Optimization of a Multi-Step Procedure for Isolation of Chicken Bone Collagen
2015-01-01
Chicken bone is not adequately utilized despite its high nutritional value and protein content. Although not a common raw material, chicken bone can be used in many different ways besides manufacturing of collagen products. In this study, a multi-step procedure was optimized to isolate chicken bone collagen for higher yield and quality for manufacture of collagen products. The chemical composition of chicken bone was 2.9% nitrogen corresponding to about 15.6% protein, 9.5% fat, 14.7% mineral and 57.5% moisture. The lowest amount of protein loss was aimed along with the separation of the highest amount of visible impurities, non-collagen proteins, minerals and fats. Treatments under optimum conditions removed 57.1% of fats and 87.5% of minerals with respect to their initial concentrations. Meanwhile, 18.6% of protein and 14.9% of hydroxyproline were lost, suggesting that a selective separation of non-collagen components and isolation of collagen were achieved. A significant part of impurities were selectively removed and over 80% of the original collagen was preserved during the treatments. PMID:26761863
Multi-step optimization strategy for fuel-optimal orbital transfer of low-thrust spacecraft
NASA Astrophysics Data System (ADS)
Rasotto, M.; Armellin, R.; Di Lizia, P.
2016-03-01
An effective method for the design of fuel-optimal transfers in two- and three-body dynamics is presented. The optimal control problem is formulated using calculus of variation and primer vector theory. This leads to a multi-point boundary value problem (MPBVP), characterized by complex inner constraints and a discontinuous thrust profile. The first issue is addressed by embedding the MPBVP in a parametric optimization problem, thus allowing a simplification of the set of transversality constraints. The second problem is solved by representing the discontinuous control function by a smooth function depending on a continuation parameter. The resulting trajectory optimization method can deal with different intermediate conditions, and no a priori knowledge of the control structure is required. Test cases in both the two- and three-body dynamics show the capability of the method in solving complex trajectory design problems.
An Optimal Schedule for Urban Road Network Repair Based on the Greedy Algorithm
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
Greedy Criterion in Orthogonal Greedy Learning.
Xu, Lin; Lin, Shaobo; Zeng, Jinshan; Liu, Xia; Fang, Yi; Xu, Zongben
2017-02-23
Orthogonal greedy learning (OGL) is a stepwise learning scheme that starts with selecting a new atom from a specified dictionary via the steepest gradient descent (SGD) and then builds the estimator through orthogonal projection. In this paper, we found that SGD is not the unique greedy criterion and introduced a new greedy criterion, called as ''δ-greedy threshold'' for learning. Based on this new greedy criterion, we derived a straightforward termination rule for OGL. Our theoretical study shows that the new learning scheme can achieve the existing (almost) optimal learning rate of OGL. Numerical experiments are also provided to support that this new scheme can achieve almost optimal generalization performance while requiring less computation than OGL.
Faries, Kaitlyn M.; Kressel, Lucas L.; Dylla, Nicholas P.; Wander, Marc J.; Hanson, Deborah K.; Holten, Dewey; Laible, Philip D.; Kirmaier, Christine
2016-02-01
Using high-throughput methods for mutagenesis, protein isolation and charge-separation functionality, we have assayed 40 Rhodobacter capsulatus reaction center (RC) mutants for their P+ QB- yield (P is a dimer of bacteriochlorophylls and Q is a ubiquinone) as produced using the normally inactive B-side cofactors BB and HB (where B is a bacteriochlorophyll and H is a bacteriopheophytin). Two sets of mutants explore all possible residues at M131 (M polypeptide, native residue Val near HB) in tandem with either a fixed His or a fixed Asn at L181 (L polypeptide, native residue Phe near BB). A third set of mutants explores all possible residues at L181 with a fixed Glu at M131 that can form a hydrogen bond to HB. For each set of mutants, the results of a rapid millisecond screening assay that probes the yield of P+ QB- are compared among that set and to the other mutants reported here or previously. For a subset of eight mutants, the rate constants and yields of the individual B-side electron transfer processes are determined via transient absorption measurements spanning 100 fs to 50 μs. The resulting ranking of mutants for their yield of P+ QB- from ultrafast experiments is in good agreement with that obtained from the millisecond screening assay, further validating the efficient, high-throughput screen for B-side transmembrane charge separation. Results from mutants that individually show progress toward optimization of P+ HB- → P+ QB- electron transfer or initial P* → P+ HB- conversion highlight unmet challenges of optimizing both processes simultaneously.
A Guiding Evolutionary Algorithm with Greedy Strategy for Global Optimization Problems.
Cao, Leilei; Xu, Lihong; Goodman, Erik D
2016-01-01
A Guiding Evolutionary Algorithm (GEA) with greedy strategy for global optimization problems is proposed. Inspired by Particle Swarm Optimization, the Genetic Algorithm, and the Bat Algorithm, the GEA was designed to retain some advantages of each method while avoiding some disadvantages. In contrast to the usual Genetic Algorithm, each individual in GEA is crossed with the current global best one instead of a randomly selected individual. The current best individual served as a guide to attract offspring to its region of genotype space. Mutation was added to offspring according to a dynamic mutation probability. To increase the capability of exploitation, a local search mechanism was applied to new individuals according to a dynamic probability of local search. Experimental results show that GEA outperformed the other three typical global optimization algorithms with which it was compared.
A Guiding Evolutionary Algorithm with Greedy Strategy for Global Optimization Problems
Cao, Leilei; Xu, Lihong; Goodman, Erik D.
2016-01-01
A Guiding Evolutionary Algorithm (GEA) with greedy strategy for global optimization problems is proposed. Inspired by Particle Swarm Optimization, the Genetic Algorithm, and the Bat Algorithm, the GEA was designed to retain some advantages of each method while avoiding some disadvantages. In contrast to the usual Genetic Algorithm, each individual in GEA is crossed with the current global best one instead of a randomly selected individual. The current best individual served as a guide to attract offspring to its region of genotype space. Mutation was added to offspring according to a dynamic mutation probability. To increase the capability of exploitation, a local search mechanism was applied to new individuals according to a dynamic probability of local search. Experimental results show that GEA outperformed the other three typical global optimization algorithms with which it was compared. PMID:27293421
Exploring Maps with Greedy Navigators
NASA Astrophysics Data System (ADS)
Lee, Sang Hoon; Holme, Petter
2012-03-01
During the last decade of network research focusing on structural and dynamical properties of networks, the role of network users has been more or less underestimated from the bird’s-eye view of global perspective. In this era of global positioning system equipped smartphones, however, a user’s ability to access local geometric information and find efficient pathways on networks plays a crucial role, rather than the globally optimal pathways. We present a simple greedy spatial navigation strategy as a probe to explore spatial networks. These greedy navigators use directional information in every move they take, without being trapped in a dead end based on their memory about previous routes. We suggest that the centralities measures have to be modified to incorporate the navigators’ behavior, and present the intriguing effect of navigators’ greediness where removing some edges may actually enhance the routing efficiency, which is reminiscent of Braess’s paradox. In addition, using samples of road structures in large cities around the world, it is shown that the navigability measure we define reflects unique structural properties, which are not easy to predict from other topological characteristics. In this respect, we believe that our routing scheme significantly moves the routing problem on networks one step closer to reality, incorporating the inevitable incompleteness of navigators’ information.
NASA Astrophysics Data System (ADS)
Hanin, Leonid; Zaider, Marco
2014-08-01
We revisit a long-standing problem of optimization of fractionated radiotherapy and solve it in considerable generality under the following three assumptions only: (1) repopulation of clonogenic cancer cells between radiation exposures follows linear birth-and-death Markov process; (2) clonogenic cancer cells do not interact with each other; and (3) the dose response function s(D) is decreasing and logarithmically concave. Optimal schedules of fractionated radiation identified in this work can be described by the following ‘greedy’ principle: give the maximum possible dose as soon as possible. This means that upper bounds on the total dose and the dose per fraction reflecting limitations on the damage to normal tissue, along with a lower bound on the time between successive fractions of radiation, determine the optimal radiation schedules completely. Results of this work lead to a new paradigm of dose delivery which we term optimal biologically-based adaptive boosting (OBBAB). It amounts to (a) subdividing the target into regions that are homogeneous with respect to the maximum total dose and maximum dose per fraction allowed by the anatomy and biological properties of the normal tissue within (or adjacent to) the region in question and (b) treating each region with an individual optimal schedule determined by these constraints. The fact that different regions may be treated to different total dose and dose per fraction mean that the number of fractions may also vary between regions. Numerical evidence suggests that OBBAB produces significantly larger tumor control probability than the corresponding conventional treatments.
Coutu, Diane L
2003-02-01
Americans are outraged at the greediness of Wall Street analysts, dot-com entrepreneurs, and, most of all, chief executive officers. How could Tyco's Dennis Kozlowski use company funds to throw his wife a million-dollar birthday bash on an Italian island? How could Enron's Ken Lay sell thousands of shares of his company's once high-flying stock just before it crashed, leaving employees with nothing? Even America's most popular domestic guru, Martha Stewart, is suspected of having her hand in the cookie jar. To some extent, our outrage may be justified, writes HBR senior editor Diane Coutu. And yet, it's easy to forget that just a couple years ago these same people were lauded as heroes. Many Americans wanted nothing more, in fact, than to emulate them, to share in their fortunes. Indeed, we spent an enormous amount of time talking and thinking about double-digit returns, IPOs, day trading, and stock options. It could easily be argued that it was public indulgence in corporate money lust that largely created the mess we're now in. It's time to take a hard look at greed, both in its general form and in its peculiarly American incarnation, says Coutu. If Federal Reserve Board chairman Alan Greenspan was correct in telling Congress that "infectious greed" contaminated U.S. business, then we need to try to understand its causes--and how the average American may have contributed to it. Why did so many of us fall prey to greed? With a deep, almost reflexive trust in the free market, are Americans somehow greedier than other peoples? And as we look at the wreckage from the 1990s, can we be sure it won't happen again?
Synthesis of Greedy Algorithms Using Dominance Relations
NASA Technical Reports Server (NTRS)
Nedunuri, Srinivas; Smith, Douglas R.; Cook, William R.
2010-01-01
Greedy algorithms exploit problem structure and constraints to achieve linear-time performance. Yet there is still no completely satisfactory way of constructing greedy algorithms. For example, the Greedy Algorithm of Edmonds depends upon translating a problem into an algebraic structure called a matroid, but the existence of such a translation can be as hard to determine as the existence of a greedy algorithm itself. An alternative characterization of greedy algorithms is in terms of dominance relations, a well-known algorithmic technique used to prune search spaces. We demonstrate a process by which dominance relations can be methodically derived for a number of greedy algorithms, including activity selection, and prefix-free codes. By incorporating our approach into an existing framework for algorithm synthesis, we demonstrate that it could be the basis for an effective engineering method for greedy algorithms. We also compare our approach with other characterizations of greedy algorithms.
Greedy algorithms in disordered systems
NASA Astrophysics Data System (ADS)
Duxbury, P. M.; Dobrin, R.
1999-08-01
We discuss search, minimal path and minimal spanning tree algorithms and their applications to disordered systems. Greedy algorithms solve these problems exactly, and are related to extremal dynamics in physics. Minimal cost path (Dijkstra) and minimal cost spanning tree (Prim) algorithms provide extremal dynamics for a polymer in a random medium (the KPZ universality class) and invasion percolation (without trapping) respectively.
Droplet-based microsystem for multi-step bioreactions.
Wang, Fang; Burns, Mark A
2010-06-01
A droplet-based microfluidic platform was used to perform on-chip droplet generation, merging and mixing for applications in multi-step reactions and assays. Submicroliter-sized droplets can be produced separately from three identical droplet-generation channels and merged together in a single chamber. Three different mixing strategies were used for mixing the merged droplet. For pure diffusion, the reagents were mixed in approximately 10 min. Using flow around the stationary droplet to induce circulatory flow within the droplet, the mixing time was decreased to approximately one minute. The shortest mixing time (10 s) was obtained with bidirectional droplet motion between the chamber and channel, and optimization could result in a total time of less than 1 s. We also tested this on-chip droplet generation and manipulation platform using a two-step thermal cycled bioreaction: nested TaqMan PCR. With the same concentration of template DNA, the two-step reaction in a well-mixed merged droplet shows a cycle threshold of approximately 6 cycles earlier than that in the diffusively mixed droplet, and approximately 40 cycles earlier than the droplet-based regular (single-step) TaqMan PCR.
48 CFR 15.202 - Advisory multi-step process.
Code of Federal Regulations, 2011 CFR
2011-10-01
... process. 15.202 Section 15.202 Federal Acquisition Regulations System FEDERAL ACQUISITION REGULATION... Information 15.202 Advisory multi-step process. (a) The agency may publish a presolicitation notice (see 5.204... concept, past performance, and limited pricing information). At a minimum, the notice shall...
48 CFR 15.202 - Advisory multi-step process.
Code of Federal Regulations, 2014 CFR
2014-10-01
... process. 15.202 Section 15.202 Federal Acquisition Regulations System FEDERAL ACQUISITION REGULATION... Information 15.202 Advisory multi-step process. (a) The agency may publish a presolicitation notice (see 5.204... concept, past performance, and limited pricing information). At a minimum, the notice shall...
48 CFR 15.202 - Advisory multi-step process.
Code of Federal Regulations, 2013 CFR
2013-10-01
... process. 15.202 Section 15.202 Federal Acquisition Regulations System FEDERAL ACQUISITION REGULATION... Information 15.202 Advisory multi-step process. (a) The agency may publish a presolicitation notice (see 5.204... concept, past performance, and limited pricing information). At a minimum, the notice shall...
48 CFR 15.202 - Advisory multi-step process.
Code of Federal Regulations, 2010 CFR
2010-10-01
... process. 15.202 Section 15.202 Federal Acquisition Regulations System FEDERAL ACQUISITION REGULATION... Information 15.202 Advisory multi-step process. (a) The agency may publish a presolicitation notice (see 5.204... concept, past performance, and limited pricing information). At a minimum, the notice shall...
On Stable Marriages and Greedy Matchings
Manne, Fredrik; Naim, Md; Lerring, Hakon; Halappanavar, Mahantesh
2016-12-11
Research on stable marriage problems has a long and mathematically rigorous history, while that of exploiting greedy matchings in combinatorial scientific computing is a younger and less developed research field. In this paper we consider the relationships between these two areas. In particular we show that several problems related to computing greedy matchings can be formulated as stable marriage problems and as a consequence several recently proposed algorithms for computing greedy matchings are in fact special cases of well known algorithms for the stable marriage problem. However, in terms of implementations and practical scalable solutions on modern hardware, the greedy matching community has made considerable progress. We show that due to the strong relationship between these two fields many of these results are also applicable for solving stable marriage problems.
Power transmission coefficients for multi-step index optical fibres.
Aldabaldetreku, Gotzon; Zubia, Joseba; Durana, Gaizka; Arrue, Jon
2006-02-20
The aim of the present paper is to provide a single analytical expression of the power transmission coefficient for leaky rays in multi-step index (MSI) fibres. This expression is valid for all tunnelling and refracting rays and allows us to evaluate numerically the power attenuation along an MSI fibre of an arbitrary number of layers. We validate our analysis by comparing the results obtained for limit cases of MSI fibres with those corresponding to step-index (SI) and graded-index (GI) fibres. We also make a similar comparison between this theoretical expression and the use of the WKB solutions of the scalar wave equation.
Microwaves in drug discovery and multi-step synthesis.
Alexandre, François-René; Domon, Lisianne; Frère, Stéphane; Testard, Alexandra; Thiéry, Valérie; Besson, Thierry
2003-01-01
The interest of microwaves in drug discovery and multi-step synthesis is exposed with the aim of describing our strategy. These studies are connected with our work on the synthesis of original heterocyclic compounds with potential pharmaceutical value. Reactions in the presence of solvent and solvent-free synthesis can be realised under a variety of conditions; for some of these selected results are given, and where available, results from comparison with the same solvent-free conditions but with classical heating are given.
A simple greedy algorithm for reconstructing pedigrees.
Cowell, Robert G
2013-02-01
This paper introduces a simple greedy algorithm for searching for high likelihood pedigrees using micro-satellite (STR) genotype information on a complete sample of related individuals. The core idea behind the algorithm is not new, but it is believed that putting it into a greedy search setting, and specifically the application to pedigree learning, is novel. The algorithm does not require age or sex information, but this information can be incorporated if desired. The algorithm is applied to human and non-human genetic data and in a simulation study.
Multi-step prediction of physiological tremor for robotics applications.
Veluvolu, K C; Tatinati, S; Hong, S M; Ang, W T
2013-01-01
The performance of surgical robotic devices in real-time mainly depends on phase-delay in sensors and filtering process. A phase delay of 16-20 ms is unavoidable in these robotics procedures due to the presence of hardware low pass filter in sensors and pre-filtering required in later stages of cancellation. To overcome this phase delay, we employ multi-step prediction with band limited multiple Fourier linear combiner (BMFLC) and Autoregressive (AR) methods. Results show that the overall accuracy is improved by 60% for tremor estimation compared to single-step prediction methods in the presence of phase delay. Experimental results with the proposed methods for 1-DOF tremor estimation highlight the improvement.
Suboptimal greedy power allocation schemes for discrete bit loading.
Al-Hanafy, Waleed; Weiss, Stephan
2013-01-01
We consider low cost discrete bit loading based on greedy power allocation (GPA) under the constraints of total transmit power budget, target BER, and maximum permissible QAM modulation order. Compared to the standard GPA, which is optimal in terms of maximising the data throughput, three suboptimal schemes are proposed, which perform GPA on subsets of subchannels only. These subsets are created by considering the minimum SNR boundaries of QAM levels for a given target BER. We demonstrate how these schemes can significantly reduce the computational complexity required for power allocation, particularly in the case of a large number of subchannels. Two of the proposed algorithms can achieve near optimal performance including a transfer of residual power between subsets at the expense of a very small extra cost. By simulations, we show that the two near optimal schemes, while greatly reducing complexity, perform best in two separate and distinct SNR regions.
Suboptimal Greedy Power Allocation Schemes for Discrete Bit Loading
2013-01-01
We consider low cost discrete bit loading based on greedy power allocation (GPA) under the constraints of total transmit power budget, target BER, and maximum permissible QAM modulation order. Compared to the standard GPA, which is optimal in terms of maximising the data throughput, three suboptimal schemes are proposed, which perform GPA on subsets of subchannels only. These subsets are created by considering the minimum SNR boundaries of QAM levels for a given target BER. We demonstrate how these schemes can significantly reduce the computational complexity required for power allocation, particularly in the case of a large number of subchannels. Two of the proposed algorithms can achieve near optimal performance including a transfer of residual power between subsets at the expense of a very small extra cost. By simulations, we show that the two near optimal schemes, while greatly reducing complexity, perform best in two separate and distinct SNR regions. PMID:24501578
NASA Astrophysics Data System (ADS)
Schuetz, Philipp; Caflisch, Amedeo
2008-08-01
We have recently introduced a multistep extension of the greedy algorithm for modularity optimization. The extension is based on the idea that merging l pairs of communities (l>1) at each iteration prevents premature condensation into few large communities. Here, an empirical formula is presented for the choice of the step width l that generates partitions with (close to) optimal modularity for 17 real-world and 1100 computer-generated networks. Furthermore, an in-depth analysis of the communities of two real-world networks (the metabolic network of the bacterium E. coli and the graph of coappearing words in the titles of papers coauthored by Martin Karplus) provides evidence that the partition obtained by the multistep greedy algorithm is superior to the one generated by the original greedy algorithm not only with respect to modularity, but also according to objective criteria. In other words, the multistep extension of the greedy algorithm reduces the danger of getting trapped in local optima of modularity and generates more reasonable partitions.
Efficient greedy algorithms for economic manpower shift planning
NASA Astrophysics Data System (ADS)
Nearchou, A. C.; Giannikos, I. C.; Lagodimos, A. G.
2015-01-01
Consideration is given to the economic manpower shift planning (EMSP) problem, an NP-hard capacity planning problem appearing in various industrial settings including the packing stage of production in process industries and maintenance operations. EMSP aims to determine the manpower needed in each available workday shift of a given planning horizon so as to complete a set of independent jobs at minimum cost. Three greedy heuristics are presented for the EMSP solution. These practically constitute adaptations of an existing algorithm for a simplified version of EMSP which had shown excellent performance in terms of solution quality and speed. Experimentation shows that the new algorithms perform very well in comparison to the results obtained by both the CPLEX optimizer and an existing metaheuristic. Statistical analysis is deployed to rank the algorithms in terms of their solution quality and to identify the effects that critical planning factors may have on their relative efficiency.
P.I. Steven M. Larson MD Co P.I. Nai-Kong Cheung MD, Ph.D.
2009-09-21
The 4 specific aims of this project are: (1) Optimization of MST to increase tumor uptake; (2) Antigen heterogeneity; (3) Characterization and reduction of renal uptake; and (4) Validation in vivo of optimized MST targeted therapy. This proposal focussed upon optimizing multistep immune targeting strategies for the treatment of cancer. Two multi-step targeting constructs were explored during this funding period: (1) anti-Tag-72 and (2) anti-GD2.
An Experimental Method for the Active Learning of Greedy Algorithms
ERIC Educational Resources Information Center
Velazquez-Iturbide, J. Angel
2013-01-01
Greedy algorithms constitute an apparently simple algorithm design technique, but its learning goals are not simple to achieve.We present a didacticmethod aimed at promoting active learning of greedy algorithms. The method is focused on the concept of selection function, and is based on explicit learning goals. It mainly consists of an…
Xu, Jiajiong; Tang, Wei; Ma, Jun; Wang, Hong
2017-04-11
Drinking water treatment processes remove undesirable chemicals and microorganisms from source water, which is vital to public health protection. The purpose of this study was to investigate the effects of treatment processes and configuration on the microbiome by comparing microbial community shifts in two series of different treatment processes operated in parallel within a full-scale drinking water treatment plant (DWTP) in Southeast China. Illumina sequencing of 16S rRNA genes of water samples demonstrated little effect of coagulation/sedimentation and pre-oxidation steps on bacterial communities, in contrast to dramatic and concurrent microbial community shifts during ozonation, granular activated carbon treatment, sand filtration, and disinfection for both series. A large number of unique operational taxonomic units (OTUs) at these four treatment steps further illustrated their strong shaping power towards the drinking water microbial communities. Interestingly, multidimensional scaling analysis revealed tight clustering of biofilm samples collected from different treatment steps, with Nitrospira, the nitrite-oxidizing bacteria, noted at higher relative abundances in biofilm compared to water samples. Overall, this study provides a snapshot of step-to-step microbial evolvement in multi-step drinking water treatment systems, and the results provide insight to control and manipulation of the drinking water microbiome via optimization of DWTP design and operation.
Link community detection by non-negative matrix factorization with multi-step similarities
NASA Astrophysics Data System (ADS)
Tang, Xianchao; Yang, Guoqing; Xu, Tao; Feng, Xia; Wang, Xiao; Li, Qiannan; Liu, Yanbei
2016-11-01
Uncovering community structures is a fundamental and important problem in analyzing the complex networks. While most of the methods focus on identifying node communities, recent works show the intuitions and advantages of detecting link communities in networks. In this paper, we propose a non-negative matrix factorization (NMF) based method to detect the link community structures. Traditional NMF-based methods mainly consider the adjacency matrix as the representation of network topology, while the adjacency matrix only shows the relationship between immediate neighbor nodes, which does not take the relationship between non-neighbor nodes into consideration. This may greatly reduce the information contained in the network topology, and thus leads to unsatisfactory results. Here, we address this by introducing multi-step similarities using the graph random walk approach so that the similarities between non-neighbor nodes can be captured. Meanwhile, in order to reduce impact caused by self-similarities (similarities between nodes themselves) and increase importance gained from similarities between other different nodes, we add a penalty term to our objective function. Then an efficient optimization scheme for the objective function is derived. Finally, we test the proposed method on both synthetic and real networks. Experimental results demonstrate the effectiveness of the proposed approach.
A Greedy reassignment algorithm for the PBS minimum monitor unit constraint.
Lin, Yuting; Kooy, Hanne; Craft, David; Depauw, Nicolas; Flanz, Jacob; Clasie, Benjamin
2016-06-21
Proton pencil beam scanning (PBS) treatment plans are made of numerous unique spots of different weights. These weights are optimized by the treatment planning systems, and sometimes fall below the deliverable threshold set by the treatment delivery system. The purpose of this work is to investigate a Greedy reassignment algorithm to mitigate the effects of these low weight pencil beams. The algorithm is applied during post-processing to the optimized plan to generate deliverable plans for the treatment delivery system. The Greedy reassignment method developed in this work deletes the smallest weight spot in the entire field and reassigns its weight to its nearest neighbor(s) and repeats until all spots are above the minimum monitor unit (MU) constraint. Its performance was evaluated using plans collected from 190 patients (496 fields) treated at our facility. The Greedy reassignment method was compared against two other post-processing methods. The evaluation criteria was the γ-index pass rate that compares the pre-processed and post-processed dose distributions. A planning metric was developed to predict the impact of post-processing on treatment plans for various treatment planning, machine, and dose tolerance parameters. For fields with a pass rate of 90 ± 1% the planning metric has a standard deviation equal to 18% of the centroid value showing that the planning metric and γ-index pass rate are correlated for the Greedy reassignment algorithm. Using a 3rd order polynomial fit to the data, the Greedy reassignment method has 1.8 times better planning metric at 90% pass rate compared to other post-processing methods. As the planning metric and pass rate are correlated, the planning metric could provide an aid for implementing parameters during treatment planning, or even during facility design, in order to yield acceptable pass rates. More facilities are starting to implement PBS and some have spot sizes (one standard deviation) smaller than 5
A Greedy reassignment algorithm for the PBS minimum monitor unit constraint
NASA Astrophysics Data System (ADS)
Lin, Yuting; Kooy, Hanne; Craft, David; Depauw, Nicolas; Flanz, Jacob; Clasie, Benjamin
2016-06-01
Proton pencil beam scanning (PBS) treatment plans are made of numerous unique spots of different weights. These weights are optimized by the treatment planning systems, and sometimes fall below the deliverable threshold set by the treatment delivery system. The purpose of this work is to investigate a Greedy reassignment algorithm to mitigate the effects of these low weight pencil beams. The algorithm is applied during post-processing to the optimized plan to generate deliverable plans for the treatment delivery system. The Greedy reassignment method developed in this work deletes the smallest weight spot in the entire field and reassigns its weight to its nearest neighbor(s) and repeats until all spots are above the minimum monitor unit (MU) constraint. Its performance was evaluated using plans collected from 190 patients (496 fields) treated at our facility. The Greedy reassignment method was compared against two other post-processing methods. The evaluation criteria was the γ-index pass rate that compares the pre-processed and post-processed dose distributions. A planning metric was developed to predict the impact of post-processing on treatment plans for various treatment planning, machine, and dose tolerance parameters. For fields with a pass rate of 90 ± 1% the planning metric has a standard deviation equal to 18% of the centroid value showing that the planning metric and γ-index pass rate are correlated for the Greedy reassignment algorithm. Using a 3rd order polynomial fit to the data, the Greedy reassignment method has 1.8 times better planning metric at 90% pass rate compared to other post-processing methods. As the planning metric and pass rate are correlated, the planning metric could provide an aid for implementing parameters during treatment planning, or even during facility design, in order to yield acceptable pass rates. More facilities are starting to implement PBS and some have spot sizes (one standard deviation) smaller than 5
Surface Modified Particles By Multi-Step Addition And Process For The Preparation Thereof
Cook, Ronald Lee; Elliott, Brian John; Luebben, Silvia DeVito; Myers, Andrew William; Smith, Bryan Matthew
2006-01-17
The present invention relates to a new class of surface modified particles and to a multi-step surface modification process for the preparation of the same. The multi-step surface functionalization process involves two or more reactions to produce particles that are compatible with various host systems and/or to provide the particles with particular chemical reactivities. The initial step comprises the attachment of a small organic compound to the surface of the inorganic particle. The subsequent steps attach additional compounds to the previously attached organic compounds through organic linking groups.
On the origin of multi-step spin transition behaviour in 1D nanoparticles
NASA Astrophysics Data System (ADS)
Chiruta, Daniel; Jureschi, Catalin-Maricel; Linares, Jorge; Dahoo, Pierre Richard; Garcia, Yann; Rotaru, Aurelian
2015-09-01
To investigate the spin state switching mechanism in spin crossover (SCO) nanoparticles, a special attention is given to three-step thermally induced SCO behavior in 1D chains. An additional term is included in the standard Ising-like Hamiltonian to account for the border interaction between SCO molecules and its local environment. It is shown that this additional interaction, together with the short range interaction, drives the multi-steps thermal hysteretic behavior in 1D SCO systems. The relation between a polymeric matrix and this particular multi-step SCO phenomenon is discussed accordingly. Finally, the environmental influence on the SCO system's size is analyzed as well.
Multi-step routes of capuchin monkeys in a laser pointer traveling salesman task.
Howard, Allison M; Fragaszy, Dorothy M
2014-09-01
Prior studies have claimed that nonhuman primates plan their routes multiple steps in advance. However, a recent reexamination of multi-step route planning in nonhuman primates indicated that there is no evidence for planning more than one step ahead. We tested multi-step route planning in capuchin monkeys using a pointing device to "travel" to distal targets while stationary. This device enabled us to determine whether capuchins distinguish the spatial relationship between goals and themselves and spatial relationships between goals and the laser dot, allocentrically. In Experiment 1, two subjects were presented with identical food items in Near-Far (one item nearer to subject) and Equidistant (both items equidistant from subject) conditions with a laser dot visible between the items. Subjects moved the laser dot to the items using a joystick. In the Near-Far condition, one subject demonstrated a bias for items closest to self but the other subject chose efficiently. In the second experiment, subjects retrieved three food items in similar Near-Far and Equidistant arrangements. Both subjects preferred food items nearest the laser dot and showed no evidence of multi-step route planning. We conclude that these capuchins do not make choices on the basis of multi-step look ahead strategies.
Use of Chiral Oxazolidinones for a Multi-Step Synthetic Laboratory Module
ERIC Educational Resources Information Center
Betush, Matthew P.; Murphree, S. Shaun
2009-01-01
Chiral oxazolidinone chemistry is used as a framework for an advanced multi-step synthesis lab. The cost-effective and robust preparation of chiral starting materials is presented, as well as the use of chiral auxiliaries in a synthesis scheme that is appropriate for students currently in the second semester of the organic sequence. (Contains 1…
Trinh, Philip; Ball, Cameron; Fu, Elain; Yager, Paul
2016-01-01
Most laboratory assays take advantage of multi-step protocols to achieve high performance, but conventional paper-based tests (e.g., lateral flow tests) are generally limited to assays that can be carried out in a single fluidic step. We have developed two-dimensional paper networks (2DPNs) that use materials from lateral flow tests but reconfigure them to enable programming of multi-step reagent delivery sequences. The 2DPN uses multiple converging fluid inlets to control the arrival time of each fluid to a detection zone or reaction zone, and it requires a method to disconnect each fluid source in a corresponding timed sequence. Here, we present a method that allows programmed disconnection of fluid sources required for multi-step delivery. A 2DPN with legs of different lengths is inserted into a shared buffer well, and the dropping fluid surface disconnects each leg at in a programmable sequence. This approach could enable multi-step laboratory assays to be converted into simple point-of-care devices that have high performance yet remain easy to use. PMID:22037591
Mechanical and Metallurgical Evolution of Stainless Steel 321 in a Multi-step Forming Process
NASA Astrophysics Data System (ADS)
Anderson, M.; Bridier, F.; Gholipour, J.; Jahazi, M.; Wanjara, P.; Bocher, P.; Savoie, J.
2016-04-01
This paper examines the metallurgical evolution of AISI Stainless Steel 321 (SS 321) during multi-step forming, a process that involves cycles of deformation with intermediate heat treatment steps. The multi-step forming process was simulated by implementing interrupted uniaxial tensile testing experiments. Evolution of the mechanical properties as well as the microstructural features, such as twins and textures of the austenite and martensite phases, was studied as a function of the multi-step forming process. The characteristics of the Strain-Induced Martensite (SIM) were also documented for each deformation step and intermediate stress relief heat treatment. The results indicated that the intermediate heat treatments considerably increased the formability of SS 321. Texture analysis showed that the effect of the intermediate heat treatment on the austenite was minor and led to partial recrystallization, while deformation was observed to reinforce the crystallographic texture of austenite. For the SIM, an Olson-Cohen equation type was identified to analytically predict its formation during the multi-step forming process. The generated SIM was textured and weakened with increasing deformation.
NASA Astrophysics Data System (ADS)
Mitran, T. L.; Melchert, O.; Hartmann, A. K.
2013-12-01
The main characteristics of biased greedy random walks (BGRWs) on two-dimensional lattices with real-valued quenched disorder on the lattice edges are studied. Here the disorder allows for negative edge weights. In previous studies, considering the negative-weight percolation (NWP) problem, this was shown to change the universality class of the existing, static percolation transition. In the presented study, four different types of BGRWs and an algorithm based on the ant colony optimization heuristic were considered. Regarding the BGRWs, the precise configurations of the lattice walks constructed during the numerical simulations were influenced by two parameters: a disorder parameter ρ that controls the amount of negative edge weights on the lattice and a bias strength B that governs the drift of the walkers along a certain lattice direction. The random walks are “greedy” in the sense that the local optimal choice of the walker is to preferentially traverse edges with a negative weight (associated with a net gain of “energy” for the walker). Here, the pivotal observable is the probability that, after termination, a lattice walk exhibits a total negative weight, which is here considered as percolating. The behavior of this observable as function of ρ for different bias strengths B is put under scrutiny. Upon tuning ρ, the probability to find such a feasible lattice walk increases from zero to 1. This is the key feature of the percolation transition in the NWP model. Here, we address the question how well the transition point ρc, resulting from numerically exact and “static” simulations in terms of the NWP model, can be resolved using simple dynamic algorithms that have only local information available, one of the basic questions in the physics of glassy systems.
Teaching multi-step math skills to adults with disabilities via video prompting.
Kellems, Ryan O; Frandsen, Kaitlyn; Hansen, Blake; Gabrielsen, Terisa; Clarke, Brynn; Simons, Kalee; Clements, Kyle
2016-11-01
The purpose of this study was to evaluate the effectiveness of teaching multi-step math skills to nine adults with disabilities in an 18-21 post-high school transition program using a video prompting intervention package. The dependent variable was the percentage of steps completed correctly. The independent variable was the video prompting intervention, which involved several multi-step math calculation skills: (a) calculating a tip (15%), (b) calculating item unit prices, and (c) adjusting a recipe for more or fewer people. Results indicated a functional relationship between the video prompting interventions and prompting package and the percentage of steps completed correctly. 8 out of the 9 adults showed significant gains immediately after receiving the video prompting intervention.
Region-based multi-step optic disk and cup segmentation from color fundus image
NASA Astrophysics Data System (ADS)
Xiao, Di; Lock, Jane; Manresa, Javier Moreno; Vignarajan, Janardhan; Tay-Kearney, Mei-Ling; Kanagasingam, Yogesan
2013-02-01
Retinal optic cup-disk-ratio (CDR) is a one of important indicators of glaucomatous neuropathy. In this paper, we propose a novel multi-step 4-quadrant thresholding method for optic disk segmentation and a multi-step temporal-nasal segmenting method for optic cup segmentation based on blood vessel inpainted HSL lightness images and green images. The performance of the proposed methods was evaluated on a group of color fundus images and compared with the manual outlining results from two experts. Dice scores of detected disk and cup regions between the auto and manual results were computed and compared. Vertical CDRs were also compared among the three results. The preliminary experiment has demonstrated the robustness of the method for automatic optic disk and cup segmentation and its potential value for clinical application.
Multi-Step Deep Reactive Ion Etching Fabrication Process for Silicon-Based Terahertz Components
NASA Technical Reports Server (NTRS)
Jung-Kubiak, Cecile (Inventor); Reck, Theodore (Inventor); Chattopadhyay, Goutam (Inventor); Perez, Jose Vicente Siles (Inventor); Lin, Robert H. (Inventor); Mehdi, Imran (Inventor); Lee, Choonsup (Inventor); Cooper, Ken B. (Inventor); Peralta, Alejandro (Inventor)
2016-01-01
A multi-step silicon etching process has been developed to fabricate silicon-based terahertz (THz) waveguide components. This technique provides precise dimensional control across multiple etch depths with batch processing capabilities. Nonlinear and passive components such as mixers and multipliers waveguides, hybrids, OMTs and twists have been fabricated and integrated into a small silicon package. This fabrication technique enables a wafer-stacking architecture to provide ultra-compact multi-pixel receiver front-ends in the THz range.
Intrinsic Micromechanism of Multi-step Structural Transformation in MnNi Shape Memory Alloys
NASA Astrophysics Data System (ADS)
Cui, Shushan; Wan, Jianfeng; Rong, Yonghua; Zhang, Jihua
2017-03-01
Simulation of the multi-step transformation of cubic matrix → multi-variant tetragonal domain → orthorhombic domain was realized by phase-field method. The intrinsic micromechanism of the second-step transformation in MnNi alloys was studied. It was found that the orthorhombic variant originated from the tetragonal variant with similar orientation, and bar-shaped orthorhombic phase firstly occurred around the interface of twinning bands. The second-step transformation resulted in localized variation of internal stress.
Photon Production through Multi-step Processes Important in Nuclear Fluorescence Experiments
Hagmann, C; Pruet, J
2006-10-26
The authors present calculations describing the production of photons through multi-step processes occurring when a beam of gamma rays interacts with a macroscopic material. These processes involve the creation of energetic electrons through Compton scattering, photo-absorption and pair production, the subsequent scattering of these electrons, and the creation of energetic photons occurring as these electrons are slowed through Bremsstrahlung emission. Unlike single Compton collisions, during which an energetic photon that is scattered through a large angle loses most of its energy, these multi-step processes result in a sizable flux of energetic photons traveling at large angles relative to an incident photon beam. These multi-step processes are also a key background in experiments that measure nuclear resonance fluorescence by shining photons on a thin foil and observing the spectrum of back-scattered photons. Effective cross sections describing the production of backscattered photons are presented in a tabular form that allows simple estimates of backgrounds expected in a variety of experiments. Incident photons with energies between 0.5 MeV and 8 MeV are considered. These calculations of effective cross sections may be useful for those designing NRF experiments or systems that detect specific isotopes in well-shielded environments through observation of resonance fluorescence.
Content-based image retrieval using greedy routing
NASA Astrophysics Data System (ADS)
Don, Anthony; Hanusse, Nicolas
2008-01-01
In this paper, we propose a new concept for browsing and searching in large collections of content-based indexed images. Our approach is inspired by greedy routing algorithms used in distributed networks. We define a navigation graph, called navgraph, whose vertices represent images. The edges of the navgraph are computed according to a similarity measure between indexed images. The resulting graph can be seen as an ad-hoc network of images in which a greedy routing algorithm can be applied for retrieval purposes. A request for a target image consists of a walk in the navigation graph using a greedy approach : starting from an arbitrary vertex/image, the neighbors of the current vertex are presented to the user, who iteratively selects the vertex which is the most similar to the target. We present the navgraph construction and prove its efficiency for greedy routing. We also propose a specific content-descriptor that we compare to the MPEG7 Color Layout Descriptor. Experimental results with test-users show the usability of this approach.
Filip, Xenia; Miclaus, Maria; Martin, Flavia; Filip, Claudiu; Grosu, Ioana Georgeta
2017-01-31
Herein we report the preparation and solid state structural investigation of the 1,4-dioxane-quercetin solvate. NMR crystallography methods were employed for crystal structure determination of the solvate from microcrystalline powder. The stability of the compound relative to other reported quercetin solvates is discussed and found to be in perfect agreement with the hydrogen bonding networks/supra-molecular architectures formed in each case. It is also clearly shown that NMR crystallography represents an ideal analytical tool in such cases when hydrogen-bonding networks are required to be constrained at a high accuracy level.
Analysis of intrinsic coupling loss in multi-step index optical fibres.
Aldabaldetreku, Gotzon; Durana, Gaizka; Zubia, Joseba; Arrue, Jon; Jiménez, Felipe; Mateo, Javier
2005-05-02
The main goal of the present paper is to provide a comprehensive analysis of the intrinsic coupling loss for multi-step index (MSI) fibres and compare it with those obtained for step- and graded-index fibres. We investigate the effects of tolerances to each waveguide parameter typical in standard manufacturing processes by carrying out several simulations using the ray-tracing method. The results obtained will serve us to identify the most critical waveguide variations to which fibre manufactures will have to pay closer attention to achieve lower coupling losses.
PRE-ADAMO: a multi-step approach for the identification of life on Mars
NASA Astrophysics Data System (ADS)
Brucato, J. R.; Vázquez, L.; Rotundi, A.; Cataldo, F.; Palomba, E.; Saladino, R.; di Mauro, E.; Baratta, G.; Barbier, B.; Battaglia, R.; Colangeli, L.; Costanzo, G.; Crestini, C.; della Corte, V.; Mazzotta Epifani, E.; Esposito, F.; Ferrini, G.; Gómez Elvira, J.; Isola, M.; Keheyan, Y.; Leto, G.; Martinez Frias, J.; Mennella, V.; Negri, R.; Palumbo, M. E.; Palumbo, P.; Strazzulla, G.; Falciani, P.; Adami, G.; Guizzo, G. P.; Campiotti, S.
2004-03-01
It is of paramount importance to detect traces of life on Mars surface. Organic molecules are highly polar and if present on Mars require to be extracted from the dust sample, separated, concentrated, processed and analysed by an appropriate apparatus. PRE-ADAMO (PRebiotic Experiment - Activity of Dust And bioMolecules Observation) is a multi-steps approach for the identification of possible polar substances present on Mars. It was proposed as instrument of Pasteur payload for the ESA (European Space Agency) ExoMars rover mission. Main scientific objectives and experimental approach of PRE-ADAMO are here presented.
Multi-step motion planning: Application to free-climbing robots
NASA Astrophysics Data System (ADS)
Bretl, Timothy Wolfe
This dissertation addresses the problem of planning the motion of a multi-limbed robot to "free-climb" vertical rock surfaces. Free-climbing relies on natural features and friction (such as holes or protrusions) rather than special fixtures or tools. It requires strength, but more importantly it requires deliberate reasoning: not only must the robot decide how to adjust its posture to reach the next feature without falling, it must plan an entire sequence of steps, where each one might have future consequences. This process of reasoning is called multi-step planning. A multi-step planning framework is presented for computing non-gaited, free-climbing motions. This framework derives from an analysis of a free-climbing robot's configuration space, which can be decomposed into constraint manifolds associated with each state of contact between the robot and its environment. An understanding of the adjacency between manifolds motivates a two-stage strategy that uses a candidate sequence of steps to direct the subsequent search for motions. Three algorithms are developed to support the framework. The first algorithm reduces the amount of time required to plan each potential step, a large number of which must be considered over an entire multi-step search. It extends the probabilistic roadmap (PRM) approach based on an analysis of the interaction between balance and the topology of closed kinematic chains. The second algorithm addresses a problem with the PRM approach, that it is unable to distinguish challenging steps (which may be critical) from impossible ones. This algorithm detects impossible steps explicitly, using automated algebraic inference and machine learning. The third algorithm provides a fast constraint checker (on which the PRM approach depends), in particular a test of balance at the initially unknown number of sampled configurations associated with each step. It is a method of incremental precomputation, fast because it takes advantage of the sample
Synergy between chemo- and bio-catalysts in multi-step transformations.
Caiazzo, Aldo; Garcia, Paula M L; Wever, Ron; van Hest, Jan C M; Rowan, Alan E; Reek, Joost N H
2009-07-21
Cascade synthetic pathways, which allow multi-step conversions to take place in one reaction vessel, are crucial for the development of biomimetic, highly efficient new methods of chemical synthesis. Theoretically, the complexity introduced by combining processes could lead to an improvement of the overall process; however, it is the current general belief that it is more efficient to run processes separately. Inspired by natural cascade procedures we successfully combined a lipase catalyzed amidation with palladium catalyzed coupling reactions, simultaneously carried out on the same molecule. Unexpectedly, the bio- and chemo-catalyzed processes show synergistic behaviour, highlighting the complexity of multi-catalyst systems.
Effective Iterated Greedy Algorithm for Flow-Shop Scheduling Problems with Time lags
NASA Astrophysics Data System (ADS)
ZHAO, Ning; YE, Song; LI, Kaidian; CHEN, Siyu
2017-03-01
Flow shop scheduling problem with time lags is a practical scheduling problem and attracts many studies. Permutation problem(PFSP with time lags) is concentrated but non-permutation problem(non-PFSP with time lags) seems to be neglected. With the aim to minimize the makespan and satisfy time lag constraints, efficient algorithms corresponding to PFSP and non-PFSP problems are proposed, which consist of iterated greedy algorithm for permutation(IGTLP) and iterated greedy algorithm for non-permutation (IGTLNP). The proposed algorithms are verified using well-known simple and complex instances of permutation and non-permutation problems with various time lag ranges. The permutation results indicate that the proposed IGTLP can reach near optimal solution within nearly 11% computational time of traditional GA approach. The non-permutation results indicate that the proposed IG can reach nearly same solution within less than 1% computational time compared with traditional GA approach. The proposed research combines PFSP and non-PFSP together with minimal and maximal time lag consideration, which provides an interesting viewpoint for industrial implementation.
Avoiding Greediness in Cooperative Peer-to-Peer Networks
NASA Astrophysics Data System (ADS)
Brust, Matthias R.; Ribeiro, Carlos H. C.; Mesit, Jaruwan
In peer-to-peer networks, peers simultaneously play the role of client and server. Since the introduction of the first file-sharing protocols, peer-to-peer networking currently causes more than 35% of all internet network traffic— with an ever increasing tendency. A common file-sharing protocol that occupies most of the peer-to-peer traffic is the BitTorrent protocol. Although based on cooperative principles, in practice it is doomed to fail if peers behave greedily. In this work-in-progress paper, we model the protocol by introducing the game named Tit-for-Tat Network Termination (T4TNT) that gives an interesting access to the greediness problem of the BitTorrent protocol. Simulations conducted under this model indicate that greediness can be reduced by solely manipulating the underlying peer-to-peer topology.
Greedy Wavelet Projections are Bounded on BV (Preprint)
2003-10-30
functions of bounded variation on IRd with d ??? 2. Let ????, ?? ??? ??, be a wavelet basis of compactly supported functions normalized in BV, i.e...Wojtaszczyk October 30, 2003 Abstract Let BV = BV(IRd) be the space of functions of bounded variation on IRd with d ≥ 2. Let ψλ, λ ∈ ∆, be a wavelet basis...greedy approximation, functions of bounded variation , thresholding, bounded projections. 1 Introduction The space BV := BV(Ω) of functions of
2014-01-01
Berth allocation is the forefront operation performed when ships arrive at a port and is a critical task in container port optimization. Minimizing the time ships spend at berths constitutes an important objective of berth allocation problems. This study focuses on the discrete dynamic berth allocation problem (discrete DBAP), which aims to minimize total service time, and proposes an iterated greedy (IG) algorithm to solve it. The proposed IG algorithm is tested on three benchmark problem sets. Experimental results show that the proposed IG algorithm can obtain optimal solutions for all test instances of the first and second problem sets and outperforms the best-known solutions for 35 out of 90 test instances of the third problem set. PMID:25295295
Lin, Shih-Wei; Ying, Kuo-Ching; Wan, Shu-Yen
2014-01-01
Berth allocation is the forefront operation performed when ships arrive at a port and is a critical task in container port optimization. Minimizing the time ships spend at berths constitutes an important objective of berth allocation problems. This study focuses on the discrete dynamic berth allocation problem (discrete DBAP), which aims to minimize total service time, and proposes an iterated greedy (IG) algorithm to solve it. The proposed IG algorithm is tested on three benchmark problem sets. Experimental results show that the proposed IG algorithm can obtain optimal solutions for all test instances of the first and second problem sets and outperforms the best-known solutions for 35 out of 90 test instances of the third problem set.
Adaptive multi-step Full Waveform Inversion based on Waveform Mode Decomposition
NASA Astrophysics Data System (ADS)
Hu, Yong; Han, Liguo; Xu, Zhuo; Zhang, Fengjiao; Zeng, Jingwen
2017-04-01
Full Waveform Inversion (FWI) can be used to build high resolution velocity models, but there are still many challenges in seismic field data processing. The most difficult problem is about how to recover long-wavelength components of subsurface velocity models when seismic data is lacking of low frequency information and without long-offsets. To solve this problem, we propose to use Waveform Mode Decomposition (WMD) method to reconstruct low frequency information for FWI to obtain a smooth model, so that the initial model dependence of FWI can be reduced. In this paper, we use adjoint-state method to calculate the gradient for Waveform Mode Decomposition Full Waveform Inversion (WMDFWI). Through the illustrative numerical examples, we proved that the low frequency which is reconstructed by WMD method is very reliable. WMDFWI in combination with the adaptive multi-step inversion strategy can obtain more faithful and accurate final inversion results. Numerical examples show that even if the initial velocity model is far from the true model and lacking of low frequency information, we still can obtain good inversion results with WMD method. From numerical examples of anti-noise test, we see that the adaptive multi-step inversion strategy for WMDFWI has strong ability to resist Gaussian noise. WMD method is promising to be able to implement for the land seismic FWI, because it can reconstruct the low frequency information, lower the dominant frequency in the adjoint source, and has a strong ability to resist noise.
SMG: Fast scalable greedy algorithm for influence maximization in social networks
NASA Astrophysics Data System (ADS)
Heidari, Mehdi; Asadpour, Masoud; Faili, Hesham
2015-02-01
Influence maximization is the problem of finding k most influential nodes in a social network. Many works have been done in two different categories, greedy approaches and heuristic approaches. The greedy approaches have better influence spread, but lower scalability on large networks. The heuristic approaches are scalable and fast but not for all type of networks. Improving the scalability of greedy approach is still an open and hot issue. In this work we present a fast greedy algorithm called State Machine Greedy that improves the existing algorithms by reducing calculations in two parts: (1) counting the traversing nodes in estimate propagation procedure, (2) Monte-Carlo graph construction in simulation of diffusion. The results show that our method makes a huge improvement in the speed over the existing greedy approaches.
Variation of nanopore diameter along porous anodic alumina channels by multi-step anodization.
Lee, Kwang Hong; Lim, Xin Yuan; Wai, Kah Wing; Romanato, Filippo; Wong, Chee Cheong
2011-02-01
In order to form tapered nanocapillaries, we investigated a method to vary the nanopore diameter along the porous anodic alumina (PAA) channels using multi-step anodization. By anodizing the aluminum in either single acid (H3PO4) or multi-acid (H2SO4, oxalic acid and H3PO4) with increasing or decreasing voltage, the diameter of the nanopore along the PAA channel can be varied systematically corresponding to the applied voltages. The pore size along the channel can be enlarged or shrunken in the range of 20 nm to 200 nm. Structural engineering of the template along the film growth direction can be achieved by deliberately designing a suitable voltage and electrolyte together with anodization time.
The solution of Parrondo’s games with multi-step jumps
NASA Astrophysics Data System (ADS)
Saakian, David B.
2016-04-01
We consider the general case of Parrondo’s games, when there is a finite probability to stay in the current state as well as multi-step jumps. We introduce a modification of the model: the transition probabilities between different games depend on the choice of the game in the previous round. We calculate the rate of capital growth as well as the variance of the distribution, following large deviation theory. The modified model allows higher capital growth rates than in standard Parrondo games for the range of parameters considered in the key articles about these games, and positive capital growth is possible for a much wider regime of parameters of the model.
Conjugate symplecticity of second-order linear multi-step methods
NASA Astrophysics Data System (ADS)
Feng, Quan-Dong; Jiao, Yan-Dong; Tang, Yi-Fa
2007-06-01
We review the two different approaches for symplecticity of linear multi-step methods (LMSM) by Eirola and Sanz-Serna, Ge and Feng, and by Feng and Tang, Hairer and Leone, respectively, and give a numerical example between these two approaches. We prove that in the conjugate relation with and being LMSMs, if is symplectic, then the B-series error expansions of , and of the form are equal to those of trapezoid, mid-point and Euler forward schemes up to a parameter [theta] (completely the same when [theta]=1), respectively, this also partially solves a problem due to Hairer. In particular we indicate that the second-order symmetric leap-frog scheme Z2=Z0+2[tau]J-1[backward difference]H(Z1) cannot be conjugate-symplectic via another LMSM.
A Multi-Step Assessment Scheme for Seismic Network Site Selection in Densely Populated Areas
NASA Astrophysics Data System (ADS)
Plenkers, Katrin; Husen, Stephan; Kraft, Toni
2015-10-01
We developed a multi-step assessment scheme for improved site selection during seismic network installation in densely populated areas. Site selection is a complex process where different aspects (seismic background noise, geology, and financing) have to be taken into account. In order to improve this process, we developed a step-wise approach that allows quantifying the quality of a site by using, in addition to expert judgement and test measurements, two weighting functions as well as reference stations. Our approach ensures that the recording quality aimed for is reached and makes different sites quantitatively comparable to each other. Last but not least, it is an easy way to document the decision process, because all relevant parameters are listed, quantified, and weighted.
Star sub-pixel centroid calculation based on multi-step minimum energy difference method
NASA Astrophysics Data System (ADS)
Wang, Duo; Han, YanLi; Sun, Tengfei
2013-09-01
The star's centroid plays a vital role in celestial navigation, star images which be gotten during daytime, due to the strong sky background, have a low SNR, and the star objectives are nearly submerged in the background, takes a great trouble to the centroid localization. Traditional methods, such as a moment method, weighted centroid calculation method is simple but has a big error, especially in the condition of a low SNR. Gaussian method has a high positioning accuracy, but the computational complexity. Analysis of the energy distribution in star image, a location method for star target centroids based on multi-step minimum energy difference is proposed. This method uses the linear superposition to narrow the centroid area, in the certain narrow area uses a certain number of interpolation to pixels for the pixels' segmentation, and then using the symmetry of the stellar energy distribution, tentatively to get the centroid position: assume that the current pixel is the star centroid position, and then calculates and gets the difference of the sum of the energy which in the symmetric direction(in this paper we take the two directions of transverse and longitudinal) and the equal step length(which can be decided through different conditions, the paper takes 9 as the step length) of the current pixel, and obtain the centroid position in this direction when the minimum difference appears, and so do the other directions, then the validation comparison of simulated star images, and compare with several traditional methods, experiments shows that the positioning accuracy of the method up to 0.001 pixel, has good effect to calculate the centroid of low SNR conditions; at the same time, uses this method on a star map which got at the fixed observation site during daytime in near-infrared band, compare the results of the paper's method with the position messages which were known of the star, it shows that :the multi-step minimum energy difference method achieves a better
Wei, Meng; Chen, Jiajun
2016-11-01
A multi-step soil washing test using a typical chelating agent (Na2EDTA), organic acid (oxalic acid), and inorganic weak acid (phosphoric acid) was conducted to remediate soil contaminated with heavy metals near an arsenic mining area. The aim of the test was to improve the heavy metal removal efficiency and investigate its influence on metal fractionation and the spectroscopy characteristics of contaminated soil. The results indicated that the orders of the multi-step washing were critical for the removal efficiencies of the metal fractions, bioavailability, and potential mobility due to the different dissolution levels of mineral fractions and the inter-transformation of metal fractions by XRD and FT-IR spectral analyses. The optimal soil washing options were identified as the Na2EDTA-phosphoric-oxalic acid (EPO) and phosphoric-oxalic acid-Na2EDTA (POE) sequences because of their high removal efficiencies (approximately 45 % for arsenic and 88 % for cadmium) and the minimal harmful effects that were determined by the mobility and bioavailability of the remaining heavy metals based on the metal stability (I R ) and modified redistribution index ([Formula: see text]).
Near-Oracle Performance Guarantees for Greedy-Like Methods
NASA Astrophysics Data System (ADS)
Giryes, Raja; Elad, Michael
2010-09-01
In this paper analysis for Greedy-Like methods are presented. These methods include Subspace Pursuit (SP), Compressive Sampling Matching Pursuit (CoSaMP) and Iterative Hard Thresholding (IHT) algorithms. The proposed analysis is based on the Restricted-Isometry-Property (RIP), establishing a near-oracle performance guarantee for each of these techniques. The signal is assumed to be corrupted by an additive random white Gaussian noise; and to have a K-sparse representation with respect to a known dictionary D. The results for the three algorithms are of the same type but uses different constants and different requirements on the cardinality of the sparse representation.
NASA Astrophysics Data System (ADS)
Xu, D. X.; Shen, G. D.; Willander, M.; Hansson, G. V.
1988-11-01
Novel bidirectional negative differential resistance (NDR) phenomena have been observed at room temperature in strained base n-Si/p-Si1-xGex/n-Si double heterojunction bipolar transistors (DHBTs). A strong and symmetric bidirectional NDR modulated by base bias, together with a multi-step characteristic in collector current IC vs emitter-collector bias voltage VCE, was obtained in the devices with very thin base. The temperature dependence of the NDR and the multi-step IC-VCE characteristics has been measured to identify the possible transport mechanism. The physical origins of these phenomena are discussed.
