Tractable Pareto Optimization of Temporal Preferences

NASA Technical Reports Server (NTRS)

Morris, Robert; Morris, Paul; Khatib, Lina; Venable, Brent

2003-01-01

This paper focuses on temporal constraint problems where the objective is to optimize a set of local preferences for when events occur. In previous work, a subclass of these problems has been formalized as a generalization of Temporal CSPs, and a tractable strategy for optimization has been proposed, where global optimality is defined as maximizing the minimum of the component preference values. This criterion for optimality, which we call 'Weakest Link Optimization' (WLO), is known to have limited practical usefulness because solutions are compared only on the basis of their worst value; thus, there is no requirement to improve the other values. To address this limitation, we introduce a new algorithm that re-applies WLO iteratively in a way that leads to improvement of all the values. We show the value of this strategy by proving that, with suitable preference functions, the resulting solutions are Pareto Optimal.

An Algorithm for the Mixed Transportation Network Design Problem

PubMed Central

Liu, Xinyu; Chen, Qun

2016-01-01

This paper proposes an optimization algorithm, the dimension-down iterative algorithm (DDIA), for solving a mixed transportation network design problem (MNDP), which is generally expressed as a mathematical programming with equilibrium constraint (MPEC). The upper level of the MNDP aims to optimize the network performance via both the expansion of the existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium (UE) problem. The idea of the proposed solution algorithm (DDIA) is to reduce the dimensions of the problem. A group of variables (discrete/continuous) is fixed to optimize another group of variables (continuous/discrete) alternately; then, the problem is transformed into solving a series of CNDPs (continuous network design problems) and DNDPs (discrete network design problems) repeatedly until the problem converges to the optimal solution. The advantage of the proposed algorithm is that its solution process is very simple and easy to apply. Numerical examples show that for the MNDP without budget constraint, the optimal solution can be found within a few iterations with DDIA. For the MNDP with budget constraint, however, the result depends on the selection of initial values, which leads to different optimal solutions (i.e., different local optimal solutions). Some thoughts are given on how to derive meaningful initial values, such as by considering the budgets of new and reconstruction projects separately. PMID:27626803

Exact and Optimal Quantum Mechanics/Molecular Mechanics Boundaries.

PubMed

Sun, Qiming; Chan, Garnet Kin-Lic

2014-09-09

Motivated by recent work in density matrix embedding theory, we define exact link orbitals that capture all quantum mechanical (QM) effects across arbitrary quantum mechanics/molecular mechanics (QM/MM) boundaries. Exact link orbitals are rigorously defined from the full QM solution, and their number is equal to the number of orbitals in the primary QM region. Truncating the exact set yields a smaller set of link orbitals optimal with respect to reproducing the primary region density matrix. We use the optimal link orbitals to obtain insight into the limits of QM/MM boundary treatments. We further analyze the popular general hybrid orbital (GHO) QM/MM boundary across a test suite of molecules. We find that GHOs are often good proxies for the most important optimal link orbital, although there is little detailed correlation between the detailed GHO composition and optimal link orbital valence weights. The optimal theory shows that anions and cations cannot be described by a single link orbital. However, expanding to include the second most important optimal link orbital in the boundary recovers an accurate description. The second optimal link orbital takes the chemically intuitive form of a donor or acceptor orbital for charge redistribution, suggesting that optimal link orbitals can be used as interpretative tools for electron transfer. We further find that two optimal link orbitals are also sufficient for boundaries that cut across double bonds. Finally, we suggest how to construct "approximately" optimal link orbitals for practical QM/MM calculations.

Popularity versus similarity in growing networks.

PubMed

Papadopoulos, Fragkiskos; Kitsak, Maksim; Serrano, M Ángeles; Boguñá, Marián; Krioukov, Dmitri

2012-09-27

The principle that 'popularity is attractive' underlies preferential attachment, which is a common explanation for the emergence of scaling in growing networks. If new connections are made preferentially to more popular nodes, then the resulting distribution of the number of connections possessed by nodes follows power laws, as observed in many real networks. Preferential attachment has been directly validated for some real networks (including the Internet), and can be a consequence of different underlying processes based on node fitness, ranking, optimization, random walks or duplication. Here we show that popularity is just one dimension of attractiveness; another dimension is similarity. We develop a framework in which new connections optimize certain trade-offs between popularity and similarity, instead of simply preferring popular nodes. The framework has a geometric interpretation in which popularity preference emerges from local optimization. As opposed to preferential attachment, our optimization framework accurately describes the large-scale evolution of technological (the Internet), social (trust relationships between people) and biological (Escherichia coli metabolic) networks, predicting the probability of new links with high precision. The framework that we have developed can thus be used for predicting new links in evolving networks, and provides a different perspective on preferential attachment as an emergent phenomenon.

Optimal investments in digital communication systems in primary exchange area

NASA Astrophysics Data System (ADS)

Garcia, R.; Hornung, R.

1980-11-01

Integer linear optimization theory, following Gomory's method, was applied to the model planning of telecommunication networks in which all future investments are made in digital systems only. The integer decision variables are the number of digital systems set up on cable or radiorelay links that can be installed. The objective function is the total cost of the extension of the existing line capacity to meet the demand between primary and local exchanges. Traffic volume constraints and flow conservation in transit nodes complete the model. Results indicating computing time and method efficiency are illustrated by an example.

Optimizing the Galileo space communication link

NASA Technical Reports Server (NTRS)

Statman, J. I.

1994-01-01

The Galileo mission was originally designed to investigate Jupiter and its moons utilizing a high-rate, X-band (8415 MHz) communication downlink with a maximum rate of 134.4 kb/sec. However, following the failure of the high-gain antenna (HGA) to fully deploy, a completely new communication link design was established that is based on Galileo's S-band (2295 MHz), low-gain antenna (LGA). The new link relies on data compression, local and intercontinental arraying of antennas, a (14,1/4) convolutional code, a (255,M) variable-redundancy Reed-Solomon code, decoding feedback, and techniques to reprocess recorded data to greatly reduce data losses during signal acquisition. The combination of these techniques will enable return of significant science data from the mission.

Evolutionary conservation of codon optimality reveals hidden signatures of cotranslational folding.

PubMed

Pechmann, Sebastian; Frydman, Judith

2013-02-01

The choice of codons can influence local translation kinetics during protein synthesis. Whether codon preference is linked to cotranslational regulation of polypeptide folding remains unclear. Here, we derive a revised translational efficiency scale that incorporates the competition between tRNA supply and demand. Applying this scale to ten closely related yeast species, we uncover the evolutionary conservation of codon optimality in eukaryotes. This analysis reveals universal patterns of conserved optimal and nonoptimal codons, often in clusters, which associate with the secondary structure of the translated polypeptides independent of the levels of expression. Our analysis suggests an evolved function for codon optimality in regulating the rhythm of elongation to facilitate cotranslational polypeptide folding, beyond its previously proposed role of adapting to the cost of expression. These findings establish how mRNA sequences are generally under selection to optimize the cotranslational folding of corresponding polypeptides.

A Scheme to Smooth Aggregated Traffic from Sensors with Periodic Reports

PubMed Central

Oh, Sungmin; Jang, Ju Wook

2017-01-01

The possibility of smoothing aggregated traffic from sensors with varying reporting periods and frame sizes to be carried on an access link is investigated. A straightforward optimization would take O(pn) time, whereas our heuristic scheme takes O(np) time where n, p denote the number of sensors and size of periods, respectively. Our heuristic scheme performs local optimization sensor by sensor, starting with the smallest to largest periods. This is based on an observation that sensors with large offsets have more choices in offsets to avoid traffic peaks than the sensors with smaller periods. A MATLAB simulation shows that our scheme excels the known scheme by M. Grenier et al. in a similar situation (aggregating periodic traffic in a controller area network) for almost all possible permutations. The performance of our scheme is very close to the straightforward optimization, which compares all possible permutations. We expect that our scheme would greatly contribute in smoothing the traffic from an ever-increasing number of IoT sensors to the gateway, reducing the burden on the access link to the Internet. PMID:28273831

A Scheme to Smooth Aggregated Traffic from Sensors with Periodic Reports.

PubMed

Oh, Sungmin; Jang, Ju Wook

2017-03-03

The possibility of smoothing aggregated traffic from sensors with varying reporting periods and frame sizes to be carried on an access link is investigated. A straightforward optimization would take O(pn) time, whereas our heuristic scheme takes O(np) time where n, p denote the number of sensors and size of periods, respectively. Our heuristic scheme performs local optimization sensor by sensor, starting with the smallest to largest periods. This is based on an observation that sensors with large offsets have more choices in offsets to avoid traffic peaks than the sensors with smaller periods. A MATLAB simulation shows that our scheme excels the known scheme by M. Grenier et al. in a similar situation (aggregating periodic traffic in a controller area network) for almost all possible permutations. The performance of our scheme is very close to the straightforward optimization, which compares all possible permutations. We expect that our scheme would greatly contribute in smoothing the traffic from an ever-increasing number of IoT sensors to the gateway, reducing the burden on the access link to the Internet.

MinFinder v2.0: An improved version of MinFinder

NASA Astrophysics Data System (ADS)

Tsoulos, Ioannis G.; Lagaris, Isaac E.

2008-10-01

A new version of the "MinFinder" program is presented that offers an augmented linking procedure for Fortran-77 subprograms, two additional stopping rules and a new start-point rejection mechanism that saves a significant portion of gradient and function evaluations. The method is applied on a set of standard test functions and the results are reported. New version program summaryProgram title: MinFinder v2.0 Catalogue identifier: ADWU_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADWU_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC Licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 14 150 No. of bytes in distributed program, including test data, etc.: 218 144 Distribution format: tar.gz Programming language used: GNU C++, GNU FORTRAN, GNU C Computer: The program is designed to be portable in all systems running the GNU C++ compiler Operating system: Linux, Solaris, FreeBSD RAM: 200 000 bytes Classification: 4.9 Catalogue identifier of previous version: ADWU_v1_0 Journal reference of previous version: Computer Physics Communications 174 (2006) 166-179 Does the new version supersede the previous version?: Yes Nature of problem: A multitude of problems in science and engineering are often reduced to minimizing a function of many variables. There are instances that a local optimum does not correspond to the desired physical solution and hence the search for a better solution is required. Local optimization techniques can be trapped in any local minimum. Global optimization is then the appropriate tool. For example, solving a non-linear system of equations via optimization, one may encounter many local minima that do not correspond to solutions, i.e. they are far from zero. Solution method: Using a uniform pdf, points are sampled from a rectangular domain. A clustering technique, based on a typical distance and a gradient criterion, is used to decide from which points a local search should be started. Further searching is terminated when all the local minima inside the search domain are thought to be found. This is accomplished via three stopping rules: the "double-box" stopping rule, the "observables" stopping rule and the "expected minimizers" stopping rule. Reasons for the new version: The link procedure for source code in Fortran 77 is enhanced, two additional stopping rules are implemented and a new criterion for accepting-start points, that economizes on function and gradient calls, is introduced. Summary of revisions:Addition of command line parameters to the utility program make_program. Augmentation of the link process for Fortran 77 subprograms, by linking the final executable with the g2c library. Addition of two probabilistic stopping rules. Introduction of a rejection mechanism to the Checking step of the original method, that reduces the number of gradient evaluations. Additional comments: A technical report describing the revisions, experiments and test runs is packaged with the source code. Running time: Depending on the objective function.

Link predication based on matrix factorization by fusion of multi class organizations of the network.

PubMed

Jiao, Pengfei; Cai, Fei; Feng, Yiding; Wang, Wenjun

2017-08-21

Link predication aims at forecasting the latent or unobserved edges in the complex networks and has a wide range of applications in reality. Almost existing methods and models only take advantage of one class organization of the networks, which always lose important information hidden in other organizations of the network. In this paper, we propose a link predication framework which makes the best of the structure of networks in different level of organizations based on nonnegative matrix factorization, which is called NMF 3 here. We first map the observed network into another space by kernel functions, which could get the different order organizations. Then we combine the adjacency matrix of the network with one of other organizations, which makes us obtain the objective function of our framework for link predication based on the nonnegative matrix factorization. Third, we derive an iterative algorithm to optimize the objective function, which converges to a local optimum, and we propose a fast optimization strategy for large networks. Lastly, we test the proposed framework based on two kernel functions on a series of real world networks under different sizes of training set, and the experimental results show the feasibility, effectiveness, and competitiveness of the proposed framework.

Generalization and Parallelization of Messy Genetic Algorithms and Communication in Parallel Genetic Algorithms.

DTIC Science & Technology

1992-12-01

Dynamics and Free Energy Perturbation Methods." Reviews in Computational Chem- istry edited by Kenny B. Lipkowitz and Donald B. Boyd, chapter 8, 295-320...atomic motions during annealing, allows the search to probabilistically move in a locally non-optimal direction. The probability of doing so is...Network processors communicate via communication links. This type of communication is generally very slow relative to other processor activities

ImNet: a fiber optic network with multistar topology for high-speed data transmission

NASA Astrophysics Data System (ADS)

Vossebuerger, F.; Keizers, Andreas; Soederman, N.; Meyer-Ebrecht, Dietrich

1993-10-01

ImNet is a fiber-optic local area network, which has been developed for high speed image communication in Picture Archiving and Communication Systems (PACS). A comprehensive analysis of image communication requirements in hospitals led to the conclusion that there is a need for networks which are optimized for the transmission of large datafiles. ImNet is optimized for this application in contrast to current-state LANs. ImNet consists of two elements: a link module and a switch module. The point-to-point link module can be up to 4 km by using fiber optic cable. For short distances up to 100 m a cheaper module using shielded twisted pair cable is available. The link module works bi-directionally and handles all protocols up to OSI-Level 3. The data rate per link is up to 140 MBit/s (clock rate 175 MHz). The switch module consists of the control unit and the cross-point-switch array. The array has up to fourteen interfaces for link modules. Up to fourteen data transfers each with a maximal transfer rate of 400 MBit/s can be handled at the same time. Thereby the maximal throughput of a switch module is 5.6 GBit/s. Out of these modules a multi-star network can be built i.e., an arbitrary tree structure of stars. This topology allows multiple transmissions at the same time as long as they do not require identical links. Therefore the overall throughput of ImNet can be a multiple of the datarate per link.

Improvement of In Situ PCR by Optimization of PCR Cycle Number and Proteinase K Concentration: Localization of X Chromosome-Linked Phosphoglycerate Kinase-1 Gene in Mouse Reproductive Organs

PubMed Central

Hishikawa, Yoshitaka; An, Shucai; Yamamoto-Fukuda, Tomomi; Shibata, Yasuaki; Koji, Takehiko

2009-01-01

In situ polymerase chain reaction (in situ PCR), which can detect a few copies of genes within a cell by amplifying the target gene, was developed to better understand the biological functions of tissues. In this study, we optimized the protocol conditions for the detection of X chromosome-linked phosphoglycerate kinase-1 (pgk-1) gene in paraffin-embedded sections of mouse reproductive organs. The effects of various concentrations of proteinase K (PK) and PCR cycle numbers were examined. To label the amplified DNA, we used digoxigenin-dUTP (Dig), Cy-3-dUTP (Cy-3), or FluorX-dCTP (FluorX). The optimal concentration of PK was 50 µg/ml for the ovary and 10 µg/ml for the testis. Ten PCR cycles were optimal for Dig and 25 cycles were optimal for FluorX and Cy-3 in the ovary and testis. The signal-to-noise ratio of FluorX and Cy-3 for ovarian tissue was better than that of Dig. Using the above conditions, we detected 1–4 and 1–2 spots of pgk-1 in the nuclei of granulosa and germ cells, respectively. Our results indicate that in situ PCR is useful for detecting a specific gene in paraffin-embedded sections under optimized conditions of both PCR cycle number and PK concentration. PMID:19492023

CD8+ T Cells Orchestrate pDC-XCR1+ Dendritic Cell Spatial and Functional Cooperativity to Optimize Priming.

PubMed

Brewitz, Anna; Eickhoff, Sarah; Dähling, Sabrina; Quast, Thomas; Bedoui, Sammy; Kroczek, Richard A; Kurts, Christian; Garbi, Natalio; Barchet, Winfried; Iannacone, Matteo; Klauschen, Frederick; Kolanus, Waldemar; Kaisho, Tsuneyasu; Colonna, Marco; Germain, Ronald N; Kastenmüller, Wolfgang

2017-02-21

Adaptive cellular immunity is initiated by antigen-specific interactions between T lymphocytes and dendritic cells (DCs). Plasmacytoid DCs (pDCs) support antiviral immunity by linking innate and adaptive immune responses. Here we examined pDC spatiotemporal dynamics during viral infection to uncover when, where, and how they exert their functions. We found that pDCs accumulated at sites of CD8 + T cell antigen-driven activation in a CCR5-dependent fashion. Furthermore, activated CD8 + T cells orchestrated the local recruitment of lymph node-resident XCR1 chemokine receptor-expressing DCs via secretion of the XCL1 chemokine. Functionally, this CD8 + T cell-mediated reorganization of the local DC network allowed for the interaction and cooperation of pDCs and XCR1 + DCs, thereby optimizing XCR1 + DC maturation and cross-presentation. These data support a model in which CD8 + T cells upon activation create their own optimal priming microenvironment by recruiting additional DC subsets to the site of initial antigen recognition. Published by Elsevier Inc.

Balancing building and maintenance costs in growing transport networks

NASA Astrophysics Data System (ADS)

Bottinelli, Arianna; Louf, Rémi; Gherardi, Marco

2017-09-01

The costs associated to the length of links impose unavoidable constraints to the growth of natural and artificial transport networks. When future network developments cannot be predicted, the costs of building and maintaining connections cannot be minimized simultaneously, requiring competing optimization mechanisms. Here, we study a one-parameter nonequilibrium model driven by an optimization functional, defined as the convex combination of building cost and maintenance cost. By varying the coefficient of the combination, the model interpolates between global and local length minimization, i.e., between minimum spanning trees and a local version known as dynamical minimum spanning trees. We show that cost balance within this ensemble of dynamical networks is a sufficient ingredient for the emergence of tradeoffs between the network's total length and transport efficiency, and of optimal strategies of construction. At the transition between two qualitatively different regimes, the dynamics builds up power-law distributed waiting times between global rearrangements, indicating a point of nonoptimality. Finally, we use our model as a framework to analyze empirical ant trail networks, showing its relevance as a null model for cost-constrained network formation.

An auxiliary optimization method for complex public transit route network based on link prediction

NASA Astrophysics Data System (ADS)

Zhang, Lin; Lu, Jian; Yue, Xianfei; Zhou, Jialin; Li, Yunxuan; Wan, Qian

2018-02-01

Inspired by the missing (new) link prediction and the spurious existing link identification in link prediction theory, this paper establishes an auxiliary optimization method for public transit route network (PTRN) based on link prediction. First, link prediction applied to PTRN is described, and based on reviewing the previous studies, the summary indices set and its algorithms set are collected for the link prediction experiment. Second, through analyzing the topological properties of Jinan’s PTRN established by the Space R method, we found that this is a typical small-world network with a relatively large average clustering coefficient. This phenomenon indicates that the structural similarity-based link prediction will show a good performance in this network. Then, based on the link prediction experiment of the summary indices set, three indices with maximum accuracy are selected for auxiliary optimization of Jinan’s PTRN. Furthermore, these link prediction results show that the overall layout of Jinan’s PTRN is stable and orderly, except for a partial area that requires optimization and reconstruction. The above pattern conforms to the general pattern of the optimal development stage of PTRN in China. Finally, based on the missing (new) link prediction and the spurious existing link identification, we propose optimization schemes that can be used not only to optimize current PTRN but also to evaluate PTRN planning.

Optimal use of EEG recordings to target active brain areas with transcranial electrical stimulation.

PubMed

Dmochowski, Jacek P; Koessler, Laurent; Norcia, Anthony M; Bikson, Marom; Parra, Lucas C

2017-08-15

To demonstrate causal relationships between brain and behavior, investigators would like to guide brain stimulation using measurements of neural activity. Particularly promising in this context are electroencephalography (EEG) and transcranial electrical stimulation (TES), as they are linked by a reciprocity principle which, despite being known for decades, has not led to a formalism for relating EEG recordings to optimal stimulation parameters. Here we derive a closed-form expression for the TES configuration that optimally stimulates (i.e., targets) the sources of recorded EEG, without making assumptions about source location or distribution. We also derive a duality between TES targeting and EEG source localization, and demonstrate that in cases where source localization fails, so does the proposed targeting. Numerical simulations with multiple head models confirm these theoretical predictions and quantify the achieved stimulation in terms of focality and intensity. We show that constraining the stimulation currents automatically selects optimal montages that involve only a few (4-7) electrodes, with only incremental loss in performance when targeting focal activations. The proposed technique allows brain scientists and clinicians to rationally target the sources of observed EEG and thus overcomes a major obstacle to the realization of individualized or closed-loop brain stimulation. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Optimal use of EEG recordings to target active brain areas with transcranial electrical stimulation

PubMed Central

Dmochowski, Jacek P.; Koessler, Laurent; Norcia, Anthony M.; Bikson, Marom; Parra, Lucas C.

2018-01-01

To demonstrate causal relationships between brain and behavior, investigators would like to guide brain stimulation using measurements of neural activity. Particularly promising in this context are electroencephalography (EEG) and transcranial electrical stimulation (TES), as they are linked by a reciprocity principle which, despite being known for decades, has not led to a formalism for relating EEG recordings to optimal stimulation parameters. Here we derive a closed-form expression for the TES configuration that optimally stimulates (i.e., targets) the sources of recorded EEG, without making assumptions about source location or distribution. We also derive a duality between TES targeting and EEG source localization, and demonstrate that in cases where source localization fails, so does the proposed targeting. Numerical simulations with multiple head models confirm these theoretical predictions and quantify the achieved stimulation in terms of focality and intensity. We show that constraining the stimulation currents automatically selects optimal montages that involve only a few (4–7) electrodes, with only incremental loss in performance when targeting focal activations. The proposed technique allows brain scientists and clinicians to rationally target the sources of observed EEG and thus overcomes a major obstacle to the realization of individualized or closed-loop brain stimulation. PMID:28578130

Learning Multirobot Hose Transportation and Deployment by Distributed Round-Robin Q-Learning.

PubMed

Fernandez-Gauna, Borja; Etxeberria-Agiriano, Ismael; Graña, Manuel

2015-01-01

Multi-Agent Reinforcement Learning (MARL) algorithms face two main difficulties: the curse of dimensionality, and environment non-stationarity due to the independent learning processes carried out by the agents concurrently. In this paper we formalize and prove the convergence of a Distributed Round Robin Q-learning (D-RR-QL) algorithm for cooperative systems. The computational complexity of this algorithm increases linearly with the number of agents. Moreover, it eliminates environment non sta tionarity by carrying a round-robin scheduling of the action selection and execution. That this learning scheme allows the implementation of Modular State-Action Vetoes (MSAV) in cooperative multi-agent systems, which speeds up learning convergence in over-constrained systems by vetoing state-action pairs which lead to undesired termination states (UTS) in the relevant state-action subspace. Each agent's local state-action value function learning is an independent process, including the MSAV policies. Coordination of locally optimal policies to obtain the global optimal joint policy is achieved by a greedy selection procedure using message passing. We show that D-RR-QL improves over state-of-the-art approaches, such as Distributed Q-Learning, Team Q-Learning and Coordinated Reinforcement Learning in a paradigmatic Linked Multi-Component Robotic System (L-MCRS) control problem: the hose transportation task. L-MCRS are over-constrained systems with many UTS induced by the interaction of the passive linking element and the active mobile robots.

Optimal Transient Growth of Submesoscale Baroclinic Instabilities

NASA Astrophysics Data System (ADS)

White, Brian; Zemskova, Varvara; Passaggia, Pierre-Yves

2016-11-01

Submesoscale instabilities are analyzed using a transient growth approach to determine the optimal perturbation for a rotating Boussinesq fluid subject to baroclinic instabilities. We consider a base flow with uniform shear and stratification and consider the non-normal evolution over finite-time horizons of linear perturbations in an ageostrophic, non-hydrostatic regime. Stone (1966, 1971) showed that the stability of the base flow to normal modes depends on the Rossby and Richardson numbers, with instabilities ranging from geostrophic (Ro -> 0) and ageostrophic (finite Ro) baroclinic modes to symmetric (Ri < 1 , Ro > 1) and Kelvin-Helmholtz (Ri < 1 / 4) modes. Non-normal transient growth, initiated by localized optimal wave packets, represents a faster mechanism for the growth of perturbations and may provide an energetic link between large-scale flows in geostrophic balance and dissipation scales via submesoscale instabilities. Here we consider two- and three-dimensional optimal perturbations by means of direct-adjoint iterations of the linearized Boussinesq Navier-Stokes equations to determine the form of the optimal perturbation, the optimal energy gain, and the characteristics of the most unstable perturbation.

Local excitation-inhibition ratio for synfire chain propagation in feed-forward neuronal networks

NASA Astrophysics Data System (ADS)

Guo, Xinmeng; Yu, Haitao; Wang, Jiang; Liu, Jing; Cao, Yibin; Deng, Bin

2017-09-01

A leading hypothesis holds that spiking activity propagates along neuronal sub-populations which are connected in a feed-forward manner, and the propagation efficiency would be affected by the dynamics of sub-populations. In this paper, how the interaction between local excitation and inhibition effects on synfire chain propagation in feed-forward network (FFN) is investigated. The simulation results show that there is an appropriate excitation-inhibition (EI) ratio maximizing the performance of synfire chain propagation. The optimal EI ratio can significantly enhance the selectivity of FFN to synchronous signals, which thereby increases the stability to background noise. Moreover, the effect of network topology on synfire chain propagation is also investigated. It is found that synfire chain propagation can be maximized by an optimal interlayer linking probability. We also find that external noise is detrimental to synchrony propagation by inducing spiking jitter. The results presented in this paper may provide insights into the effects of network dynamics on neuronal computations.

Design and implementation of an automated compound management system in support of lead optimization.

PubMed

Quintero, Catherine; Kariv, Ilona

2009-06-01

To meet the needs of the increasingly rapid and parallelized lead optimization process, a fully integrated local compound storage and liquid handling system was designed and implemented to automate the generation of assay-ready plates directly from newly submitted and cherry-picked compounds. A key feature of the system is the ability to create project- or assay-specific compound-handling methods, which provide flexibility for any combination of plate types, layouts, and plate bar-codes. Project-specific workflows can be created by linking methods for processing new and cherry-picked compounds and control additions to produce a complete compound set for both biological testing and local storage in one uninterrupted workflow. A flexible cherry-pick approach allows for multiple, user-defined strategies to select the most appropriate replicate of a compound for retesting. Examples of custom selection parameters include available volume, compound batch, and number of freeze/thaw cycles. This adaptable and integrated combination of software and hardware provides a basis for reducing cycle time, fully automating compound processing, and ultimately increasing the rate at which accurate, biologically relevant results can be produced for compounds of interest in the lead optimization process.

Design and optimization of a fiber optic data link for new generation on-board SAR processing architectures

NASA Astrophysics Data System (ADS)

Ciminelli, Caterina; Dell'Olio, Francesco; Armenise, Mario N.; Iacomacci, Francesco; Pasquali, Franca; Formaro, Roberto

2017-11-01

A fiber optic digital link for on-board data handling is modeled, designed and optimized in this paper. Design requirements and constraints relevant to the link, which is in the frame of novel on-board processing architectures, are discussed. Two possible link configurations are investigated, showing their advantages and disadvantages. An accurate mathematical model of each link component and the entire system is reported and results of link simulation based on those models are presented. Finally, some details on the optimized design are provided.

EEG functional connectivity, axon delays and white matter disease.

PubMed

Nunez, Paul L; Srinivasan, Ramesh; Fields, R Douglas

2015-01-01

Both structural and functional brain connectivities are closely linked to white matter disease. We discuss several such links of potential interest to neurologists, neurosurgeons, radiologists, and non-clinical neuroscientists. Treatment of brains as genuine complex systems suggests major emphasis on the multi-scale nature of brain connectivity and dynamic behavior. Cross-scale interactions of local, regional, and global networks are apparently responsible for much of EEG's oscillatory behaviors. Finite axon propagation speed, often assumed to be infinite in local network models, is central to our conceptual framework. Myelin controls axon speed, and the synchrony of impulse traffic between distant cortical regions appears to be critical for optimal mental performance and learning. Several experiments suggest that axon conduction speed is plastic, thereby altering the regional and global white matter connections that facilitate binding of remote local networks. Combined EEG and high resolution EEG can provide distinct multi-scale estimates of functional connectivity in both healthy and diseased brains with measures like frequency and phase spectra, covariance, and coherence. White matter disease may profoundly disrupt normal EEG coherence patterns, but currently these kinds of studies are rare in scientific labs and essentially missing from clinical environments. Copyright © 2014 International Federation of Clinical Neurophysiology. All rights reserved.

The Hyaluronic Acid Fillers: Current Understanding of the Tissue Device Interface.

PubMed

Greene, Jacqueline J; Sidle, Douglas M

2015-11-01

The article is a detailed update regarding cosmetic injectable fillers, specifically focusing on hyaluronic acid fillers. Hyaluronic acid-injectable fillers are used extensively for soft tissue volumizing and contouring. Many different hyaluronic acid-injectable fillers are available on the market and differ in terms of hyaluronic acid concentration, particle size, cross-linking density, requisite needle size, duration, stiffness, hydration, presence of lidocaine, type of cross-linking technology, and cost. Hyaluronic acid is a natural component of many soft tissues, is identical across species minimizing immunogenicity has been linked to wound healing and skin regeneration, and is currently actively being studied for tissue engineering purposes. The biomechanical and biochemical effects of HA on the local microenvironment of the injected site are key to its success as a soft tissue filler. Knowledge of the tissue-device interface will help guide the facial practitioner and lead to optimal outcomes for patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Optimizing cropland cover for stable food production in Sub-Saharan Africa using simulated yield and Modern Portfolio Theory

NASA Astrophysics Data System (ADS)

Bodin, P.; Olin, S.; Pugh, T. A. M.; Arneth, A.

2014-12-01

Food security can be defined as stable access to food of good nutritional quality. In Sub Saharan Africa access to food is strongly linked to local food production and the capacity to generate enough calories to sustain the local population. Therefore it is important in these regions to generate not only sufficiently high yields but also to reduce interannual variability in food production. Traditionally, climate impact simulation studies have focused on factors that underlie maximum productivity ignoring the variability in yield. By using Modern Portfolio Theory, a method stemming from economics, we here calculate optimum current and future crop selection that maintain current yield while minimizing variance, vs. maintaining variance while maximizing yield. Based on simulated yield using the LPJ-GUESS dynamic vegetation model, the results show that current cropland distribution for many crops is close to these optimum distributions. Even so, the optimizations displayed substantial potential to either increase food production and/or to decrease its variance regionally. Our approach can also be seen as a method to create future scenarios for the sown areas of crops in regions where local food production is important for food security.

MHC Class II and CD9 in human eosinophils localize to detergent-resistant membrane microdomains.

PubMed

Akuthota, Praveen; Melo, Rossana C N; Spencer, Lisa A; Weller, Peter F

2012-02-01

Eosinophils function in murine allergic airways inflammation as professional antigen-presenting cells (APCs). In murine professional APC cell types, optimal functioning of MHC Class II depends on its lateral association in plasma membranes and colocalization with the tetraspanin CD9 into detergent-resistant membrane microdomains (DRMs). With human eosinophils, we evaluated the localization of MHC Class II (HLA-DR) to DRMs and the functional significance of such localization. In granulocyte-macrophage colony-stimulating factor-stimulated human eosinophils, antibody cross-linked HLA-DR colocalized by immunofluorescence microscopy focally on plasma membranes with CD9 and the DRM marker ganglioside GM1. In addition, HLA-DR coimmunoprecipitates with CD9 after chemical cross-linking of CD9. HLA-DR and CD9 were localized by Western blotting in eosinophil DRM subcellular fractions. DRM disruption with the cholesterol-depleting agent methyl-β-cyclodextrin decreased eosinophil surface expression of HLA-DR and CD9. We show that CD9 is abundant on the surface of eosinophils, presenting the first electron microscopy data of the ultrastructural immunolocalization of CD9 in human eosinophils. Disruption of HLA-DR-containing DRMs decreased the ability of superantigen-loaded human eosinophils to stimulate CD4(+) T-cell activation (CD69 expression), proliferation, and cytokine production. Our results, which demonstrate that eosinophil MHC Class II localizes to DRMs in association with CD9 in a functionally significant manner, represent a novel insight into the organization of the antigen presentation complex of human eosinophils.

MHC Class II and CD9 in Human Eosinophils Localize to Detergent-Resistant Membrane Microdomains

PubMed Central

Akuthota, Praveen; Melo, Rossana C. N.; Spencer, Lisa A.

2012-01-01

Eosinophils function in murine allergic airways inflammation as professional antigen-presenting cells (APCs). In murine professional APC cell types, optimal functioning of MHC Class II depends on its lateral association in plasma membranes and colocalization with the tetraspanin CD9 into detergent-resistant membrane microdomains (DRMs). With human eosinophils, we evaluated the localization of MHC Class II (HLA-DR) to DRMs and the functional significance of such localization. In granulocyte-macrophage colony-stimulating factor–stimulated human eosinophils, antibody cross-linked HLA-DR colocalized by immunofluorescence microscopy focally on plasma membranes with CD9 and the DRM marker ganglioside GM1. In addition, HLA-DR coimmunoprecipitates with CD9 after chemical cross-linking of CD9. HLA-DR and CD9 were localized by Western blotting in eosinophil DRM subcellular fractions. DRM disruption with the cholesterol-depleting agent methyl-β-cyclodextrin decreased eosinophil surface expression of HLA-DR and CD9. We show that CD9 is abundant on the surface of eosinophils, presenting the first electron microscopy data of the ultrastructural immunolocalization of CD9 in human eosinophils. Disruption of HLA-DR–containing DRMs decreased the ability of superantigen-loaded human eosinophils to stimulate CD4+ T-cell activation (CD69 expression), proliferation, and cytokine production. Our results, which demonstrate that eosinophil MHC Class II localizes to DRMs in association with CD9 in a functionally significant manner, represent a novel insight into the organization of the antigen presentation complex of human eosinophils. PMID:21885678

The random fractional matching problem

NASA Astrophysics Data System (ADS)

Lucibello, Carlo; Malatesta, Enrico M.; Parisi, Giorgio; Sicuro, Gabriele

2018-05-01

We consider two formulations of the random-link fractional matching problem, a relaxed version of the more standard random-link (integer) matching problem. In one formulation, we allow each node to be linked to itself in the optimal matching configuration. In the other one, on the contrary, such a link is forbidden. Both problems have the same asymptotic average optimal cost of the random-link matching problem on the complete graph. Using a replica approach and previous results of Wästlund (2010 Acta Mathematica 204 91–150), we analytically derive the finite-size corrections to the asymptotic optimal cost. We compare our results with numerical simulations and we discuss the main differences between random-link fractional matching problems and the random-link matching problem.

Convective Propagation Characteristics Using a Simple Representation of Convective Organization

NASA Astrophysics Data System (ADS)

Neale, R. B.; Mapes, B. E.

2016-12-01

Observed equatorial wave propagation is intimately linked to convective organization and it's coupling to features of the larger-scale flow. In this talk we a use simple 4 level model to accommodate vertical modes of a mass flux convection scheme (shallow, mid-level and deep). Two paradigms of convection are used to represent convective processes. One that has only both random (unorganized) diagnosed fluctuations of convective properties and one with organized fluctuations of convective properties that are amplified by previously existing convection and has an explicit moistening impact on the local convecting environment We show a series of model simulations in single-column, 2D and 3D configurations, where the role of convective organization in wave propagation is shown to be fundamental. For the optimal choice of parameters linking organization to local atmospheric state, a broad array of convective wave propagation emerges. Interestingly the key characteristics of propagating modes are the low-level moistening followed by deep convection followed by mature 'large-scale' heating. This organization structure appears to hold firm across timescales from 5-day wave disturbances to MJO-like wave propagation.

Field programmable gate arrays-based number plate binarization and adjustment for automatic number plate recognition systems

NASA Astrophysics Data System (ADS)

Zhai, Xiaojun; Bensaali, Faycal; Sotudeh, Reza

2013-01-01

Number plate (NP) binarization and adjustment are important preprocessing stages in automatic number plate recognition (ANPR) systems and are used to link the number plate localization (NPL) and character segmentation stages. Successfully linking these two stages will improve the performance of the entire ANPR system. We present two optimized low-complexity NP binarization and adjustment algorithms. Efficient area/speed architectures based on the proposed algorithms are also presented and have been successfully implemented and tested using the Mentor Graphics RC240 FPGA development board, which together require only 9% of the available on-chip resources of a Virtex-4 FPGA, run with a maximum frequency of 95.8 MHz and are capable of processing one image in 0.07 to 0.17 ms.

A link-adding strategy for transport efficiency of complex networks

NASA Astrophysics Data System (ADS)

Ma, Jinlong; Han, Weizhan; Guo, Qing; Wang, Zhenyong; Zhang, Shuai

2016-12-01

The transport efficiency is one of the critical parameters to evaluate the performance of a network. In this paper, we propose an improved efficient (IE) strategy to enhance the network transport efficiency of complex networks by adding a fraction of links to an existing network based on the node’s local degree centrality and the shortest path length. Simulation results show that the proposed strategy can bring better traffic capacity and shorter average shortest path length than the low-degree-first (LDF) strategy under the shortest path routing protocol. It is found that the proposed strategy is beneficial to the improvement of overall traffic handling and delivering ability of the network. This study can alleviate the congestion in networks, and is helpful to design and optimize realistic networks.

Preentry communications study. Outer planets atmospheric entry probe

NASA Technical Reports Server (NTRS)

Hinrichs, C. A.

1976-01-01

A pre-entry communications study is presented for a relay link between a Jupiter entry probe and a spacecraft in hyperbolic orbit. Two generic communications links of interest are described: a pre-entry link to a spun spacecraft antenna, and a pre-entry link to a despun spacecraft antenna. The propagation environment of Jupiter is defined. Although this is one of the least well known features of Jupiter, enough information exists to reasonably establish bounds on the performance of a communications link. Within these bounds, optimal carrier frequencies are defined. The next step is to identify optimal relative geometries between the probe and the spacecraft. Optimal trajectories are established for both spun and despun spacecraft antennas. Given the optimal carrier frequencies, and the optimal trajectories, the data carrying capacities of the pre-entry links are defined. The impact of incorporating pre-entry communications into a basic post entry probe is then assessed. This assessment covers the disciplines of thermal control, power source, mass properties and design layout. A conceptual design is developed of an electronically despun antenna for use on a Pioneer class of spacecraft.

Multiple-copy state discrimination: Thinking globally, acting locally

NASA Astrophysics Data System (ADS)

Higgins, B. L.; Doherty, A. C.; Bartlett, S. D.; Pryde, G. J.; Wiseman, H. M.

2011-05-01

We theoretically investigate schemes to discriminate between two nonorthogonal quantum states given multiple copies. We consider a number of state discrimination schemes as applied to nonorthogonal, mixed states of a qubit. In particular, we examine the difference that local and global optimization of local measurements makes to the probability of obtaining an erroneous result, in the regime of finite numbers of copies N, and in the asymptotic limit as N→∞. Five schemes are considered: optimal collective measurements over all copies, locally optimal local measurements in a fixed single-qubit measurement basis, globally optimal fixed local measurements, locally optimal adaptive local measurements, and globally optimal adaptive local measurements. Here an adaptive measurement is one in which the measurement basis can depend on prior measurement results. For each of these measurement schemes we determine the probability of error (for finite N) and the scaling of this error in the asymptotic limit. In the asymptotic limit, it is known analytically (and we verify numerically) that adaptive schemes have no advantage over the optimal fixed local scheme. Here we show moreover that, in this limit, the most naive scheme (locally optimal fixed local measurements) is as good as any noncollective scheme except for states with less than 2% mixture. For finite N, however, the most sophisticated local scheme (globally optimal adaptive local measurements) is better than any other noncollective scheme for any degree of mixture.

Multiple-copy state discrimination: Thinking globally, acting locally

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

Higgins, B. L.; Pryde, G. J.; Wiseman, H. M.

2011-05-15

We theoretically investigate schemes to discriminate between two nonorthogonal quantum states given multiple copies. We consider a number of state discrimination schemes as applied to nonorthogonal, mixed states of a qubit. In particular, we examine the difference that local and global optimization of local measurements makes to the probability of obtaining an erroneous result, in the regime of finite numbers of copies N, and in the asymptotic limit as N{yields}{infinity}. Five schemes are considered: optimal collective measurements over all copies, locally optimal local measurements in a fixed single-qubit measurement basis, globally optimal fixed local measurements, locally optimal adaptive local measurements,more » and globally optimal adaptive local measurements. Here an adaptive measurement is one in which the measurement basis can depend on prior measurement results. For each of these measurement schemes we determine the probability of error (for finite N) and the scaling of this error in the asymptotic limit. In the asymptotic limit, it is known analytically (and we verify numerically) that adaptive schemes have no advantage over the optimal fixed local scheme. Here we show moreover that, in this limit, the most naive scheme (locally optimal fixed local measurements) is as good as any noncollective scheme except for states with less than 2% mixture. For finite N, however, the most sophisticated local scheme (globally optimal adaptive local measurements) is better than any other noncollective scheme for any degree of mixture.« less

Design and Optimization of a 3-Coil Inductive Link for Efficient Wireless Power Transmission.

PubMed

Kiani, Mehdi; Jow, Uei-Ming; Ghovanloo, Maysam

2011-07-14

Inductive power transmission is widely used to energize implantable microelectronic devices (IMDs), recharge batteries, and energy harvesters. Power transfer efficiency (PTE) and power delivered to the load (PDL) are two key parameters in wireless links, which affect the energy source specifications, heat dissipation, power transmission range, and interference with other devices. To improve the PTE, a 4-coil inductive link has been recently proposed. Through a comprehensive circuit based analysis that can guide a design and optimization scheme, we have shown that despite achieving high PTE at larger coil separations, the 4-coil inductive links fail to achieve a high PDL. Instead, we have proposed a 3-coil inductive power transfer link with comparable PTE over its 4-coil counterpart at large coupling distances, which can also achieve high PDL. We have also devised an iterative design methodology that provides the optimal coil geometries in a 3-coil inductive power transfer link. Design examples of 2-, 3-, and 4-coil inductive links have been presented, and optimized for 13.56 MHz carrier frequency and 12 cm coupling distance, showing PTEs of 15%, 37%, and 35%, respectively. At this distance, the PDL of the proposed 3-coil inductive link is 1.5 and 59 times higher than its equivalent 2- and 4-coil links, respectively. For short coupling distances, however, 2-coil links remain the optimal choice when a high PDL is required, while 4-coil links are preferred when the driver has large output resistance or small power is needed. These results have been verified through simulations and measurements.

Collective influence in evolutionary social dilemmas

NASA Astrophysics Data System (ADS)

Szolnoki, Attila; Perc, Matjaž

2016-03-01

When evolutionary games are contested in structured populations, the degree of each player in the network plays an important role. If they exist, hubs often determine the fate of the population in remarkable ways. Recent research based on optimal percolation in random networks has shown, however, that the degree is neither the sole nor the best predictor of influence in complex networks. Low-degree nodes may also be optimal influencers if they are hierarchically linked to hubs. Taking this into account leads to the formalism of collective influence in complex networks, which as we show here, has far-reaching implications for the favorable resolution of social dilemmas. In particular, there exists an optimal hierarchical depth for the determination of collective influence that we use to describe the potency of players for passing their strategies, which depends on the strength of the social dilemma. Interestingly, the degree, which corresponds to the baseline depth zero, is optimal only when the temptation to defect is small. Our research reveals that evolutionary success stories are related to spreading processes which are rooted in favorable hierarchical structures that extend beyond local neighborhoods.

Technology forecasting for space communication. Task one report: Cost and weight tradeoff studies for EOS and TDRS

NASA Technical Reports Server (NTRS)

1974-01-01

Weight and cost optimized EOS communication links are determined for 2.25, 7.25, 14.5, 21, and 60 GHz systems and for a 10.6 micron homodyne detection laser system. EOS to ground links are examined for 556, 834, and 1112 km EOS orbits, with ground terminals at the Network Test and Tracking Facility and at Goldstone. Optimized 21 GHz and 10.6 micron links are also examined. For the EOS to Tracking and Data Relay Satellite to ground link, signal-to-noise ratios of the uplink and downlink are also optimized for minimum overall cost or spaceborne weight. Finally, the optimized 21 GHz EOS to ground link is determined for various precipitation rates. All system performance parameters and mission dependent constraints are presented, as are the system cost and weight functional dependencies. The features and capabilities of the computer program to perform the foregoing analyses are described.

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

Experimental demonstration of the optical multi-mesh hypercube: scaleable interconnection network for multiprocessors and multicomputers.

PubMed

Louri, A; Furlonge, S; Neocleous, C

1996-12-10

A prototype of a novel topology for scaleable optical interconnection networks called the optical multi-mesh hypercube (OMMH) is experimentally demonstrated to as high as a 150-Mbit/s data rate (2(7) - 1 nonreturn-to-zero pseudo-random data pattern) at a bit error rate of 10(-13)/link by the use of commercially available devices. OMMH is a scaleable network [Appl. Opt. 33, 7558 (1994); J. Lightwave Technol. 12, 704 (1994)] architecture that combines the positive features of the hypercube (small diameter, connectivity, symmetry, simple routing, and fault tolerance) and the mesh (constant node degree and size scaleability). The optical implementation method is divided into two levels: high-density local connections for the hypercube modules, and high-bit-rate, low-density, long connections for the mesh links connecting the hypercube modules. Free-space imaging systems utilizing vertical-cavity surface-emitting laser (VCSEL) arrays, lenslet arrays, space-invariant holographic techniques, and photodiode arrays are demonstrated for the local connections. Optobus fiber interconnects from Motorola are used for the long-distance connections. The OMMH was optimized to operate at the data rate of Motorola's Optobus (10-bit-wide, VCSEL-based bidirectional data interconnects at 150 Mbits/s). Difficulties encountered included the varying fan-out efficiencies of the different orders of the hologram, misalignment sensitivity of the free-space links, low power (1 mW) of the individual VCSEL's, and noise.

An Optimal Schedule for Urban Road Network Repair Based on the Greedy Algorithm

PubMed Central

Lu, Guangquan; Xiong, Ying; Wang, Yunpeng

2016-01-01

The schedule of urban road network recovery caused by rainstorms, snow, and other bad weather conditions, traffic incidents, and other daily events is essential. However, limited studies have been conducted to investigate this problem. We fill this research gap by proposing an optimal schedule for urban road network repair with limited repair resources based on the greedy algorithm. Critical links will be given priority in repair according to the basic concept of the greedy algorithm. In this study, the link whose restoration produces the ratio of the system-wide travel time of the current network to the worst network is the minimum. We define such a link as the critical link for the current network. We will re-evaluate the importance of damaged links after each repair process is completed. That is, the critical link ranking will be changed along with the repair process because of the interaction among links. We repair the most critical link for the specific network state based on the greedy algorithm to obtain the optimal schedule. The algorithm can still quickly obtain an optimal schedule even if the scale of the road network is large because the greedy algorithm can reduce computational complexity. We prove that the problem can obtain the optimal solution using the greedy algorithm in theory. The algorithm is also demonstrated in the Sioux Falls network. The problem discussed in this paper is highly significant in dealing with urban road network restoration. PMID:27768732

Linking microarray reporters with protein functions.

PubMed

Gaj, Stan; van Erk, Arie; van Haaften, Rachel I M; Evelo, Chris T A

2007-09-26

The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt) entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/.

Local Estimators for Spacecraft Formation Flying

NASA Technical Reports Server (NTRS)

Fathpour, Nanaz; Hadaegh, Fred Y.; Mesbahi, Mehran; Nabi, Marzieh

2011-01-01

A formation estimation architecture for formation flying builds upon the local information exchange among multiple local estimators. Spacecraft formation flying involves the coordination of states among multiple spacecraft through relative sensing, inter-spacecraft communication, and control. Most existing formation flying estimation algorithms can only be supported via highly centralized, all-to-all, static relative sensing. New algorithms are needed that are scalable, modular, and robust to variations in the topology and link characteristics of the formation exchange network. These distributed algorithms should rely on a local information-exchange network, relaxing the assumptions on existing algorithms. In this research, it was shown that only local observability is required to design a formation estimator and control law. The approach relies on breaking up the overall information-exchange network into sequence of local subnetworks, and invoking an agreement-type filter to reach consensus among local estimators within each local network. State estimates were obtained by a set of local measurements that were passed through a set of communicating Kalman filters to reach an overall state estimation for the formation. An optimization approach was also presented by means of which diffused estimates over the network can be incorporated in the local estimates obtained by each estimator via local measurements. This approach compares favorably with that obtained by a centralized Kalman filter, which requires complete knowledge of the raw measurement available to each estimator.

Combined node and link partitions method for finding overlapping communities in complex networks

PubMed Central

Jin, Di; Gabrys, Bogdan; Dang, Jianwu

2015-01-01

Community detection in complex networks is a fundamental data analysis task in various domains, and how to effectively find overlapping communities in real applications is still a challenge. In this work, we propose a new unified model and method for finding the best overlapping communities on the basis of the associated node and link partitions derived from the same framework. Specifically, we first describe a unified model that accommodates node and link communities (partitions) together, and then present a nonnegative matrix factorization method to learn the parameters of the model. Thereafter, we infer the overlapping communities based on the derived node and link communities, i.e., determine each overlapped community between the corresponding node and link community with a greedy optimization of a local community function conductance. Finally, we introduce a model selection method based on consensus clustering to determine the number of communities. We have evaluated our method on both synthetic and real-world networks with ground-truths, and compared it with seven state-of-the-art methods. The experimental results demonstrate the superior performance of our method over the competing ones in detecting overlapping communities for all analysed data sets. Improved performance is particularly pronounced in cases of more complicated networked community structures. PMID:25715829

Link prediction with node clustering coefficient

NASA Astrophysics Data System (ADS)

Wu, Zhihao; Lin, Youfang; Wang, Jing; Gregory, Steve

2016-06-01

Predicting missing links in incomplete complex networks efficiently and accurately is still a challenging problem. The recently proposed Cannistrai-Alanis-Ravai (CAR) index shows the power of local link/triangle information in improving link-prediction accuracy. Inspired by the idea of employing local link/triangle information, we propose a new similarity index with more local structure information. In our method, local link/triangle structure information can be conveyed by clustering coefficient of common-neighbors directly. The reason why clustering coefficient has good effectiveness in estimating the contribution of a common-neighbor is that it employs links existing between neighbors of a common-neighbor and these links have the same structural position with the candidate link to this common-neighbor. In our experiments, three estimators: precision, AUP and AUC are used to evaluate the accuracy of link prediction algorithms. Experimental results on ten tested networks drawn from various fields show that our new index is more effective in predicting missing links than CAR index, especially for networks with low correlation between number of common-neighbors and number of links between common-neighbors.

3D spine reconstruction of postoperative patients from multi-level manifold ensembles.

PubMed

Kadoury, Samuel; Labelle, Hubert; Parent, Stefan

2014-01-01

The quantitative assessment of surgical outcomes using personalized anatomical models is an essential task for the treatment of spinal deformities such as adolescent idiopathic scoliosis. However an accurate 3D reconstruction of the spine from postoperative X-ray images remains challenging due to presence of instrumentation (metallic rods and screws) occluding vertebrae on the spine. In this paper, we formulate the reconstruction problem as an optimization over a manifold of articulated spine shapes learned from pathological training data. The manifold itself is represented using a novel data structure, a multi-level manifold ensemble, which contains links between nodes in a single hierarchical structure, as well as links between different hierarchies, representing overlapping partitions. We show that this data structure allows both efficient localization and navigation on the manifold, for on-the-fly building of local nonlinear models (manifold charting). Our reconstruction framework was tested on pre- and postoperative X-ray datasets from patients who underwent spinal surgery. Compared to manual ground-truth, our method achieves a 3D reconstruction accuracy of 2.37 +/- 0.85 mm for postoperative spine models and can deal with severe cases of scoliosis.

On-chip broadband silicon thermo-optic 2☓2 four-mode optical switch for optical space and local mode switching.

PubMed

Zhou, Ting; Jia, Hao; Ding, Jianfeng; Zhang, Lei; Fu, Xin; Yang, Lin

2018-04-02

We present a silicon thermo-optic 2☓2 four-mode optical switch optimized for optical space switching plus local optical mode switching. Four asymmetric directional couplers are utilized for mode multiplexing and de-multiplexing. Sixteen 2☓2 single-mode optical switches based on balanced thermally tunable Mach-Zehnder interferometers are exploited for switching function. The measured insertion losses are 8.0~12.2 dB and the optical signal-to-noise ratios are larger than 11.2 dB in the wavelength range of 1525~1565 nm. The optical links in "all-bar" and "all-cross" states exhibit less than 2.0 dB and 1.4 dB power penalties respectively below 10 -9 bit error rates for 40 Gbps data transmission.

Neighbor detection at the leaf tip adaptively regulates upward leaf movement through spatial auxin dynamics

PubMed Central

Reinen, Emilie; Anten, Niels P. R.

2017-01-01

Vegetation stands have a heterogeneous distribution of light quality, including the red/far-red light ratio (R/FR) that informs plants about proximity of neighbors. Adequate responses to changes in R/FR are important for competitive success. How the detection and response to R/FR are spatially linked and how this spatial coordination between detection and response affects plant performance remains unresolved. We show in Arabidopsis thaliana and Brassica nigra that localized FR enrichment at the lamina tip induces upward leaf movement (hyponasty) from the petiole base. Using a combination of organ-level transcriptome analysis, molecular reporters, and physiology, we show that PIF-dependent spatial auxin dynamics are key to this remote response to localized FR enrichment. Using computational 3D modeling, we show that remote signaling of R/FR for hyponasty has an adaptive advantage over local signaling in the petiole, because it optimizes the timing of leaf movement in response to neighbors and prevents hyponasty caused by self-shading. PMID:28652357

Multiband DSB-SC modulated radio over IsOWC link with coherent homodyne detection

NASA Astrophysics Data System (ADS)

Kang, Zong; Zhu, Jiang

2018-02-01

In this paper, we present a multiband double sideband-suppressed carrier (DSB-SC) modulated radio over intersatellite optical wireless communication (IsOWC) link with coherent homodyne detection. The proposed system can provide the transparent transport of multiband radio frequency (RF) signals with higher linearity and better receiver sensitivity than the intensity modulated with direct detection (IM/DD) scheme. The full system model and the exactly analytical expression of signal to noise and distortion ratio (SNDR) are derived considering the third-order intermodulation product and amplifier spontaneous emission (ASE) noise. The finite extinction ratio (ER) of Mach-Zehnder Modulator (MZM) and the saturation property of erbium doped fiber amplifier (EDFA) are also considered. Numerical results of SNDR with various numbers of subchannels and ERs are given. Results indicate that the optimal modulation index exists to maximize the SNDR and the power of local oscillator (LO) carrier should be within an appropriate range.

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.

Maximizing algebraic connectivity in interconnected networks.

PubMed

Shakeri, Heman; Albin, Nathan; Darabi Sahneh, Faryad; Poggi-Corradini, Pietro; Scoglio, Caterina

2016-03-01

Algebraic connectivity, the second eigenvalue of the Laplacian matrix, is a measure of node and link connectivity on networks. When studying interconnected networks it is useful to consider a multiplex model, where the component networks operate together with interlayer links among them. In order to have a well-connected multilayer structure, it is necessary to optimally design these interlayer links considering realistic constraints. In this work, we solve the problem of finding an optimal weight distribution for one-to-one interlayer links under budget constraint. We show that for the special multiplex configurations with identical layers, the uniform weight distribution is always optimal. On the other hand, when the two layers are arbitrary, increasing the budget reveals the existence of two different regimes. Up to a certain threshold budget, the second eigenvalue of the supra-Laplacian is simple, the optimal weight distribution is uniform, and the Fiedler vector is constant on each layer. Increasing the budget past the threshold, the optimal weight distribution can be nonuniform. The interesting consequence of this result is that there is no need to solve the optimization problem when the available budget is less than the threshold, which can be easily found analytically.

Similarity indices based on link weight assignment for link prediction of unweighted complex networks

NASA Astrophysics Data System (ADS)

Liu, Shuxin; Ji, Xinsheng; Liu, Caixia; Bai, Yi

2017-01-01

Many link prediction methods have been proposed for predicting the likelihood that a link exists between two nodes in complex networks. Among these methods, similarity indices are receiving close attention. Most similarity-based methods assume that the contribution of links with different topological structures is the same in the similarity calculations. This paper proposes a local weighted method, which weights the strength of connection between each pair of nodes. Based on the local weighted method, six local weighted similarity indices extended from unweighted similarity indices (including Common Neighbor (CN), Adamic-Adar (AA), Resource Allocation (RA), Salton, Jaccard and Local Path (LP) index) are proposed. Empirical study has shown that the local weighted method can significantly improve the prediction accuracy of these unweighted similarity indices and that in sparse and weakly clustered networks, the indices perform even better.

Linking microarray reporters with protein functions

PubMed Central

Gaj, Stan; van Erk, Arie; van Haaften, Rachel IM; Evelo, Chris TA

2007-01-01

Background The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. Results This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt) entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Conclusion Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/. PMID:17897448

Multi-objective Optimization of Departure Procedures at Gimpo International Airport

NASA Astrophysics Data System (ADS)

Kim, Junghyun; Lim, Dongwook; Monteiro, Dylan Jonathan; Kirby, Michelle; Mavris, Dimitri

2018-04-01

Most aviation communities have increasing concerns about the environmental impacts, which are directly linked to health issues for local residents near the airport. In this study, the environmental impact of different departure procedures using the Aviation Environmental Design Tool (AEDT) was analyzed. First, actual operational data were compiled at Gimpo International Airport (March 20, 2017) from an open source. Two modifications were made in the AEDT to model the operational circumstances better and the preliminary AEDT simulations were performed according to the acquired operational procedures. Simulated noise results showed good agreements with noise measurement data at specific locations. Second, a multi-objective optimization of departure procedures was performed for the Boeing 737-800. Four design variables were selected and AEDT was linked to a variety of advanced design methods. The results showed that takeoff thrust had the greatest influence and it was found that fuel burn and noise had an inverse relationship. Two points representing each fuel burn and noise optimum on the Pareto front were parsed and run in AEDT to compare with the baseline. The results showed that the noise optimum case reduced Sound Exposure Level 80-dB noise exposure area by approximately 5% while the fuel burn optimum case reduced total fuel burn by 1% relative to the baseline for aircraft-level analysis.

Computational rationality: linking mechanism and behavior through bounded utility maximization.

PubMed

Lewis, Richard L; Howes, Andrew; Singh, Satinder

2014-04-01

We propose a framework for including information-processing bounds in rational analyses. It is an application of bounded optimality (Russell & Subramanian, 1995) to the challenges of developing theories of mechanism and behavior. The framework is based on the idea that behaviors are generated by cognitive mechanisms that are adapted to the structure of not only the environment but also the mind and brain itself. We call the framework computational rationality to emphasize the incorporation of computational mechanism into the definition of rational action. Theories are specified as optimal program problems, defined by an adaptation environment, a bounded machine, and a utility function. Such theories yield different classes of explanation, depending on the extent to which they emphasize adaptation to bounds, and adaptation to some ecology that differs from the immediate local environment. We illustrate this variation with examples from three domains: visual attention in a linguistic task, manual response ordering, and reasoning. We explore the relation of this framework to existing "levels" approaches to explanation, and to other optimality-based modeling approaches. Copyright © 2014 Cognitive Science Society, Inc.

Critical phenomena in communication/computation networks with various topologies and suboptimal to optimal resource allocation

NASA Astrophysics Data System (ADS)

Cogoni, Marco; Busonera, Giovanni; Anedda, Paolo; Zanetti, Gianluigi

2015-01-01

We generalize previous studies on critical phenomena in communication networks [1,2] by adding computational capabilities to the nodes. In our model, a set of tasks with random origin, destination and computational structure is distributed on a computational network, modeled as a graph. By varying the temperature of a Metropolis Montecarlo, we explore the global latency for an optimal to suboptimal resource assignment at a given time instant. By computing the two-point correlation function for the local overload, we study the behavior of the correlation distance (both for links and nodes) while approaching the congested phase: a transition from peaked to spread g(r) is seen above a critical (Montecarlo) temperature Tc. The average latency trend of the system is predicted by averaging over several network traffic realizations while maintaining a spatially detailed information for each node: a sharp decrease of performance is found over Tc independently of the workload. The globally optimized computational resource allocation and network routing defines a baseline for a future comparison of the transition behavior with respect to existing routing strategies [3,4] for different network topologies.

Optimal Link Removal for Epidemic Mitigation: A Two-Way Partitioning Approach

PubMed Central

Enns, Eva A.; Mounzer, Jeffrey J.; Brandeau, Margaret L.

2011-01-01

The structure of the contact network through which a disease spreads may influence the optimal use of resources for epidemic control. In this work, we explore how to minimize the spread of infection via quarantining with limited resources. In particular, we examine which links should be removed from the contact network, given a constraint on the number of removable links, such that the number of nodes which are no longer at risk for infection is maximized. We show how this problem can be posed as a non-convex quadratically constrained quadratic program (QCQP), and we use this formulation to derive a link removal algorithm. The performance of our QCQP-based algorithm is validated on small Erdős-Renyi and small-world random graphs, and then tested on larger, more realistic networks, including a real-world network of injection drug use. We show that our approach achieves near optimal performance and out-perform so ther intuitive link removal algorithms, such as removing links in order of edge centrality. PMID:22115862

Measuring the value of accurate link prediction for network seeding.

PubMed

Wei, Yijin; Spencer, Gwen

2017-01-01

The influence-maximization literature seeks small sets of individuals whose structural placement in the social network can drive large cascades of behavior. Optimization efforts to find the best seed set often assume perfect knowledge of the network topology. Unfortunately, social network links are rarely known in an exact way. When do seeding strategies based on less-than-accurate link prediction provide valuable insight? We introduce optimized-against-a-sample ([Formula: see text]) performance to measure the value of optimizing seeding based on a noisy observation of a network. Our computational study investigates [Formula: see text] under several threshold-spread models in synthetic and real-world networks. Our focus is on measuring the value of imprecise link information. The level of investment in link prediction that is strategic appears to depend closely on spread model: in some parameter ranges investments in improving link prediction can pay substantial premiums in cascade size. For other ranges, such investments would be wasted. Several trends were remarkably consistent across topologies.

