Numerical Nonlinear Robust Control with Applications to Humanoid Robots

DTIC Science & Technology

2015-07-01

automatically. While optimization and optimal control theory have been widely applied in humanoid robot control, it is not without drawbacks . A blind... drawback of Galerkin-based approaches is the need to successively produce discrete forms, which is difficult to implement in practice. Related...universal function approx- imation ability, these approaches are not without drawbacks . In practice, while a single hidden layer neural network can

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

Zhou, S; Fan, Q; Lei, Y

Purpose: In-Water-Output-Ratio (IWOR) plays a significant role in linac-based radiotherapy treatment planning, linking MUs to delivered radiation dose. For an open rectangular field, IWOR depends on both its width and length, and changes rapidly when one of them becomes small. In this study, a universal functional form is proposed to fit the open field IWOR tables in Varian TrueBeam representative datasets for all photon energies. Methods: A novel Generalized Mean formula is first used to estimate the Equivalent Square (ES) for a rectangular field. The formula’s weighting factor and power index are determined by collapsing all data points as muchmore » as possible onto a single curve in IWOR vs. ES plot. The result is then fitted with a novel universal function IWOR=1+b*Log(ES/10cm)/(ES/10cm)^c via a least-square procedure to determine the optimal values for parameters b and c. The maximum relative residual error in IWOR over the entire two-dimensional measurement table with field sizes between 3cm and 40cm is used to evaluate the quality of fit for the function. Results: The two-step fitting strategy works very well in determining the optimal parameter values for open field IWOR of each photon energies in the Varian data-set. Relative residual error ≤0.71% is achieved for all photon energies (including Flattening-Filter-Free modes) with field sizes between 3cm and 40cm. The optimal parameter values change smoothly with regular photon beam quality. Conclusion: The universal functional form fits the Varian TrueBeam open field IWOR measurement tables accurately with small relative residual errors for all photon energies. Therefore, it can be an excellent choice to represent IWOR in absolute dose and MU calculations. The functional form can also be used as a QA/commissioning tool to verify the measured data quality and consistency by checking the IWOR data behavior against the function for new photon energies with arbitrary beam quality.« less

Improvement of the System of Training of Specialists by University for Coal Mining Enterprises

NASA Astrophysics Data System (ADS)

Mikhalchenko, Vadim; Seredkina, Irina

2017-11-01

In the article the ingenious technique of the Quality Function Deployment with reference to the process of training of specialists with higher education by university is considered. The method is based on the step-by-step conversion of customer requirements into specific organizational, meaningful and functional transformations of the technological process of the university. A fully deployed quality function includes four stages of tracking customer requirements while creating a product: product planning and design, process design, production design. The Quality Function Deployment can be considered as one of the methods for optimizing the technological processes of training of specialists with higher education in the current economic conditions. Implemented at the initial stages of the life cycle of the technological process, it ensures not only the high quality of the "product" of graduate school, but also the fullest possible satisfaction of consumer's requests and expectations.

Analysis of technical university information system

NASA Astrophysics Data System (ADS)

Savelyev, N. A.; Boyarkin, M. A.

2018-05-01

The paper covers a set and interaction of the existing higher education institution automated control systems in φ state budgetary educational institution of higher professional education "Industrial University of Tyumen ". A structural interaction of the existing systems and their functions has been analyzed which has become a basis for identification of a number of system-related and local (related to separate modules) drawbacks of the university activities automation. The authors suggested a new structure of the automated control system, consisting of three major subsystems: management support; training and methodology support; distance and supplementary education support. Functionality for each subsystem has been defined in accordance with the educational institution automation requirements. The suggested structure of the ACS will solve the challenges facing the university during reorganization and optimization of the processes of management of the institution activities as a whole.

The Myth of Optimality in Clinical Neuroscience.

PubMed

Holmes, Avram J; Patrick, Lauren M

2018-03-01

Clear evidence supports a dimensional view of psychiatric illness. Within this framework the expression of disorder-relevant phenotypes is often interpreted as a breakdown or departure from normal brain function. Conversely, health is reified, conceptualized as possessing a single ideal state. We challenge this concept here, arguing that there is no universally optimal profile of brain functioning. The evolutionary forces that shape our species select for a staggering diversity of human behaviors. To support our position we highlight pervasive population-level variability within large-scale functional networks and discrete circuits. We propose that, instead of examining behaviors in isolation, psychiatric illnesses can be best understood through the study of domains of functioning and associated multivariate patterns of variation across distributed brain systems. Copyright © 2018 Elsevier Ltd. All rights reserved.

PREFACE: 10th Joint Conference on Chemistry

NASA Astrophysics Data System (ADS)

2016-02-01

The 10th Joint Conference on Chemistry is an international conference organized by 4 chemistry departments of 4 universities in central Java, Indonesia. The universities are Sebelas Maret University, Diponegoro University, Semarang State University and Soedirman University. The venue was at Solo, Indonesia, at September 8-9, 2015. The total conference participants are 133 including the invited speakers. The conference emphasized the multidisciplinary chemical issue and impact of today's sustainable chemistry which covering the following topics: • Material innovation for sustainable goals • Development of renewable and sustainable energy based on chemistry • New drug design, experimental and theoretical methods • Green synthesis and characterization of material (from molecule to functionalized materials) • Catalysis as core technology in industry • Natural product isolation and optimization

Coprocessors for quantum devices

NASA Astrophysics Data System (ADS)

Kay, Alastair

2018-03-01

Quantum devices, from simple fixed-function tools to the ultimate goal of a universal quantum computer, will require high-quality, frequent repetition of a small set of core operations, such as the preparation of entangled states. These tasks are perfectly suited to realization by a coprocessor or supplementary instruction set, as is common practice in modern CPUs. In this paper, we present two quintessentially quantum coprocessor functions: production of a Greenberger-Horne-Zeilinger state and implementation of optimal universal (asymmetric) quantum cloning. Both are based on the evolution of a fixed Hamiltonian. We introduce a technique for deriving the parameters of these Hamiltonians based on the numerical integration of Toda-like flows.

One-dimensional Euclidean matching problem: exact solutions, correlation functions, and universality.

PubMed

Caracciolo, Sergio; Sicuro, Gabriele

2014-10-01

We discuss the equivalence relation between the Euclidean bipartite matching problem on the line and on the circumference and the Brownian bridge process on the same domains. The equivalence allows us to compute the correlation function and the optimal cost of the original combinatorial problem in the thermodynamic limit; moreover, we solve also the minimax problem on the line and on the circumference. The properties of the average cost and correlation functions are discussed.

[Survival strategy of photosynthetic organisms. 1. Variability of the extent of light-harvesting pigment aggregation as a structural factor optimizing the function of oligomeric photosynthetic antenna. Model calculations].

PubMed

Fetisova, Z G

2004-01-01

In accordance with our concept of rigorous optimization of photosynthetic machinery by a functional criterion, this series of papers continues purposeful search in natural photosynthetic units (PSU) for the basic principles of their organization that we predicted theoretically for optimal model light-harvesting systems. This approach allowed us to determine the basic principles for the organization of a PSU of any fixed size. This series of papers deals with the problem of structural optimization of light-harvesting antenna of variable size controlled in vivo by the light intensity during the growth of organisms, which accentuates the problem of antenna structure optimization because optimization requirements become more stringent as the PSU increases in size. In this work, using mathematical modeling for the functioning of natural PSUs, we have shown that the aggregation of pigments of model light-harvesting antenna, being one of universal optimizing factors, furthermore allows controlling the antenna efficiency if the extent of pigment aggregation is a variable parameter. In this case, the efficiency of antenna increases with the size of the elementary antenna aggregate, thus ensuring the high efficiency of the PSU irrespective of its size; i.e., variation in the extent of pigment aggregation controlled by the size of light-harvesting antenna is biologically expedient.

Estimating Optimal Transformations for Multiple Regression and Correlation.

DTIC Science & Technology

1982-07-01

algorithm; we minimize (2.4) e2 (,,, ...,) = E[e(Y) - 1I (X 2 j=l j 2holding EO =1, E6 = E0, =.-. =Ecp = 0, through a series of single function minimizations...X, x = INU = lIVe . Then (5.16) THEOREM. If 6*, p* is an optimal transformation for regression, then = ue*o Conversely, if e satisfies Xe = U6, Nll1...Stanford University, Tech. Report ORIONOO6. Gasser, T. and Rosenblatt, M. (eds.) (1979). Smoothing Techniques for Curve Estimation, in Lecture Notes in

Functional Recovery in Major Depressive Disorder: Providing Early Optimal Treatment for the Individual Patient.

PubMed

Oluboka, Oloruntoba J; Katzman, Martin A; Habert, Jeffrey; McIntosh, Diane; MacQueen, Glenda M; Milev, Roumen V; McIntyre, Roger S; Blier, Pierre

2018-02-01

Major depressive disorder is an often chronic and recurring illness. Left untreated, major depressive disorder may result in progressive alterations in brain morphometry and circuit function. Recent findings, however, suggest that pharmacotherapy may halt and possibly reverse those effects. These findings, together with evidence that a delay in treatment is associated with poorer clinical outcomes, underscore the urgency of rapidly treating depression to full recovery. Early optimized treatment, using measurement-based care and customizing treatment to the individual patient, may afford the best possible outcomes for each patient. The aim of this article is to present recommendations for using a patient-centered approach to rapidly provide optimal pharmacological treatment to patients with major depressive disorder. Offering major depressive disorder treatment determined by individual patient characteristics (e.g., predominant symptoms, medical history, comorbidities), patient preferences and expectations, and, critically, their own definition of wellness provides the best opportunity for full functional recovery. © The Author(s) 2017. Published by Oxford University Press on behalf of CINP.

A Universal Rank-Size Law

PubMed Central

2016-01-01

A mere hyperbolic law, like the Zipf’s law power function, is often inadequate to describe rank-size relationships. An alternative theoretical distribution is proposed based on theoretical physics arguments starting from the Yule-Simon distribution. A modeling is proposed leading to a universal form. A theoretical suggestion for the “best (or optimal) distribution”, is provided through an entropy argument. The ranking of areas through the number of cities in various countries and some sport competition ranking serves for the present illustrations. PMID:27812192

Robert's Rules for Optimal Learning: Model Development, Field Testing, Implications!

ERIC Educational Resources Information Center

McGinty, Robert L.

The value of accelerated learning techniques developed by the national organization for Suggestive Accelerated Learning Techniques (SALT) was tested in a study using Administrative Policy students taking the capstone course in the Eastern Washington University School of Business. Educators have linked the brain and how it functions to various…

Utilization of Renewable Energy to Meet New National Challenges in Energy and Climate Change

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

Momoh, James A.

The project aims to design a microgrid system to promote utilization of renewable energy resources such as wind and solar to address the national challenges in energy and climate change. Different optimization techniques and simulation software are used to study the performance of the renewable energy system under study. A series of research works performed under the grant Department of Energy (DOE) is presented. This grant opportunity affords Howard faculty, students, graduates, undergraduates, K-12, postdocs and visiting scholars to benefit state of the art research work. The research work has led to improve or advance understanding of new hardware technologies,more » software development and engineering optimization methods necessary and sufficient for handling probabilistic models and real-time computation and functions necessary for development of microgrid system. Consistent with State of Project Objective Howard University has partitioned the task into the following integrated activities: 1. Stochastic Model for RER and Load • Development of modeling Renewable Energy Resources (RER) and load which is used to perform distribution power flow study which leads to publication in refereed journals and conferences. The work was also published at the IEEE conference. 2. Stochastic optimization for voltage/Var • The development of voltage VAr optimization based on a review of existing knowledge in optimization led to the use of stochastic program and evolution of programming optimization method for V/VAr optimization. Papers were presented at the North America Power Systems Conference and the IEEE PES general meeting. 3. Modeling RER and Storage • Extending the concept of optimization method an RER with storage, such as the development of microgrid V/VAr and storage is performed. Several papers were published at the North America Power Systems Conference and the IEEE PES general meeting. 4. Power Game • Development of power game experiment using Labvolt to allow for hands on understanding of design and development of microgrid functions is performed. Publication were done by students at the end of their summer program. 5. Designing Microgrid Testbed • Example microgrid test bed is developed. In addition, function of the test bed are developed. The papers were presented at the North America Power Systems Conference and the IEEE general meeting. 6. Outreach Program • From the outreach program, topics from the project have been included in the revision of courses at Howard University, new book called Energy Processing and Smartgrid has being developed. • Hosted masters students from University of Denver to complete their projects with us. • Hosted high school students for early exposure for careers in STEM • Representations made in IEEE conferences to share the lessons learned in the use of micro grid to expose students to STEM education and research.« less

Understanding levels of best practice: An empirical validation.

PubMed

Phan, Huy P; Ngu, Bing H; Wang, Hui-Wen; Shih, Jen-Hwa; Shi, Sheng-Ying; Lin, Ruey-Yih

2018-01-01

Recent research has explored the nature of the theoretical concept of optimal best practice, which emphasizes the importance of personal resolve, inner strength, and the maximization of a person's development, whether it is mental, cognitive, social, or physical. In the context of academia, the study of optimal functioning places emphasis on a student's effort expenditure, positive outlook, and determination to strive for educational success and enriched subjective well-being. One major inquiry closely associated with optimal functioning is the process of optimization. Optimization, in brief, delves into the enactment of different psychological variables that could improve a person's internal state of functioning (e.g., cognitive functioning). From a social sciences point of view, very little empirical evidence exists to affirm and explain a person's achievement of optimal best practice. Over the past five years, we have made extensive progress in the area of optimal best practice by developing different quantitative measures to assess and evaluate the importance of this theoretical concept. The present study, which we collaborated with colleagues in Taiwan, involved the use of structural equation modeling (SEM) to analyze a cohort of Taiwanese university students' (N = 1010) responses to a series of Likert-scale measures that focused on three major entities: (i) the importance of optimal best practice, (ii) three major psychological variables (i.e., effective functioning, personal resolve, and emotional functioning) that could optimize student' optimal best levels in academic learning, and (iii) three comparable educational outcomes (i.e., motivation towards academic learning, interest in academic learning, and academic liking experience) that could positively associate with optimal best practice and the three mentioned psychological variables. Findings that we obtained, overall, fully supported our initial a priori model. This evidence, in its totality, has made substantive practical, theoretical, and methodological contributions. Foremost, from our point of view, is clarity into the psychological process of optimal best practice in the context of schooling. For example, in relation to subjective well-being experiences, how can educators optimize students' positive emotions? More importantly, aside from practical relevance, our affirmed research inquiry has produced insightful information for further advancement. One distinction, in this case, entails consideration of a more complex methodological design that could measure, assess, and evaluate the impact of optimization.

Understanding levels of best practice: An empirical validation

PubMed Central

Wang, Hui-Wen; Shih, Jen-Hwa; Shi, Sheng-Ying; Lin, Ruey-Yih

2018-01-01

Recent research has explored the nature of the theoretical concept of optimal best practice, which emphasizes the importance of personal resolve, inner strength, and the maximization of a person’s development, whether it is mental, cognitive, social, or physical. In the context of academia, the study of optimal functioning places emphasis on a student’s effort expenditure, positive outlook, and determination to strive for educational success and enriched subjective well-being. One major inquiry closely associated with optimal functioning is the process of optimization. Optimization, in brief, delves into the enactment of different psychological variables that could improve a person’s internal state of functioning (e.g., cognitive functioning). From a social sciences point of view, very little empirical evidence exists to affirm and explain a person’s achievement of optimal best practice. Over the past five years, we have made extensive progress in the area of optimal best practice by developing different quantitative measures to assess and evaluate the importance of this theoretical concept. The present study, which we collaborated with colleagues in Taiwan, involved the use of structural equation modeling (SEM) to analyze a cohort of Taiwanese university students’ (N = 1010) responses to a series of Likert-scale measures that focused on three major entities: (i) the importance of optimal best practice, (ii) three major psychological variables (i.e., effective functioning, personal resolve, and emotional functioning) that could optimize student’ optimal best levels in academic learning, and (iii) three comparable educational outcomes (i.e., motivation towards academic learning, interest in academic learning, and academic liking experience) that could positively associate with optimal best practice and the three mentioned psychological variables. Findings that we obtained, overall, fully supported our initial a priori model. This evidence, in its totality, has made substantive practical, theoretical, and methodological contributions. Foremost, from our point of view, is clarity into the psychological process of optimal best practice in the context of schooling. For example, in relation to subjective well-being experiences, how can educators optimize students’ positive emotions? More importantly, aside from practical relevance, our affirmed research inquiry has produced insightful information for further advancement. One distinction, in this case, entails consideration of a more complex methodological design that could measure, assess, and evaluate the impact of optimization. PMID:29902278

A trajectory planning scheme for spacecraft in the space station environment. M.S. Thesis - University of California

NASA Technical Reports Server (NTRS)

Soller, Jeffrey Alan; Grunwald, Arthur J.; Ellis, Stephen R.

1991-01-01

Simulated annealing is used to solve a minimum fuel trajectory problem in the space station environment. The environment is special because the space station will define a multivehicle environment in space. The optimization surface is a complex nonlinear function of the initial conditions of the chase and target crafts. Small permutations in the input conditions can result in abrupt changes to the optimization surface. Since no prior knowledge about the number or location of local minima on the surface is available, the optimization must be capable of functioning on a multimodal surface. It was reported in the literature that the simulated annealing algorithm is more effective on such surfaces than descent techniques using random starting points. The simulated annealing optimization was found to be capable of identifying a minimum fuel, two-burn trajectory subject to four constraints which are integrated into the optimization using a barrier method. The computations required to solve the optimization are fast enough that missions could be planned on board the space station. Potential applications for on board planning of missions are numerous. Future research topics may include optimal planning of multi-waypoint maneuvers using a knowledge base to guide the optimization, and a study aimed at developing robust annealing schedules for potential on board missions.

System Design under Uncertainty: Evolutionary Optimization of the Gravity Probe-B Spacecraft

NASA Technical Reports Server (NTRS)

Pullen, Samuel P.; Parkinson, Bradford W.

1994-01-01

This paper discusses the application of evolutionary random-search algorithms (Simulated Annealing and Genetic Algorithms) to the problem of spacecraft design under performance uncertainty. Traditionally, spacecraft performance uncertainty has been measured by reliability. Published algorithms for reliability optimization are seldom used in practice because they oversimplify reality. The algorithm developed here uses random-search optimization to allow us to model the problem more realistically. Monte Carlo simulations are used to evaluate the objective function for each trial design solution. These methods have been applied to the Gravity Probe-B (GP-B) spacecraft being developed at Stanford University for launch in 1999, Results of the algorithm developed here for GP-13 are shown, and their implications for design optimization by evolutionary algorithms are discussed.

Is there an optimal level of open-endedness in prebiotic evolution?

PubMed

Markovitch, Omer; Sorek, Daniel; Lui, Leong Ting; Lancet, Doron; Krasnogor, Natalio

2012-10-01

In this paper we explore the question of whether there is an optimal set up for a putative prebiotic system leading to open-ended evolution (OEE) of the events unfolding within this system. We do so by proposing two key innovations. First, we introduce a new index that measures OEE as a function of the likelihood of events unfolding within a universe given its initial conditions. Next, we apply this index to a variant of the graded autocatalysis replication domain (GARD) model, Segre et al. (P Natl Acad Sci USA 97(8):4112-4117, 2000; Markovitch and Lancet Artif Life 18(3), 2012), and use it to study--under a unified and concise prebiotic evolutionary framework--both a variety of initial conditions of the universe and the OEE of species that evolve from them.

Is There an Optimal Level of Open-Endedness in Prebiotic Evolution?

NASA Astrophysics Data System (ADS)

Markovitch, Omer; Sorek, Daniel; Lui, Leong Ting; Lancet, Doron; Krasnogor, Natalio

2012-10-01

In this paper we explore the question of whether there is an optimal set up for a putative prebiotic system leading to open-ended evolution (OEE) of the events unfolding within this system. We do so by proposing two key innovations. First, we introduce a new index that measures OEE as a function of the likelihood of events unfolding within a universe given its initial conditions. Next, we apply this index to a variant of the graded autocatalysis replication domain (GARD) model, Segre et al. (P Natl Acad Sci USA 97(8):4112-4117, 2000; Markovitch and Lancet Artif Life 18(3), 2012), and use it to study - under a unified and concise prebiotic evolutionary framework - both a variety of initial conditions of the universe and the OEE of species that evolve from them.

Optimal Universal Uncertainty Relations

PubMed Central

Li, Tao; Xiao, Yunlong; Ma, Teng; Fei, Shao-Ming; Jing, Naihuan; Li-Jost, Xianqing; Wang, Zhi-Xi

2016-01-01

We study universal uncertainty relations and present a method called joint probability distribution diagram to improve the majorization bounds constructed independently in [Phys. Rev. Lett. 111, 230401 (2013)] and [J. Phys. A. 46, 272002 (2013)]. The results give rise to state independent uncertainty relations satisfied by any nonnegative Schur-concave functions. On the other hand, a remarkable recent result of entropic uncertainty relation is the direct-sum majorization relation. In this paper, we illustrate our bounds by showing how they provide a complement to that in [Phys. Rev. A. 89, 052115 (2014)]. PMID:27775010

QAPgrid: A Two Level QAP-Based Approach for Large-Scale Data Analysis and Visualization

PubMed Central

Inostroza-Ponta, Mario; Berretta, Regina; Moscato, Pablo

2011-01-01

Background The visualization of large volumes of data is a computationally challenging task that often promises rewarding new insights. There is great potential in the application of new algorithms and models from combinatorial optimisation. Datasets often contain “hidden regularities” and a combined identification and visualization method should reveal these structures and present them in a way that helps analysis. While several methodologies exist, including those that use non-linear optimization algorithms, severe limitations exist even when working with only a few hundred objects. Methodology/Principal Findings We present a new data visualization approach (QAPgrid) that reveals patterns of similarities and differences in large datasets of objects for which a similarity measure can be computed. Objects are assigned to positions on an underlying square grid in a two-dimensional space. We use the Quadratic Assignment Problem (QAP) as a mathematical model to provide an objective function for assignment of objects to positions on the grid. We employ a Memetic Algorithm (a powerful metaheuristic) to tackle the large instances of this NP-hard combinatorial optimization problem, and we show its performance on the visualization of real data sets. Conclusions/Significance Overall, the results show that QAPgrid algorithm is able to produce a layout that represents the relationships between objects in the data set. Furthermore, it also represents the relationships between clusters that are feed into the algorithm. We apply the QAPgrid on the 84 Indo-European languages instance, producing a near-optimal layout. Next, we produce a layout of 470 world universities with an observed high degree of correlation with the score used by the Academic Ranking of World Universities compiled in the The Shanghai Jiao Tong University Academic Ranking of World Universities without the need of an ad hoc weighting of attributes. Finally, our Gene Ontology-based study on Saccharomyces cerevisiae fully demonstrates the scalability and precision of our method as a novel alternative tool for functional genomics. PMID:21267077

QAPgrid: a two level QAP-based approach for large-scale data analysis and visualization.

PubMed

Inostroza-Ponta, Mario; Berretta, Regina; Moscato, Pablo

2011-01-18

The visualization of large volumes of data is a computationally challenging task that often promises rewarding new insights. There is great potential in the application of new algorithms and models from combinatorial optimisation. Datasets often contain "hidden regularities" and a combined identification and visualization method should reveal these structures and present them in a way that helps analysis. While several methodologies exist, including those that use non-linear optimization algorithms, severe limitations exist even when working with only a few hundred objects. We present a new data visualization approach (QAPgrid) that reveals patterns of similarities and differences in large datasets of objects for which a similarity measure can be computed. Objects are assigned to positions on an underlying square grid in a two-dimensional space. We use the Quadratic Assignment Problem (QAP) as a mathematical model to provide an objective function for assignment of objects to positions on the grid. We employ a Memetic Algorithm (a powerful metaheuristic) to tackle the large instances of this NP-hard combinatorial optimization problem, and we show its performance on the visualization of real data sets. Overall, the results show that QAPgrid algorithm is able to produce a layout that represents the relationships between objects in the data set. Furthermore, it also represents the relationships between clusters that are feed into the algorithm. We apply the QAPgrid on the 84 Indo-European languages instance, producing a near-optimal layout. Next, we produce a layout of 470 world universities with an observed high degree of correlation with the score used by the Academic Ranking of World Universities compiled in the The Shanghai Jiao Tong University Academic Ranking of World Universities without the need of an ad hoc weighting of attributes. Finally, our Gene Ontology-based study on Saccharomyces cerevisiae fully demonstrates the scalability and precision of our method as a novel alternative tool for functional genomics.

Universal Critical Dynamics in High Resolution Neuronal Avalanche Data

NASA Astrophysics Data System (ADS)

Friedman, Nir; Ito, Shinya; Brinkman, Braden A. W.; Shimono, Masanori; DeVille, R. E. Lee; Dahmen, Karin A.; Beggs, John M.; Butler, Thomas C.

2012-05-01

The tasks of neural computation are remarkably diverse. To function optimally, neuronal networks have been hypothesized to operate near a nonequilibrium critical point. However, experimental evidence for critical dynamics has been inconclusive. Here, we show that the dynamics of cultured cortical networks are critical. We analyze neuronal network data collected at the individual neuron level using the framework of nonequilibrium phase transitions. Among the most striking predictions confirmed is that the mean temporal profiles of avalanches of widely varying durations are quantitatively described by a single universal scaling function. We also show that the data have three additional features predicted by critical phenomena: approximate power law distributions of avalanche sizes and durations, samples in subcritical and supercritical phases, and scaling laws between anomalous exponents.

A Cross-Cultural Study Testing the Universality of Basic Psychological Needs Theory across Different Academic Subjects

ERIC Educational Resources Information Center

Erturan-Ilker, Gökçe; Quested, Eleanor; Appleton, Paul; Duda, Joan L.

2018-01-01

Basic Psychological Needs Theory (BPNT) suggests that autonomy-supportive teachers can promote the satisfaction of students' three basic psychological needs (i.e., the need for autonomy, competence, and relatedness) and this is essential for optimal functioning and personal well-being. The role of need satisfaction as a determinant of well-being…

Self-transcending meditation is good for mental health: why this should be the case.

PubMed

Hankey, Alex; Shetkar, Rashmi

2016-06-01

A simple theory of health has recently been proposed: while poor quality regulation corresponds to poor quality health so that improving regulation should improve health, optimal regulation optimizes function and optimizes health. Examining the term 'optimal regulation' in biological systems leads to a straightforward definition in terms of 'criticality' in complexity biology, a concept that seems to apply universally throughout biology. Criticality maximizes information processing and sensitivity of response to external stimuli, and for these reasons may be held to optimize regulation. In this way a definition of health has been given in terms of regulation, a scientific concept, which ties into detailed properties of complex systems, including brain cortices, and mental health. Models of experience and meditation built on complexity also point to criticality: it represents the condition making self-awareness possible, and is strengthened by meditation practices leading to the state of pure consciousness-the content-free state of mind in deep meditation. From this it follows that healthy function of the brain cortex, its sensitivity,y and consistency of response to external challenges should improve by practicing techniques leading to content-free awareness-transcending the original focus introduced during practice. Evidence for this is reviewed.

Information filtering via a scaling-based function.

PubMed

Qiu, Tian; Zhang, Zi-Ke; Chen, Guang

2013-01-01

Finding a universal description of the algorithm optimization is one of the key challenges in personalized recommendation. In this article, for the first time, we introduce a scaling-based algorithm (SCL) independent of recommendation list length based on a hybrid algorithm of heat conduction and mass diffusion, by finding out the scaling function for the tunable parameter and object average degree. The optimal value of the tunable parameter can be abstracted from the scaling function, which is heterogeneous for the individual object. Experimental results obtained from three real datasets, Netflix, MovieLens and RYM, show that the SCL is highly accurate in recommendation. More importantly, compared with a number of excellent algorithms, including the mass diffusion method, the original hybrid method, and even an improved version of the hybrid method, the SCL algorithm remarkably promotes the personalized recommendation in three other aspects: solving the accuracy-diversity dilemma, presenting a high novelty, and solving the key challenge of cold start problem.

Implementing a quantum cloning machine in separate cavities via the optical coherent pulse as a quantum communication bus

NASA Astrophysics Data System (ADS)

Zhu, Meng-Zheng; Ye, Liu

2015-04-01

An efficient scheme is proposed to implement a quantum cloning machine in separate cavities based on a hybrid interaction between electron-spin systems placed in the cavities and an optical coherent pulse. The coefficient of the output state for the present cloning machine is just the direct product of two trigonometric functions, which ensures that different types of quantum cloning machine can be achieved readily in the same framework by appropriately adjusting the rotated angles. The present scheme can implement optimal one-to-two symmetric (asymmetric) universal quantum cloning, optimal symmetric (asymmetric) phase-covariant cloning, optimal symmetric (asymmetric) real-state cloning, optimal one-to-three symmetric economical real-state cloning, and optimal symmetric cloning of qubits given by an arbitrary axisymmetric distribution. In addition, photon loss of the qubus beams during the transmission and decoherence effects caused by such a photon loss are investigated.

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

PubMed

Pechmann, Sebastian; Frydman, Judith

2013-02-01

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

Update on the Management of Thyroid Disease during Pregnancy.

PubMed

Yim, Chang Hoon

2016-09-01

Thyroid dysfunction during pregnancy can result in serious complications for both the mother and infant; however, these complications can be prevented by optimal treatment of maternal overt thyroid dysfunction. Although several studies have demonstrated that maternal subclinical hypothyroidism is associated with obstetric complications and neurocognitive impairments in offspring, there is limited evidence that levothyroxine treatment can improve these complications. Therefore, most professional societies do not recommend universal screening for thyroid dysfunction during pregnancy, and instead recommend a case-finding approach in which only high-risk women are tested. However, recent studies have estimated that targeted thyroid function testing misses approximately 30% to 55% of hypothyroidism cases in pregnant women, and some associations and researchers have recommended universal screening of pregnant women to facilitate the early detection and treatment of overt hypothyroidism. This review summarizes recent data on thyroid function test changes, thyroid functional disorder management, and thyroid screening during pregnancy.

A universal Model-R Coupler to facilitate the use of R functions for model calibration and analysis

USGS Publications Warehouse

Wu, Yiping; Liu, Shuguang; Yan, Wende

2014-01-01

Mathematical models are useful in various fields of science and engineering. However, it is a challenge to make a model utilize the open and growing functions (e.g., model inversion) on the R platform due to the requirement of accessing and revising the model's source code. To overcome this barrier, we developed a universal tool that aims to convert a model developed in any computer language to an R function using the template and instruction concept of the Parameter ESTimation program (PEST) and the operational structure of the R-Soil and Water Assessment Tool (R-SWAT). The developed tool (Model-R Coupler) is promising because users of any model can connect an external algorithm (written in R) with their model to implement various model behavior analyses (e.g., parameter optimization, sensitivity and uncertainty analysis, performance evaluation, and visualization) without accessing or modifying the model's source code.

Quantum Monte Carlo calculations of NiO

NASA Astrophysics Data System (ADS)

Maezono, Ryo; Towler, Mike D.; Needs, Richard. J.

2008-03-01

We describe variational and diffusion quantum Monte Carlo (VMC and DMC) calculations [1] of NiO using a 1024-electron simulation cell. We have used a smooth, norm-conserving, Dirac-Fock pseudopotential [2] in our work. Our trial wave functions were of Slater-Jastrow form, containing orbitals generated in Gaussian-basis UHF periodic calculations. Jastrow factor is optimized using variance minimization with optimized cutoff lengths using the same scheme as our previous work. [4] We apply the lattice regulated scheme [5] to evaluate non-local pseudopotentials in DMC and find the scheme improves the smoothness of the energy-volume curve. [1] CASINO ver.2.1 User Manual, University of Cambridge (2007). [2] J.R. Trail et.al., J. Chem. Phys. 122, 014112 (2005). [3] CRYSTAL98 User's Manual, University of Torino (1998). [4] Ryo Maezono et.al., Phys. Rev. Lett., 98, 025701 (2007). [5] Michele Casula, Phys. Rev. B 74, 161102R (2006).

Determining Optimal Nursing Resources in Relation to Functions During the Oulu University Hospital Nurse Staffing Management Project.

PubMed

Liljamo, Pia; Lavander, Päivi; Kejonen, Pirjo

2016-01-01

The Oulu University Hospital's staffing management project sought information on the number of nursing staff in relation to treatment days and visits, using existing indicators to describe the activities involved. The retrospective data obtained was compared to human resources and the personnel structure. On this basis an optimal number of staff was determined for the units, taking account of a range of explanatory indicator data. The project made use of the computational model for nurse staffing and the World Health Organisation's (WHO) Workload Indicators of Staffing Need (WISN) method. The project provided extensive information on human resources issues within the units. Its results indicated the differences between wards with respect to the number and structure of resources. In addition, the nurse administrators lacked skills in gathering and using data from administrative datasets. This information will provide support for the further development of nursing operations and nursing management decision-making.

Codon usage regulates protein structure and function by affecting translation elongation speed in Drosophila cells.

PubMed

Zhao, Fangzhou; Yu, Chien-Hung; Liu, Yi

2017-08-21

Codon usage biases are found in all eukaryotic and prokaryotic genomes and have been proposed to regulate different aspects of translation process. Codon optimality has been shown to regulate translation elongation speed in fungal systems, but its effect on translation elongation speed in animal systems is not clear. In this study, we used a Drosophila cell-free translation system to directly compare the velocity of mRNA translation elongation. Our results demonstrate that optimal synonymous codons speed up translation elongation while non-optimal codons slow down translation. In addition, codon usage regulates ribosome movement and stalling on mRNA during translation. Finally, we show that codon usage affects protein structure and function in vitro and in Drosophila cells. Together, these results suggest that the effect of codon usage on translation elongation speed is a conserved mechanism from fungi to animals that can affect protein folding in eukaryotic organisms. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Optimal linear reconstruction of dark matter from halo catalogues

DOE PAGES

Cai, Yan -Chuan; Bernstein, Gary; Sheth, Ravi K.

2011-04-01

The dark matter lumps (or "halos") that contain galaxies have locations in the Universe that are to some extent random with respect to the overall matter distributions. We investigate how best to estimate the total matter distribution from the locations of the halos. We derive the weight function w(M) to apply to dark-matter haloes that minimizes the stochasticity between the weighted halo distribution and its underlying mass density field. The optimal w(M) depends on the range of masses of halos being used. While the standard biased-Poisson model of the halo distribution predicts that bias weighting is optimal, the simple factmore » that the mass is comprised of haloes implies that the optimal w(M) will be a mixture of mass-weighting and bias-weighting. In N-body simulations, the Poisson estimator is up to 15× noisier than the optimal. Optimal weighting could make cosmological tests based on the matter power spectrum or cross-correlations much more powerful and/or cost effective.« less

Zone-boundary optimization for direct laser writing of continuous-relief diffractive optical elements.

PubMed

Korolkov, Victor P; Nasyrov, Ruslan K; Shimansky, Ruslan V

2006-01-01

Enhancing the diffraction efficiency of continuous-relief diffractive optical elements fabricated by direct laser writing is discussed. A new method of zone-boundary optimization is proposed to correct exposure data only in narrow areas along the boundaries of diffractive zones. The optimization decreases the loss of diffraction efficiency related to convolution of a desired phase profile with a writing-beam intensity distribution. A simplified stepped transition function that describes optimized exposure data near zone boundaries can be made universal for a wide range of zone periods. The approach permits a similar increase in the diffraction efficiency as an individual-pixel optimization but with fewer computation efforts. Computer simulations demonstrated that the zone-boundary optimization for a 6 microm period grating increases the efficiency by 7% and 14.5% for 0.6 microm and 1.65 microm writing-spot diameters, respectively. The diffraction efficiency of as much as 65%-90% for 4-10 microm zone periods was obtained experimentally with this method.

Optimism and the brain: trait optimism mediates the protective role of the orbitofrontal cortex gray matter volume against anxiety.

PubMed

Dolcos, Sanda; Hu, Yifan; Iordan, Alexandru D; Moore, Matthew; Dolcos, Florin

2016-02-01

Converging evidence identifies trait optimism and the orbitofrontal cortex (OFC) as personality and brain factors influencing anxiety, but the nature of their relationships remains unclear. Here, the mechanisms underlying the protective role of trait optimism and of increased OFC volume against symptoms of anxiety were investigated in 61 healthy subjects, who completed measures of trait optimism and anxiety, and underwent structural scanning using magnetic resonance imaging. First, the OFC gray matter volume (GMV) was associated with increased optimism, which in turn was associated with reduced anxiety. Second, trait optimism mediated the relation between the left OFC volume and anxiety, thus demonstrating that increased GMV in this brain region protects against symptoms of anxiety through increased optimism. These results provide novel evidence about the brain-personality mechanisms protecting against anxiety symptoms in healthy functioning, and identify potential targets for preventive and therapeutic interventions aimed at reducing susceptibility and increasing resilience against emotional disturbances. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Revisiting Expansive Learning for Knowledge Production and Capability Development at Postgraduate Level in Higher Education Studies

ERIC Educational Resources Information Center

Niemann, Rita

2013-01-01

Higher education in South Africa is challenged by academic and social demands. Universities, therefore, have to produce graduates who will be able to function optimally within their field of study, as well as act as agents of change in their social environment. The main purpose of this article is to theorise about applying Engestrom's expansive…

User-oriented design strategies for a Lunar base

NASA Astrophysics Data System (ADS)

Jukola, Paivi

'Form follows function can be translated, among other, to communicate a desire to prioritize functional objectives for a particular design task. Thus it is less likely that a design program for a multi-functional habitat, for an all-purpose vehicle, or for a general community, will lead to most optimal, cost-effective and sustainable solutions. A power plant, a factory, a farm and a research center have over centuries had different logistical and functional requirements, despite of the local culture on various parts around the planet Earth. 'The same size fits all' concept is likely to lead to less user-friendly solutions. The paper proposes to rethink and to investigate alternative strategies to formulate objectives for a Lunar base. Diverse scientific experiments and potential future research programs for the Moon have a number of functional requirements that differ from each other. A crew of 4-6 may not be optimal for the most innovative research. The discussion is based on research of Human Factors and Design for visiting professor lectures for a Lunar base project with Howard University and NASA Marshall Space Center 2009-2010.

Study of college library appealing information system: A case of Longyan University

NASA Astrophysics Data System (ADS)

Liao, Jin-Hui

2014-10-01

The complaints from the readers at university libraries mainly focus on the aspects of service attitude, quality of service, reading environment, the management system, etc. Librarians should realize that reader complaints can actually promote the role of the library service and communicate with readers who complain in a friendly manner. In addition, the Longyan University library should establish an internal management system, improve library hardware facilities, improve the quality of librarians and optimize the knowledge structure of librarians, so as to improve the quality of the service for readers and reduce complaints. Based on this point, we have designed an appealing information system in cryptography machine basis, to provide readers online, remote and anonymous complaint functions.

Motor unit recruitment by size does not provide functional advantages for motor performance

PubMed Central

Dideriksen, Jakob L; Farina, Dario

2013-01-01

It is commonly assumed that the orderly recruitment of motor units by size provides a functional advantage for the performance of movements compared with a random recruitment order. On the other hand, the excitability of a motor neuron depends on its size and this is intrinsically linked to its innervation number. A range of innervation numbers among motor neurons corresponds to a range of sizes and thus to a range of excitabilities ordered by size. Therefore, if the excitation drive is similar among motor neurons, the recruitment by size is inevitably due to the intrinsic properties of motor neurons and may not have arisen to meet functional demands. In this view, we tested the assumption that orderly recruitment is necessarily beneficial by determining if this type of recruitment produces optimal motor output. Using evolutionary algorithms and without any a priori assumptions, the parameters of neuromuscular models were optimized with respect to several criteria for motor performance. Interestingly, the optimized model parameters matched well known neuromuscular properties, but none of the optimization criteria determined a consistent recruitment order by size unless this was imposed by an association between motor neuron size and excitability. Further, when the association between size and excitability was imposed, the resultant model of recruitment did not improve the motor performance with respect to the absence of orderly recruitment. A consistent observation was that optimal solutions for a variety of criteria of motor performance always required a broad range of innervation numbers in the population of motor neurons, skewed towards the small values. These results indicate that orderly recruitment of motor units in itself does not provide substantial functional advantages for motor control. Rather, the reason for its near-universal presence in human movements is that motor functions are optimized by a broad range of innervation numbers. PMID:24144879

Motor unit recruitment by size does not provide functional advantages for motor performance.

PubMed

Dideriksen, Jakob L; Farina, Dario

2013-12-15

It is commonly assumed that the orderly recruitment of motor units by size provides a functional advantage for the performance of movements compared with a random recruitment order. On the other hand, the excitability of a motor neuron depends on its size and this is intrinsically linked to its innervation number. A range of innervation numbers among motor neurons corresponds to a range of sizes and thus to a range of excitabilities ordered by size. Therefore, if the excitation drive is similar among motor neurons, the recruitment by size is inevitably due to the intrinsic properties of motor neurons and may not have arisen to meet functional demands. In this view, we tested the assumption that orderly recruitment is necessarily beneficial by determining if this type of recruitment produces optimal motor output. Using evolutionary algorithms and without any a priori assumptions, the parameters of neuromuscular models were optimized with respect to several criteria for motor performance. Interestingly, the optimized model parameters matched well known neuromuscular properties, but none of the optimization criteria determined a consistent recruitment order by size unless this was imposed by an association between motor neuron size and excitability. Further, when the association between size and excitability was imposed, the resultant model of recruitment did not improve the motor performance with respect to the absence of orderly recruitment. A consistent observation was that optimal solutions for a variety of criteria of motor performance always required a broad range of innervation numbers in the population of motor neurons, skewed towards the small values. These results indicate that orderly recruitment of motor units in itself does not provide substantial functional advantages for motor control. Rather, the reason for its near-universal presence in human movements is that motor functions are optimized by a broad range of innervation numbers.

Reexamination of optimal quantum state estimation of pure states

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

Hayashi, A.; Hashimoto, T.; Horibe, M.

2005-09-15

A direct derivation is given for the optimal mean fidelity of quantum state estimation of a d-dimensional unknown pure state with its N copies given as input, which was first obtained by Hayashi in terms of an infinite set of covariant positive operator valued measures (POVM's) and by Bruss and Macchiavello establishing a connection to optimal quantum cloning. An explicit condition for POVM measurement operators for optimal estimators is obtained, by which we construct optimal estimators with finite POVMs using exact quadratures on a hypersphere. These finite optimal estimators are not generally universal, where universality means the fidelity is independentmore » of input states. However, any optimal estimator with finite POVM for M(>N) copies is universal if it is used for N copies as input.« less

Three-dimensional desirability spaces for quality-by-design-based HPLC development.

PubMed

Mokhtar, Hatem I; Abdel-Salam, Randa A; Hadad, Ghada M

2015-04-01

In this study, three-dimensional desirability spaces were introduced as a graphical representation method of design space. This was illustrated in the context of application of quality-by-design concepts on development of a stability indicating gradient reversed-phase high-performance liquid chromatography method for the determination of vinpocetine and α-tocopheryl acetate in a capsule dosage form. A mechanistic retention model to optimize gradient time, initial organic solvent concentration and ternary solvent ratio was constructed for each compound from six experimental runs. Then, desirability function of each optimized criterion and subsequently the global desirability function were calculated throughout the knowledge space. The three-dimensional desirability spaces were plotted as zones exceeding a threshold value of desirability index in space defined by the three optimized method parameters. Probabilistic mapping of desirability index aided selection of design space within the potential desirability subspaces. Three-dimensional desirability spaces offered better visualization and potential design spaces for the method as a function of three method parameters with ability to assign priorities to this critical quality as compared with the corresponding resolution spaces. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Creating Sustainable Learning Environments in Schools by Means of Strategic Planning: The Experience of Engagement by a Comparative Education Team at a University

ERIC Educational Resources Information Center

Steyn, H.; Wolhuter, C.

2010-01-01

Many schools in South Africa are dysfunctional, or at least do not function optimally. This statement could be substantiated by just citing statistics about failure rates, school drop-out rates, school violence, matric pass rates, learner absenteeism, educator absenteeism or the incidence of discipline problems and the effect thereof on educators.…

Separation Potential for Multicomponent Mixtures: State-of-the Art of the Problem

NASA Astrophysics Data System (ADS)

Sulaberidze, G. A.; Borisevich, V. D.; Smirnov, A. Yu.

2017-03-01

Various approaches used in introducing a separation potential (value function) for multicomponent mixtures have been analyzed. It has been shown that all known potentials do not satisfy the Dirac-Peierls axioms for a binary mixture of uranium isotopes, which makes their practical application difficult. This is mainly due to the impossibility of constructing a "standard" cascade, whose role in the case of separation of binary mixtures is played by the ideal cascade. As a result, the only universal search method for optimal parameters of the separation cascade is their numerical optimization by the criterion of the minimum number of separation elements in it.

Inflammatory and Other Biomarkers: Role in Pathophysiology and Prediction of Gestational Diabetes Mellitus

PubMed Central

Abell, Sally K.; De Courten, Barbora; Boyle, Jacqueline A.; Teede, Helena J.

2015-01-01

Understanding pathophysiology and identifying mothers at risk of major pregnancy complications is vital to effective prevention and optimal management. However, in current antenatal care, understanding of pathophysiology of complications is limited. In gestational diabetes mellitus (GDM), risk prediction is mostly based on maternal history and clinical risk factors and may not optimally identify high risk pregnancies. Hence, universal screening is widely recommended. Here, we will explore the literature on GDM and biomarkers including inflammatory markers, adipokines, endothelial function and lipids to advance understanding of pathophysiology and explore risk prediction, with a goal to guide prevention and treatment of GDM. PMID:26110385

Stochastic HKMDHE: A multi-objective contrast enhancement algorithm

NASA Astrophysics Data System (ADS)

Pratiher, Sawon; Mukhopadhyay, Sabyasachi; Maity, Srideep; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.

2018-02-01

This contribution proposes a novel extension of the existing `Hyper Kurtosis based Modified Duo-Histogram Equalization' (HKMDHE) algorithm, for multi-objective contrast enhancement of biomedical images. A novel modified objective function has been formulated by joint optimization of the individual histogram equalization objectives. The optimal adequacy of the proposed methodology with respect to image quality metrics such as brightness preserving abilities, peak signal-to-noise ratio (PSNR), Structural Similarity Index (SSIM) and universal image quality metric has been experimentally validated. The performance analysis of the proposed Stochastic HKMDHE with existing histogram equalization methodologies like Global Histogram Equalization (GHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) has been given for comparative evaluation.

Computational Thermochemistry: Scale Factor Databases and Scale Factors for Vibrational Frequencies Obtained from Electronic Model Chemistries.

PubMed

Alecu, I M; Zheng, Jingjing; Zhao, Yan; Truhlar, Donald G

2010-09-14

Optimized scale factors for calculating vibrational harmonic and fundamental frequencies and zero-point energies have been determined for 145 electronic model chemistries, including 119 based on approximate functionals depending on occupied orbitals, 19 based on single-level wave function theory, three based on the neglect-of-diatomic-differential-overlap, two based on doubly hybrid density functional theory, and two based on multicoefficient correlation methods. Forty of the scale factors are obtained from large databases, which are also used to derive two universal scale factor ratios that can be used to interconvert between scale factors optimized for various properties, enabling the derivation of three key scale factors at the effort of optimizing only one of them. A reduced scale factor optimization model is formulated in order to further reduce the cost of optimizing scale factors, and the reduced model is illustrated by using it to obtain 105 additional scale factors. Using root-mean-square errors from the values in the large databases, we find that scaling reduces errors in zero-point energies by a factor of 2.3 and errors in fundamental vibrational frequencies by a factor of 3.0, but it reduces errors in harmonic vibrational frequencies by only a factor of 1.3. It is shown that, upon scaling, the balanced multicoefficient correlation method based on coupled cluster theory with single and double excitations (BMC-CCSD) can lead to very accurate predictions of vibrational frequencies. With a polarized, minimally augmented basis set, the density functionals with zero-point energy scale factors closest to unity are MPWLYP1M (1.009), τHCTHhyb (0.989), BB95 (1.012), BLYP (1.013), BP86 (1.014), B3LYP (0.986), MPW3LYP (0.986), and VSXC (0.986).

[Reorganization of the interdisciplinary emergency unit at the university clinic of Göttingen].

PubMed

Blaschke, Sabine; Müller, Gerhard A; Bergmann, Günther

2008-04-01

Configuration of the interdisciplinary emergency unit within the university clinic of Göttingen was successfully reorganized during the past two years. All emergencies except traumatologic, gynecologic and pediatric emergencies are treated within this functional unit which is guided by the center of internal medicine. It is organized in a three shift operation manner over a period of 24 hours. Due to a close interdisciplinary collaboration between different departments patients receive optimal diagnostic and therapeutic treatment within a short period of time. To improve processes within the emergency department a series of measures were taken including the -establishment of an intermediate care unit for unstable patients, setting up of special diagnostic and therapeutic units for the acute coronary syndrome as well as stroke, implementation of standardized clinical pathways, establishment of an electronic data processing network in close communication with all diagnostic entities, introduction of a quality assurance system and reduction of medical costs. Reorganization measures lead to a substantial optimization and acceleration of emergency proceedings and thus, provides optimal patient care around the clock. In addition, medical costs could clearly be reduced at the interface between preclinical and clinical emergency medicine.

MOEMs-based new functionalities for future instrumentation in space

NASA Astrophysics Data System (ADS)

Zamkotsian, Frédéric; Liotard, Arnaud; Viard, Thierry; Costes, Vincent; Hébert, Philippe-Jean; Hinglais, Emmanuel; Villenave, Michel

2017-11-01

Micro-Opto-Electro-Mechanical Systems (MOEMS) could be key components in future generation of space instruments. In Earth Observation, Universe Observation and Planet Exploration, scientific return of the instruments must be optimized in future missions. MOEMS devices are based on the mature micro-electronics technology and in addition to their compactness, scalability, and specific task customization, they could generate new functions not available with current technologies. CNES has initiated a study with LAM and TAS for listing the new functions associated with several types of MEMS (programmable slits, programmable micro-diffraction gratings, micro-deformable mirrors). Instrumental applications are then derived and promising concepts are described.

Information Filtering via a Scaling-Based Function

PubMed Central

Qiu, Tian; Zhang, Zi-Ke; Chen, Guang

2013-01-01

Finding a universal description of the algorithm optimization is one of the key challenges in personalized recommendation. In this article, for the first time, we introduce a scaling-based algorithm (SCL) independent of recommendation list length based on a hybrid algorithm of heat conduction and mass diffusion, by finding out the scaling function for the tunable parameter and object average degree. The optimal value of the tunable parameter can be abstracted from the scaling function, which is heterogeneous for the individual object. Experimental results obtained from three real datasets, Netflix, MovieLens and RYM, show that the SCL is highly accurate in recommendation. More importantly, compared with a number of excellent algorithms, including the mass diffusion method, the original hybrid method, and even an improved version of the hybrid method, the SCL algorithm remarkably promotes the personalized recommendation in three other aspects: solving the accuracy-diversity dilemma, presenting a high novelty, and solving the key challenge of cold start problem. PMID:23696829

Managing the Transition: The Role of Optimism and Self-Efficacy for First-Year Australian University Students

ERIC Educational Resources Information Center

Morton, Stephen; Mergler, Amanda; Boman, Peter

2014-01-01

Students making the transition from high school to university often encounter many stressors and new experiences. Many students adjust successfully to university; however, some students do not, often resulting in attrition from the university and mental health issues. The primary aim of the current study was to examine the effects that optimism,…

The Relationship between Optimism, Creativity and Psychopathological Symptoms in University Students

ERIC Educational Resources Information Center

Sanchez, Oscar; Martin-Brufau, Ramon; Mendez, Francisco Xavier; Corbalan, Francisco Javier; Liminana, Rosa Maria

2010-01-01

Introduction: This study examines the protective effects of variables of dispositional optimism and creativity with respect to measurements of psychopathology or psychological distress. Method: A total of 113 university students from different degree programs participated in the research. Measures of creativity (CREA), optimism (LOT-R) and…

Piece-wise quadratic approximations of arbitrary error functions for fast and robust machine learning.

PubMed

Gorban, A N; Mirkes, E M; Zinovyev, A

2016-12-01

Most of machine learning approaches have stemmed from the application of minimizing the mean squared distance principle, based on the computationally efficient quadratic optimization methods. However, when faced with high-dimensional and noisy data, the quadratic error functionals demonstrated many weaknesses including high sensitivity to contaminating factors and dimensionality curse. Therefore, a lot of recent applications in machine learning exploited properties of non-quadratic error functionals based on L 1 norm or even sub-linear potentials corresponding to quasinorms L p (0

Weight-watching at the university: the consequences of growth.

PubMed

Gallant, J A; Prothero, J W

1972-01-28

We began by pointing out that tools (for example) have size optima that are dictated by function. If we assume that the university has a function, it would seem reasonable to think about the size which will serve that function best. The principle of size optimization is fundamental, but its application to the university at once encounters a difficulty: What is the function of a university? It might take forever to secure general agreement on the answer to this question. The problem is that universities have a number of different functions, to which different individuals will attach different weights, and each function may well have a unique size optimum. Just as it is, in general, mathematically impossible to maximize simultaneously for two different functions of the same variable (29), so it is unsound to conceive of a single optimum for the multiversity. Nonetheless, a range of workable sizes may be defined by analyzing the effect of variation in size on all essential functions. The examples from biological systems illustrate this approach. Cells exist in a variety of sizes, each size presumably representing an optimization to one or another set of constraints, yet there are upper bounds. There are no cells the size of basketballs because essential metabolic functions are limited by the surface-to-volume ratio. We must emphasize that one does not need a grand theory of life in order to identify this limiting condition. If cells could talk, they would no doubt differ on the general philosophy of being a cell, yet all conceptions would be subject to certain physically inevitable limitations on size. In the case of the university, no grand theory of education is needed in order to identify dysfunctions of growth that affect essential activities (for example, the diffusion of individuals through, in, and out of the university) or that affect all activities (for example, overall morale). Balanced against these dysfunctions are such advantages of growth as economy, the achievement of a critical mass, and flexibility in staffing. Our analyis of data from the California system indicates that unit costs of education decline very little above a size of 10,000 or 15,000 students. Moreover, the critical mass for departmental excellence, at least in terms of the ACE ratings of graduate departments, is achieved by a university of about this size. Growth beyond this size range conitinues to provide flexibility in staffing and spares administrators the trouble of having to make difficult decisions. At the same time, the dysfunctions attendant on growth become steadily more severe. Our impression is that the dysfunctions have not been seriously considered, while the advantages have been greatly oversold. The idea of dysfunctional growth, although fundamental in biology, contradicts one of America's most cherished illusions. Particular dysfunctions of growth are rarely formulated, set down, and explicitly weighed against the potential advantages. Rather, the American prejudice has been to assume that growth is always good, or at least inevitable, and to treat the dysfunctions (which are inevitable) as managerial problems to be ironed out later or glossed over. There has also been a remarkable failure to think in terms of optima and to distinguish in this way between what we have termed functional and dysfunctional growth. Rather, the tendency has been to extrapolate functional growth into the dysfunctional range: If a university population of 10,000 confers certain advantages as compared with a population of 1,000, then it is assumed that a population of 100,000 must confer even more advantages. We suggest that it is time, in fact past time, to subject university growth to a more searching scrutiny. Functional and dysfunctional consequences need to be spelled out. Scale effects ought to be considered in connection with every plan for expansion. Ideally, one might expect a farsighted and tough-minded administration to carry out this function. This has rarely been the case. Too often administrators regard their function as simply that of broker among competing expansionist tendencies. Such a conception replaces philosophy by politics and often encourages mindless growth. Perhaps it is time for faculties to involve themselves in long-range planning and to pay the price of a more satisfactory environment by giving up some individual dreams of empire. The first step for every large university ought to be a careful analysis of scale effects (30). If analysis indicates that continued growth of a university will be, on balance, dysfunctional, we suggest that plans be formulated to establish an absolute limit on further enrollment increase, and an absolute limit on further building expansion. If further analysis indicates that a university is already well into the dysfunctional size range, then the obvious solution is to cut back. If this turns out to be the case, then we suggest that a program for the gradual reduction of the campus population be undertaken. There are two distinct ways to accomplish this: (i) the establishment of a new university and (ii) the decentralization of the existing university into two or more campuses. Decentralization strikes us as an attractive idea, worthy of careful study. One of the recommendations of the Scranton commission was, "Large universities should take steps to decentralize or reorganize to make possible a more human scale" (18, p. 14). Returning to the natural world, we note again that cells do not grow indefinitely. Instead, they divide.

