Efficient optimization of electrostatic interactions between biomolecules.

Energy Technology Data Exchange (ETDEWEB)

Bardhan, J. P.; Altman, M. D.; White, J. K.; Tidor, B.; Mathematics and Computer Science; MIT

2007-01-01

We present a PDE-constrained approach to optimizing the electrostatic interactions between two biomolecules. These interactions play important roles in the determination of binding affinity and specificity, and are therefore of significant interest when designing a ligand molecule to bind tightly to a receptor. Using a popular continuum model and physically reasonable assumptions, the electrostatic component of the binding free energy is a convex, quadratic function of the ligand charge distribution. Traditional optimization methods require exhaustive pre-computation, and the expense has precluded a full exploration of the promise of electrostatic optimization in biomolecule analysis and design. In this paper we describe an approach in which the electrostatic simulations and optimization problem are solved simultaneously; unlike many PDE- constrained optimization frameworks, the proposed method does not incorporate the PDE as a set of equality constraints. This co-optimization approach can be used by itself to solve unconstrained problems or those with linear equality constraints, or in conjunction with primal-dual interior point methods to solve problems with inequality constraints. Model problems demonstrate that the co-optimization method is computationally efficient and can be used to solve realistic problems.

Design, optimization, and biological evaluation of novel keto-benzimidazoles as potent and selective inhibitors of phosphodiesterase 10A (PDE10A).

Science.gov (United States)

Hu, Essa; Kunz, Roxanne K; Chen, Ning; Rumfelt, Shannon; Siegmund, Aaron; Andrews, Kristin; Chmait, Samer; Zhao, Sharon; Davis, Carl; Chen, Hang; Lester-Zeiner, Dianna; Ma, Ji; Biorn, Christopher; Shi, Jianxia; Porter, Amy; Treanor, James; Allen, Jennifer R

2013-11-14

Our development of PDE10A inhibitors began with an HTS screening hit (1) that exhibited both high p-glycoprotein (P-gp) efflux ratios in rat and human and poor metabolic stability. On the basis of cocrystal structure of 1 in human PDE10A enzyme, we designed a novel keto-benzimidazole 26 with comparable PDE10A potency devoid of efflux liabilities. On target in vivo coverage of PDE10A in rat brain was assessed using our previously reported LC-MS/MS receptor occupancy (RO) technology. Compound 26 achieved 55% RO of PDE10A at 30 mg/kg po and covered PDE10A receptors in rat brain in a dose-dependent manner. Cocrystal structure of 26 in PDE10A confirmed the binding mode of the novel scaffold. Further optimization resulted in the identification of keto-benzimidazole 34, which showed an increased in vivo efficacy of 57% RO in rats at 10 mg/kg po and an improved in vivo rat clearance and oral bioavailability.

PDE9A, PDE10A, and PDE11A expression in rat trigeminovascular pain signalling system

DEFF Research Database (Denmark)

Kruse, Lars S; Møller, Morten; Tibaek, Maiken

2009-01-01

as neocortex and cerebellar cortex. Real-time PCR and Western blotting showed that PDE9A, PDE10A and PDE11A are expressed in components of the rat trigeminovascular pain signalling system including middle cerebral artery, basilar artery, meninges, trigeminal ganglion and spinal trigeminal nucleus. Aorta...... and mesenteric artery as well as cerebral neocortex and cerebellar cortex also showed expression of PDE9A, PDE10A and PDE11A. Immunohistochemistry revealed that PDE9A, PDE10A and PDE11A are localised in the cytosol of nerve cell bodies of the trigeminal ganglion. We here present, for the first time...

Collocation methods for uncertainty quanti cation in PDE models with random data

KAUST Repository

Nobile, Fabio

2014-01-06

In this talk we consider Partial Differential Equations (PDEs) whose input data are modeled as random fields to account for their intrinsic variability or our lack of knowledge. After parametrizing the input random fields by finitely many independent random variables, we exploit the high regularity of the solution of the PDE as a function of the input random variables and consider sparse polynomial approximations in probability (Polynomial Chaos expansion) by collocation methods. We first address interpolatory approximations where the PDE is solved on a sparse grid of Gauss points in the probability space and the solutions thus obtained interpolated by multivariate polynomials. We present recent results on optimized sparse grids in which the selection of points is based on a knapsack approach and relies on sharp estimates of the decay of the coefficients of the polynomial chaos expansion of the solution. Secondly, we consider regression approaches where the PDE is evaluated on randomly chosen points in the probability space and a polynomial approximation constructed by the least square method. We present recent theoretical results on the stability and optimality of the approximation under suitable conditions between the number of sampling points and the dimension of the polynomial space. In particular, we show that for uniform random variables, the number of sampling point has to scale quadratically with the dimension of the polynomial space to maintain the stability and optimality of the approximation. Numerical results show that such condition is sharp in the monovariate case but seems to be over-constraining in higher dimensions. The regression technique seems therefore to be attractive in higher dimensions.

Constrained optimization via simulation models for new product innovation

Science.gov (United States)

Pujowidianto, Nugroho A.

2017-11-01

We consider the problem of constrained optimization where the decision makers aim to optimize the primary performance measure while constraining the secondary performance measures. This paper provides a brief overview of stochastically constrained optimization via discrete event simulation. Most review papers tend to be methodology-based. This review attempts to be problem-based as decision makers may have already decided on the problem formulation. We consider constrained optimization models as there are usually constraints on secondary performance measures as trade-off in new product development. It starts by laying out different possible methods and the reasons using constrained optimization via simulation models. It is then followed by the review of different simulation optimization approach to address constrained optimization depending on the number of decision variables, the type of constraints, and the risk preferences of the decision makers in handling uncertainties.

Convergence acceleration for time-independent first-order PDE using optimal PNB-approximations

Energy Technology Data Exchange (ETDEWEB)

Holmgren, S.; Branden, H. [Uppsala Univ. (Sweden)

1996-12-31

We consider solving time-independent (steady-state) flow problems in 2D or 3D governed by hyperbolic or {open_quotes}almost hyperbolic{close_quotes} systems of partial differential equations (PDE). Examples of such PDE are the Euler and the Navier-Stokes equations. The PDE is discretized using a finite difference or finite volume scheme with arbitrary order of accuracy. If the matrix B describes the discretized differential operator and u denotes the approximate solution, the discrete problem is given by a large system of equations.

Security constrained optimal power flow by modern optimization tools

African Journals Online (AJOL)

Security constrained optimal power flow by modern optimization tools. ... International Journal of Engineering, Science and Technology ... If you would like more information about how to print, save, and work with PDFs, Highwire Press ...

A PDE-constrained SQP algorithm for optical tomography based on the frequency-domain equation of radiative transfer

International Nuclear Information System (INIS)

Kim, Hyun Keol; Hielscher, Andreas H

2009-01-01

It is well acknowledged that transport-theory-based reconstruction algorithm can provide the most accurate reconstruction results especially when small tissue volumes or high absorbing media are considered. However, these codes have a high computational burden and are often only slowly converging. Therefore, methods that accelerate the computation are highly desirable. To this end, we introduce in this work a partial-differential-equation (PDE) constrained approach to optical tomography that makes use of an all-at-once reduced Hessian sequential quadratic programming (rSQP) scheme. The proposed scheme treats the forward and inverse variables independently, which makes it possible to update the radiation intensities and the optical coefficients simultaneously by solving the forward and inverse problems, all at once. We evaluate the performance of the proposed scheme with numerical and experimental data, and find that the rSQP scheme can reduce the computation time by a factor of 10–25, as compared to the commonly employed limited memory BFGS method. At the same time accuracy and robustness even in the presence of noise are not compromised

Coevolutionary particle swarm optimization using Gaussian distribution for solving constrained optimization problems.

Science.gov (United States)

Krohling, Renato A; Coelho, Leandro dos Santos

2006-12-01

In this correspondence, an approach based on coevolutionary particle swarm optimization to solve constrained optimization problems formulated as min-max problems is presented. In standard or canonical particle swarm optimization (PSO), a uniform probability distribution is used to generate random numbers for the accelerating coefficients of the local and global terms. We propose a Gaussian probability distribution to generate the accelerating coefficients of PSO. Two populations of PSO using Gaussian distribution are used on the optimization algorithm that is tested on a suite of well-known benchmark constrained optimization problems. Results have been compared with the canonical PSO (constriction factor) and with a coevolutionary genetic algorithm. Simulation results show the suitability of the proposed algorithm in terms of effectiveness and robustness.

Accelerated Optimization in the PDE Framework: Formulations for the Active Contour Case

KAUST Repository

Yezzi, Anthony; Sundaramoorthi, Ganesh

2017-01-01

Following the seminal work of Nesterov, accelerated optimization methods have been used to powerfully boost the performance of first-order, gradient-based parameter estimation in scenarios where second-order optimization strategies are either inapplicable or impractical. Not only does accelerated gradient descent converge considerably faster than traditional gradient descent, but it also performs a more robust local search of the parameter space by initially overshooting and then oscillating back as it settles into a final configuration, thereby selecting only local minimizers with a basis of attraction large enough to contain the initial overshoot. This behavior has made accelerated and stochastic gradient search methods particularly popular within the machine learning community. In their recent PNAS 2016 paper, Wibisono, Wilson, and Jordan demonstrate how a broad class of accelerated schemes can be cast in a variational framework formulated around the Bregman divergence, leading to continuum limit ODE's. We show how their formulation may be further extended to infinite dimension manifolds (starting here with the geometric space of curves and surfaces) by substituting the Bregman divergence with inner products on the tangent space and explicitly introducing a distributed mass model which evolves in conjunction with the object of interest during the optimization process. The co-evolving mass model, which is introduced purely for the sake of endowing the optimization with helpful dynamics, also links the resulting class of accelerated PDE based optimization schemes to fluid dynamical formulations of optimal mass transport.

Accelerated Optimization in the PDE Framework: Formulations for the Active Contour Case

KAUST Repository

Yezzi, Anthony

2017-11-27

Following the seminal work of Nesterov, accelerated optimization methods have been used to powerfully boost the performance of first-order, gradient-based parameter estimation in scenarios where second-order optimization strategies are either inapplicable or impractical. Not only does accelerated gradient descent converge considerably faster than traditional gradient descent, but it also performs a more robust local search of the parameter space by initially overshooting and then oscillating back as it settles into a final configuration, thereby selecting only local minimizers with a basis of attraction large enough to contain the initial overshoot. This behavior has made accelerated and stochastic gradient search methods particularly popular within the machine learning community. In their recent PNAS 2016 paper, Wibisono, Wilson, and Jordan demonstrate how a broad class of accelerated schemes can be cast in a variational framework formulated around the Bregman divergence, leading to continuum limit ODE\\'s. We show how their formulation may be further extended to infinite dimension manifolds (starting here with the geometric space of curves and surfaces) by substituting the Bregman divergence with inner products on the tangent space and explicitly introducing a distributed mass model which evolves in conjunction with the object of interest during the optimization process. The co-evolving mass model, which is introduced purely for the sake of endowing the optimization with helpful dynamics, also links the resulting class of accelerated PDE based optimization schemes to fluid dynamical formulations of optimal mass transport.

Boundary Control of Linear Uncertain 1-D Parabolic PDE Using Approximate Dynamic Programming.

Science.gov (United States)

Talaei, Behzad; Jagannathan, Sarangapani; Singler, John

2018-04-01

This paper develops a near optimal boundary control method for distributed parameter systems governed by uncertain linear 1-D parabolic partial differential equations (PDE) by using approximate dynamic programming. A quadratic surface integral is proposed to express the optimal cost functional for the infinite-dimensional state space. Accordingly, the Hamilton-Jacobi-Bellman (HJB) equation is formulated in the infinite-dimensional domain without using any model reduction. Subsequently, a neural network identifier is developed to estimate the unknown spatially varying coefficient in PDE dynamics. Novel tuning law is proposed to guarantee the boundedness of identifier approximation error in the PDE domain. A radial basis network (RBN) is subsequently proposed to generate an approximate solution for the optimal surface kernel function online. The tuning law for near optimal RBN weights is created, such that the HJB equation error is minimized while the dynamics are identified and closed-loop system remains stable. Ultimate boundedness (UB) of the closed-loop system is verified by using the Lyapunov theory. The performance of the proposed controller is successfully confirmed by simulation on an unstable diffusion-reaction process.

Constrained optimization of test intervals using a steady-state genetic algorithm

International Nuclear Information System (INIS)

Martorell, S.; Carlos, S.; Sanchez, A.; Serradell, V.

2000-01-01

There is a growing interest from both the regulatory authorities and the nuclear industry to stimulate the use of Probabilistic Risk Analysis (PRA) for risk-informed applications at Nuclear Power Plants (NPPs). Nowadays, special attention is being paid on analyzing plant-specific changes to Test Intervals (TIs) within the Technical Specifications (TSs) of NPPs and it seems to be a consensus on the need of making these requirements more risk-effective and less costly. Resource versus risk-control effectiveness principles formally enters in optimization problems. This paper presents an approach for using the PRA models in conducting the constrained optimization of TIs based on a steady-state genetic algorithm (SSGA) where the cost or the burden is to be minimized while the risk or performance is constrained to be at a given level, or vice versa. The paper encompasses first with the problem formulation, where the objective function and constraints that apply in the constrained optimization of TIs based on risk and cost models at system level are derived. Next, the foundation of the optimizer is given, which is derived by customizing a SSGA in order to allow optimizing TIs under constraints. Also, a case study is performed using this approach, which shows the benefits of adopting both PRA models and genetic algorithms, in particular for the constrained optimization of TIs, although it is also expected a great benefit of using this approach to solve other engineering optimization problems. However, care must be taken in using genetic algorithms in constrained optimization problems as it is concluded in this paper

Neuroevolutionary Constrained Optimization for Content Creation

DEFF Research Database (Denmark)

Liapis, Antonios; Yannakakis, Georgios N.; Togelius, Julian

2011-01-01

and thruster types and topologies) independently of game physics and steering strategies. According to the proposed framework, the designer picks a set of requirements for the spaceship that a constrained optimizer attempts to satisfy. The constraint satisfaction approach followed is based on neuroevolution...... and survival tasks and are also visually appealing....

Quasicanonical structure of optimal control in constrained discrete systems

Science.gov (United States)

Sieniutycz, S.

2003-06-01

This paper considers discrete processes governed by difference rather than differential equations for the state transformation. The basic question asked is if and when Hamiltonian canonical structures are possible in optimal discrete systems. Considering constrained discrete control, general optimization algorithms are derived that constitute suitable theoretical and computational tools when evaluating extremum properties of constrained physical models. The mathematical basis of the general theory is the Bellman method of dynamic programming (DP) and its extension in the form of the so-called Carathéodory-Boltyanski (CB) stage criterion which allows a variation of the terminal state that is otherwise fixed in the Bellman's method. Two relatively unknown, powerful optimization algorithms are obtained: an unconventional discrete formalism of optimization based on a Hamiltonian for multistage systems with unconstrained intervals of holdup time, and the time interval constrained extension of the formalism. These results are general; namely, one arrives at: the discrete canonical Hamilton equations, maximum principles, and (at the continuous limit of processes with free intervals of time) the classical Hamilton-Jacobi theory along with all basic results of variational calculus. Vast spectrum of applications of the theory is briefly discussed.

Phase-Field Relaxation of Topology Optimization with Local Stress Constraints

DEFF Research Database (Denmark)

Stainko, Roman; Burger, Martin

2006-01-01

inequality constraints. We discretize the problem by finite elements and solve the arising finite-dimensional programming problems by a primal-dual interior point method. Numerical experiments for problems with local stress constraints based on different criteria indicate the success and robustness......We introduce a new relaxation scheme for structural topology optimization problems with local stress constraints based on a phase-field method. In the basic formulation we have a PDE-constrained optimization problem, where the finite element and design analysis are solved simultaneously...

Effective Teaching of Economics: A Constrained Optimization Problem?

Science.gov (United States)

Hultberg, Patrik T.; Calonge, David Santandreu

2017-01-01

One of the fundamental tenets of economics is that decisions are often the result of optimization problems subject to resource constraints. Consumers optimize utility, subject to constraints imposed by prices and income. As economics faculty, instructors attempt to maximize student learning while being constrained by their own and students'…

Direct interaction of the inhibitory gamma-subunit of Rod cGMP phosphodiesterase (PDE6) with the PDE6 GAFa domains.

Science.gov (United States)

Muradov, Khakim G; Granovsky, Alexey E; Schey, Kevin L; Artemyev, Nikolai O

2002-03-26

Retinal rod and cone cGMP phosphodiesterases (PDE6 family) function as the effector enzyme in the vertebrate visual transduction cascade. The activity of PDE6 catalytic subunits is controlled by the Pgamma-subunits. In addition to the inhibition of cGMP hydrolysis at the catalytic sites, Pgamma is known to stimulate a noncatalytic binding of cGMP to the regulatory GAFa-GAFb domains of PDE6. The latter role of Pgamma has been attributed to its polycationic region. To elucidate the structural basis for the regulation of cGMP binding to the GAF domains of PDE6, a photoexcitable peptide probe corresponding to the polycationic region of Pgamma, Pgamma-21-45, was specifically cross-linked to rod PDE6alphabeta. The site of Pgamma-21-45 cross-linking was localized to Met138Gly139 within the PDE6alpha GAFa domain using mass spectrometric analysis. Chimeras between PDE5 and cone PDE6alpha', containing GAFa and/or GAFb domains of PDE6alpha' have been generated to probe a potential role of the GAFb domains in binding to Pgamma. Analysis of the inhibition of the PDE5/PDE6alpha' chimeras by Pgamma supported the role of PDE6 GAFa but not GAFb domains in the interaction with Pgamma. Our results suggest that a direct binding of the polycationic region of Pgamma to the GAFa domains of PDE6 may lead to a stabilization of the noncatalytic cGMP-binding sites.

Selection of magnetorheological brake types via optimal design considering maximum torque and constrained volume

International Nuclear Information System (INIS)

Nguyen, Q H; Choi, S B

2012-01-01

This research focuses on optimal design of different types of magnetorheological brakes (MRBs), from which an optimal selection of MRB types is identified. In the optimization, common types of MRB such as disc-type, drum-type, hybrid-types, and T-shaped type are considered. The optimization problem is to find the optimal value of significant geometric dimensions of the MRB that can produce a maximum braking torque. The MRB is constrained in a cylindrical volume of a specific radius and length. After a brief description of the configuration of MRB types, the braking torques of the MRBs are derived based on the Herschel–Bulkley model of the MR fluid. The optimal design of MRBs constrained in a specific cylindrical volume is then analysed. The objective of the optimization is to maximize the braking torque while the torque ratio (the ratio of maximum braking torque and the zero-field friction torque) is constrained to be greater than a certain value. A finite element analysis integrated with an optimization tool is employed to obtain optimal solutions of the MRBs. Optimal solutions of MRBs constrained in different volumes are obtained based on the proposed optimization procedure. From the results, discussions on the optimal selection of MRB types depending on constrained volumes are given. (paper)

Thermally-Constrained Fuel-Optimal ISS Maneuvers

Science.gov (United States)

Bhatt, Sagar; Svecz, Andrew; Alaniz, Abran; Jang, Jiann-Woei; Nguyen, Louis; Spanos, Pol

2015-01-01

Optimal Propellant Maneuvers (OPMs) are now being used to rotate the International Space Station (ISS) and have saved hundreds of kilograms of propellant over the last two years. The savings are achieved by commanding the ISS to follow a pre-planned attitude trajectory optimized to take advantage of environmental torques. The trajectory is obtained by solving an optimal control problem. Prior to use on orbit, OPM trajectories are screened to ensure a static sun vector (SSV) does not occur during the maneuver. The SSV is an indicator that the ISS hardware temperatures may exceed thermal limits, causing damage to the components. In this paper, thermally-constrained fuel-optimal trajectories are presented that avoid an SSV and can be used throughout the year while still reducing propellant consumption significantly.

Composite Differential Evolution with Modified Oracle Penalty Method for Constrained Optimization Problems

Directory of Open Access Journals (Sweden)

Minggang Dong

2014-01-01

Full Text Available Motivated by recent advancements in differential evolution and constraints handling methods, this paper presents a novel modified oracle penalty function-based composite differential evolution (MOCoDE for constrained optimization problems (COPs. More specifically, the original oracle penalty function approach is modified so as to satisfy the optimization criterion of COPs; then the modified oracle penalty function is incorporated in composite DE. Furthermore, in order to solve more complex COPs with discrete, integer, or binary variables, a discrete variable handling technique is introduced into MOCoDE to solve complex COPs with mix variables. This method is assessed on eleven constrained optimization benchmark functions and seven well-studied engineering problems in real life. Experimental results demonstrate that MOCoDE achieves competitive performance with respect to some other state-of-the-art approaches in constrained optimization evolutionary algorithms. Moreover, the strengths of the proposed method include few parameters and its ease of implementation, rendering it applicable to real life. Therefore, MOCoDE can be an efficient alternative to solving constrained optimization problems.

Biomolecular surface construction by PDE transform.

Science.gov (United States)

Zheng, Qiong; Yang, Siyang; Wei, Guo-Wei

2012-03-01

This work proposes a new framework for the surface generation based on the partial differential equation (PDE) transform. The PDE transform has recently been introduced as a general approach for the mode decomposition of images, signals, and data. It relies on the use of arbitrarily high-order PDEs to achieve the time-frequency localization, control the spectral distribution, and regulate the spatial resolution. The present work provides a new variational derivation of high-order PDE transforms. The fast Fourier transform is utilized to accomplish the PDE transform so as to avoid stringent stability constraints in solving high-order PDEs. As a consequence, the time integration of high-order PDEs can be done efficiently with the fast Fourier transform. The present approach is validated with a variety of test examples in two-dimensional and three-dimensional settings. We explore the impact of the PDE transform parameters, such as the PDE order and propagation time, on the quality of resulting surfaces. Additionally, we utilize a set of 10 proteins to compare the computational efficiency of the present surface generation method and a standard approach in Cartesian meshes. Moreover, we analyze the present method by examining some benchmark indicators of biomolecular surface, that is, surface area, surface-enclosed volume, solvation free energy, and surface electrostatic potential. A test set of 13 protein molecules is used in the present investigation. The electrostatic analysis is carried out via the Poisson-Boltzmann equation model. To further demonstrate the utility of the present PDE transform-based surface method, we solve the Poisson-Nernst-Planck equations with a PDE transform surface of a protein. Second-order convergence is observed for the electrostatic potential and concentrations. Finally, to test the capability and efficiency of the present PDE transform-based surface generation method, we apply it to the construction of an excessively large biomolecule, a

Optimization of an implicit constrained multi-physics system for motor wheels of electric vehicle

International Nuclear Information System (INIS)

Lei, Fei; Du, Bin; Liu, Xin; Xie, Xiaoping; Chai, Tian

2016-01-01

In this paper, implicit constrained multi-physics model of a motor wheel for an electric vehicle is built and then optimized. A novel optimization approach is proposed to solve the compliance problem between implicit constraints and stochastic global optimization. Firstly, multi-physics model of motor wheel is built from the theories of structural mechanics, electromagnetism and thermal physics. Then, implicit constraints are applied from the vehicle performances and magnetic characteristics. Implicit constrained optimization is carried out by a series of unconstrained optimization and verifications. In practice, sequentially updated subspaces are designed to completely substitute the original design space in local areas. In each subspace, a solution is obtained and is then verified by the implicit constraints. Optimal solutions which satisfy the implicit constraints are accepted as final candidates. The final global optimal solution is optimized from those candidates. Discussions are carried out to discover the differences between optimal solutions with unconstrained problem and different implicit constrained problems. Results show that the implicit constraints have significant influences on the optimal solution and the proposed approach is effective in finding the optimals. - Highlights: • An implicit constrained multi-physics model is built for sizing a motor wheel. • Vehicle dynamic performances are applied as implicit constraints for nonlinear system. • An efficient novel optimization is proposed to explore the constrained design space. • The motor wheel is optimized to achieve maximum efficiency on vehicle dynamics. • Influences of implicit constraints on vehicle performances are compared and analyzed.

Chance-constrained optimization of demand response to price signals

DEFF Research Database (Denmark)

Dorini, Gianluca Fabio; Pinson, Pierre; Madsen, Henrik

2013-01-01

within a recursive least squares (RLS) framework using data measurable at the grid level, in an adaptive fashion. Optimal price signals are generated by embedding the FIR models within a chance-constrained optimization framework. The objective is to keep the price signal as unchanged as possible from...

Bidirectional Dynamic Diversity Evolutionary Algorithm for Constrained Optimization

Directory of Open Access Journals (Sweden)

Weishang Gao

2013-01-01

Full Text Available Evolutionary algorithms (EAs were shown to be effective for complex constrained optimization problems. However, inflexible exploration-exploitation and improper penalty in EAs with penalty function would lead to losing the global optimum nearby or on the constrained boundary. To determine an appropriate penalty coefficient is also difficult in most studies. In this paper, we propose a bidirectional dynamic diversity evolutionary algorithm (Bi-DDEA with multiagents guiding exploration-exploitation through local extrema to the global optimum in suitable steps. In Bi-DDEA potential advantage is detected by three kinds of agents. The scale and the density of agents will change dynamically according to the emerging of potential optimal area, which play an important role of flexible exploration-exploitation. Meanwhile, a novel double optimum estimation strategy with objective fitness and penalty fitness is suggested to compute, respectively, the dominance trend of agents in feasible region and forbidden region. This bidirectional evolving with multiagents can not only effectively avoid the problem of determining penalty coefficient but also quickly converge to the global optimum nearby or on the constrained boundary. By examining the rapidity and veracity of Bi-DDEA across benchmark functions, the proposed method is shown to be effective.

Solving large-scale PDE-constrained Bayesian inverse problems with Riemann manifold Hamiltonian Monte Carlo

Science.gov (United States)

Bui-Thanh, T.; Girolami, M.

2014-11-01

We consider the Riemann manifold Hamiltonian Monte Carlo (RMHMC) method for solving statistical inverse problems governed by partial differential equations (PDEs). The Bayesian framework is employed to cast the inverse problem into the task of statistical inference whose solution is the posterior distribution in infinite dimensional parameter space conditional upon observation data and Gaussian prior measure. We discretize both the likelihood and the prior using the H1-conforming finite element method together with a matrix transfer technique. The power of the RMHMC method is that it exploits the geometric structure induced by the PDE constraints of the underlying inverse problem. Consequently, each RMHMC posterior sample is almost uncorrelated/independent from the others providing statistically efficient Markov chain simulation. However this statistical efficiency comes at a computational cost. This motivates us to consider computationally more efficient strategies for RMHMC. At the heart of our construction is the fact that for Gaussian error structures the Fisher information matrix coincides with the Gauss-Newton Hessian. We exploit this fact in considering a computationally simplified RMHMC method combining state-of-the-art adjoint techniques and the superiority of the RMHMC method. Specifically, we first form the Gauss-Newton Hessian at the maximum a posteriori point and then use it as a fixed constant metric tensor throughout RMHMC simulation. This eliminates the need for the computationally costly differential geometric Christoffel symbols, which in turn greatly reduces computational effort at a corresponding loss of sampling efficiency. We further reduce the cost of forming the Fisher information matrix by using a low rank approximation via a randomized singular value decomposition technique. This is efficient since a small number of Hessian-vector products are required. The Hessian-vector product in turn requires only two extra PDE solves using the adjoint

Optimal Power Constrained Distributed Detection over a Noisy Multiaccess Channel

Directory of Open Access Journals (Sweden)

Zhiwen Hu

2015-01-01

Full Text Available The problem of optimal power constrained distributed detection over a noisy multiaccess channel (MAC is addressed. Under local power constraints, we define the transformation function for sensor to realize the mapping from local decision to transmitted waveform. The deflection coefficient maximization (DCM is used to optimize the performance of power constrained fusion system. Using optimality conditions, we derive the closed-form solution to the considered problem. Monte Carlo simulations are carried out to evaluate the performance of the proposed new method. Simulation results show that the proposed method could significantly improve the detection performance of the fusion system with low signal-to-noise ratio (SNR. We also show that the proposed new method has a robust detection performance for broad SNR region.

Solving Optimal Control Problem of Monodomain Model Using Hybrid Conjugate Gradient Methods

Directory of Open Access Journals (Sweden)

Kin Wei Ng

2012-01-01

Full Text Available We present the numerical solutions for the PDE-constrained optimization problem arising in cardiac electrophysiology, that is, the optimal control problem of monodomain model. The optimal control problem of monodomain model is a nonlinear optimization problem that is constrained by the monodomain model. The monodomain model consists of a parabolic partial differential equation coupled to a system of nonlinear ordinary differential equations, which has been widely used for simulating cardiac electrical activity. Our control objective is to dampen the excitation wavefront using optimal applied extracellular current. Two hybrid conjugate gradient methods are employed for computing the optimal applied extracellular current, namely, the Hestenes-Stiefel-Dai-Yuan (HS-DY method and the Liu-Storey-Conjugate-Descent (LS-CD method. Our experiment results show that the excitation wavefronts are successfully dampened out when these methods are used. Our experiment results also show that the hybrid conjugate gradient methods are superior to the classical conjugate gradient methods when Armijo line search is used.

A One-Layer Recurrent Neural Network for Constrained Complex-Variable Convex Optimization.

Science.gov (United States)

Qin, Sitian; Feng, Jiqiang; Song, Jiahui; Wen, Xingnan; Xu, Chen

2018-03-01

In this paper, based on calculus and penalty method, a one-layer recurrent neural network is proposed for solving constrained complex-variable convex optimization. It is proved that for any initial point from a given domain, the state of the proposed neural network reaches the feasible region in finite time and converges to an optimal solution of the constrained complex-variable convex optimization finally. In contrast to existing neural networks for complex-variable convex optimization, the proposed neural network has a lower model complexity and better convergence. Some numerical examples and application are presented to substantiate the effectiveness of the proposed neural network.

A multi-objective improved teaching-learning based optimization algorithm for unconstrained and constrained optimization problems

Directory of Open Access Journals (Sweden)

R. Venkata Rao

2014-01-01

Full Text Available The present work proposes a multi-objective improved teaching-learning based optimization (MO-ITLBO algorithm for unconstrained and constrained multi-objective function optimization. The MO-ITLBO algorithm is the improved version of basic teaching-learning based optimization (TLBO algorithm adapted for multi-objective problems. The basic TLBO algorithm is improved to enhance its exploration and exploitation capacities by introducing the concept of number of teachers, adaptive teaching factor, tutorial training and self-motivated learning. The MO-ITLBO algorithm uses a grid-based approach to adaptively assess the non-dominated solutions (i.e. Pareto front maintained in an external archive. The performance of the MO-ITLBO algorithm is assessed by implementing it on unconstrained and constrained test problems proposed for the Congress on Evolutionary Computation 2009 (CEC 2009 competition. The performance assessment is done by using the inverted generational distance (IGD measure. The IGD measures obtained by using the MO-ITLBO algorithm are compared with the IGD measures of the other state-of-the-art algorithms available in the literature. Finally, Lexicographic ordering is used to assess the overall performance of competitive algorithms. Results have shown that the proposed MO-ITLBO algorithm has obtained the 1st rank in the optimization of unconstrained test functions and the 3rd rank in the optimization of constrained test functions.

Volume-constrained optimization of magnetorheological and electrorheological valves and dampers

Science.gov (United States)

Rosenfeld, Nicholas C.; Wereley, Norman M.

2004-12-01

This paper presents a case study of magnetorheological (MR) and electrorheological (ER) valve design within a constrained cylindrical volume. The primary purpose of this study is to establish general design guidelines for volume-constrained MR valves. Additionally, this study compares the performance of volume-constrained MR valves against similarly constrained ER valves. Starting from basic design guidelines for an MR valve, a method for constructing candidate volume-constrained valve geometries is presented. A magnetic FEM program is then used to evaluate the magnetic properties of the candidate valves. An optimized MR valve is chosen by evaluating non-dimensional parameters describing the candidate valves' damping performance. A derivation of the non-dimensional damping coefficient for valves with both active and passive volumes is presented to allow comparison of valves with differing proportions of active and passive volumes. The performance of the optimized MR valve is then compared to that of a geometrically similar ER valve using both analytical and numerical techniques. An analytical equation relating the damping performances of geometrically similar MR and ER valves in as a function of fluid yield stresses and relative active fluid volume, and numerical calculations are provided to calculate each valve's damping performance and to validate the analytical calculations.

Solution for state constrained optimal control problems applied to power split control for hybrid vehicles

NARCIS (Netherlands)

Keulen, van T.A.C.; Gillot, J.; Jager, de A.G.; Steinbuch, M.

2014-01-01

This paper presents a numerical solution for scalar state constrained optimal control problems. The algorithm rewrites the constrained optimal control problem as a sequence of unconstrained optimal control problems which can be solved recursively as a two point boundary value problem. The solution

A one-layer recurrent neural network for constrained nonsmooth invex optimization.

Science.gov (United States)

Li, Guocheng; Yan, Zheng; Wang, Jun

2014-02-01

Invexity is an important notion in nonconvex optimization. In this paper, a one-layer recurrent neural network is proposed for solving constrained nonsmooth invex optimization problems, designed based on an exact penalty function method. It is proved herein that any state of the proposed neural network is globally convergent to the optimal solution set of constrained invex optimization problems, with a sufficiently large penalty parameter. In addition, any neural state is globally convergent to the unique optimal solution, provided that the objective function and constraint functions are pseudoconvex. Moreover, any neural state is globally convergent to the feasible region in finite time and stays there thereafter. The lower bounds of the penalty parameter and convergence time are also estimated. Two numerical examples are provided to illustrate the performances of the proposed neural network. Copyright © 2013 Elsevier Ltd. All rights reserved.

Collocation methods for uncertainty quanti cation in PDE models with random data

KAUST Repository

Nobile, Fabio

2014-01-01

address interpolatory approximations where the PDE is solved on a sparse grid of Gauss points in the probability space and the solutions thus obtained interpolated by multivariate polynomials. We present recent results on optimized sparse grids in which

Optimal Control of Partially Miscible Two-Phase Flow with Applications to Subsurface CO2 Sequestration

KAUST Repository

Simon, Moritz; Ulbrich, Michael

2013-01-01

Motivated by applications in subsurface CO2 sequestration, we investigate constrained optimal control problems with partially miscible two-phase flow in porous media. The objective is, e.g., to maximize the amount of trapped CO2 in an underground reservoir after a fixed period of CO2 injection, where the time-dependent injection rates in multiple wells are used as control parameters. We describe the governing two-phase two-component Darcy flow PDE system and formulate the optimal control problem. For the discretization we use a variant of the BOX method, a locally conservative control-volume FE method. The timestep-wise Lagrangian of the control problem is implemented as a functional in the PDE toolbox Sundance, which is part of the HPC software Trilinos. The resulting MPI parallelized Sundance state and adjoint solvers are linked to the interior point optimization package IPOPT. Finally, we present some numerical results in a heterogeneous model reservoir.

New Exact Penalty Functions for Nonlinear Constrained Optimization Problems

Directory of Open Access Journals (Sweden)

Bingzhuang Liu

2014-01-01

Full Text Available For two kinds of nonlinear constrained optimization problems, we propose two simple penalty functions, respectively, by augmenting the dimension of the primal problem with a variable that controls the weight of the penalty terms. Both of the penalty functions enjoy improved smoothness. Under mild conditions, it can be proved that our penalty functions are both exact in the sense that local minimizers of the associated penalty problem are precisely the local minimizers of the original constrained problem.

Constrained multi-objective optimization of storage ring lattices

Science.gov (United States)

Husain, Riyasat; Ghodke, A. D.

2018-03-01

The storage ring lattice optimization is a class of constrained multi-objective optimization problem, where in addition to low beam emittance, a large dynamic aperture for good injection efficiency and improved beam lifetime are also desirable. The convergence and computation times are of great concern for the optimization algorithms, as various objectives are to be optimized and a number of accelerator parameters to be varied over a large span with several constraints. In this paper, a study of storage ring lattice optimization using differential evolution is presented. The optimization results are compared with two most widely used optimization techniques in accelerators-genetic algorithm and particle swarm optimization. It is found that the differential evolution produces a better Pareto optimal front in reasonable computation time between two conflicting objectives-beam emittance and dispersion function in the straight section. The differential evolution was used, extensively, for the optimization of linear and nonlinear lattices of Indus-2 for exploring various operational modes within the magnet power supply capabilities.

Adaptive Multi-Agent Systems for Constrained Optimization

Science.gov (United States)

Macready, William; Bieniawski, Stefan; Wolpert, David H.

2004-01-01

Product Distribution (PD) theory is a new framework for analyzing and controlling distributed systems. Here we demonstrate its use for distributed stochastic optimization. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. The updating of the Lagrange parameters in the Lagrangian can be viewed as a form of automated annealing, that focuses the MAS more and more on the optimal pure strategy. This provides a simple way to map the solution of any constrained optimization problem onto the equilibrium of a Multi-Agent System (MAS). We present computer experiments involving both the Queen s problem and K-SAT validating the predictions of PD theory and its use for off-the-shelf distributed adaptive optimization.

Stress-constrained topology optimization for compliant mechanism design

DEFF Research Database (Denmark)

de Leon, Daniel M.; Alexandersen, Joe; Jun, Jun S.

2015-01-01

This article presents an application of stress-constrained topology optimization to compliant mechanism design. An output displacement maximization formulation is used, together with the SIMP approach and a projection method to ensure convergence to nearly discrete designs. The maximum stress...... is approximated using a normalized version of the commonly-used p-norm of the effective von Mises stresses. The usual problems associated with topology optimization for compliant mechanism design: one-node and/or intermediate density hinges are alleviated by the stress constraint. However, it is also shown...

Metal artifact reduction in x-ray computed tomography (CT) by constrained optimization

International Nuclear Information System (INIS)

Zhang Xiaomeng; Wang Jing; Xing Lei

2011-01-01

Purpose: The streak artifacts caused by metal implants have long been recognized as a problem that limits various applications of CT imaging. In this work, the authors propose an iterative metal artifact reduction algorithm based on constrained optimization. Methods: After the shape and location of metal objects in the image domain is determined automatically by the binary metal identification algorithm and the segmentation of ''metal shadows'' in projection domain is done, constrained optimization is used for image reconstruction. It minimizes a predefined function that reflects a priori knowledge of the image, subject to the constraint that the estimated projection data are within a specified tolerance of the available metal-shadow-excluded projection data, with image non-negativity enforced. The minimization problem is solved through the alternation of projection-onto-convex-sets and the steepest gradient descent of the objective function. The constrained optimization algorithm is evaluated with a penalized smoothness objective. Results: The study shows that the proposed method is capable of significantly reducing metal artifacts, suppressing noise, and improving soft-tissue visibility. It outperforms the FBP-type methods and ART and EM methods and yields artifacts-free images. Conclusions: Constrained optimization is an effective way to deal with CT reconstruction with embedded metal objects. Although the method is presented in the context of metal artifacts, it is applicable to general ''missing data'' image reconstruction problems.

Filter Pattern Search Algorithms for Mixed Variable Constrained Optimization Problems

National Research Council Canada - National Science Library

Abramson, Mark A; Audet, Charles; Dennis, Jr, J. E

2004-01-01

.... This class combines and extends the Audet-Dennis Generalized Pattern Search (GPS) algorithms for bound constrained mixed variable optimization, and their GPS-filter algorithms for general nonlinear constraints...

The emperor's new clothes: PDE5 and the heart.

Directory of Open Access Journals (Sweden)

Chantal V Degen

Full Text Available Phosphodiesterase-5 (PDE5 is highly expressed in the pulmonary vasculature, but its expression in the myocardium is controversial. Cyclic guanosine monophosphate (cGMP activates protein kinase G (PKG, which has been hypothesized to blunt cardiac hypertrophy and negative remodeling in heart failure. Although PDE5 has been suggested to play a significant role in the breakdown of cGMP in cardiomyocytes and hence PKG regulation in the myocardium, the RELAX trial, which tested effect of PDE5 inhibition on exercise capacity in patients with heart failure with preserved ejection fraction (HFpEF failed to show a beneficial effect. These results highlight the controversy regarding the role and expression of PDE5 in the healthy and failing heart. This study used one- and two-dimensional electrophoresis and Western blotting to examine PDE5 expression in mouse (before and after trans-aortic constriction, dog (control and HFpEF as well as human (healthy and failing heart. We were unable to detect PDE5 in any cardiac tissue lysate, whereas PDE5 was present in the murine and bovine lung samples used as positive controls. These results indicate that if PDE5 is expressed in cardiac tissue, it is present in very low quantities, as PDE5 was not detected in either humans or any model of heart failure examined. Therefore in cardiac muscle, it is unlikely that PDE5 is involved the regulation of cGMP-PKG signaling, and hence PDE5 does not represent a suitable drug target for the treatment of cardiac hypertrophy. These results highlight the importance of rigorous investigation prior to clinical trial design.

A constrained optimization algorithm for total energy minimization in electronic structure calculations

International Nuclear Information System (INIS)

Yang Chao; Meza, Juan C.; Wang Linwang

2006-01-01

A new direct constrained optimization algorithm for minimizing the Kohn-Sham (KS) total energy functional is presented in this paper. The key ingredients of this algorithm involve projecting the total energy functional into a sequence of subspaces of small dimensions and seeking the minimizer of total energy functional within each subspace. The minimizer of a subspace energy functional not only provides a search direction along which the KS total energy functional decreases but also gives an optimal 'step-length' to move along this search direction. Numerical examples are provided to demonstrate that this new direct constrained optimization algorithm can be more efficient than the self-consistent field (SCF) iteration

Scalable algorithms for optimal control of stochastic PDEs

KAUST Repository

Ghattas, Omar

2016-01-07

We present methods for the optimal control of systems governed by partial differential equations with infinite-dimensional uncertain parameters. We consider an objective function that involves the mean and variance of the control objective, leading to a risk-averse optimal control formulation. To make the optimal control problem computationally tractable, we employ a local quadratic approximation of the objective with respect to the uncertain parameter. This enables computation of the mean and variance of the control objective analytically. The resulting risk-averse optimization problem is formulated as a PDE-constrained optimization problem with constraints given by the forward and adjoint PDEs for the first and second-order derivatives of the quantity of interest with respect to the uncertain parameter, and with an objective that involves the trace of a covariance-preconditioned Hessian (of the objective with respect to the uncertain parameters) operator. A randomized trace estimator is used to make tractable the trace computation. Adjoint-based techniques are used to derive an expression for the infinite-dimensional gradient of the risk-averse objective function via the Lagrangian, leading to a quasi-Newton method for solution of the optimal control problem. A specific problem of optimal control of a linear elliptic PDE that describes flow of a fluid in a porous medium with uncertain permeability field is considered. We present numerical results to study the consequences of the local quadratic approximation and the efficiency of the method.

Scalable algorithms for optimal control of stochastic PDEs

KAUST Repository

Ghattas, Omar; Alexanderian, Alen; Petra, Noemi; Stadler, Georg

2016-01-01

We present methods for the optimal control of systems governed by partial differential equations with infinite-dimensional uncertain parameters. We consider an objective function that involves the mean and variance of the control objective, leading to a risk-averse optimal control formulation. To make the optimal control problem computationally tractable, we employ a local quadratic approximation of the objective with respect to the uncertain parameter. This enables computation of the mean and variance of the control objective analytically. The resulting risk-averse optimization problem is formulated as a PDE-constrained optimization problem with constraints given by the forward and adjoint PDEs for the first and second-order derivatives of the quantity of interest with respect to the uncertain parameter, and with an objective that involves the trace of a covariance-preconditioned Hessian (of the objective with respect to the uncertain parameters) operator. A randomized trace estimator is used to make tractable the trace computation. Adjoint-based techniques are used to derive an expression for the infinite-dimensional gradient of the risk-averse objective function via the Lagrangian, leading to a quasi-Newton method for solution of the optimal control problem. A specific problem of optimal control of a linear elliptic PDE that describes flow of a fluid in a porous medium with uncertain permeability field is considered. We present numerical results to study the consequences of the local quadratic approximation and the efficiency of the method.

Cohesive phase-field fracture and a PDE constrained optimization approach to fracture inverse problems

Energy Technology Data Exchange (ETDEWEB)

Tupek, Michael R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-06-30

In recent years there has been a proliferation of modeling techniques for forward predictions of crack propagation in brittle materials, including: phase-field/gradient damage models, peridynamics, cohesive-zone models, and G/XFEM enrichment techniques. However, progress on the corresponding inverse problems has been relatively lacking. Taking advantage of key features of existing modeling approaches, we propose a parabolic regularization of Barenblatt cohesive models which borrows extensively from previous phase-field and gradient damage formulations. An efficient explicit time integration strategy for this type of nonlocal fracture model is then proposed and justified. In addition, we present a C++ computational framework for computing in- put parameter sensitivities efficiently for explicit dynamic problems using the adjoint method. This capability allows for solving inverse problems involving crack propagation to answer interesting engineering questions such as: 1) what is the optimal design topology and material placement for a heterogeneous structure to maximize fracture resistance, 2) what loads must have been applied to a structure for it to have failed in an observed way, 3) what are the existing cracks in a structure given various experimental observations, etc. In this work, we focus on the first of these engineering questions and demonstrate a capability to automatically and efficiently compute optimal designs intended to minimize crack propagation in structures.

A New Continuous-Time Equality-Constrained Optimization to Avoid Singularity.

Science.gov (United States)

Quan, Quan; Cai, Kai-Yuan

2016-02-01

In equality-constrained optimization, a standard regularity assumption is often associated with feasible point methods, namely, that the gradients of constraints are linearly independent. In practice, the regularity assumption may be violated. In order to avoid such a singularity, a new projection matrix is proposed based on which a feasible point method to continuous-time, equality-constrained optimization is developed. First, the equality constraint is transformed into a continuous-time dynamical system with solutions that always satisfy the equality constraint. Second, a new projection matrix without singularity is proposed to realize the transformation. An update (or say a controller) is subsequently designed to decrease the objective function along the solutions of the transformed continuous-time dynamical system. The invariance principle is then applied to analyze the behavior of the solution. Furthermore, the proposed method is modified to address cases in which solutions do not satisfy the equality constraint. Finally, the proposed optimization approach is applied to three examples to demonstrate its effectiveness.

Amodified probabilistic genetic algorithm for the solution of complex constrained optimization problems

OpenAIRE

Vorozheikin, A.; Gonchar, T.; Panfilov, I.; Sopov, E.; Sopov, S.

2009-01-01

A new algorithm for the solution of complex constrained optimization problems based on the probabilistic genetic algorithm with optimal solution prediction is proposed. The efficiency investigation results in comparison with standard genetic algorithm are presented.

On meeting capital requirements with a chance-constrained optimization model.

Science.gov (United States)

Atta Mills, Ebenezer Fiifi Emire; Yu, Bo; Gu, Lanlan

2016-01-01

This paper deals with a capital to risk asset ratio chance-constrained optimization model in the presence of loans, treasury bill, fixed assets and non-interest earning assets. To model the dynamics of loans, we introduce a modified CreditMetrics approach. This leads to development of a deterministic convex counterpart of capital to risk asset ratio chance constraint. We pursue the scope of analyzing our model under the worst-case scenario i.e. loan default. The theoretical model is analyzed by applying numerical procedures, in order to administer valuable insights from a financial outlook. Our results suggest that, our capital to risk asset ratio chance-constrained optimization model guarantees banks of meeting capital requirements of Basel III with a likelihood of 95 % irrespective of changes in future market value of assets.

Topology Optimization of Constrained Layer Damping on Plates Using Method of Moving Asymptote (MMA Approach

Directory of Open Access Journals (Sweden)

Zheng Ling

2011-01-01

Full Text Available Damping treatments have been extensively used as a powerful means to damp out structural resonant vibrations. Usually, damping materials are fully covered on the surface of plates. The drawbacks of this conventional treatment are also obvious due to an added mass and excess material consumption. Therefore, it is not always economical and effective from an optimization design view. In this paper, a topology optimization approach is presented to maximize the modal damping ratio of the plate with constrained layer damping treatment. The governing equation of motion of the plate is derived on the basis of energy approach. A finite element model to describe dynamic performances of the plate is developed and used along with an optimization algorithm in order to determine the optimal topologies of constrained layer damping layout on the plate. The damping of visco-elastic layer is modeled by the complex modulus formula. Considering the vibration and energy dissipation mode of the plate with constrained layer damping treatment, damping material density and volume factor are considered as design variable and constraint respectively. Meantime, the modal damping ratio of the plate is assigned as the objective function in the topology optimization approach. The sensitivity of modal damping ratio to design variable is further derived and Method of Moving Asymptote (MMA is adopted to search the optimized topologies of constrained layer damping layout on the plate. Numerical examples are used to demonstrate the effectiveness of the proposed topology optimization approach. The results show that vibration energy dissipation of the plates can be enhanced by the optimal constrained layer damping layout. This optimal technology can be further extended to vibration attenuation of sandwich cylindrical shells which constitute the major building block of many critical structures such as cabins of aircrafts, hulls of submarines and bodies of rockets and missiles as an

PDE1C deficiency antagonizes pathological cardiac remodeling and dysfunction

Science.gov (United States)

Knight, Walter E.; Chen, Si; Zhang, Yishuai; Oikawa, Masayoshi; Wu, Meiping; Zhou, Qian; Miller, Clint L.; Cai, Yujun; Mickelsen, Deanne M.; Moravec, Christine; Small, Eric M.; Abe, Junichi; Yan, Chen

2016-01-01

Cyclic nucleotide phosphodiesterase 1C (PDE1C) represents a major phosphodiesterase activity in human myocardium, but its function in the heart remains unknown. Using genetic and pharmacological approaches, we studied the expression, regulation, function, and underlying mechanisms of PDE1C in the pathogenesis of cardiac remodeling and dysfunction. PDE1C expression is up-regulated in mouse and human failing hearts and is highly expressed in cardiac myocytes but not in fibroblasts. In adult mouse cardiac myocytes, PDE1C deficiency or inhibition attenuated myocyte death and apoptosis, which was largely dependent on cyclic AMP/PKA and PI3K/AKT signaling. PDE1C deficiency also attenuated cardiac myocyte hypertrophy in a PKA-dependent manner. Conditioned medium taken from PDE1C-deficient cardiac myocytes attenuated TGF-β–stimulated cardiac fibroblast activation through a mechanism involving the crosstalk between cardiac myocytes and fibroblasts. In vivo, cardiac remodeling and dysfunction induced by transverse aortic constriction, including myocardial hypertrophy, apoptosis, cardiac fibrosis, and loss of contractile function, were significantly attenuated in PDE1C-knockout mice relative to wild-type mice. These results indicate that PDE1C activation plays a causative role in pathological cardiac remodeling and dysfunction. Given the continued development of highly specific PDE1 inhibitors and the high expression level of PDE1C in the human heart, our findings could have considerable therapeutic significance. PMID:27791092

A Simply Constrained Optimization Reformulation of KKT Systems Arising from Variational Inequalities

International Nuclear Information System (INIS)

Facchinei, F.; Fischer, A.; Kanzow, C.; Peng, J.-M.

1999-01-01

The Karush-Kuhn-Tucker (KKT) conditions can be regarded as optimality conditions for both variational inequalities and constrained optimization problems. In order to overcome some drawbacks of recently proposed reformulations of KKT systems, we propose casting KKT systems as a minimization problem with nonnegativity constraints on some of the variables. We prove that, under fairly mild assumptions, every stationary point of this constrained minimization problem is a solution of the KKT conditions. Based on this reformulation, a new algorithm for the solution of the KKT conditions is suggested and shown to have some strong global and local convergence properties

Gene Therapy in a Large Animal Model of PDE6A-Retinitis Pigmentosa

Directory of Open Access Journals (Sweden)

Freya M. Mowat

2017-06-01

Full Text Available Despite mutations in the rod phosphodiesterase 6-alpha (PDE6A gene being well-recognized as a cause of human retinitis pigmentosa, no definitive treatments have been developed to treat this blinding disease. We performed a trial of retinal gene augmentation in the Pde6a mutant dog using Pde6a delivery by capsid-mutant adeno-associated virus serotype 8, previously shown to have a rapid onset of transgene expression in the canine retina. Subretinal injections were performed in 10 dogs at 29–44 days of age, and electroretinography and vision testing were performed to assess functional outcome. Retinal structure was assessed using color fundus photography, spectral domain optical coherence tomography, and histology. Immunohistochemistry was performed to examine transgene expression and expression of other retinal genes. Treatment resulted in improvement in dim light vision and evidence of rod function on electroretinographic examination. Photoreceptor layer thickness in the treated area was preserved compared with the contralateral control vector treated or uninjected eye. Improved rod and cone photoreceptor survival, rhodopsin localization, cyclic GMP levels and bipolar cell dendrite distribution was observed in treated areas. Some adverse effects including foci of retinal separation, foci of retinal degeneration and rosette formation were identified in both AAV-Pde6a and control vector injected regions. This is the first description of successful gene augmentation for Pde6a retinitis pigmentosa in a large animal model. Further studies will be necessary to optimize visual outcomes and minimize complications before translation to human studies.

Phosphodiesterase-1b (Pde1b) knockout mice are resistant to forced swim and tail suspension induced immobility and show upregulation of Pde10a.

Science.gov (United States)

Hufgard, Jillian R; Williams, Michael T; Skelton, Matthew R; Grubisha, Olivera; Ferreira, Filipa M; Sanger, Helen; Wright, Mary E; Reed-Kessler, Tracy M; Rasmussen, Kurt; Duman, Ronald S; Vorhees, Charles V

2017-06-01

Major depressive disorder is a leading cause of suicide and disability. Despite this, current antidepressants provide insufficient efficacy in more than 60% of patients. Most current antidepressants are presynaptic reuptake inhibitors; postsynaptic signal regulation has not received as much attention as potential treatment targets. We examined the effects of disruption of the postsynaptic cyclic nucleotide hydrolyzing enzyme, phosphodiesterase (PDE) 1b, on depressive-like behavior and the effects on PDE1B protein in wild-type (WT) mice following stress. Littermate knockout (KO) and WT mice were tested in locomotor activity, tail suspension (TST), and forced swim tests (FST). FST was also used to compare the effects of two antidepressants, fluoxetine and bupropion, in KO versus WT mice. Messenger RNA (mRNA) expression changes were also determined. WT mice underwent acute or chronic stress and markers of stress and PDE1B expression were examined. Pde1b KO mice exhibited decreased TST and FST immobility. When treated with antidepressants, both WT and KO mice showed decreased FST immobility and the effect was additive in KO mice. Mice lacking Pde1b had increased striatal Pde10a mRNA expression. In WT mice, acute and chronic stress upregulated PDE1B expression while PDE10A expression was downregulated after chronic but not acute stress. PDE1B is a potential therapeutic target for depression treatment because of the antidepressant-like phenotype seen in Pde1b KO mice.

In vitro differentiation of human monocytes to macrophages: change of PDE profile and its relationship to suppression of tumour necrosis factor-α release by PDE inhibitors

Science.gov (United States)

Gantner, Florian; Kupferschmidt, Rochus; Schudt, Christian; Wendel, Albrecht; Hatzelmann, Armin

1997-01-01

During in vitro culture in 10% human AB serum, human peripheral blood monocytes acquire a macrophage-like phenotype. The underlying differentiation was characterized by increased activities of the macrophage marker enzymes unspecific esterase (NaF-insensitive form) and acid phosphatase, as well as by a down-regulation in surface CD14 expression. In parallel, a dramatic change in the phosphodiesterase (PDE) profile became evident within a few days that strongly resembled that previously described for human alveolar macrophages. Whereas PDE1 and PDE3 activities were augmented, PDE4 activity, which represented the major cyclic AMP-hydrolysing activity of peripheral blood monocytes, rapidly declined. Monocytes and monocyte-derived macrophages responded to lipopolysaccharide (LPS) with the release of tumour necrosis factor-α (TNF). In line with the change in CD14 expression, the EC50 value of LPS for induction of TNF release increased from approximately 0.1 ng ml−1 in peripheral blood monocytes to about 2 ng ml−1 in macrophages. Both populations of cells were equally susceptible towards inhibition of TNF release by cyclic AMP elevating agents such as dibutyryl cyclic AMP, prostaglandin E2 (PGE2) or forskolin, which all led to a complete abrogation of TNF production in a concentration-dependent manner and which were more efficient than the glucocorticoid dexamethasone. In monocytes, PDE4 selective inhibitors (rolipram, RP73401) suppressed TNF formation by 80%, whereas motapizone, a PDE3 selective compound, exerted a comparatively weak effect (10–15% inhibition). Combined use of PDE3 plus PDE4 inhibitors resulted in an additive effect and fully abrogated LPS-induced TNF release as did the mixed PDE3/4 inhibitor tolafentrine. In monocyte-derived macrophages, neither PDE3- nor PDE4-selective drugs markedly affected TNF generation when used alone (<15% inhibition), whereas in combination, they led to a maximal inhibition of TNF formation by about 40–50

Fuzzy chance constrained linear programming model for scrap charge optimization in steel production

DEFF Research Database (Denmark)

Rong, Aiying; Lahdelma, Risto

2008-01-01

the uncertainty based on fuzzy set theory and constrain the failure risk based on a possibility measure. Consequently, the scrap charge optimization problem is modeled as a fuzzy chance constrained linear programming problem. Since the constraints of the model mainly address the specification of the product...

Modified Backtracking Search Optimization Algorithm Inspired by Simulated Annealing for Constrained Engineering Optimization Problems

Directory of Open Access Journals (Sweden)

Hailong Wang

2018-01-01

Full Text Available The backtracking search optimization algorithm (BSA is a population-based evolutionary algorithm for numerical optimization problems. BSA has a powerful global exploration capacity while its local exploitation capability is relatively poor. This affects the convergence speed of the algorithm. In this paper, we propose a modified BSA inspired by simulated annealing (BSAISA to overcome the deficiency of BSA. In the BSAISA, the amplitude control factor (F is modified based on the Metropolis criterion in simulated annealing. The redesigned F could be adaptively decreased as the number of iterations increases and it does not introduce extra parameters. A self-adaptive ε-constrained method is used to handle the strict constraints. We compared the performance of the proposed BSAISA with BSA and other well-known algorithms when solving thirteen constrained benchmarks and five engineering design problems. The simulation results demonstrated that BSAISA is more effective than BSA and more competitive with other well-known algorithms in terms of convergence speed.

Estimating the magnitude of near-membrane PDE4 activity in living cells.

Science.gov (United States)

Xin, Wenkuan; Feinstein, Wei P; Britain, Andrea L; Ochoa, Cristhiaan D; Zhu, Bing; Richter, Wito; Leavesley, Silas J; Rich, Thomas C

2015-09-15

Recent studies have demonstrated that functionally discrete pools of phosphodiesterase (PDE) activity regulate distinct cellular functions. While the importance of localized pools of enzyme activity has become apparent, few studies have estimated enzyme activity within discrete subcellular compartments. Here we present an approach to estimate near-membrane PDE activity. First, total PDE activity is measured using traditional PDE activity assays. Second, known cAMP concentrations are dialyzed into single cells and the spatial spread of cAMP is monitored using cyclic nucleotide-gated channels. Third, mathematical models are used to estimate the spatial distribution of PDE activity within cells. Using this three-tiered approach, we observed two pharmacologically distinct pools of PDE activity, a rolipram-sensitive pool and an 8-methoxymethyl IBMX (8MM-IBMX)-sensitive pool. We observed that the rolipram-sensitive PDE (PDE4) was primarily responsible for cAMP hydrolysis near the plasma membrane. Finally, we observed that PDE4 was capable of blunting cAMP levels near the plasma membrane even when 100 μM cAMP were introduced into the cell via a patch pipette. Two compartment models predict that PDE activity near the plasma membrane, near cyclic nucleotide-gated channels, was significantly lower than total cellular PDE activity and that a slow spatial spread of cAMP allowed PDE activity to effectively hydrolyze near-membrane cAMP. These results imply that cAMP levels near the plasma membrane are distinct from those in other subcellular compartments; PDE activity is not uniform within cells; and localized pools of AC and PDE activities are responsible for controlling cAMP levels within distinct subcellular compartments. Copyright © 2015 the American Physiological Society.