Linking Local Food Systems and the Social Economy? Future Roles for Farmers' Markets in Alberta and British Columbia

ERIC Educational Resources Information Center

Wittman, Hannah; Beckie, Mary; Hergesheimer, Chris

2012-01-01

Often organized as grassroots, nonprofit organizations, many farmers' markets serve as strategic venues linking producers and consumers of local food while fulfilling multiple social, economic, and environmental objectives. This article examines the potential of farmers' markets to play a catalyst role in linking local food systems to the social…

Local intelligent electronic device (IED) rendering templates over limited bandwidth communication link to manage remote IED

DOEpatents

Bradetich, Ryan; Dearien, Jason A; Grussling, Barry Jakob; Remaley, Gavin

2013-11-05

The present disclosure provides systems and methods for remote device management. According to various embodiments, a local intelligent electronic device (IED) may be in communication with a remote IED via a limited bandwidth communication link, such as a serial link. The limited bandwidth communication link may not support traditional remote management interfaces. According to one embodiment, a local IED may present an operator with a management interface for a remote IED by rendering locally stored templates. The local IED may render the locally stored templates using sparse data obtained from the remote IED. According to various embodiments, the management interface may be a web client interface and/or an HTML interface. The bandwidth required to present a remote management interface may be significantly reduced by rendering locally stored templates rather than requesting an entire management interface from the remote IED. According to various embodiments, an IED may comprise an encryption transceiver.

Joint Optimal Placement and Energy Allocation of Underwater Sensors in a Tree Topology

DTIC Science & Technology

2014-03-10

underwater acoustic sensor nodes with respect to the capacity of the wireless links between the... underwater acoustic sensor nodes with respect to the capacity of the wireless links between the nodes. We assumed that the energy consumption of...nodes’ optimal placements. We achieve the optimal placement of the underwater acoustic sensor nodes with respect to the capacity of the wireless

Analysis and Optimization of Pulse Dynamics for Magnetic Stimulation

PubMed Central

Goetz, Stefan M.; Truong, Cong Nam; Gerhofer, Manuel G.; Peterchev, Angel V.; Herzog, Hans-Georg; Weyh, Thomas

2013-01-01

Magnetic stimulation is a standard tool in brain research and has found important clinical applications in neurology, psychiatry, and rehabilitation. Whereas coil designs and the spatial field properties have been intensively studied in the literature, the temporal dynamics of the field has received less attention. Typically, the magnetic field waveform is determined by available device circuit topologies rather than by consideration of what is optimal for neural stimulation. This paper analyzes and optimizes the waveform dynamics using a nonlinear model of a mammalian axon. The optimization objective was to minimize the pulse energy loss. The energy loss drives power consumption and heating, which are the dominating limitations of magnetic stimulation. The optimization approach is based on a hybrid global-local method. Different coordinate systems for describing the continuous waveforms in a limited parameter space are defined for numerical stability. The optimization results suggest that there are waveforms with substantially higher efficiency than that of traditional pulse shapes. One class of optimal pulses is analyzed further. Although the coil voltage profile of these waveforms is almost rectangular, the corresponding current shape presents distinctive characteristics, such as a slow low-amplitude first phase which precedes the main pulse and reduces the losses. Representatives of this class of waveforms corresponding to different maximum voltages are linked by a nonlinear transformation. The main phase, however, scales with time only. As with conventional magnetic stimulation pulses, briefer pulses result in lower energy loss but require higher coil voltage than longer pulses. PMID:23469168

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

Computing the Partition Function for Kinetically Trapped RNA Secondary Structures

PubMed Central

Lorenz, William A.; Clote, Peter

2011-01-01

An RNA secondary structure is locally optimal if there is no lower energy structure that can be obtained by the addition or removal of a single base pair, where energy is defined according to the widely accepted Turner nearest neighbor model. Locally optimal structures form kinetic traps, since any evolution away from a locally optimal structure must involve energetically unfavorable folding steps. Here, we present a novel, efficient algorithm to compute the partition function over all locally optimal secondary structures of a given RNA sequence. Our software, RNAlocopt runs in time and space. Additionally, RNAlocopt samples a user-specified number of structures from the Boltzmann subensemble of all locally optimal structures. We apply RNAlocopt to show that (1) the number of locally optimal structures is far fewer than the total number of structures – indeed, the number of locally optimal structures approximately equal to the square root of the number of all structures, (2) the structural diversity of this subensemble may be either similar to or quite different from the structural diversity of the entire Boltzmann ensemble, a situation that depends on the type of input RNA, (3) the (modified) maximum expected accuracy structure, computed by taking into account base pairing frequencies of locally optimal structures, is a more accurate prediction of the native structure than other current thermodynamics-based methods. The software RNAlocopt constitutes a technical breakthrough in our study of the folding landscape for RNA secondary structures. For the first time, locally optimal structures (kinetic traps in the Turner energy model) can be rapidly generated for long RNA sequences, previously impossible with methods that involved exhaustive enumeration. Use of locally optimal structure leads to state-of-the-art secondary structure prediction, as benchmarked against methods involving the computation of minimum free energy and of maximum expected accuracy. Web server and source code available at http://bioinformatics.bc.edu/clotelab/RNAlocopt/. PMID:21297972

Measuring Link-Resolver Success: Comparing 360 Link with a Local Implementation of WebBridge

ERIC Educational Resources Information Center

Herrera, Gail

2011-01-01

This study reviewed link resolver success comparing 360 Link and a local implementation of WebBridge. Two methods were used: (1) comparing article-level access and (2) examining technical issues for 384 randomly sampled OpenURLs. Google Analytics was used to collect user-generated OpenURLs. For both methods, 360 Link out-performed the local…

Exact and explicit optimal solutions for trajectory planning and control of single-link flexible-joint manipulators

NASA Technical Reports Server (NTRS)

Chen, Guanrong

1991-01-01

An optimal trajectory planning problem for a single-link, flexible joint manipulator is studied. A global feedback-linearization is first applied to formulate the nonlinear inequality-constrained optimization problem in a suitable way. Then, an exact and explicit structural formula for the optimal solution of the problem is derived and the solution is shown to be unique. It turns out that the optimal trajectory planning and control can be done off-line, so that the proposed method is applicable to both theoretical analysis and real time tele-robotics control engineering.

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.

Link prediction based on local community properties

NASA Astrophysics Data System (ADS)

Yang, Xu-Hua; Zhang, Hai-Feng; Ling, Fei; Cheng, Zhi; Weng, Guo-Qing; Huang, Yu-Jiao

2016-09-01

The link prediction algorithm is one of the key technologies to reveal the inherent rule of network evolution. This paper proposes a novel link prediction algorithm based on the properties of the local community, which is composed of the common neighbor nodes of any two nodes in the network and the links between these nodes. By referring to the node degree and the condition of assortativity or disassortativity in a network, we comprehensively consider the effect of the shortest path and edge clustering coefficient within the local community on node similarity. We numerically show the proposed method provide good link prediction results.

NordicWelfAir - Understanding the link between Air pollution and Distribution of related Health Impacts and Welfare in the Nordic countries

NASA Astrophysics Data System (ADS)

Brandt, Jørgen

2017-04-01

Air pollution has serious impacts on human health, wellbeing and welfare. The main challenge is to understand how to regulate air pollution in an optimal way both on global and local scales. Linking the detailed information of the spatio-temporal distribution of air pollution levels and the chemical composition of the atmospheric particles with register data for mortality and morbidity, we have a unique opportunity in the Nordic countries to gain new understanding of the various health impacts from different kinds of air pollution from different kind of sources. This will provide the basic understanding needed for policy making of strategies to optimally reduce the air pollution challenge and to assess the related impacts on the distribution of health impacts and related societal costs and welfare. The large interdisciplinary NordicWelfAir project (http://nordicwelfair.au.dk), funded by NordForsk, will take advantage of the unique Nordic data. The results from the project will be used in both a Nordic as well as global perspective to improve the health and welfare by finding the optimal solutions to societal and public health challenges from air pollution through high-quality research. The results from the research in this project have the potential to act as new international standards in our understanding of health impacts from air pollution for different population groups due to the possibility to integrate the unique data and knowledge of air pollution, register, health, socio-economics, and welfare research in the Nordic countries in a highly interdisciplinary project. The study will provide a Nordic contribution to international research on the topics of environmental equality and justice within the area of air quality related risks, amenities and wellbeing. Acknowledgements This project is funded by NordForsk under the Nordic Programme on Health and Welfare. Project #75007: Understanding the link between air pollution and distribution of related health impacts and welfare in the Nordic countries (http://NordicWelfAir.au.dk).

Dynamic storage in resource-scarce browsing multimedia applications

NASA Astrophysics Data System (ADS)

Elenbaas, Herman; Dimitrova, Nevenka

1998-10-01

In the convergence of information and entertainment there is a conflict between the consumer's expectation of fast access to high quality multimedia content through narrow bandwidth channels versus the size of this content. During the retrieval and information presentation of a multimedia application there are two problems that have to be solved: the limited bandwidth during transmission of the retrieved multimedia content and the limited memory for temporary caching. In this paper we propose an approach for latency optimization in information browsing applications. We proposed a method for flattening hierarchically linked documents in a manner convenient for network transport over slow channels to minimize browsing latency. Flattening of the hierarchy involves linearization, compression and bundling of the document nodes. After the transfer, the compressed hierarchy is stored on a local device where it can be partly unbundled to fit the caching limits at the local site while giving the user availability to the content.

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

Kalligiannaki, Evangelia, E-mail: ekalligian@tem.uoc.gr; Harmandaris, Vagelis, E-mail: harman@uoc.gr; Institute of Applied and Computational Mathematics

Using the probabilistic language of conditional expectations, we reformulate the force matching method for coarse-graining of molecular systems as a projection onto spaces of coarse observables. A practical outcome of this probabilistic description is the link of the force matching method with thermodynamic integration. This connection provides a way to systematically construct a local mean force and to optimally approximate the potential of mean force through force matching. We introduce a generalized force matching condition for the local mean force in the sense that allows the approximation of the potential of mean force under both linear and non-linear coarse grainingmore » mappings (e.g., reaction coordinates, end-to-end length of chains). Furthermore, we study the equivalence of force matching with relative entropy minimization which we derive for general non-linear coarse graining maps. We present in detail the generalized force matching condition through applications to specific examples in molecular systems.« less

Suppressed epidemics in multirelational networks

NASA Astrophysics Data System (ADS)

Xu, Elvis H. W.; Wang, Wei; Xu, C.; Tang, Ming; Do, Younghae; Hui, P. M.

2015-08-01

A two-state epidemic model in networks with links mimicking two kinds of relationships between connected nodes is introduced. Links of weights w1 and w0 occur with probabilities p and 1 -p , respectively. The fraction of infected nodes ρ (p ) shows a nonmonotonic behavior, with ρ drops with p for small p and increases for large p . For small to moderate w1/w0 ratios, ρ (p ) exhibits a minimum that signifies an optimal suppression. For large w1/w0 ratios, the suppression leads to an absorbing phase consisting only of healthy nodes within a range pL≤p ≤pR , and an active phase with mixed infected and healthy nodes for p pR . A mean field theory that ignores spatial correlation is shown to give qualitative agreement and capture all the key features. A physical picture that emphasizes the intricate interplay between infections via w0 links and within clusters formed by nodes carrying the w1 links is presented. The absorbing state at large w1/w0 ratios results when the clusters are big enough to disrupt the spread via w0 links and yet small enough to avoid an epidemic within the clusters. A theory that uses the possible local environments of a node as variables is formulated. The theory gives results in good agreement with simulation results, thereby showing the necessity of including longer spatial correlations.

Optimized circulation and weather type classifications relating large-scale atmospheric conditions to local PM10 concentrations in Bavaria

NASA Astrophysics Data System (ADS)

Weitnauer, C.; Beck, C.; Jacobeit, J.

2013-12-01

In the last decades the critical increase of the emission of air pollutants like nitrogen dioxide, sulfur oxides and particulate matter especially in urban areas has become a problem for the environment as well as human health. Several studies confirm a risk of high concentration episodes of particulate matter with an aerodynamic diameter < 10 μm (PM10) for the respiratory tract or cardiovascular diseases. Furthermore it is known that local meteorological and large scale atmospheric conditions are important influencing factors on local PM10 concentrations. With climate changing rapidly, these connections need to be better understood in order to provide estimates of climate change related consequences for air quality management purposes. For quantifying the link between large-scale atmospheric conditions and local PM10 concentrations circulation- and weather type classifications are used in a number of studies by using different statistical approaches. Thus far only few systematic attempts have been made to modify consisting or to develop new weather- and circulation type classifications in order to improve their ability to resolve local PM10 concentrations. In this contribution existing weather- and circulation type classifications, performed on daily 2.5 x 2.5 gridded parameters of the NCEP/NCAR reanalysis data set, are optimized with regard to their discriminative power for local PM10 concentrations at 49 Bavarian measurement sites for the period 1980 to 2011. Most of the PM10 stations are situated in urban areas covering urban background, traffic and industry related pollution regimes. The range of regimes is extended by a few rural background stations. To characterize the correspondence between the PM10 measurements of the different stations by spatial patterns, a regionalization by an s-mode principal component analysis is realized on the high-pass filtered data. The optimization of the circulation- and weather types is implemented using two representative classification approaches, a k-means cluster analysis and an objective version of the Grosswetter types. They have been run with varying spatial and temporal settings as well as modified numbers of classes. As an evaluation metric for their performance several skill scores are used. Taking into account the outcome further attempts towards the optimization of circulation type classifications are made. These are varying meteorological input parameters (e.g. geopotential height, zonal and meridional wind, specific humidity, temperature) on several pressure levels (1000, 850 and 500 hPa) and combinations of these variables. All classification variants are again evaluated. Based on these analyses it is further intended to develop robust downscaling models for estimating possible future - climate change induced - variations of local PM10 concentrations in Bavaria from scenario runs of global CMIP5 climate models.

Quality by design approach for developing chitosan-Ca-alginate microspheres for colon delivery of celecoxib-hydroxypropyl-β-cyclodextrin-PVP complex.

PubMed

Mennini, N; Furlanetto, S; Cirri, M; Mura, P

2012-01-01

The aim of the present work was to develop a new multiparticulate system, designed for colon-specific delivery of celecoxib for both systemic (in chronotherapic treatment of arthritis) and local (in prophylaxis of colon carcinogenesis) therapy. The system simultaneously benefits from ternary complexation with hydroxypropyl-β-cyclodextrin and PVP (polyvinylpyrrolidone), to increase drug solubility, and vectorization in chitosan-Ca-alginate microspheres, to exploit the colon-specific carrier properties of these polymers. Statistical experimental design was employed to investigate the combined effect of four formulation variables, i.e., % of alginate, CaCl₂, and chitosan and time of cross-linking on microsphere entrapment efficiency (EE%) and drug amount released after 4h in colonic medium, considered as the responses to be optimized. Design of experiment was used in the context of Quality by Design, which requires a multivariate approach for understanding the multifactorial relationships among formulation parameters. Doehlert design allowed for defining a design space, which revealed that variations of the considered factors had in most cases an opposite influence on the responses. Desirability function was used to attain simultaneous optimization of both responses. The desired goals were achieved for both systemic and local use of celecoxib. Experimental values obtained from the optimized formulations were in both cases very close to the predicted values, thus confirming the validity of the generated mathematical model. These results demonstrated the effectiveness of the proposed jointed use of drug cyclodextrin complexation and chitosan-Ca-alginate microsphere vectorization, as well as the usefulness of the multivariate approach for the preparation of colon-targeted celecoxib microspheres with optimized properties. Copyright © 2011 Elsevier B.V. All rights reserved.

Cascaded Optimization for a Persistent Data Ferrying Unmanned Aircraft

NASA Astrophysics Data System (ADS)

Carfang, Anthony

This dissertation develops and assesses a cascaded method for designing optimal periodic trajectories and link schedules for an unmanned aircraft to ferry data between stationary ground nodes. This results in a fast solution method without the need to artificially constrain system dynamics. Focusing on a fundamental ferrying problem that involves one source and one destination, but includes complex vehicle and Radio-Frequency (RF) dynamics, a cascaded structure to the system dynamics is uncovered. This structure is exploited by reformulating the nonlinear optimization problem into one that reduces the independent control to the vehicle's motion, while the link scheduling control is folded into the objective function and implemented as an optimal policy that depends on candidate motion control. This formulation is proven to maintain optimality while reducing computation time in comparison to traditional ferry optimization methods. The discrete link scheduling problem takes the form of a combinatorial optimization problem that is known to be NP-Hard. A derived necessary condition for optimality guides the development of several heuristic algorithms, specifically the Most-Data-First Algorithm and the Knapsack Adaptation. These heuristics are extended to larger ferrying scenarios, and assessed analytically and through Monte Carlo simulation, showing better throughput performance in the same order of magnitude of computation time in comparison to other common link scheduling policies. The cascaded optimization method is implemented with a novel embedded software system on a small, unmanned aircraft to validate the simulation results with field experiments. To address the sensitivity of results on trajectory tracking performance, a system that combines motion and link control with waypoint-based navigation is developed and assessed through field experiments. The data ferrying algorithms are further extended by incorporating a Gaussian process to opportunistically learn the RF environment. By continuously improving RF models, the cascaded planner can continually improve the ferrying system's overall performance.

Influence of Different Coupling Modes on the Robustness of Smart Grid under Targeted Attack.

PubMed

Kang, WenJie; Hu, Gang; Zhu, PeiDong; Liu, Qiang; Hang, Zhi; Liu, Xin

2018-05-24

Many previous works only focused on the cascading failure of global coupling of one-to-one structures in interdependent networks, but the local coupling of dual coupling structures has rarely been studied due to its complex structure. This will result in a serious consequence that many conclusions of the one-to-one structure may be incorrect in the dual coupling network and do not apply to the smart grid. Therefore, it is very necessary to subdivide the dual coupling link into a top-down coupling link and a bottom-up coupling link in order to study their influence on network robustness by combining with different coupling modes. Additionally, the power flow of the power grid can cause the load of a failed node to be allocated to its neighboring nodes and trigger a new round of load distribution when the load of these nodes exceeds their capacity. This means that the robustness of smart grids may be affected by four factors, i.e., load redistribution, local coupling, dual coupling link and coupling mode; however, the research on the influence of those factors on the network robustness is missing. In this paper, firstly, we construct the smart grid as a two-layer network with a dual coupling link and divide the power grid and communication network into many subnets based on the geographical location of their nodes. Secondly, we define node importance ( N I ) as an evaluation index to access the impact of nodes on the cyber or physical network and propose three types of coupling modes based on N I of nodes in the cyber and physical subnets, i.e., Assortative Coupling in Subnets (ACIS), Disassortative Coupling in Subnets (DCIS), and Random Coupling in Subnets (RCIS). Thirdly, a cascading failure model is proposed for studying the effect of local coupling of dual coupling link in combination with ACIS, DCIS, and RCIS on the robustness of the smart grid against a targeted attack, and the survival rate of functional nodes is used to assess the robustness of the smart grid. Finally, we use the IEEE 118-Bus System and the Italian High-Voltage Electrical Transmission Network to verify our model and obtain the same conclusions: (I) DCIS applied to the top-down coupling link is better able to enhance the robustness of the smart grid against a targeted attack than RCIS or ACIS, (II) ACIS applied to a bottom-up coupling link is better able to enhance the robustness of the smart grid against a targeted attack than RCIS or DCIS, and (III) the robustness of the smart grid can be improved by increasing the tolerance α . This paper provides some guidelines for slowing down the speed of the cascading failures in the design of architecture and optimization of interdependent networks, such as a top-down link with DCIS, a bottom-up link with ACIS, and an increased tolerance α .

Improving the energy efficiency of telecommunication networks

NASA Astrophysics Data System (ADS)

Lange, Christoph; Gladisch, Andreas

2011-05-01

The energy consumption of telecommunication networks has gained increasing interest throughout the recent past: Besides its environmental implications it has been identified to be a major contributor to operational expenditures of network operators. Targeting at sustainable telecommunication networks, thus, it is important to find appropriate strategies for improving their energy efficiency before the background of rapidly increasing traffic volumes. Besides the obvious benefits of increasing energy efficiency of network elements by leveraging technology progress, load-adaptive network operation is a very promising option, i.e. using network resources only to an extent and for the time they are actually needed. In contrast, current network operation takes almost no advantage of the strongly time-variant behaviour of the network traffic load. Mechanisms for energy-aware load-adaptive network operation can be subdivided in techniques based on local autonomous or per-link decisions and in techniques relying on coordinated decisions incorporating information from several links. For the transformation from current network structures and operation paradigms towards energy-efficient and sustainable networks it will be essential to use energy-optimized network elements as well as including the overall energy consumption in network design and planning phases together with the energy-aware load-adaptive operation. In load-adaptive operation it will be important to establish the optimum balance between local and overarching power management concepts in telecommunication networks.

Profile shape optimization in multi-jet impingement cooling of dimpled topologies for local heat transfer enhancement

NASA Astrophysics Data System (ADS)

Negi, Deepchand Singh; Pattamatta, Arvind

2015-04-01

The present study deals with shape optimization of dimples on the target surface in multi-jet impingement heat transfer. Bezier polynomial formulation is incorporated to generate profile shapes for the dimple profile generation and a multi-objective optimization is performed. The optimized dimple shape exhibits higher local Nusselt number values compared to the reference hemispherical dimpled plate optimized shape which can be used to alleviate local temperature hot spots on target surface.

Synthesizing epidemiological and economic optima for control of immunizing infections.

PubMed

Klepac, Petra; Laxminarayan, Ramanan; Grenfell, Bryan T

2011-08-23

Epidemic theory predicts that the vaccination threshold required to interrupt local transmission of an immunizing infection like measles depends only on the basic reproductive number and hence transmission rates. When the search for optimal strategies is expanded to incorporate economic constraints, the optimum for disease control in a single population is determined by relative costs of infection and control, rather than transmission rates. Adding a spatial dimension, which precludes local elimination unless it can be achieved globally, can reduce or increase optimal vaccination levels depending on the balance of costs and benefits. For weakly coupled populations, local optimal strategies agree with the global cost-effective strategy; however, asymmetries in costs can lead to divergent control optima in more strongly coupled systems--in particular, strong regional differences in costs of vaccination can preclude local elimination even when elimination is locally optimal. Under certain conditions, it is locally optimal to share vaccination resources with other populations.

Modeling intraspecific adaptation of Abies sachalinensis to local altitude and responses to global warming, based on a 36-year reciprocal transplant experiment.

PubMed

Ishizuka, Wataru; Goto, Susumu

2012-04-01

Intraspecific adaptation in Abies sachalinensis was examined using models based on long-term monitoring data gathered during a reciprocal transplant experiment with eight seed source populations and six transplantation sites along an altitudinal gradient. The consequence of local adaptation was evaluated by testing the home-site advantage for upslope and downslope transplants at five ages. The populations' fitness-linked trait was set as their productivity (tree height × survival rate) at each age. The effects of global warming were evaluated on the basis of the 36-year performance of downslope transplants. Evidence was found for adaptive genetic variation affecting both height and survival from an early age. Increasing the distance between seed source and planting site significantly reduced productivity for both upslope and downslope transplantation, demonstrating the existence of a significant home-site advantage. The decrease in productivity was most distinct for upslope transplantations, indicating strong local adaptation to high altitudes. Global warming is predicted to increase the productivity of high-altitude populations. However, owing to their existing local adaptation, all tested populations exhibited lower productivity under warming than demes that were optimal for the new climate. These negative predictions should be considered when planning the management of locally adapted plant species such as A. sachalinensis.

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.

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 two-objective optimization scheme for high-OSNR and low-power-consuming all-optical networks

NASA Astrophysics Data System (ADS)

Abedifar, Vahid; Mirjalili, Seyed Mohammad; Eshghi, Mohammad

2015-01-01

In all-optical networks the ASE noise of the utilized optical power amplifiers is a major impairment, making the OSNR to be the dominant parameter in QoS. In this paper, a two-objective optimization scheme using Multi-Objective Particle Swarm Optimization (MOPSO) is proposed to reach the maximum OSNR for all channels while the optical power consumed by EDFAs and lasers is minimized. Two scenarios are investigated: Scenario 1 and Scenario 2. The former scenario optimizes the gain values of a predefined number of EDFAs in physical links. The gain values may be different from each other. The latter scenario optimizes the gains value of EDFAs (which is supposed to be identical in each physical link) in addition to the number of EDFAs for each physical link. In both scenarios, the launch powers of the lasers are also taken into account during optimization process. Two novel encoding methods are proposed to uniquely represent the problem solutions. Two virtual demand sets are considered for evaluation of the performance of the proposed optimization scheme. The simulations results are described for both scenarios and both virtual demands.

A new statistical tool for NOAA local climate studies

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Meyers, J. C.; Hollingshead, A.

2011-12-01

The National Weather Services (NWS) Local Climate Analysis Tool (LCAT) is evolving out of a need to support and enhance the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) field offices' ability to efficiently access, manipulate, and interpret local climate data and characterize climate variability and change impacts. LCAT will enable NOAA's staff to conduct regional and local climate studies using state-of-the-art station and reanalysis gridded data and various statistical techniques for climate analysis. The analysis results will be used for climate services to guide local decision makers in weather and climate sensitive actions and to deliver information to the general public. LCAT will augment current climate reference materials with information pertinent to the local and regional levels as they apply to diverse variables appropriate to each locality. The LCAT main emphasis is to enable studies of extreme meteorological and hydrological events such as tornadoes, flood, drought, severe storms, etc. LCAT will close a very critical gap in NWS local climate services because it will allow addressing climate variables beyond average temperature and total precipitation. NWS external partners and government agencies will benefit from the LCAT outputs that could be easily incorporated into their own analysis and/or delivery systems. Presently we identified five existing requirements for local climate: (1) Local impacts of climate change; (2) Local impacts of climate variability; (3) Drought studies; (4) Attribution of severe meteorological and hydrological events; and (5) Climate studies for water resources. The methodologies for the first three requirements will be included in the LCAT first phase implementation. Local rate of climate change is defined as a slope of the mean trend estimated from the ensemble of three trend techniques: (1) hinge, (2) Optimal Climate Normals (running mean for optimal time periods), (3) exponentially-weighted moving average. Root mean squared error is used to determine the best fit of trend to the observations with the least error. The studies of climate variability impacts on local extremes use composite techniques applied to various definitions of local variables: from specified percentiles to critical thresholds. Drought studies combine visual capabilities of Google maps with statistical estimates of drought severity indices. The process of development will be linked to local office interactions with users to ensure the tool will meet their needs as well as provide adequate training. A rigorous internal and tiered peer-review process will be implemented to ensure the studies are scientifically-sound that will be published and submitted to the local studies catalog (database) and eventually to external sources, such as the Climate Portal.

Three-Dimensional Microwave Hyperthermia for Breast Cancer Treatment in a Realistic Environment Using Particle Swarm Optimization.

PubMed

Nguyen, Phong Thanh; Abbosh, Amin; Crozier, Stuart

2017-06-01

In this paper, a technique for noninvasive microwave hyperthermia treatment for breast cancer is presented. In the proposed technique, microwave hyperthermia of patient-specific breast models is implemented using a three-dimensional (3-D) antenna array based on differential beam-steering subarrays to locally raise the temperature of the tumor to therapeutic values while keeping healthy tissue at normal body temperature. This approach is realized by optimizing the excitations (phases and amplitudes) of the antenna elements using the global optimization method particle swarm optimization. The antennae excitation phases are optimized to maximize the power at the tumor, whereas the amplitudes are optimized to accomplish the required temperature at the tumor. During the optimization, the technique ensures that no hotspots exist in healthy tissue. To implement the technique, a combination of linked electromagnetic and thermal analyses using MATLAB and the full-wave electromagnetic simulator is conducted. The technique is tested at 4.2 GHz, which is a compromise between the required power penetration and focusing, in a realistic simulation environment, which is built using a 3-D antenna array of 4 × 6 unidirectional antenna elements. The presented results on very dense 3-D breast models, which have the realistic dielectric and thermal properties, validate the capability of the proposed technique in focusing power at the exact location and volume of tumor even in the challenging cases where tumors are embedded in glands. Moreover, the models indicate the capability of the technique in dealing with tumors at different on- and off-axis locations within the breast with high efficiency in using the microwave power.

Link between hopping models and percolation scaling laws for charge transport in mixtures of small molecules

DOE PAGES

Ha, Dong -Gwang; Kim, Jang -Joo; Baldo, Marc A.

2016-04-29

Mixed host compositions that combine charge transport materials with luminescent dyes offer superior control over exciton formation and charge transport in organic light emitting devices (OLEDs). Two approaches are typically used to optimize the fraction of charge transport materials in a mixed host composition: either an empirical percolative model, or a hopping transport model. We show that these two commonly-employed models are linked by an analytic expression which relates the localization length to the percolation threshold and critical exponent. The relation is confirmed both numerically and experimentally through measurements of the relative conductivity of Tris(4-carbazoyl-9-ylphenyl) amine (TCTA) :1,3-bis(3,5-dipyrid-3-yl-phenyl) benzene (BmPyPb)more » mixtures with different concentrations, where the TCTA plays a role as hole conductor and the BmPyPb as hole insulator. Furthermore, the analytic relation may allow the rational design of mixed layers of small molecules for high-performance OLEDs.« less

A structural design decomposition method utilizing substructuring

NASA Technical Reports Server (NTRS)

Scotti, Stephen J.

1994-01-01

A new method of design decomposition for structural analysis and optimization is described. For this method, the structure is divided into substructures where each substructure has its structural response described by a structural-response subproblem, and its structural sizing determined from a structural-sizing subproblem. The structural responses of substructures that have rigid body modes when separated from the remainder of the structure are further decomposed into displacements that have no rigid body components, and a set of rigid body modes. The structural-response subproblems are linked together through forces determined within a structural-sizing coordination subproblem which also determines the magnitude of any rigid body displacements. Structural-sizing subproblems having constraints local to the substructures are linked together through penalty terms that are determined by a structural-sizing coordination subproblem. All the substructure structural-response subproblems are totally decoupled from each other, as are all the substructure structural-sizing subproblems, thus there is significant potential for use of parallel solution methods for these subproblems.

Link between hopping models and percolation scaling laws for charge transport in mixtures of small molecules

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

Ha, Dong-Gwang; Kim, Jang-Joo; Baldo, Marc A.

2016-04-01

Mixed host compositions that combine charge transport materials with luminescent dyes offer superior control over exciton formation and charge transport in organic light emitting devices (OLEDs). Two approaches are typically used to optimize the fraction of charge transport materials in a mixed host composition: either an empirical percolative model, or a hopping transport model. We show that these two commonly-employed models are linked by an analytic expression which relates the localization length to the percolation threshold and critical exponent. The relation is confirmed both numerically and experimentally through measurements of the relative conductivity of Tris(4-carbazoyl-9-ylphenyl)amine (TCTA) :1,3-bis(3,5-dipyrid-3-yl-phenyl)benzene (BmPyPb) mixtures withmore » different concentrations, where the TCTA plays a role as hole conductor and the BmPyPb as hole insulator. The analytic relation may allow the rational design of mixed layers of small molecules for high-performance OLEDs.« less

Highly broad-specific and sensitive enzyme-linked immunosorbent assay for screening sulfonamides: Assay optimization and application to milk samples

USDA-ARS?s Scientific Manuscript database

A broad-specific and sensitive immunoassay for the detection of sulfonamides was developed by optimizing the conditions of an enzyme-linked immunosorbent assay (ELISA) in regard to different monoclonal antibodies (MAbs), assay format, immunoreagents, and several physicochemical factors (pH, salt, de...

Link Design and Planning for Mars Reconnaissance Orbiter (MRO) Ka-band (32 GHz) Telecom Demonstration

NASA Technical Reports Server (NTRS)

Shambayati, Shervin; Davarian, Faramaz; Morabito, David

2004-01-01

NASA is planning an engineering telemetry demonstration with Mars Reconnaissance Orbiter (MRO). Capabilities of Ka-band (32 GHz) for use with deep space mission are demonstrated using the link optimization algorithms and weather forecasting. Furthermore, based on the performance of previous deep space missions with Ka-band downlink capabilities, experiment plans are developed for telemetry operations during superior solar conjunction. A general overview of the demonstration is given followed by a description of the mission planning during cruise, the primary science mission and superior conjunction. As part of the primary science mission planning the expected data return for various data optimization methods is calculated. These results indicate that, given MRO's data rates, a link optimized to use of at most two data rates, subject to a minimum availability of 90%, performs almost as well as a link with no limits on the number of data rates subject to the same minimum availability.

Optimization and resilience of complex supply-demand networks

NASA Astrophysics Data System (ADS)

Zhang, Si-Ping; Huang, Zi-Gang; Dong, Jia-Qi; Eisenberg, Daniel; Seager, Thomas P.; Lai, Ying-Cheng

2015-06-01

Supply-demand processes take place on a large variety of real-world networked systems ranging from power grids and the internet to social networking and urban systems. In a modern infrastructure, supply-demand systems are constantly expanding, leading to constant increase in load requirement for resources and consequently, to problems such as low efficiency, resource scarcity, and partial system failures. Under certain conditions global catastrophe on the scale of the whole system can occur through the dynamical process of cascading failures. We investigate optimization and resilience of time-varying supply-demand systems by constructing network models of such systems, where resources are transported from the supplier sites to users through various links. Here by optimization we mean minimization of the maximum load on links, and system resilience can be characterized using the cascading failure size of users who fail to connect with suppliers. We consider two representative classes of supply schemes: load driven supply and fix fraction supply. Our findings are: (1) optimized systems are more robust since relatively smaller cascading failures occur when triggered by external perturbation to the links; (2) a large fraction of links can be free of load if resources are directed to transport through the shortest paths; (3) redundant links in the performance of the system can help to reroute the traffic but may undesirably transmit and enlarge the failure size of the system; (4) the patterns of cascading failures depend strongly upon the capacity of links; (5) the specific location of the trigger determines the specific route of cascading failure, but has little effect on the final cascading size; (6) system expansion typically reduces the efficiency; and (7) when the locations of the suppliers are optimized over a long expanding period, fewer suppliers are required. These results hold for heterogeneous networks in general, providing insights into designing optimal and resilient complex supply-demand systems that expand constantly in time.

Optimal cube-connected cube multiprocessors

NASA Technical Reports Server (NTRS)

Sun, Xian-He; Wu, Jie

1993-01-01

Many CFD (computational fluid dynamics) and other scientific applications can be partitioned into subproblems. However, in general the partitioned subproblems are very large. They demand high performance computing power themselves, and the solutions of the subproblems have to be combined at each time step. The cube-connect cube (CCCube) architecture is studied. The CCCube architecture is an extended hypercube structure with each node represented as a cube. It requires fewer physical links between nodes than the hypercube, and provides the same communication support as the hypercube does on many applications. The reduced physical links can be used to enhance the bandwidth of the remaining links and, therefore, enhance the overall performance. The concept and the method to obtain optimal CCCubes, which are the CCCubes with a minimum number of links under a given total number of nodes, are proposed. The superiority of optimal CCCubes over standard hypercubes was also shown in terms of the link usage in the embedding of a binomial tree. A useful computation structure based on a semi-binomial tree for divide-and-conquer type of parallel algorithms was identified. It was shown that this structure can be implemented in optimal CCCubes without performance degradation compared with regular hypercubes. The result presented should provide a useful approach to design of scientific parallel computers.

LIDAR mapping of ozone-episode dynamics in Paris and intercomparison with spot analyzers Supplementary material available at http://link.springer.de/journals/apb

NASA Astrophysics Data System (ADS)

Thomasson, A.; Geffroy, S.; Frejafon, E.; Weidauer, D.; Fabian, R.; Godet, Y.; Nominé, M.; Ménard, T.; Rairoux, P.; Moeller, D.; Wolf, J. P.

Continuous mapping of an ozone episode in Paris in June 1999 has been performed using a differential absorption lidar system. The 2D ozone concentration vertical maps recorded over 33 h at the Champ de Mars are compiled in a video clip that gives access to local photochemical dynamics with unprecedented precision. The lidar data are compared over the whole period with point monitors located at 0-, 50-, and 300-m altitudes on the Eiffel Tower. Very good agreement is found when spatial resolution, acquisition time, and required concentration accuracy are optimized. Sensitivity to these parameters for successful intercomparison in urban areas is discussed.

Optimizer convergence and local minima errors and their clinical importance

NASA Astrophysics Data System (ADS)

Jeraj, Robert; Wu, Chuan; Mackie, Thomas R.

2003-09-01

Two of the errors common in the inverse treatment planning optimization have been investigated. The first error is the optimizer convergence error, which appears because of non-perfect convergence to the global or local solution, usually caused by a non-zero stopping criterion. The second error is the local minima error, which occurs when the objective function is not convex and/or the feasible solution space is not convex. The magnitude of the errors, their relative importance in comparison to other errors as well as their clinical significance in terms of tumour control probability (TCP) and normal tissue complication probability (NTCP) were investigated. Two inherently different optimizers, a stochastic simulated annealing and deterministic gradient method were compared on a clinical example. It was found that for typical optimization the optimizer convergence errors are rather small, especially compared to other convergence errors, e.g., convergence errors due to inaccuracy of the current dose calculation algorithms. This indicates that stopping criteria could often be relaxed leading into optimization speed-ups. The local minima errors were also found to be relatively small and typically in the range of the dose calculation convergence errors. Even for the cases where significantly higher objective function scores were obtained the local minima errors were not significantly higher. Clinical evaluation of the optimizer convergence error showed good correlation between the convergence of the clinical TCP or NTCP measures and convergence of the physical dose distribution. On the other hand, the local minima errors resulted in significantly different TCP or NTCP values (up to a factor of 2) indicating clinical importance of the local minima produced by physical optimization.

Optimizer convergence and local minima errors and their clinical importance.

PubMed

Jeraj, Robert; Wu, Chuan; Mackie, Thomas R

2003-09-07

Two of the errors common in the inverse treatment planning optimization have been investigated. The first error is the optimizer convergence error, which appears because of non-perfect convergence to the global or local solution, usually caused by a non-zero stopping criterion. The second error is the local minima error, which occurs when the objective function is not convex and/or the feasible solution space is not convex. The magnitude of the errors, their relative importance in comparison to other errors as well as their clinical significance in terms of tumour control probability (TCP) and normal tissue complication probability (NTCP) were investigated. Two inherently different optimizers, a stochastic simulated annealing and deterministic gradient method were compared on a clinical example. It was found that for typical optimization the optimizer convergence errors are rather small, especially compared to other convergence errors, e.g., convergence errors due to inaccuracy of the current dose calculation algorithms. This indicates that stopping criteria could often be relaxed leading into optimization speed-ups. The local minima errors were also found to be relatively small and typically in the range of the dose calculation convergence errors. Even for the cases where significantly higher objective function scores were obtained the local minima errors were not significantly higher. Clinical evaluation of the optimizer convergence error showed good correlation between the convergence of the clinical TCP or NTCP measures and convergence of the physical dose distribution. On the other hand, the local minima errors resulted in significantly different TCP or NTCP values (up to a factor of 2) indicating clinical importance of the local minima produced by physical optimization.

Acceleration techniques in the univariate Lipschitz global optimization

NASA Astrophysics Data System (ADS)

Sergeyev, Yaroslav D.; Kvasov, Dmitri E.; Mukhametzhanov, Marat S.; De Franco, Angela

2016-10-01

Univariate box-constrained Lipschitz global optimization problems are considered in this contribution. Geometric and information statistical approaches are presented. The novel powerful local tuning and local improvement techniques are described in the contribution as well as the traditional ways to estimate the Lipschitz constant. The advantages of the presented local tuning and local improvement techniques are demonstrated using the operational characteristics approach for comparing deterministic global optimization algorithms on the class of 100 widely used test functions.

System-level power optimization for real-time distributed embedded systems

NASA Astrophysics Data System (ADS)

Luo, Jiong

Power optimization is one of the crucial design considerations for modern electronic systems. In this thesis, we present several system-level power optimization techniques for real-time distributed embedded systems, based on dynamic voltage scaling, dynamic power management, and management of peak power and variance of the power profile. Dynamic voltage scaling has been widely acknowledged as an important and powerful technique to trade off dynamic power consumption and delay. Efficient dynamic voltage scaling requires effective variable-voltage scheduling mechanisms that can adjust voltages and clock frequencies adaptively based on workloads and timing constraints. For this purpose, we propose static variable-voltage scheduling algorithms utilizing criticalpath driven timing analysis for the case when tasks are assumed to have uniform switching activities, as well as energy-gradient driven slack allocation for a more general scenario. The proposed techniques can achieve closeto-optimal power savings with very low computational complexity, without violating any real-time constraints. We also present algorithms for power-efficient joint scheduling of multi-rate periodic task graphs along with soft aperiodic tasks. The power issue is addressed through both dynamic voltage scaling and power management. Periodic task graphs are scheduled statically. Flexibility is introduced into the static schedule to allow the on-line scheduler to make local changes to PE schedules through resource reclaiming and slack stealing, without interfering with the validity of the global schedule. We provide a unified framework in which the response times of aperiodic tasks and power consumption are dynamically optimized simultaneously. Interconnection network fabrics point to a new generation of power-efficient and scalable interconnection architectures for distributed embedded systems. As the system bandwidth continues to increase, interconnection networks become power/energy limited as well. Variable-frequency links have been designed by circuit designers for both parallel and serial links, which can adaptively regulate the supply voltage of transceivers to a desired link frequency, to exploit the variations in bandwidth requirement for power savings. We propose solutions for simultaneous dynamic voltage scaling of processors and links. The proposed solution considers real-time scheduling, flow control, and packet routing jointly. It can trade off the power consumption on processors and communication links via efficient slack allocation, and lead to more power savings than dynamic voltage scaling on processors alone. For battery-operated systems, the battery lifespan is an important concern. Due to the effects of discharge rate and battery recovery, the discharge pattern of batteries has an impact on the battery lifespan. Battery models indicate that even under the same average power consumption, reducing peak power current and variance in the power profile can increase the battery efficiency and thereby prolong battery lifetime. To take advantage of these effects, we propose battery-driven scheduling techniques for embedded applications, to reduce the peak power and the variance in the power profile of the overall system under real-time constraints. The proposed scheduling algorithms are also beneficial in addressing reliability and signal integrity concerns by effectively controlling peak power and variance of the power profile.

Demonstration of hydrazide tagging for O-glycans and a central composite design of experiments optimization using the INLIGHT™ reagent.

PubMed

King, Samuel R; Hecht, Elizabeth S; Muddiman, David C

2018-02-01

The INLIGHT™ strategy for N-linked glycan derivatization has been shown to overcome many of the challenges associated with glycan analysis. The hydrazide tag reacts efficiently with the glycans, increasing their non-polar surface area, allowing for reversed-phase separations and increased ionization efficiency. We have taken the INLIGHT™ strategy and adopted it for use with O-linked glycans. A central composite design was utilized to find optimized tagging conditions (45% acetic acid, 0.1 μg/μL tag concentration, 37 C, 1.75 h). Derivatization at optimized conditions was much quicker than any hydrazide derivatization strategy used previously. Human immunoglobulin A (IgA) and bovine submaxillary mucin (BSM) were then deglycosylated through hydrazinolysis and the removed glycans were tagged under optimum conditions. XIC of tagged glycans and MS2 data show successful hydrazide tagging of O-linked glycans for the first time. Graphical abstract The INLIGHT™ hydrazide tag was optimized using a central composite design for derivatization of O-linked glycans. Two glycoprotein standards were deglycosylated through hydrazinolysis and tagged at the optimized conditions. MS/MS data shows INLIGHT™ derivatization of glycans demonstrating successful hydrazide tagging of O-glycans for the first time.

Impact of random pointing and tracking errors on the design of coherent and incoherent optical intersatellite communication links

NASA Technical Reports Server (NTRS)

Chen, Chien-Chung; Gardner, Chester S.

1989-01-01

Given the rms transmitter pointing error and the desired probability of bit error (PBE), it can be shown that an optimal transmitter antenna gain exists which minimizes the required transmitter power. Given the rms local oscillator tracking error, an optimum receiver antenna gain can be found which optimizes the receiver performance. The impact of pointing and tracking errors on the design of direct-detection pulse-position modulation (PPM) and heterodyne noncoherent frequency-shift keying (NCFSK) systems are then analyzed in terms of constraints on the antenna size and the power penalty incurred. It is shown that in the limit of large spatial tracking errors, the advantage in receiver sensitivity for the heterodyne system is quickly offset by the smaller antenna gain and the higher power penalty due to tracking errors. In contrast, for systems with small spatial tracking errors, the heterodyne system is superior because of the higher receiver sensitivity.

[Health system sustainability from a network perspective: a proposal to optimize healthy habits and social support].

PubMed

Marqués Sánchez, Pilar; Fernández Peña, Rosario; Cabrera León, Andrés; Muñoz Doyague, María F; Llopis Cañameras, Jaime; Arias Ramos, Natalia

2013-01-01

The search of new health management formulas focused to give wide services is one of the priorities of our present health policies. Those formulas examine the optimization of the links between the main actors involved in public health, ie, users, professionals, local socio-political and corporate agents. This paper is aimed to introduce the Social Network Analysis as a method for analyzing, measuring and interpreting those connections. The knowledge of people's relationships (what is called social networks) in the field of public health is becoming increasingly important at an international level. In fact, countries such as UK, Netherlands, Italy, Australia and U.S. are looking formulas to apply this knowledge to their health departments. With this work we show the utility of the ARS on topics related to sustainability of the health system, particularly those related with health habits and social support, topics included in the 2020 health strategies that underline the importance of the collaborative aspects in networks.

Optimal resource states for local state discrimination

NASA Astrophysics Data System (ADS)

Bandyopadhyay, Somshubhro; Halder, Saronath; Nathanson, Michael

2018-02-01

We study the problem of locally distinguishing pure quantum states using shared entanglement as a resource. For a given set of locally indistinguishable states, we define a resource state to be useful if it can enhance local distinguishability and optimal if it can distinguish the states as well as global measurements and is also minimal with respect to a partial ordering defined by entanglement and dimension. We present examples of useful resources and show that an entangled state need not be useful for distinguishing a given set of states. We obtain optimal resources with explicit local protocols to distinguish multipartite Greenberger-Horne-Zeilinger and graph states and also show that a maximally entangled state is an optimal resource under one-way local operations and classical communication to distinguish any bipartite orthonormal basis which contains at least one entangled state of full Schmidt rank.

Local-in-Time Adjoint-Based Method for Optimal Control/Design Optimization of Unsteady Compressible Flows

NASA Technical Reports Server (NTRS)

Yamaleev, N. K.; Diskin, B.; Nielsen, E. J.

2009-01-01

.We study local-in-time adjoint-based methods for minimization of ow matching functionals subject to the 2-D unsteady compressible Euler equations. The key idea of the local-in-time method is to construct a very accurate approximation of the global-in-time adjoint equations and the corresponding sensitivity derivative by using only local information available on each time subinterval. In contrast to conventional time-dependent adjoint-based optimization methods which require backward-in-time integration of the adjoint equations over the entire time interval, the local-in-time method solves local adjoint equations sequentially over each time subinterval. Since each subinterval contains relatively few time steps, the storage cost of the local-in-time method is much lower than that of the global adjoint formulation, thus making the time-dependent optimization feasible for practical applications. The paper presents a detailed comparison of the local- and global-in-time adjoint-based methods for minimization of a tracking functional governed by the Euler equations describing the ow around a circular bump. Our numerical results show that the local-in-time method converges to the same optimal solution obtained with the global counterpart, while drastically reducing the memory cost as compared to the global-in-time adjoint formulation.

Spreading of cooperative behaviour across interdependent groups

NASA Astrophysics Data System (ADS)

Jiang, Luo-Luo; Perc, Matjaž

2013-08-01

Recent empirical research has shown that links between groups reinforce individuals within groups to adopt cooperative behaviour. Moreover, links between networks may induce cascading failures, competitive percolation, or contribute to efficient transportation. Here we show that there in fact exists an intermediate fraction of links between groups that is optimal for the evolution of cooperation in the prisoner's dilemma game. We consider individual groups with regular, random, and scale-free topology, and study their different combinations to reveal that an intermediate interdependence optimally facilitates the spreading of cooperative behaviour between groups. Excessive between-group links simply unify the two groups and make them act as one, while too rare between-group links preclude a useful information flow between the two groups. Interestingly, we find that between-group links are more likely to connect two cooperators than in-group links, thus supporting the conclusion that they are of paramount importance.

Streamflow Prediction based on Chaos Theory

NASA Astrophysics Data System (ADS)

Li, X.; Wang, X.; Babovic, V. M.

2015-12-01

Chaos theory is a popular method in hydrologic time series prediction. Local model (LM) based on this theory utilizes time-delay embedding to reconstruct the phase-space diagram. For this method, its efficacy is dependent on the embedding parameters, i.e. embedding dimension, time lag, and nearest neighbor number. The optimal estimation of these parameters is thus critical to the application of Local model. However, these embedding parameters are conventionally estimated using Average Mutual Information (AMI) and False Nearest Neighbors (FNN) separately. This may leads to local optimization and thus has limitation to its prediction accuracy. Considering about these limitation, this paper applies a local model combined with simulated annealing (SA) to find the global optimization of embedding parameters. It is also compared with another global optimization approach of Genetic Algorithm (GA). These proposed hybrid methods are applied in daily and monthly streamflow time series for examination. The results show that global optimization can contribute to the local model to provide more accurate prediction results compared with local optimization. The LM combined with SA shows more advantages in terms of its computational efficiency. The proposed scheme here can also be applied to other fields such as prediction of hydro-climatic time series, error correction, etc.

A local segmentation parameter optimization approach for mapping heterogeneous urban environments using VHR imagery

NASA Astrophysics Data System (ADS)

Grippa, Tais; Georganos, Stefanos; Lennert, Moritz; Vanhuysse, Sabine; Wolff, Eléonore

2017-10-01

Mapping large heterogeneous urban areas using object-based image analysis (OBIA) remains challenging, especially with respect to the segmentation process. This could be explained both by the complex arrangement of heterogeneous land-cover classes and by the high diversity of urban patterns which can be encountered throughout the scene. In this context, using a single segmentation parameter to obtain satisfying segmentation results for the whole scene can be impossible. Nonetheless, it is possible to subdivide the whole city into smaller local zones, rather homogeneous according to their urban pattern. These zones can then be used to optimize the segmentation parameter locally, instead of using the whole image or a single representative spatial subset. This paper assesses the contribution of a local approach for the optimization of segmentation parameter compared to a global approach. Ouagadougou, located in sub-Saharan Africa, is used as case studies. First, the whole scene is segmented using a single globally optimized segmentation parameter. Second, the city is subdivided into 283 local zones, homogeneous in terms of building size and building density. Each local zone is then segmented using a locally optimized segmentation parameter. Unsupervised segmentation parameter optimization (USPO), relying on an optimization function which tends to maximize both intra-object homogeneity and inter-object heterogeneity, is used to select the segmentation parameter automatically for both approaches. Finally, a land-use/land-cover classification is performed using the Random Forest (RF) classifier. The results reveal that the local approach outperforms the global one, especially by limiting confusions between buildings and their bare-soil neighbors.

Immobilization of cross-linked tannase enzyme on multiwalled carbon nanotubes and its catalytic behavior.

PubMed

Ong, Chong-Boon; Annuar, Mohamad S M

2018-02-07

Immobilization of cross-linked tannase on pristine multiwalled carbon nanotubes (MWCNT) was successfully performed. Cross-linking of tannase molecules was made through glutaraldehyde. The immobilized tannase exhibited significantly improved pH, thermal, and recycling stability. The optimal pH for both free and immobilized tannase was observed at pH 5.0 with optimal operating temperature at 30°C. Moreover, immobilized enzyme retained greater biocatalytic activities upon 10 repeated uses compared to free enzyme in solution. Immobilization of tannase was accomplished by strong hydrophobic interaction most likely between hydrophobic amino acid moieties of the glutaraldehyde-cross-linked tannase to the MWCNT.

Optimization of naltrexone diclofenac codrugs for sustained drug delivery across microneedle-treated skin.

PubMed

Ghosh, Priyanka; Lee, DoMin; Kim, Kyung Bo; Stinchcomb, Audra L

2014-01-01

The purpose of this work was to optimize the structure of codrugs for extended delivery across microneedle treated skin. Naltrexone, the model compound was linked with diclofenac, a nonspecific cyclooxygenase inhibitor to enhance the pore lifetime following microneedle treatment and develop a 7 day transdermal system for naltrexone. Four different codrugs of naltrexone and diclofenac were compared in terms of stability and solubility. Transdermal flux, permeability and skin concentration of both parent drugs and codrugs were quantified to form a structure permeability relationship. The results indicated that all codrugs bioconverted in the skin. The degree of conversion was dependent on the structure, phenol linked codrugs were less stable compared to the secondary alcohol linked structures. The flux of naltrexone across microneedle treated skin and the skin concentration of diclofenac were higher for the phenol linked codrugs. The polyethylene glycol link enhanced solubility of the codrugs, which translated into flux enhancement. The current studies indicated that formulation stability of codrugs and the flux of naltrexone can be enhanced via structure design optimization. The polyethylene glycol linked naltrexone diclofenac codrug is better suited for a 7 day drug delivery system both in terms of stability and drug delivery.

Variable Swing Optimal Parallel Links - Minimal Power, Maximal Density for Parallel Links

DTIC Science & Technology

2009-01-01

implemented; it allows controlling the transmitter current by a simple design of a differential pair with a 100 ohms termination resistor. Figure 3.4...optimization. Zuber, P., et al. 2005. 0-7695-2288-2. 21. A 36Gb/s ACCI Multi-Channel Bus using a Fully Differential Pulse Receiver. Wilson, Lei Luo

Optimal Designs for the Rasch Model

ERIC Educational Resources Information Center

Grasshoff, Ulrike; Holling, Heinz; Schwabe, Rainer

2012-01-01

In this paper, optimal designs will be derived for estimating the ability parameters of the Rasch model when difficulty parameters are known. It is well established that a design is locally D-optimal if the ability and difficulty coincide. But locally optimal designs require that the ability parameters to be estimated are known. To attenuate this…

An evidential link prediction method and link predictability based on Shannon entropy

NASA Astrophysics Data System (ADS)

Yin, Likang; Zheng, Haoyang; Bian, Tian; Deng, Yong

2017-09-01

Predicting missing links is of both theoretical value and practical interest in network science. In this paper, we empirically investigate a new link prediction method base on similarity and compare nine well-known local similarity measures on nine real networks. Most of the previous studies focus on the accuracy, however, it is crucial to consider the link predictability as an initial property of networks itself. Hence, this paper has proposed a new link prediction approach called evidential measure (EM) based on Dempster-Shafer theory. Moreover, this paper proposed a new method to measure link predictability via local information and Shannon entropy.

Artificial Intelligence-Based Models for the Optimal and Sustainable Use of Groundwater in Coastal Aquifers

NASA Astrophysics Data System (ADS)

Sreekanth, J.; Datta, Bithin

2011-07-01

Overexploitation of the coastal aquifers results in saltwater intrusion. Once saltwater intrusion occurs, it involves huge cost and long-term remediation measures to remediate these contaminated aquifers. Hence, it is important to have strategies for the sustainable use of coastal aquifers. This study develops a methodology for the optimal management of saltwater intrusion prone aquifers. A linked simulation-optimization-based management strategy is developed. The methodology uses genetic-programming-based models for simulating the aquifer processes, which is then linked to a multi-objective genetic algorithm to obtain optimal management strategies in terms of groundwater extraction from potential well locations in the aquifer.

Real-Time Distributed Embedded Oscillator Operating Frequency Monitoring

NASA Technical Reports Server (NTRS)

Pollock, Julie; Oliver, Brett; Brickner, Christopher

2012-01-01

A document discusses the utilization of embedded clocks inside of operating network data links as an auxiliary clock source to satisfy local oscillator monitoring requirements. Modem network interfaces, typically serial network links, often contain embedded clocking information of very tight precision to recover data from the link. This embedded clocking data can be utilized by the receiving device to monitor the local oscillator for tolerance to required specifications, often important in high-integrity fault-tolerant applications. A device can utilize a received embedded clock to determine if the local or the remote device is out of tolerance by using a single link. The local device can determine if it is failing, assuming a single fault model, with two or more active links. Network fabric components, containing many operational links, can potentially determine faulty remote or local devices in the presence of multiple faults. Two methods of implementation are described. In one method, a recovered clock can be directly used to monitor the local clock as a direct replacement of an external local oscillator. This scheme is consistent with a general clock monitoring function whereby clock sources are clocking two counters and compared over a fixed interval of time. In another method, overflow/underflow conditions can be used to detect clock relationships for monitoring. These network interfaces often provide clock compensation circuitry to allow data to be transferred from the received (network) clock domain to the internal clock domain. This circuit could be modified to detect overflow/underflow conditions of the buffering required and report a fast or slow receive clock, respectively.

Crystallographic orientation mapping with an electron backscattered diffraction technique in (Bi, Pb)2Sr2Ca2Cu3O10 superconductor tapes

NASA Astrophysics Data System (ADS)

Tan, T. T.; Li, S.; Oh, J. T.; Gao, W.; Liu, H. K.; Dou, S. X.

2001-02-01

It is believed that grain boundaries act as weak links in limiting the critical current density (Jc) of bulk high-Tc superconductors. The weak-link problem can be greatly reduced by elimination or minimization of large-angle grain boundaries. It has been reported that the distribution of the Jc in (Bi, Pb)2Sr2Ca2Cu3O10+x (Bi2223) superconductor tapes presents a parabolic relationship in the transverse cross section of the tapes, with the lowest currents occurring at the centre of the tapes. It was proposed that the Jc distribution is strongly dependent on the local crystallographic orientation distribution of the Bi2223 oxides. However, the local three-dimensional crystallographic orientation distribution of Bi2223 crystals in (Bi, Pb)2Sr2Ca2Cu3O10+x superconductor tapes has not yet been experimentally determined. In this work, the electron backscattered diffraction technique was employed to map the crystallographic orientation distribution, determine the misorientation of grain boundaries and also map the misorientation distribution in Bi2223 superconductor tapes. Through crystallographic orientation mapping, the relationship between the crystallographic orientation distribution, the boundary misorientation distribution and the fabrication parameters may be understood. This can be used to optimize the fabrication processes thus increasing the critical current density in Bi2223 superconductor tapes.

The Glass is Half Full and Half Empty: A population-representative twin study testing if Optimism and Pessimism are distinct systems

PubMed Central

Bates, Timothy C.

2015-01-01

Optimism and pessimism are associated with important outcomes including health and depression. Yet it is unclear if these apparent polar opposites form a single dimension or reflect two distinct systems. The extent to which personality accounts for differences in optimism/pessimism is also controversial. Here, we addressed these questions in a genetically informative sample of 852 pairs of twins. Distinct genetic influences on optimism and pessimism were found. Significant family-level environment effects also emerged, accounting for much of the negative relationship between optimism and pessimism, as well as a link to neuroticism. A general positive genetics factor exerted significant links among both personality and life-orientation traits. Both optimism bias and pessimism also showed genetic variance distinct from all effects of personality, and from each other. PMID:26561494

Optimal lightpath placement on a metropolitan-area network linked with optical CDMA local nets

NASA Astrophysics Data System (ADS)

Wang, Yih-Fuh; Huang, Jen-Fa

2008-01-01

A flexible optical metropolitan-area network (OMAN) [J.F. Huang, Y.F. Wang, C.Y. Yeh, Optimal configuration of OCDMA-based MAN with multimedia services, in: 23rd Biennial Symposium on Communications, Queen's University, Kingston, Canada, May 29-June 2, 2006, pp. 144-148] structured with OCDMA linkage is proposed to support multimedia services with multi-rate or various qualities of service. To prioritize transmissions in OCDMA, the orthogonal variable spreading factor (OVSF) codes widely used in wireless CDMA are adopted. In addition, for feasible multiplexing, unipolar OCDMA modulation [L. Nguyen, B. Aazhang, J.F. Young, All-optical CDMA with bipolar codes, IEEE Electron. Lett. 31 (6) (1995) 469-470] is used to generate the code selector of multi-rate OMAN, and a flexible fiber-grating-based system is used for the equipment on OCDMA-OVSF code. These enable an OMAN to assign suitable OVSF codes when creating different-rate lightpaths. How to optimally configure a multi-rate OMAN is a challenge because of displaced lightpaths. In this paper, a genetically modified genetic algorithm (GMGA) [L.R. Chen, Flexible fiber Bragg grating encoder/decoder for hybrid wavelength-time optical CDMA, IEEE Photon. Technol. Lett. 13 (11) (2001) 1233-1235] is used to preplan lightpaths in order to optimally configure an OMAN. To evaluate the performance of the GMGA, we compared it with different preplanning optimization algorithms. Simulation results revealed that the GMGA very efficiently solved the problem.

On computing the global time-optimal motions of robotic manipulators in the presence of obstacles

NASA Technical Reports Server (NTRS)

Shiller, Zvi; Dubowsky, Steven

1991-01-01

A method for computing the time-optimal motions of robotic manipulators is presented that considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacles. The optimization problem is reduced to a search for the time-optimal path in the n-dimensional position space. A small set of near-optimal paths is first efficiently selected from a grid, using a branch and bound search and a series of lower bound estimates on the traveling time along a given path. These paths are further optimized with a local path optimization to yield the global optimal solution. Obstacles are considered by eliminating the collision points from the tessellated space and by adding a penalty function to the motion time in the local optimization. The computational efficiency of the method stems from the reduced dimensionality of the searched spaced and from combining the grid search with a local optimization. The method is demonstrated in several examples for two- and six-degree-of-freedom manipulators with obstacles.

Get the Facts: Drinking Water and Intake

MedlinePlus

... Physical Activity Overweight & Obesity Healthy Weight Breastfeeding Micronutrient Malnutrition State and Local Programs Related Links CDC Food ... Physical Activity Overweight & Obesity Healthy Weight Breastfeeding Micronutrient Malnutrition State and Local Programs Related Links CDC Food ...

Rapid Vortex Fluidics: Continuous Flow Synthesis of Amides and Local Anesthetic Lidocaine.

PubMed

Britton, Joshua; Chalker, Justin M; Raston, Colin L

2015-07-20

Thin film flow chemistry using a vortex fluidic device (VFD) is effective in the scalable acylation of amines under shear, with the yields of the amides dramatically enhanced relative to traditional batch techniques. The optimized monophasic flow conditions are effective in ≤80 seconds at room temperature, enabling access to structurally diverse amides, functionalized amino acids and substituted ureas on multigram scales. Amide synthesis under flow was also extended to a total synthesis of local anesthetic lidocaine, with sequential reactions carried out in two serially linked VFD units. The synthesis could also be executed in a single VFD, in which the tandem reactions involve reagent delivery at different positions along the rapidly rotating tube with in situ solvent replacement, as a molecular assembly line process. This further highlights the versatility of the VFD in organic synthesis, as does the finding of a remarkably efficient debenzylation of p-methoxybenzyl amines. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Real time monitoring of water distribution in an operando fuel cell during transient states

NASA Astrophysics Data System (ADS)

Martinez, N.; Peng, Z.; Morin, A.; Porcar, L.; Gebel, G.; Lyonnard, S.