The Witness-Voting System

NASA Astrophysics Data System (ADS)

Gerck, Ed

We present a new, comprehensive framework to qualitatively improve election outcome trustworthiness, where voting is modeled as an information transfer process. Although voting is deterministic (all ballots are counted), information is treated stochastically using Information Theory. Error considerations, including faults, attacks, and threats by adversaries, are explicitly included. The influence of errors may be corrected to achieve an election outcome error as close to zero as desired (error-free), with a provably optimal design that is applicable to any type of voting, with or without ballots. Sixteen voting system requirements, including functional, performance, environmental and non-functional considerations, are derived and rated, meeting or exceeding current public-election requirements. The voter and the vote are unlinkable (secret ballot) although each is identifiable. The Witness-Voting System (Gerck, 2001) is extended as a conforming implementation of the provably optimal design that is error-free, transparent, simple, scalable, robust, receipt-free, universally-verifiable, 100% voter-verified, and end-to-end audited.

Achilles tendon rupture: physiotherapy and endoscopy-assisted surgical treatment of a common sports injury

PubMed Central

Doral, Mahmut Nedim; Bozkurt, Murat; Turhan, Egemen; Dönmez, Gürhan; Demirel, Murat; Kaya, Defne; Ateşok, Kıvanç; Atay, Özgür Ahmet; Maffulli, Nicola

2010-01-01

Although the Achilles tendon (AT) is the strongest tendon in the human body, rupture of this tendon is one of the most common sports injuries in the athletic population. Despite numerous nonoperative and operative methods that have been described, there is no universal agreement about the optimal management strategy of acute total AT ruptures. The management of AT ruptures should aim to minimize the morbidity of the injury, optimize rapid return to full function, and prevent complications. Since endoscopy-assisted percutaneous AT repair allows direct visualization of the synovia and protects the paratenon that is important in biological healing of the AT, this technique becomes a reasonable treatment option in AT ruptures. Furthermore, Achilles tendoscopy technique may decrease the complications about the sural nerve. Also, early functional postoperative physiotherapy following surgery may improve the surgical outcomes. PMID:24198562

Examining social support, rumination, and optimism in relation to binge eating among Caucasian and African-American college women.

PubMed

Mason, Tyler B; Lewis, Robin J

2017-12-01

Binge eating is a significant concern among college age women-both Caucasian and African-American women. Research has shown that social support, coping, and optimism are associated with engaging in fewer negative health behaviors including binge eating among college students. However, the impact of sources of social support (i.e., support from family, friends, and a special person), rumination, and optimism on binge eating as a function of race/ethnicity has received less attention. The purpose of this study was to examine the association between social support, rumination, and optimism and binge eating among Caucasian and American-American women, separately. Caucasian (n = 100) and African-American (n = 84) women from a university in the Mid-Atlantic US completed an online survey about eating behaviors and psychosocial health. Social support from friends was associated with less likelihood of binge eating among Caucasian women. Social support from family was associated with less likelihood of binge eating among African-American women, but greater likelihood of binge eating among Caucasian women. Rumination was associated with greater likelihood of binge eating among Caucasian and African-American women. Optimism was associated with less likelihood of binge eating among African-American women. These results demonstrate similarities and differences in correlates of binge eating as a function of race/ethnicity.

Numerical model of tapered fiber Bragg gratings for comprehensive analysis and optimization of their sensing and strain-induced tunable dispersion properties.

PubMed

Osuch, Tomasz; Markowski, Konrad; Jędrzejewski, Kazimierz

2015-06-10

A versatile numerical model for spectral transmission/reflection, group delay characteristic analysis, and design of tapered fiber Bragg gratings (TFBGs) is presented. This approach ensures flexibility with defining both distribution of refractive index change of the gratings (including apodization) and shape of the taper profile. Additionally, sensing and tunable dispersion properties of the TFBGs were fully examined, considering strain-induced effects. The presented numerical approach, together with Pareto optimization, were also used to design the best tanh apodization profiles of the TFBG in terms of maximizing its spectral width with simultaneous minimization of the group delay oscillations. Experimental verification of the model confirms its correctness. The combination of model versatility and possibility to define the other objective functions of Pareto optimization creates a universal tool for TFBG analysis and design.

Probability density function learning by unsupervised neurons.

PubMed

Fiori, S

2001-10-01

In a recent work, we introduced the concept of pseudo-polynomial adaptive activation function neuron (FAN) and presented an unsupervised information-theoretic learning theory for such structure. The learning model is based on entropy optimization and provides a way of learning probability distributions from incomplete data. The aim of the present paper is to illustrate some theoretical features of the FAN neuron, to extend its learning theory to asymmetrical density function approximation, and to provide an analytical and numerical comparison with other known density function estimation methods, with special emphasis to the universal approximation ability. The paper also provides a survey of PDF learning from incomplete data, as well as results of several experiments performed on real-world problems and signals.

Genetic algorithms using SISAL parallel programming language

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

Tejada, S.

1994-05-06

Genetic algorithms are a mathematical optimization technique developed by John Holland at the University of Michigan [1]. The SISAL programming language possesses many of the characteristics desired to implement genetic algorithms. SISAL is a deterministic, functional programming language which is inherently parallel. Because SISAL is functional and based on mathematical concepts, genetic algorithms can be efficiently translated into the language. Several of the steps involved in genetic algorithms, such as mutation, crossover, and fitness evaluation, can be parallelized using SISAL. In this paper I will l discuss the implementation and performance of parallel genetic algorithms in SISAL.

Brain imaging predictors and the international study to predict optimized treatment for depression: study protocol for a randomized controlled trial

PubMed Central

2013-01-01

Background Approximately 50% of patients with major depressive disorder (MDD) do not respond optimally to antidepressant treatments. Given this is a large proportion of the patient population, pretreatment tests that predict which patients will respond to which types of treatment could save time, money and patient burden. Brain imaging offers a means to identify treatment predictors that are grounded in the neurobiology of the treatment and the pathophysiology of MDD. Methods/Design The international Study to Predict Optimized Treatment in Depression is a multi-center, parallel model, randomized clinical trial with an embedded imaging sub-study to identify such predictors. We focus on brain circuits implicated in major depressive disorder and its treatment. In the full trial, depressed participants are randomized to receive escitalopram, sertraline or venlafaxine-XR (open-label). They are assessed using standardized multiple clinical, cognitive-emotional behavioral, electroencephalographic and genetic measures at baseline and at eight weeks post-treatment. Overall, 2,016 depressed participants (18 to 65 years old) will enter the study, of whom a target of 10% will be recruited into the brain imaging sub-study (approximately 67 participants in each treatment arm) and 67 controls. The imaging sub-study is conducted at the University of Sydney and at Stanford University. Structural studies include high-resolution three-dimensional T1-weighted, diffusion tensor and T2/Proton Density scans. Functional studies include standardized functional magnetic resonance imaging (MRI) with three cognitive tasks (auditory oddball, a continuous performance task, and Go-NoGo) and two emotion tasks (unmasked conscious and masked non-conscious emotion processing tasks). After eight weeks of treatment, the functional MRI is repeated with the above tasks. We will establish the methods in the first 30 patients. Then we will identify predictors in the first half (n = 102), test the findings in the second half, and then extend the analyses to the total sample. Trial registration International Study to Predict Optimized Treatment - in Depression (iSPOT-D). ClinicalTrials.gov, NCT00693849. PMID:23866851

Brain imaging predictors and the international study to predict optimized treatment for depression: study protocol for a randomized controlled trial.

PubMed

Grieve, Stuart M; Korgaonkar, Mayuresh S; Etkin, Amit; Harris, Anthony; Koslow, Stephen H; Wisniewski, Stephen; Schatzberg, Alan F; Nemeroff, Charles B; Gordon, Evian; Williams, Leanne M

2013-07-18

Approximately 50% of patients with major depressive disorder (MDD) do not respond optimally to antidepressant treatments. Given this is a large proportion of the patient population, pretreatment tests that predict which patients will respond to which types of treatment could save time, money and patient burden. Brain imaging offers a means to identify treatment predictors that are grounded in the neurobiology of the treatment and the pathophysiology of MDD. The international Study to Predict Optimized Treatment in Depression is a multi-center, parallel model, randomized clinical trial with an embedded imaging sub-study to identify such predictors. We focus on brain circuits implicated in major depressive disorder and its treatment. In the full trial, depressed participants are randomized to receive escitalopram, sertraline or venlafaxine-XR (open-label). They are assessed using standardized multiple clinical, cognitive-emotional behavioral, electroencephalographic and genetic measures at baseline and at eight weeks post-treatment. Overall, 2,016 depressed participants (18 to 65 years old) will enter the study, of whom a target of 10% will be recruited into the brain imaging sub-study (approximately 67 participants in each treatment arm) and 67 controls. The imaging sub-study is conducted at the University of Sydney and at Stanford University. Structural studies include high-resolution three-dimensional T1-weighted, diffusion tensor and T2/Proton Density scans. Functional studies include standardized functional magnetic resonance imaging (MRI) with three cognitive tasks (auditory oddball, a continuous performance task, and Go-NoGo) and two emotion tasks (unmasked conscious and masked non-conscious emotion processing tasks). After eight weeks of treatment, the functional MRI is repeated with the above tasks. We will establish the methods in the first 30 patients. Then we will identify predictors in the first half (n=102), test the findings in the second half, and then extend the analyses to the total sample. International Study to Predict Optimized Treatment--in Depression (iSPOT-D). ClinicalTrials.gov, NCT00693849.

Optimization of Ballast Design: A Case Study of the Physics Entrepreneurship Program

NASA Astrophysics Data System (ADS)

Ding, Jun; Cheng, Norman; Lamouri, Abbas; Sulcs, Juris; Brown, Robert; Taylor, Cyrus

2001-10-01

This talk presents a typical internship project for students in the Physics Entrepreneurship Program at Case Western Reserve University. As part of their overall strategy, Advanced Lighting International (ADLT) is involved in the production of magnetic ballasts for metal halide lamps. The systems in which these ballasts function is undergoing rapid evolution, leading to the question of how the design of the ballasts can be optimized in order to deliver superior performance for lower cost. Addressing this question requires a full understanding of a variety of issues ranging from the basic modeling of the physics of the magnetic ballasts to questions of overall market strategy, manufacturing considerations, and the competitive environment.

The Role of Intuition in the Solving of Optimization Problems

ERIC Educational Resources Information Center

Malaspina, Uldarico; Font, Vicenc

2010-01-01

This article presents the partial results obtained in the first stage of the research, which sought to answer the following questions: (a) What is the role of intuition in university students' solutions to optimization problems? (b) What is the role of rigor in university students' solutions to optimization problems? (c) How is the combination of…

Spatial Prediction and Optimized Sampling Design for Sodium Concentration in Groundwater

PubMed Central

Shabbir, Javid; M. AbdEl-Salam, Nasser; Hussain, Tajammal

2016-01-01

Sodium is an integral part of water, and its excessive amount in drinking water causes high blood pressure and hypertension. In the present paper, spatial distribution of sodium concentration in drinking water is modeled and optimized sampling designs for selecting sampling locations is calculated for three divisions in Punjab, Pakistan. Universal kriging and Bayesian universal kriging are used to predict the sodium concentrations. Spatial simulated annealing is used to generate optimized sampling designs. Different estimation methods (i.e., maximum likelihood, restricted maximum likelihood, ordinary least squares, and weighted least squares) are used to estimate the parameters of the variogram model (i.e, exponential, Gaussian, spherical and cubic). It is concluded that Bayesian universal kriging fits better than universal kriging. It is also observed that the universal kriging predictor provides minimum mean universal kriging variance for both adding and deleting locations during sampling design. PMID:27683016

A Passion for Learning: The Theory and Practice of Optimal Match at the University of Washington

ERIC Educational Resources Information Center

Noble, Kathleen D.; Childers, Sarah A.

2008-01-01

Early entrance from secondary school to university, based on the principle of optimal match, is a rare but highly effective educational strategy for many gifted students. The University of Washington offers two early entrance options for gifted adolescents: the Early Entrance Program for students prior to age 15, and the UW Academy for Young…

The Relationship between University Students' Attitude to Listening to Music and Their Level of Optimism

ERIC Educational Resources Information Center

Aksoy, Nil

2014-01-01

The purpose of this study is to analyse the relationship between university students' attitude to listening to music and their level of optimism. The study group for the research consists of 508 students who studied at Aksaray University in the 2012-13 academic year. Simple random sampling is used. In this study, the "Attitude Scale for…

Efficient G(sup 4)FET-Based Logic Circuits

NASA Technical Reports Server (NTRS)

Vatan, Farrokh

2008-01-01

A total of 81 optimal logic circuits based on four-gate field-effect transistors (G(sup 4)4FETs) have been designed to implement all Boolean functions of up to three variables. The purpose of this development was to lend credence to the expectation that logic circuits based on G(sup 4)FETs could be more efficient (in the sense that they could contain fewer transistors), relative to functionally equivalent logic circuits based on conventional transistors. A G(sup 4)FET a combination of a junction field-effect transistor (JFET) and a metal oxide/semiconductor field-effect transistor (MOSFET) superimposed in a single silicon island and can therefore be regarded as two transistors sharing the same body. A G(sup 4)FET can also be regarded as a single device having four gates: two side junction-based gates, a top MOS gate, and a back gate activated by biasing of a silicon-on-insulator substrate. Each of these gates can be used to control the conduction characteristics of the transistor; this possibility creates new options for designing analog, radio-frequency, mixed-signal, and digital circuitry. One such option is to design a G(sup 4)FET to function as a three-input NOT-majority gate, which has been shown to be a universal and programmable logic gate. Optimal NOT-majority-gate, G(sup 4)FET-based logic-circuit designs were obtained in a comparative study that also included formulation of functionally equivalent logic circuits based on NOR and NAND gates implemented by use of conventional transistors. In the study, the problem of finding the optimal design for each logic function and each transistor type was solved as an integer-programming optimization problem. Considering all 81 non-equivalent Boolean functions included in the study, it was found that in 63% of the cases, fewer logic gates (and, hence, fewer transistors) would be needed in the G(sup 4)FET-based implementations.

On advanced configuration enhance adaptive system optimization

NASA Astrophysics Data System (ADS)

Liu, Hua; Ding, Quanxin; Wang, Helong; Guo, Chunjie; Chen, Hongliang; Zhou, Liwei

2017-10-01

For aim to find an effective method to structure to enhance these adaptive system with some complex function and look forward to establish an universally applicable solution in prototype and optimization. As the most attractive component in adaptive system, wave front corrector is constrained by some conventional technique and components, such as polarization dependence and narrow working waveband. Advanced configuration based on a polarized beam split can optimized energy splitting method used to overcome these problems effective. With the global algorithm, the bandwidth has been amplified by more than five times as compared with that of traditional ones. Simulation results show that the system can meet the application requirements in MTF and other related criteria. Compared with the conventional design, the system has reduced in volume and weight significantly. Therefore, the determining factors are the prototype selection and the system configuration, Results show their effectiveness.

The enhanced Aussie Optimism Positive Thinking Skills Program: The relationship between internalizing symptoms and family functioning in children aged 9–11 years old

PubMed Central

Kennedy, Patricia; Rooney, Rosanna M.; Kane, Robert T.; Hassan, Sharinaz; Nesa, Monique

2015-01-01

The family context plays a critical role in the health of the child. This was the first study to examine the usefulness of the General Functioning subscale of the Family Assessment Device (FAD-GF) in assessing family functioning and its relationship to internalizing symptoms in school-aged children aged between 9 and 11 years of age. Eight hundred and forty-seven year 4 and 5 students from 13 schools (607 intervention students, and 240 control students) participated in the Aussie Optimism Positive Thinking Skills Program (AO-PTS) – a universal school-based program targeting internalizing symptoms. Students rated how ‘healthy’ they perceived their family to be at pre-test and at 6-months follow-up. Although some aspects of validity and reliability could be improved, results indicated that perceptions of family functioning at pre-test were predictive of internalizing symptoms at the 6-months follow-up. The FAD-GF therefore showed promise as a potential measure of family functioning for children as young as 9 years old. Regardless of children’s pre-test levels of perceived family functioning, no intervention effects were found on the anxiety and depression scales; this finding suggests that child perceptions of family functioning may act as a general protective factor against internalizing symptomology. PMID:25983698

Positive and Negative Affectivity as Mediator and Moderator of the Relationship between Optimism and Life Satisfaction in Turkish University Students

ERIC Educational Resources Information Center

Kapikiran, Necla Acun

2012-01-01

The main purpose of this study is to examine the mediator and moderator role of positive and negative affectivity variables on the relationship between optimism and life satisfaction in university students. 397 university students, ranging in age from 18 to 27 (M = 20.98), attending different departments of the Faculty of Education, at Pamukkale…

Programmable wide field spectrograph for earth observation

NASA Astrophysics Data System (ADS)

Zamkotsian, Frédéric; Lanzoni, Patrick; Liotard, Arnaud; Viard, Thierry; Costes, Vincent; Hébert, Philippe-Jean

2017-11-01

In Earth Observation, Universe Observation and Planet Exploration, scientific return of the instruments must be optimized in future missions. Micro-Opto-Electro-Mechanical Systems (MOEMS) could be key components in future generation of space instruments. These devices are based on the mature micro-electronics technology and in addition to their compactness, scalability, and specific task customization, they could generate new functions not available with current technologies. French and European space agencies, the Centre National d'Etudes Spatiales (CNES) and the European Space Agency (ESA) have initiated several studies with LAM and TAS for listing the new functions associated with several types of MEMS, and developing new ideas of instruments.

Self-functioning and perceived parenting: relations of parental empathy and love inconsistency with narcissism, depression, and self-esteem.

PubMed

Trumpeter, Nevelyn N; Watson, P J; O'Leary, Brian J; Weathington, Bart L

2008-03-01

In Heinz Kohut's (1977, 1984) theory of the psychology of the self, good parenting provides a child with optimal frustration and just the right amount of loving empathic concern. In the present study, the authors examined the relations of perceived parental empathy and love inconsistency with measures of narcissism, self-esteem, and depression. In a sample of university undergraduates (N=232; 78 men, 153 women, and 1 nonresponder), perceived parental empathy predicted more adaptive self-functioning, whereas parental love inconsistency was related to psychological maladjustment. These results support the theoretical assumption that perceived parental empathy is associated with healthy self-development.

Monte Carlo simulation of a photodisintegration of 3 H experiment in Geant4

NASA Astrophysics Data System (ADS)

Gray, Isaiah

2013-10-01

An upcoming experiment involving photodisintegration of 3 H at the High Intensity Gamma-Ray Source facility at Duke University has been simulated in the software package Geant4. CAD models of silicon detectors and wire chambers were imported from Autodesk Inventor using the program FastRad and the Geant4 GDML importer. Sensitive detectors were associated with the appropriate logical volumes in the exported GDML file so that changes in detector geometry will be easily manifested in the simulation. Probability distribution functions for the energy and direction of outgoing protons were generated using numerical tables from previous theory, and energies and directions were sampled from these distributions using a rejection sampling algorithm. The simulation will be a useful tool to optimize detector geometry, estimate background rates, and test data analysis algorithms. This work was supported by the Triangle Universities Nuclear Laboratory REU program at Duke University.

SU-E-T-625: Robustness Evaluation and Robust Optimization of IMPT Plans Based on Per-Voxel Standard Deviation of Dose Distributions.

PubMed

Liu, W; Mohan, R

2012-06-01

Proton dose distributions, IMPT in particular, are highly sensitive to setup and range uncertainties. We report a novel method, based on per-voxel standard deviation (SD) of dose distributions, to evaluate the robustness of proton plans and to robustly optimize IMPT plans to render them less sensitive to uncertainties. For each optimization iteration, nine dose distributions are computed - the nominal one, and one each for ± setup uncertainties along x, y and z axes and for ± range uncertainty. SD of dose in each voxel is used to create SD-volume histogram (SVH) for each structure. SVH may be considered a quantitative representation of the robustness of the dose distribution. For optimization, the desired robustness may be specified in terms of an SD-volume (SV) constraint on the CTV and incorporated as a term in the objective function. Results of optimization with and without this constraint were compared in terms of plan optimality and robustness using the so called'worst case' dose distributions; which are obtained by assigning the lowest among the nine doses to each voxel in the clinical target volume (CTV) and the highest to normal tissue voxels outside the CTV. The SVH curve and the area under it for each structure were used as quantitative measures of robustness. Penalty parameter of SV constraint may be varied to control the tradeoff between robustness and plan optimality. We applied these methods to one case each of H&N and lung. In both cases, we found that imposing SV constraint improved plan robustness but at the cost of normal tissue sparing. SVH-based optimization and evaluation is an effective tool for robustness evaluation and robust optimization of IMPT plans. Studies need to be conducted to test the methods for larger cohorts of patients and for other sites. This research is supported by National Cancer Institute (NCI) grant P01CA021239, the University Cancer Foundation via the Institutional Research Grant program at the University of Texas MD Anderson Cancer Center, and MD Anderson’s cancer center support grant CA016672. © 2012 American Association of Physicists in Medicine.

Emotion: The Self-regulatory Sense

PubMed Central

2014-01-01

While emotion is a central component of human health and well-being, traditional approaches to understanding its biological function have been wanting. A dynamic systems model, however, broadly redefines and recasts emotion as a primary sensory system—perhaps the first sensory system to have emerged, serving the ancient autopoietic function of “self-regulation.” Drawing upon molecular biology and revelations from the field of epigenetics, the model suggests that human emotional perceptions provide an ongoing stream of “self-relevant” sensory information concerning optimally adaptive states between the organism and its immediate environment, along with coupled behavioral corrections that honor a universal self-regulatory logic, one still encoded within cellular signaling and immune functions. Exemplified by the fundamental molecular circuitry of sensorimotor control in the E coli bacterium, the model suggests that the hedonic (affective) categories emerge directly from positive and negative feedback processes, their good/bad binary appraisals relating to dual self-regulatory behavioral regimes—evolutionary purposes, through which organisms actively participate in natural selection, and through which humans can interpret optimal or deficit states of balanced being and becoming. The self-regulatory sensory paradigm transcends anthropomorphism, unites divergent theoretical perspectives and isolated bodies of literature, while challenging time-honored assumptions. While suppressive regulatory strategies abound, it suggests that emotions are better understood as regulating us, providing a service crucial to all semantic language, learning systems, evaluative decision-making, and fundamental to optimal physical, mental, and social health. PMID:24808986

Fully printable, strain-engineered electronic wrap for customizable soft electronics.

PubMed

Byun, Junghwan; Lee, Byeongmoon; Oh, Eunho; Kim, Hyunjong; Kim, Sangwoo; Lee, Seunghwan; Hong, Yongtaek

2017-03-24

Rapid growth of stretchable electronics stimulates broad uses in multidisciplinary fields as well as industrial applications. However, existing technologies are unsuitable for implementing versatile applications involving adaptable system design and functions in a cost/time-effective way because of vacuum-conditioned, lithographically-predefined processes. Here, we present a methodology for a fully printable, strain-engineered electronic wrap as a universal strategy which makes it more feasible to implement various stretchable electronic systems with customizable layouts and functions. The key aspects involve inkjet-printed rigid island (PRI)-based stretchable platform technology and corresponding printing-based automated electronic functionalization methodology, the combination of which provides fully printed, customized layouts of stretchable electronic systems with simplified process. Specifically, well-controlled contact line pinning effect of printed polymer solution enables the formation of PRIs with tunable thickness; and surface strain analysis on those PRIs leads to the optimized stability and device-to-island fill factor of strain-engineered electronic wraps. Moreover, core techniques of image-based automated pinpointing, surface-mountable device based electronic functionalizing, and one-step interconnection networking of PRIs enable customized circuit design and adaptable functionalities. To exhibit the universality of our approach, multiple types of practical applications ranging from self-computable digital logics to display and sensor system are demonstrated on skin in a customized form.

Fully printable, strain-engineered electronic wrap for customizable soft electronics

NASA Astrophysics Data System (ADS)

Byun, Junghwan; Lee, Byeongmoon; Oh, Eunho; Kim, Hyunjong; Kim, Sangwoo; Lee, Seunghwan; Hong, Yongtaek

2017-03-01

Rapid growth of stretchable electronics stimulates broad uses in multidisciplinary fields as well as industrial applications. However, existing technologies are unsuitable for implementing versatile applications involving adaptable system design and functions in a cost/time-effective way because of vacuum-conditioned, lithographically-predefined processes. Here, we present a methodology for a fully printable, strain-engineered electronic wrap as a universal strategy which makes it more feasible to implement various stretchable electronic systems with customizable layouts and functions. The key aspects involve inkjet-printed rigid island (PRI)-based stretchable platform technology and corresponding printing-based automated electronic functionalization methodology, the combination of which provides fully printed, customized layouts of stretchable electronic systems with simplified process. Specifically, well-controlled contact line pinning effect of printed polymer solution enables the formation of PRIs with tunable thickness; and surface strain analysis on those PRIs leads to the optimized stability and device-to-island fill factor of strain-engineered electronic wraps. Moreover, core techniques of image-based automated pinpointing, surface-mountable device based electronic functionalizing, and one-step interconnection networking of PRIs enable customized circuit design and adaptable functionalities. To exhibit the universality of our approach, multiple types of practical applications ranging from self-computable digital logics to display and sensor system are demonstrated on skin in a customized form.

Fully printable, strain-engineered electronic wrap for customizable soft electronics

PubMed Central

Byun, Junghwan; Lee, Byeongmoon; Oh, Eunho; Kim, Hyunjong; Kim, Sangwoo; Lee, Seunghwan; Hong, Yongtaek

2017-01-01

Rapid growth of stretchable electronics stimulates broad uses in multidisciplinary fields as well as industrial applications. However, existing technologies are unsuitable for implementing versatile applications involving adaptable system design and functions in a cost/time-effective way because of vacuum-conditioned, lithographically-predefined processes. Here, we present a methodology for a fully printable, strain-engineered electronic wrap as a universal strategy which makes it more feasible to implement various stretchable electronic systems with customizable layouts and functions. The key aspects involve inkjet-printed rigid island (PRI)-based stretchable platform technology and corresponding printing-based automated electronic functionalization methodology, the combination of which provides fully printed, customized layouts of stretchable electronic systems with simplified process. Specifically, well-controlled contact line pinning effect of printed polymer solution enables the formation of PRIs with tunable thickness; and surface strain analysis on those PRIs leads to the optimized stability and device-to-island fill factor of strain-engineered electronic wraps. Moreover, core techniques of image-based automated pinpointing, surface-mountable device based electronic functionalizing, and one-step interconnection networking of PRIs enable customized circuit design and adaptable functionalities. To exhibit the universality of our approach, multiple types of practical applications ranging from self-computable digital logics to display and sensor system are demonstrated on skin in a customized form. PMID:28338055

A Platform to Optimize the Field Emission Properties of Carbon Nanotube Based Fibers (Postprint)

DTIC Science & Technology

2016-08-25

University of Dayton Research Institute 300 College Park Ave., Dayton, OH 45469 6) AFRL /RD, Kirtland AFB, Albuquerque, NM 8717... AFRL -RX-WP-JA-2017-0351 A PLATFORM TO OPTIMIZE THE FIELD EMISSION PROPERTIES OF CARBON-NANOTUBE-BASED FIBERS (POSTPRINT) Steven B...Fairchild AFRL /RX M. Cahay and W. Zhu University of Cincinnati K.L. Jensen Naval Research Laboratory R.G. Forbes University of Surrey

Qubit absorption refrigerator at strong coupling

NASA Astrophysics Data System (ADS)

Mu, Anqi; Agarwalla, Bijay Kumar; Schaller, Gernot; Segal, Dvira

2017-12-01

We demonstrate that a quantum absorption refrigerator (QAR) can be realized from the smallest quantum system, a qubit, by coupling it in a non-additive (strong) manner to three heat baths. This function is un-attainable for the qubit model under the weak system-bath coupling limit, when the dissipation is additive. In an optimal design, the reservoirs are engineered and characterized by a single frequency component. We then obtain closed expressions for the cooling window and refrigeration efficiency, as well as bounds for the maximal cooling efficiency and the efficiency at maximal power. Our results agree with macroscopic designs and with three-level models for QARs, which are based on the weak system-bath coupling assumption. Beyond the optimal limit, we show with analytical calculations and numerical simulations that the cooling efficiency varies in a non-universal manner with model parameters. Our work demonstrates that strongly-coupled quantum machines can exhibit function that is un-attainable under the weak system-bath coupling assumption.

[The importance of centralized treatment: research and development].

PubMed

Højgaard, Liselotte

2006-04-10

Biomedical research in Denmark enjoys a strong position at present but will be challenged by a new organization for all hospitals in Denmark beginning in 2007. It will be very important to recognize the importance of medical research as the cornerstone of optimal patient treatment in the new hospital organizations. Centralization with a focus on efficiency and low cost, as well as decentralization combined with the loss of university hospital functions, will further challenge the conditions of clinical research already seen worldwide and also experienced in Denmark.

Turbine Engine Control Synthesis. Volume 1. Optimal Controller Synthesis and Demonstration

DTIC Science & Technology

1975-03-01

Nomenclature (Continued) Symbol Deseription M Matrix (of Table 12) M Mach number N Rotational speed, rpm N ’ Nonlinear rotational speed, rpm P Power lever... P Pressure, N /m 2; bfh/ft 2 PLA Power lever angle PR = PT3/PT2 Pressure ratio ( P Power, ft-lbf/sec Q Matrix (of Table 30) R Universal gas constant, 53...function, i = 1, 2, 3, ... in Inlet n Stage number designation out Outlet p Variable associated with particle s Static condition _se Static condition

Integrated analysis of individual codon contribution to protein biosynthesis reveals a new approach to improving the basis of rational gene design.

PubMed

Villada, Juan C; Brustolini, Otávio José Bernardes; Batista da Silveira, Wendel

2017-08-01

Gene codon optimization may be impaired by the misinterpretation of frequency and optimality of codons. Although recent studies have revealed the effects of codon usage bias (CUB) on protein biosynthesis, an integrated perspective of the biological role of individual codons remains unknown. Unlike other previous studies, we show, through an integrated framework that attributes of codons such as frequency, optimality and positional dependency should be combined to unveil individual codon contribution for protein biosynthesis. We designed a codon quantification method for assessing CUB as a function of position within genes with a novel constraint: the relativity of position-dependent codon usage shaped by coding sequence length. Thus, we propose a new way of identifying the enrichment, depletion and non-uniform positional distribution of codons in different regions of yeast genes. We clustered codons that shared attributes of frequency and optimality. The cluster of non-optimal codons with rare occurrence displayed two remarkable characteristics: higher codon decoding time than frequent-non-optimal cluster and enrichment at the 5'-end region, where optimal codons with the highest frequency are depleted. Interestingly, frequent codons with non-optimal adaptation to tRNAs are uniformly distributed in the Saccharomyces cerevisiae genes, suggesting their determinant role as a speed regulator in protein elongation. © The Author 2017. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Closed-loop, pilot/vehicle analysis of the approach and landing task

NASA Technical Reports Server (NTRS)

Anderson, M. R.; Schmidt, D. K.

1986-01-01

In the case of approach and landing, it is universally accepted that the pilot uses more than one vehicle response, or output, to close his control loops. Therefore, to model this task, a multi-loop analysis technique is required. The analysis problem has been in obtaining reasonable analytic estimates of the describing functions representing the pilot's loop compensation. Once these pilot describing functions are obtained, appropriate performance and workload metrics must then be developed for the landing task. The optimal control approach provides a powerful technique for obtaining the necessary describing functions, once the appropriate task objective is defined in terms of a quadratic objective function. An approach is presented through the use of a simple, reasonable objective function and model-based metrics to evaluate loop performance and pilot workload. The results of an analysis of the LAHOS (Landing and Approach of Higher Order Systems) study performed by R.E. Smith is also presented.

Optimal control of universal quantum gates in a double quantum dot

NASA Astrophysics Data System (ADS)

Castelano, Leonardo K.; de Lima, Emanuel F.; Madureira, Justino R.; Degani, Marcos H.; Maialle, Marcelo Z.

2018-06-01

We theoretically investigate electron spin operations driven by applied electric fields in a semiconductor double quantum dot (DQD) formed in a nanowire with longitudinal potential modulated by local gating. We develop a model that describes the process of loading and unloading the DQD taking into account the overlap between the electron wave function and the leads. Such a model considers the spatial occupation and the spin Pauli blockade in a time-dependent fashion due to the highly mixed states driven by the external electric field. Moreover, we present a road map based on the quantum optimal control theory (QOCT) to find a specific electric field that performs two-qubit quantum gates on a faster timescale and with higher possible fidelity. By employing the QOCT, we demonstrate the possibility of performing within high efficiency a universal set of quantum gates {cnot, H, and T } , where cnot is the controlled-not gate, H is the Hadamard gate, and T is the π /8 gate, even in the presence of the loading/unloading process and charge noise effects. Furthermore, by varying the intensity of the applied magnetic field B , the optimized fidelity of the gates oscillates with a period inversely proportional to the gate operation time tf. This behavior can be useful to attain higher fidelity for fast gate operations (>1 GHz) by appropriately choosing B and tf to produce a maximum of the oscillation.

Optimal Admission to Higher Education

ERIC Educational Resources Information Center

Albaek, Karsten

2017-01-01

This paper analyses admission decisions when students from different high school tracks apply for admission to university programmes. I derive a criterion that is optimal in the sense that it maximizes the graduation rates of the university programmes. The paper contains an empirical analysis that documents the relevance of theory and illustrates…

Optimizing the Reliability and Performance of Service Composition Applications with Fault Tolerance in Wireless Sensor Networks

PubMed Central

Wu, Zhao; Xiong, Naixue; Huang, Yannong; Xu, Degang; Hu, Chunyang

2015-01-01

The services composition technology provides flexible methods for building service composition applications (SCAs) in wireless sensor networks (WSNs). The high reliability and high performance of SCAs help services composition technology promote the practical application of WSNs. The optimization methods for reliability and performance used for traditional software systems are mostly based on the instantiations of software components, which are inapplicable and inefficient in the ever-changing SCAs in WSNs. In this paper, we consider the SCAs with fault tolerance in WSNs. Based on a Universal Generating Function (UGF) we propose a reliability and performance model of SCAs in WSNs, which generalizes a redundancy optimization problem to a multi-state system. Based on this model, an efficient optimization algorithm for reliability and performance of SCAs in WSNs is developed based on a Genetic Algorithm (GA) to find the optimal structure of SCAs with fault-tolerance in WSNs. In order to examine the feasibility of our algorithm, we have evaluated the performance. Furthermore, the interrelationships between the reliability, performance and cost are investigated. In addition, a distinct approach to determine the most suitable parameters in the suggested algorithm is proposed. PMID:26561818

A heterogeneous computing accelerated SCE-UA global optimization method using OpenMP, OpenCL, CUDA, and OpenACC.

PubMed

Kan, Guangyuan; He, Xiaoyan; Ding, Liuqian; Li, Jiren; Liang, Ke; Hong, Yang

2017-10-01

The shuffled complex evolution optimization developed at the University of Arizona (SCE-UA) has been successfully applied in various kinds of scientific and engineering optimization applications, such as hydrological model parameter calibration, for many years. The algorithm possesses good global optimality, convergence stability and robustness. However, benchmark and real-world applications reveal the poor computational efficiency of the SCE-UA. This research aims at the parallelization and acceleration of the SCE-UA method based on powerful heterogeneous computing technology. The parallel SCE-UA is implemented on Intel Xeon multi-core CPU (by using OpenMP and OpenCL) and NVIDIA Tesla many-core GPU (by using OpenCL, CUDA, and OpenACC). The serial and parallel SCE-UA were tested based on the Griewank benchmark function. Comparison results indicate the parallel SCE-UA significantly improves computational efficiency compared to the original serial version. The OpenCL implementation obtains the best overall acceleration results however, with the most complex source code. The parallel SCE-UA has bright prospects to be applied in real-world applications.

Neutron spectroscopy with scintillation detectors using wavelets

NASA Astrophysics Data System (ADS)

Hartman, Jessica

The purpose of this research was to study neutron spectroscopy using the EJ-299-33A plastic scintillator. This scintillator material provided a novel means of detection for fast neutrons, without the disadvantages of traditional liquid scintillation materials. EJ-299-33A provided a more durable option to these materials, making it less likely to be damaged during handling. Unlike liquid scintillators, this plastic scintillator was manufactured from a non-toxic material, making it safer to use, as well as easier to design detectors. The material was also manufactured with inherent pulse shape discrimination abilities, making it suitable for use in neutron detection. The neutron spectral unfolding technique was developed in two stages. Initial detector response function modeling was carried out through the use of the MCNPX Monte Carlo code. The response functions were developed for a monoenergetic neutron flux. Wavelets were then applied to smooth the response function. The spectral unfolding technique was applied through polynomial fitting and optimization techniques in MATLAB. Verification of the unfolding technique was carried out through the use of experimentally determined response functions. These were measured on the neutron source based on the Van de Graff accelerator at the University of Kentucky. This machine provided a range of monoenergetic neutron beams between 0.1 MeV and 24 MeV, making it possible to measure the set of response functions of the EJ-299-33A plastic scintillator detector to neutrons of specific energies. The response of a plutonium-beryllium (PuBe) source was measured using the source available at the University of Nevada, Las Vegas. The neutron spectrum reconstruction was carried out using the experimentally measured response functions. Experimental data was collected in the list mode of the waveform digitizer. Post processing of this data focused on the pulse shape discrimination analysis of the recorded response functions to remove the effects of photons and allow for source characterization based solely on the neutron response. The unfolding technique was performed through polynomial fitting and optimization techniques in MATLAB, and provided an energy spectrum for the PuBe source.

Universality of optimal measurements

NASA Astrophysics Data System (ADS)

Tarrach, Rolf; Vidal, Guifré

1999-11-01

We present optimal and minimal measurements on identical copies of an unknown state of a quantum bit when the quality of measuring strategies is quantified with the gain of information (Kullback-or mutual information-of probability distributions). We also show that the maximal gain of information occurs, among isotropic priors, when the state is known to be pure. Universality of optimal measurements follows from our results: using the fidelity or the gain of information, two different figures of merits, leads to exactly the same conclusions for isotropic distributions. We finally investigate the optimal capacity of N copies of an unknown state as a quantum channel of information.

Interstellar Communication Channel Based on a Biological Universal

NASA Technical Reports Server (NTRS)

Weber, Arthur L.; DeVincenzi, Donald L. (Technical Monitor)

1999-01-01

Cellular biosynthesis starts with sugar substrates and continues energetically downhill to yield amino acid, rapid, and nucleotide products. To understand the energetics of these processes, we calculated the energy for biosynthesis from sugars of E. cali's amino acids, nucleotides, and lipids. We found that the biosynthesis of amino acids and lipids from sugar substrates proceeds by redox disproportionation. of sugar carbon with a favorable energy of about -11 kcal/mole of carbon. Overall, redox disproportion of sugar carbon accounted for 84% and 96% (ATP only 6% and 1%) of the total biosynthetic energy of amino acids and lipids (the major cellular constituents). Next, we calculated for all 48 possible 3-carbon substrates the energy of maximal disproportionation to carbon dioxide and methane. We found no other carbon substrates than matched sugars in biosynthetic energy, efficiency, and simplicity. From this, we concluded that sugars are the optimal biosynthetic substrate. Since this conclusion is based on universal properties of carbon chemistry, other carbon-based life throughout the Universe would also use optimal sugar substrates. Furthermore, this rather obvious universal role of sugars as the optimal biosubstrate would probably be common knowledge of technological civilizations throughout the Universe. Since the elemental building block of all sugars is formaldehyde, the common knowledge that sugars are the universal optimal biosubstrate could reasonably lead to the selection of a line(s) in the microwave spectrum of formaldehyde as a frequency for interstellar communication.

Integrating Evolutionary Game Theory into Mechanistic Genotype-Phenotype Mapping.

PubMed

Zhu, Xuli; Jiang, Libo; Ye, Meixia; Sun, Lidan; Gragnoli, Claudia; Wu, Rongling

2016-05-01

Natural selection has shaped the evolution of organisms toward optimizing their structural and functional design. However, how this universal principle can enhance genotype-phenotype mapping of quantitative traits has remained unexplored. Here we show that the integration of this principle and functional mapping through evolutionary game theory gains new insight into the genetic architecture of complex traits. By viewing phenotype formation as an evolutionary system, we formulate mathematical equations to model the ecological mechanisms that drive the interaction and coordination of its constituent components toward population dynamics and stability. Functional mapping provides a procedure for estimating the genetic parameters that specify the dynamic relationship of competition and cooperation and predicting how genes mediate the evolution of this relationship during trait formation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Direct AUC optimization of regulatory motifs.

PubMed

Zhu, Lin; Zhang, Hong-Bo; Huang, De-Shuang

2017-07-15

The discovery of transcription factor binding site (TFBS) motifs is essential for untangling the complex mechanism of genetic variation under different developmental and environmental conditions. Among the huge amount of computational approaches for de novo identification of TFBS motifs, discriminative motif learning (DML) methods have been proven to be promising for harnessing the discovery power of accumulated huge amount of high-throughput binding data. However, they have to sacrifice accuracy for speed and could fail to fully utilize the information of the input sequences. We propose a novel algorithm called CDAUC for optimizing DML-learned motifs based on the area under the receiver-operating characteristic curve (AUC) criterion, which has been widely used in the literature to evaluate the significance of extracted motifs. We show that when the considered AUC loss function is optimized in a coordinate-wise manner, the cost function of each resultant sub-problem is a piece-wise constant function, whose optimal value can be found exactly and efficiently. Further, a key step of each iteration of CDAUC can be efficiently solved as a computational geometry problem. Experimental results on real world high-throughput datasets illustrate that CDAUC outperforms competing methods for refining DML motifs, while being one order of magnitude faster. Meanwhile, preliminary results also show that CDAUC may also be useful for improving the interpretability of convolutional kernels generated by the emerging deep learning approaches for predicting TF sequences specificities. CDAUC is available at: https://drive.google.com/drive/folders/0BxOW5MtIZbJjNFpCeHlBVWJHeW8 . dshuang@tongji.edu.cn. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Patient-provider communication and low-income adults: age, race, literacy, and optimism predict communication satisfaction.

PubMed

Jensen, Jakob D; King, Andy J; Guntzviller, Lisa M; Davis, LaShara A

2010-04-01

To assess whether literacy, numeracy, and optimism are related to low-income adults' satisfaction with their healthcare provider's communication skills. Low-income adults (N=131) were recruited from seven counties in Indiana through University extension programs. To achieve research triangulation, participants were surveyed and interviewed about their communication satisfaction with health providers. Survey data revealed that four variables significantly predicted satisfaction: age, race, literacy, and optimism. Low-income adults in the current study were more critical of their healthcare provider's communication skills if they were younger, White, functionally literate, and pessimistic. Follow-up interviews confirmed this pattern and suggested it was a byproduct of patient activism. In low-income populations, communication satisfaction may be lower for groups that are traditionally active in doctor-patient interactions (e.g., younger patients, patients with higher literacy skills). Healthcare providers should be aware that older, non-White, optimistic, and literacy deficient patients report greater communication satisfaction than their younger, White, pessimistic, and functionally literate peers. Both groups may be coping with their situation, the former by withdrawing and the latter by actively pushing for a higher standard of care. Healthcare providers should continue to seek out ways to facilitate dialogue with these underserved groups. 2009 Elsevier Ireland Ltd. All rights reserved.

Experimental Investigation and Optimization of TIG Welding Parameters on Aluminum 6061 Alloy Using Firefly Algorithm

NASA Astrophysics Data System (ADS)

Kumar, Rishi; Mevada, N. Ramesh; Rathore, Santosh; Agarwal, Nitin; Rajput, Vinod; Sinh Barad, AjayPal

2017-08-01

To improve Welding quality of aluminum (Al) plate, the TIG Welding system has been prepared, by which Welding current, Shielding gas flow rate and Current polarity can be controlled during Welding process. In the present work, an attempt has been made to study the effect of Welding current, current polarity, and shielding gas flow rate on the tensile strength of the weld joint. Based on the number of parameters and their levels, the Response Surface Methodology technique has been selected as the Design of Experiment. For understanding the influence of input parameters on Ultimate tensile strength of weldment, ANOVA analysis has been carried out. Also to describe and optimize TIG Welding using a new metaheuristic Nature - inspired algorithm which is called as Firefly algorithm which was developed by Dr. Xin-She Yang at Cambridge University in 2007. A general formulation of firefly algorithm is presented together with an analytical, mathematical modeling to optimize the TIG Welding process by a single equivalent objective function.

Developing human functioning and rehabilitation research. Part II: Interdisciplinary university centers and national and regional collaboration networks.

PubMed

Stucki, Gerold; Celio, Marco

2007-05-01

There is a strong movement towards interdisciplinary research around common and scientifically competitive themes, both at universities and at the national and regional level. Human functioning and rehabilitation is a new, highly innovative and relevant theme. It has the potential to attract researchers from a wide range of disciplines, institutions and organizations. It is thus of interest for universities seeking to embark upon a new and unique research area. Similarly, it is a promising theme for individual researchers, institutions and organizations aiming to develop a national or regional collaboration network for interdisciplinary research. Human functioning and rehabilitation complements established themes from the biomedical perspective. In the context of the life sciences, it can be seen as an extension of the biosciences towards a comprehensive understanding of human life, including human interaction and communication, against the background of the natural and social environment. Based on a better understanding of human functioning and disability, there is a wide range of largely unexplored possibilities to optimize populations' functioning and minimize persons' experience of disability in the presence of a health condition. Rehabilitation research is uniquely positioned to integrate and translate scientific advances into benefits for people and the society. Rehabilitation research from the comprehensive perspective can thus become a catalyst of interdisciplinary research that crosses the boundaries of the natural sciences and engineering research, the human and behavioral sciences, the social sciences and a wide range of related scientific areas. Rehabilitation research is also uniquely positioned to cross the boundaries of medicine and the health sector at large, and to translate knowledge across sectors including education, labor and social affairs.

An Optimization of Inventory Demand Forecasting in University Healthcare Centre

NASA Astrophysics Data System (ADS)

Bon, A. T.; Ng, T. K.

2017-01-01

Healthcare industry becomes an important field for human beings nowadays as it concerns about one’s health. With that, forecasting demand for health services is an important step in managerial decision making for all healthcare organizations. Hence, a case study was conducted in University Health Centre to collect historical demand data of Panadol 650mg for 68 months from January 2009 until August 2014. The aim of the research is to optimize the overall inventory demand through forecasting techniques. Quantitative forecasting or time series forecasting model was used in the case study to forecast future data as a function of past data. Furthermore, the data pattern needs to be identified first before applying the forecasting techniques. Trend is the data pattern and then ten forecasting techniques are applied using Risk Simulator Software. Lastly, the best forecasting techniques will be find out with the least forecasting error. Among the ten forecasting techniques include single moving average, single exponential smoothing, double moving average, double exponential smoothing, regression, Holt-Winter’s additive, Seasonal additive, Holt-Winter’s multiplicative, seasonal multiplicative and Autoregressive Integrated Moving Average (ARIMA). According to the forecasting accuracy measurement, the best forecasting technique is regression analysis.

BASKET on-board software library

NASA Astrophysics Data System (ADS)

Luntzer, Armin; Ottensamer, Roland; Kerschbaum, Franz

2014-07-01

The University of Vienna is a provider of on-board data processing software with focus on data compression, such as used on board the highly successful Herschel/PACS instrument, as well as in the small BRITE-Constellation fleet of cube-sats. Current contributions are made to CHEOPS, SAFARI and PLATO. The effort was taken to review the various functions developed for Herschel and provide a consolidated software library to facilitate the work for future missions. This library is a shopping basket of algorithms. Its contents are separated into four classes: auxiliary functions (e.g. circular buffers), preprocessing functions (e.g. for calibration), lossless data compression (arithmetic or Rice coding) and lossy reduction steps (ramp fitting etc.). The "BASKET" has all functionality that is needed to create an on-board data processing chain. All sources are written in C, supplemented by optimized versions in assembly, targeting popular CPU architectures for space applications. BASKET is open source and constantly growing

Vehicle System Integration, Optimization, and Robustness

Science.gov Websites

Operations Technology Exchange Initiating Partnerships University Partners Government Partners Industry Contacts Researchers Thrust Area 5: Vehicle System Integration, Optimization, and Robustness Thrust Area only optimal design of the vehicle components, but also an optimization of the interactions between

Personal experience with the procurement of 132 liver allografts

PubMed Central

Yanaga, K.; Tzakis, A.G.; Starzl, T.E.

2010-01-01

A single donor surgeon's experience procuring the livers from 132 donors is described. Thirty-seven grafts (28.9%) had hepatic arterial anomalies, 19 (14.4%) of which required arterial reconstruction prior to transplantation. Of the 121 grafts evaluated for early function, 103 grafts (85.2%) functioned well, whereas 14 grafts (11.6%) functioned poorly and 4 grafts (3.3%) failed to function at all. The variables associated with less than optimal function of the graft consisted of donor age (P < 0.05), duration of donor's stay in the intensive care unit (P < 0.005), abnormal graft appearance (P < 0.05), and such recipient problems as vascular thromboses during or immediately following transplantation (P < 0.005). A new preservation fluid, University of Wisconsin solution, allowed safe and longer cold storage of the liver allograft than did Euro-Collins' solution (P < 0.0001). A parameter of liver allograft viability, which is simple and predictive of allograft function prior to the actual transplant procedure, is urgently needed. PMID:2803485

Wind farm optimization using evolutionary algorithms

NASA Astrophysics Data System (ADS)

Ituarte-Villarreal, Carlos M.

In recent years, the wind power industry has focused its efforts on solving the Wind Farm Layout Optimization (WFLO) problem. Wind resource assessment is a pivotal step in optimizing the wind-farm design and siting and, in determining whether a project is economically feasible or not. In the present work, three (3) different optimization methods are proposed for the solution of the WFLO: (i) A modified Viral System Algorithm applied to the optimization of the proper location of the components in a wind-farm to maximize the energy output given a stated wind environment of the site. The optimization problem is formulated as the minimization of energy cost per unit produced and applies a penalization for the lack of system reliability. The viral system algorithm utilized in this research solves three (3) well-known problems in the wind-energy literature; (ii) a new multiple objective evolutionary algorithm to obtain optimal placement of wind turbines while considering the power output, cost, and reliability of the system. The algorithm presented is based on evolutionary computation and the objective functions considered are the maximization of power output, the minimization of wind farm cost and the maximization of system reliability. The final solution to this multiple objective problem is presented as a set of Pareto solutions and, (iii) A hybrid viral-based optimization algorithm adapted to find the proper component configuration for a wind farm with the introduction of the universal generating function (UGF) analytical approach to discretize the different operating or mechanical levels of the wind turbines in addition to the various wind speed states. The proposed methodology considers the specific probability functions of the wind resource to describe their proper behaviors to account for the stochastic comportment of the renewable energy components, aiming to increase their power output and the reliability of these systems. The developed heuristic considers a variable number of system components and wind turbines with different operating characteristics and sizes, to have a more heterogeneous model that can deal with changes in the layout and in the power generation requirements over the time. Moreover, the approach evaluates the impact of the wind-wake effect of the wind turbines upon one another to describe and evaluate the power production capacity reduction of the system depending on the layout distribution of the wind turbines.

Integrated testing system FiTest for diagnosis of PCBA

NASA Astrophysics Data System (ADS)

Bogdan, Arkadiusz; Lesniak, Adam

2016-12-01

This article presents the innovative integrated testing system FiTest for automatic, quick inspection of printed circuit board assemblies (PCBA) manufactured in Surface Mount Technology (SMT). Integration of Automatic Optical Inspection (AOI), In-Circuit Tests (ICT) and Functional Circuit Tests (FCT) resulted in universal hardware platform for testing variety of electronic circuits. The platform provides increased test coverage, decreased level of false calls and optimization of test duration. The platform is equipped with powerful algorithms performing tests in a stable and repetitive way and providing effective management of diagnosis.

Nonprincipal plane scattering of flat plates and pattern control of horn antennas

NASA Technical Reports Server (NTRS)

Balanis, Constantine A.; Polka, Lesley A.; Liu, Kefeng

1989-01-01

Using the geometrical theory of diffraction, the traditional method of high frequency scattering analysis, the prediction of the radar cross section of a perfectly conducting, flat, rectangular plate is limited to principal planes. Part A of this report predicts the radar cross section in nonprincipal planes using the method of equivalent currents. This technique is based on an asymptotic end-point reduction of the surface radiation integrals for an infinite wedge and enables nonprincipal plane prediction. The predicted radar cross sections for both horizontal and vertical polarizations are compared to moment method results and experimental data from Arizona State University's anechoic chamber. In part B, a variational calculus approach to the pattern control of the horn antenna is outlined. The approach starts with the optimization of the aperture field distribution so that the control of the radiation pattern in a range of directions can be realized. A control functional is thus formulated. Next, a spectral analysis method is introduced to solve for the eigenfunctions from the extremal condition of the formulated functional. Solutions to the optimized aperture field distribution are then obtained.

Money Changes Everything: Funding Shocks and Optimal Admissions and Financial Aid Policies in Higher Education

ERIC Educational Resources Information Center

Nagler, Matthew G.

2006-01-01

The paper examines the effect of a shock to university funding on tuition net of financial aid, admissions selectivity, and enrollment levels chosen by an optimizing university. Whereas a positive shock, such as a major donation, results in lower net tuition and greater selectivity with respect to all students, its effect on enrollment may not be…

The University of Arizona College of Medicine Optimal Aging Program: Stepping in the Shadows of Successful Aging

ERIC Educational Resources Information Center

Sikora, Stephanie

2006-01-01

The Optimal Aging Program (OAP) at the University of Arizona, College of Medicine is a longitudinal mentoring program that pairs students with older adults who are considered to be aging "successfully." This credit-bearing elective was initially established in 2001 through a grant from the John A. Hartford Foundation, and aims to expand…

A UVM simulation environment for the study, optimization and verification of HL-LHC digital pixel readout chips

NASA Astrophysics Data System (ADS)

Marconi, S.; Conti, E.; Christiansen, J.; Placidi, P.

2018-05-01

The operating conditions of the High Luminosity upgrade of the Large Hadron Collider are very demanding for the design of next generation hybrid pixel readout chips in terms of particle rate, radiation level and data bandwidth. To this purpose, the RD53 Collaboration has developed for the ATLAS and CMS experiments a dedicated simulation and verification environment using industry-consolidated tools and methodologies, such as SystemVerilog and the Universal Verification Methodology (UVM). This paper presents how the so-called VEPIX53 environment has first guided the design of digital architectures, optimized for processing and buffering very high particle rates, and secondly how it has been reused for the functional verification of the first large scale demonstrator chip designed by the collaboration, which has recently been submitted.

MinFinder: Locating all the local minima of a function

NASA Astrophysics Data System (ADS)

Tsoulos, Ioannis G.; Lagaris, Isaac E.

2006-01-01

A new stochastic clustering algorithm is introduced that aims to locate all the local minima of a multidimensional continuous and differentiable function inside a bounded domain. The accompanying software (MinFinder) is written in ANSI C++. However, the user may code his objective function either in C++, C or Fortran 77. We compare the performance of this new method to the performance of Multistart and Topographical Multilevel Single Linkage Clustering on a set of benchmark problems. Program summaryTitle of program:MinFinder Catalogue identifier:ADWU Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADWU Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computer for which the program is designed and others on which is has been tested:The tool is designed to be portable in all systems running the GNU C++ compiler Installation:University of Ioannina, Greece Programming language used:GNU-C++, GNU-C, GNU Fortran 77 Memory required to execute with typical data:200 KB No. of bits in a word:32 No. of processors used:1 Has the code been vectorized or parallelized?:no No. of lines in distributed program, including test data, etc.:5797 No. of bytes in distributed program, including test data, etc.:588 121 Distribution format:gzipped tar file Nature of the physical problem:A multitude of problems in science and engineering are often reduced to minimizing a function of many variables. There are instances that a local optimum does not correspond to the desired physical solution and hence the search for a better solution is required. Local optimization techniques can be trapped in any local minimum. Global optimization is then the appropriate tool. For example, solving a non-linear system of equations via optimization, employing a "least squares" type of objective, one may encounter many local minima that do not correspond to solutions, i.e. they are far from zero. Method of solution:Using a uniform pdf, points are sampled from the rectangular search domain. A clustering technique, based on a typical distance and a gradient criterion, is used to decide from which points a local search should be started. The employed local procedure is a BFGS version due to Powell. Further searching is terminated when all the local minima inside the search domain are thought to be found. This is accomplished via the double-box rule. Typical running time:Depending on the objective function

Optimizing high performance computing workflow for protein functional annotation.