Csom, Gyula; Feher, Sandor; Szieberthj, Mate
2002-07-01
Nowadays the molten salt reactor (MSR) concept seems to revive as one of the most promising systems for the realization of transmutation. In the molten salt reactors and subcritical systems the fuel and material to be transmuted circulate dissolved in some molten salt. The main advantage of this reactor type is the possibility of the continuous feed and reprocessing of the fuel. In the present paper a novel molten salt reactor concept is introduced and its transmutation capabilities are studied. The goal is the development of a transmutation technique along with a device implementing it, which yield higher transmutation efficiencies than that of the known procedures and thus results in radioactive waste whose load on the environment is reduced both in magnitude and time length. The procedure is the multi-step time-scheduled transmutation, in which transformation is done in several consecutive steps of different neutron flux and spectrum. In the new MSR concept, named 'multi-region' MSR (MRMSR), the primary circuit is made up of a few separate loops, in which salt-fuel mixtures of different compositions are circulated. The loop sections constituting the core region are only neutronically and thermally coupled. This new concept makes possible the utilization of the spatial dependence of spectrum as well as the advantageous features of liquid fuel such as the possibility of continuous chemical processing etc. In order to compare a 'conventional' MSR and a proposed MRMSR in terms of efficiency, preliminary calculational results are shown. Further calculations in order to find the optimal implementation of this new concept and to emphasize its other advantageous features are going on. (authors)
A multi-step transversal linearization (MTL) method in non-linear structural dynamics
NASA Astrophysics Data System (ADS)
Roy, D.; Kumar, Rajesh
2005-10-01
An implicit family of multi-step transversal linearization (MTL) methods is proposed for efficient and numerically stable integration of nonlinear oscillators of interest in structural dynamics. The presently developed method is a multi-step extension and further generalization of the locally transversal linearization (LTL) method proposed earlier by Roy (Proceedings of the Academy of the Royal Society (London) 457 (2001) 539-566), Roy and Ramachandra (Journal of Sound and Vibration 41 (2001a) 653-679, International Journal for Numerical Methods in Engineering 51 (2001b) 203-224) and Roy (International Journal of Numerical Methods in Engineering 61 (2004) 764). The MTL-based linearization is achieved through a non-unique replacement of the nonlinear part of the vector field by a conditionally linear interpolating expansion of known accuracy, whose coefficients contain the discretized state variables defined at a set of grid points. In the process, the nonlinear part of the vector field becomes a conditionally determinable equivalent forcing function. The MTL-based linearized differential equations thus become explicitly integrable. Based on the linearized solution, a set of algebraic, constraint equations are so formed that transversal intersections of the linearized and nonlinearized solution manifolds occur at the multiple grid points. The discretized state vectors are thus found as the zeros of the constraint equations. Simple error estimates for the displacement and velocity vectors are provided and, in particular, it is shown that the formal accuracy of the MTL methods as a function of the time step-size depends only on the error of replacement of the nonlinear part of the vector field. Presently, only two different polynomial-based interpolation schemes are employed for transversal linearization, viz. the Taylor-like interpolation and the Lagrangian interpolation. While the Taylor-like interpolation leads to numerical ill-conditioning as the order of
Exact free vibration of multi-step Timoshenko beam system with several attachments
NASA Astrophysics Data System (ADS)
Farghaly, S. H.; El-Sayed, T. A.
2016-05-01
This paper deals with the analysis of the natural frequencies, mode shapes of an axially loaded multi-step Timoshenko beam combined system carrying several attachments. The influence of system design and the proposed sub-system non-dimensional parameters on the combined system characteristics are the major part of this investigation. The effect of material properties, rotary inertia and shear deformation of the beam system for each span are included. The end masses are elastically supported against rotation and translation at an offset point from the point of attachment. A sub-system having two degrees of freedom is located at the beam ends and at any of the intermediate stations and acts as a support and/or a suspension. The boundary conditions of the ordinary differential equation governing the lateral deflections and slope due to bending of the beam system including the shear force term, due to the sub-system, have been formulated. Exact global coefficient matrices for the combined modal frequencies, the modal shape and for the discrete sub-system have been derived. Based on these formulae, detailed parametric studies of the combined system are carried out. The applied mathematical model is valid for wide range of applications especially in mechanical, naval and structural engineering fields.
Multi-step sequential batch two-phase anaerobic composting of food waste.
Shin, H S; Han, S K; Song, Y C; Lee, C Y
2001-03-01
This study was conducted to evaluate the newly devised process, called MUlti-step Sequential batch Two-phase Anaerobic Composting (MUSTAC). The MUSTAC process consisted of several leaching beds for hydrolysis, acidification and post-treatment, and a UASB reactor for methane recovery. This process to treat food waste was developed with a high-rate anaerobic composting technique based on the rate-limiting step approach. Rumen microorganisms were inoculated to improve the low efficiency of acidogenic fermentation. Both two-phase anaerobic digestion and sequential batch operation were used to control environmental constraints in anaerobic degradation. The MUSTAC process demonstrated excellent performance as it resulted in a large reduction in volatile solids (VS) (84.7%) and high methane conversion efficiency (84.4%) at high organic loading rates (10.8 kg VS m(-3) d(-1)) in a short SRT (10 days). Methane yield was 0.27 m3 kg(-1) VS, while methane gas production rate was 2.27 m3 m(-3) d(-1). The output from the post-treatment could be used as a soil amendment, which was produced at the same acidogenic fermenter without troublesome moving. The main advantages of the MUSTAC process were simple operation and high efficiency. The MUSTAC process proved stable, reliable and effective in resource recovery as well as waste stabilization.
Complex network analysis of brain functional connectivity under a multi-step cognitive task
NASA Astrophysics Data System (ADS)
Cai, Shi-Min; Chen, Wei; Liu, Dong-Bai; Tang, Ming; Chen, Xun
2017-01-01
Functional brain network has been widely studied to understand the relationship between brain organization and behavior. In this paper, we aim to explore the functional connectivity of brain network under a multi-step cognitive task involving consecutive behaviors, and further understand the effect of behaviors on the brain organization. The functional brain networks are constructed based on a high spatial and temporal resolution fMRI dataset and analyzed via complex network based approach. We find that at voxel level the functional brain network shows robust small-worldness and scale-free characteristics, while its assortativity and rich-club organization are slightly restricted to the order of behaviors performed. More interestingly, the functional connectivity of brain network in activated ROIs strongly correlates with behaviors and is obviously restricted to the order of behaviors performed. These empirical results suggest that the brain organization has the generic properties of small-worldness and scale-free characteristics, and its diverse functional connectivity emerging from activated ROIs is strongly driven by these behavioral activities via the plasticity of brain.
Automating multi-step paper-based assays using integrated layering of reagents.
Jahanshahi-Anbuhi, Sana; Kannan, Balamurali; Pennings, Kevin; Monsur Ali, M; Leung, Vincent; Giang, Karen; Wang, Jingyun; White, Dawn; Li, Yingfu; Pelton, Robert H; Brennan, John D; Filipe, Carlos D M
2017-02-28
We describe a versatile and simple method to perform sequential reactions on paper analytical devices by stacking dry pullulan films on paper, where each film contains one or more reagents or acts as a delay layer. Exposing the films to an aqueous solution of the analyte leads to sequential dissolution of the films in a temporally controlled manner followed by diffusive mixing of the reagents, so that sequential reactions can be performed. The films can be easily arranged for lateral flow assays or for spot tests (reactions take place sequentially in the z-direction). We have tested the general feasibility of the approach using three different model systems to demonstrate different capabilities: 1) pH ramping from low to high and high to low to demonstrate timing control; 2) rapid ready-to-use two-step Simon's assays on paper for detection of drugs of abuse utilizing a 2-layer stack containing two different reagents to demonstrate the ability to perform assays in the z-direction; and 3) sequential cell lysing and colorimetric detection of an intracellular bacterial enzyme, to demonstrate the ability of the method to perform sample preparation and analysis in the form of a spot assay. Overall, these studies demonstrate the potential of stacked pullulan films as useful components to enable multi-step assays on simple paper-based devices.
Michaelis-Menten kinetics in shear flow: Similarity solutions for multi-step reactions.
Ristenpart, W D; Stone, H A
2012-03-01
Models for chemical reaction kinetics typically assume well-mixed conditions, in which chemical compositions change in time but are uniform in space. In contrast, many biological and microfluidic systems of interest involve non-uniform flows where gradients in flow velocity dynamically alter the effective reaction volume. Here, we present a theoretical framework for characterizing multi-step reactions that occur when an enzyme or enzymatic substrate is released from a flat solid surface into a linear shear flow. Similarity solutions are developed for situations where the reactions are sufficiently slow compared to a convective time scale, allowing a regular perturbation approach to be employed. For the specific case of Michaelis-Menten reactions, we establish that the transversally averaged concentration of product scales with the distance x downstream as x(5/3). We generalize the analysis to n-step reactions, and we discuss the implications for designing new microfluidic kinetic assays to probe the effect of flow on biochemical processes.
Shutdown Dose Rate Analysis Using the Multi-Step CADIS Method
Ibrahim, Ahmad M.; Peplow, Douglas E.; Peterson, Joshua L.; Grove, Robert E.
2015-01-01
The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) hybrid Monte Carlo (MC)/deterministic radiation transport method was proposed to speed up the shutdown dose rate (SDDR) neutron MC calculation using an importance function that represents the neutron importance to the final SDDR. This work applied the MS-CADIS method to the ITER SDDR benchmark problem. The MS-CADIS method was also used to calculate the SDDR uncertainty resulting from uncertainties in the MC neutron calculation and to determine the degree of undersampling in SDDR calculations because of the limited ability of the MC method to tally detailed spatial and energy distributions. The analysis that used the ITER benchmark problem compared the efficiency of the MS-CADIS method to the traditional approach of using global MC variance reduction techniques for speeding up SDDR neutron MC calculation. Compared to the standard Forward-Weighted-CADIS (FW-CADIS) method, the MS-CADIS method increased the efficiency of the SDDR neutron MC calculation by 69%. The MS-CADIS method also increased the fraction of nonzero scoring mesh tally elements in the space-energy regions of high importance to the final SDDR.
Shutdown Dose Rate Analysis Using the Multi-Step CADIS Method
Ibrahim, Ahmad M.; Peplow, Douglas E.; Peterson, Joshua L.; ...
2015-01-01
The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) hybrid Monte Carlo (MC)/deterministic radiation transport method was proposed to speed up the shutdown dose rate (SDDR) neutron MC calculation using an importance function that represents the neutron importance to the final SDDR. This work applied the MS-CADIS method to the ITER SDDR benchmark problem. The MS-CADIS method was also used to calculate the SDDR uncertainty resulting from uncertainties in the MC neutron calculation and to determine the degree of undersampling in SDDR calculations because of the limited ability of the MC method to tally detailed spatial and energy distributions. The analysismore » that used the ITER benchmark problem compared the efficiency of the MS-CADIS method to the traditional approach of using global MC variance reduction techniques for speeding up SDDR neutron MC calculation. Compared to the standard Forward-Weighted-CADIS (FW-CADIS) method, the MS-CADIS method increased the efficiency of the SDDR neutron MC calculation by 69%. The MS-CADIS method also increased the fraction of nonzero scoring mesh tally elements in the space-energy regions of high importance to the final SDDR.« less
Multi-step process for concentrating magnetic particles in waste sludges
Watson, John L.
1990-01-01
This invention involves a multi-step, multi-force process for dewatering sludges which have high concentrations of magnetic particles, such as waste sludges generated during steelmaking. This series of processing steps involves (1) mixing a chemical flocculating agent with the sludge; (2) allowing the particles to aggregate under non-turbulent conditions; (3) subjecting the mixture to a magnetic field which will pull the magnetic aggregates in a selected direction, causing them to form a compacted sludge; (4) preferably, decanting the clarified liquid from the compacted sludge; and (5) using filtration to convert the compacted sludge into a cake having a very high solids content. Steps 2 and 3 should be performed simultaneously. This reduces the treatment time and increases the extent of flocculation and the effectiveness of the process. As partially formed aggregates with active flocculating groups are pulled through the mixture by the magnetic field, they will contact other particles and form larger aggregates. This process can increase the solids concentration of steelmaking sludges in an efficient and economic manner, thereby accomplishing either of two goals: (a) it can convert hazardous wastes into economic resources for recycling as furnace feed material, or (b) it can dramatically reduce the volume of waste material which must be disposed.
Multi-step process for concentrating magnetic particles in waste sludges
Watson, J.L.
1990-07-10
This invention involves a multi-step, multi-force process for dewatering sludges which have high concentrations of magnetic particles, such as waste sludges generated during steelmaking. This series of processing steps involves (1) mixing a chemical flocculating agent with the sludge; (2) allowing the particles to aggregate under non-turbulent conditions; (3) subjecting the mixture to a magnetic field which will pull the magnetic aggregates in a selected direction, causing them to form a compacted sludge; (4) preferably, decanting the clarified liquid from the compacted sludge; and (5) using filtration to convert the compacted sludge into a cake having a very high solids content. Steps 2 and 3 should be performed simultaneously. This reduces the treatment time and increases the extent of flocculation and the effectiveness of the process. As partially formed aggregates with active flocculating groups are pulled through the mixture by the magnetic field, they will contact other particles and form larger aggregates. This process can increase the solids concentration of steelmaking sludges in an efficient and economic manner, thereby accomplishing either of two goals: (a) it can convert hazardous wastes into economic resources for recycling as furnace feed material, or (b) it can dramatically reduce the volume of waste material which must be disposed. 7 figs.
A Greedy Double Auction Mechanism for Grid Resource Allocation
NASA Astrophysics Data System (ADS)
Ding, Ding; Luo, Siwei; Gao, Zhan
To improve the resource utilization and satisfy more users, a Greedy Double Auction Mechanism(GDAM) is proposed to allocate resources in grid environments. GDAM trades resources at discriminatory price instead of uniform price, reflecting the variance in requirements for profits and quantities. Moreover, GDAM applies different auction rules to different cases, over-demand, over-supply and equilibrium of demand and supply. As a new mechanism for grid resource allocation, GDAM is proved to be strategy-proof, economically efficient, weakly budget-balanced and individual rational. Simulation results also confirm that GDAM outperforms the traditional one on both the total trade amount and the user satisfaction percentage, specially as more users are involved in the auction market.
Greedy Successive Anchorization for Localizing Machine Type Communication Devices
Imtiaz Ul Haq, Mian; Kim, Dongwoo
2016-01-01
Localization of machine type communication (MTC) devices is essential for various types of location-based applications. In this paper, we investigate a distributed localization problem in noisy networks, where an estimated position of blind MTC machines (BMs) is obtained by using noisy measurements of distance between BM and anchor machines (AMs). We allow positioned BMs also to work as anchors that are referred to as virtual AMs (VAMs) in this paper. VAMs usually have greater position errors than (original) AMs, and, if used as anchors, the error propagates through the whole network. However, VAMs are necessary, especially when many BMs are distributed in a large area with an insufficient number of AMs. To overcome the error propagation, we propose a greedy successive anchorization process (GSAP). A round of GSAP consists of consecutive two steps. In the first step, a greedy selection of anchors among AMs and VAMs is done by which GSAP considers only those three anchors that possibly pertain to the localization accuracy. In the second step, each BM that can select three anchors in its neighbor determines its location with a proposed distributed localization algorithm. Iterative rounds of GSAP terminate when every BM in the network finds its location. To examine the performance of GSAP, a root mean square error (RMSE) metric is used and the corresponding Cramér–Rao lower bound (CRLB) is provided. By numerical investigation, RMSE performance of GSAP is shown to be better than existing localization methods with and without an anchor selection method and mostly close to the CRLB. PMID:27983576
Two- and multi-step annealing of cereal starches in relation to gelatinization.
Shi, Yong-Cheng
2008-02-13
Two- and multi-step annealing experiments were designed to determine how much gelatinization temperature of waxy rice, waxy barley, and wheat starches could be increased without causing a decrease in gelatinization enthalpy or a decline in X-ray crystallinity. A mixture of starch and excess water was heated in a differential scanning calorimeter (DSC) pan to a specific temperature and maintained there for 0.5-48 h. The experimental approach was first to anneal a starch at a low temperature so that the gelatinization temperature of the starch was increased without causing a decrease in gelatinization enthalpy. The annealing temperature was then raised, but still was kept below the onset gelatinization temperature of the previously annealed starch. When a second- or third-step annealing temperature was high enough, it caused a decrease in crystallinity, even though the holding temperature remained below the onset gelatinization temperature of the previously annealed starch. These results support that gelatinization is a nonequilibrium process and that dissociation of double helices is driven by the swelling of amorphous regions. Small-scale starch slurry annealing was also performed and confirmed the annealing results conducted in DSC pans. A three-phase model of a starch granule, a mobile amorphous phase, a rigid amorphous phase, and a crystalline phase, was used to interpret the annealing results. Annealing seems to be an interplay between a more efficient packing of crystallites in starch granules and swelling of plasticized amorphous regions. There is always a temperature ceiling that can be used to anneal a starch without causing a decrease in crystallinity. That temperature ceiling is starch-specific, dependent on the structure of a starch, and is lower than the original onset gelatinization of a starch.
Detection of Heterogeneous Small Inclusions by a Multi-Step MUSIC Method
NASA Astrophysics Data System (ADS)
Solimene, Raffaele; Dell'Aversano, Angela; Leone, Giovanni
2014-05-01
In this contribution the problem of detecting and localizing scatterers with small (in terms of wavelength) cross sections by collecting their scattered field is addressed. The problem is dealt with for a two-dimensional and scalar configuration where the background is given as a two-layered cylindrical medium. More in detail, while scattered field data are taken in the outermost layer, inclusions are embedded within the inner layer. Moreover, the case of heterogeneous inclusions (i.e., having different scattering coefficients) is addressed. As a pertinent applicative context we identify the problem of diagnose concrete pillars in order to detect and locate rebars, ducts and other small in-homogeneities that can populate the interior of the pillar. The nature of inclusions influences the scattering coefficients. For example, the field scattered by rebars is stronger than the one due to ducts. Accordingly, it is expected that the more weakly scattering inclusions can be difficult to be detected as their scattered fields tend to be overwhelmed by those of strong scatterers. In order to circumvent this problem, in this contribution a multi-step MUltiple SIgnal Classification (MUSIC) detection algorithm is adopted [1]. In particular, the first stage aims at detecting rebars. Once rebars have been detected, their positions are exploited to update the Green's function and to subtract the scattered field due to their presence. The procedure is repeated until all the inclusions are detected. The analysis is conducted by numerical experiments for a multi-view/multi-static single-frequency configuration and the synthetic data are generated by a FDTD forward solver. Acknowledgement This work benefited from networking activities carried out within the EU funded COST Action TU1208 "Civil Engineering Applications of Ground Penetrating Radar." [1] R. Solimene, A. Dell'Aversano and G. Leone, "MUSIC algorithms for rebar detection," J. of Geophysics and Engineering, vol. 10, pp. 1
Komatsu, Daisuke D; Tsunogai, Urumu; Kamimura, Kanae; Konno, Uta; Ishimura, Toyoho; Nakagawa, Fumiko
2011-11-15
We have developed a new automated analytical system that employs a continuous flow isotope ratio mass spectrometer to determine the stable hydrogen isotopic composition (δD) of nanomolar quantities of molecular hydrogen (H(2)) in an air sample. This method improves previous methods to attain simpler and lower-cost analyses, especially by avoiding the use of expensive or special devices, such as a Toepler pump, a cryogenic refrigerator, and a special evacuation system to keep the temperature of a coolant under reduced pressure. Instead, the system allows H(2) purification from the air matrix via automatic multi-step gas chromatographic separation using the coolants of both liquid nitrogen (77 K) and liquid nitrogen + ethanol (158 K) under 1 atm pressure. The analytical precision of the δD determination using the developed method was better than 4‰ for >5 nmol injections (250 mL STP for 500 ppbv air sample) and better than 15‰ for 1 nmol injections, regardless of the δD value, within 1 h for one sample analysis. Using the developed system, the δD values of H(2) can be quantified for atmospheric samples as well as samples of representative sources and sinks including those containing small quantities of H(2) , such as H(2) in soil pores or aqueous environments, for which there is currently little δD data available. As an example of such trace H(2) analyses, we report here the isotope fractionations during H(2) uptake by soils in a static chamber. The δD values of H(2) in these H(2)-depleted environments can be useful in constraining the budgets of atmospheric H(2) by applying an isotope mass balance model.
Mouse Embryonic Stem Cells Inhibit Murine Cytomegalovirus Infection through a Multi-Step Process
Kawasaki, Hideya; Kosugi, Isao; Arai, Yoshifumi; Iwashita, Toshihide; Tsutsui, Yoshihiro
2011-01-01
In humans, cytomegalovirus (CMV) is the most significant infectious cause of intrauterine infections that cause congenital anomalies of the central nervous system. Currently, it is not known how this process is affected by the timing of infection and the susceptibility of early-gestational-period cells. Embryonic stem (ES) cells are more resistant to CMV than most other cell types, although the mechanism responsible for this resistance is not well understood. Using a plaque assay and evaluation of immediate-early 1 mRNA and protein expression, we found that mouse ES cells were resistant to murine CMV (MCMV) at the point of transcription. In ES cells infected with MCMV, treatment with forskolin and trichostatin A did not confer full permissiveness to MCMV. In ES cultures infected with elongation factor-1α (EF-1α) promoter-green fluorescent protein (GFP) recombinant MCMV at a multiplicity of infection of 10, less than 5% of cells were GFP-positive, despite the fact that ES cells have relatively high EF-1α promoter activity. Quantitative PCR analysis of the MCMV genome showed that ES cells allow approximately 20-fold less MCMV DNA to enter the nucleus than mouse embryonic fibroblasts (MEFs) do, and that this inhibition occurs in a multi-step manner. In situ hybridization revealed that ES cell nuclei have significantly less MCMV DNA than MEF nuclei. This appears to be facilitated by the fact that ES cells express less heparan sulfate, β1 integrin, and vimentin, and have fewer nuclear pores, than MEF. This may reduce the ability of MCMV to attach to and enter through the cellular membrane, translocate to the nucleus, and cross the nuclear membrane in pluripotent stem cells (ES/induced pluripotent stem cells). The results presented here provide perspective on the relationship between CMV susceptibility and cell differentiation. PMID:21407806
Kamimura, Ryotaro
2004-02-01
In this paper, we extend our greedy network-growing algorithm to multi-layered networks. With multi-layered networks, we can solve many complex problems that single-layered networks fail to solve. In addition, the network-growing algorithm is used in conjunction with teacher-directed learning that produces appropriate outputs without computing errors between targets and outputs. Thus, the present algorithm is a very efficient network-growing algorithm. The new algorithm was applied to three problems: the famous vertical-horizontal lines detection problem, a medical data problem and a road classification problem. In all these cases, experimental results confirmed that the method could solve problems that single-layered networks failed to. In addition, information maximization makes it possible to extract salient features in input patterns.
NASA Technical Reports Server (NTRS)
Dupnick, E.; Wiggins, D.
1980-01-01
The functional specifications, functional design and flow, and the program logic of the GREEDY computer program are described. The GREEDY program is a submodule of the Scheduling Algorithm for Mission Planning and Logistics Evaluation (SAMPLE) program and has been designed as a continuation of the shuttle Mission Payloads (MPLS) program. The MPLS uses input payload data to form a set of feasible payload combinations; from these, GREEDY selects a subset of combinations (a traffic model) so all payloads can be included without redundancy. The program also provides the user a tutorial option so that he can choose an alternate traffic model in case a particular traffic model is unacceptable.
Method to Improve Indium Bump Bonding via Indium Oxide Removal Using a Multi-Step Plasma Process
NASA Technical Reports Server (NTRS)
Greer, H. Frank (Inventor); Jones, Todd J. (Inventor); Vasquez, Richard P. (Inventor); Hoenk, Michael E. (Inventor); Dickie, Matthew R. (Inventor); Nikzad, Shouleh (Inventor)
2012-01-01
A process for removing indium oxide from indium bumps in a flip-chip structure to reduce contact resistance, by a multi-step plasma treatment. A first plasma treatment of the indium bumps with an argon, methane and hydrogen plasma reduces indium oxide, and a second plasma treatment with an argon and hydrogen plasma removes residual organics. The multi-step plasma process for removing indium oxide from the indium bumps is more effective in reducing the oxide, and yet does not require the use of halogens, does not change the bump morphology, does not attack the bond pad material or under-bump metallization layers, and creates no new mechanisms for open circuits.
Cook, Ronald Lee; Elliott, Brian John; Luebben, Silvia DeVito; Myers, Andrew William; Smith, Bryan Matthew
2005-05-03
A new class of surface modified particles and a multi-step Michael-type addition surface modification process for the preparation of the same is provided. The multi-step Michael-type addition surface modification process involves two or more reactions to compatibilize particles with various host systems and/or to provide the particles with particular chemical reactivities. The initial step comprises the attachment of a small organic compound to the surface of the inorganic particle. The subsequent steps attach additional compounds to the previously attached organic compounds through reactive organic linking groups. Specifically, these reactive groups are activated carbon—carbon pi bonds and carbon and non-carbon nucleophiles that react via Michael or Michael-type additions.
Ishino, Seiya; Takahashi, Susumu; Ogawa, Masaaki; Sakurai, Yoshio
2017-02-23
Planning of multi-step actions based on the retrieval of acquired information is essential for efficient foraging. The hippocampus (HPC) and prefrontal cortex (PFC) may play critical roles in this process. However, in rodents, many studies investigating such roles utilized T-maze tasks that only require one-step actions (i.e., selection of one of two alternatives), in which memory retrieval and selection of an action based on the retrieval cannot be clearly differentiated. In monkeys, PFC has been suggested to be involved in planning of multi-step actions; however, the synchrony between HPC and PFC has not been evaluated. To address the combined role of the regions in planning of multi-step actions, we introduced a task in rats that required three successive nose-poke responses to three sequentially illuminated nose-poke holes. During the task, local field potentials (LFP) and spikes from hippocampal CA1 and medial PFC (mPFC) were simultaneously recorded. The position of the first hole indicated whether the following two holes would be presented in a predictable sequence or not. During the first nose-poke period, phase synchrony of LFPs in the theta range (4-10 Hz) between the regions was not different between predictable and unpredictable trials. However, only in trials of predictable sequences, the magnitude of theta phase synchrony during the first nose-poke period was negatively correlated with latency of the two-step ahead nose-poke response. Our findings point to the HPC-mPFC theta phase synchrony as a key mechanism underlying planning of multi-step actions based on memory retrieval rather than the retrieval itself. This article is protected by copyright. All rights reserved.
NASA Astrophysics Data System (ADS)
Lai, Zuliang; Xu, Peng; Wu, Peiyi
2009-01-01
Multi-steps infrared spectroscopic methods, including conventional Fourier transform infrared spectroscopy (FT-IR), second derivative spectroscopy and two-dimensional infrared (2D-IR) correlation spectroscopy, have been proved to be effective methods to examine complicated mixture system such as Chinese herbal medicine. The focus of this paper is the investigation on the effect of flowering on the pharmaceutical components of Cistanche tubulosa by using the Multi-steps infrared spectroscopic method. Power-spectrum analysis is applied to improve the resolution of 2D-IR contour maps and much more details of overlapped peaks are detected. According to the results of FT-IR and second derivative spectra, the peak at 1732 cm -1 assigned to C dbnd O is stronger before flowering than that after flowering in the stem, while more C dbnd O groups are found in the top after flowering. The spectra of root change a lot in the process of flowering for the reason that many peaks shift and disappear after flowering. Seven peaks in the spectra of stem, which are assigned to different kinds of glycoside components, are distinguished by Power-spectra in the range of 900-1200 cm -1. The results provide a scientific explanation to the traditional experience that flowering consumes the pharmaceutical components in stem and the seeds absorb some nutrients of stem after flowering. In conclusion, the Multi-steps infrared spectroscopic method combined with Power-spectra is a promising method to investigate the flowering process of C. tubulosa and discriminate various parts of the herbal medicine.
Aldabaldetreku, Gotzon; Durana, Gaizka; Zubia, Joseba; Arrue, Jon; Poisel, Hans; Losada, María
2005-05-30
The aim of the present paper is to provide a comprehensive analysis of the coupling losses in multi-step index (MSI) fibres. Their light power acceptance properties are investigated to obtain the corresponding analytical expressions taking into account longitudinal, transverse, and angular misalignments. For this purpose, a uniform power distribution is assumed. In addition, we perform several experimental measurements and computer simulations in order to calculate the coupling losses for two different MSI polymer optical fibres (MSI-POFs). These results serve us to validate the theoretical expressions we have obtained.
Multi-Step Ka/Ka Dichroic Plate with Rounded Corners for NASA's 34m Beam Waveguide Antenna
NASA Technical Reports Server (NTRS)
Veruttipong, Watt; Khayatian, Behrouz; Hoppe, Daniel; Long, Ezra
2013-01-01
A multi-step Ka/Ka dichroic plate Frequency Selective Surface (FSS structure) is designed, manufactured and tested for use in NASA's Deep Space Network (DSN) 34m Beam Waveguide (BWG) antennas. The proposed design allows ease of manufacturing and ability to handle the increased transmit power (reflected off the FSS) of the DSN BWG antennas from 20kW to 100 kW. The dichroic is designed using HFSS and results agree well with measured data considering the manufacturing tolerances that could be achieved on the dichroic.
Peyman, Sally A; Iles, Alexander; Pamme, Nicole
2008-03-14
We introduce a novel and extremely versatile microfluidic platform in which tedious multi-step biochemical processes can be performed in continuous flow within a fraction of the time required for conventional methods.
GreedyMAX-type Algorithms for the Maximum Independent Set Problem
NASA Astrophysics Data System (ADS)
Borowiecki, Piotr; Göring, Frank
A maximum independent set problem for a simple graph G = (V,E) is to find the largest subset of pairwise nonadjacent vertices. The problem is known to be NP-hard and it is also hard to approximate. Within this article we introduce a non-negative integer valued function p defined on the vertex set V(G) and called a potential function of a graph G, while P(G) = max v ∈ V(G) p(v) is called a potential of G. For any graph P(G) ≤ Δ(G), where Δ(G) is the maximum degree of G. Moreover, Δ(G) - P(G) may be arbitrarily large. A potential of a vertex lets us get a closer insight into the properties of its neighborhood which leads to the definition of the family of GreedyMAX-type algorithms having the classical GreedyMAX algorithm as their origin. We establish a lower bound 1/(P + 1) for the performance ratio of GreedyMAX-type algorithms which favorably compares with the bound 1/(Δ + 1) known to hold for GreedyMAX. The cardinality of an independent set generated by any GreedyMAX-type algorithm is at least sum_{vin V(G)} (p(v)+1)^{-1}, which strengthens the bounds of Turán and Caro-Wei stated in terms of vertex degrees.
Lautenschlager, Karin; Hwang, Chiachi; Ling, Fangqiong; Liu, Wen-Tso; Boon, Nico; Köster, Oliver; Egli, Thomas; Hammes, Frederik
2014-10-01
Indigenous bacterial communities are essential for biofiltration processes in drinking water treatment systems. In this study, we examined the microbial community composition and abundance of three different biofilter types (rapid sand, granular activated carbon, and slow sand filters) and their respective effluents in a full-scale, multi-step treatment plant (Zürich, CH). Detailed analysis of organic carbon degradation underpinned biodegradation as the primary function of the biofilter biomass. The biomass was present in concentrations ranging between 2-5 × 10(15) cells/m(3) in all filters but was phylogenetically, enzymatically and metabolically diverse. Based on 16S rRNA gene-based 454 pyrosequencing analysis for microbial community composition, similar microbial taxa (predominantly Proteobacteria, Planctomycetes, Acidobacteria, Bacteriodetes, Nitrospira and Chloroflexi) were present in all biofilters and in their respective effluents, but the ratio of microbial taxa was different in each filter type. This change was also reflected in the cluster analysis, which revealed a change of 50-60% in microbial community composition between the different filter types. This study documents the direct influence of the filter biomass on the microbial community composition of the final drinking water, particularly when the water is distributed without post-disinfection. The results provide new insights on the complexity of indigenous bacteria colonizing drinking water systems, especially in different biofilters of a multi-step treatment plant.
NASA Astrophysics Data System (ADS)
Chang, Fi-John; Tsai, Meng-Jung
2016-04-01
Accurate multi-step-ahead inflow forecasting during typhoon periods is extremely crucial for real-time reservoir flood control. We propose a spatio-temporal lumping of radar rainfall for modeling inflow forecasts to mitigate time-lag problems and improve forecasting accuracy. Spatial aggregation of radar cells is made based on the sub-catchment partitioning obtained from the Self-Organizing Map (SOM), and then flood forecasting is made by the Adaptive Neuro Fuzzy Inference System (ANFIS) models coupled with a 2-staged Gamma Test (2-GT) procedure that identifies the optimal non-trivial rainfall inputs. The Shihmen Reservoir in northern Taiwan is used as a case study. The results show that the proposed methods can, in general, precisely make 1- to 4-hour-ahead forecasts and the lag time between predicted and observed flood peaks could be mitigated. The constructed ANFIS models with only two fuzzy if-then rules can effectively categorize inputs into two levels (i.e. high and low) and provide an insightful view (perspective) of the rainfall-runoff process, which demonstrate their capability in modeling the complex rainfall-runoff process. In addition, the confidence level of forecasts with acceptable error can reach as high as 97% at horizon t+1 and 77% at horizon t+4, respectively, which evidently promotes model reliability and leads to better decisions on real-time reservoir operation during typhoon events.
Effects of Stroke on Ipsilesional End-Effector Kinematics in a Multi-Step Activity of Daily Living
Gulde, Philipp; Hughes, Charmayne Mary Lee; Hermsdörfer, Joachim
2017-01-01
Background: Stroke frequently impairs activities of daily living (ADL) and deteriorates the function of the contra- as well as the ipsilesional limbs. In order to analyze alterations of higher motor control unaffected by paresis or sensory loss, the kinematics of ipsilesional upper limb movements in patients with stroke has previously been analyzed during prehensile movements and simple tool use actions. By contrast, motion recording of multi-step ADL is rare and patient-control comparisons for movement kinematics are largely lacking. Especially in clinical research, objective quantification of complex externally valid tasks can improve the assessment of neurological impairments. Methods: In this preliminary study we employed three-dimensional motion recording and applied kinematic analysis in a multi-step ADL (tea-making). The trials were examined with respect to errors and sub-action structure, durations, path lengths (PLs), peak velocities, relative activity (RA) and smoothness. In order to check for specific burdens the sub-actions of the task were extracted and compared. To examine the feasibility of the approach, we determined the behavioral and kinematic metrics of the (ipsilesional) unimanual performance of seven chronic stroke patients (64a ± 11a, 3 with right/4 with left brain damage (LBD), 2 with signs of apraxia, variable severity of paresis) and compared the results with data of 14 neurologically healthy age-matched control participants (70a ± 7a). Results: T-tests revealed that while the quantity and structure of sub-actions of the task were similar. The analysis of end-effector kinematics was able to detect clear group differences in the associated parameters. Specifically, trial duration (TD) was increased (Cohen’s d = 1.77); the RA (Cohen’s d = 1.72) and the parameters of peak velocities (Cohen’s d = 1.49/1.97) were decreased in the patient group. Analysis of the task’s sub-actions repeated measures analysis of variance (rmANOVA) revealed
Larjo, Antti; Lähdesmäki, Harri
2015-12-01
Bayesian networks have become popular for modeling probabilistic relationships between entities. As their structure can also be given a causal interpretation about the studied system, they can be used to learn, for example, regulatory relationships of genes or proteins in biological networks and pathways. Inference of the Bayesian network structure is complicated by the size of the model structure space, necessitating the use of optimization methods or sampling techniques, such Markov Chain Monte Carlo (MCMC) methods. However, convergence of MCMC chains is in many cases slow and can become even a harder issue as the dataset size grows. We show here how to improve convergence in the Bayesian network structure space by using an adjustable proposal distribution with the possibility to propose a wide range of steps in the structure space, and demonstrate improved network structure inference by analyzing phosphoprotein data from the human primary T cell signaling network.
van der Meer, Larah; Kagohara, Debora; Roche, Laura; Sutherland, Dean; Balandin, Susan; Green, Vanessa A; O'Reilly, Mark F; Lancioni, Giulio E; Marschik, Peter B; Sigafoos, Jeff
2013-09-01
The present study involved comparing the acquisition of multi-step requesting and social communication across three AAC options: manual signing (MS), picture exchange (PE), and speech-generating devices (SGDs). Preference for each option was also assessed. The participants were two children with autism spectrum disorders (ASD) who had previously been taught to use each option to request preferred items. Intervention was implemented in an alternating-treatments design. During baseline, participants demonstrated low levels of correct communicative responding. With intervention, both participants learned the target responses (two- and three-step requesting responses, greetings, answering questions, and social etiquette responses) to varying levels of proficiency with each communication option. One participant demonstrated a preference for using the SGD and the other preferred PE. The importance of examining preferences for using one AAC option over others is discussed.
Mancini, Joshua A; Kodali, Goutham; Jiang, Jianbing; Reddy, Kanumuri Ramesh; Lindsey, Jonathan S; Bryant, Donald A; Dutton, P Leslie; Moser, Christopher C
2017-02-01
Synthetic proteins designed and constructed from first principles with minimal reference to the sequence of any natural protein have proven robust and extraordinarily adaptable for engineering a range of functions. Here for the first time we describe the expression and genetic fusion of a natural photosynthetic light-harvesting subunit with a synthetic protein designed for light energy capture and multi-step transfer. We demonstrate excitation energy transfer from the bilin of the CpcA subunit (phycocyanin α subunit) of the cyanobacterial photosynthetic light-harvesting phycobilisome to synthetic four-helix-bundle proteins accommodating sites that specifically bind a variety of selected photoactive tetrapyrroles positioned to enhance energy transfer by relay. The examination of combinations of different bilin, chlorin and bacteriochlorin cofactors has led to identification of the preconditions for directing energy from the bilin light-harvesting antenna into synthetic protein-cofactor constructs that can be customized for light-activated chemistry in the cell.
Kinahan, David J; Kearney, Sinéad M; Dimov, Nikolay; Glynn, Macdara T; Ducrée, Jens
2014-07-07
The centrifugal "lab-on-a-disc" concept has proven to have great potential for process integration of bioanalytical assays, in particular where ease-of-use, ruggedness, portability, fast turn-around time and cost efficiency are of paramount importance. Yet, as all liquids residing on the disc are exposed to the same centrifugal field, an inherent challenge of these systems remains the automation of multi-step, multi-liquid sample processing and subsequent detection. In order to orchestrate the underlying bioanalytical protocols, an ample palette of rotationally and externally actuated valving schemes has been developed. While excelling with the level of flow control, externally actuated valves require interaction with peripheral instrumentation, thus compromising the conceptual simplicity of the centrifugal platform. In turn, for rotationally controlled schemes, such as common capillary burst valves, typical manufacturing tolerances tend to limit the number of consecutive laboratory unit operations (LUOs) that can be automated on a single disc. In this paper, a major advancement on recently established dissolvable film (DF) valving is presented; for the very first time, a liquid handling sequence can be controlled in response to completion of preceding liquid transfer event, i.e. completely independent of external stimulus or changes in speed of disc rotation. The basic, event-triggered valve configuration is further adapted to leverage conditional, large-scale process integration. First, we demonstrate a fluidic network on a disc encompassing 10 discrete valving steps including logical relationships such as an AND-conditional as well as serial and parallel flow control. Then we present a disc which is capable of implementing common laboratory unit operations such as metering and selective routing of flows. Finally, as a pilot study, these functions are integrated on a single disc to automate a common, multi-step lab protocol for the extraction of total RNA from
Design of a new automated multi-step outflow test apparatus
NASA Astrophysics Data System (ADS)
Figueras, J.; Gribb, M. M.; McNamara, J. P.
2006-12-01
Modeling flow and transport in the vadose zone requires knowledge of the soil hydraulic properties. Laboratories studies involving vadose zone soils typically include use of the multistep outflow method (MSO), which can provide information about wetting and drying soil-moisture and hydraulic conductivity curves from a single test. However, manual MSO testing is time consuming and measurement errors can be easily introduced. A computer-automated system has been designed to allow convenient measurement of soil-water characteristic curves. Computer-controlled solenoid valves are used to regulate the pressure inside Tempe cells to drain soil samples, and outflow volumes are measured with a pressure transducer. The electronic components of the system are controlled using LabVIEW software. This system has been optimized for undisturbed core samples. System performance has been evaluated by comparing results from undisturbed samples subjected first to manual MSO testing and then automated testing. The automated and manual MSO tests yielded similar drying soil-water characteristic curves. These curves are further compared to in-situ measurements and those obtained using pedotransfer functions for a semi-arid watershed.
GreedEx: A Visualization Tool for Experimentation and Discovery Learning of Greedy Algorithms
ERIC Educational Resources Information Center
Velazquez-Iturbide, J. A.; Debdi, O.; Esteban-Sanchez, N.; Pizarro, C.
2013-01-01
Several years ago we presented an experimental, discovery-learning approach to the active learning of greedy algorithms. This paper presents GreedEx, a visualization tool developed to support this didactic method. The paper states the design goals of GreedEx, makes explicit the major design decisions adopted, and describes its main characteristics…
Tsai, Hui-Hsu Gavin; Chang, Che-Ming; Lee, Jian-Bin
2014-06-01
Membrane fusion is essential for intracellular trafficking and virus infection, but the molecular mechanisms underlying the fusion process remain poorly understood. In this study, we employed all-atom molecular dynamics simulations to investigate the membrane fusion mechanism using vesicle models which were pre-bound by inter-vesicle Ca(2+)-lipid clusters to approximate Ca(2+)-catalyzed fusion. Our results show that the formation of the hemifusion diaphragm for vesicle fusion is a multi-step event. This result contrasts with the assumptions made in most continuum models. The neighboring hemifused states are separated by an energy barrier on the energy landscape. The hemifusion diaphragm is much thinner than the planar lipid bilayers. The thinning of the hemifusion diaphragm during its formation results in the opening of a fusion pore for vesicle fusion. This work provides new insights into the formation of the hemifusion diaphragm and thus increases understanding of the molecular mechanism of membrane fusion. This article is part of a Special Issue entitled: Membrane Structure and Function: Relevance in the Cell's Physiology, Pathology and Therapy.
NASA Astrophysics Data System (ADS)
Geppert, Ch.; Blaum, K.; Diel, S.; Müller, P.; Schreiber, W. G.; Wendt, K.
2001-08-01
Diode laser based multi-step resonance ionization mass spectrometry (RIMS), which has been developed primarily for ultra trace analysis of long lived radioactive isotopes has been adapted for the application to elements within the sequence of the rare earths. First investigations concern Gd isotopes. Here high suppression of isobars, as provided by RIMS, is mandatory. Using a three step resonant excitation scheme into an autoionizing state, which has been the subject of preparatory spectroscopic investigations, high efficiency of >1×10-6 and good isobaric selectivity >107 was realized. Additionally the linearity of the method has been demonstrated over six orders of magnitude. Avoiding contaminations from the Titanium-carrier foil resulted in a suppression of background of more than one order of magnitude and a correspondingly low detection limit of 4×109 atoms, equivalent to lpg of Gd. The technique has been applied for trace determination of the Gd-content in animal tissue. Bio-medical micro samples were analyzed shortly after Gd-chelat, which is used as the primary contrast medium for magnetic resonance imaging (MRI) in biomedical investigations, has been injected. Correlated in-vivo magnetic resonance images have been taken. The RIMS measurements show high reproducibility as a well as good precision, and contribute to new insight into the distribution and kinetics of Gd within different healthy and cancerous tissues.
Multiwavelength Observations of a Slow Raise, Multi-Step X1.6 Flare and the Associated Eruption
NASA Astrophysics Data System (ADS)
Yurchyshyn, V.
2015-12-01
Using multi-wavelength observations we studied a slow rise, multi-step X1.6 flare that began on November 7, 2014 as a localized eruption of core fields inside a δ-sunspot and later engulfed the entire active region. This flare event was associated with formation of two systems of post eruption arcades (PEAs) and several J-shaped flare ribbons showing extremely fine details, irreversible changes in the photospheric magnetic fields, and it was accompanied by a fast and wide coronal mass ejection. Data from the Solar Dynamics Observatory, IRIS spacecraft along with the ground based data from the New Solar Telescope (NST) present evidence that i) the flare and the eruption were directly triggered by a flux emergence that occurred inside a δ--sunspot at the boundary between two umbrae; ii) this event represented an example of an in-situ formation of an unstable flux rope observed only in hot AIA channels (131 and 94Å) and LASCO C2 coronagraph images; iii) the global PEA system spanned the entire AR and was due to global scale reconnection occurring at heights of about one solar radii, indicating on the global spatial and temporal scale of the eruption.
NASA Astrophysics Data System (ADS)
Niu, Gang; Yang, Bo-Suk
2009-04-01
Predicting a sequence of future values of a time series using the descriptors observed in the past can be regarded as the stand-stone of data-driven machinery prognosis. The purpose of this paper is to develop a novel data-driven machinery prognosis strategy for industry application. First, the collected time-series degradation features are reconstructed based on the theorem of Takens, among which the reconstruction parameters, delay time and embedding dimension are selected by the C-C method and the false nearest neighbor method, respectively. Next, the Dempster-Shafer regression technique is developed to perform the task of time-series prediction. Moreover, the strategy of iterated multi-step-ahead prediction is discussed to keep track with the rapid variation of time-series signals during the data monitoring process in an industrial plant. The proposed scheme is validated using condition monitoring data of a methane compressor to predict the degradation trend. Experimental results show that the proposed methods have a low error rate; hence, it can be regarded as an effective tool for data-driven machinery prognosis applications.
Segmenting the Femoral Head and Acetabulum in the Hip Joint Automatically Using a Multi-Step Scheme
NASA Astrophysics Data System (ADS)
Wang, Ji; Cheng, Yuanzhi; Fu, Yili; Zhou, Shengjun; Tamura, Shinichi
We describe a multi-step approach for automatic segmentation of the femoral head and the acetabulum in the hip joint from three dimensional (3D) CT images. Our segmentation method consists of the following steps: 1) construction of the valley-emphasized image by subtracting valleys from the original images; 2) initial segmentation of the bone regions by using conventional techniques including the initial threshold and binary morphological operations from the valley-emphasized image; 3) further segmentation of the bone regions by using the iterative adaptive classification with the initial segmentation result; 4) detection of the rough bone boundaries based on the segmented bone regions; 5) 3D reconstruction of the bone surface using the rough bone boundaries obtained in step 4) by a network of triangles; 6) correction of all vertices of the 3D bone surface based on the normal direction of vertices; 7) adjustment of the bone surface based on the corrected vertices. We evaluated our approach on 35 CT patient data sets. Our experimental results show that our segmentation algorithm is more accurate and robust against noise than other conventional approaches for automatic segmentation of the femoral head and the acetabulum. Average root-mean-square (RMS) distance from manual reference segmentations created by experienced users was approximately 0.68mm (in-plane resolution of the CT data).
ERIC Educational Resources Information Center
Mechling, Linda C.; Ayres, Kevin M.; Bryant, Kathryn J.; Foster, Ashley L.
2014-01-01
The current study evaluated a relatively new video-based procedure, continuous video modeling (CVM), to teach multi-step cleaning tasks to high school students with moderate intellectual disability. CVM in contrast to video modeling and video prompting allows repetition of the video model (looping) as many times as needed while the user completes…
Greedy heuristic algorithm for solving series of eee components classification problems*
NASA Astrophysics Data System (ADS)
Kazakovtsev, A. L.; Antamoshkin, A. N.; Fedosov, V. V.
2016-04-01
Algorithms based on using the agglomerative greedy heuristics demonstrate precise and stable results for clustering problems based on k- means and p-median models. Such algorithms are successfully implemented in the processes of production of specialized EEE components for using in space systems which include testing each EEE device and detection of homogeneous production batches of the EEE components based on results of the tests using p-median models. In this paper, authors propose a new version of the genetic algorithm with the greedy agglomerative heuristic which allows solving series of problems. Such algorithm is useful for solving the k-means and p-median clustering problems when the number of clusters is unknown. Computational experiments on real data show that the preciseness of the result decreases insignificantly in comparison with the initial genetic algorithm for solving a single problem.
NASA Astrophysics Data System (ADS)
Werisch, Stefan; Lennartz, Franz; Bieberle, Andre
2013-04-01
Dynamic Multi Step Outflow (MSO) experiments serve for the estimation of the parameters from soil hydraulic functions like e.g. the Mualem van Genuchten model. The soil hydraulic parameters are derived from outflow records and corresponding matric potential measurements from commonly a single tensiometer using inverse modeling techniques. We modified the experimental set up allowing for simultaneous measurements of the matric potential with three tensiometers and the water content using a high-resolution gamma-ray densiometry measurement system (Bieberle et al., 2007, Hampel et al., 2007). Different combinations of the measured time series were used for the estimation of effective soil hydraulic properties, representing different degrees of information of the "hydraulic reality" of the sample. The inverse modeling task was solved with the multimethod search algorithm AMALGAM (Vrugt et al., 2007) in combination with the Hydrus1D model (Šimúnek et al., 2008). Subsequently, the resulting effective soil hydraulic parameters allow the simulation of the MSO experiment and the comparison of model results with observations. The results show that the information of a single tensiometer together with the outflow record result in a set of effective soil hydraulic parameters producing an overall good agreement between the simulation and the observation for the location of the tensiometer. Significantly deviating results are obtained for the other tensiometer positions using this parameter set. Inclusion of more information, such as additional matric potential measurements with the according water contents within the optimization procedure lead to different, more representative hydraulic parameters which improved the overall agreement significantly. These findings indicate that more information about the soil hydraulic state variables in space and time are necessary to obtain effective soil hydraulic properties of soil core samples. Bieberle, A., Kronenberg, J., Schleicher, E
Improving Multi-Component Maintenance Acquisition with a Greedy Heuristic Local Algorithm
2013-04-01
need to improve the decision making process for system sustainment including maintenance, repair, and overhaul ( MRO ) operations and the acquisition of... MRO parts. To help address the link between sustainment policies and acquisition, this work develops a greedy heuristic?based local search algorithm to...concerns, there is a need to improve the decision making process for system sustainment, including maintenance, repair, and overhaul ( MRO
A Subspace Pursuit–based Iterative Greedy Hierarchical Solution to the Neuromagnetic Inverse Problem
Babadi, Behtash; Obregon-Henao, Gabriel; Lamus, Camilo; Hämäläinen, Matti S.; Brown, Emery N.; Purdon, Patrick L.
2013-01-01
Magnetoencephalography (MEG) is an important non-invasive method for studying activity within the human brain. Source localization methods can be used to estimate spatiotemporal activity from MEG measurements with high temporal resolution, but the spatial resolution of these estimates is poor due to the ill-posed nature of the MEG inverse problem. Recent developments in source localization methodology have emphasized temporal as well as spatial constraints to improve source localization accuracy, but these methods can be computationally intense. Solutions emphasizing spatial sparsity hold tremendous promise, since the underlying neurophysiological processes generating MEG signals are often sparse in nature, whether in the form of focal sources, or distributed sources representing large-scale functional networks. Recent developments in the theory of compressed sensing (CS) provide a rigorous framework to estimate signals with sparse structure. In particular, a class of CS algorithms referred to as greedy pursuit algorithms can provide both high recovery accuracy and low computational complexity. Greedy pursuit algorithms are difficult to apply directly to the MEG inverse problem because of the high-dimensional structure of the MEG source space and the high spatial correlation in MEG measurements. In this paper, we develop a novel greedy pursuit algorithm for sparse MEG source localization that overcomes these fundamental problems. This algorithm, which we refer to as the Subspace Pursuit-based Iterative Greedy Hierarchical (SPIGH) inverse solution, exhibits very low computational complexity while achieving very high localization accuracy. We evaluate the performance of the proposed algorithm using comprehensive simulations, as well as the analysis of human MEG data during spontaneous brain activity and somatosensory stimuli. These studies reveal substantial performance gains provided by the SPIGH algorithm in terms of computational complexity, localization accuracy
GreedyPlus: An Algorithm for the Alignment of Interface Interaction Networks.
Law, Brian; Bader, Gary D
2015-07-13
The increasing ease and accuracy of protein-protein interaction detection has resulted in the ability to map the interactomes of multiple species. We now have an opportunity to compare species to better understand how interactomes evolve. As DNA and protein sequence alignment algorithms were required for comparative genomics, network alignment algorithms are required for comparative interactomics. A number of network alignment methods have been developed for protein-protein interaction networks, where proteins are represented as vertices linked by edges if they interact. Recently, protein interactions have been mapped at the level of amino acid positions, which can be represented as an interface-interaction network (IIN), where vertices represent binding sites, such as protein domains and short sequence motifs. However, current algorithms are not designed to align these networks and generally fail to do so in practice. We present a greedy algorithm, GreedyPlus, for IIN alignment, combining data from diverse sources, including network, protein and binding site properties, to identify putative orthologous relationships between interfaces in available worm and yeast data. GreedyPlus is fast and simple, allowing for easy customization of behaviour, yet still capable of generating biologically meaningful network alignments.
Pishva, Ehsan; Drukker, Marjan; Viechtbauer, Wolfgang; Decoster, Jeroen; Collip, Dina; van Winkel, Ruud; Wichers, Marieke; Jacobs, Nele; Thiery, Evert; Derom, Catherine; Geschwind, Nicole; van den Hove, Daniel; Lataster, Tineke; Myin-Germeys, Inez; van Os, Jim; Rutten, Bart P F; Kenis, Gunter
2014-01-01
Recent human and animal studies suggest that epigenetic mechanisms mediate the impact of environment on development of mental disorders. Therefore, we hypothesized that polymorphisms in epigenetic-regulatory genes impact stress-induced emotional changes. A multi-step, multi-sample gene-environment interaction analysis was conducted to test whether 31 single nucleotide polymorphisms (SNPs) in epigenetic-regulatory genes, i.e. three DNA methyltransferase genes DNMT1, DNMT3A, DNMT3B, and methylenetetrahydrofolate reductase (MTHFR), moderate emotional responses to stressful and pleasant stimuli in daily life as measured by Experience Sampling Methodology (ESM). In the first step, main and interactive effects were tested in a sample of 112 healthy individuals. Significant associations in this discovery sample were then investigated in a population-based sample of 434 individuals for replication. SNPs showing significant effects in both the discovery and replication samples were subsequently tested in three other samples of: (i) 85 unaffected siblings of patients with psychosis, (ii) 110 patients with psychotic disorders, and iii) 126 patients with a history of major depressive disorder. Multilevel linear regression analyses showed no significant association between SNPs and negative affect or positive affect. No SNPs moderated the effect of pleasant stimuli on positive affect. Three SNPs of DNMT3A (rs11683424, rs1465764, rs1465825) and 1 SNP of MTHFR (rs1801131) moderated the effect of stressful events on negative affect. Only rs11683424 of DNMT3A showed consistent directions of effect in the majority of the 5 samples. These data provide the first evidence that emotional responses to daily life stressors may be moderated by genetic variation in the genes involved in the epigenetic machinery.
Pishva, Ehsan; Drukker, Marjan; Viechtbauer, Wolfgang; Decoster, Jeroen; Collip, Dina; van Winkel, Ruud; Wichers, Marieke; Jacobs, Nele; Thiery, Evert; Derom, Catherine; Geschwind, Nicole; van den Hove, Daniel; Lataster, Tineke; Myin-Germeys, Inez; van Os, Jim
2014-01-01
Recent human and animal studies suggest that epigenetic mechanisms mediate the impact of environment on development of mental disorders. Therefore, we hypothesized that polymorphisms in epigenetic-regulatory genes impact stress-induced emotional changes. A multi-step, multi-sample gene-environment interaction analysis was conducted to test whether 31 single nucleotide polymorphisms (SNPs) in epigenetic-regulatory genes, i.e. three DNA methyltransferase genes DNMT1, DNMT3A, DNMT3B, and methylenetetrahydrofolate reductase (MTHFR), moderate emotional responses to stressful and pleasant stimuli in daily life as measured by Experience Sampling Methodology (ESM). In the first step, main and interactive effects were tested in a sample of 112 healthy individuals. Significant associations in this discovery sample were then investigated in a population-based sample of 434 individuals for replication. SNPs showing significant effects in both the discovery and replication samples were subsequently tested in three other samples of: (i) 85 unaffected siblings of patients with psychosis, (ii) 110 patients with psychotic disorders, and iii) 126 patients with a history of major depressive disorder. Multilevel linear regression analyses showed no significant association between SNPs and negative affect or positive affect. No SNPs moderated the effect of pleasant stimuli on positive affect. Three SNPs of DNMT3A (rs11683424, rs1465764, rs1465825) and 1 SNP of MTHFR (rs1801131) moderated the effect of stressful events on negative affect. Only rs11683424 of DNMT3A showed consistent directions of effect in the majority of the 5 samples. These data provide the first evidence that emotional responses to daily life stressors may be moderated by genetic variation in the genes involved in the epigenetic machinery. PMID:24967710
NASA Astrophysics Data System (ADS)
Pang, Kar Mun; Jangi, Mehdi; Bai, Xue-Song; Schramm, Jesper
2015-05-01
In this work, a two-dimensional computational fluid dynamics study is reported of an n-heptane combustion event and the associated soot formation process in a constant volume combustion chamber. The key interest here is to evaluate the sensitivity of the chemical kinetics and submodels of a semi-empirical soot model in predicting the associated events. Numerical computation is performed using an open-source code and a chemistry coordinate mapping approach is used to expedite the calculation. A library consisting of various phenomenological multi-step soot models is constructed and integrated with the spray combustion solver. Prior to the soot modelling, combustion simulations are carried out. Numerical results show that the ignition delay times and lift-off lengths exhibit good agreement with the experimental measurements across a wide range of operating conditions, apart from those in the cases with ambient temperature lower than 850 K. The variation of the soot precursor production with respect to the change of ambient oxygen levels qualitatively agrees with that of the conceptual models when the skeletal n-heptane mechanism is integrated with a reduced pyrene chemistry. Subsequently, a comprehensive sensitivity analysis is carried out to appraise the existing soot formation and oxidation submodels. It is revealed that the soot formation is captured when the surface growth rate is calculated using a square root function of the soot specific surface area and when a pressure-dependent model constant is considered. An optimised soot model is then proposed based on the knowledge gained through this exercise. With the implementation of optimised model, the simulated soot onset and transport phenomena before reaching quasi-steady state agree reasonably well with the experimental observation. Also, variation of spatial soot distribution and soot mass produced at oxygen molar fractions ranging from 10.0 to 21.0% for both low and high density conditions are reproduced.
