alignment, network alignment is computationally intractable. Hence, devising efficient network alignment heuristics is currently a foremost challenge in computational biology. We introduce a novel network alignment algorithm, called Matching-based Integrative GRAph ALigner (MI-GRAAL), which can integrate any number and type of similarity measures between network nodes (e.g. proteins), including, but not limited to, any topological network similarity measure, sequence similarity, functional similarity and structural similarity. Hence, we resolve the ties in similarity measures and find a combination of similarity measures yielding the largest contiguous (i.e. connected) and biologically sound alignments. MI-GRAAL exposes the largest functional, connected regions of protein-protein interaction (PPI) network similarity to date: surprisingly, it reveals that 77.7% of proteins in the baker's yeast high-confidence PPI network participate in such a subnetwork that is fully contained in the human high-confidence PPI network. This is the first demonstration that species as diverse as yeast and human contain so large, continuous regions of global network similarity. We apply MI-GRAAL's alignments to predict functions of un-annotated proteins in yeast, human and bacteria validating our predictions in the literature. Furthermore, using network alignment scores for PPI networks of different herpes viruses, we reconstruct their phylogenetic relationship. This is the first time that phylogeny is exactly reconstructed from purely topological alignments of PPI networks. Supplementary files and MI-GRAAL executables: http://bio-nets.doc.ic.ac.uk/MI-GRAAL/.

Survey of local and global biological network alignment: the need to reconcile the two sides of the same coin.

PubMed

Guzzi, Pietro Hiram; Milenkovic, Tijana

2018-05-01

Analogous to genomic sequence alignment that allows for across-species transfer of biological knowledge between conserved sequence regions, biological network alignment can be used to guide the knowledge transfer between conserved regions of molecular networks of different species. Hence, biological network alignment can be used to redefine the traditional notion of a sequence-based homology to a new notion of network-based homology. Analogous to genomic sequence alignment, there exist local and global biological network alignments. Here, we survey prominent and recent computational approaches of each network alignment type and discuss their (dis)advantages. Then, as it was recently shown that the two approach types are complementary, in the sense that they capture different slices of cellular functioning, we discuss the need to reconcile the two network alignment types and present a recent first step in this direction. We conclude with some open research problems on this topic and comment on the usefulness of network alignment in other domains besides computational biology.

HubAlign: an accurate and efficient method for global alignment of protein-protein interaction networks.

PubMed

Hashemifar, Somaye; Xu, Jinbo

2014-09-01

High-throughput experimental techniques have produced a large amount of protein-protein interaction (PPI) data. The study of PPI networks, such as comparative analysis, shall benefit the understanding of life process and diseases at the molecular level. One way of comparative analysis is to align PPI networks to identify conserved or species-specific subnetwork motifs. A few methods have been developed for global PPI network alignment, but it still remains challenging in terms of both accuracy and efficiency. This paper presents a novel global network alignment algorithm, denoted as HubAlign, that makes use of both network topology and sequence homology information, based upon the observation that topologically important proteins in a PPI network usually are much more conserved and thus, more likely to be aligned. HubAlign uses a minimum-degree heuristic algorithm to estimate the topological and functional importance of a protein from the global network topology information. Then HubAlign aligns topologically important proteins first and gradually extends the alignment to the whole network. Extensive tests indicate that HubAlign greatly outperforms several popular methods in terms of both accuracy and efficiency, especially in detecting functionally similar proteins. HubAlign is available freely for non-commercial purposes at http://ttic.uchicago.edu/∼hashemifar/software/HubAlign.zip. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Node fingerprinting: an efficient heuristic for aligning biological networks.

PubMed

Radu, Alex; Charleston, Michael

2014-10-01

With the continuing increase in availability of biological data and improvements to biological models, biological network analysis has become a promising area of research. An emerging technique for the analysis of biological networks is through network alignment. Network alignment has been used to calculate genetic distance, similarities between regulatory structures, and the effect of external forces on gene expression, and to depict conditional activity of expression modules in cancer. Network alignment is algorithmically complex, and therefore we must rely on heuristics, ideally as efficient and accurate as possible. The majority of current techniques for network alignment rely on precomputed information, such as with protein sequence alignment, or on tunable network alignment parameters, which may introduce an increased computational overhead. Our presented algorithm, which we call Node Fingerprinting (NF), is appropriate for performing global pairwise network alignment without precomputation or tuning, can be fully parallelized, and is able to quickly compute an accurate alignment between two biological networks. It has performed as well as or better than existing algorithms on biological and simulated data, and with fewer computational resources. The algorithmic validation performed demonstrates the low computational resource requirements of NF.

Functional Alignment of Metabolic Networks.

PubMed

Mazza, Arnon; Wagner, Allon; Ruppin, Eytan; Sharan, Roded

2016-05-01

Network alignment has become a standard tool in comparative biology, allowing the inference of protein function, interaction, and orthology. However, current alignment techniques are based on topological properties of networks and do not take into account their functional implications. Here we propose, for the first time, an algorithm to align two metabolic networks by taking advantage of their coupled metabolic models. These models allow us to assess the functional implications of genes or reactions, captured by the metabolic fluxes that are altered following their deletion from the network. Such implications may spread far beyond the region of the network where the gene or reaction lies. We apply our algorithm to align metabolic networks from various organisms, ranging from bacteria to humans, showing that our alignment can reveal functional orthology relations that are missed by conventional topological alignments.

PROPER: global protein interaction network alignment through percolation matching.

PubMed

Kazemi, Ehsan; Hassani, Hamed; Grossglauser, Matthias; Pezeshgi Modarres, Hassan

2016-12-12

The alignment of protein-protein interaction (PPI) networks enables us to uncover the relationships between different species, which leads to a deeper understanding of biological systems. Network alignment can be used to transfer biological knowledge between species. Although different PPI-network alignment algorithms were introduced during the last decade, developing an accurate and scalable algorithm that can find alignments with high biological and structural similarities among PPI networks is still challenging. In this paper, we introduce a new global network alignment algorithm for PPI networks called PROPER. Compared to other global network alignment methods, our algorithm shows higher accuracy and speed over real PPI datasets and synthetic networks. We show that the PROPER algorithm can detect large portions of conserved biological pathways between species. Also, using a simple parsimonious evolutionary model, we explain why PROPER performs well based on several different comparison criteria. We highlight that PROPER has high potential in further applications such as detecting biological pathways, finding protein complexes and PPI prediction. The PROPER algorithm is available at http://proper.epfl.ch .

Mean Green operators of deformable fiber networks embedded in a compliant matrix and property estimates

NASA Astrophysics Data System (ADS)

Franciosi, Patrick; Spagnuolo, Mario; Salman, Oguz Umut

2018-04-01

Composites comprising included phases in a continuous matrix constitute a huge class of meta-materials, whose effective properties, whether they be mechanical, physical or coupled, can be selectively optimized by using appropriate phase arrangements and architectures. An important subclass is represented by "network-reinforced matrices," say those materials in which one or more of the embedded phases are co-continuous with the matrix in one or more directions. In this article, we present a method to study effective properties of simple such structures from which more complex ones can be accessible. Effective properties are shown, in the framework of linear elasticity, estimable by using the global mean Green operator for the entire embedded fiber network which is by definition through sample spanning. This network operator is obtained from one of infinite planar alignments of infinite fibers, which the network can be seen as an interpenetrated set of, with the fiber interactions being fully accounted for in the alignments. The mean operator of such alignments is given in exact closed form for isotropic elastic-like or dielectric-like matrices. We first exemplify how these operators relevantly provide, from classic homogenization frameworks, effective properties in the case of 1D fiber bundles embedded in an isotropic elastic-like medium. It is also shown that using infinite patterns with fully interacting elements over their whole influence range at any element concentration suppresses the dilute approximation limit of these frameworks. We finally present a construction method for a global operator of fiber networks described as interpenetrated such bundles.

Realizations of highly heterogeneous collagen networks via stochastic reconstruction for micromechanical analysis of tumor cell invasion

NASA Astrophysics Data System (ADS)

Nan, Hanqing; Liang, Long; Chen, Guo; Liu, Liyu; Liu, Ruchuan; Jiao, Yang

2018-03-01

Three-dimensional (3D) collective cell migration in a collagen-based extracellular matrix (ECM) is among one of the most significant topics in developmental biology, cancer progression, tissue regeneration, and immune response. Recent studies have suggested that collagen-fiber mediated force transmission in cellularized ECM plays an important role in stress homeostasis and regulation of collective cellular behaviors. Motivated by the recent in vitro observation that oriented collagen can significantly enhance the penetration of migrating breast cancer cells into dense Matrigel which mimics the intravasation process in vivo [Han et al. Proc. Natl. Acad. Sci. USA 113, 11208 (2016), 10.1073/pnas.1610347113], we devise a procedure for generating realizations of highly heterogeneous 3D collagen networks with prescribed microstructural statistics via stochastic optimization. Specifically, a collagen network is represented via the graph (node-bond) model and the microstructural statistics considered include the cross-link (node) density, valence distribution, fiber (bond) length distribution, as well as fiber orientation distribution. An optimization problem is formulated in which the objective function is defined as the squared difference between a set of target microstructural statistics and the corresponding statistics for the simulated network. Simulated annealing is employed to solve the optimization problem by evolving an initial network via random perturbations to generate realizations of homogeneous networks with randomly oriented fibers, homogeneous networks with aligned fibers, heterogeneous networks with a continuous variation of fiber orientation along a prescribed direction, as well as a binary system containing a collagen region with aligned fibers and a dense Matrigel region with randomly oriented fibers. The generation and propagation of active forces in the simulated networks due to polarized contraction of an embedded ellipsoidal cell and a small group of cells are analyzed by considering a nonlinear fiber model incorporating strain hardening upon large stretching and buckling upon compression. Our analysis shows that oriented fibers can significantly enhance long-range force transmission in the network. Moreover, in the oriented-collagen-Matrigel system, the forces generated by a polarized cell in collagen can penetrate deeply into the Matrigel region. The stressed Matrigel fibers could provide contact guidance for the migrating cell cells, and thus enhance their penetration into Matrigel. This suggests a possible mechanism for the observed enhanced intravasation by oriented collagen.

Triangular Alignment (TAME). A Tensor-based Approach for Higher-order Network Alignment

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

Mohammadi, Shahin; Gleich, David F.; Kolda, Tamara G.

2015-11-01

Network alignment is an important tool with extensive applications in comparative interactomics. Traditional approaches aim to simultaneously maximize the number of conserved edges and the underlying similarity of aligned entities. We propose a novel formulation of the network alignment problem that extends topological similarity to higher-order structures and provide a new objective function that maximizes the number of aligned substructures. This objective function corresponds to an integer programming problem, which is NP-hard. Consequently, we approximate this objective function as a surrogate function whose maximization results in a tensor eigenvalue problem. Based on this formulation, we present an algorithm called Triangularmore » AlignMEnt (TAME), which attempts to maximize the number of aligned triangles across networks. We focus on alignment of triangles because of their enrichment in complex networks; however, our formulation and resulting algorithms can be applied to general motifs. Using a case study on the NAPABench dataset, we show that TAME is capable of producing alignments with up to 99% accuracy in terms of aligned nodes. We further evaluate our method by aligning yeast and human interactomes. Our results indicate that TAME outperforms the state-of-art alignment methods both in terms of biological and topological quality of the alignments.« less

Neural-network-directed alignment of optical systems using the laser-beam spatial filter as an example

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Krasowski, Michael J.; Weiland, Kenneth E.

1993-01-01

This report describes an effort at NASA Lewis Research Center to use artificial neural networks to automate the alignment and control of optical measurement systems. Specifically, it addresses the use of commercially available neural network software and hardware to direct alignments of the common laser-beam-smoothing spatial filter. The report presents a general approach for designing alignment records and combining these into training sets to teach optical alignment functions to neural networks and discusses the use of these training sets to train several types of neural networks. Neural network configurations used include the adaptive resonance network, the back-propagation-trained network, and the counter-propagation network. This work shows that neural networks can be used to produce robust sequencers. These sequencers can learn by example to execute the step-by-step procedures of optical alignment and also can learn adaptively to correct for environmentally induced misalignment. The long-range objective is to use neural networks to automate the alignment and operation of optical measurement systems in remote, harsh, or dangerous aerospace environments. This work also shows that when neural networks are trained by a human operator, training sets should be recorded, training should be executed, and testing should be done in a manner that does not depend on intellectual judgments of the human operator.

Estimation of brain network ictogenicity predicts outcome from epilepsy surgery

NASA Astrophysics Data System (ADS)

Goodfellow, M.; Rummel, C.; Abela, E.; Richardson, M. P.; Schindler, K.; Terry, J. R.

2016-07-01

Surgery is a valuable option for pharmacologically intractable epilepsy. However, significant post-operative improvements are not always attained. This is due in part to our incomplete understanding of the seizure generating (ictogenic) capabilities of brain networks. Here we introduce an in silico, model-based framework to study the effects of surgery within ictogenic brain networks. We find that factors conventionally determining the region of tissue to resect, such as the location of focal brain lesions or the presence of epileptiform rhythms, do not necessarily predict the best resection strategy. We validate our framework by analysing electrocorticogram (ECoG) recordings from patients who have undergone epilepsy surgery. We find that when post-operative outcome is good, model predictions for optimal strategies align better with the actual surgery undertaken than when post-operative outcome is poor. Crucially, this allows the prediction of optimal surgical strategies and the provision of quantitative prognoses for patients undergoing epilepsy surgery.

Improving scanner wafer alignment performance by target optimization

NASA Astrophysics Data System (ADS)

Leray, Philippe; Jehoul, Christiane; Socha, Robert; Menchtchikov, Boris; Raghunathan, Sudhar; Kent, Eric; Schoonewelle, Hielke; Tinnemans, Patrick; Tuffy, Paul; Belen, Jun; Wise, Rich

2016-03-01

In the process nodes of 10nm and below, the patterning complexity along with the processing and materials required has resulted in a need to optimize alignment targets in order to achieve the required precision, accuracy and throughput performance. Recent industry publications on the metrology target optimization process have shown a move from the expensive and time consuming empirical methodologies, towards a faster computational approach. ASML's Design for Control (D4C) application, which is currently used to optimize YieldStar diffraction based overlay (DBO) metrology targets, has been extended to support the optimization of scanner wafer alignment targets. This allows the necessary process information and design methodology, used for DBO target designs, to be leveraged for the optimization of alignment targets. In this paper, we show how we applied this computational approach to wafer alignment target design. We verify the correlation between predictions and measurements for the key alignment performance metrics and finally show the potential alignment and overlay performance improvements that an optimized alignment target could achieve.

Improved alignment evaluation and optimization : final report.

DOT National Transportation Integrated Search

2007-09-11

This report outlines the development of an enhanced highway alignment evaluation and optimization : model. A GIS-based software tool is prepared for alignment optimization that uses genetic algorithms for : optimal search. The software is capable of ...

Aligning physical learning spaces with the curriculum: AMEE Guide No. 107.

PubMed

Nordquist, Jonas; Sundberg, Kristina; Laing, Andrew

2016-08-01

This Guide explores emerging issues on the alignment of learning spaces with the changing curriculum in medical education. As technology and new teaching methods have altered the nature of learning in medical education, it is necessary to re-think how physical learning spaces are aligned with the curriculum. The better alignment of learning spaces with the curriculum depends on more directly engaged leadership from faculty and the community of medical education for briefing the requirements for the design of all kinds of learning spaces. However, there is a lack of precedent and well-established processes as to how new kinds of learning spaces should be programmed. Such programmes are essential aspects of optimizing the intended experience of the curriculum. Faculty and the learning community need better tools and instruments to support their leadership role in briefing and programming. A Guide to critical concepts for exploring the alignment of curriculum and learning spaces is provided. The idea of a networked learning landscape is introduced as a way of assessing and evaluating the alignment of physical spaces to the emerging curriculum. The concept is used to explore how technology has widened the range of spaces and places in which learning happens as well as enabling new styles of learning. The networked learning landscaped is explored through four different scales within which learning is accommodated: the classroom, the building, the campus, and the city. High-level guidance on the process of briefing for the networked learning landscape is provided, to take into account the wider scale of learning spaces and the impact of technology. Key to a successful measurement process is argued to be the involvement of relevant academic stakeholders who can identify the strategic direction and purpose for the design of the learning environments in relation to the emerging demands of the curriculum.

Aligning Biomolecular Networks Using Modular Graph Kernels

NASA Astrophysics Data System (ADS)

Towfic, Fadi; Greenlee, M. Heather West; Honavar, Vasant

Comparative analysis of biomolecular networks constructed using measurements from different conditions, tissues, and organisms offer a powerful approach to understanding the structure, function, dynamics, and evolution of complex biological systems. We explore a class of algorithms for aligning large biomolecular networks by breaking down such networks into subgraphs and computing the alignment of the networks based on the alignment of their subgraphs. The resulting subnetworks are compared using graph kernels as scoring functions. We provide implementations of the resulting algorithms as part of BiNA, an open source biomolecular network alignment toolkit. Our experiments using Drosophila melanogaster, Saccharomyces cerevisiae, Mus musculus and Homo sapiens protein-protein interaction networks extracted from the DIP repository of protein-protein interaction data demonstrate that the performance of the proposed algorithms (as measured by % GO term enrichment of subnetworks identified by the alignment) is competitive with some of the state-of-the-art algorithms for pair-wise alignment of large protein-protein interaction networks. Our results also show that the inter-species similarity scores computed based on graph kernels can be used to cluster the species into a species tree that is consistent with the known phylogenetic relationships among the species.

The relative phases of basal ganglia activities dynamically shape effective connectivity in Parkinson's disease.

PubMed

Cagnan, Hayriye; Duff, Eugene Paul; Brown, Peter

2015-06-01

Optimal phase alignment between oscillatory neural circuits is hypothesized to optimize information flow and enhance system performance. This theory is known as communication-through-coherence. The basal ganglia motor circuit exhibits exaggerated oscillatory and coherent activity patterns in Parkinson's disease. Such activity patterns are linked to compromised motor system performance as evinced by bradykinesia, rigidity and tremor, suggesting that network function might actually deteriorate once a certain level of net synchrony is exceeded in the motor circuit. Here, we characterize the processes underscoring excessive synchronization and its termination. To this end, we analysed local field potential recordings from the subthalamic nucleus and globus pallidus of five patients with Parkinson's disease (four male and one female, aged 37-64 years). We observed that certain phase alignments between subthalamic nucleus and globus pallidus amplified local neural synchrony in the beta frequency band while others either suppressed it or did not induce any significant change with respect to surrogates. The increase in local beta synchrony directly correlated with how long the two nuclei locked to beta-amplifying phase alignments. Crucially, administration of the dopamine prodrug, levodopa, reduced the frequency and duration of periods during which subthalamic and pallidal populations were phase-locked to beta-amplifying alignments. Conversely ON dopamine, the total duration over which subthalamic and pallidal populations were aligned to phases that left beta-amplitude unchanged with respect to surrogates increased. Thus dopaminergic input shifted circuit dynamics from persistent periods of locking to amplifying phase alignments, associated with compromised motoric function, to more dynamic phase alignment and improved motoric function. This effect of dopamine on local circuit resonance suggests means by which novel electrical interventions might prevent resonance-related pathological circuit interactions. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.

GraphCrunch 2: Software tool for network modeling, alignment and clustering.

PubMed

Kuchaiev, Oleksii; Stevanović, Aleksandar; Hayes, Wayne; Pržulj, Nataša

2011-01-19

Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI) data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL") for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other existing tool. Finally, GraphCruch 2 implements an algorithm for clustering nodes within a network based solely on their topological similarities. Using GraphCrunch 2, we demonstrate that eukaryotic and viral PPI networks may belong to different graph model families and show that topology-based clustering can reveal important functional similarities between proteins within yeast and human PPI networks. GraphCrunch 2 is a software tool that implements the latest research on biological network analysis. It parallelizes computationally intensive tasks to fully utilize the potential of modern multi-core CPUs. It is open-source and freely available for research use. It runs under the Windows and Linux platforms.

SANA NetGO: a combinatorial approach to using Gene Ontology (GO) terms to score network alignments.

PubMed

Hayes, Wayne B; Mamano, Nil

2018-04-15

Gene Ontology (GO) terms are frequently used to score alignments between protein-protein interaction (PPI) networks. Methods exist to measure GO similarity between proteins in isolation, but proteins in a network alignment are not isolated: each pairing is dependent on every other via the alignment itself. Existing measures fail to take into account the frequency of GO terms across networks, instead imposing arbitrary rules on when to allow GO terms. Here we develop NetGO, a new measure that naturally weighs infrequent, informative GO terms more heavily than frequent, less informative GO terms, without arbitrary cutoffs, instead downweighting GO terms according to their frequency in the networks being aligned. This is a global measure applicable only to alignments, independent of pairwise GO measures, in the same sense that the edge-based EC or S3 scores are global measures of topological similarity independent of pairwise topological similarities. We demonstrate the superiority of NetGO in alignments of predetermined quality and show that NetGO correlates with alignment quality better than any existing GO-based alignment measures. We also demonstrate that NetGO provides a measure of taxonomic similarity between species, consistent with existing taxonomic measuresa feature not shared with existing GObased network alignment measures. Finally, we re-score alignments produced by almost a dozen aligners from a previous study and show that NetGO does a better job at separating good alignments from bad ones. Available as part of SANA. whayes@uci.edu. Supplementary data are available at Bioinformatics online.

3D High Resolution Mesh Deformation Based on Multi Library Wavelet Neural Network Architecture

NASA Astrophysics Data System (ADS)

Dhibi, Naziha; Elkefi, Akram; Bellil, Wajdi; Amar, Chokri Ben

2016-12-01

This paper deals with the features of a novel technique for large Laplacian boundary deformations using estimated rotations. The proposed method is based on a Multi Library Wavelet Neural Network structure founded on several mother wavelet families (MLWNN). The objective is to align features of mesh and minimize distortion with a fixed feature that minimizes the sum of the distances between all corresponding vertices. New mesh deformation method worked in the domain of Region of Interest (ROI). Our approach computes deformed ROI, updates and optimizes it to align features of mesh based on MLWNN and spherical parameterization configuration. This structure has the advantage of constructing the network by several mother wavelets to solve high dimensions problem using the best wavelet mother that models the signal better. The simulation test achieved the robustness and speed considerations when developing deformation methodologies. The Mean-Square Error and the ratio of deformation are low compared to other works from the state of the art. Our approach minimizes distortions with fixed features to have a well reconstructed object.

Applied Graph-Mining Algorithms to Study Biomolecular Interaction Networks

PubMed Central

2014-01-01

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

LABVIEW graphical user interface for precision multichannel alignment of Raman lidar at Jet Propulsion Laboratory, Table Mountain Facility.

PubMed

Aspey, R A; McDermid, I S; Leblanc, T; Howe, J W; Walsh, T D

2008-09-01

The Jet Propulsion Laboratory operates lidar systems at Table Mountain Facility (TMF), California (34.4 degrees N, 117.7 degrees W) and Mauna Loa Observatory, Hawaii (19.5 degrees N, 155.6 degrees W) under the framework of the Network for the Detection of Atmospheric Composition Change. To complement these systems a new Raman lidar has been developed at TMF with particular attention given to optimizing water vapor profile measurements up to the tropopause and lower stratosphere. The lidar has been designed for accuracies of 5% up to 12 km in the free troposphere and a detection capability of <5 ppmv. One important feature of the lidar is a precision alignment system using range resolved data from eight Licel transient recorders, allowing fully configurable alignment via a LABVIEW/C++ graphical user interface (GUI). This allows the lidar to be aligned on any channel while simultaneously displaying signals from other channels at configurable altitude/bin combinations. The general lidar instrumental setup and the details of the alignment control system, data acquisition, and GUI alignment software are described. Preliminary validation results using radiosonde and lidar intercomparisons are briefly presented.

Optimizing performance of hybrid FSO/RF networks in realistic dynamic scenarios

NASA Astrophysics Data System (ADS)

Llorca, Jaime; Desai, Aniket; Baskaran, Eswaran; Milner, Stuart; Davis, Christopher

2005-08-01

Hybrid Free Space Optical (FSO) and Radio Frequency (RF) networks promise highly available wireless broadband connectivity and quality of service (QoS), particularly suitable for emerging network applications involving extremely high data rate transmissions such as high quality video-on-demand and real-time surveillance. FSO links are prone to atmospheric obscuration (fog, clouds, snow, etc) and are difficult to align over long distances due the use of narrow laser beams and the effect of atmospheric turbulence. These problems can be mitigated by using adjunct directional RF links, which provide backup connectivity. In this paper, methodologies for modeling and simulation of hybrid FSO/RF networks are described. Individual link propagation models are derived using scattering theory, as well as experimental measurements. MATLAB is used to generate realistic atmospheric obscuration scenarios, including moving cloud layers at different altitudes. These scenarios are then imported into a network simulator (OPNET) to emulate mobile hybrid FSO/RF networks. This framework allows accurate analysis of the effects of node mobility, atmospheric obscuration and traffic demands on network performance, and precise evaluation of topology reconfiguration algorithms as they react to dynamic changes in the network. Results show how topology reconfiguration algorithms, together with enhancements to TCP/IP protocols which reduce the network response time, enable the network to rapidly detect and act upon link state changes in highly dynamic environments, ensuring optimized network performance and availability.

Photogrammetric measurement to one part in a million

NASA Astrophysics Data System (ADS)

Fraser, Clive S.

1992-03-01

Industrial photogrammetric measurement to accuracies of 1 part in 1,000,000 of the size of the object is discussed. Network design concepts are reviewed, especially with regard both to the relationships between the first- and second-order design phases and to minimization of the influences of uncompensated systematic error. Photogrammetric system aspects are also briefly touched upon. The network optimization process for the measurement of a large compact range reflector is described and results of successive alignment surveys of this structure are summarized. These photogrammetric measurements yielded three dimensional (3D) coordinate accuracies surpassing one part in a million.

A Rapid Convergent Low Complexity Interference Alignment Algorithm for Wireless Sensor Networks.

PubMed

Jiang, Lihui; Wu, Zhilu; Ren, Guanghui; Wang, Gangyi; Zhao, Nan

2015-07-29

Interference alignment (IA) is a novel technique that can effectively eliminate the interference and approach the sum capacity of wireless sensor networks (WSNs) when the signal-to-noise ratio (SNR) is high, by casting the desired signal and interference into different signal subspaces. The traditional alternating minimization interference leakage (AMIL) algorithm for IA shows good performance in high SNR regimes, however, the complexity of the AMIL algorithm increases dramatically as the number of users and antennas increases, posing limits to its applications in the practical systems. In this paper, a novel IA algorithm, called directional quartic optimal (DQO) algorithm, is proposed to minimize the interference leakage with rapid convergence and low complexity. The properties of the AMIL algorithm are investigated, and it is discovered that the difference between the two consecutive iteration results of the AMIL algorithm will approximately point to the convergence solution when the precoding and decoding matrices obtained from the intermediate iterations are sufficiently close to their convergence values. Based on this important property, the proposed DQO algorithm employs the line search procedure so that it can converge to the destination directly. In addition, the optimal step size can be determined analytically by optimizing a quartic function. Numerical results show that the proposed DQO algorithm can suppress the interference leakage more rapidly than the traditional AMIL algorithm, and can achieve the same level of sum rate as that of AMIL algorithm with far less iterations and execution time.

High Electromechanical Response of Ionic Polymer Actuators with Controlled-Morphology Aligned Carbon Nanotube/Nafion Nanocomposite Electrodes

PubMed Central

Liu, Sheng; Liu, Yang; Cebeci, Hülya; de Villoria, Roberto Guzmán; Lin, Jun-Hong

2011-01-01

Recent advances in fabricating controlled-morphology vertically aligned carbon nanotubes (VA-CNTs) with ultrahigh volume fraction create unique opportunities for markedly improving the electromechanical performance of ionic polymer conductor network composite (IPCNC) actuators. Continuous paths through inter-VA-CNT channels allow fast ion transport, and high electrical conduction of the aligned CNTs in the composite electrodes lead to fast device actuation speed (>10% strain/second). One critical issue in developing advanced actuator materials is how to suppress the strain that does not contribute to the actuation (unwanted strain) thereby reducing actuation efficiency. Here our experiments demonstrate that the VA-CNTs give an anisotropic elastic response in the composite electrodes, which suppresses the unwanted strain and markedly enhances the actuation strain (>8% strain under 4 volts). The results reported here suggest pathways for optimizing the electrode morphology in IPCNCs using ultra-high volume fraction VA-CNTs to further enhanced performance. PMID:21765822

Effect of nanowire curviness on the percolation resistivity of transparent, conductive metal nanowire networks

NASA Astrophysics Data System (ADS)

Hicks, Jeremy; Li, Junying; Ying, Chen; Ural, Ant

2018-05-01

We study the effect of nanowire curviness on the percolation resistivity of transparent, conductive metal nanowire networks by Monte Carlo simulations. We generate curvy nanowires as one-dimensional sticks using 3rd-order Bézier curves. The degree of curviness in the network is quantified by the concept of curviness angle and curl ratio. We systematically study the interaction between the effect of curviness and five other nanowire/device parameters on the network resistivity, namely nanowire density, nanowire length, device length, device width, and nanowire alignment. We find that the resistivity exhibits a power law dependence on the curl ratio, which is a signature of percolation transport. In each case, we extract the power-law scaling critical exponents and explain the results using geometrical and physical arguments. The value of the curl ratio critical exponent is not universal, but increases as the other nanowire/device parameters drive the network toward the percolation threshold. We find that, for randomly oriented networks, curviness is undesirable since it increases the resistivity. For well-aligned networks, on the other hand, some curviness is highly desirable, since the resistivity minimum occurs for partially curvy nanowires. We explain these results by considering the two competing effects of curviness on the percolation resistivity. The results presented in this work can be extended to any network, film, or nanocomposite consisting of one-dimensional nanoelements. Our results show that Monte Carlo simulations are an essential predictive tool for both studying the percolation transport and optimizing the electronic properties of transparent, conductive nanowire networks for a wide range of applications.

Global Alignment of Pairwise Protein Interaction Networks for Maximal Common Conserved Patterns

DOE PAGES

Tian, Wenhong; Samatova, Nagiza F.

2013-01-01

A number of tools for the alignment of protein-protein interaction (PPI) networks have laid the foundation for PPI network analysis. Most of alignment tools focus on finding conserved interaction regions across the PPI networks through either local or global mapping of similar sequences. Researchers are still trying to improve the speed, scalability, and accuracy of network alignment. In view of this, we introduce a connected-components based fast algorithm, HopeMap, for network alignment. Observing that the size of true orthologs across species is small comparing to the total number of proteins in all species, we take a different approach based onmore » a precompiled list of homologs identified by KO terms. Applying this approach to S. cerevisiae (yeast) and D. melanogaster (fly), E. coli K12 and S. typhimurium , E. coli K12 and C. crescenttus , we analyze all clusters identified in the alignment. The results are evaluated through up-to-date known gene annotations, gene ontology (GO), and KEGG ortholog groups (KO). Comparing to existing tools, our approach is fast with linear computational cost, highly accurate in terms of KO and GO terms specificity and sensitivity, and can be extended to multiple alignments easily.« less

NO2 sensing at room temperature using vertically aligned MoS2 flakes network

NASA Astrophysics Data System (ADS)

Kumar, Rahul; Goel, Neeraj; Kumar, Mahesh

2018-04-01

To exploit the role of alignment of MoS2 flake in chemical sensing, here, we have synthesized the horizontally and vertically aligned MoS2 flake network using conventional chemical vapor deposition technique. The morphology and number of layers were confirmed by SEM and Raman spectroscopy, respectively. The sensing performance of horizontally aligned and vertically aligned flake network was investigated to NO2 at room temperature. Vertically aligned MoS2 based sensor showed higher sensitivity 51.54 % and 63.2 % compared to horizontally aligned MoS2 sensor' sensitivity of 35.32 % and 45.2 % to 50 ppm and 100 ppm NO2, respectively. This high sensitivity attributed to the high aspect ratio and high adsorption energy on the edge site of vertically aligned MoS2.

Global Network Alignment in the Context of Aging.

PubMed

Faisal, Fazle Elahi; Zhao, Han; Milenkovic, Tijana

2015-01-01

Analogous to sequence alignment, network alignment (NA) can be used to transfer biological knowledge across species between conserved network regions. NA faces two algorithmic challenges: 1) Which cost function to use to capture "similarities" between nodes in different networks? 2) Which alignment strategy to use to rapidly identify "high-scoring" alignments from all possible alignments? We "break down" existing state-of-the-art methods that use both different cost functions and different alignment strategies to evaluate each combination of their cost functions and alignment strategies. We find that a combination of the cost function of one method and the alignment strategy of another method beats the existing methods. Hence, we propose this combination as a novel superior NA method. Then, since human aging is hard to study experimentally due to long lifespan, we use NA to transfer aging-related knowledge from well annotated model species to poorly annotated human. By doing so, we produce novel human aging-related knowledge, which complements currently available knowledge about aging that has been obtained mainly by sequence alignment. We demonstrate significant similarity between topological and functional properties of our novel predictions and those of known aging-related genes. We are the first to use NA to learn more about aging.

B-cell Ligand Processing Pathways Detected by Large-scale Comparative Analysis

PubMed Central

Towfic, Fadi; Gupta, Shakti; Honavar, Vasant; Subramaniam, Shankar

2012-01-01

The initiation of B-cell ligand recognition is a critical step for the generation of an immune response against foreign bodies. We sought to identify the biochemical pathways involved in the B-cell ligand recognition cascade and sets of ligands that trigger similar immunological responses. We utilized several comparative approaches to analyze the gene coexpression networks generated from a set of microarray experiments spanning 33 different ligands. First, we compared the degree distributions of the generated networks. Second, we utilized a pairwise network alignment algorithm, BiNA, to align the networks based on the hubs in the networks. Third, we aligned the networks based on a set of KEGG pathways. We summarized our results by constructing a consensus hierarchy of pathways that are involved in B cell ligand recognition. The resulting pathways were further validated through literature for their common physiological responses. Collectively, the results based on our comparative analyses of degree distributions, alignment of hubs, and alignment based on KEGG pathways provide a basis for molecular characterization of the immune response states of B-cells and demonstrate the power of comparative approaches (e.g., gene coexpression network alignment algorithms) in elucidating biochemical pathways involved in complex signaling events in cells. PMID:22917187

Interference Alignment With Partial CSI Feedback in MIMO Cellular Networks

NASA Astrophysics Data System (ADS)

Rao, Xiongbin; Lau, Vincent K. N.

2014-04-01

Interference alignment (IA) is a linear precoding strategy that can achieve optimal capacity scaling at high SNR in interference networks. However, most existing IA designs require full channel state information (CSI) at the transmitters, which would lead to significant CSI signaling overhead. There are two techniques, namely CSI quantization and CSI feedback filtering, to reduce the CSI feedback overhead. In this paper, we consider IA processing with CSI feedback filtering in MIMO cellular networks. We introduce a novel metric, namely the feedback dimension, to quantify the first order CSI feedback cost associated with the CSI feedback filtering. The CSI feedback filtering poses several important challenges in IA processing. First, there is a hidden partial CSI knowledge constraint in IA precoder design which cannot be handled using conventional IA design methodology. Furthermore, existing results on the feasibility conditions of IA cannot be applied due to the partial CSI knowledge. Finally, it is very challenging to find out how much CSI feedback is actually needed to support IA processing. We shall address the above challenges and propose a new IA feasibility condition under partial CSIT knowledge in MIMO cellular networks. Based on this, we consider the CSI feedback profile design subject to the degrees of freedom requirements, and we derive closed-form trade-off results between the CSI feedback cost and IA performance in MIMO cellular networks.

Algorithms for Automatic Alignment of Arrays

NASA Technical Reports Server (NTRS)

Chatterjee, Siddhartha; Gilbert, John R.; Oliker, Leonid; Schreiber, Robert; Sheffler, Thomas J.

1996-01-01

Aggregate data objects (such as arrays) are distributed across the processor memories when compiling a data-parallel language for a distributed-memory machine. The mapping determines the amount of communication needed to bring operands of parallel operations into alignment with each other. A common approach is to break the mapping into two stages: an alignment that maps all the objects to an abstract template, followed by a distribution that maps the template to the processors. This paper describes algorithms for solving the various facets of the alignment problem: axis and stride alignment, static and mobile offset alignment, and replication labeling. We show that optimal axis and stride alignment is NP-complete for general program graphs, and give a heuristic method that can explore the space of possible solutions in a number of ways. We show that some of these strategies can give better solutions than a simple greedy approach proposed earlier. We also show how local graph contractions can reduce the size of the problem significantly without changing the best solution. This allows more complex and effective heuristics to be used. We show how to model the static offset alignment problem using linear programming, and we show that loop-dependent mobile offset alignment is sometimes necessary for optimum performance. We describe an algorithm with for determining mobile alignments for objects within do loops. We also identify situations in which replicated alignment is either required by the program itself or can be used to improve performance. We describe an algorithm based on network flow that replicates objects so as to minimize the total amount of broadcast communication in replication.

Accurate multiple sequence-structure alignment of RNA sequences using combinatorial optimization.

PubMed

Bauer, Markus; Klau, Gunnar W; Reinert, Knut

2007-07-27

The discovery of functional non-coding RNA sequences has led to an increasing interest in algorithms related to RNA analysis. Traditional sequence alignment algorithms, however, fail at computing reliable alignments of low-homology RNA sequences. The spatial conformation of RNA sequences largely determines their function, and therefore RNA alignment algorithms have to take structural information into account. We present a graph-based representation for sequence-structure alignments, which we model as an integer linear program (ILP). We sketch how we compute an optimal or near-optimal solution to the ILP using methods from combinatorial optimization, and present results on a recently published benchmark set for RNA alignments. The implementation of our algorithm yields better alignments in terms of two published scores than the other programs that we tested: This is especially the case with an increasing number of input sequences. Our program LARA is freely available for academic purposes from http://www.planet-lisa.net.

A Mathematical Optimization Problem in Bioinformatics

ERIC Educational Resources Information Center

Heyer, Laurie J.

2008-01-01

This article describes the sequence alignment problem in bioinformatics. Through examples, we formulate sequence alignment as an optimization problem and show how to compute the optimal alignment with dynamic programming. The examples and sample exercises have been used by the author in a specialized course in bioinformatics, but could be adapted…

AlignNemo: a local network alignment method to integrate homology and topology.

PubMed

Ciriello, Giovanni; Mina, Marco; Guzzi, Pietro H; Cannataro, Mario; Guerra, Concettina

2012-01-01

Local network alignment is an important component of the analysis of protein-protein interaction networks that may lead to the identification of evolutionary related complexes. We present AlignNemo, a new algorithm that, given the networks of two organisms, uncovers subnetworks of proteins that relate in biological function and topology of interactions. The discovered conserved subnetworks have a general topology and need not to correspond to specific interaction patterns, so that they more closely fit the models of functional complexes proposed in the literature. The algorithm is able to handle sparse interaction data with an expansion process that at each step explores the local topology of the networks beyond the proteins directly interacting with the current solution. To assess the performance of AlignNemo, we ran a series of benchmarks using statistical measures as well as biological knowledge. Based on reference datasets of protein complexes, AlignNemo shows better performance than other methods in terms of both precision and recall. We show our solutions to be biologically sound using the concept of semantic similarity applied to Gene Ontology vocabularies. The binaries of AlignNemo and supplementary details about the algorithms and the experiments are available at: sourceforge.net/p/alignnemo.

Neural nets for aligning optical components in harsh environments: Beam smoothing spatial filter as an example

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Krasowski, Michael J.

1991-01-01

The goal is to develop an approach to automating the alignment and adjustment of optical measurement, visualization, inspection, and control systems. Classical controls, expert systems, and neural networks are three approaches to automating the alignment of an optical system. Neural networks were chosen for this project and the judgements that led to this decision are presented. Neural networks were used to automate the alignment of the ubiquitous laser-beam-smoothing spatial filter. The results and future plans of the project are presented.

NetCoffee: a fast and accurate global alignment approach to identify functionally conserved proteins in multiple networks.

PubMed

Hu, Jialu; Kehr, Birte; Reinert, Knut

2014-02-15

Owing to recent advancements in high-throughput technologies, protein-protein interaction networks of more and more species become available in public databases. The question of how to identify functionally conserved proteins across species attracts a lot of attention in computational biology. Network alignments provide a systematic way to solve this problem. However, most existing alignment tools encounter limitations in tackling this problem. Therefore, the demand for faster and more efficient alignment tools is growing. We present a fast and accurate algorithm, NetCoffee, which allows to find a global alignment of multiple protein-protein interaction networks. NetCoffee searches for a global alignment by maximizing a target function using simulated annealing on a set of weighted bipartite graphs that are constructed using a triplet approach similar to T-Coffee. To assess its performance, NetCoffee was applied to four real datasets. Our results suggest that NetCoffee remedies several limitations of previous algorithms, outperforms all existing alignment tools in terms of speed and nevertheless identifies biologically meaningful alignments. The source code and data are freely available for download under the GNU GPL v3 license at https://code.google.com/p/netcoffee/.

Strain-Induced Alignment in Collagen Gels

PubMed Central

Vader, David; Kabla, Alexandre; Weitz, David; Mahadevan, Lakshminarayana

2009-01-01

Collagen is the most abundant extracellular-network-forming protein in animal biology and is important in both natural and artificial tissues, where it serves as a material of great mechanical versatility. This versatility arises from its almost unique ability to remodel under applied loads into anisotropic and inhomogeneous structures. To explore the origins of this property, we develop a set of analysis tools and a novel experimental setup that probes the mechanical response of fibrous networks in a geometry that mimics a typical deformation profile imposed by cells in vivo. We observe strong fiber alignment and densification as a function of applied strain for both uncrosslinked and crosslinked collagenous networks. This alignment is found to be irreversibly imprinted in uncrosslinked collagen networks, suggesting a simple mechanism for tissue organization at the microscale. However, crosslinked networks display similar fiber alignment and the same geometrical properties as uncrosslinked gels, but with full reversibility. Plasticity is therefore not required to align fibers. On the contrary, our data show that this effect is part of the fundamental non-linear properties of fibrous biological networks. PMID:19529768

Multifunctional Mesoscale Observing Networks.

NASA Astrophysics Data System (ADS)

Dabberdt, Walter F.; Schlatter, Thomas W.; Carr, Frederick H.; Friday, Elbert W. Joe; Jorgensen, David; Koch, Steven; Pirone, Maria; Ralph, F. Martin; Sun, Juanzhen; Welsh, Patrick; Wilson, James W.; Zou, Xiaolei

2005-07-01

More than 120 scientists, engineers, administrators, and users met on 8 10 December 2003 in a workshop format to discuss the needs for enhanced three-dimensional mesoscale observing networks. Improved networks are seen as being critical to advancing numerical and empirical modeling for a variety of mesoscale applications, including severe weather warnings and forecasts, hydrology, air-quality forecasting, chemical emergency response, transportation safety, energy management, and others. The participants shared a clear and common vision for the observing requirements: existing two-dimensional mesoscale measurement networks do not provide observations of the type, frequency, and density that are required to optimize mesoscale prediction and nowcasts. To be viable, mesoscale observing networks must serve multiple applications, and the public, private, and academic sectors must all actively participate in their design and implementation, as well as in the creation and delivery of value-added products. The mesoscale measurement challenge can best be met by an integrated approach that considers all elements of an end-to-end solution—identifying end users and their needs, designing an optimal mix of observations, defining the balance between static and dynamic (targeted or adaptive) sampling strategies, establishing long-term test beds, and developing effective implementation strategies. Detailed recommendations are provided pertaining to nowcasting, numerical prediction and data assimilation, test beds, and implementation strategies.

"Master-Slave" Biological Network Alignment

NASA Astrophysics Data System (ADS)

Ferraro, Nicola; Palopoli, Luigi; Panni, Simona; Rombo, Simona E.

Performing global alignment between protein-protein interaction (PPI) networks of different organisms is important to infer knowledge about conservation across species. Known methods that perform this task operate symmetrically, that is to say, they do not assign a distinct role to the input PPI networks. However, in most cases, the input networks are indeed distinguishable on the basis of how well the corresponding organism is biologically well-characterized. For well-characterized organisms the associated PPI network supposedly encode in a sound manner all the information about their proteins and associated interactions, which is far from being the case for not well characterized ones. Here the new idea is developed to devise a method for global alignment of PPI networks that in fact exploit differences in the characterization of organisms at hand. We assume that the PPI network (called Master) of the best characterized is used as a fingerprint to guide the alignment process to the second input network (called Slave), so that generated results preferably retain the structural characteristics of the Master (and using the Slave) network. We tested our method showing that the results it returns are biologically relevant.

Collectives for Multiple Resource Job Scheduling Across Heterogeneous Servers

NASA Technical Reports Server (NTRS)

Tumer, K.; Lawson, J.

2003-01-01

Efficient management of large-scale, distributed data storage and processing systems is a major challenge for many computational applications. Many of these systems are characterized by multi-resource tasks processed across a heterogeneous network. Conventional approaches, such as load balancing, work well for centralized, single resource problems, but breakdown in the more general case. In addition, most approaches are often based on heuristics which do not directly attempt to optimize the world utility. In this paper, we propose an agent based control system using the theory of collectives. We configure the servers of our network with agents who make local job scheduling decisions. These decisions are based on local goals which are constructed to be aligned with the objective of optimizing the overall efficiency of the system. We demonstrate that multi-agent systems in which all the agents attempt to optimize the same global utility function (team game) only marginally outperform conventional load balancing. On the other hand, agents configured using collectives outperform both team games and load balancing (by up to four times for the latter), despite their distributed nature and their limited access to information.

CSI Feedback Reduction for MIMO Interference Alignment

NASA Astrophysics Data System (ADS)

Rao, Xiongbin; Ruan, Liangzhong; Lau, Vincent K. N.

2013-09-01

Interference alignment (IA) is a linear precoding strategy that can achieve optimal capacity scaling at high SNR in interference networks. Most of the existing IA designs require full channel state information (CSI) at the transmitters, which induces a huge CSI signaling cost. Hence it is desirable to improve the feedback efficiency for IA and in this paper, we propose a novel IA scheme with a significantly reduced CSI feedback. To quantify the CSI feedback cost, we introduce a novel metric, namely the feedback dimension. This metric serves as a first-order measurement of CSI feedback overhead. Due to the partial CSI feedback constraint, conventional IA schemes can not be applied and hence, we develop a novel IA precoder / decorrelator design and establish new IA feasibility conditions. Via dynamic feedback profile design, the proposed IA scheme can also achieve a flexible tradeoff between the degree of freedom (DoF) requirements for data streams, the antenna resources and the CSI feedback cost. We show by analysis and simulations that the proposed scheme achieves substantial reductions of CSI feedback overhead under the same DoF requirement in MIMO interference networks.

Multiple sequence alignment using multi-objective based bacterial foraging optimization algorithm.

PubMed

Rani, R Ranjani; Ramyachitra, D

2016-12-01

Multiple sequence alignment (MSA) is a widespread approach in computational biology and bioinformatics. MSA deals with how the sequences of nucleotides and amino acids are sequenced with possible alignment and minimum number of gaps between them, which directs to the functional, evolutionary and structural relationships among the sequences. Still the computation of MSA is a challenging task to provide an efficient accuracy and statistically significant results of alignments. In this work, the Bacterial Foraging Optimization Algorithm was employed to align the biological sequences which resulted in a non-dominated optimal solution. It employs Multi-objective, such as: Maximization of Similarity, Non-gap percentage, Conserved blocks and Minimization of gap penalty. BAliBASE 3.0 benchmark database was utilized to examine the proposed algorithm against other methods In this paper, two algorithms have been proposed: Hybrid Genetic Algorithm with Artificial Bee Colony (GA-ABC) and Bacterial Foraging Optimization Algorithm. It was found that Hybrid Genetic Algorithm with Artificial Bee Colony performed better than the existing optimization algorithms. But still the conserved blocks were not obtained using GA-ABC. Then BFO was used for the alignment and the conserved blocks were obtained. The proposed Multi-Objective Bacterial Foraging Optimization Algorithm (MO-BFO) was compared with widely used MSA methods Clustal Omega, Kalign, MUSCLE, MAFFT, Genetic Algorithm (GA), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Hybrid Genetic Algorithm with Artificial Bee Colony (GA-ABC). The final results show that the proposed MO-BFO algorithm yields better alignment than most widely used methods. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Iterative pass optimization of sequence data

NASA Technical Reports Server (NTRS)

Wheeler, Ward C.

2003-01-01

The problem of determining the minimum-cost hypothetical ancestral sequences for a given cladogram is known to be NP-complete. This "tree alignment" problem has motivated the considerable effort placed in multiple sequence alignment procedures. Wheeler in 1996 proposed a heuristic method, direct optimization, to calculate cladogram costs without the intervention of multiple sequence alignment. This method, though more efficient in time and more effective in cladogram length than many alignment-based procedures, greedily optimizes nodes based on descendent information only. In their proposal of an exact multiple alignment solution, Sankoff et al. in 1976 described a heuristic procedure--the iterative improvement method--to create alignments at internal nodes by solving a series of median problems. The combination of a three-sequence direct optimization with iterative improvement and a branch-length-based cladogram cost procedure, provides an algorithm that frequently results in superior (i.e., lower) cladogram costs. This iterative pass optimization is both computation and memory intensive, but economies can be made to reduce this burden. An example in arthropod systematics is discussed. c2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.

High-speed all-optical DNA local sequence alignment based on a three-dimensional artificial neural network.

PubMed

Maleki, Ehsan; Babashah, Hossein; Koohi, Somayyeh; Kavehvash, Zahra

2017-07-01

This paper presents an optical processing approach for exploring a large number of genome sequences. Specifically, we propose an optical correlator for global alignment and an extended moiré matching technique for local analysis of spatially coded DNA, whose output is fed to a novel three-dimensional artificial neural network for local DNA alignment. All-optical implementation of the proposed 3D artificial neural network is developed and its accuracy is verified in Zemax. Thanks to its parallel processing capability, the proposed structure performs local alignment of 4 million sequences of 150 base pairs in a few seconds, which is much faster than its electrical counterparts, such as the basic local alignment search tool.

Disentangling the Role of Entanglement Density and Molecular Alignment in the Mechanical Response of Glassy Polymers

NASA Astrophysics Data System (ADS)

O'Connor, Thomas; Robbins, Mark

Glassy polymers are a ubiquitous part of modern life, but much about their mechanical properties remains poorly understood. Since chains in glassy states are hindered from exploring their conformational entropy, they can't be understood with common entropic network models. Additionally, glassy states are highly sensitive to material history and nonequilibrium distributions of chain alignment and entanglement can be produced during material processing. Understanding how these far-from equilibrium states impact mechanical properties is analytically challenging but essential to optimizing processing methods. We use molecular dynamics simulations to study the yield and strain hardening of glassy polymers as separate functions of the degree of molecular alignment and inter-chain entanglement. We vary chain alignment and entanglement with three different preparation protocols that mimic common processing conditions in and out of solution. We compare our results to common mechanical models of amorphous polymers and assess their applicability to different experimental processing conditions. This research was performed within the Center for Materials in Extreme Dynamic Environments (CMEDE) under the Hopkins Extreme Materials Institute at Johns Hopkins University. Financial support was provided by Grant W911NF-12-2-0022.

Prediction of β-turns in proteins from multiple alignment using neural network

PubMed Central

Kaur, Harpreet; Raghava, Gajendra Pal Singh

2003-01-01

A neural network-based method has been developed for the prediction of β-turns in proteins by using multiple sequence alignment. Two feed-forward back-propagation networks with a single hidden layer are used where the first-sequence structure network is trained with the multiple sequence alignment in the form of PSI-BLAST–generated position-specific scoring matrices. The initial predictions from the first network and PSIPRED-predicted secondary structure are used as input to the second structure-structure network to refine the predictions obtained from the first net. A significant improvement in prediction accuracy has been achieved by using evolutionary information contained in the multiple sequence alignment. The final network yields an overall prediction accuracy of 75.5% when tested by sevenfold cross-validation on a set of 426 nonhomologous protein chains. The corresponding Qpred, Qobs, and Matthews correlation coefficient values are 49.8%, 72.3%, and 0.43, respectively, and are the best among all the previously published β-turn prediction methods. The Web server BetaTPred2 (http://www.imtech.res.in/raghava/betatpred2/) has been developed based on this approach. PMID:12592033

An extensive assessment of network alignment algorithms for comparison of brain connectomes.

PubMed

Milano, Marianna; Guzzi, Pietro Hiram; Tymofieva, Olga; Xu, Duan; Hess, Christofer; Veltri, Pierangelo; Cannataro, Mario

2017-06-06

Recently the study of the complex system of connections in neural systems, i.e. the connectome, has gained a central role in neurosciences. The modeling and analysis of connectomes are therefore a growing area. Here we focus on the representation of connectomes by using graph theory formalisms. Macroscopic human brain connectomes are usually derived from neuroimages; the analyzed brains are co-registered in the image domain and brought to a common anatomical space. An atlas is then applied in order to define anatomically meaningful regions that will serve as the nodes of the network - this process is referred to as parcellation. The atlas-based parcellations present some known limitations in cases of early brain development and abnormal anatomy. Consequently, it has been recently proposed to perform atlas-free random brain parcellation into nodes and align brains in the network space instead of the anatomical image space, as a way to deal with the unknown correspondences of the parcels. Such process requires modeling of the brain using graph theory and the subsequent comparison of the structure of graphs. The latter step may be modeled as a network alignment (NA) problem. In this work, we first define the problem formally, then we test six existing state of the art of network aligners on diffusion MRI-derived brain networks. We compare the performances of algorithms by assessing six topological measures. We also evaluated the robustness of algorithms to alterations of the dataset. The results confirm that NA algorithms may be applied in cases of atlas-free parcellation for a fully network-driven comparison of connectomes. The analysis shows MAGNA++ is the best global alignment algorithm. The paper presented a new analysis methodology that uses network alignment for validating atlas-free parcellation brain connectomes. The methodology has been experimented on several brain datasets.

Unsupervised parameter optimization for automated retention time alignment of severely shifted gas chromatographic data using the piecework alignment algorithm.

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

Pierce, Karisa M.; Wright, Bob W.; Synovec, Robert E.

2007-02-02

First, simulated chromatographic separations with declining retention time precision were used to study the performance of the piecewise retention time alignment algorithm and to demonstrate an unsupervised parameter optimization method. The average correlation coefficient between the first chromatogram and every other chromatogram in the data set was used to optimize the alignment parameters. This correlation method does not require a training set, so it is unsupervised and automated. This frees the user from needing to provide class information and makes the alignment algorithm more generally applicable to classifying completely unknown data sets. For a data set of simulated chromatograms wheremore » the average chromatographic peak was shifted past two neighboring peaks between runs, the average correlation coefficient of the raw data was 0.46 ± 0.25. After automated, optimized piecewise alignment, the average correlation coefficient was 0.93 ± 0.02. Additionally, a relative shift metric and principal component analysis (PCA) were used to independently quantify and categorize the alignment performance, respectively. The relative shift metric was defined as four times the standard deviation of a given peak’s retention time in all of the chromatograms, divided by the peak-width-at-base. The raw simulated data sets that were studied contained peaks with average relative shifts ranging between 0.3 and 3.0. Second, a “real” data set of gasoline separations was gathered using three different GC methods to induce severe retention time shifting. In these gasoline separations, retention time precision improved ~8 fold following alignment. Finally, piecewise alignment and the unsupervised correlation optimization method were applied to severely shifted GC separations of reformate distillation fractions. The effect of piecewise alignment on peak heights and peak areas is also reported. Piecewise alignment either did not change the peak height, or caused it to slightly decrease. The average relative difference in peak height after piecewise alignment was –0.20%. Piecewise alignment caused the peak areas to either stay the same, slightly increase, or slightly decrease. The average absolute relative difference in area after piecewise alignment was 0.15%.« less

SATe-II: very fast and accurate simultaneous estimation of multiple sequence alignments and phylogenetic trees.

PubMed

Liu, Kevin; Warnow, Tandy J; Holder, Mark T; Nelesen, Serita M; Yu, Jiaye; Stamatakis, Alexandros P; Linder, C Randal

2012-01-01

Highly accurate estimation of phylogenetic trees for large data sets is difficult, in part because multiple sequence alignments must be accurate for phylogeny estimation methods to be accurate. Coestimation of alignments and trees has been attempted but currently only SATé estimates reasonably accurate trees and alignments for large data sets in practical time frames (Liu K., Raghavan S., Nelesen S., Linder C.R., Warnow T. 2009b. Rapid and accurate large-scale coestimation of sequence alignments and phylogenetic trees. Science. 324:1561-1564). Here, we present a modification to the original SATé algorithm that improves upon SATé (which we now call SATé-I) in terms of speed and of phylogenetic and alignment accuracy. SATé-II uses a different divide-and-conquer strategy than SATé-I and so produces smaller more closely related subsets than SATé-I; as a result, SATé-II produces more accurate alignments and trees, can analyze larger data sets, and runs more efficiently than SATé-I. Generally, SATé is a metamethod that takes an existing multiple sequence alignment method as an input parameter and boosts the quality of that alignment method. SATé-II-boosted alignment methods are significantly more accurate than their unboosted versions, and trees based upon these improved alignments are more accurate than trees based upon the original alignments. Because SATé-I used maximum likelihood (ML) methods that treat gaps as missing data to estimate trees and because we found a correlation between the quality of tree/alignment pairs and ML scores, we explored the degree to which SATé's performance depends on using ML with gaps treated as missing data to determine the best tree/alignment pair. We present two lines of evidence that using ML with gaps treated as missing data to optimize the alignment and tree produces very poor results. First, we show that the optimization problem where a set of unaligned DNA sequences is given and the output is the tree and alignment of those sequences that maximize likelihood under the Jukes-Cantor model is uninformative in the worst possible sense. For all inputs, all trees optimize the likelihood score. Second, we show that a greedy heuristic that uses GTR+Gamma ML to optimize the alignment and the tree can produce very poor alignments and trees. Therefore, the excellent performance of SATé-II and SATé-I is not because ML is used as an optimization criterion for choosing the best tree/alignment pair but rather due to the particular divide-and-conquer realignment techniques employed.

Gene Coexpression Network Alignment and Conservation of Gene Modules between Two Grass Species: Maize and Rice[C][W][OA

PubMed Central

Ficklin, Stephen P.; Feltus, F. Alex

2011-01-01

One major objective for plant biology is the discovery of molecular subsystems underlying complex traits. The use of genetic and genomic resources combined in a systems genetics approach offers a means for approaching this goal. This study describes a maize (Zea mays) gene coexpression network built from publicly available expression arrays. The maize network consisted of 2,071 loci that were divided into 34 distinct modules that contained 1,928 enriched functional annotation terms and 35 cofunctional gene clusters. Of note, 391 maize genes of unknown function were found to be coexpressed within modules along with genes of known function. A global network alignment was made between this maize network and a previously described rice (Oryza sativa) coexpression network. The IsoRankN tool was used, which incorporates both gene homology and network topology for the alignment. A total of 1,173 aligned loci were detected between the two grass networks, which condensed into 154 conserved subgraphs that preserved 4,758 coexpression edges in rice and 6,105 coexpression edges in maize. This study provides an early view into maize coexpression space and provides an initial network-based framework for the translation of functional genomic and genetic information between these two vital agricultural species. PMID:21606319

Gene coexpression network alignment and conservation of gene modules between two grass species: maize and rice.

PubMed

Ficklin, Stephen P; Feltus, F Alex

2011-07-01

One major objective for plant biology is the discovery of molecular subsystems underlying complex traits. The use of genetic and genomic resources combined in a systems genetics approach offers a means for approaching this goal. This study describes a maize (Zea mays) gene coexpression network built from publicly available expression arrays. The maize network consisted of 2,071 loci that were divided into 34 distinct modules that contained 1,928 enriched functional annotation terms and 35 cofunctional gene clusters. Of note, 391 maize genes of unknown function were found to be coexpressed within modules along with genes of known function. A global network alignment was made between this maize network and a previously described rice (Oryza sativa) coexpression network. The IsoRankN tool was used, which incorporates both gene homology and network topology for the alignment. A total of 1,173 aligned loci were detected between the two grass networks, which condensed into 154 conserved subgraphs that preserved 4,758 coexpression edges in rice and 6,105 coexpression edges in maize. This study provides an early view into maize coexpression space and provides an initial network-based framework for the translation of functional genomic and genetic information between these two vital agricultural species.

A Probabilistic Model of Local Sequence Alignment That Simplifies Statistical Significance Estimation

PubMed Central

Eddy, Sean R.

2008-01-01

Sequence database searches require accurate estimation of the statistical significance of scores. Optimal local sequence alignment scores follow Gumbel distributions, but determining an important parameter of the distribution (λ) requires time-consuming computational simulation. Moreover, optimal alignment scores are less powerful than probabilistic scores that integrate over alignment uncertainty (“Forward” scores), but the expected distribution of Forward scores remains unknown. Here, I conjecture that both expected score distributions have simple, predictable forms when full probabilistic modeling methods are used. For a probabilistic model of local sequence alignment, optimal alignment bit scores (“Viterbi” scores) are Gumbel-distributed with constant λ = log 2, and the high scoring tail of Forward scores is exponential with the same constant λ. Simulation studies support these conjectures over a wide range of profile/sequence comparisons, using 9,318 profile-hidden Markov models from the Pfam database. This enables efficient and accurate determination of expectation values (E-values) for both Viterbi and Forward scores for probabilistic local alignments. PMID:18516236

Capillary Printing of Highly Aligned Silver Nanowire Transparent Electrodes for High-Performance Optoelectronic Devices.

PubMed

Kang, Saewon; Kim, Taehyo; Cho, Seungse; Lee, Youngoh; Choe, Ayoung; Walker, Bright; Ko, Seo-Jin; Kim, Jin Young; Ko, Hyunhyub

2015-12-09

Percolation networks of silver nanowires (AgNWs) are commonly used as transparent conductive electrodes (TCEs) for a variety of optoelectronic applications, but there have been no attempts to precisely control the percolation networks of AgNWs that critically affect the performances of TCEs. Here, we introduce a capillary printing technique to precisely control the NW alignment and the percolation behavior of AgNW networks. Notably, partially aligned AgNW networks exhibit a greatly lower percolation threshold, which leads to the substantial improvement of optical transmittance (96.7%) at a similar sheet resistance (19.5 Ω sq(-1)) as compared to random AgNW networks (92.9%, 20 Ω sq(-1)). Polymer light-emitting diodes (PLEDs) using aligned AgNW electrodes show a 30% enhanced maximum luminance (33068 cd m(-2)) compared to that with random AgNWs and a high luminance efficiency (14.25 cd A(-1)), which is the highest value reported so far using indium-free transparent electrodes for fluorescent PLEDs. In addition, polymer solar cells (PSCs) using aligned AgNW electrodes exhibit a power conversion efficiency (PCE) of 8.57%, the highest value ever reported to date for PSCs using AgNW electrodes.

Modular and configurable optimal sequence alignment software: Cola.

PubMed

Zamani, Neda; Sundström, Görel; Höppner, Marc P; Grabherr, Manfred G

2014-01-01

The fundamental challenge in optimally aligning homologous sequences is to define a scoring scheme that best reflects the underlying biological processes. Maximising the overall number of matches in the alignment does not always reflect the patterns by which nucleotides mutate. Efficiently implemented algorithms that can be parameterised to accommodate more complex non-linear scoring schemes are thus desirable. We present Cola, alignment software that implements different optimal alignment algorithms, also allowing for scoring contiguous matches of nucleotides in a nonlinear manner. The latter places more emphasis on short, highly conserved motifs, and less on the surrounding nucleotides, which can be more diverged. To illustrate the differences, we report results from aligning 14,100 sequences from 3' untranslated regions of human genes to 25 of their mammalian counterparts, where we found that a nonlinear scoring scheme is more consistent than a linear scheme in detecting short, conserved motifs. Cola is freely available under LPGL from https://github.com/nedaz/cola.

Net2Align: An Algorithm For Pairwise Global Alignment of Biological Networks

PubMed Central

Wadhwab, Gulshan; Upadhyayaa, K. C.

2016-01-01

The amount of data on molecular interactions is growing at an enormous pace, whereas the progress of methods for analysing this data is still lacking behind. Particularly, in the area of comparative analysis of biological networks, where one wishes to explore the similarity between two biological networks, this holds a potential problem. In consideration that the functionality primarily runs at the network level, it advocates the need for robust comparison methods. In this paper, we describe Net2Align, an algorithm for pairwise global alignment that can perform node-to-node correspondences as well as edge-to-edge correspondences into consideration. The uniqueness of our algorithm is in the fact that it is also able to detect the type of interaction, which is essential in case of directed graphs. The existing algorithm is only able to identify the common nodes but not the common edges. Another striking feature of the algorithm is that it is able to remove duplicate entries in case of variable datasets being aligned. This is achieved through creation of a local database which helps exclude duplicate links. In a pervasive computational study on gene regulatory network, we establish that our algorithm surpasses its counterparts in its results. Net2Align has been implemented in Java 7 and the source code is available as supplementary files. PMID:28356678

Bioinspired Tuning of Hydrogel Permeability-Rigidity Dependency for 3D Cell Culture

NASA Astrophysics Data System (ADS)

Lee, Min Kyung; Rich, Max H.; Baek, Kwanghyun; Lee, Jonghwi; Kong, Hyunjoon

2015-03-01

Hydrogels are being extensively used for three-dimensional immobilization and culture of cells in fundamental biological studies, biochemical processes, and clinical treatments. However, it is still a challenge to support viability and regulate phenotypic activities of cells in a structurally stable gel, because the gel becomes less permeable with increasing rigidity. To resolve this challenge, this study demonstrates a unique method to enhance the permeability of a cell-laden hydrogel while avoiding a significant change in rigidity of the gel. Inspired by the grooved skin textures of marine organisms, a hydrogel is assembled to present computationally optimized micro-sized grooves on the surface. Separately, a gel is engineered to preset aligned microchannels similar to a plant's vascular bundles through a uniaxial freeze-drying process. The resulting gel displays significantly increased water diffusivity with reduced changes of gel stiffness, exclusively when the microgrooves and microchannels are aligned together. No significant enhancement of rehydration is achieved when the microgrooves and microchannels are not aligned. Such material design greatly enhances viability and neural differentiation of stem cells and 3D neural network formation within the gel.

Magnetically aligned phospholipid bilayers in weak magnetic fields: optimization, mechanism, and advantages for X-band EPR studies.