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

Science.gov (United States)

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.

Nonlinear Chance Constrained Problems: Optimality Conditions, Regularization and Solvers

Czech Academy of Sciences Publication Activity Database

Adam, Lukáš; Branda, Martin

2016-01-01

Roč. 170, č. 2 (2016), s. 419-436 ISSN 0022-3239 R&D Projects: GA ČR GA15-00735S Institutional support: RVO:67985556 Keywords : Chance constrained programming * Optimality conditions * Regularization * Algorithms * Free MATLAB codes Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.289, year: 2016 http://library.utia.cas.cz/separaty/2016/MTR/adam-0460909.pdf

Superalloy design - A Monte Carlo constrained optimization method

CSIR Research Space (South Africa)

Stander, CM

1996-01-01

Full Text Available optimization method C. M. Stander Division of Materials Science and Technology, CSIR, PO Box 395, Pretoria, Republic of South Africa Received 74 March 1996; accepted 24 June 1996 A method, based on Monte Carlo constrained... successful hit, i.e. when Liow < LMP,,, < Lhiph, and for all the properties, Pj?, < P, < Pi@?. If successful this hit falls within the ROA. Repeat steps 4 and 5 to find at least ten (or more) successful hits with values...

Novel selective PDE type 1 inhibitors cause vasodilatation and lower blood pressure in rats

DEFF Research Database (Denmark)

Laursen, Morten; Beck, Lilliana; Kehler, Jan

2017-01-01

BACKGROUND AND PURPOSE: The PDE enzymes (PDE1-11) hydrolyse and thus inactivate cyclic nucleotides and are important in the regulation of the cardiovascular system. Here,we have investigated the effects on the cardiovascular system, of two novel selective PDE1 inhibitors, Lu AF41228 and Lu AF58027...... and Lu AF58027 inhibited PDE1A, PDE1B and PDE1C enzyme activity, while micromolar concentrations were required to observe inhibitory effects at other PDEs. RT-PCR revealed expression of PDE1A, PDE1B and PDE1C in rat brain, heart and aorta, but only PDE1A and PDE1B in mesenteric arteries. In rat isolated...... and Lu AF58027 dose-dependently lowered mean BP and increased heart rate. In conscious rats with telemetric pressure transducers, repeated dosing with Lu AF41228 lowered mean arterial BP 10-15 mmHg and increased heart rate. CONCLUSIONS AND IMPLICATIONS: These novel PDE1 inhibitors induce vasodilation...

CLFs-based optimization control for a class of constrained visual servoing systems.

Science.gov (United States)

Song, Xiulan; Miaomiao, Fu

2017-03-01

In this paper, we use the control Lyapunov function (CLF) technique to present an optimized visual servo control method for constrained eye-in-hand robot visual servoing systems. With the knowledge of camera intrinsic parameters and depth of target changes, visual servo control laws (i.e. translation speed) with adjustable parameters are derived by image point features and some known CLF of the visual servoing system. The Fibonacci method is employed to online compute the optimal value of those adjustable parameters, which yields an optimized control law to satisfy constraints of the visual servoing system. The Lyapunov's theorem and the properties of CLF are used to establish stability of the constrained visual servoing system in the closed-loop with the optimized control law. One merit of the presented method is that there is no requirement of online calculating the pseudo-inverse of the image Jacobian's matrix and the homography matrix. Simulation and experimental results illustrated the effectiveness of the method proposed here. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Subspace Barzilai-Borwein Gradient Method for Large-Scale Bound Constrained Optimization

International Nuclear Information System (INIS)

Xiao Yunhai; Hu Qingjie

2008-01-01

An active set subspace Barzilai-Borwein gradient algorithm for large-scale bound constrained optimization is proposed. The active sets are estimated by an identification technique. The search direction consists of two parts: some of the components are simply defined; the other components are determined by the Barzilai-Borwein gradient method. In this work, a nonmonotone line search strategy that guarantees global convergence is used. Preliminary numerical results show that the proposed method is promising, and competitive with the well-known method SPG on a subset of bound constrained problems from CUTEr collection

PAPR-Constrained Pareto-Optimal Waveform Design for OFDM-STAP Radar

Energy Technology Data Exchange (ETDEWEB)

Sen, Satyabrata [ORNL

2014-01-01

We propose a peak-to-average power ratio (PAPR) constrained Pareto-optimal waveform design approach for an orthogonal frequency division multiplexing (OFDM) radar signal to detect a target using the space-time adaptive processing (STAP) technique. The use of an OFDM signal does not only increase the frequency diversity of our system, but also enables us to adaptively design the OFDM coefficients in order to further improve the system performance. First, we develop a parametric OFDM-STAP measurement model by considering the effects of signaldependent clutter and colored noise. Then, we observe that the resulting STAP-performance can be improved by maximizing the output signal-to-interference-plus-noise ratio (SINR) with respect to the signal parameters. However, in practical scenarios, the computation of output SINR depends on the estimated values of the spatial and temporal frequencies and target scattering responses. Therefore, we formulate a PAPR-constrained multi-objective optimization (MOO) problem to design the OFDM spectral parameters by simultaneously optimizing four objective functions: maximizing the output SINR, minimizing two separate Cramer-Rao bounds (CRBs) on the normalized spatial and temporal frequencies, and minimizing the trace of CRB matrix on the target scattering coefficients estimations. We present several numerical examples to demonstrate the achieved performance improvement due to the adaptive waveform design.

Identification of the gamma subunit-interacting residues on photoreceptor cGMP phosphodiesterase, PDE6alpha '.

Science.gov (United States)

Granovsky, A E; Artemyev, N O

2000-12-29

Photoreceptor cGMP phosphodiesterase (PDE6) is the effector enzyme in the G protein-mediated visual transduction cascade. In the dark, the activity of PDE6 is shut off by the inhibitory gamma subunit (Pgamma). Chimeric proteins between cone PDE6alpha' and cGMP-binding and cGMP-specific PDE (PDE5) have been constructed and expressed in Sf9 cells to study the mechanism of inhibition of PDE6 catalytic activity by Pgamma. Substitution of the segment PDE5-(773-820) by the corresponding PDE6alpha'-(737-784) sequence in the wild-type PDE5 or in a PDE5/PDE6alpha' chimera containing the catalytic domain of PDE5 results in chimeric enzymes capable of inhibitory interaction with Pgamma. The catalytic properties of the chimeric PDEs remained similar to those of PDE5. Ala-scanning mutational analysis of the Pgamma-binding region, PDE6alpha'-(750-760), revealed PDE6alpha' residues essential for the interaction. The M758A mutation markedly impaired and the Q752A mutation moderately impaired the inhibition of chimeric PDE by Pgamma. The analysis of the catalytic properties of mutant PDEs and a model of the PDE6 catalytic domain suggest that residues Met(758) and Gln(752) directly bind Pgamma. A model of the PDE6 catalytic site shows that PDE6alpha'-(750-760) forms a loop at the entrance to the cGMP-binding pocket. Binding of Pgamma to Met(758) would effectively block access of cGMP to the catalytic cavity, providing a structural basis for the mechanism of PDE6 inhibition.

PDE1A inhibition elicits cGMP-dependent relaxation of rat mesenteric arteries

DEFF Research Database (Denmark)

Khammy, Makhala Michell; Dalsgaard, Thomas; Larsen, Peter Hjorringgaard

2017-01-01

(EC50 = 32 nM). Inhibition of NOS with L-NAME, soluble GC with ODQ, or PKG with Rp-8-Br-PET-cGMP all attenuated PDE1 inhibition-induced relaxation, whereas PKA inhibition with H89 had no effect. CONCLUSION AND IMPLICATIONS: Pde1a was the dominant PDE1 isoform present in VSMC and relaxation mediated...... by PDE1A-inhibition was predominantly driven by enhanced cGMP signalling. These results imply that isoform-selective PDE1 inhibitors are powerful investigative tools allowing examination of physiological and pathological roles of PDE1 isoforms....

Order-Constrained Solutions in K-Means Clustering: Even Better than Being Globally Optimal

Science.gov (United States)

Steinley, Douglas; Hubert, Lawrence

2008-01-01

This paper proposes an order-constrained K-means cluster analysis strategy, and implements that strategy through an auxiliary quadratic assignment optimization heuristic that identifies an initial object order. A subsequent dynamic programming recursion is applied to optimally subdivide the object set subject to the order constraint. We show that…

Co-possession of phosphodiesterase type-5 inhibitors (PDE5-I) with nitrates.

Science.gov (United States)

Chang, Li-Ling; Ma, Mark; Allmen, Heather von; Henderson, Scott C; Harper, Kristine; Hornbuckle, Kenneth

2010-06-01

Estimate the proportion of phosphodiesterase type-5 inhibitor (PDE5-I) patients who co-possess nitrates and compare the proportion of tadalafil patients dispensed nitrates to a matched control group. Secondarily, examine the percentage of co-possession of PDE5-Is and nitrates where the products were dispensed on the same day or written by the same prescriber. Male patients aged 18+ years filling PDE5-I prescriptions between December 2003 and March 2006 were identified using a U.S. longitudinal prescription database (IMS Health LRx). Similar patients not dispensed a PDE5-I during this period were matched to the tadalafil-dispensed cohort using a propensity score approach. Co-possession, as a proxy for concurrent use, was defined as an overlap in time on therapy for a PDE5-I and nitrate and was compared for the three PDE5-Is and for tadalafil to the matched control group. Among 601,063 tadalafil patients, 3.31% were dispensed a nitrate during the study period, compared to 6.18% in control patients (n = 601,063). When co-possessed prescriptions were defined by overlapping exposure periods, the proportion of PDE5-I patients with co-possessed nitrates ranged from 1.44% (tadalafil) to 1.72% (vardenafil) and 2.13% (sildenafil). Co-possession percentages of PDE5-I prescriptions were 0.83% for tadalafil and 1.07% for sildenafil and vardenafil. The majority (54.29%) of co-possessed PDE5-I and nitrate prescriptions had the nitrate dispensed prior to the PDE5-I prescription identified in the study cohort. Keeping in mind the limitations of observational studies, these results suggest that co-dispensing of nitrates and PDE5-Is is low. Compared to control patients, the proportion of nitrate co-possession was lowest for patients filling tadalafil. Tadalafil patients also had the lowest co-possessed proportion among the three PDE5-I cohorts. While the majority of co-possessed drug pairs were prescribed by different providers, the highest percentage of co-prescribing from the same

Is PDE4 too difficult a drug target?

Science.gov (United States)

Higgs, Gerry

2010-05-01

The search for selective inhibitors of PDE4 as novel anti-inflammatory drugs has continued for more than 30 years. Although several compounds have demonstrated therapeutic effects in diseases such as asthma, COPD, atopic dermatitis and psoriasis, none have reached the market. A persistent challenge in the development of PDE4 inhibitors has been drug-induced gastrointestinal adverse effects, such as nausea. However, extensive clinical trials with well-tolerated doses of roflumilast (Daxas; Nycomed/Mitsubishi Tanabe Pharma Corp/Forest Laboratories Inc) in COPD, a disease that is generally unresponsive to existing therapies, have demonstrated significant therapeutic improvements. In addition, GlaxoSmithKline plc is developing 256066, an inhaled formulation of a PDE4 inhibitor that has demonstrated efficacy in trials in asthma, and apremilast from Celgene Corp has been reported to be effective for the treatment of psoriasis. Despite the challenges and complications that have been encountered during the development of PDE4 inhibitors, these drugs may provide a genuinely novel class of anti-inflammatory agents, and there are several compounds in development that could fulfill that promise.

An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems

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Vivek Patel

2012-08-01

Full Text Available Nature inspired population based algorithms is a research field which simulates different natural phenomena to solve a wide range of problems. Researchers have proposed several algorithms considering different natural phenomena. Teaching-Learning-based optimization (TLBO is one of the recently proposed population based algorithm which simulates the teaching-learning process of the class room. This algorithm does not require any algorithm-specific control parameters. In this paper, elitism concept is introduced in the TLBO algorithm and its effect on the performance of the algorithm is investigated. The effects of common controlling parameters such as the population size and the number of generations on the performance of the algorithm are also investigated. The proposed algorithm is tested on 35 constrained benchmark functions with different characteristics and the performance of the algorithm is compared with that of other well known optimization algorithms. The proposed algorithm can be applied to various optimization problems of the industrial environment.

Sensitive Constrained Optimal PMU Allocation with Complete Observability for State Estimation Solution

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R. Manam

2017-12-01

Full Text Available In this paper, a sensitive constrained integer linear programming approach is formulated for the optimal allocation of Phasor Measurement Units (PMUs in a power system network to obtain state estimation. In this approach, sensitive buses along with zero injection buses (ZIB are considered for optimal allocation of PMUs in the network to generate state estimation solutions. Sensitive buses are evolved from the mean of bus voltages subjected to increase of load consistently up to 50%. Sensitive buses are ranked in order to place PMUs. Sensitive constrained optimal PMU allocation in case of single line and no line contingency are considered in observability analysis to ensure protection and control of power system from abnormal conditions. Modeling of ZIB constraints is included to minimize the number of PMU network allocations. This paper presents optimal allocation of PMU at sensitive buses with zero injection modeling, considering cost criteria and redundancy to increase the accuracy of state estimation solution without losing observability of the whole system. Simulations are carried out on IEEE 14, 30 and 57 bus systems and results obtained are compared with traditional and other state estimation methods available in the literature, to demonstrate the effectiveness of the proposed method.

A first-order multigrid method for bound-constrained convex optimization

Czech Academy of Sciences Publication Activity Database

Kočvara, Michal; Mohammed, S.

2016-01-01

Roč. 31, č. 3 (2016), s. 622-644 ISSN 1055-6788 R&D Projects: GA ČR(CZ) GAP201/12/0671 Grant - others:European Commission - EC(XE) 313781 Institutional support: RVO:67985556 Keywords : bound-constrained optimization * multigrid methods * linear complementarity problems Subject RIV: BA - General Mathematics Impact factor: 1.023, year: 2016 http://library.utia.cas.cz/separaty/2016/MTR/kocvara-0460326.pdf

Identification of cancer cytotoxic modulators of PDE3A by predictive chemogenomics

Science.gov (United States)

de Waal, Luc; Lewis, Timothy A.; Rees, Matthew G.; Tsherniak, Aviad; Wu, Xiaoyun; Choi, Peter S.; Gechijian, Lara; Hartigan, Christina; Faloon, Patrick W.; Hickey, Mark J.; Tolliday, Nicola; Carr, Steven A.; Clemons, Paul A.; Munoz, Benito; Wagner, Bridget K.; Shamji, Alykhan F.; Koehler, Angela N.; Schenone, Monica; Burgin, Alex B.; Schreiber, Stuart L.; Greulich, Heidi; Meyerson, Matthew

2015-01-01

High cancer death rates indicate the need for new anti-cancer therapeutic agents. Approaches to discover new cancer drugs include target-based drug discovery and phenotypic screening. Here, we identified phosphodiesterase 3A modulators as cell-selective cancer cytotoxic compounds by phenotypic compound library screening and target deconvolution by predictive chemogenomics. We found that sensitivity to 6-(4-(diethylamino)-3-nitrophenyl)-5-methyl-4,5-dihydropyridazin-3(2H)-one, or DNMDP, across 766 cancer cell lines correlates with expression of the phosphodiesterase 3A gene, PDE3A. Like DNMDP, a subset of known PDE3A inhibitors kill selected cancer cells while others do not. Furthermore, PDE3A depletion leads to DNMDP resistance. We demonstrated that DNMDP binding to PDE3A promotes an interaction between PDE3A and Schlafen 12 (SLFN12), suggesting a neomorphic activity. Co-expression of SLFN12 with PDE3A correlates with DNMDP sensitivity, while depletion of SLFN12 results in decreased DNMDP sensitivity. Our results implicate PDE3A modulators as candidate cancer therapeutic agents and demonstrate the power of predictive chemogenomics in small-molecule discovery. PMID:26656089

Numerical Methods for Pricing American Options with Time-Fractional PDE Models

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Zhiqiang Zhou

2016-01-01

Full Text Available In this paper we develop a Laplace transform method and a finite difference method for solving American option pricing problem when the change of the option price with time is considered as a fractal transmission system. In this scenario, the option price is governed by a time-fractional partial differential equation (PDE with free boundary. The Laplace transform method is applied to the time-fractional PDE. It then leads to a nonlinear equation for the free boundary (i.e., optimal early exercise boundary function in Laplace space. After numerically finding the solution of the nonlinear equation, the Laplace inversion is used to transform the approximate early exercise boundary into the time space. Finally the approximate price of the American option is obtained. A boundary-searching finite difference method is also proposed to solve the free-boundary time-fractional PDEs for pricing the American options. Numerical examples are carried out to compare the Laplace approach with the finite difference method and it is confirmed that the former approach is much faster than the latter one.

PDE3, but not PDE4, reduces β1- and β2-adrenoceptor-mediated inotropic and lusitropic effects in failing ventricle from metoprolol-treated patients

Science.gov (United States)

Molenaar, Peter; Christ, Torsten; Hussain, Rizwan I; Engel, Andreas; Berk, Emanuel; Gillette, Katherine T; Chen, Lu; Galindo-Tovar, Alejandro; Krobert, Kurt A; Ravens, Ursula; Levy, Finn Olav; Kaumann, Alberto J

2013-01-01

Background and Purpose PDE3 and/or PDE4 control ventricular effects of catecholamines in several species but their relative effects in failing human ventricle are unknown. We investigated whether the PDE3-selective inhibitor cilostamide (0.3–1 μM) or PDE4 inhibitor rolipram (1–10 μM) modified the positive inotropic and lusitropic effects of catecholamines in human failing myocardium. Experimental Approach Right and left ventricular trabeculae from freshly explanted hearts of 5 non-β-blocker-treated and 15 metoprolol-treated patients with terminal heart failure were paced to contract at 1 Hz. The effects of (-)-noradrenaline, mediated through β1 adrenoceptors (β2 adrenoceptors blocked with ICI118551), and (-)-adrenaline, mediated through β2 adrenoceptors (β1 adrenoceptors blocked with CGP20712A), were assessed in the absence and presence of PDE inhibitors. Catecholamine potencies were estimated from –logEC50s. Key Results Cilostamide did not significantly potentiate the inotropic effects of the catecholamines in non-β-blocker-treated patients. Cilostamide caused greater potentiation (P = 0.037) of the positive inotropic effects of (-)-adrenaline (0.78 ± 0.12 log units) than (-)-noradrenaline (0.47 ± 0.12 log units) in metoprolol-treated patients. Lusitropic effects of the catecholamines were also potentiated by cilostamide. Rolipram did not affect the inotropic and lusitropic potencies of (-)-noradrenaline or (-)-adrenaline on right and left ventricular trabeculae from metoprolol-treated patients. Conclusions and Implications Metoprolol induces a control by PDE3 of ventricular effects mediated through both β1 and β2 adrenoceptors, thereby further reducing sympathetic cardiostimulation in patients with terminal heart failure. Concurrent therapy with a PDE3 blocker and metoprolol could conceivably facilitate cardiostimulation evoked by adrenaline through β2 adrenoceptors. PDE4 does not appear to reduce inotropic and lusitropic effects of

A New Interpolation Approach for Linearly Constrained Convex Optimization

KAUST Repository

Espinoza, Francisco

2012-08-01

In this thesis we propose a new class of Linearly Constrained Convex Optimization methods based on the use of a generalization of Shepard\\'s interpolation formula. We prove the properties of the surface such as the interpolation property at the boundary of the feasible region and the convergence of the gradient to the null space of the constraints at the boundary. We explore several descent techniques such as steepest descent, two quasi-Newton methods and the Newton\\'s method. Moreover, we implement in the Matlab language several versions of the method, particularly for the case of Quadratic Programming with bounded variables. Finally, we carry out performance tests against Matab Optimization Toolbox methods for convex optimization and implementations of the standard log-barrier and active-set methods. We conclude that the steepest descent technique seems to be the best choice so far for our method and that it is competitive with other standard methods both in performance and empirical growth order.

Parallel PDE-Based Simulations Using the Common Component Architecture

International Nuclear Information System (INIS)

McInnes, Lois C.; Allan, Benjamin A.; Armstrong, Robert; Benson, Steven J.; Bernholdt, David E.; Dahlgren, Tamara L.; Diachin, Lori; Krishnan, Manoj Kumar; Kohl, James A.; Larson, J. Walter; Lefantzi, Sophia; Nieplocha, Jarek; Norris, Boyana; Parker, Steven G.; Ray, Jaideep; Zhou, Shujia

2006-01-01

The complexity of parallel PDE-based simulations continues to increase as multimodel, multiphysics, and multi-institutional projects become widespread. A goal of component based software engineering in such large-scale simulations is to help manage this complexity by enabling better interoperability among various codes that have been independently developed by different groups. The Common Component Architecture (CCA) Forum is defining a component architecture specification to address the challenges of high-performance scientific computing. In addition, several execution frameworks, supporting infrastructure, and general purpose components are being developed. Furthermore, this group is collaborating with others in the high-performance computing community to design suites of domain-specific component interface specifications and underlying implementations. This chapter discusses recent work on leveraging these CCA efforts in parallel PDE-based simulations involving accelerator design, climate modeling, combustion, and accidental fires and explosions. We explain how component technology helps to address the different challenges posed by each of these applications, and we highlight how component interfaces built on existing parallel toolkits facilitate the reuse of software for parallel mesh manipulation, discretization, linear algebra, integration, optimization, and parallel data redistribution. We also present performance data to demonstrate the suitability of this approach, and we discuss strategies for applying component technologies to both new and existing applications

Selective Extraction of Entangled Textures via Adaptive PDE Transform

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Yang Wang

2012-01-01

Full Text Available Texture and feature extraction is an important research area with a wide range of applications in science and technology. Selective extraction of entangled textures is a challenging task due to spatial entanglement, orientation mixing, and high-frequency overlapping. The partial differential equation (PDE transform is an efficient method for functional mode decomposition. The present work introduces adaptive PDE transform algorithm to appropriately threshold the statistical variance of the local variation of functional modes. The proposed adaptive PDE transform is applied to the selective extraction of entangled textures. Successful separations of human face, clothes, background, natural landscape, text, forest, camouflaged sniper and neuron skeletons have validated the proposed method.

Multiscale Reaction-Diffusion Algorithms: PDE-Assisted Brownian Dynamics

KAUST Repository

Franz, Benjamin

2013-06-19

Two algorithms that combine Brownian dynami cs (BD) simulations with mean-field partial differential equations (PDEs) are presented. This PDE-assisted Brownian dynamics (PBD) methodology provides exact particle tracking data in parts of the domain, whilst making use of a mean-field reaction-diffusion PDE description elsewhere. The first PBD algorithm couples BD simulations with PDEs by randomly creating new particles close to the interface, which partitions the domain, and by reincorporating particles into the continuum PDE-description when they cross the interface. The second PBD algorithm introduces an overlap region, where both descriptions exist in parallel. It is shown that the overlap region is required to accurately compute variances using PBD simulations. Advantages of both PBD approaches are discussed and illustrative numerical examples are presented. © 2013 Society for Industrial and Applied Mathematics.

A Framework for Constrained Optimization Problems Based on a Modified Particle Swarm Optimization

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Biwei Tang

2016-01-01

Full Text Available This paper develops a particle swarm optimization (PSO based framework for constrained optimization problems (COPs. Aiming at enhancing the performance of PSO, a modified PSO algorithm, named SASPSO 2011, is proposed by adding a newly developed self-adaptive strategy to the standard particle swarm optimization 2011 (SPSO 2011 algorithm. Since the convergence of PSO is of great importance and significantly influences the performance of PSO, this paper first theoretically investigates the convergence of SASPSO 2011. Then, a parameter selection principle guaranteeing the convergence of SASPSO 2011 is provided. Subsequently, a SASPSO 2011-based framework is established to solve COPs. Attempting to increase the diversity of solutions and decrease optimization difficulties, the adaptive relaxation method, which is combined with the feasibility-based rule, is applied to handle constraints of COPs and evaluate candidate solutions in the developed framework. Finally, the proposed method is verified through 4 benchmark test functions and 2 real-world engineering problems against six PSO variants and some well-known methods proposed in the literature. Simulation results confirm that the proposed method is highly competitive in terms of the solution quality and can be considered as a vital alternative to solve COPs.

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

Science.gov (United States)

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

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

Science.gov (United States)

Liu, Qingshan; Guo, Zhishan; Wang, Jun

2012-02-01

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

Adaptively Constrained Stochastic Model Predictive Control for the Optimal Dispatch of Microgrid

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Xiaogang Guo

2018-01-01

Full Text Available In this paper, an adaptively constrained stochastic model predictive control (MPC is proposed to achieve less-conservative coordination between energy storage units and uncertain renewable energy sources (RESs in a microgrid (MG. Besides the economic objective of MG operation, the limits of state-of-charge (SOC and discharging/charging power of the energy storage unit are formulated as chance constraints when accommodating uncertainties of RESs, considering mild violations of these constraints are allowed during long-term operation, and a closed-loop online update strategy is performed to adaptively tighten or relax constraints according to the actual deviation probability of violation level from the desired one as well as the current change rate of deviation probability. Numerical studies show that the proposed adaptively constrained stochastic MPC for MG optimal operation is much less conservative compared with the scenario optimization based robust MPC, and also presents a better convergence performance to the desired constraint violation level than other online update strategies.

A Globally Convergent Parallel SSLE Algorithm for Inequality Constrained Optimization

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Zhijun Luo

2014-01-01

Full Text Available A new parallel variable distribution algorithm based on interior point SSLE algorithm is proposed for solving inequality constrained optimization problems under the condition that the constraints are block-separable by the technology of sequential system of linear equation. Each iteration of this algorithm only needs to solve three systems of linear equations with the same coefficient matrix to obtain the descent direction. Furthermore, under certain conditions, the global convergence is achieved.

Stopping test of iterative methods for solving PDE

International Nuclear Information System (INIS)

Wang Bangrong

1991-01-01

In order to assure the accuracy of the numerical solution of the iterative method for solving PDE (partial differential equation), the stopping test is very important. If the coefficient matrix of the system of linear algebraic equations is strictly diagonal dominant or irreducible weakly diagonal dominant, the stopping test formulas of the iterative method for solving PDE is proposed. Several numerical examples are given to illustrate the applications of the stopping test formulas

DISC1, PDE4B, and NDE1 at the centrosome and synapse

International Nuclear Information System (INIS)

Bradshaw, Nicholas J.; Ogawa, Fumiaki; Antolin-Fontes, Beatriz; Chubb, Jennifer E.; Carlyle, Becky C.; Christie, Sheila; Claessens, Antoine; Porteous, David J.; Millar, J. Kirsty

2008-01-01

Disrupted-In-Schizophrenia 1 (DISC1) is a risk factor for schizophrenia and other major mental illnesses. Its protein binding partners include the Nuclear Distribution Factor E Homologs (NDE1 and NDEL1), LIS1, and phosphodiesterases 4B and 4D (PDE4B and PDE4D). We demonstrate that NDE1, NDEL1 and LIS1, together with their binding partner dynein, associate with DISC1, PDE4B and PDE4D within the cell, and provide evidence that this complex is present at the centrosome. LIS1 and NDEL1 have been previously suggested to be synaptic, and we now demonstrate localisation of DISC1, NDE1, and PDE4B at synapses in cultured neurons. NDE1 is phosphorylated by cAMP-dependant Protein Kinase A (PKA), whose activity is, in turn, regulated by the cAMP hydrolysis activity of phosphodiesterases, including PDE4. We propose that DISC1 acts as an assembly scaffold for all of these proteins and that the NDE1/NDEL1/LIS1/dynein complex is modulated by cAMP levels via PKA and PDE4.

Dropout in the treatment of erectile dysfunction with PDE5: a study on predictors and a qualitative analysis of reasons for discontinuation.

Science.gov (United States)

Carvalheira, Ana A; Pereira, Nuno Monteiro; Maroco, João; Forjaz, Vera

2012-09-01

Phosphodiesterase type 5 inhibitors (PDE5) are currently the first line treatment for erectile dysfunction (ED). However, previous research shows that PDE5 treatments have high discontinuation rates. Understanding the reasons for discontinuing PDE5 will be necessary to optimize the response to treatment. The main goals were: (i) to analyze discontinuation rate of PDE5; (ii) to identify the discontinuation predictors; and (iii) to study the reasons for discontinuation using a qualitative methodology. The PDE5 discontinuation rates, predictors, and reasons for discontinuation treatment. A total of 327 men with clinical diagnosis for ED who had been treated with PDE5 were successfully interviewed by telephone, after giving their informed consent by snail mail. Telephone interviews, concerning their ongoing treatment, were carried out using a standardized questionnaire form with quantitative and qualitative items. Participation rate was 71.8%. Of the total sample, 160 men (48.9%) had discontinued PDE5 treatment. The discontinuation rate was higher among men with diabetes (73%) and in iatrogenic group (65%), and lower in venogenic etiology (38.7%). We differentiated three groups of men who discontinued treatment (i) during the first 3 months (55.1%); (ii) between 4 and 12 months (26.9%); and (iii) after a period of 12 months (18%). Qualitative analyses revealed diverse reasons for discontinuation: non-effectiveness of PDE5 (36.8%), psychological factors (e.g., anxiety, negative emotions, fears, concerns, dysfunctional beliefs) (17.5%), erection recovery (14.4%), and concerns about the cardiovascular safety of PDE5 (8.7%) were the most common. Older men and men whose partners were involved in the treatment, were less likely to discontinue treatment. Half the subjects discontinued medication. Mostly, there was a combination of factors that led to discontinuation: non-effectiveness and psychosocial factors appear to be the main reasons. Addressing those factors will allow

An L∞/L1-Constrained Quadratic Optimization Problem with Applications to Neural Networks

International Nuclear Information System (INIS)

Leizarowitz, Arie; Rubinstein, Jacob

2003-01-01

Pattern formation in associative neural networks is related to a quadratic optimization problem. Biological considerations imply that the functional is constrained in the L ∞ norm and in the L 1 norm. We consider such optimization problems. We derive the Euler-Lagrange equations, and construct basic properties of the maximizers. We study in some detail the case where the kernel of the quadratic functional is finite-dimensional. In this case the optimization problem can be fully characterized by the geometry of a certain convex and compact finite-dimensional set

A conformational switch in the inhibitory gamma-subunit of PDE6 upon enzyme activation by transducin.

Science.gov (United States)

Granovsky, A E; Artemyev, N O

2001-11-06

In response to light, a photoreceptor G protein, transducin, activates cGMP-phosphodiesterase (PDE6) by displacing the inhibitory gamma-subunits (Pgamma) from the enzyme's catalytic sites. Evidence suggests that the activation of PDE6 involves a conformational change of the key inhibitory C-terminal domain of Pgamma. In this study, the C-terminal region of Pgamma, Pgamma-73-85, has been targeted for Ala-scanning mutagenesis to identify the point-to-point interactions between Pgamma and the PDE6 catalytic subunits and to probe the nature of the conformational change. Pgamma mutants were tested for their ability to inhibit PDE6 and a chimeric PDE5-conePDE6 enzyme containing the Pgamma C-terminus-binding site of cone PDE. This analysis has revealed that in addition to previously characterized Ile86 and Ile87, important inhibitory contact residues of Pgamma include Asn74, His75, and Leu78. The patterns of mutant PDE5-conePDE6 enzyme inhibition suggest the interaction between the PgammaAsn74/His75 sequence and Met758 of the cone PDE6alpha' catalytic subunit. This interaction, and the interaction between the PgammaIle86/Ile87 and PDE6alpha'Phe777/Phe781 residues, is most consistent with an alpha-helical structure of the Pgamma C-terminus. The analysis of activation of PDE6 enzymes containing Pgamma mutants with Ala-substituted transducin-contact residues demonstrated the critical role of PgammaLeu76. Accordingly, we hypothesize that the initial step in PDE6 activation involves an interaction of transducin-alpha with PgammaLeu76. This interaction introduces a bend into the alpha-helical structure of the Pgamma C-terminus, allowing transducin-alpha to further twist the C-terminus thereby uncovering the catalytic pocket of PDE6.

Preventive Security-Constrained Optimal Power Flow Considering UPFC Control Modes

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Xi Wu

2017-08-01

Full Text Available The successful application of the unified power flow controller (UPFC provides a new control method for the secure and economic operation of power system. In order to make the full use of UPFC and improve the economic efficiency and static security of a power system, a preventive security-constrained power flow optimization method considering UPFC control modes is proposed in this paper. Firstly, an iterative method considering UPFC control modes is deduced for power flow calculation. Taking into account the influence of different UPFC control modes on the distribution of power flow after N-1 contingency, the optimization model is then constructed by setting a minimal system operation cost and a maximum static security margin as the objective. Based on this model, the particle swarm optimization (PSO algorithm is utilized to optimize power system operating parameters and UPFC control modes simultaneously. Finally, a standard IEEE 30-bus system is utilized to demonstrate that the proposed method fully exploits the potential of static control of UPFC and significantly increases the economic efficiency and static security of the power system.

Performance optimization of Sparse Matrix-Vector Multiplication for multi-component PDE-based applications using GPUs

KAUST Repository

Abdelfattah, Ahmad

2016-05-23

Simulations of many multi-component PDE-based applications, such as petroleum reservoirs or reacting flows, are dominated by the solution, on each time step and within each Newton step, of large sparse linear systems. The standard solver is a preconditioned Krylov method. Along with application of the preconditioner, memory-bound Sparse Matrix-Vector Multiplication (SpMV) is the most time-consuming operation in such solvers. Multi-species models produce Jacobians with a dense block structure, where the block size can be as large as a few dozen. Failing to exploit this dense block structure vastly underutilizes hardware capable of delivering high performance on dense BLAS operations. This paper presents a GPU-accelerated SpMV kernel for block-sparse matrices. Dense matrix-vector multiplications within the sparse-block structure leverage optimization techniques from the KBLAS library, a high performance library for dense BLAS kernels. The design ideas of KBLAS can be applied to block-sparse matrices. Furthermore, a technique is proposed to balance the workload among thread blocks when there are large variations in the lengths of nonzero rows. Multi-GPU performance is highlighted. The proposed SpMV kernel outperforms existing state-of-the-art implementations using matrices with real structures from different applications. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Performance optimization of Sparse Matrix-Vector Multiplication for multi-component PDE-based applications using GPUs

KAUST Repository

Abdelfattah, Ahmad; Ltaief, Hatem; Keyes, David E.; Dongarra, Jack

2016-01-01

Simulations of many multi-component PDE-based applications, such as petroleum reservoirs or reacting flows, are dominated by the solution, on each time step and within each Newton step, of large sparse linear systems. The standard solver is a preconditioned Krylov method. Along with application of the preconditioner, memory-bound Sparse Matrix-Vector Multiplication (SpMV) is the most time-consuming operation in such solvers. Multi-species models produce Jacobians with a dense block structure, where the block size can be as large as a few dozen. Failing to exploit this dense block structure vastly underutilizes hardware capable of delivering high performance on dense BLAS operations. This paper presents a GPU-accelerated SpMV kernel for block-sparse matrices. Dense matrix-vector multiplications within the sparse-block structure leverage optimization techniques from the KBLAS library, a high performance library for dense BLAS kernels. The design ideas of KBLAS can be applied to block-sparse matrices. Furthermore, a technique is proposed to balance the workload among thread blocks when there are large variations in the lengths of nonzero rows. Multi-GPU performance is highlighted. The proposed SpMV kernel outperforms existing state-of-the-art implementations using matrices with real structures from different applications. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Solving Multi-Resource Constrained Project Scheduling Problem using Ant Colony Optimization

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Hsiang-Hsi Huang

2015-01-01

Full Text Available This paper applied Ant Colony Optimization (ACO to develop a resource constraints scheduling model to achieve the resource allocation optimization and the shortest completion time of a project under resource constraints and the activities precedence requirement for projects. Resource leveling is also discussed and has to be achieved under the resource allocation optimization in this research. Testing cases and examples adopted from the international test bank were studied for verifying the effectiveness of the proposed model. The results showed that the solutions of different cases all have a better performance within a reasonable time. These can be obtained through ACO algorithm under the same constrained conditions. A program was written for the proposed model that is able to automatically produce the project resource requirement figure after the project duration is solved.

New Therapeutic Applications of Phosphodiesterase 5 Inhibitors (PDE5-Is).

Science.gov (United States)

Ribaudo, Giovanni; Pagano, Mario Angelo; Bova, Sergio; Zagotto, Giuseppe

2016-01-01

Phosphodiesterase 5 inhibitors (PDE5-Is) sildenafil, vardenafil, tadalafil and the recently approved avanafil represent the first-line choice for both on-demand and chronic treatment of erectile dysfunction (ED). In addition to this, sildenafil and tadalafil, have also been approved for the treatment of pulmonary arterial hypertension. Due to its expression and localization in many tissues, PDE5 and its regulation has been reported to be involved in several other diseases. We aim to provide an updated overview of the emerging therapeutic applications of PDE5-Is besides ED, taking into account the latest ongoing research reports. We searched online databases (Pubmed, Reaxys, Scopus) to lay the bases for an accurate, quality criteria-based literature update. We focused our attention on most recent research reports, in particular when supported by pre-clinical and clinical data. The regulation of PDE5 may influence pathological conditions such as, among the others, heart failure, cystic fibrosis, cancer, CNS-related diseases, diabetes and dysfunctions affecting male urinary/reproductive system. Sildenafil, vardenafil, tadalafil and the other chemical entities considered PDE5-Is showed overall positive results and significant improvements in the studied disease, thus some discordant results, in particular when comparing pre-clinical and clinical data, have to be pointed out, suggesting that further insights are needed especially to assess the exact molecular pathway underlying.

Constrained Optimization Based on Hybrid Evolutionary Algorithm and Adaptive Constraint-Handling Technique

DEFF Research Database (Denmark)

Wang, Yong; Cai, Zixing; Zhou, Yuren

2009-01-01

A novel approach to deal with numerical and engineering constrained optimization problems, which incorporates a hybrid evolutionary algorithm and an adaptive constraint-handling technique, is presented in this paper. The hybrid evolutionary algorithm simultaneously uses simplex crossover and two...... mutation operators to generate the offspring population. Additionally, the adaptive constraint-handling technique consists of three main situations. In detail, at each situation, one constraint-handling mechanism is designed based on current population state. Experiments on 13 benchmark test functions...... and four well-known constrained design problems verify the effectiveness and efficiency of the proposed method. The experimental results show that integrating the hybrid evolutionary algorithm with the adaptive constraint-handling technique is beneficial, and the proposed method achieves competitive...

Coordinated trajectory planning of dual-arm space robot using constrained particle swarm optimization

Science.gov (United States)

Wang, Mingming; Luo, Jianjun; Yuan, Jianping; Walter, Ulrich

2018-05-01

Application of the multi-arm space robot will be more effective than single arm especially when the target is tumbling. This paper investigates the application of particle swarm optimization (PSO) strategy to coordinated trajectory planning of the dual-arm space robot in free-floating mode. In order to overcome the dynamics singularities issue, the direct kinematics equations in conjunction with constrained PSO are employed for coordinated trajectory planning of dual-arm space robot. The joint trajectories are parametrized with Bézier curve to simplify the calculation. Constrained PSO scheme with adaptive inertia weight is implemented to find the optimal solution of joint trajectories while specific objectives and imposed constraints are satisfied. The proposed method is not sensitive to the singularity issue due to the application of forward kinematic equations. Simulation results are presented for coordinated trajectory planning of two kinematically redundant manipulators mounted on a free-floating spacecraft and demonstrate the effectiveness of the proposed method.

Firefly Algorithm for Cardinality Constrained Mean-Variance Portfolio Optimization Problem with Entropy Diversity Constraint

Science.gov (United States)

2014-01-01

Portfolio optimization (selection) problem is an important and hard optimization problem that, with the addition of necessary realistic constraints, becomes computationally intractable. Nature-inspired metaheuristics are appropriate for solving such problems; however, literature review shows that there are very few applications of nature-inspired metaheuristics to portfolio optimization problem. This is especially true for swarm intelligence algorithms which represent the newer branch of nature-inspired algorithms. No application of any swarm intelligence metaheuristics to cardinality constrained mean-variance (CCMV) portfolio problem with entropy constraint was found in the literature. This paper introduces modified firefly algorithm (FA) for the CCMV portfolio model with entropy constraint. Firefly algorithm is one of the latest, very successful swarm intelligence algorithm; however, it exhibits some deficiencies when applied to constrained problems. To overcome lack of exploration power during early iterations, we modified the algorithm and tested it on standard portfolio benchmark data sets used in the literature. Our proposed modified firefly algorithm proved to be better than other state-of-the-art algorithms, while introduction of entropy diversity constraint further improved results. PMID:24991645

Firefly algorithm for cardinality constrained mean-variance portfolio optimization problem with entropy diversity constraint.

Science.gov (United States)

Bacanin, Nebojsa; Tuba, Milan

2014-01-01

Portfolio optimization (selection) problem is an important and hard optimization problem that, with the addition of necessary realistic constraints, becomes computationally intractable. Nature-inspired metaheuristics are appropriate for solving such problems; however, literature review shows that there are very few applications of nature-inspired metaheuristics to portfolio optimization problem. This is especially true for swarm intelligence algorithms which represent the newer branch of nature-inspired algorithms. No application of any swarm intelligence metaheuristics to cardinality constrained mean-variance (CCMV) portfolio problem with entropy constraint was found in the literature. This paper introduces modified firefly algorithm (FA) for the CCMV portfolio model with entropy constraint. Firefly algorithm is one of the latest, very successful swarm intelligence algorithm; however, it exhibits some deficiencies when applied to constrained problems. To overcome lack of exploration power during early iterations, we modified the algorithm and tested it on standard portfolio benchmark data sets used in the literature. Our proposed modified firefly algorithm proved to be better than other state-of-the-art algorithms, while introduction of entropy diversity constraint further improved results.

Fuzzy Constrained Predictive Optimal Control of High Speed Train with Actuator Dynamics

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Xi Wang

2016-01-01

Full Text Available We investigate the problem of fuzzy constrained predictive optimal control of high speed train considering the effect of actuator dynamics. The dynamics feature of the high speed train is modeled as a cascade of cars connected by flexible couplers, and the formulation is mathematically transformed into a Takagi-Sugeno (T-S fuzzy model. The goal of this study is to design a state feedback control law at each decision step to enhance safety, comfort, and energy efficiency of high speed train subject to safety constraints on the control input. Based on Lyapunov stability theory, the problem of optimizing an upper bound on the cruise control cost function subject to input constraints is reduced to a convex optimization problem involving linear matrix inequalities (LMIs. Furthermore, we analyze the influences of second-order actuator dynamics on the fuzzy constrained predictive controller, which shows risk of potentially deteriorating the overall system. Employing backstepping method, an actuator compensator is proposed to accommodate for the influence of the actuator dynamics. The experimental results show that with the proposed approach high speed train can track the desired speed, the relative coupler displacement between the neighbouring cars is stable at the equilibrium state, and the influence of actuator dynamics is reduced, which demonstrate the validity and effectiveness of the proposed approaches.

Law of large numbers and central limit theorem for randomly forced PDE's

CERN Document Server

Shirikyan, A

2004-01-01

We consider a class of dissipative PDE's perturbed by an external random force. Under the condition that the distribution of perturbation is sufficiently non-degenerate, a strong law of large numbers (SLLN) and a central limit theorem (CLT) for solutions are established and the corresponding rates of convergence are estimated. It is also shown that the estimates obtained are close to being optimal. The proofs are based on the property of exponential mixing for the problem in question and some abstract SLLN and CLT for mixing-type Markov processes.

Order-constrained linear optimization.

Science.gov (United States)

Tidwell, Joe W; Dougherty, Michael R; Chrabaszcz, Jeffrey S; Thomas, Rick P

2017-11-01

Despite the fact that data and theories in the social, behavioural, and health sciences are often represented on an ordinal scale, there has been relatively little emphasis on modelling ordinal properties. The most common analytic framework used in psychological science is the general linear model, whose variants include ANOVA, MANOVA, and ordinary linear regression. While these methods are designed to provide the best fit to the metric properties of the data, they are not designed to maximally model ordinal properties. In this paper, we develop an order-constrained linear least-squares (OCLO) optimization algorithm that maximizes the linear least-squares fit to the data conditional on maximizing the ordinal fit based on Kendall's τ. The algorithm builds on the maximum rank correlation estimator (Han, 1987, Journal of Econometrics, 35, 303) and the general monotone model (Dougherty & Thomas, 2012, Psychological Review, 119, 321). Analyses of simulated data indicate that when modelling data that adhere to the assumptions of ordinary least squares, OCLO shows minimal bias, little increase in variance, and almost no loss in out-of-sample predictive accuracy. In contrast, under conditions in which data include a small number of extreme scores (fat-tailed distributions), OCLO shows less bias and variance, and substantially better out-of-sample predictive accuracy, even when the outliers are removed. We show that the advantages of OCLO over ordinary least squares in predicting new observations hold across a variety of scenarios in which researchers must decide to retain or eliminate extreme scores when fitting data. © 2017 The British Psychological Society.

Distribution of PDE8A in the nervous system of the Sprague-Dawley rat

DEFF Research Database (Denmark)

Kruse, Lars Schack; Møller, Morten; Kruuse, Christina

2011-01-01

in the brain of adult male Sprague-Dawley rats and in the trigeminal ganglion. PDE8A was confined to neuronal perikaryal cytoplasm and to processes extending from those perikarya. The neurons exhibiting PDE8A-immunoreactivity were widely distributed in the forebrain, brain stem, and cerebellum. Strongly...... immunoreactive neurons were located in the olfactory bulb, the septal area, zona incerta, and reticular nucleus of the thalamus. Less immunoreactivity was seen in the hippocampus and cerebral cortex. Intense staining was detected in both the substantia nigra and the sensory trigeminal nucleus. In cerebellum PDE8....... The localization of the cAMP degrading PDE8A may indicate a role for PDE8A in cAMP signaling related to pain transmission, motor function, cognition and olfaction....

Compartmentalized PDE4A5 Signaling Impairs Hippocampal Synaptic Plasticity and Long-Term Memory.

Science.gov (United States)

Havekes, Robbert; Park, Alan J; Tolentino, Rosa E; Bruinenberg, Vibeke M; Tudor, Jennifer C; Lee, Yool; Hansen, Rolf T; Guercio, Leonardo A; Linton, Edward; Neves-Zaph, Susana R; Meerlo, Peter; Baillie, George S; Houslay, Miles D; Abel, Ted

2016-08-24

Alterations in cAMP signaling are thought to contribute to neurocognitive and neuropsychiatric disorders. Members of the cAMP-specific phosphodiesterase 4 (PDE4) family, which contains >25 different isoforms, play a key role in determining spatial cAMP degradation so as to orchestrate compartmentalized cAMP signaling in cells. Each isoform binds to a different set of protein complexes through its unique N-terminal domain, thereby leading to targeted degradation of cAMP in specific intracellular compartments. However, the functional role of specific compartmentalized PDE4 isoforms has not been examined in vivo Here, we show that increasing protein levels of the PDE4A5 isoform in mouse hippocampal excitatory neurons impairs a long-lasting form of hippocampal synaptic plasticity and attenuates hippocampus-dependent long-term memories without affecting anxiety. In contrast, viral expression of a truncated version of PDE4A5, which lacks the unique N-terminal targeting domain, does not affect long-term memory. Further, overexpression of the PDE4A1 isoform, which targets a different subset of signalosomes, leaves memory undisturbed. Fluorescence resonance energy transfer sensor-based cAMP measurements reveal that the full-length PDE4A5, in contrast to the truncated form, hampers forskolin-mediated increases in neuronal cAMP levels. Our study indicates that the unique N-terminal localization domain of PDE4A5 is essential for the targeting of specific cAMP-dependent signaling underlying synaptic plasticity and memory. The development of compounds to disrupt the compartmentalization of individual PDE4 isoforms by targeting their unique N-terminal domains may provide a fruitful approach to prevent cognitive deficits in neuropsychiatric and neurocognitive disorders that are associated with alterations in cAMP signaling. Neurons exhibit localized signaling processes that enable biochemical cascades to be activated selectively in specific subcellular compartments. The

A First-order Prediction-Correction Algorithm for Time-varying (Constrained) Optimization: Preprint

Energy Technology Data Exchange (ETDEWEB)

Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Simonetto, Andrea [Universite catholique de Louvain

2017-07-25

This paper focuses on the design of online algorithms based on prediction-correction steps to track the optimal solution of a time-varying constrained problem. Existing prediction-correction methods have been shown to work well for unconstrained convex problems and for settings where obtaining the inverse of the Hessian of the cost function can be computationally affordable. The prediction-correction algorithm proposed in this paper addresses the limitations of existing methods by tackling constrained problems and by designing a first-order prediction step that relies on the Hessian of the cost function (and do not require the computation of its inverse). Analytical results are established to quantify the tracking error. Numerical simulations corroborate the analytical results and showcase performance and benefits of the algorithms.

Roles of PDE1 in Pathological Cardiac Remodeling and Dysfunction.

Science.gov (United States)

Chen, Si; Knight, Walter E; Yan, Chen

2018-04-23

Pathological cardiac hypertrophy and dysfunction is a response to various stress stimuli and can result in reduced cardiac output and heart failure. Cyclic nucleotide signaling regulates several cardiac functions including contractility, remodeling, and fibrosis. Cyclic nucleotide phosphodiesterases (PDEs), by catalyzing the hydrolysis of cyclic nucleotides, are critical in the homeostasis of intracellular cyclic nucleotide signaling and hold great therapeutic potential as drug targets. Recent studies have revealed that the inhibition of the PDE family member PDE1 plays a protective role in pathological cardiac remodeling and dysfunction by the modulation of distinct cyclic nucleotide signaling pathways. This review summarizes recent key findings regarding the roles of PDE1 in the cardiac system that can lead to a better understanding of its therapeutic potential.

A General Symbolic PDE Solver Generator: Explicit Schemes

Directory of Open Access Journals (Sweden)

K. Sheshadri

2003-01-01

Full Text Available A symbolic solver generator to deal with a system of partial differential equations (PDEs in functions of an arbitrary number of variables is presented; it can also handle arbitrary domains (geometries of the independent variables. Given a system of PDEs, the solver generates a set of explicit finite-difference methods to any specified order, and a Fourier stability criterion for each method. For a method that is stable, an iteration function is generated symbolically using the PDE and its initial and boundary conditions. This iteration function is dynamically generated for every PDE problem, and its evaluation provides a solution to the PDE problem. A C++/Fortran 90 code for the iteration function is generated using the MathCode system, which results in a performance gain of the order of a thousand over Mathematica, the language that has been used to code the solver generator. Examples of stability criteria are presented that agree with known criteria; examples that demonstrate the generality of the solver and the speed enhancement of the generated C++ and Fortran 90 codes are also presented.

Rip3 knockdown rescues photoreceptor cell death in blind pde6c zebrafish.

Science.gov (United States)

Viringipurampeer, I A; Shan, X; Gregory-Evans, K; Zhang, J P; Mohammadi, Z; Gregory-Evans, C Y

2014-05-01

Achromatopsia is a progressive autosomal recessive retinal disease characterized by early loss of cone photoreceptors and later rod photoreceptor loss. In most cases, mutations have been identified in CNGA3, CNGB3, GNAT2, PDE6C or PDE6H genes. Owing to this genetic heterogeneity, mutation-independent therapeutic schemes aimed at preventing cone cell death are very attractive treatment strategies. In pde6c(w59) mutant zebrafish, cone photoreceptors expressed high levels of receptor-interacting protein kinase 1 (RIP1) and receptor-interacting protein kinase 3 (RIP3) kinases, key regulators of necroptotic cell death. In contrast, rod photoreceptor cells were alternatively immunopositive for caspase-3 indicating activation of caspase-dependent apoptosis in these cells. Morpholino gene knockdown of rip3 in pde6c(w59) embryos rescued the dying cone photoreceptors by inhibiting the formation of reactive oxygen species and by inhibiting second-order neuron remodelling in the inner retina. In rip3 morphant larvae, visual function was restored in the cones by upregulation of the rod phosphodiesterase genes (pde6a and pde6b), compensating for the lack of cone pde6c suggesting that cones are able to adapt to their local environment. Furthermore, we demonstrated through pharmacological inhibition of RIP1 and RIP3 activity that cone cell death was also delayed. Collectively, these results demonstrate that the underlying mechanism of cone cell death in the pde6c(w59) mutant retina is through necroptosis, whereas rod photoreceptor bystander death occurs through a caspase-dependent mechanism. This suggests that targeting the RIP kinase signalling pathway could be an effective therapeutic intervention in retinal degeneration patients. As bystander cell death is an important feature of many retinal diseases, combinatorial approaches targeting different cell death pathways may evolve as an important general principle in treatment.

PDE5 inhibitors blunt inflammation in human BPH: a potential mechanism of action for PDE5 inhibitors in LUTS.

Science.gov (United States)

Vignozzi, Linda; Gacci, Mauro; Cellai, Ilaria; Morelli, Annamaria; Maneschi, Elena; Comeglio, Paolo; Santi, Raffaella; Filippi, Sandra; Sebastianelli, Arcangelo; Nesi, Gabriella; Serni, Sergio; Carini, Marco; Maggi, Mario

2013-09-01

Metabolic syndrome (MetS) and benign prostate hyperplasia (BPH)/low urinary tract symptoms (LUTS) are often comorbid. Chronic inflammation is one of the putative links between these diseases. Phosphodiesterase type 5 inhibitors (PDE5i) are recognized as an effective treatment of BPH-related LUTS. One proposed mechanism of action of PDE5 is the inhibition of intraprostatic inflammation. In this study we investigate whether PDE5i could blunt inflammation in the human prostate. Evaluation of the effect of tadalafil and vardenafil on secretion of interleukin 8 (IL-8, a surrogate marker of prostate inflammation) by human myofibroblast prostatic cells (hBPH) exposed to different inflammatory stimuli. We preliminary evaluate histological features of prostatic inflammatory infiltrates in BPH patients enrolled in a randomized, double bind, placebo controlled study aimed at investigating the efficacy of vardenafil (10 mg/day, for 12 weeks) on BPH/LUTS. In vitro treatment with tadalafil or vardenafil on hBPH reduced IL-8 secretion induced by either TNFα or metabolic factors, including oxidized low-density lipoprotein, oxLDL, to the same extent as a PDE5-insensitive PKG agonist Sp-8-Br-PET-cGMP. These effects were reverted by the PKG inhibitor KT5823, suggesting a cGMP/PKG-dependency. Treatment with tadalafil or vardenafil significantly suppressed oxLDL receptor (LOX-1) expression. Histological evaluation of anti-CD45 staining (CD45 score) in prostatectomy specimens of BPH patients showed a positive association with MetS severity. Reduced HDL-cholesterol and elevated triglycerides were the only MetS factors significantly associated with CD45 score. In the MetS cohort there was a significant lower CD45 score in the vardenafil-arm versus the placebo-one. © 2013 Wiley Periodicals, Inc.

A simple two stage optimization algorithm for constrained power economic dispatch

International Nuclear Information System (INIS)

Huang, G.; Song, K.

1994-01-01

A simple two stage optimization algorithm is proposed and investigated for fast computation of constrained power economic dispatch control problems. The method is a simple demonstration of the hierarchical aggregation-disaggregation (HAD) concept. The algorithm first solves an aggregated problem to obtain an initial solution. This aggregated problem turns out to be classical economic dispatch formulation, and it can be solved in 1% of overall computation time. In the second stage, linear programming method finds optimal solution which satisfies power balance constraints, generation and transmission inequality constraints and security constraints. Implementation of the algorithm for IEEE systems and EPRI Scenario systems shows that the two stage method obtains average speedup ratio 10.64 as compared to classical LP-based method

Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing

Science.gov (United States)

Ono, Masahiro; Kuwata, Yoshiaki

2013-01-01

A chance-constrained dynamic programming algorithm was developed that is capable of making optimal sequential decisions within a user-specified risk bound. This work handles stochastic uncertainties over multiple stages in the CEMAT (Combined EDL-Mobility Analyses Tool) framework. It was demonstrated by a simulation of Mars entry, descent, and landing (EDL) using real landscape data obtained from the Mars Reconnaissance Orbiter. Although standard dynamic programming (DP) provides a general framework for optimal sequential decisionmaking under uncertainty, it typically achieves risk aversion by imposing an arbitrary penalty on failure states. Such a penalty-based approach cannot explicitly bound the probability of mission failure. A key idea behind the new approach is called risk allocation, which decomposes a joint chance constraint into a set of individual chance constraints and distributes risk over them. The joint chance constraint was reformulated into a constraint on an expectation over a sum of an indicator function, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the chance-constraint optimization problem can be turned into an unconstrained optimization over a Lagrangian, which can be solved efficiently using a standard DP approach.

Mutation in rod PDE6 linked to congenital stationary night blindness impairs the enzyme inhibition by its gamma-subunit.

Science.gov (United States)

Muradov, Khakim G; Granovsky, Alexey E; Artemyev, Nikolai O

2003-03-25

Photoreceptor cGMP phosphodiesterase (PDE6) is the effector enzyme in the vertebrate visual transduction cascade. The activity of rod PDE6 catalytic alpha- and beta-subunits is blocked in the dark by two inhibitory Pgamma-subunits. The inhibition is released upon light-stimulation of photoreceptor cells. Mutation H258N in PDE6beta has been linked to congenital stationary night blindness (CSNB) in a large Danish family (Rambusch pedigree) (Gal, A., Orth, U., Baehr, W., Schwinger, E., and Rosenberg, T. (1994) Nat. Genet. 7, 64-67.) We have analyzed the consequences of this mutation for PDE6 function using a Pgamma-sensitive PDE6alpha'/PDE5 chimera, Chi16. Biochemical analysis of the H257N mutant, an equivalent of PDE6betaH258N, demonstrates that this substitution does not alter the ability of chimeric PDE to dimerize or the enzyme's catalytic properties. The sensitivity of H257N to a competitive inhibitor zaprinast was also unaffected. However, the mutant displayed a significant impairment in the inhibitory interaction with Pgamma, which was apparent from a approximately 20-fold increase in the K(i) value (46 nM) and incomplete maximal inhibition. The inhibitory defect of H257N is not due to perturbation of noncatalytic cGMP binding to the PDE6alpha' GAF domains. The noncatalytic cGMP-binding characteristics of the H257N mutant were similar to those of the parent PDE6alpha'/PDE5 chimera. Since rod PDE6 in the Rambusch CSNB is a catalytic heterodimer of the wild-type PDE6alpha and mutant PDE6beta, Chi16 and H257N were coexpressed, and a heterodimeric PDE, Chi16/H257N, was isolated. It displayed two Pgamma inhibitory sites with the K(i) values of 5 and 57 nM. Our results support the hypothesis that mutation H258N in PDE6beta causes CSNB through incomplete inhibition of PDE6 activity by Pgamma, which leads to desensitization of rod photoreceptors.