2017-10-01

The water distribution of an operating proton exchange membrane fuel cell (PEMFC) was monitored in real time by using Small Angle Neutron Scattering (SANS). The formation of liquid water was obtained simultaneously with the evolution of the water content inside the membrane. Measurements were performed when changing current with a time resolution of 10 s, providing insights on the kinetics of water management prior to the stationary phase. We confirmed that water distribution is strongly heterogeneous at the scale at of the whole Membrane Electrode Assembly. As already reported, at the local scale there is no straightforward link between the amounts of water present inside and outside the membrane. However, we show that the temporal evolutions of these two parameters are strongly correlated. In particular, the local membrane water content is nearly instantaneously correlated to the total liquid water content, whether it is located at the anode or cathode side. These results can help in optimizing 3D stationary diphasic models used to predict PEMFC water distribution.

An evaluation of methods for estimating the number of local optima in combinatorial optimization problems.

PubMed

Hernando, Leticia; Mendiburu, Alexander; Lozano, Jose A

2013-01-01

The solution of many combinatorial optimization problems is carried out by metaheuristics, which generally make use of local search algorithms. These algorithms use some kind of neighborhood structure over the search space. The performance of the algorithms strongly depends on the properties that the neighborhood imposes on the search space. One of these properties is the number of local optima. Given an instance of a combinatorial optimization problem and a neighborhood, the estimation of the number of local optima can help not only to measure the complexity of the instance, but also to choose the most convenient neighborhood to solve it. In this paper we review and evaluate several methods to estimate the number of local optima in combinatorial optimization problems. The methods reviewed not only come from the combinatorial optimization literature, but also from the statistical literature. A thorough evaluation in synthetic as well as real problems is given. We conclude by providing recommendations of methods for several scenarios.

Networked Microgrids for Self-healing Power Systems

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

Wang, Zhaoyu; Chen, Bokan; Wang, Jianhui

This paper proposes a transformative architecture for the normal operation and self-healing of networked microgrids (MGs). MGs can support and interchange electricity with each other in the proposed infrastructure. The networked MGs are connected by a physical common bus and a designed two-layer cyber communication network. The lower layer is within each MG where the energy management system (EMS) schedules the MG operation; the upper layer links a number of EMSs for global optimization and communication. In the normal operation mode, the objective is to schedule dispatchable distributed generators (DGs), energy storage systems (ESs) and controllable loads to minimize themore » operation costs and maximize the supply adequacy of each MG. When a generation deficiency or fault happens in a MG, the model switches to the self-healing mode and the local generation capacities of other MGs can be used to support the on-emergency portion of the system. A consensus algorithm is used to distribute portions of the desired power support to each individual MG in a decentralized way. The allocated portion corresponds to each MG’s local power exchange target which is used by its EMS to perform the optimal schedule. The resultant aggregated power output of networked MGs will be used to provide the requested power support. Test cases demonstrate the effectiveness of the proposed methodology.« less

[Biobanking requirements from the perspective of the clinician : Experiences in hematology and oncology].

PubMed

Koschmieder, S; Brümmendorf, T H

2018-04-05

The requirements for optimal biobanking from the point of view of the clinical partner can be highly variable. Depending on the material, processing, storage conditions, clinical data, and involvement of external partners, there will be special requirements for the participating clinician and specialist areas. What they all have in common is that the goal of any biobanking must be to improve clinical, translational, and basic research. While in the past biomaterials often had to be individually stored for each research project, modern biobanking offers decisive advantages: a comprehensive ethics vote fulfilling state-of-the-art data safety requirements, standardized processing and storage protocols, specialized biobank software for pseudonymization and localization, protection against power failures and defects of the equipment, centralized and sustainable storage, easy localization and return of samples, and their destruction or anonymization after completion of an individual project. In addition to this important pure storage function, central biobanking can provide a link to clinical data as well as the anonymous use of samples for project-independent research. Both biobank functions serve different purposes, are associated with specific requirements, and should be pursued in parallel. If successful, central biomaterial management can achieve a sustainable improvement of academic and non-academic biomedical research and the optimal use of resources. The close collaboration between clinicians and non-clinicians is a crucial prerequisite for this.

Grid sensitivity capability for large scale structures

NASA Technical Reports Server (NTRS)

Nagendra, Gopal K.; Wallerstein, David V.

1989-01-01

The considerations and the resultant approach used to implement design sensitivity capability for grids into a large scale, general purpose finite element system (MSC/NASTRAN) are presented. The design variables are grid perturbations with a rather general linking capability. Moreover, shape and sizing variables may be linked together. The design is general enough to facilitate geometric modeling techniques for generating design variable linking schemes in an easy and straightforward manner. Test cases have been run and validated by comparison with the overall finite difference method. The linking of a design sensitivity capability for shape variables in MSC/NASTRAN with an optimizer would give designers a powerful, automated tool to carry out practical optimization design of real life, complicated structures.

Design and Optimization of Ultrasonic Wireless Power Transmission Links for Millimeter-Sized Biomedical Implants.

PubMed

Meng, Miao; Kiani, Mehdi

2017-02-01

Ultrasound has been recently proposed as an alternative modality for efficient wireless power transmission (WPT) to biomedical implants with millimeter (mm) dimensions. This paper presents the theory and design methodology of ultrasonic WPT links that involve mm-sized receivers (Rx). For given load (R L ) and powering distance (d), the optimal geometries of transmitter (Tx) and Rx ultrasonic transducers, including their diameter and thickness, as well as the optimal operation frequency (f c ) are found through a recursive design procedure to maximize the power transmission efficiency (PTE). First, a range of realistic f c s is found based on the Rx thickness constrain. For a chosen f c within the range, the diameter and thickness of the Rx transducer are then swept together to maximize PTE. Then, the diameter and thickness of the Tx transducer are optimized to maximize PTE. Finally, this procedure is repeated for different f c s to find the optimal f c and its corresponding transducer geometries that maximize PTE. A design example of ultrasonic link has been presented and optimized for WPT to a 1 mm 3 implant, including a disk-shaped piezoelectric transducer on a silicon die. In simulations, a PTE of 2.11% at f c of 1.8 MHz was achieved for R L of 2.5 [Formula: see text] at [Formula: see text]. In order to validate our simulations, an ultrasonic link was optimized for a 1 mm 3 piezoelectric transducer mounted on a printed circuit board (PCB), which led to simulated and measured PTEs of 0.65% and 0.66% at f c of 1.1 MHz for R L of 2.5 [Formula: see text] at [Formula: see text], respectively.

Subcritical transition scenarios via linear and nonlinear localized optimal perturbations in plane Poiseuille flow

NASA Astrophysics Data System (ADS)

Farano, Mirko; Cherubini, Stefania; Robinet, Jean-Christophe; De Palma, Pietro

2016-12-01

Subcritical transition in plane Poiseuille flow is investigated by means of a Lagrange-multiplier direct-adjoint optimization procedure with the aim of finding localized three-dimensional perturbations optimally growing in a given time interval (target time). Space localization of these optimal perturbations (OPs) is achieved by choosing as objective function either a p-norm (with p\\gg 1) of the perturbation energy density in a linear framework; or the classical (1-norm) perturbation energy, including nonlinear effects. This work aims at analyzing the structure of linear and nonlinear localized OPs for Poiseuille flow, and comparing their transition thresholds and scenarios. The nonlinear optimization approach provides three types of solutions: a weakly nonlinear, a hairpin-like and a highly nonlinear optimal perturbation, depending on the value of the initial energy and the target time. The former shows localization only in the wall-normal direction, whereas the latter appears much more localized and breaks the spanwise symmetry found at lower target times. Both solutions show spanwise inclined vortices and large values of the streamwise component of velocity already at the initial time. On the other hand, p-norm optimal perturbations, although being strongly localized in space, keep a shape similar to linear 1-norm optimal perturbations, showing streamwise-aligned vortices characterized by low values of the streamwise velocity component. When used for initializing direct numerical simulations, in most of the cases nonlinear OPs provide the most efficient route to transition in terms of time to transition and initial energy, even when they are less localized in space than the p-norm OP. The p-norm OP follows a transition path similar to the oblique transition scenario, with slightly oscillating streaks which saturate and eventually experience secondary instability. On the other hand, the nonlinear OP rapidly forms large-amplitude bent streaks and skips the phases of streak saturation, providing a contemporary growth of all of the velocity components due to strong nonlinear coupling.

Partial discharge localization in power transformers based on the sequential quadratic programming-genetic algorithm adopting acoustic emission techniques

NASA Astrophysics Data System (ADS)

Liu, Hua-Long; Liu, Hua-Dong

2014-10-01

Partial discharge (PD) in power transformers is one of the prime reasons resulting in insulation degradation and power faults. Hence, it is of great importance to study the techniques of the detection and localization of PD in theory and practice. The detection and localization of PD employing acoustic emission (AE) techniques, as a kind of non-destructive testing, plus due to the advantages of powerful capability of locating and high precision, have been paid more and more attention. The localization algorithm is the key factor to decide the localization accuracy in AE localization of PD. Many kinds of localization algorithms exist for the PD source localization adopting AE techniques including intelligent and non-intelligent algorithms. However, the existed algorithms possess some defects such as the premature convergence phenomenon, poor local optimization ability and unsuitability for the field applications. To overcome the poor local optimization ability and easily caused premature convergence phenomenon of the fundamental genetic algorithm (GA), a new kind of improved GA is proposed, namely the sequence quadratic programming-genetic algorithm (SQP-GA). For the hybrid optimization algorithm, SQP-GA, the sequence quadratic programming (SQP) algorithm which is used as a basic operator is integrated into the fundamental GA, so the local searching ability of the fundamental GA is improved effectively and the premature convergence phenomenon is overcome. Experimental results of the numerical simulations of benchmark functions show that the hybrid optimization algorithm, SQP-GA, is better than the fundamental GA in the convergence speed and optimization precision, and the proposed algorithm in this paper has outstanding optimization effect. At the same time, the presented SQP-GA in the paper is applied to solve the ultrasonic localization problem of PD in transformers, then the ultrasonic localization method of PD in transformers based on the SQP-GA is proposed. And localization results based on the SQP-GA are compared with some algorithms such as the GA, some other intelligent and non-intelligent algorithms. The results of calculating examples both stimulated and spot experiments demonstrate that the localization method based on the SQP-GA can effectively prevent the results from getting trapped into the local optimum values, and the localization method is of great feasibility and very suitable for the field applications, and the precision of localization is enhanced, and the effectiveness of localization is ideal and satisfactory.

Paraformaldehyde fixation of neutrophils for immunolabeling of granule antigens in cryoultrasections.

PubMed

Elliott, E; Dennison, C; Fortgens, P H; Travis, J

1995-10-01

Paraformaldehyde (PFA) fixation was optimized to facilitate the immobilization and labeling of multiple granule antigens, using short fixation regimens and cryoultramicrotomy of unembedded neutrophils (PMNs). In the optimal protocol, extraction of azurophil granule antigens (especially of the abundant elastase) was obviated by manipulating the polymeric state of PFA, and hence its rate of cross-linking, by altering its concentration and pH in a multistep process. Primary fixation conditions used (4% PFA, pH 8.0, 5 min) favor fixative penetration and rapid cross-linking. Stable cross-linking of the antigen was achieved in a secondary fixation step using conditions that favor larger, more cross-linking polymeric forms of PFA (8% PFA, pH 7.2, 15 min). Immobilization of granule antigens was enhanced by flotation of cut sections on fixative (8% PFA, pH 8.0) before labeling and by using post-labeling fixation with 1% glutaraldehyde. The optimized protocol facilitated immobilization and immunolabeling of elastase, myeloperoxidase, lactoferrin, and cathepsin D in highly hydrated, unembedded PMNs.

Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin: Fragment‐Based Drug Design Facilitated by Dynamic Combinatorial Chemistry

PubMed Central

Mondal, Milon; Radeva, Nedyalka; Fanlo‐Virgós, Hugo; Otto, Sijbren; Klebe, Gerhard

2016-01-01

Abstract Fragment‐based drug design (FBDD) affords active compounds for biological targets. While there are numerous reports on FBDD by fragment growing/optimization, fragment linking has rarely been reported. Dynamic combinatorial chemistry (DCC) has become a powerful hit‐identification strategy for biological targets. We report the synergistic combination of fragment linking and DCC to identify inhibitors of the aspartic protease endothiapepsin. Based on X‐ray crystal structures of endothiapepsin in complex with fragments, we designed a library of bis‐acylhydrazones and used DCC to identify potent inhibitors. The most potent inhibitor exhibits an IC50 value of 54 nm, which represents a 240‐fold improvement in potency compared to the parent hits. Subsequent X‐ray crystallography validated the predicted binding mode, thus demonstrating the efficiency of the combination of fragment linking and DCC as a hit‐identification strategy. This approach could be applied to a range of biological targets, and holds the potential to facilitate hit‐to‐lead optimization. PMID:27400756

A parallel competitive Particle Swarm Optimization for non-linear first arrival traveltime tomography and uncertainty quantification

NASA Astrophysics Data System (ADS)

Luu, Keurfon; Noble, Mark; Gesret, Alexandrine; Belayouni, Nidhal; Roux, Pierre-François

2018-04-01

Seismic traveltime tomography is an optimization problem that requires large computational efforts. Therefore, linearized techniques are commonly used for their low computational cost. These local optimization methods are likely to get trapped in a local minimum as they critically depend on the initial model. On the other hand, global optimization methods based on MCMC are insensitive to the initial model but turn out to be computationally expensive. Particle Swarm Optimization (PSO) is a rather new global optimization approach with few tuning parameters that has shown excellent convergence rates and is straightforwardly parallelizable, allowing a good distribution of the workload. However, while it can traverse several local minima of the evaluated misfit function, classical implementation of PSO can get trapped in local minima at later iterations as particles inertia dim. We propose a Competitive PSO (CPSO) to help particles to escape from local minima with a simple implementation that improves swarm's diversity. The model space can be sampled by running the optimizer multiple times and by keeping all the models explored by the swarms in the different runs. A traveltime tomography algorithm based on CPSO is successfully applied on a real 3D data set in the context of induced seismicity.

Population-level thermal performance of a cold-water ectotherm is linked to ontogeny and local environmental heterogeneity

USGS Publications Warehouse

Hossack, Blake R.; Corn, P. Stephen; , Winsor H. Lowe; , Molly A. H. Webb; , Mariah J. Talbott; , Kevin M. Kappenman

2013-01-01

5. Our experiments with a cold-water species show that population-level performance varies across small geographic scales and is linked to local environmental heterogeneity. This variation could influence the rate and mode of species-level responses to climate change, both by facilitating local persistence in the face of change

Inactivation of Aerosolized Biological Agents using Filled Nanocomposite Materials

DTIC Science & Technology

2013-02-01

developed and optimized. The dry -heat inactivation of aerosolized spores was quantified separately from chemical effects and linked to DNA repair...Bacillus spores exposed to dry heat 67 - 79 Chapter 5. Mechanically alloyed Al-I composite materials 80 - 98 Chapter 6. Iodine release...and optimized. The dry -heat inactivation of aerosolized spores was quantified separately from chemical effects and linked to DNA repair mechanisms

Diffusion Monte Carlo approach versus adiabatic computation for local Hamiltonians

NASA Astrophysics Data System (ADS)

Bringewatt, Jacob; Dorland, William; Jordan, Stephen P.; Mink, Alan

2018-02-01

Most research regarding quantum adiabatic optimization has focused on stoquastic Hamiltonians, whose ground states can be expressed with only real non-negative amplitudes and thus for whom destructive interference is not manifest. This raises the question of whether classical Monte Carlo algorithms can efficiently simulate quantum adiabatic optimization with stoquastic Hamiltonians. Recent results have given counterexamples in which path-integral and diffusion Monte Carlo fail to do so. However, most adiabatic optimization algorithms, such as for solving MAX-k -SAT problems, use k -local Hamiltonians, whereas our previous counterexample for diffusion Monte Carlo involved n -body interactions. Here we present a 6-local counterexample which demonstrates that even for these local Hamiltonians there are cases where diffusion Monte Carlo cannot efficiently simulate quantum adiabatic optimization. Furthermore, we perform empirical testing of diffusion Monte Carlo on a standard well-studied class of permutation-symmetric tunneling problems and similarly find large advantages for quantum optimization over diffusion Monte Carlo.

Dispositional optimism and sleep quality: a test of mediating pathways

PubMed Central

Cribbet, Matthew; Kent de Grey, Robert G.; Cronan, Sierra; Trettevik, Ryan; Smith, Timothy W.

2016-01-01

Dispositional optimism has been related to beneficial influences on physical health outcomes. However, its links to global sleep quality and the psychological mediators responsible for such associations are less studied. This study thus examined if trait optimism predicted global sleep quality, and if measures of subjective well-being were statistical mediators of such links. A community sample of 175 participants (93 men, 82 women) completed measures of trait optimism, depression, and life satisfaction. Global sleep quality was assessed using the Pittsburgh Sleep Quality Index. Results indicated that trait optimism was a strong predictor of better PSQI global sleep quality. Moreover, this association was mediated by depression and life satisfaction in both single and multiple mediator models. These results highlight the importance of optimism for the restorative process of sleep, as well as the utility of multiple mediator models in testing distinct psychological pathways. PMID:27592128

Dispositional optimism and sleep quality: a test of mediating pathways.

PubMed

Uchino, Bert N; Cribbet, Matthew; de Grey, Robert G Kent; Cronan, Sierra; Trettevik, Ryan; Smith, Timothy W

2017-04-01

Dispositional optimism has been related to beneficial influences on physical health outcomes. However, its links to global sleep quality and the psychological mediators responsible for such associations are less studied. This study thus examined if trait optimism predicted global sleep quality, and if measures of subjective well-being were statistical mediators of such links. A community sample of 175 participants (93 men, 82 women) completed measures of trait optimism, depression, and life satisfaction. Global sleep quality was assessed using the Pittsburgh Sleep Quality Index. Results indicated that trait optimism was a strong predictor of better PSQI global sleep quality. Moreover, this association was mediated by depression and life satisfaction in both single and multiple mediator models. These results highlight the importance of optimism for the restorative process of sleep, as well as the utility of multiple mediator models in testing distinct psychological pathways.

Multimodal Microchannel and Nanowell-Based Microfluidic Platforms for Bioimaging

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

Geng, Tao; Smallwood, Chuck R.; Zhu, Ying

2017-03-30

Modern live-cell imaging approaches permit real-time visualization of biological processes. However, limitations for unicellular organism trapping, culturing and long-term imaging can preclude complete understanding of how such microorganisms respond to perturbations in their local environment or linking single-cell variability to whole population dynamics. We have developed microfluidic platforms to overcome prior technical bottlenecks to allow both chemostat and compartmentalized cellular growth conditions using the same device. Additionally, a nanowell-based platform enables a high throughput approach to scale up compartmentalized imaging optimized within the microfluidic device. These channel and nanowell platforms are complementary, and both provide fine control over the localmore » environment as well as the ability to add/replace media components at any experimental time point.« less

Efficient Convex Optimization for Energy-Based Acoustic Sensor Self-Localization and Source Localization in Sensor Networks.

PubMed

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Leng, Bing; Li, Shuangquan

2018-05-21

The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods.

Efficient Convex Optimization for Energy-Based Acoustic Sensor Self-Localization and Source Localization in Sensor Networks

PubMed Central

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Leng, Bing; Li, Shuangquan

2018-01-01

The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods. PMID:29883410

Design optimization of the sensor spatial arrangement in a direct magnetic field-based localization system for medical applications.

PubMed

Marechal, Luc; Shaohui Foong; Zhenglong Sun; Wood, Kristin L

2015-08-01

Motivated by the need for developing a neuronavigation system to improve efficacy of intracranial surgical procedures, a localization system using passive magnetic fields for real-time monitoring of the insertion process of an external ventricular drain (EVD) catheter is conceived and developed. This system operates on the principle of measuring the static magnetic field of a magnetic marker using an array of magnetic sensors. An artificial neural network (ANN) is directly used for solving the inverse problem of magnetic dipole localization for improved efficiency and precision. As the accuracy of localization system is highly dependent on the sensor spatial location, an optimization framework, based on understanding and classification of experimental sensor characteristics as well as prior knowledge of the general trajectory of the localization pathway, for design of such sensing assemblies is described and investigated in this paper. Both optimized and non-optimized sensor configurations were experimentally evaluated and results show superior performance from the optimized configuration. While the approach presented here utilizes ventriculostomy as an illustrative platform, it can be extended to other medical applications that require localization inside the body.

Analysis and Design of Novel Nanophotonic Structures

NASA Astrophysics Data System (ADS)

Shugayev, Roman

Nanophotonic devices hold promise to revolutionize the fields of optical communications, quantum computing and bioimaging. Designing viable solutions to these pressing problems require developing accurate models of the relevant systems. While a great deal of work has been performed in terms of developing individual models with varying levels of fidelity, some of these more complex systems still require improved links between scales to allow for accurate design and optimization within a reasonable amount of computing time. For instance, color centers in nanocrystals appear to be a promising platform for room-temperature scalable quantum information science, but questions still remain about the optimal structures to control single-photon emitter rates, coupling fidelity, and suitable scaling architectures. In this work, a method for efficient optical access and readout of nanocrystal states via magnetic transitions was demonstrated. Separately novel Mie resonant devices that guarantee on-demand enhancement of emission from the single vacancy sources were shown. To improve addressability of the crystal-based impurities, a new approach for realization of single photon electro-optical devices is also proposed in this work. Furthermore, this work on color centers in nanocrystals has been shown to be sensitive to the local refractive index environment. This allows this system to be adapted to biomedical applications, such as sensitive, minimally invasive cancer detection. In this work, a novel scheme for propagation loss-free sensing of local refractive index using nanocrystal probes with broken symmetry is carefully investigated. In conclusion, this thesis develops several novel simulation and optimization techniques that combine existing nanophotonic modeling tools into a unique multi-scale modeling tool. It has been successfully applied to nanophotonically-tuned color vacancy centers. Potential applications span optical communications, quantum information processing, and biomedical sensing.

Future ultra-speed tube-flight

NASA Astrophysics Data System (ADS)

Salter, Robert M.

1994-05-01

Future long-link, ultra-speed, surface transport systems will require electromagnetically (EM) driven and restrained vehicles operating under reduced-atmosphere in very straight tubes. Such tube-flight trains will be safe, energy conservative, pollution-free, and in a protected environment. Hypersonic (and even hyperballistic) speeds are theoretically achievable. Ultimate system choices will represent tradeoffs between amoritized capital costs (ACC) and operating costs. For example, long coasting links might employ aerodynamic lift coupled with EM restraint and drag make-up. Optimized, combined EM lift, and thrust vectors could reduce energy costs but at increased ACC. (Repulsive levitation can produce lift-over-drag l/d ratios a decade greater than aerodynamic), Alternatively, vehicle-emanated, induced-mirror fields in a conducting (aluminum sheet) road bed could reduce ACC but at substantial energy costs. Ultra-speed tube flight will demand fast-acting, high-precision sensors and computerized magnetic shimming. This same control system can maintain a magnetic 'guide way' invariant in inertial space with inertial detectors imbedded in tube structures to sense and correct for earth tremors. Ultra-speed tube flight can complete with aircraft for transit time and can provide even greater passenger convenience by single-model connections with local subways and feeder lines. Although cargo transport generally will not need to be performed at ultra speeds, such speeds may well be desirable for high throughput to optimize channel costs. Thus, a large and expensive pipeline might be replaced with small EM-driven pallets at high speeds.

Future ultra-speed tube-flight

NASA Technical Reports Server (NTRS)

Salter, Robert M.

1994-01-01

Future long-link, ultra-speed, surface transport systems will require electromagnetically (EM) driven and restrained vehicles operating under reduced-atmosphere in very straight tubes. Such tube-flight trains will be safe, energy conservative, pollution-free, and in a protected environment. Hypersonic (and even hyperballistic) speeds are theoretically achievable. Ultimate system choices will represent tradeoffs between amoritized capital costs (ACC) and operating costs. For example, long coasting links might employ aerodynamic lift coupled with EM restraint and drag make-up. Optimized, combined EM lift, and thrust vectors could reduce energy costs but at increased ACC. (Repulsive levitation can produce lift-over-drag l/d ratios a decade greater than aerodynamic), Alternatively, vehicle-emanated, induced-mirror fields in a conducting (aluminum sheet) road bed could reduce ACC but at substantial energy costs. Ultra-speed tube flight will demand fast-acting, high-precision sensors and computerized magnetic shimming. This same control system can maintain a magnetic 'guide way' invariant in inertial space with inertial detectors imbedded in tube structures to sense and correct for earth tremors. Ultra-speed tube flight can complete with aircraft for transit time and can provide even greater passenger convenience by single-model connections with local subways and feeder lines. Although cargo transport generally will not need to be performed at ultra speeds, such speeds may well be desirable for high throughput to optimize channel costs. Thus, a large and expensive pipeline might be replaced with small EM-driven pallets at high speeds.

Links between economic and financial theory in graduate health administration education.

PubMed

Pink, G H; Coyte, P C

1989-01-01

The curricula of graduate health administration programs have, historically, not articulated the theoretical links between health economics and health finance, although an understanding of these links could enhance comprehension of both disciplines. We provide a pedagogical approach that can be used to clarify these interconnections. It compares the standard neoclassical microeconomic concept of the hospital with the financial concept of the hospital, for the purpose of relating the optimal output decision in microeconomic theory to the optimal investment decision in financial theory. This approach can be taught in an advanced course in either economics or finance.

Formation, stability and crystal structure of mullite-type Al{sub 6−x}B{sub x}O{sub 9}

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

Hoffmann, K., E-mail: Kristin.Hoffmann@uni-bremen.de; Institut für Anorganische Chemie und Kristallographie, FB02, Leobener Straße/NW2, Universität Bremen, D-28359 Bremen; Hooper, T.J.N.

2016-11-15

Mullite-type Al{sub 6−x}B{sub x}O{sub 9} compounds were studied by means of powder diffraction and spectroscopic methods. The backbones of this structure are chains of edge-connected AlO{sub 6} octahedra crosslinked by AlO- and BO-polyhedra. Rietveld refinements show that the a and b lattice parameters can be well resolved, thus representing an orthorhombic metric. A continuous decrease of the lattice parameters most pronounced in c-direction indicates a solid solution for Al{sub 6−x}B{sub x}O{sub 9} with 1.09≤x≤2. A preference of boron in 3-fold coordination is confirmed by {sup 11}B MAS NMR spectroscopy and Fourier calculations based on neutron diffraction data collected at 4more » K. Distance Least Squares modeling was performed to simulate a local geometry avoiding long B-O distances linking two octahedral chains by planar BO{sub 3} groups yielding split positions for the oxygen atoms and a strong distortion in the octahedral chains. The lattice thermal expansion was calculated using the Grüneisen first-order equation of state Debye-Einstein-Anharmonicity model. - Graphical abstract: Local distortion induced by boron linking the octahedral chains. - Highlights: • Decreasing lattice parameters indicate a solid solution for Al{sub 6−x}B{sub x}O{sub 9} (1.09≤x≤2). • B-atoms induce a local distortion of neighboring AlO{sub 6} octahedra. • A preference of boron in BO{sub 3} coordination is confirmed by {sup 11}B MAS NMR spectroscopy. • An optimized structural model for Al{sub 6−x}B{sub x}O{sub 9} is presented.« less

Optimization of Formaldehyde Cross-Linking for Protein Interaction Analysis of Non-Tagged Integrin β1

PubMed Central

Klockenbusch, Cordula; Kast, Juergen

2010-01-01

Formaldehyde cross-linking of protein complexes combined with immunoprecipitation and mass spectrometry analysis is a promising technique for analysing protein-protein interactions, including those of transient nature. Here we used integrin β1 as a model to describe the application of formaldehyde cross-linking in detail, particularly focusing on the optimal parameters for cross-linking, the detection of formaldehyde cross-linked complexes, the utility of antibodies, and the identification of binding partners. Integrin β1 was found in a high molecular weight complex after formaldehyde cross-linking. Eight different anti-integrin β1 antibodies were used for pull-down experiments and no loss in precipitation efficiency after cross-linking was observed. However, two of the antibodies could not precipitate the complex, probably due to hidden epitopes. Formaldehyde cross-linked complexes, precipitated from Jurkat cells or human platelets and analyzed by mass spectrometry, were found to be composed of integrin β1, α4 and α6 or β1, α6, α2, and α5, respectively. PMID:20634879

Unequally Distributed Psychological Assets: Are There Social Disparities in Optimism, Life Satisfaction, and Positive Affect?

PubMed Central

Boehm, Julia K.; Chen, Ying; Williams, David R.; Ryff, Carol; Kubzansky, Laura D.

2015-01-01

Socioeconomic status is associated with health disparities, but underlying psychosocial mechanisms have not been fully identified. Dispositional optimism may be a psychosocial process linking socioeconomic status with health. We hypothesized that lower optimism would be associated with greater social disadvantage and poorer social mobility. We also investigated whether life satisfaction and positive affect showed similar patterns. Participants from the Midlife in the United States study self-reported their optimism, satisfaction, positive affect, and socioeconomic status (gender, race/ethnicity, education, occupational class and prestige, income). Social disparities in optimism were evident. Optimistic individuals tended to be white and highly educated, had an educated parent, belonged to higher occupational classes with more prestige, and had higher incomes. Findings were generally similar for satisfaction, but not positive affect. Greater optimism and satisfaction were also associated with educational achievement across generations. Optimism and life satisfaction are consistently linked with socioeconomic advantage and may be one conduit by which social disparities influence health. PMID:25671665

Unequally distributed psychological assets: are there social disparities in optimism, life satisfaction, and positive affect?

PubMed

Boehm, Julia K; Chen, Ying; Williams, David R; Ryff, Carol; Kubzansky, Laura D

2015-01-01

Socioeconomic status is associated with health disparities, but underlying psychosocial mechanisms have not been fully identified. Dispositional optimism may be a psychosocial process linking socioeconomic status with health. We hypothesized that lower optimism would be associated with greater social disadvantage and poorer social mobility. We also investigated whether life satisfaction and positive affect showed similar patterns. Participants from the Midlife in the United States study self-reported their optimism, satisfaction, positive affect, and socioeconomic status (gender, race/ethnicity, education, occupational class and prestige, income). Social disparities in optimism were evident. Optimistic individuals tended to be white and highly educated, had an educated parent, belonged to higher occupational classes with more prestige, and had higher incomes. Findings were generally similar for satisfaction, but not positive affect. Greater optimism and satisfaction were also associated with educational achievement across generations. Optimism and life satisfaction are consistently linked with socioeconomic advantage and may be one conduit by which social disparities influence health.

Linking EfS and Biodiversity? A UK-wide Survey of the Status of Education within Local Biodiversity Action Plans.

ERIC Educational Resources Information Center

Young, Jennifer

2001-01-01

Explores potential for developing education for sustainability (EfS) through biodiversity planning in the UK based on a survey conducted in April 1999. Concludes that biodiversity practitioners have the tools to deliver EfS through implementation of local biodiversity action plans (LBAPs), the concept allowing close links to Local Agenda 21,…

OptSSeq: High-throughput sequencing readout of growth enrichment defines optimal gene expression elements for homoethanologenesis

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

Ghosh, Indro Neil; Landick, Robert

The optimization of synthetic pathways is a central challenge in metabolic engineering. OptSSeq (Optimization by Selection and Sequencing) is one approach to this challenge. OptSSeq couples selection of optimal enzyme expression levels linked to cell growth rate with high-throughput sequencing to track enrichment of gene expression elements (promoters and ribosomebinding sites) from a combinatorial library. OptSSeq yields information on both optimal and suboptimal enzyme levels, and helps identify constraints that limit maximal product formation. Here we report a proof-of-concept implementation of OptSSeq using homoethanologenesis, a two-step pathway consisting of pyruvate decarboxylase (Pdc) and alcohol dehydrogenase (Adh) that converts pyruvate tomore » ethanol and is naturally optimized in the bacterium Zymomonas mobilis. We used OptSSeq to determine optimal gene expression elements and enzyme levels for Z. mobilis Pdc, AdhA, and AdhB expressed in Escherichia coli. By varying both expression signals and gene order, we identified an optimal solution using only Pdc and AdhB. We resolved current uncertainty about the functions of the Fe 2+-dependent AdhB and Zn 2+- dependent AdhA by showing that AdhB is preferred over AdhA for rapid growth in both E. coli and Z. mobilis. Finally, by comparing predictions of growth-linked metabolic flux to enzyme synthesis costs, we established that optimal E. coli homoethanologenesis was achieved by our best pdc-adhB expression cassette and that the remaining constraints lie in the E. coli metabolic network or inefficient Pdc or AdhB function in E. coli. Furthermore, OptSSeq is a general tool for synthetic biology to tune enzyme levels in any pathway whose optimal function can be linked to cell growth or survival.« less

OptSSeq: High-throughput sequencing readout of growth enrichment defines optimal gene expression elements for homoethanologenesis

DOE PAGES

Ghosh, Indro Neil; Landick, Robert

2016-07-16

The optimization of synthetic pathways is a central challenge in metabolic engineering. OptSSeq (Optimization by Selection and Sequencing) is one approach to this challenge. OptSSeq couples selection of optimal enzyme expression levels linked to cell growth rate with high-throughput sequencing to track enrichment of gene expression elements (promoters and ribosomebinding sites) from a combinatorial library. OptSSeq yields information on both optimal and suboptimal enzyme levels, and helps identify constraints that limit maximal product formation. Here we report a proof-of-concept implementation of OptSSeq using homoethanologenesis, a two-step pathway consisting of pyruvate decarboxylase (Pdc) and alcohol dehydrogenase (Adh) that converts pyruvate tomore » ethanol and is naturally optimized in the bacterium Zymomonas mobilis. We used OptSSeq to determine optimal gene expression elements and enzyme levels for Z. mobilis Pdc, AdhA, and AdhB expressed in Escherichia coli. By varying both expression signals and gene order, we identified an optimal solution using only Pdc and AdhB. We resolved current uncertainty about the functions of the Fe 2+-dependent AdhB and Zn 2+- dependent AdhA by showing that AdhB is preferred over AdhA for rapid growth in both E. coli and Z. mobilis. Finally, by comparing predictions of growth-linked metabolic flux to enzyme synthesis costs, we established that optimal E. coli homoethanologenesis was achieved by our best pdc-adhB expression cassette and that the remaining constraints lie in the E. coli metabolic network or inefficient Pdc or AdhB function in E. coli. Furthermore, OptSSeq is a general tool for synthetic biology to tune enzyme levels in any pathway whose optimal function can be linked to cell growth or survival.« less

Is death anxiety more closely linked with optimism or pessimism among older adults?

PubMed

Barnett, Michael D; Anderson, Ellen A; Marsden, Arthur D

2018-05-18

The purpose of this study was to investigate whether death anxiety is more closely linked with optimism or pessimism among older adults. Participants consisted of community-dwelling older adults (N = 253; 73.1% female) in the southern U.S. Both optimism and pessimism demonstrated a bivariate association with death anxiety; however, when considering optimism and pessimism together-and after controlling for age, gender, physical health, and mental health-optimism was not associated with death anxiety, while pessimism was associated with higher death anxiety. Post hoc analyses found a unique relationship between pessimism and greater fear of the unknown. Perhaps, given the inevitability of death, limiting negative expectancies is more salient to death anxiety than having positive expectancies, and pessimism may be particularly associated with existential and religious concerns. Copyright © 2018 Elsevier B.V. All rights reserved.

Optimal Design of Grid-Stiffened Composite Panels Using Global and Local Buckling Analysis

NASA Technical Reports Server (NTRS)

Ambur, Damodar R.; Jaunky, Navin; Knight, Norman F., Jr.

1996-01-01

A design strategy for optimal design of composite grid-stiffened panels subjected to global and local buckling constraints is developed using a discrete optimizer. An improved smeared stiffener theory is used for the global buckling analysis. Local buckling of skin segments is assessed using a Rayleigh-Ritz method that accounts for material anisotropy and transverse shear flexibility. The local buckling of stiffener segments is also assessed. Design variables are the axial and transverse stiffener spacing, stiffener height and thickness, skin laminate, and stiffening configuration. The design optimization process is adapted to identify the lightest-weight stiffening configuration and pattern for grid stiffened composite panels given the overall panel dimensions, design in-plane loads, material properties, and boundary conditions of the grid-stiffened panel.

Three-dimensional unstructured grid generation via incremental insertion and local optimization

NASA Technical Reports Server (NTRS)

Barth, Timothy J.; Wiltberger, N. Lyn; Gandhi, Amar S.

1992-01-01

Algorithms for the generation of 3D unstructured surface and volume grids are discussed. These algorithms are based on incremental insertion and local optimization. The present algorithms are very general and permit local grid optimization based on various measures of grid quality. This is very important; unlike the 2D Delaunay triangulation, the 3D Delaunay triangulation appears not to have a lexicographic characterization of angularity. (The Delaunay triangulation is known to minimize that maximum containment sphere, but unfortunately this is not true lexicographically). Consequently, Delaunay triangulations in three-space can result in poorly shaped tetrahedral elements. Using the present algorithms, 3D meshes can be constructed which optimize a certain angle measure, albeit locally. We also discuss the combinatorial aspects of the algorithm as well as implementational details.

Price of anarchy on heterogeneous traffic-flow networks

NASA Astrophysics Data System (ADS)

Rose, A.; O'Dea, R.; Hopcraft, K. I.

2016-09-01

The efficiency of routing traffic through a network, comprising nodes connected by links whose cost of traversal is either fixed or varies in proportion to volume of usage, can be measured by the "price of anarchy." This is the ratio of the cost incurred by agents who act to minimize their individual expenditure to the optimal cost borne by the entire system. As the total traffic load and the network variability—parameterized by the proportion of variable-cost links in the network—changes, the behaviors that the system presents can be understood with the introduction of a network of simpler structure. This is constructed from classes of nonoverlapping paths connecting source to destination nodes that are characterized by the number of variable-cost edges they contain. It is shown that localized peaks in the price of anarchy occur at critical traffic volumes at which it becomes beneficial to exploit ostensibly more expensive paths as the network becomes more congested. Simulation results verifying these findings are presented for the variation of the price of anarchy with the network's size, aspect ratio, variability, and traffic load.

Price of anarchy on heterogeneous traffic-flow networks.

PubMed

Rose, A; O'Dea, R; Hopcraft, K I

2016-09-01

The efficiency of routing traffic through a network, comprising nodes connected by links whose cost of traversal is either fixed or varies in proportion to volume of usage, can be measured by the "price of anarchy." This is the ratio of the cost incurred by agents who act to minimize their individual expenditure to the optimal cost borne by the entire system. As the total traffic load and the network variability-parameterized by the proportion of variable-cost links in the network-changes, the behaviors that the system presents can be understood with the introduction of a network of simpler structure. This is constructed from classes of nonoverlapping paths connecting source to destination nodes that are characterized by the number of variable-cost edges they contain. It is shown that localized peaks in the price of anarchy occur at critical traffic volumes at which it becomes beneficial to exploit ostensibly more expensive paths as the network becomes more congested. Simulation results verifying these findings are presented for the variation of the price of anarchy with the network's size, aspect ratio, variability, and traffic load.

A mitochondria-anchored isoform of the actin-nucleating spire protein regulates mitochondrial division.

PubMed

Manor, Uri; Bartholomew, Sadie; Golani, Gonen; Christenson, Eric; Kozlov, Michael; Higgs, Henry; Spudich, James; Lippincott-Schwartz, Jennifer

2015-08-25

Mitochondrial division, essential for survival in mammals, is enhanced by an inter-organellar process involving ER tubules encircling and constricting mitochondria. The force for constriction is thought to involve actin polymerization by the ER-anchored isoform of the formin protein inverted formin 2 (INF2). Unknown is the mechanism triggering INF2-mediated actin polymerization at ER-mitochondria intersections. We show that a novel isoform of the formin-binding, actin-nucleating protein Spire, Spire1C, localizes to mitochondria and directly links mitochondria to the actin cytoskeleton and the ER. Spire1C binds INF2 and promotes actin assembly on mitochondrial surfaces. Disrupting either Spire1C actin- or formin-binding activities reduces mitochondrial constriction and division. We propose Spire1C cooperates with INF2 to regulate actin assembly at ER-mitochondrial contacts. Simulations support this model's feasibility and demonstrate polymerizing actin filaments can induce mitochondrial constriction. Thus, Spire1C is optimally positioned to serve as a molecular hub that links mitochondria to actin and the ER for regulation of mitochondrial division.

Glassy nature and glass-to-crystal transition in the binary metallic glass CuZr

NASA Astrophysics Data System (ADS)

Wei, Zi-Yang; Shang, Cheng; Zhang, Xiao-Jie; Liu, Zhi-Pan

2017-06-01

The prediction for the stability of glassy material is a key challenge in physical science. Here, we report a theoretical framework to predict the glass stability based on stochastic surface walking global optimization and reaction pathway sampling. This is demonstrated by revealing for the first time the global potential energy surface (PES) of two systems, CuZr binary metallic glass and nonglassy pure Cu systems, and establishing the lowest energy pathways linking glassy/amorphous structures with crystalline structures. The CuZr system has a significant number of glassy structures on PES that are ˜0.045 eV /atom above the crystal structure. Two clear trends are identified from global PES in the glass-to-crystal transition of the CuZr system: (i) the local Zr-Cu coordination (nearest neighbor) increases, and (ii) the local Zr bonding environment becomes homogeneous. This allows us to introduce quantitative structural and energetics conditions to distinguish the glassy structures from the crystalline structures. Because of the local Zr-Cu exchange in the glass-to-crystal transition, a high reaction barrier (>0.048 eV /atom ) is present to separate the glassy structures and the crystals in CuZr. By contrast, the Cu system, although it does possess amorphous structures that appear at much higher energy (˜0.075 eV /atom ) with respect to the crystal structure, has very low reaction barriers for the crystallization of amorphous structures, i.e. <0.011 eV /atom . The quantitative data on PES now available from global optimization techniques deepens our understanding on the microscopic nature of glassy material and might eventually facilitate the design of stable glassy materials.

Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT

PubMed Central

2017-01-01

Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of “premature convergence,” that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In order to surmount the shortcomings of CSO, Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed in this paper. Firstly, Quantum-behaved Cat Swarm Optimization (QCSO) algorithm improves the accuracy of the CSO algorithm, because it is easy to fall into the local optimum in the later stage. Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed by introducing tent map for jumping out of local optimum in this paper. Secondly, CQCSO has been applied in the simulation of five different test functions, showing higher accuracy and less time consumption than CSO and QCSO. Finally, photovoltaic MPPT model and experimental platform are established and global maximum power point tracking control strategy is achieved by CQCSO algorithm, the effectiveness and efficiency of which have been verified by both simulation and experiment. PMID:29181020

Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT.

PubMed

Nie, Xiaohua; Wang, Wei; Nie, Haoyao

2017-01-01

Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of "premature convergence," that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In order to surmount the shortcomings of CSO, Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed in this paper. Firstly, Quantum-behaved Cat Swarm Optimization (QCSO) algorithm improves the accuracy of the CSO algorithm, because it is easy to fall into the local optimum in the later stage. Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed by introducing tent map for jumping out of local optimum in this paper. Secondly, CQCSO has been applied in the simulation of five different test functions, showing higher accuracy and less time consumption than CSO and QCSO. Finally, photovoltaic MPPT model and experimental platform are established and global maximum power point tracking control strategy is achieved by CQCSO algorithm, the effectiveness and efficiency of which have been verified by both simulation and experiment.

Physical function metric over measure: An illustration with the Patient-Reported Outcomes Measurement Information System (PROMIS) and the Functional Assessment of Cancer Therapy (FACT).

PubMed

Kaat, Aaron J; Schalet, Benjamin D; Rutsohn, Joshua; Jensen, Roxanne E; Cella, David

2018-01-01

Measuring patient-reported outcomes (PROs) is becoming an integral component of quality improvement initiatives, clinical care, and research studies in cancer, including comparative effectiveness research. However, the number of PROs limits comparability across studies. Herein, the authors attempted to link the Functional Assessment of Cancer Therapy-General Physical Well-Being (FACT-G PWB) subscale with the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function (PF) calibrated item bank. The also sought to augment a subset of the conceptually most similar FACT-G PWB items with PROMIS PF items to improve the linking. Baseline data from 5506 participants in the Measuring Your Health (MY-Health) study were used to identify the optimal items for linking FACT-G PWB with PROMIS PF. A mixed methods approach identified the optimal items for creating the 5-item FACT/PROMIS-PF5 scale. Both the linked and augmented relationships were cross-validated using the follow-up MY-Health data. A 5-item FACT-G PWB item subset was found to be optimal for linking with PROMIS PF. In addition, a 2-item subset, including only items that were conceptually very similar to the PROMIS item bank content, were augmented with 3 PROMIS PF items. This new FACT/PROMIS-PF5 provided superior score recovery. The PROMIS PF metric allows for the evaluation of the extent to which similar questionnaires can be linked and therefore expressed on the same metric. These results allow for the aggregation of existing data and provide an optimal measure for future studies wishing to use the FACT yet also report on the PROMIS PF metric. Cancer 2018;124:153-60. © 2017 American Cancer Society. © 2017 American Cancer Society.

Geometrical optimization of a local ballistic magnetic sensor

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

Kanda, Yuhsuke; Hara, Masahiro; Nomura, Tatsuya

2014-04-07

We have developed a highly sensitive local magnetic sensor by using a ballistic transport property in a two-dimensional conductor. A semiclassical simulation reveals that the sensitivity increases when the geometry of the sensor and the spatial distribution of the local field are optimized. We have also experimentally demonstrated a clear observation of a magnetization process in a permalloy dot whose size is much smaller than the size of an optimized ballistic magnetic sensor fabricated from a GaAs/AlGaAs two-dimensional electron gas.

Optimal designs based on the maximum quasi-likelihood estimator

PubMed Central

Shen, Gang; Hyun, Seung Won; Wong, Weng Kee

2016-01-01

We use optimal design theory and construct locally optimal designs based on the maximum quasi-likelihood estimator (MqLE), which is derived under less stringent conditions than those required for the MLE method. We show that the proposed locally optimal designs are asymptotically as efficient as those based on the MLE when the error distribution is from an exponential family, and they perform just as well or better than optimal designs based on any other asymptotically linear unbiased estimators such as the least square estimator (LSE). In addition, we show current algorithms for finding optimal designs can be directly used to find optimal designs based on the MqLE. As an illustrative application, we construct a variety of locally optimal designs based on the MqLE for the 4-parameter logistic (4PL) model and study their robustness properties to misspecifications in the model using asymptotic relative efficiency. The results suggest that optimal designs based on the MqLE can be easily generated and they are quite robust to mis-specification in the probability distribution of the responses. PMID:28163359

Developing and physicochemical evaluation of cross-linked electrospun gelatin-glycerol nanofibrous membranes for medical applications

NASA Astrophysics Data System (ADS)

Morsy, Reda; Hosny, Marwa; Reicha, Fikry; Elnimr, Tarek

2017-05-01

This study aims to develop optimal cross-linked electrospun gelatin-glycerol (GEL-GLY) nano-fibrous mats suitable for tissue engineering and wound dressing applications. The optimized procedure involves heating the gelatin and gelatin-glycerol solutions up to 90 °C. The electrospinning process was performed, followed by further cross-linking of electrospun films in a container containing glutaraldehyde (GTA) vapor. The results of X-ray diffraction (XRD), Fourier transformed infrared (FTIR), and Differential thermal analysis (DTA) confirmed that heating gelatin solution up to 90 °C in the presence of glycerol affected the cross-linking efficiency and interactions between GTA molecules and gelatin chains. Scanning Electron Microscope (SEM) analysis showed that GEL-GLY nano-fibrous mats with weight ratios less than or equal (12:3 w/w) exhibited a regular morphology with defect free in addition to increasing the degradation time, cross-linking efficiency, and swelling degree of electrospun gelatin/glycerol.

Optimal Linking Design for Response Model Parameters

ERIC Educational Resources Information Center

Barrett, Michelle D.; van der Linden, Wim J.

2017-01-01

Linking functions adjust for differences between identifiability restrictions used in different instances of the estimation of item response model parameters. These adjustments are necessary when results from those instances are to be compared. As linking functions are derived from estimated item response model parameters, parameter estimation…

Difficulty of distinguishing product states locally

NASA Astrophysics Data System (ADS)

Croke, Sarah; Barnett, Stephen M.

2017-01-01

Nonlocality without entanglement is a rather counterintuitive phenomenon in which information may be encoded entirely in product (unentangled) states of composite quantum systems in such a way that local measurement of the subsystems is not enough for optimal decoding. For simple examples of pure product states, the gap in performance is known to be rather small when arbitrary local strategies are allowed. Here we restrict to local strategies readily achievable with current technology: those requiring neither a quantum memory nor joint operations. We show that even for measurements on pure product states, there can be a large gap between such strategies and theoretically optimal performance. Thus, even in the absence of entanglement, physically realizable local strategies can be far from optimal for extracting quantum information.

Design of robust flow processing networks with time-programmed responses

NASA Astrophysics Data System (ADS)

Kaluza, P.; Mikhailov, A. S.

2012-04-01

Can artificially designed networks reach the levels of robustness against local damage which are comparable with those of the biochemical networks of a living cell? We consider a simple model where the flow applied to an input node propagates through the network and arrives at different times to the output nodes, thus generating a pattern of coordinated responses. By using evolutionary optimization algorithms, functional networks - with required time-programmed responses - were constructed. Then, continuing the evolution, such networks were additionally optimized for robustness against deletion of individual nodes or links. In this manner, large ensembles of functional networks with different kinds of robustness were obtained, making statistical investigations and comparison of their structural properties possible. We have found that, generally, different architectures are needed for various kinds of robustness. The differences are statistically revealed, for example, in the Laplacian spectra of the respective graphs. On the other hand, motif distributions of robust networks do not differ from those of the merely functional networks; they are found to belong to the first Alon superfamily, the same as that of the gene transcription networks of single-cell organisms.

Increased glycosylation efficiency of recombinant proteins in Escherichia coli by auto-induction.

PubMed

Ding, Ning; Yang, Chunguang; Sun, Shenxia; Han, Lichi; Ruan, Yao; Guo, Longhua; Hu, Xuejun; Zhang, Jianing

2017-03-25

Escherichia coli cells have been considered as promising hosts for producing N-glycosylated proteins since the successful production of N-glycosylated protein in E. coli with the pgl (N-linked protein glycosylation) locus from Campylobacter jejuni. However, one hurdle in producing N-glycosylated proteins in large scale using E. coli is inefficient glycan glycosylation. In this study, we developed a strategy for the production of N-glycosylated proteins with high efficiency via an optimized auto-induction method. The 10th human fibronectin type III domain (FN3) was engineered with native glycosylation sequon DFNRSK and optimized DQNAT sequon in C-terminus with flexible linker as acceptor protein models. The resulting glycosylation efficiencies were confirmed by Western blots with anti-FLAG M1 antibody. Increased efficiency of glycosylation was obtained by changing the conventional IPTG induction to auto-induction method, which increased the glycosylation efficiencies from 60% and 75% up to 90% and 100% respectively. Moreover, in the condition of inserting the glycosylation sequon in the loop of FN3 (the acceptor sequon with local structural conformation), the glycosylation efficiency was increased from 35% to 80% by our optimized auto-induction procedures. To justify the potential for general application of the optimized auto-induction method, the reconstituted lsg locus from Haemophilus influenzae and PglB from C. jejuni were utilized, and this led to 100% glycosylation efficiency. Our studies provided quantitative evidence that the optimized auto-induction method will facilitate the large-scale production of pure exogenous N-glycosylation proteins in E. coli cells. Copyright © 2017 Elsevier Inc. All rights reserved.

Transport and percolation in complex networks

NASA Astrophysics Data System (ADS)

Li, Guanliang

To design complex networks with optimal transport properties such as flow efficiency, we consider three approaches to understanding transport and percolation in complex networks. We analyze the effects of randomizing the strengths of connections, randomly adding long-range connections to regular lattices, and percolation of spatially constrained networks. Various real-world networks often have links that are differentiated in terms of their strength, intensity, or capacity. We study the distribution P(σ) of the equivalent conductance for Erdoḧs-Rényi (ER) and scale-free (SF) weighted resistor networks with N nodes, for which links are assigned with conductance σ i ≡ e-axi, where xi is a random variable with 0 < xi < 1. We find, both analytically and numerically, that P(σ) for ER networks exhibits two regimes: (i) For σ < e-apc, P(σ) is independent of N and scales as a power law P(σ) ˜ sk/a-1 . Here pc = 1/ is the critical percolation threshold of the network and is the average degree of the network. (ii) For σ > e -apc, P(σ) has strong N dependence and scales as P(σ) ˜ f(σ, apc/N1/3). Transport properties are greatly affected by the topology of networks. We investigate the transport problem in lattices with long-range connections and subject to a cost constraint, seeking design principles for optimal transport networks. Our network is built from a regular d-dimensional lattice to be improved by adding long-range connections with probability Pij ˜ r-aij , where rij is the lattice distance between site i and j. We introduce a cost constraint on the total length of the additional links and find optimal transport in the system for α = d + 1, established here for d = 1, 2 and 3 for regular lattices and df for fractals. Remarkably, this cost constraint approach remains optimal, regardless of the strategy used for transport, whether based on local or global knowledge of the network structure. To further understand the role that long-range connections play in optimizing the transport of complex systems, we study the percolation of spatially constrained networks. We now consider originally empty lattices embedded in d dimensions by adding long-range connections with the same power law probability p(r) ˜ r -α. We find that, for α ≤ d, the percolation transition belongs to the universality class of percolation in ER networks, while for α > 2d it belongs to the universality class of percolation in regular lattices (for one-dimensional linear chain, there is no percolation transition). However for d < α < 2d, the percolation properties show new intermediate behavior different from ER networks, with critical exponents that depend on α.

Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin: Fragment-Based Drug Design Facilitated by Dynamic Combinatorial Chemistry.

PubMed

Mondal, Milon; Radeva, Nedyalka; Fanlo-Virgós, Hugo; Otto, Sijbren; Klebe, Gerhard; Hirsch, Anna K H

2016-08-01

Fragment-based drug design (FBDD) affords active compounds for biological targets. While there are numerous reports on FBDD by fragment growing/optimization, fragment linking has rarely been reported. Dynamic combinatorial chemistry (DCC) has become a powerful hit-identification strategy for biological targets. We report the synergistic combination of fragment linking and DCC to identify inhibitors of the aspartic protease endothiapepsin. Based on X-ray crystal structures of endothiapepsin in complex with fragments, we designed a library of bis-acylhydrazones and used DCC to identify potent inhibitors. The most potent inhibitor exhibits an IC50 value of 54 nm, which represents a 240-fold improvement in potency compared to the parent hits. Subsequent X-ray crystallography validated the predicted binding mode, thus demonstrating the efficiency of the combination of fragment linking and DCC as a hit-identification strategy. This approach could be applied to a range of biological targets, and holds the potential to facilitate hit-to-lead optimization. © 2016 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Inductive power transmission to millimeter-sized biomedical implants using printed spiral coils.

PubMed

Ibrahim, Ahmed; Kiani, Mehdi

2016-08-01

The operation frequency (f) has been a key parameter in optimizing wireless power transmission links for biomedical implants with millimeter (mm) dimensions. This paper studies the feasibility of using printed spiral coils (PSCs) for powering mm-sized implants with high power transmission efficiency (PTE) at different fps. Compared to wire-wound coils (WWCs), using a PSC in the implant side allows batch fabrication on rigid or flexible substrates, which can also be used as a platform for integrating implant components. For powering an implant with 1 mm diameter, located 10 mm inside the tissue, the geometries of transmitter (Tx) and receiver (Rx) PSCs were optimized at different fPs of 50 MHz, 200 MHz, and 500 MHz using a commercial field solver (HFSS). In simulations, PSC- and WWC-based links achieved maximum PTE of 0.13% and 3.3%, and delivered power of 65.7 μW and 720 μW under specific absorption rate (SAR) constraints at the optimal fp of 50 MHz and 100 MHz, respectively, suggesting that the performance of the PSC-based link is significantly inferior to that of the WWC-based link.

COMPARISON OF NONLINEAR DYNAMICS OPTIMIZATION METHODS FOR APS-U

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

Sun, Y.; Borland, Michael

Many different objectives and genetic algorithms have been proposed for storage ring nonlinear dynamics performance optimization. These optimization objectives include nonlinear chromaticities and driving/detuning terms, on-momentum and off-momentum dynamic acceptance, chromatic detuning, local momentum acceptance, variation of transverse invariant, Touschek lifetime, etc. In this paper, the effectiveness of several different optimization methods and objectives are compared for the nonlinear beam dynamics optimization of the Advanced Photon Source upgrade (APS-U) lattice. The optimized solutions from these different methods are preliminarily compared in terms of the dynamic acceptance, local momentum acceptance, chromatic detuning, and other performance measures.

Design of weak link channel-cut crystals for fast QEXAFS monochromators

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

Polheim, O. von, E-mail: vonpolheim@uni-wuppertal.de; Müller, O.; Lützenkirchen-Hecht, D.

2016-07-27

A weak link channel-cut crystal, optimized for dedicated Quick EXAFS monochromators and measurements, was designed using finite element analysis. This channel-cut crystal offers precise detuning capabilities to enable suppression of higher harmonics in the virtually monochromatic beam. It was optimized to keep the detuning stable, withstanding the mechanical load, which occurs during oscillations with up to 50 Hz. First tests at DELTA (Dortmund, Germany), proved the design.

End-point controller design for an experimental two-link flexible manipulator using convex optimization

NASA Technical Reports Server (NTRS)

Oakley, Celia M.; Barratt, Craig H.

1990-01-01

Recent results in linear controller design are used to design an end-point controller for an experimental two-link flexible manipulator. A nominal 14-state linear-quadratic-Gaussian (LQG) controller was augmented with a 528-tap finite-impulse-response (FIR) filter designed using convex optimization techniques. The resulting 278-state controller produced improved end-point trajectory tracking and disturbance rejection in simulation and experimentally in real time.

Model-Based Speech Signal Coding Using Optimized Temporal Decomposition for Storage and Broadcasting Applications

NASA Astrophysics Data System (ADS)

Athaudage, Chandranath R. N.; Bradley, Alan B.; Lech, Margaret

2003-12-01

A dynamic programming-based optimization strategy for a temporal decomposition (TD) model of speech and its application to low-rate speech coding in storage and broadcasting is presented. In previous work with the spectral stability-based event localizing (SBEL) TD algorithm, the event localization was performed based on a spectral stability criterion. Although this approach gave reasonably good results, there was no assurance on the optimality of the event locations. In the present work, we have optimized the event localizing task using a dynamic programming-based optimization strategy. Simulation results show that an improved TD model accuracy can be achieved. A methodology of incorporating the optimized TD algorithm within the standard MELP speech coder for the efficient compression of speech spectral information is also presented. The performance evaluation results revealed that the proposed speech coding scheme achieves 50%-60% compression of speech spectral information with negligible degradation in the decoded speech quality.

An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy

PubMed Central

Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

2016-01-01

For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system. PMID:27835638

An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy.

PubMed

Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

2016-01-01

For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system.

Quasi-periodic patterns (QPP): large-scale dynamics in resting state fMRI that correlate with local infraslow electrical activity.

PubMed

Thompson, Garth John; Pan, Wen-Ju; Magnuson, Matthew Evan; Jaeger, Dieter; Keilholz, Shella Dawn

2014-01-01

Functional connectivity measurements from resting state blood-oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) are proving a powerful tool to probe both normal brain function and neuropsychiatric disorders. However, the neural mechanisms that coordinate these large networks are poorly understood, particularly in the context of the growing interest in network dynamics. Recent work in anesthetized rats has shown that the spontaneous BOLD fluctuations are tightly linked to infraslow local field potentials (LFPs) that are seldom recorded but comparable in frequency to the slow BOLD fluctuations. These findings support the hypothesis that long-range coordination involves low frequency neural oscillations and establishes infraslow LFPs as an excellent candidate for probing the neural underpinnings of the BOLD spatiotemporal patterns observed in both rats and humans. To further examine the link between large-scale network dynamics and infraslow LFPs, simultaneous fMRI and microelectrode recording were performed in anesthetized rats. Using an optimized filter to isolate shared components of the signals, we found that time-lagged correlation between infraslow LFPs and BOLD is comparable in spatial extent and timing to a quasi-periodic pattern (QPP) found from BOLD alone, suggesting that fMRI-measured QPPs and the infraslow LFPs share a common mechanism. As fMRI allows spatial resolution and whole brain coverage not available with electroencephalography, QPPs can be used to better understand the role of infraslow oscillations in normal brain function and neurological or psychiatric disorders. © 2013.

Quasi-periodic patterns (QPP): large-scale dynamics in resting state fMRI that correlate with local infraslow electrical activity

PubMed Central

Thompson, Garth John; Pan, Wen-Ju; Magnuson, Matthew Evan; Jaeger, Dieter; Keilholz, Shella Dawn

2013-01-01

Functional connectivity measurements from resting state blood-oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) are proving a powerful tool to probe both normal brain function and neuropsychiatric disorders. However, the neural mechanisms that coordinate these large networks are poorly understood, particularly in the context of the growing interest in network dynamics. Recent work in anesthetized rats has shown that the spontaneous BOLD fluctuations are tightly linked to infraslow local field potentials (LFPs) that are seldom recorded but comparable in frequency to the slow BOLD fluctuations. These findings support the hypothesis that long-range coordination involves low frequency neural oscillations and establishes infraslow LFPs as an excellent candidate for probing the neural underpinnings of the BOLD spatiotemporal patterns observed in both rats and humans. To further examine the link between large-scale network dynamics and infraslow LFPs, simultaneous fMRI and microelectrode recording were performed in anesthetized rats. Using an optimized filter to isolate shared components of the signals, we found that time-lagged correlation between infraslow LFPs and BOLD is comparable in spatial extent and timing to a quasi-periodic pattern (QPP) found from BOLD alone, suggesting that fMRI-measured QPPs and the infraslow LFPs share a common mechanism. As fMRI allows spatial resolution and whole brain coverage not available with electroencephalography, QPPs can be used to better understand the role of infraslow oscillations in normal brain function and neurological or psychiatric disorders. PMID:24071524

Affinity-tuning leukocyte integrin for development of safe therapeutics

NASA Astrophysics Data System (ADS)

Park, Spencer

Much attention has been given to the molecular and cellular pathways linking inflammation with cancer and the local tumor environment to identify new target molecules that could lead to improved diagnosis and treatment. Among the many molecular players involved in the complex response, central to the induction of inflammation is intercellular adhesion molecule (ICAM)-1, which is of particular interest for its highly sensitive and localized expression in response to inflammatory signals. ICAM-1, which has been implicated to play a critical role in tumor progression in various types of cancer, has also been linked to cancer metastases, where ICAM-1 facilitates the spread of metastatic cancer cells to secondary sites. This unique expression profile of ICAM-1 throughout solid tumor microenvironment makes ICAM-1 an intriguing molecular target, which holds great potential as an important diagnostic and therapeutic tool. Herein, we have engineered the ligand binding domain, or the inserted (I) domain of a leukocyte integrin, to exhibit a wide range of monovalent affinities to the natural ligand, ICAM-1. Using the resulting I domain variants, we have created drug and gene delivery nanoparticles, as well as targeted immunotherapeutics that have the ability to bind and migrate to inflammatory sites prevalent in tumors and the associated microenvironment. Through the delivery of diagnostic agents, chemotherapeutics, and immunotherapeutics, the following chapters demonstrate that the affinity enhancements achieved by directed evolution bring the affinity of I domains into the range optimal for numerous applications.