PubMed

Cardon, Thomas B; Tiburu, Elvis K; Lorigan, Gary A

2003-03-01

Our lab is developing a spin-labeled EPR spectroscopic technique complementary to solid-state NMR studies to study the structure, orientation, and dynamics of uniaxially aligned integral membrane proteins inserted into magnetically aligned discotic phospholipid bilayers, or bicelles. The focus of this study is to optimize and understand the mechanisms involved in the magnetic alignment process of bicelle disks in weak magnetic fields. Developing experimental conditions for optimized magnetic alignment of bicelles in low magnetic fields may prove useful to study the dynamics of membrane proteins and its interactions with lipids, drugs, steroids, signaling events, other proteins, etc. In weak magnetic fields, the magnetic alignment of Tm(3+)-doped bicelle disks was thermodynamically and kinetically very sensitive to experimental conditions. Tm(3+)-doped bicelles were magnetically aligned using the following optimized procedure: the temperature was slowly raised at a rate of 1.9K/min from an initial temperature being between 298 and 307K to a final temperature of 318K in the presence of a static magnetic field of 6300G. The spin probe 3beta-doxyl-5alpha-cholestane (cholestane) was inserted into the bicelle disks and utilized to monitor bicelle alignment by analyzing the anisotropic hyperfine splitting for the corresponding EPR spectra. The phases of the bicelles were determined using solid-state 2H NMR spectroscopy and compared with the corresponding EPR spectra. Macroscopic alignment commenced in the liquid crystalline nematic phase (307K), continued to increase upon slowly raising the temperature, and was well-aligned in the liquid crystalline lamellar smectic phase (318K).

Rod-Shaped Neural Units for Aligned 3D Neural Network Connection.

PubMed

Kato-Negishi, Midori; Onoe, Hiroaki; Ito, Akane; Takeuchi, Shoji

2017-08-01

This paper proposes neural tissue units with aligned nerve fibers (called rod-shaped neural units) that connect neural networks with aligned neurons. To make the proposed units, 3D fiber-shaped neural tissues covered with a calcium alginate hydrogel layer are prepared with a microfluidic system and are cut in an accurate and reproducible manner. These units have aligned nerve fibers inside the hydrogel layer and connectable points on both ends. By connecting the units with a poly(dimethylsiloxane) guide, 3D neural tissues can be constructed and maintained for more than two weeks of culture. In addition, neural networks can be formed between the different neural units via synaptic connections. Experimental results indicate that the proposed rod-shaped neural units are effective tools for the construction of spatially complex connections with aligned nerve fibers in vitro. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Projected power iteration for network alignment

NASA Astrophysics Data System (ADS)

Onaran, Efe; Villar, Soledad

2017-08-01

The network alignment problem asks for the best correspondence between two given graphs, so that the largest possible number of edges are matched. This problem appears in many scientific problems (like the study of protein-protein interactions) and it is very closely related to the quadratic assignment problem which has graph isomorphism, traveling salesman and minimum bisection problems as particular cases. The graph matching problem is NP-hard in general. However, under some restrictive models for the graphs, algorithms can approximate the alignment efficiently. In that spirit the recent work by Feizi and collaborators introduce EigenAlign, a fast spectral method with convergence guarantees for Erd-s-Renyí graphs. In this work we propose the algorithm Projected Power Alignment, which is a projected power iteration version of EigenAlign. We numerically show it improves the recovery rates of EigenAlign and we describe the theory that may be used to provide performance guarantees for Projected Power Alignment.

Implied alignment: a synapomorphy-based multiple-sequence alignment method and its use in cladogram search

NASA Technical Reports Server (NTRS)

Wheeler, Ward C.

2003-01-01

A method to align sequence data based on parsimonious synapomorphy schemes generated by direct optimization (DO; earlier termed optimization alignment) is proposed. DO directly diagnoses sequence data on cladograms without an intervening multiple-alignment step, thereby creating topology-specific, dynamic homology statements. Hence, no multiple-alignment is required to generate cladograms. Unlike general and globally optimal multiple-alignment procedures, the method described here, implied alignment (IA), takes these dynamic homologies and traces them back through a single cladogram, linking the unaligned sequence positions in the terminal taxa via DO transformation series. These "lines of correspondence" link ancestor-descendent states and, when displayed as linearly arrayed columns without hypothetical ancestors, are largely indistinguishable from standard multiple alignment. Since this method is based on synapomorphy, the treatment of certain classes of insertion-deletion (indel) events may be different from that of other alignment procedures. As with all alignment methods, results are dependent on parameter assumptions such as indel cost and transversion:transition ratios. Such an IA could be used as a basis for phylogenetic search, but this would be questionable since the homologies derived from the implied alignment depend on its natal cladogram and any variance, between DO and IA + Search, due to heuristic approach. The utility of this procedure in heuristic cladogram searches using DO and the improvement of heuristic cladogram cost calculations are discussed. c2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.

Molecular systematics of terraranas (Anura: Brachycephaloidea) with an assessment of the effects of alignment and optimality criteria.

PubMed

Padial, José M; Grant, Taran; Frost, Darrel R

2014-06-26

Brachycephaloidea is a monophyletic group of frogs with more than 1000 species distributed throughout the New World tropics, subtropics, and Andean regions. Recently, the group has been the target of multiple molecular phylogenetic analyses, resulting in extensive changes in its taxonomy. Here, we test previous hypotheses of phylogenetic relationships for the group by combining available molecular evidence (sequences of 22 genes representing 431 ingroup and 25 outgroup terminals) and performing a tree-alignment analysis under the parsimony optimality criterion using the program POY. To elucidate the effects of alignment and optimality criterion on phylogenetic inferences, we also used the program MAFFT to obtain a similarity-alignment for analysis under both parsimony and maximum likelihood using the programs TNT and GARLI, respectively. Although all three analytical approaches agreed on numerous points, there was also extensive disagreement. Tree-alignment under parsimony supported the monophyly of the ingroup and the sister group relationship of the monophyletic marsupial frogs (Hemiphractidae), while maximum likelihood and parsimony analyses of the MAFFT similarity-alignment did not. All three methods differed with respect to the position of Ceuthomantis smaragdinus (Ceuthomantidae), with tree-alignment using parsimony recovering this species as the sister of Pristimantis + Yunganastes. All analyses rejected the monophyly of Strabomantidae and Strabomantinae as originally defined, and the tree-alignment analysis under parsimony further rejected the recently redefined Craugastoridae and Pristimantinae. Despite the greater emphasis in the systematics literature placed on the choice of optimality criterion for evaluating trees than on the choice of method for aligning DNA sequences, we found that the topological differences attributable to the alignment method were as great as those caused by the optimality criterion. Further, the optimal tree-alignment indicates that insertions and deletions occurred in twice as many aligned positions as implied by the optimal similarity-alignment, confirming previous findings that sequence turnover through insertion and deletion events plays a greater role in molecular evolution than indicated by similarity-alignments. Our results also provide a clear empirical demonstration of the different effects of wildcard taxa produced by missing data in parsimony and maximum likelihood analyses. Specifically, maximum likelihood analyses consistently (81% bootstrap frequency) provided spurious resolution despite a lack of evidence, whereas parsimony correctly depicted the ambiguity due to missing data by collapsing unsupported nodes. We provide a new taxonomy for the group that retains previously recognized Linnaean taxa except for Ceuthomantidae, Strabomantidae, and Strabomantinae. A phenotypically diagnosable superfamily is recognized formally as Brachycephaloidea, with the informal, unranked name terrarana retained as the standard common name for these frogs. We recognize three families within Brachycephaloidea that are currently diagnosable solely on molecular grounds (Brachycephalidae, Craugastoridae, and Eleutherodactylidae), as well as five subfamilies (Craugastorinae, Eleutherodactylinae, Holoadeninae, Phyzelaphryninae, and Pristimantinae) corresponding in large part to previous families and subfamilies. Our analyses upheld the monophyly of all tested genera, but we found numerous subgeneric taxa to be non-monophyletic and modified the taxonomy accordingly.

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

Wu, Chase

A number of Department of Energy (DOE) science applications, involving exascale computing systems and large experimental facilities, are expected to generate large volumes of data, in the range of petabytes to exabytes, which will be transported over wide-area networks for the purpose of storage, visualization, and analysis. The objectives of this proposal are to (1) develop and test the component technologies and their synthesis methods to achieve source-to-sink high-performance flows, and (2) develop tools that provide these capabilities through simple interfaces to users and applications. In terms of the former, we propose to develop (1) optimization methods that align andmore » transition multiple storage flows to multiple network flows on multicore, multibus hosts; and (2) edge and long-haul network path realization and maintenance using advanced provisioning methods including OSCARS and OpenFlow. We also propose synthesis methods that combine these individual technologies to compose high-performance flows using a collection of constituent storage-network flows, and realize them across the storage and local network connections as well as long-haul connections. We propose to develop automated user tools that profile the hosts, storage systems, and network connections; compose the source-to-sink complex flows; and set up and maintain the needed network connections.« less

Probabilistic biological network alignment.

PubMed

Todor, Andrei; Dobra, Alin; Kahveci, Tamer

2013-01-01

Interactions between molecules are probabilistic events. An interaction may or may not happen with some probability, depending on a variety of factors such as the size, abundance, or proximity of the interacting molecules. In this paper, we consider the problem of aligning two biological networks. Unlike existing methods, we allow one of the two networks to contain probabilistic interactions. Allowing interaction probabilities makes the alignment more biologically relevant at the expense of explosive growth in the number of alternative topologies that may arise from different subsets of interactions that take place. We develop a novel method that efficiently and precisely characterizes this massive search space. We represent the topological similarity between pairs of aligned molecules (i.e., proteins) with the help of random variables and compute their expected values. We validate our method showing that, without sacrificing the running time performance, it can produce novel alignments. Our results also demonstrate that our method identifies biologically meaningful mappings under a comprehensive set of criteria used in the literature as well as the statistical coherence measure that we developed to analyze the statistical significance of the similarity of the functions of the aligned protein pairs.

QUASAR--scoring and ranking of sequence-structure alignments.

PubMed

Birzele, Fabian; Gewehr, Jan E; Zimmer, Ralf

2005-12-15

Sequence-structure alignments are a common means for protein structure prediction in the fields of fold recognition and homology modeling, and there is a broad variety of programs that provide such alignments based on sequence similarity, secondary structure or contact potentials. Nevertheless, finding the best sequence-structure alignment in a pool of alignments remains a difficult problem. QUASAR (quality of sequence-structure alignments ranking) provides a unifying framework for scoring sequence-structure alignments that aids finding well-performing combinations of well-known and custom-made scoring schemes. Those scoring functions can be benchmarked against widely accepted quality scores like MaxSub, TMScore, Touch and APDB, thus enabling users to test their own alignment scores against 'standard-of-truth' structure-based scores. Furthermore, individual score combinations can be optimized with respect to benchmark sets based on known structural relationships using QUASAR's in-built optimization routines.

Tweaked residual convolutional network for face alignment

NASA Astrophysics Data System (ADS)

Du, Wenchao; Li, Ke; Zhao, Qijun; Zhang, Yi; Chen, Hu

2017-08-01

We propose a novel Tweaked Residual Convolutional Network approach for face alignment with two-level convolutional networks architecture. Specifically, the first-level Tweaked Convolutional Network (TCN) module predicts the landmark quickly but accurately enough as a preliminary, by taking low-resolution version of the detected face holistically as the input. The following Residual Convolutional Networks (RCN) module progressively refines the landmark by taking as input the local patch extracted around the predicted landmark, particularly, which allows the Convolutional Neural Network (CNN) to extract local shape-indexed features to fine tune landmark position. Extensive evaluations show that the proposed Tweaked Residual Convolutional Network approach outperforms existing methods.

Optimized smith waterman processor design for breast cancer early diagnosis

NASA Astrophysics Data System (ADS)

Nurdin, D. S.; Isa, M. N.; Ismail, R. C.; Ahmad, M. I.

2017-09-01

This paper presents an optimized design of Processing Element (PE) of Systolic Array (SA) which implements affine gap penalty Smith Waterman (SW) algorithm on the Xilinx Virtex-6 XC6VLX75T Field Programmable Gate Array (FPGA) for Deoxyribonucleic Acid (DNA) sequence alignment. The PE optimization aims to reduce PE logic resources to increase number of PEs in FPGA for higher degree of parallelism during alignment matrix computations. This is useful for aligning long DNA-based disease sequence such as Breast Cancer (BC) for early diagnosis. The optimized PE architecture has the smallest PE area with 15 slices in a PE and 776 PEs implemented in the Virtex - 6 FPGA.

Using structure to explore the sequence alignment space of remote homologs.

PubMed

Kuziemko, Andrew; Honig, Barry; Petrey, Donald

2011-10-01

Protein structure modeling by homology requires an accurate sequence alignment between the query protein and its structural template. However, sequence alignment methods based on dynamic programming (DP) are typically unable to generate accurate alignments for remote sequence homologs, thus limiting the applicability of modeling methods. A central problem is that the alignment that is "optimal" in terms of the DP score does not necessarily correspond to the alignment that produces the most accurate structural model. That is, the correct alignment based on structural superposition will generally have a lower score than the optimal alignment obtained from sequence. Variations of the DP algorithm have been developed that generate alternative alignments that are "suboptimal" in terms of the DP score, but these still encounter difficulties in detecting the correct structural alignment. We present here a new alternative sequence alignment method that relies heavily on the structure of the template. By initially aligning the query sequence to individual fragments in secondary structure elements and combining high-scoring fragments that pass basic tests for "modelability", we can generate accurate alignments within a small ensemble. Our results suggest that the set of sequences that can currently be modeled by homology can be greatly extended.

Interactive software tool to comprehend the calculation of optimal sequence alignments with dynamic programming.

PubMed

Ibarra, Ignacio L; Melo, Francisco

2010-07-01

Dynamic programming (DP) is a general optimization strategy that is successfully used across various disciplines of science. In bioinformatics, it is widely applied in calculating the optimal alignment between pairs of protein or DNA sequences. These alignments form the basis of new, verifiable biological hypothesis. Despite its importance, there are no interactive tools available for training and education on understanding the DP algorithm. Here, we introduce an interactive computer application with a graphical interface, for the purpose of educating students about DP. The program displays the DP scoring matrix and the resulting optimal alignment(s), while allowing the user to modify key parameters such as the values in the similarity matrix, the sequence alignment algorithm version and the gap opening/extension penalties. We hope that this software will be useful to teachers and students of bioinformatics courses, as well as researchers who implement the DP algorithm for diverse applications. The software is freely available at: http:/melolab.org/sat. The software is written in the Java computer language, thus it runs on all major platforms and operating systems including Windows, Mac OS X and LINUX. All inquiries or comments about this software should be directed to Francisco Melo at fmelo@bio.puc.cl.

Deep neural network-based domain adaptation for classification of remote sensing images

NASA Astrophysics Data System (ADS)

Ma, Li; Song, Jiazhen

2017-10-01

We investigate the effectiveness of deep neural network for cross-domain classification of remote sensing images in this paper. In the network, class centroid alignment is utilized as a domain adaptation strategy, making the network able to transfer knowledge from the source domain to target domain on a per-class basis. Since predicted labels of target data should be used to estimate the centroid of each class, we use overall centroid alignment as a coarse domain adaptation method to improve the estimation accuracy. In addition, rectified linear unit is used as the activation function to produce sparse features, which may improve the separation capability. The proposed network can provide both aligned features and an adaptive classifier, as well as obtain label-free classification of target domain data. The experimental results using Hyperion, NCALM, and WorldView-2 remote sensing images demonstrated the effectiveness of the proposed approach.

Optimization of bicelle lipid composition and temperature for EPR spectroscopy of aligned membranes.

PubMed

McCaffrey, Jesse E; James, Zachary M; Thomas, David D

2015-01-01

We have optimized the magnetic alignment of phospholipid bilayered micelles (bicelles) for EPR spectroscopy, by varying lipid composition and temperature. Bicelles have been extensively used in NMR spectroscopy for several decades, in order to obtain aligned samples in a near-native membrane environment and take advantage of the intrinsic sensitivity of magnetic resonance to molecular orientation. Recently, bicelles have also seen increasing use in EPR, which offers superior sensitivity and orientational resolution. However, the low magnetic field strength (less than 1 T) of most conventional EPR spectrometers results in homogeneously oriented bicelles only at a temperature well above physiological. To optimize bicelle composition for magnetic alignment at reduced temperature, we prepared bicelles containing varying ratios of saturated (DMPC) and unsaturated (POPC) phospholipids, using EPR spectra of a spin-labeled fatty acid to assess alignment as a function of lipid composition and temperature. Spectral analysis showed that bicelles containing an equimolar mixture of DMPC and POPC homogeneously align at 298 K, 20 K lower than conventional DMPC-only bicelles. It is now possible to perform EPR studies of membrane protein structure and dynamics in well-aligned bicelles at physiological temperatures and below. Copyright © 2014 Elsevier Inc. All rights reserved.

3D highway alignment optimization for Brookeville Bypass : final report.

DOT National Transportation Integrated Search

2005-06-01

This study applies the previously developed Highway Alignment Optimization (HAO) : model to the MD 97 Bypass project in Brookeville, Maryland. The objective of this study is to : demonstrate the applicability of the HAO model to a real highway projec...

Piezoresistivity of mechanically drawn single-walled carbon nanotube (SWCNT) thin films-: mechanism and optimizing principle

NASA Astrophysics Data System (ADS)

Obitayo, Waris

The individual carbon nanotube (CNT) based strain sensors have been found to have excellent piezoresistive properties with a reported gauge factor (GF) of up to 3000. This GF on the other hand, has been shown to be structurally dependent on the nanotubes. In contrast, to individual CNT based strain sensors, the ensemble CNT based strain sensors have very low GFs e.g. for a single walled carbon nanotube (SWCNT) thin film strain sensor, GF is ~1. As a result, studies which are mostly numerical/analytical have revealed the dependence of piezoresistivity on key parameters like concentration, orientation, length and diameter, aspect ratio, energy barrier height and Poisson ratio of polymer matrix. The fundamental understanding of the piezoresistive mechanism in an ensemble CNT based strain sensor still remains unclear, largely due to discrepancies in the outcomes of these numerical studies. Besides, there have been little or no experimental confirmation of these studies. The goal of my PhD is to study the mechanism and the optimizing principle of a SWCNT thin film strain sensor and provide experimental validation of the numerical/analytical investigations. The dependence of the piezoresistivity on key parameters like orientation, network density, bundle diameter (effective tunneling area), and length is studied, and how one can effectively optimize the piezoresistive behavior of a SWCNT thin film strain sensors. To reach this goal, my first research accomplishment involves the study of orientation of SWCNTs and its effect on the piezoresistivity of mechanically drawn SWCNT thin film based piezoresistive sensors. Using polarized Raman spectroscopy analysis and coupled electrical-mechanical test, a quantitative relationship between the strain sensitivity and SWCNT alignment order parameter was established. As compared to randomly oriented SWCNT thin films, the one with draw ratio of 3.2 exhibited ~6x increase on the GF. My second accomplishment involves studying the influence of the network density on the piezoresistivity of mechanically drawn SWCNT thin films. Mechanically drawn SWCNT thin films with different layer (or thickness) e.g. 1-layer, 3-layer, 10-layer and 20-layer SWCNT thin films were prepared to understand the variation of SWCNT network density as well as the alignment of SWCNTs on the strain sensitivity. The less entangled SWCNT bundles observed in the sparse network density (1- layer and 3-layer SWCNT thin films) allows for easy alignment and the best gauge factors. As compared to the randomly oriented SWCNT thin films, the one with draw ratio of 3.2 exhibited ~8x increase on the GF for the 1-layer SWCNT thin films while the 20-layer SWCNT thin films exhibited ~3x increase in the GF. My third accomplishment examines the effect of SWCNT bundles with different diameters on the piezoresistive behavior of mechanically drawn SWCNT thin films. SWCNT thin film network of sparse morphology (1-layer) with different bundle sizes were prepared by varying the sonication duration e.g. S0.5hr, S4hr, S10hr and S20hr and using spraying coating. The GF increased by a factor of ~10 when the randomly oriented SWCNT thin film was stretched to a draw ratio of 3.2 for the S0.5hr SWCNT thin films and by a factor of ~2 for the S20hr SWCNT thin films. Three main mechanisms were attributed to this behavior e.g. effect of concentration of exfoliated nanotubes, bundle reduction due to mechanical stretching, and influence of bundle length on the alignment of SWCNTs. Furthermore, information about the average length and length distribution is very essential when investigating the influence of individual nanotube length on the strain sensitivity. With that in mind, we would use our previously developed preparative ultracentrifuge method (PUM), and our newly developed gel electrophoresis and simultaneous Raman and photoluminescence spectroscopy (GEP-SRSPL) to characterize the average length and length distribution of individual SWCNTs respectively.

Strategic Planning to Conduct Joint Force Network Operations: A Content Analysis of NETOPS Organizations Strategic Plans

DTIC Science & Technology

2007-03-01

information dominance , Joint Network Operations (NETOPS) organizations need to be strategically aligned. As result, to enhance the capabilities-based effects of NETOPS and reduce our NETOP infrastructures susceptibility to compromise. Once the key organizations were identified, their strategic plans were analyzed using a structured content analysis framework. The results illustrated that the strategic plans were aligned with the community of interests tasking to conduct NETOPS. Further research is required into the strategic alignment beyond the strategic

Some aspects of SR beamline alignment

NASA Astrophysics Data System (ADS)

Gaponov, Yu. A.; Cerenius, Y.; Nygaard, J.; Ursby, T.; Larsson, K.

2011-09-01

Based on the Synchrotron Radiation (SR) beamline optical element-by-element alignment with analysis of the alignment results an optimized beamline alignment algorithm has been designed and developed. The alignment procedures have been designed and developed for the MAX-lab I911-4 fixed energy beamline. It has been shown that the intermediate information received during the monochromator alignment stage can be used for the correction of both monochromator and mirror without the next stages of alignment of mirror, slits, sample holder, etc. Such an optimization of the beamline alignment procedures decreases the time necessary for the alignment and becomes useful and helpful in the case of any instability of the beamline optical elements, storage ring electron orbit or the wiggler insertion device, which could result in the instability of angular and positional parameters of the SR beam. A general purpose software package for manual, semi-automatic and automatic SR beamline alignment has been designed and developed using the developed algorithm. The TANGO control system is used as the middle-ware between the stand-alone beamline control applications BLTools, BPMonitor and the beamline equipment.

Alternative alignments development and evaluation for the US 220 project in Maryland.

DOT National Transportation Integrated Search

2011-06-01

This project aims to find the preferred alternative alignments for the Maryland section of existing US 220, using the highway : alignment optimization (HAO) model. The model was used to explore alternative alignments within a 4,000 foot-wide buffer o...

An optimal beam alignment method for large-scale distributed space surveillance radar system

NASA Astrophysics Data System (ADS)

Huang, Jian; Wang, Dongya; Xia, Shuangzhi

2018-06-01

Large-scale distributed space surveillance radar is a very important ground-based equipment to maintain a complete catalogue for Low Earth Orbit (LEO) space debris. However, due to the thousands of kilometers distance between each sites of the distributed radar system, how to optimally implement the Transmitting/Receiving (T/R) beams alignment in a great space using the narrow beam, which proposed a special and considerable technical challenge in the space surveillance area. According to the common coordinate transformation model and the radar beam space model, we presented a two dimensional projection algorithm for T/R beam using the direction angles, which could visually describe and assess the beam alignment performance. Subsequently, the optimal mathematical models for the orientation angle of the antenna array, the site location and the T/R beam coverage are constructed, and also the beam alignment parameters are precisely solved. At last, we conducted the optimal beam alignment experiments base on the site parameters of Air Force Space Surveillance System (AFSSS). The simulation results demonstrate the correctness and effectiveness of our novel method, which can significantly stimulate the construction for the LEO space debris surveillance equipment.

Optimizing Mechanical Alignment With Modular Stems in Revision TKA.

PubMed

Fleischman, Andrew N; Azboy, Ibrahim; Restrepo, Camilo; Maltenfort, Mitchell G; Parvizi, Javad

2017-09-01

Although mechanical alignment is critical for optimal function and long-term implant durability, the role of modular stems in achieving ideal alignment is unclear. We identified 319 revision total knee arthroplasty from 2003-2013, for which stem length, stem diameter, and stem fixation method were recorded prospectively. Three-dimensional canal-filling ratio, the product of canal-filling ratio at the stem tip in both the anteroposterior and lateral planes, and alignment were measured radiographically. Ideal alignment of the femur was considered to be 95° in the anteroposterior (AP) plane and from 1° of extension to 4° of flexion in the lateral plane, and ideal tibial alignment was considered to be 90° in the AP plane. Even after accounting for difference in stem size and canal-fill, ideal AP alignment was more reliably achieved with press-fit stems. Furthermore, increased engagement of the diaphysis and its anatomical axis with canal-filling stems facilitates accurate alignment. Copyright © 2017 Elsevier Inc. All rights reserved.

Clustalnet: the joining of Clustal and CORBA.

PubMed

Campagne, F

2000-07-01

Performing sequence alignment operations from a different program than the original sequence alignment code, and/or through a network connection, is often required. Interactive alignment editors and large-scale biological data analysis are common examples where such a flexibility is important. Interoperability between the alignment engine and the client should be obtained regardless of the architectures and programming languages of the server and client. Clustalnet, a Clustal alignment CORBA server is described, which was developed on the basis of Clustalw. This server brings the robustness of the algorithms and implementations of Clustal to a new level of reuse. A Clustalnet server object can be accessed from a program, transparently through the network. We present interfaces to perform the alignment operations and to control these operations via immutable contexts. The interfaces that select the contexts do not depend on the nature of the operation to be performed, making the design modular. The IDL interfaces presented here are not specific to Clustal and can be implemented on top of different sequence alignment algorithm implementations.

System alignment using the Talbot effect

NASA Astrophysics Data System (ADS)

Chevallier, Raymond; Le Falher, Eric; Heggarty, Kevin

1990-08-01

The Talbot effect is utilized to correct an alignment problem related to a neural network used for image recognition, which required the alignment of a spatial light modulator (SLM) with the input module. A mathematical model which employs the Fresnel diffraction theory is presented to describe the method. The calculation of the diffracted amplitude describes the wavefront sphericity and the original object transmittance function in order to qualify the lateral shift of the Talbot image. Another explanation is set forth in terms of plane-wave illumination in the neural network. Using a Fourier series and by describing planes where all the harmonics are in phase, the reconstruction of Talbot images is explained. The alignment is effective when the lenslet array is aligned on the even Talbot images of the SLM pixels and the incident wave is a plane wave. The alignment is evaluated in terms of source and periodicity errors, tilt of the incident plane waves, and finite object dimensions. The effects of the error sources are concluded to be negligible, the lenslet array is shown to be successfully aligned with the SLM, and other alignment applications are shown to be possible.

A Workflow to Improve the Alignment of Prostate Imaging with Whole-mount Histopathology.

PubMed

Yamamoto, Hidekazu; Nir, Dror; Vyas, Lona; Chang, Richard T; Popert, Rick; Cahill, Declan; Challacombe, Ben; Dasgupta, Prokar; Chandra, Ashish

2014-08-01

Evaluation of prostate imaging tests against whole-mount histology specimens requires accurate alignment between radiologic and histologic data sets. Misalignment results in false-positive and -negative zones as assessed by imaging. We describe a workflow for three-dimensional alignment of prostate imaging data against whole-mount prostatectomy reference specimens and assess its performance against a standard workflow. Ethical approval was granted. Patients underwent motorized transrectal ultrasound (Prostate Histoscanning) to generate a three-dimensional image of the prostate before radical prostatectomy. The test workflow incorporated steps for axial alignment between imaging and histology, size adjustments following formalin fixation, and use of custom-made parallel cutters and digital caliper instruments. The control workflow comprised freehand cutting and assumed homogeneous block thicknesses at the same relative angles between pathology and imaging sections. Thirty radical prostatectomy specimens were histologically and radiologically processed, either by an alignment-optimized workflow (n = 20) or a control workflow (n = 10). The optimized workflow generated tissue blocks of heterogeneous thicknesses but with no significant drifting in the cutting plane. The control workflow resulted in significantly nonparallel blocks, accurately matching only one out of four histology blocks to their respective imaging data. The image-to-histology alignment accuracy was 20% greater in the optimized workflow (P < .0001), with higher sensitivity (85% vs. 69%) and specificity (94% vs. 73%) for margin prediction in a 5 × 5-mm grid analysis. A significantly better alignment was observed in the optimized workflow. Evaluation of prostate imaging biomarkers using whole-mount histology references should include a test-to-reference spatial alignment workflow. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Efficient and robust model-to-image alignment using 3D scale-invariant features.

PubMed

Toews, Matthew; Wells, William M

2013-04-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. Copyright © 2012 Elsevier B.V. All rights reserved.

Efficient and Robust Model-to-Image Alignment using 3D Scale-Invariant Features

PubMed Central

Toews, Matthew; Wells, William M.

2013-01-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a-posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. PMID:23265799

Matt: local flexibility aids protein multiple structure alignment.

PubMed

Menke, Matthew; Berger, Bonnie; Cowen, Lenore

2008-01-01

Even when there is agreement on what measure a protein multiple structure alignment should be optimizing, finding the optimal alignment is computationally prohibitive. One approach used by many previous methods is aligned fragment pair chaining, where short structural fragments from all the proteins are aligned against each other optimally, and the final alignment chains these together in geometrically consistent ways. Ye and Godzik have recently suggested that adding geometric flexibility may help better model protein structures in a variety of contexts. We introduce the program Matt (Multiple Alignment with Translations and Twists), an aligned fragment pair chaining algorithm that, in intermediate steps, allows local flexibility between fragments: small translations and rotations are temporarily allowed to bring sets of aligned fragments closer, even if they are physically impossible under rigid body transformations. After a dynamic programming assembly guided by these "bent" alignments, geometric consistency is restored in the final step before the alignment is output. Matt is tested against other recent multiple protein structure alignment programs on the popular Homstrad and SABmark benchmark datasets. Matt's global performance is competitive with the other programs on Homstrad, but outperforms the other programs on SABmark, a benchmark of multiple structure alignments of proteins with more distant homology. On both datasets, Matt demonstrates an ability to better align the ends of alpha-helices and beta-strands, an important characteristic of any structure alignment program intended to help construct a structural template library for threading approaches to the inverse protein-folding problem. The related question of whether Matt alignments can be used to distinguish distantly homologous structure pairs from pairs of proteins that are not homologous is also considered. For this purpose, a p-value score based on the length of the common core and average root mean squared deviation (RMSD) of Matt alignments is shown to largely separate decoys from homologous protein structures in the SABmark benchmark dataset. We postulate that Matt's strong performance comes from its ability to model proteins in different conformational states and, perhaps even more important, its ability to model backbone distortions in more distantly related proteins.

Two Simple and Efficient Algorithms to Compute the SP-Score Objective Function of a Multiple Sequence Alignment.

PubMed

Ranwez, Vincent

2016-01-01

Multiple sequence alignment (MSA) is a crucial step in many molecular analyses and many MSA tools have been developed. Most of them use a greedy approach to construct a first alignment that is then refined by optimizing the sum of pair score (SP-score). The SP-score estimation is thus a bottleneck for most MSA tools since it is repeatedly required and is time consuming. Given an alignment of n sequences and L sites, I introduce here optimized solutions reaching O(nL) time complexity for affine gap cost, instead of O(n2L), which are easy to implement.

Optimizing alignment and growth of low-loss YAG single crystal fibers using laser heated pedestal growth technique.

PubMed

Bera, Subhabrata; Nie, Craig D; Soskind, Michael G; Harrington, James A

2017-12-10

The effect of misalignments of different optical components in the laser heated pedestal growth apparatus have been modeled using Zemax optical design software. By isolating the misalignments causing the non-uniformity in the melt zone, the alignment of the components was fine-tuned. Using this optimized alignment, low-loss YAG single crystal fibers of 120 μm diameter were grown, with total attenuation loss as low as 0.5 dB/m at 1064 nm.

Quantifying selective alignment of ensemble nitrogen-vacancy centers in (111) diamond

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

Tahara, Kosuke; Ozawa, Hayato; Iwasaki, Takayuki

2015-11-09

Selective alignment of nitrogen-vacancy (NV) centers in diamond is an important technique towards its applications. Quantification of the alignment ratio is necessary to design the optimized diamond samples. However, this is not a straightforward problem for dense ensemble of the NV centers. We estimate the alignment ratio of ensemble NV centers along the [111] direction in (111) diamond by optically detected magnetic resonance measurements. Diamond films deposited by N{sub 2} doped chemical vapor deposition have NV center densities over 1 × 10{sup 15 }cm{sup −3} and alignment ratios over 75%. Although spin coherence time (T{sub 2}) is limited to a few μs bymore » electron spins of nitrogen impurities, the combination of the selective alignment and the high density can be a possible way to optimize NV-containing diamond samples for the sensing applications.« less

Alignment-free protein interaction network comparison

PubMed Central

Ali, Waqar; Rito, Tiago; Reinert, Gesine; Sun, Fengzhu; Deane, Charlotte M.

2014-01-01

Motivation: Biological network comparison software largely relies on the concept of alignment where close matches between the nodes of two or more networks are sought. These node matches are based on sequence similarity and/or interaction patterns. However, because of the incomplete and error-prone datasets currently available, such methods have had limited success. Moreover, the results of network alignment are in general not amenable for distance-based evolutionary analysis of sets of networks. In this article, we describe Netdis, a topology-based distance measure between networks, which offers the possibility of network phylogeny reconstruction. Results: We first demonstrate that Netdis is able to correctly separate different random graph model types independent of network size and density. The biological applicability of the method is then shown by its ability to build the correct phylogenetic tree of species based solely on the topology of current protein interaction networks. Our results provide new evidence that the topology of protein interaction networks contains information about evolutionary processes, despite the lack of conservation of individual interactions. As Netdis is applicable to all networks because of its speed and simplicity, we apply it to a large collection of biological and non-biological networks where it clusters diverse networks by type. Availability and implementation: The source code of the program is freely available at http://www.stats.ox.ac.uk/research/proteins/resources. Contact: w.ali@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25161230

Optimizing multiple sequence alignments using a genetic algorithm based on three objectives: structural information, non-gaps percentage and totally conserved columns.

PubMed

Ortuño, Francisco M; Valenzuela, Olga; Rojas, Fernando; Pomares, Hector; Florido, Javier P; Urquiza, Jose M; Rojas, Ignacio

2013-09-01

Multiple sequence alignments (MSAs) are widely used approaches in bioinformatics to carry out other tasks such as structure predictions, biological function analyses or phylogenetic modeling. However, current tools usually provide partially optimal alignments, as each one is focused on specific biological features. Thus, the same set of sequences can produce different alignments, above all when sequences are less similar. Consequently, researchers and biologists do not agree about which is the most suitable way to evaluate MSAs. Recent evaluations tend to use more complex scores including further biological features. Among them, 3D structures are increasingly being used to evaluate alignments. Because structures are more conserved in proteins than sequences, scores with structural information are better suited to evaluate more distant relationships between sequences. The proposed multiobjective algorithm, based on the non-dominated sorting genetic algorithm, aims to jointly optimize three objectives: STRIKE score, non-gaps percentage and totally conserved columns. It was significantly assessed on the BAliBASE benchmark according to the Kruskal-Wallis test (P < 0.01). This algorithm also outperforms other aligners, such as ClustalW, Multiple Sequence Alignment Genetic Algorithm (MSA-GA), PRRP, DIALIGN, Hidden Markov Model Training (HMMT), Pattern-Induced Multi-sequence Alignment (PIMA), MULTIALIGN, Sequence Alignment Genetic Algorithm (SAGA), PILEUP, Rubber Band Technique Genetic Algorithm (RBT-GA) and Vertical Decomposition Genetic Algorithm (VDGA), according to the Wilcoxon signed-rank test (P < 0.05), whereas it shows results not significantly different to 3D-COFFEE (P > 0.05) with the advantage of being able to use less structures. Structural information is included within the objective function to evaluate more accurately the obtained alignments. The source code is available at http://www.ugr.es/~fortuno/MOSAStrE/MO-SAStrE.zip.

Aligning incentives in supply chains.

PubMed

Narayanan, V G; Raman, Ananth

2004-11-01

Most companies don't worry about the behavior of their supply chain partners. Instead, they expect the supply chain to work efficiently without interference, as if guided by Adam Smith's famed invisible hand. In their study of more than 50 supply networks, V.G. Narayanan and Ananth Raman found that companies often looked out for their own interests and ignored those of their network partners. Consequently, supply chains performed poorly. Those results aren't shocking when you consider that supply chains extend across several functions and many companies, each with its own priorities and goals. Yet all those functions and firms must pull in the same direction for a chain to deliver goods and services to consumers quickly and cost-effectively. According to the authors, a supply chain works well only if the risks, costs, and rewards of doing business are distributed fairly across the network. In fact, misaligned incentives are often the cause of excess inventory, stock-outs, incorrect forecasts, inadequate sales efforts, and even poor customer service. The fates of all supply chain partners are interlinked: If the firms work together to serve consumers, they will all win. However, they can do that only if incentives are aligned. Companies must acknowledge that the problem of incentive misalignment exists and then determine its root cause and align or redesign incentives. They can improve alignment by, for instance, adopting revenue-sharing contracts, using technology to track previously hidden information, or working with intermediaries to build trust among network partners. It's also important to periodically reassess incentives, because even top-performing networks find that changes in technology or business conditions alter the alignment of incentives.

Optimal Parameter Design of Coarse Alignment for Fiber Optic Gyro Inertial Navigation System.

PubMed

Lu, Baofeng; Wang, Qiuying; Yu, Chunmei; Gao, Wei

2015-06-25

Two different coarse alignment algorithms for Fiber Optic Gyro (FOG) Inertial Navigation System (INS) based on inertial reference frame are discussed in this paper. Both of them are based on gravity vector integration, therefore, the performance of these algorithms is determined by integration time. In previous works, integration time is selected by experience. In order to give a criterion for the selection process, and make the selection of the integration time more accurate, optimal parameter design of these algorithms for FOG INS is performed in this paper. The design process is accomplished based on the analysis of the error characteristics of these two coarse alignment algorithms. Moreover, this analysis and optimal parameter design allow us to make an adequate selection of the most accurate algorithm for FOG INS according to the actual operational conditions. The analysis and simulation results show that the parameter provided by this work is the optimal value, and indicate that in different operational conditions, the coarse alignment algorithms adopted for FOG INS are different in order to achieve better performance. Lastly, the experiment results validate the effectiveness of the proposed algorithm.

Sentence alignment using feed forward neural network.

PubMed

Fattah, Mohamed Abdel; Ren, Fuji; Kuroiwa, Shingo

2006-12-01

Parallel corpora have become an essential resource for work in multi lingual natural language processing. However, sentence aligned parallel corpora are more efficient than non-aligned parallel corpora for cross language information retrieval and machine translation applications. In this paper, we present a new approach to align sentences in bilingual parallel corpora based on feed forward neural network classifier. A feature parameter vector is extracted from the text pair under consideration. This vector contains text features such as length, punctuate score, and cognate score values. A set of manually prepared training data has been assigned to train the feed forward neural network. Another set of data was used for testing. Using this new approach, we could achieve an error reduction of 60% over length based approach when applied on English-Arabic parallel documents. Moreover this new approach is valid for any language pair and it is quite flexible approach since the feature parameter vector may contain more/less or different features than that we used in our system such as lexical match feature.

YAHA: fast and flexible long-read alignment with optimal breakpoint detection.

PubMed

Faust, Gregory G; Hall, Ira M

2012-10-01

With improved short-read assembly algorithms and the recent development of long-read sequencers, split mapping will soon be the preferred method for structural variant (SV) detection. Yet, current alignment tools are not well suited for this. We present YAHA, a fast and flexible hash-based aligner. YAHA is as fast and accurate as BWA-SW at finding the single best alignment per query and is dramatically faster and more sensitive than both SSAHA2 and MegaBLAST at finding all possible alignments. Unlike other aligners that report all, or one, alignment per query, or that use simple heuristics to select alignments, YAHA uses a directed acyclic graph to find the optimal set of alignments that cover a query using a biologically relevant breakpoint penalty. YAHA can also report multiple mappings per defined segment of the query. We show that YAHA detects more breakpoints in less time than BWA-SW across all SV classes, and especially excels at complex SVs comprising multiple breakpoints. YAHA is currently supported on 64-bit Linux systems. Binaries and sample data are freely available for download from http://faculty.virginia.edu/irahall/YAHA. imh4y@virginia.edu.

Multi-subject Manifold Alignment of Functional Network Structures via Joint Diagonalization.

PubMed

Nenning, Karl-Heinz; Kollndorfer, Kathrin; Schöpf, Veronika; Prayer, Daniela; Langs, Georg

2015-01-01

Functional magnetic resonance imaging group studies rely on the ability to establish correspondence across individuals. This enables location specific comparison of functional brain characteristics. Registration is often based on morphology and does not take variability of functional localization into account. This can lead to a loss of specificity, or confounds when studying diseases. In this paper we propose multi-subject functional registration by manifold alignment via coupled joint diagonalization. The functional network structure of each subject is encoded in a diffusion map, where functional relationships are decoupled from spatial position. Two-step manifold alignment estimates initial correspondences between functionally equivalent regions. Then, coupled joint diagonalization establishes common eigenbases across all individuals, and refines the functional correspondences. We evaluate our approach on fMRI data acquired during a language paradigm. Experiments demonstrate the benefits in matching accuracy achieved by coupled joint diagonalization compared to previously proposed functional alignment approaches, or alignment based on structural correspondences.

Neural network approximation of nonlinearity in laser nano-metrology system based on TLMI

NASA Astrophysics Data System (ADS)

Olyaee, Saeed; Hamedi, Samaneh

2011-02-01

In this paper, an approach based on neural network (NN) for nonlinearity modeling in a nano-metrology system using three-longitudinal-mode laser heterodyne interferometer (TLMI) for length and displacement measurements is presented. We model nonlinearity errors that arise from elliptically and non-orthogonally polarized laser beams, rotational error in the alignment of laser head with respect to the polarizing beam splitter, rotational error in the alignment of the mixing polarizer, and unequal transmission coefficients in the polarizing beam splitter. Here we use a neural network algorithm based on the multi-layer perceptron (MLP) network. The simulation results show that multi-layer feed forward perceptron network is successfully applicable to real noisy interferometer signals.

Effect of alignment perturbations in a trans-tibial prosthesis user: A pilot study.

PubMed

Courtney, Anna; Orendurff, Michael S; Buis, Arjan

2016-04-01

A recurring complication in trans-tibial prosthetic limb users is "poor socket fit" with painful residuum-socket interfaces, a consequence of excess pressure. This is due to both poor socket fit and poor socket alignment; however, the interaction of these factors has not been quantified. Through evaluation of kinetic data this study aimed to articulate an interaction uniting socket design, alignment and interface pressures. The results will help to refine future studies and will hopefully help determine whether sockets can be designed, fitted and aligned to maximize mobility whilst minimizing injurious forces. Interface pressures were recorded throughout ambulation in one user with "optimal (reference) alignment" followed by 5 malalignments in a patellar tendon-bearing and a hydrocast socket. Marked differences in pressure distribution were discovered when equating the patellar tendon-bearing against the hydrocast socket and when comparing interface pressures from reference with offset alignment. Patellar tendon-bearing sockets were found to be more sensitive to alignment perturbations than hydrocast sockets. A complex interaction was found, with the most prominent finding demonstrating the requisite for attainment of optimal alignment: a translational alignment error of 10 mm can increase maximum peak pressures by 227% (mean 17.5%). Refinements for future trials are described and the necessity for future research into socket design, alignment and interface pressures has been estabilished.

MaxAlign: maximizing usable data in an alignment.

PubMed

Gouveia-Oliveira, Rodrigo; Sackett, Peter W; Pedersen, Anders G

2007-08-28

The presence of gaps in an alignment of nucleotide or protein sequences is often an inconvenience for bioinformatical studies. In phylogenetic and other analyses, for instance, gapped columns are often discarded entirely from the alignment. MaxAlign is a program that optimizes the alignment prior to such analyses. Specifically, it maximizes the number of nucleotide (or amino acid) symbols that are present in gap-free columns - the alignment area - by selecting the optimal subset of sequences to exclude from the alignment. MaxAlign can be used prior to phylogenetic and bioinformatical analyses as well as in other situations where this form of alignment improvement is useful. In this work we test MaxAlign's performance in these tasks and compare the accuracy of phylogenetic estimates including and excluding gapped columns from the analysis, with and without processing with MaxAlign. In this paper we also introduce a new simple measure of tree similarity, Normalized Symmetric Similarity (NSS) that we consider useful for comparing tree topologies. We demonstrate how MaxAlign is helpful in detecting misaligned or defective sequences without requiring manual inspection. We also show that it is not advisable to exclude gapped columns from phylogenetic analyses unless MaxAlign is used first. Finally, we find that the sequences removed by MaxAlign from an alignment tend to be those that would otherwise be associated with low phylogenetic accuracy, and that the presence of gaps in any given sequence does not seem to disturb the phylogenetic estimates of other sequences. The MaxAlign web-server is freely available online at http://www.cbs.dtu.dk/services/MaxAlign where supplementary information can also be found. The program is also freely available as a Perl stand-alone package.

Effects on diameter and morphology of polycaprolactone nanofibers infused with various concentrations of selenium nanoparticles

NASA Astrophysics Data System (ADS)

Kamaruzaman, Nurul Asyikin; Yusoff, Abdull Rahim Mohd; Buang, Nor Aziah; Salleh, Nik Ghazali Nik

2017-12-01

Electrospinning is one of the techniques used in the fabrication of nanofibers. Polycaprolactone (PCL), is a biodegradable polymer which was commonly electrospun without the presence of nanoparticles as additives and/or filler in the applications such as tissue engineering, biosensors, filtration, wound dressings, drug delivery and enzyme immobilization. In this study, via FESEM analyses, the effects on the diameter and morphology of PCL nanofibers was investigated with respect to various concentration of selenium nanoparticles (SeNP). Increasing the concentration of SeNP from 0.2 to 1.0% (w/v) resulted in increased of fiber diameter as well as the density of the nanofiber networking. Consequently, the formation of beads have also increased with the increment of the concentration of SeNP. The images from FESEM micrographs showed the formation of "aligned fibers" with the average size of less than 550 nm. The optimized concentration of SeNP obtained was 0.4 % w/v for the formation of aligned fibers with a uniform diameter in size and the least formation of beads in the matrices. Aligned nanofibers are biocompatible and can be used in tissue engineering and wound dressing applications. Meanwhile, nanofibers with beads are suitable for filtration design in water and gaseous applications.

What are the reasons for clinical network success? A qualitative study.

PubMed

McInnes, Elizabeth; Haines, Mary; Dominello, Amanda; Kalucy, Deanna; Jammali-Blasi, Asmara; Middleton, Sandy; Klineberg, Emily

2015-11-05

Clinical networks have been established to improve patient outcomes and processes of care by implementing a range of innovations and undertaking projects based on the needs of local health services. Given the significant investment in clinical networks internationally, it is important to assess their effectiveness and sustainability. This qualitative study investigated the views of stakeholders on the factors they thought were influential in terms of overall network success. Ten participants were interviewed using face-to-face, audio-recorded semi-structured interviews about critical factors for networks' successes over the study period 2006-2008. Respondents were purposively selected from two stakeholder groups: i) chairs of networks during the study period of 2006-2008 from high- moderate- and low-impact networks (as previously determined by an independent review panel) and ii) experts in the clinical field of the network who had a connection to the network but who were not network members. Participants were blind to the performance of the network they were interviewed about. Transcribed data were coded and analysed to generate themes relating to the study aims. Themes relating to influential factors critical to network success were: network model principles; leadership; formal organisational structures and processes; nature of network projects; external relationships; profile and credibility of the network. This study provides clinical networks with guidance on essential factors for maximising optimal network outcomes and that may assist networks to move from being a 'low-impact' to 'high-impact' network. Important ingredients for successful clinical networks were visionary and strategic leadership with strong links to external stakeholders; and having formal infrastructure and processes to enable the development and management of work plans aligned with health priorities.

Ontology Alignment Architecture for Semantic Sensor Web Integration

PubMed Central

Fernandez, Susel; Marsa-Maestre, Ivan; Velasco, Juan R.; Alarcos, Bernardo

2013-01-01

Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity). Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity's names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI) tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall. PMID:24051523

Ontology alignment architecture for semantic sensor Web integration.

PubMed

Fernandez, Susel; Marsa-Maestre, Ivan; Velasco, Juan R; Alarcos, Bernardo

2013-09-18

Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity). Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity's names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI) tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall.

Optimal control of the orientation and alignment of an asymmetric-top molecule with terahertz and laser pulses

NASA Astrophysics Data System (ADS)

Coudert, L. H.

2018-03-01

Quantum optimal control theory is applied to determine numerically the terahertz and nonresonant laser pulses leading, respectively, to the highest degree of orientation and alignment of the asymmetric-top H2S molecule. The optimized terahertz pulses retrieved for temperatures of zero and 50 K lead after 50 ps to an orientation with ⟨ΦZx⟩ = 0.959 73 and ⟨⟨ΦZx⟩⟩ = 0.742 30, respectively. For the zero temperature, the orientation is close to its maximum theoretical value; for the higher temperature, it is below the maximum theoretical value. The mechanism by which the terahertz pulse populates high lying rotational levels is elucidated. The 5 ps long optimized laser pulse calculated for a zero temperature leads to an alignment with ⟨ΦZy 2 ⟩ =0.944 16 and consists of several kick pulses with a duration of ≈0.1 ps. It is found that the timing of these kick pulses is such that it leads to an increase of the rotational energy of the molecule. The optimized laser pulse retrieved for a temperature of 20 K is 6 ps long and yields a lower alignment with ⟨⟨ΦZy 2 ⟩ ⟩ =0.717 20 .

Alignment method for parabolic trough solar concentrators

DOEpatents

Diver, Richard B [Albuquerque, NM

2010-02-23

A Theoretical Overlay Photographic (TOP) alignment method uses the overlay of a theoretical projected image of a perfectly aligned concentrator on a photographic image of the concentrator to align the mirror facets of a parabolic trough solar concentrator. The alignment method is practical and straightforward, and inherently aligns the mirror facets to the receiver. When integrated with clinometer measurements for which gravity and mechanical drag effects have been accounted for and which are made in a manner and location consistent with the alignment method, all of the mirrors on a common drive can be aligned and optimized for any concentrator orientation.

Controllable synthesis of ultrathin vanadium oxide nanobelts via an EDTA-mediated hydrothermal process

NASA Astrophysics Data System (ADS)

Yu-Xiang, Qin; Cheng, Liu; Wei-Wei, Xie; Meng-Yang, Cui

2016-02-01

Ultrathin VO2 nanobelts with rough alignment features are prepared on the induction layer-coated substrates by an ethylenediaminetetraacetic acid (EDTA)-mediated hydrothermal process. EDTA acts as a chelating reagent and capping agent to facilitate the one-dimensional (1D) preferential growth of ultrathin VO2 nanobelts with high crystallinities and good uniformities. The annealed induction layer and concentration of EDTA are found to play crucial roles in the formation of aligned and ultrathin nanobelts. Variation in EDTA concentration can change the VO2 morphology of ultrathin nanobelts into that of thick nanoplates. Mild annealing of ultrathin VO2 nanobelts at 350 °C in air results in the formation of V2O5 nanobelts with a nearly unchanged ultrathin structure. The nucleation and growth mechanism involved in the formations of nanobelts and nanoplates are proposed. The ethanol gas sensing properties of the V2O5 nanobelt networks-based sensor are investigated in a temperature range from 100 °C to 300 °C over ethanol concentrations ranging from 3 ppm to 500 ppm. The results indicate that the V2O5 nanobelt network sensor exhibits high sensitivity, good reversibility, and fast response-recovery characteristics with an optimal working temperature of 250 °C. Project supported by the National Natural Science Foundation of China (Grant Nos. 61274074, 61271070, and 61574100).

Deep Brain Stimulation for Essential Tremor: Aligning Thalamic and Posterior Subthalamic Targets in 1 Surgical Trajectory.

PubMed

Bot, Maarten; van Rootselaar, Fleur; Contarino, Maria Fiorella; Odekerken, Vincent; Dijk, Joke; de Bie, Rob; Schuurman, Richard; van den Munckhof, Pepijn

2017-12-21

Ventral intermediate nucleus (VIM) deep brain stimulation (DBS) and posterior subthalamic area (PSA) DBS suppress tremor in essential tremor (ET) patients, but it is not clear which target is optimal. Aligning both targets in 1 surgical trajectory would facilitate exploring stimulation of either target in a single patient. To evaluate aligning VIM and PSA in 1 surgical trajectory for DBS in ET. Technical aspects of trajectories, intraoperative stimulation findings, final electrode placement, target used for chronic stimulation, and adverse and beneficial effects were evaluated. In 17 patients representing 33 trajectories, we successfully aligned VIM and PSA targets in 26 trajectories. Trajectory distance between targets averaged 7.2 (range 6-10) mm. In all but 4 aligned trajectories, optimal intraoperative tremor suppression was obtained in the PSA. During follow-up, active electrode contacts were located in PSA in the majority of cases. Overall, successful tremor control was achieved in 69% of patients. Stimulation-induced dysarthria or gait ataxia occurred in, respectively, 56% and 44% of patients. Neither difference in tremor suppression or side effects was noted between aligned and nonaligned leads nor between the different locations of chronic stimulation. Alignment of VIM and PSA for DBS in ET is feasible and enables intraoperative exploration of both targets in 1 trajectory. This facilitates positioning of electrode contacts in both areas, where multiple effective points of stimulation can be found. In the majority of aligned leads, optimal intraoperative and chronic stimulation were located in the PSA. Copyright © 2017 by the Congress of Neurological Surgeons

Optical alignment procedure utilizing neural networks combined with Shack-Hartmann wavefront sensor

NASA Astrophysics Data System (ADS)

Adil, Fatime Zehra; Konukseven, Erhan İlhan; Balkan, Tuna; Adil, Ömer Faruk

2017-05-01

In the design of pilot helmets with night vision capability, to not limit or block the sight of the pilot, a transparent visor is used. The reflected image from the coated part of the visor must coincide with the physical human sight image seen through the nonreflecting regions of the visor. This makes the alignment of the visor halves critical. In essence, this is an alignment problem of two optical parts that are assembled together during the manufacturing process. Shack-Hartmann wavefront sensor is commonly used for the determination of the misalignments through wavefront measurements, which are quantified in terms of the Zernike polynomials. Although the Zernike polynomials provide very useful feedback about the misalignments, the corrective actions are basically ad hoc. This stems from the fact that there exists no easy inverse relation between the misalignment measurements and the physical causes of the misalignments. This study aims to construct this inverse relation by making use of the expressive power of the neural networks in such complex relations. For this purpose, a neural network is designed and trained in MATLAB® regarding which types of misalignments result in which wavefront measurements, quantitatively given by Zernike polynomials. This way, manual and iterative alignment processes relying on trial and error will be replaced by the trained guesses of a neural network, so the alignment process is reduced to applying the counter actions based on the misalignment causes. Such a training requires data containing misalignment and measurement sets in fine detail, which is hard to obtain manually on a physical setup. For that reason, the optical setup is completely modeled in Zemax® software, and Zernike polynomials are generated for misalignments applied in small steps. The performance of the neural network is experimented and found promising in the actual physical setup.

Push-Pull and Feedback Mechanisms Can Align Signaling System Outputs with Inputs.

PubMed

Andrews, Steven S; Peria, William J; Yu, Richard C; Colman-Lerner, Alejandro; Brent, Roger

2016-11-23

Many cell signaling systems, including the yeast pheromone response system, exhibit "dose-response alignment" (DoRA), in which output of one or more downstream steps closely matches the fraction of occupied receptors. DoRA can improve the fidelity of transmitted dose information. Here, we searched systematically for biochemical network topologies that produced DoRA. Most networks, including many containing feedback and feedforward loops, could not produce DoRA. However, networks including "push-pull" mechanisms, in which the active form of a signaling species stimulates downstream activity and the nominally inactive form reduces downstream activity, enabled perfect DoRA. Networks containing feedbacks enabled DoRA, but only if they also compared feedback to input and adjusted output to match. Our results establish push-pull as a non-feedback mechanism to align output with variable input and maximize information transfer in signaling systems. They also suggest genetic approaches to determine whether particular signaling systems use feedback or push-pull control. Copyright © 2016 Elsevier Inc. All rights reserved.

Local alignment of two-base encoded DNA sequence

PubMed Central

Homer, Nils; Merriman, Barry; Nelson, Stanley F

2009-01-01

Background DNA sequence comparison is based on optimal local alignment of two sequences using a similarity score. However, some new DNA sequencing technologies do not directly measure the base sequence, but rather an encoded form, such as the two-base encoding considered here. In order to compare such data to a reference sequence, the data must be decoded into sequence. The decoding is deterministic, but the possibility of measurement errors requires searching among all possible error modes and resulting alignments to achieve an optimal balance of fewer errors versus greater sequence similarity. Results We present an extension of the standard dynamic programming method for local alignment, which simultaneously decodes the data and performs the alignment, maximizing a similarity score based on a weighted combination of errors and edits, and allowing an affine gap penalty. We also present simulations that demonstrate the performance characteristics of our two base encoded alignment method and contrast those with standard DNA sequence alignment under the same conditions. Conclusion The new local alignment algorithm for two-base encoded data has substantial power to properly detect and correct measurement errors while identifying underlying sequence variants, and facilitating genome re-sequencing efforts based on this form of sequence data. PMID:19508732

On the formation of well-aligned ZnO nanowall networks by catalyst-free thermal evaporation method

NASA Astrophysics Data System (ADS)

Yin, Zhigang; Chen, Nuofu; Dai, Ruixuan; Liu, Lei; Zhang, Xingwang; Wang, Xiaohui; Wu, Jinliang; Chai, Chunlin

2007-07-01

Two-dimensional ZnO nanowall networks were grown on ZnO-coated silicon by thermal evaporation at low temperature without catalysts or additives. All of the results from scanning electronic spectroscope, X-ray diffraction and Raman scattering confirmed that the ZnO nanowalls were vertically aligned and c-axis oriented. The room-temperature photoluminescence spectra showed a dominated UV peak at 378 nm, and a much suppressed orange emission centered at ˜590 nm. This demonstrates fairly good crystal quality and optical properties of the product. A possible three-step, zinc vapor-controlled process was proposed to explain the growth of well-aligned ZnO nanowall networks. The pre-coated ZnO template layer plays a key role during the synthesis process, which guides the growth direction of the synthesized products.

Massively-Parallel Architectures for Automatic Recognition of Visual Speech Signals

DTIC Science & Technology

1988-10-12

Secusrity Clamifieation, Nlassively-Parallel Architectures for Automa ic Recognitio of Visua, Speech Signals 12. PERSONAL AUTHOR(S) Terrence J...characteristics of speech from tJhe, visual speech signals. Neural networks have been trained on a database of vowels. The rqw images of faces , aligned and...images of faces , aligned and preprocessed, were used as input to these network which were trained to estimate the corresponding envelope of the

High Throughput via Cross-Layer Interference Alignment for Mobile Ad Hoc Networks

DTIC Science & Technology

2013-08-26

MIMO zero-forcing receiver in the presence of channel estimation error,” IEEE Transactions on Wireless Communications , vol. 6 , no. 3, pp. 805–810, Mar...Robert W. Heath, Nachiappan Valliappan. Antenna Subset Modulation for Secure Millimeter-Wave Wireless Communication , IEEE Transactions on...in MIMO Interference Alignment Networks, IEEE Transactions on Wireless Communications , (02 2012): 0. doi: 10.1109/TWC.2011.120511.111088 TOTAL: 2

Direct induction of molecular alignment in liquid crystal polymer network film by photopolymerization

NASA Astrophysics Data System (ADS)

Hisano, K.; Aizawa, M.; Ishizu, M.; Kurata, Y.; Shishido, A.

2016-09-01

Liquid crystal (LC) is the promising material for the fabrication of high-performance soft, flexible devices. The fascinating and useful properties arise from their cooperative effect that inherently allows the macroscopic integration and control of molecular alignment through various external stimuli. To date, light-matter interaction is the most attractive stimuli and researchers developed photoalignment through photochemical or photophysical reactions triggered by linearly polarized light. Here we show the new choice based on molecular diffusion by photopolymerization. We found that photopolymerization of a LC monomer and a crosslinker through a photomask enables to direct molecular alignment in the resultant LC polymer network film. The key generating the molecular alignment is molecular diffusion due to the difference of chemical potentials between irradiated and unirradiated regions. This concept is applicable to various shapes of photomask and two-dimensional molecular alignments can be fabricated depending on the spatial design of photomask. By virtue of the inherent versatility of molecular diffusion in materials, the process would shed light on the fabrication of various high-performance flexible materials with molecular alignment having controlled patterns.

Geodetic Network Design and Optimization on the Active Tuzla Fault (Izmir, Turkey) for Disaster Management

PubMed Central

Halicioglu, Kerem; Ozener, Haluk

2008-01-01

Both seismological and geodynamic research emphasize that the Aegean Region, which comprises the Hellenic Arc, the Greek mainland and Western Turkey is the most seismically active region in Western Eurasia. The convergence of the Eurasian and African lithospheric plates forces a westward motion on the Anatolian plate relative to the Eurasian one. Western Anatolia is a valuable laboratory for Earth Science research because of its complex geological structure. Izmir is a large city in Turkey with a population of about 2.5 million that is at great risk from big earthquakes. Unfortunately, previous geodynamics studies performed in this region are insufficient or cover large areas instead of specific faults. The Tuzla Fault, which is aligned trending NE–SW between the town of Menderes and Cape Doganbey, is an important fault in terms of seismic activity and its proximity to the city of Izmir. This study aims to perform a large scale investigation focusing on the Tuzla Fault and its vicinity for better understanding of the region's tectonics. In order to investigate the crustal deformation along the Tuzla Fault and Izmir Bay, a geodetic network has been designed and optimizations were performed. This paper suggests a schedule for a crustal deformation monitoring study which includes research on the tectonics of the region, network design and optimization strategies, theory and practice of processing. The study is also open for extension in terms of monitoring different types of fault characteristics. A one-dimensional fault model with two parameters – standard strike-slip model of dislocation theory in an elastic half-space – is formulated in order to determine which sites are suitable for the campaign based geodetic GPS measurements. Geodetic results can be used as a background data for disaster management systems. PMID:27873783

Geodetic Network Design and Optimization on the Active Tuzla Fault (Izmir, Turkey) for Disaster Management.

PubMed

Halicioglu, Kerem; Ozener, Haluk

2008-08-19

Both seismological and geodynamic research emphasize that the Aegean Region, which comprises the Hellenic Arc, the Greek mainland and Western Turkey is the most seismically active region in Western Eurasia. The convergence of the Eurasian and African lithospheric plates forces a westward motion on the Anatolian plate relative to the Eurasian one. Western Anatolia is a valuable laboratory for Earth Science research because of its complex geological structure. Izmir is a large city in Turkey with a population of about 2.5 million that is at great risk from big earthquakes. Unfortunately, previous geodynamics studies performed in this region are insufficient or cover large areas instead of specific faults. The Tuzla Fault, which is aligned trending NE-SW between the town of Menderes and Cape Doganbey, is an important fault in terms of seismic activity and its proximity to the city of Izmir. This study aims to perform a large scale investigation focusing on the Tuzla Fault and its vicinity for better understanding of the region's tectonics. In order to investigate the crustal deformation along the Tuzla Fault and Izmir Bay, a geodetic network has been designed and optimizations were performed. This paper suggests a schedule for a crustal deformation monitoring study which includes research on the tectonics of the region, network design and optimization strategies, theory and practice of processing. The study is also open for extension in terms of monitoring different types of fault characteristics. A one-dimensional fault model with two parameters - standard strike-slip model of dislocation theory in an elastic half-space - is formulated in order to determine which sites are suitable for the campaign based geodetic GPS measurements. Geodetic results can be used as a background data for disaster management systems.

Engineering-Aligned 3D Neural Circuit in Microfluidic Device.

PubMed

Bang, Seokyoung; Na, Sangcheol; Jang, Jae Myung; Kim, Jinhyun; Jeon, Noo Li

2016-01-07

The brain is one of the most important and complex organs in the human body. Although various neural network models have been proposed for in vitro 3D neuronal networks, it has been difficult to mimic functional and structural complexity of the in vitro neural circuit. Here, a microfluidic model of a simplified 3D neural circuit is reported. First, the microfluidic device is filled with Matrigel and continuous flow is delivered across the device during gelation. The fluidic flow aligns the extracellular matrix (ECM) components along the flow direction. Following the alignment of ECM fibers, neurites of primary rat cortical neurons are grown into the Matrigel at the average speed of 250 μm d(-1) and form axon bundles approximately 1500 μm in length at 6 days in vitro (DIV). Additionally, neural networks are developed from presynaptic to postsynaptic neurons at 14 DIV. The establishment of aligned 3D neural circuits is confirmed with the immunostaining of PSD-95 and synaptophysin and the observation of calcium signal transmission. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Functional Module Analysis for Gene Coexpression Networks with Network Integration.

PubMed

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

2015-01-01

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

Metal-modified and vertically aligned carbon nanotube sensors array for landfill gas monitoring applications.

PubMed

Penza, M; Rossi, R; Alvisi, M; Serra, E

2010-03-12

Vertically aligned carbon nanotube (CNT) layers were synthesized on Fe-coated low-cost alumina substrates using radio-frequency plasma enhanced chemical vapour deposition (RF-PECVD) technology. A miniaturized CNT-based gas sensor array was developed for monitoring landfill gas (LFG) at a temperature of 150 degrees C. The sensor array was composed of 4 sensing elements with unmodified CNT, and CNT loaded with 5 nm nominally thick sputtered nanoclusters of platinum (Pt), ruthenium (Ru) and silver (Ag). Chemical analysis of multicomponent gas mixtures constituted of CO(2), CH(4), H(2), NH(3), CO and NO(2) has been performed by the array sensor responses and pattern recognition based on principal component analysis (PCA). The PCA results demonstrate that the metal-decorated and vertically aligned CNT sensor array is able to discriminate the NO(2) presence in the multicomponent mixture LFG. The NO(2) gas detection in the mixture LFG was proved to be very sensitive, e.g.: the CNT:Ru sensor shows a relative change in the resistance of 1.50% and 0.55% for NO(2) concentrations of 3.3 ppm and 330 ppb dispersed in the LFG, respectively, with a wide NO(2) gas concentration range measured from 0.33 to 3.3 ppm, at the sensor temperature of 150 degrees C. The morphology and structure of the CNT networks have been characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM) and Raman spectroscopy. A forest-like nanostructure of vertically aligned CNT bundles in the multi-walled form appeared with a height of about 10 microm and a single-tube diameter varying in the range of 5-35 nm. The intensity ratio of the Raman spectroscopy D-peak and G-peak indicates the presence of disorder and defects in the CNT networks. The size of the metal (Pt, Ru, Ag) nanoclusters decorating the CNT top surface varies in the range of 5-50 nm. Functional characterization based on electrical charge transfer sensing mechanisms in the metal-modified CNT-chemoresistor array demonstrates high sensitivity by providing minimal sub-ppm level detection, e.g., download up to 100 ppb NO(2), at the sensor temperature of 150 degrees C. The gas sensitivity of the CNT sensor array depends on operating temperature, showing a lower optimal temperature of maximum sensitivity for the metal-decorated CNT sensors compared to unmodified CNT sensors. Results indicate that the recovery mechanisms in the CNT chemiresistors can be altered by a rapid heating pulse from room temperature to about 110 degrees C. A comparison of the NO(2) gas sensitivity for the chemiresistors based on disorderly networked CNTs and vertically aligned CNTs is also reported. Cross-sensitivity towards relative humidity of the CNT sensors array is investigated. Finally, the sensing properties of the metal-decorated and vertically aligned CNT sensor arrays are promising to monitor gas events in the LFG for practical applications with low power consumption and moderate sensor temperature.