Output Feedback-Based Boundary Control of Uncertain Coupled Semilinear Parabolic PDE Using Neurodynamic Programming.

Science.gov (United States)

Talaei, Behzad; Jagannathan, Sarangapani; Singler, John

2018-04-01

In this paper, neurodynamic programming-based output feedback boundary control of distributed parameter systems governed by uncertain coupled semilinear parabolic partial differential equations (PDEs) under Neumann or Dirichlet boundary control conditions is introduced. First, Hamilton-Jacobi-Bellman (HJB) equation is formulated in the original PDE domain and the optimal control policy is derived using the value functional as the solution of the HJB equation. Subsequently, a novel observer is developed to estimate the system states given the uncertain nonlinearity in PDE dynamics and measured outputs. Consequently, the suboptimal boundary control policy is obtained by forward-in-time estimation of the value functional using a neural network (NN)-based online approximator and estimated state vector obtained from the NN observer. Novel adaptive tuning laws in continuous time are proposed for learning the value functional online to satisfy the HJB equation along system trajectories while ensuring the closed-loop stability. Local uniformly ultimate boundedness of the closed-loop system is verified by using Lyapunov theory. The performance of the proposed controller is verified via simulation on an unstable coupled diffusion reaction process.

Optimal dispatch in dynamic security constrained open power market

International Nuclear Information System (INIS)

Singh, S.N.; David, A.K.

2002-01-01

Power system security is a new concern in the competitive power market operation, because the integration of the system controller and the generation owner has been broken. This paper presents an approach for dynamic security constrained optimal dispatch in restructured power market environment. The transient energy margin using transient energy function (TEF) approach has been used to calculate the stability margin of the system and a hybrid method is applied to calculate the approximate unstable equilibrium point (UEP) that is used to calculate the exact UEP and thus, the energy margin using TEF. The case study results illustrated on two systems shows that the operating mechanisms are compatible with the new business environment. (author)

Robust and Reliable Portfolio Optimization Formulation of a Chance Constrained Problem

Directory of Open Access Journals (Sweden)

Sengupta Raghu Nandan

2017-02-01

Full Text Available We solve a linear chance constrained portfolio optimization problem using Robust Optimization (RO method wherein financial script/asset loss return distributions are considered as extreme valued. The objective function is a convex combination of portfolio’s CVaR and expected value of loss return, subject to a set of randomly perturbed chance constraints with specified probability values. The robust deterministic counterpart of the model takes the form of Second Order Cone Programming (SOCP problem. Results from extensive simulation runs show the efficacy of our proposed models, as it helps the investor to (i utilize extensive simulation studies to draw insights into the effect of randomness in portfolio decision making process, (ii incorporate different risk appetite scenarios to find the optimal solutions for the financial portfolio allocation problem and (iii compare the risk and return profiles of the investments made in both deterministic as well as in uncertain and highly volatile financial markets.

JuPOETs: a constrained multiobjective optimization approach to estimate biochemical model ensembles in the Julia programming language.

Science.gov (United States)

Bassen, David M; Vilkhovoy, Michael; Minot, Mason; Butcher, Jonathan T; Varner, Jeffrey D

2017-01-25

Ensemble modeling is a promising approach for obtaining robust predictions and coarse grained population behavior in deterministic mathematical models. Ensemble approaches address model uncertainty by using parameter or model families instead of single best-fit parameters or fixed model structures. Parameter ensembles can be selected based upon simulation error, along with other criteria such as diversity or steady-state performance. Simulations using parameter ensembles can estimate confidence intervals on model variables, and robustly constrain model predictions, despite having many poorly constrained parameters. In this software note, we present a multiobjective based technique to estimate parameter or models ensembles, the Pareto Optimal Ensemble Technique in the Julia programming language (JuPOETs). JuPOETs integrates simulated annealing with Pareto optimality to estimate ensembles on or near the optimal tradeoff surface between competing training objectives. We demonstrate JuPOETs on a suite of multiobjective problems, including test functions with parameter bounds and system constraints as well as for the identification of a proof-of-concept biochemical model with four conflicting training objectives. JuPOETs identified optimal or near optimal solutions approximately six-fold faster than a corresponding implementation in Octave for the suite of test functions. For the proof-of-concept biochemical model, JuPOETs produced an ensemble of parameters that gave both the mean of the training data for conflicting data sets, while simultaneously estimating parameter sets that performed well on each of the individual objective functions. JuPOETs is a promising approach for the estimation of parameter and model ensembles using multiobjective optimization. JuPOETs can be adapted to solve many problem types, including mixed binary and continuous variable types, bilevel optimization problems and constrained problems without altering the base algorithm. JuPOETs is open

Discovery of a novel orally active PDE-4 inhibitor effective in an ovalbumin-induced asthma murine model.

Science.gov (United States)

Kwak, Hyun Jeong; Nam, Ji Yeon; Song, Jin Sook; No, Zaesung; Yang, Sung Don; Cheon, Hyae Gyeong

2012-06-15

Phosphodiesterase-4 (PDE-4) is responsible for metabolizing adenosine 3',5'-cyclic monophosphate that reduces the activation of a wide range of inflammatory cells including eosinophils. PDE-4 inhibitors are under development for the treatment of respiratory diseases such as asthma and chronic obstructive pulmonary disease. Herein, we report a novel PDE-4 inhibitor, PDE-423 (3-[1-(3-cyclopropylmethoxy-4-difluoromethoxybenzyl)-1H-pyrazol-3-yl]-benzoic acid), which shows good in vitro and in vivo oral activities. PDE-423 exhibited in vitro IC(50)s of 140 nM and 550 nM in enzyme assay and cell-based assay, respectively. In vivo study using ovalbumin-induced asthmatic mice revealed that PDE-423 reduced methacholine-stimulated airway hyperreactivity in a dose-dependent manner by once daily oral administration (ED(50)=18.3 mg/kg), in parallel with decreased eosinophil peroxidase activity and improved lung histology. In addition, PDE-423 was effective in diminishing lipopolysaccharide-induced neutrophilia in vivo as well as in vitro. Oral administration of PDE-423 (100 mg/kg) had no effect on the duration of xylazine/ketamine-induced anesthesia and did not induce vomiting incidence in ferrets up to the dose of 1000 mg/kg. The present study indicates that a novel PDE-4 inhibitor, PDE-423, has good pharmacological profiles implicating this as a potential candidate for the development of a new anti-asthmatic drug. Copyright © 2012 Elsevier B.V. All rights reserved.

A boundary PDE feedback control approach for the stabilization of mortgage price dynamics

Science.gov (United States)

Rigatos, G.; Siano, P.; Sarno, D.

2017-11-01

Several transactions taking place in financial markets are dependent on the pricing of mortgages (loans for the purchase of residences, land or farms). In this article, a method for stabilization of mortgage price dynamics is developed. It is considered that mortgage prices follow a PDE model which is equivalent to a multi-asset Black-Scholes PDE. Actually it is a diffusion process evolving in a 2D assets space, where the first asset is the house price and the second asset is the interest rate. By applying semi-discretization and a finite differences scheme this multi-asset PDE is transformed into a state-space model consisting of ordinary nonlinear differential equations. For the local subsystems, into which the mortgage PDE is decomposed, it becomes possible to apply boundary-based feedback control. The controller design proceeds by showing that the state-space model of the mortgage price PDE stands for a differentially flat system. Next, for each subsystem which is related to a nonlinear ODE, a virtual control input is computed, that can invert the subsystem's dynamics and can eliminate the subsystem's tracking error. From the last row of the state-space description, the control input (boundary condition) that is actually applied to the multi-factor mortgage price PDE system is found. This control input contains recursively all virtual control inputs which were computed for the individual ODE subsystems associated with the previous rows of the state-space equation. Thus, by tracing the rows of the state-space model backwards, at each iteration of the control algorithm, one can finally obtain the control input that should be applied to the mortgage price PDE system so as to assure that all its state variables will converge to the desirable setpoints. By showing the feasibility of such a control method it is also proven that through selected modification of the PDE boundary conditions the price of the mortgage can be made to converge and stabilize at specific

Repercussão cardiovascular, com e sem álcool, do carbonato de lodenafila, um novo inibidor da PDE5 Repercusión cardiovascular, con y sin alcohol, del carbonato de lodenafila, un nuevo inhibidor de la PDE5 Cardiovascular repercussion of lodenafil carbonate, a new PDE5 inhibitor, with and without alcohol consumption

OpenAIRE

Adauto Carvalho Silva; Odaly Toffoletto; Luiz Antonio Galvão Lucio; Paula Ferreira dos Santos; Jorge Barros Afiune; João Massud Filho; Sergio Tufik

2010-01-01

FUNDAMENTO: A disfunção erétil afeta um grande número de homens no mundo e os inibidores de PDE 5 (iPDE5) estão entre os principais métodos de tratamento desses pacientes. O consumo social de álcool e o ato sexual apresentam uma relação considerável. Portanto, a associação entre álcool e iPDE5 pode ocorrer. O carbonato de lodenafila é um novo iPDE5 desenvolvido por uma empresa brasileira. OBJETIVO: Avaliar a repercussão cardiovascular do carbonato de lodenafila, associado ou não ao álcool, as...

Novel benzimidazole derivatives as phosphodiesterase 10A (PDE10A) inhibitors with improved metabolic stability.

Science.gov (United States)

Chino, Ayaka; Masuda, Naoyuki; Amano, Yasushi; Honbou, Kazuya; Mihara, Takuma; Yamazaki, Mayako; Tomishima, Masaki

2014-07-01

In this study, we report the identification of potent benzimidazoles as PDE10A inhibitors. We first identified imidazopyridine 1 as a high-throughput screening hit compound from an in-house library. Next, optimization of the imidazopyridine moiety to improve inhibitory activity gave imidazopyridinone 10b. Following further structure-activity relationship development by reducing lipophilicity and introducing substituents, we acquired 35, which exhibited both improved metabolic stability and reduced CYP3A4 time-dependent inhibition. Copyright © 2014. Published by Elsevier Ltd.

Stability Constrained Efficiency Optimization for Droop Controlled DC-DC Conversion System

DEFF Research Database (Denmark)

Meng, Lexuan; Dragicevic, Tomislav; Guerrero, Josep M.

2013-01-01

implementing tertiary regulation. Moreover, system dynamic is affected when shifting VRs. Therefore, the stability is considered in optimization by constraining the eigenvalues arising from dynamic state space model of the system. Genetic algorithm is used in searching for global efficiency optimum while....... As the efficiency of each converter changes with output power, virtual resistances (VRs) are set as decision variables for adjusting power sharing proportion among converters. It is noteworthy that apart from restoring the voltage deviation, secondary control plays an important role to stabilize dc bus voltage when...

Fast optimization of statistical potentials for structurally constrained phylogenetic models

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Rodrigue Nicolas

2009-09-01

Full Text Available Abstract Background Statistical approaches for protein design are relevant in the field of molecular evolutionary studies. In recent years, new, so-called structurally constrained (SC models of protein-coding sequence evolution have been proposed, which use statistical potentials to assess sequence-structure compatibility. In a previous work, we defined a statistical framework for optimizing knowledge-based potentials especially suited to SC models. Our method used the maximum likelihood principle and provided what we call the joint potentials. However, the method required numerical estimations by the use of computationally heavy Markov Chain Monte Carlo sampling algorithms. Results Here, we develop an alternative optimization procedure, based on a leave-one-out argument coupled to fast gradient descent algorithms. We assess that the leave-one-out potential yields very similar results to the joint approach developed previously, both in terms of the resulting potential parameters, and by Bayes factor evaluation in a phylogenetic context. On the other hand, the leave-one-out approach results in a considerable computational benefit (up to a 1,000 fold decrease in computational time for the optimization procedure. Conclusion Due to its computational speed, the optimization method we propose offers an attractive alternative for the design and empirical evaluation of alternative forms of potentials, using large data sets and high-dimensional parameterizations.

PDE5 Inhibitors As Potential Tools In The Treatment Of Cystic Fibrosis

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Sabrina eNoel

2012-09-01

Full Text Available Despite great advances in the understanding of the genetics and pathophysiology of cystic fibrosis (CF, there is still no cure for the disease. Using phosphodiesterase type 5 (PDE5 inhibitors, we and others have provided evidence of rescued F508del-CFTR trafficking and corrected deficient chloride transport activity. Studies using PDE5 inhibitors in mice homozygous for the clinically relevant F508del mutation have been conducted with the aim of restoring F508del-CFTR protein function. We demonstrated, by measuring transepithelial nasal potential difference in F508del mice following intraperitoneal injection of sildenafil, vardenafil or taladafil at clinical doses are able to restore the decreased CFTR-dependent chloride transport across the nasal mucosa. Moreover, vardenafil, but not sildenafil, stimulates chloride transport through the normal CFTR protein. We developed a specific nebulizer setup for mice, with which we demonstrated, through a single inhalation of PDE5 inhibitors, local activation of CFTR protein in CF. Significant potential advantages of inhalation drug therapy over oral or intravenous routes include rapid onset of pharmacological action, reduced systemic secondary effects and reduced effective drug doses compared to the drug delivered orally; this underlines the relevance and impact of our work for translational science. More recently, we analyzed the bronchoalveolar lavage of CF and wild-type mice for cell infiltrates and expression of pro-inflammatory cytokines and chemokines; we found that the CFTR activating effect of vardenafil, selected as a representative long-lasting PDE5 inhibitor, breaks the vicious circle of lung inflammation which plays a major role in morbi-mortality in CF. Our data highlight the potential use of PDE5 inhibitors in CF. Therapeutic approaches using clinically approved PDE5 inhibitors to address F508del-CFTR defects could speed up the development of new therapies for CF.

Optimization of Regional Geodynamic Models for Mantle Dynamics

Science.gov (United States)

Knepley, M.; Isaac, T.; Jadamec, M. A.

2016-12-01

The SubductionGenerator program is used to construct high resolution, 3D regional thermal structures for mantle convection simulations using a variety of data sources, including sea floor ages and geographically referenced 3D slab locations based on seismic observations. The initial bulk temperature field is constructed using a half-space cooling model or plate cooling model, and related smoothing functions based on a diffusion length-scale analysis. In this work, we seek to improve the 3D thermal model and test different model geometries and dynamically driven flow fields using constraints from observed seismic velocities and plate motions. Through a formal adjoint analysis, we construct the primal-dual version of the multi-objective PDE-constrained optimization problem for the plate motions and seismic misfit. We have efficient, scalable preconditioners for both the forward and adjoint problems based upon a block preconditioning strategy, and a simple gradient update is used to improve the control residual. The full optimal control problem is formulated on a nested hierarchy of grids, allowing a nonlinear multigrid method to accelerate the solution.

Stochastic Averaging for Constrained Optimization With Application to Online Resource Allocation

Science.gov (United States)

Chen, Tianyi; Mokhtari, Aryan; Wang, Xin; Ribeiro, Alejandro; Giannakis, Georgios B.

2017-06-01

Existing approaches to resource allocation for nowadays stochastic networks are challenged to meet fast convergence and tolerable delay requirements. The present paper leverages online learning advances to facilitate stochastic resource allocation tasks. By recognizing the central role of Lagrange multipliers, the underlying constrained optimization problem is formulated as a machine learning task involving both training and operational modes, with the goal of learning the sought multipliers in a fast and efficient manner. To this end, an order-optimal offline learning approach is developed first for batch training, and it is then generalized to the online setting with a procedure termed learn-and-adapt. The novel resource allocation protocol permeates benefits of stochastic approximation and statistical learning to obtain low-complexity online updates with learning errors close to the statistical accuracy limits, while still preserving adaptation performance, which in the stochastic network optimization context guarantees queue stability. Analysis and simulated tests demonstrate that the proposed data-driven approach improves the delay and convergence performance of existing resource allocation schemes.

Generation and reserve dispatch in a competitive market using constrained particle swarm optimization

International Nuclear Information System (INIS)

Azadani, E. Nasr; Hosseinian, S.H.; Moradzadeh, B.

2010-01-01

Competitive bidding for energy and ancillary services is increasingly recognized as an important part of electricity markets. In addition, the transmission capacity limits should be considered to optimize the total market cost. In this paper, a new approach based on constrained particle swarm optimization (CPSO) is developed to deal with the multi-product (energy and reserve) and multi-area electricity market dispatch problem. Constraint handling is based on particle ranking and uniform distribution. CPSO method offers a new solution for optimizing the total market cost in a multi-area competitive electricity market considering the system constraints. The proposed technique shows promising performance for smooth and non smooth cost function as well. Three different systems are examined to demonstrate the effectiveness and the accuracy of the proposed algorithm. (author)

Molecular Bases of PDE4D Inhibition by Memory-Enhancing GEBR Library Compounds.

Science.gov (United States)

Prosdocimi, Tommaso; Mollica, Luca; Donini, Stefano; Semrau, Marta S; Lucarelli, Anna Paola; Aiolfi, Egidio; Cavalli, Andrea; Storici, Paola; Alfei, Silvana; Brullo, Chiara; Bruno, Olga; Parisini, Emilio

2018-05-01

Selected members of the large rolipram-related GEBR family of type 4 phosphodiesterase (PDE4) inhibitors have been shown to facilitate long-term potentiation and to improve memory functions without causing emetic-like behavior in rodents. Despite their micromolar-range binding affinities and their promising pharmacological and toxicological profiles, few if any structure-activity relationship studies have been performed to elucidate the molecular bases of their action. Here, we report the crystal structure of a number of GEBR library compounds in complex with the catalytic domain of PDE4D as well as their inhibitory profiles for both the long PDE4D3 isoform and the catalytic domain alone. Furthermore, we assessed the stability of the observed ligand conformations in the context of the intact enzyme using molecular dynamics simulations. The longer and more flexible ligands appear to be capable of forming contacts with the regulatory portion of the enzyme, thus possibly allowing some degree of selectivity between the different PDE4 isoforms.

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

Science.gov (United States)

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.

Memory and Energy Optimization Strategies for Multithreaded Operating System on the Resource-Constrained Wireless Sensor Node

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Xing Liu

2014-12-01

Full Text Available Memory and energy optimization strategies are essential for the resource-constrained wireless sensor network (WSN nodes. In this article, a new memory-optimized and energy-optimized multithreaded WSN operating system (OS LiveOS is designed and implemented. Memory cost of LiveOS is optimized by using the stack-shifting hybrid scheduling approach. Different from the traditional multithreaded OS in which thread stacks are allocated statically by the pre-reservation, thread stacks in LiveOS are allocated dynamically by using the stack-shifting technique. As a result, memory waste problems caused by the static pre-reservation can be avoided. In addition to the stack-shifting dynamic allocation approach, the hybrid scheduling mechanism which can decrease both the thread scheduling overhead and the thread stack number is also implemented in LiveOS. With these mechanisms, the stack memory cost of LiveOS can be reduced more than 50% if compared to that of a traditional multithreaded OS. Not is memory cost optimized, but also the energy cost is optimized in LiveOS, and this is achieved by using the multi-core “context aware” and multi-core “power-off/wakeup” energy conservation approaches. By using these approaches, energy cost of LiveOS can be reduced more than 30% when compared to the single-core WSN system. Memory and energy optimization strategies in LiveOS not only prolong the lifetime of WSN nodes, but also make the multithreaded OS feasible to run on the memory-constrained WSN nodes.

PDE 7 inhibitors: new potential drugs for the therapy of spinal cord injury.

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Irene Paterniti

Full Text Available BACKGROUND: Primary traumatic mechanical injury to the spinal cord (SCI causes the death of a number of neurons that to date can neither be recovered nor regenerated. During the last years our group has been involved in the design, synthesis and evaluation of PDE7 inhibitors as new innovative drugs for several neurological disorders. Our working hypothesis is based on two different facts. Firstly, neuroinflammation is modulated by cAMP levels, thus the key role for phosphodiesterases (PDEs, which hydrolyze cAMP, is undoubtedly demonstrated. On the other hand, PDE7 is expressed simultaneously on leukocytes and on the brain, highlighting the potential crucial role of PDE7 as drug target for neuroinflammation. METHODOLOGY/PRINCIPAL FINDINGS: Here we present two chemically diverse families of PDE7 inhibitors, designed using computational techniques such as virtual screening and neuronal networks. We report their biological profile and their efficacy in an experimental SCI model induced by the application of vascular clips (force of 24 g to the dura via a four-level T5-T8 laminectomy. We have selected two candidates, namely S14 and VP1.15, as PDE7 inhibitors. These compounds increase cAMP production both in macrophage and neuronal cell lines. Regarding drug-like properties, compounds were able to cross the blood brain barrier using parallel artificial membranes (PAMPA methodology. SCI in mice resulted in severe trauma characterized by edema, neutrophil infiltration, and production of a range of inflammatory mediators, tissue damage, and apoptosis. Treatment of the mice with S14 and VP1.15, two PDE7 inhibitors, significantly reduced the degree of spinal cord inflammation, tissue injury (histological score, and TNF-α, IL-6, COX-2 and iNOS expression. CONCLUSIONS/SIGNIFICANCE: All these data together led us to propose PDE7 inhibitors, and specifically S14 and VP1.15, as potential drug candidates to be further studied for the treatment of SCI.

A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty

Science.gov (United States)

Zhang, Chenglong; Guo, Ping

2017-10-01

The vague and fuzzy parametric information is a challenging issue in irrigation water management problems. In response to this problem, a generalized fuzzy credibility-constrained linear fractional programming (GFCCFP) model is developed for optimal irrigation water allocation under uncertainty. The model can be derived from integrating generalized fuzzy credibility-constrained programming (GFCCP) into a linear fractional programming (LFP) optimization framework. Therefore, it can solve ratio optimization problems associated with fuzzy parameters, and examine the variation of results under different credibility levels and weight coefficients of possibility and necessary. It has advantages in: (1) balancing the economic and resources objectives directly; (2) analyzing system efficiency; (3) generating more flexible decision solutions by giving different credibility levels and weight coefficients of possibility and (4) supporting in-depth analysis of the interrelationships among system efficiency, credibility level and weight coefficient. The model is applied to a case study of irrigation water allocation in the middle reaches of Heihe River Basin, northwest China. Therefore, optimal irrigation water allocation solutions from the GFCCFP model can be obtained. Moreover, factorial analysis on the two parameters (i.e. λ and γ) indicates that the weight coefficient is a main factor compared with credibility level for system efficiency. These results can be effective for support reasonable irrigation water resources management and agricultural production.

Topology Optimization for Minimizing the Resonant Response of Plates with Constrained Layer Damping Treatment

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Zhanpeng Fang

2015-01-01

Full Text Available A topology optimization method is proposed to minimize the resonant response of plates with constrained layer damping (CLD treatment under specified broadband harmonic excitations. The topology optimization problem is formulated and the square of displacement resonant response in frequency domain at the specified point is considered as the objective function. Two sensitivity analysis methods are investigated and discussed. The derivative of modal damp ratio is not considered in the conventional sensitivity analysis method. An improved sensitivity analysis method considering the derivative of modal damp ratio is developed to improve the computational accuracy of the sensitivity. The evolutionary structural optimization (ESO method is used to search the optimal layout of CLD material on plates. Numerical examples and experimental results show that the optimal layout of CLD treatment on the plate from the proposed topology optimization using the conventional sensitivity analysis or the improved sensitivity analysis can reduce the displacement resonant response. However, the optimization method using the improved sensitivity analysis can produce a higher modal damping ratio than that using the conventional sensitivity analysis and develop a smaller displacement resonant response.

Phosphodiesterase profile of human B lymphocytes from normal and atopic donors and the effects of PDE inhibition on B cell proliferation

Science.gov (United States)

Gantner, Florian; Götz, Christine; Gekeler, Volker; Schudt, Christian; Wendel, Albrecht; Hatzelmann, Armin

1998-01-01

CD19+ B lymphocytes were purified from the peripheral blood of normal and atopic subjects to analyse and compare the phosphodiesterase (PDE) activity profile, PDE mRNA expression and the importance of PDE activity for the regulation of B cell function.The majority of cyclic AMP hydrolyzing activity of human B cells was cytosolic PDE4, followed by cytosolic PDE7-like activity; marginal PDE3 activity was found only in the particulate B cell fraction. PDE1, PDE2 and PDE5 activities were not detected.By cDNA-PCR analysis mRNA of the PDE4 subtypes A, B (splice variant PDE4B2) and D were detected. In addition, a weak signal for PDE3A was found.No differences in PDE activities or mRNA expression of PDE subtypes were found in B cells from either normal or atopic subjects.Stimulation of B lymphocytes with the polyclonal stimulus lipopolysaccharide (LPS) induced a proliferative response in a time- and concentration-dependent manner, which was increased in the presence of interleukin-4 (IL-4). PDE4 inhibitors (rolipram, piclamilast) led to an increase in the cellular cyclic AMP concentration and to an augmentation of proliferation, whereas a PDE3 inhibitor (motapizone) was ineffective, which is in accordance with the PDE profile found. The proliferation enhancing effect of the PDE4 inhibitors was partly mimicked by the cyclic AMP analogues dibutyryl (db) cyclic AMP and 5,6-dichloro-1-β-D-ribofuranosylbenzimidazole-3′,5′-cyclic monophosphorothioate, Sp-isomer (dcl-cBIMPS), respectively. However, at concentrations exceeding 100 μM db-cyclic AMP suppressed B lymphocyte proliferation, probably as a result of cytotoxicity. Prostaglandin E2 (PGE2, 1 μM) and forskolin (10 μM) did not affect B cell proliferation, even when given in combination with rolipram.Inhibition of protein kinase A (PKA) by differentially acting selective inhibitors (KT 5720, Rp-8-Br-cyclic AMPS) decreased the proliferative response of control cells and reversed the proliferation enhancing effects

Pareto-optimal estimates that constrain mean California precipitation change

Science.gov (United States)

Langenbrunner, B.; Neelin, J. D.

2017-12-01

Global climate model (GCM) projections of greenhouse gas-induced precipitation change can exhibit notable uncertainty at the regional scale, particularly in regions where the mean change is small compared to internal variability. This is especially true for California, which is located in a transition zone between robust precipitation increases to the north and decreases to the south, and where GCMs from the Climate Model Intercomparison Project phase 5 (CMIP5) archive show no consensus on mean change (in either magnitude or sign) across the central and southern parts of the state. With the goal of constraining this uncertainty, we apply a multiobjective approach to a large set of subensembles (subsets of models from the full CMIP5 ensemble). These constraints are based on subensemble performance in three fields important to California precipitation: tropical Pacific sea surface temperatures, upper-level zonal winds in the midlatitude Pacific, and precipitation over the state. An evolutionary algorithm is used to sort through and identify the set of Pareto-optimal subensembles across these three measures in the historical climatology, and we use this information to constrain end-of-century California wet season precipitation change. This technique narrows the range of projections throughout the state and increases confidence in estimates of positive mean change. Furthermore, these methods complement and generalize emergent constraint approaches that aim to restrict uncertainty in end-of-century projections, and they have applications to even broader aspects of uncertainty quantification, including parameter sensitivity and model calibration.

SU-E-I-23: A General KV Constrained Optimization of CNR for CT Abdominal Imaging

International Nuclear Information System (INIS)

Weir, V; Zhang, J

2015-01-01

Purpose: While Tube current modulation has been well accepted for CT dose reduction, kV adjusting in clinical settings is still at its early stage. This is mainly due to the limited kV options of most current CT scanners. kV adjusting can potentially reduce radiation dose and optimize image quality. This study is to optimize CT abdomen imaging acquisition based on the assumption of a continuous kV, with the goal to provide the best contrast to noise ratio (CNR). Methods: For a given dose (CTDIvol) level, the CNRs at different kV and pitches were measured with an ACR GAMMEX phantom. The phantom was scanned in a Siemens Sensation 64 scanner and a GE VCT 64 scanner. A constrained mathematical optimization was used to find the kV which led to the highest CNR for the anatomy and pitch setting. Parametric equations were obtained from polynomial fitting of plots of kVs vs CNRs. A suitable constraint region for optimization was chosen. Subsequent optimization yielded a peak CNR at a particular kV for different collimations and pitch setting. Results: The constrained mathematical optimization approach yields kV of 114.83 and 113.46, with CNRs of 1.27 and 1.11 at the pitch of 1.2 and 1.4, respectively, for the Siemens Sensation 64 scanner with the collimation of 32 x 0.625mm. An optimized kV of 134.25 and 1.51 CNR is obtained for a GE VCT 64 slice scanner with a collimation of 32 x 0.625mm and a pitch of 0.969. At 0.516 pitch and 32 x 0.625 mm an optimized kV of 133.75 and a CNR of 1.14 was found for the GE VCT 64 slice scanner. Conclusion: CNR in CT image acquisition can be further optimized with a continuous kV option instead of current discrete or fixed kV settings. A continuous kV option is a key for individualized CT protocols

SU-E-I-23: A General KV Constrained Optimization of CNR for CT Abdominal Imaging

Energy Technology Data Exchange (ETDEWEB)

Weir, V; Zhang, J [University of Kentucky, Lexington, KY (United States)

2015-06-15

Purpose: While Tube current modulation has been well accepted for CT dose reduction, kV adjusting in clinical settings is still at its early stage. This is mainly due to the limited kV options of most current CT scanners. kV adjusting can potentially reduce radiation dose and optimize image quality. This study is to optimize CT abdomen imaging acquisition based on the assumption of a continuous kV, with the goal to provide the best contrast to noise ratio (CNR). Methods: For a given dose (CTDIvol) level, the CNRs at different kV and pitches were measured with an ACR GAMMEX phantom. The phantom was scanned in a Siemens Sensation 64 scanner and a GE VCT 64 scanner. A constrained mathematical optimization was used to find the kV which led to the highest CNR for the anatomy and pitch setting. Parametric equations were obtained from polynomial fitting of plots of kVs vs CNRs. A suitable constraint region for optimization was chosen. Subsequent optimization yielded a peak CNR at a particular kV for different collimations and pitch setting. Results: The constrained mathematical optimization approach yields kV of 114.83 and 113.46, with CNRs of 1.27 and 1.11 at the pitch of 1.2 and 1.4, respectively, for the Siemens Sensation 64 scanner with the collimation of 32 x 0.625mm. An optimized kV of 134.25 and 1.51 CNR is obtained for a GE VCT 64 slice scanner with a collimation of 32 x 0.625mm and a pitch of 0.969. At 0.516 pitch and 32 x 0.625 mm an optimized kV of 133.75 and a CNR of 1.14 was found for the GE VCT 64 slice scanner. Conclusion: CNR in CT image acquisition can be further optimized with a continuous kV option instead of current discrete or fixed kV settings. A continuous kV option is a key for individualized CT protocols.

Decreased catalytic activity and altered activation properties of PDE6C mutants associated with autosomal recessive achromatopsia

DEFF Research Database (Denmark)

Grau, Tanja; Artemyev, Nikolai O; Rosenberg, Thomas

2011-01-01

study on PDE6C mutations including the mutation spectrum, its prevalence in a large cohort of ACHM/cone dysfunction patients, the clinical phenotype and the functional characterization of mutant PDE6C proteins. Twelve affected patients from seven independent families segregating PDE6C mutations were......Mutations in the gene encoding the catalytic subunit of the cone photoreceptor phosphodiesterase (PDE6C) have been recently reported in patients with autosomal recessive inherited achromatopsia (ACHM) and early-onset cone photoreceptor dysfunction. Here we present the results of a comprehensive...... identified in our total patient cohort of 492 independent families. Eleven different PDE6C mutations were found including two nonsense mutations, three mutations affecting transcript splicing as shown by minigene assays, one 1 bp-insertion and five missense mutations. We also performed a detailed functional...

Frequent phosphodiesterase 11A gene (PDE11A) defects in patients with Carney complex (CNC) caused by PRKAR1A mutations: PDE11A may contribute to adrenal and testicular tumors in CNC as a modifier of the phenotype.

Science.gov (United States)

Libé, Rossella; Horvath, Anelia; Vezzosi, Delphine; Fratticci, Amato; Coste, Joel; Perlemoine, Karine; Ragazzon, Bruno; Guillaud-Bataille, Marine; Groussin, Lionel; Clauser, Eric; Raffin-Sanson, Marie-Laure; Siegel, Jennifer; Moran, Jason; Drori-Herishanu, Limor; Faucz, Fabio Rueda; Lodish, Maya; Nesterova, Maria; Bertagna, Xavier; Bertherat, Jerome; Stratakis, Constantine A

2011-01-01

Carney complex (CNC) is an autosomal dominant multiple neoplasia, caused mostly by inactivating mutations of the regulatory subunit 1A of the protein kinase A (PRKAR1A). Primary pigmented nodular adrenocortical disease (PPNAD) is the most frequent endocrine manifestation of CNC with a great inter-individual variability. Germline, protein-truncating mutations of phosphodiesterase type 11A (PDE11A) have been described to predispose to a variety of endocrine tumors, including adrenal and testicular tumors. Our objective was to investigate the role of PDE11A as a possible gene modifier of the phenotype in a series of 150 patients with CNC. A higher frequency of PDE11A variants in patients with CNC compared with healthy controls was found (25.3 vs. 6.8%, P CNC patients, those with PPNAD were significantly more frequently carriers of PDE11A variants compared with patients without PPNAD (30.8 vs. 13%, P = 0.025). Furthermore, men with PPNAD were significantly more frequently carriers of PDE11A sequence variants (40.7%) than women with PPNAD (27.3%) (P CNC patients, a high frequency of PDE11A variants, suggesting that PDE11A is a genetic modifying factor for the development of testicular and adrenal tumors in patients with germline PRKAR1A mutation.

Fragment-Based Discovery of Pyrimido[1,2-b]indazole PDE10A Inhibitors.

Science.gov (United States)

Chino, Ayaka; Seo, Ryushi; Amano, Yasushi; Namatame, Ichiji; Hamaguchi, Wataru; Honbou, Kazuya; Mihara, Takuma; Yamazaki, Mayako; Tomishima, Masaki; Masuda, Naoyuki

2018-01-01

In this study, we report the identification of potent pyrimidoindazoles as phosphodiesterase10A (PDE10A) inhibitors by using the method of fragment-based drug discovery (FBDD). The pyrazolopyridine derivative 2 was found to be a fragment hit compound which could occupy a part of the binding site of PDE10A enzyme by using the method of the X-ray co-crystal structure analysis. On the basis of the crystal structure of compound 2 and PDE10A protein, a number of compounds were synthesized and evaluated, by means of structure-activity relationship (SAR) studies, which culminated in the discovery of a novel pyrimidoindazole derivative 13 having good physicochemical properties.

Mini-batch optimized full waveform inversion with geological constrained gradient filtering

Science.gov (United States)

Yang, Hui; Jia, Junxiong; Wu, Bangyu; Gao, Jinghuai

2018-05-01

High computation cost and generating solutions without geological sense have hindered the wide application of Full Waveform Inversion (FWI). Source encoding technique is a way to dramatically reduce the cost of FWI but subject to fix-spread acquisition setup requirement and slow convergence for the suppression of cross-talk. Traditionally, gradient regularization or preconditioning is applied to mitigate the ill-posedness. An isotropic smoothing filter applied on gradients generally gives non-geological inversion results, and could also introduce artifacts. In this work, we propose to address both the efficiency and ill-posedness of FWI by a geological constrained mini-batch gradient optimization method. The mini-batch gradient descent optimization is adopted to reduce the computation time by choosing a subset of entire shots for each iteration. By jointly applying the structure-oriented smoothing to the mini-batch gradient, the inversion converges faster and gives results with more geological meaning. Stylized Marmousi model is used to show the performance of the proposed method on realistic synthetic model.

Electrochemomechanical constrained multiobjective optimization of PPy/MWCNT actuators

International Nuclear Information System (INIS)

Khalili, N; Naguib, H E; Kwon, R H

2014-01-01

Polypyrrole (PPy) conducting polymers have shown a great potential for the fabrication of conjugated polymer-based actuating devices. Consequently, they have been a key point in developing many advanced emerging applications such as biomedical devices and biomimetic robotics. When designing an actuator, taking all of the related decision variables, their roles and relationships into consideration is of pivotal importance to determine the actuator’s final performance. Therefore, the central focus of this study is to develop an electrochemomechanical constrained multiobjective optimization model of a PPy/MWCNTs trilayer actuator. For this purpose, the objective functions are designed to capture the three main characteristics of these actuators, namely their tip vertical displacement, blocking force and response time. To obtain the optimum range of the designated decision variables within the feasible domain, a multiobjective optimization algorithm is applied while appropriate constraints are imposed. The optimum points form a Pareto surface on which they are consistently spread. The numerical results are presented; these results enable one to design an actuator with consideration to the desired output performances. For the experimental analysis, a multilayer bending-type actuator is fabricated, which is composed of a PVDF layer and two layers of PPy with an incorporated layer of multi-walled carbon nanotubes deposited on each side of the PVDF membrane. The numerical results are experimentally verified; in order to determine the performance of the fabricated actuator, its outputs are compared with a neat PPy actuator’s experimental and numerical counterparts. (paper)

Constrained multi-objective optimization of radial expanders in organic Rankine cycles by firefly algorithm

International Nuclear Information System (INIS)

Bahadormanesh, Nikrouz; Rahat, Shayan; Yarali, Milad

2017-01-01

Highlights: • A multi-objective optimization for radial expander in Organic Rankine Cycles is implemented. • By using firefly algorithm, Pareto front based on the size of turbine and thermal efficiency is produced. • Tension and vibration constrains have a significant effect on optimum design points. - Abstract: Organic Rankine Cycles are viable energy conversion systems in sustainable energy systems due to their compatibility with low-temperature heat sources. In the present study, one dimensional model of radial expanders in conjunction with a thermodynamic model of organic Rankine cycles is prepared. After verification, by defining thermal efficiency of the cycle and size parameter of a radial turbine as the objective functions, a multi-objective optimization was conducted regarding tension and vibration constraints for 4 different organic working fluids (R22, R245fa, R236fa and N-Pentane). In addition to mass flow rate, evaporator temperature, maximum pressure of cycle and turbo-machinery design parameters are selected as the decision variables. Regarding Pareto fronts, by a little increase in size of radial expanders, it is feasible to reach high efficiency. Moreover, by assessing the distribution of decision variables, the variables that play a major role in trending between the objective functions are found. Effects of mechanical and vibration constrains on optimum decision variables are investigated. The results of optimization can be considered as an initial values for design of radial turbines for Organic Rankine Cycles.

PdeH, a high-affinity cAMP phosphodiesterase, is a key regulator of asexual and pathogenic differentiation in Magnaporthe oryzae.

Directory of Open Access Journals (Sweden)

Ravikrishna Ramanujam

2010-05-01

Full Text Available Cyclic AMP-dependent pathways mediate the communication between external stimuli and the intracellular signaling machinery, thereby influencing important aspects of cellular growth, morphogenesis and differentiation. Crucial to proper function and robustness of these signaling cascades is the strict regulation and maintenance of intracellular levels of cAMP through a fine balance between biosynthesis (by adenylate cyclases and hydrolysis (by cAMP phosphodiesterases. We functionally characterized gene-deletion mutants of a high-affinity (PdeH and a low-affinity (PdeL cAMP phosphodiesterase in order to gain insights into the spatial and temporal regulation of cAMP signaling in the rice-blast fungus Magnaporthe oryzae. In contrast to the expendable PdeL function, the PdeH activity was found to be a key regulator of asexual and pathogenic development in M. oryzae. Loss of PdeH led to increased accumulation of intracellular cAMP during vegetative and infectious growth. Furthermore, the pdeHDelta showed enhanced conidiation (2-3 fold, precocious appressorial development, loss of surface dependency during pathogenesis, and highly reduced in planta growth and host colonization. A pdeHDelta pdeLDelta mutant showed reduced conidiation, exhibited dramatically increased (approximately 10 fold cAMP levels relative to the wild type, and was completely defective in virulence. Exogenous addition of 8-Br-cAMP to the wild type simulated the pdeHDelta defects in conidiation as well as in planta growth and development. While a fully functional GFP-PdeH was cytosolic but associated dynamically with the plasma membrane and vesicular compartments, the GFP-PdeL localized predominantly to the nucleus. Based on data from cAMP measurements and Real-Time RTPCR, we uncover a PdeH-dependent biphasic regulation of cAMP levels during early and late stages of appressorial development in M. oryzae. We propose that PdeH-mediated sustenance and dynamic regulation of cAMP signaling

PDE5 inhibition alleviates functional muscle ischemia in boys with Duchenne muscular dystrophy.

Science.gov (United States)

Nelson, Michael D; Rader, Florian; Tang, Xiu; Tavyev, Jane; Nelson, Stanley F; Miceli, M Carrie; Elashoff, Robert M; Sweeney, H Lee; Victor, Ronald G

2014-06-10

To determine whether phosphodiesterase type 5 (PDE5) inhibition can alleviate exercise-induced skeletal muscle ischemia in boys with Duchenne muscular dystrophy (DMD). In 10 boys with DMD and 10 healthy age-matched male controls, we assessed exercise-induced attenuation of reflex sympathetic vasoconstriction, i.e., functional sympatholysis, a protective mechanism that matches oxygen delivery to metabolic demand. Reflex vasoconstriction was induced by simulated orthostatic stress, measured as the decrease in forearm muscle oxygenation with near-infrared spectroscopy, and performed when the forearm muscles were rested or lightly exercised with rhythmic handgrip exercise. Then, the patients underwent an open-label, dose-escalation, crossover trial with single oral doses of tadalafil or sildenafil. The major new findings are 2-fold: first, sympatholysis is impaired in boys with DMD-producing functional muscle ischemia-despite contemporary background therapy with corticosteroids alone or in combination with cardioprotective medication. Second, PDE5 inhibition with standard clinical doses of either tadalafil or sildenafil alleviates this ischemia in a dose-dependent manner. Furthermore, PDE5 inhibition also normalizes the exercise-induced increase in skeletal muscle blood flow (measured by Doppler ultrasound), which is markedly blunted in boys with DMD. These data provide in-human proof of concept for PDE5 inhibition as a putative new therapeutic strategy for DMD. This study provides Class IV evidence that in patients with DMD, PDE5 inhibition restores functional sympatholysis. © 2014 American Academy of Neurology.

Constrained Quadratic Programming and Neurodynamics-Based Solver for Energy Optimization of Biped Walking Robots

Directory of Open Access Journals (Sweden)

Liyang Wang

2017-01-01

Full Text Available The application of biped robots is always trapped by their high energy consumption. This paper makes a contribution by optimizing the joint torques to decrease the energy consumption without changing the biped gaits. In this work, a constrained quadratic programming (QP problem for energy optimization is formulated. A neurodynamics-based solver is presented to solve the QP problem. Differing from the existing literatures, the proposed neurodynamics-based energy optimization (NEO strategy minimizes the energy consumption and guarantees the following three important constraints simultaneously: (i the force-moment equilibrium equation of biped robots, (ii frictions applied by each leg on the ground to hold the biped robot without slippage and tipping over, and (iii physical limits of the motors. Simulations demonstrate that the proposed strategy is effective for energy-efficient biped walking.

The PDE4 inhibitor CHF-6001 and LAMAs inhibit bronchoconstriction-induced remodeling in lung slices

NARCIS (Netherlands)

Kistemaker, Loes E M; Oenema, Tjitske A; Baarsma, Hoeke A; Bos, I. Sophie T.; Schmidt, Martina; Facchinetti, Fabrizio; Civelli, Maurizio; Villetti, Gino; Gosens, Reinoud

2017-01-01

Combination therapy of PDE4 inhibitors and anticholinergics induces bronchoprotection in COPD. Mechanical forces that arise during bronchoconstriction may contribute to airway remodeling. Therefore, we investigated the impact of PDE4 inhibitors and anticholinergics on bronchoconstriction-induced

Cross-talk between PKA-Cβ and p65 mediates synergistic induction of PDE4B by roflumilast and NTHi

Science.gov (United States)

Susuki-Miyata, Seiko; Miyata, Masanori; Lee, Byung-Cheol; Xu, Haidong; Kai, Hirofumi; Yan, Chen; Li, Jian-Dong

2015-01-01

Phosphodiesterase 4B (PDE4B) plays a key role in regulating inflammation. Roflumilast, a phosphodiesterase (PDE)4-selective inhibitor, has recently been approved for treating severe chronic obstructive pulmonary disease (COPD) patients with exacerbation. However, there is also clinical evidence suggesting the development of tachyphylaxis or tolerance on repeated dosing of roflumilast and the possible contribution of PDE4B up-regulation, which could be counterproductive for suppressing inflammation. Thus, understanding how PDE4B is up-regulated in the context of the complex pathogenesis and medications of COPD may help improve the efficacy and possibly ameliorate the tolerance of roflumilast. Here we show that roflumilast synergizes with nontypeable Haemophilus influenzae (NTHi), a major bacterial cause of COPD exacerbation, to up-regulate PDE4B2 expression in human airway epithelial cells in vitro and in vivo. Up-regulated PDE4B2 contributes to the induction of certain important chemokines in both enzymatic activity-dependent and activity-independent manners. We also found that protein kinase A catalytic subunit β (PKA-Cβ) and nuclear factor-κB (NF-κB) p65 subunit were required for the synergistic induction of PDE4B2. PKA-Cβ phosphorylates p65 in a cAMP-dependent manner. Moreover, Ser276 of p65 is critical for mediating the PKA-Cβ–induced p65 phosphorylation and the synergistic induction of PDE4B2. Collectively, our data unveil a previously unidentified mechanism underlying synergistic up-regulation of PDE4B2 via a cross-talk between PKA-Cβ and p65 and may help develop new therapeutic strategies to improve the efficacy of PDE4 inhibitor. PMID:25831493

Inversion for Eigenvalues and Modes Using Sierra-SD and ROL.

Energy Technology Data Exchange (ETDEWEB)

Walsh, Timothy [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Aquino, Wilkins [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ridzal, Denis [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kouri, Drew Philip [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-12-01

In this report we formulate eigenvalue-based methods for model calibration using a PDE-constrained optimization framework. We derive the abstract optimization operators from first principles and implement these methods using Sierra-SD and the Rapid Optimization Library (ROL). To demon- strate this approach, we use experimental measurements and an inverse solution to compute the joint and elastic foam properties of a low-fidelity unit (LFU) model.

Multivariate constrained shape optimization: Application to extrusion bell shape for pasta production

Science.gov (United States)

Sarghini, Fabrizio; De Vivo, Angela; Marra, Francesco

2017-10-01

Computational science and engineering methods have allowed a major change in the way products and processes are designed, as validated virtual models - capable to simulate physical, chemical and bio changes occurring during production processes - can be realized and used in place of real prototypes and performing experiments, often time and money consuming. Among such techniques, Optimal Shape Design (OSD) (Mohammadi & Pironneau, 2004) represents an interesting approach. While most classical numerical simulations consider fixed geometrical configurations, in OSD a certain number of geometrical degrees of freedom is considered as a part of the unknowns: this implies that the geometry is not completely defined, but part of it is allowed to move dynamically in order to minimize or maximize the objective function. The applications of optimal shape design (OSD) are uncountable. For systems governed by partial differential equations, they range from structure mechanics to electromagnetism and fluid mechanics or to a combination of the three. This paper presents one of possible applications of OSD, particularly how extrusion bell shape, for past production, can be designed by applying a multivariate constrained shape optimization.

Computer-Aided Transformation of PDE Models: Languages, Representations, and a Calculus of Operations

Science.gov (United States)

2016-01-05

Computer-aided transformation of PDE models: languages, representations, and a calculus of operations A domain-specific embedded language called...languages, representations, and a calculus of operations Report Title A domain-specific embedded language called ibvp was developed to model initial...Computer-aided transformation of PDE models: languages, representations, and a calculus of operations 1 Vision and background Physical and engineered systems

[A study of PDE6B gene mutation and phenotype in Chinese cases with retinitis pigmentosa].

Science.gov (United States)

Cui, Yun; Zhao, Kan-xing; Wang, Li; Wang, Qing; Zhang, Wei; Chen, Wei-ying; Wang, Li-ming

2003-01-01

To identify the mutation spectrum of phosphodiesterase beta subunit (PDE6B) gene, the incidence in Chinese patients with retinitis pigmentosa (RP) and their clinical phenotypic characteristics. Screening of mutations within PDE6B gene was performed using polymerase chain reaction-heteroduplex-single strand conformation polymorphism (PCR-SSCP) and DNA sequence in 35 autosomal recessive (AR) RP and 55 sporadic RP cases. The phenotypes of the patients with the gene mutation were examined and analyzed. Novel complex heterozygous variants of PDE6B gene in a sporadic case, a T to C transversion in codon 323 resulting in the substitution of Gly by Ser and 2 base pairs (bp: G and T) insert between the 27th-28th bp upstream of the 5'-end of exon 10 were both present in a same isolate RP. But they are not found in 100 unrelated healthy individuals. Ocular findings showed diffuse pigmentary retinal degeneration in the midperipheral and peripheral fundi, optic atrophy and vessel attenuation. Multi-focal ERG indicated that the rod function was more severely deteriorated. A mutation was found in a case with RP in a ARRP family, a G to A transversion at 19th base upstream 5'-end of exon 11 (within intron 10) of PDE6B gene. A sporadic RP carried a sequence variant of PDE6B gene, a G to C transition, at the 15th base adjacent to the 3'-end of exon l8. In another isolate case with RP was found 2 bp (GT) insert between 31st and 32nd base upstream 5'-end of exon 4 (in intron 3) of PDE6B gene. There are novel complex heterozygous mutations of PDE6B gene responsible for a sporadic RP patient in China. This gene mutation associated with rod deterioration and RP. Several DNA variants were found in introns of PDE6B gene in national population.

Reinforcement learning solution for HJB equation arising in constrained optimal control problem.

Science.gov (United States)

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

2015-11-01

The constrained optimal control problem depends on the solution of the complicated Hamilton-Jacobi-Bellman equation (HJBE). In this paper, a data-based off-policy reinforcement learning (RL) method is proposed, which learns the solution of the HJBE and the optimal control policy from real system data. One important feature of the off-policy RL is that its policy evaluation can be realized with data generated by other behavior policies, not necessarily the target policy, which solves the insufficient exploration problem. The convergence of the off-policy RL is proved by demonstrating its equivalence to the successive approximation approach. Its implementation procedure is based on the actor-critic neural networks structure, where the function approximation is conducted with linearly independent basis functions. Subsequently, the convergence of the implementation procedure with function approximation is also proved. Finally, its effectiveness is verified through computer simulations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Research on odor interaction between aldehyde compounds via a partial differential equation (PDE) model.

Science.gov (United States)

Yan, Luchun; Liu, Jiemin; Qu, Chen; Gu, Xingye; Zhao, Xia

2015-01-28

In order to explore the odor interaction of binary odor mixtures, a series of odor intensity evaluation tests were performed using both individual components and binary mixtures of aldehydes. Based on the linear relation between the logarithm of odor activity value and odor intensity of individual substances, the relationship between concentrations of individual constituents and their joint odor intensity was investigated by employing a partial differential equation (PDE) model. The obtained results showed that the binary odor interaction was mainly influenced by the mixing ratio of two constituents, but not the concentration level of an odor sample. Besides, an extended PDE model was also proposed on the basis of the above experiments. Through a series of odor intensity matching tests for several different binary odor mixtures, the extended PDE model was proved effective at odor intensity prediction. Furthermore, odorants of the same chemical group and similar odor type exhibited similar characteristics in the binary odor interaction. The overall results suggested that the PDE model is a more interpretable way of demonstrating the odor interactions of binary odor mixtures.

A comparison of the inhibitory activity of selective PDE4 inhibitors on eosinophil recruitment in guinea pig skin

Directory of Open Access Journals (Sweden)

Mauro M Teixeira

1997-12-01

Full Text Available The elevation of intracellular cyclic AMP by phosphodiesterase (PDE4 inhibitors in eosinophils is associated with inhibition of the activation and recruitment of these cells. We have previously shown that systemic treatment with the PDE4 inhibitor rolipram effectively inhibt eosinophil migration in guinea pig skin. In the present study we compare the oral potency and efficacy of the PDE4 inhibitors rolipram, RP 73401 and CDP 840 on allergic and PAF-induced eosinophil recruitment. Rolipram and RP 73401 were equally effective and potent when given by the oral route and much more active than the PDE4 inhibitor CDP 840. We suggest that this guinea pig model of allergic and mediator-induced eosinophil recruitment is both a sensitive and simple tool to test the efficacy and potency of PDE4 inhibitors in vivo.

Racing Sampling Based Microimmune Optimization Approach Solving Constrained Expected Value Programming

Directory of Open Access Journals (Sweden)

Kai Yang

2016-01-01

Full Text Available This work investigates a bioinspired microimmune optimization algorithm to solve a general kind of single-objective nonlinear constrained expected value programming without any prior distribution. In the study of algorithm, two lower bound sample estimates of random variables are theoretically developed to estimate the empirical values of individuals. Two adaptive racing sampling schemes are designed to identify those competitive individuals in a given population, by which high-quality individuals can obtain large sampling size. An immune evolutionary mechanism, along with a local search approach, is constructed to evolve the current population. The comparative experiments have showed that the proposed algorithm can effectively solve higher-dimensional benchmark problems and is of potential for further applications.

Cyclic AMP-specific phosphodiesterase, PDE8A1, is activated by protein kinase A-mediated phosphorylation

OpenAIRE

Brown, Kim M.; Lee, Louisa C.Y; Findlay, Jane E.; Day, Jonathan P.; Baillie, George S.

2012-01-01

The cyclic AMP-specific phosphodiesterase PDE8 has been shown to play a pivotal role in important processes such as steroidogenesis, T cell adhesion, regulation of heart beat and chemotaxis. However, no information exists on how the activity of this enzyme is regulated. We show that under elevated cAMP conditions, PKA acts to phosphorylate PDE8A on serine 359 and this action serves to enhance the activity of the enzyme. This is the first indication that PDE8 activity can be modulated by a kin...

Constrained Optimal Transport

Science.gov (United States)

Ekren, Ibrahim; Soner, H. Mete

2018-03-01

The classical duality theory of Kantorovich (C R (Doklady) Acad Sci URSS (NS) 37:199-201, 1942) and Kellerer (Z Wahrsch Verw Gebiete 67(4):399-432, 1984) for classical optimal transport is generalized to an abstract framework and a characterization of the dual elements is provided. This abstract generalization is set in a Banach lattice X with an order unit. The problem is given as the supremum over a convex subset of the positive unit sphere of the topological dual of X and the dual problem is defined on the bi-dual of X. These results are then applied to several extensions of the classical optimal transport.

Oil Reservoir Production Optimization using Optimal Control

DEFF Research Database (Denmark)

Völcker, Carsten; Jørgensen, John Bagterp; Stenby, Erling Halfdan

2011-01-01

Practical oil reservoir management involves solution of large-scale constrained optimal control problems. In this paper we present a numerical method for solution of large-scale constrained optimal control problems. The method is a single-shooting method that computes the gradients using the adjo...... reservoir using water ooding and smart well technology. Compared to the uncontrolled case, the optimal operation increases the Net Present Value of the oil field by 10%.......Practical oil reservoir management involves solution of large-scale constrained optimal control problems. In this paper we present a numerical method for solution of large-scale constrained optimal control problems. The method is a single-shooting method that computes the gradients using...

Design of a Circularly Polarized Galileo E6-Band Textile Antenna by Dedicated Multiobjective Constrained Pareto Optimization

Directory of Open Access Journals (Sweden)

Arnaut Dierck

2015-01-01

Full Text Available Designing textile antennas for real-life applications requires a design strategy that is able to produce antennas that are optimized over a wide bandwidth for often conflicting characteristics, such as impedance matching, axial ratio, efficiency, and gain, and, moreover, that is able to account for the variations that apply for the characteristics of the unconventional materials used in smart textile systems. In this paper, such a strategy, incorporating a multiobjective constrained Pareto optimization, is presented and applied to the design of a Galileo E6-band antenna with optimal return loss and wide-band axial ratio characteristics. Subsequently, different prototypes of the optimized antenna are fabricated and measured to validate the proposed design strategy.

Optimal partial mass transportation and obstacle Monge-Kantorovich equation

Science.gov (United States)

Igbida, Noureddine; Nguyen, Van Thanh

2018-05-01

Optimal partial mass transport, which is a variant of the optimal transport problem, consists in transporting effectively a prescribed amount of mass from a source to a target. The problem was first studied by Caffarelli and McCann (2010) [6] and Figalli (2010) [12] with a particular attention to the quadratic cost. Our aim here is to study the optimal partial mass transport problem with Finsler distance costs including the Monge cost given by the Euclidian distance. Our approach is different and our results do not follow from previous works. Among our results, we introduce a PDE of Monge-Kantorovich type with a double obstacle to characterize active submeasures, Kantorovich potential and optimal flow for the optimal partial transport problem. This new PDE enables us to study the uniqueness and monotonicity results for the active submeasures. Another interesting issue of our approach is its convenience for numerical analysis and computations that we develop in a separate paper [14] (Igbida and Nguyen, 2018).

Exploring pyrazolo[3,4-d]pyrimidine phosphodiesterase 1 (PDE1) inhibitors: a predictive approach combining comparative validated multiple molecular modelling techniques.

Science.gov (United States)

Amin, Sk Abdul; Bhargava, Sonam; Adhikari, Nilanjan; Gayen, Shovanlal; Jha, Tarun

2018-02-01

Phosphodiesterase 1 (PDE1) is a potential target for a number of neurodegenerative disorders such as Schizophrenia, Parkinson's and Alzheimer's diseases. A number of pyrazolo[3,4-d]pyrimidine PDE1 inhibitors were subjected to different molecular modelling techniques [such as regression-based quantitative structure-activity relationship (QSAR): multiple linear regression, support vector machine and artificial neural network; classification-based QSAR: Bayesian modelling and Recursive partitioning; Monte Carlo based QSAR; Open3DQSAR; pharmacophore mapping and molecular docking analyses] to get a detailed knowledge about the physicochemical and structural requirements for higher inhibitory activity. The planarity of the pyrimidinone ring plays an important role for PDE1 inhibition. The N-methylated function at the 5th position of the pyrazolo[3,4-d]pyrimidine core is required for interacting with the PDE1 enzyme. The cyclopentyl ring fused with the parent scaffold is necessary for PDE1 binding potency. The phenylamino substitution at 3rd position is crucial for PDE1 inhibition. The N2-substitution at the pyrazole moiety is important for PDE1 inhibition compared to the N1-substituted analogues. Moreover, the p-substituted benzyl side chain at N2-position helps to enhance the PDE1 inhibitory profile. Depending on these observations, some new molecules are predicted that may possess better PDE1 inhibition.

Joint Optimal Production Planning for Complex Supply Chains Constrained by Carbon Emission Abatement Policies

OpenAIRE

He, Longfei; Xu, Zhaoguang; Niu, Zhanwen

2014-01-01

We focus on the joint production planning of complex supply chains facing stochastic demands and being constrained by carbon emission reduction policies. We pick two typical carbon emission reduction policies to research how emission regulation influences the profit and carbon footprint of a typical supply chain. We use the input-output model to capture the interrelated demand link between an arbitrary pair of two nodes in scenarios without or with carbon emission constraints. We design optim...