NASA Astrophysics Data System (ADS)
Guo, Xiao-Xi; Hu, Wei; Liu, Yuan; Sun, Su-Qin; Gu, Dong-Chen; He, Helen; Xu, Chang-Hua; Wang, Xi-Chang
2016-02-01
BPO is often added to wheat flour as flour improver, but its excessive use and edibility are receiving increasing concern. A multi-step IR macro-fingerprinting was employed to identify BPO in wheat flour and unveil its changes during storage. BPO contained in wheat flour (< 3.0 mg/kg) was difficult to be identified by infrared spectra with correlation coefficients between wheat flour and wheat flour samples contained BPO all close to 0.98. By applying second derivative spectroscopy, obvious differences among wheat flour and wheat flour contained BPO before and after storage in the range of 1500-1400 cm- 1 were disclosed. The peak of 1450 cm- 1 which belonged to BPO was blue shifted to 1453 cm- 1 (1455) which belonged to benzoic acid after one week of storage, indicating that BPO changed into benzoic acid after storage. Moreover, when using two-dimensional correlation infrared spectroscopy (2DCOS-IR) to track changes of BPO in wheat flour (0.05 mg/g) within one week, intensities of auto-peaks at 1781 cm- 1 and 669 cm- 1 which belonged to BPO and benzoic acid, respectively, were changing inversely, indicating that BPO was decomposed into benzoic acid. Moreover, another autopeak at 1767 cm- 1 which does not belong to benzoic acid was also rising simultaneously. By heating perturbation treatment of BPO in wheat flour based on 2DCOS-IR and spectral subtraction analysis, it was found that BPO in wheat flour not only decomposed into benzoic acid and benzoate, but also produced other deleterious substances, e.g., benzene. This study offers a promising method with minimum pretreatment and time-saving to identify BPO in wheat flour and its chemical products during storage in a holistic manner.
Guo, Xiao-Xi; Hu, Wei; Liu, Yuan; Sun, Su-Qin; Gu, Dong-Chen; He, Helen; Xu, Chang-Hua; Wang, Xi-Chang
2016-02-05
BPO is often added to wheat flour as flour improver, but its excessive use and edibility are receiving increasing concern. A multi-step IR macro-fingerprinting was employed to identify BPO in wheat flour and unveil its changes during storage. BPO contained in wheat flour (<3.0 mg/kg) was difficult to be identified by infrared spectra with correlation coefficients between wheat flour and wheat flour samples contained BPO all close to 0.98. By applying second derivative spectroscopy, obvious differences among wheat flour and wheat flour contained BPO before and after storage in the range of 1500-1400 cm(-1) were disclosed. The peak of 1450 cm(-1) which belonged to BPO was blue shifted to 1453 cm(-1) (1455) which belonged to benzoic acid after one week of storage, indicating that BPO changed into benzoic acid after storage. Moreover, when using two-dimensional correlation infrared spectroscopy (2DCOS-IR) to track changes of BPO in wheat flour (0.05 mg/g) within one week, intensities of auto-peaks at 1781 cm(-1) and 669 cm(-1) which belonged to BPO and benzoic acid, respectively, were changing inversely, indicating that BPO was decomposed into benzoic acid. Moreover, another autopeak at 1767 cm(-1) which does not belong to benzoic acid was also rising simultaneously. By heating perturbation treatment of BPO in wheat flour based on 2DCOS-IR and spectral subtraction analysis, it was found that BPO in wheat flour not only decomposed into benzoic acid and benzoate, but also produced other deleterious substances, e.g., benzene. This study offers a promising method with minimum pretreatment and time-saving to identify BPO in wheat flour and its chemical products during storage in a holistic manner.
Radulovic, Vladimir; Barbot, Loic; Fourmentel, Damien; Villard, Jean-Francois; Snoj, Luka; Zerovnik, Gasper; Trkov, Andrej
2015-07-01
Significant efforts have been made over the last few years in the French Alternative Energies and Atomic Energy Commission (CEA) to adopt multi-step Monte Carlo calculation schemes in the investigation and interpretation of the response of nuclear reactor instrumentation detectors (e.g. miniature ionization chambers - MICs and self-powered neutron or gamma detectors - SPNDs and SPGDs). The first step consists of the calculation of the primary data, i.e. evaluation of the neutron and gamma flux levels and spectra in the environment where the detector is located, using a computational model of the complete nuclear reactor core and its surroundings. These data are subsequently used to define sources for the following calculation steps, in which only a model of the detector under investigation is used. This approach enables calculations with satisfactory statistical uncertainties (of the order of a few %) within regions which are very small in size (the typical volume of which is of the order of 1 mm{sup 3}). The main drawback of a calculation scheme as described above is that perturbation effects on the radiation conditions caused by the detectors themselves are not taken into account. Depending on the detector, the nuclear reactor and the irradiation position, the perturbation in the neutron flux as primary data may reach 10 to 20%. A further issue is whether the model used in the second step calculations yields physically representative results. This is generally not the case, as significant deviations may arise, depending on the source definition. In particular, as presented in the paper, the injudicious use of special options aimed at increasing the computation efficiency (e.g. reflective boundary conditions) may introduce unphysical bias in the calculated flux levels and distortions in the spectral shapes. This paper presents examples of the issues described above related to a case study on the interpretation of the signal from different types of SPNDs, which
Foerster, Rebecca M.; Carbone, Elena; Schneider, Werner X.
2014-01-01
Evidence for long-term memory (LTM)-based control of attention has been found during the execution of highly practiced multi-step tasks. However, does LTM directly control for attention or are working memory (WM) processes involved? In the present study, this question was investigated with a dual-task paradigm. Participants executed either a highly practiced visuospatial sensorimotor task (speed stacking) or a verbal task (high-speed poem reciting), while maintaining visuospatial or verbal information in WM. Results revealed unidirectional and domain-specific interference. Neither speed stacking nor high-speed poem reciting was influenced by WM retention. Stacking disrupted the retention of visuospatial locations, but did not modify memory performance of verbal material (letters). Reciting reduced the retention of verbal material substantially whereas it affected the memory performance of visuospatial locations to a smaller degree. We suggest that the selection of task-relevant information from LTM for the execution of overlearned multi-step tasks recruits domain-specific WM. PMID:24847304
Foerster, Rebecca M; Carbone, Elena; Schneider, Werner X
2014-01-01
Evidence for long-term memory (LTM)-based control of attention has been found during the execution of highly practiced multi-step tasks. However, does LTM directly control for attention or are working memory (WM) processes involved? In the present study, this question was investigated with a dual-task paradigm. Participants executed either a highly practiced visuospatial sensorimotor task (speed stacking) or a verbal task (high-speed poem reciting), while maintaining visuospatial or verbal information in WM. Results revealed unidirectional and domain-specific interference. Neither speed stacking nor high-speed poem reciting was influenced by WM retention. Stacking disrupted the retention of visuospatial locations, but did not modify memory performance of verbal material (letters). Reciting reduced the retention of verbal material substantially whereas it affected the memory performance of visuospatial locations to a smaller degree. We suggest that the selection of task-relevant information from LTM for the execution of overlearned multi-step tasks recruits domain-specific WM.
Eon-duval, Alex; Valax, Pascal; Solacroup, Thomas; Broly, Hervé; Gleixner, Ralf; Strat, Claire L E; Sutter, James
2012-10-01
The article describes how Quality by Design principles can be applied to the drug substance manufacturing process of an Fc fusion protein. First, the quality attributes of the product were evaluated for their potential impact on safety and efficacy using risk management tools. Similarly, process parameters that have a potential impact on critical quality attributes (CQAs) were also identified through a risk assessment. Critical process parameters were then evaluated for their impact on CQAs, individually and in interaction with each other, using multivariate design of experiment techniques during the process characterisation phase. The global multi-step Design Space, defining operational limits for the entire drug substance manufacturing process so as to ensure that the drug substance quality targets are met, was devised using predictive statistical models developed during the characterisation study. The validity of the global multi-step Design Space was then confirmed by performing the entire process, from cell bank thawing to final drug substance, at its limits during the robustness study: the quality of the final drug substance produced under different conditions was verified against predefined targets. An adaptive strategy was devised whereby the Design Space can be adjusted to the quality of the input material to ensure reliable drug substance quality. Finally, all the data obtained during the process described above, together with data generated during additional validation studies as well as manufacturing data, were used to define the control strategy for the drug substance manufacturing process using a risk assessment methodology.
A Bi-objective Model Inspired Greedy Algorithm for Test Suite Minimization
NASA Astrophysics Data System (ADS)
Parsa, Saeed; Khalilian, Alireza
Regression testing is a critical activity which occurs during the maintenance stage of the software lifecycle. However, it requires large amounts of test cases to assure the attainment of a certain degree of quality. As a result, test suite sizes may grow significantly. To address this issue, Test Suite Reduction techniques have been proposed. However, suite size reduction may lead to significant loss of fault detection efficacy. To deal with this problem, a greedy algorithm is presented in this paper. This algorithm attempts to select a test case which satisfies the maximum number of testing requirements while having minimum overlap in requirements coverage with other test cases. In order to evaluate the proposed algorithm, experiments have been conducted on the Siemens suite and the Space program. The results demonstrate the effectiveness of the proposed algorithm by retaining the fault detection capability of the suites while achieving significant suite size reduction.
Price, Jeffery R; Aykac, Deniz; Hunn, John D; Kercher, Andrew K
2007-01-01
We describe new image analysis developments in support of the U.S. Department of Energy's (DOE) Advanced Gas Reactor (AGR) Fuel Development and Qualification Program. We previously reported a non-iterative, Bayesian approach for locating the boundaries of different particle layers in cross-sectional imagery. That method, however, had to be initialized by manual preprocessing where a user must select two points in each image, one indicating the particle center and the other indicating the first layer interface. Here, we describe a technique designed to eliminate the manual preprocessing and provide full automation. With a low resolution image, we use 'EdgeFlow' to approximate the layer boundaries with circular templates. Multiple snakes are initialized to these circles and deformed using a greedy Bayesian strategy that incorporates coupling terms as well as a priori information on the layer thicknesses and relative contrast. We show results indicating the effectiveness of the proposed method.
Greedy Set Cover Field Selection for Multi-object Spectroscopy in C++ MPI
NASA Astrophysics Data System (ADS)
Stenborg, T. N.
2015-09-01
Multi-object spectrographs allow efficient observation of clustered targets. Observational programs of many targets not encompassed within a telescope's field of view, however, require multiple pointings. Here, a greedy set cover algorithmic approach to efficient field selection in such a scenario is examined. The goal of this approach is not to minimize the total number of pointings needed to cover a given target set, but rather maximize the observational return for a restricted number of pointings. Telescope field of view and maximum targets per field are input parameters, allowing algorithm application to observation planning for the current range of active multi-object spectrographs (e.g. the 2dF/AAOmega, Fiber Large Array Multi Element Spectrograph, Fiber Multi-Object Spectrograph, Hectochelle, Hectospec and Hydra systems), and for any future systems. A parallel version of the algorithm is implemented with the message passing interface, facilitating execution on both shared and distributed memory systems.
2011-01-01
Background Position-specific priors (PSP) have been used with success to boost EM and Gibbs sampler-based motif discovery algorithms. PSP information has been computed from different sources, including orthologous conservation, DNA duplex stability, and nucleosome positioning. The use of prior information has not yet been used in the context of combinatorial algorithms. Moreover, priors have been used only independently, and the gain of combining priors from different sources has not yet been studied. Results We extend RISOTTO, a combinatorial algorithm for motif discovery, by post-processing its output with a greedy procedure that uses prior information. PSP's from different sources are combined into a scoring criterion that guides the greedy search procedure. The resulting method, called GRISOTTO, was evaluated over 156 yeast TF ChIP-chip sequence-sets commonly used to benchmark prior-based motif discovery algorithms. Results show that GRISOTTO is at least as accurate as other twelve state-of-the-art approaches for the same task, even without combining priors. Furthermore, by considering combined priors, GRISOTTO is considerably more accurate than the state-of-the-art approaches for the same task. We also show that PSP's improve GRISOTTO ability to retrieve motifs from mouse ChiP-seq data, indicating that the proposed algorithm can be applied to data from a different technology and for a higher eukaryote. Conclusions The conclusions of this work are twofold. First, post-processing the output of combinatorial algorithms by incorporating prior information leads to a very efficient and effective motif discovery method. Second, combining priors from different sources is even more beneficial than considering them separately. PMID:21513505
Zhang, Wenle; Liu, Jianchang; Wang, Honghai
2015-09-01
This paper deals with the ultra-fast formation control problem of high-order discrete-time multi-agent systems. Using the local neighbor-error knowledge, a novel ultra-fast protocol with multi-step predictive information and self-feedback term is proposed. The asymptotic convergence factor is improved by a power of q+1 compared to the routine protocol. To some extent, the ultra-fast algorithm overcomes the influence of communication topology to the convergence speed. Furthermore, some sufficient conditions are given herein. The ones decouple the design of the synchronizing gains from the detailed graph properties, and explicitly reveal how the agent dynamic and the communication graph jointly affect the ultra-fast formationability. Finally, some simulations are worked out to illustrate the effectiveness of our theoretical results.
Zhao, Huiying; Xu, Jin; Ghebrezadik, Helen; Hylands, Peter J
2015-10-10
Ginseng, mainly Asian ginseng and American ginseng, is the most widely consumed herbal product in the world . However, the existing quality control method is not adequate: adulteration is often seen in the market. In this study, 31 batches of ginseng from Chinese stores were analyzed using (1)H NMR metabolite profiles together with multi-step principal component analysis. The most abundant metabolites, sugars, were excluded from the NMR spectra after the first principal component analysis, in order to reveal differences contributed by less abundant metabolites. For the first time, robust, distinctive and representative differences of Asian ginseng from American ginseng were found and the key metabolites responsible were identified as sucrose, glucose, arginine, choline, and 2-oxoglutarate and malate. Differences between wild and cultivated ginseng were identified as ginsenosides. A substitute cultivated American ginseng was noticed. These results demonstrated that the combination of (1)H NMR and PCA is effective in quality control of ginseng.
Greedy data transportation scheme with hard packet deadlines for wireless ad hoc networks.
Lee, HyungJune
2014-01-01
We present a greedy data transportation scheme with hard packet deadlines in ad hoc sensor networks of stationary nodes and multiple mobile nodes with scheduled trajectory path and arrival time. In the proposed routing strategy, each stationary ad hoc node en route decides whether to relay a shortest-path stationary node toward destination or a passing-by mobile node that will carry closer to destination. We aim to utilize mobile nodes to minimize the total routing cost as far as the selected route can satisfy the end-to-end packet deadline. We evaluate our proposed routing algorithm in terms of routing cost, packet delivery ratio, packet delivery time, and usability of mobile nodes based on network level simulations. Simulation results show that our proposed algorithm fully exploits the remaining time till packet deadline to turn into networking benefits of reducing the overall routing cost and improving packet delivery performance. Also, we demonstrate that the routing scheme guarantees packet delivery with hard deadlines, contributing to QoS improvement in various network services.
A dedicated greedy pursuit algorithm for sparse spectral representation of music sound.
Rebollo-Neira, Laura; Aggarwal, Gagan
2016-10-01
A dedicated algorithm for sparse spectral representation of music sound is presented. The goal is to enable the representation of a piece of music signal as a linear superposition of as few spectral components as possible, without affecting the quality of the reproduction. A representation of this nature is said to be sparse. In the present context sparsity is accomplished by greedy selection of the spectral components, from an overcomplete set called a dictionary. The proposed algorithm is tailored to be applied with trigonometric dictionaries. Its distinctive feature being that it avoids the need for the actual construction of the whole dictionary, by implementing the required operations via the fast Fourier transform. The achieved sparsity is theoretically equivalent to that rendered by the orthogonal matching pursuit (OMP) method. The contribution of the proposed dedicated implementation is to extend the applicability of the standard OMP algorithm, by reducing its storage and computational demands. The suitability of the approach for producing sparse spectral representation is illustrated by comparison with the traditional method, in the line of the short time Fourier transform, involving only the corresponding orthonormal trigonometric basis.
A dedicated greedy pursuit algorithm for sparse spectral representation of music sound
NASA Astrophysics Data System (ADS)
Rebollo-Neira, Laura; Aggarwal, Gagan
2016-10-01
A dedicated algorithm for sparse spectral representation of music sound is presented. The goal is to enable the representation of a piece of music signal, as a linear superposition of as few spectral components as possible. A representation of this nature is said to be sparse. In the present context sparsity is accomplished by greedy selection of the spectral components, from an overcomplete set called a dictionary. The proposed algorithm is tailored to be applied with trigonometric dictionaries. Its distinctive feature being that it avoids the need for the actual construction of the whole dictionary, by implementing the required operations via the Fast Fourier Transform. The achieved sparsity is theoretically equivalent to that rendered by the Orthogonal Matching Pursuit method. The contribution of the proposed dedicated implementation is to extend the applicability of the standard Orthogonal Matching Pursuit algorithm, by reducing its storage and computational demands. The suitability of the approach for producing sparse spectral models is illustrated by comparison with the traditional method, in the line of the Short Time Fourier Transform, involving only the corresponding orthonormal trigonometric basis.
Perez-Lloret, Santiago; Videla, Alejandro J.; Richaudeau, Alba; Vigo, Daniel; Rossi, Malco; Cardinali, Daniel P.; Perez-Chada, Daniel
2013-01-01
Background: A multi-step causality pathway connecting short sleep duration to daytime somnolence and sleepiness leading to reduced attention and poor academic performance as the final result can be envisaged. However this hypothesis has never been explored. Objective: To explore consecutive correlations between sleep duration, daytime somnolence, attention levels, and academic performance in a sample of school-aged teenagers. Methods: We carried out a survey assessing sleep duration and daytime somnolence using the Pediatric Daytime Sleepiness Scale (PDSS). Sleep duration variables included week-days' total sleep time, usual bedtimes, and absolute weekdayto-weekend sleep time difference. Attention was assessed by d2 test and by the coding subtest from the WISC-IV scale. Academic performance was obtained from literature and math grades. Structural equation modeling was used to assess the independent relationships between these variables, while controlling for confounding effects of other variables, in one single model. Standardized regression weights (SWR) for relationships between these variables are reported. Results: Study sample included 1,194 teenagers (mean age: 15 years; range: 13-17 y). Sleep duration was inversely associated with daytime somnolence (SWR = -0.36, p < 0.01) while sleepiness was negatively associated with attention (SWR = -0.13, p < 0.01). Attention scores correlated positively with academic results (SWR = 0.18, p < 0.01). Daytime somnolence correlated negatively with academic achievements (SWR = -0.16, p < 0.01). The model offered an acceptable fit according to usual measures (RMSEA = 0.0548, CFI = 0.874, NFI = 0.838). A Sobel test confirmed that short sleep duration influenced attention through daytime somnolence (p < 0.02), which in turn influenced academic achievements through reduced attention (p < 0.002). Conclusions: Poor academic achievements correlated with reduced attention, which in turn was related to daytime somnolence. Somnolence
Flores, Glenn
2002-01-01
Cinematic depictions of physicians potentially can affect public expectations and the patient-physician relationship, but little attention has been devoted to portrayals of physicians in movies. The objective of the study was the analysis of cinematic depictions of physicians to determine common demographic attributes of movie physicians, major themes, and whether portrayals have changed over time. All movies released on videotape with physicians as main characters and readily available to the public were viewed in their entirety. Data were collected on physician characteristics, diagnoses, and medical accuracy, and dialogue concerning physicians was transcribed. The results showed that in the 131 films, movie physicians were significantly more likely to be male (p < 0.00001), White (p < 0.00001), and < 40 years of age (p < 0.009). The proportion of women and minority film physicians has declined steadily in recent decades. Movie physicians are most commonly surgeons (33%), psychiatrists (26%), and family practitioners (18%). Physicians were portrayed negatively in 44% of movies, and since the 1960s positive portrayals declined while negative portrayals increased. Physicians frequently are depicted as greedy, egotistical, uncaring, and unethical, especially in recent films. Medical inaccuracies occurred in 27% of films. Compassion and idealism were common in early physician movies but are increasingly scarce in recent decades. A recurrent theme is the "mad scientist," the physician-researcher that values research more than patients' welfare. Portrayals of physicians as egotistical and materialistic have increased, whereas sexism and racism have waned. Movies from the past two decades have explored critical issues surrounding medical ethics and managed care. We conclude that negative cinematic portrayals of physicians are on the rise, which may adversely affect patient expectations and the patient-physician relationship. Nevertheless, films about physicians can
Magmatically Greedy Reararc Volcanoes of the N. Tofua Segment of the Tonga Arc
NASA Astrophysics Data System (ADS)
Rubin, K. H.; Embley, R. W.; Arculus, R. J.; Lupton, J. E.
2013-12-01
Volcanism along the northernmost Tofua Arc is enigmatic because edifices of the arc's volcanic front are mostly, magmatically relatively anemic, despite the very high convergence rate of the Pacific Plate with this section of Tonga Arc. However, just westward of the arc front, in terrain generally thought of as part of the adjacent NE Lau Backarc Basin, lie a series of very active volcanoes and volcanic features, including the large submarine caldera Niuatahi (aka volcano 'O'), a large composite dacite lava flow terrain not obviously associated with any particular volcanic edifice, and the Mata volcano group, a series of 9 small elongate volcanoes in an extensional basin at the extreme NE corner of the Lau Basin. These three volcanic terrains do not sit on arc-perpendicular cross chains. Collectively, these volcanic features appear to be receiving a large proportion of the magma flux from the sub-Tonga/Lau mantle wedge, in effect 'stealing' this magma flux from the arc front. A second occurrence of such magma 'capture' from the arc front occurs in an area just to the south, on southernmost portion of the Fonualei Spreading Center. Erupted compositions at these 'magmatically greedy' volcanoes are consistent with high slab-derived fluid input into the wedge (particularly trace element abundances and volatile contents, e.g., see Lupton abstract this session). It is unclear how long-lived a feature this is, but the very presence of such hyperactive and areally-dispersed volcanism behind the arc front implies these volcanoes are not in fact part of any focused spreading/rifting in the Lau Backarc Basin, and should be thought of as 'reararc volcanoes'. Possible tectonic factors contributing to this unusually productive reararc environment are the high rate of convergence, the cold slab, the highly disorganized extension in the adjacent backarc, and the tear in the subducting plate just north of the Tofua Arc.
Massie, I; Selden, C; Morris, J; Hodgson, H; Fuller, B
2011-01-01
Acute liver failure has high mortality with unpredictable onset. A bioartificial liver, comprising alginate-encapsulated HepG2 spheroids, could temporarily replace liver function but must be cryopreservable. For clinical use, contamination risks from liquid coolants for cryopreservation and storage should be minimized. A cryogen-free cooler was compared to nitrogen vapour-controlled cryopreservation of alginate-encapsulated liver cell spheroids (AELS). AELS were cooled using a multi-step, slow-cooling profile in 12 percent v/v Me2SO Celsior and stored in liquid nitrogen; temperatures were recorded throughout, and the AELS were assayed at 24, 48 and 72 hours post-warming and results compared to unfrozen control values. Viability was assessed by fluorescent staining and quantified using image analysis; cell numbers were quantified using nuclear counts, and cell function using albumin synthesis. The cryogen-free cooler performed the cooling profile as desired, apart from one step requiring a rapid cool ramp. Viability, cell numbers and function were similarly decreased in both cryopreserved groups to about 90 percent, 70 percent and 65 percent of the controls respectively. This technology offers a clinic alternative to liquid nitrogen-coolant cryopreservation.
NASA Astrophysics Data System (ADS)
Xu, Rong; Sun, Suqin; Zhu, Weicheng; Xu, Changhua; Liu, Yougang; Shen, Liang; Shi, Yue; Chen, Jun
2014-07-01
The genus Cistanche generally has four species in China, including C. deserticola (CD), C. tubulosa (CT), C. salsa (CS) and C. sinensis (CSN), among which CD and CT are official herbal sources of Cistanche Herba (CH). To clarify the sources of CH and ensure the clinical efficacy and safety, a multi-step IR macro-fingerprint method was developed to analyze and evaluate the ethanol extracts of the four species. Through this method, the four species were distinctively distinguished, and the main active components phenylethanoid glycosides (PhGs) were estimated rapidly according to the fingerprint features in the original IR spectra, second derivative spectra, correlation coefficients and 2D-IR correlation spectra. The exclusive IR fingerprints in the spectra including the positions, shapes and numbers of peaks indicated that constitutes of CD were the most abundant, and CT had the highest level of PhGs. The results deduced by some macroscopic features in IR fingerprint were in agreement with the HPLC fingerprint of PhGs from the four species, but it should be noted that the IR provided more chemical information than HPLC. In conclusion, with the advantages of high resolution, cost effective and speediness, the macroscopic IR fingerprint method should be a promising analytical technique for discriminating extremely similar herbal medicine, monitoring and tracing the constituents of different extracts and even for quality control of the complex systems such as TCM.
Macías, Francisco; Caraballo, Manuel A; Rötting, Tobias S; Pérez-López, Rafael; Nieto, José Miguel; Ayora, Carlos
2012-09-01
Complete metal removal from highly-polluted acid mine drainage was attained by the use of a pilot multi-step passive remediation system. The remediation strategy employed can conceptually be subdivided into a first section where the complete trivalent metal removal was achieved by the employment of a previously tested limestone-based passive remediation technology followed by the use of a novel reactive substrate (caustic magnesia powder dispersed in a wood shavings matrix) obtaining a total divalent metal precipitation. This MgO-step was capable to abate high concentrations of Zn together with Mn, Cd, Co and Ni below the recommended limits for drinking waters. A reactive transport model anticipates that 1 m(3) of MgO-DAS (1 m thick × 1 m(2) section) would be able to treat a flow of 0.5 L/min of a highly acidic water (total acidity of 788 mg/L CaCO(3)) for more than 3 years.
NASA Astrophysics Data System (ADS)
Hatta, Kohei; Nakajima, Yohei; Isoda, Erika; Itoh, Mariko; Yamamoto, Tamami
The brain is one of the most complicated structures in nature. Zebrafish is a useful model to study development of vertebrate brain, because it is transparent at early embryonic stage and it develops rapidly outside of the body. We made a series of transgenic zebrafish expressing green-fluorescent protein related molecules, for example, Kaede and KikGR, whose green fluorescence can be irreversibly converted to red upon irradiation with ultra-violet (UV) or violet light, and Dronpa, whose green fluorescence is eliminated with strong blue light but can be reactivated upon irradiation with UV or violet-light. We have recently shown that infrared laser evoked gene operator (IR-LEGO) which causes a focused heat shock could locally induce these fluorescent proteins and the other genes. Neural cell migration and axonal pattern formation in living brain could be visualized by this technique. We also can express channel rhodopsine 2 (ChR2), a photoactivatable cation channel, or Natronomonas pharaonis halorhodopsin (NpHR), a photoactivatable chloride ion pump, locally in the nervous system by IR. Then, behaviors of these animals can be controlled by activating or silencing the local neurons by light. This novel strategy is useful in discovering neurons and circuits responsible for a wide variety of animal behaviors. We proposed to call this method ‘multi-stepped optogenetics’.
Kim, Jeong-Rae; Cho, Kwang-Hyun
2006-12-01
E. coli has two-component systems composed of histidine kinase proteins and response regulator proteins. For a given extracellular stimulus, a histidine kinase senses the stimulus, autophosphorylates and then passes the phosphates to the cognate response regulators. The histidine kinase in an orthodox two-component system has only one histidine domain where the autophosphorylation occurs, but a histidine kinase in some unusual two-component systems (unorthodox two-component systems) has two histidine domains and one aspartate domain. So, the unorthodox two-component systems have more complex phosphorelay mechanisms than orthodox two-component systems. In general, the two-component systems are required to promptly respond to external stimuli for survival of E. coli. In this respect, the complex multi-step phosphorelay mechanism seems to be disadvantageous, but there are several unorthodox two-component systems in E. coli. In this paper, we investigate the reason why such unorthodox two-component systems are present in E. coli. For this purpose, we have developed simplified mathematical models of both orthodox and unorthodox two-component systems and analyzed their dynamical characteristics through extensive computer simulations. We have finally revealed that the unorthodox two-component systems realize ultrasensitive responses to external stimuli and also more robust responses to noises than the orthodox two-component systems.
NASA Astrophysics Data System (ADS)
Zeb Gul, Jahan; Yang, Bong-Su; Yang, Young Jin; Chang, Dong Eui; Choi, Kyung Hyun
2016-11-01
Soft bots have the expedient ability of adopting intricate postures and fitting in complex shapes compared to mechanical robots. This paper presents a unique in situ UV curing three-dimensional (3D) printed multi-material tri-legged soft bot with spider mimicked multi-step dynamic forward gait using commercial bio metal filament (BMF) as an actuator. The printed soft bot can produce controllable forward motion in response to external signals. The fundamental properties of BMF, including output force, contractions at different frequencies, initial loading rate, and displacement-rate are verified. The tri-pedal soft bot CAD model is designed inspired by spider’s legged structure and its locomotion is assessed by simulating strain and displacement using finite element analysis. A customized rotational multi-head 3D printing system assisted with multiple wavelength’s curing lasers is used for in situ fabrication of tri-pedal soft-bot using two flexible materials (epoxy and polyurethane) in three layered steps. The size of tri-pedal soft-bot is 80 mm in diameter and each pedal’s width and depth is 5 mm × 5 mm respectively. The maximum forward speed achieved is 2.7 mm s-1 @ 5 Hz with input voltage of 3 V and 250 mA on a smooth surface. The fabricated tri-pedal soft bot proved its power efficiency and controllable locomotion at three input signal frequencies (1, 2, 5 Hz).
Sambe, Haruyo; Hoshina, Kaori; Haginaka, Jun
2007-06-08
Uniformly-sized, molecularly imprinted polymers (MIPs) for atrazine, ametryn and irgarol were prepared by a multi-step swelling and polymerization method using ethylene glycol dimethacrylate as a cross-linker and methacrylic acid (MAA), 2-(trifluoromethyl) acrylic acid (TFMAA) or 4-vinylpyridine either as a functional monomer or not. The MIP for atrazine prepared using MAA showed good molecular recognition abilities for chlorotriazine herbicides, while the MIPs for ametryn and irgarol prepared using TFMAA showed excellent molecular recognition abilities for methylthiotriazine herbicides. A restricted access media-molecularly imprinted polymer (RAM-MIP) for irgarol was prepared followed by in situ hydrophilic surface modification using glycerol dimethacrylate and glycerol monomethacrylate as hydrophilic monomers. The RAM-MIP was applied to selective pretreatment and enrichment of methylthiotriazine herbicides, simetryn, ametryn and prometryn, in river water, followed by their separation and UV detection via column-switching HPLC. The calibration graphs of these compounds showed good linearity in the range of 50-500 pg/mL (r > 0.999) with a 100 mL loading of a river water sample. The quantitation limits of simetryn, ametryn and prometryn were 50 pg/mL, and the detection limits were 25 pg/mL. The recoveries of simetryn, ametryn and prometryn at 50 pg/mL were 101%, 95.6% and 95.1%, respectively. This method was successfully applied for the simultaneous determination of simetryn, ametryn and prometryn in river water.
Xiong, Hanzhen; Li, Qiulian; Chen, Ruichao; Liu, Shaoyan; Lin, Qiongyan; Xiong, Zhongtang; Jiang, Qingping; Guo, Linlang
2016-01-01
We aimed to identify endometrioid endometrial carcinoma (EEC)-related gene signatures using a multi-step miRNA-mRNA regulatory network construction approach. Pathway analysis showed that 61 genes were enriched on many carcinoma-related pathways. Among the 14 highest scoring gene signatures, six genes had been previously shown to be endometrial carcinoma. By qRT-PCR and next generation sequencing, we found that a gene signature (CPEB1) was significantly down-regulated in EEC tissues, which may be caused by hsa-miR-183-5p up-regulation. In addition, our literature surveys suggested that CPEB1 may play an important role in EEC pathogenesis by regulating the EMT/p53 pathway. The miRNA-mRNA network is worthy of further investigation with respect to the regulatory mechanisms of miRNAs in EEC. CPEB1 appeared to be a tumor suppressor in EEC. Our results provided valuable guidance for the functional study at the cellular level, as well as the EEC mouse models. PMID:27271671
NASA Astrophysics Data System (ADS)
Prados, A. I.; Gupta, P.; Mehta, A. V.; Schmidt, C.; Blevins, B.; Carleton-Hug, A.; Barbato, D.
2014-12-01
NASA's Applied Remote Sensing Training Program (ARSET), http://arset.gsfc.nasa.gov, within NASA's Applied Sciences Program, has been providing applied remote sensing training since 2008. The goals of the program are to develop the technical and analytical skills necessary to utilize NASA resources for decision-support, and to help end-users navigate through the vast data resources freely available. We discuss our multi-step approach to improving data access and use of NASA satellite and model data for air quality, water resources, disaster, and land management. The program has reached over 1600 participants world wide using a combined online and interactive approach. We will discuss lessons learned as well as best practices and success stories in improving the use of NASA Earth Science resources archived at multiple data centers by end-users in the private and public sectors. ARSET's program evaluation method for improving the program and assessing the benefits of trainings to U.S and international organizations will also be described.
Marquette, Ian; Quesne, Christiane
2014-11-15
Type III multi-step rationally extended harmonic oscillator and radial harmonic oscillator potentials, characterized by a set of k integers m{sub 1}, m{sub 2}, ⋯, m{sub k}, such that m{sub 1} < m{sub 2} < ⋯ < m{sub k} with m{sub i} even (resp. odd) for i odd (resp. even), are considered. The state-adding and state-deleting approaches to these potentials in a supersymmetric quantum mechanical framework are combined to construct new ladder operators. The eigenstates of the Hamiltonians are shown to separate into m{sub k} + 1 infinite-dimensional unitary irreducible representations of the corresponding polynomial Heisenberg algebras. These ladder operators are then used to build a higher-order integral of motion for seven new infinite families of superintegrable two-dimensional systems separable in cartesian coordinates. The finite-dimensional unitary irreducible representations of the polynomial algebras of such systems are directly determined from the ladder operator action on the constituent one-dimensional Hamiltonian eigenstates and provide an algebraic derivation of the superintegrable systems whole spectrum including the level total degeneracies.
Abdelwahab, Siddig Ibarhim; El-Setohy, Maged; Alsharqi, Abdalla; Elsanosy, Rashad; Mohammed, Umar Yagoub
2016-01-01
Smoking is accountable for the fatality of a substantial number of persons and increases the likelihood of cancer and cardiovascular diseases. Although data have shown high prevalence rates of cigarette smoking in Saudi Arabia, relatively little is known about the broader scope. The objectives of this study were to investigate socio-demographic factors, patterns of use and cessation behavior associated with smoking in Saudi Arabia (KSA). The study utilized a cross-sectional, multi-step design of sampling. Residents (N=1,497; aged 15 years and older) were recruited from seven administrative areas in Southwest Saudi Arabia. A pretested questionnaire was utilized to obtain data on participant cigarette smoking, including their daily use, age, education, income, marital status and employment status. The current study is the first of its kind to gather data cessation behavior of Saudi subjects. With the exception of 1.5% females, all the respondents were male. The majority of the respondents were married, had a university level of education, were employed, and were younger than 34 years old. The same trends were also observed among smokers' samples. The current prevalence of cigarette smoking was 49.2% and 65.7% of smokers had smoking at less than 18 years of age. The mean daily use amongst smokers was 7.98 cigarettes (SD=4.587). More than 50% of the study sample had tried at least once to quit smoking. However, 42% of the smokers participating had never. On the other hand, about 25% of the respondents were willing to consider quitting smoking in the future. Modeling of cigarette smoking suggested that the most significant independent predictors of smoking behavior were geographic area, gender, marital status, education, job and age. Considerable variation in smoking prevalence was noted related with participant sociodemographics. Findings recommend the necessity for control and intervention programs in Saudi community.
Cheal, Sarah M.; Yoo, Barney; Boughdad, Sarah; Punzalan, Blesida; Yang, Guangbin; Dilhas, Anna; Torchon, Geralda; Pu, Jun; Axworthy, Don B.; Zanzonico, Pat; Ouerfelli, Ouathek; Larson, Steven M.
2014-01-01
A series of N-acetylgalactosamine-dendrons (NAG-dendrons) and dextrans bearing biotin moieties were compared for their ability to complex with and sequester circulating bispecific anti-tumor antibody (scFv4) streptavidin (SA) fusion protein (scFv4-SA) in vivo, to improve tumor to normal tissue concentration ratios for targeted radioimmunotherapy and diagnosis. Specifically, a total of five NAG-dendrons employing a common synthetic scaffold structure containing 4, 8, 16, or 32 carbohydrate residues and a single biotin moiety were prepared (NAGB), and for comparative purposes, a biotinylated-dextran with average molecular weight (MW) of 500 kD was synthesized from amino-dextran (DEXB). One of the NAGB compounds, CA16, has been investigated in humans; our aim was to determine if other NAGB analogs (e.g. CA8 or CA4) were bioequivalent to CA16 and/or better suited as MST reagents. In vivo studies included dynamic positron-emission tomography (PET) imaging of 124I-labelled-scFv4-SA clearance and dual-label biodistribution studies following multi-step targeting (MST) directed at subcutaneous (s.c.) human colon adenocarcinoma xenografts in mice. The MST protocol consists of three injections: first, a bispecific antibody specific for an anti-tumor associated glycoprotein (TAG-72) single chain genetically-fused with SA (scFv4-SA); second, CA16 or other clearing agent; and third, radiolabeled biotin. We observed using PET imaging of 124I-labelled-scFv4-SA clearance that the spatial arrangement of ligands conjugated to NAG (i.e. biotin) can impact the binding to antibody in circulation and subsequent liver uptake of the NAG-antibody complex. Also, NAGB CA32-LC or CA16-LC can be utilized during MST to achieve comparable tumor- to-blood ratios and absolute tumor uptake seen previously with CA16. Finally, DEXB was equally effective as NAGB CA32-LC at lowering scFv4-SA in circulation, but at the expense of reducing absolute tumor uptake of radiolabeled biotin. PMID:24219178
Carver, Charles S.; Scheier, Michael F.; Segerstrom, Suzanne C.
2010-01-01
Optimism is an individual difference variable that reflects the extent to which people hold generalized favorable expectancies for their future. Higher levels of optimism have been related prospectively to better subjective well-being in times of adversity or difficulty (i.e., controlling for previous well-being). Consistent with such findings, optimism has been linked to higher levels of engagement coping and lower levels of avoidance, or disengagement, coping. There is evidence that optimism is associated with taking proactive steps to protect one's health, whereas pessimism is associated with health-damaging behaviors. Consistent with such findings, optimism is also related to indicators of better physical health. The energetic, task-focused approach that optimists take to goals also relates to benefits in the socioeconomic world. Some evidence suggests that optimism relates to more persistence in educational efforts and to higher later income. Optimists also appear to fare better than pessimists in relationships. Although there are instances in which optimism fails to convey an advantage, and instances in which it may convey a disadvantage, those instances are relatively rare. In sum, the behavioral patterns of optimists appear to provide models of living for others to learn from. PMID:20170998
NASA Astrophysics Data System (ADS)
Deng, Guanlong; Gu, Xingsheng
2014-03-01
This article presents an enhanced iterated greedy (EIG) algorithm that searches both insert and swap neighbourhoods for the single-machine total weighted tardiness problem with sequence-dependent setup times. Novel elimination rules and speed-ups are proposed for the swap move to make the employment of swap neighbourhood worthwhile due to its reduced computational expense. Moreover, a perturbation operator is newly designed as a substitute for the existing destruction and construction procedures to prevent the search from being attracted to local optima. To validate the proposed algorithm, computational experiments are conducted on a benchmark set from the literature. The results show that the EIG outperforms the existing state-of-the-art algorithms for the considered problem.
Zhu, Chuan; Zhang, Sai; Han, Guangjie; Jiang, Jinfang; Rodrigues, Joel J. P. C.
2016-01-01
Mobile sink is widely used for data collection in wireless sensor networks. It can avoid ‘hot spot’ problems but energy consumption caused by multihop transmission is still inefficient in real-time application scenarios. In this paper, a greedy scanning data collection strategy (GSDCS) is proposed, and we focus on how to reduce routing energy consumption by shortening total length of routing paths. We propose that the mobile sink adjusts its trajectory dynamically according to the changes of network, instead of predetermined trajectory or random walk. Next, the mobile sink determines which area has more source nodes, then it moves toward this area. The benefit of GSDCS is that most source nodes are no longer needed to upload sensory data for long distances. Especially in event-driven application scenarios, when event area changes, the mobile sink could arrive at the new event area where most source nodes are located currently. Hence energy can be saved. Analytical and simulation results show that compared with existing work, our GSDCS has a better performance in specific application scenarios. PMID:27608022
Li, Cong; Li, Hui; Sun, Jin; Zhang, XinYue; Shi, Jinsong; Xu, Zhenghong
2016-08-01
Hydroxylation of dehydroepiandrosterone (DHEA) to 3β,7α,15α-trihydroxy-5-androstene-17-one (7α,15α-diOH-DHEA) by Colletotrichum lini ST-1 is an essential step in the synthesis of many steroidal drugs, while low DHEA concentration and 7α,15α-diOH-DHEA production are tough problems to be solved urgently in industry. In this study, the significant improvement of 7α,15α-diOH-DHEA yield in 5-L stirred fermenter with 15 g/L DHEA was achieved. To maintain a sufficient quantity of glucose for the bioconversion, glucose of 15 g/L was fed at 18 h, the 7α,15α-diOH-DHEA yield and dry cell weight were increased by 17.7 and 30.9 %, respectively. Moreover, multi-step DHEA addition strategy was established to diminish DHEA toxicity to C. lini, and the 7α,15α-diOH-DHEA yield raised to 53.0 %. Further, a novel strategy integrating glucose-feeding with multi-step addition of DHEA was carried out and the product yield increased to 66.6 %, which was the highest reported 7α,15α-diOH-DHEA production in 5-L stirred fermenter. Meanwhile, the conversion course was shortened to 44 h. This strategy would provide a possible way in enhancing the 7α,15α-diOH-DHEA yield in pharmaceutical industry.
Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming
2016-01-01
Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle’s position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption. PMID:27428971
Combinatorial optimization methods for disassembly line balancing
NASA Astrophysics Data System (ADS)
McGovern, Seamus M.; Gupta, Surendra M.
2004-12-01
Disassembly takes place in remanufacturing, recycling, and disposal with a line being the best choice for automation. The disassembly line balancing problem seeks a sequence which: minimizes workstations, ensures similar idle times, and is feasible. Finding the optimal balance is computationally intensive due to factorial growth. Combinatorial optimization methods hold promise for providing solutions to the disassembly line balancing problem, which is proven to belong to the class of NP-complete problems. Ant colony optimization, genetic algorithm, and H-K metaheuristics are presented and compared along with a greedy/hill-climbing heuristic hybrid. A numerical study is performed to illustrate the implementation and compare performance. Conclusions drawn include the consistent generation of optimal or near-optimal solutions, the ability to preserve precedence, the speed of the techniques, and their practicality due to ease of implementation.
Johnson, Gary E.; Khan, Fenton; Ploskey, Gene R.; Hughes, James S.; Fischer, Eric S.
2010-08-18
The goal of the study was to optimize performance of the fixed-location hydroacoustic systems at Lookout Point Dam (LOP) and the acoustic imaging system at Cougar Dam (CGR) by determining deployment and data acquisition methods that minimized structural, electrical, and acoustic interference. The general approach was a multi-step process from mount design to final system configuration. The optimization effort resulted in successful deployments of hydroacoustic equipment at LOP and CGR.
Multi-step contrast sensitivity gauge
Quintana, Enrico C; Thompson, Kyle R; Moore, David G; Heister, Jack D; Poland, Richard W; Ellegood, John P; Hodges, George K; Prindville, James E
2014-10-14
An X-ray contrast sensitivity gauge is described herein. The contrast sensitivity gauge comprises a plurality of steps of varying thicknesses. Each step in the gauge includes a plurality of recesses of differing depths, wherein the depths are a function of the thickness of their respective step. An X-ray image of the gauge is analyzed to determine a contrast-to-noise ratio of a detector employed to generate the image.
Lu, Qiaozhen; Padler-Karavani, Vered; Yu, Hai; Chen, Xi; Wu, Shiaw-Lin; Varki, Ajit; Hancock, William S.
2014-01-01
Human polyclonal IgG antibodies directly against the non-human sialic acid N-glycolylneuraminic acid (Neu5Gc) are potential biomarkers and mechanistic contributors to cancer and other diseases associated with chronic inflammation. Using a sialoglycan microarray, we screened the binding pattern of such antibodies (anti-Neu5Gc IgG) in several samples of clinically-approved human IVIG (IgG). These results were used to select an appropriate sample for a multi-step affinity purification of the xeno-autoantibody fraction. The sample was then analyzed via our multi-enzyme digestion procedure followed by nanoLC coupled to LTQ-FTMS. We used characteristic and unique peptide sequences to determine the IgG subclass distribution and thus provided direct evidence that all four IgG subclasses can be generated during a xeno-autoantibody immune response to carbohydrate Neu5Gc-antigens. Furthermore, we obtained a significant amount of sequence coverage of both the constant and variable regions. The approach described here, therefore, provides a way to characterize these clinically significant antibodies, helping to understand their origins and significance. PMID:22390546
Optimal interdiction of unreactive Markovian evaders
Hagberg, Aric; Pan, Feng; Gutfraind, Alex
2009-01-01
The interdiction problem arises in a variety of areas including military logistics, infectious disease control, and counter-terrorism. In the typical formulation of network interdiction. the task of the interdictor is to find a set of edges in a weighted network such that the removal of those edges would increase the cost to an evader of traveling on a path through the network. Our work is motivated by cases in which the evader has incomplete information about the network or lacks planning time or computational power, e.g. when authorities set up roadblocks to catch bank robbers, the criminals do not know all the roadblock locations or the best path to use for their escape. We introduce a model of network interdiction in which the motion of one or more evaders is described by Markov processes on a network and the evaders are assumed not to react to interdiction decisions. The interdiction objective is to find a node or set. of size at most B, that maximizes the probability of capturing the evaders. We prove that similar to the classical formulation this interdiction problem is NP-hard. But unlike the classical problem our interdiction problem is submodular and the optimal solution can be approximated within 1-lie using a greedy algorithm. Additionally. we exploit submodularity to introduce a priority evaluation strategy that speeds up the greedy algorithm by orders of magnitude. Taken together the results bring closer the goal of finding realistic solutions to the interdiction problem on global-scale networks.
Ant system: optimization by a colony of cooperating agents.
Dorigo, M; Maniezzo, V; Colorni, A
1996-01-01
An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed computation, and the use of a constructive greedy heuristic. Positive feedback accounts for rapid discovery of good solutions, distributed computation avoids premature convergence, and the greedy heuristic helps find acceptable solutions in the early stages of the search process. We apply the proposed methodology to the classical traveling salesman problem (TSP), and report simulation results. We also discuss parameter selection and the early setups of the model, and compare it with tabu search and simulated annealing using TSP. To demonstrate the robustness of the approach, we show how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling. Finally we discuss the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.
Shape optimization techniques for musical instrument design
NASA Astrophysics Data System (ADS)
Henrique, Luis; Antunes, Jose; Carvalho, Joao S.
2002-11-01
The design of musical instruments is still mostly based on empirical knowledge and costly experimentation. One interesting improvement is the shape optimization of resonating components, given a number of constraints (allowed parameter ranges, shape smoothness, etc.), so that vibrations occur at specified modal frequencies. Each admissible geometrical configuration generates an error between computed eigenfrequencies and the target set. Typically, error surfaces present many local minima, corresponding to suboptimal designs. This difficulty can be overcome using global optimization techniques, such as simulated annealing. However these methods are greedy, concerning the number of function evaluations required. Thus, the computational effort can be unacceptable if complex problems, such as bell optimization, are tackled. Those issues are addressed in this paper, and a method for improving optimization procedures is proposed. Instead of using the local geometric parameters as searched variables, the system geometry is modeled in terms of truncated series of orthogonal space-funcitons, and optimization is performed on their amplitude coefficients. Fourier series and orthogonal polynomials are typical such functions. This technique reduces considerably the number of searched variables, and has a potential for significant computational savings in complex problems. It is illustrated by optimizing the shapes of both current and uncommon marimba bars.
Hoffmann, Thomas J; Zhan, Yiping; Kvale, Mark N; Hesselson, Stephanie E; Gollub, Jeremy; Iribarren, Carlos; Lu, Yontao; Mei, Gangwu; Purdy, Matthew M; Quesenberry, Charles; Rowell, Sarah; Shapero, Michael H; Smethurst, David; Somkin, Carol P; Van den Eeden, Stephen K; Walter, Larry; Webster, Teresa; Whitmer, Rachel A; Finn, Andrea; Schaefer, Catherine; Kwok, Pui-Yan; Risch, Neil
2011-12-01
Four custom Axiom genotyping arrays were designed for a genome-wide association (GWA) study of 100,000 participants from the Kaiser Permanente Research Program on Genes, Environment and Health. The array optimized for individuals of European race/ethnicity was previously described. Here we detail the development of three additional microarrays optimized for individuals of East Asian, African American, and Latino race/ethnicity. For these arrays, we decreased redundancy of high-performing SNPs to increase SNP capacity. The East Asian array was designed using greedy pairwise SNP selection. However, removing SNPs from the target set based on imputation coverage is more efficient than pairwise tagging. Therefore, we developed a novel hybrid SNP selection method for the African American and Latino arrays utilizing rounds of greedy pairwise SNP selection, followed by removal from the target set of SNPs covered by imputation. The arrays provide excellent genome-wide coverage and are valuable additions for large-scale GWA studies.
Approximating random quantum optimization problems
NASA Astrophysics Data System (ADS)
Hsu, B.; Laumann, C. R.; Läuchli, A. M.; Moessner, R.; Sondhi, S. L.
2013-06-01
We report a cluster of results regarding the difficulty of finding approximate ground states to typical instances of the quantum satisfiability problem k-body quantum satisfiability (k-QSAT) on large random graphs. As an approximation strategy, we optimize the solution space over “classical” product states, which in turn introduces a novel autonomous classical optimization problem, PSAT, over a space of continuous degrees of freedom rather than discrete bits. Our central results are (i) the derivation of a set of bounds and approximations in various limits of the problem, several of which we believe may be amenable to a rigorous treatment; (ii) a demonstration that an approximation based on a greedy algorithm borrowed from the study of frustrated magnetism performs well over a wide range in parameter space, and its performance reflects the structure of the solution space of random k-QSAT. Simulated annealing exhibits metastability in similar “hard” regions of parameter space; and (iii) a generalization of belief propagation algorithms introduced for classical problems to the case of continuous spins. This yields both approximate solutions, as well as insights into the free energy “landscape” of the approximation problem, including a so-called dynamical transition near the satisfiability threshold. Taken together, these results allow us to elucidate the phase diagram of random k-QSAT in a two-dimensional energy-density-clause-density space.
Coelho, V N; Coelho, I M; Souza, M J F; Oliveira, T A; Cota, L P; Haddad, M N; Mladenovic, N; Silva, R C P; Guimarães, F G
2016-01-01
This article presents an Evolution Strategy (ES)--based algorithm, designed to self-adapt its mutation operators, guiding the search into the solution space using a Self-Adaptive Reduced Variable Neighborhood Search procedure. In view of the specific local search operators for each individual, the proposed population-based approach also fits into the context of the Memetic Algorithms. The proposed variant uses the Greedy Randomized Adaptive Search Procedure with different greedy parameters for generating its initial population, providing an interesting exploration-exploitation balance. To validate the proposal, this framework is applied to solve three different [Formula: see text]-Hard combinatorial optimization problems: an Open-Pit-Mining Operational Planning Problem with dynamic allocation of trucks, an Unrelated Parallel Machine Scheduling Problem with Setup Times, and the calibration of a hybrid fuzzy model for Short-Term Load Forecasting. Computational results point out the convergence of the proposed model and highlight its ability in combining the application of move operations from distinct neighborhood structures along the optimization. The results gathered and reported in this article represent a collective evidence of the performance of the method in challenging combinatorial optimization problems from different application domains. The proposed evolution strategy demonstrates an ability of adapting the strength of the mutation disturbance during the generations of its evolution process. The effectiveness of the proposal motivates the application of this novel evolutionary framework for solving other combinatorial optimization problems.
Detonation Diffraction in a Multi-Step Channel
2010-12-01
transmit to a larger combustor . 15. NUMBER OF PAGES 152 14. SUBJECT TERMS Detonation Diffraction in a multi–step channel 16. PRICE CODE 17...and were unable to transmit to a larger combustor . vi THIS PAGE INTENTIONALLY LEFT BLANK vii TABLE OF CONTENTS I...CHANNEL MAIN COMPONENTS............................. 29 B. COMBUSTOR OPERATION.............................................................. 30 C
Information processing in multi-step signaling pathways
NASA Astrophysics Data System (ADS)
Ganesan, Ambhi; Hamidzadeh, Archer; Zhang, Jin; Levchenko, Andre
Information processing in complex signaling networks is limited by a high degree of variability in the abundance and activity of biochemical reactions (biological noise) operating in living cells. In this context, it is particularly surprising that many signaling pathways found in eukaryotic cells are composed of long chains of biochemical reactions, which are expected to be subject to accumulating noise and delayed signal processing. Here, we challenge the notion that signaling pathways are insulated chains, and rather view them as parts of extensively branched networks, which can benefit from a low degree of interference between signaling components. We further establish conditions under which this pathway organization would limit noise accumulation, and provide evidence for this type of signal processing in an experimental model of a calcium-activated MAPK cascade. These results address the long-standing problem of diverse organization and structure of signaling networks in live cells.
Multi-Step Production of a Diphoton Resonance
Dobrescu, Bogdan A.; Fox, Patrick J.; Kearney, John
2016-05-27
Assuming that the mass peak at 750 GeV reported by the ATLAS and CMS Collaborations is due to a spin-0 particle that decays into two photons, we present two weakly-coupled renormalizable models that lead to different production mechanisms. In one model, a scalar particle produced through gluon fusion decays into the diphoton particle and a light, long-lived pseudoscalar. In another model, a $Z'$ boson produced from the annihilation of a strange-antistrange quark pair undergoes a cascade decay that leads to the diphoton particle and two sterile neutrinos. We show that various kinematic distributions may differentiate these models from the canonical model where the diphoton particle is directly produced in gluon fusion.
A variable multi-step method for transient heat conduction
NASA Technical Reports Server (NTRS)
Smolinski, Patrick
1991-01-01
A variable explicit time integration algorithm is developed for unsteady diffusion problems. The algorithm uses nodal partitioning and allows the nodal groups to be updated with different time steps. The stability of the algorithm is analyzed using energy methods and critical time steps are found in terms of element eigenvalues with no restrictions on element types. Several numerical examples are given to illustrate the accuracy of the method.
Optimally Stopped Optimization
NASA Astrophysics Data System (ADS)
Vinci, Walter; Lidar, Daniel A.
2016-11-01
We combine the fields of heuristic optimization and optimal stopping. We propose a strategy for benchmarking randomized optimization algorithms that minimizes the expected total cost for obtaining a good solution with an optimal number of calls to the solver. To do so, rather than letting the objective function alone define a cost to be minimized, we introduce a further cost-per-call of the algorithm. We show that this problem can be formulated using optimal stopping theory. The expected cost is a flexible figure of merit for benchmarking probabilistic solvers that can be computed when the optimal solution is not known and that avoids the biases and arbitrariness that affect other measures. The optimal stopping formulation of benchmarking directly leads to a real-time optimal-utilization strategy for probabilistic optimizers with practical impact. We apply our formulation to benchmark simulated annealing on a class of maximum-2-satisfiability (MAX2SAT) problems. We also compare the performance of a D-Wave 2X quantum annealer to the Hamze-Freitas-Selby (HFS) solver, a specialized classical heuristic algorithm designed for low-tree-width graphs. On a set of frustrated-loop instances with planted solutions defined on up to N =1098 variables, the D-Wave device is 2 orders of magnitude faster than the HFS solver, and, modulo known caveats related to suboptimal annealing times, exhibits identical scaling with problem size.
Offshore wind farm layout optimization
NASA Astrophysics Data System (ADS)
Elkinton, Christopher Neil
Offshore wind energy technology is maturing in Europe and is poised to make a significant contribution to the U.S. energy production portfolio. Building on the knowledge the wind industry has gained to date, this dissertation investigates the influences of different site conditions on offshore wind farm micrositing---the layout of individual turbines within the boundaries of a wind farm. For offshore wind farms, these conditions include, among others, the wind and wave climates, water depths, and soil conditions at the site. An analysis tool has been developed that is capable of estimating the cost of energy (COE) from offshore wind farms. For this analysis, the COE has been divided into several modeled components: major costs (e.g. turbines, electrical interconnection, maintenance, etc.), energy production, and energy losses. By treating these component models as functions of site-dependent parameters, the analysis tool can investigate the influence of these parameters on the COE. Some parameters result in simultaneous increases of both energy and cost. In these cases, the analysis tool was used to determine the value of the parameter that yielded the lowest COE and, thus, the best balance of cost and energy. The models have been validated and generally compare favorably with existing offshore wind farm data. The analysis technique was then paired with optimization algorithms to form a tool with which to design offshore wind farm layouts for which the COE was minimized. Greedy heuristic and genetic optimization algorithms have been tuned and implemented. The use of these two algorithms in series has been shown to produce the best, most consistent solutions. The influences of site conditions on the COE have been studied further by applying the analysis and optimization tools to the initial design of a small offshore wind farm near the town of Hull, Massachusetts. The results of an initial full-site analysis and optimization were used to constrain the boundaries of
Improving IMRT-plan quality with MLC leaf position refinement post plan optimization
Niu Ying; Zhang Guowei; Berman, Barry L.; Parke, William C.; Yi Byongyong; Yu, Cedric X.
2012-08-15
Purpose: In intensity-modulated radiation therapy (IMRT) planning, reducing the pencil-beam size may lead to a significant improvement in dose conformity, but also increase the time needed for the dose calculation and plan optimization. The authors develop and evaluate a postoptimization refinement (POpR) method, which makes fine adjustments to the multileaf collimator (MLC) leaf positions after plan optimization, enhancing the spatial precision and improving the plan quality without a significant impact on the computational burden. Methods: The authors' POpR method is implemented using a commercial treatment planning system based on direct aperture optimization. After an IMRT plan is optimized using pencil beams with regular pencil-beam step size, a greedy search is conducted by looping through all of the involved MLC leaves to see if moving the MLC leaf in or out by half of a pencil-beam step size will improve the objective function value. The half-sized pencil beams, which are used for updating dose distribution in the greedy search, are derived from the existing full-sized pencil beams without need for further pencil-beam dose calculations. A benchmark phantom case and a head-and-neck (HN) case are studied for testing the authors' POpR method. Results: Using a benchmark phantom and a HN case, the authors have verified that their POpR method can be an efficient technique in the IMRT planning process. Effectiveness of POpR is confirmed by noting significant improvements in objective function values. Dosimetric benefits of POpR are comparable to those of using a finer pencil-beam size from the optimization start, but with far less computation and time. Conclusions: The POpR is a feasible and practical method to significantly improve IMRT-plan quality without compromising the planning efficiency.