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

PubMed

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

2017-12-28

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

Sandia Corporation (Albuquerque, NM)

DOEpatents

Diver, Richard B.

2010-02-23

A Theoretical Overlay Photographic (TOP) alignment method uses the overlay of a theoretical projected image of a perfectly aligned concentrator on a photographic image of the concentrator to align the mirror facets of a parabolic trough solar concentrator. The alignment method is practical and straightforward, and inherently aligns the mirror facets to the receiver. When integrated with clinometer measurements for which gravity and mechanical drag effects have been accounted for and which are made in a manner and location consistent with the alignment method, all of the mirrors on a common drive can be aligned and optimized for any concentrator orientation.

Influence of coherent mesoscale structures on satellite-based Doppler lidar wind measurements

NASA Technical Reports Server (NTRS)

Emmitt, G. D.; Houston, S.

1985-01-01

Efforts to develop display routines for overlaying gridded and nongridded data sets are discussed. The primary objective is to have the capability to review global patterns of winds and lidar samples; to zoom in on particular wind features or global areas; and to display contours of wind components and derived fields (e.g., divergence, vorticity, deformation, etc.). Current considerations in support of a polar orbiting shuttle lidar mission are discussed. Ground truth for a shuttle lidar experiment may be limited to fortuitous alignment of lidar wind profiles and scheduled rawinsonde profiles. Any improvement on this would require special rawinsonde launches and/or optimization of the shuttle orbit with global wind measurement networks.

Multiple alignment analysis on phylogenetic tree of the spread of SARS epidemic using distance method

NASA Astrophysics Data System (ADS)

Amiroch, S.; Pradana, M. S.; Irawan, M. I.; Mukhlash, I.

2017-09-01

Multiple Alignment (MA) is a particularly important tool for studying the viral genome and determine the evolutionary process of the specific virus. Application of MA in the case of the spread of the Severe acute respiratory syndrome (SARS) epidemic is an interesting thing because this virus epidemic a few years ago spread so quickly that medical attention in many countries. Although there has been a lot of software to process multiple sequences, but the use of pairwise alignment to process MA is very important to consider. In previous research, the alignment between the sequences to process MA algorithm, Super Pairwise Alignment, but in this study used a dynamic programming algorithm Needleman wunchs simulated in Matlab. From the analysis of MA obtained and stable region and unstable which indicates the position where the mutation occurs, the system network topology that produced the phylogenetic tree of the SARS epidemic distance method, and system area networks mutation.

Two-Stream Transformer Networks for Video-based Face Alignment.

PubMed

Liu, Hao; Lu, Jiwen; Feng, Jianjiang; Zhou, Jie

2017-08-01

In this paper, we propose a two-stream transformer networks (TSTN) approach for video-based face alignment. Unlike conventional image-based face alignment approaches which cannot explicitly model the temporal dependency in videos and motivated by the fact that consistent movements of facial landmarks usually occur across consecutive frames, our TSTN aims to capture the complementary information of both the spatial appearance on still frames and the temporal consistency information across frames. To achieve this, we develop a two-stream architecture, which decomposes the video-based face alignment into spatial and temporal streams accordingly. Specifically, the spatial stream aims to transform the facial image to the landmark positions by preserving the holistic facial shape structure. Accordingly, the temporal stream encodes the video input as active appearance codes, where the temporal consistency information across frames is captured to help shape refinements. Experimental results on the benchmarking video-based face alignment datasets show very competitive performance of our method in comparisons to the state-of-the-arts.

Identifying Natural Alignments Between Ambulatory Surgery Centers and Local Health Systems: Building Broader Communities of Surgical Care.

PubMed

Funk, Russell J; Owen-Smith, Jason; Landon, Bruce E; Birkmeyer, John D; Hollingsworth, John M

2017-02-01

To develop and compare methods for identifying natural alignments between ambulatory surgery centers (ASCs) and hospitals that anchor local health systems. Using all-payer data from Florida's State Ambulatory Surgery and Inpatient Databases (2005-2009), we developed 3 methods for identifying alignments between ASCS and hospitals. The first, a geographic proximity approach, used spatial data to assign an ASC to its nearest hospital neighbor. The second, a predominant affiliation approach, assigned an ASC to the hospital with which it shared a plurality of surgeons. The third, a network community approach, linked an ASC with a larger group of hospitals held together by naturally occurring physician networks. We compared each method in terms of its ability to capture meaningful and stable affiliations and its administrative simplicity. Although the proximity approach was simplest to implement and produced the most durable alignments, ASC surgeon's loyalty to the assigned hospital was low with this method. The predominant affiliation and network community approaches performed better and nearly equivalently on these metrics, capturing more meaningful affiliations between ASCs and hospitals. However, the latter's alignments were least durable, and it was complex to administer. We describe 3 methods for identifying natural alignments between ASCs and hospitals, each with strengths and weaknesses. These methods will help health system managers identify ASCs with which to partner. Moreover, health services researchers and policy analysts can use them to study broader communities of surgical care.

MANGO: a new approach to multiple sequence alignment.

PubMed

Zhang, Zefeng; Lin, Hao; Li, Ming

2007-01-01

Multiple sequence alignment is a classical and challenging task for biological sequence analysis. The problem is NP-hard. The full dynamic programming takes too much time. The progressive alignment heuristics adopted by most state of the art multiple sequence alignment programs suffer from the 'once a gap, always a gap' phenomenon. Is there a radically new way to do multiple sequence alignment? This paper introduces a novel and orthogonal multiple sequence alignment method, using multiple optimized spaced seeds and new algorithms to handle these seeds efficiently. Our new algorithm processes information of all sequences as a whole, avoiding problems caused by the popular progressive approaches. Because the optimized spaced seeds are provably significantly more sensitive than the consecutive k-mers, the new approach promises to be more accurate and reliable. To validate our new approach, we have implemented MANGO: Multiple Alignment with N Gapped Oligos. Experiments were carried out on large 16S RNA benchmarks showing that MANGO compares favorably, in both accuracy and speed, against state-of-art multiple sequence alignment methods, including ClustalW 1.83, MUSCLE 3.6, MAFFT 5.861, Prob-ConsRNA 1.11, Dialign 2.2.1, DIALIGN-T 0.2.1, T-Coffee 4.85, POA 2.0 and Kalign 2.0.

Photoluminescence and Band Alignment of Strained GaAsSb/GaAs QW Structures Grown by MBE on GaAs

PubMed Central

Sadofyev, Yuri G.; Samal, Nigamananda

2010-01-01

An in-depth optimization of growth conditions and investigation of optical properties including discussions on band alignment of GaAsSb/GaAs quantum well (QW) on GaAs by molecular beam epitaxy (MBE) are reported. Optimal MBE growth temperature of GaAsSb QW is found to be 470 ± 10 °C. GaAsSb/GaAs QW with Sb content ~0.36 has a weak type-II band alignment with valence band offset ratio QV ~1.06. A full width at half maximum (FWHM) of ~60 meV in room temperature (RT) photoluminescence (PL) indicates fluctuation in electrostatic potential to be less than 20 meV. Samples grown under optimal conditions do not exhibit any blue shift of peak in RT PL spectra under varying excitation.

Accuracy Estimation and Parameter Advising for Protein Multiple Sequence Alignment

PubMed Central

DeBlasio, Dan

2013-01-01

Abstract We develop a novel and general approach to estimating the accuracy of multiple sequence alignments without knowledge of a reference alignment, and use our approach to address a new task that we call parameter advising: the problem of choosing values for alignment scoring function parameters from a given set of choices to maximize the accuracy of a computed alignment. For protein alignments, we consider twelve independent features that contribute to a quality alignment. An accuracy estimator is learned that is a polynomial function of these features; its coefficients are determined by minimizing its error with respect to true accuracy using mathematical optimization. Compared to prior approaches for estimating accuracy, our new approach (a) introduces novel feature functions that measure nonlocal properties of an alignment yet are fast to evaluate, (b) considers more general classes of estimators beyond linear combinations of features, and (c) develops new regression formulations for learning an estimator from examples; in addition, for parameter advising, we (d) determine the optimal parameter set of a given cardinality, which specifies the best parameter values from which to choose. Our estimator, which we call Facet (for “feature-based accuracy estimator”), yields a parameter advisor that on the hardest benchmarks provides more than a 27% improvement in accuracy over the best default parameter choice, and for parameter advising significantly outperforms the best prior approaches to assessing alignment quality. PMID:23489379

A Low Power and High Throughput Self Synchronous FPGA Using 65nm CMOS with Throughput Optimization by Pipeline Alignment

NASA Astrophysics Data System (ADS)

Stefan Devlin, Benjamin; Nakura, Toru; Ikeda, Makoto; Asada, Kunihiro

We detail a self synchronous field programmable gate array (SSFPGA) with dual-pipeline (DP) architecture to conceal pre-charge time for dynamic logic, and its throughput optimization by using pipeline alignment implemented on benchmark circuits. A self synchronous LUT (SSLUT) consists of a three input tree-type structure with 8bits of SRAM for programming. A self synchronous switch box (SSSB) consists of both pass transistors and buffers to route signals, with 12bits of SRAM. One common block with one SSLUT and one SSSB occupies 2.2Mλ2 area with 35bits of SRAM, and the prototype SSFPGA with 34 × 30 (1020) blocks is designed and fabricated using 65nm CMOS. Measured results show at 1.2V 430MHz and 647MHz operation for a 3bit ripple carry adder, without and with throughput optimization, respectively. We find that using the proposed pipeline alignment techniques we can perform at maximum throughput of 647MHz in various benchmarks on the SSFPGA. We demonstrate up to 56.1 times throughput improvement with our pipeline alignment techniques. The pipeline alignment is carried out within the number of logic elements in the array and pipeline buffers in the switching matrix.

Optimal and fast rotational alignment of volumes with missing data in Fourier space.

PubMed

Shatsky, Maxim; Arbelaez, Pablo; Glaeser, Robert M; Brenner, Steven E

2013-11-01

Electron tomography of intact cells has the potential to reveal the entire cellular content at a resolution corresponding to individual macromolecular complexes. Characterization of macromolecular complexes in tomograms is nevertheless an extremely challenging task due to the high level of noise, and due to the limited tilt angle that results in missing data in Fourier space. By identifying particles of the same type and averaging their 3D volumes, it is possible to obtain a structure at a more useful resolution for biological interpretation. Currently, classification and averaging of sub-tomograms is limited by the speed of computational methods that optimize alignment between two sub-tomographic volumes. The alignment optimization is hampered by the fact that the missing data in Fourier space has to be taken into account during the rotational search. A similar problem appears in single particle electron microscopy where the random conical tilt procedure may require averaging of volumes with a missing cone in Fourier space. We present a fast implementation of a method guaranteed to find an optimal rotational alignment that maximizes the constrained cross-correlation function (cCCF) computed over the actual overlap of data in Fourier space. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Mechanisms of Carrier Transport Induced by a Microswimmer Bath

DOE PAGES

Kaiser, Andreas; Sokolov, Andrey; Aranson, Igor S.; ...

2014-10-20

Recently, it was found that a wedgelike microparticle (referred to as ”carrier”) which is only allowed to translate but not to rotate exhibits a directed translational motion along the wedge cusp if it is exposed to a bath of microswimmers. Here we model this effect in detail by resolving the microswimmers explicitly using interaction models with different degrees of mutual alignment. Using computer simulations we study the impact of these interactions on the transport efficiency of V-shaped carrier. We show that the transport mechanisms itself strongly depends on the degree of alignment embodied in the modelling of the individual swimmermore » dynamics. For weak alignment, optimal carrier transport occurs in the turbulent microswimmer state and is induced by swirl depletion inside the carrier. For strong aligning interactions, optimal transport occurs already in the dilute regime and is mediated by a polar cloud of swimmers in the carrier wake pushing the wedge-particle forward. Finally, we also demonstrate that the optimal shape of the carrier leading to maximal transport speed depends on the kind of interaction model used.« less

Development of a method of alignment between various SOLAR MAXIMUM MISSION experiments

NASA Technical Reports Server (NTRS)

1977-01-01

Results of an engineering study of the methods of alignment between various experiments for the solar maximum mission are described. The configuration studied consists of the instruments, mounts and instrument support platform located within the experiment module. Hardware design, fabrication methods and alignment techniques were studied with regard to optimizing the coalignment between the experiments and the fine sun sensor. The proposed hardware design was reviewed with regard to loads, stress, thermal distortion, alignment error budgets, fabrication techniques, alignment techniques and producibility. Methods of achieving comparable alignment accuracies on previous projects were also reviewed.

Adaptable liquid crystal elastomers with transesterification-based bond exchange reactions.

PubMed

Hanzon, Drew W; Traugutt, Nicholas A; McBride, Matthew K; Bowman, Christopher N; Yakacki, Christopher M; Yu, Kai

2018-02-14

Adaptable liquid crystal elastomers (LCEs) have recently emerged to provide a new and robust method to program monodomain LCE samples. When a constant stress is applied with active bond exchange reactions (BERs), polymer chains and mesogens gradually align in the strain direction. Mesogen alignment is maintained after removing the BER stimulus (e.g. by lowering the temperature) and the programmed LCE samples exhibit free-standing two-way shape switching behavior. Here, a new adaptable main-chain LCE system was developed with thermally induced transesterification BERs. The network combines the conventional properties of LCEs, such as an isotropic phase transition and soft elasticity, with the dynamic features of adaptable network polymers, which are malleable to stress relaxation due to the BERs. Polarized Fourier transform infrared measurements confirmed the alignment of polymer chains and mesogens after strain-induced programming. The influence of the creep stress, temperature, and time on the strain amplitude of two-way shape switching was examined. The LCE network demonstrates an innovative feature of reprogrammability, where the reversible shape-switching memory of programmed LCEs is readily deleted by free-standing heating as random BERs disrupt the mesogen alignment, so LCEs are reprogrammed after returning to the polydomain state. Due to the dynamic nature of the LCE network, it also exhibits a surface welding effect and can be fully dissolved in the organic solvent, which might be utilized for green and sustainable recycling of LCEs.

Contrast research of CDMA and GSM network optimization

NASA Astrophysics Data System (ADS)

Wu, Yanwen; Liu, Zehong; Zhou, Guangyue

2004-03-01

With the development of mobile telecommunication network, users of CDMA advanced their request of network service quality. While the operators also change their network management object from signal coverage to performance improvement. In that case, reasonably layout & optimization of mobile telecommunication network, reasonably configuration of network resource, improvement of the service quality, and increase the enterprise's core competition ability, all those have been concerned by the operator companies. This paper firstly looked into the flow of CDMA network optimization. Then it dissertated to some keystones in the CDMA network optimization, like PN code assignment, calculation of soft handover, etc. As GSM is also the similar cellular mobile telecommunication system like CDMA, so this paper also made a contrast research of CDMA and GSM network optimization in details, including the similarity and the different. In conclusion, network optimization is a long time job; it will run through the whole process of network construct. By the adjustment of network hardware (like BTS equipments, RF systems, etc.) and network software (like parameter optimized, configuration optimized, capacity optimized, etc.), network optimization work can improve the performance and service quality of the network.

Differential evolution-simulated annealing for multiple sequence alignment

NASA Astrophysics Data System (ADS)

Addawe, R. C.; Addawe, J. M.; Sueño, M. R. K.; Magadia, J. C.

2017-10-01

Multiple sequence alignments (MSA) are used in the analysis of molecular evolution and sequence structure relationships. In this paper, a hybrid algorithm, Differential Evolution - Simulated Annealing (DESA) is applied in optimizing multiple sequence alignments (MSAs) based on structural information, non-gaps percentage and totally conserved columns. DESA is a robust algorithm characterized by self-organization, mutation, crossover, and SA-like selection scheme of the strategy parameters. Here, the MSA problem is treated as a multi-objective optimization problem of the hybrid evolutionary algorithm, DESA. Thus, we name the algorithm as DESA-MSA. Simulated sequences and alignments were generated to evaluate the accuracy and efficiency of DESA-MSA using different indel sizes, sequence lengths, deletion rates and insertion rates. The proposed hybrid algorithm obtained acceptable solutions particularly for the MSA problem evaluated based on the three objectives.

Lithographic process window optimization for mask aligner proximity lithography

NASA Astrophysics Data System (ADS)

Voelkel, Reinhard; Vogler, Uwe; Bramati, Arianna; Erdmann, Andreas; Ünal, Nezih; Hofmann, Ulrich; Hennemeyer, Marc; Zoberbier, Ralph; Nguyen, David; Brugger, Juergen

2014-03-01

We introduce a complete methodology for process window optimization in proximity mask aligner lithography. The commercially available lithography simulation software LAB from GenISys GmbH was used for simulation of light propagation and 3D resist development. The methodology was tested for the practical example of lines and spaces, 5 micron half-pitch, printed in a 1 micron thick layer of AZ® 1512HS1 positive photoresist on a silicon wafer. A SUSS MicroTec MA8 mask aligner, equipped with MO Exposure Optics® was used in simulation and experiment. MO Exposure Optics® is the latest generation of illumination systems for mask aligners. MO Exposure Optics® provides telecentric illumination and excellent light uniformity over the full mask field. MO Exposure Optics® allows the lithography engineer to freely shape the angular spectrum of the illumination light (customized illumination), which is a mandatory requirement for process window optimization. Three different illumination settings have been tested for 0 to 100 micron proximity gap. The results obtained prove, that the introduced process window methodology is a major step forward to obtain more robust processes in mask aligner lithography. The most remarkable outcome of the presented study is that a smaller exposure gap does not automatically lead to better print results in proximity lithography - what the "good instinct" of a lithographer would expect. With more than 5'000 mask aligners installed in research and industry worldwide, the proposed process window methodology might have significant impact on yield improvement and cost saving in industry.

Alignment and integration of complex networks by hypergraph-based spectral clustering

NASA Astrophysics Data System (ADS)

Michoel, Tom; Nachtergaele, Bruno

2012-11-01

Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.

Alignment and integration of complex networks by hypergraph-based spectral clustering.

PubMed

Michoel, Tom; Nachtergaele, Bruno

2012-11-01

Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.

Aligning Human Resource Development with the Strategic Priorities of Healthcare Organizations: The CFO Perspective

ERIC Educational Resources Information Center

Smith, Carla Breedlove

2013-01-01

The purpose of this qualitative study was to gain an understanding of how human resource development (HRD) can align more closely with the healthcare system's strategic priorities from the perspective of chief financial officers (CFOs). Five common themes emerged: (a) training is well aligned to the strategic priority to optimize clinical…

RBT-GA: a novel metaheuristic for solving the Multiple Sequence Alignment problem.

PubMed

Taheri, Javid; Zomaya, Albert Y

2009-07-07

Multiple Sequence Alignment (MSA) has always been an active area of research in Bioinformatics. MSA is mainly focused on discovering biologically meaningful relationships among different sequences or proteins in order to investigate the underlying main characteristics/functions. This information is also used to generate phylogenetic trees. This paper presents a novel approach, namely RBT-GA, to solve the MSA problem using a hybrid solution methodology combining the Rubber Band Technique (RBT) and the Genetic Algorithm (GA) metaheuristic. RBT is inspired by the behavior of an elastic Rubber Band (RB) on a plate with several poles, which is analogues to locations in the input sequences that could potentially be biologically related. A GA attempts to mimic the evolutionary processes of life in order to locate optimal solutions in an often very complex landscape. RBT-GA is a population based optimization algorithm designed to find the optimal alignment for a set of input protein sequences. In this novel technique, each alignment answer is modeled as a chromosome consisting of several poles in the RBT framework. These poles resemble locations in the input sequences that are most likely to be correlated and/or biologically related. A GA-based optimization process improves these chromosomes gradually yielding a set of mostly optimal answers for the MSA problem. RBT-GA is tested with one of the well-known benchmarks suites (BALiBASE 2.0) in this area. The obtained results show that the superiority of the proposed technique even in the case of formidable sequences.

An optimized and low-cost FPGA-based DNA sequence alignment--a step towards personal genomics.

PubMed

Shah, Hurmat Ali; Hasan, Laiq; Ahmad, Nasir

2013-01-01

DNA sequence alignment is a cardinal process in computational biology but also is much expensive computationally when performing through traditional computational platforms like CPU. Of many off the shelf platforms explored for speeding up the computation process, FPGA stands as the best candidate due to its performance per dollar spent and performance per watt. These two advantages make FPGA as the most appropriate choice for realizing the aim of personal genomics. The previous implementation of DNA sequence alignment did not take into consideration the price of the device on which optimization was performed. This paper presents optimization over previous FPGA implementation that increases the overall speed-up achieved as well as the price incurred by the platform that was optimized. The optimizations are (1) The array of processing elements is made to run on change in input value and not on clock, so eliminating the need for tight clock synchronization, (2) the implementation is unrestrained by the size of the sequences to be aligned, (3) the waiting time required for the sequences to load to FPGA is reduced to the minimum possible and (4) an efficient method is devised to store the output matrix that make possible to save the diagonal elements to be used in next pass, in parallel with the computation of output matrix. Implemented on Spartan3 FPGA, this implementation achieved 20 times performance improvement in terms of CUPS over GPP implementation.

Optimal design of an alignment-free two-DOF rehabilitation robot for the shoulder complex.

PubMed

Galinski, Daniel; Sapin, Julien; Dehez, Bruno

2013-06-01

This paper presents the optimal design of an alignment-free exoskeleton for the rehabilitation of the shoulder complex. This robot structure is constituted of two actuated joints and is linked to the arm through passive degrees of freedom (DOFs) to drive the flexion-extension and abduction-adduction movements of the upper arm. The optimal design of this structure is performed through two steps. The first step is a multi-objective optimization process aiming to find the best parameters characterizing the robot and its position relative to the patient. The second step is a comparison process aiming to select the best solution from the optimization results on the basis of several criteria related to practical considerations. The optimal design process leads to a solution outperforming an existing solution on aspects as kinematics or ergonomics while being more simple.

Improving accountability through alignment: the role of academic health science centres and networks in England.

PubMed

Ovseiko, Pavel V; Heitmueller, Axel; Allen, Pauline; Davies, Stephen M; Wells, Glenn; Ford, Gary A; Darzi, Ara; Buchan, Alastair M

2014-01-20

As in many countries around the world, there are high expectations on academic health science centres and networks in England to provide high-quality care, innovative research, and world-class education, while also supporting wealth creation and economic growth. Meeting these expectations increasingly depends on partnership working between university medical schools and teaching hospitals, as well as other healthcare providers. However, academic-clinical relationships in England are still characterised by the "unlinked partners" model, whereby universities and their partner teaching hospitals are neither fiscally nor structurally linked, creating bifurcating accountabilities to various government and public agencies. This article focuses on accountability relationships in universities and teaching hospitals, as well as other healthcare providers that form core constituent parts of academic health science centres and networks. The authors analyse accountability for the tripartite mission of patient care, research, and education, using a four-fold typology of accountability relationships, which distinguishes between hierarchical (bureaucratic) accountability, legal accountability, professional accountability, and political accountability. Examples from North West London suggest that a number of mechanisms can be used to improve accountability for the tripartite mission through alignment, but that the simple creation of academic health science centres and networks is probably not sufficient. At the heart of the challenge for academic health science centres and networks is the separation of accountabilities for patient care, research, and education in different government departments. Given that a fundamental top-down system redesign is now extremely unlikely, local academic and clinical leaders face the challenge of aligning their institutions as a matter of priority in order to improve accountability for the tripartite mission from the bottom up. It remains to be seen which alignment mechanisms are most effective, and whether they are strong enough to counter the separation of accountabilities for the tripartite mission at the national level, the on-going structural fragmentation of the health system in England, and the unprecedented financial challenges that it faces. Future research should focus on determining the comparative effectiveness of different alignment mechanisms, developing standardised metrics and key performance indicators, evaluating and assessing academic health science centres and networks, and empirically addressing leadership issues.

Improving accountability through alignment: the role of academic health science centres and networks in England

PubMed Central

2014-01-01

Background As in many countries around the world, there are high expectations on academic health science centres and networks in England to provide high-quality care, innovative research, and world-class education, while also supporting wealth creation and economic growth. Meeting these expectations increasingly depends on partnership working between university medical schools and teaching hospitals, as well as other healthcare providers. However, academic-clinical relationships in England are still characterised by the “unlinked partners” model, whereby universities and their partner teaching hospitals are neither fiscally nor structurally linked, creating bifurcating accountabilities to various government and public agencies. Discussion This article focuses on accountability relationships in universities and teaching hospitals, as well as other healthcare providers that form core constituent parts of academic health science centres and networks. The authors analyse accountability for the tripartite mission of patient care, research, and education, using a four-fold typology of accountability relationships, which distinguishes between hierarchical (bureaucratic) accountability, legal accountability, professional accountability, and political accountability. Examples from North West London suggest that a number of mechanisms can be used to improve accountability for the tripartite mission through alignment, but that the simple creation of academic health science centres and networks is probably not sufficient. Summary At the heart of the challenge for academic health science centres and networks is the separation of accountabilities for patient care, research, and education in different government departments. Given that a fundamental top-down system redesign is now extremely unlikely, local academic and clinical leaders face the challenge of aligning their institutions as a matter of priority in order to improve accountability for the tripartite mission from the bottom up. It remains to be seen which alignment mechanisms are most effective, and whether they are strong enough to counter the separation of accountabilities for the tripartite mission at the national level, the on-going structural fragmentation of the health system in England, and the unprecedented financial challenges that it faces. Future research should focus on determining the comparative effectiveness of different alignment mechanisms, developing standardised metrics and key performance indicators, evaluating and assessing academic health science centres and networks, and empirically addressing leadership issues. PMID:24438592

Genetic algorithms for protein threading.

PubMed

Yadgari, J; Amir, A; Unger, R

1998-01-01

Despite many years of efforts, a direct prediction of protein structure from sequence is still not possible. As a result, in the last few years researchers have started to address the "inverse folding problem": Identifying and aligning a sequence to the fold with which it is most compatible, a process known as "threading". In two meetings in which protein folding predictions were objectively evaluated, it became clear that threading as a concept promises a real breakthrough, but that much improvement is still needed in the technique itself. Threading is a NP-hard problem, and thus no general polynomial solution can be expected. Still a practical approach with demonstrated ability to find optimal solutions in many cases, and acceptable solutions in other cases, is needed. We applied the technique of Genetic Algorithms in order to significantly improve the ability of threading algorithms to find the optimal alignment of a sequence to a structure, i.e. the alignment with the minimum free energy. A major progress reported here is the design of a representation of the threading alignment as a string of fixed length. With this representation validation of alignments and genetic operators are effectively implemented. Appropriate data structure and parameters have been selected. It is shown that Genetic Algorithm threading is effective and is able to find the optimal alignment in a few test cases. Furthermore, the described algorithm is shown to perform well even without pre-definition of core elements. Existing threading methods are dependent on such constraints to make their calculations feasible. But the concept of core elements is inherently arbitrary and should be avoided if possible. While a rigorous proof is hard to submit yet an, we present indications that indeed Genetic Algorithm threading is capable of finding consistently good solutions of full alignments in search spaces of size up to 10(70).

CORAL: aligning conserved core regions across domain families.

PubMed

Fong, Jessica H; Marchler-Bauer, Aron

2009-08-01

Homologous protein families share highly conserved sequence and structure regions that are frequent targets for comparative analysis of related proteins and families. Many protein families, such as the curated domain families in the Conserved Domain Database (CDD), exhibit similar structural cores. To improve accuracy in aligning such protein families, we propose a profile-profile method CORAL that aligns individual core regions as gap-free units. CORAL computes optimal local alignment of two profiles with heuristics to preserve continuity within core regions. We benchmarked its performance on curated domains in CDD, which have pre-defined core regions, against COMPASS, HHalign and PSI-BLAST, using structure superpositions and comprehensive curator-optimized alignments as standards of truth. CORAL improves alignment accuracy on core regions over general profile methods, returning a balanced score of 0.57 for over 80% of all domain families in CDD, compared with the highest balanced score of 0.45 from other methods. Further, CORAL provides E-values to aid in detecting homologous protein families and, by respecting block boundaries, produces alignments with improved 'readability' that facilitate manual refinement. CORAL will be included in future versions of the NCBI Cn3D/CDTree software, which can be downloaded at http://www.ncbi.nlm.nih.gov/Structure/cdtree/cdtree.shtml. Supplementary data are available at Bioinformatics online.

Piezoelectric Response of Aligned Electrospun Polyvinylidene Fluoride/Carbon Nanotube Nanofibrous Membranes.

PubMed

Wu, Chang-Mou; Chou, Min-Hui; Zeng, Wun-Yuan

2018-06-10

Polyvinylidene fluoride (PVDF) shows piezoelectricity related to its β-phase content and mechanical and electrical properties influenced by its morphology and crystallinity. Electrospinning (ES) can produce ultrafine and well-aligned PVDF nanofibers. In this study, the effects of the presence of carbon nanotubes (CNT) and optimized ES parameters on the crystal structures and piezoelectric properties of aligned PVDF/CNT nanofibrous membranes were examined. The optimal β content and piezoelectric coefficient (d 33 ) of the aligned electrospun PVDF reached 88% and 27.4 pC/N; CNT addition increased the β-phase content to 89% and d 33 to 31.3 pC/N. The output voltages of piezoelectric units with aligned electrospun PVDF/CNT membranes increased linearly with applied loading and showed good stability during cyclic dynamic compression and tension. The sensitivities of the piezoelectric units with the membranes under dynamic compression and tension were 2.26 mV/N and 4.29 mV/%, respectively. In bending tests, the output voltage increased nonlinearly with bending angle because complicated forces were involved. The output of the aligned membrane-based piezoelectric unit with CNT was 1.89 V at the bending angle of 100°. The high electric outputs indicate that the aligned electrospun PVDF/CNT membranes are potentially effective for flexible wearable sensor application with high sensitivity.

Vertically Aligned and Interconnected SiC Nanowire Networks Leading to Significantly Enhanced Thermal Conductivity of Polymer Composites.

PubMed

Yao, Yimin; Zhu, Xiaodong; Zeng, Xiaoliang; Sun, Rong; Xu, Jian-Bin; Wong, Ching-Ping

2018-03-21

Efficient heat removal via thermal management materials has become one of the most critical challenges in the development of modern microelectronic devices. However, previously reported polymer composites exhibit limited enhancement of thermal conductivity, even when highly loaded with thermally conductive fillers, because of the lack of efficient heat transfer pathways. Herein, we report vertically aligned and interconnected SiC nanowire (SiCNW) networks as efficient fillers for polymer composites, achieving significantly enhanced thermal conductivity. The SiCNW networks are produced by freeze-casting nanowire aqueous suspensions followed by thermal sintering to consolidate the nanowire junctions, exhibiting a hierarchical architecture in which honeycomb-like SiCNW layers are aligned. The composite obtained by infiltrating SiCNW networks with epoxy resin, at a relatively low SiCNW loading of 2.17 vol %, represents a high through-plane thermal conductivity (1.67 W m -1 K -1 ) compared to the pure matrix, which is equivalent to a significant enhancement of 406.6% per 1 vol % loading. The orderly SiCNW network which can act as a macroscopic expressway for phonon transport is believed to be the main contributor for the excellent thermal performance. This strategy provides insights for the design of high-performance composites with potential to be used in advanced thermal management materials.

Use artificial neural network to align biological ontologies.

PubMed

Huang, Jingshan; Dang, Jiangbo; Huhns, Michael N; Zheng, W Jim

2008-09-16

Being formal, declarative knowledge representation models, ontologies help to address the problem of imprecise terminologies in biological and biomedical research. However, ontologies constructed under the auspices of the Open Biomedical Ontologies (OBO) group have exhibited a great deal of variety, because different parties can design ontologies according to their own conceptual views of the world. It is therefore becoming critical to align ontologies from different parties. During automated/semi-automated alignment across biological ontologies, different semantic aspects, i.e., concept name, concept properties, and concept relationships, contribute in different degrees to alignment results. Therefore, a vector of weights must be assigned to these semantic aspects. It is not trivial to determine what those weights should be, and current methodologies depend a lot on human heuristics. In this paper, we take an artificial neural network approach to learn and adjust these weights, and thereby support a new ontology alignment algorithm, customized for biological ontologies, with the purpose of avoiding some disadvantages in both rule-based and learning-based aligning algorithms. This approach has been evaluated by aligning two real-world biological ontologies, whose features include huge file size, very few instances, concept names in numerical strings, and others. The promising experiment results verify our proposed hypothesis, i.e., three weights for semantic aspects learned from a subset of concepts are representative of all concepts in the same ontology. Therefore, our method represents a large leap forward towards automating biological ontology alignment.

Concentration solar power optimization system and method of using the same

DOEpatents

Andraka, Charles E

2014-03-18

A system and method for optimizing at least one mirror of at least one CSP system is provided. The system has a screen for displaying light patterns for reflection by the mirror, a camera for receiving a reflection of the light patterns from the mirror, and a solar characterization tool. The solar characterization tool has a characterizing unit for determining at least one mirror parameter of the mirror based on an initial position of the camera and the screen, and a refinement unit for refining the determined parameter(s) based on an adjusted position of the camera and screen whereby the mirror is characterized. The system may also be provided with a solar alignment tool for comparing at least one mirror parameter of the mirror to a design geometry whereby an alignment error is defined, and at least one alignment unit for adjusting the mirror to reduce the alignment error.

Use of the BINP HLS to measure vertical changes in the locations of the building and ground at the PAL-XFEL

NASA Astrophysics Data System (ADS)

Choi, Hyo-Jin; Seo, Kwang-Won; Gil, Kye-Hwan; Kim, Seung-Hwan; Kang, Heung-Sik

2016-09-01

The Pohang Accelerator Laboratory's X-ray free-electron laser (PAL-XFEL), a 4 th generation light source, is currently being installed and will be completed by December 2015 so that users can be supported beginning in 2016. The PAL-XFEL equipment must continuously maintain the bunch-tobunch beam parameters (60 Hz, Energy: 10 GeV, Charge: 200 pC, Bunch Length: 60 fs, Emittance X/Y: 0.481/0.256 mm rad) in order to supply stable photons with the energy and flux appropriate for tests by beamline users. To this end, the PAL-XFEL equipment has to be kept precisely aligned (Linear Accelerator: +/- 100 μm, Undulator: +/- 50 μm). As a part of the process for installing the PAL-XFEL, a GPS-using surface geodetic network is being constructed for precise equipment measurement and alignment, and the installation of a tunnel measurement network inside the buildings is in the preparation stage; additionally, the fiducialization of major equipment is underway. After the PAL-XFEL equipment is optimized and aligned, if the ground and the buildings go through vertical changes during operation, misalignment (and tilt) of the equipment, including various magnets and RF structures, will cause errors in the electron beam's trajectory, which will lead to changes to the beam parameters. For continuous and systemic measurement of vertical changes in the buildings and monitoring of ground sinking and uplifting, the Budker Institute of Nuclear Physics (BINP) Ultrasonic-type Hydrostatic Levelling System (HLS) is to be installed and operated in all sections of the PAL-XFEL for the linear accelerator, the insertion device (undulator) and the beamline. This study will introduce the operation principle, design concept, and advantages (self-calibration) of the HLS and will outline its installation plan and operation plan.

Protein-protein interaction network-based detection of functionally similar proteins within species.

PubMed

Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

2012-07-01

Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent. Copyright © 2012 Wiley Periodicals, Inc.

Optimal image alignment with random projections of manifolds: algorithm and geometric analysis.

PubMed

Kokiopoulou, Effrosyni; Kressner, Daniel; Frossard, Pascal

2011-06-01

This paper addresses the problem of image alignment based on random measurements. Image alignment consists of estimating the relative transformation between a query image and a reference image. We consider the specific problem where the query image is provided in compressed form in terms of linear measurements captured by a vision sensor. We cast the alignment problem as a manifold distance minimization problem in the linear subspace defined by the measurements. The transformation manifold that represents synthesis of shift, rotation, and isotropic scaling of the reference image can be given in closed form when the reference pattern is sparsely represented over a parametric dictionary. We show that the objective function can then be decomposed as the difference of two convex functions (DC) in the particular case where the dictionary is built on Gaussian functions. Thus, the optimization problem becomes a DC program, which in turn can be solved globally by a cutting plane method. The quality of the solution is typically affected by the number of random measurements and the condition number of the manifold that describes the transformations of the reference image. We show that the curvature, which is closely related to the condition number, remains bounded in our image alignment problem, which means that the relative transformation between two images can be determined optimally in a reduced subspace.

A Coarse-Alignment Method Based on the Optimal-REQUEST Algorithm

PubMed Central

Zhu, Yongyun

2018-01-01

In this paper, we proposed a coarse-alignment method for strapdown inertial navigation systems based on attitude determination. The observation vectors, which can be obtained by inertial sensors, usually contain various types of noise, which affects the convergence rate and the accuracy of the coarse alignment. Given this drawback, we studied an attitude-determination method named optimal-REQUEST, which is an optimal method for attitude determination that is based on observation vectors. Compared to the traditional attitude-determination method, the filtering gain of the proposed method is tuned autonomously; thus, the convergence rate of the attitude determination is faster than in the traditional method. Within the proposed method, we developed an iterative method for determining the attitude quaternion. We carried out simulation and turntable tests, which we used to validate the proposed method’s performance. The experiment’s results showed that the convergence rate of the proposed optimal-REQUEST algorithm is faster and that the coarse alignment’s stability is higher. In summary, the proposed method has a high applicability to practical systems. PMID:29337895

High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features.

PubMed

Jones, David T; Kandathil, Shaun M

2018-04-26

In addition to substitution frequency data from protein sequence alignments, many state-of-the-art methods for contact prediction rely on additional sources of information, or features, of protein sequences in order to predict residue-residue contacts, such as solvent accessibility, predicted secondary structure, and scores from other contact prediction methods. It is unclear how much of this information is needed to achieve state-of-the-art results. Here, we show that using deep neural network models, simple alignment statistics contain sufficient information to achieve state-of-the-art precision. Our prediction method, DeepCov, uses fully convolutional neural networks operating on amino-acid pair frequency or covariance data derived directly from sequence alignments, without using global statistical methods such as sparse inverse covariance or pseudolikelihood estimation. Comparisons against CCMpred and MetaPSICOV2 show that using pairwise covariance data calculated from raw alignments as input allows us to match or exceed the performance of both of these methods. Almost all of the achieved precision is obtained when considering relatively local windows (around 15 residues) around any member of a given residue pairing; larger window sizes have comparable performance. Assessment on a set of shallow sequence alignments (fewer than 160 effective sequences) indicates that the new method is substantially more precise than CCMpred and MetaPSICOV2 in this regime, suggesting that improved precision is attainable on smaller sequence families. Overall, the performance of DeepCov is competitive with the state of the art, and our results demonstrate that global models, which employ features from all parts of the input alignment when predicting individual contacts, are not strictly needed in order to attain precise contact predictions. DeepCov is freely available at https://github.com/psipred/DeepCov. d.t.jones@ucl.ac.uk.

Aligning Solution-Derived Carbon Nanotube Film with Full Surface Coverage for High-Performance Electronics Applications.

PubMed

Zhu, Ma-Guang; Si, Jia; Zhang, Zhiyong; Peng, Lian-Mao

2018-06-01

The main challenge for application of solution-derived carbon nanotubes (CNTs) in high performance field-effect transistor (FET) is how to align CNTs into an array with high density and full surface coverage. A directional shrinking transfer method is developed to realize high density aligned array based on randomly orientated CNT network film. Through transferring a solution-derived CNT network film onto a stretched retractable film followed by a shrinking process, alignment degree and density of CNT film increase with the shrinking multiple. The quadruply shrunk CNT films present well alignment, which is identified by the polarized Raman spectroscopy and electrical transport measurements. Based on the high quality and high density aligned CNT array, the fabricated FETs with channel length of 300 nm present ultrahigh performance including on-state current I on of 290 µA µm -1 (V ds = -1.5 V and V gs = -2 V) and peak transconductance g m of 150 µS µm -1 , which are, respectively, among the highest corresponding values in the reported CNT array FETs. High quality and high semiconducting purity CNT arrays with high density and full coverage obtained through this method promote the development of high performance CNT-based electronics. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Injectable Anisotropic Nanocomposite Hydrogels Direct in Situ Growth and Alignment of Myotubes

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

De France, Kevin J.; Yager, Kevin G.; Chan, Katelyn J. W.

Here, while injectable in situ cross-linking hydrogels have attracted increasing attention as minimally invasive tissue scaffolds and controlled delivery systems, their inherently disorganized and isotropic network structure limits their utility in engineering oriented biological tissues. Traditional methods to prepare anisotropic hydrogels are not easily translatable to injectable systems given the need for external equipment to direct anisotropic gel fabrication and/or the required use of temperatures or solvents incompatible with biological systems. Herein, we report a new class of injectable nanocomposite hydrogels based on hydrazone cross-linked poly(oligoethylene glycol methacrylate) and magnetically aligned cellulose nanocrystals (CNCs) capable of encapsulating skeletal muscle myoblastsmore » and promoting their differentiation into highly oriented myotubes in situ. CNC alignment occurs on the same time scale as network gelation and remains fixed after the removal of the magnetic field, enabling concurrent CNC orientation and hydrogel injection. The aligned hydrogels show mechanical and swelling profiles that can be rationally modulated by the degree of CNC alignment and can direct myotube alignment both in two- and three-dimensions following coinjection of the myoblasts with the gel precursor components. As such, these hydrogels represent a critical advancement in anisotropic biomimetic scaffolds that can be generated noninvasively in vivo following simple injection.« less

Injectable Anisotropic Nanocomposite Hydrogels Direct in Situ Growth and Alignment of Myotubes

DOE PAGES

De France, Kevin J.; Yager, Kevin G.; Chan, Katelyn J. W.; ...

2017-09-28

Here, while injectable in situ cross-linking hydrogels have attracted increasing attention as minimally invasive tissue scaffolds and controlled delivery systems, their inherently disorganized and isotropic network structure limits their utility in engineering oriented biological tissues. Traditional methods to prepare anisotropic hydrogels are not easily translatable to injectable systems given the need for external equipment to direct anisotropic gel fabrication and/or the required use of temperatures or solvents incompatible with biological systems. Herein, we report a new class of injectable nanocomposite hydrogels based on hydrazone cross-linked poly(oligoethylene glycol methacrylate) and magnetically aligned cellulose nanocrystals (CNCs) capable of encapsulating skeletal muscle myoblastsmore » and promoting their differentiation into highly oriented myotubes in situ. CNC alignment occurs on the same time scale as network gelation and remains fixed after the removal of the magnetic field, enabling concurrent CNC orientation and hydrogel injection. The aligned hydrogels show mechanical and swelling profiles that can be rationally modulated by the degree of CNC alignment and can direct myotube alignment both in two- and three-dimensions following coinjection of the myoblasts with the gel precursor components. As such, these hydrogels represent a critical advancement in anisotropic biomimetic scaffolds that can be generated noninvasively in vivo following simple injection.« less

RBT-GA: a novel metaheuristic for solving the multiple sequence alignment problem

PubMed Central

Taheri, Javid; Zomaya, Albert Y

2009-01-01

Background Multiple Sequence Alignment (MSA) has always been an active area of research in Bioinformatics. MSA is mainly focused on discovering biologically meaningful relationships among different sequences or proteins in order to investigate the underlying main characteristics/functions. This information is also used to generate phylogenetic trees. Results This paper presents a novel approach, namely RBT-GA, to solve the MSA problem using a hybrid solution methodology combining the Rubber Band Technique (RBT) and the Genetic Algorithm (GA) metaheuristic. RBT is inspired by the behavior of an elastic Rubber Band (RB) on a plate with several poles, which is analogues to locations in the input sequences that could potentially be biologically related. A GA attempts to mimic the evolutionary processes of life in order to locate optimal solutions in an often very complex landscape. RBT-GA is a population based optimization algorithm designed to find the optimal alignment for a set of input protein sequences. In this novel technique, each alignment answer is modeled as a chromosome consisting of several poles in the RBT framework. These poles resemble locations in the input sequences that are most likely to be correlated and/or biologically related. A GA-based optimization process improves these chromosomes gradually yielding a set of mostly optimal answers for the MSA problem. Conclusion RBT-GA is tested with one of the well-known benchmarks suites (BALiBASE 2.0) in this area. The obtained results show that the superiority of the proposed technique even in the case of formidable sequences. PMID:19594869

Inter-allotropic transformations in the heterogeneous carbon nanotube networks.

PubMed

Jung, Hyun Young; Jung, Sung Mi; Kim, Dong Won; Jung, Yung Joon

2017-01-19

The allotropic transformations of carbon provide an immense technological interest for tailoring the desired molecular structures in the scalable nanoelectronic devices. Herein, we explore the effects of morphology and geometric alignment of the nanotubes for the re-engineering of carbon bonds in the heterogeneous carbon nanotube (CNT) networks. By applying alternating voltage pulses and electrical forces, the single-walled CNTs in networks were predominantly transformed into other predetermined sp 2 carbon structures (multi-walled CNTs and multi-layered graphitic nanoribbons), showing a larger intensity in a coalescence-induced mode of Raman spectra with the increasing channel width. Moreover, the transformed networks have a newly discovered sp 2 -sp 3 hybrid nanostructures in accordance with the alignment. The sp 3 carbon structures at the small channel are controlled, such that they contain up to about 29.4% networks. This study provides a controllable method for specific types of inter-allotropic transformations/hybridizations, which opens up the further possibility for the engineering of nanocarbon allotropes in the robust large-scale network-based devices.

All-optical OFDM network coding scheme for all-optical virtual private communication in PON

NASA Astrophysics Data System (ADS)

Li, Lijun; Gu, Rentao; Ji, Yuefeng; Bai, Lin; Huang, Zhitong

2014-03-01

A novel optical orthogonal frequency division multiplexing (OFDM) network coding scheme is proposed over passive optical network (PON) system. The proposed scheme for all-optical virtual private network (VPN) does not only improve transmission efficiency, but also realize full-duplex communication mode in a single fiber. Compared with the traditional all-optical VPN architectures, the all-optical OFDM network coding scheme can support higher speed, more flexible bandwidth allocation, and higher spectrum efficiency. In order to reduce the difficulty of alignment for encoding operation between inter-communication traffic, the width of OFDM subcarrier pulse is stretched in our proposed scheme. The feasibility of all-optical OFDM network coding scheme for VPN is verified, and the relevant simulation results show that the full-duplex inter-communication traffic stream can be transmitted successfully. Furthermore, the tolerance of misalignment existing in inter-ONUs traffic is investigated and analyzed for all-optical encoding operation, and the difficulty of pulse alignment is proved to be lower.

Discrete Fracture Network Characterization of Fractured Shale Reservoirs with Implications to Hydraulic Fracturing Optimization

NASA Astrophysics Data System (ADS)

Jin, G.

2016-12-01

Shales are important petroleum source rocks and reservoir seals. Recent developments in hydraulic fracturing technology have facilitated high gas production rates from shale and have had a strong impact on the U.S. gas supply and markets. Modeling of effective permeability for fractured shale reservoirs has been challenging because the presence of a fracture network significantly alters the reservoir hydrologic properties. Due to the frequent occurrence of fracture networks, it is of vital importance to characterize fracture networks and to investigate how these networks can be used to optimize the hydraulic fracturing. We have conducted basic research on 3-D fracture permeability characterization and compartmentization analyses for fractured shale formations, which takes the advantages of the discrete fracture networks (DFN). The DFN modeling is a stochastic modeling approach using the probabilistic density functions of fractures. Three common scenarios of DFN models have been studied for fracture permeability mapping using our previously proposed techniques. In DFN models with moderately to highly concentrated fractures, there exists a representative element volume (REV) for fracture permeability characterization, which indicates that the fractured reservoirs can be treated as anisotropic homogeneous media. Hydraulic fracturing will be most effective if the orientation of the hydraulic fracture is perpendicular to the mean direction of the fractures. A DFN model with randomized fracture orientations, on the other hand, lacks an REV for fracture characterization. Therefore, a fracture permeability tensor has to be computed from each element. Modeling of fracture interconnectivity indicates that there exists no preferred direction for hydraulic fracturing to be most effective oweing to the interconnected pathways of the fracture network. 3-D fracture permeability mapping has been applied to the Devonian Chattanooga Shale in Alabama and the results suggest that an REV exist for fluid flow and transport modeling at element sizes larger than 200 m. Fracture pathway analysis indicates that hydraulic fracturing can be equally effective for hydrocarbon fluid/gas exploration as long as its orientation is not aligned with that of the regional system fractures.

Bokeh mirror alignment for Cherenkov telescopes

NASA Astrophysics Data System (ADS)

Ahnen, M. L.; Baack, D.; Balbo, M.; Bergmann, M.; Biland, A.; Blank, M.; Bretz, T.; Bruegge, K. A.; Buss, J.; Domke, M.; Dorner, D.; Einecke, S.; Hempfling, C.; Hildebrand, D.; Hughes, G.; Lustermann, W.; Mannheim, K.; Mueller, S. A.; Neise, D.; Neronov, A.; Noethe, M.; Overkemping, A.-K.; Paravac, A.; Pauss, F.; Rhode, W.; Shukla, A.; Temme, F.; Thaele, J.; Toscano, S.; Vogler, P.; Walter, R.; Wilbert, A.

2016-09-01

Imaging Atmospheric Cherenkov Telescopes (IACTs) need imaging optics with large apertures and high image intensities to map the faint Cherenkov light emitted from cosmic ray air showers onto their image sensors. Segmented reflectors fulfill these needs, and composed from mass production mirror facets they are inexpensive and lightweight. However, as the overall image is a superposition of the individual facet images, alignment remains a challenge. Here we present a simple, yet extendable method, to align a segmented reflector using its Bokeh. Bokeh alig nment does not need a star or good weather nights but can be done even during daytime. Bokeh alignment optimizes the facet orientations by comparing the segmented reflectors Bokeh to a predefined template. The optimal Bokeh template is highly constricted by the reflector's aperture and is easy accessible. The Bokeh is observed using the out of focus image of a near by point like light source in a distance of about 10 focal lengths. We introduce Bokeh alignment on segmented reflectors and demonstrate it on the First Geiger-mode Avalanche Cherenkov Telescope (FACT) on La Palma, Spain.

Tailorable Dielectric Material with Complex Permittivity Characteristics

NASA Technical Reports Server (NTRS)

Smith, Joseph G. (Inventor); Watson, Kent A. (Inventor); Elliott, Holly A (Inventor); Delozier, Donavon Mark (Inventor); Connell, John W. (Inventor); Ghose, Sayata (Inventor); Dudley, Kenneth L. (Inventor)

2014-01-01

A dielectric material includes a network of nanosubstrates, such as but not limited to nanotubes, nanosheets, or other nanomaterials or nanostructures, a polymer base material or matrix, and nanoparticles constructed at least partially of an elemental metal. The network has a predetermined nanosubstrate loading percentage by weight with respect to a total weight of the dielectric material, and a preferential or predetermined longitudinal alignment with respect to an orientation of an incident electrical field. A method of forming the dielectric material includes depositing the metal-based nanoparticles onto the nanosubstrates and subsequently mixing these with a polymer matrix. Once mixed, alignment can be achieved by melt extrusion or a similar mechanical shearing process. Alignment of the nanosubstrate may be in horizontal or vertical direction with respect to the orientation of an incident electrical field.

SPARSE: quadratic time simultaneous alignment and folding of RNAs without sequence-based heuristics.

PubMed

Will, Sebastian; Otto, Christina; Miladi, Milad; Möhl, Mathias; Backofen, Rolf

2015-08-01

RNA-Seq experiments have revealed a multitude of novel ncRNAs. The gold standard for their analysis based on simultaneous alignment and folding suffers from extreme time complexity of [Formula: see text]. Subsequently, numerous faster 'Sankoff-style' approaches have been suggested. Commonly, the performance of such methods relies on sequence-based heuristics that restrict the search space to optimal or near-optimal sequence alignments; however, the accuracy of sequence-based methods breaks down for RNAs with sequence identities below 60%. Alignment approaches like LocARNA that do not require sequence-based heuristics, have been limited to high complexity ([Formula: see text] quartic time). Breaking this barrier, we introduce the novel Sankoff-style algorithm 'sparsified prediction and alignment of RNAs based on their structure ensembles (SPARSE)', which runs in quadratic time without sequence-based heuristics. To achieve this low complexity, on par with sequence alignment algorithms, SPARSE features strong sparsification based on structural properties of the RNA ensembles. Following PMcomp, SPARSE gains further speed-up from lightweight energy computation. Although all existing lightweight Sankoff-style methods restrict Sankoff's original model by disallowing loop deletions and insertions, SPARSE transfers the Sankoff algorithm to the lightweight energy model completely for the first time. Compared with LocARNA, SPARSE achieves similar alignment and better folding quality in significantly less time (speedup: 3.7). At similar run-time, it aligns low sequence identity instances substantially more accurate than RAF, which uses sequence-based heuristics. © The Author 2015. Published by Oxford University Press.

Mango: multiple alignment with N gapped oligos.

PubMed

Zhang, Zefeng; Lin, Hao; Li, Ming

2008-06-01

Multiple sequence alignment is a classical and challenging task. The problem is NP-hard. The full dynamic programming takes too much time. The progressive alignment heuristics adopted by most state-of-the-art works suffer from the "once a gap, always a gap" phenomenon. Is there a radically new way to do multiple sequence alignment? In this paper, we introduce a novel and orthogonal multiple sequence alignment method, using both multiple optimized spaced seeds and new algorithms to handle these seeds efficiently. Our new algorithm processes information of all sequences as a whole and tries to build the alignment vertically, avoiding problems caused by the popular progressive approaches. Because the optimized spaced seeds have proved significantly more sensitive than the consecutive k-mers, the new approach promises to be more accurate and reliable. To validate our new approach, we have implemented MANGO: Multiple Alignment with N Gapped Oligos. Experiments were carried out on large 16S RNA benchmarks, showing that MANGO compares favorably, in both accuracy and speed, against state-of-the-art multiple sequence alignment methods, including ClustalW 1.83, MUSCLE 3.6, MAFFT 5.861, ProbConsRNA 1.11, Dialign 2.2.1, DIALIGN-T 0.2.1, T-Coffee 4.85, POA 2.0, and Kalign 2.0. We have further demonstrated the scalability of MANGO on very large datasets of repeat elements. MANGO can be downloaded at http://www.bioinfo.org.cn/mango/ and is free for academic usage.

The network of photodetectors and diode lasers of the CMS Link alignment system

NASA Astrophysics Data System (ADS)

Arce, P.; Barcala, J. M.; Calvo, E.; Ferrando, A.; Josa, M. I.; Molinero, A.; Navarrete, J.; Oller, J. C.; Brochero, J.; Calderón, A.; Fernández, M. G.; Gómez, G.; González-Sánchez, F. J.; Martínez-Rivero, C.; Matorras, F.; Rodrigo, T.; Ruiz-Árbol, P.; Scodellaro, L.; Sobrón, M.; Vila, I.; Virto, A. L.; Fernández, J.; Raics, P.; Szabó, Zs.; Trócsnyi, Z.; Ujvári, B.; Zilizi, Gy.; Béni, N.; Christian, G.; Imrek, J.; Molnar, J.; Novak, D.; Pálinkás, J.; Székely, G.; Szillási, Z.; Bencze, G. L.; Vestergombi, G.; Benettoni, M.; Gasparini, F.; Montecassiano, F.; Rampazzo, M.; Zago, M.; Benvenuti, A.; Reithler, H.; Jiang, C.

2018-07-01

The central feature of the CMS Link alignment system is a network of Amorphous Silicon Position Detectors distributed throughout the muon spectrometer that are connected by multiple laser lines. The data collected during the years from 2008 to 2015 is presented confirming an outstanding performance of the photo sensors during more than seven years of operation. Details of the photo sensor readout of the laser signals are presented. The mechanical motions of the CMS detector are monitored using these photosensors and good agreement with distance sensors is obtained.

A recurrent self-organizing neural fuzzy inference network.

PubMed

Juang, C F; Lin, C T

1999-01-01

A recurrent self-organizing neural fuzzy inference network (RSONFIN) is proposed in this paper. The RSONFIN is inherently a recurrent multilayered connectionist network for realizing the basic elements and functions of dynamic fuzzy inference, and may be considered to be constructed from a series of dynamic fuzzy rules. The temporal relations embedded in the network are built by adding some feedback connections representing the memory elements to a feedforward neural fuzzy network. Each weight as well as node in the RSONFIN has its own meaning and represents a special element in a fuzzy rule. There are no hidden nodes (i.e., no membership functions and fuzzy rules) initially in the RSONFIN. They are created on-line via concurrent structure identification (the construction of dynamic fuzzy if-then rules) and parameter identification (the tuning of the free parameters of membership functions). The structure learning together with the parameter learning forms a fast learning algorithm for building a small, yet powerful, dynamic neural fuzzy network. Two major characteristics of the RSONFIN can thus be seen: 1) the recurrent property of the RSONFIN makes it suitable for dealing with temporal problems and 2) no predetermination, like the number of hidden nodes, must be given, since the RSONFIN can find its optimal structure and parameters automatically and quickly. Moreover, to reduce the number of fuzzy rules generated, a flexible input partition method, the aligned clustering-based algorithm, is proposed. Various simulations on temporal problems are done and performance comparisons with some existing recurrent networks are also made. Efficiency of the RSONFIN is verified from these results.

A comparison of radiographic anatomic axis knee alignment measurements and cross-sectional associations with knee osteoarthritis.

PubMed

Goulston, L M; Sanchez-Santos, M T; D'Angelo, S; Leyland, K M; Hart, D J; Spector, T D; Cooper, C; Dennison, E M; Hunter, D; Arden, N K

2016-04-01

Malalignment is associated with knee osteoarthritis (KOA), however, the optimal anatomic axis (AA) knee alignment measurement on a standard limb radiograph (SLR) is unknown. This study compares one-point (1P) and two-point (2P) AA methods using three knee joint centre locations and examines cross-sectional associations with symptomatic radiographic knee osteoarthritis (SRKOA), radiographic knee osteoarthritis (RKOA) and knee pain. AA alignment was measured six different ways using the KneeMorf software on 1058 SLRs from 584 women in the Chingford Study. Cross-sectional associations with principal outcome SRKOA combined with greatest reproducibility determined the optimal 1P and 2P AA method. Appropriate varus/neutral/valgus alignment categories were established using logistic regression with generalised estimating equation models fitted with restricted cubic spline function. The tibial plateau centre displayed greatest reproducibility and associations with SRKOA. As mean 1P and 2P values differed by >2°, new alignment categories were generated for 1P: varus <178°, neutral 178-182°, valgus >182° and for 2P methods: varus <180°, neutral 180-185°, valgus >185°. Varus vs neutral alignment was associated with a near 2-fold increase in SRKOA and RKOA, and valgus vs neutral for RKOA using 2P method. Nonsignificant associations were seen for 1P method for SRKOA, RKOA and knee pain. AA alignment was associated with SRKOA and the tibial plateau centre had the strongest association. Differences in AA alignment when 1P vs 2P methods were compared indicated bespoke alignment categories were necessary. Further replication and validation with mechanical axis alignment comparison is required. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

A comparison of radiographic anatomic axis knee alignment measurements and cross-sectional associations with knee osteoarthritis

PubMed Central

Goulston, L.M.; Sanchez-Santos, M.T.; D'Angelo, S.; Leyland, K.M.; Hart, D.J.; Spector, T.D.; Cooper, C.; Dennison, E.M.; Hunter, D.; Arden, N.K.

2016-01-01

Summary Objective Malalignment is associated with knee osteoarthritis (KOA), however, the optimal anatomic axis (AA) knee alignment measurement on a standard limb radiograph (SLR) is unknown. This study compares one-point (1P) and two-point (2P) AA methods using three knee joint centre locations and examines cross-sectional associations with symptomatic radiographic knee osteoarthritis (SRKOA), radiographic knee osteoarthritis (RKOA) and knee pain. Methods AA alignment was measured six different ways using the KneeMorf software on 1058 SLRs from 584 women in the Chingford Study. Cross-sectional associations with principal outcome SRKOA combined with greatest reproducibility determined the optimal 1P and 2P AA method. Appropriate varus/neutral/valgus alignment categories were established using logistic regression with generalised estimating equation models fitted with restricted cubic spline function. Results The tibial plateau centre displayed greatest reproducibility and associations with SRKOA. As mean 1P and 2P values differed by >2°, new alignment categories were generated for 1P: varus <178°, neutral 178–182°, valgus >182° and for 2P methods: varus <180°, neutral 180–185°, valgus >185°. Varus vs neutral alignment was associated with a near 2-fold increase in SRKOA and RKOA, and valgus vs neutral for RKOA using 2P method. Nonsignificant associations were seen for 1P method for SRKOA, RKOA and knee pain. Conclusions AA alignment was associated with SRKOA and the tibial plateau centre had the strongest association. Differences in AA alignment when 1P vs 2P methods were compared indicated bespoke alignment categories were necessary. Further replication and validation with mechanical axis alignment comparison is required. PMID:26700504

Long Read Alignment with Parallel MapReduce Cloud Platform

PubMed Central

Al-Absi, Ahmed Abdulhakim; Kang, Dae-Ki

2015-01-01

Genomic sequence alignment is an important technique to decode genome sequences in bioinformatics. Next-Generation Sequencing technologies produce genomic data of longer reads. Cloud platforms are adopted to address the problems arising from storage and analysis of large genomic data. Existing genes sequencing tools for cloud platforms predominantly consider short read gene sequences and adopt the Hadoop MapReduce framework for computation. However, serial execution of map and reduce phases is a problem in such systems. Therefore, in this paper, we introduce Burrows-Wheeler Aligner's Smith-Waterman Alignment on Parallel MapReduce (BWASW-PMR) cloud platform for long sequence alignment. The proposed cloud platform adopts a widely accepted and accurate BWA-SW algorithm for long sequence alignment. A custom MapReduce platform is developed to overcome the drawbacks of the Hadoop framework. A parallel execution strategy of the MapReduce phases and optimization of Smith-Waterman algorithm are considered. Performance evaluation results exhibit an average speed-up of 6.7 considering BWASW-PMR compared with the state-of-the-art Bwasw-Cloud. An average reduction of 30% in the map phase makespan is reported across all experiments comparing BWASW-PMR with Bwasw-Cloud. Optimization of Smith-Waterman results in reducing the execution time by 91.8%. The experimental study proves the efficiency of BWASW-PMR for aligning long genomic sequences on cloud platforms. PMID:26839887

Long Read Alignment with Parallel MapReduce Cloud Platform.

PubMed

Al-Absi, Ahmed Abdulhakim; Kang, Dae-Ki

2015-01-01

Genomic sequence alignment is an important technique to decode genome sequences in bioinformatics. Next-Generation Sequencing technologies produce genomic data of longer reads. Cloud platforms are adopted to address the problems arising from storage and analysis of large genomic data. Existing genes sequencing tools for cloud platforms predominantly consider short read gene sequences and adopt the Hadoop MapReduce framework for computation. However, serial execution of map and reduce phases is a problem in such systems. Therefore, in this paper, we introduce Burrows-Wheeler Aligner's Smith-Waterman Alignment on Parallel MapReduce (BWASW-PMR) cloud platform for long sequence alignment. The proposed cloud platform adopts a widely accepted and accurate BWA-SW algorithm for long sequence alignment. A custom MapReduce platform is developed to overcome the drawbacks of the Hadoop framework. A parallel execution strategy of the MapReduce phases and optimization of Smith-Waterman algorithm are considered. Performance evaluation results exhibit an average speed-up of 6.7 considering BWASW-PMR compared with the state-of-the-art Bwasw-Cloud. An average reduction of 30% in the map phase makespan is reported across all experiments comparing BWASW-PMR with Bwasw-Cloud. Optimization of Smith-Waterman results in reducing the execution time by 91.8%. The experimental study proves the efficiency of BWASW-PMR for aligning long genomic sequences on cloud platforms.

Using Multimedia Metadata to Improve Network Efficiency

DTIC Science & Technology

2012-09-01

the north-aligned bounding box. When compared using all angular variations for the direction-of-travel-aligned 3:4 aspect ratio bounding box, the...programs that run the experiment are written in Java . The experiment consists of two distinct programs that communicate via Java sockets (TCP). 1

Positioning and aligning CNTs by external magnetic field to assist localised epoxy cure

NASA Astrophysics Data System (ADS)

Ariu, G.; Hamerton, I.; Ivanov, D.

2016-01-01

This work focuses on the generation of conductive networks through the localised alignment of nano fillers, such as multi-walled carbon nanotubes (MWCNTs). The feasibility of alignment and positioning of functionalised MWCNTs by external DC magnetic fields was investigated. The aim of this manipulation is to enhance resin curing through AC induction heating due to hysteresis losses from the nanotubes. Experimental analyses focused on in-depth assessment of the nanotube functionalisation, processing and characterisation of magnetic, rheological and cure kinetics properties of the MWCNT solution. The study has shown that an external magnetic field has great potential for positioning and alignment of CNTs. The study demonstrated potential for creating well-ordered architectures with an unprecedented level of control of network geometry. Magnetic characterisation indicated cobalt-plated nanotubes to be the most suitable candidate for magnetic alignment due to their high magnetic sensitivity. Epoxy/metal-plated CNT nanocomposite systems were validated by thermal analysis as induction heating mediums. The curing process could therefore be optimised by the use of dielectric resins. This study offers a first step towards the proof of concept of this technique as a novel repair technology.

Strawberry: Fast and accurate genome-guided transcript reconstruction and quantification from RNA-Seq.

PubMed

Liu, Ruolin; Dickerson, Julie

2017-11-01

We propose a novel method and software tool, Strawberry, for transcript reconstruction and quantification from RNA-Seq data under the guidance of genome alignment and independent of gene annotation. Strawberry consists of two modules: assembly and quantification. The novelty of Strawberry is that the two modules use different optimization frameworks but utilize the same data graph structure, which allows a highly efficient, expandable and accurate algorithm for dealing large data. The assembly module parses aligned reads into splicing graphs, and uses network flow algorithms to select the most likely transcripts. The quantification module uses a latent class model to assign read counts from the nodes of splicing graphs to transcripts. Strawberry simultaneously estimates the transcript abundances and corrects for sequencing bias through an EM algorithm. Based on simulations, Strawberry outperforms Cufflinks and StringTie in terms of both assembly and quantification accuracies. Under the evaluation of a real data set, the estimated transcript expression by Strawberry has the highest correlation with Nanostring probe counts, an independent experiment measure for transcript expression. Strawberry is written in C++14, and is available as open source software at https://github.com/ruolin/strawberry under the MIT license.