Distributed model predictive control for constrained nonlinear systems with decoupled local dynamics.

PubMed

Zhao, Meng; Ding, Baocang

2015-03-01

This paper considers the distributed model predictive control (MPC) of nonlinear large-scale systems with dynamically decoupled subsystems. According to the coupled state in the overall cost function of centralized MPC, the neighbors are confirmed and fixed for each subsystem, and the overall objective function is disassembled into each local optimization. In order to guarantee the closed-loop stability of distributed MPC algorithm, the overall compatibility constraint for centralized MPC algorithm is decomposed into each local controller. The communication between each subsystem and its neighbors is relatively low, only the current states before optimization and the optimized input variables after optimization are being transferred. For each local controller, the quasi-infinite horizon MPC algorithm is adopted, and the global closed-loop system is proven to be exponentially stable. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks

NASA Astrophysics Data System (ADS)

Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo

2015-11-01

Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Unveiling physical principles, building theories and suggesting physical models to predict bipartite links such as product-consumer connections in recommendation systems or drug-target interactions in molecular networks can provide priceless information to improve e-commerce or to accelerate pharmaceutical research. The prediction of nonobserved connections starting from those already present in the topology of a network is known as the link-prediction problem. It represents an important subject both in many-body interaction theory in physics and in new algorithms for applied tools in computer science. The rationale is that the existing connectivity structure of a network can suggest where new connections can appear with higher likelihood in an evolving network, or where nonobserved connections are missing in a partially known network. Surprisingly, current complex network theory presents a theoretical bottle-neck: a general framework for local-based link prediction directly in the bipartite domain is missing. Here, we overcome this theoretical obstacle and present a formal definition of common neighbour index and local-community-paradigm (LCP) for bipartite networks. As a consequence, we are able to introduce the first node-neighbourhood-based and LCP-based models for topological link prediction that utilize the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks because they exploit local physical driving-forces that participate in the formation and organization of many real-world bipartite networks. Furthermore, we present a local-based formalism that allows to intuitively implement neighbourhood-based link prediction entirely in the bipartite domain.

Adaptive Power Control for Space Communications

NASA Technical Reports Server (NTRS)

Thompson, Willie L., II; Israel, David J.

2008-01-01

This paper investigates the implementation of power control techniques for crosslinks communications during a rendezvous scenario of the Crew Exploration Vehicle (CEV) and the Lunar Surface Access Module (LSAM). During the rendezvous, NASA requires that the CEV supports two communication links: space-to-ground and crosslink simultaneously. The crosslink will generate excess interference to the space-to-ground link as the distances between the two vehicles decreases, if the output power is fixed and optimized for the worst-case link analysis at the maximum distance range. As a result, power control is required to maintain the optimal power level for the crosslink without interfering with the space-to-ground link. A proof-of-concept will be described and implemented with Goddard Space Flight Center (GSFC) Communications, Standard, and Technology Lab (CSTL).

From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks

PubMed Central

Cannistraci, Carlo Vittorio; Alanis-Lobato, Gregorio; Ravasi, Timothy

2013-01-01

Growth and remodelling impact the network topology of complex systems, yet a general theory explaining how new links arise between existing nodes has been lacking, and little is known about the topological properties that facilitate link-prediction. Here we investigate the extent to which the connectivity evolution of a network might be predicted by mere topological features. We show how a link/community-based strategy triggers substantial prediction improvements because it accounts for the singular topology of several real networks organised in multiple local communities - a tendency here named local-community-paradigm (LCP). We observe that LCP networks are mainly formed by weak interactions and characterise heterogeneous and dynamic systems that use self-organisation as a major adaptation strategy. These systems seem designed for global delivery of information and processing via multiple local modules. Conversely, non-LCP networks have steady architectures formed by strong interactions, and seem designed for systems in which information/energy storage is crucial. PMID:23563395

From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks.

PubMed

Cannistraci, Carlo Vittorio; Alanis-Lobato, Gregorio; Ravasi, Timothy

2013-01-01

Growth and remodelling impact the network topology of complex systems, yet a general theory explaining how new links arise between existing nodes has been lacking, and little is known about the topological properties that facilitate link-prediction. Here we investigate the extent to which the connectivity evolution of a network might be predicted by mere topological features. We show how a link/community-based strategy triggers substantial prediction improvements because it accounts for the singular topology of several real networks organised in multiple local communities - a tendency here named local-community-paradigm (LCP). We observe that LCP networks are mainly formed by weak interactions and characterise heterogeneous and dynamic systems that use self-organisation as a major adaptation strategy. These systems seem designed for global delivery of information and processing via multiple local modules. Conversely, non-LCP networks have steady architectures formed by strong interactions, and seem designed for systems in which information/energy storage is crucial.

Optimal design of geodesically stiffened composite cylindrical shells

NASA Technical Reports Server (NTRS)

Gendron, G.; Guerdal, Z.

1992-01-01

An optimization system based on the finite element code Computations Structural Mechanics (CSM) Testbed and the optimization program, Automated Design Synthesis (ADS), is described. The optimization system can be used to obtain minimum-weight designs of composite stiffened structures. Ply thickness, ply orientations, and stiffener heights can be used as design variables. Buckling, displacement, and material failure constraints can be imposed on the design. The system is used to conduct a design study of geodesically stiffened shells. For comparison purposes, optimal designs of unstiffened shells and shells stiffened by rings and stingers are also obtained. Trends in the design of geodesically stiffened shells are identified. An approach to include local stress concentrations during the design optimization process is then presented. The method is based on a global/local analysis technique. It employs spline interpolation functions to determine displacements and rotations from a global model which are used as 'boundary conditions' for the local model. The organization of the strategy in the context of an optimization process is described. The method is validated with an example.

Workshop 2b (synthesis): linking drainage basin management to local action plans and national security--theory and practice in eastern European countries.

PubMed

Söderbaum, P; Tropp, H

2004-01-01

Efforts to link and balance national water policies, local water action and national security issues are discussed. There needs to be greater clarity of water roles, rights and responsibilities among national stakeholders as well as between states. In some cases, insufficient attention has been paid to local concerns and, in balancing national and local actions, it is necessary to address decentralization in the context of a transboundary state. There is a strong need for enhanced stakeholder participation in the formulation and implementation of national and local water management plans.

A Novel Consensus-Based Particle Swarm Optimization-Assisted Trust-Tech Methodology for Large-Scale Global Optimization.

PubMed

Zhang, Yong-Feng; Chiang, Hsiao-Dong

2017-09-01

A novel three-stage methodology, termed the "consensus-based particle swarm optimization (PSO)-assisted Trust-Tech methodology," to find global optimal solutions for nonlinear optimization problems is presented. It is composed of Trust-Tech methods, consensus-based PSO, and local optimization methods that are integrated to compute a set of high-quality local optimal solutions that can contain the global optimal solution. The proposed methodology compares very favorably with several recently developed PSO algorithms based on a set of small-dimension benchmark optimization problems and 20 large-dimension test functions from the CEC 2010 competition. The analytical basis for the proposed methodology is also provided. Experimental results demonstrate that the proposed methodology can rapidly obtain high-quality optimal solutions that can contain the global optimal solution. The scalability of the proposed methodology is promising.

Link establishment criterion and topology optimization for hybrid GPS satellite communications with laser crosslinks

NASA Astrophysics Data System (ADS)

Li, Lun; Wei, Sixiao; Tian, Xin; Hsieh, Li-Tse; Chen, Zhijiang; Pham, Khanh; Lyke, James; Chen, Genshe

2018-05-01

In the current global positioning system (GPS), the reliability of information transmissions can be enhanced with the aid of inter-satellite links (ISLs) or crosslinks between satellites. Instead of only using conventional radio frequency (RF) crosslinks, the laser crosslinks provide an option to significantly increase the data throughput. The connectivity and robustness of ISL are needed for analysis, especially for GPS constellations with laser crosslinks. In this paper, we first propose a hybrid GPS communication architecture in which uplinks and downlinks are established via RF signals and crosslinks are established via laser links. Then, we design an optical crosslink assignment criteria considering the practical optical communication factors such as optical line- of-sight (LOS) range, link distance, and angular velocity, etc. After that, to further improve the rationality of establishing crosslinks, a topology control algorithm is formulated to optimize GPS crosslink networks at both physical and network layers. The RF transmission features for uplink and downlink and optical transmission features for crosslinks are taken into account as constraints for the optimization problem. Finally, the proposed link establishment criteria are implemented for GPS communication with optical crosslinks. The designs of this paper provide a potential crosslink establishment and topology control algorithm for the next generation GPS.

Medial-based deformable models in nonconvex shape-spaces for medical image segmentation.

PubMed

McIntosh, Chris; Hamarneh, Ghassan

2012-01-01

We explore the application of genetic algorithms (GA) to deformable models through the proposition of a novel method for medical image segmentation that combines GA with nonconvex, localized, medial-based shape statistics. We replace the more typical gradient descent optimizer used in deformable models with GA, and the convex, implicit, global shape statistics with nonconvex, explicit, localized ones. Specifically, we propose GA to reduce typical deformable model weaknesses pertaining to model initialization, pose estimation and local minima, through the simultaneous evolution of a large number of models. Furthermore, we constrain the evolution, and thus reduce the size of the search-space, by using statistically-based deformable models whose deformations are intuitive (stretch, bulge, bend) and are driven in terms of localized principal modes of variation, instead of modes of variation across the entire shape that often fail to capture localized shape changes. Although GA are not guaranteed to achieve the global optima, our method compares favorably to the prevalent optimization techniques, convex/nonconvex gradient-based optimizers and to globally optimal graph-theoretic combinatorial optimization techniques, when applied to the task of corpus callosum segmentation in 50 mid-sagittal brain magnetic resonance images.

Measures of health sciences journal use: a comparison of vendor, link-resolver, and local citation statistics.

PubMed

De Groote, Sandra L; Blecic, Deborah D; Martin, Kristin

2013-04-01

Libraries require efficient and reliable methods to assess journal use. Vendors provide complete counts of articles retrieved from their platforms. However, if a journal is available on multiple platforms, several sets of statistics must be merged. Link-resolver reports merge data from all platforms into one report but only record partial use because users can access library subscriptions from other paths. Citation data are limited to publication use. Vendor, link-resolver, and local citation data were examined to determine correlation. Because link-resolver statistics are easy to obtain, the study library especially wanted to know if they correlate highly with the other measures. Vendor, link-resolver, and local citation statistics for the study institution were gathered for health sciences journals. Spearman rank-order correlation coefficients were calculated. There was a high positive correlation between all three data sets, with vendor data commonly showing the highest use. However, a small percentage of titles showed anomalous results. Link-resolver data correlate well with vendor and citation data, but due to anomalies, low link-resolver data would best be used to suggest titles for further evaluation using vendor data. Citation data may not be needed as it correlates highly with other measures.

Biogenesis of influenza a virus hemagglutinin cross-protective stem epitopes.

PubMed

Magadán, Javier G; Altman, Meghan O; Ince, William L; Hickman, Heather D; Stevens, James; Chevalier, Aaron; Baker, David; Wilson, Patrick C; Ahmed, Rafi; Bennink, Jack R; Yewdell, Jonathan W

2014-06-01

Antigenic variation in the globular domain of influenza A virus (IAV) hemagglutinin (HA) precludes effective immunity to this major human pathogen. Although the HA stem is highly conserved between influenza virus strains, HA stem-reactive antibodies (StRAbs) were long considered biologically inert. It is now clear, however, that StRAbs reduce viral replication in animal models and protect against pathogenicity and death, supporting the potential of HA stem-based immunogens as drift-resistant vaccines. Optimally designing StRAb-inducing immunogens and understanding StRAb effector functions require thorough comprehension of HA stem structure and antigenicity. Here, we study the biogenesis of HA stem epitopes recognized in cells infected with various drifted IAV H1N1 strains using mouse and human StRAbs. Using a novel immunofluorescence (IF)-based assay, we find that human StRAbs bind monomeric HA in the endoplasmic reticulum (ER) and trimerized HA in the Golgi complex (GC) with similar high avidity, potentially good news for producing effective monomeric HA stem immunogens. Though HA stem epitopes are nestled among several N-linked oligosaccharides, glycosylation is not required for full antigenicity. Rather, as N-linked glycans increase in size during intracellular transport of HA through the GC, StRAb binding becomes temperature-sensitive, binding poorly to HA at 4°C and well at 37°C. A de novo designed, 65-residue protein binds the mature HA stem independently of temperature, consistent with a lack of N-linked oligosaccharide steric hindrance due to its small size. Likewise, StRAbs bind recombinant HA carrying simple N-linked glycans in a temperature-independent manner. Chemical cross-linking experiments show that N-linked oligosaccharides likely influence StRAb binding by direct local effects rather than by globally modifying the conformational flexibility of HA. Our findings indicate that StRAb binding to HA is precarious, raising the possibility that sufficient immune pressure on the HA stem region could select for viral escape mutants with increased steric hindrance from N-linked glycans.

Optimal inverse functions created via population-based optimization.

PubMed

Jennings, Alan L; Ordóñez, Raúl

2014-06-01

Finding optimal inputs for a multiple-input, single-output system is taxing for a system operator. Population-based optimization is used to create sets of functions that produce a locally optimal input based on a desired output. An operator or higher level planner could use one of the functions in real time. For the optimization, each agent in the population uses the cost and output gradients to take steps lowering the cost while maintaining their current output. When an agent reaches an optimal input for its current output, additional agents are generated in the output gradient directions. The new agents then settle to the local optima for the new output values. The set of associated optimal points forms an inverse function, via spline interpolation, from a desired output to an optimal input. In this manner, multiple locally optimal functions can be created. These functions are naturally clustered in input and output spaces allowing for a continuous inverse function. The operator selects the best cluster over the anticipated range of desired outputs and adjusts the set point (desired output) while maintaining optimality. This reduces the demand from controlling multiple inputs, to controlling a single set point with no loss in performance. Results are demonstrated on a sample set of functions and on a robot control problem.

Health-related quality of life, optimism, and coping strategies in persons suffering from localized scleroderma.

PubMed

Szramka-Pawlak, B; Dańczak-Pazdrowska, A; Rzepa, T; Szewczyk, A; Sadowska-Przytocka, A; Żaba, R

2013-01-01

The clinical course of localized scleroderma may consist of bodily deformations, and bodily functions may also be affected. Additionally, the secondary lesions, such as discoloration, contractures, and atrophy, are unlikely to regress. The aforementioned symptoms and functional disturbances may decrease one's quality of life (QoL). Although much has been mentioned in the medical literature regarding QoL in persons suffering from dermatologic diseases, no data specifically describing patients with localized scleroderma exist. The aim of the study was to explore QoL in localized scleroderma patients and to examine their coping strategies in regard to optimism and QoL. The study included 41 patients with localized scleroderma. QoL was evaluated using the SKINDEX questionnaire, and levels of dispositional optimism were assessed using the Life Orientation Test-Revised. In addition, individual coping strategy was determined using the Mini-MAC scale and physical condition was assessed using the Localized Scleroderma Severity Index. The mean QoL score amounted to 51.10 points, with mean scores for individual components as follows: symptoms = 13.49 points, emotions = 21.29 points, and functioning = 16.32 points. A relationship was detected between QoL and the level of dispositional optimism as well as with coping strategies known as anxious preoccupation and helplessness-hopelessness. Higher levels of optimism predicted a higher general QoL. In turn, greater intensity of anxious preoccupied and helpless-hopeless behaviors predicted a lower QoL. Based on these results, it may be stated that localized scleroderma patients have a relatively high QoL, which is accompanied by optimism as well as a lower frequency of behaviors typical of emotion-focused coping strategies.

Research on particle swarm optimization algorithm based on optimal movement probability

NASA Astrophysics Data System (ADS)

Ma, Jianhong; Zhang, Han; He, Baofeng

2017-01-01

The particle swarm optimization algorithm to improve the control precision, and has great application value training neural network and fuzzy system control fields etc.The traditional particle swarm algorithm is used for the training of feed forward neural networks,the search efficiency is low, and easy to fall into local convergence.An improved particle swarm optimization algorithm is proposed based on error back propagation gradient descent. Particle swarm optimization for Solving Least Squares Problems to meme group, the particles in the fitness ranking, optimization problem of the overall consideration, the error back propagation gradient descent training BP neural network, particle to update the velocity and position according to their individual optimal and global optimization, make the particles more to the social optimal learning and less to its optimal learning, it can avoid the particles fall into local optimum, by using gradient information can accelerate the PSO local search ability, improve the multi beam particle swarm depth zero less trajectory information search efficiency, the realization of improved particle swarm optimization algorithm. Simulation results show that the algorithm in the initial stage of rapid convergence to the global optimal solution can be near to the global optimal solution and keep close to the trend, the algorithm has faster convergence speed and search performance in the same running time, it can improve the convergence speed of the algorithm, especially the later search efficiency.

Free-form Airfoil Shape Optimization Under Uncertainty Using Maximum Expected Value and Second-order Second-moment Strategies

NASA Technical Reports Server (NTRS)

Huyse, Luc; Bushnell, Dennis M. (Technical Monitor)

2001-01-01

Free-form shape optimization of airfoils poses unexpected difficulties. Practical experience has indicated that a deterministic optimization for discrete operating conditions can result in dramatically inferior performance when the actual operating conditions are different from the - somewhat arbitrary - design values used for the optimization. Extensions to multi-point optimization have proven unable to adequately remedy this problem of "localized optimization" near the sampled operating conditions. This paper presents an intrinsically statistical approach and demonstrates how the shortcomings of multi-point optimization with respect to "localized optimization" can be overcome. The practical examples also reveal how the relative likelihood of each of the operating conditions is automatically taken into consideration during the optimization process. This is a key advantage over the use of multipoint methods.

Efficient Multi-Stage Time Marching for Viscous Flows via Local Preconditioning

NASA Technical Reports Server (NTRS)

Kleb, William L.; Wood, William A.; vanLeer, Bram

1999-01-01

A new method has been developed to accelerate the convergence of explicit time-marching, laminar, Navier-Stokes codes through the combination of local preconditioning and multi-stage time marching optimization. Local preconditioning is a technique to modify the time-dependent equations so that all information moves or decays at nearly the same rate, thus relieving the stiffness for a system of equations. Multi-stage time marching can be optimized by modifying its coefficients to account for the presence of viscous terms, allowing larger time steps. We show it is possible to optimize the time marching scheme for a wide range of cell Reynolds numbers for the scalar advection-diffusion equation, and local preconditioning allows this optimization to be applied to the Navier-Stokes equations. Convergence acceleration of the new method is demonstrated through numerical experiments with circular advection and laminar boundary-layer flow over a flat plate.

Super-resolution links vinculin localization to function in focal adhesions.

PubMed

Giannone, Grégory

2015-07-01

Integrin-based focal adhesions integrate biochemical and biomechanical signals from the extracellular matrix and the actin cytoskeleton. The combination of three-dimensional super-resolution imaging and loss- or gain-of-function protein mutants now links the nanoscale dynamic localization of proteins to their activation and function within focal adhesions.

Dynamic social networks facilitate cooperation in the N-player Prisoner’s Dilemma

NASA Astrophysics Data System (ADS)

Rezaei, Golriz; Kirley, Michael

2012-12-01

Understanding how cooperative behaviour evolves in network communities, where the individual members interact via social dilemma games, is an on-going challenge. In this paper, we introduce a social network based model to investigate the evolution of cooperation in the N-player Prisoner’s Dilemma game. As such, this work complements previous studies focused on multi-player social dilemma games and endogenous networks. Agents in our model, employ different game-playing strategies reflecting varying cognitive capacities. When an agent plays cooperatively, a social link is formed with each of the other N-1 group members. Subsequent cooperative actions reinforce this link. However, when an agent defects, the links in the social network are broken. Computational simulations across a range of parameter settings are used to examine different scenarios: varying population and group sizes; the group formation process (or partner selection); and agent decision-making strategies under varying dilemma constraints (cost-to-benefit ratios), including a “discriminator” strategy where the action is based on a function of the weighted links within an agent’s social network. The simulation results show that the proposed social network model is able to evolve and maintain cooperation. As expected, as the value of N increases the equilibrium proportion of cooperators in the population decreases. In addition, this outcome is dependent on the dilemma constraint (cost-to-benefit ratio). However, in some circumstances the dynamic social network plays an increasingly important role in promoting and sustaining cooperation, especially when the agents adopt the discriminator strategy. The adjustment of social links results in the formation of communities of “like-minded” agents. Subsequently, this local optimal behaviour promotes the evolution of cooperative behaviour at the system level.

Localization of PDZD7 to the stereocilia ankle-link associates this scaffolding protein with the Usher syndrome protein network.

PubMed

Grati, M'hamed; Shin, Jung-Bum; Weston, Michael D; Green, James; Bhat, Manzoor A; Gillespie, Peter G; Kachar, Bechara

2012-10-10

Usher syndrome is the leading cause of genetic deaf-blindness. Monoallelic mutations in PDZD7 increase the severity of Usher type II syndrome caused by mutations in USH2A and GPR98, which respectively encode usherin and GPR98. PDZ domain-containing 7 protein (PDZD7) is a paralog of the scaffolding proteins harmonin and whirlin, which are implicated in Usher type 1 and type 2 syndromes. While usherin and GPR98 have been reported to form hair cell stereocilia ankle-links, harmonin localizes to the stereocilia upper tip-link density and whirlin localizes to both tip and ankle-link regions. Here, we used mass spectrometry to show that PDZD7 is expressed in chick stereocilia at a comparable molecular abundance to GPR98. We also show by immunofluorescence and by overexpression of tagged proteins in rat and mouse hair cells that PDZD7 localizes to the ankle-link region, overlapping with usherin, whirlin, and GPR98. Finally, we show in LLC-PK1 cells that cytosolic domains of usherin and GPR98 can bind to both whirlin and PDZD7. These observations are consistent with PDZD7 being a modifier and candidate gene for USH2, and suggest that PDZD7 is a second scaffolding component of the ankle-link complex.

Capillary wave Hamiltonian for the Landau-Ginzburg-Wilson density functional

NASA Astrophysics Data System (ADS)

Chacón, Enrique; Tarazona, Pedro

2016-06-01

We study the link between the density functional (DF) formalism and the capillary wave theory (CWT) for liquid surfaces, focused on the Landau-Ginzburg-Wilson (LGW) model, or square gradient DF expansion, with a symmetric double parabola free energy, which has been extensively used in theoretical studies of this problem. We show the equivalence between the non-local DF results of Parry and coworkers and the direct evaluation of the mean square fluctuations of the intrinsic surface, as is done in the intrinsic sampling method for computer simulations. The definition of effective wave-vector dependent surface tensions is reviewed and we obtain new proposals for the LGW model. The surface weight proposed by Blokhuis and the surface mode analysis proposed by Stecki provide consistent and optimal effective definitions for the extended CWT Hamiltonian associated to the DF model. A non-local, or coarse-grained, definition of the intrinsic surface provides the missing element to get the mesoscopic surface Hamiltonian from the molecular DF description, as had been proposed a long time ago by Dietrich and coworkers.

Capillary wave Hamiltonian for the Landau-Ginzburg-Wilson density functional.

PubMed

Chacón, Enrique; Tarazona, Pedro

2016-06-22

We study the link between the density functional (DF) formalism and the capillary wave theory (CWT) for liquid surfaces, focused on the Landau-Ginzburg-Wilson (LGW) model, or square gradient DF expansion, with a symmetric double parabola free energy, which has been extensively used in theoretical studies of this problem. We show the equivalence between the non-local DF results of Parry and coworkers and the direct evaluation of the mean square fluctuations of the intrinsic surface, as is done in the intrinsic sampling method for computer simulations. The definition of effective wave-vector dependent surface tensions is reviewed and we obtain new proposals for the LGW model. The surface weight proposed by Blokhuis and the surface mode analysis proposed by Stecki provide consistent and optimal effective definitions for the extended CWT Hamiltonian associated to the DF model. A non-local, or coarse-grained, definition of the intrinsic surface provides the missing element to get the mesoscopic surface Hamiltonian from the molecular DF description, as had been proposed a long time ago by Dietrich and coworkers.

[Cognitive advantages of the third age: a neural network model of brain aging].

PubMed

Karpenko, M P; Kachalova, L M; Budilova, E V; Terekhin, A T

2009-01-01

We consider a neural network model of age-related cognitive changes in aging brain based on Hopfield network with a sigmoid function of neuron activation. Age is included in the activation function as a parameter in the form of exponential rate denominator, which makes it possible to take into account the weakening of interneuronal links really observed in the aging brain. Analysis of properties of the Lyapunov function associated with the network shows that, with increasing parameter of age, its relief becomes smoother and the number of local minima (network attractors) decreases. As a result, the network gets less frequently stuck in the nearest local minima of the Lyapunov function and reaches a global minimum corresponding to the most effective solution of the cognitive task. It is reasonable to assume that similar changes really occur in the aging brain. Phenomenologically, these changes can be manifested as emergence in aged people of a cognitive quality such as wisdom i.e. ability to find optimal decisions in difficult controversial situations, to distract from secondary aspects and to see the problem as a whole.

Hybrid cooperative spectrum sharing for cognitive radio networks: A contract-based approach

NASA Astrophysics Data System (ADS)

Zhang, Songwei; Mu, Xiaomin; Wang, Ning; Zhang, Dalong; Han, Gangtao

2018-06-01

In order to improve the spectral efficiency, a contract-based hybrid cooperative spectrum sharing approach is proposed in this paper, in which multiple primary users (PUs) and multiple secondary users (SUs) share the primary channels in a hybrid manner. Specifically, the SUs switch their transmission mode between underlay and overlay based on the second-order statistics of the primary links. The average transmission rates of PUs and SUs are analyzed for the two transmission modes, and an optimization problem is formulated to maximize the utility of PUs under the constraint that the utility of SUs is nonnegative, which is further solved by a contract-based approach in global statistical channel statistical information (S-CSI) scenarios and local S-CSI scenarios, individually. Numerical results show that the average transmission rate of the PUs is significantly improved by using the proposed method in both of the two scenarios, and in the meantime, the SUs can achieve a good average rate, especially while the SUs have the same number of the PUs in the local S-CSI scenarios.

Formulation analysis and computation of an optimization-based local-to-nonlocal coupling method.

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

D'Elia, Marta; Bochev, Pavel Blagoveston

2017-01-01

In this paper, we present an optimization-based coupling method for local and nonlocal continuum models. Our approach couches the coupling of the models into a control problem where the states are the solutions of the nonlocal and local equations, the objective is to minimize their mismatch on the overlap of the local and nonlocal problem domains, and the virtual controls are the nonlocal volume constraint and the local boundary condition. We present the method in the context of Local-to-Nonlocal di usion coupling. Numerical examples illustrate the theoretical properties of the approach.

Power optimal single-axis articulating strategies

NASA Technical Reports Server (NTRS)

Kumar, Renjith R.; Heck, Michael L.

1991-01-01

Power optimal single axis articulating PV array motion for Space Station Freedom is investigated. The motivation is to eliminate one of the articular joints to reduce Station costs. Optimal (maximum power) Beta tracking is addressed for local vertical local horizontal (LVLH) and non-LVLH attitudes. Effects of intra-array shadowing are also presented. Maximum power availability while Beta tracking is compared to full sun tracking and optimal alpha tracking. The results are quantified in orbital and yearly minimum, maximum, and average values of power availability.

Two-UAV Intersection Localization System Based on the Airborne Optoelectronic Platform

PubMed Central

Bai, Guanbing; Liu, Jinghong; Song, Yueming; Zuo, Yujia

2017-01-01

To address the limitation of the existing UAV (unmanned aerial vehicles) photoelectric localization method used for moving objects, this paper proposes an improved two-UAV intersection localization system based on airborne optoelectronic platforms by using the crossed-angle localization method of photoelectric theodolites for reference. This paper introduces the makeup and operating principle of intersection localization system, creates auxiliary coordinate systems, transforms the LOS (line of sight, from the UAV to the target) vectors into homogeneous coordinates, and establishes a two-UAV intersection localization model. In this paper, the influence of the positional relationship between UAVs and the target on localization accuracy has been studied in detail to obtain an ideal measuring position and the optimal localization position where the optimal intersection angle is 72.6318°. The result shows that, given the optimal position, the localization root mean square error (RMS) will be 25.0235 m when the target is 5 km away from UAV baselines. Finally, the influence of modified adaptive Kalman filtering on localization results is analyzed, and an appropriate filtering model is established to reduce the localization RMS error to 15.7983 m. Finally, An outfield experiment was carried out and obtained the optimal results: σB=1.63×10−4 (°), σL=1.35×10−4 (°), σH=15.8 (m), σsum=27.6 (m), where σB represents the longitude error, σL represents the latitude error, σH represents the altitude error, and σsum represents the error radius. PMID:28067814

Two-UAV Intersection Localization System Based on the Airborne Optoelectronic Platform.

PubMed

Bai, Guanbing; Liu, Jinghong; Song, Yueming; Zuo, Yujia

2017-01-06

To address the limitation of the existing UAV (unmanned aerial vehicles) photoelectric localization method used for moving objects, this paper proposes an improved two-UAV intersection localization system based on airborne optoelectronic platforms by using the crossed-angle localization method of photoelectric theodolites for reference. This paper introduces the makeup and operating principle of intersection localization system, creates auxiliary coordinate systems, transforms the LOS (line of sight, from the UAV to the target) vectors into homogeneous coordinates, and establishes a two-UAV intersection localization model. In this paper, the influence of the positional relationship between UAVs and the target on localization accuracy has been studied in detail to obtain an ideal measuring position and the optimal localization position where the optimal intersection angle is 72.6318°. The result shows that, given the optimal position, the localization root mean square error (RMS) will be 25.0235 m when the target is 5 km away from UAV baselines. Finally, the influence of modified adaptive Kalman filtering on localization results is analyzed, and an appropriate filtering model is established to reduce the localization RMS error to 15.7983 m. Finally, An outfield experiment was carried out and obtained the optimal results: σ B = 1.63 × 10 - 4 ( ° ) , σ L = 1.35 × 10 - 4 ( ° ) , σ H = 15.8 ( m ) , σ s u m = 27.6 ( m ) , where σ B represents the longitude error, σ L represents the latitude error, σ H represents the altitude error, and σ s u m represents the error radius.

The Relationship between Optimism and Engagement: The Impact on Student Performance

ERIC Educational Resources Information Center

Medlin, Bobby; Faulk, Larry

2011-01-01

The concepts of optimism and employee engagement as mechanisms to improving individual performance have been discussed in the management literature. Though studies concerning optimism in the workplace are relatively limited, evidence certainly exists that links the concept to improvement in individual academic and workplace performance.…

Single Mothers and Their Infants: Factors Associated with Optimal Parenting.

ERIC Educational Resources Information Center

Barratt, Marguerite Stevenson; And Others

1991-01-01

Examined factors that might influence optimal early parenting by Caucasian single mothers (n=53). Results indicated optimal parenting was linked with older maternal age, fewer maternal psychological symptoms, and less difficult infant temperament. Recommends particular needs of single mother should be considered when formulating public policy.…

Humans make efficient use of natural image statistics when performing spatial interpolation.

PubMed

D'Antona, Anthony D; Perry, Jeffrey S; Geisler, Wilson S

2013-12-16

Visual systems learn through evolution and experience over the lifespan to exploit the statistical structure of natural images when performing visual tasks. Understanding which aspects of this statistical structure are incorporated into the human nervous system is a fundamental goal in vision science. To address this goal, we measured human ability to estimate the intensity of missing image pixels in natural images. Human estimation accuracy is compared with various simple heuristics (e.g., local mean) and with optimal observers that have nearly complete knowledge of the local statistical structure of natural images. Human estimates are more accurate than those of simple heuristics, and they match the performance of an optimal observer that knows the local statistical structure of relative intensities (contrasts). This optimal observer predicts the detailed pattern of human estimation errors and hence the results place strong constraints on the underlying neural mechanisms. However, humans do not reach the performance of an optimal observer that knows the local statistical structure of the absolute intensities, which reflect both local relative intensities and local mean intensity. As predicted from a statistical analysis of natural images, human estimation accuracy is negligibly improved by expanding the context from a local patch to the whole image. Our results demonstrate that the human visual system exploits efficiently the statistical structure of natural images.

A Unified Statistical Rain-Attenuation Model for Communication Link Fade Predictions and Optimal Stochastic Fade Control Design Using a Location-Dependent Rain-Statistic Database

NASA Technical Reports Server (NTRS)

Manning, Robert M.

1990-01-01

A static and dynamic rain-attenuation model is presented which describes the statistics of attenuation on an arbitrarily specified satellite link for any location for which there are long-term rainfall statistics. The model may be used in the design of the optimal stochastic control algorithms to mitigate the effects of attenuation and maintain link reliability. A rain-statistics data base is compiled, which makes it possible to apply the model to any location in the continental U.S. with a resolution of 0-5 degrees in latitude and longitude. The model predictions are compared with experimental observations, showing good agreement.

Carboxamide Spleen Tyrosine Kinase (Syk) Inhibitors: Leveraging Ground State Interactions To Accelerate Optimization.

PubMed

Ellis, J Michael; Altman, Michael D; Cash, Brandon; Haidle, Andrew M; Kubiak, Rachel L; Maddess, Matthew L; Yan, Youwei; Northrup, Alan B

2016-12-08

Optimization of a series of highly potent and kinome selective carbon-linked carboxamide spleen tyrosine kinase (Syk) inhibitors with favorable drug-like properties is described. A pervasive Ames liability in an analogous nitrogen-linked carboxamide series was obviated by replacement with a carbon-linked moiety. Initial efforts lacked on-target potency, likely due to strain induced between the hinge binding amide and solvent front heterocycle. Consideration of ground state and bound state energetics allowed rapid realization of improved solvent front substituents affording subnanomolar Syk potency and high kinome selectivity. These molecules were also devoid of mutagenicity risk as assessed via the Ames test using the TA97a Salmonella strain.

Carboxamide Spleen Tyrosine Kinase (Syk) Inhibitors: Leveraging Ground State Interactions To Accelerate Optimization

PubMed Central

2016-01-01

Optimization of a series of highly potent and kinome selective carbon-linked carboxamide spleen tyrosine kinase (Syk) inhibitors with favorable drug-like properties is described. A pervasive Ames liability in an analogous nitrogen-linked carboxamide series was obviated by replacement with a carbon-linked moiety. Initial efforts lacked on-target potency, likely due to strain induced between the hinge binding amide and solvent front heterocycle. Consideration of ground state and bound state energetics allowed rapid realization of improved solvent front substituents affording subnanomolar Syk potency and high kinome selectivity. These molecules were also devoid of mutagenicity risk as assessed via the Ames test using the TA97a Salmonella strain. PMID:27994755

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter

PubMed Central

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Gu, Chengfan

2018-01-01

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation. PMID:29415509

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

PubMed

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

2018-02-06

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

Particle swarm optimization and its application in MEG source localization using single time sliced data

NASA Astrophysics Data System (ADS)

Lin, Juan; Liu, Chenglian; Guo, Yongning

2014-10-01

The estimation of neural active sources from the magnetoencephalography (MEG) data is a very critical issue for both clinical neurology and brain functions research. A widely accepted source-modeling technique for MEG involves calculating a set of equivalent current dipoles (ECDs). Depth in the brain is one of difficulties in MEG source localization. Particle swarm optimization(PSO) is widely used to solve various optimization problems. In this paper we discuss its ability and robustness to find the global optimum in different depths of the brain when using single equivalent current dipole (sECD) model and single time sliced data. The results show that PSO is an effective global optimization to MEG source localization when given one dipole in different depths.

Device-Free Localization via an Extreme Learning Machine with Parameterized Geometrical Feature Extraction.

PubMed

Zhang, Jie; Xiao, Wendong; Zhang, Sen; Huang, Shoudong

2017-04-17

Device-free localization (DFL) is becoming one of the new technologies in wireless localization field, due to its advantage that the target to be localized does not need to be attached to any electronic device. In the radio-frequency (RF) DFL system, radio transmitters (RTs) and radio receivers (RXs) are used to sense the target collaboratively, and the location of the target can be estimated by fusing the changes of the received signal strength (RSS) measurements associated with the wireless links. In this paper, we will propose an extreme learning machine (ELM) approach for DFL, to improve the efficiency and the accuracy of the localization algorithm. Different from the conventional machine learning approaches for wireless localization, in which the above differential RSS measurements are trivially used as the only input features, we introduce the parameterized geometrical representation for an affected link, which consists of its geometrical intercepts and differential RSS measurement. Parameterized geometrical feature extraction (PGFE) is performed for the affected links and the features are used as the inputs of ELM. The proposed PGFE-ELM for DFL is trained in the offline phase and performed for real-time localization in the online phase, where the estimated location of the target is obtained through the created ELM. PGFE-ELM has the advantages that the affected links used by ELM in the online phase can be different from those used for training in the offline phase, and can be more robust to deal with the uncertain combination of the detectable wireless links. Experimental results show that the proposed PGFE-ELM can improve the localization accuracy and learning speed significantly compared with a number of the existing machine learning and DFL approaches, including the weighted K-nearest neighbor (WKNN), support vector machine (SVM), back propagation neural network (BPNN), as well as the well-known radio tomographic imaging (RTI) DFL approach.

Device-Free Localization via an Extreme Learning Machine with Parameterized Geometrical Feature Extraction

PubMed Central

Zhang, Jie; Xiao, Wendong; Zhang, Sen; Huang, Shoudong

2017-01-01

Device-free localization (DFL) is becoming one of the new technologies in wireless localization field, due to its advantage that the target to be localized does not need to be attached to any electronic device. In the radio-frequency (RF) DFL system, radio transmitters (RTs) and radio receivers (RXs) are used to sense the target collaboratively, and the location of the target can be estimated by fusing the changes of the received signal strength (RSS) measurements associated with the wireless links. In this paper, we will propose an extreme learning machine (ELM) approach for DFL, to improve the efficiency and the accuracy of the localization algorithm. Different from the conventional machine learning approaches for wireless localization, in which the above differential RSS measurements are trivially used as the only input features, we introduce the parameterized geometrical representation for an affected link, which consists of its geometrical intercepts and differential RSS measurement. Parameterized geometrical feature extraction (PGFE) is performed for the affected links and the features are used as the inputs of ELM. The proposed PGFE-ELM for DFL is trained in the offline phase and performed for real-time localization in the online phase, where the estimated location of the target is obtained through the created ELM. PGFE-ELM has the advantages that the affected links used by ELM in the online phase can be different from those used for training in the offline phase, and can be more robust to deal with the uncertain combination of the detectable wireless links. Experimental results show that the proposed PGFE-ELM can improve the localization accuracy and learning speed significantly compared with a number of the existing machine learning and DFL approaches, including the weighted K-nearest neighbor (WKNN), support vector machine (SVM), back propagation neural network (BPNN), as well as the well-known radio tomographic imaging (RTI) DFL approach. PMID:28420187

Optical communications and a comparison of optical technologies for a high data rate return link from Mars

NASA Technical Reports Server (NTRS)

Spence, Rodney L.

1993-01-01

The important principles of direct- and heterodyne-detection optical free-space communications are reviewed. Signal-to-noise-ratio (SNR) and bit-error-rate (BER) expressions are derived for both the direct-detection and heterodyne-detection optical receivers. For the heterodyne system, performance degradation resulting from received-signal and local oscillator-beam misalignment and laser phase noise is analyzed. Determination of interfering background power from local and extended background sources is discussed. The BER performance of direct- and heterodyne-detection optical links in the presence of Rayleigh-distributed random pointing and tracking errors is described. Finally, several optical systems employing Nd:YAG, GaAs, and CO2 laser sources are evaluated and compared to assess their feasibility in providing high-data-rate (10- to 1000-Mbps) Mars-to-Earth communications. It is shown that the root mean square (rms) pointing and tracking accuracy is a critical factor in defining the system transmitting laser-power requirements and telescope size and that, for a given rms error, there is an optimum telescope aperture size that minimizes the required power. The results of the analysis conducted indicate that, barring the achievement of extremely small rms pointing and tracking errors (less than 0.2 microrad), the two most promising types of optical systems are those that use an Nd:YAG laser (lambda = 1.064 microns) and high-order pulse position modulator (PPM) and direct detection, and those that use a CO2 laser (lambda = 10.6 microns) and phase shifting keying homodyne modulation and coherent detection. For example, for a PPM order of M = 64 and an rms pointing accuracy of 0.4 microrad, an Nd:YAG system can be used to implement a 100-Mbps Mars link with a 40-cm transmitting telescope, a 20-W laser, and a 10-m receiving photon bucket. Under the same conditions, a CO2 system would require 3-m transmitting and receiving telescopes and a 32-W laser to implement such a link. Other types of optical systems, such as a semiconductor laser systems, are impractical in the presence of large rms pointing errors because of the high power requirements of the 100-Mbps Mars link, even when optimal-size telescopes are used.

The Aeronautical Data Link: Decision Framework for Architecture Analysis

NASA Technical Reports Server (NTRS)

Morris, A. Terry; Goode, Plesent W.

2003-01-01

A decision analytic approach that develops optimal data link architecture configuration and behavior to meet multiple conflicting objectives of concurrent and different airspace operations functions has previously been developed. The approach, premised on a formal taxonomic classification that correlates data link performance with operations requirements, information requirements, and implementing technologies, provides a coherent methodology for data link architectural analysis from top-down and bottom-up perspectives. This paper follows the previous research by providing more specific approaches for mapping and transitioning between the lower levels of the decision framework. The goal of the architectural analysis methodology is to assess the impact of specific architecture configurations and behaviors on the efficiency, capacity, and safety of operations. This necessarily involves understanding the various capabilities, system level performance issues and performance and interface concepts related to the conceptual purpose of the architecture and to the underlying data link technologies. Efficient and goal-directed data link architectural network configuration is conditioned on quantifying the risks and uncertainties associated with complex structural interface decisions. Deterministic and stochastic optimal design approaches will be discussed that maximize the effectiveness of architectural designs.

In vitro validation of a shape-optimized fiber-reinforced dental bridge.

PubMed

Chen, YungChung; Li, Haiyan; Fok, Alex

2011-12-01

To improve its mechanical performance, structural optimization had been used in a previous study to obtain an alternative design for a 3-unit inlay-retained fiber-reinforced composite (FRC) dental bridge. In that study, an optimized layout of the FRC substructure had been proposed to minimize stresses in the veneering composite and interfacial stresses between the composite and substructure. The current work aimed to validate in vitro the improved fracture resistance of the optimized design. All samples for the 3-unit inlay-retained FRC dental bridge were made with glass-fibers (FibreKor) as the substructure, surrounded by a veneering composite (GC Gradia). Two different FRC substructure designs were prepared: a conventional (n=20) and an optimized design (n=21). The conventional design was a straight beam linking one proximal box to the other, while the optimized design was a curved beam following the lower outline of the pontic. All samples were loaded to 400N on a universal test machine (MTS 810) with a loading speed of 0.2mm/min. During loading, the force and displacement were recorded. Meanwhile, a two-channel acoustic emission (AE) system was used to monitor the development of cracks during loading. The load-displacement curves of the two groups displayed significant differences. For the conventional design, there were numerous drops in load corresponding to local damage of the sample. For the optimized design, the load curves were much smoother. Cracks were clearly visible on the surface of the conventional group only, and the directions of those cracks were perpendicular to those of the most tensile stresses. Results from the more sensitive AE measurement also showed that the optimized design had, on average, fewer cracking events: 38 versus 2969 in the conventional design. The much lower number of AE events and smoother load-displacement curves indicated that the optimized FRC bridge design had a higher fracture resistance. It is expected that the optimized design will significantly improve the clinical performance of FRC bridges. Copyright © 2011 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Direct discriminant locality preserving projection with Hammerstein polynomial expansion.

PubMed

Chen, Xi; Zhang, Jiashu; Li, Defang

2012-12-01

Discriminant locality preserving projection (DLPP) is a linear approach that encodes discriminant information into the objective of locality preserving projection and improves its classification ability. To enhance the nonlinear description ability of DLPP, we can optimize the objective function of DLPP in reproducing kernel Hilbert space to form a kernel-based discriminant locality preserving projection (KDLPP). However, KDLPP suffers the following problems: 1) larger computational burden; 2) no explicit mapping functions in KDLPP, which results in more computational burden when projecting a new sample into the low-dimensional subspace; and 3) KDLPP cannot obtain optimal discriminant vectors, which exceedingly optimize the objective of DLPP. To overcome the weaknesses of KDLPP, in this paper, a direct discriminant locality preserving projection with Hammerstein polynomial expansion (HPDDLPP) is proposed. The proposed HPDDLPP directly implements the objective of DLPP in high-dimensional second-order Hammerstein polynomial space without matrix inverse, which extracts the optimal discriminant vectors for DLPP without larger computational burden. Compared with some other related classical methods, experimental results for face and palmprint recognition problems indicate the effectiveness of the proposed HPDDLPP.

Young inversion with multiple linked QTLs under selection in a hybrid zone.

PubMed

Lee, Cheng-Ruei; Wang, Baosheng; Mojica, Julius P; Mandáková, Terezie; Prasad, Kasavajhala V S K; Goicoechea, Jose Luis; Perera, Nadeesha; Hellsten, Uffe; Hundley, Hope N; Johnson, Jenifer; Grimwood, Jane; Barry, Kerrie; Fairclough, Stephen; Jenkins, Jerry W; Yu, Yeisoo; Kudrna, Dave; Zhang, Jianwei; Talag, Jayson; Golser, Wolfgang; Ghattas, Kathryn; Schranz, M Eric; Wing, Rod; Lysak, Martin A; Schmutz, Jeremy; Rokhsar, Daniel S; Mitchell-Olds, Thomas

2017-04-03

Fixed chromosomal inversions can reduce gene flow and promote speciation in two ways: by suppressing recombination and by carrying locally favoured alleles at multiple loci. However, it is unknown whether favoured mutations slowly accumulate on older inversions or if young inversions spread because they capture pre-existing adaptive quantitative trait loci (QTLs). By genetic mapping, chromosome painting and genome sequencing, we have identified a major inversion controlling ecologically important traits in Boechera stricta. The inversion arose since the last glaciation and subsequently reached local high frequency in a hybrid speciation zone. Furthermore, the inversion shows signs of positive directional selection. To test whether the inversion could have captured existing, linked QTLs, we crossed standard, collinear haplotypes from the hybrid zone and found multiple linked phenology QTLs within the inversion region. These findings provide the first direct evidence that linked, locally adapted QTLs may be captured by young inversions during incipient speciation.

Young inversion with multiple linked QTLs under selection in a hybrid zone

PubMed Central

Lee, Cheng-Ruei; Wang, Baosheng; Mojica, Julius; Mandáková, Terezie; Prasad, Kasavajhala V. S. K.; Goicoechea, Jose Luis; Perera, Nadeesha; Hellsten, Uffe; Hundley, Hope N.; Johnson, Jenifer; Grimwood, Jane; Barry, Kerrie; Fairclough, Stephen; Jenkins, Jerry W.; Yu, Yeisoo; Kudrna, Dave; Zhang, Jianwei; Talag, Jayson; Golser, Wolfgang; Ghattas, Katherine; Schranz, M. Eric; Wing, Rod; Lysak, Martin A.; Schmutz, Jeremy; Rokhsar, Daniel S.; Mitchell-Olds, Thomas

2017-01-01

Fixed chromosomal inversions can reduce gene flow and promote speciation in two ways: by suppressing recombination and by carrying locally favored alleles at multiple loci. However, it is unknown whether favored mutations slowly accumulate on older inversions or if young inversions spread because they capture preexisting adaptive Quantitative Trait Loci (QTLs). By genetic mapping, chromosome painting and genome sequencing we have identified a major inversion controlling ecologically important traits in Boechera stricta. The inversion arose since the last glaciation and subsequently reached local high frequency in a hybrid speciation zone. Furthermore, the inversion shows signs of positive directional selection. To test whether the inversion could have captured existing, linked QTLs, we crossed standard, collinear haplotypes from the hybrid zone and found multiple linked phenology QTLs within the inversion region. These findings provide the first direct evidence that linked, locally adapted QTLs may be captured by young inversions during incipient speciation. PMID:28812690

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

Balance of Interactions Determines Optimal Survival in Multi-Species Communities.

PubMed

Choudhary, Anshul; Sinha, Sudeshna

2015-01-01

We consider a multi-species community modelled as a complex network of populations, where the links are given by a random asymmetric connectivity matrix J, with fraction 1 - C of zero entries, where C reflects the over-all connectivity of the system. The non-zero elements of J are drawn from a Gaussian distribution with mean μ and standard deviation σ. The signs of the elements Jij reflect the nature of density-dependent interactions, such as predatory-prey, mutualism or competition, and their magnitudes reflect the strength of the interaction. In this study we try to uncover the broad features of the inter-species interactions that determine the global robustness of this network, as indicated by the average number of active nodes (i.e. non-extinct species) in the network, and the total population, reflecting the biomass yield. We find that the network transitions from a completely extinct system to one where all nodes are active, as the mean interaction strength goes from negative to positive, with the transition getting sharper for increasing C and decreasing σ. We also find that the total population, displays distinct non-monotonic scaling behaviour with respect to the product μC, implying that survival is dependent not merely on the number of links, but rather on the combination of the sparseness of the connectivity matrix and the net interaction strength. Interestingly, in an intermediate window of positive μC, the total population is maximal, indicating that too little or too much positive interactions is detrimental to survival. Rather, the total population levels are optimal when the network has intermediate net positive connection strengths. At the local level we observe marked qualitative changes in dynamical patterns, ranging from anti-phase clusters of period 2 cycles and chaotic bands, to fixed points, under the variation of mean μ of the interaction strengths. We also study the correlation between synchronization and survival, and find that synchronization does not necessarily lead to extinction. Lastly, we propose an effective low dimensional map to capture the behavior of the entire network, and this provides a broad understanding of the interplay of the local dynamical patterns and the global robustness trends in the network.

Measures of health sciences journal use: a comparison of vendor, link-resolver, and local citation statistics*

PubMed Central

De Groote, Sandra L.; Blecic, Deborah D.; Martin, Kristin

2013-01-01

Objective: Libraries require efficient and reliable methods to assess journal use. Vendors provide complete counts of articles retrieved from their platforms. However, if a journal is available on multiple platforms, several sets of statistics must be merged. Link-resolver reports merge data from all platforms into one report but only record partial use because users can access library subscriptions from other paths. Citation data are limited to publication use. Vendor, link-resolver, and local citation data were examined to determine correlation. Because link-resolver statistics are easy to obtain, the study library especially wanted to know if they correlate highly with the other measures. Methods: Vendor, link-resolver, and local citation statistics for the study institution were gathered for health sciences journals. Spearman rank-order correlation coefficients were calculated. Results: There was a high positive correlation between all three data sets, with vendor data commonly showing the highest use. However, a small percentage of titles showed anomalous results. Discussion and Conclusions: Link-resolver data correlate well with vendor and citation data, but due to anomalies, low link-resolver data would best be used to suggest titles for further evaluation using vendor data. Citation data may not be needed as it correlates highly with other measures. PMID:23646026

A novel constrained H2 optimization algorithm for mechatronics design in flexure-linked biaxial gantry.

PubMed

Ma, Jun; Chen, Si-Lu; Kamaldin, Nazir; Teo, Chek Sing; Tay, Arthur; Mamun, Abdullah Al; Tan, Kok Kiong

2017-11-01

The biaxial gantry is widely used in many industrial processes that require high precision Cartesian motion. The conventional rigid-link version suffers from breaking down of joints if any de-synchronization between the two carriages occurs. To prevent above potential risk, a flexure-linked biaxial gantry is designed to allow a small rotation angle of the cross-arm. Nevertheless, the chattering of control signals and inappropriate design of the flexure joint will possibly induce resonant modes of the end-effector. Thus, in this work, the design requirements in terms of tracking accuracy, biaxial synchronization, and resonant mode suppression are achieved by integrated optimization of the stiffness of flexures and PID controller parameters for a class of point-to-point reference trajectories with same dynamics but different steps. From here, an H 2 optimization problem with defined constraints is formulated, and an efficient iterative solver is proposed by hybridizing direct computation of constrained projection gradient and line search of optimal step. Comparative experimental results obtained on the testbed are presented to verify the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Autonomous Modelling of X-ray Spectra Using Robust Global Optimization Methods

NASA Astrophysics Data System (ADS)

Rogers, Adam; Safi-Harb, Samar; Fiege, Jason

2015-08-01

The standard approach to model fitting in X-ray astronomy is by means of local optimization methods. However, these local optimizers suffer from a number of problems, such as a tendency for the fit parameters to become trapped in local minima, and can require an involved process of detailed user intervention to guide them through the optimization process. In this work we introduce a general GUI-driven global optimization method for fitting models to X-ray data, written in MATLAB, which searches for optimal models with minimal user interaction. We directly interface with the commonly used XSPEC libraries to access the full complement of pre-existing spectral models that describe a wide range of physics appropriate for modelling astrophysical sources, including supernova remnants and compact objects. Our algorithm is powered by the Ferret genetic algorithm and Locust particle swarm optimizer from the Qubist Global Optimization Toolbox, which are robust at finding families of solutions and identifying degeneracies. This technique will be particularly instrumental for multi-parameter models and high-fidelity data. In this presentation, we provide details of the code and use our techniques to analyze X-ray data obtained from a variety of astrophysical sources.

Multimodal optimization by using hybrid of artificial bee colony algorithm and BFGS algorithm

NASA Astrophysics Data System (ADS)

Anam, S.

2017-10-01

Optimization has become one of the important fields in Mathematics. Many problems in engineering and science can be formulated into optimization problems. They maybe have many local optima. The optimization problem with many local optima, known as multimodal optimization problem, is how to find the global solution. Several metaheuristic methods have been proposed to solve multimodal optimization problems such as Particle Swarm Optimization (PSO), Genetics Algorithm (GA), Artificial Bee Colony (ABC) algorithm, etc. The performance of the ABC algorithm is better than or similar to those of other population-based algorithms with the advantage of employing a fewer control parameters. The ABC algorithm also has the advantages of strong robustness, fast convergence and high flexibility. However, it has the disadvantages premature convergence in the later search period. The accuracy of the optimal value cannot meet the requirements sometimes. Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is a good iterative method for finding a local optimum. Compared with other local optimization methods, the BFGS algorithm is better. Based on the advantages of the ABC algorithm and the BFGS algorithm, this paper proposes a hybrid of the artificial bee colony algorithm and the BFGS algorithm to solve the multimodal optimization problem. The first step is that the ABC algorithm is run to find a point. In the second step is that the point obtained by the first step is used as an initial point of BFGS algorithm. The results show that the hybrid method can overcome from the basic ABC algorithm problems for almost all test function. However, if the shape of function is flat, the proposed method cannot work well.

Statistical similarity measures for link prediction in heterogeneous complex networks

NASA Astrophysics Data System (ADS)

Shakibian, Hadi; Charkari, Nasrollah Moghadam

2018-07-01

The majority of the link prediction measures in heterogeneous complex networks rely on the nodes connectivities while less attention has been paid to the importance of the nodes and paths. In this paper, we propose some new meta-path based statistical similarity measures to properly perform link prediction task. The main idea in the proposed measures is to drive some co-occurrence events in a number of co-occurrence matrices that are occurred between the visited nodes obeying a meta-path. The extracted co-occurrence matrices are analyzed in terms of the energy, inertia, local homogeneity, correlation, and information measure of correlation to determine various information theoretic measures. We evaluate the proposed measures, denoted as link energy, link inertia, link local homogeneity, link correlation, and link information measure of correlation, using a standard DBLP network data set. The results of the AUC score and Precision rate indicate the validity and accuracy of the proposed measures in comparison to the popular meta-path based similarity measures.

AN OPTIMAL ADAPTIVE LOCAL GRID REFINEMENT APPROACH TO MODELING CONTAMINANT TRANSPORT

EPA Science Inventory

A Lagrangian-Eulerian method with an optimal adaptive local grid refinement is used to model contaminant transport equations. pplication of this approach to two bench-mark problems indicates that it completely resolves difficulties of peak clipping, numerical diffusion, and spuri...

Localization of multilayer networks by optimized single-layer rewiring.

PubMed

Jalan, Sarika; Pradhan, Priodyuti

2018-04-01

We study localization properties of principal eigenvectors (PEVs) of multilayer networks (MNs). Starting with a multilayer network corresponding to a delocalized PEV, we rewire the network edges using an optimization technique such that the PEV of the rewired multilayer network becomes more localized. The framework allows us to scrutinize structural and spectral properties of the networks at various localization points during the rewiring process. We show that rewiring only one layer is enough to attain a MN having a highly localized PEV. Our investigation reveals that a single edge rewiring of the optimized MN can lead to the complete delocalization of a highly localized PEV. This sensitivity in the localization behavior of PEVs is accompanied with the second largest eigenvalue lying very close to the largest one. This observation opens an avenue to gain a deeper insight into the origin of PEV localization of networks. Furthermore, analysis of multilayer networks constructed using real-world social and biological data shows that the localization properties of these real-world multilayer networks are in good agreement with the simulation results for the model multilayer network. This paper is relevant to applications that require understanding propagation of perturbation in multilayer networks.

Localization of multilayer networks by optimized single-layer rewiring

NASA Astrophysics Data System (ADS)

Jalan, Sarika; Pradhan, Priodyuti

2018-04-01

We study localization properties of principal eigenvectors (PEVs) of multilayer networks (MNs). Starting with a multilayer network corresponding to a delocalized PEV, we rewire the network edges using an optimization technique such that the PEV of the rewired multilayer network becomes more localized. The framework allows us to scrutinize structural and spectral properties of the networks at various localization points during the rewiring process. We show that rewiring only one layer is enough to attain a MN having a highly localized PEV. Our investigation reveals that a single edge rewiring of the optimized MN can lead to the complete delocalization of a highly localized PEV. This sensitivity in the localization behavior of PEVs is accompanied with the second largest eigenvalue lying very close to the largest one. This observation opens an avenue to gain a deeper insight into the origin of PEV localization of networks. Furthermore, analysis of multilayer networks constructed using real-world social and biological data shows that the localization properties of these real-world multilayer networks are in good agreement with the simulation results for the model multilayer network. This paper is relevant to applications that require understanding propagation of perturbation in multilayer networks.

A linked simulation-optimization model for solving the unknown groundwater pollution source identification problems.

PubMed

Ayvaz, M Tamer

2010-09-20

This study proposes a linked simulation-optimization model for solving the unknown groundwater pollution source identification problems. In the proposed model, MODFLOW and MT3DMS packages are used to simulate the flow and transport processes in the groundwater system. These models are then integrated with an optimization model which is based on the heuristic harmony search (HS) algorithm. In the proposed simulation-optimization model, the locations and release histories of the pollution sources are treated as the explicit decision variables and determined through the optimization model. Also, an implicit solution procedure is proposed to determine the optimum number of pollution sources which is an advantage of this model. The performance of the proposed model is evaluated on two hypothetical examples for simple and complex aquifer geometries, measurement error conditions, and different HS solution parameter sets. Identified results indicated that the proposed simulation-optimization model is an effective way and may be used to solve the inverse pollution source identification problems. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Study on the preparation process of cross-linked porous cassava starch

NASA Astrophysics Data System (ADS)

Yin, Xiulian; You, Qinghong; Wan, Miaomiao; Zhang, Xuejuan; Dai, Chunhua

2017-04-01

Using cassava starch as raw material, preparation process of porous cross-linked cassava starch was studied. Using TSTP as cross-linking agents, Orthogonal design was applied for the optimization of cross-linked porous starch preparation process. The results showed that the opitmal conditions of cross-linked porous cassava starch were as follows: reaction temperature 45°C, reaction time 20 h, 1% of the amount of the enzyme, the enzyme ratio of 1:5, pH 5.50, substrate concentration of 40%.

A composite foraminiferal biostratigraphic sequence for the Lower Miocene deposits in the type area of the Qom Formation, central Iran, developed by constrained optimization (CONOP)

NASA Astrophysics Data System (ADS)

Daneshian, Jahanbakhsh; Ramezani Dana, Leila; Sadler, Peter

2017-01-01

Benthic foraminifera species commonly outnumber planktic species in the type area of the Lower Miocene Qom Formation, in north central Iran, where it records the Tethyan link between the eastern Mediterranean and Indo- Pacific provinces. Because measured sections preserve very different sequences of first and last occurrences of these species, no single section provides a completely suitable baseline for correlation. To resolve this problem, we combined bioevents from three stratigraphic sections into a single composite sequence by constrained optimization (CONOP). The composite section arranges the first and last appearance events (FAD and LAD) of 242 foraminifera in an optimal order that minimizes the implied diachronism between sections. The composite stratigraphic ranges of the planktic foraminifera support a practical biozonation which reveals substantial local changes of accumulation rate during Aquitanian to Burdigalian times. Traditional biozone boundaries emerge little changed but an order of magnitude more correlations can be interpolated. The top of the section at Dobaradar is younger than previously thought and younger than sections at Dochah and Tigheh Reza-Abad. The latter two sections probably extend older into the Aquitanian than the Dobaradar section, but likely include a hiatus near the base of the Burdigalian. The bounding contacts with the Upper Red and Lower Red Formations are shown to be diachronous.