PubMed

Stanberry, Larissa; Rekepalli, Bhanu; Liu, Yuan; Giblock, Paul; Higdon, Roger; Montague, Elizabeth; Broomall, William; Kolker, Natali; Kolker, Eugene

2014-09-10

Functional annotation of newly sequenced genomes is one of the major challenges in modern biology. With modern sequencing technologies, the protein sequence universe is rapidly expanding. Newly sequenced bacterial genomes alone contain over 7.5 million proteins. The rate of data generation has far surpassed that of protein annotation. The volume of protein data makes manual curation infeasible, whereas a high compute cost limits the utility of existing automated approaches. In this work, we present an improved and optmized automated workflow to enable large-scale protein annotation. The workflow uses high performance computing architectures and a low complexity classification algorithm to assign proteins into existing clusters of orthologous groups of proteins. On the basis of the Position-Specific Iterative Basic Local Alignment Search Tool the algorithm ensures at least 80% specificity and sensitivity of the resulting classifications. The workflow utilizes highly scalable parallel applications for classification and sequence alignment. Using Extreme Science and Engineering Discovery Environment supercomputers, the workflow processed 1,200,000 newly sequenced bacterial proteins. With the rapid expansion of the protein sequence universe, the proposed workflow will enable scientists to annotate big genome data.

Optimizing high performance computing workflow for protein functional annotation

PubMed Central

Stanberry, Larissa; Rekepalli, Bhanu; Liu, Yuan; Giblock, Paul; Higdon, Roger; Montague, Elizabeth; Broomall, William; Kolker, Natali; Kolker, Eugene

2014-01-01

Functional annotation of newly sequenced genomes is one of the major challenges in modern biology. With modern sequencing technologies, the protein sequence universe is rapidly expanding. Newly sequenced bacterial genomes alone contain over 7.5 million proteins. The rate of data generation has far surpassed that of protein annotation. The volume of protein data makes manual curation infeasible, whereas a high compute cost limits the utility of existing automated approaches. In this work, we present an improved and optmized automated workflow to enable large-scale protein annotation. The workflow uses high performance computing architectures and a low complexity classification algorithm to assign proteins into existing clusters of orthologous groups of proteins. On the basis of the Position-Specific Iterative Basic Local Alignment Search Tool the algorithm ensures at least 80% specificity and sensitivity of the resulting classifications. The workflow utilizes highly scalable parallel applications for classification and sequence alignment. Using Extreme Science and Engineering Discovery Environment supercomputers, the workflow processed 1,200,000 newly sequenced bacterial proteins. With the rapid expansion of the protein sequence universe, the proposed workflow will enable scientists to annotate big genome data. PMID:25313296

Optimizing Industrial Consumer Demand Response Through Disaggregation, Hour-Ahead Pricing, and Momentary Autonomous Control

NASA Astrophysics Data System (ADS)

Abdulaal, Ahmed

The work in this study addresses the current limitations of the price-driven demand response (DR) approach. Mainly, the dependability on consumers to respond in an energy aware conduct, the response timeliness, the difficulty of applying DR in a busy industrial environment, and the problem of load synchronization are of utmost concern. In order to conduct a simulation study, realistic price simulation model and consumers' building load models are created using real data. DR action is optimized using an autonomous control method, which eliminates the dependency on frequent consumer engagement. Since load scheduling and long-term planning approaches are infeasible in the industrial environment, the proposed method utilizes instantaneous DR in response to hour-ahead price signals (RTP-HA). Preliminary simulation results concluded savings at the consumer-side at the cost of increased supplier-side burden due to the aggregate effect of the universal DR policies. Therefore, a consumer disaggregation strategy is briefly discussed. Finally, a refined discrete-continuous control system is presented, which utilizes multi-objective Pareto optimization, evolutionary programming, utility functions, and bidirectional loads. Demonstrated through a virtual testbed fit with real data, the new system achieves momentary optimized DR in real-time while maximizing the consumer's wellbeing.

A Multi-Objective Optimization Technique to Model the Pareto Front of Organic Dielectric Polymers

NASA Astrophysics Data System (ADS)

Gubernatis, J. E.; Mannodi-Kanakkithodi, A.; Ramprasad, R.; Pilania, G.; Lookman, T.

Multi-objective optimization is an area of decision making that is concerned with mathematical optimization problems involving more than one objective simultaneously. Here we describe two new Monte Carlo methods for this type of optimization in the context of their application to the problem of designing polymers with more desirable dielectric and optical properties. We present results of applying these Monte Carlo methods to a two-objective problem (maximizing the total static band dielectric constant and energy gap) and a three objective problem (maximizing the ionic and electronic contributions to the static band dielectric constant and energy gap) of a 6-block organic polymer. Our objective functions were constructed from high throughput DFT calculations of 4-block polymers, following the method of Sharma et al., Nature Communications 5, 4845 (2014) and Mannodi-Kanakkithodi et al., Scientific Reports, submitted. Our high throughput and Monte Carlo methods of analysis extend to general N-block organic polymers. This work was supported in part by the LDRD DR program of the Los Alamos National Laboratory and in part by a Multidisciplinary University Research Initiative (MURI) Grant from the Office of Naval Research.

Universal Spatial Correlation Functions for Describing and Reconstructing Soil Microstructure

PubMed Central

Skvortsova, Elena B.; Mallants, Dirk

2015-01-01

Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification, pore-scale modelling of soil properties, soil degradation monitoring, and description of spatial dynamics of soil microbial activity. PMID:26010779

Universal spatial correlation functions for describing and reconstructing soil microstructure.

PubMed

Karsanina, Marina V; Gerke, Kirill M; Skvortsova, Elena B; Mallants, Dirk

2015-01-01

Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification, pore-scale modelling of soil properties, soil degradation monitoring, and description of spatial dynamics of soil microbial activity.

A statistical approach for inferring the 3D structure of the genome.

PubMed

Varoquaux, Nelle; Ay, Ferhat; Noble, William Stafford; Vert, Jean-Philippe

2014-06-15

Recent technological advances allow the measurement, in a single Hi-C experiment, of the frequencies of physical contacts among pairs of genomic loci at a genome-wide scale. The next challenge is to infer, from the resulting DNA-DNA contact maps, accurate 3D models of how chromosomes fold and fit into the nucleus. Many existing inference methods rely on multidimensional scaling (MDS), in which the pairwise distances of the inferred model are optimized to resemble pairwise distances derived directly from the contact counts. These approaches, however, often optimize a heuristic objective function and require strong assumptions about the biophysics of DNA to transform interaction frequencies to spatial distance, and thereby may lead to incorrect structure reconstruction. We propose a novel approach to infer a consensus 3D structure of a genome from Hi-C data. The method incorporates a statistical model of the contact counts, assuming that the counts between two loci follow a Poisson distribution whose intensity decreases with the physical distances between the loci. The method can automatically adjust the transfer function relating the spatial distance to the Poisson intensity and infer a genome structure that best explains the observed data. We compare two variants of our Poisson method, with or without optimization of the transfer function, to four different MDS-based algorithms-two metric MDS methods using different stress functions, a non-metric version of MDS and ChromSDE, a recently described, advanced MDS method-on a wide range of simulated datasets. We demonstrate that the Poisson models reconstruct better structures than all MDS-based methods, particularly at low coverage and high resolution, and we highlight the importance of optimizing the transfer function. On publicly available Hi-C data from mouse embryonic stem cells, we show that the Poisson methods lead to more reproducible structures than MDS-based methods when we use data generated using different restriction enzymes, and when we reconstruct structures at different resolutions. A Python implementation of the proposed method is available at http://cbio.ensmp.fr/pastis. © The Author 2014. Published by Oxford University Press.

Investigating Knowledge Management Status among Faculty Members of Kerman University of Medical Sciences based on the Nonaka Model in 2015

PubMed Central

Vali, Leila; Izadi, Azar; Jahani, Yunes; Okhovati, Maryam

2016-01-01

Introduction Education and research are two major functions of universities, which require proper and systematic exploitation of available knowledge and information. Therefore, it is necessary to investigate the knowledge management status in an education system by considering the function of faculty members in creation and dissemination of knowledge. This study was conducted to investigate the knowledge management status among faculty members of the Kerman University of Medical Sciences based on the Nonaka and Takeuchi models in 2015. Methods This was a descriptive-analytical and cross-sectional study. It was conducted on 165 faculty members at the Kerman University of Medical Sciences, who were selected from seven faculties as weighted using a random stratified sampling method. The Nonaka and Takeuchi knowledge management questionnaire consists of 26 questions in four dimensions of socialization, externalization, internalization, and combination. Scoring of questions was conducted using the five-point Likert scale. To analyze data, independent t-test, one-way ANOVA, Pearson correlation coefficients, and the Kruskal-Wallis test were employed. Results The four dimensions in the Nonaka and Takeuchi model are based on optimal indicators (3.5), dimensions of combination, and externalization with an average of 3.3 were found in higher ranks and internalization and socialization had averages of 3.1 and 3. According to the findings of this study, the average knowledge management among faculty members of the Kerman University of Medical Sciences was estimated to be 3.1, with a bit difference compared to the average. According to the results of t-tests, there was no significant relationship between gender and various dimensions of knowledge management (p>0.05). The findings of Kruskal-Wallis showed that there is no significant relationship between variables of age, academic rank, and type of faculty with regard to dimensions of knowledge management (p>0.05). In addition, according to the results of Pearson tests, there is no significant relation between employment history and dimensions of knowledge management (p>0.05). Conclusion Considering the function and importance of knowledge management in education and research organizations including universities, it is recommended to pay comprehensive attention to establishment of knowledge management and knowledge sharing in universities and provide the required background to from research teams and communication networks inside and outside universities. PMID:27757183

Investigating Knowledge Management Status among Faculty Members of Kerman University of Medical Sciences based on the Nonaka Model in 2015.

PubMed

Vali, Leila; Izadi, Azar; Jahani, Yunes; Okhovati, Maryam

2016-08-01

Education and research are two major functions of universities, which require proper and systematic exploitation of available knowledge and information. Therefore, it is necessary to investigate the knowledge management status in an education system by considering the function of faculty members in creation and dissemination of knowledge. This study was conducted to investigate the knowledge management status among faculty members of the Kerman University of Medical Sciences based on the Nonaka and Takeuchi models in 2015. This was a descriptive-analytical and cross-sectional study. It was conducted on 165 faculty members at the Kerman University of Medical Sciences, who were selected from seven faculties as weighted using a random stratified sampling method. The Nonaka and Takeuchi knowledge management questionnaire consists of 26 questions in four dimensions of socialization, externalization, internalization, and combination. Scoring of questions was conducted using the five-point Likert scale. To analyze data, independent t-test, one-way ANOVA, Pearson correlation coefficients, and the Kruskal-Wallis test were employed. The four dimensions in the Nonaka and Takeuchi model are based on optimal indicators (3.5), dimensions of combination, and externalization with an average of 3.3 were found in higher ranks and internalization and socialization had averages of 3.1 and 3. According to the findings of this study, the average knowledge management among faculty members of the Kerman University of Medical Sciences was estimated to be 3.1, with a bit difference compared to the average. According to the results of t-tests, there was no significant relationship between gender and various dimensions of knowledge management (p>0.05). The findings of Kruskal-Wallis showed that there is no significant relationship between variables of age, academic rank, and type of faculty with regard to dimensions of knowledge management (p>0.05). In addition, according to the results of Pearson tests, there is no significant relation between employment history and dimensions of knowledge management (p>0.05). Considering the function and importance of knowledge management in education and research organizations including universities, it is recommended to pay comprehensive attention to establishment of knowledge management and knowledge sharing in universities and provide the required background to from research teams and communication networks inside and outside universities.

Optimism and Psychological Resilience in Relation to Depressive Symptoms in University Students: Examining the Mediating Role of Self-Esteem

ERIC Educational Resources Information Center

Kapikiran, Sahin; Acun-Kapikiran, Necla

2016-01-01

This study examined the role of self-esteem as a mediator in the relationships between optimism and psychological resilience on depressive symptoms in university students. A total of 494 undergraduate students, comprising of 253 female and 241 male participated in this study. Participants' ages ranged from 18 to 30 (M = 20.85, SD = 1.57).…

The role of service areas in the optimization of FSS orbital and frequency assignments

NASA Technical Reports Server (NTRS)

Levis, C. A.; Wang, C. W.; Yamamura, Y.; Reilly, C. H.; Gonsalvez, D. J.

1985-01-01

A relationship is derived, on a single-entry interference basis, for the minimum allowable spacing between two satellites as a function of electrical parameters and service-area geometries. For circular beams, universal curves relate the topocentric satellite spacing angle to the service-area separation angle measured at the satellite. The corresponding geocentric spacing depends only weakly on the mean longitude of the two satellites, and this is true also for alliptical antenna beams. As a consequence, if frequency channels are preassigned, the orbital assignment synthesis of a satellite system can be formulated as a mixed-integer programming (MIP) problem or approximated by a linear programming (LP) problem, with the interference protection requirements enforced by constraints while some linear function is optimized. Possible objective-function choices are discussed and explicit formulations are presented for the choice of the sum of the absolute deviations of the orbital locations from some prescribed ideal location set. A test problem is posed consisting of six service areas, each served by one satellite, all using elliptical antenna beams and the same frequency channels. Numerical results are given for the three ideal location prescriptions for both the MIP and LP formulations. The resulting scenarios also satisfy reasonable aggregate interference protection requirements.

The constraints satisfaction problem approach in the design of an architectural functional layout

NASA Astrophysics Data System (ADS)

Zawidzki, Machi; Tateyama, Kazuyoshi; Nishikawa, Ikuko

2011-09-01

A design support system with a new strategy for finding the optimal functional configurations of rooms for architectural layouts is presented. A set of configurations satisfying given constraints is generated and ranked according to multiple objectives. The method can be applied to problems in architectural practice, urban or graphic design-wherever allocation of related geometrical elements of known shape is optimized. Although the methodology is shown using simplified examples-a single story residential building with two apartments each having two rooms-the results resemble realistic functional layouts. One example of a practical size problem of a layout of three apartments with a total of 20 rooms is demonstrated, where the generated solution can be used as a base for a realistic architectural blueprint. The discretization of design space is discussed, followed by application of a backtrack search algorithm used for generating a set of potentially 'good' room configurations. Next the solutions are classified by a machine learning method (FFN) as 'proper' or 'improper' according to the internal communication criteria. Examples of interactive ranking of the 'proper' configurations according to multiple criteria and choosing 'the best' ones are presented. The proposed framework is general and universal-the criteria, parameters and weights can be individually defined by a user and the search algorithm can be adjusted to a specific problem.

A study of acoustic-to-articulatory inversion of speech by analysis-by-synthesis using chain matrices and the Maeda articulatory model

PubMed Central

Panchapagesan, Sankaran; Alwan, Abeer

2011-01-01

In this paper, a quantitative study of acoustic-to-articulatory inversion for vowel speech sounds by analysis-by-synthesis using the Maeda articulatory model is performed. For chain matrix calculation of vocal tract (VT) acoustics, the chain matrix derivatives with respect to area function are calculated and used in a quasi-Newton method for optimizing articulatory trajectories. The cost function includes a distance measure between natural and synthesized first three formants, and parameter regularization and continuity terms. Calibration of the Maeda model to two speakers, one male and one female, from the University of Wisconsin x-ray microbeam (XRMB) database, using a cost function, is discussed. Model adaptation includes scaling the overall VT and the pharyngeal region and modifying the outer VT outline using measured palate and pharyngeal traces. The inversion optimization is initialized by a fast search of an articulatory codebook, which was pruned using XRMB data to improve inversion results. Good agreement between estimated midsagittal VT outlines and measured XRMB tongue pellet positions was achieved for several vowels and diphthongs for the male speaker, with average pellet-VT outline distances around 0.15 cm, smooth articulatory trajectories, and less than 1% average error in the first three formants. PMID:21476670

A novel process of viral vector barcoding and library preparation enables high-diversity library generation and recombination-free paired-end sequencing

PubMed Central

Davidsson, Marcus; Diaz-Fernandez, Paula; Schwich, Oliver D.; Torroba, Marcos; Wang, Gang; Björklund, Tomas

2016-01-01

Detailed characterization and mapping of oligonucleotide function in vivo is generally a very time consuming effort that only allows for hypothesis driven subsampling of the full sequence to be analysed. Recent advances in deep sequencing together with highly efficient parallel oligonucleotide synthesis and cloning techniques have, however, opened up for entirely new ways to map genetic function in vivo. Here we present a novel, optimized protocol for the generation of universally applicable, barcode labelled, plasmid libraries. The libraries are designed to enable the production of viral vector preparations assessing coding or non-coding RNA function in vivo. When generating high diversity libraries, it is a challenge to achieve efficient cloning, unambiguous barcoding and detailed characterization using low-cost sequencing technologies. With the presented protocol, diversity of above 3 million uniquely barcoded adeno-associated viral (AAV) plasmids can be achieved in a single reaction through a process achievable in any molecular biology laboratory. This approach opens up for a multitude of in vivo assessments from the evaluation of enhancer and promoter regions to the optimization of genome editing. The generated plasmid libraries are also useful for validation of sequencing clustering algorithms and we here validate the newly presented message passing clustering process named Starcode. PMID:27874090

A Practical Reader in Universal Design for Learning

ERIC Educational Resources Information Center

Rose, David H., Ed.; Meyer, Anne, Ed.

2006-01-01

Universal Design for Learning (UDL) stands at the forefront of contemporary efforts to create universal access to educational curricula for all students, including those with disabilities. The "universal" in UDL does not mean there is a single optimal solution for everyone. Instead, it underscores the need for flexible approaches to…

Genetic Algorithm for Optimization: Preprocessor and Algorithm

NASA Technical Reports Server (NTRS)

Sen, S. K.; Shaykhian, Gholam A.

2006-01-01

Genetic algorithm (GA) inspired by Darwin's theory of evolution and employed to solve optimization problems - unconstrained or constrained - uses an evolutionary process. A GA has several parameters such the population size, search space, crossover and mutation probabilities, and fitness criterion. These parameters are not universally known/determined a priori for all problems. Depending on the problem at hand, these parameters need to be decided such that the resulting GA performs the best. We present here a preprocessor that achieves just that, i.e., it determines, for a specified problem, the foregoing parameters so that the consequent GA is a best for the problem. We stress also the need for such a preprocessor both for quality (error) and for cost (complexity) to produce the solution. The preprocessor includes, as its first step, making use of all the information such as that of nature/character of the function/system, search space, physical/laboratory experimentation (if already done/available), and the physical environment. It also includes the information that can be generated through any means - deterministic/nondeterministic/graphics. Instead of attempting a solution of the problem straightway through a GA without having/using the information/knowledge of the character of the system, we would do consciously a much better job of producing a solution by using the information generated/created in the very first step of the preprocessor. We, therefore, unstintingly advocate the use of a preprocessor to solve a real-world optimization problem including NP-complete ones before using the statistically most appropriate GA. We also include such a GA for unconstrained function optimization problems.

A universal TagModule collection for parallel genetic analysis of microorganisms

PubMed Central

Oh, Julia; Fung, Eula; Price, Morgan N.; Dehal, Paramvir S.; Davis, Ronald W.; Giaever, Guri; Nislow, Corey; Arkin, Adam P.; Deutschbauer, Adam

2010-01-01

Systems-level analyses of non-model microorganisms are limited by the existence of numerous uncharacterized genes and a corresponding over-reliance on automated computational annotations. One solution to this challenge is to disrupt gene function using DNA tag technology, which has been highly successful in parallelizing reverse genetics in Saccharomyces cerevisiae and has led to discoveries in gene function, genetic interactions and drug mechanism of action. To extend the yeast DNA tag methodology to a wide variety of microorganisms and applications, we have created a universal, sequence-verified TagModule collection. A hallmark of the 4280 TagModules is that they are cloned into a Gateway entry vector, thus facilitating rapid transfer to any compatible genetic system. Here, we describe the application of the TagModules to rapidly generate tagged mutants by transposon mutagenesis in the metal-reducing bacterium Shewanella oneidensis MR-1 and the pathogenic yeast Candida albicans. Our results demonstrate the optimal hybridization properties of the TagModule collection, the flexibility in applying the strategy to diverse microorganisms and the biological insights that can be gained from fitness profiling tagged mutant collections. The publicly available TagModule collection is a platform-independent resource for the functional genomics of a wide range of microbial systems in the post-genome era. PMID:20494978

Optimal Cost Avoidance Investment and Pricing Strategies for Performance-Based Post-Production Service Contracts

DTIC Science & Technology

2011-04-30

a BS degree in Mathematics and an MS degree in Statistics and Financial and Actuarial Mathematics from Kiev National Taras Shevchenko University...degrees from Rutgers University in Industrial Engineering (PhD and MS) and Statistics (MS) and from Universidad Nacional Autonoma de Mexico in Actuarial ...Science. His research efforts focus on developing mathematical models for the analysis, computation, and optimization of system performance with

Symbiotic Optimization of Behavior

DTIC Science & Technology

2015-05-01

SYMBIOTIC OPTIMIZATION OF BEHAVIOR UNIVERSITY OF WASHINGTON MAY 2015 FINAL TECHNICAL REPORT APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED...2014 4. TITLE AND SUBTITLE SYMBIOTIC OPTIMIZATION OF BEHAVIOR 5a. CONTRACT NUMBER FA8750-12-1-0304 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT

Optimizing DNA assembly based on statistical language modelling.

PubMed

Fang, Gang; Zhang, Shemin; Dong, Yafei

2017-12-15

By successively assembling genetic parts such as BioBrick according to grammatical models, complex genetic constructs composed of dozens of functional blocks can be built. However, usually every category of genetic parts includes a few or many parts. With increasing quantity of genetic parts, the process of assembling more than a few sets of these parts can be expensive, time consuming and error prone. At the last step of assembling it is somewhat difficult to decide which part should be selected. Based on statistical language model, which is a probability distribution P(s) over strings S that attempts to reflect how frequently a string S occurs as a sentence, the most commonly used parts will be selected. Then, a dynamic programming algorithm was designed to figure out the solution of maximum probability. The algorithm optimizes the results of a genetic design based on a grammatical model and finds an optimal solution. In this way, redundant operations can be reduced and the time and cost required for conducting biological experiments can be minimized. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

A New Ensemble Canonical Correlation Prediction Scheme for Seasonal Precipitation

NASA Technical Reports Server (NTRS)

Kim, Kyu-Myong; Lau, William K. M.; Li, Guilong; Shen, Samuel S. P.; Lau, William K. M. (Technical Monitor)

2001-01-01

Department of Mathematical Sciences, University of Alberta, Edmonton, Canada This paper describes the fundamental theory of the ensemble canonical correlation (ECC) algorithm for the seasonal climate forecasting. The algorithm is a statistical regression sch eme based on maximal correlation between the predictor and predictand. The prediction error is estimated by a spectral method using the basis of empirical orthogonal functions. The ECC algorithm treats the predictors and predictands as continuous fields and is an improvement from the traditional canonical correlation prediction. The improvements include the use of area-factor, estimation of prediction error, and the optimal ensemble of multiple forecasts. The ECC is applied to the seasonal forecasting over various parts of the world. The example presented here is for the North America precipitation. The predictor is the sea surface temperature (SST) from different ocean basins. The Climate Prediction Center's reconstructed SST (1951-1999) is used as the predictor's historical data. The optimally interpolated global monthly precipitation is used as the predictand?s historical data. Our forecast experiments show that the ECC algorithm renders very high skill and the optimal ensemble is very important to the high value.

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

PubMed

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

2017-04-01

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

Robotic system construction with mechatronic components inverted pendulum: humanoid robot

NASA Astrophysics Data System (ADS)

Sandru, Lucian Alexandru; Crainic, Marius Florin; Savu, Diana; Moldovan, Cristian; Dolga, Valer; Preitl, Stefan

2017-03-01

Mechatronics is a new methodology used to achieve an optimal design of an electromechanical product. This methodology is collection of practices, procedures and rules used by those who work in particular branch of knowledge or discipline. Education in mechatronics at the Polytechnic University Timisoara is organized on three levels: bachelor, master and PhD studies. These activities refer and to design the mechatronics systems. In this context the design, implementation and experimental study of a family of mechatronic demonstrator occupy an important place. In this paper, a variant for a mechatronic demonstrator based on the combination of the electrical and mechanical components is proposed. The demonstrator, named humanoid robot, is equivalent with an inverted pendulum. Is presented the analyze of components for associated functions of the humanoid robot. This type of development the mechatronic systems by the combination of hardware and software, offers the opportunity to build the optimal solutions.

Egg Yolk Factor of Staphylococcus aureus II. Characterization of the Lipase Activity

PubMed Central

Shah, D. B.; Wilson, J. B.

1965-01-01

Shah, D. B. (University of Wisconsin, Madison), and J. B. Wilson. Egg yolk factor of Staphylococcus aureus. II. Characterization of the lipase activity. J. Bacteriol. 89:949–953. 1965.—The staphylococcal egg yolk factor was characterized as a lipase. The enzyme had an optimal pH of 7.8, but the optimal pH of stability was 7. Substrate specificity data showed that the relative rate of hydrolysis was lowest with triacetin as substrate, was maximal with tributyrin, and decreased as the chain length of the acyl moieties increased. The enzyme showed an absolute requirement for a fatty acid acceptor like calcium, when the acyl moiety of triglyceride was water-insoluble. Magnesium, strontium, and barium functioned equally well as fatty acid acceptors. The enzyme was able to hydrolyze coconut oil, peanut oil, olive oil, and egg yolk oil. PMID:14276120

Quantum Corral Wave-function Engineering

NASA Astrophysics Data System (ADS)

Correa, Alfredo; Reboredo, Fernando; Balseiro, Carlos

2005-03-01

We present a theoretical method for the design and optimization of quantum corrals[1] with specific electronic properties. Taking advantage that spins are subject to a RKKY interaction that is directly controlled by the scattering of the quantum corral, we design corral structures that reproduce spin Hamiltonians with coupling constants determined a priori[2]. We solve exactly the bi-dimensional scattering problem for each corral configuration within the s-wave approximation[3] and subsequently the geometry of the quantum corral is optimized by means of simulated annealing[4] and genetic algorithms[5]. We demonstrate the possibility of automatic design of structures with complicated target electronic properties[6]. This work was performed under the auspices of the US Department of Energy by the University of California at the LLNL under contract no W-7405-Eng-48. [1] M. F. Crommie, C. P. Lutz and D. M. Eigler, Nature 403, 512 (2000) [2] D. P. DiVincenzo et al., Nature 408, 339 (2000) [3] G. A. Fiete and E. J. Heller, Rev. Mod. Phys. 75, 933 (2003) [4] M. R. A. T. N. Metropolis et al., J. Chem. Phys. 1087 (1953) [5] E. Aarts and J. K. Lenstra, eds. Local search in combinatorial problems (Princeton University Press, 1997) [6] A. A. Correa, F. Reboredo and C. Balseiro, Phys. Rev. B (in press).

Divergent pathways to influence: Cognition and behavior differentially mediate the effects of optimism on physical and mental quality of life in Chinese university students.

PubMed

Ramsay, Jonathan E; Yang, Fang; Pang, Joyce S; Lai, Ching-Man; Ho, Roger Cm; Mak, Kwok-Kei

2015-07-01

Previous research has indicated that both cognitive and behavioral variables mediate the positive effect of optimism on quality of life; yet few attempts have been made to accommodate these constructs into a single explanatory framework. Adopting Fredrickson's broaden-and-build perspective, we examined the relationships between optimism, self-rated health, resilience, exercise, and quality of life in 365 Chinese university students using path analysis. For physical quality of life, a two-stage model, in which the effects of optimism were sequentially mediated by cognitive and behavioral variables, provided the best fit. A one-stage model, with full mediation by cognitive variables, provided the best fit for mental quality of life. This suggests that optimism influences physical and mental quality of life via different pathways. © The Author(s) 2013.

Optimal inverse functions created via population-based optimization.

PubMed

Jennings, Alan L; Ordóñez, Raúl

2014-06-01

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

Optimality principles in the regulation of metabolic networks.

PubMed

Berkhout, Jan; Bruggeman, Frank J; Teusink, Bas

2012-08-29

One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular "task" of the network-its function-should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide.

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

Joel E. Kostka

This project represented a joint effort between Oak Ridge National Laboratory (ORNL), the University of Tennessee (UT), and Florida State University (FSU). ORNL served as the lead in-stitution with Dr. A.V. Palumbo responsible for project coordination, integration, and deliver-ables. In situ uranium bioremediation is focused on biostimulating indigenous microorganisms through a combination of pH neutralization and the addition of large amounts of electron donor. Successful biostimulation of U(VI) reduction has been demonstrated in the field and in the laboratory. However, little data is available on the dynamics of microbial populations capable of U(VI) reduction, and the differences in the microbialmore » community dynamics between proposed electron donors have not been explored. In order to elucidate the potential mechanisms of U(VI) reduction for optimization of bioremediation strategies, structure-function relationships of microbial populations were investigated in microcosms of subsurface materials cocontaminated with radionuclides and nitrate from the Oak Ridge Field Research Center (ORFRC), Oak Ridge, Tennessee.« less

Designing scalable product families by the radial basis function-high-dimensional model representation metamodelling technique

NASA Astrophysics Data System (ADS)

Pirmoradi, Zhila; Haji Hajikolaei, Kambiz; Wang, G. Gary

2015-10-01

Product family design is cost-efficient for achieving the best trade-off between commonalization and diversification. However, for computationally intensive design functions which are viewed as black boxes, the family design would be challenging. A two-stage platform configuration method with generalized commonality is proposed for a scale-based family with unknown platform configuration. Unconventional sensitivity analysis and information on variation in the individual variants' optimal design are used for platform configuration design. Metamodelling is employed to provide the sensitivity and variable correlation information, leading to significant savings in function calls. A family of universal electric motors is designed for product performance and the efficiency of this method is studied. The impact of the employed parameters is also analysed. Then, the proposed method is modified for obtaining higher commonality. The proposed method is shown to yield design solutions with better objective function values, allowable performance loss and higher commonality than the previously developed methods in the literature.

Genetic algorithms - What fitness scaling is optimal?

NASA Technical Reports Server (NTRS)

Kreinovich, Vladik; Quintana, Chris; Fuentes, Olac

1993-01-01

A problem of choosing the best scaling function as a mathematical optimization problem is formulated and solved under different optimality criteria. A list of functions which are optimal under different criteria is presented which includes both the best functions empirically proved and new functions that may be worth trying.

Whole dietary patterns to optimize cognitive function for military mission-readiness: a systematic review and recommendations for the field.

PubMed

Teo, Lynn; Crawford, Cindy; Yehuda, Rachel; Jaghab, Danny; Bingham, John J; Gallon, Matthew D; O'Connell, Meghan L; Chittum, Holly K; Arzola, Sonya M; Berry, Kevin

2017-06-01

Optimizing cognitive performance, particularly during times of high stress, is a prerequisite to mission-readiness among military personnel. It has been of interest to determine whether such performance could be enhanced through diet. This systematic review assesses the quality of the evidence for whole dietary patterns across various outcomes related to cognitive function in healthy adult populations to develop research recommendations for the military. PubMed, CINAHL, Embase, PsycInfo, and the Cochrane Library were searched. Peer-reviewed randomized controlled trials published in the English language were eligible. Fifteen included trials were assessed for methodological quality, and descriptive data were extracted. Of the 6 acceptable-quality studies, 1 demonstrated statistically nonsignificant results, whereas the other 5 showed conflicting results across the cognitive outcomes assessed. Due to the heterogeneity across the included studies, no recommendations could be reached concerning whether certain whole dietary patterns have an effect on cognitive outcomes in healthy populations. Specific recommendations for future research are offered. © The Author(s) 2017. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Recent Developments in the Use of Intralesional Injections Keloid Treatment

PubMed Central

Trisliana Perdanasari, Aurelia; Lazzeri, Davide; Su, Weijie; Xi, Wenjing; Zheng, Zhang; Ke, Li; Min, Peiru; Feng, Shaoqing; Persichetti, Paolo

2014-01-01

Keloid scars are often considered aesthetically unattractive and frustrating problems that occur following injuries. They cause functional and cosmetic deformities, displeasure, itching, pain, and psychological stress and possibly affect joint movement. The combination of these factors ultimately results in a compromised quality of life and diminished functional performance. Various methods have been implemented to improve keloid scars using both surgical and non-surgical approaches. However, it has proven to be a challenge to identify a universal treatment that can deliver optimal results for all types of scars. Through a PubMed search, we explored most of the literature that is available about the intralesional injection treatment of hypertrophic scars and keloids and highlights both current (corticosteroid, 5-fluorouracil, bleomycin, interferon, cryotherapy and verapamil) and future treatments (interleukin-10 and botulinum toxin type A). The reference lists of retrieved articles were also analysed. Information was gathered about the mechanism of each injection treatment, its benefits and associated adverse reactions, and possible strategies to address adverse reactions to provide reliable guidelines for determining the optimal treatment for particular types of keloid scars. This article will benefit practitioners by outlining evidence-based treatment strategies using intralesional injections for patients with hypertrophic scars and keloids. PMID:25396172

Sequencing bilateral and unilateral task-oriented training versus task oriented training alone to improve arm function in individuals with chronic stroke.

PubMed

McCombe Waller, Sandy; Whitall, Jill; Jenkins, Toye; Magder, Laurence S; Hanley, Daniel F; Goldberg, Andrew; Luft, Andreas R

2014-12-14

Recovering useful hand function after stroke is a major scientific challenge for patients with limited motor recovery. We hypothesized that sequential training beginning with proximal bilateral followed by unilateral task oriented training is superior to time-matched unilateral training alone. Proximal bilateral training could optimally prepare the motor system to respond to the more challenging task-oriented training. Twenty-six participants with moderate severity hemiparesis Intervention: PARTICIPANTS received either 6-weeks of bilateral proximal training followed sequentially by 6-weeks unilateral task-oriented training (COMBO) or 12-weeks of unilateral task-oriented training alone (SAEBO). A subset of 8 COMB0 and 9 SAEBO participants underwent three functional magnetic resonance imaging (fMRI) scans of hand and elbow movement every 6 weeks. Fugl-Meyer Upper extremity scale, Modified Wolf Motor Function Test, University of Maryland Arm Questionnaire for Stroke, Motor cortex activation (fMRI). The COMBO group demonstrated significantly greater gains between baseline and 12-weeks over all outcome measures (p = .018 based on a MANOVA test) and specifically in the Modified Wolf Motor Function test (time). Both groups demonstrated within-group gains on the Fugl-Meyer Upper Extremity test (impairment) and University of Maryland Arm Questionnaire for Stroke (functional use). fMRI subset analyses showed motor cortex (primary and premotor) activation during hand movement was significantly increased by sequential combination training but not by task-oriented training alone. Sequentially combining a proximal bilateral before a unilateral task-oriented training may be an effective way to facilitate gains in arm and hand function in those with moderate to severe paresis post-stroke compared to unilateral task oriented training alone.

Shortened OR time and decreased patient risk through use of a modular surgical instrument with artificial intelligence.

PubMed

Miller, David J; Nelson, Carl A; Oleynikov, Dmitry

2009-05-01

With a limited number of access ports, minimally invasive surgery (MIS) often requires the complete removal of one tool and reinsertion of another. Modular or multifunctional tools can be used to avoid this step. In this study, soft computing techniques are used to optimally arrange a modular tool's functional tips, allowing surgeons to deliver treatment of improved quality in less time, decreasing overall cost. The investigators watched University Medical Center surgeons perform MIS procedures (e.g., cholecystectomy and Nissen fundoplication) and recorded the procedures to digital video. The video was then used to analyze the types of instruments used, the duration of each use, and the function of each instrument. These data were aggregated with fuzzy logic techniques using four membership functions to quantify the overall usefulness of each tool. This allowed subsequent optimization of the arrangement of functional tips within the modular tool to decrease overall time spent changing instruments during simulated surgical procedures based on the video recordings. Based on a prototype and a virtual model of a multifunction laparoscopic tool designed by the investigators that can interchange six different instrument tips through the tool's shaft, the range of tool change times is approximately 11-13 s. Using this figure, estimated time savings for the procedures analyzed ranged from 2.5 to over 32 min, and on average, total surgery time can be reduced by almost 17% by using the multifunction tool.

Positive factors associated with quality of life among Chinese patients with renal carcinoma: a cross-sectional study.

PubMed

Liu, Jiao; Gong, Da-Xin; Zeng, Yu; Li, Zhen-Hua; Kong, Chui-Ze

2018-01-01

Quality of life and positive psychological variables has become a focus of concern in patients with renal carcinoma. However, the integrative effects of positive psychological variables on the illness have seldom been reported. The aims of this study were to evaluate the quality of life and the integrative effects of hope, resilience and optimism on the quality of life among Chinese renal carcinoma patients. A cross-sectional study was conducted at the First Hospital of China Medical University. 284 participants completed questionnaires consisting of demographic and clinical characteristics, EORTC QLQ-C30, Adult Hope Scale, Resilience Scale-14 and Life Orientation Scale-Revised from July 2013 to July 2014. Pearson's correlation and hierarchical regression analyses were performed to explore the effects of related factors. Hope, resilience and optimism were significantly associated with quality of life. Hierarchical regression analyses indicated that hope, resilience and optimism as a whole accounted for 9.8, 24.4 and 21.9% of the variance in the global health status, functioning status and symptom status, respectively. The low level of quality of life for Chinese renal carcinoma patients should receive more attention from Chinese medical institutions. Psychological interventions to increase hope, resilience and optimism may be essential to enhancing the quality of life of Chinese cancer patients.

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…

The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development.

PubMed

Howell, Brittany R; Styner, Martin A; Gao, Wei; Yap, Pew-Thian; Wang, Li; Baluyot, Kristine; Yacoub, Essa; Chen, Geng; Potts, Taylor; Salzwedel, Andrew; Li, Gang; Gilmore, John H; Piven, Joseph; Smith, J Keith; Shen, Dinggang; Ugurbil, Kamil; Zhu, Hongtu; Lin, Weili; Elison, Jed T

2018-03-22

The human brain undergoes extensive and dynamic growth during the first years of life. The UNC/UMN Baby Connectome Project (BCP), one of the Lifespan Connectome Projects funded by NIH, is an ongoing study jointly conducted by investigators at the University of North Carolina at Chapel Hill and the University of Minnesota. The primary objective of the BCP is to characterize brain and behavioral development in typically developing infants across the first 5 years of life. The ultimate goals are to chart emerging patterns of structural and functional connectivity during this period, map brain-behavior associations, and establish a foundation from which to further explore trajectories of health and disease. To accomplish these goals, we are combining state of the art MRI acquisition and analysis techniques, including high-resolution structural MRI (T1-and T2-weighted images), diffusion imaging (dMRI), and resting state functional connectivity MRI (rfMRI). While the overall design of the BCP largely is built on the protocol developed by the Lifespan Human Connectome Project (HCP), given the unique age range of the BCP cohort, additional optimization of imaging parameters and consideration of an age appropriate battery of behavioral assessments were needed. Here we provide the overall study protocol, including approaches for subject recruitment, strategies for imaging typically developing children 0-5 years of age without sedation, imaging protocol and optimization, a description of the battery of behavioral assessments, and QA/QC procedures. Combining HCP inspired neuroimaging data with well-established behavioral assessments during this time period will yield an invaluable resource for the scientific community. Copyright © 2018 Elsevier Inc. All rights reserved.

Analyzing comprehensive QoS with security constraints for services composition applications in wireless sensor networks.

PubMed

Xiong, Naixue; Wu, Zhao; Huang, Yannong; Xu, Degang

2014-12-01

Services composition is fundamental to software development in multi-service wireless sensor networks (WSNs). The quality of service (QoS) of services composition applications (SCAs) are confronted with severe challenges due to the open, dynamic, and complex natures of WSNs. Most previous research separated various QoS indices into different fields and studied them individually due to the computational complexity. This approach ignores the mutual influence between these QoS indices, and leads to a non-comprehensive and inaccurate analysis result. The universal generating function (UGF) shows the speediness and precision in QoS analysis. However, only one QoS index at a time can be analyzed by the classic UGF. In order to efficiently analyze the comprehensive QoS of SCAs, this paper proposes an improved UGF technique-vector universal generating function (VUGF)-which considers the relationship between multiple QoS indices, including security, and can simultaneously analyze multiple QoS indices. The numerical examples demonstrate that it can be used for the evaluation of the comprehensive QoS of SCAs subjected to the security constraint in WSNs. Therefore, it can be effectively applied to the optimal design of multi-service WSNs.

Analyzing Comprehensive QoS with Security Constraints for Services Composition Applications in Wireless Sensor Networks

PubMed Central

Xiong, Naixue; Wu, Zhao; Huang, Yannong; Xu, Degang

2014-01-01

Services composition is fundamental to software development in multi-service wireless sensor networks (WSNs). The quality of service (QoS) of services composition applications (SCAs) are confronted with severe challenges due to the open, dynamic, and complex natures of WSNs. Most previous research separated various QoS indices into different fields and studied them individually due to the computational complexity. This approach ignores the mutual influence between these QoS indices, and leads to a non-comprehensive and inaccurate analysis result. The universal generating function (UGF) shows the speediness and precision in QoS analysis. However, only one QoS index at a time can be analyzed by the classic UGF. In order to efficiently analyze the comprehensive QoS of SCAs, this paper proposes an improved UGF technique—vector universal generating function (VUGF)—which considers the relationship between multiple QoS indices, including security, and can simultaneously analyze multiple QoS indices. The numerical examples demonstrate that it can be used for the evaluation of the comprehensive QoS of SCAs subjected to the security constraint in WSNs. Therefore, it can be effectively applied to the optimal design of multi-service WSNs. PMID:25470488

Characterisation of edge turbulence in relation to edge magnetic field configuration in L-mode plasmas in the Mega Amp Spherical Tokamak.

NASA Astrophysics Data System (ADS)

Dewhurst, J.; Hnat, B.; Dudson, B.; Dendy, R. O.; Counsell, G. F.; Kirk, A.

2007-12-01

Almost all astrophysical and magnetically confined fusion plasmas are turbulent. Here, we examine ion saturation current (Isat) measurements of edge plasma turbulence for three MAST L-mode plasmas that differ primarily in their edge magnetic field configurations. First, absolute moments of the coarse grained data are examined to obtain accurate values of scaling exponents. The dual scaling behaviour is identified in all samples, with the temporal scale τ ≍ 40-60 μs separating the two regimes. Strong universality is then identified in the functional form of the probability density function (PDF) for Isat fluctuations, which is well approximated by the Fréchet distribution on temporal scales τ ≤ 40μs. For temporal scales τ > 40μs, the PDFs appear to converge to the Gumbel distribution, which has been previously identified as a universal feature of many other complex phenomena. The optimal fitting parameters k=1.15 for Fréchet and a=1.35 for Gumbel provide a simple quantitative characterisation of the full spectrum of fluctuations. We conclude that, to good approximation, the properties of the edge turbulence are independent of the edge magnetic field configuration.

Characterization of edge turbulence in relation to edge magnetic field configuration in Ohmic L-mode plasmas in the Mega Amp Spherical Tokamak

NASA Astrophysics Data System (ADS)

Hnat, B.; Dudson, B. D.; Dendy, R. O.; Counsell, G. F.; Kirk, A.; MAST Team

2008-08-01

Ion saturation current (Isat) measurements of edge plasma turbulence are analysed for six MAST L-mode plasmas that differ primarily in their edge magnetic field configurations. The analysis techniques are designed to capture the strong nonlinearities of the datasets. First, absolute moments of the data are examined to obtain accurate values of scaling exponents. This confirms dual scaling behaviour in all samples, with the temporal scale τ ≈ 40-60 µs separating the two regimes. Strong universality is then identified in the functional form of the probability density function (PDF) for Isat fluctuations, which is well approximated by the Fréchet distribution on temporal scales τ <= 40 µs. For temporal scales τ > 40 µs, the PDFs appear to converge to the Gumbel distribution, which has been previously identified as a universal feature of many other complex phenomena. The optimal fitting parameters k = 1.15 for Fréchet and a = 1.35 for Gumbel provide a simple quantitative characterization of the full spectrum of fluctuations. It is concluded that, to good approximation, the properties of the edge turbulence are independent of the edge magnetic field configuration.

On the Convergence Analysis of the Optimized Gradient Method.

PubMed

Kim, Donghwan; Fessler, Jeffrey A

2017-01-01

This paper considers the problem of unconstrained minimization of smooth convex functions having Lipschitz continuous gradients with known Lipschitz constant. We recently proposed the optimized gradient method for this problem and showed that it has a worst-case convergence bound for the cost function decrease that is twice as small as that of Nesterov's fast gradient method, yet has a similarly efficient practical implementation. Drori showed recently that the optimized gradient method has optimal complexity for the cost function decrease over the general class of first-order methods. This optimality makes it important to study fully the convergence properties of the optimized gradient method. The previous worst-case convergence bound for the optimized gradient method was derived for only the last iterate of a secondary sequence. This paper provides an analytic convergence bound for the primary sequence generated by the optimized gradient method. We then discuss additional convergence properties of the optimized gradient method, including the interesting fact that the optimized gradient method has two types of worstcase functions: a piecewise affine-quadratic function and a quadratic function. These results help complete the theory of an optimal first-order method for smooth convex minimization.

On the Convergence Analysis of the Optimized Gradient Method

PubMed Central

Kim, Donghwan; Fessler, Jeffrey A.

2016-01-01

This paper considers the problem of unconstrained minimization of smooth convex functions having Lipschitz continuous gradients with known Lipschitz constant. We recently proposed the optimized gradient method for this problem and showed that it has a worst-case convergence bound for the cost function decrease that is twice as small as that of Nesterov’s fast gradient method, yet has a similarly efficient practical implementation. Drori showed recently that the optimized gradient method has optimal complexity for the cost function decrease over the general class of first-order methods. This optimality makes it important to study fully the convergence properties of the optimized gradient method. The previous worst-case convergence bound for the optimized gradient method was derived for only the last iterate of a secondary sequence. This paper provides an analytic convergence bound for the primary sequence generated by the optimized gradient method. We then discuss additional convergence properties of the optimized gradient method, including the interesting fact that the optimized gradient method has two types of worstcase functions: a piecewise affine-quadratic function and a quadratic function. These results help complete the theory of an optimal first-order method for smooth convex minimization. PMID:28461707

Countergradient variation in locomotor performance of two sympatric Polynesian skinks (Emoia impar, Emoia cyanura).

PubMed

McElroy, Matthew T

2014-01-01

Physiological function in ectotherms is tightly linked to body temperature. As a result, the thermal sensitivity of physiological function may evolve to optimize fitness across different thermal environments. One hypothesis for the evolution of thermal sensitivity, coadaptation, predicts that optimal temperatures for performance should evolve to match the temperatures that an organism experiences in nature. Another hypothesis, countergradient variation, posits that genetic variation can compensate for decreased performance in cool environments, leading to physiological phenotypes that do not track environmental temperatures. On Mo'orea, French Polynesia, thermal ecology and physiology were studied in two morphologically similar skinks that differ in habitat use. Previous studies show that Emoia impar tends to inhabit closed-canopy and interior habitats that are cooler compared to those inhabited by Emoia cyanura, but these differences had not been quantified on Mo'orea. The goal of this study was to determine whether this pattern of habitat partitioning exists on Mo'orea and relates to interspecific differences in thermal physiology and to evaluate whether the evolution of thermal sensitivity supports coadaptation or countergradient variation. I found that E. impar inhabits closed-canopy habitats with cooler substrates and with higher altitudes compared to habitats of E. cyanura. Although the two species do not differ significantly in critical thermal minimum, E. impar has a significantly lower preferred body temperature and critical thermal maximum than does E. cyanura. Despite a preference for cooler habitats and temperatures, E. impar has a warmer optimal temperature for sprint speed and sprints faster than E. cyanura at all temperatures, which supports the countergradient model of thermal adaptation. These results are robust to three different curve-fitting functions and support the view that generalist/specialist trade-offs do not universally constrain the evolution of performance curves.

Detecting independent and recurrent copy number aberrations using interval graphs.

PubMed

Wu, Hsin-Ta; Hajirasouliha, Iman; Raphael, Benjamin J

2014-06-15

Somatic copy number aberrations SCNAS: are frequent in cancer genomes, but many of these are random, passenger events. A common strategy to distinguish functional aberrations from passengers is to identify those aberrations that are recurrent across multiple samples. However, the extensive variability in the length and position of SCNA: s makes the problem of identifying recurrent aberrations notoriously difficult. We introduce a combinatorial approach to the problem of identifying independent and recurrent SCNA: s, focusing on the key challenging of separating the overlaps in aberrations across individuals into independent events. We derive independent and recurrent SCNA: s as maximal cliques in an interval graph constructed from overlaps between aberrations. We efficiently enumerate all such cliques, and derive a dynamic programming algorithm to find an optimal selection of non-overlapping cliques, resulting in a very fast algorithm, which we call RAIG (Recurrent Aberrations from Interval Graphs). We show that RAIG outperforms other methods on simulated data and also performs well on data from three cancer types from The Cancer Genome Atlas (TCGA). In contrast to existing approaches that employ various heuristics to select independent aberrations, RAIG optimizes a well-defined objective function. We show that this allows RAIG to identify rare aberrations that are likely functional, but are obscured by overlaps with larger passenger aberrations. http://compbio.cs.brown.edu/software. © The Author 2014. Published by Oxford University Press.

Phytochemicals to optimize cognitive function for military mission-readiness: a systematic review and recommendations for the field.

PubMed

Teo, Lynn; Crawford, Cindy; Snow, James; Deuster, Patricia A; Bingham, John J; Gallon, Matthew D; O'Connell, Meghan L; Chittum, Holly K; Arzola, Sonya M; Berry, Kevin

2017-06-01

Optimizing cognitive performance and preventing cognitive impairments that result from exposure to high-stress situations are important to ensure mission-readiness for military personnel. This systematic review assesses the quality of the evidence for plant-based foods and beverages, or their phytochemical constituents, across various outcomes related to cognitive function in healthy adult populations to develop research recommendations for the military. PubMed, CINAHL, Embase, PsycInfo, and the Cochrane Library were searched. Peer-reviewed randomized controlled trials published in the English language were eligible. Twenty-five trials were included and assessed for methodological quality, and descriptive data were extracted. The acceptable (n = 16) to high-quality (n = 4) studies produced either no statistically significant effect or mixed results for enhancing cognitive function. The evidence suggested that healthy populations do not experience significant changes in cognitive performance when consuming soy- and non-soy-sourced isoflavones or cocoa. Heterogeneity among other interventions precluded reaching formal conclusions surrounding the evidence. Research recommendations are offered, including conducting more studies on the effect of plant-based interventions on populations reflective of military populations when exposed to military-like situations. © The Author(s) 2017. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Omega-3 polyunsaturated fatty acids to optimize cognitive function for military mission-readiness: a systematic review and recommendations for the field.

PubMed

Teo, Lynn; Crawford, Cindy; Yehuda, Rachel; Jaghab, Danny; Bingham, John J; Chittum, Holly K; Gallon, Matthew D; O'Connell, Meghan L; Arzola, Sonya M; Berry, Kevin

2017-06-01

There has been interest in identifying whether nutrients might help optimize cognitive performance, especially for the military tasked with ensuring mission-readiness. This systematic review assesses the quality of the evidence for n-3 polyunsaturated fatty acids (PUFAs) across various outcomes related to cognitive function in healthy adult populations in order to develop research recommendations concerning n-3 PUFAs for mission-readiness. PubMed, CINAHL, Embase, PsycInfo, and the Cochrane Library were searched. Peer-reviewed randomized controlled trials published in the English language were eligible. Thirteen included trials were assessed for methodological quality, and descriptive data were extracted. Of the acceptable-quality (n = 8) and high-quality (n = 1) studies, 2 produced no statistically significant results, 5 produced mixed results, and 2 did not report between-group results. Results indicate that ingestion of n-3 PUFAs does not significantly alter cognitive performance in cognitively healthy persons. Studies exposing subjects to adverse circumstances that would be most relevant for drawing conclusions specifically for the military population are lacking. Several research recommendations are offered to enhance understanding of the role of fatty acids on cognitive functioning. © The Author(s) 2017. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Optimality Principles in the Regulation of Metabolic Networks

PubMed Central

Berkhout, Jan; Bruggeman, Frank J.; Teusink, Bas

2012-01-01

One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular “task” of the network—its function—should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide. PMID:24957646

A generalised optimal linear quadratic tracker with universal applications. Part 2: discrete-time systems

NASA Astrophysics Data System (ADS)

Ebrahimzadeh, Faezeh; Tsai, Jason Sheng-Hong; Chung, Min-Ching; Liao, Ying Ting; Guo, Shu-Mei; Shieh, Leang-San; Wang, Li

2017-01-01

Contrastive to Part 1, Part 2 presents a generalised optimal linear quadratic digital tracker (LQDT) with universal applications for the discrete-time (DT) systems. This includes (1) a generalised optimal LQDT design for the system with the pre-specified trajectories of the output and the control input and additionally with both the input-to-output direct-feedthrough term and known/estimated system disturbances or extra input/output signals; (2) a new optimal filter-shaped proportional plus integral state-feedback LQDT design for non-square non-minimum phase DT systems to achieve a minimum-phase-like tracking performance; (3) a new approach for computing the control zeros of the given non-square DT systems; and (4) a one-learning-epoch input-constrained iterative learning LQDT design for the repetitive DT systems.

A Model of College Tuition Maximization

ERIC Educational Resources Information Center

Bosshardt, Donald I.; Lichtenstein, Larry; Zaporowski, Mark P.

2009-01-01

This paper develops a series of models for optimal tuition pricing for private colleges and universities. The university is assumed to be a profit maximizing, price discriminating monopolist. The enrollment decision of student's is stochastic in nature. The university offers an effective tuition rate, comprised of stipulated tuition less financial…

Land-Grant University-Industry Relationships in Biotechnology: A Comparison with the Non-Land-Grant Research Universities.

ERIC Educational Resources Information Center

Curry, James; Kenney, Martin

1990-01-01

Presents study of industrial involvement in biotechnology research, comparing faculty surveys from land-grant colleges of agriculture and nonagricultural research universities. Agricultural biotechnologists report higher industrial involvement and more optimism about it. Industrial funding levels shown as significant factor in activities and…

Topology Trivialization and Large Deviations for the Minimum in the Simplest Random Optimization

NASA Astrophysics Data System (ADS)

Fyodorov, Yan V.; Le Doussal, Pierre

2014-01-01

Finding the global minimum of a cost function given by the sum of a quadratic and a linear form in N real variables over (N-1)-dimensional sphere is one of the simplest, yet paradigmatic problems in Optimization Theory known as the "trust region subproblem" or "constraint least square problem". When both terms in the cost function are random this amounts to studying the ground state energy of the simplest spherical spin glass in a random magnetic field. We first identify and study two distinct large-N scaling regimes in which the linear term (magnetic field) leads to a gradual topology trivialization, i.e. reduction in the total number {N}_{tot} of critical (stationary) points in the cost function landscape. In the first regime {N}_{tot} remains of the order N and the cost function (energy) has generically two almost degenerate minima with the Tracy-Widom (TW) statistics. In the second regime the number of critical points is of the order of unity with a finite probability for a single minimum. In that case the mean total number of extrema (minima and maxima) of the cost function is given by the Laplace transform of the TW density, and the distribution of the global minimum energy is expected to take a universal scaling form generalizing the TW law. Though the full form of that distribution is not yet known to us, one of its far tails can be inferred from the large deviation theory for the global minimum. In the rest of the paper we show how to use the replica method to obtain the probability density of the minimum energy in the large-deviation approximation by finding both the rate function and the leading pre-exponential factor.

Optimal time travel in the Gödel universe

NASA Astrophysics Data System (ADS)

Natário, José

2012-04-01

Using the theory of optimal rocket trajectories in general relativity, recently developed in Henriques and Natário (2011), we present a candidate for the minimum total integrated acceleration closed timelike curve in the Gödel universe, and give evidence for its minimality. The total integrated acceleration of this curve is lower than Malament's conjectured value (Malament 1984), as was already implicit in the work of Manchak (Gen. Relativ. Gravit. 51-60, 2011); however, Malament's conjecture does seem to hold for periodic closed timelike curves.

Autonomous Control Modes and Optimized Path Guidance for Shipboard Landing in High Sea States

DTIC Science & Technology

2016-08-12

Performing Organization: The Pennsylvania State University Department of Aerospace Engineering 231C Hammond Building University Park, PA 16802 Attn...Plant Models Used in the Study The H-60 class model was developed and distributed by ART to both NAVAIR and Penn State research teams. The model...To) 07 109 I 201 4 tD 07 I 08 12016 ’t TITLE AND SUBTITLE Autonomous Control Modes and Optimized Path Guidance for Shipboard Landing in High Sea States

The Relationship between Optimism-Pessimism and Personality Traits among Students in the Hashemite University

ERIC Educational Resources Information Center

Mahasneh, Ahmad M.; Al-Zoubi, Zohair H.; Batayeneh, Omar T.