High-accuracy local positioning network for the alignment of the Mu2e experiment.

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

Hejdukova, Jana B.

This Diploma thesis describes the establishment of a high-precision local positioning network and accelerator alignment for the Mu2e physics experiment. The process of establishing new network consists of few steps: design of the network, pre-analysis, installation works, measurements of the network and making adjustments. Adjustments were performed using two approaches. First is a geodetic approach of taking into account the Earth’s curvature and the metrological approach of a pure 3D Cartesian system on the other side. The comparison of those two approaches is performed and evaluated in the results and compared with expected differences. The effect of the Earth’s curvaturemore » was found to be significant for this kind of network and should not be neglected. The measurements were obtained with Absolute Tracker AT401, leveling instrument Leica DNA03 and gyrotheodolite DMT Gyromat 2000. The coordinates of the points of the reference network were determined by the Least Square Meth od and the overall view is attached as Annexes.« less

MOSAIK: a hash-based algorithm for accurate next-generation sequencing short-read mapping.

PubMed

Lee, Wan-Ping; Stromberg, Michael P; Ward, Alistair; Stewart, Chip; Garrison, Erik P; Marth, Gabor T

2014-01-01

MOSAIK is a stable, sensitive and open-source program for mapping second and third-generation sequencing reads to a reference genome. Uniquely among current mapping tools, MOSAIK can align reads generated by all the major sequencing technologies, including Illumina, Applied Biosystems SOLiD, Roche 454, Ion Torrent and Pacific BioSciences SMRT. Indeed, MOSAIK was the only aligner to provide consistent mappings for all the generated data (sequencing technologies, low-coverage and exome) in the 1000 Genomes Project. To provide highly accurate alignments, MOSAIK employs a hash clustering strategy coupled with the Smith-Waterman algorithm. This method is well-suited to capture mismatches as well as short insertions and deletions. To support the growing interest in larger structural variant (SV) discovery, MOSAIK provides explicit support for handling known-sequence SVs, e.g. mobile element insertions (MEIs) as well as generating outputs tailored to aid in SV discovery. All variant discovery benefits from an accurate description of the read placement confidence. To this end, MOSAIK uses a neural-network based training scheme to provide well-calibrated mapping quality scores, demonstrated by a correlation coefficient between MOSAIK assigned and actual mapping qualities greater than 0.98. In order to ensure that studies of any genome are supported, a training pipeline is provided to ensure optimal mapping quality scores for the genome under investigation. MOSAIK is multi-threaded, open source, and incorporated into our command and pipeline launcher system GKNO (http://gkno.me).

MOSAIK: A Hash-Based Algorithm for Accurate Next-Generation Sequencing Short-Read Mapping

PubMed Central

Lee, Wan-Ping; Stromberg, Michael P.; Ward, Alistair; Stewart, Chip; Garrison, Erik P.; Marth, Gabor T.

2014-01-01

MOSAIK is a stable, sensitive and open-source program for mapping second and third-generation sequencing reads to a reference genome. Uniquely among current mapping tools, MOSAIK can align reads generated by all the major sequencing technologies, including Illumina, Applied Biosystems SOLiD, Roche 454, Ion Torrent and Pacific BioSciences SMRT. Indeed, MOSAIK was the only aligner to provide consistent mappings for all the generated data (sequencing technologies, low-coverage and exome) in the 1000 Genomes Project. To provide highly accurate alignments, MOSAIK employs a hash clustering strategy coupled with the Smith-Waterman algorithm. This method is well-suited to capture mismatches as well as short insertions and deletions. To support the growing interest in larger structural variant (SV) discovery, MOSAIK provides explicit support for handling known-sequence SVs, e.g. mobile element insertions (MEIs) as well as generating outputs tailored to aid in SV discovery. All variant discovery benefits from an accurate description of the read placement confidence. To this end, MOSAIK uses a neural-network based training scheme to provide well-calibrated mapping quality scores, demonstrated by a correlation coefficient between MOSAIK assigned and actual mapping qualities greater than 0.98. In order to ensure that studies of any genome are supported, a training pipeline is provided to ensure optimal mapping quality scores for the genome under investigation. MOSAIK is multi-threaded, open source, and incorporated into our command and pipeline launcher system GKNO (http://gkno.me). PMID:24599324

Optimal geometrical design of inertial vibration DC piezoelectric nanogenerators based on obliquely aligned InN nanowire arrays.

PubMed

Ku, Nai-Jen; Liu, Guocheng; Wang, Chao-Hung; Gupta, Kapil; Liao, Wei-Shun; Ban, Dayan; Liu, Chuan-Pu

2017-09-28

Piezoelectric nanogenerators have been investigated to generate electricity from environmental vibrations due to their energy conversion capabilities. In this study, we demonstrate an optimal geometrical design of inertial vibration direct-current piezoelectric nanogenerators based on obliquely aligned InN nanowire (NW) arrays with an optimized oblique angle of ∼58°, and driven by the inertial force of their own weight, using a mechanical shaker without any AC/DC converters. The nanogenerator device manifests potential applications not only as a unique energy harvesting device capable of scavenging energy from weak mechanical vibrations, but also as a sensitive strain sensor. The maximum output power density of the nanogenerator is estimated to be 2.9 nW cm -2 , leading to an improvement of about 3-12 times that of vertically aligned ZnO NW DC nanogenerators. Integration of two nanogenerators also exhibits a linear increase in the output power, offering an enormous potential for the creation of self-powered sustainable nanosystems utilizing incessantly natural ambient energy sources.

Multiple sequence alignment in HTML: colored, possibly hyperlinked, compact representations.

PubMed

Campagne, F; Maigret, B

1998-02-01

Protein sequence alignments are widely used in protein structure prediction, protein engineering, modeling of proteins, etc. This type of representation is useful at different stages of scientific activity: looking at previous results, working on a research project, and presenting the results. There is a need to make it available through a network (intranet or WWW), in a way that allows biologists, chemists, and noncomputer specialists to look at the data and carry on research--possibly in a collaborative research. Previous methods (text-based, Java-based) are reported and their advantages are discussed. We have developed two novel approaches to represent the alignments as colored, hyper-linked HTML pages. The first method creates an HTML page that uses efficiently the image cache mechanism of a WWW browser, thereby allowing the user to browse different alignments without waiting for the images to be loaded through the network, but only for the first viewed alignment. The generated pages can be browsed with any HTML2.0-compliant browser. The second method that we propose uses W3C-CSS1-style sheets to render alignments. This new method generates pages that require recent browsers to be viewed. We implemented these methods in the Viseur program and made a WWW service available that allows a user to convert an MSF alignment file in HTML for WWW publishing. The latter service is available at http:@www.lctn.u-nancy.fr/viseur/services.htm l.

Identity Practices of Multilingual Writers in Social Networking Spaces

ERIC Educational Resources Information Center

Chen, Hsin-I

2013-01-01

This study examines the literacy practices of two multilingual writers in social networking communities. The findings show that the multilingual writers explored and reappropriated symbolic resources afforded by the social networking site as they aligned themselves with particular collective and personal identities at local and global levels.…

Improved, ACMG-Compliant, in silico prediction of pathogenicity for missense substitutions encoded by TP53 variants.

PubMed

Fortuno, Cristina; James, Paul A; Young, Erin L; Feng, Bing; Olivier, Magali; Pesaran, Tina; Tavtigian, Sean V; Spurdle, Amanda B

2018-05-18

Clinical interpretation of germline missense variants represents a major challenge, including those in the TP53 Li-Fraumeni syndrome gene. Bioinformatic prediction is a key part of variant classification strategies. We aimed to optimize the performance of the Align-GVGD tool used for p53 missense variant prediction, and compare its performance to other bioinformatic tools (SIFT, PolyPhen-2) and ensemble methods (REVEL, BayesDel). Reference sets of assumed pathogenic and assumed benign variants were defined using functional and/or clinical data. Area under the curve and Matthews correlation coefficient (MCC) values were used as objective functions to select an optimized protein multi-sequence alignment with best performance for Align-GVGD. MCC comparison of tools using binary categories showed optimized Align-GVGD (C15 cut-off) combined with BayesDel (0.16 cut-off), or with REVEL (0.5 cut-off), to have the best overall performance. Further, a semi-quantitative approach using multiple tiers of bioinformatic prediction, validated using an independent set of non-functional and functional variants, supported use of Align-GVGD and BayesDel prediction for different strength of evidence levels in ACMG/AMP rules. We provide rationale for bioinformatic tool selection for TP53 variant classification, and have also computed relevant bioinformatic predictions for every possible p53 missense variant to facilitate their use by the scientific and medical community. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Simulation-based comprehensive benchmarking of RNA-seq aligners

PubMed Central

Baruzzo, Giacomo; Hayer, Katharina E; Kim, Eun Ji; Di Camillo, Barbara; FitzGerald, Garret A; Grant, Gregory R

2018-01-01

Alignment is the first step in most RNA-seq analysis pipelines, and the accuracy of downstream analyses depends heavily on it. Unlike most steps in the pipeline, alignment is particularly amenable to benchmarking with simulated data. We performed a comprehensive benchmarking of 14 common splice-aware aligners for base, read, and exon junction-level accuracy and compared default with optimized parameters. We found that performance varied by genome complexity, and accuracy and popularity were poorly correlated. The most widely cited tool underperforms for most metrics, particularly when using default settings. PMID:27941783

Fourier-transform and global contrast interferometer alignment methods

DOEpatents

Goldberg, Kenneth A.

2001-01-01

Interferometric methods are presented to facilitate alignment of image-plane components within an interferometer and for the magnified viewing of interferometer masks in situ. Fourier-transforms are performed on intensity patterns that are detected with the interferometer and are used to calculate pseudo-images of the electric field in the image plane of the test optic where the critical alignment of various components is being performed. Fine alignment is aided by the introduction and optimization of a global contrast parameter that is easily calculated from the Fourier-transform.

ASPIC: a novel method to predict the exon-intron structure of a gene that is optimally compatible to a set of transcript sequences.

PubMed

Bonizzoni, Paola; Rizzi, Raffaella; Pesole, Graziano

2005-10-05

Currently available methods to predict splice sites are mainly based on the independent and progressive alignment of transcript data (mostly ESTs) to the genomic sequence. Apart from often being computationally expensive, this approach is vulnerable to several problems--hence the need to develop novel strategies. We propose a method, based on a novel multiple genome-EST alignment algorithm, for the detection of splice sites. To avoid limitations of splice sites prediction (mainly, over-predictions) due to independent single EST alignments to the genomic sequence our approach performs a multiple alignment of transcript data to the genomic sequence based on the combined analysis of all available data. We recast the problem of predicting constitutive and alternative splicing as an optimization problem, where the optimal multiple transcript alignment minimizes the number of exons and hence of splice site observations. We have implemented a splice site predictor based on this algorithm in the software tool ASPIC (Alternative Splicing PredICtion). It is distinguished from other methods based on BLAST-like tools by the incorporation of entirely new ad hoc procedures for accurate and computationally efficient transcript alignment and adopts dynamic programming for the refinement of intron boundaries. ASPIC also provides the minimal set of non-mergeable transcript isoforms compatible with the detected splicing events. The ASPIC web resource is dynamically interconnected with the Ensembl and Unigene databases and also implements an upload facility. Extensive bench marking shows that ASPIC outperforms other existing methods in the detection of novel splicing isoforms and in the minimization of over-predictions. ASPIC also requires a lower computation time for processing a single gene and an EST cluster. The ASPIC web resource is available at http://aspic.algo.disco.unimib.it/aspic-devel/.

Epitaxial growth of aligned AlGalnN nanowires by metal-organic chemical vapor deposition

DOEpatents

Han, Jung; Su, Jie

2008-08-05

Highly ordered and aligned epitaxy of III-Nitride nanowires is demonstrated in this work. <1010> M-axis is identified as a preferential nanowire growth direction through a detailed study of GaN/AlN trunk/branch nanostructures by transmission electron microscopy. Crystallographic selectivity can be used to achieve spatial and orientational control of nanowire growth. Vertically aligned (Al)GaN nanowires are prepared on M-plane AlN substrates. Horizontally ordered nanowires, extending from the M-plane sidewalls of GaN hexagonal mesas or islands demonstrate new opportunities for self-aligned nanowire devices, interconnects, and networks.

An optimization-based approach for high-order accurate discretization of conservation laws with discontinuous solutions

NASA Astrophysics Data System (ADS)

Zahr, M. J.; Persson, P.-O.

2018-07-01

This work introduces a novel discontinuity-tracking framework for resolving discontinuous solutions of conservation laws with high-order numerical discretizations that support inter-element solution discontinuities, such as discontinuous Galerkin or finite volume methods. The proposed method aims to align inter-element boundaries with discontinuities in the solution by deforming the computational mesh. A discontinuity-aligned mesh ensures the discontinuity is represented through inter-element jumps while smooth basis functions interior to elements are only used to approximate smooth regions of the solution, thereby avoiding Gibbs' phenomena that create well-known stability issues. Therefore, very coarse high-order discretizations accurately resolve the piecewise smooth solution throughout the domain, provided the discontinuity is tracked. Central to the proposed discontinuity-tracking framework is a discrete PDE-constrained optimization formulation that simultaneously aligns the computational mesh with discontinuities in the solution and solves the discretized conservation law on this mesh. The optimization objective is taken as a combination of the deviation of the finite-dimensional solution from its element-wise average and a mesh distortion metric to simultaneously penalize Gibbs' phenomena and distorted meshes. It will be shown that our objective function satisfies two critical properties that are required for this discontinuity-tracking framework to be practical: (1) possesses a local minima at a discontinuity-aligned mesh and (2) decreases monotonically to this minimum in a neighborhood of radius approximately h / 2, whereas other popular discontinuity indicators fail to satisfy the latter. Another important contribution of this work is the observation that traditional reduced space PDE-constrained optimization solvers that repeatedly solve the conservation law at various mesh configurations are not viable in this context since severe overshoot and undershoot in the solution, i.e., Gibbs' phenomena, may make it impossible to solve the discrete conservation law on non-aligned meshes. Therefore, we advocate a gradient-based, full space solver where the mesh and conservation law solution converge to their optimal values simultaneously and therefore never require the solution of the discrete conservation law on a non-aligned mesh. The merit of the proposed method is demonstrated on a number of one- and two-dimensional model problems including the L2 projection of discontinuous functions, Burgers' equation with a discontinuous source term, transonic flow through a nozzle, and supersonic flow around a bluff body. We demonstrate optimal O (h p + 1) convergence rates in the L1 norm for up to polynomial order p = 6 and show that accurate solutions can be obtained on extremely coarse meshes.

Mechanical alignment of particles for use in fabricating superconducting and permanent magnetic materials

DOEpatents

Nellis, William J.; Maple, M. Brian

1992-01-01

A method for mechanically aligning oriented superconducting or permanently magnetic materials for further processing into constructs. This pretreatment optimizes the final crystallographic orientation and, thus, properties in these constructs. Such materials as superconducting fibers, needles and platelets are utilized.

Studies on in situ magnetic alignment of bonded anisotropic Nd-Fe-B alloy powders

DOE PAGES

Nlebedim, I. C.; Ucar, Huseyin; Hatter, Christine B.; ...

2016-08-30

We presented some considerations for achieving high degree of alignment in polymer bonded permanent magnets via the results of a study on in situ magnetic alignment of anisotropic Nd-Fe-B magnet powders. Contributions from effect of the alignment temperature, alignment magnetic field and the properties of the polymer on the hard magnetic properties of the bonded magnet were considered. Moreover, the thermo-rheological properties of the polymer and the response of the magnet powders to the applied magnetic field indicate that hard magnetic properties were optimized at an alignment temperature just above the melting temperature of the EVA co-polymer. This agrees withmore » an observed correlation between the change in magnetization due to improved magnetic alignment of the anisotropic powders and the change in viscosity of the binder. Finally, manufacturing cost can be minimized by identifying optimum alignment temperatures and magnetic field strengths.« less

Studies on in situ magnetic alignment of bonded anisotropic Nd-Fe-B alloy powders

NASA Astrophysics Data System (ADS)

Nlebedim, I. C.; Ucar, Huseyin; Hatter, Christine B.; McCallum, R. W.; McCall, Scott K.; Kramer, M. J.; Paranthaman, M. Parans

2017-01-01

Considerations for achieving high degree of alignment in polymer bonded permanent magnets are presented via the results of a study on in situ magnetic alignment of anisotropic Nd-Fe-B magnet powders. Contributions from effect of the alignment temperature, alignment magnetic field and the properties of the polymer on the hard magnetic properties of the bonded magnet were considered. The thermo-rheological properties of the polymer and the response of the magnet powders to the applied magnetic field indicate that hard magnetic properties were optimized at an alignment temperature just above the melting temperature of the EVA co-polymer. This agrees with an observed correlation between the change in magnetization due to improved magnetic alignment of the anisotropic powders and the change in viscosity of the binder. Manufacturing cost can be minimized by identifying optimum alignment temperatures and magnetic field strengths.

Parasail: SIMD C library for global, semi-global, and local pairwise sequence alignments.

PubMed

Daily, Jeff

2016-02-10

Sequence alignment algorithms are a key component of many bioinformatics applications. Though various fast Smith-Waterman local sequence alignment implementations have been developed for x86 CPUs, most are embedded into larger database search tools. In addition, fast implementations of Needleman-Wunsch global sequence alignment and its semi-global variants are not as widespread. This article presents the first software library for local, global, and semi-global pairwise intra-sequence alignments and improves the performance of previous intra-sequence implementations. A faster intra-sequence local pairwise alignment implementation is described and benchmarked, including new global and semi-global variants. Using a 375 residue query sequence a speed of 136 billion cell updates per second (GCUPS) was achieved on a dual Intel Xeon E5-2670 24-core processor system, the highest reported for an implementation based on Farrar's 'striped' approach. Rognes's SWIPE optimal database search application is still generally the fastest available at 1.2 to at best 2.4 times faster than Parasail for sequences shorter than 500 amino acids. However, Parasail was faster for longer sequences. For global alignments, Parasail's prefix scan implementation is generally the fastest, faster even than Farrar's 'striped' approach, however the opal library is faster for single-threaded applications. The software library is designed for 64 bit Linux, OS X, or Windows on processors with SSE2, SSE41, or AVX2. Source code is available from https://github.com/jeffdaily/parasail under the Battelle BSD-style license. Applications that require optimal alignment scores could benefit from the improved performance. For the first time, SIMD global, semi-global, and local alignments are available in a stand-alone C library.

A three-dimensional microelectrode array composed of vertically aligned ultra-dense carbon nanotube networks

NASA Astrophysics Data System (ADS)

Nick, C.; Yadav, S.; Joshi, R.; Schneider, J. J.; Thielemann, C.

2015-07-01

Electrodes based on carbon nanotubes are a promising approach to manufacture highly sensitive sensors with a low limit of signal detection and a high signal-to-noise ratio. This is achieved by dramatically increasing the electrochemical active surface area without increasing the overall geometrical dimensions. Typically, carbon nanotube electrodes are nearly planar and composed of randomly distributed carbon nanotube networks having a limited surface gain for a specific geometrical surface area. To overcome this limitation, we have introduced vertically aligned carbon nanotube (VACNT) networks as electrodes, which are arranged in a microelectrode pattern of 60 single electrodes. Each microelectrode features a very high aspect ratio of more than 300 and thus a dramatically increased surface area. These microelectrodes composed of VACNT networks display dramatically decreased impedance over the entire frequency range compared to planar microelectrodes caused by the enormous capacity increase. This is experimentally verified by electrochemical impedance spectroscopy and cyclic voltammetry.

Mesoporous Li4Ti5O12 nanoclusters anchored on super-aligned carbon nanotubes as high performance electrodes for lithium ion batteries.

PubMed

Sun, Li; Kong, Weibang; Wu, Hengcai; Wu, Yang; Wang, Datao; Zhao, Fei; Jiang, Kaili; Li, Qunqing; Wang, Jiaping; Fan, Shoushan

2016-01-07

Mesoporous lithium titanate (LTO) nanoclusters are in situ synthesized in a network of super aligned carbon nanotubes (SACNTs) via a solution-based method followed by heat treatment in air. In the LTO-CNT composite, SACNTs not only serve as the skeleton to support a binder-free electrode, but also render the composite with high conductivity, flexibility, and mechanical strength. The homogeneously dispersed LTO nanoclusters among the SACNTs allow each LTO grain to effectively access the electrolyte and the conductive network, benefiting both ion and electron transport. By the incorporation of LTO into the CNT network, mechanical reinforcement is also achieved. When serving as a negative electrode for lithium ion batteries, such a robust composite-network architecture provides the electrodes with effective charge transport and structural integrity, leading to high-performance flexible electrodes with high capacity, high rate capability, and excellent cycling stability.

Accelerated reliability testing of highly aligned single-walled carbon nanotube networks subjected to DC electrical stressing.

PubMed

Strus, Mark C; Chiaramonti, Ann N; Kim, Young Lae; Jung, Yung Joon; Keller, Robert R

2011-07-01

We investigate the electrical reliability of nanoscale lines of highly aligned, networked, metallic/semiconducting single-walled carbon nanotubes (SWCNTs) fabricated through a template-based fluidic assembly process. We find that these SWCNT networks can withstand DC current densities larger than 10 MA cm(-2) for several hours and, in some cases, several days. We develop test methods that show that the degradation rate, failure predictability and total device lifetime can be linked to the initial resistance. Scanning electron and transmission electron microscopy suggest that fabrication variability plays a critical role in the rate of degradation, and we offer an empirical method of quickly determining the long-term performance of a network. We find that well-fabricated lines subject to constant electrical stress show a linear accumulation of damage reminiscent of electromigration in metallic interconnects, and we explore the underlying physical mechanisms that could cause such behavior.

Optimal topologies for maximizing network transmission capacity

NASA Astrophysics Data System (ADS)

Chen, Zhenhao; Wu, Jiajing; Rong, Zhihai; Tse, Chi K.

2018-04-01

It has been widely demonstrated that the structure of a network is a major factor that affects its traffic dynamics. In this work, we try to identify the optimal topologies for maximizing the network transmission capacity, as well as to build a clear relationship between structural features of a network and the transmission performance in terms of traffic delivery. We propose an approach for designing optimal network topologies against traffic congestion by link rewiring and apply them on the Barabási-Albert scale-free, static scale-free and Internet Autonomous System-level networks. Furthermore, we analyze the optimized networks using complex network parameters that characterize the structure of networks, and our simulation results suggest that an optimal network for traffic transmission is more likely to have a core-periphery structure. However, assortative mixing and the rich-club phenomenon may have negative impacts on network performance. Based on the observations of the optimized networks, we propose an efficient method to improve the transmission capacity of large-scale networks.

Magnetic field design for selecting and aligning immunomagnetic labeled cells.

PubMed

Tibbe, Arjan G J; de Grooth, Bart G; Greve, Jan; Dolan, Gerald J; Rao, Chandra; Terstappen, Leon W M M

2002-03-01

Recently we introduced the CellTracks cell analysis system, in which samples are prepared based on a combination of immunomagnetic selection, separation, and alignment of cells along ferromagnetic lines. Here we describe the underlying magnetic principles and considerations made in the magnetic field design to achieve the best possible cell selection and alignment of magnetically labeled cells. Materials and Methods Computer simulations, in combination with experimental data, were used to optimize the design of the magnets and Ni lines to obtain the optimal magnetic configuration. A homogeneous cell distribution on the upper surface of the sample chamber was obtained with a magnet where the pole faces were tilted towards each other. The spatial distribution of magnetically aligned objects in between the Ni lines was dependent on the ratio of the diameter of the aligned object and the line spacing, which was tested with magnetically and fluorescently labeled 6 microm polystyrene beads. The best result was obtained when the line spacing was equal to or smaller than the diameter of the aligned object. The magnetic gradient of the designed permanent magnet extracts magnetically labeled cells from any cell suspension to a desired plane, providing a homogeneous cell distribution. In addition, it magnetizes ferro-magnetic Ni lines in this plane whose additional local gradient adds to the gradient of the permanent magnet. The resultant gradient aligns the magnetically labeled cells first brought to this plane. This combination makes it possible, in a single step, to extract and align cells on a surface from any cell suspension. Copyright 2002 Wiley-Liss, Inc.

Overcoming low-alignment signal contrast induced alignment failure by alignment signal enhancement

NASA Astrophysics Data System (ADS)

Lee, Byeong Soo; Kim, Young Ha; Hwang, Hyunwoo; Lee, Jeongjin; Kong, Jeong Heung; Kang, Young Seog; Paarhuis, Bart; Kok, Haico; de Graaf, Roelof; Weichselbaum, Stefan; Droste, Richard; Mason, Christopher; Aarts, Igor; de Boeij, Wim P.

2016-03-01

Overlay is one of the key factors which enables optical lithography extension to 1X node DRAM manufacturing. It is natural that accurate wafer alignment is a prerequisite for good device overlay. However, alignment failures or misalignments are commonly observed in a fab. There are many factors which could induce alignment problems. Low alignment signal contrast is one of the main issues. Alignment signal contrast can be degraded by opaque stack materials or by alignment mark degradation due to processes like CMP. This issue can be compounded by mark sub-segmentation from design rules in combination with double or quadruple spacer process. Alignment signal contrast can be improved by applying new material or process optimization, which sometimes lead to the addition of another process-step with higher costs. If we can amplify the signal components containing the position information and reduce other unwanted signal and background contributions then we can improve alignment performance without process change. In this paper we use ASML's new alignment sensor (as was introduced and released on the NXT:1980Di) and sample wafers with special stacks which can induce poor alignment signal to demonstrate alignment and overlay improvement.

Multiple nodes transfer alignment for airborne missiles based on inertial sensor network

NASA Astrophysics Data System (ADS)

Si, Fan; Zhao, Yan

2017-09-01

Transfer alignment is an important initialization method for airborne missiles because the alignment accuracy largely determines the performance of the missile. However, traditional alignment methods are limited by complicated and unknown flexure angle, and cannot meet the actual requirement when wing flexure deformation occurs. To address this problem, we propose a new method that uses the relative navigation parameters between the weapons and fighter to achieve transfer alignment. First, in the relative inertial navigation algorithm, the relative attitudes and positions are constantly computed in wing flexure deformation situations. Secondly, the alignment results of each weapon are processed using a data fusion algorithm to improve the overall performance. Finally, the feasibility and performance of the proposed method were evaluated under two typical types of deformation, and the simulation results demonstrated that the new transfer alignment method is practical and has high-precision.

Energy level alignment at molecule-metal interfaces from an optimally tuned range-separated hybrid functional

DOE PAGES

Liu, Zhen-Fei; Egger, David A.; Refaely-Abramson, Sivan; ...

2017-02-21

The alignment of the frontier orbital energies of an adsorbed molecule with the substrate Fermi level at metal-organic interfaces is a fundamental observable of significant practical importance in nanoscience and beyond. Typical density functional theory calculations, especially those using local and semi-local functionals, often underestimate level alignment leading to inaccurate electronic structure and charge transport properties. Here, we develop a new fully self-consistent predictive scheme to accurately compute level alignment at certain classes of complex heterogeneous molecule-metal interfaces based on optimally tuned range-separated hybrid functionals. Starting from a highly accurate description of the gas-phase electronic structure, our method by constructionmore » captures important nonlocal surface polarization effects via tuning of the long-range screened exchange in a range-separated hybrid in a non-empirical and system-specific manner. We implement this functional in a plane-wave code and apply it to several physisorbed and chemisorbed molecule-metal interface systems. Our results are in quantitative agreement with experiments, the both the level alignment and work function changes. This approach constitutes a new practical scheme for accurate and efficient calculations of the electronic structure of molecule-metal interfaces.« less

Energy level alignment at molecule-metal interfaces from an optimally tuned range-separated hybrid functional

NASA Astrophysics Data System (ADS)

Liu, Zhen-Fei; Egger, David A.; Refaely-Abramson, Sivan; Kronik, Leeor; Neaton, Jeffrey B.

2017-03-01

The alignment of the frontier orbital energies of an adsorbed molecule with the substrate Fermi level at metal-organic interfaces is a fundamental observable of significant practical importance in nanoscience and beyond. Typical density functional theory calculations, especially those using local and semi-local functionals, often underestimate level alignment leading to inaccurate electronic structure and charge transport properties. In this work, we develop a new fully self-consistent predictive scheme to accurately compute level alignment at certain classes of complex heterogeneous molecule-metal interfaces based on optimally tuned range-separated hybrid functionals. Starting from a highly accurate description of the gas-phase electronic structure, our method by construction captures important nonlocal surface polarization effects via tuning of the long-range screened exchange in a range-separated hybrid in a non-empirical and system-specific manner. We implement this functional in a plane-wave code and apply it to several physisorbed and chemisorbed molecule-metal interface systems. Our results are in quantitative agreement with experiments, the both the level alignment and work function changes. Our approach constitutes a new practical scheme for accurate and efficient calculations of the electronic structure of molecule-metal interfaces.

ENTEL: A Case Study on Knowledge Networks and the Impact of Web 2.0 Technologies

ERIC Educational Resources Information Center

Griffiths, Paul; Arenas, Teresita

2014-01-01

This study re-visits an organisation that defined its knowledge-management strategy in 2008-9 applying an established strategy-intellectual capital alignment framework. It addresses questions "How has knowledge management evolved at ENTEL, and what lessons can be learnt? Does the strategy-knowledge management alignment framework applied at…

Electric-Field-Directed Parallel Alignment Architecting 3D Lithium-Ion Pathways within Solid Composite Electrolyte.

PubMed

Liu, Xueqing; Peng, Sha; Gao, Shuyu; Cao, Yuancheng; You, Qingliang; Zhou, Liyong; Jin, Yongcheng; Liu, Zhihong; Liu, Jiyan

2018-05-09

It is of great significance to seek high-performance solid electrolytes via a facile chemistry and simple process for meeting the requirements of solid batteries. Previous reports revealed that ion conducting pathways within ceramic-polymer composite electrolytes mainly occur at ceramic particles and the ceramic-polymer interface. Herein, one facile strategy toward ceramic particles' alignment and assembly induced by an external alternating-current (AC) electric field is presented. It was manifested by an in situ optical microscope that Li 1.3 Al 0.3 Ti 1.7 (PO 4 ) 3 particles and poly(ethylene glycol) diacrylate in poly(dimethylsiloxane) (LATP@PEGDA@PDMS) assembled into three-dimensional connected networks on applying an external AC electric field. Scanning electron microscopy revealed that the ceramic LATP particles aligned into a necklacelike assembly. Electrochemical impedance spectroscopy confirmed that the ionic conductivity of this necklacelike alignment was significantly enhanced compared to that of the random one. It was demonstrated that this facile strategy of applying an AC electric field can be a very effective approach for architecting three-dimensional lithium-ion conductive networks within solid composite electrolyte.

Relation between film character and wafer alignment: critical alignment issues on HV device for VLSI manufacturing

NASA Astrophysics Data System (ADS)

Lo, Yi-Chuan; Lee, Chih-Hsiung; Lin, Hsun-Peng; Peng, Chiou-Shian

1998-06-01

Several continuous splits for wafer alignment target topography conditions to improve epitaxy film alignment were applied. The alignment evaluation among former layer pad oxide thickness (250 angstrom - 500 angstrom), drive oxide thickness (6000 angstrom - 10000 angstrom), nitride film thickness (600 angstrom - 1500 angstrom), initial oxide etch (fully wet etch, fully dry etch and dry plus wet etch) will be split to this experiment. Also various epitaxy deposition recipe such as: epitaxy source (SiHCl2 or SiCHCl3) and growth rate (1.3 micrometer/min approximately 2.0 micrometer/min) will be used to optimize the process window for alignment issue. All the reflectance signal and cross section photography of alignment target during NIKON stepper alignment process will be examined. Experimental results show epitaxy recipe plays an important role to wafer alignment. Low growth rate with good performance conformity epitaxy lead to alignment target avoid washout, pattern shift and distortion. All the results (signal monitor and film character) combined with NIKON's stepper standard laser scanning alignment system will be discussed in this paper.

Optimal cost design of water distribution networks using a decomposition approach

NASA Astrophysics Data System (ADS)

Lee, Ho Min; Yoo, Do Guen; Sadollah, Ali; Kim, Joong Hoon

2016-12-01

Water distribution network decomposition, which is an engineering approach, is adopted to increase the efficiency of obtaining the optimal cost design of a water distribution network using an optimization algorithm. This study applied the source tracing tool in EPANET, which is a hydraulic and water quality analysis model, to the decomposition of a network to improve the efficiency of the optimal design process. The proposed approach was tested by carrying out the optimal cost design of two water distribution networks, and the results were compared with other optimal cost designs derived from previously proposed optimization algorithms. The proposed decomposition approach using the source tracing technique enables the efficient decomposition of an actual large-scale network, and the results can be combined with the optimal cost design process using an optimization algorithm. This proves that the final design in this study is better than those obtained with other previously proposed optimization algorithms.

A generalized global alignment algorithm.

PubMed

Huang, Xiaoqiu; Chao, Kun-Mao

2003-01-22

Homologous sequences are sometimes similar over some regions but different over other regions. Homologous sequences have a much lower global similarity if the different regions are much longer than the similar regions. We present a generalized global alignment algorithm for comparing sequences with intermittent similarities, an ordered list of similar regions separated by different regions. A generalized global alignment model is defined to handle sequences with intermittent similarities. A dynamic programming algorithm is designed to compute an optimal general alignment in time proportional to the product of sequence lengths and in space proportional to the sum of sequence lengths. The algorithm is implemented as a computer program named GAP3 (Global Alignment Program Version 3). The generalized global alignment model is validated by experimental results produced with GAP3 on both DNA and protein sequences. The GAP3 program extends the ability of standard global alignment programs to recognize homologous sequences of lower similarity. The GAP3 program is freely available for academic use at http://bioinformatics.iastate.edu/aat/align/align.html.

UMTS rapid response real-time seismic networks: implementation and strategies at INGV

NASA Astrophysics Data System (ADS)

Govoni, Aladino; Margheriti, Lucia; Moretti, Milena; Lauciani, Valentino; Sensale, Gianpaolo; Bucci, Augusto; Criscuoli, Fabio

2015-04-01

The benefits of portable real-time seismic networks are several and well known. During the management of a temporary experiment from the real-time data it is possible to detect and fix rapidly problems with power supply, time synchronization, disk failures and, most important, seismic signal quality degradation due to unexpected noise sources or sensor alignment/tampering. This usually minimizes field maintenance trips and maximizes both the quantity and the quality of the acquired data. When the area of the temporary experiment is not well monitored by the local permanent network, the real-time data from the temporary experiment can be fed to the permanent network monitoring system improving greatly both the real-time hypocentral locations and the final revised bulletin. All these benefits apply also in case of seismic crises when rapid deployment stations can significantly contribute to the aftershock analysis. Nowadays data transmission using meshed radio networks or satellite systems is not a big technological problem for a permanent seismic network where each site is optimized for the device power consumption and is usually installed by properly specialized technicians that can configure transmission devices and align antennas. This is not usually practical for temporary networks and especially for rapid response networks where the installation time is the main concern. These difficulties are substantially lowered using the now widespread UMTS technology for data transmission. A small (but sometimes power hungry) properly configured device with an omnidirectional antenna must be added to the station assembly. All setups are usually configured before deployment and this allows for an easy installation also by untrained personnel. We describe here the implementation of a UMTS based portable seismic network for both temporary experiments and rapid response applications developed at INGV. The first field experimentation of this approach dates back to the 2009 L'Aquila aftershock sequence and since then it has been customized and refined to overcome most reliability and security issues using an industry standard VPN architecture that allows to avoid UMTS provider firewall problems and does not expose to the Internet the usually weak and attack prone data acquisition ports. With this approach all the devices are protected inside a local network and the only exposed port is the VPN server one. This solution improves both the security and the bandwidth available to data transmission. While most of the experimentation has been carried out using the RefTek units of the INGV Mobile Network this solution applies equally well to most seismic data loggers available on the market. Overall the UMTS data transmission has been used in most temporary seismic experiments and in all seismic emergencies happened in Italy since 2010 and has proved to be a very cost effective approach with real-time data acquisition rates usually greater than 97% and all the benefits that result from the fast integration of the temporary data in the National Network monitoring system and in the EIDA data bank.

A method of network topology optimization design considering application process characteristic

NASA Astrophysics Data System (ADS)

Wang, Chunlin; Huang, Ning; Bai, Yanan; Zhang, Shuo

2018-03-01

Communication networks are designed to meet the usage requirements of users for various network applications. The current studies of network topology optimization design mainly considered network traffic, which is the result of network application operation, but not a design element of communication networks. A network application is a procedure of the usage of services by users with some demanded performance requirements, and has obvious process characteristic. In this paper, we first propose a method to optimize the design of communication network topology considering the application process characteristic. Taking the minimum network delay as objective, and the cost of network design and network connective reliability as constraints, an optimization model of network topology design is formulated, and the optimal solution of network topology design is searched by Genetic Algorithm (GA). Furthermore, we investigate the influence of network topology parameter on network delay under the background of multiple process-oriented applications, which can guide the generation of initial population and then improve the efficiency of GA. Numerical simulations show the effectiveness and validity of our proposed method. Network topology optimization design considering applications can improve the reliability of applications, and provide guidance for network builders in the early stage of network design, which is of great significance in engineering practices.

Mathematical model of highways network optimization

NASA Astrophysics Data System (ADS)

Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.

2017-12-01

The article deals with the issue of highways network design. Studies show that the main requirement from road transport for the road network is to ensure the realization of all the transport links served by it, with the least possible cost. The goal of optimizing the network of highways is to increase the efficiency of transport. It is necessary to take into account a large number of factors that make it difficult to quantify and qualify their impact on the road network. In this paper, we propose building an optimal variant for locating the road network on the basis of a mathematical model. The article defines the criteria for optimality and objective functions that reflect the requirements for the road network. The most fully satisfying condition for optimality is the minimization of road and transport costs. We adopted this indicator as a criterion of optimality in the economic-mathematical model of a network of highways. Studies have shown that each offset point in the optimal binding road network is associated with all other corresponding points in the directions providing the least financial costs necessary to move passengers and cargo from this point to the other corresponding points. The article presents general principles for constructing an optimal network of roads.

Functional annotation by sequence-weighted structure alignments: statistical analysis and case studies from the Protein 3000 structural genomics project in Japan.

PubMed

Standley, Daron M; Toh, Hiroyuki; Nakamura, Haruki

2008-09-01

A method to functionally annotate structural genomics targets, based on a novel structural alignment scoring function, is proposed. In the proposed score, position-specific scoring matrices are used to weight structurally aligned residue pairs to highlight evolutionarily conserved motifs. The functional form of the score is first optimized for discriminating domains belonging to the same Pfam family from domains belonging to different families but the same CATH or SCOP superfamily. In the optimization stage, we consider four standard weighting functions as well as our own, the "maximum substitution probability," and combinations of these functions. The optimized score achieves an area of 0.87 under the receiver-operating characteristic curve with respect to identifying Pfam families within a sequence-unique benchmark set of domain pairs. Confidence measures are then derived from the benchmark distribution of true-positive scores. The alignment method is next applied to the task of functionally annotating 230 query proteins released to the public as part of the Protein 3000 structural genomics project in Japan. Of these queries, 78 were found to align to templates with the same Pfam family as the query or had sequence identities > or = 30%. Another 49 queries were found to match more distantly related templates. Within this group, the template predicted by our method to be the closest functional relative was often not the most structurally similar. Several nontrivial cases are discussed in detail. Finally, 103 queries matched templates at the fold level, but not the family or superfamily level, and remain functionally uncharacterized. 2008 Wiley-Liss, Inc.

Practical synchronization on complex dynamical networks via optimal pinning control

NASA Astrophysics Data System (ADS)

Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu

2015-07-01

We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.

Optimal river monitoring network using optimal partition analysis: a case study of Hun River, Northeast China.

PubMed

Wang, Hui; Liu, Chunyue; Rong, Luge; Wang, Xiaoxu; Sun, Lina; Luo, Qing; Wu, Hao

2018-01-09

River monitoring networks play an important role in water environmental management and assessment, and it is critical to develop an appropriate method to optimize the monitoring network. In this study, an effective method was proposed based on the attainment rate of National Grade III water quality, optimal partition analysis and Euclidean distance, and Hun River was taken as a method validation case. There were 7 sampling sites in the monitoring network of the Hun River, and 17 monitoring items were analyzed once a month during January 2009 to December 2010. The results showed that the main monitoring items in the surface water of Hun River were ammonia nitrogen (NH 4 + -N), chemical oxygen demand, and biochemical oxygen demand. After optimization, the required number of monitoring sites was reduced from seven to three, and 57% of the cost was saved. In addition, there were no significant differences between non-optimized and optimized monitoring networks, and the optimized monitoring networks could correctly represent the original monitoring network. The duplicate setting degree of monitoring sites decreased after optimization, and the rationality of the monitoring network was improved. Therefore, the optimal method was identified as feasible, efficient, and economic.

Accelerating large-scale protein structure alignments with graphics processing units

PubMed Central

2012-01-01

Background Large-scale protein structure alignment, an indispensable tool to structural bioinformatics, poses a tremendous challenge on computational resources. To ensure structure alignment accuracy and efficiency, efforts have been made to parallelize traditional alignment algorithms in grid environments. However, these solutions are costly and of limited accessibility. Others trade alignment quality for speedup by using high-level characteristics of structure fragments for structure comparisons. Findings We present ppsAlign, a parallel protein structure Alignment framework designed and optimized to exploit the parallelism of Graphics Processing Units (GPUs). As a general-purpose GPU platform, ppsAlign could take many concurrent methods, such as TM-align and Fr-TM-align, into the parallelized algorithm design. We evaluated ppsAlign on an NVIDIA Tesla C2050 GPU card, and compared it with existing software solutions running on an AMD dual-core CPU. We observed a 36-fold speedup over TM-align, a 65-fold speedup over Fr-TM-align, and a 40-fold speedup over MAMMOTH. Conclusions ppsAlign is a high-performance protein structure alignment tool designed to tackle the computational complexity issues from protein structural data. The solution presented in this paper allows large-scale structure comparisons to be performed using massive parallel computing power of GPU. PMID:22357132

AlignMe—a membrane protein sequence alignment web server

PubMed Central

Stamm, Marcus; Staritzbichler, René; Khafizov, Kamil; Forrest, Lucy R.

2014-01-01

We present a web server for pair-wise alignment of membrane protein sequences, using the program AlignMe. The server makes available two operational modes of AlignMe: (i) sequence to sequence alignment, taking two sequences in fasta format as input, combining information about each sequence from multiple sources and producing a pair-wise alignment (PW mode); and (ii) alignment of two multiple sequence alignments to create family-averaged hydropathy profile alignments (HP mode). For the PW sequence alignment mode, four different optimized parameter sets are provided, each suited to pairs of sequences with a specific similarity level. These settings utilize different types of inputs: (position-specific) substitution matrices, secondary structure predictions and transmembrane propensities from transmembrane predictions or hydrophobicity scales. In the second (HP) mode, each input multiple sequence alignment is converted into a hydrophobicity profile averaged over the provided set of sequence homologs; the two profiles are then aligned. The HP mode enables qualitative comparison of transmembrane topologies (and therefore potentially of 3D folds) of two membrane proteins, which can be useful if the proteins have low sequence similarity. In summary, the AlignMe web server provides user-friendly access to a set of tools for analysis and comparison of membrane protein sequences. Access is available at http://www.bioinfo.mpg.de/AlignMe PMID:24753425

Optimal Alignment of Structures for Finite and Periodic Systems.

PubMed

Griffiths, Matthew; Niblett, Samuel P; Wales, David J

2017-10-10

Finding the optimal alignment between two structures is important for identifying the minimum root-mean-square distance (RMSD) between them and as a starting point for calculating pathways. Most current algorithms for aligning structures are stochastic, scale exponentially with the size of structure, and the performance can be unreliable. We present two complementary methods for aligning structures corresponding to isolated clusters of atoms and to condensed matter described by a periodic cubic supercell. The first method (Go-PERMDIST), a branch and bound algorithm, locates the global minimum RMSD deterministically in polynomial time. The run time increases for larger RMSDs. The second method (FASTOVERLAP) is a heuristic algorithm that aligns structures by finding the global maximum kernel correlation between them using fast Fourier transforms (FFTs) and fast SO(3) transforms (SOFTs). For periodic systems, FASTOVERLAP scales with the square of the number of identical atoms in the system, reliably finds the best alignment between structures that are not too distant, and shows significantly better performance than existing algorithms. The expected run time for Go-PERMDIST is longer than FASTOVERLAP for periodic systems. For finite clusters, the FASTOVERLAP algorithm is competitive with existing algorithms. The expected run time for Go-PERMDIST to find the global RMSD between two structures deterministically is generally longer than for existing stochastic algorithms. However, with an earlier exit condition, Go-PERMDIST exhibits similar or better performance.

Approximate matching of regular expressions.

PubMed

Myers, E W; Miller, W

1989-01-01

Given a sequence A and regular expression R, the approximate regular expression matching problem is to find a sequence matching R whose optimal alignment with A is the highest scoring of all such sequences. This paper develops an algorithm to solve the problem in time O(MN), where M and N are the lengths of A and R. Thus, the time requirement is asymptotically no worse than for the simpler problem of aligning two fixed sequences. Our method is superior to an earlier algorithm by Wagner and Seiferas in several ways. First, it treats real-valued costs, in addition to integer costs, with no loss of asymptotic efficiency. Second, it requires only O(N) space to deliver just the score of the best alignment. Finally, its structure permits implementation techniques that make it extremely fast in practice. We extend the method to accommodate gap penalties, as required for typical applications in molecular biology, and further refine it to search for sub-strings of A that strongly align with a sequence in R, as required for typical data base searches. We also show how to deliver an optimal alignment between A and R in only O(N + log M) space using O(MN log M) time. Finally, an O(MN(M + N) + N2log N) time algorithm is presented for alignment scoring schemes where the cost of a gap is an arbitrary increasing function of its length.

Electrospinning fundamentals: optimizing solution and apparatus parameters.

PubMed

Leach, Michelle K; Feng, Zhang-Qi; Tuck, Samuel J; Corey, Joseph M

2011-01-21

Electrospun nanofiber scaffolds have been shown to accelerate the maturation, improve the growth, and direct the migration of cells in vitro. Electrospinning is a process in which a charged polymer jet is collected on a grounded collector; a rapidly rotating collector results in aligned nanofibers while stationary collectors result in randomly oriented fiber mats. The polymer jet is formed when an applied electrostatic charge overcomes the surface tension of the solution. There is a minimum concentration for a given polymer, termed the critical entanglement concentration, below which a stable jet cannot be achieved and no nanofibers will form - although nanoparticles may be achieved (electrospray). A stable jet has two domains, a streaming segment and a whipping segment. While the whipping jet is usually invisible to the naked eye, the streaming segment is often visible under appropriate lighting conditions. Observing the length, thickness, consistency and movement of the stream is useful to predict the alignment and morphology of the nanofibers being formed. A short, non-uniform, inconsistent, and/or oscillating stream is indicative of a variety of problems, including poor fiber alignment, beading, splattering, and curlicue or wavy patterns. The stream can be optimized by adjusting the composition of the solution and the configuration of the electrospinning apparatus, thus optimizing the alignment and morphology of the fibers being produced. In this protocol, we present a procedure for setting up a basic electrospinning apparatus, empirically approximating the critical entanglement concentration of a polymer solution and optimizing the electrospinning process. In addition, we discuss some common problems and troubleshooting techniques.

Exploring the Genomic Roadmap and Molecular Phylogenetics Associated with MODY Cascades Using Computational Biology.

PubMed

Chakraborty, Chiranjib; Bandyopadhyay, Sanghamitra; Doss, C George Priya; Agoramoorthy, Govindasamy

2015-04-01

Maturity onset diabetes of the young (MODY) is a metabolic and genetic disorder. It is different from type 1 and type 2 diabetes with low occurrence level (1-2%) among all diabetes. This disorder is a consequence of β-cell dysfunction. Till date, 11 subtypes of MODY have been identified, and all of them can cause gene mutations. However, very little is known about the gene mapping, molecular phylogenetics, and co-expression among MODY genes and networking between cascades. This study has used latest servers and software such as VarioWatch, ClustalW, MUSCLE, G Blocks, Phylogeny.fr, iTOL, WebLogo, STRING, and KEGG PATHWAY to perform comprehensive analyses of gene mapping, multiple sequences alignment, molecular phylogenetics, protein-protein network design, co-expression analysis of MODY genes, and pathway development. The MODY genes are located in chromosomes-2, 7, 8, 9, 11, 12, 13, 17, and 20. Highly aligned block shows Pro, Gly, Leu, Arg, and Pro residues are highly aligned in the positions of 296, 386, 437, 455, 456 and 598, respectively. Alignment scores inform us that HNF1A and HNF1B proteins have shown high sequence similarity among MODY proteins. Protein-protein network design shows that HNF1A, HNF1B, HNF4A, NEUROD1, PDX1, PAX4, INS, and GCK are strongly connected, and the co-expression analyses between MODY genes also show distinct association between HNF1A and HNF4A genes. This study has used latest tools of bioinformatics to develop a rapid method to assess the evolutionary relationship, the network development, and the associations among eleven MODY genes and cascades. The prediction of sequence conservation, molecular phylogenetics, protein-protein network and the association between the MODY cascades enhances opportunities to get more insights into the less-known MODY disease.

Memory-efficient dynamic programming backtrace and pairwise local sequence alignment.

PubMed

Newberg, Lee A

2008-08-15

A backtrace through a dynamic programming algorithm's intermediate results in search of an optimal path, or to sample paths according to an implied probability distribution, or as the second stage of a forward-backward algorithm, is a task of fundamental importance in computational biology. When there is insufficient space to store all intermediate results in high-speed memory (e.g. cache) existing approaches store selected stages of the computation, and recompute missing values from these checkpoints on an as-needed basis. Here we present an optimal checkpointing strategy, and demonstrate its utility with pairwise local sequence alignment of sequences of length 10,000. Sample C++-code for optimal backtrace is available in the Supplementary Materials. Supplementary data is available at Bioinformatics online.

Rapid Quantification of 3D Collagen Fiber Alignment and Fiber Intersection Correlations with High Sensitivity

PubMed Central

Sun, Meng; Bloom, Alexander B.; Zaman, Muhammad H.

2015-01-01

Metastatic cancers aggressively reorganize collagen in their microenvironment. For example, radially orientated collagen fibers have been observed surrounding tumor cell clusters in vivo. The degree of fiber alignment, as a consequence of this remodeling, has often been difficult to quantify. In this paper, we present an easy to implement algorithm for accurate detection of collagen fiber orientation in a rapid pixel-wise manner. This algorithm quantifies the alignment of both computer generated and actual collagen fiber networks of varying degrees of alignment within 5°°. We also present an alternative easy method to calculate the alignment index directly from the standard deviation of fiber orientation. Using this quantitative method for determining collagen alignment, we demonstrate that the number of collagen fiber intersections has a negative correlation with the degree of fiber alignment. This decrease in intersections of aligned fibers could explain why cells move more rapidly along aligned fibers than unaligned fibers, as previously reported. Overall, our paper provides an easier, more quantitative and quicker way to quantify fiber orientation and alignment, and presents a platform in studying effects of matrix and cellular properties on fiber alignment in complex 3D environments. PMID:26158674

In-flight alignment using H ∞ filter for strapdown INS on aircraft.

PubMed

Pei, Fu-Jun; Liu, Xuan; Zhu, Li

2014-01-01

In-flight alignment is an effective way to improve the accuracy and speed of initial alignment for strapdown inertial navigation system (INS). During the aircraft flight, strapdown INS alignment was disturbed by lineal and angular movements of the aircraft. To deal with the disturbances in dynamic initial alignment, a novel alignment method for SINS is investigated in this paper. In this method, an initial alignment error model of SINS in the inertial frame is established. The observability of the system is discussed by piece-wise constant system (PWCS) theory and observable degree is computed by the singular value decomposition (SVD) theory. It is demonstrated that the system is completely observable, and all the system state parameters can be estimated by optimal filter. Then a H ∞ filter was designed to resolve the uncertainty of measurement noise. The simulation results demonstrate that the proposed algorithm can reach a better accuracy under the dynamic disturbance condition.

Improvement of the insertion axis for cochlear implantation with a robot-based system.

PubMed

Torres, Renato; Kazmitcheff, Guillaume; De Seta, Daniele; Ferrary, Evelyne; Sterkers, Olivier; Nguyen, Yann

2017-02-01

It has previously reported that alignment of the insertion axis along the basal turn of the cochlea was depending on surgeon' experience. In this experimental study, we assessed technological assistances, such as navigation or a robot-based system, to improve the insertion axis during cochlear implantation. A preoperative cone beam CT and a mastoidectomy with a posterior tympanotomy were performed on four temporal bones. The optimal insertion axis was defined as the closest axis to the scala tympani centerline avoiding the facial nerve. A neuronavigation system, a robot assistance prototype, and software allowing a semi-automated alignment of the robot were used to align an insertion tool with an optimal insertion axis. Four procedures were performed and repeated three times in each temporal bone: manual, manual navigation-assisted, robot-based navigation-assisted, and robot-based semi-automated. The angle between the optimal and the insertion tool axis was measured in the four procedures. The error was 8.3° ± 2.82° for the manual procedure (n = 24), 8.6° ± 2.83° for the manual navigation-assisted procedure (n = 24), 5.4° ± 3.91° for the robot-based navigation-assisted procedure (n = 24), and 3.4° ± 1.56° for the robot-based semi-automated procedure (n = 12). A higher accuracy was observed with the semi-automated robot-based technique than manual and manual navigation-assisted (p < 0.01). Combination of a navigation system and a manual insertion does not improve the alignment accuracy due to the lack of friendly user interface. On the contrary, a semi-automated robot-based system reduces both the error and the variability of the alignment with a defined optimal axis.

Information theory-based decision support system for integrated design of multivariable hydrometric networks

NASA Astrophysics Data System (ADS)

Keum, Jongho; Coulibaly, Paulin

2017-07-01

Adequate and accurate hydrologic information from optimal hydrometric networks is an essential part of effective water resources management. Although the key hydrologic processes in the water cycle are interconnected, hydrometric networks (e.g., streamflow, precipitation, groundwater level) have been routinely designed individually. A decision support framework is proposed for integrated design of multivariable hydrometric networks. The proposed method is applied to design optimal precipitation and streamflow networks simultaneously. The epsilon-dominance hierarchical Bayesian optimization algorithm was combined with Shannon entropy of information theory to design and evaluate hydrometric networks. Specifically, the joint entropy from the combined networks was maximized to provide the most information, and the total correlation was minimized to reduce redundant information. To further optimize the efficiency between the networks, they were designed by maximizing the conditional entropy of the streamflow network given the information of the precipitation network. Compared to the traditional individual variable design approach, the integrated multivariable design method was able to determine more efficient optimal networks by avoiding the redundant stations. Additionally, four quantization cases were compared to evaluate their effects on the entropy calculations and the determination of the optimal networks. The evaluation results indicate that the quantization methods should be selected after careful consideration for each design problem since the station rankings and the optimal networks can change accordingly.

DISCO: Distance and Spectrum Correlation Optimization Alignment for Two Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry-based Metabolomics

PubMed Central

Wang, Bing; Fang, Aiqin; Heim, John; Bogdanov, Bogdan; Pugh, Scott; Libardoni, Mark; Zhang, Xiang

2010-01-01

A novel peak alignment algorithm using a distance and spectrum correlation optimization (DISCO) method has been developed for two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC/TOF-MS) based metabolomics. This algorithm uses the output of the instrument control software, ChromaTOF, as its input data. It detects and merges multiple peak entries of the same metabolite into one peak entry in each input peak list. After a z-score transformation of metabolite retention times, DISCO selects landmark peaks from all samples based on both two-dimensional retention times and mass spectrum similarity of fragment ions measured by Pearson’s correlation coefficient. A local linear fitting method is employed in the original two-dimensional retention time space to correct retention time shifts. A progressive retention time map searching method is used to align metabolite peaks in all samples together based on optimization of the Euclidean distance and mass spectrum similarity. The effectiveness of the DISCO algorithm is demonstrated using data sets acquired under different experiment conditions and a spiked-in experiment. PMID:20476746

Composition and Realization of Source-to-Sink High-Performance Flows: File Systems, Storage, Hosts, LAN and WAN

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

Wu, Chase Qishi

A number of Department of Energy (DOE) science applications, involving exascale computing systems and large experimental facilities, are expected to generate large volumes of data, in the range of petabytes to exabytes, which will be transported over wide-area networks for the purpose of storage, visualization, and analysis. To support such capabilities, significant progress has been made in various components including the deployment of 100 Gbps networks with future 1 Tbps bandwidth, increases in end-host capabilities with multiple cores and buses, capacity improvements in large disk arrays, and deployment of parallel file systems such as Lustre and GPFS. High-performance source-to-sink datamore » flows must be composed of these component systems, which requires significant optimizations of the storage-to-host data and execution paths to match the edge and long-haul network connections. In particular, end systems are currently supported by 10-40 Gbps Network Interface Cards (NIC) and 8-32 Gbps storage Host Channel Adapters (HCAs), which carry the individual flows that collectively must reach network speeds of 100 Gbps and higher. Indeed, such data flows must be synthesized using multicore, multibus hosts connected to high-performance storage systems on one side and to the network on the other side. Current experimental results show that the constituent flows must be optimally composed and preserved from storage systems, across the hosts and the networks with minimal interference. Furthermore, such a capability must be made available transparently to the science users without placing undue demands on them to account for the details of underlying systems and networks. And, this task is expected to become even more complex in the future due to the increasing sophistication of hosts, storage systems, and networks that constitute the high-performance flows. The objectives of this proposal are to (1) develop and test the component technologies and their synthesis methods to achieve source-to-sink high-performance flows, and (2) develop tools that provide these capabilities through simple interfaces to users and applications. In terms of the former, we propose to develop (1) optimization methods that align and transition multiple storage flows to multiple network flows on multicore, multibus hosts; and (2) edge and long-haul network path realization and maintenance using advanced provisioning methods including OSCARS and OpenFlow. We also propose synthesis methods that combine these individual technologies to compose high-performance flows using a collection of constituent storage-network flows, and realize them across the storage and local network connections as well as long-haul connections. We propose to develop automated user tools that profile the hosts, storage systems, and network connections; compose the source-to-sink complex flows; and set up and maintain the needed network connections. These solutions will be tested using (1) 100 Gbps connection(s) between Oak Ridge National Laboratory (ORNL) and Argonne National Laboratory (ANL) with storage systems supported by Lustre and GPFS file systems with an asymmetric connection to University of Memphis (UM); (2) ORNL testbed with multicore and multibus hosts, switches with OpenFlow capabilities, and network emulators; and (3) 100 Gbps connections from ESnet and their Openflow testbed, and other experimental connections. This proposal brings together the expertise and facilities of the two national laboratories, ORNL and ANL, and UM. It also represents a collaboration between DOE and the Department of Defense (DOD) projects at ORNL by sharing technical expertise and personnel costs, and leveraging the existing DOD Extreme Scale Systems Center (ESSC) facilities at ORNL.« less

Optimality in mono- and multisensory map formation.

PubMed

Bürck, Moritz; Friedel, Paul; Sichert, Andreas B; Vossen, Christine; van Hemmen, J Leo

2010-07-01

In the struggle for survival in a complex and dynamic environment, nature has developed a multitude of sophisticated sensory systems. In order to exploit the information provided by these sensory systems, higher vertebrates reconstruct the spatio-temporal environment from each of the sensory systems they have at their disposal. That is, for each modality the animal computes a neuronal representation of the outside world, a monosensory neuronal map. Here we present a universal framework that allows to calculate the specific layout of the involved neuronal network by means of a general mathematical principle, viz., stochastic optimality. In order to illustrate the use of this theoretical framework, we provide a step-by-step tutorial of how to apply our model. In so doing, we present a spatial and a temporal example of optimal stimulus reconstruction which underline the advantages of our approach. That is, given a known physical signal transmission and rudimental knowledge of the detection process, our approach allows to estimate the possible performance and to predict neuronal properties of biological sensory systems. Finally, information from different sensory modalities has to be integrated so as to gain a unified perception of reality for further processing, e.g., for distinct motor commands. We briefly discuss concepts of multimodal interaction and how a multimodal space can evolve by alignment of monosensory maps.

SPARSE: quadratic time simultaneous alignment and folding of RNAs without sequence-based heuristics

PubMed Central

Will, Sebastian; Otto, Christina; Miladi, Milad; Möhl, Mathias; Backofen, Rolf

2015-01-01

Motivation: RNA-Seq experiments have revealed a multitude of novel ncRNAs. The gold standard for their analysis based on simultaneous alignment and folding suffers from extreme time complexity of O(n6). Subsequently, numerous faster ‘Sankoff-style’ approaches have been suggested. Commonly, the performance of such methods relies on sequence-based heuristics that restrict the search space to optimal or near-optimal sequence alignments; however, the accuracy of sequence-based methods breaks down for RNAs with sequence identities below 60%. Alignment approaches like LocARNA that do not require sequence-based heuristics, have been limited to high complexity (≥ quartic time). Results: Breaking this barrier, we introduce the novel Sankoff-style algorithm ‘sparsified prediction and alignment of RNAs based on their structure ensembles (SPARSE)’, which runs in quadratic time without sequence-based heuristics. To achieve this low complexity, on par with sequence alignment algorithms, SPARSE features strong sparsification based on structural properties of the RNA ensembles. Following PMcomp, SPARSE gains further speed-up from lightweight energy computation. Although all existing lightweight Sankoff-style methods restrict Sankoff’s original model by disallowing loop deletions and insertions, SPARSE transfers the Sankoff algorithm to the lightweight energy model completely for the first time. Compared with LocARNA, SPARSE achieves similar alignment and better folding quality in significantly less time (speedup: 3.7). At similar run-time, it aligns low sequence identity instances substantially more accurate than RAF, which uses sequence-based heuristics. Availability and implementation: SPARSE is freely available at http://www.bioinf.uni-freiburg.de/Software/SPARSE. Contact: backofen@informatik.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25838465

A one-layer recurrent neural network for constrained pseudoconvex optimization and its application for dynamic portfolio optimization.

PubMed

Liu, Qingshan; Guo, Zhishan; Wang, Jun

2012-02-01

In this paper, a one-layer recurrent neural network is proposed for solving pseudoconvex optimization problems subject to linear equality and bound constraints. Compared with the existing neural networks for optimization (e.g., the projection neural networks), the proposed neural network is capable of solving more general pseudoconvex optimization problems with equality and bound constraints. Moreover, it is capable of solving constrained fractional programming problems as a special case. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed as long as the designed parameters in the model are larger than the derived lower bounds. Numerical examples with simulation results illustrate the effectiveness and characteristics of the proposed neural network. In addition, an application for dynamic portfolio optimization is discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Network placement optimization for large-scale distributed system

NASA Astrophysics Data System (ADS)

Ren, Yu; Liu, Fangfang; Fu, Yunxia; Zhou, Zheng

2018-01-01

The network geometry strongly influences the performance of the distributed system, i.e., the coverage capability, measurement accuracy and overall cost. Therefore the network placement optimization represents an urgent issue in the distributed measurement, even in large-scale metrology. This paper presents an effective computer-assisted network placement optimization procedure for the large-scale distributed system and illustrates it with the example of the multi-tracker system. To get an optimal placement, the coverage capability and the coordinate uncertainty of the network are quantified. Then a placement optimization objective function is developed in terms of coverage capabilities, measurement accuracy and overall cost. And a novel grid-based encoding approach for Genetic algorithm is proposed. So the network placement is optimized by a global rough search and a local detailed search. Its obvious advantage is that there is no need for a specific initial placement. At last, a specific application illustrates this placement optimization procedure can simulate the measurement results of a specific network and design the optimal placement efficiently.

A graph decomposition-based approach for water distribution network optimization

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.; Deuerlein, Jochen W.

2013-04-01

A novel optimization approach for water distribution network design is proposed in this paper. Using graph theory algorithms, a full water network is first decomposed into different subnetworks based on the connectivity of the network's components. The original whole network is simplified to a directed augmented tree, in which the subnetworks are substituted by augmented nodes and directed links are created to connect them. Differential evolution (DE) is then employed to optimize each subnetwork based on the sequence specified by the assigned directed links in the augmented tree. Rather than optimizing the original network as a whole, the subnetworks are sequentially optimized by the DE algorithm. A solution choice table is established for each subnetwork (except for the subnetwork that includes a supply node) and the optimal solution of the original whole network is finally obtained by use of the solution choice tables. Furthermore, a preconditioning algorithm is applied to the subnetworks to produce an approximately optimal solution for the original whole network. This solution specifies promising regions for the final optimization algorithm to further optimize the subnetworks. Five water network case studies are used to demonstrate the effectiveness of the proposed optimization method. A standard DE algorithm (SDE) and a genetic algorithm (GA) are applied to each case study without network decomposition to enable a comparison with the proposed method. The results show that the proposed method consistently outperforms the SDE and GA (both with tuned parameters) in terms of both the solution quality and efficiency.

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

PubMed

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

2016-10-06

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

Optimizing Dynamical Network Structure for Pinning Control

NASA Astrophysics Data System (ADS)

Orouskhani, Yasin; Jalili, Mahdi; Yu, Xinghuo

2016-04-01

Controlling dynamics of a network from any initial state to a final desired state has many applications in different disciplines from engineering to biology and social sciences. In this work, we optimize the network structure for pinning control. The problem is formulated as four optimization tasks: i) optimizing the locations of driver nodes, ii) optimizing the feedback gains, iii) optimizing simultaneously the locations of driver nodes and feedback gains, and iv) optimizing the connection weights. A newly developed population-based optimization technique (cat swarm optimization) is used as the optimization method. In order to verify the methods, we use both real-world networks, and model scale-free and small-world networks. Extensive simulation results show that the optimal placement of driver nodes significantly outperforms heuristic methods including placing drivers based on various centrality measures (degree, betweenness, closeness and clustering coefficient). The pinning controllability is further improved by optimizing the feedback gains. We also show that one can significantly improve the controllability by optimizing the connection weights.

Focus determination for the James Webb Space Telescope Science Instruments: A Survey of Methods

NASA Technical Reports Server (NTRS)

Davila, Pamela S.; Bolcar, Matthew R.; Boss, B.; Dean, B.; Hapogian, J.; Howard, J.; Unger, B.; Wilson, M.

2006-01-01

The James Webb Space Telescope (JWST) is a segmented deployable telescope that will require on-orbit alignment using the Near Infrared Camera as a wavefront sensor. The telescope will be aligned by adjusting seven degrees of freedom on each of 18 primary mirror segments and five degrees of freedom on the secondary mirror to optimize the performance of the telescope and camera at a wavelength of 2 microns. With the completion of these adjustments, the telescope focus is set and the optical performance of each of the other science instruments should then be optimal without making further telescope focus adjustments for each individual instrument. This alignment approach requires confocality of the instruments after integration and alignment to the composite metering structure, which will be verified during instrument level testing at Goddard Space Flight Center with a telescope optical simulator. In this paper, we present the results from a study of several analytical approaches to determine the focus for each instrument. The goal of the study is to compare the accuracies obtained for each method, and to select the most feasible for use during optical testing.