A Particle Swarm Optimization-Based Approach with Local Search for Predicting Protein Folding.
Yang, Cheng-Hong; Lin, Yu-Shiun; Chuang, Li-Yeh; Chang, Hsueh-Wei
2017-03-13
The hydrophobic-polar (HP) model is commonly used for predicting protein folding structures and hydrophobic interactions. This study developed a particle swarm optimization (PSO)-based algorithm combined with local search algorithms; specifically, the high exploration PSO (HEPSO) algorithm (which can execute global search processes) was combined with three local search algorithms (hill-climbing algorithm, greedy algorithm, and Tabu table), yielding the proposed HE-L-PSO algorithm. By using 20 known protein structures, we evaluated the performance of the HE-L-PSO algorithm in predicting protein folding in the HP model. The proposed HE-L-PSO algorithm exhibited favorable performance in predicting both short and long amino acid sequences with high reproducibility and stability, compared with seven reported algorithms. The HE-L-PSO algorithm yielded optimal solutions for all predicted protein folding structures. All HE-L-PSO-predicted protein folding structures possessed a hydrophobic core that is similar to normal protein folding.
A global optimization paradigm based on change of measures
Sarkar, Saikat; Roy, Debasish; Vasu, Ram Mohan
2015-01-01
A global optimization framework, COMBEO (Change Of Measure Based Evolutionary Optimization), is proposed. An important aspect in the development is a set of derivative-free additive directional terms, obtainable through a change of measures en route to the imposition of any stipulated conditions aimed at driving the realized design variables (particles) to the global optimum. The generalized setting offered by the new approach also enables several basic ideas, used with other global search methods such as the particle swarm or the differential evolution, to be rationally incorporated in the proposed set-up via a change of measures. The global search may be further aided by imparting to the directional update terms additional layers of random perturbations such as ‘scrambling’ and ‘selection’. Depending on the precise choice of the optimality conditions and the extent of random perturbation, the search can be readily rendered either greedy or more exploratory. As numerically demonstrated, the new proposal appears to provide for a more rational, more accurate and, in some cases, a faster alternative to many available evolutionary optimization schemes. PMID:26587268
Optimal stimulus scheduling for active estimation of evoked brain networks
NASA Astrophysics Data System (ADS)
Kafashan, MohammadMehdi; Ching, ShiNung
2015-12-01
Objective. We consider the problem of optimal probing to learn connections in an evoked dynamic network. Such a network, in which each edge measures an input-output relationship between sites in sensor/actuator-space, is relevant to emerging applications in neural mapping and neural connectivity estimation. Approach. We show that the problem of scheduling nodes to a probe (i.e., stimulate) amounts to a problem of optimal sensor scheduling. Main results. By formulating the evoked network in state-space, we show that the solution to the greedy probing strategy has a convenient form and, under certain conditions, is optimal over a finite horizon. We adopt an expectation maximization technique to update the state-space parameters in an online fashion and demonstrate the efficacy of the overall approach in a series of detailed numerical examples. Significance. The proposed method provides a principled means to actively probe time-varying connections in neuronal networks. The overall method can be implemented in real time and is particularly well-suited to applications in stimulation-based cortical mapping in which the underlying network dynamics are changing over time.
Optimizing spread dynamics on graphs by message passing
NASA Astrophysics Data System (ADS)
Altarelli, F.; Braunstein, A.; Dall'Asta, L.; Zecchina, R.
2013-09-01
Cascade processes are responsible for many important phenomena in natural and social sciences. Simple models of irreversible dynamics on graphs, in which nodes activate depending on the state of their neighbors, have been successfully applied to describe cascades in a large variety of contexts. Over the past decades, much effort has been devoted to understanding the typical behavior of the cascades arising from initial conditions extracted at random from some given ensemble. However, the problem of optimizing the trajectory of the system, i.e. of identifying appropriate initial conditions to maximize (or minimize) the final number of active nodes, is still considered to be practically intractable, with the only exception being models that satisfy a sort of diminishing returns property called submodularity. Submodular models can be approximately solved by means of greedy strategies, but by definition they lack cooperative characteristics which are fundamental in many real systems. Here we introduce an efficient algorithm based on statistical physics for the optimization of trajectories in cascade processes on graphs. We show that for a wide class of irreversible dynamics, even in the absence of submodularity, the spread optimization problem can be solved efficiently on large networks. Analytic and algorithmic results on random graphs are complemented by the solution of the spread maximization problem on a real-world network (the Epinions consumer reviews network).
On the optimality of the neighbor-joining algorithm
Eickmeyer, Kord; Huggins, Peter; Pachter, Lior; Yoshida, Ruriko
2008-01-01
The popular neighbor-joining (NJ) algorithm used in phylogenetics is a greedy algorithm for finding the balanced minimum evolution (BME) tree associated to a dissimilarity map. From this point of view, NJ is "optimal" when the algorithm outputs the tree which minimizes the balanced minimum evolution criterion. We use the fact that the NJ tree topology and the BME tree topology are determined by polyhedral subdivisions of the spaces of dissimilarity maps R+(n2) to study the optimality of the neighbor-joining algorithm. In particular, we investigate and compare the polyhedral subdivisions for n ≤ 8. This requires the measurement of volumes of spherical polytopes in high dimension, which we obtain using a combination of Monte Carlo methods and polyhedral algorithms. Our results include a demonstration that highly unrelated trees can be co-optimal in BME reconstruction, and that NJ regions are not convex. We obtain the l2 radius for neighbor-joining for n = 5 and we conjecture that the ability of the neighbor-joining algorithm to recover the BME tree depends on the diameter of the BME tree. PMID:18447942
NASA Astrophysics Data System (ADS)
Guthier, C. V.; Aschenbrenner, K. P.; Müller, R.; Polster, L.; Cormack, R. A.; Hesser, J. W.
2016-08-01
This paper demonstrates that optimization strategies derived from the field of compressed sensing (CS) improve computational performance in inverse treatment planning (ITP) for high-dose-rate (HDR) brachytherapy. Following an approach applied to low-dose-rate brachytherapy, we developed a reformulation of the ITP problem with the same mathematical structure as standard CS problems. Two greedy methods, derived from hard thresholding and subspace pursuit are presented and their performance is compared to state-of-the-art ITP solvers. Applied to clinical prostate brachytherapy plans speed-up by a factor of 56-350 compared to state-of-the-art methods. Based on a Wilcoxon signed rank-test the novel method statistically significantly decreases the final objective function value (p < 0.01). The optimization times were below one second and thus planing can be considered as real-time capable. The novel CS inspired strategy enables real-time ITP for HDR brachytherapy including catheter optimization. The generated plans are either clinically equivalent or show a better performance with respect to dosimetric measures.
Ant colony optimization with selective evaluation for feature selection in character recognition
NASA Astrophysics Data System (ADS)
Oh, Il-Seok; Lee, Jin-Seon
2010-01-01
This paper analyzes the size characteristics of character recognition domain with the aim of developing a feature selection algorithm adequate for the domain. Based on the results, we further analyze the timing requirements of three popular feature selection algorithms, greedy algorithm, genetic algorithm, and ant colony optimization. For a rigorous timing analysis, we adopt the concept of atomic operation. We propose a novel scheme called selective evaluation to improve convergence of ACO. The scheme cut down the computational load by excluding the evaluation of unnecessary or less promising candidate solutions. The scheme is realizable in ACO due to the valuable information, pheromone trail which helps identify those solutions. Experimental results showed that the ACO with selective evaluation was promising both in timing requirement and recognition performance.
Multiple Object Tracking Using K-Shortest Paths Optimization.
Berclaz, Jérôme; Fleuret, François; Türetken, Engin; Fua, Pascal
2011-09-01
Multi-object tracking can be achieved by detecting objects in individual frames and then linking detections across frames. Such an approach can be made very robust to the occasional detection failure: If an object is not detected in a frame but is in previous and following ones, a correct trajectory will nevertheless be produced. By contrast, a false-positive detection in a few frames will be ignored. However, when dealing with a multiple target problem, the linking step results in a difficult optimization problem in the space of all possible families of trajectories. This is usually dealt with by sampling or greedy search based on variants of Dynamic Programming which can easily miss the global optimum. In this paper, we show that reformulating that step as a constrained flow optimization results in a convex problem. We take advantage of its particular structure to solve it using the k-shortest paths algorithm, which is very fast. This new approach is far simpler formally and algorithmically than existing techniques and lets us demonstrate excellent performance in two very different contexts.
Adaptive feature selection using v-shaped binary particle swarm optimization
Dong, Hongbin; Zhou, Xiurong
2017-01-01
Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate the dependency and redundancy of features separately, which leads to a lack of measurement of their combined effect. Moreover, a greedy search considers only the optimization of the current round and thus cannot be a global search. To evaluate the combined effect of different subsets in the entire feature space, an adaptive feature selection method based on V-shaped binary particle swarm optimization is proposed. In this method, the fitness function is constructed using the correlation information entropy. Feature subsets are regarded as individuals in a population, and the feature space is searched using V-shaped binary particle swarm optimization. The above procedure overcomes the hard constraint on the number of features, enables the combined evaluation of each subset as a whole, and improves the search ability of conventional binary particle swarm optimization. The proposed algorithm is an adaptive method with respect to the number of feature subsets. The experimental results show the advantages of optimizing the feature subsets using the V-shaped transfer function and confirm the effectiveness and efficiency of the feature subsets obtained under different classifiers. PMID:28358850
Detecting community structure in complex networks using an interaction optimization process
NASA Astrophysics Data System (ADS)
Kim, Paul; Kim, Sangwook
2017-01-01
Most complex networks contain community structures. Detecting these community structures is important for understanding and controlling the networks. Most community detection methods use network topology and edge density to identify optimal communities; however, these methods have a high computational complexity and are sensitive to network forms and types. To address these problems, in this paper, we propose an algorithm that uses an interaction optimization process to detect community structures in complex networks. This algorithm efficiently searches the candidates of optimal communities by optimizing the interactions of the members within each community based on the concept of greedy optimization. During this process, each candidate is evaluated using an interaction-based community model. This model quickly and accurately measures the difference between the quantity and quality of intra- and inter-community interactions. We test our algorithm on several benchmark networks with known community structures that include diverse communities detected by other methods. Additionally, after applying our algorithm to several real-world complex networks, we compare our algorithm with other methods. We find that the structure quality and coverage results achieved by our algorithm surpass those of the other methods.
NASA Astrophysics Data System (ADS)
Hosoi, Anette
2006-11-01
In this talk we will discuss two optimization topics related to low Reynolds number locomotion: optimal stroke patterns in linked swimmers and optimal fluid material properties in adhesive locomotion. In contrast to many optimization problems, we do not consider geometry, rather we optimize the swimming kinematics or fluid material properties for a given geometrical configuration. In the first case, we begin by optimizing stroke patterns for Purcell's 3-link swimmer. We model the swimmer as a jointed chain of three slender links moving in an inertialess flow. The swimmer is optimized for both efficiency and speed. In the second case, we analyze the adhesive locomotion used by common gastropods such as snails and slugs. Such organisms crawl on a solid substrate by propagating muscular waves of shear stress on a viscoelastic mucus. Using a simple mechanical model, we derive criteria for favorable fluid material properties to lower the energetic cost of locomotion.
NASA Astrophysics Data System (ADS)
Bai, Peng; Jeon, Mi Young; Ren, Limin; Knight, Chris; Deem, Michael W.; Tsapatsis, Michael; Siepmann, J. Ilja
2015-01-01
Zeolites play numerous important roles in modern petroleum refineries and have the potential to advance the production of fuels and chemical feedstocks from renewable resources. The performance of a zeolite as separation medium and catalyst depends on its framework structure. To date, 213 framework types have been synthesized and >330,000 thermodynamically accessible zeolite structures have been predicted. Hence, identification of optimal zeolites for a given application from the large pool of candidate structures is attractive for accelerating the pace of materials discovery. Here we identify, through a large-scale, multi-step computational screening process, promising zeolite structures for two energy-related applications: the purification of ethanol from fermentation broths and the hydroisomerization of alkanes with 18-30 carbon atoms encountered in petroleum refining. These results demonstrate that predictive modelling and data-driven science can now be applied to solve some of the most challenging separation problems involving highly non-ideal mixtures and highly articulated compounds.
NASA Astrophysics Data System (ADS)
Shaltev, M.
2016-02-01
The search for continuous gravitational waves in a wide parameter space at a fixed computing cost is most efficiently done with semicoherent methods, e.g., StackSlide, due to the prohibitive computing cost of the fully coherent search strategies. Prix and Shaltev [Phys. Rev. D 85, 084010 (2012)] have developed a semianalytic method for finding optimal StackSlide parameters at a fixed computing cost under ideal data conditions, i.e., gapless data and a constant noise floor. In this work, we consider more realistic conditions by allowing for gaps in the data and changes in the noise level. We show how the sensitivity optimization can be decoupled from the data selection problem. To find optimal semicoherent search parameters, we apply a numerical optimization using as an example the semicoherent StackSlide search. We also describe three different data selection algorithms. Thus, the outcome of the numerical optimization consists of the optimal search parameters and the selected data set. We first test the numerical optimization procedure under ideal conditions and show that we can reproduce the results of the analytical method. Then we gradually relax the conditions on the data and find that a compact data selection algorithm yields higher sensitivity compared to a greedy data selection procedure.
Tighten after Relax: Minimax-Optimal Sparse PCA in Polynomial Time
Wang, Zhaoran; Lu, Huanran; Liu, Han
2014-01-01
We provide statistical and computational analysis of sparse Principal Component Analysis (PCA) in high dimensions. The sparse PCA problem is highly nonconvex in nature. Consequently, though its global solution attains the optimal statistical rate of convergence, such solution is computationally intractable to obtain. Meanwhile, although its convex relaxations are tractable to compute, they yield estimators with suboptimal statistical rates of convergence. On the other hand, existing nonconvex optimization procedures, such as greedy methods, lack statistical guarantees. In this paper, we propose a two-stage sparse PCA procedure that attains the optimal principal subspace estimator in polynomial time. The main stage employs a novel algorithm named sparse orthogonal iteration pursuit, which iteratively solves the underlying nonconvex problem. However, our analysis shows that this algorithm only has desired computational and statistical guarantees within a restricted region, namely the basin of attraction. To obtain the desired initial estimator that falls into this region, we solve a convex formulation of sparse PCA with early stopping. Under an integrated analytic framework, we simultaneously characterize the computational and statistical performance of this two-stage procedure. Computationally, our procedure converges at the rate of 1∕t within the initialization stage, and at a geometric rate within the main stage. Statistically, the final principal subspace estimator achieves the minimax-optimal statistical rate of convergence with respect to the sparsity level s*, dimension d and sample size n. Our procedure motivates a general paradigm of tackling nonconvex statistical learning problems with provable statistical guarantees. PMID:25620858
Practical optimization of Steiner trees via the cavity method
NASA Astrophysics Data System (ADS)
Braunstein, Alfredo; Muntoni, Anna
2016-07-01
The optimization version of the cavity method for single instances, called Max-Sum, has been applied in the past to the minimum Steiner tree problem on graphs and variants. Max-Sum has been shown experimentally to give asymptotically optimal results on certain types of weighted random graphs, and to give good solutions in short computation times for some types of real networks. However, the hypotheses behind the formulation and the cavity method itself limit substantially the class of instances on which the approach gives good results (or even converges). Moreover, in the standard model formulation, the diameter of the tree solution is limited by a predefined bound, that affects both computation time and convergence properties. In this work we describe two main enhancements to the Max-Sum equations to be able to cope with optimization of real-world instances. First, we develop an alternative ‘flat’ model formulation that allows the relevant configuration space to be reduced substantially, making the approach feasible on instances with large solution diameter, in particular when the number of terminal nodes is small. Second, we propose an integration between Max-Sum and three greedy heuristics. This integration allows Max-Sum to be transformed into a highly competitive self-contained algorithm, in which a feasible solution is given at each step of the iterative procedure. Part of this development participated in the 2014 DIMACS Challenge on Steiner problems, and we report the results here. The performance on the challenge of the proposed approach was highly satisfactory: it maintained a small gap to the best bound in most cases, and obtained the best results on several instances in two different categories. We also present several improvements with respect to the version of the algorithm that participated in the competition, including new best solutions for some of the instances of the challenge.
NASA Technical Reports Server (NTRS)
Macready, William; Wolpert, David
2005-01-01
We demonstrate a new framework for analyzing and controlling distributed systems, by solving constrained optimization problems with an algorithm based on that framework. The framework is ar. information-theoretic extension of conventional full-rationality game theory to allow bounded rational agents. The associated optimization algorithm is a game in which agents control the variables of the optimization problem. They do this by jointly minimizing a Lagrangian of (the probability distribution of) their joint state. The updating of the Lagrange parameters in that Lagrangian is a form of automated annealing, one that focuses the multi-agent system on the optimal pure strategy. We present computer experiments for the k-sat constraint satisfaction problem and for unconstrained minimization of NK functions.
Wen-Chiao Lin; Humberto E. Garcia; Tae-Sic Yoo
2011-06-01
Diagnosers for keeping track on the occurrences of special events in the framework of unreliable partially observed discrete-event dynamical systems were developed in previous work. This paper considers observation platforms consisting of sensors that provide partial and unreliable observations and of diagnosers that analyze them. Diagnosers in observation platforms typically perform better as sensors providing the observations become more costly or increase in number. This paper proposes a methodology for finding an observation platform that achieves an optimal balance between cost and performance, while satisfying given observability requirements and constraints. Since this problem is generally computational hard in the framework considered, an observation platform optimization algorithm is utilized that uses two greedy heuristics, one myopic and another based on projected performances. These heuristics are sequentially executed in order to find best observation platforms. The developed algorithm is then applied to an observation platform optimization problem for a multi-unit-operation system. Results show that improved observation platforms can be found that may significantly reduce the observation platform cost but still yield acceptable performance for correctly inferring the occurrences of special events.
A Globally Optimal Particle Tracking Technique for Stereo Imaging Velocimetry Experiments
NASA Technical Reports Server (NTRS)
McDowell, Mark
2008-01-01
An important phase of any Stereo Imaging Velocimetry experiment is particle tracking. Particle tracking seeks to identify and characterize the motion of individual particles entrained in a fluid or air experiment. We analyze a cylindrical chamber filled with water and seeded with density-matched particles. In every four-frame sequence, we identify a particle track by assigning a unique track label for each camera image. The conventional approach to particle tracking is to use an exhaustive tree-search method utilizing greedy algorithms to reduce search times. However, these types of algorithms are not optimal due to a cascade effect of incorrect decisions upon adjacent tracks. We examine the use of a guided evolutionary neural net with simulated annealing to arrive at a globally optimal assignment of tracks. The net is guided both by the minimization of the search space through the use of prior limiting assumptions about valid tracks and by a strategy which seeks to avoid high-energy intermediate states which can trap the net in a local minimum. A stochastic search algorithm is used in place of back-propagation of error to further reduce the chance of being trapped in an energy well. Global optimization is achieved by minimizing an objective function, which includes both track smoothness and particle-image utilization parameters. In this paper we describe our model and present our experimental results. We compare our results with a nonoptimizing, predictive tracker and obtain an average increase in valid track yield of 27 percent
Optimized Structure of the Traffic Flow Forecasting Model With a Deep Learning Approach.
Yang, Hao-Fan; Dillon, Tharam S; Chen, Yi-Ping Phoebe
2016-07-20
Forecasting accuracy is an important issue for successful intelligent traffic management, especially in the domain of traffic efficiency and congestion reduction. The dawning of the big data era brings opportunities to greatly improve prediction accuracy. In this paper, we propose a novel model, stacked autoencoder Levenberg-Marquardt model, which is a type of deep architecture of neural network approach aiming to improve forecasting accuracy. The proposed model is designed using the Taguchi method to develop an optimized structure and to learn traffic flow features through layer-by-layer feature granulation with a greedy layerwise unsupervised learning algorithm. It is applied to real-world data collected from the M6 freeway in the U.K. and is compared with three existing traffic predictors. To the best of our knowledge, this is the first time that an optimized structure of the traffic flow forecasting model with a deep learning approach is presented. The evaluation results demonstrate that the proposed model with an optimized structure has superior performance in traffic flow forecasting.
Guimarães, Dayan Adionel; Sakai, Lucas Jun; Alberti, Antonio Marcos; de Souza, Rausley Adriano Amaral
2016-01-01
In this paper, a simple and flexible method for increasing the lifetime of fixed or mobile wireless sensor networks is proposed. Based on past residual energy information reported by the sensor nodes, the sink node or another central node dynamically optimizes the communication activity levels of the sensor nodes to save energy without sacrificing the data throughput. The activity levels are defined to represent portions of time or time-frequency slots in a frame, during which the sensor nodes are scheduled to communicate with the sink node to report sensory measurements. Besides node mobility, it is considered that sensors’ batteries may be recharged via a wireless power transmission or equivalent energy harvesting scheme, bringing to the optimization problem an even more dynamic character. We report large increased lifetimes over the non-optimized network and comparable or even larger lifetime improvements with respect to an idealized greedy algorithm that uses both the real-time channel state and the residual energy information. PMID:27657075
Forging tool shape optimization using pseudo inverse approach and adaptive incremental approach
NASA Astrophysics Data System (ADS)
Halouani, A.; Meng, F. J.; Li, Y. M.; Labergère, C.; Abbès, B.; Lafon, P.; Guo, Y. Q.
2013-05-01
This paper presents a simplified finite element method called "Pseudo Inverse Approach" (PIA) for tool shape design and optimization in multi-step cold forging processes. The approach is based on the knowledge of the final part shape. Some intermediate configurations are introduced and corrected by using a free surface method to consider the deformation paths without contact treatment. A robust direct algorithm of plasticity is implemented by using the equivalent stress notion and tensile curve. Numerical tests have shown that the PIA is very fast compared to the incremental approach. The PIA is used in an optimization procedure to automatically design the shapes of the preform tools. Our objective is to find the optimal preforms which minimize the equivalent plastic strain and punch force. The preform shapes are defined by B-Spline curves. A simulated annealing algorithm is adopted for the optimization procedure. The forging results obtained by the PIA are compared to those obtained by the incremental approach to show the efficiency and accuracy of the PIA.
Sejnowski, Terrence J; Poizner, Howard; Lynch, Gary; Gepshtein, Sergei; Greenspan, Ralph J
2014-05-01
Human performance approaches that of an ideal observer and optimal actor in some perceptual and motor tasks. These optimal abilities depend on the capacity of the cerebral cortex to store an immense amount of information and to flexibly make rapid decisions. However, behavior only approaches these limits after a long period of learning while the cerebral cortex interacts with the basal ganglia, an ancient part of the vertebrate brain that is responsible for learning sequences of actions directed toward achieving goals. Progress has been made in understanding the algorithms used by the brain during reinforcement learning, which is an online approximation of dynamic programming. Humans also make plans that depend on past experience by simulating different scenarios, which is called prospective optimization. The same brain structures in the cortex and basal ganglia that are active online during optimal behavior are also active offline during prospective optimization. The emergence of general principles and algorithms for goal-directed behavior has consequences for the development of autonomous devices in engineering applications.
Sejnowski, Terrence J.; Poizner, Howard; Lynch, Gary; Gepshtein, Sergei; Greenspan, Ralph J.
2014-01-01
Human performance approaches that of an ideal observer and optimal actor in some perceptual and motor tasks. These optimal abilities depend on the capacity of the cerebral cortex to store an immense amount of information and to flexibly make rapid decisions. However, behavior only approaches these limits after a long period of learning while the cerebral cortex interacts with the basal ganglia, an ancient part of the vertebrate brain that is responsible for learning sequences of actions directed toward achieving goals. Progress has been made in understanding the algorithms used by the brain during reinforcement learning, which is an online approximation of dynamic programming. Humans also make plans that depend on past experience by simulating different scenarios, which is called prospective optimization. The same brain structures in the cortex and basal ganglia that are active online during optimal behavior are also active offline during prospective optimization. The emergence of general principles and algorithms for goal-directed behavior has consequences for the development of autonomous devices in engineering applications. PMID:25328167
Lee, John R.
1975-01-01
Optimal fluoridation has been defined as that fluoride exposure which confers maximal cariostasis with minimal toxicity and its values have been previously determined to be 0.5 to 1 mg per day for infants and 1 to 1.5 mg per day for an average child. Total fluoride ingestion and urine excretion were studied in Marin County, California, children in 1973 before municipal water fluoridation. Results showed fluoride exposure to be higher than anticipated and fulfilled previously accepted criteria for optimal fluoridation. Present and future water fluoridation plans need to be reevaluated in light of total environmental fluoride exposure. PMID:1130041
NASA Technical Reports Server (NTRS)
Vanderplaats, G. N.; Chen, Xiang; Zhang, Ning-Tian
1988-01-01
The use of formal numerical optimization methods for the design of gears is investigated. To achieve this, computer codes were developed for the analysis of spur gears and spiral bevel gears. These codes calculate the life, dynamic load, bending strength, surface durability, gear weight and size, and various geometric parameters. It is necessary to calculate all such important responses because they all represent competing requirements in the design process. The codes developed here were written in subroutine form and coupled to the COPES/ADS general purpose optimization program. This code allows the user to define the optimization problem at the time of program execution. Typical design variables include face width, number of teeth and diametral pitch. The user is free to choose any calculated response as the design objective to minimize or maximize and may impose lower and upper bounds on any calculated responses. Typical examples include life maximization with limits on dynamic load, stress, weight, etc. or minimization of weight subject to limits on life, dynamic load, etc. The research codes were written in modular form for easy expansion and so that they could be combined to create a multiple reduction optimization capability in future.
Kreitler, Jason; Stoms, David M; Davis, Frank W
2014-01-01
Quantitative methods of spatial conservation prioritization have traditionally been applied to issues in conservation biology and reserve design, though their use in other types of natural resource management is growing. The utility maximization problem is one form of a covering problem where multiple criteria can represent the expected social benefits of conservation action. This approach allows flexibility with a problem formulation that is more general than typical reserve design problems, though the solution methods are very similar. However, few studies have addressed optimization in utility maximization problems for conservation planning, and the effect of solution procedure is largely unquantified. Therefore, this study mapped five criteria describing elements of multifunctional agriculture to determine a hypothetical conservation resource allocation plan for agricultural land conservation in the Central Valley of CA, USA. We compared solution procedures within the utility maximization framework to determine the difference between an open source integer programming approach and a greedy heuristic, and find gains from optimization of up to 12%. We also model land availability for conservation action as a stochastic process and determine the decline in total utility compared to the globally optimal set using both solution algorithms. Our results are comparable to other studies illustrating the benefits of optimization for different conservation planning problems, and highlight the importance of maximizing the effectiveness of limited funding for conservation and natural resource management.
Kreitler, Jason R.; Stoms, David M.; Davis, Frank W.
2014-01-01
Quantitative methods of spatial conservation prioritization have traditionally been applied to issues in conservation biology and reserve design, though their use in other types of natural resource management is growing. The utility maximization problem is one form of a covering problem where multiple criteria can represent the expected social benefits of conservation action. This approach allows flexibility with a problem formulation that is more general than typical reserve design problems, though the solution methods are very similar. However, few studies have addressed optimization in utility maximization problems for conservation planning, and the effect of solution procedure is largely unquantified. Therefore, this study mapped five criteria describing elements of multifunctional agriculture to determine a hypothetical conservation resource allocation plan for agricultural land conservation in the Central Valley of CA, USA. We compared solution procedures within the utility maximization framework to determine the difference between an open source integer programming approach and a greedy heuristic, and find gains from optimization of up to 12%. We also model land availability for conservation action as a stochastic process and determine the decline in total utility compared to the globally optimal set using both solution algorithms. Our results are comparable to other studies illustrating the benefits of optimization for different conservation planning problems, and highlight the importance of maximizing the effectiveness of limited funding for conservation and natural resource management.
Tippetts, Tyler J; Warner, Phillip B; Kukhareva, Polina V; Shields, David E; Staes, Catherine J; Kawamoto, Kensaku
2015-01-01
Given the close relationship between clinical decision support (CDS) and quality measurement (QM), it has been proposed that a standards-based CDS Web service could be leveraged to enable QM. Benefits of such a CDS-QM framework include semantic consistency and implementation efficiency. However, earlier research has identified execution performance as a critical barrier when CDS-QM is applied to large populations. Here, we describe challenges encountered and solutions devised to optimize CDS-QM execution performance. Through these optimizations, the CDS-QM execution time was optimized approximately three orders of magnitude, such that approximately 370,000 patient records can now be evaluated for 22 quality measure groups in less than 5 hours (approximately 2 milliseconds per measure group per patient). Several key optimization methods were identified, with the most impact achieved through population-based retrieval of relevant data, multi-step data staging, and parallel processing. These optimizations have enabled CDS-QM to be operationally deployed at an enterprise level.
Multidisciplinary optimization
Dennis, J.; Lewis, R.M.; Cramer, E.J.; Frank, P.M.; Shubin, G.R.
1994-12-31
This talk will use aeroelastic design and reservoir characterization as examples to introduce some approaches to MDO, or Multidisciplinary Optimization. This problem arises especially in engineering design, where it is considered of paramount importance in today`s competitive global business climate. It is interesting to an optimizer because the constraints involve coupled dissimilar systems of parameterized partial differential equations each arising from a different discipline, like structural analysis, computational fluid dynamics, etc. Usually, these constraints are accessible only through pde solvers rather than through algebraic residual calculations as we are used to having. Thus, just finding a multidisciplinary feasible point is a daunting task. Many such problems have discrete variable disciplines, multiple objectives, and other challenging features. After discussing some interesting practical features of the design problem, we will give some standard ways to formulate the problem as well as some novel ways that lend themselves to divide-and-conquer parallelism.
Optimal space-time attacks on system state estimation under a sparsity constraint
NASA Astrophysics Data System (ADS)
Lu, Jingyang; Niu, Ruixin; Han, Puxiao
2016-05-01
System state estimation in the presence of an adversary that injects false information into sensor readings has attracted much attention in wide application areas, such as target tracking with compromised sensors, secure monitoring of dynamic electric power systems, secure driverless cars, and radar tracking and detection in the presence of jammers. From a malicious adversary's perspective, the optimal strategy for attacking a multi-sensor dynamic system over sensors and over time is investigated. It is assumed that the system defender can perfectly detect the attacks and identify and remove sensor data once they are corrupted by false information injected by the adversary. With this in mind, the adversary's goal is to maximize the covariance matrix of the system state estimate by the end of attack period under a sparse attack constraint such that the adversary can only attack the system a few times over time and over sensors. The sparsity assumption is due to the adversary's limited resources and his/her intention to reduce the chance of being detected by the system defender. This becomes an integer programming problem and its optimal solution, the exhaustive search, is intractable with a prohibitive complexity, especially for a system with a large number of sensors and over a large number of time steps. Several suboptimal solutions, such as those based on greedy search and dynamic programming are proposed to find the attack strategies. Examples and numerical results are provided in order to illustrate the effectiveness and the reduced computational complexities of the proposed attack strategies.
Optimization methods for decision making in disease prevention and epidemic control.
Deng, Yan; Shen, Siqian; Vorobeychik, Yevgeniy
2013-11-01
This paper investigates problems of disease prevention and epidemic control (DPEC), in which we optimize two sets of decisions: (i) vaccinating individuals and (ii) closing locations, given respective budgets with the goal of minimizing the expected number of infected individuals after intervention. The spread of diseases is inherently stochastic due to the uncertainty about disease transmission and human interaction. We use a bipartite graph to represent individuals' propensities of visiting a set of location, and formulate two integer nonlinear programming models to optimize choices of individuals to vaccinate and locations to close. Our first model assumes that if a location is closed, its visitors stay in a safe location and will not visit other locations. Our second model incorporates compensatory behavior by assuming multiple behavioral groups, always visiting the most preferred locations that remain open. The paper develops algorithms based on a greedy strategy, dynamic programming, and integer programming, and compares the computational efficacy and solution quality. We test problem instances derived from daily behavior patterns of 100 randomly chosen individuals (corresponding to 195 locations) in Portland, Oregon, and provide policy insights regarding the use of the two DPEC models.
[SIAM conference on optimization
Not Available
1992-05-10
Abstracts are presented of 63 papers on the following topics: large-scale optimization, interior-point methods, algorithms for optimization, problems in control, network optimization methods, and parallel algorithms for optimization problems.
Optimization and scale-up of a fluid bed tangential spray rotogranulation process.
Bouffard, J; Dumont, H; Bertrand, F; Legros, R
2007-04-20
The production of pellets in the pharmaceutical industry generally involves multi-step processing: (1) mixing, (2) wet granulation, (3) spheronization and (4) drying. While extrusion-spheronization processes have been popular because of their simplicity, fluid-bed rotogranulation (FBRG) is now being considered as an alternative, since it offers the advantages of combining the different steps into one processing unit, thus reducing processing time and material handling. This work aimed at the development of a FBRG process for the production of pellets in a 4.5-l Glatt GCPG1 tangential spray rotoprocessor and its optimization using factorial design. The factors considered were: (1) rotor disc velocity, (2) gap air pressure, (3) air flow rate, (4) binder spray rate and (5) atomization pressure. The pellets were characterized for their physical properties by measuring size distribution, roundness and flow properties. The results indicated that: pellet mean particle size is negatively affected by air flow rate and rotor plate speed, while binder spray rate has a positive effect on size; pellet flow properties are enhanced by operating with increased air flow rate and worsened with increased binder spray rate. Multiple regression analysis enabled the identification of an optimal operating window for production of acceptable pellets. Scale-up of these operating conditions was tested in a 30-l Glatt GPCG15 FBRG.
Optimization of propranolol HCl release kinetics from press coated sustained release tablets.
Ali, Adel Ahmed; Ali, Ahmed Mahmoud
2013-01-01
Press-coated sustained release tablets offer a valuable, cheap and easy manufacture alternative to the highly expensive, multi-step manufacture and filling of coated beads. In this study, propranolol HCl press-coated tablets were prepared using hydroxylpropylmethylcellulose (HPMC) as tablet coating material together with carbopol 971P and compressol as release modifiers. The prepared formulations were optimized for zero-order release using artificial neural network program (INForm, Intelligensys Ltd, North Yorkshire, UK). Typical zero-order release kinetics with extended release profile for more than 12 h was obtained. The most important variables considered by the program in optimizing formulations were type and proportion of polymer mixture in the coat layer and distribution ratio of drug between core and coat. The key elements found were; incorporation of 31-38 % of the drug in the coat, fixing the amount of polymer in coat to be not less than 50 % of coat layer. Optimum zero-order release kinetics (linear regression r2 = 0.997 and Peppas model n value > 0.80) were obtained when 2.5-10 % carbopol and 25-42.5% compressol were incorporated into the 50 % HPMC coat layer.
A Hybrid Optimization Framework with POD-based Order Reduction and Design-Space Evolution Scheme
NASA Astrophysics Data System (ADS)
Ghoman, Satyajit S.
The main objective of this research is to develop an innovative multi-fidelity multi-disciplinary design, analysis and optimization suite that integrates certain solution generation codes and newly developed innovative tools to improve the overall optimization process. The research performed herein is divided into two parts: (1) the development of an MDAO framework by integration of variable fidelity physics-based computational codes, and (2) enhancements to such a framework by incorporating innovative features extending its robustness. The first part of this dissertation describes the development of a conceptual Multi-Fidelity Multi-Strategy and Multi-Disciplinary Design Optimization Environment (M3 DOE), in context of aircraft wing optimization. M 3 DOE provides the user a capability to optimize configurations with a choice of (i) the level of fidelity desired, (ii) the use of a single-step or multi-step optimization strategy, and (iii) combination of a series of structural and aerodynamic analyses. The modularity of M3 DOE allows it to be a part of other inclusive optimization frameworks. The M 3 DOE is demonstrated within the context of shape and sizing optimization of the wing of a Generic Business Jet aircraft. Two different optimization objectives, viz. dry weight minimization, and cruise range maximization are studied by conducting one low-fidelity and two high-fidelity optimization runs to demonstrate the application scope of M3 DOE. The second part of this dissertation describes the development of an innovative hybrid optimization framework that extends the robustness of M 3 DOE by employing a proper orthogonal decomposition-based design-space order reduction scheme combined with the evolutionary algorithm technique. The POD method of extracting dominant modes from an ensemble of candidate configurations is used for the design-space order reduction. The snapshot of candidate population is updated iteratively using evolutionary algorithm technique of
Mdluli, Thembi; Buzzard, Gregery T; Rundell, Ann E
2015-09-01
This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm's scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements.
NASA Astrophysics Data System (ADS)
Allahverdyan, Armen E.; Hovhannisyan, Karen; Mahler, Guenter
2010-05-01
We study a refrigerator model which consists of two n -level systems interacting via a pulsed external field. Each system couples to its own thermal bath at temperatures Th and Tc , respectively (θ≡Tc/Th<1) . The refrigerator functions in two steps: thermally isolated interaction between the systems driven by the external field and isothermal relaxation back to equilibrium. There is a complementarity between the power of heat transfer from the cold bath and the efficiency: the latter nullifies when the former is maximized and vice versa. A reasonable compromise is achieved by optimizing the product of the heat-power and efficiency over the Hamiltonian of the two systems. The efficiency is then found to be bounded from below by ζCA=(1)/(1-θ)-1 (an analog of the Curzon-Ahlborn efficiency), besides being bound from above by the Carnot efficiency ζC=(1)/(1-θ)-1 . The lower bound is reached in the equilibrium limit θ→1 . The Carnot bound is reached (for a finite power and a finite amount of heat transferred per cycle) for lnn≫1 . If the above maximization is constrained by assuming homogeneous energy spectra for both systems, the efficiency is bounded from above by ζCA and converges to it for n≫1 .
Temporal variability of the optimal monitoring setup assessed using information theory
NASA Astrophysics Data System (ADS)
Fahle, Marcus; Hohenbrink, Tobias L.; Dietrich, Ottfried; Lischeid, Gunnar
2015-09-01
Hydrology is rich in methods that use information theory to evaluate monitoring networks. Yet in most existing studies, only the available data set as a whole is used, which neglects the intraannual variability of the hydrological system. In this paper, we demonstrate how this variability can be considered by extending monitoring evaluation to subsets of the available data. Therefore, we separately evaluated time windows of fixed length, which were shifted through the data set, and successively extended time windows. We used basic information theory measures and a greedy ranking algorithm based on the criterion of maximum information/minimum redundancy. The network investigated monitored surface and groundwater levels at quarter-hourly intervals and was located at an artificially drained lowland site in the Spreewald region in north-east Germany. The results revealed that some of the monitoring stations were of value permanently while others were needed only temporally. The prevailing meteorological conditions, particularly the amount of precipitation, affected the degree of similarity between the water levels measured. The hydrological system tended to act more individually during periods of no or little rainfall. The optimal monitoring setup, its stability, and the monitoring effort necessary were influenced by the meteorological forcing. Altogether, the methodology presented can help achieve a monitoring network design that has a more even performance or covers the conditions of interest (e.g., floods or droughts) best.
Multiple Satellite Trajectory Optimization
2004-12-01
SOLVING OPTIMAL CONTROL PROBLEMS ........................................5...OPTIMIZATION A. SOLVING OPTIMAL CONTROL PROBLEMS The driving principle used to solve optimal control problems was first formalized by the Soviet...methods and processes of solving optimal control problems , this section will demonstrate how the formulations work as expected. Once coded, the
Deciphering the multi-step degradation mechanisms of carbonate-based electrolyte in Li batteries
NASA Astrophysics Data System (ADS)
Gachot, Gregory; Grugeon, Sylvie; Armand, Michel; Pilard, Serge; Guenot, Pierre; Tarascon, Jean-Marie; Laruelle, Stephane
Electrolytes are crucial to the safety and long life of Li-ion batteries, however, the understanding of their degradation mechanisms is still sketchy. Here we report on the nature and formation of organic/inorganic degradation products generated at low potential in a lithium-based cell using cyclic and linear carbonate-based electrolyte mixtures. The global formation mechanism of ethylene oxide oligomers produced from EC/DMC (1/1 w/w)-LiPF 6 salt (1 M) electrolyte decomposition is proposed then mimicked via chemical tests. Each intermediary product structure/formula/composition is identified by means of combined NMR, FTIR and high resolution mass spectrometry (ESI-HRMS) analysis. The key role played by lithium methoxide as initiator of the electrolyte degradation is evidenced, but more importantly we isolated for the first time lithium methyl carbonate as a side product of the ethylene oxide oligomers chemical formation. The same degradation mechanism was found to hold on for another cyclic and linear carbonate-based electrolyte such as EC/DEC (1/1 w/w)-LiPF 6 salt (1 M). Such findings have important implications in the choice of chemical additives for developing highly performing electrolytes.
A multi-step model for the origin of E3 (enstatite) chondrites
NASA Astrophysics Data System (ADS)
Hutson, Melinda; Ruzicka, Alex
2000-05-01
It appears that the mineralogy and chemical properties of type 3 enstatite chondrites could have been established by fractionation processes (removal of a refractory component, and depletion of water) in the solar nebula, and by equilibration with nebular gas at low-to-intermediate temperatures (~700-950 K). We describe a model for the origin of type 3 enstatite chondrites that for the first time can simultaneously account for the mineral abundances, bulk-chemistry, and phase compositions of these chondrites, by the operation of plausible processes in the solar nebula. This model, which assumes a representative nebular gas pressure of 10-5 bar, entails three steps: (1) initial removal of 56% of the equilibrium condensed phases in a system of solar composition at 1270 K; (2) an average loss of 80-85% water vapor in the remaining gas; and (3) two different closure temperatures for the condensed phases. The first step involves a "refractory-element fractionation" and is needed to account for the overall major-element composition of enstatite chondrites, assuming an initial system with a solar composition. The second step, water-vapor depletion, is needed to stabilize Si-bearing metal, oldhamite, and niningerite, which are characteristic minerals of the enstatite chondrites. Variations in closure temperatures are suggested by the way in which the bulk chemistry and mineral assemblages of predicted condensates change with temperature, and how these parameters correlate with the observations of enstatite chondrites. In general, most phases in type 3 enstatite chondrites appear to have ceased equilibrating with nebular gas at ~900-950 K, except for Fe-metal, which continued to partially react with nebular gas to temperatures as low as ~700 K.
Multi-step process control and characterization of scanning probe lithography
NASA Astrophysics Data System (ADS)
Peterson, C. A.; Ruskell, T. G.; Pyle, J. L.; Workman, R. K.; Yao, X.; Hunt, J. P.; Sarid, D.; Parks, H. G.; Vermeire, B.
An atomic force microscope with a conducting tip (CT-AFM) was used to fabricate and characterize nanometer scale lines of (1) silicon oxide and (2) silicon nitride on H-terminated n-type silicon (100) wafers. In process (1), a negative bias was applied to the tip of the CT-AFM system and the resulting electric field caused electrolysis of ambient water vapor and local oxidation of the silicon surface. In addition, the accompanying current was detected by a sub-pA current amplifier. In process (2), the presence of a nitrogen atmosphere containing a small partial pressure of ammonia resulted in the local nitridation of the surface. The CT-AFM system was also used to locate and study the dielectric properties of the silicon-oxide lines as well as copper islands buried under 20 nm of silicon dioxide. A computer-controlled feedback system and raster scanning of the sample produced simultaneous topographic and Fowler-Nordheim tunneling maps of the structures under study. Detailed aspects of nanolithography and local-probe Fowler-Nordheim characterization using a CT-AFM will be discussed.
[Successful multi-step management of developmental heart defects after intrauterine diagnosis].
Hartyánszky, I; Kádár, K; Oprea, V; Palik, I; Sápi, E; Prodán, Z; Bodor, G; Mihályi, S
1997-03-23
At 28th week of gestation a conotruncal malformation with ventricular septal defect was diagnosed by fetal echocardiography. Postnatal echocardiographic and angiocardiographic examinations confirmed the diagnosis of conotruncal malformation (pulmonary atresia, ventricular septal defect, patent ductus arteriosus, aortopulmonary collateral arteries). The unifocalization (age: 11 months) and total correction with aortic homograft (age: 7 years) were performed. To our knowledge our case is the first whose intrauterine diagnosis of complex congenital heart disease was confirmed after delivery and had successful two-stage surgical management.
Multi-off-grid methods in multi-step integration of ordinary differential equations
NASA Technical Reports Server (NTRS)
Beaudet, P. R.
1974-01-01
Description of methods of solving first- and second-order systems of differential equations in which all derivatives are evaluated at off-grid locations in order to circumvent the Dahlquist stability limitation on the order of on-grid methods. The proposed multi-off-grid methods require off-grid state predictors for the evaluation of the n derivatives at each step. Progressing forward in time, the off-grid states are predicted using a linear combination of back on-grid state values and off-grid derivative evaluations. A comparison is made between the proposed multi-off-grid methods and the corresponding Adams and Cowell on-grid integration techniques in integrating systems of ordinary differential equations, showing a significant reduction in the error at larger step sizes in the case of the multi-off-grid integrator.
Multi-Step Attack Detection via Bayesian Modeling under Model Parameter Uncertainty
ERIC Educational Resources Information Center
Cole, Robert
2013-01-01
Organizations in all sectors of business have become highly dependent upon information systems for the conduct of business operations. Of necessity, these information systems are designed with many points of ingress, points of exposure that can be leveraged by a motivated attacker seeking to compromise the confidentiality, integrity or…
Multi-step usage of in vivo models during rational drug design and discovery.
Williams, Charles H; Hong, Charles C
2011-01-01
In this article we propose a systematic development method for rational drug design while reviewing paradigms in industry, emerging techniques and technologies in the field. Although the process of drug development today has been accelerated by emergence of computational methodologies, it is a herculean challenge requiring exorbitant resources; and often fails to yield clinically viable results. The current paradigm of target based drug design is often misguided and tends to yield compounds that have poor absorption, distribution, metabolism, and excretion, toxicology (ADMET) properties. Therefore, an in vivo organism based approach allowing for a multidisciplinary inquiry into potent and selective molecules is an excellent place to begin rational drug design. We will review how organisms like the zebrafish and Caenorhabditis elegans can not only be starting points, but can be used at various steps of the drug development process from target identification to pre-clinical trial models. This systems biology based approach paired with the power of computational biology; genetics and developmental biology provide a methodological framework to avoid the pitfalls of traditional target based drug design.
Successive magnetic transitions and multi-step magnetization in GdBC
NASA Astrophysics Data System (ADS)
Matsumoto, Akinori; Muramoto, Akihiro; Noguchi, Satoru
2003-05-01
We report the results of the magnetization measurements in the GdBC single crystal using a pulsed-magnet system up to 30 T and a SQUID magnetometer up to 5 T. The magnetization for the b-axis at 4.2 K shows three steps at 1, 5 and 15 T, being saturated above 23 T. The saturation moment is almost 7 μB/Gd. Temperature dependence of the step fields is obtained for all axes. These imply that GdBC has the successive antiferromagnetic transitions with the complex magnetic structures in spite of the simple spin system of Gd 3+.
Modeling the Auto-Ignition of Biodiesel Blends with a Multi-Step Model
Toulson, Dr. Elisa; Allen, Casey M; Miller, Dennis J; McFarlane, Joanna; Schock, Harold; Lee, Tonghun
2011-01-01
There is growing interest in using biodiesel in place of or in blends with petrodiesel in diesel engines; however, biodiesel oxidation chemistry is complicated to directly model and existing surrogate kinetic models are very large, making them computationally expensive. The present study describes a method for predicting the ignition behavior of blends of n-heptane and methyl butanoate, fuels whose blends have been used in the past as a surrogate for biodiesel. The autoignition is predicted using a multistep (8-step) model in order to reduce computational time and make this a viable tool for implementation into engine simulation codes. A detailed reaction mechanism for n-heptane-methyl butanoate blends was used as a basis for validating the multistep model results. The ignition delay trends predicted by the multistep model for the n-heptane-methyl butanoate blends matched well with that of the detailed CHEMKIN model for the majority of conditions tested.
Multi-step control of muscle diversity by Hox proteins in the Drosophila embryo
Enriquez, Jonathan; Boukhatmi, Hadi; Dubois, Laurence; Philippakis, Anthony A.; Bulyk, Martha L.; Michelson, Alan M.; Crozatier, Michèle; Vincent, Alain
2010-01-01
Summary Hox transcription factors control many aspects of animal morphogenetic diversity. The segmental pattern of Drosophila larval muscles shows stereotyped variations along the anteroposterior body axis. Each muscle is seeded by a founder cell and the properties specific to each muscle reflect the expression by each founder cell of a specific combination of ‘identity’ transcription factors. Founder cells originate from asymmetric division of progenitor cells specified at fixed positions. Using the dorsal DA3 muscle lineage as a paradigm, we show here that Hox proteins play a decisive role in establishing the pattern of Drosophila muscles by controlling the expression of identity transcription factors, such as Nautilus and Collier (Col), at the progenitor stage. High-resolution analysis, using newly designed intron-containing reporter genes to detect primary transcripts, shows that the progenitor stage is the key step at which segment-specific information carried by Hox proteins is superimposed on intrasegmental positional information. Differential control of col transcription by the Antennapedia and Ultrabithorax/Abdominal-A paralogs is mediated by separate cis-regulatory modules (CRMs). Hox proteins also control the segment-specific number of myoblasts allocated to the DA3 muscle. We conclude that Hox proteins both regulate and contribute to the combinatorial code of transcription factors that specify muscle identity and act at several steps during the muscle-specification process to generate muscle diversity. PMID:20056681
Multi-step shot noise spectrum induced by a local large spin
NASA Astrophysics Data System (ADS)
Niu, Peng-Bin; Shi, Yun-Long; Sun, Zhu; Nie, Yi-Hang
2015-12-01
We use non-equilibrium Green’s function method to analyze the shot noise spectrum of artificial single molecular magnets (ASMM) model in the strong spin-orbit coupling limit in sequential tunneling regime, mainly focusing on the effects of local large spin. In the linear response regime, the shot noise shows 2S + 1 peaks and is strongly spin-dependent. In the nonlinear response regime, one can observe 2S + 1 steps in shot noise and Fano factor. In these steps one can see the significant enhancement effect due to the spin-dependent multi-channel process of local large spin, which reduces electron correlations. Project supported by the National Natural Science Foundation of China (Grant Nos. 11504210, 11504211, 11504212, 11274207, 11274208, 11174115, and 11325417), the Key Program of the Ministry of Education of China (Grant No. 212018), the Scientific and Technological Project of Shanxi Province, China (Grant No. 2015031002-2), the Natural Science Foundation of Shanxi Province, China (Grant Nos. 2013011007-2 and 2013021010-5), and the Outstanding Innovative Teams of Higher Learning Institutions of Shanxi Province, China.
Multi-step regulation of interferon induction by hepatitis C virus.
Oshiumi, Hiroyuki; Funami, Kenji; Aly, Hussein H; Matsumoto, Misako; Seya, Tsukasa
2013-04-01
Acute hepatitis C virus (HCV) infection evokes several distinct innate immune responses in host, but the virus usually propagates by circumventing these responses. Although a replication intermediate double-stranded RNA is produced in infected cells, type I interferon (IFN) induction and immediate cell death are largely blocked in infected cells. In vitro studies suggested that type I and III IFNs are mainly produced in HCV-infected hepatocytes if the MAVS pathway is functional, and dysfunction of this pathway may lead to cellular permissiveness to HCV replication and production. Cellular immunity, including natural killer cell activation and antigen-specific CD8 T-cell proliferation, occurs following innate immune activation in response to HCV, but is often ineffective for eradication of HCV. Constitutive dsRNA stimulation differs in output from type I IFN therapy, which has been an authentic therapy for patients with HCV. Host innate immune responses to HCV RNA/proteins may be associated with progressive hepatic fibrosis and carcinogenesis once persistent HCV infection is established in opposition to the IFN system. Hence, innate RNA sensing exerts pivotal functions against HCV genome replication and host pathogenesis through modulation of the IFN system. Molecules participating in the RIG-I and Toll-like receptor 3 pathways are the main targets for HCV, disabling the anti-viral functions of these IFN-inducing molecules. We discuss the mechanisms that abolish type I and type III IFN production in HCV-infected cells, which may contribute to understanding the mechanism of virus persistence and resistance to the IFN therapy.
The p27Kip1 Tumor Suppressor and Multi-Step Tumorigenesis
2001-08-01
completion of the Celera mouse genome . Sequenced IPCR clones were searched against the Celera database and clones that fell within the same Celera ...in all of the lymphomas containing XPC-1 insertions. There is significant sequence conservation between the murine XPC-1 locus and the syntenic human ...Xq26 region, and sequences homologous to A1464896 and the cloned insertion sites are present in the human Xq26 region with spacing quite similar to
The Multi-Step CADIS method for shutdown dose rate calculations and uncertainty propagation
Ibrahim, Ahmad M.; Peplow, Douglas E.; Grove, Robert E.; ...
2015-12-01
Shutdown dose rate (SDDR) analysis requires (a) a neutron transport calculation to estimate neutron flux fields, (b) an activation calculation to compute radionuclide inventories and associated photon sources, and (c) a photon transport calculation to estimate final SDDR. In some applications, accurate full-scale Monte Carlo (MC) SDDR simulations are needed for very large systems with massive amounts of shielding materials. However, these simulations are impractical because calculation of space- and energy-dependent neutron fluxes throughout the structural materials is needed to estimate distribution of radioisotopes causing the SDDR. Biasing the neutron MC calculation using an importance function is not simple becausemore » it is difficult to explicitly express the response function, which depends on subsequent computational steps. Furthermore, the typical SDDR calculations do not consider how uncertainties in MC neutron calculation impact SDDR uncertainty, even though MC neutron calculation uncertainties usually dominate SDDR uncertainty.« less
The Multi-Step CADIS method for shutdown dose rate calculations and uncertainty propagation
Ibrahim, Ahmad M.; Peplow, Douglas E.; Grove, Robert E.; Peterson, Joshua L.; Johnson, Seth R.
2015-12-01
Shutdown dose rate (SDDR) analysis requires (a) a neutron transport calculation to estimate neutron flux fields, (b) an activation calculation to compute radionuclide inventories and associated photon sources, and (c) a photon transport calculation to estimate final SDDR. In some applications, accurate full-scale Monte Carlo (MC) SDDR simulations are needed for very large systems with massive amounts of shielding materials. However, these simulations are impractical because calculation of space- and energy-dependent neutron fluxes throughout the structural materials is needed to estimate distribution of radioisotopes causing the SDDR. Biasing the neutron MC calculation using an importance function is not simple because it is difficult to explicitly express the response function, which depends on subsequent computational steps. Furthermore, the typical SDDR calculations do not consider how uncertainties in MC neutron calculation impact SDDR uncertainty, even though MC neutron calculation uncertainties usually dominate SDDR uncertainty.
Use of DBMS in Multi-step Information Systems for LANDSAT
NASA Technical Reports Server (NTRS)
Noll, C. E.
1984-01-01
Data are obtained by the thematic mapper on LANDSAT 4 in seven bands and are telemetered and electronically recorded at ground station where the data must be geometrically and rediometrically corrected before a photographic image is produced. Current system characteristics for processing this information are described including the menu for data products reports. The tracking system provides up-to-date and complete information and requires that production stages adhere to the inherent DBMS structure. The concept can be applied to any procedures requiring status information.
Simulation of multi-steps thermal transition in 2D spin-crossover nanoparticles
NASA Astrophysics Data System (ADS)
Jureschi, Catalin-Maricel; Pottier, Benjamin-Louis; Linares, Jorge; Richard Dahoo, Pierre; Alayli, Yasser; Rotaru, Aurelian
2016-04-01
We have used an Ising like model to study the thermal behavior of a 2D spin crossover (SCO) system embedded in a matrix. The interaction parameter between edge SCO molecules and its local environment was included in the standard Ising like model as an additional term. The influence of the system's size and the ratio between the number of edge molecules and the other molecules were also discussed.
Computation of Growth Rates of Random Sequences with Multi-step Memory
NASA Astrophysics Data System (ADS)
Zhang, Chenfei; Lan, Yueheng
2013-02-01
We extend the generating function approach to the computation of growth rate of random Fibonacci sequences with long memory. Functional iteration equations are obtained and its general form is conjectured and proved, based on which an asymptotic representation of the growth rate is obtained. The validity of both the derived and the conjectured formula are verified upon comparison with Monte Carlo simulation. A numerical scheme of the functional iteration is designed and implemented successfully.
A Multi-Step Simulation Approach Toward Secure Fault Tolerant System Evaluation
2010-01-01
Level Dependability Analysis”, IEEE Transactions on Computers, v.46 n.1, p.60-74, January 1997 [11] B. Meyer , Object-Oriented Software Construction...Prentice Hall, 1988 [12] E. N. (Mootaz) Elnozahy , Lorenzo Alvisi , Yi-Min Wang , David B. Johnson, “A survey of rollback-recovery protocols in
Multi-step approach in a complex case of Cushing's syndrome and medullary thyroid carcinoma.
Parenti, G; Nassi, R; Silvestri, S; Bianchi, S; Valeri, A; Manca, G; Mangiafico, S; Ammannati, F; Serio, M; Mannelli, M; Peri, A
2006-02-01
The diagnosis of Cushing's syndrome (CS) may sometimes be cumbersome. In particular, in ACTH-dependent CS it may be difficult to distinguish between the presence of an ACTH-secreting pituitary adenoma and ectopic ACTH and/or CRH secretion. In such instances, the etiology of CS may remain unknown despite extensive diagnostic workout, and the best therapeutic option for each patient has to be determined. We report here the case of a 54-yr-old man affected by ACTH-dependent CS in association with a left adrenal adenoma and medullary thyroid carcinoma (MTC). He presented with clinical features and laboratory indexes of hypercortisolism associated with elevated levels of calcitonin. Ectopic CS due to MTC was reported previously. In our case hypercortisolism persisted after surgical treatment of MTC. Thorough diagnostic assessment was performed, in order to define the aetiology of CS. He was subjected to basal and dynamic hormonal evaluation, including bilateral inferior petrosal sinus sampling. Extensive imaging evaluation was also performed. Overall, the laboratory data together with the results of radiological procedures suggested that CS might be due to inappropriate CRH secretion. However, the source of CRH secretion in this patient remained unknown. It was then decided to remove the left adenomatous adrenal gland. Cortisol level fell and has remained within the normal range nine months after surgery. This case well depicts the complexity of the diagnostic workout, which is needed sometimes to correctly diagnose and treat CS, and suggests that monolateral adrenalectomy may represent, at least temporarily, a reasonable therapeutic option in occult ACTH-dependent hypercortisolism.