2013-01-01

This study aimed to examine the correlation between optimism-pessimism and personality traits (extraversion, introversion, emotional stability and neuroticism), also aimed to identify the prevalence of optimism and pessimism in the study sample according to the variable sex, academic specialization, level of study, and grade point average. The…

FAST TRACK COMMUNICATION: Criticality-induced universality in ratchets

NASA Astrophysics Data System (ADS)

Chacón, Ricardo

2010-08-01

Conclusive mathematical arguments are presented supporting the ratchet conjecture (Chacón 2007 J. Phys. A: Math. Theor. 40 F413), i.e. the existence of a universal force waveform which optimally enhances directed transport by symmetry breaking. Specifically, such a particular waveform is shown to be unique for both temporal and spatial biharmonic forces, and general (non-perturbative) laws providing the dependence of the strength of directed transport on the force parameters are deduced for these forces. The theory explains previous results for a great diversity of systems subjected to such biharmonic forces and provides a universal quantitative criterion to optimize any application of the ratchet effect induced by symmetry breaking of temporal and spatial biharmonic forces.

Evolution of a designless nanoparticle network into reconfigurable Boolean logic

NASA Astrophysics Data System (ADS)

Bose, S. K.; Lawrence, C. P.; Liu, Z.; Makarenko, K. S.; van Damme, R. M. J.; Broersma, H. J.; van der Wiel, W. G.

2015-12-01

Natural computers exploit the emergent properties and massive parallelism of interconnected networks of locally active components. Evolution has resulted in systems that compute quickly and that use energy efficiently, utilizing whatever physical properties are exploitable. Man-made computers, on the other hand, are based on circuits of functional units that follow given design rules. Hence, potentially exploitable physical processes, such as capacitive crosstalk, to solve a problem are left out. Until now, designless nanoscale networks of inanimate matter that exhibit robust computational functionality had not been realized. Here we artificially evolve the electrical properties of a disordered nanomaterials system (by optimizing the values of control voltages using a genetic algorithm) to perform computational tasks reconfigurably. We exploit the rich behaviour that emerges from interconnected metal nanoparticles, which act as strongly nonlinear single-electron transistors, and find that this nanoscale architecture can be configured in situ into any Boolean logic gate. This universal, reconfigurable gate would require about ten transistors in a conventional circuit. Our system meets the criteria for the physical realization of (cellular) neural networks: universality (arbitrary Boolean functions), compactness, robustness and evolvability, which implies scalability to perform more advanced tasks. Our evolutionary approach works around device-to-device variations and the accompanying uncertainties in performance. Moreover, it bears a great potential for more energy-efficient computation, and for solving problems that are very hard to tackle in conventional architectures.

Optimized universal color palette design for error diffusion

NASA Astrophysics Data System (ADS)

Kolpatzik, Bernd W.; Bouman, Charles A.

1995-04-01

Currently, many low-cost computers can only simultaneously display a palette of 256 color. However, this palette is usually selectable from a very large gamut of available colors. For many applications, this limited palette size imposes a significant constraint on the achievable image quality. We propose a method for designing an optimized universal color palette for use with halftoning methods such as error diffusion. The advantage of a universal color palette is that it is fixed and therefore allows multiple images to be displayed simultaneously. To design the palette, we employ a new vector quantization method known as sequential scalar quantization (SSQ) to allocate the colors in a visually uniform color space. The SSQ method achieves near-optimal allocation, but may be efficiently implemented using a series of lookup tables. When used with error diffusion, SSQ adds little computational overhead and may be used to minimize the visual error in an opponent color coordinate system. We compare the performance of the optimized algorithm to standard error diffusion by evaluating a visually weighted mean-squared-error measure. Our metric is based on the color difference in CIE L*AL*B*, but also accounts for the lowpass characteristic of human contrast sensitivity.

Model selection using cosmic chronometers with Gaussian Processes

NASA Astrophysics Data System (ADS)

Melia, Fulvio; Yennapureddy, Manoj K.

2018-02-01

The use of Gaussian Processes with a measurement of the cosmic expansion rate based solely on the observation of cosmic chronometers provides a completely cosmology-independent reconstruction of the Hubble constant H(z) suitable for testing different models. The corresponding dispersion σH is smaller than ~ 9% over the entire redshift range (lesssim zlesssim 20) of the observations, rivaling many kinds of cosmological measurements available today. We use the reconstructed H(z) function to test six different cosmologies, and show that it favours the Rh=ct universe, which has only one free parameter (i.e., H0) over other models, including Planck ΛCDM . The parameters of the standard model may be re-optimized to improve the fits to the reconstructed H(z) function, but the results have smaller p-values than one finds with Rh=ct.

A New Approach for Semantic Web Matching

NASA Astrophysics Data System (ADS)

Zamanifar, Kamran; Heidary, Golsa; Nematbakhsh, Naser; Mardukhi, Farhad

In this work we propose a new approach for semantic web matching to improve the performance of Web Service replacement. Because in automatic systems we should ensure the self-healing, self-configuration, self-optimization and self-management, all services should be always available and if one of them crashes, it should be replaced with the most similar one. Candidate services are advertised in Universal Description, Discovery and Integration (UDDI) all in Web Ontology Language (OWL). By the help of bipartite graph, we did the matching between the crashed service and a Candidate one. Then we chose the best service, which had the maximum rate of matching. In fact we compare two services' functionalities and capabilities to see how much they match. We found that the best way for matching two web services, is comparing the functionalities of them.

Data transmission system and method

NASA Technical Reports Server (NTRS)

Bruck, Jehoshua (Inventor); Langberg, Michael (Inventor); Sprintson, Alexander (Inventor)

2010-01-01

A method of transmitting data packets, where randomness is added to the schedule. Universal broadcast schedules using encoding and randomization techniques are also discussed, together with optimal randomized schedules and an approximation algorithm for finding near-optimal schedules.

Optimisation of Design of Air Inlets in Air Distribution Channels of a Double-Skin Transparent Façade

NASA Astrophysics Data System (ADS)

Bielek, Boris; Szabó, Daniel; Palko, Milan; Rychtáriková, Monika

2017-12-01

This paper reports on an optimization of design of air inlets in naturally ventilated double-skin transparent facades; the design aims at the proper functioning of these facades from the point of view of their aerodynamic and hydrodynamic behaviour. A comparison was made of five different variants of ventilation louvers used in air openings with different shapes, positions and overall geometry. The aerodynamic response of the louvers was determined by 2D simulations using ANSYS software. The hydrodynamic properties were investigated by conducting driven-rain measurements in a large rain chamber at the Slovak University of Technology in Bratislava.

Developing a discrete event simulation model for university student shuttle buses

NASA Astrophysics Data System (ADS)

Zulkepli, Jafri; Khalid, Ruzelan; Nawawi, Mohd Kamal Mohd; Hamid, Muhammad Hafizan

2017-11-01

Providing shuttle buses for university students to attend their classes is crucial, especially when their number is large and the distances between their classes and residential halls are far. These factors, in addition to the non-optimal current bus services, typically require the students to wait longer which eventually opens a space for them to complain. To considerably reduce the waiting time, providing the optimal number of buses to transport them from location to location and the effective route schedules to fulfil the students' demand at relevant time ranges are thus important. The optimal bus number and schedules are to be determined and tested using a flexible decision platform. This paper thus models the current services of student shuttle buses in a university using a Discrete Event Simulation approach. The model can flexibly simulate whatever changes configured to the current system and report its effects to the performance measures. How the model was conceptualized and formulated for future system configurations are the main interest of this paper.

Optimal trajectories for the aeroassisted flight experiment, 1988-89

NASA Technical Reports Server (NTRS)

Miele, A.

1989-01-01

Research is summarized on optimal trajectories for the aeroassisted flight experiment, performed by the Aero-Astronautics Group of Rice University during the period 1988 through 1989. This research includes the following topics: (1) equations of motion in an Earth-fixed system; (2) equations of motion in an inertial system; (3) formultion of the optimal trajectory problem; (4) results on the optimal trajectory problem; and (5) guidance implications.

Optimal Path Determination for Flying Vehicle to Search an Object

NASA Astrophysics Data System (ADS)

Heru Tjahjana, R.; Heri Soelistyo U, R.; Ratnasari, L.; Irawanto, B.

2018-01-01

In this paper, a method to determine optimal path for flying vehicle to search an object is proposed. Background of the paper is controlling air vehicle to search an object. Optimal path determination is one of the most popular problem in optimization. This paper describe model of control design for a flying vehicle to search an object, and focus on the optimal path that used to search an object. In this paper, optimal control model is used to control flying vehicle to make the vehicle move in optimal path. If the vehicle move in optimal path, then the path to reach the searched object also optimal. The cost Functional is one of the most important things in optimal control design, in this paper the cost functional make the air vehicle can move as soon as possible to reach the object. The axis reference of flying vehicle uses N-E-D (North-East-Down) coordinate system. The result of this paper are the theorems which say that the cost functional make the control optimal and make the vehicle move in optimal path are proved analytically. The other result of this paper also shows the cost functional which used is convex. The convexity of the cost functional is use for guarantee the existence of optimal control. This paper also expose some simulations to show an optimal path for flying vehicle to search an object. The optimization method which used to find the optimal control and optimal path vehicle in this paper is Pontryagin Minimum Principle.

Optimal Government Subsidies to Universities in the Face of Tuition and Enrollment Constraints

ERIC Educational Resources Information Center

Easton, Stephen T.; Rockerbie, Duane W.

2008-01-01

This paper develops a simple static model of an imperfectly competitive university operating under government-imposed constraints on the ability to raise tuition fees and increase enrollments. The model has particular applicability to Canadian universities. Assuming an average cost pricing rule, rules for adequate government subsidies (operating…

University Policies under Varying Market Conditions: The Training of Electrical Engineers.

ERIC Educational Resources Information Center

Eckstein, Zvi; And Others

1988-01-01

Analyzes an Israeli university's problem in optimizing the quality and quantity of electrical engineers in response to fluctuating enrollment. An equilibrium model considers the effect of students' occupation choice and the university's decision on the current and future demand and supply of engineers, in order to predict the equilibrium number of…

Joint University Program for Air Transportation Research, 1985

NASA Technical Reports Server (NTRS)

Morrell, Frederick R. (Compiler)

1987-01-01

Air transportation research being carried on at the Massachusetts Institute of Technology, Princeton University, and Ohio University is discussed. Global Positioning System experiments, Loran-C monitoring, inertial navigation, the optimization of aircraft trajectories through severe microbursts, fault tolerant flight control systems, and expert systems for air traffic control are among the topics covered.

Optimal service distribution in WSN service system subject to data security constraints.

PubMed

Wu, Zhao; Xiong, Naixue; Huang, Yannong; Gu, Qiong

2014-08-04

Services composition technology provides a flexible approach to building Wireless Sensor Network (WSN) Service Applications (WSA) in a service oriented tasking system for WSN. Maintaining the data security of WSA is one of the most important goals in sensor network research. In this paper, we consider a WSN service oriented tasking system in which the WSN Services Broker (WSB), as the resource management center, can map the service request from user into a set of atom-services (AS) and send them to some independent sensor nodes (SN) for parallel execution. The distribution of ASs among these SNs affects the data security as well as the reliability and performance of WSA because these SNs can be of different and independent specifications. By the optimal service partition into the ASs and their distribution among SNs, the WSB can provide the maximum possible service reliability and/or expected performance subject to data security constraints. This paper proposes an algorithm of optimal service partition and distribution based on the universal generating function (UGF) and the genetic algorithm (GA) approach. The experimental analysis is presented to demonstrate the feasibility of the suggested algorithm.

Traj_opt User's Guide

NASA Technical Reports Server (NTRS)

Saunders, David A.

2005-01-01

Trajectory optimization program Traj_opt was developed at Ames Research Center to help assess the potential benefits of ultrahigh temperature ceramic materials applied to reusable space vehicles with sharp noses and wing leading edges. Traj_opt loosely couples the Ames three-degrees-of-freedom trajectory package Traj (see NASA-TM-2004-212847) with the SNOPT optimization package (Stanford University Technical Report SOL 98-1). Traj_opt version January 22, 2003 is covered by this user guide. The program has been applied extensively to entry and ascent abort trajectory calculations for sharp and blunt crew transfer vehicles. The main optimization variables are control points for the angle of attack and bank angle time histories. No propulsion options are provided, but numerous objective functions may be specified and the nonlinear constraints implemented include a distributed surface heating constraint capability. Aero-capture calculations are also treated with an option to minimize orbital eccentricity at apoapsis. Traj_opt runs efficiently on a single processor, using forward or central differences for the gradient calculations. Results may be displayed conveniently with Gnuplot scripts. Control files recommended for five standard reentry and ascent abort trajectories are included along with detailed descriptions of the inputs and outputs.

Optimal Service Distribution in WSN Service System Subject to Data Security Constraints

PubMed Central

Wu, Zhao; Xiong, Naixue; Huang, Yannong; Gu, Qiong

2014-01-01

Services composition technology provides a flexible approach to building Wireless Sensor Network (WSN) Service Applications (WSA) in a service oriented tasking system for WSN. Maintaining the data security of WSA is one of the most important goals in sensor network research. In this paper, we consider a WSN service oriented tasking system in which the WSN Services Broker (WSB), as the resource management center, can map the service request from user into a set of atom-services (AS) and send them to some independent sensor nodes (SN) for parallel execution. The distribution of ASs among these SNs affects the data security as well as the reliability and performance of WSA because these SNs can be of different and independent specifications. By the optimal service partition into the ASs and their distribution among SNs, the WSB can provide the maximum possible service reliability and/or expected performance subject to data security constraints. This paper proposes an algorithm of optimal service partition and distribution based on the universal generating function (UGF) and the genetic algorithm (GA) approach. The experimental analysis is presented to demonstrate the feasibility of the suggested algorithm. PMID:25093346

Optimism in the face of uncertainty supported by a statistically-designed multi-armed bandit algorithm.

PubMed

Kamiura, Moto; Sano, Kohei

2017-10-01

The principle of optimism in the face of uncertainty is known as a heuristic in sequential decision-making problems. Overtaking method based on this principle is an effective algorithm to solve multi-armed bandit problems. It was defined by a set of some heuristic patterns of the formulation in the previous study. The objective of the present paper is to redefine the value functions of Overtaking method and to unify the formulation of them. The unified Overtaking method is associated with upper bounds of confidence intervals of expected rewards on statistics. The unification of the formulation enhances the universality of Overtaking method. Consequently we newly obtain Overtaking method for the exponentially distributed rewards, numerically analyze it, and show that it outperforms UCB algorithm on average. The present study suggests that the principle of optimism in the face of uncertainty should be regarded as the statistics-based consequence of the law of large numbers for the sample mean of rewards and estimation of upper bounds of expected rewards, rather than as a heuristic, in the context of multi-armed bandit problems. Copyright © 2017 Elsevier B.V. All rights reserved.

Development of a large-scale transportation optimization course.

DOT National Transportation Integrated Search

2011-11-01

"In this project, a course was developed to introduce transportation and logistics applications of large-scale optimization to graduate students. This report details what : similar courses exist in other universities, and the methodology used to gath...

Optimization and performance of the Robert Stobie Spectrograph Near-InfraRed detector system

NASA Astrophysics Data System (ADS)

Mosby, Gregory; Indahl, Briana; Eggen, Nathan; Wolf, Marsha; Hooper, Eric; Jaehnig, Kurt; Thielman, Don; Burse, Mahesh

2018-01-01

At the University of Wisconsin-Madison, we are building and testing the near-infrared (NIR) spectrograph for the Southern African Large Telescope-RSS-NIR. RSS-NIR will be an enclosed cooled integral field spectrograph. The RSS-NIR detector system uses a HAWAII-2RG (H2RG) HgCdTe detector from Teledyne controlled by the SIDECAR ASIC and an Inter-University Centre for Astronomy and Astrophysics (IUCCA) ISDEC card. We have successfully characterized and optimized the detector system and report on the optimization steps and performance of the system. We have reduced the CDS read noise to ˜20 e- for 200 kHz operation by optimizing ASIC settings. We show an additional factor of 3 reduction of read noise using Fowler sampling techniques and a factor of 2 reduction using up-the-ramp group sampling techniques. We also provide calculations to quantify the conditions for sky-limited observations using these sampling techniques.

Does optimal partitioning of color space account for universal color categorization?

PubMed Central

2017-01-01

A 2007 study by Regier, Kay, and Khetarpal purports to show that universal categories emerge as a result of optimal partitioning of color space. Regier, Kay, and Khetarpal only consider color categorizations of up to six categories. However, in most industrialized societies eleven color categories are observed. This paper shows that when applied to the case of eleven categories, Regier, Kay, and Khetarpal’s optimality criterion yields unsatisfactory results. Applications of the criterion to the intermediate cases of seven, eight, nine, and ten color categories are also briefly considered and are shown to yield mixed results. We consider a number of possible explanations of the failure of the criterion in the case of eleven categories, and suggest that, as color categorizations get more complex, further criteria come to play a role, alongside Regier, Kay, and Khetarpal’s optimality criterion. PMID:28570598

Achieving Consistent Near-Optimal Pattern Recognition Accuracy Using Particle Swarm Optimization to Pre-Train Artificial Neural Networks

ERIC Educational Resources Information Center

Nikelshpur, Dmitry O.

2014-01-01

Similar to mammalian brains, Artificial Neural Networks (ANN) are universal approximators, capable of yielding near-optimal solutions to a wide assortment of problems. ANNs are used in many fields including medicine, internet security, engineering, retail, robotics, warfare, intelligence control, and finance. "ANNs have a tendency to get…

Applied optimal shape design

NASA Astrophysics Data System (ADS)

Mohammadi, B.; Pironneau, O.

2002-12-01

This paper is a short survey of optimal shape design (OSD) for fluids. OSD is an interesting field both mathematically and for industrial applications. Existence, sensitivity, correct discretization are important theoretical issues. Practical implementation issues for airplane designs are critical too. The paper is also a summary of the material covered in our recent book, Applied Optimal Shape Design, Oxford University Press, 2001.

Biologically-Inspired Anisotropic Flexible Wing for Optimal Flapping Flight

DTIC Science & Technology

2013-07-01

AFRL-OSR-VA-TR-2013-0400 Biologically-Inspired, Anisotropic Flexible Wing for Optimal Flapping Flight Luis Bernal, Wei Shyy...Final Report Contract Number: FA9550-07-1-0547 Biologically-Inspired, Anisotropic Flexible Wing for Optimal Flapping Flight University of...minimize power consumption; 2. The interactions of unsteady aerodynamic loading with flexible structures; 3. Flexible , light-weight, multifunctional

Homotopy method for optimization of variable-specific-impulse low-thrust trajectories

NASA Astrophysics Data System (ADS)

Chi, Zhemin; Yang, Hongwei; Chen, Shiyu; Li, Junfeng

2017-11-01

The homotopy method has been used as a useful tool in solving fuel-optimal trajectories with constant-specific-impulse low thrust. However, the specific impulse is often variable for many practical solar electric power-limited thrusters. This paper investigates the application of the homotopy method for optimization of variable-specific-impulse low-thrust trajectories. Difficulties arise when the two commonly-used homotopy functions are employed for trajectory optimization. The optimal power throttle level and the optimal specific impulse are coupled with the commonly-used quadratic and logarithmic homotopy functions. To overcome these difficulties, a modified logarithmic homotopy function is proposed to serve as a gateway for trajectory optimization, leading to decoupled expressions of both the optimal power throttle level and the optimal specific impulse. The homotopy method based on this homotopy function is proposed. Numerical simulations validate the feasibility and high efficiency of the proposed method.

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 trajectory and guidance design for the Mars Science Laboratory mission but may be applied to any optimization problem.

Optimal feedback scheme and universal time scaling for Hamiltonian parameter estimation.

PubMed

Yuan, Haidong; Fung, Chi-Hang Fred

2015-09-11

Time is a valuable resource and it is expected that a longer time period should lead to better precision in Hamiltonian parameter estimation. However, recent studies in quantum metrology have shown that in certain cases more time may even lead to worse estimations, which puts this intuition into question. In this Letter we show that by including feedback controls this intuition can be restored. By deriving asymptotically optimal feedback controls we quantify the maximal improvement feedback controls can provide in Hamiltonian parameter estimation and show a universal time scaling for the precision limit under the optimal feedback scheme. Our study reveals an intriguing connection between noncommutativity in the dynamics and the gain of feedback controls in Hamiltonian parameter estimation.

Comparative Approaches to Understanding the Relation Between Aging and Physical Function.

PubMed

Justice, Jamie N; Cesari, Matteo; Seals, Douglas R; Shively, Carol A; Carter, Christy S

2016-10-01

Despite dedicated efforts to identify interventions to delay aging, most promising interventions yielding dramatic life-span extension in animal models of aging are often ineffective when translated to clinical trials. This may be due to differences in primary outcomes between species and difficulties in determining the optimal clinical trial paradigms for translation. Measures of physical function, including brief standardized testing batteries, are currently being proposed as biomarkers of aging in humans, are predictive of adverse health events, disability, and mortality, and are commonly used as functional outcomes for clinical trials. Motor outcomes are now being incorporated into preclinical testing, a positive step toward enhancing our ability to translate aging interventions to clinical trials. To further these efforts, we begin a discussion of physical function and disability assessment across species, with special emphasis on mice, rats, monkeys, and man. By understanding how physical function is assessed in humans, we can tailor measurements in animals to better model those outcomes to establish effective, standardized translational functional assessments with aging. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Design Considerations for Proposed Fermilab Integrable RCS

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

Eldred, Jeffrey; Valishev, Alexander

2017-03-02

Integrable optics is an innovation in particle accelerator design that provides strong nonlinear focusing while avoiding parametric resonances. One promising application of integrable optics is to overcome the traditional limits on accelerator intensity imposed by betatron tune-spread and collective instabilities. The efficacy of high-intensity integrable accelerators will be undergo comprehensive testing over the next several years at the Fermilab Integrable Optics Test Accelerator (IOTA) and the University of Maryland Electron Ring (UMER). We propose an integrable Rapid-Cycling Synchrotron (iRCS) as a replacement for the Fermilab Booster to achieve multi-MW beam power for the Fermilab high-energy neutrino program. We provide amore » overview of the machine parameters and discuss an approach to lattice optimization. Integrable optics requires arcs with integer-pi phase advance followed by drifts with matched beta functions. We provide an example integrable lattice with features of a modern RCS - long dispersion-free drifts, low momentum compaction, superperiodicity, chromaticity correction, separate-function magnets, and bounded beta functions.« less

Collaborating in Dialogue for an Optimal Leadership Education

ERIC Educational Resources Information Center

Werder, Carmen; Garcia, Joseph; Bush, Jamie; Dallstream, Caroline

2016-01-01

Four different perspectives--from the director of a scholarship of teaching and learning dialogue forum, the director of a leadership institute, and two undergraduate students--join together to discuss a collaboration in optimizing leadership education at Western Washington University.

High-level expression of Camelid nanobodies in Nicotiana benthamiana.

PubMed

Teh, Yi-Hui Audrey; Kavanagh, Tony A

2010-08-01

Nanobodies (or VHHs) are single-domain antigen-binding fragments derived from Camelid heavy chain-only antibodies. Their small size, monomeric behaviour, high stability and solubility, and ability to bind epitopes not accessible to conventional antibodies make them especially suitable for many therapeutic and biotechnological applications. Here we describe high-level expression, in Nicotiana benthamiana, of three versions of an anti-hen egg white lysozyme (HEWL) nanobody which include the original VHH from an immunized library (cAbLys3), a codon-optimized derivative, and a codon-optimized hybrid nanobody comprising the CDRs of cAbLys3 grafted onto an alternative 'universal' nanobody framework. His6- and StrepII-tagged derivatives of each nanobody were targeted for accumulation in the cytoplasm, chloroplast and apoplast using different pre-sequences. When targeted to the apoplast, intact functional nanobodies accumulated at an exceptionally high level (up to 30% total leaf protein), demonstrating the great potential of plants as a nanobody production system.

An iterative method for tri-level quadratic fractional programming problems using fuzzy goal programming approach

NASA Astrophysics Data System (ADS)

Kassa, Semu Mitiku; Tsegay, Teklay Hailay

2017-08-01

Tri-level optimization problems are optimization problems with three nested hierarchical structures, where in most cases conflicting objectives are set at each level of hierarchy. Such problems are common in management, engineering designs and in decision making situations in general, and are known to be strongly NP-hard. Existing solution methods lack universality in solving these types of problems. In this paper, we investigate a tri-level programming problem with quadratic fractional objective functions at each of the three levels. A solution algorithm has been proposed by applying fuzzy goal programming approach and by reformulating the fractional constraints to equivalent but non-fractional non-linear constraints. Based on the transformed formulation, an iterative procedure is developed that can yield a satisfactory solution to the tri-level problem. The numerical results on various illustrative examples demonstrated that the proposed algorithm is very much promising and it can also be used to solve larger-sized as well as n-level problems of similar structure.

All-optical universal logic gates on nonlinear multimode interference coupler using tunable input intensity

NASA Astrophysics Data System (ADS)

Tajaldini, Mehdi; Jafri, Mohd Zubir Mat

2015-04-01

The theory of Nonlinear Modal Propagation Analysis Method (NMPA) have shown significant features of nonlinear multimode interference (MMI) coupler with compact dimension and when launched near the threshold of nonlinearity. Moreover, NMPA have the potential to allow studying the nonlinear MMI based the modal interference to explorer the phenomenon that what happen due to the natural of multimode region. Proposal of all-optical switch based NMPA has approved its capability to achieving the all-optical gates. All-optical gates have attracted increasing attention due to their practical utility in all-optical signal processing networks and systems. Nonlinear multimode interference devices could apply as universal all-optical gates due to significant features that NMPA introduce them. In this Paper, we present a novel Ultra-compact MMI coupler based on NMPA method in low intensity compared to last reports either as a novel design method and potential application for optical NAND, NOR as universal gates on single structure for Boolean logic signal processing devices and optimize their application via studding the contrast ratio between ON and OFF as a function of output width. We have applied NMPA for several applications so that the miniaturization in low nonlinear intensities is their main purpose.

A Decision Support Model and Tool to Assist Financial Decision-Making in Universities

ERIC Educational Resources Information Center

Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive

2015-01-01

In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…

Redundancy of primary RNA-binding functions of the bacterial transcription terminator Rho.

PubMed

Shashni, Rajesh; Qayyum, M Zuhaib; Vishalini, V; Dey, Debashish; Sen, Ranjan

2014-09-01

The bacterial transcription terminator, Rho, terminates transcription at half of the operons. According to the classical model derived from in vitro assays on a few terminators, Rho is recruited to the transcription elongation complex (EC) by recognizing specific sites (rut) on the nascent RNA. Here, we explored the mode of in vivo recruitment process of Rho. We show that sequence specific recognition of the rut site, in majority of the Rho-dependent terminators, can be compromised to a great extent without seriously affecting the genome-wide termination function as well as the viability of Escherichia coli. These terminators function optimally only through a NusG-assisted recruitment and activation of Rho. Our data also indicate that at these terminators, Rho-EC-bound NusG interaction facilitates the isomerization of Rho into a translocase-competent form by stabilizing the interactions of mRNA with the secondary RNA binding site, thereby overcoming the defects of the primary RNA binding functions. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

NaLi-H1: A universal synthetic library of humanized nanobodies providing highly functional antibodies and intrabodies

PubMed Central

Moutel, Sandrine; Bery, Nicolas; Bernard, Virginie; Keller, Laura; Lemesre, Emilie; de Marco, Ario; Ligat, Laetitia; Rain, Jean-Christophe; Favre, Gilles; Olichon, Aurélien; Perez, Franck

2016-01-01

In vitro selection of antibodies allows to obtain highly functional binders, rapidly and at lower cost. Here, we describe the first fully synthetic phage display library of humanized llama single domain antibody (NaLi-H1: Nanobody Library Humanized 1). Based on a humanized synthetic single domain antibody (hs2dAb) scaffold optimized for intracellular stability, the highly diverse library provides high affinity binders without animal immunization. NaLi-H1 was screened following several selection schemes against various targets (Fluorescent proteins, actin, tubulin, p53, HP1). Conformation antibodies against active RHO GTPase were also obtained. Selected hs2dAb were used in various immunoassays and were often found to be functional intrabodies, enabling tracking or inhibition of endogenous targets. Functionalization of intrabodies allowed specific protein knockdown in living cells. Finally, direct selection against the surface of tumor cells produced hs2dAb directed against tumor-specific antigens further highlighting the potential use of this library for therapeutic applications. DOI: http://dx.doi.org/10.7554/eLife.16228.001 PMID:27434673

Functional and Structural Optimality in Plant Growth: A Crop Modelling Case Study

NASA Astrophysics Data System (ADS)

Caldararu, S.; Purves, D. W.; Smith, M. J.

2014-12-01

Simple mechanistic models of vegetation processes are essential both to our understanding of plant behaviour and to our ability to predict future changes in vegetation. One concept that can take us closer to such models is that of plant optimality, the hypothesis that plants aim to achieve an optimal state. Conceptually, plant optimality can be either structural or functional optimality. A structural constraint would mean that plants aim to achieve a certain structural characteristic such as an allometric relationship or nutrient content that allows optimal function. A functional condition refers to plants achieving optimal functionality, in most cases by maximising carbon gain. Functional optimality conditions are applied on shorter time scales and lead to higher plasticity, making plants more adaptable to changes in their environment. In contrast, structural constraints are optimal given the specific environmental conditions that plants are adapted to and offer less flexibility. We exemplify these concepts using a simple model of crop growth. The model represents annual cycles of growth from sowing date to harvest, including both vegetative and reproductive growth and phenology. Structural constraints to growth are represented as an optimal C:N ratio in all plant organs, which drives allocation throughout the vegetative growing stage. Reproductive phenology - i.e. the onset of flowering and grain filling - is determined by a functional optimality condition in the form of maximising final seed mass, so that vegetative growth stops when the plant reaches maximum nitrogen or carbon uptake. We investigate the plants' response to variations in environmental conditions within these two optimality constraints and show that final yield is most affected by changes during vegetative growth which affect the structural constraint.

The Fully-Functioning University and Its Higher Education

ERIC Educational Resources Information Center

Bourner, Tom; Heath, Linda; Rospigliosi, Pericles

2013-01-01

In 2008 an article in this journal introduced the concept of a "fully-functioning university". This new article explores the sort of higher education (HE) that such a university would offer. It starts by examining the idea of a fully-functioning university and its relationship with the "tripartite mission" of a university. In…

An optimal generic model for multi-parameters and big data optimizing: a laboratory experimental study

NASA Astrophysics Data System (ADS)

Utama, D. N.; Ani, N.; Iqbal, M. M.

2018-03-01

Optimization is a process for finding parameter (parameters) that is (are) able to deliver an optimal value for an objective function. Seeking an optimal generic model for optimizing is a computer science study that has been being practically conducted by numerous researchers. Generic model is a model that can be technically operated to solve any varieties of optimization problem. By using an object-oriented method, the generic model for optimizing was constructed. Moreover, two types of optimization method, simulated-annealing and hill-climbing, were functioned in constructing the model and compared to find the most optimal one then. The result said that both methods gave the same result for a value of objective function and the hill-climbing based model consumed the shortest running time.

The Dolinar Receiver in an Information Theoretic Framework

NASA Technical Reports Server (NTRS)

Erkmen, Baris I.; Birnbaum, Kevin M.; Moision, Bruce E.; Dolinar, Samuel J.

2011-01-01

Optical communication at the quantum limit requires that measurements on the optical field be maximally informative, but devising physical measurements that accomplish this objective has proven challenging. The Dolinar receiver exemplifies a rare instance of success in distinguishing between two coherent states: an adaptive local oscillator is mixed with the signal prior to photodetection, which yields an error probability that meets the Helstrom lower bound with equality. Here we apply the same local-oscillator-based architecture with aninformation-theoretic optimization criterion. We begin with analysis of this receiver in a general framework for an arbitrary coherent-state modulation alphabet, and then we concentrate on two relevant examples. First, we study a binary antipodal alphabet and show that the Dolinar receiver's feedback function not only minimizes the probability of error, but also maximizes the mutual information. Next, we study ternary modulation consistingof antipodal coherent states and the vacuum state. We derive an analytic expression for a near-optimal local oscillator feedback function, and, via simulation, we determine its photon information efficiency (PIE). We provide the PIE versus dimensional information efficiency (DIE) trade-off curve and show that this modulation and the our receiver combination performs universally better than (generalized) on-off keying plus photoncounting, although, the advantage asymptotically vanishes as the bits-per-photon diverges towards infinity.

The Dopaminergic Midbrain Encodes the Expected Certainty about Desired Outcomes.

PubMed

Schwartenbeck, Philipp; FitzGerald, Thomas H B; Mathys, Christoph; Dolan, Ray; Friston, Karl

2015-10-01

Dopamine plays a key role in learning; however, its exact function in decision making and choice remains unclear. Recently, we proposed a generic model based on active (Bayesian) inference wherein dopamine encodes the precision of beliefs about optimal policies. Put simply, dopamine discharges reflect the confidence that a chosen policy will lead to desired outcomes. We designed a novel task to test this hypothesis, where subjects played a "limited offer" game in a functional magnetic resonance imaging experiment. Subjects had to decide how long to wait for a high offer before accepting a low offer, with the risk of losing everything if they waited too long. Bayesian model comparison showed that behavior strongly supported active inference, based on surprise minimization, over classical utility maximization schemes. Furthermore, midbrain activity, encompassing dopamine projection neurons, was accurately predicted by trial-by-trial variations in model-based estimates of precision. Our findings demonstrate that human subjects infer both optimal policies and the precision of those inferences, and thus support the notion that humans perform hierarchical probabilistic Bayesian inference. In other words, subjects have to infer both what they should do as well as how confident they are in their choices, where confidence may be encoded by dopaminergic firing. © The Author 2014. Published by Oxford University Press.

Optimal Learning for Efficient Experimentation in Nanotechnology and Biochemistry

DTIC Science & Technology

2015-12-22

AFRL-AFOSR-VA-TR-2016-0018 Optimal Learning for Efficient Experimentation in Nanotechnology , Biochemistry Warren Powell TRUSTEES OF PRINCETON...3. DATES COVERED (From - To) 01-07-2012 to 30-09-2015 4. TITLE AND SUBTITLE Optimal Learning for Efficient Experimentation in Nanotechnology and...in Nanotechnology and Biochemistry Principal Investigators: Warren B. Powell Princeton University Department of Operations Research and

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

Fang Baolong; Department of Mathematics and Physics, Hefei University, Hefei 230022; Yang Zhen

We propose a scheme for implementing a partial general quantum cloning machine with superconducting quantum-interference devices coupled to a nonresonant cavity. By regulating the time parameters, our system can perform optimal symmetric (asymmetric) universal quantum cloning, optimal symmetric (asymmetric) phase-covariant cloning, and optimal symmetric economical phase-covariant cloning. In the scheme the cavity is only virtually excited, thus, the cavity decay is suppressed during the cloning operations.

Design of Power System Architectures for Small Spacecraft Systems

NASA Technical Reports Server (NTRS)

Momoh, James A.; Subramonian, Rama; Dias, Lakshman G.

1996-01-01

The objective of this research is to perform a trade study on several candidate power system architectures for small spacecrafts to be used in NASA's new millennium program. Three initial candidate architectures have been proposed by NASA and two other candidate architectures have been proposed by Howard University. Howard University is currently conducting the necessary analysis, synthesis, and simulation needed to perform the trade studies and arrive at the optimal power system architecture. Statistical, sensitivity and tolerant studies has been performed on the systems. It is concluded from present studies that certain components such as the series regulators, buck-boost converters and power converters can be minimized while retaining the desired functionality of the overall architecture. This in conjunction with battery scalability studies and system efficiency studies have enabled us to develop more economic architectures. Future studies will include artificial neural networks and fuzzy logic to analyze the performance of the systems. Fault simulation studies and fault diagnosis studies using EMTP and artificial neural networks will also be conducted.

Real-time dual-loop electric current measurement for label-free nanofluidic preconcentration chip.

PubMed

Chung, Pei-Shan; Fan, Yu-Jui; Sheen, Horn-Jiunn; Tian, Wei-Cheng

2015-01-07

An electrokinetic trapping (EKT)-based nanofluidic preconcentration device with the capability of label-free monitoring trapped biomolecules through real-time dual-loop electric current measurement was demonstrated. Universal current-voltage (I-V) curves of EKT-based preconcentration devices, consisting of two microchannels connected by ion-selective channels, are presented for functional validation and optimal operation; universal onset current curves indicating the appearance of the EKT mechanism serve as a confirmation of the concentrating action. The EKT mechanism and the dissimilarity in the current curves related to the volume flow rate (Q), diffusion coefficient (D), and diffusion layer (DL) thickness were explained by a control volume model with a five-stage preconcentration process. Different behaviors of the trapped molecular plug were categorized based on four modes associated with different degrees of electroosmotic instability (EOI). A label-free approach to preconcentrating (bio)molecules and monitoring the multibehavior molecular plug was demonstrated through real-time electric current monitoring, rather than through the use of microscope images.

Designing optimal universal pulses using second-order, large-scale, non-linear optimization

NASA Astrophysics Data System (ADS)

Anand, Christopher Kumar; Bain, Alex D.; Curtis, Andrew Thomas; Nie, Zhenghua

2012-06-01

Recently, RF pulse design using first-order and quasi-second-order pulses has been actively investigated. We present a full second-order design method capable of incorporating relaxation, inhomogeneity in B0 and B1. Our model is formulated as a generic optimization problem making it easy to incorporate diverse pulse sequence features. To tame the computational cost, we present a method of calculating second derivatives in at most a constant multiple of the first derivative calculation time, this is further accelerated by using symbolic solutions of the Bloch equations. We illustrate the relative merits and performance of quasi-Newton and full second-order optimization with a series of examples, showing that even a pulse already optimized using other methods can be visibly improved. To be useful in CPMG experiments, a universal refocusing pulse should be independent of the delay time and insensitive of the relaxation time and RF inhomogeneity. We design such a pulse and show that, using it, we can obtain reliable R2 measurements for offsets within ±γB1. Finally, we compare our optimal refocusing pulse with other published refocusing pulses by doing CPMG experiments.

Global linear-irreversible principle for optimization in finite-time thermodynamics

NASA Astrophysics Data System (ADS)

Johal, Ramandeep S.

2018-03-01

There is intense effort into understanding the universal properties of finite-time models of thermal machines —at optimal performance— such as efficiency at maximum power, coefficient of performance at maximum cooling power, and other such criteria. In this letter, a global principle consistent with linear irreversible thermodynamics is proposed for the whole cycle —without considering details of irreversibilities in the individual steps of the cycle. This helps to express the total duration of the cycle as τ \\propto {\\bar{Q}^2}/{Δ_\\text{tot}S} , where \\bar{Q} models the effective heat transferred through the machine during the cycle, and Δ_ \\text{tot} S is the total entropy generated. By taking \\bar{Q} in the form of simple algebraic means (such as arithmetic and geometric means) over the heats exchanged by the reservoirs, the present approach is able to predict various standard expressions for figures of merit at optimal performance, as well as the bounds respected by them. It simplifies the optimization procedure to a one-parameter optimization, and provides a fresh perspective on the issue of universality at optimal performance, for small difference in reservoir temperatures. As an illustration, we compare the performance of a partially optimized four-step endoreversible cycle with the present approach.

Multi-Criteria Optimization of Regulation in Metabolic Networks

PubMed Central

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

2012-01-01

Determining the regulation of metabolic networks at genome scale is a hard task. It has been hypothesized that biochemical pathways and metabolic networks might have undergone an evolutionary process of optimization with respect to several criteria over time. In this contribution, a multi-criteria approach has been used to optimize parameters for the allosteric regulation of enzymes in a model of a metabolic substrate-cycle. This has been carried out by calculating the Pareto set of optimal solutions according to two objectives: the proper direction of flux in a metabolic cycle and the energetic cost of applying the set of parameters. Different Pareto fronts have been calculated for eight different “environments” (specific time courses of end product concentrations). For each resulting front the so-called knee point is identified, which can be considered a preferred trade-off solution. Interestingly, the optimal control parameters corresponding to each of these points also lead to optimal behaviour in all the other environments. By calculating the average of the different parameter sets for the knee solutions more frequently found, a final and optimal consensus set of parameters can be obtained, which is an indication on the existence of a universal regulation mechanism for this system.The implications from such a universal regulatory switch are discussed in the framework of large metabolic networks. PMID:22848435

[Workflow management in the operating room. Analysis of potentials for optimizing efficiency at a university hospital].

PubMed

Welker, A; Wolcke, B; Schleppers, A; Schmeck, S B; Focke, U; Gervais, H W; Schmeck, J

2010-10-01

The introduction of the diagnosis-related groups reimbursement system has increased cost pressures. Due to the interaction of many different professional groups, analysis and optimization of internal coordination and scheduling in the operating room (OR) is mandatory. The aim of this study was to analyze the processes at a university hospital in order to optimize strategies by identifying potential weak points. Over a period 6 weeks before and 4 weeks after intervention processes time intervals in the OR of a tertiary care hospital (university hospital) were documented in a structured data collection sheet. The main reason for lack of efficiency of labor was underused OR utilization. Multifactorial reasons, particularly in the management of perioperative interfaces, led to vacant ORs. A significant deficit was in the use of OR capacity at the end of the daily OR schedule. After harmonization of working hours of different staff groups and implementation of several other changes an increase in efficiency could be verified. These results indicate that optimization of perioperative processes considerably contribute to the success of OR organization. Additionally, the implementation of standard operating procedures and a generally accepted OR statute are mandatory. In this way an efficient OR management can contribute to the economic success of a hospital.

A concept analysis of optimality in perinatal health.

PubMed

Kennedy, Holly Powell

2006-01-01

This analysis was conducted to describe the concept of optimality and its appropriateness for perinatal health care. The concept was identified in 24 scientific disciplines. Across all disciplines, the universal definition of optimality is the robust, efficient, and cost-effective achievement of best possible outcomes within a rule-governed framework. Optimality, specifically defined for perinatal health care, is the maximal perinatal outcome with minimal intervention placed against the context of the woman's social, medical, and obstetric history.

antaRNA: ant colony-based RNA sequence design.

PubMed

Kleinkauf, Robert; Mann, Martin; Backofen, Rolf

2015-10-01

RNA sequence design is studied at least as long as the classical folding problem. Although for the latter the functional fold of an RNA molecule is to be found ,: inverse folding tries to identify RNA sequences that fold into a function-specific target structure. In combination with RNA-based biotechnology and synthetic biology ,: reliable RNA sequence design becomes a crucial step to generate novel biochemical components. In this article ,: the computational tool antaRNA is presented. It is capable of compiling RNA sequences for a given structure that comply in addition with an adjustable full range objective GC-content distribution ,: specific sequence constraints and additional fuzzy structure constraints. antaRNA applies ant colony optimization meta-heuristics and its superior performance is shown on a biological datasets. http://www.bioinf.uni-freiburg.de/Software/antaRNA CONTACT: backofen@informatik.uni-freiburg.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.

PubMed

Lavoie, Benjamin R; Okoniewski, Michal; Fear, Elise C

2016-01-01

We present preliminary results from a method for estimating the optimal effective permittivity for reconstructing microwave-radar images. Using knowledge of how microwave-radar images are formed, we identify characteristics that are typical of good images, and define a fitness function to measure the relative image quality. We build a polynomial interpolant of the fitness function in order to identify the most likely permittivity values of the tissue. To make the estimation process more efficient, the polynomial interpolant is constructed using a locally and dimensionally adaptive sampling method that is a novel combination of stochastic collocation and polynomial chaos. Examples, using a series of simulated, experimental and patient data collected using the Tissue Sensing Adaptive Radar system, which is under development at the University of Calgary, are presented. These examples show how, using our method, accurate images can be reconstructed starting with only a broad estimate of the permittivity range.

Risk factors for suicide in Taiwanese college students.

PubMed

Gau, Susan Shur-Fen; Chen, Ying-Yeh; Tsai, Fang-Ju; Lee, Ming-Been; Chiu, Yen-Nan; Soong, Wei-Tsuen; Hwu, Hai-Gwo

2008-01-01

The authors investigated the personality characteristics, psychopathology, parenting style, and family function among Taiwanese college students with high, moderate, and low suicidal risks. The sample included 2,919 first-year college students (1,414 men, 1,505 women) from a university in Taipei, Taiwan. A self-administered questionnaire assessed domains covering demographics, personality, psychopathology, frequency of substance use, parenting style, family functioning, and suicidal behaviors. The authors used mixed models for data analysis. The authors observed a positive linear trend between increased suicidal tendency and levels of neuroticism, harm avoidance, novelty seeking, psychopathology, and parenting styles of low affection, overprotection, and authoritarian controlling. Use of tobacco and alcohol and impaired family adaptation and cohesion were associated with high and moderate suicidal risks. Personality, psychopathology, substance use, and familial factors are important correlates of suicidal risks among college students in Taiwan. Optimal suicide prevention strategies in the college setting should incorporate the multiple facets of suicidal risks.

Optimization of lattice surgery is NP-hard

NASA Astrophysics Data System (ADS)

Herr, Daniel; Nori, Franco; Devitt, Simon J.

2017-09-01

The traditional method for computation in either the surface code or in the Raussendorf model is the creation of holes or "defects" within the encoded lattice of qubits that are manipulated via topological braiding to enact logic gates. However, this is not the only way to achieve universal, fault-tolerant computation. In this work, we focus on the lattice surgery representation, which realizes transversal logic operations without destroying the intrinsic 2D nearest-neighbor properties of the braid-based surface code and achieves universality without defects and braid-based logic. For both techniques there are open questions regarding the compilation and resource optimization of quantum circuits. Optimization in braid-based logic is proving to be difficult and the classical complexity associated with this problem has yet to be determined. In the context of lattice-surgery-based logic, we can introduce an optimality condition, which corresponds to a circuit with the lowest resource requirements in terms of physical qubits and computational time, and prove that the complexity of optimizing a quantum circuit in the lattice surgery model is NP-hard.

Optimization of topological quantum algorithms using Lattice Surgery is hard

NASA Astrophysics Data System (ADS)

Herr, Daniel; Nori, Franco; Devitt, Simon

The traditional method for computation in the surface code or the Raussendorf model is the creation of holes or ''defects'' within the encoded lattice of qubits which are manipulated via topological braiding to enact logic gates. However, this is not the only way to achieve universal, fault-tolerant computation. In this work we turn attention to the Lattice Surgery representation, which realizes encoded logic operations without destroying the intrinsic 2D nearest-neighbor interactions sufficient for braided based logic and achieves universality without using defects for encoding information. In both braided and lattice surgery logic there are open questions regarding the compilation and resource optimization of quantum circuits. Optimization in braid-based logic is proving to be difficult to define and the classical complexity associated with this problem has yet to be determined. In the context of lattice surgery based logic, we can introduce an optimality condition, which corresponds to a circuit with lowest amount of physical qubit requirements, and prove that the complexity of optimizing the geometric (lattice surgery) representation of a quantum circuit is NP-hard.

A Study of Penalty Function Methods for Constraint Handling with Genetic Algorithm

NASA Technical Reports Server (NTRS)

Ortiz, Francisco

2004-01-01

COMETBOARDS (Comparative Evaluation Testbed of Optimization and Analysis Routines for Design of Structures) is a design optimization test bed that can evaluate the performance of several different optimization algorithms. A few of these optimization algorithms are the sequence of unconstrained minimization techniques (SUMT), sequential linear programming (SLP) and the sequential quadratic programming techniques (SQP). A genetic algorithm (GA) is a search technique that is based on the principles of natural selection or "survival of the fittest". Instead of using gradient information, the GA uses the objective function directly in the search. The GA searches the solution space by maintaining a population of potential solutions. Then, using evolving operations such as recombination, mutation and selection, the GA creates successive generations of solutions that will evolve and take on the positive characteristics of their parents and thus gradually approach optimal or near-optimal solutions. By using the objective function directly in the search, genetic algorithms can be effectively applied in non-convex, highly nonlinear, complex problems. The genetic algorithm is not guaranteed to find the global optimum, but it is less likely to get trapped at a local optimum than traditional gradient-based search methods when the objective function is not smooth and generally well behaved. The purpose of this research is to assist in the integration of genetic algorithm (GA) into COMETBOARDS. COMETBOARDS cast the design of structures as a constrained nonlinear optimization problem. One method used to solve constrained optimization problem with a GA to convert the constrained optimization problem into an unconstrained optimization problem by developing a penalty function that penalizes infeasible solutions. There have been several suggested penalty function in the literature each with there own strengths and weaknesses. A statistical analysis of some suggested penalty functions is performed in this study. Also, a response surface approach to robust design is used to develop a new penalty function approach. This new penalty function approach is then compared with the other existing penalty functions.

A survey of compiler optimization techniques

NASA Technical Reports Server (NTRS)

Schneck, P. B.

1972-01-01

Major optimization techniques of compilers are described and grouped into three categories: machine dependent, architecture dependent, and architecture independent. Machine-dependent optimizations tend to be local and are performed upon short spans of generated code by using particular properties of an instruction set to reduce the time or space required by a program. Architecture-dependent optimizations are global and are performed while generating code. These optimizations consider the structure of a computer, but not its detailed instruction set. Architecture independent optimizations are also global but are based on analysis of the program flow graph and the dependencies among statements of source program. A conceptual review of a universal optimizer that performs architecture-independent optimizations at source-code level is also presented.

Cost effective simulation-based multiobjective optimization in the performance of an internal combustion engine

NASA Astrophysics Data System (ADS)

Aittokoski, Timo; Miettinen, Kaisa

2008-07-01

Solving real-life engineering problems can be difficult because they often have multiple conflicting objectives, the objective functions involved are highly nonlinear and they contain multiple local minima. Furthermore, function values are often produced via a time-consuming simulation process. These facts suggest the need for an automated optimization tool that is efficient (in terms of number of objective function evaluations) and capable of solving global and multiobjective optimization problems. In this article, the requirements on a general simulation-based optimization system are discussed and such a system is applied to optimize the performance of a two-stroke combustion engine. In the example of a simulation-based optimization problem, the dimensions and shape of the exhaust pipe of a two-stroke engine are altered, and values of three conflicting objective functions are optimized. These values are derived from power output characteristics of the engine. The optimization approach involves interactive multiobjective optimization and provides a convenient tool to balance between conflicting objectives and to find good solutions.

RNAblueprint: flexible multiple target nucleic acid sequence design.

PubMed

Hammer, Stefan; Tschiatschek, Birgit; Flamm, Christoph; Hofacker, Ivo L; Findeiß, Sven

2017-09-15

Realizing the value of synthetic biology in biotechnology and medicine requires the design of molecules with specialized functions. Due to its close structure to function relationship, and the availability of good structure prediction methods and energy models, RNA is perfectly suited to be synthetically engineered with predefined properties. However, currently available RNA design tools cannot be easily adapted to accommodate new design specifications. Furthermore, complicated sampling and optimization methods are often developed to suit a specific RNA design goal, adding to their inflexibility. We developed a C ++  library implementing a graph coloring approach to stochastically sample sequences compatible with structural and sequence constraints from the typically very large solution space. The approach allows to specify and explore the solution space in a well defined way. Our library also guarantees uniform sampling, which makes optimization runs performant by not only avoiding re-evaluation of already found solutions, but also by raising the probability of finding better solutions for long optimization runs. We show that our software can be combined with any other software package to allow diverse RNA design applications. Scripting interfaces allow the easy adaption of existing code to accommodate new scenarios, making the whole design process very flexible. We implemented example design approaches written in Python to demonstrate these advantages. RNAblueprint , Python implementations and benchmark datasets are available at github: https://github.com/ViennaRNA . s.hammer@univie.ac.at, ivo@tbi.univie.ac.at or sven@tbi.univie.ac.at. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Adolescents with congenital heart disease: the importance of perceived parenting for psychosocial and health outcomes.

PubMed

Luyckx, Koen; Goossens, Eva; Missotten, Lies; Moons, Philip

2011-11-01

: Little is known about how parenting relates to psychosocial functioning and health behavior in adolescents with congenital heart disease (CHD). Different parenting styles were identified through relying on adolescent perceptions of multiple dimensions (regulation, responsiveness, and psychological control). The degree to which parents were perceived as consistent in their rearing style was assessed. : Adolescents with CHD were selected from the database of pediatric and congenital cardiology of the University Hospitals Leuven; control individuals were recruited at secondary schools. A total of 429 adolescents (14-18 years) with CHD participated; 403 were matched on gender and age with control individuals. Adolescents completed questionnaires on maternal and paternal regulation, psychological control, and responsiveness. Main outcome measures were depressive symptoms, loneliness, quality of life, health status, alcohol, cigarette, and drug use. : No significant differences emerged between adolescents with CHD and controls in perceived parenting styles. Democratic parenting was accompanied by the most optimal pattern of outcomes in adolescents with CHD, whereas psychologically controlling parenting by the least optimal pattern. Overprotective parenting was related to high patient substance use. Perceiving both parents as democratic turned out most favorably for psychosocial functioning and quality of life, whereas parental consistency was unrelated to substance use in adolescents with CHD. : By building bridges between the fields of adolescent medicine and family studies, the present study generated important information on the role of parents in psychosocial and behavioral functioning of adolescents with CHD. Future longitudinal studies could inform family-based interventions for this population.

Reduced-Order Modeling for Optimization and Control of Complex Flows

DTIC Science & Technology

2010-11-30

Statistics Colloquium, Auburn, AL, (January 2009). 16. University of Pittsburgh, Mathematics Colloquium, Pittsburgh, PA, (February 2009). 17. Goethe ...Center for Scientific Computing, Goethe University Frankfurt am Main, Ger- many, (June 2009). 18. Air Force Institute of Technology, Wright-Patterson

Automated Testability Decision Tool

DTIC Science & Technology

1991-09-01

Vol. 16,1968, pp. 538-558. Bertsekas, D. P., "Constraints Optimization and Lagrange Multiplier Methods," Academic Press, New York. McLeavey , D.W... McLeavey , J.A., "Parallel Optimization Methods in Standby Reliability, " University of Connecticut, School of Business Administration, Bureau of Business

Optimization study for the experimental configuration of CMB-S4

NASA Astrophysics Data System (ADS)

Barron, Darcy; Chinone, Yuji; Kusaka, Akito; Borril, Julian; Errard, Josquin; Feeney, Stephen; Ferraro, Simone; Keskitalo, Reijo; Lee, Adrian T.; Roe, Natalie A.; Sherwin, Blake D.; Suzuki, Aritoki

2018-02-01

The CMB Stage 4 (CMB-S4) experiment is a next-generation, ground-based experiment that will measure the cosmic microwave background (CMB) polarization to unprecedented accuracy, probing the signature of inflation, the nature of cosmic neutrinos, relativistic thermal relics in the early universe, and the evolution of the universe. CMB-S4 will consist of O(500,000) photon-noise-limited detectors that cover a wide range of angular scales in order to probe the cosmological signatures from both the early and late universe. It will measure a wide range of microwave frequencies to cleanly separate the CMB signals from galactic and extra-galactic foregrounds. To advance the progress towards designing the instrument for CMB-S4, we have established a framework to optimize the instrumental configuration to maximize its scientific output. The framework combines cost and instrumental models with a cosmology forecasting tool, and evaluates the scientific sensitivity as a function of various instrumental parameters. The cost model also allows us to perform the analysis under a fixed-cost constraint, optimizing for the scientific output of the experiment given finite resources. In this paper, we report our first results from this framework, using simplified instrumental and cost models. We have primarily studied two classes of instrumental configurations: arrays of large-aperture telescopes with diameters ranging from 2–10 m, and hybrid arrays that combine small-aperture telescopes (0.5-m diameter) with large-aperture telescopes. We explore performance as a function of telescope aperture size, distribution of the detectors into different microwave frequencies, survey strategy and survey area, low-frequency noise performance, and balance between small and large aperture telescopes for hybrid configurations. Both types of configurations must cover both large (~ degree) and small (~ arcmin) angular scales, and the performance depends on assumptions for performance vs. angular scale. The configurations with large-aperture telescopes have a shallow optimum around 4–6 m in aperture diameter, assuming that large telescopes can achieve good performance for low-frequency noise. We explore some of the uncertainties of the instrumental model and cost parameters, and we find that the optimum has a weak dependence on these parameters. The hybrid configuration shows an even broader optimum, spanning a range of 4–10 m in aperture for the large telescopes. We also present two strawperson configurations as an outcome of this optimization study, and we discuss some ideas for improving our simple cost and instrumental models used here. There are several areas of this analysis that deserve further improvement. In our forecasting framework, we adopt a simple two-component foreground model with spatially varying power-law spectral indices. We estimate de-lensing performance statistically and ignore non-idealities such as anisotropic mode coverage, boundary effect, and possible foreground residual. Instrumental systematics, which is not accounted for in our analyses, may also influence the conceptual design. Further study of the instrumental and cost models will be one of the main areas of study by the entire CMB-S4 community. We hope that our framework will be useful for estimating the influence of these improvements in the future, and we will incorporate them in order to further improve the optimization.