Optimization of Buckypaper-enhanced Multifunctional Thermoplastic Composites

PubMed Central

Li, Zhongrui; Liang, Zhiyong

2017-01-01

A series of flattened-nanotube reinforced thermoplastic composites are sizably fabricated as a function of buckypaper loading. The effects of the volume fraction, nanotube alignment and length on the tensile performance of the composites are factored into a general expression. The incorporation of self-reinforcing polyphenylene resin (Parmax) into a highly aligned buckypaper frame at an optimal weight ratio boosts the tensile strength and Young’s modulus of the buckypaper/Parmax composite to 1145 MPa and 150 GPa, respectively, far exceeding those of Parmax and aligned buckypaper individually. The composite also exhibits improved thermal (>65 W/m-K) and electrical (~700 S/cm) conductivities, as well as high thermoelectric power (22 μV/K) at room temperature. Meanwhile, the composite displays a heterogeneously complex structure. The hexyl groups of Parmax noncovalently interact with the honeycomb structure of the flattened nanotube through π-stacking and CH-π interaction, correspondingly improving the dispersity of polymer on the nanotube surface and the interfacial stress transferring while the high alignment degrees of nanotube facilitate phonon and charge transport in the composites. PMID:28205637

Development of a reinforced electrochemically aligned collagen bioscaffold for tendon tissue engineering applications

NASA Astrophysics Data System (ADS)

Uquillas Paredes, Jorge Alfredo

Type-I collagen is a promising biomaterial that can be used to synthesize bioscaffolds as a strategy to regenerate and repair damaged tendons. The existing in vitro prepared collagen bioscaffolds are in the form of gels, foams, or extruded fibers. These bioscaffolds readily present sites for attachment of biological factors and cells; however, they have extremely poor biomechanical properties in comparison to the properties of native tendons. The biomechanical function of type-I collagen bioscaffolds needs to be elevated to the level of natural tissues for this biomaterial to replace mechanically challenged tendons in a functionally meaningful way. The overall goal of this dissertation is to develop a reinforced electrochemically aligned collagenous bioscaffold for applications in tendon tissue engineering. The bioscaffold is synthesized by a unique electrochemical process via isoelectric focusing (IEF) to attain a very high degree of molecular alignment and packing density. This dissertation presents progress made on four aims: A) development of simple and descriptive electrochemical theory via the mathematical model of IEF and the forces acting on collagen alignment under an electric field; B) optimization of the post-alignment PBS treatment step to achieve d- banding pattern in uncrosslinked electrochemically aligned collagen (ELAC) bioscaffolds; C) optimization of the best crosslinking protocol to produce the strongest possible ELAC biomaterial with excellent cellular compatibility; and D) in vivo evaluation of the biocompatibility and biodegradability properties of electronically aligned collagen bioscaffolds. The results of this dissertation provide strong evidence showing that reinforced ELAC bioscaffolds could be used clinically in the future to repair damaged tendons.

Creep-induced anisotropy in covalent adaptable network polymers.

PubMed

Hanzon, Drew W; He, Xu; Yang, Hua; Shi, Qian; Yu, Kai

2017-10-11

Anisotropic polymers with aligned macromolecule chains exhibit directional strengthening of mechanical and physical properties. However, manipulating the orientation of polymer chains in a fully cured thermoset is almost impossible due to its permanently crosslinked nature. In this paper, we demonstrate that rearrangeable networks with bond exchange reactions (BERs) can be utilized to tailor the anisotropic mechanical properties of thermosetting polymers. When a constant force is maintained at BER activated temperatures, the malleable thermoset creeps in the direction of stress, and macromolecule chains align themselves in the same direction. The aligned polymer chains result in an anisotropic network with a stiffer mechanical behavior in the direction of creep, while with a more compliant behavior in the transverse direction. The degree of network anisotropy is proportional to the amount of creep strain. A multi-length scale constitutive model is developed to study the creep-induced anisotropy of thermosetting polymers. The model connects the micro-scale BER kinetics, orientation of polymer chains, and directional mechanical properties of network polymers. Without any fitting parameters, it is able to predict the evolution of creep strain at different temperatures and anisotropic stress-strain behaviors of CANs after creep. Predictions on the chain orientation are verified by molecular dynamics (MD) simulation. Based on parametric studies, it is shown that the influences of creep time and temperature on the network anisotropy can be generalized into a single parameter, and the evolution of directional modulus follows an Arrhenius type time-temperature superposition principle (TTSP). The presented work provides a facile approach to transform isotropic thermosets into anisotropic ones using simple heating, and their directional properties can be readily tailored by the processing conditions.

2D reentrant auxetic structures of graphene/CNT networks for omnidirectionally stretchable supercapacitors.

PubMed

Kim, Byoung Soo; Lee, Kangsuk; Kang, Seulki; Lee, Soyeon; Pyo, Jun Beom; Choi, In Suk; Char, Kookheon; Park, Jong Hyuk; Lee, Sang-Soo; Lee, Jonghwi; Son, Jeong Gon

2017-09-14

Stretchable energy storage systems are essential for the realization of implantable and epidermal electronics. However, high-performance stretchable supercapacitors have received less attention because currently available processing techniques and material structures are too limited to overcome the trade-off relationship among electrical conductivity, ion-accessible surface area, and stretchability of electrodes. Herein, we introduce novel 2D reentrant cellular structures of porous graphene/CNT networks for omnidirectionally stretchable supercapacitor electrodes. Reentrant structures, with inwardly protruded frameworks in porous networks, were fabricated by the radial compression of vertically aligned honeycomb-like rGO/CNT networks, which were prepared by a directional crystallization method. Unlike typical porous graphene structures, the reentrant structure provided structure-assisted stretchability, such as accordion and origami structures, to otherwise unstretchable materials. The 2D reentrant structures of graphene/CNT networks maintained excellent electrical conductivities under biaxial stretching conditions and showed a slightly negative or near-zero Poisson's ratio over a wide strain range because of their structural uniqueness. For practical applications, we fabricated all-solid-state supercapacitors based on 2D auxetic structures. A radial compression process up to 1/10 th densified the electrode, significantly increasing the areal and volumetric capacitances of the electrodes. Additionally, vertically aligned graphene/CNT networks provided a plentiful surface area and induced sufficient ion transport pathways for the electrodes. Therefore, they exhibited high gravimetric and areal capacitance values of 152.4 F g -1 and 2.9 F cm -2 , respectively, and had an excellent retention ratio of 88% under a biaxial strain of 100%. Auxetic cellular and vertically aligned structures provide a new strategy for the preparation of robust platforms for stretchable energy storage electrodes.

Optimal synchronization in space

NASA Astrophysics Data System (ADS)

Brede, Markus

2010-02-01

In this Rapid Communication we investigate spatially constrained networks that realize optimal synchronization properties. After arguing that spatial constraints can be imposed by limiting the amount of “wire” available to connect nodes distributed in space, we use numerical optimization methods to construct networks that realize different trade offs between optimal synchronization and spatial constraints. Over a large range of parameters such optimal networks are found to have a link length distribution characterized by power-law tails P(l)∝l-α , with exponents α increasing as the networks become more constrained in space. It is also shown that the optimal networks, which constitute a particular type of small world network, are characterized by the presence of nodes of distinctly larger than average degree around which long-distance links are centered.

A robust cloud registration method based on redundant data reduction using backpropagation neural network and shift window

NASA Astrophysics Data System (ADS)

Xin, Meiting; Li, Bing; Yan, Xiao; Chen, Lei; Wei, Xiang

2018-02-01

A robust coarse-to-fine registration method based on the backpropagation (BP) neural network and shift window technology is proposed in this study. Specifically, there are three steps: coarse alignment between the model data and measured data, data simplification based on the BP neural network and point reservation in the contour region of point clouds, and fine registration with the reweighted iterative closest point algorithm. In the process of rough alignment, the initial rotation matrix and the translation vector between the two datasets are obtained. After performing subsequent simplification operations, the number of points can be reduced greatly. Therefore, the time and space complexity of the accurate registration can be significantly reduced. The experimental results show that the proposed method improves the computational efficiency without loss of accuracy.

Local alignment vectors reveal cancer cell-induced ECM fiber remodeling dynamics

PubMed Central

Lee, Byoungkoo; Konen, Jessica; Wilkinson, Scott; Marcus, Adam I.; Jiang, Yi

2017-01-01

Invasive cancer cells interact with the surrounding extracellular matrix (ECM), remodeling ECM fiber network structure by condensing, degrading, and aligning these fibers. We developed a novel local alignment vector analysis method to quantitatively measure collagen fiber alignment as a vector field using Circular Statistics. This method was applied to human non-small cell lung carcinoma (NSCLC) cell lines, embedded as spheroids in a collagen gel. Collagen remodeling was monitored using second harmonic generation imaging under normal conditions and when the LKB1-MARK1 pathway was disrupted through RNAi-based approaches. The results showed that inhibiting LKB1 or MARK1 in NSCLC increases the collagen fiber alignment and captures outward alignment vectors from the tumor spheroid, corresponding to high invasiveness of LKB1 mutant cancer cells. With time-lapse imaging of ECM micro-fiber morphology, the local alignment vector can measure the dynamic signature of invasive cancer cell activity and cell-migration-induced ECM and collagen remodeling and realigning dynamics. PMID:28045069

Tabu Search enhances network robustness under targeted attacks

NASA Astrophysics Data System (ADS)

Sun, Shi-wen; Ma, Yi-lin; Li, Rui-qi; Wang, Li; Xia, Cheng-yi

2016-03-01

We focus on the optimization of network robustness with respect to intentional attacks on high-degree nodes. Given an existing network, this problem can be considered as a typical single-objective combinatorial optimization problem. Based on the heuristic Tabu Search optimization algorithm, a link-rewiring method is applied to reconstruct the network while keeping the degree of every node unchanged. Through numerical simulations, BA scale-free network and two real-world networks are investigated to verify the effectiveness of the proposed optimization method. Meanwhile, we analyze how the optimization affects other topological properties of the networks, including natural connectivity, clustering coefficient and degree-degree correlation. The current results can help to improve the robustness of existing complex real-world systems, as well as to provide some insights into the design of robust networks.

LAMBADA and InflateGRO2: efficient membrane alignment and insertion of membrane proteins for molecular dynamics simulations.

PubMed

Schmidt, Thomas H; Kandt, Christian

2012-10-22

At the beginning of each molecular dynamics membrane simulation stands the generation of a suitable starting structure which includes the working steps of aligning membrane and protein and seamlessly accommodating the protein in the membrane. Here we introduce two efficient and complementary methods based on pre-equilibrated membrane patches, automating these steps. Using a voxel-based cast of the coarse-grained protein, LAMBADA computes a hydrophilicity profile-derived scoring function based on which the optimal rotation and translation operations are determined to align protein and membrane. Employing an entirely geometrical approach, LAMBADA is independent from any precalculated data and aligns even large membrane proteins within minutes on a regular workstation. LAMBADA is the first tool performing the entire alignment process automatically while providing the user with the explicit 3D coordinates of the aligned protein and membrane. The second tool is an extension of the InflateGRO method addressing the shortcomings of its predecessor in a fully automated workflow. Determining the exact number of overlapping lipids based on the area occupied by the protein and restricting expansion, compression and energy minimization steps to a subset of relevant lipids through automatically calculated and system-optimized operation parameters, InflateGRO2 yields optimal lipid packing and reduces lipid vacuum exposure to a minimum preserving as much of the equilibrated membrane structure as possible. Applicable to atomistic and coarse grain structures in MARTINI format, InflateGRO2 offers high accuracy, fast performance, and increased application flexibility permitting the easy preparation of systems exhibiting heterogeneous lipid composition as well as embedding proteins into multiple membranes. Both tools can be used separately, in combination with other methods, or in tandem permitting a fully automated workflow while retaining a maximum level of usage control and flexibility. To assess the performance of both methods, we carried out test runs using 22 membrane proteins of different size and transmembrane structure.

Multi-species Identification of Polymorphic Peptide Variants via Propagation in Spectral Networks*

PubMed Central

Bandeira, Nuno

2016-01-01

Peptide and protein identification remains challenging in organisms with poorly annotated or rapidly evolving genomes, as are commonly encountered in environmental or biofuels research. Such limitations render tandem mass spectrometry (MS/MS) database search algorithms ineffective as they lack corresponding sequences required for peptide-spectrum matching. We address this challenge with the spectral networks approach to (1) match spectra of orthologous peptides across multiple related species and then (2) propagate peptide annotations from identified to unidentified spectra. We here present algorithms to assess the statistical significance of spectral alignments (Align-GF), reduce the impurity in spectral networks, and accurately estimate the error rate in propagated identifications. Analyzing three related Cyanothece species, a model organism for biohydrogen production, spectral networks identified peptides from highly divergent sequences from networks with dozens of variant peptides, including thousands of peptides in species lacking a sequenced genome. Our analysis further detected the presence of many novel putative peptides even in genomically characterized species, thus suggesting the possibility of gaps in our understanding of their proteomic and genomic expression. A web-based pipeline for spectral networks analysis is available at http://proteomics.ucsd.edu/software. PMID:27609420

Optimizing Nutrient Uptake in Biological Transport Networks

NASA Astrophysics Data System (ADS)

Ronellenfitsch, Henrik; Katifori, Eleni

2013-03-01

Many biological systems employ complex networks of vascular tubes to facilitate transport of solute nutrients, examples include the vascular system of plants (phloem), some fungi, and the slime-mold Physarum. It is believed that such networks are optimized through evolution for carrying out their designated task. We propose a set of hydrodynamic governing equations for solute transport in a complex network, and obtain the optimal network architecture for various classes of optimizing functionals. We finally discuss the topological properties and statistical mechanics of the resulting complex networks, and examine correspondence of the obtained networks to those found in actual biological systems.

Simulations in site error estimation for direction finders

NASA Astrophysics Data System (ADS)

López, Raúl E.; Passi, Ranjit M.

1991-08-01

The performance of an algorithm for the recovery of site-specific errors of direction finder (DF) networks is tested under controlled simulated conditions. The simulations show that the algorithm has some inherent shortcomings for the recovery of site errors from the measured azimuth data. These limitations are fundamental to the problem of site error estimation using azimuth information. Several ways for resolving or ameliorating these basic complications are tested by means of simulations. From these it appears that for the effective implementation of the site error determination algorithm, one should design the networks with at least four DFs, improve the alignment of the antennas, and increase the gain of the DFs as much as it is compatible with other operational requirements. The use of a nonzero initial estimate of the site errors when working with data from networks of four or more DFs also improves the accuracy of the site error recovery. Even for networks of three DFs, reasonable site error corrections could be obtained if the antennas could be well aligned.

Feed Forward Neural Network and Optimal Control Problem with Control and State Constraints

NASA Astrophysics Data System (ADS)

Kmet', Tibor; Kmet'ová, Mária

2009-09-01

A feed forward neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints. The paper extends adaptive critic neural network architecture proposed by [5] to the optimal control problems with control and state constraints. The optimal control problem is transcribed into a nonlinear programming problem which is implemented with adaptive critic neural network. The proposed simulation method is illustrated by the optimal control problem of nitrogen transformation cycle model. Results show that adaptive critic based systematic approach holds promise for obtaining the optimal control with control and state constraints.

The Alignment of the Informal and Formal Organizational Supports for Reform: Implications for Improving Teaching in Schools

ERIC Educational Resources Information Center

Penuel, William R.; Riel, Margaret; Joshi, Aasha; Pearlman, Leslie; Kim, Chong Min; Frank, Kenneth A.

2010-01-01

Previous qualitative studies show that when the formal organization of a school and patterns of informal interaction are aligned, faculty and leaders in a school are better able to coordinate instructional change. This article combines social network analysis with interview data to analyze how well the formal and informal aspects of a school's…

Toward End-to-End Face Recognition Through Alignment Learning

NASA Astrophysics Data System (ADS)

Zhong, Yuanyi; Chen, Jiansheng; Huang, Bo

2017-08-01

Plenty of effective methods have been proposed for face recognition during the past decade. Although these methods differ essentially in many aspects, a common practice of them is to specifically align the facial area based on the prior knowledge of human face structure before feature extraction. In most systems, the face alignment module is implemented independently. This has actually caused difficulties in the designing and training of end-to-end face recognition models. In this paper we study the possibility of alignment learning in end-to-end face recognition, in which neither prior knowledge on facial landmarks nor artificially defined geometric transformations are required. Specifically, spatial transformer layers are inserted in front of the feature extraction layers in a Convolutional Neural Network (CNN) for face recognition. Only human identity clues are used for driving the neural network to automatically learn the most suitable geometric transformation and the most appropriate facial area for the recognition task. To ensure reproducibility, our model is trained purely on the publicly available CASIA-WebFace dataset, and is tested on the Labeled Face in the Wild (LFW) dataset. We have achieved a verification accuracy of 99.08\\% which is comparable to state-of-the-art single model based methods.

Mobile and replicated alignment of arrays in data-parallel programs

NASA Technical Reports Server (NTRS)

Chatterjee, Siddhartha; Gilbert, John R.; Schreiber, Robert

1993-01-01

When a data-parallel language like FORTRAN 90 is compiled for a distributed-memory machine, aggregate data objects (such as arrays) are distributed across the processor memories. The mapping determines the amount of residual communication needed to bring operands of parallel operations into alignment with each other. A common approach is to break the mapping into two stages: first, an alignment that maps all the objects to an abstract template, and then a distribution that maps the template to the processors. We solve two facets of the problem of finding alignments that reduce residual communication: we determine alignments that vary in loops, and objects that should have replicated alignments. We show that loop-dependent mobile alignment is sometimes necessary for optimum performance, and we provide algorithms with which a compiler can determine good mobile alignments for objects within do loops. We also identify situations in which replicated alignment is either required by the program itself (via spread operations) or can be used to improve performance. We propose an algorithm based on network flow that determines which objects to replicate so as to minimize the total amount of broadcast communication in replication. This work on mobile and replicated alignment extends our earlier work on determining static alignment.

Performance improvement of optical CDMA networks with stochastic artificial bee colony optimization technique

NASA Astrophysics Data System (ADS)

Panda, Satyasen

2018-05-01

This paper proposes a modified artificial bee colony optimization (ABC) algorithm based on levy flight swarm intelligence referred as artificial bee colony levy flight stochastic walk (ABC-LFSW) optimization for optical code division multiple access (OCDMA) network. The ABC-LFSW algorithm is used to solve asset assignment problem based on signal to noise ratio (SNR) optimization in OCDM networks with quality of service constraints. The proposed optimization using ABC-LFSW algorithm provides methods for minimizing various noises and interferences, regulating the transmitted power and optimizing the network design for improving the power efficiency of the optical code path (OCP) from source node to destination node. In this regard, an optical system model is proposed for improving the network performance with optimized input parameters. The detailed discussion and simulation results based on transmitted power allocation and power efficiency of OCPs are included. The experimental results prove the superiority of the proposed network in terms of power efficiency and spectral efficiency in comparison to networks without any power allocation approach.

Research on robust optimization of emergency logistics network considering the time dependence characteristic

NASA Astrophysics Data System (ADS)

WANG, Qingrong; ZHU, Changfeng; LI, Ying; ZHANG, Zhengkun

2017-06-01

Considering the time dependence of emergency logistic network and complexity of the environment that the network exists in, in this paper the time dependent network optimization theory and robust discrete optimization theory are combined, and the emergency logistics dynamic network optimization model with characteristics of robustness is built to maximize the timeliness of emergency logistics. On this basis, considering the complexity of dynamic network and the time dependence of edge weight, an improved ant colony algorithm is proposed to realize the coupling of the optimization algorithm and the network time dependence and robustness. Finally, a case study has been carried out in order to testify validity of this robustness optimization model and its algorithm, and the value of different regulation factors was analyzed considering the importance of the value of the control factor in solving the optimal path. Analysis results show that this model and its algorithm above-mentioned have good timeliness and strong robustness.

Network-optimized congestion pricing : a parable, model and algorithm

DOT National Transportation Integrated Search

1995-05-31

This paper recites a parable, formulates a model and devises an algorithm for optimizing tolls on a road network. Such tolls induce an equilibrium traffic flow that is at once system-optimal and user-optimal. The parable introduces the network-wide c...

MetaGO: Predicting Gene Ontology of Non-homologous Proteins Through Low-Resolution Protein Structure Prediction and Protein-Protein Network Mapping.

PubMed

Zhang, Chengxin; Zheng, Wei; Freddolino, Peter L; Zhang, Yang

2018-03-10

Homology-based transferal remains the major approach to computational protein function annotations, but it becomes increasingly unreliable when the sequence identity between query and template decreases below 30%. We propose a novel pipeline, MetaGO, to deduce Gene Ontology attributes of proteins by combining sequence homology-based annotation with low-resolution structure prediction and comparison, and partner's homology-based protein-protein network mapping. The pipeline was tested on a large-scale set of 1000 non-redundant proteins from the CAFA3 experiment. Under the stringent benchmark conditions where templates with >30% sequence identity to the query are excluded, MetaGO achieves average F-measures of 0.487, 0.408, and 0.598, for Molecular Function, Biological Process, and Cellular Component, respectively, which are significantly higher than those achieved by other state-of-the-art function annotations methods. Detailed data analysis shows that the major advantage of the MetaGO lies in the new functional homolog detections from partner's homology-based network mapping and structure-based local and global structure alignments, the confidence scores of which can be optimally combined through logistic regression. These data demonstrate the power of using a hybrid model incorporating protein structure and interaction networks to deduce new functional insights beyond traditional sequence homology-based referrals, especially for proteins that lack homologous function templates. The MetaGO pipeline is available at http://zhanglab.ccmb.med.umich.edu/MetaGO/. Copyright © 2018. Published by Elsevier Ltd.

Optimal percolation on multiplex networks.

PubMed

Osat, Saeed; Faqeeh, Ali; Radicchi, Filippo

2017-11-16

Optimal percolation is the problem of finding the minimal set of nodes whose removal from a network fragments the system into non-extensive disconnected clusters. The solution to this problem is important for strategies of immunization in disease spreading, and influence maximization in opinion dynamics. Optimal percolation has received considerable attention in the context of isolated networks. However, its generalization to multiplex networks has not yet been considered. Here we show that approximating the solution of the optimal percolation problem on a multiplex network with solutions valid for single-layer networks extracted from the multiplex may have serious consequences in the characterization of the true robustness of the system. We reach this conclusion by extending many of the methods for finding approximate solutions of the optimal percolation problem from single-layer to multiplex networks, and performing a systematic analysis on synthetic and real-world multiplex networks.

Fine-tuning structural RNA alignments in the twilight zone.

PubMed

Bremges, Andreas; Schirmer, Stefanie; Giegerich, Robert

2010-04-30

A widely used method to find conserved secondary structure in RNA is to first construct a multiple sequence alignment, and then fold the alignment, optimizing a score based on thermodynamics and covariance. This method works best around 75% sequence similarity. However, in a "twilight zone" below 55% similarity, the sequence alignment tends to obscure the covariance signal used in the second phase. Therefore, while the overall shape of the consensus structure may still be found, the degree of conservation cannot be estimated reliably. Based on a combination of available methods, we present a method named planACstar for improving structure conservation in structural alignments in the twilight zone. After constructing a consensus structure by alignment folding, planACstar abandons the original sequence alignment, refolds the sequences individually, but consistent with the consensus, aligns the structures, irrespective of sequence, by a pure structure alignment method, and derives an improved sequence alignment from the alignment of structures, to be re-submitted to alignment folding, etc.. This circle may be iterated as long as structural conservation improves, but normally, one step suffices. Employing the tools ClustalW, RNAalifold, and RNAforester, we find that for sequences with 30-55% sequence identity, structural conservation can be improved by 10% on average, with a large variation, measured in terms of RNAalifold's own criterion, the structure conservation index.

A One-Layer Recurrent Neural Network for Real-Time Portfolio Optimization With Probability Criterion.

PubMed

Liu, Qingshan; Dang, Chuangyin; Huang, Tingwen

2013-02-01

This paper presents a decision-making model described by a recurrent neural network for dynamic portfolio optimization. The portfolio-optimization problem is first converted into a constrained fractional programming problem. Since the objective function in the programming problem is not convex, the traditional optimization techniques are no longer applicable for solving this problem. Fortunately, the objective function in the fractional programming is pseudoconvex on the feasible region. It leads to a one-layer recurrent neural network modeled by means of a discontinuous dynamic system. To ensure the optimal solutions for portfolio optimization, the convergence of the proposed neural network is analyzed and proved. In fact, the neural network guarantees to get the optimal solutions for portfolio-investment advice if some mild conditions are satisfied. A numerical example with simulation results substantiates the effectiveness and illustrates the characteristics of the proposed neural network.

Nurses' Satisfaction With Using Nursing Information Systems From Technology Acceptance Model and Information Systems Success Model Perspectives: A Reductionist Approach.

PubMed

Lin, Hsien-Cheng

2017-02-01

Nursing information systems can enhance nursing practice and the efficiency and quality of administrative affairs within the nursing department and thus have been widely considered for implementation. Close alignment of human-computer interaction can advance optimal clinical performance with the use of information systems. However, a lack of introduction of the concept of alignment between users' perceptions and technological functionality has caused dissatisfaction, as shown in the existing literature. This study provides insight into the alignment between nurses' perceptions and how technological functionality affects their satisfaction with Nursing Information System use through a reductionist perspective of alignment. This cross-sectional study collected data from 531 registered nurses in Taiwan. The results indicated that "perceived usefulness in system quality alignment," "perceived usefulness in information quality alignment," "perceived ease of use in system quality alignment," "perceived ease of use in information quality alignment," and "perceived ease of use in service quality alignment" have significantly affected nurses' satisfaction with Nursing Information System use. However, "perceived usefulness in service quality alignment" had no significant effect on nurses' satisfaction. This study also provides some meaningful implications for theoretical and practical aspects of design.

Precise Synaptic Efficacy Alignment Suggests Potentiation Dominated Learning.

PubMed

Hartmann, Christoph; Miner, Daniel C; Triesch, Jochen

2015-01-01

Recent evidence suggests that parallel synapses from the same axonal branch onto the same dendritic branch have almost identical strength. It has been proposed that this alignment is only possible through learning rules that integrate activity over long time spans. However, learning mechanisms such as spike-timing-dependent plasticity (STDP) are commonly assumed to be temporally local. Here, we propose that the combination of temporally local STDP and a multiplicative synaptic normalization mechanism is sufficient to explain the alignment of parallel synapses. To address this issue, we introduce three increasingly complex models: First, we model the idealized interaction of STDP and synaptic normalization in a single neuron as a simple stochastic process and derive analytically that the alignment effect can be described by a so-called Kesten process. From this we can derive that synaptic efficacy alignment requires potentiation-dominated learning regimes. We verify these conditions in a single-neuron model with independent spiking activities but more realistic synapses. As expected, we only observe synaptic efficacy alignment for long-term potentiation-biased STDP. Finally, we explore how well the findings transfer to recurrent neural networks where the learning mechanisms interact with the correlated activity of the network. We find that due to the self-reinforcing correlations in recurrent circuits under STDP, alignment occurs for both long-term potentiation- and depression-biased STDP, because the learning will be potentiation dominated in both cases due to the potentiating events induced by correlated activity. This is in line with recent results demonstrating a dominance of potentiation over depression during waking and normalization during sleep. This leads us to predict that individual spine pairs will be more similar after sleep compared to after sleep deprivation. In conclusion, we show that synaptic normalization in conjunction with coordinated potentiation--in this case, from STDP in the presence of correlated pre- and post-synaptic activity--naturally leads to an alignment of parallel synapses.

A parallel adaptive quantum genetic algorithm for the controllability of arbitrary networks.

PubMed

Li, Yuhong; Gong, Guanghong; Li, Ni

2018-01-01

In this paper, we propose a novel algorithm-parallel adaptive quantum genetic algorithm-which can rapidly determine the minimum control nodes of arbitrary networks with both control nodes and state nodes. The corresponding network can be fully controlled with the obtained control scheme. We transformed the network controllability issue into a combinational optimization problem based on the Popov-Belevitch-Hautus rank condition. A set of canonical networks and a list of real-world networks were experimented. Comparison results demonstrated that the algorithm was more ideal to optimize the controllability of networks, especially those larger-size networks. We demonstrated subsequently that there were links between the optimal control nodes and some network statistical characteristics. The proposed algorithm provides an effective approach to improve the controllability optimization of large networks or even extra-large networks with hundreds of thousands nodes.

78 FR 57845 - Notice of Availability (NOA) for Strategic Network Optimization (SNO) Program Environmental...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-20

... (NOA) for Strategic Network Optimization (SNO) Program Environmental Assessment AGENCY: Defense Logistics Agency, DoD. ACTION: Notice of Availability (NOA) for Strategic Network Optimization (SNO) Program... implement the SNO initiative for improvements to material distribution network for the Department of Defense...

Coordinated and uncoordinated optimization of networks

NASA Astrophysics Data System (ADS)

Brede, Markus

2010-06-01

In this paper, we consider spatial networks that realize a balance between an infrastructure cost (the cost of wire needed to connect the network in space) and communication efficiency, measured by average shortest path length. A global optimization procedure yields network topologies in which this balance is optimized. These are compared with network topologies generated by a competitive process in which each node strives to optimize its own cost-communication balance. Three phases are observed in globally optimal configurations for different cost-communication trade offs: (i) regular small worlds, (ii) starlike networks, and (iii) trees with a center of interconnected hubs. In the latter regime, i.e., for very expensive wire, power laws in the link length distributions P(w)∝w-α are found, which can be explained by a hierarchical organization of the networks. In contrast, in the local optimization process the presence of sharp transitions between different network regimes depends on the dimension of the underlying space. Whereas for d=∞ sharp transitions between fully connected networks, regular small worlds, and highly cliquish periphery-core networks are found, for d=1 sharp transitions are absent and the power law behavior in the link length distribution persists over a much wider range of link cost parameters. The measured power law exponents are in agreement with the hypothesis that the locally optimized networks consist of multiple overlapping suboptimal hierarchical trees.

Energy optimization in mobile sensor networks

NASA Astrophysics Data System (ADS)

Yu, Shengwei

Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while consuming negligible amount of energy for mobility cost. For the second problem, the problem is extended to accommodate mobile robotic nodes with energy harvesting capability, which makes it a non-convex optimization problem. The non-convexity issue is tackled by using the existing sequential convex approximation method, based on which we propose a novel procedure of modified sequential convex approximation that has fast convergence speed. For the third problem, the proposed procedure is used to solve another challenging non-convex problem, which results in utilizing mobility and routing simultaneously in mobile robotic sensor networks to prolong the network lifetime. The results indicate that joint design of mobility and routing has an edge over other methods in prolonging network lifetime, which is also the justification for the use of mobility in mobile sensor networks for energy efficiency purpose. For the fourth problem, we include the dynamics of the robotic nodes in the problem by modeling the networked robotic system using hybrid systems theory. A novel distributed method for the networked hybrid system is used to solve the optimal moving trajectories for robotic nodes and optimal network links, which are not answered by previous approaches. Finally, the fact that mobility is more effective in prolonging network lifetime for a data-intensive network leads us to apply our methods to study mobile visual sensor networks, which are useful in many applications. We investigate the joint design of mobility, data routing, and encoding power to help improving the video quality while maximizing the network lifetime. This study leads to a better understanding of the role mobility can play in data-intensive surveillance sensor networks.

In-Flight Alignment Using H ∞ Filter for Strapdown INS on Aircraft

PubMed Central

Pei, Fu-Jun; Liu, Xuan; Zhu, Li

2014-01-01

In-flight alignment is an effective way to improve the accuracy and speed of initial alignment for strapdown inertial navigation system (INS). During the aircraft flight, strapdown INS alignment was disturbed by lineal and angular movements of the aircraft. To deal with the disturbances in dynamic initial alignment, a novel alignment method for SINS is investigated in this paper. In this method, an initial alignment error model of SINS in the inertial frame is established. The observability of the system is discussed by piece-wise constant system (PWCS) theory and observable degree is computed by the singular value decomposition (SVD) theory. It is demonstrated that the system is completely observable, and all the system state parameters can be estimated by optimal filter. Then a H ∞ filter was designed to resolve the uncertainty of measurement noise. The simulation results demonstrate that the proposed algorithm can reach a better accuracy under the dynamic disturbance condition. PMID:24511300

Application of Neural Network Optimized by Mind Evolutionary Computation in Building Energy Prediction

NASA Astrophysics Data System (ADS)

Song, Chen; Zhong-Cheng, Wu; Hong, Lv

2018-03-01

Building Energy forecasting plays an important role in energy management and plan. Using mind evolutionary algorithm to find the optimal network weights and threshold, to optimize the BP neural network, can overcome the problem of the BP neural network into a local minimum point. The optimized network is used for time series prediction, and the same month forecast, to get two predictive values. Then two kinds of predictive values are put into neural network, to get the final forecast value. The effectiveness of the method was verified by experiment with the energy value of three buildings in Hefei.

Thermodynamic characterization of synchronization-optimized oscillator networks

NASA Astrophysics Data System (ADS)

Yanagita, Tatsuo; Ichinomiya, Takashi

2014-12-01

We consider a canonical ensemble of synchronization-optimized networks of identical oscillators under external noise. By performing a Markov chain Monte Carlo simulation using the Kirchhoff index, i.e., the sum of the inverse eigenvalues of the Laplacian matrix (as a graph Hamiltonian of the network), we construct more than 1 000 different synchronization-optimized networks. We then show that the transition from star to core-periphery structure depends on the connectivity of the network, and is characterized by the node degree variance of the synchronization-optimized ensemble. We find that thermodynamic properties such as heat capacity show anomalies for sparse networks.

Freeze Tape Casting of Functionally Graded Porous Ceramics

NASA Technical Reports Server (NTRS)

Sofie, Stephen W.

2007-01-01

Freeze tape casting is a means of making preforms of ceramic sheets that, upon subsequent completion of fabrication processing, can have anisotropic and/or functionally graded properties that notably include aligned and graded porosity. Freeze tape casting was developed to enable optimization of the microstructures of porous ceramic components for use as solid oxide electrodes in fuel cells: Through alignment and grading of pores, one can tailor surface areas and diffusion channels for flows of gas and liquid species involved in fuel-cell reactions. Freeze tape casting offers similar benefits for fabrication of optimally porous ceramics for use as catalysts, gas sensors, and filters.

Resolving the multiple sequence alignment problem using biogeography-based optimization with multiple populations.

PubMed

Zemali, El-Amine; Boukra, Abdelmadjid

2015-08-01

The multiple sequence alignment (MSA) is one of the most challenging problems in bioinformatics, it involves discovering similarity between a set of protein or DNA sequences. This paper introduces a new method for the MSA problem called biogeography-based optimization with multiple populations (BBOMP). It is based on a recent metaheuristic inspired from the mathematics of biogeography named biogeography-based optimization (BBO). To improve the exploration ability of BBO, we have introduced a new concept allowing better exploration of the search space. It consists of manipulating multiple populations having each one its own parameters. These parameters are used to build up progressive alignments allowing more diversity. At each iteration, the best found solution is injected in each population. Moreover, to improve solution quality, six operators are defined. These operators are selected with a dynamic probability which changes according to the operators efficiency. In order to test proposed approach performance, we have considered a set of datasets from Balibase 2.0 and compared it with many recent algorithms such as GAPAM, MSA-GA, QEAMSA and RBT-GA. The results show that the proposed approach achieves better average score than the previously cited methods.

Self-optimizing approach for automated laser resonator alignment

NASA Astrophysics Data System (ADS)

Brecher, C.; Schmitt, R.; Loosen, P.; Guerrero, V.; Pyschny, N.; Pavim, A.; Gatej, A.

2012-02-01

Nowadays, the assembly of laser systems is dominated by manual operations, involving elaborate alignment by means of adjustable mountings. From a competition perspective, the most challenging problem in laser source manufacturing is price pressure, a result of cost competition exerted mainly from Asia. From an economical point of view, an automated assembly of laser systems defines a better approach to produce more reliable units at lower cost. However, the step from today's manual solutions towards an automated assembly requires parallel developments regarding product design, automation equipment and assembly processes. This paper introduces briefly the idea of self-optimizing technical systems as a new approach towards highly flexible automation. Technically, the work focuses on the precision assembly of laser resonators, which is one of the final and most crucial assembly steps in terms of beam quality and laser power. The paper presents a new design approach for miniaturized laser systems and new automation concepts for a robot-based precision assembly, as well as passive and active alignment methods, which are based on a self-optimizing approach. Very promising results have already been achieved, considerably reducing the duration and complexity of the laser resonator assembly. These results as well as future development perspectives are discussed.

Electrospun Collagen/Silk Tissue Engineering Scaffolds: Fiber Fabrication, Post-Treatment Optimization, and Application in Neural Differentiation of Stem Cells

NASA Astrophysics Data System (ADS)

Zhu, Bofan

Biocompatible scaffolds mimicking the locally aligned fibrous structure of native extracellular matrix (ECM) are in high demand in tissue engineering. In this thesis research, unidirectionally aligned fibers were generated via a home-built electrospinning system. Collagen type I, as a major ECM component, was chosen in this study due to its support of cell proliferation and promotion of neuroectodermal commitment in stem cell differentiation. Synthetic dragline silk proteins, as biopolymers with remarkable tensile strength and superior elasticity, were also used as a model material. Good alignment, controllable fiber size and morphology, as well as a desirable deposition density of fibers were achieved via the optimization of solution and electrospinning parameters. The incorporation of silk proteins into collagen was found to significantly enhance mechanical properties and stability of electrospun fibers. Glutaraldehyde (GA) vapor post-treatment was demonstrated as a simple and effective way to tune the properties of collagen/silk fibers without changing their chemical composition. With 6-12 hours GA treatment, electrospun collagen/silk fibers were not only biocompatible, but could also effectively induce the polarization and neural commitment of stem cells, which were optimized on collagen rich fibers due to the unique combination of biochemical and biophysical cues imposed to cells. Taken together, electrospun collagen rich composite fibers are mechanically strong, stable and provide excellent cell adhesion. The unidirectionally aligned fibers can accelerate neural differentiation of stem cells, representing a promising therapy for neural tissue degenerative diseases and nerve injuries.

A Novel Framework for the Comparative Analysis of Biological Networks

PubMed Central

Pache, Roland A.; Aloy, Patrick

2012-01-01

Genome sequencing projects provide nearly complete lists of the individual components present in an organism, but reveal little about how they work together. Follow-up initiatives have deciphered thousands of dynamic and context-dependent interrelationships between gene products that need to be analyzed with novel bioinformatics approaches able to capture their complex emerging properties. Here, we present a novel framework for the alignment and comparative analysis of biological networks of arbitrary topology. Our strategy includes the prediction of likely conserved interactions, based on evolutionary distances, to counter the high number of missing interactions in the current interactome networks, and a fast assessment of the statistical significance of individual alignment solutions, which vastly increases its performance with respect to existing tools. Finally, we illustrate the biological significance of the results through the identification of novel complex components and potential cases of cross-talk between pathways and alternative signaling routes. PMID:22363585

Scalable multi-sample single-cell data analysis by Partition-Assisted Clustering and Multiple Alignments of Networks

PubMed Central

Samusik, Nikolay; Wang, Xiaowei; Guan, Leying; Nolan, Garry P.

2017-01-01

Mass cytometry (CyTOF) has greatly expanded the capability of cytometry. It is now easy to generate multiple CyTOF samples in a single study, with each sample containing single-cell measurement on 50 markers for more than hundreds of thousands of cells. Current methods do not adequately address the issues concerning combining multiple samples for subpopulation discovery, and these issues can be quickly and dramatically amplified with increasing number of samples. To overcome this limitation, we developed Partition-Assisted Clustering and Multiple Alignments of Networks (PAC-MAN) for the fast automatic identification of cell populations in CyTOF data closely matching that of expert manual-discovery, and for alignments between subpopulations across samples to define dataset-level cellular states. PAC-MAN is computationally efficient, allowing the management of very large CyTOF datasets, which are increasingly common in clinical studies and cancer studies that monitor various tissue samples for each subject. PMID:29281633

Glacier moraine formation-mimicking colloidal particle assembly in microchanneled, bioactive hydrogel for guided vascular network construction.

PubMed

Lee, Min Kyung; Rich, Max H; Shkumatov, Artem; Jeong, Jae Hyun; Boppart, Marni D; Bashir, Rashid; Gillette, Martha U; Lee, Jonghwi; Kong, Hyunjoon

2015-01-28

This study demonstrates that a new method to align microparticles releasing bioactive molecules in microchannels of a hydrogel allows the guiding of growth direction and spacing of vascular networks. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Genome-Wide Networks of Amino Acid Covariances Are Common among Viruses

PubMed Central

Donlin, Maureen J.; Szeto, Brandon; Gohara, David W.; Aurora, Rajeev

2012-01-01

Coordinated variation among positions in amino acid sequence alignments can reveal genetic dependencies at noncontiguous positions, but methods to assess these interactions are incompletely developed. Previously, we found genome-wide networks of covarying residue positions in the hepatitis C virus genome (R. Aurora, M. J. Donlin, N. A. Cannon, and J. E. Tavis, J. Clin. Invest. 119:225–236, 2009). Here, we asked whether such networks are present in a diverse set of viruses and, if so, what they may imply about viral biology. Viral sequences were obtained for 16 viruses in 13 species from 9 families. The entire viral coding potential for each virus was aligned, all possible amino acid covariances were identified using the observed-minus-expected-squared algorithm at a false-discovery rate of ≤1%, and networks of covariances were assessed using standard methods. Covariances that spanned the viral coding potential were common in all viruses. In all cases, the covariances formed a single network that contained essentially all of the covariances. The hepatitis C virus networks had hub-and-spoke topologies, but all other networks had random topologies with an unusually large number of highly connected nodes. These results indicate that genome-wide networks of genetic associations and the coordinated evolution they imply are very common in viral genomes, that the networks rarely have the hub-and-spoke topology that dominates other biological networks, and that network topologies can vary substantially even within a given viral group. Five examples with hepatitis B virus and poliovirus are presented to illustrate how covariance network analysis can lead to inferences about viral biology. PMID:22238298

Wireless Sensor Network Optimization: Multi-Objective Paradigm.

PubMed

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-07-20

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.

Statistical Significance of Optical Map Alignments

PubMed Central

Sarkar, Deepayan; Goldstein, Steve; Schwartz, David C.

2012-01-01

Abstract The Optical Mapping System constructs ordered restriction maps spanning entire genomes through the assembly and analysis of large datasets comprising individually analyzed genomic DNA molecules. Such restriction maps uniquely reveal mammalian genome structure and variation, but also raise computational and statistical questions beyond those that have been solved in the analysis of smaller, microbial genomes. We address the problem of how to filter maps that align poorly to a reference genome. We obtain map-specific thresholds that control errors and improve iterative assembly. We also show how an optimal self-alignment score provides an accurate approximation to the probability of alignment, which is useful in applications seeking to identify structural genomic abnormalities. PMID:22506568

SVM-dependent pairwise HMM: an application to protein pairwise alignments.

PubMed

Orlando, Gabriele; Raimondi, Daniele; Khan, Taushif; Lenaerts, Tom; Vranken, Wim F

2017-12-15

Methods able to provide reliable protein alignments are crucial for many bioinformatics applications. In the last years many different algorithms have been developed and various kinds of information, from sequence conservation to secondary structure, have been used to improve the alignment performances. This is especially relevant for proteins with highly divergent sequences. However, recent works suggest that different features may have different importance in diverse protein classes and it would be an advantage to have more customizable approaches, capable to deal with different alignment definitions. Here we present Rigapollo, a highly flexible pairwise alignment method based on a pairwise HMM-SVM that can use any type of information to build alignments. Rigapollo lets the user decide the optimal features to align their protein class of interest. It outperforms current state of the art methods on two well-known benchmark datasets when aligning highly divergent sequences. A Python implementation of the algorithm is available at http://ibsquare.be/rigapollo. wim.vranken@vub.be. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

40 CFR 63.9632 - What are the installation, operation, and maintenance requirements for my monitoring equipment?

Code of Federal Regulations, 2012 CFR

2012-07-01

... document is available on the EPA's Technology Transfer Network at http://www.epa.gov/ttn/emc/cem/tribo.pdf... alignment of each COMS. (3) You must operate and maintain each COMS according to § 63.8(e) and your quality... alignment audit. (4) You must determine and record the 6-minute average opacity for periods during which the...

40 CFR 63.9632 - What are the installation, operation, and maintenance requirements for my monitoring equipment?

Code of Federal Regulations, 2013 CFR

2013-07-01

... document is available on the EPA's Technology Transfer Network at http://www.epa.gov/ttn/emc/cem/tribo.pdf... alignment of each COMS. (3) You must operate and maintain each COMS according to § 63.8(e) and your quality... alignment audit. (4) You must determine and record the 6-minute average opacity for periods during which the...

40 CFR 63.9632 - What are the installation, operation, and maintenance requirements for my monitoring equipment?

Code of Federal Regulations, 2014 CFR

2014-07-01

... document is available on the EPA's Technology Transfer Network at http://www.epa.gov/ttn/emc/cem/tribo.pdf... alignment of each COMS. (3) You must operate and maintain each COMS according to § 63.8(e) and your quality... alignment audit. (4) You must determine and record the 6-minute average opacity for periods during which the...

Dynamic Spectrum Sharing with Limited Network State Information

DTIC Science & Technology

2010-11-01

M. L. Honig,"Two-Cell Downlink Noncoherent Cooperation Without Transmitter Phase Alignment", Proc. Globecom Conf., Miami, FL, Dec. 2010. D. Schmidt, W...restrict the number of active streams even though the maximum multiplexing gain is not achieved. 3 Noncoherent Cooperative Broadcasting...study a noncoherent cooperative transmission scheme with two interfering links, which does not require phase alignment. It is assumed that the

Formation of contractile networks and fibers in the medial cell cortex through myosin-II turnover, contraction, and stress-stabilization

PubMed Central

Nie, Wei; Wei, Ming-Tzo; Ou-Yang, Daniel H.; Jedlicka, Sabrina S.; Vavylonis, Dimitrios

2015-01-01

The morphology of adhered cells depends crucially on the formation of a contractile meshwork of parallel and cross-linked fibers along the contacting surface. The motor activity and minifilament assembly of non-muscle myosin-II is an important component of cortical cytoskeletal remodeling during mechanosensing. We used experiments and computational modeling to study cortical myosin-II dynamics in adhered cells. Confocal microscopy was used to image the medial cell cortex of HeLa cells stably expressing myosin regulatory light chain tagged with GFP (MRLC-GFP). The distribution of MRLC-GFP fibers and focal adhesions was classified into three types of network morphologies. Time-lapse movies show: myosin foci appearance and disappearance; aligning and contraction; stabilization upon alignment. Addition of blebbistatin, which perturbs myosin motor activity, leads to a reorganization of the cortical networks and to a reduction of contractile motions. We quantified the kinetics of contraction, disassembly and reassembly of myosin networks using spatio-temporal image correlation spectroscopy (STICS). Coarse-grained numerical simulations include bipolar minifilaments that contract and align through specified interactions as basic elements. After assuming that minifilament turnover decreases with increasing contractile stress, the simulations reproduce stress-dependent fiber formation in between focal adhesions above a threshold myosin concentration. The STICS correlation function in simulations matches the function measured in experiments. This study provides a framework to help interpret how different cortical myosin remodeling kinetics may contribute to different cell shape and rigidity depending on substrate stiffness. PMID:25641802

PrimerDesign-M: A multiple-alignment based multiple-primer design tool for walking across variable genomes

DOE PAGES

Yoon, Hyejin; Leitner, Thomas

2014-12-17

Analyses of entire viral genomes or mtDNA requires comprehensive design of many primers across their genomes. In addition, simultaneous optimization of several DNA primer design criteria may improve overall experimental efficiency and downstream bioinformatic processing. To achieve these goals, we developed PrimerDesign-M. It includes several options for multiple-primer design, allowing researchers to efficiently design walking primers that cover long DNA targets, such as entire HIV-1 genomes, and that optimizes primers simultaneously informed by genetic diversity in multiple alignments and experimental design constraints given by the user. PrimerDesign-M can also design primers that include DNA barcodes and minimize primer dimerization. PrimerDesign-Mmore » finds optimal primers for highly variable DNA targets and facilitates design flexibility by suggesting alternative designs to adapt to experimental conditions.« less

Pinning down high-performance Cu-chalcogenides as thin-film solar cell absorbers: A successive screening approach

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

Zhang, Yubo; Zhang, Wenqing, E-mail: wqzhang@mail.sic.ac.cn, E-mail: pzhang3@buffalo.edu; State Key Laboratory of High Performance Ceramics and Superfine Microstructures, Shanghai Institute of Ceramics, Chinese Academy of Sciences, Shanghai 200050

2016-05-21

Photovoltaic performances of Cu-chalcogenides solar cells are strongly correlated with the absorber fundamental properties such as optimal bandgap, desired band alignment with window material, and high photon absorption ability. According to these criteria, we carry out a successive screening for 90 Cu-chalcogenides using efficient theoretical approaches. Besides the well-recognized CuInSe{sub 2} and Cu{sub 2}ZnSnSe{sub 4} materials, several novel candidates are identified to have optimal bandgaps of around 1.0–1.5 eV, spike-like band alignments with CdS window layer, sharp photon absorption edges, and high absorption coefficients. These new systems have great potential to be superior absorbers for photovolatic applications if their carrriermore » transport and defect properties are properly optimized.« less

Cloud Computing with Context Cameras

NASA Astrophysics Data System (ADS)

Pickles, A. J.; Rosing, W. E.

2016-05-01

We summarize methods and plans to monitor and calibrate photometric observations with our autonomous, robotic network of 2m, 1m and 40cm telescopes. These are sited globally to optimize our ability to observe time-variable sources. Wide field "context" cameras are aligned with our network telescopes and cycle every ˜2 minutes through BVr'i'z' filters, spanning our optical range. We measure instantaneous zero-point offsets and transparency (throughput) against calibrators in the 5-12m range from the all-sky Tycho2 catalog, and periodically against primary standards. Similar measurements are made for all our science images, with typical fields of view of ˜0.5 degrees. These are matched against Landolt, Stetson and Sloan standards, and against calibrators in the 10-17m range from the all-sky APASS catalog. Such measurements provide pretty good instantaneous flux calibration, often to better than 5%, even in cloudy conditions. Zero-point and transparency measurements can be used to characterize, monitor and inter-compare sites and equipment. When accurate calibrations of Target against Standard fields are required, monitoring measurements can be used to select truly photometric periods when accurate calibrations can be automatically scheduled and performed.

A Computational Analysis of Neural Mechanisms Underlying the Maturation of Multisensory Speech Integration in Neurotypical Children and Those on the Autism Spectrum

PubMed Central

Cuppini, Cristiano; Ursino, Mauro; Magosso, Elisa; Ross, Lars A.; Foxe, John J.; Molholm, Sophie

2017-01-01

Failure to appropriately develop multisensory integration (MSI) of audiovisual speech may affect a child's ability to attain optimal communication. Studies have shown protracted development of MSI into late-childhood and identified deficits in MSI in children with an autism spectrum disorder (ASD). Currently, the neural basis of acquisition of this ability is not well understood. Here, we developed a computational model informed by neurophysiology to analyze possible mechanisms underlying MSI maturation, and its delayed development in ASD. The model posits that strengthening of feedforward and cross-sensory connections, responsible for the alignment of auditory and visual speech sound representations in posterior superior temporal gyrus/sulcus, can explain behavioral data on the acquisition of MSI. This was simulated by a training phase during which the network was exposed to unisensory and multisensory stimuli, and projections were crafted by Hebbian rules of potentiation and depression. In its mature architecture, the network also reproduced the well-known multisensory McGurk speech effect. Deficits in audiovisual speech perception in ASD were well accounted for by fewer multisensory exposures, compatible with a lack of attention, but not by reduced synaptic connectivity or synaptic plasticity. PMID:29163099

A comparison of registration errors with imageless computer navigation during MIS total knee arthroplasty versus standard incision total knee arthroplasty: a cadaveric study.

PubMed

Davis, Edward T; Pagkalos, Joseph; Gallie, Price A M; Macgroarty, Kelly; Waddell, James P; Schemitsch, Emil H

2015-01-01

Optimal component alignment in total knee arthroplasty has been associated with better functional outcome as well as improved implant longevity. The ability to align components optimally during minimally invasive (MIS) total knee replacement (TKR) has been a cause of concern. Computer navigation is a useful aid in achieving the desired alignment although it is limited by the error during the manual registration of landmarks. Our study aims to compare the registration process error between a standard and a MIS surgical approach. We hypothesized that performing the registration error via an MIS approach would increase the registration process error. Five fresh frozen lower limbs were routinely prepared and draped. The registration process was performed through an MIS approach. This was then extended to the standard approach and the registration was performed again. Two surgeons performed the registration process five times with each approach. Performing the registration process through the MIS approach was not associated with higher error compared to the standard approach in the alignment parameters of interest. This rejects our hypothesis. Image-free navigated MIS TKR does not appear to carry higher risk of component malalignment due to the registration process error. Navigation can be used during MIS TKR to improve alignment without reduced accuracy due to the approach.

Finite-time convergent recurrent neural network with a hard-limiting activation function for constrained optimization with piecewise-linear objective functions.

PubMed

Liu, Qingshan; Wang, Jun

2011-04-01

This paper presents a one-layer recurrent neural network for solving a class of constrained nonsmooth optimization problems with piecewise-linear objective functions. The proposed neural network is guaranteed to be globally convergent in finite time to the optimal solutions under a mild condition on a derived lower bound of a single gain parameter in the model. The number of neurons in the neural network is the same as the number of decision variables of the optimization problem. Compared with existing neural networks for optimization, the proposed neural network has a couple of salient features such as finite-time convergence and a low model complexity. Specific models for two important special cases, namely, linear programming and nonsmooth optimization, are also presented. In addition, applications to the shortest path problem and constrained least absolute deviation problem are discussed with simulation results to demonstrate the effectiveness and characteristics of the proposed neural network.

Software for Alignment of Segments of a Telescope Mirror

NASA Technical Reports Server (NTRS)

Hall, Drew P.; Howard, Richard T.; Ly, William C.; Rakoczy, John M.; Weir, John M.

2006-01-01

The Segment Alignment Maintenance System (SAMS) software is designed to maintain the overall focus and figure of the large segmented primary mirror of the Hobby-Eberly Telescope. This software reads measurements made by sensors attached to the segments of the primary mirror and from these measurements computes optimal control values to send to actuators that move the mirror segments.

Electronic neural networks for global optimization

NASA Technical Reports Server (NTRS)

Thakoor, A. P.; Moopenn, A. W.; Eberhardt, S.

1990-01-01

An electronic neural network with feedback architecture, implemented in analog custom VLSI is described. Its application to problems of global optimization for dynamic assignment is discussed. The convergence properties of the neural network hardware are compared with computer simulation results. The neural network's ability to provide optimal or near optimal solutions within only a few neuron time constants, a speed enhancement of several orders of magnitude over conventional search methods, is demonstrated. The effect of noise on the circuit dynamics and the convergence behavior of the neural network hardware is also examined.

Topology Optimization for Energy Management in Underwater Sensor Networks

DTIC Science & Technology

2015-02-01

1 To appear in International Journal of Control as a regular paper Topology Optimization for Energy Management in Underwater Sensor Networks ⋆ Devesh...K. Jha1 Thomas A. Wettergren2 Asok Ray1 Kushal Mukherjee3 Keywords: Underwater Sensor Network , Energy Management, Pareto Optimization, Adaptation...Optimization for Energy Management in Underwater Sensor Networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d

Inclusion of tank configurations as a variable in the cost optimization of branched piped-water networks

NASA Astrophysics Data System (ADS)

Hooda, Nikhil; Damani, Om

2017-06-01

The classic problem of the capital cost optimization of branched piped networks consists of choosing pipe diameters for each pipe in the network from a discrete set of commercially available pipe diameters. Each pipe in the network can consist of multiple segments of differing diameters. Water networks also consist of intermediate tanks that act as buffers between incoming flow from the primary source and the outgoing flow to the demand nodes. The network from the primary source to the tanks is called the primary network, and the network from the tanks to the demand nodes is called the secondary network. During the design stage, the primary and secondary networks are optimized separately, with the tanks acting as demand nodes for the primary network. Typically the choice of tank locations, their elevations, and the set of demand nodes to be served by different tanks is manually made in an ad hoc fashion before any optimization is done. It is desirable therefore to include this tank configuration choice in the cost optimization process itself. In this work, we explain why the choice of tank configuration is important to the design of a network and describe an integer linear program model that integrates the tank configuration to the standard pipe diameter selection problem. In order to aid the designers of piped-water networks, the improved cost optimization formulation is incorporated into our existing network design system called JalTantra.

CAFE: aCcelerated Alignment-FrEe sequence analysis.

PubMed

Lu, Yang Young; Tang, Kujin; Ren, Jie; Fuhrman, Jed A; Waterman, Michael S; Sun, Fengzhu

2017-07-03

Alignment-free genome and metagenome comparisons are increasingly important with the development of next generation sequencing (NGS) technologies. Recently developed state-of-the-art k-mer based alignment-free dissimilarity measures including CVTree, $d_2^*$ and $d_2^S$ are more computationally expensive than measures based solely on the k-mer frequencies. Here, we report a standalone software, aCcelerated Alignment-FrEe sequence analysis (CAFE), for efficient calculation of 28 alignment-free dissimilarity measures. CAFE allows for both assembled genome sequences and unassembled NGS shotgun reads as input, and wraps the output in a standard PHYLIP format. In downstream analyses, CAFE can also be used to visualize the pairwise dissimilarity measures, including dendrograms, heatmap, principal coordinate analysis and network display. CAFE serves as a general k-mer based alignment-free analysis platform for studying the relationships among genomes and metagenomes, and is freely available at https://github.com/younglululu/CAFE. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Application of SNODAS and hydrologic models to enhance entropy-based snow monitoring network design

NASA Astrophysics Data System (ADS)

Keum, Jongho; Coulibaly, Paulin; Razavi, Tara; Tapsoba, Dominique; Gobena, Adam; Weber, Frank; Pietroniro, Alain

2018-06-01

Snow has a unique characteristic in the water cycle, that is, snow falls during the entire winter season, but the discharge from snowmelt is typically delayed until the melting period and occurs in a relatively short period. Therefore, reliable observations from an optimal snow monitoring network are necessary for an efficient management of snowmelt water for flood prevention and hydropower generation. The Dual Entropy and Multiobjective Optimization is applied to design snow monitoring networks in La Grande River Basin in Québec and Columbia River Basin in British Columbia. While the networks are optimized to have the maximum amount of information with minimum redundancy based on entropy concepts, this study extends the traditional entropy applications to the hydrometric network design by introducing several improvements. First, several data quantization cases and their effects on the snow network design problems were explored. Second, the applicability the Snow Data Assimilation System (SNODAS) products as synthetic datasets of potential stations was demonstrated in the design of the snow monitoring network of the Columbia River Basin. Third, beyond finding the Pareto-optimal networks from the entropy with multi-objective optimization, the networks obtained for La Grande River Basin were further evaluated by applying three hydrologic models. The calibrated hydrologic models simulated discharges using the updated snow water equivalent data from the Pareto-optimal networks. Then, the model performances for high flows were compared to determine the best optimal network for enhanced spring runoff forecasting.

Reverse alignment "mirror image" visualization as a laparoscopic training tool improves task performance.

PubMed

Dunnican, Ward J; Singh, T Paul; Ata, Ashar; Bendana, Emma E; Conlee, Thomas D; Dolce, Charles J; Ramakrishnan, Rakesh

2010-06-01

Reverse alignment (mirror image) visualization is a disconcerting situation occasionally faced during laparoscopic operations. This occurs when the camera faces back at the surgeon in the opposite direction from which the surgeon's body and instruments are facing. Most surgeons will attempt to optimize trocar and camera placement to avoid this situation. The authors' objective was to determine whether the intentional use of reverse alignment visualization during laparoscopic training would improve performance. A standard box trainer was configured for reverse alignment, and 34 medical students and junior surgical residents were randomized to train with either forward alignment (DIRECT) or reverse alignment (MIRROR) visualization. Enrollees were tested on both modalities before and after a 4-week structured training program specific to their modality. Student's t test was used to determine differences in task performance between the 2 groups. Twenty-one participants completed the study (10 DIRECT, 11 MIRROR). There were no significant differences in performance time between DIRECT or MIRROR participants during forward or reverse alignment initial testing. At final testing, DIRECT participants had improved times only in forward alignment performance; they demonstrated no significant improvement in reverse alignment performance. MIRROR participants had significant time improvement in both forward and reverse alignment performance at final testing. Reverse alignment imaging for laparoscopic training improves task performance for both reverse alignment and forward alignment tasks. This may be translated into improved performance in the operating room when faced with reverse alignment situations. Minimal lab training can account for drastic adaptation to this environment.

Recapitulating phylogenies using k-mers: from trees to networks.

PubMed

Bernard, Guillaume; Ragan, Mark A; Chan, Cheong Xin

2016-01-01

Ernst Haeckel based his landmark Tree of Life on the supposed ontogenic recapitulation of phylogeny, i.e. that successive embryonic stages during the development of an organism re-trace the morphological forms of its ancestors over the course of evolution. Much of this idea has since been discredited. Today, phylogenies are often based on families of molecular sequences. The standard approach starts with a multiple sequence alignment, in which the sequences are arranged relative to each other in a way that maximises a measure of similarity position-by-position along their entire length. A tree (or sometimes a network) is then inferred. Rigorous multiple sequence alignment is computationally demanding, and evolutionary processes that shape the genomes of many microbes (bacteria, archaea and some morphologically simple eukaryotes) can add further complications. In particular, recombination, genome rearrangement and lateral genetic transfer undermine the assumptions that underlie multiple sequence alignment, and imply that a tree-like structure may be too simplistic. Here, using genome sequences of 143 bacterial and archaeal genomes, we construct a network of phylogenetic relatedness based on the number of shared k -mers (subsequences at fixed length k ). Our findings suggest that the network captures not only key aspects of microbial genome evolution as inferred from a tree, but also features that are not treelike. The method is highly scalable, allowing for investigation of genome evolution across a large number of genomes. Instead of using specific regions or sequences from genome sequences, or indeed Haeckel's idea of ontogeny, we argue that genome phylogenies can be inferred using k -mers from whole-genome sequences. Representing these networks dynamically allows biological questions of interest to be formulated and addressed quickly and in a visually intuitive manner.

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction.

PubMed

Cui, Xuefeng; Lu, Zhiwu; Wang, Sheng; Jing-Yan Wang, Jim; Gao, Xin

2016-06-15

Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that try to find transitive paths in the protein structure space demonstrate the importance of incorporating network information of the structure space. Yet, current methods merge the sequence space and the structure space into a single space, and thus introduce inconsistency in combining different sources of information. We present a novel network-based protein homology detection method, CMsearch, based on cross-modal learning. Instead of exploring a single network built from the mixture of sequence and structure space information, CMsearch builds two separate networks to represent the sequence space and the structure space. It then learns sequence-structure correlation by simultaneously taking sequence information, structure information, sequence space information and structure space information into consideration. We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. Our results demonstrate that CMsearch is insensitive to the similarity metrics used to define the sequence and the structure spaces. By using HMM-HMM alignment as the sequence similarity metric, CMsearch clearly outperforms state-of-the-art homology detection methods and the CASP-winning template-based protein structure prediction methods. Our program is freely available for download from http://sfb.kaust.edu.sa/Pages/Software.aspx : xin.gao@kaust.edu.sa Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Fine-tuning structural RNA alignments in the twilight zone

PubMed Central

2010-01-01

Background A widely used method to find conserved secondary structure in RNA is to first construct a multiple sequence alignment, and then fold the alignment, optimizing a score based on thermodynamics and covariance. This method works best around 75% sequence similarity. However, in a "twilight zone" below 55% similarity, the sequence alignment tends to obscure the covariance signal used in the second phase. Therefore, while the overall shape of the consensus structure may still be found, the degree of conservation cannot be estimated reliably. Results Based on a combination of available methods, we present a method named planACstar for improving structure conservation in structural alignments in the twilight zone. After constructing a consensus structure by alignment folding, planACstar abandons the original sequence alignment, refolds the sequences individually, but consistent with the consensus, aligns the structures, irrespective of sequence, by a pure structure alignment method, and derives an improved sequence alignment from the alignment of structures, to be re-submitted to alignment folding, etc.. This circle may be iterated as long as structural conservation improves, but normally, one step suffices. Conclusions Employing the tools ClustalW, RNAalifold, and RNAforester, we find that for sequences with 30-55% sequence identity, structural conservation can be improved by 10% on average, with a large variation, measured in terms of RNAalifold's own criterion, the structure conservation index. PMID:20433706

Score distributions of gapped multiple sequence alignments down to the low-probability tail

NASA Astrophysics Data System (ADS)

Fieth, Pascal; Hartmann, Alexander K.

2016-08-01

Assessing the significance of alignment scores of optimally aligned DNA or amino acid sequences can be achieved via the knowledge of the score distribution of random sequences. But this requires obtaining the distribution in the biologically relevant high-scoring region, where the probabilities are exponentially small. For gapless local alignments of infinitely long sequences this distribution is known analytically to follow a Gumbel distribution. Distributions for gapped local alignments and global alignments of finite lengths can only be obtained numerically. To obtain result for the small-probability region, specific statistical mechanics-based rare-event algorithms can be applied. In previous studies, this was achieved for pairwise alignments. They showed that, contrary to results from previous simple sampling studies, strong deviations from the Gumbel distribution occur in case of finite sequence lengths. Here we extend the studies to multiple sequence alignments with gaps, which are much more relevant for practical applications in molecular biology. We study the distributions of scores over a large range of the support, reaching probabilities as small as 10-160, for global and local (sum-of-pair scores) multiple alignments. We find that even after suitable rescaling, eliminating the sequence-length dependence, the distributions for multiple alignment differ from the pairwise alignment case. Furthermore, we also show that the previously discussed Gaussian correction to the Gumbel distribution needs to be refined, also for the case of pairwise alignments.

Bio-mimic optimization strategies in wireless sensor networks: a survey.

PubMed

Adnan, Md Akhtaruzzaman; Abdur Razzaque, Mohammd; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

2013-12-24

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.

Numerical Analysis of Micromixers for Optimization of Mixing Action

NASA Astrophysics Data System (ADS)

Panta, Yogendra; Adhikari, Param

2011-03-01

Micro-bio/chemical applications often require rapid and uniform mixing of a number of fluid streams that carries bio/chemical species in the solution. At microscale, fluid flow is highly laminar with low Reynolds number, fluids mixing mechanism is primarily by diffusion and free from any turbulence. Demand for highly efficient micromixers for microfluidic networks is due to slower mixing process for larger bio-molecules such as peptides, proteins, and nucleic acids compared to micro-scale molecules. Passive and active mixers are two basic mixers that are currently in use for these applications. Passive mixers often require very long mixing channels where are most active mixers require bulky moving parts to stir the fluids. In this study, electroosmotic effects orthogonally aligned with the fluid flowstream are utilized for optimum mixing effect in various micromixers. Cross-dependencies among several geometrical, electrical, and fluid parameters and their significance are studied in order to achieve an optimum mixing effect. It has been planned to optimize the mixer by non-moving stirring actions provided by an external magnetic field. Acknowledgements to School of Graduate Studies and Research at YSU for URC Grant and RP Award 2009-2010.