Linderane Suppresses Hepatic Gluconeogenesis by Inhibiting the cAMP/PKA/CREB Pathway Through Indirect Activation of PDE 3 via ERK/STAT3

Directory of Open Access Journals (Sweden)

Wei Xie

2018-05-01

Full Text Available The role of phosphodiesterase 3 (PDE3, a cyclic AMP (cAMP-degrading enzyme, in modulating gluconeogenesis remains unknown. Here, linderane, a natural compound, was found to inhibit gluconeogenesis by activating hepatic PDE3 in rat primary hepatocytes. The underlying molecular mechanism and its effects on whole-body glucose and lipid metabolism were investigated. The effect of linderane on gluconeogenesis, cAMP content, phosphorylation of cAMP-response element-binding protein (CREB and PDE activity were examined in cultured primary hepatocytes and C57BL/6J mice. The precise mechanism by which linderane activates PDE3 and inhibits the cAMP pathway was explored using pharmacological inhibitors. The amelioration of metabolic disorders was observed in ob/ob mice. Linderane inhibited gluconeogenesis, reduced phosphoenolpyruvate carboxykinase (Pck1 and glucose-6-phosphatase (G6pc gene expression, and decreased intracellular cAMP concentration and CREB phosphorylation in rat primary hepatocytes under both basal and forskolin-stimulated conditions. In rat primary hepatocytes, it also increased total PDE and PDE3 activity but not PDE4 activity. The suppressive effect of linderane on the cAMP pathway and gluconeogenesis was abolished by the non-specific PDE inhibitor 3-isobutyl-1-methylxanthine (IBMX and the specific PDE3 inhibitor cilostazol. Linderane indirectly activated PDE3 through extracellular regulated protein kinase 1/2 (ERK1/2 and signal transducer and activator of transcription 3 (STAT3 activation. Linderane improved glucose and lipid metabolism after chronic oral administration in ob/ob mice. Our findings revealed linderane as an indirect PDE3 activator that suppresses gluconeogenesis through cAMP pathway inhibition and has beneficial effects on metabolic syndromes in ob/ob mice. This investigation highlighted the potential for PDE3 activation in the treatment of type 2 diabetes.

A General Symbolic PDE Solver Generator: Beyond Explicit Schemes

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K. Sheshadri

2003-01-01

Full Text Available This paper presents an extension of our Mathematica- and MathCode-based symbolic-numeric framework for solving a variety of partial differential equation (PDE problems. The main features of our earlier work, which implemented explicit finite-difference schemes, include the ability to handle (1 arbitrary number of dependent variables, (2 arbitrary dimensionality, and (3 arbitrary geometry, as well as (4 developing finite-difference schemes to any desired order of approximation. In the present paper, extensions of this framework to implicit schemes and the method of lines are discussed. While C++ code is generated, using the MathCode system for the implicit method, Modelica code is generated for the method of lines. The latter provides a preliminary PDE support for the Modelica language. Examples illustrating the various aspects of the solver generator are presented.

LDRD Report: Topological Design Optimization of Convolutes in Next Generation Pulsed Power Devices.

Energy Technology Data Exchange (ETDEWEB)

Cyr, Eric C. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); von Winckel, Gregory John [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kouri, Drew Philip [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gardiner, Thomas Anthony [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ridzal, Denis [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Shadid, John N. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Miller, Sean [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-09-01

This LDRD project was developed around the ambitious goal of applying PDE-constrained opti- mization approaches to design Z-machine components whose performance is governed by elec- tromagnetic and plasma models. This report documents the results of this LDRD project. Our differentiating approach was to use topology optimization methods developed for structural design and extend them for application to electromagnetic systems pertinent to the Z-machine. To achieve this objective a suite of optimization algorithms were implemented in the ROL library part of the Trilinos framework. These methods were applied to standalone demonstration problems and the Drekar multi-physics research application. Out of this exploration a new augmented Lagrangian approach to structural design problems was developed. We demonstrate that this approach has favorable mesh-independent performance. Both the final design and the algorithmic performance were independent of the size of the mesh. In addition, topology optimization formulations for the design of conducting networks were developed and demonstrated. Of note, this formulation was used to develop a design for the inner magnetically insulated transmission line on the Z-machine. The resulting electromagnetic device is compared with theoretically postulated designs.

Plano de Desenvolvimento da Escola (PDE-Escola): ferramenta de autonomia escolar?

OpenAIRE

Schimonek, Elisangela Maria Pereira; Muranaka, Maria Aparecida Segatto

2013-01-01

Resumo O presente artigo objetiva promover uma análise da implantação do PDE-Escola em duas unidades educacionais do município de Limeira-SP, que apresentaram o IDEB/2007 abaixo da média nacional e que foram direcionadas a implantar o Programa a partir de 2009. O PDE-Escola trata-se de um programa do Governo Federal que se proclama capaz de viabilizar a autonomia, a obtenção de melhores resultados educacionais e a modernização da estrutura, organização e gestão escolar a partir da adoção d...

Effects of PDE5 Inhibitors and sGC Stimulators in a Rat Model of Artificial Ureteral Calculosis.

Directory of Open Access Journals (Sweden)

Peter Sandner

Full Text Available Urinary colics from calculosis are frequent and intense forms of pain whose current pharmacological treatment remains unsatisfactory. New and more effective drugs are needed to control symptoms and improve stone expulsion. Recent evidence suggested that the Nitric Oxide (NO / cyclic guanosine monophosphate (cGMP/phosphodiesterase type 5 (PDE5 system may contribute to ureteral motility influencing stone expulsion. We investigated if PDE5 inhibitors and sGC stimulators influence ureteral contractility, pain behaviour and stone expulsion in a rat model of ureteral calculosis. We investigated: a the sex-specific PDE5 distribution in the rat ureter; b the functional in vitro effects of vardenafil and sildenafil (PDE5 inhibitors and BAY41-2272 (sGC stimulator on induced ureteral contractility in rats and c the in vivo effectiveness of vardenafil and BAY41-2272, alone and combined with ketoprofen, vs hyoscine-N-butylbromide alone or combined with ketoprofen, on behavioural pain indicators and stone expulsion in rats with artificial calculosis in one ureter. PDE5 was abundantly expressed in male and female rats' ureter. In vitro, both vardenafil and BAY41-2272 significantly relaxed pre-contracted ureteral strips. In vivo, all compounds significantly reduced number and global duration of "ureteral crises" and post-stone lumbar muscle hyperalgesia in calculosis rats. The highest level of reduction of the pain behaviour was observed with BAY41-2272 among all spasmolytics administered alone, and with the combination of ketoprofen with BAY41-2272. The percentage of stone expulsion was maximal in the ketoprofen+BAY41-2272 group. The NO/cGMP/PDE5 pathway is involved in the regulation of ureteral contractility and pain behaviour in urinary calculosis. PDE5 inhibitors and sGC stimulators could become a potent new option for treatment of urinary colic pain.

Repercussão cardiovascular, com e sem álcool, do carbonato de lodenafila, um novo inibidor da PDE5

OpenAIRE

Silva, Adauto Carvalho; Toffoletto, Odaly; Lucio, Luiz Antonio Galvão; Santos, Paula Ferreira dos; Afiune, Jorge Barros; Massud Filho, João; Tufik, Sergio

2010-01-01

FUNDAMENTO: A disfunção erétil afeta um grande número de homens no mundo e os inibidores de PDE 5 (iPDE5) estão entre os principais métodos de tratamento desses pacientes. O consumo social de álcool e o ato sexual apresentam uma relação considerável. Portanto, a associação entre álcool e iPDE5 pode ocorrer. O carbonato de lodenafila é um novo iPDE5 desenvolvido por uma empresa brasileira. OBJETIVO: Avaliar a repercussão cardiovascular do carbonato de lodenafila, associado ou não ao álcool, as...

Carbon-11 labeled papaverine as a PET tracer for imaging PDE10A: radiosynthesis, in vitro and in vivo evaluation

Energy Technology Data Exchange (ETDEWEB)

Tu Zhude [Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110 (United States)], E-mail: tuz@mir.wustl.edu; Xu Jinbin; Jones, Lynne A.; Li Shihong; Mach, Robert H. [Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110 (United States)

2010-05-15

Papaverine, 1-(3,4-dimethoxybenzyl)-6,7-dimethoxyisoquinoline, a specific inhibitor of phosphodiesterase (PDE) 10A with IC{sub 50} values of 36 nM for PDE10A, 1,300 nM for PDE3A and 320 nM for PDE4D, has served as a useful pharmaceutical tool to study the physiological role of PDE10A. Here, we report the radiosynthesis of [{sup 11}C]papaverine and the in vitro and in vivo evaluation of [{sup 11}C]papaverine as a potential positron emission tomography (PET) radiotracer for imaging PDE10A in the central nervous system (CNS). The radiosynthesis of papaverine with {sup 11}C was achieved by O-methylation of the corresponding des-methyl precursor with [{sup 11}C]methyl iodide. [{sup 11}C]papaverine was obtained with {approx}70% radiochemical yield and a specific activity >10 Ci/{mu}mol. In vitro autoradiography studies of rat and monkey brain sections revealed selective binding of [{sup 11}C]papaverine to PDE10A enriched regions: the striatum of rat brain and the caudate and putamen of rhesus monkey brain. The biodistribution of [{sup 11}C]papaverine in rats at 5 min demonstrated an initially higher accumulation in striatum than in other brain regions, however the washout was rapid. MicroPET imaging studies in rhesus macaques similarly displayed initial specific uptake in the striatum with very rapid clearance of [{sup 11}C]papaverine from brain. Our initial evaluation suggests that despite papaverine's utility for in vitro studies and as a pharmaceutical tool, [{sup 11}C]papaverine is not an ideal radioligand for clinical imaging of PDE10A in the CNS. Analogs of papaverine having a higher potency for inhibiting PDE10A and improved pharmacokinetic properties will be necessary for imaging this enzyme with PET.

Scheduling Appliances with GA, TLBO, FA, OSR and Their Hybrids Using Chance Constrained Optimization for Smart Homes

Directory of Open Access Journals (Sweden)

Zunaira Nadeem

2018-04-01

Full Text Available In this paper, we design a controller for home energy management based on following meta-heuristic algorithms: teaching learning-based optimization (TLBO, genetic algorithm (GA, firefly algorithm (FA and optimal stopping rule (OSR theory. The principal goal of designing this controller is to reduce the energy consumption of residential sectors while reducing consumer’s electricity bill and maximizing user comfort. Additionally, we propose three hybrid schemes OSR-GA, OSR-TLBO and OSR-FA, by combining the best features of existing algorithms. We have also optimized the desired parameters: peak to average ratio, energy consumption, cost, and user comfort (appliance waiting time for 20, 50, 100 and 200 heterogeneous homes in two steps. In the first step, we obtain the optimal scheduling of home appliances implementing our aforementioned hybrid schemes for single and multiple homes while considering user preferences and threshold base policy. In the second step, we formulate our problem through chance constrained optimization. Simulation results show that proposed hybrid scheduling schemes outperformed for single and multiple homes and they shift the consumer load demand exceeding a predefined threshold to the hours where the electricity price is low thus following the threshold base policy. This helps to reduce electricity cost while considering the comfort of a user by minimizing delay and peak to average ratio. In addition, chance-constrained optimization is used to ensure the scheduling of appliances while considering the uncertainties of a load hence smoothing the load curtailment. The major focus is to keep the appliances power consumption within the power constraint, while keeping power consumption below a pre-defined acceptable level. Moreover, the feasible regions of appliances electricity consumption are calculated which show the relationship between cost and energy consumption and cost and waiting time.

PDE-Foam - a probability-density estimation method using self-adapting phase-space binning

CERN Document Server

Dannheim, Dominik; Voigt, Alexander; Grahn, Karl-Johan; Speckmayer, Peter

2009-01-01

Probability-Density Estimation (PDE) is a multivariate discrimination technique based on sampling signal and background densities defined by event samples from data or Monte-Carlo (MC) simulations in a multi-dimensional phase space. To efficiently use large event samples to estimate the probability density, a binary search tree (range searching) is used in the PDE-RS implementation. It is a generalisation of standard likelihood methods and a powerful classification tool for problems with highly non-linearly correlated observables. In this paper, we present an innovative improvement of the PDE method that uses a self-adapting binning method to divide the multi-dimensional phase space in a finite number of hyper-rectangles (cells). The binning algorithm adjusts the size and position of a predefined number of cells inside the multidimensional phase space, minimizing the variance of the signal and background densities inside the cells. The binned density information is stored in binary trees, allowing for a very ...

Modified Covariance Matrix Adaptation – Evolution Strategy algorithm for constrained optimization under uncertainty, application to rocket design

Directory of Open Access Journals (Sweden)

Chocat Rudy

2015-01-01

Full Text Available The design of complex systems often induces a constrained optimization problem under uncertainty. An adaptation of CMA-ES(λ, μ optimization algorithm is proposed in order to efficiently handle the constraints in the presence of noise. The update mechanisms of the parametrized distribution used to generate the candidate solutions are modified. The constraint handling method allows to reduce the semi-principal axes of the probable research ellipsoid in the directions violating the constraints. The proposed approach is compared to existing approaches on three analytic optimization problems to highlight the efficiency and the robustness of the algorithm. The proposed method is used to design a two stage solid propulsion launch vehicle.

Adaptive wavelet collocation methods for initial value boundary problems of nonlinear PDE's

Science.gov (United States)

Cai, Wei; Wang, Jian-Zhong

1993-01-01

We have designed a cubic spline wavelet decomposition for the Sobolev space H(sup 2)(sub 0)(I) where I is a bounded interval. Based on a special 'point-wise orthogonality' of the wavelet basis functions, a fast Discrete Wavelet Transform (DWT) is constructed. This DWT transform will map discrete samples of a function to its wavelet expansion coefficients in O(N log N) operations. Using this transform, we propose a collocation method for the initial value boundary problem of nonlinear PDE's. Then, we test the efficiency of the DWT transform and apply the collocation method to solve linear and nonlinear PDE's.

Linux software for large topology optimization problems

DEFF Research Database (Denmark)

evolving product, which allows a parallel solution of the PDE, it lacks the important feature that the matrix-generation part of the computations is localized to each processor. This is well-known to be critical for obtaining a useful speedup on a Linux cluster and it motivates the search for a COMSOL......-like package for large topology optimization problems. One candidate for such software is developed for Linux by Sandia Nat’l Lab in the USA being the Sundance system. Sundance also uses a symbolic representation of the PDE and a scalable numerical solution is achieved by employing the underlying Trilinos...

Constrained Optimization Methods in Health Services Research-An Introduction: Report 1 of the ISPOR Optimization Methods Emerging Good Practices Task Force.

Science.gov (United States)

Crown, William; Buyukkaramikli, Nasuh; Thokala, Praveen; Morton, Alec; Sir, Mustafa Y; Marshall, Deborah A; Tosh, Jon; Padula, William V; Ijzerman, Maarten J; Wong, Peter K; Pasupathy, Kalyan S

2017-03-01

Providing health services with the greatest possible value to patients and society given the constraints imposed by patient characteristics, health care system characteristics, budgets, and so forth relies heavily on the design of structures and processes. Such problems are complex and require a rigorous and systematic approach to identify the best solution. Constrained optimization is a set of methods designed to identify efficiently and systematically the best solution (the optimal solution) to a problem characterized by a number of potential solutions in the presence of identified constraints. This report identifies 1) key concepts and the main steps in building an optimization model; 2) the types of problems for which optimal solutions can be determined in real-world health applications; and 3) the appropriate optimization methods for these problems. We first present a simple graphical model based on the treatment of "regular" and "severe" patients, which maximizes the overall health benefit subject to time and budget constraints. We then relate it back to how optimization is relevant in health services research for addressing present day challenges. We also explain how these mathematical optimization methods relate to simulation methods, to standard health economic analysis techniques, and to the emergent fields of analytics and machine learning. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Role of Ser102 and Ser104 as Regulators of cGMP Hydrolysis by PDE5A

DEFF Research Database (Denmark)

Carøe Nordgaard, Julie; Kruse, Lars Schack; Gammeltoft, Steen

2014-01-01

-N-AS neuroblastoma cells as C-terminal fusions with green fluorescent protein. Transfected cells were treated with sildenafil, cilostazol, glyceryl trinitrate, calcitonin gene-related peptide (CGRP) or sumatriptan. PDE5A-GFP fusion proteins were localized in fixed cells by immunofluorescence and PDE activity...

Phosphodiesterase (PDE5) inhibition assay for rapid detection of erectile dysfunction drugs and analogs in sexual enhancement products.

Science.gov (United States)

Santillo, Michael F; Mapa, Mapa S T

2018-02-28

Products marketed as dietary supplements for sexual enhancement are frequently adulterated with phosphodiesterase-5 (PDE5) inhibitors, which are erectile dysfunction drugs or their analogs that can cause adverse health effects. Due to widespread adulteration, a rapid screening assay was developed to detect PDE5 inhibitors in adulterated products. The assay employs fluorescence detection and is based on measuring inhibition of PDE5 activity, the pharmacological mechanism shared among the adulterants. Initially, the assay reaction scheme was established and characterized, followed by analysis of 9 representative PDE5 inhibitors (IC 50 , 0.4-4.0 ng mL -1 ), demonstrating sensitive detection in matrix-free solutions. Next, dietary supplements serving as matrix blanks (n = 25) were analyzed to determine matrix interference and establish a threshold value; there were no false positives. Finally, matrix blanks were spiked with 9 individual PDE5 inhibitors, along with several mixtures. All 9 adulterants were successfully detected (≤ 5 % false negative rate; n = 20) at a concentration of 1.00 mg g -1 , which is over 5 times lower than concentrations commonly encountered in adulterated products. A major distinction of the PDE5 inhibition assay is the ability to detect adulterants without prior knowledge of their chemical structures, demonstrating a broad-based detection capability that can address a continuously evolving threat of new adulterants. The PDE5 inhibition assay can analyze over 40 samples simultaneously within 15 minutes and involves a single incubation step and simple data analysis, all of which are advantageous for combating the widespread adulteration of sex-enhancement products. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

A PDE Pricing Framework for Cross-Currency Interest Rate Derivatives with Target Redemption Features

Science.gov (United States)

Christara, Christina C.; Minh Dang, Duy; Jackson, Kenneth R.; Lakhany, Asif

2010-09-01

We propose a general framework for efficient pricing via a partial differential equation (PDE) approach for exotic cross-currency interest rate (IR) derivatives, with strong emphasis on long-dated foreign exchange (FX) IR hybrids, namely Power Reverse Dual Currency (PRDC) swaps with a FX Target Redemption (FX-TARN) provision. The FX-TARN provision provides a cap on the FX-linked PRDC coupon amounts, and once the accumulated coupon amount reaches this cap, the underlying PRDC swap terminates. Our PDE pricing framework is based on an auxiliary state variable to keep track of the total accumulated PRDC coupon amount. Finite differences on uniform grids and the Alternating Direction Implicit (ADI) method are used for the spatial and time discretizations, respectively, of the model-dependent PDE corresponding to each discretized value of the auxiliary variable. Numerical examples illustrating the convergence properties of the numerical methods are provided.

Structure-Based Design, Synthesis, Biological Evaluation, and Molecular Docking of Novel PDE10 Inhibitors with Antioxidant Activities

Science.gov (United States)

Li, Jinxuan; Chen, Jing-Yi; Deng, Ya-Lin; Zhou, Qian; Wu, Yinuo; Wu, Deyan; Luo, Hai-Bin

2018-05-01

Phosphodiesterase 10 is a promising target for the treatment of a series of central nervous system (CNS) diseases. Imbalance between oxidative stress and antioxidant defense systems as a universal condition in neurodegenerative disorders is widely studied as a potential therapy for CNS diseases, such as Alzheimer’s disease (AD), Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS). To discover multifunctional pharmaceuticals as a treatment for neurodegenerative diseases, a series of quinazoline-based derivatives with PDE10 inhibitory activities and antioxidant activities were designed and synthesized. Nine out of thirteen designed compounds showed good PDE10 inhibition at the concentration of 1.0 μM. Among these compounds, eight exhibited moderate to excellent antioxidant activity with ORAC (oxygen radical absorbance capacity) value above 1.0. Molecular docking was performed for better understanding of the binding patterns of these compounds with PDE10. Compound 11e, which showed remarkable inhibitory activity against PDE10 and antioxidant activity may serve as a lead for the further modification.

A Constrained Least Squares Approach to Mobile Positioning: Algorithms and Optimality

Science.gov (United States)

Cheung, KW; So, HC; Ma, W.-K.; Chan, YT

2006-12-01

The problem of locating a mobile terminal has received significant attention in the field of wireless communications. Time-of-arrival (TOA), received signal strength (RSS), time-difference-of-arrival (TDOA), and angle-of-arrival (AOA) are commonly used measurements for estimating the position of the mobile station. In this paper, we present a constrained weighted least squares (CWLS) mobile positioning approach that encompasses all the above described measurement cases. The advantages of CWLS include performance optimality and capability of extension to hybrid measurement cases (e.g., mobile positioning using TDOA and AOA measurements jointly). Assuming zero-mean uncorrelated measurement errors, we show by mean and variance analysis that all the developed CWLS location estimators achieve zero bias and the Cramér-Rao lower bound approximately when measurement error variances are small. The asymptotic optimum performance is also confirmed by simulation results.

Chance constrained uncertain classification via robust optimization

NARCIS (Netherlands)

Ben-Tal, A.; Bhadra, S.; Bhattacharayya, C.; Saketha Nat, J.

2011-01-01

This paper studies the problem of constructing robust classifiers when the training is plagued with uncertainty. The problem is posed as a Chance-Constrained Program (CCP) which ensures that the uncertain data points are classified correctly with high probability. Unfortunately such a CCP turns out

SU-G-BRA-08: Diaphragm Motion Tracking Based On KV CBCT Projections with a Constrained Linear Regression Optimization

Energy Technology Data Exchange (ETDEWEB)

Wei, J [City College of New York, New York, NY (United States); Chao, M [The Mount Sinai Medical Center, New York, NY (United States)

2016-06-15

Purpose: To develop a novel strategy to extract the respiratory motion of the thoracic diaphragm from kilovoltage cone beam computed tomography (CBCT) projections by a constrained linear regression optimization technique. Methods: A parabolic function was identified as the geometric model and was employed to fit the shape of the diaphragm on the CBCT projections. The search was initialized by five manually placed seeds on a pre-selected projection image. Temporal redundancies, the enabling phenomenology in video compression and encoding techniques, inherent in the dynamic properties of the diaphragm motion together with the geometrical shape of the diaphragm boundary and the associated algebraic constraint that significantly reduced the searching space of viable parabolic parameters was integrated, which can be effectively optimized by a constrained linear regression approach on the subsequent projections. The innovative algebraic constraints stipulating the kinetic range of the motion and the spatial constraint preventing any unphysical deviations was able to obtain the optimal contour of the diaphragm with minimal initialization. The algorithm was assessed by a fluoroscopic movie acquired at anteriorposterior fixed direction and kilovoltage CBCT projection image sets from four lung and two liver patients. The automatic tracing by the proposed algorithm and manual tracking by a human operator were compared in both space and frequency domains. Results: The error between the estimated and manual detections for the fluoroscopic movie was 0.54mm with standard deviation (SD) of 0.45mm, while the average error for the CBCT projections was 0.79mm with SD of 0.64mm for all enrolled patients. The submillimeter accuracy outcome exhibits the promise of the proposed constrained linear regression approach to track the diaphragm motion on rotational projection images. Conclusion: The new algorithm will provide a potential solution to rendering diaphragm motion and ultimately

SU-G-BRA-08: Diaphragm Motion Tracking Based On KV CBCT Projections with a Constrained Linear Regression Optimization

International Nuclear Information System (INIS)

Wei, J; Chao, M

2016-01-01

Purpose: To develop a novel strategy to extract the respiratory motion of the thoracic diaphragm from kilovoltage cone beam computed tomography (CBCT) projections by a constrained linear regression optimization technique. Methods: A parabolic function was identified as the geometric model and was employed to fit the shape of the diaphragm on the CBCT projections. The search was initialized by five manually placed seeds on a pre-selected projection image. Temporal redundancies, the enabling phenomenology in video compression and encoding techniques, inherent in the dynamic properties of the diaphragm motion together with the geometrical shape of the diaphragm boundary and the associated algebraic constraint that significantly reduced the searching space of viable parabolic parameters was integrated, which can be effectively optimized by a constrained linear regression approach on the subsequent projections. The innovative algebraic constraints stipulating the kinetic range of the motion and the spatial constraint preventing any unphysical deviations was able to obtain the optimal contour of the diaphragm with minimal initialization. The algorithm was assessed by a fluoroscopic movie acquired at anteriorposterior fixed direction and kilovoltage CBCT projection image sets from four lung and two liver patients. The automatic tracing by the proposed algorithm and manual tracking by a human operator were compared in both space and frequency domains. Results: The error between the estimated and manual detections for the fluoroscopic movie was 0.54mm with standard deviation (SD) of 0.45mm, while the average error for the CBCT projections was 0.79mm with SD of 0.64mm for all enrolled patients. The submillimeter accuracy outcome exhibits the promise of the proposed constrained linear regression approach to track the diaphragm motion on rotational projection images. Conclusion: The new algorithm will provide a potential solution to rendering diaphragm motion and ultimately

Assessment of sperm quality, oxidative stress injury as well as ACP, AC and PDE expression in patients with oligoasthenozoospermia before and after qilin pill treatment

Directory of Open Access Journals (Sweden)

Shi-Jun Zhang

2016-09-01

Full Text Available Objective: To analyze the sperm quality, oxidative stress injury as well as ACP, AC and PDE expression in patients with oligoasthenozoospermia before and after qilin pill treatment. Methods: A total of 60 patients with oligoasthenozoospermia were randomly divided into observation group and control group, control group received routine western medicine treatment, observation group received qilin pill + conventional western medicine treatment, and then differences in sperm quality, oxidative stress injury, ACP, AC and PDE expression, etc. were compared between two groups after treatment. Results: Semen volume and sperm density in semen samples of observation group after qilin pill treatment were higher than those of control group; serum FSH and LH levels were lower than those of control group, and the T level was higher than that of control group; ROS and MDA levels in seminal plasma were lower than those of control group, and SOD level was higher than that of control group; ACP, AC, α-Glu and Fru levels in seminal plasma were higher than those of control group, and PDE level was lower than that of control group. Conclusion: Qilin pill can improve sperm quality and optimize testicular internal environment in patients with oligoasthenozoospermia, and it has positive clinical significance.

The PDE4 inhibitor CHF-6001 and LAMAs inhibit bronchoconstriction-induced remodeling in lung slices.

Science.gov (United States)

Kistemaker, Loes E M; Oenema, Tjitske A; Baarsma, Hoeke A; Bos, I Sophie T; Schmidt, Martina; Facchinetti, Fabrizio; Civelli, Maurizio; Villetti, Gino; Gosens, Reinoud

2017-09-01

Combination therapy of PDE4 inhibitors and anticholinergics induces bronchoprotection in COPD. Mechanical forces that arise during bronchoconstriction may contribute to airway remodeling. Therefore, we investigated the impact of PDE4 inhibitors and anticholinergics on bronchoconstriction-induced remodeling. Because of the different mechanism of action of PDE4 inhibitors and anticholinergics, we hypothesized functional interactions of these two drug classes. Guinea pig precision-cut lung slices were preincubated with the PDE4 inhibitors CHF-6001 or roflumilast and/or the anticholinergics tiotropium or glycopyorrolate, followed by stimulation with methacholine (10 μM) or TGF-β 1 (2 ng/ml) for 48 h. The inhibitory effects on airway smooth muscle remodeling, airway contraction, and TGF-β release were investigated. Methacholine-induced protein expression of smooth muscle-myosin was fully inhibited by CHF-6001 (0.3-100 nM), whereas roflumilast (1 µM) had smaller effects. Tiotropium and glycopyrrolate fully inhibited methacholine-induced airway remodeling (0.1-30 nM). The combination of CHF-6001 and tiotropium or glycopyrrolate, in concentrations partially effective by themselves, fully inhibited methacholine-induced remodeling in combination. CHF-6001 did not affect airway closure and had limited effects on TGF-β 1 -induced remodeling, but rather, it inhibited methacholine-induced TGF-β release. The PDE4 inhibitor CHF-6001, and to a lesser extent roflumilast, and the LAMAs tiotropium and glycopyrrolate inhibit bronchoconstriction-induced remodeling. The combination of CHF-6001 and anticholinergics was more effective than the individual compounds. This cooperativity might be explained by the distinct mechanisms of action inhibiting TGF-β release and bronchoconstriction. Copyright © 2017 the American Physiological Society.

Meshes optimized for discrete exterior calculus (DEC).

Energy Technology Data Exchange (ETDEWEB)

Mousley, Sarah C. [Univ. of Illinois, Urbana-Champaign, IL (United States); Deakin, Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Knupp, Patrick [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mitchell, Scott A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-12-01

We study the optimization of an energy function used by the meshing community to measure and improve mesh quality. This energy is non-traditional because it is dependent on both the primal triangulation and its dual Voronoi (power) diagram. The energy is a measure of the mesh's quality for usage in Discrete Exterior Calculus (DEC), a method for numerically solving PDEs. In DEC, the PDE domain is triangulated and this mesh is used to obtain discrete approximations of the continuous operators in the PDE. The energy of a mesh gives an upper bound on the error of the discrete diagonal approximation of the Hodge star operator. In practice, one begins with an initial mesh and then makes adjustments to produce a mesh of lower energy. However, we have discovered several shortcomings in directly optimizing this energy, e.g. its non-convexity, and we show that the search for an optimized mesh may lead to mesh inversion (malformed triangles). We propose a new energy function to address some of these issues.

Optimal traffic control in highway transportation networks using linear programming

KAUST Repository

Li, Yanning

2014-06-01

This article presents a framework for the optimal control of boundary flows on transportation networks. The state of the system is modeled by a first order scalar conservation law (Lighthill-Whitham-Richards PDE). Based on an equivalent formulation of the Hamilton-Jacobi PDE, the problem of controlling the state of the system on a network link in a finite horizon can be posed as a Linear Program. Assuming all intersections in the network are controllable, we show that the optimization approach can be extended to an arbitrary transportation network, preserving linear constraints. Unlike previously investigated transportation network control schemes, this framework leverages the intrinsic properties of the Halmilton-Jacobi equation, and does not require any discretization or boolean variables on the link. Hence this framework is very computational efficient and provides the globally optimal solution. The feasibility of this framework is illustrated by an on-ramp metering control example.

New PDE-based methods for image enhancement using SOM and Bayesian inference in various discretization schemes

International Nuclear Information System (INIS)

Karras, D A; Mertzios, G B

2009-01-01

A novel approach is presented in this paper for improving anisotropic diffusion PDE models, based on the Perona–Malik equation. A solution is proposed from an engineering perspective to adaptively estimate the parameters of the regularizing function in this equation. The goal of such a new adaptive diffusion scheme is to better preserve edges when the anisotropic diffusion PDE models are applied to image enhancement tasks. The proposed adaptive parameter estimation in the anisotropic diffusion PDE model involves self-organizing maps and Bayesian inference to define edge probabilities accurately. The proposed modifications attempt to capture not only simple edges but also difficult textural edges and incorporate their probability in the anisotropic diffusion model. In the context of the application of PDE models to image processing such adaptive schemes are closely related to the discrete image representation problem and the investigation of more suitable discretization algorithms using constraints derived from image processing theory. The proposed adaptive anisotropic diffusion model illustrates these concepts when it is numerically approximated by various discretization schemes in a database of magnetic resonance images (MRI), where it is shown to be efficient in image filtering and restoration applications

A model for optimal constrained adaptive testing

NARCIS (Netherlands)

van der Linden, Willem J.; Reese, Lynda M.

2001-01-01

A model for constrained computerized adaptive testing is proposed in which the information on the test at the ability estimate is maximized subject to a large variety of possible constraints on the contents of the test. At each item-selection step, a full test is first assembled to have maximum

A model for optimal constrained adaptive testing

NARCIS (Netherlands)

van der Linden, Willem J.; Reese, Lynda M.

1997-01-01

A model for constrained computerized adaptive testing is proposed in which the information in the test at the ability estimate is maximized subject to a large variety of possible constraints on the contents of the test. At each item-selection step, a full test is first assembled to have maximum

N Termini of apPDE4 Isoforms Are Responsible for Targeting the Isoforms to Different Cellular Membranes

Science.gov (United States)

Jang, Deok-Jin; Park, Soo-Won; Lee, Jin-A; Lee, Changhoon; Chae, Yeon-Su; Park, Hyungju; Kim, Min-Jeong; Choi, Sun-Lim; Lee, Nuribalhae; Kim, Hyoung; Kaang, Bong-Kiun

2010-01-01

Phosphodiesterases (PDEs) are known to play a key role in the compartmentalization of cAMP signaling; however, the molecular mechanisms underlying intracellular localization of different PDE isoforms are not understood. In this study, we have found that each of the supershort, short, and long forms of apPDE4 showed distinct localization in the…

Synthesis and biological evaluation of 5-carbamoyl-2-phenylpyrimidine derivatives as novel and potent PDE4 inhibitors.

Science.gov (United States)

Goto, Taiji; Shiina, Akiko; Yoshino, Toshiharu; Mizukami, Kiyoshi; Hirahara, Kazuki; Suzuki, Osamu; Sogawa, Yoshitaka; Takahashi, Tomoko; Mikkaichi, Tsuyoshi; Nakao, Naoki; Takahashi, Mizuki; Hasegawa, Masashi; Sasaki, Shigeki

2013-11-15

5-Carbamoyl-2-phenylpyrimidine derivative 2 has been identified as a phosphodiesterase 4 (PDE4) inhibitor with moderate PDE4B inhibitory activity (IC50=200 nM). Modification of the carboxylic acid moiety of 2 gave N-neopentylacetamide derivative 10f, which had high in vitro PDE4B inhibitory activity (IC50=8.3 nM) and in vivo efficacy against lipopolysaccharide (LPS)-induced pulmonary neutrophilia in mice (ID50=16 mg/kg, ip). Furthermore, based on the X-ray crystallography of 10f bound to the human PDE4B catalytic domain, we designed 7,8-dihydro-6H-pyrido[4,3-d]pyrimidin-5-one derivative 39 which has a fused bicyclic lactam scaffold. Compound 39 exhibited excellent inhibitory activity against LPS-induced tumor necrosis factor alpha (TNF-α) production in mouse splenocytes (IC50=0.21 nM) and in vivo anti-inflammatory activity against LPS-induced pulmonary neutrophilia in mice (41% inhibition at a dose of 1.0 mg/kg, i.t.). Copyright © 2013 Elsevier Ltd. All rights reserved.

Review of applications of TLBO algorithm and a tutorial for beginners to solve the unconstrained and constrained optimization problems

Directory of Open Access Journals (Sweden)

R. Venkata Rao

2016-01-01

Full Text Available The teaching-learning-based optimization (TLBO algorithm is finding a large number of applications in different fields of engineering and science since its introduction in 2011. The major applications are found in electrical engineering, mechanical design, thermal engineering, manufacturing engineering, civil engineering, structural engineering, computer engineering, electronics engineering, physics, chemistry, biotechnology and economics. This paper presents a review of applications of TLBO algorithm and a tutorial for solving the unconstrained and constrained optimization problems. The tutorial is expected to be useful to the beginners.

Adaptive optimal control of unknown constrained-input systems using policy iteration and neural networks.

Science.gov (United States)

Modares, Hamidreza; Lewis, Frank L; Naghibi-Sistani, Mohammad-Bagher

2013-10-01

This paper presents an online policy iteration (PI) algorithm to learn the continuous-time optimal control solution for unknown constrained-input systems. The proposed PI algorithm is implemented on an actor-critic structure where two neural networks (NNs) are tuned online and simultaneously to generate the optimal bounded control policy. The requirement of complete knowledge of the system dynamics is obviated by employing a novel NN identifier in conjunction with the actor and critic NNs. It is shown how the identifier weights estimation error affects the convergence of the critic NN. A novel learning rule is developed to guarantee that the identifier weights converge to small neighborhoods of their ideal values exponentially fast. To provide an easy-to-check persistence of excitation condition, the experience replay technique is used. That is, recorded past experiences are used simultaneously with current data for the adaptation of the identifier weights. Stability of the whole system consisting of the actor, critic, system state, and system identifier is guaranteed while all three networks undergo adaptation. Convergence to a near-optimal control law is also shown. The effectiveness of the proposed method is illustrated with a simulation example.

PDE7B is involved in nandrolone decanoate hydrolysis in liver cytosol and its transcription is up-regulated by androgens in HepG2

Directory of Open Access Journals (Sweden)

Emmanuel eStrahm

2014-05-01

Full Text Available Most androgenic drugs are available as esters for a prolonged depot action. However the enzymes involved in the hydrolysis of the esters have not been identified. There is one study indicating that PDE7B may be involved in the activation of testosterone enanthate. The aims are to identify the cellular compartments where the hydrolysis of testosterone enanthate and nandrolone decanoate occurs, and to investigate the involvement of PDE7B in the activation. We also determined if testosterone and nandrolone affect the expression of the PDE7B gene. The hydrolysis studies were performed in isolated human liver cytosolic and microsomal preparations with and without specific PDE7B inhibitor. The gene expression was studied in human hepatoma cells (HepG2 exposed to testosterone and nandrolone. We show that PDE7B serves as a catalyst of the hydrolysis of testosterone enanthate and nandrolone decanoate in liver cytosol. The gene expression of PDE7B was significantly induced 3- and 5- fold after 2 hours exposure to 1 µM testosterone enanthate and nandrolone decanoate, respectively. These results show that PDE7B is involved in the activation of esterified nandrolone and testosterone and that the gene expression of PDE7B is induced by supra-physiological concentrations of androgenic drugs.

Loading pattern optimization with maximum utilization of discharging fuel employing adaptively constrained discontinuous penalty function

International Nuclear Information System (INIS)

Park, T. K.; Joo, H. G.; Kim, C. H.

2010-01-01

In order to find the most economical loading pattern (LP) considering multi-cycle fuel loading, multi-objective fuel LP optimization problems are examined by employing an adaptively constrained discontinuous penalty function (ACDPF) method. This is an improved method to simplify the complicated acceptance logic of the original DPF method in that the stochastic effects caused by the different random number sequence can be reduced. The effectiveness of the multi-objective simulated annealing (SA) algorithm employing ACDPF is examined for the reload core LP of Cycle 4 of Yonggwang Nuclear Unit 4. Several optimization runs are performed with different numbers of objectives consisting of cycle length and average burnup of fuels to be discharged or reloaded. The candidate LPs obtained from the multi-objective optimization runs turn out to be better than the reference LP in the aspects of cycle length and utilization of given fuels. It is note that the proposed ACDPF based MOSA algorithm can be a practical method to obtain an economical LP considering multi-cycle fuel loading. (authors)

PERSEPSI PENGOLAH DATA TERHADAP EFEKTIVITAS PDE HOTEL BERBINTANG DI KOTA DENPASAR

Directory of Open Access Journals (Sweden)

I KETUT SUWARTHA

2010-07-01

Full Text Available The development of information technology provides more expectations for the businessman, spesifically in the hotel sector. Nevertheless, in it’s implementation raise expectation gap between the user of the information and data processing in the Electronic Data Processing (PDE. The objective of this research is to find out the effectivity and dimension that should be improved on the side of data processing perception in the Electronic Data Processing (PDE of  star hotels  in Denpasar. The data collected by using questionnaire and interview and the data analysis technique used in this research is quantitative analysis technique. The conclusions from the analysis are (1 data processing perception included in the category of very effective by 81.64%, (2 there are three dimensions which needs more attention and improved, namely time dimension, report variation dimension or out put, information quality dimension.

Thermodynamic optimization of mixed refrigerant Joule- Thomson systems constrained by heat transfer considerations

International Nuclear Information System (INIS)

Hinze, J F; Klein, S A; Nellis, G F

2015-01-01

Mixed refrigerant (MR) working fluids can significantly increase the cooling capacity of a Joule-Thomson (JT) cycle. The optimization of MRJT systems has been the subject of substantial research. However, most optimization techniques do not model the recuperator in sufficient detail. For example, the recuperator is usually assumed to have a heat transfer coefficient that does not vary with the mixture. Ongoing work at the University of Wisconsin-Madison has shown that the heat transfer coefficients for two-phase flow are approximately three times greater than for a single phase mixture when the mixture quality is between 15% and 85%. As a result, a system that optimizes a MR without also requiring that the flow be in this quality range may require an extremely large recuperator or not achieve the performance predicted by the model. To ensure optimal performance of the JT cycle, the MR should be selected such that it is entirely two-phase within the recuperator. To determine the optimal MR composition, a parametric study was conducted assuming a thermodynamically ideal cycle. The results of the parametric study are graphically presented on a contour plot in the parameter space consisting of the extremes of the qualities that exist within the recuperator. The contours show constant values of the normalized refrigeration power. This ‘map’ shows the effect of MR composition on the cycle performance and it can be used to select the MR that provides a high cooling load while also constraining the recuperator to be two phase. The predicted best MR composition can be used as a starting point for experimentally determining the best MR. (paper)

Wave speed in excitable random networks with spatially constrained connections.

Directory of Open Access Journals (Sweden)

Nikita Vladimirov

Full Text Available Very fast oscillations (VFO in neocortex are widely observed before epileptic seizures, and there is growing evidence that they are caused by networks of pyramidal neurons connected by gap junctions between their axons. We are motivated by the spatio-temporal waves of activity recorded using electrocorticography (ECoG, and study the speed of activity propagation through a network of neurons axonally coupled by gap junctions. We simulate wave propagation by excitable cellular automata (CA on random (Erdös-Rényi networks of special type, with spatially constrained connections. From the cellular automaton model, we derive a mean field theory to predict wave propagation. The governing equation resolved by the Fisher-Kolmogorov PDE fails to describe wave speed. A new (hyperbolic PDE is suggested, which provides adequate wave speed v( that saturates with network degree , in agreement with intuitive expectations and CA simulations. We further show that the maximum length of connection is a much better predictor of the wave speed than the mean length. When tested in networks with various degree distributions, wave speeds are found to strongly depend on the ratio of network moments / rather than on mean degree , which is explained by general network theory. The wave speeds are strikingly similar in a diverse set of networks, including regular, Poisson, exponential and power law distributions, supporting our theory for various network topologies. Our results suggest practical predictions for networks of electrically coupled neurons, and our mean field method can be readily applied for a wide class of similar problems, such as spread of epidemics through spatial networks.

Optimal Financing Decisions of Two Cash-Constrained Supply Chains with Complementary Products

Directory of Open Access Journals (Sweden)

Yuting Li

2016-04-01

Full Text Available In recent years; financing difficulties have been obsessed small and medium enterprises (SMEs; especially emerging SMEs. Inter-members’ joint financing within a supply chain is one of solutions for SMEs. How about members’ joint financing of inter-supply chains? In order to answer the question, we firstly employ the Stackelberg game to propose three kinds of financing decision models of two cash-constrained supply chains with complementary products. Secondly, we analyze qualitatively these models and find the joint financing decision of the two supply chains is the most optimal one. Lastly, we conduct some numerical simulations not only to illustrate above results but also to find that the larger are cross-price sensitivity coefficients; the higher is the motivation for participants to make joint financing decisions; and the more are profits for them to gain.

Development of a Scintillation Proximity Assay (SPA) Based, High Throughput Screening Feasible Method for the Identification of PDE12 Activity Modulators.

Science.gov (United States)

Mang, Samuel; Bucher, Hannes; Nickolaus, Peter

2016-01-01

The scintillation proximity assay (SPA) technology has been widely used to establish high throughput screens (HTS) for a range of targets in the pharmaceutical industry. PDE12 (aka. 2'- phosphodiesterase) has been published to participate in the degradation of oligoadenylates that are involved in the establishment of an antiviral state via the activation of ribonuclease L (RNAse-L). Degradation of oligoadenylates by PDE12 terminates these antiviral activities, leading to decreased resistance of cells for a variety of viral pathogens. Therefore inhibitors of PDE12 are discussed as antiviral therapy. Here we describe the use of the yttrium silicate SPA bead technology to assess inhibitory activity of compounds against PDE12 in a homogeneous, robust HTS feasible assay using tritiated adenosine-P-adenylate ([3H]ApA) as substrate. We found that the used [3H]ApA educt, was not able to bind to SPA beads, whereas the product [3H]AMP, as known before, was able to bind to SPA beads. This enables the measurement of PDE12 activity on [3H]ApA as a substrate using a wallac microbeta counter. This method describes a robust and high throughput capable format in terms of specificity, commonly used compound solvents, ease of detection and assay matrices. The method could facilitate the search for PDE12 inhibitors as antiviral compounds.

Linearly constrained minimax optimization

DEFF Research Database (Denmark)

Madsen, Kaj; Schjær-Jacobsen, Hans

1978-01-01

We present an algorithm for nonlinear minimax optimization subject to linear equality and inequality constraints which requires first order partial derivatives. The algorithm is based on successive linear approximations to the functions defining the problem. The resulting linear subproblems...

A Variant of the Topkis-Veinott Method for Solving Inequality Constrained Optimization Problems

International Nuclear Information System (INIS)

Birge, J. R.; Qi, L.; Wei, Z.

2000-01-01

In this paper we give a variant of the Topkis-Veinott method for solving inequality constrained optimization problems. This method uses a linearly constrained positive semidefinite quadratic problem to generate a feasible descent direction at each iteration. Under mild assumptions, the algorithm is shown to be globally convergent in the sense that every accumulation point of the sequence generated by the algorithm is a Fritz-John point of the problem. We introduce a Fritz-John (FJ) function, an FJ1 strong second-order sufficiency condition (FJ1-SSOSC), and an FJ2 strong second-order sufficiency condition (FJ2-SSOSC), and then show, without any constraint qualification (CQ), that (i) if an FJ point z satisfies the FJ1-SSOSC, then there exists a neighborhood N(z) of z such that, for any FJ point y element of N(z) {z } , f 0 (y) ≠ f 0 (z) , where f 0 is the objective function of the problem; (ii) if an FJ point z satisfies the FJ2-SSOSC, then z is a strict local minimum of the problem. The result (i) implies that the entire iteration point sequence generated by the method converges to an FJ point. We also show that if the parameters are chosen large enough, a unit step length can be accepted by the proposed algorithm

Incorporating a Constrained Optimization Algorithm into Remote- Sensing/Precision Agriculture Methodology

Science.gov (United States)

Morgenthaler, George; Khatib, Nader; Kim, Byoungsoo

with information to improve their crop's vigor has been a major topic of interest. With world population growing exponentially, arable land being consumed by urbanization, and an unfavorable farm economy, the efficiency of farming must increase to meet future food requirements and to make farming a sustainable occupation for the farmer. "Precision Agriculture" refers to a farming methodology that applies nutrients and moisture only where and when they are needed in the field. The goal is to increase farm revenue by increasing crop yield and decreasing applications of costly chemical and water treatments. In addition, this methodology will decrease the environmental costs of farming, i.e., reduce air, soil, and water pollution. Sensing/Precision Agriculture has not grown as rapidly as early advocates envisioned. Technology for a successful Remote Sensing/Precision Agriculture system is now available. Commercial satellite systems can image (multi-spectral) the Earth with a resolution of approximately 2.5 m. Variable precision dispensing systems using GPS are available and affordable. Crop models that predict yield as a function of soil, chemical, and irrigation parameter levels have been formulated. Personal computers and internet access are in place in most farm homes and can provide a mechanism to periodically disseminate, e.g. bi-weekly, advice on what quantities of water and chemicals are needed in individual regions of the field. What is missing is a model that fuses the disparate sources of information on the current states of the crop and soil, and the remaining resource levels available with the decisions farmers are required to make. This must be a product that is easy for the farmer to understand and to implement. A "Constrained Optimization Feed-back Control Model" to fill this void will be presented. The objective function of the model will be used to maximize the farmer's profit by increasing yields while decreasing environmental costs and decreasing

Incorporating a constrained optimization algorithm into remote sensing/precision agriculture methodology

Science.gov (United States)

Moreenthaler, George W.; Khatib, Nader; Kim, Byoungsoo

2003-08-01

For two decades now, the use of Remote Sensing/Precision Agriculture to improve farm yields while reducing the use of polluting chemicals and the limited water supply has been a major goal. With world population growing exponentially, arable land being consumed by urbanization, and an unfavorable farm economy, farm efficiency must increase to meet future food requirements and to make farming a sustainable, profitable occupation. "Precision Agriculture" refers to a farming methodology that applies nutrients and moisture only where and when they are needed in the field. The real goal is to increase farm profitability by identifying the additional treatments of chemicals and water that increase revenues more than they increase costs and do no exceed pollution standards (constrained optimization). Even though the economic and environmental benefits appear to be great, Remote Sensing/Precision Agriculture has not grown as rapidly as early advocates envisioned. Technology for a successful Remote Sensing/Precision Agriculture system is now in place, but other needed factors have been missing. Commercial satellite systems can now image the Earth (multi-spectrally) with a resolution as fine as 2.5 m. Precision variable dispensing systems using GPS are now available and affordable. Crop models that predict yield as a function of soil, chemical, and irrigation parameter levels have been developed. Personal computers and internet access are now in place in most farm homes and can provide a mechanism for periodically disseminating advice on what quantities of water and chemicals are needed in specific regions of each field. Several processes have been selected that fuse the disparate sources of information on the current and historic states of the crop and soil, and the remaining resource levels available, with the critical decisions that farmers are required to make. These are done in a way that is easy for the farmer to understand and profitable to implement. A "Constrained

Slope constrained Topology Optimization

DEFF Research Database (Denmark)

Petersson, J.; Sigmund, Ole

1998-01-01

The problem of minimum compliance topology optimization of an elastic continuum is considered. A general continuous density-energy relation is assumed, including variable thickness sheet models and artificial power laws. To ensure existence of solutions, the design set is restricted by enforcing...

Use of the KlADH3 promoter for the quantitative production of the murine PDE5A isoforms in the yeast Kluyveromyces lactis.

Science.gov (United States)

Cardarelli, Silvia; Giorgi, Mauro; Naro, Fabio; Malatesta, Francesco; Biagioni, Stefano; Saliola, Michele

2017-09-22

Phosphodiesterases (PDE) are a superfamily of enzymes that hydrolyse cyclic nucleotides (cAMP/cGMP), signal molecules in transduction pathways regulating crucial aspects of cell life. PDEs regulate the intensity and duration of the cyclic nucleotides signal modulating the downstream biological effect. Due to this critical role associated with the extensive distribution and multiplicity of isozymes, the 11 mammalian families (PDE1 to PDE11) constitute key therapeutic targets. PDE5, one of these cGMP-specific hydrolysing families, is the molecular target of several well known drugs used to treat erectile dysfunction and pulmonary hypertension. Kluyveromyces lactis, one of the few yeasts capable of utilizing lactose, is an attractive host alternative to Saccharomyces cerevisiae for heterologous protein production. Here we established K. lactis as a powerful host for the quantitative production of the murine PDE5 isoforms. Using the promoter of the highly expressed KlADH3 gene, multicopy plasmids were engineered to produce the native and recombinant Mus musculus PDE5 in K. lactis. Yeast cells produced large amounts of the purified A1, A2 and A3 isoforms displaying K m , V max and Sildenafil inhibition values similar to those of the native murine enzymes. PDE5 whose yield was nearly 1 mg/g wet weight biomass for all three isozymes (30 mg/L culture), is well tolerated by K. lactis cells without major growth deficiencies and interferences with the endogenous cAMP/cGMP signal transduction pathways. To our knowledge, this is the first time that the entire PDE5 isozymes family containing both regulatory and catalytic domains has been produced at high levels in a heterologous eukaryotic organism. K. lactis has been shown to be a very promising host platform for large scale production of mammalian PDEs for biochemical and structural studies and for the development of new specific PDE inhibitors for therapeutic applications in many pathologies.

Improved helicopter aeromechanical stability analysis using segmented constrained layer damping and hybrid optimization

Science.gov (United States)

Liu, Qiang; Chattopadhyay, Aditi

2000-06-01

Aeromechanical stability plays a critical role in helicopter design and lead-lag damping is crucial to this design. In this paper, the use of segmented constrained damping layer (SCL) treatment and composite tailoring is investigated for improved rotor aeromechanical stability using formal optimization technique. The principal load-carrying member in the rotor blade is represented by a composite box beam, of arbitrary thickness, with surface bonded SCLs. A comprehensive theory is used to model the smart box beam. A ground resonance analysis model and an air resonance analysis model are implemented in the rotor blade built around the composite box beam with SCLs. The Pitt-Peters dynamic inflow model is used in air resonance analysis under hover condition. A hybrid optimization technique is used to investigate the optimum design of the composite box beam with surface bonded SCLs for improved damping characteristics. Parameters such as stacking sequence of the composite laminates and placement of SCLs are used as design variables. Detailed numerical studies are presented for aeromechanical stability analysis. It is shown that optimum blade design yields significant increase in rotor lead-lag regressive modal damping compared to the initial system.

WE-AB-209-12: Quasi Constrained Multi-Criteria Optimization for Automated Radiation Therapy Treatment Planning

Energy Technology Data Exchange (ETDEWEB)

Watkins, W.T.; Siebers, J.V. [University of Virginia, Charlottesville, VA (United States)

2016-06-15

Purpose: To introduce quasi-constrained Multi-Criteria Optimization (qcMCO) for unsupervised radiation therapy optimization which generates alternative patient-specific plans emphasizing dosimetric tradeoffs and conformance to clinical constraints for multiple delivery techniques. Methods: For N Organs At Risk (OARs) and M delivery techniques, qcMCO generates M(N+1) alternative treatment plans per patient. Objective weight variations for OARs and targets are used to generate alternative qcMCO plans. For 30 locally advanced lung cancer patients, qcMCO plans were generated for dosimetric tradeoffs to four OARs: each lung, heart, and esophagus (N=4) and 4 delivery techniques (simple 4-field arrangements, 9-field coplanar IMRT, 27-field non-coplanar IMRT, and non-coplanar Arc IMRT). Quasi-constrained objectives included target prescription isodose to 95% (PTV-D95), maximum PTV dose (PTV-Dmax)< 110% of prescription, and spinal cord Dmax<45 Gy. The algorithm’s ability to meet these constraints while simultaneously revealing dosimetric tradeoffs was investigated. Statistically significant dosimetric tradeoffs were defined such that the coefficient of determination between dosimetric indices which varied by at least 5 Gy between different plans was >0.8. Results: The qcMCO plans varied mean dose by >5 Gy to ipsilateral lung for 24/30 patients, contralateral lung for 29/30 patients, esophagus for 29/30 patients, and heart for 19/30 patients. In the 600 plans computed without human interaction, average PTV-D95=67.4±3.3 Gy, PTV-Dmax=79.2±5.3 Gy, and spinal cord Dmax was >45 Gy in 93 plans (>50 Gy in 2/600 plans). Statistically significant dosimetric tradeoffs were evident in 19/30 plans, including multiple tradeoffs of at least 5 Gy between multiple OARs in 7/30 cases. The most common statistically significant tradeoff was increasing PTV-Dmax to reduce OAR dose (15/30 patients). Conclusion: The qcMCO method can conform to quasi-constrained objectives while revealing

WE-AB-209-12: Quasi Constrained Multi-Criteria Optimization for Automated Radiation Therapy Treatment Planning

International Nuclear Information System (INIS)

Watkins, W.T.; Siebers, J.V.

2016-01-01

Purpose: To introduce quasi-constrained Multi-Criteria Optimization (qcMCO) for unsupervised radiation therapy optimization which generates alternative patient-specific plans emphasizing dosimetric tradeoffs and conformance to clinical constraints for multiple delivery techniques. Methods: For N Organs At Risk (OARs) and M delivery techniques, qcMCO generates M(N+1) alternative treatment plans per patient. Objective weight variations for OARs and targets are used to generate alternative qcMCO plans. For 30 locally advanced lung cancer patients, qcMCO plans were generated for dosimetric tradeoffs to four OARs: each lung, heart, and esophagus (N=4) and 4 delivery techniques (simple 4-field arrangements, 9-field coplanar IMRT, 27-field non-coplanar IMRT, and non-coplanar Arc IMRT). Quasi-constrained objectives included target prescription isodose to 95% (PTV-D95), maximum PTV dose (PTV-Dmax)< 110% of prescription, and spinal cord Dmax<45 Gy. The algorithm’s ability to meet these constraints while simultaneously revealing dosimetric tradeoffs was investigated. Statistically significant dosimetric tradeoffs were defined such that the coefficient of determination between dosimetric indices which varied by at least 5 Gy between different plans was >0.8. Results: The qcMCO plans varied mean dose by >5 Gy to ipsilateral lung for 24/30 patients, contralateral lung for 29/30 patients, esophagus for 29/30 patients, and heart for 19/30 patients. In the 600 plans computed without human interaction, average PTV-D95=67.4±3.3 Gy, PTV-Dmax=79.2±5.3 Gy, and spinal cord Dmax was >45 Gy in 93 plans (>50 Gy in 2/600 plans). Statistically significant dosimetric tradeoffs were evident in 19/30 plans, including multiple tradeoffs of at least 5 Gy between multiple OARs in 7/30 cases. The most common statistically significant tradeoff was increasing PTV-Dmax to reduce OAR dose (15/30 patients). Conclusion: The qcMCO method can conform to quasi-constrained objectives while revealing

Adjoint based optimal control of partially miscible two-phase flow in porous media with applications to CO2 sequestration in underground reservoirs

KAUST Repository

Simon, Moritz

2014-11-14

© 2014, Springer Science+Business Media New York. With the target of optimizing CO2 sequestration in underground reservoirs, we investigate constrained optimal control problems with partially miscible two-phase flow in porous media. Our objective is to maximize the amount of trapped CO2 in an underground reservoir after a fixed period of CO2 injection, while time-dependent injection rates in multiple wells are used as control parameters. We describe the governing two-phase two-component Darcy flow PDE system, formulate the optimal control problem and derive the continuous adjoint equations. For the discretization we apply a variant of the so-called BOX method, a locally conservative control-volume FE method that we further stabilize by a periodic averaging feature to reduce oscillations. The timestep-wise Lagrange function of the control problem is implemented as a variational form in Sundance, a toolbox for rapid development of parallel FE simulations, which is part of the HPC software Trilinos. We discuss the BOX method and our implementation in Sundance. The MPI parallelized Sundance state and adjoint solvers are linked to the interior point optimization package IPOPT, using limited-memory BFGS updates for approximating second derivatives. Finally, we present and discuss different types of optimal control results.

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

Science.gov (United States)

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

2017-11-01

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

Sequential optimization of a terrestrial biosphere model constrained by multiple satellite based products

Science.gov (United States)

Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.

2012-12-01

Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis

PDE7B is a novel, prognostically significant mediator of glioblastoma growth whose expression is regulated by endothelial cells.

Directory of Open Access Journals (Sweden)

Michael D Brooks

Full Text Available Cell-cell interactions between tumor cells and constituents of their microenvironment are critical determinants of tumor tissue biology and therapeutic responses. Interactions between glioblastoma (GBM cells and endothelial cells (ECs establish a purported cancer stem cell niche. We hypothesized that genes regulated by these interactions would be important, particularly as therapeutic targets. Using a computational approach, we deconvoluted expression data from a mixed physical co-culture of GBM cells and ECs and identified a previously undescribed upregulation of the cAMP specific phosphodiesterase PDE7B in GBM cells in response to direct contact with ECs. We further found that elevated PDE7B expression occurs in most GBM cases and has a negative effect on survival. PDE7B overexpression resulted in the expansion of a stem-like cell subpopulation in vitro and increased tumor growth and aggressiveness in an in vivo intracranial GBM model. Collectively these studies illustrate a novel approach for studying cell-cell interactions and identifying new therapeutic targets like PDE7B in GBM.