Weiss Brennan, Claire V; Walck, Scott D; Swab, Jeffrey J
2014-12-01
A new technique for the preparation of heavily cracked, heavily damaged, brittle materials for examination in a transmission electron microscope (TEM) is described in detail. In this study, cross-sectional TEM samples were prepared from indented silicon carbide (SiC) bulk ceramics, although this technique could also be applied to other brittle and/or multiphase materials. During TEM sample preparation, milling-induced damage must be minimized, since in studying deformation mechanisms, it would be difficult to distinguish deformation-induced cracking from cracking occurring due to the sample preparation. The samples were prepared using a site-specific, two-step ion milling sequence accompanied by epoxy vacuum infiltration into the cracks. This technique allows the heavily cracked, brittle ceramic material to stay intact during sample preparation and also helps preserve the true microstructure of the cracked area underneath the indent. Some preliminary TEM results are given and discussed in regards to deformation studies in ceramic materials. This sample preparation technique could be applied to other cracked and/or heavily damaged materials, including geological materials, archaeological materials, fatigued materials, and corrosion samples.
Optimizing Site Selection in Urban Areas in Northern Switzerland
NASA Astrophysics Data System (ADS)
Plenkers, K.; Kraft, T.; Bethmann, F.; Husen, S.; Schnellmann, M.
2012-04-01
There is a need to observe weak seismic events (M<2) in areas close to potential nuclear-waste repositories or nuclear power plants, in order to analyze the underlying seismo-tectonic processes and estimate their seismic hazard. We are therefore densifying the existing Swiss Digital Seismic Network in northern Switzerland by additional 20 stations. The new network that will be in operation by the end of 2012, aims at observing seismicity in northern Switzerland with a completeness of M_c=1.0 and a location error < 0.5 km in epicenter and < 2 km in focal depth. Monitoring of weak seismic events in this region is challenging, because the area of interest is densely populated and geology is dominated by the Swiss molasse basin. A optimal network-design and a thoughtful choice for station-sites is, therefore, mandatory. To help with decision making we developed a step-wise approach to find the optimum network configuration. Our approach is based on standard network optimization techniques regarding the localization error. As a new feature, our approach uses an ambient noise model to compute expected signal-to-noise ratios for a given site. The ambient noise model uses information on land use and major infrastructures such as highways and train lines. We ran a series of network optimizations with increasing number of stations until the requirements regarding localization error and magnitude of completeness are reached. The resulting network geometry serves as input for the site selection. Site selection is done by using a newly developed multi-step assessment-scheme that takes into account local noise level, geology, infrastructure, and costs necessary to realize the station. The assessment scheme is weighting the different parameters and the most promising sites are identified. In a first step, all potential sites are classified based on information from topographic maps and site inspection. In a second step, local noise conditions are measured at selected sites. We
SOPRA: Scaffolding algorithm for paired reads via statistical optimization
2010-01-01
Background High throughput sequencing (HTS) platforms produce gigabases of short read (<100 bp) data per run. While these short reads are adequate for resequencing applications, de novo assembly of moderate size genomes from such reads remains a significant challenge. These limitations could be partially overcome by utilizing mate pair technology, which provides pairs of short reads separated by a known distance along the genome. Results We have developed SOPRA, a tool designed to exploit the mate pair/paired-end information for assembly of short reads. The main focus of the algorithm is selecting a sufficiently large subset of simultaneously satisfiable mate pair constraints to achieve a balance between the size and the quality of the output scaffolds. Scaffold assembly is presented as an optimization problem for variables associated with vertices and with edges of the contig connectivity graph. Vertices of this graph are individual contigs with edges drawn between contigs connected by mate pairs. Similar graph problems have been invoked in the context of shotgun sequencing and scaffold building for previous generation of sequencing projects. However, given the error-prone nature of HTS data and the fundamental limitations from the shortness of the reads, the ad hoc greedy algorithms used in the earlier studies are likely to lead to poor quality results in the current context. SOPRA circumvents this problem by treating all the constraints on equal footing for solving the optimization problem, the solution itself indicating the problematic constraints (chimeric/repetitive contigs, etc.) to be removed. The process of solving and removing of constraints is iterated till one reaches a core set of consistent constraints. For SOLiD sequencer data, SOPRA uses a dynamic programming approach to robustly translate the color-space assembly to base-space. For assessing the quality of an assembly, we report the no-match/mismatch error rate as well as the rates of various
NASA Astrophysics Data System (ADS)
Siepmann, J. Ilja; Bai, Peng; Tsapatsis, Michael; Knight, Chris; Deem, Michael W.
2015-03-01
Zeolites play numerous important roles in modern petroleum refineries and have the potential to advance the production of fuels and chemical feedstocks from renewable resources. The performance of a zeolite as separation medium and catalyst depends on its framework structure and the type or location of active sites. To date, 213 framework types have been synthesized and >330000 thermodynamically accessible zeolite structures have been predicted. Hence, identification of optimal zeolites for a given application from the large pool of candidate structures is attractive for accelerating the pace of materials discovery. Here we identify, through a large-scale, multi-step computational screening process, promising zeolite structures for two energy-related applications: the purification of ethanol beyond the ethanol/water azeotropic concentration in a single separation step from fermentation broths and the hydroisomerization of alkanes with 18-30 carbon atoms encountered in petroleum refining. These results demonstrate that predictive modeling and data-driven science can now be applied to solve some of the most challenging separation problems involving highly non-ideal mixtures and highly articulated compounds. Financial support from the Department of Energy Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences under Award DE-FG02-12ER16362 is gratefully acknowledged.
Optimization of composite structures
NASA Technical Reports Server (NTRS)
Stroud, W. J.
1982-01-01
Structural optimization is introduced and examples which illustrate potential problems associated with optimized structures are presented. Optimized structures may have very low load carrying ability for an off design condition. They tend to have multiple modes of failure occurring simultaneously and can, therefore, be sensitive to imperfections. Because composite materials provide more design variables than do metals, they allow for more refined tailoring and more extensive optimization. As a result, optimized composite structures can be especially susceptible to these problems.
Particle Swarm Optimization Toolbox
NASA Technical Reports Server (NTRS)
Grant, Michael J.
2010-01-01
The Particle Swarm Optimization Toolbox is a library of evolutionary optimization tools developed in the MATLAB environment. The algorithms contained in the library include a genetic algorithm (GA), a single-objective particle swarm optimizer (SOPSO), and a multi-objective particle swarm optimizer (MOPSO). Development focused on both the SOPSO and MOPSO. A GA was included mainly for comparison purposes, and the particle swarm optimizers appeared to perform better for a wide variety of optimization problems. All algorithms are capable of performing unconstrained and constrained optimization. The particle swarm optimizers are capable of performing single and multi-objective optimization. The SOPSO and MOPSO algorithms are based on swarming theory and bird-flocking patterns to search the trade space for the optimal solution or optimal trade in competing objectives. The MOPSO generates Pareto fronts for objectives that are in competition. A GA, based on Darwin evolutionary theory, is also included in the library. The GA consists of individuals that form a population in the design space. The population mates to form offspring at new locations in the design space. These offspring contain traits from both of the parents. The algorithm is based on this combination of traits from parents to hopefully provide an improved solution than either of the original parents. As the algorithm progresses, individuals that hold these optimal traits will emerge as the optimal solutions. Due to the generic design of all optimization algorithms, each algorithm interfaces with a user-supplied objective function. This function serves as a "black-box" to the optimizers in which the only purpose of this function is to evaluate solutions provided by the optimizers. Hence, the user-supplied function can be numerical simulations, analytical functions, etc., since the specific detail of this function is of no concern to the optimizer. These algorithms were originally developed to support entry
Ridzal, Danis
2007-03-01
Aristos is a Trilinos package for nonlinear continuous optimization, based on full-space sequential quadratic programming (SQP) methods. Aristos is specifically designed for the solution of large-scale constrained optimization problems in which the linearized constraint equations require iterative (i.e. inexact) linear solver techniques. Aristos' unique feature is an efficient handling of inexactness in linear system solves. Aristos currently supports the solution of equality-constrained convex and nonconvex optimization problems. It has been used successfully in the area of PDE-constrained optimization, for the solution of nonlinear optimal control, optimal design, and inverse problems.
Multidisciplinary Optimization for Aerospace Using Genetic Optimization
NASA Technical Reports Server (NTRS)
Pak, Chan-gi; Hahn, Edward E.; Herrera, Claudia Y.
2007-01-01
In support of the ARMD guidelines NASA's Dryden Flight Research Center is developing a multidisciplinary design and optimization tool This tool will leverage existing tools and practices, and allow the easy integration and adoption of new state-of-the-art software. Optimization has made its way into many mainstream applications. For example NASTRAN(TradeMark) has its solution sequence 200 for Design Optimization, and MATLAB(TradeMark) has an Optimization Tool box. Other packages, such as ZAERO(TradeMark) aeroelastic panel code and the CFL3D(TradeMark) Navier-Stokes solver have no built in optimizer. The goal of the tool development is to generate a central executive capable of using disparate software packages ina cross platform network environment so as to quickly perform optimization and design tasks in a cohesive streamlined manner. A provided figure (Figure 1) shows a typical set of tools and their relation to the central executive. Optimization can take place within each individual too, or in a loop between the executive and the tool, or both.
Lokutsievskiy, Lev V
2011-05-31
This paper is concerned with the optimal search of an object at rest with unknown exact position in the n-dimensional space. A necessary condition for optimality of a trajectory is obtained. An explicit form of a differential equation for an optimal trajectory is found while searching over R-strongly convex sets. An existence theorem is also established. Bibliography: 8 titles.
Aircraft configuration optimization including optimized flight profiles
NASA Technical Reports Server (NTRS)
Mccullers, L. A.
1984-01-01
The Flight Optimization System (FLOPS) is an aircraft configuration optimization program developed for use in conceptual design of new aircraft and in the assessment of the impact of advanced technology. The modular makeup of the program is illustrated. It contains modules for preliminary weights estimation, preliminary aerodynamics, detailed mission performance, takeoff and landing, and execution control. An optimization module is used to drive the overall design and in defining optimized profiles in the mission performance. Propulsion data, usually received from engine manufacturers, are used in both the mission performance and the takeoff and landing analyses. Although executed as a single in-core program, the modules are stored separately so that the user may select the appropriate modules (e.g., fighter weights versus transport weights) or leave out modules that are not needed.
Face sketch synthesis via sparse representation-based greedy search.
Shengchuan Zhang; Xinbo Gao; Nannan Wang; Jie Li; Mingjin Zhang
2015-08-01
Face sketch synthesis has wide applications in digital entertainment and law enforcement. Although there is much research on face sketch synthesis, most existing algorithms cannot handle some nonfacial factors, such as hair style, hairpins, and glasses if these factors are excluded in the training set. In addition, previous methods only work on well controlled conditions and fail on images with different backgrounds and sizes as the training set. To this end, this paper presents a novel method that combines both the similarity between different image patches and prior knowledge to synthesize face sketches. Given training photo-sketch pairs, the proposed method learns a photo patch feature dictionary from the training photo patches and replaces the photo patches with their sparse coefficients during the searching process. For a test photo patch, we first obtain its sparse coefficient via the learnt dictionary and then search its nearest neighbors (candidate patches) in the whole training photo patches with sparse coefficients. After purifying the nearest neighbors with prior knowledge, the final sketch corresponding to the test photo can be obtained by Bayesian inference. The contributions of this paper are as follows: 1) we relax the nearest neighbor search area from local region to the whole image without too much time consuming and 2) our method can produce nonfacial factors that are not contained in the training set and is robust against image backgrounds and can even ignore the alignment and image size aspects of test photos. Our experimental results show that the proposed method outperforms several state-of-the-arts in terms of perceptual and objective metrics.
Greedy Learning of Graphical Models with Small Girth
2013-01-01
with the Department of Electrical and Computer Engineering , The University of Texas at Austin, USA, Emails: avik@utexas.edu, sanghavi@mail.utexas.edu...61, pp. 401-425, 1996. [7] A. Dobra , C. Hans, B. Jones, J. R. Nevins, G. Yao, and M. West, “Sparse graphical models for exploring gene expression data
GPSR: Greedy Perimeter Stateless Routing for Wireless Networks
2005-01-01
use sim- ulation parameters identical to a subset of those used by Broch et al. [4]. Our simulations are for networks of 50, 112, and 200 nodes with...as they are the most demanding of a routing algorithm. Broch at al. also simu- lated 300-, 600-, and 900-second pause times, perhaps in large part...sending nodes. Each CBR flow sends at 2 Kbps, and uses 64-byte packets. Broch et al. simulated a wider range of flow counts (10, 20, and 30 flows); we
Mikhalevich, V.S.; Sergienko, I.V.; Zadiraka, V.K.; Babich, M.D.
1994-11-01
This article examines some topics of optimization of computations, which have been discussed at 25 seminar-schools and symposia organized by the V.M. Glushkov Institute of Cybernetics of the Ukrainian Academy of Sciences since 1969. We describe the main directions in the development of computational mathematics and present some of our own results that reflect a certain design conception of speed-optimal and accuracy-optimal (or nearly optimal) algorithms for various classes of problems, as well as a certain approach to optimization of computer computations.
McGuire-Snieckus, Rebecca
2014-01-01
Optimism is generally accepted by psychiatrists, psychologists and other caring professionals as a feature of mental health. Interventions typically rely on cognitive-behavioural tools to encourage individuals to ‘stop negative thought cycles’ and to ‘challenge unhelpful thoughts’. However, evidence suggests that most individuals have persistent biases of optimism and that excessive optimism is not conducive to mental health. How helpful is it to facilitate optimism in individuals who are likely to exhibit biases of optimism already? By locating the cause of distress at the individual level and ‘unhelpful’ cognitions, does this minimise wider systemic social and economic influences on mental health? PMID:25237497
NASA Technical Reports Server (NTRS)
Venter, Gerhard; Sobieszczanski-Sobieski Jaroslaw
2002-01-01
The purpose of this paper is to show how the search algorithm known as particle swarm optimization performs. Here, particle swarm optimization is applied to structural design problems, but the method has a much wider range of possible applications. The paper's new contributions are improvements to the particle swarm optimization algorithm and conclusions and recommendations as to the utility of the algorithm, Results of numerical experiments for both continuous and discrete applications are presented in the paper. The results indicate that the particle swarm optimization algorithm does locate the constrained minimum design in continuous applications with very good precision, albeit at a much higher computational cost than that of a typical gradient based optimizer. However, the true potential of particle swarm optimization is primarily in applications with discrete and/or discontinuous functions and variables. Additionally, particle swarm optimization has the potential of efficient computation with very large numbers of concurrently operating processors.
Integrated controls design optimization
Lou, Xinsheng; Neuschaefer, Carl H.
2015-09-01
A control system (207) for optimizing a chemical looping process of a power plant includes an optimizer (420), an income algorithm (230) and a cost algorithm (225) and a chemical looping process models. The process models are used to predict the process outputs from process input variables. Some of the process in puts and output variables are related to the income of the plant; and some others are related to the cost of the plant operations. The income algorithm (230) provides an income input to the optimizer (420) based on a plurality of input parameters (215) of the power plant. The cost algorithm (225) provides a cost input to the optimizer (420) based on a plurality of output parameters (220) of the power plant. The optimizer (420) determines an optimized operating parameter solution based on at least one of the income input and the cost input, and supplies the optimized operating parameter solution to the power plant.
Supercomputer optimizations for stochastic optimal control applications
NASA Technical Reports Server (NTRS)
Chung, Siu-Leung; Hanson, Floyd B.; Xu, Huihuang
1991-01-01
Supercomputer optimizations for a computational method of solving stochastic, multibody, dynamic programming problems are presented. The computational method is valid for a general class of optimal control problems that are nonlinear, multibody dynamical systems, perturbed by general Markov noise in continuous time, i.e., nonsmooth Gaussian as well as jump Poisson random white noise. Optimization techniques for vector multiprocessors or vectorizing supercomputers include advanced data structures, loop restructuring, loop collapsing, blocking, and compiler directives. These advanced computing techniques and superconducting hardware help alleviate Bellman's curse of dimensionality in dynamic programming computations, by permitting the solution of large multibody problems. Possible applications include lumped flight dynamics models for uncertain environments, such as large scale and background random aerospace fluctuations.
Wheeler, Ward C
2003-08-01
The problem of determining the minimum cost hypothetical ancestral sequences for a given cladogram is known to be NP-complete (Wang and Jiang, 1994). Traditionally, point estimations of hypothetical ancestral sequences have been used to gain heuristic, upper bounds on cladogram cost. These include procedures with such diverse approaches as non-additive optimization of multiple sequence alignment, direct optimization (Wheeler, 1996), and fixed-state character optimization (Wheeler, 1999). A method is proposed here which, by extending fixed-state character optimization, replaces the estimation process with a search. This form of optimization examines a diversity of potential state solutions for cost-efficient hypothetical ancestral sequences and can result in greatly more parsimonious cladograms. Additionally, such an approach can be applied to other NP-complete phylogenetic optimization problems such as genomic break-point analysis.
NASA Technical Reports Server (NTRS)
Wheeler, Ward C.
2003-01-01
The problem of determining the minimum cost hypothetical ancestral sequences for a given cladogram is known to be NP-complete (Wang and Jiang, 1994). Traditionally, point estimations of hypothetical ancestral sequences have been used to gain heuristic, upper bounds on cladogram cost. These include procedures with such diverse approaches as non-additive optimization of multiple sequence alignment, direct optimization (Wheeler, 1996), and fixed-state character optimization (Wheeler, 1999). A method is proposed here which, by extending fixed-state character optimization, replaces the estimation process with a search. This form of optimization examines a diversity of potential state solutions for cost-efficient hypothetical ancestral sequences and can result in greatly more parsimonious cladograms. Additionally, such an approach can be applied to other NP-complete phylogenetic optimization problems such as genomic break-point analysis. c2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.
Zhou, Zhi; de Bedout, Juan Manuel; Kern, John Michael; Biyik, Emrah; Chandra, Ramu Sharat
2013-01-22
A system for optimizing customer utility usage in a utility network of customer sites, each having one or more utility devices, where customer site is communicated between each of the customer sites and an optimization server having software for optimizing customer utility usage over one or more networks, including private and public networks. A customer site model for each of the customer sites is generated based upon the customer site information, and the customer utility usage is optimized based upon the customer site information and the customer site model. The optimization server can be hosted by an external source or within the customer site. In addition, the optimization processing can be partitioned between the customer site and an external source.
Optimization and optimal statistics in neuroscience
NASA Astrophysics Data System (ADS)
Brookings, Ted
Complex systems have certain common properties, with power law statistics being nearly ubiquitous. Despite this commonality, we show that a variety of mechanisms can be responsible for complexity, illustrated by the example of a lattice on a Cayley Tree. Because of this, analysis must probe more deeply than merely looking for power laws, instead details of the dynamics must be examined. We show how optimality---a frequently-overlooked source of complexity---can produce typical features such as power laws, and describe inherent trade-offs in optimal systems, such as performance vs. robustness to rare disturbances. When applied to biological systems such as the nervous system, optimality is particularly appropriate because so many systems have identifiable purpose. We show that the "grid cells" in rats are extremely efficient in storing position information. Assuming the system to be optimal allows us to describe the number and organization of grid cells. By analyzing systems from an optimal perspective provides insights that permit description of features that would otherwise be difficult to observe. As well, careful analysis of complex systems requires diligent avoidance of assumptions that are unnecessary or unsupported. Attributing unwarranted meaning to ambiguous features, or assuming the existence of a priori constraints may quickly lead to faulty results. By eschewing unwarranted and unnecessary assumptions about the distribution of neural activity and instead carefully integrating information from EEG and fMRI, we are able to dramatically improve the quality of source-localization. Thus maintaining a watchful eye towards principles of optimality, while avoiding unnecessary statistical assumptions is an effective theoretical approach to neuroscience.
Homotopy optimization methods for global optimization.
Dunlavy, Daniel M.; O'Leary, Dianne P. (University of Maryland, College Park, MD)
2005-12-01
We define a new method for global optimization, the Homotopy Optimization Method (HOM). This method differs from previous homotopy and continuation methods in that its aim is to find a minimizer for each of a set of values of the homotopy parameter, rather than to follow a path of minimizers. We define a second method, called HOPE, by allowing HOM to follow an ensemble of points obtained by perturbation of previous ones. We relate this new method to standard methods such as simulated annealing and show under what circumstances it is superior. We present results of extensive numerical experiments demonstrating performance of HOM and HOPE.
Conceptual design optimization study
NASA Technical Reports Server (NTRS)
Hollowell, S. J.; Beeman, E. R., II; Hiyama, R. M.
1990-01-01
The feasibility of applying multilevel functional decomposition and optimization techniques to conceptual design of advanced fighter aircraft was investigated. Applying the functional decomposition techniques to the conceptual design phase appears to be feasible. The initial implementation of the modified design process will optimize wing design variables. A hybrid approach, combining functional decomposition techniques for generation of aerodynamic and mass properties linear sensitivity derivatives with existing techniques for sizing mission performance and optimization, is proposed.
Control and optimization system
Xinsheng, Lou
2013-02-12
A system for optimizing a power plant includes a chemical loop having an input for receiving an input parameter (270) and an output for outputting an output parameter (280), a control system operably connected to the chemical loop and having a multiple controller part (230) comprising a model-free controller. The control system receives the output parameter (280), optimizes the input parameter (270) based on the received output parameter (280), and outputs an optimized input parameter (270) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.
Elastic swimming I: Optimization
NASA Astrophysics Data System (ADS)
Lauga, Eric; Yu, Tony; Hosoi, Anette
2006-03-01
We consider the problem of swimming at low Reynolds number by oscillating an elastic filament in a viscous liquid, as investigated by Wiggins and Goldstein (1998, Phys Rev Lett). In this first part of the study, we characterize the optimal forcing conditions of the swimming strategy and its optimal geometrical characteristics.
Optimal synchronization in space.
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) proportional to l(-alpha), with exponents alpha 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.
Optimal Limited Contingency Planning
NASA Technical Reports Server (NTRS)
Meuleau, Nicolas; Smith, David E.
2003-01-01
For a given problem, the optimal Markov policy over a finite horizon is a conditional plan containing a potentially large number of branches. However, there are applications where it is desirable to strictly limit the number of decision points and branches in a plan. This raises the question of how one goes about finding optimal plans containing only a limited number of branches. In this paper, we present an any-time algorithm for optimal k-contingency planning. It is the first optimal algorithm for limited contingency planning that is not an explicit enumeration of possible contingent plans. By modelling the problem as a partially observable Markov decision process, it implements the Bellman optimality principle and prunes the solution space. We present experimental results of applying this algorithm to some simple test cases.
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.
Algorithms for bilevel optimization
NASA Technical Reports Server (NTRS)
Alexandrov, Natalia; Dennis, J. E., Jr.
1994-01-01
General multilevel nonlinear optimization problems arise in design of complex systems and can be used as a means of regularization for multi-criteria optimization problems. Here, for clarity in displaying our ideas, we restrict ourselves to general bi-level optimization problems, and we present two solution approaches. Both approaches use a trust-region globalization strategy, and they can be easily extended to handle the general multilevel problem. We make no convexity assumptions, but we do assume that the problem has a nondegenerate feasible set. We consider necessary optimality conditions for the bi-level problem formulations and discuss results that can be extended to obtain multilevel optimization formulations with constraints at each level.
Optimal operational conditions for the electrochemical regeneration of a soil washing EDTA solution.
Cesaro, Raffaele; Esposito, Giovanni
2009-02-01
The present research deals with the optimization of the operating parameters (cathode replacement time, hydraulic retention time, current intensity and pH) of an electrochemical process aimed at the regeneration of a soil washing EDTA solution used for heavy metal extraction from a natural contaminated soil (excavated from Bellolampo, Palermo, Italy), which was vastly polluted with Cu (59 261.0 mg kg(-1)), Pb (14 178.1 mg kg(-1)) and Zn (14 084.9 mg kg(-1)). The electrolytic regeneration of the exhausted washing solution was performed in a laboratory scale electrolytic cell with 50 ml each cathodic and anodic chambers divided by a cation exchange membrane. Experiments II and III showed maximum Cu and Zn removal efficiencies from the EDTA solution, of 99.2+/-0.2 and 31.5+/-9.3%, respectively, when a current intensity of 0.25 A and a hydraulic retention time of 60 min were applied to the electrolytic cell, while the maximum Pb removal efficiency of 70.9+/-4.6% was obtained with a current intensity of 1.25 A and a hydraulic retention time of 60 min. During Experiment I the overall heavy metals removal efficiency was stable and close to 90% up to 20 h, while decreased to values lower than 80% after 40 h, indicating the occurrence of a significant saturation of the cathode graphite bed between 20 and 40 h. The capability of the regenerated EDTA solution to treat heavy metals polluted soils was tested in further experiments applying both a single and a multi-step washing treatment procedure. In particular, the latter showed the feasibility to increase heavy metal soil extractions over subsequent washing steps with Cu, Pb and Zn total removal efficiencies of 52.6, 100.0 and 41.3%, respectively.
Avron, J E; Elgart, A; Graf, G M; Sadun, L
2001-12-03
We study adiabatic quantum pumps on time scales that are short relative to the cycle of the pump. In this regime the pump is characterized by the matrix of energy shift which we introduce as the dual to Wigner's time delay. The energy shift determines the charge transport, the dissipation, the noise, and the entropy production. We prove a general lower bound on dissipation in a quantum channel and define optimal pumps as those that saturate the bound. We give a geometric characterization of optimal pumps and show that they are noiseless and transport integral charge in a cycle. Finally we discuss an example of an optimal pump related to the Hall effect.
Optimal control computer programs
NASA Technical Reports Server (NTRS)
Kuo, F.
1992-01-01
The solution of the optimal control problem, even with low order dynamical systems, can usually strain the analytical ability of most engineers. The understanding of this subject matter, therefore, would be greatly enhanced if a software package existed that could simulate simple generic problems. Surprisingly, despite a great abundance of commercially available control software, few, if any, address the part of optimal control in its most generic form. The purpose of this paper is, therefore, to present a simple computer program that will perform simulations of optimal control problems that arise from the first necessary condition and the Pontryagin's maximum principle.
Optimal domain decomposition strategies
NASA Technical Reports Server (NTRS)
Yoon, Yonghyun; Soni, Bharat K.
1995-01-01
The primary interest of the authors is in the area of grid generation, in particular, optimal domain decomposition about realistic configurations. A grid generation procedure with optimal blocking strategies has been developed to generate multi-block grids for a circular-to-rectangular transition duct. The focus of this study is the domain decomposition which optimizes solution algorithm/block compatibility based on geometrical complexities as well as the physical characteristics of flow field. The progress realized in this study is summarized in this paper.
1979-12-01
OPTIMAL LINEAR CONTROL C.A. HARVEY M.G. SAFO NOV G. STEIN J.C. DOYLE HONEYWELL SYSTEMS & RESEARCH CENTER j 2600 RIDGWAY PARKWAY j [ MINNEAPOLIS...RECIPIENT’S CAT ALC-’ W.IMIJUff’? * J~’ CR2 15-238-4F TP P EI)ŕll * (~ Optimal Linear Control ~iOGRPR UBA m a M.G Lnar o Con_ _ _ _ _ _ R PORT__ _ _ I RE...Characterizations of optimal linear controls have been derived, from which guides for selecting the structure of the control system and the weights in
Contingency contractor optimization.
Gearhart, Jared Lee; Adair, Kristin Lynn; Jones, Katherine A.; Bandlow, Alisa; Detry, Richard Joseph; Durfee, Justin David.; Jones, Dean A.; Martin, Nathaniel; Nanco, Alan Stewart; Nozick, Linda Karen
2013-06-01
The goal of Phase 3 the OSD ATL Contingency Contractor Optimization (CCO) project is to create an engineering prototype of a tool for the contingency contractor element of total force planning during the Support for Strategic Analysis (SSA). An optimization model was developed to determine the optimal mix of military, Department of Defense (DoD) civilians, and contractors that accomplishes a set of user defined mission requirements at the lowest possible cost while honoring resource limitations and manpower use rules. An additional feature allows the model to understand the variability of the Total Force Mix when there is uncertainty in mission requirements.
Contingency contractor optimization.
Gearhart, Jared Lee; Adair, Kristin Lynn; Jones, Katherine A.; Bandlow, Alisa; Durfee, Justin David.; Jones, Dean A.; Martin, Nathaniel; Detry, Richard Joseph; Nanco, Alan Stewart; Nozick, Linda Karen
2013-10-01
The goal of Phase 3 the OSD ATL Contingency Contractor Optimization (CCO) project is to create an engineering prototype of a tool for the contingency contractor element of total force planning during the Support for Strategic Analysis (SSA). An optimization model was developed to determine the optimal mix of military, Department of Defense (DoD) civilians, and contractors that accomplishes a set of user defined mission requirements at the lowest possible cost while honoring resource limitations and manpower use rules. An additional feature allows the model to understand the variability of the Total Force Mix when there is uncertainty in mission requirements.
Denis Rldzal, Drew Kouri
2014-05-13
ROL provides interfaces to and implementations of algorithms for gradient-based unconstrained and constrained optimization. ROL can be used to optimize the response of any client simulation code that evaluates scalar-valued response functions. If the client code can provide gradient information for the response function, ROL will take advantage of it, resulting in faster runtimes. ROL's interfaces are matrix-free, in other words ROL only uses evaluations of scalar-valued and vector-valued functions. ROL can be used to solve optimal design problems and inverse problems based on a variety of simulation software.
Alicia Hofler; Pavel Evtushenko
2007-07-03
Injector gun design is an iterative process where the designer optimizes a few nonlinearly interdependent beam parameters to achieve the required beam quality for a particle accelerator. Few tools exist to automate the optimization process and thoroughly explore the parameter space. The challenging beam requirements of new accelerator applications such as light sources and electron cooling devices drive the development of RF and SRF photo injectors. A genetic algorithm (GA) has been successfully used to optimize DC photo injector designs at Cornell University [1] and Jefferson Lab [2]. We propose to apply GA techniques to the design of RF and SRF gun injectors. In this paper, we report on the initial phase of the study where we model and optimize a system that has been benchmarked with beam measurements and simulation.
Flyby Geometry Optimization Tool
NASA Technical Reports Server (NTRS)
Karlgaard, Christopher D.
2007-01-01
The Flyby Geometry Optimization Tool is a computer program for computing trajectories and trajectory-altering impulsive maneuvers for spacecraft used in radio relay of scientific data to Earth from an exploratory airplane flying in the atmosphere of Mars.
Optimizing influenza vaccine distribution.
Medlock, Jan; Galvani, Alison P
2009-09-25
The criteria to assess public health policies are fundamental to policy optimization. Using a model parametrized with survey-based contact data and mortality data from influenza pandemics, we determined optimal vaccine allocation for five outcome measures: deaths, infections, years of life lost, contingent valuation, and economic costs. We find that optimal vaccination is achieved by prioritization of schoolchildren and adults aged 30 to 39 years. Schoolchildren are most responsible for transmission, and their parents serve as bridges to the rest of the population. Our results indicate that consideration of age-specific transmission dynamics is paramount to the optimal allocation of influenza vaccines. We also found that previous and new recommendations from the U.S. Centers for Disease Control and Prevention both for the novel swine-origin influenza and, particularly, for seasonal influenza, are suboptimal for all outcome measures.
General shape optimization capability
NASA Technical Reports Server (NTRS)
Chargin, Mladen K.; Raasch, Ingo; Bruns, Rudolf; Deuermeyer, Dawson
1991-01-01
A method is described for calculating shape sensitivities, within MSC/NASTRAN, in a simple manner without resort to external programs. The method uses natural design variables to define the shape changes in a given structure. Once the shape sensitivities are obtained, the shape optimization process is carried out in a manner similar to property optimization processes. The capability of this method is illustrated by two examples: the shape optimization of a cantilever beam with holes, loaded by a point load at the free end (with the shape of the holes and the thickness of the beam selected as the design variables), and the shape optimization of a connecting rod subjected to several different loading and boundary conditions.
Kawase, Mitsuhiro
2009-11-22
The zipped file contains a directory of data and routines used in the NNMREC turbine depth optimization study (Kawase et al., 2011), and calculation results thereof. For further info, please contact Mitsuhiro Kawase at kawase@uw.edu. Reference: Mitsuhiro Kawase, Patricia Beba, and Brian Fabien (2011), Finding an Optimal Placement Depth for a Tidal In-Stream Conversion Device in an Energetic, Baroclinic Tidal Channel, NNMREC Technical Report.
NASA Technical Reports Server (NTRS)
Hart-Smith, L. J.; Bunin, B. L.; Watts, D. J.
1986-01-01
Computer technique aids joint optimization. Load-sharing between fasteners in multirow bolted composite joints computed by nonlinear-analysis computer program. Input to analysis was load-deflection data from 180 specimens tested as part of program to develop technology of structural joints for advanced transport aircraft. Bolt design optimization technique applicable to major joints in composite materials for primary and secondary structures and generally applicable for metal joints as well.
Optimization Of Simulated Trajectories
NASA Technical Reports Server (NTRS)
Brauer, Garry L.; Olson, David W.; Stevenson, Robert
1989-01-01
Program To Optimize Simulated Trajectories (POST) provides ability to target and optimize trajectories of point-mass powered or unpowered vehicle operating at or near rotating planet. Used successfully to solve wide variety of problems in mechanics of atmospheric flight and transfer between orbits. Generality of program demonstrated by its capability to simulate up to 900 distinct trajectory phases, including generalized models of planets and vehicles. VAX version written in FORTRAN 77 and CDC version in FORTRAN V.
Modeling using optimization routines
NASA Technical Reports Server (NTRS)
Thomas, Theodore
1995-01-01
Modeling using mathematical optimization dynamics is a design tool used in magnetic suspension system development. MATLAB (software) is used to calculate minimum cost and other desired constraints. The parameters to be measured are programmed into mathematical equations. MATLAB will calculate answers for each set of inputs; inputs cover the boundary limits of the design. A Magnetic Suspension System using Electromagnets Mounted in a Plannar Array is a design system that makes use of optimization modeling.
Introduction: optimization in networks.
Motter, Adilson E; Toroczkai, Zoltan
2007-06-01
The recent surge in the network modeling of complex systems has set the stage for a new era in the study of fundamental and applied aspects of optimization in collective behavior. This Focus Issue presents an extended view of the state of the art in this field and includes articles from a large variety of domains in which optimization manifests itself, including physical, biological, social, and technological networked systems.
Cyclone performance and optimization
Leith, D.
1990-09-15
The objectives of this project are: to characterize the gas flow pattern within cyclones, to revise the theory for cyclone performance on the basis of these findings, and to design and test cyclones whose dimensions have been optimized using revised performance theory. This work is important because its successful completion will aid in the technology for combustion of coal in pressurized, fluidized beds. This quarter, an empirical model for predicting pressure drop across a cyclone was developed through a statistical analysis of pressure drop data for 98 cyclone designs. The model is shown to perform better than the pressure drop models of First (1950), Alexander (1949), Barth (1956), Stairmand (1949), and Shepherd-Lapple (1940). This model is used with the efficiency model of Iozia and Leith (1990) to develop an optimization curve which predicts the minimum pressure drop and the dimension rations of the optimized cyclone for a given aerodynamic cut diameter, d{sub 50}. The effect of variation in cyclone height, cyclone diameter, and flow on the optimization curve is determined. The optimization results are used to develop a design procedure for optimized cyclones. 37 refs., 10 figs., 4 tabs.
Regularizing portfolio optimization
NASA Astrophysics Data System (ADS)
Still, Susanne; Kondor, Imre
2010-07-01
The optimization of large portfolios displays an inherent instability due to estimation error. This poses a fundamental problem, because solutions that are not stable under sample fluctuations may look optimal for a given sample, but are, in effect, very far from optimal with respect to the average risk. In this paper, we approach the problem from the point of view of statistical learning theory. The occurrence of the instability is intimately related to over-fitting, which can be avoided using known regularization methods. We show how regularized portfolio optimization with the expected shortfall as a risk measure is related to support vector regression. The budget constraint dictates a modification. We present the resulting optimization problem and discuss the solution. The L2 norm of the weight vector is used as a regularizer, which corresponds to a diversification 'pressure'. This means that diversification, besides counteracting downward fluctuations in some assets by upward fluctuations in others, is also crucial because it improves the stability of the solution. The approach we provide here allows for the simultaneous treatment of optimization and diversification in one framework that enables the investor to trade off between the two, depending on the size of the available dataset.
NASA Astrophysics Data System (ADS)
Wecker, Dave; Hastings, Matthew B.; Troyer, Matthias
2016-08-01
We study a variant of the quantum approximate optimization algorithm [E. Farhi, J. Goldstone, and S. Gutmann, arXiv:1411.4028] with a slightly different parametrization and a different objective: rather than looking for a state which approximately solves an optimization problem, our goal is to find a quantum algorithm that, given an instance of the maximum 2-satisfiability problem (MAX-2-SAT), will produce a state with high overlap with the optimal state. Using a machine learning approach, we chose a "training set" of instances and optimized the parameters to produce a large overlap for the training set. We then tested these optimized parameters on a larger instance set. As a training set, we used a subset of the hard instances studied by Crosson, Farhi, C. Y.-Y. Lin, H.-H. Lin, and P. Shor (CFLLS) (arXiv:1401.7320). When tested, on the full set, the parameters that we find produce a significantly larger overlap than the optimized annealing times of CFLLS. Testing on other random instances from 20 to 28 bits continues to show improvement over annealing, with the improvement being most notable on the hardest instances. Further tests on instances of MAX-3-SAT also showed improvement on the hardest instances. This algorithm may be a possible application for near-term quantum computers with limited coherence times.
NASA Technical Reports Server (NTRS)
Rasmussen, John
1990-01-01
Structural optimization has attracted the attention since the days of Galileo. Olhoff and Taylor have produced an excellent overview of the classical research within this field. However, the interest in structural optimization has increased greatly during the last decade due to the advent of reliable general numerical analysis methods and the computer power necessary to use them efficiently. This has created the possibility of developing general numerical systems for shape optimization. Several authors, eg., Esping; Braibant & Fleury; Bennet & Botkin; Botkin, Yang, and Bennet; and Stanton have published practical and successful applications of general optimization systems. Ding and Homlein have produced extensive overviews of available systems. Furthermore, a number of commercial optimization systems based on well-established finite element codes have been introduced. Systems like ANSYS, IDEAS, OASIS, and NISAOPT are widely known examples. In parallel to this development, the technology of computer aided design (CAD) has gained a large influence on the design process of mechanical engineering. The CAD technology has already lived through a rapid development driven by the drastically growing capabilities of digital computers. However, the systems of today are still considered as being only the first generation of a long row of computer integrated manufacturing (CIM) systems. These systems to come will offer an integrated environment for design, analysis, and fabrication of products of almost any character. Thus, the CAD system could be regarded as simply a database for geometrical information equipped with a number of tools with the purpose of helping the user in the design process. Among these tools are facilities for structural analysis and optimization as well as present standard CAD features like drawing, modeling, and visualization tools. The state of the art of structural optimization is that a large amount of mathematical and mechanical techniques are
Colas, Cyril; Garcia, Patrice; Popot, Marie-Agnès; Bonnaire, Yves; Bouchonnet, Stéphane
2008-02-01
Solid-phase extraction cartridges among those usually used for screening in horse doping analyses are tested to optimize the extraction of harpagoside (HS), harpagide (HG), and 8-para-coumaroyl harpagide (8PCHG) from plasma and urine. Extracts are analyzed by liquid chromatography coupled with multi-step tandem mass spectrometry. The extraction process retained for plasma applies BondElut PPL cartridges and provides extraction recoveries between 91% and 93%, with RSD values between 8 and 13% at 0.5 ng/mL. Two different procedures are needed to extract analytes from urine. HS and 8PCHG are extracted using AbsElut Nexus cartridges, with recoveries of 85% and 77%, respectively (RSD between 7% and 19%). The extraction of HG involves the use of two cartridges: BondElut PPL and BondElut C18 HF, with recovery of 75% and RSD between 14% and 19%. The applicability of the extraction methods is determined on authentic equine plasma and urine samples after harpagophytum or harpagoside administration.
Optimized Kernel Entropy Components.
Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gomez-Chova, Luis; Camps-Valls, Gustau
2016-02-25
This brief addresses two main issues of the standard kernel entropy component analysis (KECA) algorithm: the optimization of the kernel decomposition and the optimization of the Gaussian kernel parameter. KECA roughly reduces to a sorting of the importance of kernel eigenvectors by entropy instead of variance, as in the kernel principal components analysis. In this brief, we propose an extension of the KECA method, named optimized KECA (OKECA), that directly extracts the optimal features retaining most of the data entropy by means of compacting the information in very few features (often in just one or two). The proposed method produces features which have higher expressive power. In particular, it is based on the independent component analysis framework, and introduces an extra rotation to the eigen decomposition, which is optimized via gradient-ascent search. This maximum entropy preservation suggests that OKECA features are more efficient than KECA features for density estimation. In addition, a critical issue in both the methods is the selection of the kernel parameter, since it critically affects the resulting performance. Here, we analyze the most common kernel length-scale selection criteria. The results of both the methods are illustrated in different synthetic and real problems. Results show that OKECA returns projections with more expressive power than KECA, the most successful rule for estimating the kernel parameter is based on maximum likelihood, and OKECA is more robust to the selection of the length-scale parameter in kernel density estimation.
Optimization of Heat Exchangers
Ivan Catton
2010-10-01
The objective of this research is to develop tools to design and optimize heat exchangers (HE) and compact heat exchangers (CHE) for intermediate loop heat transport systems found in the very high temperature reator (VHTR) and other Generation IV designs by addressing heat transfer surface augmentation and conjugate modeling. To optimize heat exchanger, a fast running model must be created that will allow for multiple designs to be compared quickly. To model a heat exchanger, volume averaging theory, VAT, is used. VAT allows for the conservation of mass, momentum and energy to be solved for point by point in a 3 dimensional computer model of a heat exchanger. The end product of this project is a computer code that can predict an optimal configuration for a heat exchanger given only a few constraints (input fluids, size, cost, etc.). As VAT computer code can be used to model characteristics )pumping power, temperatures, and cost) of heat exchangers more quickly than traditional CFD or experiment, optimization of every geometric parameter simultaneously can be made. Using design of experiment, DOE and genetric algorithms, GE, to optimize the results of the computer code will improve heat exchanger disign.
Nielsen, P. |
1991-08-12
The following is intended to be a short introduction to the design and analysis of a Bayes-optimal detector, and Middleton`s Locally Optimum Bayes Detector (LOBD). The relationship between these two detectors is clarified. There are three examples of varying complexity included to illustrate the design of these detectors. The final example illustrates the difficulty involved in choosing the bias function for the LOBD. For the examples, the corrupting noise is Gaussian. This allows for a relatively easy solution to the optimal and the LOBD structures. As will be shown, for Bayes detection, the threshold is determined by the costs associated with making a decision and the a priori probabilities of each hypothesis. The threshold of the test cannot be set by simulation. One will notice that the optimal Bayes detector and the LOBD look very much like the Neyman-Pearson optimal and locally optimal detectors respectively. In the latter cases though, the threshold is set by a constraint on the false alarm probability. Note that this allows the threshold to be set by simulation.
Nielsen, P. Arizona Univ., Tucson, AZ . Dept. of Electrical and Computer Engineering)
1991-08-12
The following is intended to be a short introduction to the design and analysis of a Bayes-optimal detector, and Middleton's Locally Optimum Bayes Detector (LOBD). The relationship between these two detectors is clarified. There are three examples of varying complexity included to illustrate the design of these detectors. The final example illustrates the difficulty involved in choosing the bias function for the LOBD. For the examples, the corrupting noise is Gaussian. This allows for a relatively easy solution to the optimal and the LOBD structures. As will be shown, for Bayes detection, the threshold is determined by the costs associated with making a decision and the a priori probabilities of each hypothesis. The threshold of the test cannot be set by simulation. One will notice that the optimal Bayes detector and the LOBD look very much like the Neyman-Pearson optimal and locally optimal detectors respectively. In the latter cases though, the threshold is set by a constraint on the false alarm probability. Note that this allows the threshold to be set by simulation.
NASA Technical Reports Server (NTRS)
Demmel, J.; Lafferriere, G.
1989-01-01
Consideration is given to the problem of optimal force distribution among three point fingers holding a planar object. A scheme that reduces the nonlinear optimization problem to an easily solved generalized eigenvalue problem is proposed. This scheme generalizes and simplifies results of Ji and Roth (1988). The generalizations include all possible geometric arrangements and extensions to three dimensions and to the case of variable coefficients of friction. For the two-dimensional case with constant coefficients of friction, it is proved that, except for some special cases, the optimal grasping forces (in the sense of minimizing the dependence on friction) are those for which the angles with the corresponding normals are all equal (in absolute value).
Fuzzy logic controller optimization
Sepe, Jr., Raymond B; Miller, John Michael
2004-03-23
A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.
Optimally combined confidence limits
NASA Astrophysics Data System (ADS)
Janot, P.; Le Diberder, F.
1998-02-01
An analytical and optimal procedure to combine statistically independent sets of confidence levels on a quantity is presented. This procedure does not impose any constraint on the methods followed by each analysis to derive its own limit. It incorporates the a priori statistical power of each of the analyses to be combined, in order to optimize the overall sensitivity. It can, in particular, be used to combine the mass limits obtained by several analyses searching for the Higgs boson in different decay channels, with different selection efficiencies, mass resolution and expected background. It can also be used to combine the mass limits obtained by several experiments (e.g. ALEPH, DELPHI, L3 and OPAL, at LEP 2) independently of the method followed by each of these experiments to derive their own limit. A method to derive the limit set by one analysis is also presented, along with an unbiased prescription to optimize the expected mass limit in the no-signal-hypothesis.
Discrete Variational Optimal Control
NASA Astrophysics Data System (ADS)
Jiménez, Fernando; Kobilarov, Marin; Martín de Diego, David
2013-06-01
This paper develops numerical methods for optimal control of mechanical systems in the Lagrangian setting. It extends the theory of discrete mechanics to enable the solutions of optimal control problems through the discretization of variational principles. The key point is to solve the optimal control problem as a variational integrator of a specially constructed higher dimensional system. The developed framework applies to systems on tangent bundles, Lie groups, and underactuated and nonholonomic systems with symmetries, and can approximate either smooth or discontinuous control inputs. The resulting methods inherit the preservation properties of variational integrators and result in numerically robust and easily implementable algorithms. Several theoretical examples and a practical one, the control of an underwater vehicle, illustrate the application of the proposed approach.
NASA Astrophysics Data System (ADS)
Amir, Ornit; Braunstein, David; Altman, Ami
2003-05-01
A dose optimization tool for CT scanners is presented using patient raw data to calculate noise. The tool uses a single patient image which is modified for various lower doses. Dose optimization is carried out without extra measurements by interactively visualizing the dose-induced changes in this image. This tool can be used either off line, on existing image(s) or, as a pre - requisite for dose optimization for the specific patient, during the patient clinical study. The algorithm of low-dose simulation consists of reconstruction of two images from a single measurement and uses those images to create the various lower dose images. This algorithm enables fast simulation of various low dose (mAs) images on a real patient image.
McMordie Stoughton, Kate; Duan, Xiaoli; Wendel, Emily M.
2013-08-26
This technology evaluation was prepared by Pacific Northwest National Laboratory on behalf of the U.S. Department of Energy’s Federal Energy Management Program (FEMP). ¬The technology evaluation assesses techniques for optimizing reverse osmosis (RO) systems to increase RO system performance and water efficiency. This evaluation provides a general description of RO systems, the influence of RO systems on water use, and key areas where RO systems can be optimized to reduce water and energy consumption. The evaluation is intended to help facility managers at Federal sites understand the basic concepts of the RO process and system optimization options, enabling them to make informed decisions during the system design process for either new projects or recommissioning of existing equipment. This evaluation is focused on commercial-sized RO systems generally treating more than 80 gallons per hour.¬
2013-08-01
This technology evaluation was prepared by Pacific Northwest National Laboratory on behalf of the U.S. Department of Energy’s Federal Energy Management Program (FEMP). The technology evaluation assesses techniques for optimizing reverse osmosis (RO) systems to increase RO system performance and water efficiency. This evaluation provides a general description of RO systems, the influence of RO systems on water use, and key areas where RO systems can be optimized to reduce water and energy consumption. The evaluation is intended to help facility managers at Federal sites understand the basic concepts of the RO process and system optimization options, enabling them to make informed decisions during the system design process for either new projects or recommissioning of existing equipment. This evaluation is focused on commercial-sized RO systems generally treating more than 80 gallons per hour.
Optimal Composite Curing System
NASA Astrophysics Data System (ADS)
Handel, Paul; Guerin, Daniel
The Optimal Composite Curing System (OCCS) is an intelligent control system which incorporates heat transfer and resin kinetic models coupled with expert knowledge. It controls the curing of epoxy impregnated composites, preventing part overheating while maintaining maximum cure heatup rate. This results in a significant reduction in total cure time over standard methods. The system uses a cure process model, operating in real-time, to determine optimal cure profiles for tool/part configurations of varying thermal characteristics. These profiles indicate the heating and cooling necessary to insure a complete cure of each part in the autoclave in the minimum amount of time. The system coordinates these profiles to determine an optimal cure profile for a batch of thermally variant parts. Using process specified rules for proper autoclave operation, OCCS automatically controls the cure process, implementing the prescribed cure while monitoring the operation of the autoclave equipment.
Optimal symmetric flight studies
NASA Technical Reports Server (NTRS)
Weston, A. R.; Menon, P. K. A.; Bilimoria, K. D.; Cliff, E. M.; Kelley, H. J.
1985-01-01
Several topics in optimal symmetric flight of airbreathing vehicles are examined. In one study, an approximation scheme designed for onboard real-time energy management of climb-dash is developed and calculations for a high-performance aircraft presented. In another, a vehicle model intermediate in complexity between energy and point-mass models is explored and some quirks in optimal flight characteristics peculiar to the model uncovered. In yet another study, energy-modelling procedures are re-examined with a view to stretching the range of validity of zeroth-order approximation by special choice of state variables. In a final study, time-fuel tradeoffs in cruise-dash are examined for the consequences of nonconvexities appearing in the classical steady cruise-dash model. Two appendices provide retrospective looks at two early publications on energy modelling and related optimal control theory.
Optimality in neuromuscular systems.
Theodorou, Evangelos; Valero-Cuevas, Francisco J
2010-01-01
We provide an overview of optimal control methods to nonlinear neuromuscular systems and discuss their limitations. Moreover we extend current optimal control methods to their application to neuromuscular models with realistically numerous musculotendons; as most prior work is limited to torque-driven systems. Recent work on computational motor control has explored the used of control theory and estimation as a conceptual tool to understand the underlying computational principles of neuromuscular systems. After all, successful biological systems regularly meet conditions for stability, robustness and performance for multiple classes of complex tasks. Among a variety of proposed control theory frameworks to explain this, stochastic optimal control has become a dominant framework to the point of being a standard computational technique to reproduce kinematic trajectories of reaching movements (see [12]) In particular, we demonstrate the application of optimal control to a neuromuscular model of the index finger with all seven musculotendons producing a tapping task. Our simulations include 1) a muscle model that includes force- length and force-velocity characteristics; 2) an anatomically plausible biomechanical model of the index finger that includes a tendinous network for the extensor mechanism and 3) a contact model that is based on a nonlinear spring-damper attached at the end effector of the index finger. We demonstrate that it is feasible to apply optimal control to systems with realistically large state vectors and conclude that, while optimal control is an adequate formalism to create computational models of neuro-musculoskeletal systems, there remain important challenges and limitations that need to be considered and overcome such as contact transitions, curse of dimensionality, and constraints on states and controls.
NASA Technical Reports Server (NTRS)
Santala, T.; Sabol, R.; Carbajal, B. G.
1978-01-01
The minimum cost per unit of power output from flat plate solar modules can most likely be achieved through efficient packaging of higher efficiency solar cells. This paper outlines a module optimization method which is broadly applicable, and illustrates the potential results achievable from a specific high efficiency tandem junction (TJ) cell. A mathematical model is used to assess the impact of various factors influencing the encapsulated cell and packing efficiency. The optimization of the packing efficiency is demonstrated. The effect of encapsulated cell and packing efficiency on the module add-on cost is shown in a nomograph form.
2009-11-01
McGraw-Hill, New York). [16] J. S. Meditch , 1967, “Orthogonal Projection and Discrete Optimal Linear Smoothing ,” SIAM Journal on Control and...Optimization, 5, 74-89. [17] J. S. Meditch , 1973, “A Survey of Data Smoothing for Linear and Nonlinear Dynamic Systems,” Automatica, 9, 151-162... smoothing window forward of each fixed epoch. The length of the smoothing window is bounded above by 5 hours, the maximum time-length of a ground
Multidisciplinary design and optimization
NASA Technical Reports Server (NTRS)
Sobieszczanski-Sobieski, Jaroslaw
1992-01-01
Mutual couplings among the mathematical models of physical phenomena and parts of a system such as an aircraft complicate the design process because each contemplated design change may have a far reaching consequence throughout the system. This paper outlines techniques for computing these influences as system design derivatives useful to both judgmental and formal optimization purposes. The techniques facilitate decomposition of the design process into smaller, more manageable tasks and they form a methodology that can easily fit into existing engineering optimizations and incorporate their design tools.
Terascale Optimal PDE Simulations
David Keyes
2009-07-28
The Terascale Optimal PDE Solvers (TOPS) Integrated Software Infrastructure Center (ISIC) was created to develop and implement algorithms and support scientific investigations performed by DOE-sponsored researchers. These simulations often involve the solution of partial differential equations (PDEs) on terascale computers. The TOPS Center researched, developed and deployed an integrated toolkit of open-source, optimal complexity solvers for the nonlinear partial differential equations that arise in many DOE application areas, including fusion, accelerator design, global climate change and reactive chemistry. The algorithms created as part of this project were also designed to reduce current computational bottlenecks by orders of magnitude on terascale computers, enabling scientific simulation on a scale heretofore impossible.
Cherniak, Christopher
2012-01-01
Combinatorial network optimization theory concerns minimization of connection costs among interconnected components in systems such as electronic circuits. As an organization principle, similar wiring minimization can be observed at various levels of nervous systems, invertebrate and vertebrate, including primate, from placement of the entire brain in the body down to the subcellular level of neuron arbor geometry. In some cases, the minimization appears either perfect, or as good as can be detected with current methods. One question such best-of-all-possible-brains results raise is, what is the map of such optimization, does it have a distinct neural domain?
Optimal Quantum Phase Estimation
Dorner, U.; Smith, B. J.; Lundeen, J. S.; Walmsley, I. A.; Demkowicz-Dobrzanski, R.; Banaszek, K.; Wasilewski, W.
2009-01-30
By using a systematic optimization approach, we determine quantum states of light with definite photon number leading to the best possible precision in optical two-mode interferometry. Our treatment takes into account the experimentally relevant situation of photon losses. Our results thus reveal the benchmark for precision in optical interferometry. Although this boundary is generally worse than the Heisenberg limit, we show that the obtained precision beats the standard quantum limit, thus leading to a significant improvement compared to classical interferometers. We furthermore discuss alternative states and strategies to the optimized states which are easier to generate at the cost of only slightly lower precision.
NASA Astrophysics Data System (ADS)
Klesh, Andrew T.
This dissertation studies optimal exploration, defined as the collection of information about given objects of interest by a mobile agent (the explorer) using imperfect sensors. The key aspects of exploration are kinematics (which determine how the explorer moves in response to steering commands), energetics (which determine how much energy is consumed by motion and maneuvers), informatics (which determine the rate at which information is collected) and estimation (which determines the states of the objects). These aspects are coupled by the steering decisions of the explorer. We seek to improve exploration by finding trade-offs amongst these couplings and the components of exploration: the Mission, the Path and the Agent. A comprehensive model of exploration is presented that, on one hand, accounts for these couplings and on the other hand is simple enough to allow analysis. This model is utilized to pose and solve several exploration problems where an objective function is to be minimized. Specific functions to be considered are the mission duration and the total energy. These exploration problems are formulated as optimal control problems and necessary conditions for optimality are obtained in the form of two-point boundary value problems. An analysis of these problems reveals characteristics of optimal exploration paths. Several regimes are identified for the optimal paths including the Watchtower, Solar and Drag regime, and several non-dimensional parameters are derived that determine the appropriate regime of travel. The so-called Power Ratio is shown to predict the qualitative features of the optimal paths, provide a metric to evaluate an aircrafts design and determine an aircrafts capability for flying perpetually. Optimal exploration system drivers are identified that provide perspective as to the importance of these various regimes of flight. A bank-to-turn solar-powered aircraft flying at constant altitude on Mars is used as a specific platform for
Distributed Optimization System
Hurtado, John E.; Dohrmann, Clark R.; Robinett, III, Rush D.
2004-11-30
A search system and method for controlling multiple agents to optimize an objective using distributed sensing and cooperative control. The search agent can be one or more physical agents, such as a robot, and can be software agents for searching cyberspace. The objective can be: chemical sources, temperature sources, radiation sources, light sources, evaders, trespassers, explosive sources, time dependent sources, time independent sources, function surfaces, maximization points, minimization points, and optimal control of a system such as a communication system, an economy, a crane, and a multi-processor computer.