Paraplegic patients: how to measure balance and what is normal or functional?

PubMed

Barkoh, Kaku; Lucas, Joshua W; Lee, Larry; Hsieh, Patrick C; Wang, Jeffrey C; Rolfe, Kevin

2018-02-01

To review the current understanding and data of sagittal balance and alignment considerations in paraplegic patients. A PubMed literature search was conducted to identify all relevant articles relating to sagittal alignment and sagittal balance considerations in paraplegic and spinal cord injury patients. While there are numerous studies and publications on sagittal balance in the ambulatory patient with spinal deformity or complex spine disorders, there is paucity of the literature on "normal" sagittal balance in the paraplegic patients. Studies have reported significantly alterations of the sagittal alignment parameters in the non-ambulatory paraplegic patients compared to ambulatory patients. The variability of the alignment changes is related to the differences in the level of the spinal cord injury and their differences in the activations of truncal muscles to allow functional movements in those patients, particularly in optimizing sitting and transferring. Surgical goal in treating paraplegic patients with complex pathologies should not be solely directed to achieve the "normal" radiographic parameters of sagittal alignment in the ambulatory patients. The goal should be to maintain good coronal balance to allow ideal sitting position and to preserve motion segment to optimize functions of paraplegia patients. Current available literature data have not defined normal sagittal parameters for paraplegic patients. There are significant differences in postural sagittal parameters and muscle activations in paraplegic and non-spinal cord injury patients that can lead to differences in sagittal alignment and balance. Treatment goal in spine surgery for paraplegic patients should address their global function, sitting balance, and ability to perform self-care rather than the accepted radiographic parameters for adult spinal deformity in ambulatory patients.

Optimization of rainfall networks using information entropy and temporal variability analysis

NASA Astrophysics Data System (ADS)

Wang, Wenqi; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin

2018-04-01

Rainfall networks are the most direct sources of precipitation data and their optimization and evaluation are essential and important. Information entropy can not only represent the uncertainty of rainfall distribution but can also reflect the correlation and information transmission between rainfall stations. Using entropy this study performs optimization of rainfall networks that are of similar size located in two big cities in China, Shanghai (in Yangtze River basin) and Xi'an (in Yellow River basin), with respect to temporal variability analysis. Through an easy-to-implement greedy ranking algorithm based on the criterion called, Maximum Information Minimum Redundancy (MIMR), stations of the networks in the two areas (each area is further divided into two subareas) are ranked during sliding inter-annual series and under different meteorological conditions. It is found that observation series with different starting days affect the ranking, alluding to the temporal variability during network evaluation. We propose a dynamic network evaluation framework for considering temporal variability, which ranks stations under different starting days with a fixed time window (1-year, 2-year, and 5-year). Therefore, we can identify rainfall stations which are temporarily of importance or redundancy and provide some useful suggestions for decision makers. The proposed framework can serve as a supplement for the primary MIMR optimization approach. In addition, during different periods (wet season or dry season) the optimal network from MIMR exhibits differences in entropy values and the optimal network from wet season tended to produce higher entropy values. Differences in spatial distribution of the optimal networks suggest that optimizing the rainfall network for changing meteorological conditions may be more recommended.

Current progress and technical challenges of flexible liquid crystal displays

NASA Astrophysics Data System (ADS)

Fujikake, Hideo; Sato, Hiroto

2009-02-01

We focused on several technical approaches to flexible liquid crystal (LC) display in this report. We have been developing flexible displays using plastic film substrates based on polymer-dispersed LC technology with molecular alignment control. In our representative devices, molecular-aligned polymer walls keep plastic-substrate gap constant without LC alignment disorder, and aligned polymer networks create monostable switching of fast-response ferroelectric LC (FLC) for grayscale capability. In the fabrication process, a high-viscosity FLC/monomer solution was printed, sandwiched and pressed between plastic substrates. Then the polymer walls and networks were sequentially formed based on photo-polymerization-induced phase separation in the nematic phase by two exposure processes of patterned and uniform ultraviolet light. The two flexible backlight films of direct illumination and light-guide methods using small three-primary-color light-emitting diodes were fabricated to obtain high-visibility display images. The fabricated flexible FLC panels were driven by external transistor arrays, internal organic thin film transistor (TFT) arrays, and poly-Si TFT arrays. We achieved full-color moving-image displays using the flexible FLC panel and the flexible backlight film based on field-sequential-color driving technique. Otherwise, for backlight-free flexible LC displays, flexible reflective devices of twisted guest-host nematic LC and cholesteric LC were discussed with molecular-aligned polymer walls. Singlesubstrate device structure and fabrication method using self-standing polymer-stabilized nematic LC film and polymer ceiling layer were also proposed for obtaining LC devices with excellent flexibility.

Alignment methods: strategies, challenges, benchmarking, and comparative overview.

PubMed

Löytynoja, Ari

2012-01-01

Comparative evolutionary analyses of molecular sequences are solely based on the identities and differences detected between homologous characters. Errors in this homology statement, that is errors in the alignment of the sequences, are likely to lead to errors in the downstream analyses. Sequence alignment and phylogenetic inference are tightly connected and many popular alignment programs use the phylogeny to divide the alignment problem into smaller tasks. They then neglect the phylogenetic tree, however, and produce alignments that are not evolutionarily meaningful. The use of phylogeny-aware methods reduces the error but the resulting alignments, with evolutionarily correct representation of homology, can challenge the existing practices and methods for viewing and visualising the sequences. The inter-dependency of alignment and phylogeny can be resolved by joint estimation of the two; methods based on statistical models allow for inferring the alignment parameters from the data and correctly take into account the uncertainty of the solution but remain computationally challenging. Widely used alignment methods are based on heuristic algorithms and unlikely to find globally optimal solutions. The whole concept of one correct alignment for the sequences is questionable, however, as there typically exist vast numbers of alternative, roughly equally good alignments that should also be considered. This uncertainty is hidden by many popular alignment programs and is rarely correctly taken into account in the downstream analyses. The quest for finding and improving the alignment solution is complicated by the lack of suitable measures of alignment goodness. The difficulty of comparing alternative solutions also affects benchmarks of alignment methods and the results strongly depend on the measure used. As the effects of alignment error cannot be predicted, comparing the alignments' performance in downstream analyses is recommended.

Wireless Sensor Network Optimization: Multi-Objective Paradigm

PubMed Central

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-01-01

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks. PMID:26205271

A molecular-field-based similarity study of non-nucleoside HIV-1 reverse transcriptase inhibitors

NASA Astrophysics Data System (ADS)

Mestres, Jordi; Rohrer, Douglas C.; Maggiora, Gerald M.

1999-01-01

This article describes a molecular-field-based similarity method for aligning molecules by matching their steric and electrostatic fields and an application of the method to the alignment of three structurally diverse non-nucleoside HIV-1 reverse transcriptase inhibitors. A brief description of the method, as implemented in the program MIMIC, is presented, including a discussion of pairwise and multi-molecule similarity-based matching. The application provides an example that illustrates how relative binding orientations of molecules can be determined in the absence of detailed structural information on their target protein. In the particular system studied here, availability of the X-ray crystal structures of the respective ligand-protein complexes provides a means for constructing an 'experimental model' of the relative binding orientations of the three inhibitors. The experimental model is derived by using MIMIC to align the steric fields of the three protein P66 subunit main chains, producing an overlay with a 1.41 Å average rms distance between the corresponding Cα's in the three chains. The inter-chain residue similarities for the backbone structures show that the main-chain conformations are conserved in the region of the inhibitor-binding site, with the major deviations located primarily in the 'finger' and RNase H regions. The resulting inhibitor structure overlay provides an experimental-based model that can be used to evaluate the quality of the direct a priori inhibitor alignment obtained using MIMIC. It is found that the 'best' pairwise alignments do not always correspond to the experimental model alignments. Therefore, simply combining the best pairwise alignments will not necessarily produce the optimal multi-molecule alignment. However, the best simultaneous three-molecule alignment was found to reproduce the experimental inhibitor alignment model. A pairwise consistency index has been derived which gauges the quality of combining the pairwise alignments and aids in efficiently forming the optimal multi-molecule alignment analysis. Two post-alignment procedures are described that provide information on feature-based and field-based pharmacophoric patterns. The former corresponds to traditional pharmacophore models and is derived from the contribution of individual atoms to the total similarity. The latter is based on molecular regions rather than atoms and is constructed by computing the percent contribution to the similarity of individual points in a regular lattice surrounding the molecules, which when contoured and colored visually depict regions of highly conserved similarity. A discussion of how the information provided by each of the procedures is useful in drug design is also presented.

Toward Optimal Transport Networks

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia; Kincaid, Rex K.; Vargo, Erik P.

2008-01-01

Strictly evolutionary approaches to improving the air transport system a highly complex network of interacting systems no longer suffice in the face of demand that is projected to double or triple in the near future. Thus evolutionary approaches should be augmented with active design methods. The ability to actively design, optimize and control a system presupposes the existence of predictive modeling and reasonably well-defined functional dependences between the controllable variables of the system and objective and constraint functions for optimization. Following recent advances in the studies of the effects of network topology structure on dynamics, we investigate the performance of dynamic processes on transport networks as a function of the first nontrivial eigenvalue of the network's Laplacian, which, in turn, is a function of the network s connectivity and modularity. The last two characteristics can be controlled and tuned via optimization. We consider design optimization problem formulations. We have developed a flexible simulation of network topology coupled with flows on the network for use as a platform for computational experiments.

Dynamic mobility applications policy analysis : policy and institutional issues for intelligent network flow optimization (INFLO).

DOT National Transportation Integrated Search

2014-12-01

The report documents policy considerations for the Intelligent Network Flow Optimization (INFLO) connected vehicle applications bundle. INFLO aims to optimize network flow on freeways and arterials by informing motorists of existing and impendi...

SANSparallel: interactive homology search against Uniprot

PubMed Central

Somervuo, Panu; Holm, Liisa

2015-01-01

Proteins evolve by mutations and natural selection. The network of sequence similarities is a rich source for mining homologous relationships that inform on protein structure and function. There are many servers available to browse the network of homology relationships but one has to wait up to a minute for results. The SANSparallel webserver provides protein sequence database searches with immediate response and professional alignment visualization by third-party software. The output is a list, pairwise alignment or stacked alignment of sequence-similar proteins from Uniprot, UniRef90/50, Swissprot or Protein Data Bank. The stacked alignments are viewed in Jalview or as sequence logos. The database search uses the suffix array neighborhood search (SANS) method, which has been re-implemented as a client-server, improved and parallelized. The method is extremely fast and as sensitive as BLAST above 50% sequence identity. Benchmarks show that the method is highly competitive compared to previously published fast database search programs: UBLAST, DIAMOND, LAST, LAMBDA, RAPSEARCH2 and BLAT. The web server can be accessed interactively or programmatically at http://ekhidna2.biocenter.helsinki.fi/cgi-bin/sans/sans.cgi. It can be used to make protein functional annotation pipelines more efficient, and it is useful in interactive exploration of the detailed evidence supporting the annotation of particular proteins of interest. PMID:25855811

Optimized mirror shape tuning using beam weightings based on distance, angle of incidence, reflectivity, and power.

PubMed

Goldberg, Kenneth A; Yashchuk, Valeriy V

2016-05-01

For glancing-incidence optical systems, such as short-wavelength optics used for nano-focusing, incorporating physical factors in the calculations used for shape optimization can improve performance. Wavefront metrology, including the measurement of a mirror's shape or slope, is routinely used as input for mirror figure optimization on mirrors that can be bent, actuated, positioned, or aligned. Modeling shows that when the incident power distribution, distance from focus, angle of incidence, and the spatially varying reflectivity are included in the optimization, higher Strehl ratios can be achieved. Following the works of Maréchal and Mahajan, optimization of the Strehl ratio (for peak intensity with a coherently illuminated system) occurs when the expectation value of the phase error's variance is minimized. We describe an optimization procedure based on regression analysis that incorporates these physical parameters. This approach is suitable for coherently illuminated systems of nearly diffraction-limited quality. Mathematically, this work is an enhancement of the methods commonly applied for ex situ alignment based on uniform weighting of all points on the surface (or a sub-region of the surface). It follows a similar approach to the optimization of apodized and non-uniformly illuminated optical systems. Significantly, it reaches a different conclusion than a more recent approach based on minimization of focal plane ray errors.

Deployment-based lifetime optimization for linear wireless sensor networks considering both retransmission and discrete power control.

PubMed

Li, Ruiying; Ma, Wenting; Huang, Ning; Kang, Rui

2017-01-01

A sophisticated method for node deployment can efficiently reduce the energy consumption of a Wireless Sensor Network (WSN) and prolong the corresponding network lifetime. Pioneers have proposed many node deployment based lifetime optimization methods for WSNs, however, the retransmission mechanism and the discrete power control strategy, which are widely used in practice and have large effect on the network energy consumption, are often neglected and assumed as a continuous one, respectively, in the previous studies. In this paper, both retransmission and discrete power control are considered together, and a more realistic energy-consumption-based network lifetime model for linear WSNs is provided. Using this model, we then propose a generic deployment-based optimization model that maximizes network lifetime under coverage, connectivity and transmission rate success constraints. The more accurate lifetime evaluation conduces to a longer optimal network lifetime in the realistic situation. To illustrate the effectiveness of our method, both one-tiered and two-tiered uniformly and non-uniformly distributed linear WSNs are optimized in our case studies, and the comparisons between our optimal results and those based on relatively inaccurate lifetime evaluation show the advantage of our method when investigating WSN lifetime optimization problems.

Group sparse multiview patch alignment framework with view consistency for image classification.

PubMed

Gui, Jie; Tao, Dacheng; Sun, Zhenan; Luo, Yong; You, Xinge; Tang, Yuan Yan

2014-07-01

No single feature can satisfactorily characterize the semantic concepts of an image. Multiview learning aims to unify different kinds of features to produce a consensual and efficient representation. This paper redefines part optimization in the patch alignment framework (PAF) and develops a group sparse multiview patch alignment framework (GSM-PAF). The new part optimization considers not only the complementary properties of different views, but also view consistency. In particular, view consistency models the correlations between all possible combinations of any two kinds of view. In contrast to conventional dimensionality reduction algorithms that perform feature extraction and feature selection independently, GSM-PAF enjoys joint feature extraction and feature selection by exploiting l(2,1)-norm on the projection matrix to achieve row sparsity, which leads to the simultaneous selection of relevant features and learning transformation, and thus makes the algorithm more discriminative. Experiments on two real-world image data sets demonstrate the effectiveness of GSM-PAF for image classification.

Vertically aligned N-doped CNTs growth using Taguchi experimental design

NASA Astrophysics Data System (ADS)

Silva, Ricardo M.; Fernandes, António J. S.; Ferro, Marta C.; Pinna, Nicola; Silva, Rui F.

2015-07-01

The Taguchi method with a parameter design L9 orthogonal array was implemented for optimizing the nitrogen incorporation in the structure of vertically aligned N-doped CNTs grown by thermal chemical deposition (TCVD). The maximization of the ID/IG ratio of the Raman spectra was selected as the target value. As a result, the optimal deposition configuration was NH3 = 90 sccm, growth temperature = 825 °C and catalyst pretreatment time of 2 min, the first parameter having the main effect on nitrogen incorporation. A confirmation experiment with these values was performed, ratifying the predicted ID/IG ratio of 1.42. Scanning electron microscopy (SEM) characterization revealed a uniform completely vertically aligned array of multiwalled CNTs which individually exhibit a bamboo-like structure, consisting of periodically curved graphitic layers, as depicted by high resolution transmission electron microscopy (HRTEM). The X-ray photoelectron spectroscopy (XPS) results indicated a 2.00 at.% of N incorporation in the CNTs in pyridine-like and graphite-like, as the predominant species.

Optimization methods of pulse-to-pulse alignment using femtosecond pulse laser based on temporal coherence function for practical distance measurement

NASA Astrophysics Data System (ADS)

Liu, Yang; Yang, Linghui; Guo, Yin; Lin, Jiarui; Cui, Pengfei; Zhu, Jigui

2018-02-01

An interferometer technique based on temporal coherence function of femtosecond pulses is demonstrated for practical distance measurement. Here, the pulse-to-pulse alignment is analyzed for large delay distance measurement. Firstly, a temporal coherence function model between two femtosecond pulses is developed in the time domain for the dispersive unbalanced Michelson interferometer. Then, according to this model, the fringes analysis and the envelope extraction process are discussed. Meanwhile, optimization methods of pulse-to-pulse alignment for practical long distance measurement are presented. The order of the curve fitting and the selection of points for envelope extraction are analyzed. Furthermore, an averaging method based on the symmetry of the coherence function is demonstrated. Finally, the performance of the proposed methods is evaluated in the absolute distance measurement of 20 μ m with path length difference of 9 m. The improvement of standard deviation in experimental results shows that these approaches have the potential for practical distance measurement.

Representing and comparing protein structures as paths in three-dimensional space

PubMed Central

Zhi, Degui; Krishna, S Sri; Cao, Haibo; Pevzner, Pavel; Godzik, Adam

2006-01-01

Background Most existing formulations of protein structure comparison are based on detailed atomic level descriptions of protein structures and bypass potential insights that arise from a higher-level abstraction. Results We propose a structure comparison approach based on a simplified representation of proteins that describes its three-dimensional path by local curvature along the generalized backbone of the polypeptide. We have implemented a dynamic programming procedure that aligns curvatures of proteins by optimizing a defined sum turning angle deviation measure. Conclusion Although our procedure does not directly optimize global structural similarity as measured by RMSD, our benchmarking results indicate that it can surprisingly well recover the structural similarity defined by structure classification databases and traditional structure alignment programs. In addition, our program can recognize similarities between structures with extensive conformation changes that are beyond the ability of traditional structure alignment programs. We demonstrate the applications of procedure to several contexts of structure comparison. An implementation of our procedure, CURVE, is available as a public webserver. PMID:17052359

Models and algorithm of optimization launch and deployment of virtual network functions in the virtual data center

NASA Astrophysics Data System (ADS)

Bolodurina, I. P.; Parfenov, D. I.

2017-10-01

The goal of our investigation is optimization of network work in virtual data center. The advantage of modern infrastructure virtualization lies in the possibility to use software-defined networks. However, the existing optimization of algorithmic solutions does not take into account specific features working with multiple classes of virtual network functions. The current paper describes models characterizing the basic structures of object of virtual data center. They including: a level distribution model of software-defined infrastructure virtual data center, a generalized model of a virtual network function, a neural network model of the identification of virtual network functions. We also developed an efficient algorithm for the optimization technology of containerization of virtual network functions in virtual data center. We propose an efficient algorithm for placing virtual network functions. In our investigation we also generalize the well renowned heuristic and deterministic algorithms of Karmakar-Karp.

Smart-Grid Backbone Network Real-Time Delay Reduction via Integer Programming.

PubMed

Pagadrai, Sasikanth; Yilmaz, Muhittin; Valluri, Pratyush

2016-08-01

This research investigates an optimal delay-based virtual topology design using integer linear programming (ILP), which is applied to the current backbone networks such as smart-grid real-time communication systems. A network traffic matrix is applied and the corresponding virtual topology problem is solved using the ILP formulations that include a network delay-dependent objective function and lightpath routing, wavelength assignment, wavelength continuity, flow routing, and traffic loss constraints. The proposed optimization approach provides an efficient deterministic integration of intelligent sensing and decision making, and network learning features for superior smart grid operations by adaptively responding the time-varying network traffic data as well as operational constraints to maintain optimal virtual topologies. A representative optical backbone network has been utilized to demonstrate the proposed optimization framework whose simulation results indicate that superior smart-grid network performance can be achieved using commercial networks and integer programming.

Optimization of cascading failure on complex network based on NNIA

NASA Astrophysics Data System (ADS)

Zhu, Qian; Zhu, Zhiliang; Qi, Yi; Yu, Hai; Xu, Yanjie

2018-07-01

Recently, the robustness of networks under cascading failure has attracted extensive attention. Different from previous studies, we concentrate on how to improve the robustness of the networks from the perspective of intelligent optimization. We establish two multi-objective optimization models that comprehensively consider the operational cost of the edges in the networks and the robustness of the networks. The NNIA (Non-dominated Neighbor Immune Algorithm) is applied to solve the optimization models. We finished simulations of the Barabási-Albert (BA) network and Erdös-Rényi (ER) network. In the solutions, we find the edges that can facilitate the propagation of cascading failure and the edges that can suppress the propagation of cascading failure. From the conclusions, we take optimal protection measures to weaken the damage caused by cascading failures. We also consider actual situations of operational cost feasibility of the edges. People can make a more practical choice based on the operational cost. Our work will be helpful in the design of highly robust networks or improvement of the robustness of networks in the future.

Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases

PubMed Central

Ritchie, Marylyn D; White, Bill C; Parker, Joel S; Hahn, Lance W; Moore, Jason H

2003-01-01

Background Appropriate definition of neural network architecture prior to data analysis is crucial for successful data mining. This can be challenging when the underlying model of the data is unknown. The goal of this study was to determine whether optimizing neural network architecture using genetic programming as a machine learning strategy would improve the ability of neural networks to model and detect nonlinear interactions among genes in studies of common human diseases. Results Using simulated data, we show that a genetic programming optimized neural network approach is able to model gene-gene interactions as well as a traditional back propagation neural network. Furthermore, the genetic programming optimized neural network is better than the traditional back propagation neural network approach in terms of predictive ability and power to detect gene-gene interactions when non-functional polymorphisms are present. Conclusion This study suggests that a machine learning strategy for optimizing neural network architecture may be preferable to traditional trial-and-error approaches for the identification and characterization of gene-gene interactions in common, complex human diseases. PMID:12846935

Data-driven reconstruction of directed networks

NASA Astrophysics Data System (ADS)

Hempel, Sabrina; Koseska, Aneta; Nikoloski, Zoran

2013-06-01

We investigate the properties of a recently introduced asymmetric association measure, called inner composition alignment (IOTA), aimed at inferring regulatory links (couplings). We show that the measure can be used to determine the direction of coupling, detect superfluous links, and to account for autoregulation. In addition, the measure can be extended to infer the type of regulation (positive or negative). The capabilities of IOTA to correctly infer couplings together with their directionality are compared against Kendall's rank correlation for time series of different lengths, particularly focussing on biological examples. We demonstrate that an extended version of the measure, bidirectional inner composition alignment (biIOTA), increases the accuracy of the network reconstruction for short time series. Finally, we discuss the applicability of the measure to infer couplings in chaotic systems.

Network anomaly detection system with optimized DS evidence theory.

PubMed

Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu

2014-01-01

Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network-complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each sensor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly.

A greedy, graph-based algorithm for the alignment of multiple homologous gene lists.

PubMed

Fostier, Jan; Proost, Sebastian; Dhoedt, Bart; Saeys, Yvan; Demeester, Piet; Van de Peer, Yves; Vandepoele, Klaas

2011-03-15

Many comparative genomics studies rely on the correct identification of homologous genomic regions using accurate alignment tools. In such case, the alphabet of the input sequences consists of complete genes, rather than nucleotides or amino acids. As optimal multiple sequence alignment is computationally impractical, a progressive alignment strategy is often employed. However, such an approach is susceptible to the propagation of alignment errors in early pairwise alignment steps, especially when dealing with strongly diverged genomic regions. In this article, we present a novel accurate and efficient greedy, graph-based algorithm for the alignment of multiple homologous genomic segments, represented as ordered gene lists. Based on provable properties of the graph structure, several heuristics are developed to resolve local alignment conflicts that occur due to gene duplication and/or rearrangement events on the different genomic segments. The performance of the algorithm is assessed by comparing the alignment results of homologous genomic segments in Arabidopsis thaliana to those obtained by using both a progressive alignment method and an earlier graph-based implementation. Especially for datasets that contain strongly diverged segments, the proposed method achieves a substantially higher alignment accuracy, and proves to be sufficiently fast for large datasets including a few dozens of eukaryotic genomes. http://bioinformatics.psb.ugent.be/software. The algorithm is implemented as a part of the i-ADHoRe 3.0 package.

Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey

PubMed Central

Adnan, Md. Akhtaruzzaman; Razzaque, Mohammd Abdur; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

2014-01-01

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted. PMID:24368702

Fast-switching chiral nematic liquid-crystal mode with polymer-sustained twisted vertical alignment.

PubMed

Chang, Kai-Han; Joshi, Vinay; Chien, Liang-Chy

2017-04-01

We demonstrate a fast-switching liquid-crystal mode with polymer-sustained twisted vertical alignment. By optimizing the polymerization condition, a polymer microstructure with controlled orientation is produced. The polymer microstructure not only synergistically suppresses the optical bounce during field-induced homeotropic-twist transition but also shortens the response time significantly. Theoretical analyses validate that the ground state free energy density is modified by the aligning field of the polymer microstructure, which affects the driving voltage of the device. The outcomes of this paper will enable the development of fast-switching and achromatic electro-optical and photonic devices.

Fast-switching chiral nematic liquid-crystal mode with polymer-sustained twisted vertical alignment

NASA Astrophysics Data System (ADS)

Chang, Kai-Han; Joshi, Vinay; Chien, Liang-Chy

2017-04-01

We demonstrate a fast-switching liquid-crystal mode with polymer-sustained twisted vertical alignment. By optimizing the polymerization condition, a polymer microstructure with controlled orientation is produced. The polymer microstructure not only synergistically suppresses the optical bounce during field-induced homeotropic-twist transition but also shortens the response time significantly. Theoretical analyses validate that the ground state free energy density is modified by the aligning field of the polymer microstructure, which affects the driving voltage of the device. The outcomes of this paper will enable the development of fast-switching and achromatic electro-optical and photonic devices.

FPGA-based protein sequence alignment : A review

NASA Astrophysics Data System (ADS)

Isa, Mohd. Nazrin Md.; Muhsen, Ku Noor Dhaniah Ku; Saiful Nurdin, Dayana; Ahmad, Muhammad Imran; Anuar Zainol Murad, Sohiful; Nizam Mohyar, Shaiful; Harun, Azizi; Hussin, Razaidi

2017-11-01

Sequence alignment have been optimized using several techniques in order to accelerate the computation time to obtain the optimal score by implementing DP-based algorithm into hardware such as FPGA-based platform. During hardware implementation, there will be performance challenges such as the frequent memory access and highly data dependent in computation process. Therefore, investigation in processing element (PE) configuration where involves more on memory access in load or access the data (substitution matrix, query sequence character) and the PE configuration time will be the main focus in this paper. There are various approaches to enhance the PE configuration performance that have been done in previous works such as by using serial configuration chain and parallel configuration chain i.e. the configuration data will be loaded into each PEs sequentially and simultaneously respectively. Some researchers have proven that the performance using parallel configuration chain has optimized both the configuration time and area.

Investigation of compaction and permeability during the out-of-autoclave and vacuum-bag-only manufacturing of a laminate composite with aligned carbon nanofibers

NASA Astrophysics Data System (ADS)

Mann, Erin

Both industry and commercial entities are in the process of using more lightweight composites. Fillers, such as fibers, nanofibers and other nanoconstituents in polymer matrix composites have been proven to enhance the properties of composites and are still being studied in order to optimize the benefits. Further optimization can be studied during the manufacturing process. The air permeability during the out-of-autoclave-vacuum-bag-only (OOA-VBO) cure method is an important property to understand during the optimization of manufacturing processes. Changes in the manufacturing process can improve or decrease composite quality depending on the ability of the composite to evacuate gases such as air and moisture during curing. Therefore, in this study, the axial permeability of a prepreg stack was experimentally studied. Three types of samples were studied: control (no carbon nanofiber (CNF) modification), unaligned CNF modified and aligned CNF modified samples.

Improving the quality of biomarker candidates in untargeted metabolomics via peak table-based alignment of comprehensive two-dimensional gas chromatography-mass spectrometry data

PubMed Central

Bean, Heather D.; Hill, Jane E.; Dimandja, Jean-Marie D.

2015-01-01

The potential of high-resolution analytical technologies like GC×GC/TOF MS in untargeted metabolomics and biomarker discovery has been limited by the development of fully automated software that can efficiently align and extract information from multiple chromatographic data sets. In this work we report the first investigation on a peak-by-peak basis of the chromatographic factors that impact GC×GC data alignment. A representative set of 16 compounds of different chromatographic characteristics were followed through the alignment of 63 GC×GC chromatograms. We found that varying the mass spectral match parameter had a significant influence on the alignment for poorly- resolved peaks, especially those at the extremes of the detector linear range, and no influence on well- chromatographed peaks. Therefore, optimized chromatography is required for proper GC×GC data alignment. Based on these observations, a workflow is presented for the conservative selection of biomarker candidates from untargeted metabolomics analyses. PMID:25857541

Feature-based Alignment of Volumetric Multi-modal Images

PubMed Central

Toews, Matthew; Zöllei, Lilla; Wells, William M.

2014-01-01

This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

CAB-Align: A Flexible Protein Structure Alignment Method Based on the Residue-Residue Contact Area.

PubMed

Terashi, Genki; Takeda-Shitaka, Mayuko

2015-01-01

Proteins are flexible, and this flexibility has an essential functional role. Flexibility can be observed in loop regions, rearrangements between secondary structure elements, and conformational changes between entire domains. However, most protein structure alignment methods treat protein structures as rigid bodies. Thus, these methods fail to identify the equivalences of residue pairs in regions with flexibility. In this study, we considered that the evolutionary relationship between proteins corresponds directly to the residue-residue physical contacts rather than the three-dimensional (3D) coordinates of proteins. Thus, we developed a new protein structure alignment method, contact area-based alignment (CAB-align), which uses the residue-residue contact area to identify regions of similarity. The main purpose of CAB-align is to identify homologous relationships at the residue level between related protein structures. The CAB-align procedure comprises two main steps: First, a rigid-body alignment method based on local and global 3D structure superposition is employed to generate a sufficient number of initial alignments. Then, iterative dynamic programming is executed to find the optimal alignment. We evaluated the performance and advantages of CAB-align based on four main points: (1) agreement with the gold standard alignment, (2) alignment quality based on an evolutionary relationship without 3D coordinate superposition, (3) consistency of the multiple alignments, and (4) classification agreement with the gold standard classification. Comparisons of CAB-align with other state-of-the-art protein structure alignment methods (TM-align, FATCAT, and DaliLite) using our benchmark dataset showed that CAB-align performed robustly in obtaining high-quality alignments and generating consistent multiple alignments with high coverage and accuracy rates, and it performed extremely well when discriminating between homologous and nonhomologous pairs of proteins in both single and multi-domain comparisons. The CAB-align software is freely available to academic users as stand-alone software at http://www.pharm.kitasato-u.ac.jp/bmd/bmd/Publications.html.

Designing Industrial Networks Using Ecological Food Web Metrics.

PubMed

Layton, Astrid; Bras, Bert; Weissburg, Marc

2016-10-18

Biologically Inspired Design (biomimicry) and Industrial Ecology both look to natural systems to enhance the sustainability and performance of engineered products, systems and industries. Bioinspired design (BID) traditionally has focused on a unit operation and single product level. In contrast, this paper describes how principles of network organization derived from analysis of ecosystem properties can be applied to industrial system networks. Specifically, this paper examines the applicability of particular food web matrix properties as design rules for economically and biologically sustainable industrial networks, using an optimization model developed for a carpet recycling network. Carpet recycling network designs based on traditional cost and emissions based optimization are compared to designs obtained using optimizations based solely on ecological food web metrics. The analysis suggests that networks optimized using food web metrics also were superior from a traditional cost and emissions perspective; correlations between optimization using ecological metrics and traditional optimization ranged generally from 0.70 to 0.96, with flow-based metrics being superior to structural parameters. Four structural food parameters provided correlations nearly the same as that obtained using all structural parameters, but individual structural parameters provided much less satisfactory correlations. The analysis indicates that bioinspired design principles from ecosystems can lead to both environmentally and economically sustainable industrial resource networks, and represent guidelines for designing sustainable industry networks.

The Relationship between Distributed Leadership and Teachers' Academic Optimism

ERIC Educational Resources Information Center

Mascall, Blair; Leithwood, Kenneth; Straus, Tiiu; Sacks, Robin

2008-01-01

Purpose: The goal of this study was to examine the relationship between four patterns of distributed leadership and a modified version of a variable Hoy et al. have labeled "teachers' academic optimism." The distributed leadership patterns reflect the extent to which the performance of leadership functions is consciously aligned across…

Proposing an Optimal Learning Architecture for the Digital Enterprise.

ERIC Educational Resources Information Center

O'Driscoll, Tony

2003-01-01

Discusses the strategic role of learning in information age organizations; analyzes parallels between the application of technology to business and the application of technology to learning; and proposes a learning architecture that aligns with the knowledge-based view of the firm and optimizes the application of technology to achieve proficiency…

Sensitivity Analysis of Genetic Algorithm Parameters for Optimal Groundwater Monitoring Network Design

NASA Astrophysics Data System (ADS)

Abdeh-Kolahchi, A.; Satish, M.; Datta, B.

2004-05-01

A state art groundwater monitoring network design is introduced. The method combines groundwater flow and transport results with optimization Genetic Algorithm (GA) to identify optimal monitoring well locations. Optimization theory uses different techniques to find a set of parameter values that minimize or maximize objective functions. The suggested groundwater optimal monitoring network design is based on the objective of maximizing the probability of tracking a transient contamination plume by determining sequential monitoring locations. The MODFLOW and MT3DMS models included as separate modules within the Groundwater Modeling System (GMS) are used to develop three dimensional groundwater flow and contamination transport simulation. The groundwater flow and contamination simulation results are introduced as input to the optimization model, using Genetic Algorithm (GA) to identify the groundwater optimal monitoring network design, based on several candidate monitoring locations. The groundwater monitoring network design model is used Genetic Algorithms with binary variables representing potential monitoring location. As the number of decision variables and constraints increase, the non-linearity of the objective function also increases which make difficulty to obtain optimal solutions. The genetic algorithm is an evolutionary global optimization technique, which is capable of finding the optimal solution for many complex problems. In this study, the GA approach capable of finding the global optimal solution to a groundwater monitoring network design problem involving 18.4X 1018 feasible solutions will be discussed. However, to ensure the efficiency of the solution process and global optimality of the solution obtained using GA, it is necessary that appropriate GA parameter values be specified. The sensitivity analysis of genetic algorithms parameters such as random number, crossover probability, mutation probability, and elitism are discussed for solution of monitoring network design.

Neural network for nonsmooth pseudoconvex optimization with general convex constraints.

PubMed

Bian, Wei; Ma, Litao; Qin, Sitian; Xue, Xiaoping

2018-05-01

In this paper, a one-layer recurrent neural network is proposed for solving a class of nonsmooth, pseudoconvex optimization problems with general convex constraints. Based on the smoothing method, we construct a new regularization function, which does not depend on any information of the feasible region. Thanks to the special structure of the regularization function, we prove the global existence, uniqueness and "slow solution" character of the state of the proposed neural network. Moreover, the state solution of the proposed network is proved to be convergent to the feasible region in finite time and to the optimal solution set of the related optimization problem subsequently. In particular, the convergence of the state to an exact optimal solution is also considered in this paper. Numerical examples with simulation results are given to show the efficiency and good characteristics of the proposed network. In addition, some preliminary theoretical analysis and application of the proposed network for a wider class of dynamic portfolio optimization are included. Copyright © 2018 Elsevier Ltd. All rights reserved.

Energy-Aware Multipath Routing Scheme Based on Particle Swarm Optimization in Mobile Ad Hoc Networks

PubMed Central

Robinson, Y. Harold; Rajaram, M.

2015-01-01

Mobile ad hoc network (MANET) is a collection of autonomous mobile nodes forming an ad hoc network without fixed infrastructure. Dynamic topology property of MANET may degrade the performance of the network. However, multipath selection is a great challenging task to improve the network lifetime. We proposed an energy-aware multipath routing scheme based on particle swarm optimization (EMPSO) that uses continuous time recurrent neural network (CTRNN) to solve optimization problems. CTRNN finds the optimal loop-free paths to solve link disjoint paths in a MANET. The CTRNN is used as an optimum path selection technique that produces a set of optimal paths between source and destination. In CTRNN, particle swarm optimization (PSO) method is primly used for training the RNN. The proposed scheme uses the reliability measures such as transmission cost, energy factor, and the optimal traffic ratio between source and destination to increase routing performance. In this scheme, optimal loop-free paths can be found using PSO to seek better link quality nodes in route discovery phase. PSO optimizes a problem by iteratively trying to get a better solution with regard to a measure of quality. The proposed scheme discovers multiple loop-free paths by using PSO technique. PMID:26819966

Assembly and alignment method for optimized spatial resolution of off-axis three-mirror fore optics of hyperspectral imager.

PubMed

Kim, Youngsoo; Hong, Jinsuk; Choi, Byungin; Lee, Jong-Ung; Kim, Yeonsoo; Kim, Hyunsook

2017-08-21

A fore optics for the hyperspectral spectrometer is designed, manufactured, assembled, and aligned. The optics has a telecentric off-axis three-mirror configuration with a field of view wider than 14 degrees and an f-number as small as 2.3. The primary mirror (M1) and the secondary mirror (M2) are axially symmetric aspheric surfaces to minimize the sensitivity. The tertiary mirror (M3) is a decentered aspheric surface to minimize the coma and astigmatism aberration. The M2 also has a hole for the slit to maintain the optical performance while maximizing the telecentricity. To ensure the spatial resolution performance of the optical system, an alignment procedure is established to assemble and align the entrance slit of the spectrometer to the rear end of the fore optics. It has a great advantage to confirm and maintain the alignment integrity of the fore optics module throughout the alignment procedure. To perform the alignment procedure successfully, the precision movement control requirements are calculated and applied. As a result, the alignment goal of the RMS wave front error (WFE) to be smaller than 90 nm at all fields is achieved.

A Fast and Robust Extrinsic Calibration for RGB-D Camera Networks.

PubMed

Su, Po-Chang; Shen, Ju; Xu, Wanxin; Cheung, Sen-Ching S; Luo, Ying

2018-01-15

From object tracking to 3D reconstruction, RGB-Depth (RGB-D) camera networks play an increasingly important role in many vision and graphics applications. Practical applications often use sparsely-placed cameras to maximize visibility, while using as few cameras as possible to minimize cost. In general, it is challenging to calibrate sparse camera networks due to the lack of shared scene features across different camera views. In this paper, we propose a novel algorithm that can accurately and rapidly calibrate the geometric relationships across an arbitrary number of RGB-D cameras on a network. Our work has a number of novel features. First, to cope with the wide separation between different cameras, we establish view correspondences by using a spherical calibration object. We show that this approach outperforms other techniques based on planar calibration objects. Second, instead of modeling camera extrinsic calibration using rigid transformation, which is optimal only for pinhole cameras, we systematically test different view transformation functions including rigid transformation, polynomial transformation and manifold regression to determine the most robust mapping that generalizes well to unseen data. Third, we reformulate the celebrated bundle adjustment procedure to minimize the global 3D reprojection error so as to fine-tune the initial estimates. Finally, our scalable client-server architecture is computationally efficient: the calibration of a five-camera system, including data capture, can be done in minutes using only commodity PCs. Our proposed framework is compared with other state-of-the-arts systems using both quantitative measurements and visual alignment results of the merged point clouds.

A Fast and Robust Extrinsic Calibration for RGB-D Camera Networks †

PubMed Central

Shen, Ju; Xu, Wanxin; Luo, Ying

2018-01-01

From object tracking to 3D reconstruction, RGB-Depth (RGB-D) camera networks play an increasingly important role in many vision and graphics applications. Practical applications often use sparsely-placed cameras to maximize visibility, while using as few cameras as possible to minimize cost. In general, it is challenging to calibrate sparse camera networks due to the lack of shared scene features across different camera views. In this paper, we propose a novel algorithm that can accurately and rapidly calibrate the geometric relationships across an arbitrary number of RGB-D cameras on a network. Our work has a number of novel features. First, to cope with the wide separation between different cameras, we establish view correspondences by using a spherical calibration object. We show that this approach outperforms other techniques based on planar calibration objects. Second, instead of modeling camera extrinsic calibration using rigid transformation, which is optimal only for pinhole cameras, we systematically test different view transformation functions including rigid transformation, polynomial transformation and manifold regression to determine the most robust mapping that generalizes well to unseen data. Third, we reformulate the celebrated bundle adjustment procedure to minimize the global 3D reprojection error so as to fine-tune the initial estimates. Finally, our scalable client-server architecture is computationally efficient: the calibration of a five-camera system, including data capture, can be done in minutes using only commodity PCs. Our proposed framework is compared with other state-of-the-arts systems using both quantitative measurements and visual alignment results of the merged point clouds. PMID:29342968

Large-Area Cross-Aligned Silver Nanowire Electrodes for Flexible, Transparent, and Force-Sensitive Mechanochromic Touch Screens.

PubMed

Cho, Seungse; Kang, Saewon; Pandya, Ashish; Shanker, Ravi; Khan, Ziyauddin; Lee, Youngsu; Park, Jonghwa; Craig, Stephen L; Ko, Hyunhyub

2017-04-25

Silver nanowire (AgNW) networks are considered to be promising structures for use as flexible transparent electrodes for various optoelectronic devices. One important application of AgNW transparent electrodes is the flexible touch screens. However, the performances of flexible touch screens are still limited by the large surface roughness and low electrical to optical conductivity ratio of random network AgNW electrodes. In addition, although the perception of writing force on the touch screen enables a variety of different functions, the current technology still relies on the complicated capacitive force touch sensors. This paper demonstrates a simple and high-throughput bar-coating assembly technique for the fabrication of large-area (>20 × 20 cm 2 ), highly cross-aligned AgNW networks for transparent electrodes with the sheet resistance of 21.0 Ω sq -1 at 95.0% of optical transmittance, which compares favorably with that of random AgNW networks (sheet resistance of 21.0 Ω sq -1 at 90.4% of optical transmittance). As a proof of concept demonstration, we fabricate flexible, transparent, and force-sensitive touch screens using cross-aligned AgNW electrodes integrated with mechanochromic spiropyran-polydimethylsiloxane composite film. Our force-sensitive touch screens enable the precise monitoring of dynamic writings, tracing and drawing of underneath pictures, and perception of handwriting patterns with locally different writing forces. The suggested technique provides a robust and powerful platform for the controllable assembly of nanowires beyond the scale of conventional fabrication techniques, which can find diverse applications in multifunctional flexible electronic and optoelectronic devices.

A proposal of optimal sampling design using a modularity strategy

NASA Astrophysics Data System (ADS)

Simone, A.; Giustolisi, O.; Laucelli, D. B.

2016-08-01

In real water distribution networks (WDNs) are present thousands nodes and optimal placement of pressure and flow observations is a relevant issue for different management tasks. The planning of pressure observations in terms of spatial distribution and number is named sampling design and it was faced considering model calibration. Nowadays, the design of system monitoring is a relevant issue for water utilities e.g., in order to manage background leakages, to detect anomalies and bursts, to guarantee service quality, etc. In recent years, the optimal location of flow observations related to design of optimal district metering areas (DMAs) and leakage management purposes has been faced considering optimal network segmentation and the modularity index using a multiobjective strategy. Optimal network segmentation is the basis to identify network modules by means of optimal conceptual cuts, which are the candidate locations of closed gates or flow meters creating the DMAs. Starting from the WDN-oriented modularity index, as a metric for WDN segmentation, this paper proposes a new way to perform the sampling design, i.e., the optimal location of pressure meters, using newly developed sampling-oriented modularity index. The strategy optimizes the pressure monitoring system mainly based on network topology and weights assigned to pipes according to the specific technical tasks. A multiobjective optimization minimizes the cost of pressure meters while maximizing the sampling-oriented modularity index. The methodology is presented and discussed using the Apulian and Exnet networks.

Using confidence intervals to evaluate the focus alignment of spectrograph detector arrays.

PubMed

Sawyer, Travis W; Hawkins, Kyle S; Damento, Michael

2017-06-20

High-resolution spectrographs extract detailed spectral information of a sample and are frequently used in astronomy, laser-induced breakdown spectroscopy, and Raman spectroscopy. These instruments employ dispersive elements such as prisms and diffraction gratings to spatially separate different wavelengths of light, which are then detected by a charge-coupled device (CCD) or complementary metal-oxide-semiconductor (CMOS) detector array. Precise alignment along the optical axis (focus position) of the detector array is critical to maximize the instrumental resolution; however, traditional approaches of scanning the detector through focus lack a quantitative measure of precision, limiting the repeatability and relying on one's experience. Here we propose a method to evaluate the focus alignment of spectrograph detector arrays by establishing confidence intervals to measure the alignment precision. We show that propagation of uncertainty can be used to estimate the variance in an alignment, thus providing a quantitative and repeatable means to evaluate the precision and confidence of an alignment. We test the approach by aligning the detector array of a prototype miniature echelle spectrograph. The results indicate that the procedure effectively quantifies alignment precision, enabling one to objectively determine when an alignment has reached an acceptable level. This quantitative approach also provides a foundation for further optimization, including automated alignment. Furthermore, the procedure introduced here can be extended to other alignment techniques that rely on numerically fitting data to a model, providing a general framework for evaluating the precision of alignment methods.

Optimal resource allocation strategy for two-layer complex networks

NASA Astrophysics Data System (ADS)

Ma, Jinlong; Wang, Lixin; Li, Sufeng; Duan, Congwen; Liu, Yu

2018-02-01

We study the traffic dynamics on two-layer complex networks, and focus on its delivery capacity allocation strategy to enhance traffic capacity measured by the critical value Rc. With the limited packet-delivering capacity, we propose a delivery capacity allocation strategy which can balance the capacities of non-hub nodes and hub nodes to optimize the data flow. With the optimal value of parameter αc, the maximal network capacity is reached because most of the nodes have shared the appropriate delivery capacity by the proposed delivery capacity allocation strategy. Our work will be beneficial to network service providers to design optimal networked traffic dynamics.

Biaxial Anisotropic Material Development and Characterization using Rectangular to Square Waveguide

DTIC Science & Technology

2015-03-26

holder 68 Figure 29. Measurement Setup with Test port cables and Network Analyzer VNA and the waveguide adapters are torqued to specification with...calibrated torque wrenches and waveguide flanges are aligned using precision alignment pins. A TRL calibration is performed prior to measuring the sample as...set to 0.0001. This enables the Frequency domain solver to refine the mesh until the tolerance is achieved. Tightening the error tolerance results in

A generalized optimization principle for asymmetric branching in fluidic networks

PubMed Central

Stephenson, David

2016-01-01

When applied to a branching network, Murray’s law states that the optimal branching of vascular networks is achieved when the cube of the parent channel radius is equal to the sum of the cubes of the daughter channel radii. It is considered integral to understanding biological networks and for the biomimetic design of artificial fluidic systems. However, despite its ubiquity, we demonstrate that Murray’s law is only optimal (i.e. maximizes flow conductance per unit volume) for symmetric branching, where the local optimization of each individual channel corresponds to the global optimum of the network as a whole. In this paper, we present a generalized law that is valid for asymmetric branching, for any cross-sectional shape, and for a range of fluidic models. We verify our analytical solutions with the numerical optimization of a bifurcating fluidic network for the examples of laminar, turbulent and non-Newtonian fluid flows. PMID:27493583

Optimization of wireless sensor networks based on chicken swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Wang, Qingxi; Zhu, Lihua

2017-05-01

In order to reduce the energy consumption of wireless sensor network and improve the survival time of network, the clustering routing protocol of wireless sensor networks based on chicken swarm optimization algorithm was proposed. On the basis of LEACH agreement, it was improved and perfected that the points on the cluster and the selection of cluster head using the chicken group optimization algorithm, and update the location of chicken which fall into the local optimum by Levy flight, enhance population diversity, ensure the global search capability of the algorithm. The new protocol avoided the die of partial node of intensive using by making balanced use of the network nodes, improved the survival time of wireless sensor network. The simulation experiments proved that the protocol is better than LEACH protocol on energy consumption, also is better than that of clustering routing protocol based on particle swarm optimization algorithm.

Optimal exponential synchronization of general chaotic delayed neural networks: an LMI approach.

PubMed

Liu, Meiqin

2009-09-01

This paper investigates the optimal exponential synchronization problem of general chaotic neural networks with or without time delays by virtue of Lyapunov-Krasovskii stability theory and the linear matrix inequality (LMI) technique. This general model, which is the interconnection of a linear delayed dynamic system and a bounded static nonlinear operator, covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks (CNNs), bidirectional associative memory (BAM) networks, and recurrent multilayer perceptrons (RMLPs) with or without delays. Using the drive-response concept, time-delay feedback controllers are designed to synchronize two identical chaotic neural networks as quickly as possible. The control design equations are shown to be a generalized eigenvalue problem (GEVP) which can be easily solved by various convex optimization algorithms to determine the optimal control law and the optimal exponential synchronization rate. Detailed comparisons with existing results are made and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.

Growing Carbon Nanotubes

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

None

In situ transmission electron microscope (TEM) video (accelerated 10 times) of nucleation and self-organization of a high-density carbon nanotube network from catalytic iron nanoparticles, forming a vertically aligned forest.

LinkMind: link optimization in swarming mobile sensor networks.

PubMed

Ngo, Trung Dung

2011-01-01

A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation.

LinkMind: Link Optimization in Swarming Mobile Sensor Networks

PubMed Central

Ngo, Trung Dung

2011-01-01

A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation. PMID:22164070

Optimization of municipal pressure pumping station layout and sewage pipe network design

NASA Astrophysics Data System (ADS)

Tian, Jiandong; Cheng, Jilin; Gong, Yi

2018-03-01

Accelerated urbanization places extraordinary demands on sewer networks; thus optimization research to improve the design of these systems has practical significance. In this article, a subsystem nonlinear programming model is developed to optimize pumping station layout and sewage pipe network design. The subsystem model is expanded into a large-scale complex nonlinear programming system model to find the minimum total annual cost of the pumping station and network of all pipe segments. A comparative analysis is conducted using the sewage network in Taizhou City, China, as an example. The proposed method demonstrated that significant cost savings could have been realized if the studied system had been optimized using the techniques described in this article. Therefore, the method has practical value for optimizing urban sewage projects and provides a reference for theoretical research on optimization of urban drainage pumping station layouts.

Reconfiguration of Smart Distribution Network in the Presence of Renewable DG’s Using GWO Algorithm

NASA Astrophysics Data System (ADS)

Siavash, M.; Pfeifer, C.; Rahiminejad, A.; Vahidi, B.

2017-08-01

In this paper, the optimal reconfiguration of smart distribution system is performed with the aim of active power loss reduction and voltage stability improvement. The distribution network is considered equipped with wind turbines and solar cells as Renewable DG’s (RDG’s). Because of the presence of smart metering devices, the network state is known accurately at any moment. Based on the network conditions (the amount of load and generation of RDG’s), the optimal configuration of the network is obtained. The optimization problem is solved using a recently introduced method known as Grey Wolf Optimizer (GWO). The proposed approach is applied on 69-bus radial test system and the results of the GWO are compared to those of Particle Swarm Optimization (PSO), and Genetic Algorithm (GA). The results show the effectiveness of the proposed approach and the selected optimization method.

Joint Optimization of Receiver Placement and Illuminator Selection for a Multiband Passive Radar Network.

PubMed

Xie, Rui; Wan, Xianrong; Hong, Sheng; Yi, Jianxin

2017-06-14

The performance of a passive radar network can be greatly improved by an optimal radar network structure. Generally, radar network structure optimization consists of two aspects, namely the placement of receivers in suitable places and selection of appropriate illuminators. The present study investigates issues concerning the joint optimization of receiver placement and illuminator selection for a passive radar network. Firstly, the required radar cross section (RCS) for target detection is chosen as the performance metric, and the joint optimization model boils down to the partition p -center problem (PPCP). The PPCP is then solved by a proposed bisection algorithm. The key of the bisection algorithm lies in solving the partition set covering problem (PSCP), which can be solved by a hybrid algorithm developed by coupling the convex optimization with the greedy dropping algorithm. In the end, the performance of the proposed algorithm is validated via numerical simulations.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

PubMed

Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

2017-07-19

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

IMU-to-Segment Assignment and Orientation Alignment for the Lower Body Using Deep Learning

PubMed Central

2018-01-01

Human body motion analysis based on wearable inertial measurement units (IMUs) receives a lot of attention from both the research community and the and industrial community. This is due to the significant role in, for instance, mobile health systems, sports and human computer interaction. In sensor based activity recognition, one of the major issues for obtaining reliable results is the sensor placement/assignment on the body. For inertial motion capture (joint kinematics estimation) and analysis, the IMU-to-segment (I2S) assignment and alignment are central issues to obtain biomechanical joint angles. Existing approaches for I2S assignment usually rely on hand crafted features and shallow classification approaches (e.g., support vector machines), with no agreement regarding the most suitable features for the assignment task. Moreover, estimating the complete orientation alignment of an IMU relative to the segment it is attached to using a machine learning approach has not been shown in literature so far. This is likely due to the high amount of training data that have to be recorded to suitably represent possible IMU alignment variations. In this work, we propose online approaches for solving the assignment and alignment tasks for an arbitrary amount of IMUs with respect to a biomechanical lower body model using a deep learning architecture and windows of 128 gyroscope and accelerometer data samples. For this, we combine convolutional neural networks (CNNs) for local filter learning with long-short-term memory (LSTM) recurrent networks as well as generalized recurrent units (GRUs) for learning time dynamic features. The assignment task is casted as a classification problem, while the alignment task is casted as a regression problem. In this framework, we demonstrate the feasibility of augmenting a limited amount of real IMU training data with simulated alignment variations and IMU data for improving the recognition/estimation accuracies. With the proposed approaches and final models we achieved 98.57% average accuracy over all segments for the I2S assignment task (100% when excluding left/right switches) and an average median angle error over all segments and axes of 2.91° for the I2S alignment task. PMID:29351262

Suppressing turbulence of self-propelling rods by strongly coupled passive particles.

PubMed

Su, Yen-Shuo; Wang, Hao-Chen; I, Lin

2015-03-01

The strong turbulence suppression, mainly for large-scale modes, of two-dimensional self-propelling rods, by increasing the long-range coupling strength Γ of low-concentration passive particles, is numerically demonstrated. It is found that large-scale collective rod motion in forms of swirls or jets is mainly contributed from well-aligned dense patches, which can push small poorly aligned rod patches and uncoupled passive particles. The more efficient momentum transfer and dissipation through increasing passive particle coupling leads to the formation of a more ordered and slowed down network of passive particles, which competes with coherent dense active rod clusters. The frustration of active rod alignment ordering and coherent motion by the passive particle network, which interrupt the inverse cascading of forming large-scale swirls, is the key for suppressing collective rod motion with scales beyond the interpassive distance, even in the liquid phase of passive particles. The loosely packed active rods are weakly affected by increasing passive particle coupling due to the weak rod-particle interaction. They mainly contribute to the small-scale modes and high-speed motion.

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.

Influence maximization in complex networks through optimal percolation

NASA Astrophysics Data System (ADS)

Morone, Flaviano; Makse, Hernán A.

2015-08-01

The whole frame of interconnections in complex networks hinges on a specific set of structural nodes, much smaller than the total size, which, if activated, would cause the spread of information to the whole network, or, if immunized, would prevent the diffusion of a large scale epidemic. Localizing this optimal, that is, minimal, set of structural nodes, called influencers, is one of the most important problems in network science. Despite the vast use of heuristic strategies to identify influential spreaders, the problem remains unsolved. Here we map the problem onto optimal percolation in random networks to identify the minimal set of influencers, which arises by minimizing the energy of a many-body system, where the form of the interactions is fixed by the non-backtracking matrix of the network. Big data analyses reveal that the set of optimal influencers is much smaller than the one predicted by previous heuristic centralities. Remarkably, a large number of previously neglected weakly connected nodes emerges among the optimal influencers. These are topologically tagged as low-degree nodes surrounded by hierarchical coronas of hubs, and are uncovered only through the optimal collective interplay of all the influencers in the network. The present theoretical framework may hold a larger degree of universality, being applicable to other hard optimization problems exhibiting a continuous transition from a known phase.

Influence maximization in complex networks through optimal percolation.

PubMed

Morone, Flaviano; Makse, Hernán A

2015-08-06

The whole frame of interconnections in complex networks hinges on a specific set of structural nodes, much smaller than the total size, which, if activated, would cause the spread of information to the whole network, or, if immunized, would prevent the diffusion of a large scale epidemic. Localizing this optimal, that is, minimal, set of structural nodes, called influencers, is one of the most important problems in network science. Despite the vast use of heuristic strategies to identify influential spreaders, the problem remains unsolved. Here we map the problem onto optimal percolation in random networks to identify the minimal set of influencers, which arises by minimizing the energy of a many-body system, where the form of the interactions is fixed by the non-backtracking matrix of the network. Big data analyses reveal that the set of optimal influencers is much smaller than the one predicted by previous heuristic centralities. Remarkably, a large number of previously neglected weakly connected nodes emerges among the optimal influencers. These are topologically tagged as low-degree nodes surrounded by hierarchical coronas of hubs, and are uncovered only through the optimal collective interplay of all the influencers in the network. The present theoretical framework may hold a larger degree of universality, being applicable to other hard optimization problems exhibiting a continuous transition from a known phase.

Optimization of hierarchical structure and nanoscale-enabled plasmonic refraction for window electrodes in photovoltaics.

PubMed

Han, Bing; Peng, Qiang; Li, Ruopeng; Rong, Qikun; Ding, Yang; Akinoglu, Eser Metin; Wu, Xueyuan; Wang, Xin; Lu, Xubing; Wang, Qianming; Zhou, Guofu; Liu, Jun-Ming; Ren, Zhifeng; Giersig, Michael; Herczynski, Andrzej; Kempa, Krzysztof; Gao, Jinwei

2016-09-26

An ideal network window electrode for photovoltaic applications should provide an optimal surface coverage, a uniform current density into and/or from a substrate, and a minimum of the overall resistance for a given shading ratio. Here we show that metallic networks with quasi-fractal structure provides a near-perfect practical realization of such an ideal electrode. We find that a leaf venation network, which possesses key characteristics of the optimal structure, indeed outperforms other networks. We further show that elements of hierarchal topology, rather than details of the branching geometry, are of primary importance in optimizing the networks, and demonstrate this experimentally on five model artificial hierarchical networks of varied levels of complexity. In addition to these structural effects, networks containing nanowires are shown to acquire transparency exceeding the geometric constraint due to the plasmonic refraction.

Network Anomaly Detection System with Optimized DS Evidence Theory

PubMed Central

Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu

2014-01-01

Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network—complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each senor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly. PMID:25254258

Accuracy of Patient Specific Cutting Blocks in Total Knee Arthroplasty

PubMed Central

Helmy, Naeder; Kühnel, Stefanie P.

2014-01-01

Background. Long-term survival of total knee arthroplasty (TKA) is mainly determined by optimal positioning of the components and prosthesis alignment. Implant positioning can be optimized by computer assisted surgery (CAS). Patient specific cutting blocks (PSCB) seem to have the potential to improve component alignment compared to the conventional technique and to be comparable to CAS. Methods. 113 knees were selected for PSI and included in this study. Pre- and postoperative mechanical axis, represented by the hip-knee-angle (HKA), the proximal tibial angle (PTA), the distal femoral angle (DFA), and the tibial slope (TS) were measured and the deviation from expected ideal values was calculated. Results. With a margin of error of ±3°, success rates were 81.4% for HKA, 92.0% for TPA, and 94.7% for DFA. With the margin of error for alignments extended to ±4°, we obtained a success rate of 92.9% for the HKA, 98.2% for the PTA, and 99.1% for the DFA. The TS showed postoperative results of 2.86 ± 2.02° (mean change 1.76 ± 2.85°). Conclusion. PSCBs for TKA seem to restore the overall leg alignment. Our data suggest that each individual component can be implanted accurately and the results are comparable to the ones in CAS. PMID:25254210

Forecasting the mortality rates of Indonesian population by using neural network

NASA Astrophysics Data System (ADS)

Safitri, Lutfiani; Mardiyati, Sri; Rahim, Hendrisman

2018-03-01

A model that can represent a problem is required in conducting a forecasting. One of the models that has been acknowledged by the actuary community in forecasting mortality rate is the Lee-Certer model. Lee Carter model supported by Neural Network will be used to calculate mortality forecasting in Indonesia. The type of Neural Network used is feedforward neural network aligned with backpropagation algorithm in python programming language. And the final result of this study is mortality rate in forecasting Indonesia for the next few years

Improving the magnetoelectric performance of Metglas/PZT laminates by annealing in a magnetic field.

PubMed

Freeman, E; Harper, J; Goel, N; Gilbert, I; Unguris, J; Schiff, S J; Tadigadapa, S

2017-01-01

A comprehensive investigation of magnetostriction optimization in Metglas 2605SA1 ribbons is performed to enhance magnetoelectric performance. We explore a range of annealing conditions to relieve remnant stress and align the magnetic domains in the Metglas, while minimizing unwanted crystallization. The magnetostriction coefficient, magnetoelectric coefficient, and magnetic domain alignment are correlated to optimize magnetoelectric performance. We report on direct magnetostriction observed by in-plane Doppler vibrometer and domain imagining using scanning electron microscopy with polarization analysis for a range of annealing conditions. We find that annealing in an oxygen-free environment at 400 °C for 30 min yields an optimal magnetoelectric coefficient, magnetostriction and magnetostriction coefficient. The optimized ribbons had a magnetostriction of 50.6 ± 0.2 μ m m -1 and magnetoelectric coefficient of 79.3 ± 1.5 μ m m -1 mT -1 . The optimized Metglas 2605SA1 ribbons and PZT-5A (d 31 mode) sensor achieves a magnetic noise floor of approximately 600 pT Hz -1/2 at 100 Hz and a magnetoelectric coefficient of 6.1 ± 0.03 MV m -1 T -1 .

Improving the magnetoelectric performance of Metglas/PZT laminates by annealing in a magnetic field

NASA Astrophysics Data System (ADS)

Freeman, E.; Harper, J.; Goel, N.; Gilbert, I.; Unguris, J.; Schiff, S. J.; Tadigadapa, S.

2017-08-01

A comprehensive investigation of magnetostriction optimization in Metglas 2605SA1 ribbons is performed to enhance magnetoelectric performance. We explore a range of annealing conditions to relieve remnant stress and align the magnetic domains in the Metglas, while minimizing unwanted crystallization. The magnetostriction coefficient, magnetoelectric coefficient, and magnetic domain alignment are correlated to optimize magnetoelectric performance. We report on direct magnetostriction observed by in-plane Doppler vibrometer and domain imagining using scanning electron microscopy with polarization analysis for a range of annealing conditions. We find that annealing in an oxygen-free environment at 400 {}\\circ {{C}} for 30 min yields an optimal magnetoelectric coefficient, magnetostriction and magnetostriction coefficient. The optimized ribbons had a magnetostriction of 50.6 ± 0.2 μ {{m}} {{{m}}}-1 and magnetoelectric coefficient of 79.3 ± 1.5 µm m-1 mT-1. The optimized Metglas 2605SA1 ribbons and PZT-5A (d31 mode) sensor achieves a magnetic noise floor of approximately 600 pT {{{H}}{{z}}}-1/2 at 100 Hz and a magnetoelectric coefficient of 6.1 ± 0.03 MV m-1 T-1.

CAMPways: constrained alignment framework for the comparative analysis of a pair of metabolic pathways.

PubMed

Abaka, Gamze; Bıyıkoğlu, Türker; Erten, Cesim

2013-07-01

Given a pair of metabolic pathways, an alignment of the pathways corresponds to a mapping between similar substructures of the pair. Successful alignments may provide useful applications in phylogenetic tree reconstruction, drug design and overall may enhance our understanding of cellular metabolism. We consider the problem of providing one-to-many alignments of reactions in a pair of metabolic pathways. We first provide a constrained alignment framework applicable to the problem. We show that the constrained alignment problem even in a primitive setting is computationally intractable, which justifies efforts for designing efficient heuristics. We present our Constrained Alignment of Metabolic Pathways (CAMPways) algorithm designed for this purpose. Through extensive experiments involving a large pathway database, we demonstrate that when compared with a state-of-the-art alternative, the CAMPways algorithm provides better alignment results on metabolic networks as far as measures based on same-pathway inclusion and biochemical significance are concerned. The execution speed of our algorithm constitutes yet another important improvement over alternative algorithms. Open source codes, executable binary, useful scripts, all the experimental data and the results are freely available as part of the Supplementary Material at http://code.google.com/p/campways/. Supplementary data are available at Bioinformatics online.

Network planning under uncertainties

NASA Astrophysics Data System (ADS)

Ho, Kwok Shing; Cheung, Kwok Wai

2008-11-01

One of the main focuses for network planning is on the optimization of network resources required to build a network under certain traffic demand projection. Traditionally, the inputs to this type of network planning problems are treated as deterministic. In reality, the varying traffic requirements and fluctuations in network resources can cause uncertainties in the decision models. The failure to include the uncertainties in the network design process can severely affect the feasibility and economics of the network. Therefore, it is essential to find a solution that can be insensitive to the uncertain conditions during the network planning process. As early as in the 1960's, a network planning problem with varying traffic requirements over time had been studied. Up to now, this kind of network planning problems is still being active researched, especially for the VPN network design. Another kind of network planning problems under uncertainties that has been studied actively in the past decade addresses the fluctuations in network resources. One such hotly pursued research topic is survivable network planning. It considers the design of a network under uncertainties brought by the fluctuations in topology to meet the requirement that the network remains intact up to a certain number of faults occurring anywhere in the network. Recently, the authors proposed a new planning methodology called Generalized Survivable Network that tackles the network design problem under both varying traffic requirements and fluctuations of topology. Although all the above network planning problems handle various kinds of uncertainties, it is hard to find a generic framework under more general uncertainty conditions that allows a more systematic way to solve the problems. With a unified framework, the seemingly diverse models and algorithms can be intimately related and possibly more insights and improvements can be brought out for solving the problem. This motivates us to seek a generic framework for solving the network planning problem under uncertainties. In addition to reviewing the various network planning problems involving uncertainties, we also propose that a unified framework based on robust optimization can be used to solve a rather large segment of network planning problem under uncertainties. Robust optimization is first introduced in the operations research literature and is a framework that incorporates information about the uncertainty sets for the parameters in the optimization model. Even though robust optimization is originated from tackling the uncertainty in the optimization process, it can serve as a comprehensive and suitable framework for tackling generic network planning problems under uncertainties. In this paper, we begin by explaining the main ideas behind the robust optimization approach. Then we demonstrate the capabilities of the proposed framework by giving out some examples of how the robust optimization framework can be applied to the current common network planning problems under uncertain environments. Next, we list some practical considerations for solving the network planning problem under uncertainties with the proposed framework. Finally, we conclude this article with some thoughts on the future directions for applying this framework to solve other network planning problems.