Security constrained optimal power flow by modern optimization tools

African Journals Online (AJOL)

The main objective of an optimal power flow (OPF) functions is to optimize .... It is characterized as propagation of plants and this happens by gametes union. ... ss and different variables, for example, wind, nearby fertilization can have a critic.

The inotropic effect of the active metabolite of levosimendan, OR-1896, is mediated through inhibition of PDE3 in rat ventricular myocardium.

Directory of Open Access Journals (Sweden)

Øivind Ørstavik

Full Text Available We recently published that the positive inotropic response (PIR to levosimendan can be fully accounted for by phosphodiesterase (PDE inhibition in both failing human heart and normal rat heart. To determine if the PIR of the active metabolite OR-1896, an important mediator of the long-term clinical effects of levosimendan, also results from PDE3 inhibition, we compared the effects of OR-1896, a representative Ca2+ sensitizer EMD57033 (EMD, levosimendan and other PDE inhibitors.Contractile force was measured in rat ventricular strips. PDE assay was conducted on rat ventricular homogenate. cAMP was measured using RII_epac FRET-based sensors.OR-1896 evoked a maximum PIR of 33 ± 10% above basal at 1 μM. This response was amplified in the presence of the PDE4 inhibitor rolipram (89 ± 14% and absent in the presence of the PDE3 inhibitors cilostamide (0.5 ± 5.3% or milrinone (3.2 ± 4.4%. The PIR was accompanied by a lusitropic response, and both were reversed by muscarinic receptor stimulation with carbachol and absent in the presence of β-AR blockade with timolol. OR-1896 inhibited PDE activity and increased cAMP levels at concentrations giving PIRs. OR-1896 did not sensitize the concentration-response relationship to extracellular Ca2+. Levosimendan, OR-1896 and EMD all increased the sensitivity to β-AR stimulation. The combination of either EMD and levosimendan or EMD and OR-1896 further sensitized the response, indicating at least two different mechanisms responsible for the sensitization. Only EMD sensitized the α1-AR response.The observed PIR to OR-1896 in rat ventricular strips is mediated through PDE3 inhibition, enhancing cAMP-mediated effects. These results further reinforce our previous finding that Ca2+ sensitization does not play a significant role in the inotropic (and lusitropic effect of levosimendan, nor of its main metabolite OR-1896.

The pde2 gene of Saccharomyces cerevisiae is allelic to rca1 and encodes a phosphodiesterase which protects the cell from extracellular cAMP.

Science.gov (United States)

Wilson, R B; Renault, G; Jacquet, M; Tatchell, K

1993-07-05

The high affinity cAMP phosphodiesterase, encoded by PDE2, is an important component of the cAMP-dependent protein kinase signaling system in Saccharomyces cerevisiae. An unexpected phenotype of pde2 mutants is sensitivity to external cAMP. This trait has been found independently for rca1 mutants and has been used to monitor the effects of cAMP on several biological processes. We demonstrate here that RCA1 is identical to PDE2. Further analysis of the phenotype of pde2 deletions reveal that exogenously added cAMP results in an increase in the internal level of cAMP. This increase slows down the rate of cell division by increasing the length of the G1 phase of the cell cycle and leads to increased cell volume. Also, cells with a disrupted PDE2 gene previously arrested by nutrient starvation rapidly lose thermotolerance when incubated with exogenous cAMP. From these observations we propose that a role of the PDE2-encoded phosphodiesterase may be to help insulate the internal cAMP pools from the external environment. This protective role might also be important in other eukaryotic organisms where cAMP is a key second messenger.

An Algebraic Programming Style for Numerical Software and Its Optimization

Directory of Open Access Journals (Sweden)

T.B. Dinesh

2000-01-01

Full Text Available The abstract mathematical theory of partial differential equations (PDEs is formulated in terms of manifolds, scalar fields, tensors, and the like, but these algebraic structures are hardly recognizable in actual PDE solvers. The general aim of the Sophus programming style is to bridge the gap between theory and practice in the domain of PDE solvers. Its main ingredients are a library of abstract datatypes corresponding to the algebraic structures used in the mathematical theory and an algebraic expression style similar to the expression style used in the mathematical theory. Because of its emphasis on abstract datatypes, Sophus is most naturally combined with object-oriented languages or other languages supporting abstract datatypes. The resulting source code patterns are beyond the scope of current compiler optimizations, but are sufficiently specific for a dedicated source-to-source optimizer. The limited, domain-specific, character of Sophus is the key to success here. This kind of optimization has been tested on computationally intensive Sophus style code with promising results. The general approach may be useful for other styles and in other application domains as well.

SU-E-T-574: Novel Chance-Constrained Optimization in Intensity-Modulated Proton Therapy Planning to Account for Range and Patient Setup Uncertainties

International Nuclear Information System (INIS)

An, Y; Liang, J; Liu, W

2015-01-01

Purpose: We propose to apply a probabilistic framework, namely chanceconstrained optimization, in the intensity-modulated proton therapy (IMPT) planning subject to range and patient setup uncertainties. The purpose is to hedge against the influence of uncertainties and improve robustness of treatment plans. Methods: IMPT plans were generated for a typical prostate patient. Nine dose distributions are computed — the nominal one and one each for ±5mm setup uncertainties along three cardinal axes and for ±3.5% range uncertainty. These nine dose distributions are supplied to the solver CPLEX as chance constraints to explicitly control plan robustness under these representative uncertainty scenarios with certain probability. This probability is determined by the tolerance level. We make the chance-constrained model tractable by converting it to a mixed integer optimization problem. The quality of plans derived from this method is evaluated using dose-volume histogram (DVH) indices such as tumor dose homogeneity (D5% – D95%) and coverage (D95%) and normal tissue sparing like V70 of rectum, V65, and V40 of bladder. We also compare the results from this novel method with the conventional PTV-based method to further demonstrate its effectiveness Results: Our model can yield clinically acceptable plans within 50 seconds. The chance-constrained optimization produces IMPT plans with comparable target coverage, better target dose homogeneity, and better normal tissue sparing compared to the PTV-based optimization [D95% CTV: 67.9 vs 68.7 (Gy), D5% – D95% CTV: 11.9 vs 18 (Gy), V70 rectum: 0.0 % vs 0.33%, V65 bladder: 2.17% vs 9.33%, V40 bladder: 8.83% vs 21.83%]. It also simultaneously makes the plan more robust [Width of DVH band at D50%: 2.0 vs 10.0 (Gy)]. The tolerance level may be varied to control the tradeoff between plan robustness and quality. Conclusion: The chance-constrained optimization generates superior IMPT plan compared to the PTV-based optimization with

Accelerated Optimization in the PDE Framework: Formulations for the Manifold of Diffeomorphisms

KAUST Repository

Sundaramoorthi, Ganesh

2018-04-04

We consider the problem of optimization of cost functionals on the infinite-dimensional manifold of diffeomorphisms. We present a new class of optimization methods, valid for any optimization problem setup on the space of diffeomorphisms by generalizing Nesterov accelerated optimization to the manifold of diffeomorphisms. While our framework is general for infinite dimensional manifolds, we specifically treat the case of diffeomorphisms, motivated by optical flow problems in computer vision. This is accomplished by building on a recent variational approach to a general class of accelerated optimization methods by Wibisono, Wilson and Jordan, which applies in finite dimensions. We generalize that approach to infinite dimensional manifolds. We derive the surprisingly simple continuum evolution equations, which are partial differential equations, for accelerated gradient descent, and relate it to simple mechanical principles from fluid mechanics. Our approach has natural connections to the optimal mass transport problem. This is because one can think of our approach as an evolution of an infinite number of particles endowed with mass (represented with a mass density) that moves in an energy landscape. The mass evolves with the optimization variable, and endows the particles with dynamics. This is different than the finite dimensional case where only a single particle moves and hence the dynamics does not depend on the mass. We derive the theory, compute the PDEs for accelerated optimization, and illustrate the behavior of these new accelerated optimization schemes.

Accelerated Optimization in the PDE Framework: Formulations for the Manifold of Diffeomorphisms

KAUST Repository

Sundaramoorthi, Ganesh; Yezzi, Anthony

2018-01-01

We consider the problem of optimization of cost functionals on the infinite-dimensional manifold of diffeomorphisms. We present a new class of optimization methods, valid for any optimization problem setup on the space of diffeomorphisms by generalizing Nesterov accelerated optimization to the manifold of diffeomorphisms. While our framework is general for infinite dimensional manifolds, we specifically treat the case of diffeomorphisms, motivated by optical flow problems in computer vision. This is accomplished by building on a recent variational approach to a general class of accelerated optimization methods by Wibisono, Wilson and Jordan, which applies in finite dimensions. We generalize that approach to infinite dimensional manifolds. We derive the surprisingly simple continuum evolution equations, which are partial differential equations, for accelerated gradient descent, and relate it to simple mechanical principles from fluid mechanics. Our approach has natural connections to the optimal mass transport problem. This is because one can think of our approach as an evolution of an infinite number of particles endowed with mass (represented with a mass density) that moves in an energy landscape. The mass evolves with the optimization variable, and endows the particles with dynamics. This is different than the finite dimensional case where only a single particle moves and hence the dynamics does not depend on the mass. We derive the theory, compute the PDEs for accelerated optimization, and illustrate the behavior of these new accelerated optimization schemes.

Adjoint-Baed Optimal Control on the Pitch Angle of a Single-Bladed Vertical-Axis Wind Turbine

Science.gov (United States)

Tsai, Hsieh-Chen; Colonius, Tim

2017-11-01

Optimal control on the pitch angle of a NACA0018 single-bladed vertical-axis wind turbine (VAWT) is numerically investigated at a low Reynolds number of 1500. With fixed tip-speed ratio, the input power is minimized and mean tangential force is maximized over a specific time horizon. The immersed boundary method is used to simulate the two-dimensional, incompressible flow around a horizontal cross section of the VAWT. The problem is formulated as a PDE constrained optimization problem and an iterative solution is obtained using adjoint-based conjugate gradient methods. By the end of the longest control horizon examined, two controls end up with time-invariant pitch angles of about the same magnitude but with the opposite signs. The results show that both cases lead to a reduction in the input power but not necessarily an enhancement in the mean tangential force. These reductions in input power are due to the removal of a power-damaging phenomenon that occurs when a vortex pair is captured by the blade in the upwind-half region of a cycle. This project was supported by Caltech FLOWE center/Gordon and Betty Moore Foundation.

Chronic Inhibition of PDE5 Limits Pro-Inflammatory Monocyte-Macrophage Polarization in Streptozotocin-Induced Diabetic Mice.

Science.gov (United States)

Venneri, Mary Anna; Giannetta, Elisa; Panio, Giuseppe; De Gaetano, Rita; Gianfrilli, Daniele; Pofi, Riccardo; Masciarelli, Silvia; Fazi, Francesco; Pellegrini, Manuela; Lenzi, Andrea; Naro, Fabio; Isidori, Andrea M

2015-01-01

Diabetes mellitus is characterized by changes in endothelial cells that alter monocyte recruitment, increase classic (M1-type) tissue macrophage infiltration and lead to self-sustained inflammation. Our and other groups recently showed that chronic inhibition of phosphodiesterase-5 (PDE5i) affects circulating cytokine levels in patients with diabetes; whether PDE5i also affects circulating monocytes and tissue inflammatory cell infiltration remains to be established. Using murine streptozotocin (STZ)-induced diabetes and in human vitro cell-cell adhesion models we show that chronic hyperglycemia induces changes in myeloid and endothelial cells that alter monocyte recruitment and lead to self-sustained inflammation. Continuous PDE5i with sildenafil (SILD) expanded tissue anti-inflammatory TIE2-expressing monocytes (TEMs), which are known to limit inflammation and promote tissue repair. Specifically, SILD: 1) normalizes the frequency of circulating pro-inflammatory monocytes triggered by hyperglycemia (53.7 ± 7.9% of CD11b+Gr-1+ cells in STZ vs. 30.4 ± 8.3% in STZ+SILD and 27.1 ± 1.6% in CTRL, PTEMs (30.9 ± 3.6% in STZ+SILD vs. 6.9 ± 2.7% in STZ, P TEMs are defective in chronic hyperglycemia and that SILD normalizes their levels by facilitating the shift from classic (M1-like) to alternative (M2-like)/TEM macrophage polarization. Restoration of tissue TEMs with PDE5i could represent an additional pharmacological tool to prevent end-organ diabetic complications.

Effect of PVA and PDE on selected structural characteristics of extrusion-cooked starch foams

Directory of Open Access Journals (Sweden)

Maciej Combrzyński

2018-03-01

Full Text Available Abstract The aim of this work was to determine selected physical properties of biodegradable thermoplastic starch (TPS filling foams manufactured by extrusion-cooking technique from different combinations of potato starch and two additives: poly(vinyl alcohol PVA and Plastronfoam PDE. Foams were processed with seven starch/additives combinations at two different extruder-cooker’s screw rotational speeds. The densities of starch foams depended significantly on the additive type and content. The linear relationship between the Young modulus and the ultimate compression force and apparent density was found. The foams processed with the addition of PVA had low density, porosity and lower values of the Young modulus than the foams prepared with PDE.

Phosphodiesterase-9 (PDE9) inhibition with BAY 73-6691 increases corpus cavernosum relaxations mediated by nitric oxide-cyclic GMP pathway in mice.

Science.gov (United States)

da Silva, F H; Pereira, M N; Franco-Penteado, C F; De Nucci, G; Antunes, E; Claudino, M A

2013-01-01

Phosphodiesterase-9 (PDE9) specifically hydrolyzes cyclic GMP, and was detected in human corpus cavernosum. However, no previous studies explored the selective PDE9 inhibition with BAY 73-6691 in corpus cavernosum relaxations. Therefore, this study aimed to characterize the PDE9 mRNA expression in mice corpus cavernosum, and investigate the effects of BAY 73-6691 in endothelium-dependent and -independent relaxations, along with the nitrergic corpus cavernosum relaxations. Male mice received daily gavage of BAY 73-6691 (or dimethylsulfoxide) at 3 mg kg(-1) per day for 21 days. Relaxant responses to acetylcholine (ACh), nitric oxide (NO) (as acidified sodium nitrite; NaNO2 solution), sildenafil and electrical-field stimulation (EFS) were obtained in corpus cavernosum in control and BAY 73-6691-treated mice. BAY 73-6691 was also added in vitro 30 min before construction of concentration-responses and frequency curves. PDE9A and PDE5 mRNA expression was detected in the mice corpus cavernosum in a similar manner. In vitro addition of BAY 73-6691 neither itself relaxed mice corpus cavernosum nor changed the NaNO2, sildenafil and EFS-induced relaxations. However, in mice treated chronically with BAY 73-6691, the potency (pEC50) values for ACh, NaNO2 and sildenafil were significantly greater compared with control group. The maximal responses (Emax) to NaNO2 and sildenafil were also significantly greater in BAY 73-6691-treated mice. BAY 73-6691 treatment also significantly increased the magnitude and duration of the nitrergic corpus cavernosum relaxations (8-32 Hz). In conclusion, murine corpus cavernosum expresses PDE9 mRNA. Prolonged PDE9 inhibition with BAY 73-6691 amplifies the NO-cGMP-mediated cavernosal responses, and may be of therapeutic value for erectile dysfunction.

Constrained Optimization of MIMO Training Sequences

Directory of Open Access Journals (Sweden)

Coon Justin P

2007-01-01

Full Text Available Multiple-input multiple-output (MIMO systems have shown a huge potential for increased spectral efficiency and throughput. With an increasing number of transmitting antennas comes the burden of providing training for channel estimation for coherent detection. In some special cases optimal, in the sense of mean-squared error (MSE, training sequences have been designed. However, in many practical systems it is not feasible to analytically find optimal solutions and numerical techniques must be used. In this paper, two systems (unique word (UW single carrier and OFDM with nulled subcarriers are considered and a method of designing near-optimal training sequences using nonlinear optimization techniques is proposed. In particular, interior-point (IP algorithms such as the barrier method are discussed. Although the two systems seem unrelated, the cost function, which is the MSE of the channel estimate, is shown to be effectively the same for each scenario. Also, additional constraints, such as peak-to-average power ratio (PAPR, are considered and shown to be easily included in the optimization process. Numerical examples illustrate the effectiveness of the designed training sequences, both in terms of MSE and bit-error rate (BER.

Optimal traffic control in highway transportation networks using linear programming

KAUST Repository

Li, Yanning; Canepa, Edward S.; Claudel, Christian G.

2014-01-01

of the Hamilton-Jacobi PDE, the problem of controlling the state of the system on a network link in a finite horizon can be posed as a Linear Program. Assuming all intersections in the network are controllable, we show that the optimization approach can

Discovery of novel PDE9 inhibitors capable of inhibiting Aβ aggregation as potential candidates for the treatment of Alzheimer’s disease

Science.gov (United States)

Su, Tao; Zhang, Tianhua; Xie, Shishun; Yan, Jun; Wu, Yinuo; Li, Xingshu; Huang, Ling; Luo, Hai-Bin

2016-02-01

Recently, phosphodiesterase-9 (PDE9) inhibitors and biometal-chelators have received much attention as potential therapeutics for the treatment of Alzheimer’s disease (AD). Here, we designed, synthesized, and evaluated a novel series of PDE9 inhibitors with the ability to chelate metal ions. The bioassay results showed that most of these molecules strongly inhibited PDE9 activity. Compound 16 showed an IC50 of 34 nM against PDE9 and more than 55-fold selectivity against other PDEs. In addition, this compound displayed remarkable metal-chelating capacity and a considerable ability to halt copper redox cycling. Notably, in comparison to the reference compound clioquinol, it inhibited metal-induced Aβ1-42 aggregation more effectively and promoted greater disassembly of the highly structured Aβ fibrils generated through Cu2+-induced Aβ aggregation. These activities of 16, together with its favorable blood-brain barrier permeability, suggest that 16 may be a promising compound for treatment of AD.

Association study of PDE4B gene variants in Scandinavian schizophrenia and bipolar disorder multicenter case-control samples

DEFF Research Database (Denmark)

Kähler, Anna K; Otnæss, Mona K; Wirgenes, Katrine V

2010-01-01

The phosphodiesterase 4B (PDE4B), which is involved in cognitive function in animal models, is a candidate susceptibility gene for schizophrenia (SZ) and bipolar disorder (BP). Variations in PDE4B have previously been associated with SZ, with a suggested gender-specific effect. We have genotyped......SNPs were nominally associated (0.0005 gender-specific subgroups. None of these findings remained significant after correction for multiple testing. However, a number of tagSNPs found to be nominally associated with SZ and BP...... were located in a high LD region spanning the splice site of PDE4B3, an isoform with altered brain expression in BP patients. Four tagSNPs were associated with SZ in women, but none in men, in agreement with the previously reported gender-specific effect. Proxies of two nominally associated SNPs...

Continuous dynamic assimilation of the inner region data in hydrodynamics modelling: optimization approach

Directory of Open Access Journals (Sweden)

F. I. Pisnitchenko

2008-11-01

Full Text Available In meteorological and oceanological studies the classical approach for finding the numerical solution of the regional model consists in formulating and solving a Cauchy-Dirichlet problem. The boundary conditions are obtained by linear interpolation of coarse-grid data provided by a global model. Errors in boundary conditions due to interpolation may cause large deviations from the correct regional solution. The methods developed to reduce these errors deal with continuous dynamic assimilation of known global data available inside the regional domain. One of the approaches of this assimilation procedure performs a nudging of large-scale components of regional model solution to large-scale global data components by introducing relaxation forcing terms into the regional model equations. As a result, the obtained solution is not a valid numerical solution to the original regional model. Another approach is the use a four-dimensional variational data assimilation procedure which is free from the above-mentioned shortcoming. In this work we formulate the joint problem of finding the regional model solution and data assimilation as a PDE-constrained optimization problem. Three simple model examples (ODE Burgers equation, Rossby-Oboukhov equation, Korteweg-de Vries equation are considered in this paper. Numerical experiments indicate that the optimization approach can significantly improve the precision of the regional solution.

Dynamic Optimization of Constrained Layer Damping Structure for the Headstock of Machine Tools with Modal Strain Energy Method

Directory of Open Access Journals (Sweden)

Yakai Xu

2017-01-01

Full Text Available Dynamic stiffness and damping of the headstock, which is a critical component of precision horizontal machining center, are two main factors that influence machining accuracy and surface finish quality. Constrained Layer Damping (CLD structure is proved to be effective in raising damping capacity for the thin plate and shell structures. In this paper, one kind of high damping material is utilized on the headstock to improve damping capacity. The dynamic characteristic of the hybrid headstock is investigated analytically and experimentally. The results demonstrate that the resonant response amplitudes of the headstock with damping material can decrease significantly compared to original cast structure. To obtain the optimal configuration of damping material, a topology optimization method based on the Evolutionary Structural Optimization (ESO is implemented. Modal Strain Energy (MSE method is employed to analyze the damping and to derive the sensitivity of the modal loss factor. The optimization results indicate that the added weight of damping material decreases by 50%; meanwhile the first two orders of modal loss factor decrease by less than 23.5% compared to the original structure.

Design optimization of shell-and-tube heat exchangers using single objective and multiobjective particle swarm optimization

International Nuclear Information System (INIS)

Elsays, Mostafa A.; Naguib Aly, M; Badawi, Alya A.

2010-01-01

The Particle Swarm Optimization (PSO) algorithm is used to optimize the design of shell-and-tube heat exchangers and determine the optimal feasible solutions so as to eliminate trial-and-error during the design process. The design formulation takes into account the area and the total annual cost of heat exchangers as two objective functions together with operating as well as geometrical constraints. The Nonlinear Constrained Single Objective Particle Swarm Optimization (NCSOPSO) algorithm is used to minimize and find the optimal feasible solution for each of the nonlinear constrained objective functions alone, respectively. Then, a novel Nonlinear Constrained Mult-objective Particle Swarm Optimization (NCMOPSO) algorithm is used to minimize and find the Pareto optimal solutions for both of the nonlinear constrained objective functions together. The experimental results show that the two algorithms are very efficient, fast and can find the accurate optimal feasible solutions of the shell and tube heat exchangers design optimization problem. (orig.)

Radiosynthesis and initial characterization of a PDE10A specific PET tracer [18 F]AMG 580 in non-human primates

International Nuclear Information System (INIS)

Hwang, Dah-Ren; Hu, Essa; Allen, Jennifer R.; Davis, Carl; Treanor, James; Miller, Silke; Chen, Hang; Shi, Bingzhi; Narayanan, Tanjorie K.; Barret, Olivier; Alagille, David; Yu, Zhigang; Slifstein, Mark

2015-01-01

Introduction: Phosphodiesterase 10A (PDE10A) is an intracellular enzyme responsible for the breakdown of cyclic nucleotides which are important second messengers for neurotransmission. Inhibition of PDE10A has been identified as a potential target for treatment of various neuropsychiatric disorders. To assist drug development, we have identified a selective PDE10A positron emission tomography (PET) tracer, AMG 580. We describe here the radiosynthesis of [ 18 F]AMG 580 and in vitro and in vivo characterization results. Methods: The potency and selectivity were determined by in vitro assay using [ 3 H]AMG 580 and baboon brain tissues. [ 18 F]AMG 580 was prepared by a 1-step [ 18 F]fluorination procedure. Dynamic brain PET scans were performed in non-human primates. Regions-of-interest were defined on individuals’ MRIs and transferred to the co-registered PET images. Data were analyzed using two tissue compartment analysis (2TC), Logan graphical (Logan) analysis with metabolite-corrected input function and the simplified reference tissue model (SRTM) method. A PDE10A inhibitor and unlabeled AMG 580 were used to demonstrate the PDE10A specificity. K D was estimated by Scatchard analysis of high and low affinity PET scans. Results: AMG 580 has an in vitro K D of 71.9 pM. Autoradiography showed specific uptake in striatum. Mean activity of 121 ± 18 MBq was used in PET studies. In Rhesus, the baseline BP ND for putamen and caudate was 3.38 and 2.34, respectively, via 2TC, and 3.16, 2.34 via Logan, and 2.92, and 2.01 via SRTM. A dose dependent decrease of BP ND was observed by the pre-treatment with a PDE10A inhibitor. In baboons, 0.24 mg/kg dose of AMG 580 resulted in about 70% decrease of BP ND . The in vivo K D of [ 18 F]AMG 580 was estimated to be around 0.44 nM in baboons. Conclusion: [ 18 F]AMG 580 is a selective and potent PDE10A PET tracer with excellent specific striatal binding in non-human primates. It warrants further evaluation in humans

Commutator identities on associative algebras and integrability of nonlinear pde's

OpenAIRE

Pogrebkov, A. K.

2007-01-01

It is shown that commutator identities on associative algebras generate solutions of linearized integrable equations. Next, a special kind of the dressing procedure is suggested that in a special class of integral operators enables to associate to such commutator identity both nonlinear equation and its Lax pair. Thus problem of construction of new integrable pde's reduces to construction of commutator identities on associative algebras.

Pole shifting with constrained output feedback

International Nuclear Information System (INIS)

Hamel, D.; Mensah, S.; Boisvert, J.

1984-03-01

The concept of pole placement plays an important role in linear, multi-variable, control theory. It has received much attention since its introduction, and several pole shifting algorithms are now available. This work presents a new method which allows practical and engineering constraints such as gain limitation and controller structure to be introduced right into the pole shifting design strategy. This is achieved by formulating the pole placement problem as a constrained optimization problem. Explicit constraints (controller structure and gain limits) are defined to identify an admissible region for the feedback gain matrix. The desired pole configuration is translated into an appropriate cost function which must be closed-loop minimized. The resulting constrained optimization problem can thus be solved with optimization algorithms. The method has been implemented as an algorithmic interactive module in a computer-aided control system design package, MVPACK. The application of the method is illustrated to design controllers for an aircraft and an evaporator. The results illustrate the importance of controller structure on overall performance of a control system

MO-FG-CAMPUS-TeP2-01: A Graph Form ADMM Algorithm for Constrained Quadratic Radiation Treatment Planning

Energy Technology Data Exchange (ETDEWEB)

Liu, X; Belcher, AH; Wiersma, R [The University of Chicago, Chicago, IL (United States)

2016-06-15

Purpose: In radiation therapy optimization the constraints can be either hard constraints which must be satisfied or soft constraints which are included but do not need to be satisfied exactly. Currently the voxel dose constraints are viewed as soft constraints and included as a part of the objective function and approximated as an unconstrained problem. However in some treatment planning cases the constraints should be specified as hard constraints and solved by constrained optimization. The goal of this work is to present a computation efficiency graph form alternating direction method of multipliers (ADMM) algorithm for constrained quadratic treatment planning optimization and compare it with several commonly used algorithms/toolbox. Method: ADMM can be viewed as an attempt to blend the benefits of dual decomposition and augmented Lagrangian methods for constrained optimization. Various proximal operators were first constructed as applicable to quadratic IMRT constrained optimization and the problem was formulated in a graph form of ADMM. A pre-iteration operation for the projection of a point to a graph was also proposed to further accelerate the computation. Result: The graph form ADMM algorithm was tested by the Common Optimization for Radiation Therapy (CORT) dataset including TG119, prostate, liver, and head & neck cases. Both unconstrained and constrained optimization problems were formulated for comparison purposes. All optimizations were solved by LBFGS, IPOPT, Matlab built-in toolbox, CVX (implementing SeDuMi) and Mosek solvers. For unconstrained optimization, it was found that LBFGS performs the best, and it was 3–5 times faster than graph form ADMM. However, for constrained optimization, graph form ADMM was 8 – 100 times faster than the other solvers. Conclusion: A graph form ADMM can be applied to constrained quadratic IMRT optimization. It is more computationally efficient than several other commercial and noncommercial optimizers and it also

Constrained Dynamic Optimality and Binomial Terminal Wealth

DEFF Research Database (Denmark)

Pedersen, J. L.; Peskir, G.

2018-01-01

with interest rate $r \\in {R}$). Letting $P_{t,x}$ denote a probability measure under which $X^u$ takes value $x$ at time $t,$ we study the dynamic version of the nonlinear optimal control problem $\\inf_u\\, Var{t,X_t^u}(X_T^u)$ where the infimum is taken over admissible controls $u$ subject to $X_t^u \\ge e...... a martingale method combined with Lagrange multipliers, we derive the dynamically optimal control $u_*^d$ in closed form and prove that the dynamically optimal terminal wealth $X_T^d$ can only take two values $g$ and $\\beta$. This binomial nature of the dynamically optimal strategy stands in sharp contrast...... with other known portfolio selection strategies encountered in the literature. A direct comparison shows that the dynamically optimal (time-consistent) strategy outperforms the statically optimal (time-inconsistent) strategy in the problem....

Repercussão cardiovascular, com e sem álcool, do carbonato de lodenafila, um novo inibidor da PDE5 Repercusión cardiovascular, con y sin alcohol, del carbonato de lodenafila, un nuevo inhibidor de la PDE5 Cardiovascular repercussion of lodenafil carbonate, a new PDE5 inhibitor, with and without alcohol consumption

Directory of Open Access Journals (Sweden)

Adauto Carvalho Silva

2010-02-01

Full Text Available FUNDAMENTO: A disfunção erétil afeta um grande número de homens no mundo e os inibidores de PDE 5 (iPDE5 estão entre os principais métodos de tratamento desses pacientes. O consumo social de álcool e o ato sexual apresentam uma relação considerável. Portanto, a associação entre álcool e iPDE5 pode ocorrer. O carbonato de lodenafila é um novo iPDE5 desenvolvido por uma empresa brasileira. OBJETIVO: Avaliar a repercussão cardiovascular do carbonato de lodenafila, associado ou não ao álcool, assim como as alterações na farmacocinética que esta associação possa determinar. MÉTODOS: Estudo realizado com 15 voluntários sadios que receberam em momentos diferentes o carbonato de lodenafila (CL na dose de 160 mg em jejum, CL (160 mg com álcool, ou somente placebo. Esses pacientes foram monitorados por 24 horas, sendo avaliado o quadro clínico, a pressão arterial (PA, a frequência cardíaca (FC, o intervalo QT e também os dados de farmacocinética. RESULTADOS: O carbonato de lodenafila, isoladamente ou associado com álcool, não determinou alterações clínicas significativas na PA ou FC, embora tenha ocorrido diminuição da PA estatisticamente significativa após 4 horas, nos voluntários que receberam medicamento e álcool, assim como um aumento da FC após 6 horas nos pacientes que receberam o CL. A análise do intervalo QT corrigido não mostrou alteração significativa. O álcool aumentou a biodisponibilidade do medicamento em 74%. Houve somente 2 queixas de cefaleia leve, possivelmente associada ao medicamento. CONCLUSÃO: O carbonato de lodenafila, mesmo associado ao álcool, não determinou repercussões clínicas importantes na PA, FC, ou alterações no intervalo QTc; a ingestão com álcool, por sua vez, aumentou significativamente sua biodisponibilidade.FUNDAMENTO: La disfunción eréctil afecta a un gran número de hombres en el mundo y los inhibidores de PDE5 (iPDE5 están entre los principales métodos de

Pricing and lot sizing optimization in a two-echelon supply chain with a constrained Logit demand function

Directory of Open Access Journals (Sweden)

Yeison Díaz-Mateus

2017-07-01

Full Text Available Decision making in supply chains is influenced by demand variations, and hence sales, purchase orders and inventory levels are therefore concerned. This paper presents a non-linear optimization model for a two-echelon supply chain, for a unique product. In addition, the model includes the consumers’ maximum willingness to pay, taking socioeconomic differences into account. To do so, the constrained multinomial logit for discrete choices is used to estimate demand levels. Then, a metaheuristic approach based on particle swarm optimization is proposed to determine the optimal product sales price and inventory coordination variables. To validate the proposed model, a supply chain of a technological product was chosen and three scenarios are analyzed: discounts, demand segmentation and demand overestimation. Results are analyzed on the basis of profits, lotsizing and inventory turnover and market share. It can be concluded that the maximum willingness to pay must be taken into consideration, otherwise fictitious profits may mislead decision making, and although the market share would seem to improve, overall profits are not in fact necessarily better.

Assessment of electricity demand-supply in health facilities in resource-constrained settings : optimization and evaluation of energy systems for a case in Rwanda

NARCIS (Netherlands)

Palacios, S.G.

2015-01-01

In health facilities in resource-constrained settings, a lack of access to sustainable and reliable electricity can result on a sub-optimal delivery of healthcare services, as they do not have lighting for medical procedures and power to run essential equipment and devices to treat their patients.

Pharmacological characterization of a novel phosphodiesterase type 5 (PDE5) inhibitor lodenafil carbonate on human and rabbit corpus cavernosum.

Science.gov (United States)

Toque, Haroldo A; Teixeira, Cleber E; Lorenzetti, Raquel; Okuyama, Cristina E; Antunes, Edson; De Nucci, Gilberto

2008-09-04

Nitrergic nerves and endothelial cells release nitric oxide (NO) in the corpus cavernosum, a key mediator that stimulates soluble guanylyl cyclase to increase cGMP levels causing penile erection. Phosphodiesterase 5 (PDE5) inhibitors, such as sildenafil, prolong the NO effects by inhibiting cGMP breakdown. Here, we report a novel PDE5 inhibitor, lodenafil carbonate, (Bis-(2-{4-[4-ethoxy-3-(1-methyl-7-oxo-3-propyl-6,7-dihydro-1H-pyrazolo[4,3-d]pyrimidin-5-yl)-benzenesulfonyl]piperazin-1-yl}-ethyl)carbonate) that is a dimer of lodenafil. We therefore aimed to compare the effects of sildenafil, lodenafil and lodenafil carbonate on in vitro human and rabbit cavernosal relaxations, activity of crude PDE extracts from human platelets, as well as stability and metabolic studies in rat, dog and human plasma. Pharmacokinetic evaluations after intravenous and oral administration were performed in male beagles. Functional experiments were conducted using organ bath techniques. Pharmacokinetics was studied in beagles by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), following oral or intravascular administration. All PDE5 inhibitors tested concentration-dependently relaxed (0.001-100 microM) phenylephrine-precontracted rabbit and human corpus cavernosum. The cavernosal relaxations evoked by either acetylcholine (0.01-100 microM) or electrical field stimulation (EFS, 1-20 Hz) were markedly potentiated by sildenafil, lodenafil and lodenafil carbonate. Lodenafil carbonate was more potent to inhibit the cGMP hydrolysis in PDE extracts compared with lodenafil and sildenafil. Following intravascular and single oral administration of lodenafil carbonate, only lodenafil and norlodenafil were detected in vivo. These results indicate that lodenafil carbonate works as a prodrug, being lodenafil the active moiety of lodenafil carbonate.

Viscoelastic material inversion using Sierra-SD and ROL

Energy Technology Data Exchange (ETDEWEB)

Walsh, Timothy [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Aquino, Wilkins [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ridzal, Denis [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kouri, Drew Philip [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); van Bloemen Waanders, Bart Gustaaf [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Urbina, Angel [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2014-11-01

In this report we derive frequency-domain methods for inverse characterization of the constitutive parameters of viscoelastic materials. The inverse problem is cast in a PDE-constrained optimization framework with efficient computation of gradients and Hessian vector products through matrix free operations. The abstract optimization operators for first and second derivatives are derived from first principles. Various methods from the Rapid Optimization Library (ROL) are tested on the viscoelastic inversion problem. The methods described herein are applied to compute the viscoelastic bulk and shear moduli of a foam block model, which was recently used in experimental testing for viscoelastic property characterization.

Key role of phosphodiesterase 4A (PDE4A) in autophagy triggered by yessotoxin

International Nuclear Information System (INIS)

Fernández-Araujo, A.; Alfonso, A.; Vieytes, M.R.; Botana, L.M.

2015-01-01

Highlights: • YTX activates autophagic cell death after 48 h of treatment. • After 24 h of YTX incubation, the autophagic LC3B expression is increased. • High LC3B levels after 24 h can be related with extrinsic apoptosis activated by YTX. • PDEA4 plays a key role in the autophagy activation. - Abstract: Understanding the mechanism of action of the yessotoxin (YTX) is crucial since this drug has potential pharmacological effects in allergic processes, tumor proliferation and neurodegenerative diseases. It has been described that YTX activates apoptosis after 24 h of treatment, while after 48 h of incubation with the toxin a decrease in cell viability corresponding to cellular differentiation or non-apoptotic cell death was observed. In this paper, these processes were extensively studied by using the erythroleukemia K-562 cell line. On one hand, events of K-562 cell differentiation into erythrocytes after YTX treatment were studied using hemin as positive control of cell differentiation. Cell differentiation was studied through the cyclic nucleotide response element binding (phospho-CREB) and the transferrin receptor (TfR) expression. On the other hand, using rapamycin as positive control, autophagic hallmarks, as non-apoptotic cell death, were studied after toxin exposure. In this case, the mechanistic target of rapamycin (mTOR) and light chain 3B (LC3B) levels were measured to check autophagy activation. The results showed that cell differentiation was not occurring after 48 h of toxin incubation while at this time the autophagy was triggered. Furthermore after 24 h of toxin treatment none of these processes were activated. In addition, the role of the type 4A phosphodiesterase (PDE4A), the intracellular target of YTX, was checked. PDE4A-silencing experiments showed different regulation steps of PDE4A in the autophagic processes triggered either by traditional compounds or YTX. In summary, after 48 h YTX treatment PDE4A-dependent autophagy, as non

Multi-objective hybrid PSO-APO algorithm based security constrained optimal power flow with wind and thermal generators

Directory of Open Access Journals (Sweden)

Kiran Teeparthi

2017-04-01

Full Text Available In this paper, a new low level with teamwork heterogeneous hybrid particle swarm optimization and artificial physics optimization (HPSO-APO algorithm is proposed to solve the multi-objective security constrained optimal power flow (MO-SCOPF problem. Being engaged with the environmental and total production cost concerns, wind energy is highly penetrating to the main grid. The total production cost, active power losses and security index are considered as the objective functions. These are simultaneously optimized using the proposed algorithm for base case and contingency cases. Though PSO algorithm exhibits good convergence characteristic, fails to give near optimal solution. On the other hand, the APO algorithm shows the capability of improving diversity in search space and also to reach a near global optimum point, whereas, APO is prone to premature convergence. The proposed hybrid HPSO-APO algorithm combines both individual algorithm strengths, to get balance between global and local search capability. The APO algorithm is improving diversity in the search space of the PSO algorithm. The hybrid optimization algorithm is employed to alleviate the line overloads by generator rescheduling during contingencies. The standard IEEE 30-bus and Indian 75-bus practical test systems are considered to evaluate the robustness of the proposed method. The simulation results reveal that the proposed HPSO-APO method is more efficient and robust than the standard PSO and APO methods in terms of getting diverse Pareto optimal solutions. Hence, the proposed hybrid method can be used for the large interconnected power system to solve MO-SCOPF problem with integration of wind and thermal generators.

Pricing index-based catastrophe bonds: Part 1: Formulation and discretization issues using a numerical PDE approach

Science.gov (United States)

Unger, André J. A.

2010-02-01

This work is the first installment in a two-part series, and focuses on the development of a numerical PDE approach to price components of a Bermudan-style callable catastrophe (CAT) bond. The bond is based on two underlying stochastic variables; the PCS index which posts quarterly estimates of industry-wide hurricane losses as well as a single-factor CIR interest rate model for the three-month LIBOR. The aggregate PCS index is analogous to losses claimed under traditional reinsurance in that it is used to specify a reinsurance layer. The proposed CAT bond model contains a Bermudan-style call feature designed to allow the reinsurer to minimize their interest rate risk exposure on making substantial fixed coupon payments using capital from the reinsurance premium. Numerical PDE methods are the fundamental strategy for pricing early-exercise constraints, such as the Bermudan-style call feature, into contingent claim models. Therefore, the objective and unique contribution of this first installment in the two-part series is to develop a formulation and discretization strategy for the proposed CAT bond model utilizing a numerical PDE approach. Object-oriented code design is fundamental to the numerical methods used to aggregate the PCS index, and implement the call feature. Therefore, object-oriented design issues that relate specifically to the development of a numerical PDE approach for the component of the proposed CAT bond model that depends on the PCS index and LIBOR are described here. Formulation, numerical methods and code design issues that relate to aggregating the PCS index and introducing the call option are the subject of the companion paper.

On the optimal identification of tag sets in time-constrained RFID configurations.

Science.gov (United States)

Vales-Alonso, Javier; Bueno-Delgado, María Victoria; Egea-López, Esteban; Alcaraz, Juan José; Pérez-Mañogil, Juan Manuel

2011-01-01

In Radio Frequency Identification facilities the identification delay of a set of tags is mainly caused by the random access nature of the reading protocol, yielding a random identification time of the set of tags. In this paper, the cumulative distribution function of the identification time is evaluated using a discrete time Markov chain for single-set time-constrained passive RFID systems, namely those ones where a single group of tags is assumed to be in the reading area and only for a bounded time (sojourn time) before leaving. In these scenarios some tags in a set may leave the reader coverage area unidentified. The probability of this event is obtained from the cumulative distribution function of the identification time as a function of the sojourn time. This result provides a suitable criterion to minimize the probability of losing tags. Besides, an identification strategy based on splitting the set of tags in smaller subsets is also considered. Results demonstrate that there are optimal splitting configurations that reduce the overall identification time while keeping the same probability of losing tags.

Current drug therapy of patients with BPH-LUTS with the special emphasis on PDE5 inhibitors.

Science.gov (United States)

Kolontarev, Konstantin; Govorov, Alexander; Kasyan, George; Priymak, Diana; Pushkar, Dmitry

2016-01-01

Benign prostatic hyperplasia (BPH) is the most common cause of lower urinary tract symptom (LUTS) development in men [1]. The intensity of the symptoms may vary from mild to severe, significantly affecting the quality of life. Erectile dysfunction (ED) is one of the most challenging issues in modern urology that significantly influences the quality of life in men worldwide. The objective of this literature review was to analyze the current drug therapies of patients with BPH-LUTS, with the special emphasis on PDE5 inhibitors. The authors searched the literature for the period from 2000 until 2015 in MEDLINE and PubMed. Twenty-three articles were selected based on their reliability. A detailed analysis of the selected papers was performed. Primary attention was given to articles describing the use of PDE5. Works describing the use of different groups of drugs in patients with BPH-LUTS were also selected. The current literature analysis suggests that the introduction of PDE5 inhibitors in clinical practice for the treatment of patients with BPH-LUTS will allow for significant expansion of the therapeutic options for the treatment of this disease.

Simulation of Stochastic Processes by Coupled ODE-PDE

Science.gov (United States)

Zak, Michail

2008-01-01

A document discusses the emergence of randomness in solutions of coupled, fully deterministic ODE-PDE (ordinary differential equations-partial differential equations) due to failure of the Lipschitz condition as a new phenomenon. It is possible to exploit the special properties of ordinary differential equations (represented by an arbitrarily chosen, dynamical system) coupled with the corresponding Liouville equations (used to describe the evolution of initial uncertainties in terms of joint probability distribution) in order to simulate stochastic processes with the proscribed probability distributions. The important advantage of the proposed approach is that the simulation does not require a random-number generator.

Functions of PDE3 Isoforms in Cardiac Muscle

Science.gov (United States)

Movsesian, Matthew; Ahmad, Faiyaz

2018-01-01

Isoforms in the PDE3 family of cyclic nucleotide phosphodiesterases have important roles in cyclic nucleotide-mediated signalling in cardiac myocytes. These enzymes are targeted by inhibitors used to increase contractility in patients with heart failure, with a combination of beneficial and adverse effects on clinical outcomes. This review covers relevant aspects of the molecular biology of the isoforms that have been identified in cardiac myocytes; the roles of these enzymes in modulating cAMP-mediated signalling and the processes mediated thereby; and the potential for targeting these enzymes to improve the profile of clinical responses. PMID:29415428

Statistical mechanics of budget-constrained auctions

OpenAIRE

Altarelli, F.; Braunstein, A.; Realpe-Gomez, J.; Zecchina, R.

2009-01-01

Finding the optimal assignment in budget-constrained auctions is a combinatorial optimization problem with many important applications, a notable example being the sale of advertisement space by search engines (in this context the problem is often referred to as the off-line AdWords problem). Based on the cavity method of statistical mechanics, we introduce a message passing algorithm that is capable of solving efficiently random instances of the problem extracted from a natural distribution,...

Experimental design approach to the process parameter optimization for laser welding of martensitic stainless steels in a constrained overlap configuration

Science.gov (United States)

Khan, M. M. A.; Romoli, L.; Fiaschi, M.; Dini, G.; Sarri, F.

2011-02-01

This paper presents an experimental design approach to process parameter optimization for the laser welding of martensitic AISI 416 and AISI 440FSe stainless steels in a constrained overlap configuration in which outer shell was 0.55 mm thick. To determine the optimal laser-welding parameters, a set of mathematical models were developed relating welding parameters to each of the weld characteristics. These were validated both statistically and experimentally. The quality criteria set for the weld to determine optimal parameters were the minimization of weld width and the maximization of weld penetration depth, resistance length and shearing force. Laser power and welding speed in the range 855-930 W and 4.50-4.65 m/min, respectively, with a fiber diameter of 300 μm were identified as the optimal set of process parameters. However, the laser power and welding speed can be reduced to 800-840 W and increased to 4.75-5.37 m/min, respectively, to obtain stronger and better welds.

Convex optimisation approach to constrained fuel optimal control of spacecraft in close relative motion

Science.gov (United States)

Massioni, Paolo; Massari, Mauro

2018-05-01

This paper describes an interesting and powerful approach to the constrained fuel-optimal control of spacecraft in close relative motion. The proposed approach is well suited for problems under linear dynamic equations, therefore perfectly fitting to the case of spacecraft flying in close relative motion. If the solution of the optimisation is approximated as a polynomial with respect to the time variable, then the problem can be approached with a technique developed in the control engineering community, known as "Sum Of Squares" (SOS), and the constraints can be reduced to bounds on the polynomials. Such a technique allows rewriting polynomial bounding problems in the form of convex optimisation problems, at the cost of a certain amount of conservatism. The principles of the techniques are explained and some application related to spacecraft flying in close relative motion are shown.

The multinational Men's Attitudes to Life Events and Sexuality (MALES) Study Phase II: understanding PDE5 inhibitor treatment seeking patterns, among men with erectile dysfunction.

Science.gov (United States)

Fisher, William A; Rosen, Raymond C; Eardley, Ian; Niederberger, Craig; Nadel, Andrea; Kaufman, Joel; Sand, Michael

2004-09-01

The aim of Phase II of the Men's Attitudes to Life Events and Sexuality (MALES) Study is to explore PDE5 inhibitor treatment seeking among men with erectile dysfunction (ED). Phase II of the MALES study involved 2,912 men, aged 20-75 years, from 8 countries (U.S., U.K., Germany, France, Italy, Spain, Mexico, and Brazil), who reported ED. Participants were recruited from the MALES Phase I sample [1] and via booster methods (e.g., physician referral, street interception), and completed self-report questionnaires concerning the characteristics of their ED, their efforts to seek PDE5 inhibitor treatment for their sexual dysfunction, and attitudinal and referent influences that potentially affect treatment-seeking. Statistical analyses focus on identification of correlates of PDE5 inhibitor treatment seeking. PDE5 inhibitor utilization is strongly associated with ED sufferers' assessment of the severity of their sexual dysfunction, with their belief that medication for ED is dangerous, and with their perceptions of whether physicians, other professionals, and spouses or family members are supportive of their seeking treatment. ED sufferers who evaluate their sexual dysfunction as severe, who believe that medication for ED is not dangerous, and who perceive support for treatment seeking from referent others, are more likely to utilize PDE5 inhibitor treatment. Findings indicate that perceived ED severity, beliefs about ED medication, and referent influences are strongly correlated with utilization of PDE5 inhibitor therapy. These findings aid our understanding of factors that may incline men with ED to seek-or to avoid-PDE5 inhibitor therapy for their sexual dysfunction, and provide a basis for clinical and educational interventions to assist men with ED to seek appropriate treatment.

Joint Optimal Production Planning for Complex Supply Chains Constrained by Carbon Emission Abatement Policies

Directory of Open Access Journals (Sweden)

Longfei He

2014-01-01

Full Text Available We focus on the joint production planning of complex supply chains facing stochastic demands and being constrained by carbon emission reduction policies. We pick two typical carbon emission reduction policies to research how emission regulation influences the profit and carbon footprint of a typical supply chain. We use the input-output model to capture the interrelated demand link between an arbitrary pair of two nodes in scenarios without or with carbon emission constraints. We design optimization algorithm to obtain joint optimal production quantities combination for maximizing overall profit under regulatory policies, respectively. Furthermore, numerical studies by featuring exponentially distributed demand compare systemwide performances in various scenarios. We build the “carbon emission elasticity of profit (CEEP” index as a metric to evaluate the impact of regulatory policies on both chainwide emissions and profit. Our results manifest that by facilitating the mandatory emission cap in proper installation within the network one can balance well effective emission reduction and associated acceptable profit loss. The outcome that CEEP index when implementing Carbon emission tax is elastic implies that the scale of profit loss is greater than that of emission reduction, which shows that this policy is less effective than mandatory cap from industry standpoint at least.

Modulation of oxazolone-induced hypersensitivity in mice by selective PDE inhibitors

Directory of Open Access Journals (Sweden)

I. Moodley

1995-01-01

Full Text Available The effects of PDE inhibitors on oxazolone-induced contact hypersensitivity (CS were studied in mice. Rolipram, Ro 20-1724 and theophylline dose dependently inhibited CS but none caused >53% inhibition. ED30 values at 24 h before challenge for rolipram, Ro 20-1724 and theophylline were 2.1, 5.4 and 30.4 mg/kg, p.o., respectively. Milrinone and SKF 94836 at 30 mg/kg caused a small, but significant inhibition of 13% and 18%, respectively, although the inhibition (8% caused by zaprinast was not significant. Betamethasone (10 mg/kg, p.o. caused a marked inhibition (80% as did indomethacin (65% at 5 mg/kg, p.o.. Rolipram and Ro 20-1724 inhibited proliferation of mouse lymphoblasts with IC50 values of 0.08 μM and 0.83 μM, respectively. In contrast, zaprinast caused only a weak inhibition (IC50 = 119 μM of lymphocyte proliferation, whereas SKF 94836 and theophylline failed to cause any significant inhibition at 100 μM (26% and 2%, respectively. These findings suggest that PDE IV isozymes play a principal role in mediating CS by inhibiting lymphocyte activation.

PDE5 inhibitor treatment persistence and adherence in Brazilian men: post-hoc analyses from a 6-month, prospective, observational study.

Science.gov (United States)

Cairoli, Carlos; Reyes, Luis Antonio; Henneges, Carsten; Sorsaburu, Sebastian

2014-01-01

Characterize persistence and adherence to phosphodiesterase type - 5 inhibitor (PDE5I) on-demand therapy over 6 months among Brazilian men in an observational, non-interventional study of Latin American men naïve to PDE5Is with erectile dysfunction (ED). Men were prescribed PDE5Is per routine clinical practice. Persistence was defined as using ≥ 1 dose during the previous 4 - weeks, and adherence as following dosing instructions for the most recent dose, assessed using the Persistence and Adherence Questionnaire. Other measures included the Self - Esteem and Relationship (SEAR) Questionnaire, and International Index of Erectile Function (IIEF). Multivariate logistic regression was used to identify factors associated with persistence/adherence. 104 Brazilian men were enrolled; mean age by treatment was 53 to 59 years, and most presented with moderate ED (61.7%). The prescribed PDE5I was sildenafil citrate for 50 (48.1%), tadalafil for 36 (34.6%), vardenafil for 15 (14.4%), and lodenafil for 3 patients (2.9%). Overall treatment persistence was 69.2% and adherence was 70.2%; both were numerically higher with tadalafil (75.0%) versus sildenafil or vardenafil (range 60.0% to 68.0%). Potential associations of persistence and/or adherence were observed with education level, ED etiology, employment status, and coronary artery disease. Improvements in all IIEF domain scores, and both SEAR domain scores were observed for all treatments. Study limitations included the observational design, brief duration, dependence on patient self - reporting, and limited sample size. Approximately two-thirds of PDE5I-naive, Brazilian men with ED were treatment persistent and adherent after 6 months. Further study is warranted to improve long-term outcomes of ED treatment.

PKA and PDE4D3 anchoring to AKAP9 provides distinct regulation of cAMP signals at the centrosome

Science.gov (United States)

Terrin, Anna; Monterisi, Stefania; Stangherlin, Alessandra; Zoccarato, Anna; Koschinski, Andreas; Surdo, Nicoletta C.; Mongillo, Marco; Sawa, Akira; Jordanides, Niove E.; Mountford, Joanne C.

2012-01-01

Previous work has shown that the protein kinase A (PKA)–regulated phosphodiesterase (PDE) 4D3 binds to A kinase–anchoring proteins (AKAPs). One such protein, AKAP9, localizes to the centrosome. In this paper, we investigate whether a PKA–PDE4D3–AKAP9 complex can generate spatial compartmentalization of cyclic adenosine monophosphate (cAMP) signaling at the centrosome. Real-time imaging of fluorescence resonance energy transfer reporters shows that centrosomal PDE4D3 modulated a dynamic microdomain within which cAMP concentration selectively changed over the cell cycle. AKAP9-anchored, centrosomal PKA showed a reduced activation threshold as a consequence of increased autophosphorylation of its regulatory subunit at S114. Finally, disruption of the centrosomal cAMP microdomain by local displacement of PDE4D3 impaired cell cycle progression as a result of accumulation of cells in prophase. Our findings describe a novel mechanism of PKA activity regulation that relies on binding to AKAPs and consequent modulation of the enzyme activation threshold rather than on overall changes in cAMP levels. Further, we provide for the first time direct evidence that control of cell cycle progression relies on unique regulation of centrosomal cAMP/PKA signals. PMID:22908311

Using system theory and energy methods to prove existence of non-linear PDE's

NARCIS (Netherlands)

Zwart, H.J.

2015-01-01

In this discussion paper we present an idea of combining techniques known from systems theory with energy estimates to show existence for a class of non-linear partial differential equations (PDE's). At the end of the paper a list of research questions with possible approaches is given.

PDE4 and mAKAPβ are nodal organizers of β2-ARs nuclear PKA signaling in cardiac myocytes.

Science.gov (United States)

Bedioune, Ibrahim; Lefebvre, Florence; Lechêne, Patrick; Varin, Audrey; Domergue, Valérie; Kapiloff, Michael S; Fischmeister, Rodolphe; Vandecasteele, Grégoire

2018-05-03

β1- and β2-adrenergic receptors (β-ARs) produce different acute contractile effects on the heart partly because they impact on different cytosolic pools of cAMP-dependent protein kinase (PKA). They also exert different effects on gene expression but the underlying mechanisms remain unknown. The aim of this study was to understand the mechanisms by which β1- and β2-ARs regulate nuclear PKA activity in cardiomyocytes. We used cytoplasmic and nuclear targeted biosensors to examine cAMP signals and PKA activity in adult rat ventricular myocytes upon selective β1- or β2-ARs stimulation. Both β1- and β2-AR stimulation increased cAMP and activated PKA in the cytoplasm. While the two receptors also increased cAMP in the nucleus, only β1-ARs increased nuclear PKA activity and up-regulated the PKA target gene and pro-apoptotic factor, inducible cAMP element repressor (ICER). Inhibition of PDE4, but not Gi, PDE3, GRK2 nor caveolae disruption disclosed nuclear PKA activation and ICER induction by β2-ARs. Both nuclear and cytoplasmic PKI prevented nuclear PKA activation and ICER induction by β1-ARs, indicating that PKA activation outside the nucleus is required for subsequent nuclear PKA activation and ICER mRNA expression. Cytoplasmic PKI also blocked ICER induction by β2-AR stimulation (with concomitant PDE4 inhibition). However, in this case nuclear PKI decreased ICER up-regulation by only 30%, indicating that other mechanisms are involved. Down-regulation of mAKAPβ partially inhibited nuclear PKA activation upon β1-AR stimulation, and drastically decreased nuclear PKA activation upon β2-AR stimulation in the presence of PDE4 inhibition. β1- and β2-ARs differentially regulate nuclear PKA activity and ICER expression in cardiomyocytes. PDE4 insulates a mAKAPβ-targeted PKA pool at the nuclear envelope that prevents nuclear PKA activation upon β2-AR stimulation.

SmartFix: Indoor Locating Optimization Algorithm for Energy-Constrained Wearable Devices

Directory of Open Access Journals (Sweden)

Xiaoliang Wang

2017-01-01

Full Text Available Indoor localization technology based on Wi-Fi has long been a hot research topic in the past decade. Despite numerous solutions, new challenges have arisen along with the trend of smart home and wearable computing. For example, power efficiency needs to be significantly improved for resource-constrained wearable devices, such as smart watch and wristband. For a Wi-Fi-based locating system, most of the energy consumption can be attributed to real-time radio scan; however, simply reducing radio data collection will cause a serious loss of locating accuracy because of unstable Wi-Fi signals. In this paper, we present SmartFix, an optimization algorithm for indoor locating based on Wi-Fi RSS. SmartFix utilizes user motion features, extracts characteristic value from history trajectory, and corrects deviation caused by unstable Wi-Fi signals. We implemented a prototype of SmartFix both on Moto 360 2nd-generation Smartwatch and on HTC One Smartphone. We conducted experiments both in a large open area and in an office hall. Experiment results demonstrate that average locating error is less than 2 meters for more than 80% cases, and energy consumption is only 30% of Wi-Fi fingerprinting method under the same experiment circumstances.

A 6 month, prospective, observational study of PDE5 inhibitor treatment persistence and adherence in Latin American men with erectile dysfunction.