Numerical Optimization of Synergetic Maneuvers
1994-06-01
optimality conditions is termed the Karush-Kuln-Tucker ( KKT ) conditions . These necessary ...CONVERGENCE ................................................. 15 1. Su mnary Of Convexity and Optimality Conditions .............................. 15 2...point x. A point x* is called the optimal solution to the problem. 14 B. ALGORITHMS AND CONVERGENCE 1. Summary of Convexity and Optimality Conditions
Orbital-Maneuver-Sequence Optimization
1985-12-01
optimization computer program and applied it to the generation of optimal cog-brbital attack4ianeuver sequences * and to the generation of optimal evasions...maneuver-sequence- optimization computer programs can be improved by a general restructuring and streamlining and the addition of various features. It is...believed that with further development and systematic testing the programs have potential for real-time generation of optimal maneuver sequences in an
Numerical-Optimization Program
NASA Technical Reports Server (NTRS)
Vanderplaats, Garret N.
1991-01-01
Automated Design Synthesis (ADS) computer program is general-purpose numerical-optimization program for design engineering. Provides wide range of options for solution of constrained and unconstrained function minimization problems. Suitable for such applications as minimum-weight design. Written in FORTRAN 77.
Optimizing Computer Technology Integration
ERIC Educational Resources Information Center
Dillon-Marable, Elizabeth; Valentine, Thomas
2006-01-01
The purpose of this study was to better understand what optimal computer technology integration looks like in adult basic skills education (ABSE). One question guided the research: How is computer technology integration best conceptualized and measured? The study used the Delphi method to map the construct of computer technology integration and…
Goldman, A J
2006-01-01
Dr. Christoph Witzgall, the honoree of this Symposium, can count among his many contributions to applied mathematics and mathematical operations research a body of widely-recognized work on the optimal location of facilities. The present paper offers to non-specialists a sketch of that field and its evolution, with emphasis on areas most closely related to Witzgall's research at NBS/NIST.
Fourier Series Optimization Opportunity
ERIC Educational Resources Information Center
Winkel, Brian
2008-01-01
This note discusses the introduction of Fourier series as an immediate application of optimization of a function of more than one variable. Specifically, it is shown how the study of Fourier series can be motivated to enrich a multivariable calculus class. This is done through discovery learning and use of technology wherein students build the…
Optimization in Cardiovascular Modeling
NASA Astrophysics Data System (ADS)
Marsden, Alison L.
2014-01-01
Fluid mechanics plays a key role in the development, progression, and treatment of cardiovascular disease. Advances in imaging methods and patient-specific modeling now reveal increasingly detailed information about blood flow patterns in health and disease. Building on these tools, there is now an opportunity to couple blood flow simulation with optimization algorithms to improve the design of surgeries and devices, incorporating more information about the flow physics in the design process to augment current medical knowledge. In doing so, a major challenge is the need for efficient optimization tools that are appropriate for unsteady fluid mechanics problems, particularly for the optimization of complex patient-specific models in the presence of uncertainty. This article reviews the state of the art in optimization tools for virtual surgery, device design, and model parameter identification in cardiovascular flow and mechanobiology applications. In particular, it reviews trade-offs between traditional gradient-based methods and derivative-free approaches, as well as the need to incorporate uncertainties. Key future challenges are outlined, which extend to the incorporation of biological response and the customization of surgeries and devices for individual patients.
ERIC Educational Resources Information Center
Cody, Martin L.
1974-01-01
Discusses the optimality of natural selection, ways of testing for optimum solutions to problems of time - or energy-allocation in nature, optimum patterns in spatial distribution and diet breadth, and how best to travel over a feeding area so that food intake is maximized. (JR)
ERIC Educational Resources Information Center
Rebilas, Krzysztof
2013-01-01
Consider a skier who goes down a takeoff ramp, attains a speed "V", and jumps, attempting to land as far as possible down the hill below (Fig. 1). At the moment of takeoff the angle between the skier's velocity and the horizontal is [alpha]. What is the optimal angle [alpha] that makes the jump the longest possible for the fixed magnitude of the…
Optimizing Conferencing Freeware
ERIC Educational Resources Information Center
Baggaley, Jon; Klaas, Jim; Wark, Norine; Depow, Jim
2005-01-01
The increasing range of options provided by two popular conferencing freeware products, "Yahoo Messenger" and "MSN Messenger," are discussed. Each tool contains features designed primarily for entertainment purposes, which can be customized for use in online education. This report provides suggestions for optimizing the educational potential of…
Optimal Periodic Control Theory.
1980-08-01
are control variables. For many aircraft, this energy state space produces a hodograph which is not convex. The physical explanation for this is that...convexity in the hodograph and preserve an "optimal" steady-state cruise, Schultz and Zagalsky [61 revised the energy state model so that altitude becomes a
Toward Optimal Transport Networks
NASA Technical Reports Server (NTRS)
Alexandrov, Natalia; Kincaid, Rex K.; Vargo, Erik P.
2008-01-01
Strictly evolutionary approaches to improving the air transport system a highly complex network of interacting systems no longer suffice in the face of demand that is projected to double or triple in the near future. Thus evolutionary approaches should be augmented with active design methods. The ability to actively design, optimize and control a system presupposes the existence of predictive modeling and reasonably well-defined functional dependences between the controllable variables of the system and objective and constraint functions for optimization. Following recent advances in the studies of the effects of network topology structure on dynamics, we investigate the performance of dynamic processes on transport networks as a function of the first nontrivial eigenvalue of the network's Laplacian, which, in turn, is a function of the network s connectivity and modularity. The last two characteristics can be controlled and tuned via optimization. We consider design optimization problem formulations. We have developed a flexible simulation of network topology coupled with flows on the network for use as a platform for computational experiments.
ERIC Educational Resources Information Center
Simmons, Joseph P.; Massey, Cade
2012-01-01
Is optimism real, or are optimistic forecasts just cheap talk? To help answer this question, we investigated whether optimistic predictions persist in the face of large incentives to be accurate. We asked National Football League football fans to predict the winner of a single game. Roughly half (the partisans) predicted a game involving their…
Optimization of digital designs
NASA Technical Reports Server (NTRS)
Whitaker, Sterling R. (Inventor); Miles, Lowell H. (Inventor)
2009-01-01
An application specific integrated circuit is optimized by translating a first representation of its digital design to a second representation. The second representation includes multiple syntactic expressions that admit a representation of a higher-order function of base Boolean values. The syntactic expressions are manipulated to form a third representation of the digital design.
Optimal GENCO bidding strategy
NASA Astrophysics Data System (ADS)
Gao, Feng
Electricity industries worldwide are undergoing a period of profound upheaval. The conventional vertically integrated mechanism is being replaced by a competitive market environment. Generation companies have incentives to apply novel technologies to lower production costs, for example: Combined Cycle units. Economic dispatch with Combined Cycle units becomes a non-convex optimization problem, which is difficult if not impossible to solve by conventional methods. Several techniques are proposed here: Mixed Integer Linear Programming, a hybrid method, as well as Evolutionary Algorithms. Evolutionary Algorithms share a common mechanism, stochastic searching per generation. The stochastic property makes evolutionary algorithms robust and adaptive enough to solve a non-convex optimization problem. This research implements GA, EP, and PS algorithms for economic dispatch with Combined Cycle units, and makes a comparison with classical Mixed Integer Linear Programming. The electricity market equilibrium model not only helps Independent System Operator/Regulator analyze market performance and market power, but also provides Market Participants the ability to build optimal bidding strategies based on Microeconomics analysis. Supply Function Equilibrium (SFE) is attractive compared to traditional models. This research identifies a proper SFE model, which can be applied to a multiple period situation. The equilibrium condition using discrete time optimal control is then developed for fuel resource constraints. Finally, the research discusses the issues of multiple equilibria and mixed strategies, which are caused by the transmission network. Additionally, an advantage of the proposed model for merchant transmission planning is discussed. A market simulator is a valuable training and evaluation tool to assist sellers, buyers, and regulators to understand market performance and make better decisions. A traditional optimization model may not be enough to consider the distributed
Jayaram, Smitha; Kapoor, Sabeeta; Dharmesh, Shylaja M
2015-06-25
Corn pectic polysaccharide (COPP) inhibited galectin-3 mediated hemagglutination at Minimum Inhibitory Concentration (MIC) of 4.08 μg/mL as opposed to citrus pectin (25 μg/mL), a well known galectin-3 inhibitor and lactose (4.16 μg/mL)--sugar specific to galectin-3. COPP effectively (72%) inhibited invasion and metastasis in experimental animals. In vivo results were substantiated by modulation of cancer specific markers such as galectin-3, which is a key molecule for initiation of metastatic cascade, vascular endothelial growth factor (VEGF) that enhances angiogenesis, matrix metalloproteinases 2 and 9 that are required for invasion, NF-κB, a transcription factor for proliferative potency of tumor cells and a phosphoglucoisomerase (PGI), the activity of which favors cancer cell growth. Structural characterization studies indicate the active component (relatively less acidic, 0.05 M ammonium carbonate, 160 kDa fraction) which showed antimetastatic potency in vitro with MIC of 0.09 μg/mL, and ∼ 45 fold increase in the activity when compared to that of COPP. Gas liquid chromatographic analysis indicated the presence of rhamnose (1%), arabinose (20%), xylose (3%), mannose (4%), galactose (54%) and uronic acid (10%) in different proportions. However, correlative data attributed galectin-3 inhibitory activity to enhanced levels of arabinose and galactose. FTIR, HPLC and NMR spectroscopic analysis further highlights that COPP is an arabinogalactan with methyl/ethyl esters. It is therefore suggested that the blockade of galectin-3 mediated lung metastasis appears to be a result of an inhibition of mixed functions induced during metastasis. The data signifies the importance of dietary carbohydrate as cancer-preventive agent. Although pectin digestibility and absorption are issues of concern, promising in vivo data provides evidence for the cancer preventive property of corn. The present study reveals for the first time a new component of corn, i.e.,--corn pectin with cancer preventive activity apart from corn starch that has been in wide use for multipurpose health benefits.
Yoon, Yeong Keng; Choon, Tan Soo
2016-01-01
Benzimidazole derivatives have been shown to possess sirtuin-inhibitory activity. In the continuous search for potent sirtuin inhibitors, systematic changes on the terminal benzene ring were performed on previously identified benzimidazole-based sirtuin inhibitors, to further investigate their structure-activity relationships. It was demonstrated that the sirtuin activities of these novel compounds followed the trend where meta-substituted compounds possessed markedly weaker potency than ortho- and para-substituted compounds, with the exception of halogenated substituents. Molecular docking studies were carried out to rationalize these observations. Apart from this, the methods used to synthesize the interesting compounds are also discussed.
A multi-step model for facilitated unwinding of the yeast U4/U6 RNA duplex.
Rodgers, Margaret L; Didychuk, Allison L; Butcher, Samuel E; Brow, David A; Hoskins, Aaron A
2016-12-15
The small nuclear RNA (snRNA) components of the spliceosome undergo many conformational rearrangements during its assembly, catalytic activation and disassembly. The U4 and U6 snRNAs are incorporated into the spliceosome as a base-paired complex within the U4/U6.U5 small nuclear ribonucleoprotein (tri-snRNP). U4 and U6 are then unwound in order for U6 to pair with U2 to form the spliceosome's active site. After splicing, U2/U6 is unwound and U6 annealed to U4 to reassemble the tri-snRNP. U6 rearrangements are crucial for spliceosome formation but are poorly understood. We have used single-molecule Förster resonance energy transfer and unwinding assays to identify interactions that promote U4/U6 unwinding and have studied their impact in yeast. We find that U4/U6 is efficiently unwound using DNA oligonucleotides by coupling unwinding of U4/U6 stem II with strand invasion of stem I. Unwinding is stimulated by the U6 telestem, which transiently forms in the intact U4/U6 RNA complex. Stabilization of the telestem in vivo results in accumulation of U4/U6 di-snRNP and impairs yeast growth. Our data reveal conserved mechanisms for U4/U6 unwinding and indicate telestem dynamics are critical for tri-snRNP assembly and stability.
ERIC Educational Resources Information Center
de Souza, Rebecca; Dauner, Kim Nichols; Goei, Ryan; LaCaille, Lara; Kotowski, Michael R.; Schultz, Jennifer Feenstra; LaCaille, Rick; Versnik Nowak, Amy L.
2014-01-01
Background: Obesity prevention efforts typically involve changing eating and exercise behaviors as well as the physical and social environment in which those behaviors occur. Due to existing social networks, worksites are a logical choice for implementing such interventions. Purpose: This article describes the development and implementation of a…
SU-C-BRF-07: A Pattern Fusion Algorithm for Multi-Step Ahead Prediction of Surrogate Motion
Zawisza, I; Yan, H; Yin, F
2014-06-15
Purpose: To assure that tumor motion is within the radiation field during high-dose and high-precision radiosurgery, real-time imaging and surrogate monitoring are employed. These methods are useful in providing real-time tumor/surrogate motion but no future information is available. In order to anticipate future tumor/surrogate motion and track target location precisely, an algorithm is developed and investigated for estimating surrogate motion multiple-steps ahead. Methods: The study utilized a one-dimensional surrogate motion signal divided into three components: (a) training component containing the primary data including the first frame to the beginning of the input subsequence; (b) input subsequence component of the surrogate signal used as input to the prediction algorithm: (c) output subsequence component is the remaining signal used as the known output of the prediction algorithm for validation. The prediction algorithm consists of three major steps: (1) extracting subsequences from training component which best-match the input subsequence according to given criterion; (2) calculating weighting factors from these best-matched subsequence; (3) collecting the proceeding parts of the subsequences and combining them together with assigned weighting factors to form output. The prediction algorithm was examined for several patients, and its performance is assessed based on the correlation between prediction and known output. Results: Respiratory motion data was collected for 20 patients using the RPM system. The output subsequence is the last 50 samples (∼2 seconds) of a surrogate signal, and the input subsequence was 100 (∼3 seconds) frames prior to the output subsequence. Based on the analysis of correlation coefficient between predicted and known output subsequence, the average correlation is 0.9644±0.0394 and 0.9789±0.0239 for equal-weighting and relative-weighting strategies, respectively. Conclusion: Preliminary results indicate that the prediction algorithm is effective in estimating surrogate motion multiple-steps in advance. Relative-weighting method shows better prediction accuracy than equal-weighting method. More parameters of this algorithm are under investigation.
NASA Astrophysics Data System (ADS)
M'chirgui, A.; Zouaoui, M.; Ben Azzouz, F.; Ben Saı̈d, M. A.; Smirani, R.; Ben Salem, M.
2002-08-01
A kinetic study of the (Bi,Pb)-2223 phase formation has been performed through a two-cycles annealing process at a temperature of 835°C by X-ray diffraction and SEM observations. Samples were Pb-doped (part 0.4 of Bi substituted by Pb) during the first thermal cycle. A second substantial addition of up to 10% excess of PbO in weight was added at the beginning of the second thermal cycle. PbO addition was shown to be more effective during the second cycle. Using the Avrami equation, a kinetic study of the (Bi,Pb)-2223 phase formation mechanism was conducted. The reaction order, n has been shown to depend on PbO excess and thus the (Bi,Pb)-2223 formation mechanism. With lower excess of PbO (0% and 4%), n is about 0.5 and the related formation mechanism corresponds to the thickening of plates after their edges have been impinged. With higher excess of PbO (10%), n is about 2,2 and the related mechanism corresponds to the initial growth of particles nucleated at a constant rate.
Evidence of Multi-step Nucleation Leading to Various Crystallization Pathways from an Fe-O-Al Melt
Wang, G. C.; Wang, Q.; Li, S. L.; Ai, X. G.; Fan, C. G.
2014-01-01
The crystallization process from a solution begins with nucleation, which determines the structure and size of the resulting crystals. Further understanding of multi-pathway crystallizations from solution through two-step nucleation mechanisms is needed. This study uses density functional theory to probe the thermodynamic properties of alumina clusters at high temperature and reveals the thermodynamic relationship between these clusters and the saturation levels of dissolved oxygen and aluminum in an Fe–O–Al melt. Based on the thermodynamics of cluster formation and the experimental evidence for both excess oxygen in the Fe-O-Al melt and for alumina with a polycrystalline structure in solidified iron, we demonstrate that the appearance of various types of clusters that depends on the saturation ratio determines the nucleation steps that lead to the various crystallization pathways. Such mechanisms may also be important in nucleation and crystallization from solution. PMID:24866413
Liu, Chang; Wang, Xin; Chen, Yuhuang; Hao, Huijing; Li, Xu; Liang, Junrong; Duan, Ran; Li, Chuchu; Zhang, Jing; Shao, Shihe; Jing, Huaiqi
2016-01-01
In many gram negative bacilli, AmpD plays a key role in both cell well-recycling pathway and β-lactamase regulation, inactivation of the ampD causes the accumulation of 1,6-anhydromuropeptides, and results in the ampC overproduction. In Yersinia enterocolitica, the regulation of ampC expression may also rely on the ampR-ampC system, the role of AmpD in this species is still unknown. In this study, three AmpD homologs (AmpD1, AmpD2, and AmpD3) have been identified in complete sequence of strain Y. enterocolitica subsp. palearctica 105.5R(r). To understand the role of three AmpD homologs, several mutant strains were constructed and analyzed where a rare ampC regulation mechanism was observed: low-effective ampD2 and ampD3 cooperate with the high-effective ampD1 in the three levels regulation of ampC expression. Enterobacteriaceae was used to be supposed to regulate ampC expression by two steps, three steps regulation was only observed in Pseudomonas aeruginosa. In this study, we first reported that Enterobacteriaceae Y. enterocolitica can also possess a three steps stepwise regulation mechanism, regulating the ampC expression precisely. PMID:27588018
NASA Astrophysics Data System (ADS)
Jeschke, Harald O.; Opahle, Ingo; Valenti, Roser; Das, Hena; Saha-Dasgupta, Tanusri; Lang, Michael; Hu, Shijie; Wang, Xiaoqun; Peters, Robert; Honecker, Andreas
2012-02-01
The natural mineral azurite Cu3(CO3)2(OH)2 is a frustrated magnet displaying unusual and controversially discussed magnetic behavior. We perform a theoretical study based on density functional theory as well as state-of-the-art numerical many-body calculations [1]. We propose an effective generalized spin-1/2 diamond chain model which provides a consistent description of experiments: low-temperature magnetization, inelastic neutron scattering, nuclear magnetic resonance measurements, magnetic susceptibility as well as new specific heat measurements. With this study we demonstrate that the balanced combination of first principles with powerful many-body methods successfully describes the behavior of this frustrated material. [1] H. O. Jeschke et al., Phys. Rev. Lett. 106, 217201 (2011)
Pietrzykowski, Andrzej Z.; Spijker, Sabine
2014-01-01
Malfunction of synaptic plasticity in different brain regions, including the amygdala plays a role in impulse control deficits that are characteristics of several psychiatric disorders, such as ADHD, schizophrenia, depression and addiction. Previously, we discovered a locus for impulsivity (Impu1) containing the neuregulin 3 (Nrg3) gene, of which the level of expression determines levels of inhibitory control. MicroRNAs (miRNAs) are potent regulators of gene expression, and have recently emerged as important factors contributing to the development of psychiatric disorders. However, their role in impulsivity, as well as control of Nrg3 expression or malfunction of the amygdala, is not well established. Here, we used the GeneNetwork database of BXD mice to search for correlated traits with impulsivity using an overrepresentation analysis to filter for biologically meaningful traits. We determined that inhibitory control was significantly correlated with expression of miR-190b, -28a, -340, -219a, and -491 in the amygdala, and that the overrepresented correlated traits showed a specific pattern of coregulation with these miRNAs. A bioinformatics analysis identified that miR-190b, by targeting an Nrg3-related network, could affect synaptic plasticity in the amygdala, targeting bot impulsive and compulsive traits. Moreover, miR-28a, -340, -219a, and possibly -491 could act on synaptic function by determining the balance between neuronal outgrowth and differentiation. We propose that these miRNAs are attractive candidates of regulation of amygdala synaptic plasticity, possibly during development but also in maintaining the impulsive phenotype. These results can help us to better understand mechanisms of synaptic dysregulation in psychiatric disorders. PMID:25561905
NASA Astrophysics Data System (ADS)
Kajani, M. Tavassoli; Gholampoor, I.
2015-10-01
The purpose of this study is to present a new direct method for the approximate solution and approximate derivatives up to order k to the solution for kth-order Volterra integro-differential equations with a regular kernel. This method is based on the approximation by shifting the original problem into a sequence of subintervals. A Legendre-Gauss-Lobatto collocation method is proposed to solving the Volterra integro-differential equation. Numerical examples show that the approximate solutions have a good degree of accuracy.
Liu, Chang; Wang, Xin; Chen, Yuhuang; Hao, Huijing; Li, Xu; Liang, Junrong; Duan, Ran; Li, Chuchu; Zhang, Jing; Shao, Shihe; Jing, Huaiqi
2016-01-01
In many gram negative bacilli, AmpD plays a key role in both cell well-recycling pathway and β-lactamase regulation, inactivation of the ampD causes the accumulation of 1,6-anhydromuropeptides, and results in the ampC overproduction. In Yersinia enterocolitica, the regulation of ampC expression may also rely on the ampR-ampC system, the role of AmpD in this species is still unknown. In this study, three AmpD homologs (AmpD1, AmpD2, and AmpD3) have been identified in complete sequence of strain Y. enterocolitica subsp. palearctica 105.5R(r). To understand the role of three AmpD homologs, several mutant strains were constructed and analyzed where a rare ampC regulation mechanism was observed: low-effective ampD2 and ampD3 cooperate with the high-effective ampD1 in the three levels regulation of ampC expression. Enterobacteriaceae was used to be supposed to regulate ampC expression by two steps, three steps regulation was only observed in Pseudomonas aeruginosa. In this study, we first reported that Enterobacteriaceae Y. enterocolitica can also possess a three steps stepwise regulation mechanism, regulating the ampC expression precisely.
Benhammouda, Brahim; Vazquez-Leal, Hector
2016-01-01
This work presents an analytical solution of some nonlinear delay differential equations (DDEs) with variable delays. Such DDEs are difficult to treat numerically and cannot be solved by existing general purpose codes. A new method of steps combined with the differential transform method (DTM) is proposed as a powerful tool to solve these DDEs. This method reduces the DDEs to ordinary differential equations that are then solved by the DTM. Furthermore, we show that the solutions can be improved by Laplace-Padé resummation method. Two examples are presented to show the efficiency of the proposed technique. The main advantage of this technique is that it possesses a simple procedure based on a few straight forward steps and can be combined with any analytical method, other than the DTM, like the homotopy perturbation method.
NASA Astrophysics Data System (ADS)
Zsirka, Balázs; Horváth, Erzsébet; Szabó, Péter; Juzsakova, Tatjána; Szilágyi, Róbert K.; Fertig, Dávid; Makó, Éva; Varga, Tamás; Kónya, Zoltán; Kukovecz, Ákos; Kristóf, János
2017-03-01
Surface modification of the halloysite-10 Å mineral with tubular morphology can be achieved by slightly modified procedures developed for the delamination of kaolinite minerals. The resulting delaminated halloysite nanoparticles have unexpected surface/morphological properties that display, new potentials in catalyst development. In this work, a four-step intercalation/delamination procedure is described for the preparation of thin-walled nanoscrolls from the multi-layered hydrated halloysite mineral that consists of (1) intercalation of halloysite with potassium acetate, (2) replacement intercalation with ethylene glycol, (3) replacement intercalation with hexylamine, and (4) delamination with toluene. The intercalation steps were followed by X-ray diffraction, transmission electron microscopy, N2 adsorption-desorption, thermogravimetry, and infrared spectroscopy. Delamination eliminated the crystalline order and the crystallite size along the 'c'-axis, increased the specific surface area, greatly decreased the thickness of the mineral tubes to a monolayer, and shifted the pore diameter toward the micropore region. Unexpectedly, the removal of residual organics from intercalation steps adsorbed at the nanoscroll surface with a peroxide treatment resulted in partial recovery of crystallinity and increase of crystallite size along the 'c'-crystal direction. The d(001) value showed a diffuse pattern at 7.4-7.7 Å due to the rearrangement of the thin-walled nanoscrolls toward the initial tubular morphology of the dehydrated halloysite-7 Å mineral.
Sun, Bo; Yu, XiangHui; Yin, Yuhe; Liu, Xintao; Wu, Yongge; Chen, Yan; Zhang, Xizhen; Jiang, Chunlai; Kong, Wei
2013-09-01
The demand for pharmaceutical-grade plasmid DNA in vaccine applications and gene therapy has been increasing in recent years. In the present study, a process consisting of alkaline lysis, tangential flow filtration, purification by anion exchange chromatography, hydrophobic interaction chromatography and size exclusion chromatography was developed. The final product met the requirements for pharmaceutical-grade plasmid DNA. The chromosomal DNA content was <1 μg/mg plasmid DNA, and RNA was not detectable by agarose gel electrophoresis. Moreover, the protein content was <2 μg/mg plasmid DNA, and the endotoxin content was <10 EU/mg plasmid DNA. The process was scaled up to yield 800 mg of pharmaceutical-grade plasmid DNA from approximately 2 kg of bacterial cell paste. The overall yield of the final plasmid DNA reached 48%. Therefore, we have established a rapid and efficient production process for pharmaceutical-grade plasmid DNA.
Velasco, Silvia; Ibrahim, Mahmoud M; Kakumanu, Akshay; Garipler, Görkem; Aydin, Begüm; Al-Sayegh, Mohamed Ahmed; Hirsekorn, Antje; Abdul-Rahman, Farah; Satija, Rahul; Ohler, Uwe; Mahony, Shaun; Mazzoni, Esteban O
2017-02-02
Direct cell programming via overexpression of transcription factors (TFs) aims to control cell fate with the degree of precision needed for clinical applications. However, the regulatory steps involved in successful terminal cell fate programming remain obscure. We have investigated the underlying mechanisms by looking at gene expression, chromatin states, and TF binding during the uniquely efficient Ngn2, Isl1, and Lhx3 motor neuron programming pathway. Our analysis reveals a highly dynamic process in which Ngn2 and the Isl1/Lhx3 pair initially engage distinct regulatory regions. Subsequently, Isl1/Lhx3 binding shifts from one set of targets to another, controlling regulatory region activity and gene expression as cell differentiation progresses. Binding of Isl1/Lhx3 to later motor neuron enhancers depends on the Ebf and Onecut TFs, which are induced by Ngn2 during the programming process. Thus, motor neuron programming is the product of two initially independent transcriptional modules that converge with a feedforward transcriptional logic.
Properties of Electron-Beam Irradiated CuInSe2 Layers by Multi-Step Sputtering Method.
Kim, Chae-Woong; Kim, Jin Hyeok; Jeong, Chaehwan
2015-10-01
Typically, CuInSe2 (CIS) based thin films for photovoltaic devices are deposited by co-evaporation or by deposition of the metals, followed by treatment in a selenium environment. This article describes CIS films that are instead deposited by DC and RF magnetron sputtering from binary Cu2Se and In2Se3 targets without the supply of selenium. As a novel method, electron beam annealing was used for crystallization of Cu2Se/In2Se3 stacked precursors. The surface, cross-sectional morphology, and compositional ratio of CIS films were investigated to confirm the possibility in crystallization without any addition of selenium. Our work demonstrates that the e-beam annealing method can be a good candidate for the rapid crystallization of Cu-In-Se sputtered precursors.
Tsujiuchi, Toshifumi; Nakae, Dai; Konishi, Yoichi
2014-03-01
N-Nitrosobis(2-hydroxypropyl)amine (BHP) was first synthesized by Krüger et al. (1974), and has been shown to primarily induce pancreatic duct adenocarcinomas by a subcutaneous injection in Syrian hamsters. By contrast, the carcinogenic effect of BHP has been indicated at the different target organs in rats, namely the lung. When rats are received by an oral administration of BHP in drinking water for 25 weeks, a high incidence of lung carcinomas are induced, which include adenocarcinomas, squamous cell carcinomas and combined squamous cell and adenocarcinomas. So many similarities are observed in terms of not only histological appearances but also gene alterations between human and BHP-induced rat lung cancers. Moreover, the step by step development of lung lesions, from preneoplastic lesions to cancers in rat lung carcinogenesis by BHP offers a good model to investigate the mechanisms underlying the pathogenesis of lung cancers. Because data for genetic and epigenetic alterations have indeed been accumulated during the BHP-induced rat lung carcinogenesis, we will introduce them in this review and hence demonstrate that this lung carcinogenesis model provides a useful opportunity for the research on the pathogenesis of lung cancers of both humans and rats.
A multi-step model for facilitated unwinding of the yeast U4/U6 RNA duplex
Rodgers, Margaret L.; Didychuk, Allison L.; Butcher, Samuel E.; Brow, David A.; Hoskins, Aaron A.
2016-01-01
The small nuclear RNA (snRNA) components of the spliceosome undergo many conformational rearrangements during its assembly, catalytic activation and disassembly. The U4 and U6 snRNAs are incorporated into the spliceosome as a base-paired complex within the U4/U6.U5 small nuclear ribonucleoprotein (tri-snRNP). U4 and U6 are then unwound in order for U6 to pair with U2 to form the spliceosome's active site. After splicing, U2/U6 is unwound and U6 annealed to U4 to reassemble the tri-snRNP. U6 rearrangements are crucial for spliceosome formation but are poorly understood. We have used single-molecule Förster resonance energy transfer and unwinding assays to identify interactions that promote U4/U6 unwinding and have studied their impact in yeast. We find that U4/U6 is efficiently unwound using DNA oligonucleotides by coupling unwinding of U4/U6 stem II with strand invasion of stem I. Unwinding is stimulated by the U6 telestem, which transiently forms in the intact U4/U6 RNA complex. Stabilization of the telestem in vivo results in accumulation of U4/U6 di-snRNP and impairs yeast growth. Our data reveal conserved mechanisms for U4/U6 unwinding and indicate telestem dynamics are critical for tri-snRNP assembly and stability. PMID:27484481
A simple and efficient error analysis for multi-step solution of the Navier-Stokes equations
NASA Astrophysics Data System (ADS)
Fithen, R. M.
2002-02-01
A simple error analysis is used within the context of segregated finite element solution scheme to solve incompressible fluid flow. An error indicator is defined based on the difference between a numerical solution on an original mesh and an approximated solution on a related mesh. This error indicator is based on satisfying the steady-state momentum equations. The advantages of this error indicator are, simplicity of implementation (post-processing step), ability to show regions of high and/or low error, and as the indicator approaches zero the solution approaches convergence. Two examples are chosen for solution; first, the lid-driven cavity problem, followed by the solution of flow over a backward facing step. The solutions are compared to previously published data for validation purposes. It is shown that this rather simple error estimate, when used as a re-meshing guide, can be very effective in obtaining accurate numerical solutions. Copyright
Lloyd-Price, Jason; Tran, Huy; Ribeiro, Andre S.
2016-01-01
Transcription kinetics is limited by its initiation steps, which differ between promoters and with intra- and extracellular conditions. Regulation of these steps allows tuning both the rate and stochasticity of RNA production. We used time-lapse, single-RNA microscopy measurements in live Escherichia coli to study how the rate-limiting steps in initiation of the Plac/ara-1 promoter change with temperature and induction scheme. For this, we compared detailed stochastic models fit to the empirical data in maximum likelihood sense using statistical methods. Using this analysis, we found that temperature affects the rate limiting steps unequally, as nonlinear changes in the closed complex formation suffice to explain the differences in transcription dynamics between conditions. Meanwhile, a similar analysis of the PtetA promoter revealed that it has a different rate limiting step configuration, with temperature regulating different steps. Finally, we used the derived models to explore a possible cause for why the identified steps are preferred as the main cause for behavior modifications with temperature: we find that transcription dynamics is either insensitive or responds reciprocally to changes in the other steps. Our results suggests that different promoters employ different rate limiting step patterns that control not only their rate and variability, but also their sensitivity to environmental changes. PMID:27792724
An optimal structural design algorithm using optimality criteria
NASA Technical Reports Server (NTRS)
Taylor, J. E.; Rossow, M. P.
1976-01-01
An algorithm for optimal design is given which incorporates several of the desirable features of both mathematical programming and optimality criteria, while avoiding some of the undesirable features. The algorithm proceeds by approaching the optimal solution through the solutions of an associated set of constrained optimal design problems. The solutions of the constrained problems are recognized at each stage through the application of optimality criteria based on energy concepts. Two examples are described in which the optimal member size and layout of a truss is predicted, given the joint locations and loads.
Peng, Ting; Sun, Xiaochun; Mumm, Rita H
2014-01-01
Multiple trait integration (MTI) is a multi-step process of converting an elite variety/hybrid for value-added traits (e.g. transgenic events) through backcross breeding. From a breeding standpoint, MTI involves four steps: single event introgression, event pyramiding, trait fixation, and version testing. This study explores the feasibility of marker-aided backcross conversion of a target maize hybrid for 15 transgenic events in the light of the overall goal of MTI of recovering equivalent performance in the finished hybrid conversion along with reliable expression of the value-added traits. Using the results to optimize single event introgression (Peng et al. Optimized breeding strategies for multiple trait integration: I. Minimizing linkage drag in single event introgression. Mol Breed, 2013) which produced single event conversions of recurrent parents (RPs) with ≤8 cM of residual non-recurrent parent (NRP) germplasm with ~1 cM of NRP germplasm in the 20 cM regions flanking the event, this study focused on optimizing process efficiency in the second and third steps in MTI: event pyramiding and trait fixation. Using computer simulation and probability theory, we aimed to (1) fit an optimal breeding strategy for pyramiding of eight events into the female RP and seven in the male RP, and (2) identify optimal breeding strategies for trait fixation to create a 'finished' conversion of each RP homozygous for all events. In addition, next-generation seed needs were taken into account for a practical approach to process efficiency. Building on work by Ishii and Yonezawa (Optimization of the marker-based procedures for pyramiding genes from multiple donor lines: I. Schedule of crossing between the donor lines. Crop Sci 47:537-546, 2007a), a symmetric crossing schedule for event pyramiding was devised for stacking eight (seven) events in a given RP. Options for trait fixation breeding strategies considered selfing and doubled haploid approaches to achieve homozygosity
Optimization of Anguilliform Swimming
NASA Astrophysics Data System (ADS)
Kern, Stefan; Koumoutsakos, Petros
2006-03-01
Anguilliform swimming is investigated by 3D computer simulations coupling the dynamics of an undulating eel-like body with the surrounding viscous fluid flow. The body is self-propelled and, in contrast to previous computational studies of swimming, the motion pattern is not prescribed a priori but obtained by an evolutionary optimization procedure. Two different objective functions are used to characterize swimming efficiency and maximum swimming velocity with limited input power. The found optimal motion patterns represent two distinct swimming modes corresponding to migration, and burst swimming, respectively. The results support the hypothesis from observations of real animals that eels can modify their motion pattern generating wakes that reflect their propulsive mode. Unsteady drag and thrust production of the swimming body are thoroughly analyzed by recording the instantaneous fluid forces acting on partitions of the body surface.
Córdova, Natalia; Yee, Debbie; Barto, Andrew G.; Niv, Yael; Botvinick, Matthew M.
2014-01-01
Human behavior has long been recognized to display hierarchical structure: actions fit together into subtasks, which cohere into extended goal-directed activities. Arranging actions hierarchically has well established benefits, allowing behaviors to be represented efficiently by the brain, and allowing solutions to new tasks to be discovered easily. However, these payoffs depend on the particular way in which actions are organized into a hierarchy, the specific way in which tasks are carved up into subtasks. We provide a mathematical account for what makes some hierarchies better than others, an account that allows an optimal hierarchy to be identified for any set of tasks. We then present results from four behavioral experiments, suggesting that human learners spontaneously discover optimal action hierarchies. PMID:25122479
Cyclone performance and optimization
Leith, D.
1990-06-15
The objectives of this project are: to characterize the gas flow pattern within cyclones, to revise the theory for cyclone performance on the basis of these findings, and to design and test cyclones whose dimensions have been optimized using revised performance theory. This work is important because its successful completion will aid in the technology for combustion of coal in pressurized, fluidized beds. During the past quarter, we have nearly completed modeling work that employs the flow field measurements made during the past six months. In addition, we have begun final work using the results of this project to develop improved design methods for cyclones. This work involves optimization using the Iozia-Leith efficiency model and the Dirgo pressure drop model. This work will be completed this summer. 9 figs.
Optimal Electric Utility Expansion
1989-10-10
SAGE-WASP is designed to find the optimal generation expansion policy for an electrical utility system. New units can be automatically selected from a user-supplied list of expansion candidates which can include hydroelectric and pumped storage projects. The existing system is modeled. The calculational procedure takes into account user restrictions to limit generation configurations to an area of economic interest. The optimization program reports whether the restrictions acted as a constraint on the solution. All expansion configurations considered are required to pass a user supplied reliability criterion. The discount rate and escalation rate are treated separately for each expansion candidate and for each fuel type. All expenditures are separated into local and foreign accounts, and a weighting factor can be applied to foreign expenditures.
Heliostat cost optimization study
NASA Astrophysics Data System (ADS)
von Reeken, Finn; Weinrebe, Gerhard; Keck, Thomas; Balz, Markus
2016-05-01
This paper presents a methodology for a heliostat cost optimization study. First different variants of small, medium sized and large heliostats are designed. Then the respective costs, tracking and optical quality are determined. For the calculation of optical quality a structural model of the heliostat is programmed and analyzed using finite element software. The costs are determined based on inquiries and from experience with similar structures. Eventually the levelised electricity costs for a reference power tower plant are calculated. Before each annual simulation run the heliostat field is optimized. Calculated LCOEs are then used to identify the most suitable option(s). Finally, the conclusions and findings of this extensive cost study are used to define the concept of a new cost-efficient heliostat called `Stellio'.
NASA Astrophysics Data System (ADS)
Costoiu, M.; Ioana, A.; Semenescu, A.; Marcu, D.
2016-11-01
The article presents the main advantages of electric arc furnace (EAF): it has a great contribution to reintroduce significant quantities of reusable metallic materials in the economic circuit, it constitutes itself as an important part in the Primary Materials and Energy Recovery (PMER), good productivity, good quality / price ratio, the possibility of developing a wide variety of classes and types of steels, including special steels and high alloy. In this paper it is presented some important developments of electric arc furnace: vacuum electric arc furnace, artificial intelligence expert systems for pollution control Steelworks. Another important aspect presented in the article is an original block diagram for optimization the EAF management system. This scheme is based on the original objective function (criterion function) represented by the price / quality ratio. The article presents an original block diagram for optimization the control system of the EAF. For designing this concept of EAF management system, many principles were used.
Combinatorial optimization games
Deng, X.; Ibaraki, Toshihide; Nagamochi, Hiroshi
1997-06-01
We introduce a general integer programming formulation for a class of combinatorial optimization games, which immediately allows us to improve the algorithmic result for finding amputations in the core (an important solution concept in cooperative game theory) of the network flow game on simple networks by Kalai and Zemel. An interesting result is a general theorem that the core for this class of games is nonempty if and only if a related linear program has an integer optimal solution. We study the properties for this mathematical condition to hold for several interesting problems, and apply them to resolve algorithmic and complexity issues for their cores along the line as put forward in: decide whether the core is empty; if the core is empty, find an imputation in the core; given an imputation x, test whether x is in the core. We also explore the properties of totally balanced games in this succinct formulation of cooperative games.
Trajectory Optimization: OTIS 4
NASA Technical Reports Server (NTRS)
Riehl, John P.; Sjauw, Waldy K.; Falck, Robert D.; Paris, Stephen W.
2010-01-01
The latest release of the Optimal Trajectories by Implicit Simulation (OTIS4) allows users to simulate and optimize aerospace vehicle trajectories. With OTIS4, one can seamlessly generate optimal trajectories and parametric vehicle designs simultaneously. New features also allow OTIS4 to solve non-aerospace continuous time optimal control problems. The inputs and outputs of OTIS4 have been updated extensively from previous versions. Inputs now make use of objectoriented constructs, including one called a metastring. Metastrings use a greatly improved calculator and common nomenclature to reduce the user s workload. They allow for more flexibility in specifying vehicle physical models, boundary conditions, and path constraints. The OTIS4 calculator supports common mathematical functions, Boolean operations, and conditional statements. This allows users to define their own variables for use as outputs, constraints, or objective functions. The user-defined outputs can directly interface with other programs, such as spreadsheets, plotting packages, and visualization programs. Internally, OTIS4 has more explicit and implicit integration procedures, including high-order collocation methods, the pseudo-spectral method, and several variations of multiple shooting. Users may switch easily between the various methods. Several unique numerical techniques such as automated variable scaling and implicit integration grid refinement, support the integration methods. OTIS4 is also significantly more user friendly than previous versions. The installation process is nearly identical on various platforms, including Microsoft Windows, Apple OS X, and Linux operating systems. Cross-platform scripts also help make the execution of OTIS and post-processing of data easier. OTIS4 is supplied free by NASA and is subject to ITAR (International Traffic in Arms Regulations) restrictions. Users must have a Fortran compiler, and a Python interpreter is highly recommended.
Singularity in structural optimization
NASA Technical Reports Server (NTRS)
Patnaik, S. N.; Guptill, J. D.; Berke, L.
1993-01-01
The conditions under which global and local singularities may arise in structural optimization are examined. Examples of these singularities are presented, and a framework is given within which the singularities can be recognized. It is shown, in particular, that singularities can be identified through the analysis of stress-displacement relations together with compatibility conditions or the displacement-stress relations derived by the integrated force method of structural analysis. Methods of eliminating the effects of singularities are suggested and illustrated numerically.
HOMER® Micropower Optimization Model
Lilienthal, P.
2005-01-01
NREL has developed the HOMER micropower optimization model. The model can analyze all of the available small power technologies individually and in hybrid configurations to identify least-cost solutions to energy requirements. This capability is valuable to a diverse set of energy professionals and applications. NREL has actively supported its growing user base and developed training programs around the model. These activities are helping to grow the global market for solar technologies.
Center for Parallel Optimization
1993-09-30
34, University of Wisconsin Computer Sciences Technical Report # 998, 1991, to appear, Linear Algebra and Its Applications. 29. K.P. Bennett & O.L...Robust linear programming discrimination of two lineally inseparable sets, Optimization Methods and Software 1, 1992, 23-34. 4. M.C. Ferris and O.L...variational in equality problems. Linear Algebra and Its Applications 174, 1992, 153-164. 9. O.L. Mangasarian and R.R. Meyer, Proceedings of the
Optimal Centroid Position Estimation
Candy, J V; McClay, W A; Awwal, A S; Ferguson, S W
2004-07-23
The alignment of high energy laser beams for potential fusion experiments demand high precision and accuracy by the underlying positioning algorithms. This paper discusses the feasibility of employing online optimal position estimators in the form of model-based processors to achieve the desired results. Here we discuss the modeling, development, implementation and processing of model-based processors applied to both simulated and actual beam line data.
Optimized lithium oxyhalide cells
NASA Astrophysics Data System (ADS)
Kilroy, W. P.; Schlaikjer, C.; Polsonetti, P.; Jones, M.
1993-04-01
Lithium thionyl chloride cells were optimized with respect to electrolyte and carbon cathode composition. Wound 'C-size' cells with various mixtures of Chevron acetylene black with Ketjenblack EC-300J and containing various concentrations of LiAlCl4 and derivatives, LiGaCl4, and mixtures of SOCl2 and SO2Cl2 were evaluated as a function of discharge rate, temperature, and storage condition.
Fault Tolerant Optimal Control.
1982-08-01
i k+l since the cost to be minimized in (D.2.3) increases withXk (for fixed xsk). When we have b k _ x~ ji ] Aj M 2a(j) R(j) x bOk +l x]rkt] -b (j...22, pp. 236-239. 69. D.D.Sworder and L.L. Choi (1976): Stationary Cost Densities for Optimally Controlled Stochastic Systems, IEEE Trans. Automatic
Nicholas, D.M.; Wilkins, J.T.
1983-09-01
Innovative design of physical solvent plants for acid gas removal can materially reduce both installation and operating costs. A review of the design considerations for one physical solvent process (Selexol) points to numerous arrangements for potential improvement. These are evaluated for a specific case in four combinations that identify an optimum for the case in question but, more importantly, illustrate the mechanism for use for such optimization elsewhere.
NASA Astrophysics Data System (ADS)
Bottasso, C. L.; Croce, A.; Riboldi, C. E. D.
2014-06-01
The paper presents a novel approach for the synthesis of the open-loop pitch profile during emergency shutdowns. The problem is of interest in the design of wind turbines, as such maneuvers often generate design driving loads on some of the machine components. The pitch profile synthesis is formulated as a constrained optimal control problem, solved numerically using a direct single shooting approach. A cost function expressing a compromise between load reduction and rotor overspeed is minimized with respect to the unknown blade pitch profile. Constraints may include a load reduction not-to-exceed the next dominating loads, a not-to-be-exceeded maximum rotor speed, and a maximum achievable blade pitch rate. Cost function and constraints are computed over a possibly large number of operating conditions, defined so as to cover as well as possible the operating situations encountered in the lifetime of the machine. All such conditions are simulated by using a high-fidelity aeroservoelastic model of the wind turbine, ensuring the accuracy of the evaluation of all relevant parameters. The paper demonstrates the capabilities of the novel proposed formulation, by optimizing the pitch profile of a multi-MW wind turbine. Results show that the procedure can reliably identify optimal pitch profiles that reduce design-driving loads, in a fully automated way.
NASA Technical Reports Server (NTRS)
Vanderplaats, Garrett; Townsend, James C. (Technical Monitor)
2002-01-01
The purpose of this research under the NASA Small Business Innovative Research program was to develop algorithms and associated software to solve very large nonlinear, constrained optimization tasks. Key issues included efficiency, reliability, memory, and gradient calculation requirements. This report describes the general optimization problem, ten candidate methods, and detailed evaluations of four candidates. The algorithm chosen for final development is a modern recreation of a 1960s external penalty function method that uses very limited computer memory and computational time. Although of lower efficiency, the new method can solve problems orders of magnitude larger than current methods. The resulting BIGDOT software has been demonstrated on problems with 50,000 variables and about 50,000 active constraints. For unconstrained optimization, it has solved a problem in excess of 135,000 variables. The method includes a technique for solving discrete variable problems that finds a "good" design, although a theoretical optimum cannot be guaranteed. It is very scalable in that the number of function and gradient evaluations does not change significantly with increased problem size. Test cases are provided to demonstrate the efficiency and reliability of the methods and software.
Miller, Jeff; Ulrich, Rolf
2016-09-01
In this article, we present a model for determining how total research payoff depends on researchers' choices of sample sizes, α levels, and other parameters of the research process. The model can be used to quantify various trade-offs inherent in the research process and thus to balance competing goals, such as (a) maximizing both the number of studies carried out and also the statistical power of each study, (b) minimizing the rates of both false positive and false negative findings, and (c) maximizing both replicability and research efficiency. Given certain necessary information about a research area, the model can be used to determine the optimal values of sample size, statistical power, rate of false positives, rate of false negatives, and replicability, such that overall research payoff is maximized. More specifically, the model shows how the optimal values of these quantities depend upon the size and frequency of true effects within the area, as well as the individual payoffs associated with particular study outcomes. The model is particularly relevant within current discussions of how to optimize the productivity of scientific research, because it shows which aspects of a research area must be considered and how these aspects combine to determine total research payoff.
Optimal Gaussian entanglement swapping
Hoelscher-Obermaier, Jason; Loock, Peter van
2011-01-15
We consider entanglement swapping with general mixed two-mode Gaussian states and calculate the optimal gains for a broad class of such states including those states most relevant in communication scenarios. We show that, for this class of states, entanglement swapping adds no additional mixedness; that is, the ensemble-average output state has the same purity as the input states. This implies that, by using intermediate entanglement swapping steps, it is, in principle, possible to distribute entangled two-mode Gaussian states of higher purity as compared to direct transmission. We then apply the general results on optimal Gaussian swapping to the problem of quantum communication over a lossy fiber and demonstrate that, in contrast to the negative conclusions in the literature, swapping-based schemes in fact often perform better than direct transmission for high input squeezing. However, an effective transmission analysis reveals that the hope for improved performance based on optimal Gaussian entanglement swapping is spurious since the swapping does not lead to an enhancement of the effective transmission. This implies that the same or better results can always be obtained using direct transmission in combination with, in general, less squeezing.
Optimization by record dynamics
NASA Astrophysics Data System (ADS)
Barettin, Daniele; Sibani, Paolo
2014-03-01
Large dynamical changes in thermalizing glassy systems are triggered by trajectories crossing record sized barriers, a behavior revealing the presence of a hierarchical structure in configuration space. The observation is here turned into a novel local search optimization algorithm dubbed record dynamics optimization, or RDO. RDO uses the Metropolis rule to accept or reject candidate solutions depending on the value of a parameter akin to the temperature and minimizes the cost function of the problem at hand through cycles where its ‘temperature’ is raised and subsequently decreased in order to expediently generate record high (and low) values of the cost function. Below, RDO is introduced and then tested by searching for the ground state of the Edwards-Anderson spin-glass model, in two and three spatial dimensions. A popular and highly efficient optimization algorithm, parallel tempering (PT), is applied to the same problem as a benchmark. RDO and PT turn out to produce solutions of similar quality for similar numerical effort, but RDO is simpler to program and additionally yields geometrical information on the system’s configuration space which is of interest in many applications. In particular, the effectiveness of RDO strongly indicates the presence of the above mentioned hierarchically organized configuration space, with metastable regions indexed by the cost (or energy) of the transition states connecting them.
2016-10-04
In this work, we have implemented and developed the simulation software to implement the mathematical model of an AC Optimal Power Flow (OPF) problem. The objective function is to minimize the total cost of generation subject to constraints of node power balance (both real and reactive) and line power flow limits (MW, MVAr, and MVA). We have currently implemented the polar coordinate version of the problem. In the present work, we have used the optimization solver, Knitro (proprietary and not included in this software) to solve the problem and we have kept option for both the native numerical derivative evaluation (working satisfactorily now) as well as for analytical formulas corresponding to the derivatives being provided to Knitro (currently, in the debugging stage). Since the AC OPF is a highly non-convex optimization problem, we have also kept the option for a multistart solution. All of these can be decided by the user during run-time in an interactive manner. The software has been developed in C++ programming language, running with GCC compiler on a Linux machine. We have tested for satisfactory results against Matpower for the IEEE 14 bus system.
Optimal Temporal Risk Assessment
Balci, Fuat; Freestone, David; Simen, Patrick; deSouza, Laura; Cohen, Jonathan D.; Holmes, Philip
2011-01-01
Time is an essential feature of most decisions, because the reward earned from decisions frequently depends on the temporal statistics of the environment (e.g., on whether decisions must be made under deadlines). Accordingly, evolution appears to have favored a mechanism that predicts intervals in the seconds to minutes range with high accuracy on average, but significant variability from trial to trial. Importantly, the subjective sense of time that results is sufficiently imprecise that maximizing rewards in decision-making can require substantial behavioral adjustments (e.g., accumulating less evidence for a decision in order to beat a deadline). Reward maximization in many daily decisions therefore requires optimal temporal risk assessment. Here, we review the temporal decision-making literature, conduct secondary analyses of relevant published datasets, and analyze the results of a new experiment. The paper is organized in three parts. In the first part, we review literature and analyze existing data suggesting that animals take account of their inherent behavioral variability (their “endogenous timing uncertainty”) in temporal decision-making. In the second part, we review literature that quantitatively demonstrates nearly optimal temporal risk assessment with sub-second and supra-second intervals using perceptual tasks (with humans and mice) and motor timing tasks (with humans). We supplement this section with original research that tested human and rat performance on a task that requires finding the optimal balance between two time-dependent quantities for reward maximization. This optimal balance in turn depends on the level of timing uncertainty. Corroborating the reviewed literature, humans and rats exhibited nearly optimal temporal risk assessment in this task. In the third section, we discuss the role of timing uncertainty in reward maximization in two-choice perceptual decision-making tasks and review literature that implicates timing uncertainty
Dall'Anese, Emiliano
2016-08-01
Past works that focused on addressing power-quality and reliability concerns related to renewable energy resources (RESs) operating with business-as-usual practices have looked at the design of Volt/VAr and Volt/Watt strategies to regulate real or reactive powers based on local voltage measurements, so that terminal voltages are within acceptable levels. These control strategies have the potential of operating at the same time scale of distribution-system dynamics, and can therefore mitigate disturbances precipitated fast time-varying loads and ambient conditions; however, they do not necessarily guarantee system-level optimality, and stability claims are mainly based on empirical evidences. On a different time scale, centralized and distributed optimal power flow (OPF) algorithms have been proposed to compute optimal steady-state inverter setpoints, so that power losses and voltage deviations are minimized and economic benefits to end-users providing ancillary services are maximized. However, traditional OPF schemes may offer decision making capabilities that do not match the dynamics of distribution systems. Particularly, during the time required to collect data from all the nodes of the network (e.g., loads), solve the OPF, and subsequently dispatch setpoints, the underlying load, ambient, and network conditions may have already changed; in this case, the DER output powers would be consistently regulated around outdated setpoints, leading to suboptimal system operation and violation of relevant electrical limits. The present work focuses on the synthesis of distributed RES-inverter controllers that leverage the opportunities for fast feedback offered by power-electronics interfaced RESs. The overarching objective is to bridge the temporal gap between long-term system optimization and real-time control, to enable seamless RES integration in large scale with stability and efficiency guarantees, while congruently pursuing system-level optimization objectives. The
Ames Optimized TCA Configuration
NASA Technical Reports Server (NTRS)
Cliff, Susan E.; Reuther, James J.; Hicks, Raymond M.
1999-01-01
Configuration design at Ames was carried out with the SYN87-SB (single block) Euler code using a 193 x 49 x 65 C-H grid. The Euler solver is coupled to the constrained (NPSOL) and the unconstrained (QNMDIF) optimization packages. Since the single block grid is able to model only wing-body configurations, the nacelle/diverter effects were included in the optimization process by SYN87's option to superimpose the nacelle/diverter interference pressures on the wing. These interference pressures were calculated using the AIRPLANE code. AIRPLANE is an Euler solver that uses a unstructured tetrahedral mesh and is capable of computations about arbitrary complete configurations. In addition, the buoyancy effects of the nacelle/diverters were also included in the design process by imposing the pressure field obtained during the design process onto the triangulated surfaces of the nacelle/diverter mesh generated by AIRPLANE. The interference pressures and nacelle buoyancy effects are added to the final forces after each flow field calculation. Full details of the (recently enhanced) ghost nacelle capability are given in a related talk. The pseudo nacelle corrections were greatly improved during this design cycle. During the Ref H and Cycle 1 design activities, the nacelles were only translated and pitched. In the cycle 2 design effort the nacelles can translate vertically, and pitch to accommodate the changes in the lower surface geometry. The diverter heights (between their leading and trailing edges) were modified during design as the shape of the lower wing changed, with the drag of the diverter changing accordingly. Both adjoint and finite difference gradients were used during optimization. The adjoint-based gradients were found to give good direction in the design space for configurations near the starting point, but as the design approached a minimum, the finite difference gradients were found to be more accurate. Use of finite difference gradients was limited by the
Taking Stock of Unrealistic Optimism.
Shepperd, James A; Klein, William M P; Waters, Erika A; Weinstein, Neil D
2013-07-01
Researchers have used terms such as unrealistic optimism and optimistic bias to refer to concepts that are similar but not synonymous. Drawing from three decades of research, we critically discuss how researchers define unrealistic optimism and we identify four types that reflect different measurement approaches: unrealistic absolute optimism at the individual and group level and unrealistic comparative optimism at the individual and group level. In addition, we discuss methodological criticisms leveled against research on unrealistic optimism and note that the criticisms are primarily relevant to only one type-the group form of unrealistic comparative optimism. We further clarify how the criticisms are not nearly as problematic even for unrealistic comparative optimism as they might seem. Finally, we note boundary conditions on the different types of unrealistic optimism and reflect on five broad questions that deserve further attention.
Taking Stock of Unrealistic Optimism
Shepperd, James A.; Klein, William M. P.; Waters, Erika A.; Weinstein, Neil D.
2015-01-01
Researchers have used terms such as unrealistic optimism and optimistic bias to refer to concepts that are similar but not synonymous. Drawing from three decades of research, we critically discuss how researchers define unrealistic optimism and we identify four types that reflect different measurement approaches: unrealistic absolute optimism at the individual and group level and unrealistic comparative optimism at the individual and group level. In addition, we discuss methodological criticisms leveled against research on unrealistic optimism and note that the criticisms are primarily relevant to only one type—the group form of unrealistic comparative optimism. We further clarify how the criticisms are not nearly as problematic even for unrealistic comparative optimism as they might seem. Finally, we note boundary conditions on the different types of unrealistic optimism and reflect on five broad questions that deserve further attention. PMID:26045714
Computer program for parameter optimization
NASA Technical Reports Server (NTRS)
Glatt, C. R.; Hague, D. S.
1968-01-01
Flexible, large scale digital computer program was designed for the solution of a wide range of multivariable parameter optimization problems. The program has the ability to solve constrained optimization problems involving up to one hundred parameters.
Combinatorial optimization in foundry practice
NASA Astrophysics Data System (ADS)
Antamoshkin, A. N.; Masich, I. S.
2016-04-01
The multicriteria mathematical model of foundry production capacity planning is suggested in the paper. The model is produced in terms of pseudo-Boolean optimization theory. Different search optimization methods were used to solve the obtained problem.
A Primer on Unrealistic Optimism.
Shepperd, James A; Waters, Erika; Weinstein, Neil D; Klein, William M P
2015-06-01
People display unrealistic optimism in their predictions for countless events, believing that their personal future outcomes will be more desirable than can possibly be true. We summarize the vast literature on unrealistic optimism by focusing on four broad questions: What is unrealistic optimism; when does it occur; why does it occur; and what are its consequences.