Preparation of poly-L-lysine functionalized magnetic nanoparticles and their influence on viability of cancer cells

NASA Astrophysics Data System (ADS)

Khmara, I.; Koneracka, M.; Kubovcikova, M.; Zavisova, V.; Antal, I.; Csach, K.; Kopcansky, P.; Vidlickova, I.; Csaderova, L.; Pastorekova, S.; Zatovicova, M.

2017-04-01

This study was aimed at development of biocompatible amino-functionalized magnetic nanoparticles as carriers of specific antibodies able to detect and/or target cancer cells. Poly-L-lysine (PLL)-modified magnetic nanoparticle samples with different PLL/Fe3O4 content were prepared and tested to define the optimal PLL/Fe3O4 weight ratio. The samples were characterized for particle size and morphology (SEM, TEM and DLS), and surface properties (zeta potential measurements). The optimal PLL/Fe3O4 weight ratio of 1.0 based on both zeta potential and DLS measurements was in agreement with the UV/VIS measurements. Magnetic nanoparticles with the optimal PLL content were conjugated with antibody specific for the cancer biomarker carbonic anhydrase IX (CA IX), which is induced by hypoxia, a physiologic stress present in solid tumors and linked with aggressive tumor behavior. CA IX is localized on the cell surface with the antibody-binding epitope facing the extracellular space and is therefore suitable for antibody-based targeting of tumor cells. Here we showed that PLL/Fe3O4 magnetic nanoparticles exhibit cytotoxic activities in a cell type-dependent manner and bind to cells expressing CA IX when conjugated with the CA IX-specific antibody. These data support further investigations of the CA IX antibody-conjugated, magnetic field-guided/activated nanoparticles as tools in anticancer strategies.

Value versus Accuracy: application of seasonal forecasts to a hydro-economic optimization model for the Sudanese Blue Nile

NASA Astrophysics Data System (ADS)

Satti, S.; Zaitchik, B. F.; Siddiqui, S.; Badr, H. S.; Shukla, S.; Peters-Lidard, C. D.

2015-12-01

The unpredictable nature of precipitation within the East African (EA) region makes it one of the most vulnerable, food insecure regions in the world. There is a vital need for forecasts to inform decision makers, both local and regional, and to help formulate the region's climate change adaptation strategies. Here, we present a suite of different seasonal forecast models, both statistical and dynamical, for the EA region. Objective regionalization is performed for EA on the basis of interannual variability in precipitation in both observations and models. This regionalization is applied as the basis for calculating a number of standard skill scores to evaluate each model's forecast accuracy. A dynamically linked Land Surface Model (LSM) is then applied to determine forecasted flows, which drive the Sudanese Hydroeconomic Optimization Model (SHOM). SHOM combines hydrologic, agronomic and economic inputs to determine the optimal decisions that maximize economic benefits along the Sudanese Blue Nile. This modeling sequence is designed to derive the potential added value of information of each forecasting model to agriculture and hydropower management. A rank of each model's forecasting skill score along with its added value of information is analyzed in order compare the performance of each forecast. This research aims to improve understanding of how characteristics of accuracy, lead time, and uncertainty of seasonal forecasts influence their utility to water resources decision makers who utilize them.

Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Admissibility and Termination Analysis.

PubMed

Wei, Qinglai; Liu, Derong; Lin, Qiao

In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.

Measuring distance through dense weighted networks: The case of hospital-associated pathogens

PubMed Central

Smieszek, Timo; Henderson, Katherine L.; Johnson, Alan P.

2017-01-01

Hospital networks, formed by patients visiting multiple hospitals, affect the spread of hospital-associated infections, resulting in differences in risks for hospitals depending on their network position. These networks are increasingly used to inform strategies to prevent and control the spread of hospital-associated pathogens. However, many studies only consider patients that are received directly from the initial hospital, without considering the effect of indirect trajectories through the network. We determine the optimal way to measure the distance between hospitals within the network, by reconstructing the English hospital network based on shared patients in 2014–2015, and simulating the spread of a hospital-associated pathogen between hospitals, taking into consideration that each intermediate hospital conveys a delay in the further spread of the pathogen. While the risk of transferring a hospital-associated pathogen between directly neighbouring hospitals is a direct reflection of the number of shared patients, the distance between two hospitals far-away in the network is determined largely by the number of intermediate hospitals in the network. Because the network is dense, most long distance transmission chains in fact involve only few intermediate steps, spreading along the many weak links. The dense connectivity of hospital networks, together with a strong regional structure, causes hospital-associated pathogens to spread from the initial outbreak in a two-step process: first, the directly surrounding hospitals are affected through the strong connections, second all other hospitals receive introductions through the multitude of weaker links. Although the strong connections matter for local spread, weak links in the network can offer ideal routes for hospital-associated pathogens to travel further faster. This hold important implications for infection prevention and control efforts: if a local outbreak is not controlled in time, colonised patients will appear in other regions, irrespective of the distance to the initial outbreak, making import screening ever more difficult. PMID:28771581

Distributed Optimization for a Class of Nonlinear Multiagent Systems With Disturbance Rejection.

PubMed

Wang, Xinghu; Hong, Yiguang; Ji, Haibo

2016-07-01

The paper studies the distributed optimization problem for a class of nonlinear multiagent systems in the presence of external disturbances. To solve the problem, we need to achieve the optimal multiagent consensus based on local cost function information and neighboring information and meanwhile to reject local disturbance signals modeled by an exogenous system. With convex analysis and the internal model approach, we propose a distributed optimization controller for heterogeneous and nonlinear agents in the form of continuous-time minimum-phase systems with unity relative degree. We prove that the proposed design can solve the exact optimization problem with rejecting disturbances.

The use of optimization techniques to design controlled diffusion compressor blading

NASA Technical Reports Server (NTRS)

Sanger, N. L.

1982-01-01

A method for automating compressor blade design using numerical optimization, and applied to the design of a controlled diffusion stator blade row is presented. A general purpose optimization procedure is employed, based on conjugate directions for locally unconstrained problems and on feasible directions for locally constrained problems. Coupled to the optimizer is an analysis package consisting of three analysis programs which calculate blade geometry, inviscid flow, and blade surface boundary layers. The optimizing concepts and selection of design objective and constraints are described. The procedure for automating the design of a two dimensional blade section is discussed, and design results are presented.

A Glider-Assisted Link Disruption Restoration Mechanism in Underwater Acoustic Sensor Networks.

PubMed

Jin, Zhigang; Wang, Ning; Su, Yishan; Yang, Qiuling

2018-02-07

Underwater acoustic sensor networks (UASNs) have become a hot research topic. In UASNs, nodes can be affected by ocean currents and external forces, which could result in sudden link disruption. Therefore, designing a flexible and efficient link disruption restoration mechanism to ensure the network connectivity is a challenge. In the paper, we propose a glider-assisted restoration mechanism which includes link disruption recognition and related link restoring mechanism. In the link disruption recognition mechanism, the cluster heads collect the link disruption information and then schedule gliders acting as relay nodes to restore the disrupted link. Considering the glider's sawtooth motion, we design a relay location optimization algorithm with a consideration of both the glider's trajectory and acoustic channel attenuation model. The utility function is established by minimizing the channel attenuation and the optimal location of glider is solved by a multiplier method. The glider-assisted restoration mechanism can greatly improve the packet delivery rate and reduce the communication energy consumption and it is more general for the restoration of different link disruption scenarios. The simulation results show that glider-assisted restoration mechanism can improve the delivery rate of data packets by 15-33% compared with cooperative opportunistic routing (OVAR), the hop-by-hop vector-based forwarding (HH-VBF) and the vector based forward (VBF) methods, and reduce communication energy consumption by 20-58% for a typical network's setting.

A Glider-Assisted Link Disruption Restoration Mechanism in Underwater Acoustic Sensor Networks

PubMed Central

Wang, Ning; Su, Yishan; Yang, Qiuling

2018-01-01

Underwater acoustic sensor networks (UASNs) have become a hot research topic. In UASNs, nodes can be affected by ocean currents and external forces, which could result in sudden link disruption. Therefore, designing a flexible and efficient link disruption restoration mechanism to ensure the network connectivity is a challenge. In the paper, we propose a glider-assisted restoration mechanism which includes link disruption recognition and related link restoring mechanism. In the link disruption recognition mechanism, the cluster heads collect the link disruption information and then schedule gliders acting as relay nodes to restore the disrupted link. Considering the glider’s sawtooth motion, we design a relay location optimization algorithm with a consideration of both the glider’s trajectory and acoustic channel attenuation model. The utility function is established by minimizing the channel attenuation and the optimal location of glider is solved by a multiplier method. The glider-assisted restoration mechanism can greatly improve the packet delivery rate and reduce the communication energy consumption and it is more general for the restoration of different link disruption scenarios. The simulation results show that glider-assisted restoration mechanism can improve the delivery rate of data packets by 15–33% compared with cooperative opportunistic routing (OVAR), the hop-by-hop vector-based forwarding (HH-VBF) and the vector based forward (VBF) methods, and reduce communication energy consumption by 20–58% for a typical network’s setting. PMID:29414898

Growing children's bodies and minds: maximizing child nutrition and development.

PubMed

Engle, Patrice; Huffman, Sandra L

2010-06-01

For their optimal growth, and for greater long-term human capital development, children profit not only from improved nutrition but also from improved learning opportunities in the earliest years of life. This paper describes how actions to enhance optimal infant and young child nutrition can be linked with child development interventions for children under 3 years of age. In countries with high rates of malnutrition, linking these two components will result in synergies of program activities, and will bring about a greater impact at reduced cost than either activity conducted separately. New understanding of social marketing and communication strategies can increase effectiveness of linked interventions. Public-private partnerships to improve both child development and nutrition offer promise for sustainable interventions.

Understanding Older Adults' Resilience During the Brisbane Floods: Social Capital, Life Experience, and Optimism.

PubMed

Brockie, Lauren; Miller, Evonne

2017-02-01

The purpose of this study was to explore how social capital or the impact of life and previous disaster experience facilitated resilience in older adults who experienced the 2011 and 2013 floods in Brisbane, Australia. Data were drawn from in-depth interviews of 10 older adults from Brisbane who were evacuated in both the 2011 and 2013 floods. A combined qualitative approach drawing from the methods of constructivist grounded theory and narrative inquiry was applied and the data were analyzed by using (inductive) line-by-line and axial coding. The narratives of the older adults revealed a strong theme of resilience linked to social capital (bonding, bridging, and linking) and previous disaster experience. The results reflected the changing face of disaster management strategies and sources of social capital. Changes in disaster management polices (toward self-reliance) and more formalized sources of social capital highlight the need to build strong and healthy resilient communities that are capable of positively recovering from natural disasters. The results from this research emphasize the importance of initiatives that enhance social cohesion, trust, and social capital within local communities. (Disaster Med Public Health Preparedness. 2017;11:72-79).

A novel communication mechanism based on node potential multi-path routing

NASA Astrophysics Data System (ADS)

Bu, Youjun; Zhang, Chuanhao; Jiang, YiMing; Zhang, Zhen

2016-10-01

With the network scales rapidly and new network applications emerge frequently, bandwidth supply for today's Internet could not catch up with the rapid increasing requirements. Unfortunately, irrational using of network sources makes things worse. Actual network deploys single-next-hop optimization paths for data transmission, but such "best effort" model leads to the imbalance use of network resources and usually leads to local congestion. On the other hand Multi-path routing can use the aggregation bandwidth of multi paths efficiently and improve the robustness of network, security, load balancing and quality of service. As a result, multi-path has attracted much attention in the routing and switching research fields and many important ideas and solutions have been proposed. This paper focuses on implementing the parallel transmission of multi next-hop data, balancing the network traffic and reducing the congestion. It aimed at exploring the key technologies of the multi-path communication network, which could provide a feasible academic support for subsequent applications of multi-path communication networking. It proposed a novel multi-path algorithm based on node potential in the network. And the algorithm can fully use of the network link resource and effectively balance network link resource utilization.

A mitochondria-anchored isoform of the actin-nucleating spire protein regulates mitochondrial division

PubMed Central

Manor, Uri; Bartholomew, Sadie; Golani, Gonen; Christenson, Eric; Kozlov, Michael; Higgs, Henry; Spudich, James; Lippincott-Schwartz, Jennifer

2015-01-01

Mitochondrial division, essential for survival in mammals, is enhanced by an inter-organellar process involving ER tubules encircling and constricting mitochondria. The force for constriction is thought to involve actin polymerization by the ER-anchored isoform of the formin protein inverted formin 2 (INF2). Unknown is the mechanism triggering INF2-mediated actin polymerization at ER-mitochondria intersections. We show that a novel isoform of the formin-binding, actin-nucleating protein Spire, Spire1C, localizes to mitochondria and directly links mitochondria to the actin cytoskeleton and the ER. Spire1C binds INF2 and promotes actin assembly on mitochondrial surfaces. Disrupting either Spire1C actin- or formin-binding activities reduces mitochondrial constriction and division. We propose Spire1C cooperates with INF2 to regulate actin assembly at ER-mitochondrial contacts. Simulations support this model's feasibility and demonstrate polymerizing actin filaments can induce mitochondrial constriction. Thus, Spire1C is optimally positioned to serve as a molecular hub that links mitochondria to actin and the ER for regulation of mitochondrial division. DOI: http://dx.doi.org/10.7554/eLife.08828.001 PMID:26305500

An Agent-Based Simulation for Investigating the Impact of Stereotypes on Task-Oriented Group Formation

NASA Astrophysics Data System (ADS)

Maghami, Mahsa; Sukthankar, Gita

In this paper, we introduce an agent-based simulation for investigating the impact of social factors on the formation and evolution of task-oriented groups. Task-oriented groups are created explicitly to perform a task, and all members derive benefits from task completion. However, even in cases when all group members act in a way that is locally optimal for task completion, social forces that have mild effects on choice of associates can have a measurable impact on task completion performance. In this paper, we show how our simulation can be used to model the impact of stereotypes on group formation. In our simulation, stereotypes are based on observable features, learned from prior experience, and only affect an agent's link formation preferences. Even without assuming stereotypes affect the agents' willingness or ability to complete tasks, the long-term modifications that stereotypes have on the agents' social network impair the agents' ability to form groups with sufficient diversity of skills, as compared to agents who form links randomly. An interesting finding is that this effect holds even in cases where stereotype preference and skill existence are completely uncorrelated.

Mixed Integer Programming and Heuristic Scheduling for Space Communication

NASA Technical Reports Server (NTRS)

Lee, Charles H.; Cheung, Kar-Ming

2013-01-01

Optimal planning and scheduling for a communication network was created where the nodes within the network are communicating at the highest possible rates while meeting the mission requirements and operational constraints. The planning and scheduling problem was formulated in the framework of Mixed Integer Programming (MIP) to introduce a special penalty function to convert the MIP problem into a continuous optimization problem, and to solve the constrained optimization problem using heuristic optimization. The communication network consists of space and ground assets with the link dynamics between any two assets varying with respect to time, distance, and telecom configurations. One asset could be communicating with another at very high data rates at one time, and at other times, communication is impossible, as the asset could be inaccessible from the network due to planetary occultation. Based on the network's geometric dynamics and link capabilities, the start time, end time, and link configuration of each view period are selected to maximize the communication efficiency within the network. Mathematical formulations for the constrained mixed integer optimization problem were derived, and efficient analytical and numerical techniques were developed to find the optimal solution. By setting up the problem using MIP, the search space for the optimization problem is reduced significantly, thereby speeding up the solution process. The ratio of the dimension of the traditional method over the proposed formulation is approximately an order N (single) to 2*N (arraying), where N is the number of receiving antennas of a node. By introducing a special penalty function, the MIP problem with non-differentiable cost function and nonlinear constraints can be converted into a continuous variable problem, whose solution is possible.

Speed and convergence properties of gradient algorithms for optimization of IMRT.

PubMed

Zhang, Xiaodong; Liu, Helen; Wang, Xiaochun; Dong, Lei; Wu, Qiuwen; Mohan, Radhe

2004-05-01

Gradient algorithms are the most commonly employed search methods in the routine optimization of IMRT plans. It is well known that local minima can exist for dose-volume-based and biology-based objective functions. The purpose of this paper is to compare the relative speed of different gradient algorithms, to investigate the strategies for accelerating the optimization process, to assess the validity of these strategies, and to study the convergence properties of these algorithms for dose-volume and biological objective functions. With these aims in mind, we implemented Newton's, conjugate gradient (CG), and the steepest decent (SD) algorithms for dose-volume- and EUD-based objective functions. Our implementation of Newton's algorithm approximates the second derivative matrix (Hessian) by its diagonal. The standard SD algorithm and the CG algorithm with "line minimization" were also implemented. In addition, we investigated the use of a variation of the CG algorithm, called the "scaled conjugate gradient" (SCG) algorithm. To accelerate the optimization process, we investigated the validity of the use of a "hybrid optimization" strategy, in which approximations to calculated dose distributions are used during most of the iterations. Published studies have indicated that getting trapped in local minima is not a significant problem. To investigate this issue further, we first obtained, by trial and error, and starting with uniform intensity distributions, the parameters of the dose-volume- or EUD-based objective functions which produced IMRT plans that satisfied the clinical requirements. Using the resulting optimized intensity distributions as the initial guess, we investigated the possibility of getting trapped in a local minimum. For most of the results presented, we used a lung cancer case. To illustrate the generality of our methods, the results for a prostate case are also presented. For both dose-volume and EUD based objective functions, Newton's method far outperforms other algorithms in terms of speed. The SCG algorithm, which avoids expensive "line minimization," can speed up the standard CG algorithm by at least a factor of 2. For the same initial conditions, all algorithms converge essentially to the same plan. However, we demonstrate that for any of the algorithms studied, starting with previously optimized intensity distributions as the initial guess but for different objective function parameters, the solution frequently gets trapped in local minima. We found that the initial intensity distribution obtained from IMRT optimization utilizing objective function parameters, which favor a specific anatomic structure, would lead to a local minimum corresponding to that structure. Our results indicate that from among the gradient algorithms tested, Newton's method appears to be the fastest by far. Different gradient algorithms have the same convergence properties for dose-volume- and EUD-based objective functions. The hybrid dose calculation strategy is valid and can significantly accelerate the optimization process. The degree of acceleration achieved depends on the type of optimization problem being addressed (e.g., IMRT optimization, intensity modulated beam configuration optimization, or objective function parameter optimization). Under special conditions, gradient algorithms will get trapped in local minima, and reoptimization, starting with the results of previous optimization, will lead to solutions that are generally not significantly different from the local minimum.

New estimation architecture for multisensor data fusion

NASA Astrophysics Data System (ADS)

Covino, Joseph M.; Griffiths, Barry E.

1991-07-01

This paper describes a novel method of hierarchical asynchronous distributed filtering called the Net Information Approach (NIA). The NIA is a Kalman-filter-based estimation scheme for spatially distributed sensors which must retain their local optimality yet require a nearly optimal global estimate. The key idea of the NIA is that each local sensor-dedicated filter tells the global filter 'what I've learned since the last local-to-global transmission,' whereas in other estimation architectures the local-to-global transmission consists of 'what I think now.' An algorithm based on this idea has been demonstrated on a small-scale target-tracking problem with many encouraging results. Feasibility of this approach was demonstrated by comparing NIA performance to an optimal centralized Kalman filter (lower bound) via Monte Carlo simulations.

Multi objective multi refinery optimization with environmental and catastrophic failure effects objectives

NASA Astrophysics Data System (ADS)

Khogeer, Ahmed Sirag

2005-11-01

Petroleum refining is a capital-intensive business. With stringent environmental regulations on the processing industry and declining refining margins, political instability, increased risk of war and terrorist attacks in which refineries and fuel transportation grids may be targeted, higher pressures are exerted on refiners to optimize performance and find the best combination of feed and processes to produce salable products that meet stricter product specifications, while at the same time meeting refinery supply commitments and of course making profit. This is done through multi objective optimization. For corporate refining companies and at the national level, Intea-Refinery and Inter-Refinery optimization is the second step in optimizing the operation of the whole refining chain as a single system. Most refinery-wide optimization methods do not cover multiple objectives such as minimizing environmental impact, avoiding catastrophic failures, or enhancing product spec upgrade effects. This work starts by carrying out a refinery-wide, single objective optimization, and then moves to multi objective-single refinery optimization. The last step is multi objective-multi refinery optimization, the objectives of which are analysis of the effects of economic, environmental, product spec, strategic, and catastrophic failure. Simulation runs were carried out using both MATLAB and ASPEN PIMS utilizing nonlinear techniques to solve the optimization problem. The results addressed the need to debottleneck some refineries or transportation media in order to meet the demand for essential products under partial or total failure scenarios. They also addressed how importing some high spec products can help recover some of the losses and what is needed in order to accomplish this. In addition, the results showed nonlinear relations among local and global objectives for some refineries. The results demonstrate that refineries can have a local multi objective optimum that does not follow the same trends as either global or local single objective optimums. Catastrophic failure effects on refinery operations and on local objectives are more significant than environmental objective effects, and changes in the capacity or the local objectives follow a discrete behavioral pattern, in contrast to environmental objective cases in which the effects are smoother. (Abstract shortened by UMI.)

Design and Experimental Implementation of Optimal Spacecraft Antenna Slews

DTIC Science & Technology

2013-12-01

LINK PENDULUM MODEL ............................................................58  C.  AZIMUTH-ELEVATION SYSTEM...BOUNDARY VALUE PROBLEM ......................77  B.  DOUBLE PENDULUM EXAMPLE............................................................82  C.  SOLVING THE...Figure 15.  Two-link Pendulum .........................................................................................58  Figure 16.  Double

Locality-Conscious Lock-Free Linked Lists

NASA Astrophysics Data System (ADS)

Braginsky, Anastasia; Petrank, Erez

We extend state-of-the-art lock-free linked lists by building linked lists with special care for locality of traversals. These linked lists are built of sequences of entries that reside on consecutive chunks of memory. When traversing such lists, subsequent entries typically reside on the same chunk and are thus close to each other, e.g., in same cache line or on the same virtual memory page. Such cache-conscious implementations of linked lists are frequently used in practice, but making them lock-free requires care. The basic component of this construction is a chunk of entries in the list that maintains a minimum and a maximum number of entries. This basic chunk component is an interesting tool on its own and may be used to build other lock-free data structures as well.

Rainfall-triggered shallow landslides at catchment scale: Threshold mechanics-based modeling for abruptness and localization

NASA Astrophysics Data System (ADS)

von Ruette, J.; Lehmann, P.; Or, D.

2013-10-01

Rainfall-induced shallow landslides may occur abruptly without distinct precursors and could span a wide range of soil mass released during a triggering event. We present a rainfall-induced landslide-triggering model for steep catchments with surfaces represented as an assembly of hydrologically and mechanically interconnected soil columns. The abruptness of failure was captured by defining local strength thresholds for mechanical bonds linking soil and bedrock and adjacent columns, whereby a failure of a single bond may initiate a chain reaction of subsequent failures, culminating in local mass release (a landslide). The catchment-scale hydromechanical landslide-triggering model (CHLT) was applied to results from two event-based landslide inventories triggered by two rainfall events in 2002 and 2005 in two nearby catchments located in the Prealps in Switzerland. Rainfall radar data, surface elevation and vegetation maps, and a soil production model for soil depth distribution were used for hydromechanical modeling of failure patterns for the two rainfall events at spatial and temporal resolutions of 2.5 m and 0.02 h, respectively. The CHLT model enabled systematic evaluation of the effects of soil type, mechanical reinforcement (soil cohesion and lateral root strength), and initial soil water content on landslide characteristics. We compared various landslide metrics and spatial distribution of simulated landslides in subcatchments with observed inventory data. Model parameters were optimized for the short but intense rainfall event in 2002, and the calibrated model was then applied for the 2005 rainfall, yielding reasonable predictions of landslide events and volumes and statistically reproducing localized landslide patterns similar to inventory data. The model provides a means for identifying local hot spots and offers insights into the dynamics of locally resolved landslide hazards in mountainous regions.

Image segmentation using local shape and gray-level appearance models

NASA Astrophysics Data System (ADS)

Seghers, Dieter; Loeckx, Dirk; Maes, Frederik; Suetens, Paul

2006-03-01

A new generic model-based segmentation scheme is presented, which can be trained from examples akin to the Active Shape Model (ASM) approach in order to acquire knowledge about the shape to be segmented and about the gray-level appearance of the object in the image. Because in the ASM approach the intensity and shape models are typically applied alternately during optimizing as first an optimal target location is selected for each landmark separately based on local gray-level appearance information only to which the shape model is fitted subsequently, the ASM may be misled in case of wrongly selected landmark locations. Instead, the proposed approach optimizes for shape and intensity characteristics simultaneously. Local gray-level appearance information at the landmark points extracted from feature images is used to automatically detect a number of plausible candidate locations for each landmark. The shape information is described by multiple landmark-specific statistical models that capture local dependencies between adjacent landmarks on the shape. The shape and intensity models are combined in a single cost function that is optimized non-iteratively using dynamic programming which allows to find the optimal landmark positions using combined shape and intensity information, without the need for initialization.

Uncovering the Links between Prospective Teachers' Personal Responsibility, Academic Optimism, Hope, and Emotions about Teaching: A Mediation Analysis

ERIC Educational Resources Information Center

Eren, Altay

2014-01-01

Prospective teachers' sense of personal responsibility has not been examined together with their academic optimism, hope, and emotions about teaching in a single study to date. However, to consider hope, academic optimism, and emotions about teaching together with personal responsibility is important to uncover the factors affecting…

Knowledge-Based Topic Model for Unsupervised Object Discovery and Localization.

PubMed

Niu, Zhenxing; Hua, Gang; Wang, Le; Gao, Xinbo

Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.

Connecting science, policy, and implementation for landscape-scale habitat connectivity.

PubMed

Brodie, Jedediah F; Paxton, Midori; Nagulendran, Kangayatkarasu; Balamurugan, G; Clements, Gopalasamy Reuben; Reynolds, Glen; Jain, Anuj; Hon, Jason

2016-10-01

We examined the links between the science and policy of habitat corridors to better understand how corridors can be implemented effectively. As a case study, we focused on a suite of landscape-scale connectivity plans in tropical and subtropical Asia (Malaysia, Singapore, and Bhutan). The process of corridor designation may be more efficient if the scientific determination of optimal corridor locations and arrangement is synchronized in time with political buy-in and establishment of policies to create corridors. Land tenure and the intactness of existing habitat in the region are also important to consider because optimal connectivity strategies may be very different if there are few, versus many, political jurisdictions (including commercial and traditional land tenures) and intact versus degraded habitat between patches. Novel financing mechanisms for corridors include bed taxes, payments for ecosystem services, and strategic forest certifications. Gaps in knowledge of effective corridor design include an understanding of how corridors, particularly those managed by local communities, can be protected from degradation and unsustainable hunting. There is a critical need for quantitative, data-driven models that can be used to prioritize potential corridors or multicorridor networks based on their relative contributions to long-term metacommunity persistence. © 2016 Society for Conservation Biology.

Maintained Individual Data Distributed Likelihood Estimation (MIDDLE)

PubMed Central

Boker, Steven M.; Brick, Timothy R.; Pritikin, Joshua N.; Wang, Yang; von Oertzen, Timo; Brown, Donald; Lach, John; Estabrook, Ryne; Hunter, Michael D.; Maes, Hermine H.; Neale, Michael C.

2015-01-01

Maintained Individual Data Distributed Likelihood Estimation (MIDDLE) is a novel paradigm for research in the behavioral, social, and health sciences. The MIDDLE approach is based on the seemingly-impossible idea that data can be privately maintained by participants and never revealed to researchers, while still enabling statistical models to be fit and scientific hypotheses tested. MIDDLE rests on the assumption that participant data should belong to, be controlled by, and remain in the possession of the participants themselves. Distributed likelihood estimation refers to fitting statistical models by sending an objective function and vector of parameters to each participants’ personal device (e.g., smartphone, tablet, computer), where the likelihood of that individual’s data is calculated locally. Only the likelihood value is returned to the central optimizer. The optimizer aggregates likelihood values from responding participants and chooses new vectors of parameters until the model converges. A MIDDLE study provides significantly greater privacy for participants, automatic management of opt-in and opt-out consent, lower cost for the researcher and funding institute, and faster determination of results. Furthermore, if a participant opts into several studies simultaneously and opts into data sharing, these studies automatically have access to individual-level longitudinal data linked across all studies. PMID:26717128

Optimization of WAVE2 complex–induced actin polymerization by membrane-bound IRSp53, PIP3, and Rac

PubMed Central

Suetsugu, Shiro; Kurisu, Shusaku; Oikawa, Tsukasa; Yamazaki, Daisuke; Oda, Atsushi; Takenawa, Tadaomi

2006-01-01

WAVE2 activates the actin-related protein (Arp) 2/3 complex for Rac-induced actin polymerization during lamellipodium formation and exists as a large WAVE2 protein complex with Sra1/PIR121, Nap1, Abi1, and HSPC300. IRSp53 binds to both Rac and Cdc42 and is proposed to link Rac to WAVE2. We found that the knockdown of IRSp53 by RNA interference decreased lamellipodium formation without a decrease in the amount of WAVE2 complex. Localization of WAVE2 at the cell periphery was retained in IRSp53 knockdown cells. Moreover, activated Cdc42 but not Rac weakened the association between WAVE2 and IRSp53. When we measured Arp2/3 activation in vitro, the WAVE2 complex isolated from the membrane fraction of cells was fully active in an IRSp53-dependent manner but WAVE2 isolated from the cytosol was not. Purified WAVE2 and purified WAVE2 complex were activated by IRSp53 in a Rac-dependent manner with PIP3-containing liposomes. Therefore, IRSp53 optimizes the activity of the WAVE2 complex in the presence of activated Rac and PIP3. PMID:16702231

Optimization of WAVE2 complex-induced actin polymerization by membrane-bound IRSp53, PIP(3), and Rac.

PubMed

Suetsugu, Shiro; Kurisu, Shusaku; Oikawa, Tsukasa; Yamazaki, Daisuke; Oda, Atsushi; Takenawa, Tadaomi

2006-05-22

WAVE2 activates the actin-related protein (Arp) 2/3 complex for Rac-induced actin polymerization during lamellipodium formation and exists as a large WAVE2 protein complex with Sra1/PIR121, Nap1, Abi1, and HSPC300. IRSp53 binds to both Rac and Cdc42 and is proposed to link Rac to WAVE2. We found that the knockdown of IRSp53 by RNA interference decreased lamellipodium formation without a decrease in the amount of WAVE2 complex. Localization of WAVE2 at the cell periphery was retained in IRSp53 knockdown cells. Moreover, activated Cdc42 but not Rac weakened the association between WAVE2 and IRSp53. When we measured Arp2/3 activation in vitro, the WAVE2 complex isolated from the membrane fraction of cells was fully active in an IRSp53-dependent manner but WAVE2 isolated from the cytosol was not. Purified WAVE2 and purified WAVE2 complex were activated by IRSp53 in a Rac-dependent manner with PIP(3)-containing liposomes. Therefore, IRSp53 optimizes the activity of the WAVE2 complex in the presence of activated Rac and PIP(3).

Optimization of the propulsion for multistage solid rocket motor launchers

NASA Astrophysics Data System (ADS)

Calabro, M.; Dufour, A.; Macaire, A.

2002-02-01

Some tools focused on a rapid multidisciplinary optimization capability for multistage launch vehicle design were developed at EADS-LV. These tools may be broken down into two categories, those related to propulsion design optimization and a computer code devoted to trajectories and under constraints optimization. Both are linked in order to obtain optimal vehicle design after an iterative process. After a description of the two categories tools, an example of application is given on a small space launcher.

Portfolio selection and asset pricing under a benchmark approach

NASA Astrophysics Data System (ADS)

Platen, Eckhard

2006-10-01

The paper presents classical and new results on portfolio optimization, as well as the fair pricing concept for derivative pricing under the benchmark approach. The growth optimal portfolio is shown to be a central object in a market model. It links asset pricing and portfolio optimization. The paper argues that the market portfolio is a proxy of the growth optimal portfolio. By choosing the drift of the discounted growth optimal portfolio as parameter process, one obtains a realistic theoretical market dynamics.

A Memetic Algorithm for Global Optimization of Multimodal Nonseparable Problems.

PubMed

Zhang, Geng; Li, Yangmin

2016-06-01

It is a big challenging issue of avoiding falling into local optimum especially when facing high-dimensional nonseparable problems where the interdependencies among vector elements are unknown. In order to improve the performance of optimization algorithm, a novel memetic algorithm (MA) called cooperative particle swarm optimizer-modified harmony search (CPSO-MHS) is proposed in this paper, where the CPSO is used for local search and the MHS for global search. The CPSO, as a local search method, uses 1-D swarm to search each dimension separately and thus converges fast. Besides, it can obtain global optimum elements according to our experimental results and analyses. MHS implements the global search by recombining different vector elements and extracting global optimum elements. The interaction between local search and global search creates a set of local search zones, where global optimum elements reside within the search space. The CPSO-MHS algorithm is tested and compared with seven other optimization algorithms on a set of 28 standard benchmarks. Meanwhile, some MAs are also compared according to the results derived directly from their corresponding references. The experimental results demonstrate a good performance of the proposed CPSO-MHS algorithm in solving multimodal nonseparable problems.

Georeferenced model simulations efficiently support targeted monitoring

NASA Astrophysics Data System (ADS)

Berlekamp, Jürgen; Klasmeier, Jörg

2010-05-01

The European Water Framework Directive (WFD) demands the good ecological and chemical status of surface waters. To meet the definition of good chemical status of the WFD surface water concentrations of priority pollutants must not exceed established environmental quality standards (EQS). Surveillance of the concentrations of numerous chemical pollutants in whole river basins by monitoring is laborious and time-consuming. Moreover, measured data do often not allow for immediate source apportionment which is a prerequisite for defining promising reduction strategies to be implemented within the programme of measures. In this context, spatially explicit model approaches are highly advantageous because they provide a direct link between local point emissions (e.g. treated wastewater) or diffuse non-point emissions (e.g. agricultural runoff) and resulting surface water concentrations. Scenario analyses with such models allow for a priori investigation of potential positive effects of reduction measures such as optimization of wastewater treatment. The geo-referenced model GREAT-ER (Geography-referenced Regional Exposure Assessment Tool for European Rivers) has been designed to calculate spatially resolved averaged concentrations for different flow conditions (e.g. mean or low flow) based on emission estimations for local point source emissions such as treated effluents from wastewater treatment plants. The methodology was applied to selected pharmaceuticals (diclofenac, sotalol, metoprolol, carbamazepin) in the Main river basin in Germany (approx. 27,290 km²). Average concentrations of the compounds were calculated for each river reach in the whole catchment. Simulation results were evaluated by comparison with available data from orienting monitoring and used to develop an optimal monitoring strategy for the assessment of water quality regarding micropollutants at the catchment scale.

Supermarket access, transport mode and BMI: the potential for urban design and planning policy across socio-economic areas.

PubMed

Murphy, Maureen; Koohsari, Mohammad Javad; Badland, Hannah; Giles-Corti, Billie

2017-12-01

To investigate dietary intake, BMI and supermarket access at varying geographic scales and transport modes across areas of socio-economic disadvantage, and to evaluate the implementation of an urban planning policy that provides guidance on spatial access to supermarkets. Cross-sectional study used generalised estimating equations to investigate associations between supermarket density and proximity, vegetable and fruit intake and BMI at five geographic scales representing distances people travel to purchase food by varying transport modes. A stratified analysis by area-level disadvantage was conducted to detect optimal distances to supermarkets across socio-economic areas. Spatial distribution of supermarket and transport access was analysed using a geographic information system. Melbourne, Australia. Adults (n 3128) from twelve local government areas (LGA) across Melbourne. Supermarket access was protective of BMI for participants in high disadvantaged areas within 800 m (P=0·040) and 1000 m (P=0·032) road network buffers around the household but not for participants in less disadvantaged areas. In urban growth area LGA, only 26 % of dwellings were within 1 km of a supermarket, far less than 80-90 % of dwellings suggested in the local urban planning policy. Low public transport access compounded disadvantage. Rapid urbanisation is a global health challenge linked to increases in dietary risk factors and BMI. Our findings highlight the importance of identifying the most appropriate geographic scale to inform urban planning policy for optimal health outcomes across socio-economic strata. Urban planning policy implementation in disadvantaged areas within cities has potential for reducing health inequities.

Optimal habits can develop spontaneously through sensitivity to local cost

PubMed Central

Desrochers, Theresa M.; Jin, Dezhe Z.; Goodman, Noah D.; Graybiel, Ann M.

2010-01-01

Habits and rituals are expressed universally across animal species. These behaviors are advantageous in allowing sequential behaviors to be performed without cognitive overload, and appear to rely on neural circuits that are relatively benign but vulnerable to takeover by extreme contexts, neuropsychiatric sequelae, and processes leading to addiction. Reinforcement learning (RL) is thought to underlie the formation of optimal habits. However, this theoretic formulation has principally been tested experimentally in simple stimulus-response tasks with relatively few available responses. We asked whether RL could also account for the emergence of habitual action sequences in realistically complex situations in which no repetitive stimulus-response links were present and in which many response options were present. We exposed naïve macaque monkeys to such experimental conditions by introducing a unique free saccade scan task. Despite the highly uncertain conditions and no instruction, the monkeys developed a succession of stereotypical, self-chosen saccade sequence patterns. Remarkably, these continued to morph for months, long after session-averaged reward and cost (eye movement distance) reached asymptote. Prima facie, these continued behavioral changes appeared to challenge RL. However, trial-by-trial analysis showed that pattern changes on adjacent trials were predicted by lowered cost, and RL simulations that reduced the cost reproduced the monkeys’ behavior. Ultimately, the patterns settled into stereotypical saccade sequences that minimized the cost of obtaining the reward on average. These findings suggest that brain mechanisms underlying the emergence of habits, and perhaps unwanted repetitive behaviors in clinical disorders, could follow RL algorithms capturing extremely local explore/exploit tradeoffs. PMID:20974967

Joint global optimization of tomographic data based on particle swarm optimization and decision theory

NASA Astrophysics Data System (ADS)

Paasche, H.; Tronicke, J.

2012-04-01

In many near surface geophysical applications multiple tomographic data sets are routinely acquired to explore subsurface structures and parameters. Linking the model generation process of multi-method geophysical data sets can significantly reduce ambiguities in geophysical data analysis and model interpretation. Most geophysical inversion approaches rely on local search optimization methods used to find an optimal model in the vicinity of a user-given starting model. The final solution may critically depend on the initial model. Alternatively, global optimization (GO) methods have been used to invert geophysical data. They explore the solution space in more detail and determine the optimal model independently from the starting model. Additionally, they can be used to find sets of optimal models allowing a further analysis of model parameter uncertainties. Here we employ particle swarm optimization (PSO) to realize the global optimization of tomographic data. PSO is an emergent methods based on swarm intelligence characterized by fast and robust convergence towards optimal solutions. The fundamental principle of PSO is inspired by nature, since the algorithm mimics the behavior of a flock of birds searching food in a search space. In PSO, a number of particles cruise a multi-dimensional solution space striving to find optimal model solutions explaining the acquired data. The particles communicate their positions and success and direct their movement according to the position of the currently most successful particle of the swarm. The success of a particle, i.e. the quality of the currently found model by a particle, must be uniquely quantifiable to identify the swarm leader. When jointly inverting disparate data sets, the optimization solution has to satisfy multiple optimization objectives, at least one for each data set. Unique determination of the most successful particle currently leading the swarm is not possible. Instead, only statements about the Pareto optimality of the found solutions can be made. Identification of the leading particle traditionally requires a costly combination of ranking and niching techniques. In our approach, we use a decision rule under uncertainty to identify the currently leading particle of the swarm. In doing so, we consider the different objectives of our optimization problem as competing agents with partially conflicting interests. Analysis of the maximin fitness function allows for robust and cheap identification of the currently leading particle. The final optimization result comprises a set of possible models spread along the Pareto front. For convex Pareto fronts, solution density is expected to be maximal in the region ideally compromising all objectives, i.e. the region of highest curvature.

Optimizing Linked Perceptual Class Formation and Transfer of Function

ERIC Educational Resources Information Center

Fields, Lanny; Garruto, Michelle

2009-01-01

A linked perceptual class consists of two distinct perceptual classes, A' and B', the members of which have become related to each other. For example, a linked perceptual class might be composed of many pictures of a woman (one perceptual class) and the sounds of that woman's voice (the other perceptual class). In this case, any sound of the…

Improving local clustering based top-L link prediction methods via asymmetric link clustering information

NASA Astrophysics Data System (ADS)

Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

2018-02-01

Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

Links between Local Language Competence and Peer Relations among Swiss and Immigrant Children: The Mediating Role of Social Behavior

ERIC Educational Resources Information Center

von Grunigen, Renate; Kochenderfer-Ladd, Becky; Perren, Sonja; Alsaker, Francoise D.

2012-01-01

The primary aim of this investigation was to evaluate a model in which children's social behaviors, including prosocial behavior, setting limits, and social withdrawal, were hypothesized to mediate the links between local language competence (LLC) and peer acceptance and victimization. Longitudinal data were collected via teacher and peer reports…

Optimization of immunohistochemical and fluorescent antibody techniques for localization of foot-and-mouth disease virus in animal tissues

USDA-ARS?s Scientific Manuscript database

Immunohistochemical (IHC) and immunofluorescent (IF) techniques were optimized for the detection of foot-and-mouth disease virus (FMDV) structural and non-structural proteins in frozen and paraformaldehyde-fixed paraffin embedded (PFPE) tissues of bovine and porcine origin. Immunohistochemical local...

DNA unwinding produced by site-specific intrastrand cross-links of the antitumor drug cis-diamminedichloroplatinum(II)

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

Bellon, S.F.; Coleman, J.H.; Lippard, S.J.

The DNA unwinding produced by specific adducts of the antitumor drug cis-diamminedi-chloroplatinum(II) has been quantitatively determined. Synthetic DNA duplex oligonucleotides of varying lengths with two base pair cohesive ends were synthesized and characterized that contained site-specific intrastrand N7-purine/N7-purine cross-links. Included are cis-(Pt(NH{sub 3}){sub 2}(d(GpG))), cis-(Pt(NH){sub 3}{sub 2}(d(ApG))), and cis-(Pt(NH{sub 3}){sub 2}(d(GpTpG))) adducts, respectively referred to as cis-GG, cis-AG, and cis-GTG. Local DNA distortions at the site of platination were amplified by polymerization of these monomers and quantitatively evaluated by using polyacrylamide gel electrophoresis. The extent of DNA unwinding was determined by systematically varying the interplatinum distance, or phasing, in polymersmore » containing the adducts. The multimer that migrates most slowly gives the optimal phasing for cooperative bending, from which the degree of unwinding can be obtained. The authors find that the cis-GG and cis-AG adducts both unwind DNA by 13{degrees}, while the cis-GTG adduct unwinds DNA by 23{degrees}. In addition, experiments are presented that support previous studies revealing that a hinge joint forms at the sites of platination in DNA molecules containing trans-GTG adducts. On the basis of an analysis of the present and other published studies of site-specifically modified DNA. The authors propose that local duplex unwinding is a major determinant in the recognition of DNA damage by the Escherichia coli (A)BC excinuclease. In addition, local duplex unwinding of 13{degrees} and bending by 35{degrees} are shown to correlate well with the recognition of platinated DNA by a previously identified damage recognition protein (DRP) in human cells.« less

Linking Local Scale Ecosystem Science to Regional Scale Management

NASA Astrophysics Data System (ADS)

Shope, C. L.; Tenhunen, J.; Peiffer, S.

2012-04-01

Ecosystem management with respect to sufficient water yield, a quality water supply, habitat and biodiversity conservation, and climate change effects requires substantial observational data at a range of scales. Complex interactions of local physical processes oftentimes vary over space and time, particularly in locations with extreme meteorological conditions. Modifications to local conditions (ie: agricultural land use changes, nutrient additions, landscape management, water usage) can further affect regional ecosystem services. The international, inter-disciplinary TERRECO research group is intensively investigating a variety of local processes, parameters, and conditions to link complex physical, economic, and social interactions at the regional scale. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. The data are used to parameterize suite of models describing local to landscape level water, sediment, nutrient, and monetary relationships. We focus on using the agricultural and hydrological SWAT model to synthesize the experimental field data and local-scale models throughout the catchment. The approach of our study was to describe local scientific processes, link potential interrelationships between different processes, and predict environmentally efficient management efforts. The Haean catchment case study shows how research can be structured to provide cross-disciplinary scientific linkages describing complex ecosystems and landscapes that can be used for regional management evaluations and predictions.

Multi-objective optimization of piezoelectric circuitry network for mode delocalization and suppression of bladed disk

NASA Astrophysics Data System (ADS)

Yoo, David; Tang, J.

2017-04-01

Since weakly-coupled bladed disks are highly sensitive to the presence of uncertainties, they can easily undergo vibration localization. When vibration localization occurs, vibration modes of bladed disk become dramatically different from those under the perfectly periodic condition, and the dynamic response under engine-order excitation is drastically amplified. In previous studies, it is investigated that amplified vibration response can be suppressed by connecting piezoelectric circuitry into individual blades to induce the damped absorber effect, and localized vibration modes can be alleviated by integrating piezoelectric circuitry network. Delocalization of vibration modes and vibration suppression of bladed disk, however, require different optimal set of circuit parameters. In this research, multi-objective optimization approach is developed to enable finding the best circuit parameters, simultaneously achieving both objectives. In this way, the robustness and reliability in bladed disk can be ensured. Gradient-based optimizations are individually developed for mode delocalization and vibration suppression, which are then integrated into multi-objective optimization framework.

Understanding and mimicking the dual optimality of the fly ear

NASA Astrophysics Data System (ADS)

Liu, Haijun; Currano, Luke; Gee, Danny; Helms, Tristan; Yu, Miao

2013-08-01

The fly Ormia ochracea has the remarkable ability, given an eardrum separation of only 520 μm, to pinpoint the 5 kHz chirp of its cricket host. Previous research showed that the two eardrums are mechanically coupled, which amplifies the directional cues. We have now performed a mechanics and optimization analysis which reveals that the right coupling strength is key: it results in simultaneously optimized directional sensitivity and directional cue linearity at 5 kHz. We next demonstrated that this dual optimality is replicable in a synthetic device and can be tailored for a desired frequency. Finally, we demonstrated a miniature sensor endowed with this dual-optimality at 8 kHz with unparalleled sound localization. This work provides a quantitative and mechanistic explanation for the fly's sound-localization ability from a new perspective, and it provides a framework for the development of fly-ear inspired sensors to overcoming a previously-insurmountable size constraint in engineered sound-localization systems.

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.

Analytic Optimization of Near-Field Optical Chirality Enhancement

PubMed Central

2017-01-01

We present an analytic derivation for the enhancement of local optical chirality in the near field of plasmonic nanostructures by tuning the far-field polarization of external light. We illustrate the results by means of simulations with an achiral and a chiral nanostructure assembly and demonstrate that local optical chirality is significantly enhanced with respect to circular polarization in free space. The optimal external far-field polarizations are different from both circular and linear. Symmetry properties of the nanostructure can be exploited to determine whether the optimal far-field polarization is circular. Furthermore, the optimal far-field polarization depends on the frequency, which results in complex-shaped laser pulses for broadband optimization. PMID:28239617

Groundwater Pollution Source Identification using Linked ANN-Optimization Model

NASA Astrophysics Data System (ADS)

Ayaz, Md; Srivastava, Rajesh; Jain, Ashu

2014-05-01

Groundwater is the principal source of drinking water in several parts of the world. Contamination of groundwater has become a serious health and environmental problem today. Human activities including industrial and agricultural activities are generally responsible for this contamination. Identification of groundwater pollution source is a major step in groundwater pollution remediation. Complete knowledge of pollution source in terms of its source characteristics is essential to adopt an effective remediation strategy. Groundwater pollution source is said to be identified completely when the source characteristics - location, strength and release period - are known. Identification of unknown groundwater pollution source is an ill-posed inverse problem. It becomes more difficult for real field conditions, when the lag time between the first reading at observation well and the time at which the source becomes active is not known. We developed a linked ANN-Optimization model for complete identification of an unknown groundwater pollution source. The model comprises two parts- an optimization model and an ANN model. Decision variables of linked ANN-Optimization model contain source location and release period of pollution source. An objective function is formulated using the spatial and temporal data of observed and simulated concentrations, and then minimized to identify the pollution source parameters. In the formulation of the objective function, we require the lag time which is not known. An ANN model with one hidden layer is trained using Levenberg-Marquardt algorithm to find the lag time. Different combinations of source locations and release periods are used as inputs and lag time is obtained as the output. Performance of the proposed model is evaluated for two and three dimensional case with error-free and erroneous data. Erroneous data was generated by adding uniformly distributed random error (error level 0-10%) to the analytically computed concentration values. The main advantage of the proposed model is that it requires only upper half of the breakthrough curve and is capable of predicting source parameters when the lag time is not known. Linking of ANN model with proposed optimization model reduces the dimensionality of the decision variables of the optimization model by one and hence complexity of optimization model is reduced. The results show that our proposed linked ANN-Optimization model is able to predict the source parameters for the error-free data accurately. The proposed model was run several times to obtain the mean, standard deviation and interval estimate of the predicted parameters for observations with random measurement errors. It was observed that mean values as predicted by the model were quite close to the exact values. An increasing trend was observed in the standard deviation of the predicted values with increasing level of measurement error. The model appears to be robust and may be efficiently utilized to solve the inverse pollution source identification problem.

Concurrent hypercube system with improved message passing

NASA Technical Reports Server (NTRS)

Peterson, John C. (Inventor); Tuazon, Jesus O. (Inventor); Lieberman, Don (Inventor); Pniel, Moshe (Inventor)

1989-01-01

A network of microprocessors, or nodes, are interconnected in an n-dimensional cube having bidirectional communication links along the edges of the n-dimensional cube. Each node's processor network includes an I/O subprocessor dedicated to controlling communication of message packets along a bidirectional communication link with each end thereof terminating at an I/O controlled transceiver. Transmit data lines are directly connected from a local FIFO through each node's communication link transceiver. Status and control signals from the neighboring nodes are delivered over supervisory lines to inform the local node that the neighbor node's FIFO is empty and the bidirectional link between the two nodes is idle for data communication. A clocking line between neighbors, clocks a message into an empty FIFO at a neighbor's node and vica versa. Either neighbor may acquire control over the bidirectional communication link at any time, and thus each node has circuitry for checking whether or not the communication link is busy or idle, and whether or not the receive FIFO is empty. Likewise, each node can empty its own FIFO and in turn deliver a status signal to a neighboring node indicating that the local FIFO is empty. The system includes features of automatic message rerouting, block message transfer and automatic parity checking and generation.

Andean rural children's views of the environment: A qualitative study

NASA Astrophysics Data System (ADS)

Maurial, Mahia

Andean rural children's drawings and narratives about their crops and the immediate biological environment are rich tools to understand local views of the environment. Children's drawings and narratives were collected and linked to interviews as well as participant observation gathered from parents, leaders and teachers. The research sites are the community of Willca and the school of Mayu. Fieldwork was completed in 1998. In the conceptual framework I distinguish between two dissimilar knowledges, school knowledge and local knowledge. These knowledges produce two dissimilar views of the environment. I further analyze relationships of knowledge and power and argue that school knowledge overpowers local knowledge. Concomitantly, I studied set of ideas associated with two knowledges aforementioned: superacion (surpass) and regeneration (Apffel-Marglin 1995). Although these ideas coexist in peoples' minds they are not linked or effectively connected. In order to link local knowledge and school knowledge together, I propose the integration of environmental studies and art education to enhance a local sense of place (Blandy et. al 1993) in Andean and other schools. This will contribute to grassroots educational policy.

The role of health promotion: between global thinking and local action.

PubMed

King, Lesley

2006-12-01

The persistence of health inequities provides an ongoing challenge for health promotion. The dictum 'think globally, act locally' fails to recognise the significance of infrastructure and policy in linking global issues and local practices as a means of addressing health inequities. Commentary and opinion. Through analytic tools and methods, health promotion has much to contribute to facilitating health-improving changes in social, economic and physical environments. Local actions provide excellent illustrations of organisational change and intersectoral action, and present the possibility that such actions could be widely implemented. While this has occurred on some issues, this is not usually the case. Political support, policy and infrastructure are required to link global ideas and local actions and overcome the impasse. Media advocacy is one example of an approach with potential to make these links and mobilise political support. Reframing media and political discussion, away from the dichotomy of individual responsibility and government intervention and towards acknowledging the social context of human behaviour, could contribute to policy and social environments with greater capacity to address inequities.

Local production of medical technologies and its effect on access in low and middle income countries: a systematic review of the literature

PubMed Central

Kaplan, Warren Allan; Ritz, Lindsay Sarah; Vitello, Marie

2011-01-01

Objectives: The objective of this study was to assess the existing theoretical and empirical literature examining the link between "local production" of pharmaceuticals and medical devices and increased local access to these products. Our preliminary hypothesis is that studies showing a robust relationship between local production and access to medical products are sparse, at best. Methods: An extensive literature search was conducted using a wide variety of databases and search terms intending to capture as many different aspects of this issue as possible. The results of the search were reviewed and categorized according to their relevance to the research question. The literature was also reviewed to determine the rigor used to examine the effects of local production and what implications these experiences hold for other developing countries. Results: Literature addressing the benefits of local production and the link between it and access to medical products is sparse, mainly descriptive and lacking empirical evidence. Of the literature we reviewed that addressed comparative economics and strategic planning of multinational and domestic firms, there are few dealing with emerging markets and lower-middle income countries and even fewer that compare local biomedical producers with multinational corporations in terms of a reasonable metric. What comparisons exist mainly relate to prices of local versus foreign/multinational produced medicines. Conclusions: An assessment of the existing theoretical and empirical literature examining the link between "local production" of pharmaceuticals and medical devices and increased local access to these products reveals a paucity of literature explicitly dealing with this issue. Of the literature that does exist, methods used to date are insufficient to prove a robust relationship between local production of medical products and access to these products. There are mixed messages from various studies, and although the studies may correctly depict specific situations in specific countries with reference to specific products, such evidence cannot be generalized. Our review strongly supports the need for further research in understanding the dynamic link between local production and access to medical products PMID:23093883

On Optimizing the Configuration of Time-Transfer Links Used to Generate TAI

DTIC Science & Technology

2007-01-01

TAI be generated through combinations of Two Way Satellite Time and Frequency Transfer ( TWSTFT ) links and GPS links. It is assumed that Study Group I...the lack of low-noise connectivity between the Asian and American-European TWSTFT links may require two pivot sites instead of one. We recommend...band Two Way Satellite Time and Frequency Transfer ( TWSTFT ), and X-band TWSTFT [1]. In order to improve TAI-generation, the BIPM Time Section asked

Efficiency optimization of class-D biomedical inductive wireless power transfer systems by means of frequency adjustment.

PubMed

Schormans, Matthew; Valente, Virgilio; Demosthenous, Andreas

2015-01-01

Inductive powering for implanted medical devices is a commonly employed technique, that allows for implants to avoid more dangerous methods such as the use of transcutaneous wires or implanted batteries. However, wireless powering in this way also comes with a number of difficulties and conflicting requirements, which are often met by using designs based on compromise. In particular, one aspect common to most inductive power links is that they are driven with a fixed frequency, which may not be optimal depending on factors such as coupling and load. In this paper, a method is proposed in which an inductive power link is driven by a frequency that is maintained at an optimum value f(opt), to ensure that the link is in resonance. In order to maintain this resonance, a phase tracking technique is employed at the primary side of the link; this allows for compensation of changes in coil separation and load. The technique is shown to provide significant improvements in maintained secondary voltage and efficiency for a range of loads when the link is overcoupled.

Multidimensional Optimization of Signal Space Distance Parameters in WLAN Positioning

PubMed Central

Brković, Milenko; Simić, Mirjana

2014-01-01

Accurate indoor localization of mobile users is one of the challenging problems of the last decade. Besides delivering high speed Internet, Wireless Local Area Network (WLAN) can be used as an effective indoor positioning system, being competitive both in terms of accuracy and cost. Among the localization algorithms, nearest neighbor fingerprinting algorithms based on Received Signal Strength (RSS) parameter have been extensively studied as an inexpensive solution for delivering indoor Location Based Services (LBS). In this paper, we propose the optimization of the signal space distance parameters in order to improve precision of WLAN indoor positioning, based on nearest neighbor fingerprinting algorithms. Experiments in a real WLAN environment indicate that proposed optimization leads to substantial improvements of the localization accuracy. Our approach is conceptually simple, is easy to implement, and does not require any additional hardware. PMID:24757443

Time to Go Local!

MedlinePlus

... Bar Home Current Issue Past Issues Time to Go Local! Past Issues / Winter 2007 Table of Contents ... MedlinePlus.gov health topic pages, you will find "Go Local" links that take you to information about ...

Information flows in hierarchical networks and the capability of organizations to successfully respond to failures, crises, and disasters

NASA Astrophysics Data System (ADS)

Helbing, Dirk; Ammoser, Hendrik; Kühnert, Christian

2006-04-01

In this paper we discuss the problem of information losses in organizations and how they depend on the organization network structure. Hierarchical networks are an optimal organization structure only when the failure rate of nodes or links is negligible. Otherwise, redundant information links are important to reduce the risk of information losses and the related costs. However, as redundant information links are expensive, the optimal organization structure is not a fully connected one. It rather depends on the failure rate. We suggest that sidelinks and temporary, adaptive shortcuts can improve the information flows considerably by generating small-world effects. This calls for modified organization structures to cope with today's challenges of businesses and administrations, in particular, to successfully respond to crises or disasters.

Proposal for implementation of CCSDS standards for use with spacecraft engineering/housekeeping data

NASA Technical Reports Server (NTRS)

Welch, Dave

1994-01-01

Many of today's low earth orbiting spacecraft are using the Consultative Committee for Space Data Systems (CCSDS) protocol for better optimization of down link RF bandwidth and onboard storage space. However, most of the associated housekeeping data has continued to be generated and down linked in a synchronous, Time Division Multiplexed (TDM) fashion. There are many economies that the CCSDS protocol will allow to better utilize the available bandwidth and storage space in order to optimize the housekeeping data for use in operational trending and analysis work. By only outputting what is currently important or of interest, finer resolution of critical items can be obtained. This can be accomplished by better utilizing the normally allocated housekeeping data down link and storage areas rather than taking space reserved for science.

The Affective Core of Emotion: Linking Pleasure, Subjective Well-Being, and Optimal Metastability in the Brain

PubMed Central

Kringelbach, Morten L.; Berridge, Kent C.

2017-01-01

Arguably, emotion is always valenced—either pleasant or unpleasant—and dependent on the pleasure system. This system serves adaptive evolutionary functions; relying on separable wanting, liking, and learning neural mechanisms mediated by mesocorticolimbic networks driving pleasure cycles with appetitive, consummatory, and satiation phases. Liking is generated in a small set of discrete hedonic hotspots and coldspots, while wanting is linked to dopamine and to larger distributed brain networks. Breakdown of the pleasure system can lead to anhedonia and other features of affective disorders. Eudaimonia and well-being are difficult to study empirically, yet whole-brain computational models could offer novel insights (e.g., routes to eudaimonia such as caregiving of infants or music) potentially linking eudaimonia to optimal metastability in the pleasure system. PMID:28943891

Proposal for implementation of CCSDS standards for use with spacecraft engineering/housekeeping data

NASA Astrophysics Data System (ADS)

Welch, Dave

1994-11-01

Many of today's low earth orbiting spacecraft are using the Consultative Committee for Space Data Systems (CCSDS) protocol for better optimization of down link RF bandwidth and onboard storage space. However, most of the associated housekeeping data has continued to be generated and down linked in a synchronous, Time Division Multiplexed (TDM) fashion. There are many economies that the CCSDS protocol will allow to better utilize the available bandwidth and storage space in order to optimize the housekeeping data for use in operational trending and analysis work. By only outputting what is currently important or of interest, finer resolution of critical items can be obtained. This can be accomplished by better utilizing the normally allocated housekeeping data down link and storage areas rather than taking space reserved for science.

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.

Investigation of Natural Gas Fugitive Leak Detection Using an Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Yang, S.; Talbot, R. W.; Frish, M. B.; Golston, L.; Aubut, N. F.; Zondlo, M. A.

2017-12-01

The U.S is now the world's largest natural gas producer, of which methane (CH4) is the main component. About 2% of the CH4 is lost through fugitive leaks. This research is under the DOE Methane Observation Networks with Innovative Technology to Obtain Reductions (MONITOR) program of ARPA-E. Our sentry measurement system is composed of four state-of-the-art technologies centered around the RMLDTM (Remote Methane Leak Detector). An open path RMLDTM measures column-integrated CH4 concentration that incorporates fluctuations in the vertical CH4 distribution. Based on Backscatter Tunable Diode Laser Absorption Spectroscopy and Small Unmanned Aerial Vehicles, the sentry system can autonomously, consistently and cost-effectively monitor and quantify CH4 leakage from sites associated with natural gas production. This system provides an advanced capability in detecting leaks at hard-to-access sites (e.g., wellheads) compared to traditional manual methods. Automated leak detecting and reporting algorithms combined with wireless data link implement real-time leak information reporting. Early data were gathered to set up and test the prototype system, and to optimize the leak localization and calculation strategies. The flight pattern is based on a raster scan which can generate interpolated CH4 concentration maps. The localization and quantification algorithms can be derived from the plume images combined with wind vectors. Currently, the accuracy of localization algorithm can reach 2 m and the calculation algorithm has a factor of 2 accuracy. This study places particular emphasis on flux quantification. The data collected at Colorado and Houston test fields were processed, and the correlation between flux and other parameters analyzed. Higher wind speeds and lower wind variation are preferred to optimize flux estimation. Eventually, this system will supply an enhanced detection capability to significantly reduce fugitive CH4 emissions in the natural gas industry.

In vitro/in vivo characterization of nanoemulsion formulation of metronidazole with improved skin targeting and anti-rosacea properties.