Science.gov (United States)

Rubio-Aurioles, Eusebio; Reyes, Luis Antonio; Borregales, Leonardo; Cairoli, Carlos; Sorsaburu, Sebastian

2013-06-01

To assess persistence/adherence rates of phosphodiesterase type-5 inhibitor (PDE5I) on-demand dosing in Latin American men with erectile dysfunction (ED), and explore patient characteristics and treatment factors that may be predictive for PDE5I persistence and adherence. Men from Brazil, Mexico, and Venezuela with ED who were naïve to PDE5Is were prescribed sildenafil, tadalafil, vardenafil, or lodenafil on-demand dosing and asked to provide information about PDE5I use at baseline and at 1, 3, and 6 months. Patients were persistent if they used ≥1 dose during the 4 week period prior to each evaluation. Patients were adherent if they complied with dosing instructions during most recent dose. Main outcome measures included Persistence and Adherence Questionnaire (PAQ), Partner Relationship Questionnaire (PRQ), Self-Esteem and Relationship (SEAR) Questionnaire, and International Index of Erectile Function (IIEF). Multivariate logistic regression was used to identify factors associated with persistence and adherence. A total of 511 men were enrolled; most had mild to moderate ED (77.1%); 317 patients (62.0%) were prescribed tadalafil, 116 (22.7%) sildenafil, 75 (14.7%) vardenafil, and 3 (0.6%) lodenafil (not further analyzed). A total of 340 patients (66.5%) were 'persistent' at 6 months; 345 (67.5%) were 'adherent'. Persistence and adherence were associated with age, education level, and ED duration. Reasons for non-persistence included medication cost and lack of efficacy. Study limitations included its design, brief observation period, its bias observed toward tadalafil selection; its dependence on patient self-reporting, limited number of factors that were analyzed for persistence/adherence association, its small number of participating patients and Latin American countries, and inherent differences in PDE5I preference and medical practices. Approximately two-thirds of PDE5I-naïve, Latin American men with ED were persistent and adherent after 6 months of

PDE5 Inhibitor Treatment Persistence and Adherence in Brazilian Men: Post-hoc Analyses from a 6-Month, Prospective, Observational Study

Directory of Open Access Journals (Sweden)

Carlos Cairoli

2014-06-01

Full Text Available Purpose Characterize persistence and adherence to phosphodiesterase type - 5 inhibitor (PDE5I on-demand therapy over 6 months among Brazilian men in an observational, non-interventional study of Latin American men naïve to PDE5Is with erectile dysfunction (ED. Materials and Methods Men were prescribed PDE5Is per routine clinical practice. Persistence was defined as using ≥ 1 dose during the previous 4 - weeks, and adherence as following dosing instructions for the most recent dose, assessed using the Persistence and Adherence Questionnaire. Other measures included the Self - Esteem and Relationship (SEAR Questionnaire, and International Index of Erectile Function (IIEF. Multivariate logistic regression was used to identify factors associated with persistence/adherence. Results 104 Brazilian men were enrolled; mean age by treatment was 53 to 59 years, and most presented with moderate ED (61.7%. The prescribed PDE5I was sildenafil citrate for 50 (48.1%, tadalafil for 36 (34.6%, vardenafil for 15 (14.4%, and lodenafil for 3 patients (2.9%. Overall treatment persistence was 69.2% and adherence was 70.2%; both were numerically higher with tadalafil (75.0% versus sildenafil or vardenafil (range 60.0% to 68.0%. Potential associations of persistence and/or adherence were observed with education level, ED etiology, employment status, and coronary artery disease. Improvements in all IIEF domain scores, and both SEAR domain scores were observed for all treatments. Study limitations included the observational design, brief duration, dependence on patient self - reporting, and limited sample size. Conclusion Approximately two-thirds of PDE5I-naive, Brazilian men with ED were treatment persistent and adherent after 6 months. Further study is warranted to improve long-term outcomes of ED treatment.

In Silico Investigations of Chemical Constituents of Clerodendrum colebrookianum in the Anti-Hypertensive Drug Targets: ROCK, ACE, and PDE5.

Science.gov (United States)

Arya, Hemant; Syed, Safiulla Basha; Singh, Sorokhaibam Sureshkumar; Ampasala, Dinakar R; Coumar, Mohane Selvaraj

2017-06-16

Understanding the molecular mode of action of natural product is a key step for developing drugs from them. In this regard, this study is aimed to understand the molecular-level interactions of chemical constituents of Clerodendrum colebrookianum Walp., with anti-hypertensive drug targets using computational approaches. The plant has ethno-medicinal importance for the treatment of hypertension and reported to show activity against anti-hypertensive drug targets-Rho-associated coiled-coil protein kinase (ROCK), angiotensin-converting enzyme, and phosphodiesterase 5 (PDE5). Docking studies showed that three chemical constituents (acteoside, martinoside, and osmanthuside β6) out of 21 reported from the plant to interact with the anti-hypertensive drug targets with good glide score. In addition, they formed H-bond interactions with the key residues Met156/Met157 of ROCK I/ROCK II and Gln817 of PDE5. Further, molecular dynamics (MD) simulation of protein-ligand complexes suggest that H-bond interactions between acteoside/osmanthuside β6 and Met156/Met157 (ROCK I/ROCK II), acteoside and Gln817 (PDE5) were stable. The present investigation suggests that the anti-hypertensive activity of the plant is due to the interaction of acteoside and osmanthuside β6 with ROCK and PDE5 drug targets. The identified molecular mode of binding of the plant constituents could help to design new drugs to treat hypertension.

Inhibition of the striatal specific phosphodiesterase PDE10A ameliorates striatal and cortical pathology in R6/2 mouse model of Huntington's disease.

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Carmela Giampà

2010-10-01

Full Text Available Huntington's disease is a devastating neurodegenerative condition for which there is no therapy to slow disease progression. The particular vulnerability of striatal medium spiny neurons to Huntington's pathology is hypothesized to result from transcriptional dysregulation within the cAMP and CREB signaling cascades in these neurons. To test this hypothesis, and a potential therapeutic approach, we investigated whether inhibition of the striatal-specific cyclic nucleotide phosphodiesterase PDE10A would alleviate neurological deficits and brain pathology in a highly utilized model system, the R6/2 mouse.R6/2 mice were treated with the highly selective PDE10A inhibitor TP-10 from 4 weeks of age until euthanasia. TP-10 treatment significantly reduced and delayed the development of the hind paw clasping response during tail suspension, deficits in rotarod performance, and decrease in locomotor activity in an open field. Treatment prolonged time to loss of righting reflex. These effects of PDE10A inhibition on neurological function were reflected in a significant amelioration in brain pathology, including reduction in striatal and cortical cell loss, the formation of striatal neuronal intranuclear inclusions, and the degree of microglial activation that occurs in response to the mutant huntingtin-induced brain damage. Striatal and cortical levels of phosphorylated CREB and BDNF were significantly elevated.Our findings provide experimental support for targeting the cAMP and CREB signaling pathways and more broadly transcriptional dysregulation as a therapeutic approach to Huntington's disease. It is noteworthy that PDE10A inhibition in the R6/2 mice reduces striatal pathology, consistent with the localization of the enzyme in medium spiny neurons, and also cortical pathology and the formation of neuronal nuclear inclusions. These latter findings suggest that striatal pathology may be a primary driver of these secondary pathological events. More

Constraining neutron guide optimizations with phase-space considerations

Energy Technology Data Exchange (ETDEWEB)

Bertelsen, Mads, E-mail: mads.bertelsen@gmail.com; Lefmann, Kim

2016-09-11

We introduce a method named the Minimalist Principle that serves to reduce the parameter space for neutron guide optimization when the required beam divergence is limited. The reduced parameter space will restrict the optimization to guides with a minimal neutron intake that are still theoretically able to deliver the maximal possible performance. The geometrical constraints are derived using phase-space propagation from moderator to guide and from guide to sample, while assuming that the optimized guides will achieve perfect transport of the limited neutron intake. Guide systems optimized using these constraints are shown to provide performance close to guides optimized without any constraints, however the divergence received at the sample is limited to the desired interval, even when the neutron transport is not limited by the supermirrors used in the guide. As the constraints strongly limit the parameter space for the optimizer, two control parameters are introduced that can be used to adjust the selected subspace, effectively balancing between maximizing neutron transport and avoiding background from unnecessary neutrons. One parameter is needed to describe the expected focusing abilities of the guide to be optimized, going from perfectly focusing to no correlation between position and velocity. The second parameter controls neutron intake into the guide, so that one can select exactly how aggressively the background should be limited. We show examples of guides optimized using these constraints which demonstrates the higher signal to noise than conventional optimizations. Furthermore the parameter controlling neutron intake is explored which shows that the simulated optimal neutron intake is close to the analytically predicted, when assuming that the guide is dominated by multiple scattering events.

Improved solution for ill-posed linear systems using a constrained optimization ruled by a penalty: evaluation in nuclear medicine tomography

International Nuclear Information System (INIS)

Walrand, Stephan; Jamar, François; Pauwels, Stanislas

2009-01-01

Ill-posed linear systems occur in many different fields. A class of regularization methods, called constrained optimization, aims to determine the extremum of a penalty function whilst constraining an objective function to a likely value. We propose here a novel heuristic way to screen the local extrema satisfying the discrepancy principle. A modified version of the Landweber algorithm is used for the iteration process. After finding a local extremum, a bound is performed to the 'farthest' estimate in the data space still satisfying the discrepancy principle. Afterwards, the modified Landweber algorithm is again applied to find a new local extremum. This bound-iteration process is repeated until a satisfying solution is reached. For evaluation in nuclear medicine tomography, a novel penalty function that preserves the edge steps in the reconstructed solution was evaluated on Monte Carlo simulations and using real SPECT acquisitions as well. Surprisingly, the first bound always provided a significantly better solution in a wide range of statistics

[Cardiovascular repercussion of lodenafil carbonate, a new PDE5 inhibitor, with and without alcohol consumption].

Science.gov (United States)

Silva, Adauto Carvalho; Toffoletto, Odaly; Lucio, Luiz Antonio Galvão; Santos, Paula Ferreira Dos; Afiune, Jorge Barros; Massud Filho, João; Tufik, Sergio

2010-02-01

Millions of men around the world suffer from erectile dysfunction, for which phosphodiesterase 5 inhibitors (PDE-5 inhibitors) are currently the first treatment option. Sexual activity and alcohol consumption are closely related, and the simultaneous use of alcohol and PDE-5 inhibitors can happen. Lodenafil carbonate is a new PDE-5 inhibitor, developed by a Brazilian pharmaceutical company. This work aimed at evaluating the cardiovascular safety of lodenafil carbonate, with and without simultaneous alcohol consumption. Fifteen male volunteers received 160 mg lodenafil carbonate (LC), in three different moments. Participants were assigned to three groups, treated with LC in fasting condition, with alcohol or receiving only placebo. The volunteers were continuously monitored during 24 hours for physical impairment, blood pressure, heart rate, QT interval and lodenafil's pharmacokinetic parameters. Lodenafil carbonate alone or with alcohol did not induce clinically relevant modifications in arterial blood pressure or heart rate. A statistically significant decrease in blood pressure was seen four hours after LC and alcohol intake, and an increase in heart rate six hours after intake of lodenafil carbonate alone. The QTc interval was not significantly modified. Lodenafil carbonate bioavailability was increased in 74% when drug intake was associated with alcohol. These results show that the use of lodenafil carbonate did not have clinically relevant effects on blood pressure or heart rate, and was not associated with QT interval prolongation. The association of lodenafil carbonate and alcohol affected its pharmacokinetic properties, increasing the bioavailability of the drug.

Optimal moving grids for time-dependent partial differential equations

Science.gov (United States)

Wathen, A. J.

1992-01-01

Various adaptive moving grid techniques for the numerical solution of time-dependent partial differential equations were proposed. The precise criterion for grid motion varies, but most techniques will attempt to give grids on which the solution of the partial differential equation can be well represented. Moving grids are investigated on which the solutions of the linear heat conduction and viscous Burgers' equation in one space dimension are optimally approximated. Precisely, the results of numerical calculations of optimal moving grids for piecewise linear finite element approximation of PDE solutions in the least-squares norm are reported.

#DDOD Use Case: Access to Medicare Part D Drug Event File (PDE) for cost transparency

Data.gov (United States)

U.S. Department of Health & Human Services — SUMMARY DDOD use case to request access to Medicare Part D Drug Event File (PDE) for cost transparency to pharmacies and patients. WHAT IS A USE CASE? A “Use Case”...

PDE2A2 regulates mitochondria morphology and apoptotic cell death via local modulation of cAMP/PKA signalling.

Science.gov (United States)

Monterisi, Stefania; Lobo, Miguel J; Livie, Craig; Castle, John C; Weinberger, Michael; Baillie, George; Surdo, Nicoletta C; Musheshe, Nshunge; Stangherlin, Alessandra; Gottlieb, Eyal; Maizels, Rory; Bortolozzi, Mario; Micaroni, Massimo; Zaccolo, Manuela

2017-05-02

cAMP/PKA signalling is compartmentalised with tight spatial and temporal control of signal propagation underpinning specificity of response. The cAMP-degrading enzymes, phosphodiesterases (PDEs), localise to specific subcellular domains within which they control local cAMP levels and are key regulators of signal compartmentalisation. Several components of the cAMP/PKA cascade are located to different mitochondrial sub-compartments, suggesting the presence of multiple cAMP/PKA signalling domains within the organelle. The function and regulation of these domains remain largely unknown. Here, we describe a novel cAMP/PKA signalling domain localised at mitochondrial membranes and regulated by PDE2A2. Using pharmacological and genetic approaches combined with real-time FRET imaging and high resolution microscopy, we demonstrate that in rat cardiac myocytes and other cell types mitochondrial PDE2A2 regulates local cAMP levels and PKA-dependent phosphorylation of Drp1. We further demonstrate that inhibition of PDE2A, by enhancing the hormone-dependent cAMP response locally, affects mitochondria dynamics and protects from apoptotic cell death.

The NO/cGMP pathway inhibits transient cAMP signals through the activation of PDE2 in striatal neurons

Directory of Open Access Journals (Sweden)

Marina ePolito

2013-11-01

Full Text Available The NO-cGMP signaling plays an important role in the regulation of striatal function although the mechanisms of action of cGMP specifically in medium spiny neurons (MSNs remain unclear. Using genetically encoded fluorescent biosensors, including a novel Epac-based sensor (EPAC-SH150 with increased sensitivity for cAMP, we analyze the cGMP response to NO and whether it affected cAMP/PKA signaling in MSNs. The Cygnet2 sensor for cGMP reported large responses to NO donors in both striatonigral and striatopallidal MSNs, and this cGMP signal was controlled partially by PDE2. At the level of cAMP brief forskolin stimulations produced transient cAMP signals which differed between D1 and D2 medium spiny neurons. NO inhibited these cAMP transients through cGMP-dependent PDE2 activation, an effect that was translated and magnified downstream of cAMP, at the level of PKA. PDE2 thus appears as a critical effector of NO which modulates the post-synaptic response of MSNs to dopaminergic transmission.

[Efficacy and tolerance of PDE-5 in the treatment of erectile dysfunction in schizophrenic patients: A literature review].

Science.gov (United States)

Bacconi, L; Gressier, F

2017-02-01

Sexual dysfunction is an important public health problem in men and is associated with reduced quality of life. It is more common in patients with schizophrenia. It is well-established that antipsychotic drugs cause sexual dysfunction with consequences on the quality of life of patients, adherence to treatment, and public health costs. Phosphodiesterase type 5 inhibitors (PDE5 inhibitors) are indicated for the management of erectile dysfunction. However, there is little information on such treatment in schizophrenic patients. This literature review aimed to summarize the current data on the efficacy and tolerability of PDE-5 inhibitors in the erectile dysfunction in schizophrenic patients. PubMed, PsycInfo and Cochrane databases were searched for studies published until August 2014. Only 6 studies met the inclusion criteria. Three were randomized, double-blind, cross-over, placebo-controlled trials and three were open studies. Various scales were used to measure erectile and orgasmic function, desire, satisfaction during intercourse, overall satisfaction, quality of life and intensity of schizophrenic symptoms. In the 3 randomized studies (one with sildenafil 25-50 mg, one with lodenafil carbonate 80 mg/j and the last one with tadalafil 10 mg), the rate of participants who completed the trial was high (around 95 %). All three included patients with schizophrenia or schizophrenia spectrum disorders. Patients reported significant improvement on sexual dysfunction. However, no statistical difference was reported between lodenafil and placebo, on different scales, suggesting a very important placebo effect in patients with schizophrenia. All three found a good tolerance of PDE-5 inhibitors. Side effects were rare and were mainly nasal congestion, headaches, nausea and dizziness. There were no major side effects or drug interactions. Considering the 3 open studies, 2 involved sildenafil and one tadalafil. All concluded in improved erectile and orgasmic

Increase of Intracellular Cyclic AMP by PDE4 Inhibitors Affects HepG2 Cell Cycle Progression and Survival.

Science.gov (United States)

Massimi, Mara; Cardarelli, Silvia; Galli, Francesca; Giardi, Maria Federica; Ragusa, Federica; Panera, Nadia; Cinque, Benedetta; Cifone, Maria Grazia; Biagioni, Stefano; Giorgi, Mauro

2017-06-01

Type 4 cyclic nucleotide phosphodiesterases (PDE4) are major members of a superfamily of enzymes (PDE) involved in modulation of intracellular signaling mediated by cAMP. Broadly expressed in most human tissues and present in large amounts in the liver, PDEs have in the last decade been key therapeutic targets for several inflammatory diseases. Recently, a significant body of work has underscored their involvement in different kinds of cancer, but with no attention paid to liver cancer. The present study investigated the effects of two PDE4 inhibitors, rolipram and DC-TA-46, on the growth of human hepatoma HepG2 cells. Treatment with these inhibitors caused a marked increase of intracellular cAMP level and a dose- and time-dependent effect on cell growth. The concentrations of inhibitors that halved cell proliferation to about 50% were used for cell cycle experiments. Rolipram (10 μM) and DC-TA-46 (0.5 μM) produced a decrease of cyclin expression, in particular of cyclin A, as well as an increase in p21, p27 and p53, as evaluated by Western blot analysis. Changes in the intracellular localization of cyclin D1 were also observed after treatments. In addition, both inhibitors caused apoptosis, as demonstrated by an Annexin-V cytofluorimetric assay and analysis of caspase-3/7 activity. Results demonstrated that treatment with PDE4 inhibitors affected HepG2 cell cycle and survival, suggesting that they might be useful as potential adjuvant, chemotherapeutic or chemopreventive agents in hepatocellular carcinoma. J. Cell. Biochem. 118: 1401-1411, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Depletion mapping and constrained optimization to support managing groundwater extraction

Science.gov (United States)

Fienen, Michael N.; Bradbury, Kenneth R.; Kniffin, Maribeth; Barlow, Paul M.

2018-01-01

Groundwater models often serve as management tools to evaluate competing water uses including ecosystems, irrigated agriculture, industry, municipal supply, and others. Depletion potential mapping—showing the model-calculated potential impacts that wells have on stream baseflow—can form the basis for multiple potential management approaches in an oversubscribed basin. Specific management approaches can include scenarios proposed by stakeholders, systematic changes in well pumping based on depletion potential, and formal constrained optimization, which can be used to quantify the tradeoff between water use and stream baseflow. Variables such as the maximum amount of reduction allowed in each well and various groupings of wells using, for example, K-means clustering considering spatial proximity and depletion potential are considered. These approaches provide a potential starting point and guidance for resource managers and stakeholders to make decisions about groundwater management in a basin, spreading responsibility in different ways. We illustrate these approaches in the Little Plover River basin in central Wisconsin, United States—home to a rich agricultural tradition, with farmland and urban areas both in close proximity to a groundwater-dependent trout stream. Groundwater withdrawals have reduced baseflow supplying the Little Plover River below a legally established minimum. The techniques in this work were developed in response to engaged stakeholders with various interests and goals for the basin. They sought to develop a collaborative management plan at a watershed scale that restores the flow rate in the river in a manner that incorporates principles of shared governance and results in effective and minimally disruptive changes in groundwater extraction practices.

Fragment-assisted hit investigation involving integrated HTS and fragment screening: Application to the identification of phosphodiesterase 10A (PDE10A) inhibitors.

Science.gov (United States)

Varnes, Jeffrey G; Geschwindner, Stefan; Holmquist, Christopher R; Forst, Janet; Wang, Xia; Dekker, Niek; Scott, Clay W; Tian, Gaochao; Wood, Michael W; Albert, Jeffrey S

2016-01-01

Fragment-based drug design (FBDD) relies on direct elaboration of fragment hits and typically requires high resolution structural information to guide optimization. In fragment-assisted drug discovery (FADD), fragments provide information to guide selection and design but do not serve as starting points for elaboration. We describe FADD and high-throughput screening (HTS) campaign strategies conducted in parallel against PDE10A where fragment hit co-crystallography was not available. The fragment screen led to prioritized fragment hits (IC50's ∼500μM), which were used to generate a hypothetical core scaffold. Application of this scaffold as a filter to HTS output afforded a 4μM hit, which, after preparation of a small number of analogs, was elaborated into a 16nM lead. This approach highlights the strength of FADD, as fragment methods were applied despite the absence of co-crystallographical information to efficiently identify a lead compound for further optimization. Copyright © 2015 Elsevier Ltd. All rights reserved.

3Es System Optimization under Uncertainty Using Hybrid Intelligent Algorithm: A Fuzzy Chance-Constrained Programming Model

Directory of Open Access Journals (Sweden)

Jiekun Song

2016-01-01

Full Text Available Harmonious development of 3Es (economy-energy-environment system is the key to realize regional sustainable development. The structure and components of 3Es system are analyzed. Based on the analysis of causality diagram, GDP and industrial structure are selected as the target parameters of economy subsystem, energy consumption intensity is selected as the target parameter of energy subsystem, and the emissions of COD, ammonia nitrogen, SO2, and NOX and CO2 emission intensity are selected as the target parameters of environment system. Fixed assets investment of three industries, total energy consumption, and investment in environmental pollution control are selected as the decision variables. By regarding the parameters of 3Es system optimization as fuzzy numbers, a fuzzy chance-constrained goal programming (FCCGP model is constructed, and a hybrid intelligent algorithm including fuzzy simulation and genetic algorithm is proposed for solving it. The results of empirical analysis on Shandong province of China show that the FCCGP model can reflect the inherent relationship and evolution law of 3Es system and provide the effective decision-making support for 3Es system optimization.

The Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem

Directory of Open Access Journals (Sweden)

Denis Pinha

2016-11-01

Full Text Available This paper presents the formulation and solution of the Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem. The focus of the proposed method is not on finding a single optimal solution, instead on presenting multiple feasible solutions, with cost and duration information to the project manager. The motivation for developing such an approach is due in part to practical situations where the definition of optimal changes on a regular basis. The proposed approach empowers the project manager to determine what is optimal, on a given day, under the current constraints, such as, change of priorities, lack of skilled worker. The proposed method utilizes a simulation approach to determine feasible solutions, under the current constraints. Resources can be non-consumable, consumable, or doubly constrained. The paper also presents a real-life case study dealing with scheduling of ship repair activities.

Administration of PDE4 Inhibitors Suppressed the Pannus-Like Inflammation by Inhibition of Cytokine Production by Macrophages and Synovial Fibroblast Proliferation

Directory of Open Access Journals (Sweden)

Katsuya Kobayashi

2007-01-01

Full Text Available A marked proliferation of synovial fibroblasts in joints leads to pannus formation in rheumatoid arthritis (RA. Various kinds of cytokines are produced in the pannus. The purpose of this study is to elucidate the effects of phosphodiesterase 4 (PDE4 inhibitors in a new animal model for the evaluation of pannus formation and cytokine production in the pannus. Mice sensitized with methylated bovine serum albumin (mBSA were challenged by subcutaneous implantation of a membrane filter soaked in mBSA solution in the back of the mice. Drugs were orally administered for 10 days. The granuloma formed around the filter was collected on day 11. It was chopped into pieces and cultured in vitro for 24 hr. The cytokines were measured in the supernatants. The type of cytokines produced in the granuloma was quite similar to those produced in pannus in RA. Both PDE4 inhibitors, KF66490 and SB207499, suppressed the production of IL-1β, TNF-α, and IL-12, and the increase in myeloperoxidase activity, a marker enzyme for neutrophils and hydroxyproline content. Compared to leflunomide, PDE4 inhibitors more strongly suppressed IL-12 production and the increase in myeloperoxidase activity. PDE4 inhibitors also inhibited lipopolysaccharide-induced TNF-α and IL-12 production from thioglycolate-induced murine peritoneal macrophages and the proliferation of rat synovial fibroblasts. These results indicate this model makes it easy to evaluate the effect of drugs on various cytokine productions in a granuloma without any purification step and may be a relevant model for evaluating novel antirheumatic drugs on pannus formation in RA. PDE4 inhibitors could have therapeutic effects on pannus formation in RA by inhibition of cytokine production by macrophages and synovial fibroblast proliferation.

Administration of PDE4 inhibitors suppressed the pannus-like inflammation by inhibition of cytokine production by macrophages and synovial fibroblast proliferation.

Science.gov (United States)

Kobayashi, Katsuya; Suda, Toshio; Manabe, Haruhiko; Miki, Ichiro

2007-01-01

A marked proliferation of synovial fibroblasts in joints leads to pannus formation in rheumatoid arthritis (RA). Various kinds of cytokines are produced in the pannus. The purpose of this study is to elucidate the effects of phosphodiesterase 4 (PDE4) inhibitors in a new animal model for the evaluation of pannus formation and cytokine production in the pannus. Mice sensitized with methylated bovine serum albumin (mBSA) were challenged by subcutaneous implantation of a membrane filter soaked in mBSA solution in the back of the mice. Drugs were orally administered for 10 days. The granuloma formed around the filter was collected on day 11. It was chopped into pieces and cultured in vitro for 24 hr. The cytokines were measured in the supernatants. The type of cytokines produced in the granuloma was quite similar to those produced in pannus in RA. Both PDE4 inhibitors, KF66490 and SB207499, suppressed the production of IL-1beta, TNF-alpha, and IL-12, and the increase in myeloperoxidase activity, a marker enzyme for neutrophils and hydroxyproline content. Compared to leflunomide, PDE4 inhibitors more strongly suppressed IL-12 production and the increase in myeloperoxidase activity. PDE4 inhibitors also inhibited lipopolysaccharide-induced TNF-alpha and IL-12 production from thioglycolate-induced murine peritoneal macrophages and the proliferation of rat synovial fibroblasts. These results indicate this model makes it easy to evaluate the effect of drugs on various cytokine productions in a granuloma without any purification step and may be a relevant model for evaluating novel antirheumatic drugs on pannus formation in RA. PDE4 inhibitors could have therapeutic effects on pannus formation in RA by inhibition of cytokine production by macrophages and synovial fibroblast proliferation.

Chronic Inhibition of PDE5 Limits Pro-Inflammatory Monocyte-Macrophage Polarization in Streptozotocin-Induced Diabetic Mice.

Directory of Open Access Journals (Sweden)

Mary Anna Venneri

Full Text Available Diabetes mellitus is characterized by changes in endothelial cells that alter monocyte recruitment, increase classic (M1-type tissue macrophage infiltration and lead to self-sustained inflammation. Our and other groups recently showed that chronic inhibition of phosphodiesterase-5 (PDE5i affects circulating cytokine levels in patients with diabetes; whether PDE5i also affects circulating monocytes and tissue inflammatory cell infiltration remains to be established. Using murine streptozotocin (STZ-induced diabetes and in human vitro cell-cell adhesion models we show that chronic hyperglycemia induces changes in myeloid and endothelial cells that alter monocyte recruitment and lead to self-sustained inflammation. Continuous PDE5i with sildenafil (SILD expanded tissue anti-inflammatory TIE2-expressing monocytes (TEMs, which are known to limit inflammation and promote tissue repair. Specifically, SILD: 1 normalizes the frequency of circulating pro-inflammatory monocytes triggered by hyperglycemia (53.7 ± 7.9% of CD11b+Gr-1+ cells in STZ vs. 30.4 ± 8.3% in STZ+SILD and 27.1 ± 1.6% in CTRL, P<0.01; 2 prevents STZ-induced tissue inflammatory infiltration (4-fold increase in F4/80+ macrophages in diabetic vs. control mice by increasing renal and heart anti-inflammatory TEMs (30.9 ± 3.6% in STZ+SILD vs. 6.9 ± 2.7% in STZ, P <0.01, and 11.6 ± 2.9% in CTRL mice; 3 reduces vascular inflammatory proteins (iNOS, COX2, VCAM-1 promoting tissue protection; 4 lowers monocyte adhesion to human endothelial cells in vitro through the TIE2 receptor. All these changes occurred independently from changes of glycemic status. In summary, we demonstrate that circulating renal and cardiac TEMs are defective in chronic hyperglycemia and that SILD normalizes their levels by facilitating the shift from classic (M1-like to alternative (M2-like/TEM macrophage polarization. Restoration of tissue TEMs with PDE5i could represent an additional pharmacological tool to prevent

Bio-inspired varying subspace based computational framework for a class of nonlinear constrained optimal trajectory planning problems.

Science.gov (United States)

Xu, Y; Li, N

2014-09-01

Biological species have produced many simple but efficient rules in their complex and critical survival activities such as hunting and mating. A common feature observed in several biological motion strategies is that the predator only moves along paths in a carefully selected or iteratively refined subspace (or manifold), which might be able to explain why these motion strategies are effective. In this paper, a unified linear algebraic formulation representing such a predator-prey relationship is developed to simplify the construction and refinement process of the subspace (or manifold). Specifically, the following three motion strategies are studied and modified: motion camouflage, constant absolute target direction and local pursuit. The framework constructed based on this varying subspace concept could significantly reduce the computational cost in solving a class of nonlinear constrained optimal trajectory planning problems, particularly for the case with severe constraints. Two non-trivial examples, a ground robot and a hypersonic aircraft trajectory optimization problem, are used to show the capabilities of the algorithms in this new computational framework.

Bio-inspired varying subspace based computational framework for a class of nonlinear constrained optimal trajectory planning problems

International Nuclear Information System (INIS)

Xu, Y; Li, N

2014-01-01

Biological species have produced many simple but efficient rules in their complex and critical survival activities such as hunting and mating. A common feature observed in several biological motion strategies is that the predator only moves along paths in a carefully selected or iteratively refined subspace (or manifold), which might be able to explain why these motion strategies are effective. In this paper, a unified linear algebraic formulation representing such a predator–prey relationship is developed to simplify the construction and refinement process of the subspace (or manifold). Specifically, the following three motion strategies are studied and modified: motion camouflage, constant absolute target direction and local pursuit. The framework constructed based on this varying subspace concept could significantly reduce the computational cost in solving a class of nonlinear constrained optimal trajectory planning problems, particularly for the case with severe constraints. Two non-trivial examples, a ground robot and a hypersonic aircraft trajectory optimization problem, are used to show the capabilities of the algorithms in this new computational framework. (paper)

PDE4 inhibition reduces neointima formation and inhibits VCAM-1 expression and histone methylation in an Epac-dependent manner.

Science.gov (United States)

Lehrke, Michael; Kahles, Florian; Makowska, Anna; Tilstam, Pathricia V; Diebold, Sebastian; Marx, Judith; Stöhr, Robert; Hess, Katharina; Endorf, Elizabeth B; Bruemmer, Dennis; Marx, Nikolaus; Findeisen, Hannes M

2015-04-01

Phosphodiesterase 4 (PDE4) activity mediates cAMP-dependent smooth muscle cell (SMC) activation following vascular injury. In this study we have investigated the effects of specific PDE4 inhibition with roflumilast on SMC proliferation and inflammatory activation in vitro and neointima formation following guide wire-induced injury of the femoral artery in mice in vivo. In vitro, roflumilast did not affect SMC proliferation, but diminished TNF-α induced expression of the vascular cell adhesion molecule 1 (VCAM-1). Specific activation of the cAMP effector Epac, but not PKA activation mimicked the effects of roflumilast on VCAM-1 expression. Consistently, the reduction of VCAM-1 expression was rescued following inhibition of Epac. TNF-α induced NFκB p65 translocation and VCAM-1 promoter activity were not altered by roflumilast in SMCs. However, roflumilast treatment and Epac activation repressed the induction of the activating epigenetic histone mark H3K4me2 at the VCAM-1 promoter, while PKA activation showed no effect. Furthermore, HDAC inhibition blocked the inhibitory effect of roflumilast on VCAM-1 expression. Both, roflumilast and Epac activation reduced monocyte adhesion to SMCs in vitro. Finally, roflumilast treatment attenuated femoral artery intima-media ratio by more than 50% after 4weeks. In summary, PDE4 inhibition regulates VCAM-1 through a novel Epac-dependent mechanism, which involves regulatory epigenetic components and reduces neointima formation following vascular injury. PDE4 inhibition and Epac activation might represent novel approaches for the treatment of vascular diseases, including atherosclerosis and in-stent restenosis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Computer-aided design of multi-target ligands at A1R, A2AR and PDE10A, key proteins in neurodegenerative diseases.

Science.gov (United States)

Kalash, Leen; Val, Cristina; Azuaje, Jhonny; Loza, María I; Svensson, Fredrik; Zoufir, Azedine; Mervin, Lewis; Ladds, Graham; Brea, José; Glen, Robert; Sotelo, Eddy; Bender, Andreas

2017-12-30

Compounds designed to display polypharmacology may have utility in treating complex diseases, where activity at multiple targets is required to produce a clinical effect. In particular, suitable compounds may be useful in treating neurodegenerative diseases by promoting neuronal survival in a synergistic manner via their multi-target activity at the adenosine A 1 and A 2A receptors (A 1 R and A 2A R) and phosphodiesterase 10A (PDE10A), which modulate intracellular cAMP levels. Hence, in this work we describe a computational method for the design of synthetically feasible ligands that bind to A 1 and A 2A receptors and inhibit phosphodiesterase 10A (PDE10A), involving a retrosynthetic approach employing in silico target prediction and docking, which may be generally applicable to multi-target compound design at several target classes. This approach has identified 2-aminopyridine-3-carbonitriles as the first multi-target ligands at A 1 R, A 2A R and PDE10A, by showing agreement between the ligand and structure based predictions at these targets. The series were synthesized via an efficient one-pot scheme and validated pharmacologically as A 1 R/A 2A R-PDE10A ligands, with IC 50 values of 2.4-10.0 μM at PDE10A and K i values of 34-294 nM at A 1 R and/or A 2A R. Furthermore, selectivity profiling of the synthesized 2-amino-pyridin-3-carbonitriles against other subtypes of both protein families showed that the multi-target ligand 8 exhibited a minimum of twofold selectivity over all tested off-targets. In addition, both compounds 8 and 16 exhibited the desired multi-target profile, which could be considered for further functional efficacy assessment, analog modification for the improvement of selectivity towards A 1 R, A 2A R and PDE10A collectively, and evaluation of their potential synergy in modulating cAMP levels.

Optimization and transferability of non-electrostatic repulsion in the polarizable density embedding model

DEFF Research Database (Denmark)

Hrsak, Dalibor; Olsen, Jógvan Magnus Haugaard; Kongsted, Jacob

2017-01-01

Embedding techniques in combination with response theory represent a successful approach to calculate molecular properties and excited states in large molecular systems such as solutions and proteins. Recently, the polarizable embedding model has been extended by introducing explicit electronic...... densities of the molecules in the nearest environment, resulting in the polarizable density embedding (PDE) model. This improvement provides a better description of the intermolecular interactions at short distances. However, the electronic densities of the environment molecules are calculated in isolation...... interaction energies calculated on the basis of full quantum-mechanical calculations. The obtained optimal factors are used in PDE calculations of various ground- and excited-state properties of molecules embedded in solvents described as polarizable environments. © 2017 Wiley Periodicals, Inc....

Efficient topology optimization in MATLAB using 88 lines of code

DEFF Research Database (Denmark)

Andreassen, Erik; Clausen, Anders; Schevenels, Mattias

2011-01-01

The paper presents an efficient 88 line MATLAB code for topology optimization. It has been developed using the 99 line code presented by Sigmund (Struct Multidisc Optim 21(2):120–127, 2001) as a starting point. The original code has been extended by a density filter, and a considerable improvemen...... of the basic code to include recent PDE-based and black-and-white projection filtering methods. The complete 88 line code is included as an appendix and can be downloaded from the web site www.topopt.dtu.dk....

Workshop on Computational Optimization

CERN Document Server

2015-01-01

Our everyday life is unthinkable without optimization. We try to minimize our effort and to maximize the achieved profit. Many real world and industrial problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization 2013. It presents recent advances in computational optimization. The volume includes important real life problems like parameter settings for controlling processes in bioreactor, resource constrained project scheduling, problems arising in transport services, error correcting codes, optimal system performance and energy consumption and so on. It shows how to develop algorithms for them based on new metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming and others.

Exact methods for time constrained routing and related scheduling problems

DEFF Research Database (Denmark)

Kohl, Niklas

1995-01-01

of customers. In the VRPTW customers must be serviced within a given time period - a so called time window. The objective can be to minimize operating costs (e.g. distance travelled), fixed costs (e.g. the number of vehicles needed) or a combination of these component costs. During the last decade optimization......This dissertation presents a number of optimization methods for the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW is a generalization of the well known capacity constrained Vehicle Routing Problem (VRP), where a fleet of vehicles based at a central depot must service a set...... of J?rnsten, Madsen and S?rensen (1986), which has been tested computationally by Halse (1992). Both methods decompose the problem into a series of time and capacity constrained shotest path problems. This yields a tight lower bound on the optimal objective, and the dual gap can often be closed...

Sequential unconstrained minimization algorithms for constrained optimization

International Nuclear Information System (INIS)

Byrne, Charles

2008-01-01

The problem of minimizing a function f(x):R J → R, subject to constraints on the vector variable x, occurs frequently in inverse problems. Even without constraints, finding a minimizer of f(x) may require iterative methods. We consider here a general class of iterative algorithms that find a solution to the constrained minimization problem as the limit of a sequence of vectors, each solving an unconstrained minimization problem. Our sequential unconstrained minimization algorithm (SUMMA) is an iterative procedure for constrained minimization. At the kth step we minimize the function G k (x)=f(x)+g k (x), to obtain x k . The auxiliary functions g k (x):D subset of R J → R + are nonnegative on the set D, each x k is assumed to lie within D, and the objective is to minimize the continuous function f:R J → R over x in the set C = D-bar, the closure of D. We assume that such minimizers exist, and denote one such by x-circumflex. We assume that the functions g k (x) satisfy the inequalities 0≤g k (x)≤G k-1 (x)-G k-1 (x k-1 ), for k = 2, 3, .... Using this assumption, we show that the sequence {(x k )} is decreasing and converges to f(x-circumflex). If the restriction of f(x) to D has bounded level sets, which happens if x-circumflex is unique and f(x) is closed, proper and convex, then the sequence {x k } is bounded, and f(x*)=f(x-circumflex), for any cluster point x*. Therefore, if x-circumflex is unique, x* = x-circumflex and {x k } → x-circumflex. When x-circumflex is not unique, convergence can still be obtained, in particular cases. The SUMMA includes, as particular cases, the well-known barrier- and penalty-function methods, the simultaneous multiplicative algebraic reconstruction technique (SMART), the proximal minimization algorithm of Censor and Zenios, the entropic proximal methods of Teboulle, as well as certain cases of gradient descent and the Newton–Raphson method. The proof techniques used for SUMMA can be extended to obtain related results

Immunohistochemical distribution of cAMP- and cGMP-phosphodiesterase (PDE) isoenzymes in the human prostate

NARCIS (Netherlands)

Uckert, Stefan; Oelke, Matthias; Stief, Christian G.; Andersson, K.-E.; Jonas, Udo; Hedlund, Petter

2006-01-01

With the introduction of sildenafil citrate (Viagra), the concept of phosphodiesterase (PDE) inhibition has gained tremendous interest in the field of urology. Cyclic nucleotide second messengers cGMP and cAMP have been assumed to be involved in the control of the normal function of the prostate.

OPTIMIZED PARTICLE SWARM OPTIMIZATION BASED DEADLINE CONSTRAINED TASK SCHEDULING IN HYBRID CLOUD

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Dhananjay Kumar

2016-01-01

Full Text Available Cloud Computing is a dominant way of sharing of computing resources that can be configured and provisioned easily. Task scheduling in Hybrid cloud is a challenge as it suffers from producing the best QoS (Quality of Service when there is a high demand. In this paper a new resource allocation algorithm, to find the best External Cloud provider when the intermediate provider’s resources aren’t enough to satisfy the customer’s demand is proposed. The proposed algorithm called Optimized Particle Swarm Optimization (OPSO combines the two metaheuristic algorithms namely Particle Swarm Optimization and Ant Colony Optimization (ACO. These metaheuristic algorithms are used for the purpose of optimization in the search space of the required solution, to find the best resource from the pool of resources and to obtain maximum profit even when the number of tasks submitted for execution is very high. This optimization is performed to allocate job requests to internal and external cloud providers to obtain maximum profit. It helps to improve the system performance by improving the CPU utilization, and handle multiple requests at the same time. The simulation result shows that an OPSO yields 0.1% - 5% profit to the intermediate cloud provider compared with standard PSO and ACO algorithms and it also increases the CPU utilization by 0.1%.

The Regularized Fast Hartley Transform Optimal Formulation of Real-Data Fast Fourier Transform for Silicon-Based Implementation in Resource-Constrained Environments

CERN Document Server

Jones, Keith

2010-01-01

The Regularized Fast Hartley Transform provides the reader with the tools necessary to both understand the proposed new formulation and to implement simple design variations that offer clear implementational advantages, both practical and theoretical, over more conventional complex-data solutions to the problem. The highly-parallel formulation described is shown to lead to scalable and device-independent solutions to the latency-constrained version of the problem which are able to optimize the use of the available silicon resources, and thus to maximize the achievable computational density, th

Application of a Double-Sided Chance-Constrained Integer Linear Program for Optimization of the Incremental Value of Ecosystem Services in Jilin Province, China

Directory of Open Access Journals (Sweden)

Baofeng Cai

2017-08-01

Full Text Available The Interconnected River System Network Project (IRSNP is a significant water supply engineering project, which is capable of effectively utilizing flood resources to generate ecological value, by connecting 198 lakes and ponds in western Jilin, northeast China. In this article, an optimization research approach has been proposed to maximize the incremental value of IRSNP ecosystem services. A double-sided chance-constrained integer linear program (DCCILP method has been proposed to support the optimization, which can deal with uncertainties presented as integers or random parameters that appear on both sides of the decision variable at the same time. The optimal scheme indicates that after rational optimization, the total incremental value of ecosystem services from the interconnected river system network project increased 22.25%, providing an increase in benefits of 3.26 × 109 ¥ compared to the original scheme. Most of the functional area is swamp wetland, which provides the greatest ecological benefits. Adjustment services increased obviously, implying that the optimization scheme prioritizes ecological benefits rather than supply and production services.

Optimal control applied to native-invasive species competition via a PDE model

Directory of Open Access Journals (Sweden)

Wandi Ding

2012-12-01

Full Text Available We consider an optimal control problem of a system of parabolic partial differential equations modelling the competition between an invasive and a native species. The motivating example is cottonwood-salt cedar competition, where the effect of disturbance in the system (such as flooding is taken to be a control variable. Flooding being detrimental at low and high levels, and advantageous at medium levels led us to consider the quadratic growth function of the control. The objective is to maximize the native species and minimize the invasive species while minimizing the cost of implementing the control. An existence result for an optimal control is given. Numerical examples are presented to illustrate the results.

Workshop on Computational Optimization

CERN Document Server

2016-01-01

This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization 2014, held at Warsaw, Poland, September 7-10, 2014. The book presents recent advances in computational optimization. The volume includes important real problems like parameter settings for controlling processes in bioreactor and other processes, resource constrained project scheduling, infection distribution, molecule distance geometry, quantum computing, real-time management and optimal control, bin packing, medical image processing, localization the abrupt atmospheric contamination source and so on. It shows how to develop algorithms for them based on new metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming and others. This research demonstrates how some real-world problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks.

Multivariable controller for discrete stochastic amplitude-constrained systems

Directory of Open Access Journals (Sweden)

Hannu T. Toivonen

1983-04-01

Full Text Available A sub-optimal multivariable controller for discrete stochastic amplitude-constrained systems is presented. In the approach the regulator structure is restricted to the class of linear saturated feedback laws. The stationary covariances of the controlled system are evaluated by approximating the stationary probability distribution of the state by a gaussian distribution. An algorithm for minimizing a quadratic loss function is given, and examples are presented to illustrate the performance of the sub-optimal controller.

An algorithm for mass matrix calculation of internally constrained molecular geometries

International Nuclear Information System (INIS)

Aryanpour, Masoud; Dhanda, Abhishek; Pitsch, Heinz

2008-01-01

Dynamic models for molecular systems require the determination of corresponding mass matrix. For constrained geometries, these computations are often not trivial but need special considerations. Here, assembling the mass matrix of internally constrained molecular structures is formulated as an optimization problem. Analytical expressions are derived for the solution of the different possible cases depending on the rank of the constraint matrix. Geometrical interpretations are further used to enhance the solution concept. As an application, we evaluate the mass matrix for a constrained molecule undergoing an electron-transfer reaction. The preexponential factor for this reaction is computed based on the harmonic model

An algorithm for mass matrix calculation of internally constrained molecular geometries.

Science.gov (United States)

Aryanpour, Masoud; Dhanda, Abhishek; Pitsch, Heinz

2008-01-28

Dynamic models for molecular systems require the determination of corresponding mass matrix. For constrained geometries, these computations are often not trivial but need special considerations. Here, assembling the mass matrix of internally constrained molecular structures is formulated as an optimization problem. Analytical expressions are derived for the solution of the different possible cases depending on the rank of the constraint matrix. Geometrical interpretations are further used to enhance the solution concept. As an application, we evaluate the mass matrix for a constrained molecule undergoing an electron-transfer reaction. The preexponential factor for this reaction is computed based on the harmonic model.

Binary classification posed as a quadratically constrained quadratic ...

Indian Academy of Sciences (India)

Binary classification is posed as a quadratically constrained quadratic problem and solved using the proposed method. Each class in the binary classification problem is modeled as a multidimensional ellipsoid to forma quadratic constraint in the problem. Particle swarms help in determining the optimal hyperplane or ...

The PDE10A inhibitor MP-10 and haloperidol produce distinct gene expression profiles in the striatum and influence cataleptic behavior in rodents.

Science.gov (United States)

Gentzel, Renee C; Toolan, Dawn; Roberts, Rhonda; Koser, Amy Jo; Kandebo, Monika; Hershey, James; Renger, John J; Uslaner, Jason; Smith, Sean M

2015-12-01

Phosphodiesterase 10A (PDE10A) has garnered attention as a potential therapeutic target for schizophrenia due to its prominent striatal expression and ability to modulate striatal signaling. The present study used the selective PDE10A inhibitor MP-10 and the dopamine D2 antagonist haloperidol to compare effects of PDE10A inhibition and dopamine D2 blockade on striatopallidal (D2) and striatonigral (D1) pathway activation. Our studies confirmed that administration of MP-10 significantly elevates expression of the immediate early genes (IEG) c-fos, egr-1, and arc in rat striatum. Furthermore, we demonstrated that MP-10 induced egr-1 expression was distributed evenly between enkephalin-containing D2-neurons and substance P-containing D1-neurons. In contrast, haloperidol (3 mg/kg) selectively activated egr-1 expression in enkephalin neurons. Co-administration of MP-10 and haloperidol (0.5 mg/kg) increased IEG expression to a greater extent than either compound alone. Similarly, in a rat catalepsy assay, administration of haloperidol (0.5 mg/kg) or MP-10 (3-30 mg/kg) did not produce cataleptic behavior when dosed alone, but co-administration of haloperidol with MP-10 (3 and 10 mg/kg) induced cataleptic behaviors. Interestingly, co-administration of haloperidol with a high dose of MP-10 (30 mg/kg) failed to produce cataleptic behavior. These findings are important for understanding the neural circuits involved in catalepsy and suggest that the behavioral effects produced by PDE10A inhibitors may be influenced by concomitant medication and the level of PDE10A inhibition achieved by the dose of the inhibitor. Copyright © 2015. Published by Elsevier Ltd.

New insights into selective PDE4D inhibitors: 3-(Cyclopentyloxy)-4-methoxybenzaldehyde O-(2-(2,6-dimethylmorpholino)-2-oxoethyl) oxime (GEBR-7b) structural development and promising activities to restore memory impairment.

Science.gov (United States)

Brullo, Chiara; Ricciarelli, Roberta; Prickaerts, Jos; Arancio, Ottavio; Massa, Matteo; Rotolo, Chiara; Romussi, Alessia; Rebosio, Claudia; Marengo, Barbara; Pronzato, Maria Adelaide; van Hagen, Britt T J; van Goethem, Nick P; D'Ursi, Pasqualina; Orro, Alessandro; Milanesi, Luciano; Guariento, Sara; Cichero, Elena; Fossa, Paola; Fedele, Ernesto; Bruno, Olga

2016-11-29

Phosphodiesterase type 4D (PDE4D) has been indicated as a promising target for treating neurodegenerative pathologies such as Alzheimer's Disease (AD). By preventing cAMP hydrolysis, PDE4 inhibitors (PDE4Is) increase the cAMP response element-binding protein (CREB) phosphorylation, synaptic plasticity and long-term memory formation. Pharmacological and behavioral studies on our hit GEBR-7b demonstrated that selective PDE4DIs could improve memory without causing emesis and sedation. The hit development led to new molecule series, herein reported, characterized by a catechol structure bonded to five member heterocycles. Molecular modeling studies highlighted the pivotal role of a polar alkyl chain in conferring selective enzyme interaction. Compound 8a showed PDE4D3 selective inhibition and was able to increase intracellular cAMP levels in neuronal cells, as well as in the hippocampus of freely moving rats. Furthermore, 8a was able to readily cross the blood-brain barrier and enhanced memory performance in mice without causing any emetic-like behavior. These data support the view that PDE4D is an adequate molecular target to restore memory deficits in different neuropathologies, including AD, and also indicate compound 8a as a promising candidate for further preclinical development. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

The Person-Event Data Environment (PDE: Leveraging Big Data for Studies of Psychological Strengths in Soldiers

Directory of Open Access Journals (Sweden)

Loryana L. Vie

2013-12-01

Full Text Available The Department of Defense (DoD strives to efficiently manage the large volumes of administrative data collected and repurpose this information for research and analyses with policy implications. This need is especially present in the United States Army, which maintains numerous electronic databases with information on more than one million Active-Duty, Reserve, and National Guard soldiers, their family members, and Army civilian employees. The accumulation of vast amounts of digitized health, military service, and demographic data thus approaches, and may even exceed, traditional benchmarks for Big Data. Given the challenges of disseminating sensitive personal and health information, the Person-Event Data Environment (PDE was created to unify disparate Army and DoD databases in a secure cloud-based enclave. This electronic repository serves the ultimate goal of achieving cost efficiencies in psychological and healthcare studies and provides a platform for collaboration among diverse scientists. This paper provides an overview of the uses of the PDE to perform command surveillance and policy analysis for Army leadership. The paper highlights the confluence of both economic and behavioral science perspectives elucidating empirically-based studies examining relations between psychological assets, health, and healthcare utilization. Specific examples explore the role of psychological assets in major cost drivers such as medical expenditures both during deployment and stateside, drug use, attrition from basic training, and low reenlistment rates. Through creation of the PDE, the Army and scientific community can now capitalize on the vast amounts of personnel, financial, medical, training and education, deployment and security systems that influence Army-wide policies and procedures.

Hyperprolactinemia contributes to reproductive deficit in male rats chronically administered PDE5 inhibitors (sildenafil and tadalafil and opioid (tramadol

Directory of Open Access Journals (Sweden)

V.U. Nna

2016-09-01

Conclusion: Serum prolactin concentration correlated negatively with male reproductive hormones and may play a major role in reproductive deficits associated with chronic use of PDE5 inhibitors and opioids.

Decision tree analyses of key patient characteristics in Middle Eastern/North African and Latin American men treated with long-acting and short-acting PDE5 inhibitors for erectile dysfunction.

Science.gov (United States)

Rubio-Aurioles, Eusebio; El-Meliegy, Amr; Abdulwahed, Samer; Henneges, Carsten; Sorsaburu, Sebastian; Gurbuz, Sirel

2015-02-01

Phosphodiesterase type 5 (PDE5) inhibitors have discontinuation rates as high as 60% in men with erectile dysfunction. Treatment satisfaction has been significantly associated with treatment continuation. Understanding key characteristics in terms of treatment preference, relationship, and lifestyle issues could provide direction on how to improve compliance with PDE5 inhibitor treatment globally. The objective was to identify subgroups of interest in the pooled database of two observational studies conducted in Latin America (LA) and Middle East/North Africa (MENA) exploring patient characteristics and prescription of either a long- or short-acting PDE5 inhibitor at baseline. Two identical prospective, non-interventional, observational, studies in MENA (N = 493) and LA (N = 511) treated men with an 'on demand' (pro re nata, PRN) PDE5 inhibitor (sildenafil, tadalafil, vardenafil, or lodenafil) during 6 months. In this post-hoc meta-analysis of two observational studies with equal design, pooled data were analyzed to determine patient characteristics and PDE5 inhibitor prescribed/used most likely to be associated with patient expectations, satisfaction, self-esteem, and patient-partner relationships. Decision tree analyses, with and without weighting, were used to identify and describe key features. In each analysis of patient expectations, patient-partner relationship, and self-esteem, we describe the two major subgroups at baseline for each decision tree. Analyses of patient expectations and sexual self-esteem revealed that patients prescribed long-acting PDE5 inhibitors (59%) highlighted the importance of treatment effect duration, second to partner satisfaction with treatment, while patients prescribed short-acting PDE5 inhibitors (32%) placed less importance on treatment effect duration but considerable importance on treatment effect lasting until intercourse completion. Further insights regarding patients, partner relationship characteristics, and

Statistical mechanics of budget-constrained auctions

International Nuclear Information System (INIS)

Altarelli, F; Braunstein, A; Realpe-Gomez, J; Zecchina, R

2009-01-01

Finding the optimal assignment in budget-constrained auctions is a combinatorial optimization problem with many important applications, a notable example being in the sale of advertisement space by search engines (in this context the problem is often referred to as the off-line AdWords problem). On the basis of the cavity method of statistical mechanics, we introduce a message-passing algorithm that is capable of solving efficiently random instances of the problem extracted from a natural distribution, and we derive from its properties the phase diagram of the problem. As the control parameter (average value of the budgets) is varied, we find two phase transitions delimiting a region in which long-range correlations arise

Statistical mechanics of budget-constrained auctions

Science.gov (United States)

Altarelli, F.; Braunstein, A.; Realpe-Gomez, J.; Zecchina, R.

2009-07-01

Finding the optimal assignment in budget-constrained auctions is a combinatorial optimization problem with many important applications, a notable example being in the sale of advertisement space by search engines (in this context the problem is often referred to as the off-line AdWords problem). On the basis of the cavity method of statistical mechanics, we introduce a message-passing algorithm that is capable of solving efficiently random instances of the problem extracted from a natural distribution, and we derive from its properties the phase diagram of the problem. As the control parameter (average value of the budgets) is varied, we find two phase transitions delimiting a region in which long-range correlations arise.

Alternating Direction Implicit (ADI) schemes for a PDE-based image osmosis model

Science.gov (United States)

Calatroni, L.; Estatico, C.; Garibaldi, N.; Parisotto, S.

2017-10-01

We consider Alternating Direction Implicit (ADI) splitting schemes to compute efficiently the numerical solution of the PDE osmosis model considered by Weickert et al. in [10] for several imaging applications. The discretised scheme is shown to preserve analogous properties to the continuous model. The dimensional splitting strategy traduces numerically into the solution of simple tridiagonal systems for which standard matrix factorisation techniques can be used to improve upon the performance of classical implicit methods, even for large time steps. Applications to the shadow removal problem are presented.

Constrained variational calculus for higher order classical field theories

Energy Technology Data Exchange (ETDEWEB)

Campos, Cedric M; De Leon, Manuel; De Diego, David MartIn, E-mail: cedricmc@icmat.e, E-mail: mdeleon@icmat.e, E-mail: david.martin@icmat.e [Instituto de Ciencias Matematicas, CSIC-UAM-UC3M-UCM, Serrano 123, 28006 Madrid (Spain)

2010-11-12

We develop an intrinsic geometrical setting for higher order constrained field theories. As a main tool we use an appropriate generalization of the classical Skinner-Rusk formalism. Some examples of applications are studied, in particular to the geometrical description of optimal control theory for partial differential equations.

Constrained variational calculus for higher order classical field theories

International Nuclear Information System (INIS)

Campos, Cedric M; De Leon, Manuel; De Diego, David MartIn

2010-01-01

We develop an intrinsic geometrical setting for higher order constrained field theories. As a main tool we use an appropriate generalization of the classical Skinner-Rusk formalism. Some examples of applications are studied, in particular to the geometrical description of optimal control theory for partial differential equations.

Fast Multipole-Based Elliptic PDE Solver and Preconditioner

KAUST Repository

Ibeid, Huda

2016-12-07

Exascale systems are predicted to have approximately one billion cores, assuming Gigahertz cores. Limitations on affordable network topologies for distributed memory systems of such massive scale bring new challenges to the currently dominant parallel programing model. Currently, there are many efforts to evaluate the hardware and software bottlenecks of exascale designs. It is therefore of interest to model application performance and to understand what changes need to be made to ensure extrapolated scalability. Fast multipole methods (FMM) were originally developed for accelerating N-body problems for particle-based methods in astrophysics and molecular dynamics. FMM is more than an N-body solver, however. Recent efforts to view the FMM as an elliptic PDE solver have opened the possibility to use it as a preconditioner for even a broader range of applications. In this thesis, we (i) discuss the challenges for FMM on current parallel computers and future exascale architectures, with a focus on inter-node communication, and develop a performance model that considers the communication patterns of the FMM for spatially quasi-uniform distributions, (ii) employ this performance model to guide performance and scaling improvement of FMM for all-atom molecular dynamics simulations of uniformly distributed particles, and (iii) demonstrate that, beyond its traditional use as a solver in problems for which explicit free-space kernel representations are available, the FMM has applicability as a preconditioner in finite domain elliptic boundary value problems, by equipping it with boundary integral capability for satisfying conditions at finite boundaries and by wrapping it in a Krylov method for extensibility to more general operators. Compared with multilevel methods, FMM is capable of comparable algebraic convergence rates down to the truncation error of the discretized PDE, and it has superior multicore and distributed memory scalability properties on commodity

Combination of 2D/3D ligand-based similarity search in rapid virtual screening from multimillion compound repositories. Selection and biological evaluation of potential PDE4 and PDE5 inhibitors.

Science.gov (United States)

Dobi, Krisztina; Hajdú, István; Flachner, Beáta; Fabó, Gabriella; Szaszkó, Mária; Bognár, Melinda; Magyar, Csaba; Simon, István; Szisz, Dániel; Lőrincz, Zsolt; Cseh, Sándor; Dormán, György

2014-05-28

Rapid in silico selection of target focused libraries from commercial repositories is an attractive and cost effective approach. If structures of active compounds are available rapid 2D similarity search can be performed on multimillion compound databases but the generated library requires further focusing by various 2D/3D chemoinformatics tools. We report here a combination of the 2D approach with a ligand-based 3D method (Screen3D) which applies flexible matching to align reference and target compounds in a dynamic manner and thus to assess their structural and conformational similarity. In the first case study we compared the 2D and 3D similarity scores on an existing dataset derived from the biological evaluation of a PDE5 focused library. Based on the obtained similarity metrices a fusion score was proposed. The fusion score was applied to refine the 2D similarity search in a second case study where we aimed at selecting and evaluating a PDE4B focused library. The application of this fused 2D/3D similarity measure led to an increase of the hit rate from 8.5% (1st round, 47% inhibition at 10 µM) to 28.5% (2nd round at 50% inhibition at 10 µM) and the best two hits had 53 nM inhibitory activities.

Preconditioning for Allen–Cahn variational inequalities with non-local constraints

KAUST Repository

Blank, Luise

2012-06-01

The solution of Allen-Cahn variational inequalities with mass constraints is of interest in many applications. This problem can be solved both in its scalar and vector-valued form as a PDE-constrained optimization problem by means of a primal-dual active set method. At the heart of this method lies the solution of linear systems in saddle point form. In this paper we propose the use of Krylov-subspace solvers and suitable preconditioners for the saddle point systems. Numerical results illustrate the competitiveness of this approach. © 2012 Elsevier Inc.