ERIC Educational Resources Information Center
Reivich, Karen
2010-01-01
Dictionary definitions of optimism encompass two related concepts. The first of these is a hopeful disposition or a conviction that good will ultimately prevail. The second, broader conception of optimism refers to the belief, or the inclination to believe, that the world is the best of all possible worlds. In psychological research, optimism has…
Multicriteria VMAT optimization
Craft, David; McQuaid, Dualta; Wala, Jeremiah; Chen, Wei; Salari, Ehsan; Bortfeld, Thomas
2012-02-15
Purpose: To make the planning of volumetric modulated arc therapy (VMAT) faster and to explore the tradeoffs between planning objectives and delivery efficiency. Methods: A convex multicriteria dose optimization problem is solved for an angular grid of 180 equi-spaced beams. This allows the planner to navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus organ at risk sparing. The selected plan is then made VMAT deliverable by a fluence map merging and sequencing algorithm, which combines neighboring fluence maps based on a similarity score and then delivers the merged maps together, simplifying delivery. Successive merges are made as long as the dose distribution quality is maintained. The complete algorithm is called VMERGE. Results: VMERGE is applied to three cases: a prostate, a pancreas, and a brain. In each case, the selected Pareto-optimal plan is matched almost exactly with the VMAT merging routine, resulting in a high quality plan delivered with a single arc in less than 5 min on average. Conclusions: VMERGE offers significant improvements over existing VMAT algorithms. The first is the multicriteria planning aspect, which greatly speeds up planning time and allows the user to select the plan, which represents the most desirable compromise between target coverage and organ at risk sparing. The second is the user-chosen epsilon-optimality guarantee of the final VMAT plan. Finally, the user can explore the tradeoff between delivery time and plan quality, which is a fundamental aspect of VMAT that cannot be easily investigated with current commercial planning systems.
Experience in grid optimization
NASA Technical Reports Server (NTRS)
Mastin, C. W.; Soni, B. K.; Mcclure, M. D.
1987-01-01
Two optimization methods for solving a variational problem in grid generation are described and evaluated. The smoothness, cell volumes, and orthogonality of the variational integrals are examined. The Jacobi-Newton iterative method is compared to the Fletcher-Reeves conjugate gradient method. It is observed that a combination of the Jacobi-Newton iteration and the direct solution of the variational problem produces an algorithm which is easy to program and requires less storage and computer time/iteration than the conjugate gradient method.
Optimizing Methods in Simulation
1981-08-01
exploited by Kiefer and Wolfowitz -; (1959). Wald (1943) used the criterion of D-optimality - in some other context and was so named by Kiefer and...of discrepency between the observed and expected value A is obtained in terms of mean squared errors ( MSE ). i Consider the model, E(Ylx) = a + ex and...V(YIX) = 0 2 Let L < x < U, be the interval of possible x values. The MSE (x) is the mean squared error of x as obtained from y. Let w(x) be a weight
Astrocytes optimize synaptic fidelity
NASA Astrophysics Data System (ADS)
Nadkarni, Suhita; Jung, Peter; Levine, Herbert
2007-03-01
Most neuronal synapses in the central nervous system are enwrapped by an astrocytic process. This relation allows the astrocyte to listen to and feed back to the synapse and to regulate synaptic transmission. We combine a tested mathematical model for the Ca^2+ response of the synaptic astrocyte and presynaptic feedback with a detailed model for vesicle release of neurotransmitter at active zones. The predicted Ca^2+ dependence of the presynaptic synaptic vesicle release compares favorably for several types of synapses, including the Calyx of Held. We hypothesize that the feedback regulation of the astrocyte onto the presynaptic terminal optimizes the fidelity of the synapse in terms of information transmission.
Universal optimal quantum correlator
NASA Astrophysics Data System (ADS)
Buscemi, Francesco; Dall'Arno, Michele; Ozawa, Masanao; Vedral, Vlatko
2014-10-01
Recently, a novel operational strategy to access quantum correlation functions of the form Tr[AρB] was provided in [F. Buscemi, M. Dall'Arno, M. Ozawa and V. Vedral, arXiv:1312.4240]. Here we propose a realization scheme, that we call partial expectation values, implementing such strategy in terms of a unitary interaction with an ancillary system followed by the measurement of an observable on the ancilla. Our scheme is universal, being independent of ρ, A, and B, and it is optimal in a statistical sense. Our scheme is suitable for implementation with present quantum optical technology, and provides a new way to test uncertainty relations.
Optimizing passive quantum clocks
NASA Astrophysics Data System (ADS)
Mullan, Michael; Knill, Emanuel
2014-10-01
We describe protocols for passive atomic clocks based on quantum interrogation of the atoms. Unlike previous techniques, our protocols are adaptive and take advantage of prior information about the clock's state. To reduce deviations from an ideal clock, each interrogation is optimized by means of a semidefinite program for atomic state preparation and measurement whose objective function depends on the prior information. Our knowledge of the clock's state is maintained according to a Bayesian model that accounts for noise and measurement results. We implement a full simulation of a running clock with power-law noise models and find significant improvements by applying our techniques.
Nonconvex optimization and jamming
NASA Astrophysics Data System (ADS)
Kallus, Yoav
Recent work on the jamming transition of particles with short-range interactions has drawn connections with models based on minimization problems with linear inequality constraints and a concave objective. These properties reduce the continuous optimization problem to a discrete search among the corners of the feasible polytope. I will discuss results from simulations of models with and without quenched disorder, exhibiting critical power laws, scaling collapse, and protocol dependence. These models are also well-suited for study using tools of algebraic topology, which I will discuss briefly. Supported by an Omidyar Fellowship at the Santa Fe Institute.
Constructing optimal entanglement witnesses
Chruscinski, Dariusz; Pytel, Justyna; Sarbicki, Gniewomir
2009-12-15
We provide a class of indecomposable entanglement witnesses. In 4x4 case, it reproduces the well-known Breuer-Hall witness. We prove that these witnesses are optimal and atomic, i.e., they are able to detect the 'weakest' quantum entanglement encoded into states with positive partial transposition. Equivalently, we provide a construction of indecomposable atomic maps in the algebra of 2kx2k complex matrices. It is shown that their structural physical approximations give rise to entanglement breaking channels. This result supports recent conjecture by Korbicz et al. [Phys. Rev. A 78, 062105 (2008)].
Optimized joystick controller.
Ding, D; Cooper, R A; Spaeth, D
2004-01-01
The purpose of the study was to develop an optimized joystick control interface for electric powered wheelchairs and thus provide safe and effective control of electric powered wheelchairs to people with severe physical disabilities. The interface enables clinicians to tune joystick parameters for each individual subject through selecting templates, dead zones, and bias axes. In terms of hand tremor usually associated with people with traumatic brain injury, cerebral palsy, and multiple sclerosis, fuzzy logic rules were applied to suppress erratic hand movements and extract the intended motion from the joystick. Simulation results were presented to show the graphical tuning interface as well as the performance of the fuzzy logic controller.
An Improved Cockroach Swarm Optimization
Obagbuwa, I. C.; Adewumi, A. O.
2014-01-01
Hunger component is introduced to the existing cockroach swarm optimization (CSO) algorithm to improve its searching ability and population diversity. The original CSO was modelled with three components: chase-swarming, dispersion, and ruthless; additional hunger component which is modelled using partial differential equation (PDE) method is included in this paper. An improved cockroach swarm optimization (ICSO) is proposed in this paper. The performance of the proposed algorithm is tested on well known benchmarks and compared with the existing CSO, modified cockroach swarm optimization (MCSO), roach infestation optimization RIO, and hungry roach infestation optimization (HRIO). The comparison results show clearly that the proposed algorithm outperforms the existing algorithms. PMID:24959611
Design Optimization Toolkit: Users' Manual
Aguilo Valentin, Miguel Alejandro
2014-07-01
The Design Optimization Toolkit (DOTk) is a stand-alone C++ software package intended to solve complex design optimization problems. DOTk software package provides a range of solution methods that are suited for gradient/nongradient-based optimization, large scale constrained optimization, and topology optimization. DOTk was design to have a flexible user interface to allow easy access to DOTk solution methods from external engineering software packages. This inherent flexibility makes DOTk barely intrusive to other engineering software packages. As part of this inherent flexibility, DOTk software package provides an easy-to-use MATLAB interface that enables users to call DOTk solution methods directly from the MATLAB command window.
Wang, Yong; Li, Han-Xiong; Yen, Gary G; Song, Wu
2015-04-01
In the field of evolutionary computation, there has been a growing interest in applying evolutionary algorithms to solve multimodal optimization problems (MMOPs). Due to the fact that an MMOP involves multiple optimal solutions, many niching methods have been suggested and incorporated into evolutionary algorithms for locating such optimal solutions in a single run. In this paper, we propose a novel transformation technique based on multiobjective optimization for MMOPs, called MOMMOP. MOMMOP transforms an MMOP into a multiobjective optimization problem with two conflicting objectives. After the above transformation, all the optimal solutions of an MMOP become the Pareto optimal solutions of the transformed problem. Thus, multiobjective evolutionary algorithms can be readily applied to find a set of representative Pareto optimal solutions of the transformed problem, and as a result, multiple optimal solutions of the original MMOP could also be simultaneously located in a single run. In principle, MOMMOP is an implicit niching method. In this paper, we also discuss two issues in MOMMOP and introduce two new comparison criteria. MOMMOP has been used to solve 20 multimodal benchmark test functions, after combining with nondominated sorting and differential evolution. Systematic experiments have indicated that MOMMOP outperforms a number of methods for multimodal optimization, including four recent methods at the 2013 IEEE Congress on Evolutionary Computation, four state-of-the-art single-objective optimization based methods, and two well-known multiobjective optimization based approaches.
Bower, Stanley
2011-12-31
A 5.0L V8 twin-turbocharged direct injection engine was designed, built, and tested for the purpose of assessing the fuel economy and performance in the F-Series pickup of the Dual Fuel engine concept and of an E85 optimized FFV engine. Additionally, production 3.5L gasoline turbocharged direct injection (GTDI) EcoBoost engines were converted to Dual Fuel capability and used to evaluate the cold start emissions and fuel system robustness of the Dual Fuel engine concept. Project objectives were: to develop a roadmap to demonstrate a minimized fuel economy penalty for an F-Series FFV truck with a highly boosted, high compression ratio spark ignition engine optimized to run with ethanol fuel blends up to E85; to reduce FTP 75 energy consumption by 15% - 20% compared to an equally powered vehicle with a current production gasoline engine; and to meet ULEV emissions, with a stretch target of ULEV II / Tier II Bin 4. All project objectives were met or exceeded.
Optimization Methods in Sherpa
NASA Astrophysics Data System (ADS)
Siemiginowska, Aneta; Nguyen, Dan T.; Doe, Stephen M.; Refsdal, Brian L.
2009-09-01
Forward fitting is a standard technique used to model X-ray data. A statistic, usually assumed weighted chi^2 or Poisson likelihood (e.g. Cash), is minimized in the fitting process to obtain a set of the best model parameters. Astronomical models often have complex forms with many parameters that can be correlated (e.g. an absorbed power law). Minimization is not trivial in such setting, as the statistical parameter space becomes multimodal and finding the global minimum is hard. Standard minimization algorithms can be found in many libraries of scientific functions, but they are usually focused on specific functions. However, Sherpa designed as general fitting and modeling application requires very robust optimization methods that can be applied to variety of astronomical data (X-ray spectra, images, timing, optical data etc.). We developed several optimization algorithms in Sherpa targeting a wide range of minimization problems. Two local minimization methods were built: Levenberg-Marquardt algorithm was obtained from MINPACK subroutine LMDIF and modified to achieve the required robustness; and Nelder-Mead simplex method has been implemented in-house based on variations of the algorithm described in the literature. A global search Monte-Carlo method has been implemented following a differential evolution algorithm presented by Storn and Price (1997). We will present the methods in Sherpa and discuss their usage cases. We will focus on the application to Chandra data showing both 1D and 2D examples. This work is supported by NASA contract NAS8-03060 (CXC).
Optimal Synchronizability of Bearings
NASA Astrophysics Data System (ADS)
Araújo, N. A. M.; Seybold, H.; Baram, R. M.; Herrmann, H. J.; Andrade, J. S., Jr.
2013-02-01
Bearings are mechanical dissipative systems that, when perturbed, relax toward a synchronized (bearing) state. Here we find that bearings can be perceived as physical realizations of complex networks of oscillators with asymmetrically weighted couplings. Accordingly, these networks can exhibit optimal synchronization properties through fine-tuning of the local interaction strength as a function of node degree [Motter, Zhou, and Kurths, Phys. Rev. E 71, 016116 (2005)PLEEE81539-3755]. We show that, in analogy, the synchronizability of bearings can be maximized by counterbalancing the number of contacts and the inertia of their constituting rotor disks through the mass-radius relation, m˜rα, with an optimal exponent α=α× which converges to unity for a large number of rotors. Under this condition, and regardless of the presence of a long-tailed distribution of disk radii composing the mechanical system, the average participation per disk is maximized and the energy dissipation rate is homogeneously distributed among elementary rotors.
[Optimizing surgical hand disinfection].
Kampf, G; Kramer, A; Rotter, M; Widmer, A
2006-08-01
For more than 110 years hands of surgeons have been treated before a surgical procedure in order to reduce the bacterial density. The kind and duration of treatment, however, has changed significantly over time. Recent scientific evidence suggests a few changes with the aim to optimize both the efficacy and the dermal tolerance. Aim of this article is the presentation and discussion of new insights in surgical hand disinfection. A hand wash should be performed before the first disinfection of a day, ideally at least 10 min before the beginning of the disinfection as it has been shown that a 1 min hand wash significantly increases skin hydration for up to 10 min. The application time may be as short as 1.5 min depending on the type of hand rub. Hands and forearms should be kept wet with the hand rub for the recommended application time in any case. A specific rub-in procedure according to EN 12791 has been found to be suitable in order to avoid untreated skin areas. The alcohol-based hand rub should have a proven excellent dermal tolerance in order to ensure appropriate compliance. Considering these elements in clinical practice can have a significant impact to optimize the high quality of surgical hand disinfection for prevention of surgical site infections.
Optimal synchronizability of networks
NASA Astrophysics Data System (ADS)
Wang, B.; Zhou, T.; Xiu, Z. L.; Kim, B. J.
2007-11-01
We numerically investigate how to enhance synchronizability of coupled identical oscillators in complex networks with research focus on the roles of the high level of clustering for a given heterogeneity in the degree distribution. By using the edge-exchange method with the fixed degree sequence, we first directly maximize synchronizability measured by the eigenratio of the coupling matrix, through the use of the so-called memory tabu search algorithm developed in applied mathematics. The resulting optimal network, which turns out to be weakly disassortative, is observed to exhibit a small modularity. More importantly, it is clearly revealed that the optimally synchronizable network for a given degree sequence shows a very low level of clustering, containing much fewer small-size loops than the original network. We then use the clustering coefficient as an object function to be reduced during the edge exchanges, and find it a very efficient way to enhance synchronizability. We thus conclude that under the condition of a given degree heterogeneity, the clustering plays a very important role in the network synchronization.
Optimality and sub-optimality in a bacterial growth law.
Towbin, Benjamin D; Korem, Yael; Bren, Anat; Doron, Shany; Sorek, Rotem; Alon, Uri
2017-01-19
Organisms adjust their gene expression to improve fitness in diverse environments. But finding the optimal expression in each environment presents a challenge. We ask how good cells are at finding such optima by studying the control of carbon catabolism genes in Escherichia coli. Bacteria show a growth law: growth rate on different carbon sources declines linearly with the steady-state expression of carbon catabolic genes. We experimentally modulate gene expression to ask if this growth law always maximizes growth rate, as has been suggested by theory. We find that the growth law is optimal in many conditions, including a range of perturbations to lactose uptake, but provides sub-optimal growth on several other carbon sources. Combining theory and experiment, we genetically re-engineer E. coli to make sub-optimal conditions into optimal ones and vice versa. We conclude that the carbon growth law is not always optimal, but represents a practical heuristic that often works but sometimes fails.
Strong Combination of Ant Colony Optimization with Constraint Programming Optimization
NASA Astrophysics Data System (ADS)
Khichane, Madjid; Albert, Patrick; Solnon, Christine
We introduce an approach which combines ACO (Ant Colony Optimization) and IBM ILOG CP Optimizer for solving COPs (Combinatorial Optimization Problems). The problem is modeled using the CP Optimizer modeling API. Then, it is solved in a generic way by a two-phase algorithm. The first phase aims at creating a hot start for the second: it samples the solution space and applies reinforcement learning techniques as implemented in ACO to create pheromone trails. During the second phase, CP Optimizer performs a complete tree search guided by the pheromone trails previously accumulated. The first experimental results on knapsack, quadratic assignment and maximum independent set problems show that this new algorithm enhances the performance of CP Optimizer alone.
Particle swarm optimization for complex nonlinear optimization problems
NASA Astrophysics Data System (ADS)
Alexandridis, Alex; Famelis, Ioannis Th.; Tsitouras, Charalambos
2016-06-01
This work presents the application of a technique belonging to evolutionary computation, namely particle swarm optimization (PSO), to complex nonlinear optimization problems. To be more specific, a PSO optimizer is setup and applied to the derivation of Runge-Kutta pairs for the numerical solution of initial value problems. The effect of critical PSO operational parameters on the performance of the proposed scheme is thoroughly investigated.
NASA Astrophysics Data System (ADS)
Rebilas, Krzysztof
2013-02-01
Consider a skier who goes down a takeoff ramp, attains a speed V, and jumps, attempting to land as far as possible down the hill below (Fig. 1). At the moment of takeoff the angle between the skier's velocity and the horizontal is α. What is the optimal angle α that makes the jump the longest possible for the fixed magnitude of the velocity V? Of course, in practice, this is a very sophisticated problem; the skier's range depends on a variety of complex factors in addition to V and α. However, if we ignore these and assume the jumper is in free fall between the takeoff ramp and the landing point below, the problem becomes an exercise in kinematics that is suitable for introductory-level students. The solution is presented here.
The optimal target hemoglobin.
Ritz, E; Schwenger, V
2000-07-01
There is still controversy concerning the optimal target hemoglobin during treatment with recombinant human erythropoietin (rHuEPO). Some evidence suggests that hemoglobin concentrations higher than currently recommended lead to improvements in cognitive function, physical performance, and rehabilitation. At least in patients with advanced cardiac disease, however, one controlled trial failed to show a benefit from normalizing predialysis hemoglobin concentrations. In contrast, preliminary observations in three additional studies (albeit with limited statistical power) failed to show adverse cardiovascular effects from normalization of hemoglobin, but definite benefit with respect to quality of life, physical performance, and cardiac geometry. These observations are consistent with the notion that hemoglobin concentrations higher than those recommended by the National Kidney Foundation Dialysis Outcomes Quality Initiative Anemia Work Group are beneficial, at least in patients without advanced cardiac disease.
DENSE MEDIA CYCLONE OPTIMIZATION
Gerald H. Luttrell
2002-01-14
During the past quarter, float-sink analyses were completed for four of seven circuits evaluated in this project. According to the commercial laboratory, the analyses for the remaining three sites will be finished by mid February 2002. In addition, it was necessary to repeat several of the float-sink tests to resolve problems identified during the analysis of the experimental data. In terms of accomplishments, a website is being prepared to distribute project findings and software to the public. This site will include (i) an operators manual for HMC operation and maintenance (already available in hard copy), (ii) an expert system software package for evaluating and optimizing HMC performance (in development), and (iii) a spreadsheet-based process model for plant designers (in development). Several technology transfer activities were also carried out including the publication of project results in proceedings and the training of plant operations via workshops.
Cyclone performance and optimization
Leith, D.
1989-06-15
The objectives of this project are: to characterize the gas flow pattern within cyclones, to revise the theory for cyclone performance on the basis of these findings, and to design and test cyclones whose dimensions have been optimized using revised performance theory. This work is important because its successful completion will aid in the technology for combustion of coal in pressurized, fluidized beds. We have now received all the equipment necessary for the flow visualization studies described over the last two progress reports. We have begun more detailed studies of the gas flow pattern within cyclones as detailed below. Third, we have begun studies of the effect of particle concentration on cyclone performance. This work is critical to application of our results to commercial operations. 1 fig.
Optimal optoacoustic detector design
NASA Technical Reports Server (NTRS)
Rosengren, L.-G.
1975-01-01
Optoacoustic detectors are used to measure pressure changes occurring in enclosed gases, liquids, or solids being excited by intensity or frequency modulated electromagnetic radiation. Radiation absorption spectra, collisional relaxation rates, substance compositions, and reactions can be determined from the time behavior of these pressure changes. Very successful measurements of gaseous air pollutants have, for instance, been performed by using detectors of this type together with different lasers. The measuring instrument consisting of radiation source, modulator, optoacoustic detector, etc. is often called spectrophone. In the present paper, a thorough optoacoustic detector optimization analysis based upon a review of its theory of operation is introduced. New quantitative rules and suggestions explaining how to design detectors with maximal pressure responsivity and over-all sensitivity and minimal background signal are presented.
Optimal Blind Quantum Computation
NASA Astrophysics Data System (ADS)
Mantri, Atul; Pérez-Delgado, Carlos A.; Fitzsimons, Joseph F.
2013-12-01
Blind quantum computation allows a client with limited quantum capabilities to interact with a remote quantum computer to perform an arbitrary quantum computation, while keeping the description of that computation hidden from the remote quantum computer. While a number of protocols have been proposed in recent years, little is currently understood about the resources necessary to accomplish the task. Here, we present general techniques for upper and lower bounding the quantum communication necessary to perform blind quantum computation, and use these techniques to establish concrete bounds for common choices of the client’s quantum capabilities. Our results show that the universal blind quantum computation protocol of Broadbent, Fitzsimons, and Kashefi, comes within a factor of (8)/(3) of optimal when the client is restricted to preparing single qubits. However, we describe a generalization of this protocol which requires exponentially less quantum communication when the client has a more sophisticated device.
RLV Turbine Performance Optimization
NASA Technical Reports Server (NTRS)
Griffin, Lisa W.; Dorney, Daniel J.
2001-01-01
A task was developed at NASA/Marshall Space Flight Center (MSFC) to improve turbine aerodynamic performance through the application of advanced design and analysis tools. There are four major objectives of this task: 1) to develop, enhance, and integrate advanced turbine aerodynamic design and analysis tools; 2) to develop the methodology for application of the analytical techniques; 3) to demonstrate the benefits of the advanced turbine design procedure through its application to a relevant turbine design point; and 4) to verify the optimized design and analysis with testing. Final results of the preliminary design and the results of the two-dimensional (2D) detailed design of the first-stage vane of a supersonic turbine suitable for a reusable launch vehicle (R-LV) are presented. Analytical techniques for obtaining the results are also discussed.
Optimality in Data Assimilation
NASA Astrophysics Data System (ADS)
Nearing, Grey; Yatheendradas, Soni
2016-04-01
It costs a lot more to develop and launch an earth-observing satellite than it does to build a data assimilation system. As such, we propose that it is important to understand the efficiency of our assimilation algorithms at extracting information from remote sensing retrievals. To address this, we propose that it is necessary to adopt completely general definition of "optimality" that explicitly acknowledges all differences between the parametric constraints of our assimilation algorithm (e.g., Gaussianity, partial linearity, Markovian updates) and the true nature of the environmetnal system and observing system. In fact, it is not only possible, but incredibly straightforward, to measure the optimality (in this more general sense) of any data assimilation algorithm as applied to any intended model or natural system. We measure the information content of remote sensing data conditional on the fact that we are already running a model and then measure the actual information extracted by data assimilation. The ratio of the two is an efficiency metric, and optimality is defined as occurring when the data assimilation algorithm is perfectly efficient at extracting information from the retrievals. We measure the information content of the remote sensing data in a way that, unlike triple collocation, does not rely on any a priori presumed relationship (e.g., linear) between the retrieval and the ground truth, however, like triple-collocation, is insensitive to the spatial mismatch between point-based measurements and grid-scale retrievals. This theory and method is therefore suitable for use with both dense and sparse validation networks. Additionally, the method we propose is *constructive* in the sense that it provides guidance on how to improve data assimilation systems. All data assimilation strategies can be reduced to approximations of Bayes' law, and we measure the fractions of total information loss that are due to individual assumptions or approximations in the
Yang, S.; Gohar, Y.
1985-01-01
Design analyses and tradeoff studies for the bulk shield of the Tokamak Fusion Core Experiment (TFCX) were performed. Several shielding options were considered to lower the capital cost of the shielding system. Optimization analyses were carried out to reduce the nuclear responses in the TF coils and the dose equivalent in the reactor hall one day after shutdown. Two TFCX designs with different toroidal field (TF) coil configurations were considered during this work. The materials for the shield were selected based upon tradeoff studies and the results from the previous design studies. The main shielding materials are water, concrete, and steel balls (Fe1422 or Nitronic 33). Small amounts of boron carbide and lead are employed to reduce activation, nuclear heating in the TF coils, and dose equivalent after shutdown.
Optimized nanoporous materials.
Braun, Paul V.; Langham, Mary Elizabeth; Jacobs, Benjamin W.; Ong, Markus D.; Narayan, Roger J.; Pierson, Bonnie E.; Gittard, Shaun D.; Robinson, David B.; Ham, Sung-Kyoung; Chae, Weon-Sik; Gough, Dara V.; Wu, Chung-An Max; Ha, Cindy M.; Tran, Kim L.
2009-09-01
Nanoporous materials have maximum practical surface areas for electrical charge storage; every point in an electrode is within a few atoms of an interface at which charge can be stored. Metal-electrolyte interfaces make best use of surface area in porous materials. However, ion transport through long, narrow pores is slow. We seek to understand and optimize the tradeoff between capacity and transport. Modeling and measurements of nanoporous gold electrodes has allowed us to determine design principles, including the fact that these materials can deplete salt from the electrolyte, increasing resistance. We have developed fabrication techniques to demonstrate architectures inspired by these principles that may overcome identified obstacles. A key concept is that electrodes should be as close together as possible; this is likely to involve an interpenetrating pore structure. However, this may prove extremely challenging to fabricate at the finest scales; a hierarchically porous structure can be a worthy compromise.
Optimal inverse functions created via population-based optimization.
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.
Public optimism towards nanomedicine
Bottini, Massimo; Rosato, Nicola; Gloria, Fulvia; Adanti, Sara; Corradino, Nunziella; Bergamaschi, Antonio; Magrini, Andrea
2011-01-01
Background Previous benefit–risk perception studies and social experiences have clearly demonstrated that any emerging technology platform that ignores benefit–risk perception by citizens might jeopardize its public acceptability and further development. The aim of this survey was to investigate the Italian judgment on nanotechnology and which demographic and heuristic variables were most influential in shaping public perceptions of the benefits and risks of nanotechnology. Methods In this regard, we investigated the role of four demographic (age, gender, education, and religion) and one heuristic (knowledge) predisposing factors. Results The present study shows that gender, education, and knowledge (but not age and religion) influenced the Italian perception of how nanotechnology will (positively or negatively) affect some areas of everyday life in the next twenty years. Furthermore, the picture that emerged from our study is that Italian citizens, despite minimal familiarity with nanotechnology, showed optimism towards nanotechnology applications, especially those related to health and medicine (nanomedicine). The high regard for nanomedicine was tied to the perception of risks associated with environmental and societal implications (division among social classes and increased public expenses) rather than health issues. However, more highly educated people showed greater concern for health issues but this did not decrease their strong belief about the benefits that nanotechnology would bring to medical fields. Conclusion The results reported here suggest that public optimism towards nanomedicine appears to justify increased scientific effort and funding for medical applications of nanotechnology. It also obligates toxicologists, politicians, journalists, entrepreneurs, and policymakers to establish a more responsible dialog with citizens regarding the nature and implications of this emerging technology platform. PMID:22267931
OPTIMAL NETWORK TOPOLOGY DESIGN
NASA Technical Reports Server (NTRS)
Yuen, J. H.
1994-01-01
This program was developed as part of a research study on the topology design and performance analysis for the Space Station Information System (SSIS) network. It uses an efficient algorithm to generate candidate network designs (consisting of subsets of the set of all network components) in increasing order of their total costs, and checks each design to see if it forms an acceptable network. This technique gives the true cost-optimal network, and is particularly useful when the network has many constraints and not too many components. It is intended that this new design technique consider all important performance measures explicitly and take into account the constraints due to various technical feasibilities. In the current program, technical constraints are taken care of by the user properly forming the starting set of candidate components (e.g. nonfeasible links are not included). As subsets are generated, they are tested to see if they form an acceptable network by checking that all requirements are satisfied. Thus the first acceptable subset encountered gives the cost-optimal topology satisfying all given constraints. The user must sort the set of "feasible" link elements in increasing order of their costs. The program prompts the user for the following information for each link: 1) cost, 2) connectivity (number of stations connected by the link), and 3) the stations connected by that link. Unless instructed to stop, the program generates all possible acceptable networks in increasing order of their total costs. The program is written only to generate topologies that are simply connected. Tests on reliability, delay, and other performance measures are discussed in the documentation, but have not been incorporated into the program. This program is written in PASCAL for interactive execution and has been implemented on an IBM PC series computer operating under PC DOS. The disk contains source code only. This program was developed in 1985.
Topology optimization under stochastic stiffness
NASA Astrophysics Data System (ADS)
Asadpoure, Alireza
Topology optimization is a systematic computational tool for optimizing the layout of materials within a domain for engineering design problems. It allows variation of structural boundaries and connectivities. This freedom in the design space often enables discovery of new, high performance designs. However, solutions obtained by performing the optimization in a deterministic setting may be impractical or suboptimal when considering real-world engineering conditions with inherent variabilities including (for example) variabilities in fabrication processes and operating conditions. The aim of this work is to provide a computational methodology for topology optimization in the presence of uncertainties associated with structural stiffness, such as uncertain material properties and/or structural geometry. Existing methods for topology optimization under deterministic conditions are first reviewed. Modifications are then proposed to improve the numerical performance of the so-called Heaviside Projection Method (HPM) in continuum domains. Next, two approaches, perturbation and Polynomial Chaos Expansion (PCE), are proposed to account for uncertainties in the optimization procedure. These approaches are intrusive, allowing tight and efficient coupling of the uncertainty quantification with the optimization sensitivity analysis. The work herein develops a robust topology optimization framework aimed at reducing the sensitivity of optimized solutions to uncertainties. The perturbation-based approach combines deterministic topology optimization with a perturbation method for the quantification of uncertainties. The use of perturbation transforms the problem of topology optimization under uncertainty to an augmented deterministic topology optimization problem. The PCE approach combines the spectral stochastic approach for the representation and propagation of uncertainties with an existing deterministic topology optimization technique. The resulting compact representations
Metacognitive control and optimal learning.
Son, Lisa K; Sethi, Rajiv
2006-07-08
The notion of optimality is often invoked informally in the literature on metacognitive control. We provide a precise formulation of the optimization problem and show that optimal time allocation strategies depend critically on certain characteristics of the learning environment, such as the extent of time pressure, and the nature of the uptake function. When the learning curve is concave, optimality requires that items at lower levels of initial competence be allocated greater time. On the other hand, with logistic learning curves, optimal allocations vary with time availability in complex and surprising ways. Hence there are conditions under which optimal strategies will be relatively easy to uncover, and others in which suboptimal time allocation might be expected. The model can therefore be used to address the question of whether and when learners should be able to exercise good metacognitive control in practice.
Large-scale structural optimization
NASA Technical Reports Server (NTRS)
Sobieszczanski-Sobieski, J.
1983-01-01
Problems encountered by aerospace designers in attempting to optimize whole aircraft are discussed, along with possible solutions. Large scale optimization, as opposed to component-by-component optimization, is hindered by computational costs, software inflexibility, concentration on a single, rather than trade-off, design methodology and the incompatibility of large-scale optimization with single program, single computer methods. The software problem can be approached by placing the full analysis outside of the optimization loop. Full analysis is then performed only periodically. Problem-dependent software can be removed from the generic code using a systems programming technique, and then embody the definitions of design variables, objective function and design constraints. Trade-off algorithms can be used at the design points to obtain quantitative answers. Finally, decomposing the large-scale problem into independent subproblems allows systematic optimization of the problems by an organization of people and machines.
Optimal management strategies in variable environments: Stochastic optimal control methods
Williams, B.K.
1985-01-01
Dynamic optimization was used to investigate the optimal defoliation of salt desert shrubs in north-western Utah. Management was formulated in the context of optimal stochastic control theory, with objective functions composed of discounted or time-averaged biomass yields. Climatic variability and community patterns of salt desert shrublands make the application of stochastic optimal control both feasible and necessary. A primary production model was used to simulate shrub responses and harvest yields under a variety of climatic regimes and defoliation patterns. The simulation results then were used in an optimization model to determine optimal defoliation strategies. The latter model encodes an algorithm for finite state, finite action, infinite discrete time horizon Markov decision processes. Three questions were addressed: (i) What effect do changes in weather patterns have on optimal management strategies? (ii) What effect does the discounting of future returns have? (iii) How do the optimal strategies perform relative to certain fixed defoliation strategies? An analysis was performed for the three shrub species, winterfat (Ceratoides lanata), shadscale (Atriplex confertifolia) and big sagebrush (Artemisia tridentata). In general, the results indicate substantial differences among species in optimal control strategies, which are associated with differences in physiological and morphological characteristics. Optimal policies for big sagebrush varied less with variation in climate, reserve levels and discount rates than did either shadscale or winterfat. This was attributed primarily to the overwintering of photosynthetically active tissue and to metabolic activity early in the growing season. Optimal defoliation of shadscale and winterfat generally was more responsive to differences in plant vigor and climate, reflecting the sensitivity of these species to utilization and replenishment of carbohydrate reserves. Similarities could be seen in the influence of both
Recent developments in multilevel optimization
NASA Technical Reports Server (NTRS)
Vanderplaats, Garret N.; Kim, D.-S.
1989-01-01
Recent developments in multilevel optimization are briefly reviewed. The general nature of the multilevel design task, the use of approximations to develop and solve the analysis design task, the structure of the formal multidiscipline optimization problem, a simple cantilevered beam which demonstrates the concepts of multilevel design and the basic mathematical details of the optimization task and the system level are among the topics discussed.
Optimal Control of Electrodynamic Tethers
2008-06-01
method.46 Even though the derivation that produced Eq. (11) required integration over a hypothetical integer number of revolutions, the optimizer ... approach to multi-revolution, long time scale optimal control of an electrodynamic tether is investigated for a tethered satellite system in Low Earth...time scale approach is used to capture the effects of the Earth’s rotating tilted magnetic field. Optimal control solutions are achieved using a
GAPS IN SUPPORT VECTOR OPTIMIZATION
STEINWART, INGO; HUSH, DON; SCOVEL, CLINT; LIST, NICOLAS
2007-01-29
We show that the stopping criteria used in many support vector machine (SVM) algorithms working on the dual can be interpreted as primal optimality bounds which in turn are known to be important for the statistical analysis of SVMs. To this end we revisit the duality theory underlying the derivation of the dual and show that in many interesting cases primal optimality bounds are the same as known dual optimality bounds.
Optimality Functions in Stochastic Programming
2009-12-02
nonconvex. Non - convex stochastic optimization problems arise in such diverse applications as estimation of mixed logit models [2], engineering design...first- order necessary optimality conditions ; see for example Propositions 3.3.1 and 3.3.5 in [7] or Theorem 2.2.4 in [25]. If the evaluation of f j...procedures for validation analysis of a candidate point x ∈ IRn. Since P may be nonconvex, we focus on first-order necessary optimality conditions as
Stochastic Optimization of Complex Systems
Birge, John R.
2014-03-20
This project focused on methodologies for the solution of stochastic optimization problems based on relaxation and penalty methods, Monte Carlo simulation, parallel processing, and inverse optimization. The main results of the project were the development of a convergent method for the solution of models that include expectation constraints as in equilibrium models, improvement of Monte Carlo convergence through the use of a new method of sample batch optimization, the development of new parallel processing methods for stochastic unit commitment models, and the development of improved methods in combination with parallel processing for incorporating automatic differentiation methods into optimization.
Structural Optimization in automotive design
NASA Technical Reports Server (NTRS)
Bennett, J. A.; Botkin, M. E.
1984-01-01
Although mathematical structural optimization has been an active research area for twenty years, there has been relatively little penetration into the design process. Experience indicates that often this is due to the traditional layout-analysis design process. In many cases, optimization efforts have been outgrowths of analysis groups which are themselves appendages to the traditional design process. As a result, optimization is often introduced into the design process too late to have a significant effect because many potential design variables have already been fixed. A series of examples are given to indicate how structural optimization has been effectively integrated into the design process.
Structural optimization by multilevel decomposition
NASA Technical Reports Server (NTRS)
Sobieszczanski-Sobieski, J.; James, B.; Dovi, A.
1983-01-01
A method is described for decomposing an optimization problem into a set of subproblems and a coordination problem which preserves coupling between the subproblems. The method is introduced as a special case of multilevel, multidisciplinary system optimization and its algorithm is fully described for two level optimization for structures assembled of finite elements of arbitrary type. Numerical results are given for an example of a framework to show that the decomposition method converges and yields results comparable to those obtained without decomposition. It is pointed out that optimization by decomposition should reduce the design time by allowing groups of engineers, using different computers to work concurrently on the same large problem.
Optimal Reconfiguration of Tetrahedral Formations
NASA Technical Reports Server (NTRS)
Huntington, Geoffrey; Rao, Anil V.; Hughes, Steven P.
2004-01-01
The problem of minimum-fuel formation reconfiguration for the Magnetospheric Multi-Scale (MMS) mission is studied. This reconfiguration trajectory optimization problem can be posed as a nonlinear optimal control problem. In this research, this optimal control problem is solved using a spectral collocation method called the Gauss pseudospectral method. The objective of this research is to provide highly accurate minimum-fuel solutions to the MMS formation reconfiguration problem and to gain insight into the underlying structure of fuel-optimal trajectories.
NASA Astrophysics Data System (ADS)
Grigoriev, D. Yu.; Jankowski, E.; Tkachov, F. V.
2003-09-01
We describe a FORTRAN 77 implementation of the optimal jet definition for identification of jets in hadronic final states of particle collisions. We discuss details of the implementation, explain interface subroutines and provide a usage example. The source code is available from http://www.inr.ac.ru/~ftkachov/projects/jets/. Program summaryTitle of program: Optimal Jet Finder (OJF_014) Catalogue identifier: ADSB Program Summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSB Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computer: Any computer with the FORTRAN 77 compiler Tested with: g77/Linux on Intel, Alpha and Sparc; Sun f77/Solaris (thwgs.cern.ch); xlf/AIX (rsplus.cern.ch); MS Fortran PowerStation 4.0/Win98 Programming language used: FORTRAN 77 Memory required: ˜1 MB (or more, depending on the settings) Number of bytes in distributed program, including examples and test data: 251 463 Distribution format: tar gzip file Keywords: Hadronic jets, jet finding algorithms Nature of physical problem: Analysis of hadronic final states in high energy particle collision experiments often involves identification of hadronic jets. A large number of hadrons detected in the calorimeter is reduced to a few jets by means of a jet finding algorithm. The jets are used in further analysis which would be difficult or impossible when applied directly to the hadrons. Grigoriev et al. [ hep-ph/0301185] provide a brief introduction to the subject of jet finding algorithms and a general review of the physics of jets can be found in [Rep. Prog. Phys. 36 (1993) 1067]. Method of solution: The software we provide is an implementation of the so-called optimal jet definition ( OJD). The theory of OJD was developed by Tkachov [Phys. Rev. Lett. 73 (1994) 2405; 74 (1995) 2618; Int. J. Mod. Phys. A 12 (1997) 5411; 17 (2002) 2783]. The desired jet configuration is obtained as the one that minimizes Ω R, a certain function of the input particles and jet
Optimal control, optimization and asymptotic analysis of Purcell's microswimmer model
NASA Astrophysics Data System (ADS)
Wiezel, Oren; Or, Yizhar
2016-11-01
Purcell's swimmer (1977) is a classic model of a three-link microswimmer that moves by performing periodic shape changes. Becker et al. (2003) showed that the swimmer's direction of net motion is reversed upon increasing the stroke amplitude of joint angles. Tam and Hosoi (2007) used numerical optimization in order to find optimal gaits for maximizing either net displacement or Lighthill's energetic efficiency. In our work, we analytically derive leading-order expressions as well as next-order corrections for both net displacement and energetic efficiency of Purcell's microswimmer. Using these expressions enables us to explicitly show the reversal in direction of motion, as well as obtaining an estimate for the optimal stroke amplitude. We also find the optimal swimmer's geometry for maximizing either displacement or energetic efficiency. Additionally, the gait optimization problem is revisited and analytically formulated as an optimal control system with only two state variables, which can be solved using Pontryagin's maximum principle. It can be shown that the optimal solution must follow a "singular arc". Numerical solution of the boundary value problem is obtained, which exactly reproduces Tam and Hosoi's optimal gait.
NASA Astrophysics Data System (ADS)
Inanloo, B.
2011-12-01
The Caspian Sea is considered to be the largest inland body of water in the world, which located between the Caucasus Mountains and Central Asia. The Caspian Sea has been a source of the most contentious international conflicts between five littoral states now borders the sea: Azerbaijan, Iran, Kazakhstan, Russia, and Turkmenistan. The conflict over the legal status of this international body of water as an aftermath of the breakup of the Soviet Union in 1991. Since then the parties have been negotiating without coming up with any agreement neither on the ownerships of waters, nor the oil and natural gas beneath them. The number of involved stakeholders, the unusual characteristics of the Caspian Sea in considering it as a lake or a sea, and a large number of external parties are interested in the valuable resources of the Sea has made this conflict complex and unique. This paper intends to apply methods to find the best allocation schemes considering acceptability and stability of selected solution to share the Caspian Sea and its resources fairly and efficiently. Although, there are several allocation methods in solving such allocation problems, however, most of those seek a socially optimal solution that can satisfy majority of criteria or decision makers, while, in practice, especially in multi-nation problems, such solution may not be necessarily a stable solution and to be acceptable to all parties. Hence, there is need to apply a method that considers stability and acceptability of solutions to find a solution with high chance to be agreed upon that. Application of some distance-based methods in studying the Caspian Sea conflict provides some policy insights useful for finding solutions that can resolve the dispute. In this study, we use methods such as Goal Programming, Compromise Programming, and considering stability of solution the logic of Power Index is used to find a division rule that is stable negotiators. The results of this study shows that the
RNA based evolutionary optimization
NASA Astrophysics Data System (ADS)
Schuster, Peter
1993-12-01
. Evolutionary optimization of two-letter sequences in thus more difficult than optimization in the world of natural RNA sequences with four bases. This fact might explain the usage of four bases in the genetic language of nature. Finally we study the mapping from RNA sequences into secondary structures and explore the topology of RNA shape space. We find that ‘neutral paths’ connecting neighbouring sequences with identical structures go very frequently through entire sequence space. Sequences folding into common structures are found everywhere in sequence space. Hence, evolution can migrate to almost every part of sequence space without ‘hill climbing’ and only small fractions of the entire number of sequences have to be searched in order to find suitable structures.
Industrial cogeneration optimization program
Not Available
1980-01-01
The purpose of this program was to identify up to 10 good near-term opportunities for cogeneration in 5 major energy-consuming industries which produce food, textiles, paper, chemicals, and refined petroleum; select, characterize, and optimize cogeneration systems for these identified opportunities to achieve maximum energy savings for minimum investment using currently available components of cogenerating systems; and to identify technical, institutional, and regulatory obstacles hindering the use of industrial cogeneration systems. The analysis methods used and results obtained are described. Plants with fuel demands from 100,000 Btu/h to 3 x 10/sup 6/ Btu/h were considered. It was concluded that the major impediments to industrial cogeneration are financial, e.g., high capital investment and high charges by electric utilities during short-term cogeneration facility outages. In the plants considered an average energy savings from cogeneration of 15 to 18% compared to separate generation of process steam and electric power was calculated. On a national basis for the 5 industries considered, this extrapolates to saving 1.3 to 1.6 quads per yr or between 630,000 to 750,000 bbl/d of oil. Properly applied, federal activity can do much to realize a substantial fraction of this potential by lowering the barriers to cogeneration and by stimulating wider implementation of this technology. (LCL)
Genetically optimizing weather predictions
NASA Astrophysics Data System (ADS)
Potter, S. B.; Staats, Kai; Romero-Colmenero, Encarni
2016-07-01
humidity, air pressure, wind speed and wind direction) into a database. Built upon this database, we have developed a remarkably simple approach to derive a functional weather predictor. The aim is provide up to the minute local weather predictions in order to e.g. prepare dome environment conditions ready for night time operations or plan, prioritize and update weather dependent observing queues. In order to predict the weather for the next 24 hours, we take the current live weather readings and search the entire archive for similar conditions. Predictions are made against an averaged, subsequent 24 hours of the closest matches for the current readings. We use an Evolutionary Algorithm to optimize our formula through weighted parameters. The accuracy of the predictor is routinely tested and tuned against the full, updated archive to account for seasonal trends and total, climate shifts. The live (updated every 5 minutes) SALT weather predictor can be viewed here: http://www.saao.ac.za/ sbp/suthweather_predict.html
Cyclone performance and optimization
Leith, D.
1989-03-15
The objectives of this project are: to characterize the gas flow pattern within cyclones, to revise the theory for cyclone performance on the basis of these findings, and to design and test cyclones whose dimensions have been optimized using revised performance theory. This work is important because its successful completion will aid in the technology for combustion of coal in pressurized, fluidized beds. This quarter, we have been hampered somewhat by flow delivery of the bubble generation system and arc lighting system placed on order last fall. This equipment is necessary to map the flow field within cyclones using the techniques described in last quarter's report. Using the bubble generator, we completed this quarter a study of the natural length'' of cyclones of 18 different configurations, each configuration operated at five different gas flows. Results suggest that the equation by Alexander for natural length is incorrect; natural length as measured with the bubble generation system is always below the bottom of the cyclones regardless of the cyclone configuration or gas flow, within the limits of the experimental cyclones tested. This finding is important because natural length is a term in equations used to predict cyclone efficiency. 1 tab.
Optimal Phase Oscillatory Network
NASA Astrophysics Data System (ADS)
Follmann, Rosangela
2013-03-01
Important topics as preventive detection of epidemics, collective self-organization, information flow and systemic robustness in clusters are typical examples of processes that can be studied in the context of the theory of complex networks. It is an emerging theory in a field, which has recently attracted much interest, involving the synchronization of dynamical systems associated to nodes, or vertices, of the network. Studies have shown that synchronization in oscillatory networks depends not only on the individual dynamics of each element, but also on the combination of the topology of the connections as well as on the properties of the interactions of these elements. Moreover, the response of the network to small damages, caused at strategic points, can enhance the global performance of the whole network. In this presentation we explore an optimal phase oscillatory network altered by an additional term in the coupling function. The application to associative-memory network shows improvement on the correct information retrieval as well as increase of the storage capacity. The inclusion of some small deviations on the nodes, when solutions are attracted to a false state, results in additional enhancement of the performance of the associative-memory network. Supported by FAPESP - Sao Paulo Research Foundation, grant number 2012/12555-4
Optimized System Identification
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Longman, Richard W.
1999-01-01
In system identification, one usually cares most about finding a model whose outputs are as close as possible to the true system outputs when the same input is applied to both. However, most system identification algorithms do not minimize this output error. Often they minimize model equation error instead, as in typical least-squares fits using a finite-difference model, and it is seen here that this distinction is significant. Here, we develop a set of system identification algorithms that minimize output error for multi-input/multi-output and multi-input/single-output systems. This is done with sequential quadratic programming iterations on the nonlinear least-squares problems, with an eigendecomposition to handle indefinite second partials. This optimization minimizes a nonlinear function of many variables, and hence can converge to local minima. To handle this problem, we start the iterations from the OKID (Observer/Kalman Identification) algorithm result. Not only has OKID proved very effective in practice, it minimizes an output error of an observer which has the property that as the data set gets large, it converges to minimizing the criterion of interest here. Hence, it is a particularly good starting point for the nonlinear iterations here. Examples show that the methods developed here eliminate the bias that is often observed using any system identification methods of either over-estimating or under-estimating the damping of vibration modes in lightly damped structures.
Boiler modeling optimizes sootblowing
Piboontum, S.J.; Swift, S.M.; Conrad, R.S.
2005-10-01
Controlling the cleanliness and limiting the fouling and slagging of heat transfer surfaces are absolutely necessary to optimize boiler performance. The traditional way to clean heat-transfer surfaces is by sootblowing using air, steam, or water at regular intervals. But with the advent of fuel-switching strategies, such as switching to PRB coal to reduce a plant's emissions, the control of heating surface cleanliness has become more problematic for many owners of steam generators. Boiler modeling can help solve that problem. The article describes Babcock & Wilcox's Powerclean modeling system which consists of heating surface models that produce real-time cleanliness indexes. The Heat Transfer Manager (HTM) program is the core of the system, which can be used on any make or model of boiler. A case study is described to show how the system was successfully used at the 1,350 MW Unit 2 of the American Electric Power's Rockport Power Plant in Indiana. The unit fires a blend of eastern bituminous and Powder River Basin coal. 5 figs.
Powers, Tom
2013-09-01
This work describes preliminary results of a new software tool that allows one to vary parameters and understand the effects on the optimized costs of construction plus 10 year operations of an SRF linac, the associated cryogenic facility, and controls, where operations includes the cost of the electrical utilities but not the labor or other costs. It derives from collaborative work done with staff from Accelerator Science and Technology Centre, Daresbury, UK several years ago while they were in the process of developing a conceptual design for the New Light Source project.[1] The initial goal was to convert a spread sheet format to a graphical interface to allow the ability to sweep different parameter sets. The tools also allow one to compare the cost of the different facets of the machine design and operations so as to better understand the tradeoffs. The work was first published in an ICFA Beam Dynamics News Letter.[2] More recent additions to the software include the ability to save and restore input parameters as well as to adjust the Qo versus E parameters in order to explore the potential costs savings associated with doing so. Additionally, program changes now allow one to model the costs associated with a linac that makes use of energy recovery mode of operation.
Optimizing haemodialysate composition
Locatelli, Francesco; La Milia, Vincenzo; Violo, Leano; Del Vecchio, Lucia; Di Filippo, Salvatore
2015-01-01
Survival and quality of life of dialysis patients are strictly dependent on the quality of the haemodialysis (HD) treatment. In this respect, dialysate composition, including water purity, plays a crucial role. A major aim of HD is to normalize predialysis plasma electrolyte and mineral concentrations, while minimizing wide swings in the patient's intradialytic plasma concentrations. Adequate sodium (Na) and water removal is critical for preventing intra- and interdialytic hypotension and pulmonary edema. Avoiding both hyper- and hypokalaemia prevents life-threatening cardiac arrhythmias. Optimal calcium (Ca) and magnesium (Mg) dialysate concentrations may protect the cardiovascular system and the bones, preventing extraskeletal calcifications, severe secondary hyperparathyroidism and adynamic bone disease. Adequate bicarbonate concentration [HCO3−] maintains a stable pH in the body fluids for appropriate protein and membrane functioning and also protects the bones. An adequate dialysate glucose concentration prevents severe hyperglycaemia and life-threating hypoglycaemia, which can lead to severe cardiovascular complications and a worsening of diabetic comorbidities. PMID:26413285
Optimally Squeezed Spin States
NASA Astrophysics Data System (ADS)
Rojo, Alberto
2004-03-01
We consider optimally spin-squeezed states that maximize the sensitivity of the Ramsey spectroscopy, and for which the signal to noise ratio scales as the number of particles N. Using the variational principle we prove that these states are eigensolutions of the Hamiltonian H(λ)=λ S_z^2-S_x, and that, for large N, the states become equivalent to the quadrature squeezed states of the harmonic oscillator. We present numerical results that illustrate the validity of the equivalence. We also present results of spin squeezing via atom-field interactions within the context of the Tavis-Cummings model. An ensemble of N two-level atoms interacts with a quantized cavity field. For all the atoms initially in their ground states, it is shown that spin squeezing of both the atoms and the field can be achieved provided the initial state of the cavity field has coherence between number states differing by 2. Most of the discussion is restricted to the case of a cavity field initially in a coherent state, but initial squeezed states for the field are also discussed. An analytic solution is found that is valid in the limit that the number of atoms is much greater than unity. References: A. G. Rojo, Phys. Rev A, 68, 013807 (2003); Claudiu Genes, P. R. Berman, and A. G. Rojo Phys. Rev. A 68, 043809 (2003).
Sweeping Jet Optimization Studies
NASA Technical Reports Server (NTRS)
Melton, LaTunia Pack; Koklu, Mehti; Andino, Marlyn; Lin, John C.; Edelman, Louis
2016-01-01
Progress on experimental efforts to optimize sweeping jet actuators for active flow control (AFC) applications with large adverse pressure gradients is reported. Three sweeping jet actuator configurations, with the same orifice size but di?erent internal geometries, were installed on the flap shoulder of an unswept, NACA 0015 semi-span wing to investigate how the output produced by a sweeping jet interacts with the separated flow and the mechanisms by which the flow separation is controlled. For this experiment, the flow separation was generated by deflecting the wing's 30% chord trailing edge flap to produce an adverse pressure gradient. Steady and unsteady pressure data, Particle Image Velocimetry data, and force and moment data were acquired to assess the performance of the three actuator configurations. The actuator with the largest jet deflection angle, at the pressure ratios investigated, was the most efficient at controlling flow separation on the flap of the model. Oil flow visualization studies revealed that the flow field controlled by the sweeping jets was more three-dimensional than expected. The results presented also show that the actuator spacing was appropriate for the pressure ratios examined.
Query Evaluation: Strategies and Optimizations.
ERIC Educational Resources Information Center
Turtle, Howard; Flood, James
1995-01-01
Discusses two query evaluation strategies used in large text retrieval systems: (1) term-at-a-time; and (2) document-at-a-time. Describes optimization techniques that can reduce query evaluation costs. Presents simulation results that compare the performance of these optimization techniques when applied to natural language query evaluation. (JMV)
Optimal Inputs for System Identification.
1995-09-01
The derivation of the power spectral density of the optimal input for system identification is addressed in this research. Optimality is defined in...identification potential of general System Identification algorithms, a new and efficient System Identification algorithm that employs Iterated Weighted Least
A Problem on Optimal Transportation
ERIC Educational Resources Information Center
Cechlarova, Katarina
2005-01-01
Mathematical optimization problems are not typical in the classical curriculum of mathematics. In this paper we show how several generalizations of an easy problem on optimal transportation were solved by gifted secondary school pupils in a correspondence mathematical seminar, how they can be used in university courses of linear programming and…
Optimizing Medical Kits for Spaceflight
NASA Technical Reports Server (NTRS)
Keenan, A. B,; Foy, Millennia; Myers, G.
2014-01-01
The Integrated Medical Model (IMM) is a probabilistic model that estimates medical event occurrences and mission outcomes for different mission profiles. IMM simulation outcomes describing the impact of medical events on the mission may be used to optimize the allocation of resources in medical kits. Efficient allocation of medical resources, subject to certain mass and volume constraints, is crucial to ensuring the best outcomes of in-flight medical events. We implement a new approach to this medical kit optimization problem. METHODS We frame medical kit optimization as a modified knapsack problem and implement an algorithm utilizing a dynamic programming technique. Using this algorithm, optimized medical kits were generated for 3 different mission scenarios with the goal of minimizing the probability of evacuation and maximizing the Crew Health Index (CHI) for each mission subject to mass and volume constraints. Simulation outcomes using these kits were also compared to outcomes using kits optimized..RESULTS The optimized medical kits generated by the algorithm described here resulted in predicted mission outcomes more closely approached the unlimited-resource scenario for Crew Health Index (CHI) than the implementation in under all optimization priorities. Furthermore, the approach described here improves upon in reducing evacuation when the optimization priority is minimizing the probability of evacuation. CONCLUSIONS This algorithm provides an efficient, effective means to objectively allocate medical resources for spaceflight missions using the Integrated Medical Model.
Trajectory optimization using regularized variables
NASA Technical Reports Server (NTRS)
Lewallen, J. M.; Szebehely, V.; Tapley, B. D.
1969-01-01
Regularized equations for a particular optimal trajectory are compared with unregularized equations with respect to computational characteristics, using perturbation type numerical optimization. In the case of the three dimensional, low thrust, Earth-Jupiter rendezvous, the regularized equations yield a significant reduction in computer time.
Supply-Chain Optimization Template
NASA Technical Reports Server (NTRS)
Quiett, William F.; Sealing, Scott L.
2009-01-01
The Supply-Chain Optimization Template (SCOT) is an instructional guide for identifying, evaluating, and optimizing (including re-engineering) aerospace- oriented supply chains. The SCOT was derived from the Supply Chain Council s Supply-Chain Operations Reference (SCC SCOR) Model, which is more generic and more oriented toward achieving a competitive advantage in business.
assigned to the operational support airlift mission, located at Andrews Air Force Base, Maryland and Scott Air Force Base, Illinois. The missions flown... Scott and Andrews AFB is the optimal assignment. If nine total assets were optimized, five would be assigned to Scott AFB and four to Andrews AFB
Optimized dynamic rotation with wedges.
Rosen, I I; Morrill, S M; Lane, R G
1992-01-01
Dynamic rotation is a computer-controlled therapy technique utilizing an automated multileaf collimator in which the radiation beam shape changes dynamically as the treatment machine rotates about the patient so that at each instant the beam shape matches the projected shape of the target volume. In simple dynamic rotation, the dose rate remains constant during rotation. For optimized dynamic rotation, the dose rate is varied as a function of gantry angle. Optimum dose rate at each gantry angle is computed by linear programming. Wedges can be included in the optimized dynamic rotation therapy by using additional rotations. Simple and optimized dynamic rotation treatment plans, with and without wedges, for a pancreatic tumor have been compared using optimization cost function values, normal tissue complication probabilities, and positive difference statistic values. For planning purposes, a continuous rotation is approximated by static beams at a number of gantry angles equally spaced about the patient. In theory, the quality of optimized treatment planning solutions should improve as the number of static beams increases. The addition of wedges should further improve dose distributions. For the case studied, no significant improvements were seen for more than 36 beam angles. Open and wedged optimized dynamic rotations were better than simple dynamic rotation, but wedged optimized dynamic rotation showed no definitive improvement over open beam optimized dynamic rotation.
Optimized layout generator for microgyroscope
NASA Astrophysics Data System (ADS)
Tay, Francis E.; Li, Shifeng; Logeeswaran, V. J.; Ng, David C.
2000-10-01
This paper presents an optimized out-of-plane microgyroscope layout generator using AutoCAD R14 and MS ExcelTM as a first attempt to automating the design of resonant micro- inertial sensors. The out-of-plane microgyroscope with two degrees of freedom lumped parameter model was chosen as the synthesis topology. Analytical model for the open loop operating has been derived for the gyroscope performance characteristics. Functional performance parameters such as sensitivity are ensured to be satisfied while simultaneously optimizing a design objective such as minimum area. A single algorithm will optimize the microgyroscope dimensions, while simultaneously maximizing or minimizing the objective functions: maximum sensitivity and minimum area. The multi- criteria objective function and optimization methodology was implemented using the Generalized Reduced Gradient algorithm. For data conversion a DXF to GDS converter was used. The optimized theoretical design performance parameters show good agreement with finite element analysis.