PubMed

Yu, Meng; Ma, Huixian; Lei, Mingzhu; Li, Nan; Tan, Fengping

2014-09-01

Topical skin treatment was limited due to the lack of suitable delivery system with significant cutaneous localization and systemic safety. The aim of this study was to develop and optimize a nanoemulsion (NE) to enhance targeting localization of metronidazole (MTZ) in skin layers. In vitro studies were used to optimize NE formulations, and a series of experiments were carried in vitro and in vivo to validate the therapeutic efficacy of MTZ-loaded optimal NE. NE type selection and D-optimal design study were applied to optimize NE formulation with maximum skin retention and minimum skin penetration. Three formulation variables: Oil X1 (Labrafil), Smix X2 (a mixture of Cremophor EL/Tetraethylene glycol, 2:1 w/w) and water X3 were included in D-design. The system was assessed for skin retention Y1, cumulative MTZ amount after 24 h Y2 and droplet size Y3. Following optimization, the values of formulation components (X1, X2 and X3) were 4.13%, 16.42% and 79.45%, respectively. The optimized NE was assessed for viscosity, droplet size, morphological study and in vitro permeation in pig skin. Distributions of MTZ were validated by confocal laser scanning microscopy (CLSM). Active agent of NE transferred into deeper skin and localized in epidermal/dermal layers after 24 h, which showed significant advantages of the optimal NE over Gel. The skin targeting localization and minimal systemic escape of optimal NE was further proved by in vivo study on rat skin. Current in vitro-in vivo correlation (IVIVC) enabled the prediction of pharmacokinetic profile of MTZ from in vitro permeation results. Further, the in vivo anti-rosacea efficacy of optimal formulation was investigated by pharmacodynamics study on mice ear. Copyright © 2014 Elsevier B.V. All rights reserved.

Enhanced method of fast re-routing with load balancing in software-defined networks

NASA Astrophysics Data System (ADS)

Lemeshko, Oleksandr; Yeremenko, Oleksandra

2017-11-01

A two-level method of fast re-routing with load balancing in a software-defined network (SDN) is proposed. The novelty of the method consists, firstly, in the introduction of a two-level hierarchy of calculating the routing variables responsible for the formation of the primary and backup paths, and secondly, in ensuring a balanced load of the communication links of the network, which meets the requirements of the traffic engineering concept. The method provides implementation of link, node, path, and bandwidth protection schemes for fast re-routing in SDN. The separation in accordance with the interaction prediction principle along two hierarchical levels of the calculation functions of the primary (lower level) and backup (upper level) routes allowed to abandon the initial sufficiently large and nonlinear optimization problem by transiting to the iterative solution of linear optimization problems of half the dimension. The analysis of the proposed method confirmed its efficiency and effectiveness in terms of obtaining optimal solutions for ensuring balanced load of communication links and implementing the required network element protection schemes for fast re-routing in SDN.

Enantiomers Recognition of Propranolol Based on Organic-Inorganic Hybrid Open-Tubular MIPs-CEC Column Using 3-(Trimethoxysilyl)Propyl Methacrylate as a Cross-Linking Monomer.

PubMed

Chen, Guo-Ning; Li, Ning; Luo, Tian; Dong, Yu-Ming

2017-04-01

In this study, 3-(trimethoxysilyl)propyl methacrylate (γ-MPS), a bifunctional group compound, was used as a single cross-linking agent to prepare molecular imprinted inorganic-organic hybrid polymers by in situ polymerization for open-tubular capillary electro chromatography (CEC) column. The optimal preparation conditions were: the ratio between template molecule and functional monomer was 1:4; the volume proportion of porogen toluene and methanol was 1:1 and the volume of cross-linking agent γ-MPS was 69 μL. The optimal separation conditions were separation voltage of 15 kV; detection wavelength at 215 nm and background electrolyte composed of 70% acetonitrile/20 mmol/L boric acid salt (pH 6.9). Under the optimized conditions, the propranolol enantiomers can be separated well by CEC. The method is simple and fast, it can be a potentially useful approach for propranolol enantiomers separation. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Particle swarm optimization-based local entropy weighted histogram equalization for infrared image enhancement

NASA Astrophysics Data System (ADS)

Wan, Minjie; Gu, Guohua; Qian, Weixian; Ren, Kan; Chen, Qian; Maldague, Xavier

2018-06-01

Infrared image enhancement plays a significant role in intelligent urban surveillance systems for smart city applications. Unlike existing methods only exaggerating the global contrast, we propose a particle swam optimization-based local entropy weighted histogram equalization which involves the enhancement of both local details and fore-and background contrast. First of all, a novel local entropy weighted histogram depicting the distribution of detail information is calculated based on a modified hyperbolic tangent function. Then, the histogram is divided into two parts via a threshold maximizing the inter-class variance in order to improve the contrasts of foreground and background, respectively. To avoid over-enhancement and noise amplification, double plateau thresholds of the presented histogram are formulated by means of particle swarm optimization algorithm. Lastly, each sub-image is equalized independently according to the constrained sub-local entropy weighted histogram. Comparative experiments implemented on real infrared images prove that our algorithm outperforms other state-of-the-art methods in terms of both visual and quantized evaluations.

A quantum annealing architecture with all-to-all connectivity from local interactions.

PubMed

Lechner, Wolfgang; Hauke, Philipp; Zoller, Peter

2015-10-01

Quantum annealers are physical devices that aim at solving NP-complete optimization problems by exploiting quantum mechanics. The basic principle of quantum annealing is to encode the optimization problem in Ising interactions between quantum bits (qubits). A fundamental challenge in building a fully programmable quantum annealer is the competing requirements of full controllable all-to-all connectivity and the quasi-locality of the interactions between physical qubits. We present a scalable architecture with full connectivity, which can be implemented with local interactions only. The input of the optimization problem is encoded in local fields acting on an extended set of physical qubits. The output is-in the spirit of topological quantum memories-redundantly encoded in the physical qubits, resulting in an intrinsic fault tolerance. Our model can be understood as a lattice gauge theory, where long-range interactions are mediated by gauge constraints. The architecture can be realized on various platforms with local controllability, including superconducting qubits, NV-centers, quantum dots, and atomic systems.

A quantum annealing architecture with all-to-all connectivity from local interactions

PubMed Central

Lechner, Wolfgang; Hauke, Philipp; Zoller, Peter

2015-01-01

Quantum annealers are physical devices that aim at solving NP-complete optimization problems by exploiting quantum mechanics. The basic principle of quantum annealing is to encode the optimization problem in Ising interactions between quantum bits (qubits). A fundamental challenge in building a fully programmable quantum annealer is the competing requirements of full controllable all-to-all connectivity and the quasi-locality of the interactions between physical qubits. We present a scalable architecture with full connectivity, which can be implemented with local interactions only. The input of the optimization problem is encoded in local fields acting on an extended set of physical qubits. The output is—in the spirit of topological quantum memories—redundantly encoded in the physical qubits, resulting in an intrinsic fault tolerance. Our model can be understood as a lattice gauge theory, where long-range interactions are mediated by gauge constraints. The architecture can be realized on various platforms with local controllability, including superconducting qubits, NV-centers, quantum dots, and atomic systems. PMID:26601316

Small-Tip-Angle Spokes Pulse Design Using Interleaved Greedy and Local Optimization Methods

PubMed Central

Grissom, William A.; Khalighi, Mohammad-Mehdi; Sacolick, Laura I.; Rutt, Brian K.; Vogel, Mika W.

2013-01-01

Current spokes pulse design methods can be grouped into methods based either on sparse approximation or on iterative local (gradient descent-based) optimization of the transverse-plane spatial frequency locations visited by the spokes. These two classes of methods have complementary strengths and weaknesses: sparse approximation-based methods perform an efficient search over a large swath of candidate spatial frequency locations but most are incompatible with off-resonance compensation, multifrequency designs, and target phase relaxation, while local methods can accommodate off-resonance and target phase relaxation but are sensitive to initialization and suboptimal local cost function minima. This article introduces a method that interleaves local iterations, which optimize the radiofrequency pulses, target phase patterns, and spatial frequency locations, with a greedy method to choose new locations. Simulations and experiments at 3 and 7 T show that the method consistently produces single- and multifrequency spokes pulses with lower flip angle inhomogeneity compared to current methods. PMID:22392822

Adaptive behaviors in multi-agent source localization using passive sensing.

PubMed

Shaukat, Mansoor; Chitre, Mandar

2016-12-01

In this paper, the role of adaptive group cohesion in a cooperative multi-agent source localization problem is investigated. A distributed source localization algorithm is presented for a homogeneous team of simple agents. An agent uses a single sensor to sense the gradient and two sensors to sense its neighbors. The algorithm is a set of individualistic and social behaviors where the individualistic behavior is as simple as an agent keeping its previous heading and is not self-sufficient in localizing the source. Source localization is achieved as an emergent property through agent's adaptive interactions with the neighbors and the environment. Given a single agent is incapable of localizing the source, maintaining team connectivity at all times is crucial. Two simple temporal sampling behaviors, intensity-based-adaptation and connectivity-based-adaptation, ensure an efficient localization strategy with minimal agent breakaways. The agent behaviors are simultaneously optimized using a two phase evolutionary optimization process. The optimized behaviors are estimated with analytical models and the resulting collective behavior is validated against the agent's sensor and actuator noise, strong multi-path interference due to environment variability, initialization distance sensitivity and loss of source signal.

A Smart Wirelessly Powered Homecage for Long-Term High-Throughput Behavioral Experiments

PubMed Central

Lee, Byunghun; Kiani, Mehdi

2015-01-01

A wirelessly powered homecage system, called the EnerCage-HC, that is equipped with multicoil wireless power transfer, closed-loop power control, optical behavioral tracking, and a graphic user interface is presented for longitudinal electrophysiology and behavioral neuroscience experiments. The EnerCage-HC system can wirelessly power a mobile unit attached to a small animal subject and also track its behavior in real-time as it is housed inside a standard homecage. The EnerCage-HC system is equipped with one central and four overlapping slanted wire-wound coils with optimal geometries to form three- and four-coil power transmission links while operating at 13.56 MHz. Utilizing multicoil links increases the power transfer efficiency (PTE) compared with conventional two-coil links and also reduces the number of power amplifiers to only one, which significantly reduces the system complexity, cost, and heat dissipation. A Microsoft Kinect installed 90 cm above the homecage localizes the animal position and orientation with 1.6-cm accuracy. Moreover, a power management ASIC, including a high efficiency active rectifier and automatic coil resonance tuning, was fabricated in a 0.35-μm 4M2P standard CMOS process for the mobile unit. The EnerCage-HC achieves a max/min PTE of 36.3%/16.1% at the nominal height of 7 cm. In vivo experiments were conducted on freely behaving rats by continuously delivering 24 mW to the mobile unit for >7 h inside a standard homecage. PMID:26257586

Scalability enhancement of AODV using local link repairing

NASA Astrophysics Data System (ADS)

Jain, Jyoti; Gupta, Roopam; Bandhopadhyay, T. K.

2014-09-01

Dynamic change in the topology of an ad hoc network makes it difficult to design an efficient routing protocol. Scalability of an ad hoc network is also one of the important criteria of research in this field. Most of the research works in ad hoc network focus on routing and medium access protocols and produce simulation results for limited-size networks. Ad hoc on-demand distance vector (AODV) is one of the best reactive routing protocols. In this article, modified routing protocols based on local link repairing of AODV are proposed. Method of finding alternate routes for next-to-next node is proposed in case of link failure. These protocols are beacon-less, means periodic hello message is removed from the basic AODV to improve scalability. Few control packet formats have been changed to accommodate suggested modification. Proposed protocols are simulated to investigate scalability performance and compared with basic AODV protocol. This also proves that local link repairing of proposed protocol improves scalability of the network. From simulation results, it is clear that scalability performance of routing protocol is improved because of link repairing method. We have tested protocols for different terrain area with approximate constant node densities and different traffic load.

Local Feature Selection for Data Classification.

PubMed

Armanfard, Narges; Reilly, James P; Komeili, Majid

2016-06-01

Typical feature selection methods choose an optimal global feature subset that is applied over all regions of the sample space. In contrast, in this paper we propose a novel localized feature selection (LFS) approach whereby each region of the sample space is associated with its own distinct optimized feature set, which may vary both in membership and size across the sample space. This allows the feature set to optimally adapt to local variations in the sample space. An associated method for measuring the similarities of a query datum to each of the respective classes is also proposed. The proposed method makes no assumptions about the underlying structure of the samples; hence the method is insensitive to the distribution of the data over the sample space. The method is efficiently formulated as a linear programming optimization problem. Furthermore, we demonstrate the method is robust against the over-fitting problem. Experimental results on eleven synthetic and real-world data sets demonstrate the viability of the formulation and the effectiveness of the proposed algorithm. In addition we show several examples where localized feature selection produces better results than a global feature selection method.

Incremental social learning in particle swarms.

PubMed

de Oca, Marco A Montes; Stutzle, Thomas; Van den Enden, Ken; Dorigo, Marco

2011-04-01

Incremental social learning (ISL) was proposed as a way to improve the scalability of systems composed of multiple learning agents. In this paper, we show that ISL can be very useful to improve the performance of population-based optimization algorithms. Our study focuses on two particle swarm optimization (PSO) algorithms: a) the incremental particle swarm optimizer (IPSO), which is a PSO algorithm with a growing population size in which the initial position of new particles is biased toward the best-so-far solution, and b) the incremental particle swarm optimizer with local search (IPSOLS), in which solutions are further improved through a local search procedure. We first derive analytically the probability density function induced by the proposed initialization rule applied to new particles. Then, we compare the performance of IPSO and IPSOLS on a set of benchmark functions with that of other PSO algorithms (with and without local search) and a random restart local search algorithm. Finally, we measure the benefits of using incremental social learning on PSO algorithms by running IPSO and IPSOLS on problems with different fitness distance correlations.

Genetic particle swarm parallel algorithm analysis of optimization arrangement on mistuned blades

NASA Astrophysics Data System (ADS)

Zhao, Tianyu; Yuan, Huiqun; Yang, Wenjun; Sun, Huagang

2017-12-01

This article introduces a method of mistuned parameter identification which consists of static frequency testing of blades, dichotomy and finite element analysis. A lumped parameter model of an engine bladed-disc system is then set up. A bladed arrangement optimization method, namely the genetic particle swarm optimization algorithm, is presented. It consists of a discrete particle swarm optimization and a genetic algorithm. From this, the local and global search ability is introduced. CUDA-based co-evolution particle swarm optimization, using a graphics processing unit, is presented and its performance is analysed. The results show that using optimization results can reduce the amplitude and localization of the forced vibration response of a bladed-disc system, while optimization based on the CUDA framework can improve the computing speed. This method could provide support for engineering applications in terms of effectiveness and efficiency.

Linking knowledge and action through mental models of sustainable agriculture.

PubMed

Hoffman, Matthew; Lubell, Mark; Hillis, Vicken

2014-09-09

Linking knowledge to action requires understanding how decision-makers conceptualize sustainability. This paper empirically analyzes farmer "mental models" of sustainability from three winegrape-growing regions of California where local extension programs have focused on sustainable agriculture. The mental models are represented as networks where sustainability concepts are nodes, and links are established when a farmer mentions two concepts in their stated definition of sustainability. The results suggest that winegrape grower mental models of sustainability are hierarchically structured, relatively similar across regions, and strongly linked to participation in extension programs and adoption of sustainable farm practices. We discuss the implications of our findings for the debate over the meaning of sustainability, and the role of local extension programs in managing knowledge systems.

Linking knowledge and action through mental models of sustainable agriculture

PubMed Central

Hoffman, Matthew; Lubell, Mark; Hillis, Vicken

2014-01-01

Linking knowledge to action requires understanding how decision-makers conceptualize sustainability. This paper empirically analyzes farmer “mental models” of sustainability from three winegrape-growing regions of California where local extension programs have focused on sustainable agriculture. The mental models are represented as networks where sustainability concepts are nodes, and links are established when a farmer mentions two concepts in their stated definition of sustainability. The results suggest that winegrape grower mental models of sustainability are hierarchically structured, relatively similar across regions, and strongly linked to participation in extension programs and adoption of sustainable farm practices. We discuss the implications of our findings for the debate over the meaning of sustainability, and the role of local extension programs in managing knowledge systems. PMID:25157158

Optimal Design of Grid-Stiffened Panels and Shells With Variable Curvature

NASA Technical Reports Server (NTRS)

Ambur, Damodar R.; Jaunky, Navin

2001-01-01

A design strategy for optimal design of composite grid-stiffened structures with variable curvature subjected to global and local buckling constraints is developed using a discrete optimizer. An improved smeared stiffener theory is used for the global buckling analysis. Local buckling of skin segments is assessed using a Rayleigh-Ritz method that accounts for material anisotropy and transverse shear flexibility. The local buckling of stiffener segments is also assessed. Design variables are the axial and transverse stiffener spacing, stiffener height and thickness, skin laminate, and stiffening configuration. Stiffening configuration is herein defined as a design variable that indicates the combination of axial, transverse and diagonal stiffeners in the stiffened panel. The design optimization process is adapted to identify the lightest-weight stiffening configuration and stiffener spacing for grid-stiffened composite panels given the overall panel dimensions. in-plane design loads, material properties. and boundary conditions of the grid-stiffened panel or shell.

Feminist Social Justice Orientation: An Indicator of Optimal Functioning?

ERIC Educational Resources Information Center

Moradi, Bonnie

2012-01-01

This article underscores several themes evident in Yoder, Snell, and Tobias's research; these include the conceptualization of feminism and social justice as inextricably linked, the conceptualization and operationalization of optimal functioning at intrapersonal, interpersonal, and collective levels, and potential connections and disconnections…

Exploring local borders of distribution in the shrub Daphne laureola: Individual and populations traits

NASA Astrophysics Data System (ADS)

Castilla, Antonio R.; Alonso, Conchita; Herrera, Carlos M.

2011-05-01

Biogeographic models predict that marginal populations should be more geographically isolated and smaller than central populations, linked to more stressful conditions and likely also to a reduction in density of individuals, individual growth, survival and reproductive output. This variation in population features could have important consequences for different aspects of plant ecology such as individual reproductive success, population genetic structure or plant-animal interactions. In this study, we analyze if individuals of the evergreen shrub Daphne laureola at disjunt populations in a local border of its distribution area in southern Iberian Peninsula differ in individual size, shoot growth, reproductive output and the pollination environment from central continuous populations within the area. Plants of central continuous populations were larger and produced more flowers and fruits than plants of marginal disjunct populations suggesting more optimal conditions, although they had lower annual shoot growth. In contrast, fruit set was higher in plants at the local border, suggesting a more efficient pollinator service in these populations where the main pollinator in central continuous populations, the pollen beetle Meligethes elongatus, was not present. Our results do not support strong differences in the ecological stress between marginal disjunct and central continuous populations of D. laureola in the south of the Iberian Peninsula but indicate some changes in plant-pollinator interactions that could be relevant for the sexual polymorphism in this gynodioecious species.

Autaptic pacemaker mediated propagation of weak rhythmic activity across small-world neuronal networks

NASA Astrophysics Data System (ADS)

Yilmaz, Ergin; Baysal, Veli; Ozer, Mahmut; Perc, Matjaž

2016-02-01

We study the effects of an autapse, which is mathematically described as a self-feedback loop, on the propagation of weak, localized pacemaker activity across a Newman-Watts small-world network consisting of stochastic Hodgkin-Huxley neurons. We consider that only the pacemaker neuron, which is stimulated by a subthreshold periodic signal, has an electrical autapse that is characterized by a coupling strength and a delay time. We focus on the impact of the coupling strength, the network structure, the properties of the weak periodic stimulus, and the properties of the autapse on the transmission of localized pacemaker activity. Obtained results indicate the existence of optimal channel noise intensity for the propagation of the localized rhythm. Under optimal conditions, the autapse can significantly improve the propagation of pacemaker activity, but only for a specific range of the autaptic coupling strength. Moreover, the autaptic delay time has to be equal to the intrinsic oscillation period of the Hodgkin-Huxley neuron or its integer multiples. We analyze the inter-spike interval histogram and show that the autapse enhances or suppresses the propagation of the localized rhythm by increasing or decreasing the phase locking between the spiking of the pacemaker neuron and the weak periodic signal. In particular, when the autaptic delay time is equal to the intrinsic period of oscillations an optimal phase locking takes place, resulting in a dominant time scale of the spiking activity. We also investigate the effects of the network structure and the coupling strength on the propagation of pacemaker activity. We find that there exist an optimal coupling strength and an optimal network structure that together warrant an optimal propagation of the localized rhythm.

Efficiency of quantum vs. classical annealing in nonconvex learning problems

PubMed Central

Zecchina, Riccardo

2018-01-01

Quantum annealers aim at solving nonconvex optimization problems by exploiting cooperative tunneling effects to escape local minima. The underlying idea consists of designing a classical energy function whose ground states are the sought optimal solutions of the original optimization problem and add a controllable quantum transverse field to generate tunneling processes. A key challenge is to identify classes of nonconvex optimization problems for which quantum annealing remains efficient while thermal annealing fails. We show that this happens for a wide class of problems which are central to machine learning. Their energy landscapes are dominated by local minima that cause exponential slowdown of classical thermal annealers while simulated quantum annealing converges efficiently to rare dense regions of optimal solutions. PMID:29382764

Towards enhancement of performance of K-means clustering using nature-inspired optimization algorithms.

PubMed

Fong, Simon; Deb, Suash; Yang, Xin-She; Zhuang, Yan

2014-01-01

Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario.

Study of motion of optimal bodies in the soil of grid method

NASA Astrophysics Data System (ADS)

Kotov, V. L.; Linnik, E. Yu

2016-11-01

The paper presents a method of calculating the optimum forms in axisymmetric numerical method based on the Godunov and models elastoplastic soil vedium Grigoryan. Solved two problems in a certain definition of generetrix rotation of the body of a given length and radius of the base, having a minimum impedance and maximum penetration depth. Numerical calculations are carried out by a modified method of local variations, which allows to significantly reduce the number of operations at different representations of generetrix. Significantly simplify the process of searching for optimal body allows the use of a quadratic model of local interaction for preliminary assessments. It is noted the qualitative similarity of the process of convergence of numerical calculations for solving the optimization problem based on local interaction model and within the of continuum mechanics. A comparison of the optimal bodies with absolutely optimal bodies possessing the minimum resistance of penetration below which is impossible to achieve under given constraints on the geometry. It is shown that the conical striker with a variable vertex angle, which equal to the angle of the solution is absolutely optimal body of minimum resistance of penetration for each value of the velocity of implementation will have a final depth of penetration is only 12% more than the traditional body absolutely optimal maximum depth penetration.

Towards Enhancement of Performance of K-Means Clustering Using Nature-Inspired Optimization Algorithms

PubMed Central

Deb, Suash; Yang, Xin-She

2014-01-01

Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario. PMID:25202730

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

Kametani, F.; Jiang, J.; Matras, M.

Why Bi₂Sr₂CaCu₂O x (Bi2212) allows high critical current density J c in round wires rather than only in the anisotropic tape form demanded by all other high temperature superconductors is important for future magnet applications. Here we compare the local texture of state-of-the-art Bi2212 and Bi2223 ((Bi,Pb)₂Sr₂Ca₂Cu₃O₁₀), finding that round wire Bi2212 generates a dominant a-axis growth texture that also enforces a local biaxial texture (FWHM <15°) while simultaneously allowing the c-axes of its polycrystals to rotate azimuthally along and about the filament axis so as to generate macroscopically isotropic behavior. By contrast Bi2223 shows only a uniaxial (FWHM <15°)more » c-axis texture perpendicular to the tape plane without any in-plane texture. Consistent with these observations, a marked, field-increasing, field-decreasing J c(H) hysteresis characteristic of weak-linked systems appears in Bi2223 but is absent in Bi2212 round wire. Growth-induced texture on cooling from the melt step of the Bi2212 J c optimization process appears to be the key step in generating this highly desirable microstructure.« less

Systems genetics: a paradigm to improve discovery of candidate genes and mechanisms underlying complex traits.

PubMed

Feltus, F Alex

2014-06-01

Understanding the control of any trait optimally requires the detection of causal genes, gene interaction, and mechanism of action to discover and model the biochemical pathways underlying the expressed phenotype. Functional genomics techniques, including RNA expression profiling via microarray and high-throughput DNA sequencing, allow for the precise genome localization of biological information. Powerful genetic approaches, including quantitative trait locus (QTL) and genome-wide association study mapping, link phenotype with genome positions, yet genetics is less precise in localizing the relevant mechanistic information encoded in DNA. The coupling of salient functional genomic signals with genetically mapped positions is an appealing approach to discover meaningful gene-phenotype relationships. Techniques used to define this genetic-genomic convergence comprise the field of systems genetics. This short review will address an application of systems genetics where RNA profiles are associated with genetically mapped genome positions of individual genes (eQTL mapping) or as gene sets (co-expression network modules). Both approaches can be applied for knowledge independent selection of candidate genes (and possible control mechanisms) underlying complex traits where multiple, likely unlinked, genomic regions might control specific complex traits. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Distributed plug-and-play optimal generator and load control for power system frequency regulation

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

Zhao, Changhong; Mallada, Enrique; Low, Steven H.

A distributed control scheme, which can be implemented on generators and controllable loads in a plug-and-play manner, is proposed for power system frequency regulation. The proposed scheme is based on local measurements, local computation, and neighborhood information exchanges over a communication network with an arbitrary (but connected) topology. In the event of a sudden change in generation or load, the proposed scheme can restore the nominal frequency and the reference inter-area power flows, while minimizing the total cost of control for participating generators and loads. Power network stability under the proposed control is proved with a relatively realistic model whichmore » includes nonlinear power flow and a generic (potentially nonlinear or high-order) turbine-governor model, and further with first- and second-order turbine-governor models as special cases. Finally, in simulations, the proposed control scheme shows a comparable performance to the existing automatic generation control (AGC) when implemented only on the generator side, and demonstrates better dynamic characteristics than AGC when each scheme is implemented on both generators and controllable loads. Simulation results also show robustness of the proposed scheme to communication link failure.« less

Distributed plug-and-play optimal generator and load control for power system frequency regulation

DOE PAGES

Zhao, Changhong; Mallada, Enrique; Low, Steven H.; ...

2018-03-14

A distributed control scheme, which can be implemented on generators and controllable loads in a plug-and-play manner, is proposed for power system frequency regulation. The proposed scheme is based on local measurements, local computation, and neighborhood information exchanges over a communication network with an arbitrary (but connected) topology. In the event of a sudden change in generation or load, the proposed scheme can restore the nominal frequency and the reference inter-area power flows, while minimizing the total cost of control for participating generators and loads. Power network stability under the proposed control is proved with a relatively realistic model whichmore » includes nonlinear power flow and a generic (potentially nonlinear or high-order) turbine-governor model, and further with first- and second-order turbine-governor models as special cases. Finally, in simulations, the proposed control scheme shows a comparable performance to the existing automatic generation control (AGC) when implemented only on the generator side, and demonstrates better dynamic characteristics than AGC when each scheme is implemented on both generators and controllable loads. Simulation results also show robustness of the proposed scheme to communication link failure.« less

Coordination and resource maximization during disaster relief efforts.

PubMed

Lee, Vernon J; Low, Edwin

2006-01-01

In the aftermath of the Earthquake and Tsunami in Southeast Asia, many relief organizations sent medical aid to affected areas. The aim of this paper is to examine the mix of healthcare workers resulting from an influx of aid to Meulaboh, Indonesia, and how they met local healthcare needs. Data were collected from the registration center for relief organizations in Meulaboh and daily hospital meetings on healthcare needs and available workers. Prior to the Tsunami, there were 14 doctors and 120 nurses in the hospital. By the third week after the Tsunami, there were 21 surgeons performing 10 surgeries daily, and >20 non-surgical doctors in the 90-bed hospital. There were <70 nurses available during the month after the Tsunami, which was insufficient for the needs of the hospital. In the town of Meulaboh, the number of doctors exceeded the number of nurses, while public health workers comprised <5% of the healthcare workers. An initial disaster-coordinating agency, formed by the United Nations (UN) in conjunction with affected countries, should link actively with relief organizations. This will optimize help in meeting local needs, and direct relief to where it is needed most.

Joint optimization of a partially coherent Gaussian beam for free-space optical communication over turbulent channels with pointing errors.

PubMed

Lee, It Ee; Ghassemlooy, Zabih; Ng, Wai Pang; Khalighi, Mohammad-Ali

2013-02-01

Joint beam width and spatial coherence length optimization is proposed to maximize the average capacity in partially coherent free-space optical links, under the combined effects of atmospheric turbulence and pointing errors. An optimization metric is introduced to enable feasible translation of the joint optimal transmitter beam parameters into an analogous level of divergence of the received optical beam. Results show that near-ideal average capacity is best achieved through the introduction of a larger receiver aperture and the joint optimization technique.

A coupling strategy for nonlocal and local diffusion models with mixed volume constraints and boundary conditions

DOE PAGES

D'Elia, Marta; Perego, Mauro; Bochev, Pavel B.; ...

2015-12-21

We develop and analyze an optimization-based method for the coupling of nonlocal and local diffusion problems with mixed volume constraints and boundary conditions. The approach formulates the coupling as a control problem where the states are the solutions of the nonlocal and local equations, the objective is to minimize their mismatch on the overlap of the nonlocal and local domains, and the controls are virtual volume constraints and boundary conditions. When some assumptions on the kernel functions hold, we prove that the resulting optimization problem is well-posed and discuss its implementation using Sandia’s agile software components toolkit. As a result,more » the latter provides the groundwork for the development of engineering analysis tools, while numerical results for nonlocal diffusion in three-dimensions illustrate key properties of the optimization-based coupling method.« less

Annealing Ant Colony Optimization with Mutation Operator for Solving TSP.

PubMed

Mohsen, Abdulqader M

2016-01-01

Ant Colony Optimization (ACO) has been successfully applied to solve a wide range of combinatorial optimization problems such as minimum spanning tree, traveling salesman problem, and quadratic assignment problem. Basic ACO has drawbacks of trapping into local minimum and low convergence rate. Simulated annealing (SA) and mutation operator have the jumping ability and global convergence; and local search has the ability to speed up the convergence. Therefore, this paper proposed a hybrid ACO algorithm integrating the advantages of ACO, SA, mutation operator, and local search procedure to solve the traveling salesman problem. The core of algorithm is based on the ACO. SA and mutation operator were used to increase the ants population diversity from time to time and the local search was used to exploit the current search area efficiently. The comparative experiments, using 24 TSP instances from TSPLIB, show that the proposed algorithm outperformed some well-known algorithms in the literature in terms of solution quality.

Tensin stabilizes integrin adhesive contacts in Drosophila.

PubMed

Torgler, Catherine N; Narasimha, Maithreyi; Knox, Andrea L; Zervas, Christos G; Vernon, Matthew C; Brown, Nicholas H

2004-03-01

We report the functional characterization of the Drosophila ortholog of tensin, a protein implicated in linking integrins to the cytoskeleton and signaling pathways. A tensin null was generated and is viable with wing blisters, a phenotype characteristic of loss of integrin adhesion. In tensin mutants, mechanical abrasion is required during wing expansion to cause wing blisters, suggesting that tensin strengthens integrin adhesion. The localization of tensin requires integrins, talin, and integrin-linked kinase. The N-terminal domain and C-terminal PTB domain of tensin provide essential recruitment signals. The intervening SH2 domain is not localized on its own. We suggest a model where tensin is recruited to sites of integrin adhesion via its PTB and N-terminal domains, localizing the SH2 domain so that it can interact with phosphotyrosine-containing proteins, which stabilize the integrin link to the cytoskeleton.

Optimal dietary patterns designed from local foods to achieve maternal nutritional goals.

PubMed

Raymond, Jofrey; Kassim, Neema; Rose, Jerman W; Agaba, Morris

2018-04-04

Achieving nutritional requirements for pregnant and lactating mothers in rural households while maintaining the intake of local and culture-specific foods can be a difficult task. Deploying a linear goal programming approach can effectively generate optimal dietary patterns that incorporate local and culturally acceptable diets. The primary objective of this study was to determine whether a realistic and affordable diet that achieves nutritional goals for rural pregnant and lactating women can be formulated from locally available foods in Tanzania. A cross sectional study was conducted to assess dietary intakes of 150 pregnant and lactating women using a weighed dietary record (WDR), 24 h dietary recalls and a 7-days food record. A market survey was also carried out to estimate the cost per 100 g of edible portion of foods that are frequently consumed in the study population. Dietary survey and market data were then used to define linear programming (LP) model parameters for diet optimisation. All LP analyses were done using linear program solver to generate optimal dietary patterns. Our findings showed that optimal dietary patterns designed from locally available foods would improve dietary adequacy for 15 and 19 selected nutrients in pregnant and lactating women, respectively, but inadequacies remained for iron, zinc, folate, pantothenic acid, and vitamin E, indicating that these are problem nutrients (nutrients that did not achieve 100% of their RNIs in optimised diets) in the study population. These findings suggest that optimal use of local foods can improve dietary adequacy for rural pregnant and lactating women aged 19-50 years. However, additional cost-effective interventions are needed to ensure adequate intakes for the identified problem nutrients.

Link prediction based on local weighted paths for complex networks

NASA Astrophysics Data System (ADS)

Yao, Yabing; Zhang, Ruisheng; Yang, Fan; Yuan, Yongna; Hu, Rongjing; Zhao, Zhili

As a significant problem in complex networks, link prediction aims to find the missing and future links between two unconnected nodes by estimating the existence likelihood of potential links. It plays an important role in understanding the evolution mechanism of networks and has broad applications in practice. In order to improve prediction performance, a variety of structural similarity-based methods that rely on different topological features have been put forward. As one topological feature, the path information between node pairs is utilized to calculate the node similarity. However, many path-dependent methods neglect the different contributions of paths for a pair of nodes. In this paper, a local weighted path (LWP) index is proposed to differentiate the contributions between paths. The LWP index considers the effect of the link degrees of intermediate links and the connectivity influence of intermediate nodes on paths to quantify the path weight in the prediction procedure. The experimental results on 12 real-world networks show that the LWP index outperforms other seven prediction baselines.

Advanced Intelligent System Application to Load Forecasting and Control for Hybrid Electric Bus

NASA Technical Reports Server (NTRS)

Momoh, James; Chattopadhyay, Deb; Elfayoumy, Mahmoud

1996-01-01

The primary motivation for this research emanates from providing a decision support system to the electric bus operators in the municipal and urban localities which will guide the operators to maintain an optimal compromise among the noise level, pollution level, fuel usage etc. This study is backed up by our previous studies on study of battery characteristics, permanent magnet DC motor studies and electric traction motor size studies completed in the first year. The operator of the Hybrid Electric Car must determine optimal power management schedule to meet a given load demand for different weather and road conditions. The decision support system for the bus operator comprises three sub-tasks viz. forecast of the electrical load for the route to be traversed divided into specified time periods (few minutes); deriving an optimal 'plan' or 'preschedule' based on the load forecast for the entire time-horizon (i.e., for all time periods) ahead of time; and finally employing corrective control action to monitor and modify the optimal plan in real-time. A fully connected artificial neural network (ANN) model is developed for forecasting the kW requirement for hybrid electric bus based on inputs like climatic conditions, passenger load, road inclination, etc. The ANN model is trained using back-propagation algorithm employing improved optimization techniques like projected Lagrangian technique. The pre-scheduler is based on a Goal-Programming (GP) optimization model with noise, pollution and fuel usage as the three objectives. GP has the capability of analyzing the trade-off among the conflicting objectives and arriving at the optimal activity levels, e.g., throttle settings. The corrective control action or the third sub-task is formulated as an optimal control model with inputs from the real-time data base as well as the GP model to minimize the error (or deviation) from the optimal plan. These three activities linked with the ANN forecaster proving the output to the GP model which in turn produces the pre-schedule of the optimal control model. Some preliminary results based on a hypothetical test case will be presented for the load forecasting module. The computer codes for the three modules will be made available fe adoption by bus operating agencies. Sample results will be provided using these models. The software will be a useful tool for supporting the control systems for the Electric Bus project of NASA.

A Stochastic Optimization Algorithm using Intelligent Agents: With Constraints and Rate of Convergence

DTIC Science & Technology

2010-11-01

Novembre 2010. Contexte: La puissance des ordinateurs nous permet aujourd’hui d’étudier des problèmes pour lesquels une solution analytique n’existe... 13 4.8 Proof of Corollary........................................................................................................ 13 ...optimal capacities for links. e DRDC CORA TM 2010-249 13 4.9 Example Figure 4 below shows that the probability of achieving the optimal

Query optimization for graph analytics on linked data using SPARQL

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

Hong, Seokyong; Lee, Sangkeun; Lim, Seung -Hwan

2015-07-01

Triplestores that support query languages such as SPARQL are emerging as the preferred and scalable solution to represent data and meta-data as massive heterogeneous graphs using Semantic Web standards. With increasing adoption, the desire to conduct graph-theoretic mining and exploratory analysis has also increased. Addressing that desire, this paper presents a solution that is the marriage of Graph Theory and the Semantic Web. We present software that can analyze Linked Data using graph operations such as counting triangles, finding eccentricity, testing connectedness, and computing PageRank directly on triple stores via the SPARQL interface. We describe the process of optimizing performancemore » of the SPARQL-based implementation of such popular graph algorithms by reducing the space-overhead, simplifying iterative complexity and removing redundant computations by understanding query plans. Our optimized approach shows significant performance gains on triplestores hosted on stand-alone workstations as well as hardware-optimized scalable supercomputers such as the Cray XMT.« less

Postoperative analgesia after pulmonary resection with a focus on video-assisted thoracoscopic surgery.

PubMed

Umari, Marzia; Carpanese, Valentina; Moro, Valeria; Baldo, Gaia; Addesa, Stefano; Lena, Enrico; Lovadina, Stefano; Lucangelo, Umberto

2018-05-01

Video-assisted thoracoscopic surgery is a widespread technique that has been linked to improved postoperative respiratory function, reduced hospital length of stay and a higher level of tolerability for the patients. Acute postoperative pain is of considerable significance, and the late development of neuropathic pain syndrome is also an issue. As anaesthesiologists, we have investigated the available evidence to optimize postoperative pain management. An opioid-sparing multimodal approach is highly recommended. Loco-regional techniques such as the thoracic epidural and peripheral blocks can be performed. Several adjuvants have been employed with varying degrees of success both intravenously and in combination with local anesthetics. Opioids with different pharmacodynamic and pharmacokinetic profiles can be used, either through continuous infusion or on demand. Non-opioid analgesics are also beneficial. Finally, perioperative gabapentinoids may be implemented to prevent the onset of chronic neuropathic pain.

ILF2 Is a Regulator of RNA Splicing and DNA Damage Response in 1q21-Amplified Multiple Myeloma.

PubMed

Marchesini, Matteo; Ogoti, Yamini; Fiorini, Elena; Aktas Samur, Anil; Nezi, Luigi; D'Anca, Marianna; Storti, Paola; Samur, Mehmet Kemal; Ganan-Gomez, Irene; Fulciniti, Maria Teresa; Mistry, Nipun; Jiang, Shan; Bao, Naran; Marchica, Valentina; Neri, Antonino; Bueso-Ramos, Carlos; Wu, Chang-Jiun; Zhang, Li; Liang, Han; Peng, Xinxin; Giuliani, Nicola; Draetta, Giulio; Clise-Dwyer, Karen; Kantarjian, Hagop; Munshi, Nikhil; Orlowski, Robert; Garcia-Manero, Guillermo; DePinho, Ronald A; Colla, Simona

2017-07-10

Amplification of 1q21 occurs in approximately 30% of de novo and 70% of relapsed multiple myeloma (MM) and is correlated with disease progression and drug resistance. Here, we provide evidence that the 1q21 amplification-driven overexpression of ILF2 in MM promotes tolerance of genomic instability and drives resistance to DNA-damaging agents. Mechanistically, elevated ILF2 expression exerts resistance to genotoxic agents by modulating YB-1 nuclear localization and interaction with the splicing factor U2AF65, which promotes mRNA processing and the stabilization of transcripts involved in homologous recombination in response to DNA damage. The intimate link between 1q21-amplified ILF2 and the regulation of RNA splicing of DNA repair genes may be exploited to optimize the use of DNA-damaging agents in patients with high-risk MM. Copyright © 2017 Elsevier Inc. All rights reserved.

A Biomimetic-Computational Approach to Optimizing the Quantum Efficiency of Photovoltaics

NASA Astrophysics Data System (ADS)

Perez, Lisa M.; Holzenburg, Andreas

The most advanced low-cost organic photovoltaic cells have a quantum efficiency of 10%. This is in stark contrast to plant/bacterial light-harvesting systems which offer quantum efficiencies close to unity. Of particular interest is the highly effective quantum coherence-enabled energy transfer (Fig. 1). Noting that quantum coherence is promoted by charged residues and local dielectrics, classical atomistic simulations and time-dependent density functional theory (DFT) are used to identify charge/dielectric patterns and electronic coupling at exactly defined energy transfer interfaces. The calculations make use of structural information obtained on photosynthetic protein-pigment complexes while still in the native membrane making it possible to establish a link between supramolecular organization and quantum coherence in terms of what length scales enable fast energy transport and prevent quenching. Calculating energy transfer efficiencies between components based on different proximities will permit the search for patterns that enable defining material properties suitable for advanced photovoltaics.

The collaboration imperative.

PubMed

Nidumolu, Ram; Ellison, Jib; Whalen, John; Billman, Erin

2014-04-01

Addressing global sustainability challenges--including climate change, resource depletion, and ecosystem loss--is beyond the individual capabilities of even the largest companies. To tackle these threats, and unleash new value, companies and other stakeholders must collaborate in new ways that treat fragile and complex ecosystems as a whole. In this article, the authors draw on cases including the Latin American Water Funds Partnership, the Sustainable Apparel Coalition (led by Nike, Patagonia, and Walmart), and Action to Accelerate Recycling (a partnership between Alcoa, consumer packaged goods companies, and local governments, among others) to describe four new collaboration models that create shared value and address environmental protection across the value stream. Optimal collaborations focus on improving either business processes or outcomes. They start with a small group of key organizations, bring in project management expertise, link self-interest to shared interest, encourage productive competition, create quick wins, and, above all, build and maintain trust.

NIMROD: The Near and InterMediate Range Order Diffractometer of the ISIS second target station.

PubMed

Bowron, D T; Soper, A K; Jones, K; Ansell, S; Birch, S; Norris, J; Perrott, L; Riedel, D; Rhodes, N J; Wakefield, S R; Botti, A; Ricci, M-A; Grazzi, F; Zoppi, M

2010-03-01

NIMROD is the Near and InterMediate Range Order Diffractometer of the ISIS second target station. Its design is optimized for structural studies of disordered materials and liquids on a continuous length scale that extends from the atomic, upward of 30 nm, while maintaining subatomic distance resolution. This capability is achieved by matching a low and wider angle array of high efficiency neutron scintillation detectors to the broad band-pass radiation delivered by a hybrid liquid water and liquid hydrogen neutron moderator assembly. The capabilities of the instrument bridge the gap between conventional small angle neutron scattering and wide angle diffraction through the use of a common calibration procedure for the entire length scale. This allows the instrument to obtain information on nanoscale systems and processes that are quantitatively linked to the local atomic and molecular order of the materials under investigation.

On the dynamics of StemBells: Microbubble-conjugated stem cells for ultrasound-controlled delivery

NASA Astrophysics Data System (ADS)

Kokhuis, Tom J. A.; Naaijkens, Benno A.; Juffermans, Lynda J. M.; Kamp, Otto; van der Steen, Antonius F. W.; Versluis, Michel; de Jong, Nico

2017-07-01

The use of stem cells for regenerative tissue repair is promising but hampered by the low number of cells delivered to the site of injury. To increase the delivery, we propose a technique in which stem cells are linked to functionalized microbubbles, creating echogenic complex dubbed StemBells. StemBells are highly susceptible to acoustic radiation force which can be employed after injection to push the StemBells locally to the treatment site. To optimally benefit from the delivery technique, a thorough characterization of the dynamics of StemBells during ultrasound exposure is needed. Using high-speed optical imaging, we study the dynamics of StemBells as a function of the applied frequency from which resonance curves were constructed. A theoretical model, based on a modified Rayleigh-Plesset type equation, captured the experimental resonance characteristics and radial dynamics in detail.

A Figure-of-Merit for Designing High-Performance Inductive Power Transmission Links

PubMed Central

Kiani, Mehdi; Ghovanloo, Maysam

2014-01-01

Power transfer efficiency (PTE) and power delivered to the load (PDL) are two key inductive link design parameters that relate to the power source and driver specs, power loss, transmission range, robustness against misalignment, variations in loading, and interference with other devices. Designers need to strike a delicate balance between these two because designing the link to achieve high PTE will degrade the PDL and vice versa. We are proposing a new figure-of-merit (FoM), which can help designers to find out whether a two-, three-, or four-coil link is appropriate for their particular application and guide them through an iterative design procedure to reach optimal coil geometries based on how they weigh the PTE versus PDL for that application. Three design examples at three different power levels have been presented based on the proposed FoM for implantable microelectronic devices, handheld mobile devices, and electric vehicles. The new FoM suggests that the two-coil links are suitable when the coils are strongly coupled, and a large PDL is needed. Three-coil links are the best when the coils are loosely coupled, the coupling distance varies considerably, and large PDL is necessary. Finally, four-coil links are optimal when the PTE is paramount, the coils are loosely coupled, and their relative distance and alignment are stable. Measurement results support the accuracy of the theoretical design procedure and conclusions. PMID:25382898

Fluid status monitoring with a wireless network to reduce cardiovascular-related hospitalizations and mortality in heart failure: rationale and design of the OptiLink HF Study (Optimization of Heart Failure Management using OptiVol Fluid Status Monitoring and CareLink).

PubMed

Brachmann, Johannes; Böhm, Michael; Rybak, Karin; Klein, Gunnar; Butter, Christian; Klemm, Hanno; Schomburg, Rolf; Siebermair, Johannes; Israel, Carsten; Sinha, Anil-Martin; Drexler, Helmut

2011-07-01

The Optimization of Heart Failure Management using OptiVol Fluid Status Monitoring and CareLink (OptiLink HF) study is designed to investigate whether OptiVol fluid status monitoring with an automatically generated wireless CareAlert notification via the CareLink Network can reduce all-cause death and cardiovascular hospitalizations in an HF population, compared with standard clinical assessment. Methods Patients with newly implanted or replacement cardioverter-defibrillator devices with or without cardiac resynchronization therapy, who have chronic HF in New York Heart Association class II or III and a left ventricular ejection fraction ≤35% will be eligible to participate. Following device implantation, patients are randomized to either OptiVol fluid status monitoring through CareAlert notification or regular care (OptiLink 'on' vs. 'off'). The primary endpoint is a composite of all-cause death or cardiovascular hospitalization. It is estimated that 1000 patients will be required to demonstrate superiority of the intervention group to reduce the primary outcome by 30% with 80% power. The OptiLink HF study is designed to investigate whether early detection of congestion reduces mortality and cardiovascular hospitalization in patients with chronic HF. The study is expected to close recruitment in September 2012 and to report first results in May 2014.

A Figure-of-Merit for Designing High-Performance Inductive Power Transmission Links.

PubMed

Kiani, Mehdi; Ghovanloo, Maysam

2012-11-16

Power transfer efficiency (PTE) and power delivered to the load (PDL) are two key inductive link design parameters that relate to the power source and driver specs, power loss, transmission range, robustness against misalignment, variations in loading, and interference with other devices. Designers need to strike a delicate balance between these two because designing the link to achieve high PTE will degrade the PDL and vice versa. We are proposing a new figure-of-merit (FoM), which can help designers to find out whether a two-, three-, or four-coil link is appropriate for their particular application and guide them through an iterative design procedure to reach optimal coil geometries based on how they weigh the PTE versus PDL for that application. Three design examples at three different power levels have been presented based on the proposed FoM for implantable microelectronic devices, handheld mobile devices, and electric vehicles. The new FoM suggests that the two-coil links are suitable when the coils are strongly coupled, and a large PDL is needed. Three-coil links are the best when the coils are loosely coupled, the coupling distance varies considerably, and large PDL is necessary. Finally, four-coil links are optimal when the PTE is paramount, the coils are loosely coupled, and their relative distance and alignment are stable. Measurement results support the accuracy of the theoretical design procedure and conclusions.

National outbreak of Salmonella Give linked to a local food manufacturer in Malta, October 2016.

PubMed

Donachie, A; Melillo, T; Bubba, L; Hartman, H; Borg, M-L

2018-06-26

Salmonella Give is a rare serotype across Europe. In October 2016, a national outbreak of S. Give occurred in Malta. We describe the epidemiological, environmental, microbiological and veterinary investigations. Whole-genome sequencing (WGS) was performed on human, food, environmental and veterinary isolates. Thirty-six human cases were reported between October and November 2016, 10 (28%) of whom required hospitalisation. Twenty-six (72%) cases were linked to four restaurants. S. Give was isolated from ready-to-eat antipasti served by three restaurants which were all supplied by the same local food manufacturer. Food-trace-back investigations identified S. Give in packaged bean dips, ham, pork and an asymptomatic food handler at the manufacturer; inspections found inadequate separation between raw and ready-to-eat food during processing. WGS indicated two genetically distinguishable strains of S. Give with two distinct clusters identified; one cluster linked to the local food manufacturer and a second linked to veterinary samples. Epidemiological, environmental and WGS evidence pointed towards cross-contamination of raw and ready-to-eat foods at the local manufacturer as the likely source of one cluster. Severity of illness indicates a high virulence of this specific serotype. To prevent future cases and outbreaks, adherence to food safety practices at manufacturing level need to be reinforced.

Novel magnetic cross-linked lipase aggregates for improving the resolution of (R, S)-2-octanol.

PubMed

Liu, Ying; Guo, Chen; Liu, Chun-Zhao

2015-03-01

Novel magnetic cross-linked lipase aggregates were fabricated by immobilizing the cross-linked lipase aggregates onto magnetic particles with a high number of -NH2 terminal groups using p-benzoquinone as the cross-linking agent. At the optimal fabrication conditions, 100% of immobilization efficiency and 139% of activity recovery of the magnetic cross-linked lipase aggregates were achieved. The magnetic cross-linked lipase aggregates were able to efficiently resolve (R, S)-2-octanol, and retained 100% activity and 100% enantioselectivity after 10 cycles of reuse, whereas the cross-linked lipase aggregates only retained about 50% activity and 70% enantioselectivity due to insufficient cross-linking. These results provide a great potential for industrial applications of the magnetic cross-linked lipase aggregates. © 2014 Wiley Periodicals, Inc.

Improving Evaluation Use in Local School Settings. Optimizing Evaluation Use: Final Report.

ERIC Educational Resources Information Center

King, Jean A.; And Others

A project for studying ways to optimize utilization of evaluation products in public schools is reported. The results indicate that the negative picture of use prevalent in recent literature stems from the unrealistic expectation that local decision-makers will behave in a classically rational manner. Such a view ignores the political settings of…

TestSTORM: Simulator for optimizing sample labeling and image acquisition in localization based super-resolution microscopy

PubMed Central

Sinkó, József; Kákonyi, Róbert; Rees, Eric; Metcalf, Daniel; Knight, Alex E.; Kaminski, Clemens F.; Szabó, Gábor; Erdélyi, Miklós

2014-01-01

Localization-based super-resolution microscopy image quality depends on several factors such as dye choice and labeling strategy, microscope quality and user-defined parameters such as frame rate and number as well as the image processing algorithm. Experimental optimization of these parameters can be time-consuming and expensive so we present TestSTORM, a simulator that can be used to optimize these steps. TestSTORM users can select from among four different structures with specific patterns, dye and acquisition parameters. Example results are shown and the results of the vesicle pattern are compared with experimental data. Moreover, image stacks can be generated for further evaluation using localization algorithms, offering a tool for further software developments. PMID:24688813

Consequences of Energetic Frustration on the Ligand-Coupled Folding/Dimerization Dynamics of Allosteric Protein S100A12.

PubMed

Ren, Weitong; Li, Wenfei; Wang, Jun; Zhang, Jian; Wang, Wei

2017-10-26

Allosteric proteins are featured by energetic degeneracy of two (or more) functionally relevant conformations, therefore their energy landscapes are often locally frustrated. How such frustration affects the protein folding/binding dynamics is not well understood. Here, by using molecular simulations we study the consequences of local frustration in the dimerization dynamics of allosteric proteins based on a homodimer protein S100A12. Despite of the structural symmetry of the two EF-hand motifs in the three-dimensional structures, the S100A12 homodimer shows allosteric behaviors and local frustration only in half of its structural elements, i.e., the C-terminal EF-hand. We showed that such spatially asymmetric location of frustration leads to asymmetric dimerization pathways, in which the dimerization is dominantly initiated by the interchain binding of the minimally frustrated N-terminal EF-hands, achieving optimal balance between the requirements of rapid conformational switching and interchain assembling to the energy landscapes. We also showed that the local frustration, as represented by the double-basin topography of the energy landscape, gives rise to multiple cross-linked dimerization pathways, in which the dimerization is coupled with the allosteric motions of the C-terminal EF-hands. Binding of metal ions tends to reshape the energy landscape and modulate the dimerization pathways. In addition, by employing the frustratometer method, we showed that the highly frustrated residue-pairs in the C-terminal EF-hand are partially unfolded during the conformational transitions of the native homodimer, leading to lowing of free energy barrier. Our results revealed tight interplay between the local frustration of the energy landscape and the dimerization dynamics for allosteric proteins.

Local Approximation and Hierarchical Methods for Stochastic Optimization

NASA Astrophysics Data System (ADS)

Cheng, Bolong

In this thesis, we present local and hierarchical approximation methods for two classes of stochastic optimization problems: optimal learning and Markov decision processes. For the optimal learning problem class, we introduce a locally linear model with radial basis function for estimating the posterior mean of the unknown objective function. The method uses a compact representation of the function which avoids storing the entire history, as is typically required by nonparametric methods. We derive a knowledge gradient policy with the locally parametric model, which maximizes the expected value of information. We show the policy is asymptotically optimal in theory, and experimental works suggests that the method can reliably find the optimal solution on a range of test functions. For the Markov decision processes problem class, we are motivated by an application where we want to co-optimize a battery for multiple revenue, in particular energy arbitrage and frequency regulation. The nature of this problem requires the battery to make charging and discharging decisions at different time scales while accounting for the stochastic information such as load demand, electricity prices, and regulation signals. Computing the exact optimal policy becomes intractable due to the large state space and the number of time steps. We propose two methods to circumvent the computation bottleneck. First, we propose a nested MDP model that structure the co-optimization problem into smaller sub-problems with reduced state space. This new model allows us to understand how the battery behaves down to the two-second dynamics (that of the frequency regulation market). Second, we introduce a low-rank value function approximation for backward dynamic programming. This new method only requires computing the exact value function for a small subset of the state space and approximate the entire value function via low-rank matrix completion. We test these methods on historical price data from the PJM Interconnect and show that it outperforms the baseline approach used in the industry.

A statistical rain attenuation prediction model with application to the advanced communication technology satellite project. 3: A stochastic rain fade control algorithm for satellite link power via non linear Markow filtering theory

NASA Technical Reports Server (NTRS)

Manning, Robert M.

1991-01-01

The dynamic and composite nature of propagation impairments that are incurred on Earth-space communications links at frequencies in and above 30/20 GHz Ka band, i.e., rain attenuation, cloud and/or clear air scintillation, etc., combined with the need to counter such degradations after the small link margins have been exceeded, necessitate the use of dynamic statistical identification and prediction processing of the fading signal in order to optimally estimate and predict the levels of each of the deleterious attenuation components. Such requirements are being met in NASA's Advanced Communications Technology Satellite (ACTS) Project by the implementation of optimal processing schemes derived through the use of the Rain Attenuation Prediction Model and nonlinear Markov filtering theory.

Multiple local feature representations and their fusion based on an SVR model for iris recognition using optimized Gabor filters

NASA Astrophysics Data System (ADS)

He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Dong, Hongxing

2014-12-01

Gabor descriptors have been widely used in iris texture representations. However, fixed basic Gabor functions cannot match the changing nature of diverse iris datasets. Furthermore, a single form of iris feature cannot overcome difficulties in iris recognition, such as illumination variations, environmental conditions, and device variations. This paper provides multiple local feature representations and their fusion scheme based on a support vector regression (SVR) model for iris recognition using optimized Gabor filters. In our iris system, a particle swarm optimization (PSO)- and a Boolean particle swarm optimization (BPSO)-based algorithm is proposed to provide suitable Gabor filters for each involved test dataset without predefinition or manual modulation. Several comparative experiments on JLUBR-IRIS, CASIA-I, and CASIA-V4-Interval iris datasets are conducted, and the results show that our work can generate improved local Gabor features by using optimized Gabor filters for each dataset. In addition, our SVR fusion strategy may make full use of their discriminative ability to improve accuracy and reliability. Other comparative experiments show that our approach may outperform other popular iris systems.

Global/Local: What Does It Mean for Global Health Educators and How Do We Do It?

PubMed

Rowthorn, Virginia

2015-01-01

There has been dramatic growth in the number of innovative university programs that focus on social justice and teach community-based strategies that are applicable both domestically in North America and internationally. These programs often are referred to as global/local and reflect an effort to link global health and campus community engagement efforts to acknowledge that a common set of transferable skills can be adapted to work with vulnerable populations wherever they may be. However, the concepts underlying global/local education are undertheorized and universities struggle to make the global/local link without a conceptual framework to guide them in this pursuit. This study reports on the outcomes of a 2015 national meeting of 120 global health educators convened to discuss the concepts underlying global/local education, to share models of global/local programs, and to draft a preliminary list of critical elements of a meaningful and didactically sound global/local educational program. A qualitative analysis was conducted of the discussions that took place at the national meeting. The analysis was supported by videorecordings made of full-group discussions. Results were categorized into a preliminary list of global/local program elements. Additionally, a synthesis was developed of critical issues raised at the meeting that warrant future discussion and study. A preliminary list was developed of 7 program components that global health educators consider essential to categorize a program as global/local and to ensure that such a program includes specific critical elements. Interest is great among global health educators to understand and teach the conceptual link between learning on both the global and community levels. Emphasis on this link has high potential to unite the siloed fields of global health and domestic community public health and the institutions, funding options, and career pathways that flow from them. Future research should focus on implementation of global/local programming and evaluation of student learning and community health outcomes related to such programs. Copyright © 2015 The Author. Published by Elsevier Inc. All rights reserved.

Optimal design of low-density SNP arrays for genomic prediction: algorithm and applications

USDA-ARS?s Scientific Manuscript database

Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for their optimal design. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optim...

Multidisciplinary Optimization and Damage Tolerance of Stiffened Structures

NASA Astrophysics Data System (ADS)

Jrad, Mohamed

THE structural optimization of a cantilever aircraft wing with curvilinear spars and ribs and stiffeners is described. For the optimization of a complex wing, a common strategy is to divide the optimization procedure into two subsystems: the global wing optimization which optimizes the geometry of spars, ribs and wing skins; and the local panel optimization which optimizes the design variables of local panels bordered by spars and ribs. The stiffeners are placed on the local panels to increase the stiffness and buckling resistance. During the local panel optimization, the stress information is taken from the global model as a displacement boundary condition on the panel edges using the so-called "Global-Local Approach". Particle swarm optimization is used in the integration of global/local optimization to optimize the SpaRibs. Parallel computing approach has been developed in the Python programming language to reduce the CPU time. The license cycle-check method and memory self-adjustment method are two approaches that have been applied in the parallel framework in order to optimize the use of the resources by reducing the license and memory limitations and making the code robust. The integrated global-local optimization approach has been applied to subsonic NASA common research model (CRM) wing, which proves the methodology's application scaling with medium fidelity FEM analysis. The structural weight of the wing has been reduced by 42% and the parallel implementation allowed a reduction in the CPU time by 89%. The aforementioned Global-Local Approach is investigated and applied to a composite panel with crack at its center. Because of composite laminates' heterogeneity, an accurate analysis of these requires very high time and storage space. A possible alternative to reduce the computational complexity is the global-local analysis which involves an approximate analysis of the whole structure followed by a detailed analysis of a significantly smaller region of interest. Buckling analysis of a composite panel with attached longitudinal stiffeners under compressive loads is performed using Ritz method with trigonometric functions. Results are then compared to those from Abaqus FEA for different shell elements. The case of composite panel with one, two, and three stiffeners is investigated. The effect of the distance between the stiffeners on the buckling load is also studied. The variation of the buckling load and buckling modes with the stiffeners' height is investigated. It is shown that there is an optimum value of stiffeners' height beyond which the structural response of the stiffened panel is not improved and the buckling load does not increase. Furthermore, there exist different critical values of stiffener's height at which the buckling mode of the structure changes. Next, buckling analysis of a composite panel with two straight stiffeners and a crack at the center is performed. Finally, buckling analysis of a composite panel with curvilinear stiffeners and a crack at the center is also conducted. Results show that panels with a larger crack have a reduced buckling load and that the buckling load decreases slightly when using higher order 2D shell FEM elements. A damage tolerance framework, EBF3PanelOpt, has been developed to design and analyze curvilinearly stiffened panels. The framework is written with the scripting language Python and it interacts with the commercial software MSC. Patran (for geometry and mesh creation), MSC. Nastran (for finite element analysis), and MSC. Marc (for damage tolerance analysis). The crack location is set to the location of the maximum value of the major principal stress while its orientation is set normal to the major principal axis direction. The effective stress intensity factor is calculated using the Virtual Crack Closure Technique and compared to the fracture toughness of the material in order to decide whether the crack will expand or not. The ratio of these two quantities is used as a constraint, along with the buckling factor, Kreisselmeier and Steinhauser criteria, and crippling factor. The EBF3PanelOpt framework is integrated within a two-step Particle Swarm Optimization in order to minimize the weight of the panel while satisfying the aforementioned constraints and using all the shape and thickness parameters as design variables. The result of the PSO is used then as an initial guess for the Gradient Based Optimization using only the thickness parameters as design variables and employing VisualDOC. Stiffened panel with two curvilinear stiffeners is optimized for two load cases. In both cases, significant reduction has been made for the panel's weight.

An automated, fast and accurate registration method to link stranded seeds in permanent prostate implants

NASA Astrophysics Data System (ADS)

Westendorp, Hendrik; Nuver, Tonnis T.; Moerland, Marinus A.; Minken, André W.

2015-10-01

The geometry of a permanent prostate implant varies over time. Seeds can migrate and edema of the prostate affects the position of seeds. Seed movements directly influence dosimetry which relates to treatment quality. We present a method that tracks all individual seeds over time allowing quantification of seed movements. This linking procedure was tested on transrectal ultrasound (TRUS) and cone-beam CT (CBCT) datasets of 699 patients. These datasets were acquired intraoperatively during a dynamic implantation procedure, that combines both imaging modalities. The procedure was subdivided in four automatic linking steps. (I) The Hungarian Algorithm was applied to initially link seeds in CBCT and the corresponding TRUS datasets. (II) Strands were identified and optimized based on curvature and linefits: non optimal links were removed. (III) The positions of unlinked seeds were reviewed and were linked to incomplete strands if within curvature- and distance-thresholds. (IV) Finally, seeds close to strands were linked, also if the curvature-threshold was violated. After linking the seeds an affine transformation was applied. The procedure was repeated until the results were stable or the 6th iteration ended. All results were visually reviewed for mismatches and uncertainties. Eleven implants showed a mismatch and in 12 cases an uncertainty was identified. On average the linking procedure took 42 ms per case. This accurate and fast method has the potential to be used for other time spans, like Day 30, and other imaging modalities. It can potentially be used during a dynamic implantation procedure to faster and better evaluate the quality of the permanent prostate implant.