Path-Constrained Motion Planning for Robotics Based on Kinematic Constraints

NARCIS (Netherlands)

Dijk, van N.J.M.; Wouw, van de N.; Pancras, W.C.M.; Nijmeijer, H.

2007-01-01

Common robotic tracking tasks consist of motions along predefined paths. The design of time-optimal path-constrained trajectories for robotic applications is discussed in this paper. To increase industrial applicability, the proposed method accounts for robot kinematics together with actuator

Joint Chance-Constrained Dynamic Programming

Science.gov (United States)

Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J. Bob

2012-01-01

This paper presents a novel dynamic programming algorithm with a joint chance constraint, which explicitly bounds the risk of failure in order to maintain the state within a specified feasible region. A joint chance constraint cannot be handled by existing constrained dynamic programming approaches since their application is limited to constraints in the same form as the cost function, that is, an expectation over a sum of one-stage costs. We overcome this challenge by reformulating the joint chance constraint into a constraint on an expectation over a sum of indicator functions, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the primal variables can be optimized by a standard dynamic programming, while the dual variable is optimized by a root-finding algorithm that converges exponentially. Error bounds on the primal and dual objective values are rigorously derived. We demonstrate the algorithm on a path planning problem, as well as an optimal control problem for Mars entry, descent and landing. The simulations are conducted using a real terrain data of Mars, with four million discrete states at each time step.

Improved Sensitivity Relations in State Constrained Optimal Control

International Nuclear Information System (INIS)

Bettiol, Piernicola; Frankowska, Hélène; Vinter, Richard B.

2015-01-01

Sensitivity relations in optimal control provide an interpretation of the costate trajectory and the Hamiltonian, evaluated along an optimal trajectory, in terms of gradients of the value function. While sensitivity relations are a straightforward consequence of standard transversality conditions for state constraint free optimal control problems formulated in terms of control-dependent differential equations with smooth data, their verification for problems with either pathwise state constraints, nonsmooth data, or for problems where the dynamic constraint takes the form of a differential inclusion, requires careful analysis. In this paper we establish validity of both ‘full’ and ‘partial’ sensitivity relations for an adjoint state of the maximum principle, for optimal control problems with pathwise state constraints, where the underlying control system is described by a differential inclusion. The partial sensitivity relation interprets the costate in terms of partial Clarke subgradients of the value function with respect to the state variable, while the full sensitivity relation interprets the couple, comprising the costate and Hamiltonian, as the Clarke subgradient of the value function with respect to both time and state variables. These relations are distinct because, for nonsmooth data, the partial Clarke subdifferential does not coincide with the projection of the (full) Clarke subdifferential on the relevant coordinate space. We show for the first time (even for problems without state constraints) that a costate trajectory can be chosen to satisfy the partial and full sensitivity relations simultaneously. The partial sensitivity relation in this paper is new for state constraint problems, while the full sensitivity relation improves on earlier results in the literature (for optimal control problems formulated in terms of Lipschitz continuous multifunctions), because a less restrictive inward pointing hypothesis is invoked in the proof, and because

A homotopy analysis method for the option pricing PDE in illiquid markets

Science.gov (United States)

E-Khatib, Youssef

2012-09-01

One of the shortcomings of the Black and Scholes model on option pricing is the assumption that trading the underlying asset does not affect the underlying asset price. This can happen in perfectly liquid markets and it is evidently not viable in markets with imperfect liquidity (illiquid markets). It is well-known that markets with imperfect liquidity are more realistic. Thus, the presence of price impact while studying options is very important. This paper investigates a solution for the option pricing PDE in illiquid markets using the homotopy analysis method.

Constrained Burn Optimization for the International Space Station

Science.gov (United States)

Brown, Aaron J.; Jones, Brandon A.

2017-01-01

In long-term trajectory planning for the International Space Station (ISS), translational burns are currently targeted sequentially to meet the immediate trajectory constraints, rather than simultaneously to meet all constraints, do not employ gradient-based search techniques, and are not optimized for a minimum total deltav (v) solution. An analytic formulation of the constraint gradients is developed and used in an optimization solver to overcome these obstacles. Two trajectory examples are explored, highlighting the advantage of the proposed method over the current approach, as well as the potential v and propellant savings in the event of propellant shortages.

Luteinizing hormone signaling phosphorylates and activates the cyclic GMP phosphodiesterase PDE5 in mouse ovarian follicles, contributing an additional component to the hormonally induced decrease in cyclic GMP that reinitiates meiosis.

Science.gov (United States)

Egbert, Jeremy R; Yee, Siu-Pok; Jaffe, Laurinda A

2018-03-01

Prior to birth, oocytes within mammalian ovarian follicles initiate meiosis, but then arrest in prophase until puberty, when with each reproductive cycle, one or more follicles are stimulated by luteinizing hormone (LH) to resume meiosis in preparation for fertilization. Within preovulatory follicles, granulosa cells produce high levels of cGMP, which diffuses into the oocyte to maintain meiotic arrest. LH signaling restarts meiosis by rapidly lowering the levels of cGMP in the follicle and oocyte. Part of this decrease is mediated by the dephosphorylation and inactivation the NPR2 guanylyl cyclase in response to LH, but the mechanism for the remainder of the cGMP decrease is unknown. At least one cGMP phosphodiesterase, PDE5, is activated by LH signaling, which would contribute to lowering cGMP. PDE5 exhibits increased cGMP-hydrolytic activity when phosphorylated on serine 92, and we recently demonstrated that LH signaling phosphorylates PDE5 on this serine and increases its activity in rat follicles. To test the extent to which this mechanism contributes to the cGMP decrease that restarts meiosis, we generated a mouse line in which serine 92 was mutated to alanine (Pde5-S92A), such that it cannot be phosphorylated. Here we show that PDE5 phosphorylation is required for the LH-induced increase in cGMP-hydrolytic activity, but that this increase has only a modest effect on the LH-induced cGMP decrease in mouse follicles, and does not affect the timing of meiotic resumption. Though we show that the activation of PDE5 is among the mechanisms contributing to the cGMP decrease, these results suggest that another cGMP phosphodiesterase is also activated by LH signaling. Copyright © 2018 Elsevier Inc. All rights reserved.

Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method

Science.gov (United States)

Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan

2017-05-01

In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability.

Conditions for the Solvability of the Linear Programming Formulation for Constrained Discounted Markov Decision Processes

Energy Technology Data Exchange (ETDEWEB)

Dufour, F., E-mail: dufour@math.u-bordeaux1.fr [Institut de Mathématiques de Bordeaux, INRIA Bordeaux Sud Ouest, Team: CQFD, and IMB (France); Prieto-Rumeau, T., E-mail: tprieto@ccia.uned.es [UNED, Department of Statistics and Operations Research (Spain)

2016-08-15

We consider a discrete-time constrained discounted Markov decision process (MDP) with Borel state and action spaces, compact action sets, and lower semi-continuous cost functions. We introduce a set of hypotheses related to a positive weight function which allow us to consider cost functions that might not be bounded below by a constant, and which imply the solvability of the linear programming formulation of the constrained MDP. In particular, we establish the existence of a constrained optimal stationary policy. Our results are illustrated with an application to a fishery management problem.

Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

Science.gov (United States)

Chen, Wei

2015-07-01

In this paper, we discuss the portfolio optimization problem with real-world constraints under the assumption that the returns of risky assets are fuzzy numbers. A new possibilistic mean-semiabsolute deviation model is proposed, in which transaction costs, cardinality and quantity constraints are considered. Due to such constraints the proposed model becomes a mixed integer nonlinear programming problem and traditional optimization methods fail to find the optimal solution efficiently. Thus, a modified artificial bee colony (MABC) algorithm is developed to solve the corresponding optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and the corresponding algorithm.

A brief introduction to continuous evolutionary optimization

CERN Document Server

Kramer, Oliver

2014-01-01

Practical optimization problems are often hard to solve, in particular when they are black boxes and no further information about the problem is available except via function evaluations. This work introduces a collection of heuristics and algorithms for black box optimization with evolutionary algorithms in continuous solution spaces. The book gives an introduction to evolution strategies and parameter control. Heuristic extensions are presented that allow optimization in constrained, multimodal, and multi-objective solution spaces. An adaptive penalty function is introduced for constrained optimization. Meta-models reduce the number of fitness and constraint function calls in expensive optimization problems. The hybridization of evolution strategies with local search allows fast optimization in solution spaces with many local optima. A selection operator based on reference lines in objective space is introduced to optimize multiple conflictive objectives. Evolutionary search is employed for learning kernel ...

Adaptive observer for the joint estimation of parameters and input for a coupled wave PDE and infinite dimensional ODE system

KAUST Repository

Belkhatir, Zehor; Mechhoud, Sarra; Laleg-Kirati, Taous-Meriem

2016-01-01

This paper deals with joint parameters and input estimation for coupled PDE-ODE system. The system consists of a damped wave equation and an infinite dimensional ODE. This model describes the spatiotemporal hemodynamic response in the brain

The bounds of feasible space on constrained nonconvex quadratic programming

Science.gov (United States)

Zhu, Jinghao

2008-03-01

This paper presents a method to estimate the bounds of the radius of the feasible space for a class of constrained nonconvex quadratic programmingsE Results show that one may compute a bound of the radius of the feasible space by a linear programming which is known to be a P-problem [N. Karmarkar, A new polynomial-time algorithm for linear programming, Combinatorica 4 (1984) 373-395]. It is proposed that one applies this method for using the canonical dual transformation [D.Y. Gao, Canonical duality theory and solutions to constrained nonconvex quadratic programming, J. Global Optimization 29 (2004) 377-399] for solving a standard quadratic programming problem.

The equivalence of multi-criteria methods for radiotherapy plan optimization

International Nuclear Information System (INIS)

Breedveld, Sebastiaan; Storchi, Pascal R M; Heijmen, Ben J M

2009-01-01

Several methods can be used to achieve multi-criteria optimization of radiation therapy treatment planning, which strive for Pareto-optimality. The property of the solution being Pareto optimal is desired, because it guarantees that no criteria can be improved without deteriorating another criteria. The most widely used methods are the weighted-sum method, in which the different treatment objectives are weighted, and constrained optimization methods, in which treatment goals are set and the algorithm has to find the best plan fulfilling these goals. The constrained method used in this paper, the 2pεc (2-phase ε-constraint) method is based on the ε-constraint method, which generates Pareto-optimal solutions. Both approaches are uniquely related to each other. In this paper, we will show that it is possible to switch from the constrained method to the weighted-sum method by using the Lagrange multipliers from the constrained optimization problem, and vice versa by setting the appropriate constraints. In general, the theory presented in this paper can be useful in cases where a new situation is slightly different from the original situation, e.g. in online treatment planning, with deformations of the volumes of interest, or in automated treatment planning, where changes to the automated plan have to be made. An example of the latter is given where the planner is not satisfied with the result from the constrained method and wishes to decrease the dose in a structure. By using the Lagrange multipliers, a weighted-sum optimization problem is constructed, which generates a Pareto-optimal solution in the neighbourhood of the original plan, but fulfills the new treatment objectives.

Dynamic Convex Duality in Constrained Utility Maximization

OpenAIRE

Li, Yusong; Zheng, Harry

2016-01-01

In this paper, we study a constrained utility maximization problem following the convex duality approach. After formulating the primal and dual problems, we construct the necessary and sufficient conditions for both the primal and dual problems in terms of FBSDEs plus additional conditions. Such formulation then allows us to explicitly characterize the primal optimal control as a function of the adjoint process coming from the dual FBSDEs in a dynamic fashion and vice versa. Moreover, we also...

Constrained Fuzzy Predictive Control Using Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Oussama Ait Sahed

2015-01-01

Full Text Available A fuzzy predictive controller using particle swarm optimization (PSO approach is proposed. The aim is to develop an efficient algorithm that is able to handle the relatively complex optimization problem with minimal computational time. This can be achieved using reduced population size and small number of iterations. In this algorithm, instead of using the uniform distribution as in the conventional PSO algorithm, the initial particles positions are distributed according to the normal distribution law, within the area around the best position. The radius limiting this area is adaptively changed according to the tracking error values. Moreover, the choice of the initial best position is based on prior knowledge about the search space landscape and the fact that in most practical applications the dynamic optimization problem changes are gradual. The efficiency of the proposed control algorithm is evaluated by considering the control of the model of a 4 × 4 Multi-Input Multi-Output industrial boiler. This model is characterized by being nonlinear with high interactions between its inputs and outputs, having a nonminimum phase behaviour, and containing instabilities and time delays. The obtained results are compared to those of the control algorithms based on the conventional PSO and the linear approach.

A Generic High-performance GPU-based Library for PDE solvers

DEFF Research Database (Denmark)

Glimberg, Stefan Lemvig; Engsig-Karup, Allan Peter

, the privilege of high-performance parallel computing is now in principle accessible for many scientific users, no matter their economic resources. Though being highly effective units, GPUs and parallel architectures in general, pose challenges for software developers to utilize their efficiency. Sequential...... legacy codes are not always easily parallelized and the time spent on conversion might not pay o in the end. We present a highly generic C++ library for fast assembling of partial differential equation (PDE) solvers, aiming at utilizing the computational resources of GPUs. The library requires a minimum...... of GPU computing knowledge, while still oering the possibility to customize user-specic solvers at kernel level if desired. Spatial dierential operators are based on matrix free exible order nite dierence approximations. These matrix free operators minimize both memory consumption and main memory access...

Optimization of constrained multiple-objective reliability problems using evolutionary algorithms

International Nuclear Information System (INIS)

Salazar, Daniel; Rocco, Claudio M.; Galvan, Blas J.

2006-01-01

This paper illustrates the use of multi-objective optimization to solve three types of reliability optimization problems: to find the optimal number of redundant components, find the reliability of components, and determine both their redundancy and reliability. In general, these problems have been formulated as single objective mixed-integer non-linear programming problems with one or several constraints and solved by using mathematical programming techniques or special heuristics. In this work, these problems are reformulated as multiple-objective problems (MOP) and then solved by using a second-generation Multiple-Objective Evolutionary Algorithm (MOEA) that allows handling constraints. The MOEA used in this paper (NSGA-II) demonstrates the ability to identify a set of optimal solutions (Pareto front), which provides the Decision Maker with a complete picture of the optimal solution space. Finally, the advantages of both MOP and MOEA approaches are illustrated by solving four redundancy problems taken from the literature

Optimization of constrained multiple-objective reliability problems using evolutionary algorithms

Energy Technology Data Exchange (ETDEWEB)

Salazar, Daniel [Instituto de Sistemas Inteligentes y Aplicaciones Numericas en Ingenieria (IUSIANI), Division de Computacion Evolutiva y Aplicaciones (CEANI), Universidad de Las Palmas de Gran Canaria, Islas Canarias (Spain) and Facultad de Ingenieria, Universidad Central Venezuela, Caracas (Venezuela)]. E-mail: danielsalazaraponte@gmail.com; Rocco, Claudio M. [Facultad de Ingenieria, Universidad Central Venezuela, Caracas (Venezuela)]. E-mail: crocco@reacciun.ve; Galvan, Blas J. [Instituto de Sistemas Inteligentes y Aplicaciones Numericas en Ingenieria (IUSIANI), Division de Computacion Evolutiva y Aplicaciones (CEANI), Universidad de Las Palmas de Gran Canaria, Islas Canarias (Spain)]. E-mail: bgalvan@step.es

2006-09-15

This paper illustrates the use of multi-objective optimization to solve three types of reliability optimization problems: to find the optimal number of redundant components, find the reliability of components, and determine both their redundancy and reliability. In general, these problems have been formulated as single objective mixed-integer non-linear programming problems with one or several constraints and solved by using mathematical programming techniques or special heuristics. In this work, these problems are reformulated as multiple-objective problems (MOP) and then solved by using a second-generation Multiple-Objective Evolutionary Algorithm (MOEA) that allows handling constraints. The MOEA used in this paper (NSGA-II) demonstrates the ability to identify a set of optimal solutions (Pareto front), which provides the Decision Maker with a complete picture of the optimal solution space. Finally, the advantages of both MOP and MOEA approaches are illustrated by solving four redundancy problems taken from the literature.

Constrained convex minimization via model-based excessive gap

OpenAIRE

Tran Dinh, Quoc; Cevher, Volkan

2014-01-01

We introduce a model-based excessive gap technique to analyze first-order primal- dual methods for constrained convex minimization. As a result, we construct new primal-dual methods with optimal convergence rates on the objective residual and the primal feasibility gap of their iterates separately. Through a dual smoothing and prox-function selection strategy, our framework subsumes the augmented Lagrangian, and alternating methods as special cases, where our rates apply.

Multi-Objective Differential Evolution for Voltage Security Constrained Optimal Power Flow in Deregulated Power Systems

Science.gov (United States)

Roselyn, J. Preetha; Devaraj, D.; Dash, Subhransu Sekhar

2013-11-01

Voltage stability is an important issue in the planning and operation of deregulated power systems. The voltage stability problems is a most challenging one for the system operators in deregulated power systems because of the intense use of transmission line capabilities and poor regulation in market environment. This article addresses the congestion management problem avoiding offline transmission capacity limits related to voltage stability by considering Voltage Security Constrained Optimal Power Flow (VSCOPF) problem in deregulated environment. This article presents the application of Multi Objective Differential Evolution (MODE) algorithm to solve the VSCOPF problem in new competitive power systems. The maximum of L-index of the load buses is taken as the indicator of voltage stability and is incorporated in the Optimal Power Flow (OPF) problem. The proposed method in hybrid power market which also gives solutions to voltage stability problems by considering the generation rescheduling cost and load shedding cost which relieves the congestion problem in deregulated environment. The buses for load shedding are selected based on the minimum eigen value of Jacobian with respect to the load shed. In the proposed approach, real power settings of generators in base case and contingency cases, generator bus voltage magnitudes, real and reactive power demands of selected load buses using sensitivity analysis are taken as the control variables and are represented as the combination of floating point numbers and integers. DE/randSF/1/bin strategy scheme of differential evolution with self-tuned parameter which employs binomial crossover and difference vector based mutation is used for the VSCOPF problem. A fuzzy based mechanism is employed to get the best compromise solution from the pareto front to aid the decision maker. The proposed VSCOPF planning model is implemented on IEEE 30-bus system, IEEE 57 bus practical system and IEEE 118 bus system. The pareto optimal

Optimization algorithms and applications

CERN Document Server

Arora, Rajesh Kumar

2015-01-01

Choose the Correct Solution Method for Your Optimization ProblemOptimization: Algorithms and Applications presents a variety of solution techniques for optimization problems, emphasizing concepts rather than rigorous mathematical details and proofs. The book covers both gradient and stochastic methods as solution techniques for unconstrained and constrained optimization problems. It discusses the conjugate gradient method, Broyden-Fletcher-Goldfarb-Shanno algorithm, Powell method, penalty function, augmented Lagrange multiplier method, sequential quadratic programming, method of feasible direc

Minimum Time Trajectory Optimization of CNC Machining with Tracking Error Constraints

Directory of Open Access Journals (Sweden)

Qiang Zhang

2014-01-01

Full Text Available An off-line optimization approach of high precision minimum time feedrate for CNC machining is proposed. Besides the ordinary considered velocity, acceleration, and jerk constraints, dynamic performance constraint of each servo drive is also considered in this optimization problem to improve the tracking precision along the optimized feedrate trajectory. Tracking error is applied to indicate the servo dynamic performance of each axis. By using variable substitution, the tracking error constrained minimum time trajectory planning problem is formulated as a nonlinear path constrained optimal control problem. Bang-bang constraints structure of the optimal trajectory is proved in this paper; then a novel constraint handling method is proposed to realize a convex optimization based solution of the nonlinear constrained optimal control problem. A simple ellipse feedrate planning test is presented to demonstrate the effectiveness of the approach. Then the practicability and robustness of the trajectory generated by the proposed approach are demonstrated by a butterfly contour machining example.

A one-layer recurrent neural network for constrained nonsmooth optimization.

Science.gov (United States)

Liu, Qingshan; Wang, Jun

2011-10-01

This paper presents a novel one-layer recurrent neural network modeled by means of a differential inclusion for solving nonsmooth optimization problems, in which the number of neurons in the proposed neural network is the same as the number of decision variables of optimization problems. Compared with existing neural networks for nonsmooth optimization problems, the global convexity condition on the objective functions and constraints is relaxed, which allows the objective functions and constraints to be nonconvex. It is proven that the state variables of the proposed neural network are convergent to optimal solutions if a single design parameter in the model is larger than a derived lower bound. Numerical examples with simulation results substantiate the effectiveness and illustrate the characteristics of the proposed neural network.

Constrained optimization by radial basis function interpolation for high-dimensional expensive black-box problems with infeasible initial points

Science.gov (United States)

Regis, Rommel G.

2014-02-01

This article develops two new algorithms for constrained expensive black-box optimization that use radial basis function surrogates for the objective and constraint functions. These algorithms are called COBRA and Extended ConstrLMSRBF and, unlike previous surrogate-based approaches, they can be used for high-dimensional problems where all initial points are infeasible. They both follow a two-phase approach where the first phase finds a feasible point while the second phase improves this feasible point. COBRA and Extended ConstrLMSRBF are compared with alternative methods on 20 test problems and on the MOPTA08 benchmark automotive problem (D.R. Jones, Presented at MOPTA 2008), which has 124 decision variables and 68 black-box inequality constraints. The alternatives include a sequential penalty derivative-free algorithm, a direct search method with kriging surrogates, and two multistart methods. Numerical results show that COBRA algorithms are competitive with Extended ConstrLMSRBF and they generally outperform the alternatives on the MOPTA08 problem and most of the test problems.

Closed-Form Formulas vs. PDE Based Numerical Solution for the FRAP Data Processing: Theoretical and Practical Comparison

Czech Academy of Sciences Publication Activity Database

Papáček, Š.; Macdonald, B.; Matonoha, Ctirad

2017-01-01

Roč. 73, č. 8 (2017), s. 1673-1683 ISSN 0898-1221 Grant - others:GA MŠk(CZ) ED2.1.00/01.0024; GA MŠk(CZ) LO1205 Institutional support: RVO:67985807 Keywords : fluorescence recovery after photobleaching (FRAP) * parameter estimation * sensitivity analysis * partial differential equation (PDE) Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.531, year: 2016

Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method.

Science.gov (United States)

Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan

2017-05-01

In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability. Copyright © 2017 Elsevier B.V. All rights reserved.

A chance-constrained stochastic approach to intermodal container routing problems.

Science.gov (United States)

Zhao, Yi; Liu, Ronghui; Zhang, Xi; Whiteing, Anthony

2018-01-01

We consider a container routing problem with stochastic time variables in a sea-rail intermodal transportation system. The problem is formulated as a binary integer chance-constrained programming model including stochastic travel times and stochastic transfer time, with the objective of minimising the expected total cost. Two chance constraints are proposed to ensure that the container service satisfies ship fulfilment and cargo on-time delivery with pre-specified probabilities. A hybrid heuristic algorithm is employed to solve the binary integer chance-constrained programming model. Two case studies are conducted to demonstrate the feasibility of the proposed model and to analyse the impact of stochastic variables and chance-constraints on the optimal solution and total cost.

A new approach to nonlinear constrained Tikhonov regularization

KAUST Repository

Ito, Kazufumi

2011-09-16

We present a novel approach to nonlinear constrained Tikhonov regularization from the viewpoint of optimization theory. A second-order sufficient optimality condition is suggested as a nonlinearity condition to handle the nonlinearity of the forward operator. The approach is exploited to derive convergence rate results for a priori as well as a posteriori choice rules, e.g., discrepancy principle and balancing principle, for selecting the regularization parameter. The idea is further illustrated on a general class of parameter identification problems, for which (new) source and nonlinearity conditions are derived and the structural property of the nonlinearity term is revealed. A number of examples including identifying distributed parameters in elliptic differential equations are presented. © 2011 IOP Publishing Ltd.

A one-layer recurrent neural network for constrained nonconvex optimization.

Science.gov (United States)

Li, Guocheng; Yan, Zheng; Wang, Jun

2015-01-01

In this paper, a one-layer recurrent neural network is proposed for solving nonconvex optimization problems subject to general inequality constraints, designed based on an exact penalty function method. It is proved herein that any neuron state of the proposed neural network is convergent to the feasible region in finite time and stays there thereafter, provided that the penalty parameter is sufficiently large. The lower bounds of the penalty parameter and convergence time are also estimated. In addition, any neural state of the proposed neural network is convergent to its equilibrium point set which satisfies the Karush-Kuhn-Tucker conditions of the optimization problem. Moreover, the equilibrium point set is equivalent to the optimal solution to the nonconvex optimization problem if the objective function and constraints satisfy given conditions. Four numerical examples are provided to illustrate the performances of the proposed neural network.

Chance-Constrained Guidance With Non-Convex Constraints

Science.gov (United States)

Ono, Masahiro

2011-01-01

Missions to small bodies, such as comets or asteroids, require autonomous guidance for descent to these small bodies. Such guidance is made challenging by uncertainty in the position and velocity of the spacecraft, as well as the uncertainty in the gravitational field around the small body. In addition, the requirement to avoid collision with the asteroid represents a non-convex constraint that means finding the optimal guidance trajectory, in general, is intractable. In this innovation, a new approach is proposed for chance-constrained optimal guidance with non-convex constraints. Chance-constrained guidance takes into account uncertainty so that the probability of collision is below a specified threshold. In this approach, a new bounding method has been developed to obtain a set of decomposed chance constraints that is a sufficient condition of the original chance constraint. The decomposition of the chance constraint enables its efficient evaluation, as well as the application of the branch and bound method. Branch and bound enables non-convex problems to be solved efficiently to global optimality. Considering the problem of finite-horizon robust optimal control of dynamic systems under Gaussian-distributed stochastic uncertainty, with state and control constraints, a discrete-time, continuous-state linear dynamics model is assumed. Gaussian-distributed stochastic uncertainty is a more natural model for exogenous disturbances such as wind gusts and turbulence than the previously studied set-bounded models. However, with stochastic uncertainty, it is often impossible to guarantee that state constraints are satisfied, because there is typically a non-zero probability of having a disturbance that is large enough to push the state out of the feasible region. An effective framework to address robustness with stochastic uncertainty is optimization with chance constraints. These require that the probability of violating the state constraints (i.e., the probability of

Model Based Optimal Control, Estimation, and Validation of Lithium-Ion Batteries

Science.gov (United States)

Perez, Hector Eduardo

notion of interval observers to PDE models using a sensitivity-based approach. Practically, this chapter quantifies the sensitivity of battery state estimates to parameter variations, enabling robust battery management schemes. The effectiveness of the proposed sensitivity-based interval observers is verified via a numerical study for the range of uncertain parameters. Chapter 4: This chapter seeks to derive insight on battery charging control using electrochemistry models. Directly using full order complex multi-partial differential equation (PDE) electrochemical battery models is difficult and sometimes impossible to implement. This chapter develops an approach for obtaining optimal charge control schemes, while ensuring safety through constraint satisfaction. An optimal charge control problem is mathematically formulated via a coupled reduced order electrochemical-thermal model which conserves key electrochemical and thermal state information. The Legendre-Gauss-Radau (LGR) pseudo-spectral method with adaptive multi-mesh-interval collocation is employed to solve the resulting nonlinear multi-state optimal control problem. Minimum time charge protocols are analyzed in detail subject to solid and electrolyte phase concentration constraints, as well as temperature constraints. The optimization scheme is examined using different input current bounds, and an insight on battery design for fast charging is provided. Experimental results are provided to compare the tradeoffs between an electrochemical-thermal model based optimal charge protocol and a traditional charge protocol. Chapter 5: Fast and safe charging protocols are crucial for enhancing the practicality of batteries, especially for mobile applications such as smartphones and electric vehicles. This chapter proposes an innovative approach to devising optimally health-conscious fast-safe charge protocols. A multi-objective optimal control problem is mathematically formulated via a coupled electro

Inverse Diffusion Curves Using Shape Optimization.

Science.gov (United States)

Zhao, Shuang; Durand, Fredo; Zheng, Changxi

2018-07-01

The inverse diffusion curve problem focuses on automatic creation of diffusion curve images that resemble user provided color fields. This problem is challenging since the 1D curves have a nonlinear and global impact on resulting color fields via a partial differential equation (PDE). We introduce a new approach complementary to previous methods by optimizing curve geometry. In particular, we propose a novel iterative algorithm based on the theory of shape derivatives. The resulting diffusion curves are clean and well-shaped, and the final image closely approximates the input. Our method provides a user-controlled parameter to regularize curve complexity, and generalizes to handle input color fields represented in a variety of formats.

A CLASS OF NONMONOTONE TRUST REGION ALGORITHMS FOR LINEARLY CONSTRAINED OPTIMIZATION%线性约束优化的一类非单调信赖域算法

Institute of Scientific and Technical Information of China (English)

葛恒武; 陈中文

2002-01-01

We present a class of nonmonotone trust region algorithms for linearly constrained optimization in this paper.The algorithm may adjust automatically the scope of the monotonicity by the degree that the quadratic model is "trusted".Under the suitable conditions,it is proved that any limit point of the infinite sequence generated by the algorithm is the Kuhn-Tucker point of the primal problem.Finally,some numerical results show that the new algorithm is very effective.

Optimal set values of zone modeling in the simulation of a walking beam type reheating furnace on the steady-state operating regime

International Nuclear Information System (INIS)

Yang, Zhi; Luo, Xiaochuan

2016-01-01

Highlights: • The adjoint equation is introduced to the PDE optimal control problem. • Lipschitz continuity for the gradient of the cost functional is derived. • The simulation time and iterations reduce by a large margin in the simulations. • The model validation and comparison are made to verify the proposed math model. - Abstract: In this paper, this study proposed a new method to solve the PDE optimal control problem by introducing the adjoint problem to the optimization model, which was used to get the reference values for the optimal furnace zone temperatures and the optimal temperature distribution of steel slabs in the reheating furnace on the steady-state operating regime. It was proved that the gradient of the cost functional could be written via the weak solution of this adjoint problem and then Lipschitz continuity of the gradient was derived. Model validation and comparison between the mathematics model and the experiment results indicated that the present heat transfer model worked well for the prediction of thermal behavior about a slab in the reheating furnace. Iterations and simulation time had shown a significant decline in the simulations of 20MnSi slab, and it was shown by numerical simulations for 0.4 m thick slabs that the proposed method was better applied in the medium and heavy plate plant, leading to better performance in terms of productivity, energy efficiency and other features of reheating furnaces.

Methods of mathematical optimization

Science.gov (United States)

Vanderplaats, G. N.

The fundamental principles of numerical optimization methods are reviewed, with an emphasis on potential engineering applications. The basic optimization process is described; unconstrained and constrained minimization problems are defined; a general approach to the design of optimization software programs is outlined; and drawings and diagrams are shown for examples involving (1) the conceptual design of an aircraft, (2) the aerodynamic optimization of an airfoil, (3) the design of an automotive-engine connecting rod, and (4) the optimization of a 'ski-jump' to assist aircraft in taking off from a very short ship deck.

Application of pattern search method to power system security constrained economic dispatch with non-smooth cost function

International Nuclear Information System (INIS)

Al-Othman, A.K.; El-Naggar, K.M.

2008-01-01

Direct search methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This paper presents a new approach based on a constrained pattern search algorithm to solve a security constrained power system economic dispatch problem (SCED) with non-smooth cost function. Operation of power systems demands a high degree of security to keep the system satisfactorily operating when subjected to disturbances, while and at the same time it is required to pay attention to the economic aspects. Pattern recognition technique is used first to assess dynamic security. Linear classifiers that determine the stability of electric power system are presented and added to other system stability and operational constraints. The problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Pattern search method is then applied to solve the constrained optimization formulation. In particular, the method is tested using three different test systems. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving security constrained power system economic dispatch problem (SCED). In addition, valve-point effect loading and total system losses are considered to further investigate the potential of the PS technique. Based on the results, it can be concluded that the PS has demonstrated ability in handling highly nonlinear discontinuous non-smooth cost function of the SCED. (author)

FAST COMMUNICATION: A PDE Based Two Level Model of the Masking Property of the Human Ear

OpenAIRE

Xin, Jack; Qi, Yingyong

2003-01-01

Human ear has the masking property that certain audible sound becomes inaudible in the presence of another sound. Masking is quantified by the raised threshold from the absolute hearing threshold in quiet. It is of scientific and practical importance to compute masking thresholds. Empirical models on masking have applications in low bit rate digital music compression. A first principle based two level model is developed with partial differential equation (PDE) at the periphe...

Kinetic Constrained Optimization of the Golf Swing Hub Path

Directory of Open Access Journals (Sweden)

Steven M. Nesbit

2014-12-01

Full Text Available This study details an optimization of the golf swing, where the hand path and club angular trajectories are manipulated. The optimization goal was to maximize club head velocity at impact within the interaction kinetic limitations (force, torque, work, and power of the golfer as determined through the analysis of a typical swing using a two-dimensional dynamic model. The study was applied to four subjects with diverse swing capabilities and styles. It was determined that it is possible for all subjects to increase their club head velocity at impact within their respective kinetic limitations through combined modifications to their respective hand path and club angular trajectories. The manner of the modifications, the degree of velocity improvement, the amount of kinetic reduction, and the associated kinetic limitation quantities were subject dependent. By artificially minimizing selected kinetic inputs within the optimization algorithm, it was possible to identify swing trajectory characteristics that indicated relative kinetic weaknesses of a subject. Practical implications are offered based upon the findings of the study.

Constrained Optimal Stochastic Control of Non-Linear Wave Energy Point Absorbers

DEFF Research Database (Denmark)

Sichani, Mahdi Teimouri; Chen, Jian-Bing; Kramer, Morten

2014-01-01

to extract energy. Constrains are enforced on the control force to prevent large structural stresses in the floater at specific hot spots with the risk of inducing fatigue damage, or because the demanded control force cannot be supplied by the actuator system due to saturation. Further, constraints...... are enforced on the motion of the floater to prevent it from hitting the bottom of the sea or to make unacceptable jumps out of the water. The applied control law, which is of the feedback type with feedback from the displacement, velocity, and acceleration of the floater, contains two unprovided gain...

Optimizing color reproduction of natural images

NARCIS (Netherlands)

Yendrikhovskij, S.N.; Blommaert, F.J.J.; Ridder, de H.

1998-01-01

The paper elaborates on understanding, measuring and optimizing perceived color quality of natural images. We introduce a model for optimal color reproduction of natural scenes which is based on the assumption that color quality of natural images is constrained by perceived naturalness and

A SEMI-LAGRANGIAN TWO-LEVEL PRECONDITIONED NEWTON-KRYLOV SOLVER FOR CONSTRAINED DIFFEOMORPHIC IMAGE REGISTRATION.

Science.gov (United States)

Mang, Andreas; Biros, George

2017-01-01

We propose an efficient numerical algorithm for the solution of diffeomorphic image registration problems. We use a variational formulation constrained by a partial differential equation (PDE), where the constraints are a scalar transport equation. We use a pseudospectral discretization in space and second-order accurate semi-Lagrangian time stepping scheme for the transport equations. We solve for a stationary velocity field using a preconditioned, globalized, matrix-free Newton-Krylov scheme. We propose and test a two-level Hessian preconditioner. We consider two strategies for inverting the preconditioner on the coarse grid: a nested preconditioned conjugate gradient method (exact solve) and a nested Chebyshev iterative method (inexact solve) with a fixed number of iterations. We test the performance of our solver in different synthetic and real-world two-dimensional application scenarios. We study grid convergence and computational efficiency of our new scheme. We compare the performance of our solver against our initial implementation that uses the same spatial discretization but a standard, explicit, second-order Runge-Kutta scheme for the numerical time integration of the transport equations and a single-level preconditioner. Our improved scheme delivers significant speedups over our original implementation. As a highlight, we observe a 20 × speedup for a two dimensional, real world multi-subject medical image registration problem.

On benchmarking Stochastic Global Optimization Algorithms

NARCIS (Netherlands)

Hendrix, E.M.T.; Lancinskas, A.

2015-01-01

A multitude of heuristic stochastic optimization algorithms have been described in literature to obtain good solutions of the box-constrained global optimization problem often with a limit on the number of used function evaluations. In the larger question of which algorithms behave well on which

Efficient relaxations for joint chance constrained AC optimal power flow

Energy Technology Data Exchange (ETDEWEB)

Baker, Kyri; Toomey, Bridget

2017-07-01

Evolving power systems with increasing levels of stochasticity call for a need to solve optimal power flow problems with large quantities of random variables. Weather forecasts, electricity prices, and shifting load patterns introduce higher levels of uncertainty and can yield optimization problems that are difficult to solve in an efficient manner. Solution methods for single chance constraints in optimal power flow problems have been considered in the literature, ensuring single constraints are satisfied with a prescribed probability; however, joint chance constraints, ensuring multiple constraints are simultaneously satisfied, have predominantly been solved via scenario-based approaches or by utilizing Boole's inequality as an upper bound. In this paper, joint chance constraints are used to solve an AC optimal power flow problem while preventing overvoltages in distribution grids under high penetrations of photovoltaic systems. A tighter version of Boole's inequality is derived and used to provide a new upper bound on the joint chance constraint, and simulation results are shown demonstrating the benefit of the proposed upper bound. The new framework allows for a less conservative and more computationally efficient solution to considering joint chance constraints, specifically regarding preventing overvoltages.

Evolutionary optimization methods for accelerator design

Science.gov (United States)

Poklonskiy, Alexey A.

Many problems from the fields of accelerator physics and beam theory can be formulated as optimization problems and, as such, solved using optimization methods. Despite growing efficiency of the optimization methods, the adoption of modern optimization techniques in these fields is rather limited. Evolutionary Algorithms (EAs) form a relatively new and actively developed optimization methods family. They possess many attractive features such as: ease of the implementation, modest requirements on the objective function, a good tolerance to noise, robustness, and the ability to perform a global search efficiently. In this work we study the application of EAs to problems from accelerator physics and beam theory. We review the most commonly used methods of unconstrained optimization and describe the GATool, evolutionary algorithm and the software package, used in this work, in detail. Then we use a set of test problems to assess its performance in terms of computational resources, quality of the obtained result, and the tradeoff between them. We justify the choice of GATool as a heuristic method to generate cutoff values for the COSY-GO rigorous global optimization package for the COSY Infinity scientific computing package. We design the model of their mutual interaction and demonstrate that the quality of the result obtained by GATool increases as the information about the search domain is refined, which supports the usefulness of this model. We Giscuss GATool's performance on the problems suffering from static and dynamic noise and study useful strategies of GATool parameter tuning for these and other difficult problems. We review the challenges of constrained optimization with EAs and methods commonly used to overcome them. We describe REPA, a new constrained optimization method based on repairing, in exquisite detail, including the properties of its two repairing techniques: REFIND and REPROPT. We assess REPROPT's performance on the standard constrained

Optimizing some 3-stage W-methods for the time integration of PDEs

Science.gov (United States)

Gonzalez-Pinto, S.; Hernandez-Abreu, D.; Perez-Rodriguez, S.

2017-07-01

The optimization of some W-methods for the time integration of time-dependent PDEs in several spatial variables is considered. In [2, Theorem 1] several three-parametric families of three-stage W-methods for the integration of IVPs in ODEs were studied. Besides, the optimization of several specific methods for PDEs when the Approximate Matrix Factorization Splitting (AMF) is used to define the approximate Jacobian matrix (W ≈ fy(yn)) was carried out. Also, some convergence and stability properties were presented [2]. The derived methods were optimized on the base that the underlying explicit Runge-Kutta method is the one having the largest Monotonicity interval among the thee-stage order three Runge-Kutta methods [1]. Here, we propose an optimization of the methods by imposing some additional order condition [7] to keep order three for parabolic PDE problems [6] but at the price of reducing substantially the length of the nonlinear Monotonicity interval of the underlying explicit Runge-Kutta method.

Inexact Multistage Stochastic Chance Constrained Programming Model for Water Resources Management under Uncertainties

Directory of Open Access Journals (Sweden)

Hong Zhang

2017-01-01

Full Text Available In order to formulate water allocation schemes under uncertainties in the water resources management systems, an inexact multistage stochastic chance constrained programming (IMSCCP model is proposed. The model integrates stochastic chance constrained programming, multistage stochastic programming, and inexact stochastic programming within a general optimization framework to handle the uncertainties occurring in both constraints and objective. These uncertainties are expressed as probability distributions, interval with multiply distributed stochastic boundaries, dynamic features of the long-term water allocation plans, and so on. Compared with the existing inexact multistage stochastic programming, the IMSCCP can be used to assess more system risks and handle more complicated uncertainties in water resources management systems. The IMSCCP model is applied to a hypothetical case study of water resources management. In order to construct an approximate solution for the model, a hybrid algorithm, which incorporates stochastic simulation, back propagation neural network, and genetic algorithm, is proposed. The results show that the optimal value represents the maximal net system benefit achieved with a given confidence level under chance constraints, and the solutions provide optimal water allocation schemes to multiple users over a multiperiod planning horizon.

Nonlinear optimization

CERN Document Server

Ruszczynski, Andrzej

2011-01-01

Optimization is one of the most important areas of modern applied mathematics, with applications in fields from engineering and economics to finance, statistics, management science, and medicine. While many books have addressed its various aspects, Nonlinear Optimization is the first comprehensive treatment that will allow graduate students and researchers to understand its modern ideas, principles, and methods within a reasonable time, but without sacrificing mathematical precision. Andrzej Ruszczynski, a leading expert in the optimization of nonlinear stochastic systems, integrates the theory and the methods of nonlinear optimization in a unified, clear, and mathematically rigorous fashion, with detailed and easy-to-follow proofs illustrated by numerous examples and figures. The book covers convex analysis, the theory of optimality conditions, duality theory, and numerical methods for solving unconstrained and constrained optimization problems. It addresses not only classical material but also modern top...

An historical survey of computational methods in optimal control.

Science.gov (United States)

Polak, E.

1973-01-01

Review of some of the salient theoretical developments in the specific area of optimal control algorithms. The first algorithms for optimal control were aimed at unconstrained problems and were derived by using first- and second-variation methods of the calculus of variations. These methods have subsequently been recognized as gradient, Newton-Raphson, or Gauss-Newton methods in function space. A much more recent addition to the arsenal of unconstrained optimal control algorithms are several variations of conjugate-gradient methods. At first, constrained optimal control problems could only be solved by exterior penalty function methods. Later algorithms specifically designed for constrained problems have appeared. Among these are methods for solving the unconstrained linear quadratic regulator problem, as well as certain constrained minimum-time and minimum-energy problems. Differential-dynamic programming was developed from dynamic programming considerations. The conditional-gradient method, the gradient-projection method, and a couple of feasible directions methods were obtained as extensions or adaptations of related algorithms for finite-dimensional problems. Finally, the so-called epsilon-methods combine the Ritz method with penalty function techniques.

Predictive simulations and optimization of nanowire field-effect PSA sensors including screening

KAUST Repository

Baumgartner, Stefan; Heitzinger, Clemens; Vacic, Aleksandar; Reed, Mark A

2013-01-01

We apply our self-consistent PDE model for the electrical response of field-effect sensors to the 3D simulation of nanowire PSA (prostate-specific antigen) sensors. The charge concentration in the biofunctionalized boundary layer at the semiconductor-electrolyte interface is calculated using the propka algorithm, and the screening of the biomolecules by the free ions in the liquid is modeled by a sensitivity factor. This comprehensive approach yields excellent agreement with experimental current-voltage characteristics without any fitting parameters. Having verified the numerical model in this manner, we study the sensitivity of nanowire PSA sensors by changing device parameters, making it possible to optimize the devices and revealing the attributes of the optimal field-effect sensor. © 2013 IOP Publishing Ltd.

Predictive simulations and optimization of nanowire field-effect PSA sensors including screening

KAUST Repository

Baumgartner, Stefan

2013-05-03

We apply our self-consistent PDE model for the electrical response of field-effect sensors to the 3D simulation of nanowire PSA (prostate-specific antigen) sensors. The charge concentration in the biofunctionalized boundary layer at the semiconductor-electrolyte interface is calculated using the propka algorithm, and the screening of the biomolecules by the free ions in the liquid is modeled by a sensitivity factor. This comprehensive approach yields excellent agreement with experimental current-voltage characteristics without any fitting parameters. Having verified the numerical model in this manner, we study the sensitivity of nanowire PSA sensors by changing device parameters, making it possible to optimize the devices and revealing the attributes of the optimal field-effect sensor. © 2013 IOP Publishing Ltd.

Topology optimization problems with design-dependent sets of constraints

DEFF Research Database (Denmark)

Schou, Marie-Louise Højlund

Topology optimization is a design tool which is used in numerous fields. It can be used whenever the design is driven by weight and strength considerations. The basic concept of topology optimization is the interpretation of partial differential equation coefficients as effective material...... properties and designing through changing these coefficients. For example, consider a continuous structure. Then the basic concept is to represent this structure by small pieces of material that are coinciding with the elements of a finite element model of the structure. This thesis treats stress constrained...... structural topology optimization problems. For such problems a stress constraint for an element should only be present in the optimization problem when the structural design variable corresponding to this element has a value greater than zero. We model the stress constrained topology optimization problem...

Pareto optimality in infinite horizon linear quadratic differential games

NARCIS (Netherlands)

Reddy, P.V.; Engwerda, J.C.

2013-01-01

In this article we derive conditions for the existence of Pareto optimal solutions for linear quadratic infinite horizon cooperative differential games. First, we present a necessary and sufficient characterization for Pareto optimality which translates to solving a set of constrained optimal

On energy efficient power allocation for power-constrained systems

KAUST Repository

Sboui, Lokman

2014-09-01

Recently, the energy efficiency (EE) has become an important factor when designing new wireless communication systems. Due to economic and environmental challenges, new trends and efforts are oriented toward “green” communication especially for energy-constrained applications such as wireless sensors network and cognitive radio. To this end, we analyze the power allocation scheme that maximizes the EE defined as rate over the total power including circuit power. We derive an explicit expression of the optimal power with instantaneous channel gain based on EE criterion. We show that the relation between the EE and the spectral efficiency (SE) when the optimal power is adopted is strictly increasing in contrast with the SE-EE trade-off discussed in the literature. We also solve a non-convex problem and compute explicitly the optimal power for ergodic EE under either a peak or an average power constraint. When the instantaneous channel is not available, we provide the optimal power equation and compute simple sub-optimal power. In the numerical results, we show that the sup-optimal solution is very close to the optimal solution. In addition, we show that the absence of the channel state information (CSI) only affects the EE and the SE performances at high power regime compared to the full CSI case.

Identification of two new mutations in the GPR98 and the PDE6B genes segregating in a Tunisian family.

Science.gov (United States)

Hmani-Aifa, Mounira; Benzina, Zeineb; Zulfiqar, Fareeha; Dhouib, Houria; Shahzadi, Amber; Ghorbel, Abdelmonem; Rebaï, Ahmed; Söderkvist, Peter; Riazuddin, Sheikh; Kimberling, William J; Ayadi, Hammadi

2009-04-01

Autosomal recessive retinitis pigmentosa (ARRP) is a genetically heterogeneous disorder. ARRP could be associated with extraocular manifestations that define specific syndromes such as Usher syndrome (USH) characterized by retinal degeneration and congenital hearing loss (HL). The USH type II (USH2) associates RP and mild-to-moderate HL with preserved vestibular function. At least three genes USH2A, the very large G-protein-coupled receptor, GPR98, and DFNB31 are responsible for USH2 syndrome. Here, we report on the segregation of non-syndromic ARRP and USH2 syndrome in a consanguineous Tunisian family, which was previously used to define USH2B locus. With regard to the co-occurrence of these two different pathologies, clinical and genetic reanalysis of the extended family showed (i) phenotypic heterogeneity within USH2 patients and (ii) excluded linkage to USH2B locus. Indeed, linkage analysis disclosed the cosegregation of the USH2 phenotype with the USH2C locus markers, D5S428 and D5S618, whereas the ARRP perfectly segregates with PDE6B flanking markers D4S3360 and D4S2930. Molecular analysis revealed two new missense mutations, p.Y6044C and p.W807R, occurring in GPR98 and PDE6B genes, respectively. In conclusion, our results show that the USH2B locus at chromosome 3p23-24.2 does not exist, and we therefore withdraw this locus designation. The combination of molecular findings for GPR98 and PDE6B genes enable us to explain the phenotypic heterogeneity and particularly the severe ocular affection first observed in one USH2 patient. This report presents an illustration of how consanguinity could increase familial clustering of multiple hereditary diseases within the same family.

Conformationally constrained farnesoid X receptor (FXR) agonists: alternative replacements of the stilbene.

Science.gov (United States)

Akwabi-Ameyaw, Adwoa; Caravella, Justin A; Chen, Lihong; Creech, Katrina L; Deaton, David N; Madauss, Kevin P; Marr, Harry B; Miller, Aaron B; Navas, Frank; Parks, Derek J; Spearing, Paul K; Todd, Dan; Williams, Shawn P; Wisely, G Bruce

2011-10-15

To further explore the optimum placement of the acid moiety in conformationally constrained analogs of GW 4064 1a, a series of stilbene replacements were prepared. The benzothiophene 1f and the indole 1g display the optimal orientation of the carboxylate for enhanced FXR agonist potency. Copyright © 2011 Elsevier Ltd. All rights reserved.

A penalization approach to linear programming duality with application to capacity constrained transport

OpenAIRE

Korman, Jonathan; McCann, Robert J.; Seis, Christian

2013-01-01

A new approach to linear programming duality is proposed which relies on quadratic penalization, so that the relation between solutions to the penalized primal and dual problems becomes affine. This yields a new proof of Levin's duality theorem for capacity-constrained optimal transport as an infinite-dimensional application.

Exploring the Metabolic and Perceptual Correlates of Self-Selected Walking Speed under Constrained and Un-Constrained Conditions

Directory of Open Access Journals (Sweden)

David T Godsiff, Shelly Coe, Charlotte Elsworth-Edelsten, Johnny Collett, Ken Howells, Martyn Morris, Helen Dawes

2018-03-01

Full Text Available Mechanisms underpinning self-selected walking speed (SSWS are poorly understood. The present study investigated the extent to which SSWS is related to metabolism, energy cost, and/or perceptual parameters during both normal and artificially constrained walking. Fourteen participants with no pathology affecting gait were tested under standard conditions. Subjects walked on a motorized treadmill at speeds derived from their SSWS as a continuous protocol. RPE scores (CR10 and expired air to calculate energy cost (J.kg-1.m-1 and carbohydrate (CHO oxidation rate (J.kg-1.min-1 were collected during minutes 3-4 at each speed. Eight individuals were re-tested under the same conditions within one week with a hip and knee-brace to immobilize their right leg. Deflection in RPE scores (CR10 and CHO oxidation rate (J.kg-1.min-1 were not related to SSWS (five and three people had deflections in the defined range of SSWS in constrained and unconstrained conditions, respectively (p > 0.05. Constrained walking elicited a higher energy cost (J.kg-1.m-1 and slower SSWS (p 0.05. SSWS did not occur at a minimum energy cost (J.kg-1.m-1 in either condition, however, the size of the minimum energy cost to SSWS disparity was the same (Froude {Fr} = 0.09 in both conditions (p = 0.36. Perceptions of exertion can modify walking patterns and therefore SSWS and metabolism/ energy cost are not directly related. Strategies which minimize perceived exertion may enable faster walking in people with altered gait as our findings indicate they should self-optimize to the same extent under different conditions.

Preconditioning for partial differential equation constrained optimization with control constraints

KAUST Repository

Stoll, Martin

2011-10-18

Optimal control problems with partial differential equations play an important role in many applications. The inclusion of bound constraints for the control poses a significant additional challenge for optimization methods. In this paper, we propose preconditioners for the saddle point problems that arise when a primal-dual active set method is used. We also show for this method that the same saddle point system can be derived when the method is considered as a semismooth Newton method. In addition, the projected gradient method can be employed to solve optimization problems with simple bounds, and we discuss the efficient solution of the linear systems in question. In the case when an acceleration technique is employed for the projected gradient method, this again yields a semismooth Newton method that is equivalent to the primal-dual active set method. We also consider the Moreau-Yosida regularization method for control constraints and efficient preconditioners for this technique. Numerical results illustrate the competitiveness of these approaches. © 2011 John Wiley & Sons, Ltd.

Preconditioning for partial differential equation constrained optimization with control constraints

KAUST Repository

Stoll, Martin; Wathen, Andy

2011-01-01

Optimal control problems with partial differential equations play an important role in many applications. The inclusion of bound constraints for the control poses a significant additional challenge for optimization methods. In this paper, we propose preconditioners for the saddle point problems that arise when a primal-dual active set method is used. We also show for this method that the same saddle point system can be derived when the method is considered as a semismooth Newton method. In addition, the projected gradient method can be employed to solve optimization problems with simple bounds, and we discuss the efficient solution of the linear systems in question. In the case when an acceleration technique is employed for the projected gradient method, this again yields a semismooth Newton method that is equivalent to the primal-dual active set method. We also consider the Moreau-Yosida regularization method for control constraints and efficient preconditioners for this technique. Numerical results illustrate the competitiveness of these approaches. © 2011 John Wiley & Sons, Ltd.

Investigation of a Putative Estrogen-Imprinting Gene, Phosphodiesterase Type IV Variant (Pde4d4), in Determining Prostate Cancer Risk

Science.gov (United States)

2008-04-01

arrays. Methods Mol Biol 2002;200:87–100. [78] Craig JM, Kraus J, Cremer T. Removal of repetitive sequences from FISH probes using PCR-assisted affinity...Worcester, MA), David Hepps, MD, and Lynn Birch for technical contributions. Figure 5. Alterations in PDE4D4 CpG methylation and gene expression in NbE-1

Distribution Locational Marginal Pricing for Optimal Electric Vehicle Charging through Chance Constrained Mixed-Integer Programming

DEFF Research Database (Denmark)

Liu, Zhaoxi; Wu, Qiuwei; Oren, Shmuel S.

2017-01-01

This paper presents a distribution locational marginal pricing (DLMP) method through chance constrained mixed-integer programming designed to alleviate the possible congestion in the future distribution network with high penetration of electric vehicles (EVs). In order to represent the stochastic...

Constrained Null Space Component Analysis for Semiblind Source Separation Problem.

Science.gov (United States)

Hwang, Wen-Liang; Lu, Keng-Shih; Ho, Jinn

2018-02-01

The blind source separation (BSS) problem extracts unknown sources from observations of their unknown mixtures. A current trend in BSS is the semiblind approach, which incorporates prior information on sources or how the sources are mixed. The constrained independent component analysis (ICA) approach has been studied to impose constraints on the famous ICA framework. We introduced an alternative approach based on the null space component (NCA) framework and referred to the approach as the c-NCA approach. We also presented the c-NCA algorithm that uses signal-dependent semidefinite operators, which is a bilinear mapping, as signatures for operator design in the c-NCA approach. Theoretically, we showed that the source estimation of the c-NCA algorithm converges with a convergence rate dependent on the decay of the sequence, obtained by applying the estimated operators on corresponding sources. The c-NCA can be formulated as a deterministic constrained optimization method, and thus, it can take advantage of solvers developed in optimization society for solving the BSS problem. As examples, we demonstrated electroencephalogram interference rejection problems can be solved by the c-NCA with proximal splitting algorithms by incorporating a sparsity-enforcing separation model and considering the case when reference signals are available.

Maximum entropy production: Can it be used to constrain conceptual hydrological models?

Science.gov (United States)

M.C. Westhoff; E. Zehe

2013-01-01

In recent years, optimality principles have been proposed to constrain hydrological models. The principle of maximum entropy production (MEP) is one of the proposed principles and is subject of this study. It states that a steady state system is organized in such a way that entropy production is maximized. Although successful applications have been reported in...

Terascale Optimal PDE Simulations (TOPS) Center

Energy Technology Data Exchange (ETDEWEB)

Professor Olof B. Widlund

2007-07-09

Our work has focused on the development and analysis of domain decomposition algorithms for a variety of problems arising in continuum mechanics modeling. In particular, we have extended and analyzed FETI-DP and BDDC algorithms; these iterative solvers were first introduced and studied by Charbel Farhat and his collaborators, see [11, 45, 12], and by Clark Dohrmann of SANDIA, Albuquerque, see [43, 2, 1], respectively. These two closely related families of methods are of particular interest since they are used more extensively than other iterative substructuring methods to solve very large and difficult problems. Thus, the FETI algorithms are part of the SALINAS system developed by the SANDIA National Laboratories for very large scale computations, and as already noted, BDDC was first developed by a SANDIA scientist, Dr. Clark Dohrmann. The FETI algorithms are also making inroads in commercial engineering software systems. We also note that the analysis of these algorithms poses very real mathematical challenges. The success in developing this theory has, in several instances, led to significant improvements in the performance of these algorithms. A very desirable feature of these iterative substructuring and other domain decomposition algorithms is that they respect the memory hierarchy of modern parallel and distributed computing systems, which is essential for approaching peak floating point performance. The development of improved methods, together with more powerful computer systems, is making it possible to carry out simulations in three dimensions, with quite high resolution, relatively easily. This work is supported by high quality software systems, such as Argonne's PETSc library, which facilitates code development as well as the access to a variety of parallel and distributed computer systems. The success in finding scalable and robust domain decomposition algorithms for very large number of processors and very large finite element problems is, e.g., illustrated in [24, 25, 26]. This work is based on [29, 31]. Our work over these five and half years has, in our opinion, helped advance the knowledge of domain decomposition methods significantly. We see these methods as providing valuable alternatives to other iterative methods, in particular, those based on multi-grid. In our opinion, our accomplishments also match the goals of the TOPS project quite closely.

Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients

KAUST Repository

Beck, Joakim; Nobile, Fabio; Tamellini, Lorenzo; Tempone, Raul

2014-01-01

In this work we consider quasi-optimal versions of the Stochastic Galerkin method for solving linear elliptic PDEs with stochastic coefficients. In particular, we consider the case of a finite number N of random inputs and an analytic dependence of the solution of the PDE with respect to the parameters in a polydisc of the complex plane CN. We show that a quasi-optimal approximation is given by a Galerkin projection on a weighted (anisotropic) total degree space and prove a (sub)exponential convergence rate. As a specific application we consider a thermal conduction problem with non-overlapping inclusions of random conductivity. Numerical results show the sharpness of our estimates. © 2013 Elsevier Ltd. All rights reserved.

Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients

KAUST Repository

Beck, Joakim

2014-03-01

In this work we consider quasi-optimal versions of the Stochastic Galerkin method for solving linear elliptic PDEs with stochastic coefficients. In particular, we consider the case of a finite number N of random inputs and an analytic dependence of the solution of the PDE with respect to the parameters in a polydisc of the complex plane CN. We show that a quasi-optimal approximation is given by a Galerkin projection on a weighted (anisotropic) total degree space and prove a (sub)exponential convergence rate. As a specific application we consider a thermal conduction problem with non-overlapping inclusions of random conductivity. Numerical results show the sharpness of our estimates. © 2013 Elsevier Ltd. All rights reserved.

Robust optimization methods for chance constrained, simulation-based, and bilevel problems

NARCIS (Netherlands)

Yanikoglu, I.