Risk modelling in portfolio optimization
NASA Astrophysics Data System (ADS)
Lam, W. H.; Jaaman, Saiful Hafizah Hj.; Isa, Zaidi
2013-09-01
Risk management is very important in portfolio optimization. The mean-variance model has been used in portfolio optimization to minimize the investment risk. The objective of the mean-variance model is to minimize the portfolio risk and achieve the target rate of return. Variance is used as risk measure in the mean-variance model. The purpose of this study is to compare the portfolio composition as well as performance between the optimal portfolio of mean-variance model and equally weighted portfolio. Equally weighted portfolio means the proportions that are invested in each asset are equal. The results show that the portfolio composition of the mean-variance optimal portfolio and equally weighted portfolio are different. Besides that, the mean-variance optimal portfolio gives better performance because it gives higher performance ratio than the equally weighted portfolio.
Optimal dynamic detection of explosives
Moore, David Steven; Mcgrane, Shawn D; Greenfield, Margo T; Scharff, R J; Rabitz, Herschel A; Roslund, J
2009-01-01
The detection of explosives is a notoriously difficult problem, especially at stand-off distances, due to their (generally) low vapor pressure, environmental and matrix interferences, and packaging. We are exploring optimal dynamic detection to exploit the best capabilities of recent advances in laser technology and recent discoveries in optimal shaping of laser pulses for control of molecular processes to significantly enhance the standoff detection of explosives. The core of the ODD-Ex technique is the introduction of optimally shaped laser pulses to simultaneously enhance sensitivity of explosives signatures while reducing the influence of noise and the signals from background interferents in the field (increase selectivity). These goals are being addressed by operating in an optimal nonlinear fashion, typically with a single shaped laser pulse inherently containing within it coherently locked control and probe sub-pulses. With sufficient bandwidth, the technique is capable of intrinsically providing orthogonal broad spectral information for data fusion, all from a single optimal pulse.
Optimal Distinctiveness Signals Membership Trust.
Leonardelli, Geoffrey J; Loyd, Denise Lewin
2016-07-01
According to optimal distinctiveness theory, sufficiently small minority groups are associated with greater membership trust, even among members otherwise unknown, because the groups are seen as optimally distinctive. This article elaborates on the prediction's motivational and cognitive processes and tests whether sufficiently small minorities (defined by relative size; for example, 20%) are associated with greater membership trust relative to mere minorities (45%), and whether such trust is a function of optimal distinctiveness. Two experiments, examining observers' perceptions of minority and majority groups and using minimal groups and (in Experiment 2) a trust game, revealed greater membership trust in minorities than majorities. In Experiment 2, participants also preferred joining minorities over more powerful majorities. Both effects occurred only when minorities were 20% rather than 45%. In both studies, perceptions of optimal distinctiveness mediated effects. Discussion focuses on the value of relative size and optimal distinctiveness, and when membership trust manifests.
Hansborough, L.; Hamm, R.; Stovall, J.; Swenson, D.
1980-01-01
PIGMI (Pion Generator for Medical Irradiations) is a compact linear proton accelerator design, optimized for pion production and cancer treatment use in a hospital environment. Technology developed during a four-year PIGMI Prototype experimental program allows the design of smaller, less expensive, and more reliable proton linacs. A new type of low-energy accelerating structure, the radio-frequency quadrupole (RFQ) has been tested; it produces an exceptionally good-quality beam and allows the use of a simple 30-kV injector. Average axial electric-field gradients of over 9 MV/m have been demonstrated in a drift-tube linac (DTL) structure. Experimental work is underway to test the disk-and-washer (DAW) structure, another new type of accelerating structure for use in the high-energy coupled-cavity linac (CCL). Sufficient experimental and developmental progress has been made to closely define an actual PIGMI. It will consist of a 30-kV injector, and RFQ linac to a proton energy of 2.5 MeV, a DTL linac to 125 MeV, and a CCL linac to the final energy of 650 MeV. The total length of the accelerator is 133 meters. The RFQ and DTL will be driven by a single 440-MHz klystron; the CCL will be driven by six 1320-MHz klystrons. The peak beam current is 28 mA. The beam pulse length is 60 ..mu..s at a 60-Hz repetition rate, resulting in a 100-..mu..A average beam current. The total cost of the accelerator is estimated to be approx. $10 million.
Optimization of the Structures at Shakedown and Rosen's Optimality Criterion
NASA Astrophysics Data System (ADS)
Alawdin, Piotr; Atkociunas, Juozas; Liepa, Liudas
2016-09-01
Paper focuses on the problems of application of extreme energy principles and nonlinear mathematical programing in the theory of structural shakedown. By means of energy principles, which describes the true stress-strain state conditions of the structure, the dual mathematical models of analysis problems are formed (static and kinematic formulations). It is shown how common mathematical model of the structures optimization at shakedown with safety and serviceability constraints (according to the ultimate limit state (ULS) and serviceability limit state (SLS) requirements) on the basis of previously mentioned mathematical models is formed. The possibilities of optimization problem solution in the context of physical interpretation of optimality criterion of Rosen's algorithm are analyzed.
Optimal multiobjective design of digital filters using spiral optimization technique.
Ouadi, Abderrahmane; Bentarzi, Hamid; Recioui, Abdelmadjid
2013-01-01
The multiobjective design of digital filters using spiral optimization technique is considered in this paper. This new optimization tool is a metaheuristic technique inspired by the dynamics of spirals. It is characterized by its robustness, immunity to local optima trapping, relative fast convergence and ease of implementation. The objectives of filter design include matching some desired frequency response while having minimum linear phase; hence, reducing the time response. The results demonstrate that the proposed problem solving approach blended with the use of the spiral optimization technique produced filters which fulfill the desired characteristics and are of practical use.
Optimal Multiobjective Design of Digital Filters Using Taguchi Optimization Technique
NASA Astrophysics Data System (ADS)
Ouadi, Abderrahmane; Bentarzi, Hamid; Recioui, Abdelmadjid
2014-01-01
The multiobjective design of digital filters using the powerful Taguchi optimization technique is considered in this paper. This relatively new optimization tool has been recently introduced to the field of engineering and is based on orthogonal arrays. It is characterized by its robustness, immunity to local optima trapping, relative fast convergence and ease of implementation. The objectives of filter design include matching some desired frequency response while having minimum linear phase; hence, reducing the time response. The results demonstrate that the proposed problem solving approach blended with the use of the Taguchi optimization technique produced filters that fulfill the desired characteristics and are of practical use.
Biocapacity optimization in regional planning
NASA Astrophysics Data System (ADS)
Guo, Jianjun; Yue, Dongxia; Li, Kai; Hui, Cang
2017-01-01
Ecological overshoot has been accelerating across the globe. Optimizing biocapacity has become a key to resolve the overshoot of ecological demand in regional sustainable development. However, most literature has focused on reducing ecological footprint but ignores the potential of spatial optimization of biocapacity through regional planning of land use. Here we develop a spatial probability model and present four scenarios for optimizing biocapacity of a river basin in Northwest China. The potential of enhanced biocapacity and its effects on ecological overshoot and water consumption in the region were explored. Two scenarios with no restrictions on croplands and water use reduced the overshoot by 29 to 53%, and another two scenarios which do not allow croplands and water use to increase worsened the overshoot by 11 to 15%. More spatially flexible transition rules of land use led to higher magnitude of change after optimization. However, biocapacity optimization required a large amount of additional water resources, casting considerable pressure on the already water-scarce socio-ecological system. Our results highlight the potential for policy makers to manage/optimize regional land use which addresses ecological overshoot. Investigation on the feasibility of such spatial optimization complies with the forward-looking policies for sustainable development and deserves further attention.
Biocapacity optimization in regional planning
Guo, Jianjun; Yue, Dongxia; Li, Kai; Hui, Cang
2017-01-01
Ecological overshoot has been accelerating across the globe. Optimizing biocapacity has become a key to resolve the overshoot of ecological demand in regional sustainable development. However, most literature has focused on reducing ecological footprint but ignores the potential of spatial optimization of biocapacity through regional planning of land use. Here we develop a spatial probability model and present four scenarios for optimizing biocapacity of a river basin in Northwest China. The potential of enhanced biocapacity and its effects on ecological overshoot and water consumption in the region were explored. Two scenarios with no restrictions on croplands and water use reduced the overshoot by 29 to 53%, and another two scenarios which do not allow croplands and water use to increase worsened the overshoot by 11 to 15%. More spatially flexible transition rules of land use led to higher magnitude of change after optimization. However, biocapacity optimization required a large amount of additional water resources, casting considerable pressure on the already water-scarce socio-ecological system. Our results highlight the potential for policy makers to manage/optimize regional land use which addresses ecological overshoot. Investigation on the feasibility of such spatial optimization complies with the forward-looking policies for sustainable development and deserves further attention. PMID:28112224
Optimizing WFIRST Coronagraph Science
NASA Astrophysics Data System (ADS)
Macintosh, Bruce
We propose an in-depth scientific investigation that will define how the WFIRST coronagraphic instrument will discover and characterize nearby planetary systems and how it will use observations of planets and disks to probe the diversity of their compositions, dynamics, and formation. Given the enormous diversity of known planetary systems it is not enough to optimize a coronagraph mission plan for the characterization of solar system analogs. Instead, we must design a mission to characterize a wide variety of planets, from gas and ice giant planets at a range of separations to mid-sized planets with no analogs in our solar system. We must consider updated planet distributions based on the results of the Kepler mission, long-term radial velocity (RV) surveys and updated luminosity distributions of exo-zodiacal dust from interferometric thermal infrared surveys of nearby stars. The properties of all these objects must be informed by our best models of planets and disks, and the process of using WFIRST observations to measure fundamental planetary properties such as composition must derive from rigorous methods. Our team brings a great depth of expertise to inform and accomplish these and all of the other tasks enumerated in the SIT proposal call. We will perform end-to-end modeling that starts with model spectra of planets and images of disks, simulates WFIRST data using these models, accounts for geometries of specific star / planet / disk systems, and incorporates detailed instrument performance models. We will develop and implement data analysis techniques to extract well-calibrated astrophysical signals from complex data, and propose observing plans that maximize the mission's scientific yield. We will work with the community to build observing programs and target lists, inform them of WFIRSTs capabilities, and supply simulated scientific observations for data challenges. Our work will be informed by the experience we have gained from building and observing with
NASA Technical Reports Server (NTRS)
Allan, Brian; Owens, Lewis
2010-01-01
In support of the Blended-Wing-Body aircraft concept, a new flow control hybrid vane/jet design has been developed for use in a boundary-layer-ingesting (BLI) offset inlet in transonic flows. This inlet flow control is designed to minimize the engine fan-face distortion levels and the first five Fourier harmonic half amplitudes while maximizing the inlet pressure recovery. This concept represents a potentially enabling technology for quieter and more environmentally friendly transport aircraft. An optimum vane design was found by minimizing the engine fan-face distortion, DC60, and the first five Fourier harmonic half amplitudes, while maximizing the total pressure recovery. The optimal vane design was then used in a BLI inlet wind tunnel experiment at NASA Langley's 0.3-meter transonic cryogenic tunnel. The experimental results demonstrated an 80-percent decrease in DPCPavg, the reduction in the circumferential distortion levels, at an inlet mass flow rate corresponding to the middle of the operational range at the cruise condition. Even though the vanes were designed at a single inlet mass flow rate, they performed very well over the entire inlet mass flow range tested in the wind tunnel experiment with the addition of a small amount of jet flow control. While the circumferential distortion was decreased, the radial distortion on the outer rings at the aerodynamic interface plane (AIP) increased. This was a result of the large boundary layer being distributed from the bottom of the AIP in the baseline case to the outer edges of the AIP when using the vortex generator (VG) vane flow control. Experimental results, as already mentioned, showed an 80-percent reduction of DPCPavg, the circumferential distortion level at the engine fan-face. The hybrid approach leverages strengths of vane and jet flow control devices, increasing inlet performance over a broader operational range with significant reduction in mass flow requirements. Minimal distortion level requirements
Optimal Protocols and Optimal Transport in Stochastic Thermodynamics
NASA Astrophysics Data System (ADS)
Aurell, Erik; Mejía-Monasterio, Carlos; Muratore-Ginanneschi, Paolo
2011-06-01
Thermodynamics of small systems has become an important field of statistical physics. Such systems are driven out of equilibrium by a control, and the question is naturally posed how such a control can be optimized. We show that optimization problems in small system thermodynamics are solved by (deterministic) optimal transport, for which very efficient numerical methods have been developed, and of which there are applications in cosmology, fluid mechanics, logistics, and many other fields. We show, in particular, that minimizing expected heat released or work done during a nonequilibrium transition in finite time is solved by the Burgers equation and mass transport by the Burgers velocity field. Our contribution hence considerably extends the range of solvable optimization problems in small system thermodynamics.
Social Emotional Optimization Algorithm for Nonlinear Constrained Optimization Problems
NASA Astrophysics Data System (ADS)
Xu, Yuechun; Cui, Zhihua; Zeng, Jianchao
Nonlinear programming problem is one important branch in operational research, and has been successfully applied to various real-life problems. In this paper, a new approach called Social emotional optimization algorithm (SEOA) is used to solve this problem which is a new swarm intelligent technique by simulating the human behavior guided by emotion. Simulation results show that the social emotional optimization algorithm proposed in this paper is effective and efficiency for the nonlinear constrained programming problems.
Optimal energy growth and optimal control in swept Hiemenz flow
NASA Astrophysics Data System (ADS)
Guégan, Alan; Schmid, Peter J.; Huerre, Patrick
2006-11-01
The objective of the study is first to examine the optimal transient growth of Görtler Hämmerlin perturbations in swept Hiemenz flow. This configuration constitutes a model of the flow in the attachment-line boundary layer at the leading-edge of swept wings. The optimal blowing and suction at the wall which minimizes the energy of the optimal perturbations is then determined. An adjoint-based optimization procedure applicable to both problems is devised, which relies on the maximization or minimization of a suitable objective functional. The variational analysis is carried out in the framework of the set of linear partial differential equations governing the chordwise and wall-normal velocity fluctuations. Energy amplifications of up to three orders of magnitude are achieved at low spanwise wavenumbers (k {˜} 0.1) and large sweep Reynolds number (textit{Re} {˜} 2000). Optimal perturbations consist of spanwise travelling chordwise vortices, with a vorticity distribution which is inclined against the sweep. Transient growth arises from the tilting of the vorticity distribution by the spanwise shear via a two-dimensional Orr mechanism acting in the basic flow dividing plane. Two distinct regimes have been identified: for k {≤sssim} 0.25, vortex dipoles are formed which induce large spanwise perturbation velocities; for k {gtrsim} 0.25, dipoles are not observed and only the Orr mechanism remains active. The optimal wall blowing control yields for instance an 80% decrease of the maximum perturbation kinetic energy reached by optimal disturbances at textit{Re} {=} 550 and k {=} 0.25. The optimal wall blowing pattern consists of spanwise travelling waves which follow the naturally occurring vortices and qualitatively act in the same manner as a more simple constant gain feedback control strategy.
Method of constrained global optimization
NASA Astrophysics Data System (ADS)
Altschuler, Eric Lewin; Williams, Timothy J.; Ratner, Edward R.; Dowla, Farid; Wooten, Frederick
1994-04-01
We present a new method for optimization: constrained global optimization (CGO). CGO iteratively uses a Glauber spin flip probability and the Metropolis algorithm. The spin flip probability allows changing only the values of variables contributing excessively to the function to be minimized. We illustrate CGO with two problems-Thomson's problem of finding the minimum-energy configuration of unit charges on a spherical surface, and a problem of assigning offices-for which CGO finds better minima than other methods. We think CGO will apply to a wide class of optimization problems.
Adaptive approximation models in optimization
Voronin, A.N.
1995-05-01
The paper proposes a method for optimization of functions of several variables that substantially reduces the number of objective function evaluations compared to traditional methods. The method is based on the property of iterative refinement of approximation models of the optimand function in approximation domains that contract to the extremum point. It does not require subjective specification of the starting point, step length, or other parameters of the search procedure. The method is designed for efficient optimization of unimodal functions of several (not more than 10-15) variables and can be applied to find the global extremum of polymodal functions and also for optimization of scalarized forms of vector objective functions.
Metabolism at Evolutionary Optimal States
Rabbers, Iraes; van Heerden, Johan H.; Nordholt, Niclas; Bachmann, Herwig; Teusink, Bas; Bruggeman, Frank J.
2015-01-01
Metabolism is generally required for cellular maintenance and for the generation of offspring under conditions that support growth. The rates, yields (efficiencies), adaptation time and robustness of metabolism are therefore key determinants of cellular fitness. For biotechnological applications and our understanding of the evolution of metabolism, it is necessary to figure out how the functional system properties of metabolism can be optimized, via adjustments of the kinetics and expression of enzymes, and by rewiring metabolism. The trade-offs that can occur during such optimizations then indicate fundamental limits to evolutionary innovations and bioengineering. In this paper, we review several theoretical and experimental findings about mechanisms for metabolic optimization. PMID:26042723
An Efficient Chemical Reaction Optimization Algorithm for Multiobjective Optimization.
Bechikh, Slim; Chaabani, Abir; Ben Said, Lamjed
2015-10-01
Recently, a new metaheuristic called chemical reaction optimization was proposed. This search algorithm, inspired by chemical reactions launched during collisions, inherits several features from other metaheuristics such as simulated annealing and particle swarm optimization. This fact has made it, nowadays, one of the most powerful search algorithms in solving mono-objective optimization problems. In this paper, we propose a multiobjective variant of chemical reaction optimization, called nondominated sorting chemical reaction optimization, in an attempt to exploit chemical reaction optimization features in tackling problems involving multiple conflicting criteria. Since our approach is based on nondominated sorting, one of the main contributions of this paper is the proposal of a new quasi-linear average time complexity quick nondominated sorting algorithm; thereby making our multiobjective algorithm efficient from a computational cost viewpoint. The experimental comparisons against several other multiobjective algorithms on a variety of benchmark problems involving various difficulties show the effectiveness and the efficiency of this multiobjective version in providing a well-converged and well-diversified approximation of the Pareto front.
Optimality and sub-optimality in a bacterial growth law
Towbin, Benjamin D.; Korem, Yael; Bren, Anat; Doron, Shany; Sorek, Rotem; Alon, Uri
2017-01-01
Organisms adjust their gene expression to improve fitness in diverse environments. But finding the optimal expression in each environment presents a challenge. We ask how good cells are at finding such optima by studying the control of carbon catabolism genes in Escherichia coli. Bacteria show a growth law: growth rate on different carbon sources declines linearly with the steady-state expression of carbon catabolic genes. We experimentally modulate gene expression to ask if this growth law always maximizes growth rate, as has been suggested by theory. We find that the growth law is optimal in many conditions, including a range of perturbations to lactose uptake, but provides sub-optimal growth on several other carbon sources. Combining theory and experiment, we genetically re-engineer E. coli to make sub-optimal conditions into optimal ones and vice versa. We conclude that the carbon growth law is not always optimal, but represents a practical heuristic that often works but sometimes fails. PMID:28102224
NASA Astrophysics Data System (ADS)
Tarpine, Ryan; Lam, Fumei; Istrail, Sorin
We present results on two classes of problems. The first result addresses the long standing open problem of finding unifying principles for Linkage Disequilibrium (LD) measures in population genetics (Lewontin 1964 [10], Hedrick 1987 [8], Devlin and Risch 1995 [5]). Two desirable properties have been proposed in the extensive literature on this topic and the mutual consistency between these properties has remained at the heart of statistical and algorithmic difficulties with haplotype and genome-wide association study analysis. The first axiom is (1) The ability to extend LD measures to multiple loci as a conservative extension of pairwise LD. All widely used LD measures are pairwise measures. Despite significant attempts, it is not clear how to naturally extend these measures to multiple loci, leading to a "curse of the pairwise". The second axiom is (2) The Interpretability of Intermediate Values. In this paper, we resolve this mutual consistency problem by introducing a new LD measure, directed informativeness overrightarrow{I} (the directed graph theoretic counterpart of the informativeness measure introduced by Halldorsson et al. [6]) and show that it satisfies both of the above axioms. We also show the maximum informative subset of tagging SNPs based on overrightarrow{I} can be computed exactly in polynomial time for realistic genome-wide data. Furthermore, we present polynomial time algorithms for optimal genome-wide tagging SNPs selection for a number of commonly used LD measures, under the bounded neighborhood assumption for linked pairs of SNPs. One problem in the area is the search for a quality measure for tagging SNPs selection that unifies the LD-based methods such as LD-select (implemented in Tagger, de Bakker et al. 2005 [4], Carlson et al. 2004 [3]) and the information-theoretic ones such as informativeness. We show that the objective function of the LD-select algorithm is the Minimal Dominating Set (MDS) on r 2-SNP graphs and show that we can
Energy Criteria for Resource Optimization
ERIC Educational Resources Information Center
Griffith, J. W.
1973-01-01
Resource optimization in building design is based on the total system over its expected useful life. Alternative environmental systems can be evaluated in terms of resource costs and goal effectiveness. (Author/MF)
Putting combustion optimization to work
Spring, N.
2009-05-15
New plants and plants that are retrofitting can benefit from combustion optimization. Boiler tuning and optimization can complement each other. The continuous emissions monitoring system CEMS, and tunable diode laser absorption spectroscopy TDLAS can be used for optimisation. NeuCO's CombustionOpt neural network software can determine optimal fuel and air set points. Babcock and Wilcox Power Generation Group Inc's Flame Doctor can be used in conjunction with other systems to diagnose and correct coal-fired burner performance. The four units of the Colstrip power plant in Colstrips, Montana were recently fitted with combustion optimization systems based on advanced model predictive multi variable controls (MPCs), ABB's Predict & Control tool. Unit 4 of Tampa Electric's Big Bend plant in Florida is fitted with Emerson's SmartProcess fuzzy neural model based combustion optimisation system. 1 photo.
Nonlinear optimization for stochastic simulations.
Johnson, Michael M.; Yoshimura, Ann S.; Hough, Patricia Diane; Ammerlahn, Heidi R.
2003-12-01
This report describes research targeting development of stochastic optimization algorithms and their application to mission-critical optimization problems in which uncertainty arises. The first section of this report covers the enhancement of the Trust Region Parallel Direct Search (TRPDS) algorithm to address stochastic responses and the incorporation of the algorithm into the OPT++ optimization library. The second section describes the Weapons of Mass Destruction Decision Analysis Center (WMD-DAC) suite of systems analysis tools and motivates the use of stochastic optimization techniques in such non-deterministic simulations. The third section details a batch programming interface designed to facilitate criteria-based or algorithm-driven execution of system-of-system simulations. The fourth section outlines the use of the enhanced OPT++ library and batch execution mechanism to perform systems analysis and technology trade-off studies in the WMD detection and response problem domain.
Habitat Design Optimization and Analysis
NASA Technical Reports Server (NTRS)
SanSoucie, Michael P.; Hull, Patrick V.; Tinker, Michael L.
2006-01-01
Long-duration surface missions to the Moon and Mars will require habitats for the astronauts. The materials chosen for the habitat walls play a direct role in the protection against the harsh environments found on the surface. Choosing the best materials, their configuration, and the amount required is extremely difficult due to the immense size of the design region. Advanced optimization techniques are necessary for habitat wall design. Standard optimization techniques are not suitable for problems with such large search spaces; therefore, a habitat design optimization tool utilizing genetic algorithms has been developed. Genetic algorithms use a "survival of the fittest" philosophy, where the most fit individuals are more likely to survive and reproduce. This habitat design optimization tool is a multi-objective formulation of structural analysis, heat loss, radiation protection, and meteoroid protection. This paper presents the research and development of this tool.
Dual approximations in optimal control
NASA Technical Reports Server (NTRS)
Hager, W. W.; Ianculescu, G. D.
1984-01-01
A dual approximation for the solution to an optimal control problem is analyzed. The differential equation is handled with a Lagrange multiplier while other constraints are treated explicitly. An algorithm for solving the dual problem is presented.
Optimal solar sail planetocentric trajectories
NASA Technical Reports Server (NTRS)
Sackett, L. L.
1977-01-01
The analysis of solar sail planetocentric optimal trajectory problem is described. A computer program was produced to calculate optimal trajectories for a limited performance analysis. A square sail model is included and some consideration is given to a heliogyro sail model. Orbit to a subescape point and orbit to orbit transfer are considered. Trajectories about the four inner planets can be calculated and shadowing, oblateness, and solar motion may be included. Equinoctial orbital elements are used to avoid the classical singularities, and the method of averaging is applied to increase computational speed. Solution of the two-point boundary value problem which arises from the application of optimization theory is accomplished with a Newton procedure. Time optimal trajectories are emphasized, but a penalty function has been considered to prevent trajectories which intersect a planet's surface.
Data Understanding Applied to Optimization
NASA Technical Reports Server (NTRS)
Buntine, Wray; Shilman, Michael
1998-01-01
The goal of this research is to explore and develop software for supporting visualization and data analysis of search and optimization. Optimization is an ever-present problem in science. The theory of NP-completeness implies that the problems can only be resolved by increasingly smarter problem specific knowledge, possibly for use in some general purpose algorithms. Visualization and data analysis offers an opportunity to accelerate our understanding of key computational bottlenecks in optimization and to automatically tune aspects of the computation for specific problems. We will prototype systems to demonstrate how data understanding can be successfully applied to problems characteristic of NASA's key science optimization tasks, such as central tasks for parallel processing, spacecraft scheduling, and data transmission from a remote satellite.
CENTRAL PLATEAU REMEDIATION OPTIMIZATION STUDY
BERGMAN, T. B.; STEFANSKI, L. D.; SEELEY, P. N.; ZINSLI, L. C.; CUSACK, L. J.
2012-09-19
THE CENTRAL PLATEAU REMEDIATION OPTIMIZATION STUDY WAS CONDUCTED TO DEVELOP AN OPTIMAL SEQUENCE OF REMEDIATION ACTIVITIES IMPLEMENTING THE CERCLA DECISION ON THE CENTRAL PLATEAU. THE STUDY DEFINES A SEQUENCE OF ACTIVITIES THAT RESULT IN AN EFFECTIVE USE OF RESOURCES FROM A STRATEGIC PERSPECTIVE WHEN CONSIDERING EQUIPMENT PROCUREMENT AND STAGING, WORKFORCE MOBILIZATION/DEMOBILIZATION, WORKFORCE LEVELING, WORKFORCE SKILL-MIX, AND OTHER REMEDIATION/DISPOSITION PROJECT EXECUTION PARAMETERS.
MISO - Mixed Integer Surrogate Optimization
Mueller, Juliane
2016-01-20
MISO is an optimization framework for solving computationally expensive mixed-integer, black-box, global optimization problems. MISO uses surrogate models to approximate the computationally expensive objective function. Hence, derivative information, which is generally unavailable for black-box simulation objective functions, is not needed. MISO allows the user to choose the initial experimental design strategy, the type of surrogate model, and the sampling strategy.
Design optimization of space structures
NASA Astrophysics Data System (ADS)
Felippa, Carlos
1991-11-01
The topology-shape-size optimization of space structures is investigated through Kikuchi's homogenization method. The method starts from a 'design domain block,' which is a region of space into which the structure is to materialize. This domain is initially filled with a finite element mesh, typically regular. Force and displacement boundary conditions corresponding to applied loads and supports are applied at specific points in the domain. An optimal structure is to be 'carved out' of the design under two conditions: (1) a cost function is to be minimized, and (2) equality or inequality constraints are to be satisfied. The 'carving' process is accomplished by letting microstructure holes develop and grow in elements during the optimization process. These holes have a rectangular shape in two dimensions and a cubical shape in three dimensions, and may also rotate with respect to the reference axes. The properties of the perforated element are obtained through an homogenization procedure. Once a hole reaches the volume of the element, that element effectively disappears. The project has two phases. In the first phase the method was implemented as the combination of two computer programs: a finite element module, and an optimization driver. In the second part, focus is on the application of this technique to planetary structures. The finite element part of the method was programmed for the two-dimensional case using four-node quadrilateral elements to cover the design domain. An element homogenization technique different from that of Kikuchi and coworkers was implemented. The optimization driver is based on an augmented Lagrangian optimizer, with the volume constraint treated as a Courant penalty function. The optimizer has to be especially tuned to this type of optimization because the number of design variables can reach into the thousands. The driver is presently under development.
Optimality Functions and Lopsided Convergence
2015-03-16
Problems involving functions defined in terms of integrals or optimization problems (as the maxi - mization in Example 3), functions defined on infinite...optimization methods in finite time. The key technical challenge associate with the above scheme is to establish ( weak ) consistency. In the next...Theorem 4.3. In view of this result, it is clear that ( weak ) consistency will be ensured by epi-convergence of the approximating objective functions and
Optimal encryption of quantum bits
Boykin, P. Oscar; Roychowdhury, Vwani
2003-04-01
We show that 2n random classical bits are both necessary and sufficient for encrypting any unknown state of n quantum bits in an informationally secure manner. We also characterize the complete set of optimal protocols in terms of a set of unitary operations that comprise an orthonormal basis in a canonical inner product space. Moreover, a connection is made between quantum encryption and quantum teleportation that allows for a different proof of optimality of teleportation.
Numerical Optimization Using Computer Experiments
NASA Technical Reports Server (NTRS)
Trosset, Michael W.; Torczon, Virginia
1997-01-01
Engineering design optimization often gives rise to problems in which expensive objective functions are minimized by derivative-free methods. We propose a method for solving such problems that synthesizes ideas from the numerical optimization and computer experiment literatures. Our approach relies on kriging known function values to construct a sequence of surrogate models of the objective function that are used to guide a grid search for a minimizer. Results from numerical experiments on a standard test problem are presented.
A systolic array optimizing compiler
Lam, M.S. )
1988-01-01
This book documents the research and results of the compiler technology developed for the Warp machine. A major challenge in the development of Warp was to build an optimizing compiler for the machine. This book describes a compiler that shields most of the difficulty from the user and generates very efficient code. Several new optimizations are described and evaluated. The research described confirms that compilers play a valuable role in the development, usage and effectiveness of novel high-performance architectures.
Optimization of neutron imaging plate
NASA Astrophysics Data System (ADS)
Haga, Y. K.; Neriishi, K.; Takahashi, K.; Niimura, N.
2002-07-01
Considering the elementary processes of neutron detection occurring in the neutron imaging plate (NIP) has optimized the performance of NIP. For these processes, the color center creation efficiencies ( ɛcc values) have been experimentally determined with NIPs which have different mole fraction of photostimulated (PSL) material ( φPSL values) and different thickness ( t). The effectiveness of the optimization procedure has been demonstrated by the measurement of the neutron diffraction intensities from a hen egg-white lysozyme protein crystal.
Unrealistic optimism: East and west?
Joshi, Mary Sissons; Carter, Wakefield
2013-01-01
Following Weinstein's (1980) pioneering work many studies established that people have an optimistic bias concerning future life events. At first, the bulk of research was conducted using populations in North America and Northern Europe, the optimistic bias was thought of as universal, and little attention was paid to cultural context. However, construing unrealistic optimism as a form of self-enhancement, some researchers noted that it was far less common in East Asian cultures. The current study extends enquiry to a different non-Western culture. Two hundred and eighty seven middle aged and middle income participants (200 in India, 87 in England) rated 11 positive and 11 negative events in terms of the chances of each event occurring in "their own life," and the chances of each event occurring in the lives of "people like them." Comparative optimism was shown for bad events, with Indian participants showing higher levels of optimism than English participants. The position regarding comparative optimism for good events was more complex. In India those of higher socioeconomic status (SES) were optimistic, while those of lower SES were on average pessimistic. Overall, English participants showed neither optimism nor pessimism for good events. The results, whose clinical relevance is discussed, suggest that the expression of unrealistic optimism is shaped by an interplay of culture and socioeconomic circumstance.
Optimal control of motorsport differentials
NASA Astrophysics Data System (ADS)
Tremlett, A. J.; Massaro, M.; Purdy, D. J.; Velenis, E.; Assadian, F.; Moore, A. P.; Halley, M.
2015-12-01
Modern motorsport limited slip differentials (LSD) have evolved to become highly adjustable, allowing the torque bias that they generate to be tuned in the corner entry, apex and corner exit phases of typical on-track manoeuvres. The task of finding the optimal torque bias profile under such varied vehicle conditions is complex. This paper presents a nonlinear optimal control method which is used to find the minimum time optimal torque bias profile through a lane change manoeuvre. The results are compared to traditional open and fully locked differential strategies, in addition to considering related vehicle stability and agility metrics. An investigation into how the optimal torque bias profile changes with reduced track-tyre friction is also included in the analysis. The optimal LSD profile was shown to give a performance gain over its locked differential counterpart in key areas of the manoeuvre where a quick direction change is required. The methodology proposed can be used to find both optimal passive LSD characteristics and as the basis of a semi-active LSD control algorithm.
Efficient computation of optimal actions.
Todorov, Emanuel
2009-07-14
Optimal choice of actions is a fundamental problem relevant to fields as diverse as neuroscience, psychology, economics, computer science, and control engineering. Despite this broad relevance the abstract setting is similar: we have an agent choosing actions over time, an uncertain dynamical system whose state is affected by those actions, and a performance criterion that the agent seeks to optimize. Solving problems of this kind remains hard, in part, because of overly generic formulations. Here, we propose a more structured formulation that greatly simplifies the construction of optimal control laws in both discrete and continuous domains. An exhaustive search over actions is avoided and the problem becomes linear. This yields algorithms that outperform Dynamic Programming and Reinforcement Learning, and thereby solve traditional problems more efficiently. Our framework also enables computations that were not possible before: composing optimal control laws by mixing primitives, applying deterministic methods to stochastic systems, quantifying the benefits of error tolerance, and inferring goals from behavioral data via convex optimization. Development of a general class of easily solvable problems tends to accelerate progress--as linear systems theory has done, for example. Our framework may have similar impact in fields where optimal choice of actions is relevant.
Optimal lattice-structured materials
NASA Astrophysics Data System (ADS)
Messner, Mark C.
2016-11-01
This work describes a method for optimizing the mesostructure of lattice-structured materials. These materials are periodic arrays of slender members resembling efficient, lightweight macroscale structures like bridges and frame buildings. Current additive manufacturing technologies can assemble lattice structures with length scales ranging from nanometers to millimeters. Previous work demonstrates that lattice materials have excellent stiffness- and strength-to-weight scaling, outperforming natural materials. However, there are currently no methods for producing optimal mesostructures that consider the full space of possible 3D lattice topologies. The inverse homogenization approach for optimizing the periodic structure of lattice materials requires a parameterized, homogenized material model describing the response of an arbitrary structure. This work develops such a model, starting with a method for describing the long-wavelength, macroscale deformation of an arbitrary lattice. The work combines the homogenized model with a parameterized description of the total design space to generate a parameterized model. Finally, the work describes an optimization method capable of producing optimal mesostructures. Several examples demonstrate the optimization method. One of these examples produces an elastically isotropic, maximally stiff structure, here called the isotruss, that arguably outperforms the anisotropic octet truss topology.
Pyomo : Python Optimization Modeling Objects.
Siirola, John; Laird, Carl Damon; Hart, William Eugene; Watson, Jean-Paul
2010-11-01
The Python Optimization Modeling Objects (Pyomo) package [1] is an open source tool for modeling optimization applications within Python. Pyomo provides an objected-oriented approach to optimization modeling, and it can be used to define symbolic problems, create concrete problem instances, and solve these instances with standard solvers. While Pyomo provides a capability that is commonly associated with algebraic modeling languages such as AMPL, AIMMS, and GAMS, Pyomo's modeling objects are embedded within a full-featured high-level programming language with a rich set of supporting libraries. Pyomo leverages the capabilities of the Coopr software library [2], which integrates Python packages (including Pyomo) for defining optimizers, modeling optimization applications, and managing computational experiments. A central design principle within Pyomo is extensibility. Pyomo is built upon a flexible component architecture [3] that allows users and developers to readily extend the core Pyomo functionality. Through these interface points, extensions and applications can have direct access to an optimization model's expression objects. This facilitates the rapid development and implementation of new modeling constructs and as well as high-level solution strategies (e.g. using decomposition- and reformulation-based techniques). In this presentation, we will give an overview of the Pyomo modeling environment and model syntax, and present several extensions to the core Pyomo environment, including support for Generalized Disjunctive Programming (Coopr GDP), Stochastic Programming (PySP), a generic Progressive Hedging solver [4], and a tailored implementation of Bender's Decomposition.
Optimal lattice-structured materials
Messner, Mark C.
2016-07-09
This paper describes a method for optimizing the mesostructure of lattice-structured materials. These materials are periodic arrays of slender members resembling efficient, lightweight macroscale structures like bridges and frame buildings. Current additive manufacturing technologies can assemble lattice structures with length scales ranging from nanometers to millimeters. Previous work demonstrates that lattice materials have excellent stiffness- and strength-to-weight scaling, outperforming natural materials. However, there are currently no methods for producing optimal mesostructures that consider the full space of possible 3D lattice topologies. The inverse homogenization approach for optimizing the periodic structure of lattice materials requires a parameterized, homogenized material model describingmore » the response of an arbitrary structure. This work develops such a model, starting with a method for describing the long-wavelength, macroscale deformation of an arbitrary lattice. The work combines the homogenized model with a parameterized description of the total design space to generate a parameterized model. Finally, the work describes an optimization method capable of producing optimal mesostructures. Several examples demonstrate the optimization method. One of these examples produces an elastically isotropic, maximally stiff structure, here called the isotruss, that arguably outperforms the anisotropic octet truss topology.« less
Optimal lattice-structured materials
Messner, Mark C.
2016-07-09
This paper describes a method for optimizing the mesostructure of lattice-structured materials. These materials are periodic arrays of slender members resembling efficient, lightweight macroscale structures like bridges and frame buildings. Current additive manufacturing technologies can assemble lattice structures with length scales ranging from nanometers to millimeters. Previous work demonstrates that lattice materials have excellent stiffness- and strength-to-weight scaling, outperforming natural materials. However, there are currently no methods for producing optimal mesostructures that consider the full space of possible 3D lattice topologies. The inverse homogenization approach for optimizing the periodic structure of lattice materials requires a parameterized, homogenized material model describing the response of an arbitrary structure. This work develops such a model, starting with a method for describing the long-wavelength, macroscale deformation of an arbitrary lattice. The work combines the homogenized model with a parameterized description of the total design space to generate a parameterized model. Finally, the work describes an optimization method capable of producing optimal mesostructures. Several examples demonstrate the optimization method. One of these examples produces an elastically isotropic, maximally stiff structure, here called the isotruss, that arguably outperforms the anisotropic octet truss topology.
Unrealistic Optimism: East and West?
Joshi, Mary Sissons; Carter, Wakefield
2013-01-01
Following Weinstein’s (1980) pioneering work many studies established that people have an optimistic bias concerning future life events. At first, the bulk of research was conducted using populations in North America and Northern Europe, the optimistic bias was thought of as universal, and little attention was paid to cultural context. However, construing unrealistic optimism as a form of self-enhancement, some researchers noted that it was far less common in East Asian cultures. The current study extends enquiry to a different non-Western culture. Two hundred and eighty seven middle aged and middle income participants (200 in India, 87 in England) rated 11 positive and 11 negative events in terms of the chances of each event occurring in “their own life,” and the chances of each event occurring in the lives of “people like them.” Comparative optimism was shown for bad events, with Indian participants showing higher levels of optimism than English participants. The position regarding comparative optimism for good events was more complex. In India those of higher socioeconomic status (SES) were optimistic, while those of lower SES were on average pessimistic. Overall, English participants showed neither optimism nor pessimism for good events. The results, whose clinical relevance is discussed, suggest that the expression of unrealistic optimism is shaped by an interplay of culture and socioeconomic circumstance. PMID:23407689
Efficient computation of optimal actions
Todorov, Emanuel
2009-01-01
Optimal choice of actions is a fundamental problem relevant to fields as diverse as neuroscience, psychology, economics, computer science, and control engineering. Despite this broad relevance the abstract setting is similar: we have an agent choosing actions over time, an uncertain dynamical system whose state is affected by those actions, and a performance criterion that the agent seeks to optimize. Solving problems of this kind remains hard, in part, because of overly generic formulations. Here, we propose a more structured formulation that greatly simplifies the construction of optimal control laws in both discrete and continuous domains. An exhaustive search over actions is avoided and the problem becomes linear. This yields algorithms that outperform Dynamic Programming and Reinforcement Learning, and thereby solve traditional problems more efficiently. Our framework also enables computations that were not possible before: composing optimal control laws by mixing primitives, applying deterministic methods to stochastic systems, quantifying the benefits of error tolerance, and inferring goals from behavioral data via convex optimization. Development of a general class of easily solvable problems tends to accelerate progress—as linear systems theory has done, for example. Our framework may have similar impact in fields where optimal choice of actions is relevant. PMID:19574462
Optimal BLS: Optimizing transit-signal detection for Keplerian dynamics
NASA Astrophysics Data System (ADS)
Ofir, Aviv
2015-08-01
Transit surveys, both ground- and space-based, have already accumulated a large number of light curves that span several years. We optimize the search for transit signals for both detection and computational efficiencies by assuming that the searched systems can be described by Keplerian, and propagating the effects of different system parameters to the detection parameters. Importnantly, we mainly consider the information content of the transit signal and not any specific algorithm - and use BLS (Kovács, Zucker, & Mazeh 2002) just as a specific example.We show that the frequency information content of the light curve is primarily determined by the duty cycle of the transit signal, and thus the optimal frequency sampling is found to be cubic and not linear. Further optimization is achieved by considering duty-cycle dependent binning of the phased light curve. By using the (standard) BLS, one is either fairly insensitive to long-period planets or less sensitive to short-period planets and computationally slower by a significant factor of ~330 (for a 3 yr long dataset). We also show how the physical system parameters, such as the host star's size and mass, directly affect transit detection. This understanding can then be used to optimize the search for every star individually.By considering Keplerian dynamics explicitly rather than implicitly one can optimally search the transit signal parameter space. The presented Optimal BLS enhances the detectability of both very short and very long period planets, while allowing such searches to be done with much reduced resources and time. The Matlab/Octave source code for Optimal BLS is made available.
A novel metaheuristic for continuous optimization problems: Virus optimization algorithm
NASA Astrophysics Data System (ADS)
Liang, Yun-Chia; Rodolfo Cuevas Juarez, Josue
2016-01-01
A novel metaheuristic for continuous optimization problems, named the virus optimization algorithm (VOA), is introduced and investigated. VOA is an iteratively population-based method that imitates the behaviour of viruses attacking a living cell. The number of viruses grows at each replication and is controlled by an immune system (a so-called 'antivirus') to prevent the explosive growth of the virus population. The viruses are divided into two classes (strong and common) to balance the exploitation and exploration effects. The performance of the VOA is validated through a set of eight benchmark functions, which are also subject to rotation and shifting effects to test its robustness. Extensive comparisons were conducted with over 40 well-known metaheuristic algorithms and their variations, such as artificial bee colony, artificial immune system, differential evolution, evolutionary programming, evolutionary strategy, genetic algorithm, harmony search, invasive weed optimization, memetic algorithm, particle swarm optimization and simulated annealing. The results showed that the VOA is a viable solution for continuous optimization.
Schedule path optimization for adiabatic quantum computing and optimization
NASA Astrophysics Data System (ADS)
Zeng, Lishan; Zhang, Jun; Sarovar, Mohan
2016-04-01
Adiabatic quantum computing and optimization have garnered much attention recently as possible models for achieving a quantum advantage over classical approaches to optimization and other special purpose computations. Both techniques are probabilistic in nature and the minimum gap between the ground state and first excited state of the system during evolution is a major factor in determining the success probability. In this work we investigate a strategy for increasing the minimum gap and success probability by introducing intermediate Hamiltonians that modify the evolution path between initial and final Hamiltonians. We focus on an optimization problem relevant to recent hardware implementations and present numerical evidence for the existence of a purely local intermediate Hamiltonian that achieve the optimum performance in terms of pushing the minimum gap to one of the end points of the evolution. As a part of this study we develop a convex optimization formulation of the search for optimal adiabatic schedules that makes this computation more tractable, and which may be of independent interest. We further study the effectiveness of random intermediate Hamiltonians on the minimum gap and success probability, and empirically find that random Hamiltonians have a significant probability of increasing the success probability, but only by a modest amount.
Optimal Arrangement of Components Via Pairwise Rearrangements.
1987-10-01
reliability function under component pairwise rearrangement. They use this property to find the optimal component arrangement. Worked examples illustrate the methods proposed. Keywords: Optimization; Permutations; Nodes.
Remediation Optimization: Definition, Scope and Approach
This document provides a general definition, scope and approach for conducting optimization reviews within the Superfund Program and includes the fundamental principles and themes common to optimization.
Optimal singular control with applications to trajectory optimization
NASA Technical Reports Server (NTRS)
Vinh, N. X.
1977-01-01
A comprehensive discussion of the problem of singular control is presented. Singular control enters an optimal trajectory when the so called switching function vanishes identically over a finite time interval. Using the concept of domain of maneuverability, the problem of optical switching is analyzed. Criteria for the optimal direction of switching are presented. The switching, or junction, between nonsingular and singular subarcs is examined in detail. Several theorems concerning the necessary, and also sufficient conditions for smooth junction are presented. The concepts of quasi-linear control and linearized control are introduced. They are designed for the purpose of obtaining approximate solution for the difficult Euler-Lagrange type of optimal control in the case where the control is nonlinear.
On optimal velocity during cycling.
Maroński, R
1994-02-01
This paper focuses on the solution of two problems related to cycling. One is to determine the velocity as a function of distance which minimizes the cyclist's energy expenditure in covering a given distance in a set time. The other is to determine the velocity as a function of the distance which minimizes time for fixed energy expenditure. To solve these problems, an equation of motion for the cyclist riding over arbitrary terrain is written using Newton's second law. This equation is used to evaluate either energy expenditure or time, and the minimization problems are solved using an optimal control formulation in conjunction with the method of Miele [Optimization Techniques with Applications to Aerospace Systems, pp. 69-98 (1962) Academic Press, New York]. Solutions to both optimal control problems are the same. The solutions are illustrated through two examples. In one example where the relative wind velocity is zero, the optimal cruising velocity is constant regardless of terrain. In the second, where the relative wind velocity fluctuates, the optimal cruising velocity varies.
Recent Advances in Stellarator Optimization
NASA Astrophysics Data System (ADS)
Gates, David; Brown, T.; Breslau, J.; Landreman, M.; Lazerson, S. A.; Mynick, H.; Neilson, G. H.; Pomphrey, N.
2016-10-01
Computational optimization has revolutionized the field of stellarator design. To date, optimizations have focused primarily on optimization of neoclassical confinement and ideal MHD stability, although limited optimization of other parameters has also been performed. One criticism that has been levelled at this method of design is the complexity of the resultant field coils. Recently, a new coil optimization code, COILOPT + + , was written and included in the STELLOPT suite of codes. The advantage of this method is that it allows the addition of real space constraints on the locations of the coils. As an initial exercise, a constraint that the windings be vertical was placed on large major radius half of the non-planar coils. Further constraints were also imposed that guaranteed that sector blanket modules could be removed from between the coils, enabling a sector maintenance scheme. Results of this exercise will be presented. We have also explored possibilities for generating an experimental database that could check whether the reduction in turbulent transport that is predicted by GENE as a function of local shear would be consistent with experiments. To this end, a series of equilibria that can be made in the now latent QUASAR experiment have been identified. This work was supported by U.S. DoE Contract #DE-AC02-09CH11466.
Optimization of the magnetic dynamo.
Willis, Ashley P
2012-12-21
In stars and planets, magnetic fields are believed to originate from the motion of electrically conducting fluids in their interior, through a process known as the dynamo mechanism. In this Letter, an optimization procedure is used to simultaneously address two fundamental questions of dynamo theory: "Which velocity field leads to the most magnetic energy growth?" and "How large does the velocity need to be relative to magnetic diffusion?" In general, this requires optimization over the full space of continuous solenoidal velocity fields possible within the geometry. Here the case of a periodic box is considered. Measuring the strength of the flow with the root-mean-square amplitude, an optimal velocity field is shown to exist, but without limitation on the strain rate, optimization is prone to divergence. Measuring the flow in terms of its associated dissipation leads to the identification of a single optimal at the critical magnetic Reynolds number necessary for a dynamo. This magnetic Reynolds number is found to be only 15% higher than that necessary for transient growth of the magnetic field.
Current Trends in Multidrug Optimization.
Weiss, Andrea; Nowak-Sliwinska, Patrycja
2016-12-01
The identification of effective and long-lasting cancer therapies still remains elusive, partially due to patient and tumor heterogeneity, acquired drug resistance, and single-drug dose-limiting toxicities. The use of drug combinations may help to overcome some limitations of current cancer therapies by challenging the robustness and redundancy of biological processes. However, effective drug combination optimization requires the careful consideration of numerous parameters. The complexity of this optimization problem is clearly nontrivial and likely requires the assistance of advanced heuristic optimization techniques. In the current review, we discuss the application of optimization techniques for the identification of optimal drug combinations. More specifically, we focus on the application of phenotype-based screening approaches in the field of cancer therapy. These methods are divided into three categories: (1) modeling methods, (2) model-free approaches based on biological search algorithms, and (3) merged approaches, particularly phenotypically driven network biology methods and computation network models relying on phenotypic data. In addition to a brief description of each approach, we include a critical discussion of the advantages and disadvantages of each method, with a strong focus on the limitations and considerations needed to successfully apply such methods in biological research.
Optimal design of solidification processes
NASA Technical Reports Server (NTRS)
Dantzig, Jonathan A.; Tortorelli, Daniel A.
1991-01-01
An optimal design algorithm is presented for the analysis of general solidification processes, and is demonstrated for the growth of GaAs crystals in a Bridgman furnace. The system is optimal in the sense that the prespecified temperature distribution in the solidifying materials is obtained to maximize product quality. The optimization uses traditional numerical programming techniques which require the evaluation of cost and constraint functions and their sensitivities. The finite element method is incorporated to analyze the crystal solidification problem, evaluate the cost and constraint functions, and compute the sensitivities. These techniques are demonstrated in the crystal growth application by determining an optimal furnace wall temperature distribution to obtain the desired temperature profile in the crystal, and hence to maximize the crystal's quality. Several numerical optimization algorithms are studied to determine the proper convergence criteria, effective 1-D search strategies, appropriate forms of the cost and constraint functions, etc. In particular, we incorporate the conjugate gradient and quasi-Newton methods for unconstrained problems. The efficiency and effectiveness of each algorithm is presented in the example problem.
Machine Translation Evaluation and Optimization
NASA Astrophysics Data System (ADS)
Dorr, Bonnie; Olive, Joseph; McCary, John; Christianson, Caitlin
The evaluation of machine translation (MT) systems is a vital field of research, both for determining the effectiveness of existing MT systems and for optimizing the performance of MT systems. This part describes a range of different evaluation approaches used in the GALE community and introduces evaluation protocols and methodologies used in the program. We discuss the development and use of automatic, human, task-based and semi-automatic (human-in-the-loop) methods of evaluating machine translation, focusing on the use of a human-mediated translation error rate HTER as the evaluation standard used in GALE. We discuss the workflow associated with the use of this measure, including post editing, quality control, and scoring. We document the evaluation tasks, data, protocols, and results of recent GALE MT Evaluations. In addition, we present a range of different approaches for optimizing MT systems on the basis of different measures. We outline the requirements and specific problems when using different optimization approaches and describe how the characteristics of different MT metrics affect the optimization. Finally, we describe novel recent and ongoing work on the development of fully automatic MT evaluation metrics that have the potential to substantially improve the effectiveness of evaluation and optimization of MT systems.
Large deviations and portfolio optimization
NASA Astrophysics Data System (ADS)
Sornette, Didier
Risk control and optimal diversification constitute a major focus in the finance and insurance industries as well as, more or less consciously, in our everyday life. We present a discussion of the characterization of risks and of the optimization of portfolios that starts from a simple illustrative model and ends by a general functional integral formulation. A major item is that risk, usually thought of as one-dimensional in the conventional mean-variance approach, has to be addressed by the full distribution of losses. Furthermore, the time-horizon of the investment is shown to play a major role. We show the importance of accounting for large fluctuations and use the theory of Cramér for large deviations in this context. We first treat a simple model with a single risky asset that exemplifies the distinction between the average return and the typical return and the role of large deviations in multiplicative processes, and the different optimal strategies for the investors depending on their size. We then analyze the case of assets whose price variations are distributed according to exponential laws, a situation that is found to describe daily price variations reasonably well. Several portfolio optimization strategies are presented that aim at controlling large risks. We end by extending the standard mean-variance portfolio optimization theory, first within the quasi-Gaussian approximation and then using a general formulation for non-Gaussian correlated assets in terms of the formalism of functional integrals developed in the field theory of critical phenomena.
Multivariate optimization of production systems
Carroll, J.A.; Horne, R.N. )
1992-07-01
This paper reports that mathematically, optimization involves finding the extreme values of a function. Given a function of several variables, Z = {integral}({rvec x}{sub 1}, {rvec x}{sub 2},{rvec x}{sub 3},{yields}x{sub n}), an optimization scheme will find the combination of these variables that produces an extreme value in the function, whether it is a minimum or a maximum value. Many examples of optimization exist. For instance, if a function gives and investor's expected return on the basis of different investments, numerical optimization of the function will determine the mix of investments that will yield the maximum expected return. This is the basis of modern portfolio theory. If a function gives the difference between a set of data and a model of the data, numerical optimization of the function will produce the best fit of the model to the data. This is the basis for nonlinear parameter estimation. Similar examples can be given for network analysis, queuing theory, decision analysis, etc.
Systematic Propulsion Optimization Tools (SPOT)
NASA Technical Reports Server (NTRS)
Bower, Mark; Celestian, John
1992-01-01
This paper describes a computer program written by senior-level Mechanical Engineering students at the University of Alabama in Huntsville which is capable of optimizing user-defined delivery systems for carrying payloads into orbit. The custom propulsion system is designed by the user through the input of configuration, payload, and orbital parameters. The primary advantages of the software, called Systematic Propulsion Optimization Tools (SPOT), are a user-friendly interface and a modular FORTRAN 77 code designed for ease of modification. The optimization of variables in an orbital delivery system is of critical concern in the propulsion environment. The mass of the overall system must be minimized within the maximum stress, force, and pressure constraints. SPOT utilizes the Design Optimization Tools (DOT) program for the optimization techniques. The SPOT program is divided into a main program and five modules: aerodynamic losses, orbital parameters, liquid engines, solid engines, and nozzles. The program is designed to be upgraded easily and expanded to meet specific user needs. A user's manual and a programmer's manual are currently being developed to facilitate implementation and modification.
Event valence and unrealistic optimism.
Gold, Ron S; Martyn, Kate
2003-06-01
The effect of event valence on unrealistic optimism was studied. 94 Deakin University students rated the comparative likelihood that they would experience either a controllable or an uncontrollable health-related event. Valence was manipulated to be positive (outcome was desirable) or negative (outcome was undesirable) by varying the way a given event was framed. Participants either were told the conditions which promote the event and rated the comparative likelihood they would experience it or were told the conditions which prevent the event and rated the comparative likelihood they would avoid it. For both the controllable and the uncontrollable events, unrealistic optimism was greater for negative than positive valence. It is suggested that a combination of the 'motivational account' of unrealistic optimism and prospect theory provides a good explanation of the results.
Business process optimization for RHIOs.
Soti, Praveen; Pandey, Seema
2007-01-01
Implementation of an electronic health record (EHR) network entails significant changes in the business processes of participating organizations. Business process management, increased automation, process optimization, user training and end-user adoption together form the keys to success with an EHR. Redesigned processes should be mapped to benefit lines and performance indicators, and monitored continuously to identify improvement opportunities. It is important the new business work flows should match, if not exceed, the existing benchmarks for performance. Business process redesign is all the more challenging in the context of regional health information organizations (RHIOs), as the business processes of the EHR network have to be aligned with existing process flows of several organizations, each with its own preferences and specific requirements. Even so, most of the discrete individual processes have to be converged, streamlined, assimilated and optimized in the redesigned business processes. This paper proposes a methodology for business process redesign and optimization for RHIOs.
Optimizing Stellarators for Turbulent Transport
H.E. Mynick, N.Pomphrey, and P. Xanthopoulos
2010-05-27
Up to now, the term "transport-optimized" stellarators has meant optimized to minimize neoclassical transport, while the task of also mitigating turbulent transport, usually the dominant transport channel in such designs, has not been addressed, due to the complexity of plasma turbulence in stellarators. Here, we demonstrate that stellarators can also be designed to mitigate their turbulent transport, by making use of two powerful numerical tools not available until recently, namely gyrokinetic codes valid for 3D nonlinear simulations, and stellarator optimization codes. A first proof-of-principle configuration is obtained, reducing the level of ion temperature gradient turbulent transport from the NCSX baseline design by a factor of about 2.5.
Robust Portfolio Optimization Using Pseudodistances.
Toma, Aida; Leoni-Aubin, Samuela
2015-01-01
The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature.
Optimization of polarization lidar structure
NASA Astrophysics Data System (ADS)
Abramochkin, Alexander I.; Kaul, Bruno V.; Tikhomirov, Alexander A.
1999-11-01
The problems of the polarization lidar transceiver optimization are considered. The basic features and the optimization criteria of lidar polarization units are presented and the comparative analysis of polarization units is fulfilled. We have analyzed optical arrangements of the transmitter to form the desired polarization state of sounding radiation. We have also considered various types of lidar receiving systems: (1) one-channel, providing measurement of Stocks parameters at a successive change of position of polarization analyzers in the lidar receiver, and (2) multichannel, where each channel has a lens, an analyzer, and a photodetector. In the latter case measurements of Stocks parameters are carried out simultaneously. The optimization criteria of the polarization lidar considering the atmospheric state are determined with the purpose to decrease the number of polarization devices needed.