Optimization of extraction of polysaccharides from fruiting body of Cordyceps militaris (L.) link using response surface methodology

NASA Astrophysics Data System (ADS)

Nguyen, Hoang Chinh; Thi, Dinh Huynh Mong; Pham, Dinh Chuong

2018-04-01

Polysaccharides from fruiting body of Cordyceps militaris (L.) Link possess various pharmaceutical activities. In this study, polysaccharides from the fruiting body of C. militaris were extracted with different solvents. Of those solvents tested, distilled water was identified as the most efficient solvent for the extraction, resulting in a significant increase in polysaccharides yield. Response surface methodology was then used to optimize the extraction conditions and establish a reliable mathematical model for prediction. A maximum polysaccharides yield of 11.07% was reached at a ratio of water to raw material of 23.2:1 mL/g, an extraction time of 76 min, and a temperature of 93.6°C. This study indicates that the obtained optimal extraction conditions are an efficient method for extraction of polysaccharides from the fruiting body of C. militaris.

Local Estuary Programs

EPA Pesticide Factsheets

This page provides information about Local Individual Estuary Programs including links to their NEP homepages, social media, Comprehensive Conservation and Management Plans, and state of the bay reports.

Linking search space structure, run-time dynamics, and problem difficulty : a step toward demystifying tabu search.

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

Whitley, L. Darrell; Howe, Adele E.; Watson, Jean-Paul

2004-09-01

Tabu search is one of the most effective heuristics for locating high-quality solutions to a diverse array of NP-hard combinatorial optimization problems. Despite the widespread success of tabu search, researchers have a poor understanding of many key theoretical aspects of this algorithm, including models of the high-level run-time dynamics and identification of those search space features that influence problem difficulty. We consider these questions in the context of the job-shop scheduling problem (JSP), a domain where tabu search algorithms have been shown to be remarkably effective. Previously, we demonstrated that the mean distance between random local optima and the nearestmore » optimal solution is highly correlated with problem difficulty for a well-known tabu search algorithm for the JSP introduced by Taillard. In this paper, we discuss various shortcomings of this measure and develop a new model of problem difficulty that corrects these deficiencies. We show that Taillard's algorithm can be modeled with high fidelity as a simple variant of a straightforward random walk. The random walk model accounts for nearly all of the variability in the cost required to locate both optimal and sub-optimal solutions to random JSPs, and provides an explanation for differences in the difficulty of random versus structured JSPs. Finally, we discuss and empirically substantiate two novel predictions regarding tabu search algorithm behavior. First, the method for constructing the initial solution is highly unlikely to impact the performance of tabu search. Second, tabu tenure should be selected to be as small as possible while simultaneously avoiding search stagnation; values larger than necessary lead to significant degradations in performance.« less

Optimal Audiovisual Integration in the Ventriloquism Effect But Pervasive Deficits in Unisensory Spatial Localization in Amblyopia.

PubMed

Richards, Michael D; Goltz, Herbert C; Wong, Agnes M F

2018-01-01

Classically understood as a deficit in spatial vision, amblyopia is increasingly recognized to also impair audiovisual multisensory processing. Studies to date, however, have not determined whether the audiovisual abnormalities reflect a failure of multisensory integration, or an optimal strategy in the face of unisensory impairment. We use the ventriloquism effect and the maximum-likelihood estimation (MLE) model of optimal integration to investigate integration of audiovisual spatial information in amblyopia. Participants with unilateral amblyopia (n = 14; mean age 28.8 years; 7 anisometropic, 3 strabismic, 4 mixed mechanism) and visually normal controls (n = 16, mean age 29.2 years) localized brief unimodal auditory, unimodal visual, and bimodal (audiovisual) stimuli during binocular viewing using a location discrimination task. A subset of bimodal trials involved the ventriloquism effect, an illusion in which auditory and visual stimuli originating from different locations are perceived as originating from a single location. Localization precision and bias were determined by psychometric curve fitting, and the observed parameters were compared with predictions from the MLE model. Spatial localization precision was significantly reduced in the amblyopia group compared with the control group for unimodal visual, unimodal auditory, and bimodal stimuli. Analyses of localization precision and bias for bimodal stimuli showed no significant deviations from the MLE model in either the amblyopia group or the control group. Despite pervasive deficits in localization precision for visual, auditory, and audiovisual stimuli, audiovisual integration remains intact and optimal in unilateral amblyopia.

The Role of Local Development Organizations in Rural America

ERIC Educational Resources Information Center

Green, Gary Paul; Haines, Anna; Dunn, Adam; Sullivan, Daniel Monroe

2002-01-01

Rural communities rely increasingly on local development organizations (LDOs) to promote economic development. The rise of LDOs has been the source of much debate. Using a national data set that links local governments with development organizations, we contrast the economic development activities, and their outcomes, of local governments and…

Determining the Optimal Number of Spinal Manipulation Sessions for Chronic Low-Back Pain

MedlinePlus

... health-related information is available. Related Topics NIH Analysis Shows Americans Are In Pain Research Results Research Results by Date This page last modified September 13, 2016 Follow NCCIH: Read our disclaimer about external links Twitter Read our disclaimer about external links Facebook Read ...

Photoregulating RNA digestion using azobenzene linked dumbbell antisense oligodeoxynucleotides.

PubMed

Wu, Li; He, Yujian; Tang, Xinjing

2015-06-17

Introduction of 4,4'-bis(hydroxymethyl)-azobenzene (azo) to dumbbell hairpin oligonucleotides at the loop position was able to reversibly control the stability of the whole hairpin structure via UV or visible light irradiation. Here, we designed and synthesized a series of azobenzene linked dumbbell antisense oligodeoxynucleotides (asODNs) containing two terminal hairpins that are composed of an asODN and a short inhibitory sense strand. Thermal melting studies of these azobenzene linked dumbbell asODNs indicated that efficient trans to cis photoisomerization of azobenzene moieties induced large difference in thermal stability (ΔTm = 12.1-21.3 °C). In addition, photomodulation of their RNA binding abilities and RNA digestion by RNase H was investigated. The trans-azobenzene linked asODNs with the optimized base pairs between asODN strands and inhibitory sense strands could only bind few percentage of the target RNA, while it was able to recover their binding to the target RNA and degrade it by RNase H after light irradiation. Upon optimization, it is promising to use these azobenzene linked asODNs for reversible spatial and temporal regulation of antisense activities based on both steric binding and RNA digestion by RNase H.

Do Vascular Networks Branch Optimally or Randomly across Spatial Scales?

PubMed Central

Newberry, Mitchell G.; Savage, Van M.

2016-01-01

Modern models that derive allometric relationships between metabolic rate and body mass are based on the architectural design of the cardiovascular system and presume sibling vessels are symmetric in terms of radius, length, flow rate, and pressure. Here, we study the cardiovascular structure of the human head and torso and of a mouse lung based on three-dimensional images processed via our software Angicart. In contrast to modern allometric theories, we find systematic patterns of asymmetry in vascular branching, potentially explaining previously documented mismatches between predictions (power-law or concave curvature) and observed empirical data (convex curvature) for the allometric scaling of metabolic rate. To examine why these systematic asymmetries in vascular branching might arise, we construct a mathematical framework to derive predictions based on local, junction-level optimality principles that have been proposed to be favored in the course of natural selection and development. The two most commonly used principles are material-cost optimizations (construction materials or blood volume) and optimization of efficient flow via minimization of power loss. We show that material-cost optimization solutions match with distributions for asymmetric branching across the whole network but do not match well for individual junctions. Consequently, we also explore random branching that is constrained at scales that range from local (junction-level) to global (whole network). We find that material-cost optimizations are the strongest predictor of vascular branching in the human head and torso, whereas locally or intermediately constrained random branching is comparable to material-cost optimizations for the mouse lung. These differences could be attributable to developmentally-programmed local branching for larger vessels and constrained random branching for smaller vessels. PMID:27902691

Memetic Approaches for Optimizing Hidden Markov Models: A Case Study in Time Series Prediction

NASA Astrophysics Data System (ADS)

Bui, Lam Thu; Barlow, Michael

We propose a methodology for employing memetics (local search) within the framework of evolutionary algorithms to optimize parameters of hidden markov models. With this proposal, the rate and frequency of using local search are automatically changed over time either at a population or individual level. At the population level, we allow the rate of using local search to decay over time to zero (at the final generation). At the individual level, each individual is equipped with information of when it will do local search and for how long. This information evolves over time alongside the main elements of the chromosome representing the individual.

RNA localization in Xenopus oocytes uses a core group of trans-acting factors irrespective of destination.

PubMed

Snedden, Donald D; Bertke, Michelle M; Vernon, Dominic; Huber, Paul W

2013-07-01

The 3' untranslated region of mRNA encoding PHAX, a phosphoprotein required for nuclear export of U-type snRNAs, contains cis-acting sequence motifs E2 and VM1 that are required for localization of RNAs to the vegetal hemisphere of Xenopus oocytes. However, we have found that PHAX mRNA is transported to the opposite, animal, hemisphere. A set of proteins that cross-link to the localization elements of vegetally localized RNAs are also cross-linked to PHAX and An1 mRNAs, demonstrating that the composition of RNP complexes that form on these localization elements is highly conserved irrespective of the final destination of the RNA. The ability of RNAs to bind this core group of proteins is correlated with localization activity. Staufen1, which binds to Vg1 and VegT mRNAs, is not associated with RNAs localized to the animal hemisphere and may determine, at least in part, the direction of RNA movement in Xenopus oocytes.

Evaluation of Methods for Multidisciplinary Design Optimization (MDO). Part 2

NASA Technical Reports Server (NTRS)

Kodiyalam, Srinivas; Yuan, Charles; Sobieski, Jaroslaw (Technical Monitor)

2000-01-01

A new MDO method, BLISS, and two different variants of the method, BLISS/RS and BLISS/S, have been implemented using iSIGHT's scripting language and evaluated in this report on multidisciplinary problems. All of these methods are based on decomposing a modular system optimization system into several subtasks optimization, that may be executed concurrently, and the system optimization that coordinates the subtasks optimization. The BLISS method and its variants are well suited for exploiting the concurrent processing capabilities in a multiprocessor machine. Several steps, including the local sensitivity analysis, local optimization, response surfaces construction and updates are all ideally suited for concurrent processing. Needless to mention, such algorithms that can effectively exploit the concurrent processing capabilities of the compute servers will be a key requirement for solving large-scale industrial design problems, such as the automotive vehicle problem detailed in Section 3.4.

A hybrid multi-objective evolutionary algorithm for wind-turbine blade optimization

NASA Astrophysics Data System (ADS)

Sessarego, M.; Dixon, K. R.; Rival, D. E.; Wood, D. H.

2015-08-01

A concurrent-hybrid non-dominated sorting genetic algorithm (hybrid NSGA-II) has been developed and applied to the simultaneous optimization of the annual energy production, flapwise root-bending moment and mass of the NREL 5 MW wind-turbine blade. By hybridizing a multi-objective evolutionary algorithm (MOEA) with gradient-based local search, it is believed that the optimal set of blade designs could be achieved in lower computational cost than for a conventional MOEA. To measure the convergence between the hybrid and non-hybrid NSGA-II on a wind-turbine blade optimization problem, a computationally intensive case was performed using the non-hybrid NSGA-II. From this particular case, a three-dimensional surface representing the optimal trade-off between the annual energy production, flapwise root-bending moment and blade mass was achieved. The inclusion of local gradients in the blade optimization, however, shows no improvement in the convergence for this three-objective problem.

Intelligent Optimization of Modulation Indexes in Unified Tracking and Communication System

NASA Astrophysics Data System (ADS)

Yang, Wei-wei; Cong, Bo; Huang, Qiong; Zhu, Li-wei

2016-02-01

In the unified tracking and communication system, the ranging signal and the telemetry, communication signals are used in the same channel. In the link budget, it is necessary to allocate the power reasonably, so as to ensure the performance of system and reduce the cost. In this paper, the nonlinear optimization problem is studied using intelligent optimization method. Simulation analysis results show that the proposed method is effective.

Real-Time Optimal Flood Control Decision Making and Risk Propagation Under Multiple Uncertainties

NASA Astrophysics Data System (ADS)

Zhu, Feilin; Zhong, Ping-An; Sun, Yimeng; Yeh, William W.-G.

2017-12-01

Multiple uncertainties exist in the optimal flood control decision-making process, presenting risks involving flood control decisions. This paper defines the main steps in optimal flood control decision making that constitute the Forecast-Optimization-Decision Making (FODM) chain. We propose a framework for supporting optimal flood control decision making under multiple uncertainties and evaluate risk propagation along the FODM chain from a holistic perspective. To deal with uncertainties, we employ stochastic models at each link of the FODM chain. We generate synthetic ensemble flood forecasts via the martingale model of forecast evolution. We then establish a multiobjective stochastic programming with recourse model for optimal flood control operation. The Pareto front under uncertainty is derived via the constraint method coupled with a two-step process. We propose a novel SMAA-TOPSIS model for stochastic multicriteria decision making. Then we propose the risk assessment model, the risk of decision-making errors and rank uncertainty degree to quantify the risk propagation process along the FODM chain. We conduct numerical experiments to investigate the effects of flood forecast uncertainty on optimal flood control decision making and risk propagation. We apply the proposed methodology to a flood control system in the Daduhe River basin in China. The results indicate that the proposed method can provide valuable risk information in each link of the FODM chain and enable risk-informed decisions with higher reliability.

Optimization of locations of diffusion spots in indoor optical wireless local area networks

NASA Astrophysics Data System (ADS)

Eltokhey, Mahmoud W.; Mahmoud, K. R.; Ghassemlooy, Zabih; Obayya, Salah S. A.

2018-03-01

In this paper, we present a novel optimization of the locations of the diffusion spots in indoor optical wireless local area networks, based on the central force optimization (CFO) scheme. The users' performance uniformity is addressed by using the CFO algorithm, and adopting different objective function's configurations, while considering maximization and minimization of the signal to noise ratio and the delay spread, respectively. We also investigate the effect of varying the objective function's weights on the system and the users' performance as part of the adaptation process. The results show that the proposed objective function configuration-based optimization procedure offers an improvement of 65% in the standard deviation of individual receivers' performance.

Damage identification in beams using speckle shearography and an optimal spatial sampling

NASA Astrophysics Data System (ADS)

Mininni, M.; Gabriele, S.; Lopes, H.; Araújo dos Santos, J. V.

2016-10-01

Over the years, the derivatives of modal displacement and rotation fields have been used to localize damage in beams. Usually, the derivatives are computed by applying finite differences. The finite differences propagate and amplify the errors that exist in real measurements, and thus, it is necessary to minimize this problem in order to get reliable damage localizations. A way to decrease the propagation and amplification of the errors is to select an optimal spatial sampling. This paper presents a technique where an optimal spatial sampling of modal rotation fields is computed and used to obtain the modal curvatures. Experimental measurements of modal rotation fields of a beam with single and multiple damages are obtained with shearography, which is an optical technique allowing the measurement of full-fields. These measurements are used to test the validity of the optimal sampling technique for the improvement of damage localization in real structures. An investigation on the ability of a model updating technique to quantify the damage is also reported. The model updating technique is defined by the variations of measured natural frequencies and measured modal rotations and aims at calibrating the values of the second moment of area in the damaged areas, which were previously localized.

Machine learning framework for analysis of transport through complex networks in porous, granular media: A focus on permeability

NASA Astrophysics Data System (ADS)

van der Linden, Joost H.; Narsilio, Guillermo A.; Tordesillas, Antoinette

2016-08-01

We present a data-driven framework to study the relationship between fluid flow at the macroscale and the internal pore structure, across the micro- and mesoscales, in porous, granular media. Sphere packings with varying particle size distribution and confining pressure are generated using the discrete element method. For each sample, a finite element analysis of the fluid flow is performed to compute the permeability. We construct a pore network and a particle contact network to quantify the connectivity of the pores and particles across the mesoscopic spatial scales. Machine learning techniques for feature selection are employed to identify sets of microstructural properties and multiscale complex network features that optimally characterize permeability. We find a linear correlation (in log-log scale) between permeability and the average closeness centrality of the weighted pore network. With the pore network links weighted by the local conductance, the average closeness centrality represents a multiscale measure of efficiency of flow through the pore network in terms of the mean geodesic distance (or shortest path) between all pore bodies in the pore network. Specifically, this study objectively quantifies a hypothesized link between high permeability and efficient shortest paths that thread through relatively large pore bodies connected to each other by high conductance pore throats, embodying connectivity and pore structure.

Laser Frequency Noise in Coherent Optical Systems: Spectral Regimes and Impairments.

PubMed

Kakkar, Aditya; Rodrigo Navarro, Jaime; Schatz, Richard; Pang, Xiaodan; Ozolins, Oskars; Udalcovs, Aleksejs; Louchet, Hadrien; Popov, Sergei; Jacobsen, Gunnar

2017-04-12

Coherent communication networks are based on the ability to use multiple dimensions of the lightwave together with electrical domain compensation of transmission impairments. Electrical-domain dispersion compensation (EDC) provides many advantages such as network flexibility and enhanced fiber nonlinearity tolerance, but makes the system more susceptible to laser frequency noise (FN), e.g. to the local oscillator FN in systems with post-reception EDC. Although this problem has been extensively studied, statistically, for links assuming lasers with white-FN, many questions remain unanswered. Particularly, the influence of a realistic non-white FN-spectrum due to e.g., the presence of 1/f-flicker and carrier induced noise remains elusive and a statistical analysis becomes insufficient. Here we provide an experimentally validated theory for coherent optical links with lasers having general non-white FN-spectrum and EDC. The fundamental reason of the increased susceptibility is shown to be FN-induced symbol displacement that causes timing jitter and/or inter/intra symbol interference. We establish that different regimes of the laser FN-spectrum cause a different set of impairments. The influence of the impairments due to some regimes can be reduced by optimizing the corresponding mitigation algorithms, while other regimes cause irretrievable impairments. Theoretical boundaries of these regimes and corresponding criteria applicable to system/laser design are provided.

Inverse Electrocardiographic Source Localization of Ischemia: An Optimization Framework and Finite Element Solution

PubMed Central

Wang, Dafang; Kirby, Robert M.; MacLeod, Rob S.; Johnson, Chris R.

2013-01-01

With the goal of non-invasively localizing cardiac ischemic disease using body-surface potential recordings, we attempted to reconstruct the transmembrane potential (TMP) throughout the myocardium with the bidomain heart model. The task is an inverse source problem governed by partial differential equations (PDE). Our main contribution is solving the inverse problem within a PDE-constrained optimization framework that enables various physically-based constraints in both equality and inequality forms. We formulated the optimality conditions rigorously in the continuum before deriving finite element discretization, thereby making the optimization independent of discretization choice. Such a formulation was derived for the L2-norm Tikhonov regularization and the total variation minimization. The subsequent numerical optimization was fulfilled by a primal-dual interior-point method tailored to our problem’s specific structure. Our simulations used realistic, fiber-included heart models consisting of up to 18,000 nodes, much finer than any inverse models previously reported. With synthetic ischemia data we localized ischemic regions with roughly a 10% false-negative rate or a 20% false-positive rate under conditions up to 5% input noise. With ischemia data measured from animal experiments, we reconstructed TMPs with roughly 0.9 correlation with the ground truth. While precisely estimating the TMP in general cases remains an open problem, our study shows the feasibility of reconstructing TMP during the ST interval as a means of ischemia localization. PMID:23913980

Tapping mode SPM local oxidation nanolithography with sub-10 nm resolution

NASA Astrophysics Data System (ADS)

Nishimura, S.; Ogino, T.; Takemura, Y.; Shirakashi, J.

2008-03-01

Tapping mode SPM local oxidation nanolithography with sub-10 nm resolution is investigated by optimizing the applied bias voltage (V), scanning speed (S) and the oscillation amplitude of the cantilever (A). We fabricated Si oxide wires with an average width of 9.8 nm (V = 17.5 V, S = 250 nm/s, A = 292 nm). In SPM local oxidation with tapping mode operation, it is possible to decrease the size of the water meniscus by enhancing the oscillation amplitude of cantilever. Hence, it seems that the water meniscus with sub-10 nm dimensions could be formed by precisely optimizing the oxidation conditions. Moreover, we quantitatively explain the size (width and height) of Si oxide wires with a model based on the oxidation ratio, which is defined as the oxidation time divided by the period of the cantilever oscillation. The model allows us to understand the mechanism of local oxidation in tapping mode operation with amplitude modulation. The results imply that the sub-10 nm resolution could be achieved using tapping mode SPM local oxidation technique with the optimization of the cantilever dynamics.

Proxy functions for turbulent transport optimization of stellarators

NASA Astrophysics Data System (ADS)

Rorvig, Mordechai; Hegna, Chris; Mynick, Harry; Xanthopoulos, Pavlos

2012-10-01

The design freedom of toroidal confinement shaping suggests the possibility of optimizing the magnetic geometry for turbulent transport, particularly in stellarators. The framework for implementing such an optimization was recently established [1] using a proxy function as a measure of the ITG induced turbulent transport associated with a given geometry. Working in the framework of local 3-D equilibrium [2], we investigate the theory and implications of such proxy functions by analyzing the linear instability dependence on curvature and local shear, and the associated quasilinear transport estimates. Simple analytic models suggest the beneficial effect of local shear enters through polarization effects, which can be controlled by field torsion in small net current regimes. We test the proxy functions with local, electrostatic gyrokinetics calculations [3] of ITG modes for experimentally motivated local 3-D equilibria.[4pt] [1] H. E. Mynick, N. Pomphrey, and P. Xanthopoulos, Phys. Rev. Lett. 105, 095004 (2010).[0pt] [2] C. C. Hegna, Physics of Plasmas 7, 3921 (2000).[0pt] [3] F. Jenko, W. Dorland, M. Kotschenreuther, and B. N. Rogers, Physical Review Letters 7, 1904 (2000).

Non-linear pattern formation in bone growth and architecture.

PubMed

Salmon, Phil

2014-01-01

The three-dimensional morphology of bone arises through adaptation to its required engineering performance. Genetically and adaptively bone travels along a complex spatiotemporal trajectory to acquire optimal architecture. On a cellular, micro-anatomical scale, what mechanisms coordinate the activity of osteoblasts and osteoclasts to produce complex and efficient bone architectures? One mechanism is examined here - chaotic non-linear pattern formation (NPF) - which underlies in a unifying way natural structures as disparate as trabecular bone, swarms of birds flying, island formation, fluid turbulence, and others. At the heart of NPF is the fact that simple rules operating between interacting elements, and Turing-like interaction between global and local signals, lead to complex and structured patterns. The study of "group intelligence" exhibited by swarming birds or shoaling fish has led to an embodiment of NPF called "particle swarm optimization" (PSO). This theoretical model could be applicable to the behavior of osteoblasts, osteoclasts, and osteocytes, seeing them operating "socially" in response simultaneously to both global and local signals (endocrine, cytokine, mechanical), resulting in their clustered activity at formation and resorption sites. This represents problem-solving by social intelligence, and could potentially add further realism to in silico computer simulation of bone modeling. What insights has NPF provided to bone biology? One example concerns the genetic disorder juvenile Pagets disease or idiopathic hyperphosphatasia, where the anomalous parallel trabecular architecture characteristic of this pathology is consistent with an NPF paradigm by analogy with known experimental NPF systems. Here, coupling or "feedback" between osteoblasts and osteoclasts is the critical element. This NPF paradigm implies a profound link between bone regulation and its architecture: in bone the architecture is the regulation. The former is the emergent consequence of the latter.

Cytoplasmically Retargeted HSV1-tk/GFP Reporter Gene Mutants for Optimization of Noninvasive Molecular-Genetic Imaging

PubMed Central

Ponomarev, Vladimir; Doubrovin, Michael; Serganova, Inna; Beresten, Tatiana; Vider, Jelena; Shavrin, Aleksander; Ageyeva, Ludmila; Balatoni, Julius; Blasberg, Ronald; Tjuvajev, Juri Gelovani

2003-01-01

Abstract To optimize the sensitivity of imaging HSV1-tk/GFP reporter gene expression, a series of HSV1-tk/GFP mutants was developed with altered nuclear localization and better cellular enzymatic activity, compared to that of the native HSV1-tk/GFP fusion protein (HSV1-tk/GFP). Several modifications of HSV1-tk/GFP reporter gene were performed, including targeted inactivating mutations in the nuclear localization signal (NLS), the addition of a nuclear export signal (NES), a combination of both mutation types, and a truncation of the first 135 bp of the native hsv1-tk coding sequence containing a “cryptic” testicular promoter and the NLS. A recombinant HSV1-tk/GFP protein and a highly sensitive sandwich enzyme-linked immunosorbent assay for HSV1-tk/GFP were developed to quantitate the amount of reporter gene product in different assays to allow normalization of the data. These different mutations resulted in various degrees of nuclear clearance, predominant cytoplasmic distribution, and increased total cellular enzymatic activity of the HSV1-tk/GFP mutants, compared to native HSV1-tk/GFP when expressed at the same levels. This appears to be the result of improvedmetabolic bioavailability of cytoplasmically retargeted mutant HSV1-tk/GFP enzymes for reaction with the radiolabeled probe (e.g., FIAU). The analysis of enzymatic properties of different HSV1-tk/GFP mutants using FIAU as a substrate revealed no significant differences from that of the native HSV1-tk/GFP. Improved total cellular enzymatic activity of cytoplasmically retargeted HSV1-tk/GFP mutants observed in vitro was confirmed by noninvasive imaging of transduced subcutaneous tumor xenografts bearing these reporters using [131I]FIAU and a γ-camera. PMID:12869307

Expression and subcellular localization of the Qa-SNARE syntaxin17 in human eosinophils.

PubMed

Carmo, Lívia A S; Dias, Felipe F; Malta, Kássia K; Amaral, Kátia B; Shamri, Revital; Weller, Peter F; Melo, Rossana C N

2015-10-01

SNARE members mediate membrane fusion during intracellular trafficking underlying innate and adaptive immune responses by different cells. However, little is known about the expression and function of these proteins in human eosinophils, cells involved in allergic, inflammatory and immunoregulatory responses. Here, we investigate the expression and distribution of the Qa-SNARE syntaxin17 (STX17) within human eosinophils isolated from the peripheral blood. Flow cytometry and a pre-embedding immunonanogold electron microscopy (EM) technique that combines optimal epitope preservation and secondary Fab-fragments of antibodies linked to 1.4 nm gold particles for optimal access to microdomains, were used to investigate STX17. STX17 was detected within unstimulated eosinophils. Immunogold EM revealed STX17 on secretory granules and on granule-derived vesiculotubular transport carriers (Eosinophil Sombrero Vesicles-EoSVs). Quantitative EM analyses showed that 77.7% of the granules were positive for STX17 with a mean±SEM of 3.9±0.2 gold particles/granule. Labeling was present on both granule outer membranes and matrices while EoSVs showed clear membrane-associated labeling. STX17 was also present in secretory granules in eosinophils stimulated with the cytokine tumor necrosis factor alpha (TNF-α) or the CC-chemokine ligand 11 CCL11 (eotaxin-1), stimuli that induce eosinophil degranulation. The number of secretory granules labeled for STX17 was significantly higher in CCL11 compared with the unstimulated group. The level of cell labeling did not change when unstimulated cells were compared with TNF-α-stimulated eosinophils. The present study clearly shows by immunanonogold EM that STX17 is localized in eosinophil secretory granules and transport vesicles and might be involved in the transport of granule-derived cargos. Copyright © 2015 Elsevier Inc. All rights reserved.

A method to incorporate leakage and head scatter corrections into a tomotherapy inverse treatment planning algorithm

NASA Astrophysics Data System (ADS)

Holmes, Timothy W.

2001-01-01

A detailed tomotherapy inverse treatment planning method is described which incorporates leakage and head scatter corrections during each iteration of the optimization process, allowing these effects to be directly accounted for in the optimized dose distribution. It is shown that the conventional inverse planning method for optimizing incident intensity can be extended to include a `concurrent' leaf sequencing operation from which the leakage and head scatter corrections are determined. The method is demonstrated using the steepest-descent optimization technique with constant step size and a least-squared error objective. The method was implemented using the MATLAB scientific programming environment and its feasibility demonstrated for 2D test cases simulating treatment delivery using a single coplanar rotation. The results indicate that this modification does not significantly affect convergence of the intensity optimization method when exposure times of individual leaves are stratified to a large number of levels (>100) during leaf sequencing. In general, the addition of aperture dependent corrections, especially `head scatter', reduces incident fluence in local regions of the modulated fan beam, resulting in increased exposure times for individual collimator leaves. These local variations can result in 5% or greater local variation in the optimized dose distribution compared to the uncorrected case. The overall efficiency of the modified intensity optimization algorithm is comparable to that of the original unmodified case.

Two-phase simulation-based location-allocation optimization of biomass storage distribution

USDA-ARS?s Scientific Manuscript database

This study presents a two-phase simulation-based framework for finding the optimal locations of biomass storage facilities that is a very critical link on the biomass supply chain, which can help to solve biorefinery concerns (e.g. steady supply, uniform feedstock properties, stable feedstock costs,...

Numerical integration and optimization of motions for multibody dynamic systems

NASA Astrophysics Data System (ADS)

Aguilar Mayans, Joan

This thesis considers the optimization and simulation of motions involving rigid body systems. It does so in three distinct parts, with the following topics: optimization and analysis of human high-diving motions, efficient numerical integration of rigid body dynamics with contacts, and motion optimization of a two-link robot arm using Finite-Time Lyapunov Analysis. The first part introduces the concept of eigenpostures, which we use to simulate and analyze human high-diving motions. Eigenpostures are used in two different ways: first, to reduce the complexity of the optimal control problem that we solve to obtain such motions, and second, to generate an eigenposture space to which we map existing real world motions to better analyze them. The benefits of using eigenpostures are showcased through different examples. The second part reviews an extensive list of integration algorithms used for the integration of rigid body dynamics. We analyze the accuracy and stability of the different integrators in the three-dimensional space and the rotation space SO(3). Integrators with an accuracy higher than first order perform more efficiently than integrators with first order accuracy, even in the presence of contacts. The third part uses Finite-time Lyapunov Analysis to optimize motions for a two-link robot arm. Finite-Time Lyapunov Analysis diagnoses the presence of time-scale separation in the dynamics of the optimized motion and provides the information and methodology for obtaining an accurate approximation to the optimal solution, avoiding the complications that timescale separation causes for alternative solution methods.

Debiasing comparative optimism and increasing worry for health outcomes.

PubMed

Rose, Jason P

2012-11-01

Comparative optimism - feeling at less personal risk for negative outcomes than one's peers - has been linked to reduced prevention efforts. This study examined a novel debiasing technique aimed at simultaneously reducing both indirectly and directly measured comparative optimism. Before providing direct comparative estimates, participants provided absolute self and peer estimates in a joint format (same computer screen) or a separate format (different computer screens). Relative to the separate format condition, participants in the joint format condition showed (1) lower comparative optimism in absolute/indirect measures, (2) lower direct comparative optimism, and (3) heightened worry. Implications for risk perception screening are discussed.

An efficient algorithm for function optimization: modified stem cells algorithm

NASA Astrophysics Data System (ADS)

Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad Hadi

2013-03-01

In this paper, we propose an optimization algorithm based on the intelligent behavior of stem cell swarms in reproduction and self-organization. Optimization algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm and Artificial Bee Colony (ABC) algorithm, can give solutions to linear and non-linear problems near to the optimum for many applications; however, in some case, they can suffer from becoming trapped in local optima. The Stem Cells Algorithm (SCA) is an optimization algorithm inspired by the natural behavior of stem cells in evolving themselves into new and improved cells. The SCA avoids the local optima problem successfully. In this paper, we have made small changes in the implementation of this algorithm to obtain improved performance over previous versions. Using a series of benchmark functions, we assess the performance of the proposed algorithm and compare it with that of the other aforementioned optimization algorithms. The obtained results prove the superiority of the Modified Stem Cells Algorithm (MSCA).

Orbit design and optimization based on global telecommunication performance metrics

NASA Technical Reports Server (NTRS)

Lee, Seungwon; Lee, Charles H.; Kerridge, Stuart; Cheung, Kar-Ming; Edwards, Charles D.

2006-01-01

The orbit selection of telecommunications orbiters is one of the critical design processes and should be guided by global telecom performance metrics and mission-specific constraints. In order to aid the orbit selection, we have coupled the Telecom Orbit Analysis and Simulation Tool (TOAST) with genetic optimization algorithms. As a demonstration, we have applied the developed tool to select an optimal orbit for general Mars telecommunications orbiters with the constraint of being a frozen orbit. While a typical optimization goal is to minimize tele-communications down time, several relevant performance metrics are examined: 1) area-weighted average gap time, 2) global maximum of local maximum gap time, 3) global maximum of local minimum gap time. Optimal solutions are found with each of the metrics. Common and different features among the optimal solutions as well as the advantage and disadvantage of each metric are presented. The optimal solutions are compared with several candidate orbits that were considered during the development of Mars Telecommunications Orbiter.

Thermometric enzyme linked immunosorbent assay in continuous flow system: optimization and evaluation using human serum albumin as a model system.

PubMed

Borrebaeck, C; Börjeson, J; Mattiasson, B

1978-06-15

Thermometric enzyme-linked immunosorbent assay (TELISA) is described. After the procedure of optimization, human serum albumin was assayed using anti-human serum albumin bound to Sepharose CL 4-B in the enzyme thermistor unit and catalase as label on the free antigen. The model system was used for assays down to 10(-13)M and the preparation of immobilized antibodies was used repeatedly up to 100 times. Comparative studies of the TELISA technique with bromocresol green, immunoturbidimetric and rocket immunoelectrophoretic methods were carried out and showed that TELISA could be used as an alternative method.

Study to investigate and evaluate means of optimizing the Ku-band communication function for the space shuttle

NASA Technical Reports Server (NTRS)

Simon, M. K.; Udalov, S.; Huth, G. K.

1976-01-01

The forward link of the overall Ku-band communication system consists of the ground- TDRS-orbiter communication path. Because the last segment of the link is directed towards a relatively low orbiting shuttle, a PN code is used to reduce the spectral density. A method is presented for incorporating code acquisition and tracking functions into the orbiter's Ku-band receiver. Optimization of a three channel multiplexing technique is described. The importance of Costas loop parameters to provide false lock immunity for the receiver, and the advantage of using a sinusoidal subcarrier waveform, rather than square wave, are discussed.

Smart grid technologies in local electric grids

NASA Astrophysics Data System (ADS)

Lezhniuk, Petro D.; Pijarski, Paweł; Buslavets, Olga A.

2017-08-01

The research is devoted to the creation of favorable conditions for the integration of renewable sources of energy into electric grids, which were designed to be supplied from centralized generation at large electric power stations. Development of distributed generation in electric grids influences the conditions of their operation - conflict of interests arises. The possibility of optimal functioning of electric grids and renewable sources of energy, when complex criterion of the optimality is balance reliability of electric energy in local electric system and minimum losses of electric energy in it. Multilevel automated system for power flows control in electric grids by means of change of distributed generation of power is developed. Optimization of power flows is performed by local systems of automatic control of small hydropower stations and, if possible, solar power plants.

A hierarchical transition state search algorithm

NASA Astrophysics Data System (ADS)

del Campo, Jorge M.; Köster, Andreas M.

2008-07-01

A hierarchical transition state search algorithm is developed and its implementation in the density functional theory program deMon2k is described. This search algorithm combines the double ended saddle interpolation method with local uphill trust region optimization. A new formalism for the incorporation of the distance constrain in the saddle interpolation method is derived. The similarities between the constrained optimizations in the local trust region method and the saddle interpolation are highlighted. The saddle interpolation and local uphill trust region optimizations are validated on a test set of 28 representative reactions. The hierarchical transition state search algorithm is applied to an intramolecular Diels-Alder reaction with several internal rotors, which makes automatic transition state search rather challenging. The obtained reaction mechanism is discussed in the context of the experimentally observed product distribution.

Effect of local minima on adiabatic quantum optimization.

PubMed

Amin, M H S

2008-04-04

We present a perturbative method to estimate the spectral gap for adiabatic quantum optimization, based on the structure of the energy levels in the problem Hamiltonian. We show that, for problems that have an exponentially large number of local minima close to the global minimum, the gap becomes exponentially small making the computation time exponentially long. The quantum advantage of adiabatic quantum computation may then be accessed only via the local adiabatic evolution, which requires phase coherence throughout the evolution and knowledge of the spectrum. Such problems, therefore, are not suitable for adiabatic quantum computation.

QM/MM Geometry Optimization on Extensive Free-Energy Surfaces for Examination of Enzymatic Reactions and Design of Novel Functional Properties of Proteins.

PubMed

Hayashi, Shigehiko; Uchida, Yoshihiro; Hasegawa, Taisuke; Higashi, Masahiro; Kosugi, Takahiro; Kamiya, Motoshi

2017-05-05

Many remarkable molecular functions of proteins use their characteristic global and slow conformational dynamics through coupling of local chemical states in reaction centers with global conformational changes of proteins. To theoretically examine the functional processes of proteins in atomic detail, a methodology of quantum mechanical/molecular mechanical (QM/MM) free-energy geometry optimization is introduced. In the methodology, a geometry optimization of a local reaction center is performed with a quantum mechanical calculation on a free-energy surface constructed with conformational samples of the surrounding protein environment obtained by a molecular dynamics simulation with a molecular mechanics force field. Geometry optimizations on extensive free-energy surfaces by a QM/MM reweighting free-energy self-consistent field method designed to be variationally consistent and computationally efficient have enabled examinations of the multiscale molecular coupling of local chemical states with global protein conformational changes in functional processes and analysis and design of protein mutants with novel functional properties.

Automated sequence-specific protein NMR assignment using the memetic algorithm MATCH.

PubMed

Volk, Jochen; Herrmann, Torsten; Wüthrich, Kurt

2008-07-01

MATCH (Memetic Algorithm and Combinatorial Optimization Heuristics) is a new memetic algorithm for automated sequence-specific polypeptide backbone NMR assignment of proteins. MATCH employs local optimization for tracing partial sequence-specific assignments within a global, population-based search environment, where the simultaneous application of local and global optimization heuristics guarantees high efficiency and robustness. MATCH thus makes combined use of the two predominant concepts in use for automated NMR assignment of proteins. Dynamic transition and inherent mutation are new techniques that enable automatic adaptation to variable quality of the experimental input data. The concept of dynamic transition is incorporated in all major building blocks of the algorithm, where it enables switching between local and global optimization heuristics at any time during the assignment process. Inherent mutation restricts the intrinsically required randomness of the evolutionary algorithm to those regions of the conformation space that are compatible with the experimental input data. Using intact and artificially deteriorated APSY-NMR input data of proteins, MATCH performed sequence-specific resonance assignment with high efficiency and robustness.

Integration and Optimization of Alternative Sources of Energy in a Remote Region

NASA Astrophysics Data System (ADS)

Berberi, Pellumb; Inodnorjani, Spiro; Aleti, Riza

2010-01-01

In a remote coastal region supply of energy from national grid is insufficient for a sustainable development. Integration and optimization of local alternative renewable energy sources is an optional solution of the problem. In this paper we have studied the energetic potential of local sources of renewable energy (water, solar, wind and biomass). A bottom-up energy system optimization model is proposed in order to support planning policies for promoting the use of renewable energy sources. A software, based on multiple factors and constrains analysis for optimization energy flow is proposed, which provides detailed information for exploitation each source of energy, power and heat generation, GHG emissions and end-use sectors. Economical analysis shows that with existing technologies both stand alone and regional facilities may be feasible. Improving specific legislation will foster investments from Central or Local Governments and also from individuals, private companies or small families. The study is carried on the frame work of a FP6 project "Integrated Renewable Energy System."

QuickVina: accelerating AutoDock Vina using gradient-based heuristics for global optimization.

PubMed

Handoko, Stephanus Daniel; Ouyang, Xuchang; Su, Chinh Tran To; Kwoh, Chee Keong; Ong, Yew Soon

2012-01-01

Predicting binding between macromolecule and small molecule is a crucial phase in the field of rational drug design. AutoDock Vina, one of the most widely used docking software released in 2009, uses an empirical scoring function to evaluate the binding affinity between the molecules and employs the iterated local search global optimizer for global optimization, achieving a significantly improved speed and better accuracy of the binding mode prediction compared its predecessor, AutoDock 4. In this paper, we propose further improvement in the local search algorithm of Vina by heuristically preventing some intermediate points from undergoing local search. Our improved version of Vina-dubbed QVina-achieved a maximum acceleration of about 25 times with the average speed-up of 8.34 times compared to the original Vina when tested on a set of 231 protein-ligand complexes while maintaining the optimal scores mostly identical. Using our heuristics, larger number of different ligands can be quickly screened against a given receptor within the same time frame.

QM/MM Geometry Optimization on Extensive Free-Energy Surfaces for Examination of Enzymatic Reactions and Design of Novel Functional Properties of Proteins

NASA Astrophysics Data System (ADS)

Hayashi, Shigehiko; Uchida, Yoshihiro; Hasegawa, Taisuke; Higashi, Masahiro; Kosugi, Takahiro; Kamiya, Motoshi

2017-05-01

Many remarkable molecular functions of proteins use their characteristic global and slow conformational dynamics through coupling of local chemical states in reaction centers with global conformational changes of proteins. To theoretically examine the functional processes of proteins in atomic detail, a methodology of quantum mechanical/molecular mechanical (QM/MM) free-energy geometry optimization is introduced. In the methodology, a geometry optimization of a local reaction center is performed with a quantum mechanical calculation on a free-energy surface constructed with conformational samples of the surrounding protein environment obtained by a molecular dynamics simulation with a molecular mechanics force field. Geometry optimizations on extensive free-energy surfaces by a QM/MM reweighting free-energy self-consistent field method designed to be variationally consistent and computationally efficient have enabled examinations of the multiscale molecular coupling of local chemical states with global protein conformational changes in functional processes and analysis and design of protein mutants with novel functional properties.

Investigation and process optimization of SONOS cell's drain disturb in 2-transistor structure flash arrays

NASA Astrophysics Data System (ADS)

Xu, Zhaozhao; Qian, Wensheng; Chen, Hualun; Xiong, Wei; Hu, Jun; Liu, Donghua; Duan, Wenting; Kong, Weiran; Na, Wei; Zou, Shichang

2017-03-01

The mechanism and distribution of drain disturb (DD) are investigated in silicon-oxide-nitride-oxide-silicon (SONOS) flash cells. It is shown that DD is the only concern in this paper. First, the distribution of trapped charge in nitride layer is found to be non-localized (trapped in entire nitride layer along the channel) after programming. Likewise, the erase is also non-localized. Then, the main disturb mechanism: Fowler Nordheim tunneling (FNT) has been confirmed in this paper with negligible disturb effect from hot-hole injection (HHI). And then, distribution of DD is confirmed to be non-localized similarly, which denotes that DD exists in entire tunneling oxide (Oxide for short). Next, four process optimization ways are proposed for minimization of DD, and VTH shift is measured. It reveals that optimized lightly doped drain (LDD), halo, and channel implant are required for the fabrication of a robust SONOS cell. Finally, data retention and endurance of the optimized SONOS are demonstrated.

Optimization of culture conditions and bench-scale production of L-asparaginase by submerged fermentation of Aspergillus terreus MTCC 1782.

PubMed

Gurunathan, Baskar; Sahadevan, Renganathan

2012-07-01

Optimization of culture conditions for L-asparaginase production by submerged fermentation of Aspergillus terreus MTCC 1782 was studied using a 3-level central composite design of response surface methodology and artificial neural network linked genetic algorithm. The artificial neural network linked genetic algorithm was found to be more efficient than response surface methodology. The experimental L-asparaginase activity of 43.29 IU/ml was obtained at the optimum culture conditions of temperature 35 degrees C, initial pH 6.3, inoculum size 1% (v/v), agitation rate 140 rpm, and incubation time 58.5 h of the artificial neural network linked genetic algorithm, which was close to the predicted activity of 44.38 IU/ml. Characteristics of L-asparaginase production by A. terreus MTCC 1782 were studied in a 3 L bench-scale bioreactor.

Computer simulation and design of a three degree-of-freedom shoulder module

NASA Technical Reports Server (NTRS)

Marco, David; Torfason, L.; Tesar, Delbert

1989-01-01

An in-depth kinematic analysis of a three degree of freedom fully-parallel robotic shoulder module is presented. The major goal of the analysis is to determine appropriate link dimensions which will provide a maximized workspace along with desirable input to output velocity and torque amplification. First order kinematic influence coefficients which describe the output velocity properties in terms of actuator motions provide a means to determine suitable geometric dimensions for the device. Through the use of computer simulation, optimal or near optimal link dimensions based on predetermined design criteria are provided for two different structural designs of the mechanism. The first uses three rotational inputs to control the output motion. The second design involves the use of four inputs, actuating any three inputs for a given position of the output link. Alternative actuator placements are examined to determine the most effective approach to control the output motion.

Neonatal period: linking best nutrition practices at birth to optimize maternal and infant health and survival.

PubMed

Lutter, Chessa K; Chaparro, Camila M

2009-06-01

Delayed umbilical cord clamping, immediate skin-to-skin contact, and early initiation of breastfeeding have been shown to be simple, safe, and effective and should be implemented in all deliveries, with very few exceptions. Although these practices can also prevent death, their importance extends beyond survival and optimizes both short-and long-term neonatal and maternal health and nutrition. Their implementation requires that they be integrated with one another and included with other standard lifesaving care practices. Leveraging knowledge of efficacious interventions into high-quality programs with broad coverage is often the main obstacle to improving neonatal and maternal health in low-income countries. To achieve results at-scale, attention must be given to increasing access to scientific information supporting evidence-based practices and addressing the skills needed to implement the recommended practices; establishing and communicating global, national, and local policies and guidelines for implementation in conjunction with advocacy and synchronization with other maternal and neonatal care efforts; reorganizing delivery care services; and monitoring and evaluation. This will require international investments similar to those being made for other lifesaving neonatal interventions. Neonatal vitamin A supplementation, recommended for implementation in Asia, is controversial, and the evidence for and against this recommendation is reviewed.

Programmed to learn? The ontogeny of mirror neurons.

PubMed

Del Giudice, Marco; Manera, Valeria; Keysers, Christian

2009-03-01

Mirror neurons are increasingly recognized as a crucial substrate for many developmental processes, including imitation and social learning. Although there has been considerable progress in describing their function and localization in the primate and adult human brain, we still know little about their ontogeny. The idea that mirror neurons result from Hebbian learning while the child observes/hears his/her own actions has received remarkable empirical support in recent years. Here we add a new element to this proposal, by suggesting that the infant's perceptual-motor system is optimized to provide the brain with the correct input for Hebbian learning, thus facilitating the association between the perception of actions and their corresponding motor programs. We review evidence that infants (1) have a marked visual preference for hands, (2) show cyclic movement patterns with a frequency that could be in the optimal range for enhanced Hebbian learning, and (3) show synchronized theta EEG (also known to favour synaptic Hebbian learning) in mirror cortical areas during self-observation of grasping. These conditions, taken together, would allow mirror neurons for manual actions to develop quickly and reliably through experiential canalization. Our hypothesis provides a plausible pathway for the emergence of mirror neurons that integrates learning with genetic pre-programming, suggesting new avenues for research on the link between synaptic processes and behaviour in ontogeny.

Accuracy of buffered-force QM/MM simulations of silica

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

Peguiron, Anke; Moras, Gianpietro; Colombi Ciacchi, Lucio

2015-02-14

We report comparisons between energy-based quantum mechanics/molecular mechanics (QM/MM) and buffered force-based QM/MM simulations in silica. Local quantities—such as density of states, charges, forces, and geometries—calculated with both QM/MM approaches are compared to the results of full QM simulations. We find the length scale over which forces computed using a finite QM region converge to reference values obtained in full quantum-mechanical calculations is ∼10 Å rather than the ∼5 Å previously reported for covalent materials such as silicon. Electrostatic embedding of the QM region in the surrounding classical point charges gives only a minor contribution to the force convergence. Whilemore » the energy-based approach provides accurate results in geometry optimizations of point defects, we find that the removal of large force errors at the QM/MM boundary provided by the buffered force-based scheme is necessary for accurate constrained geometry optimizations where Si–O bonds are elongated and for finite-temperature molecular dynamics simulations of crack propagation. Moreover, the buffered approach allows for more flexibility, since special-purpose QM/MM coupling terms that link QM and MM atoms are not required and the region that is treated at the QM level can be adaptively redefined during the course of a dynamical simulation.« less

Biblio-Link and Pro-Cite: The Searcher's Workstation.

ERIC Educational Resources Information Center

Hoyle, Norman; McNamara, Kathleen

1987-01-01

Describes the Biblio-Link and Pro-Cite software packages, which can be used together to create local databases with downloaded records, or to reorganize and repackage downloaded records for client reports. (CLB)

Deep Space Quantum Link

NASA Astrophysics Data System (ADS)

Mohageg, M.; Strekalov, D.; Dolinar, S.; Shaw, M.; Yu, N.

2018-02-01

The Deep Space Quantum Link will test the effects of gravity on quantum systems, test the non-locality of quantum states at deep space distances, and perform long distance quantum teleportation to an Earth-based receiver.

Simulated annealing in orbital flight planning

NASA Technical Reports Server (NTRS)

Soller, Jeffrey

1990-01-01

Simulated annealing is used to solve a minimum fuel trajectory problem in the space station environment. The environment is unique because the space station will define the first true multivehicle environment in space. The optimization yields surfaces which are potentially complex, with multiple local minima. Because of the likelihood of these local minima, descent techniques are unable to offer robust solutions. Other deterministic optimization techniques were explored without success. The simulated annealing optimization is capable of identifying a minimum-fuel, two-burn trajectory subject to four constraints. Furthermore, the computational efforts involved in the optimization are such that missions could be planned on board the space station. Potential applications could include the on-site planning of rendezvous with a target craft of the emergency rescue of an astronaut. Future research will include multiwaypoint maneuvers, using a knowledge base to guide the optimization.

Biological Monitoring of 3-Phenoxybenzoic Acid in Urine by an Enzyme -Linked Immunosorbent Assay

EPA Science Inventory

An enzyme-linked immunosorbent assay (ELISA) method was employed for determination of the pyrethroid biomarker, 3-phenoxybenzoic acid (3-PBA) in human urine samples. The optimized coating antigen concentration was 0.5 ng/mL with a dilution of 1:4000 for the 3-PBA antibody and 1:6...

Local concurrent error detection and correction in data structures using virtual backpointers

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

Li, C.C.J.; Chen, P.P.; Fuchs, W.K.

1989-11-01

A new technique, based on virtual backpointers, is presented in this paper for local concurrent error detection and correction in linked data structures. Two new data structures utilizing virtual backpointers, the Virtual Double-Linked List and the B-Tree and Virtual Backpointers, are described. For these structures, double errors within a fixed-size checking window can be detected in constant time and single errors detected during forward moves can be corrected in constant time.

Fluid status monitoring with a wireless network to reduce cardiovascular-related hospitalizations and mortality in heart failure: rationale and design of the OptiLink HF Study (Optimization of Heart Failure Management using OptiVol Fluid Status Monitoring and CareLink)

PubMed Central

Brachmann, Johannes; Böhm, Michael; Rybak, Karin; Klein, Gunnar; Butter, Christian; Klemm, Hanno; Schomburg, Rolf; Siebermair, Johannes; Israel, Carsten; Sinha, Anil-Martin; Drexler, Helmut

2011-01-01

Aims The Optimization of Heart Failure Management using OptiVol Fluid Status Monitoring and CareLink (OptiLink HF) study is designed to investigate whether OptiVol fluid status monitoring with an automatically generated wireless CareAlert notification via the CareLink Network can reduce all-cause death and cardiovascular hospitalizations in an HF population, compared with standard clinical assessment. Methods Patients with newly implanted or replacement cardioverter-defibrillator devices with or without cardiac resynchronization therapy, who have chronic HF in New York Heart Association class II or III and a left ventricular ejection fraction ≤35% will be eligible to participate. Following device implantation, patients are randomized to either OptiVol fluid status monitoring through CareAlert notification or regular care (OptiLink ‘on' vs. ‘off'). The primary endpoint is a composite of all-cause death or cardiovascular hospitalization. It is estimated that 1000 patients will be required to demonstrate superiority of the intervention group to reduce the primary outcome by 30% with 80% power. Conclusion The OptiLink HF study is designed to investigate whether early detection of congestion reduces mortality and cardiovascular hospitalization in patients with chronic HF. The study is expected to close recruitment in September 2012 and to report first results in May 2014. ClinicalTrials.gov Identifier: NCT00769457 PMID:21555324

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

Annealing Ant Colony Optimization with Mutation Operator for Solving TSP

PubMed Central

2016-01-01

Ant Colony Optimization (ACO) has been successfully applied to solve a wide range of combinatorial optimization problems such as minimum spanning tree, traveling salesman problem, and quadratic assignment problem. Basic ACO has drawbacks of trapping into local minimum and low convergence rate. Simulated annealing (SA) and mutation operator have the jumping ability and global convergence; and local search has the ability to speed up the convergence. Therefore, this paper proposed a hybrid ACO algorithm integrating the advantages of ACO, SA, mutation operator, and local search procedure to solve the traveling salesman problem. The core of algorithm is based on the ACO. SA and mutation operator were used to increase the ants population diversity from time to time and the local search was used to exploit the current search area efficiently. The comparative experiments, using 24 TSP instances from TSPLIB, show that the proposed algorithm outperformed some well-known algorithms in the literature in terms of solution quality. PMID:27999590

Optimal control of epidemic information dissemination over networks.

PubMed

Chen, Pin-Yu; Cheng, Shin-Ming; Chen, Kwang-Cheng

2014-12-01

Information dissemination control is of crucial importance to facilitate reliable and efficient data delivery, especially in networks consisting of time-varying links or heterogeneous links. Since the abstraction of information dissemination much resembles the spread of epidemics, epidemic models are utilized to characterize the collective dynamics of information dissemination over networks. From a systematic point of view, we aim to explore the optimal control policy for information dissemination given that the control capability is a function of its distribution time, which is a more realistic model in many applications. The main contributions of this paper are to provide an analytically tractable model for information dissemination over networks, to solve the optimal control signal distribution time for minimizing the accumulated network cost via dynamic programming, and to establish a parametric plug-in model for information dissemination control. In particular, we evaluate its performance in mobile and generalized social networks as typical examples.

Teleconnection Paths via Climate Network Direct Link Detection.

PubMed

Zhou, Dong; Gozolchiani, Avi; Ashkenazy, Yosef; Havlin, Shlomo

2015-12-31

Teleconnections describe remote connections (typically thousands of kilometers) of the climate system. These are of great importance in climate dynamics as they reflect the transportation of energy and climate change on global scales (like the El Niño phenomenon). Yet, the path of influence propagation between such remote regions, and weighting associated with different paths, are only partially known. Here we propose a systematic climate network approach to find and quantify the optimal paths between remotely distant interacting locations. Specifically, we separate the correlations between two grid points into direct and indirect components, where the optimal path is found based on a minimal total cost function of the direct links. We demonstrate our method using near surface air temperature reanalysis data, on identifying cross-latitude teleconnections and their corresponding optimal paths. The proposed method may be used to quantify and improve our understanding regarding the emergence of climate patterns on global scales.

Virtual optical network mapping and core allocation in elastic optical networks using multi-core fibers

NASA Astrophysics Data System (ADS)

Xuan, Hejun; Wang, Yuping; Xu, Zhanqi; Hao, Shanshan; Wang, Xiaoli

2017-11-01

Virtualization technology can greatly improve the efficiency of the networks by allowing the virtual optical networks to share the resources of the physical networks. However, it will face some challenges, such as finding the efficient strategies for virtual nodes mapping, virtual links mapping and spectrum assignment. It is even more complex and challenging when the physical elastic optical networks using multi-core fibers. To tackle these challenges, we establish a constrained optimization model to determine the optimal schemes of optical network mapping, core allocation and spectrum assignment. To solve the model efficiently, tailor-made encoding scheme, crossover and mutation operators are designed. Based on these, an efficient genetic algorithm is proposed to obtain the optimal schemes of the virtual nodes mapping, virtual links mapping, core allocation. The simulation experiments are conducted on three widely used networks, and the experimental results show the effectiveness of the proposed model and algorithm.

Preparation and Optimisation of Cross-Linked Enzyme Aggregates Using Native Isolate White Rot Fungi Trametes versicolor and Fomes fomentarius for the Decolourisation of Synthetic Dyes

PubMed Central

Vršanská, Martina; Voběrková, Stanislava; Jiménez Jiménez, Ana María; Strmiska, Vladislav; Adam, Vojtěch

2017-01-01

The key to obtaining an optimum performance of an enzyme is often a question of devising a suitable enzyme and optimisation of conditions for its immobilization. In this study, laccases from the native isolates of white rot fungi Fomes fomentarius and/or Trametes versicolor, obtained from Czech forests, were used. From these, cross-linked enzyme aggregates (CLEA) were prepared and characterised when the experimental conditions were optimized. Based on the optimization steps, saturated ammonium sulphate solution (75 wt.%) was used as the precipitating agent, and different concentrations of glutaraldehyde as a cross-linking agent were investigated. CLEA aggregates formed under the optimal conditions showed higher catalytic efficiency and stabilities (thermal, pH, and storage, against denaturation) as well as high reusability compared to free laccase for both fungal strains. The best concentration of glutaraldehyde seemed to be 50 mM and higher efficiency of cross-linking was observed at a low temperature 4 °C. An insignificant increase in optimum pH for CLEA laccases with respect to free laccases for both fungi was observed. The results show that the optimum temperature for both free laccase and CLEA laccase was 35 °C for T. versicolor and 30 °C for F. fomentarius. The CLEAs retained 80% of their initial activity for Trametes and 74% for Fomes after 70 days of cultivation. Prepared cross-linked enzyme aggregates were also investigated for their decolourisation activity on malachite green, bromothymol blue, and methyl red dyes. Immobilised CLEA laccase from Trametes versicolor showed 95% decolourisation potential and CLEA from Fomes fomentarius demonstrated 90% decolourisation efficiency within 10 h for all dyes used. These results suggest that these CLEAs have promising potential in dye decolourisation. PMID:29295505

Augmented Lagrange Programming Neural Network for Localization Using Time-Difference-of-Arrival Measurements.

PubMed

Han, Zifa; Leung, Chi Sing; So, Hing Cheung; Constantinides, Anthony George

2017-08-15

A commonly used measurement model for locating a mobile source is time-difference-of-arrival (TDOA). As each TDOA measurement defines a hyperbola, it is not straightforward to compute the mobile source position due to the nonlinear relationship in the measurements. This brief exploits the Lagrange programming neural network (LPNN), which provides a general framework to solve nonlinear constrained optimization problems, for the TDOA-based localization. The local stability of the proposed LPNN solution is also analyzed. Simulation results are included to evaluate the localization accuracy of the LPNN scheme by comparing with the state-of-the-art methods and the optimality benchmark of Cramér-Rao lower bound.

An analytical optimization model for infrared image enhancement via local context

NASA Astrophysics Data System (ADS)

Xu, Yongjian; Liang, Kun; Xiong, Yiru; Wang, Hui

2017-12-01

The requirement for high-quality infrared images is constantly increasing in both military and civilian areas, and it is always associated with little distortion and appropriate contrast, while infrared images commonly have some shortcomings such as low contrast. In this paper, we propose a novel infrared image histogram enhancement algorithm based on local context. By constraining the enhanced image to have high local contrast, a regularized analytical optimization model is proposed to enhance infrared images. The local contrast is determined by evaluating whether two intensities are neighbors and calculating their differences. The comparison on 8-bit images shows that the proposed method can enhance the infrared images with more details and lower noise.

The trust-region self-consistent field method in Kohn-Sham density-functional theory.

PubMed

Thøgersen, Lea; Olsen, Jeppe; Köhn, Andreas; Jørgensen, Poul; Sałek, Paweł; Helgaker, Trygve

2005-08-15

The trust-region self-consistent field (TRSCF) method is extended to the optimization of the Kohn-Sham energy. In the TRSCF method, both the Roothaan-Hall step and the density-subspace minimization step are replaced by trust-region optimizations of local approximations to the Kohn-Sham energy, leading to a controlled, monotonic convergence towards the optimized energy. Previously the TRSCF method has been developed for optimization of the Hartree-Fock energy, which is a simple quadratic function in the density matrix. However, since the Kohn-Sham energy is a nonquadratic function of the density matrix, the local energy functions must be generalized for use with the Kohn-Sham model. Such a generalization, which contains the Hartree-Fock model as a special case, is presented here. For comparison, a rederivation of the popular direct inversion in the iterative subspace (DIIS) algorithm is performed, demonstrating that the DIIS method may be viewed as a quasi-Newton method, explaining its fast local convergence. In the global region the convergence behavior of DIIS is less predictable. The related energy DIIS technique is also discussed and shown to be inappropriate for the optimization of the Kohn-Sham energy.

Estimating cellular parameters through optimization procedures: elementary principles and applications.

PubMed

Kimura, Akatsuki; Celani, Antonio; Nagao, Hiromichi; Stasevich, Timothy; Nakamura, Kazuyuki

2015-01-01

Construction of quantitative models is a primary goal of quantitative biology, which aims to understand cellular and organismal phenomena in a quantitative manner. In this article, we introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. The aim of optimization is to minimize the sum of squared errors (SSE) in a prediction or to maximize likelihood. A (local) maximum of likelihood or (local) minimum of the SSE can efficiently be identified using gradient approaches. Addition of a stochastic process enables us to identify the global maximum/minimum without becoming trapped in local maxima/minima. Sampling approaches take advantage of increasing computational power to test numerous sets of parameters in order to determine the optimum set. By combining Bayesian inference with gradient or sampling approaches, we can estimate both the optimum parameters and the form of the likelihood function related to the parameters. Finally, we introduce four examples of research that utilize parameter optimization to obtain biological insights from quantified data: transcriptional regulation, bacterial chemotaxis, morphogenesis, and cell cycle regulation. With practical knowledge of parameter optimization, cell and developmental biologists can develop realistic models that reproduce their observations and thus, obtain mechanistic insights into phenomena of interest.

Experiment definition phase shuttle laboratory LDRL-10.6 experiment. [using a molniya satellite and ground communication links

NASA Technical Reports Server (NTRS)

1975-01-01

The acquisition and tracking links of shuttle to molniya satellite and shuttle to ground are established. Link parameters and tolerance are analyzed. A 10-micromillimeter optomechanical subsystem brassboard model was designed and measured for optical properties and weight optimization. The design incorporates an afocal rotating Gregorian telescope in a two-gimbal berylium structure with beam steering control mechanisms. Parameters for both the optomechanical subsystem and spaceborne terminals are included.