Energy-Efficient Next-Generation Passive Optical Networks Based on Sleep Mode and Heuristic Optimization

NASA Astrophysics Data System (ADS)

Zulai, Luis G. T.; Durand, Fábio R.; Abrão, Taufik

2015-05-01

In this article, an energy-efficiency mechanism for next-generation passive optical networks is investigated through heuristic particle swarm optimization. Ten-gigabit Ethernet-wavelength division multiplexing optical code division multiplexing-passive optical network next-generation passive optical networks are based on the use of a legacy 10-gigabit Ethernet-passive optical network with the advantage of using only an en/decoder pair of optical code division multiplexing technology, thus eliminating the en/decoder at each optical network unit. The proposed joint mechanism is based on the sleep-mode power-saving scheme for a 10-gigabit Ethernet-passive optical network, combined with a power control procedure aiming to adjust the transmitted power of the active optical network units while maximizing the overall energy-efficiency network. The particle swarm optimization based power control algorithm establishes the optimal transmitted power in each optical network unit according to the network pre-defined quality of service requirements. The objective is controlling the power consumption of the optical network unit according to the traffic demand by adjusting its transmitter power in an attempt to maximize the number of transmitted bits with minimum energy consumption, achieving maximal system energy efficiency. Numerical results have revealed that it is possible to save 75% of energy consumption with the proposed particle swarm optimization based sleep-mode energy-efficiency mechanism compared to 55% energy savings when just a sleeping-mode-based mechanism is deployed.

Modeling Training Site Vegetation Coverage Probability with a Random Optimizing Procedure: An Artificial Neural Network Approach.

DTIC Science & Technology

1998-05-01

Coverage Probability with a Random Optimization Procedure: An Artificial Neural Network Approach by Biing T. Guan, George Z. Gertner, and Alan B...Modeling Training Site Vegetation Coverage Probability with a Random Optimizing Procedure: An Artificial Neural Network Approach 6. AUTHOR(S) Biing...coverage based on past coverage. Approach A literature survey was conducted to identify artificial neural network analysis techniques applicable for

On Maximizing the Lifetime of Wireless Sensor Networks by Optimally Assigning Energy Supplies

PubMed Central

Asorey-Cacheda, Rafael; García-Sánchez, Antonio Javier; García-Sánchez, Felipe; García-Haro, Joan; Gonzalez-Castaño, Francisco Javier

2013-01-01

The extension of the network lifetime of Wireless Sensor Networks (WSN) is an important issue that has not been appropriately solved yet. This paper addresses this concern and proposes some techniques to plan an arbitrary WSN. To this end, we suggest a hierarchical network architecture, similar to realistic scenarios, where nodes with renewable energy sources (denoted as primary nodes) carry out most message delivery tasks, and nodes equipped with conventional chemical batteries (denoted as secondary nodes) are those with less communication demands. The key design issue of this network architecture is the development of a new optimization framework to calculate the optimal assignment of renewable energy supplies (primary node assignment) to maximize network lifetime, obtaining the minimum number of energy supplies and their node assignment. We also conduct a second optimization step to additionally minimize the number of packet hops between the source and the sink. In this work, we present an algorithm that approaches the results of the optimization framework, but with much faster execution speed, which is a good alternative for large-scale WSN networks. Finally, the network model, the optimization process and the designed algorithm are further evaluated and validated by means of computer simulation under realistic conditions. The results obtained are discussed comparatively. PMID:23939582

On maximizing the lifetime of Wireless Sensor Networks by optimally assigning energy supplies.

PubMed

Asorey-Cacheda, Rafael; García-Sánchez, Antonio Javier; García-Sánchez, Felipe; García-Haro, Joan; González-Castano, Francisco Javier

2013-08-09

The extension of the network lifetime of Wireless Sensor Networks (WSN) is an important issue that has not been appropriately solved yet. This paper addresses this concern and proposes some techniques to plan an arbitrary WSN. To this end, we suggest a hierarchical network architecture, similar to realistic scenarios, where nodes with renewable energy sources (denoted as primary nodes) carry out most message delivery tasks, and nodes equipped with conventional chemical batteries (denoted as secondary nodes) are those with less communication demands. The key design issue of this network architecture is the development of a new optimization framework to calculate the optimal assignment of renewable energy supplies (primary node assignment) to maximize network lifetime, obtaining the minimum number of energy supplies and their node assignment. We also conduct a second optimization step to additionally minimize the number of packet hops between the source and the sink. In this work, we present an algorithm that approaches the results of the optimization framework, but with much faster execution speed, which is a good alternative for large-scale WSN networks. Finally, the network model, the optimization process and the designed algorithm are further evaluated and validated by means of computer simulation under realistic conditions. The results obtained are discussed comparatively.

Bicriteria Network Optimization Problem using Priority-based Genetic Algorithm

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Lin, Lin; Cheng, Runwei

Network optimization is being an increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. In many applications, however, there are several criteria associated with traversing each edge of a network. For example, cost and flow measures are both important in the networks. As a result, there has been recent interest in solving Bicriteria Network Optimization Problem. The Bicriteria Network Optimization Problem is known a NP-hard. The efficient set of paths may be very large, possibly exponential in size. Thus the computational effort required to solve it can increase exponentially with the problem size in the worst case. In this paper, we propose a genetic algorithm (GA) approach used a priority-based chromosome for solving the bicriteria network optimization problem including maximum flow (MXF) model and minimum cost flow (MCF) model. The objective is to find the set of Pareto optimal solutions that give possible maximum flow with minimum cost. This paper also combines Adaptive Weight Approach (AWA) that utilizes some useful information from the current population to readjust weights for obtaining a search pressure toward a positive ideal point. Computer simulations show the several numerical experiments by using some difficult-to-solve network design problems, and show the effectiveness of the proposed method.

Feed-forward alignment correction for advanced overlay process control using a standalone alignment station "Litho Booster"

NASA Astrophysics Data System (ADS)

Yahiro, Takehisa; Sawamura, Junpei; Dosho, Tomonori; Shiba, Yuji; Ando, Satoshi; Ishikawa, Jun; Morita, Masahiro; Shibazaki, Yuichi

2018-03-01

One of the main components of an On-Product Overlay (OPO) error budget is the process induced wafer error. This necessitates wafer-to-wafer correction in order to optimize overlay accuracy. This paper introduces the Litho Booster (LB), standalone alignment station as a solution to improving OPO. LB can execute high speed alignment measurements without throughput (THP) loss. LB can be installed in any lithography process control loop as a metrology tool, and is then able to provide feed-forward (FF) corrections to the scanners. In this paper, the detailed LB design is described and basic LB performance and OPO improvement is demonstrated. Litho Booster's extendibility and applicability as a solution for next generation manufacturing accuracy and productivity challenges are also outlined

Aligner optimization increases accuracy and decreases compute times in multi-species sequence data.

PubMed

Robinson, Kelly M; Hawkins, Aziah S; Santana-Cruz, Ivette; Adkins, Ricky S; Shetty, Amol C; Nagaraj, Sushma; Sadzewicz, Lisa; Tallon, Luke J; Rasko, David A; Fraser, Claire M; Mahurkar, Anup; Silva, Joana C; Dunning Hotopp, Julie C

2017-09-01

As sequencing technologies have evolved, the tools to analyze these sequences have made similar advances. However, for multi-species samples, we observed important and adverse differences in alignment specificity and computation time for bwa- mem (Burrows-Wheeler aligner-maximum exact matches) relative to bwa-aln. Therefore, we sought to optimize bwa-mem for alignment of data from multi-species samples in order to reduce alignment time and increase the specificity of alignments. In the multi-species cases examined, there was one majority member (i.e. Plasmodium falciparum or Brugia malayi ) and one minority member (i.e. human or the Wolbachia endosymbiont w Bm) of the sequence data. Increasing bwa-mem seed length from the default value reduced the number of read pairs from the majority sequence member that incorrectly aligned to the reference genome of the minority sequence member. Combining both source genomes into a single reference genome increased the specificity of mapping, while also reducing the central processing unit (CPU) time. In Plasmodium , at a seed length of 18 nt, 24.1 % of reads mapped to the human genome using 1.7±0.1 CPU hours, while 83.6 % of reads mapped to the Plasmodium genome using 0.2±0.0 CPU hours (total: 107.7 % reads mapping; in 1.9±0.1 CPU hours). In contrast, 97.1 % of the reads mapped to a combined Plasmodium- human reference in only 0.7±0.0 CPU hours. Overall, the results suggest that combining all references into a single reference database and using a 23 nt seed length reduces the computational time, while maximizing specificity. Similar results were found for simulated sequence reads from a mock metagenomic data set. We found similar improvements to computation time in a publicly available human-only data set.

Engineering highly organized and aligned single walled carbon nanotube networks for electronic device applications: Interconnects, chemical sensor, and optoelectronics

NASA Astrophysics Data System (ADS)

Kim, Young Lae

For 20 years, single walled carbon nanotubes (SWNTs) have been studied actively due to their unique one-dimensional nanostructure and superior electrical, thermal, and mechanical properties. For these reasons, they offer the potential to serve as building blocks for future electronic devices such as field effect transistors (FETs), electromechanical devices, and various sensors. In order to realize these applications, it is crucial to develop a simple, scalable, and reliable nanomanufacturing process that controllably places aligned SWNTs in desired locations, orientations, and dimensions. Also electronic properties (semiconducting/metallic) of SWNTs and their organized networks must be controlled for the desired performance of devices and systems. These fundamental challenges are significantly limiting the use of SWNTs for future electronic device applications. Here, we demonstrate a strategy to fabricate highly controlled micro/nanoscale SWNT network structures and present the related assembly mechanism to engineer the SWNT network topology and its electrical transport properties. A method designed to evaluate the electrical reliability of such nano- and microscale SWNT networks is also presented. Moreover, we develop and investigate a robust SWNT based multifunctional selective chemical sensor and a range of multifunctional optoelectronic switches, photo-transistors, optoelectronic logic gates and complex optoelectronic digital circuits.

All-Printed, Self-Aligned Carbon Nanotube Thin-Film Transistors on Imprinted Plastic Substrates.

PubMed

Song, Donghoon; Zare Bidoky, Fazel; Hyun, Woo Jin; Walker, S Brett; Lewis, Jennifer A; Frisbie, C Daniel

2018-05-09

We present a self-aligned process for printing thin-film transistors (TFTs) on plastic with single-walled carbon nanotube (SWCNT) networks as the channel material. The SCALE (self-aligned capillarity-assisted lithography for electronics) process combines imprint lithography with inkjet printing. Specifically, inks are jetted into imprinted reservoirs, where they then flow into narrow device cavities due to capillarity. Here, we incorporate a composite high- k gate dielectric and an aligned conducting polymer gate electrode in the SCALE process to enable a smaller areal footprint than prior designs that yields low-voltage SWCNT TFTs with average p-type carrier mobilities of 4 cm 2 /V·s and ON/OFF current ratios of 10 4 . Our work demonstrates the promising potential of the SCALE process to fabricate SWCNT-based TFTs with favorable I- V characteristics on plastic substrates.

Experimental demonstration of wavelength domain rogue-free ONU based on wavelength-pairing for TDM/WDM optical access networks.

PubMed

Lee, Jie Hyun; Park, Heuk; Kang, Sae-Kyoung; Lee, Joon Ki; Chung, Hwan Seok

2015-11-30

In this study, we propose and experimentally demonstrate a wavelength domain rogue-free ONU based on wavelength-pairing of downstream and upstream signals for time/wavelength division-multiplexed optical access networks. The wavelength-pairing tunable filter is aligned to the upstream wavelength channel by aligning it to one of the downstream wavelength channels. Wavelength-pairing is implemented with a compact and cyclic Si-AWG integrated with a Ge-PD. The pairing filter covered four 100 GHz-spaced wavelength channels. The feasibility of the wavelength domain rogue-free operation is investigated by emulating malfunction of the misaligned laser. The wavelength-pairing tunable filter based on the Si-AWG blocks the upstream signal in the non-assigned wavelength channel before data collision with other ONUs.

A collagen and elastic network in the wing of the bat.

PubMed

Holbrook, K A; Odland, G F

1978-05-01

Bundles of collagen fibrils, elastic fibres and fibroblasts are organized into a network that lies in the plane of a large portion of the bat wing. By ultrastructural (TEM and SEM) and biochemical analyses it was found that individual bundles of the net are similar to elastic ligaments. Although elastic fibres predominate, they are integrated and aligned in parallel with small bundles of collagen. A reticulum of fibroblasts, joined by focal junctions, forms a cellular framework throughout each bundle. Because of the unique features of the fibre bundles of the bat's wing, in particular their accessibility, and the parallel alignment of the collagen fibrils and elastic fibres in each easily isolatable fibre bundle, they should prove a most valuable model for connective tissue studies, particularly for the study of collagen-elastin interactions.

Self-centering fiber alignment structures for high-precision field installable single-mode fiber connectors

NASA Astrophysics Data System (ADS)

Van Erps, Jürgen; Ebraert, Evert; Gao, Fei; Vervaeke, Michael; Berghmans, Francis; Beri, Stefano; Watté, Jan; Thienpont, Hugo

2014-05-01

There is a steady increase in the demand for internet bandwidth, primarily driven by cloud services and high-definition video streaming. Europe's Digital Agenda states the ambitious objective that by 2020 all Europeans should have access to internet at speeds of 30Mb/s or above, with 50% or more of households subscribing to connections of 100Mb/s. Today however, internet access in Europe is mainly based on the first generation of broadband, meaning internet accessed over legacy telephone copper and TV cable networks. In recent years, Fiber-To-The-Home (FTTH) networks have been adopted as a replacement of traditional electrical connections for the `last mile' transmission of information at bandwidths over 1Gb/s. However, FTTH penetration is still very low (< 5%) in most major Western economies. The main reason for this is the high deployment cost of FTTH networks. Indeed, the success and adoption of optical access networks critically depend on the quality and reliability of connections between optical fibers. In particular a further reduction of insertion loss of field- installable connectors must be achieved without a significant increase in component cost. This requires precise alignment of fibers that can differ in terms of ellipticity, eccentricity or diameter and seems hardly achievable using today's widespread ferrule-based alignment systems. In this paper, we present a field-installable connector based on deflectable/compressible spring structures, providing a self-centering functionality for the fiber. This way, it can accommodate for possible fiber cladding diameter variations (the tolerance on the cladding diameter of G.652 fiber is typically +/-0.7μm). The mechanical properties of the cantilever are derived through an analytical approximation and a mathematical model of the spring constant, and finite element-based simulations are carried out to find the maximum first principal stress as well as the stress distribution distribution in the fiber alignment structure. Elastic constants of the order of 104N=m are found to be compatible with a proof stress of 70 M Pa. We show the successful prototyping of 3-spring fiber alignment structures using deep proton writing and investigate their compatibility with replication techniques such as hot embossing and injection moulding. Fiber insertion in our self-centering alignment structures is achieved by means of a dedicated interferometric setup allowing assessment of the fiber facet quality, of the fiber's position in relation to the connector's front and of the spring deformation during fiber insertion. These self-centering structures have the potential to become the basic building blocks for a new generation of field-installable connectors, ultimately breaking the current paradigm of ferrule-based connectivity requiring extensive pre-engineering and highly specialized manpower for field deployment.

Neural Network Prediction of New Aircraft Design Coefficients

NASA Technical Reports Server (NTRS)

Norgaard, Magnus; Jorgensen, Charles C.; Ross, James C.

1997-01-01

This paper discusses a neural network tool for more effective aircraft design evaluations during wind tunnel tests. Using a hybrid neural network optimization method, we have produced fast and reliable predictions of aerodynamical coefficients, found optimal flap settings, and flap schedules. For validation, the tool was tested on a 55% scale model of the USAF/NASA Subsonic High Alpha Research Concept aircraft (SHARC). Four different networks were trained to predict coefficients of lift, drag, moment of inertia, and lift drag ratio (C(sub L), C(sub D), C(sub M), and L/D) from angle of attack and flap settings. The latter network was then used to determine an overall optimal flap setting and for finding optimal flap schedules.

DNAAlignEditor: DNA alignment editor tool

PubMed Central

Sanchez-Villeda, Hector; Schroeder, Steven; Flint-Garcia, Sherry; Guill, Katherine E; Yamasaki, Masanori; McMullen, Michael D

2008-01-01

Background With advances in DNA re-sequencing methods and Next-Generation parallel sequencing approaches, there has been a large increase in genomic efforts to define and analyze the sequence variability present among individuals within a species. For very polymorphic species such as maize, this has lead to a need for intuitive, user-friendly software that aids the biologist, often with naïve programming capability, in tracking, editing, displaying, and exporting multiple individual sequence alignments. To fill this need we have developed a novel DNA alignment editor. Results We have generated a nucleotide sequence alignment editor (DNAAlignEditor) that provides an intuitive, user-friendly interface for manual editing of multiple sequence alignments with functions for input, editing, and output of sequence alignments. The color-coding of nucleotide identity and the display of associated quality score aids in the manual alignment editing process. DNAAlignEditor works as a client/server tool having two main components: a relational database that collects the processed alignments and a user interface connected to database through universal data access connectivity drivers. DNAAlignEditor can be used either as a stand-alone application or as a network application with multiple users concurrently connected. Conclusion We anticipate that this software will be of general interest to biologists and population genetics in editing DNA sequence alignments and analyzing natural sequence variation regardless of species, and will be particularly useful for manual alignment editing of sequences in species with high levels of polymorphism. PMID:18366684

Designing optimal greenhouse gas monitoring networks for Australia

NASA Astrophysics Data System (ADS)

Ziehn, T.; Law, R. M.; Rayner, P. J.; Roff, G.

2016-01-01

Atmospheric transport inversion is commonly used to infer greenhouse gas (GHG) flux estimates from concentration measurements. The optimal location of ground-based observing stations that supply these measurements can be determined by network design. Here, we use a Lagrangian particle dispersion model (LPDM) in reverse mode together with a Bayesian inverse modelling framework to derive optimal GHG observing networks for Australia. This extends the network design for carbon dioxide (CO2) performed by Ziehn et al. (2014) to also minimise the uncertainty on the flux estimates for methane (CH4) and nitrous oxide (N2O), both individually and in a combined network using multiple objectives. Optimal networks are generated by adding up to five new stations to the base network, which is defined as two existing stations, Cape Grim and Gunn Point, in southern and northern Australia respectively. The individual networks for CO2, CH4 and N2O and the combined observing network show large similarities because the flux uncertainties for each GHG are dominated by regions of biologically productive land. There is little penalty, in terms of flux uncertainty reduction, for the combined network compared to individually designed networks. The location of the stations in the combined network is sensitive to variations in the assumed data uncertainty across locations. A simple assessment of economic costs has been included in our network design approach, considering both establishment and maintenance costs. Our results suggest that, while site logistics change the optimal network, there is only a small impact on the flux uncertainty reductions achieved with increasing network size.

Medium scale carbon nanotube thin film integrated circuits on flexible plastic substrates

DOEpatents

Rogers, John A; Cao, Qing; Alam, Muhammad; Pimparkar, Ninad

2015-02-03

The present invention provides device components geometries and fabrication strategies for enhancing the electronic performance of electronic devices based on thin films of randomly oriented or partially aligned semiconducting nanotubes. In certain aspects, devices and methods of the present invention incorporate a patterned layer of randomly oriented or partially aligned carbon nanotubes, such as one or more interconnected SWNT networks, providing a semiconductor channel exhibiting improved electronic properties relative to conventional nanotubes-based electronic systems.

SANSparallel: interactive homology search against Uniprot.

PubMed

Somervuo, Panu; Holm, Liisa

2015-07-01

Proteins evolve by mutations and natural selection. The network of sequence similarities is a rich source for mining homologous relationships that inform on protein structure and function. There are many servers available to browse the network of homology relationships but one has to wait up to a minute for results. The SANSparallel webserver provides protein sequence database searches with immediate response and professional alignment visualization by third-party software. The output is a list, pairwise alignment or stacked alignment of sequence-similar proteins from Uniprot, UniRef90/50, Swissprot or Protein Data Bank. The stacked alignments are viewed in Jalview or as sequence logos. The database search uses the suffix array neighborhood search (SANS) method, which has been re-implemented as a client-server, improved and parallelized. The method is extremely fast and as sensitive as BLAST above 50% sequence identity. Benchmarks show that the method is highly competitive compared to previously published fast database search programs: UBLAST, DIAMOND, LAST, LAMBDA, RAPSEARCH2 and BLAT. The web server can be accessed interactively or programmatically at http://ekhidna2.biocenter.helsinki.fi/cgi-bin/sans/sans.cgi. It can be used to make protein functional annotation pipelines more efficient, and it is useful in interactive exploration of the detailed evidence supporting the annotation of particular proteins of interest. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

A 3D metrology system for the GMT

NASA Astrophysics Data System (ADS)

Rakich, A.; Dettmann, Lee; Leveque, S.; Guisard, S.

2016-08-01

The Giant Magellan Telescope (GMT)1 is a 25 m telescope composed of seven 8.4 m "unit telescopes", on a common mount. Each primary and conjugated secondary mirror segment will feed a common instrument interface, their focal planes co-aligned and co-phased. During telescope operation, the alignment of the optical components will deflect due to variations in thermal environment and gravity induced structural flexure of the mount. The ultimate co-alignment and co-phasing of the telescope is achieved by a combination of the Acquisition Guiding and Wavefront Sensing system and two segment edge-sensing systems2. An analysis of the capture range of the wavefront sensing system indicates that it is unlikely that that system will operate efficiently or reliably with initial mirror positions provided by open-loop corrections alone3. The project is developing a Telescope Metrology System (TMS) which incorporates a large number of absolute distance measuring interferometers. The system will align optical components of the telescope to the instrument interface to (well) within the capture range of the active optics wavefront sensing systems. The advantages offered by this technological approach to a TMS, over a network of laser trackers, are discussed. Initial investigations of the Etalon Absolute Multiline Technology™ by Etalon Ag4 show that a metrology network based on this product is capable of meeting requirements. A conceptual design of the system is presented and expected performance is discussed.

Optimal Design of River Monitoring Network in Taizihe River by Matter Element Analysis

PubMed Central

Wang, Hui; Liu, Zhe; Sun, Lina; Luo, Qing

2015-01-01

The objective of this study is to optimize the river monitoring network in Taizihe River, Northeast China. The situation of the network and water characteristics were studied in this work. During this study, water samples were collected once a month during January 2009 - December 2010 from seventeen sites. Futhermore, the 16 monitoring indexes were analyzed in the field and laboratory. The pH value of surface water sample was found to be in the range of 6.83 to 9.31, and the average concentrations of NH4 +-N, chemical oxygen demand (COD), volatile phenol and total phosphorus (TP) were found decreasing significantly. The water quality of the river has been improved from 2009 to 2010. Through the calculation of the data availability and the correlation between adjacent sections, it was found that the present monitoring network was inefficient as well as the optimization was indispensable. In order to improve the situation, the matter element analysis and gravity distance were applied in the optimization of river monitoring network, which were proved to be a useful method to optimize river quality monitoring network. The amount of monitoring sections were cut from 17 to 13 for the monitoring network was more cost-effective after being optimized. The results of this study could be used in developing effective management strategies to improve the environmental quality of Taizihe River. Also, the results show that the proposed model can be effectively used for the optimal design of monitoring networks in river systems. PMID:26023785

Optimization of hierarchical structure and nanoscale-enabled plasmonic refraction for window electrodes in photovoltaics

PubMed Central

Han, Bing; Peng, Qiang; Li, Ruopeng; Rong, Qikun; Ding, Yang; Akinoglu, Eser Metin; Wu, Xueyuan; Wang, Xin; Lu, Xubing; Wang, Qianming; Zhou, Guofu; Liu, Jun-Ming; Ren, Zhifeng; Giersig, Michael; Herczynski, Andrzej; Kempa, Krzysztof; Gao, Jinwei

2016-01-01

An ideal network window electrode for photovoltaic applications should provide an optimal surface coverage, a uniform current density into and/or from a substrate, and a minimum of the overall resistance for a given shading ratio. Here we show that metallic networks with quasi-fractal structure provides a near-perfect practical realization of such an ideal electrode. We find that a leaf venation network, which possesses key characteristics of the optimal structure, indeed outperforms other networks. We further show that elements of hierarchal topology, rather than details of the branching geometry, are of primary importance in optimizing the networks, and demonstrate this experimentally on five model artificial hierarchical networks of varied levels of complexity. In addition to these structural effects, networks containing nanowires are shown to acquire transparency exceeding the geometric constraint due to the plasmonic refraction. PMID:27667099

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks

PubMed Central

Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Li, Baoqing; Yuan, Xiaobing

2017-01-01

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum–minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms. PMID:28753962

Optimization of a large-scale microseismic monitoring network in northern Switzerland

NASA Astrophysics Data System (ADS)

Kraft, Toni; Mignan, Arnaud; Giardini, Domenico

2013-10-01

We have developed a network optimization method for regional-scale microseismic monitoring networks and applied it to optimize the densification of the existing seismic network in northeastern Switzerland. The new network will build the backbone of a 10-yr study on the neotectonic activity of this area that will help to better constrain the seismic hazard imposed on nuclear power plants and waste repository sites. This task defined the requirements regarding location precision (0.5 km in epicentre and 2 km in source depth) and detection capability [magnitude of completeness Mc = 1.0 (ML)]. The goal of the optimization was to find the geometry and size of the network that met these requirements. Existing stations in Switzerland, Germany and Austria were considered in the optimization procedure. We based the optimization on the simulated annealing approach proposed by Hardt & Scherbaum, which aims to minimize the volume of the error ellipsoid of the linearized earthquake location problem (D-criterion). We have extended their algorithm to: calculate traveltimes of seismic body waves using a finite difference ray tracer and the 3-D velocity model of Switzerland, calculate seismic body-wave amplitudes at arbitrary stations assuming the Brune source model and using scaling and attenuation relations recently derived for Switzerland, and estimate the noise level at arbitrary locations within Switzerland using a first-order ambient seismic noise model based on 14 land-use classes defined by the EU-project CORINE and open GIS data. We calculated optimized geometries for networks with 10-35 added stations and tested the stability of the optimization result by repeated runs with changing initial conditions. Further, we estimated the attainable magnitude of completeness (Mc) for the different sized optimal networks using the Bayesian Magnitude of Completeness (BMC) method introduced by Mignan et al. The algorithm developed in this study is also applicable to smaller optimization problems, for example, small local monitoring networks. Possible applications are volcano monitoring, the surveillance of induced seismicity associated with geotechnical operations and many more. Our algorithm is especially useful to optimize networks in populated areas with heterogeneous noise conditions and if complex velocity structures or existing stations have to be considered.

Evolutionary trade-offs and the structure of polymorphisms.

PubMed

Sheftel, Hila; Szekely, Pablo; Mayo, Avi; Sella, Guy; Alon, Uri

2018-05-26

Populations of organisms show genetic differences called polymorphisms. Understanding the effects of polymorphisms is important for biology and medicine. Here, we ask which polymorphisms occur at high frequency when organisms evolve under trade-offs between multiple tasks. Multiple tasks present a problem, because it is not possible to be optimal at all tasks simultaneously and hence compromises are necessary. Recent work indicates that trade-offs lead to a simple geometry of phenotypes in the space of traits: phenotypes fall on the Pareto front, which is shaped as a polytope: a line, triangle, tetrahedron etc. The vertices of these polytopes are the optimal phenotypes for a single task. Up to now, work on this Pareto approach has not considered its genetic underpinnings. Here, we address this by asking how the polymorphism structure of a population is affected by evolution under trade-offs. We simulate a multi-task selection scenario, in which the population evolves to the Pareto front: the line segment between two archetypes or the triangle between three archetypes. We find that polymorphisms that become prevalent in the population have pleiotropic phenotypic effects that align with the Pareto front. Similarly, epistatic effects between prevalent polymorphisms are parallel to the front. Alignment with the front occurs also for asexual mating. Alignment is reduced when drift or linkage is strong, and is replaced by a more complex structure in which many perpendicular allele effects cancel out. Aligned polymorphism structure allows mating to produce offspring that stand a good chance of being optimal multi-taskers in at least one of the locales available to the species.This article is part of the theme issue 'Self-organization in cell biology'. © 2018 The Author(s).

Optimizing Virtual Network Functions Placement in Virtual Data Center Infrastructure Using Machine Learning

NASA Astrophysics Data System (ADS)

Bolodurina, I. P.; Parfenov, D. I.

2018-01-01

We have elaborated a neural network model of virtual network flow identification based on the statistical properties of flows circulating in the network of the data center and characteristics that describe the content of packets transmitted through network objects. This enabled us to establish the optimal set of attributes to identify virtual network functions. We have established an algorithm for optimizing the placement of virtual data functions using the data obtained in our research. Our approach uses a hybrid method of visualization using virtual machines and containers, which enables to reduce the infrastructure load and the response time in the network of the virtual data center. The algorithmic solution is based on neural networks, which enables to scale it at any number of the network function copies.

3D QSAR studies on protein tyrosine phosphatase 1B inhibitors: comparison of the quality and predictivity among 3D QSAR models obtained from different conformer-based alignments.

PubMed

Pandey, Gyanendra; Saxena, Anil K

2006-01-01

A set of 65 flexible peptidomimetic competitive inhibitors (52 in the training set and 13 in the test set) of protein tyrosine phosphatase 1B (PTP1B) has been used to compare the quality and predictive power of 3D quantitative structure-activity relationship (QSAR) comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models for the three most commonly used conformer-based alignments, namely, cocrystallized conformer-based alignment (CCBA), docked conformer-based alignment (DCBA), and global minima energy conformer-based alignment (GMCBA). These three conformers of 5-[(2S)-2-({(2S)-2-[(tert-butoxycarbonyl)amino]-3-phenylpropanoyl}amino)3-oxo-3-pentylamino)propyl]-2-(carboxymethoxy)benzoic acid (compound number 66) were obtained from the X-ray structure of its cocrystallized complex with PTP1B (PDB ID: 1JF7), its docking studies, and its global minima by simulated annealing. Among the 3D QSAR models developed using the above three alignments, the CCBA provided the optimal predictive CoMFA model for the training set with cross-validated r2 (q2)=0.708, non-cross-validated r2=0.902, standard error of estimate (s)=0.165, and F=202.553 and the optimal CoMSIA model with q2=0.440, r2=0.799, s=0.192, and F=117.782. These models also showed the best test set prediction for the 13 compounds with predictive r2 values of 0.706 and 0.683, respectively. Though the QSAR models derived using the other two alignments also produced statistically acceptable models in the order DCBA>GMCBA in terms of the values of q2, r2, and predictive r2, they were inferior to the corresponding models derived using CCBA. Thus, the order of preference for the alignment selection for 3D QSAR model development may be CCBA>DCBA>GMCBA, and the information obtained from the CoMFA and CoMSIA contour maps may be useful in designing specific PTP1B inhibitors.

Cooperative Interference Alignment for the Multiple Access Channel

DTIC Science & Technology

2015-11-01

Communications. I. INTRODUCTION Conventional wireless networks were previously thought to be interference-limited, where interference is mainly caused by...interference-free capacity for any number of users K at high SNR. This fundamental result showed that wireless networks are not interference-limited as...decoding of the K users’ messages. This is applicable in uplink transmissions in cellular communications, where mobiles transmit independent messages

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

PubMed

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

2014-09-07

Due to the central roles of lipid binding proteins (LBPs) in many biological processes, sequence based identification of LBPs is of great interest. The major challenge is that LBPs are diverse in sequence, structure, and function which results in low accuracy of sequence homology based methods. Therefore, there is a need for developing alternative functional prediction methods irrespective of sequence similarity. To identify LBPs from non-LBPs, the performances of support vector machine (SVM) and neural network were compared in this study. Comprehensive protein features and various techniques were employed to create datasets. Five-fold cross-validation (CV) and independent evaluation (IE) tests were used to assess the validity of the two methods. The results indicated that SVM outperforms neural network. SVM achieved 89.28% (CV) and 89.55% (IE) overall accuracy in identification of LBPs from non-LBPs and 92.06% (CV) and 92.90% (IE) (in average) for classification of different LBPs classes. Increasing the number and the range of extracted protein features as well as optimization of the SVM parameters significantly increased the efficiency of LBPs class prediction in comparison to the only previous report in this field. Altogether, the results showed that the SVM algorithm can be run on broad, computationally calculated protein features and offers a promising tool in detection of LBPs classes. The proposed approach has the potential to integrate and improve the common sequence alignment based methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

An Alignment Model for Collaborative Value Networks

NASA Astrophysics Data System (ADS)

Bremer, Carlos; Azevedo, Rodrigo Cambiaghi; Klen, Alexandra Pereira

This paper presents parts of the work carried out in several global organizations through the development of strategic projects with high tactical and operational complexity. By investing in long-term relationships, strongly operating in the transformation of the competitive model and focusing on the value chain management, the main aim of these projects was the alignment of multiple value chains. The projects were led by the Axia Transformation Methodology as well as by its Management Model and following the principles of Project Management. As a concrete result of the efforts made in the last years in the Brazilian market this work also introduces the Alignment Model which supports the transformation process that the companies undergo.

Retro-detective control structures for free-space optical communication links.

PubMed

Jin, Xian; Barg, Jason E; Holzman, Jonathan F

2009-12-21

A corner-cube-based retro-detection photocell is introduced. The structure consists of three independent and mutually perpendicular photodiodes (PDs), whose differential photocurrents can be used to probe the alignment state of incident beams. These differential photocurrents are used in an actively-controlled triangulation procedure to optimize the communication channel alignment in a free-space optical (FSO) system. The active downlink and passive uplink communication capabilities of this system are demonstrated.

Aligning with physicians to regionalize services.

PubMed

Fink, John

2014-11-01

When effectively designed and implemented, regionalization allows a health system to coordinate care, eliminate redundancies, reduce costs, optimize resource utilization, and improve outcomes. The preferred model to manage service lines regionally will depend on each facility's capabilities and the willingness of physicians to accept changes in clinical delivery. Health systems can overcome physicians' objections to regionalization by implementing a hospital-physician alignment structure that gives a measure of shared control in the management of the organization.

Tolerancing the alignment of large-core optical fibers, fiber bundles and light guides using a Fourier approach.

PubMed

Sawyer, Travis W; Petersburg, Ryan; Bohndiek, Sarah E

2017-04-20

Optical fiber technology is found in a wide variety of applications to flexibly relay light between two points, enabling information transfer across long distances and allowing access to hard-to-reach areas. Large-core optical fibers and light guides find frequent use in illumination and spectroscopic applications, for example, endoscopy and high-resolution astronomical spectroscopy. Proper alignment is critical for maximizing throughput in optical fiber coupling systems; however, there currently are no formal approaches to tolerancing the alignment of a light-guide coupling system. Here, we propose a Fourier alignment sensitivity (FAS) algorithm to determine the optimal tolerances on the alignment of a light guide by computing the alignment sensitivity. The algorithm shows excellent agreement with both simulated and experimentally measured values and improves on the computation time of equivalent ray-tracing simulations by two orders of magnitude. We then apply FAS to tolerance and fabricate a coupling system, which is shown to meet specifications, thus validating FAS as a tolerancing technique. These results indicate that FAS is a flexible and rapid means to quantify the alignment sensitivity of a light guide, widely informing the design and tolerancing of coupling systems.

Tolerancing the alignment of large-core optical fibers, fiber bundles and light guides using a Fourier approach

PubMed Central

Sawyer, Travis W.; Petersburg, Ryan; Bohndiek, Sarah E.

2017-01-01

Optical fiber technology is found in a wide variety of applications to flexibly relay light between two points, enabling information transfer across long distances and allowing access to hard-to-reach areas. Large-core optical fibers and light guides find frequent use in illumination and spectroscopic applications; for example, endoscopy and high-resolution astronomical spectroscopy. Proper alignment is critical for maximizing throughput in optical fiber coupling systems, however, there currently are no formal approaches to tolerancing the alignment of a light guide coupling system. Here, we propose a Fourier Alignment Sensitivity (FAS) algorithm to determine the optimal tolerances on the alignment of a light guide by computing the alignment sensitivity. The algorithm shows excellent agreement with both simulated and experimentally measured values and improves on the computation time of equivalent ray tracing simulations by two orders of magnitude. We then apply FAS to tolerance and fabricate a coupling system, which is shown to meet specifications, thus validating FAS as a tolerancing technique. These results indicate that FAS is a flexible and rapid means to quantify the alignment sensitivity of a light guide, widely informing the design and tolerancing of coupling systems. PMID:28430250

Quantification of Cardiomyocyte Alignment from Three-Dimensional (3D) Confocal Microscopy of Engineered Tissue.

PubMed

Kowalski, William J; Yuan, Fangping; Nakane, Takeichiro; Masumoto, Hidetoshi; Dwenger, Marc; Ye, Fei; Tinney, Joseph P; Keller, Bradley B

2017-08-01

Biological tissues have complex, three-dimensional (3D) organizations of cells and matrix factors that provide the architecture necessary to meet morphogenic and functional demands. Disordered cell alignment is associated with congenital heart disease, cardiomyopathy, and neurodegenerative diseases and repairing or replacing these tissues using engineered constructs may improve regenerative capacity. However, optimizing cell alignment within engineered tissues requires quantitative 3D data on cell orientations and both efficient and validated processing algorithms. We developed an automated method to measure local 3D orientations based on structure tensor analysis and incorporated an adaptive subregion size to account for multiple scales. Our method calculates the statistical concentration parameter, κ, to quantify alignment, as well as the traditional orientational order parameter. We validated our method using synthetic images and accurately measured principal axis and concentration. We then applied our method to confocal stacks of cleared, whole-mount engineered cardiac tissues generated from human-induced pluripotent stem cells or embryonic chick cardiac cells and quantified cardiomyocyte alignment. We found significant differences in alignment based on cellular composition and tissue geometry. These results from our synthetic images and confocal data demonstrate the efficiency and accuracy of our method to measure alignment in 3D tissues.

Influence maximization in complex networks through optimal percolation

NASA Astrophysics Data System (ADS)

Morone, Flaviano; Makse, Hernan; CUNY Collaboration; CUNY Collaboration

The whole frame of interconnections in complex networks hinges on a specific set of structural nodes, much smaller than the total size, which, if activated, would cause the spread of information to the whole network, or, if immunized, would prevent the diffusion of a large scale epidemic. Localizing this optimal, that is, minimal, set of structural nodes, called influencers, is one of the most important problems in network science. Here we map the problem onto optimal percolation in random networks to identify the minimal set of influencers, which arises by minimizing the energy of a many-body system, where the form of the interactions is fixed by the non-backtracking matrix of the network. Big data analyses reveal that the set of optimal influencers is much smaller than the one predicted by previous heuristic centralities. Remarkably, a large number of previously neglected weakly connected nodes emerges among the optimal influencers. Reference: F. Morone, H. A. Makse, Nature 524,65-68 (2015)

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

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

Ding, Tao; Li, Cheng; Huang, Can

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

Adaptation, Growth, and Resilience in Biological Distribution Networks

NASA Astrophysics Data System (ADS)

Ronellenfitsch, Henrik; Katifori, Eleni

Highly optimized complex transport networks serve crucial functions in many man-made and natural systems such as power grids and plant or animal vasculature. Often, the relevant optimization functional is nonconvex and characterized by many local extrema. In general, finding the global, or nearly global optimum is difficult. In biological systems, it is believed that such an optimal state is slowly achieved through natural selection. However, general coarse grained models for flow networks with local positive feedback rules for the vessel conductivity typically get trapped in low efficiency, local minima. We show how the growth of the underlying tissue, coupled to the dynamical equations for network development, can drive the system to a dramatically improved optimal state. This general model provides a surprisingly simple explanation for the appearance of highly optimized transport networks in biology such as plant and animal vasculature. In addition, we show how the incorporation of spatially collective fluctuating sources yields a minimal model of realistic reticulation in distribution networks and thus resilience against damage.

Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

NASA Technical Reports Server (NTRS)

Cheung, Kar-Ming; Lee, Charles H.

2012-01-01

We developed framework and the mathematical formulation for optimizing communication network using mixed integer programming. The design yields a system that is much smaller, in search space size, when compared to the earlier approach. Our constrained network optimization takes into account the dynamics of link performance within the network along with mission and operation requirements. A unique penalty function is introduced to transform the mixed integer programming into the more manageable problem of searching in a continuous space. The constrained optimization problem was proposed to solve in two stages: first using the heuristic Particle Swarming Optimization algorithm to get a good initial starting point, and then feeding the result into the Sequential Quadratic Programming algorithm to achieve the final optimal schedule. We demonstrate the above planning and scheduling methodology with a scenario of 20 spacecraft and 3 ground stations of a Deep Space Network site. Our approach and framework have been simple and flexible so that problems with larger number of constraints and network can be easily adapted and solved.

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DOE PAGES

Ding, Tao; Li, Cheng; Huang, Can; ...

2017-01-09

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

Dynamic modeling and optimization for space logistics using time-expanded networks

NASA Astrophysics Data System (ADS)

Ho, Koki; de Weck, Olivier L.; Hoffman, Jeffrey A.; Shishko, Robert

2014-12-01

This research develops a dynamic logistics network formulation for lifecycle optimization of mission sequences as a system-level integrated method to find an optimal combination of technologies to be used at each stage of the campaign. This formulation can find the optimal transportation architecture considering its technology trades over time. The proposed methodologies are inspired by the ground logistics analysis techniques based on linear programming network optimization. Particularly, the time-expanded network and its extension are developed for dynamic space logistics network optimization trading the quality of the solution with the computational load. In this paper, the methodologies are applied to a human Mars exploration architecture design problem. The results reveal multiple dynamic system-level trades over time and give recommendation of the optimal strategy for the human Mars exploration architecture. The considered trades include those between In-Situ Resource Utilization (ISRU) and propulsion technologies as well as the orbit and depot location selections over time. This research serves as a precursor for eventual permanent settlement and colonization of other planets by humans and us becoming a multi-planet species.

Integrated design of multivariable hydrometric networks using entropy theory with a multiobjective optimization approach

NASA Astrophysics Data System (ADS)

Kim, Y.; Hwang, T.; Vose, J. M.; Martin, K. L.; Band, L. E.

2016-12-01

Obtaining quality hydrologic observations is the first step towards a successful water resources management. While remote sensing techniques have enabled to convert satellite images of the Earth's surface to hydrologic data, the importance of ground-based observations has never been diminished because in-situ data are often highly accurate and can be used to validate remote measurements. The existence of efficient hydrometric networks is becoming more important to obtain as much as information with minimum redundancy. The World Meteorological Organization (WMO) has recommended a guideline for the minimum hydrometric network density based on physiography; however, this guideline is not for the optimum network design but for avoiding serious deficiency from a network. Moreover, all hydrologic variables are interconnected within the hydrologic cycle, while monitoring networks have been designed individually. This study proposes an integrated network design method using entropy theory with a multiobjective optimization approach. In specific, a precipitation and a streamflow networks in a semi-urban watershed in Ontario, Canada were designed simultaneously by maximizing joint entropy, minimizing total correlation, and maximizing conditional entropy of streamflow network given precipitation network. After comparing with the typical individual network designs, the proposed design method would be able to determine more efficient optimal networks by avoiding the redundant stations, in which hydrologic information is transferable. Additionally, four quantization cases were applied in entropy calculations to assess their implications on the station rankings and the optimal networks. The results showed that the selection of quantization method should be considered carefully because the rankings and optimal networks are subject to change accordingly.

Integrated design of multivariable hydrometric networks using entropy theory with a multiobjective optimization approach

NASA Astrophysics Data System (ADS)

Keum, J.; Coulibaly, P. D.

2017-12-01

Obtaining quality hydrologic observations is the first step towards a successful water resources management. While remote sensing techniques have enabled to convert satellite images of the Earth's surface to hydrologic data, the importance of ground-based observations has never been diminished because in-situ data are often highly accurate and can be used to validate remote measurements. The existence of efficient hydrometric networks is becoming more important to obtain as much as information with minimum redundancy. The World Meteorological Organization (WMO) has recommended a guideline for the minimum hydrometric network density based on physiography; however, this guideline is not for the optimum network design but for avoiding serious deficiency from a network. Moreover, all hydrologic variables are interconnected within the hydrologic cycle, while monitoring networks have been designed individually. This study proposes an integrated network design method using entropy theory with a multiobjective optimization approach. In specific, a precipitation and a streamflow networks in a semi-urban watershed in Ontario, Canada were designed simultaneously by maximizing joint entropy, minimizing total correlation, and maximizing conditional entropy of streamflow network given precipitation network. After comparing with the typical individual network designs, the proposed design method would be able to determine more efficient optimal networks by avoiding the redundant stations, in which hydrologic information is transferable. Additionally, four quantization cases were applied in entropy calculations to assess their implications on the station rankings and the optimal networks. The results showed that the selection of quantization method should be considered carefully because the rankings and optimal networks are subject to change accordingly.

BAYESIAN PROTEIN STRUCTURE ALIGNMENT.

PubMed

Rodriguez, Abel; Schmidler, Scott C

The analysis of the three-dimensional structure of proteins is an important topic in molecular biochemistry. Structure plays a critical role in defining the function of proteins and is more strongly conserved than amino acid sequence over evolutionary timescales. A key challenge is the identification and evaluation of structural similarity between proteins; such analysis can aid in understanding the role of newly discovered proteins and help elucidate evolutionary relationships between organisms. Computational biologists have developed many clever algorithmic techniques for comparing protein structures, however, all are based on heuristic optimization criteria, making statistical interpretation somewhat difficult. Here we present a fully probabilistic framework for pairwise structural alignment of proteins. Our approach has several advantages, including the ability to capture alignment uncertainty and to estimate key "gap" parameters which critically affect the quality of the alignment. We show that several existing alignment methods arise as maximum a posteriori estimates under specific choices of prior distributions and error models. Our probabilistic framework is also easily extended to incorporate additional information, which we demonstrate by including primary sequence information to generate simultaneous sequence-structure alignments that can resolve ambiguities obtained using structure alone. This combined model also provides a natural approach for the difficult task of estimating evolutionary distance based on structural alignments. The model is illustrated by comparison with well-established methods on several challenging protein alignment examples.

Optimization of electrospun TSF nanofiber alignment and diameter to promote growth and migration of mesenchymal stem cells

NASA Astrophysics Data System (ADS)

Qu, Jing; Zhou, Dandan; Xu, Xiaojing; Zhang, Feng; He, Lihong; Ye, Rong; Zhu, Ziyu; Zuo, Baoqi; Zhang, Huanxiang

2012-11-01

Silk fibroin scaffolds are a naturally derived biocompatible matrix with the potential for reconstructive surgical applications. In this study, tussah silk fibroin (TSF) nanofiber with different diameters (400 nm, 800 nm and 1200 nm) and alignment (random and aligned) were prepared by electrospinning, then the growth and migration of mesenchymal stem cells (MSCs) on these materials were further evaluated. CD90 immunofluorescence staining showed that fiber alignment exhibited a strong influence on the morphology of MSCs, indicating that the alignment of the scaffolds could determine the distribution of cells. Moreover, smaller diameter and aligned TSF scaffolds are more favorable to the growth of MSCs as compared with 800 nm and 1200 nm random TSF scaffolds. In addition, the increased migration speed and efficiency of MSCs induced by three-D TSF were verified, highlighting the guiding roles of TSF to the migrated MSCs. More importantly, 400 nm aligned TSF scaffolds dramatically improved cell migratory speed and further induced the most efficient migration of MSCs as compared with larger diameter TSF scaffolds. In conclusion, the data demonstrate that smaller diameter and aligned electrospun TSF represent valuable scaffolds for supporting and promoting MSCs growth and migration, thus raising the possibility of manipulating TSF scaffolds to enhance homing and therapeutic potential of MSCs in cellular therapy.

CPAC: Energy-Efficient Data Collection through Adaptive Selection of Compression Algorithms for Sensor Networks

PubMed Central

Lee, HyungJune; Kim, HyunSeok; Chang, Ik Joon

2014-01-01

We propose a technique to optimize the energy efficiency of data collection in sensor networks by exploiting a selective data compression. To achieve such an aim, we need to make optimal decisions regarding two aspects: (1) which sensor nodes should execute compression; and (2) which compression algorithm should be used by the selected sensor nodes. We formulate this problem into binary integer programs, which provide an energy-optimal solution under the given latency constraint. Our simulation results show that the optimization algorithm significantly reduces the overall network-wide energy consumption for data collection. In the environment having a stationary sink from stationary sensor nodes, the optimized data collection shows 47% energy savings compared to the state-of-the-art collection protocol (CTP). More importantly, we demonstrate that our optimized data collection provides the best performance in an intermittent network under high interference. In such networks, we found that the selective compression for frequent packet retransmissions saves up to 55% energy compared to the best known protocol. PMID:24721763

Generalized networking engineering: optimal pricing and routing in multiservice networks

NASA Astrophysics Data System (ADS)

Mitra, Debasis; Wang, Qiong

2002-07-01

One of the functions of network engineering is to allocate resources optimally to forecasted demand. We generalize the mechanism by incorporating price-demand relationships into the problem formulation, and optimizing pricing and routing jointly to maximize total revenue. We consider a network, with fixed topology and link bandwidths, that offers multiple services, such as voice and data, each having characteristic price elasticity of demand, and quality of service and policy requirements on routing. Prices, which depend on service type and origin-destination, determine demands, that are routed, subject to their constraints, so as to maximize revenue. We study the basic properties of the optimal solution and prove that link shadow costs provide the basis for both optimal prices and optimal routing policies. We investigate the impact of input parameters, such as link capacities and price elasticities, on prices, demand growth, and routing policies. Asymptotic analyses, in which network bandwidth is scaled to grow, give results that are noteworthy for their qualitative insights. Several numerical examples illustrate the analyses.

An optimization framework for measuring spatial access over healthcare networks.

PubMed

Li, Zihao; Serban, Nicoleta; Swann, Julie L

2015-07-17

Measurement of healthcare spatial access over a network involves accounting for demand, supply, and network structure. Popular approaches are based on floating catchment areas; however the methods can overestimate demand over the network and fail to capture cascading effects across the system. Optimization is presented as a framework to measure spatial access. Questions related to when and why optimization should be used are addressed. The accuracy of the optimization models compared to the two-step floating catchment area method and its variations is analytically demonstrated, and a case study of specialty care for Cystic Fibrosis over the continental United States is used to compare these approaches. The optimization models capture a patient's experience rather than their opportunities and avoid overestimating patient demand. They can also capture system effects due to change based on congestion. Furthermore, the optimization models provide more elements of access than traditional catchment methods. Optimization models can incorporate user choice and other variations, and they can be useful towards targeting interventions to improve access. They can be easily adapted to measure access for different types of patients, over different provider types, or with capacity constraints in the network. Moreover, optimization models allow differences in access in rural and urban areas.

A molecular design principle of lyotropic liquid-crystalline conjugated polymers with directed alignment capability for plastic electronics

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

Kim, Bong-Gi; Jeong, Eun Jeong; Chung, Jong Won

Conjugated polymers with a one-dimensional p-orbital overlap exhibit optoelectronic anisotropy. Their unique anisotropic properties can be fully realized in device applications only when the conjugated chains are aligned. Here, we report a molecular design principle of conjugated polymers to achieve concentration-regulated chain planarization, self-assembly, liquid-crystal-like good mobility and non-interdigitated side chains. As a consequence of these intra- and intermolecular attributes, chain alignment along an applied flow field occurs. This liquid-crystalline conjugated polymer was realized by incorporating intramolecular sulphur–fluorine interactions and bulky side chains linked to a tetrahedral carbon having a large form factor. By optimizing the polymer concentration and themore » flow field, we could achieve a high dichroic ratio of 16.67 in emission from conducting conjugated polymer films. Two-dimensional grazing-incidence X-ray diffraction was performed to analyse a well-defined conjugated polymer alignment. Thin-film transistors built on highly aligned conjugated polymer films showed more than three orders of magnitude faster carrier mobility along the conjugated polymer alignment direction than the perpendicular direction.« less

Joint Multi-Leaf Segmentation, Alignment, and Tracking for Fluorescence Plant Videos.

PubMed

Yin, Xi; Liu, Xiaoming; Chen, Jin; Kramer, David M

2018-06-01

This paper proposes a novel framework for fluorescence plant video processing. The plant research community is interested in the leaf-level photosynthetic analysis within a plant. A prerequisite for such analysis is to segment all leaves, estimate their structures, and track them over time. We identify this as a joint multi-leaf segmentation, alignment, and tracking problem. First, leaf segmentation and alignment are applied on the last frame of a plant video to find a number of well-aligned leaf candidates. Second, leaf tracking is applied on the remaining frames with leaf candidate transformation from the previous frame. We form two optimization problems with shared terms in their objective functions for leaf alignment and tracking respectively. A quantitative evaluation framework is formulated to evaluate the performance of our algorithm with four metrics. Two models are learned to predict the alignment accuracy and detect tracking failure respectively in order to provide guidance for subsequent plant biology analysis. The limitation of our algorithm is also studied. Experimental results show the effectiveness, efficiency, and robustness of the proposed method.

A low-complexity add-on score for protein remote homology search with COMER.

PubMed

Margelevicius, Mindaugas

2018-06-15

Protein sequence alignment forms the basis for comparative modeling, the most reliable approach to protein structure prediction, among many other applications. Alignment between sequence families, or profile-profile alignment, represents one of the most, if not the most, sensitive means for homology detection but still necessitates improvement. We aim at improving the quality of profile-profile alignments and the sensitivity induced by them by refining profile-profile substitution scores. We have developed a new score that represents an additional component of profile-profile substitution scores. A comprehensive evaluation shows that the new add-on score statistically significantly improves both the sensitivity and the alignment quality of the COMER method. We discuss why the score leads to the improvement and its almost optimal computational complexity that makes it easily implementable in any profile-profile alignment method. An implementation of the add-on score in the open-source COMER software and data are available at https://sourceforge.net/projects/comer. The COMER software is also available on Github at https://github.com/minmarg/comer and as a Docker image (minmar/comer). Supplementary data are available at Bioinformatics online.

Transcription Factor Map Alignment of Promoter Regions

PubMed Central

Blanco, Enrique; Messeguer, Xavier; Smith, Temple F; Guigó, Roderic

2006-01-01

We address the problem of comparing and characterizing the promoter regions of genes with similar expression patterns. This remains a challenging problem in sequence analysis, because often the promoter regions of co-expressed genes do not show discernible sequence conservation. In our approach, thus, we have not directly compared the nucleotide sequence of promoters. Instead, we have obtained predictions of transcription factor binding sites, annotated the predicted sites with the labels of the corresponding binding factors, and aligned the resulting sequences of labels—to which we refer here as transcription factor maps (TF-maps). To obtain the global pairwise alignment of two TF-maps, we have adapted an algorithm initially developed to align restriction enzyme maps. We have optimized the parameters of the algorithm in a small, but well-curated, collection of human–mouse orthologous gene pairs. Results in this dataset, as well as in an independent much larger dataset from the CISRED database, indicate that TF-map alignments are able to uncover conserved regulatory elements, which cannot be detected by the typical sequence alignments. PMID:16733547

Energy optimization system

DOEpatents

Zhou, Zhi; de Bedout, Juan Manuel; Kern, John Michael; Biyik, Emrah; Chandra, Ramu Sharat

2013-01-22

A system for optimizing customer utility usage in a utility network of customer sites, each having one or more utility devices, where customer site is communicated between each of the customer sites and an optimization server having software for optimizing customer utility usage over one or more networks, including private and public networks. A customer site model for each of the customer sites is generated based upon the customer site information, and the customer utility usage is optimized based upon the customer site information and the customer site model. The optimization server can be hosted by an external source or within the customer site. In addition, the optimization processing can be partitioned between the customer site and an external source.

Optimization of controllability and robustness of complex networks by edge directionality

NASA Astrophysics Data System (ADS)

Liang, Man; Jin, Suoqin; Wang, Dingjie; Zou, Xiufen

2016-09-01

Recently, controllability of complex networks has attracted enormous attention in various fields of science and engineering. How to optimize structural controllability has also become a significant issue. Previous studies have shown that an appropriate directional assignment can improve structural controllability; however, the evolution of the structural controllability of complex networks under attacks and cascading has always been ignored. To address this problem, this study proposes a new edge orientation method (NEOM) based on residual degree that changes the link direction while conserving topology and directionality. By comparing the results with those of previous methods in two random graph models and several realistic networks, our proposed approach is demonstrated to be an effective and competitive method for improving the structural controllability of complex networks. Moreover, numerical simulations show that our method is near-optimal in optimizing structural controllability. Strikingly, compared to the original network, our method maintains the structural controllability of the network under attacks and cascading, indicating that the NEOM can also enhance the robustness of controllability of networks. These results alter the view of the nature of controllability in complex networks, change the understanding of structural controllability and affect the design of network models to control such networks.

Call for Papers: Photonics in Switching

NASA Astrophysics Data System (ADS)

Wosinska, Lena; Glick, Madeleine

2006-04-01

Call for Papers: Photonics in Switching

Guest Editors:

Lena Wosinska, Royal Institute of Technology (KTH) / ICT Sweden Madeleine Glick, Intel Research, Cambridge, UK

Scope of Submission

• WDM node architectures
• Novel device technologies enabling photonics in switching, such as optical switch fabrics, optical memory, and wavelength conversion
• Routing protocols
• WDM switching and routing
• Quality of service
• Performance measurement and evaluation
• Next-generation optical networks: architecture, signaling, and control
• Traffic measurement and field trials
• Optical burst and packet switching
• OBS/OPS node architectures
• Burst/Packet scheduling and routing algorithms
• Contention resolution/avoidance strategies
• Services and applications for OBS/OPS (e.g., grid networks, storage-area networks, etc.)
• Burst assembly and ingress traffic shaping
• Hybrid OBS/TDM or OBS/wavelength routing

Manuscript Submission

RNA-SeQC: RNA-seq metrics for quality control and process optimization.

PubMed

DeLuca, David S; Levin, Joshua Z; Sivachenko, Andrey; Fennell, Timothy; Nazaire, Marc-Danie; Williams, Chris; Reich, Michael; Winckler, Wendy; Getz, Gad

2012-06-01

RNA-seq, the application of next-generation sequencing to RNA, provides transcriptome-wide characterization of cellular activity. Assessment of sequencing performance and library quality is critical to the interpretation of RNA-seq data, yet few tools exist to address this issue. We introduce RNA-SeQC, a program which provides key measures of data quality. These metrics include yield, alignment and duplication rates; GC bias, rRNA content, regions of alignment (exon, intron and intragenic), continuity of coverage, 3'/5' bias and count of detectable transcripts, among others. The software provides multi-sample evaluation of library construction protocols, input materials and other experimental parameters. The modularity of the software enables pipeline integration and the routine monitoring of key measures of data quality such as the number of alignable reads, duplication rates and rRNA contamination. RNA-SeQC allows investigators to make informed decisions about sample inclusion in downstream analysis. In summary, RNA-SeQC provides quality control measures critical to experiment design, process optimization and downstream computational analysis. See www.genepattern.org to run online, or www.broadinstitute.org/rna-seqc/ for a command line tool.

Wireless Cooperative Networks: Self-Configuration and Optimization

DTIC Science & Technology

2011-09-09

TERMS wireless sensor networks , wireless cooperative networks, resource optimization, ultra-wideband, localization, ranging 16. SECURITY...Communications We consider two prevalent relay protocols for wireless sensor networks : decode-and-forward (DF) and amplify-and-forward (AF). To... sensor networks where each node may have its own sensing data to transmit, since they can maximally conserve energy while helping others as relays

Image Mapping and Visual Attention on the Sensory Ego-Sphere

NASA Technical Reports Server (NTRS)

Fleming, Katherine Achim; Peters, Richard Alan, II

2012-01-01

The Sensory Ego-Sphere (SES) is a short-term memory for a robot in the form of an egocentric, tessellated, spherical, sensory-motor map of the robot s locale. Visual attention enables fast alignment of overlapping images without warping or position optimization, since an attentional point (AP) on the composite typically corresponds to one on each of the collocated regions in the images. Such alignment speeds analysis of the multiple images of the area. Compositing and attention were performed two ways and compared: (1) APs were computed directly on the composite and not on the full-resolution images until the time of retrieval; and (2) the attentional operator was applied to all incoming imagery. It was found that although the second method was slower, it produced consistent and, thereby, more useful APs. The SES is an integral part of a control system that will enable a robot to learn new behaviors based on its previous experiences, and that will enable it to recombine its known behaviors in such a way as to solve related, but novel, task problems with apparent creativity. The approach is to combine sensory-motor data association and dimensionality reduction to learn navigation and manipulation tasks as sequences of basic behaviors that can be implemented with a small set of closed-loop controllers. Over time, the aggregate of behaviors and their transition probabilities form a stochastic network. Then given a task, the robot finds a path in the network that leads from its current state to the goal. The SES provides a short-term memory for the cognitive functions of the robot, association of sensory and motor data via spatio-temporal coincidence, direction of the attention of the robot, navigation through spatial localization with respect to known or discovered landmarks, and structured data sharing between the robot and human team members, the individuals in multi-robot teams, or with a C3 center.

High-Lift Optimization Design Using Neural Networks on a Multi-Element Airfoil

NASA Technical Reports Server (NTRS)

Greenman, Roxana M.; Roth, Karlin R.; Smith, Charles A. (Technical Monitor)

1998-01-01

The high-lift performance of a multi-element airfoil was optimized by using neural-net predictions that were trained using a computational data set. The numerical data was generated using a two-dimensional, incompressible, Navier-Stokes algorithm with the Spalart-Allmaras turbulence model. Because it is difficult to predict maximum lift for high-lift systems, an empirically-based maximum lift criteria was used in this study to determine both the maximum lift and the angle at which it occurs. Multiple input, single output networks were trained using the NASA Ames variation of the Levenberg-Marquardt algorithm for each of the aerodynamic coefficients (lift, drag, and moment). The artificial neural networks were integrated with a gradient-based optimizer. Using independent numerical simulations and experimental data for this high-lift configuration, it was shown that this design process successfully optimized flap deflection, gap, overlap, and angle of attack to maximize lift. Once the neural networks were trained and integrated with the optimizer, minimal additional computer resources were required to perform optimization runs with different initial conditions and parameters. Applying the neural networks within the high-lift rigging optimization process reduced the amount of computational time and resources by 83% compared with traditional gradient-based optimization procedures for multiple optimization runs.

Trade-offs between robustness and small-world effect in complex networks

PubMed Central

Peng, Guan-Sheng; Tan, Suo-Yi; Wu, Jun; Holme, Petter

2016-01-01

Robustness and small-world effect are two crucial structural features of complex networks and have attracted increasing attention. However, little is known about the relation between them. Here we demonstrate that, there is a conflicting relation between robustness and small-world effect for a given degree sequence. We suggest that the robustness-oriented optimization will weaken the small-world effect and vice versa. Then, we propose a multi-objective trade-off optimization model and develop a heuristic algorithm to obtain the optimal trade-off topology for robustness and small-world effect. We show that the optimal network topology exhibits a pronounced core-periphery structure and investigate the structural properties of the optimized networks in detail. PMID:27853301

Optimal Design of Multitype Groundwater Monitoring Networks Using Easily Accessible Tools.

PubMed

Wöhling, Thomas; Geiges, Andreas; Nowak, Wolfgang

2016-11-01

Monitoring networks are expensive to establish and to maintain. In this paper, we extend an existing data-worth estimation method from the suite of PEST utilities with a global optimization method for optimal sensor placement (called optimal design) in groundwater monitoring networks. Design optimization can include multiple simultaneous sensor locations and multiple sensor types. Both location and sensor type are treated simultaneously as decision variables. Our method combines linear uncertainty quantification and a modified genetic algorithm for discrete multilocation, multitype search. The efficiency of the global optimization is enhanced by an archive of past samples and parallel computing. We demonstrate our methodology for a groundwater monitoring network at the Steinlach experimental site, south-western Germany, which has been established to monitor river-groundwater exchange processes. The target of optimization is the best possible exploration for minimum variance in predicting the mean travel time of the hyporheic exchange. Our results demonstrate that the information gain of monitoring network designs can be explored efficiently and with easily accessible tools prior to taking new field measurements or installing additional measurement points. The proposed methods proved to be efficient and can be applied for model-based optimal design of any type of monitoring network in approximately linear systems. Our key contributions are (1) the use of easy-to-implement tools for an otherwise complex task and (2) yet to consider data-worth interdependencies in simultaneous optimization of multiple sensor locations and sensor types. © 2016, National Ground Water Association.

System, apparatus and methods to implement high-speed network analyzers

DOEpatents

Ezick, James; Lethin, Richard; Ros-Giralt, Jordi; Szilagyi, Peter; Wohlford, David E

2015-11-10

Systems, apparatus and methods for the implementation of high-speed network analyzers are provided. A set of high-level specifications is used to define the behavior of the network analyzer emitted by a compiler. An optimized inline workflow to process regular expressions is presented without sacrificing the semantic capabilities of the processing engine. An optimized packet dispatcher implements a subset of the functions implemented by the network analyzer, providing a fast and slow path workflow used to accelerate specific processing units. Such dispatcher facility can also be used as a cache of policies, wherein if a policy is found, then packet manipulations associated with the policy can be quickly performed. An optimized method of generating DFA specifications for network signatures is also presented. The method accepts several optimization criteria, such as min-max allocations or optimal allocations based on the probability of occurrence of each signature input bit.

Hierarchical winner-take-all particle swarm optimization social network for neural model fitting.

PubMed

Coventry, Brandon S; Parthasarathy, Aravindakshan; Sommer, Alexandra L; Bartlett, Edward L

2017-02-01

Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models.

Navigating neurites utilize cellular topography of Schwann cell somas and processes for optimal guidance

PubMed Central

Lopez-Fagundo, Cristina; Mitchel, Jennifer A.; Ramchal, Talisha D.; Dingle, Yu-Ting L.; Hoffman-Kim, Diane

2013-01-01

The path created by aligned Schwann cells (SCs) after nerve injury underlies peripheral nerve regeneration. We developed geometric bioinspired substrates to extract key information needed for axon guidance by deconstructing the topographical cues presented by SCs. We have previously reported materials that directly replicate SC topography with micro- and nanoscale resolution, but a detailed explanation of the means of directed axon extension on SC topography has not yet been described. Here, using neurite tracing and time-lapse microscopy, we analyzed the SC features that influence axon guidance. Novel poly(dimethylsiloxane) materials, fabricated via photolithography, incorporated bioinspired topographical components with the shapes and sizes of aligned SCs, namely somas and processes, where the length of the processes were varied but the soma geometry and dimensions were kept constant. Rat dorsal root ganglia neurites aligned to all materials presenting bioinspired topography after a 5 days in culture and to bioinspired materials presenting soma and process features after only 17 hours in culture. Key findings of this study were: Neurite response to underlying bioinspired topographical features was time dependent, where at 5 days, neurites aligned most strongly to materials presenting combinations of soma and process features, with higher than average density of either process or soma features; but at 17 hours they aligned more strongly to materials presenting average densities of soma and process features and to materials presenting process features only. These studies elucidate the influence of SC topography on axon guidance in a time-dependent setting and have implications for the optimization of nerve regeneration strategies. PMID:23557939

Simultaneous dual-color fluorescence microscope: a characterization study.