Ant colony optimization for solving university facility layout problem

NASA Astrophysics Data System (ADS)

Mohd Jani, Nurul Hafiza; Mohd Radzi, Nor Haizan; Ngadiman, Mohd Salihin

2013-04-01

Quadratic Assignment Problems (QAP) is classified as the NP hard problem. It has been used to model a lot of problem in several areas such as operational research, combinatorial data analysis and also parallel and distributed computing, optimization problem such as graph portioning and Travel Salesman Problem (TSP). In the literature, researcher use exact algorithm, heuristics algorithm and metaheuristic approaches to solve QAP problem. QAP is largely applied in facility layout problem (FLP). In this paper we used QAP to model university facility layout problem. There are 8 facilities that need to be assigned to 8 locations. Hence we have modeled a QAP problem with n ≤ 10 and developed an Ant Colony Optimization (ACO) algorithm to solve the university facility layout problem. The objective is to assign n facilities to n locations such that the minimum product of flows and distances is obtained. Flow is the movement from one to another facility, whereas distance is the distance between one locations of a facility to other facilities locations. The objective of the QAP is to obtain minimum total walking (flow) of lecturers from one destination to another (distance).

A molecular model for the active site of S-adenosyl- l-homocysteine hydrolase

NASA Astrophysics Data System (ADS)

Yeh, Jerry C.; Borchardt, Ronald T.; Vedani, Angelo

1991-06-01

S-adenosyl- l-homocysteine hydrolase (AdoHcy hydrolase, EC 3.3.1.1.), a specific target for antiviral drug design, catalyzes the hydrolysis of AdoHcy to adenosine (Ado) and homocysteine (Hcy) as well as the synthesis of AdoHcy from Ado and Hcy. The enzyme isolated from different sources has been shown to contain tightly bound NAD+. Based on the 2.0 Å-resolution X-ray crystal structure of dogfish lactate dehydrogenase (LDH), which is functionally homologous to AdoHcy hydrolase, and the primary sequence of rat liver AdoHcy hydrolase, we have derived a molecular model of an extended active site for AdoHcy hydrolase. The computational mutation was performed using the software MUTAR (Yeh et al., University of Kansas, Lawrence), followed by molecular mechanics optimizations using the programs AMBER (Singh et al., University of California, San Francisco) and YETI (Vedani, University of Kansas). Solvation of the model structure was achieved by use of the program SOLVGEN (Jacober, University of Kansas); 56 water molecules were explicitly included in all refinements. Some of these may be involved in the catalytic reaction. We also studied a model of the complex of AdoHcy hydrolase with NAD+, as well as the ternary complexes of the redox reaction catalyzed by AdoHcy hydrolase and has been used to differentiate the relative binding strength of inhibitors.

Expanding the PACS archive to support clinical review, research, and education missions

NASA Astrophysics Data System (ADS)

Honeyman-Buck, Janice C.; Frost, Meryll M.; Drane, Walter E.

1999-07-01

Designing an image archive and retrieval system that supports multiple users with many different requirements and patterns of use without compromising the performance and functionality required by diagnostic radiology is an intellectual and technical challenge. A diagnostic archive, optimized for performance when retrieving diagnostic images for radiologists needed to be expanded to support a growing clinical review network, the University of Florida Brain Institute's demands for neuro-imaging, Biomedical Engineering's imaging sciences, and an electronic teaching file. Each of the groups presented a different set of problems for the designers of the system. In addition, the radiologists did not want to see nay loss of performance as new users were added.

Combined genetic algorithm and multiple linear regression (GA-MLR) optimizer: Application to multi-exponential fluorescence decay surface.

PubMed

Fisz, Jacek J

2006-12-07

The optimization approach based on the genetic algorithm (GA) combined with multiple linear regression (MLR) method, is discussed. The GA-MLR optimizer is designed for the nonlinear least-squares problems in which the model functions are linear combinations of nonlinear functions. GA optimizes the nonlinear parameters, and the linear parameters are calculated from MLR. GA-MLR is an intuitive optimization approach and it exploits all advantages of the genetic algorithm technique. This optimization method results from an appropriate combination of two well-known optimization methods. The MLR method is embedded in the GA optimizer and linear and nonlinear model parameters are optimized in parallel. The MLR method is the only one strictly mathematical "tool" involved in GA-MLR. The GA-MLR approach simplifies and accelerates considerably the optimization process because the linear parameters are not the fitted ones. Its properties are exemplified by the analysis of the kinetic biexponential fluorescence decay surface corresponding to a two-excited-state interconversion process. A short discussion of the variable projection (VP) algorithm, designed for the same class of the optimization problems, is presented. VP is a very advanced mathematical formalism that involves the methods of nonlinear functionals, algebra of linear projectors, and the formalism of Fréchet derivatives and pseudo-inverses. Additional explanatory comments are added on the application of recently introduced the GA-NR optimizer to simultaneous recovery of linear and weakly nonlinear parameters occurring in the same optimization problem together with nonlinear parameters. The GA-NR optimizer combines the GA method with the NR method, in which the minimum-value condition for the quadratic approximation to chi(2), obtained from the Taylor series expansion of chi(2), is recovered by means of the Newton-Raphson algorithm. The application of the GA-NR optimizer to model functions which are multi-linear combinations of nonlinear functions, is indicated. The VP algorithm does not distinguish the weakly nonlinear parameters from the nonlinear ones and it does not apply to the model functions which are multi-linear combinations of nonlinear functions.

Individual Functional ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles

PubMed Central

Li, Kaiming; Guo, Lei; Zhu, Dajiang; Hu, Xintao; Han, Junwei; Liu, Tianming

2013-01-01

Studying connectivities among functional brain regions and the functional dynamics on brain networks has drawn increasing interest. A fundamental issue that affects functional connectivity and dynamics studies is how to determine the best possible functional brain regions or ROIs (regions of interest) for a group of individuals, since the connectivity measurements are heavily dependent on ROI locations. Essentially, identification of accurate, reliable and consistent corresponding ROIs is challenging due to the unclear boundaries between brain regions, variability across individuals, and nonlinearity of the ROIs. In response to these challenges, this paper presents a novel methodology to computationally optimize ROIs locations derived from task-based fMRI data for individuals so that the optimized ROIs are more consistent, reproducible and predictable across brains. Our computational strategy is to formulate the individual ROI location optimization as a group variance minimization problem, in which group-wise consistencies in functional/structural connectivity patterns and anatomic profiles are defined as optimization constraints. Our experimental results from multimodal fMRI and DTI data show that the optimized ROIs have significantly improved consistency in structural and functional profiles across individuals. These improved functional ROIs with better consistency could contribute to further study of functional interaction and dynamics in the human brain. PMID:22281931

Developing Optimized Trajectories Derived from Mission and Thermo-Structural Constraints

NASA Technical Reports Server (NTRS)

Lear, Matthew H.; McGrath, Brian E.; Anderson, Michael P.; Green, Peter W.

2008-01-01

In conjunction with NASA and the Department of Defense, the Johns Hopkins University Applied Physics Laboratory (JHU/APL) has been investigating analytical techniques to address many of the fundamental issues associated with solar exploration spacecraft and high-speed atmospheric vehicle systems. These issues include: thermo-structural response including the effects of thermal management via the use of surface optical properties for high-temperature composite structures; aerodynamics with the effects of non-equilibrium chemistry and gas radiation; and aero-thermodynamics with the effects of material ablation for a wide range of thermal protection system (TPS) materials. The need exists to integrate these discrete tools into a common framework that enables the investigation of interdisciplinary interactions (including analysis tool, applied load, and environment uncertainties) to provide high fidelity solutions. In addition to developing robust tools for the coupling of aerodynamically induced thermal and mechanical loads, JHU/APL has been studying the optimal design of high-speed vehicles as a function of their trajectory. Under traditional design methodology the optimization of system level mission parameters such as range and time of flight is performed independently of the optimization for thermal and mechanical constraints such as stress and temperature. A truly optimal trajectory should optimize over the entire range of mission and thermo-mechanical constraints. Under this research, a framework for the robust analysis of high-speed spacecraft and atmospheric vehicle systems has been developed. It has been built around a generic, loosely coupled framework such that a variety of readily available analysis tools can be used. The methodology immediately addresses many of the current analysis inadequacies and allows for future extension in order to handle more complex problems.

Nonlinear Multidimensional Assignment Problems Efficient Conic Optimization Methods and Applications

DTIC Science & Technology

2015-06-24

WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Arizona State University School of Mathematical & Statistical Sciences 901 S...SUPPLEMENTARY NOTES 14. ABSTRACT The major goals of this project were completed: the exact solution of previously unsolved challenging combinatorial optimization... combinatorial optimization problem, the Directional Sensor Problem, was solved in two ways. First, heuristically in an engineering fashion and second, exactly

Convergence analysis of evolutionary algorithms that are based on the paradigm of information geometry.

PubMed

Beyer, Hans-Georg

2014-01-01

The convergence behaviors of so-called natural evolution strategies (NES) and of the information-geometric optimization (IGO) approach are considered. After a review of the NES/IGO ideas, which are based on information geometry, the implications of this philosophy w.r.t. optimization dynamics are investigated considering the optimization performance on the class of positive quadratic objective functions (the ellipsoid model). Exact differential equations describing the approach to the optimizer are derived and solved. It is rigorously shown that the original NES philosophy optimizing the expected value of the objective functions leads to very slow (i.e., sublinear) convergence toward the optimizer. This is the real reason why state of the art implementations of IGO algorithms optimize the expected value of transformed objective functions, for example, by utility functions based on ranking. It is shown that these utility functions are localized fitness functions that change during the IGO flow. The governing differential equations describing this flow are derived. In the case of convergence, the solutions to these equations exhibit an exponentially fast approach to the optimizer (i.e., linear convergence order). Furthermore, it is proven that the IGO philosophy leads to an adaptation of the covariance matrix that equals in the asymptotic limit-up to a scalar factor-the inverse of the Hessian of the objective function considered.

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

Chen Qing; Department of Modern Physics, University of Science and Technology of China, Hefei 230026; Cheng Jianhua

In this paper we demonstrate that optimal 1{yields}M phase-covariant cloning quantum cloning is available via free dynamical evolution of spin networks. By properly designing the network and the couplings between spins, we show that optimal 1{yields}M phase-covariant cloning can be achieved if the initial state is prepared as a specific symmetric state. Especially, when M is an odd number, the optimal phase-covariant cloning can be achieved without ancillas. Moreover, we demonstrate that the same framework is capable for optimal 1{yields}2 universal cloning.

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

Fang Baolong; Department of Mathematics and Physics, Hefei University, Hefei, 230022; Song Qingming

We present a scheme to realize a special quantum cloning machine in separate cavities. The quantum cloning machine can copy the quantum information from a photon pulse to two distant atoms. Choosing the different parameters, the method can perform optimal symmetric (asymmetric) universal quantum cloning and optimal symmetric (asymmetric) phase-covariant cloning.

New numerical methods for open-loop and feedback solutions to dynamic optimization problems

NASA Astrophysics Data System (ADS)

Ghosh, Pradipto

The topic of the first part of this research is trajectory optimization of dynamical systems via computational swarm intelligence. Particle swarm optimization is a nature-inspired heuristic search method that relies on a group of potential solutions to explore the fitness landscape. Conceptually, each particle in the swarm uses its own memory as well as the knowledge accumulated by the entire swarm to iteratively converge on an optimal or near-optimal solution. It is relatively straightforward to implement and unlike gradient-based solvers, does not require an initial guess or continuity in the problem definition. Although particle swarm optimization has been successfully employed in solving static optimization problems, its application in dynamic optimization, as posed in optimal control theory, is still relatively new. In the first half of this thesis particle swarm optimization is used to generate near-optimal solutions to several nontrivial trajectory optimization problems including thrust programming for minimum fuel, multi-burn spacecraft orbit transfer, and computing minimum-time rest-to-rest trajectories for a robotic manipulator. A distinct feature of the particle swarm optimization implementation in this work is the runtime selection of the optimal solution structure. Optimal trajectories are generated by solving instances of constrained nonlinear mixed-integer programming problems with the swarming technique. For each solved optimal programming problem, the particle swarm optimization result is compared with a nearly exact solution found via a direct method using nonlinear programming. Numerical experiments indicate that swarm search can locate solutions to very great accuracy. The second half of this research develops a new extremal-field approach for synthesizing nearly optimal feedback controllers for optimal control and two-player pursuit-evasion games described by general nonlinear differential equations. A notable revelation from this development is that the resulting control law has an algebraic closed-form structure. The proposed method uses an optimal spatial statistical predictor called universal kriging to construct the surrogate model of a feedback controller, which is capable of quickly predicting an optimal control estimate based on current state (and time) information. With universal kriging, an approximation to the optimal feedback map is computed by conceptualizing a set of state-control samples from pre-computed extremals to be a particular realization of a jointly Gaussian spatial process. Feedback policies are computed for a variety of example dynamic optimization problems in order to evaluate the effectiveness of this methodology. This feedback synthesis approach is found to combine good numerical accuracy with low computational overhead, making it a suitable candidate for real-time applications. Particle swarm and universal kriging are combined for a capstone example, a near optimal, near-admissible, full-state feedback control law is computed and tested for the heat-load-limited atmospheric-turn guidance of an aeroassisted transfer vehicle. The performance of this explicit guidance scheme is found to be very promising; initial errors in atmospheric entry due to simulated thruster misfirings are found to be accurately corrected while closely respecting the algebraic state-inequality constraint.

Optimization of response surface and neural network models in conjugation with desirability function for estimation of nutritional needs of methionine, lysine, and threonine in broiler chickens.

PubMed

Mehri, Mehran

2014-07-01

The optimization algorithm of a model may have significant effects on the final optimal values of nutrient requirements in poultry enterprises. In poultry nutrition, the optimal values of dietary essential nutrients are very important for feed formulation to optimize profit through minimizing feed cost and maximizing bird performance. This study was conducted to introduce a novel multi-objective algorithm, desirability function, for optimization the bird response models based on response surface methodology (RSM) and artificial neural network (ANN). The growth databases on the central composite design (CCD) were used to construct the RSM and ANN models and optimal values for 3 essential amino acids including lysine, methionine, and threonine in broiler chicks have been reevaluated using the desirable function in both analytical approaches from 3 to 16 d of age. Multi-objective optimization results showed that the most desirable function was obtained for ANN-based model (D = 0.99) where the optimal levels of digestible lysine (dLys), digestible methionine (dMet), and digestible threonine (dThr) for maximum desirability were 13.2, 5.0, and 8.3 g/kg of diet, respectively. However, the optimal levels of dLys, dMet, and dThr in the RSM-based model were estimated at 11.2, 5.4, and 7.6 g/kg of diet, respectively. This research documented that the application of ANN in the broiler chicken model along with a multi-objective optimization algorithm such as desirability function could be a useful tool for optimization of dietary amino acids in fractional factorial experiments, in which the use of the global desirability function may be able to overcome the underestimations of dietary amino acids resulting from the RSM model. © 2014 Poultry Science Association Inc.

Optimal structure and parameter learning of Ising models

DOE PAGES

Lokhov, Andrey; Vuffray, Marc Denis; Misra, Sidhant; ...

2018-03-16

Reconstruction of the structure and parameters of an Ising model from binary samples is a problem of practical importance in a variety of disciplines, ranging from statistical physics and computational biology to image processing and machine learning. The focus of the research community shifted toward developing universal reconstruction algorithms that are both computationally efficient and require the minimal amount of expensive data. Here, we introduce a new method, interaction screening, which accurately estimates model parameters using local optimization problems. The algorithm provably achieves perfect graph structure recovery with an information-theoretically optimal number of samples, notably in the low-temperature regime, whichmore » is known to be the hardest for learning. Here, the efficacy of interaction screening is assessed through extensive numerical tests on synthetic Ising models of various topologies with different types of interactions, as well as on real data produced by a D-Wave quantum computer. Finally, this study shows that the interaction screening method is an exact, tractable, and optimal technique that universally solves the inverse Ising problem.« less

Optimal structure and parameter learning of Ising models

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

Lokhov, Andrey; Vuffray, Marc Denis; Misra, Sidhant

Reconstruction of the structure and parameters of an Ising model from binary samples is a problem of practical importance in a variety of disciplines, ranging from statistical physics and computational biology to image processing and machine learning. The focus of the research community shifted toward developing universal reconstruction algorithms that are both computationally efficient and require the minimal amount of expensive data. Here, we introduce a new method, interaction screening, which accurately estimates model parameters using local optimization problems. The algorithm provably achieves perfect graph structure recovery with an information-theoretically optimal number of samples, notably in the low-temperature regime, whichmore » is known to be the hardest for learning. Here, the efficacy of interaction screening is assessed through extensive numerical tests on synthetic Ising models of various topologies with different types of interactions, as well as on real data produced by a D-Wave quantum computer. Finally, this study shows that the interaction screening method is an exact, tractable, and optimal technique that universally solves the inverse Ising problem.« less

Institutional Commitment to Community Engagement: A Case Study of Makerere University

ERIC Educational Resources Information Center

Mugabi, Henry

2015-01-01

Although the earliest medieval universities began as teaching-only institutions, the university as an institution has since experienced revolutions in the way its functions are conceived. Currently, the university embraces three functions: teaching, research and community engagement. Although the teaching and research functions of the university…

The Functions of Function Discourse--University Mathematics Teaching from a Commognitive Standpoint

ERIC Educational Resources Information Center

Viirman, Olov

2014-01-01

This paper addresses a topic within university mathematics education which has been somewhat underexplored: the teaching practices actually used by university mathematics teachers when giving lectures. The study investigates the teaching practices of seven Swedish university teachers on the topic of functions using a discursive approach, the…

Performance index and meta-optimization of a direct search optimization method

NASA Astrophysics Data System (ADS)

Krus, P.; Ölvander, J.

2013-10-01

Design optimization is becoming an increasingly important tool for design, often using simulation as part of the evaluation of the objective function. A measure of the efficiency of an optimization algorithm is of great importance when comparing methods. The main contribution of this article is the introduction of a singular performance criterion, the entropy rate index based on Shannon's information theory, taking both reliability and rate of convergence into account. It can also be used to characterize the difficulty of different optimization problems. Such a performance criterion can also be used for optimization of the optimization algorithms itself. In this article the Complex-RF optimization method is described and its performance evaluated and optimized using the established performance criterion. Finally, in order to be able to predict the resources needed for optimization an objective function temperament factor is defined that indicates the degree of difficulty of the objective function.

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.

Analytical optimal pulse shapes obtained with the aid of genetic algorithms

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

Guerrero, Rubén D., E-mail: rdguerrerom@unal.edu.co; Arango, Carlos A.; Reyes, Andrés

2015-09-28

We propose a methodology to design optimal pulses for achieving quantum optimal control on molecular systems. Our approach constrains pulse shapes to linear combinations of a fixed number of experimentally relevant pulse functions. Quantum optimal control is obtained by maximizing a multi-target fitness function using genetic algorithms. As a first application of the methodology, we generated an optimal pulse that successfully maximized the yield on a selected dissociation channel of a diatomic molecule. Our pulse is obtained as a linear combination of linearly chirped pulse functions. Data recorded along the evolution of the genetic algorithm contained important information regarding themore » interplay between radiative and diabatic processes. We performed a principal component analysis on these data to retrieve the most relevant processes along the optimal path. Our proposed methodology could be useful for performing quantum optimal control on more complex systems by employing a wider variety of pulse shape functions.« less

A robust optimization methodology for preliminary aircraft design

NASA Astrophysics Data System (ADS)

Prigent, S.; Maréchal, P.; Rondepierre, A.; Druot, T.; Belleville, M.

2016-05-01

This article focuses on a robust optimization of an aircraft preliminary design under operational constraints. According to engineers' know-how, the aircraft preliminary design problem can be modelled as an uncertain optimization problem whose objective (the cost or the fuel consumption) is almost affine, and whose constraints are convex. It is shown that this uncertain optimization problem can be approximated in a conservative manner by an uncertain linear optimization program, which enables the use of the techniques of robust linear programming of Ben-Tal, El Ghaoui, and Nemirovski [Robust Optimization, Princeton University Press, 2009]. This methodology is then applied to two real cases of aircraft design and numerical results are presented.

Stability, Crisis, and Other Reasons for Optimism: University Foreign Language Education in the United States

ERIC Educational Resources Information Center

Levine, Glenn S.

2011-01-01

This article presents a brief overview of the state of university language education in the United States. Despite the impact of the world economic crisis on university language education in the United States, the profession has not yet been impacted to the extent many believe it has. Current scholarly debates allow for both a sober assessment of…

US GODAE: Global Ocean Prediction with the Hybrid Coordinate Ocean Model (HYCOM)

DTIC Science & Technology

2009-06-01

Administration, New York, NY, USA, and Earth Systems Research Laboratory, NOAA, Boulder, CO, USA. Remy Baraille is Research Scientist, Service Hydrographique...Coastal Sciences, Rutgers University, New Brunswick, NJ, USA. John Wilkin is Associate Professor, Institute of Marine and Coastal Sciences, Rutgers...University, New Brunswick, NJ, USA. Oceanography June 2009 67 coordinates (depth, density, and terrain- following) provide universal optimality, it is

Validity of the AUDIT-C screen for at-risk drinking among students utilizing university primary care.

PubMed

Campbell, Clare E; Maisto, Stephen A

2018-03-22

Research is needed to establish the psychometric properties of brief screens in university primary care settings. This study aimed to assess the construct validity of one such screen, the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C), for detecting at-risk drinking among students who have utilized on-campus primary care. 389 students recently seen in university primary care completed a confidential online survey in December 2014. Bivariate correlations between the AUDIT-C and measures of alcohol consumption and negative drinking consequences provided concurrent evidence for construct validity. Receiver Operating Characteristic curve analyses determined optimal cut-off scores for at-risk drinking. The AUDIT-C significantly correlated with measures of alcohol consumption and negative drinking consequences (p < .001). Analyses support optimal AUDIT-C cut-off scores of 5 for females and 7 for males. The AUDIT-C is a valid screen for at-risk drinking among students who utilize university primary care.

Real-time adaptive ramp metering : phase I, MILOS proof of concept (multi-objective, integrated, large-scale, optimized system).

DOT National Transportation Integrated Search

2006-12-01

Over the last several years, researchers at the University of Arizonas ATLAS Center have developed an adaptive ramp : metering system referred to as MILOS (Multi-Objective, Integrated, Large-Scale, Optimized System). The goal of this project : is ...

Conditions for Optimal Growth of Black Hole Seeds

NASA Astrophysics Data System (ADS)

Pacucci, Fabio; Natarajan, Priyamvada; Volonteri, Marta; Cappelluti, Nico; Urry, C. Megan

2017-12-01

Supermassive black holes weighing up to ˜109 M ⊙ are in place by z ˜ 7, when the age of the universe is ≲1 Gyr. This implies a time crunch for their growth, since such high masses cannot be easily reached in standard accretion scenarios. Here, we explore the physical conditions that would lead to optimal growth wherein stable super-Eddington accretion would be permitted. Our analysis suggests that the preponderance of optimal conditions depends on two key parameters: the black hole mass and the host galaxy central gas density. In the high-efficiency region of this parameter space, a continuous stream of gas can accrete onto the black hole from large to small spatial scales, assuming a global isothermal profile for the host galaxy. Using analytical initial mass functions for black hole seeds, we find an enhanced probability of high-efficiency growth for seeds with initial masses ≳104 M ⊙. Our picture suggests that a large population of high-z lower-mass black holes that formed in the low-efficiency region, with low duty cycles and accretion rates, might remain undetectable as quasars, since we predict their bolometric luminosities to be ≲1041 erg s-1. The presence of these sources might be revealed only via gravitational wave detections of their mergers.

Analog design optimization methodology for ultralow-power circuits using intuitive inversion-level and saturation-level parameters

NASA Astrophysics Data System (ADS)

Eimori, Takahisa; Anami, Kenji; Yoshimatsu, Norifumi; Hasebe, Tetsuya; Murakami, Kazuaki

2014-01-01

A comprehensive design optimization methodology using intuitive nondimensional parameters of inversion-level and saturation-level is proposed, especially for ultralow-power, low-voltage, and high-performance analog circuits with mixed strong, moderate, and weak inversion metal-oxide-semiconductor transistor (MOST) operations. This methodology is based on the synthesized charge-based MOST model composed of Enz-Krummenacher-Vittoz (EKV) basic concepts and advanced-compact-model (ACM) physics-based equations. The key concept of this methodology is that all circuit and system characteristics are described as some multivariate functions of inversion-level parameters, where the inversion level is used as an independent variable representative of each MOST. The analog circuit design starts from the first step of inversion-level design using universal characteristics expressed by circuit currents and inversion-level parameters without process-dependent parameters, followed by the second step of foundry-process-dependent design and the last step of verification using saturation-level criteria. This methodology also paves the way to an intuitive and comprehensive design approach for many kinds of analog circuit specifications by optimization using inversion-level log-scale diagrams and saturation-level criteria. In this paper, we introduce an example of our design methodology for a two-stage Miller amplifier.

Childhood amblyopia: current management and new trends.

PubMed

Tailor, Vijay; Bossi, Manuela; Greenwood, John A; Dahlmann-Noor, Annegret

2016-09-01

With a prevalence of 2-5%, amblyopia is the most common vision deficit in children in the UK and the second most common cause of functional low vision in children in low-income countries. Pubmed, Cochrane library and clinical trial registries (clinicaltrials.gov, ISRCTN, UKCRN portfolio database). Screening and treatment at the age of 4-5 years are cost efficient and clinically effective. Optical treatment (glasses) alone can improve visual acuity, with residual amblyopia treated by part-time occlusion or pharmacological blurring of the better-seeing eye. Treatment after the end of the conventional 'critical period' can improve vision, but in strabismic amblyopia carries a low risk of double vision. It is not clear whether earlier vision screening would be cost efficient and associated with better outcomes. Optimization of treatment by individualized patching regimes or early start of occlusion, and novel binocular treatment approaches may enhance adherence to treatment, provide better outcomes and shorten treatment duration. Binocular treatments for amblyopia. Impact of amblyopia on education and quality of life; optimal screening timing and tests; optimal administration of conventional treatments; development of child-friendly, effective and safe binocular treatments. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

An indirect method for numerical optimization using the Kreisselmeir-Steinhauser function

NASA Technical Reports Server (NTRS)

Wrenn, Gregory A.

1989-01-01

A technique is described for converting a constrained optimization problem into an unconstrained problem. The technique transforms one of more objective functions into reduced objective functions, which are analogous to goal constraints used in the goal programming method. These reduced objective functions are appended to the set of constraints and an envelope of the entire function set is computed using the Kreisselmeir-Steinhauser function. This envelope function is then searched for an unconstrained minimum. The technique may be categorized as a SUMT algorithm. Advantages of this approach are the use of unconstrained optimization methods to find a constrained minimum without the draw down factor typical of penalty function methods, and that the technique may be started from the feasible or infeasible design space. In multiobjective applications, the approach has the advantage of locating a compromise minimum design without the need to optimize for each individual objective function separately.

Development and characterization of a pre-treatment procedure to eliminate human monoclonal antibody therapeutic drug and matrix interference in cell-based functional neutralizing antibody assays.

PubMed

Xu, Weifeng; Jiang, Hao; Titsch, Craig; Haulenbeek, Jonathan R; Pillutla, Renuka C; Aubry, Anne-Françoise; DeSilva, Binodh S; Arnold, Mark E; Zeng, Jianing; Dodge, Robert W

2015-01-01

Biological therapeutics can induce an undesirable immune response resulting in the formation of anti-drug antibodies (ADA), including neutralizing antibodies (NAbs). Functional (usually cell-based) NAb assays are preferred to determine NAb presence in patient serum, but are often subject to interferences from numerous serum factors, such as growth factors and disease-related cytokines. Many functional cell-based NAb assays are essentially drug concentration assays that imply the presence of NAbs by the detection of small changes in functional drug concentration. Any drug contained in the test sample will increase the total amount of drug in the assay, thus reducing the sensitivity of NAb detection. Biotin-drug Extraction with Acid Dissociation (BEAD) has been successfully applied to extract ADA, thereby removing drug and other interfering factors from human serum samples. However, to date there has been no report to estimate the residual drug level after BEAD treatment when the drug itself is a human monoclonal antibody; mainly due to the limitation of traditional ligand-binding assays. Here we describe a universal BEAD optimization procedure for human monoclonal antibody (mAb) drugs by using a LC-MS/MS method to simultaneously measure drug (a mutant human IgG4), NAb positive control (a mouse IgG), and endogenous human IgGs as an indicator of nonspecific carry-over in the BEAD eluate. This is the first report demonstrating that residual human mAb drug level in clinical sample can be measured after BEAD pre-treatment, which is critical for further BEAD procedure optimization and downstream immunogenicity testing. Copyright © 2014 Elsevier B.V. All rights reserved.

Physical activity and frailty as indicators of cardiorespiratory reserve and predictors of surgical prognosis: General and digestive surgery population characterization.

PubMed

Dana, F; Capitán, D; Ubré, M; Hervás, A; Risco, R; Martínez-Pallí, G

2018-01-01

Frailty and low physical activity and cardiorespiratory reserve are related to higher perioperative morbimortality. The crucial step in improving the prognosis is to implement specific measures to optimize these aspects. It is critical to know the magnitude of the problem in order to implement preoperative optimization programmes. To characterize surgical population in a university hospital. All patients undergoing preoperative evaluation for abdominal surgery with admission were prospectively included during a 3-month period. Level of physical activity, functional capacity, frailty and emotional state were assessed using score tests. Additionally, physical condition was evaluated using 5 Times Sit-to-Stand Test. Demographic, clinical and surgical data were collected. One hundred and forty patients were included (60±15yr-old, 56% male, 25% ASA III or IV). Forty-nine percent of patients were proposed for oncologic surgery and 13% of which had received neoadjuvant treatment. Seventy percent of patients presented a low functional capacity and were sedentary. Eighteen percent of patients were considered frail and more than 50% completed the 5 Times Sit-to-Stand Test at a higher time than the reference values adjusted to age and sex. Advanced age, ASA III/IV, sedentarism, frailty and a high level of anxiety and depression were related to a lower functional capacity. The surgical population of our area has a low functional reserve and a high index of sedentary lifestyle and frailty, predictors of postoperative morbidity. It is mandatory to implement preoperative measures to identify population at risk and prehabilitation programmes, considered highly promising preventive interventions towards improving surgical outcome. Copyright © 2017 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Publicado por Elsevier España, S.L.U. All rights reserved.

Error-based analysis of optimal tuning functions explains phenomena observed in sensory neurons.

PubMed

Yaeli, Steve; Meir, Ron

2010-01-01

Biological systems display impressive capabilities in effectively responding to environmental signals in real time. There is increasing evidence that organisms may indeed be employing near optimal Bayesian calculations in their decision-making. An intriguing question relates to the properties of optimal encoding methods, namely determining the properties of neural populations in sensory layers that optimize performance, subject to physiological constraints. Within an ecological theory of neural encoding/decoding, we show that optimal Bayesian performance requires neural adaptation which reflects environmental changes. Specifically, we predict that neuronal tuning functions possess an optimal width, which increases with prior uncertainty and environmental noise, and decreases with the decoding time window. Furthermore, even for static stimuli, we demonstrate that dynamic sensory tuning functions, acting at relatively short time scales, lead to improved performance. Interestingly, the narrowing of tuning functions as a function of time was recently observed in several biological systems. Such results set the stage for a functional theory which may explain the high reliability of sensory systems, and the utility of neuronal adaptation occurring at multiple time scales.

Optimization of removal function in computer controlled optical surfacing

NASA Astrophysics Data System (ADS)

Chen, Xi; Guo, Peiji; Ren, Jianfeng

2010-10-01

The technical principle of computer controlled optical surfacing (CCOS) and the common method of optimizing removal function that is used in CCOS are introduced in this paper. A new optimizing method time-sharing synthesis of removal function is proposed to solve problems of the removal function being far away from Gaussian type and slow approaching of the removal function error that encountered in the mode of planet motion or translation-rotation. Detailed time-sharing synthesis of using six removal functions is discussed. For a given region on the workpiece, six positions are selected as the centers of the removal function; polishing tool controlled by the executive system of CCOS revolves around each centre to complete a cycle in proper order. The overall removal function obtained by the time-sharing process is the ratio of total material removal in six cycles to time duration of the six cycles, which depends on the arrangement and distribution of the six removal functions. Simulations on the synthesized overall removal functions under two different modes of motion, i.e., planet motion and translation-rotation are performed from which the optimized combination of tool parameters and distribution of time-sharing synthesis removal functions are obtained. The evaluation function when optimizing is determined by an approaching factor which is defined as the ratio of the material removal within the area of half of the polishing tool coverage from the polishing center to the total material removal within the full polishing tool coverage area. After optimization, it is found that the optimized removal function obtained by time-sharing synthesis is closer to the ideal Gaussian type removal function than those by the traditional methods. The time-sharing synthesis method of the removal function provides an efficient way to increase the convergence speed of the surface error in CCOS for the fabrication of aspheric optical surfaces, and to reduce the intermediate- and high-frequency error.

American School & University. Volume 76, Number 5

ERIC Educational Resources Information Center

Agron, Joe, Ed.

2004-01-01

Each month "American School & University" provides a mix of thought-provoking features, how-to-articles, industry reports, exclusive surveys, new sections, insightful columns, new product introductions and case histories to assist education officials in better performing their jobs. This January 2004 issue includes the following: "Optimism in…

Optimization of High-Dimensional Functions through Hypercube Evaluation

PubMed Central

Abiyev, Rahib H.; Tunay, Mustafa

2015-01-01

A novel learning algorithm for solving global numerical optimization problems is proposed. The proposed learning algorithm is intense stochastic search method which is based on evaluation and optimization of a hypercube and is called the hypercube optimization (HO) algorithm. The HO algorithm comprises the initialization and evaluation process, displacement-shrink process, and searching space process. The initialization and evaluation process initializes initial solution and evaluates the solutions in given hypercube. The displacement-shrink process determines displacement and evaluates objective functions using new points, and the search area process determines next hypercube using certain rules and evaluates the new solutions. The algorithms for these processes have been designed and presented in the paper. The designed HO algorithm is tested on specific benchmark functions. The simulations of HO algorithm have been performed for optimization of functions of 1000-, 5000-, or even 10000 dimensions. The comparative simulation results with other approaches demonstrate that the proposed algorithm is a potential candidate for optimization of both low and high dimensional functions. PMID:26339237

Research on an augmented Lagrangian penalty function algorithm for nonlinear programming

NASA Technical Reports Server (NTRS)

Frair, L.

1978-01-01

The augmented Lagrangian (ALAG) Penalty Function Algorithm for optimizing nonlinear mathematical models is discussed. The mathematical models of interest are deterministic in nature and finite dimensional optimization is assumed. A detailed review of penalty function techniques in general and the ALAG technique in particular is presented. Numerical experiments are conducted utilizing a number of nonlinear optimization problems to identify an efficient ALAG Penalty Function Technique for computer implementation.

Plate/shell structure topology optimization of orthotropic material for buckling problem based on independent continuous topological variables

NASA Astrophysics Data System (ADS)

Ye, Hong-Ling; Wang, Wei-Wei; Chen, Ning; Sui, Yun-Kang

2017-10-01

The purpose of the present work is to study the buckling problem with plate/shell topology optimization of orthotropic material. A model of buckling topology optimization is established based on the independent, continuous, and mapping method, which considers structural mass as objective and buckling critical loads as constraints. Firstly, composite exponential function (CEF) and power function (PF) as filter functions are introduced to recognize the element mass, the element stiffness matrix, and the element geometric stiffness matrix. The filter functions of the orthotropic material stiffness are deduced. Then these filter functions are put into buckling topology optimization of a differential equation to analyze the design sensitivity. Furthermore, the buckling constraints are approximately expressed as explicit functions with respect to the design variables based on the first-order Taylor expansion. The objective function is standardized based on the second-order Taylor expansion. Therefore, the optimization model is translated into a quadratic program. Finally, the dual sequence quadratic programming (DSQP) algorithm and the global convergence method of moving asymptotes algorithm with two different filter functions (CEF and PF) are applied to solve the optimal model. Three numerical results show that DSQP&CEF has the best performance in the view of structural mass and discretion.

Pre-liver transplant psychosocial evaluation predicts post-transplantation outcomes.

PubMed

Benson, Ariel A; Rowe, Mina; Eid, Ahmad; Bluth, Keren; Merhav, Hadar; Khalaileh, Abed; Safadi, Rifaat

2018-08-01

Psychosocial factors greatly impact the course of patients throughout the liver transplantation process. A retrospective chart review was performed of patients who underwent liver transplantation at Hadassah-Hebrew University Medical Center between 2002 and 2012. A composite psychosocial score was computed based on the patient's pre-transplant evaluation. Patients were divided into two groups based on compliance, support and insight: Optimal psychosocial score and Non-optimal psychosocial score. Post-liver transplantation survival and complication rates were evaluated. Out of 100 patients who underwent liver transplantation at the Hadassah-Hebrew University Medical Center between 2002 and 2012, 93% had a complete pre-liver transplant psychosocial evaluation in the medical record performed by professional psychologists and social workers. Post-liver transplantation survival was significantly higher in the Optimal group (85%) as compared to the Non-optimal group (56%, p = .002). Post-liver transplantation rate of renal failure was significantly lower in the Optimal group. No significant differences were observed between the groups in other post-transplant complications. A patient's psychosocial status may impact outcomes following transplantation as inferior psychosocial grades were associated with lower overall survival and increased rates of complications. Pre-liver transplant psychosocial evaluations are an important tool to help predict survival following transplantation.

Compliance with AAPM Practice Guideline 1.a: CT Protocol Management and Review — from the perspective of a university hospital

PubMed Central

Bour, Robert K.; Pozniak, Myron; Ranallo, Frank N.

2015-01-01

The purpose of this paper is to describe our experience with the AAPM Medical Physics Practice Guideline 1.a: “CT Protocol Management and Review Practice Guideline”. Specifically, we will share how our institution's quality management system addresses the suggestions within the AAPM practice report. We feel this paper is needed as it was beyond the scope of the AAPM practice guideline to provide specific details on fulfilling individual guidelines. Our hope is that other institutions will be able to emulate some of our practices and that this article would encourage other types of centers (e.g., community hospitals) to share their methodology for approaching CT protocol optimization and quality control. Our institution had a functioning CT protocol optimization process, albeit informal, since we began using CT. Recently, we made our protocol development and validation process compliant with a number of the ISO 9001:2008 clauses and this required us to formalize the roles of the members of our CT protocol optimization team. We rely heavily on PACS‐based IT solutions for acquiring radiologist feedback on the performance of our CT protocols and the performance of our CT scanners in terms of dose (scanner output) and the function of the automatic tube current modulation. Specific details on our quality management system covering both quality control and ongoing optimization have been provided. The roles of each CT protocol team member have been defined, and the critical role that IT solutions provides for the management of files and the monitoring of CT protocols has been reviewed. In addition, the invaluable role management provides by being a champion for the project has been explained; lack of a project champion will mitigate the efforts of a CT protocol optimization team. Meeting the guidelines set forth in the AAPM practice guideline was not inherently difficult, but did, in our case, require the cooperation of radiologists, technologists, physicists, IT, administrative staff, and hospital management. Some of the IT solutions presented in this paper are novel and currently unique to our institution. PACS number: 87.57.Q PMID:26103176

The Functional Breakdown Structure (FBS) and Its Relationship to Life Cycle Cost

NASA Technical Reports Server (NTRS)

DeHoff, Bryan; Levack, Danie J. H.; Rhodes, Russell E.

2009-01-01

The Functional Breakdown Structure (FBS) is a structured, modular breakdown of every function that must be addressed to perform a generic mission. It is also usable for any subset of the mission. Unlike a Work Breakdown Structure (WBS), the FBS is a function-oriented tree, not a product-oriented tree. The FBS details not products, but operations or activities that should be performed. The FBS is not tied to any particular architectural implementation because it is a listing of the needed functions, not the elements, of the architecture. The FBS for Space Transportation Systems provides a universal hierarchy of required functions, which include ground and space operations as well as infrastructure - it provides total visibility of the entire mission. By approaching the systems engineering problem from the functional view, instead of the element or hardware view, the SPST has created an exhaustive list of potential requirements which the architecture designers can use to evaluate the completeness of their designs. This is a new approach that will provide full accountability of all functions required to perform the planned mission. It serves as a giant check list to be sure that no functions are omitted, especially in the early architectural design phase. A significant characteristic of a FBS is that if architecture options are compared using this approach, then any missing or redundant elements of each option will be ' identified. Consequently, valid Life Cycle Costs (LCC) comparisons can be made. For example, one architecture option might not need a particular function while another option does. One option may have individual elements to perform each of three functions while another option needs only one element to perform the three functions. Once an architecture has been selected, the FBS will serve as a guide in development of the work breakdown structure, provide visibility of those technologies that need to be further developed to perform required functions, and help identify the personnel skills required to develop and operate the architecture. It also wifi allow the systems engineering activities to totally integrate each discipline to the maximum extent possible and optimize at the total system level, thus avoiding optimizing at the element level (stove-piping). In addition, it furnishes a framework that wifi help prevent over or under specifying requirements because all functions are identified and all elements are aligned to functions.

Evaluation of the selection methods used in the exIWO algorithm based on the optimization of multidimensional functions

NASA Astrophysics Data System (ADS)

Kostrzewa, Daniel; Josiński, Henryk

2016-06-01

The expanded Invasive Weed Optimization algorithm (exIWO) is an optimization metaheuristic modelled on the original IWO version inspired by dynamic growth of weeds colony. The authors of the present paper have modified the exIWO algorithm introducing a set of both deterministic and non-deterministic strategies of individuals' selection. The goal of the project was to evaluate the modified exIWO by testing its usefulness for multidimensional numerical functions optimization. The optimized functions: Griewank, Rastrigin, and Rosenbrock are frequently used as benchmarks because of their characteristics.

Structural optimization of framed structures using generalized optimality criteria

NASA Technical Reports Server (NTRS)

Kolonay, R. M.; Venkayya, Vipperla B.; Tischler, V. A.; Canfield, R. A.

1989-01-01

The application of a generalized optimality criteria to framed structures is presented. The optimality conditions, Lagrangian multipliers, resizing algorithm, and scaling procedures are all represented as a function of the objective and constraint functions along with their respective gradients. The optimization of two plane frames under multiple loading conditions subject to stress, displacement, generalized stiffness, and side constraints is presented. These results are compared to those found by optimizing the frames using a nonlinear mathematical programming technique.

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

Spagnolo, Nicolo; Consorzio Interuniversitario per le Scienze Fisiche della Materia, piazzale Aldo Moro 5, I-00185 Roma; Sciarrino, Fabio

We show that the quantum states generated by universal optimal quantum cloning of a single photon represent a universal set of quantum superpositions resilient to decoherence. We adopt the Bures distance as a tool to investigate the persistence of quantum coherence of these quantum states. According to this analysis, the process of universal cloning realizes a class of quantum superpositions that exhibits a covariance property in lossy configuration over the complete set of polarization states in the Bloch sphere.

Performance Envelopes and Optimal Appropriateness Measurement.

DTIC Science & Technology

1984-12-01

20370 Dr. Hans Crombag University of Leyden Mr. Raymond E. Christal Education Research Center AFHRL/MOE Boerhaavelaan 2 Brooks AFB, TX 78235 2334 EN... Leyden The NETHERLANDS Dr. Norman Cliff Department of Psychology CTB/McGraw-Hill Library Univ. of So. California 2500 Garden Road University Park...Psychology Dr William Montague University of Western Australia NPRDC Code 13 Nedlands W.A. 6009 San Diego, CA 92152 AUSTRALIA Ms. Kathleen Moreno Dr

Campus Energy Approach, REopt Overview, and Solar for Universities

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

Elgqvist, Emma M; Van Geet, Otto D

2017-10-19

This presentation gives an overview of the climate neutral research campus framework for reducing energy use and meeting net zero electricity on research campuses. It gives an overview of REopt and the REopt Lite web tool, which can be used to evaluate cost optimal sizes of behind the meter PV and storage. It includes solar PV installation trends at universities and case studies for projects implemented on university campuses.

Jointly Optimal Design for MIMO Radar Frequency-Hopping Waveforms Using Game Theory

DTIC Science & Technology

2016-04-01

Washington University in St . Louis St . Louis, MO, USA Using a colocated multiple input/multiple output (MIMO) radar system, we consider the problem of...Authors’ address: Preston M. Green Department of Electrical and Systems Engineering, Washington University in St . Louis, St . Louis, MO, 63130...engineering from Washington University in St . Louis, under the guidance of Dr. Arye Nehorai, in 2012 and 2015, respectively. His research interests

Optimization of an exchange-correlation density functional for water

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

Fritz, Michelle; Fernández-Serra, Marivi; Institute for Advanced Computational Science, Stony Brook University, Stony Brook, New York 11794-3800

2016-06-14

We describe a method, that we call data projection onto parameter space (DPPS), to optimize an energy functional of the electron density, so that it reproduces a dataset of experimental magnitudes. Our scheme, based on Bayes theorem, constrains the optimized functional not to depart unphysically from existing ab initio functionals. The resulting functional maximizes the probability of being the “correct” parameterization of a given functional form, in the sense of Bayes theory. The application of DPPS to water sheds new light on why density functional theory has performed rather poorly for liquid water, on what improvements are needed, and onmore » the intrinsic limitations of the generalized gradient approximation to electron exchange and correlation. Finally, we present tests of our water-optimized functional, that we call vdW-DF-w, showing that it performs very well for a variety of condensed water systems.« less

Optimization and guidance of flight trajectories for the national aerospace plane

NASA Technical Reports Server (NTRS)

Miele, Angelo

1990-01-01

The research on optimal trajectories for the National Aerospace Plane (NASP) performed by the Aero-Astronautics Group of Rice University from June 22, 1989 to December 31, 1990 is summarized. The aerospace plane is assumed to be controlled via the angle of attack and the power setting. The time history of the controls is optimized simultaneously with the switch times from one powerplant to another and the final time. The intent is to arrive at NASP guidance trajectories exhibiting many of the desirable characteristics of NASP optimal trajectories.

Parametric Optimization of Some Critical Operating System Functions--An Alternative Approach to the Study of Operating Systems Design

ERIC Educational Resources Information Center

Sobh, Tarek M.; Tibrewal, Abhilasha

2006-01-01

Operating systems theory primarily concentrates on the optimal use of computing resources. This paper presents an alternative approach to teaching and studying operating systems design and concepts by way of parametrically optimizing critical operating system functions. Detailed examples of two critical operating systems functions using the…

Sustainability for the Americas Initiative: Land Design Institute, Ball State University

Treesearch

J. L. Motloch; Pedro Pacheco; Eloy F. Jr. Casagrande

2006-01-01

The Ball State University Land Design Institute (LDI) pursues ecologically and culturally sustainable land design through education, research, outreach, and demonstration. LDI seeks to lead communities (local, regional, global) to sustainable futures. It connects communities and sustainability experts to optimize education about land management, planning, and design...

Flex Year: A Concept to Optimize Human Resources.

ERIC Educational Resources Information Center

Wulf, Gary W.

1981-01-01

Flex Year, which was designed to provide a variety of work schedules for employees, tailored to the college or university's needs and the individual's preference, is being used within the university system of New Hampshire. This concept provides for year-round employment with voluntary leaves without pay. (MLW)

When "Less is More": The Optimal Design of Language Laboratory Hardware.

ERIC Educational Resources Information Center

Kershaw, Gary; Boyd, Gary

1980-01-01

The results of a process of designing, building, and "de-bugging" two replacement language laboratory hardware systems at Concordia University (Montreal) are described. Because commercially available systems did not meet specifications within budgetary constraints, the systems were built by the university technical department. The systems replaced…

Health Coaching to Optimize Well-Being among Returning Veterans with Suicide Risk

DTIC Science & Technology

2017-10-01

AWARD NUMBER: W81XWH-16-1-0630 TITLE: Health Coaching to Optimize Well-Being among Returning Veterans with Suicide Risk PRINCIPAL INVESTIGATOR...Lauren M. Denneson, PhD CONTRACTING ORGANIZATION: Oregon Health & Science University Portland, OR 97239 REPORT DATE: October 2017 TYPE OF...COVERED (From - To) 15 Sept 2016 - 14 Sept 2017 4. TITLE AND SUBTITLE Health Coaching to Optimize Well-Being among Returning Veterans with Suicide Risk

Using Approximations to Accelerate Engineering Design Optimization

NASA Technical Reports Server (NTRS)

Torczon, Virginia; Trosset, Michael W.

1998-01-01

Optimization problems that arise in engineering design are often characterized by several features that hinder the use of standard nonlinear optimization techniques. Foremost among these features is that the functions used to define the engineering optimization problem often are computationally intensive. Within a standard nonlinear optimization algorithm, the computational expense of evaluating the functions that define the problem would necessarily be incurred for each iteration of the optimization algorithm. Faced with such prohibitive computational costs, an attractive alternative is to make use of surrogates within an optimization context since surrogates can be chosen or constructed so that they are typically much less expensive to compute. For the purposes of this paper, we will focus on the use of algebraic approximations as surrogates for the objective. In this paper we introduce the use of so-called merit functions that explicitly recognize the desirability of improving the current approximation to the objective during the course of the optimization. We define and experiment with the use of merit functions chosen to simultaneously improve both the solution to the optimization problem (the objective) and the quality of the approximation. Our goal is to further improve the effectiveness of our general approach without sacrificing any of its rigor.

Increasing Optimism Protects Against Pain-Induced Impairment in Task-Shifting Performance.

PubMed

Boselie, Jantine J L M; Vancleef, Linda M G; Peters, Madelon L

2017-04-01

Persistent pain can lead to difficulties in executive task performance. Three core executive functions that are often postulated are inhibition, updating, and shifting. Optimism, the tendency to expect that good things happen in the future, has been shown to protect against pain-induced performance deterioration in executive function updating. This study tested whether this protective effect of a temporary optimistic state by means of a writing and visualization exercise extended to executive function shifting. A 2 (optimism: optimism vs no optimism) × 2 (pain: pain vs no pain) mixed factorial design was conducted. Participants (N = 61) completed a shifting task once with and once without concurrent painful heat stimulation after an optimism or neutral manipulation. Results showed that shifting performance was impaired when experimental heat pain was applied during task execution, and that optimism counteracted pain-induced deterioration in task-shifting performance. Experimentally-induced heat pain impairs shifting task performance and manipulated optimism or induced optimism counteracted this pain-induced performance deterioration. Identifying psychological factors that may diminish the negative effect of persistent pain on the ability to function in daily life is imperative. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

Improving ATLAS grid site reliability with functional tests using HammerCloud

NASA Astrophysics Data System (ADS)

Elmsheuser, Johannes; Legger, Federica; Medrano Llamas, Ramon; Sciacca, Gianfranco; van der Ster, Dan

2012-12-01

With the exponential growth of LHC (Large Hadron Collider) data in 2011, and more coming in 2012, distributed computing has become the established way to analyse collider data. The ATLAS grid infrastructure includes almost 100 sites worldwide, ranging from large national computing centers to smaller university clusters. These facilities are used for data reconstruction and simulation, which are centrally managed by the ATLAS production system, and for distributed user analysis. To ensure the smooth operation of such a complex system, regular tests of all sites are necessary to validate the site capability of successfully executing user and production jobs. We report on the development, optimization and results of an automated functional testing suite using the HammerCloud framework. Functional tests are short lightweight applications covering typical user analysis and production schemes, which are periodically submitted to all ATLAS grid sites. Results from those tests are collected and used to evaluate site performances. Sites that fail or are unable to run the tests are automatically excluded from the PanDA brokerage system, therefore avoiding user or production jobs to be sent to problematic sites.

Metal Composition and Polyethylenimine Doping Capacity Effects on Semiconducting Metal Oxide-Polymer Blend Charge Transport.

PubMed

Huang, Wei; Guo, Peijun; Zeng, Li; Li, Ran; Wang, Binghao; Wang, Gang; Zhang, Xinan; Chang, Robert P H; Yu, Junsheng; Bedzyk, Michael J; Marks, Tobin J; Facchetti, Antonio

2018-04-25

Charge transport and film microstructure evolution are investigated in a series of polyethylenimine (PEI)-doped (0.0-6.0 wt%) amorphous metal oxide (MO) semiconductor thin film blends. Here, PEI doping generality is broadened from binary In 2 O 3 to ternary (e.g., In+Zn in IZO, In+Ga in IGO) and quaternary (e.g., In+Zn+Ga in IGZO) systems, demonstrating the universality of this approach for polymer electron doping of MO matrices. Systematic comparison of the effects of various metal ions on the electronic transport and film microstructure of these blends are investigated by combined thin-film transistor (TFT) response, AFM, XPS, XRD, X-ray reflectivity, and cross-sectional TEM. Morphological analysis reveals that layered MO film microstructures predominate in PEI-In 2 O 3 , but become less distinct in IGO and are not detectable in IZO and IGZO. TFT charge transport measurements indicate a general coincidence of a peak in carrier mobility (μ peak ) and overall TFT performance at optimal PEI doping concentrations. Optimal PEI loadings that yield μ peak values depend not only on the MO elemental composition but also, equally important, on the metal atomic ratios. By investigating the relationship between the MO energy levels and PEI doping by UPS, it is concluded that the efficiency of PEI electron-donation is highly dependent on the metal oxide matrix work function in cases where film morphology is optimal, as in the IGO compositions. The results of this investigation demonstrate the broad generality and efficacy of PEI electron doping applied to electronically functional metal oxide systems and that the resulting film microstructure, morphology, and energy level modifications are all vital to understanding charge transport in these amorphous oxide blends.

Student project of optical system analysis API-library development

NASA Astrophysics Data System (ADS)

Ivanova, Tatiana; Zhukova, Tatiana; Dantcaranov, Ruslan; Romanova, Maria; Zhadin, Alexander; Ivanov, Vyacheslav; Kalinkina, Olga

2017-08-01

In the paper API-library software developed by students of Applied and Computer Optics Department (ITMO University) for optical system design is presented. The library performs paraxial and real ray tracing, calculates 3d order (Seidel) aberration and real ray aberration of axis and non-axis beams (wave, lateral, longitudinal, coma, distortion etc.) and finally, approximate wave aberration by Zernike polynomials. Real aperture can be calculated by considering of real rays tracing failure on each surface. So far we assume optical system is centered, with spherical or 2d order aspherical surfaces. Optical glasses can be set directly by refraction index or by dispersion coefficients. The library can be used for education or research purposes in optical system design area. It provides ready to use software functions for optical system simulation and analysis that developer can simply plug into their software development for different purposes, for example for some specific synthesis tasks or investigation of new optimization modes. In the paper we present an example of using the library for development of cemented doublet synthesis software based on Slusarev's methodology. The library is used in optical system optimization recipes course for deep studying of optimization model and its application for optical system design. Development of such software is an excellent experience for students and help to understanding optical image modeling and quality analysis. This development is organized as student group joint project. We try to organize it as a group in real research and development project, so each student has his own role in the project and then use whole library functionality in his own master or bachelor thesis. Working in such group gives students useful experience and opportunity to work as research and development engineer of scientific software in the future.

Formal development of a clock synchronization circuit

NASA Technical Reports Server (NTRS)

Miner, Paul S.

1995-01-01

This talk presents the latest stage in formal development of a fault-tolerant clock synchronization circuit. The development spans from a high level specification of the required properties to a circuit realizing the core function of the system. An abstract description of an algorithm has been verified to satisfy the high-level properties using the mechanical verification system EHDM. This abstract description is recast as a behavioral specification input to the Digital Design Derivation system (DDD) developed at Indiana University. DDD provides a formal design algebra for developing correct digital hardware. Using DDD as the principle design environment, a core circuit implementing the clock synchronization algorithm was developed. The design process consisted of standard DDD transformations augmented with an ad hoc refinement justified using the Prototype Verification System (PVS) from SRI International. Subsequent to the above development, Wilfredo Torres-Pomales discovered an area-efficient realization of the same function. Establishing correctness of this optimization requires reasoning in arithmetic, so a general verification is outside the domain of both DDD transformations and model-checking techniques. DDD represents digital hardware by systems of mutually recursive stream equations. A collection of PVS theories was developed to aid in reasoning about DDD-style streams. These theories include a combinator for defining streams that satisfy stream equations, and a means for proving stream equivalence by exhibiting a stream bisimulation. DDD was used to isolate the sub-system involved in Torres-Pomales' optimization. The equivalence between the original design and the optimized verified was verified in PVS by exhibiting a suitable bisimulation. The verification depended upon type constraints on the input streams and made extensive use of the PVS type system. The dependent types in PVS provided a useful mechanism for defining an appropriate bisimulation.