Link and Network Layers Design for Ultra-High-Speed Terahertz-Band Communications Networks

DTIC Science & Technology

2017-01-01

throughput, and identify the optimal parameter values for their design (Sec. 6.2.3). Moreover, we validate and test the scheme with experimental data obtained...LINK AND NETWORK LAYERS DESIGN FOR ULTRA-HIGH- SPEED TERAHERTZ-BAND COMMUNICATIONS NETWORKS STATE UNIVERSITY OF NEW YORK (SUNY) AT BUFFALO JANUARY...TYPE FINAL TECHNICAL REPORT 3. DATES COVERED (From - To) FEB 2015 – SEP 2016 4. TITLE AND SUBTITLE LINK AND NETWORK LAYERS DESIGN FOR ULTRA-HIGH

Optimization and throughput estimation of optical ground networks for LEO-downlinks, GEO-feeder links and GEO-relays

NASA Astrophysics Data System (ADS)

Fuchs, Christian; Poulenard, Sylvain; Perlot, Nicolas; Riedi, Jerome; Perdigues, Josep

2017-02-01

Optical satellite communications play an increasingly important role in a number of space applications. However, if the system concept includes optical links to the surface of the Earth, the limited availability due to clouds and other atmospheric impacts need to be considered to give a reliable estimate of the system performance. An OGS network is required for increasing the availability to acceptable figures. In order to realistically estimate the performance and achievable throughput in various scenarios, a simulation tool has been developed under ESA contract. The tool is based on a database of 5 years of cloud data with global coverage and can thus easily simulate different optical ground station network topologies for LEO- and GEO-to-ground links. Further parameters, like e.g. limited availability due to sun blinding and atmospheric turbulence, are considered as well. This paper gives an overview about the simulation tool, the cloud database, as well as the modelling behind the simulation scheme. Several scenarios have been investigated: LEO-to-ground links, GEO feeder links, and GEO relay links. The key results of the optical ground station network optimization and throughput estimations will be presented. The implications of key technical parameters, as e.g. memory size aboard the satellite, will be discussed. Finally, potential system designs for LEO- and GEO-systems will be presented.

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

Luo, Sukun; University of Chinese Academy of Sciences, Beijing 100049; Hu, Kai

HSV-2 is the major cause of genital herpes and its infection increases the risk of HIV-1 acquisition and transmission. HSV-2 glycoprotein B together with glycoproteins D, H and L are indispensable for viral entry, of which gB, as a class III fusogen, plays an essential role. HSV-2 gB has seven potential N-linked glycosylation (N-CHO) sites, but their significance has yet to be determined. For the first time, we systematically analyzed the contributions of N-linked glycans on gB to cell–cell fusion and viral entry. Our results demonstrated that, of the seven potential N-CHO sites on gB, mutation at N390, N483 ormore » N668 decreased cell–cell fusion and viral entry, while mutation at N133 mainly affected protein expression and the production of infectious virus particles by blocking the transport of gB from the endoplasmic reticulum to Golgi. Our findings highlight the significance of N-linked glycans on HSV-2 gB expression and function. - Highlights: • N-linked glycan at N133 is important for gB intracellular trafficking and maturation. • N-linked glycans at N390, N483 and N668 on gB are necessary for optimal cell–cell fusion. • N-linked glycans at N390, N483 and N668 on gB are necessary for optimal viral entry.« less

Locally optimal extracellular stimulation for chaotic desynchronization of neural populations.

PubMed

Wilson, Dan; Moehlis, Jeff

2014-10-01

We use optimal control theory to design a methodology to find locally optimal stimuli for desynchronization of a model of neurons with extracellular stimulation. This methodology yields stimuli which lead to positive Lyapunov exponents, and hence desynchronizes a neural population. We analyze this methodology in the presence of interneuron coupling to make predictions about the strength of stimulation required to overcome synchronizing effects of coupling. This methodology suggests a powerful alternative to pulsatile stimuli for deep brain stimulation as it uses less energy than pulsatile stimuli, and could eliminate the time consuming tuning process.

Decomposition of the linking number of a closed ribbon: A problem from molecular biology

PubMed Central

Fuller, F. Brock

1978-01-01

A closed duplex DNA molecule relaxed and containing nucleosomes has a different linking number from the same molecule relaxed and without nucleosomes. What does this say about the structure of the nucleosome? A mathematical study of this question is made, representing the DNA molecule by a ribbon. It is shown that the linking number of a closed ribbon can be decomposed into the linking number of a reference ribbon plus a sum of locally determined “linking differences.” PMID:16592550

Constraint Optimization Literature Review

DTIC Science & Technology

2015-11-01

COPs. 15. SUBJECT TERMS high-performance computing, mobile ad hoc network, optimization, constraint, satisfaction 16. SECURITY CLASSIFICATION OF: 17...Optimization Problems 1 2.1 Constraint Satisfaction Problems 1 2.2 Constraint Optimization Problems 3 3. Constraint Optimization Algorithms 9 3.1...Constraint Satisfaction Algorithms 9 3.1.1 Brute-Force search 9 3.1.2 Constraint Propagation 10 3.1.3 Depth-First Search 13 3.1.4 Local Search 18

Optimal Learning in Schools--Theoretical Evidence: Part 4 Metacognition

ERIC Educational Resources Information Center

Crossland, John

2017-01-01

Parts 1 and 2 in this four-part series of articles (Crossland, 2016, 2017a) discussed the recent research from neuroscience linked to concepts from cognitive development that brought Piaget's theories into the 21st century and showed the most effective provision towards more optimal learning strategies. Part 2 reviewed Demetriou's latest thinking…

Optimal Learning in Schools--Theoretical Evidence: Part 3 Individual Differences

ERIC Educational Resources Information Center

Crossland, John

2017-01-01

Parts 1 and 2 in this four-part series of articles (Crossland, 2016, 2017) discussed the recent research from neuroscience linked to concepts from cognitive development that brought Piaget's theories into the 21st century and showed the most effective provision towards more optimal learning strategies. Then the discussion moved onto Demetriou's…

Linking Temporal-Optimization and Spatial-Simulation Models for Forest Planning

Treesearch

Larry A. Leefers; Eric J. Gustafson; Phillip Freeman

2003-01-01

Increasingly, resource management agencies and researchers have turned their analysis and modeling efforts towards spatial and temporal information. This is driven by the need to address wildlife concerns, landscape issues, and social/economic questions. Historically, the USDA Forest Service has used optimization models (i.e., FORPLAN and Spectrum) for timber harvest...

Optimizing Word Learning via Links to Perceptual and Motoric Experience

ERIC Educational Resources Information Center

Hald, Lea A.; de Nooijer, Jacqueline; van Gog, Tamara; Bekkering, Harold

2016-01-01

The aim of this review is to consider how current vocabulary training methods could be optimized by considering recent scientific insights in how the brain represents conceptual knowledge. We outline the findings from several methods of vocabulary training. In each case, we consider how taking an embodied cognition perspective could impact word…

Genetic algorithm optimization of transcutaneous energy transmission systems for implantable ventricular assist devices.

PubMed

Byron, Kelly; Bluvshtein, Vlad; Lucke, Lori

2013-01-01

Transcutaneous energy transmission systems (TETS) wirelessly transmit power through the skin. TETS is particularly desirable for ventricular assist devices (VAD), which currently require cables through the skin to power the implanted pump. Optimizing the inductive link of the TET system is a multi-parameter problem. Most current techniques to optimize the design simplify the problem by combining parameters leading to sub-optimal solutions. In this paper we present an optimization method using a genetic algorithm to handle a larger set of parameters, which leads to a more optimal design. Using this approach, we were able to increase efficiency while also reducing power variability in a prototype, compared to a traditional manual design method.

Design optimization studies using COSMIC NASTRAN

NASA Technical Reports Server (NTRS)

Pitrof, Stephen M.; Bharatram, G.; Venkayya, Vipperla B.

1993-01-01

The purpose of this study is to create, test and document a procedure to integrate mathematical optimization algorithms with COSMIC NASTRAN. This procedure is very important to structural design engineers who wish to capitalize on optimization methods to ensure that their design is optimized for its intended application. The OPTNAST computer program was created to link NASTRAN and design optimization codes into one package. This implementation was tested using two truss structure models and optimizing their designs for minimum weight, subject to multiple loading conditions and displacement and stress constraints. However, the process is generalized so that an engineer could design other types of elements by adding to or modifying some parts of the code.

A Figure-of-Merit for Design and Optimization of Inductive Power Transmission Links for Millimeter-Sized Biomedical Implants.

PubMed

Ibrahim, Ahmed; Kiani, Mehdi

2016-12-01

Power transmission efficiency (PTE) has been the key parameter for wireless power transmission (WPT) to biomedical implants with millimeter (mm) dimensions. It has been suggested that for mm-sized implants increasing the power carrier frequency (f p ) of the WPT link to hundreds of MHz improves PTE. However, increasing f p significantly reduces the maximum allowable power that can be transmitted under the specific absorption rate (SAR) constraints. This paper presents a new figure-of-merit (FoM) and a design methodology for optimal WPT to mm-sized implants via inductive coupling by striking a balance between PTE and maximum delivered power under SAR constraints (P L,SAR ). First, the optimal mm-sized receiver (Rx) coil geometry is identified for a wide range of f p to maximize the Rx coil quality factor (Q). Secondly, the optimal transmitter (Tx) coil geometry and f p are found to maximize the proposed FoM under a low-loss Rx matched-load condition. Finally, proper Tx coil and tissue spacing is identified based on FoM at the optimal f p . We demonstrate that f p in order of tens of MHz still offer higher P L,SAR and FoM, which is key in applications that demand high power such as optogenetics. An inductive link to power a 1 mm 3 implant was designed based on our FoM and verified through full-wave electromagnetic field simulations and measurements using de-embedding method. In our measurements, an Rx coil with 1 mm diameter, located 10 mm inside the tissue, achieved PTE and P L,SAR of 1.4% and 2.2 mW at f p of 20 MHz, respectively.

Cross-layer Joint Relay Selection and Power Allocation Scheme for Cooperative Relaying System

NASA Astrophysics Data System (ADS)

Zhi, Hui; He, Mengmeng; Wang, Feiyue; Huang, Ziju

2018-03-01

A novel cross-layer joint relay selection and power allocation (CL-JRSPA) scheme over physical layer and data-link layer is proposed for cooperative relaying system in this paper. Our goal is finding the optimal relay selection and power allocation scheme to maximize system achievable rate when satisfying total transmit power constraint in physical layer and statistical delay quality-of-service (QoS) demand in data-link layer. Using the concept of effective capacity (EC), our goal can be formulated into an optimal joint relay selection and power allocation (JRSPA) problem to maximize the EC when satisfying total transmit power limitation. We first solving optimal power allocation (PA) problem with Lagrange multiplier approach, and then solving optimal relay selection (RS) problem. Simulation results demonstrate that CL-JRSPA scheme gets larger EC than other schemes when satisfying delay QoS demand. In addition, the proposed CL-JRSPA scheme achieves the maximal EC when relay located approximately halfway between source and destination, and EC becomes smaller when the QoS exponent becomes larger.

Utility of coupling nonlinear optimization methods with numerical modeling software

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

Murphy, M.J.

1996-08-05

Results of using GLO (Global Local Optimizer), a general purpose nonlinear optimization software package for investigating multi-parameter problems in science and engineering is discussed. The package consists of the modular optimization control system (GLO), a graphical user interface (GLO-GUI), a pre-processor (GLO-PUT), a post-processor (GLO-GET), and nonlinear optimization software modules, GLOBAL & LOCAL. GLO is designed for controlling and easy coupling to any scientific software application. GLO runs the optimization module and scientific software application in an iterative loop. At each iteration, the optimization module defines new values for the set of parameters being optimized. GLO-PUT inserts the new parametermore » values into the input file of the scientific application. GLO runs the application with the new parameter values. GLO-GET determines the value of the objective function by extracting the results of the analysis and comparing to the desired result. GLO continues to run the scientific application over and over until it finds the ``best`` set of parameters by minimizing (or maximizing) the objective function. An example problem showing the optimization of material model is presented (Taylor cylinder impact test).« less

Combining local search with co-evolution in a remarkably simple way

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

Boettcher, S.; Percus, A.

2000-05-01

The authors explore a new general-purpose heuristic for finding high-quality solutions to hard optimization problem. The method, called extremal optimization, is inspired by self-organized criticality, a concept introduced to describe emergent complexity in physical systems. In contrast to genetic algorithms, which operate on an entire gene-pool of possible solutions, extremal optimization successively replaces extremely undesirable elements of a single sub-optimal solution with new, random ones. Large fluctuations, or avalanches, ensue that efficiently explore many local optima. Drawing upon models used to simulate far-from-equilibrium dynamics, extremal optimization complements heuristics inspired by equilibrium statistical physics, such as simulated annealing. With only onemore » adjustable parameter, its performance has proved competitive with more elaborate methods, especially near phase transitions. Phase transitions are found in many combinatorial optimization problems, and have been conjectured to occur in the region of parameter space containing the hardest instances. We demonstrate how extremal optimization can be implemented for a variety of hard optimization problems. We believe that this will be a useful tool in the investigation of phase transitions in combinatorial optimization, thereby helping to elucidate the origin of computational complexity.« less

Magnetofluorescent nanocomposites and quantum dots used for optimal application in magnetic fluorescence-linked immunoassay.

PubMed

Tsai, H Y; Li, S Y; Fuh, C Bor

2018-03-01

Magnetofluorescent nanocomposites with optimal magnetic and fluorescent properties were prepared and characterized by combining magnetic nanoparticles (iron oxide@polymethyl methacrylate) with fluorescent nanoparticles (rhodamine 6G@mSiO 2 ). Experimental parameters were optimized to produce nanocomposites with high magnetic susceptibility and fluorescence intensity. The detection of a model biomarker (alpha-fetoprotein) was used to demonstrate the feasibility of applying the magnetofluorescent nanocomposites combined with quantum dots and using magnetic fluorescence-linked immunoassay. The magnetofluorescent nanocomposites enable efficient mixing, fast re-concentration, and nanoparticle quantization for optimal reactions. Biofunctional quantum dots were used to confirm the alpha-fetoprotein (AFP) content in sandwich immunoassay after mixing and washing. The analysis time was only one third that required in ELISA. The detection limit was 0.2 pg mL -1 , and the linear range was 0.68 pg mL -1 -6.8 ng mL -1 . This detection limit is lower, and the linear range is wider than those of ELISA and other methods. The measurements made using the proposed method differed by less than 13% from those obtained using ELISA for four AFP concentrations (0.03, 0.15, 0.75, and 3.75 ng mL -1 ). The proposed method has a considerable potential for biomarker detection in various analytical and biomedical applications. Graphical abstract Magnetofluorescent nanocomposites combined with fluorescent quantum dots were used in magnetic fluorescence-linked immunoassay.

Preparing for Local Labor: Curricular Stratification across Local Economies in the United States

ERIC Educational Resources Information Center

Sutton, April

2017-01-01

I investigate how the educational demands of local labor markets shape high school course offerings and student course taking. Using the Education Longitudinal Study of 2002 linked to the U.S. Census 2000, I focus on local economic variation in the share of jobs that do not demand a bachelor's degree. I find that schools in local labor markets…

Optimal Verification of Entangled States with Local Measurements

NASA Astrophysics Data System (ADS)

Pallister, Sam; Linden, Noah; Montanaro, Ashley

2018-04-01

Consider the task of verifying that a given quantum device, designed to produce a particular entangled state, does indeed produce that state. One natural approach would be to characterize the output state by quantum state tomography, or alternatively, to perform some kind of Bell test, tailored to the state of interest. We show here that neither approach is optimal among local verification strategies for 2-qubit states. We find the optimal strategy in this case and show that quadratically fewer total measurements are needed to verify to within a given fidelity than in published results for quantum state tomography, Bell test, or fidelity estimation protocols. We also give efficient verification protocols for any stabilizer state. Additionally, we show that requiring that the strategy be constructed from local, nonadaptive, and noncollective measurements only incurs a constant-factor penalty over a strategy without these restrictions.

Oscillator strengths, first-order properties, and nuclear gradients for local ADC(2).

PubMed

Schütz, Martin

2015-06-07

We describe theory and implementation of oscillator strengths, orbital-relaxed first-order properties, and nuclear gradients for the local algebraic diagrammatic construction scheme through second order. The formalism is derived via time-dependent linear response theory based on a second-order unitary coupled cluster model. The implementation presented here is a modification of our previously developed algorithms for Laplace transform based local time-dependent coupled cluster linear response (CC2LR); the local approximations thus are state specific and adaptive. The symmetry of the Jacobian leads to considerable simplifications relative to the local CC2LR method; as a result, a gradient evaluation is about four times less expensive. Test calculations show that in geometry optimizations, usually very similar geometries are obtained as with the local CC2LR method (provided that a second-order method is applicable). As an exemplary application, we performed geometry optimizations on the low-lying singlet states of chlorophyllide a.

Closed-loop motor control using high-speed fiber optics

NASA Technical Reports Server (NTRS)

Dawson, Reginald (Inventor); Rodriquiz, Dagobert (Inventor)

1991-01-01

A closed-loop control system for controlling the operation of one or more servo motors or other controllable devices is described. The system employs a fiber optics link immune to electromagnetic interference, for transmission of control signals from a controller or controllers at a remote station to the power electronics located in proximity to the motors or other devices at the local station. At the remote station the electrical control signals are time-multiplexed, converted to a formatted serial bit stream, and converted to light signals for transmission over a single fiber of the fiber optics link. At the local station, the received optical signals are reconstructed as electrical control signals for the controlled motors or other devices. At the local station, an encoder sensor linked to the driven device generates encoded feedback signals which provide information as to a condition of the controlled device. The encoded signals are placed in a formatted serial bit stream, multiplexed, and transmitted as optical signals over a second fiber of the fiber optic link which closes the control loop of the closed-loop motor controller. The encoded optical signals received at the remote station are demultiplexed, reconstructed and coupled to the controller(s) as electrical feedback signals.

Development of swellable local implants of a polyethyleneimine-poly(vinyl pyrrolidone) (PEI-PVP) hydrogel as a socket filler.

PubMed

Chang, Ching-Wen; Ho, Hsiu-O; Lo, Yi-June; Lee, Sheng-Yang; Yang, You-Ren; Sheu, Ming-Thau

2012-01-01

In this study, hydrogels composed of polyethyleneimine (PEI) and poly(vinyl pyrrolidone) K90 (PVP) cross-linked with various concentrations (0, 0.125, 0.25 and 0.5%) of glutaraldehyde were evaluated as a hydrogel filler for the local delivery of lidocaine after tooth extraction. The drug-release kinetics, swellability, cytotoxicity and wound healing after tooth extraction of these non-cross-linked and cross-linked PEI-PVP hydrogels were examined in male beagles and compared to values using Spongostan(®). Results demonstrated that the extent of cross-linking influenced the swelling of the resulting hydrogel, but the drug-release rates were similar. No significant changes were observed in gingival fibroblasts in contact with the PEI- PVP hydrogels or Spongostan(®). In the in vivo study, PEI-PVP hydrogels showed good retention in the socket for 2 days and showed comparable wound-healing rates within 2 weeks with those of Spongostan(®). In conclusion, PEI-PVP hydrogels are suitable for use as socket-dressing materials, and the release of local anaesthesia from PEI-PVP hydrogels can be sustained for a desirable period of time to prevent pain after a tooth extraction.

Weighted link graphs: a distributed IDS for secondary intrusion detection and defense

NASA Astrophysics Data System (ADS)

Zhou, Mian; Lang, Sheau-Dong

2005-03-01

While a firewall installed at the perimeter of a local network provides the first line of defense against the hackers, many intrusion incidents are the results of successful penetration of the firewalls. One computer"s compromise often put the entire network at risk. In this paper, we propose an IDS that provides a finer control over the internal network. The system focuses on the variations of connection-based behavior of each single computer, and uses a weighted link graph to visualize the overall traffic abnormalities. The functionality of our system is of a distributed personal IDS system that also provides a centralized traffic analysis by graphical visualization. We use a novel weight assignment schema for the local detection within each end agent. The local abnormalities are quantitatively carried out by the node weight and link weight and further sent to the central analyzer to build the weighted link graph. Thus, we distribute the burden of traffic processing and visualization to each agent and make it more efficient for the overall intrusion detection. As the LANs are more vulnerable to inside attacks, our system is designed as a reinforcement to prevent corruption from the inside.

Open space preservation, property value, and optimal spatial configuration

Treesearch

Yong Jiang; Stephen K. Swallow

2007-01-01

The public has increasingly demonstrated a strong support for open space preservation. How to finance the socially efficient level of open space with the optimal spatial structure is of high policy relevance to local governments. In this study, we developed a spatially explicit open space model to help identify the socially optimal amount and optimal spatial...

Quantum key distribution over an installed multimode optical fiber local area network.

PubMed

Namekata, Naoto; Mori, Shigehiko; Inoue, Shuichiro

2005-12-12

We have investigated the possibility of a multimode fiber link for a quantum channel. Transmission of light in an extremely underfilled mode distribution promises a single-mode-like behavior in the multimode fiber. To demonstrate the performance of the fiber link we performed quantum key distribution, on the basis of the BB84 four-state protocol, over 550 m of an installed multimode optical fiber local area network, and the quantum-bit-error rate of 1.09 percent was achieved.

An unusual birthmark case thought to be linked to a person who had previously died.

PubMed

Keil, H H; Tucker, J B

2000-12-01

The following case report describes a Burmese subject with an unusual birthmark and birth defects thought by local people to be linked to events surrounding the death of his mother's first husband. The nature of the link is explored, including how the assumption of a linkage could have led to subsequent events.

Link removal for the control of stochastically evolving epidemics over networks: a comparison of approaches.

PubMed

Enns, Eva A; Brandeau, Margaret L

2015-04-21

For many communicable diseases, knowledge of the underlying contact network through which the disease spreads is essential to determining appropriate control measures. When behavior change is the primary intervention for disease prevention, it is important to understand how to best modify network connectivity using the limited resources available to control disease spread. We describe and compare four algorithms for selecting a limited number of links to remove from a network: two "preventive" approaches (edge centrality, R0 minimization), where the decision of which links to remove is made prior to any disease outbreak and depends only on the network structure; and two "reactive" approaches (S-I edge centrality, optimal quarantining), where information about the initial disease states of the nodes is incorporated into the decision of which links to remove. We evaluate the performance of these algorithms in minimizing the total number of infections that occur over the course of an acute outbreak of disease. We consider different network structures, including both static and dynamic Erdös-Rényi random networks with varying levels of connectivity, a real-world network of residential hotels connected through injection drug use, and a network exhibiting community structure. We show that reactive approaches outperform preventive approaches in averting infections. Among reactive approaches, removing links in order of S-I edge centrality is favored when the link removal budget is small, while optimal quarantining performs best when the link removal budget is sufficiently large. The budget threshold above which optimal quarantining outperforms the S-I edge centrality algorithm is a function of both network structure (higher for unstructured Erdös-Rényi random networks compared to networks with community structure or the real-world network) and disease infectiousness (lower for highly infectious diseases). We conduct a value-of-information analysis of knowing which nodes are initially infected by comparing the performance improvement achieved by reactive over preventive strategies. We find that such information is most valuable for moderate budget levels, with increasing value as disease spread becomes more likely (due to either increased connectedness of the network or increased infectiousness of the disease). Copyright © 2015 Elsevier Ltd. All rights reserved.

Link removal for the control of stochastically evolving epidemics over networks: A comparison of approaches

PubMed Central

Brandeau, Margaret L.

2015-01-01

For many communicable diseases, knowledge of the underlying contact network through which the disease spreads is essential to determining appropriate control measures. When behavior change is the primary intervention for disease prevention, it is important to understand how to best modify network connectivity using the limited resources available to control disease spread. We describe and compare four algorithms for selecting a limited number of links to remove from a network: two “preventive” approaches (edge centrality, R0 minimization), where the decision of which links to remove is made prior to any disease outbreak and depends only on the network structure; and two “reactive” approaches (S-I edge centrality, optimal quarantining), where information about the initial disease states of the nodes is incorporated into the decision of which links to remove. We evaluate the performance of these algorithms in minimizing the total number of infections that occur over the course of an acute outbreak of disease. We consider different network structures, including both static and dynamic Erdős-Rényi random networks with varying levels of connectivity, a real-world network of residential hotels connected through injection drug use, and a network exhibiting community structure. We show that reactive approaches outperform preventive approaches in averting infections. Among reactive approaches, removing links in order of S-I edge centrality is favored when the link removal budget is small, while optimal quarantining performs best when the link removal budget is sufficiently large. The budget threshold above which optimal quarantining outperforms the S-I edge centrality algorithm is a function of both network structure (higher for unstructured Erdős-Rényi random networks compared to networks with community structure or the real-world network) and disease infectiousness (lower for highly infectious diseases). We conduct a value-of-information analysis of knowing which nodes are initially infected by comparing the performance improvement achieved by reactive over preventive strategies. We find that such information is most valuable for moderate budget levels, with increasing value as disease spread becomes more likely (due to either increased connectedness of the network or increased infectiousness of the disease). PMID:25698229

Energy Efficiency Maximization of Practical Wireless Communication Systems

NASA Astrophysics Data System (ADS)

Eraslan, Eren

Energy consumption of the modern wireless communication systems is rapidly growing due to the ever-increasing data demand and the advanced solutions employed in order to address this demand, such as multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) techniques. These MIMO systems are power hungry, however, they are capable of changing the transmission parameters, such as number of spatial streams, number of transmitter/receiver antennas, modulation, code rate, and transmit power. They can thus choose the best mode out of possibly thousands of modes in order to optimize an objective function. This problem is referred to as the link adaptation problem. In this work, we focus on the link adaptation for energy efficiency maximization problem, which is defined as choosing the optimal transmission mode to maximize the number of successfully transmitted bits per unit energy consumed by the link. We model the energy consumption and throughput performances of a MIMO-OFDM link and develop a practical link adaptation protocol, which senses the channel conditions and changes its transmission mode in real-time. It turns out that the brute force search, which is usually assumed in previous works, is prohibitively complex, especially when there are large numbers of transmit power levels to choose from. We analyze the relationship between the energy efficiency and transmit power, and prove that energy efficiency of a link is a single-peaked quasiconcave function of transmit power. This leads us to develop a low-complexity algorithm that finds a near-optimal transmit power and take this dimension out of the search space. We further prune the search space by analyzing the singular value decomposition of the channel and excluding the modes that use higher number of spatial streams than the channel can support. These algorithms and our novel formulations provide simpler computations and limit the search space into a much smaller set; hence reducing the computational complexity by orders of magnitude without sacrificing the performance. The result of this work is a highly practical link adaptation protocol for maximizing the energy efficiency of modern wireless communication systems. Simulation results show orders of magnitude gain in the energy efficiency of the link. We also implemented the link adaptation protocol on real-time MIMO-OFDM radios and we report on the experimental results. To the best of our knowledge, this is the first reported testbed that is capable of performing energy-efficient fast link adaptation using PHY layer information.

Comparative evaluation of endodontic pressure syringe, insulin syringe, jiffy tube, and local anesthetic syringe in obturation of primary teeth: An in vitro study.

PubMed

Hiremath, Mallayya C; Srivastava, Pooja

2016-01-01

The purpose of this in vitro study was to compare four methods of root canal obturation in primary teeth using conventional radiography. A total of 96 root canals of primary molars were prepared and obturated with zinc oxide eugenol. Obturation methods compared were endodontic pressure syringe, insulin syringe, jiffy tube, and local anesthetic syringe. The root canal obturations were evaluated by conventional radiography for the length of obturation and presence of voids. The obtained data were analyzed using Chi-square test. The results showed significant differences between the four groups for the length of obturation (P < 0.05). The endodontic pressure syringe showed the best results (98.5% optimal fillings) and jiffy tube showed the poor results (37.5% optimal fillings) for the length of obturation. The insulin syringe (79.2% optimal fillings) and local anesthetic syringe (66.7% optimal fillings) showed acceptable results for the length of root canal obturation. However, minor voids were present in all the four techniques used. Endodontic pressure syringe produced the best results in terms of length of obturation and controlling paste extrusion from the apical foramen. However, insulin syringe and local anesthetic syringe can be used as effective alternative methods.

Optimal control to modelling motorcycle rider steering: local versus global coordinate systems in rider preview

NASA Astrophysics Data System (ADS)

Rowell, S.; Popov, A. A.; Meijaard, J. P.

2010-04-01

The response of a motorcycle is heavily dependent on the rider's control actions, and consequently a means of replicating the rider's behaviour provides an important extension to motorcycle dynamics. The primary objective here is to develop effective path-following simulations and to understand how riders control motorcycles. Optimal control theory is applied to the tracking of roadway by a motorcycle, using a non-linear motorcycle model operating in free control by steering torque input. A path-following controller with road preview is designed by minimising tracking errors and control effort. Tight controls with high weightings on performance and loose controls with high weightings on control power are defined. Special attention is paid to the modelling of multipoint preview in local and global coordinate systems. The controller model is simulated over a standard single lane-change manoeuvre. It is argued that the local coordinates point of view is more representative of the way that a human rider operates and interprets information. The simulations suggest that for accurate path following, using optimal control, the problem must be solved by the local coordinates approach in order to achieve accurate results with short preview horizons. Furthermore, some weaknesses of the optimal control approach are highlighted here.

Mid-sagittal plane and mid-sagittal surface optimization in brain MRI using a local symmetry measure

NASA Astrophysics Data System (ADS)

Stegmann, Mikkel B.; Skoglund, Karl; Ryberg, Charlotte

2005-04-01

This paper describes methods for automatic localization of the mid-sagittal plane (MSP) and mid-sagittal surface (MSS). The data used is a subset of the Leukoaraiosis And DISability (LADIS) study consisting of three-dimensional magnetic resonance brain data from 62 elderly subjects (age 66 to 84 years). Traditionally, the mid-sagittal plane is localized by global measures. However, this approach fails when the partitioning plane between the brain hemispheres does not coincide with the symmetry plane of the head. We instead propose to use a sparse set of profiles in the plane normal direction and maximize the local symmetry around these using a general-purpose optimizer. The plane is parameterized by azimuth and elevation angles along with the distance to the origin in the normal direction. This approach leads to solutions confirmed as the optimal MSP in 98 percent of the subjects. Despite the name, the mid-sagittal plane is not always planar, but a curved surface resulting in poor partitioning of the brain hemispheres. To account for this, this paper also investigates an optimization strategy which fits a thin-plate spline surface to the brain data using a robust least median of squares estimator. Albeit computationally more expensive, mid-sagittal surface fitting demonstrated convincingly better partitioning of curved brains into cerebral hemispheres.

Linking Place and Mind: Localness As a Factor in Socio-Cognitive Salience

PubMed Central

Jensen, Marie M.

2016-01-01

This paper investigates the salience of vernacular Tyneside forms on the basis of theories of enregisterment and exemplar processing. On one level, exemplar theory provides a psycholinguistic account of how the link between social value and linguistic features is possible. Conversely, integrating the notion of social value into exemplar theory extends the value of this originally cognitive theory to social domains. It is suggested that the association of social value and particular local, linguistic forms may contribute to the salience of these forms among local speakers. The empirical work reported here takes the form of a questionnaire study, which aims to uncover Tyneside inhabitants' awareness of forms as well as their affiliation with the local community. Results showed differences in frequency perceptions between participants themselves and others which indicate that speakers can identify local forms as such, but that the variety is stigmatized. The strength of local affiliation correlated with participants' own language use and it is suggested that this can be accounted for by employing a social personae explanation, where speakers use certain salient forms to index local belonging despite overt stigma. PMID:27524976

Estimating 3D positions and velocities of projectiles from monocular views.

PubMed

Ribnick, Evan; Atev, Stefan; Papanikolopoulos, Nikolaos P

2009-05-01

In this paper, we consider the problem of localizing a projectile in 3D based on its apparent motion in a stationary monocular view. A thorough theoretical analysis is developed, from which we establish the minimum conditions for the existence of a unique solution. The theoretical results obtained have important implications for applications involving projectile motion. A robust, nonlinear optimization-based formulation is proposed, and the use of a local optimization method is justified by detailed examination of the local convexity structure of the cost function. The potential of this approach is validated by experimental results.

Global Optimization of Low-Thrust Interplanetary Trajectories Subject to Operational Constraints

NASA Technical Reports Server (NTRS)

Englander, Jacob A.; Vavrina, Matthew A.; Hinckley, David

2016-01-01

Low-thrust interplanetary space missions are highly complex and there can be many locally optimal solutions. While several techniques exist to search for globally optimal solutions to low-thrust trajectory design problems, they are typically limited to unconstrained trajectories. The operational design community in turn has largely avoided using such techniques and has primarily focused on accurate constrained local optimization combined with grid searches and intuitive design processes at the expense of efficient exploration of the global design space. This work is an attempt to bridge the gap between the global optimization and operational design communities by presenting a mathematical framework for global optimization of low-thrust trajectories subject to complex constraints including the targeting of planetary landing sites, a solar range constraint to simplify the thermal design of the spacecraft, and a real-world multi-thruster electric propulsion system that must switch thrusters on and off as available power changes over the course of a mission.

Cache Locality Optimization for Recursive Programs

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

Lifflander, Jonathan; Krishnamoorthy, Sriram

We present an approach to optimize the cache locality for recursive programs by dynamically splicing--recursively interleaving--the execution of distinct function invocations. By utilizing data effect annotations, we identify concurrency and data reuse opportunities across function invocations and interleave them to reduce reuse distance. We present algorithms that efficiently track effects in recursive programs, detect interference and dependencies, and interleave execution of function invocations using user-level (non-kernel) lightweight threads. To enable multi-core execution, a program is parallelized using a nested fork/join programming model. Our cache optimization strategy is designed to work in the context of a random work stealing scheduler. Wemore » present an implementation using the MIT Cilk framework that demonstrates significant improvements in sequential and parallel performance, competitive with a state-of-the-art compile-time optimizer for loop programs and a domain- specific optimizer for stencil programs.« less

Optimal charge control strategies for stationary photovoltaic battery systems

NASA Astrophysics Data System (ADS)

Li, Jiahao; Danzer, Michael A.

2014-07-01

Battery systems coupled to photovoltaic (PV) modules for example fulfill one major function: they locally decouple PV generation and consumption of electrical power leading to two major effects. First, they reduce the grid load, especially at peak times and therewith reduce the necessity of a network expansion. And second, they increase the self-consumption in households and therewith help to reduce energy expenses. For the management of PV batteries charge control strategies need to be developed to reach the goals of both the distribution system operators and the local power producer. In this work optimal control strategies regarding various optimization goals are developed on the basis of the predicted household loads and PV generation profiles using the method of dynamic programming. The resulting charge curves are compared and essential differences discussed. Finally, a multi-objective optimization shows that charge control strategies can be derived that take all optimization goals into account.

A near-optimal low complexity sensor fusion technique for accurate indoor localization based on ultrasound time of arrival measurements from low-quality sensors

NASA Astrophysics Data System (ADS)

Mitilineos, Stelios A.; Argyreas, Nick D.; Thomopoulos, Stelios C. A.

2009-05-01

A fusion-based localization technique for location-based services in indoor environments is introduced herein, based on ultrasound time-of-arrival measurements from multiple off-the-shelf range estimating sensors which are used in a market-available localization system. In-situ field measurements results indicated that the respective off-the-shelf system was unable to estimate position in most of the cases, while the underlying sensors are of low-quality and yield highly inaccurate range and position estimates. An extensive analysis is performed and a model of the sensor-performance characteristics is established. A low-complexity but accurate sensor fusion and localization technique is then developed, which consists inof evaluating multiple sensor measurements and selecting the one that is considered most-accurate based on the underlying sensor model. Optimality, in the sense of a genie selecting the optimum sensor, is subsequently evaluated and compared to the proposed technique. The experimental results indicate that the proposed fusion method exhibits near-optimal performance and, albeit being theoretically suboptimal, it largely overcomes most flaws of the underlying single-sensor system resulting in a localization system of increased accuracy, robustness and availability.

Glocal clinical registries: pacemaker registry design and implementation for global and local integration--methodology and case study.

PubMed

da Silva, Kátia Regina; Costa, Roberto; Crevelari, Elizabeth Sartori; Lacerda, Marianna Sobral; de Moraes Albertini, Caio Marcos; Filho, Martino Martinelli; Santana, José Eduardo; Vissoci, João Ricardo Nickenig; Pietrobon, Ricardo; Barros, Jacson V

2013-01-01

The ability to apply standard and interoperable solutions for implementing and managing medical registries as well as aggregate, reproduce, and access data sets from legacy formats and platforms to advanced standard formats and operating systems are crucial for both clinical healthcare and biomedical research settings. Our study describes a reproducible, highly scalable, standard framework for a device registry implementation addressing both local data quality components and global linking problems. We developed a device registry framework involving the following steps: (1) Data standards definition and representation of the research workflow, (2) Development of electronic case report forms using REDCap (Research Electronic Data Capture), (3) Data collection according to the clinical research workflow and, (4) Data augmentation by enriching the registry database with local electronic health records, governmental database and linked open data collections, (5) Data quality control and (6) Data dissemination through the registry Web site. Our registry adopted all applicable standardized data elements proposed by American College Cardiology / American Heart Association Clinical Data Standards, as well as variables derived from cardiac devices randomized trials and Clinical Data Interchange Standards Consortium. Local interoperability was performed between REDCap and data derived from Electronic Health Record system. The original data set was also augmented by incorporating the reimbursed values paid by the Brazilian government during a hospitalization for pacemaker implantation. By linking our registry to the open data collection repository Linked Clinical Trials (LinkedCT) we found 130 clinical trials which are potentially correlated with our pacemaker registry. This study demonstrates how standard and reproducible solutions can be applied in the implementation of medical registries to constitute a re-usable framework. Such approach has the potential to facilitate data integration between healthcare and research settings, also being a useful framework to be used in other biomedical registries.

Optimization of spatiotemporally fractionated radiotherapy treatments with bounds on the achievable benefit

NASA Astrophysics Data System (ADS)

Gaddy, Melissa R.; Yıldız, Sercan; Unkelbach, Jan; Papp, Dávid

2018-01-01

Spatiotemporal fractionation schemes, that is, treatments delivering different dose distributions in different fractions, can potentially lower treatment side effects without compromising tumor control. This can be achieved by hypofractionating parts of the tumor while delivering approximately uniformly fractionated doses to the surrounding tissue. Plan optimization for such treatments is based on biologically effective dose (BED); however, this leads to computationally challenging nonconvex optimization problems. Optimization methods that are in current use yield only locally optimal solutions, and it has hitherto been unclear whether these plans are close to the global optimum. We present an optimization framework to compute rigorous bounds on the maximum achievable normal tissue BED reduction for spatiotemporal plans. The approach is demonstrated on liver tumors, where the primary goal is to reduce mean liver BED without compromising any other treatment objective. The BED-based treatment plan optimization problems are formulated as quadratically constrained quadratic programming (QCQP) problems. First, a conventional, uniformly fractionated reference plan is computed using convex optimization. Then, a second, nonconvex, QCQP model is solved to local optimality to compute a spatiotemporally fractionated plan that minimizes mean liver BED, subject to the constraints that the plan is no worse than the reference plan with respect to all other planning goals. Finally, we derive a convex relaxation of the second model in the form of a semidefinite programming problem, which provides a rigorous lower bound on the lowest achievable mean liver BED. The method is presented on five cases with distinct geometries. The computed spatiotemporal plans achieve 12-35% mean liver BED reduction over the optimal uniformly fractionated plans. This reduction corresponds to 79-97% of the gap between the mean liver BED of the uniform reference plans and our lower bounds on the lowest achievable mean liver BED. The results indicate that spatiotemporal treatments can achieve substantial reductions in normal tissue dose and BED, and that local optimization techniques provide high-quality plans that are close to realizing the maximum potential normal tissue dose reduction.

Fragment-Based Drug Design Facilitated by Protein-Templated Click Chemistry: Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin.

PubMed

Mondal, Milon; Unver, M Yagiz; Pal, Asish; Bakker, Matthijs; Berrier, Stephan P; Hirsch, Anna K H

2016-10-10

There is an urgent need for the development of efficient methodologies that accelerate drug discovery. We demonstrate that the strategic combination of fragment linking/optimization and protein-templated click chemistry is an efficient and powerful method that accelerates the hit-identification process for the aspartic protease endothiapepsin. The best binder, which inhibits endothiapepsin with an IC 50 value of 43 μm, represents the first example of triazole-based inhibitors of endothiapepsin. Our strategy could find application on a whole range of drug targets. © 2016 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Percolation threshold determines the optimal population density for public cooperation

NASA Astrophysics Data System (ADS)

Wang, Zhen; Szolnoki, Attila; Perc, Matjaž

2012-03-01

While worldwide census data provide statistical evidence that firmly link the population density with several indicators of social welfare, the precise mechanisms underlying these observations are largely unknown. Here we study the impact of population density on the evolution of public cooperation in structured populations and find that the optimal density is uniquely related to the percolation threshold of the host graph irrespective of its topological details. We explain our observations by showing that spatial reciprocity peaks in the vicinity of the percolation threshold, when the emergence of a giant cooperative cluster is hindered neither by vacancy nor by invading defectors, thus discovering an intuitive yet universal law that links the population density with social prosperity.

A sensitive monoclonal antibody-based enzyme-linked immunosorbent assay for chlorpyrifos residue determination in Chinese agricultural smaples

USDA-ARS?s Scientific Manuscript database

A monoclonal antibody-based competitive antibody-coated enzyme-linked immunosorbent assay (ELISA) was developed and optimized for determining chlorpyrifos residue in agricultural products. The IC50 and IC10 of this ELISA were 3.3 ng/mL and 0.1 ng/mL respectively. The average recoveries recovery rate...

Toward Optimal Manifold Hashing via Discrete Locally Linear Embedding.

PubMed

Rongrong Ji; Hong Liu; Liujuan Cao; Di Liu; Yongjian Wu; Feiyue Huang

2017-11-01

Binary code learning, also known as hashing, has received increasing attention in large-scale visual search. By transforming high-dimensional features to binary codes, the original Euclidean distance is approximated via Hamming distance. More recently, it is advocated that it is the manifold distance, rather than the Euclidean distance, that should be preserved in the Hamming space. However, it retains as an open problem to directly preserve the manifold structure by hashing. In particular, it first needs to build the local linear embedding in the original feature space, and then quantize such embedding to binary codes. Such a two-step coding is problematic and less optimized. Besides, the off-line learning is extremely time and memory consuming, which needs to calculate the similarity matrix of the original data. In this paper, we propose a novel hashing algorithm, termed discrete locality linear embedding hashing (DLLH), which well addresses the above challenges. The DLLH directly reconstructs the manifold structure in the Hamming space, which learns optimal hash codes to maintain the local linear relationship of data points. To learn discrete locally linear embeddingcodes, we further propose a discrete optimization algorithm with an iterative parameters updating scheme. Moreover, an anchor-based acceleration scheme, termed Anchor-DLLH, is further introduced, which approximates the large similarity matrix by the product of two low-rank matrices. Experimental results on three widely used benchmark data sets, i.e., CIFAR10, NUS-WIDE, and YouTube Face, have shown superior performance of the proposed DLLH over the state-of-the-art approaches.

Globally optimal trial design for local decision making.

PubMed

Eckermann, Simon; Willan, Andrew R

2009-02-01

Value of information methods allows decision makers to identify efficient trial design following a principle of maximizing the expected value to decision makers of information from potential trial designs relative to their expected cost. However, in health technology assessment (HTA) the restrictive assumption has been made that, prospectively, there is only expected value of sample information from research commissioned within jurisdiction. This paper extends the framework for optimal trial design and decision making within jurisdiction to allow for optimal trial design across jurisdictions. This is illustrated in identifying an optimal trial design for decision making across the US, the UK and Australia for early versus late external cephalic version for pregnant women presenting in the breech position. The expected net gain from locally optimal trial designs of US$0.72M is shown to increase to US$1.14M with a globally optimal trial design. In general, the proposed method of globally optimal trial design improves on optimal trial design within jurisdictions by: (i) reflecting the global value of non-rival information; (ii) allowing optimal allocation of trial sample across jurisdictions; (iii) avoiding market failure associated with free-rider effects, sub-optimal spreading of fixed costs and heterogeneity of trial information with multiple trials. Copyright (c) 2008 John Wiley & Sons, Ltd.

PSO Algorithm Particle Filters for Improving the Performance of Lane Detection and Tracking Systems in Difficult Roads

PubMed Central

Cheng, Wen-Chang

2012-01-01

In this paper we propose a robust lane detection and tracking method by combining particle filters with the particle swarm optimization method. This method mainly uses the particle filters to detect and track the local optimum of the lane model in the input image and then seeks the global optimal solution of the lane model by a particle swarm optimization method. The particle filter can effectively complete lane detection and tracking in complicated or variable lane environments. However, the result obtained is usually a local optimal system status rather than the global optimal system status. Thus, the particle swarm optimization method is used to further refine the global optimal system status in all system statuses. Since the particle swarm optimization method is a global optimization algorithm based on iterative computing, it can find the global optimal lane model by simulating the food finding way of fish school or insects under the mutual cooperation of all particles. In verification testing, the test environments included highways and ordinary roads as well as straight and curved lanes, uphill and downhill lanes, lane changes, etc. Our proposed method can complete the lane detection and tracking more accurately and effectively then existing options. PMID:23235453

Cross Layer Design for Optimizing Transmission Reliability, Energy Efficiency, and Lifetime in Body Sensor Networks.

PubMed

Chen, Xi; Xu, Yixuan; Liu, Anfeng

2017-04-19

High transmission reliability, energy efficiency, and long lifetime are pivotal issues for wireless body area networks (WBANs. However, these performance metrics are not independent of each other, making it hard to obtain overall improvements through optimizing one single aspect. Therefore, a Cross Layer Design Optimal (CLDO) scheme is proposed to simultaneously optimize transmission reliability, energy efficiency, and lifetime of WBANs from several layers. Firstly, due to the fact that the transmission power of nodes directly influences the reliability of links, the optimized transmission power of different nodes is deduced, which is able to maximize energy efficiency in theory under the premise that requirements on delay and jitter are fulfilled. Secondly, a relay decision algorithm is proposed to choose optimized relay nodes. Using this algorithm, nodes will choose relay nodes that ensure a balance of network energy consumption, provided that all nodes transmit with optimized transmission power and the same packet size. Thirdly, the energy consumption of nodes is still unbalanced even with optimized transmission power because of their different locations in the topology of the network. In addition, packet size also has an impact on final performance metrics. Therefore, a synthesized cross layer method for optimization is proposed. With this method, the transmission power of nodes with more residual energy will be enhanced while suitable packet size is determined for different links in the network, leading to further improvements in the WBAN system. Both our comprehensive theoretical analysis and experimental results indicate that the performance of our proposed scheme is better than reported in previous studies. Relative to the relay selection and power control game (RSPCG) scheme, the CLDO scheme can enhance transmission reliability by more than 44.6% and prolong the lifetime by as much as 33.2%.

Cross Layer Design for Optimizing Transmission Reliability, Energy Efficiency, and Lifetime in Body Sensor Networks

PubMed Central

Chen, Xi; Xu, Yixuan; Liu, Anfeng

2017-01-01

High transmission reliability, energy efficiency, and long lifetime are pivotal issues for wireless body area networks (WBANs). However, these performance metrics are not independent of each other, making it hard to obtain overall improvements through optimizing one single aspect. Therefore, a Cross Layer Design Optimal (CLDO) scheme is proposed to simultaneously optimize transmission reliability, energy efficiency, and lifetime of WBANs from several layers. Firstly, due to the fact that the transmission power of nodes directly influences the reliability of links, the optimized transmission power of different nodes is deduced, which is able to maximize energy efficiency in theory under the premise that requirements on delay and jitter are fulfilled. Secondly, a relay decision algorithm is proposed to choose optimized relay nodes. Using this algorithm, nodes will choose relay nodes that ensure a balance of network energy consumption, provided that all nodes transmit with optimized transmission power and the same packet size. Thirdly, the energy consumption of nodes is still unbalanced even with optimized transmission power because of their different locations in the topology of the network. In addition, packet size also has an impact on final performance metrics. Therefore, a synthesized cross layer method for optimization is proposed. With this method, the transmission power of nodes with more residual energy will be enhanced while suitable packet size is determined for different links in the network, leading to further improvements in the WBAN system. Both our comprehensive theoretical analysis and experimental results indicate that the performance of our proposed scheme is better than reported in previous studies. Relative to the relay selection and power control game (RSPCG) scheme, the CLDO scheme can enhance transmission reliability by more than 44.6% and prolong the lifetime by as much as 33.2%. PMID:28422062

A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks.

PubMed

Gallos, Lazaros K; Makse, Hernán A; Sigman, Mariano

2012-02-21

The human brain is organized in functional modules. Such an organization presents a basic conundrum: Modules ought to be sufficiently independent to guarantee functional specialization and sufficiently connected to bind multiple processors for efficient information transfer. It is commonly accepted that small-world architecture of short paths and large local clustering may solve this problem. However, there is intrinsic tension between shortcuts generating small worlds and the persistence of modularity, a global property unrelated to local clustering. Here, we present a possible solution to this puzzle. We first show that a modified percolation theory can define a set of hierarchically organized modules made of strong links in functional brain networks. These modules are "large-world" self-similar structures and, therefore, are far from being small-world. However, incorporating weaker ties to the network converts it into a small world preserving an underlying backbone of well-defined modules. Remarkably, weak ties are precisely organized as predicted by theory maximizing information transfer with minimal wiring cost. This trade-off architecture is reminiscent of the "strength of weak ties" crucial concept of social networks. Such a design suggests a natural solution to the paradox of efficient information flow in the highly modular structure of the brain.

A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks

PubMed Central

Gallos, Lazaros K.; Makse, Hernán A.; Sigman, Mariano

2012-01-01

The human brain is organized in functional modules. Such an organization presents a basic conundrum: Modules ought to be sufficiently independent to guarantee functional specialization and sufficiently connected to bind multiple processors for efficient information transfer. It is commonly accepted that small-world architecture of short paths and large local clustering may solve this problem. However, there is intrinsic tension between shortcuts generating small worlds and the persistence of modularity, a global property unrelated to local clustering. Here, we present a possible solution to this puzzle. We first show that a modified percolation theory can define a set of hierarchically organized modules made of strong links in functional brain networks. These modules are “large-world” self-similar structures and, therefore, are far from being small-world. However, incorporating weaker ties to the network converts it into a small world preserving an underlying backbone of well-defined modules. Remarkably, weak ties are precisely organized as predicted by theory maximizing information transfer with minimal wiring cost. This trade-off architecture is reminiscent of the “strength of weak ties” crucial concept of social networks. Such a design suggests a natural solution to the paradox of efficient information flow in the highly modular structure of the brain. PMID:22308319

In vivo disruption of T cell development by expression of a dominant-negative polypeptide designed to abolish the SLP-76/Gads interaction.

PubMed

Jordan, Martha S; Maltzman, Jonathan S; Kliche, Stefanie; Shabason, Jacob; Smith, Jennifer E; Obstfeld, Amrom; Schraven, Burkhart; Koretzky, Gary A

2007-10-01

Multi-molecular complexes nucleated by adaptor proteins play a central role in signal transduction. In T cells, one central axis consists of the assembly of several signaling proteins linked together by the adaptors linker of activated T cells (LAT), Src homology 2 domain-containing leukocyte-specific phosphoprotein of 76 kDa (SLP-76), and Grb2-related adaptor downstream of Shc (Gads). Each of these adaptors has been shown to be important for normal T cell development, and their proper sub-cellular localization is critical for optimal function in cell lines. We previously demonstrated in Jurkat T cells and a rat basophilic leukemic cell line that expression of a 50-amino acid polypeptide identical to the site on SLP-76 that binds to Gads blocks proper localization of SLP-76 and SLP-76-dependent signaling events. Here we extend these studies to investigate the ability of this polypeptide to inhibit TCR-induced integrin activity in Jurkat cells and to inhibit in vivo thymocyte development and primary T cell function. These data provide evidence for the in vivo function of a dominant-negative peptide based upon the biology of SLP-76 action and suggest the possibility of therapeutic potential of targeting the SLP-76/Gads interaction.

Community Detection in Complex Networks via Clique Conductance.

PubMed

Lu, Zhenqi; Wahlström, Johan; Nehorai, Arye

2018-04-13

Network science plays a central role in understanding and modeling complex systems in many areas including physics, sociology, biology, computer science, economics, politics, and neuroscience. One of the most important features of networks is community structure, i.e., clustering of nodes that are locally densely interconnected. Communities reveal the hierarchical organization of nodes, and detecting communities is of great importance in the study of complex systems. Most existing community-detection methods consider low-order connection patterns at the level of individual links. But high-order connection patterns, at the level of small subnetworks, are generally not considered. In this paper, we develop a novel community-detection method based on cliques, i.e., local complete subnetworks. The proposed method overcomes the deficiencies of previous similar community-detection methods by considering the mathematical properties of cliques. We apply the proposed method to computer-generated graphs and real-world network datasets. When applied to networks with known community structure, the proposed method detects the structure with high fidelity and sensitivity. When applied to networks with no a priori information regarding community structure, the proposed method yields insightful results revealing the organization of these complex networks. We also show that the proposed method is guaranteed to detect near-optimal clusters in the bipartition case.

Comparison of growth texture in round Bi2212 and flat Bi2223 wires and its relation to high critical current density development

DOE PAGES

Kametani, F.; Jiang, J.; Matras, M.; ...

2015-02-10

Why Bi₂Sr₂CaCu₂O x (Bi2212) allows high critical current density J c in round wires rather than only in the anisotropic tape form demanded by all other high temperature superconductors is important for future magnet applications. Here we compare the local texture of state-of-the-art Bi2212 and Bi2223 ((Bi,Pb)₂Sr₂Ca₂Cu₃O₁₀), finding that round wire Bi2212 generates a dominant a-axis growth texture that also enforces a local biaxial texture (FWHM <15°) while simultaneously allowing the c-axes of its polycrystals to rotate azimuthally along and about the filament axis so as to generate macroscopically isotropic behavior. By contrast Bi2223 shows only a uniaxial (FWHM <15°)more » c-axis texture perpendicular to the tape plane without any in-plane texture. Consistent with these observations, a marked, field-increasing, field-decreasing J c(H) hysteresis characteristic of weak-linked systems appears in Bi2223 but is absent in Bi2212 round wire. Growth-induced texture on cooling from the melt step of the Bi2212 J c optimization process appears to be the key step in generating this highly desirable microstructure.« less

Links between local language competence and peer relations among Swiss and immigrant children: the mediating role of social behavior.

PubMed

von Grünigen, Renate; Kochenderfer-Ladd, Becky; Perren, Sonja; Alsaker, Françoise D

2012-04-01

The primary aim of this investigation was to evaluate a model in which children's social behaviors, including prosocial behavior, setting limits, and social withdrawal, were hypothesized to mediate the links between local language competence (LLC) and peer acceptance and victimization. Longitudinal data were collected via teacher and peer reports on 541 (286 boys and 255 girls) immigrant and Swiss native 5-to-6 year-old kindergarteners. Results showed the immigrant children were less fluent in the local language compared to native Swiss classmates. Moreover, results from structural equation models, with bootstrap tests of indirect effects, indicated that social behaviors mediated the link between LLC and the quality of children's peer relationships. Implications of these findings for school professionals are discussed, such as the need to help immigrant children make a smoother transition to their host communities by providing additional language and social supports while children acculturate and acclimate to their new surroundings and peer group. Published by Elsevier Ltd.

In vivo covalent cross-linking of photon-converted rare-earth nanostructures for tumour localization and theranostics

NASA Astrophysics Data System (ADS)

Ai, Xiangzhao; Ho, Chris Jun Hui; Aw, Junxin; Attia, Amalina Binte Ebrahim; Mu, Jing; Wang, Yu; Wang, Xiaoyong; Wang, Yong; Liu, Xiaogang; Chen, Huabing; Gao, Mingyuan; Chen, Xiaoyuan; Yeow, Edwin K. L.; Liu, Gang; Olivo, Malini; Xing, Bengang

2016-01-01

The development of precision nanomedicines to direct nanostructure-based reagents into tumour-targeted areas remains a critical challenge in clinics. Chemical reaction-mediated localization in response to tumour environmental perturbations offers promising opportunities for rational design of effective nano-theranostics. Here, we present a unique microenvironment-sensitive strategy for localization of peptide-premodified upconversion nanocrystals (UCNs) within tumour areas. Upon tumour-specific cathepsin protease reactions, the cleavage of peptides induces covalent cross-linking between the exposed cysteine and 2-cyanobenzothiazole on neighbouring particles, thus triggering the accumulation of UCNs into tumour site. Such enzyme-triggered cross-linking of UCNs leads to enhanced upconversion emission upon 808 nm laser irradiation, and in turn amplifies the singlet oxygen generation from the photosensitizers attached on UCNs. Importantly, this design enables remarkable tumour inhibition through either intratumoral UCNs injection or intravenous injection of nanoparticles modified with the targeting ligand. Our strategy may provide a multimodality solution for effective molecular sensing and site-specific tumour treatment.

Responses to climate change in hot desert ecosystems: connecting local to global scales

USDA-ARS?s Scientific Manuscript database

The consequences of connectivity in resources, propagules, and information to the interplay between drivers and responses across scales can result in ecological dynamics that are not easily predicted based on local drivers. Three major classes of connectivity events link local ecological dynamics wi...

Optimal Sensor Layouts in Underwater Locomotory Systems

NASA Astrophysics Data System (ADS)

Colvert, Brendan; Kanso, Eva

2015-11-01

Retrieving and understanding global flow characteristics from local sensory measurements is a challenging but extremely relevant problem in fields such as defense, robotics, and biomimetics. It is an inverse problem in that the goal is to translate local information into global flow properties. In this talk we present techniques for optimization of sensory layouts within the context of an idealized underwater locomotory system. Using techniques from fluid mechanics and control theory, we show that, under certain conditions, local measurements can inform the submerged body about its orientation relative to the ambient flow, and allow it to recognize local properties of shear flows. We conclude by commenting on the relevance of these findings to underwater navigation in engineered systems and live organisms.

Grants and Funding for State and Local Transportation

EPA Pesticide Factsheets

State and Local Transportation resources are for air quality and transportation government and community leaders. Guidance, strategies and links to grant opportunities are offered for reducing vehicle air pollution, including ozone or smog.

Design optimization of aircraft landing gear assembly under dynamic loading

NASA Astrophysics Data System (ADS)

Wong, Jonathan Y. B.

As development cycles and prototyping iterations begin to decrease in the aerospace industry, it is important to develop and improve practical methodologies to meet all design metrics. This research presents an efficient methodology that applies high-fidelity multi-disciplinary design optimization techniques to commercial landing gear assemblies, for weight reduction, cost savings, and structural performance dynamic loading. Specifically, a slave link subassembly was selected as the candidate to explore the feasibility of this methodology. The design optimization process utilized in this research was sectioned into three main stages: setup, optimization, and redesign. The first stage involved the creation and characterization of the models used throughout this research. The slave link assembly was modelled with a simplified landing gear test, replicating the behavior of the physical system. Through extensive review of the literature and collaboration with Safran Landing Systems, dynamic and structural behavior for the system were characterized and defined mathematically. Once defined, the characterized behaviors for the slave link assembly were then used to conduct a Multi-Body Dynamic (MBD) analysis to determine the dynamic and structural response of the system. These responses were then utilized in a topology optimization through the use of the Equivalent Static Load Method (ESLM). The results of the optimization were interpreted and later used to generate improved designs in terms of weight, cost, and structural performance under dynamic loading in stage three. The optimized designs were then validated using the model created for the MBD analysis of the baseline design. The design generation process employed two different approaches for post-processing the topology results produced. The first approach implemented a close replication of the topology results, resulting in a design with an overall peak stress increase of 74%, weight savings of 67%, and no apparent cost savings due to complex features present in the design. The second design approach focused on realizing reciprocating benefits for cost and weight savings. As a result, this design was able to achieve an overall peak stress increase of 6%, weight and cost savings of 36%, and 60%, respectively.

Optimization of the fabrication of novel stealth PLA-based nanoparticles by dispersion polymerization using D-optimal mixture design.

PubMed

Adesina, Simeon K; Wight, Scott A; Akala, Emmanuel O

2014-11-01

Nanoparticle size is important in drug delivery. Clearance of nanoparticles by cells of the reticuloendothelial system has been reported to increase with increase in particle size. Further, nanoparticles should be small enough to avoid lung or spleen filtering effects. Endocytosis and accumulation in tumor tissue by the enhanced permeability and retention effect are also processes that are influenced by particle size. We present the results of studies designed to optimize cross-linked biodegradable stealth polymeric nanoparticles fabricated by dispersion polymerization. Nanoparticles were fabricated using different amounts of macromonomer, initiators, crosslinking agent and stabilizer in a dioxane/DMSO/water solvent system. Confirmation of nanoparticle formation was by scanning electron microscopy (SEM). Particle size was measured by dynamic light scattering (DLS). D-optimal mixture statistical experimental design was used for the experimental runs, followed by model generation (Scheffe polynomial) and optimization with the aid of a computer software. Model verification was done by comparing particle size data of some suggested solutions to the predicted particle sizes. Data showed that average particle sizes follow the same trend as predicted by the model. Negative terms in the model corresponding to the cross-linking agent and stabilizer indicate the important factors for minimizing particle size.

Multilevel decomposition approach to integrated aerodynamic/dynamic/structural optimization of helicopter rotor blades

NASA Technical Reports Server (NTRS)

Walsh, Joanne L.; Young, Katherine C.; Pritchard, Jocelyn I.; Adelman, Howard M.; Mantay, Wayne R.

1994-01-01

This paper describes an integrated aerodynamic, dynamic, and structural (IADS) optimization procedure for helicopter rotor blades. The procedure combines performance, dynamics, and structural analyses with a general purpose optimizer using multilevel decomposition techniques. At the upper level, the structure is defined in terms of local quantities (stiffnesses, mass, and average strains). At the lower level, the structure is defined in terms of local quantities (detailed dimensions of the blade structure and stresses). The IADS procedure provides an optimization technique that is compatible with industrial design practices in which the aerodynamic and dynamic design is performed at a global level and the structural design is carried out at a detailed level with considerable dialogue and compromise among the aerodynamic, dynamic, and structural groups. The IADS procedure is demonstrated for several cases.