PubMed

Li, Zheng; Chen, Xiaodong; Ren, Liqiang; Song, Jie; Li, Yuhua; Zheng, Bin; Liu, Hong

2013-01-01

High spatial resolution and geometric accuracy is crucial for chromosomal analysis of clinical cytogenetic applications. High resolution and rapid simultaneous acquisition of multiple fluorescent wavelengths can be achieved by utilizing concurrent imaging with multiple detectors. However, such class of microscopic systems functions differently from traditional fluorescence microscopes. To develop a practical characterization framework to assess and optimize the performance of a high resolution and dual-color fluorescence microscope designed for clinical chromosomal analysis. A dual-band microscopic imaging system utilizes a dichroic mirror, two sets of specially selected optical filters, and two detectors to simultaneously acquire two fluorescent wavelengths. The system's geometric distortion, linearity, the modulation transfer function, and the dual detectors' alignment were characterized. Experiment results show that the geometric distortion at lens periphery is less than 1%. Both fluorescent channels show linear signal responses, but there exists discrepancy between the two due to the detectors' non-uniform response ratio to different wavelengths. In terms of the spatial resolution, the two contrast transfer function curves trend agreeably with the spatial frequency. The alignment measurement allows quantitatively assessing the cameras' alignment. A result image of adjusted alignment is demonstrated to show the reduced discrepancy by using the alignment measurement method. In this paper, we present a system characterization study and its methods for a specially designed imaging system for clinical cytogenetic applications. The presented characterization methods are not only unique to this dual-color imaging system but also applicable to evaluation and optimization of other similar multi-color microscopic image systems for improving their clinical utilities for future cytogenetic applications.

Particle swarm optimization-based automatic parameter selection for deep neural networks and its applications in large-scale and high-dimensional data

PubMed Central

2017-01-01

In this paper, we propose a new automatic hyperparameter selection approach for determining the optimal network configuration (network structure and hyperparameters) for deep neural networks using particle swarm optimization (PSO) in combination with a steepest gradient descent algorithm. In the proposed approach, network configurations were coded as a set of real-number m-dimensional vectors as the individuals of the PSO algorithm in the search procedure. During the search procedure, the PSO algorithm is employed to search for optimal network configurations via the particles moving in a finite search space, and the steepest gradient descent algorithm is used to train the DNN classifier with a few training epochs (to find a local optimal solution) during the population evaluation of PSO. After the optimization scheme, the steepest gradient descent algorithm is performed with more epochs and the final solutions (pbest and gbest) of the PSO algorithm to train a final ensemble model and individual DNN classifiers, respectively. The local search ability of the steepest gradient descent algorithm and the global search capabilities of the PSO algorithm are exploited to determine an optimal solution that is close to the global optimum. We constructed several experiments on hand-written characters and biological activity prediction datasets to show that the DNN classifiers trained by the network configurations expressed by the final solutions of the PSO algorithm, employed to construct an ensemble model and individual classifier, outperform the random approach in terms of the generalization performance. Therefore, the proposed approach can be regarded an alternative tool for automatic network structure and parameter selection for deep neural networks. PMID:29236718

Optimization of water-level monitoring networks in the eastern Snake River Plain aquifer using a kriging-based genetic algorithm method

USGS Publications Warehouse

Fisher, Jason C.

2013-01-01

Long-term groundwater monitoring networks can provide essential information for the planning and management of water resources. Budget constraints in water resource management agencies often mean a reduction in the number of observation wells included in a monitoring network. A network design tool, distributed as an R package, was developed to determine which wells to exclude from a monitoring network because they add little or no beneficial information. A kriging-based genetic algorithm method was used to optimize the monitoring network. The algorithm was used to find the set of wells whose removal leads to the smallest increase in the weighted sum of the (1) mean standard error at all nodes in the kriging grid where the water table is estimated, (2) root-mean-squared-error between the measured and estimated water-level elevation at the removed sites, (3) mean standard deviation of measurements across time at the removed sites, and (4) mean measurement error of wells in the reduced network. The solution to the optimization problem (the best wells to retain in the monitoring network) depends on the total number of wells removed; this number is a management decision. The network design tool was applied to optimize two observation well networks monitoring the water table of the eastern Snake River Plain aquifer, Idaho; these networks include the 2008 Federal-State Cooperative water-level monitoring network (Co-op network) with 166 observation wells, and the 2008 U.S. Geological Survey-Idaho National Laboratory water-level monitoring network (USGS-INL network) with 171 wells. Each water-level monitoring network was optimized five times: by removing (1) 10, (2) 20, (3) 40, (4) 60, and (5) 80 observation wells from the original network. An examination of the trade-offs associated with changes in the number of wells to remove indicates that 20 wells can be removed from the Co-op network with a relatively small degradation of the estimated water table map, and 40 wells can be removed from the USGS-INL network before the water table map degradation accelerates. The optimal network designs indicate the robustness of the network design tool. Observation wells were removed from high well-density areas of the network while retaining the spatial pattern of the existing water-table map.

Alignment Test Results of the JWST Pathfinder Telescope Mirrors in the Cryogenic Environment

NASA Technical Reports Server (NTRS)

Whitman, Tony L.; Wells, Conrad; Hadaway, James; Knight, J. Scott; Lunt, Sharon

2016-01-01

After integration of the Optical Telescope Element (OTE) to the Integrated Science Instrument Module (ISIM) to become the OTIS, the James Webb Space Telescope OTIS is tested at NASAs Johnson Space Center (JSC) in the cryogenic vacuum Chamber A for alignment and optical performance. The alignment of the mirrors comprises a sequence of steps as follows: The mirrors are coarsely aligned using photogrammetry cameras with reflective targets attached to the sides of the mirrors. Then a multi-wavelength interferometer is aligned to the 18-segment primary mirror using cameras at the center of curvature to align reflected light from the segments and using fiducials at the edge of the primary mirror. Once the interferometer is aligned, the 18 primary mirror segments are then adjusted to optimize wavefront error of the aggregate mirror. This process phases the piston and tilt positions of all the mirror segments. An optical fiber placed at the Cassegrain focus of the telescope then emits light towards the secondary mirror to create a collimated beam emitting from the primary mirror. Portions of the collimated beam are retro-reflected from flat mirrors at the top of the chamber to pass through the telescope to the SI detector. The image on the detector is used for fine alignment of the secondary mirror and a check of the primary mirror alignment using many of the same analysis techniques used in the on-orbit alignment. The entire process was practiced and evaluated in 2015 at cryogenic temperature with the Pathfinder telescope.

Vertically aligned carbon nanotubes as anode and air-cathode in single chamber microbial fuel cells

NASA Astrophysics Data System (ADS)

Amade, R.; Moreno, H. A.; Hussain, S.; Vila-Costa, M.; Bertran, E.

2016-10-01

Electrode optimization in microbial fuel cells is a key issue to improve the power output and cell performance. Vertically aligned carbon nanotubes (VACNTs) grown on low cost stainless-steel mesh present an attractive approach to increase the cell performance while avoiding the use of expensive Pt-based materials. In comparison with non-aligned carbon nanotubes (NACNTs), VACNTs increase the oxygen reduction reaction taking place at the cathode by a factor of two. In addition, vertical alignment also increases the power density up to 2.5 times with respect to NACNTs. VACNTs grown at the anode can further improve the cell performance by increasing the electrode surface area and thus the electron transfer between bacteria and the electrode. The maximum power density obtained using VACNTs was 14 mW/m2 and 160 mV output voltage.

Traffic signal coordination and queue management in oversaturated intersection.

DOT National Transportation Integrated Search

2011-03-18

Traffic signal timing optimization when done properly, could significantly improve network : performance by reducing delay, increasing network throughput, reducing number of stops, or : increasing average speed in the network. The optimization can be...

Traffic signal coordination and queue management in oversaturated intersections.

DOT National Transportation Integrated Search

2011-03-18

Traffic signal timing optimization when done properly, could significantly improve network performance by reducing delay, increasing network throughput, reducing number of stops, or increasing average speed in the network. The optimization can become...

Language comprehension and brain function in individuals with an optimal outcome from autism.

PubMed

Eigsti, Inge-Marie; Stevens, Michael C; Schultz, Robert T; Barton, Marianne; Kelley, Elizabeth; Naigles, Letitia; Orinstein, Alyssa; Troyb, Eva; Fein, Deborah A

2016-01-01

Although Autism Spectrum Disorder (ASD) is generally a lifelong disability, a minority of individuals with ASD overcome their symptoms to such a degree that they are generally indistinguishable from their typically-developing peers. That is, they have achieved an Optimal Outcome (OO). The question addressed by the current study is whether this normalized behavior reflects normalized brain functioning, or alternatively, the action of compensatory systems. Either possibility is plausible, as most participants with OO received years of intensive therapy that could alter brain networks to align with typical function or work around ASD-related neural dysfunction. Individuals ages 8 to 21 years with high-functioning ASD (n = 23), OO (n = 16), or typical development (TD; n = 20) completed a functional MRI scan while performing a sentence comprehension task. Results indicated similar activations in frontal and temporal regions (left middle frontal, left supramarginal, and right superior temporal gyri) and posterior cingulate in OO and ASD groups, where both differed from the TD group. Furthermore, the OO group showed heightened "compensatory" activation in numerous left- and right-lateralized regions (left precentral/postcentral gyri, right precentral gyrus, left inferior parietal lobule, right supramarginal gyrus, left superior temporal/parahippocampal gyrus, left middle occipital gyrus) and cerebellum, relative to both ASD and TD groups. Behaviorally normalized language abilities in OO individuals appear to utilize atypical brain networks, with increased recruitment of language-specific as well as right homologue and other systems. Early intensive learning and experience may normalize behavioral language performance in OO, but some brain regions involved in language processing may continue to display characteristics that are more similar to ASD than typical development, while others show characteristics not like ASD or typical development.

Optimizing topological cascade resilience based on the structure of terrorist networks.

PubMed

Gutfraind, Alexander

2010-11-10

Complex socioeconomic networks such as information, finance and even terrorist networks need resilience to cascades--to prevent the failure of a single node from causing a far-reaching domino effect. We show that terrorist and guerrilla networks are uniquely cascade-resilient while maintaining high efficiency, but they become more vulnerable beyond a certain threshold. We also introduce an optimization method for constructing networks with high passive cascade resilience. The optimal networks are found to be based on cells, where each cell has a star topology. Counterintuitively, we find that there are conditions where networks should not be modified to stop cascades because doing so would come at a disproportionate loss of efficiency. Implementation of these findings can lead to more cascade-resilient networks in many diverse areas.

Alignment-free detection of horizontal gene transfer between closely related bacterial genomes.

PubMed

Domazet-Lošo, Mirjana; Haubold, Bernhard

2011-09-01

Bacterial epidemics are often caused by strains that have acquired their increased virulence through horizontal gene transfer. Due to this association with disease, the detection of horizontal gene transfer continues to receive attention from microbiologists and bioinformaticians alike. Most software for detecting transfer events is based on alignments of sets of genes or of entire genomes. But despite great advances in the design of algorithms and computer programs, genome alignment remains computationally challenging. We have therefore developed an alignment-free algorithm for rapidly detecting horizontal gene transfer between closely related bacterial genomes. Our implementation of this algorithm is called alfy for "ALignment Free local homologY" and is freely available from http://guanine.evolbio.mpg.de/alfy/. In this comment we demonstrate the application of alfy to the genomes of Staphylococcus aureus. We also argue that-contrary to popular belief and in spite of increasing computer speed-algorithmic optimization is becoming more, not less, important if genome data continues to accumulate at the present rate.

Ultrahigh density alignment of carbon nanotube arrays by dielectrophoresis.

PubMed

Shekhar, Shashank; Stokes, Paul; Khondaker, Saiful I

2011-03-22

We report ultrahigh density assembly of aligned single-walled carbon nanotube (SWNT) two-dimensional arrays via AC dielectrophoresis using high-quality surfactant-free and stable SWNT solutions. After optimization of frequency and trapping time, we can reproducibly control the linear density of the SWNT between prefabricated electrodes from 0.5 SWNT/μm to more than 30 SWNT/μm by tuning the concentration of the nanotubes in the solution. Our maximum density of 30 SWNT/μm is the highest for aligned arrays via any solution processing technique reported so far. Further increase of SWNT concentration results in a dense array with multiple layers. We discuss how the orientation and density of the nanotubes vary with concentrations and channel lengths. Electrical measurement data show that the densely packed aligned arrays have low sheet resistances. Selective removal of metallic SWNTs via controlled electrical breakdown produced field-effect transistors with high current on-off ratio. Ultrahigh density alignment reported here will have important implications in fabricating high-quality devices for digital and analog electronics.

NASA Tech Briefs, October 2010

NASA Technical Reports Server (NTRS)

2010-01-01

Topics covered include: Hybrid Architecture Active Wavefront Sensing and Control; Carbon-Nanotube-Based Chemical Gas Sensor; Aerogel-Positronium Technology for the Detection of Small Quantities of Organic and/or Toxic Materials; Graphene-Based Reversible Nano-Switch/Sensor Schottky Diode; Inductive Non-Contact Position Sensor; High-Temperature Surface-Acoustic-Wave Transducer; Grid-Sphere Electrodes for Contact with Ionospheric Plasma; Enabling IP Header Compression in COTS Routers via Frame Relay on a Simplex Link; Ka-Band SiGe Receiver Front-End MMIC for Transponder Applications; Robust Optimization Design Algorithm for High-Frequency TWTs; Optimal and Local Connectivity Between Neuron and Synapse Array in the Quantum Dot/Silicon Brain; Method and Circuit for In-Situ Health Monitoring of Solar Cells in Space; BGen: A UML Behavior Network Generator Tool; Platform for Post-Processing Waveform-Based NDE; Electrochemical Hydrogen Peroxide Generator; Fabrication of Single, Vertically Aligned Carbon Nanotubes in 3D Nanoscale Architectures; Process to Create High-Fidelity Lunar Dust Simulants; Lithium-Ion Electrolytes Containing Phosphorous-Based, Flame-Retardant Additives; InGaP Heterojunction Barrier Solar Cells; Straight-Pore Microfilter with Efficient Regeneration; Determining Shear Stress Distribution in a Laminate; Self-Adjusting Liquid Injectors for Combustors; Handling Qualities Prediction of an F-16XL-Based Reduced Sonic Boom Aircraft; Tele-Robotic ATHLETE Controller for Kinematics - TRACK; Three-Wheel Brush-Wheel Sampler; Heterodyne Interferometer Angle Metrology; Aligning Astronomical Telescopes via Identification of Stars; Generation of Optical Combs in a WGM Resonator from a Bichromatic Pump; Large-Format AlGaN PIN Photodiode Arrays for UV Images; Fiber-Coupled Planar Light-Wave Circuit for Seed Laser Control in High Spectral Resolution Lidar Systems; On Calculating the Zero-Gravity Surface Figure of a Mirror; Optical Modification of Casimir Forces for Improved Function of Micro- and Nano-Scale Devices; Analysis, Simulation, and Verification of Knowledge-Based, Rule-Based, and Expert Systems; Core and Off-Core Processes in Systems Engineering; Digital Reconstruction Supporting Investigation of Mishaps; and Template Matching Approach to Signal Prediction.

A Domain Decomposition Parallelization of the Fast Marching Method

NASA Technical Reports Server (NTRS)

Herrmann, M.

2003-01-01

In this paper, the first domain decomposition parallelization of the Fast Marching Method for level sets has been presented. Parallel speedup has been demonstrated in both the optimal and non-optimal domain decomposition case. The parallel performance of the proposed method is strongly dependent on load balancing separately the number of nodes on each side of the interface. A load imbalance of nodes on either side of the domain leads to an increase in communication and rollback operations. Furthermore, the amount of inter-domain communication can be reduced by aligning the inter-domain boundaries with the interface normal vectors. In the case of optimal load balancing and aligned inter-domain boundaries, the proposed parallel FMM algorithm is highly efficient, reaching efficiency factors of up to 0.98. Future work will focus on the extension of the proposed parallel algorithm to higher order accuracy. Also, to further enhance parallel performance, the coupling of the domain decomposition parallelization to the G(sub 0)-based parallelization will be investigated.

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization.

PubMed

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-03-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization

PubMed Central

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-01-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm. PMID:28257060

A combined geostatistical-optimization model for the optimal design of a groundwater quality monitoring network

NASA Astrophysics Data System (ADS)

Kolosionis, Konstantinos; Papadopoulou, Maria P.

2017-04-01

Monitoring networks provide essential information for water resources management especially in areas with significant groundwater exploitation due to extensive agricultural activities. In this work, a simulation-optimization framework is developed based on heuristic optimization methodologies and geostatistical modeling approaches to obtain an optimal design for a groundwater quality monitoring network. Groundwater quantity and quality data obtained from 43 existing observation locations at 3 different hydrological periods in Mires basin in Crete, Greece will be used in the proposed framework in terms of Regression Kriging to develop the spatial distribution of nitrates concentration in the aquifer of interest. Based on the existing groundwater quality mapping, the proposed optimization tool will determine a cost-effective observation wells network that contributes significant information to water managers and authorities. The elimination of observation wells that add little or no beneficial information to groundwater level and quality mapping of the area can be obtain using estimations uncertainty and statistical error metrics without effecting the assessment of the groundwater quality. Given the high maintenance cost of groundwater monitoring networks, the proposed tool could used by water regulators in the decision-making process to obtain a efficient network design that is essential.

An ontology for sensor networks

NASA Astrophysics Data System (ADS)

Compton, Michael; Neuhaus, Holger; Bermudez, Luis; Cox, Simon

2010-05-01

Sensors and networks of sensors are important ways of monitoring and digitizing reality. As the number and size of sensor networks grows, so too does the amount of data collected. Users of such networks typically need to discover the sensors and data that fit their needs without necessarily understanding the complexities of the network itself. The burden on users is eased if the network and its data are expressed in terms of concepts familiar to the users and their job functions, rather than in terms of the network or how it was designed. Furthermore, the task of collecting and combining data from multiple sensor networks is made easier if metadata about the data and the networks is stored in a format and conceptual models that is amenable to machine reasoning and inference. While the OGC's (Open Geospatial Consortium) SWE (Sensor Web Enablement) standards provide for the description and access to data and metadata for sensors, they do not provide facilities for abstraction, categorization, and reasoning consistent with standard technologies. Once sensors and networks are described using rich semantics (that is, by using logic to describe the sensors, the domain of interest, and the measurements) then reasoning and classification can be used to analyse and categorise data, relate measurements with similar information content, and manage, query and task sensors. This will enable types of automated processing and logical assurance built on OGC standards. The W3C SSN-XG (Semantic Sensor Networks Incubator Group) is producing a generic ontology to describe sensors, their environment and the measurements they make. The ontology provides definitions for the structure of sensors and observations, leaving the details of the observed domain unspecified. This allows abstract representations of real world entities, which are not observed directly but through their observable qualities. Domain semantics, units of measurement, time and time series, and location and mobility ontologies can be easily attached when instantiating the ontology for any particular sensors in a domain. After a review of previous work on the specification of sensors, the group is developing the ontology in conjunction with use case development. Part of the difficulty of such work is that relevant concepts from for example OGC standards and other ontologies must be identified and aligned and also placed in a consistent and logically correct way into the ontology. In terms of alignment with OGC's SWE, the ontology is intended to be able to model concepts from SensorML and O&M. Similar to SensorML and O&M, the ontology is based around concepts of systems, processes, and observations. It supports the description of the physical and processing structure of sensors. Sensors are not constrained to physical sensing devices: rather a sensor is anything that can estimate or calculate the value of a phenomenon, so a device or computational process or combination could play the role of a sensor. The representation of a sensor in the ontology links together what is measured (the domain phenomena), the sensor's physical and other properties and its functions and processing. Parts of the ontology are well aligned with SensorML and O&M, but parts are not, and the group is working to understand how differences from (and alignment with) the OGC standards affect the application of the ontology.

RAMTaB: Robust Alignment of Multi-Tag Bioimages

PubMed Central

Raza, Shan-e-Ahmed; Humayun, Ahmad; Abouna, Sylvie; Nattkemper, Tim W.; Epstein, David B. A.; Khan, Michael; Rajpoot, Nasir M.

2012-01-01

Background In recent years, new microscopic imaging techniques have evolved to allow us to visualize several different proteins (or other biomolecules) in a visual field. Analysis of protein co-localization becomes viable because molecules can interact only when they are located close to each other. We present a novel approach to align images in a multi-tag fluorescence image stack. The proposed approach is applicable to multi-tag bioimaging systems which (a) acquire fluorescence images by sequential staining and (b) simultaneously capture a phase contrast image corresponding to each of the fluorescence images. To the best of our knowledge, there is no existing method in the literature, which addresses simultaneous registration of multi-tag bioimages and selection of the reference image in order to maximize the overall overlap between the images. Methodology/Principal Findings We employ a block-based method for registration, which yields a confidence measure to indicate the accuracy of our registration results. We derive a shift metric in order to select the Reference Image with Maximal Overlap (RIMO), in turn minimizing the total amount of non-overlapping signal for a given number of tags. Experimental results show that the Robust Alignment of Multi-Tag Bioimages (RAMTaB) framework is robust to variations in contrast and illumination, yields sub-pixel accuracy, and successfully selects the reference image resulting in maximum overlap. The registration results are also shown to significantly improve any follow-up protein co-localization studies. Conclusions For the discovery of protein complexes and of functional protein networks within a cell, alignment of the tag images in a multi-tag fluorescence image stack is a key pre-processing step. The proposed framework is shown to produce accurate alignment results on both real and synthetic data. Our future work will use the aligned multi-channel fluorescence image data for normal and diseased tissue specimens to analyze molecular co-expression patterns and functional protein networks. PMID:22363510

Design and fabrication of advanced fiber alignment structures for field-installable fiber connectors

NASA Astrophysics Data System (ADS)

Van Erps, Jürgen; Vervaeke, Michael; Sánchez Martínez, Alberto; Beri, Stefano; Debaes, Christof; Watté, Jan; Thienpont, Hugo

2012-06-01

Fiber-To-The-Home (FTTH) networks have been adopted as a potential replacement of traditional electrical connections for the 'last mile' transmission of information at bandwidths over 1Gb/s. However, the success and adoption of optical access networks critically depend on the quality and reliability of connections between optical fibers. In particular a further reduction of insertion loss of field-installable connectors must be achieved without a significant increase in component cost. This requires precise alignment of fibers that can differ in terms of ellipticity, eccentricity or diameter and seems hardly achievable using today's widespread ferrule-based alignment systems. Novel low-cost structures for bare fiber alignment with outstanding positioning accuracies are strongly desired as they would allow reducing loss beyond the level achievable with ferrule-bore systems. However, the realization of such alignment system is challenging as it should provide sufficient force to position the fiber with sub-micron accuracy required in positioning the fiber. In this contribution we propose, design and prototype a bare-fiber alignment system which makes use of deflectable/compressible micro-cantilevers. Such cantilevers behave as springs and provide self-centering functionality to the structure. Simulations of the mechanical properties of the cantilevers are carried out in order to get an analytical approximation and a mathematical model of the spring constant and stress in the structure. Elastic constants of the order of 104 to 105N/m are found out to be compatible with a proof stress of 70 MPa. Finally a first self-centering structure is prototyped in PMMA using our Deep Proton Writing technology. The spring constants of the fabricated cantilevers are in the range of 4 to 6 × 104N/m and the stress is in the range 10 to 20 MPa. These self-centering structures have the potential to become the basic building blocks for a new generation of field-installable connectors.

Minimum energy control and optimal-satisfactory control of Boolean control network

NASA Astrophysics Data System (ADS)

Li, Fangfei; Lu, Xiwen

2013-12-01

In the literatures, to transfer the Boolean control network from the initial state to the desired state, the expenditure of energy has been rarely considered. Motivated by this, this Letter investigates the minimum energy control and optimal-satisfactory control of Boolean control network. Based on the semi-tensor product of matrices and Floyd's algorithm, minimum energy, constrained minimum energy and optimal-satisfactory control design for Boolean control network are given respectively. A numerical example is presented to illustrate the efficiency of the obtained results.

Effect of electric field induced alignment and dispersion of functionalized carbon nanotubes on properties of natural rubber

NASA Astrophysics Data System (ADS)

Gao, Jiangshan; He, Yan; Gong, Xiubin

2018-06-01

The original equipment and method for orienting multi-walled carbon nanotubes (MWCNTs) in natural rubber (NR) by alternating current (AC) electric field were reported in the present study. MWCNTs with various volume fractions were dispersed in the mixture latex which composed of natural rubber, additives and methylbenzene. The application of AC electric field during nanocomposites curing process was used to induce the formation of aligned conductive nanotube networks between the electrodes. The aligned MWCNTs in the composites have a better orientation performance and dispersion quality than these of random MWCNTs by analyzing TEM and SEM images. The effects of MWCNTs anisotropy on thermal conductivity, dielectric properties, and dynamic mechanical properties of NR were studied. The mean value of thermal conductivity of composites loading with aligned MWCNTs was 8.67% higher than that of composites with random MWCNTs due to the anisotropy of aligned MWCNTs. The compounds with aligned MWCNTs possessed low dielectric constant, loss tangents and conductivity, namely a good insulativity. The compounds loading with aligned MWCNTs had lower loss modulus and better dynamic mechanical properties than those with random MWCNTs. This method can make full use of the high thermal conductivity of MWCNTs axis, and expand the application areas of natural rubber like conducting heat in a certain direction with a high efficiency.

The Impact of Imaging Modality on the Measurement of Coronal Plane Alignment After Total Knee Arthroplasty.

PubMed

Nam, Denis; Vajapey, Sravya; Nunley, Ryan M; Barrack, Robert L

2016-10-01

The optimal coronal alignment after total knee arthroplasty (TKA) has become an area of increased debate. Sources of variability among investigations include the radiographic technique used for both preoperative surgical planning and postoperative alignment assessments. This study's purpose was to assess the impact of the imaging modality used on the measurement of coronal plane alignment after TKA. A consecutive series of patients undergoing TKA using the same cruciate-retaining prosthesis were included for analysis. Postoperatively, all patients received both a rotationally controlled, scout computed tomography scan and a hip-knee-ankle (HKA) image using the EOS Imaging system (EOS Inc., Paris, France). Two, independent observers measured the HKA angle, and femoral and tibial component alignment from each image. After classifying overall and component alignment as neutral, varus, or valgus, 40.6% (65 of 160) of knees had a discordant alignment classification for HKA, 28.1% (45 of 160) for femoral component alignment, and 26.9% (43 of 160) for tibial component alignment between their computed tomography and EOS images. Overall, 24.4% (39 of 160) of patients had a HKA difference of ≥3° between the 2 images, whereas 18.8% (30 of 160) and 20.0% (32 of 160) of patients had a femoral and tibial component alignment difference of ≥2°, respectively. Significant differences are present when comparing 2 measurement techniques of mechanical alignment after TKA. The impact of imaging modality on postoperative assessments must be accounted for and be consistent when comparing the results of different investigations. Copyright © 2016 Elsevier Inc. All rights reserved.

Transition of vertically aligned liquid crystal driven by fan-shaped electric field

NASA Astrophysics Data System (ADS)

Tsung, J. W.; Ting, T. L.; Chen, C. Y.; Liang, W. L.; Lai, C. W.; Lin, T. H.; Hsu, W. H.

2017-09-01

Interdigital electrodes are implemented in many commercial and novel liquid crystal devices to align molecules. Although many empirical principles and patents apply to electrode design, only a few numerical simulations of alignment have been conducted. Why and how the molecules align in an ordered manner has never been adequately explained. Hence, this investigation addresses the Fréedericksz transition of vertically aligned liquid crystal that is driven by fishbone electrodes, and thereafter identifies the mechanism of liquid crystal alignment. Theoretical calculations suggest that the periodic deformation that is caused by the fan-shaped fringe field minimizes the free energy in the liquid crystal cell, and the optimal alignment can be obtained when the cell parameters satisfy the relation p /2 d =√{k11/k33 } , where p is the spatial period of the strips of the electrode; d denotes the cell gap; and k11 and k33 are the splay and bend elastic constants of the liquid crystal, respectively. Polymer-stabilized vertical alignment test cells with various p values and spacings between the electrodes were fabricated, and the process of liquid crystal alignment was observed under an optical microscope. The degree of alignment was evaluated by measuring the transmittance of the test cell. The experimental results were consistent with the theoretical predictions. The principle of design, p /2 d =√{k11/k33 } , greatly improves the uniformity and stability of the aligned liquid crystal. The methods that are presented here can be further applied to cholesteric liquid crystal and other self-assembled soft materials.

Mechanical function near defects in an aligned nanofiber composite is preserved by inclusion of disorganized layers: Insight into meniscus structure and function.

PubMed

Bansal, Sonia; Mandalapu, Sai; Aeppli, Céline; Qu, Feini; Szczesny, Spencer E; Mauck, Robert L; Zgonis, Miltiadis H

2017-07-01

The meniscus is comprised of circumferentially aligned fibers that resist the tensile forces within the meniscus (i.e., hoop stress) that develop during loading of the knee. Although these circumferential fibers are severed by radial meniscal tears, tibial contact stresses do not increase until the tear reaches ∼90% of the meniscus width, suggesting that the severed circumferential fibers still bear load and maintain the mechanical functionality of the meniscus. Recent data demonstrates that the interfibrillar matrix can transfer strain energy to disconnected fibrils in tendon fascicles. In the meniscus, interdigitating radial tie fibers, which function to stabilize and bind the circumferential fibers together, are hypothesized to function in a similar manner by transmitting load to severed circumferential fibers near a radial tear. To test this hypothesis, we developed an engineered fibrous analog of the knee meniscus using poly(ε-caprolactone) to create aligned scaffolds with variable amounts of non-aligned elements embedded within the scaffold. We show that the tensile properties of these scaffolds are a function of the ratio of aligned to non-aligned elements, and change in a predictable fashion following a simple mixture model. When measuring the loss of mechanical function in scaffolds with a radial tear, compared to intact scaffolds, the decrease in apparent linear modulus was reduced in scaffolds containing non-aligned layers compared to purely aligned scaffolds. Increased strains in areas adjacent to the defect were also noted in composite scaffolds. These findings indicate that non-aligned (disorganized) elements interspersed within an aligned network can improve overall mechanical function by promoting strain transfer to nearby disconnected fibers. This finding supports the notion that radial tie fibers may similarly promote tear tolerance in the knee meniscus, and will direct changes in clinical practice and provide guidance for tissue engineering strategies. The meniscus is a complex fibrous tissue, whose architecture includes radial tie fibers that run perpendicular to and interdigitate with the predominant circumferential fibers. We hypothesized that these radial elements function to preserve mechanical function in the context of interruption of circumferential bundles, as would be the case in a meniscal tear. To test this hypothesis, we developed a biomaterial analog containing disorganized layers enmeshed regularly throughout an otherwise aligned network. Using this material formulation, we showed that strain transmission is improved in the vicinity of defects when disorganized fiber layers were present. This supports the idea that radial elements within the meniscus improve function near a tear, and will guide future clinical interventions and the development of engineered replacements. Copyright © 2017 Acta Materialia Inc. All rights reserved.

Design framework for entanglement-distribution switching networks

NASA Astrophysics Data System (ADS)

Drost, Robert J.; Brodsky, Michael

2016-09-01

The distribution of quantum entanglement appears to be an important component of applications of quantum communications and networks. The ability to centralize the sourcing of entanglement in a quantum network can provide for improved efficiency and enable a variety of network structures. A necessary feature of an entanglement-sourcing network node comprising several sources of entangled photons is the ability to reconfigurably route the generated pairs of photons to network neighbors depending on the desired entanglement sharing of the network users at a given time. One approach to such routing is the use of a photonic switching network. The requirements for an entanglement distribution switching network are less restrictive than for typical conventional applications, leading to design freedom that can be leveraged to optimize additional criteria. In this paper, we present a mathematical framework defining the requirements of an entanglement-distribution switching network. We then consider the design of such a switching network using a number of 2 × 2 crossbar switches, addressing the interconnection of these switches and efficient routing algorithms. In particular, we define a worst-case loss metric and consider 6 × 6, 8 × 8, and 10 × 10 network designs that optimize both this metric and the number of crossbar switches composing the network. We pay particular attention to the 10 × 10 network, detailing novel results proving the optimality of the proposed design. These optimized network designs have great potential for use in practical quantum networks, thus advancing the concept of quantum networks toward reality.

Cyclic mechanical stretch contributes to network development of osteocyte-like cells with morphological change and autophagy promotion but without preferential cell alignment in rat.

PubMed

Inaba, Nao; Kuroshima, Shinichiro; Uto, Yusuke; Sasaki, Muneteru; Sawase, Takashi

2017-09-01

Osteocytes play important roles in controlling bone quality as well as preferential alignment of biological apatite c -axis/collagen fibers. However, the relationship between osteocytes and mechanical stress remains unclear due to the difficulty of three-dimensional (3D) culture of osteocytes in vitro . The aim of this study was to investigate the effect of cyclic mechanical stretch on 3D-cultured osteocyte-like cells. Osteocyte-like cells were established using rat calvarial osteoblasts cultured in a 3D culture system. Cyclic mechanical stretch (8% amplitude at a rate of 2 cycles min -1 ) was applied for 24, 48 and 96 consecutive hours. Morphology, cell number and preferential cell alignment were evaluated. Apoptosis- and autophagy-related gene expression levels were measured using quantitative PCR. 3D-cultured osteoblasts became osteocyte-like cells that expressed osteocyte-specific genes such as Dmp1 , Cx43 , Sost , Fgf23 and RANKL , with morphological changes similar to osteocytes. Cell number was significantly decreased in a time-dependent manner under non-loaded conditions, whereas cyclic mechanical stretch significantly prevented decreased cell numbers with increased expression of anti-apoptosis-related genes. Moreover, cyclic mechanical stretch significantly decreased cell size and ellipticity with increased expression of autophagy-related genes, LC3b and atg7 . Interestingly, preferential cell alignment did not occur, irrespective of mechanical stretch. These findings suggest that an anti-apoptotic effect contributes to network development of osteocyte-like cells under loaded condition. Spherical change of osteocyte-like cells induced by mechanical stretch may be associated with autophagy upregulation. Preferential alignment of osteocytes induced by mechanical load in vivo may be partially predetermined before osteoblasts differentiate into osteocytes and embed into bone matrix.

Neural dynamic programming and its application to control systems

NASA Astrophysics Data System (ADS)

Seong, Chang-Yun

There are few general practical feedback control methods for nonlinear MIMO (multi-input-multi-output) systems, although such methods exist for their linear counterparts. Neural Dynamic Programming (NDP) is proposed as a practical design method of optimal feedback controllers for nonlinear MIMO systems. NDP is an offspring of both neural networks and optimal control theory. In optimal control theory, the optimal solution to any nonlinear MIMO control problem may be obtained from the Hamilton-Jacobi-Bellman equation (HJB) or the Euler-Lagrange equations (EL). The two sets of equations provide the same solution in different forms: EL leads to a sequence of optimal control vectors, called Feedforward Optimal Control (FOC); HJB yields a nonlinear optimal feedback controller, called Dynamic Programming (DP). DP produces an optimal solution that can reject disturbances and uncertainties as a result of feedback. Unfortunately, computation and storage requirements associated with DP solutions can be problematic, especially for high-order nonlinear systems. This dissertation presents an approximate technique for solving the DP problem based on neural network techniques that provides many of the performance benefits (e.g., optimality and feedback) of DP and benefits from the numerical properties of neural networks. We formulate neural networks to approximate optimal feedback solutions whose existence DP justifies. We show the conditions under which NDP closely approximates the optimal solution. Finally, we introduce the learning operator characterizing the learning process of the neural network in searching the optimal solution. The analysis of the learning operator provides not only a fundamental understanding of the learning process in neural networks but also useful guidelines for selecting the number of weights of the neural network. As a result, NDP finds---with a reasonable amount of computation and storage---the optimal feedback solutions to nonlinear MIMO control problems that would be very difficult to solve with DP. NDP was demonstrated on several applications such as the lateral autopilot logic for a Boeing 747, the minimum fuel control of a double-integrator plant with bounded control, the backward steering of a two-trailer truck, and the set-point control of a two-link robot arm.

Manganese oxide nanowires, films, and membranes and methods of making

DOEpatents

Suib, Steven Lawrence [Storrs, CT; Yuan, Jikang [Storrs, CT

2008-10-21

Nanowires, films, and membranes comprising ordered porous manganese oxide-based octahedral molecular sieves, and methods of making, are disclosed. A single crystal ultra-long nanowire includes an ordered porous manganese oxide-based octahedral molecular sieve, and has an average length greater than about 10 micrometers and an average diameter of about 5 nanometers to about 100 nanometers. A film comprises a microporous network comprising a plurality of single crystal nanowires in the form of a layer, wherein a plurality of layers is stacked on a surface of a substrate, wherein the nanowires of each layer are substantially axially aligned. A free standing membrane comprises a microporous network comprising a plurality of single crystal nanowires in the form of a layer, wherein a plurality of layers is aggregately stacked, and wherein the nanowires of each layer are substantially axially aligned.

Automated interpretation of ventilation-perfusion lung scintigrams for the diagnosis of pulmonary embolism using artificial neural networks.

PubMed

Holst, H; Aström, K; Järund, A; Palmer, J; Heyden, A; Kahl, F; Tägil, K; Evander, E; Sparr, G; Edenbrandt, L

2000-04-01

The purpose of this study was to develop a completely automated method for the interpretation of ventilation-perfusion (V-P) lung scintigrams used in the diagnosis of pulmonary embolism. An artificial neural network was trained for the diagnosis of pulmonary embolism using 18 automatically obtained features from each set of V-P scintigrams. The techniques used to process the images included their alignment to templates, the construction of quotient images based on the ventilation and perfusion images, and the calculation of measures describing V-P mismatches in the quotient images. The templates represented lungs of normal size and shape without any pathological changes. Images that could not be properly aligned to the templates were detected and excluded automatically. After exclusion of those V-P scintigrams not properly aligned to the templates, 478 V-P scintigrams remained in a training group of consecutive patients with suspected pulmonary embolism, and a further 87 V-P scintigrams formed a separate test group comprising patients who had undergone pulmonary angiography. The performance of the neural network, measured as the area under the receiver operating characteristic curve, was 0.87 (95% confidence limits 0.82-0.92) in the training group and 0.79 (0.69-0.88) in the test group. It is concluded that a completely automated method can be used for the interpretation of V-P scintigrams. The performance of this method is similar to others previously presented, whereby features were extracted manually.

3-D Survey Applied to Industrial Archaeology by Tls Methodology

NASA Astrophysics Data System (ADS)

Monego, M.; Fabris, M.; Menin, A.; Achilli, V.

2017-05-01

This work describes the three-dimensional survey of "Ex Stazione Frigorifera Specializzata": initially used for agricultural storage, during the years it was allocated to different uses until the complete neglect. The historical relevance and the architectural heritage that this building represents has brought the start of a recent renovation project and functional restoration. In this regard it was necessary a global 3-D survey that was based on the application and integration of different geomatic methodologies (mainly terrestrial laser scanner, classical topography, and GNSS). The acquisitions of point clouds was performed using different laser scanners: with time of flight (TOF) and phase shift technologies for the distance measurements. The topographic reference network, needed for scans alignment in the same system, was measured with a total station. For the complete survey of the building, 122 scans were acquired and 346 targets were measured from 79 vertices of the reference network. Moreover, 3 vertices were measured with GNSS methodology in order to georeference the network. For the detail survey of machine room were executed 14 scans with 23 targets. The 3-D global model of the building have less than one centimeter of error in the alignment (for the machine room the error in alignment is not greater than 6 mm) and was used to extract products such as longitudinal and transversal sections, plans, architectural perspectives, virtual scans. A complete spatial knowledge of the building is obtained from the processed data, providing basic information for restoration project, structural analysis, industrial and architectural heritage valorization.

Second Harmonic Generation Mediated by Aligned Water in Starch Granules.

PubMed

Cisek, Richard; Tokarz, Danielle; Krouglov, Serguei; Steup, Martin; Emes, Michael J; Tetlow, Ian J; Barzda, Virginijus

2014-12-26

The origin of second harmonic generation (SHG) in starch granules was investigated using ab initio quantum mechanical modeling and experimentally examined using polarization-in, polarization-out (PIPO) second harmonic generation microscopy. Ab initio calculations revealed that the largest contribution to the SHG signal from A- and B-type allomorphs of starch originates from the anisotropic organization of hydroxide and hydrogen bonds mediated by aligned water found in the polymers. The hypothesis was experimentally tested by imaging maize starch granules under various hydration and heat treatment conditions that alter the hydrogen bond network. The highest SHG intensity was found in fully hydrated starch granules, and heat treatment diminished the SHG intensity. The PIPO SHG imaging showed that dried starch granules have a much higher nonlinear optical susceptibility component ratio than fully hydrated granules. In contrast, deuterated starch granules showed a smaller susceptibility component ratio demonstrating that SHG is highly sensitive to the organization of the hydroxyl and hydrogen bond network. The polarization SHG imaging results of potato starch granules, representing starch allomorph B, were compared to those of maize starch granules representing allomorph A. The results showed that the amount of aligned water was higher in the maize granules. Nonlinear microscopy of starch granules provides evidence that varying hydration conditions leads to significant changes in the nonlinear susceptibility ratio as well as the SHG intensity, supporting the hypothesis from ab initio calculations that the dominant contribution to SHG is due to the ordered hydroxide and hydrogen bond network.

Application of a neural network to simulate analysis in an optimization process

NASA Technical Reports Server (NTRS)

Rogers, James L.; Lamarsh, William J., II

1992-01-01

A new experimental software package called NETS/PROSSS aimed at reducing the computing time required to solve a complex design problem is described. The software combines a neural network for simulating the analysis program with an optimization program. The neural network is applied to approximate results of a finite element analysis program to quickly obtain a near-optimal solution. Results of the NETS/PROSSS optimization process can also be used as an initial design in a normal optimization process and make it possible to converge to an optimum solution with significantly fewer iterations.

A constraint optimization based virtual network mapping method

NASA Astrophysics Data System (ADS)

Li, Xiaoling; Guo, Changguo; Wang, Huaimin; Li, Zhendong; Yang, Zhiwen

2013-03-01

Virtual network mapping problem, maps different virtual networks onto the substrate network is an extremely challenging work. This paper proposes a constraint optimization based mapping method for solving virtual network mapping problem. This method divides the problem into two phases, node mapping phase and link mapping phase, which are all NP-hard problems. Node mapping algorithm and link mapping algorithm are proposed for solving node mapping phase and link mapping phase, respectively. Node mapping algorithm adopts the thinking of greedy algorithm, mainly considers two factors, available resources which are supplied by the nodes and distance between the nodes. Link mapping algorithm is based on the result of node mapping phase, adopts the thinking of distributed constraint optimization method, which can guarantee to obtain the optimal mapping with the minimum network cost. Finally, simulation experiments are used to validate the method, and results show that the method performs very well.

Self-configuration and self-optimization process in heterogeneous wireless networks.

PubMed

Guardalben, Lucas; Villalba, Luis Javier García; Buiati, Fábio; Sobral, João Bosco Mangueira; Camponogara, Eduardo

2011-01-01

Self-organization in Wireless Mesh Networks (WMN) is an emergent research area, which is becoming important due to the increasing number of nodes in a network. Consequently, the manual configuration of nodes is either impossible or highly costly. So it is desirable for the nodes to be able to configure themselves. In this paper, we propose an alternative architecture for self-organization of WMN based on Optimized Link State Routing Protocol (OLSR) and the ad hoc on demand distance vector (AODV) routing protocols as well as using the technology of software agents. We argue that the proposed self-optimization and self-configuration modules increase the throughput of network, reduces delay transmission and network load, decreases the traffic of HELLO messages according to network's scalability. By simulation analysis, we conclude that the self-optimization and self-configuration mechanisms can significantly improve the performance of OLSR and AODV protocols in comparison to the baseline protocols analyzed.

Automated assembly of VECSEL components

NASA Astrophysics Data System (ADS)

Brecher, C.; Pyschny, N.; Haag, S.; Mueller, T.

2013-02-01

Due to the architectural advantage of an external cavity architecture that enables the integration of additional elements into the cavity (e.g. for mode control, frequency conversion, wavelength tuning or passive mode-locking) VECSELs are a rapidly developing laser technology. Nevertheless they often have to compete with direct (edge) emitting laser diodes which can have significant cost advantages thanks to their rather simple structure and production processes. One way to compensate the economical disadvantages of VECSELs is to optimize each component in terms of quality and costs and to apply more efficient (batch) production processes. In this context, the paper presents recent process developments for the automated assembly of VECSELs using a new type of desktop assembly station with an ultra-precise micromanipulator. The core concept is to create a dedicated process development environment from which implemented processes can be transferred fluently to production equipment. By now two types of processes have been put into operation on the desktop assembly station: 1.) passive alignment of the pump optics implementing a camera-based alignment process, where the pump spot geometry and position on the semiconductor chip is analyzed and evaluated; 2.) active alignment of the end mirror based on output power measurements and optimization algorithms. In addition to the core concept and corresponding hardware and software developments, detailed results of both processes are presented explaining measurement setups as well as alignment strategies and results.

A Robust Method to Generate Mechanically Anisotropic Vascular Smooth Muscle Cell Sheets for Vascular Tissue Engineering.

PubMed

Backman, Daniel E; LeSavage, Bauer L; Shah, Shivem B; Wong, Joyce Y

2017-06-01

In arterial tissue engineering, mimicking native structure and mechanical properties is essential because compliance mismatch can lead to graft failure and further disease. With bottom-up tissue engineering approaches, designing tissue components with proper microscale mechanical properties is crucial to achieve the necessary macroscale properties in the final implant. This study develops a thermoresponsive cell culture platform for growing aligned vascular smooth muscle cell (VSMC) sheets by photografting N-isopropylacrylamide (NIPAAm) onto micropatterned poly(dimethysiloxane) (PDMS). The grafting process is experimentally and computationally optimized to produce PNIPAAm-PDMS substrates optimal for VSMC attachment. To allow long-term VSMC sheet culture and increase the rate of VSMC sheet formation, PNIPAAm-PDMS surfaces were further modified with 3-aminopropyltriethoxysilane yielding a robust, thermoresponsive cell culture platform for culturing VSMC sheets. VSMC cell sheets cultured on patterned thermoresponsive substrates exhibit cellular and collagen alignment in the direction of the micropattern. Mechanical characterization of patterned, single-layer VSMC sheets reveals increased stiffness in the aligned direction compared to the perpendicular direction whereas nonpatterned cell sheets exhibit no directional dependence. Structural and mechanical anisotropy of aligned, single-layer VSMC sheets makes this platform an attractive microstructural building block for engineering a vascular graft to match the in vivo mechanical properties of native arterial tissue. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Propagation of high-energy laser beams through the earth's atmosphere II; Proceedings of the Meeting, Los Angeles, CA, Jan. 21-23, 1991

NASA Technical Reports Server (NTRS)

Ulrich, Peter B. (Editor); Wilson, Leroy E. (Editor)

1991-01-01

Consideration is given to turbulence at the inner scale, modeling turbulent transport in laser beam propagation, variable wind direction effects on thermal blooming correction, realistic wind effects on turbulence and thermal blooming compensation, wide bandwidth spectral measurements of atmospheric tilt turbulence, remote alignment of adaptive optical systems with far-field optimization, focusing infrared laser beams on targets in space without using adaptive optics, and a simplex optimization method for adaptive optics system alignment. Consideration is also given to ground-to-space multiline propagation at 1.3 micron, a path integral approach to thermal blooming, functional reconstruction predictions of uplink whole beam Strehl ratios in the presence of thermal blooming, and stability analysis of semidiscrete schemes for thermal blooming computation.

High-resolution comparative modeling with RosettaCM.

PubMed

Song, Yifan; DiMaio, Frank; Wang, Ray Yu-Ruei; Kim, David; Miles, Chris; Brunette, Tj; Thompson, James; Baker, David

2013-10-08

We describe an improved method for comparative modeling, RosettaCM, which optimizes a physically realistic all-atom energy function over the conformational space defined by homologous structures. Given a set of sequence alignments, RosettaCM assembles topologies by recombining aligned segments in Cartesian space and building unaligned regions de novo in torsion space. The junctions between segments are regularized using a loop closure method combining fragment superposition with gradient-based minimization. The energies of the resulting models are optimized by all-atom refinement, and the most representative low-energy model is selected. The CASP10 experiment suggests that RosettaCM yields models with more accurate side-chain and backbone conformations than other methods when the sequence identity to the templates is greater than ∼15%. Copyright © 2013 Elsevier Ltd. All rights reserved.

Advanced Accelerators for Medical Applications

NASA Astrophysics Data System (ADS)

Uesaka, Mitsuru; Koyama, Kazuyoshi

We review advanced accelerators for medical applications with respect to the following key technologies: (i) higher RF electron linear accelerator (hereafter “linac”); (ii) optimization of alignment for the proton linac, cyclotron and synchrotron; (iii) superconducting magnet; (iv) laser technology. Advanced accelerators for medical applications are categorized into two groups. The first group consists of compact medical linacs with high RF, cyclotrons and synchrotrons downsized by optimization of alignment and superconducting magnets. The second group comprises laser-based acceleration systems aimed of medical applications in the future. Laser plasma electron/ion accelerating systems for cancer therapy and laser dielectric accelerating systems for radiation biology are mentioned. Since the second group has important potential for a compact system, the current status of the established energy and intensity and of the required stability are given.

Advanced Accelerators for Medical Applications

NASA Astrophysics Data System (ADS)

Uesaka, Mitsuru; Koyama, Kazuyoshi

We review advanced accelerators for medical applications with respect to the following key technologies: (i) higher RF electron linear accelerator (hereafter "linac"); (ii) optimization of alignment for the proton linac, cyclotron and synchrotron; (iii) superconducting magnet; (iv) laser technology. Advanced accelerators for medical applications are categorized into two groups. The first group consists of compact medical linacs with high RF, cyclotrons and synchrotrons downsized by optimization of alignment and superconducting magnets. The second group comprises laserbased acceleration systems aimed of medical applications in the future. Laser plasma electron/ion accelerating systems for cancer therapy and laser dielectric accelerating systems for radiation biology are mentioned. Since the second group has important potential for a compact system, the current status of the established energy and intensity and of the required stability are given.

Quantum Assisted Learning for Registration of MODIS Images

NASA Astrophysics Data System (ADS)

Pelissier, C.; Le Moigne, J.; Fekete, G.; Halem, M.

2017-12-01

The advent of the first large scale quantum annealer by D-Wave has led to an increased interest in quantum computing. However, the quantum annealing computer of the D-Wave is limited to either solving Quadratic Unconstrained Binary Optimization problems (QUBOs) or using the ground state sampling of an Ising system that can be produced by the D-Wave. These restrictions make it challenging to find algorithms to accelerate the computation of typical Earth Science applications. A major difficulty is that most applications have continuous real-valued parameters rather than binary. Here we present an exploratory study using the ground state sampling to train artificial neural networks (ANNs) to carry out image registration of MODIS images. The key idea to using the D-Wave to train networks is that the quantum chip behaves thermally like Boltzmann machines (BMs), and BMs are known to be successful at recognizing patterns in images. The ground state sampling of the D-Wave also depends on the dynamics of the adiabatic evolution and is subject to other non-thermal fluctuations, but the statistics are thought to be similar and ANNs tend to be robust under fluctuations. In light of this, the D-Wave ground state sampling is used to define a Boltzmann like generative model and is investigated to register MODIS images. Image intensities of MODIS images are transformed using a Discrete Cosine Transform and used to train a several layers network to learn how to align images to a reference image. The network layers consist of an initial sigmoid layer acting as a binary filter of the input followed by a strict binarization using Bernoulli sampling, and then fed into a Boltzmann machine. The output is then classified using a soft-max layer. Results are presented and discussed.

Analysis of power management and system latency in wireless sensor networks

NASA Astrophysics Data System (ADS)

Oswald, Matthew T.; Rohwer, Judd A.; Forman, Michael A.

2004-08-01

Successful power management in a wireless sensor network requires optimization of the protocols which affect energy-consumption on each node and the aggregate effects across the larger network. System optimization for a given deployment scenario requires an analysis and trade off of desired node and network features with their associated costs. The sleep protocol for an energy-efficient wireless sensor network for event detection, target classification, and target tracking developed at Sandia National Laboratories is presented. The dynamic source routing (DSR) algorithm is chosen to reduce network maintenance overhead, while providing a self-configuring and self-healing network architecture. A method for determining the optimal sleep time is developed and presented, providing reference data which spans several orders of magnitude. Message timing diagrams show, that a node in a five-node cluster, employing an optimal cyclic single-radio sleep protocol, consumes 3% more energy and incurs a 16-s increase latency than nodes employing the more complex dual-radio STEM protocol.

A Task-Optimized Neural Network Replicates Human Auditory Behavior, Predicts Brain Responses, and Reveals a Cortical Processing Hierarchy.

PubMed

Kell, Alexander J E; Yamins, Daniel L K; Shook, Erica N; Norman-Haignere, Sam V; McDermott, Josh H

2018-05-02

A core goal of auditory neuroscience is to build quantitative models that predict cortical responses to natural sounds. Reasoning that a complete model of auditory cortex must solve ecologically relevant tasks, we optimized hierarchical neural networks for speech and music recognition. The best-performing network contained separate music and speech pathways following early shared processing, potentially replicating human cortical organization. The network performed both tasks as well as humans and exhibited human-like errors despite not being optimized to do so, suggesting common constraints on network and human performance. The network predicted fMRI voxel responses substantially better than traditional spectrotemporal filter models throughout auditory cortex. It also provided a quantitative signature of cortical representational hierarchy-primary and non-primary responses were best predicted by intermediate and late network layers, respectively. The results suggest that task optimization provides a powerful set of tools for modeling sensory systems. Copyright © 2018 Elsevier Inc. All rights reserved.

CAFE: aCcelerated Alignment-FrEe sequence analysis

PubMed Central

Lu, Yang Young; Tang, Kujin; Ren, Jie; Fuhrman, Jed A.; Waterman, Michael S.

2017-01-01

Abstract Alignment-free genome and metagenome comparisons are increasingly important with the development of next generation sequencing (NGS) technologies. Recently developed state-of-the-art k-mer based alignment-free dissimilarity measures including CVTree, \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$d_2^*$\\end{document} and \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$d_2^S$\\end{document} are more computationally expensive than measures based solely on the k-mer frequencies. Here, we report a standalone software, aCcelerated Alignment-FrEe sequence analysis (CAFE), for efficient calculation of 28 alignment-free dissimilarity measures. CAFE allows for both assembled genome sequences and unassembled NGS shotgun reads as input, and wraps the output in a standard PHYLIP format. In downstream analyses, CAFE can also be used to visualize the pairwise dissimilarity measures, including dendrograms, heatmap, principal coordinate analysis and network display. CAFE serves as a general k-mer based alignment-free analysis platform for studying the relationships among genomes and metagenomes, and is freely available at https://github.com/younglululu/CAFE. PMID:28472388

Optimal quantum networks and one-shot entropies

NASA Astrophysics Data System (ADS)

Chiribella, Giulio; Ebler, Daniel

2016-09-01

We develop a semidefinite programming method for the optimization of quantum networks, including both causal networks and networks with indefinite causal structure. Our method applies to a broad class of performance measures, defined operationally in terms of interative tests set up by a verifier. We show that the optimal performance is equal to a max relative entropy, which quantifies the informativeness of the test. Building on this result, we extend the notion of conditional min-entropy from quantum states to quantum causal networks. The optimization method is illustrated in a number of applications, including the inversion, charge conjugation, and controlization of an unknown unitary dynamics. In the non-causal setting, we show a proof-of-principle application to the maximization of the winning probability in a non-causal quantum game.

Discrete particle swarm optimization for identifying community structures in signed social networks.

PubMed

Cai, Qing; Gong, Maoguo; Shen, Bo; Ma, Lijia; Jiao, Licheng

2014-10-01

Modern science of networks has facilitated us with enormous convenience to the understanding of complex systems. Community structure is believed to be one of the notable features of complex networks representing real complicated systems. Very often, uncovering community structures in networks can be regarded as an optimization problem, thus, many evolutionary algorithms based approaches have been put forward. Particle swarm optimization (PSO) is an artificial intelligent algorithm originated from social behavior such as birds flocking and fish schooling. PSO has been proved to be an effective optimization technique. However, PSO was originally designed for continuous optimization which confounds its applications to discrete contexts. In this paper, a novel discrete PSO algorithm is suggested for identifying community structures in signed networks. In the suggested method, particles' status has been redesigned in discrete form so as to make PSO proper for discrete scenarios, and particles' updating rules have been reformulated by making use of the topology of the signed network. Extensive experiments compared with three state-of-the-art approaches on both synthetic and real-world signed networks demonstrate that the proposed method is effective and promising. Copyright © 2014 Elsevier Ltd. All rights reserved.

Neural coordination can be enhanced by occasional interruption of normal firing patterns: a self-optimizing spiking neural network model.

PubMed

Woodward, Alexander; Froese, Tom; Ikegami, Takashi

2015-02-01

The state space of a conventional Hopfield network typically exhibits many different attractors of which only a small subset satisfies constraints between neurons in a globally optimal fashion. It has recently been demonstrated that combining Hebbian learning with occasional alterations of normal neural states avoids this problem by means of self-organized enlargement of the best basins of attraction. However, so far it is not clear to what extent this process of self-optimization is also operative in real brains. Here we demonstrate that it can be transferred to more biologically plausible neural networks by implementing a self-optimizing spiking neural network model. In addition, by using this spiking neural network to emulate a Hopfield network with Hebbian learning, we attempt to make a connection between rate-based and temporal coding based neural systems. Although further work is required to make this model more realistic, it already suggests that the efficacy of the self-optimizing process is independent from the simplifying assumptions of a conventional Hopfield network. We also discuss natural and cultural processes that could be responsible for occasional alteration of neural firing patterns in actual brains. Copyright © 2014 Elsevier Ltd. All rights reserved.

Optimization with artificial neural network systems - A mapping principle and a comparison to gradient based methods

NASA Technical Reports Server (NTRS)

Leong, Harrison Monfook

1988-01-01

General formulae for mapping optimization problems into systems of ordinary differential equations associated with artificial neural networks are presented. A comparison is made to optimization using gradient-search methods. The performance measure is the settling time from an initial state to a target state. A simple analytical example illustrates a situation where dynamical systems representing artificial neural network methods would settle faster than those representing gradient-search. Settling time was investigated for a more complicated optimization problem using computer simulations. The problem was a simplified version of a problem in medical imaging: determining loci of cerebral activity from electromagnetic measurements at the scalp. The simulations showed that gradient based systems typically settled 50 to 100 times faster than systems based on current neural network optimization methods.

Remote Sensing of Subsurface Fractures in the Otway Basin, South Australia

NASA Astrophysics Data System (ADS)

Bailey, Adam; King, Rosalind; Holford, Simon; Hand, Martin

2013-04-01

A detailed understanding of naturally occurring fracture networks within the subsurface is becoming increasingly important to the energy sector, as the focus of exploration has expanded to include unconventional reservoirs such as coal seam gas, shale gas, tight gas, and engineered geothermal systems. Successful production from such reservoirs, where primary porosity and permeability is often negligible, is heavily reliant on structural permeability provided by naturally occurring and induced fracture networks, permeability, which is often not provided for through primary porosity and permeability. In this study the Penola Trough, located within the onshore Otway Basin in South Australia, is presented as a case study for remotely detecting and defining subsurface fracture networks that may contribute to secondary permeability. This area is prospective for shale and tight gas and geothermal energy. The existence and nature of natural fractures is verified through an integrated analysis of geophysical logs (including wellbore image logs) and 3D seismic data. Wellbore image logs from 11 petroleum wells within the Penola Trough were interpreted for both stress indicators and natural fractures. A total of 507 naturally occurring fractures were identified, striking approximately WNE-ESE. Fractures which are aligned in the in-situ stress field are optimally oriented for reactivation, and are hence likely to be open to fluid flow. Fractures are identifiable as being either resistive or conductive sinusoids on the resistivity image logs used in this study. Resistive fractures, of which 239 were identified, are considered to be cemented with electrically resistive cements (such as quartz or calcite) and thus closed to fluid flow. Conductive fractures, of which 268 were identified, are considered to be uncemented and open to fluid flow, and thus important to geothermal exploration. Fracture susceptibility diagrams constructed for the identified fractures illustrate that the conductive fractures are optimally oriented for reactivation in the present-day strike-slip fault regime, and so are likely to be open to fluid flow. To gain an understanding of the broader extent of these natural fractures, it is necessary to analyse more regional 3D seismic data. It is well documented that fault and fracture networks like those generally observed in image logs lie well below seismic amplitude resolution, making them difficult to observe directly on amplitude data. However, seismic attributes can be calculated to provide some information on sub-seismic scale structural and stratigraphic features. Using the merged Balnaves/Haselgrove 3D seismic cube acquired over the Penola Trough, attribute maps of complex multi-trace dip-steered coherency and most positive curvature, among others, were used to document the presence of discontinuities within the seismic data which area likely to represent natural fractures, and to best constrain the likely extent of the fracture network which they form. The resulting fracture network model displays relatively good connectivity surrounding structural features intersecting the studied horizons, although large areas lacking significant discontinuities are observed. These areas make it unlikely that the fracture network contributes to permeability on a basin-wide scale, though observed features are optimally oriented for reactivation under contemporary stress conditions and are thus likely to provide at least local increases in permeability.

Acceleration of short and long DNA read mapping without loss of accuracy using suffix array.

PubMed

Tárraga, Joaquín; Arnau, Vicente; Martínez, Héctor; Moreno, Raul; Cazorla, Diego; Salavert-Torres, José; Blanquer-Espert, Ignacio; Dopazo, Joaquín; Medina, Ignacio

2014-12-01

HPG Aligner applies suffix arrays for DNA read mapping. This implementation produces a highly sensitive and extremely fast mapping of DNA reads that scales up almost linearly with read length. The approach presented here is faster (over 20× for long reads) and more sensitive (over 98% in a wide range of read lengths) than the current state-of-the-art mappers. HPG Aligner is not only an optimal alternative for current sequencers but also the only solution available to cope with longer reads and growing throughputs produced by forthcoming sequencing technologies. https://github.com/opencb/hpg-aligner. © The Author 2014. Published by Oxford University Press.

Preparation of Liquid Crystal Networks for Macroscopic Oscillatory Motion Induced by Light.

PubMed

Vantomme, Ghislaine; Gelebart, Anne Helene; Broer, Dirk J; Meijer, E W

2017-09-20

A strategy based on doped liquid crystalline networks is described to create mechanical self-sustained oscillations of plastic films under continuous light irradiation. The photo-excitation of dopants that can quickly dissipate light into heat, coupled with anisotropic thermal expansion and self-shadowing of the film, gives rise to the self-sustained deformation. The oscillations observed are influenced by the dimensions and the modulus of the film, and by the directionality and intensity of the light. The system developed offers applications in energy conversion and harvesting for soft-robotics and automated systems. The general method described here consists of creating free-standing liquid crystalline films and characterizing the mechanical and thermal effects observed. The molecular alignment is achieved using alignment layers (rubbed polyimide), commonly used in the display manufacturing industry. To obtain actuators with large deformation, the mesogens are aligned and polymerized in a splay/bend configuration, i.e., with the director of the liquid crystals (LCs) going gradually from planar to homeotropic through the film thickness. Upon irradiation, the mechanical and thermal oscillations obtained are monitored with a high-speed camera. The results are further quantified by image analysis using an image processing program.

Preparation of Liquid Crystal Networks for Macroscopic Oscillatory Motion Induced by Light

PubMed Central

Broer, Dirk J.; Meijer, E. W.

2017-01-01

A strategy based on doped liquid crystalline networks is described to create mechanical self-sustained oscillations of plastic films under continuous light irradiation. The photo-excitation of dopants that can quickly dissipate light into heat, coupled with anisotropic thermal expansion and self-shadowing of the film, gives rise to the self-sustained deformation. The oscillations observed are influenced by the dimensions and the modulus of the film, and by the directionality and intensity of the light. The system developed offers applications in energy conversion and harvesting for soft-robotics and automated systems. The general method described here consists of creating free-standing liquid crystalline films and characterizing the mechanical and thermal effects observed. The molecular alignment is achieved using alignment layers (rubbed polyimide), commonly used in the display manufacturing industry. To obtain actuators with large deformation, the mesogens are aligned and polymerized in a splay/bend configuration, i.e., with the director of the liquid crystals (LCs) going gradually from planar to homeotropic through the film thickness. Upon irradiation, the mechanical and thermal oscillations obtained are monitored with a high-speed camera. The results are further quantified by image analysis using an image processing program. PMID:28994766

A multiwavelength frequency-domain near-infrared cerebral oximeter

NASA Astrophysics Data System (ADS)

Kurth, C. Dean; Thayer, William S.

1999-03-01

This study tests a multiwavelength frequency-domain near-infrared oximeter (fdNIRS) in an in vitro model of the human brain. The model is a solid plastic structure containing a vascular network perfused with blood in which haemoglobin oxygen saturation was measured by co-oximetry, providing a standard for comparison. Plastic shells of varying thickness (0.5-2 cm), with a vascular network of their own and encircling the brain model, were also added to simulate extracranial tissues of the infant, child and adult. The fdNIRS oximeter utilizes frequency-domain technology to monitor phaseshifts at 754 nm, 785 nm and 816 nm relative to a 780 nm reference to derive through photon transport and Beer-Lambert equations. We found a linear relationship between fdNIRS and co-oximetry with excellent correlation that fitted the line of identity in all experiments ( n = 7). The bias of fdNIRS oximetry was -2% and the precision was 6%. Blood temperature and fdNIRS source-detector distance did not affect fdNIRS oximetry. Low haemoglobin concentration altered the fdNIRS versus co-oximetry line slope and intercept, producing a 15% error at the extremes of . The infant- and child-like shells overlying the brain model did not alter fdNIRS oximetry, whereas the adult-like shell yielded an error as high as 32%. In conclusion, fdNIRS accurately measures in an in vitro brain model, although low haemoglobin concentration and extracranial tissue of adult thickness influence accuracy.

Optimal input sizes for neural network de-interlacing

NASA Astrophysics Data System (ADS)

Choi, Hyunsoo; Seo, Guiwon; Lee, Chulhee

2009-02-01

Neural network de-interlacing has shown promising results among various de-interlacing methods. In this paper, we investigate the effects of input size for neural networks for various video formats when the neural networks are used for de-interlacing. In particular, we investigate optimal input sizes for CIF, VGA and HD video formats.