2014-01-01

The objective of robust optimization is to find solutions that are immune to the uncertainty of the parameters in a mathematical optimization problem. It requires that the constraints of a given problem should be satisfied for all realizations of the uncertain parameters in a so-called uncertainty

Multi-Objective Design Optimization of an Over-Constrained Flexure-Based Amplifier

Directory of Open Access Journals (Sweden)

Yuan Ni

2015-07-01

Full Text Available The optimizing design for enhancement of the micro performance of manipulator based on analytical models is investigated in this paper. By utilizing the established uncanonical linear homogeneous equations, the quasi-static analytical model of the micro-manipulator is built, and the theoretical calculation results are tested by FEA simulations. To provide a theoretical basis for a micro-manipulator being used in high-precision engineering applications, this paper investigates the modal property based on the analytical model. Based on the finite element method, with multipoint constraint equations, the model is built and the results have a good match with the simulation. The following parametric influences studied show that the influences of other objectives on one objective are complicated.  Consequently, the multi-objective optimization by the derived analytical models is carried out to find out the optimal solutions of the manipulator. Besides the inner relationships among these design objectives during the optimization process are discussed.

Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks

Science.gov (United States)

Bistra Dilkina; Rachel Houtman; Carla P. Gomes; Claire A. Montgomery; Kevin S. McKelvey; Katherine Kendall; Tabitha A. Graves; Richard Bernstein; Michael K. Schwartz

2016-01-01

Conservation biologists recognize that a system of isolated protected areas will be necessary but insufficient to meet biodiversity objectives. Current approaches to connecting core conservation areas through corridors consider optimal corridor placement based on a single optimization goal: commonly, maximizing the movement for a target species across a...

The evolutionary value of recombination is constrained by genome modularity.

Directory of Open Access Journals (Sweden)

Darren P Martin

2005-10-01

Full Text Available Genetic recombination is a fundamental evolutionary mechanism promoting biological adaptation. Using engineered recombinants of the small single-stranded DNA plant virus, Maize streak virus (MSV, we experimentally demonstrate that fragments of genetic material only function optimally if they reside within genomes similar to those in which they evolved. The degree of similarity necessary for optimal functionality is correlated with the complexity of intragenomic interaction networks within which genome fragments must function. There is a striking correlation between our experimental results and the types of MSV recombinants that are detectable in nature, indicating that obligatory maintenance of intragenome interaction networks strongly constrains the evolutionary value of recombination for this virus and probably for genomes in general.

Food processing optimization using evolutionary algorithms | Enitan ...

African Journals Online (AJOL)

Evolutionary algorithms are widely used in single and multi-objective optimization. They are easy to use and provide solution(s) in one simulation run. They are used in food processing industries for decision making. Food processing presents constrained and unconstrained optimization problems. This paper reviews the ...

Optimization and optimal control in automotive systems

CERN Document Server

Kolmanovsky, Ilya; Steinbuch, Maarten; Re, Luigi

2014-01-01

This book demonstrates the use of the optimization techniques that are becoming essential to meet the increasing stringency and variety of requirements for automotive systems. It shows the reader how to move away from earlier  approaches, based on some degree of heuristics, to the use of  more and more common systematic methods. Even systematic methods can be developed and applied in a large number of forms so the text collects contributions from across the theory, methods and real-world automotive applications of optimization. Greater fuel economy, significant reductions in permissible emissions, new drivability requirements and the generally increasing complexity of automotive systems are among the criteria that the contributing authors set themselves to meet. In many cases multiple and often conflicting requirements give rise to multi-objective constrained optimization problems which are also considered. Some of these problems fall into the domain of the traditional multi-disciplinary optimization applie...

Constrained ripple optimization of Tokamak bundle divertors

International Nuclear Information System (INIS)

Hively, L.M.; Rome, J.A.; Lynch, V.E.; Lyon, J.F.; Fowler, R.H.; Peng, Y-K.M.; Dory, R.A.

1983-02-01

Magnetic field ripple from a tokamak bundle divertor is localized to a small toroidal sector and must be treated differently from the usual (distributed) toroidal field (TF) coil ripple. Generally, in a tokamak with an unoptimized divertor design, all of the banana-trapped fast ions are quickly lost due to banana drift diffusion or to trapping between the 1/R variation in absolute value vector B ω B and local field maxima due to the divertor. A computer code has been written to optimize automatically on-axis ripple subject to these constraints, while varying up to nine design parameters. Optimum configurations have low on-axis ripple ( 0 ) are lost. However, because finite-sized TF coils have not been used in this study, the flux bundle is not expanded

Constrained optimal motion planning for autonomous vehicles using PRONTO

NARCIS (Netherlands)

Aguiar, A.P.; Bayer, F.A.; Hauser, J.; Häusler, A.J.; Notarstefano, G.; Pascoal, A.M.; Rucco, A.; Saccon, A.

2017-01-01

This chapter provides an overview of the authors’ efforts in vehicle trajectory exploration and motion planning based on PRONTO, a numerical method for solving optimal control problems developed over the last two decades. The chapter reviews the basics of PRONTO, providing the appropriate references

Constrained non-linear optimization in 3D reflexion tomography; Problemes d'optimisation non-lineaire avec contraintes en tomographie de reflexion 3D

Energy Technology Data Exchange (ETDEWEB)

Delbos, F

2004-11-01

Reflexion tomography allows the determination of a subsurface velocity model from the travel times of seismic waves. The introduction of a priori information in this inverse problem can lead to the resolution of a constrained non-linear least-squares problem. The goal of the thesis is to improve the resolution techniques of this optimization problem, whose main difficulties are its ill-conditioning, its large scale and an expensive cost function in terms of CPU time. Thanks to a detailed study of the problem and to numerous numerical experiments, we justify the use of a sequential quadratic programming method, in which the tangential quadratic programs are solved by an original augmented Lagrangian method. We show the global linear convergence of the latter. The efficiency and robustness of the approach are demonstrated on several synthetic examples and on two real data cases. (author)

Energy efficient LED layout optimization for near-uniform illumination

Science.gov (United States)

Ali, Ramy E.; Elgala, Hany

2016-09-01

In this paper, we consider the problem of designing energy efficient light emitting diodes (LEDs) layout while satisfying the illumination constraints. Towards this objective, we present a simple approach to the illumination design problem based on the concept of the virtual LED. We formulate a constrained optimization problem for minimizing the power consumption while maintaining a near-uniform illumination throughout the room. By solving the resulting constrained linear program, we obtain the number of required LEDs and the optimal output luminous intensities that achieve the desired illumination constraints.

Partial differential equation methods for stochastic dynamic optimization: an application to wind power generation with energy storage.

Science.gov (United States)

Johnson, Paul; Howell, Sydney; Duck, Peter

2017-08-13

A mixed financial/physical partial differential equation (PDE) can optimize the joint earnings of a single wind power generator (WPG) and a generic energy storage device (ESD). Physically, the PDE includes constraints on the ESD's capacity, efficiency and maximum speeds of charge and discharge. There is a mean-reverting daily stochastic cycle for WPG power output. Physically, energy can only be produced or delivered at finite rates. All suppliers must commit hourly to a finite rate of delivery C , which is a continuous control variable that is changed hourly. Financially, we assume heavy 'system balancing' penalties in continuous time, for deviations of output rate from the commitment C Also, the electricity spot price follows a mean-reverting stochastic cycle with a strong evening peak, when system balancing penalties also peak. Hence the economic goal of the WPG plus ESD, at each decision point, is to maximize expected net present value (NPV) of all earnings (arbitrage) minus the NPV of all expected system balancing penalties, along all financially/physically feasible future paths through state space. Given the capital costs for the various combinations of the physical parameters, the design and operating rules for a WPG plus ESD in a finite market may be jointly optimizable.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

Data Science and Optimal Learning for Material Discovery and Design

Science.gov (United States)

; Optimal Learning for Material Discovery & Design Data Science and Optimal Learning for Material inference and optimization methods that can constrain predictions using insights and results from theory directions in the application of information theoretic tools to materials problems related to learning from

Kinetic constrained optimization of the golf swing hub path.

Science.gov (United States)

Nesbit, Steven M; McGinnis, Ryan S

2014-12-01

This study details an optimization of the golf swing, where the hand path and club angular trajectories are manipulated. The optimization goal was to maximize club head velocity at impact within the interaction kinetic limitations (force, torque, work, and power) of the golfer as determined through the analysis of a typical swing using a two-dimensional dynamic model. The study was applied to four subjects with diverse swing capabilities and styles. It was determined that it is possible for all subjects to increase their club head velocity at impact within their respective kinetic limitations through combined modifications to their respective hand path and club angular trajectories. The manner of the modifications, the degree of velocity improvement, the amount of kinetic reduction, and the associated kinetic limitation quantities were subject dependent. By artificially minimizing selected kinetic inputs within the optimization algorithm, it was possible to identify swing trajectory characteristics that indicated relative kinetic weaknesses of a subject. Practical implications are offered based upon the findings of the study. Key PointsThe hand path trajectory is an important characteristic of the golf swing and greatly affects club head velocity and golfer/club energy transfer.It is possible to increase the energy transfer from the golfer to the club by modifying the hand path and swing trajectories without increasing the kinetic output demands on the golfer.It is possible to identify relative kinetic output strengths and weakness of a golfer through assessment of the hand path and swing trajectories.Increasing any one of the kinetic outputs of the golfer can potentially increase the club head velocity at impact.The hand path trajectory has important influences over the club swing trajectory.

Phenotypic Variability in a Family with Acrodysostosis Type 2 Caused by a Novel PDE4D Mutation Affecting the Serine Target of Protein Kinase-A Phosphorylation

Science.gov (United States)

Hoppmann, Julia; Gesing, Julia; Silve, Caroline; Leroy, Chrystel; Bertsche, Astrid; Hirsch, Franz Wolfgang; Kiess, Wieland; Pfäffle, Roland; Schuster, Volker

2017-01-01

Acrodysostosis is a very rare congenital multisystem condition characterized by skeletal dysplasia with severe brachydactyly, midfacial hypoplasia, and short stature, varying degrees of intellectual disability, and possible resistance to multiple G protein-coupled receptor signalling hormones. Two distinct subtypes are differentiated: acrodysostosis type 1 resulting from defects in protein kinase type 1-α regulatory subunit and acrodysostosis type 2 caused by mutations in phosphodiesterase 4D (PDE4D). Most cases are sporadic. We report on a rare multigenerational familial case of acrodysostosis type 2 due to a novel autosomal dominantly inherited PDE4D mutation. A 3.5-year-old boy presented with short stature, midfacial hypoplasia, severe brachydactyly, developmental delay, and behavioural problems. Laboratory investigations revealed mild thyrotropin resistance. His mother shared some characteristic features, such as midfacial hypoplasia and severe brachydactyly, but did not show short stature, intellectual disability or hormonal resistance. Genetic analysis identified the identical, novel heterozygous missense mutation of the PDE4D gene c.569C>T (p.Ser190Phe) in both patients. This case illustrates the significant phenotypic variability of acrodysostosis even within one family with identical mutations. Hence, a specific clinical diagnosis of acrodysostosis remains challenging because of great interindividual variability and a substantial overlap of the two subtypes as well as with other related Gsα-cAMP-signalling-linked disorders. PMID:28515031

Production Optimization for Two-Phase Flow in an Oil Reservoir

DEFF Research Database (Denmark)

Völcker, Carsten; Jørgensen, John Bagterp; Thomsen, Per Grove

2012-01-01

framework to increase the production and economic value of an oil reservoir. Wether the objective is to maximize recovery or some financial measure like Net Present Value, the increased production is achieved by manipulation of the well rates and bottom-hole pressures of the injection and production wells....... The optimal water injection rates and production well bottom-hole pressures are computed by solution of a large-scale constrained optimal control problem. The objective is to maximize production by manipulating the well rates and bottom hole pressures of injection and production wells. Optimal control...... settings of injection and production wells are computed by solution of a large scale constrained optimal control problem. We describe a gradient based method to compute the optimal control strategy of the water flooding process. An explicit singly diagonally implicit Runge-Kutta (ESDIRK) method...

Canonical Duality Theory for Topology Optimization

OpenAIRE

Gao, David Yang

2016-01-01

This paper presents a canonical duality approach for solving a general topology optimization problem of nonlinear elastic structures. By using finite element method, this most challenging problem can be formulated as a mixed integer nonlinear programming problem (MINLP), i.e. for a given deformation, the first-level optimization is a typical linear constrained 0-1 programming problem, while for a given structure, the second-level optimization is a general nonlinear continuous minimization pro...

Parallels between control PDE's (Partial Differential Equations) and systems of ODE's (Ordinary Differential Equations)

Science.gov (United States)

Hunt, L. R.; Villarreal, Ramiro

1987-01-01

System theorists understand that the same mathematical objects which determine controllability for nonlinear control systems of ordinary differential equations (ODEs) also determine hypoellipticity for linear partial differentail equations (PDEs). Moreover, almost any study of ODE systems begins with linear systems. It is remarkable that Hormander's paper on hypoellipticity of second order linear p.d.e.'s starts with equations due to Kolmogorov, which are shown to be analogous to the linear PDEs. Eigenvalue placement by state feedback for a controllable linear system can be paralleled for a Kolmogorov equation if an appropriate type of feedback is introduced. Results concerning transformations of nonlinear systems to linear systems are similar to results for transforming a linear PDE to a Kolmogorov equation.

Optimal control landscape for the generation of unitary transformations with constrained dynamics

International Nuclear Information System (INIS)

Hsieh, Michael; Wu, Rebing; Rabitz, Herschel; Lidar, Daniel

2010-01-01

The reliable and precise generation of quantum unitary transformations is essential for the realization of a number of fundamental objectives, such as quantum control and quantum information processing. Prior work has explored the optimal control problem of generating such unitary transformations as a surface-optimization problem over the quantum control landscape, defined as a metric for realizing a desired unitary transformation as a function of the control variables. It was found that under the assumption of nondissipative and controllable dynamics, the landscape topology is trap free, which implies that any reasonable optimization heuristic should be able to identify globally optimal solutions. The present work is a control landscape analysis, which incorporates specific constraints in the Hamiltonian that correspond to certain dynamical symmetries in the underlying physical system. It is found that the presence of such symmetries does not destroy the trap-free topology. These findings expand the class of quantum dynamical systems on which control problems are intrinsically amenable to a solution by optimal control.

Source identification in acoustics and structural mechanics using Sierra/SD.

Energy Technology Data Exchange (ETDEWEB)

Walsh, Timothy Francis; Aquino, Wilkins [Duke University Durham, NC; Ross, Michael

2013-03-01

In this report we derive both time and frequency-domain methods for inverse identification of sources in elastodynamics and acoustics. The inverse/design problem is cast in a PDE-constrained optimization framework with efficient computation of gradients using the adjoint method. The implementation of source inversion in Sierra/SD is described, and results from both time and frequency domain source inversion are compared to actual experimental data for a weapon store used in captive carry on a military aircraft. The inverse methodology is advantageous in that it provides a method for creating ground based acoustic and vibration tests that can reduce the actual number of flight tests, and thus, saving costs and time for the program.

Muscle MRS detects elevated PDE/ATP ratios prior to fatty infiltration in Becker muscular dystrophy.

Science.gov (United States)

Wokke, B H; Hooijmans, M T; van den Bergen, J C; Webb, A G; Verschuuren, J J; Kan, H E

2014-11-01

Becker muscular dystrophy (BMD) is characterized by progressive muscle weakness. Muscles show structural changes (fatty infiltration, fibrosis) and metabolic changes, both of which can be assessed using MRI and MRS. It is unknown at what stage of the disease process metabolic changes arise and how this might vary for different metabolites. In this study we assessed metabolic changes in skeletal muscles of Becker patients, both with and without fatty infiltration, quantified via Dixon MRI and (31) P MRS. MRI and (31) P MRS scans were obtained from 25 Becker patients and 14 healthy controls using a 7 T MR scanner. Five lower-leg muscles were individually assessed for fat and muscle metabolite levels. In the peroneus, soleus and anterior tibialis muscles with non-increased fat levels, PDE/ATP ratios were higher (P < 0.02) compared with controls, whereas in all muscles with increased fat levels PDE/ATP ratios were higher compared with healthy controls (P ≤ 0.05). The Pi /ATP ratio in the peroneus muscles was higher in muscles with increased fat fractions (P = 0.005), and the PCr/ATP ratio was lower in the anterior tibialis muscles with increased fat fractions (P = 0.005). There were no other significant changes in metabolites, but an increase in tissue pH was found in all muscles of the total group of BMD patients in comparison with healthy controls (P < 0.05). These findings suggest that (31) P MRS can be used to detect early changes in individual muscles of BMD patients, which are present before the onset of fatty infiltration. Copyright © 2014 John Wiley & Sons, Ltd.

Discovery of Selective Phosphodiesterase 1 Inhibitors with Memory Enhancing Properties.

Science.gov (United States)

Dyck, Brian; Branstetter, Bryan; Gharbaoui, Tawfik; Hudson, Andrew R; Breitenbucher, J Guy; Gomez, Laurent; Botrous, Iriny; Marrone, Tami; Barido, Richard; Allerston, Charles K; Cedervall, E Peder; Xu, Rui; Sridhar, Vandana; Barker, Ryan; Aertgeerts, Kathleen; Schmelzer, Kara; Neul, David; Lee, Dong; Massari, Mark Eben; Andersen, Carsten B; Sebring, Kristen; Zhou, Xianbo; Petroski, Robert; Limberis, James; Augustin, Martin; Chun, Lawrence E; Edwards, Thomas E; Peters, Marco; Tabatabaei, Ali

2017-04-27

A series of potent thienotriazolopyrimidinone-based PDE1 inhibitors was discovered. X-ray crystal structures of example compounds from this series in complex with the catalytic domain of PDE1B and PDE10A were determined, allowing optimization of PDE1B potency and PDE selectivity. Reduction of hERG affinity led to greater than a 3000-fold selectivity for PDE1B over hERG. 6-(4-Methoxybenzyl)-9-((tetrahydro-2H-pyran-4-yl)methyl)-8,9,10,11-tetrahydropyrido[4',3':4,5]thieno[3,2-e][1,2,4]triazolo[1,5-c]pyrimidin-5(6H)-one was identified as an orally bioavailable and brain penetrating PDE1B enzyme inhibitor with potent memory-enhancing effects in a rat model of object recognition memory.

Construction of an optimal background profile for the Kuramoto–Sivashinsky equation using semidefinite programming

International Nuclear Information System (INIS)

Fantuzzi, G.; Wynn, A.

2015-01-01

A method to construct systematically an optimal background profile for the Kuramoto–Sivashinsky equation is developed by formulating the classical problem as an optimisation problem. In particular, we show that the infinite-dimensional problem can be rewritten as a finite-dimensional convex semidefinite problem, which is solved to construct a background profile and to obtain an upper bound on the energy of the solution ‖u‖ that applies to the infinite-dimensional PDE. The results are compared to existing analytical results, and support the fact that limsup t→∞ ‖u‖≤O(L 3/2 ) is the optimal estimate achievable with the background profile method and a quadratic Lyapunov function. - Highlights: • Optimal background profiles are constructed for the Kuramoto–Sivashinsky equation. • Analytical L 2 bounds for the solution are found using convex optimisation. • The optimal background profile is a double shock profile. • Results attest that L 1.5 scaling is optimal within the classic Lyapunov argument. • We improve the proportionality constant of the scaling law for the attracting set

Effect of PDE5 inhibition on the modulation of sympathetic α-adrenergic vasoconstriction in contracting skeletal muscle of young and older recreationally active humans

DEFF Research Database (Denmark)

Nyberg, Michael Permin; Piil, Peter Bergmann; Egelund, Jon

2015-01-01

Aging is associated with an altered regulation of blood flow to contracting skeletal muscle; however, the precise mechanisms remain unclear. We recently demonstrated that inhibition of cGMP-binding phosphodiesterase 5 (PDE5) increased blood flow to contracting skeletal muscle of older but not you...

GA based CNC turning center exploitation process parameters optimization

Directory of Open Access Journals (Sweden)

Z. Car

2009-01-01

Full Text Available This paper presents machining parameters (turning process optimization based on the use of artificial intelligence. To obtain greater efficiency and productivity of the machine tool, optimal cutting parameters have to be obtained. In order to find optimal cutting parameters, the genetic algorithm (GA has been used as an optimal solution finder. Optimization has to yield minimum machining time and minimum production cost, while considering technological and material constrains.

Multiple utility constrained multi-objective programs using Bayesian theory

Science.gov (United States)

Abbasian, Pooneh; Mahdavi-Amiri, Nezam; Fazlollahtabar, Hamed

2018-03-01

A utility function is an important tool for representing a DM's preference. We adjoin utility functions to multi-objective optimization problems. In current studies, usually one utility function is used for each objective function. Situations may arise for a goal to have multiple utility functions. Here, we consider a constrained multi-objective problem with each objective having multiple utility functions. We induce the probability of the utilities for each objective function using Bayesian theory. Illustrative examples considering dependence and independence of variables are worked through to demonstrate the usefulness of the proposed model.

Chance-constrained programming approach to natural-gas curtailment decisions

Energy Technology Data Exchange (ETDEWEB)

Guldmann, J M

1981-10-01

This paper presents a modeling methodology for the determination of optimal-curtailment decisions by a gas-distribution utility during a chronic gas-shortage situation. Based on the end-use priority approach, a linear-programming model is formulated, that reallocates the available gas supply among the utility's customers while minimizing fuel switching, unemployment, and utility operating costs. This model is then transformed into a chance-constrained program in order to account for the weather-related variability of the gas requirements. The methodology is applied to the East Ohio Gas Company. 16 references, 2 figures, 3 tables.

Particle Swarm Optimization

Science.gov (United States)

Venter, Gerhard; Sobieszczanski-Sobieski Jaroslaw

2002-01-01

The purpose of this paper is to show how the search algorithm known as particle swarm optimization performs. Here, particle swarm optimization is applied to structural design problems, but the method has a much wider range of possible applications. The paper's new contributions are improvements to the particle swarm optimization algorithm and conclusions and recommendations as to the utility of the algorithm, Results of numerical experiments for both continuous and discrete applications are presented in the paper. The results indicate that the particle swarm optimization algorithm does locate the constrained minimum design in continuous applications with very good precision, albeit at a much higher computational cost than that of a typical gradient based optimizer. However, the true potential of particle swarm optimization is primarily in applications with discrete and/or discontinuous functions and variables. Additionally, particle swarm optimization has the potential of efficient computation with very large numbers of concurrently operating processors.

Optimal Design of Gravity Pipeline Systems Using Genetic Algorithm and Mathematical Optimization

Directory of Open Access Journals (Sweden)

maryam rohani

2015-03-01

Full Text Available In recent years, the optimal design of pipeline systems has become increasingly important in the water industry. In this study, the two methods of genetic algorithm and mathematical optimization were employed for the optimal design of pipeline systems with the objective of avoiding the water hammer effect caused by valve closure. The problem of optimal design of a pipeline system is a constrained one which should be converted to an unconstrained optimization problem using an external penalty function approach in the mathematical programming method. The quality of the optimal solution greatly depends on the value of the penalty factor that is calculated by the iterative method during the optimization procedure such that the computational effort is simultaneously minimized. The results obtained were used to compare the GA and mathematical optimization methods employed to determine their efficiency and capabilities for the problem under consideration. It was found that the mathematical optimization method exhibited a slightly better performance compared to the GA method.

Development of two fluorine-18 labeled PET radioligands targeting PDE10A and in vivo PET evaluation in nonhuman primates.

Science.gov (United States)

Stepanov, Vladimir; Takano, Akihiro; Nakao, Ryuji; Amini, Nahid; Miura, Shotaro; Hasui, Tomoaki; Kimura, Haruhide; Taniguchi, Takahiko; Halldin, Christer

2018-02-01

Phosphodiesterase 10A (PDE10A) is a member of the PDE enzyme family that degrades cyclic adenosine and guanosine monophosphates (cAMP and cGMP). Based on the successful development of [ 11 C]T-773 as PDE10A positron emission tomography (PET) radioligand, in this study our aim was to develop and evaluate fluorine-18 analogs of [ 11 C]T-773. [ 18 F]FM-T-773-d 2 and [ 18 F]FE-T-773-d 4 were synthesized from the same precursor used for 11 C-labeling of T-773 in a two-step approach via 18 F-fluoromethylation and 18 F-fluoroethylation, respectively, using corresponding deuterated synthons. A total of 12 PET measurements were performed in seven non-human primates. First, baseline PET measurements were performed using High Resolution Research Tomograph system with both [ 18 F]FM-T-773-d 2 and [ 18 F]FE-T-773-d 4 ; the uptake in whole brain and separate brain regions, as well as the specific binding and tissue ratio between putamen and cerebellum, was examined. Second, baseline and pretreatment PET measurements using MP-10 as the blocker were performed for [ 18 F]FM-T-773-d 2 including arterial blood sampling with radiometabolite analysis in four NHPs. Both [ 18 F]FM-T-773-d 2 and [ 18 F]FE-T-773-d 4 were successfully radiolabeled with an average molar activity of 293 ± 114 GBq/μmol (n=8) for [ 18 F]FM-T-773-d 2 and 209 ± 26 GBq/μmol (n=4) for [ 18 F]FE-T-773-d 4 , and a radiochemical yield of 10% (EOB, n=12, range 3%-16%). Both radioligands displayed high brain uptake (~5.5% of injected radioactivity for [ 18 F]FM-T-773-d 2 and ~3.5% for [ 18 F]FE-T-773-d 4 at the peak) and a fast washout. Specific binding reached maximum within 30 min for [ 18 F]FM-T-773-d 2 and after approximately 45 min for [ 18 F]FE-T-773-d 4 . [ 18 F]FM-T-773-d 2 data fitted well with kinetic compartment models. BP ND values obtained indirectly through compartment models were correlated well with those obtained by SRTM. BP ND calculated with SRTM was 1.0-1.7 in the putamen. The occupancy with 1

Optimal Control of Evolution Mixed Variational Inclusions

Energy Technology Data Exchange (ETDEWEB)

Alduncin, Gonzalo, E-mail: alduncin@geofisica.unam.mx [Universidad Nacional Autónoma de México, Departamento de Recursos Naturales, Instituto de Geofísica (Mexico)

2013-12-15

Optimal control problems of primal and dual evolution mixed variational inclusions, in reflexive Banach spaces, are studied. The solvability analysis of the mixed state systems is established via duality principles. The optimality analysis is performed in terms of perturbation conjugate duality methods, and proximation penalty-duality algorithms to mixed optimality conditions are further presented. Applications to nonlinear diffusion constrained problems as well as quasistatic elastoviscoplastic bilateral contact problems exemplify the theory.

Optimal Control of Evolution Mixed Variational Inclusions

International Nuclear Information System (INIS)

Alduncin, Gonzalo

2013-01-01

Optimal control problems of primal and dual evolution mixed variational inclusions, in reflexive Banach spaces, are studied. The solvability analysis of the mixed state systems is established via duality principles. The optimality analysis is performed in terms of perturbation conjugate duality methods, and proximation penalty-duality algorithms to mixed optimality conditions are further presented. Applications to nonlinear diffusion constrained problems as well as quasistatic elastoviscoplastic bilateral contact problems exemplify the theory

Preconditioners for state-constrained optimal control problems with Moreau-Yosida penalty function

KAUST Repository

Pearson, John W.; Stoll, Martin; Wathen, Andrew J.

2012-01-01

Optimal control problems with partial differential equations as constraints play an important role in many applications. The inclusion of bound constraints for the state variable poses a significant challenge for optimization methods. Our focus here

Optimization of the box-girder of overhead crane with constrained ...

African Journals Online (AJOL)

haroun

Keywords: Overhead crane - Box-girder - New bat algorithm - level of ... much more efficiency and robustness compared to the genetic algorithm (GA) and PSO ...... optimization: developments, applications and resources," in Evolutionary.

Constrained non-linear optimization in 3D reflexion tomography; Problemes d'optimisation non-lineaire avec contraintes en tomographie de reflexion 3D

Energy Technology Data Exchange (ETDEWEB)

Delbos, F.

2004-11-01

Reflexion tomography allows the determination of a subsurface velocity model from the travel times of seismic waves. The introduction of a priori information in this inverse problem can lead to the resolution of a constrained non-linear least-squares problem. The goal of the thesis is to improve the resolution techniques of this optimization problem, whose main difficulties are its ill-conditioning, its large scale and an expensive cost function in terms of CPU time. Thanks to a detailed study of the problem and to numerous numerical experiments, we justify the use of a sequential quadratic programming method, in which the tangential quadratic programs are solved by an original augmented Lagrangian method. We show the global linear convergence of the latter. The efficiency and robustness of the approach are demonstrated on several synthetic examples and on two real data cases. (author)

Production Optimization of Oil Reservoirs

DEFF Research Database (Denmark)

Völcker, Carsten

with emphasis on optimal control of water ooding with the use of smartwell technology. We have implemented immiscible ow of water and oil in isothermal reservoirs with isotropic heterogenous permeability elds. We use the method of lines for solution of the partial differential equation (PDE) system that governs...... the uid ow. We discretize the the two-phase ow model spatially using the nite volume method (FVM), and we use the two point ux approximation (TPFA) and the single-point upstream (SPU) scheme for computing the uxes. We propose a new formulation of the differential equation system that arise...... as a consequence of the spatial discretization of the two-phase ow model. Upon discretization in time, the proposed equation system ensures the mass conserving property of the two-phase ow model. For the solution of the spatially discretized two-phase ow model, we develop mass conserving explicit singly diagonally...

Constrained evolution in numerical relativity

Science.gov (United States)

Anderson, Matthew William

The strongest potential source of gravitational radiation for current and future detectors is the merger of binary black holes. Full numerical simulation of such mergers can provide realistic signal predictions and enhance the probability of detection. Numerical simulation of the Einstein equations, however, is fraught with difficulty. Stability even in static test cases of single black holes has proven elusive. Common to unstable simulations is the growth of constraint violations. This work examines the effect of controlling the growth of constraint violations by solving the constraints periodically during a simulation, an approach called constrained evolution. The effects of constrained evolution are contrasted with the results of unconstrained evolution, evolution where the constraints are not solved during the course of a simulation. Two different formulations of the Einstein equations are examined: the standard ADM formulation and the generalized Frittelli-Reula formulation. In most cases constrained evolution vastly improves the stability of a simulation at minimal computational cost when compared with unconstrained evolution. However, in the more demanding test cases examined, constrained evolution fails to produce simulations with long-term stability in spite of producing improvements in simulation lifetime when compared with unconstrained evolution. Constrained evolution is also examined in conjunction with a wide variety of promising numerical techniques, including mesh refinement and overlapping Cartesian and spherical computational grids. Constrained evolution in boosted black hole spacetimes is investigated using overlapping grids. Constrained evolution proves to be central to the host of innovations required in carrying out such intensive simulations.

Application of Heuristic and Metaheuristic Algorithms in Solving Constrained Weber Problem with Feasible Region Bounded by Arcs

Directory of Open Access Journals (Sweden)

Igor Stojanović

2017-01-01

Full Text Available The continuous planar facility location problem with the connected region of feasible solutions bounded by arcs is a particular case of the constrained Weber problem. This problem is a continuous optimization problem which has a nonconvex feasible set of constraints. This paper suggests appropriate modifications of four metaheuristic algorithms which are defined with the aim of solving this type of nonconvex optimization problems. Also, a comparison of these algorithms to each other as well as to the heuristic algorithm is presented. The artificial bee colony algorithm, firefly algorithm, and their recently proposed improved versions for constrained optimization are appropriately modified and applied to the case study. The heuristic algorithm based on modified Weiszfeld procedure is also implemented for the purpose of comparison with the metaheuristic approaches. Obtained numerical results show that metaheuristic algorithms can be successfully applied to solve the instances of this problem of up to 500 constraints. Among these four algorithms, the improved version of artificial bee algorithm is the most efficient with respect to the quality of the solution, robustness, and the computational efficiency.

Model Predictive Control Based on Kalman Filter for Constrained Hammerstein-Wiener Systems

Directory of Open Access Journals (Sweden)

Man Hong

2013-01-01

Full Text Available To precisely track the reactor temperature in the entire working condition, the constrained Hammerstein-Wiener model describing nonlinear chemical processes such as in the continuous stirred tank reactor (CSTR is proposed. A predictive control algorithm based on the Kalman filter for constrained Hammerstein-Wiener systems is designed. An output feedback control law regarding the linear subsystem is derived by state observation. The size of reaction heat produced and its influence on the output are evaluated by the Kalman filter. The observation and evaluation results are calculated by the multistep predictive approach. Actual control variables are computed while considering the constraints of the optimal control problem in a finite horizon through the receding horizon. The simulation example of the CSTR tester shows the effectiveness and feasibility of the proposed algorithm.

Constrained Optimization via Stochastic approximation with a simultaneous perturbation gradient approximation

DEFF Research Database (Denmark)

Sadegh, Payman

1997-01-01

This paper deals with a projection algorithm for stochastic approximation using simultaneous perturbation gradient approximation for optimization under inequality constraints where no direct gradient of the loss function is available and the inequality constraints are given as explicit functions...... of the optimization parameters. It is shown that, under application of the projection algorithm, the parameter iterate converges almost surely to a Kuhn-Tucker point, The procedure is illustrated by a numerical example, (C) 1997 Elsevier Science Ltd....

Optimal Route Searching with Multiple Dynamical Constraints—A Geometric Algebra Approach

Directory of Open Access Journals (Sweden)

Dongshuang Li

2018-05-01

Full Text Available The process of searching for a dynamic constrained optimal path has received increasing attention in traffic planning, evacuation, and personalized or collaborative traffic service. As most existing multiple constrained optimal path (MCOP methods cannot search for a path given various types of constraints that dynamically change during the search, few approaches for dynamic multiple constrained optimal path (DMCOP with type II dynamics are available for practical use. In this study, we develop a method to solve the DMCOP problem with type II dynamics based on the unification of various types of constraints under a geometric algebra (GA framework. In our method, the network topology and three different types of constraints are represented by using algebraic base coding. With a parameterized optimization of the MCOP algorithm based on a greedy search strategy under the generation-refinement paradigm, this algorithm is found to accurately support the discovery of optimal paths as the constraints of numerical values, nodes, and route structure types are dynamically added to the network. The algorithm was tested with simulated cases of optimal tourism route searches in China’s road networks with various combinations of constraints. The case study indicates that our algorithm can not only solve the DMCOP with different types of constraints but also use constraints to speed up the route filtering.

Extended Information Ratio for Portfolio Optimization Using Simulated Annealing with Constrained Neighborhood

Science.gov (United States)

Orito, Yukiko; Yamamoto, Hisashi; Tsujimura, Yasuhiro; Kambayashi, Yasushi

The portfolio optimizations are to determine the proportion-weighted combination in the portfolio in order to achieve investment targets. This optimization is one of the multi-dimensional combinatorial optimizations and it is difficult for the portfolio constructed in the past period to keep its performance in the future period. In order to keep the good performances of portfolios, we propose the extended information ratio as an objective function, using the information ratio, beta, prime beta, or correlation coefficient in this paper. We apply the simulated annealing (SA) to optimize the portfolio employing the proposed ratio. For the SA, we make the neighbor by the operation that changes the structure of the weights in the portfolio. In the numerical experiments, we show that our portfolios keep the good performances when the market trend of the future period becomes different from that of the past period.

PDK1/Akt/PDE4D axis identified as a target for asthma remedy synergistic with β2 AR agonists by a natural agent arctigenin.

Science.gov (United States)

Fang, R; Cui, Q; Sun, J; Duan, X; Ma, X; Wang, W; Cheng, B; Liu, Y; Hou, Y; Bai, G

2015-12-01

Asthma is a heterogenetic disorder characterized by chronic inflammation with variable airflow obstruction and airway hyper-responsiveness. As the most potent and popular bronchodilators, β2 adrenergic receptor (β2 AR) agonists bind to the β2 ARs that are coupled via a stimulatory G protein to adenylyl cyclase, thereby improving cAMP accumulation and resulting in airway smooth muscle relaxation. We previously demonstrated arctigenin had a synergistic function with the β2 AR agonist, but the target for this remained elusive. Chemical proteomics capturing was used to enrich and uncover the target of arctigenin in human bronchial smooth muscle cells, and reverse docking and molecular dynamic stimulation were performed to evaluate the binding of arctigenin and its target. In vitro enzyme activities and protein levels were demonstrated with special kits and Western blotting. Finally, guinea pig tracheal muscle segregation and ex vivo function were analysed. Arctigenin bound to PDK1 with an ideal binding free energy -25.45 kcal/mol and inhibited PDK1 kinase activity without changing its protein level. Additionally, arctigenin reduced PKB/Akt-induced phosphorylation of PDE4D, which was first identified in this study. Attenuation of PDE4D resulted in cAMP accumulation in human bronchial smooth muscle. The inhibition of PDK1 showed a synergistic function with β2 AR agonists and relaxed the constriction of segregated guinea pig tracheal muscle. The PDK1/Akt/PDE4D axis serves as a novel asthma target, which may benefit airflow obstruction. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Firefly Algorithm for Cardinality Constrained Mean-Variance Portfolio Optimization Problem with Entropy Diversity Constraint

Directory of Open Access Journals (Sweden)

Nebojsa Bacanin

2014-01-01

portfolio model with entropy constraint. Firefly algorithm is one of the latest, very successful swarm intelligence algorithm; however, it exhibits some deficiencies when applied to constrained problems. To overcome lack of exploration power during early iterations, we modified the algorithm and tested it on standard portfolio benchmark data sets used in the literature. Our proposed modified firefly algorithm proved to be better than other state-of-the-art algorithms, while introduction of entropy diversity constraint further improved results.

Inexact nonlinear improved fuzzy chance-constrained programming model for irrigation water management under uncertainty

Science.gov (United States)

Zhang, Chenglong; Zhang, Fan; Guo, Shanshan; Liu, Xiao; Guo, Ping

2018-01-01

An inexact nonlinear mλ-measure fuzzy chance-constrained programming (INMFCCP) model is developed for irrigation water allocation under uncertainty. Techniques of inexact quadratic programming (IQP), mλ-measure, and fuzzy chance-constrained programming (FCCP) are integrated into a general optimization framework. The INMFCCP model can deal with not only nonlinearities in the objective function, but also uncertainties presented as discrete intervals in the objective function, variables and left-hand side constraints and fuzziness in the right-hand side constraints. Moreover, this model improves upon the conventional fuzzy chance-constrained programming by introducing a linear combination of possibility measure and necessity measure with varying preference parameters. To demonstrate its applicability, the model is then applied to a case study in the middle reaches of Heihe River Basin, northwest China. An interval regression analysis method is used to obtain interval crop water production functions in the whole growth period under uncertainty. Therefore, more flexible solutions can be generated for optimal irrigation water allocation. The variation of results can be examined by giving different confidence levels and preference parameters. Besides, it can reflect interrelationships among system benefits, preference parameters, confidence levels and the corresponding risk levels. Comparison between interval crop water production functions and deterministic ones based on the developed INMFCCP model indicates that the former is capable of reflecting more complexities and uncertainties in practical application. These results can provide more reliable scientific basis for supporting irrigation water management in arid areas.

Optimization of radiotherapy to target volumes with concave outlines: target-dose homogenization and selective sparing of critical structures by constrained matrix inversion

Energy Technology Data Exchange (ETDEWEB)

Colle, C; Van den Berge, D; De Wagter, C; Fortan, L; Van Duyse, B; De Neve, W

1995-12-01

The design of 3D-conformal dose distributions for targets with concave outlines is a technical challenge in conformal radiotherapy. For these targets, it is impossible to find beam incidences for which the target volume can be isolated from the tissues at risk. Commonly occurring examples are most thyroid cancers and the targets located at the lower neck and upper mediastinal levels related to some head and neck. A solution to this problem was developed, using beam intensity modulation executed with a multileaf collimator by applying a static beam-segmentation technique. The method includes the definition of beam incidences and beam segments of specific shape as well as the calculation of segment weights. Tests on Sherouse`s GRATISTM planning system allowed to escalate the dose to these targets to 65-70 Gy without exceeding spinal cord tolerance. Further optimization by constrained matrix inversion was investigated to explore the possibility of further dose escalation.

Optimizations of Unstructured Aerodynamics Computations for Many-core Architectures

KAUST Repository

Al Farhan, Mohammed Ahmed

2018-04-13

We investigate several state-of-the-practice shared-memory optimization techniques applied to key routines of an unstructured computational aerodynamics application with irregular memory accesses. We illustrate for the Intel KNL processor, as a representative of the processors in contemporary leading supercomputers, identifying and addressing performance challenges without compromising the floating point numerics of the original code. We employ low and high-level architecture-specific code optimizations involving thread and data-level parallelism. Our approach is based upon a multi-level hierarchical distribution of work and data across both the threads and the SIMD units within every hardware core. On a 64-core KNL chip, we achieve nearly 2.9x speedup of the dominant routines relative to the baseline. These exhibit almost linear strong scalability up to 64 threads, and thereafter some improvement with hyperthreading. At substantially fewer Watts, we achieve up to 1.7x speedup relative to the performance of 72 threads of a 36-core Haswell CPU and roughly equivalent performance to 112 threads of a 56-core Skylake scalable processor. These optimizations are expected to be of value for many other unstructured mesh PDE-based scientific applications as multi and many-core architecture evolves.

Modeling and Simulation of High Dimensional Stochastic Multiscale PDE Systems at the Exascale

Energy Technology Data Exchange (ETDEWEB)

Kevrekidis, Ioannis [Princeton Univ., NJ (United States)

2017-03-22

The thrust of the proposal was to exploit modern data-mining tools in a way that will create a systematic, computer-assisted approach to the representation of random media -- and also to the representation of the solutions of an array of important physicochemical processes that take place in/on such media. A parsimonious representation/parametrization of the random media links directly (via uncertainty quantification tools) to good sampling of the distribution of random media realizations. It also links directly to modern multiscale computational algorithms (like the equation-free approach that has been developed in our group) and plays a crucial role in accelerating the scientific computation of solutions of nonlinear PDE models (deterministic or stochastic) in such media – both solutions in particular realizations of the random media, and estimation of the statistics of the solutions over multiple realizations (e.g. expectations).

Design Optimization Toolkit: Users' Manual

Energy Technology Data Exchange (ETDEWEB)

Aguilo Valentin, Miguel Alejandro [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Computational Solid Mechanics and Structural Dynamics

2014-07-01

The Design Optimization Toolkit (DOTk) is a stand-alone C++ software package intended to solve complex design optimization problems. DOTk software package provides a range of solution methods that are suited for gradient/nongradient-based optimization, large scale constrained optimization, and topology optimization. DOTk was design to have a flexible user interface to allow easy access to DOTk solution methods from external engineering software packages. This inherent flexibility makes DOTk barely intrusive to other engineering software packages. As part of this inherent flexibility, DOTk software package provides an easy-to-use MATLAB interface that enables users to call DOTk solution methods directly from the MATLAB command window.

Optimal Water-Power Flow Problem: Formulation and Distributed Optimal Solution

Energy Technology Data Exchange (ETDEWEB)

Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhao, Changhong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zamzam, Admed S. [University of Minnesota; Sidiropoulos, Nicholas D. [University of Minnesota; Taylor, Josh A. [University of Toronto

2018-01-12

This paper formalizes an optimal water-power flow (OWPF) problem to optimize the use of controllable assets across power and water systems while accounting for the couplings between the two infrastructures. Tanks and pumps are optimally managed to satisfy water demand while improving power grid operations; {for the power network, an AC optimal power flow formulation is augmented to accommodate the controllability of water pumps.} Unfortunately, the physics governing the operation of the two infrastructures and coupling constraints lead to a nonconvex (and, in fact, NP-hard) problem; however, after reformulating OWPF as a nonconvex, quadratically-constrained quadratic problem, a feasible point pursuit-successive convex approximation approach is used to identify feasible and optimal solutions. In addition, a distributed solver based on the alternating direction method of multipliers enables water and power operators to pursue individual objectives while respecting the couplings between the two networks. The merits of the proposed approach are demonstrated for the case of a distribution feeder coupled with a municipal water distribution network.

Optimal control of coupled parabolic-hyperbolic non-autonomous PDEs: infinite-dimensional state-space approach

Science.gov (United States)

Aksikas, I.; Moghadam, A. Alizadeh; Forbes, J. F.

2018-04-01

This paper deals with the design of an optimal state-feedback linear-quadratic (LQ) controller for a system of coupled parabolic-hypebolic non-autonomous partial differential equations (PDEs). The infinite-dimensional state space representation and the corresponding operator Riccati differential equation are used to solve the control problem. Dynamical properties of the coupled system of interest are analysed to guarantee the existence and uniqueness of the solution of the LQ-optimal control problem and also to guarantee the exponential stability of the closed-loop system. Thanks to the eigenvalues and eigenfunctions of the parabolic operator and also the fact that the hyperbolic-associated operator Riccati differential equation can be converted to a scalar Riccati PDE, an algorithm to solve the LQ control problem has been presented. The results are applied to a non-isothermal packed-bed catalytic reactor. The LQ optimal controller designed in the early portion of the paper is implemented for the original non-linear model. Numerical simulations are performed to show the controller performances.

Partial regularity of weak solutions to a PDE system with cubic nonlinearity

Science.gov (United States)

Liu, Jian-Guo; Xu, Xiangsheng

2018-04-01

In this paper we investigate regularity properties of weak solutions to a PDE system that arises in the study of biological transport networks. The system consists of a possibly singular elliptic equation for the scalar pressure of the underlying biological network coupled to a diffusion equation for the conductance vector of the network. There are several different types of nonlinearities in the system. Of particular mathematical interest is a term that is a polynomial function of solutions and their partial derivatives and this polynomial function has degree three. That is, the system contains a cubic nonlinearity. Only weak solutions to the system have been shown to exist. The regularity theory for the system remains fundamentally incomplete. In particular, it is not known whether or not weak solutions develop singularities. In this paper we obtain a partial regularity theorem, which gives an estimate for the parabolic Hausdorff dimension of the set of possible singular points.

Restoration of vision in the pde6β-deficient dog, a large animal model of rod-cone dystrophy.

Science.gov (United States)

Petit, Lolita; Lhériteau, Elsa; Weber, Michel; Le Meur, Guylène; Deschamps, Jack-Yves; Provost, Nathalie; Mendes-Madeira, Alexandra; Libeau, Lyse; Guihal, Caroline; Colle, Marie-Anne; Moullier, Philippe; Rolling, Fabienne

2012-11-01

Defects in the β subunit of rod cGMP phosphodiesterase 6 (PDE6β) are associated with autosomal recessive retinitis pigmentosa (RP), a childhood blinding disease with early retinal degeneration and vision loss. To date, there is no treatment for this pathology. The aim of this preclinical study was to test recombinant adeno-associated virus (AAV)-mediated gene addition therapy in the rod-cone dysplasia type 1 (rcd1) dog, a large animal model of naturally occurring PDE6β deficiency that strongly resembles the human pathology. A total of eight rcd1 dogs were injected subretinally with AAV2/5RK.cpde6β (n = 4) or AAV2/8RK.cpde6β (n = 4). In vivo and post-mortem morphological analysis showed a significant preservation of the retinal structure in transduced areas of both AAV2/5RK.cpde6β- and AAV2/8RK.cpde6β-treated retinas. Moreover, substantial rod-derived electroretinography (ERG) signals were recorded as soon as 1 month postinjection (35% of normal eyes) and remained stable for at least 18 months (the duration of the study) in treated eyes. Rod-responses were undetectable in untreated contralateral eyes. Most importantly, dim-light vision was restored in all treated rcd1 dogs. These results demonstrate for the first time that gene therapy effectively restores long-term retinal function and vision in a large animal model of autosomal recessive rod-cone dystrophy, and provide great promise for human treatment.

Optimization of temporal networks under uncertainty

CERN Document Server

Wiesemann, Wolfram

2012-01-01

Many decision problems in Operations Research are defined on temporal networks, that is, workflows of time-consuming tasks whose processing order is constrained by precedence relations. For example, temporal networks are used to model projects, computer applications, digital circuits and production processes. Optimization problems arise in temporal networks when a decision maker wishes to determine a temporal arrangement of the tasks and/or a resource assignment that optimizes some network characteristic (e.g. the time required to complete all tasks). The parameters of these optimization probl

A numerical investigation into the ability of the Poisson PDE to extract the mass-density from land-based gravity data: A case study of salt diapirs in the north coast of the Persian Gulf

Science.gov (United States)

AllahTavakoli, Yahya; Safari, Abdolreza

2017-08-01

This paper is counted as a numerical investigation into the capability of Poisson's Partial Differential Equation (PDE) at Earth's surface to extract the near-surface mass-density from land-based gravity data. For this purpose, first it focuses on approximating the gradient tensor of Earth's gravitational potential by means of land-based gravity data. Then, based on the concepts of both the gradient tensor and Poisson's PDE at the Earth's surface, certain formulae are proposed for the mass-density determination. Furthermore, this paper shows how the generalized Tikhonov regularization strategy can be used for enhancing the efficiency of the proposed approach. Finally, in a real case study, the formulae are applied to 6350 gravity stations located within a part of the north coast of the Persian Gulf. The case study numerically indicates that the proposed formulae, provided by Poisson's PDE, has the ability to convert land-based gravity data into the terrain mass-density which has been used for depicting areas of salt diapirs in the region of the case study.

A New Hybrid Whale Optimizer Algorithm with Mean Strategy of Grey Wolf Optimizer for Global Optimization

Directory of Open Access Journals (Sweden)

Narinder Singh

2018-03-01

Full Text Available The quest for an efficient nature-inspired optimization technique has continued over the last few decades. In this paper, a hybrid nature-inspired optimization technique has been proposed. The hybrid algorithm has been constructed using Mean Grey Wolf Optimizer (MGWO and Whale Optimizer Algorithm (WOA. We have utilized the spiral equation of Whale Optimizer Algorithm for two procedures in the Hybrid Approach GWO (HAGWO algorithm: (i firstly, we used the spiral equation in Grey Wolf Optimizer algorithm for balance between the exploitation and the exploration process in the new hybrid approach; and (ii secondly, we also applied this equation in the whole population in order to refrain from the premature convergence and trapping in local minima. The feasibility and effectiveness of the hybrid algorithm have been tested by solving some standard benchmarks, XOR, Baloon, Iris, Breast Cancer, Welded Beam Design, Pressure Vessel Design problems and comparing the results with those obtained through other metaheuristics. The solutions prove that the newly existing hybrid variant has higher stronger stability, faster convergence rate and computational accuracy than other nature-inspired metaheuristics on the maximum number of problems and can successfully resolve the function of constrained nonlinear optimization in reality.

An analytical method for optimal design of MR valve structures

International Nuclear Information System (INIS)

Nguyen, Q H; Choi, S B; Lee, Y S; Han, M S

2009-01-01

This paper proposes an analytical methodology for the optimal design of a magnetorheological (MR) valve structure. The MR valve structure is constrained in a specific volume and the optimization problem identifies geometric dimensions of the valve structure that maximize the yield stress pressure drop of a MR valve or the yield stress damping force of a MR damper. In this paper, the single-coil and two-coil annular MR valve structures are considered. After describing the schematic configuration and operating principle of a typical MR valve and damper, a quasi-static model is derived based on the Bingham model of a MR fluid. The magnetic circuit of the valve and damper is then analyzed by applying Kirchoff's law and the magnetic flux conservation rule. Based on quasi-static modeling and magnetic circuit analysis, the optimization problem of the MR valve and damper is built. In order to reduce the computation load, the optimization problem is simplified and a procedure to obtain the optimal solution of the simplified optimization problem is presented. The optimal solution of the simplified optimization problem of the MR valve structure constrained in a specific volume is then obtained and compared with the solution of the original optimization problem and the optimal solution obtained from the finite element method

Designing equitable antiretroviral allocation strategies in resource-constrained countries.

Directory of Open Access Journals (Sweden)

David P Wilson

2005-02-01

Full Text Available Recently, a global commitment has been made to expand access to antiretrovirals (ARVs in the developing world. However, in many resource-constrained countries the number of individuals infected with HIV in need of treatment will far exceed the supply of ARVs, and only a limited number of health-care facilities (HCFs will be available for ARV distribution. Deciding how to allocate the limited supply of ARVs among HCFs will be extremely difficult. Resource allocation decisions can be made on the basis of many epidemiological, ethical, or preferential treatment priority criteria.Here we use operations research techniques, and we show how to determine the optimal strategy for allocating ARVs among HCFs in order to satisfy the equitable criterion that each individual infected with HIV has an equal chance of receiving ARVs. We present a novel spatial mathematical model that includes heterogeneity in treatment accessibility. We show how to use our theoretical framework, in conjunction with an equity objective function, to determine an optimal equitable allocation strategy (OEAS for ARVs in resource-constrained regions. Our equity objective function enables us to apply the egalitarian principle of equity with respect to access to health care. We use data from the detailed ARV rollout plan designed by the government of South Africa to determine an OEAS for the province of KwaZulu-Natal. We determine the OEAS for KwaZulu-Natal, and we then compare this OEAS with two other ARV allocation strategies: (i allocating ARVs only to Durban (the largest urban city in KwaZulu-Natal province and (ii allocating ARVs equally to all available HCFs. In addition, we compare the OEAS to the current allocation plan of the South African government (which is based upon allocating ARVs to 17 HCFs. We show that our OEAS significantly improves equity in treatment accessibility in comparison with these three ARV allocation strategies. We also quantify how the size of the

Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization(in English

Directory of Open Access Journals (Sweden)

Shi Chen-guang

2014-08-01

Full Text Available A novel optimal power allocation algorithm for radar network systems is proposed for Low Probability of Intercept (LPI technology in modern electronic warfare. The algorithm is based on the LPI optimization. First, the Schleher intercept factor for a radar network is derived, and then the Schleher intercept factor is minimized by optimizing the transmission power allocation among netted radars in the network to guarantee target-tracking performance. Furthermore, the Nonlinear Programming Genetic Algorithm (NPGA is used to solve the resulting nonconvex, nonlinear, and constrained optimization problem. Numerical simulation results show the effectiveness of the proposed algorithm.

Optimization of sources for focusing wave energy in targeted formations

KAUST Repository

Jeong, C; Kallivokas, L F; Huh, C; Lake, L W

2010-01-01

that will maximize the kinetic energy in the target zone, while keeping silent the neighbouring zones. To this end, we cast the problem as an inverse-source problem, and use a partial-differential- equation-constrained optimization approach to arrive at an optimized

Direct Speed Control of PMSM Drive Using SDRE and Convex Constrained Optimization

Czech Academy of Sciences Publication Activity Database

Šmídl, V.; Janouš, Š.; Adam, Lukáš; Peroutka, Z.

2018-01-01

Roč. 65, č. 1 (2018), s. 532-542 ISSN 1932-4529 Grant - others:GA MŠk(CZ) LO1607 Institutional support: RVO:67985556 Keywords : Velocity control * Optimization * Stators * Voltage control * Predictive control * Optimal control * Rotors Subject RIV: BD - Theory of Information Impact factor: 10.710, year: 2016 http://library.utia.cas.cz/separaty/2017/AS/smidl-0481225.pdf

Structure-constrained sparse canonical correlation analysis with an application to microbiome data analysis.

Science.gov (United States)

Chen, Jun; Bushman, Frederic D; Lewis, James D; Wu, Gary D; Li, Hongzhe

2013-04-01

Motivated by studying the association between nutrient intake and human gut microbiome composition, we developed a method for structure-constrained sparse canonical correlation analysis (ssCCA) in a high-dimensional setting. ssCCA takes into account the phylogenetic relationships among bacteria, which provides important prior knowledge on evolutionary relationships among bacterial taxa. Our ssCCA formulation utilizes a phylogenetic structure-constrained penalty function to impose certain smoothness on the linear coefficients according to the phylogenetic relationships among the taxa. An efficient coordinate descent algorithm is developed for optimization. A human gut microbiome data set is used to illustrate this method. Both simulations and real data applications show that ssCCA performs better than the standard sparse CCA in identifying meaningful variables when there are structures in the data.

Loss of ABHD15 Impairs the Anti-lipolytic Action of Insulin by Altering PDE3B Stability and Contributes to Insulin Resistance.

Science.gov (United States)

Xia, Wenmin; Pessentheiner, Ariane R; Hofer, Dina C; Amor, Melina; Schreiber, Renate; Schoiswohl, Gabriele; Eichmann, Thomas O; Walenta, Evelyn; Itariu, Bianca; Prager, Gerhard; Hackl, Hubert; Stulnig, Thomas; Kratky, Dagmar; Rülicke, Thomas; Bogner-Strauss, Juliane G

2018-05-15

Elevated circulating fatty acids (FAs) contribute to obesity-associated metabolic complications, but the mechanisms by which insulin suppresses lipolysis are poorly understood. We show that α/β-hydrolase domain-containing 15 (ABHD15) is required for the anti-lipolytic action of insulin in white adipose tissue (WAT). Neither insulin nor glucose treatments can suppress FA mobilization in global and conditional Abhd15-knockout (KO) mice. Accordingly, insulin signaling is impaired in Abhd15-KO adipocytes, as indicated by reduced AKT phosphorylation, glucose uptake, and de novo lipogenesis. In vitro data reveal that ABHD15 associates with and stabilizes phosphodiesterase 3B (PDE3B). Accordingly, PDE3B expression is decreased in the WAT of Abhd15-KO mice, mechanistically explaining increased protein kinase A (PKA) activity, hormone-sensitive lipase (HSL) phosphorylation, and undiminished FA release upon insulin signaling. Ultimately, Abhd15-KO mice develop insulin resistance. Notably, ABHD15 expression is decreased in humans with obesity and diabetes compared to humans with obesity and normal glucose tolerance, identifying ABHD15 as a potential therapeutic target to mitigate insulin resistance. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Inhibition of PAF-induced expression of CD11b and shedding of L-selectin on human neutrophils and eosinophils by the type IV selective PDE inhibitor, rolipram

NARCIS (Netherlands)

Dijkhuizen, B; deMonchy, JGR; Dubois, AEJ; Gerritsen, J; Kauffman, HF

We quantitatively determined whether the selective phosphodiesterase (PDE) inhibitor, rolipram, inhibits changes in the adhesion molecules CD11b and L-selectin on platelet-activating factor (PAF)-stimulated human neutrophils and eosinophils in vitro. Incubations were performed in human whole blood

Incorporating Charging/Discharging Strategy of Electric Vehicles into Security-Constrained Optimal Power Flow to Support High Renewable Penetration

Directory of Open Access Journals (Sweden)

Kyungsung An

2017-05-01

Full Text Available This research aims to improve the operational efficiency and security of electric power systems at high renewable penetration by exploiting the envisioned controllability or flexibility of electric vehicles (EVs; EVs interact with the grid through grid-to-vehicle (G2V and vehicle-to-grid (V2G services to ensure reliable and cost-effective grid operation. This research provides a computational framework for this decision-making process. Charging and discharging strategies of EV aggregators are incorporated into a security-constrained optimal power flow (SCOPF problem such that overall energy cost is minimized and operation within acceptable reliability criteria is ensured. Particularly, this SCOPF problem has been formulated for Jeju Island in South Korea, in order to lower carbon emissions toward a zero-carbon island by, for example, integrating large-scale renewable energy and EVs. On top of conventional constraints on the generators and line flows, a unique constraint on the system inertia constant, interpreted as the minimum synchronous generation, is considered to ensure grid security at high renewable penetration. The available energy constraint of the participating EV associated with the state-of-charge (SOC of the battery and market price-responsive behavior of the EV aggregators are also explored. Case studies for the Jeju electric power system in 2030 under various operational scenarios demonstrate the effectiveness of the proposed method and improved operational flexibility via controllable EVs.