Optimal Operation of a Thermal Energy Storage Tank Using Linear Optimization

NASA Astrophysics Data System (ADS)

Civit Sabate, Carles

In this thesis, an optimization procedure for minimizing the operating costs of a Thermal Energy Storage (TES) tank is presented. The facility in which the optimization is based is the combined cooling, heating, and power (CCHP) plant at the University of California, Irvine. TES tanks provide the ability of decoupling the demand of chilled water from its generation, over the course of a day, from the refrigeration and air-conditioning plants. They can be used to perform demand-side management, and optimization techniques can help to approach their optimal use. The proposed optimization approach provides a fast and reliable methodology of finding the optimal use of the TES tank to reduce energy costs and provides a tool for future implementation of optimal control laws on the system. Advantages of the proposed methodology are studied using simulation with historical data.

Quantum cost optimized design of 4-bit reversible universal shift register using reduced number of logic gate

NASA Astrophysics Data System (ADS)

Maity, H.; Biswas, A.; Bhattacharjee, A. K.; Pal, A.

In this paper, we have proposed the design of quantum cost (QC) optimized 4-bit reversible universal shift register (RUSR) using reduced number of reversible logic gates. The proposed design is very useful in quantum computing due to its low QC, less no. of reversible logic gate and less delay. The QC, no. of gates, garbage outputs (GOs) are respectively 64, 8 and 16 for proposed work. The improvement of proposed work is also presented. The QC is 5.88% to 70.9% improved, no. of gate is 60% to 83.33% improved with compared to latest reported result.

Comment on ``Ratchet universality in the presence of thermal noise''

NASA Astrophysics Data System (ADS)

Quintero, Niurka R.; Alvarez-Nodarse, Renato; Cuesta, José A.

2013-12-01

A recent paper [P. J. Martínez and R. Chacón, Phys. Rev. EPLEEE81539-375510.1103/PhysRevE.87.062114 87, 062114 (2013)] presents numerical simulations on a system exhibiting directed ratchet transport of a driven overdamped Brownian particle subjected to a spatially periodic, symmetric potential. The authors claim that their simulations prove the existence of a universal waveform of the external force that optimally enhances directed transport, hence confirming the validity of a previous conjecture put forth by one of them in the limit of vanishing noise intensity. With minor corrections due to noise, the conjecture holds even in the presence of noise, according to the authors. On the basis of their results the authors claim that all previous theories, which predict a different optimal force waveform, are incorrect. In this Comment we provide sufficient numerical evidence showing that there is no such universal force waveform and that the evidence obtained by the authors otherwise is due to their particular choice of parameters. Our simulations also suggest that previous theories correctly predict the shape of the optimal waveform within their validity regime, namely, when the forcing is weak. On the contrary, the aforementioned conjecture does not hold.

Comment on "Ratchet universality in the presence of thermal noise".

PubMed

Quintero, Niurka R; Alvarez-Nodarse, Renato; Cuesta, José A

2013-12-01

A recent paper [P. J. Martínez and R. Chacón, Phys. Rev. E 87, 062114 (2013)] presents numerical simulations on a system exhibiting directed ratchet transport of a driven overdamped Brownian particle subjected to a spatially periodic, symmetric potential. The authors claim that their simulations prove the existence of a universal waveform of the external force that optimally enhances directed transport, hence confirming the validity of a previous conjecture put forth by one of them in the limit of vanishing noise intensity. With minor corrections due to noise, the conjecture holds even in the presence of noise, according to the authors. On the basis of their results the authors claim that all previous theories, which predict a different optimal force waveform, are incorrect. In this Comment we provide sufficient numerical evidence showing that there is no such universal force waveform and that the evidence obtained by the authors otherwise is due to their particular choice of parameters. Our simulations also suggest that previous theories correctly predict the shape of the optimal waveform within their validity regime, namely, when the forcing is weak. On the contrary, the aforementioned conjecture does not hold.

Sugars as the Optimal Biosynthetic Carbon Substrate of Aqueous Life throughout the Universe

NASA Technical Reports Server (NTRS)

Weber, Arthur L.

1999-01-01

Our previous analysis of the energetics of metabolism showed that both the biosynthesis of amino acids and lipids from sugars, and the fermentation of organic substrates, were energetically driven by electron transfer reactions resulting in carbon redox disproportionation (Weber 1997). Redox disproportionation -- the spontaneous (energetically favorable) direction of carbon group transformation in biosynthesis -- is brought about and driven by the energetically downhill transfer of electron pairs from more oxidized carbon groups (with lower half-cell reduction potentials) to more reduced carbon groups (with higher half-cell reduction potentials). In this report, we compare the redox and kinetic properties of carbon groups in order to evaluate the relative biosynthetic capability of organic substrates, and to identify the optimal biosubstrate. This analysis revealed that sugars (monocarbonyl alditols) are the optimal biosynthetic substrate because they contain the maximum number of biosynthetically useful .high energy electrons/carbon atom , while still containing a single carbonyl group needed to kinetically facilitate their conversion to useful biosynthetic intermediates. This conclusion applies to aqueous life throughout the Universe because it is based on invariant aqueous carbon chemistry -- primarily, the universal reduction potentials of carbon groups.

Sugars as the optimal biosynthetic carbon substrate of aqueous life throughout the universe

NASA Technical Reports Server (NTRS)

Weber, A. L.

2000-01-01

Our previous analysis of the energetics of metabolism showed that both the biosynthesis of amino acids and lipids from sugars, and the fermentation of organic substrates, were energetically driven by electron transfer reactions resulting in carbon redox disproportionation (Weber, 1997). Redox disproportionation--the spontaneous (energetically favorable) direction of carbon group transformation in biosynthesis--is brought about and driven by the energetically downhill transfer of electron pairs from more oxidized carbon groups (with lower half-cell reduction potentials) to more reduced carbon groups (with higher half-cell reduction potentials). In this report, we compare the redox and kinetic properties of carbon groups in order to evaluate the relative biosynthetic capability of organic substrates, and to identify the optimal biosubstrate. This analysis revealed that sugars (monocarbonyl alditols) are the optimal biosynthetic substrate because they contain the maximum number of biosynthetically useful high energy electrons/carbon atom while still containing a single carbonyl group needed to kinetically facilitate their conversion to useful biosynthetic intermediates. This conclusion applies to aqueous life throughout the Universe because it is based on invariant aqueous carbon chemistry--primarily, the universal reduction potentials of carbon groups.

Coordinated Optimization of Visual Cortical Maps (I) Symmetry-based Analysis

PubMed Central

Reichl, Lars; Heide, Dominik; Löwel, Siegrid; Crowley, Justin C.; Kaschube, Matthias; Wolf, Fred

2012-01-01

In the primary visual cortex of primates and carnivores, functional architecture can be characterized by maps of various stimulus features such as orientation preference (OP), ocular dominance (OD), and spatial frequency. It is a long-standing question in theoretical neuroscience whether the observed maps should be interpreted as optima of a specific energy functional that summarizes the design principles of cortical functional architecture. A rigorous evaluation of this optimization hypothesis is particularly demanded by recent evidence that the functional architecture of orientation columns precisely follows species invariant quantitative laws. Because it would be desirable to infer the form of such an optimization principle from the biological data, the optimization approach to explain cortical functional architecture raises the following questions: i) What are the genuine ground states of candidate energy functionals and how can they be calculated with precision and rigor? ii) How do differences in candidate optimization principles impact on the predicted map structure and conversely what can be learned about a hypothetical underlying optimization principle from observations on map structure? iii) Is there a way to analyze the coordinated organization of cortical maps predicted by optimization principles in general? To answer these questions we developed a general dynamical systems approach to the combined optimization of visual cortical maps of OP and another scalar feature such as OD or spatial frequency preference. From basic symmetry assumptions we obtain a comprehensive phenomenological classification of possible inter-map coupling energies and examine representative examples. We show that each individual coupling energy leads to a different class of OP solutions with different correlations among the maps such that inferences about the optimization principle from map layout appear viable. We systematically assess whether quantitative laws resembling experimental observations can result from the coordinated optimization of orientation columns with other feature maps. PMID:23144599

A new optimal sliding mode controller design using scalar sign function.

PubMed

Singla, Mithun; Shieh, Leang-San; Song, Gangbing; Xie, Linbo; Zhang, Yongpeng

2014-03-01

This paper presents a new optimal sliding mode controller using the scalar sign function method. A smooth, continuous-time scalar sign function is used to replace the discontinuous switching function in the design of a sliding mode controller. The proposed sliding mode controller is designed using an optimal Linear Quadratic Regulator (LQR) approach. The sliding surface of the system is designed using stable eigenvectors and the scalar sign function. Controller simulations are compared with another existing optimal sliding mode controller. To test the effectiveness of the proposed controller, the controller is implemented on an aluminum beam with piezoceramic sensor and actuator for vibration control. This paper includes the control design and stability analysis of the new optimal sliding mode controller, followed by simulation and experimental results. The simulation and experimental results show that the proposed approach is very effective. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Full Wave Function Optimization with Quantum Monte Carlo and Its Effect on the Dissociation Energy of FeS.

PubMed

Haghighi Mood, Kaveh; Lüchow, Arne

2017-08-17

Diffusion quantum Monte Carlo calculations with partial and full optimization of the guide function are carried out for the dissociation of the FeS molecule. For the first time, quantum Monte Carlo orbital optimization for transition metal compounds is performed. It is demonstrated that energy optimization of the orbitals of a complete active space wave function in the presence of a Jastrow correlation function is required to obtain agreement with the experimental dissociation energy. Furthermore, it is shown that orbital optimization leads to a 5 Δ ground state, in agreement with experiments but in disagreement with other high-level ab initio wave function calculations which all predict a 5 Σ + ground state. The role of the Jastrow factor in DMC calculations with pseudopotentials is investigated. The results suggest that a large Jastrow factor may improve the DMC accuracy substantially at small additional cost.

Mental resilience, perceived immune functioning, and health.

PubMed

Van Schrojenstein Lantman, Marith; Mackus, Marlou; Otten, Leila S; de Kruijff, Deborah; van de Loo, Aurora Jae; Kraneveld, Aletta D; Garssen, Johan; Verster, Joris C

2017-01-01

Mental resilience can be seen as a trait that enables an individual to recover from stress and to face the next stressor with optimism. People with resilient traits are considered to have a better mental and physical health. However, there are limited data available assessing the relationship between resilient individuals and their perspective of their health and immune status. Therefore, this study was conducted to examine the relationship between mental resilience, perceived health, and perceived immune status. A total of 779 participants recruited at Utrecht University completed a questionnaire consisting of demographic characteristics, the brief resilience scale for the assessment of mental resilience, the immune function questionnaire (IFQ), and questions regarding their perceived health and immune status. When correcting for gender, age, height, weight, smoker status, amount of cigarettes smoked per week, alcohol consumption status, amount of drinks consumed per week, drug use, and frequency of past year drug use, mental resilience was significantly correlated with perceived health ( r =0.233, p =0.0001), perceived immune functioning ( r =0.124, p =0.002), and IFQ score ( r =-0.185, p =0.0001). A significant, albeit modest, relationship was found between mental resilience and perceived immune functioning and health.

Generation of optimal artificial neural networks using a pattern search algorithm: application to approximation of chemical systems.

PubMed

Ihme, Matthias; Marsden, Alison L; Pitsch, Heinz

2008-02-01

A pattern search optimization method is applied to the generation of optimal artificial neural networks (ANNs). Optimization is performed using a mixed variable extension to the generalized pattern search method. This method offers the advantage that categorical variables, such as neural transfer functions and nodal connectivities, can be used as parameters in optimization. When used together with a surrogate, the resulting algorithm is highly efficient for expensive objective functions. Results demonstrate the effectiveness of this method in optimizing an ANN for the number of neurons, the type of transfer function, and the connectivity among neurons. The optimization method is applied to a chemistry approximation of practical relevance. In this application, temperature and a chemical source term are approximated as functions of two independent parameters using optimal ANNs. Comparison of the performance of optimal ANNs with conventional tabulation methods demonstrates equivalent accuracy by considerable savings in memory storage. The architecture of the optimal ANN for the approximation of the chemical source term consists of a fully connected feedforward network having four nonlinear hidden layers and 117 synaptic weights. An equivalent representation of the chemical source term using tabulation techniques would require a 500 x 500 grid point discretization of the parameter space.

The Sizing and Optimization Language (SOL): A computer language to improve the user/optimizer interface

NASA Technical Reports Server (NTRS)

Lucas, S. H.; Scotti, S. J.

1989-01-01

The nonlinear mathematical programming method (formal optimization) has had many applications in engineering design. A figure illustrates the use of optimization techniques in the design process. The design process begins with the design problem, such as the classic example of the two-bar truss designed for minimum weight as seen in the leftmost part of the figure. If formal optimization is to be applied, the design problem must be recast in the form of an optimization problem consisting of an objective function, design variables, and constraint function relations. The middle part of the figure shows the two-bar truss design posed as an optimization problem. The total truss weight is the objective function, the tube diameter and truss height are design variables, with stress and Euler buckling considered as constraint function relations. Lastly, the designer develops or obtains analysis software containing a mathematical model of the object being optimized, and then interfaces the analysis routine with existing optimization software such as CONMIN, ADS, or NPSOL. This final state of software development can be both tedious and error-prone. The Sizing and Optimization Language (SOL), a special-purpose computer language whose goal is to make the software implementation phase of optimum design easier and less error-prone, is presented.

LDRD Final Report: Global Optimization for Engineering Science Problems

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

HART,WILLIAM E.

1999-12-01

For a wide variety of scientific and engineering problems the desired solution corresponds to an optimal set of objective function parameters, where the objective function measures a solution's quality. The main goal of the LDRD ''Global Optimization for Engineering Science Problems'' was the development of new robust and efficient optimization algorithms that can be used to find globally optimal solutions to complex optimization problems. This SAND report summarizes the technical accomplishments of this LDRD, discusses lessons learned and describes open research issues.

Microfluidic platform for optimization of crystallization conditions

NASA Astrophysics Data System (ADS)

Zhang, Shuheng; Gerard, Charline J. J.; Ikni, Aziza; Ferry, Gilles; Vuillard, Laurent M.; Boutin, Jean A.; Ferte, Nathalie; Grossier, Romain; Candoni, Nadine; Veesler, Stéphane

2017-08-01

We describe a universal, high-throughput droplet-based microfluidic platform for crystallization. It is suitable for a multitude of applications, due to its flexibility, ease of use, compatibility with all solvents and low cost. The platform offers four modular functions: droplet formation, on-line characterization, incubation and observation. We use it to generate droplet arrays with a concentration gradient in continuous long tubing, without using surfactant. We control droplet properties (size, frequency and spacing) in long tubing by using hydrodynamic empirical relations. We measure droplet chemical composition using both an off-line and a real-time on-line method. Applying this platform to a complicated chemical environment, membrane proteins, we successfully handle crystallization, suggesting that the platform is likely to perform well in other circumstances. We validate the platform for fine-gradient screening and optimization of crystallization conditions. Additional on-line detection methods may well be integrated into this platform in the future, for instance, an on-line diffraction technique. We believe this method could find applications in fields such as fluid interaction engineering, live cell study and enzyme kinetics.

Cure Cycle Design Methodology for Fabricating Reactive Resin Matrix Fiber Reinforced Composites: A Protocol for Producing Void-free Quality Laminates

NASA Technical Reports Server (NTRS)

Hou, Tan-Hung

2014-01-01

For the fabrication of resin matrix fiber reinforced composite laminates, a workable cure cycle (i.e., temperature and pressure profiles as a function of processing time) is needed and is critical for achieving void-free laminate consolidation. Design of such a cure cycle is not trivial, especially when dealing with reactive matrix resins. An empirical "trial and error" approach has been used as common practice in the composite industry. Such an approach is not only costly, but also ineffective at establishing the optimal processing conditions for a specific resin/fiber composite system. In this report, a rational "processing science" based approach is established, and a universal cure cycle design protocol is proposed. Following this protocol, a workable and optimal cure cycle can be readily and rationally designed for most reactive resin systems in a cost effective way. This design protocol has been validated through experimental studies of several reactive polyimide composites for a wide spectrum of usage that has been documented in the previous publications.

On the utilization of engineering knowledge in design optimization

NASA Technical Reports Server (NTRS)

Papalambros, P.

1984-01-01

Some current research work conducted at the University of Michigan is described to illustrate efforts for incorporating knowledge in optimization in a nontraditional way. The incorporation of available knowledge in a logic structure is examined in two circumstances. The first examines the possibility of introducing global design information in a local active set strategy implemented during the iterations of projection-type algorithms for nonlinearly constrained problems. The technique used algorithms for nonlinearly constrained problems. The technique used combines global and local monotinicity analysis of the objective and constraint functions. The second examines a knowledge-based program which aids the user to create condigurations that are most desirable from the manufacturing assembly viewpoint. The data bank used is the classification scheme suggested by Boothroyd. The important aspect of this program is that it is an aid for synthesis intended for use in the design concept phase in a way similar to the so-called idea-triggers in creativity-enhancement techniques like brain-storming. The idea generation, however, is not random but it is driven by the goal of achieving the best acceptable configuration.

Could Revision of the Embryology Influence Our Cesarean Delivery Technique: Towards an Optimized Cesarean Delivery for Universal Use

PubMed Central

Stark, Michael; Mynbaev, Ospan; Vassilevski, Yuri; Rozenberg, Patrick

2016-01-01

Until today, there is no standardized Cesarean Section method and many variations exist. The main variations concern the type of abdominal incision, usage of abdominal packs, suturing the uterus in one or two layers, and suturing the peritoneal layers or leaving them open. One of the questions is the optimal location of opening the uterus. Recently, omission of the bladder flap was recommended. The anatomy and histology as results from the embryological knowledge might help to solve this question. The working thesis is that the higher the incision is done, the more damage to muscle tissue can take place contrary to incision in the lower segment, where fibrous tissue prevails. In this perspective, a call for participation in a two-armed prospective study is included, which could result in an optimal, evidence-based Cesarean Section for universal use. PMID:28078171

The dimensioning and development of hospital electric installations to guarantee the continuity of use of the therapeutic and diagnostic system.

PubMed

Stroili, M; Pavan, E C; Gorela, M; Kenda, F

2015-08-01

The Technical Services and the Medical Administration of the Hospitals of Trieste have been working for years to ensure the optimal functioning of the Medicine, Surgery, Diagnostics and Research services offered to the Patients and to the University in an 800-bed hospital complex, transforming and innovating the buildings and support installations. We have dedicated special attention to the technologies necessary to guarantee the continuity of the power supply to the electromedical devices, increasingly numerous in highly specialized hospitals. We report our electricity consumption and the power of the generator sets and the UPS and our opinion that their power must be related to the overall consumption of the Hospital, with a reserve margin.

The pharmacist and the EHR.

PubMed

Nelson, Scott D; Poikonen, John; Reese, Thomas; El Halta, David; Weir, Charlene

2017-01-01

The adoption of electronic health records (EHRs) across the United States has impacted the methods by which health care professionals care for their patients. It is not always recognized, however, that pharmacists also actively use advanced functionality within the EHR. As critical members of the health care team, pharmacists utilize many different features of the EHR. The literature focuses on 3 main roles: documentation, medication reconciliation, and patient evaluation and monitoring. As health information technology proliferates, it is imperative that pharmacists' workflow and information needs are met within the EHR to optimize medication therapy quality, team communication, and patient outcomes. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Research of flaw image collecting and processing technology based on multi-baseline stereo imaging

NASA Astrophysics Data System (ADS)

Yao, Yong; Zhao, Jiguang; Pang, Xiaoyan

2008-03-01

Aiming at the practical situations such as accurate optimal design, complex algorithms and precise technical demands of gun bore flaw image collecting, the design frame of a 3-D image collecting and processing system based on multi-baseline stereo imaging was presented in this paper. This system mainly including computer, electrical control box, stepping motor and CCD camera and it can realize function of image collection, stereo matching, 3-D information reconstruction and after-treatments etc. Proved by theoretical analysis and experiment results, images collected by this system were precise and it can slake efficiently the uncertainty problem produced by universally veins or repeated veins. In the same time, this system has faster measure speed and upper measure precision.

The design of mobile robot control system for the aged and the disabled

NASA Astrophysics Data System (ADS)

Qiang, Wang; Lei, Shi; Xiang, Gao; Jin, Zhang

2017-01-01

This paper designs a control system of mobile robot for the aged and the disabled, which consists of two main parts: human-computer interaction and drive control module. The data of the two parts is transferred via universal asynchronous receiver/transmitter. In the former part, the speed and direction information of the mobile robot is obtained by hall joystick. In the latter part, the electronic differential algorithm is developed to implement the robot mobile function by driving two-wheel motors. In order to improve the comfort of the robot when speed or direction is changed, the least squares algorithm is used to optimize the speed characteristic curves of the two motors. Experimental results have verified the effectiveness of the designed system.

Data collection system for a wide range of gas-discharge proportional neutron counters

NASA Astrophysics Data System (ADS)

Oskomov, V.; Sedov, A.; Saduyev, N.; Kalikulov, O.; Kenzhina, I.; Tautaev, E.; Mukhamejanov, Y.; Dyachkov, V.; Utey, Sh

2017-12-01

This article describes the development and creation of a universal system of data collection to measure the intensity of pulsed signals. As a result of careful analysis of time conditions and operating conditions of software and hardware complex circuit solutions were selected that meet the required specifications: frequency response is optimized in order to obtain the maximum ratio signal/noise; methods and modes of operation of the microcontroller were worked out to implement the objectives of continuous measurement of signal amplitude at the output of amplifier and send the data to a computer; function of control of high voltage source was implemented. The preliminary program has been developed for microcontroller in its simplest form, which works on a particular algorithm.

Control of functional differential equations with function space boundary conditions

NASA Technical Reports Server (NTRS)

Banks, H. T.

1972-01-01

Problems involving functional differential equations with terminal conditions in function space are considered. Their application to mechanical and electrical systems is discussed. Investigations of controllability, existence of optimal controls, and necessary and sufficient conditions for optimality are reported.

Analytical and numerical analysis of inverse optimization problems: conditions of uniqueness and computational methods

PubMed Central

Zatsiorsky, Vladimir M.

2011-01-01

One of the key problems of motor control is the redundancy problem, in particular how the central nervous system (CNS) chooses an action out of infinitely many possible. A promising way to address this question is to assume that the choice is made based on optimization of a certain cost function. A number of cost functions have been proposed in the literature to explain performance in different motor tasks: from force sharing in grasping to path planning in walking. However, the problem of uniqueness of the cost function(s) was not addressed until recently. In this article, we analyze two methods of finding additive cost functions in inverse optimization problems with linear constraints, so-called linear-additive inverse optimization problems. These methods are based on the Uniqueness Theorem for inverse optimization problems that we proved recently (Terekhov et al., J Math Biol 61(3):423–453, 2010). Using synthetic data, we show that both methods allow for determining the cost function. We analyze the influence of noise on the both methods. Finally, we show how a violation of the conditions of the Uniqueness Theorem may lead to incorrect solutions of the inverse optimization problem. PMID:21311907

Optimal Cotton Insecticide Application Termination Timing: A Meta-Analysis.

PubMed

Griffin, T W; Zapata, S D

2016-08-01

The concept of insecticide termination timing is generally accepted among cotton (Gossypium hirsutum) researchers; however, exact timings are often disputed. Specifically, there is uncertainty regarding the last economic insecticide application to control fruit-feeding pests including tarnished plant bug (Lygus lineolaris (Palisot de Beauvois)), boll weevil (Anthonomus grandis), bollworm (Helicoverpa zea), tobacco budworm (Heliothis virescens), and cotton fleahopper (Pseudatomoscelis seriatus). A systematic review of prior studies was conducted within a meta-analytic framework. Nine publicly available articles were amalgamated to develop an optimal timing principle. These prior studies reported 53 independent multiple means comparison field experiments for a total of 247 trial observations. Stochastic plateau theory integrated with econometric meta-analysis methodology was applied to the meta-database to determine the shape of the functional form of both the agronomic optimal insecticide termination timing and corresponding yield potential. Results indicated that current university insecticide termination timing recommendations are later than overall estimated timing suggested. The estimated 159 heat units (HU) after the fifth position above white flower (NAWF5) was found to be statistically different than the 194 HU termination used as the status quo recommended termination timing. Insecticides applied after 159 HU may have been applied in excess, resulting in unnecessary economic and environmental costs. Empirical results also suggested that extending the insecticide termination time by one unit resulted in a cotton lint yield increase of 0.27 kilograms per hectare up to the timing where the plateau began. Based on economic analyses, profit-maximizing producers may cease application as soon as 124 HU after NAWF5. These results provided insights useful to improve production systems by applying inputs only when benefits were expected to be in excess of the respective costs. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

78 FR 48845 - Hydrofluorosilicic Acid in Drinking Water; TSCA Section 21 Petition; Reasons for Agency Response

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-12

... the corrosivity of the water including: Taking further steps to optimize their corrosion control treatment (for water systems serving 50,000 people that have not fully optimized their corrosion control... Control Act (TSCA). The TSCA section 21 petition, dated May 9, 2013, was submitted by American University...

Majorization as a Tool for Optimizing a Class of Matrix Functions.

ERIC Educational Resources Information Center

Kiers, Henk A.

1990-01-01

General algorithms are presented that can be used for optimizing matrix trace functions subject to certain constraints on the parameters. The parameter set that minimizes the majorizing function also decreases the matrix trace function, providing a monotonically convergent algorithm for minimizing the matrix trace function iteratively. (SLD)

Medical Applications of IR Focal Plane Arrays

DTIC Science & Technology

1998-03-15

University of Memphis, USA, E. Wolf, H. Bada C Leffler - University of Tennessee at Memphis, USA, M. Daley ■ University of Memphis, USA A two channel ...optical aperture versus thermal sensitivity at two different resolution settings for an optimized medical IR camera LIST OF TABLES TABLE 1 Advantages...34. Technology Transferred: Through this work, infrared imaging in medicine was exposed to ever-growing audiences. For the first time, the work of the last two

A modified multi-objective particle swarm optimization approach and its application to the design of a deepwater composite riser

NASA Astrophysics Data System (ADS)

Zheng, Y.; Chen, J.

2017-09-01

A modified multi-objective particle swarm optimization method is proposed for obtaining Pareto-optimal solutions effectively. Different from traditional multi-objective particle swarm optimization methods, Kriging meta-models and the trapezoid index are introduced and integrated with the traditional one. Kriging meta-models are built to match expensive or black-box functions. By applying Kriging meta-models, function evaluation numbers are decreased and the boundary Pareto-optimal solutions are identified rapidly. For bi-objective optimization problems, the trapezoid index is calculated as the sum of the trapezoid's area formed by the Pareto-optimal solutions and one objective axis. It can serve as a measure whether the Pareto-optimal solutions converge to the Pareto front. Illustrative examples indicate that to obtain Pareto-optimal solutions, the method proposed needs fewer function evaluations than the traditional multi-objective particle swarm optimization method and the non-dominated sorting genetic algorithm II method, and both the accuracy and the computational efficiency are improved. The proposed method is also applied to the design of a deepwater composite riser example in which the structural performances are calculated by numerical analysis. The design aim was to enhance the tension strength and minimize the cost. Under the buckling constraint, the optimal trade-off of tensile strength and material volume is obtained. The results demonstrated that the proposed method can effectively deal with multi-objective optimizations with black-box functions.

Conformational Space Annealing explained: A general optimization algorithm, with diverse applications

NASA Astrophysics Data System (ADS)

Joung, InSuk; Kim, Jong Yun; Gross, Steven P.; Joo, Keehyoung; Lee, Jooyoung

2018-02-01

Many problems in science and engineering can be formulated as optimization problems. One way to solve these problems is to develop tailored problem-specific approaches. As such development is challenging, an alternative is to develop good generally-applicable algorithms. Such algorithms are easy to apply, typically function robustly, and reduce development time. Here we provide a description for one such algorithm called Conformational Space Annealing (CSA) along with its python version, PyCSA. We previously applied it to many optimization problems including protein structure prediction and graph community detection. To demonstrate its utility, we have applied PyCSA to two continuous test functions, namely Ackley and Eggholder functions. In addition, in order to provide complete generality of PyCSA to any types of an objective function, we demonstrate the way PyCSA can be applied to a discrete objective function, namely a parameter optimization problem. Based on the benchmarking results of the three problems, the performance of CSA is shown to be better than or similar to the most popular optimization method, simulated annealing. For continuous objective functions, we found that, L-BFGS-B was the best performing local optimization method, while for a discrete objective function Nelder-Mead was the best. The current version of PyCSA can be run in parallel at the coarse grained level by calculating multiple independent local optimizations separately. The source code of PyCSA is available from http://lee.kias.re.kr.

Geometry Genetics and Evolution

NASA Astrophysics Data System (ADS)

Siggia, Eric

2011-03-01

Darwin argued that highly perfected organs such as the vertebrate eye could evolve by a series of small changes, each of which conferred a selective advantage. In the context of gene networks, this idea can be recast into a predictive algorithm, namely find networks that can be built by incremental adaptation (gradient search) to perform some task. It embodies a ``kinetic'' view of evolution where a solution that is quick to evolve is preferred over a global optimum. Examples of biochemical kinetic networks were evolved for temporal adaptation, temperature compensated entrainable clocks, explore-exploit trade off in signal discrimination, will be presented as well as networks that model the spatially periodic somites (vertebrae) and HOX gene expression in the vertebrate embryo. These models appear complex by the criterion of 19th century applied mathematics since there is no separation of time or spatial scales, yet they are all derivable by gradient optimization of simple functions (several in the Pareto evolution) often based on the Shannon entropy of the time or spatial response. Joint work with P. Francois, Physics Dept. McGill University. With P. Francois, Physics Dept. McGill University

Realizing a partial general quantum cloning machine with superconducting quantum-interference devices in a cavity QED

NASA Astrophysics Data System (ADS)

Fang, Bao-Long; Yang, Zhen; Ye, Liu

2009-05-01

We propose a scheme for implementing a partial general quantum cloning machine with superconducting quantum-interference devices coupled to a nonresonant cavity. By regulating the time parameters, our system can perform optimal symmetric (asymmetric) universal quantum cloning, optimal symmetric (asymmetric) phase-covariant cloning, and optimal symmetric economical phase-covariant cloning. In the scheme the cavity is only virtually excited, thus, the cavity decay is suppressed during the cloning operations.

Overtaking method based on sand-sifter mechanism: Why do optimistic value functions find optimal solutions in multi-armed bandit problems?

PubMed

Ochi, Kento; Kamiura, Moto

2015-09-01

A multi-armed bandit problem is a search problem on which a learning agent must select the optimal arm among multiple slot machines generating random rewards. UCB algorithm is one of the most popular methods to solve multi-armed bandit problems. It achieves logarithmic regret performance by coordinating balance between exploration and exploitation. Since UCB algorithms, researchers have empirically known that optimistic value functions exhibit good performance in multi-armed bandit problems. The terms optimistic or optimism might suggest that the value function is sufficiently larger than the sample mean of rewards. The first definition of UCB algorithm is focused on the optimization of regret, and it is not directly based on the optimism of a value function. We need to think the reason why the optimism derives good performance in multi-armed bandit problems. In the present article, we propose a new method, which is called Overtaking method, to solve multi-armed bandit problems. The value function of the proposed method is defined as an upper bound of a confidence interval with respect to an estimator of expected value of reward: the value function asymptotically approaches to the expected value of reward from the upper bound. If the value function is larger than the expected value under the asymptote, then the learning agent is almost sure to be able to obtain the optimal arm. This structure is called sand-sifter mechanism, which has no regrowth of value function of suboptimal arms. It means that the learning agent can play only the current best arm in each time step. Consequently the proposed method achieves high accuracy rate and low regret and some value functions of it can outperform UCB algorithms. This study suggests the advantage of optimism of agents in uncertain environment by one of the simplest frameworks. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Beller Lectureship Talk: Active response of biological cells to mechanical stress

NASA Astrophysics Data System (ADS)

Safran, Samuel

2009-03-01

Forces exerted by and on adherent cells are important for many physiological processes such as wound healing and tissue formation. In addition, recent experiments have shown that stem cell differentiation is controlled, at least in part, by the elasticity of the surrounding matrix. We present a simple and generic theoretical model for the active response of biological cells to mechanical stress. The theory includes cell activity and mechanical forces as well as random forces as factors that determine the polarizability that relates cell orientation to stress. This allows us to explain the puzzling observation of parallel (or sometimes random) alignment of cells for static and quasi-static stresses and of nearly perpendicular alignment for dynamically varying stresses. In addition, we predict the response of the cellular orientation to a sinusoidally varying applied stress as a function of frequency and compare the theory with recent experiments. The dependence of the cell orientation angle on the Poisson ratio of the surrounding material distinguishes cells whose activity is controlled by stress from those controlled by strain. We have extended the theory to generalize the treatment of elastic inclusions in solids to ''living'' inclusions (cells) whose active polarizability, analogous to the polarizability of non-living matter, results in the feedback of cellular forces that develop in response to matrix stresses. We use this to explain recent observations of the non-monotonic dependence of stress-fiber polarization in stem cells on matrix rigidity. These findings provide a mechanical correlate for the existence of an optimal substrate elasticity for cell differentiation and function. [3pt] *In collaboration with R. De (Brown University), Y. Biton (Weizmann Institute), and A. Zemel (Hebrew University) and the experimental groups: Max Planck Institute, Stuttgart: S. Jungbauer, R. Kemkemer, J. Spatz; University of Pennsylvania: A. Brown, D. Discher, F. Rehfeldt.

HPA axis hyperactivity as suicide predictor in elderly mood disorder inpatients.

PubMed

Jokinen, Jussi; Nordström, Peter

2008-11-01

Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis function is associated with suicidal behaviour and age-associated alterations in HPA axis functioning may render elderly individuals more susceptible to HPA dysregulation related to mood disorders. Research on HPA axis function in suicide prediction in elderly mood disorder patients is sparse. The study sample consisted of 99 depressed elderly inpatients 65 years of age or older admitted to the department of Psychiatry at the Karolinska University Hospital between 1980 and 2000. The hypothesis was that elderly mood disorder inpatients who fail to suppress cortisol in the dexamethasone suppression test (DST) are at higher risk of suicide. The DST non-suppression distinguished between suicides and survivors in elderly depressed inpatients and the suicide attempt at the index episode was a strong predictor for suicide. Additionally, the DST non-suppression showed higher specificity and predictive value in the suicide attempter group. Due to age-associated alterations in HPA axis functioning, the optimal cut-off for DST non-suppression in suicide prediction may be higher in elderly mood disorder inpatients. These data demonstrate the importance of attempted suicide and DST non-suppression as predictors of suicide risk in late-life depression and suggest the use for neuroendocrine testing of HPA axis functioning as a complementary tool in suicide prevention.

A probabilistic multi-criteria decision making technique for conceptual and preliminary aerospace systems design

NASA Astrophysics Data System (ADS)

Bandte, Oliver

It has always been the intention of systems engineering to invent or produce the best product possible. Many design techniques have been introduced over the course of decades that try to fulfill this intention. Unfortunately, no technique has succeeded in combining multi-criteria decision making with probabilistic design. The design technique developed in this thesis, the Joint Probabilistic Decision Making (JPDM) technique, successfully overcomes this deficiency by generating a multivariate probability distribution that serves in conjunction with a criterion value range of interest as a universally applicable objective function for multi-criteria optimization and product selection. This new objective function constitutes a meaningful Xnetric, called Probability of Success (POS), that allows the customer or designer to make a decision based on the chance of satisfying the customer's goals. In order to incorporate a joint probabilistic formulation into the systems design process, two algorithms are created that allow for an easy implementation into a numerical design framework: the (multivariate) Empirical Distribution Function and the Joint Probability Model. The Empirical Distribution Function estimates the probability that an event occurred by counting how many times it occurred in a given sample. The Joint Probability Model on the other hand is an analytical parametric model for the multivariate joint probability. It is comprised of the product of the univariate criterion distributions, generated by the traditional probabilistic design process, multiplied with a correlation function that is based on available correlation information between pairs of random variables. JPDM is an excellent tool for multi-objective optimization and product selection, because of its ability to transform disparate objectives into a single figure of merit, the likelihood of successfully meeting all goals or POS. The advantage of JPDM over other multi-criteria decision making techniques is that POS constitutes a single optimizable function or metric that enables a comparison of all alternative solutions on an equal basis. Hence, POS allows for the use of any standard single-objective optimization technique available and simplifies a complex multi-criteria selection problem into a simple ordering problem, where the solution with the highest POS is best. By distinguishing between controllable and uncontrollable variables in the design process, JPDM can account for the uncertain values of the uncontrollable variables that are inherent to the design problem, while facilitating an easy adjustment of the controllable ones to achieve the highest possible POS. Finally, JPDM's superiority over current multi-criteria decision making techniques is demonstrated with an optimization of a supersonic transport concept and ten contrived equations as well as a product selection example, determining an airline's best choice among Boeing's B-747, B-777, Airbus' A340, and a Supersonic Transport. The optimization examples demonstrate JPDM's ability to produce a better solution with a higher POS than an Overall Evaluation Criterion or Goal Programming approach. Similarly, the product selection example demonstrates JPDM's ability to produce a better solution with a higher POS and different ranking than the Overall Evaluation Criterion or Technique for Order Preferences by Similarity to the Ideal Solution (TOPSIS) approach.

Adaptive Constrained Optimal Control Design for Data-Based Nonlinear Discrete-Time Systems With Critic-Only Structure.

PubMed

Luo, Biao; Liu, Derong; Wu, Huai-Ning

2018-06-01

Reinforcement learning has proved to be a powerful tool to solve optimal control problems over the past few years. However, the data-based constrained optimal control problem of nonaffine nonlinear discrete-time systems has rarely been studied yet. To solve this problem, an adaptive optimal control approach is developed by using the value iteration-based Q-learning (VIQL) with the critic-only structure. Most of the existing constrained control methods require the use of a certain performance index and only suit for linear or affine nonlinear systems, which is unreasonable in practice. To overcome this problem, the system transformation is first introduced with the general performance index. Then, the constrained optimal control problem is converted to an unconstrained optimal control problem. By introducing the action-state value function, i.e., Q-function, the VIQL algorithm is proposed to learn the optimal Q-function of the data-based unconstrained optimal control problem. The convergence results of the VIQL algorithm are established with an easy-to-realize initial condition . To implement the VIQL algorithm, the critic-only structure is developed, where only one neural network is required to approximate the Q-function. The converged Q-function obtained from the critic-only VIQL method is employed to design the adaptive constrained optimal controller based on the gradient descent scheme. Finally, the effectiveness of the developed adaptive control method is tested on three examples with computer simulation.

Minority-Serving Institutions and Disability, Health, Independent Living, and Rehabilitation Research Participation Challenges: A Review of the Literature and Policy

ERIC Educational Resources Information Center

Manyibe, Edward O.; Moore, Corey L.; Aref, Fariborz; Sagini, Meshack M.; Zeng, Steve; Alston, Reginald J.

2017-01-01

Purpose: This article provided a comprehensive overview of select challenges that oftentimes prevent minority-serving institutions (MSIs) in the United States (i.e., historically Black colleges/universities, Hispanic-serving institutions, and American Indian tribal colleges/universities) from participating optimally in the federal research…

University-Affiliated Schools as Sites for Research Learning in Pre-Service Teacher Education

ERIC Educational Resources Information Center

Henning, Elizabeth; Petker, Gadija; Petersen, Nadine

2015-01-01

This article proposes that the "teaching/practice schools" formally affiliated to initial teacher education programmes at universities, can be utilised more optimally as research sites by student teachers. The argument is put forward with reference to the role that such schools have played historically in teacher education in the United…

Europe's Austerity Measures Take Their Toll on Academe

ERIC Educational Resources Information Center

Labi, Aisha

2012-01-01

When the global financial crisis hit in 2008, it looked at first as if many European universities were going to escape the worst. Higher education has long been considered a public right and a taxpayer-financed obligation, and there was optimism that universities, which government leaders hail as drivers of economic growth, would emerge relatively…

An Optimization Model for the Allocation of University Based Merit Aid

ERIC Educational Resources Information Center

Sugrue, Paul K.

2010-01-01

The allocation of merit-based financial aid during the college admissions process presents postsecondary institutions with complex and financially expensive decisions. This article describes the application of linear programming as a decision tool in merit based financial aid decisions at a medium size private university. The objective defined for…

Postgraduate Supervision at an Open Distance E-Learning Institution in South Africa

ERIC Educational Resources Information Center

Manyike, Tintswalo Vivian

2017-01-01

Effective postgraduate supervision is a concern at universities worldwide, even under optimal conditions where postgraduate students are studying full-time. Universities are being pressured by their governments to increase the throughput of postgraduates where there is a need for supervisory guidance in order to produce quality graduates within a…

Tutorials in the Polytechnic University of the Philippines (PUP) Open University System

ERIC Educational Resources Information Center

Castolo, Carmencita L.

2016-01-01

Tutorial is one of the student support services often provided by open and distance teaching institutions. These are regularly scheduled meetings between a tutor and his/here students which may include individual consultation sessions, either face-to-face or through telephone; a more formal "lecture format;" optimal participation in…

Life in the Universe

ERIC Educational Resources Information Center

Lowman, Paul D., Jr.

2003-01-01

The belief that life exists in the universe is an optimism shared by many. With several manned missions expected to be carried out in the future, the possibility of discovering life in outer space will revolutionize the field of astrobiology. In this article, the author presents a summary of recent developments and discoveries made in the search…

The importance of functional form in optimal control solutions of problems in population dynamics

USGS Publications Warehouse

Runge, M.C.; Johnson, F.A.

2002-01-01

Optimal control theory is finding increased application in both theoretical and applied ecology, and it is a central element of adaptive resource management. One of the steps in an adaptive management process is to develop alternative models of system dynamics, models that are all reasonable in light of available data, but that differ substantially in their implications for optimal control of the resource. We explored how the form of the recruitment and survival functions in a general population model for ducks affected the patterns in the optimal harvest strategy, using a combination of analytical, numerical, and simulation techniques. We compared three relationships between recruitment and population density (linear, exponential, and hyperbolic) and three relationships between survival during the nonharvest season and population density (constant, logistic, and one related to the compensatory harvest mortality hypothesis). We found that the form of the component functions had a dramatic influence on the optimal harvest strategy and the ultimate equilibrium state of the system. For instance, while it is commonly assumed that a compensatory hypothesis leads to higher optimal harvest rates than an additive hypothesis, we found this to depend on the form of the recruitment function, in part because of differences in the optimal steady-state population density. This work has strong direct consequences for those developing alternative models to describe harvested systems, but it is relevant to a larger class of problems applying optimal control at the population level. Often, different functional forms will not be statistically distinguishable in the range of the data. Nevertheless, differences between the functions outside the range of the data can have an important impact on the optimal harvest strategy. Thus, development of alternative models by identifying a single functional form, then choosing different parameter combinations from extremes on the likelihood profile may end up producing alternatives that do not differ as importantly as if different functional forms had been used. We recommend that biological knowledge be used to bracket a range of possible functional forms, and robustness of conclusions be checked over this range.

Application of the gravity search algorithm to multi-reservoir operation optimization

NASA Astrophysics Data System (ADS)

Bozorg-Haddad, Omid; Janbaz, Mahdieh; Loáiciga, Hugo A.

2016-12-01

Complexities in river discharge, variable rainfall regime, and drought severity merit the use of advanced optimization tools in multi-reservoir operation. The gravity search algorithm (GSA) is an evolutionary optimization algorithm based on the law of gravity and mass interactions. This paper explores the GSA's efficacy for solving benchmark functions, single reservoir, and four-reservoir operation optimization problems. The GSA's solutions are compared with those of the well-known genetic algorithm (GA) in three optimization problems. The results show that the GSA's results are closer to the optimal solutions than the GA's results in minimizing the benchmark functions. The average values of the objective function equal 1.218 and 1.746 with the GSA and GA, respectively, in solving the single-reservoir hydropower operation problem. The global solution equals 1.213 for this same problem. The GSA converged to 99.97% of the global solution in its average-performing history, while the GA converged to 97% of the global solution of the four-reservoir problem. Requiring fewer parameters for algorithmic implementation and reaching the optimal solution in fewer number of functional evaluations are additional advantages of the GSA over the GA. The results of the three optimization problems demonstrate a superior performance of the GSA for optimizing general mathematical problems and the operation of reservoir systems.

Facing the Corporate University: The New Wave of Student Movements in Europe

ERIC Educational Resources Information Center

Fernández, Joseba

2014-01-01

The transformation of the historical functions and goals of the European university is producing the transition from mass university to what has been called "corporate university". With this goal, I will examine how the new functions of the university are aimed at providing services and precarious workers to the labor structure of…

Exploring optimal topology of thermal cloaks by CMA-ES

NASA Astrophysics Data System (ADS)

Fujii, Garuda; Akimoto, Youhei; Takahashi, Masayuki

2018-02-01

This paper presents topology optimization for thermal cloaks expressed by level-set functions and explored using the covariance matrix adaptation evolution strategy (CMA-ES). Designed optimal configurations provide superior performances in thermal cloaks for the steady-state thermal conduction and succeed in realizing thermal invisibility, despite the structures being simply composed of iron and aluminum and without inhomogeneities caused by employing metamaterials. To design thermal cloaks, a prescribed objective function is used to evaluate the difference between the temperature field controlled by a thermal cloak and when no thermal insulator is present. The CMA-ES involves searches for optimal sets of level-set functions as design variables that minimize a regularized fitness involving a perimeter constraint. Through topology optimization subject to structural symmetries about four axes, we obtain a concept design of a thermal cloak that functions in an isotropic heat flux.

New beginnings: evidence that the meditational regimen can lead to optimization of perception, attention, cognition, and other functions.

PubMed

Bushell, William C

2009-08-01

A "framework" is presented for understanding empirically confirmed and unconfirmed phenomena in the Indo-Tibetan meditation system, from an integrative perspective, and providing evidence that certain meditative practices enable meditators to realize the innate human potential to perceive light "at the limits imposed by quantum mechanics," on the level of individual photons. This is part of a larger Buddhist agenda to meditatitively develop perceptual/attentional capacities to achieve penetrating insight into the nature of phenomena. Such capacities may also allow advanced meditators to perceive changes in natural scenes that are "hidden" from persons with "normal" attentional capacities, according to research on "change blindness," and to enhance their visual system functioning akin to high-speed and time-lapse photography, in toto allowing for the perception, as well as sophisticated understanding, of the "moment to moment change or impermanence" universally characteristic of the phenomenal world but normally outside untrained attention and perception according to Buddhist doctrine.

Gait Rather Than Cognition Predicts Decline in Specific Cognitive Domains in Early Parkinson's Disease.

PubMed

Morris, Rosie; Lord, Sue; Lawson, Rachael A; Coleman, Shirley; Galna, Brook; Duncan, Gordon W; Khoo, Tien K; Yarnall, Alison J; Burn, David J; Rochester, Lynn

2017-11-09

Dementia is significant in Parkinson's disease (PD) with personal and socioeconomic impact. Early identification of risk is of upmost importance to optimize management. Gait precedes and predicts cognitive decline and dementia in older adults. We aimed to evaluate gait characteristics as predictors of cognitive decline in newly diagnosed PD. One hundred and nineteen participants recruited at diagnosis were assessed at baseline, 18 and 36 months. Baseline gait was characterized by variables that mapped to five domains: pace, rhythm, variability, asymmetry, and postural control. Cognitive assessment included attention, fluctuating attention, executive function, visual memory, and visuospatial function. Mixed-effects models tested independent gait predictors of cognitive decline. Gait characteristics of pace, variability, and postural control predicted decline in fluctuating attention and visual memory, whereas baseline neuropsychological assessment performance did not predict decline. This provides novel evidence for gait as a clinical biomarker for PD cognitive decline in early disease. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America.

A deterministic global optimization using smooth diagonal auxiliary functions

NASA Astrophysics Data System (ADS)

Sergeyev, Yaroslav D.; Kvasov, Dmitri E.

2015-04-01

In many practical decision-making problems it happens that functions involved in optimization process are black-box with unknown analytical representations and hard to evaluate. In this paper, a global optimization problem is considered where both the goal function f (x) and its gradient f‧ (x) are black-box functions. It is supposed that f‧ (x) satisfies the Lipschitz condition over the search hyperinterval with an unknown Lipschitz constant K. A new deterministic 'Divide-the-Best' algorithm based on efficient diagonal partitions and smooth auxiliary functions is proposed in its basic version, its convergence conditions are studied and numerical experiments executed on eight hundred test functions are presented.

Techniques for shuttle trajectory optimization

NASA Technical Reports Server (NTRS)

Edge, E. R.; Shieh, C. J.; Powers, W. F.

1973-01-01

The application of recently developed function-space Davidon-type techniques to the shuttle ascent trajectory optimization problem is discussed along with an investigation of the recently developed PRAXIS algorithm for parameter optimization. At the outset of this analysis, the major deficiency of the function-space algorithms was their potential storage problems. Since most previous analyses of the methods were with relatively low-dimension problems, no storage problems were encountered. However, in shuttle trajectory optimization, storage is a problem, and this problem was handled efficiently. Topics discussed include: the shuttle ascent model and the development of the particular optimization equations; the function-space algorithms; the operation of the algorithm and typical simulations; variable final-time problem considerations; and a modification of Powell's algorithm.

A Rigorous Framework for Optimization of Expensive Functions by Surrogates

NASA Technical Reports Server (NTRS)

Booker, Andrew J.; Dennis, J. E., Jr.; Frank, Paul D.; Serafini, David B.; Torczon, Virginia; Trosset, Michael W.

1998-01-01

The goal of the research reported here is to develop rigorous optimization algorithms to apply to some engineering design problems for which design application of traditional optimization approaches is not practical. This paper presents and analyzes a framework for generating a sequence of approximations to the objective function and managing the use of these approximations as surrogates for optimization. The result is to obtain convergence to a minimizer of an expensive objective function subject to simple constraints. The approach is widely applicable because it does not require, or even explicitly approximate, derivatives of the objective. Numerical results are presented for a 31-variable helicopter rotor blade design example and for a standard optimization test example.

Universal scaling function in discrete time asymmetric exclusion processes

NASA Astrophysics Data System (ADS)

Chia, Nicholas; Bundschuh, Ralf

2005-03-01

In the universality class of the one dimensional Kardar-Parisi-Zhang surface growth, Derrida and Lebowitz conjectured the universality of not only the scaling exponents, but of an entire scaling function. Since Derrida and Lebowitz' original publication this universality has been verified for a variety of continuous time systems in the KPZ universality class. We study the Derrida-Lebowitz scaling function for multi-particle versions of the discrete time Asymmetric Exclusion Process. We find that in this discrete time system the Derrida-Lebowitz scaling function not only properly characterizes the large system size limit, but even accurately describes surprisingly small systems. These results have immediate applications in searching biological sequence databases.

Application of Boiler Op for combustion optimization at PEPCO

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

Maines, P.; Williams, S.; Levy, E.

1997-09-01

Title IV requires the reduction of NOx at all stations within the PEPCO system. To assist PEPCO plant personnel in achieving low heat rates while meeting NOx targets, Lehigh University`s Energy Research Center and PEPCO developed a new combustion optimization software package called Boiler Op. The Boiler Op code contains an expert system, neural networks and an optimization algorithm. The expert system guides the plant engineer through a series of parametric boiler tests, required for the development of a comprehensive boiler database. The data are then analyzed by the neural networks and optimization algorithm to provide results on the boilermore » control settings which result in the best possible heat rate at a target NOx level or produce minimum NOx. Boiler Op has been used at both Potomac River and Morgantown Stations to help PEPCO engineers optimize combustion. With the use of Boiler Op, Morgantown Station operates under low NOx restrictions and continues to achieve record heat rate values, similar to pre-retrofit conditions. Potomac River Station achieves the regulatory NOx limit through the use of Boiler Op recommended control settings and without NOx burners. Importantly, any software like Boiler Op cannot be used alone. Its application must be in concert with human intelligence to ensure unit safety, reliability and accurate data collection.« less

Seeking consensus on universal health coverage indicators in the sustainable development goals.

PubMed

Reddock, Jennifer

2017-01-01

There is optimism that the inclusion of universal health coverage in the Sustainable Development Goals advances its prominence in global and national health policy. However, formulating indicators for Target 3.8 through the Inter-Agency Expert Group on Sustainable Development Indicators has been challenging. Achieving consensus on the conceptual and methodological aspects of universal health coverage is likely to take some time in multi-stakeholder fora compared with national efforts to select indicators.

A Method to Predict the Reliability of Military Ground Vehicles Using High Performance Computing

DTIC Science & Technology

2006-11-01

Krayterman U.S. Army RDECOM-TARDEC Warren, MI 48397 K.K. Choi, Ed Hardee University of Iowa Coralville , IA 52242 Byeng D. Youn Michigan...University of Iowa , performed an optimization of the design for an A-arm on a military ground vehicle (a Stryker), using no sources of uncertainty...LSF for the queueing system. 3.3 Reliability/Fatigue Analysis software We used several pieces of propriety code from the University of Iowa

Local Approximation and Hierarchical Methods for Stochastic Optimization

NASA Astrophysics Data System (ADS)

Cheng, Bolong

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

Post optimization paradigm in maximum 3-satisfiability logic programming

NASA Astrophysics Data System (ADS)

Mansor, Mohd. Asyraf; Sathasivam, Saratha; Kasihmuddin, Mohd Shareduwan Mohd

2017-08-01

Maximum 3-Satisfiability (MAX-3SAT) is a counterpart of the Boolean satisfiability problem that can be treated as a constraint optimization problem. It deals with a conundrum of searching the maximum number of satisfied clauses in a particular 3-SAT formula. This paper presents the implementation of enhanced Hopfield network in hastening the Maximum 3-Satisfiability (MAX-3SAT) logic programming. Four post optimization techniques are investigated, including the Elliot symmetric activation function, Gaussian activation function, Wavelet activation function and Hyperbolic tangent activation function. The performances of these post optimization techniques in accelerating MAX-3SAT logic programming will be discussed in terms of the ratio of maximum satisfied clauses, Hamming distance and the computation time. Dev-C++ was used as the platform for training, testing and validating our proposed techniques. The results depict the Hyperbolic tangent activation function and Elliot symmetric activation function can be used in doing MAX-3SAT logic programming.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

2010 ESMD Faculty Fellowship Project

NASA Technical Reports Server (NTRS)

Carmen, Christina L.; Morris, Tommy; Schmidt, Peter; van Susante, Paul; Zalewski, Janusz; Murphy, Gloria

2010-01-01

This slide presentation reviews is composed of 6 individual sections. The first is a introductory section that explains the Exploration Systems Mission Directorate (ESMD) Faculty Fellowship Project, the purpose of which is to prepare selected university faculty to work with senior design students to complete projects that have potential to contribute to NASA objectives. The following university presentations represent the chosen projects: (1) the use of Exploration Toolset for the Optimization of Launch and Space Systems (X-TOOLSS) to optimize the Lunar Wormbot design; (2) development of Hardware Definition Language (HDL) realization of ITU G.729 for FGPA; (3) cryogenic fluid and electrical quick connect system and a lunar regolith design; (4) Lunar Landing Pad development; and (5) Prognostics for complex systems.

Universal optimal hole-doping concentration in single-layer high-temperature cuprate superconductors

NASA Astrophysics Data System (ADS)

Honma, T.; Hor, P. H.

2006-09-01

We argue that in cuprate physics there are two types, hole content per CuO2 plane (Ppl) and the corresponding hole content per unit volume (P3D), of hole-doping concentrations for addressing physical properties that are two dimensional (2D) and three dimensional (3D) in nature, respectively. We find that the superconducting transition temperature (Tc) varies systematically with P3D as a superconducting 'dome' with a universal optimal hole-doping concentration of P3Dopt = 1.6 × 1021 cm-3 for single-layer high-temperature superconductors. We suggest that P3Dopt determines the upper bound of the electronic energy of underdoped single-layer high-Tc cuprates.

Faithful Remote Information Concentration Based on the Optimal Universal 1→2 Telecloning of Arbitrary Two-Qubit States

NASA Astrophysics Data System (ADS)

Peng, Jia-Yin; Lei, Hong-Xuan; Mo, Zhi-Wen

2014-05-01

The previous protocols of remote quantum information concentration were focused on the reverse process of quantum telecloning of single-qubit states. We here investigate the reverse process of optimal universal 1→2 telecloning of arbitrary two-qubit states. The aim of this telecloning is to distribute respectively the quantum information to two groups of spatially separated receivers from a group of two senders situated at two different locations. Our scheme shows that the distributed quantum information can be remotely concentrated back to a group of two different receivers with 1 of probability by utilizing maximally four-particle cluster state and four-particle GHZ state as quantum channel.

On the functional optimization of a certain class of nonstationary spatial functions

USGS Publications Warehouse

Christakos, G.; Paraskevopoulos, P.N.

1987-01-01

Procedures are developed in order to obtain optimal estimates of linear functionals for a wide class of nonstationary spatial functions. These procedures rely on well-established constrained minimum-norm criteria, and are applicable to multidimensional phenomena which are characterized by the so-called hypothesis of inherentity. The latter requires elimination of the polynomial, trend-related components of the spatial function leading to stationary quantities, and also it generates some interesting mathematics within the context of modelling and optimization in several dimensions. The arguments are illustrated using various examples, and a case study computed in detail. ?? 1987 Plenum Publishing Corporation.

About the geothermal electric power plant from the University of Oradea, Romania

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

Gordan, M.I.; Maghiar, T.

1997-12-31

The purpose of this paper consists in the exposure of a short description of the geothermal electric power plant from Oradea, Romania, and of the research directions regarding the optimization of the behaviour of this plant, especially the determination of the optimal thermodynamic cycle based on the analysis of the practical results.

Relationship between Optimism, Religiosity and Self-Esteem with Marital Satisfaction and Life Satisfaction

ERIC Educational Resources Information Center

Homaei, Rezvan; Bozorgi, Zahra Dasht; Ghahfarokhi, Maryam Sadat Mirbabaei; Hosseinpour, Shima

2016-01-01

The purpose of the current study is to investigate the relationship between Optimism, Religiosity and Self-esteem with Marital Satisfaction and Life Satisfaction in married university students. The research method was a descriptive study kind of correlation. The sample group included 200 married students that were selected using a simple random…

Optimizing the Number of Students for an Effective Online Discussion Board Learning Experience

ERIC Educational Resources Information Center

Reonieri, Dean C., Sr.

2006-01-01

The purpose of this research was to determine if there is an opportunity for colleges and universities to improve the quality of knowledge constructed in online (asynchronous) discussion boards by optimizing the number of students in the discussion. 93 online graduate students and 36 online faculty were surveyed to gain the perspective from both…

Optimal design of a combustion chamber of gas turbine engine by a Combustion chamber 1D-2D computer program

NASA Astrophysics Data System (ADS)

Aleksandrov, Y. B.; Mingazov, B. G.

2017-09-01

The paper shows a method of modeling and optimization of processes in combustion chambers of gas turbine engines using a computer program developed by a team at the Department of Jet Engines and Power Plants (DJEPP) of Technical University named after A N Tupolev KNRTU-KAI.

Optimizing the Environmental Attitudes Inventory: Establishing a Baseline of Change in Students' Attitudes

ERIC Educational Resources Information Center

Sutton, Stephen G.; Gyuris, Emma

2015-01-01

Purpose: The purpose of this study was twofold: first, to optimize the Environmental Attitudes Inventory (EAI) and second, to establish a baseline of the difference in environmental attitudes between first and final year students, taken at the start of a university's declaration of commitment to EfS. Design/methodology/approach: The…

A Systematic Software, Firmware, and Hardware Codesign Methodology for Digital Signal Processing

DTIC Science & Technology

2014-03-01

possible mappings ...................................................60 Table 25. Possible optimal leaf -nodes... size weight and power UAV unmanned aerial vehicle UHF ultra-high frequency UML universal modeling language Verilog verify logic VHDL VHSIC...optimal leaf -nodes to some design patterns for embedded system design. Software and hardware partitioning is a very difficult challenge in the field of

Seeking the Optimal Time for Integrated Curriculum in Jinan University School of Medicine

ERIC Educational Resources Information Center

Pan, Sanqiang; Cheng, Xin; Zhou, Yanghai; Li, Ke; Yang, Xuesong

2017-01-01

The curricular integration of the basic sciences and clinical medicine has been conducted for over 40 years and proved to increase medical students' study interests and clinical reasoning. However, there is still no solid data suggesting what time, freshmen or year 3, is optimal to begin with the integrated curriculum. In this study, the…

Advanced Nuclear Technology. Using Technology for Small Modular Reactor Staff Optimization, Improved Effectiveness, and Cost Containment, 3002007071

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

Loflin, Leonard

Through this grant, the U.S. Department of Energy (DOE) will review several functional areas within a nuclear power plant, including fire protection, operations and operations support, refueling, training, procurement, maintenance, site engineering, and others. Several functional areas need to be examined since there appears to be no single staffing area or approach that alone has the potential for significant staff optimization at new nuclear power plants. Several of the functional areas will require a review of technology options such as automation, remote monitoring, fleet wide monitoring, new and specialized instrumentation, human factors engineering, risk informed analysis and PRAs, component andmore » system condition monitoring and reporting, just in time training, electronic and automated procedures, electronic tools for configuration management and license and design basis information, etc., that may be applied to support optimization. Additionally, the project will require a review key regulatory issues that affect staffing and could be optimized with additional technology input. Opportunities to further optimize staffing levels and staffing functions by selection of design attributes of physical systems and structures need also be identified. A goal of this project is to develop a prioritized assessment of the functional areas, and R&D actions needed for those functional areas, to provide the best optimization« less

Flocking in Distributed Control and Optimization

DTIC Science & Technology

2015-06-01

AFRL-AFOSR-VA-TR-2015-0309 Flocking in Distributed Control and Optimization Alfredo Garcia UNIVERSITY OF VIRGINIA Final Report 06/01/2015... control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION. 1. REPORT DATE (DD-MM-YYYY)      30-09-2015 2. REPORT TYPE Final Performance 3...DATES COVERED (From - To) 01-04-2012 to 31-03-2015 4. TITLE AND SUBTITLE Flocking in Distributed Control and Optimization 5a.  CONTRACT NUMBER 5b

Optimal Server Scheduling to Maintain Constant Customer Waiting Times

DTIC Science & Technology

1988-12-01

I I• I I I I I LCn CN OPTIMAL SERVER SCHEDUUNG TO MAINTAIN CONSTANT CUSTOMER WAITING TIMES THESIS Thomas J. Frey Captain UISAF AFIT/GOR/ENS/88D-7...hw bees appsewlf in ple rtan. cd = , ’ S 087 AFIT/GORMENS/8D-7 OPTIMAL SERVER SCHEDUUNG TO MAINTAIN~ CONSTANT CUSTOMER WAITING TIMES THESIS Thomas j...CONSTANT CUSTOMER WAITING TIMES THESIS Presented to the Faculty of the School of Engineering of the Air Force Institute of Technology Air University In

Toward a Universal Sea Spray Source Function (UNISOURCE)

DTIC Science & Technology

2003-09-30

Toward a Universal Sea Spray Source Function ( UNISOURCE ) Gerrit de Leeuw TNO Physics and Electronics Laboratory P.O. Box 96864 2509 JG The...00-00-2003 to 00-00-2003 4. TITLE AND SUBTITLE Toward a Universal Sea Spray Source Function ( UNISOURCE ) 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

Purpose and Function of the University

ERIC Educational Resources Information Center

Potter, V. R.; And Others

1970-01-01

The authors believe that the primary function of the university is to examine and preserve the value judgments that can elevate the condition of society. It can serve this function by a future-oriented search for truth. University scholars have a major responsibility for survival and qualiity of life in the future. Bibliography. (LC)

Triplet Tuning - a New ``BLACK-BOX'' Computational Scheme for Photochemically Active Molecules

NASA Astrophysics Data System (ADS)

Lin, Zhou; Van Voorhis, Troy

2017-06-01

Density functional theory (DFT) is an efficient computational tool that plays an indispensable role in the design and screening of π-conjugated organic molecules with photochemical significance. However, due to intrinsic problems in DFT such as self-interaction error, the accurate prediction of energy levels is still a challenging task. Functionals can be parameterized to correct these problems, but the parameters that make a well-behaved functional are system-dependent rather than universal in most cases. To alleviate both problems, optimally tuned range-separated hybrid functionals were introduced, in which the range-separation parameter, ω, can be adjusted to impose Koopman's theorem, ɛ_{HOMO} = -I. These functionals turned out to be good estimators for asymptotic properties like ɛ_{HOMO} and ɛ_{LUMO}. In the present study, we propose a ``black-box'' procedure that allows an automatic construction of molecule-specific range-separated hybrid functionals following the idea of such optimal tuning. However, instead of focusing on ɛ_{HOMO} and ɛ_{LUMO}, we target more local, photochemistry-relevant energy levels such as the lowest triplet state, T_1. In practice, we minimize the difference between two E_{{T}_1}'s that are obtained from two DFT-based approaches, Δ-SCF and linear-response TDDFT. We achieve this minimization using a non-empirical adjustment of two parameters in the range-separated hybrid functional - ω, and the percentage of Hartree-Fock contribution in the short-range exchange, c_{HF}. We apply this triplet tuning scheme to a variety of organic molecules with important photochemical applications, including laser dyes, photovoltaics, and light-emitting diodes, and achieved good agreements with the spectroscopic measurements for E_{{T}_1}'s and related local properties. A. Dreuw and M. Head-Gordon, Chem. Rev. 105, 4009 (2015). O. A. Vydrov and G. E. Scuseria, J. Chem. Phys. 125, 234109 (2006). L. Kronik, T. Stein, S. Refaely-Abramson, and R. Baer, J. Chem. Theory Comput. 8, 1515 (2012). Z. Lin and T. A. Van Voorhis, in preparation for submission to J. Chem. Theory Comput.

Design optimization of axial flow hydraulic turbine runner: Part II - multi-objective constrained optimization method

NASA Astrophysics Data System (ADS)

Peng, Guoyi; Cao, Shuliang; Ishizuka, Masaru; Hayama, Shinji

2002-06-01

This paper is concerned with the design optimization of axial flow hydraulic turbine runner blade geometry. In order to obtain a better design plan with good performance, a new comprehensive performance optimization procedure has been presented by combining a multi-variable multi-objective constrained optimization model with a Q3D inverse computation and a performance prediction procedure. With careful analysis of the inverse design of axial hydraulic turbine runner, the total hydraulic loss and the cavitation coefficient are taken as optimization objectives and a comprehensive objective function is defined using the weight factors. Parameters of a newly proposed blade bound circulation distribution function and parameters describing positions of blade leading and training edges in the meridional flow passage are taken as optimization variables.The optimization procedure has been applied to the design optimization of a Kaplan runner with specific speed of 440 kW. Numerical results show that the performance of designed runner is successfully improved through optimization computation. The optimization model is found to be validated and it has the feature of good convergence. With the multi-objective optimization model, it is possible to control the performance of designed runner by adjusting the value of weight factors defining the comprehensive objective function. Copyright

Deep Eutectic Solvents Modified Molecular Imprinted Polymers for Optimized Purification of Chlorogenic Acid from Honeysuckle.

PubMed

Li, Guizhen; Wang, Wei; Wang, Qian; Zhu, Tao

2016-02-01

Deep eutectic solvents (DES) were synthesized with choline chloride (ChCl), and DES modified molecular imprinted polymers (DES-MIPs), DES modified non-imprinted polymers (DES-NIPs, without template), MIPs and NIPs were prepared in an identical procedure. Fourier transform infrared spectrometer (FT-IR) and field emission scanning electron microscopy (FE-SEM) were used to characterize the obtained polymers. Rebinding experiment and solid-phase extraction (SPE) were used to prove the high selectivity adsorption properties of the polymers. Box-Behnken design (BBD) with three factors was used to optimize the extraction condition of chlorogenic acid (CA) from honeysuckles. The optimum extraction conditions were found to be ultrasonic time optimized (20 min), the volume fraction of ethanol (60%) and ratio of liquid to material (15 mL g(-1)). Under these conditions, the mean extraction yield of CA was 12.57 mg g(-1), which was in good agreement with the predicted BBD model value. Purification of hawthorn extract was achieved by SPE process, and SPE recoveries of CA were 72.56, 64.79, 69.34 and 60.08% by DES-MIPs, DES-NIPs, MIPs and NIPs, respectively. The results showed DES-MIPs had potential for promising functional adsorption material for the purification of bioactive compounds. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Nonparametric variational optimization of reaction coordinates

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

Banushkina, Polina V.; Krivov, Sergei V., E-mail: s.krivov@leeds.ac.uk

State of the art realistic simulations of complex atomic processes commonly produce trajectories of large size, making the development of automated analysis tools very important. A popular approach aimed at extracting dynamical information consists of projecting these trajectories into optimally selected reaction coordinates or collective variables. For equilibrium dynamics between any two boundary states, the committor function also known as the folding probability in protein folding studies is often considered as the optimal coordinate. To determine it, one selects a functional form with many parameters and trains it on the trajectories using various criteria. A major problem with such anmore » approach is that a poor initial choice of the functional form may lead to sub-optimal results. Here, we describe an approach which allows one to optimize the reaction coordinate without selecting its functional form and thus avoiding this source of error.« less

Regularization by Functions of Bounded Variation and Applications to Image Enhancement

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

Casas, E.; Kunisch, K.; Pola, C.

1999-09-15

Optimization problems regularized by bounded variation seminorms are analyzed. The optimality system is obtained and finite-dimensional approximations of bounded variation function spaces as well as of the optimization problems are studied. It is demonstrated that the choice of the vector norm in the definition of the bounded variation seminorm is of special importance for approximating subspaces consisting of piecewise constant functions. Algorithms based on a primal-dual framework that exploit the structure of these nondifferentiable optimization problems are proposed. Numerical examples are given for denoising of blocky images with very high noise.

Reconfiguration of Intrinsic Functional Coupling Patterns Following Circumscribed Network Lesions.

PubMed

Eldaief, Mark C; McMains, Stephanie; Hutchison, R Matthew; Halko, Mark A; Pascual-Leone, Alvaro

2017-05-01

Communication between cortical regions is necessary for optimal cognitive processing. Functional relationships between cortical regions can be inferred through measurements of temporal synchrony in spontaneous activity patterns. These relationships can be further elaborated by surveying effects of cortical lesions upon inter-regional connectivity. Lesions to cortical hubs and heteromodal association regions are expected to induce distributed connectivity changes and higher-order cognitive deficits, yet their functional consequences remain relatively unexplored. Here, we used resting-state fMRI to investigate intrinsic functional connectivity (FC) and graph theoretical metrics in 12 patients with circumscribed lesions of the medial prefrontal cortex (mPFC) portion of the Default Network (DN), and compared these metrics with those observed in healthy matched comparison participants and a sample of 1139 healthy individuals. Despite significant mPFC destruction, patients did not demonstrate weakened intrinsic FC among undamaged DN nodes. Instead, network-specific changes were manifested as weaker negative correlations between the DN and attentional and somatomotor networks. These findings conflict with the DN being a homogenous system functionally anchored at mPFC. Rather, they implicate a role for mPFC in mediating cross-network functional interactions. More broadly, our data suggest that lesions to association cortical hubs might induce clinical deficits by disrupting communication between interacting large-scale systems. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Optimal Energy Efficiency Fairness of Nodes in Wireless Powered Communication Networks.

PubMed

Zhang, Jing; Zhou, Qingjie; Ng, Derrick Wing Kwan; Jo, Minho

2017-09-15

In wireless powered communication networks (WPCNs), it is essential to research energy efficiency fairness in order to evaluate the balance of nodes for receiving information and harvesting energy. In this paper, we propose an efficient iterative algorithm for optimal energy efficiency proportional fairness in WPCN. The main idea is to use stochastic geometry to derive the mean proportionally fairness utility function with respect to user association probability and receive threshold. Subsequently, we prove that the relaxed proportionally fairness utility function is a concave function for user association probability and receive threshold, respectively. At the same time, a sub-optimal algorithm by exploiting alternating optimization approach is proposed. Through numerical simulations, we demonstrate that our sub-optimal algorithm can obtain a result close to optimal energy efficiency proportional fairness with significant reduction of computational complexity.

Optimal Energy Efficiency Fairness of Nodes in Wireless Powered Communication Networks

PubMed Central

Zhou, Qingjie; Ng, Derrick Wing Kwan; Jo, Minho

2017-01-01

In wireless powered communication networks (WPCNs), it is essential to research energy efficiency fairness in order to evaluate the balance of nodes for receiving information and harvesting energy. In this paper, we propose an efficient iterative algorithm for optimal energy efficiency proportional fairness in WPCN. The main idea is to use stochastic geometry to derive the mean proportionally fairness utility function with respect to user association probability and receive threshold. Subsequently, we prove that the relaxed proportionally fairness utility function is a concave function for user association probability and receive threshold, respectively. At the same time, a sub-optimal algorithm by exploiting alternating optimization approach is proposed. Through numerical simulations, we demonstrate that our sub-optimal algorithm can obtain a result close to optimal energy efficiency proportional fairness with significant reduction of computational complexity. PMID:28914818

NASA Lewis Research Center/university graduate research program on engine structures

NASA Technical Reports Server (NTRS)

Chamis, C. C.

1985-01-01

NASA Lewis Research Center established a graduate research program in support of the Engine Structures Research activities. This graduate research program focuses mainly on structural and dynamics analyses, computational mechanics, mechanics of composites and structural optimization. The broad objectives of the program, the specific program, the participating universities and the program status are briefly described.

NASA Lewis Research Center/University Graduate Research Program on Engine Structures

NASA Technical Reports Server (NTRS)

Chamis, C. C.

1985-01-01

NASA Lewis Research Center established a graduate research program in support of the Engine Structures Research activities. This graduate research program focuses mainly on structural and dynamics analyses, computational mechanics, mechanics of composites and structural optimization. The broad objectives of the program, the specific program, the participating universities and the program status are briefly described.

Investigating University Educators' Design Thinking and the Implications for Design Support Tools

ERIC Educational Resources Information Center

Bennett, Sue; Agostinho, Shirley; Lockyer, Lori

2016-01-01

All university educators perform design work as they prepare and plan learning experiences for their students. How such design work is undertaken, conceptualised, and optimally supported is the focus of ongoing research for the authors. The purpose of this article is to present the results of a research study that sought to gain a richer…

Leveraging University Research to Serve Economic Development: An Analysis of Policy Dynamics in and across Three US States

ERIC Educational Resources Information Center

Warshaw, Jarrett B.; Hearn, James C.

2014-01-01

As economic competition becomes more global and knowledge-based, US states have independently pursued initiatives in research and development (R&D) and science and technology (S&T). Policy efforts often entwine government, universities, and industry, aiming to stimulate socially optimal levels of innovation and economic growth.…

NOAA & Academia Partnership Building Conference. Highlights (3rd, Washington, DC, November 14-15, 2001).

ERIC Educational Resources Information Center

National Oceanic and Atmospheric Administration (DOC), Silver Spring, MD.

In November 2001 the National Oceanic and Atmospheric Administration (NOAA) hosted the third NOAA and Academia Partnership to evaluate, maintain, and expand on efforts to optimize NOAA-university cooperation. Close partnership between the NOAA and U.S. universities has produced many benefits for the U.S. economy and the environment. Based on the…

Packing Optimization of an Intentionally Stratified Sorbent Bed Containing Dissimilar Media Types

NASA Technical Reports Server (NTRS)

Kidd, Jessica; Guttromson, Jayleen; Holland, Nathan

2010-01-01

The Fire Cartridge is a packed bed air filter with two different and separate layers of media designed to provide respiratory protection from combustion products after a fire event on the International Space Station (ISS). The first layer of media is a carbon monoxide catalyst made from gold nanoparticles dispersed on iron oxide. The second layer of media is universal carbon, commonly used in commercial respirator filters. Each layer must be optimally packed to effectively remove contaminants from the air. Optimal packing is achieved by vibratory agitations. However, if post-packing movement of the media within the cartridge occurs, mixing of the bed layers, air voids, and channeling could cause preferential air flow and allow contaminants to pass. Several iterations of prototype fire cartridges were developed to reduce post-packing movement of the media within each layer (settling), and to prevent mixing of the two media types. Both types of movement of the media contribute to decreased fire cartridge performance. Each iteration of the fire cartridge design was tested to demonstrate mechanical loads required to cause detrimental movement within the bed, and resulting level of functionality of the media beds after movement was detected. In order to optimally pack each layer, vertical, horizontal, and orbital agitations were tested and a final packed bulk density was calculated for each method. Packed bulk density must be calculated for each lot of catalyst to accommodate variations in particle size, shape, and density. In addition, a physical divider sheet between each type of media was added within the fire cartridge design to further inhibit intermixing of the bed layers.

CURE-SMOTE algorithm and hybrid algorithm for feature selection and parameter optimization based on random forests.

PubMed

Ma, Li; Fan, Suohai

2017-03-14

The random forests algorithm is a type of classifier with prominent universality, a wide application range, and robustness for avoiding overfitting. But there are still some drawbacks to random forests. Therefore, to improve the performance of random forests, this paper seeks to improve imbalanced data processing, feature selection and parameter optimization. We propose the CURE-SMOTE algorithm for the imbalanced data classification problem. Experiments on imbalanced UCI data reveal that the combination of Clustering Using Representatives (CURE) enhances the original synthetic minority oversampling technique (SMOTE) algorithms effectively compared with the classification results on the original data using random sampling, Borderline-SMOTE1, safe-level SMOTE, C-SMOTE, and k-means-SMOTE. Additionally, the hybrid RF (random forests) algorithm has been proposed for feature selection and parameter optimization, which uses the minimum out of bag (OOB) data error as its objective function. Simulation results on binary and higher-dimensional data indicate that the proposed hybrid RF algorithms, hybrid genetic-random forests algorithm, hybrid particle swarm-random forests algorithm and hybrid fish swarm-random forests algorithm can achieve the minimum OOB error and show the best generalization ability. The training set produced from the proposed CURE-SMOTE algorithm is closer to the original data distribution because it contains minimal noise. Thus, better classification results are produced from this feasible and effective algorithm. Moreover, the hybrid algorithm's F-value, G-mean, AUC and OOB scores demonstrate that they surpass the performance of the original RF algorithm. Hence, this hybrid algorithm provides a new way to perform feature selection and parameter optimization.

Doing without: serving allied health programs at universities without medical schools.

PubMed

Devin, Robin B

2009-01-01

This article compares libraries in the United States that serve allied health programs at universities without medical schools. Although these university libraries all serve a similar array of health sciences programs, the organization of their library services differ dramatically. There is also little similarity in their collections, particularly in their choice of indexing and abstracting databases. Yet librarians serving as liaisons to allied health programs at universities without medical schools face comparable challenges in meeting the needs of their users. All reported concerns about gaps in their collections and felt hard pressed to provide optimal library service.

Universal field matching in craniospinal irradiation by a background-dose gradient-optimized method.

PubMed

Traneus, Erik; Bizzocchi, Nicola; Fellin, Francesco; Rombi, Barbara; Farace, Paolo

2018-01-01

The gradient-optimized methods are overcoming the traditional feathering methods to plan field junctions in craniospinal irradiation. In this note, a new gradient-optimized technique, based on the use of a background dose, is described. Treatment planning was performed by RayStation (RaySearch Laboratories, Stockholm, Sweden) on the CT scans of a pediatric patient. Both proton (by pencil beam scanning) and photon (by volumetric modulated arc therapy) treatments were planned with three isocenters. An 'in silico' ideal background dose was created first to cover the upper-spinal target and to produce a perfect dose gradient along the upper and lower junction regions. Using it as background, the cranial and the lower-spinal beams were planned by inverse optimization to obtain dose coverage of their relevant targets and of the junction volumes. Finally, the upper-spinal beam was inversely planned after removal of the background dose and with the previously optimized beams switched on. In both proton and photon plans, the optimized cranial and the lower-spinal beams produced a perfect linear gradient in the junction regions, complementary to that produced by the optimized upper-spinal beam. The final dose distributions showed a homogeneous coverage of the targets. Our simple technique allowed to obtain high-quality gradients in the junction region. Such technique universally works for photons as well as protons and could be applicable to the TPSs that allow to manage a background dose. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

The association between resting functional connectivity and dispositional optimism.

PubMed

Ran, Qian; Yang, Junyi; Yang, Wenjing; Wei, Dongtao; Qiu, Jiang; Zhang, Dong

2017-01-01

Dispositional optimism is an individual characteristic that plays an important role in human experience. Optimists are people who tend to hold positive expectations for their future. Previous studies have focused on the neural basis of optimism, such as task response neural activity and brain structure volume. However, the functional connectivity between brain regions of the dispositional optimists are poorly understood. Previous study suggested that the ventromedial prefrontal cortex (vmPFC) are associated with individual differences in dispositional optimism, but it is unclear whether there are other brain regions that combine with the vmPFC to contribute to dispositional optimism. Thus, the present study used the resting-state functional connectivity (RSFC) approach and set the vmPFC as the seed region to examine if differences in functional brain connectivity between the vmPFC and other brain regions would be associated with individual differences in dispositional optimism. The results found that dispositional optimism was significantly positively correlated with the strength of the RSFC between vmPFC and middle temporal gyrus (mTG) and negativly correlated with RSFC between vmPFC and inferior frontal gyrus (IFG). These findings may be suggested that mTG and IFG which associated with emotion processes and emotion regulation also play an important role in the dispositional optimism.

The association between resting functional connectivity and dispositional optimism

PubMed Central

Yang, Wenjing; Wei, Dongtao; Qiu, Jiang; Zhang, Dong

2017-01-01

Dispositional optimism is an individual characteristic that plays an important role in human experience. Optimists are people who tend to hold positive expectations for their future. Previous studies have focused on the neural basis of optimism, such as task response neural activity and brain structure volume. However, the functional connectivity between brain regions of the dispositional optimists are poorly understood. Previous study suggested that the ventromedial prefrontal cortex (vmPFC) are associated with individual differences in dispositional optimism, but it is unclear whether there are other brain regions that combine with the vmPFC to contribute to dispositional optimism. Thus, the present study used the resting-state functional connectivity (RSFC) approach and set the vmPFC as the seed region to examine if differences in functional brain connectivity between the vmPFC and other brain regions would be associated with individual differences in dispositional optimism. The results found that dispositional optimism was significantly positively correlated with the strength of the RSFC between vmPFC and middle temporal gyrus (mTG) and negativly correlated with RSFC between vmPFC and inferior frontal gyrus (IFG). These findings may be suggested that mTG and IFG which associated with emotion processes and emotion regulation also play an important role in the dispositional optimism. PMID:28700613

SU-D-12A-06: A Comprehensive Parameter Analysis for Low Dose Cone-Beam CT Reconstruction

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

Lu, W; Southern Medical University, Guangzhou; Yan, H

Purpose: There is always a parameter in compressive sensing based iterative reconstruction (IR) methods low dose cone-beam CT (CBCT), which controls the weight of regularization relative to data fidelity. A clear understanding of the relationship between image quality and parameter values is important. The purpose of this study is to investigate this subject based on experimental data and a representative advanced IR algorithm using Tight-frame (TF) regularization. Methods: Three data sets of a Catphan phantom acquired at low, regular and high dose levels are used. For each tests, 90 projections covering a 200-degree scan range are used for reconstruction. Threemore » different regions-of-interest (ROIs) of different contrasts are used to calculate contrast-to-noise ratios (CNR) for contrast evaluation. A single point structure is used to measure modulation transfer function (MTF) for spatial-resolution evaluation. Finally, we analyze CNRs and MTFs to study the relationship between image quality and parameter selections. Results: It was found that: 1) there is no universal optimal parameter. The optimal parameter value depends on specific task and dose level. 2) There is a clear trade-off between CNR and resolution. The parameter for the best CNR is always smaller than that for the best resolution. 3) Optimal parameters are also dose-specific. Data acquired under a high dose protocol require less regularization, yielding smaller optimal parameter values. 4) Comparing with conventional FDK images, TF-based CBCT images are better under a certain optimally selected parameters. The advantages are more obvious for low dose data. Conclusion: We have investigated the relationship between image quality and parameter values in the TF-based IR algorithm. Preliminary results indicate optimal parameters are specific to both the task types and dose levels, providing guidance for selecting parameters in advanced IR algorithms. This work is supported in part by NIH (1R01CA154747-01)« less

Pair-Wise and Many-Body Dispersive Interactions Coupled to an Optimally Tuned Range-Separated Hybrid Functional.

PubMed

Agrawal, Piyush; Tkatchenko, Alexandre; Kronik, Leeor

2013-08-13

We propose a nonempirical, pair-wise or many-body dispersion-corrected, optimally tuned range-separated hybrid functional. This functional retains the advantages of the optimal-tuning approach in the prediction of the electronic structure. At the same time, it gains accuracy in the prediction of binding energies for dispersively bound systems, as demonstrated on the S22 and S66 benchmark sets of weakly bound dimers.

Optimization technique of wavefront coding system based on ZEMAX externally compiled programs

NASA Astrophysics Data System (ADS)

Han, Libo; Dong, Liquan; Liu, Ming; Zhao, Yuejin; Liu, Xiaohua

2016-10-01

Wavefront coding technique as a means of athermalization applied to infrared imaging system, the design of phase plate is the key to system performance. This paper apply the externally compiled programs of ZEMAX to the optimization of phase mask in the normal optical design process, namely defining the evaluation function of wavefront coding system based on the consistency of modulation transfer function (MTF) and improving the speed of optimization by means of the introduction of the mathematical software. User write an external program which computes the evaluation function on account of the powerful computing feature of the mathematical software in order to find the optimal parameters of phase mask, and accelerate convergence through generic algorithm (GA), then use dynamic data exchange (DDE) interface between ZEMAX and mathematical software to realize high-speed data exchanging. The optimization of the rotational symmetric phase mask and the cubic phase mask have been completed by this method, the depth of focus increases nearly 3 times by inserting the rotational symmetric phase mask, while the other system with cubic phase mask can be increased to 10 times, the consistency of MTF decrease obviously, the maximum operating temperature of optimized system range between -40°-60°. Results show that this optimization method can be more convenient to define some unconventional optimization goals and fleetly to optimize optical system with special properties due to its externally compiled function and DDE, there will be greater significance for the optimization of unconventional optical system.

Antecedents of basic psychological need satisfaction of pharmacy students: The role of peers, family, lecturers and workload.

PubMed

Basson, Mariëtta J; Rothmann, Sebastiaan

2018-04-01

Self-determination theory (SDT) provides a model to improve pharmacy students' well-being or functioning in their study context. According to SDT, students need a context that satisfies their needs for autonomy, relatedness and competence in order to function optimally. Contextual factors that could have an impact on a student's functioning are lecturers, family, peers and workload. To investigate whether there is a difference between the contributions family, lecturers, peers and workload make towards the satisfaction of pharmacy students' basic psychological needs within a university context. An electronic survey was administered amongst students registered with the North-West University's School of Pharmacy. Registered pharmacy students, 779, completed said electronic survey comprised of a questionnaire on demographics, BMPN (Balanced Measure of Psychological Needs) and self-developed ANPNS (Antecedents of Psychological Need-satisfaction Scale). Data derived from the afore-going was analysed with the aid of structural equation modelling (SEM). Structural equation modelling explained 46%, 25% and 30% respectively of the total group's variances in autonomy, competence and relatedness satisfaction, and 26% of the variance in psychological need frustration. Peers and family played a significant role in the satisfaction of students' need for autonomy, relatedness and competence, whilst workload seemingly hampered satisfaction with regards to relatedness and autonomy. Workload contributed towards frustration with regards to psychological need satisfaction. The role played by lecturers in satisfying pharmacy students' need for autonomy, relatedness and competence will also be highlighted. This study added to the body of knowledge regarding contextual factors and the impact those factors have on pharmacy students' need satisfaction by illustrating that not all factors (family, lecturers, peers and workload) can be considered equal. Lecturers ought to recognise the important role family and peers play in the emotional and mental wellbeing of students and utilise those factors in their teaching. The mechanism of basic psychological need satisfaction as described in Self-determination theory provide insight into pharmacy students' optimal functioning. Hence the influence of contextual factors, (lecturers, peers, family and workload) on the need satisfaction was investigated by means of a survey. The structural model explained 46%, 25% and 30% of the variances in autonomy, competence and relatedness satisfaction and 26% of the variance in psychological need frustration. Family and Peer support contributed the most to the variance explained of the variables. Lecturers should acknowledge this important role of family and peers and utilise this premise when they design learning encounters. Copyright © 2017 Elsevier Inc. All rights reserved.

Quasi-Square Hole with Optimum Shape in an Infinite Plate Subjected to In-Plane Loading. Optimization of Inner and Outer Boundaries of Beams and Plates with Holes,

DTIC Science & Technology

1982-04-01

Division 045 Administracion Naval Ship Resarc; and Development 14114 (Technical Library) Structures Research Division Center Langley Research Center...Virginia 23607 university of California. San Diego Dr. J. L. Swedlow Department of Applied Mechanics Carnegie-Mellon University La Jolla, California...Batdorf Keman AviDyne Suite 220 University of California Division of Kaman La Jolla, California 92037 School of Engineering Sciences Corporation and

An Universal and Easy-to-Use Model for the Pressure of Arbitrary-Shape 3D Multifunctional Integumentary Cardiac Membranes.

PubMed

Su, Yewang; Liu, Zhuangjian; Xu, Lizhi

2016-04-20

Recently developed concepts for 3D, organ-mounted electronics for cardiac applications require a universal and easy-to-use mechanical model to calculate the average pressure associated with operation of the device, which is crucial for evaluation of design efficacy and optimization. This work proposes a simple, accurate, easy-to-use, and universal model to quantify the average pressure for arbitrary-shape organs. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modeling and Optimization of Shaped Charge Liner Collapse and Jet Formation

DTIC Science & Technology

1993-01-01

Properties of Chemical Explosives and Explosive Simulants," Technical Report UCRL -52997, University of California, CA, 1981. 22. Mader, C. L., "FORTRAN...Numerical Modeling of Detonations, University of California Press, CA, 19,9. 49. Wilkens, M. L., "The Equation of State of PBX 9404 and LX04-01 ," Report UCRL ...of High Explosive Detonation Products, Report UCRL -50422, University of Califor- nia, CA, 1968. 51. Green, L. G.; Traver, C. M.; and Erskine, D. J

A Multivariate Quality Loss Function Approach for Optimization of Spinning Processes

NASA Astrophysics Data System (ADS)

Chakraborty, Shankar; Mitra, Ankan

2018-05-01

Recent advancements in textile industry have given rise to several spinning techniques, such as ring spinning, rotor spinning etc., which can be used to produce a wide variety of textile apparels so as to fulfil the end requirements of the customers. To achieve the best out of these processes, they should be utilized at their optimal parametric settings. However, in presence of multiple yarn characteristics which are often conflicting in nature, it becomes a challenging task for the spinning industry personnel to identify the best parametric mix which would simultaneously optimize all the responses. Hence, in this paper, the applicability of a new systematic approach in the form of multivariate quality loss function technique is explored for optimizing multiple quality characteristics of yarns while identifying the ideal settings of two spinning processes. It is observed that this approach performs well against the other multi-objective optimization techniques, such as desirability function, distance function and mean squared error methods. With slight modifications in the upper and lower specification limits of the considered quality characteristics, and constraints of the non-linear optimization problem, it can be successfully applied to other processes in textile industry to determine their optimal parametric settings.

Performance of Grey Wolf Optimizer on large scale problems

NASA Astrophysics Data System (ADS)

Gupta, Shubham; Deep, Kusum

2017-01-01

For solving nonlinear continuous problems of optimization numerous nature inspired optimization techniques are being proposed in literature which can be implemented to solve real life problems wherein the conventional techniques cannot be applied. Grey Wolf Optimizer is one of such technique which is gaining popularity since the last two years. The objective of this paper is to investigate the performance of Grey Wolf Optimization Algorithm on large scale optimization problems. The Algorithm is implemented on 5 common scalable problems appearing in literature namely Sphere, Rosenbrock, Rastrigin, Ackley and Griewank Functions. The dimensions of these problems are varied from 50 to 1000. The results indicate that Grey Wolf Optimizer is a powerful nature inspired Optimization Algorithm for large scale problems, except Rosenbrock which is a unimodal function.

Optimism, coping and long-term recovery from coronary artery surgery in women.

PubMed

King, K B; Rowe, M A; Kimble, L P; Zerwic, J J

1998-02-01

Optimism, coping strategies, and psychological and functional outcomes were measured in 55 women undergoing coronary artery surgery. Data were collected in-hospital and at 1, 6, and 12 months after surgery. Optimism was related to positive moods and life satisfaction, and inversely related to negative moods. Few relationships were found between optimism and functional ability. Cognitive coping strategies accounted for a mediating effect between optimism and negative mood. Optimists were more likely to accept their situation, and less likely to use escapism. In turn, these coping strategies were inversely related to negative mood and mediated the relationship between optimism and this outcome. Optimism was not related to problem-focused coping strategies; this, these coping strategies cannot explain the relationship between optimism and outcomes.

Executive Function: Comparing Bilingual and Monolingual Iranian University Students

ERIC Educational Resources Information Center

Kazemeini, Toktam; Fadardi, Javad Salehi

2016-01-01

The study aimed to examine whether Kurdish-Persian early Bilingual university students (EBL) and Persian Monolingual university students (ML) differ on tasks of executive function (EF). Thirty male EBL and 30 male ML students from Ferdowsi University of Mashhad completed a Persian Stroop Color-Word task (SCWT), Backward Digit Span Test (BDST),…

Evidence for composite cost functions in arm movement planning: an inverse optimal control approach.

PubMed

Berret, Bastien; Chiovetto, Enrico; Nori, Francesco; Pozzo, Thierry

2011-10-01

An important issue in motor control is understanding the basic principles underlying the accomplishment of natural movements. According to optimal control theory, the problem can be stated in these terms: what cost function do we optimize to coordinate the many more degrees of freedom than necessary to fulfill a specific motor goal? This question has not received a final answer yet, since what is optimized partly depends on the requirements of the task. Many cost functions were proposed in the past, and most of them were found to be in agreement with experimental data. Therefore, the actual principles on which the brain relies to achieve a certain motor behavior are still unclear. Existing results might suggest that movements are not the results of the minimization of single but rather of composite cost functions. In order to better clarify this last point, we consider an innovative experimental paradigm characterized by arm reaching with target redundancy. Within this framework, we make use of an inverse optimal control technique to automatically infer the (combination of) optimality criteria that best fit the experimental data. Results show that the subjects exhibited a consistent behavior during each experimental condition, even though the target point was not prescribed in advance. Inverse and direct optimal control together reveal that the average arm trajectories were best replicated when optimizing the combination of two cost functions, nominally a mix between the absolute work of torques and the integrated squared joint acceleration. Our results thus support the cost combination hypothesis and demonstrate that the recorded movements were closely linked to the combination of two complementary functions related to mechanical energy expenditure and joint-level smoothness.

Optimization for high-dose-rate brachytherapy of cervical cancer with adaptive simulated annealing and gradient descent.

PubMed

Yao, Rui; Templeton, Alistair K; Liao, Yixiang; Turian, Julius V; Kiel, Krystyna D; Chu, James C H

2014-01-01

To validate an in-house optimization program that uses adaptive simulated annealing (ASA) and gradient descent (GD) algorithms and investigate features of physical dose and generalized equivalent uniform dose (gEUD)-based objective functions in high-dose-rate (HDR) brachytherapy for cervical cancer. Eight Syed/Neblett template-based cervical cancer HDR interstitial brachytherapy cases were used for this study. Brachytherapy treatment plans were first generated using inverse planning simulated annealing (IPSA). Using the same dwell positions designated in IPSA, plans were then optimized with both physical dose and gEUD-based objective functions, using both ASA and GD algorithms. Comparisons were made between plans both qualitatively and based on dose-volume parameters, evaluating each optimization method and objective function. A hybrid objective function was also designed and implemented in the in-house program. The ASA plans are higher on bladder V75% and D2cc (p=0.034) and lower on rectum V75% and D2cc (p=0.034) than the IPSA plans. The ASA and GD plans are not significantly different. The gEUD-based plans have higher homogeneity index (p=0.034), lower overdose index (p=0.005), and lower rectum gEUD and normal tissue complication probability (p=0.005) than the physical dose-based plans. The hybrid function can produce a plan with dosimetric parameters between the physical dose-based and gEUD-based plans. The optimized plans with the same objective value and dose-volume histogram could have different dose distributions. Our optimization program based on ASA and GD algorithms is flexible on objective functions, optimization parameters, and can generate optimized plans comparable with IPSA. Copyright © 2014 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Optimism Moderates the Influence of Pain Catastrophizing on Shoulder Pain Outcome: A Longitudinal Analysis.

PubMed

Coronado, Rogelio A; Simon, Corey B; Lentz, Trevor A; Gay, Charles W; Mackie, Lauren N; George, Steven Z

2017-01-01

Study Design Secondary analysis of prospectively collected data. Background An abundance of evidence has highlighted the influence of pain catastrophizing and fear avoidance on clinical outcomes. Less is known about the interaction of positive psychological resources with these pain-associated distress factors. Objective To assess whether optimism moderates the influence of pain catastrophizing and fear avoidance on 3-month clinical outcomes in patients with shoulder pain. Methods Data from 63 individuals with shoulder pain (mean ± SD age, 38.8 ± 14.9 years; 30 female) were examined. Demographic, psychological, and clinical characteristics were obtained at baseline. Validated measures were used to assess optimism (Life Orientation Test-Revised), pain catastrophizing (Pain Catastrophizing Scale), fear avoidance (Fear-Avoidance Beliefs Questionnaire physical activity subscale), shoulder pain intensity (Brief Pain Inventory), and shoulder function (Pennsylvania Shoulder Score function subscale). Shoulder pain and function were reassessed at 3 months. Regression models assessed the influence of (1) pain catastrophizing and optimism and (2) fear avoidance and optimism. The final multivariable models controlled for factors of age, sex, education, and baseline scores, and included 3-month pain intensity and function as separate dependent variables. Results Shoulder pain (mean difference, -1.6; 95% confidence interval [CI]: -2.1, -1.2) and function (mean difference, 2.4; 95% CI: 0.3, 4.4) improved over 3 months. In multivariable analyses, there was an interaction between pain catastrophizing and optimism (β = 0.19; 95% CI: 0.02, 0.35) for predicting 3-month shoulder function (F = 16.8, R 2 = 0.69, P<.001), but not pain (P = .213). Further examination of the interaction with the Johnson-Neyman technique showed that higher levels of optimism lessened the influence of pain catastrophizing on function. There was no evidence of significant moderation of fear-avoidance beliefs for 3-month shoulder pain (P = .090) or function (P = .092). Conclusion Optimism decreased the negative influence of pain catastrophizing on shoulder function, but not pain intensity. Optimism did not alter the influence of fear-avoidance beliefs on these outcomes. Level of Evidence Prognosis, level 2b. J Orthop Sports Phys Ther 2017;47(1):21-30. Epub 5 Nov 2016. doi:10.2519/jospt.2017.7068.

Overt attention toward oriented objects in free-viewing barn owls.

PubMed

Harmening, Wolf Maximilian; Orlowski, Julius; Ben-Shahar, Ohad; Wagner, Hermann

2011-05-17

Visual saliency based on orientation contrast is a perceptual product attributed to the functional organization of the mammalian brain. We examined this visual phenomenon in barn owls by mounting a wireless video microcamera on the owls' heads and confronting them with visual scenes that contained one differently oriented target among similarly oriented distracters. Without being confined by any particular task, the owls looked significantly longer, more often, and earlier at the target, thus exhibiting visual search strategies so far demonstrated in similar conditions only in primates. Given the considerable differences in phylogeny and the structure of visual pathways between owls and humans, these findings suggest that orientation saliency has computational optimality in a wide variety of ecological contexts, and thus constitutes a universal building block for efficient visual information processing in general.

Program to study optimal protocol for cardiovascular and muscular efficiency. [physical fitness training for manned space flight

NASA Technical Reports Server (NTRS)

Olree, H. D.

1974-01-01

Training programs necessary for the development of optimal strength during prolonged manned space flight were examined, and exercises performed on the Super Mini Gym Skylab 2 were compared with similar exercises on the Universal Gym and calisthenics. Cardiopulmonary gains were found negligible but all training groups exhibited good gains in strength.

Assessment Tools for Basic Army Noncommissioned Officer Training

DTIC Science & Technology

2009-05-01

2008). Optimal learning in optimal contexts : The role of self -determination in education. Canadian Psychology, 49, 233–240. Magolda, M.B.B...1999). Creating contexts for learning and self -authorship: constructive- developmental pedagogy. Nashville, TN: Vanderbilt Press. Neisser, U...participation. New York, NY: Cambridge University Press. Magolda, M.B.B. (1999). Creating contexts for learning and self -authorship: constructive

WORK FORCE OPTIMIZATION FOR 2025

DTIC Science & Technology

2016-02-08

AIR WAR COLLEGE AIR UNIVERSITY WORK FORCE OPTIMIZATION FOR 2025 By Edward Buckner, GS-14, Army A Research Report Submitted to the...not copyrighted, but is the property of the United States government. iii Biography GS-14 Edward Buckner attends the Air War College , Air...in improving civilian fitness should reduce medical cost paid by DOD. 3. Decision Making Skills Development Everyone is required to make

The role of under-determined approximations in engineering and science application

NASA Technical Reports Server (NTRS)

Carpenter, William C.

1992-01-01

There is currently a great deal of interest in using response surfaces in the optimization of aircraft performance. The objective function and/or constraint equations involved in these optimization problems may come from numerous disciplines such as structures, aerodynamics, environmental engineering, etc. In each of these disciplines, the mathematical complexity of the governing equations usually dictates that numerical results be obtained from large computer programs such as a finite element method program. Thus, when performing optimization studies, response surfaces are a convenient way of transferring information from the various disciplines to the optimization algorithm as opposed to bringing all the sundry computer programs together in a massive computer code. Response surfaces offer another advantage in the optimization of aircraft structures. A characteristic of these types of optimization problems is that evaluation of the objective function and response equations (referred to as a functional evaluation) can be very expensive in a computational sense. Because of the computational expense in obtaining functional evaluations, the present study was undertaken to investigate under-determinined approximations. An under-determined approximation is one in which there are fewer training pairs (pieces of information about a function) than there are undetermined parameters (coefficients or weights) associated with the approximation. Both polynomial approximations and neural net approximations were examined. Three main example problems were investigated: (1) a function of one design variable was considered; (2) a function of two design variables was considered; and (3) a 35 bar truss with 4 design variables was considered.

Reconstruction of the unknown optimization cost functions from experimental recordings during static multi-finger prehension

PubMed Central

Niu, Xun; Terekhov, Alexander V.; Latash, Mark L.; Zatsiorsky, Vladimir M.

2013-01-01

The goal of the research is to reconstruct the unknown cost (objective) function(s) presumably used by the neural controller for sharing the total force among individual fingers in multi-finger prehension. The cost function was determined from experimental data by applying the recently developed Analytical Inverse Optimization (ANIO) method (Terekhov et al 2010). The core of the ANIO method is the Theorem of Uniqueness that specifies conditions for unique (with some restrictions) estimation of the objective functions. In the experiment, subjects (n=8) grasped an instrumented handle and maintained it at rest in the air with various external torques, loads, and target grasping forces applied to the object. The experimental data recorded from 80 trials showed a tendency to lie on a 2-dimensional hyperplane in the 4-dimensional finger-force space. Because the constraints in each trial were different, such a propensity is a manifestation of a neural mechanism (not the task mechanics). In agreement with the Lagrange principle for the inverse optimization, the plane of experimental observations was close to the plane resulting from the direct optimization. The latter plane was determined using the ANIO method. The unknown cost function was reconstructed successfully for each performer, as well as for the group data. The cost functions were found to be quadratic with non-zero linear terms. The cost functions obtained with the ANIO method yielded more accurate results than other optimization methods. The ANIO method has an evident potential for addressing the problem of optimization in motor control. PMID:22104742

Cryopreservation of Hepatocyte Microbeads for Clinical Transplantation

PubMed Central

Jitraruch, Suttiruk; Hughes, Robin D.; Filippi, Celine; Lehec, Sharon C.; Glover, Leanne; Mitry, Ragai R.

2017-01-01

Intraperitoneal transplantation of hepatocyte microbeads is an attractive option for the management of acute liver failure. Encapsulation of hepatocytes in alginate microbeads supports their function and prevents immune attack of the cells. Establishment of banked cryopreserved hepatocyte microbeads is important for emergency use. The aim of this study was to develop an optimized protocol for cryopreservation of hepatocyte microbeads for clinical transplantation using modified freezing solutions. Four freezing solutions with potential for clinical application were investigated. Human and rat hepatocytes cryopreserved with University of Wisconsin (UW)/10% dimethyl sulfoxide (DMSO)/5% (300 mM) glucose and CryoStor CS10 showed better postthawing cell viability, attachment, and hepatocyte functions than with histidine–tryptophan–ketoglutarate/10% DMSO/5% glucose and Bambanker. The 2 freezing solutions that gave better results were studied with human and rat hepatocytes microbeads. Similar effects on cryopreserved microbead morphology (external and ultrastructural), viability, and hepatocyte-functions post thawing were observed over 7 d in culture. UW/DMSO/glucose, as a basal freezing medium, was used to investigate the additional effects of cytoprotectants: a pan-caspase inhibitor (benzyloxycarbonyl-Val-Ala-dl-Asp-fluoromethylketone [ZVAD]), an antioxidant (desferoxamine [DFO]), and a buffering and mechanical protectant (human serum albumin [HSA]) on RMBs. ZVAD (60 µM) had a beneficial effect on cell viability that was greater than with DFO (1 mM), HSA (2%), and basal freezing medium alone. Improvements in the ultrastructure of encapsulated hepatocytes and a lower degree of cell apoptosis were observed with all 3 cytoprotectants, with ZVAD tending to provide the greatest effect. Cytochrome P450 activity was significantly higher in the 3 cytoprotectant groups than with fresh microbeads. In conclusion, developing an optimized cryopreservation protocol by adding cytoprotectants such as ZVAD could improve the outcome of cryopreserved hepatocyte microbeads for future clinical use. PMID:28901189

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

PubMed

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

2015-06-01

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

A Case-Controlled Study of Successful Aging in Older Adults with HIV

PubMed Central

Moore, Raeanne C.; Moore, David J.; Thompson, Wesley; Vahia, Ipsit V.; Grant, Igor; Jeste, Dilip V.

2013-01-01

OBJECTIVES There is a growing public health interest in the aging HIV-infected (HIV+) population, although there is a dearth of research on successful aging with HIV. This study aimed to understand the risk and protective factors associated with self-rated successful aging (SRSA) with HIV. DESIGN Cross-sectional, case-controlled. SETTING HIV Neurobehavioral Research Program and the Stein Institute for Research on Aging at University of California, San Diego. PARTICIPANTS Eighty-three community-dwelling HIV+ and 83 demographically matched HIV-uninfected (HIV−) individuals, enrolled between 12/1/11 and 5/10/12, mean age of 59 years, primarily Caucasian males, 69% with AIDS, who had been living with an HIV diagnosis for 16 years. Diagnostic criteria for HIV/AIDS was obtained through a blood draw. MEASUREMENTS Participants provided ratings of SRSA as part of a comprehensive survey which included measures of physical and emotional functioning and positive psychological traits. Relationships between how the different variables related to SRSA were explored. RESULTS While SRSA was lower in the HIV+ individuals than their HIV− counterparts, 66% of adults with HIV reported scores of 5 or higher on a 10-point scale of SRSA. Despite worse physical and mental functioning and greater psychosocial stress among the HIV+ participants, the two groups had comparable levels of optimism, personal mastery, and social support. SRSA in HIV+ individuals was associated with better physical and emotional functioning and positive psychological factors, but not HIV disease status or negative life events. CONCLUSION Successful psychosocial aging is possible in older HIV+ individuals. Positive psychological traits such as resilience, optimism, and sense of personal mastery have stronger relationship with SRSA than duration or severity of HIV disease. Research on interventions to enhance these positive traits in HIV+ adults is warranted. PMID:23759460

A universal strategy for the creation of machine learning-based atomistic force fields

NASA Astrophysics Data System (ADS)

Huan, Tran Doan; Batra, Rohit; Chapman, James; Krishnan, Sridevi; Chen, Lihua; Ramprasad, Rampi

2017-09-01

Emerging machine learning (ML)-based approaches provide powerful and novel tools to study a variety of physical and chemical problems. In this contribution, we outline a universal strategy to create ML-based atomistic force fields, which can be used to perform high-fidelity molecular dynamics simulations. This scheme involves (1) preparing a big reference dataset of atomic environments and forces with sufficiently low noise, e.g., using density functional theory or higher-level methods, (2) utilizing a generalizable class of structural fingerprints for representing atomic environments, (3) optimally selecting diverse and non-redundant training datasets from the reference data, and (4) proposing various learning approaches to predict atomic forces directly (and rapidly) from atomic configurations. From the atomistic forces, accurate potential energies can then be obtained by appropriate integration along a reaction coordinate or along a molecular dynamics trajectory. Based on this strategy, we have created model ML force fields for six elemental bulk solids, including Al, Cu, Ti, W, Si, and C, and show that all of them can reach chemical accuracy. The proposed procedure is general and universal, in that it can potentially be used to generate ML force fields for any material using the same unified workflow with little human intervention. Moreover, the force fields can be systematically improved by adding new training data progressively to represent atomic environments not encountered previously.

Effective algorithm for solving complex problems of production control and of material flows control of industrial enterprise

NASA Astrophysics Data System (ADS)

Mezentsev, Yu A.; Baranova, N. V.

2018-05-01

A universal economical and mathematical model designed for determination of optimal strategies for managing subsystems (components of subsystems) of production and logistics of enterprises is considered. Declared universality allows taking into account on the system level both production components, including limitations on the ways of converting raw materials and components into sold goods, as well as resource and logical restrictions on input and output material flows. The presented model and generated control problems are developed within the framework of the unified approach that allows one to implement logical conditions of any complexity and to define corresponding formal optimization tasks. Conceptual meaning of used criteria and limitations are explained. The belonging of the generated tasks of the mixed programming with the class of NP is shown. An approximate polynomial algorithm for solving the posed optimization tasks for mixed programming of real dimension with high computational complexity is proposed. Results of testing the algorithm on the tasks in a wide range of dimensions are presented.

On the optimality of a universal noiseless coder

NASA Technical Reports Server (NTRS)

Yeh, Pen-Shu; Rice, Robert F.; Miller, Warner H.

1993-01-01

Rice developed a universal noiseless coding structure that provides efficient performance over an extremely broad range of source entropy. This is accomplished by adaptively selecting the best of several easily implemented variable length coding algorithms. Variations of such noiseless coders have been used in many NASA applications. Custom VLSI coder and decoder modules capable of processing over 50 million samples per second have been fabricated and tested. In this study, the first of the code options used in this module development is shown to be equivalent to a class of Huffman code under the Humblet condition, for source symbol sets having a Laplacian distribution. Except for the default option, other options are shown to be equivalent to the Huffman codes of a modified Laplacian symbol set, at specified symbol entropy values. Simulation results are obtained on actual aerial imagery over a wide entropy range, and they confirm the optimality of the scheme. Comparison with other known techniques are performed on several widely used images and the results further validate the coder's optimality.

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

PubMed

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

2004-05-01

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

Optimal Control for Quantum Driving of Two-Level Systems

NASA Astrophysics Data System (ADS)

Qi, Xiao-Qiu

2018-01-01

In this paper, the optimal quantum control of two-level systems is studied by the decompositions of SU(2). Using the Pontryagin maximum principle, the minimum time of quantum control is analyzed in detail. The solution scheme of the optimal control function is given in the general case. Finally, two specific cases, which can be applied in many quantum systems, are used to illustrate the scheme, while the corresponding optimal control functions are obtained.

Generalized Convexity and Concavity Properties of the Optimal Value Function in Parametric Nonlinear Programming.

DTIC Science & Technology

1983-04-11

existing ones. * -37- !I T-472 REFERENCES [1] Avriel, M., W. E. Diewert, S. Schaible and W. T. Ziemba (1981). Introduction to concave and generalized concave...functions. In Generalized Concavity in Optimization and Economics (S. Schaible and W. T. Ziemba , eds.), Academic Press, New York, pp. 21-50. (21 Bank...Optimality conditions involving generalized convex mappings. In Generalized Concavity in Optimization and Economics (S. Schaible and W. T. Ziemba

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been provEn effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. Several approaches that have proven effective for other evolutionary algorithms are modified and implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for standard test optimization problems and for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

Solving bi-level optimization problems in engineering design using kriging models

NASA Astrophysics Data System (ADS)

Xia, Yi; Liu, Xiaojie; Du, Gang

2018-05-01

Stackelberg game-theoretic approaches are applied extensively in engineering design to handle distributed collaboration decisions. Bi-level genetic algorithms (BLGAs) and response surfaces have been used to solve the corresponding bi-level programming models. However, the computational costs for BLGAs often increase rapidly with the complexity of lower-level programs, and optimal solution functions sometimes cannot be approximated by response surfaces. This article proposes a new method, namely the optimal solution function approximation by kriging model (OSFAKM), in which kriging models are used to approximate the optimal solution functions. A detailed example demonstrates that OSFAKM can obtain better solutions than BLGAs and response surface-based methods, and at the same time reduce the workload of computation remarkably. Five benchmark problems and a case study of the optimal design of a thin-walled pressure vessel are also presented to illustrate the feasibility and potential of the proposed method for bi-level optimization in engineering design.

Finite burn maneuver modeling for a generalized spacecraft trajectory design and optimization system.

PubMed

Ocampo, Cesar

2004-05-01

The modeling, design, and optimization of finite burn maneuvers for a generalized trajectory design and optimization system is presented. A generalized trajectory design and optimization system is a system that uses a single unified framework that facilitates the modeling and optimization of complex spacecraft trajectories that may operate in complex gravitational force fields, use multiple propulsion systems, and involve multiple spacecraft. The modeling and optimization issues associated with the use of controlled engine burn maneuvers of finite thrust magnitude and duration are presented in the context of designing and optimizing a wide class of finite thrust trajectories. Optimal control theory is used examine the optimization of these maneuvers in arbitrary force fields that are generally position, velocity, mass, and are time dependent. The associated numerical methods used to obtain these solutions involve either, the solution to a system of nonlinear equations, an explicit parameter optimization method, or a hybrid parameter optimization that combines certain aspects of both. The theoretical and numerical methods presented here have been implemented in copernicus, a prototype trajectory design and optimization system under development at the University of Texas at Austin.

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.

Solvability of some partial functional integrodifferential equations with finite delay and optimal controls in Banach spaces.

PubMed

Ezzinbi, Khalil; Ndambomve, Patrice

2016-01-01

In this work, we consider the control system governed by some partial functional integrodifferential equations with finite delay in Banach spaces. We assume that the undelayed part admits a resolvent operator in the sense of Grimmer. Firstly, some suitable conditions are established to guarantee the existence and uniqueness of mild solutions for a broad class of partial functional integrodifferential infinite dimensional control systems. Secondly, it is proved that, under generally mild conditions of cost functional, the associated Lagrange problem has an optimal solution, and that for each optimal solution there is a minimizing sequence of the problem that converges to the optimal solution with respect to the trajectory, the control, and the functional in appropriate topologies. Our results extend and complement many other important results in the literature. Finally, a concrete example of application is given to illustrate the effectiveness of our main results.

CONORBIT: constrained optimization by radial basis function interpolation in trust regions

DOE PAGES

Regis, Rommel G.; Wild, Stefan M.

2016-09-26

Here, this paper presents CONORBIT (CONstrained Optimization by Radial Basis function Interpolation in Trust regions), a derivative-free algorithm for constrained black-box optimization where the objective and constraint functions are computationally expensive. CONORBIT employs a trust-region framework that uses interpolating radial basis function (RBF) models for the objective and constraint functions, and is an extension of the ORBIT algorithm. It uses a small margin for the RBF constraint models to facilitate the generation of feasible iterates, and extensive numerical tests confirm that such a margin is helpful in improving performance. CONORBIT is compared with other algorithms on 27 test problems, amore » chemical process optimization problem, and an automotive application. Numerical results show that CONORBIT performs better than COBYLA, a sequential penalty derivative-free method, an augmented Lagrangian method, a direct search method, and another RBF-based algorithm on the test problems and on the automotive application.« less

An Effective Way to Optimize the Functionality of Graphene-Based Nanocomposite: Use of the Colloidal Mixture of Graphene and Inorganic Nanosheets

NASA Astrophysics Data System (ADS)

Jin, Xiaoyan; Adpakpang, Kanyaporn; Young Kim, In; Mi Oh, Seung; Lee, Nam-Suk; Hwang, Seong-Ju

2015-06-01

The best electrode performance of metal oxide-graphene nanocomposite material for lithium secondary batteries can be achieved by using the colloidal mixture of layered CoO2 and graphene nanosheets as a precursor. The intervention of layered CoO2 nanosheets in-between graphene nanosheets is fairly effective in optimizing the pore and composite structures of the Co3O4-graphene nanocomposite and also in enhancing its electrochemical activity via the depression of interaction between graphene nanosheets. The resulting CoO2 nanosheet-incorporated nanocomposites show much greater discharge capacity of ~1750 mAhg-1 with better cyclability and rate characteristics than does CoO2-free Co3O4-graphene nanocomposite (~1100 mAhg-1). The huge discharge capacity of the present nanocomposite is the largest one among the reported data of cobalt oxide-graphene nanocomposite. Such a remarkable enhancement of electrode performance upon the addition of inorganic nanosheet is also observed for Mn3O4-graphene nanocomposite. The improvement of electrode performance upon the incorporation of inorganic nanosheet is attributable to an improved Li+ ion diffusion, an enhanced mixing between metal oxide and graphene, and the prevention of electrode agglomeration. The present experimental findings underscore an efficient and universal role of the colloidal mixture of graphene and redoxable metal oxide nanosheets as a precursor for improving the electrode functionality of graphene-based nanocomposites.

Variational Calculation of the Ground State of Closed-Shell Nuclei Up to $A$ = 40

DOE PAGES

Lonardoni, Diego; Lovato, Alessandro; Pieper, Steven C.; ...

2017-08-31

Variational calculations of ground-state properties of 4He, 16O and 40Ca are carried out employing realistic phenomenological two- and three-nucleon potentials. The trial wave function includes twoand three-body correlations acting on a product of single-particle determinants. Expectation values are evaluated with a cluster expansion for the spin-isospin dependent correlations considering up to five-body cluster terms. The optimal wave function is obtained by minimizing the energy expectation value over a set of up to 20 parameters by means of a nonlinear optimization library. We present results for the binding energy, charge radius, point density, single-nucleon momentum distribution, charge form factor, and Coulombmore » sum rule. We find that the employed three-nucleon interaction becomes repulsive for A ≥ 16. In 16O the inclusion of such a force provides a better description of the properties of the nucleus. In 40Ca instead, the repulsive behavior of the three-body interaction fails to reproduce experimental data for the charge radius and the charge form factor. We find that the high-momentum region of the momentum distributions, determined by the short-range terms of nuclear correlations, exhibit a universal behavior independent of the particular nucleus. The comparison of the Coulomb sum rules for 4He, 16O, and 40Ca reported in this work will help elucidate in-medium modifications of the nucleon form factors.« less

[Clinical laboratory tests supporting respiratory disease treatment--chairman's introductory remarks].

PubMed

Takai, Daiya

2014-12-01

The symposium consisted of four parts: history of lung function tests, nitric oxide for diagnosis and monitoring of bronchial asthma, radiological and functional changes of the lung in COPD, and combined pulmonary fibrosis and emphysema (CPFE) occasionally showing almost normal results in lung function tests. The history of lung function tests was presented by Dr. Naoko Tojo of the Tokyo Medical and Dental University. Nitric oxide tests in clinical use for diagnosis and monitoring of bronchial asthma were presented by Dr. Hiroyuki Nagase of Teikyo University. Radiological and functional changes of the lung in COPD were presented by Dr. Shigeo Muro of Kyoto University. Clinical features of combined pulmonary fibrosis and emphysema and their associated lung function were presented by Dr. Daiya Takai of the University of Tokyo. I hope that discussing the history of lung function tests until the present was useful for many medical technologists. (Review).

Numerical experience with a class of algorithms for nonlinear optimization using inexact function and gradient information

NASA Technical Reports Server (NTRS)

Carter, Richard G.

1989-01-01

For optimization problems associated with engineering design, parameter estimation, image reconstruction, and other optimization/simulation applications, low accuracy function and gradient values are frequently much less expensive to obtain than high accuracy values. Here, researchers investigate the computational performance of trust region methods for nonlinear optimization when high accuracy evaluations are unavailable or prohibitively expensive, and confirm earlier theoretical predictions when the algorithm is convergent even with relative gradient errors of 0.5 or more. The proper choice of the amount of accuracy to use in function and gradient evaluations can result in orders-of-magnitude savings in computational cost.

Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

NASA Astrophysics Data System (ADS)

Lin, Jian-Fu; Xu, You-Lin; Law, Siu-Seong

2018-05-01

A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

Optimal control of nonlinear continuous-time systems in strict-feedback form.

PubMed

Zargarzadeh, Hassan; Dierks, Travis; Jagannathan, Sarangapani

2015-10-01

This paper proposes a novel optimal tracking control scheme for nonlinear continuous-time systems in strict-feedback form with uncertain dynamics. The optimal tracking problem is transformed into an equivalent optimal regulation problem through a feedforward adaptive control input that is generated by modifying the standard backstepping technique. Subsequently, a neural network-based optimal control scheme is introduced to estimate the cost, or value function, over an infinite horizon for the resulting nonlinear continuous-time systems in affine form when the internal dynamics are unknown. The estimated cost function is then used to obtain the optimal feedback control input; therefore, the overall optimal control input for the nonlinear continuous-time system in strict-feedback form includes the feedforward plus the optimal feedback terms. It is shown that the estimated cost function minimizes the Hamilton-Jacobi-Bellman estimation error in a forward-in-time manner without using any value or policy iterations. Finally, optimal output feedback control is introduced through the design of a suitable observer. Lyapunov theory is utilized to show the overall stability of the proposed schemes without requiring an initial admissible controller. Simulation examples are provided to validate the theoretical results.

Optical Implementation of the Optimal Universal and Phase-Covariant Quantum Cloning Machines

NASA Astrophysics Data System (ADS)

Ye, Liu; Song, Xue-Ke; Yang, Jie; Yang, Qun; Ma, Yang-Cheng

Quantum cloning relates to the security of quantum computation and quantum communication. In this paper, firstly we propose a feasible unified scheme to implement optimal 1 → 2 universal, 1 → 2 asymmetric and symmetric phase-covariant cloning, and 1 → 2 economical phase-covariant quantum cloning machines only via a beam splitter. Then 1 → 3 economical phase-covariant quantum cloning machines also can be realized by adding another beam splitter in context of linear optics. The scheme is based on the interference of two photons on a beam splitter with different splitting ratios for vertical and horizontal polarization components. It is shown that under certain condition, the scheme is feasible by current experimental technology.

Comparison of particle swarm optimization and simulated annealing for locating additional boreholes considering combined variance minimization

NASA Astrophysics Data System (ADS)

Soltani-Mohammadi, Saeed; Safa, Mohammad; Mokhtari, Hadi

2016-10-01

One of the most important stages in complementary exploration is optimal designing the additional drilling pattern or defining the optimum number and location of additional boreholes. Quite a lot research has been carried out in this regard in which for most of the proposed algorithms, kriging variance minimization as a criterion for uncertainty assessment is defined as objective function and the problem could be solved through optimization methods. Although kriging variance implementation is known to have many advantages in objective function definition, it is not sensitive to local variability. As a result, the only factors evaluated for locating the additional boreholes are initial data configuration and variogram model parameters and the effects of local variability are omitted. In this paper, with the goal of considering the local variability in boundaries uncertainty assessment, the application of combined variance is investigated to define the objective function. Thus in order to verify the applicability of the proposed objective function, it is used to locate the additional boreholes in Esfordi phosphate mine through the implementation of metaheuristic optimization methods such as simulated annealing and particle swarm optimization. Comparison of results from the proposed objective function and conventional methods indicates that the new changes imposed on the objective function has caused the algorithm output to be sensitive to the variations of grade, domain's boundaries and the thickness of mineralization domain. The comparison between the results of different optimization algorithms proved that for the presented case the application of particle swarm optimization is more appropriate than simulated annealing.

Functional group interactions with single wall carbon NT studied by ab-initio calculations

NASA Astrophysics Data System (ADS)

Cicero, Giancarlo

2005-03-01

With the goal of designing functionalized nanotube materials, recent AFM measurements have succeeded in determining the force between individual chemical groups an single-wall carbon nanotubes (SWCNT) [1]. In order to rationalize and understand these experimental results, we have performed Density Functional Theory calculations for a number of structural arrangements of model tips functionalized with the same groups as those used experimentally. Our calculations include full geometry optimization of the composite SWCNT/tip system as well as `pulling-out' simulations to compute interaction forces. We considered (14x0), semi- conducting tubes, and AFM tips where modeled by a SiH3CH2-X molecule, with X- representing -CN, -CH3, -NH2 or -CH2OCH2. As X is varied, computed forces reproduce the same trend as that observed experimentally when n-doped SWCNT are considered; significantly different trends are observed for neutral and p-doped tubes. We propose that the polar solvent present in the experimental setup may be responsible for the n-doping of the nanotube suggested by our calculations. This work was performed under the auspices of the U.S. Department of Energy by University of California Lawrence Livermore National Laboratory under contract No. W-7405-Eng-48. [1] M.C. LeMieux et al, preprint

Study of genetic direct search algorithms for function optimization

NASA Technical Reports Server (NTRS)

Zeigler, B. P.

1974-01-01

The results are presented of a study to determine the performance of genetic direct search algorithms in solving function optimization problems arising in the optimal and adaptive control areas. The findings indicate that: (1) genetic algorithms can outperform standard algorithms in multimodal and/or noisy optimization situations, but suffer from lack of gradient exploitation facilities when gradient information can be utilized to guide the search. (2) For large populations, or low dimensional function spaces, mutation is a sufficient operator. However for small populations or high dimensional functions, crossover applied in about equal frequency with mutation is an optimum combination. (3) Complexity, in terms of storage space and running time, is significantly increased when population size is increased or the inversion operator, or the second level adaptation routine is added to the basic structure.

Mesenchymal Stem Cell Therapy for Nerve Regeneration and Immunomodulation after Composite Tissue Allotransplantation

DTIC Science & Technology

2012-02-01

10-1-0927 TITLE: Mesenchymal Stem Cell Therapy for Nerve Regeneration and Immunomodulation after Composite Tissue Allotransplantation...immunosuppression. Bone Marrow Derived Mesenchymal stem cells (BM-MSCs) are pluripotent cells, capable of differentiation along multiple mesenchymal lineages into...As part of implemented transition from University of Pittsburgh to Johns Hopkins University, we optimized our mesenchymal stem cell (MSC) isolation

A University Math Help Centre as a Support Framework for Students, the Instructor, the Course, and the Department

ERIC Educational Resources Information Center

Menz, Petra; Jungic, Veselin

2015-01-01

Among many challenges a math department at a post-secondary institution will most likely be faced with the optimization problem of how best to offer out-of-lecture learning support to several thousand first- and second-year university students enrolled in large math service courses within given spatial, scheduling, financial, technological, and…

Uniformed Services University of the Health Sciences Journal. 2004/5 Edition

DTIC Science & Technology

2005-10-30

Goal 5: STEWARDSHIP: We will protect and enhance the human and physical resources of the University, optimize productivity , promote a...Other OSD- Recognized, Significant Areas of Support and Products Are Provided by USU for the MHS ...... 46-47 - Clinical Support for the Military...Comprehensive Annual Faculty Listing Report ......................................... 51-52 Two Significant OSD Awards Recognize the Multiple Products of USU

Searching for a New Way to Reach Patrons: A Search Engine Optimization Pilot Project at Binghamton University Libraries

ERIC Educational Resources Information Center

Rushton, Erin E.; Kelehan, Martha Daisy; Strong, Marcy A.

2008-01-01

Search engine use is one of the most popular online activities. According to a recent OCLC report, nearly all students start their electronic research using a search engine instead of the library Web site. Instead of viewing search engines as competition, however, librarians at Binghamton University Libraries decided to employ search engine…

Control of functional differential equations to target sets in function space

NASA Technical Reports Server (NTRS)

Banks, H. T.; Kent, G. A.

1971-01-01

Optimal control of systems governed by functional differential equations of retarded and neutral type is considered. Problems with function space initial and terminal manifolds are investigated. Existence of optimal controls, regularity, and bang-bang properties are discussed. Necessary and sufficient conditions are derived, and several solved examples which illustrate the theory are presented.

Generalized slow roll in the unified effective field theory of inflation

NASA Astrophysics Data System (ADS)

Motohashi, Hayato; Hu, Wayne

2017-07-01

We provide a compact and unified treatment of power spectrum observables for the effective field theory (EFT) of inflation with the complete set of operators that lead to second-order equations of motion in metric perturbations in both space and time derivatives, including Horndeski and Gleyzes-Langlois-Piazza-Vernizzi theories. We relate the EFT operators in ADM form to the four additional free functions of time in the scalar and tensor equations. Using the generalized slow-roll formalism, we show that each power spectrum can be described by an integral over a single source that is a function of its respective sound horizon. With this correspondence, existing model independent constraints on the source function can be simply reinterpreted in the more general inflationary context. By expanding these sources around an optimized freeze-out epoch, we also provide characterizations of these spectra in terms of five slow-roll hierarchies whose leading-order forms are compact and accurate as long as EFT coefficients vary only on time scales greater than an e -fold. We also clarify the relationship between the unitary gauge observables employed in the EFT and the comoving gauge observables of the postinflationary universe.

When Art Meets Gardens: Does It Enhance the Benefits? The Nancy Hypothesis of Care for Persons with Alzheimer's Disease.

PubMed

Jonveaux, Thérèse Rivasseau; Fescharek, Reinhard

2018-01-01

The creation of healing gardens for persons with Alzheimer's disease and related diseases (ADRD) offers vast potential. They can play a role in the scaffolding of cognitive disorders, emotional stress, sensory processing, sense of harmony, and appeasement. These effects are achieved through a distributed interplay of psychological functions with the immediate environment and local culture on the one hand, and dialogue on the other. The garden, a natural canvas created by man, shares with art the ability to foster an esthetic sense for which the perception can be measured by functional neurological imaging exploration. Art represents a mediator for the collaborative realization of distributed psychological functions between different individuals. Based on the hypothesis of an optimization of the therapeutic potential of a garden by a design adapted to the neuro-psycho-social and cultural specificities of its users combined with the thoughtful introduction of an artistic dimension, the "art, memory and life" healing garden was created at the University Hospital of Nancy as a prototype for persons with ADRD. The design concept was based on two hypotheses that we formulate herein, discuss their theoretical foundation, and suggest enhanced design for therapeutic gardens based upon our experience.

PI-in-a-box: Intelligent onboard assistance for spaceborne experiments in vestibular physiology

NASA Technical Reports Server (NTRS)

Colombano, Silvano; Young, Laurence; Wogrin, Nancy; Rosenthal, Don

1988-01-01

In construction is a knowledge-based system that will aid astronauts in the performance of vestibular experiments in two ways: it will provide real-time monitoring and control of signals and it will optimize the quality of the data obtained, by helping the mission specialists and payload specialists make decisions that are normally the province of a principal investigator, hence the name PI-in-a-box. An important and desirable side-effect of this tool will be to make the astronauts more productive and better integrated members of the scientific team. The vestibular experiments are planned by Prof. Larry Young of MIT, whose team has already performed similar experiments in Spacelab missions SL-1 and D-1, and has experiments planned for SLS-1 and SLS-2. The knowledge-based system development work, performed in collaboration with MIT, Stanford University, and the NASA-Ames Research Center, addresses six major related functions: (1) signal quality monitoring; (2) fault diagnosis; (3) signal analysis; (4) interesting-case detection; (5) experiment replanning; and (6) integration of all of these functions within a real-time data acquisition environment. Initial prototyping work has been done in functions (1) through (4).

Structural and magnetic properties of turmeric functionalized CoFe2O4 nanocomposite powder

NASA Astrophysics Data System (ADS)

Mehran, E.; Farjami Shayesteh, S.; Sheykhan, M.

2016-10-01

The structural and magnetic properties of the synthesized pure and functionalized CoFe2O4 magnetic nanoparticles (NPs) are studied by analyzing the results from the x-ray diffraction (XRD), transmission electron microscopy (TEM), FT-IR spectroscopy, thermogravimetry (TG), and vibrating sample magnetometer (VSM). To extract the structure and lattice parameters from the XRD analysis results, we first apply the pseudo-Voigt model function to the experimental data obtained from XRD analysis and then the Rietveld algorithm is used in order to optimize the model function to estimate the true intensity values. Our simulated intensities are in good agreement with the experimental peaks, therefore, all structural parameters such as crystallite size and lattice constant are achieved through this simulation. Magnetic analysis reveals that the synthesized functionalized NPs have a saturation magnetization almost equal to that of pure nanoparticles (PNPs). It is also found that the presence of the turmeric causes a small reduction in coercivity of the functionalized NPs in comparison with PNP. Our TGA and FTIR results show that the turmeric is bonded very well to the surface of the NPs. So it can be inferred that a nancomposite (NC) powder of turmeric and nanoparticles is produced. As an application, the anti-arsenic characteristic of turmeric makes the synthesized functionalized NPs or NC powder a good candidate for arsenic removal from polluted industrial waste water. Project supported by the University of Guilan and the Iran Nanotechnology Initiative Council.

SU-F-18C-01: Minimum Detectability Analysis for Comprehensive Sized Based Optimization of Image Quality and Radiation Dose Across CT Protocols

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

Smitherman, C; Chen, B; Samei, E

2014-06-15

Purpose: This work involved a comprehensive modeling of task-based performance of CT across a wide range of protocols. The approach was used for optimization and consistency of dose and image quality within a large multi-vendor clinical facility. Methods: 150 adult protocols from the Duke University Medical Center were grouped into sub-protocols with similar acquisition characteristics. A size based image quality phantom (Duke Mercury Phantom) was imaged using these sub-protocols for a range of clinically relevant doses on two CT manufacturer platforms (Siemens, GE). The images were analyzed to extract task-based image quality metrics such as the Task Transfer Function (TTF),more » Noise Power Spectrum, and Az based on designer nodule task functions. The data were analyzed in terms of the detectability of a lesion size/contrast as a function of dose, patient size, and protocol. A graphical user interface (GUI) was developed to predict image quality and dose to achieve a minimum level of detectability. Results: Image quality trends with variations in dose, patient size, and lesion contrast/size were evaluated and calculated data behaved as predicted. The GUI proved effective to predict the Az values representing radiologist confidence for a targeted lesion, patient size, and dose. As an example, an abdomen pelvis exam for the GE scanner, with a task size/contrast of 5-mm/50-HU, and an Az of 0.9 requires a dose of 4.0, 8.9, and 16.9 mGy for patient diameters of 25, 30, and 35 cm, respectively. For a constant patient diameter of 30 cm, the minimum detected lesion size at those dose levels would be 8.4, 5, and 3.9 mm, respectively. Conclusion: The designed CT protocol optimization platform can be used to evaluate minimum detectability across dose levels and patient diameters. The method can be used to improve individual protocols as well as to improve protocol consistency across CT scanners.« less

Optimization of algorithm of coding of genetic information of Chlamydia

NASA Astrophysics Data System (ADS)

Feodorova, Valentina A.; Ulyanov, Sergey S.; Zaytsev, Sergey S.; Saltykov, Yury V.; Ulianova, Onega V.

2018-04-01

New method of coding of genetic information using coherent optical fields is developed. Universal technique of transformation of nucleotide sequences of bacterial gene into laser speckle pattern is suggested. Reference speckle patterns of the nucleotide sequences of omp1 gene of typical wild strains of Chlamydia trachomatis of genovars D, E, F, G, J and K and Chlamydia psittaci serovar I as well are generated. Algorithm of coding of gene information into speckle pattern is optimized. Fully developed speckles with Gaussian statistics for gene-based speckles have been used as criterion of optimization.

Event-Triggered Distributed Approximate Optimal State and Output Control of Affine Nonlinear Interconnected Systems.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-06-08

This paper presents an approximate optimal distributed control scheme for a known interconnected system composed of input affine nonlinear subsystems using event-triggered state and output feedback via a novel hybrid learning scheme. First, the cost function for the overall system is redefined as the sum of cost functions of individual subsystems. A distributed optimal control policy for the interconnected system is developed using the optimal value function of each subsystem. To generate the optimal control policy, forward-in-time, neural networks are employed to reconstruct the unknown optimal value function at each subsystem online. In order to retain the advantages of event-triggered feedback for an adaptive optimal controller, a novel hybrid learning scheme is proposed to reduce the convergence time for the learning algorithm. The development is based on the observation that, in the event-triggered feedback, the sampling instants are dynamic and results in variable interevent time. To relax the requirement of entire state measurements, an extended nonlinear observer is designed at each subsystem to recover the system internal states from the measurable feedback. Using a Lyapunov-based analysis, it is demonstrated that the system states and the observer errors remain locally uniformly ultimately bounded and the control policy converges to a neighborhood of the optimal policy. Simulation results are presented to demonstrate the performance of the developed controller.

Challenges with the implementation of an Integrated Disease Surveillance and Response (IDSR) system: systematic review of the lessons learned.

PubMed

Phalkey, Revati K; Yamamoto, Shelby; Awate, Pradip; Marx, Michael

2015-02-01

Despite a realistic strategy and availability of resources, multiple challenges still overwhelm countries grappling with the challenges of communicable disease surveillance. The Integrated Disease Surveillance and Response (IDSR) strategy is by far the most pragmatic strategy in resource-poor settings. The objective of this study was to systematically review and document the lessons learned and the challenges identified with the implementation of the IDSR in low- and middle-income countries and to identify the main barriers that contribute to its sub-optimal functioning. A systematic review of literature published in English using Web of Knowledge, PubMed, and databases of the World Health Organization (WHO) and the Centers for Disease Control (CDC) between 1998 and 2012 was undertaken. Additionally, manual reference and grey literature searches were conducted. Citations describing core and support functions or the quality attributes of the IDSR as described by WHO and CDC were included in the review. Thirty-three assessment studies met the inclusion criteria. IDSR strategy has been best adopted and implemented in the WHO-AFRO region. Although significant progress is made in overcoming the challenges identified with vertical disease surveillance strategies, gaps still exist. Mixed challenges with core and support IDSR functions were observed across countries. Main issues identified include non-sustainable financial resources, lack of co-ordination, inadequate training and turnover of peripheral staff, erratic feedback, inadequate supervision from the next level, weak laboratory capacities coupled with unavailability of job aids (case definitions/reporting formats), and poor availability of communication and transport systems particularly at the periphery. Best outcomes in core functions and system attributes were reported when support surveillance functions performed optimally. Apart from technical and technological issues, human resources and the health care system structures that receive the IDSR determine its output. The challenges identified with IDSR implementation are largely 'systemic'. IDSR will best benefit from skill-based training of personnel and strengthening of the support surveillance functions alongside health care infrastructures at the district level. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2013; all rights reserved.

On algorithmic optimization of histogramming functions for GEM systems

NASA Astrophysics Data System (ADS)

Krawczyk, Rafał D.; Czarski, Tomasz; Kolasinski, Piotr; Poźniak, Krzysztof T.; Linczuk, Maciej; Byszuk, Adrian; Chernyshova, Maryna; Juszczyk, Bartlomiej; Kasprowicz, Grzegorz; Wojenski, Andrzej; Zabolotny, Wojciech

2015-09-01

This article concerns optimization methods for data analysis for the X-ray GEM detector system. The offline analysis of collected samples was optimized for MATLAB computations. Compiled functions in C language were used with MEX library. Significant speedup was received for both ordering-preprocessing and for histogramming of samples. Utilized techniques with obtained results are presented.

On optimizing the treatment of exchange perturbations

NASA Technical Reports Server (NTRS)

Hirschfelder, J. O.; Chipman, D. M.

1972-01-01

A method using the zeroth plus first order wave functions, obtained by optimizing the basic equation used in exchange perturbation treatments, is utilized in an attempt to determine the exact energy and wave function in the exchange process. Attempts to determine the first order perturbation solution by optimizing the sum of the first and second order energies were unsuccessful.

An objective function exploiting suboptimal solutions in metabolic networks

PubMed Central

2013-01-01

Background Flux Balance Analysis is a theoretically elegant, computationally efficient, genome-scale approach to predicting biochemical reaction fluxes. Yet FBA models exhibit persistent mathematical degeneracy that generally limits their predictive power. Results We propose a novel objective function for cellular metabolism that accounts for and exploits degeneracy in the metabolic network to improve flux predictions. In our model, regulation drives metabolism toward a region of flux space that allows nearly optimal growth. Metabolic mutants deviate minimally from this region, a function represented mathematically as a convex cone. Near-optimal flux configurations within this region are considered equally plausible and not subject to further optimizing regulation. Consistent with relaxed regulation near optimality, we find that the size of the near-optimal region predicts flux variability under experimental perturbation. Conclusion Accounting for suboptimal solutions can improve the predictive power of metabolic FBA models. Because fluctuations of enzyme and metabolite levels are inevitable, tolerance for suboptimality may support a functionally robust metabolic network. PMID:24088221

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.

An Empirical Comparison of Seven Iterative and Evolutionary Function Optimization Heuristics

NASA Technical Reports Server (NTRS)

Baluja, Shumeet

1995-01-01

This report is a repository of the results obtained from a large scale empirical comparison of seven iterative and evolution-based optimization heuristics. Twenty-seven static optimization problems, spanning six sets of problem classes which are commonly explored in genetic algorithm literature, are examined. The problem sets include job-shop scheduling, traveling salesman, knapsack, binpacking, neural network weight optimization, and standard numerical optimization. The search spaces in these problems range from 2368 to 22040. The results indicate that using genetic algorithms for the optimization of static functions does not yield a benefit, in terms of the final answer obtained, over simpler optimization heuristics. Descriptions of the algorithms tested and the encodings of the problems are described in detail for reproducibility.

The universal function in color dipole model

NASA Astrophysics Data System (ADS)

Jalilian, Z.; Boroun, G. R.

2017-10-01

In this work we review color dipole model and recall properties of the saturation and geometrical scaling in this model. Our primary aim is determining the exact universal function in terms of the introduced scaling variable in different distance than the saturation radius. With inserting the mass in calculation we compute numerically the contribution of heavy productions in small x from the total structure function by the fraction of universal functions and show the geometrical scaling is established due to our scaling variable in this study.

Measuring effectiveness of a university by a parallel network DEA model

NASA Astrophysics Data System (ADS)

Kashim, Rosmaini; Kasim, Maznah Mat; Rahman, Rosshairy Abd

2017-11-01

Universities contribute significantly to the development of human capital and socio-economic improvement of a country. Due to that, Malaysian universities carried out various initiatives to improve their performance. Most studies have used the Data Envelopment Analysis (DEA) model to measure efficiency rather than effectiveness, even though, the measurement of effectiveness is important to realize how effective a university in achieving its ultimate goals. A university system has two major functions, namely teaching and research and every function has different resources based on its emphasis. Therefore, a university is actually structured as a parallel production system with its overall effectiveness is the aggregated effectiveness of teaching and research. Hence, this paper is proposing a parallel network DEA model to measure the effectiveness of a university. This model includes internal operations of both teaching and research functions into account in computing the effectiveness of a university system. In literature, the graduate and the number of program offered are defined as the outputs, then, the employed graduates and the numbers of programs accredited from professional bodies are considered as the outcomes for measuring the teaching effectiveness. Amount of grants is regarded as the output of research, while the different quality of publications considered as the outcomes of research. A system is considered effective if only all functions are effective. This model has been tested using a hypothetical set of data consisting of 14 faculties at a public university in Malaysia. The results show that none of the faculties is relatively effective for the overall performance. Three faculties are effective in teaching and two faculties are effective in research. The potential applications of the parallel network DEA model allow the top management of a university to identify weaknesses in any functions in their universities and take rational steps for improvement.

Impact of the ion transportome of chloroplasts on the optimization of photosynthesis.

PubMed

Szabò, Ildikò; Spetea, Cornelia

2017-06-01

Ions play fundamental roles in all living cells, and their gradients are often essential to fuel transport, regulate enzyme activities, and transduce energy within cells. Regulation of their homeostasis is essential for cell metabolism. Recent results indicate that modulation of ion fluxes might also represent a useful strategy to regulate one of the most important physiological processes taking place in chloroplasts, photosynthesis. Photosynthesis is highly regulated, due to its unique role as a cellular engine for growth in the light. Controlling the balance between ATP and NADPH synthesis is a critical task, and availability of these molecules can limit the overall photosynthetic yield. Photosynthetic organisms optimize photosynthesis in low light, where excitation energy limits CO2 fixation, and minimize photo-oxidative damage in high light by dissipating excess photons. Despite extensive studies of these phenomena, the mechanism governing light utilization in plants is still poorly understood. In this review, we provide an update of the recently identified chloroplast-located ion channels and transporters whose function impacts photosynthetic efficiency in plants. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Multiobjective Particle Swarm Optimization for the optimal design of photovoltaic grid-connected systems

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

Kornelakis, Aris

2010-12-15

Particle Swarm Optimization (PSO) is a highly efficient evolutionary optimization algorithm. In this paper a multiobjective optimization algorithm based on PSO applied to the optimal design of photovoltaic grid-connected systems (PVGCSs) is presented. The proposed methodology intends to suggest the optimal number of system devices and the optimal PV module installation details, such that the economic and environmental benefits achieved during the system's operational lifetime period are both maximized. The objective function describing the economic benefit of the proposed optimization process is the lifetime system's total net profit which is calculated according to the method of the Net Present Valuemore » (NPV). The second objective function, which corresponds to the environmental benefit, equals to the pollutant gas emissions avoided due to the use of the PVGCS. The optimization's decision variables are the optimal number of the PV modules, the PV modules optimal tilt angle, the optimal placement of the PV modules within the available installation area and the optimal distribution of the PV modules among the DC/AC converters. (author)« less

Real Estate Site Selection: An Application of Artificial Intelligence for Military Retail Facilities

DTIC Science & Technology

2006-09-01

Information and Spatial Analysis (SCGISA), University of Sheffield. Kotler , P. (1984). Marketing Management: Analysis, Planning, and Control...Spatial Distribution of Retail Sales. Journal of Real Estate Finance and Economics, Vol. 31 Iss. 1, 53. Lilien, G., & Kotler , P. (1983). Marketing ...commissaries). The current business model for military retail facilities may not be optimized based upon current trends market data. Optimizing

Optimization of Nanoscale Zero-Valent Iron for the Remediation of Groundwater Contaminants

DTIC Science & Technology

2012-03-22

the polyelectrolyte’s adsorption to the nZVI surface via physisorption. In contrast, studies on CMC and polyacrylic acid (PAA) stabilization of nZVI...OPTIMIZATION OF NANOSCALE ZERO‒VALENT IRON FOR THE REMEDIATION OF GROUNDWATER CONTAMINANTS THESIS...Andrew W.E. McPherson, Second Lieutenant, USAF AFIT/GES/ENV/12-M01 DEPARTMENT OF THE AIR FORCE AIR UNIVERSITY AIR FORCE INSTITUTE OF

Control of functional differential equations with function space boundary conditions.

NASA Technical Reports Server (NTRS)

Banks, H. T.

1972-01-01

The results of various authors dealing with problems involving functional differential equations with terminal conditions in function space are reviewed. The review includes not only very recent results, but also some little known results of Soviet mathematicians prior to 1970. Particular attention is given to results concerning controllability, existence of optimal controls, and necessary and sufficient conditions for optimality.

Optimization of locations of diffusion spots in indoor optical wireless local area networks

NASA Astrophysics Data System (ADS)

Eltokhey, Mahmoud W.; Mahmoud, K. R.; Ghassemlooy, Zabih; Obayya, Salah S. A.

2018-03-01

In this paper, we present a novel optimization of the locations of the diffusion spots in indoor optical wireless local area networks, based on the central force optimization (CFO) scheme. The users' performance uniformity is addressed by using the CFO algorithm, and adopting different objective function's configurations, while considering maximization and minimization of the signal to noise ratio and the delay spread, respectively. We also investigate the effect of varying the objective function's weights on the system and the users' performance as part of the adaptation process. The results show that the proposed objective function configuration-based optimization procedure offers an improvement of 65% in the standard deviation of individual receivers' performance.

Optimization of two-photon wave function in parametric down conversion by adaptive optics control of the pump radiation.

PubMed

Minozzi, M; Bonora, S; Sergienko, A V; Vallone, G; Villoresi, P

2013-02-15

We present an efficient method for optimizing the spatial profile of entangled-photon wave function produced in a spontaneous parametric down conversion process. A deformable mirror that modifies a wavefront of a 404 nm CW diode laser pump interacting with a nonlinear β-barium borate type-I crystal effectively controls the profile of the joint biphoton function. The use of a feedback signal extracted from the biphoton coincidence rate is used to achieve the optimal wavefront shape. The optimization of the two-photon coupling into two, single spatial modes for correlated detection is used for a practical demonstration of this physical principle.

An optimized method to calculate error correction capability of tool influence function in frequency domain

NASA Astrophysics Data System (ADS)

Wang, Jia; Hou, Xi; Wan, Yongjian; Shi, Chunyan

2017-10-01

An optimized method to calculate error correction capability of tool influence function (TIF) in certain polishing conditions will be proposed based on smoothing spectral function. The basic mathematical model for this method will be established in theory. A set of polishing experimental data with rigid conformal tool is used to validate the optimized method. The calculated results can quantitatively indicate error correction capability of TIF for different spatial frequency errors in certain polishing conditions. The comparative analysis with previous method shows that the optimized method is simpler in form and can get the same accuracy results with less calculating time in contrast to previous method.

Multiobjective optimization techniques for structural design

NASA Technical Reports Server (NTRS)

Rao, S. S.

1984-01-01

The multiobjective programming techniques are important in the design of complex structural systems whose quality depends generally on a number of different and often conflicting objective functions which cannot be combined into a single design objective. The applicability of multiobjective optimization techniques is studied with reference to simple design problems. Specifically, the parameter optimization of a cantilever beam with a tip mass and a three-degree-of-freedom vabration isolation system and the trajectory optimization of a cantilever beam are considered. The solutions of these multicriteria design problems are attempted by using global criterion, utility function, game theory, goal programming, goal attainment, bounded objective function, and lexicographic methods. It has been observed that the game theory approach required the maximum computational effort, but it yielded better optimum solutions with proper balance of the various objective functions in all the cases.

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. These approaches are implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

A new approach of optimal control for a class of continuous-time chaotic systems by an online ADP algorithm

NASA Astrophysics Data System (ADS)

Song, Rui-Zhuo; Xiao, Wen-Dong; Wei, Qing-Lai

2014-05-01

We develop an online adaptive dynamic programming (ADP) based optimal control scheme for continuous-time chaotic systems. The idea is to use the ADP algorithm to obtain the optimal control input that makes the performance index function reach an optimum. The expression of the performance index function for the chaotic system is first presented. The online ADP algorithm is presented to achieve optimal control. In the ADP structure, neural networks are used to construct a critic network and an action network, which can obtain an approximate performance index function and the control input, respectively. It is proven that the critic parameter error dynamics and the closed-loop chaotic systems are uniformly ultimately bounded exponentially. Our simulation results illustrate the performance of the established optimal control method.

Machining fixture layout optimization using particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Dou, Jianping; Wang, Xingsong; Wang, Lei

2011-05-01

Optimization of fixture layout (locator and clamp locations) is critical to reduce geometric error of the workpiece during machining process. In this paper, the application of particle swarm optimization (PSO) algorithm is presented to minimize the workpiece deformation in the machining region. A PSO based approach is developed to optimize fixture layout through integrating ANSYS parametric design language (APDL) of finite element analysis to compute the objective function for a given fixture layout. Particle library approach is used to decrease the total computation time. The computational experiment of 2D case shows that the numbers of function evaluations are decreased about 96%. Case study illustrates the effectiveness and efficiency of the PSO based optimization approach.

Motor planning under temporal uncertainty is suboptimal when the gain function is asymmetric

PubMed Central

Ota, Keiji; Shinya, Masahiro; Kudo, Kazutoshi

2015-01-01

For optimal action planning, the gain/loss associated with actions and the variability in motor output should both be considered. A number of studies make conflicting claims about the optimality of human action planning but cannot be reconciled due to their use of different movements and gain/loss functions. The disagreement is possibly because of differences in the experimental design and differences in the energetic cost of participant motor effort. We used a coincident timing task, which requires decision making with constant energetic cost, to test the optimality of participant's timing strategies under four configurations of the gain function. We compared participant strategies to an optimal timing strategy calculated from a Bayesian model that maximizes the expected gain. We found suboptimal timing strategies under two configurations of the gain function characterized by asymmetry, in which higher gain is associated with higher risk of zero gain. Participants showed a risk-seeking strategy by responding closer than optimal to the time of onset/offset of zero gain. Meanwhile, there was good agreement of the model with actual performance under two configurations of the gain function characterized by symmetry. Our findings show that human ability to make decisions that must reflect uncertainty in one's own motor output has limits that depend on the configuration of the gain function. PMID:26236227

Neural networks: What non-linearity to choose

NASA Technical Reports Server (NTRS)

Kreinovich, Vladik YA.; Quintana, Chris

1991-01-01

Neural networks are now one of the most successful learning formalisms. Neurons transform inputs (x(sub 1),...,x(sub n)) into an output f(w(sub 1)x(sub 1) + ... + w(sub n)x(sub n)), where f is a non-linear function and w, are adjustable weights. What f to choose? Usually the logistic function is chosen, but sometimes the use of different functions improves the practical efficiency of the network. The problem of choosing f as a mathematical optimization problem is formulated and solved under different optimality criteria. As a result, a list of functions f that are optimal under these criteria are determined. This list includes both the functions that were empirically proved to be the best for some problems, and some new functions that may be worth trying.

Distributed Constrained Optimization with Semicoordinate Transformations

NASA Technical Reports Server (NTRS)

Macready, William; Wolpert, David

2006-01-01

Recent work has shown how information theory extends conventional full-rationality game theory to allow bounded rational agents. The associated mathematical framework can be used to solve constrained optimization problems. This is done by translating the problem into an iterated game, where each agent controls a different variable of the problem, so that the joint probability distribution across the agents moves gives an expected value of the objective function. The dynamics of the agents is designed to minimize a Lagrangian function of that joint distribution. Here we illustrate how the updating of the Lagrange parameters in the Lagrangian is a form of automated annealing, which focuses the joint distribution more and more tightly about the joint moves that optimize the objective function. We then investigate the use of "semicoordinate" variable transformations. These separate the joint state of the agents from the variables of the optimization problem, with the two connected by an onto mapping. We present experiments illustrating the ability of such transformations to facilitate optimization. We focus on the special kind of transformation in which the statistically independent states of the agents induces a mixture distribution over the optimization variables. Computer experiment illustrate this for &sat constraint satisfaction problems and for unconstrained minimization of NK functions.

Concurrent topology optimization for minimization of total mass considering load-carrying capabilities and thermal insulation simultaneously

NASA Astrophysics Data System (ADS)

Long, Kai; Wang, Xuan; Gu, Xianguang

2017-09-01

The present work introduces a novel concurrent optimization formulation to meet the requirements of lightweight design and various constraints simultaneously. Nodal displacement of macrostructure and effective thermal conductivity of microstructure are regarded as the constraint functions, which means taking into account both the load-carrying capabilities and the thermal insulation properties. The effective properties of porous material derived from numerical homogenization are used for macrostructural analysis. Meanwhile, displacement vectors of macrostructures from original and adjoint load cases are used for sensitivity analysis of the microstructure. Design variables in the form of reciprocal functions of relative densities are introduced and used for linearization of the constraint function. The objective function of total mass is approximately expressed by the second order Taylor series expansion. Then, the proposed concurrent optimization problem is solved using a sequential quadratic programming algorithm, by splitting into a series of sub-problems in the form of the quadratic program. Finally, several numerical examples are presented to validate the effectiveness of the proposed optimization method. The various effects including initial designs, prescribed limits of nodal displacement, and effective thermal conductivity on optimized designs are also investigated. An amount of optimized macrostructures and their corresponding microstructures are achieved.

Variation of parameters using Battin's universal functions

NASA Astrophysics Data System (ADS)

Burton, James R., III; Melton, Robert G.

This paper presents a variation of parameters analysis, suitable for use in situations involving small perturbations to the two-body problem, using Battin's universal functions. Unlike the universal variable formulation, this approach avoids the need to switch among different functional representations if the orbit transitions from elliptical, through parabolic, to hyperbolic state, making it attractive for use in simulating low-thrust trajectories ascending to escape or capturing into orbit.

On the Training Model of China's Local Normal University Students during the Transitional Period from the Perspective of Happiness Management

ERIC Educational Resources Information Center

Weiwei, Huang

2016-01-01

As a theory based on the hypothesis of "happy man" about human nature, happiness management plays a significant guiding role in the optimization of the training model of local Chinese normal university students during the transitional period. Under the guidance of this theory, China should adhere to the people-oriented principle,…

Uniformed Services University of the Health Sciences Journal 2003 Edition

DTIC Science & Technology

2004-08-18

practice nurses for the MHS. The Joint Meritorious Unit Award was presented to Doctor Zimble in 2000 and officially recognized the multiple products ...of the University, optimize productivity , promote a sense of family and community, while emphasizing flexibility in response...Alumni and their Achievements, Five Other OSD- Recognized, Significant Areas of Support and Products Are Provided by USU for the MHS ...... 48-49

Androgen Deprivation Therapy and Cognitive Impairment

DTIC Science & Technology

2017-08-01

development of new strategies to optimize the physical and mental health of men with prostate cancer and improve the quality of life and well-being...CONTRACTING ORGANIZATION: Western University of Health Sciences Pomona, CA 91766 REPORT DATE: August 2017 TYPE OF REPORT: Annual PREPARED FOR...NAME(S) AND ADDRESS(ES) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER Western University of Health Sciences 309 East Second Street

Numerical Optimization.

DTIC Science & Technology

1988-01-01

TASK AREA & WORK UNIT NUMBERS Dipartimento di Matematica -G.--iattelnuoz .’ Universita di Roma "La Sapienze" rlnlRr% Pnmaq (Tt-al’g) I$. CONTROLLING...guaranteed. 3. Adminisrtrative actions The following investigators are working on the contract: (i) Francesco Zirilli Dipartimento di Matematica "G...Castelnuovo" Universiti di Roma "La Sapienza" 00185 Romna (Italy) (ii) Filippo Aluffi-Pentini Dipartimento di Matematica Universiti di Barn 80125 Bari (Italy

Cloud Computing Solutions for the Marine Corps: An Architecture to Support Expeditionary Logistics

DTIC Science & Technology

2013-09-01

reform IT financial , acquisition, and contracting practices (Takai, 2012). The second step is to optimize data center consolidation . Kundra (2010...the U.S. Government. IRB Protocol number ____N/A____. 12a. DISTRIBUTION / AVAILABILITY STATEMENT Approved for public release;distribution is...USB universal serial bus USMCELC United States Marine Corps Expeditionary Logistics Cloud UUNS urgent universal needs statement xix VA volt

Direct position determination for digital modulation signals based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Yu, Wan-Ting; Yu, Hong-yi; Du, Jian-Ping; Wang, Ding

2018-04-01

The Direct Position Determination (DPD) algorithm has been demonstrated to achieve a better accuracy with known signal waveforms. However, the signal waveform is difficult to be completely known in the actual positioning process. To solve the problem, we proposed a DPD method for digital modulation signals based on improved particle swarm optimization algorithm. First, a DPD model is established for known modulation signals and a cost function is obtained on symbol estimation. Second, as the optimization of the cost function is a nonlinear integer optimization problem, an improved Particle Swarm Optimization (PSO) algorithm is considered for the optimal symbol search. Simulations are carried out to show the higher position accuracy of the proposed DPD method and the convergence of the fitness function under different inertia weight and population size. On the one hand, the proposed algorithm can take full advantage of the signal feature to improve the positioning accuracy. On the other hand, the improved PSO algorithm can improve the efficiency of symbol search by nearly one hundred times to achieve a global optimal solution.

Fuzzy Adaptive Decentralized Optimal Control for Strict Feedback Nonlinear Large-Scale Systems.

PubMed

Sun, Kangkang; Sui, Shuai; Tong, Shaocheng

2018-04-01

This paper considers the optimal decentralized fuzzy adaptive control design problem for a class of interconnected large-scale nonlinear systems in strict feedback form and with unknown nonlinear functions. The fuzzy logic systems are introduced to learn the unknown dynamics and cost functions, respectively, and a state estimator is developed. By applying the state estimator and the backstepping recursive design algorithm, a decentralized feedforward controller is established. By using the backstepping decentralized feedforward control scheme, the considered interconnected large-scale nonlinear system in strict feedback form is changed into an equivalent affine large-scale nonlinear system. Subsequently, an optimal decentralized fuzzy adaptive control scheme is constructed. The whole optimal decentralized fuzzy adaptive controller is composed of a decentralized feedforward control and an optimal decentralized control. It is proved that the developed optimal decentralized controller can ensure that all the variables of the control system are uniformly ultimately bounded, and the cost functions are the smallest. Two simulation examples are provided to illustrate the validity of the developed optimal decentralized fuzzy adaptive control scheme.

Admitting the Inadmissible: Adjoint Formulation for Incomplete Cost Functionals in Aerodynamic Optimization

NASA Technical Reports Server (NTRS)

Arian, Eyal; Salas, Manuel D.

1997-01-01

We derive the adjoint equations for problems in aerodynamic optimization which are improperly considered as "inadmissible." For example, a cost functional which depends on the density, rather than on the pressure, is considered "inadmissible" for an optimization problem governed by the Euler equations. We show that for such problems additional terms should be included in the Lagrangian functional when deriving the adjoint equations. These terms are obtained from the restriction of the interior PDE to the control surface. Demonstrations of the explicit derivation of the adjoint equations for "inadmissible" cost functionals are given for the potential, Euler, and Navier-Stokes equations.

Optimization of the coherence function estimation for multi-core central processing unit

NASA Astrophysics Data System (ADS)

Cheremnov, A. G.; Faerman, V. A.; Avramchuk, V. S.

2017-02-01

The paper considers use of parallel processing on multi-core central processing unit for optimization of the coherence function evaluation arising in digital signal processing. Coherence function along with other methods of spectral analysis is commonly used for vibration diagnosis of rotating machinery and its particular nodes. An algorithm is given for the function evaluation for signals represented with digital samples. The algorithm is analyzed for its software implementation and computational problems. Optimization measures are described, including algorithmic, architecture and compiler optimization, their results are assessed for multi-core processors from different manufacturers. Thus, speeding-up of the parallel execution with respect to sequential execution was studied and results are presented for Intel Core i7-4720HQ и AMD FX-9590 processors. The results show comparatively high efficiency of the optimization measures taken. In particular, acceleration indicators and average CPU utilization have been significantly improved, showing high degree of parallelism of the constructed calculating functions. The developed software underwent state registration and will be used as a part of a software and hardware solution for rotating machinery fault diagnosis and pipeline leak location with acoustic correlation method.

General equations for optimal selection of diagnostic image acquisition parameters in clinical X-ray imaging.

PubMed

Zheng, Xiaoming

2017-12-01

The purpose of this work was to examine the effects of relationship functions between diagnostic image quality and radiation dose on the governing equations for image acquisition parameter variations in X-ray imaging. Various equations were derived for the optimal selection of peak kilovoltage (kVp) and exposure parameter (milliAmpere second, mAs) in computed tomography (CT), computed radiography (CR), and direct digital radiography. Logistic, logarithmic, and linear functions were employed to establish the relationship between radiation dose and diagnostic image quality. The radiation dose to the patient, as a function of image acquisition parameters (kVp, mAs) and patient size (d), was used in radiation dose and image quality optimization. Both logistic and logarithmic functions resulted in the same governing equation for optimal selection of image acquisition parameters using a dose efficiency index. For image quality as a linear function of radiation dose, the same governing equation was derived from the linear relationship. The general equations should be used in guiding clinical X-ray imaging through optimal selection of image acquisition parameters. The radiation dose to the patient could be reduced from current levels in medical X-ray imaging.

Case studies on optimization problems in MATLAB and COMSOL multiphysics by means of the livelink

NASA Astrophysics Data System (ADS)

Ozana, Stepan; Pies, Martin; Docekal, Tomas

2016-06-01

LiveLink for COMSOL is a tool that integrates COMSOL Multiphysics with MATLAB to extend one's modeling with scripting programming in the MATLAB environment. It allows user to utilize the full power of MATLAB and its toolboxes in preprocessing, model manipulation, and post processing. At first, the head script launches COMSOL with MATLAB and defines initial value of all parameters, refers to the objective function J described in the objective function and creates and runs the defined optimization task. Once the task is launches, the COMSOL model is being called in the iteration loop (from MATLAB environment by use of API interface), changing defined optimization parameters so that the objective function is minimized, using fmincon function to find a local or global minimum of constrained linear or nonlinear multivariable function. Once the minimum is found, it returns exit flag, terminates optimization and returns the optimized values of the parameters. The cooperation with MATLAB via LiveLink enhances a powerful computational environment with complex multiphysics simulations. The paper will introduce using of the LiveLink for COMSOL for chosen case studies in the field of technical cybernetics and bioengineering.

Stochastic Methods for Aircraft Design

NASA Technical Reports Server (NTRS)

Pelz, Richard B.; Ogot, Madara

1998-01-01

The global stochastic optimization method, simulated annealing (SA), was adapted and applied to various problems in aircraft design. The research was aimed at overcoming the problem of finding an optimal design in a space with multiple minima and roughness ubiquitous to numerically generated nonlinear objective functions. SA was modified to reduce the number of objective function evaluations for an optimal design, historically the main criticism of stochastic methods. SA was applied to many CFD/MDO problems including: low sonic-boom bodies, minimum drag on supersonic fore-bodies, minimum drag on supersonic aeroelastic fore-bodies, minimum drag on HSCT aeroelastic wings, FLOPS preliminary design code, another preliminary aircraft design study with vortex lattice aerodynamics, HSR complete aircraft aerodynamics. In every case, SA provided a simple, robust and reliable optimization method which found optimal designs in order 100 objective function evaluations. Perhaps most importantly, from this academic/industrial project, technology has been successfully transferred; this method is the method of choice for optimization problems at Northrop Grumman.

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

PubMed

Liu, Qingshan; Wang, Jun

2011-04-01

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

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.

Reduction of shock induced noise in imperfectly expanded supersonic jets using convex optimization

NASA Astrophysics Data System (ADS)

Adhikari, Sam

2007-11-01

Imperfectly expanded jets generate screech noise. The imbalance between the backpressure and the exit pressure of the imperfectly expanded jets produce shock cells and expansion or compression waves from the nozzle. The instability waves and the shock cells interact to generate the screech sound. The mathematical model consists of cylindrical coordinate based full Navier-Stokes equations and large-eddy-simulation turbulence modeling. Analytical and computational analysis of the three-dimensional helical effects provide a model that relates several parameters with shock cell patterns, screech frequency and distribution of shock generation locations. Convex optimization techniques minimize the shock cell patterns and the instability waves. The objective functions are (convex) quadratic and the constraint functions are affine. In the quadratic optimization programs, minimization of the quadratic functions over a set of polyhedrons provides the optimal result. Various industry standard methods like regression analysis, distance between polyhedra, bounding variance, Markowitz optimization, and second order cone programming is used for Quadratic Optimization.

Prediction and standard error estimation for a finite universe total when a stratum is not sampled

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

Wright, T.

1994-01-01

In the context of a universe of trucks operating in the United States in 1990, this paper presents statistical methodology for estimating a finite universe total on a second occasion when a part of the universe is sampled and the remainder of the universe is not sampled. Prediction is used to compensate for the lack of data from the unsampled portion of the universe. The sample is assumed to be a subsample of an earlier sample where stratification is used on both occasions before sample selection. Accounting for births and deaths in the universe between the two points in time,more » the detailed sampling plan, estimator, standard error, and optimal sample allocation, are presented with a focus on the second occasion. If prior auxiliary information is available, the methodology is also applicable to a first occasion.« less

Optimal design application on the advanced aeroelastic rotor blade

NASA Technical Reports Server (NTRS)

Wei, F. S.; Jones, R.

1985-01-01

The vibration and performance optimization procedure using regression analysis was successfully applied to an advanced aeroelastic blade design study. The major advantage of this regression technique is that multiple optimizations can be performed to evaluate the effects of various objective functions and constraint functions. The data bases obtained from the rotorcraft flight simulation program C81 and Myklestad mode shape program are analytically determined as a function of each design variable. This approach has been verified for various blade radial ballast weight locations and blade planforms. This method can also be utilized to ascertain the effect of a particular cost function which is composed of several objective functions with different weighting factors for various mission requirements without any additional effort.